increase in average revenue per user by optimizing product detail page (PDP) recommendations
Founded in 2004, e.l.f. Cosmetics launched with a simple mission to create high-quality products at an accessible price point. Not only one of the earliest digitally-native beauty brands, e.l.f. was also one of the first to adopt a direct-to-consumer model.
In order to stay true to its business model, the cosmetics line places its customers at the core of all product and marketing decisions. So when e.l.f. sought to ensure every shopper was met with experiences tailored to their unique beauty regimen, the team partnered with Dynamic Yield to help them deliver.
After utilizing the first-party integration in Experience OS, recommendations and personalization capabilities, e.l.f. witnessed a 4.2% increase in average revenue per user and an 17.6% uplift in customer engagement.
Personalized recommendations also drove an 8.5 return on investment in a short period, meaning the tactics led to direct revenue gains that were more than eight times greater than expenses related to the personalization platform.
“Dynamic Yield has been instrumental in helping us uncover the different types of audiences coming to and interacting with the e.l.f. site, enabling us to cater to each beauty lover’s specific needs. Experience OS has allowed us to easily test new strategies and optimize on the fly for quick, meaningful results.”
e.l.f. opted to go beyond skin care and makeup junkies by creating and targeting niche customer groups. E.l.f. has created approximately 75 customer segments in a short period of time, such as frequent purchasers and people who frequently visit the website but have not completed a purchase.
e.l.f. targets segments based on needs and uses Predictive Targeting to match segments to variations.
Knowing PDPs are a valuable piece of the product discovery phase, e.l.f. chose this space to optimize its product recommendations. The team wanted to serve the most relevant products on PDPs to improve discovery and engagement. They decided to run a bake-off between Dynamic Yield and its incumbent recommendation point solution. Each vendor served a “Viewed Together” strategy in e.l.f.’s “You May Love” section, with a 50/50 split between the two vendors.
After reaching a statistical significance of 95% in just two weeks, Dynamic Yield proved the strongest engine, generating a significant uplift in click-through rate on recommended products (+23.2%) and a higher average revenue per user (+4.2%) compared to the other vendor.
With limited real estate, e.l.f. wanted its mobile menu to resonate with each shopper. To do this effectively, the team decided to personalize the menu based on browsing history, allowing customers to find products that are best suited to their needs quickly.
New visitors were shown high-level categories while returning visitors were exposed to subcategories of the main category in which they had previously shown interest.
For example, if a shopper had browsed the “skincare” category, the menu bar would include “cleanser,” “face masks,” and “treatments.”
Using Dynamic Yield’s unique affinity identification and matching capabilities with these menu optimizations, e.l.f. saw a 17.6% increase in clickthrough rate, driving visitors deeper into its product catalog.
e.l.f.’s customers have always been influential to the beauty brand. Yet, the team still had a significant opportunity to better understand shoppers’ needs and preferences throughout the customer journey.
After deploying Dynamic Yield, e.l.f. was able to truly tap into the critical audiences engaging with the brand to ensure each cosmetic lover received the most relevant experiences. And through strategically implementing several desktop and mobile web personalization campaigns, saw site engagement boost and revenue increase.
