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How to identify, target your best customers

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Let’s face it. No matter what some vendors say, there’s no silver bullet that instantly connects marketers with those who are ready to buy. But perhaps the next-best thing is segmentation.

As businesses struggle to generate more leads and higher revenues during lean economic times, many marketers are revisiting proven segmentation techniques to gain actionable insights into customer needs and behaviors.

No longer the exclusive domain of large companies with supercomputers and massive marketing budgets, segmentation tools are now accessible to virtually any company with customer data and a desire to maximize marketing return on investment. Using business intelligence software, it’s now relatively easy to slice and dice customer and prospect populations into distinct clusters defined by shared characteristics. Armed with this knowledge, marketers can confidently build programs targeting the most attractive of these segments.

The segmentation process isn’t rocket science. However, success depends on your ability to identify the actionable attributes

that matter most to your business. Critical success factors may change from one situation to another, and they may shift over time. Therefore, it’s essential to be flexible and resourceful in your approach to segmentation—across multiple marketing scenarios and as a particular marketing challenges evolve.

To illustrate the power and practical benefits of segmentation, let’s look at some real-life b-to-b examples.

A global industrial equipment manufacturer is planning an integrated direct marketing campaign to launch its newest product. Hoping to gain early market momentum, the company seeks to target those who are most likely to buy before others.

Relying on seven years of data collected from direct and indirect sales channels, we segment customer companies into five tiers according to the total volume of products each has purchased. (See Figure 1.) Next, by calculating the median time interval between product launch and purchase date for each tier, tier 3 emerges as the "rapid response" segment—with companies that tend to purchase new products within 74 days. That’s at least 108 days faster than any other group.

Further examination of tier 3 buying companies produces an interesting profile:

• Size:
48% are located at midsize companies with revenues from $25 million to $250 million.

• Job title:
87% include at least one technical manager contact in the database; 31% include at least one executive level contact in the database.

• Recency:
65% purchased a product in the last two years.

• New products:
52% purchased at least one of the five products introduced within the last year (yet only 2% purchased all five new products).

• Products purchased:
On average, companies bought 11 products in seven transactions (about 1.6 products per purchase).

This analysis suggests that an effective launch strategy would first appeal to tier 3 customers, emphasizing the company’s strong connection with technical managers at these midsize organizations. It might also be beneficial to penetrate tier 3 executive ranks more deeply, to supplement relationships with technically astute early adopters.

Furthermore, as the company reaches beyond its existing customer base to identify "high potential" prospects, it would be wise to "clone" tier 3 customers by selecting prospect lists whose attributes match the tier 3 profile.

One size doesn’t fit all

Often, companies that serve multiple markets feel they’re diluting their resources, but they’re unsure of the trade-offs associated with targeted programs.

How is it possible to optimize finite resources while serving both business and consumer segments? Profiling each customer group according to its value can help prioritize marketing investments.

Consider a well-known service company with long-established brand dominance in both business and residential markets. Applying classic RFM (recency/frequency/
monetary value) analysis to a dozen years of customer data, we define high-value segments for both business and residential customers. RFM is an appropriate tool because those who represent the highest worth to an organization often justify the cost of specialized marketing programs. Specifically, we calculate total lifetime sales and average purchase frequency associated with the company’s high-value segments.

We discover that, among high-value segments, business customers generate more than twice the average total lifetime sales ($1,267) of consumers ($555). What’s more, business customers typically purchase about twice a year, compared with a two-year purchase cycle for residential customers.

It definitely makes sense for this company to initiate marketing programs for high-value customers. However, these programs should be customized to align with the distinctly different behaviors of business and residential customers. For example, service reminder postcards should be sent every six months to business contacts, but every two years to consumers.

Timing is everything

Across the b-to-b sphere, direct marketing response rates are slipping—and our next example company is no exception. This world-class business software publisher wants to reverse its declining numbers, but standard metrics haven’t revealed a cause or a corrective course of action.

We begin with detailed statistical analysis that weighs various buyer attributes and behaviors. Ultimately, our scorecard maps small, midsize and large customers according to their likelihood of purchasing within the next 60 days. Using this model as our guide, we anticipate each segment’s receptiveness to marketing efforts. (See Figure 2.)

In this case, previous purchase timing is an important response predictor. For example, we discover that small-business customers that are likely to purchase in the next 60 days most recently purchased three to 12 months ago. And the predicted order rate among these most-likely small-business targets is 13% (compared with a 3.3% order rate for all other small businesses).

The implications are clear:

• Dollar-for-dollar, return on investment is significantly higher when likely buyers are targeted.

• Persuading unlikely segments to act immediately will probably require very costly incentives.

• Even if cost is no object, pursuing unlikely segments with ill-timed campaigns may desensitize many recipients to future messages—or worse, build negative brand associations that are difficult to erase.

By not marketing to unlikely targets in the short term, the software publisher can reallocate resources to more promising initiatives. In addition, the door remains open to revisit these unlikely targets as they transition to likely status at a more receptive point in their decision cycle.

Rebecca Bell Ellis is founder and president of Database Marketing Solutions, a San Jose, Calif.-based marketing consulting firm. She may be reached at rebecca@database-marketing.com.

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