Internet-enabled lead generation

• US 6,868,389 B1
• Filed: 01/18/2000
• Issued: 03/15/2005
• Est. Priority Date: 01/19/1999
• Status: Expired due to Term

• Current Assignee: Media Direct Incorporated
• Original Assignee: Jeffrey K. Wilkins
• Inventors: Wilkins, Jeffrey Kohl, Zoken, Jack Marshall
• Primary Examiner(s): Hafiz, Tariq R.
• Assistant Examiner(s): ALLEN, AKIBA KANELLE
• Application Number:
  US09/484,861
• Time in Patent Office: 1,883 Days
• Field of Search: 705/10, 705/7, 705/1, 705/500
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

A method of generating intender leads in a distributed computer system includes the steps of identifying purchase indicators and extracting prospect identifiers from the purchase indicators. Purchase indicators are pieces of data that represent a potential future purchase by a prospect. For example, an online classified advertisement selling an automobile is a purchase indicator for a potential future purchase of a new car by the old car seller. The prospect identifier, such as a telephone number or email address, uniquely identifies the prospect likely to make the future purchase. Preferably, the method also contains the steps of obtaining full contact information for the prospect from a profile database, applying a predictive model to the prospects to select intender leads, and transferring the intender leads to an interested party, such as a direct marketing service or sales force. An intender lead is a lead for a person intending to make a purchase of a particular product or service within a given time period. Only some of the prospects are actual intenders. Preferably, the method also includes the steps of extracting auxiliary data that is independent of the prospect from the purchase indicator, and obtaining data enhancement information about the prospect from data enhancement databases. The predictive model is preferably also applied to the data enhancement information and auxiliary data. The method is particularly well-suited for the Internet, which is a large source of publicly-available purchase indicators that is constantly updated. The intender leads are preferably transferred over the Internet, e.g. by email, so that they arrive at the sales force when they are still “hot.”

Claims

1. A computer-implemented method of automatically generating intender leads, said method comprising the steps of:

a) determining appropriate purchase indicators that are leading indicators for desired near future purchases and defining in a sources configuration file one or more web page sources that contain said purchase indicators;

b) locating and searching, based on step a), said one or more web page sources on the Internet via an automated spider tailored to access said one or more web page sources;

wherein

said spider is located on a server computer connected to the Internet and wherein

said spider for translating semi-structured information into a structured format;

c) obtaining said purchase indicators from said one or more web page sources by

downloading each of said one or more web page sources onto said server computer and into a specified directory,

identifying and normalizing said purchase indicators according to a normalizer configuration file, and

loading normalized high confidence purchase indicators into a database table;

d) extracting prospect identifiers from said purchase indicators obtained in step c), wherein said prospect identifiers identify prospects;

e) obtaining full contact information of each of said prospects;

f) extracting auxiliary data from said purchase indicators via said automated spider;

g) obtaining data enhancement information including behavioral data, demographic data, and psychographic data;

h) applying a predictive model to said full contact information, said auxiliary data, and said data enhancement information stored in said database table to assess each of said prospects'"'"' likelihood of making said desired near future purchases, said predictive model for predicting whether and what a seller is likely to buy in near future; and

i) selecting intenders from said prospects based on step h), said intenders having a stated or likely intention of making said desired near future purchases in accordance with said predictive model.

2. The method of claim 1, further comprising the step of transferring said intenders selected in step i) to an interested party before said desired near future purchases occur.

3. The method of claim 1, further comprising the step of initiating a direct marketing contact with said intenders selected in step i).

4. The method of claim 1 wherein said prospect identifiers are selected from the group consisting of telephone numbers, email addresses, and postal addresses.

5. The method of claim 1, further comprising the step of obtaining additional information associated with said prospects from a profile database, wherein said additional information is associated with said prospect identifiers in said profile database.

6. The method of claim 1, wherein said auxiliary data are independent of said prospects, and wherein said auxiliary data are semi-structured, further comprising the step of:

translating said auxiliary data into a standard structured format, said translating step is highly tailored to said purchase indicators.

7. The method of claim 1, wherein said one or more sources are selected from the group consisting of classified advertising, resumes, auction boards, life change announcements, and postings to newsgroups, discussion forums, and email lists.

8. The method of claim 7, wherein said purchase indicators comprise classified automobile sales advertisements, and said desired near future purchases are selected from the group consisting of automobile, automobile insurance, and roadside assistance package purchases.

9. The method of claim 7, wherein said purchase indicators comprise classified home sales advertisements, and said desired near future purchases are selected from the group consisting of home, home insurance, telephone service, and moving service purchases.

10. The method of claim 7, wherein said purchase indicators comprise classified boat and RV sales advertisements, and said desired near future purchases comprise leisure product purchases.

11. The method of claim 7, wherein said purchase indicators comprise resumes, and said desired near future purchases comprise financial planning services comprising 401(k) rollover services.

12. The method of claim 7, wherein said purchase indicators comprise resumes comprising a current job title, company, and contact information, and said desired near future purchases comprise purchases of business products appropriate for said company and said job title.

13. The method of claim 7, wherein said postings comprise requests for purchase recommendations, and said desired near future purchases comprise purchases of products corresponding to said requests.

14. The method of claim 7, wherein said auction boards comprise bids for auctioned items, and said desired near future purchases comprise purchases of items similar to said auctioned items.

15. The method of claim 7, wherein said purchase indicators are selected from the group consisting of engagement announcements and wedding announcements, and said desired near future purchases are selected from the group consisting of home, household appliances, home insurance, and life insurance purchases.

16. The method of claim 7, wherein said purchase indicators comprise birth announcements, and said desired near future purchases comprise infant product purchases.

17. The method of claim 7, wherein said purchase indicators comprise obituaries, and said desired near future purchases comprise financial planning service purchases made by a surviving family member.

18. A digital computer system programmed to perform the method of claim 1.

19. The method of claim 1, further comprising the step of:

obtaining said data enhancement information from a profile database, wherein said data enhancement information is associated with said prospect identifiers.

20. The method of claim 1, wherein said auxiliary data includes a classification of a product of said desired near future purchases.

21. A computer-readable medium tangibly embodying a program of instructions executable by a computer to perform the method steps of claim 1.