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Database and Relationship Marketing

Situation

Companies are increasingly outsourcing e-commerce solutions such as database marketing and relationship marketing. One Pennsylvania-based firm is a leading provider of these kinds of solutions for nationally recognized retailers, manufacturers, and professional sports organizations.

Challenge

The survival of many companies depends heavily on knowing the answer to a seemingly simple question: "How well do you know your customer?" In a challenging environment where competition is just a click away, this e-commerce provider helps its clients become familiar with and ultimately understand their customers.

Solution

After reviewing various data utilization tools, the e-commerce company selected PASW Modeler, SPSS Inc.'s data mining workbench, to help analyze its clients' customer transactions and gain deeper customer insights. They use PASW Modeler to help improve customer understanding by determining what and when customers buy, who spends the most, and who is likely to spend even more.

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Results

Blue chip companies such as Reebok, Palm, and Nickelodeon frequently partner with outside experts to develop and operate their online retailing and direct response marketing operations. One such leading outsource provider of e-commerce solutions offers a comprehensive suite of services, including Web design and development, customer service, fulfillment, merchandising, online and database marketing, and relationship marketing.

This company set out to implement a comprehensive customer relationship management (CRM) solution to help its clients better use information to deepen customer understanding and build stronger relationships.

The organization's first priority was to build a CRM team of dedicated professionals with the right experience, desire, skills, and passion to accomplish the organization's overall goals.

Once assembled, the team knew just the right questions to ask:

  1. Which customers are most likely to purchase a product?
  2. When are they likely to make that purchase?
  3. Which customers are most likely to buy again?

To answer these and other questions, the team turned to SPSS Inc. and PASW Modeler, which the team's leader had used with great success at previous companies.

The group examined accumulated data using PASW Modeler and sorted customers based on attributes such as frequency of purchase, recency of purchase, and expected customer lifetime value. The software gave the team the tools to understand what their clients' customers wanted. In addition, it let them know which customers were likely to churn, at what time, and how best to focus retention efforts.

With the help of PASW Modeler's powerful data mining and data analysis tools, they developed a fully integrated e-mail marketing engine capable of implementing targeted one-to-one e-mail campaigns.

Increased revenue through new e-mail marketing opportunities

The CRM team began by conducting several small-scale projects as a way to begin flexing its data mining muscle. For example, in working with an online sports merchandiser, PASW Modeler was used to identify which of the company's customers would be most responsive to an e-mail marketing campaign.

Prior to using PASW Modeler, the group would e-mail all 475,000 of the sports company's opt-in customers. However, with PASW Modeler, the CRM team was now able to segment those customers based on past purchase history, merchandise preferences, and geographic considerations (i.e., those living near a sports stadium, who might be more likely to buy tickets as a result). Through this approach, they identified who would be most likely to respond to a merchandise offer via e-mail.

Over the course of several months, these targeted campaigns have generated between a five and seven percent clickthrough rate, and nearly a two percent conversion rate. In contrast, blast e-mails typically generate a click-through rate of only one to two percent and conversion rate of less than one percent. Already, these and other e-mail campaigns have begun generating revenue for the company and its clients.

Increased customer lifetime value

The CRM group also uses PASW Modeler to segment customers based on frequency of purchase. They've divided customers into different buckets"—visitors; prospects; and one-time, two-time, three-time, and four-plus time customers—and then used the software to accurately determine a customer's lifetime value. For example, in one client's case they learned that a two-time customer's lifetime value was twice that of a one-time customer, and a four-time customer was worth nearly five times as much.

The goal is to transition Web site visitors from a lower purchasing bracket to a higher bracket. The team uses PASW Modeler to target which customers in each bracket are most likely to move.

Made data mining an integral part of the business development process

During the data mining process, new marketing opportunities are inevitably uncovered. For example, while working with the previously referenced sports merchandiser, the CRM team used PASW Modeler and found that people who like baseball also tend to like basketball—an observation that may have been identified without the benefit of data mining. However, it wouldn't have been supported without such insight as knowing exactly who these customers were, and what, when, and where they would most likely purchase merchandise.

These kinds of insights make PASW Modeler an invaluable part of this e-commerce group's core business solution, and also help win new prospects through the power of data mining.