Download
1 / 7
70 likes | 75 Vues
Here are a few ways in which weather data can play an integral role in the retail industry.
E N D
No other external variable shifts consumer buying behavior as immediately and frequently as the weather. A mere 1℉ drop in temperature in the US alone leads to a massive demand for soup, porridge, and lip-care products. However, many retailers ignore the influence of weather on their demand trends, adding scope for error in demand forecasts. Ignoring the effects of weather can lead to poorly planned inventories and erosions in margins. • Integration of weather data in functions across supply chain, marketing, and ops drives efficiency allowing retailers to better plan and adjust to weather's impact on retail processes. With predictive weather analytics, customized datasets, and severe weather alerts, retailers can optimize production and avoid markdowns and inventory overages. Here are a few ways in which weather data can play an integral role in the retail industry:
ForecastingDemand Combining product sales trends with weather data can help establish demand correlation, thus improving forecast accuracy. This improvement in accuracy results in optimized inventory planning across categories, eliminating the need for markdowns. To forecast demand precisely, organizations using inventory planning systems can easily integrate Ambee’s frictionless weather APIs.
Planning Inventory Ensuring product availability with consistency across outlets drives sales, customer satisfaction, and brand loyalty. With weather-based demand forecasting, retailers can improve outcomes with optimized inventory and minimal stockouts. For instance, products with demand affected by rainfall, such as tea or umbrellas, can be ordered ahead of time to maximize sales. Similarly, integrating Ambee’s weather API can help with innovations in visual merchandising and optimizing product and shelf placement.
Minimizing Markdowns Weather data can help minimize markdowns by aligning store inventories to weather-based shifts. Weather-based demand forecasting helps planners make smarter decisions for their inventory and account for longer lead times. Markdowns help retailers clear shelves, but most retailers make identical price reductions every year. Weather-driven demand forecasting helps better time and price markdowns without facing a loss in revenue.
Optimizing Logistics Extreme weather conditions, such as snow, ice, and heavy rain, can make transporting products to distributors and retailers impossible. Even in cases where roads can still be used, adverse weather conditions can heavily intensify traffic. Weather data can help formulate predictive route mapping leading to efficient supply chain routing and on-time delivery.
Enhancing Marketing Retailers can improve conversions by using weather-driven personalization to make campaigns more relevant. With weather data, retailers can target favorable weather periods, regions, and markets to enable sales from relevant audiences and improve return on advertising spend (ROAS). Weather forecasting can help plan a more targeted approach to advertising and focus on the products most likely to sell. For example, a sunscreen ad is ineffective on a cold and rainy day, the ad must be showcased on a hot summer day, reminding consumers about the importance of sunscreen.
