Learning Outcomes
You will learn that there are two types of engagements on TRAC: engagements as an actual piece of content and engagements as counts.
You will learn how the engagement metric differs based on the data sources that you're looking at.
What is an Engagement?
An engagement on TRAC is a reaction to a post, for example a repost, a share, a reply or a comment, and this varies depending on the platform or data source.
Before we delve into the types of engagements we collect, firstly we need to distinguish how we view and store these engagements on TRAC.
Engagement as a piece of content
The first type of engagement data in TRAC refers to engagements that are stored as actual pieces of content. This means you can perform a full-text search on these items within your results. Examples of this type include reposts, replies, and comments. In TRAC, reposts and comments are treated as distinct types of posts. As such, when calculating the total volume of data collected in your search (and its changes over time), these engagements are included in your overall mention volume.
In other words: Total Volume of Mentions = Posts + Engagements
Where:
Posts include original pieces of content, such as X posts or blog posts.
Engagements include reposts, comments, and replies, all of which are indexed as individual content items.
This ensures that TRAC captures a complete picture of the conversation, accounting for both original posts and the interactions that amplify them.
Engagement as a count
The second type of engagement data in TRAC refers to numerical engagements, i.e. metrics that represent counts rather than actual content you can view or read. These include figures such as the number of shares, number of comments, or number of likes. Because these are simply numerical values (and not physical pieces of content, like posts or comments), they are stored as counts rather than as content objects.
As a result, these engagement counts are not included in the total data volume collected in your search. This means they will not appear in the Key Numbers charts or the Overview Mentions graph.
This behavior is intentional and relates to how Pulsar indexes different types of data. Including metrics like comment_count, like_count, and share_count in your total data volume would significantly inflate the dataset; leading to inaccurate representations of your actual content volume and data usage.
Now that we've explained the 2 types of engagements that we collect, below is a breakdown of the types of engagements that we collect for each data source on TRAC.
X Data
We collect reposts, replies, and no. of likes. However, as noted above, the number of likes is stored and displayed separately and is not summed up to the total engagements in the Key Numbers chart or the Timeline charts. Only reposts and replies are factored into this metric, and therefore will count towards the overall volume of data collected in a search.
Note:
When in the Feed Results, Likes are displayed separately.
For historic data, we collect matching replies, that is, replies containing your search terms.
For real-time data, we collect all replies, regardless of whether they contain the search terms.
Facebook Public Pages in a Panel Search
In a Facebook Page Panel search, we collect the following:
Actual Comments (sampled)
No. of Comments
No. of Likes
As noted previously, the no. of likes and the no.of comments are indexed separately, and not summed up to the total engagements in the Key Numbers chart, or the Timeline charts. Only the actual comments are factored into the volume metric, and therefore count towards the overall volume of data collected in a search.
Note
When in the Feed Results, Likes are displayed separately.
The no. of comments might differ from the actual comments because the actual comments are sampled to first 100 comments, during each fetching cycle.
Facebook Public Pages in a Topic Search
In a Facebook Topic search, we collect are the no. of likes. And if available, we also collect the no. of comments. We are unable to collect the actual comments. And as mentioned previously, the no.of likes and no.of comments, are not factored into the Key Numbers chart or the Timeline charts, and therefore are not counted towards the overall volume of data collected in your search.
Note
When in the Feed Results, Likes are displayed separately.
Online News, Blogs, Forums & Review Sites
Engagements on these channels are the no.of social shares that the article has received on Facebook. In other words, this is the number of times the article URL has been shared on Facebook. For Reviews, we also also get the Review rating that has been left by users on the site. And similar to the no. of likes and no. of comments, the no. of social shares is not counted towards your overall volume of mentions.
Instagram Data
Following changes to Instagram data in Spring 2026, we only collect the no. of likes and the no. of comments, not the actual comments that a post has received. So, for Instagram, when looking at the total engagements from Instagram in the Key Numbers chart, this will always show 0. To view these metrics, navigate to the Feed → Results section, where you will be able to see the no. of likes count and no. of comments for each post. These counts are displayed as separate metrics and are not included in the overall "Engagements" total.
The only exception to this rule is if you are using the TRAC functionality which allows you to collect tagged mentions of your brand. This is a common practice on Instagram, where a user tags your business or brand in a photo or video. In this case we are able to collect the actual comments, in addition to the no.of comments and no. of likes.
Global Radio
For Radio we don't collect engagements. We have the Media Reach, Duration and AVE.
Global TV
For TV we don't collect engagements. We have the Media Reach, Duration and AVE.
Global Podcasts
For Podcasts we don't collect engagements. We have the Media Reach, Duration and AVE.
For Print data we don't have engagements. We have the Circulation figure and AVE.
Threads
For Threads we collect the no. of likes and the no. of replies for each post.
Twitch
For Twitch engagements, we only collect the no. of video views for each video.
For Pinterest, we collect the no. of re-pins or no. of saves and the no. of comments left on a post.
Discord
For Discord, engagements are only collected on Thread type posts. Otherwise, all comments are considered posts in their own right.
Threads are a unique type of conversation on discord that collect all replies within a singular grouping rather than in-line with the rest of conversation as most of discord functions. It's not an incredibly common conversational tool within discord servers but it depends on the server!
YouTube
YouTube provides an engagement count based on the total no. of comments on a video, and also the actual comments that match your topic search. As such, the total number of comments and the actual comments may differ, and that's because the actual comments will be fewer, since we are only indexing comments that only contain your keywords.
VK
For VK engagements, we collect the no. of comments only. We do not collect any other type of engagement metric.
Limitations of Engagement Metrics in TRAC
While TRAC provides detailed per-post engagement data, it does not currently offer built-in features to aggregate engagement metrics across multiple posts. For example:
There is no chart or widget to display overall monthly engagement totals.
Custom charts cannot sum engagement metrics across posts.
Workarounds for Aggregating Engagement Data
To analyse aggregate engagement metrics over time, you can use the following methods:
Export Data:
Export content-level data from TRAC (e.g., via the Feed → Results section).
Use spreadsheet software or other tools to calculate aggregate metrics externally.
Use the API:
Leverage the Pulsar API to export engagement data.
Import the data into a third-party analytics tool for advanced aggregation and visualisation.
When in the Feed Results, Likes are displayed separately.- Navigate to the Feed → Results section to view the no. of likes and no. of comments for each post.
We hope you enjoyed reading this article! 📚
If you have any questions or would like to learn more, please don't hesitate to reach out to our support team via live chat. 🚀