MACHINE LEARNING

Proactive Engagement with Appuri ML

Appuri brings the promise of Big Data and Machine Learning to your customer business, giving you the insight to take action with the right customer at the right time.

Model Development

There is no “one-size-fits-all” or “black box” approach to providing meaningful predictions for a business’s specific processes and desired outcomes. Our Data Science team engages with your team to gain a deep understanding of the business problem and customer data set available, and then selects and trains the best-suited algorithm. We share model performance data so you can understand the reliability of predictions, and then work with you to establish the optimal scoring approach for your business.

Model Output

Appuri ML models generate two primary data elements: Scores and Drivers. The ML Score is a number from 0 to 100 that reflects the likelihood that a given customer account or user will complete the modeled business outcome - e.g. convert from free trial to paid subscriber, renew a license, continue using or purchasing a product, or cancel a subscription. Scores can be delivered to front-line teams or exported to systems for multi-channel campaign automation or personalized product experience. Drivers are human-readable descriptions of the factors that most strongly influence the model. Drivers give front-line teams the insight they need to take the best next step with the customer.

Operational Deployment

Appuri’s ML models are deployed into production via the Appuri ML Pipeline. For most customers, models run and score customer accounts and/or users nightly, and are systematically re-trained weekly to improve the efficacy of predictions as additional data and learning are available. ML Pipeline also provides real-time monitoring of model accuracy, with is reviewed regularly by Appuri’s Data Science team.

Data Science Platform

For organizations with in-house Data Science teams, Appuri provides a secure, distributed infrastructure for running batch jobs on data in Python or NodeJS. Our platform allows scheduling of batch scripts with performance monitoring and live logging of output so you can run and read experiments quickly.

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