Customer Profiling & Analysis Results

Processing Overview

Your Customers:

Company X provided a file of 3,028 customers. These customers were recent buyers who attended auctions within the last year (as you defined at project kick-off). The customer file was then matched to a leading compiled universe of over 200 million consumers. We were able to append the following:

• 2,852 records were appended with individual information. Individual information consists of specific intelligence known about the person—attributes such as age and gender which are associated only with a specific individual.

• 2,925 records were appended with household information. Household data includes those pieces of information that are shared by the household. Some examples include Estimated Household Income and Presence of Children in the Household.

• 3,012 records were matched at the neighborhood level and were appended with US Census Bureau information. Census data is only available at the neighborhood level but is useful for analysis because of the excellent coverage. From the census, we get %’s such as, for example, how Asian is a neighborhood.

There were only 16 names and addresses that were missing the necessary data to allow us to match to the prospect universe.

The Prospects

In order to provide optimum value in a profiling environment, it is necessary to compare your customers to the universe at large. After all, how would you know if a specific attribute has significance if you didn’t compare customer attributes to the general population?

Simply stated, our process of comparing your customers to a group of prospects accomplishes two things:

1. It quickly points out areas where your customers are different from the overall universe.
2. It allows us to easily isolate those differences AND take action on your understanding of the differences. We’ve translated learning’s from your profile to list selections so that you can quickly apply findings into list selections to finely target your prospects.

We’ve compared your customer universe to a randomly selected, statistically sound prospect universe of approximately 20,000 records. We’ve also extrapolated this prospect universe to the entire compiled database and reported on actual counts to give you a clear understanding of the available prospect universe, specific to your profile results. We’ve defined and quantified your lead-pool.

The Data

The following suite of data was analyzed:
• Age
• Income
• Presence of Children
• Etc

Profile Reports

These reports, called Customer and Prospect Comparison Reports illustrate the difference between your customers and the randomly selected group of prospects. To help with report interpretation, we’ve included a “Customer Similarity Indicator” which is simply a “+” or a “-“ score. A “+” means that your customers display that specific attribute more than your prospects do.

For both report sets, we’ve included raw numbers and have also translated the numbers into a visually-pleasing graph. While there is a lot of information included in these reports, we’ve attempted to present the data in an easy-to-understand method.

Income:

Income: (continued)

Age:

Age: (continued)

Education:

Education: (continued)

Gender:

Presence of Children:

Marital Status:

Ethnicity:

Homeownership:

Estimated Home Value:

Home Purchase Amount:

Estimated Equity:

Length of Residence: (In Years)

Estimated Monthly Mortgage Payment:

Loan-to-Value:

Number of Open Trades with Balances Greater than $0:

Number of Trades Ever Reported Derogatory:

Average Balance of Open Trades:

Key Findings

• Your customers are slightly less likely to be married than the general population.

• However, they are more likely to have children in the household.

• They are more likely to be homeowners than the general population. And, they live in Single Family Homes.

• Your customers are middle-aged. They are more likely to be 40-58 years old than they are to be either younger than 39 or older than 59.

• They are much more likely to be Asian than the general population.

• Similarly, your customers are more likely to be African-American.

• Also, they are slightly more likely to be Hispanic.

• Your customers have not just moved into their homes within the last year. Conversely, they haven’t been in their homes for more than 19 years. The sweet spot, in terms of Length of Residence is 2-8 years.

Your customer niche is middle-income. You enjoy a high percentage of customers in the income ranges of $50-$150,000 estimated annual household income.

Prospecting Recommendations

The above findings have allowed us to identify a core group of list selects that have targeted your prospect universe, as well as a secondary niche that you should consider.

Core Group Selects: National Count: 4,760,834
• Homeowners
• Presence of Children
• Income of $50-$150,000
• Age 40-58
• Length of Residence 2-8 years

Niche Group: National Count: 134,555
• Apply all of the above selects
• Select Asian ethnicities

If you are planning a direct marketing campaign to reach these targeted prospects and need help with your list selections and data purchase, please let us know.