How Analytics Will Drive Retail Pricing

Who handles the most crucial decisions in your Analytics Drive Pricingbrick-and-mortar operations? Likely those decisions are in the capable hands of decision-makers who have decades of experience studying your sales and identifying trends.

Still, undesirable results such as out-of-stocks and overstocks exist, because the sales data your experts study breaks down into an overwhelming number of variables that no human can hope to process. That’s why businesses are taking an interest in data analytics for everything – pricing being one of them.

Markdown optimization

Most resistance to data analysis in retail decision-making comes from those who currently make those decisions. They find it hard to believe that computer analysis can make better predictions than they can. With that in mind, Stage Stores, the parent company of Bealls, Peebles, Goody’s and Palais Royal, embarked on a split test of its human-driven decision-making model versus an analytics model.

Human decision makers held prices for seasonal merchandise high until demand was almost gone, then slashed prices dramatically to clear it out before the next season’s merchandise arrived. Stores in which pricing decisions were determined by analytics decreased prices gradually throughout the season. The results? Data-analysis stores had higher seasonal profits 90% of the time.

Product stocking optimization

Stage isn’t the only company that has found striking benefits in data analysis, either. Shoe retailer DSW has used analytics to make stocking decisions at its 363 stores. Rather than shipping to each store based on national averages, DSW used data from each store to determine what assortment of sizes to ship to each. Results are that DSW has encountered fewer out-of-stocks, required fewer markdowns and enjoyed higher margins throughout their stores.

Segmentation and personalization

Data analysis allows examination of data at a granular level impossible for human decision makers. It can break down sales data to segment your highest spenders from lower-spending segments and predict what offerings will appeal to that high-spending segment most, based on segment members’ previous purchases. This allows highly targeted marketing that brings extremely high returns.

As knowledgeable as your best decision-makers are, analytics tools like PriceManager can help them sift through the overwhelming amount of data available in your business to make their pricing decisions even more effective.

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