SALES LEAD QUALIFICATION OF A CONSUMER BASED ON SALES LEAD RULES

• US 20150046214A1
• Filed: 08/12/2013
• Published: 02/12/2015
• Est. Priority Date: 08/12/2013
• Status: Active Grant

• Current Assignee: Thryv, Inc. (Mudrick Capital Management LP)
• Original Assignee: YP Intellectual Property LLC
• Inventors: Jain, Mehul, Laux, Kent William
• Granted Patent: US 10,984,430 B2
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

Systems and methods for qualifying a sales lead may include one or more of the following. Information, received via a network, about an identified end-user computing device and/or an end-user of the identified end-user computing device may be processed. Lead qualification rules that include criteria for qualifying a lead may be accessed. A characteristic of the end-user of the identified end-user computing device may be derived based at least in part on the information about the identified end-user computing device and/or the end-user. A lead characterization of the end-user of the identified end-user computing device may be generated based at least in part on the characteristic of the end-user of the identified end-user computing device and the lead qualification rules. The lead characterization may indicate a lead assessment of the end-user. The lead characterization of the end-user of the identified end-user computing device may be stored.

Claims

1. A computer-implemented method for qualifying a sales lead, the computer-implemented method comprising:

processing, by an information handling system, information, received via a network, about one or both of an identified end-user computing device and an end-user of the identified end-user computing device, the information corresponding at least in part to data captured about one or more telephone calls placed via the end-user computing device, wherein the information is retained in one or more tracking information repositories;

accessing, by the information handling system, a set of lead qualification rules that includes a set of criteria for qualifying end-users as leads, the qualifying comprising determining lead assessments, where each lead assessment indicates a respective potential of a respective end-user to conduct business;

deriving, by the information handling system, a characteristic of the end-user of the identified end-user computing device based at least in part on the information about one or both of the identified end-user computing device and the end-user of the identified end-user computing device, wherein the deriving a characteristic of the end-user comprises identifying one or more aspects of the one or more telephone calls as indicia of a lead based at least in part on data captured during one or more conversation streams, the data captured during one or more conversation streams comprising call content from at least one of the one or more telephone calls, and the identifying one or more aspects comprising analyzing the call content;

generating, by the information handling system, a lead characterization of the end-user of the identified end-user computing device based at least in part on the characteristic of the end-user of the identified end-user computing device and the set of lead qualification rules, wherein the lead characterization indicates a lead assessment of the end-user; and

storing, by the information handling system, the lead characterization of the end-user of the identified end-user computing device.

2. The computer-implemented method of claim 1, wherein the lead characterization of the end-user of the identified end-user computing device comprises associating the end-user with a first category or a second category from a set of categories, wherein the first category corresponds to affirmative lead determinations and the second category corresponds to negative lead determinations.

3. The computer-implemented method of claim 1, wherein the lead characterization of the end-user of the identified end-user computing device comprises associating the end-user with a lead score.

4. The computer-implemented method of claim 1, wherein generating the lead characterization of the end-user of the identified end-user computing device comprises:

assigning a lead score to the end-user based at least in part on the characteristic of the end-user of the identified end-user computing device; and

correlating the lead score to a category from a set of categories, wherein the category indicates the lead assessment of the end-user.

5. The computer-implemented method of claim 1, further comprising:

processing call information corresponding to a call responsive to an advertisement presented on the identified end-user computing device; and

charging an advertiser for the call responsive to the advertisement based at least in part on the lead characterization of the end-user of the identified end-user computing device.

6. The computer-implemented method of claim 5, further comprising:

determining an amount to charge the advertiser, wherein the amount is based at least in part on the lead characterization of the end-user of the identified end-user computing device.

7. The computer-implemented method of claim 1, further comprising:

processing call information corresponding to a selection of a user-selectable call option responsive to an advertisement presented on the identified end-user computing device;

selecting a callee based at least in part on the lead characterization; and

initiating a communication session with a communication device of the callee.

8. A system for qualifying a sales lead, the system comprising:

one or more network interfaces accessible from a network;

one or more processors coupled to at least one of the one or more network interfaces and to one or more repositories, the one or more processors to execute instructions to;

process information, received via the network, about one or both of an identified end-user computing device and an end-user of the identified end-user computing device, the information corresponding at least in part to data captured about one or more telephone calls placed via the end-user computing device, wherein the information is retained in one or more tracking information repositories;

access a set of lead qualification rules that includes a set of criteria for qualifying end-users as leads, the qualifying comprising determining lead assessments, where each lead assessment indicates a respective potential of a respective end-user to conduct business;

derive a characteristic of the end-user of the identified end-user computing device based at least in part on the information about one or both of the identified end-user computing device and the end-user of the identified end-user computing device, wherein the deriving a characteristic of the end-user comprises identifying one or more aspects of the one or more telephone calls as indicia of a lead based at least in part on data captured during one or more conversation streams, the data captured during one or more conversation streams comprising call content from at least one of the one or more telephone calls, and the identifying one or more aspects comprising analyzing the call content;

generate a lead characterization of the end-user of the identified end-user computing device based at least in part on the characteristic of the end-user of the identified end-user computing device and the set of lead qualification rules, wherein the lead characterization indicates a lead assessment of the end-user; and

store the lead characterization of the end-user of the identified end-user computing device in at least one of the one or more repositories.

9. The system of claim 8, wherein the lead characterization of the end-user of the identified end-user computing device comprises associating the end-user with a first category or a second category from a set of categories, wherein the first category corresponds to affirmative lead determinations and the second category corresponds to negative lead determinations.

10. The system of claim 8, wherein the lead characterization of the end-user of the identified end-user computing device comprises associating the end-user with a lead score.

11. The system of claim 8, wherein generating the lead characterization of the end-user of the identified end-user computing device comprises:

assigning a lead score to the end-user based at least in part on the characteristic of the end-user of the identified end-user computing device; and

correlating the lead score to a category from a set of categories, wherein the category indicates the lead assessment of the end-user.

12. The system of claim 8, the one or more processors to further execute instructions to:

process call information corresponding to a call responsive to an advertisement presented on the identified end-user computing device; and

charge an advertiser for the call responsive to the advertisement based at least in part on the lead characterization of the end-user of the identified end-user computing device.

13. The system of claim 12, the one or more processors to further execute instructions to:

determine an amount to charge the advertiser, wherein the amount is based at least in part on the lead characterization of the end-user of the identified end-user computing device.

14. The system of claim 8, the one or more processors to further execute instructions to:

process call information corresponding to a selection of a user-selectable call option responsive to an advertisement presented on the identified end-user computing device;

select a callee based at least in part on the lead characterization; and

initiate a communication session with a communication device of the callee.

15. A non-transitory machine-readable medium having machine-readable instructions thereon for qualifying a sales lead, which instructions, when executed by one or more computers or other processing devices, cause the one or more computers or other processing devices to:

process information, received via the network, about one or both of an identified end-user computing device and an end-user of the identified end-user computing device, the information corresponding at least in part to data captured about one or more telephone calls placed via the end-user computing device, wherein the information is retained in one or more tracking information repositories;

access a set of lead qualification rules that includes a set of criteria for qualifying end-users as leads, the qualifying comprising determining lead assessments, where each lead assessment indicates a respective potential of a respective end-user to conduct business;

derive a characteristic of the end-user of the identified end-user computing device based at least in part on the information about one or both of the identified end-user computing device and the end-user of the identified end-user computing device, wherein the deriving a characteristic of the end-user comprises identifying one or more aspects of the one or more telephone calls as indicia of a lead based at least in part on data captured during one or more conversation streams, the data captured during one or more conversation streams comprising call content from at least one of the one or more telephone calls, and the identifying one or more aspects comprising analyzing the call content;

generate a lead characterization of the end-user of the identified end-user computing device based at least in part on the characteristic of the end-user of the identified end-user computing device and the set of lead qualification rules, wherein the lead characterization indicates a lead assessment of the end-user; and

store the lead characterization of the end-user of the identified end-user computing device.

16. The non-transitory machine-readable medium of claim 15, wherein the lead characterization of the end-user of the identified end-user computing device comprises associating the end-user with a first category or a second category from a set of categories, wherein the first category corresponds to affirmative lead determinations and the second category corresponds to negative lead determinations.

17. The non-transitory machine-readable medium of claim 15, wherein the lead characterization of the end-user of the identified end-user computing device comprises associating the end-user with a lead score.

18. The non-transitory machine-readable medium of claim 15, wherein generating the lead characterization of the end-user of the identified end-user computing device comprises:

assigning a lead score to the end-user based at least in part on the characteristic of the end-user of the identified end-user computing device; and

correlating the lead score to a category from a set of categories, wherein the category indicates the lead assessment of the end-user.

19. The non-transitory machine-readable medium of claim 15, wherein the instructions further cause the one or more computers or other processing devices to:

process call information corresponding to a call responsive to an advertisement presented on the identified end-user computing device; and

charge an advertiser for the call responsive to the advertisement based at least in part on the lead characterization of the end-user of the identified end-user computing device.

20. The non-transitory machine-readable medium of claim 19, wherein the instructions further cause the one or more computers or other processing devices to:

determine an amount to charge the advertiser, wherein the amount is based at least in part on the lead characterization of the end-user of the identified end-user computing device.