STRATEGIES AND SOLUTIONS FOR CUSTOMER ANALYTICS

processes, services and solutions.

Customer analytics solutions are a lot like cars in that purchasers are often overwhelmed by sheer choice. At the end of the day, a car is, for the most part, a means of transportation. Speed, performance and reliability at any cost may top the priority list of others. While the following three types of analytics solutions were selected most often, one size does not necessarily fit all enterprises. In fact, larger organizations often deploy all three to address varying challenges and roles within an organization:

• Embedded tools are most often deployed when integrated with either a marketing data mart and/or or data warehouse. The chief benefit provided is the ability to explore and build customer profiles, predictive models and/or scores such as propensity to buy. Some tools also provide data visualization capabilities for modeling what-if campaign planning scenarios.
• Point solutions, such as marketing automation, customer relationship management and/or Web marketing applications, allow users to define customer segments and to create profiles prior to campaign execution. Moreover, they also provide operational and dashboard reports on campaign results. While such solutions are not currently capable of modeling predictive scores, users can create rules-based workflows and/or decisioning trees to address customer interactions. Enterprises that integrate embedded tools into marketing automation applications for inbound and outbound campaigns often realize higher results in key marketing metrics (see "The Precision Marketing Benchmark Report: How Top Performers Turbo-Charge Investments" at www.aberdeen.com/summary/report/benchmark/ ra_precisionmkt_la_3482.asp. .
• Enterprise platform—Utilization of customer lifetime value metrics in inbound and outbound marketing processes presupposes use of both transactional (historical) purchasing data, as well as interactional (behavioral) customer data. In most organizations, transactional data is most often stored within a data warehouse, enterprise resource planning systems (ERP) or financial management/accounting systems, while interactional information is most often captured through multichannel touch points: online, call center, in-store or mail. Behavioral information is stored within multiple systems: customer relationship management (42 percent), marketing automation (32 percent) and Web tools (40 percent). Creation of predictive models, scores or workflow can be done with either business intelligence platforms or predictive analytics tools (43 percent) embedded within existing marketing processes.
• Top performers focus on customer value and customer retention at rates two times higher than other benchmarked groups. Moreover, leaders outperform their peers at performance rates that are nearly twice as high in all key metrics except customer acquisition rates—pointing to the efficiencies and greater profitability realized through use of customer analytics.