Modifying a computer-based interaction based on eye gaze

A computer program product for modifying a computer-based interaction based on historical eye gaze data, the computer program product comprising a non-transitory computer readable storage device having program instructions embodied therewith, the program instructions readable and executable by a computer to perform a method comprising:

• collecting eye gaze data points to create an eye gaze corpus of information, wherein the eye gaze data points describe an eye gaze of viewers of a first set of at least one user interface;
• applying an unsupervised machine learning algorithm to the eye gaze corpus to generate a plurality of clusters based upon the eye gaze data points;
• determining a target action performance of the first set of at least one user interface for each of the plurality of clusters;
• collecting, from a device having eye tracking technology, real time eye gaze data from a plurality of current users who are viewing a second set of at least one user interface;
• segmenting the plurality of current users based upon the plurality of clusters by analyzing patterns among the real-time eye gaze data and by analyzing scenario data pertaining to the target action performance;
• and
• responsive to the segmenting of the plurality of current users, modifying a computer-based interaction for at least one segment of the plurality of current users in order to maximize target action performance of the second set of at least one user interface.

A computer system comprising one or more processors, one or more computer readable memories, one or more computer readable storage mediums, and program instructions stored on at least one of the one or more storage mediums for execution by at least one of the one or more processors via at least one of the one or more memories, the stored program instructions comprising:

• program instructions to collect eye gaze data points to create an eye gaze corpus of information, wherein the eye gaze data points describe an eye gaze of viewers of a first set of at least one user interface;
• program instructions to apply an unsupervised machine learning algorithm to the eye gaze corpus to generate a plurality of clusters based upon the eye gaze data points;
• program instructions to determine a target action performance of the first set of at least one user interface for each of the plurality of clusters;
• program instructions to collect, from a device having eye tracking technology, real time eye gaze data from a plurality of current users who are viewing a second set of at least one user interface;
• program instructions to segment the plurality of current users based upon the plurality of clusters by analyzing patterns among the real-time eye gaze data and by analyzing scenario data pertaining to the target action performance;
• and
• program instructions to, responsive to segmenting the plurality of current users, modify a computer-based interaction for at least one segment of the plurality of current users in order to maximize target action performance of the second set of at least one user interface.