Our client wanted to recommend personalised product bundles to its e-commerce customers in order to increase Average Order Value (AOV). The Datatonic team implemented a deep recommender system which is capable of finding the best products to serve to users when they buy a high-value product. Predictions were based on historical browsing behaviour & transactional data both for new and returning users.
Fully automated and serverless pipeline
Batch recommendations served in real-time to enable customization of live browsing sessions
If there’s data, we can optimise, innovate with and automate it to drive business value. Find out how we’ve supported the biggest brands across industries.
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* Duration dependent on data complexity and use case chosen for POC model
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