Commerce Unlocked #7: One Stack for Retail AI: From transactional planning to agentic intelligence built natively on Databricks. Register Free →
Commerce Unlocked #7: One Stack for Retail AI: From transactional planning to agentic intelligence built natively on Databricks. Register Free →
B2C Fashion Marketplace
Personalize the customer experience across 12 markets at scale
Recommend™, Discover and Engage
Miinto is one of Europe’s largest fashion marketplaces, connecting shoppers with boutiques and brands across 12 markets, from the Nordics to Southern Europe. At that scale, personalization isn’t a feature decision. It’s an infrastructure one.
For almost a decade, Miinto has run Algonomy’s personalization suite across its full market footprint, using Recommend™, Discover, and Engage to cover every meaningful moment in the shopper journey, from product recommendations to discovery and homepage content.
Twelve markets. Three products. One consistent personalization layer.
Here’s what Miinto’s personalization program achieved across twelve markets in 2025.
Different languages, different shopper behaviors, different catalog structures. Most personalization tools break down under that complexity. The usual fix is to customize market by market, which creates inconsistency and makes it hard to improve anything at scale.
Miinto’s approach, built on Algonomy’s personalization suite, takes a different path.
Rather than managing each market separately, Miinto runs a single, unified personalization stack across all twelve. A unified stack across all markets means the same logic, data infrastructure, and optimization levers, regardless of geography. What gets refined in one market strengthens the others. What works in Stockholm gets tested in Warsaw.
From discovery to purchase, Algonomy covers every stage of the shopper journey. Here’s how it performs across twelve markets.
For shoppers who arrive without a specific destination, Discover surfaces personalized product feeds that turn browsing into buying.
Personalized Accessories PLP based on the customer’s affinity towards sunglasses.
Revenue attribution from Discover, the share of total sales traceable to a discovery interaction, reached 33.65% in Belgium and 31.37% in Norway in a single year in 2025.
Across the mid-tier European markets, including Poland, the Netherlands, France, Italy, and Germany, attribution consistently sat between 22% and 27% that same year.
Even in earlier-stage deployments in the UK, Discover accounted for 17.46% of revenue.
The consistency across markets at different stages of maturity is what the almost-decade of optimization delivers. Discovery isn’t a feature that works for Miinto’s best market. It works for all of them.
Where Discover captures exploratory shoppers, Recommend™ works at the product and cart levels, surfacing relevant suggestions when a shopper is closest to making a purchase.
Relevant product recommendations at PDP, powered by Recommend™.
Revenue attribution from Recommend™ reached 5.76% in Sweden and 5.39% in Norway in 2025, with most European markets contributing in the 3–4% range that same year.
These numbers reflect what a well-tuned recommendation engine should deliver at this stage of the journey: incremental revenue from shoppers already in purchase mode, adding to baskets that are already forming.
Relevant product recommendations at the Add-to-cart page, powered by Recommend™.
“We just wanted personalization that actually worked for our customers across every market, without the complexity. Almost a decade with Algonomy has given us the infrastructure, the data, and the partnership to make it real. Today, we have a program that scales across twelve markets, delivers consistent results, and keeps getting stronger.”
Director of Product & CX, Miinto
Ongoing optimization is built into how Miinto and Algonomy operate together.
Strategy refinements on recommendation placements, multivariate testing on discovery configurations, and continuous tuning across markets. The partnership is structured around improvement, not maintenance.
Almost a decade of that work shows in the 2025 results. And that’s what the next chapter is built on.
Let’s face it—customers nowadays expect deeper and relevant communication, not cookie-cutter-styled messaging across every channel.
Deliver a best-in-class customer experience, increase online sales, and drive operational efficiency at scale
AI-powered social proof that reads every context and serves what converts.