.png)
Introducing Semantic Search - an advanced search technology designed to understand and interpret user natural language queries. Unlike traditional keyword-based search, Semantic Search goes beyond just looking at the words you use. It understands what you mean and look for, by turning your words into a mathematical form (vector embeddings) that captures the full idea, delivering more results - precise and context-aware and of course personalized!!
Using Semantic Search does not mean that you have to forfeit our advanced business logic, you can still apply complex query rules to filter or promote results and use boosting to reflect item popularity or highlight key attributes.
Improves Accuracy: By understanding the meaning and context of queries, semantic search delivers more accurate and relevant results.
Enhance User Experience: The search engine can comprehend complex queries and provide precise answers.
Better Handling of Ambiguity: Semantic search effectively handles contextual clues to infer the most likely meaning.
All-in-one solution: Within one comprehensive solution we offer precise search engine, with deep contextual understanding by semantic search, with state-of-art recommenders’ system and advanced business logic layer
Implementing Synerise Semantic Search correctly involves several key steps and considerations to ensure optimal performance and user satisfaction. Follow these best practices to leverage the full potential of semantic search.
Ensure every product in your item feed has a comprehensive and detailed description. Usually, a few sentences.
Include relevant attributes such as size, color, material, use cases, and unique features.
Use natural language to describe products, avoiding jargon and overly technical terms where possible.
Use the hybrid search mode to combine the strengths of keyword and semantic search.
Example: A search for "summer dresses for beach vacation" should return results for both specific keywords like "summer dresses" and semantically related items like "lightweight sundresses."
Select the attributes that provide the most descriptive information about an item, typically the title and description fields.
Conduct A/B tests on different search index configurations (keyword vs. hybrid) to determine the best-performing setup.
Use the integrated preview and comparison tools to analyze the results in a single view.
Example: Test the effectiveness of semantic search on queries like "laptops for graphic design" versus traditional keyword search and compare user engagement metrics.
Regularly monitor the performance of your semantic search implementation.
Use analytics to track search success rates and user satisfaction.
Example: Track metrics such as click-through rates, conversion rates, and search abandonment rates to gauge the effectiveness of semantic search.