Innovative Retail Technologies

SEP-OCT 2016

Innovative Retail Technologies (formerly Integrated Solutions For Retailers) is the premier source for innovative yet pragmatic technology solutions in the retail industry.

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T hink pricing strategy was impor- tant ten years ago? It's an absolute imperative today. Consider that back in July, Amazon Prime day stoked so much interest in price strategy and op- timization software from so many retailers that we struggled to get our calls on the schedules of this column's guest experts. Their talents and time are in high demand. Fortunately, Jeff Moore and Guru Hariharan managed to squeeze us in. Moore, who was previously lead architect of demand management science at SAP, is now chief science officer at Revionics. Hariharan, who launched Boomerang Commerce four years ago, is CEO of the company after successful stints at Amazon, eBay, and Shutterfly. Changing Demand Elasticity Rules Hariharan says price transparency among consumers — who habitually check competitive pricing while shopping — has changed the rules around measuring elastic- ity of demand. "The holy grail used to be analyzing and optimizing internal elasticity of demand," he says. "Understanding how tweaks to the price of bananas or sugar elicited a market reaction helped merchants maximize their margins on those products." Now, he says, the merchant's focus must be on market elasticity of demand. "If you're selling a particular Cuisinart blender, internal demand elasticity might tell you that your customers are willing to pay $200 for it. But it's equally important to know where your competitors have that blender priced, because today, competitive pricing has a much greater bearing on sales than internal elasticity of demand." These dynamics support the case for price optimization solutions to ensure competitive and strategic pricing. Moore says modern price optimization solutions are built using big data technology that leverages the increasing frequency and volume of data that retailers have access to. "We're seeing very mature mathematical techniques and ever-increasing sophistication of self-learn- ing algorithms that monitor and respond in real time to changing demand signals," he says. "We're using scalable cluster-based computing architectures and leveraging grid optimization to serve customers no matter where they are on the globe." If that sounds pretty high-tech for determining the amount printed on your price tags, it's because pricing is a pretty high-stakes game. Hariharan relays the story of a new Boomerang customer who realized those stakes the hard way. "Price intelligence and price optimization are two different things," he says. "This customer had price intelligence, but it didn't have price hygiene. Last year, the company accidentally put a $199.00 television on sale for $19.99 and sold 10,000 units in an hour." This risk, says Hariharan and Moore, necessitates the high technology and data science that go into setting strategic prices and ensuring those prices are executed. "If you only have price intelligence, you've just crossed half the bridge," says Hariharan. Sept-Oct 2016 26 "You also need automation that supports pricing hygiene in a system that has your back. The more adoption of price optimi- zation we see, the more difficult it is for consumers to go to sites like Slickdeals and exploit those mistakes and missteps." Testing The Limits Of Price Moore says that sophisticated scenario planning and simulation capabilities can help merchants simulate various pricing ap- proaches and understand the impact of tak- ing a price or launching a promotion before they commit by using predictive models. "It's also important to test and learn in the real world to get beyond any limitations of the data in the model," he says. "The real-world data feeds back into the models and helps them evolve and continuously become even more accurate. We see test-and-learn tools such as Applied Predictive Technologies as complementary solutions to price optimiza- tion. It's a powerful way for retailers to em- pirically validate the model before deploying wholesale, while enabling predictive models to improve even more quickly." Hariharan warns, however, that the day of the "sacred cow" is behind us. "There was a time when auto parts retailers could get away with setting very high and inelastic prices on the items consumers needed when their cars broke down, things like gas cans and tire repair kits, for instance," he says. "Floor mats, on the other hand, were highly competitive, less a necessity, and therefore far less sacred. Is this really still true today?" What's Next Price transparency is putting pressure on merchants to get strategic and granular about how they manage prices and drive profits. Smarter Pricing, Bigger Profit BY MATT PILLAR

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