Data Appending

• Ad Mailing List
• Auto Finance Info
• B2B Direct Mail
• Business Lead Gen
• Business Leads

• Business Lists
• Credit Card Debt
• Consumer Direct Mail
• Consumer Lists
• Credit Bureau Leads

• Custom Email Lists
• Data Appending
• Direct Mail Marketing
• Direct Mail Postcards
• Direct Marketing

• FHA VA Mortgage List
• Financial Marketing
• Insurance Marketing
• Lead Generation
• List Services

• Mailing List
• Prospect List
• Specialty Lists
• Telemarketing List
• Website Marketing

Data Appending

Data Appending and Direct Mail List information: The fourth Quadrant represents the worst of all worlds: the customer who doesn't spend very much or very often. The potential payoff in identifying such customers is in saving money by targeting a higher proportion of spending toward customers in the first three quadrants. We can further assess the potential of these customers by observing the degree to which companies with certain characteristics, such as SIC code, size, and geographic location, tend to be concentrated in certain quadrants.

For example, if customers from four SIC codes are predominant within Quadrant I (highest sales volume, greatest purchase frequency), we should then analyze what our share of market or degree of penetration is in each of the four SIC codes. When this is done by comparing the customers in our house file against the total number of businesses within each SIC code on the national database, a profile of our market penetration can be seen clearly.

Sometimes there is insufficient information available for profiling, particularly when a new market or segment is being entered. Such situations call for the marketer to obtain primary information directly from prospects in the form of qualitative information (focus groups or in-depth personal interviews) and/or quantitative data (surveys). The research we've just described can tell a company who, exactly, will sign up for the Disney experience, buy the new health food product, or purchase the new fax machine.

Basically, we're talking about sophisticated direct marketing list enhancement married to survey research that measures responsiveness and customer value.

An equation is then developed to predict the behavior we are interested in understanding—say, purchase probability for the Disney experience, health foods, or a new Sony home fax machine. The "independent" or "predictor" variables are the account data, stuff from third-party databases, census info, and so on. Not just that 2.7 percent will buy in the first year (assuming awareness and availability) but who they are attitudinally, psychographically, and geodemographically.

If we have built the bridge from the test to the market properly, the computer will print out (as it did) the names and addresses of approximately 4,680,000 very reachable people.