Topic covered
CUSTOMER STORIES
How Miriyam Store Increased AOV by 11.84% with Anphonic
Miriyam Store partnered with Anphonic to drive higher-value purchases through discovery-led personalization, achieving an 11.84% increase in Average Order Value, influencing 12.72% of total orders, and generating 10.59% of total revenue through personalized shopping journeys.
Results
11.84% increase in AOV through personalized experiences
12.72% of total orders influenced by Anphonic
10.59% of total revenue generated through personalization
91.75% of revenue driven by Product Discovery
Use Cases
AI-powered recommendations helped users explore relevant products, significantly increasing cross-category purchases.
Users were shown relevant products early in their journey, improving engagement and reducing decision fatigue.
Subtle cart-stage nudges encouraged incremental additions without disrupting checkout.
Smart bundles enabled users to purchase complementary products together, increasing overall basket size.
Industry
Fashion and apparel
Miriyam Store is a fashion and lifestyle brand offering curated products for modern consumers. With a diverse catalog, enabling seamless discovery is critical to helping users find relevant products and increasing purchase value.
Challenge: Driving Discovery in a High-Intent Catalog
Miriyam Store operates in a category where users often arrive with intent but may not fully explore the catalog.
This leads to:
- Limited product discovery
- Lower cross-category purchases
- Missed opportunities to increase basket size
The brand’s key objectives were to:
- Improve product discovery across the catalog
- Increase AOV through complementary purchases
- Influence more orders through personalization
- Guide users toward higher-value baskets
They needed a solution that could surface the right products at the right time.
Strategy: Discovery-Led Personalization Across the Journey
Anphonic was implemented with a strong focus on product discovery as the primary growth lever.
Using real-time behavioral data, Anphonic enabled:
- Personalized product recommendations during browsing
- Intelligent product sequencing to guide users
- Contextual nudges across key touchpoints
This ensured users were consistently exposed to relevant products throughout their journey.
Key Approaches
Product Discovery
Product discovery contributed 91.75% of total revenue, making it the dominant driver of growth.
AI-powered recommendations helped users explore more products, increasing cross-sell and basket size.
Cart Upsells
Cart-based recommendations contributed 4.16% of revenue, driving incremental value at checkout.
Dynamic Bundles
Bundles contributed 4.08% of revenue, encouraging users to purchase complementary items together.
Results: Measurable Impact
Within a short span, Miriyam Store saw clear improvements:
- Increased product exploration across categories
- Higher AOV driven by discovery-led journeys
- Meaningful revenue contribution from personalization
- Strong reliance on discovery as the primary growth lever
The results showed that early-stage guidance plays a critical role in driving higher-value purchases.
Impact: Scaling Revenue Through Discovery
Anphonic enabled Miriyam Store to transform product discovery into a consistent revenue driver.
Instead of relying heavily on discounts, the brand increased revenue by:
- Guiding users toward relevant products early
- Encouraging cross-category exploration
- Personalizing the browsing experience
This resulted in improved basket sizes and a more engaging shopping journey.
Looking Ahead
With strong gains in AOV and discovery-driven revenue, Miriyam Store can expand personalization into:
- Trend-based and seasonal recommendations
- Personalized collections and edits
- Post-purchase and repeat journey optimization
FAQs
1. Did Miriyam Store rely on discounts for growth?
No. Growth was driven through personalized product discovery and smart recommendations.
2. Which feature contributed the most revenue?
Product Discovery was the highest contributor, driving 91.75% of revenue.
3. Why is discovery important for fashion brands?
Because users often need guidance to explore styles, categories, and combinations.
4. Did personalization improve user experience?
Yes. It made browsing more relevant and reduced decision fatigue.
5. How quickly were results visible?
Results were observed within weeks of implementation.
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