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God yes.
Only thing we have found testing useful for is setting the adstock length (better creative = longer adstock = stays in memory longer) in a model, which is a pretty fundamental thing to know, with a longer adstock you have to deploy less ratings to get the same effect, and there tends to be a correlation (albeit weak) between testing and adstock length.
Yep, econometrics only works as well as the data that goes into it ( and the person running the analysis), and Covid is certainly leading to some interesting debates as to the impact, thankfully there are lots of data streams available which does help, we have a lot of success of using Google trends data on a basket of key terms to understand the shape of the consumer response. The main complicating factor is that most brands responded to Covid happening, normally in a way that has not been seen before, so it’s hard to know what is the effect of Covid is and what the effect of the changes in response to Covid, if that makes sense? Good example is we have a client who did a 2 week free trial, when Covid hit they got a massive rush in sign ups, so they changed their offer to 50% off, which changed sales, but it’s difficult to unpick what is caused by Covid and what is caused by the change in offer.