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On the Amazon Effect, winning in B2B ecommerce, and the mid-market playbook
Whether you manage hundreds of SKUs or millions, Zoovu’s AI site search helps your customers find exactly what they need, quickly.
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Increase in searches
Lower bounce rate
Increase in average order value
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Show the most relevant products with AI-powered search that understands the intent of every query.
Whether it’s trending items or niche requests, our search engine guarantees customers find exactly what they want.
From products to support articles, Zoovu makes all your content accessible.
Offer personalized product suggestions and promotions that resonate with customers at the perfect moment.
Zoovu's search understands the relationships between your product attributes and customer intent to deliver accurate, context-specific results.
Zoovu’s large language model (LLM) interprets complex customer queries, translating vague or subjective terms into precise, relevant results.
Help customers filter results by needs-based categories instead of confusing and irrelevant terms.
Suggest relevant queries and popular items as customers type to help customers discover products faster.
Collect, clean, and enrich your product data with AI to turn it into a search experience your customers will love
Ingest and standardize data from various sources, ensuring a complete and reliable product catalog.
Automatically correct errors and standardize values, ensuring consistency across your catalog.
Convert technical specs into customer-friendly descriptions with generative AI, making it easy for customers to understand product benefits and discover complementary items.
Effortlessly update product data across all channels, keeping your catalog current and error-free.
Turn more visitors into customers with effective search.
Speed up searches with instant suggestions.
Streamline navigation and reduce friction.
Tailor results to match customer intent.
Boost sales with targeted suggestions.
Gain insights to refine search performance.
Understand complex customer queries.
Deliver contextually relevant results.
Fine-tune search to maximize conversions.
Integrate Zoovu with Salesforce, SAP, and any ecommerce platform, CMS, CRM, ERP, or PIM.
Zoovu ensures 99.9%+ uptime with our high-availability infrastructure.
We handle user data with care, keeping it confidential and secure through strict agreements.
We meet SOC 2, GDPR, ADA, CCPA, and ISO 27001 standards to keep your data secure and compliant.
B2C site search focuses on helping customers discover products they might want, often using NLP and AI to understand vague or broad queries. B2B site search, on the other hand, helps customers who usually know exactly what they need but need help finding it. For B2B, an ontology-based approach is more effective, as it understands the complex relationships between specific products, parts, and industry terminology.
B2C customers often start with vague ideas of what they want, such as “summer shoes” or “outdoor furniture.” NLP and AI help by interpreting these broad queries, offering relevant suggestions, and guiding customers toward products they might not have initially considered, enhancing the discovery process.
B2B customers typically have precise needs, like finding a specific part number or component. An ontology-based search understands and organizes information according to a structured framework, making navigating complex product catalogs easier and delivering highly relevant, context-specific results.
In B2C, the search experience is about exploration and discovery, where customers enjoy browsing and finding products they didn’t initially think of. In B2B, the search experience is more about efficiency and accuracy, helping customers quickly locate the item they need within a vast and complex catalog.
While there are overlaps, the strategies are generally tailored to different goals. B2C search strategies like AI-driven recommendations can inspire B2B improvements, but B2B’s focus on precision and ontology might not translate as effectively to the exploratory nature of B2C searches. Each approach is optimized for its specific user base.
B2C search development often emphasizes user-friendly interfaces, personalized recommendations, and dynamic content. B2B search development focuses on integrating deep product knowledge and industry-specific terminology and ensuring that search results are highly relevant to complex and specific queries.
A hybrid model might benefit from combining elements of both approaches. NLP and AI can enhance product discovery for less experienced users, while an ontology-based system ensures that professional buyers with specific needs can quickly find what they’re looking for. Balancing both can create a versatile search experience that caters to all customer segments.
Read about the trends, challenges, strategies being used by top B2B companies to digitally transform the way they sell
