When any SKU is priced, it is done with the hope sales will be X units at Y price. Merchants do this for a living and it is a complicated process. For products never sold in your store before, it is an especially tough call.

In most firms, there is a vast trove of data on pricing history but it is not in actionable form for the buyers every day needs. Our system uses all the available data on every SKU by store sold. The system processes this data, examining price, units sold and profitability results. As prices change due to sales, circulars, markdowns, or reaction to competition, the information is examined, continually growing more predictive. Siblings are used for products new to the store.

When price/profitability points are obtained and analyzed at the SKU level, the system predicts unit sales/profitability at specific prices as well as an "optimal" price in the sense that any price, higher or lower, will yield a lower total profit dollar quantity.

Statistically derived confidence levels lend support to the unit sales/ profitability prediction. Estimates based on results from the retail drug and grocery fields suggest that use of this tool could yield a bottom line gross margin improvement of up to ten percent by just adjusting prices.

It is our experience that, in most situations, there are sufficient price/profitability fluctuations over time to produce useable results. Setting random price points in the market just to collect data is not required.

The unit sales predictor is also excellent at forecasting sales and profitability at a given price when introducing a new product of any kind. It is also a useful tool in helping the merchant decide if increasing gross margin percent also increases gross margin dollars.