Macys.com uses private cloud to personalize digital shopping strategies
Macys.com has made a name for itself by analyzing consumer data to gain insight into its loyal shopper base. The retailer, which features more than 60,000 products online and leverages multiple digital channels to share product information cross-channel, has armed itself with a set of internal cloud-based, high-performance analytics tools designed to improve customer segmentation, market-basket analysis and real-time personalization cross-channel, based on a broader scope of product attributes.
“We need to understand where the demand is coming from and how to use the data to know how to best serve our shoppers,” said Kerem Tomak, VP marketing analytics, macys.com. “But managing the volume of data is an increasing challenge.” Indeed, he described the amount of data that the retailer collects as “mind-blowing.”
It is made even more so by the fact that macys.com is looking to harness three dimensions of data: volume of the data, variety of data (including structured and unstructured information), and the velocity with which they receive and process it.
“We have a short time frame to process these large product attributes and match these to customer needs,” Tomak explained. “Traditional BI or near-real-time solutions don’t meet our needs because we have less than a minute to really > capture customer attention. If we don’t do it the right way, she’s gone.”
Knowing how crucial it is to quickly turn raw data into actionable information, macys.com turned its attention to a high-performance analytics tool from SAS, Cary, N.C. The retailer linked the SAS Enterprise Miner to a Hadoop cluster, an open-source, data-management platform initiated by Yahoo and Google. This private cloud platform sits behind macys.com’s firewalls and processes large data sets in a distributed computing environment.
Macys.com compiled two years worth of data, which ranges from 20 terabytes to 30 terabytes. As new data comes into macys.com servers, it is stored on Hadoop and passed to the SAS tool, where macys.com analysts compare information with its historical database to build reports on products, marketing and merchandising views.
Since going live with the system in late 2010, macys.com has gained a unified view of data and performance across its omni-channel enterprise, including insight into who buys which products across what channels, according to Tomak.
“We are also more effectively measuring the impact of online marketing initiatives and how this translates into general sales, as well as sales by channel,” he added.
Macys.com is also able to complete these tasks in shorter, more efficient durations. When processing these reports on the previous system, the system often crashed due to the size of the queries. But that doesn’t happen anymore.
“Now we can get answers within two hours and pass information to SAS. The automation of report generation also saves more than $500,000 a year in comp analyst time. It has become a life saver,” Tomak said.
Looking forward, macys.com plans to use Hadoop to connect its marketing and merchandising operations with its call center to gain a truly unified view of customer response.
“The Macy’s brand has so many customer touchpoints that we need to make sure we can improve how we serve them, deliver the right offers and merchandise when they need it,” Tomak said. “That is the Holy Grail. And it is only possible if we connect different systems across the organization onto one data-processing environment.”
Macys.com hopes to have the integration complete by the end of 2012.