Datorium today released results from a recent study comparing popular ride-hailing apps Uber and Lyft among US consumers. Among its findings, critical differences were shown between genders, with notable differences between peer recommendations and actual purchases.
Additional findings from the study show other demographic differences such as geography, income and age.
Notable among the results was that usage/familiarity of the brands increased, not decreased, the disparity: women who had used Uber within the last year were more likely to have a lower purchase probability than those that did not use Uber at all. Also, generally women tended to prefer Lyft, while men tend to prefer Uber.
“We’re excited to share this study as a part of the launch of the Octain predictive platform,” said Cameron Turner, Founder and CEO of Datorium. “We believe that AI-driven metrics represent a vast opportunity for predicting brand performance, using the facts of the past to model the future.”
The study was completed as a part of a broader study analyzing many top US consumer brands through primary research conducted among a US census-balanced panel, including Microsoft, Starbucks, Method, Adobe, Intuit, Nike, Airbnb, TiVo, Alaska Airlines and Hewlett-Packard. (Note: several of those measured are among Datorium’s customers.) Results were tabulated using Datorium’s Octain scoring system, a zero to one thousand value indicating the probability of future purchase.
“Having a single score which represents a consumer’s propensity to buy brings clarity to an overcluttered space of metrics and models,” said Turner. “Similar to the FICO score for credit, Octain is straightforward, comparable, and highly actionable at both individual and aggregate levels.”
The study further compared traditional consumer metrics such as Net Promoter Score (NPS) to demonstrate that what people say to others does not necessarily map to what they do as consumers.
Link to Full Study: https://docsend.com/view/hshcyuz