Case study card:

Evolutionary algorithms to power a dynamic web environment to improve conversion rates

Evolutionary algorithms to power a dynamic web environment to improve conversion rates

Vertical

eCommerce & Marketing

Business Challenge
Online retail giant AO.com has a market-leading position supplying an expanding range of household appliances throughout the UK and Europe. Cross channel and cross-device marketing was becoming a key focus

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.

Supplier Solution
The supplier delivered econometric market mix modelling and propensity modelling with impressive, award winning results in UK and Germany.

They 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. They 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.

Industry

Retailer

Client

AO.com

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