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Click-Through and Conversion Analytics

Click-through and Conversion Analytics takes our out-of-the-box Search Analytics further, providing insight into what significant actions a user takes after performing a search. Let’s look at these in detail and see how to implement it.

How to implement it?

With Click-through and Conversion Analytics, you can analyze two kinds of events:

  • clicks - clicking on results
  • conversions - a single significant event that tracks which searches lead most often to that event. Any event can be chosen as a conversion point.

This data is available by sending us events when your users click on a result or go to a certain page after a search. These events are sent by adding small bits of code to your application.

You can view Click and Conversion Analytics either in the Dashboard or programmatically via the Analytics API. If you signed up for your plan with an Account Executive, please refer to your service order for your analytics features.

Why track clicks and conversions?

By default, Algolia has no idea what happens after it returns search results. It does not know what you do with the results, nor what your users do with them. For Algolia to create a useful set of click analytics data, you need to send click-related information that answers the following questions:

  • Are your users clicking on the results?
  • If yes, which ones? The first or last? On which page?
  • And do your users take a significant action like adding one of your products to a wish list?

Algolia can compute such metrics as Click-Through-Rate (CTR), Average click position, and Conversion following a click for all queries. From these metrics, you can data-mine / measure the quality of the relevance of your results. For example, you can see which items your users consistently think should be higher in the ranking. Or you can analyze whether a user follows a click with a conversion, which could mean, for example, adding an item to a cart.

What can we learn from clicks and conversions?

We can learn a lot from data gathered by sending click and conversion events from your implementation. Especially conversion can tell us a lot about whether your search implementation is successful or needs some tweaking.


To give a preview of how these metrics can help, let’s compare 3 queries that use different words to convey the same intent (to find an eco-friendly refrigerator):

  • “refrigerator efficient” → lots of results, 50% click rate
  • “eco refrigerator” → less results, 10% click rate
  • “refrigerator saves energy” → no results

What can we learn?

  • You could add synonyms between “eco refrigerator” and “refrigerator efficient”.
  • You could do the same for “saves energy”, creating a 3-way synonym with “eco” and “efficient”.
  • You could rename your products in your catalog to use these words in all your records.
  • You could create a filter or a category for “eco-friendly”.
  • You could use these keywords more often in public-facing communication.
  • You could use the word “efficient” more often in your product descriptions, or promote products that describe themselves as “efficient”, since your users seem to prefer the word “efficient” over the word “eco” (50% vs 10%).


If we make some of the above changes, what can we learn with conversion rates?

  • “refrigerator efficient” → 10% conversion
  • “eco refrigerator” → 5% conversion
  • “refrigerator saves energy” → 5% conversion

  • We can see that we were right to include all these terms in our data, because they all convert.
  • It was also good to emphasize “efficient” over other words: given the higher conversion rate on the “efficient” query, it seems to be the preferred term.
  • If “no results” still appear, or you have low click rates, maybe none of your refrigerators are eco-friendly. Yet, if this is a popular search, you might want to consider adding these items to your product line.

  • If you don’t have enough of your highest converting items in your inventory, you might want to improve your stocks.

In these and other ways, search and click analytics give you insights into buying trends, and help you improve your data and index settings.

Insights events (click, conversion, view) used for analytics and/or personalization do not take immediate effect. The delay can range from 10 to 60 minutes depending on how long after the search they are sent. For precise times, see our page on when Insights events take effect.

Insights Validator plugin

Algolia provides a powerful API to track the usage of your search and surface metrics such as click-through rate, conversion and no result rate. To get access to these metrics, you have to implement click analytics and send events to our Insights API). You can test and debug your implementation by using the Insights Validator plugin for Google Chrome. This plugin shows you all the events your page is sending to Algolia.

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