{
  "id": 14868425,
  "title": "Why “Would You Use This?” Is the Most Useless Question in Product Research",
  "url": "https://urgent.news/2026/10/16/why-would-you-use-this-is-the-most-useless-question-in-product",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-10-16T04:30:27.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/starebrain/why-would-you-use-this-is-the-most-useless-question-in-product-research-247g"
  },
  "original_language": "en",
  "account": "Many product developers make the mistake of asking \"Would you use this?\" when seeking feedback. This question is purely hypothetical, requiring no effort from the respondent. They imagine themselves in the future using the product as it might exist, but that future self is purely imagined and their response is not genuine. What's needed is real behavior, which only occurs in the past.\n\nA far more effective question is \"Walk me through the last time you dealt with [the issue].\" This forces people to recall an actual event they experienced. They can't respond with a hypothetical scenario. The story they recount reveals far more than a hundred survey answers could. It shows exactly what they did in that situation, not what they think they'd do.\n\nThe insights gained from this question are significant:\n\n1. What they actually did, not what they believe they'd do. Someone who says they'd pay for a productivity tool may already have an alternative method like a spreadsheet or Slack thread. Their real behavior shows what they'd actually use, not what they're planning to adopt.\n\n2. What your true competition is. It's rarely another product. It's often just doing it manually, asking an assistant, or giving up altogether. Knowing the real alternatives shows you the hurdle you must overcome.\n\n3. Whether the problem is significant enough to warrant a solution. If people can't remember the last time the issue occurred, it's not a pressing problem. Lack of vivid recollection means the pain isn't great enough to drive behavior change.\n\nAfter hearing the story, ask follow-up questions like \"What did you do next?\" Keep probing. Each \"what did you do next?\" uncovers a new friction point in their workaround process. Those friction points become features you could eliminate in your product.\n\nThe \"Would you use this?\" question feels like validation because people are polite and say yes. It filters for politeness, not pain. The \"last time\" question, while potentially revealing a problem isn't severe enough, is far more informative. Learning this through conversation is better than learning it too late after six months of development.\n\nIn summary, replace generic validation questions with more targeted ones. Instead of asking \"Would you use a tool for X?\", ask \"Walk me through the last time you did X.\" Ask \"Is X a problem for you?\" then follow up with \"How often does X come up? What did you do last time? Would you pay for this? What have you already tried? What did it cost you? Does this solve your problem?\" The most valuable signal comes from revisiting your product after a week, not from survey answers. This conversation method can provide far more valuable insights than a hundred \"would you use this?\" responses. Go find one person, ask them about the last time, and see what knowledge you gain.",
  "summary": "You’ve done it. I’ve done it. Everyone building something has done it. You post your idea, your landing page, your demo. You ask “would you use this?” or “does this solve a problem for you?” Everyone says yes. You feel validated. You learn nothing. ** The Problem With Hypothetical Questions ** “Would you use this?” is a hypothetical. It costs the person nothing to say yes. They’re imagining a…",
  "key_points": [
    "\"Would you use this?\" question is hypothetical and unproductive",
    "Effective question: \"Walk me through the last time you dealt with [the issue]\"",
    "Insights from this question: actual behavior, true competition, problem significance"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}