In the previous article we talked about how to build reports in the online reporting interface.
Well, Google Analytics also allows us to create reports and dashboards through its APIs (Application Programming Interface) reports through which we will be able to automate complex tasks.
Currently, there are five reporting APIs:
- Central reporting API. This allows us to create customised reports by consulting dimensions and metrics.
- Multi-channel funnel API. which accesses users' attribution and conversion path data.
- Real-time reporting API. That accesses activity occurring on a website or application in real time.
- Embed API. It allows you to insert panels into a third-party website in a simple way.
- Metadata API. That accesses the list of dimensions, metrics and attributes of the API.
Using reporting APIs, it is possible to integrate GA data with business data and generate customised dashboards showing information from different sources. To do this, it is necessary to create your own application or acquire some of those available on the market, such as Supermetrics Functionsor dashboard tools such as DataStudio, Chartio, Welovroi...

Whether it is your own application or a third party application, it must be able to write and send requests to the Google Analytics reporting API, which will interpret this request and get the data from the tables to send a response to the application with the requested data.
Each request sent to the API must contain specific information, such as the ID of the view from which the data will be requested, a start and end date for the report, and the dimensions and metrics to be retrieved. Within this request you can filter, segment and sort the data you wish to obtain, in the same way as in the Google Analytics online interface.
To understand it better, let's put an example. Let's imagine that the data obtained from the API is a table with a header and a list of rows, the header will indicate the name and data type of each column (dimensions and / or metrics) while each row will include the values of the dimensions and metrics (the headers) requested in the query. From there how they are presented depends on the programming of the application we are handling.

In short, either because we create an application to obtain information via the Analytics reporting API, for which we will have to know programming or have a programmer nearby, with access to reporting APIs we can automate and simplify complex tasks when generating reports that help us to better understand user behavior.
I invite you to leave your impressions and/or doubts in the contact form and to suggest new topics that you would like me to cover in these tutorials. I will be happy to answer you by email and write in this blog.