Positioning Data

Demographic data is not as valuable by itself as it is when combined with other categories of data elements used to identify and predict profiles and behavior, respectively. In typical database marketing, data is used to understand what customers look like and how they behave.

Demographic data tends to be quantitative (i.e., age, income, home value); Psychographic tends to be qualitative since it captures what people are doing and thinking; of course. It is indisputable that Behavioral [transactional] data is the most powerful category of data an analyst can work with when predicting and understanding customer activity. These three categories of data are used to help us answer the Who-WhatWhen-Where-How-and-Why questions.

Behavioral data is the most prized (especially if it describes two or three years worth of activity) because it encompasses service plans used and changes made, payment amounts and regularity, etc. The benefit of history allows us to understand how customers are changing, when they are likely to act, and what they are likely to buy. But since that type of external data is not always available for purchase, Real Estate and Utility data, which can identify new home purchases, loans and phone line connections can be quite accommodative and revealing when taking into account future discretionary income and household consumption.

Psychographic data relates to people’s tastes and opinions and what they have done before and are thinking of doing in the future. Now, ‘attitudinal’ and ‘lifestyle’ are two sub-categories of psychographic data that are not interchangeable or synonymous. For example, ‘intending’ to take up fly fishing is attitudinal; fly fishing is a lifestyle.

Psychographic data adds octane to demographics when it comes to segmentation and enrichment when carving out the appropriate buyer group. Because even though you may be demographically targeting individuals for investment in oil and gas securities it would also be nice to know who within that target group of people with the same age and income are also interested in wildlife and environmental issues. It would be like marketing mail order steaks to a vegetarian. It’s that psychographic ingredient that truly gauges interest.

The idea is to be able to be creative! Like a painter to canvas, utilize together the categories of data like the colors on a palette waiting to be combined to meet the artist’s expression, or in this case, the marketing objective. You want to elicit depth: for example, to be able to identify and target a “36-year old, married mother, who likes gourmet cooking and travel, and holds an FHA variable rate loan.”

This is not to say that demographic data isn’t valuable. Heck, you can’t sell insurance or allocate media without it. But demographic information alone offers far less insight, because it cannot differentiate people’s tastes, attitudes and opinions as well.

If you do find clients using only demographic information, counsel them to look at other data that can provide increased targeting and better insight.

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