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Pointer Profiling

How we target your best customers


Direct marketing campaigns are fully effective when you can target a customer that is most likely to buy your product or service. 


Database profiling has been around for a long time, but technology has made it a
whole new business. Mass mailings have given way to surgically precise campaigns
that are marketed to specific customers with an accuracy unheard of in the past.
Using all this data to produce more effective direct-response campaigns is another
matter. That’s where customer profiling comes in. 



Factors to consider when you’re building customer profiles:


Affinity profiling analyzes current buying habits to better match the customer to
the product. Using information on what kinds of products a particular customer
is buying, you build an affinity matrix showing how that customer would be
stimulated to purchase a variety of related products. This type of analysis requires
that you have detailed customer information for campaign success.  


Demographic information can be used effectively to build profiles. Demographic
data alone can be effective in segmenting the market for certain products for which such factors as age, marital status, and income are key determinants ofwho buys.  
Lifestyle coding can be used to enhance basic demographic information. The rationale is simple: People in certain demographic categories are likely to have similar hobbies and other interests. 


Mapping is another useful tool in building customer profiles. Census data,
topographic information, geographic coordinates, and zip+4 postal data can all be fed into a computer, yielding maps that can be coded and shaded to reflect certain characteristics of consumers in a particular neighborhood. 


Cluster coding has become a popular means of grouping people by lifestyle characteristics. You’ve no doubt heard such terms as Urban Up-and-Comers, Settled In, and White Picket Fence used to describe market segments. These are clusters--groups of consumers in which various demographic factors suggest a certain lifestyle. Each cluster is given a score according to affluence, and the names suggest social position, activities, and aspirations. 


Survey data can be used to enhance the effectiveness of demographic, lifestyle, and other forms of data in building profiles. Data collected directly from customers via application forms, customer surveys, and credit histories is referred to as internal demographic data. It typically provides a more personal portrait of the customer than data collected from, say, motor vehicle bureaus or the Bureau of Census, which is referred to as external demographic data.


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