The beginning of spring is the most important time of year for DIY retailers. This is the period where homeowners start new renovation projects, revive dormant ones, and repair any damage caused by winter weather. It is also when new construction begins on homes and other major projects that drive new business. However, a poorly predicted demand plan could have a damaging impact on a DIY’s “Christmas” season and cause a surplus or shortage of inventory. But how can a DIY retailer better predict sales and customer behavior pre-season and in-season to adjust accordingly?
Deweatherization Greatly Reduces the Guessing Game
Did you know that the weather only repeats itself year to year about 20% of the time? If you use last year’s metrics to plan for this year’s sales, you will unintentionally build error into your plans. For example, let’s take a look at spring 2015. The 2015 spring season for DIY retailers was better than 2014 because there was warmer weather early-on, providing a strong start. Warmer weather in March was favorable and drove consumer demand. DIY sales leveled off in early summer when wetter weather drowned out many outdoor projects.
By analyzing historical weather and sales, Planalytics estimated a $1 billion favorable weather-driven sales impact for DIY retailers in spring 2015. If those retailers had used 2014’s weather data to make decisions about 2015 spring sales, they would have missed out on excellent opportunities to leverage the warmer early spring weather and may have experienced losses due to the poorer weather later in the season.
Deweatherizing sales to plan from a weather-neutral baseline can greatly enhance a retailer’s ability to mitigate weather-related costs and capitalize on the opportunities. Reviewing last year’s weather data is simply not good enough for predicting what will happen in the upcoming season. While there is no way to control the weather, a retailer can certainly control how it forecasts sales based off accurate predictive analytics.
Planalytics allows DIY retailers to see exactly how customers in a particular region are affected by changes in the weather during a certain time of the year. Weather analytics goes beyond just looking at the data and instead measures how weather volatility affects sales. This is certainly the case when it comes to the DIY retail market. A warm or cold start to the season or ongoing precipitation could have a significant impact on sales with ramifications that extend throughout the season.
Planalytics can help DIY retailers deweatherize their business, so they are prepared for whatever the weather may bring, especially during the incredibly important early spring retail period. Deweatherizing takes the guessing game out of weather’s impacts.