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Kat Manalac

Causal Analytics - What causes your best users to convert?

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ClearBrain helps you analyze your web & app data to determine what actions cause vs correlate to signup / purchase / activation. In partnership with Segment, you can now get access to real-time causal analytics for free, and without a single line of code.

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Bilal Mahmood
Maker
Hi everyone I’m Bilal, cofounder of ClearBrain. Our team comes from Optimizely and Google where we spent over a decade building ML and Experimentation platforms to answer the question that every growth and product team is asking: “What causes my best users to convert”. We built ClearBrain to automate what we used to do at our prior jobs. We invented a new algorithm that can automatically distinguish causation vs correlation, without running an experiment. So now anyone can in minutes: a) monitor their conversion goals, b) determine what actions cause those goals, and c) understand the path to conversion for the most causal actions. We’re also excited to be releasing this product in partnership with Segment. Segment is a single data integration API that tracks user actions, and enables you to automatically sync them to ClearBrain for analysis with the click of a button. This partnership has enabled us to release the product today on a self-serve basis, and completely for free. No lines of code. No talking to a sales rep. Excited for you to try out ClearBrain!
Matthew Sadofsky
The platform truly allows you to unlock insights in minutes you'd need to hire an entire data science team to replicate - at no or a fraction of the cost.
Yin Wu
Excited to try this out! What are the use cases where this is a good fit?
Bilal Mahmood
Maker
@yinyinwu Thank you! Some of the most powerful use cases for causal analytics that our customers have found include: - Identifying which landing pages have the most causal impact on sign ups - Analyzing the projected lift that different product features have towards activation - Segmenting your users by high value vs low value, based on those that do causal behaviors - Comparing the high value and low value users to see differences in their engagement, user attributes
Mathew Pregasen
This is super sick
Sudheendra
Maker
Hey people, PM here from Segment. Excited to be collaborating with the ClearBrain team on delivering causal analytics as a joint solution for free. A lot of our customers at Segment have expressed desire for a new type of analytics tool that can predict causation vs correlation, and was a delight to build the automated integration layer via Segment that enables the ClearBrain platform to work on a self-serve basis. Feel free to give it a try and if you are not a Segment user, get started for free - https://learn.segment.com/clearb... :)
Jason Shen
What kind of black magic lets you simulate A/B tests and predict results with just prior data? Can you explain how this works to a non data scientist?
Bilal Mahmood
Maker
@jasonshen not black magic - just some good statistics! Our algorithm basically works in two steps: 1) automatically identify the "confounding" variables that introduce correlation bias, 2) simulate control-treatment experiments on your historical data via an "observational study". We outline how the algorithm works in more detail here: https://blog.clearbrain.com/post...
Nate Leung
I’m interested! Any User references or case studies? @bilalmahmood @grant_lee1
David Huie
Very interesting! How does ClearBrain ingest the data for analysis?