Direct Marketing Strategy: Data Mining

We talk about direct marketing strategy in just about every blog post. The reason why we do this is because we see so many marketers in a frenzied state -- just trying to get the campaigns out on time without fully thinking through how they will track and measure them on the back end. Therefore, this step never occurs, or occurs only as an afterthought. So, the value of it is diminished -- it becomes more of an exercise than a defined part of your overall strategy.

What to do about this? Well, we found an excellent article in MultiChannel Merchant today that gives you some excellent advice on how to integrate data mining into your strategy. The article, written by Rich Brough or Transcontinental Database Marketing in Toronto, provides his ideas on what he feels are "the six stages in the hierarchy of data analytics, and the value of each to a well-rounded strategic approach."

Brough emphasizes that the first thing that marketers need to employ is a consistent approach up-front to identify opportunities within the customer base. He argues that while this may take some time to put in place, the results will be well worth the effort. Therefore, he identifies these six stages for us to consider as part of building this framework:

1) Data access: This is the foundation on which marketers build by collecting all pertinent information about customers, including name, address, demographic data, history of transactions, product and service purchases, and responses to past campaigns. Every business should earmark the appropriate resources to ensure this data is as accurate and up-to-date as possible.

2) Reporting/profiling: Key performance indicators are developed and applied to track the performance of customer relationship management (CRM) initiatives over time and across customer segments. Here, marketers can also track client migrations across various segments, compare responders versus non-responders, and gauge campaign response over time.

3) Current value: The underlying premise for CRM is that not all customers provide equal value to an organization. Therefore, the first step for any CRM initiative is to measure customers by their value to the organization.

For example, 20% of clients might account for 80% of a company’s business, and would be worth a lot of the marketer’s time and money. Another 30% might be designated as moderately valuable, but having the potential to move up into the top 20%; they’d require a different kind of pitch.

The last 50% could account for just 5% of the company’s business; they are less committed, motivated largely by price, and require still another approach (or, maybe, none at all).

4) Segmentation: In this stage, marketers identify prospects who share similar characteristics – who, therefore, belong to one of several specific segments.

This provides the opportunity to focus on the highest-value segments and acquire new customers who match the segments identified as most desirable. As well, sales pitches can be custom-tailored to suit each segment using what is known about those segments. Customers can be segmented using many criteria.

But segments should focus on identifying customers with similar product and service needs as implied through neighborhood socio-demographic characteristics, life stage, usage behavior, or needs and attitudes as identified by market research.

5) Predictive analytics: Use this to predict each customer’s likelihood to initiate a particular activity in future based on their unique characteristics and past behavior.

The benefits represent a “win-win” for the organization and its customers, with marketing ROI rising, and customers receiving more relevant offers – the principle of “right message to the right customer.” Predictive models are developed to assist marketing at all stages of the customer lifecycle, including acquisition, cross-sell and up-sell, retention, and re-activation.

6) Potential value: This is assessed by combining each customer’s current value with their potential to buy more in the future. As with current value, potential value creates an even clearer way to identify the most valuable customers, the ones worth keeping.

It also helps to identify those less valuable customers with potential for entering the most-valuable category, and those low-value clients on whom it may not be necessary to spend as much.

I'm sure that you'll agree that this is excellent advice. As Brogh's states: "Using these six stages, marketers can develop a database-marketing strategic framework that differentiates customers based on the value they currently contribute to an organization, their product and service needs, and their potential future value." This is a much more strategic approach to direct marketing, and one that will have a positive impact on your ROI.

Let's face it, if we are consistently in a hurry in getting out our campaigns, we need to be as efficient as possible. This approach may take some time to set up at the beginning. However, as you move through time, your campaigns will take you less time to create, they'll be more responsive, you'll be targeting the most profitable customers, and you'll be able to demonstrate that your DM efforts are paying off -- in terms of bottom-line profitability.