Prospective customer selection using customer and market reference data

• US 6,061,658 A
• Filed: 05/14/1998
• Issued: 05/09/2000
• Est. Priority Date: 05/14/1998
• Status: Expired due to Term

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: International Business Machines Corporation
• Inventors: Grossman, Edna, Chou, Paul B., Kamesam, Pasumarti V., Gunopulos, Dimitrios
• Primary Examiner(s): MacDonald, Allen R.
• Assistant Examiner(s): Jeanty, Romain
• Application Number:
  US09/078,672
• Time in Patent Office: 726 Days
• Field of Search: 705/1, 705/10, 705/14, 705/26
• US Class Current: 705/7.33
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0247 Calculate past, present or future revenues
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: Y10S 707/99931 Database or file accessing

Abstract

Prospective customers may be selected for target making with respect to a particular product and market without the need to conduct designed marketing campaigns. A computer implemented process applies data mining techniques to databases containing records representing customer and overall market populations for the purpose of selecting market segments and prospective customers for targeted marketing.

Claims

1. A computer implemented method of selecting customers comprising the steps of:

selecting a reference market population;

inputting demographic data on a multiplicity of households in a reference market population;

selecting a customer population;

inputting demographic data on a multiplicity of customers in a customer population;

inputting a variable identifier to each of said multiplicity of customers in said customer population and to each of said multiplicity of households of said reference market population;

sorting said demographic data on said multiplicity of households and said multiplicity of customers by a multiplicity of segments, each said segment representing one or more demographic characteristics; and

calculating a statistical score representing each of said segments from a ratio comparing an amount of said multiplicity of said customers to an amount of said multiplicity of said households, and

using said statistical score to select a group of households from said reference market population.

2. The computer implemented method as in claim 1, further comprising the step of displaying the statistical score and prospect records based on the statistical score.

3. The computer implemented method as in claim 1, wherein said step of calculating a score includes the steps of:

determining a percentage of said customers represented in each segment; and

determining a percentage of said households represented in each segment.

4. The computer implemented method as in claim 1 wherein said demographic characteristics are determined by a user'"'"'s customer records.

5. The computer implemented method as in claim 1 further comprising the steps of:

sorting said segments by said score;

computing an amount of each of said multiplicity of customers for each of said segments;

for each of said segments, summing an amount of said multiplicity of customers covered by segments with scores bounded by score of said segment;

computing an amount of each of said multiplicity of reference records for each of said segments;

for each of said segments, summing an amount of said multiplicity of reference records covered by segments with scores bounded by score of said segment;

selecting segments based on a threshold score; and

determining a target market based on a characteristic of said selected segments.

6. The computer implemented method as in claim 5, wherein said step of sorting said segments is by ascending score.

7. The computer implemented method as in claim 5, wherein said step of sorting said segments is by descending score.

8. A computer system for selecting customers comprising:

an input device for inputting demographic data on a multiplicity of households in a reference market population and demographic data on a multiplicity of customers in a customer population and inputting a variable identifier to each of said multiplicity of customers in said customer population and to each of said multiplicity of households of the reference population;

a central processor for sorting said demographic data on said multiplicity of households and said multiplicity of customers by a multiplicity segments, each said segment representing one or more demographic characteristics, said central processor further calculating a statistical score representing each of said segments from a ratio comparing an amount of said multiplicity of said customers to an amount of said multiplicity of said households; and

an output device responsive to said central processor for displaying the statistical score and prospect records based on the statistical score.