Cautions more that Perils. Not so much that the results are wrong, but how they are implemented. This gets back to understanding how they exist in a process, and the implications of that. Consider frequent re-tests of results. Monitoring metadata. Good cautions, in Gartner.
The Perils of Algorithmic Marketing, By Martin Kihn
Inspired by results from retargeting, marketers are scrambling to stitch together customer data, unleash machine learning and deliver personalized experiences in display and video ads, websites, apps, watches and – soon – refrigerators.
But in our rush to hypertarget, marketers ignore the perils of personalization. Algorithms – or “algos,” as we say – can be intrusive and are prone to overuse. They build a commercial echo chamber and hone us down to our obvious features. Every time an optimization is made, some data is discarded. Usually, it’s data that doesn’t fit the model, which are exactly the features that make us unique. .... "
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