If you build it they will come - if they can find it

All modern consumers - including ourselves here at The Cloud Community - are demanding. Whether it's expecting instant search results, self-service help or personalised recommendations, we make our buying decisions in an instant.

According to research from Google Cloud, retailers in the US alone lose over $300 billion every year due to bad search experience. Put another way, minimising customer effort increases conversion, sales and retention to the tune of a cool 20% revenue gain.

So how does Vector Search provide the foundation for giving your customers - and potential customers - the next generation search experiences needed to win and retain them?

Similarity search: Find visually similar images, video clips, and audio that match specific styles or samples. Similarity search enables applications such as reverse image search, image recommendation, and video and audio matching.

Personalised search: Model user behaviors and profiles, and find items similar to the ones a user has shown interest in. This lets you personalise recommendations for consumer products, movies, music, and more, and dynamically adapt any user experience to individual or cohort of users.

Enriched search experiences: Modern natural language processing (NLP) lets you enrich search experiences. Use vector search to retrieve a configurable subset of relevant documents. In a second step, identify the paragraph answering a specific question using a question-answer transformer, extract named entities (NER), or determine emotional content by applying sentiment analysis.

Transform search experiences with AI: Leverage large language models (LLMs) on business-specific information from your organisation's private data (not just publicly trained data).