I thought about what I liked most about Google Analytics – what made digital analysis and optimization easier and more insightful.  Here are my top fifteen favorite Google Analytics features, in alphabetical order.


Google Analytics allows a user to record an event in the website timeline.  This feature allows a user to record the date and comment on what has changed or updated on the website that may affect the website metics and may be hard to understand without the annotation.  This could be a change to a running campaign, an issue with the tracking code, or content changes.  This really helps when you find outliers in the data – check the annotations and see if anything comes up for the given time period.


Google Analytics isn’t the only digital analytics tool with an API, but it is an important feature to me.  Much of the work I do is outside the GA interface.  I use R to graph and do more advanced data analysis, and having the API makes this a lot easier to accomplish.

Asynchronous Data Capture

Back in 2009, GA launched a new tracking code snippet.  This was a very different type of tracking code.  Prior to this release, tracking code was always placed at the bottom of the webpage.  That was because analytics tools should not get in the way of the user experience.  If the tracking code was at the top of the page, it would fire first, delaying the page from loading and decreasing the user experience.

This new tracking code was asynchronous.  That meant that it did not have to fire immediately when the page loaded.  The beauty of this was that the tracking code could now be placed at the top of the webpage, with no degradation of the user experience.  Additionally and importantly, this feature allowed more webpage visits to be captured and the page loading time increased.

Attribution Modeling

Most digital analytics tools capture the last website, email or campaign that a visitor came from before a conversion.  When analyzing which website, email, or campaign (channels) to give credit for (attribute) the conversion, most of the time it is attributed to the last click – last-click attribution.  However, for a while now Google Analytics has added features to analyze a visitor’s multiple visits before a conversion.  The process of crediting the channels for their attribution to the conversion is called multi-channel attribution.  More recently, a tool that was only available of Google Analytics 360 has been made available to the free version as well – the Attribution Modeling Tool.  This allows analysts to model different attributions to the channels involved in conversions.  Instead of last-click attribution, an analyst can model first-click or time-decay attribution, if they think that more accurately reflects the actual value of each channel for their website.  Additionally, there is the option to customize attribution and new data-driven models have been in development.

What is great about this feature is that it allows an analyst to understand what is really driving revenue.  That can be compared to the cost of each channel to optimize spend.

Calculated Metrics

Calculated metrics are just what they sound like – metrics that can be created by the user.  For example, I liked the old ROI, but it was removed.  No problem – I recreated it using the calculated metric feature.  I also wanted to see conversion based on visitor instead of session.  These new metrics will appear in the custom report drop-down menu.

Cohort Analysis

A cohort is a group of visitor that have shared an event at the same time.  For example, visited the website or purchased a product.  The reason to analyze them is to see differences and similarities between them.  Additionally, they can be segmented to further analyze their behavior.  The greatest thing about this feature is that it is pan-session (more than one visit), so we can get past the single visit metrics.

Custom Dashboards

Custom dashboards is a feature where a user can create a collection of reports, pick custom dashboards from the Google Analytics Solutions Gallery, or create their own.  The real power to be with custom dashboards is that they can be emailed to team members or clients.  You can have different dashboards – one for social media and another for media, for example.

Custom Dimensions

Custom dimensions is a feature that allows data to be imported into Google Analytics that is not natively available.  For example, if you know the age range of a visitor and want to capture that data in Google Analytics, that can be done through a custom dimension.

Custom Metrics

Custom metrics are the partner data of custom dimensions.  Whereas a custom dimension is discrete and makes sense to segment, a custom metric is continuous and makes sense to add up.  For example, capturing the phone call click on a mobile website would make sense as a custom metric.  You would want to know how many clicks.

Custom Reports

Custom reports are awesome!  I rarely look at canned reports because there are specific data I want to analyze (not to mention custom dimensions, custom metrics and calculated metrics that I want incorporated into my reports.  Custom reports are the only way to see this data inside of Google Analytics.  Also, you can add the metrics & dimensions from the standard reports that you want, leaving off the ones that you don’t want.  Lastly, you can add these to a dashboard or schedule in an automated email.

Event Tagging

Before event tagging, all events on a page would have to be captured as a page view.  We call it a fake page view – because it’s actually an event.  Event tagging is a feature that allows a more nuanced approach to capturing interaction data.  For example, capturing the playing, pausing, and time watching a video on a site is fairly straightforward with event tagging, but would be rather cumbersome to do using fake page views.

External Data Import

This is an exciting feature.  One of the key things I use this for is to import Bing PPC cost data into Google Analytics so I can compare CTR, cost, revenue and ROI with other media sources.  But it can be used for other data sources, like off-line advertising, so that the data can be married up to online data.  This is a wonderful way to get external data into Google Analytics.

Property Filters

Property filters is a feature that allows a Google Analytics view, property, or account to filter or change data before it is inserted into Google Analytics.  For example, some URLs may have both lower and upper case, when they go to the same destination.  A filter can make all URLs either all upper or all lower case, so in Google Analytics, only one URI will be visible, instead of two or more.  Also, this can be used to filter out visits from spammers or in-house visitors that you don’t want to capture data from (since they’re coming from inside your organization).

Report Segmentation

I use this feature All.The.Time!  It is the best way to slice and dice through the data to quickly find insights.  I have dozens of segments, and Google Analytics has evolved it to be even more robust with additional segmenting options like cohorts and sequences.  This feature alone makes Google Analytics enormously powerful.

Scheduled Emails

When people want reports on a regular basis, don’t be a reporting monkey – use the this feature to schedule the reports to go out on an automated basis.  You can even set up a dashboard for multiple reports and schedule it to be sent out automatically.

Web Property Rollup

Lastly, there is web property rollup feature.  Unfortunately, this is only available to Google Analytics 360 subscribers (hopefully it will come to the free version – I do have some need of roll up capability).  This feature allows a user to roll up multiple properties into a new, single property.  This can be really helpful if there are a couple different sites or if the mobile site is separate from the desktop site and there is a need to see the metrics merged together.


These are my fifteen favorite features that make Google Analytics an outstanding digital analytics tool.  If you are wondering what the difference is between Google Analytics and other tools, check this list and find out if your tool is missing any of these features.  If it is missing some of these, you will probably miss them.

Last modified: January 13, 2021