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Building ML-Powered Real-Time Search Personalisation
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Get a technical roadmap for implementing personalised search using Snowplow data from initial setup to deployment and ongoing optimisation.
Experts from Infinite Lambda and Snowplow created this technical guide, sharing actionable insights based on real-world experiences with leading companies in travel and retail tech.
The case for ML-driven personalisation
Traditional search is no longer enough for your customers. Overwhelmed by hundreds of results to sift through, users struggle with decision fatigue, causing them to abandon their search and costing you conversions even when you have exactly what users are looking for.
Meanwhile, brands that leverage proprietary data for personalisation increase revenue by up to 10% two to three times faster than those that do not (Boston Consulting Group) and improve conversion rates by up to 50% (WiserNotify).
To turn the tide, you need to transform the raw behavioural data you already have into a ranking system that automatically surfaces the most relevant results for each individual user.
Serving your users exactly what they want in seconds boosts engagement, dramatically increasing conversions, and driving millions in incremental revenue.
The numbers are clear: our client, a global travel leader, achieved £2M in additional profit by implementing search personalisation on their website.
Build your own
Learning-to-Rank algorithm
We are sharing a step-by-step guide you can use to leverage your Snowplow data and build your own Learning-to-Rank algorithm and enable ML-powered personalisation.
Download the guide for insights into end-to-end implementation, from architecture and feature engineering to model training and production deployment.
Get the guide
About the authors
Infinite Lambda is a global data and AI consultancy and academy. We help top organisations build cutting-edge data capabilities across the value chain — from fast data use cases, such as intelligent applications, ML, and GenAI, to the more deliberate and collaborative slow data use cases, such as BI, analytics, and data science.
Having delivered over 250 data and AI projects, we have developed proprietary methodologies and tools that help our clients fully benefit from our wealth of expertise.
Strategising, building, and mentoring with scalability in mind, we help clients adopt innovation and stay agile in highly competitive business landscapes.
Snowplow is the global leader in customer data infrastructure (CDI) for AI. They enable organisations to own and unlock the value of customer behavioural data, turning it into a powerful asset for AI-driven decision-making and customer understanding.
Industry leaders like Burberry, Strava, Auto Trader, and DPG Media use Snowplow to collect and manage real-time, structured and unstructured behavioural data, governed in their cloud data platforms.
Today, thousands of companies worldwide rely on Snowplow to generate AI-ready data that enables deeper insights into customer journeys, accurate prediction of customer behaviours, tailored customer experiences, and enhanced fraud detection.