The discipline of database marketing analysis has historical moorings in direct mail, where issues of advertising productivity continue to dominate the agenda.
Even today, the lion's share of analytical work in our area tends to focus on how to “mail less, mail smarter.” But increasingly, database marketers are discovering that analysis can be extended well beyond mailing list selection. Nontraditional applications of data analysis can produce substantial gains in sales and profit.
Promoting cross sales. Most direct marketers are accustomed to utilizing predictive models to identify likely responders to specific promotions. However, astute marketers have learned that analysis of customer information can also be used to identify product propensities, product affinities and purchase cycles — which in turn can drive product packaging and bundling, customer contact strategies and merchandising.
For example, cable companies have learned that the premium channels customers desire are often not those that have traditionally been packaged together. They have used analytical techniques to identify the unique combinations of channels that customers within each segment prefer and are willing to pay full price for.
Rather than suffer from significant discounting, these cable marketers have learned how to appropriately package their services to more profitably match customer segment preferences. In telecommunications, one local phone company was able to identify the calling features to bundle for specific customer segments. For other segments, they promoted a “pick your own” feature bundling approach. Customers who highly valued choice, even at a premium price, were identified and specifically targeted.
For savvy retailers, innovative planograms and fixturing can be supported by an analysis of in-store product adjacencies. Knowing which products and categories are purchased in combination during the same trip can provide a significant strategic advantage. For example, travel guides, maps, binoculars, portable personal care products and other related items can be displayed in the luggage department, creating a virtual “Travel World” that encourages add-on sales. The same type of analysis supports page layout and design as well as order entry scripting for catalogers.
Product affinity and cross-sell analyses can also be used to understand the implications of exiting a particular product or category. A product may appear to be unprofitable, yet may actually serve as a “magnet,” drawing profitable customers who generate sales of other, higher margin products. By analyzing the correlation between new customers' first purchases and lifetime value, the shortsighted elimination of magnet products can be averted.
Keying in on customer value. Most database marketers know that it's important to look at customer value in allocating their marketing dollars for acquisition, customer development and customer retention. But, most organizations identify value in only one or two ways. There are actually four dimensions of customer value that should be considered: current spending, profitability, share and potential. Innovative analytical techniques can help an organization look at all four of these dimensions.
The current spending of customers is easiest to identify. Profitability is sometimes more problematic, chiefly because marketing databases have not traditionally carried the data necessary to perform the calculations.
Share of customer is more difficult to determine. Sophisticated analytical techniques coupled with industry research can help an organization identify just how much of each customer's business they own. This information can be maintained on your database, providing share ratios for each customer and optimally for each product category.
While companies increasingly calculate customer lifetime value, customer potential is a more complex calculation. While a customer may have a current profitability and forecasted lifetime value, more advanced analysis can identify major changes that may positively or negatively impact potential.
Marrying customer value and customer satisfaction. Most marketers know intuitively that satisfied customers spend more than their dissatisfied counterparts. Yet, placing a dollar value on customer satisfaction has always been an elusive concept, meaning that expenditures designed to promote satisfaction are seldom evaluated for return on investment. The economics of customer satisfaction are even more problematic when the goal is to quantify change. Is a $2 million infrastructure improvement that produces a 15 percent shift from “Not Too Satisfied” to “Somewhat Satisfied” cost effective?
The key is to integrate an ongoing, sufficiently large, representative sample of survey research results with database transactional information. Changes in satisfaction can then be correlated with purchase patterns among multiple segments in the total customer franchise. If measured, pre- and post-event incremental profit can be directly attributed to the initiative designed to increase satisfaction. Equally important, knowing that what customers say and do is often at variance, the attitudinal components of overall satisfaction — the specific “drivers” — can be prioritized in terms of bottom line contribution.
Integrating multiple channels and media. Innovative analyses can make numerous contributions to an integrated customer contact strategy.
As catalogers add retail outlets, or as retailers add a catalog or e-commerce to their mix of channels, database analysis can quantify channel strategies. Organizations are learning that no one channel “owns a customer” — instead, many customers take advantage of multiple channels.
While financial services organizations opened multiple channels several years ago, many have only recently monitored customer profitability results based on channel usage. Retailers and manufacturers have recently opened new direct and e-commerce channels to customers — detailed analyses will be required to monitor performance and identify individual customer preferences.
Creative database analyses will also support media decisions and identify the most appropriate mix of media to support customer contact strategies. While most organizations have learned that reliance on direct mail alone is usually insufficient to sustain the brand, few use analysis to effectively plan, track and measure media usage outside of direct mail. With the accurate capture of promotional history across all media, including broadcast, print, inserts, direct mail, telemarketing and special events, detailed promotion analysis can provide accurate response measurement. Organizations can also more accurately identify the appropriate mix, timing and frequency of promotion by media category for each customer segment.
Basis for planning. Organizations are recognizing that a focused database marketing plan and customer contact strategy are essential to insuring that marketing dollars are spent wisely.
Comprehensive customer analysis can facilitate the planning process by defining and profiling customer segments, identifying channel and media preferences and ascertaining key segment performance statistics such as market penetration, profitability, product penetration, cross-sell and retention. With accurate performance benchmarks, the organization can then establish reasonable and measurable goals for each unique customer segment.
The few examples above demonstrate that marketers' analytical techniques need to extend well beyond predictive models for list selection. Ongoing analysis of all aspects of your business are essential to optimizing customer profitability.
Robert Bibb is a senior consultant and Carla McEachern is senior vice president of analytical services, both with Nykamp Consulting Group, Lombard, IL, a professional services firm specializing in customer relationship management and database marketing.
