Whether sales are up or down, it is important for managers to understand why. However, existing demand forecasting models do not sufficiently explain the portion of demand driven by each influencer on sales, limiting the usefulness of these forecasts to production planning use cases. Identifying the factors that cause sales to fluctuate is the first step in deciding what a retail or CPG company can do to grow their sales more efficiently. While some external and environmental factors such as the weather or holidays are outside management’s control, there are many factors such as sales coverage, advertising, pricing, and promotions that can and should be leveraged where they are most impactful by management teams to maximize sales.
Machine learning algorithms can take all of the confounding factors in each market to identify key sales drivers and how much they individually impact sales at each store. With these insights, managers will be armed to tailor their strategies for each market and maximize sales across them.
Understand drivers and forecast sales
Discover how sales are affected by location, segment, channel, packaging type, market category, or product type. Neal Analytics’ unique analytical methodology helps managers explain which levers influence sales, and by how much but at an unprecedented level of detail. Instead of analyzing sales drivers at a company-wide or otherwise aggregate level, we can determine how sales driver impact fluctuates across channels, product groups, or geographic territories.
These insights are delivered continually instead of annually, enabling Neal Analytics’ Sales Driver Analysis to empower users with up-to-the-minute projections of sales impacts for a dynamic strategy. For example, if a company understands that a particular sports event is going to cause a significant increase in sales, it can adjust supply or pricing in order to match the new demand curve, and reset it when the event finishes.
Reduce stock-outs and increase profits
With deeper understanding in sales drivers and augmented demand forecasting, managers can tune and improve their strategies. For example, if temperature is going to increase next week and boost sales in a certain region, then preventing stock-outs rather than running a promotion event may be the key action item. Business strategies will be guided by managing the “levers” that impact sales outcome.