Website Analytics
Website Analytics
TL;DR
As I transitioned into the Digital Experience Designer role, website analytics became part of my responsibility. After several major redesigns, we still knew surprisingly little about how visitors actually moved through the site or where they encountered friction.
I used GA4, Hotjar, Google Search Console and occasionally Looker Studio to study user behaviour, identify problem areas and turn those findings into hypotheses and website improvements.
My role: supplementary role to a GA4 expert on our team
The problem
We had redesigned the website several times, but we had no clear way of knowing whether the new pages were actually helping users move toward conversion.
Elastic Email was a SaaS product with a relatively complex customer journey. There was no simple path from landing page to purchase, and users often moved between product pages, pricing pages, documentation and registration before converting.
Without a clearly defined marketing funnel, it was often difficult to tell what had helped a user convert, what had discouraged them, or where the website's responsibility ended and the product journey began.
What I did
I used GA4 as my main analytics tool, supported by Hotjar, Google Search Console and occasional Looker Studio reports.
My goal was to understand how visitors moved through the website, identify pages or behaviours that suggested friction, and look for opportunities to improve the experience.
Over time, I uncovered a number of interesting patterns.
Friction on the product choice page
The product choice page had a relatively high exit rate, suggesting that some visitors were struggling to decide which Elastic Email product was right for them.
This finding contributed to a redesign of the page.
Uncertainty on pricing pages
Users frequently switched back and forth between different product pricing pages.
This suggested that product differences and positioning were causing confusion for the visitors.
Unexpected interest in Getting Started
A noticeable number of visitors were reaching the Getting Started page, even though the page itself provided relatively little useful information.
This indicated a strong need for orientation and eventually led to a redesign of the page.
Brand campaigns attracting existing users
I also found that a substantial share of visitors arriving through paid brand campaigns appeared to be existing customers who had simply clicked the first search result when looking for Elastic Email.
This raised questions about how much incremental value those campaigns were actually producing.
Outcome
The analytics work generated a steady stream of behavioural insights and helped identify several areas of friction across the website.
Some of those findings led directly to changes, including redesigns of the product choice page and the Getting Started page.
The effect of those changes on conversion was ultimately inconclusive however.
The biggest limitation was not access to data, but the absence of a clearly defined marketing funnel and shared customer journey. I could identify behavioural patterns, formulate hypotheses and recommend improvements, but it was often difficult to connect individual website changes to measurable business outcomes.
Even with that limitation, the work gave the team a clearer view of how visitors were actually using the website and gave me practical experience in using behavioural data to guide UX decisions.