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Inductis White Paper

The Data-Driven Business
Martin Ahrens, Vice President Methodology & Quality Assurance Inductis

Successful customer acquisition, retention and new product development, all depend upon customer understanding. Customers’ needs, wants, sensitivity to offer details, channel preferences, price sensitivities, risk characteristics and demographics are all important factors in the creation or maintenance of a profitable relationship. Clearly, finding all the relevant data is one of the marketer’s biggest ongoing challenges.

There are several major categories of data that can lead to an understanding of customers or prospects, and how they might respond to new products and offers:

Past marketing efforts – How have they been reached in the past? What were the results, including whether they responded, how much they spent, how long they remained a customer, exactly what they bought, whether they met risk criteria, etc.
Existing customer relationships – Depending upon the business, individual customers may have many interactions that provide a lot of useful information: transaction history, levels of spending, payment history, etc.
Third party data on customers and prospects (whether or not they have already been contacted) – Demographics (both neighborhood and household), credit information, shared information from other marketers, and additional information that can be inferred (for example, a recently married couple might soon be in the market for baby products or a prospect with little or no debt and a good income might be in the market for investment products).
New data generation – Using focus groups, surveys or test marketing (this is a form of scientific experimentation and can be very valuable because it is controlled). It can be used to test the effectiveness of product design, message, channel and price; compare different settings of these parameters, identify overall optima or customize offerings to specific segments (also identified through the same experimental process).

Tradeoffs among Data Categories

Each data category has its strengths and weaknesses when compared to the others.

BENEFITS	COSTS/WEAKNESSES

*1. Prior Marketing Experience*
Data is already available; no additional cost or delay. Accurately reflects real experience in the marketplace.	Data is usually not statistically balanced, so comparisons may be less reliable. Other nuisance variables may have influenced the marketing results. Data may not be available on all options to be assessed. Data is historic and may not be relevant to future time periods.
*2. Existing Customer Relationships*
Data is already available; no additional cost or delay. Accurately reflects real customer behavior. Provides learnings about both specific individuals and others with similar profiles.	Not useful for understanding how existing customers would react to completely new products. Not useful for understanding reactions and preferences of prospects who differ from current customers.
*3. Third Party Information*
Usually extensive information is available. Cost is usually affordable. Enables leveraging experience of other marketers or discovering new prospect profiles.	Too expensive in some marketing situations. Coverage is sometimes insufficient. Some systematic bias in terms of whose data is available.
*4. New Data Generation*
Enables testing of exact offer and product characteristics of interest. Accurate and reliable comparisons facilitated by carefully balancing design of questionnaire. Close in time to full marketing roll out.	Delay relative to using historic data Cost for multifactorial understanding may be prohibitive for some businesses. Need to consider risks to brand image

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