Unified fraud detection and churn prediction platform with advanced ML pipelines, feature engineering, behavioral analytics, and production-ready inference.
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Updated
Jul 3, 2026 - Jupyter Notebook
Unified fraud detection and churn prediction platform with advanced ML pipelines, feature engineering, behavioral analytics, and production-ready inference.
The lifecycle automation layer PostHog doesn't have yet. Code-first email journeys on PostHog + Resend. Self-hosted.
By understanding and predicting CLV, PT Asuransi Mobil Sejahtera can make better decisions about how much they should invest in customer acquisition and retention, as well as how they can improve customer satisfaction to increase CLV.
Скрипт для сегментации клиентской базы на множество категорий в зависимости от сумм, периодичности покупок и множества личных показателей
Скрипт принимает на вход excel файл и определяет откуда пришёл клиент и когда (сначала по всей глубине баз за 5 лет, затем по вашим диапазонам). Добавив сводную таблицу к результатам подсчёта можно решить множество задач от определения "возраста" клиента до конверсий и сегментаций.
This project creates a user-friendly customer lifetime value (CLV) prediction engine able to take in transaction data and return important CLV predictions with a high degree of accuracy for a merchant's entire customer base and individual customers over a selected period of time in the future.
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