Advanced Buyer Analytics Reports

This feature provides raw analytics data for how the audience uses the configurators.


The Analytics Reports can be used to garner insight into what the customers care about the most. The data can provide information about buyer trends for specific products or options, over a given time period.
These reports capture three broad categories of data:
  • Configuration Changes - what the customer looks for
  • Player Load Time - how long the customer has to wait to get the visuals
  • Session Length - how long the customer spends during configuration
The resulting reports are presented as a set of spreadsheets which contain the raw analytics data, ready for download as .csv files.
In order to visualize the data or extract specific information, these spreadsheets would need to be processed by an external data manipulation toolset or script.


Enable Advanced Buyer Analytics

To get access to these reports, org administrators need to enable the Advanced Buyer Analytics feature for that org.
Enable Advanced Buyer Analytics

Generate Reports

Once the feature has been enabled, you will then be able to generate the reports by accessing the Reports page under the main Analytics section from the org sidebar.
Access the Reports
You have the choice to generate any of the following reports, based on a given Start Date and End Date:
  • Configuration Changes
  • Player Load Time
  • Session Length
Generate new Reports
Once the reports have been generated, they will become available as entries on the Reports page. Each one will have an Export button available that enables the user to download the CSV file for that particular report.
The View Full Log option beside each report will take the user to the Job page that was used to generate the report. The task in that job can provide some additional information about the job, for troubleshooting purposes.
The Reports page can also be filtered by Report Type, Start Date, and End Date.
Filter the Reports Page

Configuration Changes Report

The Configuration Changes report will likely end up being the most important one out of the three. Events will show up on this spreadsheet based on when the buyers perform configuration changes on any of the catalog items.
Custom events can also be triggered through a custom script using the Create Event API. This could be particularly useful for modular configuration.
The current_configuration column inside the Configuration Changes report will contain the configuration data for each event stored as a JSON script, which includes the asset IDs of all the options used in that configuration.
Example of current_configuration column

Excluding Items From The List

The Advanced Buyer Analytics will be enabled by default on all existing and newly created Items in the Catalog. If you wish to stop tracking analytics on specific items, this can be done in a couple of different ways, from the individual Item page. Simply choose to Un-track Buyer Analytics from the More... button on the Item preview page, or check off the Track Buyer Analytics checkbox on the Item's Quick Edit panel.
Un-track Buyer Analytics on the Item Page
Track Buyer Analytics checkbox on Quick Edit Panel


Conversion Data

A very important aspect of buyer analytics are the choices that buyers actually make at the end of their experience with the configurator, and the journey that took them to their final decision.
At this time, ThreeKit is unfortunately unable to provide access to analytics data on Add-To-Cart or Buy-Button clicks by the end users, as these functions exist outside of the ThreeKit Player.
It is possible, however, to correlate the data from the ThreeKit reports with the external webpage analytics data (such as Google Analytics) based on session IDs and time-stamps. This would ideally be performed by an external data manipulation script or toolset.
Here is a guide on matching the session IDs from the external analytics data, to the data from the ThreeKit reports.

Data Analysis

The reports currently generated by ThreeKit only contain the raw analytics data. This makes it difficult to extract specific information, such as buyer trends for most popular configuration options over a given time period.
In order to easily visualize the data, an external toolset or scripts would be necessary at this time.