Useful tips and resources for setting up and taking action from Google Analytics.

9 min readOct 24, 2022

There’s a famous quote attributed to Peter Drucker: “What gets measured, gets managed.”

By regularly measuring and analysing what happens on your website, you can better understand what is working and what is not, make better decisions about how to improve, and manage your site to better serve your customers.

That’s why web analytics are so important

And one of the most popular web analytics tools is Google Analytics.

What is Google Analytics?

Google Analytics is a tool to help you track your site’s traffic and help you make informed decisions on how to optimise your site.

It provides data on where users come from, what they do on your site, and how they interact with your content.

The data it provides can help you identify areas of improvement for your website and make improvements based on what you learn about the performance of different products, pages and how visitors interact with your content.

What is the difference between GA4 and Universal Analytics?

he version of Google Analytics that a lot of marketers know and feel comfortable with is called Universal Analytics.

Universal Analytics has been around since 2005 and uses a session-based approach to measuring user behaviour on your website.

But from 1st July 2023, Universal Analytics is no longer going to be supported. Google Analytics is moving to GA4.

Some people mistakenly believe GA4 is just an ‘upgrade’. But it’s not. It’s a whole new way of reviewing and analysing your data.

One of the biggest differences is that Universal Analytics uses a session-based data model, whereas GA4 uses a more flexible approach of events and parameters (which will need setting up and configuring correctly).

GA4 is also fully cross device and cross-platform and uses machine learning to help enhance the insights that Google Analytics delivers.

Where can I learn more about GA4?

If you’re feeling a bit worried that you don’t know enough about GA4 yet, you’re not on your own.

Many established and experienced marketers feel exactly the same.

Some GA4 resources I recommend to help get up to speed include:

Should I be setting up GA4 or Universal Analytics?

Right now, I would say set up both.

A lot of people in the marketing community are still getting to grips with GA4 and they prefer the comfort and familiarity of Universal Analytics.

We all need to start the transition over to GA4, but for now I would say the best route is to install both versions of Google Analytics so that any consultants, agencies and employees can use the version they are familiar with while it is still available.

Tips for a successful setup of Google Analytics

In the confines of a blog post, I’m probably not going to do as good a job as Google at explaining the steps you should go through for a successful Google Analytics setup.

The official links for the setup guides for Universal Analytics and GA4 are below:

Where I’m probably most valuable in offering insight and experience is on the common mistakes that I see on the Google Analytics accounts of clients. I’ve listed some of these below.

Not filtering out traffic from your company IP address

A common mistake is not filtering out traffic from your companies own IP address.

People within your business are going to have different browsing behaviours than legitimate customers. So if you’re tracking the visits of your employees within GA, it’s going to skew your analytics data.

In order to avoid this, you should make sure that you have a filter set up on your Google Analytics account so that it only includes traffic from outside of your company’s IP address (and IP addresses of remote workers regularly accessing the site)

This is easily done by going into your Admin settings and excluding IP addresses in the filters.

Not enabling enhanced e-commerce functionality

If you’re an online retailer and you haven’t enabled enhanced e-commerce functionality, you’re potentially missing out on a lot of valuable data.

Enhanced E-Commerce is a feature that allows you to track transaction details within Google Analytics, so you can see revenue breakdowns by transaction, product category, SKU and variety of other dimensions.

This can help you better understand what’s working and what isn’t, so that you can make more informed decisions about where to focus your efforts.

Not setting up UTM parameters correctly (or consistently)

You may not be familiar with the term “UTM parameters” but you’ve certainly seen them as you’ve been browsing the internet.

They tend to be the values that are in a URL after a question mark, and you’ll most commonly see them after clicking on an ad or some form of paid traffic.

They have a very basic function — they help Google Analytics to categorise data.

One of the mistakes I’ve commonly seen is inconsistent setup of UTM parameters, which can make it difficult to accurately analyse data.

It’s worth agreeing tagging rules within your business to make sure UTM parameters are consistently applied. If any team members are apprehensive about adding UTM parameters, there is a very useful campaign URL builder provided by Google.

Duplicate code

One of the first things I look for when I get access to a new GA account is an extremely low bounce rate, or an extremely high pages/session. This is often indicative of duplicate GA code (the same piece of code firing twice)

It’s easily done, often if developers have implemented GA directly and then the marketing team use a GA plugin. And although it doesn’t affect key metrics like number of sales or sessions, it can lead to some analysis being less accurate than it should be.

Not using annotations

One of the things I love about Google Analytics is the ability to add annotations to your account highlighting the dates that important changes were made to the site, or the dates that specific sales or promotions were running. This can help you (and others) put context around statistics when you come to review them in the future. But it’s a feature of GA that very few people use!

Some of the most valuable reports within Universal Analytics

I probably spend a few hours of each working day in Google Analytics for various businesses.

The reports I find most valuable are:

Acquisition Overview (Acquisition > Overview)

The acquisition report is probably the most popular ‘go to’ report for marketers. It helps you to understand where your site traffic is coming from and how each traffic source is performing from a variety of different perspectives (bounce rate, time on site, conversion rate). You’re able to drill down quite granularly into each traffic source if you have UTM parameters set up correctly.

Landing Pages (Behaviour > Site Content > Landing Pages)

The landing pages report analyses the entry points into your website. It’s often useful to look at metrics such as bounce rate, time on page and the conversion rate for any goals you might have set up.

If you use either ‘Source/Medium’ or ‘Campaign’ as a secondary dimension on this report, it can be really insightful in helping you understand how users coming to the site from different marketing channels behave on each landing page.

New vs Returning (Audience > Behaviour > New vs Returning)

How many people are new visitors to your website, and how many people are coming back for another look? Understanding your new vs returning customer ratio and how the different groups of customers behave can help you adapt your site to meet their different needs.

I often find it valuable to set up ‘segments’ of new users and returning users to help analyse different reports across Google Analytics.

Assisted Conversions (Conversions > Multi-Channel Funnels > Assisted Conversions)

Google Analytics typically uses a ‘last click’ model to attribute credit for a conversion.

This essentially means that if a visitor has been to your site 5 times before converting, it is the channel that drove the 5th visit that gets 100% of the credit for the conversion. Hardly fair on the channels that helped earlier in the journey, right?

The assisted conversions report can help you understand which channels are involved earlier in the sales process, but maybe aren’t getting full credit in the main dashboards.

Model Comparison Tool (Conversions > Multi-Channel Funnels > Model Comparison Tool)

Another report I like to help better understand the value of each channel is the model comparison tool. Here, you can look at the performance of each channel on a first touch, last touch, positional, linear and time decay (and depending on the nature of your business, data driven) attribution models.

Looking at how different channels and campaigns fare on different attribution models can often bring a new perspective on how you view them, and the action you might want to take.

Some of the powerful new features and reports within GA4

As I transition fully over to GA4 in the next 6–9 months, I’m going to be sharing everything I learn on this blog. If you’re interested in coming along for the journey, you can sign up for my email newsletters.

From what I’ve seen on GA4 so far, there are some exciting new developments that will help marketers and business owners with actionable analysis.

AI predictions and insights

Using machine learning and historic data, GA4 is able to predict purchase probability and deliver revenue predictions for the next 7 days. I can see how this can potentially be a really useful barometer for brands.

Machine learning to fill in data gaps

When any business implements cookie consent, they are likely to have some data loss from people who choose not to accept analytics cookies. At the minute, that data is just ‘lost’. In GA4, behavioural modelling is used to fill in the data gaps of the users who have declined analytics cookies. Is this an ideal scenario? No. Is it better than having missing data? In my opinion, absolutely.

Easily create custom reports

As a self-confessed data geek, the ‘explorations’ reports in GA4 make it really easy to start analysing website data from a variety of different perspectives. It’s a lot easier to set up custom reports and drill down into your data than Universal Analytics.

Anomaly detection

Another AI feature, anomaly detection allows Google Analytics to alert you when something that it thought was going to happen, doesn’t happen.

So, if you’re regularly making 100 sales per day and then one day you make 10, Google will flag that as an anomaly. This is a really nice feature that will help business owners and marketers stay more on the ball and react more quickly to issues on their site.

The next 6–9 months in analytics are going to be busy as businesses make the transition from Universal Analytics to GA4.

I completely understand the reluctance to move away from the comfort and familiarity of Universal Analytics. But once people understand the power and capabilities of GA4 I believe this will ease the transition.

If you’re interested in finding out more about GA4, I’m going to be positing regular updates over the next 6–9 months. Sign up to the Bright Cat email newsletter to be the first to know.

If you’re interested in someone managing the transition from UA to GA4 for you, please drop me an email and I’d be happy to discuss this in more detail.