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UnRespiro

How a Spanish startup validated mental health demand before writing a single line of code

Summary

UnRespiro launched as a Spanish mental health app targeting young adults aged 18-35 who could not afford or access traditional therapy. Before building, the founders ran extensive user discovery, built a landing page that converted at 8%, and ran a concierge MVP with 12 paying users — all before committing to full development.

What worked

  • Ran 43 user interviews before writing code — discovered the real problem
  • 8.3% landing page conversion with only €200 in ad spend validated demand
  • Concierge MVP with 12 paying users proved willingness to pay before full development
  • Wizard of Oz test revealed users wanted micro-sessions, not weekly sessions

What failed

  • Initial product vision was based on assumptions about what users wanted, not user research
  • First version included complex AI matching that users did not need or request

The full story

The Spanish mental health app market in 2021 was dominated by either expensive online therapy platforms (€70-150/session) or free self-help content with no personalization. The gap was clear: young Spaniards who knew they needed mental health support but could not afford weekly sessions and did not find generic meditation apps sufficient.

The UnRespiro founding team — two non-technical founders with backgrounds in psychology and marketing — spent 6 weeks conducting 43 user interviews before building anything. They found that their target users were acutely aware of their mental health needs, had already tried Headspace and Calm and found them insufficient, but were reluctant to commit to formal therapy due to cost and stigma.

Their validation process included a landing page test that achieved 8.3% email capture rate with €200 in Facebook ads, a concierge phase where founders personally matched users with psychologists via WhatsApp for 3 months, and a Wizard of Oz phase where they built a basic iOS interface while human psychologists handled all the "AI" recommendations behind the scenes.

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