safari media engagement index

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To Play, or Not to Play – AutoPlay Policies for Safari 14 and Chrome 64

Updates to the autoplay policies in Safari and Chrome could have significant implications for both advertisers and content providers

As of September 2017, Safari 11 on macOS and iOS, as well as Chrome for Desktop and Mobile introduced a new auto-play policy. The main goal of these policies was to improve a user’s browsing experience by eliminating distractions and surprising media playbacks of unmuted content. Thus providing users with more control over the autoplay capabilities on individual websites. Since then, Apple has made significant improvements to its playback and autoplay capabilities. For any app or service to successfully run an autoplay element, the video must either come without an audio track or with a muted attribute. The video element will automatically pause when and if the video becomes unmuted without user interaction or if the video is no longer onscreen. Additional options are available in the respective website preferences pane to allow or disable autoplay, disable audio in general, or more. In addition to that, both browsers are going to introduce an automated approach, which decides if auto-play will be blocked for media elements with sound in general or if auto-play is disabled at all.

Safari 11.0 Behavior

Developer recommendations from Safari:

This policy applies to all ways how video can be used on a website (e.g. background videos, video-as-animated-gif, …). Therefore you should check how this impacts our website accordingly.
Assume that it always requires user gestures in order to start the playback of <video> or <audio> elements, as users can disable auto-play for any type of content by now.
Auto-play restrictions are on a per-element basis. So instead of using multiple media elements to play multiple videos consecutively, use one media element and change its source (e.g. preroll-ads followed by the actual content, playlists, and so on)
Don’t play Ads without showing media controls, as they might not be able to play automatically due to the new policy, and your users won’t be able to start the playback on their own. audio tracks containing “silence” are not recognized as muted. Therefore, an audio track has to be muted or not set at all.

It’s also now possible to enable inline video playback in Safari 14.1 by including the <video playsinline> element. Without it, the video will play in full-screen mode by default.

Google Chrome 64

New behavior.

Google Chrome’s (chromium) latest auto-play policy for Mobile and Desktop was released in its stable version with Chrome 64 in November 2018 . One of their main goals is to unify the autoplay behavior across platforms and to allow the user to control which websites and contents can be played automatically. Doing so, they won’t get surprised by an unexpected media playback or increased data and power usage by their device due to that. Further, it makes a developer’s life easier as well, as the auto-play behavior will be the same for Desktop and Mobile (see table below). While muted autoplay is always allowed, unmuted autoplay requires any of the following conditions to be fulfilled:

clicking anywhere on the document, navigation, …
scrolling is excluded as a valid user interaction in this context
MEI (Media Engagement Index) threshold has to be crossed (Desktop only)
User has added a PWA (Progressive Web App) to their home screen (Mobile only)

Auto-play in Iframes requires a delegation of the auto-play approval from the origin by adding a new HTML attribute “ allow=”autoplay” ” to it. Otherwise, unmuted autoplay will be denied.

Removing the block autoplay setting that is currently available on Chrome for Android
Removing autoplay blocking on mobile when data saver mode is enabled

These two changes should encourage sites and advertisers to use muted videos instead of animated gifs, which will reduce the overall bandwidth consumption on both sides.

How do they evaluate the Media Engagement Index?

While for Safari only the name of their “automatic inference engine” is available, Google Chrome’s “Media Engagement Index” or MEI, comes with a little bit more information about how it will influence those new auto-play restrictions. Beginning with Chrome 62 Canary and Dev in September 2017, they will start collecting data for the MEI. It will be used to evaluate the interest of the user into the media available on a visited website. The conditions, which influence this new metric are not finalized yet, but Google already presented how their initial approach will look like:

Consumption of the video must be greater than 7 seconds
Audio must be present and unmuted
Tab with video is active
Size of the largest dimension of the video must be greater than 256px

So, the MEI score will be highest on sites, and therefore enable unmuted autoplay (Desktop only), which mainly provide video content, while other websites like news sites, or blogs will have a lower score, as they are more focused on textual content than videos, so they are more likely not to be able to autoplay their videos. Nevertheless, also the number of visits of a certain website by the user impacts this metric. Google also provided some example scenarios for that on slide 8 in their Autoplay Policy Presentation , which should explain how the MEI will impact the autoplay functionality in Chrome for Desktop.

Developer recommendations by Google

Use auto-play sparingly. Autoplay can be a powerful engagement tool, but it can also annoy users if undesired sound is played or they perceive unnecessary resource usage (e.g. data, battery) as the result of unwanted video playback.
If you do want to use autoplay, consider starting with muted content and let the user unmute if they are interested in exploring more. This technique is being effectively used by numerous sites and social networks.
Unless there is a specific reason to do so, we recommend using the browser’s native controls for video and audio playback. This will ensure that autoplay policies are properly handled. Prompt users to add your mobile site to the homescreen on Android devices . This will automatically give your application unmuted autoplay privileges.

How to check if auto-play is available?

Both browser vendors recommend the same best practice in order to detect the availability of auto-play, by listening to the promise returned by the play() function of an HTMLMediaElement, if it got rejected or resolved.

The Bitmovin Player team is constantly monitoring the landscape to ensure that we have solutions ready for changes just like this. Sign up for a free test account and get your Bitmovin Player up and running in just a few minutes.

Video technology guides and articles

Back to Basics: Guide to the HTML5 Video Tag
What is a VoD Platform? A comprehensive guide to Video on Demand (VOD)
Video Technology [2022] : Top 5 video technology trends
HEVC vs VP9 : Modern codecs comparison
What is the AV1 Codec ?
Video Compression: Encoding Definition and Adaptive Bitrate
What is adaptive bitrate streaming
MP4 vs MKV : Battle of the Video Formats
AVOD vs SVOD ; the “fall” of SVOD and Rise of AVOD & TVOD (Video Tech Trends)
MPEG-DASH (Dynamic Adaptive Streaming over HTTP)
Container Formats : The 4 most common container formats and why they matter to you.
Quality of Experience (QoE) in Video Technology [2022 Guide]

Gernot Zwantschko

Head of Support, Global

Gernot is one of Bitmovin's most experienced developers, and leads the customer support team as well as assisting in many areas of our product development cycle. His knowledge spans the entire range of Bitmovin products, features and solutions.

Open-Source vs. Commercial Players: Understanding the True Cost of Ownership

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Safari Media Engagement Score?

Docs or debug information available for Safari Media Engagement Scoring?

I'm working with WebRTC over the web. Code is very mature. The site is fully interactive. It is not an advertising application.

With Safari Mobile iPadOS 15.1 and Safari Desktop 15.1 MacOS 12.0.1 I'm seeing a new issue.

Occasionally video is not displayed to the user. Audio is working.

I'd like to verify this is not impact from MES effects on 15.1.

thanks team.

Posted on Nov 3, 2021 4:28 PM

Autoplay policy in Chrome

Improved user experience, minimized incentives to install ad blockers, and reduced data consumption

Chrome's autoplay policies changed in April of 2018 and I'm here to tell you why and how this affects video playback with sound. Spoiler alert: users are going to love it!

Liam Neeson: I will find you and I will pause you.

New behaviors

As you may have noticed , web browsers are moving towards stricter autoplay policies in order to improve the user experience, minimize incentives to install ad blockers, and reduce data consumption on expensive and/or constrained networks. These changes are intended to give greater control of playback to users and to benefit publishers with legitimate use cases.

Chrome's autoplay policies are simple:

Muted autoplay is always allowed.
The user has interacted with the domain (click, tap, etc.).
On desktop, the user's Media Engagement Index threshold has been crossed, meaning the user has previously played video with sound.
The user has added the site to their home screen on mobile or installed the PWA on desktop.
Top frames can delegate autoplay permission to their iframes to allow autoplay with sound.

Media Engagement Index

The Media Engagement Index (MEI) measures an individual's propensity to consume media on a site. Chrome's approach is a ratio of visits to significant media playback events per origin:

Consumption of the media (audio/video) must be greater than seven seconds.
Audio must be present and unmuted.
The tab with the video is active.
Size of the video (in px) must be greater than 200x140 .

From that, Chrome calculates a media engagement score, which is highest on sites where media is played on a regular basis. When it is high enough, media is allowed to autoplay on desktop only.

A user's MEI is available at the about://media-engagement internal page.

Screenshot of about://media-engagement internal page.

Developer switches

As a developer, you may want to change Chrome autoplay policy behavior locally to test your website for different levels of user engagement.

You can disable the autoplay policy entirely by using a command line flag : chrome.exe --autoplay-policy=no-user-gesture-required . This allows you to test your website as if user were strongly engaged with your site and playback autoplay would be always allowed.

You can also decide to make sure autoplay is never allowed by disabling MEI and whether sites with the highest overall MEI get autoplay by default for new users. Do this with flags : chrome.exe --disable-features=PreloadMediaEngagementData, MediaEngagementBypassAutoplayPolicies .

Iframe delegation

A permissions policy allows developers to selectively enable and disable browser features and APIs. Once an origin has received autoplay permission, it can delegate that permission to cross-origin iframes with the permissions policy for autoplay . Note that autoplay is allowed by default on same-origin iframes.

When the permissions policy for autoplay is disabled, calls to play() without a user gesture will reject the promise with a NotAllowedError DOMException. And the autoplay attribute will also be ignored.

Example 1: Every time a user visits VideoSubscriptionSite.com on their laptop they watch a TV show or a movie. As their media engagement score is high, autoplay is allowed.

Example 2: GlobalNewsSite.com has both text and video content. Most users go to the site for text content and watch videos only occasionally. Users' media engagement score is low, so autoplay wouldn't be allowed if a user navigates directly from a social media page or search.

Example 3: LocalNewsSite.com has both text and video content. Most people enter the site through the homepage and then click on the news articles. Autoplay on the news article pages would be allowed because of user interaction with the domain. However, care should be taken to make sure users aren't surprised by autoplaying content.

Example 4: MyMovieReviewBlog.com embeds an iframe with a movie trailer to go with a review. Users interacted with the domain to get to the blog, so autoplay is allowed. However, the blog needs to explicitly delegate that privilege to the iframe in order for the content to autoplay.

Chrome enterprise policies

It is possible to change the autoplay behavior with Chrome enterprise policies for use cases such as kiosks or unattended systems. Check out the Policy List help page to learn how to set the autoplay related enterprise policies:

The AutoplayAllowed policy controls whether autoplay is allowed or not.
The AutoplayAllowlist policy allows you to specify an allowlist of URL patterns where autoplay will always be enabled.

Best practices for web developers

Audio/video elements.

Here's the one thing to remember: Don't ever assume a video will play, and don't show a pause button when the video is not actually playing. It is so important that I'm going to write it one more time below for those who simply skim through that post.

You should always look at the Promise returned by the play function to see if it was rejected :

One cool way to engage users is to use muted autoplay and let them chose to unmute. (See the example below.) Some websites already do this effectively, including Facebook, Instagram, Twitter, and YouTube.

Events that trigger user activation are still to be defined consistently across browsers. I'd recommend you stick to "click" for the time being then. See GitHub issue whatwg/html#3849 .

The Web Audio API has been covered by autoplay since Chrome 71. There are a few things to know about it. First, it is good practice to wait for a user interaction before starting audio playback so that users are aware of something happening. Think of a "play" button or "on/off" switch for instance. You can also add an "unmute" button depending on the flow of the app.

If you create your AudioContext on page load, you'll have to call resume() at some time after the user interacted with the page (e.g., after a user clicks a button). Alternatively, the AudioContext will be resumed after a user gesture if start() is called on any attached node.

You may also create the AudioContext only when the user interacts with the page.

To detect whether the browser requires a user interaction to play audio, check AudioContext.state after you've created it. If playing is allowed, it should immediately switch to running . Otherwise it will be suspended . If you listen to the statechange event, you can detect changes asynchronously.

To see an example, check out the small Pull Request that fixes Web Audio playback for these autoplay policy rules for https://airhorner.com .

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2017-09-13 UTC.

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webrtcHacks

[10 years of] guides and information for WebRTC developers

Technology audiocontext , autoplay , playsinline , Web Audio Dag-Inge Aas · May 7, 2018

Autoplay restrictions and WebRTC (Dag-Inge Aas)

One of the great things about WebRTC is that it is built right into the web platform. The web platform is generally great for WebRTC, but occasionally it can cause huge headaches when specific WebRTC needs do not exactly align with more general browser usage requirements. The latest example of this is has to do with the autoplay of media where sound(s) suddenly went missing for many users. Former webrtcHacks guest author Dag-Inge Aas has been dealing with this first hand. See below for his write-up on browser expectations around the playback of media, the recent Chrome 66+ changes, and some tips and tricks for working around these issues.

{“editor”: “ chad hart “}

If you’re reading this, there’s a good chance you have encountered weird issues with your WebRTC application in Safari >=11 and Chrome >=66. This error, or similar, may surface as your interface sounds no longer playing (incoming call sound), your audio visualizer is no longer working, or your WebRTC application is not playing any sound at all from remote peers.

Currently, this bug is impacting major WebRTC players, such as Jitsi, Tokbox, appear.in, Twilio, Webex and many, many more. Interestingly, it seems Google’s Meet and Chromebox for meetings is also affected.

The source of our woes: Autoplay policy changes. In this blogpost, I’ll tell you what they are and how they affect WebRTC, and how you can fix this in your application. But first, what are the changes?

Error message from Chrome: The AudioContext was not allowed to start. It must be resume (or created) after a user gesture on the page. https://goo.gl/7K7WLu

What are the changes?

This whole story starts in 2007, when the iPhone, and subsequently iOS, was released. If you have worked with Safari for iOS in the past, you may have noticed that Safari has required a user gesture to play <audio> and <video> elements with sound . This requirement has in some ways been relaxed over the years, with iOS 10 allowing video elements to start playing automatically in a muted state. This causes some problems in WebRTC, as a < video > element is required to see and hear a MediaStream. It’s no use being able to play a video element with no sound automatically, because when having a video call it’s nice to be able to hear the other party as well, without requiring the user to “click play”. However, Safari for iOS hasn’t been on most WebRTC developers mind because WebRTC hasn’t been supported on the platform until relatively recently. Until iOS 11.

The first time I encountered this issue was while testing to see if my then recent implementation of a video call in Confrere worked on iOS. To my surprise, it didn’t, but it I found I wasn’t alone. Github user kylemcdonald reported on webrtc-adapter that the getUserMedia sample did not work on iOS. The fix? Adding the newly created property playsinline to the video element allowed it to be played, with audio, on iOS. The details for WebRTC are unfortunately not in the original autoplay changes blog post from Safari, but they remedied that fact by publishing a blog post on WebRTC in Safari before release. Here, it clearly states that the following applies to MediaStreams and audio playback:

MediaStream -backed media will autoplay if the web page is already capturing.
MediaStream -backed media will autoplay if the web page is already playing audio. A user gesture will still be required to initiate audio playback.

Now, there is no mention of playsinline in that document, but if you combine the two announcements, one should be able to figure out how to make your WebRTC application work on Safari for iOS.

Why is autoplay being restricted?

Initially, the focus was on avoiding substantial data costs for users. Back in 2007, data was expensive (and still is in most of the world), and few web pages were adapted for mobile. Also, autoplaying audio was and still is, one of the most annoying things on the web. Making sure that video could only be played (and loaded) with a user gesture made sure that the user was aware that they were playing video and audio.

Then came the GIF. GIFs are just animated < img > s, so they did not require a user gesture to be loaded. However, they can be quite large , and therefore costly to our poor mobile users. A video is more space efficient, but they required a user gesture to load, which was quite annoying, so pages continued to use GIFs. This all changed in iOS 10 when Safari allowed autoplaying videos in a muted state. Saving bandwidth was now a matter of allowing video, and discouraging the use of 3 minute long GIFs.

Autoplay restrictions are rolling out for desktop browsers

If you search for “how to stop autoplaying audio”, you will find quite a few hits. Recently, certain news outlets have figured that if they play REALLY LOUD audio upon page load, users will stay longer and click their ads. Of course, this is wrong, but for some reason, that doesn’t stop them from doing it. Due to this, desktop browsers are now following Safari’s example of disallowing audio playback. Most notably is Chrome, which rolled out new autoplay policies in Chrome 66.

Chrome comes with a twist to the original model though, the Media Engagement Index .

The Media Engagement Index (MEI)

The Media Engagement Index, or MEI for short, is a way for Chrome to gauge how likely you as a user is to want to allow autoplaying audio on a page, based on your previous interactions with that web page. You can see what this looks like by going to chrome://media-engagement/. The MEI is calculated per user profile , and is persisted to incognito mode. That last bit makes it really hard for developers to test their pages with a zero-sum MEI, which would help uncover issues with autoplaying audio before hitting production. Does anybody want to guess what happens next?

It’s not just about <audio> and <video>

Now as it turns out, the new autoplay policy changes affect other things than the < audio > and < video > tag. A common UX pattern in WebRTC is to provide users with feedback on microphone input volume . To do this, audio is analyzed using AudioContext , which takes a MediaStream and outputs its waveform as buckets. No audio is being played here through the speakers, but for some reason even analyzing the audio is blocked because AudioContext , in theory, allows you to output the audio.

This issue was first reported to the Webkit bug tracker in December , and a fix was merged six days later into Webkit. The fix? To allow AudioContext to work if the page is already capturing audio and video.

So why are you still reading this blog post? It turns out Chrome did the same mistake as Safari did. Even though this affects many WebRTC providers, Google has been relatively silent on this matter. There have been many attempts to get them to do a publish a PSA on the effects of autoplay on WebRTC, but this has not yet happened.

MEI scores messing with your testing

How did we get into this mess? Surely many developers must have tested their AudioContext code before this change made it into Chrome 66 stable where it effectively hits every single user. This is where MEI hits you. You see, frequent interactions with a page give you a higher MEI score, meaning that developers who frequently test in new releases on their own product are not likely to encounter the bug, as audio is allowed to be played and analyzed. Not even incognito mode helps you, as MEI is persisted. Only starting Chrome with a fresh user profile will surface the issue, a fact which is easy to forget for even seasoned Google QA people .

What should browser vendors do?

Changes to core functionality on the web is difficult to do right. Chrome has put out numerous autoplay policy change notices, but none of them mention WebRTC or MediaStreams. The seemingly forgotten Permissions API has not been updated, so that developers have no way to synchronously test if they need to prompt the user for a gesture. One suggestion is to allow AudioContext to output audio if the page is already capturing as Safari has done, but this feels like a hack rather than a solution. It also doesn’t support other legitimate use cases for analyzing audio when getUserMedia is not involved.

One concrete solution for browser vendors is to allow media permissions to impact the media engagement index. If the user has granted perpetual access to user media, then one should probably assume that the web page is trusted enough to output audio as well with no user interaction, regardless of if it’s capturing at the moment. After all, at that point the user trusts that you do not broadcast their microphone and camera to millions of users without their knowledge, so being able to play interface sounds is at that point is a minimal concern.

How to fix this in your application

There are luckily a couple of things you can do, depending on what you are trying to fix. These are the things we added at Confrere when we first met this issue rolling out support for Safari for iOS.

add playsinline

To fix videos having no sound, add the playsinline attribute on your video element. This is well documented by now. It works in both Safari and Chrome, and has no adverse effects in other browsers.

user gestures

To fix your audio visualizer, just add a user gesture. We were lucky here because we had the luxury of being able to add multiple steps without user disruption in our onboarding flow to a video call. You might not be so lucky. Until Google fixes this, there is no workaround but to add a user gesture.

no fix for interface sounds

There is no workaround at the moment for fixing interface sounds. Some are experimenting with creating an AudioContext that is reused across the application which you pipe sounds through, but I haven’t tested this. In Safari it is a little better. As long as you are capturing, you can play sounds for incoming chat messages and calls, but you probably don’t want to have user media enabled all the time just to be able to get the user’s attention that there’s an incoming call.

As you can see, there are a few things you can do to remedy this issue until there is a more long-term solution. And don’t forget to follow the bug for more updates.

{“author”: “ Dag-Inge Aas “}

All the ways to send a video file over WebRTC

Reader Interactions

May 9, 2018 at 9:43 am

this spec might be changed again. Many users complains it.

https://bugs.chromium.org/p/chromium/issues/detail?id=840866

May 10, 2018 at 6:04 am

iOS Safari only allow a single video element to play sound. You can’t play video elements with sound of two conference participants. It might be possible with a single audio element but I couldn’t make it work. https://bugs.webkit.org/show_bug.cgi?id=176282#c4

May 11, 2018 at 2:33 am

@Ben: That’s weird, I’m not able to replicate that on Confrere. We’re running full mesh with multiple participants. I’ll follow up on that bug as well, very interesting!

May 15, 2018 at 7:42 pm

Some updates from the Chrome Team: https://bugs.chromium.org/p/chromium/issues/detail?id=840866#c103

We’ve updated Chrome 66 to temporarily remove the autoplay policy for the Web Audio API. This change does not affect most media playback on the web, as the autoplay policy will remain in effect for video and audio . … The policy will be re-applied to the Web Audio API in Chrome 70 (October). Developers should update their code based on the recommendations at: https://developers.google.com/web/updates/2017/09/autoplay-policy-changes#webaudio

June 11, 2018 at 3:16 pm

In my case, I have both the playsinline and user gesture working when establishing the call. However, when I toggle MediaStreamTrack.enable on and off for two times, the remote sound is lost.

Repository URL: https://github.com/Unrupt/unrupt-demo/blob/master/unrupt.js

June 11, 2018 at 3:20 pm

Please note, we’re using AudioBufferNode, which stop receiving sound after unmuting for the second time. However, the sound is still being played through the MediaStream.

Here’s Github Issue: https://github.com/Unrupt/unrupt-demo/issues/11

January 17, 2019 at 12:45 pm

https://github.com/versatica/mediasoup/issues/264#issuecomment-455262127 — quite a good hack to synchronously check if autoplay is blocked.

How does Media Engagement Index (MEI) affect Autoplay on Chrome

The question above is related to the following questions:

Why is autoplay not working on Chrome?
Is THEOplayer limited by the Media Engagement Index?

In summary, it's possible that on the desktop-version of Chrome (unmuted) autoplay is no longer working on your web page due to the Media Engagement Index . The following two strategies can help you resolve this issue:

Increase your MEI.
Enable muted autoplay. ( How to combat autoplay policies )

You can read more about Chrome's autoplay policy at https://www.theoplayer.com/blog/chrome-autoplay-policy-what-you-need-to-know . A demo illustrating this policy can be viewed at http://demo.theoplayer.com/autoplay-policy .

The following scenario is possible due to the Chrome autoplay policy: when you first land on a web page, unmuted autoplay is not permitted. When you click through to another page, or refresh the page, unmuted autoplay is permitted, due to the additional user interactions which affect the MEI.
You can check your MEI at chrome://media-engagement/.

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General and Common Questions

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Why are some autoplaying videos muted?

Why don’t my videos autoplay with sound.

You may have noticed that videos with autoplay enabled start off muted in most browsers. This is because most modern web browsers have implemented strict policies around autoplaying videos in an effort to improve the user experience and provide greater control of playback to viewers. In most cases, videos will only be allowed to autoplay with sound if the user has already previously played a video with sound on the same domain.

Consider adding a custom animated poster frame to your videos to improve the experience for your viewers. Animated poster frames are eye-catching and ensure that your viewers are much more likely to watch your videos with sound.

Do any browsers support autoplaying video with sound?

The short answer is no. Autoplaying videos in Safari, Chrome, Firefox, and Edge are all muted by default. Each browser and operating system will have its own policy, but most modern platforms generally follow similar guidelines. Unfortunately, SproutVideo does not have the ability to change this or override these policies.

Here are links to the recent policy updates for the most common platforms:

Autoplaying video policy for iOS
Autoplaying video policy for Android
Autoplaying video policy for Safari
Autoplaying video policy for Chrome
Autoplaying video policy for Firefox
Autoplaying video policy for Edge

Note: Chrome will rely on your viewer’s Media Engagement Index to decide if it will autoplay a video with sound or not. Chrome calculates a media engagement score which is highest on sites where media is played on a regular basis. When it is high enough, media playback is allowed to autoplay with sound on desktop only.

Example of an Autoplaying Video

The video below is set to autoplay, and you can try viewing it in different browsers to see how their different policies take effect.

Unless you’ve already played a video on this domain with sound, you should most likely see a muted volume icon in the bottom left corner of the following video:

If you prefer to hide the volume control icon , you can do so by including the volume=0 or background=true embed code parameters. Learn more about embed code parameters.

Here’s an example of the same autoplaying video with the muted volume control icon hidden:

Note: If your video has no audio track, the volume control icon is hidden by default, so no additional embed code parameters are needed to remove the muted icon.

Other articles in the General and Common Questions section:

How to Download Your Videos
How to Reactivate Your On-Hold SproutVideo Account
What is SproutVideo?
Why Choose SproutVideo Over Other Video Services?
Core Features of the SproutVideo Platform
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Video Not Autoplaying

Sometimes you may see that your videos are not autoplaying, even though you have autoplay enabled. In many cases, this is due to browsers restricting autoplay with sound. Much of this depends on the browser the visitor is using.

Chrome/Chrome Mobile

Autoplay (with sound) is allowed only when:

The user has interacted with the domain (click, tap, etc.)
On desktop, the user’s Media Engagement Index threshold has been crossed, meaning the user has previously played video with sound.
The user has added the site to their home screen on mobile.

Muted autoplay is always allowed on Google Chrome.

Autoplay (with sound) is not allowed.

Muted autoplay is always allowed on Safari.

Muted autoplay is always allowed on Edge.

Autoplay (with sound) is allowed when

The user has previously interacted with the site (by clicking, tapping, pressing keys, etc.)
If the site has been allow listed; this may happen either automatically if the browser determines that the user engages with media frequently, or manually through preferences or other user interface features

Muted autoplay is always allowed on Firefox.

Mobile Safari

Autoplay with or without sound is not supported by Presto Player. Safari has too many limitations on this to reliably autoplay video. Additionally, it’s generally considered a poor user experience to autoplay videos on mobile devices, since this automatically uses data without the users permission.

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The Chromium Projects

Autoplay pre-seeding in chrome, chrome's autoplay policy uses a metric called media engagement index (mei) to determine whether or not to permit media to autoplay on a given site. mei learns, locally, from a user's individual browsing behaviors, on a site-by-site basis, whether the user regularly consumes media on each site. this helps chrome to meet user expectations; if a user frequently consumes media for longer than 7 seconds in a previously activated tab, their media engagement score will increase, and eventually autoplay will be permitted for that site without a user gesture. today, chrome typically learns a user’s preferences within six to twenty visits..

Generally users do expect autoplay behavior for some sites, and until Chrome learns individual preferences, based on MEI history, simply blocking all autoplay isn’t the best match for user expectations. So, for new users, or users who clear their browsing history, who won’t have historical media engagement data, Chrome has a pre-seeded list of sites that are permitted to autoplay media, based on aggregated anonymized data on what percentage of visitors to that site regularly permit media playback with sound. This ensures that the default behavior for sites with a high frequency of permitted media playbacks is most likely to match what a typical visitor to that site expects - as a user continues to use Chrome, their individual preferences will supplant the pre-seeded MEI scores.

The pre-seeded site list is generated based on the global percentage of site visitors who train Chrome to allow autoplay for that site; a site will be included on the list if a sizable majority of site visitors permit autoplay on it. The list is algorithmically generated, rather than manually curated, and with no minimum traffic requirement. With the implementation of the autoplay policy for Web Audio in M71, Web Audio playback is also included in calculating the MEI score for a given site.

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New Chrome/Safari autoplay policy issues #264

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Why are Some Autoplaying Videos Muted

Why don’t my videos autoplay with sound?

You may have noticed that videos autoplay muted in the Chrome and Safari browsers. Google and Apple both recently changed how their software handles autoplaying videos.

Which browsers support autoplaying video with sound?

According to the new autoplay specifications, autoplaying videos on IOS, Safari, Chrome, and Android must start out muted. This policy is controlled by the browser manufacturers, and all video hosting services must adhere to it.

Here are links to the policy change for each browser:

Autoplaying video policy for IOS
Autoplaying video policy for macOS
Autoplaying video policy for Chrome
Autoplaying video policy for Android

Example of an Autoplaying Video

The video below is set to autoplay, and you can try viewing it in different browsers to see how their different policies take effect. In Chrome and Safari this video will be muted, but in Firefox it will autoplay with sound.

**Note: Chrome will rely on your viewer’s Media Engagement Index to decide if it will autoplay a video with sound or not. Chrome calculates a media engagement score which is highest on sites where media is played on a regular basis. When it is high enough, media playback is allowed to autoplay with sound on desktop only.

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Safari, Chromeの自動再生ポリシー変更のまとめ

本記事は、 AbemaTV Advent Calendar 2017 の12/23分の投稿です。

Safari, Chromeにおいて、メディア要素（ <video> , <audio> ）の自動再生におけるポリシーが変更が発表されました。Safariは 11.0 で既に適用済み、Chromeは2018年3月頃予定の 65 で適用されます。

自動再生が許可される条件は、大まかに以下です。

タップやクリック等のユーザーインタラクションをきっかけに再生される（＝自動再生ではない）
ミュートされている、またはビデオ要素の場合は音声トラックを含んでいない
その他、ブラウザ毎の条件（後述）を満たしている

本記事では、自動再生可否の確認方法と、ブラウザ毎の詳細について紹介します。

自動再生可否の確認方法

自動再生の条件を満たしていない場合には、再生しようとしても一時停止 paused=true の状態になります。

実際にこちらのプロパティを確認する以外の手段として、メディア要素の play() 実行時に、Promiseが得られるようになっており、再生が成功したかどうかが判別できます。

例えば、音声つきが許可されていなければミュート状態で自動再生したい、といった場合は以下のように振り分けることができます。

Safariでは、自動再生の振る舞いについて、設定できるようになりました。

環境設定の環境設定 → Webサイト → 自動再生もしくは、アドレスバーを右クリックしてこのWebサイトでの設定より、以下の中から指定できます。

すべてのメディアを自動再生
サウンド付きメディアは再生しない（デフォルト）

さらに自動再生しないを指定された場合はミュート状態に関わらず、自動再生されないため、こちらの考慮も求められます。

なお、YouTube, Netflixあたりはデフォルトが「すべてのメディアを自動再生」になっている様子...

Chromeの場合は、Safariよりも条件が複雑です。

まず、デスクトップでは新たに Media Engagement Index （以下、MEI）という指標が追加されており、これに基いて自動再生の可否が変化します。他方、モバイルではホームスクリーンに追加されていることが条件になります。

このMEIについて見ていきましょう。

Media Engagement Index

MEIは chrome://media-engagement/ （※）から確認でき、Webサイト毎にそのユーザーによって重要なメディア（Significant playback）が再生されていたかどうかを元にスコアを決定します。

Significant playback かどうかは、1回の訪問毎に判別され、訪問数と共にオリジン別に記録されます。 <iframe> の場合はメインフレームのオリジンに記録されます。

以下がその判別の条件です。

ビデオ要素の大きさが 200 x 140 以上であること
音声トラックがあること
ミュートされていないこと
タブが最後の2秒間に音声を出していること（Androidを除く）
タブが表示されていること
タブがミュートされていないこと

記録された結果より、さらに以下の通りMEIのスコアが算出され、次回の訪問時に適用されます。

MEIが 0.7 に達すると音声つきの自動再生が許可され、 0.5 を下回ると拒否されます。例えば、一度 0.7 で許可状態になれば 0.5 を下回らない限り、すなわち 0.51 などでも許可状態のままです。MEIの収集は既に開始されているため、自動再生ポリシーの適用時点では既に相応のスコアが算出されている状態になります。

これによって、ユーザーの閲覧状況に応じ、頻繁にビデオを視聴しているWebサイトのみで音声つきの自動再生が許可されるようになります。違う見方をすると、自動で決められるため、頻度は少ないが音声つきで構わない、といった設定をユーザー側が任意にすることはできません。

※ Canary 65.0.3301.0 時点では Significant Playbacks はスコアに使われず、代わりに Playbacks が用いられています。違いについての情報は見つけられていませんが、 Playbacks でも先程の条件と同様に考えてよさそうです。また、訪問数やMEIの閾値については、変更される可能性があるとのことです。

https://webkit.org/blog/7734/auto-play-policy-changes-for-macos/
https://developers.google.com/web/updates/2017/09/autoplay-policy-changes
https://www.chromium.org/audio-video/autoplay
https://docs.google.com/document/d/1_278v_plodvgtXSgnEJ0yjZJLg14Ogf-ekAFNymAJoU/edit#heading=h.c1rqulonmckg

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Conceptualising and measuring social media engagement: A systematic literature review

Review Article
Open access
Published: 11 August 2021
Volume 2021 , pages 267–292, ( 2021 )

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Mariapina Trunfio 1 &
Simona Rossi ORCID: orcid.org/0000-0003-4384-0002 1

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Explore all metrics

The spread of social media platforms enhanced academic and professional debate on social media engagement that attempted to better understand its theoretical foundations and measurements. This paper aims to systematically contribute to this academic debate by analysing, discussing, and synthesising social media engagement literature in the perspective of social media metrics. Adopting a systematic literature review, the research provides an overarching picture of what has already been investigated and the existing gaps that need further research. The paper confirms the polysemic and multidimensional nature of social media engagement. It identifies the behavioural dimension as the most used proxy for users' level of engagement suggesting the COBRA model as a conceptual tool to classify and interpret the construct. Four categories of metrics emerged: quantitative metrics, normalised indexes, set of indexes, qualitative metrics. It also offers insights and guidance to practitioners on modelling and managing social media engagement.

A Model of Social Media Engagement: User Profiles, Gratifications, and Experiences

Impact of content characteristics and emotion on behavioral engagement in social media: literature review and research agenda

Melanie Schreiner, Thomas Fischer & Rene Riedl

Social Media as Online Information Grounds: A Preliminary Conceptual Framework

Avoid common mistakes on your manuscript.

1 Introduction

Over the last decade, customer engagement has received increasing attention in academic and professional debate (Hollebeek, 2019 ; Kumar et al., 2019 ; Marketing Science Institute, 2020 ; Peltier et al., 2020 ; Rather et al., 2019 ; Rossmann et al., 2016 ). It can be considered a “consumer’s positively brand-related cognitive, emotional and behavioural activity during, or related to, focal consumer/brand interactions” (Hollebeek, 2014 , p.149). Engaged customers display greater brand loyalty and satisfaction (Bowden, 2009 ; Jaakkola & Alexander, 2014 ) and are more likely to contribute to new product development (Haumann et al., 2015 ), service innovation (Kumar et al., 2010 ), and viral marketing activity spread by word of mouth (Wu et al., 2018 ). Customer engagement can also be linked with important brand performance indicators, including sales growth, feedback, and referrals (Van Doorn et al., 2010 ).

Acknowledging the potential of ICTs, scholars and practitioners are experimenting with new ways to capitalise on customer engagement and adapt to the new challenges of digital platforms (Barger et al., 2016 ; Peltier et al., 2020 ). Social media platforms reshaped the dyadic interaction between customers and organisations, creating spaces for digital sharing and engagement. By enabling users to comment, review, create, and share content across online networks, social media provide direct access to brands and allow co-creation processes. As such, the pervasive character of social media with its potential for engaging with customers and building relationships generated much interest in the concept of social media engagement (Barger et al., 2016 ; Hallock et al., 2019 ; Oviedo-García et al., 2014 ; Peltier et al., 2020 ; Schivinski et al., 2016 ). Engaging with customers in real-time and managing many incoming customers’ big data interested academic investigation and opened opportunities for marketers to enhance social media marketing success (Liu et al., 2019 ).

Understanding, monitoring, and measuring social media engagement are key aspects that interest scholars and practitioners who proposed diverse conceptualisations, several indicators and KPIs. With the spread of social media analytics, social networking platforms, digital service providers, marketers, and freelancers developed their metrics to measure engagement with brand-related social media contents and advertising campaigns. At the same time, scholars have pointed out various metrics and procedures that contribute to evaluating social media engagement in different fields (Mariani et al., 2018 ; Muñoz-Expósito et al., 2017 ; Trunfio & Della Lucia, 2019 ). Nevertheless, many of these studies offer a partial perspective of analysis that does not allow the phenomenon to be represented in diverse aspects (Oviedo-García et al., 2014 ). As a result, social media engagement remains an enigma wrapped in a riddle for many executives (McKinsey, 2012 ). How communities across an ever-growing variety of platforms, new forms of customer-brand interactions, different dimensions and cultural differences impact social media engagement measurement represents one of the main challenges (Peltier et al., 2020 ).

Although social media engagement represented a key topic in marketing research (Barger et al., 2016 ; Peltier et al., 2020 ), an overarching perspective of the existing knowledge can drive the investigation of the state of the field, including the study of the research streams, and the analysis of the measurement tools. This paper aims to systematically contribute to the academic debate by analysing, discussing, and synthesising social media engagement literature from the social media metrics perspective. A systematic literature review approach provides an overarching picture of what has already been investigated and the existing gaps that need further research. It contributes towards a systematic advancement of knowledge in the field and offers insights and guidance to practitioners on modelling and managing social media engagement (Tranfield et al., 2003 ).

The remainder of the paper is structured as follows. Section 2 presents the theoretical background of the study on customer engagement and social media engagement. Section 3 describes the methodology used for conducting the systematic literature review (Pickering & Byrne, 2014 ; Tranfield et al., 2003 ). Section 4 presents the bibliometric analysis results, including the year in which research began, the journals that publish most research, and the most relevant authors with publications on the topic. Then, Sect. 5 classifies these studies in terms of four macro-themes, conceptualisations, platforms, measurement, and behaviours and describes the key results available in the literature. Section 6 provides a critical discussion of the findings from the literature review and highlights its key contributions. Lastly, Sect. 7 concludes the study by highlighting its limitations and proposing directions for future research.

2 Theoretical background

2.1 customer engagement.

Although customer engagement research has increased theoretical and managerial relevance (Brodie et al., 2011 ; Hollebeek et al., 2016 , 2019 ; Kumar et al., 2019 ; Vivek et al., 2012 ), to date, there is still no consensus on its definition due to its multidimensional, multidisciplinary and polysemic nature.

Several customer engagement conceptualisations have been proposed in the literature, drawing on various theoretical backgrounds, particularly service-dominant logic, and relationship marketing. From a psychological perspective, one of the first definitions of customer engagement is the one of Bowden ( 2009 ) that conceptualises it as a psychological process that drives customer loyalty. Similarly, Brodie et al. ( 2011 ) define customer engagement as a psychological state that occurs by interactive, co-creative customer experiences with a focal object. Later, focusing on the behavioural aspects, it has been described as the intensity of an individual’s participation in an organisation’s offerings or organisational activities (Vivek et al., 2012 ). More recently, from a value-based perspective, customer engagement has been defined as the mechanics that customers use to add value to the firm (Kumar et al., 2019 ).

Although the perspectives may vary, common elements can be identified in various conceptualisations. Literature generally understands customer engagement as a highly experiential, subjective, and context-dependent construct (Brodie et al., 2011 ) based on customer-brand interactions (Hollebeek, 2018 ). Moreover, scholars agree on its multidimensional nature (Brodie et al., 2013 ; Hollebeek et al., 2016 ; So et al., 2016 ; Vivek et al., 2012 ) encompassing cognitive (customer focus and interest in a brand), emotional (feelings of inspiration or pride caused by a brand), and behavioural (customer effort and energy necessary for interaction with a brand) dimensions. Also, researchers have proposed that customer engagement affects different marketing constructs (Brodie et al., 2011 ; Van Doorn et al., 2010 ). For example, in Bowden’s research (2009), there is evidence to support that customer engagement is a predictor of loyalty. Brodie et al. ( 2011 ) explore its effects on customer satisfaction, empowerment, trust, and affective commitment towards the members of a community. Van Doorn et al. ( 2010 ) propose customer-based drivers, including attitudinal factors such as satisfaction, brand commitment and trust, as well as customer goals, resources, and value perceptions.

2.2 Social media engagement: The academic perspective

Social media engagement has also been investigated as brand-user interaction on social media platforms (Barger et al., 2016 ; De Vries & Carlson, 2014 ; Hallock et al., 2019 ; Oviedo-García et al., 2014 ; Peltier et al., 2020 ; Schivinski et al., 2016 ). However, while conceptual discussions appear to dominate the existing customer engagement literature, research results fragmented when moving to the online context. Scholars agree that social media engagement is a context-specific occurrence of customer engagement (Brodie et al., 2013 ) that reflects customers’ individual positive dispositions towards the community or a focal brand (Dessart, 2017 ). Social media engagement can emerge with respect to different objects: the community, representing other customers in the network, and the brand (Dessart, 2017 ). Furthermore, antecedents and consequences of social media engagement have been identified to understand why customers interact on social media and the possible outcomes (Barger et al., 2016 ), such as loyalty, satisfaction, trust, and commitment (Van Doorn et al., 2010 ).

In continuity with literature on customer engagement, also social media engagement can be traced back to affective, cognitive, and behavioural dimensions (Van Doorn et al., 2010 ). Most of the literature focuses on the behavioural dimension as it can be expressed through actions such as liking, commenting, sharing, and viewing contents from a brand (Barger et al., 2016 ; Muntinga et al., 2011 ; Oh et al., 2017 ; Oviedo-García et al., 2014 ; Peltier et al., 2020 ; Rietveld et al., 2020 ; Schivinski et al., 2016 ). It is worth pointing out that not all these actions determine the same level of engagement. Schivinski et al. ( 2016 ) in the COBRA (Consumer Online Brand Related Activities) Model differentiate between three levels of social media engagement: consumption, contribution, and creation. Consumption constitutes the minimum level of engagement and is the most common brand-related activity among customers (e.g., viewing brand-related audio, video, or pictures). Contribution denotes the response in peer-to-peer interactions related to brands (e.g., liking, sharing, commenting on brand-related contents). Creation is the most substantial level of the online brand-related activities that occur when customers spontaneously participate in customising the brand experiences (e.g., publishing brand-related content, uploading brand-related video, pictures, audio or writing brand-related articles). Starting from these social media actions, scholars attempted to measure social media engagement in several ways developing scales, indexes, and metrics (Harrigan et al., 2017 ; Oviedo-García et al., 2014 ; Schivinski et al., 2016 ; Trunfio & Della Lucia, 2019 ). Nevertheless, many of these studies offer a partial perspective of analysis that does not allow the phenomenon to be represented in its diverse aspects (Oviedo-García et al., 2014 ). Researchers have also examined emotional and cognitive dimensions (Dessart, 2017 ) as essential components of social media engagement that lead to positive brand outcomes (Loureiro et al., 2017 ).

2.3 Social media engagement: The practitioners’ perspective

In business practice, the concept of customer engagement appeared for the first time in 2006 when the Advertising Research Foundation (ARF), in conjunction with the American Association of Advertising Agencies and the Association of National Advertisers, defined it as a turning on a prospect to a brand idea enhanced by the surrounding context (ARF, 2006 ) . Later, several consulting firms tried to give their definition emphasising different aspects and perspectives. For example, in 2008, Forrester Consulting, an American market research company, defined customer engagement as a way to create ‘deep connections with customers that drive purchase decisions, interaction, and participation over time’ (Forrester Consulting, 2008 , p.4). Gallup Consulting identified four levels of customer engagement and defined it as an emotional connection between customers and companies (Gallup Consulting, 2009 ). Similarly, the famous American software provider Hubspot ( 2014 ) identified social media engagement as ‘ the ongoing interactions between company and customer, offered by the company, chosen by the customer’ (Hubspot, 2014 , p.1).

With the increasing spread of social networks and their exploitation as an important marketing tool, practitioners recognised a clear linkage between customer engagement and the metrics to assess digital strategy success. Over time, social networking platforms such as Facebook, LinkedIn, and YouTube, developed their metrics to measure engagement with brand-related social media contents and advertising campaigns (Table 1 ).

With the spread of social media analytics, platforms and digital service providers developed dashboards and analytical indicators to assess, measure and monitor the engagement generated by social media marketing activities (Table 2 ). At the same time, many bloggers, marketers, and freelancers have weighed in on the topic, enriching the debate with new contributions.

As a result, while scholars still have to agree upon a shared definition of social media engagement, marketers have recognised it as one of the most important online outcome companies need to deliver with social media and a key metric to assess social media strategy success . Despite the growing interest in business practice and its solid traditional theoretical roots, most of the existing literature on social media engagement offers only conceptual guidelines (Barger et al., 2016 ; Peltier et al., 2020 ). The measurement of engagement in social media and its financial impact remains an enigma wrapped in a riddle for many executives (McKinsey, 2012 ) and requires further investigations. Mainly, how new and emerging platforms, new forms of customer-brand interactions, different dimensions, and cultural differences impact social media engagement measurement remains an understudied phenomenon (Peltier et al., 2020 ).

3 Methodology

The literature review is one of the most appropriate research methods, which aims to map the relevant literature identifying the potential research gaps that need further research to contribute towards a systematic advancement of new knowledge in the field (Tranfield et al., 2003 ). This research is built upon the rigorous, transparent, and reproducible protocol of the systematic literature review as a scientific and transparent process that reduces the selection bias through an exhaustive literature search (Pencarelli & Mele, 2019 ; Pickering & Byrne, 2014 ; Tranfield et al., 2003 ). Building on recent studies (Inamdar et al., 2020 ; Linnenluecke et al., 2020 ; Phulwani et al., 2020 ), in addition to the systematic literature review, a bibliometric analysis (Li et al., 2017 ) was also performed to provide greater comprehensions into the field's current state and highlight the future research directions.

3.1 Database, keywords, inclusion, and exclusion criteria

To conduct a literature review, quality journals are considered the basis for selecting quality publications (Wallace & Wray, 2016 ). Therefore, the database Scopus, run by Elsevier Publishing, was considered to search for relevant literature, being the most significant abstract and citation source database used in recent reviews.

When conducting a literature review, a fundamental issue is determining the keywords that allow identifying the papers (Aveyard, 2007 ). To address it, the most frequently used keywords in peer-reviewed literature have been under investigation. As such, the following research chain was used: “Social media” “Engagement” AND “metric*”, searching under title, abstract, and keywords.

The systematic literature review protocol (Fig. 1 ) has been conducted on the 26 th of March 2020. The study considers an open starting time to trace back to the origin of social media engagement metrics research up to late March 2020. The initial search attempts identified 259 documents.

The systematic literature review protocol

After the articles’ identification, criteria for inclusion and exclusion were adopted. First, the 259 articles were screened, considering English-language articles published in peer-reviewed academic journals to safeguard the quality and effectiveness of the review. Due to variability in the peer-review process and their limited availability, book reviews, editorials, and papers from conference proceedings were excluded from this research. After the screening, a sample of 157 papers was obtained.

Afterwards, the full text of these papers was reviewed to assess eligible articles. As a result, 116 articles were excluded because their subject matter was not closely related to the topic of social media engagement metrics. In detail, papers were excluded when: 1) they mainly focused on social media engagement but superficially touched the metrics or 2) they mainly focused on metrics but superficially touched on social media engagement. In the end, 41 eligible articles were identified.

3.2 Analysis tools

The relevant data of the 41 documents in the final sample were saved and organised in a Microsoft Excel spreadsheet to include all the essential paper information such as paper title, authors’ names, and affiliations, abstract, keywords and references. Then, adopting the bibliometrics analysis method (Aria & Cuccurullo, 2017 ), the R-Tool ‘Biblioshiny for Bibliometrix’ was used to perform a comprehensive bibliometric analysis. Bibliometrix is a recent R-package that facilitates a more complete bibliometric analysis, employing specific tools for both bibliometric and scientometric quantitative research (Aria & Cuccurullo, 2017 ; Dervis, 2019 ; Jalal, 2019 ).

4 An overview of social media engagement metrics research.

The bibliometric analysis provided information on the 41 articles, allowing to highlight the significance of the topic.

4.1 Publication trend

The number of annual publications shows a rollercoaster trend (Fig. 2 ). Although the first relevant paper was published in 2013, only since 2016 publications begun to increase significantly with a slight decrease in 2018. This renders social media engagement metrics a relatively young research field.

Timeline of the studies (January 2013- March 2020)

It is worth pointing out that the articles extraction was done in March 2020: this explains the low number of articles published in 2020.

4.2 Most relevant sources

When looking at the Journal sources overview, the analysis revealed 34 journals covering different fields, including marketing, management, economics, tourism and hospitality, engineering, communication, and technology. As shown in Fig. 3 , only four journals have more than two publications: Internet Research , Journal of Engineering and Applied Sciences , International Journal of Sports Marketing and Sponsorship. and Online Information Review .

Most relevant sources

4.3 Seminal papers

Interesting findings emerged considering the most global cited documents that allow identifying the seminal articles in according to the timeliness, utility and quality, expressed by the scientific community (Okubo, 1997 ). The number of citations an article receives, and the studies cited in an article are two of the most popular bibliometric indicators used to determine the popularity of a publication.

Figure 4 shows the number of author citations for each article, identifying as seminal works: Malthouse’s (2013) paper ‘ Managing Customer Relationships in the Social Media Era: Introducing the Social CRM House’ with 278 global citations; Sabate’s (2014) paper ‘Factors influencing popularity of branded content in Facebook fan pages’ with 145 global citations; Mariani’s (2016) paper ‘ Facebook as a destination marketing tool: Evidence from Italian regional Destination Management Organizations ’ with 104 global citations; Oh’s (2017) paper ‘ Beyond likes and tweets: Consumer engagement behavior and movie box office in social media ’ with 54 global citations; Colicev’s (2018)’ Improving consumer mindset metrics and shareholder value through social media: The different roles of owned and earned media ’ with 39 global citations; Rossmann’s (2016) ‘ Drivers of user engagement in eWoM communication ’ with 35 global citations; Oviedo-Garcia’s (2014) ‘ Metric proposal for customer engagement in Facebook’ with 33 global citations .

Most cited articles

The analysis of the papers reviewed revealed that the theme of social media engagement metrics turns out to be a hot topic and a newly emerging stream of research.

5 Social media engagement: areas of investigation

In recent years social media engagement has gained relevance in academic research, and many scholars have questioned its measurement, intensifying the academic debate with ever new contributions. Following previous studies, a comprehensive analysis allows framing the following categories of broad research subjects, used to conduct the subsequent systematic literature review (Fig. 5 ): (1) conceptualisation, (2) platforms, (3) measurement and (4) behaviours. All 41 articles were analysed according to the proposed scheme.

Areas of investigation

5.1 Investigating social media engagement

What emerges from the analysis of the 41 papers is that scholars used different approaches and methodologies to conceptualise and measure engagement in the digital context of social media.

As shown in Fig. 6 , most studies (66%) employ quantitative methodologies. For instance, Yoon et al. ( 2018 ) explored the relationship between digital engagement metrics and financial performance in terms of company revenue, confirming that customer engagement on a company’s Facebook fan page can influence revenue. Colicev et al. ( 2018 ) developed three social media metrics, including engagement, to study the effects of earned social media and owned social media on brand awareness, purchase intention, and customer satisfaction. In comparison, Wang and Kubickova ( 2017 ) examined factors affecting the engagement metrics of Facebook fan pages in the Northeast America hotel industry, factors such as time-of-day, day-of-week, age, gender and distance between the hotel and users’ origin of residence. They also analysed the impact of Facebook engagement on electronic word-of-mouth (eWOM), to better understand the importance of the engagement metrics within the hospitality context.

Classification of the 41 articles based on the methodology applied

From a qualitative point of view (17% of the papers), Hallock et al. ( 2019 ) used a case study approach to understand the firm perspective on social media engagement metrics, shedding light on how companies view engagement with social media as measurable metrics of customer interactions with the platform. Conversely, Michopoulou and Moisa ( 2019 ) used the same approach to investigate the use of social media marketing metrics and practices in the U.K. hotel industry.

Only a small part of the studies analysed (10% of the papers) explores social media engagement from a purely conceptual perspective. In this sense, Oviedo-Garcìa et al. ( 2014 ) and Muñoz-Expósito et al. ( 2017 ) directly identified social media engagement metrics for Facebook and Twitter, providing fascinating insights for scholars and practitioners.

Finally, among the papers analysed, only three studies (7% of the papers) use mixed methodologies to explore the phenomenon from qualitative and quantitative perspectives.

5.2 Defining social media engagement

Researchers identified 30 unique definitions of engagement applied to the social media context. Multiple definitions used several terms when defining engagement on social media. They were not singular and straightforward but were interspersed with various key terms and overlapping concepts, as presented in Table 3 .

The presence of synonymous terms directly addresses the lack of a standard definition and the challenges that this presents to researchers and practitioners in the field (Table 4 ).

As a relevant result, most authors focus on its behavioural manifestation (22% of the studies) resulting from motivational drivers when defining social media engagement. It is considered as the active behavioural efforts that both existing and potential customers exert toward online brand-related content (Yoon et al., 2018 ). It involves various activities that range from consuming content, participating in discussions, and interacting with other customers to digital buying (Oh et al., 2017 ; Yoon et al., 2018 ). Similarly, in addition to the behavioural manifestations, other scholars (12%) focus on the emotional connection expressed through the intensity of interactions and their implications, toward the offers and activities of a brand, product, or firm, regardless of whether it is initiated by the individual or by the firm (Muñoz-Expósito et al., 2017 ).

Shifting the observation lens from the customers to the firms, another group of scholars (10% of the studies) define social media engagement as the non-monetary return that derives from the online marketing strategies of brands (Khan, 2017 ; Medjani et al., 2019 ; Michopoulou & Moisa, 2019 ). In this case, engagement is viewed exclusively as a non-financial metric and as a measure of the performance of social media marketing activities.

Lastly, a small percentage of studies (10% of the studies) considers engagement as the number of people who acknowledge agreement or preference for content, who participate in creating, sharing and using content (Colicev et al., 2018 ; Li et al., 2019 ; Rahman et al., 2017 ).

5.3 Social Media Platforms

In a total of 41 articles reviewed, 85% of studies mention the platforms analysed, as shown in Table 5 . Facebook is the most popular platform analysed, followed by Twitter, YouTube, LinkedIn, and Instagram. These results were rather expected, given the fact that Facebook, with 2.6 billion monthly active users (Facebook, May 2020), is the most popular social media platform worldwide.

An interesting finding is that there are several articles (15% of the studies) which do not refer to a specific platform or that consider all the platforms together, when measuring social media engagement (e.g., Hallock et al., 2019 ; Medjani et al., 2019 ). This is interesting, given that each social network has different features that make the engagement measurement unique and not replicable.

5.4 Measuring social media engagement

The systematic literature review confirms that there is no theoretical certainty or solid consensus among scholars about measuring engagement on social media.

As can be seen from Table 6 , studies on social media engagement metrics can be grouped and classified into four macro-categories. The first group of studies, namely ‘quantitative metrics’, which is also the most numerous (66% of the studies), attempts to propose a simplistic assessment of the impact of social media engagement, based on the number of comments, likes, shares, followers etc. (Khan et al., 2019 ; Medjani et al., 2019 ; Yoon et al., 2018 ).

The second group of studies (17% of the studies), namely ‘normalised indexes’, provide a quantitative evaluation of the engagement a content generates in relation to the number of people to whom that content has been displayed. In this way, it is possible to obtain an average measure of the users’ engagement, dividing the total actions of interest by the total number of posts (Osokin, 2019 ; Zanini et al., 2019 ), the number of followers (Vlachvei & Kyparissi, 2017 ) or the number of people reached by a post (Muñoz-Expósito et al., 2017 ; Rossmann et al., 2016 ).

In a more complex and detailed way, studies from the third group (10% of the studies) identify social media engagement metrics developing ‘set of indexes’. For example, Li et al. ( 2019 ) use three social media metrics to measure engagement in the casual-dining restaurant setting: rates of conversation, amplification, and applause. In detail, conversation rate measures the number of comments or reviews in response to a post, amplification rate measures how much online content is shared, and applause rate measures the number of positive reactions on posts. Similarly, drawing from previous literature, Mariani et al. ( 2018 ) develop three social media metrics, namely generic engagement, brand engagement, and user engagement. Authors calculated these metrics by assessing different weights to different interaction actions, to emphasise the degree of users’ involvement implied by the underlying activities of respectively liking, sharing, or commenting.

Despite their great diffusion among academics and practitioners, some scholars (7% of the studies) argue that quantitative metrics are not enough to appreciate the real value of customer engagement on social media, and a qualitative approach is more suitable. For example, Abuljadail and Ha ( 2019 ) conducted an online survey of 576 Facebook users in Saudi Arabia to examine customer engagement on Facebook. Rogers ( 2018 ) critiques contemporary social media metrics considered ‘vanity metrics’ and repurpose alt metrics scores and other engagement measures for social research—namely dominant voice, concern, commitment, positioning, and alignment—to measure the ‘otherwise engaged’.

5.5 Social media engagement brand-related activities

When measuring social media engagement, scholars dealt with different social media actions that can be classified (Table 7 ) according to the three dimensions of the COBRA model (Consumer Online Brand Related Activities): consumption, contribution, or creation (Schivinski et al., 2016 ).

In a total of 41 articles reviewed, the most investigated dimension by researchers is contribution, i.e. when a customer comments, shares, likes a form of pre-existing brand content (e.g., Buffard et al., 2020 ; Khan et al., 2019 ). Its popularity among the studies may be due to its interactive nature of “liking” and “commenting”, which can be said to be the most common behaviour exhibited across social media platforms and often one of the most manageable interactions to obtain data. Additionally, studies that include creation in the measurement of social media engagement consider posting/publishing brand-related content, uploading brand-related video, pictures, audio or writing brand-related articles (e.g., Zanini et al., 2019 ). Among the sampled papers, the least investigated dimension of the COBRA model is consumption, considered by only seven studies (e.g., Colicev et al., 2018 ; Oh et al., 2017 ). It considers viewing brand-related audio, video, and pictures, following threads on online brand community forums or downloading branded widgets.

Dimensions have been investigated individually, for example, just considering the number of likes or comments (Khan et al., 2019 ; Yoon et al., 2018 ), or jointly using composite indicators, as in the case of Oviedo-Oviedo-García et al., 2014 ).

6 Discussion

This research presents fresh knowledge in the academic debate by providing an overarching picture of social media engagement, framing the phenomenon conceptually and offering a lens to interpret platforms and measuring tools. Conceptual and empirical studies tried to define, conceptualise, and measure social media engagement in diverse ways from different fields of research. They increased the gap between academia and managerial practice, where the topic of social media engagement metrics seems to be much more consolidated. The paper contributes to the academic debate on social media engagement, presenting continuity and discontinuity elements between different fields of enquiry. It also offers avenues for future research that both academics and marketers should explore. It also provides insights and guidance to practitioners on modelling and managing social media engagement.

6.1 Theoretical contribution

The article offers some theoretical contributions to this relatively young research field through the systematic literature review approach.

Firstly, the paper confirms the multidimensional and polysemic nature of engagement, even in the specific context of social media platforms, in continuity with the academic customer engagement research (Brodie et al., 2013 ; Hollebeek et al., 2016 ; So et al., 2016 ; Vivek et al., 2012 ). The concept of social media engagement can be traced back to three dimensions of analysis (Van Doorn, 2010 )—affective, cognitive, and behavioural—and some empirical studies measure it as such (Dessart, 2017 ; Vivek et al., 2014 ). However, the behavioural dimension is still the most used proxy to measure users’ level of engagement. Similarly, marketers and social media platforms have focused on behavioural interactions associated with likes, comments and sharing when reporting engagement metric (Peltier et al., 2020 ). What is worth pointing out is that emotional and cognitive dimensions are also essential components of social media engagement and should be adequately addressed by future research.

Secondly, strictly related to the first point, the paper suggests the COBRA model (Schivinski, 2016 ) as a conceptual tool to classify and interpret social media engagement from the behavioural perspective. Social media engagement can be manifested symbolically through actions (Barger et al., 2016 ; Oh et al., 2017 ; Van Doorn et al., 2010 ) that can be traced back to the three dimensions of consumption, contribution and creation (Schivinski et al., 2016 ). However, it is worth pointing out that not all these actions determine the same level of engagement. When measuring social media engagement, researchers should pay attention not only to ‘contribution’ but also to ‘consumption’ and ‘creation’, which are important indicators of the attention a post receives (Oviedo-Garcìa, 2014 ; Schivinski et al., 2016 ), giving them a different weight. It becomes even more important if considering that the same social networks provide different weights to users' actions. For example, in several countries, Instagram has tested removing the like feature on content posted by others, although users can still see the number of likes on their posts. YouTube has also decided to stop showing precise subscriber counts and Facebook is experimenting with hiding like counts, similar to Instagram.

Thirdly, the paper presents some of the key metrics used to evaluate social media engagement identifying quantitative metrics, normalised indexes, set of indexes and qualitative metrics. Although all indicators are based on the interaction between the user and the brand, as the literature suggests (Barger et al., 2016 ; Oviedo-Garcìa, 2014 ; Vivek et al., 2014 ), the paper argues that different metrics measure diverse aspects of social media engagement and should be used carefully by researchers. Despite the conceptual and qualitative research on the topic, even the most recent metrics offer measurements that do not allow engagement to be widely represented in its multidimensional and polysemic nature (Oviedo-García et al., 2014 ; Peltier et al., 2020 ). To get a deeper understanding of the construct, researchers should also consider some of the most recent advances in business practice. As an example, more and more practitioners have the chance to measure engagement by tracking the time spent on content and web pages to blend the different types of material, such as pictures, text, or even videos. Also, cursor movements, which are known to correlate with visual attention, and eye-tracking, can provide insights into the within-content engagement.

6.2 Managerial implications

Even if the topic of social media engagement seems to be more consolidated in business practice, this study also provides valuable implications for practitioners. Particularly, the findings shed light on the nature of social media engagement construct and on how metrics can be an extremely useful tool to evaluate, monitor, and interpret the effectiveness of social media strategies and campaigns.

This research offers a strategic-operational guide to the measurement of social media engagement, helping marketers understand what engagement is and choose the most effective and suitable KPIs to assess the performance and success of their marketing efforts. In this sense, marketers should accompany traditional metrics, such as likes, comments and shares, with new metrics capable of better capturing user behaviours.

Marketers also need to realise that engagement is a complex construct that goes beyond the simple behavioural dimension, encompassing cognitive and emotional traits. As a result, in some cases, the so-called “vanity metrics” could fail in fully representing all the aspects of social media engagement. In these cases, it should be accompanied by qualitative insights to analyse what users like to share or talk about and not merely look at likes, comments, and shares counts.

7 Limitations and future research

This research is not without limitations. First, the systematic literature review only includes English articles published in Journals. As social media engagement and engagement metrics are emerging research topics, conference proceedings and book chapters could also be included to deepen the understanding of the subject. Second, this research was conducted on the database Scopus of Elsevier for the keywords “social media engagement metrics”. Researchers could use a combination of different databases and keywords to search for new contributions and insights. Third, although the paper is based on a systematic literature review, this methodology reveals the subjectivity in the social sciences.

As this is a relatively young field of research, a further academic investigation is needed to overcome the limitations of the study and outline new scenarios and directions for future research. In addition, considering the growing importance of social media, there is value in broadening the analysis through additional studies. Future marketing research could use mixed approaches to integrate the three dimensions of social media engagement, linking qualitative and quantitative data. Advanced sentiment web mining techniques could be applied to allow researchers to analyse what users like to share or talk about and not merely look at likes, comments, and shares as the only metrics (Peltier et al., 2020 ).

Although Facebook and Twitter are the most used social network by brands, and the most significant part of the literature focuses on these two platforms, researchers should not forget that there are new and emerging social media in different countries (e.g., TikTok, Clubhouse). They already represent a hot topic for practitioners and are calling scholars to define new metrics to measure engagement. Additionally, as the use of social media increased during the COVID-19 pandemic, future research should take this into account to better understand social media engagement across different social media platforms.

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Trunfio, M., Rossi, S. Conceptualising and measuring social media engagement: A systematic literature review. Ital. J. Mark. 2021 , 267–292 (2021). https://doi.org/10.1007/s43039-021-00035-8

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Conceptualising and measuring social media engagement: A systematic literature review

Mariapina trunfio.

Department of Management and Quantitative Studies, University of Naples “Parthenope”, Naples, Italy

Simona Rossi

Introduction

Theoretical background

Customer engagement.

Social media engagement: The academic perspective

Social media engagement: The practitioners’ perspective

Social media engagement metrics by social networking platforms (2020)

With the spread of social media analytics, platforms and digital service providers developed dashboards and analytical indicators to assess, measure and monitor the engagement generated by social media marketing activities (Table (Table2). 2 ). At the same time, many bloggers, marketers, and freelancers have weighed in on the topic, enriching the debate with new contributions.

Social media engagement metrics by social media management and analytics platforms (2020)

Methodology

Database, keywords, inclusion, and exclusion criteria

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The systematic literature review protocol

Analysis tools

An overview of social media engagement metrics research.

The bibliometric analysis provided information on the 41 articles, allowing to highlight the significance of the topic.

Publication trend

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Timeline of the studies (January 2013- March 2020)

It is worth pointing out that the articles extraction was done in March 2020: this explains the low number of articles published in 2020.

Most relevant sources

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Seminal papers

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Most cited articles

The analysis of the papers reviewed revealed that the theme of social media engagement metrics turns out to be a hot topic and a newly emerging stream of research.

Social media engagement: areas of investigation

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Areas of investigation

Investigating social media engagement

What emerges from the analysis of the 41 papers is that scholars used different approaches and methodologies to conceptualise and measure engagement in the digital context of social media.

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Object name is 43039_2021_35_Fig6_HTML.jpg

Classification of the 41 articles based on the methodology applied

Finally, among the papers analysed, only three studies (7% of the papers) use mixed methodologies to explore the phenomenon from qualitative and quantitative perspectives.

Defining social media engagement

Frequency of the terms used to define engagement in social media

The presence of synonymous terms directly addresses the lack of a standard definition and the challenges that this presents to researchers and practitioners in the field (Table (Table4 4 ).

Social media engagement main definitions

Social Media Platforms

In a total of 41 articles reviewed, 85% of studies mention the platforms analysed, as shown in Table Table5. 5 . Facebook is the most popular platform analysed, followed by Twitter, YouTube, LinkedIn, and Instagram. These results were rather expected, given the fact that Facebook, with 2.6 billion monthly active users (Facebook, May 2020), is the most popular social media platform worldwide.

Platforms mentioned in the 41 articles and related frequencies

Measuring social media engagement

The systematic literature review confirms that there is no theoretical certainty or solid consensus among scholars about measuring engagement on social media.

As can be seen from Table Table6, 6 , studies on social media engagement metrics can be grouped and classified into four macro-categories. The first group of studies, namely ‘quantitative metrics’, which is also the most numerous (66% of the studies), attempts to propose a simplistic assessment of the impact of social media engagement, based on the number of comments, likes, shares, followers etc. (Khan et al., 2019 ; Medjani et al., 2019 ; Yoon et al., 2018 ).

Social media engagement metrics used in the 41 articles

Social media engagement brand-related activities

When measuring social media engagement, scholars dealt with different social media actions that can be classified (Table (Table7) 7 ) according to the three dimensions of the COBRA model (Consumer Online Brand Related Activities): consumption, contribution, or creation (Schivinski et al., 2016 ).

Dimensions of the COBRA model and related frequencies

Theoretical contribution

The article offers some theoretical contributions to this relatively young research field through the systematic literature review approach.

Managerial implications

Limitations and future research

Open access funding provided by Università Parthenope di Napoli within the CRUI-CARE Agreement.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Mariapina Trunfio, Email: ti.eponehtrapinu@oifnurt .

Simona Rossi, Email: [email protected] .

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Our perspective

Introducing the Engagement Index: A New Metric Redefining Audience Content Preferences

June 21, 2021 // 7 minute read

By harnessing the power of artificial intelligence and machine learning, we can gather analytics and insights that would be impossible for humans alone to deliver. Immedia COO, Richard Jones , explains how.

Looking for a new way to map out content opportunities for your business? Enter Contrend and the EI metric, a new audience engagement tool to transform content marketing. The beating heart of Contrend is a key metric — the Engagement Index (EI) — that is redefining audience measurement. Using a balanced combination of SEO, Audience Impact and NLP analytics, EI can help brands find hidden audiences, assess competitors’ plans and identify trends and topics for maximum engagement and content ROI. Here’s how.

How Did Contrend Begin?

Let’s first rewind 18 months… It’s early 2019 and at Immedia Content we knew that central to successful content strategy, and therefore content creation, is a great understanding of the target audience and competitive landscape. Our diverse B2B and B2C clients were across industries such as finance, tech and travel and were spread over multiple markets across Asia, Europe and the US.

As a result, getting hold of the data we needed to create audience-centric, data-driven strategies was extremely difficult. Let’s rephrase that— it was impossible.

Add to that: ever-increasing competition and the need for us to manage our global pool of 1,200+ expert contributors. We knew we needed something to help us gather and analyze huge, complex data sets and generate the insights we needed.

We needed a way to do this, as our in-house editorial team alone couldn’t do this data collection, analysis and manage our clients. After a lot of head scratching, we realized that AI and ML technology was the only way we could deliver such unique services to our clients and evolve our business.

We Intentionally Built the Contrend Platform to Fill an Obvious Gap in the Market

Over the next 18 months, Immedia built Contrend, a proprietary AI/ML-driven content marketing platform. Securely hosted in the cloud by Amazon Web Services (AWS), Contrend’s DNA includes a coding language called Python that allows it to harvest and analyze huge, complex data sets, and apply AI algorithms and ML techniques to provide unique audience insights and fresh market perspectives. This gives Immedia’s team of Editors the ability to build effective, data-driven content strategies that are regionally consistent and relevant to local audiences.

Contrend was built to do all the heavy lifting that would be impossible for us mere humans, and create output recommendations and predictions that content marketers can use to create great strategy and content. It was, and always will be, an invaluable member of our team.

Introducing EI: The Engagement Index

One of the stars of Contrend is a metric we developed called the “Engagement Index,” or EI. It was created to measure, compare, track, and predict content effectiveness across any industry, vertical, or market. Essentially, it’s the beating heart of Contrend. Here’s what EI does:

Shows what content topics, formats and styles your audiences’ prefer
Benchmarks content against your competitors and the wider content landscape
Shows if content is relevant to the target audience
Identifies opportunities to maximize the impact of your content
By measuring and tracking EI to identify audience preferences and trends, Contrend recommends content topics, formats and messaging styles that will increase audience engagement.

Over time it predicts optimum future content topics, formats and channels that will deliver maximum content ROI.

Identifying the “Hidden Audience” with EI

As content marketers, we’re interested in understanding audience content preference and how these vary over time and across different markets. This is essential when creating content assets to build long-term audience interest and engagement for clients, whether they are in B2C or B2B. We want to base our strategy on strong, reliable foundations rather than being reliant on short-term chatter or noise from channels such as social media.

It became clear to us that we needed a metric that considered deeper content engagement levels, not just reactions. It was at this point that we discovered the 1:9:90 Audience Participation Inequality, which states that 1% of an audience creates content, only 9% visibly engage with it through likes, shares and comments, with the remaining 90% of the audience just reading or viewing your content. In our minds, if we relied on traditional audience analysis methods, such as social listening tools, we could be missing up to 90% of audience engagement.

So our objective was clear: we wanted to go beyond the short-term trends and chatter often reported by social media, to understand what content audiences engage with, across different topics, formats and messaging styles. To do this, EI measures and tracks this ‘hidden audience’ by identifying content preferences of the 90% ‘hidden audience members’ owned content, competitor websites and the wider content landscape in one, or multiple markets.

How is EI Calculated?

Data used by Contrend includes:

Audience Impact Assessment: how relevant is the content? How often has it been viewed?
SEO Performance Analytics: does the content contain optimum keywords and phrases? Plus backlink analysis.
Website Scraping and NLP Interrogation: what format is the content? What topic is the content about? What is the intent behind the content?

Algorithms in the platform then allocate the following scores to the content:

SEO Performance Score
Audience Relevance Score
NLP-derived Topic, Format and Intent Tag

Contrend then collates, clusters and allocates weighting to the content, and finally, gives an Ei Score to the content. This score delivers a balanced combination of SEO, Audience Impact and NLP analytics, which would be impossible for humans alone to deliver.

EI Maps New Content Territory for You to Explore

Let’s look at a recent case study. Research for one of our banking clients looked at engagement across an audience segment in Singapore and SEA. Contrend generated some powerful new insights:

Only 9% of SME engagement (EI) was towards content created by banks. 91% of SME engagement (EI) was with content created by non-banks, about topics that banks were not talking about.

This was the proverbial eye-opener, and presented a number of incredible opportunities:

Contrend could show our client the topics they should be creating content about in each market, to differentiate them from their competitors, and better engage with their target audience
Contrend identified similarities in EI across the markets, along with significant cultural, behavioral and attitudinal differences that needed to be considered
EI allows you to understand the underlying interests of different audiences, offering you the opportunity to talk about topics they are genuinely interested in

Sense Check: Another Way of Looking at the Benefits of EI

Imagine, God forbid, that one of your best friends has a car accident. Now, of course you’ll spend time making sure he’s okay and if there’s anything you can do. But, over time, you’ll want to take his mind off it and talk about things that you know he likes. So rather than bleating on about being there for him, the cost of car repairs, health insurance and physiotherapy, you’ll talk about his hobbies, favorite music, arranging to go out to your favorite coffee shop or restaurant. Stuff your friend is genuinely interested in. Something different to all the other injury-related things coming from everywhere else. Because he’s your friend, you know him, and you want to be their friend in the future.

Exactly the same analogy relates to content marketing, especially during the recent pandemic.

How many meaningless and shallow messages have you received over the last few months from brands that want to “help you through these hard times” and who are “in this with you”? I bet it’s a lot. And it all feels predictable and meaningless.

Because they don’t know what else to talk about.

If you’re reliant on short-term audience analysis tools such as social listening, and a PR, campaign-focused mindset, you run the risk of just talking about COVID-19, and not what’s really of interest to your audience.

It doesn’t have to be this way.

EI lets you to say something different to your audience, by allowing you to create content that will resonate and engage.

Key Takeaways: The Benefits of Contrend and the EI Metric

The Contrend platform — and the EI metric within it — collects and crunches huge data sets to deliver multiple benefits:

Define and quantify audience content preferences across multiple markets
Identify competitor EI and competitor content strategy
Benchmark your EI versus competitors, identifying opportunities for differentiation
Identify EI of the wider target audience, identifying new ways to engage
Recommend optimum content pillars, at regional and local levels
Recommend actionable content calendars with review and success metric
Hyper-efficient workflow management
Predict future audience and competitor trends and content opportunities

Our perspective // July 31, 2023

AI Lawsuits Are Coming

Our perspective // July 14, 2023

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More Bookings for your Safari Business

We help busy safari businesses spend less time on marketing and get more safari bookings…, safari content written for safari experts by safari experts.

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Make connections

Through content you build authority, position yourself as an expert and build connection with your ideal clients.

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Once people know you and respect you they will trust you want to buy from you.

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Hi I’m Natasha

A freelance photographer, digital content creator and Safari planner based in Kenya. Let me take the stress of content creation away from your busy safari business by photographing and creating authentic content for your safari accommodation or service. Content that will make you stand out from the crowd, grow your reach and increase your revenue.

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Chrome 新的自动播放策略

最近看来自 Chrome 团队在 IO 2018上的分享《Build awesome media experiences on the web》。大概主要是说关于音视频在 Chrome 上的更新。其中业务团队需要及时关注新的自动播放策略，虽然在去年9月份 Chrome 团队就更新了博客《Autoplay Policy Changes》。 Chrome 会在 2018年的第二个季度，采取新的自动播放策略。自己在去年 2017年9月更新了关于最新的 Webkit 内核团队关于新版本的 Safari 的《MacOS High Sierra Safari 11限制了 video 自动播放》一些处理方法，而这些方法也可以运用到现在的 Chrome 自动播放策略中去。

页面中的视频处于静音状态下是允许自动播放的，大概这个产品交互可以参考微博的主站策略

如果用户与当前页面有任何的交互比如点击或者 tap 这样的行为，视频的自动播放将会允许(Safari 最早采用这个策略)

在移动端如果页面是被添加到桌面上，自动播放是云讯的。

在桌面端我们会根据用户的媒体参与指数 Media Engagement Index, MEI，后文会详细说这个) 来决定这个视频是否自动播放。

如何判断当前媒体是否允许自动播放可以参考下面代码:

Chrome 还强调了开发者可以通过 allow 属性来控制页面中通过 iframe 来控制引用页面内的媒体权限。比如 :

如果是同一个域下的自动播放默认是允许的

媒体参与指数 (Media Engagement Index)

MEI 是一个评估用户对于当前站点的媒体参与程度的指数，它取决于下面几个维度:

用户在媒体上停留时间超过了 7秒以上
音频必须是展示出来，并且没有静音
与 video 之间有过交互
媒体的尺寸不小于 200x140.

你可以在 Chrome 的地址栏输入:

查看一些视频网站的的 MSI 评估:

如果你是作为开发者，你也可以手动调整这个策略:

在地址栏输入上面的地址，可以进行手动的策略调整，进行测试。

You Can Speak "Hi" to Me in Those Ways

Top 2 Engagement Drivers by Country, from The Marcus Buckingham Company Global Engagement Index (Graphic: Business Wire)

LOS ANGELES--( BUSINESS WIRE )--While employee engagement has been consistently linked to positive business outcomes — including revenue, customer satisfaction and performance — never before has there been a methodological, calibrated global study of engagement across countries. Meanwhile, in the increasingly globalized nature of the Fortune 500, companies continue to struggle with fundamental people processes, much less implementing effective engagement measures that resonate in multinational teams. In fact, 64 percent of respondents in Sierra-Cedar's 2014-2015 HR Systems survey cites basic “business process improvement” as their top initiative.

The Marcus Buckingham Company (TMBC) , providers of integrated, personalized and strengths-based employee engagement and performance solutions, today announces the results of the StandOut Global Engagement Index (GEI), the first-ever standardized worldwide employee engagement study. To equip team leaders with actionable, accurate data needed to effectively manage global workforces, the Index uncovers the percentage of fully engaged employees across more than a dozen participating countries as well as the leading country-specific drivers of engagement today.

“Consistent, reliable data is at the core of every great people decision we make. TMBC is committed to filling a substantial gap in such data with the release of the StandOut Global Engagement Index, sharing both country benchmarks and actionable, country-specific engagement drivers for teams globally,” said Marcus Buckingham, Founder, TMBC. “The StandOut GEI results will be immediately embedded within our education, consulting and technology solutions for TMBC customers.”

Ranking of Countries with Most Engaged Workforces

Based on responses of employees across the 13 countries included in the Index, the U.S. and China reported the highest percentage of “fully engaged” employees (19% each), while Argentina and Spain show the lowest occurrence of such employees (13% each). “Fully engaged” employees constitute those who strongly agree with the eight engagement-related statements posed in the Index. Full country by country rankings are available at http://www.tmbc.com/gei .

“These findings point to two key themes in the state of engagement today. The first is that despite China and the U.S. leading the pack in terms of the most fully engaged workforces, even in those countries less than a quarter of employees are wholly committed,” said Jason Averbook, CEO, TMBC. “The second is the urgent need for country-specific resources — not a one-size-fits-all approach — to drive up the percent of fully engaged workforces, team by team and country by country.”

Leading Drivers of Engagement Vary across Countries

TMBC’s StandOut Global Engagement Index leverages eight predictor statements from TMBC’s Engagement Pulse . The eight statement survey, which TMBC is making available for all teams globally to take at no cost, are the result of decades of research with a focus on reducing both measurement and psychometric error, and are measured on a Likert scale (1-5). The StandOut Global Engagement Index is the only worldwide engagement survey to be calibrated according to both cultural survey-taking nuances (i.e. Mexican respondents tend to lean toward extremes of survey scales) as well as the variable weight of each of these eight statements across countries.

The Index reveals that in each country, despite significant cultural differences, the single biggest driver of fully-engaged employees is the statement: “I have the chance to use my strengths every day at work.” This finding holds even after applying the country-specific calibration, and is consistent with academic research over the past decade.

“Although corporate methods, behaviors and values vary by country—and by industry—the most powerful human need at work remains the same: ‘help me discover my strengths, and help me use them a lot,’” continued Buckingham. “Yet, the alarming reality is, by and large, companies continue to obsess about fixing employee weaknesses, rather than leveraging their strengths.”

The secondary factors driving engagement vary meaningfully by country, and can be found at http://www.tmbc.com/gei .

“Beyond responding to the call to play to employee strengths, leaders can finally inform their talent strategies – on a regional level – by these secondary engagement drivers to create higher-performing, committed teams,” added Averbook. “That’s why every TMBC solution is designed to increase the percentage of fully-engaged workforces, country by country, leader and leader, and team by team.”

Full StandOut Global Engagement Index results are available at http://www.tmbc.com/gei . TMBC plans to repeat the Global Engagement Index quarterly to help equip teams with the latest data and benchmarking when it comes to building the world’s most engaged teams.

For more details, visit www.tmbc.com .

Survey Methodology

The TMBC Global Engagement Index was conducted between April-May 2015 and translated into eight languages, each independently reviewed for accuracy. Administered via SurveyMonkey to more than 1,000 employees in 13 countries (United States, Britain, Germany, France, Canada, Brazil, Argentina, Australia, Mexico, China, Italy, Spain, and India). Past research suggested that individuals respond to survey items differently based on language and culture. To control for this “source effect” error, the items were adjusted across countries using a sub-set of items, the “calibration items.” Item means were calculated within each country, and then compared to the grand mean. This difference was treated as a cultural/language effect, and the engagement data were adjusted prior to further analysis.

Through past research, TMBC identified which of the eight items are the most powerful predictors of productive employee behaviors, and have the most explanatory power of overall engagement. These items were given additional weightings.

A multi-group confirmatory factor analysis (MG-CFA) of the eight Engagement Pulse items was completed to determine whether this new global sample had the same factor structure as previously established. These weightings were then incorporated into an algorithm. To generate the GEI scores, TMBC took the calibrated data by country and then applied this algorithm.

About The Marcus Buckingham Company

The Marcus Buckingham Company (TMBC) delivers integrated talent development solutions that are strengths-based and personalized to produce high-performing talent and optimized workforces. The company’s proprietary StandOut performance management solution encompasses education, coaching and technology tools that enable team leaders and organizations to fuel engagement and accelerate performance. TMBC clients include many of the world’s leading companies including Chevron, GE, HP, Intel, Starbucks and many others. For additional information, visit www.tmbc.com .

M Public Relations, Inc. (mPR) Maggie Habib 310.916.6934 direct [email protected]

Release Summary

The Marcus Buckingham Company announces the results of the StandOut Global Engagement Index (GEI), the first-ever standardized worldwide employee engagement study.

A Safari Engagement: The Most Enchanting Places to Pop the Question

Safari Engagement, Sherice Major

At Journeys by Emerge, we believe in creating moments that last a lifetime. Here's a carefully curated list of the most enchanting African destinations for unforgettable proposals. Get ready to make your engagement a story to be told for generations to come.

The Serene Oasis - Eden of Zanzibar, Tanzania

Escape to the Eden of Zanzibar for a proposal that's nothing short of magical. With ivory sands and azure waters, this secluded beach offers the perfect canvas for your love story. As the sun dips below the horizon, surprise your beloved with a private dinner, complete with candlelight and the soothing sounds of the ocean. The stage is set for an unforgettable moment. Let us plan the secret set up for you, with every detail executed to perfection. There wont be a second she doesn’t think YES!

Kilimanjaro's Embrace - Tanzania

For adventurous couples, embark on an epic journey together up Africa's highest peak, Mount Kilimanjaro. The sense of accomplishment as you reach the summit is matched only by the significance of your proposal. As the sun rises over the vast African landscape, drop to one knee and let the stunning views be the witness to your commitment. Then enjoy the moment together on a luxury safari, with spa pampers and memory making experiences.

Victoria's Secret - Victoria Falls Island, Zambia

Take your proposal to new heights at Victoria Falls Island, where you can stand on the edge of one of the world's most magnificent waterfalls. The falls, known locally as "The Mist that Thunders" create a breath-taking backdrop as you ask the most important question of your life. Opt for a private helicopter ride for an even more dramatic entrance to this natural wonder.

Hidden Gem - Anse Lazio Beach, Seychelles

If pristine beaches and turquoise waters are your idea of romance, then Seychelles' Anse Lazio Beach is the place to be. Its idyllic setting, framed by granite boulders and lush greenery, creates a paradise-like atmosphere for a beachfront proposal at sunset.

Ngorongoro's Beauty - Tanzania

Experience the magic of the Ngorongoro Crater, often called the "Eighth Wonder of the World." With its diverse wildlife and stunning scenery, it's a remarkable place for a proposal. Arrange for a private safari and propose against the backdrop of this natural marvel, making it a moment both of you will cherish forever.

Rwanda's Serenade - Volcanoes National Park, Rwanda

Take your proposal to new heights amid the lush landscapes of Volcanoes National Park in Rwanda. Trek to see majestic mountain gorillas in their natural habitat, and when you find the perfect moment, declare your love amidst these incredible creatures. It's an engagement story that's both wild and profoundly touching.

Romance in the Air - Sunrise Balloon Flight over Sossusvlei, Namibia

Thinking of popping the question while staying at the romantic &Beyond Sossusvlei Desert Lodge? Then hop on a hot air balloon at dawn for a soulful float across the Namib Desert – and a mile-high proposal (note – make sure that neither you nor your future fiancé are scared of heights!) As you drift amongst the clouds, the sun rises dramatically over the horizon, throwing hues of gold and rose across the vast sky, and revealing the mesmerizing landscapes of Sossusvlei. Whip the ring out whilst your other half gazes out across the sand dunes and upon landing, toast the happy news over a champagne breakfast.

Watercolor Dreams - Dhow Cruise in Zanzibar, Tanzania

There’s something truly special about being out in the open water – and never more so than aboard a traditional dhow sailing vessel in tropical Zanzibar. Used by fishermen for thousands of years, a cruise along the Swahili Coast equals a journey back in time. Surprise your other half with a private sunset cruise; as the sails sway in the evening breeze and you watch the sun set the horizon aglow, asking the life-changing question will come naturally. And if you really want to go all out, you can even hire a private butler or traditional Taarab musician!

Rovos Rail Romance - South Africa to Tanzania

A trip on Rovos Rail, often hailed as the most luxurious train company in the world, is high up on many a bucket list. Now, imagine proposing to your loved one whilst on board. Various routes are on offer, from three-day Pretoria to Cape Town trips, to an extensive 15-day journey all the way to Dar es Salaam. Life on board is luxurious to say the least; picture spacious suites complete with en-suite bathrooms, fine dining in an Edwardian setting, and special lounge cars from which to admire the passing landscapes. The general dress code is smart-casual, but you are expected to rock up for dinner in your finest garbs, meaning that you’ll really look the part when you pop the all-important question.

A Night in the Treetops - Lion Sands, South Africa

For a super intimate proposal in the middle of the bush, you can’t beat Lion Sands Game Reserve. Imagine a four-poster bed, high on a platform in a centuries-old Leadwood Tree, surrounded by cushions, twinkling lights, and a million stars. A guide will take you and an overnight bag (don’t forget the ring!) to the Treehouse at sunset where drinks and a picnic dinner await, and your only companions will be the nocturnal animals that roam below. It’s wild and authentic – and safe to say that a marriage proposal in this hopelessly romantic setting will be a hit.

At Journeys by Emerge, we specialize in crafting romantic and unforgettable experiences. If you're ready to make your proposal a once-in-a-lifetime moment in one of these breath-taking African destinations, contact us to start planning your dream engagement.

Honeymoon in Africa: Embarking on a Once-in-a-Lifetime Journey

Crafting unforgettable family memories on safari.

When Facebook blocks news, studies show the political risks that follow

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Aftermath of a knife attack at the Assyrian Christ The Good Shepherd Church, in Sydney

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Social media platform X said on Saturday it would challenge in court an order from an Australian regulator demanding the company remove some posts related to the stabbing of a bishop in Sydney.

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Romantic South African Safari Engagement Session
How to Improve Your Social Media Engagement
Romantic South African Safari Engagement Session
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Analysis of Social Media Engagement of 14 Different Industries Across

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COMMENTS

How to detect if Chrome/Safari/Firefox prevented autoplay for video?
Chrome uses something they call Media Engagement Index and you can read more about that here and their autoplay policy here. Safari developers made a post on webkit.org regarding this. Firefox seems to put it in the hands of the user to choose if it's allowed or not . Best practices Detecting if autoplay is disabled
AutoPlay Policies for Safari 14 and Chrome 64
MEI (Media Engagement Index) threshold has to be crossed (Desktop only) User has added a PWA (Progressive Web App) to their home screen (Mobile only) Auto-play in Iframes requires a delegation of the auto-play approval from the origin by adding a new HTML attribute "allow="autoplay"" to it. Otherwise, unmuted autoplay will be denied.
Safari Media Engagement Score?
Docs or debug information available for Safari Media Engagement Scoring? I'm working with WebRTC over the web. Code is very mature. The site is fully interactive. It is not an advertising application. With Safari Mobile iPadOS 15.1 and Safari Desktop 15.1 MacOS 12.0.1 I'm seeing a new issue. Occasionally video is not displayed to the user.
Autoplay policy in Chrome
Media Engagement Index. The Media Engagement Index (MEI) measures an individual's propensity to consume media on a site. Chrome's approach is a ratio of visits to significant media playback events per origin: Consumption of the media (audio/video) must be greater than seven seconds. Audio must be present and unmuted. The tab with the video is ...
Autoplay restrictions and WebRTC (Dag-Inge Aas)
Due to this, desktop browsers are now following Safari's example of disallowing audio playback. Most notably is Chrome, which rolled out new autoplay policies in Chrome 66. Chrome comes with a twist to the original model though, the Media Engagement Index. The Media Engagement Index (MEI)
video
Go to chrome://version/ and note the Profile Path. Close Chrome. Open the Preferences file in your profile folder with a text editor. Delete the media_engagement entry. Go to chrome://media-engagement to verify that everything has been cleared. Alternatively you can just remove the Preferences file altogether but this removes a bunch of other ...
How does Media Engagement Index (MEI) affect Autoplay on Chrome
The following scenario is possible due to the Chrome autoplay policy: when you first land on a web page, unmuted autoplay is not permitted. When you click through to another page, or refresh the page, unmuted autoplay is permitted, due to the additional user interactions which affect the MEI. You can check your MEI at chrome://media-engagement/.
Why are some autoplaying videos muted?
Autoplaying video policy for Safari Autoplaying video policy for Chrome Autoplaying video policy for Firefox Autoplaying video policy for Edge Note: Chrome will rely on your viewer's Media Engagement Index to decide if it will autoplay a video with sound or not. Chrome calculates a media engagement score which is highest on sites where media ...
Video Not Autoplaying
Safari. Autoplay (with sound) is not allowed. Muted autoplay is always allowed on Safari. Edge. The user has interacted with the domain (click, tap, etc.) On desktop, the user's Media Engagement Index threshold has been crossed, meaning the user has previously played video with sound. The user has added the site to their home screen on mobile.
Autoplay Pre-Seeding in Chrome
Autoplay Pre-Seeding in Chrome. Chrome's Autoplay policy uses a metric called Media Engagement Index (MEI) to determine whether or not to permit media to autoplay on a given site. MEI learns, locally, from a user's individual browsing behaviors, on a site-by-site basis, whether the user regularly consumes media on each site. This helps Chrome ...
New Chrome/Safari autoplay policy issues #264
Scenario. Have mediasoup-client connect to a room as viewer (no getUserMedia() called). Receive some audio and video consumers, create MediaStreams and attach them to audio and/or video HTML elements via elem.srcObject = stream. They can have autoplay attribute, or you may with to call play() via JS. You get no audio and blank video.
Why are Some Autoplaying Videos Muted
Example of an Autoplaying Video. The video below is set to autoplay, and you can try viewing it in different browsers to see how their different policies take effect. In Chrome and Safari this video will be muted, but in Firefox it will autoplay with sound. **Note: Chrome will rely on your viewer's Media Engagement Index to decide if it will ...
Safari, Chromeの自動再生ポリシー変更のまとめ #Chrome
Chromeの場合は、Safariよりも条件が複雑です。まず、デスクトップでは新たに Media Engagement Index（以下、MEI）という指標が追加されており、これに基いて自動再生の可否が変化します。他方、モバイルではホームスクリーンに追加されていることが条件になり ...
Conceptualising and measuring social media engagement: A ...
The spread of social media platforms enhanced academic and professional debate on social media engagement that attempted to better understand its theoretical foundations and measurements. This paper aims to systematically contribute to this academic debate by analysing, discussing, and synthesising social media engagement literature in the perspective of social media metrics. Adopting a ...
Conceptualising and measuring social media engagement: A systematic
Customer engagement. Although customer engagement research has increased theoretical and managerial relevance (Brodie et al., 2011; Hollebeek et al., 2016, 2019; Kumar et al., 2019; Vivek et al., 2012), to date, there is still no consensus on its definition due to its multidimensional, multidisciplinary and polysemic nature. Several customer engagement conceptualisations have been proposed in ...
(PDF) Conceptualising and measuring social media engagement: A
The spread of social media platforms enhanced academic and professional debate on. social media engagement that attempted to better understand its theoretical founda-. tions and measurements. This ...
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The Media Sustainability Index provides in-depth analyses of the conditions for independent media, and reveals benchmark insights into how media systems change over time and across borders. ... Visit this website from your computer for the best experience with the rich data of the Media Sustainability Index. ... Safari, or Edge web browsers. In ...
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Safari content written for safari experts by safari experts Prints Across Africa is an unique artisan photography & done-for-you content service that will help you attract your ideal safari client and increase bookings without ... 2-3 social media posts a week; community engagement; account monitoring; spam moderation *minimum 3 months; Book a ...
Chrome 新的自动播放策略
最近看来自 Chrome 团队在 IO 2018上的分享《Build awesome media experiences on the web》。大概主要是说关于音视频在 Chrome 上的更新。其中业务团队需要及时关注新的自动播放策略，虽然在去年9月份 Chrome 团队就更新了博客《Autoplay Policy Changes》。 Chrome 会在 2018年的第二个季度，采取新的自动播放策略。
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New Chrome/Safari autoplay policy issues #264

ibc commented Jan 17, 2019 • edited

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AJLoveChina commented Jun 9, 2020

Why are Some Autoplaying Videos Muted

Why don’t my videos autoplay with sound? ﻿

Which browsers support autoplaying video with sound?

Example of an Autoplaying Video ﻿

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Safari, Chromeの自動再生ポリシー変更のまとめ

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Conceptualising and measuring social media engagement: A systematic literature review

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2 Theoretical background

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4 An overview of social media engagement metrics research.

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Why don’t my videos autoplay with sound?

Example of an Autoplaying Video