American underwear brand supercharges emails with personalized product recommendations

Popular New York-based underwear brand creates personalized, omnichannel experiences and overhauls email marketing campaigns

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increase in revenue per thousand impressions (RPM) from personalized recommendations for email using the User Affinity algorithm


Over a decade ago, the now-founders of a leading American retail brand set out to solve the common frustrations the average consumer faced with men’s and women’s underwear. Now home to premium collections of underwear, undershirts, loungewear, and more, the duo’s products are available in over 1,000 retail stores, in addition to its eCommerce site. As the New York-based company has evolved, it has shifted its focus to overcoming a key challenge: breaking down data silos in order to deliver more memorable experiences and better connect with its customers. And in an effort to deliver highly-personalized recommendations within its emails, as well as across its site, the team began searching for a personalization solution that automates and serves cohesive, tailored experiences across channels, eventually selecting Dynamic Yield to scale the impact of its email campaigns.

The Challenge

Email functions as a high-value channel for the retailer, but the marketing team lacked an ability to deliver truly personalized email campaigns. Like many other eCommerce businesses, the team would curate a selection of products to display in recommendation widgets in each email campaign, which was incredibly tedious and based on minimal segmentation. As a result, they were unable to provide the rich and engaging experiences – ones tailored to users’ affinities and behavior – they sought to deliver and that today’s consumers expect in their inboxes after expressing interest in products on-site. The team was looking to maximize the impact of their efforts, especially within emails, and required a solution that could:

  • Serve personalized recommendations to all users based on their unique affinities
  • Create a cohesive omnichannel experience for users across channels, from web to email
  • Automate the delivery of personalized product recommendations based on real-time behavioral data
That’s when the team decided to replace its existing personalization solution provider with Dynamic Yield. They quickly hit the ground running, using the platform to deliver tailored, on-site recommendations, as well as personalized product recommendations for emails.

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Delivered personalized, affinity-based recommendations to users across web and email
In an effort to create a seamless user experience for users interacting with both its eCommerce site and email campaigns, the marketing team knew it needed to begin by identifying and tracking on-site browsing behavior. Using omnichannel events to capture new and returning user activity, the team was able to begin creating a single view of the customer, linking behavior across devices and browsers in order to create a snapshot of each user’s individual preferences.

The team then began testing a number of algorithms to deliver personalized product recommendations based on users’ past interactions both on-site and in emails. Over time, they found the most success with the User Affinity algorithm, which delivered more relevant, personalized, and suitable recommendations to each user, especially as each user’s affinity profile grew with time. And because the team was tracking behavior across channels, they were able to ensure recommendations within emails were personalized according to users’ on-site browsing habits.
Example of an on-site recommendation widget using the User Affinity algorithm
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Used deep learning AI to serve personalized recommendations directly within emails
Prior to partnering with Dynamic Yield, the marketing team lacked access to AI-based targeting and was handpicking the products it displayed in its email recommendation widgets. Looking to develop more customer-centric email campaigns tailored to users’ expressed interests, they began using the solution to create a more cohesive user experience based on customers’ on-site interactions. Using smart, machine learning-powered recommendation algorithms, they retargeted users with product recommendation widgets within emails, using a customer’s entire order history and online activity to predict and display the most relevant products. Not only did this allow the team to deliver more relevant recommendations, but automating the experience delivery process also eliminated hours of manual work for their merchandising team and resulted in a 40% increase in revenue per thousand impressions (RPM) from its email campaigns.
Personalized email recommendation widget
Email recommendations example

The Key Takeaway

Understanding the importance of delivering truly tailored experiences to its customers, the retailer’s marketing team knew it needed the ability to not only connect user behavior across channels but also deliver dynamic email experiences personalized to each user. Using Dynamic Yield, the team was able to ensure users were served personalized product recommendations in emails according to past behavior and affinity data. Catering to each user’s preferences and creating cohesive, cross-channel experiences paid dividends, boosting CTRs in emails and generating revenue, in addition to saving its team hours of manual work it previously was allocating to curating product recommendations for static email experiences.