Engagement analytics has a blind spot
Every X analytics tool reports engagement metrics: likes, retweets, replies, quotes, bookmarks, link clicks, engagement rate.
These numbers are useful for content strategy. A post with 200 likes and 50 retweets performed better than one with 10 likes and 2 retweets. Engagement rate benchmarks tell you whether your content is above or below average.
But engagement analytics has a fundamental blind spot: it treats all engagement equally. A like from a bot counts the same as a like from a VP at your dream client. A retweet from an inactive account weighs the same as a retweet from an investor with 100K followers.
The quantity of engagement matters for content strategy. The quality of engagement - who is engaging - matters for everything else.
What identity-level engagement reveals
When you add identity data to engagement analytics, the same numbers tell a completely different story:
Standard engagement report: "Your post got 47 likes, 12 retweets, and 3 replies. Engagement rate: 2.3%. Above your average of 1.8%."
Identity-level engagement report: "Your post got 47 likes. Three were from brand directors at companies you could work with. One was from an investor who has been researching your space. Five were from creators with 50K+ audiences. Engagement rate: 2.3%."
The first report tells you your content worked. The second report tells you your content attracted the right people. The action that follows is completely different:
- Standard: keep posting similar content
- Identity: DM the brand director, follow the investor, engage with the creators
Tracking X engagement beyond the basics
X provides several engagement signals, each with different meaning:
Likes - the lowest-friction signal. Someone saw your content and approved. Useful at scale but individually weak.
Retweets/reposts - stronger than likes. The person is willing to associate your content with their personal brand. Pay attention to who retweets you.
Replies - the strongest public engagement signal. Someone took time to write a response. Check replies from accounts matching your target profile.
Quotes - similar to replies but more visible. A quote from a high-follower account extends your reach significantly.
Bookmarks - invisible to you in aggregate but X counts them. A bookmark means "I want to come back to this." This is often a buying signal.
Profile visits - X shows total profile visits but not who visited. The gap here is significant - a profile visit from a VP at your target account is the strongest interest signal, but you cannot see it.
Tools for identity-level engagement analytics
X native (limited): Tap the like count to see who liked a post. This shows a limited list with no classification. Useful for spot-checking individual posts, impractical at scale.
Catch The Good Ones: Automatically identifies your fastest-growing post daily, fetches the people who liked it, and classifies each liker by job title, personality, and influence. You see a daily report of who engaged, filtered to match your criteria. This is the only tool focused on engagement identity rather than engagement volume.
Chrome extensions: "Who Liked/Reposted This Tweet" shows all likers in one view with CSV export. Useful for getting a complete list, but no classification.
X API (developer access): The `GET /2/tweets/:id/liking_users` endpoint returns likers programmatically. Requires developer access and does not include classification.
For most users, the practical choice is between manual checking (free, time-intensive) and automated classification (Catch The Good Ones, low cost, daily reports).
Acting on engagement signals
Identity-level engagement analytics is only valuable if it drives action. Here is a simple framework:
High-value engagement detected (brand director, investor, decision-maker):
1. Check their profile and recent posts (2 minutes)
2. Engage with something they posted - add genuine value (5 minutes)
3. If appropriate, follow them
4. After 1-2 exchanges, consider a warm DM
Medium-value engagement (relevant professional, growing creator):
1. Follow them if relevant
2. Engage with their content when it appears in your timeline
3. Build familiarity over time
Low-value engagement (bots, irrelevant accounts):
1. Ignore. Do not waste time.
The time investment is minimal - 10-15 minutes daily reviewing identity signals and engaging with the right people. The return is disproportionate because each engagement is targeted at someone who has already shown interest in your content.