Sales promotions are something that everyone looks forward to. The retailer gets to see it's sales increase while getting rid of unnecessary stock, and the consumer gets more products at a lower price.
Despite the joy that promotions may bring, according to Nielsen data, only half of promotions increase sales for the retailer. Brands and manufacturers use this technique to avoid seeing revenue diminish, but often times the result is that profitability drops.
The key to getting out of this vicious cycle: Schedule less, but more effective promotions.
In order to do this, Predictive Analytics can be used to understand how long promotions should run, what tactics work best, and what combinations will best help you achieve the results you want.
Accelerate your insights.
In the past, data and analytics remained in Business Intelligence tools that were used for presenting findings in monthly or quarterly business meetings. It's still common for manufacturers and retailers to be using spreadsheets and taking hours of human effort to make decisions. This is a major problem because real-time data is not being captured. The opportunity to send tailor-made promotions to consumers is missed.
While predicting product sales is critical, predicting sales by customer segment is essential to promotions. How do you know whether your promotions are great for one-time customers but awful for your regular customers? Integrating behavioral and attitudinal information to create a consumer-centric view of your data establishes a clear path for leveraging customer science and predictive analytics.
For example, these advanced analytic approaches can be used to develop consumer segmentations, predict customer churn, and calculate a retailer's share of the market. You can identify price elasticity and know what shoppers are willing to pay and you will be able to move away from simple competitor price matching. If you cannot predict your performance by customer group, you are throwing promotions against a wall and hoping some will stick.
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