Leveraging information for real-time decisioning at all touchpoints is at the heart of active enterprise intelligence. Whether it is the Web site, kiosk or ATM, point of sale (POS), call center, branch teller or ticket reservation office, providing intelligence to front-line decision makers and systems in response to customer events is critical to driving long-term profitable relationships with customers.

This kind of intelligence requires both historical and in-session information to determine the most appropriate course of action, taking into account the customer's past and predicted value, the customer's history of complaints, and the company's service responses, stock in hand, variable pricing and special promotions.

Coupling active data warehousing with a real-time analytic infrastructure can provide an integrated solution for real-time channel interaction to maximize opportunities with your customers.

A specific channel: call center
Customers hate telemarketing calls—especially at dinnertime. So marketers now focus more on inbound marketing and must take steps to be ready to react when customers initiate calls to their company.

When a customer calls the toll-free phone number because she has a question about her mobile phone bill, that is the time to not only service her problem but also initiate a conversation on other offers. Perhaps she needs a phone with stronger reception capabilities or is over her minute limit and needs a different plan. In general, after the customer's question or problem is resolved, companies can suggest next best offers. Research from Teradata's Financial Industry Board of Advisors meeting in spring 2007 concluded that because there are 10 times the number of inbound versus outbound calls, and inbound acceptance rates are up to three times as high as outbound, the net result boosts offer acceptance rates from just 2-4% to 20-40%.

This kind of real-time decisioning is good for customers but also better for the company for two reasons. First, in the call center example, complete and accessible information improves agent productivity and morale and reduces turnover, which in some industries averages 20% per year. Second, the same strategic insights that guide what to say on the call center channel can be reused on other channels, like the in-store or in-branch computer screen or on the Web site.

What's new under the touchpoints
To see how to enable active enterprise intelligence with real-time channel integration, look at the real-time analytic infrastructure. (See figure.)

A real-time analytic infrastructure builds a unique profile dynamically each time a customer comes into a channel. It retrieves information from the data warehouse and uses real-time information that is dynamically gathered during the interaction. This dynamic profile is then run through a set of business rules to determine the individual's eligibility for campaigns or offers. Once eligibility is determined, the analytic infrastructure runs real-time analytics to determine the likelihood estimate for this individual to respond to any of the offers for which he or she qualifies. Once likelihood estimates are calculated, they are applied to a set of arbitration rules to determine the most relevant, prioritized offer to deliver to that customer.

enlarge The real-time analytic infrastructure dynamically builds data profiles in real time from multiple sources, executes decision engines and then delivers a prioritized offer to the customer.

These four steps—dynamic profile construction, eligibility qualification, likelihood estimator analytics and arbitration—are done in real time while the customer is at the channel. With a real-time analytic infrastructure, marketers can improve inbound offer effectiveness automatically and continuously. They can also apply these findings to outbound channels.

This approach is better than a business-rules-only system, which is unable to learn. Rules-only systems also require marketing and IT to account for and manage every possible customer scenario in advance. This, in effect, can lead to more offers, segments and scenarios. The resulting complexity makes the system difficult to adapt and costly to maintain.

Another key differentiator is that the real-time analytic infrastructure is self-learning. It continuously refines the models and the scores based on how different customers respond to different offers. This continuous refinement reduces day-to-day maintenance of the models and improves offer effectiveness.

Any real-time analytic infrastructure must be scalable and capable of running real-time analytics on millions of offers per day to thousands of different channel instances. Whether thousands of customers transact with call center agents or make hits on the Web site, the real-time analytic infrastructure needs to scale to meet enterprise levels of functionality. T

Inbound marketing in action Bell Mobility, a division of Bell Canada Enterprises, implemented a real-time analytic infrastructure to transform Bell Mobility's call centers into selling centers. Though wireless service is a main profit source for Bell Mobility, the only way to generate new revenue from existing customers is to cross-sell features and upsell new rate plans. To meet this challenge, the company's marketing and customer service teams implemented Inbound Marketing from Infor, which Teradata OEMs as Teradata Interaction Advisor. With Inbound Marketing, inbound calls are handled more efficiently, because the system immediately identifies customers from their phone numbers; analyzes dozens of customer attributes such as transactional, demographic and usage data; and immediately presents customer service representatives (CSRs) with the most appropriate offers for a specific customer. The company has 7,000 CSRs using the tool, and it plans to train an additional 3,000. CSRs are now more comfortable with selling complex product offerings, because they have all of the details on their desktops to walk customers through the new services and value-added benefits. It paid off, with a more than 50% response rate to offers. The industry average is 35%. "When we initially started, we were looking at a 10-15 percent response rate, so this is a huge increase," says Owen Sonnenschein, associate director of CRM Development and Implementation for Bell Canada. "Inbound Marketing has helped us remain competitive. Our customer service representatives can now easily determine whether customers qualify for services and extend the right set of offers and promotions." The company's investment in Inbound Marketing has already paid for itself and requires only a small administration team. "With Inbound Marketing, all of our metrics are up and we have increased our ability to sell to customers," Sonnenschein adds. "That is success." —C.T. and D.S.

A new Teradata customer management addition: Teradata Interaction Advisor enlarge The customer experience management architecture establishes the value of having "corporate memory" based on an enterprise data warehouse and how real-time integration establishes connections to channels to differentiate the customer's experience. Teradata Interaction Advisor provides a real-time analytic infrastructure to enable real-time channel integration and active enterprise intelligence. Teradata Interaction Advisor is channel-agnostic: You can integrate virtually any channel using your existing channel infrastructure via a core set of technology integration points. (See figure.) Teradata Interaction Advisor works with Teradata Relationship Manager to enhance the effectiveness of inbound and outbound channels, driving better response and greater returns. Enterprise rules drive the selection of the best action and channel to deliver to each customer. The combination provides centralized offer management, improving consistency and providing better campaign control, execution and management. Also, it uses a single data repository and single customer record for a holistic view of customers and campaigns, reducing costs related to data management. —C.T. and D.S.

Chris Twogood is director of Teradata CRM Analytical Applications.

Dave Schrader is director of Strategy and Active Enterprise Intelligence Marketing for Teradata.

Teradata Magazine-March 2008