It recently surfaced in a story by AdExchanger and The Wall Street Journal that Facebook had, for a year, been feeding incorrect data to advertisers paying to display adverts across Facebook's network using their lift conversion tool.
Specifically, the bug was caused by a data pipeline migration in August of last year that affected the way in which certain impressions were logged into Facebook’s conversion lift systems.
As a result, Facebook undercounted the number of conversions from people who were exposed to impressions on Facebook apps.
In other words, Facebook miscalculated the number of sales that came from people that saw an ad, which is a key ratio necessary to measure incrementality, because it’s used to calculate other metrics, including conversion lift percentage, which is the difference in conversions between the people who did and didn’t see ads during a test.
In finding and fixing this issue, they also surfaced two other bugs affecting data quality for a period of a few months.
During Facebook’s investigation into the original bug, it also came across and patched two additional, separate and, it says, “smaller” technical issues that affected conversion-based metrics for some lift tests.
This follows not long after LinkedIn fessed up to their own measurement fuckup that saw 418,000 advertisers served incorrect data over a period of two years.
In a blog post, the Microsoft Corp.-owned company said its engineering team found and fixed two measurement issues in its ad products, which led to overreporting of video views and ad impressions on sponsored-content campaigns. The bugs affected more than 418,000 advertisers over the course of more than two years, it said.
I recently wrote about the problem marketers have with bad data and their inability to recognise and understand the data they're being presented from opaque third parties. Not necessarily through any real fault of their own, I hasten to add.
These most recent examples are particular pernicious. Marketers rely on data from Facebook, LinkedIn and similar to optimise campaigns and to assign limited budget. In both cases, incorrect data could have, and probably did have, a tangible effect on how marketers allocated their budget. This lead to Facebook and LinkedIn directly profiting from these fuck-ups.
I can't say this enough, but marketers without a healthy degree of scepticism are going to fall victim to this more and more frequently. If you let garbage data define your media strategy, you'll get garbage results.