Ad & marketing teams
CTR Prediction
Predicts which creatives and placements will actually get clicked, before you spend on them.
A machine-learning model that predicts click-through rate for ad creatives and placements, so budget goes to what will actually perform instead of being decided by gut feel.
Spend goes to the creatives most likely to be clicked, not the ones that just looked good in the meeting.
The challenge
Deciding which ads and placements to back is mostly guesswork until the spend is already out the door. By the time CTR comes in, the budget is gone.
What we built
- Learns from historical creative, placement and audience data.
- Predicts CTR for new creatives and placements before spend.
- Ranks the options so budget goes to the strongest.
- Sharpens as more performance data comes in.
How it works
- 1
Feed in historical creative and performance data.
- 2
The model predicts CTR for new options.
- 3
Budget follows the highest-ranked creatives.
Key capabilities
CTR prediction
Estimates click-through before you spend.
Creative ranking
Ranks creatives and placements by likely performance.
Budget guidance
Points spend at what will actually perform.
Learns over time
Improves as new performance data arrives.
The payoff
- Budget aimed at creatives that will perform.
- Less spend wasted on weak placements.
- Decisions backed by data, not gut feel.
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