eBay and Redbox on their predictive analytics play

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eBay and Redbox shared their uses and plans for predictive analytics at the Predictive Analytics World Conference in Chicago recently.

Ashok Ramani, Product Lead in Big Data at eBay, said they have a deep understanding of their customers by virtue of their massive collection of consumer data. "That understanding includes customers' payment data--eBay owns PayPal--and data from multiple shopping sites, as well as behavioral data, bidding, and third-party demographics," writes Ellis Booker in his post in DataInformed.

"The new program will layer on a predictive model, which can be transferred to a merchant partner without disclosing the eBay customer's personally identifiable information for use in real-time, targeted content, pricing, and marketing messages," continues Booker. "The program is being tested in a limited pilot with existing eBay partners beginning this month, running for four to six weeks, Ramani said."

"For instance, a merchant site can be advised that the arriving shopper belongs to an 'adventure-seeker' customer segment--information the merchant can then use to create a dynamic, personalized shopping experience for the shopper, wrote Booker.

"But eBay's new program will go further than a one-time transfer of a predicted segment to a partner. It will establish a feedback loop that should improve the prediction model over time."

Redbox, on the other hand, is struggling with correctly detecting trends in the face of rapid growth.

"'Growth was "clouding the data,"' said Taly Kanfi, Manager, Strategy and Analytics at Redbox. Specifically, trends such as same-store sales couldn't be examined using a simple linear model.

"To address this problem, Kanfi began by identifying October 2009 as a turning point in the company's growth and market share," reports Booker. "She then created a model that treated 2008 as if the company had 35,000 kiosks, thus normalizing the data from 2008 onward. 'This let us get value out of our historical data,' she said, adding that, 'A little bit of analytical sophistication goes a long way over standard reporting.'"

Read the entire post for more details. For now, I am encouraged to see a slow but steady uptick in predictive analytics use in these companies and others. Great promise has always existed in this class of analytics but it's only a promise until it's realized.

Predictive analytics--especially when combined with automated actions and machine learning--is one of the most powerful tools at our disposal. A future made less uncertain is a future that can be better managed for greater profit.

For more:
- see the DataInformed post

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