CUSTOMER STORIES

How Stylley Increased AOV by 12.69% with Anphonic

Stylley partnered with Anphonic to drive higher revenue through AI-powered personalization, achieving a 12.69% increase in Average Order Value, influencing 11.68% of total orders, and generating 11.26% of revenue through personalized shopping journeys.

Topic covered

Results
12.69% increase in AOV through personalized experiences
11.68% of total orders influenced by Anphonic
11.26% of total revenue generated through personalization
83.30% driven by Product Discovery
Use Cases
AI-driven recommendations helped users discover relevant fashion items, increasing cross-category exploration and basket size.
Anphonic Product RecommendationsReturning shoppers were shown tailored product suggestions based on past behavior, encouraging repeat purchases.
Smart bundling encouraged customers to shop complete looks instead of individual pieces, naturally increasing order value.
Industry
Fashion and apparel

Stylley is a fashion-focused ecommerce brand offering trend-led styles for modern consumers. With a strong digital presence, the brand focuses on making fashion discovery seamless while encouraging higher-value purchases.

Challenge: Driving Higher Basket Value

As Stylley scaled its online store, the brand aimed to increase average order value and maximize revenue per customer without relying heavily on discounts.

Fashion shoppers often purchase single items instead of complete looks, limiting basket size and overall revenue potential.

The brand’s key objectives were to:

  • Increase AOV organically
  • Encourage multi-product purchases
  • Influence more orders through personalization
  • Improve product discovery across categories

Stylley needed a solution that could intelligently guide shoppers toward complementary products and complete outfits.

Strategy: Personalization Across Discovery and Cart

Anphonic was implemented across key stages of the customer journey, enabling real-time product recommendations based on shopper behavior and preferences.

Anphonic used data signals to surface relevant products during browsing and checkout, nudging users toward higher-value purchases.

Key Approaches

Personalized Product Discovery

AI-driven recommendations helped users discover relevant fashion items, increasing cross-category exploration and basket size.

Anphonic Product Recommendations

Returning shoppers were shown tailored product suggestions based on past behavior, encouraging repeat purchases.

Dynamic Product Bundles

Smart bundling encouraged customers to shop complete looks instead of individual pieces, naturally increasing order value.

Results: Measurable Impact

Within a short optimization period, Stylley saw clear improvements:

  • Strong uplift in AOV driven by better product pairing
  • Increased order influence through personalized journeys
  • Revenue growth without over-reliance on discounts

Product discovery emerged as the primary revenue driver, highlighting the importance of guiding users early in the shopping journey.

Impact: Fashion Commerce Powered by Personalization

Anphonic enabled Stylley to shift from transactional shopping to curated, discovery-led experiences.

Instead of pushing discounts, the brand increased revenue by:

  • Recommending complementary products
  • Encouraging outfit-based shopping
  • Personalizing the journey from browsing to checkout

This resulted in higher basket sizes while maintaining a seamless shopping experience.

Looking Ahead

With strong gains in AOV and order influence, Stylley is well-positioned to expand personalization into:

  • Post-purchase recommendations
  • Repeat purchase journeys
  • Seasonal and trend-based styling suggestions

FAQs

1. Did Stylley rely on discounts for growth?
No. Growth was driven through personalized product recommendations and smarter discovery.

2. Which feature drove the most revenue?
Product Discovery contributed the largest share.

3. Did personalization affect user experience?
No. It enhanced the journey by making product discovery more relevant and seamless.

4. Can this work for fashion brands?
Yes. Personalization is highly effective in driving outfit-based purchases and increasing basket size.

5. How quickly were results visible?
Results were observed within weeks of implementation.

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