The state of the analytics union


Gartner recently published a study "Marketing Data and Analytics Survey 2020" that finds that most clients aren't getting the value they expected from their analytics implementations.

The results of the study are not entirely surprising and represent a huge opportunity for analytics experts. I have first-hand knowledge of multi-billion dollar companies that have purchased Adobe Analytics (AA) but are grossly under-investing in qualified resources to implement and support the platform. 

They hire resources that are not required to be experts in AA with the expectation that they can learn on the job, just to save a few dollars in hourly rates. Big mistake! It’s like buying a Ferrari and then filling it up with regular gas and taking it to the local mechanic for service.  Upskilling in-house talent can only work if you have core expertise in-house (or contracted). But we’re often seeing clients who are lacking that in-house expertise and leaving their resources to fend for themselves. 

We, the analytics community, need to continue to coach these clients on how not to be penny wise and pound foolish. 

Secondly, the human race is still learning to interpret data correctly and trust what it’s telling us (confirmation bias). It’s human nature to second guess the machine. For example, there are many studies that show that machines are able to diagnose cancer with a higher level of certainty than doctors. However, patients still trust doctors more than they trust machines. Apparently, because machines can be wrong. Except that doctors can be wrong more often (they are human, after all).

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