By Brad W. Smith, special to RetailWire
Retailers are looking to make better and timelier decisions. For a growing number that has meant looking to provide business users with near real-time data analysis through the use of an enterprise data warehouse.
"Retail wants us to help them to be more affective in mining the large amounts of data and to move it to more exception in dashboard capabilities with the data," Darryl McDonald, chief marketing officer at data warehouse vendor Teradata, said at the company's annual user conference in Las Vegas last month. "They still need all the data to do the analysis. But what they are saying is we need to operationalize it, make it more usable by more associates within their enterprise.
"Retail customers are wondering how to handle the impact of RFID, and with some of the pilots, there has been a 10-20x explosion of a single item as it is tracked through the enterprise. We are helping them to understand how much data to keep, how much history to keep, how to then aggregate that (data) and then how to better use that information to run their business."
McDonald added, "There was a big push in retail to understand their customers, and then there was a big push to have more effective marketing with them; now they are looking for more real-time ways to communicate with their customers. Especially with their best customers, the top 20 percent, how do they treat them differently? Companies are being innovative with those customers."
As an example, he said Teradata is working with a company now that can push offers when customers enter the store; customers swipe their card at a kiosk and the offers are available right away. Also if a customer is in their car or at home, and is planning a visit to a store, they can enter a number in their cell phones and any valid offers are made available to them.
Discussion Questions: What impact will the move to near real-time data analysis have on retailers, both at the store level and at headquarters? What areas (merchandising, customer marketing, replenishment, labor management, etc.) do you believe will be most greatly impacted by improvements in the analysis of near real-time data?