Product · Performance Scoring
Know what will work before you spend a rupee.
Every variant is scored on predicted hook strength and ROAS before it launches - then the model learns from what actually happened.
The problem
Most creative decisions are still a guess
Which hook wins, which cut to scale, which variant to kill - without a predictive signal, teams find out only after real budget has already been spent finding out.
How it works
Scored before launch, learned after
Every variant scored
Hook strength, predicted retention and projected ROAS are estimated before spend.
Compare side by side
Scores are ranked so the strongest concepts are obvious at a glance.
Machine trial on the top scorers
A small-budget live test confirms the prediction before full scale.
Results feed the next score
Live performance is fed back into the model, so scoring improves with every campaign.
Signals that build into one score
Four layers, one confidence score
Each layer sharpens the prediction - by the time a variant launches, the score reflects real signal, not a guess.
Hook strength
Predicted stop-scroll rate from the opening frame and first line.
Retention curve
Where viewers are predicted to drop off across the full cut.
Projected ROAS
Modeled return based on category benchmarks and past spend.
Live feedback loop
Real results feed back in, sharpening the score for the next brief.
Proof point
Trained on real ad performance
FAQ
Questions, answered
What is the score actually predicting?
A blend of predicted hook strength (stop-scroll rate), retention curve, and projected ROAS based on patterns from past campaigns in similar categories.
Does the model improve over time?
Yes - live results from every launched campaign feed back into the scoring model, so it's tuned to your account's actual performance, not just category averages.
Is a machine trial required before full launch?
It's the default recommendation on Growth and Scale, but you can skip straight to full launch at any time.