US 12,169,803 B2
Systems and methods for automating comparative user experience test analyses
Dustin Garvey, Exeter, NH (US); Frank Chiang, Boston, MA (US); Alexa Stewart, Andover, MA (US); Janet Muto, Boston, MA (US); Andrea Paola Aguilera García, Cambridge, MA (US); Nitzan Shaer, Boston, MA (US); and Alexander Barza, Cambridge, MA (US)
Assigned to Wevo, Inc, Boston, MA (US)
Filed by Wevo, Inc., Boston, MA (US)
Filed on Nov. 9, 2023, as Appl. No. 18/505,951.
Claims priority of provisional application 63/502,351, filed on May 15, 2023.
Claims priority of provisional application 63/492,194, filed on Mar. 24, 2023.
Prior Publication US 2024/0320591 A1, Sep. 26, 2024
Int. Cl. G06Q 10/0637 (2023.01); G06F 11/34 (2006.01); G06F 16/34 (2019.01); G06F 30/27 (2020.01); G06Q 30/0203 (2023.01)
CPC G06Q 10/0637 (2013.01) [G06F 11/3438 (2013.01); G06F 16/345 (2019.01); G06F 30/27 (2020.01); G06Q 30/0203 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
generating, by a process based at least in part on a first set of message fragments and a plurality of user experience test result sets, a first set of automated prompts for a generative language model to generate an analysis for each user experience test result set of the plurality of user experience test result sets;
providing, by the process, the first set of automated prompts as input to the generative language model, wherein the generative language model applies at least one of a recurrent neural network or a transformer model to the first set of automated prompts;
generating, by the process based at least in part on a second set of message fragments and the analysis for each user experience test result set of the plurality of user experience test result sets, a second set of automated prompts for the generative language model to compare at least part of different analyses for the plurality of user experience test result sets;
providing, by the process, the first set of automated prompts as input to the generative language model, wherein the generative language model applies at least one of the recurrent neural network or the transformer model to the second set of automated prompts; and
presenting, within a user interface based on at least one response received from the generative language model to the second set of automated prompts, a comparison of the analysis for each user experience test result set of the plurality of user experience test result sets, wherein the comparison is used to implement at least one product design optimization to enhance user experiences with a product.