Buyer-driven targeting of purchasing entities

Abstract

A method for buyer-driven targeting comprising the steps of: separately receiving from each of a plurality of buyer entities a respective third party proof of purchase record; entering information contained in the received proof of purchase records into a searchable electronic database; obtaining search criteria for the database; searching the information in the database based on the search criteria to obtain a group of buyer entities; and providing an incentive to each of a plurality of the buyer entities in the group.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application is a Continuation of U.S. application Ser. No. 09 / 888,439, filed Jun. 26, 2001, which is a Continuation-In-Part of U.S. application Ser. No. 09 / 758,239, filed Jan. 12, 2001, which claims priority from Provisional Application U.S. Application 60 / 243,960, filed Oct. 30, 2000. U.S. application Ser. No. 09 / 888,439 is also a Continuation-In-Part of U.S. application Ser. No. 09 / 837,377, filed Apr. 19, 2001, which claims priority from Provisional Application U.S. Application 60 / 243,960, filed Oct. 30, 2000. All the aforesaid applications are incorporated herein by reference in their entirety.FIELD OF THE INVENTION[0002]The present invention relates generally to the field of marketing, and more particularly to the field of buyer-driven targeting of purchasing entities.BACKGROUND OF THE INVENTION[0003]In the U.S. alone, marketers spend more than $230 billion per year on advertisements to acquire new customers. Yet, there is no goo...

AI Technical Summary

Benefits of technology

[0020]Briefly, in one embodiment the present invention comprises a method for buyer-driven targeting comprising the steps of: separately receiving for each of a plurality of buyer entities a respective third party proof of purchase record; entering information from the received proof of purchase records into a searchable electronic database; obtaining search criteria for the database; searching the information in the database using the search criteria to obtain a group of buyer entities; and providing an incentive to each of a plurality of the buyer entities in said group.

Problems solved by technology

Yet, there is no good way to target these advertisements and promotions at those buyer entities—such as individuals and businesses—who are most likely to become valuable customers.

Marketers suffer from improper targeting of their promotions and so do buyer entities.

Yet, marketers generally cannot not access information on the purchases of a buyer entity who has not yet been acquired and on the purchases that an existing or potential customer makes with other companies.

Both of these methods have significant drawbacks.

The main drawback of this method is that information given by customers about their past purchases cannot be properly verified.

In fact, because these companies cannot verify information about purchases obtained in this manner, they cannot pay higher rewards to members who claim to have stronger and more relevant purchase histories without encouraging false or misleading answers.

In fact, to date, none of these companies is known to have implemented a system of differential rewards.

Also, buyer entities generally give highly unreliable answers to questions asked by web sites and direct marketing companies, even when their answers do not affect the benefits that they get when using the service.

Additionally, answering questions takes time which the buyer entity may not be willing to give and which also ties up the network.

The main drawback of this method is that Abacus Direct and other companies that compile transaction data from certain marketers cannot—and do not—allow other marketers to use this information for the purpose of directly competing with those who provide the information in the first place.

But Abacus Direct cannot allow him to review a list of consumers who have bought jewelry itself.

Furthermore, because these companies obtain records from a limited number of marketers, they obtain only very fragmented information on individual customers or business entities.

Abacus Direct, for instance, maintains records that cover many million households, but with very limited information about the average household in its database.

But an established reputable company cannot send Emails to customers without first having obtained the customer's permission to do so.

However, these players face the same problem than the one described above for networks of non-competing merchants: they cannot allow marketers to use the information that is provided by participating companies for the purpose of competing with the very same companies that provide the information.

A credit card company for instance, like American Express, cannot reasonably hope to retain it's merchants as clients if it was to potentially use the information obtained from these clients to grant the competition access to its' clients proprietary customer lists.

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