While the Google Analytics Property is the main storage group (you only have one UA-ID per Property) you can use Goals to determine how effective your marketing, landing pages and others are performing. Furthermore you can add filters to keep your data clean while also assuring it meets various privacy laws like GDPR and CCPA.
There are two key areas where Google Analytics settings are changed, Property settings and View Settings. These are often confused. Property settings, as we setup first, allow you to integrate Google Products, change session and campaign duration, and set privacy settings. View settings, as you will see, allow you to customize that same data towards your own specific business, department, geo-area and more. This is done through goals, filters, and general settings seen below.
4.a Configure General View Settings
- When naming Google Analytics Views, you should always have at least three views named accordingly:
MASTER – [URL] This is the View that you want everyone to go to most often (some organizations may have a master view per department, geolocation, etc.). In short, this is where you go for reporting
RAW – [URL] While the Master view will likely contain filters that alter the data collection, this view should contain no filters, goals, channel groupings, or anything. Plain Jane. This is used for debugging when things are looking off.
TEST – [URL] This is where you try out new settings before promoting to the Master View, assuring data quality.
- Make sure and change the Website’s URL dropdown to https:// if that is how your website is hosted.
What is entered into this box is the value Google Analytics will use when following links within the Pages reports. If you are using multiple sub-domains and domains list the most popular one.
- Enter in the Time Zone that you would like all reporting to be normalized by.
NOTE: When a visitor from another timezone starts a session, their time will be translated to what is selected here.
So, If a user is visiting a site at noon in Germany then it will still appear as coming in at 7am (-5hrs) within your reports.
(NOTE, we can fix this with the collection of a custom dimension)
- Leave the Default page text box blank unless you still use index.html, default.asp, etc. (or just stop using these!)
- In order to assure proper page tracking and easier reporting you likely want to get rid of query parameters. Read our dedicated post on excluding query parameters including a Google Sheet tool to help find them.
- If you are selling anything on your site you will want to set this to your local currency. This will also be used for AdWords and other areas where revenue is used. You may want to consult an expert if you support multiple currencies on your site.
- Check “Exclude all hits from known bots and spiders”. Google excludes traffic from sites listed within the IAB International Spiders and Bots list. See the filter section below for additional resources on Google Analytics spam.
- We will follow-up with more details on connecting Google Ads and Google Analytics, but here is an article from Google
- Set up site search [if the function exists on the website]. All you need to do is perform a site search on the website and look for a single letter (typically either “q” or “s”) right after the “?” and before the “=” and then input that into the field in Google Analytics.
4.b Set-up recommended Goal Sets
By far, Google Analytics goals are the cornerstone of your entire setup. At MashMetrics, we spend a great deal of time within our Measurement Plan defining micro and macro conversions on your website.
Within our preview process, we setup a standard series of 15 goals within our clients accounts. Our goals are set to capture data on top funnel engagement metrics like scroll depth rate, video view percentage, time on site, and pages per visit. Then we also have middle funnel goals setup to capture metrics regarding content downloads and all form submissions.
NOTE: Importing goals into Google Analytics from the link below does not allow you to keep the organization of our goal sets.
Alternatively you can copy and paste the settings from our Best Practices guide.
One of the most popular types of goals is counting when users hit a certain page, namely the “Thank You” page. This is used most commonly after someone completes a form, makes a purchase (though you would use eCommerce tracking for that) or another important “last step” in a user scenario. One mistake we often see when setting up a destination page goal is using a page that users can also begin their session with. As a common rule, if the page can be indexed by Google, do not use it as a goal.
- Give the Goal a Name (Finish Audit)
- Choose how to organize the goal (see our illustration for an example on how we organized goal sets)
- Chose Destination
- Press Continue
- In order to assure only valid pages are counted, you will need to pay attention to the URL. You can use match types in order to drill into the needed page. Google has a great guide on the different Google Analytics goal Match Types here.
- Enter the actual page name or URL
- One of the filters we will install below turns all pages into lowercase so you can likely ignore this setting
The folks at Mighty Citizen have a wonderful post dedicated to destination goals in Google Analytics that also walks through setting up goal funnels as well. This is a feature that can only be done with destination goals.
More and more often the activities you want to track do not have a destination page. In fact, you will notice a great majority of the goals within our worksheet are created from events. This comes in handy if your lead form doesn’t load a new page, you want to measure a partner click, and more. By using Google Tag Manager to fire off events you can create goals easier than ever. Event based goals allow you to designate the Event Category, Action, Label, even a specific value.
- Give the Goal a Name (Finish Audit)
- Chose Event
- Press Continue
- Use our worksheet (or look at your own event reports) to fill in the appropriate fields (Event Category, Action, Label)
- Press Save
While we are not huge fans of how the Session Duration time is calculated within Google Analytics, this will help you guage how long certain users are staying (vs. relying on averages). We recommend setting a few variations up to see the differences.
1) Give the Goal a Name (Visits > 5 min)
2) Choose Duration
3) Press Continue
1) Choose Greater than (or Less than) and then enter 5 under minutes
2) Press Save
You may want a “reverse goal” and choose Less than 30 seconds to quickly see percentage of low engaged users.
If you are a service oriented website, eCommerce or site where you feel users need to see a couple pages before you can consider their visit successful, set these goals up to see how far users are getting. (NOTE: These can also be setup as segments and then used for re-marketing audiences!)
1) Give the Goal a Name (Viewed > 6 pages)
2) Choose Pages / Screens per session
3) Press Continue
1) Enter the desired quantity of pages
2) Press Save
Through the years we have maintained a list of key Google Analytics filters we install (and keep up to date) for all our clients. Quite honestly, filter is not a great name for these settings. As you can see, filters can be used for much more than to simply exclude pages or users. In order to keep track of the use case for all the filters we use an easy to follow naming convention.
- INTERNAL – These filters attempt to exclude employee and test traffic from your production data.
- CASE – Keeps your data clean by forcing key elements to lowercase
- URL – Cleans up your URL into something you can show your boss.
- PII – Removes various information such as emails, names and more so your account doesn’t get suspended (this is NOT a guarantee)
- SPAM – While the bot exclusion setting within your View Settings helps, at times we have found bots and ugly traffic before Google does
- ISSUE – Solves data collection issues and various nuances we run into. (excluding Facebook Form Submit hits)
- CHANNEL – Clean up your some of your channel data.
To start creating filters, with the Google Analytics Admin area, navigate to the Filters section under View Settings and click ADD FILTER
Before you begin to create Google Analytics filters:
- Filters are NOT retroactive
- Filters effect the data being collected from the moment they are saved and can even be tested within Real-Time mode
- Once collected, Data can never be deleted from Google Analytics (except some user data for GDPR and other privacy compliance)
- Google Analytics starts from the top of your filter list and moves down the list. For example, the Request URL (URL) can be forced all lowercase and then a query parameter can be removed
Google Analytics is case sensitive. That means when reviewing your marketing reports you may see Facebook and FaceBook and facebook. Your UTM parameters may be incorrect. This also goes for your page URL too. www.site.com/blog/ is different than www.site.com/Blog/. While your webserver (hopefully) recognizes both, Google Analytics will treat this as two different pages. Luckily there is a built in Lowercase or Uppercase filter, but you have to set it up for each desired dimension.
We suggest forcing the following Dimensions into lowercase:
- Request URL (URL)
- Search Term
- Campaign Source, Medium, Name, AdGroup, Term, Content
- Transaction Item Name, Item Variation
While also not cool for consumers, Google Analytics’s usage guidelines specifically state that they can (and will) suspend your account if it is known to collect Personally Identifiable Information (PII). More often than not the collection of this information is not intentional and you may even be unaware of it happening. We find this most commonly happening when forms on your site send the email or name through a query string in the URL.
It is worth stating that you CAN use Google Tag Manager to collect and send PII to other tools.
Illustrated are various regular expressions used within a Search and Replace filter that will obfuscate PII found in your Google Analytics reports.
Have you ever noticed a jump in traffic from some pretty unlikely places? Do you see strange referral URLs promoting website buttons or traffic stats? Is one of your top listed Organic Search phrases “amazon”? In 2020, not even your Google Analytics is safe from being spam-free.
Since the IAB list costs up to $14,000, here are some of the top (free) resources that keep up to date Google Analytics spam filter lists:
- Carlos has always help the most complete filter guide his own site
- If you want more of an explanation of what Spam Traffic is read his article in Moz.
- Analytics Edge also does a great job explaining more advanced (but risky) solutions
- We keep our clients up to date by automating updates with analytics-toolkit.com
For accurate channel attribution these filters help condense social media and email traffic as often social or email traffic gets lumped into referral or direct in the channel reports. There are several industry specific social media networks, and you may want them automatically sorted in the social Media reports. Traffic coming from various email providers like gmail, Yahoo Mail, and Outlook also drop the referral source.
This filter does not take the place of using UTM parameters! Continue to have a UTM strategy for Organic and Paid Posts, Tweets, and other links. Also make sure your email (MailChimp, AutoPilot, HubSpot, Drip, Eloqua, Signature Line) linkbacks have UTMs as well.
While we may assume that our URL’s (Google Analytics calls this the Request URI) are nicely formatted when we build our websites, they are not. Some of the ways the filters included in our Best Practice Guide make reading URLs easier are:
- Making sure you always have a trailing slash: site.com/blog and site.com/blog/
- Displaying the hostname along with the Request URI. landpage.yoursite.com/productpage/ vs www.yoursite.com/productpage/
- Removing page or extension variations (index.html vs index.php)
- Got any suggestions? Please comment below!
Internal Traffic can be a finicky thing. While you should certainly test the tracking on your website, landing pages, etc; you likely do not want to include this traffic in your marketing reports. It doesn’t stop there. Another type of internal traffic that is rarely talked about is from your various SaaS systems.
Some common sources that we see internal traffic come from are:
While filtering your internal IP address (Find your IP Address here) is a common practices, it is not very effective. IP Addresses change, your marketing team, marketing agency, or designer has remote workers, and Starbucks might be most common location for your outside sales staff grabbing content off the site.
What has worked the best for us in the past is either purchasing a cheap domain name or using a subdomain that redirects to your site with a query parameter attached (internal_traffic=true). We then use Google Tag Manager to drop a cookie that stores this information, places into a Custom Dimension, and is then filtered accordingly. This can also be done after a WordPress or Magento preview page, Shopify username, and more.
If you a marketing agency, development shop, or multi-brand organization you must make sure your setups are consistent across the board so that you know each time you setup a new account everything will go smoothly.
If your team is using WordPress, Shopify, Magento, HubSpot, or any website type, do not rely upon plug-ins such as MonsterInsights and WP4GTM alone. Many of these steps will not be covered. it is critical that you make sure your data will be both reliable long term and that no steps are skipped through the process.
The only way to get consistent setups every time is by following detailed processes and leveraging tools that can remove some of the manual work where errors and inconsistencies tend to happen.
If all this has been way too much for you, we get it, perhaps our Data Adoption Plan is for you.
If this was a cake walk, but now you want to copy it all over to another property, or perhaps you are an agency that wants to do this en mass, schedule a meeting below and we will discuss your needs.