Skill UI

Automate customer engagement workflows including broadcast triggers, message analytics, segment management, and newsletter tracking through Customer.io via Composio

A comprehensive toolkit for advanced debugging and systematic incident response within Customer.io. It provides structured playbooks, API debug clients, and investigation scripts to diagnose complex delivery issues, analyze user profiles, or troubleshoot campaign failures, ensuring robust incident management.

This skill provides a comprehensive setup for Customer.io CI/CD pipelines. It includes GitHub Actions workflows for running unit and integration tests, managing test fixtures, and implementing pre-commit hooks. It ensures robust, automated validation of Customer.io code changes, providing a reliable quality gate during the development and deployment lifecycle.

A comprehensive guide for diagnosing and fixing common integration errors with Customer.io. It covers critical topics such as API status codes (400, 401, 429), authentication failures, incorrect timestamp formatting, and best practices for event tracking and transactional message delivery. Use this resource when troubleshooting campaign failures or API calls failing.

This skill implements core Customer.io platform features, enabling sophisticated customer communication workflows. Key functionalities include sending transactional messages (e.g., receipts, password resets) and push notifications, executing API-triggered broadcasts to defined segments, and managing user attributes to dynamically drive segment membership. Ideal for building advanced, data-driven marketing automation and customer lifecycle management systems.

A comprehensive guide and set of scripts for optimizing Customer.io spending. It details strategies for auditing profile counts, suppressing/deleting inactive users, deduplicating high-volume events, and implementing event sampling to reduce billing costs and maintain data hygiene.

A comprehensive debugging bundle designed to collect all necessary evidence for Customer.io support tickets. It performs API connectivity diagnostics (Track/App), validates user profiles, captures environment details (Node.js, SDK versions), and generates a structured report. Ideal for investigating delivery failures or complex integration issues.

This skill provides a comprehensive pipeline for deploying Customer.io integrations to major production cloud platforms, including Google Cloud Run, Vercel, AWS Lambda, and Kubernetes. It details best practices for secure deployment using dedicated secrets managers, integrating robust health check endpoints, and implementing blue-green strategies, ensuring reliable and scalable CI/CD workflows.

This comprehensive guide demonstrates the essential workflow for integrating with Customer.io using its SDK. It covers the core functions required for user lifecycle management: identifying and updating user profiles, tracking custom events (both authenticated and anonymous), and sending transactional emails. Ideal for developers performing quick customer journey mapping or initial platform setup.

This comprehensive guide details how to install and configure the Customer.io SDK for programmatic integration in Node.js projects. It covers the critical setup of authentication using two distinct API keys: the Track API Key (for user identification and event tracking) and the App API Key (for sending transactional messages and broadcasts). Essential for developers integrating Customer.io's core customer data and marketing features.

This comprehensive guide identifies and explains the most common anti-patterns and mistakes when integrating with Customer.io. It covers crucial development topics, including proper API key usage, Unix timestamp formatting, ensuring correct event tracking order (Identify before Track), and optimizing API calls for performance. Use this as a definitive checklist for code review and developer onboarding.

This guide provides comprehensive strategies for scaling Customer.io integrations to handle high volumes of daily events. It covers implementing k6 load tests for performance benchmarking and outlines architectural patterns—from simple Direct APIs to complex Redis/Kafka queue-backed systems—ensuring reliability and managing API rate limits for massive data throughput.