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Hybrid Vector Search: Beta Tester Guide

Written by Florian Niedermayr

Feature Value and Overview

Nosto's Hybrid Vector Search is an advanced search technology that merges traditional keyword matching with vector-based semantic understanding. This intelligent approach goes beyond simple character matching to understand the intent of a user's query, leading to a smarter shopping experience.

The primary benefits include:

  • Eliminating 'zero-result' pages.

  • Improving search relevance overall.

  • Driving higher click-through rates (CTR) and conversion rates (CR).

What it Does

The system automatically decides whether to use traditional keyword search results or vector search results based on specific scenarios that can be individually configured and controlled by the user.

Vector search works by capturing the conceptual similarity between the user's search query and your product data, ensuring that conceptually related products are found even without exact keyword matches.

User Configuration and Control

You can actively manage how Hybrid Vector Search works through the Nosto Admin UI:

  • Basic Activation: Toggle to activate the vector search component of hybrid vector search.

  • Trigger Scenarios: The system is designed to trigger vector search for 0-Results Pages and for Low CTR/CR Queries. You can configure the performance thresholds that define a 'low' performing query. The additional information when choosing a certain value shows you the expected ratio of vector search based results. This helps you understand the impact of the chosen configuration.

  • Query Management: You have granular control to either exclude specific queries from ever showing vector-based results or to force vector search activation for queries that the automatic system doesn’t cover.

  • Score Insights: Similarly to keyword search, you can see the impact ratio between vector search and merchandising rules in the score insights UI.

  • Merchandising: All your existing merchandising rules, such as pinning and boosting, remain fully applicable to results surfaced via vector search.

  • Searchable Fields: To achieve the best results, ensure that only fields containing precise and concise product information are selected as searchable fields. This is as important for keyword search as it is for vector search.

  • Integration: Activation is done solely through the Admin UI. For front-end customisation, the Search API response will include new information to identify which results were powered by vector search. For more information on the API, see the related Tech Docs.

  • Data Vectorisation Frequency: Vectors are generated every 24 hours.

Analytics

All accounts using hybrid vector search, will see enhanced search analytics that highlight the impact of vector search to the overall search metrics. The highlighted percentage in the blue box shows the percentage of all vector search interactions that contributed to a certain metric, available for:

  • Total searches

  • Orders

  • Sales

  • Click-through rate

  • Conversion rate

  • Product clicks

Moreover, there are also some vector search specific metrics available in the search analytics tab:

  • Amount of vector search responses

  • Amount of avoided no results pages

  • A dedicated table showing all queries that led to a vector search response

Ongoing Improvements

This feature is currently in a closed beta program as we continuously refine the technology, which means some limitations apply. We are actively working on improving the feature, and future plans include:

  • Supporting product data from more fields, including extracted fields

  • A mechanism to understand and compute price expressions in queries

  • Expanding language support for vector search.

  • Continuous training of the underlying AI

  • Introducing blended result sets, combining keyword and vector search results instead of the current "either/or" approach.

  • Increasing the frequency of product data updates (vectorisation).

  • Adding support for data vectorisation for merchants who index SKUs separately.

We appreciate your active participation and feedback - it will help us shape this feature.

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