When it comes to commerce search, helping shoppers find what they are looking for efficiently and effectively is crucial for a successful shopping experience. Limiting search results to keyword matches can only lead to missed opportunities and frustrated shoppers.

The traditional keyword search approach has been the foundation of search functionality in commerce stores. However, as shoppers’ expectations evolve and search technologies advance, there’s a need for more intelligent and effective search solutions. This is where hybrid search, based on keyword and vector search, comes into play.

Empathy Platform embraces a hybrid search approach that combines the strengths of different search techniques to deliver enhanced and personalised search experiences in commerce stores. It integrates together keyword search, which matches search queries to indexed terms in the product catalogue, with vector search, which leverages advanced algorithms to understand the semantic meaning and context of search queries and documents.

Vector search complements keyword search by identifying the semantic similarity between queries, and thus yielding more relevant results faster. It extends keyword models to resolve no-results scenarios, provide synonym suggestions, and offer responses to long-tail queries.

Vector search can step in in certain cases where zero-results scenarios are more likely, helping to minimise those by offering results for semantically similar queries. The use of vector similarity enables a powerful recommendation system that enriches results by creating a cascade of relevant products.

If a customer searches for the term ‘tweed’, but there are no direct results, vector search jumps into action by displaying results for similar searches like plaid, plaid jacket, and blazer. The related results give the shopper a number of relevant choices that are semantically similar to their initial search. Vector search achieves this by interpreting search queries as vectors, the semantic neighbours of words.

Empathy Platform’s vector search is built on a completely native stack, ensuring that customer data and privacy are protected. Empathy Platform uses brand-specific tagging events to guarantee a personalised search experience that respects shoppers’ privacy.

Vector search goes beyond finding products, serving as an important tool for merchants to understand shopper intent and deliver a curated shopping experience. The result? A shopping experience with more precise results and fewer dead ends.

As Empathy Platform’s vector search evolves, its capabilities will start to become part of shoppers’ search experiences. They’ll be seamlessly integrated into their shopping routines and eventually become a unified index with the old-school keyword-based searching as part of a unified, powerful search solution.