In my last post, I discussed how we’ve paired events that happen after a conversion point. For example, after a user submits an enquiry form, did they go on to book an appointment? This time, we’re going to discuss the UserID function and the analytics measurement protocol to measure online performance with offline outcomes.
The beauty of the measurement protocol in my view is that you do not need a webpage with an analytics snippet to fire analytics data. The enormity of this awesomeness goes beyond mobile analytics SDKs: what I’m talking about here is not just mobile apps: we can fire data directly from CRM systems, servers and applications into analytics.
Think beacons, smart fridges, etc – essentially, as long as it has the ability to do POST or GET requests and an internet connection, it can be done. Additionally, you can splice offline outcomes with online dimensions such as: which channel drove the most leads that resulted in the most actual customers.
First, compile your payload data. The payload data is what you want to send into analytics. It looks something like this:
Other parameters to consider:
Note that this example uses Google Tagmanager-style variables in some parameter values – please do not do that. That’s just me denoting which values are dynamically pulled. In reality, the format of all parameters in the request must be on the same line, have no spaces between them, and not include comments eg:
You can send via a HTTP POST or GET method but analytics prefers POST for larger payloads. If you’re sending via a POST request, just remember to:
Remember that you MUST accept Google Analytics’ Use Policy about USERIDs and update your privacy policies. You are not allowed to use PII information.
In the example above for instance, you can apply it to the following scenario for a say, Property Agent website:
Step 1) User logs in to their profile and submits an enquiry on the property website
Step 2) Enquiry is saved in server
Step 3) User then becomes an actual customer
Step 4) Server updates analytics
You can see this data in tabular view in the usual Behavior > Events section in analytics as this payload example is specifically for an event. But I prefer creating a custom dashboard to visualize the data more meaningfully:
Hope that was a useful read! :)
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