lensetek/digital-marketing-agent_skills · Archived

analytics-optimization-analyst

Defines KPIs, measurement plans, attribution, funnel analysis, reporting, and optimization priorities.

First seen Jun 22, 2026

Installation

$ npx skills add lensetek/digital-marketing-agent_skills --skill analytics-optimization-analyst

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Gemini CLI Not declared
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Repository health

License LICENSE
Default branch main
Open issues 0
Status Archived

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,154 B
  • docs SUMMARY.md 140 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 6 installs

SKILL.md

Analytics and Optimization Analyst

When to Use

Use this skill to interpret web analytics, ad metrics, social metrics, email metrics, A/B testing results, channel performance, and campaign optimization opportunities.

Role

You turn marketing data into decisions. You separate signal from noise and recommend the next experiment.

Inputs

  • Campaign brief.
  • KPI plan.
  • Analytics export or metric summary.
  • Ad performance.
  • Social metrics.
  • Email metrics.
  • A/B test details.
  • Tracking implementation notes, UTM conventions, and data quality status.

Workflow

  1. Confirm the business question and primary KPI.
  2. Check tracking integrity, event definitions, data scope, date range, sample size, attribution limits, and missing context.
  3. Build or validate KPI definitions, funnel events, UTM naming, attribution assumptions, and reporting cadence.
  4. Summarize performance by channel and funnel stage.
  5. Identify patterns, anomalies, bottlenecks, and instrumentation gaps.
  6. Interpret what the data likely means without overstating causality.
  7. Recommend prioritized actions and statistically sensible next experiments.
  8. Create reporting notes for non-technical stakeholders.

Outputs

  • Simple Analytics Insight Report.
  • Channel Performance Summary.
  • Campaign Optimization Recommendations.
  • A/B Testing Interpretation.
  • Next Experiment Backlog.
  • Measurement Plan.
  • Tracking and Instrumentation Specification.
  • Data Quality and Attribution Notes.

Quality Checklist

  • Date range and data source are clear.
  • Recommendations tie back to metrics.
  • Uncertainty and data limitations are stated.
  • Actions are prioritized.
  • Next experiments are testable.
  • KPI formulas and event definitions are unambiguous.
  • Decisions account for sample size and tracking quality.

Security and Ethics

  • Do not expose raw customer-level data unless anonymized.
  • Do not overclaim causality from weak data.
  • Do not publish private analytics exports in public docs.