customer journey analysis google analytics

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[GA4] Mini guides: Explorations

[ga4] explorations: user journeys through your content.

To understand how users engage with your content across platforms and devices, and from event type to event type, implement User-ID to uniquely identify users , and use the path exploration technique to see which paths they take.

A path exploration starts with a screen or an event that represents the first step of the user's journey. You can then see the next top-five screens viewed or events triggered by the user following that initial step. You can also create a backwards path, which shows the steps leading up to a final step. Along the way, you can expand the graph to show what users did in each step.

For example, if you start with a screen, you might see that users viewed a photo of a new product on your app, then tapped to read a description on another screen, and then completed the purchase on your website.

If want to examine the succession of events, you might start with ad_exposure , then see which ad_click events follow that, and which view_item , add_to_cart , and ecommerce_purchase events follow ad_click .

Learn more about the events Analytics collects automatically and which ones are recommended for different verticals.

Learn more about path exploration.

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Analysing user journeys within Google Analytics

Richard Robertson

6th October 2020

*This article is about Universal Analytics which will sunset on 1 July 2023 and be replaced with Google Analytics 4. You can find our GA4 content  here .

In its purest form, a user journey is the journey a user takes on your website to perform an action. Understanding these journeys is critical for optimising your website as identifying them also highlights any blockers that could be causing you to lose revenue.

On larger websites, there are countless ways in which a user can navigate around and, without a way to track these routes, it can be difficult to optimise them efficiently. Thankfully, with the help of Google Analytics, these can be analysed with ease if you know the right places to look.

Google Analytics has many great features and reports, but certain pieces of analysis can be more difficult to produce from the standard reports. This post will breakdown the different methods and features that can be explored in Google Analytics to support you in discovering, mapping and troubleshooting user journeys on your website.

Segmentation

Segments allow you to group sessions or users based on specific behaviours performed. Segments enhance your ability to find insightful data on your users’ journeys when applied to reports, especially the ones I will be discussing with you today. Aside from enhancing your reports, you can also use segments themselves to analyse user journeys – we can break this down into two main functions.

The first function is to group sessions based on a specific interaction. For instance, I could create a segment for sessions that had signed up to our newsletter. Utilising the ‘All Pages’ report, I can see the exact pages users visited during converting visits. Additionally, if I had content groupings set up, I’d be able to quickly identify the types of content read before my users went on to sign-up to my newsletter. This information can be passed to the content team to prioritise the creation of articles that are likely to assist us with driving more newsletter sign-ups.

The second function is to create a segment with the sequencing rules, essentially allowing you to build a custom funnel without the ability to see drop off along the steps. One of the ways to utilise this feature is to create an open funnel with the first and last step. This way, using the ‘All Pages’ Report, you can exclude those two steps and analyse the pages viewed between these steps.

Behaviour Flow

Behaviour flow visualises the paths that users most-frequently take on your website with the ability to change the granularity to gain insights into the behaviours that are important to you. You can find out which pages users are frequently navigating between or if users are diverting journeys.

User Explorer

If you’re interested in looking at a specific user’s journey, User Explorer is the report for you. To use this feature, you’re first required to enable the User-ID feature in your property settings if you have not done so already. Once set up, you can find this report in Audience > User Explorer.

The User Explorer report stitches together the pages and events an individual user has performed on your site, displaying them as a timeline that can be analysed.

This can be harder for larger sites, due to the volume of users; however, using segments, you can filter down the list to find individuals that have done specific actions on your site. For instance, you can segment users who have completed very particular activities to discover if there’s any commonalities between similar users.

Previous Page Path

The Previous Page Path dimension is an excellent tool for analysing journeys. The primary purpose of using the Previous Page Path is for looking at how users are navigating to a specific page. This is handy for pages with multiple entrance points to a page like “Contact Us”, allowing you to analyse which pages are driving people to contact you.

This will highlight irrelevant pages and will assist you to  find pages where users are struggling to find the information they are after.

Checkout Behaviour/Shopping Behaviour

Checkout Behaviour/Shopping Behaviour are both available once you have set up enhanced ecommerce tracking on your website. Due to this, it’s one of the key ways to analyse ecommerce journeys in Google Analytics. You can find this report in Conversions > Ecommerce > Shopping Behaviour/Checkout Behaviour.

Shopping behaviour is a quick way to understand the health of your ecommerce journey. It provides a snapshot of your users’ shopping experience and gives you a breakdown of the percentage of users that have gone from viewing a product, all the way to purchasing a product on your website. You can build segments from any of the steps to help you analyse users in that funnel or even create segments from the drop-offs to understand why those users haven’t moved on to subsequent steps.

Checkout Behaviour focuses specifically on the checkout journey itself, highlighting any potential issues your users might be having once they’ve committed to purchasing a product from you by showing at which page they drop off at.

Site Search

Site Search is a custom feature of Google Analytics and uses query parameters to map internal search terms and categories. It must be enabled first which you can do in the view settings.

Though it isn’t a traditional way to analyse user journeys, it helps to analyse which terms users are searching internally. This can help you find gaps in content by looking at the keywords with low clickthrough rate, suggesting there wasn’t any content that the user wanted to read.

You can also use it to discover content that users are struggling to find whilst navigating your site. You can deep dive these by grouping users that have searched a specific term in a segment and analysing which pages they visited.

Custom Funnels

Custom funnels let you build a user journey and monitor the drop-off between steps. There are several ways you can build these in Google Analytics. As mentioned above, you can use a segment utilising the sequence feature. While this won’t allow you to monitor drop-off from your funnel, this feature can be used via the Google Analytics Reporting API and in Google Data Studio, unlike the options below. If you’re fortunate enough to have Google Analytics 360 within your organisation, then building custom funnels and analysing drop-off is easier.

Custom Reports – Funnel Report Type

Custom Funnels are one of the easiest ways to map and analyse specific user journeys within Google Analytics. This feature allows you to visualise the journey a user takes to complete an action on your site. Unlike the Behaviour Flow feature, you have to set up the journey you would like to analyse.

This feature is fully customisable, allowing you to choose whether the user must perform the actions during the same session or across multiple sessions. You can also choose if the funnel is open or closed, meaning users must perform each subsequent step or they can join further along. Furthermore, there’s the option to decide if you would like users to be able to divert between steps, or whether each step must be followed by the next.

You can even build segments based on users who have dropped off at certain points in the funnel, which helps to spot trends that have caused users to divert from their journey.

There are limitations to this feature; you can only have up to five stages in each custom funnel and each of these steps is limited to five rules.

Advanced Analysis

Advanced Analysis is another 360-exclusive feature. It was released in May 2018 and, at the time of writing this post, is still in beta. It’s Google’s answer to the workspaces available in Adobe Analytics, allowing a user to build fully customised reporting for a quick and easy way to delve into the data and derive insights.

Advanced Analysis has a few different report types. The one we’re focusing on for analysing user journeys is ‘Funnel Analysis’. It’s very similar to Custom Funnels with additional features that make this an incredibly powerful feature – one being that you can choose to analyse up to 10 steps rather than five. But the real advantage is the ability to use segments and dimensions to further breakdown your funnel.

When choosing between Custom Funnels and Advanced Analysis, it all depends on how in-depth you want to go with the analysis. Custom Funnels are fantastic as a start, but if you want to really analyse the user types that are dropping off, Advanced Analysis is the tool for you.

There are tons of features in Google Analytics and even more ways of using them to analyse your users. By understanding the limitations and features of them you’ll be able to use the right one to gather the insights you want to drive. User journeys can be complex, but by using the features above you’ll be able to improve user experience on your site and drive increased revenue for your business.

If you have any questions about this post, or want to talk more about user journeys, please leave a comment below and I’ll get back to you.

Comments are closed.

Very good analysis.

Kabza De Small

Thanks so much

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How To Track The Customer Journey With Google Analytics

by Madison Cassel | Jan 19, 2024

In the dynamic realm of online business, understanding and optimizing the customer journey is paramount. Google Analytics serves as a guiding light, providing businesses with the tools they need to decipher user behavior, make data-driven decisions, and continually refine their strategies. This blog will delve into the importance of tracking the customer journey and explore how Google Analytics can be leveraged to unravel valuable insights.

Why Track the Customer Journey With Google Analytics?

First, it’s important to understand why tracking the customer journey is an essential factor in achieving business goals. Comprehending the aspects of the customer journey can help you create an enhanced user experience and give insight into how to optimize your website. The customer journey can also assist in informed decision-making. Tracking the customer journey provides data-backed insights, enabling businesses to make informed decisions about content, marketing strategies, and website improvements. Additionally, from this informed decision-making, you can also determine the marketing ROI of the customer journey. By tracking user behavior, businesses can assess the effectiveness of marketing campaigns, identifying which channels and strategies yield the best results.

1. Acquisition Analysis

Delve into the “Acquisition” section of Google Analytics to understand the sources bringing users to your site. Identify which channels —be it organic search, paid advertising, or referrals—are driving traffic.

2. Behavior Flow

The “Behavior Flow” report illustrates the path users take through your site. Identify popular pages and potential drop-off points to refine the user experience.

3. Conversion Tracking

Monitor conversions through the “Goals” section in Google Analytics. Analyze which channels and campaigns contribute most to your business objectives, allowing for strategic adjustments.

4. Attribution Modeling

Dive into attribution modeling to understand the touchpoints that lead to conversions. This feature helps allocate credit to various marketing channels in the customer journey.

5. Custom Reports And Dashboards

Tailor reports and dashboards to focus on specific aspects of the customer journey. Customize your view to track metrics that directly align with your unique business goals and objectives.

In a digital era where customer interactions span various online touchpoints, tracking the customer journey is imperative for business success. Google Analytics provides a robust set of tools to unravel the mysteries of user behavior, empowering businesses to make data-driven decisions and optimize their online presence. By harnessing the power of Google Analytics, businesses can embark on a journey of continuous improvement, ensuring a seamless and satisfying experience for their customers.

In conclusion, Google Analytics emerges as an indispensable tool in the quest to understand and enhance the customer journey. By meticulously tracking how users interact with your online presence—from the first click to the final conversion—Google Analytics offers unparalleled insights into customer behavior and preferences. Businesses are better positioned to craft a user experience that not only meets but exceeds customer expectations!

Do you need help navigating Google Analytics to understand your customer journey(s)? Contact Corkboard Concepts today!

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Customer journey mapping: The path to loyalty

A version of this tutorial originally appeared in the free Primer app .

In an ideal world, the journey people take to become loyal customers would be a straight shot down a highway: See your product. Buy your product. Use your product. Repeat.

In reality, this journey is often more like a sightseeing tour with stops, exploration, and discussion along the way—all moments when you need to convince people to pick your brand and stick with it instead of switching to a competitor.

Staying on top of all of these moments might seem overwhelming, but mapping your customer’s journey can help. It can give you and your team a greater understanding of how your customers are currently interacting and engaging with your brand, and also help illustrate how your products and services fit into their lives, schedules, goals, and aspirations.

Let’s take a look at five steps your team can take to start journey mapping.

1. Find the sweet spot where your customers’ goals and your own align

Before you start journey mapping, nail down your business goals. Any marketing and communication you deliver during the customer journey should be focused on helping your brand reach those goals.

However, it’s important to acknowledge that your customers’ goals might be different from yours. For example, let’s say your goal is to sell more sunglasses with new, improved lenses that have a better profit margin. Meanwhile, your customers’ top concern might be getting sunglasses that match their personal style. Lens protection could be their second or even third priority.

Consider how your marketing and communication strategies can help your customers reach their goals while also getting you closer to yours.

2. Identify all of the communication touchpoints in your customer’s journey

When do you traditionally communicate or engage with customers? Make a list of these moments and group them based on when they happen during the journey: pre-purchase, purchase, and post-purchase.

Now find communication touchpoints you may have missed. Track what actions and interactions between your brand and your customers happen just before and after each of the pre-purchase, purchase, and post-purchase stages.

For example, you might decide that a major moment in your purchase stage is when your customers are guided through your website to buy an item in their shopping cart. But you might notice other communication touchpoints right before that purchase moment, like your website confirming to customers that an item has been added to their shopping cart, then suggesting related products.

Looking for all these touchpoints can quickly bog your team down in a lot of details and micro-interactions. To avoid that, prioritize the moments that get you closer to achieving your business goals.

3. Recognize pain points and moments of delight

How might your customers feel at the pre-purchase, purchase, and post-purchase stages as they attempt to achieve their goals? For example, could your customers be happy that your website makes browsing easy, but frustrated at how confusing it is to purchase a product?

Find the moments where your customers might have negative experiences. Who on your team is involved in those touchpoints? Your web designers? Your marketing team? Your copywriters? Are there other team members who could collaborate and improve the situation?

Say a customer likes how your online ad describes your product. But when they go to your store, salespeople present the product differently. That’s an opportunity for your copywriters and salespeople to better align their language and sales pitches.

4. Experience the customer journey yourself

Imagining how your customers might feel during their journey is valuable, but actually experiencing it for yourself can uncover much-needed insights.

If your business is run online, open a browser and experience what it’s like to be your customer. Similarly, if you have a brick-and-mortar store, go into a location that sells your product. Afterwards, ask yourself about the main communication touchpoints you encountered. Did they work well? Did they help you complete your journey? What was missing?

And don’t forget about the competition. Become one of their customers and experience the journey they’ve created. Then ask yourself all of the same questions.

5. Visualize your customer journey map

Go beyond just writing down your customer journey and communication touchpoints, and actually create a visual map of them. This doesn’t need to be a polished, heavily-designed visualization. Simply write each of your touchpoints down on individual sticky notes or papers, then pin them in order to a wall.

By doing this exercise, you’re helping your team take a bird’s eye view of the entire customer journey. You can organize your thoughts and collaboratively brainstorm new ideas for changing or adding to your communication at these touchpoints.

Make sure to create hypotheses around why new communication touchpoints will improve the customer journey, then implement and test them. If your hypotheses are wrong, go back to your journey map, reassess, tweak, and improve.

Yes, the journey mapping process can be fairly intensive, but it can have a big impact on your business. That’s why it shouldn’t be just a one-time event. Customer tastes can shift, new technology can become available, and your brand itself might evolve. So it’s important to do journey mapping at least once a year and evaluate what communication touchpoints are still working and what needs to be revisited.

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Stuart Hogg is a marketing consultant who has worked with a number of Fortune 500 brands. He created “Journey Mapping: Connect the Customer Dots” for the Primer app.

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What is Customer Journey Analytics

Updated: July 23, 2024

Published: June 28, 2023

A customer doesn’t just mindlessly purchase a product or service. They go through an entire journey, from discovering your brand, to purchasing your product or service, to sometimes recommending it to someone else. 

To make sense of your customer’s journey, you’ll need to leverage customer journey analytics.

Every business, startup or enterprise — in any industry — needs to understand how customers interact with their brand. Insights gathered from customer journey analytics can help, while leading to increased customer lifetime value, customer loyalty, and revenue growth. 

In this blog post, we cover the following:

What is customer journey analytics?

• Customer Journey Stages
• Customer Journey Analytics Benefits

Customer Journey Analytics Software

• Customer Journey Analytics vs. Customer Journey Mapping

Customer journey analytics is a collection of data that helps you to understand how your prospects or customers behave, engage, and convert along the customer journey. 

Customer journey analytics often begins with a customer journey map , which is a visual representation of every step the customer goes through with your business. Then, it applies data on how your customer behaves throughout different phases of that map,  to help you assess the effect your customers’ journey has on your business, or what’s holding customer’s back from completing that journey and purchasing a product

Customer Journey Analytics Steps

1. outline a customer journey map..

Create your customer journey map using HubSpot’s template

The first step to customer journey analytics is creating a customer journey map. A typical customer journey map includes the following: the buying process, user actions, emotions, pain points, and solutions. The customer journey map is the foundation for further analysis.

2. Identify the right analytics tools.

To accurately conduct customer journey analysis, you'll need the right tools. 

A good customer journey analytics tool will monitor, track, and analyze data like website data, conversion data, and detail data across multiple channels.

Customer data platforms (CDPs) also play a role in supporting customer journey analytics. The platforms assign unique IDs to your website and app to build single customer views, which can include information such as location, browser, device type, operating system, historical transactions, and visitor logs.

3. Collect your data.

A robust analytics platform should enable you to collect data on customer behavior. Data can be broken down into two main buckets: user data and interaction data. 

• User data: Provides context on a user and their traits. Data can include email, age, industry, and occupation.
• Interaction data: Gives information about how a user interacts with your product or service.

4. Analyze data.

Data in itself is not meaningful without analysis. The purpose of customer journey analytics is to make sense of the data and extract insights that can inform your business strategy. 

For example, an e-commerce company might identify, through analysis, that requiring customers to create an account to complete a purchase leads to the customer not completing the purchase — a solution could be implementing a guest checkout option.

5. Update customer journey map.

Using the insights you’ve gained, you can now update the customer journey map accordingly. For example, you might add additional pain points uncovered through data analysis, like requiring customers to create accounts to complete a purchase.

6. Use customer journey analytics to test new strategies.

The next step is to figure out how to enhance the customer journey experience. Testing new strategies like adding a guest checkout option, making the account creation process faster with fewer steps, and sending abandoned cart emails are all examples.

Benefits of Customer Journey Analytics

By leveraging customer journey analytics, you'll be able to improve your customer’s experience with actionable insights, while unlocking benefits like:

Better Understanding Customers

By gathering and synthesizing data, you will better understand what aspects of the buyer’s journey lead them to purchase a product or service, or not. For example, an e-commerce company might learn that customers that come from a specific social media platform are more likely to buy, or discover that certain audience demographics or affinities are more likely to become leads.

Pinpointing Where You’re Losing Customers

Not all customers follow through, and unless they fill out a survey, it can be difficult to figure out why they churn. By leveraging customer journey analytics, you can pinpoint where you’re losing potential customers. 

For example, a business can lose potential customers during channel or device transitions. A prospect  might start filling out a form on a mobile device but choose to complete it on a laptop. If information entered is lost, the potential customer might not take the time to complete the signup process.

Optimizing and Solving for Prospects

With a better understanding of customers’ pain points and the reasons behind them, you'll be able to figure out how to improve and strategize around an accurate customer journey.

Improve ROI

Are your investments in customer experience worth it? By using customer journey analytics, you’ll be able to measure ROI for customer experience initiatives. From there, you can streamline, remove, or cost cut initiatives that don’t benefit your bottom line, or double down on the aspects of the buyer’s journey that do.

For instance, if you run an incredibly expensive advertising campaign that doesn’t yield the same level of new customers or purchase page visits as unpaid or more in-house content, you can aim to save money on ads and focus on the more affordable strategies that actually earn you money.

1. HubSpot Marketing Hub: Advanced Marketing Reporting

Get started with customer journey analytics

HubSpot Marketing Hub is equipped with robust customer journey analytics capabilities and tools, which can map data around conversions, leads, deals, and website engagements around different stages of the customer journey. 

The Advanced Marketing Reporting tool also enables you to  attribute every customer interaction to revenue, analyze conversion rates and time between nurturing path steps, and provides further data to help you build informed strategies that can improve ROI and purchase rates.

2. Content Square

Content Square captures UX, performance and product, and content data throughout the customer journey. The platform also enables you to visualize metrics so that they are easily digestible. You will be able to get insights like bounce rate and number of lost conversions, and dig deeper to pinpoint why.

3. Google Analytics

Google Analytics is a widely used website analytics software that enables you to track user behavior on different platforms, including mobile applications. Features like daily traffic reporting give you insight into what visitors are engaging with. Plus, its Analytics Amplifier can combine Google Analytics and HubSpot data .

Customer Journey Mapping vs. Customer Journey Analytics

Customer journey analytics and customer journey mapping are often confused with each other. Although they’re complementary, customer journey mapping visually presents customer journey stages from start to finish, while customer journey analytics offers data about a  customers’ interactions in each stage.

Customer journey maps often include the following:

• The buying process: By pulling data from places like CMS and prospecting tools, you will be able to figure out what goes into a customer’s purchasing process. 
• User actions: This part of the customer journey map details the actions the customer takes throughout their journey.
• Emotions: Emotions help color your understanding of how your customer is feeling and reacting as they go through their journey with your business.
• Pain points: Adding pain points to your customer journey map gives you a comprehensive picture of the challenges your customer may experience.
• Solutions: Figuring out solutions can help your customers experience fewer pain points. The data and insights you’ve gathered can help inform your solutions.

Customer journey analytics delves deeper. The customer journey map is the “what” and customer journey analytics is the “why” because it organizes customer or prospect data around each stage.  

Here’s an example of how customer journey analytics works in HubSpot Marketing Hub:

HubSpot’s Advanced Marketing Reporting Tool

Customer Journey Map vs. Analytics Example: Let’s say your business offers CMS tools and your ideal customer, a graphic design firm, finds you through a targeted Instagram ad.

In the customer journey map you’ve built , your target customer considers using your CMS tools to build a new website that showcases their strengths. They schedule a demo before trying the free version and are initially excited, but become frustrated with the limited design elements offered by the free version. Their biggest pain point quickly becomes lack of versatility. They then look into purchasing the paid version or go to a cheaper competitor.

With customer journey analytics, you’ll apply real-time data to that map: From journey mapping, you’ve identified the steps your customer often takes  and their common pain points. A strong customer journey analytics tool can then collect, aggregate, synthesize, and visualize data to help you make sense of your customer’s actions and see if your mapping and journey-based strategies work. 

For example, data might show how your customer is interacting with your product. 

A good Customer Journey Analytics platform combines data like user data, survey results, and website analytics, you can gain a comprehensive view of why your customer is experiencing those pain points and consequently address their concerns.

Cultivate an Impactful Customer Journey

In order to remain competitive, it is important to understand and create strategies to enhance the customer’s journey. Customer Journey Analytics is just one component. Other key steps include creating buyer personas , mapping out the customer journey , and continuously updating strategies based on data.

To get started with improving the customer journey, learn more about HubSpot’s marketing solution Marketing Hub .

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Customer Journey Analytics: Definition, Tools, & Examples

Learn how customer journey analytics helps you measure the ROI on your customer experience initiatives. Use it to boost revenue, reduce churn, and improve CX.

Customer journey analytics (CJA) is the process of analyzing the entire customer journey through customer data points, then strategizing ways to improve the overall customer experience (CX) . Customer journey analytics is a holistic process that makes customer journeys measurable and helps you identify insights and actions to delight and retain your customers.

Key takeaways

• Customer journey analytics is the process of examining critical data pertaining to user journeys to make informed decisions on improving the customer experience.
• Some of the benefits of customer journey analytics include the ability to measure the ROI on CX initiatives and improve the customer experience through the insights it provides, as well as reduce churn and boost revenue.
• Measuring customer journeys is a process that involves creating user journey maps, determining and collecting data pertaining to those journeys, and defining success metrics and milestones along the way.

What is customer journey analytics (CJA)?

Customer journey analytics is the gathering and analyzing of data that pertains to customer behavior to improve the customer experience. Analysis happens over multiple customer touchpoints and channels over a period of time and measures the impact of behavior on business outcomes.

While gathering customer data, you can collect all user actions in one central database with an associated timestamp. Information is collected through a unique identifier on what the user is doing and who the user is.

Using this information, it’s possible to map out customer journeys and then analyze the customer engagement levels for each journey to understand what’s going well and where customers might be getting stuck. The analysis helps to optimize these customer journeys and also measures the performance of your CX initiatives.

Example insights from customer journey analytics

Customer journey analytics provides deep insights to improve the customer experience. Some examples include:

• Customer journey analytics makes it possible to analyze the path customers take to resolve customer queries. Some insights derived from this analysis might include what types of issues can be resolved by self-service channels and which ones need human interference. This information makes it possible to optimize self-service channels, improve the operational efficiency of resolving customer queries, and enable customer support staff to focus on more complex customer issues.
• For ecommerce companies, customer journey analytics makes it possible to view the steps a customer takes while completing a purchase, which can help identify any barriers to completing the transaction. You might find, for example, that a common frustration while completing a purchase is having to create a user account. You can then use this insight to A/B test a guest checkout option and see if it removes the friction.
• Customer journey analytics can help you identify channel-specific insights to improve the customer experience. For example, you might find that users on your mobile app drop off at a higher rate than users on your website. This insight could indicate that you need to rethink parts of your mobile experience.

Benefits of customer journey analytics

There are several benefits of customer journey analytics, including:

Measuring the ROI on CX initiatives

In a CX survey, 20% of respondents said that measuring customer experience initiatives was one of the key challenges being faced by organizations in the U.S. Customer journey analytics solves this problem by making it possible to measure the ROI on CX initiatives.

Product managers and CX designers can use customer journey analytics to connect data and numbers to customer journeys. For instance, CJA can compare the revenue generated from two user journeys to figure out which user journey leads to more revenue for the business, making it possible to shift to the journey that’s most beneficial.

Customer journey analytics makes it possible to understand how the customer interacts with the product, how their behavior changes when modifications are made to the customer journey, and how your product metrics are impacted because of this changed user behavior.

Improving the customer experience

By visualizing user journeys built by customer journey analytics tools, it’s possible to identify bottlenecks people might face in your product, minimize them, and make smart product suggestions based on their past behavior.

For example, with customer journey analytics, it’s possible to diagnose that users of an ecommerce app fail to make a purchase during the last step of the transaction, especially when using the app for the second time. They might be getting stuck since they don’t remember what they bought the last time, so CJA makes it possible to autosuggest items based on what the customer purchased on their last visit. Reminding customers about their past transactions can improve the overall shopping experience by helping users purchase with ease.

Customer journey analytics tracks data in real time. This enables you to analyze customer behavior while the customer interacts with your website or product, build user journeys around that behavior, then find opportunities to make improvements to the customer experience.

Reducing customer churn

Since customer journey analytics helps predict customer behavior based on their past actions, it can also identify customers at risk of leaving the product or website, enabling you to take action to retain at-risk customers.

Upon identifying at-risk customers, it’s possible to use CJA to personalize interactions with them and help them feel more positive about the brand, so they’ll change their minds about leaving. In a CX study, 58% of respondents stated that their organization had seen significant increases in customer retention as a result of using customer analytics.

Boosting revenue

By helping you identify the customer journeys that result in a purchase, it’s possible to boost revenue using customer journey analytics. You can further optimize these journeys by reaching out to customers in real time with relevant communication like upsell and cross-sell offers.

CJA can also help identify your best-performing channels by monitoring customer behavior across different touchpoints. So if your website is performing better than your app, you can focus on optimizing the revenue from your website while making improvements to your mobile app.

Steps for measuring customer journeys

Step 1: create or capture user journey maps.

Before you start measuring a customer journey, it’s important to first create a user journey map. You can create this journey map using prototyping tools or Post-it Notes based on the actions users take. For example, if you want to measure the journey of playing a song on a music app like Spotify, you need to create the entire journey map so you can visualize it.

In this example, the user journey might consist of the following steps: going to the Spotify website, downloading the app, creating a login, searching for a song, and then playing the song. You’d need to write these steps out in the form of a “journey” or use a tool that captures these user actions and creates the journey maps for you.

The goal, in this example, is to play a song on the app. And the journey to that goal consists of several steps along the way. You need to view the journey across different channels since, at the end of the day, your user is trying to accomplish a goal and it doesn’t matter whether they do it via your mobile app or your website.

Step 2: Determine the data you need to collect at each step of the customer journey

To measure a customer journey, you need to define the critical data points you need to measure for that journey. For instance, in our Spotify example, here are some data points that might be relevant to help quantify the journey:

• Number of attempts to download the app
• Time it takes to download the Spotify app
• Time it takes to create a user login
• Number of attempts to play a song

Collecting all of the data in one centralized place makes it easy to access it and pick the relevant bits of data needed along with their timestamps. The data required will depend on the journey you decide to measure.

For every part of the customer journey, there’s an action that your brand wants the user to complete. Every journey has a goal, and there are milestones to achieving that goal. It’s important to define both the goal and the milestones along the way, so you know what to measure and what success looks like.

With the example of playing a song on Spotify, some success metrics or milestones would be:

• Downloading the Spotify app
• Creating a user login
• Playing the first song
• Subscribing to the Spotify service
• Sharing the first playlist
• Renewing the subscription

Think of milestones as critically important steps in the process of achieving a goal. Make a list of these steps, so you can have clearly defined milestones.

Step 3: Analyze the customer data

The next step is to identify your data sources and capture behavioral customer data across the customer journey. Once you’ve collected data, you can start analyzing it and measuring key metrics along critical flows of the journey. You’ll be able to gauge where customers are spending their time, what’s causing them frustration, and which behaviors lead to revenue-generating outcomes. Using this information, you’ll be able to measure the customer journey effectively and figure out how to improve it.

Customer journey analytics tools

Using the Journeys feature on Amplitude , it’s possible to discover what’s making users convert or drop off. With Journeys, you can:

• View step-by-step breakdowns of the paths taken by converted and dropped-off users.
• Uncover the paths most likely to accelerate conversion.
• Identify what your users do if they don’t convert.
• Understand the friction points in your customer experience and develop a strategy to fix them.

By defining the start and endpoints of the journey, the Journeys feature within Amplitude helps you see what percentage of paths converted and what percentage dropped off.

• What are the biggest challenges currently being faced by your organization in terms of customer experience? Statista
• Performance enhancements resulting from the use of customer analytics in the United States as of March 2018 . Statista

See what customer journey analytics looks like in our self-service demo , or get started with journeys using your own data in a free Amplitude account .

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More best practices.

Customer Journey Analytics 101: Comprehensive Guide for SaaS Companies

How can product and marketing teams leverage customer journey analytics to make data-driven decisions and build delightful customer experiences?

This is the key question we discuss in our guide, so if you’re after the answer, let’s dive right in!

• Customer journey analytics is the process of tracking user interactions at all the touchpoints in their journey .
• Customer journey mapping is a part of customer journey analytics and it uses qualitative insights. Journey analytics uses quantitative data to assess what happens at different stages of the journey.
• In addition to increasing customer satisfaction and reducing customer churn , customer journey analytics helps teams boost customer lifetime value.
• The first step of customer journey analysis involves mapping out all the stages, actions, milestones, and touchpoints for each user persona.
• Next, you need to collect relevant data from various sources, like web traffic or in-app product usage.
• After that, analyze the data collected via various channels. There are different ways to do it, depending on your goals. For example, you could analyze conversion rates .
• Attribution analysis allows you to evaluate the effectiveness of your touchpoints.
• User flow analysis identifies and visualizes all actions taken by users.
• Trends analysis focuses on long-term patterns and changes in user behavior.
• How you act on the customer journey analytics insights depends on the problems you’ve identified. For example, you can improve the sign-up rates by enabling single sign-on (SSO) or delaying email confirmation.
• Both Amplitude and Google Analytics are robust analytics tools for tracking user behavior in web and mobile apps but they lack the engagement layer to act on the insights.
• Userpilot is a product growth platform with analytics , feedback, and engagement features.
• To see how to use it to analyze and optimize your customer journeys, book the demo!

What is customer journey analytics?

Customer journey analytics is the process of tracking and analyzing customer interactions with the brand and product across all touchpoints in their journey .

Customer analytics focuses not only on what the customer does inside the product. But rather, its goal is to obtain insights into engagement along the entire user journey and across all channels, starting from the moment they learn about the product to the purchase – and beyond.

Customer journey mapping vs customer journey analytics

Customer journey mapping and customer journey analytics are two related but distinct processes.

A customer journey map is a visual representation of the journey with your company, including their interactions, experiences, and emotions. It presents all the touchpoints and stages that the user goes through, from the initial awareness to post-purchase.

Customer journey mapping usually relies on qualitative data collected via interviews, surveys, and customer behavior observations.

On the other hand, customer journey analytics uses quantitative data from various sources, like website or product analytics, or customer feedback , to uncover patterns and trends in customer behaviors to optimize their journey.

The benefits of tracking customer journey analytics

Why does customer journey analytics matter in product management? Here are a few benefits:

Improves customer experience

Analyzing customer journeys enable SaaS companies to improve the customer experience by identifying stages that need optimization.

For example, tracking conversions during the sign-up process can help you identify friction points that slow users down and make the process unnecessarily challenging.

By optimizing the touchpoints, you will be able to make the experience less painful and increase the conversion rates as a result.

Reduces customer churn

Friction in the customer journey often leads to churn . Customers who struggle to complete tasks or discover important features eventually give up and go looking somewhere else.

Consequently, identifying the friction points and addressing them will help you boost the retention rate.

What’s more, by tracking your power users, you can identify which practices or behaviors contribute to their success. By making other users follow the happy paths of power users with similar objectives, you will increase their chances of success as well.

Increases the customer lifetime value

A higher retention rate goes hand in hand with a greater customer lifetime value (LTV) . The longer your customers stay with you, the more money they spend.

Additionally, analyzing customer journeys will help you take better advantage of account expansion opportunities through upsells and cross-sells.

For example, it can help you identify user behavior patterns indicating that the user may need more advanced functionality. Armed with this knowledge, you could trigger contextual messages offering them an upgrade to a higher plan.

What is an example of customer journey analytics?

Let’s imagine a SaaS product that witnessed a high churn rate during the onboarding stage.

Here’s how the onboarding process works:

• Users log into the product.
• A welcome survey pops out.
• Completing the survey triggers an onboarding checklist .
• Users complete the tasks from the checklist to familiarize themselves with the key product features.

How could the team diagnose the problem?

By looking at the conversion rates from each of the stages, the team realizes that most churned users don’t complete the checklist tasks.

Specifically, customer journey data shows users fail to complete a task involving product customization. That’s the step they need to have a closer look at.

Session recordings of the churned users trying to customize the product and surveys reveal that there are too many customization options and users find the experience overwhelming. What’s more, they don’t know exactly how each of the settings will affect their experience.

What’s the solution?

Based on the findings, the team decides to reduce the number of available options. They also design a set of tooltips to provide in-app guidance on each of them.

How to conduct a user journey analysis to improve the customer experience?

Let’s look at a step-by-step guide on how to use customer journey analytics to create outstanding customer experiences.

Step 1: Map out the entire customer journey

Start mapping out the customer journey by identifying the user personas. While all of them may use the core features of the product, they may have different goals and use them in a unique way. That’s why each of them will have a separate map.

Next, list the key stages of the customer journey.

To kick off, you could use the Pirate funnel (Awareness, Acquisition, Activation , Retention, Revenue, Referral) and adapt them to the unique characteristics of the product. For example, your CJM steps could be Discovery, Engagement, Evaluation, Purchase/Onboarding, and Account Growth/Advocacy.

For each of the stages, identify the goals that are specific to the user persona.

After that, identify all the user actions at each stage. For example, at the Discovery stage, the user could run a Google search for ‘best software for X’, read reviews, and ask peers for recommendations. Decide which of the actions are the milestones that will drive conversions to the next stage.

Finally, list all the touchpoints where the customers will interact with the product. For example, at the Discovery stage, this could be the Google SERP, your blog posts, or your YouTube channel.

Step 2: Collect customer data from multiple channels

The data that feeds into your customer journey analytics will come from various sources.

These could be web analytics, in-app product usage tracking, heat maps , customer feedback surveys , reviews, social media mentions, or calls with the customer success teams.

Each of the channels may require a dedicated tool to ensure you get a complete picture of how customers behave along the journey.

For example, you may need a tool that enables you to track feature engagement both in your web and mobile apps, or an NLP-powered feedback tool that will help you analyze qualitative responses.

Step 3: Analyze data related to customer interactions and customer behavior

Once the data starts coming, it’s time to analyze it. There’s no one way to do it as it’s very much dependent on your product or your goals . Here are examples of a few possible kinds of analysis.

Customer journey reports

Customer journey reports focus on user progress from one stage of the journey to another.

The reports contain information about conversion rates for different stages. Analyzing the data enables you to identify bottlenecks and pain points that stop users from achieving their goals.

In addition, you can use the collected data for user segmentation . For example, you could group users into power users and churned users and analyze their behavior in greater detail.

Attribution reports

Attribution reports help product teams to assess the effectiveness of different touchpoints along the customer journey and determine which of them are most influential in driving customer conversions or desired business outcomes.

With such knowledge, they can optimize the underperforming touchpoints or allocate their resources to prioritize the future development of the most successful ones.

Attribution reports also help teams evaluate the impact of new customer experience initiatives.

User flow chart reports

User flow reports provide teams with granular insights into the specific steps taken by users to complete a task. They are normally visualized in charts consisting of boxes representing each action.

User flow charts are a valuable tool for identifying the happy path for each user segment and eliminating friction or unnecessary steps from the customer experience.

Trends analysis reports

Trends analysis focuses on identifying and analyzing patterns and changes in customer behavior over time to keep track of their evolving needs and preferences.

For example, trends analysis can reveal new pain points in the customer journey.

Examining customer feedback or support tickets can help you identify recurring issues or growing dissatisfaction at different touchpoints. Such knowledge enables you to proactively address these issues before they become significant problems.

Step 4: Act on customer behavioral data analysis to improve customer satisfaction

The final step involves acting on the insights you gained by analyzing the customer journey data. What exactly you do will depend on the problems you’ve identified.

For example, to improve the conversion rates at the sign-up stage, you could enable single sign-on (SSO) or delay the email confirmation. To improve feature discovery and drive upsells , you could trigger in-app messages with contextual prompts.

The best customer journey analytics tools for SaaS

To effectively track and analyze user behavior at all touchpoints in the customer journey, you need the right tool stack .

Let’s check out a few customer journey analytics tools available to SaaS product teams.

Userpilot – The complete product growth and analytics platform

Userpilot is a digital adoption platform that offers feedback, analytics, and engagement functionalities.

In practice, this means that you can track product usage , gather customer feedback , analyze the data for insights, and then act on it to drive engagement and conversions with in-app guidance.

What customer journey analytics features does Userpilot offer?

• Event tracking, including custom events
• Goal tracking for customer journey analysis
• Funnel analysis and paths (coming soon)
• Feature usage tracking ( clicks , hovers, text infills)
• In-app surveys to gather customer feedback
• Survey, checklist, and resource center analytics
• User segmentation
• Real-time data relay for event-based message or survey triggering
• Webhooks and integrations with specialist analytics tools, including Amplitude, Heap, and Mixpanel

Userpilot offers 3 pricing plans.

The lowest one, Traction, starts from $249/month if paid annually. It gives you access to most of the analytics features above with the exception of webhooks and event-based content triggering.

To get access to the features, you’ll need either the Growth or Enterprise plan. Both of them come with custom pricing and usage limits.

Amplitude – Advanced analytics platform

Amplitude is a dedicated analytics platform with cutting-edge functionality.

Here are the top Amplitude features :

• Cohort analysis/customer segmentation
• Milestone analysis/goal tracking for customer journey analysis
• Funnel and impact analysis
• Conversion drivers for attribution analysis
• Pathfinder for user flow analysis
• Root cause analysis
• Custom dashboards
• Real-time data reporting
• Integrations with feedback and engagement tools

Amplitude offers 3 pricing plans.

The lowest one is free and it gives you access to the main customer journey analytics features.

Google Analytics – Free analytics platform to track customer journeys

Google Analytics 4, the new incarnation of the legendary Universal Analytics, allows you to track both web traffic and in-app user behavior. This makes it a comprehensive analytics platform for end-to-end journey tracking.

The main GA4 features include:

• Real-time activity tracking
• No-code event tracking
• Event filtering by category, action, and label
• Behavior reports – insights into visitor interactions with your website or product
• Audience reports
• Acquisition reports
• Goals and conversion tracking
• Funnel analysis
• Customized dashboards

All of the above features are available for free.

However, to get access to features like attribution analysis, you need the Analytics 360 subscription which is pretty expensive – it costs up to $12,500/month.

Customer journey analytics allow teams to gain a deeper understanding of user behavior at various touchpoints. As a result, they can optimize the journey by removing friction and providing users with the guidance they need to achieve their goals in less time.

If you want to see how to use Userpilot for customer journey analytics, book the demo!

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How to Analyze (and Improve) Customer Journeys

We walk through everything you need to know to measure, analyze, and optimize the customer journey.

What are customer journey analytics?

Customer journey analytics is the process of identifying customer touchpoints and understanding how they affect customer experiences and business outcomes. It includes interactions that take place before, during, and after the point of sale.

3 reasons companies are focusing on customer journey analytics

Measure engagement across channels

Customer journey analytics help identify the channels that are effective at engaging customers.

Glossier, a beauty and skincare brand, analyzed customer behavior between its eCommerce platform and its publication Into The Gloss . By bringing this data together into a unified customer profile, Glossier discovered that people who browse both sites tend to spend more than those who browse only one. Digging further, Glossier found out which articles led to purchases, and was able to replicate that recipe for success.

Optimize omnichannel customer experiences

In an omnichannel approach , you connect all of your customer engagement channels to provide a continuous experience for customers. 

Nike has been lauded for its omnichannel experiences across its app, online shop, and brick-and-mortar stores. The inventory and events in Nike Live stores are tailored to suit the shared traits and user behaviors of local NikePlus members. Shoppers are encouraged to use the Nike app in stores to scan QR codes and learn more about products, or to have clothes delivered to a fitting room.

Reduce customer churn and improve retention

Amid economic uncertainty and rising digital advertising costs , customer retention has become a crucial growth strategy .

Being able to recognize the telltale signs of customer satisfaction or dissatisfaction helps businesses proactively launch personalized campaigns to either keep users engaged and prevent them from churning. 

One way to do this is by identifying the interactions that increase customer value and loyalty. For instance, at Segment we studied the behavior of our loyal customers and identified a set of  high-value actions they all had in common. Using this data, we crafted personalized messages and engagement campaigns to nudge other customers to follow suit.  

How to analyze customer journeys in 5 steps

1. identify touchpoints and define interactions.

First, organize customer touchpoints by journey stage: awareness, consideration, conversion, service, and advocacy. Here are a few examples:

Awareness: clicking on a link from another website

Consideration: watching a product demo video

Conversion: setting up a paid account

Service: chatting with customer support

Advocacy: sending a referral code to potential users

2. Measure how customers interact on each channel

Identify all the channels where you interact with potential and current customers (e.g. social media, email, your website, or app) and connect these to a business intelligence tool or a customer data platform (CDP). 

From there, you can start comparing engagement rates across channels, and identify the most important metrics to track depending on your business goals. 

3. Set up an attribution program

Attribution helps determine which touchpoints lead a customer to convert (e.g. creating an account, signing up for a free trial, etc). We recommend using multi-touch attribution because it takes into account the entire customer journey.

To set up an attribution program, identify the events and user traits significant to your model, as well as the channels that generate this data. For example, if you have a blog and also advertise on LinkedIn, you’d want to pull data from Google Analytics and LinkedIn, focusing on actions like scrolling down a page and clicking on an ad.

4. Identify where and why customers churn

Sometimes, customers will fill out a survey explaining why they decided to churn. Other times, they drop off without explanation. For the latter, businesses can dig through customer support interactions or session analytics  to find the cause of their dissatisfaction (e.g. frequent bugs, rage clicks).

Customer journey analytics can also unearth the signs of someone who’s about to churn. For example, you may find that in the weeks prior to churning, customers tend to unsubscribe from your email list, and leverage this insight to re-engage at-risk users. 

5. Use your data to create a customer journey map

Using the data from customer journey analytics, you can create customer journey maps, which Forrester Research defines as “ documents that visually illustrate customers’ processes, needs, and perceptions throughout their relationships with a company.”

Some maps capture the entire customer experience, while others focus on specific stages, like illustrating the path to adopting a new product feature.

Here’s an example of a journey map we in the early stages of Twilio Engage .

7 metrics for analyzing the customer journey

High-level metrics, customer satisfaction score (csat).

A customer satisfaction score (CSAT) measures users’ satisfaction with your product or service, typically on a scale from 1-10.

Calculation: average CSAT =sum of satisfaction ratings ÷ total # of responses

Customer Lifetime Value (CLV)

CLV reflects the total revenue you expect to earn from a customer throughout their relationship with your business. 

Calculation: CLV = (annual revenue per customer x customer lifespan in years) – customer acquisition cost

Customer Effort Score (CES)

CES measures how easy or difficult it is to do business with you via surveys where customers rate ease of use on a numerical scale. 

Calculation: CES = sum of effort ratings ÷ total # of responses

Touchpoint & engagement metrics

Session/activity time.

Tracking the average session time helps you identify trends or outliers in app usage (e.g. drastic drops can point to bugs or outages, while a steadily declining drop can signal waning engagement). 

Calculation:

length of session time = time when the user leaves the app − time when the user enters the app

average session time = total session time ÷ # of sessions

Bounce rate

Bounce rate refers to the percentage of single-page sessions – where a visitor leaves your site after viewing just one page – out of the total number of sessions. The optimal bounce rate is 26% to 40%, according to SEMrush. Keep in mind that a bounce isn’t always bad (a bounce off a FAQ page may indicate the reader got the answers they needed).

Calculation: bounce rate = (single-page sessions ÷ all sessions) x 100

Open rate measures the percentage of emails that were opened among all emails sent in a campaign (a study by MailChimp found the average open rate is 21.33% ). 

Calculation: open rate = (# of opened emails ÷ # of emails sent) x 100

Conversion rate

Conversion measures the percentage of people who perform an action you’ve asked them to take. If 100 people see your CTA to download an ebook and half of them did so, you have a 50% conversion rate.

Calculation: conversion rate = (# of users who completed a specific action ÷ # of users you exposed to that option) x 100

5 tools for customer journey analytics

Customer data platforms (cdps).

CDPs collect data on customer interactions across multiple channels. They unify the data into a single customer view and update customer profiles in real time based on the latest touchpoints. They also help you identify customer segments and implement tailored workflows based on each segment’s shared journeys.

Customer Engagement Platforms (CEPs)

CEPs like Twilio do everything a CDP does while also letting you orchestrate customer engagement workflows. For example, if you answer a support call from a customer and send updates on their issue through WhatsApp, you can do both on a CEP instead of switching from one app to another.

Attribution tools

Attribution tools like Adjust , Criteo , and Singular analyze how much each touchpoint contributes to a conversion event. Choose a tool that supports your preferred attribution model. Better yet, get one that supports several different models, including multi-touch attribution.

You don’t have to stop at analyzing the first conversion event. Integrate your attribution tool with a CDP so you can measure the impact of different marketing campaigns throughout a customer’s journey.

Behavioral analytics tools

Behavioral analytics tools like Indicative and Mixpanel identify patterns and changes in customer behavior. They also spot behavior “cohorts,” which are customer segments formed on the basis of shared actions.

With this data, you can predict customer behavior and lifetime value, and create workflows that are automatically triggered when a customer performs a certain action. 

Business intelligence (BI) tools

BI platforms like Holistics , SAS , and Tableau collect and process unstructured data from various sources to help you make sense of it through reports and visualizations. BI reports are descriptive, as they’re based on past and present events. So while they’re useful for spotting trends, they’re more powerful when integrated with other analytics and customer-facing tools.

When you integrate a BI tool with a CDP, you can use the data to enrich customer profiles, inform customer segmentation, and create effective customer engagement campaigns.

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Frequently asked questions

How is customer journey analytics different from customer journey mapping.

Customer journey analytics provides the statistical foundation for customer journey mapping. You need the data and insights from analytics to create a detailed and accurate journey map.

What are the benefits of customer journey analytics?

Customer journey analytics software lets you measure engagement across channels, optimize omnichannel customer experiences, and improve customer retention.

What are some tools or software businesses can use for customer journey analytics?

Customer data platforms, customer engagement platforms, and behavioral analytics tools are useful for performing customer journey analytics.

How can Twilio Segment help businesses conduct customer journey analytics?

Twilio Segment unifies customer data across multiple platforms and channels, while also empowering marketers to trigger personalized campaigns based on specific user or traits.

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A complete guide to customer journey analytics.

13 min read Customer journey analytics can help you to nail down exactly why your customers behave the way they do and tie your customer experience efforts to financial outcomes. Learn how to use customer journey analytics for improved CX with our ultimate guide.

What is customer journey analytics?

Customer Journey Analytics is the process of understanding the impact of every interaction a customer has with your business.

Often, customer journey analytics starts with a customer journey map , which is presented as a graph, flow chart, or other visual that documents each stage of the relationship between a customer and a brand.

However, instead of just charting their customer journey on a map, customer journey analytics takes a further step to analyze what effect each interaction has on your customers’ decisions.

Further information is overlaid to help analyze how each interaction drives customers toward the end goal.

Customer journey analytics can include analysis of:

• Customer needs
• Emotional highs and lows
• Key metrics per step in the journey
• Customer satisfaction scores , customer effort scores , and other survey results

Customer journey analytics can help you to direct your customers’ attention and resolve any pain points that stop them from taking desired actions. It helps you to augment your customer experience and develop a customer journey that not only gets customers to where you want them to go, but helps them connect to the journey itself.

Free course: Customer journey management & improvement

Customer journey analytics vs. customer journey mapping

Many brands have a broad sense of their customer journey but haven’t optimized it by creating a comprehensive customer journey map or analyzing what affects their customers’ experience.

Customer journey analytics and customer journey mapping are complementary but different processes. Here are the main ways in which they are distinct, and how they work together.

What is customer journey mapping?

Customer journey mapping is the process of laying out the end-to-end journey in a clear way. Creating a map of every touchpoint your customer will experience means you can see what steps your customers take to reach the end goal of a purchase, signup, or other action.

Often, journey maps are documented at the process level. For example, an insurance provider would map the claims process, and a bank would document the new account process.

Some common components of customer journey maps include:

• The process being evaluated
• The stages of the journey
• Critical customer interactions and touchpoints
• Representative customer quotes
• Key customer expectations
• Metrics like satisfaction score, mention volume, NPS
• Trends in topics related to this part of the journey

Our ultimate guide to customer journey mapping can help you to draft your first customer journey map or optimize one you have already.

How do you use customer journey analytics with customer journey mapping?

As we’ve already explained, customer journey analytics is the process of gathering as much information as you can from every part of the journey and analyzing the journey for pain points and successes.

Understanding which parts of the journey function as planned and which obstacles are in the way of your customers’ progress means you can take action to ensure they complete their journey as you intend.

Benefits of customer journey analytics

There are several benefits to completing customer journey analytics. From better understanding your customers’ behavior to a better ROI for your customer experience , customer journey analytics gives you better insights and a more informed strategy for improvement.

Your brand becomes more customer-centric

Understanding the customer journey allows your company to be more customer-centric . It allows you to closely evaluate the activities, expectations, thoughts, and feelings of your customers . You learn what they like and dislike, how to move them through your buying cycle, and how to satisfy and retain them . When journey mapping is complemented with customer journey analytics it helps you understand the priority for your customer experience initiatives.

Your business becomes more unified

In addition, with the right focus, customer journey mapping and customer journey analytics break down internal silos. They empower you to streamline services across departments. Not only that, but they help to align everyone by providing a common understanding of the customer experience. Employees get greater visibility into what happens upstream and downstream of their interactions with customers, letting everybody provide a more consistent, high-quality experience.

You can find track issues as they happen

With a sophisticated customer journey analytics platform, you can pinpoint issues in real-time. You can test new approaches and see their influence on your customer experience and bottom line with analytics that update as quickly as you need them.

You see direct and indirect feedback in one place

Explicit feedback – for example, the information you gather through surveys – is easier to pinpoint to specific interactions customers have with your brand. The customer has an experience and directly after, you request input.

Implicit feedback is more complex to understand. This type of data might include operational data such as sales numbers, or it might cover social mentions, what your customers say on the phone to your care center, third-party reviews, and more.

Understanding how your audience thinks, feels, and acts in response to customer interactions without directly asking them might seem impossible, but with tools such as conversation analytics , you’re able to link your customer journey to this type of customer data.

An example of using customer journey analytics

Customer journey analytics can be used to understand the impact of sub-journeys limited to single processes – such as opening a new account – or the entire digital customer journey .

Below is an example of how you can use customer journey analytics to chart the success of each journey.

Resolving a customer satisfaction issue for a specific sub-journey

Let’s take a printer business that provides hardware to its customers. The brand has realized that the repair sub-journey is currently leading to low Net Promoter Scores (NPS) and a higher cost to serve per customer.

The journey

First, the brand needs to chart the customer journey. It looks like the below:

• A customer has an issue with their printing device
• They call the customer care center to schedule a repair
• The service agents arrive at their place of residence
• The repair is made

However, there are other ways this journey might unfold. For example:

• The service agents arrive at their place of residence but the customer is not present
• The repair cannot occur, so the customer has to call again to reschedule the repair
• The repair is made at a later date when the customer is present

The analysis

Overlaying the NPS scores on this latter journey, the company realizes that the NPS score drops when the customer has to reschedule the repair. Asking the customer to go through the same process once again to rebook their appointment is causing customers to feel less satisfied with their experience.

Using natural language processing (NLU), the team can also see that there is a more negative sentiment expressed in the open text question they have added to the NPS survey. With the additional calls to the care center, the cost to serve each customer also increases.

The resulting action  

The brand decides it’s best to provide other means to customers to book their appointments at a time to suit them. Offering customers a self-service booking system that they can access via their mobile on an app or through the website gives the customers more control over when their appointment occurs. Adding a facility to reschedule any booked appointments for a more convenient time and accentuating this with push or text notifications when the repair team is on their way can help to see if this reduces the instances of missed repairs and reduces the impact on the customer care center .

With customer journey analytics in place, the brand team can see if this improves NPS scores at the same points in the customer journey, and measure in financial terms the impact of actions taken for improved customer experience .

How to use customer journey analytics

Customer journey analytics provides the insight you need to successfully manage your customer’s journey. From lowering customer churn to helping you predict customer behavior, putting a customer journey analytics solution in place will help you to leverage your customer behavioral data for financial success.

But how do you start using customer journey analytics? Below is the outline of the actions you’ll need to take.

1. Map your customer journeys and aggregate data

First, you need to create a customer journey and aggregate the customer data that you already have. Good customer journey analytics tools will be able to do this for you, cutting down the time your team needs to spend sourcing data from third-party locations, customer service chat logs, and survey results.

Competent customer journey analytics software will also be able to track data in real-time, allowing you to build a comprehensive map that reacts to current customer behavior . It should also be able to draw data from numerous sources, helping you to break down traditional business silos and understanding customer interactions from all business angles: sales, marketing, and more.

Learn the five competencies for customer journey mapping

2. Analyze your customer behavior and data

Once you have your customer journeys mapped out and your data collected, you can link specific interactions to particular customer behavior, survey results, social media comments , and more. You’ll need a customer journey analytics solution to be able to link all of this data together in an efficient way.

3. Take action informed by data-led insights

Customer journey analytics provides you with the ability to see cause and effect, as well as providing you with concrete steps to change specific interactions or the entire customer journey. When customers react badly to specific processes or interactions, you can test how changes in your customer journeys affect their future decisions.

Not only that, but you can coordinate your teams across your business to work on customer satisfaction with their experience, based on the data you’ve analyzed. For example, if customers are led to purchase through your marketing but aren’t happy with their purchase, they will deal with your marketing , sales, and customer care teams. Understanding what specifically caused a problem for them means you can inform each team of actions they can take to improve.

How customer journey analytics can improve your customer experience

Brands often hit a wall when trying to measure customer experience . Charting your customers’ often nebulous sentiment and which actions have an impact on customer experience can be difficult without the right tools to hand.

Understanding the return on investment for specific actions taken for customer experience is difficult for a number of reasons:

• Data is siloed or overwhelming
• Business departments work separately with a lack of oversight
• Actions aren’t based on data
• There isn’t a way to track the impact of actions on customer experience

Qualtrics Customer Journey Optimizer allows you to see the value of customer journeys with rich data analysis, provided through conversational analytics . With natural language understanding, Qualtrics is able to provide you unrivaled insights into customer emotions, sentiment, and more to paint a complete picture of friction points and their rationale. Powered by feedback from multiple areas of your business, you are able to create a plan of action with a tangible effect on your customer experience and business outcomes.

With a deeper understanding of customer behavior, your brand is able to not only understand the return on investment of your actions but develop a customer experience that delivers results. Extending your customer lifetime value , increasing customer satisfaction, and reducing customer churn becomes easier when you understand the triggers for the behavior.

Related resources

Customer Journey

How to Create a Customer Journey Map 21 min read

Customer interactions 11 min read, consumer decision journey 14 min read, customer journey orchestration 12 min read, customer journey management 14 min read, customer profiles 16 min read, customer journey stages 12 min read, request demo.

Ready to learn more about Qualtrics?

Customer Journey Analytics: The Complete Guide

How well do you know your customers? Chances are you’ve developed personas to illuminate who they are and the information they care about. But do you know the paths they take to find that information?

A comprehensive guide to customer journey analytics

Today’s digital-savvy consumers interact with multiple channels throughout their day — often combining more than one at the same time to get the answers they seek. To drive more business in an omnichannel environment, customer journey analytics help you understand the key touchpoints on your customer journeys so they find you more often and provide insights to improve their experiences once they get there.

Key takeaways

Ideally, your vision for your customer journeys and how they experience your brand online aligns with their actual journeys and experiences This guide will define customer journey analytics and provide a better understanding of how the data can help you:

Get the 30,000 ft view

Whether it’s your website or mobile app, social media, email or another channel, you need to know how your customers are engaging with your digital brand to deliver the right experiences that help them move forward but also support your business goals.

Keep your customers engaged

Consumers are more fickle than ever with user-friendly devices and vast resources to explore at the touch of a button. Avoid analysis/paralysis and get the insights you need to identify where your customers are struggling and why they may be leaving to guide user experience (UX) changes that keep them engaged.

ROI-focused guidance

Customer interests are fluid and constantly changing. Understand how user behavior ultimately impacts your business metrics to focus your efforts where it matters most to the bottom line and ensure your touchpoints are aligned with each stage of the customer journey: awareness, consideration, purchase, retention and advocacy.

What is customer journey analytics?

Digital experiences must continue to evolve in order to maintain alignment with the needs of current and prospective customers. Customer journey analytics help teams that manage these experiences better understand the impact each digital interaction has on a customer’s decision.

Customer experience (CX) and UX professionals use customer journey analytics tools to gather important customer engagement data at different touchpoints and channels of the customer journey over a period of time. The data tells a story of what customers like and where they struggle. This information enables teams to better optimize the customer journey and improve CX.

💡 Expert tip: Combining customer journey analytics with a digital experience intelligence (DXI) platform provides a deeper understanding of why customers behave the way they do. Digital teams can use this information to not only optimize the customer journey to improve the user experience but also to quantify the revenue impact as a result of poor experiences.

Definition of customer journey analytics

Customer journey analytics is the process of gathering and analyzing key data points of the customer experience across every touchpoint in the customer journey. This data illuminates customer behaviors and is used to guide decisions on where and how to improve the experience.

User journey analytics vs. customer journey analytics

At the heart of understanding the difference between user journey analytics and customer journey analytics are the types of channel(s) involved with the journey itself.

Specifically, a user journey is solely about a person’s interactions online. The goal of the online journey may be about finding a specific product at the best price or browsing or searching for information on a specific topic. User journey analytics are purely focused on the user’s experiences in the digital space.

Customer journeys are often more robust and complex as they include both online interactions but also offline engagements. As such, customer journey analytics look at every channel a customer goes through–whether they're visiting a website on their laptop, interacting with a mobile app or speaking to a customer service representative on the phone or in person at a physical location.

The role of customer journey analytics in customer journey mapping

To completely understand customer experiences, marketing and IT teams need to share and understand customer data to collectively make data-driven decisions. Helping customers move forward with their overall journey requires being able to see that journey in totality at a high level but also having the ability to dive into the weeds when needed to better understand what’s happening at each stage.

Customer journey maps are a great way to visualize all of the touchpoints customers are interacting with along their journey with a brand, service or product. Journey maps start at the very beginning and encompass all of the steps a customer goes through to complete an objective over a period of time.

For a potential customer, this could start with gaining initial awareness from advertising, social media or simply browsing the web on a related topic through their actual purchase, continued engagement with customer service, advocacy via a product review or social media and a repeat purchase.

Omnichannel customer journeys often include multiple opportunities to convert a potential customer by completing a desired task before completing their ultimate objective of making a purchase. These conversions could be signing up to receive free content, creating a new account or asking to speak with a company representative to answer their questions.

👉🏻 Check out the guide Digital Customer Journey Mapping in Today's World .

The importance of analyzing customer data

The ability to create more meaningful customer experiences that convert hinges on leveraging the data behind every interaction. Customer journey analytics measure key metrics and capture valuable behavioral data to provide a better understanding of where customers are spending their time and how they’re feeling at each stage of the journey.

In addition to illuminating why a particular step is converting at a high rate that can be applied to other areas, customer journey analytics help identify potential pain points and frustrations that hinder conversions or, worse, lead to abandonment. This information helps digital teams gauge where they’re winning and losing and determine where improvements need to be made to achieve desired business outcomes.

Benefits of customer journey analytics

Customer conversations are still happening at the same frequency, but the digital space facilitates these interactions in an entirely new and often disparate way. Customers want experiences that enable a continuous conversation even though they now happen through a series of separate engagements through more channels than ever before.

Leveraging customer journey analytics can help businesses gain valuable insights into what is important to their customers so they can evolve those experiences to better meet customer expectations. Companies that embrace a customer-first mentality are succeeding because they are invested in making the most of every interaction to continually move their customers forward in their journeys.

Maximizing CX investments

Today’s customers have little patience and high expectations—especially when they’re engaging digitally with a brand. If they feel like they’re starting over after previously engaging with a company online, they will likely move on to a competitor.

Access to loads of valuable data and additional context collected from customer journey analytics drives the ability to assess individual customer needs in real-time. For those entrusted with optimizing the experiences along the customer journey , data-driven insights can lead to user experience changes that improve customer engagement. More personalized interactions fueled by customer journey analytics can ultimately lead to higher conversion rates with new customers and reduce customer churn.

With the ability to predict customer behavior from previous actions, high-risk customers can be offered a different experience that help address the way they feel about the brand to improve retention. Variations on this approach combined with audience segmentation can result in more loyal customers and even generate additional purchases from existing customers.

Growing the bottom line

The days of guessing what customers want are long gone. While providing a toolset to help improve customer experiences, investment in a customer-first approach with customer journey analytics can drive powerful change throughout a company culture that results in new revenue-generating opportunities.

In addition to helping optimize digital experiences, product development leaders can gain valuable insights that can help guide and prioritize their efforts. Identifying valuable improvements to existing products that aren’t meeting sales targets will improve customer satisfaction. Customer journey analytics also inform the opportunity to develop potential new product offerings and fill gaps in the product portfolio.

How customer journey analytics work

The way modern, digitally-driven customers arrive at a purchase decision is anything but prescriptive. There is no linear path from awareness to research to purchase to advocacy. Customers might require 7-8 interactions before becoming a customer, or they may transition from initial awareness to a purchase within a few seconds. In some cases, advocacy may happen as part of initial research or social media engagement without any purchase intent at all.

Customers are expecting their experiences to be informed and personalized to their specific needs regardless of where they are on their journeys. And they certainly don’t want this type of content to only be delivered on a single channel or entice them down a path to a product they’ve already purchased or isn’t currently available.

Customer journey analytics combine a variety of data sources and contextualized visualizations to help create the right content at the right time to help businesses maintain relevant, easy experiences that build relationships and empower customers. Gathering data on customer demographics, psychographics and how they behave provides a deeper context for a better understanding of the customer journey.

This added context from the various types of data is a critical part of building out a customer journey map and guiding refinements to each stage of that journey. The customer journey map provides the foundation for this ongoing analysis process.

👉🏻 Learn how to create effective customer journey maps in this complete guide .

Customer journey analytics tools and software

There are many digital and AI-powered tools to help maximize the customer journey analytics process and optimize areas of the digital experience to better connect with your customers and move them forward on their journey. Below we take a look at a few of the most common types.

Customer data platforms (CDPs)

CDPs are becoming an increasingly popular part of the marketing communications toolset. With the ability to centralize data collection from multiple sources, CDPs help marketers refine customer profiles along with creating and managing segments to ultimately drive engagement across a variety of channels. While they are easier for non-technical people to use, finding the right solution can be challenging, given the number of options and volatility in the market. Additionally, integrating a CDPs into a company’s marcom toolset can be costly and time-consuming.

Customer engagement platforms (CEPs)

CEPs take the concept of customer relationship management (CRM) to the next level by consolidating customer data and engagement functionality typically provided by multiple systems. Marketers and other teams within the company, like sales, service and support, are using the same customer data and working within the same system to perform their individual tasks, which can help provide more personalized customer experiences.

Behavioral analytics (BA) tools

Behavioral analytics tools collect and analyze data from actions performed by users on a website or app. This data provides a foundation for businesses to understand how users interact with the different sections and touchpoints of their digital experiences. The data can inform decisions on user experience changes while providing a guidepost to show if the changes are working to improve the desired outcomes.

BA tools include:

Traditional analytics like Google Analytics

Session replay tools that capture user interactions, like Glassbox and Crazy Egg

Heatmap tools that show where users are interacting the most, like Lucky Orange

A/B testing tools that allow testing of variations to a website or app page, like AB Tasty and Adobe Target

Voice of customer (VoC) and survey tools , like Medallia and Survey Monkey

👉🏻 Want to learn more about BA tools? Check out The Complete Guide to Behavioral Analytics .

Business intelligence (BI) tools

BI tools help guide more informed decisions by providing accurate data across a variety of business systems to better understand what’s happening throughout the entire organization. In addition to mining the data to illuminate valuable insights, BI tools also provide visualization capabilities to transform the data and insights into graphs and charts that can be incorporated into dashboards that non-technical business leaders can use to monitor and make changes to the business.

🔥 Hot tip: A digital experience intelligence (DXI) solution combines all these tools into one platform so you can access advanced insights across the company in one place. These advanced insights give you the complete picture of the digital customer experience, not just bits and pieces.

Types of data used in customer journey analytics

A variety of data types are needed to help businesses ensure they are providing an exceptional customer experience at every touchpoint of the customer journey.

Basic data analytics can help set the stage by providing quantitative measurements of customer actions taken when interacting with a touchpoint—how long they stay, what pages are generating the most traffic, if they click a desired call to action, etc. Qualitative data helps fill in the details around these actions by providing the human context that helps illuminate what’s driving their pain points and successes. Combining these disparate types of data provides insights to optimize the touchpoints in the website user experience.

Quantitative data

Quantitative data is a set of touchpoint and engagement performance metrics for a digital asset (website, mobile app, etc.) that reflect how users interact with the experience. This numerical data is collected indirectly and pertains to different types of user actions. The most common quantitative data metrics involved with customer journey analytics include:

Session activity

The amount of time a user spends along with specific pages on your website or mobile app. Tracking this metric provides the ability to spot usage trends or anomalies. Significant drops in a short period might be related to a bug or other development issues, while a steady decline could identify an engagement problem related to the content or user experience.

Bounce rate

This is an indicator of when users leave your website or mobile app after viewing just a single page. The fact that users may be finding the information they were seeking when landing on the page—along with the page type and its content—should be considered when evaluating the bounce rate.

This reflects the percentage of all emails in a particular campaign that were opened. This information is especially helpful when evaluating email subject lines and/or preheader text as part of an A/B testing initiative .

Conversion rate

This is the percentage of users who perform a desired action, such as clicking a CTA button.

Qualitative data

Quantitative data is a great way to track key customer engagement touchpoints and identify where to make necessary changes to address basic issues with a digital experience. This data can also provide a solid foundation to start implementing more strategic changes to specific parts of the customer journey, such as improving information in a shopping cart or making additional suggestions on a checkout page.

While it may be harder and take longer to acquire, qualitative data provides the valuable “color” surrounding the quantitative numerical data and illuminates a more complete picture of the customer journey. Qualitative data also helps improve the customer experience by understanding the perceptions, feelings, thoughts and preferences of your users. Qualitative data collection methods include one-on-one interviews, focus groups, surveys, observation notes and more.

👉🏻 Find out how teams can use qualitative data to improve the digital customer experience (CX) .

The importance of having the right data for customer journey analytics

With today’s omnichannel customer journeys, the results of efforts to connect and build better relationships with customers along their journey will only be as good as the data that’s driving CX changes. It’s mission-critical to not only be able to see what actions customers are taking but also to understand the why behind the behavior.

Customers want more personalized experiences, and they are more likely to purchase from businesses that meet that expectation. Efficient, effective optimization of a customer journey can only occur with the right mix of data focused on key touchpoints and interactions while also providing the valuable human-centered context to understand what is driving the choices being made in those moments. The cost of making the wrong decisions couldn’t be higher as customers have plenty of options and likely won’t return after deciding to move on.

The power of custom journey data with digital experience intelligence

Customer journey data plays an important foundational role in identifying where to make changes that improve digital experiences—especially since today’s customer journey most likely starts and ends in the digital space. Yet, customer journey analytics tools provide a limited view of customer behavior. To create and refine digital experiences that ultimately lead to loyal customers, teams need to go beyond the basic information provided by typical quantifiable data.

Digital experience intelligence platforms are designed to take that data and maximize its value to help businesses build comprehensive and personalized experiences. That value is provided in the form of powerful insights that can lead to true one-to-one experiences with the right content that completes an end-to-end customer journey—from websites to apps to emails to SMS mobile messages and other messaging in social media and even digital advertising.

How to implement customer journey analytics in 4 steps

To provide the most value, there are a few key steps that align the paths of an ideal vision for a customer journey with what customers are experiencing. Taken in order, each step supports the next, along with helpful references that help provide focus during team discussions and prioritization to guide decision-making.

1. Identify goals

Successful journeys have an endpoint that is identified early on and set as a “north star” for initial planning efforts and to be referenced during critical moments of the customer journey. In addition to setting goals for particular interactions or performance metrics, every experience and related touchpoint should be aligned with supporting the goals of the business to ensure they are positively impacting the bottom line.

2. Collect and analyze data

With business and experience goals in place, establish a time parameter to collect the data. In some cases, a minimum amount of time is needed to get a sense for what is happening on a macro level. Seasonal timing, holidays and other events can create anomalies that can mislead teams if data is collected too quickly or without important context that could be influencing customer behavior. Additionally, qualitative data may take longer to secure—especially to meet a minimum threshold of customers surveyed or interviewed so the data is meaningful.

Once the data is collected, the next step is to analyze it. We’ve identified a few areas to be mindful of to ensure seamless digital experiences and anticipate customer needs to help along each step of the journey:

Points of friction

Look out for potential friction points in your digital experiences. This could be gaps in content that may not be providing what is needed to move on to the next step or a broken form. Friction points can also be technical issues or bugs, which could slow page load times down or app crashes.

Poor transitions

Successful omnichannel experiences rely on delivering the right content to customers at the right time. As they transition between a website, mobile app, email or text message, there are many potential issues that could lead to friction. If customers are challenged to perform a desired action, or they have to start over because their data gets lost, chances are they’re getting frustrated from the overall experience and are likely to abandon the website or app and never return.

Stage duration excess

Be especially critical of the time it should take a customer to complete specific tasks at each stage of the journey. Identify areas along the journey to minimize the time and effort involved—especially if the path to purchase is longer.

Replicate successes

Each interaction provides an opportunity to build (or lose) customer trust and happiness. While a lot of time and effort is spent identifying pain points and issues with the customer experience, things that are doing well and working as intended should be noted. Once identified, those learnings should be applied to other areas to optimize the customer experience for success.

3. Capture actionable insights

Along with providing the power of context, turning customer journey analytics into actionable insights enhances the ability to quickly assess customer needs and even anticipate them to make every experience more relevant and personal.

4. Implement changes based on insights surfaced

The ability to combine customer journey analytics with digital experience intelligence lets teams gain an understanding of why customers behave the way they do so you can fix any issues or optimize the journey to improve the digital user experience.

Whether it’s refined recommendations based on previous searches, a specific program that helps customers better understand a new product or a personalized email campaign and landing pages, quickly implementing these experiences helps connect with customers and let them know you value them. Combined with digital experience intelligence data, customer journey analytics can also quantify the revenue impact of the cost of poor experiences.

🤔 Did you know? There are limitations to standalone customer journey analytics tools. Customer journey analytics tools provide a limited view of customer behavior. The ability to combine customer journey analytics with digital experience intelligence lets teams gain an understanding of why customers behave the way they do so you can implement changes to fix any issues or optimize the journey to improve the digital user experience. Combined with digital experience intelligence data, customer journey analytics can also quantify the revenue impact of the cost of poor experiences. Armed with these insights, CX teams can focus on the areas that provide the most impact to optimize that experience and add the most value to the organization.

Check out these customer journey analytics FAQs if you’re short on time or are looking for a quick cheat sheet.

Customer journey analytics is the process of gathering and analyzing key CX data points across every touchpoint in the customer journey. This helps businesses better understand what their customers want and need so they can provide optimized experiences and help them move forward in their purchase journey.

Through a variety of quantitative and qualitative data, customer journey analytics can help illuminate customer behaviors and guide the decisions of marketing, customer experience (CX) and IT teams on where and how to improve customer experiences. This can involve providing the right content at a certain stage of the journey and reducing pain points that are causing friction and abandonment.

Multiple digital tools and techniques help businesses ensure they are providing an exceptional customer experience at every touchpoint of the customer journey:

Business intelligence (BI)

Teams can measure the effectiveness of customer journey analytics by establishing initial CX goals that align with industry best practices, along with tools that show the behavior of users before and after changes are made. In addition to setting goals for particular interactions or performance metrics, every experience and related touchpoint should be aligned with supporting the business's goals to demonstrate if they are ultimately impacting the bottom line.

Customer journeys involve multiple channels that may or may not be in the digital space. As a result, there are multiple functions within an organization—along with separate systems and data silos connected to those systems—that are involved in providing the end-to-end customer experience.

Customer expectations have also never been higher, as they expect businesses to provide connected experiences that anticipate who they are and where they are on their journey. In addition to the CDPs and CEPs mentioned above that can help aggregate data into one centralized location, businesses can utilize digital experience intelligence and a comprehensive set of digital experience tools to provide the data and actionable insights to help their teams optimize the various parts of the customer journey.

What is Customer Experience? A Complete Guide

Customer Journey Maps: The Complete Guide

Blog / Journey Measurement

9 Customer Journey Analytics Examples (+3 Tools for Better CX)

• October 2, 2023

Table of Contents

Key takeaways.

• You can use customer analytics to track the impact of paid ads, understand how customers interact with your brand at every stage of their journey, and optimize the user journey overall.
• Customer analytics can also reduce churn while increasing marketing ROI by helping you nurture loyal customers.
• Customer feedback is vital to identify and optimize key touchpoints throughout the customer journey.
• You can use customer journey analytics software like Funnelytics to get the most from your analysis.
• Customer journey analytics examples and use cases

Best practices for analyzing your customer journey

• Funnelytics 

HubSpot Marketing Hub

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9 customer journey analytics examples and use cases

1. track the impact of paid ad campaigns, the results of analyzing ad data.

• You can employ different strategies to make your landing page more effective. Offer whitepapers, ebooks, tutorials, or other valuable information, or perhaps take another look at the design or usability of the page. This can reduce your bounce rate and support your campaign goals.
• You can use topic targeting to make sure your display ad appears on relevant websites. This helps ensure the right audience sees your ad where it’s more likely to catch their interest.

2. Understand how customers interact with your brand

Results of simplifying analytics and reporting.

• They increased their average order value by 46% by gaining more clarity into their customer journeys and understanding where they were and weren’t making money.
• Everyone in their company—from sales to business divisions—switched to the same customer analytics tool to stay on the same page.

3. Identify and segment your target audience

Results of segmenting your audience.

• You can send targeted communication that helps keep your customers engaged.
• You can craft a solid lead magnet funnel to attract your ideal customers and convert them down the line.
• You can craft highly personalized product recommendations and find opportunities to convert hot leads into clients.

4. Focus on the most profitable customers

Results of focusing on profitable customers.

• You find opportunities to upsell or cross-sell to those customers, making more revenue.
• It helps you retain these customers even longer by offering them top-class customer service.

5. Identify opportunities for cross-selling and upselling

Results of cross-selling and upselling.

• You generate additional channels of revenue with existing customers.
• With insights into what your customers want and need, you build stronger and deeper customer relationships.
• When customers see long-term benefits in associating with you, they tend to stick with you for the long haul. This increases customer lifetime value, ie the total net profit you can generate from a customer throughout their interaction with you.

6. Analyze the cause of churn and reduce it

The results of consolidating analytics data.

• They could pinpoint where people were leaving their websites. They targeted these spots for improvement.
• By optimizing their website, they made their customer journey smoother. This resulted in more sales.
• They could see how effective their advertisements were and figure out ways to improve their ad strategy for a better ROI.

7. Build effective loyalty programs

• Identify what you want to achieve through your loyalty program—like increasing retention, spending, or referrals. Based on your goals, define KPIs such as targetted retention rates, churn rates, or lifetime value, and track your progress.
• Collect data from multiple sources, including your loyalty program platform, point of sales (PoS) system, email marketing platform, social media, customer feedback surveys, and other relevant sources. Combine and organize the data.
• Then, analyze and segment your data to understand your program’s patterns, trends, and anomalies.

Results of optimizing your loyalty program

• You achieve better conversion rates.
• You can experiment with different elements of your loyalty program—rewards, redemption options, and communication channels—and dig deep into your customer journey.

8. Gather channel-specific insights

Results of analyzing channel-specific insights.

• You’re able to identify and fix any bugs that might hamper a channel’s performance.
• You can create a more personalized and satisfying experience for your customers by optimizing these platforms.

9. Optimize customer onboarding

• Rate of new downloads and installations
• Average daily or weekly logins
• The adoption rate of features available for every user

Results of optimizing customer onboarding

• Customers will use their accounts more often, which leads to higher retention and profitability.
• Once you create a 360-degree customer view during the onboarding process, it’s easier to identify high-risk activities.

1. Collect customer feedback at different touchpoints

• When they visit your website
• Receive an order
• Contact customer support

2. Identify unnecessary or redundant touchpoints

3. evaluate the total time it takes for a customer to take the journey, 4. consolidate data and eliminate silos, 3 tools to improve your customer experience and journey analysis, funnelytics.

Top features:

• Filtering and segmentation of customers
• Easy integration with Zapier
• Traffic Explorer to trace the origin of a sale
• Identify trends and bottlenecks using traffic light indicators

• Built-in revenue impact metrics to identify poor customer experiences and quantify their costs
• Augmented journey map with over 25 dimensions to filter your customer journey
• One-click integrations with third-party tools

• You get the Customer Relationship Management (CRM) tool free of cost
• Easy integration with third-party tools to make your workflow more powerful and effective
• Automated workflow for faster data analysis and decision-making

Analyze your customer journey data with Funnelytics

Positive customer experience is the key to building a successful business. By gaining insights from customer journey analytics, you can track the most important metrics and make data-driven decisions. Funnelytics helps you visualize these metrics in real time in a single canvas, and pinpoint the areas needing improvement. Plus, you can centralize all your analytics data in Funnelytics, and ditch those manual and time-consuming analytics tools. Sign up for a free trial today

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The Complete Guide to Customer Journey Analytics

What is customer journey analytics all about, how does customer journey analytics affect customer journey mapping, what are the benefits of customer journey analytics, how to analyze customer journeys, key metrics in customer journey analytics, fullsession is the customer journey analytics solution you need, fullsession pricing plans, start analyzing your customer journey maps today, faqs about customer journey analytics.

If you want to give your audience the experience they want, you have to understand how they behave.

Customer journey analytics can show you how your customers behave at various touchpoints and why they behave that way. Ultimately, the goal is to get a better grasp of how each interaction affects your customers' decisions.

Let's take a deeper look into customer journey analytics, how it works, and how you can analyze data for yourself.

Customer journey analytics is the process of tracking and analyzing the interactions a customer has with your business across various touchpoints⎯from the moment they first hear about your brand to when they make a purchase and beyond.

Think of it as piecing together a giant puzzle. Each piece represents a different interaction or "touchpoint" a customer has with your brand. By gathering data from these touchpoints, you can build a complete picture of the customer’s experience and understand the story behind those interactions.

For example, you run an online clothing store and notice many customers abandon their carts at the shipping stage. By using customer journey analytics, you discover that the shipping options are confusing. And voila, simplifying this process reduces cart abandonment and increases sales.

However, we wish that it's as simple as that. Let's dive in deeper.

Customer journey mapping and customer journey analytics go hand in hand. But before we dive into how they work together, let's review their key differences.

Customer journey mapping creates a visual representation of the customer’s experience with your brand. It outlines the steps a customer takes from the initial contact through to the final purchase and beyond, highlighting key touchpoints and emotions experienced along the way.

Meanwhile, customer journey analytics collects and analyzes data from various touchpoints to understand and improve the customer experience. It involves tracking customer interactions, behaviors, and preferences across multiple channels and using this data to gain actionable insights.

Customer journey analytics and journey mapping complement each other perfectly. Analytics provides the hard data that shows you exactly what’s happening at each touchpoint in the entire customer journey. This data is then used to create accurate, detailed journey maps.

These maps, in turn, offer a visual representation of the customer experience so it's easier to see the overall flow and identify areas for improvement. By combining the two, you can pinpoint specific pain points, optimize interactions, personalize experiences, and measure the impact of any changes you make.

Customer journey analytics offers a treasure trove of benefits that can transform how you do business and satisfy your customers. Here’s how:

Improve Your Customer Experience

With customer journey analytics, you pinpoint exactly where your customers face hurdles. Whether it's a confusing checkout process or a lack of information, you address these pain points head-on.

The result? A smoother, more enjoyable experience that keeps customers coming back for more.

Increase Your Customer Retention Rates

Happy customers are loyal customers. By continuously refining the customer journey based on analytics, you significantly increase satisfaction and, therefore, retention.

When customers feel valued and understood, they’re far more likely to stick around and become repeat buyers (and maybe even brand ambassadors via positive word-of-mouth).

Improve Your ROI on Customer Experience Initiatives

Knowing which customer touchpoints drive conversions allows you to focus your marketing efforts where they count the most. Instead of spreading your budget thin across various channels, you invest in the ones that yield the best results for a higher return on investment.

Make Data-Driven Decisions

Say goodbye to guesswork. Customer journey analytics provides hard data to back up your decisions. Whether you’re launching a new feature, revamping your website, or tweaking your marketing strategy, having concrete insights helps make sure you’re making the right moves.

For example, a customer journey analytics platform can help you predict customer behavior and make business decisions based on what they expect from your brand.

Personalize Your Customer Interactions

Analytics allows you to segment your customers based on their behaviors and preferences. This means you tailor your communications and offers to meet individual needs, which helps create a personalized experience that resonates with each customer's journey. 

Also, personalization leads to higher satisfaction and stronger loyalty.

Upgrade Your Product and Service Development

Understanding how customers interact with your products provides invaluable feedback. You can use customer journey analytics to reveal what features they love, what confuses them, and what they’re asking for.

This information guides your development efforts to help you create offerings that truly meet customer needs.

Reduce Customer Churn

Analytics helps you understand why customers leave and what you can do to retain them. By addressing the root causes of dissatisfaction, you take proactive steps to reduce churn. In turn, this can help you keep your customer base stable and growing.

Increase Your Efficiency

Identifying areas where the customer journey needs improvement can help you eliminate inefficiencies. This leads to faster service, reduced costs, and a more enjoyable experience for your customers.

Analyzing customer journeys might seem daunting, but breaking it down into manageable steps makes the process straightforward and effective. We've created a comprehensive guide to help you get started.

1. Collect Customer Data From All Touchpoints

The first step is to gather data from every customer interaction with your brand. This includes:

• Website analytics: Track page visits, click paths, time spent on pages, and bounce rates.
• Social media engagement: Track metrics such as likes, shares, comments, and click-through rates on platforms like Facebook, Instagram, and Twitter.
• Customer support interactions: Record inquiries, complaint resolution times, and customer satisfaction scores from support channels.
• Transactional data: Analyze purchase history, cart abandonment rates, and average transaction values.
• Surveys and feedback: Collect direct feedback from customers through surveys and review platforms.

2. Create Customer Journey Maps

Next, create a visual representation of the customer journey by outlining each step a customer takes from awareness to post-purchase.

Include key touchpoints such as how customers first hear about your brand (awareness), how they research and evaluate your products (consideration), the process they go through to buy your product (purchase), and how you support and engage customers after their purchase (post-purchase). This is also known as your conversion funnel .

3. Identify Key Moments and Pain Points

Once you have your customer journey map, identify critical moments that impact customer decisions. Look for drop-off points where customers abandon their journey, friction points where they encounter difficulties or frustrations, and moments of delight where they have positive experiences that can be amplified.

4. Analyze Customer Behavior

Leveraging customer journey analytics tools helps you gain a deeper understanding of customer or user behavior at each touchpoint.

Start with segmentation to group customers based on their behaviors and characteristics. This helps you see different journey patterns. Next, use path analysis to look at the sequences of steps customers take and identify common paths and where they diverge.

Finally, apply conversion analysis to see how well different touchpoints turn customers into buyers. These methods give you a clear picture of customer behavior to help you make smart decisions to improve their journey.

5. Derive Insights and Take Action

The last step is to translate your findings into actionable insights. For example, you can optimize touchpoints where customers face friction or drop off and personalize experiences by using data to tailor interactions and offer to individual customer preferences.

Implement changes and monitor their impact so you can keep refining the customer journey based on how customers behave.

Tracking metrics in customer journey analytics offers clear insights into how your customers interact with your brand. More specifically, it can help you identify pain points and uncover opportunities for improvement.

Here are some of the most important metrics you should keep an eye on during the customer journey analytics process:

Customer Satisfaction (CSAT)

Customer satisfaction gauges how happy customers are with their experiences at various touchpoints. Typically gathered through surveys where customers rate their satisfaction on a scale, high CSAT scores indicate that your customers are pleased with their interactions. Low scores highlight areas that need immediate attention.

Net Promoter Score (NPS)

Net promoter score reveals how likely customers are to recommend your brand to others. By asking customers to rate, on a scale from 0 to 10, their likelihood of recommending your business, you can classify them as promoters, passives, or detractors.

A high NPS means you have enthusiastic promoters who drive positive word-of-mouth and improve your brand reputation.

Customer Effort Score (CES)

Customer effort score measures how easy it is for customers to complete a task, such as making a purchase or resolving an issue. This score is usually obtained by asking customers to agree or disagree with statements like "The company made it easy for me to handle my issue."

Lower effort scores suggest a smoother, more user-friendly experience, which is critical for maintaining customer satisfaction and loyalty.

Conversion Rate

The conversion rate measures the percentage of customers who complete a desired action, such as making a purchase, signing up for a newsletter, or filling out a form.

Monitoring conversion rates at different touchpoints helps you see what’s working well and what needs improvement. In turn, this will allow you to optimize those touchpoints for better business outcomes.

The churn rate measures the rate at which customers stop doing business with you over a specific period. A high churn rate can indicate dissatisfaction with your product or service.

By analyzing churn rates, you can uncover patterns and address the issues causing customers to leave and ultimately help you retain more customers.

Customer Lifetime Value (CLV)

Customer lifetime value (CLV) calculates the total revenue a business anticipates earning from a single customer account over the duration of their relationship.

Understanding CLV helps you allocate resources more effectively and focus on retaining high-value customers who contribute significantly to your bottom line.

Average Transaction Value (ATV)

Average transaction value measures the average amount spent by customers per transaction. This metric provides insight into spending patterns and helps you pinpoint opportunities to increase revenue through strategies like upselling and cross-selling.

First Contact Resolution (FCR)

First contact resolution measures the percentage of customer issues resolved in a single interaction. A high FCR indicates efficient and effective customer service, which leads to higher satisfaction and reduced follow-up interactions.

Ever wish you could collect, analyze, and interpret customer journey data all in one place?

FullSession is the exact solution you're looking for. As a high-powered web analytics tool, FullSession can help you capture customer behavior without all the grunt work. Here are some of the advanced analytics tools you can gain access to:

• Heatmaps : Visualize user interactions on your website, highlighting hot spots where users click, scroll, or hover the most.
• Session recordings: Capture real-time user interactions on your site, allowing you to watch how users navigate, click, and scroll.
• Market filtering tools : Segment and analyze customer data based on demographics, behavior, and preferences.
• Customer feedback tools : Gain insights into how to improve customer satisfaction and areas needing improvement to enhance overall experience.

Understanding customer experiences shouldn't be a long-winded process. Sign up for FullSession today !

The FullSession platform offers a 14-day free trial. It provides two paid plans—Basic and Business. Here are more details on each plan.

• The Basic plan costs $39/month and allows you to monitor up to 5,000 monthly sessions.
• The Business plan costs $149/month and helps you to track and analyze up to 25,000 monthly sessions.
• The Enterprise plan starts from 100,000 monthly sessions and has custom pricing.

If you need more information, you can get a demo.

It takes less than 5 minutes to set up your customer journey analytics with FullSession , and it's completely free!

How often should I analyze my customer journeys?

Aim for quarterly reviews to keep your insights fresh. But don’t be shy about diving in more often during major campaigns or when you spot significant changes in customer behavior. Quick checks can provide timely insights, letting you tweak things on the fly.

Can small businesses benefit from customer journey analytics?

Yes. Small businesses might even have the upper hand here. By understanding your customers' journeys, you can tailor your services and communication to hit all the right notes. Even with limited resources, simple tools and basic analytics can offer game-changing insights.

How can I improve my customer journey based on analytics?

It’s all about turning insights into action. If you see customers dropping off at a certain point, dig into why that might be happening. Maybe your checkout process is too complicated, or your website’s navigation is confusing. Use the data to streamline these areas, make the experience smoother, and watch your customer satisfaction soar.

Are there any common pitfalls to avoid with customer journey analytics?

Absolutely. One major pitfall is drowning in data without a clear strategy. Focus on the metrics that matter most to your business goals. Another is not acting on the insights you gain. Data is only powerful if you use it to make improvements. Lastly, remember to respect customer privacy and use data ethically.

CX Circle is coming to NYC on September 10 → Register for your spot at the #1 DX event

Intuitive visualizations of your customers journey

See how users progress through your site, page by page, from entry to exit. Discover your biggest opportunities and frustrations within minutes, including looping behaviors and where unexpected drop-offs occur.

360 degree view of the user journey

Experience the customer journey from start to finish

Our customer journey analysis capability aggregates data from 100% of your customers experience to give you a full picture of their journey on-site, including which pages they visited and in which order. 

• Enjoy clear, color-coded visualizations that every team can understand.
• Use segments to narrow your focus, such as customers who arrived from a specific channel or campaign.

Shortcut straight to Zone-Based Heatmaps or Session Replay for further insight.

Intuitive customer journey mapping

Clear visualizations help you make data driven decisions

Our signature sunburst helps you visualize at a glance your biggest opportunities for improvement, enabling you to make informed, data-driven decisions about where to invest, optimize, or rethink your digital experience. 

• Within minutes, make decisions based on visual data to improve your customer satisfaction, remove friction, and increase revenue.
• A thorough understanding of your customer journey lets you drive intelligent action at an enterprise scale.

Reverse digital journeys

User flow insights help create successful journeys

Uncover the pages visitors viewed before they arrived at particular pages and events, such as Voice of Customer feedback, 404 site errors, site abandonment, or conversion. This helps you understand and quantify specific desirable or undesirable outcomes better to build more intuitive digital journeys.

Most common use cases

• 01 Reveal unexpected journeys
• 02 Detect recurring bottlenecks
• 03 Identify the most valuable journeys
• 04 Segment journeys by source
• 05 Compare journeys side-by-side

Reveal unexpected journeys and looping behaviors

Drill down into your user journeys to reveal your biggest customer pain points and optimization opportunities. Shortcut to Session Replay to discover exactly which content or feature is causing customers to loop or drop off.

Detect recurring bottlenecks which affect conversion

Quickly identify where customers are getting stuck in their path to purchase and optimize the experience in line with customer data to improve conversion rates. 

Identify the content and journeys of your most valuable customers

Find out exactly which content journeys lead to the most conversions and revenue, then optimize your site to encourage new and returning users along the same path. 

Hone journeys by channel, campaign, or persona based on actual behaviors

Gain a thorough understanding of nuances between customer behaviors from different channels and personas to build more meaningful, relevant experiences. 

Compare customer journeys side-by-side

Quickly compare how customers from different traffic sources navigate through your website to understand intents and behaviors.

Customer Journey Analysis in action

How Leeds Building Society used Customer Journey Analysis to improve conversion rate on key product pages by 80%

Contentsquare is one of the most important tools I have to make design decisions. I base much of my design work on the data I get from Contentsquare, using it to test whether my pages are doing what I thought they would. I use Contentsquare every day and I’d be lost without it."

Rosie Dent-Spargo

UX Designer at Leeds Building Society

Want to demo Customer Journey Analysis?

Frequently asked questions

How to analyze the customer journey effectively?

Analyzing the customer journey involves mapping and understanding the various touchpoints a customer has with a brand. Utilize tools like customer journey maps and analytics platforms to identify key interactions, pain points, and opportunities for improvement, allowing businesses to enhance the overall customer experience.

What are the benefits of customer journey analysis?

Customer journey analysis give brands the power to optimize their digital properties in line with customer data. By understanding how visitors progress through a site, page by page, from entry to exit, brands can make data-driven decisions about how to improve their customer journeys to increase customer satisfaction, remove frustration, and increase revenue and retention.

What is customer journey analysis?

Customer journey analysis is the process of measuring and analyzing digital customer behavior across a series of touchpoints over time to understand how these impact business performance.

What role do customer personas play in journey analysis?

Customer personas help in understanding the diverse needs and behaviors of different customer segments. When analyzing the customer journey, businesses can use personas to tailor their strategies, ensuring a personalized and targeted approach that resonates with specific customer groups, ultimately improving overall engagement and satisfaction.

What is customer journey mapping?

Journey mapping is the process of understanding each step a customer takes on your website, from entry to exit. Journey mapping can help brands uncover unexpected looping behaviors, their most profitable customer journeys, and opportunities for optimization.

Why is data collection crucial for journey analysis?

Effective customer journey analysis relies on robust data collection. Utilize a combination of quantitative and qualitative data from sources such as surveys, analytics tools, and customer feedback to gain comprehensive insights into customer behaviors, preferences, and pain points, forming the foundation for strategic improvements.

How can businesses identify touchpoints in the customer journey?

Identifying touchpoints involves mapping out every interaction a customer has with a brand. This includes online and offline interactions, such as website visits, social media engagement, customer support interactions, and purchasing experiences. By recognizing these touchpoints, businesses can optimize each stage of the customer journey.

What is the significance of customer feedback in journey analysis?

Customer feedback is a valuable source of insights for understanding the customer journey. Collect feedback through surveys, reviews, and direct communication to uncover customers' perceptions, challenges, and expectations at different touchpoints. This information is essential for refining strategies and delivering a more customer-centric experience.

How can businesses leverage technology for journey analysis?

Utilizing technology, businesses can employ customer journey analytics tools and platforms. These tools help aggregate and analyze data from various touchpoints, providing a holistic view of the customer journey. Leveraging technology allows businesses to identify trends, patterns, and areas for improvement more efficiently.

What steps should businesses take after analyzing the customer journey?

After analyzing the customer journey, businesses should implement actionable insights to enhance the customer experience . This may involve refining marketing strategies, improving product offerings, or optimizing customer support processes. Continuous monitoring and adaptation based on journey analysis contribute to long-term customer satisfaction and loyalty.

Customer Journey Map Guide: Your Mapping is Missing One Key Element

August 26, 2024

John Abbasi

Customer journey mapping is an essential process for marketers to deliver a great experience that converts. But the modern customer journey map needs to consider what happens when visitors go off the rails of the curated path and beyond.

Redefining How to Build an Effective Customer Journey Map

Customer journey maps give organizations a chance to understand and improve the key touchpoints, channels and digital pathways their customers take to conversion. Learning how to map the customer journey is a great first step, but going beyond the basic mapping process is essential to staying agile and on top of your customers’ needs.

Consider a typical customer. No matter how well your brand is established, and no matter how you present your website content, will the customer take your ideal path to conversion every time?

Almost never.

Most often, they’ll jump right to your search bar to find exactly what they need.

The solution is to build a customer journey that fits their needs and is optimized to deliver an exceptional website experience even when visitors stray from the planned path to your search bar. We want to help you see your journey differently and give your mapping an edge over the competition.

What is a Customer Journey Map?

A customer journey is the series of steps and engagements a person experiences before, during and after becoming a customer of a service, brand or product. The customer journey encompasses the entirety of a customer’s interactions with an organization, be it through a digital ad, exposure on social media, reading a guest blog or otherwise. The variations of touchpoints are virtually endless.

A customer journey map is a complete overview of all the interactions the customer experiences in their journey. The journey map provides important insight into the efficacy of a company’s marketing touchpoints and highlights moments when a visitor moved closer or further from becoming a customer.

Why is Customer Journey Mapping so Important?

Creating a customer journey map, when done correctly, can completely change the way you interact with customers. Here are some of the most common benefits that come from mapping:

• Provides organizational insight about customer lifecycles. Mapping offers connectivity within a company/organization, bringing interdepartmental adherence as each team understands the steps of their typical customer journey – including pain points, areas for improvement and more.
• Results in higher quality leads. It’s crucial to target the right types of people with your marketing campaigns, those more likely to become leads and then customers. Because mapping shows customer behaviors, it gives marketers a way to address the needs of their customers at specific points in the funnel, producing more qualified leads.
• Reduces churn rate. The best mapping process illuminates patterns of current and previous customers, including the patterns that occur right before or at the moment of the customer switching to a different company’s product/service. This informs strategy to reduce churn.

Understanding the Customer Journey

The traditional customer journey isn’t a mystery at this point; it has well-defined key stages and necessary elements for success that marketers should consider when mapping their journey.

At this point, you’re likely familiar with the 5 stages of the journey : Awareness, Consideration, Decision, Retention and Advocacy. Rather than focusing on those well-defined stages, we want to zoom in on the tactical elements for how to build the base of your customer journey map and then discuss the layers that can elevate the experience.

Key Elements of a Customer Journey Map

Before we consider the optimal way to build a customer journey map, let’s look at some of the most important elements that make it up:

• Touchpoints. Touchpoints are interactions between customers and your organization. These can range from communications on social media, offline event interactions, website visits and more.
• Customer emotions. Though not the most concrete element, there are methods to gain insight into a customer’s emotions that arise as a result of their experiences with your brand. For example, a questionnaire could help reveal the ways customers are enjoying the overall experience.
• Pain points. Pain points drive customers toward or away from a company; your customer journey map should identify and correct them as soon as possible.
• Access considerations. Part of any good mapping will consider the types of access customers have, including things like the devices on which they access your company websites, products or services. There may be drastic differences between customers who exclusively use mobile devices, for example, compared to those who don’t.
• Customer personalities and demographics. Customer journey maps should highlight the different customer types your organization will encounter, giving a better understanding of how to connect with customers.

Creating a Customer Journey Map

The best process for creating a customer journey map includes 5 steps:

• Gathering materials
• Defining goals
• Highlighting touchpoints
• Including pain points
• Testing and iterating

1. Gather all Prerequisite Materials

Before starting the mapping process, you’ll want to gather all necessary information and materials and put them in order.

Gather customer data/analytics

First, take account of your current customer data situation: what types of data would be important, what information do you already have and what data would be helpful to collect? Make sure you have a process or tool in place to easily analyze and segment your customer data.

Identify customer personas

Part of a successful map is the ability to narrow customers down into different categories. That way, you’re able to see the paths they take and what works best for them on a more personalized level. To kick off this process, you’ll want a clear understanding of the many different customer personas and demographics in your customer base.

Take into account their specific goals in using your product or service. What are they trying to achieve or solve? 

2. Define Detailed Mapping Goals

The mapping process can be a nebulous process without clearly defined goals. Before starting one, record the most important reasons a customer journey map would be beneficial for your company.

What would a highly successful map look like and what types of decisions would it ultimately open up to you? How would the customer experience improve as a result of your new mapping?

3. Highlight Touchpoints and Channels

Your customers are each unique, so identifying the different touchpoints they encountered along their journey is crucial to map and learn from. It’s also important to know the channels and devices your customers use to connect with your brand. The more this is recorded, the better you’ll be able to improve customer experience.

4. Include Pain Points

It’s not always easy finding pain points without direct communication between customer and organization. But there are other ways to go about pinpointing patterns where customers may struggle within your systems. During your planning stage, you can ask team members to test out the proposed follow to see where they experience friction.

Once you’ve implemented your customer journey, look for places where customers experience bottlenecks or roadblocks in achieving the goals you identified above. The pain points you hypothesize will often not be what your customers experience when moving through the funnel; it’s important to stay agile and to keep up with your customers’ pain points.

5. Test and Analyze Results for Iteration

Your customer journey map isn’t finished once you complete the first iteration. If you don’t test and analyze it, you’ll leave a lot of potential improvement on the table. Be sure to periodically evaluate your customer journey maps to ensure they’re up to date with your current data and strategy in mind.

Also remember that a map usually applies to a specific customer type. There will be different maps for different customer profiles.

Map-Building Best Practices

Though you’ll have different customer journey mapping processes based on your ideal customer, there are some universal best practices to follow.

Leverage Internal Collaboration

This is something that often goes overlooked in a mapping process, as it can be easy to get caught up in your own team’s construction and application of a customer journey map.

It’s important to:

• Request and implement insights from cross-functional teams.
• Ensure extensive collaboration with customer-facing teams.

Conduct Data Analysis

A customer journey map without comprehensive data analysis is bound to fall flat. Incorporate high-quality customer data into each mapping process to ensure your map points to the right issues to correct. When including data, remember to use both qualitative and quantitative data, as well as incorporate customer feedback and analytics.

Build Mapping Visuals

A strong visual representation helps teams get a better feel for the overall structure of the map, which helps them better address any issues it uncovers.

Here are a couple examples of visuals that helped simplify complex customer journeys.

As you can see in this example journey map, a higher education institution would want to carefully map out the most important touchpoints and phases of a prospective student’s journey to attending their school.

The map is easy to follow and helps with planning thoughtful follow ups and personalized communication at each stage of the journey.

It’s great to start with a flow of the main touchpoints and moments for a customer (or student in this example).

Additional mapping layers could include:

• Pain points that prospective students may encounter
• Types of devices they may be accessing information on for each stage
• Forms of communication between the institution and the student along the way

Next we have a journey map for a typical patient who is on the road from content discovery to becoming an ongoing patient with a healthcare provider. This maps out all critical touch points and moments in the journey when the healthcare provider would need to optimize to deliver an exceptional experience.

Some of those moments may seem like smaller, expected processes but have a major impact on the patient’s experience and perception of the healthcare company.

For example, receiving and filling prescriptions in a digital format needs to be optimized for the smoothest process possible. Not only is it essential for people’s healthcare needs, but it’s also critical to optimize the digital experience so that people know they can rely on the company’s website or app. It’s a worthy touchpoint to note on a customer journey map like the example above.

Update Journey Maps Regularly

Lastly, no customer journey map will be relevant forever. Ensure your mapping is a dynamic process that adapts to changes in product, service, website and customers.

The Missing Link for Customer Journey Maps: Site Search

Customer journey mapping involves planning and curating for the ideal pathways to content and pages people need to navigate in order to convert to customers. But that’s just it; it’s an ideal scenario that you optimize for, but can’t guarantee your visitors will follow.

One of the most common ways visitors break the expected customer journey path is by searching exactly what they need to find on the organization’s website.

When a customer uses your website’s search bar, you want to be confident that they won’t exit the site out of frustration with the search results. Additionally, site search should be an asset to your customer journey, bringing them a better experience, even when they deviate from your original curated path.

Prioritizing site search means equipping your marketing team with the ability to understand common search queries, the means to identify content gaps and the agility to make changes to search outcomes to best fit your visitors’ behaviors.

From a mapping perspective, site search gives companies the power to analyze detailed data and optimize for this commonly overlooked aspect of the customer journey. Many visitors will inevitably use your search bar; it’s up to you to connect them with the content they need through a great search experience.

If you’re looking for a site search solution to improve search outcomes and performance on your site, check out our Site Search solution .

How Well Do You Know Your Customers?

If you’ve taken the time to build extensive customer journey maps, your team will get to know your customers on a deeper level and be able to personalize the journey. You’ll be able to better identify pain points and bottlenecks in the journey and fine-tune the experience.

It’s almost like a superpower for organizations, and it starts with understanding stages of the customer journey, building out a map, including analysis from site search and putting it all together to deliver an elevated experience.

By John Abbasi

Editorial and content manager, "if you’ve taken the time to build extensive customer journey maps, your team will get to know your customers on a deeper level and be able to personalize the journey.", you might also like:, what is site search a marketer’s guide to better website search, site search data unveiled: 7 key insights into your website visitors’ behavior, how to improve your website click-through rate, get the latest content first.

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A Guide to Telecom Customer Journey Analytics

Table of Contents

  Improving the customer experience (CX) is now a high priority for many telecoms. According to the  2022 State of Customer Loyalty and Churn in Telecom report , the telecom industry experiences the highest churn rates—by far. Almost half (46%) of the 2,706 survey respondents reported canceling a phone, internet, TV or cable contract within the past year due to poor customer service. More than one-fifth (21%) churned after a single negative experience. The next highest churn rate (18.7%) occurs in the online services/app industry.

Communication service providers (CSPs) understand the importance of improving the customer experience, but many find it difficult to do so. In a global survey of 121 telco CX leaders,  48%  of respondents indicated that lack of understanding or appreciation for customer journeys is one of the biggest challenges to delivering successful CX. Employees don’t have access to the tools and data they need to fully  understand customer journeys . Telco CX executives reported that they find it extremely challenging to:

• Analyze and make sense of  customer data  to gain insights about customer behaviors (42%)
• Provide employees access to real-time customer behavior data (44%)

Journey analytics offers the solution. Telecom customer journey analytics transforms customer journey data into valuable insights, guiding improvements in CX and driving business outcomes.

What Is Customer Journey Analytics?

Customer journey analytics  describes what’s happening on  the customer journey –the unique path of interactions a consumer has with your brand, products or services, from initial awareness through purchasing and using the products or services. Journey analytics tracks and measures every interaction with your brand, across every channel (e.g., website, email or SMS) and device (e.g., laptop, tablet or smartphone) the customer uses. By giving you valuable insights into how customers interact with your telecom business, journey analytics helps you understand and guide customer behavior in ways that are relevant to them. It also identifies friction points—areas of customer experience that need improvement.

Customer Journey Analytics Helps You Understand:

Customer behavior, interests, desires, needs and expectations.  This understanding makes it easier to connect with customers and personalize communications and content based on what customers need at any given moment. For example, if journey analytics detects that a customer regularly exceeds their data allowance, incurring overage charges, the  journey orchestration system  can send an offer for an upgraded data package.

Where the customer journey derails.  Journeys don’t always go as planned. When something goes awry (i.e., the customer doesn’t achieve the desired outcome), journey analytics provides a visualization layer that shows you what happened (e.g., friction points that disrupted the journey). For example, a customer may have trouble logging in to the payment portal (a friction point), resulting in late payment.

How to improve the customer journey and CX.  Journey analytics tells you which customer interactions to focus on to have the maximum impact on CX. If journey analytics reveals that many customers are calling the contact center after viewing their wireless bill, you may decide to implement a  digital bill explanation tool  to reduce bill confusion and prevent those costly live agent calls.

When you use these valuable insights to improve CX, you can:

• Improve conversion rates
• Increase customer loyalty and retention
• Boost revenue and reduce cost (e.g., by reducing contact center calls)

Customer Journey Analytics Also Allows You to:

Identify the customer journey steps that have the biggest impact on specific business goals.  For example, are customers canceling their internet service after a negative call center interaction?

Make data-driven decisions and respond more quickly.  You can refer to real-time data analytics for the information you need right now instead of relying on guesswork or waiting for reports from IT teams who may not have all the answers needed to handle an immediate problem. For example, real time customer data reveals that broadband customers in the Northeast are calling your contact center because they are rolling off their introductory rate and are surprised by the higher rate. To prevent churn, you can immediately trigger an upgrade offer for affected customers. You can also implement a digital bill explanation tool.

4 Types of Customer Analytics

Four types of customer analytics apply to customer journeys: Descriptive, diagnostic, predictive and prescriptive.

• What it Does: Answers the question: What happened?
• What Doesn’t Tell You: Why something happened
• Telcom Churn Example: Analyzes usage and customer data to determine the overall churn rate over a specific period. The current churn rate is 15% higher than last quarter.
• What it Does: Why did it happen?
• What Doesn’t Tell You: What will happen in the future
• Analyzes customer feedback, call records and service quality metrics to determine why the churn rate increased. Churn increased due to poor customer service; customers had to call several times to resolve a problem.
• What it Does: What is likely to happen?
• What Doesn’t Tell You: What action to take in the future
• Analyzes historical data on customer behavior (usage patterns, payment history and customer service interactions) to predict which customers are likely to churn. Customers who have to call more than twice to resolve a problem are more likely to churn in the next month.
• What it Does: What should we do about it?
• What Doesn’t Tell You: How to act in a particular situation (by considering the broader context)
• Recommends specific actions to reduce churn. Proactive service outage notifications eliminate the need for customers to call repeatedly for status updates.

6 Best Practices for Implementing Telecom Customer Journey Analytics

To improve CX and customer loyalty, follow these best practices as you collect and analyze telecom customer journey data.

1. Define business objectives and set specific goals .  What do you want to achieve by collecting and analyzing customer data?

• Increase cross/upsell sales
• Reduce churn
• Increase customer satisfaction/CX
• Reduce call center volume and associated costs

After you’ve spelled out your general objectives, it’s time to set specific, measurable goals that align with them, such as:

• Boost upsell conversions by 10%
• Increase contract renewal rates by 2%
• Increase CSAT scores by 2 points
• Reduce the number of contact center calls by 22%
• Increase first contact resolution by 35%

2. Decide how to collect customer journey data.

• Customer journey analytics software
• Contact center software (customer service interactions)
• Customer relationship management (CRM) software
• AI-driven tools (e.g., natural language processing)
• Customer surveys
• Social media listening tools
• All of the above

A  customer data platform  collects, integrates and manages data across various systems (CRM, contact center software, billing system) and departments (sales and marketing, customer service), simplifying the process.

3. Create a customer journey map.  A journey map is a visual representation of the steps/actions a customer takes while trying to accomplish a particular task (pay a bill, schedule a service appointment, change plans/bundles). Customer journey mapping helps you understand customers’ behaviors, needs and preferences so you can tailor communications accordingly.

4. Use customer journey analytics software to analyze the data .  Journey analytics software combines individual channel analytics (email open and click through rates, time on website, time to serve) and customer intent (e.g., intent to purchase or cancel). Journey analytics software assigns each journey step (logging into the payment portal, viewing the bill, calling the contact center) a positive, neutral or negative value, allowing you to see at a glance if journeys are leading to positive action (e.g., paying a bill right away). If a journey step doesn’t lead to positive action, you can implement strategies to improve or prevent the step. For example, a digital bill explanation tool reduces bill confusion, preventing customers from calling the contact center.

5. Identify areas for improvement and implement changes.  Using the valuable insights you’ve acquired through predictive analytics and prescriptive analytics, decide where to make changes to improve CX. For example, you could improve first contact resolution by implementing a  telco-specific agent desktop solution  that provides all the information agents need to assist customers quickly and accurately the first time they call. Or reduce call center volume by instituting a  digital bill explanation tool that reduces bill confusion .

6. Track changes to evaluate CX improvement efforts.  Use  metrics  to evaluate the impact of your CX improvement efforts on customer satisfaction, retention, revenue and other key performance indicators.

• Number of calls per desired time frame
• Average call length
• Average hold time
• Average handle time (includes post-call tasks)
• First contact resolution (FCR)
• Customer satisfaction (CSAT)
• Net Promoter Score (NPS)
• Customer effort score (CES)
• Customer retention rate

Ready to Start Improving the Telecom Customer Experience?

Take advantage of customer journey analytics to understand customer behavior and needs, identify where journeys break down and make data-driven decisions about CX improvement efforts.

CSG Xponent , our award-winning customer journey management solution, includes journey analytics to help you understand how customers interact with your brand, predict behavior and deliver tailored communications to improve CX.

Start Optimizing Your Customer Journeys

Speak to an expert today to start improving telecom customer journeys.

Getting Started with Adobe Journey Optimizer Analysis in Customer Journey Analytics

CREATED FOR:

• Intermediate

This session is intended to demonstrate the way Customer Journey Analytics and Adobe Journey Optimizer work together to streamline the measurement of multiple Adobe Journey Optimizer campaigns and journeys.

https://video.tv.adobe.com/v/3432996/?learn=on

This webinar demonstrates the integration and capabilities of Agile Analytics in Adobe Journey Optimizer Analytics in order to help users understand the value and benefits of using these tools together for deeper analysis and insights.

Key takeaways

Integration of Agile Analytics with Adobe Journey Optimizer Analytics allows for deeper analysis and insights by combining data from different sources to generate more meaningful metrics.

Tags and categories in Adobe Journey Optimizer can be applied to journeys and campaigns to filter and group them effectively, providing a way to analyze and measure performance based on different criteria.

The configuration and setup process for leveraging Agile data in Adobe Journey Optimizer Analytics involves creating connections, data views, and metrics, which can be a one-time effort done by administrators to enable users to access and utilize the data effectively.