Strategic & Foundational

Product Design Framework

Customer-Led Product Design Framework

Customer-Led Product Design Framework

A customer-led decision framework developed from behavioural research, exit surveys, competitor analysis and experimentation. The initiative uncovered critical information gaps and established a scalable model for improving accommodation content across Discovery Parks.

500+

500+

Exit survey responses analysed

50%+

50%+

of users left the website due to insufficient information

58

58

Content Gaps Identified

Through competitor analysis

17

17

Accommodation pages in live A/B test

Problem

Customer feedback consistently highlighted frustration when evaluating accommodation options, yet the specific causes remained unclear.

While customers frequently requested more information, it was difficult to determine which information was missing, why it mattered, and how it influenced booking decisions.

Existing accommodation pages had evolved over time without a consistent framework, resulting in content gaps, inconsistent information hierarchy and uncertainty around what customers actually needed to see.

The challenge was not simply adding more content. The challenge was understanding which decisions customers were trying to make and identifying the information required to support those decisions.

My role

I identified an opportunity to better understand why customers were abandoning accommodation pages and whether existing content was supporting booking decisions.

I led the initiative end to end, combining customer feedback, behavioural analysis, competitor benchmarking, content audits and decision modelling to uncover the information customers needed to make confident booking decisions.

Rather than focusing on page design alone, I reframed the challenge around customer decision making and developed a repeatable framework that could scale across accommodation types, parks and future optimisation initiatives.

I also established the measurement approach, including A/B testing through VWO and behavioural analysis through Heap, to validate whether the framework improved customer engagement and decision confidence.

The challenge

Understand which customer decisions were failing and identify the information needed to support confident booking decisions.

Key Insight

Customers were not simply looking for more information. They were trying to answer specific booking decisions, yet the information needed to support those decisions was either missing, difficult to find, or inconsistent across accommodation pages.

What I did

Customer Feedback Analysis

  • Exit survey review

  • Common themes identification

  • Customer sentiment

Behavioural Analysis

  • Journey review

  • Decision friction points

  • Information gaps

Competitive Review

  • Accommodation websites

  • Industry benchmarks

  • Best practice patterns

Decision Modelling

  • Customer decision mapping

  • Information hierarchy

  • Decision framework

Content Framework Design

  • Accommodation information model

  • Scalable content structure

  • Standardised page framework

Measurement Planning

  • Success metrics

  • VWO experimentation

  • Heap behavioural analysis

Validation Through Experimentation

Validation Through Experimentation

To validate whether the framework improved customer decision confidence, a live A/B test was launched across 17 accommodation pages using VWO and Heap Analytics. In addition, unique events were created on each content group to measure engagement.

Measure of Success:

Variant A - Number of users that progressed to the next stage of the funnel to add a booking to the cart

Variant B - Increase in the number of bookings purchased

Time on Page
Bounce Rate

Insights

What content was interacted with

[Test is currently in progress]

To validate whether the framework improved customer decision confidence, a live A/B test was launched across 17 accommodation pages using VWO and Heap Analytics. In addition, unique events were created on each content group to measure engagement.

Measure of Success:

Variant A - Number of users that progressed to the next stage of the funnel to add a booking to the cart

Variant B - Increase in the number of bookings purchased

Time on Page
Bounce Rate

Insights

What content was interacted with

[Test is currently in progress]

Outcome

The framework established a scalable approach for identifying customer information needs and translating those insights into accommodation content improvements.

The initiative also introduced a measurable experimentation model, enabling future content decisions to be validated through behavioural data rather than assumptions.

The framework established a scalable approach for identifying customer information needs and translating those insights into accommodation content improvements.

The initiative also introduced a measurable experimentation model, enabling future content decisions to be validated through behavioural data rather than assumptions.

The framework established a scalable approach for identifying customer information needs and translating those insights into accommodation content improvements.

The initiative also introduced a measurable experimentation model, enabling future content decisions to be validated through behavioural data rather than assumptions.

Research Outcomes

  • 500+ survey responses analysed

  • Key information gaps identified

  • Customer decision model established

Research Outcomes

  • 500+ survey responses analysed

  • Key information gaps identified

  • Customer decision model established

Framework Outcomes

  • Content framework created

  • Accommodation information hierarchy defined

  • A/B testing framework implemented

Framework Outcomes

  • Content framework created

  • Accommodation information hierarchy defined

  • A/B testing framework implemented

Organisational Outcomes

  • Shifted discussions from content requests to customer decision making

  • Created repeatable methodology for future optimisation

  • Established measurable validation approach

Organisational Outcomes

  • Shifted discussions from content requests to customer decision making

  • Created repeatable methodology for future optimisation

  • Established measurable validation approach