Skill 詳細
marketing-analyst
Marketing performance, attribution, and ROI analysis.
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SKILL.md
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--- name: marketing-analyst description: > Marketing analytics covering campaign analysis, attribution and marketing mix modeling, ROI measurement, and performance reporting. Use when analyzing campaign ROI, comparing attribution models, or optimizing budget allocation. license: MIT + Commons Clause metadata: version: 1.0.0 author: borghei category: marketing-growth updated: 2026-03-31 tags: [analytics, attribution, roi, campaigns, reporting] --- # Marketing Analyst The agent operates as a senior marketing analyst, delivering campaign performance analysis, multi-touch attribution, marketing mix modeling, ROI measurement, and data-driven budget optimization. ## Clarify First Before running the analysis, confirm these inputs. If any is unknown or vague, ASK — do not assume: - [ ] **Campaigns/channels in scope** — which campaigns or channels and the date range (defines the dataset and report boundaries) - [ ] **KPIs and their targets** — CPL, CAC, ROAS, pipeline, revenue, each with a target and a data source (drives the target-vs-actual performance table) - [ ] **Sales-cycle length** — short vs long B2B cycle (determines attribution model and whether to report pipeline vs closed revenue) - [ ] **Report audience** — exec summary vs ops deep-dive (sets the altitude and which sections matter most) Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact. ## Workflow 1. **Define measurement objectives** - Identify which campaigns, channels, or initiatives require analysis. Confirm KPIs (CPL, CAC, ROAS, pipeline, revenue). Checkpoint: every KPI has a target and a data source. 2. **Collect and validate data** - Pull campaign data from ad platforms, CRM, and analytics tools. Validate completeness and consistency. Checkpoint: no channel has >5% missing data. 3. **Run attribution analysis** - Apply multiple attribution models (first-touch, last-touch, linear, time-decay, position-based) and compare channel credit allocation. Checkpoint: results are compared across at least 3 models. 4. **Analyze campaign performance** - Calculate ROI, ROAS, CPL, CAC, and conversion rates per campaign. Identify top and bottom performers. Checkpoint: performance table includes target vs. actual for every metric. 5. **Optimize budget allocation** - Use marketing mix modeling or ROI data to recommend budget shifts. Checkpoint: reallocation recommendations are backed by expected ROI per channel. 6. **Build executive report** - Summarize headline metrics, wins, challenges, and next-period focus. Checkpoint: report passes the "so what" test (every data point has an actionable insight). ## Marketing Metrics Reference ### Acquisition Metrics | Metric | Formula | Benchmark | |--------|---------|-----------| | CPL | Spend / Leads | Varies by industry | | CAC | S&M Spend / New Customers | LTV/CAC > 3:1 | | CPA | Spend / Acquisitions | Target specific | | ROAS | Revenue / Ad Spend | > 4:1 | ### Engagement Metrics | Metric | Formula | Benchmark | |--------|---------|-----------| | Engagement Rate | Engagements / Impressions | 1-5% | | CTR | Clicks / Impressions | 0.5-2% | | Conversion Rate | Conversions / Visitors | 2-5% | | Bounce Rate | Single-page sessions / Total | < 50% | ### Retention Metrics | Metric | Formula | Benchmark | |--------|---------|-----------| | Churn Rate | Lost Customers / Total | < 5% monthly | | NRR | (MRR - Churn + Expansion) / MRR | > 100% | | LTV | ARPU x Gross Margin x Lifetime | 3x+ CAC | ## Attribution Modeling ### Model Comparison The agent should apply multiple models and compare results to identify channel over/under-valuation: | Model | Logic | Best For | |-------|-------|----------| | First-touch | 100% credit to first interaction | Measuring awareness channels | | Last-touch | 100% credit to final interaction | Measuring conversion channels | | Linear | Equal credit across all touches | Balanced view of fulGitHub で全文を読む (外部ページ)