Retention analytics
Know exactly where
viewers stop watching.
The AI video retention analyzer lines up your real retention curve with a scene-by-scene read of the edit — pacing, cuts, captions, visuals, voiceover — and tells you what to change.
One feature inside Global Creator Studio — discover, create, publish, analyze, improve.
Upload or connect
Two ways to get a video analyzed.
Connect an account for real numbers, or upload a file to get the AI read of the edit before anyone sees it.
Connect an account
Link YouTube or another supported platform to pull your own retention data.
Or upload a file
Drop in a finished cut, or a rough one, straight from your machine.
Analysis runs
The video is broken into scenes and read frame by frame alongside the retention curve.
Review and fix
Work through flagged moments and apply the suggested edits.
Retention graph
The curve, second by second.
See the full audience retention graph with watch time, average view duration and the exact timestamps where the line bends. Hover any second to see the frame that was on screen when viewers made their decision.
Start creatingExample read
Hook score
82 / 100
3s hold
91%
30s hold
64%
Avg. view duration
4:12
AI scene-by-scene analysis
What the AI actually looks at.
Every scene is measured on the things that move attention, so a drop-off gets an explanation instead of a shrug.
Pacing
Scene duration, cuts per minute and how long a single shot holds.
Visuals
Motion versus static images, B-roll coverage, transitions and visual change rate.
Audio
Voiceover speed, pauses, music energy and moments of dead air.
Text
Captions, on-screen text density and how much information lands per minute.
Drop-off detection
A real drop-off, explained.
Retention dropped 13% at 1:42 after the video switched from moving footage to a static image for 11 seconds.
AI recommendation
Replace this section with 3–4 shorter visual clips.
Each flagged moment names the timestamp, the size of the drop and the change in the edit that lines up with it.
Retention spikes
Learn from the moments people rewind.
Spikes matter as much as dips. When the curve goes back up, viewers rewatched something — a reveal, a number on screen, a visual gag. The studio marks those moments and describes what was happening, so you can build more of them into the next script.
Start creatingSpike report
Rewatched segments with their timestamps
What changed on screen at that second
Whether the spike follows a reveal, a cut or a caption
Patterns repeating across your recent videos
Hook score
The first fifteen seconds, graded.
Most of a video's fate is decided before the intro ends. The hook score rates how quickly the promise lands, how fast the first visual change arrives and how much of the audience is still there at three, ten and thirty seconds — with a rewrite suggestion when the opening drags.
Start creatingHook breakdown
Promise clarity
Strong
First visual change
0:02
Words before payoff
34
10s hold
78%
Predicted retention
Check the edit before you publish.
Run an unpublished cut through the same analysis and get a predicted retention profile, so the weak stretch gets fixed before launch rather than after.
Forecast curve
An estimated retention shape for the current edit.
Risk moments
Sections most likely to lose viewers, ranked by size.
Compare cuts
Run two versions and see which structure holds better.
Clear labelling
Predictions are shown as forecasts, never as measured analytics.
Data honesty
Your videos versus public videos.
The difference between measured and estimated is always visible on screen.
Fix automatically
From diagnosis to a finished edit.
A flagged problem comes with a proposed change. Approve it and the studio applies the edit — swapping a static stretch for shorter clips, trimming a slow opening, tightening a scene — then hands you the updated cut to review, caption and schedule.
Start creatingThe loop
Flagged moment with the measured impact
A specific proposed edit, not generic advice
One-click apply, with the original kept intact
Re-run the analysis on the new cut
Export or send straight to your calendar
FAQs
Retention analysis, answered.
What does a video retention analyzer do?
It maps how much of your audience is still watching at every second, then explains what happened in the video at the points where people left or rewatched.
Where does the retention data come from?
For videos on accounts you connect, retention comes from that platform's own analytics where the platform makes it available. Nothing is guessed when real data exists.
Can I analyze a competitor's retention?
No. Retention curves are private analytics that only the account owner can see. For public or competitor videos the studio analyzes the video itself — pacing, cuts, hook, captions, visual changes — and shows estimated signals, clearly labelled as estimates.
Can it predict retention before I publish?
It gives a predicted retention profile based on the structure of the video and how similar videos have performed. It is a forecast to guide edits, not a guarantee.
What is the Fix automatically workflow?
Where a problem has an obvious edit — a static stretch, an overlong scene, a slow opening — the studio proposes the specific change and can apply it in the editor for you to review before export.
Stop losing viewers
at the same moment every time.