Bosonozka Case Study: Driving Revenue Growth Through AI Product Discovery
- Antónia Volčková
- Jun 23
- 2 min read
Updated: Jun 24
Bosonozka.cz is one of the largest Czech e-commerce retailers specializing in barefoot footwear. They sell online across multiple European markets and operate a brick-and-mortar store in Brno. Managing hundreds of products alongside strong seasonality places high demands on search quality and recommendation relevance.
The Challenge: Unlocking Revenue Lost to Ineffective Search and Product Discovery
The default search and recommendation features on Shoptet were leaving significant revenue on the table:
Keyword-based search: Standard search relied purely on keyword matching. Natural language queries, typos, or colloquial expressions returned poor or zero results. Every edge case required manual synonym configuration.
Irrelevant recommendations: Similar and complementary products lacked visual and contextual connection. Customers frequently missed out on products they would have otherwise purchased.
Overwhelming manual management: A growing catalog and seasonal product rotations meant the team spent hours hardcoding rules instead of focusing on growth strategy.
The Goal: Increase total revenue and Average Order Value (AOV) without driving up marketing costs.
The Solution: Intelligent Product Discovery Across the Customer Journey
Bosonozka deployed Raventic’s AI product discovery stack across three critical touchpoints of the customer journey – from search to checkout:
Semantic Search: Replaced rigid keyword matching with a deep understanding of shopper intent. The system automatically processes natural language, typos, and synonyms without requiring manual rules.
Similar Products: Displayed visually and semantically relevant alternatives on product detail pages. This keeps customers engaged in the shopping funnel even if their initial click wasn't a perfect match.
AI Cross-sell in Cart: Recommends complementary items at the moment of highest purchase intent. Suggestions are based on actual product relevance and real performance data, rather than generic "customers also bought" logic.
Seamless Onboarding: The entire stack was implemented via Google Tag Manager. No custom development, zero IT dependency, and absolutely no ongoing maintenance required.
The Test: Validating AI Performance Through A/B Testing
To measure the real-world business impact, Bosonozka launched a controlled A/B test during the high-volume Christmas season.
Duration: 19 days
Sample Size: ~44,800 users
Split: 50/50 – Raventic vs. default Shoptet functionality
Tracking: GA4 + Raventic Analytics (event-based tracking)
The Results: Double-Digit Gains in Revenue and AOV
Overall Business Impact
+17.5%
higher revenue
+19.8%
higher Average Order Value (AOV)
in the Raventic group compared to the control group
Performance by Feature
Feature | Revenue Share |
Semantic Search | 40% of revenue went through on-site search |
Similar Products | 41% of revenue driven via product recommendations |
Cart Cross-sell | 12% of revenue driven via in-cart recommendations |
Why It Worked
Full-Funnel Optimization: Raventic optimizes search, product pages, and the shopping cart – capturing value at every critical decision-making moment.
Zero Maintenance: No synonyms, no manual rules, and no seasonal reconfiguration. The AI interprets shopper intent entirely automatically.
What Bosonozka Says:
“The A/B test results were clearly positive – both revenue and average order value went up. The implementation via GTM was fast and required no effort from our dev team. For e-shops looking for a quick solution without custom development, Raventic is definitely a smart move.”
Jaroslav Bednář, CTO Bosonozka.cz
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