Weather is not just for small talk. Whether it’s sunny or rainy can have a big impact on shopping behavior. A few years ago, a warmer-than-usual winter across the U.S. lost retail stores $185 million in sales, with furry boots, scarves and snow shovels left to gather dust in shop windows. Although unusual, the warm winter was not unexpected; as a matter of fact, it had been forecast. The problem is that retailers planned their merchandising as they always had before: based on the previous year’s weather variations and sales trends, without considering the forecast.
This is the kind of mistake retailers can avoid. With accurate atmosphere mapping and accurate weather forecasts now easily available, you can move from being reactive – and acting too late – to anticipating weather events, and being ready for their impact. And once you have acquired enough information on your sales, you can improve your replenishment by matching weather forecasts with historical retail data, checking for example how specific weather patterns have been affecting store traffic, inventory, and basket mixes in specific stores.
In the short term, retailers can use hyper-localized weather information – which is now available down to the post code - to create differentiated marketing, staffing and merchandising strategies for each store location. IBM and the Weather Company’s high-resolution weather model can forecast weather with a resolution of just 3 km, with hourly updates, allowing to quickly predict the development of small-scale weather events like heavy rain anywhere on Earth.
Here are five ways retailers can use weather insights to limit waste and improve decision-making.
1. Make cost-effective staffing decisions
Knowing the weather forecast can help your store managers plan more effective work schedules. For example, on a sunny winter day, you may expect more customers to visit your high street shops than your mall locations, so you should staff those locations accordingly. During stormy and snowy days, you might want to have an extra employee to keep the store entrance clean and dry. When the weather is particularly bad, there usually is higher demand for pick-up services; make sure you have enough staff members on the home delivery and product picking teams.
These staffing decisions are quite intuitive, if you have been in the business for a while. Still, on an average day, few store managers have the time to check the weather forecast and decide how many employees they need in every single shop based on the conditions. That’s where technology comes in. A staff management solution that takes into consideration multiple variables - employees’ availability, overtimes, and external factors like the weather - can help you automate and optimize your staffing decisions. In the best software solutions, you can just input your settings into the system – for example, you may want to have two extra staff members in the downtown café if it’s sunny during the weekend – and the solution will take care of organizing the staffing for you.
2. Improve merchandising
Having accurate weather forecast data can help you order the right items at the right moment. If this spring is expected to be unseasonably warm, you may want to start displaying barbecues, mosquito repellent and shorts earlier than usual. Are temperatures expected to go up and down? Make sure you have enough flu and cold medicine in stock – and don’t move the warm socks from the shelves just yet.
A good way to understand how to optimize your merchandising is to look at your customers’ basket mix in relation to the weather – you may find some counter-intuitive correlations. For example, the Weather Company discovered that sales of ice cream increase with the temperature only until the weather reaches 25°C (77°F). Once it gets warmer than that, ice-cream sales plummet. Wal-Mart noticed that families bought smaller-sized products during economic downturns, but reverted to large packages during bad weather. Thanks to big data, the company was able to understand otherwise unexplainable fluctuations in sales, and get the right stock.
3. Make your marketing more effective
Have you ever thought of using weather information in your marketing campaigns? Hotel chain Red Roof Inn increased business by 10% in just one year by using big data and geo-based mobile marketing. Using freely available weather and flight cancellation info, Red Roof Inn built an algorithm which considered many variables - including weather, travel conditions and cancellation rates by airport and airline. Knowing that most travelers use mobile devices, the company sent targeted mobile ads to stranded travelers, with a link to book a nearby hotel in a click. The effort paid off.
If you have done your homework, and know what kind of items are most popular during specific weather conditions, you can also take other actions, such as changing your store displays, shop window, or homepage to match what your customers are looking for. When fashion retailer Burton started displaying merchandise based on local weather conditions on their homepage, they saw an 11,6% increase in conversions.
4. Be ready for severe weather events
With extreme weather events on the rise worldwide, retailers need to be prepared for the impact weather will have on their operations. It’s not just about stocking canned foods or flashlights; events like floods, droughts, heavy storms or tornadoes can cause all sort of retail disruptions, leading to delayed deliveries, staffing challenges and unavailable stock. Technology can help retailers be prepared when such events hit. For example, predictive software can be used alongside geospatial information to find alternate suppliers when needed, re-route deliveries, and generally mitigate business risks associated with extreme weather.
5. Optimize pricing
By adjusting pricing to weather conditions, retailers can increase their revenue. If you know that there will be a heatwave in early August, you can for example postpone the end-of-season sale, and keep selling summer items full-priced during the hot spell. Dynamic pricing is also increasingly popular not just online. Retail expert and author Doug Stephens believes we’ll soon see more dynamic pricing used in-store, as brick-and-mortar retailers start experimenting with models based on various factors, including weather data. Some companies are already seeing returns from adjusting prices to the weather. Dublin Airport saw healthy return from a dynamic pricing scheme that automatically calculates the optimal price to charge for parking spaces close to the gate based on both weather conditions and space availability.
The outlook is sunny for agile retailers
Big data like weather information can be very valuable for retailers who want to match and anticipate customer demand. By combining big data analytics, omni-channel strategies and innovation, retailers can reduce costs, optimize resources – and stay several steps ahead of businesses that still order stock based on last season, organize staffing on paper, and close doors when the storm comes.
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