Facebook’s Latest Error Shakes Advertisers’ Confidence
wsj.com
wsj.com
So, the thing here is that FB's tool for helping advertisers measure the effectiveness of their ads was producing falsely positive results for an entire year, and nobody noticed.
This is a shocking indictment of multiple teams and their code quality and QA, and is going to really, really damage their advertiser relationships for many years to come.
The reason that this matters is that the only real way to measure effectiveness of different strategies on FB is using this tool, as FB can actually match users based on their conversion probability, allowing for valid tests.
> each of equal repute
This seems incredibly hard, how would you accomplish this?
So, the whole point of the conversion lift tool is to track all conversions associated with your ad (i.e. post view or click on the platform), while having a rigorously balanced control group.
This allows you to estimate the incremental impact of your ads, which is what you want in order to make budgeting decisions.
Your proposed design doesn't appear to accomplish any of this, can you clarify what you are attempting to accomplish with this design?
So, for my money, I would have the following concerns around this design: 1) You're actually assuming that the audiences reached by platform A and B are identical
2) You're assuming that Platform A and Platform B are identically effective at showing your ads to people
From my experience, neither of these things are true (unless you run untargeted CPM ads, which seems unlikely in a digital world). Can you explain how this works?