PromptsEdge
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SaaS Valuation Compression

Your AI analyzes how a private SaaS company’s ARR multiple changed between funding rounds, attributes the causes, and benchmarks against market medians and peers. Includes charts and a concise verdict.

Try asking: “Analyze ARR multiple compression for Vercel between Series B and D”

himself65 on GitHub

Curated by PromptsEdge from a public repo · MIT license. All credit goes to the author.

What is this skill?

For founders, investors, and analysts, understanding why a SaaS company’s valuation multiple compresses or expands across funding rounds is critical—especially in volatile markets. With this skill, your AI researches a company’s funding history, calculates ARR-based valuation multiples for each round, and attributes the change to macro cycles, growth trends, narrative shifts (like an AI premium), competition, and investor demand. Results are benchmarked against private-market medians and relevant peers, with clear charts and a concise summary.

What you can do

  • Track ARR multiple changes across rounds: "How did Vercel’s ARR multiple change from Series B to C?"
  • Attribute compression or expansion: "Why did Stripe’s multiple compress in 2026?" gives a breakdown by macro, growth, and narrative factors.
  • Compare to market benchmarks and peers: "Is Netlify’s latest round above or below the median?"
  • Visualize valuation, ARR, and multiples: Get line and bar charts showing trends and peer comparisons.
  • Get a concise verdict and forward outlook: Each analysis ends with a one-sentence summary and implications.

How it works

When you request a SaaS valuation analysis, your AI gathers funding round data, valuations, and ARR figures via web search. It calculates the ARR multiple for each round, measures the change, and benchmarks against dated private-market medians and comparables. The AI then attributes the compression or expansion to factors like rate cycles, growth deceleration, narrative shifts (including the AI premium), and competitive dynamics. Visualizations and a concise verdict are included for clarity.

Good to know

  • Works on all platforms (Claude.ai, Claude Code, etc.).
  • Uses web search for funding and ARR data; accuracy depends on public disclosures.
  • Reference files provide dated benchmarks and comparable round analyses.