Why are Meta & Google moving away from digital attribution as a way of measuring marketing effectiveness?
Data issues are part of the story, but it’s bigger than that. This Google report gives some insight into their thinking. 1/9
thinkwithgoogle.com/intl/en-gb/fut…
#marketing
#advertising The big problem is that digital attribution models struggle to measure “incrementality”. If 1m people see your ad, and 1k buy your product, how many sales are genuinely incremental? The answer might be anywhere between 0 and 1k. Attribution models on their own can’t tell. 2/9

New research from Meta highlights the importance of long term advertising effects. Econometric analysis of over 3,500 campaigns reveals that 60% of the payback comes from long term effects, and only 40% from the short term.

#brand
#advertising
#marketing
#econometrics This means that short term measurement measurement systems (which include most digital attribution models) probably underestimate ROI by a factor of ~2.5.

Both Facebook and Google tell me that they are pivoting away from attribution modelling towards econometrics for evaluating effectiveness. Potentially, this has big implications. Attribution models over-estimate the short-term, direct effects of marketing. So they tend to favour performance marketing, direct response, promotions, etc.

Peter Field & I recommend that marketers use a mix of “brand building” & “activation” comms. Our research suggests the optimum split is usually ~60% brand, ~40% activation, but varies by context.

But why split brand & activation at all? Why not do both at once?

1/16 Definitions first.

By “brand building” we mean building & maintaining memory structures that have a lasting influence on consumer behaviour.

By “activation” we mean activating existing memory structures to elicit immediate behavioural responses.

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