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There’s quite a few odd things in their setup, whether it’s inflating numbers to seem cool or terrible inefficiency I can’t tell. Doing 80B predictions a day f

There’s quite a few odd things in their setup, whether it’s inflating numbers to seem cool or terrible inefficiency I can’t tell. Doing 80B predictions a day for 500,000 conversions would make this the lowest efficiency ad platform I’ve ever seen by several orders of magnitude.

vrih 7y ago
Those numbers aren't too far off. That's making a decision on every auction at 1M QPS, which is most of what is worth listening to in RTB globally. Most of those decisions won't actually involve much ML though, it'll be straight targeting rules matching and checking whether there is any budget. The actual attribution shouldn't be on 80B though. It's pointless analysing requests you didn't buy. There might be some value in using that data in ML to feed into a pricing algorithm, but it would be marginal and I doubt cost/benefit would ever stack up. it would technically be in breach of pretty much every SSP contract I've seen (although everyone does it).
- dialtone 7y ago
  It's a bit more complicated than that given that attribution looks at the past 30+ days of data (120 in NextRoll's case) to determine if any marketing activity happened and allows the customer to adjust the attribution window to whatever they want. There are 150B+ auctions each day, of those we participate in at least 80B and in those 80B there are at least 5 separate predictions, to determine the type of auction (1st price v 2nd price for example), determine the price likely to win, determine the likelihood of the placement being viewable, determine the likelihood of the user to click, determine the likelihood of the user to convert given that they click, and then we run these last 2 for each candidate (campaign, creative) that is eligible for the current auction. We obviously don't analyse the stuff we didn't buy but 80B IS the number of top level ML-generated prices from our system. The budgeting and targeting rules don't apply to the 80B number and they are slightly different systems.

vrih 7y ago

Those numbers aren't too far off. That's making a decision on every auction at 1M QPS, which is most of what is worth listening to in RTB globally. Most of those decisions won't actually involve much ML though, it'll be straight targeting rules matching and checking whether there is any budget. The actual attribution shouldn't be on 80B though. It's pointless analysing requests you didn't buy. There might be some value in using that data in ML to feed into a pricing algorithm, but it would be marginal and I doubt cost/benefit would ever stack up. it would technically be in breach of pretty much every SSP contract I've seen (although everyone does it).

dialtone 7y ago
It's a bit more complicated than that given that attribution looks at the past 30+ days of data (120 in NextRoll's case) to determine if any marketing activity happened and allows the customer to adjust the attribution window to whatever they want. There are 150B+ auctions each day, of those we participate in at least 80B and in those 80B there are at least 5 separate predictions, to determine the type of auction (1st price v 2nd price for example), determine the price likely to win, determine the likelihood of the placement being viewable, determine the likelihood of the user to click, determine the likelihood of the user to convert given that they click, and then we run these last 2 for each candidate (campaign, creative) that is eligible for the current auction. We obviously don't analyse the stuff we didn't buy but 80B IS the number of top level ML-generated prices from our system. The budgeting and targeting rules don't apply to the 80B number and they are slightly different systems.