Other marketing analytics options (such as HubSpot) can give you all the data you need with much less work. HubSpot users can follow these simple instructions for adding GA. For more, read our guide to installing the Google Analytics tracking code on your site. GA lets you create custom dimensions and metrics from Analytics data plus non-Analytics data. You can apply up to four segments at a time to any report. Because HubSpot is a SaaS company, not an ecommerce business, I look at goal completions per user, pageviews per user, and sessions per user by Acquisition Channel. All Pages Let’s start with Site Content > All Pages. page load time and page value Looking at these two together helps you find slow-loading pages that are valuable to your bottom line (even if they don’t get a ton of traffic), making them a high priority to fix First things first: if users can search your website, make sure you’ve set up Site Search in GA. You must enable it for every view separately (here are the step-by-step instructions). I won’t go into any more detail here, but I recommend reading the following resources if you want to know more: Google Analytics Conversion Reports If you have a website, you have an objective — probably several — for the people who visit your site. There are four main types of goals: Destination: this goal is completed when a user reaches a specific page, like a product page, order confirmation page, or thank you page Event: this goal is completed when a predefined event fires (like the Events you can set up as, well, Events — think watching a video or sharing something to social media) Duration: this goal is completed when a user’s session lasts longer than a pre-set time Pages/screens per session: this goal is completed when a user views a specific number of pages (or screens for an app) per session The first two are insanely useful. This report allows you to see the last three pages a user visited before completing the goal.
Are you confused — even intimidated — by Google Analytics? Good news: you’re not alone. GA is notoriously complicated.
In fact, when I first started to delve into GA’s waters, I wondered if I’d ever truly get it. There were so many concepts to learn and reports to run. How did people ever conquer this thing?!?!
Lots and lots of reading and trial and error, it turns out. I’m not saying I’ve reached total mastery — there’s always something new to pick up — but I’m vastly more comfortable.
And I want you to be, too. So here’s the cheat sheet to everything I’ve learned over the years. This guide might be long, but it’ll take you from zero to hero in 6,000 words. And if you still have questions, let me know! I’m @ajavuu on Twitter.
Time for a lightning round of questions.
What is Google Analytics?
GA is an analytics tool that gives you an extremely in-depth look at your website and/or app performance. It integrates with all of Google’s marketing products (including Google Ads, Search Console, and Data Studio) making it a popular choice for anyone using multiple Google tools.
Should you use Google Analytics?
If you want a lot of data — and more importantly, have the time and ability to analyze and act on it — GA is a great fit. However, if you’re looking for something that’s easy to set up and quick to learn, you’ll be disappointed. GA is definitely a time commitment: to implement and get onboarded, to maintain, and to use. Other marketing analytics options (such as HubSpot) can give you all the data you need with much less work.
Is Google Analytics free?
There is a free and paid version of GA (the latter is called Analytics 360). Small and medium-sized businesses will likely get all the features you need from the free version. Enterprise businesses need to upgrade — at least if you want advanced funnel reporting and attribution modeling; roll-up reporting; more views, dimensions, and metrics per property; and unlimited and unsampled data.
Paying for 360 also gives you access to dedicated support, including your own account manager. This alone can make the subscription fee worth it.
And about that subscription fee? It’s not cheap. Analytics 360 begins at $150,000 per year (invoiced monthly) and increases after your site receives more than one billion monthly hits.
360’s cost will price out many businesses. However, if you have the budget for both the service and an agency or in-house analyst to manage your analytics operations, consider investing.
With that out of the way, let’s get to the good stuff.
How to Use Google Analytics
- Create an account, if you haven’t already.
- Add the name, URL, and industry of the website you want to track.
- Add this code directly after the <head> tag of your site. (More on this below.)
- Visit your GA portal and verify the code is working by looking at the “Real-Time reports” section while clicking around on your site in a different tab or on your phone. The report should show at least one visitor to the site (that’s you!)
Do you need to add the GA code to every page of your site?
That’s a lot of manual work — especially if your website has more than 50 pages. Plus, what happens when you create new pages? Do you need to add the tag every time?!?
Relax, because the short answer is: no. The longer answer: you only need to add the tag to every page template. So, if you have one page type on your site (meaning every individual page uses the same header module), you only need to add it to that module — and it’ll be applied to every page.
If you have two page types, you’d need to paste the code into the two separate header modules. Three page types? Three header modules.
And if you use a CMS like HubSpot or WordPress, this task is even easier. These tools come with a separate field where you paste your tracking code just once. HubSpot users can follow these simple instructions for adding GA.
For more, read our guide to installing the Google Analytics tracking code on your site.
Google Analytics Hierarchy
To set up GA properly, you must understand the various layers.
The organization is the highest level. It represents a company. For example, our organization is HubSpot, Inc. One organization can encompass multiple GA accounts.
Organizations are recommended for larger businesses, but not mandatory.
Accounts are not optional. Using Google Analytics requires at least one (sometimes several) accounts.
An account doesn’t mean a user account. I can log into the HubSpot Google Analytics accounts using my Google email ID. HubSpot’s head of technical SEO can also log into the same account using his Google email ID. Our historical optimization specialist can also log into the same account using his Google email ID.
- You can assign one property to each account or multiple properties to one account. Every account can hold up to 50 properties.
- You can give user permissions for an entire Analytics account, a property in an account, or a view in a property.
You might be wondering, “What’s better: creating a new account for every property or adding every account to the same property?”
It depends on your use case and goals.
For example, suppose you have one website — the Stark Industries corporate site — and five subdirectories, including the Stark Industries blog, careers section, media resources, case studies, and investor relations information. You want to create separate properties for each subdirectory so the people on each team can look at how their portion of the site is performing, as well as the larger site.
But maybe you have another site that discusses Tony Stark’s work with S.H.I.E.L.D. You want the S.H.I.E.L.D. team to see data for this subdirectory, but you don’t want them to see data for the rest of the website. You create a new account and property for the S.H.I.E.L.D. site.
A property is a website or app. Each property can support up to 25 views.
At the minimum, you need two views per property:
- One with zero configuration — essentially the “raw” version of the view
- One with filters set up to exclude any traffic from within your company (i.e. a filter for your IP address) as well as bots and spam traffic
A view only captures the information after your filters and configured settings have been applied. And once you delete a view, that data is gone forever. For those reasons, it’s critical to keep an unfiltered view of your data.
Google Analytics Dimensions and Metrics
To use GA successfully, you need to understand dimensions versus metrics. I’ve found the easiest way to think about it is:
- Dimensions = categorical variables. Simple examples include names, colors, and places.
- Metrics = quantitative variables. Basic examples include age, temperature, and population.
Or as my Data Analytics professor put it, “Metrics are what you can do math on.” Not the most eloquent phrasing, but it works.
- Landing page
- Customer type
- Bounce rate
- Session duration
In any GA report, your dimensions are your rows and your metrics are your columns.
GA lets you create custom dimensions and metrics from Analytics data plus non-Analytics data. To give you an idea, suppose you track the membership type of customers who have created an account in your CRM. You could combine this information with pageviews to see pageviews by member type.
Or maybe you run a blog. If you want to understand how audience engagement impacts other metrics (like conversions, pages per session, etc.), you could create three custom dimensions for each type of reader:
- Advocate: user who shared one-plus posts on social media
- Subscriber: user who signed up for your email list
- Customer: user who purchased premium access
Using these dimensions will give you invaluable information. Follow GA’s instructions to set up custom dimensions and metrics.
An audience is a group of users that have something in common. That commonality could be anything: maybe you’re targeting consumers in Australia, so you have an “Australian audience,” or you want to sell to millennials, so you have a “25-34 audience.”
GA comes with several built-in audiences (including the two I just mentioned, location and age). You don’t need to do a thing to set these up — once you have the tracking code installed, GA will automatically break down your visitor data into these audience reports.
However, you can also create custom audiences. Perhaps you’re only interested in Australian millennials; you’d need to make a custom audience that only includes visitors who are A) in Australia and B) between the ages of 25 and 34.
Creating an audience is fairly easy. Honestly, the hardest part is figuring out what you’re trying to accomplish and then identifying the user characteristics that’ll help you do that.
Once you’ve done that, follow these instructions to create a new audience segment. From there you can import a segment to use as the basis for your Audience Report.
That brings us to the next question:
A segment is a subset of your data. I like to picture an entire pizza made up of all different slices — one slice has pesto and mozzarella, another has sausages and spicy peppers, another has ham and pineapple, and so on. Metaphorically speaking, each slice is a segment.
You can create segments based on:
- Users (e.g. users who have bought something on your site before, users who have signed up for a consultation, etc.)
- Sessions (e.g. all sessions that were generated from a specific marketing campaign, all sessions where a pricing page was viewed)
- Hits (e.g. all hits where the purchase exceeded $85, all hits where a specific product was added to the cart)
Like audiences, GA provides you with several segments. I wouldn’t stop there: you can get incredibly granular with your segments.
To give you some inspiration, here are a few of HubSpot’s segments:
- Users who viewed a specific product page and watched the demo video
- Users who viewed the same product page and didn’t watch the demo video
- Users who view a specific Academy course page
- Users who view a specific Academy lesson page
- Users who view a blog post and a product page
The sky is your limit — well, that, and GA’s segment cap.
You can apply up to four segments at a time to any report.
Google Analytics Reports
GA’s left-hand sidebar can be a bit overwhelming. You’ve got six reporting options (all with confusing, vague names), and clicking on any of those only gives you more options.
Let’s walk through each report together.
The Google Analytics Real-Time Report
As the name suggests, the Real-Time report gives you insight into what’s happening on your site at this very moment. You can see how many visitors are on your site, which pages they’re visiting, which social platforms they’re coming from, where they’re located, and more.
While this report is fun to look at occasionally, it’s probably the least valuable. Here are some ways to use Real-Time:
- See how much traffic you’re getting from a new social or blog post
- Know immediately if a one-day sale or event is driving views and/or conversions
- Make sure tracking URLs and custom events that you’ve just set up are working as they should
These are useful, but as you’ll see, the other reports pack a far greater punch.
The Google Analytics Audience Report
This report gives you a high-level overview for the property you’re currently looking at.
Underneath “Overview,” you’ll see “Audiences,” as well as expandable menus for “Demographics,” “Interests,” “Geo,” “Behavior,” “Technology,” “Mobile,” “Cross-Device,” “Custom,” and “Benchmarking.” Explore each of these sections to get a sense of what they can tell you about your visitors.
Every section describes an audience.
Whoever named this report belongs in the same group as the person who named guinea pigs: “active users” doesn’t refer to users currently on your site — that’s the Real-Time report — and guinea pigs are neither pigs nor from Guinea.
The Active Users report shows you the number of users who visited in the last day (1-day active users), week (7-day active users), two weeks (14-day active users), and four weeks (28-day active users.)
If you have more 1-day users than longer-term ones, you’re struggling with retention. People aren’t coming back to your site or app — you need to figure out why.
I’d also recommend looking at this report with various segments; for instance, perhaps you see that users in a certain age bracket have much better retention than the average.
First things first: do you need a refresher on Customer Lifetime Value (CLV) and how to calculate it? We’ve got you.
The Lifetime Value report gives you a sense of how valuable users are to your company. You can see lifetime value for, say, the users you generated from email marketing versus the ones you acquired from organic search. Armed with this information, you can decide which channel to invest more in.
A few notes: Lifetime Value is capped at 90 days. The Acquisition date range, however — which you can adjust — is available from March 2017 onward. This range reflects all the users you acquired in that time frame.
Imagine you’re interested in looking at transactions per user for users you acquired in the week before Black Friday. You’d adjust the date range to that week specifically. Then you’d see the average transactions per user for that cohort over the following 90 days.
Because HubSpot is a SaaS company, not an ecommerce business, I look at goal completions per user, pageviews per user, and sessions per user by Acquisition Channel.
If my team has recently wrapped up a marketing campaign, I’ll look at the same metrics by Acquisition Campaign.
But if you are in ecommerce and want to see transaction and revenue data, you’ll need to have ecommerce tracking set up. I recommend this excellent blog post on tracking CLV with custom dimensions and metrics as well.
You should also give this explanation of why you shouldn’t track CLV in GA a read.
(By the way, here’s how to track revenue in HubSpot.)
Some people have gone so far as to call Cohort Analysis “the single most powerful report in GA.”
So, how does it work? This report groups users by one characteristic — so far, “Acquisition Date” is the only “Cohort Type” you can use. By the way, Acquisition Date is the day a user first visited your website.
You have several options from there.
- First, pick your cohort size: day, week, or month.
- Next, pick your metric, or what you want to explore for this cohort. It can be further broken down into Per user, Retention, and Total.
- Per user means the total count of that metric divided by the cohort size. So if you choose Transactions per user, for…