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Channel performance audit

Skill duandigi/duandigi-growth-marketing-skill/skills/channel-performance-audit

Evidence-first AI Agent Skills for growth marketing — multi-channel analytics (SEO, paid media, social, local search, CRM), secure account integration, AI evaluation, experimentation & approval-safe optimization for Claude Code.

Install
npx -y skills add duandigi/duandigi-growth-marketing-skill --skill channel-performance-audit

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What its author says it does

Copied from the file, not written here

Use this skill when auditing one marketing channel from account summary down to campaigns, content, audiences, queries, landing pages, conversions, qualified outcomes, revenue, and operational constraints.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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Channel Performance Audit

Purpose

Apply a consistent channel-audit frame while preserving the provider-specific metrics, mechanisms, and limitations of the selected channel.

Inputs

  • Channel objective, owner, budget, and target audience
  • Provider, analytics, CRM, revenue, and landing-page data
  • Campaign, content, asset, query, audience, device, location, and time dimensions
  • Historical changes, experiments, and channel constraints

If a required input is unavailable, label it unknown, state how it limits the decision, and create a collection, mapping, validation, or instrumentation task. Never invent credentials, assets, metrics, permissions, or business outcomes.

Workflow

  1. Define the channel job: demand creation, demand capture, activation, retention, referral, or revenue support.
  2. Validate data health, attribution boundaries, and the last complete period.
  3. Review channel totals, trend, mix, efficiency, quality, and downstream business outcomes.
  4. Drill down to the smallest actionable object supported by the data.
  5. Identify winners, losers, concentration risk, saturation, decay, tracking gaps, and landing-page mismatch.
  6. Compare channel performance against its own objective and constraints, not a universal benchmark.
  7. Return prioritized actions and experiments with expected mechanism and approval level.

Required output

Return a concise, decision-oriented result containing:

  • Channel role and health summary
  • Top-level and drill-down findings
  • Efficiency, quality, and downstream outcome analysis
  • Data and attribution limitations
  • Prioritized actions, experiments, and stop rules

Label material statements as confirmed, calculated, inferred, assumed, or unknown. Include the data period, last complete period, source lineage, and confidence whenever they can change the decision.

Guardrails

  • Do not judge every channel by last-click revenue alone.

  • Do not use generic industry benchmarks as proof that performance is good or bad.

  • Do not optimize top-of-funnel metrics while ignoring lead quality, retention, or margin.

  • Do not recommend write actions without an approval plan.

  • Do not claim guaranteed growth or present an estimate as observed fact.

  • Do not reveal secrets, personal data, private provider payloads, or cross-project information.

  • When an action can spend money, publish, contact people, alter access, modify production, or delete data, prepare an approval request instead of executing automatically.

Completion check

Before finishing, verify that the output:

  • answers a specific business or implementation decision;
  • uses the correct organization, project, asset, date range, time zone, and currency;
  • separates performance problems from data, connection, and attribution problems;
  • includes evidence, uncertainty, affected scope, and a measurable next step;
  • respects least privilege, approval, audit, and rollback requirements;
  • is no longer than necessary for the decision.

Keep looking

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