#APC2014 Data Scientists Are The Rock Stars

Gail Chiasson, North American Editor

One of the best sessions at the Scala Americas Partners Conference in Austin last week was on the topic of analytics and big data, run by Scala’s Amy Wilson, product manager, and Stefan Menger, vice-president of analytics.

“The retail market is being driven by analytics,” said Wilson. “Retailers have data but they aren’t using it. They know they need it, and are putting money into getting it. A good 69% know that they have to use it, but they aren’t taking advantage of having it.

“Why? They don’t know how to use it and don’t have people on board who know how to use it. Those who know anything about it are usually far from the customers.

“They must get marketers and data scientists on board. Chief marketing officers learn more about their markets and customers through data, and in using it, see true results-driven ROI. But they are getting overwhelmed because data has gotten so big.

“Today, the data scientist is the rock star. These are super freaking smart math guys and you have to get them on board.”

Wilson said that data is gathered from digital signage and magic mirrors, from consumer apps, from who is buying what and why, from ecommerce and emails sent, and all sorts of consumer behavior and how it is influenced.

“Big data is a lot of little data,” said Wilson.

These data scientists are able to comb through the data and suggest the optimized content and other actions to be taken.

Menger gave a Scala-suggested optimization outline that involves:

  • assess the business situation;
  • define objectives and goals;
  • select suitable digital content (based on best guess given the analytics and based on optimization);
  • display and measure;
  • analyze;
  • then optimize.

He gave examples of successful cases involving analysis of big data and following such a schedule. One was with Panos, a fast food restaurant chain in Belgium and The Netherlands that wanted proof that digital signage increased sales. Using a small group of its 250 restaurants, it added a soft drink to a menu item and saw sales increase 2.5%. Then, looking at the dwell time for consumers seeing the offer and changing the length of time of the commercials and adding subtle motion, it saw sales increase 7.75%. It was noted that weather was always a factor and their analysis was that the changing factors were exposure time and motion, and then were able to measure the optimized campaign.

Another case was with Last Call Studio and how, after a display of dresses, shoes and handbags, sales of dresses and shoes increased but not those of handbags. An analysis of that showed that there were less commercials seen of the handbags and that all stores didn’t have the stock in store. Clips of the handbags were increased and inventory was rearranged among stores. The campaign was then optimized and sales resulted in a 30% increase.

Menger told the Scala partners that, when testing, always concentrate on a limited number of stores and products, and also watch for timing, weather and such factors when optimizing a campaign.

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