ClearBrain is like a Sherpa guiding you to find the most efficient trail to climb the Everest. ClearBrain helps growth marketers create predictions and target their users based on intent.
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.
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!
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.
@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
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