Research-as-a-service
Provide paid research for clients (market, competitor, prospect) delivered as reports or briefs, billed hourly or per project.
The idea, in plain language
Research-as-a-service sells market, competitor, prospect, testing, due-diligence, or operational research as fixed reports, retainers, or software-assisted services. Customers include SMBs, SaaS operators, investors, communities, founders, and niche operators who need decisions supported by better data. It requires research judgment, automation, outreach, packaging, and sometimes a community or SaaS layer; the videos cite ListKit reaching over $1M/year in 87 days, Tiger 21 doing $20M+ in revenue, an agency running 100x more tests, and a stump-grinding listener doing $32K in two months. The numbers are stronger for adjacent productized services and communities than for pure paid reports, so the best version combines AI agents, scraping, and a narrow vertical offer.
Where the sources agree
- The valuable piece is turning messy information into a decision or workflow the buyer can act on.
- Productized scope and repeatable delivery matter more than bespoke consulting on every engagement.
- AI agents and automation can increase test volume, data gathering, and report production.
- A narrow niche makes selling and differentiation easier than broad general research.
Where they differ
- Starter Story presents a SaaS plus productized-service cold-email model with a specific $1M/year outcome.
- Greg Isenberg frames research as autonomous experimentation, agent-in-a-box products, due diligence, and internal productivity labs.
- MFM mixes paid communities, pandemic monitoring, trust-as-a-service, certifications, deepfakes, and memory infrastructure rather than one research service playbook.
- The Koerner example is field research for a local service business, including hundreds of cold calls and financial projections.
- Some versions sell reports directly, while others monetize the research through software, community, consulting, or agency upsells.
What each source says
Starter StoryI Built A $1M SaaS In 87 Days
Andre Haykal Jr. built ListKit into over $1M/year in 87 days by combining productized service and SaaS distribution through cold email.
Watch on YouTubeIsenbergKarpathy's "autoresearch" broke the internet
Greg turns Karpathy's Autoresearch into ideas like always-on experiments, research-as-a-service, due diligence shops, and agency-scale testing.
Watch on YouTubeMFMMFM #160: How to Build a Paid Community Making $20M a Year
MFM uses Tiger 21 at $20M+ revenue and Sole Savy to show paid communities built around valuable shared information.
Watch on YouTubeMFMHow To Build A 100 Year Old Company (#469)
The episode suggests pandemic-monitoring data services and deepfake-related data opportunities inside a broader long-lived-company discussion.
Watch on YouTubeMFMHow to Make Millions With a Modern Day Infomercial | My First Million #221
The infomercial episode points to trust-as-a-service, subscription content, certifications, and marketplace-founder research angles.
Watch on YouTubeIsenberg"Y Combinator Is Overrated" - Inside the brain of this 22-Year-Old who built Multiple Viral Products
Avi Schiffmann argues for Memory as a Service and category creation, with research value tied to AI memory infrastructure.
Watch on YouTubeKoernerHow to Launch and Grow a $4m/Year Stump Grinding Business
The stump-grinding discussion uses cold-call research with hundreds of tree companies, projections, and a B2B home-service agency wrapper.
Watch on YouTubeTools people use for this
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