n8n-workflow

Six production-ready demos that show agents:

1. Analyzing funnel drop-offs and generating A/B test hypotheses
2. Creating paid media audiences (enhanced conversions, retargeting)
3. Detecting anomalies and sending Slack alerts with N8N automation
4. Identifying "aha moments" in trial-to-paid conversion data
5. Auditing tracking implementation and UTM parameter consistency
6. Analyzing landing pages using vision capabilities for CRO recommendations

Each demo includes:

• ✅ Complete prompt sequences
• ✅ Synthetic datasets with engineered patterns
• ✅ Example outputs showing expected results
• ✅ SQL queries and Python scripts (auto-generated by Claude Code)
• ✅ Setup instructions for integrations (Slack, ClickUp, BigQuery, etc.)

---

1. Read the Playbook (Recommended)

Start with [PLAYBOOK.md](./PLAYBOOK.md) to understand:

• Why agents matter for marketers (strategic context)
• The Insight → Hypothesis → Action framework (mental model)
• Real use cases with strategic narratives (what becomes possible)
• Getting started guide (practical steps)
• The vision (where this is going)

Then come back here for technical implementation.

2. Choose Your Demo

Browse the [demos/](./demos) folder or read [DEMOS.md](./DEMOS.md) for detailed descriptions:

• New to agents? Start with Demo 2 (Paid Media Activation) - clear inputs, tangible outputs
• Want to see vision? Try Demo 6 (Live Website Audit)
• Love automation? Check out Demo 3 (Anomaly Detection + Slack + N8N)

3. Set Up Your Environment

Follow [SETUP.md](./SETUP.md) to:

• Install dependencies
• Configure environment variables (Slack webhooks, API tokens, etc.)
• Load synthetic data into BigQuery or DuckDB

4. Run a Demo

Each demo folder contains:

```

demos/01-funnel-hypothesis-brief/

├── README.md # Overview and instructions

├── PROMPT_SEQUENCE.md # Exact prompts to copy/paste

├── queries/ # SQL queries

├── scripts/ # Python scripts (auto-generated)

└── example_outputs/ # What to expect

```

To run:

1. Open your AI agent tool (Claude Code, Codex CLI, etc.)
2. Follow the PROMPT_SEQUENCE.md step-by-step
3. Compare your results to example_outputs/

---

All demos use realistic synthetic data with engineered patterns:

• Funnel data with 40% drop-off at pricing page
• Daily metrics with 3 anomalies (bug, improvement, activation issue)
• Trial users with clear "aha moment" (configure_integration in first 3 days = 3.7x conversion)
• Tracking data with intentional gaps (missing events)
• UTM data with consistency issues (case variations, typos)

See [DATA.md](./DATA.md) for complete schemas and sample queries.

---

| Platform | Required For | Setup Difficulty |

|----------|--------------|------------------|

| BigQuery or DuckDB | Demos 1-5 | ⚡ Easy |

| Slack Webhook | Demo 3 | ⚡ Easy |

| ClickUp API | Demo 1 | ⭐ Medium |

| N8N Instance | Demo 3 (optional) | ⭐⭐ Medium |

| Playwright | Demo 6 | ⭐ Medium |

No integrations are required to explore the prompts and outputs—the data is all local CSV/JSON files.

---

These demos follow a three-step framework:

1. Insight: