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Leaders from consumer tech, product, marketing, and AI shared how community-driven thinking, smarter attribution, and practical AI adoption are reshaping sustainable mobile app growth in an era of constant disruption.
Building sustainable growth in mobile apps has become harder. Rising acquisition costs, shrinking budgets, fragmented customer journeys, and rapid AI disruption are forcing leaders to rethink how growth is defined, measured, and delivered.
That was the message from a panel featuring Frank (Yu Hang) Ng, VP Commercial & Marketing, PRISM+ (Formerly Ex-SVP, Growth, Intellect); Jennifer Choi, Head of AI Product Development & Government Transformation, Grab; Willynn Ng, Regional Head (International Markets), TanTan; Shubham Sinha, Product Lead, FairPrice Group; and Daniel Tan, APAC CMO and Media Executive.
At Unlocked: Mobile & App Growth Summit, they explored how community has emerged as a critical growth lever, both externally with users and internally within teams, while debating how brands can balance scale with personalisation, deliver impact with limited resources, and adopt AI without losing trust or relevance.
The panel also unpacked how attribution models are evolving, why post-install behaviour matters more than downloads, and how constraints can spark creativity rather than limit growth.
Top insights Martechvibe learned from the panel;
1. Community is a growth engine, not a brand add-on
Communities drive retention, advocacy, and long-term value by moving beyond transactional engagement. When users, partners, or employees feel involved in co-creation and shared purpose, platforms benefit from stronger loyalty, organic growth, and resilience in competitive markets.
2. High-impact growth prioritises quality over volume
Success is no longer defined by downloads or reach alone. Focusing on meaningful actions—post-install engagement, retention signals, referrals, and trust—creates sustainable growth. Brands that optimise for long-term user value outperform those chasing short-term vanity metrics.
3. AI works best when grounded in real problems
AI adoption succeeds when tied to clear business challenges, rapid experimentation, and practical guardrails. Showing tangible outcomes through small pilots builds confidence, while blending automation with human judgment helps organisations innovate without sacrificing safety, trust, or relevance.
Watch the full video here.
