It’s very easy to go on Google Analytics and think you know how to use it because the interface is pretty user-friendly. I know, that’s what I did the first year of using Google Analytics for one of my eCommerce stores.
I was searching for certain data, moving flawlessly in the platform and I always ended finding what I needed. The truth is I wasn’t finding the inefficiencies and that’s why you should use Google Analytics.
The data you find on google analytics serves on purpose and it is to find inefficiencies. It’s not about tapping yourself on the back for doing great work (although you should sometimes).
An article like this would have made a huge difference if I read it when I started using Google Analytics, so I hope it has a good impact on the way you’ll see the platform moving forward.
We’ll probably use GA for Google Analytics during the article. I hope you don’t mind.
Table of contents
1. Start with questions in Google Analytics
3. Linking events to your Google Analytics goals
4. Bounce rates are not what they seem
6. Enhanced eCommerce – horizontal funnel
7. Testing tool integrated with Google Analytics
8 – Knowing precisely what you want
9. Become a Google Analytics developer
10. Custom reports matter in Google Analytics
11. Why not automating repetitive reports?
12. Make sure you don’t have bugs
13. View your Google Analytics setup
15. Solve cross-domain or subdomain issues
17. Leveraging custom dimensions
18. Letting Google Analytics calculate for you
19. Using filters
20. Custom alerts
21. Sampling limitations in Google Analytics
23. Using what people search to create articles
24. Integrating pre-purchase & post-purchase analytics data
25. Attribution, should you worry?
#1 – Start with questions in Google Analytics
The basis of Google Analytics is to have questions in order to translate analytics into business value. This means you need to know what data impacts positively or negatively the business revenue.
This is one of the reasons why using checklists made by experts is often not the best solution. Your business might need to know what products people buy the most after buying a certain product instead of which time people buy the most (while this might also be relevant data).
You get the point. Searching for data is a case-by-case scenario. Everybody knows how to find data on Google Analytics but knowing which data impacts revenue is where the big players make a huge difference. Looking at the data in the wrong way is what Avinash Kaushik calls data puke. One of the most productive and useful ways to search and retrieve data is to export google analytics data.
#2 – Set your goals
Your Google Analytics needs goals. Simple as that. I mean, you can look around for data, but it won’t mean anything. You need to know what the end goal is when people visit your website and then find what affects that.
Do you want to get leads? Do you want to get sales? What is the winning situation for you once people are on your website? This represents 90%+ of Google Analytics utility, helping improve the ultimate objective.
One thing I always recommend to my clients is to create goals and segment them inside a funnel. In the eCommerce world, this translates into:
View Product >> Add To Cart >> Initiate Checkout >> Purchase
This way you can analyze each step of the process and see where you have a big weak point that needs to be taken care of. You can definitely see GA as a roadmap in that sense. If you don’t know how to set up goals, I recommend Google’s resource on the subject.
You have three options at the goal level:
- Goal Template
- Custom Goals
- Smart Goals
#3 – Linking events to your Google Analytics goals
It’s one thing to have goals it’s another to have events. While you might realize that 50% of your traffic is leaving after they add to the cart, you might not know if they watched a video on that page or if they signed up to your newsletter.
These events might give you important insights as to why people didn’t move the needle or if there’s even a correlation with the event you chose in the first place.
The events on GA have the following structure:
This is a subject I could really dive deep into especially with all the options of events. I’ll link you guys up with a resource I found useful back in the days.
#4 – Bounce rates are not what they seem
The bounce rate is essentially when someone goes on one page of your site and doesn’t trigger any interaction worthy event. The thing is though, you can choose what are worthy interaction events in your google analytics.
You might choose to say that when someone watches a video or enters their email address, it means they interacted with your site. This is why you have to make sure you control all the variables so the bounce rate actually means something. This is called the adjusted bounce rate.
The synonym of the bounce rate is wasted traffic. It’s traffic that enters your website, looks around, and leaves. On the flip side, if that traffic took an action you deem not wasted then you have to change your criteria so your bounce rate truly reflects what it’s supposed to in the first place.
#5 – Funnels set up
A good way to understand the way people end up giving you what your business wants is to set up a funnel in Google Analytics. This helps you find where people leave your website in their process towards the ultimate objective you set for your business website.
Most funnel, especially in eCommerce, follow the same sequence. Here are the steps:
Add To Cart >> Initiate Checkout >> Purchased
The more steps you can create (have to be essential to the process) the better because it gives you more points of reference to work on. These actions have to be necessary for the person to go from wanting something to buy it or whatever objective your business have when people visit your website.
#6 – Enhanced eCommerce – horizontal funnel
If you want to level up your eCommerce Google Analytics game then you need to use the enhanced eCommerce by using the “Shopping Behaviour Report”.
Why should you use it? There are many limitations to the classic funnel. The classic funnel is not bad, it’s actually pretty good, but you can’t segment your audience based on the user’s quality such as their device, etc.
On the horizontal funnel, you can also segment & create powerful audiences and use them inside Google Adwords or Double Click. Audiences such as iPhone users who added products to the cart.
This is what the horizontal funnel looks like in real life.
Now you might wonder why using the classic funnel if the horizontal funnel has the same function and also enables you to segment users when looking at the data.
My answer is you don’t, but I love the funnel display and the way it looks. Looking at good visual representations of data makes a big difference in creating a better understanding.
#7 – Testing tool integrated with Google Analytics
I’m not saying your A/B testing tool is limited or am I? You might get to know which test does well overall, but by integrating with GA you’ll find that you have way more segmentation abilities.
You can, for instance, know how your test affected revenue, which is often a pain in the ass to find on your A/B testing tool. My point is you can dive deeper into the data which is essential to understand your business.
For A/B testing tool, I recommend Unbounce and I have no affiliation to them, I just love what they do.
#8 – Knowing precisely what you want
This is a concept that a lot of people don’t seem to understand. The average of everything doesn’t mean everything inside is good or bad. The best example I can give is the stock market.
You can’t be an investor and only look at the indexes, because while most companies are doing well and others are performing. The economy is doing well, and your investments could go sour.
In the same sense, if you don’t dive deep enough in your data and just look at it from a birds-eye view then you don’t know anything about your business.
You might realize that people from Africa and South America mess up all your funnel data, but when you look at the United States your conversions are really good.
I could find a million examples to prove this point, but your role remains to dive deeper into the data, question things and find what’s relevant to your business. For example, what needs to be improved, where you should spend your traffic, etc.
#9 – Become a Google Analytics developer
There’s something called RegEx, it means regular expressions. It’s a sequence of symbol and characters that enables you to create the following:
- One goal matching multiple-goal pages
- You can put pages that have the same goal together
- Fine-tune your goals
Learning RegEx can definitely improve your Google Analytics skills. It’s honestly pretty intuitive & logical, after doing it a couple of times you remember it pretty easily.
If you want to learn more, I recommend you read this fantastic PDF by Luna.
#10 – Custom reports matter in Google Analytics
Custom reports allow you to create your own reports & dashboard directly on Google’s interface. Google’s definition is pretty straightforward:
“A Custom Report is a report that you create. You pick the dimensions (City and Browser, for example) and metrics (Sessions, Pageviews, and Bounce Rate, for example) and decide how they should be displayed. You must specify at least one dimension and one metric.”
There are three types of custom reports :
- Map overlay: a global map with colours to indicate metrics.
- Flat table: sortable data table.
- Explore simple reports with line graphs & data tables.
You can find custom reports in the “Customization” section under “Custom Reports”. I won’t speak too long about the nuances as this could be the subject of an entire article, but if you want to learn more about the subject, I recommend this great article from Monster Insights.
#11 – Why not automating repetitive reports?
In Google Analytics, it’s crucial to know the goals of your business as we’ve talked about earlier. The thing is once you know your goals, you’ll start to realize that certain reports become repetitive. How can you make the process faster? Automate your reports.
Here are two ways you can automate your reporting inside Google Analytics.
- Using Google API studio & Google Sheets
- Data Studio
#12 – Make sure you don’t have bugs
You always need to remember that no amount of pretty design or branding can make a difference if you have bugs on your website or your loading speed is slower than a turtle.
One amazing feature of Google Analytics is its ability to give you insight and information on bugs and website speed. For example, you can figure out if you have bugs on certain device types. You simply have to go inside GA and click on those buttons:
Audience >> Technology >> Browser & OS Report
IMPORTANT NOTE: look at one browser at a time because, remember, averages don’t mean much. Your Chrome browser might need some fixing while all the other browsers are cruising (if ya know what I mean).
To see if your website is faster than a mafia yacht fleeing marine police:
Behaviour >> Speed >> Page Timings
You can then go Google PageSpeed Insights to find the ways in which you can fix issues (if you have some).
Looks like www.example.com is doing pretty well.
#13 – View your Google Analytics setup
Every business is different and has its own set of principles, but in terms of setting up views on your google analytics, it’s pretty universal for all businesses. There are 3 types of views:
- Master View
- Raw Data View
- Sandbox View
The raw data view is the one you haven’t edited at all. Adding filters changes the data permanently so it’s important to have a raw data view as well.
Your sandbox view is where you play and try new filters that you would later use inside your master view. The master view is where all your successful sandbox test ends up.
This can be hard to understand especially if you don’t know what a view is. I recommend looking at this article on Google to further understand.
#14 – Trusting the data
It’s often overlooked but setting up your data so you can trust it is very important. If you don’t trust the data, everything is worthless because you can’t draw conclusions from something false in the first place.
Trusting the data also means which numbers matter in your business enough for you to care and see a big impact if you work on fixing or improving the metrics you receive.
Remember, data only tells you which way you went after you tried something new in order to course-correct. Many people just look at their data every day without doing anything, that’s no way to leverage Google Analytics.
#15 – Solve cross-domain or subdomain issues
Let me give you an example of the problem so you stop scratching wondering what that means.
Imagine if a guy went on your website and added a product to the cart. Imagine the same guy then came back and added the same product to the cart and decided to buy. Google Analytics would track it as two different users when in fact it was only one user.
How can you know there’s an issue in the first place? Luckily for you, there’s a Chrome Extension called GA Debugger that does that for you. Gotta love google.
#16 – Campaign tracking audit
One very useful feature of Google Analytics is to track campaign results which essentially tells you the true results of your campaign within different channels you are using.
UTM tags are the links that track your campaigns and gives the data to Google Analytics. They are made of five elements:
- Source: channel from where the traffic is coming from.
- Campaign: segmenting your campaigns.
- Content: segmenting your ad creatives.
- Term: often used as a PPC keyword.
If you’re still confused, check out this Cardinal Path Google Spreadsheet to understand what you should put in each part of the UTM tag.
The most important rules in campaign tagging are to stay organized & simple.
#17 – Leveraging custom dimensions
While there are many built-in dimensions in Google Analytics, you might not always find exactly what your business needs in terms of analysis. This is where custom dimensions come in.
I generally use custom dimensions to connect Google Analytics metrics with non-Google Analytics metrics. For example, when you get a phone call and you want to link it to a certain IP address or customer.
Apart from that, you can use custom dimensions to track your A/B tests and get the deep data you wouldn’t get on A/B tests platforms.
Here’s an article to further understand custom dimensions and set them up.
#18 – Letting Google Analytics calculate for you
You should definitely look into getting calculated metrics as they will greatly improve your experience of Google Analytics.
For example, if your eCommerce order value includes shipping, you can ask Google Analytics to show revenue less shipping to get a better view of actual revenue per product.
Another example would be to calculate your Average Order Value (AOV) if you’re in the eCommerce game which is the amount of revenue divided by the number of customers.
I would recommend reading this article to get ideas of calculated metrics you might want to use.
Be careful though, you can only have 5 calculated metrics. Make sure you use them wisely.
#19 – Using filters
Filters are essentially another way to segment your data and get a better understanding of things. There’s not much to say.
Here are quick ideas of filters to use:
- Including/Excluding internal IPs
- Lowercase campaign tags
- Lowercase page URL’s
- Lowercase site search terms
#20 – Custom alerts
Custom alerts serve one purpose for me. It’s to tell me when my clients have a traffic, conversion or revenue dip. It usually means something is broken and we need to fix it.
Looking at your data every day to check something that could be automated is not very efficient (and as you probably know I’m all about efficiency).
Here’s how you add custom alerts:
View >> Open Reports >> Customization >> Custom Alert >> Manage Custom Alerts >> New Alert
Enjoy this new gadget if you haven’t used it before.
#21 – Sampling limitations in Google Analytics
When you get past a certain amount of traffic, Google Analytics gives you only a sample of your data to analyze. Here’s how it looks like:
That’s an issue because you don’t get to analyze your entire data. Simple as that. If the sample is based on 90% of your data then you might not care, but if the sample represents 25% of your traffic then it might have a big enough impact for you to look for solutions.
Here are a few solutions to this problem:
- Adjust your date range
- Use the Standard Report
- Create new views with filters
- Reduce the amount of traffic per property
- Sample your data by modifying tracking codes
- Use Google analytics API
- Use Google Analytics Premium
- Use Adobe Analytics
- Use BigQuery
If that problem becomes persistent then it might be best to look into Google Analytics Premium, Adobe Analytics or BigQuery.
#22 – Analyzing data in R
I’ll go quickly over this because it’s pretty complicated. Using Data in R can help you build impressive visualizations, automate reports and run models that you could not create in excel.
Some of those models include the Markov attribution model, time of the day data heat maps as well as creating personas based on PCA/Factor analysis.
#23 – Using what people search to create articles
If you want some extra efficient ideas for your content, then you should create what people are looking for? Happy we agree on this. Now let me tell you how easy it is to know what’s in your customer’s mind.
If you have set up a site search on your website, you can follow this path to find what people are searching for and in what quantities (if you haven’t click on the link):
Behaviour >> Site Search >> Search Terms
Want to do it even better? Compare the results in terms of the time period to see which searches are becoming more and more popular. This way you know what the trends are.
#24 – Integrating pre-purchase & post-purchase analytics data
I love examples so I’ll make one for ya. What if the people who read your “about us” page were ending up buying more from you in the long run? Wouldn’t you want to know that?
This is actually something we realized for a lot of our eCommerce clients because the people who read the “about us” page were often more interested in the brand than the actual product.
Nike has one of my favourite about us page. Nike nails it as usual.
Let’s just say it’s no easy feature to be able to connect your CRM to Google Analytics, it takes a lot of energy, but we’re here for that. You can use a company like Fivetran to replicate your data.
#25 – Attribution, should you worry?
Here’s why attribution matters. You need to know where the revenue came from so you can spend more there, right? What if people buy in a window of 7 days and they came from different places? Then you’re kinda screwed. Let me explain…
Imagine someone clicked on your Facebook ad, visited your website and left. Then, 4 days later, that same individual saw an ad of yours on Google, clicked and then decided to buy. Google might have attributed the sale to Facebook & Google which would mess up your metrics.
It’s good if you want to show off your screenshot to other scammy online marketers, but not so good if you actually want to grow your business.
Lol, I swear this is (almost) every online marketer ever.
The first thing to check is your purchase window. If people buy within 1-2 days, then you might not even care about the attribution problem because they might only use 1 or 2 touchpoints and so double attribution would rarely (if ever) happen.
You’re not in the dark, GA has many attribution models inside their platform already. You can choose:
- Last click
- First click
- Time decay
- Linear models
Google has also recently announced that they will launch Google Attribution, so keep an eye on that (it’s good news).
What’s next with Google Analytics?
Remember, Google Analytics is not just a cool platform to explore like you would watch cat videos on Youtube but actually a goldmine of information to improve your marketing efforts if you know what you are looking for.
Data is gaining a lot of importance because there’s nothing like raw feedback to succeed. If you need a truth-teller, your data will do just that.