The world of marketing is much deeper than you make it out to be. Brands spend millions - obviously if someone smart came in and did testing to prove it was ine

The world of marketing is much deeper than you make it out to be. Brands spend millions - obviously if someone smart came in and did testing to prove it was ineffective thus move that money elsewhere. You can easily test branding dollars with things like brand lift studies, but I’ll skip over branding. The majority of small business and good chunks of large companies ad spend is spent on performance marketing. These campaigns have strictly enforced goals of return on ad spend (or sometimes net profit return on ad spend). When a new client starts running big budgets they run incremental alit y tests with their internal data science team, a neutral third party vendor (paid regardless of the outcome), and with the platform their spending money on. Each team shares their analysis but brands usually just ignore the platforms numbers. The advertiser can determine in their own, with legit statistical analysis, whether purchases would’ve occurred even if they hadn’t seen an ad. I don’t work on one of those teams, but I think it’s basically you spend 80% if your budget like normal on 80% of users. Then on 20% of users you use the same targeting but serve 1 single blank ad. Then you compare how the test and control groups make purchases, and how much of a lift in purchases the advertising drives. They also compare the user buckets before even doing the test to ensure users are evenly split so each group was making the same amount of purchases on average before the campaign begins. They remove outliers, etc. It’s not a bunch of rich old established men in a room high giving themselves, it’s data scientists who don’t at all trust the guys spending their money. So they test the shit out of it over and over. All of the raw data can be seen by the advertiser, and they track each individual impression, click, etc. that data can also be filtered through vendors to identify potential fraud, brand safety, etc. I’ve had more than a couple client run an incrementality test and then stop spending on the platform because the results were too low. But I’ve had many many more be happy with their own internal analysis and increase budgets, then run another test at that budget level. I have clients who only pay us if we spend $1 and they get $2 in incremental revenue from users who their data science team would not have purchased without the ad. Those teams don’t care if they spend money, and they even get bonused on increasing incremental revenue so they constantly test new vendors and move spend to whoever performs the best.