Data from Google analytics can be difficult to interpret when trying to understand user behavior and user experience. Broadly speaking, the information is not detailed enough or integrated enough with the needs of individual users to directly answer complex user experience questions. However, if the problems are tied closely to individual pages on the site, then we can make immediate changes and measure their impact directly from the data at hand.
The challenge is knowing which kind of performance problem you’re facing. When is the issue resolvable through focused application of “small UX” best practices? When is it something deeper, a problem that requires you to draw from user experience tools like information architecture, user testing, persona development, user journeys, and detailed business analysis? Choosing incorrectly can lead to a huge waste of cycles, increased cost, and “solutions” that might make things even worse. So it’s critically important to know which kind of issue your site has.
Start with Two Questions
Fortunately, the scope of a user experience problem can usually be resolved by answering two simple questions:
- Is the problem clearly due to a single page, or is it on multiple pages?
- Do the solutions seem immediately clear and testable?
The chart below shows the factors that lead to “direct” or “correlative” input, along with the general problem areas and typical improvement strategies.
How Google Analytics Can Help
How do we determine if a factor is on a single page? This can be done, generally speaking, through two main reports from Google analytics: the landing page report and the conversion funnel report.
- If a landing page or landing page template has a lower than average conversion rate, it’s a landing page issue.
- If a page in a conversion funnel represents more than 40% of the conversion failures, it may be an issue with that page.
If problems are isolated within a single page, you’re in luck: most web analytics packages have statistical tools for page-level testing. These are fairly easy to learn and can be applied to general UX best practices or general visual heuristics for any given page to run statistical experiments.
More general UX needs, on the other hand should be addressed with the help of experts, either from your internal team or with consultants. This isn’t to say that the problems will require expensive analysis or expensive solutions, just that in situations where Google analytics cannot directly point to what the problem is, the inquiry should be expanded to include a broader set of techniques and tools.