Find out how to create a measurement plan to accurately track the impact your website is having on your top-line business objectives
Julian Erbsloeh
A measurement plan is a document that translates your top-line business objectives into dimensions, parameters, and metrics you can measure on your website. It provides a robust framework for customised web analytics configuration and forms a vital part of your broader digital marketing strategy.
The plan helps you understand how your digital channels work together most effectively to achieve your KPIs.
For us, this sounds like common sense, but you'd be surprised how the analytics and data team is still met with silence and confused looks when asking simple questions such as:
What do you need your website to do for your business?
What are the critical conversion points you need to measure?
Creating a robust measurement framework is a core element of an advanced configuration of Google Analytics 4 (GA4), usually preceded by an audit of the current setup. Without exception, every online business needs to have a measurement plan.
Many great blogs exist on the subject (Avinash Kaushik's post is an old goodie worth reading). Google also provides many good resources on the topic, for example, in the Google Skillshop, where you can find a host of learning resources and even professionally recognised certifications.
However, we've found that good resources can be quite technical and challenging to follow for non-analysts. That's why we've decided to share our process and a free downloadable measurement and implementation plan for you to use for your website.
The first version of this post is quite a few years old now and we updated it regularly, to ensure that it stays aligned with our ever improving process for measurment planning. The template is also changing, so is our approach to pretty much everything. So even if you have been here before and you have downloaded our template in the past, it's worth checking that you have the most recent version of it.
The first thing to consider is who needs to be involved in this exercise. The complexity and implementation of your measurement framework depend on your organisation's maturity and size, as does the number of people involved.
With that in mind, ensure that one of the team members has the following skills to create the plan:
Someone who understands your business objectives and strategy
Someone who understands web analytics and how it supports the organisation's success
Someone in charge of (digital) marketing campaign activity and budgets
Someone technical who can set up your custom tracking configuration
Someone from the web or development teams who can help with the implementation of the dataLayer
A data engineer or data scientist who may work with the raw data outputs of whatever you collect, planning to feed them into LLMs or AI tools of some description
This process means bringing different stakeholders together for large organisations (which can be challenging). Importantly, obtaining buy-in from C-suite executives at this stage provides the project with the attention it deserves and the motivation to complete the exercise.
Create a simple document (MS Excel or Google Sheets works well for this) and outline the top-line business objectives for your website horizontally across the top:
Identify strategies and tactics to support the achievement of those objectives and define the KPIs for each; remember, some goals will have multiple KPIs.
Example: If the objective is revenue, key strategies to drive revenue could be increasing sales, increasing average order value, and reducing returns, which in turn form the KPIs.
At Fresh Egg, we started doing this as a group exercise to include all the stakeholders, but it felt like not everyone participated equally and the output was therefore skewed towards the more vocal attendees. What works much better is a post-it exercise (IRL or virtual using Whimsical) where we ask a few simple questions like 'what are the key objectives for your website', 'who are your key audiences' or 'which are the most important user journeys'. Filling the board with post-its ensures that everyone gets heard.
Once the list of KPIs is complete, you can start to define the data points that support each one. To achieve the objective of brand building and the relevant KPI of 'gain new customers', suitable data points include total sessions, new users, first-time purchases, and new customer registrations.
Once your plan is complete, seek approval from key stakeholders and, ideally, the Board. It is worth noting that this list is never definitive and will need periodic review to ensure it remains up-to-date and in line with the ever-changing digital environment.
A measurement plan can be as simple or complex and detailed as you need it to be. If this is the first time you are creating one, maybe start simple and build it out later, once you are familiar with the process.
For some of the bigger measurement frameworks we have created, we have broken the measurement plan down by audience because if you have more than one distinct audience coming to your website, chances are they are there to achieve very different things. Imagine your business is eBay, for example. Your two main audiences are Sellers and Buyers, and the objectives for those two could not be more different. You would consider Sellers your most important audience because without sellers, you won't have a business. For these types of business, we add a row for 'Audience' above the 'Objectives' row and then assign objectives, KPIs and metrics to each of the audiences.
With the basic measurement framework in place, it is time to consider segmentation and data engineering requirements.
Should you be able to analyse your data by more than device category?
How do we capture and report on membership tiers or different levels of subscriptions to our services?
How do we want to report on product category and sub-category performance by seasonality, and how do we know whether a user bought an item during the sale (or not)?
What data points will we need to create audiences of high-net-worth individuals, cart abandoners, loyal customers, or those with a high propensity to churn?
These questions need to be addressed at this stage, as most advanced segmentation will require custom parameters when creating the data model for your web analytics platform (let's assume it's GA4). Your data engineering team (or agency/contractor) should also review your proposed data model to ensure that it does not create unforeseen issues later.
For example, custom events, parameters, metrics, and dimensions must be set up. This is also when you need to start thinking about your different audiences (like marketing audiences and personas). If you want to be able to create an audience of high value users, you need to track value so you can segment them by this data point. If you want to create audiences of members or subscribers, you need to be tracking membership, login and subscription, in order to be able to build those segments. The measurement planning session with the wider stakeholder group should have produced a list to help you with this.
At this stage, the measurement plan should outline the detailed translation of business objectives into measurable performance metrics.
Not all the metrics you have picked can be measured using Google Analytics (GA) or your analytics platform of choice. Social metrics, such as likes, retweets, and repins, are good examples of metrics in most measurement plans that a GA implementation cannot deliver on. Page speed data typically comes from Google Lighthouse or Search Console and customer reviews might come from Trustpilot. Highlight these metrics in your plan for later consideration.
With all the primary metrics in place, you can begin to set targets for each metric. If you don't already have something in mind, the wider team and key stakeholders may get involved again.
Now that you know what you want to measure and track, you need to implement all the tracking. An audit of the existing GA4 configuration will identify gaps and indicate any additional tracking required.
For analytics tools like GA4, you now need to start thinking about the data model. The data model is the structure of event names, parameters, values, and other elements that form the dataset with which you will be working as an analyst. Getting this right from the beginning is so important that we recently published a separate blog post on the subject of creating a robust data model. Follow this link to also find an up-to-date template of our solution design document (aka event map).
If you aren't already using a tag management solution like Google Tag Manager, this is the right time to reconsider. Implementing your tracking code using a tag container instead of adding it directly to the website code means you will be more agile in the future when changes are needed. This is especially true when additional tags are required or the tracking needs to be modified due to changes on your website, which happens more frequently than you'd think.
Using a tag container reduces the risk of missing a tag during migration. If, for example, your website is likely to change or migrate, it is more manageable for your developers to transfer a Google Tag Manager snippet, along with any dataLayer information, than to locate various third-party tags individually.
Google Tag Manager is a free tag container solution that covers all the tagging requirements for most online businesses. Find out more about how the solution works in our recent blog post, "A guide to getting started with Google Tag Manager." The best-in-class way to implement your tracking these days is to use a server-side implementation of Google Tag Manager which brings a host of benefits from data quality to quantity and the ability to enrich it to send better conversion signals to your paid media platforms. We'll write about that in a separate post.
Once you know what tracking is in place and decide how you want to implement your tracking code, it's time to devise an implementation plan. You can use another tab in the same Excel document, utilising columns to highlight what is in scope, already in place or any required additions.
While we often skip this stage of the project these days, proceeding directly to solution design (see example below) provides a good working document for implementation. It makes it easy to assign individual tasks to specific people, keep shared checklists of all required steps, and communicate across teams and departments if needed. You can utilise a preferred project management solution to manage the process.
After considering all technical aspects and agreement on the tracking solutions for the KPIs, it will be time to implement the new, advanced tracking.
It is unlikely that everything will work as expected from the word 'go'. We always set up a test web property in GA to verify the data and ensure everything is tracking accurately before sending the 'new' data to the existing reporting property. This task is best practice and is essential to avoid collecting inaccurate data throughout the transition period.
The final step of the measurement planning cycle is to plan for ongoing maintenance and refinement of the plan as time goes on. Your technical requirements, business, and the digital landscape can and will change over time, so it is essential to periodically review the measurement plan and adjust it accordingly to ensure reports remain accurate.
Remember to set up GA4 Intelligence alerts to inform you immediately of unusual peaks and drops in your data.
This next step is not part of creating the measurement plan itself, but the logical extension – agreeing on the reporting format and frequency.
In some cases, which usually apply to smaller businesses and websites, all KPIs can be tracked and reported using the standard reports in GA4. Gathering all the key numbers can be simplified by creating an Explore report and sending automated emails to all stakeholders on a weekly basis, typically every Monday.
However, many businesses we work with have more specific reporting requirements for their monthly or weekly BAU reporting. We offer a variety of reporting and custom performance dashboarding solutions that help our clients in various ways. We build reporting dashboards in Looker Studio and Power BI, and we almost exclusively extract raw GA4 data to BigQuery, allowing us to be much more flexible in blending it with other data sources. The accuracy and speed of reporting are also significantly improved when the data comes from BigQuery, as it eliminates the 'guesswork' of GA4's data modelling.
Even better, BigQuery also captures the anonymised data of users who did not consent to analytics cookies so that you can model their behaviour yourself.
We published a great blog post last year about the GA4 export schema and what you can do with the GA4 data.
Consider what information you need and how frequently you need it to stay on top of what's happening on your website.
The final step of the measurement planning cycle is to plan for ongoing maintenance and refinement of the plan as time goes on. Your technical requirements, business, and the digital landscape can and will change over time, so it is essential to periodically review the measurement plan and adjust it accordingly to ensure reports remain accurate.
Maintenance is not a glorious task but when it comes to data integrity it is really important. Whether it is the dashboards that are used by the entire organisation or you are using an AI chat interface to extract wisdom and insight nuggets from the depth of your data set, it is absolutely critical that those numbers are correct or people will soon lose trust in the data.
The downloadable measurement plan template also contains an example of a maintenance schedule as we would typically run our clients through, monthly or at the very least quarterly. This gives you an idea of how much work this used to be! These days we use tools and automation, often proprietary. The best one out there available to you (for auditing and maintaining your setup) is this one: https://app.analyticsdetectives.com/
Remember to also always update the solution design you have created. With GA4 configurations being more customised and complicated than ever, up-to-date documentation of what you have in place is critical.
If you need help creating and implementing a measurement plan, we can help. We are passionate about all things digital analytics, data engineering, analysis, reporting, and business insights, and would love to discuss your needs and challenges with you.
Get in touch to learn more about how we can help you and your business extract valuable, actionable insight and get a step ahead of your competition.
