/digital-marketing-pro:performance-check

/digital-marketing-pro:performance-check

Script location. If your host does not set ${CLAUDE_PLUGIN_ROOT}, the scripts are in this plugin's scripts/ folder, next to skills/. Run them with Python 3.10 or newer: python, or python3 where python is not found (macOS, many Linux systems).

Purpose

Pull live metrics from all connected analytics MCPs and produce a comprehensive performance snapshot. Compares current performance to KPI targets defined in the brand profile, previous-period benchmarks, and industry averages. Designed for quick health checks — run it daily, weekly, or on-demand to stay on top of marketing performance without switching between platforms.

Scope (vs /digital-marketing-pro:performance-report): this skill is the live-pull + snapshot-persistence layer — it fetches current metrics from the platforms and saves a snapshot for trend history. When you need a formatted, narrative deliverable for stakeholders (executive summary, channel commentary, prioritized recommendations, branded formatting), run /digital-marketing-pro:performance-report, which consumes the snapshots this skill persists rather than re-pulling. Use performance-check to see the numbers now; use performance-report to tell the story.

Input Required

The user must provide (or will be prompted for):

• Time period: Today, this week, this month, this quarter, or a custom date range (e.g., "last 14 days", "Jan 1 - Jan 31")
• Channel focus (optional): Specific channels or platforms to prioritize (e.g., "paid search only", "email and social"). If omitted, all connected platforms are included
• Comparison period (optional): Period to compare against — previous period, same period last year, or custom range. Defaults to the equivalent previous period
• KPI targets (optional): Override targets for this check. If omitted, targets are pulled from profile.json goals and KPI settings
• Granularity (optional): Daily, weekly, or aggregate view. Defaults to aggregate for the selected period

Process

1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply brand voice, compliance rules for target markets (skills/context-engine/compliance-rules.md), and industry context. Also check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load restrictions. Check for agency SOPs at ~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults.
2. Detect connected analytics MCPs: Check .mcp.json and active MCP connections to identify which platforms are available (google-analytics, google-ads, meta-marketing, linkedin-marketing, tiktok-ads, mailchimp, stripe, mixpanel, amplitude, shopify, etc.). Log any expected platforms that are not connected so the user knows about gaps in coverage.
3. Pull metrics from each connected platform: Request key metrics for the specified time period:
   • Traffic: sessions, users, pageviews, new vs returning (break out GA4's "AI Assistant" default channel — referrals from ChatGPT, Gemini, Copilot, Perplexity, etc. — so AI-sourced traffic isn't buried under Referral/Direct)
   • Ads: impressions, clicks, spend, CPC, CPM
   • Conversions: leads, purchases, sign-ups, goal completions
   • Revenue: total revenue, average order value, transaction count
   • Engagement: open rate, click rate, bounce rate, time on site
   • Platform-specific: email deliverability, social reach, video views, app installs
4. Aggregate into unified dashboard: Normalize metrics across platforms into a single cross-channel view with consistent naming, currency conversion if multi-currency, and de-duplicated conversion counts where platforms overlap
5. Calculate KPIs vs targets: Compare actuals to targets from profile.json goals — flag green (on track or exceeding), yellow (within 10% of target), or red (missing by >10%). Include absolute and percentage variance for each KPI.