Embedding research into product decisions helped translate customer insight into growth.
Within 2 weeks of launch.
Across 300 recommendations.
Behavioural observations captured through qualitative analysis.
Recoverable 3 days after launch at the measured growth rate.
Sportsbet customers regularly chose between multiple providers. Market share depended on customers choosing the product again, and that choice was shaped by the quality of the experience, the relevance of rewards and the perceived value of each interaction.
Product teams needed to move quickly, but they also needed to avoid costly decisions based on assumptions. My role was to give teams and executives stronger evidence before product changes reached customers.
The challenge was not simply to run research. It was to make research useful inside product decision-making: fast enough for agile delivery, credible enough for quantitative practitioners, and influential enough to change what teams built.
Sportsbet is Australia’s leading mobile app in the gaming category. Half a million customers spend up to $1 million per day across thousands of products on two websites and two mobile apps. As UX Researcher it was my responsibility to support the decisions of a team of 15 product owners, 15 designers and an executive board.
I was responsible for shaping a 12-month research plan, setting up the research capability, managing recruitment and incentives, designing research activities, analysing customer behaviour, and turning findings into recommendations that product teams could act on.
I partnered with product owners, designers, executives, analysts, security teams and other stakeholders. I did not own final product decisions, but influenced them by making customer evidence visible, reusable and connected to commercial impact.
Research reports can fail when stakeholders first encounter the evidence at the end. I needed teams to understand the customer problems early enough to act on them.
The research programme generated a large volume of evidence. If that evidence lived only in individual reports, teams would repeatedly rediscover the same problems.
The obvious move was to support feature delivery as requests arrived. That would have made research reactive and limited its influence to late-stage validation.
Some stakeholders were more comfortable with quantitative methods than qualitative observation. Relying on interviews and usability sessions alone risked limiting confidence in the findings.
The programme needed to support strategic direction, product discovery and delivery decisions at the same time. I created a mixed-methods operating model that combined stakeholder alignment, quantitative studies, qualitative observation and prioritisation. For each research activity I wrote up a full report every two weeks detailing the results of each analysis.
The research generated evidence across discovery, personalisation, trust, accessibility and checkout behaviour. Here’s a sample of the insights generated. For each finding, evidence was written up in a report, analysis was presented, recommendations were discussed, and follow-up actions were prioritised.
I researched customer discovery of entry, exit and re-entry points for core journeys like registration, product selection, and product purchase.
Recruiting participants from carefully managed customer cohorts made prototype testing more realistic and helped simulate machine learning personalisation.
By observing participants as they used the product in a naturalistic way, the impact of friction points became clear.
Product innovation could not rely on instruction alone. Combination products required clear journey entry points, eligibility messaging and offer framing.
The research programme required investment in software, recruitment, incentives and consultancy. The total research cost was $300,000.
After launch, measured growth was 10%, based on $1,000,000 per day actual performance compared with the previous $900,000 per day trend. At that growth rate, the $300,000 research cost was recoverable 3 days after launch.
The biggest lesson from this work was that evidence only creates value when people are ready to use it. The research methods mattered, but stakeholder participation was what turned findings into product decisions.
If I approached this again, I would formalise the knowledge base earlier in the programme. The volume of insight grew quickly, and earlier structure would have made it easier for teams to reuse evidence across related product decisions.
