Identify High Propensity Segments. Improve Lift and Retention.
Integrate in minutes. No code required.
ClearBrain automatically connects to your analytics, email, or payment data via Redshift or API. No waiting weeks to collect data, or instrument your product. Absolutely no code or engineering required.
Choose any segment. Predict any behavior.
Once integrated, we map your data into an easy-to-use interface for predictive segmentation. You can define segments of users by any property or behavior, and choose any behavior you’ve tracked as a goal you’d like to predict.
A score for every user. For every action.
ClearBrain learns from your users’ past actions who is most likely to perform your predicted behavior, in a given week or month. Each user is assigned a ClearBrain score, indicating their likelihood to perform the action, and their respective probabilities based on each attribute.
User targeting at the right time, right place.
With automated predictions, you can segment your users by high vs. medium vs. low propensity. This allows you to target only those users most likely to perform an action in the right period of time. You can now target users at the right time and right place, for any ad, email, or personalization campaign.
ClearBrain is an early-stage startup, building a self-service AI to predict any user behavior.
Started in 2016 by the first SRE on Google Ads and the Data Science PM at Optimizely, we've built a self-service machine learning layer that operates on terabytes of data to automatically predict propensity to convert or churn.
We're growing fast, serving mid-market to public customers, and well funded by early investors in Dropbox, Optimizely, and AppDynamics.
We dabble in Spark, Scala, Go, and Node every day. And we face exciting challenges in the months ahead - from scaling our infra to handle 10X the data volume, to data normalization and identity resolution, and leveraging network effects for more accurate predictive insights - all towards the goal of making machine learning as self-service and scalable as possible.