Strategic & Foundational
Data-Led Experimentation
Using behavioural analytics, heatmaps, session recordings and experimentation to identify hidden opportunities and validate product decisions through measurable outcomes.
This work demonstrates how customer behaviour can reveal opportunities that traditional stakeholder assumptions often miss.
Homepage conversion uplift
(Case Study 1)
Progression rate when map used
(Case Study 2)
Problem
Product decisions were often influenced by stakeholder opinions, customer feedback and business priorities, but there was limited behavioural evidence showing how customers actually navigated key journeys.
The challenge was identifying which interactions genuinely influenced customer progression and where optimisation opportunities existed.
My role
I led the behavioural analysis and experimentation process, combining Heap Analytics, Hotjar, GA4 and VWO to identify opportunities across key customer journeys.
My role involved analysing behavioural patterns, identifying friction points, forming hypotheses, designing experiments and validating outcomes through measurable customer behaviour.
Rather than relying solely on assumptions, recommendations were supported through behavioural evidence and experimentation.
The challenge
Use customer behaviour to identify optimisation opportunities and validate whether design changes improved progression and conversion.
What I did
Behavioural Analytics
Heap analysis
Funnel progression
Journey review
Heatmaps
Scroll behaviour
Click patterns
Engagement zones
Session Recordings
Friction identification
Navigation review
Behaviour observation
Hypothesis Development
Opportunity framing
Experiment planning
Success metrics
Experiment Design
A/B testing
Variant creation
Measurement setup
Validation & Reporting
Results analysis
Stakeholder reporting
Recommendations
Design process evolution
Before
Stakeholder assumptions
Limited behavioural evidence
Design-first decisions
After
Behaviour-led decisions
Measurable validation
Continuous optimisation
Case Study 1
Homepage Optimisation Through Behavioural Analytics
Homepage Engagement Did Not Match Business Priorities
Behavioural analysis revealed that one of the most commercially valuable homepage modules, Deals, was receiving significantly lower engagement than expected.
While the Deals component contributed strongly to booking activity, only a small percentage of users were reaching it due to its placement lower on the page.
Behavioural analysis of the homepage revealed a disconnect between business priorities and customer visibility. While the Deals module was one of the strongest commercial drivers on the page, only a small percentage of visitors were scrolling far enough to see it.
Using Hotjar heatmaps and scroll tracking, I analysed how customers engaged with the homepage to understand whether commercially valuable content was positioned where customers were most likely to see it.
Based on the behavioural evidence, an A/B test was created to determine whether increasing the visibility of the Deals module would improve customer engagement and conversion.
The hypothesis was simple: if more customers could see the content, more customers would interact with it.
Conversion increase
Increase in annual revenue
Case Study 2
Park Search Experience & Conversion Analysis
Map Interaction Was Driving Stronger Customer Progression
Analysis of Park Search behaviour showed that customers interacting with the map progressed through the journey at significantly higher rates than customers who relied solely on the listing view.
The Park Search map experience had existed on desktop for some time but remained unavailable on mobile. Despite being discussed for more than twelve months, the feature consistently remained low on the delivery roadmap because its value to the business had never been clearly demonstrated.
Rather than relying on assumptions, I analysed customer behaviour to understand whether map usage influenced progression through the booking journey and whether the opportunity justified development investment.
Quantifying the Opportunity
The analysis revealed a clear behavioural pattern.
Customers who interacted with the map were significantly more likely to progress to the next stage of the booking funnel than customers who relied solely on the list view.
This shifted the conversation away from development effort and towards opportunity cost. The question was no longer whether the map would take time to build, but what value was being lost by delaying it.
Recommendation
Based on the behavioural evidence, the recommendation was to prioritise the mobile map experience and increase visibility of map interactions across the search journey.
The findings demonstrated that map interaction was strongly correlated with customer progression and represented a meaningful opportunity to improve the browsing experience.
These findings provided the evidence required to prioritise mobile map development and shift the discussion from implementation cost to customer value.
Outcome
These initiatives demonstrate how behavioural analytics and experimentation can uncover hidden opportunities, validate assumptions and support evidence-based product decisions.
Go-Live Results
Implementing Map View on mobile resulted in a higher conversion rate to the next stage of the funnel.
progressed to the next
stage of the funnel
uplift in conversion