Unlocking 21x ROI: Lovisa’s Success with AfterShip Personalization

“After implementing personalized product recommendations, we see a 4.3% increase in upsell revenue across the entire site by AfterShip Personalization. 74% of personalization revenues actually come from product detail pages.”

Matthew Stuckings, CRM & Data Manager

About Lovisa

Established in April 2010, Australia-based Lovisa quickly became a global leader in fast-fashion jewelry retail. With over 900 stores across 37 countries, Lovisa achieved sales revenue exceeding US $459 million in the 2024 financial year.

Demonstrating a commitment to staying ahead of trends, Lovisa introduces 150 new styles weekly, providing shoppers with a continual selection of fresh, fashionable jewelry.

The Challenges

"Anything in the eCommerce game is all about costs," noted Matthew Stuckings. "Everyone's now feeling the pressure of high expenses, constantly fielding questions about ROI."

Lovisa faced hurdles with its average order value (AOV) below many of its competitors. Meanwhile, acquisition costs were rising as tactics like free shipping and discounts added strain on profit margins.

"Everything we do aims to maximize AOV and customer lifetime value (LTV). We see personalization as the solution," explained Matthew, emphasizing that "80% of shoppers are more likely to buy from brands offering personalized experiences."

Yet, implementing effective personalization was challenging for Lovisa, particularly given its extensive product range and frequent new launches.

Specific Challenges:

• Shopify Plus didn’t support all stages of the shopping journey, requiring Lovisa to add multiple vendors or tools, complicating data storage and management.
• Manually bundling products became nearly impossible with the volume of in-stock items and frequent new releases.

The Results

After implementing AfterShip Personalization (APZ), Lovisa overcame its challenges, achieving outstanding results across its AU, UK, and US sites.

• The AU site, Lovisa's largest store, witnessed:
  • Revenue saw a 3% boost, and
  • 11% of orders attributable to AfterShip Personalization
• Among all the APZ-enhanced pages, the product page stood out as the star performer

“Lovisa's overall revenue achieved an impressive 21x ROI, with AfterShip Personalization contributing around 3% of total revenue,” shared Matthew.

The Strategy

“What strategy are you going to use? There are so many options; you need to find a starting point,” said Matthew. “We use the existing data in our customer data platform (CDP) to gain some insights first.”

Leveraging buying patterns
Shoppers’ behavior differs at each stage of the journey, making it critical—but challenging—to select the right recommendation algorithm.

Matthew noted, “One interesting insight is that whatever product type a shopper buys first, the second order is likely to include a similar product type.”

Lovisa’s team evaluated multiple algorithm options, such as “Similar products,” “Complementary,” and “Frequently bought together,” using these as starting points for testing across pages.

Targeted product recommendations
Initially, Lovisa deployed recommendations across all key touchpoints—the homepage, product page, checkout, thank-you page, and more. They soon found that over 70% of personalization revenue originated from the product page.

“The closer you get to the ‘add to cart’ stage, the more impactful the recommendations become,” Matthew explained. “We prioritized optimizing the product page.”

Lovisa structured its product page personalization strategy by:

• Testing “Similar products” and “Frequently bought together” algorithms via A/B testing.
• Discovering that “Similar products” drove 30-40% more revenue than “Frequently bought together,” with a 13% higher click-through rate and a 1% higher conversion rate.
  
  

These findings reinforced the trend that shoppers tend to buy items in matching colors or styles, often purchasing within the same category on repeat visits. For instance, a shopper who buys blue earrings is likely to add a matching blue bracelet or necklace to complete the look.

APZ's efficient data storage capabilities allowed Lovisa to use product page insights to enhance recommendations across all stages, from the homepage through post-purchase touchpoints.

Key learnings from Lovisa’s personalization journey

• Even small increases in AOV can significantly impact revenue
• Personalization closer to the add-to-cart click yields better results
• A well-structured A/B testing plan is essential for optimizing personalization
  
  

What’s next with product recommendation and AI
Despite having a robust data storage platform and APZ in place, Lovisa faced challenges in recommending products to new shoppers or items lacking prior sales data.

“We’re still optimizing areas like the homepage and post-purchase pages to further boost LTV,” shared Matthew. “However, due to our high volume of new shoppers, frequent product launches, and our extensive product catalog, we currently lack enough data to generate precise recommendations for these areas.”

Lovisa has tackled this by leveraging APZ’s advanced capabilities, which allow shoppers to discover relevant products based on product intelligence, even with minimal behavioral data or site engagement.

Powered by the Large Language Model (LLM), APZ identifies associations between various product tags, drawing on industry insights and feeding them into Discovery AI. This ensures real-time recommendations that effectively match products to audiences.

Lovisa is currently enhancing its personalization approach with APZ to improve on-site conversions and elevate AOV to new heights.

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