Analytics
What the retention curve said about the shoot
Using watch-time data to plan production, not just to grade it.
- Client
- Meridian Interiors
- Year
- 2026
- Role
- Analysis, production planning
- Stack
- Meta Ads, YouTube Analytics, Premiere Pro
- 30 Curves analysed
- -25% Shoot day length
01 The brief
A production budget being spent on the parts of the video nobody watched.
02 The brainstorm
Retention graphs are normally used as a post-mortem. Read across thirty videos instead of one, they become a shot list.
We overlaid the curves and found the drops landed on the same three things every time: establishing wides, logo stings, and any shot without a person in it. The rises landed on faces and on hands doing something.
So the next shoot day was planned from the graph: no establishing shots at all, twice the hands, and the logo moved to the end where it costs nothing.
03 The build
Thirty retention curves normalised to length, annotated by shot type, turned into a one-page production rule sheet.
04 The result
Shoot days got shorter and cheaper because we stopped filming coverage the data said was never watched.
