Developer Goals for e-Commerce Startups: Applying AI-enhanced Mind Genomics to Thinking about Everyday Issues

Abstract

Mind Genomics explored responses for an e-commerce website, focusing on a website with ‘deep knowledge’ of the user’s preferences. To understand the application of Mind Genomics in a real-world setting, the timing of the setup and the fielding were limited to a total of 120 minutes. The data were collected in Spring, 2019. Four years later, newly developed AI analysis further interpreted the results. The initial analysis in 2019 deconstructed the ratings assigned by the respondents to vignettes, combinations of messages, describing the website. The respondents used an anchored 5-point scale, with the anchors ‘buy’ and ‘not buy’, respectively. The deconstruction by OLS regression revealed the contribution of each element to the ‘buy’ rating. Clustering the 46 respondents using the 16 coefficients uncovered three Mind-Sets: MS1-Help the client grow, MS2-Client Consulting, and MS3-Generate Leads. Four years later AI was applied to each group in the population, using six standard AI queries applied to all positive elements which were deemed to be strong drivers of ‘buy.’ This paper shows the possibility of rapid and insightful learning on new topics. Learning is promoted through experimental design coupled with human validation, and AI interpretation.