AUTOMATED RATINGS OF NEW PRODUCTS AND SERVICES

• US 20110119161A1
• Filed: 11/18/2009
• Published: 05/19/2011
• Est. Priority Date: 11/18/2009
• Status: Abandoned Application

• Current Assignee: George M Van Treeck
• Original Assignee: George M Van Treeck
• Inventors: Van Treeck, George M.
• Application Number:
  US12/621,061
• Publication Number:
  US 20110119161A1
• Time in Patent Office: Days
• US Class Current: 705/27.2
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0643 Graphical representation of items or shoppers

Abstract

A system for automating comparisons and ratings of new product models and services that is timely, efficient, objective and consistent where an expert system extracts model information from a plurality of web page and compares and rates each model against comparable competing models gathered from one or more web sites and stored in a database to be displayed when requested by a user.

Claims

1. A system for automating comparisons and ratings of new product models and services that is timely, efficient, objective and consistent the system comprising:

a) a web crawler;

b) a database communicatively coupled to the web crawler,

where the database comprises rules, stored in the database, that are operable to locate web pages from the web site of a product manufacturer or a service provider that comprises information on models offered;

c) an expert system communicatively coupled to the web crawler and the database,

where the expert system extracts model information from a plurality of web page content provided by the web crawler that is compared and rated against comparable competing models gathered from one or more web sites and stores the extracted model information, comparisons, and ratings in the database;

d) a web server-based application communicatively coupled to the database,

where the web server-based application transforms the comparisons and ratings stored in the database into reports; and

e) an internet-connected device communicatively coupled to the web server-based application for displaying the extracted information, comparisons, and ratings reports.

2. The system of claim 1, where the expert system comprises:

a) an administration component;

b) a database communicatively coupled to the administration component;

c) a price band generator component communicatively coupled to the database;

d) a statistics calculator component communicatively coupled to the database;

e) a ratings calculator component; and

f) a rater component that is communicatively coupled to the database, price band generator component, the statistics calculator component and the ratings calculator component.

3. The system of claim 2, where the database comprises at least three data tables.

4. The system of claim 3, where the at least three data tables are selected from the group consisting of a table of benefits to the customer, a table of benefit satisfaction ratings and a table of grade definitions.

5. The system of claim 4, where the table of benefit satisfaction ratings comprises a primary key field, a benefit name field that indicates the level of benefit satisfaction, a numeric weight field and a description field that explains the measurable criteria required to use the corresponding rating.

6. The system of claim 5, where the level of benefit satisfaction comprises at least four benefit satisfaction ratings.

7. The system of claim 6, where the benefit satisfaction ratings are selected from the group consisting of high, medium, low and none.

8. The system of claim 7, where the benefit satisfaction ratings comprise a numeric value where the number 7 is a high rating, 3 is a medium rating, 1 is a low rating and 0 is a none rating.

9. The system of claim 4, where the at least three database tables are a table of benefits to the customer, a table of benefit satisfaction ratings and a table of grade definitions.

10. The system of claim 9, where the table of benefits to the customer comprises a primary key field, a benefit name field, a numeric benefit weight field, and a benefit description field.

11. The system of claim 10, where each weight field comprises a numeric value.

12. The system of claim 11, where the numeric value is between 1 and 7.

13. The system of claim 10, where the table of benefits to the customer further comprises table rows where the benefit name field of each row comprises a value indicating one or more categories of benefit.

14. The system of claim 13, where the categories of benefit comprises the group selected from a primary purpose of the product, generality/compatibility, usability, reliability, performance, safety, economy, low price, aesthetic and amenity.

15. The system of claim 1, where the database further comprises a report table.

16. The system of claim 15, where the report table further comprises:

a) one or more row headers;

b) one or more column headers; and

c) one or more table cells, where each table cell is at an intersection of the one or more row header and the one or more column header.

17. The system of claim 16, where each row header comprises a product feature name and the units of measure for that feature.

18. The system of claim 16, where each column header includes a manufacturer name or service provider name, a brand name, a model name, a price, an overall rating for the named model, and an internet link to a web page to purchase the named model or to a web page containing links to one or more retailers of the named model.

19. The system of claim 16, where each table cell of the report table has a side-by-side comparison of each model.

20. The system of claim 16, where each table cell comprises a model feature value and a calculated rating of how the model feature compares to the same or similar features of one or more models.

21. The system of claim 20, where each of the one or more table cells comprises a model feature value and a rating of the model feature value that are displayed in the ratings report.

22. The system of claim 1, where the ratings report comprises one or more hypertext links corresponding to each product or service displayed in the ratings report, where the hypertext link links to a web page for purchasing the product or service associated with the rating.

42. A method for one or more experts to enter data for automating comparisons and ratings of new product models and services that is timely, efficient, objective and consistent, the method comprising the steps of:

a) providing the system of claim 1;

b) displaying one or more than one data entry fields for data to be entered into the system;

c) entering data, for each product or service category fields, where the data entry fields comprises names of all the features for that category of product or service, and for each named feature data fields units of measure for that feature, a description of the feature;

a name of a primary benefit to a customer selected from the list of customer benefits in a database table;

an explanation of how the feature provides the selected benefit;

a benefit satisfaction rating selected from the list of benefit satisfaction ratings in a database table;

an explanation of the selected benefit satisfaction rating;

fields to enter an internet URLs and regular expression rules that can be used by a web crawler to locate the models of a product; and

fields to enter regular expression rules to extract the model brand name, model numbers, model price, and feature values of product models from web pages product or service;

d) determining if all the entries are complete;

e) storing the entered information the database;

f) locating web pages containing information on product models using URLs and regular expressions stored in the database to located the web pages;

g) transmitting the web page content to the rater component of the expert system; and

h) estimating the relative importance of product and service features by multiplying the identified primary benefit of a feature times the assigned satisfaction level of the benefit based on the measurable satisfaction level criteria to yield a feature'"'"'s importance weight.

23. A method for automating comparisons and ratings of new product models and services that is timely, efficient, objective and consistent, the method comprising the steps of:

a) transmitting instructions from a rater component of the expert system to a price band generator component;

b) separating each model price into a price band for each category of a product or service, where the price band comprises one or more high price bands and one or more low price bands;

c) storing the price bands in a database; and

d) estimating the relative importance of product and service features by multiplying an identified primary benefit of a feature times an assigned satisfaction level of a benefit based on a measurable satisfaction level criteria to yield a feature'"'"'s importance.

24. The method of claim 23, where the range of each high price band is calculated by the formula:

band_high=rounded_up_price(bound*(1+(1/(sqrt(bound)))),

where the variable bound is initialized to a highest price of an adjacent lower price band;

the function rounded_up_price calculates a value representing the lowest price having all zeros in the least significant digits that is greater than or equal to the input value to the function.

25. The method of claim 23, where the range of each low price band is calculated by the formula:

band_low=bound*overlap_factor,

where the variable bound is initialized to a highest price of an adjacent lower price band.

26. The method of claim 25, where the overlap_factor is between 0.1 and 1.0.

27. The method of claim 25, where the overlap_factor is 0.8.

28. The method of claim 23, further comprising the steps of:

a) assigning a model into one or more of the price bands associated with the category of a product, a service or both a product and a service using the price of a model; and

b) storing the assignments in the database.

29. The method of claim 25, where price bands overlap near a boundary of a price band.

30. The method of claim 25, where the lowest price of a price band overlaps the lower price band.

31. The method of claim 23, where the step of separating each model price into a price band for each category of a product or service further comprises calculating the mean value and standard deviation of each model feature of a category in a price band.

32. The method of claim 23, where the step of estimating the relative importance of product and service features further comprises grading on a curve for each model feature in a price band based on an the amount and a direction from the mean value of each model feature value and storing the grade in the database.

33. The method of claim 23, where separating each model price into a price band for each category of a product or service further comprises the steps of:

a) multiplying the numeric weight corresponding to the model feature grade times the calculated importance weight of that feature to yield the weighted model feature score;

b) storing the weighted model feature score in the database;

c) summing the weighted model feature scores to yield a raw cumulative model score;

d) storing the raw cumulative model score in the database;

e) calculating the mean value and standard deviation of the raw cumulative model scores in a price band;

f) storing the mean value and standard deviation in the database;

g) calculating an overall grade for each model in a price band, where the statistics calculator calculates an overall grade for a model by grading a raw cumulative model score on a curve; and

h) storing the overall grade in the database.

34. The method of claim 33, further comprising the step of calculating comparisons and rankings for each product and service for each category stored in the database.

35. The method of claim 34, where each ranking has a measurable criteria.

36. The method of claim 35, where the measurable criteria is calculated from the formula:

X=50/log N and Y=10/log N,

where N is the number of features providing some amount of a particular benefit (log base

     2);

X is a high satisfaction level threshold of a single feature of a product, a service or both a product and a service;

Y is a high satisfaction level threshold of a single feature of a product, a service or both a product and a service; and

where a level of satisfaction less than Y% and greater than zero is assigned a low satisfaction level rating and a satisfaction level of none is assigned where Y% is zero.

39. The method of claim 36, where product or service data is provided via industry standard protocols.

40. The method of claim 36, where product or service data is transferred from data files located on a web server of an internet-connected computer.

41. The method of claim 40, where the data files are provided in industry standard formats.

37. A method of estimating the relative importance of product and service features by multiplying an identified primary benefit of a feature times an assigned satisfaction level of a benefit based on a measurable satisfaction level criteria to yield a feature'"'"'s importance weight.

38. A method for automating comparisons and ratings of new product models and services that is timely, efficient, objective and consistent, the method comprising the steps of:

a) use of regular expression rules to extract brand name, model numbers, model price feature values of models from web pages and product databases and store the extracted information in a database;

b) dividing a range of model prices arranged from highest to lowest into price bands for each model category;

c) assigning a model into at least one price band;

d) grading each model feature in the at least one price band on a curve,

e) storing the grade in a database;

f) multiplying the weight for each model feature with a corresponding assigned benefit multiplied by a weight corresponding to an assigned satisfaction level producing a model feature'"'"'s importance weight;

g) storing the importance weight in the database;

h) multiplying each model feature of each model in a price band by a numeric weight corresponding to provide a feature grade and multiplying by a calculated importance weight of the feature providing a weighted feature score;

i) storing the weighted model feature score in the database;

j) summing the weighted model feature scores for each model in a price band providing a raw cumulative model score;

k) storing the raw cumulative model score in the database;

l) calculating an overall grade for each model in a price band by grading the raw cumulative model score on a curve,

where the curve is based on the amount and direction of deviation from the mean that compares the model to one or more models in the same price band;

m) storing the overall grade in the database;

n) estimating the relative importance of product and service features by multiplying an identified primary benefit of a feature times an assigned satisfaction level of a benefit based on a measurable satisfaction level criteria to yield a feature'"'"'s importance weight;

o) requesting a model comparison report;

p) transforming the model comparisons and ratings stored in the database into a model comparison and rating report using a program storage device readable by a machine, tangibly embodying a program of instructions executable by a web server-based application;

q) transmitting the model comparison and ratings report to a user; and

r) displaying the transmitted report to the user.