Method, apparatus, and computer program product for calculating a provider quality score

• US 10,346,887 B1
• Filed: 03/14/2013
• Issued: 07/09/2019
• Est. Priority Date: 10/04/2012
• Status: Active Grant

• Current Assignee: Groupon Incorporated
• Original Assignee: Groupon Incorporated
• Inventors: Shariff, Shafiq, Deland, Matt, Beaty, Bob, Nordquist, Derek
• Primary Examiner(s): Whitaker, Andrew B
• Application Number:
  US13/826,866
• Time in Patent Office: 2,308 Days
• Field of Search: None
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 20/10 using kernel methods, e.g. support vector machines [SVM]
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 10/06311 Scheduling, planning or task assignment for a person or group
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• 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
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0609 Buyer or seller confidence or verification
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Abstract

Provided herein are systems, methods and computer readable media for assigning, calculating or determining a provider quality score. An example method comprises capturing metric information from a web source, the metric information indicative of a product, service, or experience performance of a provider. For example each of a number of reviews and the total number of reviews may be captured. The method may further comprise assigning a provider quality score.

Claims

1. A method for identifying one or more supply sources as able to supply at least a portion of a residual demand in a particular geographic region for the at least one of one or more virtual offers, the one or more supply sources not currently engaged in offering any portion of the total demand, by calculating a provider quality score for each of the one or more supply sources, the provider quality score being a predictive value that is indicative of how well a potential supply source tasked with supplying a good or service determined to be in demand would perform during a promotion offered by a promotion and marketing service and how well consumers would react to the promotion, the method comprising:

receiving information indicative of the residual demand for a particular good or service;

identifying the one or more supply sources that are able to supply at least a portion of the residual demand in the particular geographic region;

for each of the one or more supply sources;

capturing, via a web data capturing algorithm, from one or more third-party websites, one or more metrics relating to a provider, wherein the one or more metrics are indicative of a third party evaluation of at least one of a product, service or experience provided by the provider, a performance of a provider, or the provider itself;

capturing, via the web data capturing algorithm, from the one or more third-party websites, a number indicative of a quantity of the one or more captured metrics;

calculating, via one or more processors, a provider quality score based on the one or more metrics and the number indicative of the quantity of the one or more captured metrics, wherein the provider score provides an indication of future provider performance and future third party reaction to the provider,

wherein the calculation of the provider quality score comprises;

aggregating ranking-type review information, like-type review information, and star-type review information, and category-specific type information,

wherein the aggregating of the ranking-type review information, like-type review information, and star-type review information, and category-specific type information comprises;

converting ranking-type review information into provider quality score type information;

converting like-type review information into provider quality score type information by determining that providers with review information indicating that 0%-20% liked it, a 1.0;

21%-40% liked it, a 2.0;

41%-60 liked it, a 3.0, 61%-80% liked it, a 4.0, and 81%-100% liked it, a 5.0; and

converting category-specific type information into provider quality score type information by calculating a weighted average of any two or more categories, the calculation being dependent on a category, sub-category, location, hyper-location, or price of the product, service or experience the provider is expected to provide;

assigning one of a first subset of provider quality scores upon a determination that an average review score of the one or more metrics meets a first review threshold and the number indicative of the quantity of the one more captured metrics meets a first quantity threshold such that a merchant assigned one of the first subset of provider quality scores comprise both the average review score that meets the first review threshold and the quantity the one more captured metrics that meets the first quantity threshold;

assigning one of a second subset of provider quality scores upon a determination that the average review score of the one or more metrics meets the first review threshold and the number indicative of the quantity of the one more captured metrics fails to meet the first quantity threshold such that a merchant assigned one of the second subset of provider quality scores comprise both the average review score that meets the first review threshold and a quantity the one more captured metrics that fails to meet the first quantity threshold;

assigning one of a third subset of provider quality scores upon a determination that the average review score of the one or more metrics fails to meet the first review threshold and the number indicative of the quantity of the one more captured metrics fails to meet the first quantity threshold such that a merchant assigned one of the third subset of provider quality scores comprise both an average review score that fails to meet the first review threshold and a quantity the one more captured metrics that fails to meet the first quantity threshold;

upon a determination that one of the first subset of provider quality scores is assigned, assigning a higher of two provider scores from the first subset of provider quality scores by;

capturing, via the web data capturing algorithm, from the one or more third-party websites, a press review, the press review comprising text data; and

determining, upon capture of the press review, that the text data comprises predefined text data; and

generating a ranking of the one or more supply sources associated with provider quality scores that meet a predetermined threshold;

generating a list, utilizing the portion of the residual demand in the particular geographic region that each of the one or more supply sources associated with provider quality scores that meet a predetermined threshold is able to provide, the list comprising (i) in accordance with the ranking, one or more supply sources associated with provider quality scores that meet a predetermined threshold; and

(ii) a quantity of the portion that each of the one or more supply sources is able to provide; and

providing, via a communications module, to an assignment module configured to facilitate contact with a portion of the one or more supply sources, the list comprised of the one or more supply sources associated with provider quality scores that meet a predetermined threshold and the quantity of the portion that each of the one or more supply sources is able to provide.

2. A method according to claim 1, wherein the metrics are review information, the method further comprising:

calculating an average review score based on the one or more metrics and the number indicative of a quantity of metrics.

3. A method according to claim 1, further comprising:

detecting one or more web sources related to provider information; and

determining whether the one or more web sources provide metrics related to the provider.

4. A method according to claim 1, further comprising:

detecting a provider website;

rating a quality of the provider website; and

factoring the quality of the provider website into the provider quality score calculation.

5. A method according to claim 1, further comprising:

accessing prior performance data,

wherein prior performance data comprises one or more of data related to a previous provider promotion, data related to a previous promotion promoted by a related provider, or data related to a previous promotion promoted by a different promotion service by the provider; and

factoring the prior performance data into the provider quality score calculation.

6. A method according to claim 1, further comprising:

capturing positive press review information related to a provider;

determining if the positive press review information is from an acceptable source; and

factoring the positive press review information into the provider quality score calculation.

7. A method according to claim 1, further comprising:

capturing a number of “

likes”

related to a provider from one or more web sources; and

factoring in the number of “

likes”

into the provider quality score application.

8. An apparatus for identifying one or more supply sources as able to supply at least a portion of a residual demand in a particular geographic region for the at least one of one or more virtual offers, the one or more supply sources not currently engaged in offering any portion of the total demand, by calculating a provider quality score for each of the one or more supply sources, the provider quality score being a predictive value that is indicative of how well the potential supply source tasked with supplying a good or service determined to be in demand would perform during a promotion offered by a promotion and marketing service and how well consumers would react to the promotion, the apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to:

receive information indicative of the residual demand for a particular good or service;

identify the one or more supply sources that are able to supply at least a portion of the residual demand in the particular geographic region;

for each of the one or more supply sources;

capture, via a web data capturing algorithm, from one or more third-party websites, one or more metrics relating to a provider, wherein the one or more metrics are indicative of a third party evaluation of at least one of a product, service or experience provided by the provider, a performance of a provider, or the provider itself;

capture, via the web data capturing algorithm, from the one or more third-party websites, a number indicative of a quantity of the one or more captured metrics; and

calculate, via one or more processors, a provider quality score based on the one or more metrics and the number indicative of a quantity of the one or more captured metrics, wherein the provider score provides an indication of future provider performance and future third party reaction to the provider,

wherein the calculation of the provider quality score comprises;

aggregating ranking-type review information, like-type review information, and star-type review information, and category-specific type information, wherein the aggregating of the ranking-type review information, like-type review information, and star-type review information, and category-specific type information comprises;

converting ranking-type review information into provider quality score type information;

converting like-type review information into provider quality score type information by determining that providers with review information indicating that 0%-20% liked it, a 1.0;

21%-40% liked it, a 2.0;

41%-60 liked it, a 3.0, 61%-80% liked it, a 4.0, and 81%-100% liked it, a 5.0; and

converting category-specific type information into provider quality score type information by calculating a weighted average of any two or more categories, the calculation being dependent on a category, sub-category, location, hyper-location, or price of the product, service or experience the provider is expected to provide;

assigning one of a first subset of provider quality scores upon a determination that an average review score of the one or more metrics meets a first review threshold and the number indicative of the quantity of the one more captured metrics meets a first quantity threshold such that a merchant assigned one of the first subset of provider quality scores comprise both the average review score that meets the first review threshold and the quantity the one more captured metrics that meets the first quantity threshold;

assigning one of a second subset of provider quality scores upon a determination that the average review score of the one or more metrics meets the first review threshold and the number indicative of the quantity of the one more captured metrics fails to meet the first quantity threshold such that a merchant assigned one of the second subset of provider quality scores comprise both the average review score that meets the first review threshold and a quantity the one more captured metrics that fails to meet the first quantity threshold;

assigning one of a third subset of provider quality scores upon a determination that the average review score of the one or more metrics fails to meet the first review threshold and the number indicative of the quantity of the one more captured metrics fails to meet the first quantity threshold such that a merchant assigned one of the third subset of provider quality scores comprise both an average review score that fails to meet the first review threshold and a quantity the one more captured metrics that fails to meet the first quantity threshold;

upon a determination that one of the first subset of provider quality scores is assigned, assigning a higher of two provider scores from the first subset of provider quality scores by;

capturing, via the web data capturing algorithm, from the one or more third-party websites, a press review, the press review comprising text data; and

determining, upon capture of the press review, that the text data comprises predefined text data; and

generating a ranking of the one or more supply sources associated with provider quality scores that meet a predetermined threshold;

generate a list, utilizing the portion of the residual demand in the particular geographic region that each of the one or more supply sources associated with provider quality scores that meet a predetermined threshold is able to provide, the list comprising (i) in accordance with the ranking, one or more supply sources associated with provider quality scores that meet a predetermined threshold; and

(ii) a quantity of the portion that each of the one or more supply sources is able to provide; and

provide, via a communications module, to an assignment module configured to facilitate contact with a portion of the one or more supply sources, the list comprised of the one or more supply sources associated with provider quality scores that meet a predetermined threshold and the quantity of the portion that each of the one or more supply sources is able to provide.

9. The apparatus of claim 8, wherein the metrics are review information, wherein the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to:

calculate an average review score based on the one or more metrics and the number indicative of a quantity of metrics.

10. The apparatus of claim 8, wherein the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to:

detect one or more web sources related to provider information; and

determine whether the one or more web sources provide metrics related to the provider.

11. The apparatus of claim 8, wherein the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to:

detect a provider website;

rate a quality of the provider website; and

factor the quality of the provider website into the provider quality score calculation.

12. The apparatus of claim 8, wherein the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to:

access prior performance data,

wherein prior performance data comprises one or more of data related to a previous provider promotion, data related to a previous promotion promoted by a related provider, or data related to a previous promotion promoted by a different promotion service by the provider; and

factor the prior performance data into the provider quality score calculation.

13. The apparatus of claim 8, wherein the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to:

capture positive press review information related to a provider;

determine if the positive press review information is from an acceptable source; and

factor the positive press review information into the provider quality score calculation.

14. The apparatus of claim 8, wherein the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to:

capture a number of “

likes”

related to a provider from one or more web sources; and

factor in the number of “

likes”

into the provider quality score application.

15. The apparatus of claim 8 wherein the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to:

in an instance in which the average review score is greater than a first predetermined threshold, and the number of reviews is greater than a second predetermined threshold, perform a first quality analysis.

16. The apparatus of claim 15, wherein the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to:

in an instance in which the average review score is less than the first predetermined threshold, or the number of reviews is less than the second predetermined threshold, perform a second quality analysis.

17. The apparatus of claim 16, wherein the second quality analysis comprises:

in an instance in which the average review score is less than an eighth predetermined threshold or in an instance in which the number of reviews is less than a tenth predetermined threshold, assigning a tenth provider quality score.

18. The apparatus of claim 16, wherein in an instance in which the average review score is greater than an eighth predetermined threshold and in an instance in which the number of reviews is greater than a tenth predetermined threshold, the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to perform a fifth quality analysis.

19. The apparatus of claim 18, wherein the fifth quality analysis comprises:

in an instance in which the average review score is less than a ninth predetermined threshold, assigning an ninth provider quality score.

20. The apparatus of claim 18, wherein the fifth quality analysis comprises:

in an instance in which the average review score is greater than a ninth predetermined threshold, performing a sixth quality analysis.

21. The apparatus of claim 20, wherein the sixth quality analysis comprises:

capturing a number of “

likes”

from one or more web sources; and

determining whether the provider is associated with a positive press review from one or more web sources.

22. The apparatus of claim 21, wherein, in an instance in which the provider is not associated with a positive press review or in an instance in which the number of likes is less than an eleventh predetermined threshold, the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to assign an eighth provider quality score.

23. The apparatus of claim 21, wherein, in an instance in which the provider is associated with a positive press review, and in an instance in which the number of likes is greater than an eleventh predetermined threshold, wherein the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to perform a seventh quality analysis.

24. The apparatus of claim 23, wherein the seventh quality analysis comprises:

in an instance in which the average review score is greater than a twelfth predetermined threshold and in an instance in which the number of “

likes”

is greater than a thirteenth predetermined threshold, assigning a sixth provider quality score.

25. The apparatus of claim 23, wherein the seventh quality analysis comprises:

in an instance in which the average review score is less than a twelfth predetermined threshold or in an instance in which the number of “

likes”

is less than a thirteenth predetermined threshold, assigning a seventh provider quality score.

26. The apparatus of claim 15, wherein the first quality analysis comprises:

in an instance in which the average review score is greater than a third predetermined threshold and in an instance in which the number of reviews is greater than a fourth predetermined threshold, performing a third quality analysis.

27. The apparatus of claim 26, wherein the third quality analysis comprises:

determining whether the provider is associated with a positive press review;

in an instance in which the provider is associated with a positive press review, assigning a first provider quality score.

28. The apparatus of claim 26, wherein the third quality analysis comprises:

determining whether the provider is associated with a positive press review;

in an instance in which the provider is not associated with a positive press review, assigning a second provider quality score.

29. The apparatus of claim 15, wherein the first quality analysis comprises:

in an instance in which the average review score is less than a third predetermined threshold or in an instance in which the number of reviews is less than a fourth predetermined threshold, performing a fourth quality analysis.

30. The apparatus of claim 29, wherein the fourth quality analysis comprises:

in an instance in which the average review score is at least than a fifth predetermined threshold and in an instance in which the number of reviews is at least a sixth predetermined threshold, assigning a third provider quality score.

31. The apparatus of claim 30, wherein in an instance in which the average review score is less than the fifth predetermined threshold or in an instance in which the number of reviews is less than a sixth predetermined threshold, the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to determine a number of “

likes”

.

32. The apparatus of claim 31, wherein in an instance in which the average review score is at least the fifth predetermined threshold and in an instance in which the number of “

likes”

is at least a seventh predetermined threshold, the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to assign a fourth provider quality score.

33. The apparatus of claim 32, wherein in an instance in which the average review score is less than the fifth predetermined threshold or in an instance in which the number of “

likes”

is less than the seventh predetermined threshold, the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to assign a fifth provider quality score.

34. The apparatus of claim 15 wherein the at least one memory and computer program code are configured to, with the at least one processor, cause the apparatus to determine whether a provider is associated with an online presence, and in an instance where the provider is not associated with an online presence, assigning a minimum provider quality score.

35. A computer program product for identifying one or more supply sources as able to supply at least a portion of a residual demand in a particular geographic region for the at least one of one or more virtual offers, the one or more supply sources not currently engaged in offering any portion of the total demand, by calculating a provider quality score for each of the one or more supply sources, the provider quality score being a predictive value that is indicative of how well the potential supply source tasked with supplying a good or service determined to be in demand would perform during a promotion offered by a promotion and marketing service and how well consumers would react to the promotion, the computer program product comprising at least one computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising program code instructions for:

receiving information indicative of the residual demand for a particular good or service;

identifying the one or more supply sources that are able to supply at least a portion of the residual demand in the particular geographic region;

for each of the one or more supply sources;

capturing, via a web data capturing algorithm, from one or more third-party websites, one or more metrics relating to a provider, wherein the one or more metrics are indicative of a third parties evaluation of at least one of a product, service or experience provided by the provider, a performance of a provider, or the provider itself;

capturing, via the web data capturing algorithm, from the one or more third-party websites, a number indicative of a quantity of the one or more captured metrics; and

calculating, via one or more processors, a provider quality score based on the one or more metrics and the number indicative of a quantity of the one or more captured metrics, wherein the provider score provides an indication of future provider performance and future third party reaction to the provider,

wherein the calculation of the provider quality score comprises;

aggregating ranking-type review information, like-type review information, and star-type review information, and category-specific type information, wherein the aggregating of the ranking-type review information, like-type review information, and star-type review information, and category-specific type information comprises;

converting ranking-type review information into provider quality score type information;

converting like-type review information into provider quality score type information by determining that providers with review information indicating that 0%-20% liked it, a 1.0;

21%-40% liked it, a 2.0;

41%-60 liked it, a 3.0, 61%-80% liked it, a 4.0, and 81%-100% liked it, a 5.0; and

converting category-specific type information into provider quality score type information by calculating a weighted average of any two or more categories, the calculation being dependent on a category, sub-category, location, hyper-location, or price of the product, service or experience the provider is expected to provide;

assigning one of a first subset of provider quality scores upon a determination that an average review score of the one or more metrics meets a first review threshold and the number indicative of the quantity of the one more captured metrics meets a first quantity threshold such that a merchant assigned one of the first subset of provider quality scores comprise both the average review score that meets the first review threshold and the quantity the one more captured metrics that meets the first quantity threshold;

assigning one of a second subset of provider quality scores upon a determination that the average review score of the one or more metrics meets the first review threshold and the number indicative of the quantity of the one more captured metrics fails to meet the first quantity threshold such that a merchant assigned one of the second subset of provider quality scores comprise both the average review score that meets the first review threshold and a quantity the one more captured metrics that fails to meet the first quantity threshold;

assigning one of a third subset of provider quality scores upon a determination that the average review score of the one or more metrics fails to meet the first review threshold and the number indicative of the quantity of the one more captured metrics fails to meet the first quantity threshold such that a merchant assigned one of the third subset of provider quality scores comprise both an average review score that fails to meet the first review threshold and a quantity the one more captured metrics that fails to meet the first quantity threshold;

upon a determination that one of the first subset of provider quality scores is assigned, assigning a higher of two provider scores from the first subset of provider quality scores by;

capturing, via the web data capturing algorithm, from the one or more third-party websites, a press review, the press review comprising text data; and

determining, upon capture of the press review, that the text data comprises predefined text data; and

generating a ranking of the one or more supply sources associated with provider quality scores that meet a predetermined threshold; and

generating a list, utilizing the portion of the residual demand in the particular geographic region that each of the one or more supply sources associated with provider quality scores that meet a predetermined threshold is able to provide, the list comprising (i) in accordance with the ranking, one or more supply sources associated with provider quality scores that meet a predetermined threshold; and

(ii) a quantity of the portion that each of the one or more supply sources is able to provide; and

providing, via a communications module, to an assignment module configured to facilitate contact with a portion of the one or more supply sources, the list comprised of the one or more supply sources associated with provider quality scores that meet a predetermined threshold and the quantity of the portion that each of the one or more supply sources is able to provide.