# US 8,751,632 B2 · Methods for web site analysis > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 8,751,632 B2 - Document ID: US8751632B2 - Status: Granted - Kind: B2 - Application number: 12/770,665 - Filed: 2010-04-29 - Published: 2011-11-03 - Granted: 2014-06-10 - Earliest claimed: 2010-04-29 - Assignees: Yahoo! Inc. - Applicants: Barbara Poblete; Ricardo Baeza-Yates - Inventors: Barbara Poblete; Ricardo Baeza-Yates - Web page: https://patentgrep.com/patent/US8751632B2 ## CPC - G06Q 30/00: Commerce - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract A specification of a target web site is received. A number of field web sites related to the target web site are identified. Data values are acquired for a set of metrics for the target and each field web site. These data values are processed to evaluate a standing of the target web site relative to the field web sites, while maintaining anonymity of the field web sites. An average web site is determined by respectively averaging data values for the field web sites. A bounding web site is characterized by the best data values from among all field web sites. Target web site data values are compared to average and/or bounding web site data values at a given time. Variations in differences between target web site data values and corresponding average and/or bounding web site data values over time determines improvement and/or success of the target web site. ## Claims ### Claim 1 A computer implemented method for web site analysis, comprising: receiving a specification of a target web site; identifying a number of field web sites related to the target web site; acquiring data values for a set of metrics for the target web site and for each field web site at a first time; and processing the acquired data values for the set of metrics to evaluate a standing of the target web site relative to the field web sites at the first time, wherein processing the acquired data values includes averaging the data values acquired at the first time for each metric within the set of metrics for the field web sites to generate average data values for the set of metrics acquired at the first time to define an average field web site at the first time. ### Claim 2 (depends on 1) A computer implemented method for web site analysis as recited in claim 1, wherein the processing of the acquired data values for the set of metrics is performed without disclosing an association of data values with any specific field web site. ### Claim 3 (depends on 1) A computer implemented method for web site analysis as recited in claim 1, further comprising: reporting a universal resource locator (URL) for each identified field web site without disclosing an association of data values with any specific field web site. ### Claim 4 (depends on 1) A computer implemented method for web site analysis as recited in claim 1, wherein the data values for the set of metrics for the target web site and for each field web site are acquired from public web site data. ### Claim 5 (depends on 4) A computer implemented method for web site analysis as recited in claim 4, wherein the public web site data includes search engine data. ### Claim 6 (depends on 4) A computer implemented method for web site analysis as recited in claim 4, wherein some of the data values for the set of metrics for the target web site are acquired from private target web site data. ### Claim 7 (depends on 6) A computer implemented method for web site analysis as recited in claim 6, wherein the private target web site data includes a usage log of the target web site. ### Claim 8 (depends on 1) A computer implemented method for web site analysis as recited in claim 1, further comprising: receiving a specification of the set of metrics for which data values are to be acquired. ### Claim 9 (depends on 1) A computer implemented method for web site analysis as recited in claim 1, wherein the field web sites related to the target web site are automatically identified based on comparison of a content of the target web site to a content of potential field web sites. ### Claim 10 (depends on 1) A computer implemented method for web site analysis as recited in claim 1, wherein processing the acquired data values further includes: calculating and recording target-to-average difference values for each metric within the set of metrics at the first time, wherein the target-to-average difference value for a given metric at a particular time is defined as a difference between the data value for the given metric for the target web site and the average value for the given metric for the average field web site at the particular time. ### Claim 11 (depends on 10) A computer implemented method for web site analysis as recited in claim 10, wherein processing the acquired data values further includes: acquiring data values for the set of metrics for the target web site and for each field web site at a second time later than the first time; averaging the data values acquired at the second time for each metric within the set of metrics for the field web sites to generate average data values for the set of metrics acquired at the second time to define the average field web site at the second time; calculating and recording target-to-average difference values for each metric within the set of metrics at the second time; comparing the target-to-average difference values for each metric within the set of metrics at the second time with corresponding target-to-average difference values for each metric within the set of metrics at the first time to determine whether or not the target web site has improved relative to the average field web site between the first and second times with regard to each metric within the set of metrics; and generating a report to convey whether or not the target web site has improved relative to the average field web site between the first and second times with regard to each metric within the set of metrics. ### Claim 12 (depends on 1) A computer implemented method for web site analysis as recited in claim 1, wherein processing the acquired data values includes: for each metric within the set of metrics, assigning a best data value acquired for the metric at the first time from among all field web sites as a bounding data value for the metric at the first time, wherein the bounding data values for the set of metrics at the first time characterize a bounding field web site at the first time. ### Claim 13 (depends on 12) A computer implemented method for web site analysis as recited in claim 12, wherein processing the acquired data values further includes: calculating and recording target-to-bounding difference values for each metric within the set of metrics at the first time, wherein the target-to-bounding difference value for a given metric at a particular time is defined as a difference between the data value for the given metric for the target web site and the corresponding bounding data value for the given metric for the bounding field web site at the particular time. ### Claim 14 (depends on 13) A computer implemented method for web site analysis as recited in claim 13, wherein processing the acquired data values further includes: acquiring data values for the set of metrics for the target web site and for each field web site at a second time later than the first time; for each metric within the set of metrics, assigning a best data value acquired for the metric at the second time from among all field web sites as a bounding data value for the metric at the second time, wherein the bounding data values for the set of metrics at the second time characterize the bounding field web site at the second time; calculating and recording target-to-bounding difference values for each metric within the set of metrics at the second time; comparing the target-to-bounding difference values for each metric within the set of metrics at the second time with corresponding target-to-bounding difference values for each metric within the set of metrics at the first time to determine whether or not the target web site has improved relative to the bounding field web site between the first and second times with regard to each metric within the set of metrics; and generating a report to convey whether or not the target web site has improved relative to the bounding web site between the first and second times with regard to each metric within the set of metrics. ### Claim 15 A computer implemented method for characterizing an average web site relevant to a target web site, comprising: receiving a specification of the target web site; identifying a number of field web sites related to the target web site; acquiring data values for a set of metrics for each field web site; for each metric within the set of metrics, averaging the data values acquired for the metric from among all field web sites to generate an average data value for the metric, wherein the average data values for the set of metrics characterize the average field web site; and generating a report to convey the average data values for the set of metrics that characterize the average field web site. ### Claim 16 (depends on 15) A computer implemented method for characterizing an average web site relevant to a target web site as recited in claim 15, wherein the generation of the report is performed without disclosing an association of data values with any specific field web site. ### Claim 17 (depends on 15) A computer implemented method for characterizing an average web site relevant to a target web site as recited in claim 15, wherein the data values for the set of metrics for each field web site are acquired from public web site data. ### Claim 18 (depends on 15) A computer implemented method for characterizing an average web site relevant to a target web site as recited in claim 15, wherein the field web sites related to the target web site are automatically identified based on comparison of a content of the target web site to a content of potential field web sites. ### Claim 19 A computer implemented method for characterizing a bounding web site relevant to a target web site, comprising: receiving a specification of the target web site; identifying a number of field web sites related to the target web site; acquiring data values for a set of metrics for each field web site; for each metric within the set of metrics, assigning a best data value acquired for the metric from among all field web sites as a bounding data value for the metric, wherein the bounding data values for the set of metrics characterize the bounding field web site; and generating a report to convey the bounding data values for the set of metrics that characterize the bounding field web site. ### Claim 20 (depends on 19) A computer implemented method for characterizing a bounding web site relevant to a target web site as recited in claim 19, wherein the generation of the report is performed without disclosing an association of data values with any specific field web site. ### Claim 21 (depends on 19) A computer implemented method for characterizing a bounding web site relevant to a target web site as recited in claim 19, wherein the data values for the set of metrics for each field web site are acquired from public web site data. ### Claim 22 (depends on 19) A computer implemented method for characterizing a bounding web site relevant to a target web site as recited in claim 19, wherein the field web sites related to the target web site are automatically identified based on comparison of a content of the target web site to a content of potential field web sites.