Analyse This Daily Demand Driver to Increase Sales
The Retailer, British Retail Consortium (BRC)
David Frieberg, VP Marketing, Planalytics
WEATHER ANALYTICS HELP RETAILERS AVOID LOST SALES BY BETTER ALIGNING INVENTORIES WITH CHANGES IN CUSTOMER DEMAND.
Taking advantage of selling opportunities when they materialise has never been more important. The pandemic has constrained spending, consumers are focusing more on need-based purchases than discretionary ones, and shoppers are making fewer trips to stores. All in all, retailers have a limited number of chances to get it right, capture sales, and satisfy customers before their competitors do.
Staying ahead of shifting consumer demand patterns is difficult; after all, there are a lot of external variables that a retailer can’t control. For many of these uncontrollable factors – the economy, consumer confidence, and of course, COVID-19 – businesses can really only react and adapt. Many of these large-scale underlying factors tend to develop over time and evolve slowly. Retailers make the adjustments they can until circumstances begin to change, often months later.
The weather is another uncontrollable demand driver. However, unlike the previously mentioned factors, the weather’s impact on demand will flip between positive and negative frequently and often dramatically, creating new opportunities (and risks) on a daily basis. There is another key difference between weather and the other external demand influencers – the weather’s impacts can be proactively managed by retailers.
WEATHER-DRIVEN DEMAND ANALYTICS IDENTIFY OPPORTUNITIES
Leveraging analytics that pinpoint when, where, and how much demand will be increasing due to changes in the weather is a very effective way to boost sales without sacrificing margin. Favourable weather is like a promotion or markdown, without the cost. Retailers can ring up healthy sales in outerwear when items are discounted 40% but retailers also see sales volumes jump when cold, wintry weather sets in. Warm, sunny days will move as many or more units of bottled water as a “3 for the price of 2” deal. The right weather will generate demand and, for retailers that are prepared, a chance to satisfy customers and increase sales.
Of course this only works if a retailer has the inventory on hand to meet demand. The easiest path to increasing turnover and profit is to minimise lost sales due to out-of-stocks. Overstocking stores (or warehouses for online orders) is not the answer – this just balloons inventory costs and leads to operational inefficiencies, deeper markdowns, and/or increased waste.
Businesses can capture sales opportunities sensibly and repeatedly by using weather-driven demand analytics to better align inventories with consumer demand. Typically, retailers can grow revenue by 50 to 200 basis points by optimising inventories for weather impacted sales.
However, using raw meteorological forecast data to capitalise on weather opportunities does not work. Companies that try this approach quickly discover how challenging it is to operationalise the data and effectively integrate temperatures, precipitation amounts, etc. into demand forecasts, replenishment solutions, and decision making. Even businesses that bring weather data into ML/AI platforms do not come close to matching the accuracy improvement generated by weather-driven demand analytics.
Weather-driven demand metrics are developed by modeling multiple years of actual product sales by location and time period with the corresponding historical observed weather. The process accurately identifies weather-to-sales relationships and precisely quantifies the impacts with percent or unit change metrics a business can action.
A retailer can apply weather-driven demand insights to more optimally match up inventories with consumer demand in both pre-season planning and allocation and for near-term replenishment.
From a pre-season standpoint, weather-driven demand is used to correct planning baselines for both positive and negative weather-based sales distortions that are highly unlikely to repeat from one year to the next. Retailers that do this will improve planning accuracy by 20% or more for specific categories and uncover the times and geographies where demand is projected to be higher and more merchandise should be allocated. By weather-adjusting inventories ahead of the season, retailers increase revenue by reducing lost sales. At the same time, companies decrease the costs associated with over-stocking in situations where demand will fail to match last year’s levels.
In-season, grocers and other retailers with fast turning categories utilise weather-driven demand projections that account for forecasted weather conditions over the next week or two. Weather informed replenishment adjusts store-level demand forecasts to reflect how demand will be changing rather than simply restocking locations based on recent or historical sales trends. Just because the weather deflated demand in a location last week, doesn’t mean it will do so again this week. In this scenario, sales get missed because the weather has all of the sudden produced a bump in demand and there is not enough product available.
“MIND THE GAPS” THIS CHRISTMAS SHOPPING SEASON
How can weather-driven demand insights help retailers during the Christmas trading season?
Broadly speaking, November will present a challenging “weather comp” for retailers looking to move seasonal items. Winter apparel (coats, knitwear, boots, etc.) and other cold weather categories (hot beverages, comfort foods, heaters, etc.) received a nice assist from the weather a year ago. November 2019 was the coldest in over 20 years for the UK overall with above average rainfall. However, December should allow for better like-for-like performance as last year’s temperatures were warmer than normal.
Retailers using weather-driven demand insights will have planned for slower seasonal product sales in November but will also have planned to have enough inventory on hand to meet a stronger sales trend in December.
Without this perspective, it is not unusual for retailers to react to lagging year-over-year sales by taking deeper by scaling back stock levels and/or taking deeper markdowns earlier. Should December sales begin to outpace year ago figures due to more positive weather, a gap will open between demand and inventories, resulting in lost sales.
Additionally, retailers using weather analytics as they move through the Christmas season and replenish stores will be able to identify and fill the gaps that could be created due to day-to-day fluctuations in the conditions outside. Recognising and addressing the stock shortages that could arise due to weather-fueled sales spikes will help retailers maximise sales during this critical shopping season.
Read the original article here.
David Frieberg, VP Marketing, Planalytics
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