When Good Content Meets Bad Discovery

UKTV Play had great content but a big problem: viewers weren't sticking around. Despite having shows people loved, the platform was bleeding users faster than it could acquire them. New viewers would land on the homepage, struggle to find something worth watching, and disappear, often after just one session.

The team knew they had an engagement crisis, but they didn't know why. Was it the content? The interface? Something deeper about how people actually use streaming platforms? Without understanding their users' real motivations and behaviors, they were essentially throwing features at the wall and hoping something would stick.

Fighting Blind Against User Churn

The deeper we dug, the clearer the problem became: UKTV Play was treating all users like they were the same person. Everyone got the same onboarding experience, the same recommendation logic, and the same content discovery flow.

But viewers aren't all the same. Some people binge-watch crime dramas at midnight. Others catch up on comedy shows during lunch breaks. Some are genre loyalists who know exactly what they want, while others browse aimlessly, looking for something to surprise them.

The brutal reality: UKTV's one-size-fits-all approach was fitting nobody particularly well. Users were bouncing because the platform didn't understand them, couldn't predict what they wanted, and certainly couldn't deliver the right content at the right moment in the right way.

While competitors were mastering personalization, UKTV Play was stuck in the broadcast era—great at making content, not so great at connecting it with the right viewers.

Meeting Users Where They Actually Are

Instead of guessing what users wanted, I decided to watch what they did. We launched a mixed-methods research blitz: qualitative interviews to understand motivations, diary studies to capture real viewing contexts, and deep analytics dives to see exactly how people moved through the platform.

The breakthrough came from behavioral clustering: Using K-Means analysis on actual usage data, we discovered that UKTV's users naturally fell into distinct groups. There were the late-night binge-watchers who'd consume entire seasons in one sitting, casual catch-up viewers who popped in for specific shows, and genre-loyal fans who had very particular tastes and viewing rituals.

Each cluster told a completely different story about what streaming success looked like.

Impact

From data to design: We turned these behavioral patterns into tangible user personas, then designed completely different user journeys for each group. Using interactive wireframes in Miro, we prototyped personalised onboarding flows, tailored recommendation engines, and targeted re-engagement strategies.

The impact was immediate: Instead of forcing everyone through the same funnel, UKTV Play could now meet users where they were—whether that was helping binge-watchers dive deep into series, making it easy for casual viewers to jump back into their favorites, or giving genre fans the curated experience they craved.

The research didn't just fix the immediate engagement problem; it created a repeatable framework for understanding users that influenced UKTV's entire product roadmap. The team finally had a clear picture of who they were building for and what those people actually needed from a streaming platform.