How to build a solid Google Analytics 4 measurement plan [Step by step + free template]

If there’s one thing we learned during our work with over 100 companies, there’s a complete and total lack of strategic documentation despite all the data tracking in place. Now that’s a mouthful. We know. 
So, let’s try to understand what we mean by that. In the absence of a documented plan and a designated person responsible for implementing it and keeping it up-to-date, chaos will rise any time someone is asked to take over a businesses’ data analytics.

The tracking is already skewed beyond repair by the time this new person wraps his head around what is what. Trying to fix one thing here usually brings to light three other flaws there. And frustration is the least of the problems. Chaotic and disorganized data tracking costs the business money and generates opportunity losses.

Throughout this post, you’re going to find out how to design an efficient analytics measurement and technical plan so you can:

• Gain clarity over what you need to track & configure in your Analytics account
• Correctly integrate additional analytics implementations (without breaking your existing setups)
• Save precious time that’s usually wasted in unnecessary back and forth communication when working with new analytics hires.

Absolutely anyone part of your company’s analytics account can use this plan. From your marketing team, analytics specialists, to experts from outside the company whom you’ve hired to work on your analytics.

To help you form a better, and more structured understanding of how to create a robust plan, this post will walk you through our exact five-step methodology. While the first four steps focus on providing the answer to the question of WHAT needs to be measured, the last one will shift our attention towards HOW we’ll track our relevant metrics.

Here’s a sneak peek of what you’re about to discover along the way: 

• How to set your Measurement Plan to track for valuable insights 
• How to determine exactly what a Measurement Plan needs to include
• How to guarantee your Measurement Plan’s efficiency

Let’s get to it!

Step #1: Set Your Business Objectives & KPIs

Determining the metrics you’re going to track derives from looking at your main business objectives. As a result, the very first item on your to-do list is to make sure your Plan is aligned to these objectives & KPIs.

Let’s say you’re a software company. Your objectives are to increase revenue and grow your customer base. Based on these, we can derive the following measurable metrics:

Increase Revenue (KPI)

1. Number of purchases (metric)
2. Average order value (metric)
3. Revenue (metric)

Increase Customer Base (KPI)

1. Number of free trials (metric)
2. Conversion rate from free trial to customer (metric)

By outlining your Measurement Plan to Business Objectives you achieve a clearer understanding of what and how you need to track to get the most valuable insights.

So, next time you’ve set out to develop a Measurement Plan, make sure to chart your main objectives before moving on to the next step.

Step #2: Business Measurement Plan

This is the part where you’ll find out HOW you should be thinking about what metrics to measure to squeeze the most $$$ out of your analytics account.

The example above is nothing more than your average marketer’s idea of a Business Measurement Plan. Tracking sales, revenue, sign-ups, etc.

For insights that can lead to real business growth, you need a more in-depth level analysis.

Here’s what we mean by that.

Let’s say you’re given the task of increasing the conversion rate of an e-commerce business that generates tons of traffic but gets very few sales.

How would you tackle this task?

A good starting point would be to understand the behavioral patterns of high-converting visitors vs. low-converting visitors. 

Looking into how visitors interact with your website filters would be yet another important micro behavior to look at.

• Are your top customers using filters more often? 
• Which type of filter brings in the highest conversion rate? What about the average order value? 
• Is there a certain preference towards filter types depending on the channels they’re coming from or the category they’re visiting? 

Find out the answers to these questions and you may find yourself sitting on a gold mine. 

This is where a more in-depth Measurement Plan springs into action. By tracking the right metrics (like filter usage), you can form a big picture of your visitors’ behavior. 
There is no exhaustive list of actions you should be tracking. Everything is different from business to business.

But to make sure you never leave any important metric out of your Measurement Plan, think about all the actions users can take on your website. Then, make sure to track them so you can, later on, do a more in-depth analysis that can lead to revenue-boosting insights. 

Step #3: Check Data Accuracy

No analytics tool offers a one-size-fits-all solution. And, by the looks of it, that’s not going to change anytime soon. 

This is why we highly recommend you take data accuracy as seriously as possible. Since any business decision is – or at least it should be –  based on data, skewed data can have a devastating impact. 

Here, at Growth Savvy, any time we work with our analytics clients, we’ll often start by doing a health check on their analytics account(s). Without this crucial step, we risk drawing conclusions based on inaccurate data.

This is where the data accuracy action plan comes into place. This is an essential part of any ‘Analytics Strategic Plan’.

 Here are a few examples of configurations that help improve data accuracy:

Step #4: Enrich Your Data With Additional Information

Being able to capture data from multiple customer touchpoints is something every CMO wishes for his birthday. No, seriously. Something like this would be huge.

Right now, this can be done to some extent using Google Analytics.

• Integrating offline data with Google Analytics to understand the full journey of your customer.
• Integrating CRM data with Google Analytics to create Google Ads Re-Marketing Audiences.
• Or, you can simply integrate Google Ads data with Google Analytics to understand what goes on beyond clicks and conversion rate.

There are virtually an endless number of options to help enrich our data and easily connect the dots. However, we recommend you explore the possibilities that make the most sense for you.

Step #5: Create a Techincal Implementation Plan

Everything we covered so far will help you gain more clarity about your analytics setup. Plus, it also serves the purpose of helping you stay organized and on the same page as your team when it comes to tracking.

This final step dives into HOW to track each meter.

Here’s something for you to take into account: a technical plan doesn’t include the coding lines or every step of the implementation process. However, it does enclose the main guidelines.
Web analytics implementations deteriorate over time, as the site gets updated. Because of this, before making any change, take a look at the implementation plan and see what it might affect. 

Having said that, let’s explore what you should document:

• GA Settings Variables
• Events
• Goals
• Custom Metrics & Dimensions

Warning! We’re about to turn our geek on.

GA Settings Variable

Last year, Google Tag Manager (GTM) released a new feature called GA Settings Variable. The feature adds a bit of scalability to building tags. Which is great.

That’s why the GTM tracking implementation journey should always start with your GA Settings Variable. This will be a part of any tag you create and set the tone for what Google Analytics will track.

Here are some examples of general settings you might need to attach to every hit:

• settings for cross-domain tracking
• IP anonymization
• advertising features enabled etc.

Events

Top of mind questions when I see events within an analytics account are: 

1. What does this event track, on what page, and when is it triggered?
2. Is it implemented in GTM or is it hardcoded? 
3. Does the event impact metrics like bounce rate or session duration?

Now would probably be a good time to introduce…

The Analytics Technical Plan (events section)

Any time an event category is not sufficiently self-explanatory…

Any time someone new doesn’t know what an event category stands for…

Whenever the website structure changes and your team has to adapt the analytics implementations without breaking your entire setup… 

This plan will feel like a Godsent gift that lights a beacon of hope amidst all the chaos.

Goals

Most of the time, events are interconnected with goals [event-based goals]. However, when it comes to goals, you’re limited in terms of how many you can have.

As you may already be aware, a Google Analytics account only allows you to set up to 20 goals. Plus, once you save a goal, you won’t be able to delete it – only overwrite it.

Even with annotations, this can be confusing when looking at historical data across the years. 

This is why we can’t stress enough the importance of using your available goals wisely, according to your Plan. 

Our recommendation is to divide them into two main goal types:

1. Macro Goals
2. Micro Goals

Once you’ve done that, make sure to assign a few details so the goal becomes crystal clear:

• Goal type: destination, event-based,  duration, pages/screens per session
• Additional condition
• Funnel path (if required)

Custom Metrics & Dimensions

We’ve already established the importance of asking more in-depth questions when looking at your analytics data. 

Well, custom dimensions & metrics are a big part of that. 

The User ID dimension can help you collect additional information about your visitors. 

You can either collect status information – like whether they’re logged id in their account or not – or more descriptive information. 

For example, you can find out if your users filled out a form that asked about their profession. 

You can collect this information as a user-level custom dimension, and use it to look at your users’ behavioral patterns based on their profession.

This article from Moz highlights some additional examples and goes into how to set up custom dimensions to measure performance.

Conclusion

Often your analytics account can get out of hand, and you end up spending hours trying to figure out how things work and why it’s showing the data it’s showing. 

The consequences range from confusion, loss of valuable historical data, and, more troublesome than any, bad decision-making. 

By having a measurement plan in place, your team, and anyone else with access to your analytic account will have some much-needed clarity on everything going on. 

Next time you’re tasked with creating a Measurement Plan, work your way through the five-step methodology we’ve shared across this post.

1. Start by setting your business objectives & KPIs
2. Draft out your in-depth analytics measurement plan
3. Make sure to eliminate any potentially skewed data 
4. Enrich your data with additional information
5. Create a technical implementation plan

And remember: a solid Measurement Plan is not something you can set and forget. Creating it is just as important as updating it every time someone makes a change. Otherwise, as the business evolves, data quality degrades.