In the early 1990’s, the retail grocery industry began leaving the growth stage and entered the maturity stage in the industry life cycle. The vast number of grocery stores that had been built in growth stage and the emergence of new grocery retail formats such as warehouse clubs and dollar stores led to increase in competition forcing firms to compete with each other for the same customers by lowering prices
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.
Instead of simply basing pricing on past methods such as cost plus strategies or reacting to competitors pricing, today’s need is to optimize retail pricing for every item in the store in order to achieve volume, sales, profitability and price image goals. Retail Analytics have proven to be a major tool for decision makers to optimize their pricing strategy.
Several niche analytics service providers such as Fractal Analytics provide pricing elasticity solutions enabling grocers define and optimize consumer-centric pricing strategies based on consumer, demand, and market insights. Known Value Items are often used to compare prices across stores and hence it is very important to price them appropriately and merchandise & communicate effectively about them. Identifying these KVI Items requires multi-stage data mining and analytics.
For more information on pricing analytics for grocery industry, attend the webinar on Grocery Price Optimization to be held on June 12.
Tags: Data Analytics, Fractal Analytics, Grocery Price Optimization, Grocery Pricing, Grocery Retail, Merchandise Analytics, Predictive Analytics, Pricing Analytics, Pricing Elasticity, Pricing Strategy, Retail Analytics, Retail Pricing, Webinar
