Agent skill · business finance · himself65
saas-valuation-compression
Analyze how a private SaaS company's ARR valuation multiple changed across funding rounds, and attribute the compression or expansion to rate cycles and macro selloffs, growth deceleration, narrative shifts (including an AI premium), competition, and investor demand, benchmarked against private-market medians and peers. Use this skill whenever the user asks about valuation compression, ARR multiples, round-to-round valuation or multiple changes, down rounds, or wants to compare a VC-backed software company's funding rounds. Research the rounds rather than answering from memory.
Why this skill is useful
Provides a structured framework and specific metrics for analyzing SaaS valuation changes that the AI wouldn't reliably generate on its own.
What it needs
About 4k tokens when loaded. Last updated 2026-08-05. 3,127 stars on the source repository.
What this skill does
SaaS Valuation Compression Analyzer What This Skill Does For a given SaaS company, research its funding history and compute ARR-based valuation multiples at each round. Then explain the compression (or expansion) using a structured framework that covers macro rates, growth trajectory, narrative shifts, and comparables. Render the output as an inline visualization (using the Visualizer tool) plus a concise prose explanation, rather than a wall of numbers. --- Workflow 1. Gather Data via Web Search Research these, running independent searches in parallel: Each funding round of the target company — round name, date, amount raised, post-money valuation, and lead investor. ARR at or near each round date — from press coverage, founder interviews, or investor posts; note when a figure is estimated. Growth and retention around each round — ARR growth rate, NRR, churn, notable customers. Narrative context — AI positioning and product launches, category leadership, competitive moves. Private-market SaaS multiples at each round date — fall back on the dated tables in references/benchmarks.md when search is thin. 2. Build the Data Model For each funding round, extract or estimate: Field How to get it --- --- Round name Direct from search Date Direct from search Amount raised Direct from search Post-money valuation Direct or compute from ownership %; if unavailable, note as estimated ARR at round date Search explicitly; if not found, estimate from customer count x ARPC or interpolate ARR multiple valuation / ARR Lead investor Direct ARR estimation heuristics (when not public): Seed/Series A: ARR often $500K–$3M Series B: typically $5M–$20M Series C: typically $20M–$60M Cross-check against customer count x average deal size if available 3. Compute Compression Metrics For each consecutive round pair (e.g., B → C): The three changes multiply rather than add: valuation multiplier = ARR multiplier × multiple multiplier, i.e. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills himself65/saas-valuation-compression