Find Response Report

The Find Response Report from the Omnichannel Personalization dashboard provides a comprehensive analysis of search responses. It helps retailers understand which products are returned in search results, which products are clicked on the most, and which positions are clicked most frequently. This insight enables retailers to identify high-performing products and optimize search result positioning to enhance user engagement and sales.

To view the Find Response Report:

On the Omnichannel Personalization Dashboard page, go to Reports > Find Response Report.

Filters

Any changes to the filters require the user to apply the changes:

With all Algonomy reports, the date range is the first option that can be adjusted. You can specify a custom date range by selecting start date and end date, or you can select from a list of presets, such as Week, Month, Quarter, and Year.

Find Response Table

The Find Response Table displays all the data available based on the date range.

The table includes the following dimensions used to calculate the rollup:

  • event_date: This column stores the date on which a user entered a search query in the MM-DD-YYYY format.

  • search_string: This column captures the exact search term the user entered. This allows you to analyze what users are searching for.

  • product_ext_id: The external ID of the product.

  • product_name: This column provides the name of the product that appeared in the search results for a particular search query. This is the name users see when browsing products.

  • region_id: The region in which the search was done.

  • product_position: The position in which the product appeared in the search results.

  • Total Product Position Count: Total number of times a product appeared at a specific position.

  • Product Position Percentage: Product Position Percentage is the frequency at which a product appears in a specific position in search results,

    Product Position Percentage = (Number of times a product is returned in a specific position for a given search query / Total number of search queries) * 100

  • Total Num Of Queries: Total number of times the search term was searched for.

  • Total Num of Clicks: The number of times a product was clicked when it was in a certain position in the serach results.

  • Position Click Rate: The rate at which users click on the product based on its position.

    Position Click Rate = (Number of times users clicked on a product in a specific position / Number of times a product returned in specific position) * 100