Using Google Analytics Measurement Protocol Hit Builder

This article is related to measurement protocol in Google Analytics.

If you are brand new to measurement protocol, then read this article first: Understanding Google Analytics measurement protocol.

In this article, I will show you, how to use the measurement protocol hit builder to create and validate payload data.

The best and easiest way to create and test payload data is by using the measurement protocol hit builder tool.

By using the hit builder tool, you can skip encoding the URLs and other type of data.

You probability of creating a valid payload data will be very high, if you use the hit builder tool.

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Follow the steps below to create and validate payload data for sending pageview data to Google Analytics via the measurement protocol:

Step-1: Navigate to measurement protocol hit builder tool: https://ga-dev-tools.appspot.com/hit-builder/

Step-2: Click on the ‘click here to authorize’ button:

click here to authorize

Step-3: Sign in with your Google account. Once you signed in, you can technically use the hit builder tool.

Step-4: Click on the ‘Add parameter’ button and add various hit parameters:

hit-parameter-details

Step-5: Scroll up (within the hit builder tool) and then click on the ‘Validate hit’ button:

valid-hit

You should now see the ‘Hit is Valid’ message:

hit-is-valid

Note: If the hit is not valid, then you won’t be able to send it to Google Analytics.

Step-6: Click on the ‘Send hit to Google Analytics’ button (shown above) and then check the GA Real time report, to see the pageview hit you sent via the measurement protocol:

testing-page-tracking

If you have created payload data outside of the hit builder tool, you can also validate that payload via the hit builder.

Just copy-paste the payload data you want to validate in the ‘Hit payload’ text box and then click on the ‘Validate Hit’ button:

copy-paste-payload

Learn about the Google Analytics Usage Trends Tool

The Google Analytics usage trend is a new tool which is used to visualise trends in your Google Analytics data and to perform trend analysis.


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