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6 Powerful Steps to Set Up Your Google Analytics Instance the Right Way

By Ata Khan | October 22, 2018

Google Analytics can be found on many websites these days. It is likely that your competitors are using the awesome power of this tool, and you should too!


A properly set up Google Analytics system can track visitors that convert into customers, track and attribute revenue generation, breakdown visitor demographics and website behavior, and leverage various AI and retargeting systems on platforms like Google Ads.


However, few businesses (and agencies for that matter) get the set-up process right. The results are inaccurate data and poor performance of marketing campaigns.


This happens because there are so many ways of setting up the platform, there are many settings, attribution models, and data aggregation methods that all need to be implemented correctly for the system to represent accurate and reliable data.


This article will explain exactly how to set up your Google Analytics system the right way.


Start with Google Tag Manager


google tag manager


For any type of tracking system to work a script must be installed on every page of your website (this is what allows the system to collect data about your visitors).


The old way of doing things was to install a tracking script from each platform one at a time on every page of your website. Not only was it labor prohibitive, but it also slows down your website as all the scripts must load with each visit.


Bring in the new way! Google Tag Manager is the best way to implement tracking codes on your website because you only need to set one single script on your pages and nothing else.


The tracking codes from the various platforms are then then loaded via the backend of the GTM account. Only the GTM script needs to fire in order for all your other scripts to work. This speeds up your page load times and reduces the need for developer intervention.


Here’s how to install Google Tag Manager on your website:


  1. Add a new Account here. Input the name of your organization, set your country, and choose whether or not you would like to share anonymous data with Google.
  2. Next, set up your Container. Give it a name (use the canonical domain of your website) and then click on the “Website” button and hit next.
  3. Accept the terms and then copy and paste the code onto every page of every domain of your website (see below).


google tag manager script


The first code is placed right after the <head> tag of every page of your website. The second is placed right after the <body> tag of every page of your website. Once that is done, there is no need for further development work to place scripts on your site.


The next step is to now start setting up your Google Analytics instance.


Set Up the Basics


Jump over to Google Analytics and hit the sign up button. On the next page fill in the necessary details.


Input the name of the account (i.e. your company name), the name of the website you are tracking, the URL of the website (be sure to use the canonical domain), your industry, and your time zone.


Check all of the boxes for data sharing options, and hit “Get Tracking ID”. Then accept the terms of service and move forward.


Before inputting this script in your GTM instance you first have to do something. Click on “Property Settings” on the left hand sidebar and update the “Property Name” to “Dummy Property 1”.


Hit “Save” at the bottom and then hit “Create Property” at the top of the left hand sidebar. Name it “Dummy Property 2”, hit “Save” and then hit “Create Property” again. Do this 7 times (which will effectively generate 7 Google Analytics IDs).


You must be asking why do this? It turns out that many types of spam traffic will only go a few properties deep in order to spoof Google Analytics. In this case, setting up 7 properties deep keeps your instance safe for a long time to come.


When you come up to the 7th property, start loading the correct details. Your “Website Name” should be the name of your website, your “Default URL” is the web address of your website (i.e. the canonical domain), select your industry and time zone, hit “Get Tracking ID”.


On the next page you are presented with the Google Analytics script that now needs to be implemented across your website. Luckily, you have already installed the GTM container script, and at this point all you need to do is copy the ID (which should end with the number “7”) highlighted in the below image.


Google Analytics script


Copy this ID and jump back to your GTM account. Once in GTM, click on the “Tags” link on the left hand sidebar. Tags are the actual scripts that you wish to have implemented (like Google Analytics, Google Ads, Facebook Analytics, etc).


On the next page click on “New”, then name your tag (in this case it should be called “Universal Analytics Script”). Then edit the “Tag Configuration”.


Upon hitting the edit button a window will slide in from the right with a list of various platforms. Choose “Google Analytics – Universal Analytics”.


Next, leave the “Track Type” as “Page View”, leave the “Google Analytics Setting Variable” as is, and then check the “Enable Override Settings in This Tag” box.


Remember that code you copied? Go ahead and paste it in the “Tracking ID” field (as seen below). Skip the “More Settings” section and “Advanced Settings Section”.


Google tag manager tracking id


Jump down to “Triggers” and hit the edit icon for this section. Tags reference the actual script/platform of choice, triggers reference the actual event that needs to take place in order for the tag to fire (this could be a pageview, a click, a purchase, etc).


Once you hit that edit button, a new window will slide in from the right. Click on the only option presented there (which will be called “All Pages”) and then hit “Add”. This commands the Tag to fire on all page loads of your website.


Upon hitting the “Add” button, you will be directed to the original page with both your Tag and Trigger. You can now hit the “Save” button.


Once you hit the “Save” button, close out the window and jump back to the GTM homepage. Here you can now hit the “Submit” button on the top right hand corner. Your changes only propagate to your live site when you hit that button.


Google tag manager submit button


Upon doing so, a window will slide in from the right. This window tracks all of the changes that are made to your GTM account (in the “History” section).


Give this change a name (under “Version Name”); in this case, call it “Google Analytics Script – Initial Implementation”. Then in the box below describe the change.


In this case you can put something like “Implementing the GA script for the first time on website.” Hit the “Publish button on the top right hand corner.


Congratulations, now your Google Analytics script has been installed on your live site using Google Tag Manager.


Test Your Instance


Now that your GA script has been installed you should test it to make sure it is working properly. There are two ways to do this. One is using the GTM preview and debug mode, and the other is using a Chrome add on called Google Tag Assistant.


GTM Preview and Debug Mode


This is the best way to test your code implementation. Jump to the GTM homepage, and click on the “Preview” button on the top right hand corner.


Once you have done that you’ll notice that an orange bar will be present across the top of the page that says “Now Previewing Workspace”.


Next, jump to your website. You’ll notice that across the bottom there will be a new section that says Google Tag Manager. This is what you can use to test and debug your system.


Under “Tags Fired on This Page” you should see a block that indicates your Google Analytics script has fired 1 time. If you see the block it means your GA script is firing correctly.


GTM preview and debug mode


If you do not see the block it means that the GA script did not fire and there is an issue. This will require you to debug the issue. Google has a great guide on key elements that you can start checking if you are experiencing issues with your GTM tag.


Google Tag Assistant


Use Google’s Tag Assistant for Chrome to test your GA script. Once this extension has been activated, simply browse your website pages.


Upon doing so you, click on the extension on the top right hand corner to see if your GTM container code has fired. You should see it there in Green.


You should also see the GA script (although it will show up in blue indicating a non-standard implementation – but ignore that as Google confirmed this is a bug on their end).


Google tag assistant


Get Your Settings Right


Now that everything’s set up and running smoothly, it’s time to input all the correct settings.


One thing to keep in mind is that Google Analytics sets up its hierarchy in the following way: Accounts>Properties>Views. Where Accounts are the highest level and refer to entire organizations or companies, properties are the next level down (or child to accounts) and refer to assets the company owns (like websites, mobile apps, etc), and views are the lowest level (or child to properties) and refer to the specific reporting structure and data aggregation within a property.




Click on the “Admin” link at the bottom of the left hand sidebar. This will take you to the administrative section of GA. Under the “Account” column, click on “User Management” (you may skip “Account Settings” since these were already done during the initial set up).


google analytics admin section


The “User Management” section is used to give folks access to your GA account. Hit the “+” button on the top right hand corner to add users.


For a definition of the various user permissions, Google explains them well here. Keep in mind that whatever user permissions you set at the account level will trickle down to all properties nested under the account and all views nested under those properties.


The “All Filters” section is used to apply filters to your data. We’ll come back to this later.


The “Change History” section is used to track any and all changes made by any user on your GA instance.


The “Trash Can” contains anything you delete (such as properties or views).




Jumping back to the admin section of GA. Now focus on the center column titled “Property”. Start by clicking on the “Property Settings”.


Make sure your “Property Name” is the name of your website, and that the “Default URL” is the canonical domain.


For “Default View” leave this as is for now (you will have a chance to change this later). For “Industry Category” use the value that aligns best with your business.


Under “Advanced Settings” leave the “Allow manual tagging (UTM values)…” unchecked.


Where it says “Enable Demographics and Interests Reports”, switch that to “On”. This allows you to identify the visitors coming to your website (i.e. their demographic info and interests).


Where it says “Use enhanced link attribution” go ahead and switch this to “On” in case you want to track links to your web pages.


Leave “Embedded mode” on in the “Start In-Page Analytics” section.


Below that you will find the button to “Adjust Search Console”. This is where you can connect your GA instance to your Google Search Console account.


Google Search Console allows you to troubleshoot your website for SEO (it’s your website viewed from the eyes of Google). This is an indispensable tool for SEO (so integrating with GA will give you an edge).


Click on the “Adjust Search Console” button. On the next page click on “Add”, this will open a new window where you can choose your Google Search Console property.


Click the canonical version of your Google Search Console property, hit save to be redirected back to Google Analytics where you will now see your Search Console property listed.


Google Webmaster Tools Snapshot


For “Enabled Views” leave this as is for now (i.e. choose the default view) and then hit “Save”. Your GA instance and your Search Console are now connected.


Jump back to the Properties>Property Settings page of the admin section. Pick up where you left off. You will now see “Enable Users Metric in Reporting”, check this to “On”.


This will help provide more robust reporting when layering different dimensions on top of your user data. Next, hit “Save” at the bottom of the page. This completes set up for the “Property Settings” section.


Move on to the next section in the “Property” column (which is “User Management”).


Just as it was in the “Account” column, you may give user access to your people. The rules are the same, only now the access granted will not be at the account level, but at the property levels (with trickle down affect to nested views).


The next section down is titled “JS Tracking Info”. Clicking this will open a dropdown full of sections. The first is called “Tracking Code”. Click on it.


google anlaytics tracking code section


First thing’s first, click on the “Send Test Traffic” button. You should see a window popup with your website and then see the counter move from “0” to “1”. That should do it for this section.


Google anlaytics test


Next, click on the “Data Collection” section, and toggle the “Remarketing” and “Advertising Reporting Features” button to “On”.


The remarketing feature will allow GA to track and identify users and segment them into lists. These lists can then be used for remarketing campaigns.


The advertising reporting feature allows GA to display various demographic attributes of your users in the reports views.


Now click on the “Data Retention” section and toggle the “User and Data Retention” field to “Do Not Automatically Expire”. This means that your data (no matter how old) will never be deleted from your GA instance.


By doing so, it doesn’t matter what you toggle the “Reset on new activity” field to since your data will never expire (and this field is used to renew the expiration countdown on a user), but we leave this in the “On” position just in case something changes.


Skip the “User-ID” section; this is only used when you want to merge other data sources with your Google Analytics data.


For example, if you have a CRM system and want to know the source of a closed/won deal you can connect the contact record associated with that deal (via a unique ID) to the user in Google Analytics that corresponds to the contact record. In other words, you are connecting both data sets.


Moving on to the “Session Settings” section; this is where you define what a visitor has to do on your site in order for GA to call it a session.


For “Session Timeout” we usually leave this at 30 minutes. This defines the amount of time it takes for an inactive user to be considered “gone”.


For “Campaign Timeout” we usually leave this at 6 months. This is the timeout window between visits.


When a visitor hits your website, leaves and then comes back some time later; how long does it have to be before the second visit is declared as the original source of that visit?


Setting the appropriate “Campaign Timeout” is good for things like revenue attribution.


google analytics session timeout


Skip the “Organic Search Sources” section since Google lists out most of the referring search engines automatically.


The “Referral Exclusion List” section is an important one.


This means that if you (for example) have a subdomain (let’s call it “marketing.yoursite.com”) then any traffic that moves from that subdomain to your main site will actually be tracked as a referral from marketing.yoursite.com. When this happens the original source of that visitor is lost.


By listing “marketing.yoursite.com” in the referral exclusion list, that visitor moving from the subdomain to the root domain will not be tracked as a referral but rather as coming from the original source that brought them to marketing.yoursite.com subdomain (in other words, the source is carried through).


You can do this with any website you choose to list on the referral exclusion page (even external domains). For our purposes, go ahead and list the root domain (i.e. “yoursite.com”) which automatically covers subdomains since they are nested inside the root domain.


If you have external domains, marketing sites, etc then go ahead and list these as well.


Skip the “Search Terms Exclusion List”. This is used to remove certain keywords driving traffic to your pages (it’s usually categorized under “Organic” sources in the reports). In our experience this is rarely required.


Jumping to the “Google Ads Linking” section, this is where you can connect your Google Ads and Google Analytics accounts (and begin passing data back bi-directionally).


If you have a Google Ads account go ahead and select the ID that corresponds to that account and hit “Continue” to configure the connection.


Next, under “Link Configuration” set the title (which can be “YourWebsiteName – Google Ads Account”), select the views that the data should show up for (choose the default view given for now), and click on “Advanced Settings”.


Under “Advanced Settings” choose “Enable Auto-tagging on any….”. This will ensure that your Google Ads instance is passing the appropriate data to Google Analytics. Hit “Save” and then “Done”.


If you don’t have an Adsense account, skip the “Adsense Linking” section. If you do, much of it is very similar to how Google Ads was linked in the section above. Same goes for “Ad Exchange Linking” (except that it has to do with other ad platforms).


To verify your various connections, hit the “All Products” section and take a look at everything. You’ll notice that every connection is listed and will have a green checkmark next to it if all is good (see below example).


google anlaytics product linking


At this point you can skip to the “Audience Definitions” section (as most businesses don’t require “Postbacks”).


Here you can build lists of users that are important to your business. This could be users of a particular demographic, users exhibiting behavior that is indicative of buyer personas, etc.


Upon clicking “Audience Definitions” a menu will drop down.


Click on “Audiences”, this is where you will create your target demographic lists (to be used in remarketing campaigns). You have to have your Google Ads account synced with GA in order for this feature to work.


google analytics audience list


Click on the “+New Audience” button to start creating segments.


Google Analytics already has a list of standard audience segments that you can leverage. Choose the ones that are important to your business (i.e. users, returning visitors, new visitors, visitors that completed a goal, etc).


You also have to choose the View that these lists are being populated from. For now just choose the default view (whatever is given). Then give your segment a name, and hit “Next Step”.


Google analytics audience definition


Choose your “Audience Destination” (we recommend publishing lists to all available destinations) and hit “Publish”.


Congratulations, you have just created a retargeting list! Next, try using the “Audience Builder” tool and get really creative.


Use the logic capabilities provided by the system to build your segments.


You can segment visitors that visit specific pages, are referred by certain sources, read your blog, spend a certain amount of time on your site, complete goals, are a certain age, use a certain device, etc. The possibilities are endless.


google analytics audience builder


Hold off on creating more audience segments until your views are established.


That’s all for Properties, it’s time to move on to Views.




Jump back to the Admin section of GA and click on the “View Settings” section in the 3rd column (or the furthest right column).


Update the “View Name” to “Raw Data”. This is a view that will have no filters, and as the name implies will contain data that is unadulterated.


Set your canonical domain on the “Website’s URL” field, set the time zone, and leave the “Default Page” and “Exclude URL Query Parameters” fields blank.


Set your preferred currency and leave the “Bot Filtering” field unchecked (remember, this is the “Raw Data” view and as such, nothing gets filtered).


Leave “Site Search Tracking” off and hit “Save”. Next, click on “Create View” at the top of the left hand sidebar.


google anlaytics create view


Repeat the same process except this time name your view “Filtered View” (the only difference is to check the “Bots” box in order to block them from muddying up your data).


As the name implies, this view will have filters on it, and will only contain data that is relevant and accurate (the “Raw Data” view is meant to serve as a background for comparison when looking at the Filtered View).


Before doing anything else, recall how the search console integration, the Google Ads integration, the “All Products” integration, and the audience lists all required a specific view that needed to be associated with them.


Well, the “Filtered View” is the view that you want to now go back and associate with those property attributes. Take a minute to do that.


Next, jump to the “User Management” section under “Filtered View”. Just like before, give permission and access to your people. However, the difference here is that they will only have permission to access the specific view and nothing else.


Skip the “Goals” and “Filters” sections because they will be covered later in this article.


The “Content Grouping” and “Channel Settings” sections relate to how data is displayed in your view. This can be skipped as the default data display suffices for most needs.


Jump to “Ecommerce Settings” if you have an eCommerce store (if you don’t, skip this step). Turn the switch for “Enable eCommerce Set Up” to the “On” position.


This helps track purchases, revenue, etc. For this to work, your developer will need to create a data layer that should be embedded in your shopping cart script (the data layer is what presents the values in the shopping cart in a way that GA can read them and display them in your reports).


“Calculated Metrics” allows you to create formulas that apply basic arithmetic to the measures in your reports. You may skip this for now as GA provides mostly what you need by default.


“Segments” are used to create custom dimensions in GA. Most dimensions needed come out of the box, but if (for example) you want to report on converters from a specific email campaign, then segments become useful.


The same logic that was used to segment your audience lists is used here as well. Get creative and try different combinations.


Google analytics segments


“Annotations” are markers associated with specific dates that contain text about an event (such as a Google algorithmic update). These markers are then overlaid on your reports adding depth to the insights one can gain from them.


The “Attribution Models” section is very important. This determines which campaign source gets credit for conversions (in the scenario where a visitor has hit your website through more than one channel).


There are various attribution models to choose from. Pick the one that suits your business best. Here is a list of attribution models that Google Analytics uses:


  • Linear – this gives equal credit across all campaign sources.
  • First Interaction – this gives 100% of credit to the first campaign source.
  • Last Interaction – this is the default model Google Analytics uses and gives 100% of credit to the last campaign source.
  • Time Decay – as time moves forward this model gives increasing credit to later campaign sources.
  • Position Based – gives most credit to first and last campaign sources (equal weightage to each), and gives less to the middle campaign sources (equal weightage to each).


If you are okay with using the default “Last Interaction” attribution model already set in GA then there’s nothing more that you need to do.


If, however, your business model requires something else then click on “+New Attribution Model” to begin.


google anlaytics attribution modeling


Start by naming your model. Then choose your model using the “Baseline Model” field and specify the “Lookback Window” (i.e. how long it takes for things to time out and reset the model).

Next, adjust the weightage of credit based on user engagement, and then apply any custom rules you need. Hit “Save”, and you’re done with Attribution Models.


Skip “Custom Channel Grouping” since the default channel grouping that GA has set is usually the best way to look at data in reports.


“Custom Alerts” are basically email/text alerts that you can set to receive when certain conditions are met (i.e. a certain traffic threshold is met, conversions are made, etc).


The “Scheduled Emails” section lists out any emails you may have scheduled (in queue) as a result of alerts.


The “Saved Reports” section lists out all saved reports. Use this when you frequently visualize data in a particular way that requires a lot of work. Once saved, you can always quickly jump back to the saved report to view your data.


The “Share Assets” section allows you to share assets with other team members (these can be custom audiences, segments, etc).


This wraps up the “Views” section of Google Analytics. Hopefully, by this point you are ready for the last part of set up, adding filters and setting goals.


Apply Your Filters


Google Analytics allows for very robust filters. This means that your data can be very clean. You can kick out spam, geo-target, exclude internal employees, etc from your reporting.


The best way to use Google Analytics filters is to create them at the account level and then apply them to the correct views.


Jump to the administrative section of GA, then under the “Accounts” column, click on “Filters”. Then click the “Add Filter” button.


google analytics filters


Name your filter and use the logic provided by Google Analytics to do one of many things (such as exclude spam, bots, and internal employees from your reports). Then apply the filter to your “Filtered View”.


Do this for every filter you create. The result will be accurate reports, and thus, better campaign targeting by your team.


Set Your Goals


The final step to complete the setup of your GA instance is to set your goals (the most important thing!). A goal can be anything that is important to your business. It could be an ecommerce sale, a phone call, a form fill, etc.


In the admin section, jump to the “Filtered View”, then click on “Goals”. Then click on “+New Goal” to begin creating goals. Choose the “Custom” goal option and hit “Continue”.


Then name your goal, choose the goal slot (start by taking “Goal ID 1 / Slot 1”). Most goals can be tracked by recording the URL of the thank you page that visitors are redirected to after they convert.


That being said, hit the “Destination” value in the “Type” field and then continue. In the next section input the URL of that thank you page. You may add a “Value” if you can quantify how much the conversion is worth.


If you have a shopping cart funnel, you can specify that path via the “Funnel” field.


Then hit “Verify” to test your goal. Once verified hit “Save”.




Many marketers fail to get Google Analytics right. Anyone can set it up, but as you can see, doing it the right way is a different story.


If you need help implementing your Google Analytics instance please don’t hesitate to reach out to us. The reward of dominating the competition and generating new revenue from marketing with better analytics is well worth it!



Have questions about your Google Analytics implementation? Feel free to ask them in the comments section below.

Ata Khan

Ata Khan

Ata is Co-Founder and Chief Operating Officer at Xoobo, a digital marketing agency that is on the bleeding edge of the industry. After leading in-house marketing teams at various organizations, Ata quickly realized the space was underserved and felt that someone needed to step in to bring clarity to the field and provide services that truly made a positive impact on businesses. Ata calls on more than 11 years of marketing experience to guide Xoobo on its journey across the industry. Most recently, he led marketing operations at billion dollar tech titan, Ellucian, where he built their marketing analytics infrastructure and generated over $30 million in pipeline bookings via marketing campaigns and various efforts. Before that he directed the SEO strategy for one of the nation’s largest home builder, Ryan Homes, where he was responsible for a ~25% year over year growth of search engine traffic.

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