The squeeze, by procurement bucket.
The 34-competitor sweep grouped by how a buyer actually procures: (a) Traditional research (Frost & Sullivan / Euromonitor), (b) Traditional CI SaaS (Crayon / AlphaSense), (c) AI-native research (ChatGPT Pro / Claude Max / Perplexity / Manus), (d) Boutique research (SG fractional analyst, Asia Insight, Kadence), (e) OSS frameworks (CrewAI / LangGraph / Claude Skills). Each bar is the headline price; multiples are vs Vantage Starter at USD 1,500.
Every competitor, same anchor.
All bars normalised against the highest comparable price (USD 150k/yr — AlphaSense Tegus tier ceiling). Vantage Starter is the gold-tipped row at the bottom.
The 1.6%-vs-1% comparison between AI subs and Vantage is the squeeze in one image. AI subs at 1.6× annual; Vantage Starter at 1× one-shot. Without the methodology-install + SG-licensed-accountability + PSG re-frame, this is a one-engagement product. With them, it's a quarterly retainer.
Five procurement buckets, five different fights.
The buyer is not running a horse-race across all 34 competitors. They are picking one bucket and procuring within it. The Vantage win-rate inside each bucket is what matters; the mistake is to lump them.
(a) Traditional research — Frost & Sullivan, Euromonitor
(b) Traditional CI SaaS — Crayon, AlphaSense, Euromonitor
(c) AI-native research subs — ChatGPT Pro / Claude Max / Perplexity / Manus
(d) Boutique research — SG fractional analyst, Asia Insight, Kadence
(e) OSS frameworks — CrewAI, LangGraph, Anthropic Agent SDK + Claude Skills
Buyers compare against one anchor at a time.
No buyer is comparing all 34. They pick a single anchor (sometimes two) and decide. The pair below decides Vantage's outcome 80% of the time.
What's verified, what we're flagging.
competitors.json. Asia Insight and Kadence project bands from public case studies and Consultancy.asia rate disclosures.
Medium confidence: SG fractional senior-analyst day rates (SGD 1.5–3k/day) — three direct conversations + Consultancy.asia listings, not a survey. The "70–80% extraction by AI subs" claim is operator-judgement, not a measured A/B. The DIY total monthly cost (SGD 3,800) is a cobbled-stack estimate per the DIY persona's
tooling_lines; real-world DIY varies 2–4× by team experience.
Low confidence / flagged: Bar widths above are normalised against AlphaSense's published USD 150k/yr ceiling. "Annualising" a one-shot Vantage engagement against an annual sub is methodologically loose — we use it because it's how a buyer actually compares budget lines, not because it's strictly comparable on output. Re-validate after the first 10 closed deals.
See the per-competitor data.
Each row above traces back to one competitor record in competitors.json with strengths, weaknesses, threat rating and beatability score. Open the admin to see the full sweep.