Resources Merchandising Actions

Analytics

The Analytics section of the dashboard contains metrics that help you better understand your end users’ search-related activity.

This page outlines those metrics and the different tabs of the Analytics dashboard.

The metrics in the Overview tab and others come in two categories: out of the box metrics and click and conversion metrics. Click and conversion metrics only appear if your plan includes Event Analytics and if you’ve implemented event tracking.

NOTE

All metrics on all tabs are index specific. If you’re seeing unexpected metrics, make sure you’ve selected the correct index and date range. You can choose to include all replicas to aggregate replica index analytics.

Algolia’s new Merchandising Studio features Quick Analytics, allowing you to view your Search and Category Page KPIs at a glance as soon as you log into the tool. On the homepage, you’re able to choose to see data from a Last 7 days or a Last 30 days timeframe.

Quick Analytics

Need a closer look? Click See analytics to select a custom date range, filter by analytics tags, and compare performance for different date ranges of your choice. Our Trends Overview provides you with a visual view of how your KPIs performed for the date range you’ve chosen. Click Position shows you the average position of the product engagement from the search results.


  1. Load the dashboard section “Analytics”
  2. Select the correct index
  3. In the top navigation menu select “Overview” tab
    Overview
  4. Review the following analytics summary data:
    • Total Users - How many unique users performed a search. 
    • Note: One IP address counts as one user
    • Total Searches - How many searches were performed.
    • Note: As-you-type searches are aggregated. For example, “i” → “ip” → “ipa” → “ipad” counts as one search. The aggregation time frame is 30 seconds. For example, “i” → “ip” → “ipa” → 30 seconds → “ipad” counts as two searches—one for “ipa” one for “ipad”.
    • No Results Rate - The percentage of searches that returned no results.
  1. Load the dashboard section “Analytics”
  2. Select the correct index
  3. In the top navigation menu select “Searches” tab
  4. This tab shows:
    • Query - the most popular query terms
    • Count - the number of times they’ve been searched for
    • CTR - click-through rate
    • CVR - conversion rate
    • Click Pos. - the average click position
    • Total Searches - the percentage of all searches made up by this query term
    Searches
  5. In the “Query” column, click on a search term to see:
    • Average click position and a click position histogram, in addition to the previously listed metrics from step 4.
    • Rules, if any were applied
    • Filters, if any were used 
    • The results displayed for the search term
    Searches GIF
  1. Load the dashboard section “Analytics”
  2. Select the correct index
  3. In the top navigation menu select “Searches without Results” tab
    Searches without Results
  4. You can view all the searches your customers made on the website that returned no results. This information can be used to identify synonyms that you may need to configure in order to improve search relevance. Additionally, these queries can serve as an indicator of a trend or customer demand for products or services not currently featured in your online catalog, but might be worse considering to be added to it.
  1. Load the dashboard section “Analytics”
  2. Select the correct index
  3. In the top navigation menu select “Searches without Results” tab
    Searches without Results
  4. In the "Query" column, click on the search term to see 
    • Popular results for this search
    • Popular filters for this search
    Popular results for Search
  1. Load the dashboard section “Analytics”
  2. Select the correct index
  3. In the top navigation menu select “Searches without Clicks” tab
    Results
  4. Review the top results or search for a specific catalog item
    Review Results
  5. Optional: Filter the results by attributes
    Filter results
  1. Load the dashboard section “Analytics”
  2. Select the correct index
  3. In the top navigation menu select “Filters” tab
  4. Select the date range
    Filters
  5. Optional: Toggle the Analytics tags to get a more granular view. For example, you can get a more granular view for users who did not see the 'promo' by selecting "sawPromo:false"
    Analytics tags
  6. Review the filters tab data:
    • Top filtering attributes - the attributes users filter on most, for example, “color,” “category,” “brand,” etc.
    • Popular values per filter - the attributes values users filter with, for example, “red,” “yellow,” “purple” etc. You can select which filtering attribute (for example, “color”) you want to see the values for.
    Review filters
  7. You can use this analytics to improve your faceting configuration. For example, if your users filter on "size" and "color" attributes, but not your brand one, then you can remove your brand filter, or display it lower on your page. The same goes for filter values: If colors red and yellow are used more often than purple, you can adjust your inventory by stocking less purple items, or adjust your index settings by favoring or promoting red and yellow over purple. 
  1. Load the dashboard section “Analytics”
  2. Select the correct index
  3. In the top navigation menu select “Geo” tab
  4. Optional: Toggle the "analytics tags" to get more granular view. For example, you can get a granular view for new users by selecting "customerType:new"
  5. Review the "Geo" tab data:
    • Average search latency
    • Geographical origin of the searches, and the associated network latency (sorted by country, in descending order)
    Geo

Q: What is “empty search”? 

A: Search performed without text input:

  • Search-as-you-type experiences trigger a search request even before users start typing to instantly show results.
  • Users browsing the website without typing search queries in the search bar

Q: What is the analytical value of the “empty search” metric?

A: Analyse the relevance of your index, including the ways users interact with an empty search. For example, are products that show up first in the empty search popular or not?

Q: When to exclude the “empty search” metric from the analysis?

A: When an “empty search” lacks analytical value or skews the data. For example, most blogs sort articles by publication date, so empty search metrics give little insight into relevance.

Q: How to exclude the “empty search” metric from the analysis?

Note: you might need to be assisted by the engineering team to perform this task.

Q: How to prevent sending empty queries all together?

Note: you might need to be assisted by the development team to perform this task.


Implementing A/B Testing Configuring Analytics Tags