Every Reader, Every Touchpoint: How Saxo Personalised the Reader Journey
Digital Bookstore and Streaming
Extend personalization across the streaming app, all customer segments, and late-funnel pages
The Results
Across 2025 and early 2026, Saxo’s personalisation programme delivered significant improvements across every pillar: the streaming app, customer engagement, and the funnel.
The Client
Saxo is Denmark’s largest online bookstore, carrying millions of titles across every genre. Founded as a bookshop in Copenhagen in 1961, it expanded into eCommerce in 2000 and offers membership services across its online bookstore and streaming app for e-books and audiobooks.
With a catalogue of this scale running alongside an active membership service, Saxo’s personalisation challenge is to ensure each reader, whether browsing the store or streaming on the app, finds their next favourite author or book series.
With Ada Global, Saxo uses two products across both experiences. Recommend™ delivers book and audiobook suggestions, and personalises the content each reader sees based on their preferences and history. Find™ makes a catalogue of millions searchable and explorable.
The Challenge
Saxo serves a wide spectrum of readers, from anonymous first-time visitors browsing the bookstore to long-term members mid-way through a series on the app. Each brings different behaviours, histories, and signals, and requires a very different approach to personalisation.
To achieve this, Saxo and Ada Global focused on three things:
- Bringing personalised recommendations into the streaming app, where discovery works differently.
- Launching affinity-based content personalisation across all reader segments on the online bookstore, regardless of browsing history.
- Optimising cross-sell recommendations at the Add to Cart page on the online bookstore to drive measurable additional revenue.
How Ada Global Makes it Work
The results across 2025 and early 2026 show how each of the three challenges came together.
1 Pillar 1: Personalized Recommendations in the Streaming App
The Saxo streaming app offers millions of audiobooks and e-books on a membership basis. There is no cart, no checkout, and no order value to optimise against. The goal is to help members discover their next listen, which drives engagement and ultimately retention.
While Find™, Ada Global’s search tool, helps members quickly locate books and authors, Recommend™, Ada Global’s AI recommendation engine, takes over once they’re ready for their next listen.
The most differentiated win occurs when a member finishes a book. The Inspiration placement, powered by Recommend™, surfaces the next title at precisely that moment.
After finishing “Da Vinci Mysteriet” by Dan Brown, the Saxo app’s Inspiration placement surfaces personalised recommendations, including books by the same author and audiobooks by the same narrator, powered by Recommend™.

Optimising the strategies behind this placement led to strong engagement.
2 Pillar 2: Affinity-Based Content Personalisation Across Every Reader Segment on the Website
With Saxo’s diverse reader base, the question was whether affinity-based content personalisation could lift engagement across all readers on the online bookstore, not just the easiest ones to personalise for.
Saxo switched on Engage Affinity, a capability in Recommend™ that automatically personalises the homepage banners each reader sees based on their browsing history, purchase patterns, and reading preferences.
The more data available, the sharper the personalisation. But even with very little to go on, every segment saw a lift.
3 Pillar 3: Cross-Sell Optimisation at the Add to Cart Page on the Website
The Add to Cart page was already one of the most efficient placements in Saxo’s website funnel, driving approximately 21.3% of attributable sales from cross-sell recommendations from just 5.5% of placement views.

To further optimise cross-selling on the website, Saxo and Ada Global ran a three-week A/B test in February 2026 using Configurable Strategies in Recommend™. This allows users to design and fine-tune custom recommendations without relying on engineering.
All three metrics moved positively at greater than 96.5% confidence, proving that optimisation at this placement drives measurable revenue gains.
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