When is “Good” Good Enough?

This article was published in full here at ​martechadvisor.com. Here are some key passages and takeaways.

  • If your goal is people-based marketing and delivering addressable ads to just those most likely to be interested in your product, or tailoring messages to the needs of individual customers, then accuracy should be a concern...
  • Like brain surgery, mistakes in identity resolution are surprisingly common. Accuracy can vary greatly based on selected approaches, use of deterministic vs. probabilistic methods, and the match key used.
  • Likewise, scale should matter if you want to leverage your customer data to employ more precise, people-based marketing and measurement with your campaigns. I’ve seen match rates against first-party data files and digital identifiers as low as 15 percent. Why even step up to bat with your advertising dollars if, at best, you’ll only be able to employ precision marketing with one out of every six or seven of your customers?
  • The scale at which identity platforms are able to accurately map customer data to digital IDs also varies greatly from one vendor to the next. It’s not unusual to see scale differences between vendors of 5X — not five percent, but 5 hundred percent! If you’ve developed and tested a campaign that you know generates incremental sales lift of $200 thousand, imagine if just switching indentity resolution technologies could grow that amount 500 percent with little or no change in your cost? That would improve gains by $800 thousand!

There's much more in the article, including Chuck's theory on why marketers sometimes don't press for better accuracy and scale, plus a three-step approach to filling gaps in accuracy and scale on your people-based marketing and ads.  Read the full article here.


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