Success Story: Product Recommendation Engine Trained on Nuanced Customer Preferences
Digitally savvy consumers are exposed to an ever-increasing variety of products and information. This deluge of information has led to an increased diversity in product demand ... a growing challenge for retailers.
I solved this challenge through the application of advanced data mining and artificial intelligence. My out-of-the-box recommendation algorithms analyzed large groups of customer attributes and preferences.
Then, to reduce bias, I imputed missing data with estimated values based on available information and trends.
The outcome was an assertive and personalized customer product recommendation engine at global scale; all of this in just eight weeks.