Research method
Analytics Data Analysis
Analysis of website analytics data to determine overall performance, performance by segment, e.g. device, channel, user type, analysis of on-site behaviour or digging into the impact a specific element or piece of functionality has on performance and user experience.
When to reach for it
Understand overall on-site user behaviour with high levels of certainty (assuming no sampling) and the differences across key segments.
Dig deeper into the performance and / or impact of a specific page, element, or area of the website.
Strengths and limits
Pros
Analytics data is one of the most robust sources of data you can use to help you understand on-site engagement, interaction, and user behaviour. This is because this data is based on real user behaviour, without research bias, at a large scale.
Cons
Sampling issues can reduce the accuracy of your data, which can result in drawing false assumptions, making decisions based on flawed data, etc.
Analytics data will tell you what is happening on your site, but not why. As with session recordings and heatmaps, the data is also open to interpretation.
Robust analytics data analysis is a skill. It can easily be misunderstood or misinterpreted.
Practical considerations
Configuration
Effective analytics data analysis is reliant on a robust tool configuration, ensuring the data you're looking at is accurate. Effective set up can be complex and requires in-depth tool knowledge, ideally from a developer or from someone with experience in setting up analytics tools.
Analysis
As analytics data is open to interpretation it is important to keep analysis actionable. At times it is relevant to simply point out facts, e.g. x% of data comes from mobile devices. But from an optimisation perspective, we should be considering the "so what?", e.g. what does this tell us, what opportunities does this present, etc?
Tools
There are many digital analytics tools available. Chances are the business you work in or with will already use one. Google Analytics (now GA4) is one of the most popular and most well-known tools. The transition from Universal Analytics to GA4 happened in 2023 which significantly changed the way GA works.
Common tools
Go deeper
Recipes that use this method
A method earns its value when its signal corroborates others. Here is where this one does its work.
- Acquisition Research
- Category & Listing Page Optimisation
- Checkout & Cart Optimisation
- Churn & Retention Research
- Content-to-Lead Conversion Research
- Conversion Research
- Engagement Decay & Habit Research
- Free Trial to Paid Conversion
- Involuntary Churn & Payment Recovery Research
- Lead-Gen Form Optimisation
- Mobile Experience Optimisation
- Navigation & Information Architecture
- Onboarding & Activation Research
- Product Page Optimisation
- Repeat Purchase & Post-Purchase Research
- SEO & Search Intent Research
- Traffic Quality & Channel Fit Research
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