Redefining SonyLIV’s Android TV Subscription Flow

Redefining SonyLIV’s Android TV Subscription Flow

SonyLIV was growing fast, but subscription conversions weren’t scaling at the same pace. I redesigned the plan selection → payment journey to reduce confusion, improve plan clarity, and increase purchase confidence.

SonyLIV was growing fast, but subscription conversions weren’t scaling at the same pace. I redesigned the plan selection → payment journey to reduce confusion, improve plan clarity, and increase purchase confidence.

Role: Product Designer (End-to-end)

Role: Product Designer (End-to-end)

Role: Product Designer (End-to-end)

Platform: OTT, B2C

Platform: OTT, B2C

Platform: OTT, B2C

Team: 1 Product Designer • 1 PM • 3 Engineers

Team: 1 Product Designer • 1 PM • 3 Engineers

Team: 1 Product Designer • 1 PM • 3 Engineers

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Paid subscriptions

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Paid subscriptions

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Paid subscriptions

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Paid subscriptions

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Paid subscriptions

-0%

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Checkout drop-offs

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Checkout drop-offs

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Checkout drop-offs

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Checkout drop-offs

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Checkout drop-offs

0%

0%

Faster plan decision-making

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Faster plan decision-making

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Faster plan decision-making

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Faster plan decision-making

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0%

Faster plan decision-making

0x

0x

Higher plan selection engagement

0x

0x

Higher plan selection engagement

0x

0x

Higher plan selection engagement

0x

0x

Higher plan selection engagement

0x

0x

Higher plan selection engagement

TL;DR

TL;DR

TL;DR

Problem

Problem

Users were dropping because plan selection felt unclear and pricing differentiation wasn’t obvious.

Users were dropping because plan selection felt unclear and pricing differentiation wasn’t obvious.

What I did

What I did

Built clearer plan comparisons, added pricing/upsell clarity, and streamlined selection → checkout.

Built clearer plan comparisons, added pricing/upsell clarity, and streamlined selection → checkout.

Outcome

Outcome

+0

+0

+0

+0

+0%

+0%

+0

+0

+0%

+0%

Subscriptions

-0

-0

-0

-0

-0%

-0%

-0

-0

-0%

-0%

Drop-offs

0%

0%

0%

0%

-0%

-0%

0%

0%

-0%

-0%

Faster Decisions

0x

0x

0x

0x

-0%

-0%

0x

0x

-0%

-0%

Engagement

Context

Context

Between 2019–2021 SonyLIV saw major growth, including a spike in content consumption and reaching 21M unique visitors (March 2021), but retention and conversion didn’t rise proportionally.

Between 2019–2021 SonyLIV saw major growth, including a spike in content consumption and reaching 21M unique visitors (March 2021), but retention and conversion didn’t rise proportionally.

Why it mattered

Why it mattered

Subscription is where growth becomes revenue. If the plan page is confusing, users don’t “decide later”—they leave.

Subscription is where growth becomes revenue. If the plan page is confusing, users don’t “decide later”—they leave.

A simple “Subscribe funnel” diagram: Landing → Plan selection → Payment → Success

A simple “Subscribe funnel” diagram: Landing → Plan selection → Payment → Success

The Problem

The Problem

The Problem

Despite strong demand, the plan selection experience created friction:

Despite strong demand, the plan selection experience created friction:

  • Plans weren’t easy to compare

  • Pricing value wasn’t structured clearly

  • Users dropped before checkout

  • Plans weren’t easy to compare

  • Pricing value wasn’t structured clearly

  • Users dropped before checkout

Your analytics backed it: 38% exit rate on the plan selection page.

Your analytics backed it: 38% exit rate on the plan selection page.

Before: unclear plan differentiation + too much thinking at a high-intent moment.

Before: unclear plan differentiation + too much thinking at a high-intent moment.

Before: unclear plan differentiation + too much thinking at a high-intent moment.

Goals & Success Metrics

Goals & Success Metrics

Goals & Success Metrics

Goals

Goals

  1. Simplify decision-making with structured plan comparisons

  2. Improve pricing visibility and upsell clarity

  3. Smooth selection → payment so momentum isn’t lost

  1. Simplify decision-making with structured plan comparisons

  2. Improve pricing visibility and upsell clarity

  3. Smooth selection → payment so momentum isn’t lost

Success metrics

Success metrics

  • Exit/drop-off rate from plan selection (baseline: 38%)

  • Conversion to paid subscription (+22%)

  • Checkout drop-off (-17%)

  • Plan decision time (40% faster via A/B)

  • Plan decision time (40% faster via A/B)

  • Exit/drop-off rate from plan selection (baseline: 38%)

  • Conversion to paid subscription (+22%)

  • Checkout drop-off (-17%)

  • Plan decision time (40% faster via A/B)

  • Plan decision time (40% faster via A/B)

Insights

Insights

Insights

Discovery combined

Discovery combined

  • Google Analytics (38% exits)

  • Support signals pointing to pricing confusion

  • Benchmarking with Disney+ Hotstar and Zee5

  • Google Analytics (38% exits)

  • Support signals pointing to pricing confusion

  • Benchmarking with Disney+ Hotstar and Zee5

Key insights

Key insights

  1. People weren’t rejecting pricing, they were rejecting uncertainty.

  2. The winning plan needs to feel obvious without removing choice.

  3. Checkout drop-offs often happen when users lose confidence mid-flow.

  1. People weren’t rejecting pricing, they were rejecting uncertainty.

  2. The winning plan needs to feel obvious without removing choice.

  3. Checkout drop-offs often happen when users lose confidence mid-flow.

Before: unclear plan differentiation + too much thinking at a high-intent moment.

Before: unclear plan differentiation + too much thinking at a high-intent moment.

Before: unclear plan differentiation + too much thinking at a high-intent moment.

Key Decisions

Key Decisions

Key Decisions

Decision 1: Make plans comparable at a glance

Decision 1: Make plans comparable at a glance

Why

Why

Users can’t decide if they can’t compare.

Users can’t decide if they can’t compare.

What changed

What changed

Side-by-side comparisons for clearer differentiation.

Side-by-side comparisons for clearer differentiation.

Result

Result

Faster decisions, fewer exits.

Faster decisions, fewer exits.

Before vs After plan layout

Decision 2: Use clear pricing structure across durations

Decision 2: Use clear pricing structure across durations

Why

Why

Monthly/quarterly/annual pricing needs an obvious value ladder.

Monthly/quarterly/annual pricing needs an obvious value ladder.

What changed

What changed

Cleaner pricing hierarchy across durations.

Cleaner pricing hierarchy across durations.

Expected effect

Expected effect

Higher confidence + fewer “I’ll think later” drop-offs.

Higher confidence + fewer “I’ll think later” drop-offs.

Pricing ladder

Decision 3: Reduce friction in payment

Decision 3: Reduce friction in payment

Why

Why

Even after selecting a plan, confusion around payment/discounts causes drop-offs.

Even after selecting a plan, confusion around payment/discounts causes drop-offs.

What changed

What changed

Clear discount callouts + QR-based transactions + clearer CTAs.

Clear discount callouts + QR-based transactions + clearer CTAs.

Impact signal

Impact signal

-17% drop-offs and fewer failed transactions.

-17% drop-offs and fewer failed transactions.

Payment step

Solution Walkthrough

Solution Walkthrough

Solution Walkthrough

Impact

Impact

Impact

+22%

Paid subscriptions

Clearer plan comparison and pricing structure

-17%

Smoother selection

Checkout + payment clarity

40%

Faster decisions

Side-by-side comparisons + nudges

2.3x

Engagement

More confident exploration and selection

Learnings + Next Steps

Learnings + Next Steps

Learnings + Next Steps

Learnings

Learnings

  • Plan selection is a trust problem, not a UI problem.

  • The best conversion wins came from reducing uncertainty, not removing features.

  • Plan selection is a trust problem, not a UI problem.

  • The best conversion wins came from reducing uncertainty, not removing features.

Next steps

Next steps

  • A/B test different value ladders and default selections

  • Improve personalization (recommend plan based on viewing intent)

  • Track drop-offs by payment method and discount type

  • A/B test different value ladders and default selections

  • Improve personalization (recommend plan based on viewing intent)

  • Track drop-offs by payment method and discount type