April 9, 2020
Transforming data using configuration rules (5:12)

Transforming data using configuration rules (5:12)


In Google Analytics, you can setup data configuration
rules that determine how your data will be processed. This includes implementing features like data filters, goals, data grouping, Custom Dimensions, Custom Metrics, and imported data
that can help you better define and analyze the data in your reports. As we discussed in Google Analytics for Beginners,
you can set a filter on a view that can exclude particular data, only include particular data,
or modify the data during processing. This helps you align the data that shows up in
your reports with your business needs. Filters are essentially “rules” that Google Analytics
applies to the data during processing. If the “filter type” is true, Google Analytics
will apply the filter to the data. If the filter type is false, Google Analytics won’t
apply the filter. There are two reasons you might want to apply
filters. You may need to transform the data that shows up in a view. For example, you
might want to include only data from a particular country in a view devoted to reporting on
that country. Or you might want to exclude any internal employee traffic from a view
reporting on customer data. The filters you choose to implement will depend
on your specific measurement objectives, so it’s important to plan what data you want
to collect before you set up your filters. We’ll discuss filters in more detail a little
later. There are four types of Goals in Google Analytics. Destination (or Pageview) Goals are based
on when a user views a particular page on your website. 
Event Goals are when a particular action defined as an event is triggered.
These are the two most common types of Goals, but you can also set up additional goals to
measure user engagement: Duration Goals are based on sessions that
last over a set amount of time. “Pages or Screens per Session” Goals are
based on whether a user has viewed a set amount of pages in a session.
A conversion is counted once per session per configured goal. So if you’ve defined an
Event goal of downloading a PDF, and the user downloads the PDF five times in the same session, this action will only count as one conversion. During processing, when Analytics detects
hit data for a goal, it calculates the goal completions, goal value (if you’ve indicated
one), and goal conversion rate, and includes these in your reports. Note that in Google Analytics, conversions
and Ecommerce transactions are credited to the last campaign, search, or ad that referred
the user. You may want to organize the data you collect
in different ways than the standard Google Analytics reports. Channel Groupings let you
organize your data into customized channels, while Content Grouping lets you aggregate metrics
within reports based on the organization of your website. You learned about dimensions and metrics in
Google Analytics for Beginners. But you also can create your own dimensions and metrics
in Analytics called “Custom Dimensions” and “Custom Metrics.” Custom Dimensions
help you define a group of metric data that’s specific to your business and then apply that
as a dimension across your reports. Custom Dimensions can be used as a secondary
dimension in standard reports, a primary dimension in a Custom Report, or as a segment. We’ll
discuss Custom Reports and segments later in the course. 
“Custom Metrics” can be collected for any standard dimension or Custom Dimension
that can’t be measured by any predefined metric in Google Analytics. 
You can also upload your own data to Google Analytics including hit data, extended data
that is stored in a Custom Dimension or Custom Metric, and Summary data that lets you sum
up any uploaded metrics. Typically, this information is exported from an offline business tool
like a content management system or customer relationship management system into text files. Data Import lets you combine this offline
data to the hit data that Analytics collects from your website. This will allow you to
include your own business-specific data you collected independently to give you more context
and insight in your reports. These are only a few of the features you can
configure to help customize the data you collect for your business. Note that you’ll need
to set up these data configuration rules prior to your data being processed.
Once data has been processed, you can’t retroactively apply configuration settings
to that data. We’ll discuss how to set up these configurations and use them for analysis
a little later in the course.

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