10 Google Analytics Checklist Items For A Healthy Data Analysis

When you install Google Analytics on your website it comes with pretty sufficient default settings. It is easy, even tempting, to start analyzing your website data right away. However, making a decision from garbage/noisy data is even worse than not making a decision at all. 

Here are the 10 most important things you should consider before starting your website analytics journey:

  1. Exclude known IP’s
  2. Check Spam Traffic
  3. User Permissions 
  4. Profile Naming Conventions
  5. Profile Strategy for App, Web, Mobile, Blog, Test
  6. Double Check Hits, Pageviews or Events 
  7. Overwrite Channel Groupings
  8. Http or Https In Views?
  9. Exclude URL Parameters For Reducing Cardinality Problems
  10. Referral Exclusion For Right Attribution (e-commerce sites)

Exclude known IP’s

This one is easy but the most effective in terms of getting right and clean data. As an organization, you should exclude the visits coming internally, which include both people visiting the site from the business network as well as home networks. Often times companies forget to exclude home visits of their employees, which might generate quite a lot of sessions!

If you have retail stores across cities or any remote locations, their network IP’s should also be excluded. 

Another important exclusion is your business partners. If their visits to your site is not generating any goals for you, their IP’s should also be excluded.

Excluding an IP is one of the easiest things to do in Google Analytics. You must create an IP Exclusion filter. Here are the steps:

  1. From the Admin page, go to Account > All Filters > Add Filter
  2. Give descriptive names for your IP’s like Exclude Home IP, Exclude Work IP, Exclude Retail IP…
  3. From Filter Type you may use a Predefined IP exclusion filter but it is better if you use a Custom filter.
  4. From Filter Type > Custom, select Exclude > Filter Field (IP Address) then enter your IP in the text box named Filter Pattern.
  5. In here you have to write text that Regular Expression accepts. Regex, which is shorthand for regular expression, is another topic but just enter your IP’s with a backslash (\). For example: 192\.168\.33.\22 
  6. If you want to enter multiple IP’s at once, which is good for your organization, then you must use the pipe character (|) between IP’s. Like this: 192\.168\.33.\22 | 192\.68\.83.\44
  7. As the last step, you have to apply the filter to Views. Just select Views from the left side and ADD them into Selected Views.
Exclude ip from Google Analytics
Exclude ip from Google Analytics

Check Spam Traffic

Spammers lately targeted Google Analytics as a platform to spread spam. Because of one of the features?! of Google Analytics (measurement protocol) it is easier to send external data to Google Analytics. This backdoor is used by spammers extensively. 

Although Google acknowledged the issue and provided solutions, there are several things you can do to clean spams yourself.

  1. From View > View Settings, tick the Bot Filtering option.
  2. Create a Language Spammer filter which only accepts languages from universal short abbreviations for languages (like tr, en-us, en-uk ..)
  3. Go to Filters and add Custom > Include > Filter Field (Language Settings)
  4. Enter this regex: ^[A-Za-z-_()\s\d]{1,10}$
  5. Save and close.
Language Spam Filter in Google Analytics
Language Spam Filter in Google Analytics

From time to time you might see Referrals from domains, like bestseo-tool.xyz or seoguru.io etc. These are clearly spams which in this case you must include a filter for these referrals. Create an Exclude filter for Campaign Source with the tld’s like .xyz etc. or Hostname exclusion.

User permissions

Google Analytics provides a per user level access for Views, Properties and Accounts. You should organize your access level permissions for both individuals. 

In Organizations, people come and people go, but your analytics account stays. Periodically, you need to check your User Management and update/remove user access permissions.

Here are some scenarios that you may find in User Permission clean up:

  • No longer working business partners.
  • New interns whom should not be able to access confidential e-commerce data
  • Old colleagues who are no longer working with you
  • Multi Regions that do not have access to other Regions data. Maybe US users should not see Europe data
  • People between different departments, maybe Sales reps would not need to see the Social media property view
User Permissions in Google Analytics
User Permissions in Google Analytics

Keep in mind that you can grant access per property or view level.

Profile Naming Conventions

In Google Analytics you can have 50 Properties and up to 25 Views per property. That's more than enough for most businesses. However as you add more views with no naming conventions, you may easily forget that specific views show filtered sales data for, for example, only mobile apps.

Agreeing on a set of naming rules within your account will benefit all users because the name itself will be self-descriptive of the contents of that view. Also by including numbers into view names, you can easily type those numbers in a search and find that specific view quickly.

Here are some examples and best practices for naming views:

View Strategy for App Web Mobile Blog Test

View strategy goes hand in hand with the naming convention. As a default user, you can create 25 different views. It's better to give some thought on how your views are created. 

Here are some View examples:

  • Raw view (this is where no filters applied)
  • All View (includes web, mobile app, mobile web excluding ip, spam etc..)
  • Separate views for Apps (ios, android), Blog views
  • Test view (only one person access), Stating or Development views
  • Geo Region views (if your business operates in multiple regions), Domestic or International views
  • Traffic Channel specific views (only Organic, only Paid etc..)
  • Department specific views (only Marketing people, only Sales people via user permissions)

Your business dynamic might be different from all others. Possibilities are endless but you have a very limited 25 view option. Choose wisely and gather all parties and their needs as to create meaningful Google Analytics views.

Double Check hits, pageviews and events

As time goes by your website changes. You update URL structures, add new pages, include some new functionalities or delete sections. Companies easily forget this dynamic nature of websites. It is very probable that when you change something in the codebase of your website, it might affect how Google Analytics receives and reports data. 

Periodically, you should check your data collection is in a healthy state. Here are some issues to consider for periodic check-up:

  • Open a view that only filters your hits. If you are a small company and have static ip, this can be done easily with an IP filter.
  • If you don't have a static ip in your large organization, then just for your computer you can add UTM tags for a test. Something like this will do the trick: utm_source=Test&utm_medium=Tester . Now append this at the end of your domain and visit the page. Now you are filtered by this specific Medium and Source. You can even create a segment later and see your pageview hits.
  • Check for double hits, non hits etc… Are there any pages that look suspicious in receiving hit data?
  • Check your app and mobile website as well
  • Check your events are still firing. Maybe that innovative UI team made changes to the buttons and now all your events are gone?

There are of course tools for a Google Analytics health check. One that I highly suggest is Google's own Google Tag Assistant extention. It's only a Chrome extension but it gives extreme detail of information about your implementation of Google Analytics setup. There are also commercial tag inspectors like WASP which is also free up to 100 pages.

Overwrite Channel groupings

Channels in Google Analytics, are Google's grouping of your traffic sources. Collecting traffic sources in specific buckets makes it easy to understand where your users come from. 

Google Analytics comes with a good default channel grouping. If you want to understand how Google sees traffic sources and put them in their respective channels, please read Google's own docs.

Probably you have more varied types of traffic sources than provided by Google's channel definition. 

For example, you may depend on third party Meta Searches as a traffic source. Or you may depend on business partners traffic and rather than including these in Referrals it is better for you to open a new channel and include them there. 

Maybe you are dependent on traffic from PDF files? Links from PDF's are counted as a Direct source if you don't manually tag them with UTM parameters. Give good UTM parameters and include their respective channel. 

As a general tip, I think most of the Referrals can be added in different channels. Looking into your referrals from Acquisition > Referrals > Source you might find some traffic sources are better to be included in a different channel. Maybe your paid blogger content advertorials might be better to include in Blogger channels where you might import cost data.

As a bonus tip, you can also create just two channels for all Paid and all Non-Paid traffic sources. This will give you a quick understanding of your performance.

Google's own default channels are good but not enough. Open a new grouping and add new traffic sources in terms of their marketing importance. This way, you can have a better understanding of marketing channels and make better decisions.

Http or Https in views?

Although modern and secure websites use HTTPS in their url's, and we assume you are one of them, some websites are still on non secure HTTP urls. 

This is somewhat fine, but sometimes websites serve both HTTP and HTTPS versions. This is not only bad for your organic results but if you did not choose proper website URLs it might pose a problem to your data.

This setting is under View Settings > Basic Settings > Website URL

https view in google analytics
https view in google analytics

Enter your main website and be careful to check whether it is http or https.

Exclude URL Parameters for reducing cardinality problems

Your website might get lot's of traffic and you might have thousands of duplicate pages or similar filtered pages that might cause cardinality in reports. So what is this fancy statistician jargon called cardinality in Google Analytics?

Basically, if a dimension has very high, like tens/thousands of unique values, that may cause a high-cardinalty problem. For example, your filter widget causes the same page to have tons of different page URL's whereas basically they are the same page with different view presentations.

You might be faced with a high-cardinalty problem, then Google Analytics will notify you at the top of the site with a yellow box.

Or in your reports, you see in the Pages dimension the grouping of (other) and wonder what that "other" contains. 

As I said above in the session parameters, filter parameters or any parameter combinations that create lots of pageviews, Google Analytics will group them as one (other) entry in your pages report.

One easy way of decreeing cardinality is by removing parameters from your url's. 

Get a list of your website urls and look for parameters that do not give you unique page content. These are a good candidate for exclusion. Here are the steps that you should take:

  1. Go to View > View Settings > Exclude URL Query Parameters
  2. Enter your parameters. separate with comma. Like q, sk, sessionID …
Exclude URL query parameters 2
Exclude URL query parameters 2

Keep in mind that, you might depend on some url parameters to get unique pages or other important page views. Those may stay in Google Analytics.

Referral Exclusion for right attribution (e-commerce sites)

This one is also an important topic for healthy Google Analytics data. There can be times where you want to bypass some traffic sources to create a new session or a traffic source channel. 

For example in most e-commerce websites, users might go out of the site to a payment gateway website and are later redirected back to the original page. If you don't exclude these payment gateway websites, each time a user is redirected back, it will create a new session as well, as their channel attribution will be written to the payment gateway website.

Another scenario is when you have multiple subdomains and users might have to jump between subdomains. In this case, you must include your domain in Referral Exclusion. This is done automatically but you should check it again.

Here are the steps that you should take:

  1. Go to Property > Tracking Info > Referral Exclusion List
  2. Add the domains that you want to exclude, like pos.bank.com payment.bank.com
  3. Check whether your own domain is included there
  4. Save and close

There you have it. These are the 10 Google Analytics checklist items for healthy data analysis. But as Kubixers, as always, we want to give you one more thing….

Bonus Tip: Lowercase aa your url's

Creating a filter that will lowercase all your hits will allow you to see more clearly and more orderly.

This filter also removes wrongly entered UTM links into one consistent structure. For Google, uppercase and lowercases are different.

Lowercase Google Analytics
Lowercase Google Analytics

You have to create a filter for the items below:

  • Lowercase Campaign SOURCE 
  • Lowercase Campaign MEDIUM
  • Lowercase Campaign TERM
  • Lowercase Campaign CONTENT
  • Lowercase Event CATEGORY
  • Lowercase Event LABEL
  • Lowercase Event ACTION
  • Lowercase SEARCH TERM
  • Lowercase REQUEST URI

We hope you enjoy reading our Google Analytics Health checklist guide. For further Analytics Consultancy you can just get in touch with us. We are here to help. 

serdar
30 Jun 2017

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