Parker Avery’s approach preserved the client’s price image using a mix of competitor price matching and AI-driven price optimization while improving the sales mix to augment financial metrics. Combining Parker Avery’s Enterprise Intelligence demand platform and the firm’s deep retail industry and pricing expertise, the Parker Avery team partnered with the client’s analytics, product, and operations teams to optimize the retailer’s private label tire pricing across regions, products, and channels.
Parker Avery staged, cleansed, and filtered multiple years of transaction-level data, representing several terabytes of information. The team integrated the previously modeled product warranty price with private label price information to model price elasticity and cross elasticity. The elasticity models span the company’s private label products, geographies, and selling channels to optimize units, revenue, and margin. Parker Avery’s team designed and conducted a multi-stage field price test that confirmed the benefits of the price recommendations on financial results.
