Meanwhile, PayPal acquires mobile payments firm Paydient.
Retailers ponder polishing up pricing strategies as the web and new software yield real-time data on what the market will bear.
Everyone remembers last year’s online price testing debacle at Amazon.com. The poster child for Internet retailing sparked a major backlash from consumers when it gave different DVD buyers different discounts to test sales response. When shoppers found out - and some who’d been offered lesser discounts complained - the buzz got so negative that Amazon changed it policy to give everyone the lowest price at the end of a test.
It was a lesson for online merchants in how not to do price testing: seemingly at whim, on a heavily-visited site featuring products with high price recall, and without appropriate communication to consumers.
But there’s random price testing-and then there’s strategic price optimization. The concept of price optimization is about trying to get the right product in front of the right consumer at a price that drives sales and value all the way back into the supply chain, and it’s core to retailing. As part of that, merchants have long conducted market research so as to develop pricing strategies. The difference is that now the Internet can give retailers information on con-
Consumer response to pricing in real time, and they can adjust pricing online instantly if they want to. But when experimenting with online pricing under the umbrella of price optimization, retailers must take care both in how they position tests with consumers and in what they do with the data.
Amazon’s early misadventure in online price testing aside, there’s growing interest in the subject among retailers. One indicator is the number of software vendors now offering analytics to retailers that track Internet sales trends and inventory in Internet time. While it doesn’t automatically push new prices out to the web based on the data, analytics software presents the information to retailers in a structured format, runs proven algorithms against it, and then issues price strategy recommendations, making what’s been an art increasingly into a science. “The web offers opportunities retailers never had in the offline world,” says Craig Zawada, senior analyst with McKinsey & Co. “So the questions become: To what extent are they real opportunities? And can you use your online channel not only for pricing more effectively along the dimensions of forecasting, time and segmentation, but also to inform your offline strategy?”
Knocking the barriers
While they have focused for 20 years on wringing much of the excess out of the supply-chain side to lower costs, merchants today are looking to the customer-facing side of their operations for profits. And the online channel’s unique ability to measure response and make rapid adjustments at much less cost than changing store shelf prices or producing catalog supplements remains a tantalizing prospect. So, as Amazon did, merchants are beginning to use the web to experiment with “optimizing” revenues by tracking a variety of customer behaviors and preferences around price. They’re testing online markdown strategies that help them capture greater returns once merchandise hits the virtual sales floor. They’re seeking out safer ways to do it, with tools and techniques that aim to squeeze out profits or sales without impinging on brand promise. And they are so far, not inclined to share the details.
“The web removes a number of barriers to gaining information about consumers’ tolerance to price elasticity,” says Paul Bieganski, chief technology officer of Net Perceptions Inc., a provider of online marketing and merchandising solutions. “You have almost real-time feedback regarding consumer reaction to price. But I have yet to see anyone vary price online to obtain price elasticity information successfully-or at least, they’re not talking about it.”
Those dabbling in online price optimization are keeping it close to the vest. At Santa Clara University, home base for think tank Retail Management Institute, associate director Kirthi Kalyanam says he’s aware of at least four pilots and project implementations in which price testing has generated profit gains in the range of 15% to 40% for e-commerce companies. Zawada says he’s seen companies that have “pushed the edge” in testing price levels online raising prices by 5% to 10% without cutting into sales.
Neither would disclose names. Though silent on specific client cases, however, industry consultants are downright gabby when it comes to describing methods merchants could use to optimize pricing online; there are a bunch of them. The keys to success are how the price tests are designed, how the customer base is segmented, and how price change information is communicated to the online consumer.
“What’s being presented to retailers by the Internet is an opportunity to put intelligence and rigor behind a pricing process that for years has been rules-based ,” says Chris Verheuvel, director of strategic consulting services for Manugistics Group Inc., a provider of analytics software and services. Indeed, price optimization in the brick-and-mortar world has depended on the time-consuming manual review of sales and inventory trends and competitive data. A standard practice has been to decide at the season’s outset how long merchandise would remain at full price, and follow up with incremental markdowns at set times.
But the new analytics software is changing that. Look at what happened when store retailer FashionStyle compared its traditional markdown strategy, based on rate of sale versus weeks of supply, with the software-generated recommendations of ProfitLogics’ Pricing4Profit tool. The goal was to clear inventory of a knit shirt while maximizing the retailer’s return on markdown merchandise. To price and time markdowns as the shirt neared the end of the season, the conventional method forecast that at week 10, the weeks of inventory supply would be greater than the number of weeks until the merchandise would be outdated. The recommendation: a price cut at week 10.
Not so fast