Report that saves your marketing team 40 hours every month
One of the central values of high-level analytics is to see the general situation with marketing in one report.
We use DWH based on Google BigQuery, which helps to make good reports with its logic. These reports allow our clients to get various answers quickly and safely, including concerning marketing costs.
If the company has several websites, mobile applications, and different traffic sources, such as Google ADS, Facebook ADS, Twitter ADS, LinkedIn ADS, and others, it isn’t easy to see marketing cost efficiency in one place.
Usually for this
- Use simple tools such as Google Analytics that don’t allow you to combine different data sources correctly;
- Look at separate insight account for each source;
- Combine all data on Google Sheets.
Regarding Google Analytics, it is a good tool. Still, it has its calculation logic, and it is not possible to calculate your metrics, especially if it is metrics from other data sources (such as an internal database).
For example, here is such a case: on a particular day, there was a fact of registration of the user, after which they made a few more important actions, but when it happened, it was not important for the business. Therefore, in one report, we can show the situation with the actions today and those that will occur in the future, with a binding to the registration date.
In addition, combining different data, such as costs, in Google Analytics is often done with simple keys, only by the name of campaigns, source, and date. But in general, if the structure of our advertising campaigns includes country, device, and language, then it is possible to use these parameters as a filter.
Firstly, working with Google Sheets is uncomfortable. It takes a lot of time to correctly collect all the data from various sources. As a result, often, this report compiles only once a month, making it impossible to decide quickly on changes in advertising campaigns. Also, there is no way to drill down this report. Usually, it is the level of ad sources or campaigns, not ad groups or ads.
Now, the capabilities of Google Data Studio allow you to drill down different levels in a table:
Using the down/up arrows, we can look at different parameters.
Comparison of different periods on Google Data Studio
If you expand the functionality of Google Data Studio a little, you can get opportunities in the displayed data. For example, you can compare different periods. If you need to compare some metrics with the previous period or the last year, you can do it (by simply switching the green switch).
Calculated metrics on GDS
Usually, in ready-made analytics systems, indicators are calculated from some metric, for example, sessions or users. That is, you can see what percentage of users took helpful action. But often, you also need to see the percentages between different activities.
You can do this simply on Data Studio:
Data from the backend to GDS
For the correct calculation of marketing effectiveness, it is often necessary to take data from internal systems, such as a database or CRM. It cannot be easy to load this data into Google Analytics correctly, and in many cases, it is not possible.
For example, there is a situation where there can be many users under one google client ID (user_id) or vice versa. One user has multiple devices at once (home computer, work computer, tablet, phone). In such a case, it is impossible to see correct statistics in conditional Google Analytics.
There is a big question about where and how such data is stored and who has access to it. In cases with Google BigQuery, you can only provide access to the data necessary for a specific user’s work.
We do all complex data calculations in DBT, which connect to the Source Repository, which helps to use logic to calculate metrics and control the process of changes.
Four tips on how to make your GDS reports faster and easier to use
- The reports generate in 1–2 seconds, even with large volumes of data.
Using DBT helps not only to perform complex calculations but also to create optimized tables that work quickly with Data Studio.
- You can use filtering directly in the data.
This is a great opportunity when the tables you work with are filters. That is, by clicking on a variable, the entire report displays data only on it. It helps a lot in data analysis.
- Show any deviations on small charts.
For essential metrics, we also create small graphs showing this metric’s trend, so you can immediately see if something is wrong.
- Charts, funnels, and tables at once
It’s convenient when there are both tables with data and graphs showing how the situation changes over time on one report sheet.
