Measurement Plans – The Missing
One thing that exasperates me more than anything else is companies’ reluctance to create documents on how their website or app flows in steps and then specifically record what and how those steps are measured; some companies even outsource all that thinking and understanding to agencies. If you take anything from this book, ensure you have a regularly maintained and updated measurement plan to go along with your site and ensure that internal and external teams can always access it. If someone says the tracking is broken, expect a line-specific definition.
Marketer One – ‘You know old line 33 on the sheet is broken again; it says here our agency fixed that only last week!’. Shocked response From Marketer Two – ‘That’s important because it triggers one of our key conversion goals. STFD! (shut the front door). Let’s get on that!’
This document details what needs to be tracked as a checklist. Developers work through and update their comments, while the analytics team tests and assists developers.
But what should we have in our Measurement Plan, and how do we create and fill it in?
Here is a structure I recommend, using Google Sheets and breaking the sections into tabs.
Overview – Audiences, Objectives, and Assets
Conversions and Targets – Web Analytics (usually GA3 and GA4)
Event and DataLayer Tracking – This could be simple or detailed
Configuration Checklist – Web Analytics (usually GA3 and GA4)
UTM Link Tagging Tool
Overview – Audiences, Objectives, and Assets
Source: MckTui Consulting.
We start here with our website or app up on one screen and this sheet up on another. Who are the key audiences for assets? What do we want each audience to do? And what possible goals and events may be needed to track those specific engagements? Can we think of rough targets, such as the number of contact forms?
How many assets (websites and apps) are we looking to track? And how can we start mapping out the potential properties and data streams we need? This would be required for setting up Google Analytics 4 if we decided that’s the web analytics tool for us.
Conversions and Targets – Web Analytics (usually GA3 and GA4)
Source: MckTui Consulting.
Once we have a rough idea of those objectives and goals, we can break them into specific conversions. I find it helpful to map the most important and work my way down. Often these are bottom-of-the-funnel conversions as well. As many organisations will previously have had Google Analytics 3, this can also help to ensure we’re transitioning our new setup based on the learnings and structure of the old. We can also note here particular conditions used to trigger our conversions; this is useful when we’re unsure precisely what the data we’re looking at really means.
Event and DataLayer Tracking – This Could Be Simple or Detailed
Source: MckTui Consulting.
Source: MckTui Consulting.
Once we have our agreed conversions, we can break down the engagements that we want to track, identifying those as events and the parameters we may wish to pass on with those events. The best way to start here is by noting those events already tracked in the tool and those recommended, following the tool’s existing structure, before attempting any original custom tracking.
In order to effectively manage and analyse data in web analytics, it is important to standardise the data points across different setups and libraries. By doing this, you ensure that the data you collect is consistent and compatible across various uses. Standardisation helps streamline processes and improve the quality of your data. It also enables you to analyse and compare data more effectively. So, when setting up your data layer and working with different data libraries, make sure to define a set of standardised data points that are relevant to each type of engagement. This will help you maintain consistency and get the most out of your web analytics efforts.
