US 11,720,845 B2
Data driven systems and methods for optimization of a target business
Anirban Bhattacharyya, Edison, NJ (US); Himanshu Misra, Tracy, CA (US); Navaneeth Seshadri, Piscataway, NJ (US); Pooja Soni, Piscataway, NJ (US); Sonia Banerjee, Piscataway, NJ (US); Srinivas Kancharla, Piscataway, NJ (US); and Shilpa Singh, Piscataway, NJ (US)
Assigned to Amplo Global Inc., Piscataway, NJ (US)
Filed by Amplo Global Inc., Piscataway, NJ (US)
Filed on Aug. 29, 2020, as Appl. No. 17/6,828.
Claims priority of provisional application 62/894,400, filed on Aug. 30, 2019.
Prior Publication US 2021/0065091 A1, Mar. 4, 2021
Int. Cl. G06Q 10/0631 (2023.01); G06Q 10/0637 (2023.01); G06F 16/33 (2019.01); G06F 40/279 (2020.01); G06F 40/30 (2020.01); G06N 5/02 (2023.01); G06Q 10/0639 (2023.01); G06Q 10/067 (2023.01); G06Q 10/101 (2023.01); G06Q 30/0201 (2023.01); G06V 20/40 (2022.01); G06V 40/16 (2022.01)
CPC G06Q 10/06375 (2013.01) [G06F 16/3344 (2019.01); G06F 40/279 (2020.01); G06F 40/30 (2020.01); G06N 5/02 (2013.01); G06Q 10/067 (2013.01); G06Q 10/06393 (2013.01); G06Q 10/06395 (2013.01); G06Q 10/063112 (2013.01); G06Q 10/101 (2013.01); G06Q 30/0201 (2013.01); G06V 20/40 (2022.01); G06V 40/174 (2022.01)] 14 Claims
OG exemplary drawing
 
1. A method for evaluating a performance of a target business with a computer system, the method comprising:
receiving, by the computer system, problem data, the problem data including information associated with a first problem of the target business associated with a first industry;
receiving, by the computer system, pain-point and solution data, wherein:
a first portion of the pain-point and solution data is associated with the first problem and the first industry, and
a second portion of the pain-point and solution data is associated with a second problem and a second industry;
storing, by the computer system, the pain-point and solution data in a database;
determining, using a machine learning model, an applicability of the second portion of the pain-point and solution data to the first industry;
updating the pain-point and solution data in the database based on an output of the machine learning model, the output of the machine learning model indicative of the applicability;
comparing, by the computer system, the problem data to the updated pain-point and solution data by matching one or more pain-points of the updated pain-point and solution data to the first problem;
identifying, by the computer system, one or more solutions associated with the one or more matched pain-points;
determining, by the computer system, whether the one or more solutions are associated with a key performance indicator (KPI), the KPI being at least one of: a solution KPI or a pain-point KPI;
providing, by the computer system, a recommendation of the KPI when a solution of the one or more solutions is associated with the KPI;
forgoing, by the computer system, the recommendation of the KPI when the one or more solutions are not associated with the KPI;
generating, by the computer system, a customized user interface (UI) based on the updated pain-point and solution data and the recommendation of the KPI;
presenting, by the computer system, the customized UI to a user associated with the target business, wherein the customized UI displays a single visualization comprising the one or more matched pain-points, the one or more solutions, and the recommended KPI;
receiving, by the computer system, an indication of an effectiveness of the one or more solutions or the recommended KPI; and
updating, by the computer system, the database, and the customized UI based on the received indication.