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E-Sales E-Service Feature Article
April 2001

The Challenges And Rewards Of Personalizing Customer Interactions


If today's marketplace is so rich with ways to communicate with customers, why are so many companies struggling to optimize online interactions? The answer is personalization -- the strategy of successfully marrying in-depth customer understanding with marketing and sales execution to provide customers relevant offers and information. Personalization is the key to optimizing a company's online dialog and enhancing its ability to cross-sell and upsell customers. Knowing and understanding what customers are looking for makes a company's dialog with them -- regardless of channel -- that much more effective. Additionally, because the online channel is 'self-service' in real-time with no direct sales contact, it's critical that every interaction is optimized for mutual benefit.

The challenge is gaining an in-depth understanding of browsing customers' habits and real-time needs without intruding on their privacy or not providing value for the exchange of personal information. Recently published statistics indicate that companies can achieve at least a 20 percent increase in purchases through personalized online dialog. This is supported by a study by the Center for Democracy and Technology that found that 78 percent of Internet users would be willing to provide personal information in exchange for customized services. The dialog, or exchange of personal information for customized offers, must prove valuable to both the customer and the company. Additionally, companies that have successfully gained the trust of the consumer and privilege of learning more about their buying preferences have also been the ones that have been able to increase their customers' annual and lifetime value. Personalization has enabled them to target offers more specifically to the individual buyer's needs for higher response rates to cross- and upsell.

A company cannot rely solely on customers to provide all the necessary information. Online dialogue must be based on predictive analysis. Today, real-time personalization applications that use rich customer data provide the right level of personalization with the most effective offer, content or service to individuals. The technology uses both online and off-line data, combining predictive profiles, current interaction context and business objectives for powerful personalization. Because customers are dynamic, the technology must be dynamic as well. In looking for an appropriate real-time personalization technology, look for those that have an open architecture to enable integration with any real-time system, including Web and contact center systems. Consider how easy or hard it will be to change and enhance your business rules that drive personalization. You want to empower marketers to manage the business rules as much as possible. Look for applications built on RAM-based cache technology so as not to introduce latency into real-time channels. Again, you can only be relevant if you understand the customers in all their dimensions. By combining historical information such as recency, frequency, monetary value, predictive analysis (such as cross-sell recommendations), attrition likelihood and lifetime value with real-time context of the customer interaction including minutes on the Web site, which products they are viewing and pre-defined business rules, you can achieve effective personalization techniques.

Let's take a look at a few examples. Let's suppose there is a "retail/e-tail" company called Gizmos.com that has both a traditional store and an online store, and supports various customer touch points for traditional channels such as a contact center, direct mail and fax, as well as newer channels such as e-mail, Web sites and wireless devices. Gizmos.com is a sophisticated marketing company that understands the value of building long-term relationships with its customers by using analytical CRM and marketing automation for its marketing communications. Additionally, Gizmos.com provides real-time context-sensitive personalization at its Web and contact centers for anonymous and known users based on online and off-line data.

Scenario #1. An individual arrives at Gizmos.com from an affiliate Web page, Gadgets.com. Based on informational profiles the marketing team at Gizmos.com has built for an individual coming from Gadgets.com, Gizmos automatically personalizes the site. Based on lifetime value information, an instant offer of "10 percent off your next purchase" pops up while the customer is browsing. Additionally, after the customer has put a few items into his or her shopping cart, specific cross-sell recommendations are made. The profile is based on information from individuals who have come to Gizmos.com from Gadgets.com, as well as what has been accumulated in the shopping cart. The Gizmos.com site can be tailored with banner ads, graphics, information and articles more relevant in nature to these individuals than the standard Gizmos.com site.

Scenario #2. An anonymous visitor arrives at Gizmos.com. The marketing team at Gizmos.com needs to be armed with ways in which to personalize the site based on the new individual's interests, and again must be willing to personalize in exchange for information. As a hook, the marketing team makes a "free shipping" instant offer in exchange for registration on the site, which includes just a few key questions about the visitor's interests. Then, as the shopper continues to browse, the real-time personalization application may recommend specific graphics, banner ads and information. As the customer puts items into his or her shopping cart, cross-sell offers are presented based on the product profile.

Scenario #3. A known customer visits Gizmos.com. The Web site will already be personalized with a welcome screen identifying the customer's name and, as this is a high-value customer, offers "free shipping on your next purchase over $100." As the customer places items in the cart, a live chat becomes activated and is displayed for this high-value customer to ensure there are no barriers to purchase. The high value associated with this customer has been generated from historical data, predictive analysis and data from online and off-line sources. Again, cross-sell items can be displayed based on a customer profile that was generated by sophisticated models.

Overall, the technology enables marketers to be nimble and flexible in tailoring personalized exchanges. It exploits available online and off-line data for known and anonymous users and adapts to user and aggregate site behaviors. Unlike touch-point-specific, hard-coded rules or simplistic modeling around a single channel's data, the personalization strategy and technology facilitates flexible dialog, increasing the likelihood of a successful sales transaction. Successful personalization techniques ensure that what you are offering your customer is relevant. The more relevant the offer, the more likely the customer is to accept, creating higher ROI for your company and satisfaction for your customer.

In today's changing marketplace, every customer interaction is critical. Each customer contact is an opportunity to keep or lose a customer, as well as build brand loyalty or undermine it. Effective personalization, based on rich cross-channel customer understanding, is key to successful interactions. Consumers are willing to provide information in exchange for a value-added relationship. By using online interactions and the Web's ability to collect information directly and indirectly from your customers, you should leverage that information to enhance the value of the exchange. By offering timely personalized communications, companies will find that they optimize all their online interactions.

Jennifer L. Sullivan is the manager of Database Marketing at Unica Corporation (www.unicacorp.com) in Lincoln, Massachusetts.

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