Promo Power™: Promotion Forecasting & Allocation

The automated Promo Power™ solution enables retailers to eliminate costly manual interventions and dramatically improve retail execution processes and effectiveness at the store level.

Promo Power™: Promotion Forecasting & Allocation

CPG companies continue to spend a significant portion of their revenue on trade promotions, driving sales through retail partners. Similarly, retailers spend a significant amount of time on promotional forecasting. With trade spend approaching 25% in the U.S. (and 30% in China), it is imperative for suppliers to make sure that their investments in promotions are efficient and effective.

On-shelf availability and out-of-stock (OOS) issues also continue to plague promotion success. For retailers and manufacturers, the standard OOS rate remains at 8% to 10%: that rate jumps upwards of 15% while promotions are happening – in fact, according to an FMI/GMA Trading Partner Alliance Report, one out of every 10 shoppers cannot find a promoted item on a store shelf.

That is why RSi is leveraging its CPG industry expertise to focus on predictive analytics, which allows for better and more accurate stock in high-volume retail stores, while simultaneously reducing markdowns in lower volume retail stores. As such, RSi facilitates the easy capture, viewing and interaction of promotional data to help suppliers and retailers make more informed decisions.

With RSi’s new Promo Power™ solution, retailers and their CPG trading partners can strengthen their joint business planning to improve promotional effectiveness by 20-25%.

By combining real-time retailer POS data with a collaborative forecasting process, RSi customers can address key promotional activities, make sure items are on store shelves during a promotional period and boost more collaborative trading partner relationships – making sure the right products are in the right store (in the right quantity) at the right time.

The RSi Advantage:
*Optimize promotional efforts through collaborative predictive analytics.
*Less residual and less markdown on products after promotion.
*Ensure high-volume stores remain in-stock.

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