8 repositorios
Systems for measuring and optimizing user progression through defined conversion paths.
Distinguishing note: Focuses on performance analysis and drop-off identification within funnels, distinct from diagnostic tools.
Explore 8 awesome GitHub repositories matching data & databases · Conversion Funnel Analytics. Refine with filters or upvote what's useful.
This project is an open-source, privacy-focused web analytics platform designed for high-throughput data ingestion and multi-tenant data management. It provides a cookie-less tracking engine that captures visitor interactions using ephemeral request metadata, ensuring comprehensive traffic visibility while maintaining strict privacy standards. The architecture utilizes an event-driven ingestion pipeline and aggregated metric storage to decouple data collection from processing, enabling efficient long-term retrieval and responsive dashboard performance. What distinguishes this platform is its
Tracks visitor progress through defined sequences of events to identify drop-off points and calculate conversion rates.
This project is a comprehensive link management and marketing attribution platform designed for creating, tracking, and analyzing shortened URLs. It functions as a centralized hub for marketing analytics, providing tools to monitor link performance, visualize conversion funnels, and manage affiliate programs through a unified dashboard. The platform distinguishes itself by integrating advanced attribution modeling and partner management directly into the link infrastructure. It supports complex marketing workflows, including automated commission calculations, fraud detection, and payout distr
Visualizes user progression through conversion paths using funnels and time-series charts to identify drop-off points.
Rybbit is an open-source, self-hosted web analytics platform designed for comprehensive user behavior tracking and product engagement analysis. It provides a complete suite for monitoring visitor interactions, conversion funnels, and site performance, allowing organizations to maintain full ownership of their data and infrastructure. The platform distinguishes itself through a strong emphasis on privacy-compliant data collection and visual session replay capabilities. It supports advanced traffic routing through custom domains to bypass ad blockers and includes configurable masking tools to p
Measures user progress through multi-stage journeys to identify drop-off points and improve conversion rates.
This project is a comprehensive software entrepreneurship curriculum and solopreneurship business playbook designed for developers. It provides a strategic framework for building, validating, and monetizing side businesses using lean startup methodology and a systematic product development approach. The project distinguishes itself by offering specific guides for digital monetization and career anti-fragility, helping software engineers transition from employment to self-employment. It focuses on turning technical skills into scalable digital assets, paid communities, and independent software
Tracks user progression from acquisition to payment to identify and optimize revenue drop-off points.
GrowthBook is a feature flagging and experimentation platform that utilizes a warehouse-native approach to data analysis. It serves as a system for managing feature rollouts and conducting A/B tests by executing SQL queries directly against existing data warehouses to calculate experiment results. The platform is distinguished by its integration of a Model Context Protocol server, which allows AI coding assistants and IDEs to manage flags and query analytics using natural language. It also provides specialized capabilities for AI model optimization, enabling the testing of prompts and models
Evaluates single changes across multiple stages of the user journey from conversion to long-term retention.
xmall is a distributed e-commerce platform based on a service-oriented architecture. It separates business logic into independent services that communicate over a network to ensure scalability and fault tolerance, utilizing a decoupled storefront interface for customer transactions. The platform employs a distributed architecture using Dubbo for service orchestration and Zookeeper for cluster coordination and service discovery. It integrates a specialized set of components including an asynchronous message broker for background tasks, an indexed search system for product catalogs, and a centr
Identifies drop-off points within guided user processes to measure and optimize the storefront conversion rate.
Marqo es una plataforma de descubrimiento de productos de comercio electrónico, base de datos vectorial multimodal y herramienta de merchandising de búsqueda por IA. Proporciona infraestructura para implementar búsqueda semántica y recomendaciones, permitiendo a los compradores encontrar productos utilizando lenguaje natural e imágenes. La plataforma se distingue por un pipeline de clasificación híbrido que combina puntuaciones semánticas neuronales con reglas de impulso y fijación definidas por el negocio. Cuenta con un motor de comercio conversacional que utiliza modelos de lenguaje grandes para procesar la intención del usuario y proporciona una suite de análisis de rendimiento de búsqueda para medir el aumento de conversión y los ingresos mediante pruebas A/B. Sus capacidades más amplias incluyen indexación multimodal para la recuperación unificada de texto e imagen, aprendizaje conductual automatizado para optimizar clasificaciones basadas en datos de clickstream y motores de recomendación personalizados. El sistema también cubre la sincronización de catálogos, la agregación de facetas basada en atributos y la generación de resúmenes de compras conversacionales.
Measures the user progression from initial search queries through to completed purchases.
Ahoy es un framework de análisis de primera parte para aplicaciones Ruby on Rails. Proporciona herramientas para capturar comportamientos de usuario y vistas de página, permitiendo a los desarrolladores mantener la propiedad total de sus datos de análisis. El sistema se distingue por el análisis de datos relacionales, que vincula los identificadores de visita directamente a los modelos de aplicación para una atribución profunda de objetos de negocio. Incluye una herramienta de seguimiento que preserva la privacidad que utiliza enmascaramiento de direcciones IP y agrupación de visitantes sin cookies para anonimizar los datos del usuario. El proyecto cubre una amplia gama de capacidades de análisis, incluyendo seguimiento de eventos personalizados, resolución de ubicación geográfica mediante geocodificación IP y análisis de embudo de usuario. Gestiona los datos a través de la persistencia en bases de datos relacionales y utiliza rollups pre-agregados para mantener el rendimiento de las consultas en grandes datasets. Las características de infraestructura adicionales incluyen enrutamiento de mensajes asíncrono, filtrado de tráfico a nivel de middleware para excluir bots y una API dedicada para recopilar datos de clientes móviles o externos.
Measures conversion rates by tracking the progression of visitors through a sequence of specific events.