Transforming Houseland’s Product Recommendation Experience with Raventic Multimodal Technology
- Katerina Vaclavkova
- Jul 3
- 2 min read
Updated: Jul 18
Houseland is a leading retailer specializing in home décor and furnishings, offering a wide range of products from designer furniture to children’s toys. As part of its digital strategy, the company aimed to enhance its product recommendation experience to improve customer satisfaction and drive revenue growth.
By partnering with Raventic AI, Houseland implemented a Multimodal Similar Products solution — and achieved measurable impact within just a few days.
The Challenge: Large Catalog, Diverse Categories, and Underperforming Recommendations
Houseland faced several significant operational challenges:
Massive Product Catalog: Over 90,000 products across two countries
Diverse Categories: 267 product categories, from high-end furniture to children’s toys
Ineffective In-House System: The previous recommendation engine relied on product family, brand, supplier, and category — but failed to provide accurate or engaging suggestions, ultimately limiting revenue potential.
Product Discovery Is Especially Hard in Home & Décor because of no standardized product identifiers — visual AI is the key.
In the Home & Decor segment, product recommendation is particularly challenging due to the lack of standardized identifiers — for example, furniture items don’t have a universal system for classification or comparison. Different manufacturers use varying names, labels, and descriptions, making traditional filtering or rule-based pairing unreliable. That’s why visual similarity is often the most effective approach in this category — it allows customers to easily discover alternatives or complementary products that match their aesthetic preferences, regardless of how the items are named or categorized.
Raventic’s AI-Powered Multimodal Recommendation Engine: Fast, Accurate, Seamlessly Integrated
Raventic delivered its Multimodal Similar Products solution, customized to fit Houseland’s specific needs:
Strategic Placement: Recommendations were embedded directly on product detail pages, maximizing discoverability.
Rapid Implementation: The system went live in just 2 days.
High Accuracy: Without requiring long setup or training, the system delivered precise and relevant results.
Visual Consistency: The look and feel of the recommendations were fully aligned with Houseland’s UX and brand aesthetic.
Product Recommendations Before and After Raventic AI:
The Impact: Higher Revenue, Better Engagement, and Bigger Baskets
Raventic’s solution led to measurable business outcomes:
+7% | 31 % | +40 % | 2.6x |
total revenue growth | of total revenue | higher AOV | longer time on site |
attributed to product recommendations | came from users who interacted with Raventic-powered content | from these users | reflecting greater engagement and satisfaction |
What Houseland Says:
Raventic’s recommendations impressed us with both their speed and accuracy. They are the only provider offering a solution that truly understands the unique needs of the Home & Decor segment, where visual appearance plays a crucial role. For our customers, design is a key factor in decision-making — and Raventic handles this effortlessly. We believe this approach will remain a vital part of our digital strategy moving forward.
Jméno a Příjmení, E-commerce Manager
From Better Recommendations to a Stronger Digital Strategy
By integrating Raventic’s cutting-edge AI technology, Houseland elevated its customer experience and significantly boosted revenue. The next step: expanding personalized discovery into additional categories and stages of the customer journey.
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