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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. Always render the output as an inline visualization (using the Visualizer tool) plus a concise prose explanation. Do not just return a wall of numbers. Step-by-Step Workflow 1. Gather Data via Web Search Search for each of the following. Run searches in parallel where possible. For the target company: [company] funding rounds valuation ARR revenue [company] Series [X] raised valuation for each round [company] annual recurring revenue ARR [year] for each round date [company] investors lead investor [round] For macro context: SaaS ARR valuation multiples [year] private market Use the known benchmark table below as fallback if search is thin. For narrative context: [company] AI customers product announcement [year] — AI narrative premium? [company] growth rate churn NRR [year] — fundamentals shift? 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): multiple_compression_pct = (later_multiple - earlier_multiple) / earlier_multiple × 100 valuation_growth_pct = (later_val - earlier_val) / earlier_val × 100 arr_growth_pct = (later_arr - earlier_arr) / earlier_arr × 100 Key insight: valuation_growth = arr_growth + multiple_change If ARR grows faster than the multiple compresses, absolute valuation still rises. 4. Attribute Compression to Causes Use this checklist. For each cause, rate it: Primary / Contributing / Not applicable. Macro / Rate Environment Was the earlier round during 2020–2021 ZIRP bubble? (adds ~2–5x artificial premium) Was the later round during 2022–2023 rate hikes? (removes bubble premium) Was the later round during or after the April 2026 Software Meltdown? (public SaaS down 40–86% from 52w highs; tariff/trade-war driven selloff crushed multiples sector-wide — even high-growth names like Figma -87%, monday.com -80%, HubSpot -70%, ServiceNow -58%) Reference: SaaS private market median multiples by period: Period Approx Median ARR Multiple (private) Context 2019 ~8–12x Pre-pandemic baseline 2020 ~12–18x ZIRP begins, multiple expansion 2021 Q1–Q3 peak ~35–45x Peak bubble 2022 H2 ~15–20x Rate hikes begin, first compression wave 2023 trough ~8–12x Rate plateau, valuation reset 2024 ~12–18x AI narrative recovery, selective re-rating 2025 H1 ~16–22x Continued AI-driven recovery 2025 H2–2026 Q1 ~10–16x Tariff shock / trade-war selloff begins 2026 Q2 (Apr meltdown) ~6–10x Software Meltdown — broad sector crash, public SaaS down 40–86% from 52w highs (These are rough private market estimates. Public SaaS multiples are ~30–50% lower. The April 2026 figures reflect the acute selloff; private marks typically lag public by 1–2 quarters.) Growth Deceleration Did YoY ARR growth rate slow materially between rounds? (most common cause) Did NRR/net retention drop? Narrative Shift Did the company lose a major product story (e.g., lost PLG thesis, missed category leadership)? Did competitors emerge or incumbents catch up? AI Premium (positive or negative) Does the company serve AI-native companies (OpenAI, Anthropic, etc.) as customers? → premium Did the company pivot to AI narrative credibly? → premium Did the company fail to articulate AI story? → discount vs peers Note: In the Apr 2026 meltdown, even strong AI narratives did not protect multiples — Snowflake (-53%), Datadog (-46%), MongoDB (-48%) all cratered despite AI tailwinds. AI premium may be necessary but not sufficient in a macro-driven selloff. Competitive / Market Market saturation signal (e.g., Okta pressure on WorkOS, Auth0 competition) Customer concentration risk revealed Investor Supply / Demand Was the later round smaller and more selective? → price discipline New tier of lead investor (e.g., Tier 1 growth fund vs seed fund)? → may signal higher or lower conviction 5. Build the Visualization Use the Visualizer tool to render: Metric cards row — valuation at each round, ARR at each round, multiple at each round, compression % Line chart — ARR multiple over time for the company vs macro SaaS median Bar chart — valuation growth vs ARR growth vs multiple change (decomposition) Comparison bar — company compression vs 2–3 peer comparables (Vercel, Netlify, Fastly, or sector peers) Cause attribution table inline in prose (Primary / Contributing / N/A per factor) See design guidance: use teal for positive/growth, coral for compression/negative, gray for macro baseline, blue for valuation figures. Follow the CSS variable system throughout. 6. Write the Prose Summary Structure as: One-sentence verdict — e.g., "Multiple compressed 36% but ARR grew 5x, so absolute valuation rose 3.8x." Primary cause — the #1 factor explaining compression Narrative premium/discount — AI story, category leadership, or lack thereof Comparable context — how does this company's compression compare to peers? Forward implication — what would need to be true for the multiple to expand at next round? Output Format Always produce: Inline visualization (Visualizer tool) — comes first Prose summary (5–8 sentences) — follows the visualization Optional: flag data confidence level if ARR had to be estimated Known Benchmarks & Comparables (pre-loaded) Use these as context when search results are thin or for the comparison chart. Company Round pair Earlier multiple Later multiple Compression % Primary cause Vercel D → E (2021→2024) ~140x ~32x -77% ZIRP unwind + growth decel WorkOS B → C (2022→2026) ~105x ~67x -36% Partial ZIRP unwind; defended by AI narrative Netlify B → stalled (2021→?) ~90x N/A N/A No new round; AI narrative absent Fastly Public (2021 peak→2024) ~35x rev ~3x rev -91% No AI pivot, growth decel Stripe — — — — Private; est. flat/compressed 2021→2023 down round HashiCorp Acquired by IBM 2024 — — — Acq at ~8x ARR vs ~40x peak April 2026 Software Meltdown — Public SaaS Drawdowns As of April 9, 2026, a broad tariff/trade-war driven selloff crushed public software valuations. Use these as reference for how private multiples will lag-compress over the following 1–2 quarters. Ticker Company Δ from 52w High Sector relevance FIG Figma -86.7% Design/dev tools — worst hit MNDY monday.com -80.2% Work management SaaS TEAM Atlassian -75.7% Dev tools / collaboration HUBS HubSpot -69.9% Marketing/CRM SaaS WIX WIX -65.1% Website builder GTLB GitLab -63.6% DevOps CVLT Commvault -61.7% Data protection WDAY Workday -59.1% HR/Finance SaaS NOW ServiceNow -57.8% Enterprise IT workflows INTU Intuit -56.0% FinTech/SMB SaaS SNOW Snowflake -52.8% Data cloud KVYO Klaviyo -52.9% Marketing automation DOCU DocuSign -52.3% eSignature MDB MongoDB -47.9% Database SAP SAP -47.6% Enterprise ERP DDOG Datadog -45.7% Observability APP AppLovin -47.6% AdTech/mobile CRM Salesforce -42.5% CRM market leader ADBE Adobe -34.6% Creative/doc SaaS ZM Zoom -13.9% Video/collab (already de-rated) Source: @speculator_io, April 9, 2026. Average drawdown across tracked software names: ~50–55%. Edge Cases Down round: Multiple and absolute valuation both dropped. Note dilution implications. No public ARR: Use customer count x estimated ARPC, and label as estimate with +/- range. Single round only: Compute multiple vs sector median for that date; can't do compression analysis. Explain this. Pre-revenue: Use forward ARR or GMV multiple if applicable; note the different basis. Acqui-hire / strategic acquisition: Acquisition price often reflects strategic premium or distress, not pure ARR multiple — flag this.
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