• Joseph Lowe

Performing a Google Analytics Audit for Small Businesses

The year 2020 has been far from normal for anyone with a pulse. The COVID-19 pandemic has affected each of us in different ways – from job losses to wage or budget cuts to the state of our floundering economy. Today, many small businesses around the world find themselves in a precarious situation. For those companies that do not sell essential items, such as boutiques, salons, barbershops, plant shops, shoe stores, department stores and the like, they must figure out contingency plans to stay in business. For some businesses those are loans administered by the Small Business Administration. Others have chosen to offer their services through delivery or shipping. Sadly, several have chosen the difficult option of letting valuable employees go, and unfortunately, for most businesses those losses hit the marketing department or marketing agency.

As small businesses across the globe cut budgets, they will all find themselves trying to better understand marketing insights and set up head-turning advertising campaigns with little insight into how they’re campaigns performed in the first place. This post aims to clear the air and lend a hand to the businesses trying to search through their Analytics account for valuable insights and understand how they’re account is set up. We’re going to learn how to begin a Google Analytics audit with some incredible tips and suggestions from Fred Pike, the Managing Director & CFO of Northwoods Digital Solutions. So let’s get started!

In our last post on event goals, I asked for readers to check out a few Chrome extensions that we’ll detail in this piece. For small businesses who might be in the transition process from agency to agency or perhaps just haven’t been given full transparency into how your Google Analytics account has been run, these four plugins will allow you to explore your site, what’s being measured and find areas to improve upon.

Google Tag Assistant

  • Google Tag Assistant allows you to record a full session on any site and gain insights into things like Analytics, Google Tag Manager or Google Ads account numbers and whether or not those tags are firing or configured correctly.

Adswerve dataLayer Inspector

  • Adserve dataLayer Inspector allows you to open up your Google Developer Tools and quickly view data across your site in real-time. For example, perhaps you’re curious if your agency set up events for certain merchandise on your e-commerce site. If you open up Adswerve, when you click through a few product pages you should see a GA event fire when you visit the correct pages. In addition, it gives access to hit information as it’s sent to Google Analytics (information such as GCLID and whether it’s an enhanced ecommerce account or not)

GTM GA Debug

  • GTM/GA Debug is very similar to Adswerve dataLayer Inspector and offers the exact same information. The big difference is simply how the data is displayed. The interface (in my opinion) is a little more user friendly and easier to sparse through.

Google Analytics Debugger

  • Google Analytics Debugger offers the same insight as GTM/GA Debug and Adswerve

All of these Google Chrome extensions are free to download and serve as a good starting point for your Google Analytics audit – especially if you don’t have access to the Google Analytics account. Now let’s get started with the actual auditing process.

Starting with the Basics

Where is the data coming from?

So where do we start? The best place to begin is figuring out how the data in Google Analytics (GA) is getting to the GA account in the first place. This will also allow you to figure out all the tagging systems associated with your website. There are a few different ways the data reaches Google Analytics including: Classic GA (which I’ve personally never seen in an account before), a Universal GA Tag, a Global Javascript Tag, or via Google Tag Manager. Let’s look at an example with and Google Tag Assistant.

In the example above, we see that Nike is using Global Site tag to relay information back to Google Analytics – great. But what else do we see here? It appears that there are multiple installations of Global Site tag on their website, and if you were to scroll down you would see multiple iterations of Google Ads conversion tracking as well. All in all, if the agency or internal marketing team has a special setup in place that accounts for the multiple tagging accounts associated with the website, then it could be completely okay. However, in several cases, it simply means that the previous developer or marketing strategist didn’t want to clean up the mess of code before and left it there along with the new Global Site tag. In this example, if Nike were a small business, it would be important to check data in Google Analytics to see if everything lined up in the raw view. But what if you didn’t have a raw view?

What views do we have?

Once access to the Google Analytics account is granted, the next big step is understanding what views are available in the account and hoping there isn’t just one view called “All Website Data”. All Analytics accounts should have at least three views: a testing view, a raw data view and a master view. With no raw view, there will be no way to compare data over time to ensure something is not broken within the account. Without a testing view, there is no way for marketing strategists to test new filters before implementing them in the master view. The only way to obtain that information is with account administrative access or at the very least full property administrative access to your account. If you don’t, ask your agency for it – now.

Are those pageviews real?

What do you think is the most talked about vanity metric in digital marketing? If you guessed pageviews, then you’re correct! Now don’t get me wrong, pageviews are incredibly important in the grand scheme of things. I mean how will your site thrive if users aren’t there to view the content? But in my opinion the bigger question is how engaged are the visitors when they get there and do they commit events or goals? I digress.

GA users must know what pages are gaining the most pageviews to better understand what pages gain the most engagement, but it’s not all that uncommon to be missing pageviews from your Google Analytics account in the first place. Let’s look at another example,

We see here that Guitar Center has their Google Analytics property set up correctly in that it’s recording pageviews (in the highlighted section above) after checking Adswerve. Great! The problem occurs when that highlighted section doesn’t show or shows twice. Undercounting due to incorrectly created filters and overcounting due to Global Tag Manager code and Google Analytics Universal code both being added to a site is more common than you think, and that misstep can truly impact your bounce rate, pageview metrics and more.

Speaking of incorrect filters, it might be a smart move to audit your account for rogue filters or the opportunity to add these new filters for better reporting.

What filters should my Google Analytics account have?

IP Address Filters

How often do you visit your website? I know I do pretty often, and there’s no problem with that unless it’s showing up in your GA data. For most small businesses, the amount of times they visit their website isn’t going to make or break their reporting. But it can be a nuisance for small businesses that are growing or large corporations. Imagine how often Nike employees check out the site while at work. Let’s say 3000 times in total a day? So you’re looking at your metrics and the pageviews are skewed by 3000+? You can’t have that. IP address filters block out one or multiple IP addresses from reporting in your Google Analytics account.

Hostname Filters

In most cases, the traffic to your site will be legitimate, however there are cases in which spam traffic can be sent to your website. Fred Pike mentioned an excellent example during his course in which one of his clients received bot traffic to a page that wasn’t even on their site. The bounce rate was nearly 99% and it effectively hurt the accuracy of their metrics. So how do you stop spam? The hostname filter. The hostname filter configures your view so that it only captures data related to the specific domain you’re tracking. Essentially, as opposed to tracking /contact-us on, our hostname filter only tracks which ensures that no spam is being inserted into the data.

Query Parameter Filters

Query Parameters are simply URLs with information after the question mark in the URL. The problem with query parameters is that the data is often fractured in Google Analytics. For example, might get 100 pageviews per month while might get 10 views per month and receives 15 views per month. We’re missing 20% of our traffic just because the data is fractured. Query parameter filters allow you to build a filter to exclude certain query parameters that are nonmeaningful to you, therefore binding the data back together.

Default Channel Groupings

I believe it’s safe to say GA users often hope for the best when it comes to channel grouping. Of course, you can use UTM codes to ensure certain links report to the correct channel grouping of direct, organic search, social, email, referral, paid search or display. However, it’s a little known fact that if the default channel groupings do not match the exact definitions of the grouping that the traffic will automatically go to direct or other, which can really skew your reporting.

For example, how accurate is your email channel reporting? In Pike’s course, he goes into detail on the fact that a lot of email reporting is incorrect. For the email channel to report correctly the source medium must exactly match “email”. It won’t match “Email” or “eMail” or “e-mail” or “EMAIL”. Furthermore, several email providers will not automatically UTM their links. What that means is for email, most businesses must manually provide UTM codes on their links to successfully track it, which can be difficult across large teams who occasionally misspell or over capitalize things. As mentioned in previous posts, this is where things like a lowercase filter come into play and really help you sort through the mess.

Still confused on how to audit your Analytics account? What weird filters do you have in your account? We’d love to hear how you’re optimizing your Analytics account to better suit your business. Next week will take a deeper look into goal and event audits as well as how to optimize those conversions. Thanks for reading and I look forward to sharing more insights next week!

This post was created in an effort to complete my CXL Institute Mindegree Scholarship obligation and speak to the materials reviewed in the course. The information is a combination of my previous knowledge and excellent insights from a phenomenal program.

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