To improve the accuracy of your Google Analytics data, you must spend some time with the tool’s admin screens. Every good GA implementation should engage the 10 settings described below, and every webmaster should know the life-saving trouble-shooting tip I will share at the end of this article.
The Google Analytics admin screen divides into three columns / categories.
- The Account column defines the organization – in this case, our company, Northwoods.
- The Property column includes one or more website(s) or mobile app(s) under that account, up to 50. Northwoods' multiple properties are all websites: Our main Northwoods website; a website for TitanCMS, our enterprise-level content management system; and a website for our workshops and webinars; and a few other sites. A development or test version and international versions of a website are also common Properties.
- The View category shows analytics data from up to 25 points of view per Property.
One Account can have up to 50 different Properties (websites or mobile apps), and each Property can have up to 25 Views.
The 10 tips below cause changes in all three categories – Account, Property, and View.
To get to the Admin screen to make these changes, click on the bottom menu item. (The appearance of the menu depends on whether you have minimized the menu.)
Please keep in mind: the recommended changes require admin editing rights.
Tips Quick Links
- Tip One: Set Up Multiple Views Within a Property; How to Create a New View in Google Analytics
- Tip Two: Set Up Filters
- Tip Three: Check the Bot Filter
- Tip Four: Site Search Tracking
- Tip Five: Set Up a Custom Alert
- Tip Six: Annotations
- Tip Seven: Set a Default View and Industry Category
- Tip Eight: Search Console
- Tip Nine: Referral Exclusion in Property Settings
- Tip Ten: “Benchmarking” in Account Settings
- Lifesaver Tip: Test Your Changes via Realtime
Tip #1: Set Up Multiple Views Within a Property; Creating a New View
How to Create a New View in Google Analytics
This is not a new tip. For about 12 years, every GA influencer has touted the importance of having multiple views in your account. And yet, I audit many accounts that have just one view.
When you first set up a property, Google Analytics creates one default view – the All Web Site Data view. When I see no other view in an account, I know I’m dealing with an unsophisticated set-up.
At a minimum, you should set up three (of the available 25) views:
- A filtered view, which excludes traffic from, for example, your own company and your vendors, so you see only traffic from clients or prospects.
- A test view, so you can test changes to the settings without breaking anything.
- A raw, or “unfiltered” view, which shows all traffic.
If you already have at least two of these views (the raw and filtered), feel free to skip to Tip 2. If you only have one view, proceed to Tip 1A.
Tip 1A: The Raw View
Let’s create a Google Analytics raw data view. It’s your ultimate backstop. (I’ll explain more in Tip 2 – filters.)
It’s easy to set up a new view. In the admin screen, click on +Create View.
In the dialog box:
- Choose Website.
- Name it. I always specify the company name and the type of view – e.g., Northwoods – Raw (unfiltered) view.
- Set your country and time zone.
- Click on Create View.
That’s it! Don’t add filters in this view or do anything else – leave it truly raw.
Congratulations, you have set up your first level of defense in case anything goes wrong with your main view.
Important: A new view activates immediately at creation point. It will not apply retroactively to existing data.
Tip 1B: The Test View
Follow the same procedure to set up a test view (more to come on when to use this).
Tip 1C: The “Filtered” View
Assuming you started this process with only one view, you should now have three – the original one, a raw view, and a test view.
Make your original view, which has all your historical data, your filtered view. Think of it as your Google Analytics master view. Change the name of that view to include “filtered” or “main” in the name, as in the Northwoods example below:
Open View Settings, change the View Name as appropriate, and save your changes.
I recommend using the company name, or at least a designation other than the default All Web Site Data. The new name should indicate what the view tracks. If you have access to multiple accounts and multiple views, a descriptive, unique name adds clarity.
I like some combination of raw, filtered and test in my views. Any name will do, as long as it describes the function of each view. The GA account for the Google Merchandise Store, for example, uses different names than I do – but it’s clear that the set-up intention is the same.
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Tip 2: Set Up Filters
This work in the Google Analytics Admin Section is so scary that I almost left it out of this list of tips.
Generally, it’s hard to screw up your GA data. Not so with filters. You use them to block GA from reporting certain data. A filter miscue can block all traffic, as illustrated in this screen shot:
If you have a raw view (see tip 1A, above), to which you apply no filters or any type of processing, you at least have a backup if disaster strikes your main view. And seeing no traffic in your main view, because somehow your Google Analytics filter failed, feels like disaster.
Despite the risks, filters make sense. Their most common uses are for blocking internal traffic and for blocking spam. Traffic from your employees and, perhaps, your main vendors can be misleading. Traffic worth analyzing and applying to policy comes from clients and prospects (though traffic from competitors often seeps into the mix). And spam is spam.
Tip 2A: Setting up IP Filters (for internal traffic) and Hostname Filters (for spam)
Block traffic from your own workplace by using a Google Analytics IP address filter.
For simplicity’s sake, assume you work from a unified office in a single location. The easiest way to find your IP address is to go to https://www.whatismyip.com:
Once you have that number (22.214.171.124, for Northwoods), click on the Filters option in your test view (which you set up in Tip 1B).
Click on +Add Filter
In the dialog box that comes up, follow these steps:
- Choose Create New Filter.
- Give your filter a meaningful name.
- Choose the Predefined type of filter.
You’ll now have three drop-down boxes. Choose:
- traffic from the IP addresses
- that are equal to
- Enter your IP address – the one you got above, from whatismyip.com.
- Finally, save your filter.
Super-important tip: Do this in your test view, not your main view! Never apply filters directly to your main view without testing them first.
Testing Your Filter
You can test your filter set-up in a couple of ways.
First, make sure the test view is still getting traffic. Apply the Lifesaver Tip (more on that below) to see, immediately, if you messed up the filter. If the number of visitors keeps dropping and never increases, you probably made a mistake.
Next, assuming you’re working in your own company IP address (the address you added in the filter)- open a web browser and go to the website. Navigate to a rarely-viewed page, where you are likely to be the lone reader. (On the Northwoods site, that would be one of my 5,000-word blog entries.)
Open Google Analytics and in the regular GA interface:
- Make sure you’re in your unfiltered view.
- Go to Real-Time / Content and
- Find that rarely-visited page you’re on.
Next, switch to test view. If you have set up the filter correctly, you should no longer be able to see your session. Your traffic has been filtered out of the view.
For your final test: Wait a couple of days, if not a full week. Then compare traffic from your filtered view to the test view by checking several reports in the main interface (e.g., the Audience / Overview report or the Behavior / Site Content / All Pages). I can’t tell you exactly what to look for, but assuming you have decent traffic from your office/location, many session-related metrics should be lower – fewer visitors, fewer pages viewed, etc.
Once you are confident the filter is correct, you can add it to your filtered view. In filtered view, click on Filters and +Add Filters, as you did before. Then:
- Apply Existing Filter
- Highlight the filter you created.
- Press Add.
- Save your changes.
I started this tip by saying we’d look at a simple set-up. Things can get much more complicated. If, for example, you have dozens of locations, you might have to set up a RegEx of one or more IP ranges. You might not have a static IP address. You might have AnonymizeIP set in Google Tag Manager, to comply with GDPR. That means setting up your full IP address won’t work, because the AnonymizeIP setting drops the last octet of numbers in the IP range.
I won’t explain how to deal with complexity in IP filtering. There are too many variables and too much risk of getting it wrong. Work with your IT department, if you have one, to figure out the best way to filter out the right traffic. Or drop me a line and I’ll do my best to tailor an answer.
Regardless of how simple or complex your situation, the process remains the same:
- Identify the IP address(es) you want to block.
- In your test view, set up a filter (or filters) to block them.
- Immediately verify you haven’t killed all traffic to your website (see the Lifesaver Tip at the end of this blog).
- Let the filters run in test view for a while, then compare traffic in that view to your main view and make sure things look okay.
- Apply the filter(s) to your main view.
Yes, but keep your fire extinguisher handy. The only real way to screw up your Google Analytics data is to mess up your filters. Double-check them, test them, and/or ask for help if you’re unsure.
Don’t give up on this. You need filters to block in-house and vendor traffic. You want relevant GA numbers.
Tip 2B: Hostname Filters
There’s an ongoing issue with filtering spam traffic in Google Analytics.
Some traffic that could be interpreted as spam comes from bots or crawlers that actually visit your site. More often, though, it’s from fake traffic submitted to Google Analytics through something called the GA measurement protocol. The measurement protocol lets you import data, typically revenue or ecommerce information, into your account.
It is a legitimately awesome tool, but spammers can and do use it. Block them, with relative ease, through the hostname filter.
First, some background
Spammers use the measurement protocol by sending information to random tracking ID numbers. They have no trouble figuring out the pattern of the tracking ID:
Spammers can guess that UA-nnnnnn-1 will likely correspond to a website, so they can use that with the measurement protocol. But the spammers don’t know what website they’re sending in the fake information for. They might randomly guess the Northwoods tracking ID, as shown above, but they have no way of knowing that that tracking ID belongs to www.northwoodsoft.com.
Any legitimate traffic on your website will know the hostname or URL and report it to GA. In our case, each of the hostnames (or URLs) shown below are legitimate ones, and the Northwoods Google Analytics Property ID runs on them.
The above is my filtered view. My raw view shows some suspect hostnames:
Those are all spam. As much as I love moz.com, for example, the Northwoods GA Property ID is not running there, so there’s no way that’s legitimate.
Determining Your Hostnames
The key, then, is to figure out which hostnames are legitimate for your site – which ones are running your Google Analytics property ID. If you run just one website, you can probably figure out your hostname! But your best option is always to look at a wide date range to verify the hostname(s).
In the GA view, which goes furthest back in time, set your date range for a year or so, then:
- Go to Audience / Technology / Network.
- Change the dimension to Hostname.
- Verify that Hostname is indeed the dimension column name.
Now you’ll see the hostnames that have been reported back to Google. In this case, they’re all either our main domain (www.northwoodsoft.com) or subdomains (try.northwoodsoft.com). Those are all legitimate hostnames, which we control and on which our GA Property ID runs.
Setting up RegEx of Your Hostnames
Let’s assume that my hostnames show the following legitimate entries:
- Northwoodsoft.com and all the subdomains and variations
- Pages.services – the landing pages created in our marketing automation tool, Sharpspring.
I’ll want to set up a filter that allows those two hostnames. To do that, I’ll use Regex (Regular Expressions) to define them. I won’t go into a Regex tutorial – tons are available – but I’ll give you an idea of what it will look like.
Here’s the filter I’ll use:
- ^ starts the expression I’m going to evaluate
- (.*\.)? – this is what will allow any or no subdomain or www to be recognized.
- northwoodsoft\.com – the first legitimate hostname (the “\.” just means treat the period as a period, not as a RegEx character)
- | “or”
- pages\.services – the second legitimate hostname
- $ End of the expression
Does this Regex look confusing? It is. The good news is that almost any developer can help you set up a Regex string.
Setting Up the Hostnames Filter
Now that we know what the string is, we will use it to create a filter in a test view. You can create it in the test view you already created. I prefer to create a separate test view just for hostnames, so I’ll show that.
Assuming you’ve created a test view for hostnames:
- Go to that view.
- Click on Filters.
- Click on +Add Filter
Start building your filter.
- Choose Create New Filter.
- Give it a great name.
- Choose a Custom filter type.
- Click on Include. (Please please please do not click on Exclude. You most definitely want Include.)
- From the dropdown list, choose Hostname.
- Enter your awesome Regex string, from above.
Moving down the page, you’ll see an option to Verify this filter. If you have just set up the view, this option won’t work, because the newly-created view doesn’t show data retroactively; it works from the time of creation onward. Go ahead and save the filter.
After a week or so, compare this test view with your main view. Look at the Audience / Technology / Network report and change the dimension to Hostname, as we did before. The traffic metrics could differ, because you might have other filters running in your main view. But the hostnames should be the same. Your main view may have other hostnames, which could be ones you missed or could be spam hostnames. Adjust and test your filter as necessary.
Once you are confident your filter is correct, apply it to your main view the same way you did at the end of Tip 2A.
Confused? Mike Sullivan, at www.analyticsedge.com, does a nice job of further describing hostname filters. I’m not sure he explains it better (well, he probably does), but a different take might help you make sense of a complicated procedure.
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Tip 3: Check the Bot Filter
If you made it through tip 2, congratulations! Move on to the easiest no-brainer tip in our list.
Bot and spam traffic continue to inflate and otherwise mess up your numbers, even though Google, to its credit, usually catches the worst offenders pretty quickly. But you can take one tiny step to help your account: Click the bot filter checkbox.
You can find this handy little item in the View Settings, in the View Category.
Scroll down to see the checkbox.
Bot filtering won’t get rid of everything, but it won’t hurt and will probably help. Why isn’t this the default setting? Beats me. Just click it. Make sure to do so in your filtered view, not in your raw or unfiltered view, where you want ALL traffic to show.
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Tip 4: Site Search Tracking
Here’s another no-brainer: Capture the search terms visitors enter on your site. This tells you a lot about your users, customers and potential customers.
In the first step, enter a search query on your site and note the URL, specifically whatever precedes the search term you just typed.
For example, let’s say I searched for “GA admin” on the Northwoods site. If I look at the URL, I can see that my search query is defined by “Search_Keywords” (everything between the “?” and the “=”).
Or say I’m looking for alpaca on Patagonia.com – “q” defines their search query, as it does on lots of sites.
In the second step, go to Google Analytics site search within the admin panel and enter the search query parameter:
- Go to View Settings.
- Scroll down to Site search Tracking and make sure it’s On.
- Enter whatever defines your search queries.
- As shown above, this would be Search_Keywords in Northwoods’ case; “q” in Patagonia’s case
- Save your changes.
For the third and final step, go into the Behavior / Site Search / Search Terms report to see the terms users entered. Wait a few days before you do this; again, this change is not retroactive.
Pretty cool – you can see exactly what your visitors seek on your website. You can gain great insight from that.
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Tip 5: Set Up a Custom Alert
I recently noticed a crack in the screen protector on my iPhone. When I peeled it off to install the new one, I found six other scratches.
Holy cow! For a year, it had been protecting my phone and I wasn’t even aware of it. Not bad for a $9 add-on.
A Google Analytics "no-traffic" custom alert is like that screen protector. This custom alert will let you know when your site has little or no traffic. It does absolutely nothing 99.9% of the time. But when something goes wrong, it can save you.
To create your no-traffic alert, go to the View column of the admin section. Scroll down to Custom Alerts.
Click on Custom Alerts and then +New Alert.
Specify the following:
- The name of the alert.
- What view this alert will apply to. At a minimum, apply it to your filtered view -- where things are most likely to break -- as opposed to your raw view.
- The email(s) to which the alert should be sent.
- Create the conditions – e.g., sessions less than 1. If you typically have 5,000 sessions on your site, I might set the alert at anything below 500 – something that represents a drastic drop in traffic.
When the alert fires, you’ll receive an email like the one below. In this case, I’ve set up an alert for a client whose websites haven’t yet launched.
This alert won’t fix the problem causing the traffic drop. It just tells you about it within a day, and that’s a huge weight lifted.
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Tip 6: Annotations
This tip will not affect the quality of your Google Analytics data. It simply reminds you of important changes made to your website. Always make a note of any significant change that could affect your data.
Those annotations will show up when you’re looking at any of the date charts.
Creating an annotation is easy. Click on the Annotations link, then on +New Annotation.
On the next screen:
- Specify the date of the change.
- Describe the change (up to 160 characters).
- Shared – anybody who can view the GA data can see the annotation
- Private – only you can see the annotation
- Create it.
NOTE: Annotations are specific to a view. If you create an annotation in your filtered view, it won’t show up in other views.
Bonus tip: When I see annotations in a GA account, I know I’m likely dealing with a well-set-up account and a smart client.
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Tip 7: Set the Default View and Industry Category
We now consider changing items in the Property Column, starting with Property Settings.
Click on Property Settings.
- Specify the Google Analytics Default Views. In almost all cases, this will be your filtered or main view. Set this up so that each time you go into the GA interface for your property, it will default to this view. This tiny time saver will make your life easier.
- Set the Industry Category. This will be used for the benchmarking report (
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