A Google Analytics Spring Cleaning Checklist

Published May 2, 2016
When spring comes around, you probably take some time to clean out your garage, sweep out the leaves, and take down the cobwebs. As a digital marketer, spring is also a perfect time to dive into your Google Analytics account to do a little cleaning up there.
No matter how carefully you’ve set up the account, data tracking errors can creep in, and with a little tidying up, you can position yourself to measure your results more accurately. Let’s dive into a few items you can check within your Analytics account right now.


Google Analytics Spring Cleaning


Look at Notifications

To start, look for any notifications you may be receiving via the top right “bell” symbol. These frequently highlight problems or opportunities to improve your account. While some may be false flags or not applicable to your situation, often you’ll encounter warnings for errors you didn’t know existed.


Google Analytics Notifications


For any of the Google notifications we don’t get into here today, see our article on resolving common Google Analytics notifications.

Filter Internal IP Addresses

Double-check that you’re excluding IP addresses for yourself and anyone else involved with maintaining a site. You don’t want to skew data by visiting the same page 20 times in a day while editing the copy.

For a detailed explanation of how to filter out one or more IP addresses from your account, see “Filter Your Internal Traffic” in this article on using Google Analytics filters.

Even if you’ve already set up IP filtering, IP addresses can change periodically, such as when an office switches to a new internet provider. Check with your team to make sure everybody’s IP is excluded from the Google Analytics view, including any employees who may work remotely.

Watch for Messy URLs

Just like cobwebs can hide in dark corners of your garage, messy URLs can hide throughout your account, skewing the data you’re able to measure about website performance. If a user can access the same page via multiple URL variations, you’ll see data for that page split across those URLs in Analytics.


Messy URLs


In this example, arrows point to four different variations of this site’s homepage URL. Users can access the same page at:

  • /
  • /Default.asp
  • /default.asp
  • /Default.asp?src=acic

Now, in order to see an accurate total for homepage pageviews, we have to add together pageviews for these four URLs and more that appear elsewhere in the report. That may seem like easy math, but in order to measure an accurate average time on page, we need to take the average of the data from all of the URLs, doing the same for all of the other metrics. You can see how aggregating data across URLs quickly becomes unwieldy.

You’ll want to ensure that visitors can only access any particular page at one URL, so, for example, typing in would 301 redirect to Also, you should only allow users to go directly to using internal links.

Finally, make sure that you understand the proper use of campaign tagging in Google Analytics. You’ll want to use tags that are recognized by Google Analytics and won’t appear tacked onto the end of the URL in reports.

Look for Spam Traffic

Like spiders making nests in the corners of your garage, spam referrals relentlessly find their way into Google Analytics. These come either from ghost referrals, in which a hit is registered to your Google Analytics account but nobody reaches your site, or from bot referrals, in which a bot creates an automated visit to your site.

For example, see the referrals highlighted in this screenshot. One of the most telling signs of their inauthenticity is the fact that they share the suspicious characteristics of all visits having 1 page per session, a 100% Bounce Rate, and an Avg. Session Duration of zero.


Spam Referrrals


While Google appears to be deploying a fix to the problem, we’re still seeing some spam traffic slip through. To eliminate these fake sessions from your data, see our tips for getting rid of Google Analytics spam.

Check Conversion Tracking

Google Analytics Goals allow you to track how well your site is generating leads or sales. However, inaccurate goal tracking can be just as dangerous as no goal tracking. “Thank You” pages may change, forms may break, or goals may be inaccurately setup in the first place. Too often, these faults deter organizations from tracking the most important metrics to their online success.

If you are tracking form submissions as a Goal, double-check that the data you see in Analytics matches up with outside data. Does the number of submissions correlate with the number of leads you received via email or into your CRM over the same timeframe?

While numbers won’t always match up perfectly due to factors such as the occasional user blocking JavaScript, you shouldn’t see major discrepancies. If the numbers are off, double-check that your Goal is still accurately setup to monitor the form submissions. Submit the form yourself and check that the “Thank You” URL is the same or that the event code to track a submission is still firing. Also, double-check that the Google Analytics code is indeed in place on both the form page and the “Thank You” page.

While unfortunately you can’t retroactively correct faulty data, you should make a note of when conversion tracking was not working properly and how much the numbers were off. That way, when you’re comparing future performance to historical data, you’re not measuring against inaccurate figures.

Check AdWords Linking

If you’re running AdWords campaigns, you should ensure that your AdWords account is properly linked to Google Analytics and that data is showing up in the proper place. You should see data under Acquisition > AdWords > Campaigns that matches up with what you see within your AdWords account.

If your AdWords campaigns aren’t showing up here, not only are you not tracking paid search data properly in Analytics, but the clicks may be appearing as organic Sessions, skewing the overall accuracy of your search data. You’ll want to select your desired Property under the Admin section of Analytics and check AdWords Linking to ensure the setup is valid.


image showing linked adwords and google analytics accounts



Having a Google Analytics account in place is an excellent first step for any marketer, but occasionally it’s in your best interest to do a little regular maintenance to ensure you’re looking at accurate data. Our guide will give you a good starting point for getting better data tracking in place for your organization.

Go ahead and work through this checklist in your own Google Analytics account. Make sure that you are filtering out unnecessary data and properly tracking the metrics that matter to your business.


When the client first came to you, you talked up the value of Google Analytics. You emphasized the importance of seeing where your traffic was coming from. You went on and on about how Google Analytics can show traffic sources to pinpoint whether people came from search, social media or a specific site referral, and how valuable this data was. You sold them on it, so much so that your client looked forward to receiving that first report, the magical day when they would finally understand where visitors were coming from.
But then the report came, and it looked like this:



It showed that 10% of your client’s traffic came from “(direct)/(none)”. What does this label mean? How do you explain Direct traffic to your client? Better yet, how do you explain “none”?
Let’s take a closer look at understanding Direct traffic in Google Analytics and how we can address it with clients.
Digital marketers spend a lot of time focused on PPC and SEO campaigns in order to drive desirable traffic to a website. The phrases we’re ranking for and bidding on get meticulous attention, so much so that we often forget about some of the other ways that visitors find us.

We put a tremendous amount of the effort we put into reviewing organic search data and PPC campaign performance in analytics. But how closely do we monitor referral reports?

If that’s not a channel you review regularly, you may be missing out on seeing traffic that is coming directly from links you’ve obtained around the web, local business listings, news mentions, and more. Many times, links are only considered as a means to an end, a metric that Google uses in determining how to rank sites in the SERPs (search engine results pages). But the fact is, many of a site’s links may be directly contributing to its traffic.

In this article, we’ll review how to look at referral reports in Google Analytics, and some of the many ways to use that data to better inform your web marketing decisions.


Remember how your mom told you not to stand too close to the television because it might hurt your eyes?

The same rules can apply to data. If you’re too close, you may miss the patterns and trends that are crucial to understanding your website’s performance. You can’t judge a site’s performance looking at data in the bubble of a single day, you must consider any day’s traffic compared to the days before and after.

Google Analytics makes it fairly easy to analyze trends over long periods of time. But it also allows you to stand right in front of that TV, to look at more granular levels of time, right down to the hour.
There’s a better way to get that close to the data, without burning your retinas. We’ll cover how to analyze traffic effectively in today’s post.