Retail Analytics - Grocery Industry

Competition in retail grocery continues to grow as stores fight for the attention of better informed and price conscious customers. In response, merchandising and marketing managers can adjust different aspects of the marketing mix to help drive demand, but of those, price optimization is typically the most complex, challenging, and critical to business success.

Consumer reactions to prices are driven by a wide range of interdependent variables, including price elasticity , regional differences, seasonality, trade promotions , shelf placement and more. With so many variables to consider retailers must adopt robust, science-based decision processes and analysis tools to enable retail price optimization.

Due to these unique complexities leading grocers around the world are working with Fractal Analytics for retail price optimization to make pricing a more strategic component of their overall merchandising strategy.

Instead of simply basing pricing on past methods such as cost plus strategies or reacting to competitors pricing, Fractal’s Grocery Customers are leveraging powerful consumer, demand and market insights to optimize retail pricing for every item in the store in order to achieve volume, sales, profitability and price image goals.

Pricing Elasticity

Fractal’s pricing elasticity solutions provide grocers with the ability to define and optimize consumer-centric pricing strategies based on consumer, demand, and market insights:

• Define strategies and optimize prices across the complete product lifecycle - initial, everyday, promoted, and markdown pricing - given local market demand and competition
• Determine the right balance of EDLP and Hi-Lo pricing
• Validate and refine price tiers, image items, and category roles
• Leverage superior insights into price elasticity, consumer demand and competitor actions.

KVI

KVI items comprise some select SKUs about which the shoppers are well aware and are often used to compare prices across stores. These items disproportionately drive the store’s value perception and their precise pricing is critical in projecting store’s intended price image.

The business driving KVI items have been typically found to have high penetration, good purchase frequency, very stable or highly promoted prices, good shelf space occupancy and a reasonable price elasticity. Involvement and information search categories also play a role in certain categories. It is imperative for a store to price the KVIs appropriately and merchandise & communicate effectively about them to be in a position to leverage the non KVI pricing. The identification of such items takes place through a multi stage data intensive research and analysis. This proposal develops a research approach for the identification of KVIs that would lead to a pricing mechanism for the identified items.