Priced to sell ... to you

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Priced to sell ... to you

By David L. Margulius
February 15, 2002

	CRM price optimization Price optimization gives companies a way to apply analytics to existing CRM data to improve profitability. Companies can create prices on the fly, based on customers' past buying history and the profitability of the product or service. Successful CRM price optimization depends on access to multiple data sources and correct design of the sophisticated business rules and algorithms that generate the prices.

"HOW MUCH DOES it cost? For you?"

If you've ever heard these words at the corner store, you've experienced CRM-driven price optimization. Throughout history, sellers have tried to get to know their customers, and then used that knowledge to optimize their dealings with them.

Today, companies want more than ever to tap their mountains of CRM data to optimize pricing for individual customers. Until recently, CRM analytics software has been better suited to planning than to actual price generation. But this is starting to change, and large companies are increasingly deploying apps that tap into both CRM and back-office systems to generate prices based on individual customer value and transaction profitability data.

Take Las Vegas-based Harrah's Entertainment, which operates 24 casinos and 16 hotels, under the Harrah's, Harveys, Rio, and Showboat brands. The company decided five years ago to adopt a "world-class CRM strategy," according to director of revenue management Eileen Moore, and built a homegrown CRM system to track the 26 million members of its Total Rewards loyalty program.

When a customer calls Harrah's for a reservation, the system generates a customized room rate for him or her, calculated to optimize profit for the company. The rate is partially based on the "customer segment" the caller falls into. Customers fall into up to 64 segments, derived from statistical techniques and based on prior activity and preferences. Each segment has a code, such as AEP for Avid Experienced Player. "We auto-classify them based on their gaming profit," Moore explains. "What is this customer's value, not just on this visit but on future visits?"

Slot machine customers are more profitable than table customers, for example. The company's 300 call-center reps can see the customer's rating on their screens, alongside the approved offers. "CRM has been done in a vacuum and revenue management has been done in a vacuum and the two never met," Moore explains. "It's what we do on the back end that's so special."

The back end consists of the company's CRM system, a reservation system from International American Data, and an RMS revenue management system from Rockville, Md.-based Manugistics, which performs the segmentation of Harrah's customers, forecasts daily hotel room demand for each segment, and calculates the rate for each segment on any given day. "The whole quoting and pricing process has been left somewhat to chance in the past," said John Hagerty, an analyst at AMR Research in Boston. "People are just out there quoting stuff, making swags."

To rectify this situation, Hagerty said, companies are increasingly migrating planning and pricing intelligence from their ERP order management systems to their CRM systems, and leveraging data from across the enterprise. "This is a natural for the CRM guys to do. ... It's taking horizontal slices through a broad swath of existing applications to optimize price."

Across the CRM spectrum, software is enabling more surgically precise profit optimization based on analyzing customer demand data and cost data. Startups such as DemandTec, in San Carlos, Calif., and KhiMetrics, in Scottsdale, Ariz., offer solutions that enable supermarkets to optimize profit on, say, a bottle of taco sauce, by varying the price in a given store based on expected demand, product inventory, and related events such as a sale on taco shells. Offerings from E.piphany, in San Mateo, Calif., and others enable marketers to predict the likelihood of certain segments turning over (say of mobile phone subscribers) and to generate specially priced promotions to retain them.

The most interesting are those applications that take this trend to its ultimate conclusion: generating unique offers, on the fly, based on individual customers' histories plus profitability factors.

DHL Worldwide Express is deploying startup Metreo's Supplier Response and Supplier Insight products, designed to improve both the speed and profitability of its price-quote approvals for high-volume shipments. Currently, the process takes as long as 10 days and is subject to human imprecision and so-called maverick selling, a technique by which salespeople stretch a company's pricing guidelines in order to get deals done, which can be good for their commissions but bad for the company's profitability.

"We're in the business of urgency," said Isabelle Bax, director of pricing, yield management, and sales support at DHL. She explained that the company's 500 U.S. salespeople will now be able to get quick approvals using the software, which combines historical data and business rules to find the optimal prices at which customers are kept happy and shipments kept profitable. "The idea is to empower the sales force to make decisions on the spot. This is a sales tool, pure and simple," Bax said.

The system will pull customer histories and shipping profiles from DHL's customer master file, data warehouse, and billing system, and combine them with profitability calculations to either accept or modify the salesperson's proposed quotes (including terms). "At what price level am I winning and losing business?" is the primary question the software will consider, according to Bax. What quotes did the customer accept or reject previously, what levels of volume discounts? What competitors have they used? And what is the cost of providing the shipment, based on metrics such as shipment density?

Making this kind of price optimization work requires not just tapping into multiple databases, but designing business rules ("never discount the honeymoon suite on a Saturday night" or "prioritize revenue over profits at the end of the quarter") and leveraging complex algorithms that predict customers' buying behavior based on past history. Metreo's software, for example, was derived from Co-founder and CTO Nachum Shacham's research at the Stanford Research Institute on how to make routing trade-offs between data and voice packets for optimizing videoconferencing network bandwidth.

Despite its rocket-science reputation, expect CRM price optimization to become more and more of an off-the-shelf experience, and a must have for many enterprises. Not only are startups emerging to do the heavy statistical lifting, but mainstream CRM vendors such as Peoplesoft and Siebel are already offering analytics, pricing, and customer profiling modules as part of their suites. Vendors from other enterprise software sectors are scrambling to get into the act as well.

As Paul Rodwick, E.piphany's vice president of market development and strategy, points out, the desire among enterprises to translate CRM data into greater profits is widespread, especially in the current economy: "Everybody wants to make the most out of their current customers," he said.

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