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Adobe Experience Platform

Data-driven Magic: Crafting Personalized Experiences with Adobe Experience Platform

• Audience Manager

From Debugging to Optimization: Leveraging the Adobe Experience Platform Debugger for Success

Introduction.

The Adobe Experience Platform Debugger is a robust software tool specifically designed to streamline the process of diagnosing and troubleshooting issues in applications running on the Adobe Experience Platform. In the ever-evolving landscape of software development, the importance of efficient debugging and code optimization cannot be overstated. This tool not only helps developers identify and resolve issues in their applications but also enhances performance by offering optimization features.

Functionality of Adobe Experience Platform Debugger

The Adobe Experience Platform Debugger offers two key functionalities: debugging and optimization. Each of these functionalities involves several sub-features designed to facilitate developers in enhancing the efficiency and performance of their applications.

Debugging is a critical process in software development, involving identification and resolution of issues or bugs in the application code. The Adobe Experience Platform Debugger offers the following sub-features for debugging:

• Breakpoints: Breakpoints allow developers to pause the execution of code at a specific point, enabling them to examine the state of the application at that moment.
• Variable Inspection: This feature allows developers to inspect the values of variables at any point during the execution of the program, providing valuable insights into the state of the application.
• Error Tracing: Error tracing helps in tracking down the origin of errors. With this feature, developers can trace the sequence of events leading up to an error, making it easier to identify and fix the problem.

Optimization

After the debugging process, optimization comes into play. It involves improving the performance and efficiency of the application code. The optimization features include:

• Performance Analysis: This feature allows developers to analyze the execution time of their codes, helping them identify bottlenecks and areas that require improvement.
• Code Efficiency: This feature offers insights into how efficiently the code is running. It provides metrics like CPU usage and memory consumption, helping developers optimize their code for better performance.

Components of Adobe Experience Platform Debugger

The Adobe Experience Platform Debugger comprises two main components: the User Interface and the Backend. These components work in tandem to offer a seamless debugging and optimization experience.

User Interface

The User Interface (UI) is the part of the debugger that users interact with. It is designed to be intuitive and user-friendly, providing a smooth user experience. The UI includes:

• Toolbar: The toolbar contains buttons that provide quick access to the debugger’s most frequently used features and commands.
• Diagnostic Panel: This panel displays detailed information about the current debugging or optimization process, helping developers understand what’s happening behind the scenes.
• Console View: The console view displays output from the application, including logs, errors, and other messages. It is an essential tool for developers to understand the runtime behavior of their application.

The Backend of the Adobe Experience Platform Debugger comprises the server-side components that handle the processing of the debugging and optimization tasks. It includes:

• Debug Server: The Debug Server is the heart of the debugger. It manages the debugging session, controls the execution of the application, and provides information to the UI.
• Runtime Environment: The Runtime Environment is where the application runs during debugging. It includes the application, the runtime libraries, and the debugger agent that communicates with the Debug Server.

Integration of Adobe Experience Platform Debugger

The Adobe Experience Platform Debugger is not an isolated tool. It is designed to interact seamlessly with other software and platforms, enhancing its capabilities and offering a comprehensive debugging solution.

With Adobe Experience Platform

The debugger is designed to work with applications running on the Adobe Experience Platform. It can connect to these applications, manage debugging sessions, and retrieve information for debugging and optimization purposes.

With Adobe Cloud Services

The Adobe Experience Platform Debugger can also be integrated with other Adobe Cloud Services. This integration allows developers to debug applications that interact with these services, providing a unified debugging experience across the Adobe ecosystem.

With Third-party Tools

Lastly, the Adobe Experience Platform Debugger can be integrated with third-party tools. This enables developers to use the debugger alongside their favorite development tools, enhancing its usability and flexibility.

The capabilities and features of the Adobe Experience Platform Debugger make it a powerful ally in the software development process. Its debugging and optimization functionalities, coupled with its seamless integration with the Adobe ecosystem and third-party tools, offer a comprehensive solution for diagnosing and fixing issues in applications. The importance of this tool in the broader context of software development cannot be overstated, as it paves the way for creating efficient, high-performing applications.

Dzmitry Kazlow

Hey there, I'm Dzmitry Kazlow, a web analytics pro with over 12 years of experience. I've been immersed in the realm of data-driven marketing, turning numbers into actionable insights that fuel business growth. My journey has revolved around helping businesses unlock the potential of data to enhance customer experiences and supercharge marketing efforts. I've dived into the technicalities of data integration and mastered the art of crafting personalized campaigns that hit the mark. Over the years, I've closely followed tech and marketing trends, making me a recognized expert in the Adobe Experience Platform. From decoding data mapping to delving into ethical data use, I bring my expertise to every blog post. Join me in exploring the incredible potential of Adobe Experience Platform and the transformative role of data-driven decisions.

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• October 1, 2021

3 Ways to Debug an Adobe Analytics Implementation

• Analytics Validation , Technology Governance

The goal of debugging an Adobe Analytics implementation is to verify your tags are firing as expected on any given page.

Specifically, you’re trying to answer the following questions:

• Is the Adobe Analytics tag present and firing off its request to the analytics server?
• Does the request to the analytics server include all the variables I expect?
• Are the variables populated with the right values in the right format?

Below are three ways you can debug your Adobe Analytics implementation, listed in order of most manual to least:

• Checking network requests with the developer tools
• Using an Adobe Analytics debugger
• Conducting an automated Adobe Analytics audit

1. Checking network requests in dev tools

The most basic way to debug your Adobe Analytics tags is by perusing the Network tab in your browser’s developer tools. This technique will work on any browser but is largely unnecessary considering the availability of free debugging tools to accomplish the same task.

For the sake of illustrating why analysts prefer to use the subsequent techniques over this one, here is the basic process for debugging a network request using your dev tools.

Locating the tag in dev tools

• Open your browser’s developer tools in Chrome , Firefox , or Safari .
• Navigate to the Network tab.
• Initiate the action that should trigger your tag to fire, such as a page load or an interaction event.
• Locate the network request that should result from that event. Finding the request is most difficult the first time. Common ways to find the request are by filtering the list for terms like “adobe” or the subdomain you set up for your tracking server.

If you can’t find any request, go back to your tag manager to evaluate your triggering rules to see why the tag isn’t firing as expected.

Debugging the analytics request

• Select the request and scroll down to the section that says Query Parameters (assuming data is being passed via query parameters and not via POST payload).
• Select “View Decoded” to decode the URL character encoding.
• Locate the variables you want to check and verify those variables are present and contain the values you expect.

Below is what the full process might look like:

As you can imagine, this process will become highly tedious after even just a few repetitions. Thankfully, you should never have to take this approach, since, at a minimum, you can use an Adobe Analytics debugger to more easily debug individual requests.

2. Using an Adobe Analytics Debugger

ObservePoint’s TagDebugger is a free Google Chrome extension that enables you to debug not only your Adobe Analytics requests but also those of any analytics platform collecting data on your site. You can also see other installed marketing vendors, like social media pixels, marketing automation tags, and more.

After you install the TagDebugger in Chrome, here are the basic steps to use this free tool.

How to use our Adobe Analytics debugger

• Open your Chrome Developer tools.
• Locate and click the new tab that says “ObservePoint.”
• Refresh the page. You should start seeing the tool capture and parse recognized network requests.
• To filter for any Adobe Analytics requests, click the filter button on the Tag Name column and type in “adobe analytics.” You’ll be able to see high-level data about the tag like the Account (i.e. report suite), Category (i.e. analytics), status, and more.
• To see specific variables in the network request, click on the tag you’re interested in. You will then be able to peruse which variables are present in the request, as well as the data contained in each variable.

Here is what that process would look like:

Upgrading from manually reviewing network requests to using a TagDebugger is a powerful leap. Debugging tags this way is perfectly suited for situations where you need to:

• Quickly validate a new update to your site didn’t affect tracking
• Verify a new aspect of your implementation is working correctly

But as much as we love our TagDebugger, it has its limitations. Your site is not just one page that changes occasionally—it’s hundreds if not thousands of pages that change often. Change is the reason analytics implementations break down, and you can’t possibly debug a critical mass of pages every time your website or implementation changes.

Which brings us to the third technique for debugging an analytics implementation.

3. Conducting an Automated Adobe Analytics Audit

Applying the word “debugging” to this final technique is a generous use of the term, considering how powerful an automated audit can be.

While your website will certainly change with time, the analytics data you hope to collect shouldn’t. Yes, you’ll collect more data as your analytics program matures, but once you start collecting data, you want to ensure you continue collecting the same data for the foreseeable future.

An automated Adobe Analytics audit does a few things, including:

• Verify your Adobe Analytics tags are present on each page
• Verify your variables are always present
• Validate each variable has the right data in the right format

The beauty of the audit is that you can configure it to run on a set schedule and notify you if anything is amiss. You’ll save time and rest easy knowing that if something goes wrong, you’ll quickly receive a notification so you can fix the error.

ObservePoint’s Technology Governance platform makes automated audits possible. Learn more about audits in the video below

Ensure Your Adobe Analytics Implementation Is Always Working

You spend a lot of time and money on Adobe Analytics, so you want to ensure you get the best return on your efforts. Regularly debugging and/or auditing your implementation can help you realize the return you’re hoping for.

If you’re interested in seeing the current state of your Adobe Analytics implementation across your site, schedule your free Adobe Analytics audit with an ObservePoint rep.

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Deciphering Adobe Analytics’s Mobile SDK Debug Output

Frederik Werner | Posted on March 1, 2020 |

Developing Mobile Applications is hard. Period. As a company offering Mobile Applications, you need to go to great length to develop Apps that don’t disappoint or annoy your customers, let alone engage them. New versions have to go through tedious testing, both from you and Google or Apple before any changes can be rolled out to your users. This is why accurate measurement of your Apps is crucial to making them successful and delivering value to your customers.

But this introduces a whole new layer of complexity. Now your developers not only need to make the App work but also need to implement Analytics into it. This can go two ways: Either they follow your tracking concept to the letter while not understanding the methodology and purpose behind it. Or you try to involve them more and make them understand why things are done in a specific way and how correct Analytics provide value to the company.

I think it’s quite clear that the second approach is the more mature one. It helps to propagate your mission and align the business with your goals. But now there is a new challenge: Testing the Analytics implementation has to be democratized to your developers. They need a way to get immediate feedback on how the App behaves in regards to Analytics, so they can fix any obvious bugs. This also helps to free up resources on QA and increase development quality.

There are some possibilities for developers to monitor Adobe Analytics requests in an App:

• Using a proxy like Charles or Fiddler. This involves monitoring network traffic and has become increasingly difficult with newer versions of Android and iOS due to security improvements.
• Using the Project Griffon Beta . Adobe has recognized the need for easier debugging and developed Project Griffon. It is a bit like the Experience Cloud Debugger for web and involves some changes to the code of your App. It is still in beta at time of writing.
• Utilizing Debug Output while development. This is the most direct way for your developers to get feedback. They will look at log output during development anyway. Logging is enabled with “MobileCore.setLogLevel(LoggingMode.DEBUG);” with the new Experience Cloud SDKs or “Config.setDebugLogging(true);” on the 4.x SKDs (or the iOS equivalent).

Since the last method is the most intuitive and direct way for developers to get feedback, we will focus on that way. Once Debug Logging is enabled, Android Studio or Xcode will print Log lines in the console, telling us what’s happening in the SDK. An Adobe Analytics logline will look like this:

So, if we filter our console with “Analytics – Request Queued”, we will only see the Analytics requests that are fired on a specific action, like below:

It’s quite obvious what those lines mean. The part in brackets contains the actual request parameters in an URL-encoded string. When we want to read it more clearly, we can throw it in an URL prettyprinter to get a more readable version like below:

The developers can now compare those variables to what you gave them in the tracking concept. Any deviations can be addressed immediately without any external involvement.

But this might get very cumbersome when every requests needs to be handled individually. To make this more manageable, I quickly put together a tool to streamline the process for our specific usecase.

The Adobe Analytics Mobile SDK Debug Parser

I wanted a way to pretty print multiple lines of debug output, at once, in a flexible way. So I came up with a single page HTML and JS app to do exactly that, you can find it here: https://www.fullstackanalyst.io/analytics_log_parser.html (Link also on top and bottom of this website). And since I am not much of a frontend developer, I put it in a Github Repo to allow contributions of more talented people than myself. Here is a quick rundown on the features:

• Easy Workflow: Just paste all your Analytics Requests in the Textbox and hit the button to get a nice table with all Requests in an understandable way.
• Built for Adobe Analytics: Columns are highlighted according to the variable type (Context Variables vs. SDK Variables vs. Normal Variables).
• Layout options: Columns can be rearranged by drag-and-drop or hidden individually or in Groups.
• Sorting options: Sort rows by clicking the column header.
• Search: Simple search to filter table by keyword.
• Export options: Export the table as CSV, Excel, or PDF, copy it to the clipboard or print it.
• Row highlighting: Highlight single or multiple rows by clicking them (with ctrl or shift for multiple).

Given that this tool is built for myself, I tested it on my machine (Chrome on Windows) to get everything running. If some things don’t work for you, try fixing it and submit a pull request on Github! As always: No guarantees on functionality and availability, use at your own risk!

German Analyst and Data Scientist working in and writing about (Web) Analytics and Online Marketing Tech.

2021 – current Adobe Analytics Champion

EMEA Adobe Analytics User Group Lead

Adobe Analytics Community Advisor

Other cool posts:

• Migrating from Android’s BroadcastReceiver to Google Play Install Referrer API with Adobe Analytics Adobe Analytics can track not only websites, but mobile apps just the same. This is achieved by using the Adobe Experience Platform Mobile SKDs for native iOS and Android apps. One very interesting part of tracking mobile apps is known as acquisition tracking, which looks at how users found the...
• Importing Organic Google Search data to Adobe Analytics with a single script Some time ago, I published an article explaining how to get Google Search performance data from the Google Search Console to Adobe Analytics. For that post, I explained to query the Google Search API, write the result to an Adobe Analytics Data Source file, and upload it to Adobe Analytics....
• Trying out the new Adobe Analytics App Adobe Analytics still is the most complete solution for Digital Analytics. But for years, there has been one thing missing: A mature way to use dashboards on the go, without using your computer. While Analytics is usable on mobile browsers on a technical level, it is not the best user...

Using Analysis Workspace to Build Adobe Analytics API 2.0 Requests using-analysis-workspace-to-build-adobe-analytics-api-requests

CREATED FOR:

• Experienced

In this video, we show you how to leverage Analysis Workspace to build API 2.0 requests automatically. By debugging the UI, you can copy & paste JSON requests directly into any API client to return Analytics data. You can now enable the debugger more easily by going to Workspace Help > Enable Debugger.

https://video.tv.adobe.com/v/25890/?quality=12&learn=on

For more information, visit the documentation .

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Debugger for Adobe Analytics

Prints to JavaScript console what data is sent to Adobe Analytics.

To see what data is being sent in JS console: - On Windows press ctrl+shift+j - On Mac press alt+cmd+j Adobe Analytics Debugger for POST and GET requests. Prints following info: - displays all page load data, link events, file downloads - shows information about data collection servers and informs if it is an RDC server or not - provides recommendations on how to improve the implementation - displays Adobe Marketing Cloud visitor ID and Adobe Marketing Cloud organisation ID

4.4 out of 5 56 ratings Google doesn't verify reviews. Learn more about results and reviews.

Kathy Dyer Oct 31, 2023

I can't watch my metrics, I'm just seeing an error message that I can't understand :( Adobe Client Data Layer v2.0.2 has already been imported/initialized on this page. You may be erroneously loading it a second time.

Bogdan Nazaruk Oct 3, 2023

Uh, tried contacting the author to help fixing the extension, but failed. So I just made a fixed version from scratch instead: https://chromewebstore.google.com/detail/universal-adobe-debugger/ehadnibhemgjphdjgkallndphbghlpkn?hl=en-US

John Fitzgerald Mar 29, 2023

Doesn't work.

• Version 1.4.6
• Updated August 27, 2024
• Report a concern
• Offered by Tomas Balciunas
• Size 17.19KiB
• Languages English
• Developer Email [email protected]
• Non-trader This developer has not identified itself as a trader. For consumers in the European Union, please note that consumer rights do not apply to contracts between you and this developer.

This developer declares that your data is

• Not being sold to third parties, outside of the approved use cases
• Not being used or transferred for purposes that are unrelated to the item's core functionality
• Not being used or transferred to determine creditworthiness or for lending purposes

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