google-analytics-measurement-protocol | Python package to send hits | Analytics library
kandi X-RAY | google-analytics-measurement-protocol Summary
kandi X-RAY | google-analytics-measurement-protocol Summary
Python package to send hits to Google Analytics through its Measurement Protocol API.
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Top functions reviewed by kandi - BETA
- Send an event
- Send a HIT
- Get content groups
- Build the base payload
- Get custom dimensions
- Get a list of custom metrics
- Handle a debug response
- Send a timing hit
- Send a page view
- Sends a social hit
- Sends a screenview hit
- Sends an exception
google-analytics-measurement-protocol Key Features
google-analytics-measurement-protocol Examples and Code Snippets
Community Discussions
Trending Discussions on google-analytics-measurement-protocol
QUESTION
I've fond this reference online about using the measurement protocol to capture user data from your CRM and appending it to the information that Google Analytics also captures, to get a holistic snapshot of your customer. https://www.upbuild.io/blog/crm-data-google-analytics-measurement-protocol/#comments
My questions is: Is the measurement protocol the right tool to match records in Hubspot to records in Google Analytics?
Can I use it to send Hubspot Client ID/ Properties to Google Analytics at the client level?
...ANSWER
Answered 2020-Jan-11 at 09:52Yes, with the same principle described in the comment of your link.
QUESTION
We have an online marketplace website with auctions. We would like to measure won auctions in Google Analytics, but this is not a frontend event, but a backend event (a timer for auction end expires). The user, who leads with the highest bid placed, wins the auction, once the timer runs out. The auction can last several days.
We would like to know where the winners of the auctions came from to place their first bid. So we are interested in source, medium and campaign. Currently we store in our backend DB a clientId and if present in URL also source, medium and campaign (or gclid). Later a backend job sends the data of finished auctions using measurement protocol to Google Analytics. But using this way we gather too few source, medium, campaign data in comparison to all clientIds for user bid events. User can come from search or ad to the website, click through the website and then place a bid and information about source, medium or campaign is lost.
So my question is
how to gather more source, medium and campaign data at the time when a bid is placed? Data will be send to GA using measurement protocol a few days later.
I did some research:
Should we use non-interaction hit? I found the suggestion here. But it is only briefly explained. Would the GA pair correctly automatically a frontend bid event with a few days later sent hit using MP? We know clientId.
Will it help us to define a new dimension for clientId that can be used to fetch source, medium and campaign data using report api v4 when a bid is placed using the steps described here?
...ANSWER
Answered 2018-Mar-16 at 10:04But using this way we gather too few source, medium, campaign data in comparison to all clientIds for user bid events.
The way you're doing it currently should work. When you send a measurement protocol hit to Google Analytics from your server, assuming the following is true:
- You include the user's client ID in the MP hit
- You do not include any utm parameters in the MP hit
Google Analytics should automatically apply it's last non-direct click attribution logic and the "auction-win" event should be automatically attributed to the source/medium/campaign that the user used to arrive at your site in the first place.
If this is not happening, then my suspicion would be that the two conditions above are not being satisfied.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install google-analytics-measurement-protocol
You can use google-analytics-measurement-protocol like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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