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A Python library for customer segmentation in marketing data pipelines — RFM analysis, clustering, segment profiling, and streaming updates in one import. ClusterAudienceKit is a Python library that replaces the scikit-learn + pandas + lifetimes stack for customer segmentation. If you've built this before, you've probably written hundreds of lines of boilerplate glue and still ended up with a pipeline that can't handle 100k customers in any reasonable time.
ClusterAudienceKit was born from a simple problem: audience analysis is often manual, fragmented, and difficult to scale. I wanted to make it easy for anyone to discover audience segments, understand customer behavior, and generate actionable insights from their data in minutes instead of days.
Would love to see a built-in way to export segment definitions as SQL queries so I can apply them directly in our warehouse without round-tripping back to Python every time we refresh.
About ClusterAudienceKit on Product Hunt
“Customer segmentation in Martech pipelines ”
ClusterAudienceKit was submitted on Product Hunt and earned 0 upvotes and 2 comments, placing #17 on the daily leaderboard. A Python library for customer segmentation in marketing data pipelines — RFM analysis, clustering, segment profiling, and streaming updates in one import. ClusterAudienceKit is a Python library that replaces the scikit-learn + pandas + lifetimes stack for customer segmentation. If you've built this before, you've probably written hundreds of lines of boilerplate glue and still ended up with a pipeline that can't handle 100k customers in any reasonable time.
ClusterAudienceKit was featured in Open Source (68.6k followers), Analytics (172.8k followers), GitHub (41.3k followers) and Data Science (3.9k followers) on Product Hunt. Together, these topics include over 54.9k products, making this a competitive space to launch in.
Who hunted ClusterAudienceKit?
ClusterAudienceKit was hunted by Georgi Mullassery. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Georgi Mullassery