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User acquisition was strong, but a significant proportion of users were not progressing through key stages of the journey. Despite having access to analytics, the team couldn’t confidently explain why users were dropping off or which parts of the experience were causing hesitation. This created a gap between performance data and actual understanding, limiting the ability to improve conversion in a meaningful way.
The data showed where users were leaving, but not why. When we mapped the experience from a behavioural perspective, patterns began to emerge. Certain stages introduced uncertainty — unclear expectations, lack of reassurance, or friction in decision-making. These weren’t technical issues; they were psychological ones. Users weren’t failing to complete the journey — they were choosing not to continue.
We focused on the specific moments where users needed clarity or reassurance and redesigned those interactions to remove ambiguity. This included simplifying key decisions, adjusting messaging to reduce perceived risk, and aligning the experience more closely with user expectations at each stage.
As those changes were introduced, completion rates increased by 27% across targeted journey stages. Drop-off became more predictable and, more importantly, more manageable. The team gained a clearer understanding of user behaviour, allowing them to prioritise improvements based on impact rather than assumption.
Marketing Director
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