System and method for predicting an optimal stop point during an experiment test

A computer-implemented method for predicting an optimal stop point during an experiment test:

• obtaining a total test time for a test on a webpage on a server, wherein the test is an active test on the webpage on the server and the webpage comprises at least one interaction with an interface element of the webpage from at least one user device;
• obtaining a minimum detectable effect trend data over the total test time from the test on the server based on the at least one interaction from the at least one user device;
• determining an average minimum detectable effect change over the total test time associated with the minimum detectable effect trend data;
• determining a minimum detectable effect cumulative change threshold over the total test time associated with the minimum detectable effect trend data;
• determining a plurality of instantaneous minimum detectable effect changes over the total test time associated with the minimum detectable effect trend data;
• determining a plurality of cumulative minimum detectable effect changes associated with the plurality of instantaneous minimum detectable effect;
• determining an optimal stop point time based on the average minimum detectable effect change, the plurality of instantaneous minimum detectable effect changes, and the minimum detectable effect cumulative change threshold;
• and
• concluding the test at the optimal stop point time by terminating the active test on the webpage on the server.

A computer-implemented system for predicting an optimal stop point during an experiment test, the system comprising:

• a memory storing instructions;
• and
• at least one or more processors configured to execute the instructions to perform steps comprising:
• obtaining a total test time for a test on a webpage on a server, wherein the test is an active test on the webpage on the server and the webpage comprises at least one interaction with an interface element of the webpage from at least one user device;
• obtaining a minimum detectable effect trend data over the total test time from the test on the server based on the at least one interaction from the at least one user device;
• determining an average minimum detectable effect change over the total test time associated with the minimum detectable effect trend data;
• determining a minimum detectable effect cumulative change threshold over the total test time associated with the minimum detectable effect trend data;
• determining a plurality of instantaneous minimum detectable effect changes over the total test time associated with the minimum detectable effect trend data;
• determining a plurality of cumulative minimum detectable effect changes associated with the plurality of instantaneous minimum detectable effect;
• storing the total test time, the minimum detectable effect cumulative change threshold, the minimum detectable effect trend data, the average minimum detectable effect change, the plurality of instantaneous minimum detectable effect changes, the plurality of cumulative minimum detectable effect changes, and the optimal stop point time in a database;
• receiving updated minimum detectable effect trend data when an instantaneous minimum detectable effect change is greater than or equal to the average minimum detectable effect change;
• determining an optimal stop point time when an instantaneous minimum detectable effect change associated with the optimal stop point time from the database is less than the average minimum detectable effect change, and a cumulative detectable effect change associated with the optimal stop point time from the database is greater than the minimum detectable effect cumulative change threshold;
• and
• concluding the test at the optimal stop point time, by terminating the active test on the webpage on the server.