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Working with Non-Aggregatable (Non-Agg) Metrics in Funnel
Working with Non-Aggregatable (Non-Agg) Metrics in Funnel

Create Monthly and Weekly Facebook Reach in Funnel

Daniel Norén avatar
Written by Daniel Norén
Updated over 5 months ago



Intro

This article aims to explain how you can work with non-agg metrics in Funnel and visualize them in e.g. Google Data Studio. Before implementing and visualizing non-agg metrics you need to understand two concepts.

When setting up the connectors of non-agg metrics in Funnel, you need to make a choice on the time window. This choice will have an impact on how the data is shown. E.g. when you choose Calendar month, then data of a whole calendar month are aggregated.

Working with time windows and non-agg metrics

Start by thinking about the widgets that you like to show your audience. Two common use-cases of customers are, for example, reporting on both Facebook Reach broken down month by month and week by week. The same way of working with a non-agg metric such as Facebook Reach can be applied for other non-agg metrics in other sources such as X Ads, Google Analytics, etc.

After deciding how you would like to report on your non-agg metric, it is time to connect the data sources to Funnel with the breakdown needed to build your widgets.

There are two separate data sources from the Facebook connector needed for the two use-cases presented above, one connected with time window calendar month and the other with 7-days.

When viewing non-agg metrics it is also important to connect the data source to the “correct” level. The data needs to be viewed on the level the data source is connected on. Since our goal is to view data month by month, we will choose Account level. If we choose Campaign level we would need to view the data on a Campaign breakdown. As the name suggests, it is not possible to aggregate the data and connect it on the Campaign level and look at it on the Account level.

1. Connect your non-agg data sources with the desired time window and report level

Funnel will start downloading the data based on the breakdown and time-window selected in the configuration step. You can move on to the next step once the data has been downloaded and available in Funnel.

Please be advised that the data sources should be connected to the level you are planning on reporting. Adding optional dimensions in the data source means that they need to be used when viewing the data.

Connect Calendar month

Connect 7 days

2. Build Monthly/Weekly Reach metrics

In this step, we are going to create monthly and weekly reach metrics that can be used to report on.

Monthly Reach

Facebook is connected on Account level with a Calendar-month time window in the example above. That makes it possible to create a metric that returns a Monthly Reach by only using values from Reach when the date is the end of the month. By including a condition for today in the rule is it possible to also make the rule work for the ongoing current month.

Weekly Reach

In the Weekly Reach example is the condition on the “last day of the week” instead of "last day of month". The last day of the week in Funnel depends on your Funnel Workspace setting. You can find the setting under About in the “Manage Workspace” section

3. View in Data Explorer

Both Monthly and Weekly Reach can be viewed in Data Explorer with either Month or Week to see the respective value for the period.

Weekly reach is shown per week

4. Connect the data to Google Data Studio

Create a new view in Funnel in the section Data Studio and add the fields needed to visualize the data.

This article describes in more detail how to work with Data Studio views in Funnel.

Here is the result of how Monthly Reach from Facebook is visualized in Data Studio. However, Monthly and Weekly Reach are still non-agg metrics and needs to remembered when visualizing the data

Understand time windows

Funnel downloads aggregatable data (such as cost, clicks & impressions) with a daily granularity, and they can be summarized by week, month, year etc. Non-agg metrics however typically involve starting by selecting a time window. What time window selection you make will impact what value is displayed on a given day for the metric. This means that when looking at the output in a table or a graph, for each day the metric will represent the total metric value for the last x days. The option Calendar Month has slightly different behavior and the metric for each day represents the total value from the first of the month to date x in the month.

Example of a Source connected with Calendar Month

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