American lifestyle brand adapts its emails to each recipient
2026-02-28 17:06 Diff
https://www.dynamicyield.com/case-studies/email-personalization/

Leading clothing and accessories retailer reimagines its email marketing program, delivering fully personalized content and recommendations

Increase in visits from email to website

after layering personalized content and recommendations into email marketing campaigns

Improved email open rates

due to increased relevance of experiences as users navigated between web and email  

Increase in demand from email

from segmenting campaigns according to affinity, past purchases, and shopping behavior

Introduction

For nearly 50 years, a leading American retailer has specialized in casual clothing, luggage, and home furnishings. Known for its quality and legendary service, the lifestyle brand has grown from a mail-order catalog business to a publicly-traded organization with over 5,000 employees. With the majority of revenue now coming from online sales, email marketing is critical to reaching its broad customer base. But amid high competition, the brand set off on a mission to adapt its email campaigns based on the meaningful interactions users were making on the site. Fast forward and its team is using Dynamic Yield to drive greater relevance and engagement across channels.

The Challenge

One of the most effective channels for driving sales and retention, the prevalence of email marketing across multiple sectors has made it difficult to stand out, despite increasing demand from consumers. To continue generating the most ROI from the channel, the retailer decided it needed to more deeply connect its web and email experiences.

The marketing team would need to be able to:

  • Incorporate meaningful on-site interactions into email campaigns.
  • Tailor content according to the recipient’s expressed product affinities.
  • Experiment with different contextual- and behavioral-based recommendations.
  • Ensure the most relevant email content and recommendations rendered upon open.

That’s when they turned to Dynamic Yield for AI-infused email personalization.

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Execution

Deployed affinity-based targeting for email campaigns

Using Dynamic Yield’s affinity-based personalization, which automatically detects, scores, and calculates individual affinity profiles as the site is interacted with, the marketing team was able to build audiences based on each customer’s affinity to certain categories (men or women) and types of products. They even created smaller, more niche audiences for those who showcased a preference to a particular color, or responded more to sale items than regular-priced items.

The affinity audiences were built dynamically based on on-site behavioral signals, context, and attributes in the product feed. So if the brand knew that a customer viewed women’s tops and plus-size products, the team could create an audience and then target them with personalized, dynamic content and product recommendations tailored just for them.

With deep behavior- and affinity-based audiences such as these, that are shared across platforms and channels, the brand could bring true personalization into their email program.

Created targeted, personalized email experiences using dynamic content blocks

With a “customer-centric” mindset, the retailer was laser-focused on ensuring every email experience was highly relevant to the recipient. To create such targeted experiences, the team decided to incorporate dynamic content into its post-subscription email campaigns, with each block based on previously-viewed items, such as Bedding or Women’s apparel.

When setting up these campaigns, the company programmed fallback images in the off-chance a user in the segmented campaign did not meet any of the targeting conditions, which is especially useful for shoppers who often switch between desktop and mobile.

Examples of personalized Dynamic Content based on Recently Viewed items in post-subscription emails (Image 1 & 2) as well as a fallback image for Dynamic Content (Image 3) 

Additionally, the team could rest assured that if the recipient browsed different items after the email had been sent, Dynamic Yield would reflect the customer’s most recent behavior and automatically showcase the most relevant content at the time of email open.

Re-engaged users via post-purchase emails with tailored product recommendations

To maximize exposure of its broad product catalog and create a consistent feel with email, the retailer took a granular approach to cross-selling products based on a customer’s purchase history. For example, if a customer purchased a women’s item but did not purchase outerwear recently, the team then targeted that customer with messaging around women’s outerwear and personalized recommendations that aligned with what they viewed with recent purchases.

They experimented with a number of contextual recommendation algorithms, including products or categories that are ‘similar,’ ‘bought with,’ or ‘viewed with’ the item purchased. The team also tested a variety of personalized recommendation strategies, including “Viewed Together Based on Recent Browsing History,” “Products Purchased with the Item Last Bought,” and a collaborative filtering-based strategy that displayed what customers with a similar user profile would have typically purchased.

Example of post-purchase email campaigns featuring contextual and personalized product recommendation strategies

Depending on the use case, the team discovered certain recommendation strategies made more sense than other – learnings that are being used to inform future email campaigns.

The Key Takeaway

In an effort to stand out in users’ inboxes and compete in an email-centric eCommerce landscape, this leading retailer set out to transform what were once static emails into fully personalized experiences. With the help of Dynamic Yield, its team was able to do just that, using the technology to not only create the logic and design of each email campaign but also to ensure the right products and offers were matched to different audiences based on their affinities, past purchases, and shopping behavior. The payoff of which has generated an increase in visits to the site, an improvement in open rates, and a greater demand from email overall.

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