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Growth idea action plan

Right-user feedback filter

Treat feedback as strategic signal only when it comes from the segment you are actually building for, and translate feature requests into root problems before acting on them.

rare tactic free budget User Research, Product, Community Stages: 0-100, product-market-fit, roadmap

Why this can grow a startup

Early teams can drown in feedback that is thoughtful but directionally wrong. Filtering by target segment preserves product coherence, while asking for the use case and underlying problem turns reactive feature collection into real market learning. That keeps growth work pointed at the users who could actually become your wedge, not the loudest people in the inbox.

Ian's take

From scaling consumer platforms across MENA and Southeast Asia, my default is to distrust growth work that only looks good in a slide. My bias is to treat this as a small market test first. Make the audience narrow, make the promise concrete, and let the first real response decide whether it deserves more work. I would run it small enough to learn quickly, then only scale the parts that real users repeat, save, reply to, or buy from. For this tactic, I would watch one clear growth signal before putting more time or budget behind it.

Action plan

  1. Define one narrow startup segment where right-user feedback filter can create a measurable lift.
  2. Turn the tactic into one offer, page, campaign, or workflow for the User Research and Product channel.
  3. Use the evidence from linear.app to set the first version of the message, format, and audience.
  4. Launch a small test for 7 to 14 days with one success metric: one measurable growth signal.
  5. Review the result, keep the winning message, remove weak variants, and turn the learning into a repeatable growth playbook.

Source-backed example

Linear's Method warns that if you are building for early-stage startups, listening too closely to enterprise feedback will likely send the product in the wrong direction. It also recommends moving feature requests back to the underlying problem and use case.

Source: Linear Method (linear.app)

GrowthDex source hub: Linear Method

Last checked: May 24, 2026

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Ian Goh has helped grow consumer platforms across Southeast Asia, India, and MENA. His work includes scaling Tiki to 100M+ users, doubling BIGO's MENA revenue in 7 months, and increasing OYO's direct booking share across 6 Southeast Asian markets.

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If you want someone to pressure-test this against your real market, Ian works with founders on growth, market entry, and operator-led distribution.

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