Factoring in the Weather’s Impact

Using Weather-Driven Demand Analytics to Evaluate Performance & Improve Plans 

Weather often “masks” underlying business performance, making performance analysis, planning, and forward earnings guidance challenging. To clearly gauge performance (and not inadvertently draw incorrect conclusions or miss hidden issues) businesses need to know when, where, and how much the weather affected traffic levels, total or division/department transactions, and category-specific sales. Planalytics Weather-Driven Demand (WDD) calculations isolate the impacts enabling companies to evaluate results (such as regional sales, promotions, marketing campaigns, etc.) from a weather-neutral perspective.  

The business can also leverage WDD projections to look forward to next weekend or the next few weeks, to optimize labor costs, more accurately forecast revenue, inform markdown strategies, and more. When planning for the season ahead, businesses can improve accuracy by using a weather-adjusted baseline that has quantified and removed the effects of weather volatility from historical sales.

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Winning With The Weather

A QSR chain needed to understand why sales were disappointing during an early spring period.		An apparel retailer saw an opportunity to clear inventory at higher prices due to positive WDD.
Weather-adjusted sales showed that poor weather, not product or promos, hurt performance		Lower markdowns (20% vs. 50%) boosted profit while still meeting end-of-season inventory targets

What Our Clients Are Saying

Enables the business to unlock much better accuracy and a much better understanding of what our sales and transactions are. It makes it easy, not just as the analysts, but also being able to roll that up to the executive level.

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Descriptive, Predictive & Prescriptive: Understand & Optimize Performance

You Can Mark This Down. Retailers Preserve Margin with Predictive Demand Analytics

Boost Sales by Factoring in This Everyday Driver of Demand

Profiting from Predictive Weather-Driven Demand Analytics