It's well known that weather affects shopping behavior. Not only it influences consumers’ emotional state, but it also drives purchase decisions as well as spending habits. Temperature ranges and weather conditions can, therefore, impact your store traffic and sales volume in more ways than one. Let me give you an example. Last winter, much of the world experienced unseasonably warm weather. Although many were happy about the low heating bill, retailers were not celebrating. Customers stayed away from seasonal buys and left the winter boots, coats, scarves and snow shovels to gather dust in the shop windows. It was calculated that the warmer-than-usual winter lost retail stores $185 million in sales in the USA alone. 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: not based on forecast, but based on the previous year’s near-record cold temperatures.A new retail climate
Last year retailer paid dearly for their merchandising mistake. It was, however, a mistake that could have been avoided. The Internet of Things (IOT) has made atmosphere mapping and weather forecast much more accurate, detailed and easily available. Retailers now have the tools to move from coping with events out of their hands, such as weather, to anticipating them, so that they can face them well prepared. By matching accurate weather forecasts with historical retail data (for example analyzing how the weather has been affecting store traffic, inventory and basket mixes), retailers can obtain a wealth of information which they can use to plan for future actions. The Weather Company’s coverage can now scale down to a 500-square meter resolution. Retailers can now use this hyper-localized weather info to create differentiated and meaningful strategies for every single one of their stores, improving their marketing, to merchandising, to staffing decisions.
How can weather information transform a weak season into a robust one?
Retailers can leverage weather insights to:
Take cost-effective staffing decisions
Weather conditions can affect your staffing needs. If it’s a sunny autumn day, you will probably want to have more staff in your downtown shops than in the mall locations. During stormy and snowy days, you will need extra employees to keep the store entrance clean and dry. When it’s cold or stormy, and the demand for pick up service increases, you need to ensure you have enough staff members on the home delivery team. Some of these decisions are quite intuitive, if you have been in the business for a while. Yet, 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. A solution such as LS Staff Management can help you optimize your staffing and plan ahead, taking into consideration multiple variables: your staff’s availability, overtimes, and even external factors like the weather. 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 over 25°C and not raining – and the solution will take care of organizing the staffing for you.
Improve inventoryAccurate weather forecast data can solve many inventory-related doubts. If you know there is going to be a warm spring, you may want to start displaying barbecues, mosquito repellent and light dresses earlier than usual. Will temperatures go down? Make sure you are carrying enough flu and cold medicine. Don’t forget to analyze your customers’ basket mix in relation to the weather: you may find counter-intuitive but illuminating correlations. The Weather Company discovered that sales of ice cream increase with the temperature – but only up to 25°C (77°F)! If it’s warmer than that, the 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.
Increase marketing effectiveness and revenueTie your marketing efforts to the weather conditions to attract more people to your store and sell more. A hotel chain, Red Roof Inn, increased business by 10% in just one year with a big data and geo-based mobile marketing Red Roof Inn used freely available weather and flight cancellation info, and 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 make booking at a nearby hotel easy. The effort paid off. If you have done your homework, and know what kind of items are most popular during given weather spells, you can also change your store displays, shop window, or homepage based on these insights. Displaying appropriate merchandise based on local weather on their homepage brought fashion retailer Burton an 11,6% increase in conversions.
Be ready for stormy weathersWith extreme weather events on the rise worldwide, it’s a smart idea for retailers to be prepared. It’s not just about stocking canned foods and flashlights; floods, droughts, heavy storms and tornadoes can cause all sort of retail disruptions, from delayed deliveries to unavailable stock. IOT helps retailers be ready for the worst: by using geospatial info and predictive tools, retailers can find alternate suppliers, re-route deliveries and mitigate business risks associated with extreme weather.
Optimize pricingRetailers can increase their revenue by adapting pricing to the weather conditions. If a retailer knows that there will be a heatwave in early August, they 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. Online retailers such as Amazon have made their fortune with it, and offline retailers are now stealing a page from their book. Doug Stephens, the Retail Prophet, believes we’ll soon see more dynamic pricing in-store, as brick-and-mortar retailers will start experimenting with models based on various factors, including weather data. Some companies are already seeing returns from adapting price to the weather. Dublin Airport, running LS Nav, has experienced big gains since implementing a dynamic pricing scheme that, based on weather conditions and available spaces, automatically calculates the optimal price to charge for parking spaces close to the gate.