Weather affects everyone, every day. From the clothes we wear to the food we buy, weather influences our behaviors, decisions, and purchases in countless ways. And, what drives consumers to purchase specific goods or services varies depending on many factors, including location and time of year. Although day-to-day weather conditions greatly affect consumer demand, game-changers like winter snow storms and extreme cold significantly influence consumer buying behavior and hinder store traffic.
The following article has been written by Planalytics, Inc. (www.planalytics.com), a leading provider of weather analytics and planning insights for retailers, consumer goods suppliers, restaurants, and consumer service companies. Through advanced weather analysis technologies, planning and optimization solutions and industry-specific expertise, Planalytics helps companies assess and measure weather-driven impacts and effectively manage the never-ending variability of climate. Planalytics service for institutional investors, Financial Insights, currently tracks close to 80 U.S. based public retailers and restaurants.
Juno’s Impact on Retailers
This week, major media outlets forecasted that the Northeast would receive a record amount of snow, but the storm ended up moving further east resulting in lower amounts in most areas. Although the significance of the storm dwindled, the simple forecast of a blizzard in the media affected consumer demand and in turn retailers across the region. Most major retailers had between 25% and 50% of their stores in the path of this storm. A few notable retailers with high store concentration (% of total store base that were impacted by snowfall this week) in the path of the storm were:
- BJ’s – 79% of stores
- Five Below – 77%
- Bon-Ton – 62%
Most of the national retailers and restaurants covered by Planalytics’ Financial Insights research service saw 30-45% of their locations hit by significant snow in the northeast event this week.
Every storm produces winners and losers among retailers. Sectors that won throughout this storm were home centers, online retailers, and grocery/convenience stores. The losers were restaurant chains and mall-based retailers, such as apparel and department stores. However, since the storm hit early in the week and not during a key retail holiday period, the impact was minimized. Quick service restaurants were the most negatively impacted as these types of purchases were completely lost and will not be made up.
Winter 2014 versus 2013
Looking broadly at retailers’ Q4 (Nov.-Jan.), consumers have not had to make many need-based purchases. Through December, most major markets (NYC, Boston, Philadelphia, Chicago, Detroit) have snowfall below normal and below last year’s totals. Season to date, demand for snow removal, ice melt, and snow throwers has been down -5% to -10% versus last year across the United States, and even more in the Northeast and Midwest.
November 2014 proved positive for retailers as it was colder and drier than last year. Cold temperatures drove demand for seasonal purchases, and the dry conditions supported store traffic. A Nor’easter the week of Thanksgiving disrupted travel plans for many, but cleared just in time for the Black Friday weekend, benefiting traffic into stores.
December brought mild conditions from coast to coast, with all 5 weeks trending warmer than last year at a national level, and this aided holiday spending. Snowfall was 66% below last year and 57% below normal for December
Reflecting on Q4 of 2013, the winter saw numerous significant winter events along with extreme cold and the polar vortex. A strong system hit the Eastern states during the run-up to Thanksgiving, but cleared in time for Black Friday shopping. Two winter storms in December impacted major cities along the I-95 corridor; January had 3 significant storms in the East, and many retailers cited the extreme cold and snow storms as the reasons for disappointing sales and earnings.
Weather strongly influences consumer behavior and is a major cause of volatility in sales and earnings for retailers, restaurants and other consumer-driven businesses. Institutional investors use various data and research services like Planalytics to better understand and anticipate upside and downside surprises in monthly/quarterly comp sales, as well as quarterly earnings.