> ## Documentation Index > Fetch the complete documentation index at: https://docs.introw.io/llms.txt > Use this file to discover all available pages before exploring further. # Micro-Courses from Closed-Lost Patterns > Use when a Partner Enablement lead, Channel Chief, or RevOps user wants to detect patterns in closed-lost partner deals, clustering by lost-reason and customer context, and generate /… *Vendor skill for [Use case 05: Training](/headless/agentic-use-cases/training).* **Skill ID:** `vendor-microcourse-from-closed-lost` Use when a Partner Enablement lead, Channel Chief, or RevOps user wants to detect patterns in closed-lost partner deals, clustering by lost-reason and customer context, and generate / suggest targeted micro-courses that address the specific gaps the losses reveal. Trigger phrases include "what are we losing on", "closed-lost patterns", "training from losses", "micro-courses from lost deals", "what should we train on next", "closed-lost driven enablement". **Built for:** Partner Enablement Manager · Partner Program Manager · Channel RevOps **Workflow:** Closed-lost partner deals + lost-reasons → Failure patterns → underlying gap (when loss-driven) → Outline · worked example · open-question rubric → Targeted to partners working similar pipeline ```md SKILL.md theme={"theme":{"light":"github-light","dark":"github-dark"}} --- name: vendor-microcourse-from-closed-lost description: Use when a Partner Enablement lead, Channel Chief, or RevOps user wants to detect patterns in closed-lost partner deals, clustering by lost-reason and customer context, and generate / suggest targeted micro-courses that address the specific gaps the losses reveal. Trigger phrases include "what are we losing on", "closed-lost patterns", "training from losses", "micro-courses from lost deals", "what should we train on next", "closed-lost driven enablement". --- # Micro-Courses from Closed-Lost Patterns (Vendor) **Audience**: Vendor, **claude.ai Introw** MCP. **Use case**: 05, Training. ## When to use this skill Use when a Partner Enablement lead, Channel Chief, or RevOps user wants to detect patterns in closed-lost partner deals, clustering by lost-reason and customer context, and generate / suggest targeted micro-courses that address the specific gaps the losses reveal. **Sample prompts that fire this skill:** - "what are we losing on" - "closed-lost patterns" - "training from losses" - "micro-courses from lost deals" - "what should we train on next" - "closed-lost driven enablement" ## Why this matters Up to **70% of training content is forgotten within 24 hours, 87% within a week** without reinforcement (Ebbinghaus / industry consensus). Static training catalogs accumulate content nobody uses while real, current losses go un-addressed. The signal that matters most: **partners losing deals tells you exactly what they need to learn**. Introw can generate and push a 15-minute micro-course to all enabled resellers in **under one hour**: vs. the typical multi-week instructional design cycle. SalesHood / Whatfix research shows AI-coaching delivers **38% skill improvement, 40% faster time to readiness, and 32% win-rate lift** within six months. The leverage move: drive the next micro-course from the gap a closed-lost cluster just exposed. ## Process ### Step 1: Define the loss cohort Default: closed-lost partner-attached deals over the trailing 90 days. Confirm with the user. Optional scoping: by partner type, region, product, or specific competitor. ### Step 2: Pull the data - `Introw:search_crm_objects`: closed-lost deals in scope, with full record (vertical, deal size, products, stage at loss, lost-reason, competitor, key contacts, last activity). - `Introw:search_partner_engagement`: engagement on those deals (was the partner active or absent in the late stages?). - `Introw:search_partners`: partner profile for each lost deal (tier, certifications held). - `Introw:search_tasks`: task history (was anything stuck or skipped?). - Comment history on each deal via `Introw:search_crm_objects` notes for objection / blocker context. ### Step 3: Cluster by failure pattern Group losses into patterns rather than treating each as one-off. Common clusters: - **Pricing / packaging objection**: partner couldn't defend price or pitched wrong SKU. - **Competitor positioning**: partner lost head-to-head against a specific competitor. - **Technical-fit / capability**: buyer concluded the product didn't fit; partner couldn't address technical objection. - **Implementation / timeline**: buyer concerned about deployment risk; partner lacked services answer. - **Champion loss / power gap**: internal champion left or never emerged. - **No decision**: buyer stalled; partner couldn't drive urgency. - **Compliance / security**: buyer concern partner couldn't address (HIPAA, SOC 2, GDPR). - **Late-stage discovery gap**: discovery wasn't deep enough early on. For each cluster, capture: - **Volume** (how many deals). - **Aggregate value lost.** - **Affected partners** (which partners lost most often in this pattern; which partner types). - **Affected verticals / regions / products.** - **Sample evidence**: 2–3 representative deals with quotes from the lost-reason notes. ### Step 4: Diagnose the underlying gap per cluster What knowledge / skill / asset / motion would have changed the outcome? Examples: - Pricing objection cluster → partner needs ROI-calculator competency + pricing-defense talk-track. - Competitor cluster → partner needs current battle card + 2–3 fresh competitive case studies. - Technical-fit cluster → partner needs deeper product-architecture training for that vertical. - Implementation cluster → partner needs deployment-services-positioning training. - Champion-loss cluster → partner needs MEDDIC-style champion-development coaching. - Compliance cluster → partner needs vertical-specific compliance positioning. ### Step 5: Generate the micro-course outline per gap For each high-priority cluster, draft a micro-course that meets Introw's training model: - **Length**: 15–30 min, deployable in under 1 hour. - **Pulls from**: vendor's existing knowledge base (Notion, Confluence, product docs, asset library): don't fabricate content. - **Structure**: - 2-min framing: the pattern that's costing us deals. - 5-min content: the gap and how to close it. - 5-min worked example: walk through a real (or anonymized) lost deal and the alternate path. - **Open-question assessment** (not multiple choice): partner answers a real scenario in their own words; rubric grades response. - Inline AI tutoring hook, partner can ask follow-ups during the course. - **Asset bundle**: battle card / ROI calculator / case study / objection-handling cheat sheet attached. ### Step 6: Target the right partners Per cluster, identify which partners benefit most: - Partners with high concentration of losses in this pattern. - Partners working pipeline that fits this profile (use `search_crm_objects` to find current active deals in the same vertical/competitive context). - Partner-type-aware tailoring (the SI version vs. the reseller version). - Tier-aware delivery (top tier may get a live walkthrough; long tail gets the async micro-course). ### Step 7: Distribute and track - Push the course assignment via `Introw:add_task` per partner, with due-date. - `Introw:add_comment` on each partner record explaining why this course was sent (refers to the loss cluster). - Establish measurement: re-pull win-rate on similar deals 60 / 90 days post-deployment to validate impact (target: 32%+ win-rate lift on the addressed pattern, per Whatfix benchmarks). ## Output format - **Loss cohort summary**: total deals, aggregate value, period. - **Cluster table**: pattern, volume, value, affected partners/verticals, diagnosed gap. - **Micro-course outlines** per priority cluster, title, learning objective, content sections, assessment scenario, asset bundle. - **Distribution plan**: partner targets, channel, due-dates. - **Measurement plan**: what to track, when, with what comparison. ## Guardrails & PRM best practice - **Evidence-grounded.** Every micro-course traces to a specific cluster with sample lost-deal evidence. Generic "let's train on objection handling" without evidence misallocates effort. - **Don't over-fragment.** If there's a dominant cluster (>40% of losses), focus there before fragmenting into 6 minor courses. Triage matters. - **Open-question assessments only.** Multiple-choice quizzes get gamed (industry consensus); rubric-graded open-question assessments measure actual understanding. - **Knowledge-base sourced.** Course content draws from existing vendor docs over MCP, not fabricated. Cite the source for every section. - **Don't blame partners for ambiguous losses.** Some losses (no-decision, competitor pre-empted, customer reorg) aren't training gaps. Filter cleanly before clustering. - **Tier and persona awareness.** A reseller and an SI losing the same way may need different versions of the course, generate variants. - **Compliance-cluster sensitivity.** Compliance losses (HIPAA, SOC 2, GDPR) may need legal-team review of the course content before distribution, flag it. - **Don't auto-distribute without human sign-off on first cycle.** Surface the courses + targets; get user approval before pushing tasks. - **Measure impact.** Pair every course deployment with a post-period win-rate measurement on the addressed pattern. If the pattern's win-rate doesn't improve, the diagnosis or course was wrong, surface that loop. - **Cross-skill handoff.** Pattern reveals a coaching gap on live deals → `vendor-deal-coach-from-similar-wins`. Pattern reveals a partner-fit issue → `vendor-training-gap-analysis` for tier-coverage view. ``` Drop this file into `.claude/skills/vendor-microcourse-from-closed-lost/SKILL.md` in your repo and Claude Code triggers it on the prompts in its `description`. Or run the same play in plain language from Claude, ChatGPT, Slack, Teams, or your CRM through [Introw's MCP server](/features/developer/mcp): every action writes back to your CRM source of truth.