Castled – Marketing automation using customer data from Snowflake
Hi HN! We are excited to share something we have been building for the last 12 months. Castled is a warehouse-native marketing platform built directly on cloud data warehouses like Snowflake, BigQuery, Redshift, and Postgres. Castled allows you to directly use the customer data in your data warehouse and engage them across different channels like Email, Sms, WhatsApp, push, and In-app - without having to copy the data to another tool. We started our journey by building an open-source Reverse ETL solution to make the warehouse data actionable to marketers. However, after talking to 100s of…
What it does
In the maker’s words, at launch
Hi HN! We are excited to share something we have been building for the last 12 months. Castled is a warehouse-native marketing platform built directly on cloud data warehouses like Snowflake, BigQuery, Redshift, and Postgres. Castled allows you to directly use the customer data in your data warehouse and engage them across different channels like Email, Sms, WhatsApp, push, and In-app - without having to copy the data to another tool. We started our journey by building an open-source Reverse ETL solution to make the warehouse data actionable to marketers. However, after talking to 100s of marketers, we realised that modern B2C marketers needed to use billions of customer data points from the data warehouse to run personalised marketing campaigns. While Reverse ETL could sync all this data to marketing tools like Braze, Iterable, etc., the traditional tools were fundamentally not designed to store and process so much data. The restrictions surfaced in the form of illogical data volume-based pricing and restrictive data retention - usually just a few months. Moreover, copying the data to multiple external tools created more complications w.r.t security audits(e.g., SOC2, GDPR, etc.) and other data privacy protocols. The data engineers also faced numerous issues maintaining the Reverse ETL pipelines, which often failed due to API timeouts, rate limits, etc. That's when we changed course to build a warehouse-native marketing solution. Since we do not store any customer data with us, marketers could finally use all the data from the data warehouse to engage their customers without any tradeoffs. I have been an avid follower of HN for years now. So we look forward to hearing any thoughts, insights, questions, and concerns about our product in the comments below. Also, feel free to reach out to me personally at [email protected].
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