The flow view of this template
Transformations:
Set, rename, filter rows, round, counta, ceiling, sum, pivot
This template shows how to extract advanced reports from google analytics objects like Sitecontent, Sitesearch, Sitespeed and Traffic data from a typical google analytics database.
The flow comes with detailed annotation of each dataset. Once you understand the sql logic, you can customize this flow to jumpstart your own development or share it with others in your workspace.
The flow comprises of standard datasets like sitecontent, sitesearch, sitespeed, traffic and useractivity data. Each dataset is a report ranging from StartDate to EndDate.
Site content report allows you to analyze key metrics like page views, time on page, entrance, exit, bounce and exit rate etc.
Traffic report allows you to see which posts drive the most traffic (users/new users/sessions) and how that traffic behaves (bounce rate/pages per session/average session duration). You can also analyze the traffic and user acquisition behaviour based on organic channels and paid channels.
Site search report shows how frequently people used site search for keywords and time period specified. It also shows how audience interact with content after a search.
Site speed report shows website performance in devices and determines which browsers your customers often use to browse your website.
This template is a pre-packaged, customisable and modular flow that leverage industry standard practices to report and analyze google analytics data.
The input datasets are dummy datasets that need to be replaced by your google analytics data. You can utilize this document to create your connection to google analytics.
The flow canvas also has detailed instructions of how to replace the dummy datasets(csv) with a SQL data from your google analytics datasource. You don’t have to create the SQL from scratch but simply copy the SQL corresponding to each dataset from the flow note and paste the SQL in “Create dataset with SQL” from the import page.
Once you have replaced the input datasets, follow the instructions to create output and run job.