The most important step in this sprint is checking that  everything is production ready.Your Algolia implementation should comply with your typical testing standards, preferably being covered by both unit and integration tests. 

To ensure you haven’t missed any steps during the onboarding process, you should double check against the implementation checklist and complete the go-live track. 

If you are concerned about usage and overages, follow the guide for optimizing search requests.

If you had clear KPIs you wanted to track your Algolia implementation against, it is important to make sure they are being tracked so we can measure any potential uplift.

By default, Algolia doesn’t track what happens after returning search results. It doesn’t know what you do with the results, nor what your users do with them. For Algolia to calculate Click and Conversion Analytics, you need to send information in the form of Insights events whenever your users click on search results or take meaningful actions like bookmarking, sharing, or purchasing items.

Click and Conversion Analytics also form the basis for more advanced features like A/B testing, AI Re-Ranking, and Personalization.

On top of that, you can use 3rd party systems such as Google Analytics, Datadog, etc. to track business metrics such as average order size, session time etc.

Once you’ve validated against the A/B Testing implementation checklist, you can start running A/B tests to optimize your relevance.  

A/B tests should run as long as possible to ensure significance. They can only be run on one index at a time, which is why it’s best to keep a schedule ahead of time of what you would like to test. 

You cannot have multiple tests running on the same index at the same time. But, you can run more than one A/B test simultaneously if the indices are different for each A/B test.

Additional details on A/B testing can be found here.