This repository contains the code for the proprietary JNEURO algorithm. This algorithm consists of a chain of prompts for AI agents that analyze conversation histories with users, highlighting their unmet needs to launch products and drive business growth. The input to the algorithm is a conversation history with clients, and the output is a map of unmet client needs, which influence their purchase of features or products:
Problem: ;
Description: ; Quote: (name, timing); Negative emotion: ; Want (Avoidance): ; Want (Achievement): ; So that: ; Positive emotion: ; Importance: <1-10 rating>; Frequency: ; Events: ; Deadline: ; Criteria: ; Past solutions: ; Satisfaction: <rating for past solutions, 1-10>; Cost: ; Dissatisfaction: ; Consequences: ; Drivers: ; Barriers: <what's stopping them>; Ideal solution; Respondent's name.
The results of the algorithm are validated for accuracy and accompanied by supporting quotes with time stamps from conversations with clients. The algorithm reduces the time required to understand clients' pain points, helps ensure no needs influencing their purchases are missed, and the quotes and conclusions it generates (along with external human feedback) can be used to train empathetic AI agents and scale qualitative interviews personalized for each user. Such agents can engage personally with every client (including dormant and inactive clients from cold databases), identify their pain points by asking the right questions, structure a map of their jobs to be done, and match the product to them while communicating value in a way that considers each person's personal and individual traits.