Case Study

Customer recommendations fuel revenue rise for Argos

24 August 2023

Q. How did Argos generate £millions in incremental revenue through personalised emails?

A. We delivered Recommender to maximise cross-sell and conversion opportunities.

What’s the story?

With a Single Customer View in place, Argos had a deep understanding of each customer’s transactional and engagement behaviour. With a huge inventory of products across lots of different categories, Argos wanted to make full use of this asset by sending emails with highly intelligent cross- and up-sell messages to increase basket sizes and encourage conversions.

What we did

We built a machine-learning predictive model that offers intelligent, customer- and product-level recommendations and that is trained to make cross- and up-sell specific suggestions.

Hugely powerful and self-optimising, Recommender analyses the correlation between interest and purchase for more than 45,000 products and trillions of basket combinations. Making full use of customer data, it also tailors recommendations to individual customer’s price sensitivity and previous behaviour. What’s more, it’s channel agnostic and can be used to tailor all marketing channel and online experiences.

The Impact

We built a machine-learning predictive model that offers intelligent, customer- and product-level recommendations and that is trained to make cross- and up-sell specific suggestions.

Hugely powerful and self-optimising, Recommender analyses the correlation between interest and purchase for more than 45,000 products and trillions of basket combinations. Making full use of customer data, it also tailors recommendations to individual customer’s price sensitivity and previous behaviour. What’s more, it’s channel agnostic and can be used to tailor all marketing channel and online experiences.

Are we a fit for you?

If you’d like to chat about how we can help you get more value from your customer marketing, get in touch or request a demo.We’re happy to chat, no pressure.

Let’s talk