Step by step
- Predict before you post. Note the moment you think is weakest and how well you expect the opening to hold. It has to be written down before the result exists, or hindsight rewrites it.
- Wait for the curve to settle. Give the video a few days. Early retention on a small sample moves a lot.
- Compare moment by moment. Did the drop happen where you expected? Did the hook hold better or worse than you thought?
- Adjust the instinct, not just the video. If you keep overrating your hooks, spend more time on openings before filming. The goal is a better predictor, not one better video.
How Flurra does this
Flurra's pre-post scan gives a hook score, a drop-off risk, and flagged moments. When you import the post's retention graph later, Flurra checks each one: whether the drop was confirmed, whether the hook was overestimated or underestimated, and whether a flagged moment matched where viewers left.
Common questions
- Are AI retention predictions accurate?
- Treat them as estimates. That's exactly why comparing them with the real graph matters: it shows you where the estimate and your audience disagree.