Vertical industry data SaaS
Build a B2B SaaS that aggregates 'sawdust' data from one industry (permits, shipments, transactions) into a paid dashboard.
The idea, in plain language
This business aggregates overlooked industry data such as permits, listings, prices, shipments, directories, or transactions into paid dashboards, APIs, alerts, or executive briefings. Customers are operators, investors, service businesses, or niche professionals who need better market intelligence than they can gather manually. It takes scraping, cleaning, enrichment, workflow design, niche domain knowledge, sales, and enough product polish to make the data useful; startup capital can be modest because the main inputs are software, automation, and distribution. The videos cite CB Insights at $100M/year, Mattermark growing 31% month over month, Flexport/Import Genius-style trade data, a $50M phone-booths case study, and adjacent examples such as Carfax-for-homes and lead sales to home-service businesses.
Where the sources agree
- Valuable data products usually come from boring, fragmented, or hard-to-access information in specific industries.
- Domain knowledge is a moat because customers care about useful answers, not raw scraped data.
- A daily briefing, dashboard, paid API, or lead feed can turn the same dataset into recurring revenue.
- Fast prototypes and early niche users are more important than knowing every detail of the industry upfront.
Where they differ
- MFM frames sawdust data through large company stories such as CB Insights, Mattermark, Import Genius, and Flexport-adjacent data plays.
- Koerner frames the same pattern as approachable AI automations, niche data products, lead sales, and property or contractor data services.
- Some videos emphasize software dashboards and APIs, while others emphasize workflow automation or selling leads to local businesses.
- Scale expectations vary from simple MVPs and local lead products to $100M/year companies, 31% month-over-month growth, and $50M arbitrage stories.
- The customer could be local SMBs, home-service companies, investors, property operators, or specialized industry teams depending on the dataset chosen.
What each source says
MFMAsking A $100M/Year Founder For Profitable Business Ideas (#413)
Anand Sanwal describes sawdust-data businesses, tiny growing niches, daily executive briefings, and CB Insights-scale opportunities.
Watch on YouTubeKoernerThe Most Useful AI Skill You Can Learn Today
Michael Shimeles argues that industry knowledge plus AI workflows can become simple web apps and automations outside the tech bubble.
Watch on YouTubeKoernerHow to Use AI to Clone Others for Profit
Sam Thompson connects AI clones, niche data products, MVP pricing, retention, and lead sales to home-service businesses.
Watch on YouTubeMFMUnicorn Founder on Unseen Arbitrages, the Paradox of Wealth + Charlie Munger Wisdom
Ryan Petersen's discussion uses Import Genius, data-as-a-service, unseen arbitrages, and a $50M phone-booths case study as models.
Watch on YouTubeMFMHow Mattermark Acquired Early Users – Danielle Morrill speaks at Hustle Con 2016
Danielle Morrill's Mattermark talk shows a startup-prediction data product prototyped quickly and grown at 31% month over month.
Watch on YouTubeKoernerExploring a New Business Idea: Drone Roof Inspections and Selling Leads to Roofers
Chris's Q&A includes drone roof inspection leads and a Carfax-for-homes service as local data and lead-generation variants.
Watch on YouTubeindie-hackers#021 – Starting a Mission-Driven Company with Rachel Carpenter of Intrinio
Rachel Carpenter recounts how her team built Intrinio, a marketplace/API selling financial data to developers and fintechs, through a scrappy, mission-driven early stage.
Listen on Indie HackersTools people use for this
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