Test content formats the way you test keywords
A feed post has no query behind it. What carries it is the shape — and shapes transfer between categories far better than topics do.
For: B2C
Inside this
- Train a research feed until it shows you your category all day30m
Twenty minutes of deliberately watching and saving the content around your category buys you a permanent, self-updating swipe file.
- Collect a dozen formats, and keep only the ones you can remake in 15 minutes1h
The two-hour video that gets 300 views is what kills the habit. Cheap to remake is a selection criterion, not a compromise.
- Post three different formats a day, not three takes on one5h
Five days of one format tells you almost nothing. Different shapes on the same day is the only way the numbers mean anything.
- Read the failure, not just the view count45m
Walk one ladder: views, then engagement, then clicks, then signups, then people who stayed. The rung it stops on is the thing to fix, and a post that stops at views is not a win.
- Make twenty more of the one that worked before inventing another5h
You have seen every post you ever made; your audience has seen roughly none of them. Boredom is not a signal that a format is spent.
- Hand the winning format to someone else to produce2h
A proven format is a brief anyone can follow. This is the difference between a channel and a hobby you personally sustain.
- Put five small creators on the format you already proved8h
Hire for whether they can stop a scroll, not for follower count, and hand them your winners. A creator inventing your strategy is a creator running your first experiment again.
- Label the synthetic ones, and never let one give a testimonial15m
If the face, voice or scene is generated and meant to read as real, tick the platform’s own AI box — YouTube, TikTok and Meta all require it and detect it anyway. The harder line is separate: a person who does not exist cannot describe using your product. That is a fabricated testimonial, a label does not cure it, and the FTC rule names AI-generated ones explicitly. The same goes for a generated before-and-after: an AI transformation shows a result your product did not produce.