Revionics, Planalytics Enhance Weather-Driven Demand Pricing Solution

Price optimization solutions provider Revionics, Inc., and its partner, Planalytics Inc., a global source of business weather intelligence, have enhanced the weather-driven demand intelligence feature, which is integrated into Revionics’ cloud-based Life Cycle Price Optimization suite that includes base, promotion and markdown pricing management and optimization solutions.

“Our partnership with Revionics allows us to help their customers understand how weather impacts consumer demand and spending across time, region and product category,” stated David Frieberg, VP of marketing for Planalytics. “Equipping retailers with this type of weather-driven data and insight, ensures their pricing decisions are more accurate, which will drive higher sales and profits.”

On a weekly basis, weather only repeats itself 20 percent of the time from the previous year; therefore, if retailers are relying on just historical weather events and data, they will not be accurate in their pricing forecasts and decisions. In addition, weather is the one external variable that creates opportunities for retailers by helping drive consumer demand. Due to this market need, Revionics and Planalytics forged a partnership in 2009 to develop a solution that would help retailers be more “spot on” with their weather-driven forecast and pricing strategies.

One of the benefits of this enhancement is the ability to incorporate historic weather effects into the demand model to adjust pricing based upon the impact of weather. This provides retailers with cleaner and more accurate elasticity and seasonal parameters by removing the “noise” that weather anomalies might have caused in the data. The benefits include improved forecasting, resulting in a stronger financial performance. Specific highlights of the enhancements include:

  • “De-weatherization” of data: A proprietary optimization process that objectively removes the influence of weather from historical sales of products by market and time, which eliminates the error inherent in historical weather-driven sales curves.
  • On-demand weather information: Provides the ability to graphically view historical and future weather trends in order to simulate different business scenarios for pricing, promotions, or markdowns.
  • Full transparency/visibility: Allows for additional insights into how weather is impacting pricing such as the historical impact of weather on elasticity, seasonality and demand. In addition, provides insight into decomposition of elasticity; how much of it is due to raw demand and how much to one-time weather events.




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