Contact
Better Customer Preference Models with Cognitive Machine-learning
Data scientist in Basel
3000
portfolio_page-template-default,single,single-portfolio_page,postid-3000,bridge-core-3.1.8,qode-page-transition-enabled,ajax_fade,page_not_loaded,,qode-title-hidden,qode_grid_1300,side_area_uncovered_from_content,overlapping_content,qode-content-sidebar-responsive,qode-theme-ver-30.5,qode-theme-bridge,disabled_footer_top,qode_header_in_grid,qode-portfolio-single-template-4,wpb-js-composer js-comp-ver-7.6,vc_responsive

Topic

Products

Customer experience of new products matters in many business areas

Setup

UniBas

Part of the University of Basel research in Economic Psychology

Design

R

Realized in R-Statistics, C++, C#, PHP

Improving Customer Preference Models through Cognitive Machine-learning

Finding the best model to forecast the perceptions and judgments of online and offline consumer products, using real user experience.

In this project, I developed and validated a new cognitive machine-learning algorithm to model and predict consumer choices and product perceptions. The new machine-learning model outperformed two existing models of preferences in two datasets, that contained the actual preferences of people, cross-validation, and predictive testing.

You can read the scientific paper in DECISION.

Related Projects