メニュー
Use when building KPI frameworks, designing dashboards, analyzing marketing performance, setting up attribution models, or creating automated reports. Covers Google Analytics 4, social media analytics, funnel analysis, cohort analysis, A/B test analysis, ROI calculation, competitive benchmarking, and stakeholder reporting.
Use when managing Laravel Forge servers, sites, deployments, SSL, databases, queue workers, scheduled jobs, security rules, and server provisioning. Covers Forge CLI, API, deployment scripts, Nginx templates, daemon management, and zero-downtime deployments.
Project-specific Ansible operations template — customize with your inventory, playbook catalog, deployment workflows, and host group details
Use when implementing or auditing accessibility features. Covers WCAG 2.1 AA/AAA compliance, ARIA roles and attributes, keyboard navigation, screen reader support, color contrast, focus management, and accessible component patterns.
Use when evaluating AI/LLM systems — benchmark design, automated evaluation pipelines, human evaluation protocols, A/B testing, hallucination detection, factuality checking, bias testing, safety evaluation (red teaming), latency/cost metrics, eval datasets, regression testing for prompts, and model comparison frameworks.
Use when designing or implementing REST APIs. Covers RESTful conventions, versioning, pagination, filtering, error handling, rate limiting, HATEOAS, OpenAPI documentation, and API security best practices.
Use when implementing authentication, authorization, or access control. Covers Laravel Sanctum, OAuth 2.0, RBAC with Spatie Permissions, multi-tenant auth, API token management, MFA, and session security.
| name | analytics-reporting |
| description | Use when building KPI frameworks, designing dashboards, analyzing marketing performance, setting up attribution models, or creating automated reports. Covers Google Analytics 4, social media analytics, funnel analysis, cohort analysis, A/B test analysis, ROI calculation, competitive benchmarking, and stakeholder reporting. |
| user-invocable | true |
| allowed-tools | ["Read","Write","Edit","Grep","Glob","Bash"] |
Business Objectives -> Strategic KPIs (quarterly) -> Tactical KPIs (monthly) -> Operational Metrics (weekly/daily) -> Raw Data (events)
| Stage | Key Metrics |
|---|---|
| Awareness | Impressions, reach, brand mentions, share of voice, new sessions |
| Consideration | Engagement rate, CTR, avg session duration, email open/click rate |
| Conversion | Conversion rate, CPA, CPL, ROAS, marketing-sourced revenue, CAC |
| Retention | CLV, churn rate, NPS, repeat purchase rate, CSAT |
Must be: measurable, actionable, leading (predicts future revenue), and understandable company-wide.
| Business Type | North Star Example |
|---|---|
| SaaS | Weekly active users |
| E-commerce | Purchases per customer per quarter |
| Marketplace | Transactions completed per week |
| Content/Media | Daily reading time per subscriber |
| B2B Services | Monthly active projects per client |
Pick 3-5 supporting input metrics that drive the North Star (e.g., sign-ups/week, onboarding completion, feature adoption in first 7 days).
| Tier | Examples | Setup |
|---|---|---|
| Auto-collected | page_view, session_start, first_visit | None |
| Enhanced measurement | scroll, outbound_click, site_search, file_download | Toggle in GA4 settings |
| Recommended events | sign_up, purchase, add_to_cart, generate_lead | Manual implementation, standard names |
| Custom events | demo_requested, pricing_viewed, feature_compared | Manual, business-specific |
utm_source: Platform (lowercase): google, facebook, linkedin, newsletter
utm_medium: Channel type: cpc, organic_social, paid_social, email, referral
utm_campaign: Campaign name (lowercase, hyphens): spring-launch-2026
utm_content: Variant for A/B testing: cta-red-button, hero-video
| Model | Rule | Best For |
|---|---|---|
| Last-click | 100% to last touchpoint | Direct response, bottom-funnel |
| First-click | 100% to first touchpoint | Understanding awareness channels |
| Linear | Equal credit to all touchpoints | Long sales cycles |
| Time-decay | More credit closer to conversion | B2B with long consideration |
| Position-based (U-shaped) | 40% first, 40% last, 20% middle | Balanced full-funnel view |
| Data-driven (GA4 default) | ML-assigned based on patterns | Any business with 300+ conversions/month |
| Stage | Metrics | Content Types | Goal |
|---|---|---|---|
| TOFU (Awareness) | Impressions, reach, new visitors | Blog, social, video, PR | Get noticed |
| MOFU (Consideration) | Engagement, email sign-ups, downloads | Whitepapers, webinars, case studies | Build trust |
| BOFU (Decision) | Demo requests, trials, pricing views | Demos, trials, ROI calculators | Convert |
| Post-funnel | NPS, retention, referrals | Onboarding, community, loyalty | Retain and expand |
Stage | Volume | Conv % | Drop-off | Benchmark
Website visitors | 50,000 | --- | --- | ---
Engaged visitors | 15,000 | 30.0% | 70.0% | 25-35%
Lead (form fill) | 1,500 | 10.0% | 90.0% | 8-12%
MQL | 450 | 30.0% | 70.0% | 25-35%
SQL | 135 | 30.0% | 70.0% | 20-30%
Opportunity | 55 | 40.7% | 59.3% | 35-45%
Customer | 22 | 40.0% | 60.0% | 25-40%
Bottleneck: [Stage with lowest % or largest absolute drop]
Action: Improve [content/UX/targeting] at bottleneck stage
Cohort types: Acquisition (sign-up month), behavioral (completed action X), channel (source), feature (adopted feature Y).
Retention cohort table: Rows = cohort month, columns = months since join, cells = % still active.
Action triggers:
Hypothesis: If we [change X], then [metric Y] will [increase/decrease]
by [expected %] because [rationale].
Primary metric: [Single winner-determining metric]
Guardrail metrics: [Must NOT degrade: page load, error rate, support tickets]
Sample size: [Calculate based on baseline rate and MDE]
Duration: [Until sample size reached -- no peeking]
| Baseline Rate | MDE 10% | MDE 20% | MDE 50% |
|---|---|---|---|
| 2% | 39K/variant | 10K | 1.6K |
| 5% | 15K | 3.8K | 625 |
| 10% | 7.2K | 1.8K | 306 |
| 20% | 3.2K | 838 | 144 |
Marketing ROI = (Revenue from Marketing - Marketing Cost) / Marketing Cost x 100
ROAS = Revenue from Ads / Ad Spend
CAC = Total Marketing & Sales Spend / New Customers
CLV = ARPU x Gross Margin x (1 / Churn Rate)
CLV:CAC = Target 3:1 or higher
Payback = CAC / (ARPU x Gross Margin) -- Target < 12 months for SaaS
| Channel | Typical ROAS |
|---|---|
| Google Search | 2x-8x |
| Google Shopping | 3x-10x |
| Meta Ads | 2x-5x |
| LinkedIn Ads | 1.5x-4x (higher CPL, higher deal value) |
| TikTok Ads | 1.5x-4x |
| Platform | Engagement Rate Formula | Quality Signal | Benchmark |
|---|---|---|---|
| (reactions + comments + shares + clicks) / impressions | Comments | 3-5% | |
| (likes + comments + saves + shares) / reach | Saves | 3-6% | |
| X/Twitter | (likes + replies + retweets + clicks) / impressions | Bookmarks | 0.5-1.5% |
| YouTube | Watch time, avg view duration | Avg % viewed | CTR 4-10% |
| TikTok | Likes + comments + shares / views | Watch-through rate | 3-9% |
| Purpose | Chart Type |
|---|---|
| Compare categories | Bar chart |
| Trend over time | Line chart |
| Parts of whole | Stacked bar (avoid pie with > 5 segments) |
| Distribution | Histogram, box plot |
| Funnel stages | Funnel chart |
| Two-variable relationship | Scatter plot |
Anti-patterns: 3D charts, dual y-axes, truncated axes without indication, rainbow palettes, averages without variance.
| Frequency | Content | Audience |
|---|---|---|
| Daily | Key metrics snapshot, anomaly alerts, spend pacing | Marketing team |
| Weekly | Full dashboard review, top/bottom content, WoW trends | Marketing team + leadership |
| Monthly | Channel attribution, funnel analysis, ROI by campaign, budget vs actual | Leadership + stakeholders |
| Quarterly | North Star progress, competitive landscape, strategy review, budget reallocation | Executive team |
| Audience | Format | Focus |
|---|---|---|
| C-Suite | 1-page summary, 5-7 KPIs | Business impact: revenue, ROI, growth |
| Marketing leadership | 5-10 page dashboard | Channel performance, strategy progress |
| Marketing team | Interactive dashboard with filters | Tactical: engagement, CTR, conversion by ad |
| Sales team | Lead/pipeline report | Lead quality, source attribution, conversion rate |
For every data point: (1) WHAT happened? (2) WHY did it happen? (3) SO WHAT should we do?
Template: "[Metric] [changed] by [X]% [period]. Driven by [cause]. Recommend [action], expected result [outcome]."