Calculating each of the predictive variables, and the final eCPM value, is very complex and beyond the scope of this article – but to make it easy to understand, let’s bring it to life with a simplified example.
eCPM = ƒ(CPC or COS or CPO, pCTR, pCR, pAOV)
Three shoppers who have all previously browsed your website are now individually browsing a publisher website. The Criteo Engine is about to bid for ad inventory, having determined that it would be valuable to display your campaign to these shoppers. When setting your campaign up, you’ve decided on a Cost-Per-Click of one dollar.
eCPM = ƒ(1, pCTR, pCR, pAOV)
Predictive Bidding uses its predictive models and data on the shoppers, context, and inventory available to determine each shopper’s chance of engaging (pCTR) and converting (pCR), and their likely order value (pAOV).
Shopper 1
pCTR = 0.5%, pCR = 10%, pAOV = $100
Shopper 2
pCTR = 0.75%, pCR = 6%, pAOV = $200
Shopper 3
pCTR = 1.25%, pCR = 6%, pAOV = $75
These figures plug into the formula to provide the eCPM values for each shopper, which shows what bid amount they are worth to you.
Shopper 1 eCPM = $5
Shopper 2 eCPM = $9
Shopper 3 eCPM = $5.62
Remember, this is a very simplified example to demonstrate the concept of eCPM. Real-world situations are considerably more complex, with Predictive Bidding’s machine learning technology using a vast dataset and real-time shopping signals to calculate the formula’s predictive variables and additional parameters.
These calculations happen almost instantaneously to reach shoppers in the moment. For each impression, Predictive Bidding takes only 10 microseconds to choose a relevant campaign to show, calculate all variables plus the eCPM value, and place the correct bid at inventory auction!