How To Conduct a Google Analytics Audit — The Basics
For many Google Analytics (GA) users, the time comes when you need to perform what’s often referred to as a Google Analytics audit. For example, you may need to go into a GA account that is new to you and start poking around to see what’s going on inside. This is common when doing an initial Google Analytics audit for a new client or when working to revive and reinvigorate a dormant GA account — perhaps one that was set up months or even years ago and has been a bit neglected since then.
In this context, the Google Analytics audit is an initial health check on the GA account. Our main focus at this stage is to verify all major settings and make sure the account is ready for further analysis. We can also fix some issues on-the-fly during the audit, and/or flag items for follow-on configuration updates.
The areas below are the first things I look at when performing an initial Google Analytics audit on a new (to me) website. This is not a complete walk-through of the setup process for GA, but rather a first look at the items I typically review to verify basic Google Analytics health and functionality. It sets the stage for more of the actual reporting and analysis work that follows.
For this post, I’m using the free Google Analytics demo account, which includes live data from the Google Merchandise Store.
Let’s begin this basic Google Analytics audit in the Administration section of the GA interface.
This is the upper portion of the Admin interface, which includes the Account – Property – View hierarchy and their various sub-areas.
To get started, I look at the Account Settings and User Management areas under the Account column. Many GA accounts will have ‘outdated’ users listed for access to the account, and now is a great time to clean that up. For example, there may be former employees and/or marketing agency staff listed here, and those can be removed. It’s also a good idea to verify the access levels for those remaining on the account. Options here include Manage Users, Edit, Collaborate, and Read & Analyze.
This is also a good time to check the All Filters area to see if any data filters have been created and applied. More on this later.
This is the full stack of settings in the Property column of the Admin interface.
It’s a good idea to review each of these sub-areas, but for an initial look I start at the top and verify the Property Name and Tracking ID in the Property Settings section, and look for recent activity in the Property Hit Volume area in that section as well.
This snapshot shows that the property (e.g., website) has been sending traffic to GA servers recently, so that’s a great sign that things are working OK on at least some of the site’s pages. It also shows current active users (greater than zero… also a good sign) and provides a feature to send test traffic as well.
The tracking code snippet shows the current ‘Universal Analytics’ code format, which should be present near the top of every tracked web page, typically just before the closing </head> tag. The red arrow shows the ‘analytics.js’ code, which is also an indicator of the latest Universal Analytics code snippet. The older code snippet version used ‘ga.js’ here. All new GA setups will use the analytics.js version by default, while older code snippets should be upgraded to this in order to stay current.
I often use a web browser’s ‘view source’ feature (via mouse right click) to inspect a website’s page to look for placement of the code above.
We can then look further down at the Product Linking area to see if other Google products have been linked to this GA property.
The All Products area will look something like this below.
For businesses that are using Google AdWords for PPC advertising, it’s always a good idea to actively link AdWords to GA for more fully-integrated reporting and insights.
For all websites, I’d recommend establishing a Google Search Console account and linking that to GA. See the bottom of the Property Settings area for that, if needed.
The Audience Definitions, Custom Definitions, and Data Import areas at the bottom of the Property section are more advanced, and may or may not apply to your situation. Check these as needed.
We continue the Google Analytics audit by moving to the right side of the overall Administration section…
Views, Basic Filters, and Goals
This is the full stack of settings in the View part of the Admin interface. There should be multiple views visible via the pull-down tab here — a main view that includes filtered data (e.g., the Master View as named below), an unfiltered view with raw GA data (e.g., the default All Web Site Data), and perhaps other views for testing and/or other specific uses.
The establishment of multiple views is a sign that this GA account has been set up properly, but it’s still worth checking more things here. For initial audit purposes, I usually focus on the upper areas of the full stack bellow.
In the View Settings area, verify the basic config settings near the top and then go ahead and check the ‘Bot Filtering’ option for any views other than the raw/unfiltered one.
Also note here whether an AdWords account has been properly linked, just to verify what we looked at above.
I then like to look at the Filters area to see if proper GA data filters have been established. This is another indicator of the maturity of a GA account. In this case, the Google Merchandise Store analytics team has built a Search and Replace filter and also a Hostname filter.
A Hostname (‘include’) filter is used to make sure that GA hits are collected only from this property, and not from any spammy domains that may have hijacked its GA code snippet. We’ll look for evidence of that a bit further below. For now, it’s good to see that this filter is in place.
Not shown below, but also very common, are IP Filter (‘exclude’) filters to exclude hits from the internal team, marketing agencies, etc., who visit the website frequently. We want to filter out as much of that activity as possible since it will skew the overall data. It’s possible to filter based on IPv4 and/or IPv6 address formats. It may make sense to add exclude filters for both IP address formats in some cases.
The Goals area is another one that indicates whether this GA account is being fully leveraged or not. The fact that we see specific goals established here is a great sign of GA maturity. Of course, we should expect this from a Google-owned property on a demo GA account!
Many typical GA accounts will not have goals established, so this becomes an area for further discussion about what the website owner really wants the site to accomplish for them. The concepts of micro- and macro-conversions come into play here.
In the set we see below, the ‘Entered Checkout’ and ‘Registrations’ goals would be considered micro-conversions, and the ‘Purchase Completed’ goal would be a macro-conversion since this is an ecommerce website and the ultimate goal is to drive revenue directly from the online store. Many different types of goals are available, up to a max of 20 defined goals.
Speaking of ecommerce, here we see the Ecommerce area within the overall View settings.
The Google Merchandise Store analytics team has set up basic Ecommerce tracking and has gone further by setting up Enhanced Ecommerce and defining a typical ‘checkout funnel’ with specific expected steps.
Obviously, all of this applies only to ecommerce websites. Many GA audits will find this area empty, which is fine and expected for non-ecommerce sites (e.g., most B2B websites).
The Calculated Metrics area is still in beta as of this writing, but it’s interesting to see them used below for this site. Many Google Analytics audits will find this area empty, which is not unexpected. It’s a cool feature, though, and will come in handy for many users. At a minimum, it means GA users won’t need to export data to spreadsheets in order to conduct a few simple related calculations.
The items we covered above are what I see as the most important items of the Administration section to verify during an initial audit. Other items may also be important to review right from the start and should be reviewed/adjusted on a case-by-case basis.
Now let’s move into the Reporting interface to check a few more things. This is the upper left part of the main GA interface for this view. It is shown un-collapsed below. Only the icons show when this pane is collapsed to the left. I like to take a quick look at the Real-Time view to verify current GA activity, then check the Audience Overview report and look for ‘Referrer Spam’ issues in the Acquisition section.
Quick Real-Time Tests
This Real-Time snapshot shows lots of current activity on the site. This is another positive sign that the GA code snippet has been deployed properly across the full website and that things are behaving well.
In the snapshot below I’m just quickly looking for ‘normal’ activity on the site and getting a first look at session volumes over time. I’ve looked back for over 1.5 years below and can see that this GA view appears to have started back in ~ July 2015.
I also see five ‘Annotation Bubbles’ sprinkled across the timeline. These text entries are visible via the Annotation pull-down arrow centered underneath the timeline. The presence of these annotations/comments is another good sign that the GA users of this account are actively keeping track of different events that impact GA analysis and interpretation.
The session data, bounce rate, etc., all look fine so there are no immediate concerns here.
Check for Referrer Spam Data
The screenshot below shows the Referral Traffic data for this time period. (Acquisition>>All Traffic>>Referrals in the reporting panel). We’re looking for spammy referral sources that pollute the overall GA data. The good news here is that there’s no evidence of a major spam problem in the top referral sources for this website. These look like legitimate domains that we would expect to see linking over to the Google Merchandise Store.
If we see sources above that include terms such as ‘free-share-buttons’, ‘fix-website-errors’, ‘free-video-tool’, etc., and strange endings for the domain name (after the last ‘dot’), that’s a sure sign we have some referral spam issues to deal with. Spammy referral sources should be filtered out during reporting for historical data. Then, going forward, it’s possible to proactively exclude them from hitting the GA data set altogether so that no (or very little) additional filtering is required.
Check for Hostname Spam
The screenshot below shows the Hostname dimension for all the data in this time period. (Use Audience>>Technology>>Network and set the Primary Dimension to Hostname.) We earlier noted a view filter added to include only GA hits from the correct Hostname structure for this web property. Since that was configured properly, we see only two valid Hostnames in the report below. This is good since it means we are proactively filtering out any spam sources that may be trying to send erroneous hits to GA servers based on our UA- XXXXXXX-XX property identifier.
Check for Custom Reports and Dashboards
Finally, I like to look at the Customization area of GA in the upper left of the reporting panel. This tells me if the other/prior users on this account have set up any custom dashboards, reports, shortcuts, or alerts. Use of these features is another sign of a more robust and mature GA implementation.
The Google Store GA team has set up five useful dashboards that give them at-a-glance insights into how their ecommerce site is performing. I’ve included a screenshot of the upper part of the Audience Snapshot report here as well.
This post highlights some of the basic areas to review when performing an initial Google Analytics audit. This is not an exhaustive check of all GA settings and user-configurable areas, but rather a first look intended to identify any major GA setup issues.
Understanding the basic purpose of the website under review is critical as guidance for these audits. Websites that are highly complex, ecommerce sites, and other considerations may require a deeper dive into other aspects of the Google Analytics configuration settings.
This work also sets the stage for follow-on reporting and analysis activity. Once we’re convinced that the basic GA setup is sound, we can start looking in more detail at the Audience – Acquisition – Behavior – Conversions report areas.
I hope this post helps to demystify the process of performing a Google Analytics audit and inspires readers to do a GA check-up on their own web properties.
Related Google Analytics Audit Tools
Several related tools can assist with Google Analytics audits, implementation, and management. I’ve listed a few below.
Google Tag Assistant — A free Chrome browser extension for verifying GA tags, GTM tags, etc.
Google Analytics Opt-out (browser extension) — A browser extension that prevents the GA code snippet from sending hits to GA servers. Useful for GA users, website developers, and corporate marketers who do not want their own site visits to artificially inflate GA stats for websites they are working with. Also not a bad idea just for general privacy reasons. Available for Chrome, IE 11, Firefox, Safari, and Opera.
Google Analytics URL Builder — A useful (non-Google) Chrome extension for quickly building UTM-tagged links that will show as custom campaigns in GA. Not technically a GA debug tool, but still useful and worth mentioning in this post. Google provides a similar Google Analytics URL builder online resource here.
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