Google Analytics is the most popular analytics platform today. It is used on all types of websites, from simple WordPress blogs to Shopify e-commerce sites to complex one-page applications. It’s powerful, flexible and, perhaps most importantly, free.

What’s more, getting started with Google Analytics is as easy as installing a little JavaScript snippet on your site.

However, simply installing the default JavaScript snippet won’t provide you with the clean, accurate data you need to get real insights from analytics. It requires a few additional steps, which we’ll cover in this Google Analytics Checklist.

Once you complete this Google Analytics Checklist, you’ll have a basic Google Analytics setup that provides accurate and clean data to determine where your traffic is coming from and what content people are viewing on your site.

While you’ll still need to create goals and actions specific to your site, you can do so with the confidence that you’re building on a solid foundation.

IMPORTANT TO NOTE:

• One of the drawbacks of Google Analytics is that you can’t overwrite historical data. In other words, any changes you make will only apply to the data in the future. This means that it’s best to run this Google Analytics Checklist as soon as possible, ideally before you launch your site.
• While this Google Analytics Checklist serves as the basis for all Google Analytics implementations, it does not cover more complex topics such as e-commerce sites, single-page applications or cross-domain data tracking.
• Google Analytics collects data on visits to your site, but it does not aggregate data on ad spend, campaign performance or revenue. However, you can use a tool like Improvado to collect this data and send it to your visualization tool.
• If you’re new to Google Analytics, we also recommend reading an introduction to Google Analytics before jumping into this Google Analytics Checklist

Google Analytics Checklist of the Best Practices

Google Analytics best practices include two phases:

Phase 1: Proper Visitor Tracking. This includes properly tracking page views, eliminating internal traffic and spam, and accurately tracking page information. These steps are absolutely necessary to ensure clean analytics data.

Phase 2: Track attribution information. Attribution is probably the most important part of Google Analytics. It tells you where your traffic is coming from – organic Google search, paid Google search, paid Facebook ads, etc. Most attribution problems are fixed with the two steps we’ll look at in this article.

Proper Visitor Tracking

The following steps are absolutely essential to keeping your analytics data clean – properly tracking page views, eliminating internal traffic and spam, and accurately tracking page information.

Create multiple views

By default, the Google Analytics property contains only one view, which is called “All Site Data.” Different views may have different filters, goals, etc., but they track the same property. Before you do anything else, we recommend creating at least the following three views:

1.Master View – This view will be the default for almost everyone in your organization. To set it up, change the name of the All Site Data view to Master and check Bot Filtering.

2.Test View – If you need to change something in the future, whether it’s a filter or a target, you may want to test it before making changes to the main view. To do that, use this view. To create it, just copy the Master view we just created:

3.Unfiltered View – Filters (more below) are destructive in Google Analytics. So it’s always a good idea to have a backup view without any filters in case one of them destroys the data you really need. To create one, simply click the Create View button:

Note: When you create goals, it’s best to apply them to all of your views. To do this, select Share Assets in the Administrator section of the view in which you created the goal.

Make sure you’re tracking pageviews accurately

Pageviews are a really fundamental metric in Google Analytics, so we want to make sure we’re tracking them correctly. Luckily, this is easy to do with a quick check of the real-time report in Google Analytics.

1.Add a source and medium UTM parameter called “test” to your site URL using Google Campaign URL Builder and copy it

2.Paste the URL into your browser, go to the “Traffic Source” section of the Real Time report and click “Page Views (last 30 minutes)”.

3.You should only see one pageview for the Medium and Source test. If you see more than one, repeat the steps with Medium=test2. If you still see more than one pageview, it is likely that there is double-counting of pageviews somewhere. This will require some tweaking, but you can start by checking whether you have both Google Tag Manager and hard-coded analytics counting pageviews on your site.

Note: how we used a real-time report to debug our setup. Although there are problems with it, it’s often the fastest and best debugging tool.

Filter out internal traffic

Regardless of the size of your organization, internal traffic-that is, traffic from you, your employees, your contractors, your developers, etc.-can skew your data.

There are two ways to filter out internal traffic. The first, the most classic way, is to create an IP filter for each IP address in your office, such as this:

Note that this filter should only be applied to the Master view.

The IP filter works fine if you only have a few offices that view your site. However, if you have many people working remotely, it becomes impractical. In that case, you should have everyone set Block Yourself from Analytics and select Block Analytics for this website on your site.

Exclude query parameters

Query parameters are additional information added to the URL after the question mark, such as this:

https://mysite.com/?blogdemo=true&blogdemo2=yes/

Sometimes these parameters are needed to distinguish one page from another. For example, your site may use query parameters for blog posts, as shown below

https://mysite.com/blog/?postid=1

In that case, you don’t want to exclude these parameters from Google Analytics. However, many parameters do not point to different posts, and they do need to be excluded.

For example, Facebook adds the fbclid parameter to your URL when someone links to your site through Facebook. This should definitely be excluded.

To do this, go to the main view settings and add all the query parameters to be excluded.

Note: that you don’t need to exclude the Google UTM settings, they are excluded by default.

Make all page URLs lowercase

By default, Google Analytics is case sensitive, meaning it will treat page views of “mysite.com/awesome-post” and “mysite.com/Awesome-Post” as different pages.

You need to fix this for page URIs, host names, search terms, and campaign names. Here’s how to do it for URI pages:

Create the same filter for host names, search terms, and campaign names (source, medium, campaign, etc.).

Track subdomains

By default, page measurement in Google Analytics only shows the page path. For example, if your site is improvado.io/ Google Analytics will show “/” as the page.

This works in most cases. However, if you have a site with multiple subdomains (i.e. mysite.com and app.mysite.com), it will cause Google Analytics to show page “/” visits for BOTH subdomains as the same page.

To fix this, you need to create an advanced filter that tells Google Analytics to use the full URL as the page. Here’s what it looks like:

Tracking attribution information

All of the above ensures that your Google Analytics records are clean. In this section, we’ll look at the steps you need to follow to ensure attribution information is accurate.

Attribution is probably the most important part of Google Analytics. It tells you where your traffic is coming from – organic Google search, paid Google search, paid Facebook ads, etc.

While there can be complex technical issues that cause attribution errors (e.g., for single-page apps, you need to fix the problem of unauthorized referrals), most attribution issues are fixed in two steps.

Create a referral exception

By default, Google Analytics counts all conversions when the previous page (referrer) is not part of your site (that is, does not share a domain name with your site).

For example, if someone clicks on a link from DGTLONE’s Facebook page to our site, Google Analytics will count that hit as a referral as facebook.com.

This is usually correct. However, sometimes when a user is redirected from our site and then returns to our site, we don’t want to count the returning user as a referral.

For example, if our site allows the user to log in with Google authentication, the user will be briefly redirected to accounts.google.com to log in, and after logging in will be redirected back to our site.

Or, for example, on the Shopify site, the user places an order on pay.shopify.com and then returns to the site’s thank you page.

In both of these cases, the user hasn’t actually been referred by either Google or Shopify, but without the referral exclusion setting, Google Analytics will attribute the user to Google or Shopify, respectively.

To fix this, we need to add a referral exception for each interaction, such as Google authentication or Shopify checkout.

To create a referral exception for Google authentication, go to Admin > Property > Referral Exclusion List and add a referral exception for “accounts.google.com” as follows:

Note: only you can determine which domains should have referral exclusions. It may take a little time, but it’s worth it.

Also note that referral exclusions are important for cross-domain tracking, which is a big topic in itself, which we’ll cover in a future blog post.

Adding UTM parameters

By default, Google Analytics will attribute:

• Paid Google search to Paid Google search
• Google Organic Search to Google Organic Search
• And all Facebook traffic to Facebook.

But what if we want to distinguish between paid Facebook traffic and organic Facebook traffic?

To do that, we need to use UTM parameters.

We’ve used UTM parameters to test pageviews, but they’re usually used to correctly attribute non-Google traffic to the right medium and campaign, such as distinguishing paid Facebook traffic from organic Facebook traffic.

To do this, we add UTM parameters using the campaign URL builder, which looks like this for all paid Facebook traffic:

“cpc” stands for “cost per click,” and Google Analytics is smart enough to understand that cpc traffic is paid traffic.

Looking at all the UTM parameters deserves a separate blog post, but suffice it to say that creating a new URL using the Campaign URL Builder every time we want to publish anywhere quickly becomes cumbersome.

That’s why we created this Google Analytics URL Builder spreadsheet to help you keep track of UTM codes and implement best practices.

Using UTM parameters correctly, even with a spreadsheet, takes discipline. But it provides the most valuable information available in Google Analytics. It also provides clean data for later use when you want to combine and transform data into reports and dashboards using a tool like Improvado.

Doing the above Google Analytics Checklist will ensure that you have clean and accurate data coming into your Google Analytics account. Using this information, you will be able to answer many of the most important questions about where your traffic is coming from and what content users are viewing on your site.

This will serve as a solid foundation for building the rest of your Analytics. If your numbers are starting to look wrong, we recommend a full Google Analytics audit to identify any errors.