# Commercial Discovery > Prepare and conduct B2B discovery meetings for technology consulting engagements. Generate pre-meeting research briefs, SPIN-based question guides adapted for consulting, stakeholder/buying committee mapping, and structured discovery notes. Use when preparing for a first discovery call, conducting needs analysis for consulting projects, or mapping the decision-making unit within a prospect organization. - Skill: `piperubio/commercial-discovery` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add piperubio/commercial-discovery` - Raw SKILL.md: https://api.skillmd.com/api/skills/piperubio/commercial-discovery/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Product & Planning - Author: piperubio (https://skillmd.com/u/piperubio) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/piperubio/commercial-discovery --- # Commercial Discovery (B2B Consulting Sales) Purpose - Enable thorough, structured discovery for B2B consulting sales. - Unlike SaaS discovery (which demos a product), consulting discovery must deeply understand the client's current state, desired future state, organizational dynamics, and constraints to later design a custom solution. - Prepare the seller and capture structured notes. Key Differentiation from SaaS Discovery - No product to demo — discovery IS the product sample. - Must assess organizational readiness, not just feature fit. - Need to understand current tech stack, team capabilities, and culture. - Must map multiple stakeholders (not just a single buyer). - Consulting discovery often spans 2-3 meetings, not one. Scope - This skill WILL: - Generate pre-meeting research briefs with tailored SPIN questions - Map buying committees and stakeholder dynamics - Produce structured post-meeting discovery notes - Run mini tech-maturity assessments during discovery - Update pipeline state with discovery insights - This skill WILL NOT: - Propose solutions (defer to solution-design phase) - Generate proposals or SOWs - Conduct qualification scoring (see commercial-qualification) Inputs - **prospect-profile.md** — from commercial-prospecting - **commercial-state.md** — pipeline context - **user_input** — meeting details, known contacts, specific areas to explore Outputs (contract) # Output 1: Pre-Meeting Brief (`discovery-prep.md`) - **Company research summary** — key facts, recent news, strategic context - **Known pain points and hypotheses** — from prospecting or prior interactions - **Stakeholder map** — known contacts, roles, likely agenda - **SPIN question guide** — 15-20 questions tailored to this prospect, organized by S/P/I/N (see `references/discovery-frameworks.md`) - **Meeting agenda suggestion** — 45-60 min structure - **Red flags to watch for** — signals this opportunity may not be real - **Success criteria for the meeting** — what "good" looks like # Output 2: Post-Meeting Discovery Notes (`discovery-notes.md`) - **Meeting metadata** — date, attendees, duration - **Current State summary** — tech stack, processes, team, pain points - **Desired Future State** — what success looks like for them - **Gap Analysis** — current → desired, organized by Software / Data / AI - **Buying Committee Map** — Champion, Economic Buyer, Technical Buyer, Coach, Blocker — with names - **Budget signals** — explicit mentions, inferred range - **Timeline signals** — urgency drivers, deadlines, fiscal year - **Competition signals** — other vendors mentioned, internal alternatives - **Next steps agreed** - **Open questions requiring follow-up** # Output 3: Updated `commercial-state.md` Update the opportunity with discovery insights: stage, champion, key pain points, next action. --- SPIN Framework Adapted for Tech Consulting - **Situation**: Current tech landscape, team structure, processes, recent initiatives - **Problem**: Pain points, inefficiencies, failed past initiatives, technical debt - **Implication**: Business impact of not solving (revenue loss, competitive risk, team attrition, compliance risk) - **Need-payoff**: Value of solving (ROI, speed, capability unlock, market advantage) For the full SPIN question bank organized by service line (Software, Data, AI) with 10 questions per category, see `references/discovery-frameworks.md`. Mini Tech Maturity Assessment (during discovery) - Run a quick 5-question assessment per axis (Software / Data / AI) to validate or update prospecting scores. - Compare self-reported maturity vs. observed indicators. - Full questionnaire available in `references/discovery-frameworks.md`. --- Guardrails (must follow) 1. Discovery is about listening, not pitching — question-to-statement ratio should be 3:1 minimum. 2. Never propose a solution during discovery — note the urge, defer to solution-design phase. 3. Always map at least Champion + Economic Buyer — if you cannot identify both, flag as risk. 4. Capture exact quotes when possible — client's own words are gold for proposals. 5. Never assume budget — probe with indirect questions. 6. If discovery reveals the prospect is not a fit, say so honestly rather than forcing it. 7. Flag when a single discovery meeting is insufficient and recommend follow-up. --- Example **Context**: Logistics company (Acme Logistics) exploring data platform modernization. Legacy SQL Server data warehouse, 15-person IT team, $40M revenue. **Sample SPIN Questions**: Situation: - "Walk me through how data currently flows from your TMS and WMS into the SQL Server warehouse." - "How many people on the team write queries or reports against the warehouse today?" Problem: - "What happens when leadership asks for a report that crosses multiple source systems?" - "How long does it take to onboard a new data source into the warehouse?" Implication: - "When route optimization decisions are delayed because data isn't ready, what's the cost per day in fuel and driver hours?" - "If the warehouse goes down during peak shipping season, what's the operational impact?" Need-payoff: - "If your operations team had real-time visibility into shipment status across all carriers, how would that change your customer SLA performance?" - "What would it mean for the business if you could add a new data source in days instead of months?"