The Science and Art of Price Optimization
February 5, 2013 Alex Woodie
As a retailer, you strive to get top dollar for every item. But you also realize that setting the price too high will cut into sales. Finding that happy medium can be a difficult experience, fraught with false starts, lost profits, and alienated customers. For price optimization service provider Revionics, which just signed a prominent IBM i-based multi-channel retailer to a contract, finding that perfect price involves a lot of science–and a little bit of art, too.
You’d think it would be fairly easy to set the correct price for a given item. Potato chips, for example, ship from the factory with a price stamped onto the bag that is rarely deviated from. Jeans, video games, and cars have a manufacturer’s suggest retail price (MSRP) that provides a starting point for the pricing conversation.
But any retailers worth their salt will adjust prices according to their current business goal, which could be maximizing profit, maximizing sales, or clearing out old merchandise. Once they develop a strategy, they’ll fine tune their systems to account for additional variables. There’s nothing new here–merchant pricing strategies are as old as commerce itself.
What is new is the way in which retailers are applying information technology to the pricing conundrum. For years, only the largest tier-one retailers could afford price optimization solutions, which require moving, storing, and processing very large amounts of data. Today, thanks to cheap and plentiful processing power and bandwidth, firms like Revionics are selling access to cloud-based price optimization software at a price point that mid-market firms can afford.
Revionics was founded about 10 years ago by Jeff Smith, who also was a founding member of KhiMetrics, which was one of the early developers of modern price optimization software and techniques, and which was acquired by SAP in 2005. The idea behind Revionics was to take price optimization mainstream, and start serving mid-market, regional retailers who were still executing their pricing strategies in Excel.
The business plan has worked well for Revionics, says Karen Dutch, vice president of marketing for the Roseville, California-based company. “When we first started selling products in 2007, we were selling to small regional grocers with between one and 10 stores that were not being served by the big firms, like IBM, NCR, Oracle, or JDA,” she says. “We grow into the tier one grocers and along the way started serving industries outside of groceries, like e-commerce.”
Today, Revionics provides price optimization services for about 31,000 stores in the US. The firm’s client list includes names such as Food City, Save-A-Lot Stores, Gander Mountain, and Woodman’s Market. Last month, Revionics announced that it signed Cabela’s, the $2.7 billion company that sells outdoor products through its catalog, website, and 40 stores. Cabela’s is a long-time IBM i user, and client of JDA and Manhattan Associates. In addition to Cabela’s, Revionics helps other retailers who run IBM i-based ERP systems, including Dick’s Sporting Goods, Scolari’s, BevMo!, and others.
Revionics claims its price, promotion, and markdown optimization solutions have an immediate impact on customers, with an ROI well under 12 months. Price optimization customers can typically expect to see profits increase between 1 and 4 percent, and gross margins increase 2 to 4 percent. Similar, if not better, results are foretold for promotion and markdown optimization solutions.
Dutch says it’s all about leveraging big data. “We require about two years of POS [point of sale] or transaction log data to build the demand model at the store-SKU level, so that you can understand how price sensitive your customers are,” she tells IT Jungle. “Then you’ll be able to understand whether it makes sense to change the price either up or down, and what that’s going to do to your demand.”
Tracking buyer behavior at the store level is critical to setting optimal prices. “Shoppers vote with their dollars,” Dutch says. “If you drop a product’s price by 10 percent, why does it sell 3 percent more, versus some products you drop 10 percent, you sell 5 percent more. That’s what price elasticity is all about.”
What’s neat about Revionics’ system is the simplicity it presents to the customers. All that customers have to do is provide POS data–on a daily, weekly, monthly, or quarterly basis–and Revionics does all the slicing, dicing, and interpretation of the data. The result of the analysis is then presented to the users in a way that shows them the effects of their pricing actions.
Revionics solutions, which run on banks of X86 servers in multiple data centers, typically replace Excel spreadsheets. Once a retailer expands to a number of stores and SKUs [stock keeping units], then it’s almost impossible to track pricing in a spreadsheet. “When you start growing your SKUs and growing your stores, it [Excel] starts to buckle. You just can’t get the answers out. It breaks. You don’t have consistency. You don’t even have time.”
While customers no longer get their hands dirty with spreadsheet formulas, that doesn’t mean they can’t add their own twist to the pricing strategy. “Merchants like to blend in a little bit of what’s called art in retail,” Dutch says. “Regardless of all the knobs we allow them to control around business objectives, strategies, constraints, and operational policies, there’s always that art that allows them to make sense [of their particular situation].”
In addition to price optimization solutions, Revionics helps retailers execute loyalty programs across social commerce platforms, as well as assortment and space-optimization solutions. But despite the pricing transparency that Revionics provides its customers, the privately held company is tight-lipped when it comes to the cost of its own solutions. Suffice it to say, annual subscriptions are likely in the five-figures. For more information, see www.revionics.com.