Skip to main content

Blog Archives

Older posts

Every Reader, Every Touchpoint: How Saxo Personalised the Reader Journey

Case Study

Every Reader, Every Touchpoint: How Saxo Personalised the Reader Journey

Segment

Digital Bookstore and Streaming

Objective

Extend personalization across the streaming app, all customer segments, and late-funnel pages

Challenge
Recommend

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.

~ 0 %
Streaming app recommendation CTR
+ 0 %
Engage CTR lift, Shopping members (website)
+ 0 %
Engage CTR lift, non-members (website)
+ 0 %
Revenue Per Visit (website)

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 Algonomy (now part of ADA), 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 Algonomy (now part of ADA) 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 Algonomy (now part of ADA) 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™, Algonomy’s (now part of ADA) search tool, helps members quickly locate books and authors, Recommend™, Algonomy’s (now part of ADA) 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.

Custom Cross-sell Recommendations on the Add-to-Cart page, powered by Recommend™.

To further optimise cross-selling on the website, Saxo and Algonomy (now part of ADA) 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.

Table Of Contents
The Results
The Client
The Challenge
How ADA Makes it Work

“Algonomy has helped us connect different Saxo readers with the right title, at the right moment, across different touchpoints. We’re already seeing stronger engagement, and we’re excited about the road ahead as our personalisation programme continues to mature.”

Pernille Reinhold Larsen
CRM and Personalization Manager
Saxo

“Personalisation plays an important role in helping readers discover books that match their interests throughout their journey with Saxo.”

Cicilia Carlsen Heide
Content Manager
Saxo

Explore More Resources on Commerce Personalization

Wine.com Drives AttributeBased Recommendations for Personalization
Food & Beverage US

Wine.com Drives AttributeBased Recommendations for Personalization

See full story
0 %
Reduction in out-of-stock across stores
0 %
increase in revenue

400+ Retailers & Brands Across the World Trust ADA

Looking to hyper-personalize your marketing? Let’s talk.

Scaling Personalization Across 12 European Markets: A Decade of E-Commerce Growth with Miinto

Case Study

Miinto + ADA:
 A Decade of Personalization Partnership Across
 12 Markets

Segment

B2C Fashion Marketplace

Objective

Personalize the customer experience across 
12 markets at scale

Product

Recommend™, Discover and Engage

The Results

Here’s what Miinto’s personalization program achieved across twelve markets in 2025.

0 %
Revenue from Discover in Belgium
22- 0 %
Revenue attributed to Discover across core Europe
0 %
Incremental revenue
from Recommend™
in Sweden
0
Markets across Europe

The Client

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 (now part of ADA) 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.

The Challenge

The challenge with multi-market personalization isn’t getting it to work; It’s getting it to work everywhere.

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 (now part of ADA) 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.

How ADA Makes it Work

From discovery to purchase, Algonomy (now part of ADA) covers every stage of the shopper journey. Here’s how it performs across twelve markets.

1 Discover: Turning Exploration Into Revenue

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.

2 Recommend™: Closing the Loop at the Conversion Moment

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™.

Almost a Decade of Compounding

Ongoing optimization is built into how Miinto and Algonomy (now part of ADA) 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.

Table Of Contents
The Results
The Client
The Challenge
How ADA Makes it Work
Almost a Decade of Compounding

“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.”

Paloma Hellfeier-Truong
Director of Product & CX
Miinto

Explore More Resources on Commerce Personalization

Wine.com Drives AttributeBased Recommendations for Personalization
Food & Beverage US

Wine.com Drives AttributeBased Recommendations for Personalization

See full story
0 %
Reduction in out-of-stock across stores
0 %
increase in revenue

Your Retail Media program starts here.

Book a Demo

400+ Retailers & Brands Across the World Trust ADA

Looking to hyper-personalize your marketing? Let’s talk.

From Pilot to Profit:
 How Martin & Servera Built Retail Media In-House

Case Study

From Pilot to Profit:
 How Martin & Servera Built Retail Media In-House

Download PDF
Segment

Food, Beverage & Equipment Wholesaler & Foodservice

Objective

Generate new revenue by introducing sponsored product recommendations on the B2B e-commerce platform.

Product

Recommend™ with Data Science Workbench

The Results

Martin & Servera validated Retail Media as a scalable revenue stream using Algonomy’s (now part of ADA) Recommend™ and DSW, without investing in a costly point solution.

From September 2025 through April 2026, the program delivered strong outcomes across all key metrics.

0 %
Average Purchase Rate
0 %
Click-Through Rate (CTR)
0 X
CTR vs. standard recommendations
0 +
Suppliers onboarded within the first year

Placements closer to the point of purchase, such as the search results page, consistently delivered the highest engagement and conversion rates.

The Client

Martin & Servera is Sweden’s leading wholesaler for the restaurant and foodservice industry. Formed in 2012 through the merger of Martin Olsson and Servera R&S, the company supplies fresh produce, beverages, equipment, services, and training to restaurants, cafés, bars, and canteens across the country.

For over a decade, Martin & Servera has partnered with Algonomy (now part of ADA), using Recommend™ (with Engage) to deliver personalized, data-driven recommendations on their B2B platform. This helps engage customers, improve relevance, and ensure users quickly find what they need.

Personalized Product Recommendations on Home Page, powered by Recommend™.

The Challenge

Having built a personalized procurement experience, Martin & Servera saw Retail Media as the next growth opportunity. They wanted to monetize website space by displaying sponsored product recommendations from supplier brands and private labels.

While they had identified high-impact placements and built a business case, they lacked the infrastructure to execute. The team needed to:

  • Automate sponsored placements: Activate sponsored products by keyword, placement, audience, and campaign dates without manual merchandising.
  • Manage campaigns efficiently: Onboard, monitor, and optimize supplier campaigns without creating operational burden for the eCommerce team.
  • Personalize sponsored ads: Ensure sponsored products remain relevant through segmentation and behavioral context.
  • Avoid third-party ad solutions: Validate retail media in-house without revenue share models or vendor lock-in.

Martin & Servera required flexibility, automation, and control without overhead.

The Solution

To bring personalized sponsored recommendations to life, Martin & Servera leveraged Recommend™ and Data Science Workbench (DSW).

DSW is a self-service tool that allows data and analytics teams to move beyond pre-built models and build, test, and deploy custom AI strategies using customer, product, and behavioral data.
By using DSW as an add-on to Recommend™, Martin & Servera could control which sponsored products appear for which search terms, to which audiences, and for how long.

How it works

Martin & Servera activated sponsored recommendations in four key areas:
search results page, search flyout, mini cart, and checkout.

Sponsored product ads for spirits on Search Results page, powered by Recommend™ and DSW.

Suppliers purchase sponsored placements for specific search terms. Martin & Servera manages these agreements and uploads campaign files to DSW. Each file contains the search term, product SKU, campaign dates, and ranking score.

DSW combines campaign inputs with Martin & Servera’s product catalog and customer behavioral data, including searches, clicks, add-to-carts, and purchases collected through Recommend™. Using queries, the data team generated structured tables that mapped keywords to sponsored SKUs.

These tables power custom strategies that automatically inject sponsored products into the right placements for the right audience segments, and activate and expire campaigns, without manual merchandising.

Sponsored product ads for Heinz in the Search Flyout, powered by Recommend™ and DSW.

Built on Martin & Servera’s existing Algonomy (now part of ADA) setup, the team built a custom campaign planning tool to complement it. Together with Algonomy (now part of ADA), this avoided the cost and complexity of a dedicated third-party retail media platform. After go-live, the only ongoing step was regularly uploading supplier campaign files.

Sponsored product ads for milk in the Checkout pop-up, powered by Recommend™ and DSW.

What Sets This Program Apart

  • Built on Existing Personalization Infrastructure
    Sponsored product ads are launched on the existing Algonomy (now part of ADA) stack, with no vendor lock-in or revenue share models. Operationally, this means that Martin & Servera have access to the full suite of merchandising controls within Recommend™, which they use to optimize their campaigns.

    With the Segment Library feature, they can create different customer segments based on shopper business type and location, then target those segments in Merchandising Rules to prevent sponsored products from appearing to audiences where they are unlikely to perform well and vice versa.

  • Full Control with Automation

    Brand relationships, placements, segmentation, and revenue stayed in-house, while execution was automated.
  • Flexibility by Design
    The solution was built with several business goals in mind from the start, making it flexible and versatile enough to serve both supplier brands and private-label products across multiple placements and customer segments.
  • Built for Growth, Powered by a Small Team
    Managed by a small, cross-functional team with high autonomy, the solution is designed to grow with their needs. This makes decision-making agile, without the cost or complexity of a third-party ad server.

What’s Next for Martin & Servera and Algonomy (now part of ADA)

Martin & Servera is scaling their Retail Media program, closing deals with new suppliers while ensuring existing partners continue to see the value and reinvest. The team is continuing to fine-tune targeting options, gather deeper insights from campaign performance, and build greater automation into their campaign management process.

Table Of Contents
The Results
The Client
The Challenge
The Solution
How it works
What Sets This Program Apart
What’s Next for Martin & Servera and ADA

“We are happy for the flexible solution that Algonomy’s Recommend™ and DSW provide us in this start-up phase of our online Retail Media business.”

Hanna Hutter
Product Owner, Sales Tech
Martin & Servera

Explore More Resources on Commerce Personalization

Wine.com Drives AttributeBased Recommendations for Personalization
Food & Beverage US

Wine.com Drives AttributeBased Recommendations for Personalization

See full story
0 %
Reduction in out-of-stock across stores
0 %
increase in revenue

Build your own Retail Media program with ADA. No vendor lock-in. No revenue share.

Your Retail Media program starts here. Let’s talk.

Bergfreunde Cuts Campaign Prep Time by 75% Across 12 European Markets

Case Study

Bergfreunde Cuts Campaign Prep Time by 75% Across 12 European Markets

Download Case Study
Segment

Outdoor & Sports Retail

Objective

Automate and scale localized promotional emails across 12 European markets — modernize design, lift conversion.

Challenge
Active Content
Recommend

The Results

0 %
Reduction in campaign prep time (4 hrs → under 1 hr)
0 %
Faster lead time
on changes (1.5 weeks → 2 days)
0 %
CTR uplift on the Birthday campaign
0 %
Revenue-per-user uplift on the Birthday campaign

The Client

A pure-play outdoor retailer scaling across Europe, Bergfreunde GmbH is one of Europe’s leading online retailers for mountaineering, climbing, and outdoor equipment. The pure-play online business carries 40,000+ products from 700+ brands, serving ambitious climbers, expedition mountaineers, and urban outdoor enthusiasts across a localized footprint of 12 European markets.

40,000+
Items in catalog

700+
Brands

12
European markets

The Challenge

A twice-weekly campaign that wouldn’t scale. Bergfreunde’s flagship promotional campaign — PreisGrounder — was being hand-built directly inside their marketing automation platform, twice a week, for every country. Every send meant rebuilding layouts, swapping products, and re-translating copy: roughly four hours of work and a 1.5-week lead time per campaign.


With seven markets live and five more on the way, the manual workflow had become a hard ceiling on speed, modernization, and scale — and a blocker to introducing countdown timers, star ratings, and other social-proof elements the team wanted to test.

The Solution

Active Content and Recommend, working in lock-step. Bergfreunde turned to Algonomy’s (now part of ADA) Active Content to automate the entire PreisGrounder workflow — from data feed to localized creative for every market — and paired it with Algonomy’s (now part of ADA) Recommend to personalize the product picks inside every send. As a Recommend customer since 2015, Bergfreunde already had the product catalog and behavioral data fully integrated, so the team moved fast.

Today, the CRM team simply updates the product feed. Active Content assembles a modern, on-brand email — complete with countdown timers, star ratings, and gender-specific product labels — and pushes localized variants through their marketing automation platform to every country. Recommend handles the intelligence layer, surfacing the right product to the right shopper, every time.

Campaigns Powered by Active Content + Recommend

Two campaigns. One automated workflow. Below are the two campaign creatives that ship from the new setup — rendered on mobile, where the majority of Bergfreunde’s shoppers open their email.

Campaign 1

PreisGrounder — Twice-weekly promotional

Auto-assembled and localized for each of 12 European markets via Active Content.
Campaign 2

Birthday — Personalized via Recommend

Same campaign, same audience — personalized picks delivered +19.44% CTR and +32.33% RPU.

What’s inside the full case study

Get the playbook behind the numbers.
A four-page deep-dive into how Bergfreunde and Algonomy (now part of ADA) partnered to automate, personalize, and scale Europe’s most demanding email program.

  • The exact before-and-after of Bergfreunde’s PreisGrounder workflow.
  • How Active Content and Recommend combine to deliver compounding efficiency and personalization gains.
  • Detailed metrics on the Birthday campaign pilot — and what comes next for Bergfreunde.
  • A practical playbook for scaling localized, high-frequency email across multiple markets.
Table Of Contents
The Results
The Client
The Challenge
The Solution
Campaigns Powered by Active Content + Recommend
What’s inside the full case study

The collaboration has been very positive and constructive. Algonomy’s technology is flexible and powerful — particularly in automating campaign execution and enabling more modern, engaging designs. I am especially pleased with the efficiency gains and the improved scalability of our campaigns.

Martin Hauf
CRM Manager
Bergfreunde

Explore More Resources on Commerce Personalization

Wine.com Drives AttributeBased Recommendations for Personalization
Food & Beverage US

Wine.com Drives AttributeBased Recommendations for Personalization

See full story
0 %
Reduction in out-of-stock across stores
0 %
increase in revenue

Talk to an ADA specialist. Want to scale email campaigns like Bergfreunde?

We’ll be in touch within one business day. Let’s talk.

Personalizing Beauty at Scale: How Matas Grew Attributable Sales by 36% with Personalized Recommendations

Case Study

Personalizing Beauty at Scale: How Matas Grew Attributable Sales by 36% with Personalized Recommendations

Download PDF
Segment

Health, Beauty & Wellness Retail

Objective

Deliver a best-in-class customer experience, increase online sales, and drive operational efficiency at scale

Product
RecommendTM

The Results

Matas saw impressive YoY gains after expanding personalization across web, mobile, and email:

0 %
Lift in attributable sales from recommendations
0 %
Increase in orders via recommendations
0 %
Increase in items sold via recommendations
0 %
Growth in total site views
0 M
Clicks on recommendations, with improved CTR (1.6%)

These results highlight not just growing shopper engagement, but also the effectiveness of real-time personalization in driving revenue.

The Client

Established in 1949, Matas is Denmark’s premier health and beauty retailer. With over 250 stores and Denmark’s second-most-visited ecommerce site, Matas serves millions of customers through both its physical network and robust digital presence. In 2023, Matas expanded its regional footprint by acquiring KICKS, a major beauty retailer across Sweden, Norway, and Finland.

With personalization playing a pivotal role in customer engagement, Matas sought to create a seamless, data-driven experience across all channels—web, mobile, and email. Their long-standing partnership with Algonomy (now part of ADA), dating back to 2018, laid the foundation for a phased, scalable personalization program that continues to evolve.

The Opportunity

Matas wasn’t looking for just another recommendations engine—they wanted a best-of-breed personalization layer that could unify customer experiences across touchpoints and deliver results at scale. Key business objectives included:

  1. Creating a coherent and personalized CX across channels
  2. Driving online profitability and engagement
  3. Ensuring operational efficiency with fast time-to-market

The Solutions

Matas uses Algonomy’s (now part of ADA) RecommendTM across web, mobile, and email, with coverage across key customer journeys.

1 Web & Mobile Personalization

Across home, category, search, item, add-to-cart, and cart/checkout pages, Matas deployed hyper-relevant product recommendations that mirrored campaign messaging and user context.

Key strategies included:

Seamless cross-selling during Add-to-Cart

(For e.g., “More amazing skincare products” or “Bestsellers from the same brand”)

Cart page cross-sells

(For e.g., “Other customers also bought” or “Discounts on your favourite brands”)

Smart replenishment

(For e.g., “Buy again?” and “Your previous purchases”)

2 Email Personalization

Across home, category, search, item, add-to-cart, and cart/checkout pages, Matas deployed hyper-relevant product recommendations that mirrored campaign messaging and user context.

Matas added recommendations to all email journeys and campaigns. With both OOTB strategies and tailored algorithms, marketers could:

  • Personalize emails at scale using customer data and behavior
  • Match product campaigns to user interests
  • Trigger replenishment reminders and promote subscription products
  • Maintain brand tone and design consistency without sacrificing relevance

Advanced merchandising and configuration controls gave Matas full autonomy to manage everything in-house—no dev cycles needed.

3 Additional use cases reflect the advanced maturity of Matas’ personalization strategy:

  • Landing Pages & Campaign Pages: These are fully automated and personalized to match promotional campaigns with hyper-relevant product assortments at scale, enabling rapid time-to-market.
  • Subscribed/Auto-Replenishment Products: De-boosting strategies are intelligently applied to help customers discover new products beyond their routine purchases, adding a layer of thoughtful curation.
Table Of Contents
The Results
The Client
The Opportunity
The Solutions

“All I care about is relevance on the customer’s terms—full transparency and real control. Algonomy helps us make every interaction meaningful without compromising trust or customer experience.”

Peter Hestbaek
SVP of Digital Sales
Matas

Explore More Resources on Personalized Marketing

See all customer stories
Wine.com Drives AttributeBased Recommendations for Personalization
Food & Beverage US

Wine.com Drives AttributeBased Recommendations for Personalization

See full story
0 %
Reduction in out-of-stock across stores
0 %
increase in revenue
See all customer stories

400+ Retailers & Brands Across the World Trust ADA

Looking to hyper-personalize your marketing? Let’s talk.

Consum Cuts Campaign Costs by 60% with ADA’s Active Content

Case Study

Consum Cuts Campaign Costs by 60% with ADA’s Active Content

Download PDF
Objective

Internalize campaign execution and scale personalized communications efficiently across channels and languages.

Solution

Automate and scale Consum’s monthly communications with a centralized, no-code solution—powering real-time personalization across cashback emails, targeted offers, and localized newsletters.

Challenge

To personalize the key commerce touchpoints of product recommendations, search, category pages, and content.

Geography

Spain, Europe

Product Used
Active Content

Industry – Supermarket

0 +
Supermarkets
0 +
Company-owned stores
0 +
Franchise Stores
0 m+
Member-customers

The Results

0 %
marketing service provider cost savings for the loyalty team
0 %
reduction in time to prepare a campaign
0 %
reduced in turnaround time in additional communications

The Client

Consum is Spain’s cooperative with the largest number of members and a leading regional supermarket chain, headquartered in Silla, Valencia. Founded in 1975, Consum has grown into a trusted brand for over 5 million customers, operating a network of 1,000+ supermarkets across six autonomous communities (Comunidad Valenciana, Cataluña, Murcia, Castilla-La Mancha, Andalucía y Aragón). Consum operates a robust benefits program called Mundo Consum, which offers exclusive benefits to its member-customers, including a monthly cashback check and personalized product offers.

The Challenge

Consum aimed to streamline how it delivered personalized campaigns across channels, languages, and customer segments.

Internalize Campaign Execution

Reduce dependency on external vendors by fully in-house managing key communications, such as monthly cashback checks and personalized offers, for better speed and control.

Simplify Scalable Personalization

Deliver hyper-personalized, multi-language content at scale without adding IT complexity, even as offers and segmentation varied month to month.

The Solutions

Consum adopted Algonomy’s (now part of ADA) Active Content to centralize campaign personalization, streamline execution, and bring agility to their monthly communications.

1 Monthly Gift Check Emails

Sent mid-month, these emails automatically displayed the customer’s individual cashback amount as soon as it was available in the app, driving immediate engagement and traffic.

2 Personalized Discount Campaigns

At the start of each month, customers received product-specific offers based on supplier-defined segments. Active Content ensured the right message reached the right customer without manual intervention.

3 Localized & Personalized Newsletters

Each customer received a rich, tailored email featuring “My Favorites,” “Cheque Crece,” regional promotions, and a store-specific brochure—all assembled from over 15 localized assets in real time.

Table Of Contents
Industry – Supermarket
The Results
The Client
The Challenge
The Solution

“With Algonomy’s Active Content, we were able to take full control of our campaign execution. It’s given us the speed, flexibility, and personalization scale we needed to elevate how we connect with millions of members every month.”

Santiago Mozas Hernando
Jefe de área Digital de Fidelización, Departamento Socio-cliente y Marketing, Consum

Explore More Resources on Personalized Marketing

Wine.com Drives AttributeBased Recommendations for Personalization
Food & Beverage US

Wine.com Drives AttributeBased Recommendations for Personalization

See full story
0 %
Reduction in out-of-stock across stores
0 %
increase in revenue

400+ Retailers & Brands Across the World Trust ADA

Read the Case Study

Stadium Drives +17% RPV with AI-Optimized Messaging

Case Study

Scoring Big with Social Proof: Stadium Drives +17% RPV with AI-Optimized Messaging

Download PDF
Segment

Sporting Goods Retailer

Objective

Enhance conversion rate, customer experience, and operational scalability

Product Used
Social Proof Messaging

The Results

The implementation of social proof delivered compelling results.

On products where Social Proof was shown (Stadium SE PoC):

+ 0 %
Revenu per Visitor (RPV)
+ 0 %
Conversion Rate (CVR)
+ 0 %
Add-to-Cart Rate (ATC)

Early sitewide results after rollout across all five Scandinavian domains:

+ 0 %
Revenue Per Visitor (RPV)
+ 0 %
Conversion Rate (CVR)
+ 0 %
Add-to-Cart Rate (ATC)

Note: These sitewide numbers reflect early performance post-PoC. As the rollout expands and ongoing optimizations continue, results are expected to evolve further.

The real-time, data-driven messaging resonated strongly with Stadium’s online audience, encouraging faster purchase decisions and reducing hesitancy through the subtle influence of crowd signals.

The Client

Stadium is one of Scandinavia’s most prominent sports retailers, offering apparel, footwear, and gear across all activity levels. With a strong omnichannel presence across Sweden, Finland, and Norway, Stadium is deeply committed to promoting an active lifestyle and delivering seamless customer experiences both in-store and online.

With personalization already in motion through long-term use of Algonomy’s (now part of ADA) Recommend™ and Engage™ solutions, Stadium was ready to take the next step by adding social proof to elevate their ecommerce game.

The Opportunity

While Stadium wasn’t grappling with specific pain points, a quick pitch and demo of Algonomy’s (now part of ADA) Social Proof Messaging sparked their curiosity. The promise: real-time social validation layered into the shopping journey to boost CVR and shopper confidence.

As a data-forward brand, Stadium saw potential in experimenting with message types that conveyed what others were viewing, buying, and adding to cart—all in real time. Importantly, they wanted a solution that could scale across five different sites and languages, without compromising on speed or customer experience.

The Solution

1 Social Proof Messaging

Stadium partnered with Algonomy (now part of ADA) to roll out Social Proof Messaging across item pages on all five of its Scandinavian sites—stadium.se, stadium.fi, stadiumoutlet.se, stadiumoutlet.fi, and stadiumoutlet.no.

Over a 6-week proof of concept (PoC) for stadium.se, the teams tested six message types, each triggered by different shopper behavior signals—views, add-to-carts, and purchases. Each message was displayed in Swedish, with formats such as:

  • Trendar idag (Trending Today) and Trendar (Trending) based on real-time views
  • Säljer snabbt (Selling Fast) and Veckans snabbsäljare (This Week’s Bestsellers) based on recent purchases
  • Populär idag (Popular Today) and Populär (Popular) based on add-to-cart activity

Messages were prioritized by metric, with the system automatically selecting the next best-performing message if the primary one didn’t meet its display threshold. This ensured maximum coverage without compromising message credibility.

The logic and design were optimized collaboratively between Stadium’s team and Algonomy’s (now part of ADA) solution consultants, taking into account thresholds, time intervals, tone of voice, and aesthetic preferences.

Here is a key use case implemented on the site:

Social Proof Message on Item Page Based on Add-to-Carts Activity
Message displayed: Popular Today

2 Testing and Optimization

The solution was rigorously A/B tested using a 50/50 control vs. treatment split. Key metrics were tracked for products with social proof shown versus those without.

Algonomy’s (now part of ADA) MVT (Multivariate Testing) tool enabled Stadium to:

  • Compare message types like Trendar idag (Trending Today) and Säljer snabbt (Selling Fast)
  • Experiment with different triggers, including product views, add-to-carts, and purchases
  • Optimize placement, design, and thresholds to maximize visibility and impact

While full AI-powered decisioning was not yet live during the PoC, the foundation was laid for Stadium to eventually automate message selection using real-time performance metrics like RPV, CVR, and ATC rate. This next step is expected to further streamline optimization and reduce manual tuning.

The tests revealed consistent performance uplifts across combinations of messages, time intervals, and placements. The strongest lifts were seen on product detail pages where social proof was visible, validating its influence on shopper behavior.

Next Steps

Buoyed by the success of the item page rollout, Stadium is now planning:

  • Category page messaging: Showing popular products on collection pages
  • Social proof within recs placements: Enhancing engagement inside product recommendation carousels
  • Segment-based messaging: Tailoring proof by shopper type and behavior patterns

These efforts reflect Stadium’s ongoing ambition to create smarter, more intuitive digital journeys and its confidence in Algonomy’s (now part of ADA) personalization capabilities.

Table Of Contents
The Results
The Client
The Opportunity
The Solution
Next Steps
We saw clear results almost immediately after launch.

“Even small variations in message type created surprisingly different uplifts. It’s rare to see a tool this flexible and impactful at the same time.”

Vivian Nadim
Head of Digital CX
Stadium

Explore More Resources on Commerce Personalization

Wine.com Drives AttributeBased Recommendations for Personalization
Food & Beverage US

Wine.com Drives AttributeBased Recommendations for Personalization

See full story
0 %
Reduction in out-of-stock across stores
0 %
increase in revenue

400+ Retailers & Brands Across the World Trust ADA

Looking to hyper-personalize your marketing? Let’s talk.

How a US-based Retailer of Skin Care Devices Achieved 24% Increase in Revenue Per Session with ADA’s Engage™

Case Study

How a US-based Retailer of Skin Care Devices Achieved 24% Increase in Revenue Per Session with ADA’s EngageTM

Download PDF
Segment

Beauty & Wellness

Challenge

The client wanted to maximize revenue per session by optimizing home page content tiles for different customer segments.

Product Used

The Results

0 %
Increase in clickthrough rate (CTR)
0 %
Increase in revenue per session
0 %
Increase in overall clicks

The Client

The client’s mission is to beautifully transform skin through its award-winning devices, which cleanse skin six times better than hands. Hand-assembled at its headquarters, the devices are distributed through prestige retailers, dermatologists, cosmetic surgeons, spas and online at the client’s own ecommerce website.

The Director of Ecommerce and Digital Marketing for the client is in charge of managing customer website experiences to achieve the direct-to-consumer revenue goals for the business. In addition to optimizing traffic, conversion and revenue, the team manages all content, paid media channels, affiliates, search engine optimization and search engine marketing as well as retargeting, email and loyalty programs.

For the client, engaging and educating the new user is a critical objective for the website. When new visitors have their first experience with the brand on the website, they want the site to represent the “knowledge hub of the brand” so they can learn everything—from which device is right for them to what skin care products and brush heads pair best with their chosen device.

Old Way: Multiple messages meet multiple needs

The client’s mission is to beautifully transform skin through its award-winning devices, which cleanse skin six times better than hands. Hand-assembled at its headquarters, the devices are distributed through prestige retailers, dermatologists, cosmetic surgeons, spas and online at the client’s own ecommerce website.

The Director of Ecommerce and Digital Marketing for the client is in charge of managing customer website experiences to achieve the direct-to-consumer revenue goals for the business. In addition to optimizing traffic, conversion and revenue, the team manages all content, paid media channels, affiliates, search engine optimization and search engine marketing as well as retargeting, email and loyalty programs.

For the client, engaging and educating the new user is a critical objective for the website. When new visitors have their first experience with the brand on the website, they want the site to represent the “knowledge hub of the brand” so they can learn everything—from which device is right for them to what skin care products and brush heads pair best with their chosen device.

New Way: Content and Context Motivate Visitors through the purchase funnel

Having learned about Algonomy (now part of ADA) through existing partnerships with sister brands, the client decided to use the Engage™ solution to segment audiences, and test and optimize content tiles against key metrics—click through rate and revenue per session.

“Everyone will always have an opinion, but our job is to move from opinions to data-based decisions that show what customers are gravitating toward,” said the client.

“Clickthrough rate may be a function of the creative; revenue per session may be a function of the right message and content. A lot of times we don’t know, and that’s why it’s critical to always be testing.”

Engage™ maps individual shopper behavior against advanced targeting and audience segmentation tools so that marketers can deliver highly personalized campaigns with relevant content. Its ability to automatically target each segment, optimize the most effective creative for that segment, then pass the data back to the business to inform creative decisions for the next round of campaigns saves valuable time and eliminates the need to run hundreds of manual A/B tests to get content personalization right.

After implementing Engage™, the client has seen significant success in key metrics for users that interact with its home page content tiles, such as a 20 percent increase in clickthrough rate and a 24 percent increase in revenue per session, while also seeing a 35 percent increase in overall clicks.

“Engage™ gave us information on what messages and creative were resonating with customers. We tested 12-15 pieces of content for each customer segment and found two that resonated very well: ‘Find your Product’, which linked visitors to an interactive skin quiz recommendation engine, and a tile with the message ‘Great Skin Starts Here,’ which highlighted our key skin care benefits to our users,” said the client.

With plans to continue testing current content “winners” against new content, the client looks forward to uncovering more learnings and insight from using Engage™.

“The fact that I can keep testing content and justify why I’m showing it is amazing! I’m confident that these data-driven decisions are helping to move visitors efficiently through the purchase funnel,” they said.

Table Of Contents
The Results
The Client
Old Way
New Way

“The fact that I can keep testing content and justify why I’m showing it is amazing! I’m confident that these data-driven decisions are helping to move visitors efficiently through the purchase funnel.”

Director of Ecommerce and Digital Marketing

Explore More Resources on Commerce Personalization

Wine.com Drives AttributeBased Recommendations for Personalization
Food & Beverage US

Wine.com Drives AttributeBased Recommendations for Personalization

See full story
0 %
Reduction in out-of-stock across stores
0 %
increase in revenue

400+ retailers & brands across the world trust ADA to consistently deliver on their commerce KPIs

Looking to hyper-personalize all commerce touchpoints? Let’s talk.

UK’s FastGrowing Supermarket Drives 46% Revenue Lift

Case Study

UK’s FastGrowing Supermarket Drives 46% Revenue Lift

Download PDF
Segment

Supermarket chain/Discount retailer

Objective

Surface more of the client catalog to shoppers without compromising relevance, boost digital engagement and repeat visits, and reduce manual merchandising effort

Product
Discover™
Engage™
Recommend
Deep recs

The Results

  • Using personalized content targeted to shoppers interested in specific categories, such as Fishing and Pets, resulted in up to 6X higher click-through rates for these categories.
  • Algonomy (now part of ADA) DeepRecs NLP resulted in 2X higher engagement and 25X higher RPMI (revenue per 1000 impressions) for the special weekly event.
  • The client witnessed a 10% higher average order value and a 46% lift in revenue per visitor.
0 %
higher Revenue Per Visitor (RPV)
0 X
RPMI from DeepRecs NLP for new launches
0 %
Attributable Revenue
0 %
higher Average Order Value (AOV)

The Client

A UK-based supermarket chain launched its online store and wanted to improve customer experience and increase sales through website personalization. The online shop ran two weekly events where products would sell out quickly. Therefore, there was a need to monitor inventory levels, recommend substitutes for out-of-stock items, and alert shoppers when a product was back in stock.

The Challenge

The client needed a strategic partner to guide their personalization plans and provide the technology that meets the client’s unique business model. An essential requirement was strategic advisory services to help the business teams better understand personalization’s role across the customer journey, identify specific opportunities, and roll out the plan systematically.

The Solutions

  • Algonomy (now part of ADA) Engage™ allowed the team to experiment with content to guide visitors to the most relevant categories and campaigns based on their behavioral affinities and customer trends.
  • Algonomy (now part of ADA) DeepRecs Natural Language Processing (NLP) generated recommendations markedly differently from the traditional collaborative filtering recommendation techniques that rely on historical events.
  • Algonomy (now part of ADA) Discover™ helped to achieve their vision of delivering a cohesive experience to shoppers no matter how they interact with the site.
Table Of Contents
The Results
The Client
The Challenge
The Solutions

“Algonomy’s ability to personalize for unknown shoppers is key. We’re now successfully able to engage shoppers with deeper journeys, leading to a 10% higher average order value and a 46% lift in revenue per visitor. We’re also witnessing organic repeat visits, which is invaluable.”

Managing Director

Explore More Resources on Personalized Marketing

Wine.com Drives AttributeBased Recommendations for Personalization
Food & Beverage US

Wine.com Drives AttributeBased Recommendations for Personalization

See full story
0 %
Reduction in out-of-stock across stores
0 %
increase in revenue

Contact Us

Riachuelo Sees Nearly 4X Increase in CTRs and 5% Surge in Sales with a Nifty Countdown Widget

Case Study

Riachuelo Sees Nearly 4X Increase in CTRs and 5% Surge in Sales with a Nifty Countdown Widget

Download PDF
Segment

Department Store

Challenge

Enhance Riachuelo’s customer engagement, ensuring efficiency and flexibility

Product Used
Recommend
Engage™

The Results

0 %
Surge in sales
0 %
Growth in Black Friday Sale fragrance category
0 %
Increase in overall click-through rates
0 x
Rise compared to regular CTRs in other recommendation locations

Using Algonomy (now part of ADA), Riachuelo was able to see:

  • Significant Revenue Increase
  • Improved Engagement
  • Consistent Conversion Rates
  • Whopping Black Friday Flashsale Results

The Client

Riachuelo stands as one of Brazil’s largest and most distinguished fashion retailers. Established in 1947, the brand currently operates more than 300 stores and boasts a growing team of over 44,000 employees. With a history spanning over seven decades, Riachuelo has become a household name, offering a diverse range of apparel, accessories, and home products. Riachuelo’s commitment to delivering the latest fashion trends, top-notch products, and exceptional customer service has solidified its position as the preferred destination for millions of shoppers nationwide.

The Solution

1 The Countdown Widget — A Closer Look

Developed in collaboration with Algonomy (now part of ADA), the Countdown Widget is a dynamic and personalized feature that displays targeted product recommendations and a real-time countdown timer. Utilizing AI, custom merchandising rules, and data analytics, the Countdown Widget tailors product recommendations based on user behavior, preferences, and business rules, aligning seamlessly with merchandising objectives for the ongoing campaign.

The Motivation

Implementing Algonomy’s (now part of ADA) Countdown Widget at Riachuelo stems from various motivations, aligning with Riachuelo’s commitment to agility, efficiency, and customer-centricity:

  • Effortless Deployment
  • Streamlined Experience Management
  • Efficiency through Reusable Templates
  • Dynamic Injection for Flexibility in Page Placement

Table Of Contents
The Results
The Client
The Solution
The Motivation

“The Algonomy platform analyzes and acts based on behavioral data collected on the website, providing personalized experiences to consumers, which enhances our understanding of customers and drives business results.”

Ana Paula Santos Silva
Business Analyst
Riachuelo

Explore More Resources on Commerce Personalization

Wine.com Drives AttributeBased Recommendations for Personalization
Food & Beverage US

Wine.com Drives AttributeBased Recommendations for Personalization

See full story
0 %
Reduction in out-of-stock across stores
0 %
increase in revenue

Seamlessly Transform Your Results with Effortless Data Integrations

Talk to our Experts today

Older posts