Effective Recommendation System With Machine Learning for Ecommerce
The client
Countr makes shopping a social activity. It gives people recommendations they can trust, somewhere to show their own style, and a way to earn money doing it.
Its founder built the product around style tribes formed from users’ interests and preferences: shopping alongside friends, finding inspiration, showing taste, exchanging recommendations, and earning from the content created along the way.
The challengeWhat the teams actually needed
Netguru joined the team early in 2018, at a point where the alpha build needed reorganising from the ground up.
Challenge 01An alpha that needed restructuring
The existing version required reorganising before anything could be built on top of it.
Challenge 02Recommendations that work
The whole proposition rests on a recommendation system people actually trust.
Challenge 03Knowing what is working
The product needed the right metrics tracked, which had not been established.
What we did
An alpha reorganised into a product
A code review and a scoping session gathered what was needed, and design work began on a product matching the client’s vision.
Code and scope first
An initial code review and scoping session collected the data the team needed before proposing anything.
Tracking what matters
Solutions were recommended for tracking the metrics that actually describe how the product is doing.
A better structure
A stronger app architecture was recommended and the existing one restructured toward it.
Effective, not decorative
Design work went into what would make the social shopping experience work, across a network of more than 160 retailers.
Client testimonial
Getting this app up and running was not easy. We're super thrilled to work with Netguru. The team have been fantastic on that front. Making this platform look the way it looks now was one of our biggest goals.
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What’s next