Researching competitor products

Concept

Users answer a series of questions about their viewing preferences - starting with broad mood-based categories ("I want to escape", "I want to learn"), then drilling into sub-genres and content attributes. The journey culminates in a personalised "viewing profile" that reflects their choices back to them, complete with a generated label like "The Curious Explorer."

Behavioural Framework

This approach leans on identity reinforcement and the IKEA effect. By asking users to articulate who they are as viewers, we activate consistency bias; people act in accordance with their stated identity. The profile becomes a psychological anchor, and the effort invested in creating it raises switching costs.

Pros

• Captures rich, explicit preference data that powers accurate recommendations from day one
• Creates emotional resonance - users feel understood, not processed
• The profile artefact provides a memorable moment and a reason to return ("my iView")
• Works well for users who enjoy self-reflection and appreciate personalisation
• Scales cleanly across content categories without needing extensive media assets
  

Cons

• Relies on users accurately knowing and articulating their preferences (which research suggests is unreliable)
• Longer flow with more steps - higher risk of abandonment
• May feel effortful for casual viewers who just want to watch something
• Abstract categories can be difficult to map to actual content decisions

Concept

Users swipe through a curated sequence of content cards, saving what interests them and skipping what doesn't. There's no explicit preference capture - instead, the system infers taste from behaviour. Users leave onboarding with a functional watchlist ready to play.

Behavioural Framework

This approach leverages recognition over recall - people are far better at reacting to concrete options than articulating abstract preferences. The swipe mechanic introduces variable reward psychology (each card is a small surprise), while the growing watchlist creates visible progress and immediate utility.

Pros

• Lower cognitive load - users react rather than reflect
• Captures implicit preferences that may be more accurate than self-reported data
• Delivers tangible value immediately (a watchlist they can use tonight)
• Gamified interaction feels lighter and more engaging
• Natural content discovery mechanism that doubles as marketing

Cons

• Relies on users accurately knowing and articulating their preferences (which research suggests is unreliable)
• Longer flow with more steps - higher risk of abandonment
• May feel effortful for casual viewers who just want to watch something
• Abstract categories can be difficult to map to actual content decisions

Method

I ran moderated remote sessions through UserTesting.com with 12 participants across two rounds. Participants were Australian adults aged 25–54 who had used at least one streaming service in the past month but were not current iView users. This ensured familiarity with streaming conventions without existing expectations of iView specifically

Each participant was randomly assigned to one of the two prototypes. Sessions lasted 15–20 minutes and included a think-aloud walkthrough followed by a short post-task interview.

Tasks

• Open-ended start: "You've just downloaded the ABC iView app. Go ahead and set it up however feels natural to you."
• Comprehension check: "In your own words, what was that experience trying to do?"
• Preference articulation: "How confident are you that iView now understands what you like to watch?" (1–5 scale)
• Immediate intent: "What would you do next - watch something now, or come back later?"
• Comparative reflection (post-task): Participants were shown a brief walkthrough of the alternate approach and asked which they'd prefer if downloading the app today.

Insights

1. The Taste Test was faster, but the Profile Builder felt more personal

Participants who used the Profile Builder described the experience as "thoughtful" and "like it actually cared what I wanted." Taste Test users completed faster and with less friction, but several noted it felt "a bit random" or "like Tinder for TV." Speed didn't translate directly to satisfaction.

"I liked picking the categories because it felt like I was teaching it about me. The swiping thing—I wasn't sure if it was learning or just showing me stuff." — P4, Profile Builder

2. The swipe mechanic drove immediate action; the profile drove return intent

Taste Test users were significantly more likely to say they'd "watch something now" (83% vs 50%). However, Profile Builder users more often mentioned coming back—they felt they'd invested in something worth returning to. This suggests the approaches may optimise for different parts of the funnel.

3. Minimum save threshold caused hesitation

In the Taste Test, requiring 3 saves before unlocking the feed created a small but noticeable friction point. Two participants saved content they weren't genuinely interested in just to proceed. One described it as "forced liking." This risks polluting preference data.

4. Sub-genre fatigue appeared in multi-mood selections

Profile Builder participants who selected 3+ moods showed visible fatigue by the second or third sub-genre screen. Two participants began selecting randomly to "just get through it." The dynamic screen count—intended to capture richer data—backfired when it extended the flow.

5. The profile reveal was a moment of delight

The generated label ("The Curious Explorer", etc.) consistently prompted positive reactions - smiles, screenshots mentioned, one participant read it aloud. This was the most emotionally resonant moment across either flow.

"Oh that's fun! 'The Drama Devotee.' I'd actually share that." - P9, Profile Builder

6. Sliders were misunderstood

In the Taste Test's context screen, the binary sliders ("Short bursts ↔ Long binges") confused several participants. They expected a neutral midpoint to mean "no preference" but weren't sure if the system interpreted it that way. Two participants skipped the screen rather than guess.

Based on testing, I recommended proceeding with the Taste Test as the primary onboarding experience, with targeted refinements to address its weaker points.

The data made a compelling case: 100% completion rate, nearly a minute faster to complete, and significantly higher immediate activation intent (83% vs 50%). Users who watch something on day one are far more likely to return on day seven.

The Profile Builder's strengths were optimised for a user who's already committed. The Taste Test wins the users who aren't sure yet, and in a competitive landscape, that's the bigger win.

Refinements to the Taste Test based on insights:

• Lower the save threshold to 2 and soften the framing: "Save a couple that catch your eye" rather than "Save at least 3 to unlock." This removes the forced-liking behaviour I observed.
• Cut the context screen entirely. The sliders confused users and the skip rate was high. We can infer these preferences from viewing behaviour within the first few sessions - no need to ask upfront.
• Add a single confidence-building moment after the swipe sequence: a brief screen that summarises what we learned ("You're into drama, true crime, and local stories"). This borrows the Profile Builder's "reflection" moment without the overhead of building an entire profile.
• Retain the swipe mechanic for ongoing discovery. Multiple participants mentioned they'd use it again. I recommended surfacing "More to discover" swipe sessions in the home feed after the first week - turning the onboarding mechanic into a re-engagement feature.

The Profile Builder remains a viable future addition for power users who want more control—but it's a settings feature, not a gate. The Taste Test gets people watching, and that's the job.