Williams-Sonoma uses big data to zero in on customers

To target individual customers, Williams-Sonoma needed data from a broad swath of sources, a Hadoop platform, and a dashboard to make sense of it all

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The marketing attribution SaaS solution that Williams-Sonoma selected was created by UpStream. The UpStream development team employs a multidisciplinary approach combining backgrounds in business, marketing, computer science, math, physics and statistics to solve complex business problems.

To handle both the big data and data silo challenges, UpStream's hosted service uses Hadoop as both ETL (extract-transform-load) middleware and as a distributed processing data store. Hadoop is used to prepare the data from marketing programs and score consumers' behavior: Consumer X clicked on an ad and purchased a product, and so on. Williams-Sonoma provides its in-house marketing data (website visits, mobile sites, call center data, and more) to UpStream, which aggregates it with third-party consumer data from brokers like Experian.

The data aggregation enables UpStream to tackle a number of tasks. First, it can score the integrated data with Hadoop to instantly drive the right marketing campaigns to individual consumers at a massive scale, processing more than 50 million scores per day per client. Second, it enables Williams-Sonoma to have a single dashboard of all campaign touches, interactions with the retail stores, online behaviors, and purchasing.

The data aggregation enables statistical analytics as well. UpStream employs a novel approach, having created survival regression models (also known as hazard models, or time-to-event models) in the R language. Those models have been used successfully in the health care industry, but for much smaller data sets covering a few hundred patients.

UpStream retrofitted the models to handle attributive marketing for retail to analyze the weighted effect of each campaign on a consumer's purchase. With this understanding, budget can be allocated much more effectively. To make this part of the solution more scalable, UpStream uses a commercial edition of R from Revolution Analytics. Finally, the models can be used to predict the likelihood for a given customer to buy based upon a marketing campaign.

UpStream and Williams-Sonoma continue to work together to create customized, targeted campaigns to individual consumers. Their models let them determine which consumers are left in which kind of marketing stream (email versus regular mail), as well as which are taken out and to only be targeted with online campaigns such as targeted banner ads.

Although Williams-Sonoma will not disclose detailed results, Namboodiri indicates they are encouraging, seeing improvements on scale and qualitative levels that have not been available until now.

This article, "Williams-Sonoma uses big data to zero in on customers," was originally published at InfoWorld.com. Read more of Andrew Lampitt's Think Big Data blog, and keep up on the latest developments in big data at InfoWorld.com For the latest business technology news, follow InfoWorld.com on Twitter.

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