Evolutionary algorithms to power a dynamic web enviornment to improve conversion rates.
eCommerce & Marketing
Econometric market mix and propensity modelling with impressive, award winning results in UK and Germany. When a customer walks into a typical bricks and mortar store there are salespeople to assist towards making a purchase; the same is clearly not possible in an online setting, which the pandemic has made the most important focus and competitive environment for retailers.
We were tasked to create a machine learning solution that could identify types of customers to the website in real time based on their predicted purchase behaviour. We used data signals from web and sales and explored trillions of possible model and data variants - using "genetic algorithms" - to find the best models.
The result was an online web environment that dynamically presented consumers information that was most likely to lead to a sale - much like a real salesperson would provide.