How to Measure Your Search

You've made changes to your search algorithm or your LLM, you run a couple of searches and everything looks good. You roll it out to your users... and the complaints start flooding in. How do you prevent this?

How do you know that your search changes are good before you send them off to production?

Join us Feb 25 at 7 PM to learn just this topic.

Learn from the following:
Paul-Louis Nech - Algolia - Search Relevance in the Gen AI Age
You’re just done tuning search relevance perfectly for your human users, and just when you think you’re done, now you must do it again for robots? This is the age of RAG: we return relevant search results, not to a user, but to a LLM. What does this change? Can I reuse what I already know about relevance? You’ll learn that relevance for LLMs is not far from relevance for human users, and most of your hard work can be reused!

Elizabeth Sankey - Vestiaire Collective - Beyond the Metrics: Using User Research to Validate Search Improvements
Learn how to supplement quantitative search data with qualitative data.

Dustin Coates - Causaly - Measuring Search Relevance When Precision Really Matters
Certain domains require a high precision, such as biomedical research. How do you address that while still moving fast? It's all about tradeoffs, and we'll see some things that ensure accurate information doesn't get in the way of responding quickly to searcher needs.