The constant evolution in buyer sophistication is a driving influence pushing innovation and advancement in the retail industry. One area of influence in particular that is causing disruption, or “good trouble,” is the increasing attention on how weather influences shopper behavior, demand patterns, and a retailer’s demand forecasting. As customers become savvier, retailers must be shrewder and more exacting – not only when making production decisions, but also when determining when a product needs to be available, where the product needs to be, and at what price the product should be on shelves. Understanding how weather patterns affect purchasing behaviors is becoming a vital input for many retailers. Businesses like Ross Stores, Dicks Sporting Goods, Inspire Brands, Unilever, and more are leveraging predictive weather-driven demand analytics to gain a competitive advantage, improve decision-making, and realize increased profitability. In this piece, we’ll dive into how weather analytics affect demand forecasting in retail and how companies can make more streamlined and effective decisions.
Demand Forecasting in Retail
What are weather analytics, and how are companies using them?
Understanding how weather affects customer behavior is one way that businesses are leveraging the power of predictive demand analytics. At its simplest form, weather-driven demand (WDD) analytics enable retailers to understand how historical purchasing patterns correlate with historical weather to create actionable insights that inform how customers will react in the future. This includes using information on what customers bought, how promotions faired, what channels customers shopped during a given point in time, and a host of other insights, to make an informed decision.
Retailers are integrating innovative platforms like Planalytics with their ERP and demand planning solutions at scale to aid in their understanding of WDD, which can further aid in reducing lost sales, improving plan accuracy, lowering inventory cost, and improving returns on marketing campaigns.
What are the benefits of using weather analytics in retail?
The business benefits of using weather analytics don’t end at improving demand forecast understanding and planning. The impact of weather on customer purchasing can also directly influence pricing strategy and marketing decisions, as well as give an additional lever to inform decisions that directly affect sustainability goals. The benefits are measurable as well, including increases in top-line sales and bottom-line profits and a reduction of waste.
Companies are using predictive weather-driven demand analytics to optimize pricing strategies. They are using the historical sales of products by market to assist in eliminating possible errors in weather-driven sales curves. By using near-term predictive weather analytics, retailers can simulate business scenarios that optimize pricing, promotion, and markdowns. Also, by having a greater understanding of the elasticity of seasonal demand, retailers can understand – by each category, location, and time of year – how to localize their pricing and promotional levels throughout their sales channels with a high level of precision.
Customers in different parts of the world react to weather nuances differently. For instance, 100 degrees Fahrenheit in Atlanta, Georgia, is a normal summer day, but 100 degrees Fahrenheit in London, England, could cause significant changes in buying habits due to the region’s infrastructure limitations. Understanding these types of nuances is vital for retailers to understand where to drive promotions by providing a lower level of customer segmentation, which further aids in the personalization of marketing campaigns. Any good marketing manager understands that there’s no such thing as “a one-size-fits-all” customer. Having a greater consideration of how consumer decision-making changes by region given the same weather factors can arm retailers with key information to combat the volatility that weather can have on the sales of seasonal products. Enabling marketing campaigns to be ‘weather-smart’ will ensure that the right message reaches each customer at a time when they are more likely to make a purchase.
If you talk to any CEO today, you will hear that producing and providing their products in the most environmentally ethical way is of critical importance—not only because of internal core values, but because consumers are demanding it, and governments are putting in place regulations to ensure it happens. With this being the case, sourcing more sustainable materials, reducing waste, and having a keener pulse on inventory levels are vital inputs to understand if retailers are to achieve future and current ESG goals. Through having a clearer picture of demand, retailers can better regulate their supply chains and reduce waste in the manufacturing of their goods. Also, better estimations of demand ensure that retailers are not overstocking their shelves and having to combat this occurrence with unplanned markdowns. With such a major emphasis on retailers to reduce their carbon footprint, they will need to rely on every metric possible for them to be able to achieve their sustainability goals.
The Future of Retail and Weather Analytics
Post-pandemic, there has been a greater sense of urgency around making improvements and investments in ways to advance decision-making in their demand forecasting in retail, processes, and technologies to ensure supply for the right products is available to customers at the right times. Businesses are consistently searching for competitive advantages, and looking to predictive demand analytics will help retailers ensure they are putting themselves in a position to win with their partners, customers, stakeholders, and regulators.
Many companies already have the data in place to get started, and others are using the power of predictive weather analytics to help in making critical business decisions on future demand, optimize inventory levels, tune pricing strategies, better engage with customers, and help reduce waste. There are measurable benefits of incorporating these analytics at scale across a business.