Tools
Understanding TrustMRR Clusters: 4 Types of AI-Generated SaaS Segments
Last updated: April 2026
Clusters are AI-generated segments that group TrustMRR startups by shared characteristics. Each cluster carries a thesis, member list, defining traits, tech-stack trends, and market gaps. Four cluster types exist - revenue tier, growth pattern, business model, and acquisition - and each surfaces a different angle on the same dataset.
On this page
Revenue-tier clusters
Group startups by where they sit on the revenue distribution. Typical clusters include pre-traction (< $1k MRR), early traction ($1k–$10k), product-market fit ($10k–$50k), scaling ($50k–$200k), and breakout ($200k+).
Use these when you want to benchmark against operators at your stage rather than across the full dataset.
Growth-pattern clusters
Group startups by their 30-day growth trajectory. Typical clusters include hyper-growth (>50% MoM), steady growth (5–20% MoM), flat (0–5%), and declining (negative).
Use these to identify pattern peers and learn what's working for startups on your trajectory.
Business-model clusters
Group startups by how they make money - pure SaaS subscriptions, freemium with conversion, usage-based, marketplace, consumer subscription, or hybrid.
Use these when you're considering a pricing model change and want to see how comparable startups monetize.
Acquisition clusters
Group startups currently for sale by buyer-thesis archetype - turnkey operations, distribution plays, defensible IP, founder-burnout sales, and consolidation opportunities.
Use these as a buy-side filter when sourcing acquisition targets that match a specific acquisition thesis.
How to use clusters in practice
Clusters are most useful in three workflows:
- Competitive analysis: 'Which growth-pattern cluster does my startup belong to, and who are the peers?'
- Strategy validation: 'Does my pricing model match the business-model cluster of the operators with my target MRR?'
- Acquisition sourcing: 'Show me the consolidation-opportunity cluster - listings where rolling several together creates leverage.'
FAQ
How are clusters generated?
GPT-class models analyze the full startup dataset, identify defining traits per cluster type, and assign each startup to the best-fit cluster. Clusters are re-generated periodically as the dataset grows.
Can a startup belong to multiple clusters?
Yes - across cluster types. A startup can be in a 'breakout' revenue-tier cluster and a 'hyper-growth' growth-pattern cluster simultaneously.
Are clusters useful for outsiders or only for buyers?
Both. Operators use them to benchmark against peers; buyers use them to source acquisition candidates by archetype.
How do I query a specific cluster?
Use the getClusters tool in the AI Research Chat, or browse /revenue-intelligence/clusters directly.
Related help pages
Getting Started
Getting Started with TrustMRR: A 5-Step Walkthrough
Learn how to use TrustMRR - the revenue intelligence tool with verified MRR across 6,040 SaaS startups. Step-by-step guide from dashboard to category deep-dive to export.
Getting Started
TrustMRR Research Chat: All 7 Tools Explained with Examples
Learn how each of TrustMRR's 7 research-chat tools works - searchStartups, getStartupDetails, getClusters, getCategoryAnalysis, getDeals, getRevenueBenchmarks, and searchMarketData - with example questions.
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