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Why You Should Organise an Immersion Trip for Your Next Project
Summary
Grab Ventures relies on on-the-ground immersion trips to uncover real consumer behaviors and validate hypotheses that desktop research cannot address. Placing cross-functional teams directly into target markets reveals nuanced consumer motivations, such as Indonesian grocery shoppers prioritizing physical product freshness and price sensitivity over mere convenience. Effective immersion trips require pre-fieldwork reconnaissance by local residents, collaborative hypothesis generation across business and tech disciplines, and non-leading question design. Research teams should operate in small groups of two or three alongside experienced local translators while holding structured end-of-day debriefs to synthesize contextual observations. Within the Double Diamond framework, these field insights support the Discover phase and directly feed into design sprint workshops for problem framing.
Context
Traditional research methods like desktop research, reports, and surveys are often insufficient to uncover the authentic motivations, pain points, and environmental realities of overseas consumers.
Approach / What changed
Deploying cross-functional teams on structured field immersion trips that combine local reconnaissance, observational shadowing, non-leading contextual interviews, and daily debriefs.
Takeaways
Field research in Indonesia disproved the assumption that online grocery adoption is driven by convenience, revealing that physical verification of freshness and price sensitivity are the primary consumer motivators.
Observational shadowing revealed wet market vendors organically coordinating grocery orders over WhatsApp, accepting e-wallets or bank transfers, and utilizing bike drivers for delivery.
Immersion teams should split into groups of two or three and dress like locals to avoid triggering facility security interventions or intimidating interview participants.
Source and freshness
- Source
- engineering.grab.com
- Published
- Added to Yomu
- Last updated
Summaries are generated from the original by a language model. Check the original before relying on it.
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