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Advance Auto Parts Selects SPSS Predictive Analytics Software


Improving Market Basket Analysis, Inventory Control so Advance Auto Parts Customers Receive Right Part at the Right Time – Every Time

CHICAGO.- In today’s economy, more car owners are opting to keep their current vehicle longer and invest in preventative maintenance than purchase a new car, according to a recent study. Therefore, automotive retailers need to stay one step ahead of car owners and repair shops by providing the best product availability. To help improve inventory control, customer satisfaction and increase sales, Advance Auto Parts chose SPSS Inc. (Nasdaq: SPSS), the leading global provider of Predictive Analytics software and solutions.

Supporting its ‘Availability Excellence’ initiative, defined as ‘delivering the right parts to the right place at the right time - every time’, Advance Auto Parts, the second-largest retailer of automotive parts in the United States, selected SPSS Predictive Analytics Software (PASW). Advance Auto Parts is using PASW Modeler (formerly Clementine) and PASW Collaboration & Deployment Services (formerly Predictive Enterprise Services) for market basket analysis and to help optimize its supply chain to accurately manage inventory at warehouses and individual stores.

Jim North, vice president of inventory market replenishment at Advance Auto Parts, said, “Our organization has a 77 year history of providing our customers in-stock, quality, affordable auto parts, driving tremendous satisfaction. SPSS Predictive Analytics Software helps enable our organization to bring the right product closer to the customer improving product availability, overall profitability, and the propensity to move SKUs at stores.”

Jack Noonan, SPSS chairman, president and CEO, said, “Organizations such as Advance Auto Parts are using SPSS Predictive Analytics Software to capture, predict and act on customers’ needs, preferences, and habits over time to ensure longer-term customer loyalty, grow revenue, reduce fraud and mitigate risk.”


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