Methods and systems for automatically testing and applying codes to electronic shopping carts

Abstract

Disclosed are methods, systems, and non-transitory computer-readable medium for automatically testing and applying codes to electronic shopping carts. For instance, the method may include: monitoring a browsing session of a user on an e-commerce website; determining whether a trigger condition is present based on the monitoring; when the determining determines the trigger condition is present, automatically performing a code test process for a first set of codes to obtain a first test result, the first set of codes being one or more codes among a plurality of codes for the e-commerce website; and upon completion of the code test process for the first set of codes, displaying a first menu, the first menu including information corresponding to the first test result.

1 .- 20 . (canceled) 
     
     
         21 . A method for automatic code testing, comprising:
 monitoring a browsing session of a user on an e-commerce website;   determining whether a trigger condition is present based on the monitoring; and   when the trigger condition is present, automatically performing a code test process by:
 obtaining a plurality of codes for the e-commerce website, each code of the plurality of codes comprising corresponding data comprising one or more of a savings amount, a last successful application, a popularity, a number of sources for each code, or a number of uses of each code; 
 providing the corresponding data to a scoring machine learning model trained to output a score for each code based on the corresponding data; 
 receiving a score for each code, from the scoring machine learning model; 
 determining a subset number equal to a threshold period of time for the code test process divided by a time to process a code; 
 determining a first subset of codes of the plurality of codes having a maximum quantity of codes equal to the subset number of the plurality of codes and having a score higher than a threshold score; and 
 performing the code test process for the first subset of codes to obtain a first test result. 
   
     
     
         22 . The method of  claim 21 , wherein the corresponding data further comprises a likelihood of success. 
     
     
         23 . The method of  claim 21 , wherein the time to process the code is an average time to process the code. 
     
     
         24 . The method of  claim 21 , wherein the threshold score is based on a second subset of codes each having a score lower than each of the codes of the first subset of codes. 
     
     
         25 . The method of  claim 21 , wherein the determining whether the trigger condition is present based on the monitoring includes:
 obtaining current web page information of the browsing session;   analyzing the current web page information to determine whether code input identifiers are present; and   when the analyzing determines the code input identifiers are present, determining the trigger condition is present.   
     
     
         26 . The method of  claim 25 , wherein the current web page information includes a currently viewed web page of the browsing session, a universal resource locator (URL) of the currently viewed web page, and/or network requests associated with the currently viewed web page, the currently viewed web page being displayed to the user or being about to be displayed to the user, and
 the code input identifiers include one or more cascading style sheets (CSS) elements, one or more hypertext markup language (HTML) elements, and/or one or more URL elements; and   the analyzing the current web page information to determine whether the code input identifiers are present includes:
 parsing the currently viewed web page to determine whether one of the one or more CSS elements and/or the one or more HTML elements are present; and 
 parsing the URL of the currently viewed web page and/or the network requests to determine whether one of the one or more URL elements are present. 
   
     
     
         27 . The method of  claim 21 , wherein the performing the code test process for the first subset of codes includes:
 automatically applying, sequentially or in parallel, codes of the first subset of codes to the browsing session of the user;   receiving, for each applied code of the applied codes, responses from the e-commerce website;   analyzing the responses to determine a result for each of the applied codes; and   compiling the first test result based on the determined result for each of the applied codes.   
     
     
         28 . The method of  claim 21 , further comprising displaying a first menu comprising the first test result, the first menu comprising:
 when the first test result indicates one or more successful codes of the first subset of codes, a success indicator, the success indicator displaying a summary of savings or reward points for the one or more successful codes;   when the first test result indicates no successful codes of the first subset of codes, a no-savings indicator; or   when the first subset of codes does not include all of the plurality of codes, a continue testing indicator to test a second subset of codes.   
     
     
         29 . The method of  claim 28 , further comprising:
 when a continue testing indicator to test the second subset of codes is displayed in the first menu, receiving a user input to test the second subset of codes;   in response to receiving the user input to test the second subset of codes, performing the code test process for the second subset of codes to obtain a second test result; and   upon completion of the code test process for the second subset of codes, displaying a second menu, the second menu including information corresponding to the second test result.   
     
     
         30 . The method of  claim 21 , further comprising automatically performing the code test process further based on a user input to perform the code test process. 
     
     
         31 . A method for automatic code testing, comprising:
 monitoring a browsing session of a user on an e-commerce website;   determining whether a trigger condition is present based on the monitoring; and   when the trigger condition is present, automatically performing a code test process by:
 obtaining a plurality of codes for the e-commerce website, each code of the plurality of codes comprising corresponding data comprising one or more of a savings amount, a last successful application, a popularity, a number of sources for each code, or a number of uses of each code; 
 providing the corresponding data to a scoring machine learning model trained to output a score for each code based on the corresponding data; 
 receiving a score for each code, from the scoring machine learning model; 
 determining a first subset of codes having a score higher than a threshold score; 
 performing the code test process for the first subset of codes to obtain a valid set of codes; and 
 applying a selection algorithm to select a selected code from the valid set of codes based on at least one of the selected code being associated with the user, the selected code having a most optimal score, or the selected code being associated with a fastest estimated shipping time. 
   
     
     
         32 . The method of  claim 31 , further comprising providing a success indicator based on obtaining a valid set of codes. 
     
     
         33 . The method of  claim 32 , wherein the success indicator comprises a selectable component selectable by a user, wherein selection of the selectable component causes the selected code to be applied. 
     
     
         34 . The method of  claim 31 , wherein determining whether the trigger condition is present further includes:
 obtaining current web page information of the browsing session;   analyzing the current web page information to determine whether code input identifiers are present; and   when the analyzing determines the code input identifiers are present, determining the trigger condition is present.   
     
     
         35 . The method of  claim 34 , wherein the current web page information includes a currently viewed web page of the browsing session, a universal resource locator (URL) of the currently viewed web page, and/or network requests associated with the currently viewed web page, the currently viewed web page being displayed to the user or being about to be displayed to the user, and
 the code input identifiers include one or more cascading style sheets (CSS) elements, one or more hypertext markup language (HTML) elements, and/or one or more URL elements; and   wherein the process further includes, to analyze the current web page information to determine whether the code input identifiers are present:   parsing the currently viewed web page to determine whether one of the one or more CSS elements and/or the one or more HTML elements are present; and   parsing the URL of the currently viewed web page and/or the network requests to determine whether one of the one or more URL elements are present.   
     
     
         36 . The method of  claim 31 , wherein performing the code test process for the first subset of codes comprises:
 automatically applying, sequentially or in parallel, codes of the first subset of codes to the browsing session of the user;   receiving, for each applied code of the applied codes, responses from the e-commerce website;   analyzing the responses to determine a result for each of the applied codes; and   obtaining a valid set of codes based on the determined result for each of the applied codes.   
     
     
         37 . The method of  claim 31 , further comprising determining a first test result based on performing the code test process and displaying a first menu based on the first test result, the first menu comprising:
 when the first test result indicates one or more successful codes of the first subset of codes, a success indicator, the success indicator displaying a summary of savings or reward points for the one or more successful codes;   when the first test result indicates no successful codes of the first subset of codes, a no-savings indicator; or   when the first subset of codes does not include all of the plurality of codes, a continue testing indicator to test a second subset of codes.   
     
     
         38 . The method of  claim 37 , wherein the process further includes:
 when a continue testing indicator to test a second subset of codes is displayed in the first menu, receiving a user input to test the second subset of codes;   in response to receiving the user input to test the second subset of codes, performing the code test process for the second subset of codes to obtain a second test result; and   after the code test process for the second subset of codes ends, displaying a second menu, the second menu including information corresponding to the second test result.   
     
     
         39 . The method of  claim 31 , wherein the corresponding data further comprises a likelihood of success. 
     
     
         40 . A system for automatic code testing, the system comprising:
 a memory storing instructions; and   a processor executing the instructions to perform a process including:
 determining that a trigger condition is present based on monitoring a browsing session of an e-commerce website; and 
 automatically performing a code test process, in response to determining that the trigger condition is present, by:
 obtaining a plurality of codes for the e-commerce website, each code of the plurality of codes comprising corresponding data comprising one or more of a savings amount, a last successful application, a popularity, a number of sources for each code, or a number of uses of each code; 
 providing the corresponding data to a scoring machine learning model trained to output a score for each code based on the corresponding data; 
 receiving a score for each code, from the scoring machine learning model; 
 determining a first subset of codes having a score higher than a threshold score; 
 performing the code test process for the first subset of codes to obtain a valid set of codes; and 
 applying a selection algorithm to select a selected code from the valid set of codes based on at least one of the selected code being associated with the user, the selected code having a most optimal score, or the selected code being associated with a fastest estimated shipping time.