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Avoiding Analysis Paralysis
Single-view. Real-time. Predictive. The variety of analytics applications can be overwhelming. Here are the key trends in analytics to help sort through the clutter.
For the rest of the July 2002 issue of CRM magazine please click here
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The Internet boom, improvements in reporting tools, and the general desire to better understand customers have all contributed to a phenomenon proliferating among corporations: Data collection is growing at an astounding rate. "There's a new world of data volumes," says Douglas Hackney, president of Enterprise Group Ltd., a business intelligence consulting company in San Diego. "There used to be the terabyte club. Now, petabytes are casually discussed. We are on the cusp of a deluge of data beyond our imaginations." Considering 1.44 petabytes equals 1 billion 3.5-inch floppy disks, it is easy to agree with Hackney's assessment. Industry pundits claim investments in operational CRM started the trend toward the petabyte club. With dataconsumption levels soaring--specifically customer data--it makes sense for organizations to interpret the data through the use of analytics to better understand their customers. "Initially, a lot of the investment in CRM has been on the operational side, to enhance the efficiency and effectiveness of call centers, sales force automation, and Web integration. This gives companies the ability to better manage the customer interaction. Now, we're seeing a drive toward the analytical side--connecting the head to the torso--to determine how to get those interactions to drive value," says Paul Cole, vice president and global leader of the CRM service line at global consultancy Cap Gemini Ernst & Young, based in New York. Aberdeen Group Inc., an IT consultancy based in Boston, has also recognized the drive toward the analytical side of CRM, and as a result started tracking the analytics market last year. In 2001 corporations worldwide spent more than $4 billion on analytical CRM, which includes infrastructure, tools, and applications, according to Aberdeen Group. It expects that number to grow to nearly $11 billion by 2005. "If you look across the spectrum of CRM suppliers, they either have analytics, are looking to get analytics, are increasing the sophistication of their analytics, are making analytics easier to use, or are attempting to make their analytics available to a broader population of business users," says Bob Moran, research vice president and managing director, covering data knowledge and analytics at Aberdeen.
"Analytics will become the dominant way of doing things. It's a winning idea all the way around," adds Bob Blumstein, director of CRM analytics and marketing applications for research firm IDC, based in Framingham, Mass. Wrong Impression Although many corporations have long understood the value of analytics in gaining a competitive edge, their methods of collecting and measuring data for analysis were cumbersome and their choice of analytical metrics were inadequate, says John Hughes, senior vice president of sales and marketing at Silvon Software Inc., an analytics software vendor in Westmont, Ill. Hughes is a 29-year industry veteran who has held management positions in sales and marketing at companies such as Motorola Inc. and Hewlett-Packard Co. Ten years ago, Hughes recalls, analyzing customer data often required employees to sift through large volumes of paper-based recency, frequency, and monetary (RFM) monthly reports. The problem, however, with RFM reports is they only identify how recently customers bought something, how frequently they buy, and how much they spend when they buy, but it does not identify how much it costs to keep each customer--an oversight that could prove fatal. "Marketers were killing trees and getting nowhere," Hughes concedes. By solely focusing on RFM, marketers are only watching sales and neglecting profitability. If a customer's request deviates from the norm, it can often be costly to an organization--in some cases too costly to keep the customer. Some customers may have special shipping, billing, or packaging needs. Others may not pay their bills on time or may demand large discounts. Additionally, a customer may be a huge support burden, perhaps due to a high product-return rate. If, however, organizations can identify which customers cost more to keep and why, the companies can try to resolve the situation. They could, for example, bill the customer with appropriate restocking charges, packaging charges, service charges, or shipping charges; refer the customer to a business partner such as a distributor that can better handle shipping needs; or drop the customer altogether. Analytical applications and tools are providing what is commonly called a single view of the customer across the enterprise. "Without these tools you don't have a simple view of a customer's true profitability," Hughes says. Real Time, One View To obtain a single view of the customer, businesses need to see how each customer interacts with the company in the sales, marketing, and customer call centers, as well as make this information available across the enterprise to whomever might benefit from the information. The next step for the single-view approach is to make it real time. By enabling analytics to be conducted in real time across the enterprise, organizations are realizing they can turn their service centers into sales centers by enabling customer service representatives (CSRs) to cross-sell and upsell when customers call for support, IDC's Blumstein says. An example might be a CSR fielding a customer complaint about a product. If the CSR can instantaneously access known information about the customer's preferences and cross-reference them with existing sales or promotions, the CSR could make a sale right over the phone, enabling the company to keep a customer it may have otherwise lost. Already, vendors are coming out with real-time, single-view CRM solutions. E.piphany Inc.'s latest release, E.6, offers E.piphany Dialogs, which enables real-time, guided conversations and multichannel support for customer dialogs through any touch point. "Most CRM applications just store the customer data. We allow you to look at the information across the enterprise and possibly change the process of how you want to deal with that customer," says Roger Siboni, president and chief executive of E.piphany, in San Mateo, Calif. Predictive Analytics A real-time, single-view solution helps organizations make the best decisions based on up-to-the-second information, as opposed to making decisions based solely on old information collected in the past. This is a significant improvement, however, analytics vendors are now taking the next step. They are helping organizations step into the future by offering predictive analytics. Predictive analytics, used in conjunction with RFM metrics, enables organizations to go beyond what they think might be true based on customer profiles, and enables companies to target people who act like their customers and not those who look like their customers. For example, a 35-year-old soccer mom may buy like a 45-year-old male. Predictive analytics more accurately identifies what people are likely to do, says Carla McGrew, director of retail client development at Sightward Inc., a predictive analytics software vendor based in Bellevue, Wash. Going beyond RFM, which measures only transactional data, predictive analytics measures behavioral data. Behavioral data includes such customer information as click stream data (how customers move through a Web site), whether customers use coupons when they buy, or whether customers used a credit card to buy, and so on. "Predictive analytics can determine whether you target a certain customer with a specific insurance offer or not, or if a customer is likely to leave a cell phone company for a competitor. It can find out if a potential customer is likely to buy if I give him 10 percent off or give him free shipping. Will he buy from me if I mail him more often? It can tell you not only who to contact, but how to contact the customer and with what type of offer," McGrew says. So if your organization is contributing to the data consumption phenomenon, why not make use of the data it is already collecting with smarter analytics tools?
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