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Why analyzing customer data takes a janitor

When it comes to analyzing customer data, we are often surprised to find it difficult and time consuming. Unless we've been doing it for awhile, we'll be bummed to discover inaccurate data, gaps and conflicts. No matter how small our business, it's never to late to start creating a customer database that speaks to us. Cleaning the data is not that much different from housekeeping services. We can put it off, but the problems will just pile up.

NY Times: For Big-Data Scientists, 'Janitor Work' Is Key Hurdle to Insights", 2014-Aug-17 by Steve Lohr

Data scientists, according to interviews and expert estimates, spend from 50 percent to 80 percent of their time mired in this more mundane labor of collecting and preparing unruly digital data, before it can be explored for useful nuggets.

“Data wrangling is a huge — and surprisingly so — part of the job,” said Monica Rogati, vice president for data science at Jawbone, whose sensor-filled wristband and software track activity, sleep and food consumption, and suggest dietary and health tips based on the numbers. “It’s something that is not appreciated by data civilians. At times, it feels like everything we do.”

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