# US 12,001,274 B2 · System and method for automatically monitoring and diagnosing user experience problems > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,001,274 B2 - Document ID: US12001274B2 - Status: Granted - Kind: B2 - Application number: 17/826,124 - Filed: 2022-05-26 - Published: 2022-09-08 - Granted: 2024-06-04 - Earliest claimed: 2020-05-14 - Assignees: State Farm Mutual Automobile Insurance Company - Applicants: State Farm Mutual Automobile Insurance Company - Inventors: Si Sun; Forrestt Severtson - Web page: https://patentgrep.com/patent/US12001274B2 ## CPC - G06F 11/079: {Root cause analysis, i.e. error or fault diagnosis (in a hardware test environment G06F11/22; in a software test environment G06F11/36)} - G06F 11/0751: {Error or fault detection not based on redundancy (power supply failures G06F1/30; network fault management H04L41/06)} - G06F 11/0778: {Dumping, i.e. gathering error/state information after a fault for later diagnosis} - G06F 11/2263: {using neural networks} - G06F 11/302: {where the computing system component is a software system} - G06F 11/3438: {monitoring of user actions (tracking the activity of the user H04L67/535)} - G06F 16/957: Browsing optimisation, e.g. caching or content distillation - G06N 5/04: Inference or reasoning models - G06N 20/00: Machine learning - G06F 2201/865: Monitoring of software - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract The following relates generally to diagnosing problems with websites. In some embodiments, a webpage interaction processor receives a list of potential user experience problems. The webpage interaction processor then extracts click data from the website, and processes the extracted click data into grams. Subsequently, an analytics engine is trained based on the processed click data. The trained analytics engine may then diagnose the problem of the website with a potential user experience problem from the received list of potential user experience problems. In some embodiments, the process is entirely automated. ## Claims ### Claim 1 A computer-implemented method for diagnosing a problem of a website, the website comprising a plurality of webpages, and the method comprising, via one or more processors: receiving a list of potential user experience problems; extracting click data from the website; processing the extracted click data by processing the extracted click data into at least one forward gram, and at least one reverse gram; training an analytics engine based on the processed click data; and using the trained analytics engine to diagnose the problem of the website with a potential user experience problem of the received list of potential user experience problems. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein the list of potential user experience problems includes at least one of: difficulty in locating information relevant to a particular problem; difficulty in completing a process; and difficulty in noticing or accessing a button of the website. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, further comprising dynamically retraining the trained analytics engine as new click data is extracted. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein the processing the extracted click data further comprises processing the extracted click data further into at least one interruption gram. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, further comprising: for at least one webpage of the plurality of webpages, calculating an index based on weight of diagnosis history; and outputting a visual alert based on the index of the at least one webpage of the plurality of webpages. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein the processing the extracted click data further comprises processing the extracted click data into weighted grams, the weighted grams further comprising a weight based on a webpage frequency derived from the click data. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein: at least one webpage of the website comprises a plurality of elements configured to lead to another website of the webpage; the click data comprises click data of the plurality of elements; and processing the extracted click data comprises converting the click data into behavioral features. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein the analytics engine is trained via a machine learning algorithm. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, further comprising: for at least one webpage of the plurality of webpages, calculating an index based on weight of diagnosis history; and determining to generate an output alert based on the index of the at least one webpage of the plurality of webpages. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, further comprising: displaying, on a display, the diagnosed problem of the website. ### Claim 11 A system for diagnosing a problem of a website, the website comprising a plurality of webpages, and the system comprising one or more processors configured to: receive a list of potential user experience problems; extract click data from the website; process the extracted click data by processing the extracted click data into at least one forward gram, and at least one reverse gram; train an analytics engine based on the processed click data; and use the trained analytics engine to diagnose the problem of the website with a potential user experience problem of the received list of potential user experience problems. ### Claim 12 (depends on 11) The system of claim 11, wherein the list of potential user experience problems includes at least one of: difficulty in locating information relevant to a particular problem; difficulty in completing a process; and difficulty in noticing or accessing a button of the website. ### Claim 13 (depends on 11) The system of claim 11, wherein the one or more processors are further configured to: for at least one webpage of the plurality of webpages, calculate an index based on weight of diagnosis history; and cause a visual alert to be output based on the index of the at least one webpage of the plurality of webpages. ### Claim 14 (depends on 11) The system of claim 11, wherein the one or more processors are further configured to process the extracted click data by processing the extracted click data into weighted grams, the weighted grams comprising a weight based on a webpage frequency derived from the click data. ### Claim 15 (depends on 11) The system of claim 11, further comprising a display configured to display the diagnosed problem of the website. ### Claim 16 A computer-implemented method for diagnosing a problem of a website, the website comprising a plurality of webpages, and the method comprising, via one or more processors: with a webpage interaction processor, receiving a list of potential user experience problems; with the webpage interaction processor, extracting click data from the website; with the webpage interaction processor, processing the extracted click data by processing the extracted click data into at least one forward gram, and at least one reverse gram; training an analytics engine based on the processed click data; and with the trained analytics engine, diagnosing the problem of the website with a potential user experience problem of the received list of potential user experience problems. ### Claim 17 (depends on 16) The computer-implemented method of claim 16, wherein the list of potential user experience problems includes all of: difficulty in locating information relevant to a particular problem; difficulty in completing a process; and difficulty in noticing or accessing a button of the website. ### Claim 18 (depends on 16) The computer-implemented method of claim 16, further comprising: for at least one webpage of the plurality of webpages, calculating an index based on weight of diagnosis history; and outputting a visual alert based on the index of the at least one webpage of the plurality of webpages. ### Claim 19 (depends on 16) The computer-implemented method of claim 16, wherein the processing the extracted click data comprises processing the extracted click data into weighted grams, the weighted grams comprising a weight based on a webpage frequency derived from the click data. ### Claim 20 (depends on 16) The computer-implemented method of claim 16, further comprising: displaying, on a display, the diagnosed problem of the website.