{"id":"0b781d5f-a423-45cf-be10-8fb7d589ca11","shortId":"uepxVA","kind":"skill","title":"marketplace-liquidity","tagline":"Diagnose and improve marketplace liquidity: metric tree, fragmentation map, bottleneck diagnosis.","description":"# Marketplace Liquidity Management\n\n## Scope\n\n**Covers**\n- Defining **liquidity as reliability**: how often a user can complete the marketplace’s core action (find → match → transact) within an acceptable time and quality threshold\n- Measuring liquidity **where it actually happens** (by “local markets” like geo × category × time window), not just in global averages\n- Diagnosing liquidity failure modes: **fragmentation**, supply–demand imbalance (“flip-flop”), matching/mechanics issues, and quality/trust breakdowns\n- Designing a practical **liquidity operating system**: scorecards, weekly review cadence, and a “whac-a-mole” rebalancing plan (move attention/inventory/incentives)\n- Producing an actionable **experiment backlog** to improve liquidity (supply, demand, matching, pricing/incentives, trust & safety)\n\n**When to use**\n- “We need to improve marketplace liquidity / match rate / fill rate”\n- “Time-to-match is too slow” / “buyers can’t find availability”\n- “Supply and demand are imbalanced across cities/categories”\n- “Our marketplace feels unreliable” / “conversion drops due to no availability”\n- “We need a liquidity dashboard + operating cadence + experiments”\n\n**When NOT to use**\n- You don’t operate a two-sided marketplace (no matching between supply and demand).\n- The primary problem is **value proposition / ICP** (use `problem-definition` or `measuring-product-market-fit`).\n- You only need **pricing changes** (use `pricing-strategy`) without a liquidity diagnosis.\n- You need a general growth plan unrelated to matching reliability (use `designing-growth-loops` / `retention-engagement`).\n- You want to measure whether you have product-market fit (use `measuring-product-market-fit`); liquidity assumes the core value proposition is already validated.\n- You need to design or optimize a referral/viral/content growth loop (use `designing-growth-loops`); this skill focuses on match reliability, not acquisition loops.\n- You need a retention or engagement playbook for a non-marketplace product (use `retention-engagement`).\n\n## Inputs\n\n**Minimum required**\n- Marketplace type + sides (who are “buyers” and “sellers”)\n- The **core action** you consider a successful outcome (e.g., request → booked; search → purchase; message → hire)\n- Top 1–3 priority segments (geo/category/user cohort) and the time window you care about\n- Best-available baseline metrics (even if rough): demand volume, supply availability, match/fill rate, time-to-match, cancellations/quality\n- Constraints: budget, incentives you can/can’t use, policy/brand/trust, engineering capacity, timebox\n\n**Missing-info strategy**\n- Ask up to 5 questions from [references/INTAKE.md](references/INTAKE.md), then proceed.\n- If data is missing, proceed with explicit assumptions and label confidence.\n- Do not request secrets or PII; prefer aggregated metrics or redacted examples.\n\n## Outputs (deliverables)\n\nProduce a **Marketplace Liquidity Management Pack** (Markdown in-chat; or as files if requested) containing:\n\n1) **Context snapshot** (goal, timebox, segments, constraints, decision this informs)\n2) **Liquidity definition + thresholds** (reliability definition and “good enough” targets)\n3) **Liquidity metric tree** (north-star + driver metrics, with event definitions)\n4) **Fragmentation map + segment scorecard** (where liquidity is weak/strong; the “local markets” that matter)\n5) **Bottleneck diagnosis** (supply vs demand vs matching/mechanics vs quality; include “flip-flop” state)\n6) **Intervention plan + prioritized experiment backlog** (including reallocation/“whac-a-mole” plan)\n7) **Measurement + instrumentation plan** (dashboards, alerts, tracking gaps)\n8) **Operating cadence** (weekly liquidity review agenda + owners)\n9) **Risks / Open questions / Next steps** (always included)\n\nTemplates and expanded guidance:\n- [references/TEMPLATES.md](references/TEMPLATES.md)\n- [references/WORKFLOW.md](references/WORKFLOW.md)\n- [references/CHECKLISTS.md](references/CHECKLISTS.md)\n- [references/RUBRIC.md](references/RUBRIC.md)\n\n## Workflow (7 steps)\n\n### 1) Intake + define the decision and local market(s)\n- **Inputs:** User context; [references/INTAKE.md](references/INTAKE.md).\n- **Actions:** Clarify the goal (metric + target + by when), define the core action, pick the “local market” unit (e.g., city × category × week), and decide the decision this work will inform (what you’ll do differently).\n- **Outputs:** Context snapshot + local market definition.\n- **Checks:** A stakeholder can answer: “Which segment(s) improve by how much, by when, and what will we change based on the result?”\n\n### 2) Define liquidity as reliability + set thresholds\n- **Inputs:** Core action, time sensitivity, quality constraints (cancellations, refunds, etc.).\n- **Actions:** Define liquidity as the probability of success within thresholds (time-to-match, quality). Choose 1 north-star liquidity metric and 3–6 drivers (fill rate/match rate, time-to-match, availability, acceptance, cancellation).\n- **Outputs:** Liquidity definition + “good enough” targets + metric tree outline.\n- **Checks:** The definition is measurable, segmentable, and aligned to the user’s experience (“reliability”).\n\n### 3) Build a segment scorecard + diagnose fragmentation\n- **Inputs:** Baseline data by geo/category/time window (best available).\n- **Actions:** Create a segment scorecard for each local market: demand, supply, matching, and quality metrics. Identify fragmentation (thin markets, long tail categories, uneven geo distribution) and “uniform needs” vs heterogeneous needs.\n- **Outputs:** Fragmentation map + ranked list of worst segments (where liquidity blocks growth).\n- **Checks:** The scorecard avoids global averages and includes enough volume to be meaningful (or flags low-confidence segments).\n\n### 4) Diagnose bottlenecks (flip-flop + mechanics + quality)\n- **Inputs:** Segment scorecard; any qualitative evidence (support tickets, user feedback, ops notes).\n- **Actions:** For each priority segment, label the primary failure mode:\n  - **Supply-limited** (not enough availability/inventory)\n  - **Demand-limited** (not enough intent/requests)\n  - **Matching/mechanics-limited** (ranking, discovery, response time, pricing friction)\n  - **Quality/trust-limited** (cancellations, no-shows, fraud, low ratings)\n  Also check for the “flip-flop” dynamic (which side is currently the constraint) and the **graduation problem** (top suppliers leaving).\n- **Outputs:** Bottleneck diagnosis per segment + evidence notes.\n- **Checks:** Each diagnosis includes at least 1 metric signal and 1 plausible causal story you can test.\n\n### 5) Generate interventions + experiment backlog (including reallocation)\n- **Inputs:** Bottleneck diagnosis; constraints; available levers.\n- **Actions:** Create intervention options for each bottleneck type (supply, demand, mechanics, quality). Include a “whac-a-mole” plan: how you will reallocate attention/inventory/incentives across segments weekly. Convert interventions into experiments with clear hypotheses and success metrics.\n- **Outputs:** Prioritized experiment backlog + reallocation playbook.\n- **Checks:** Every experiment has (a) a segment, (b) a primary metric, (c) a target effect size or directional expectation, and (d) a plausible cycle time.\n\n### 6) Design measurement + liquidity operating cadence\n- **Inputs:** Chosen metrics and experiments.\n- **Actions:** Specify dashboards/alerts, event definitions, and instrumentation gaps. Create a weekly liquidity review agenda and decision log (what gets rebalanced, what gets shut down, what gets scaled).\n- **Outputs:** Measurement plan + operating cadence (owners if known).\n- **Checks:** Each key metric is tied to a data source and update frequency; the cadence produces concrete decisions, not status updates.\n\n### 7) Quality gate + finalize the pack\n- **Inputs:** Draft pack; [references/CHECKLISTS.md](references/CHECKLISTS.md) and [references/RUBRIC.md](references/RUBRIC.md).\n- **Actions:** Run the checklist and score with the rubric. Tighten the pack until it is specific, segment-aware, and testable. Always include **Risks / Open questions / Next steps**.\n- **Outputs:** Final Marketplace Liquidity Management Pack.\n- **Checks:** The next 2 weeks of work are unblocked (data pulls, 1–3 experiments, cadence).\n\n## Anti-patterns\n\n1. **Global-average blindness** — Reporting a single marketplace-wide match rate instead of segmenting by local market (geo x category x time). A 70% global fill rate can hide a 30% rate in your fastest-growing city. Always segment before diagnosing.\n2. **Supply-side-only tunnel vision** — Assuming liquidity problems are always supply shortages. Many marketplaces have adequate supply but poor matching/discovery mechanics or quality/trust breakdowns that suppress conversion.\n3. **Incentive addiction without diagnosis** — Throwing subsidies or promotions at both sides without first identifying whether the bottleneck is supply, demand, mechanics, or quality. This burns budget and masks the real constraint.\n4. **Ignoring the flip-flop dynamic** — Treating the supply/demand balance as static. Marketplaces oscillate: today's supply shortage becomes tomorrow's demand shortage once you over-correct. The operating cadence must track which side is currently the constraint.\n5. **Fragmentation denial** — Treating heterogeneous local markets as one uniform market. A marketplace with 50 categories where 5 drive 90% of volume needs a long-tail strategy, not a blanket growth plan.\n\n## Quality gate (required)\n- Use [references/CHECKLISTS.md](references/CHECKLISTS.md) and [references/RUBRIC.md](references/RUBRIC.md).\n- Always include: **Risks**, **Open questions**, **Next steps**.\n\n## Examples\n\n**Example 1 (services marketplace, geo fragmentation):**  \n“Use `marketplace-liquidity`. We run a home cleaning marketplace across 12 cities. Goal: increase booking fill rate from 62% → 80% in 8 weeks in our bottom 4 cities. We suspect supply is thin and response times are slow. Output a Marketplace Liquidity Management Pack with a segment scorecard, bottleneck diagnosis, and a prioritized experiment backlog.”\n\n**Example 2 (B2B marketplace, category imbalance):**  \n“Use `marketplace-liquidity`. We match startups with freelance designers. Liquidity is strong in ‘logo design’ but weak in ‘product design’ and ‘brand refresh.’ Goal: cut median time-to-first-qualified-match from 5 days to 2 days for product design in 60 days. Provide a liquidity metric tree, fragmentation map, and operating cadence.”\n\n**Boundary example (not a liquidity problem — acquisition copy):**\n“Write Google Ads copy to get more buyers.”\nResponse: this is primarily acquisition/copy. If marketplace reliability is already strong, use `copywriting` / channel-specific growth work. If reliability is unknown, start with an intake to confirm a liquidity bottleneck first.\n\n**Boundary example (redirect to measuring-product-market-fit):**\n“We launched a pet-sitting marketplace 3 months ago. Do we even have product-market fit?”\nResponse: This is a PMF measurement question, not a liquidity diagnosis. Use `measuring-product-market-fit` to run a Sean Ellis survey and retention analysis first. Once PMF is confirmed for at least one segment, return here to optimize match reliability.","tags":["marketplace","liquidity","lenny","skills","plus","liqiongyu","agent-skills","ai-agents","automation","claude","codex","prompt-engineering"],"capabilities":["skill","source-liqiongyu","skill-marketplace-liquidity","topic-agent-skills","topic-ai-agents","topic-automation","topic-claude","topic-codex","topic-prompt-engineering","topic-refoundai","topic-skillpack"],"categories":["lenny_skills_plus"],"synonyms":[],"warnings":[],"endpointUrl":"https://skills.sh/liqiongyu/lenny_skills_plus/marketplace-liquidity","protocol":"skill","transport":"skills-sh","auth":{"type":"none","details":{"cli":"npx skills add liqiongyu/lenny_skills_plus","source_repo":"https://github.com/liqiongyu/lenny_skills_plus","install_from":"skills.sh"}},"qualityScore":"0.474","qualityRationale":"deterministic score 0.47 from registry signals: · indexed on github topic:agent-skills · 49 github stars · SKILL.md body 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