Starter Story
Starter Story lists 3,032 revenue-generating startup case studies with tools, timelines, and income, so indie hackers can copy a working playbook.
Product facts
Commercial Suite- Data checked
- 2026-10-01
Capabilities
- Breaks down real cases
- Searchable idea database
- Maps monetization paths
Snapshot figures reflect the check date and may change over time.
What stalls most side projects is not the code — it’s not knowing what to build or how anyone else made theirs work. Starter Story is a startup case-study database whose own pages claim 3,032 real, revenue-generating projects (checked 2026-10-01), each broken down by founder, start year, revenue, channels, and tools. A Chinese short-video channel summed it up well: nearly 3,000 real projects with the tools and timelines laid out plain.
Core Purpose
Starter Story takes a different lane from idea-of-the-day products like IdeaBrowser: it documents businesses that already made money. Each case study details the stack, startup cost, timeline, and revenue; the companion idea database (the Ideas page reads “Search 3,032+ real, revenue-generating projects”) browses categories by median monthly revenue, such as marketplaces with a $200K/mo median. Idea generators answer “what to build”; this answers “how others actually did it.”
Key Scenarios
- Finding a direction: browse cases by category to see which businesses actually get paid for, before committing to one.
- Benchmarking: median monthly revenue and startup costs for similar projects are directly comparable, so budgets stop being guesses.
- Learning go-to-market: cases name the acquisition channels and tool combinations, which you can recombine into your own cold-start plan.
Trying it and its limits
Browsing starterstory.com needs no signup — case lists and the idea database are open. Two limits: most full case studies sit behind a membership wall, so check how many you’d actually read before subscribing; and the catalog skews to Western markets, so treat the channels and pricing as calibrated for US-style distribution, not universal. For methodology on mining ideas in the first place, our earlier piece on Product Hunt idea mining pairs well with it.