AI, Robotics & Automation

Become profitable by anticipating users' behaviors and patterns of action using AI and machine learning.

Get more out of new and existing customers with user behavior prediction

By using AI, machine learning and deep learning we can form user segments based on predicted user behavior. Predictions give you insight into which segments of users are likely to stop and use your service or purchase new services.

This is critical because it is much cheaper to keep an existing customer than it is to acquire new ones. Prediction and machine learning gains you valuable insights so that you can make informed product decisions.

Customize the user experience for increased revenue and more satisfied customers.

Customize the user experience

Predictions are important so you can customize and change the user experience of your service for users in different segments. For example, you can show ads to users who are unlikely to buy something in your service as an alternative revenue strategy. You can combine predictions with other conversion goals including audiences, user properties, device languages, OS type, software versions, and countries.

Export BigData to Omnii and BigQuery

Deeper analysis and understanding of the valuable data you possess are results of linking your predictions to BigQuery. With Omnii, you can break the barriers that block the interaction between the different channels and create a holistic communication and user experience for your customers. Our goal is to achieve a seamless and meaningful customer journey regardless of the channel the customer chooses to use.

Run multiple sophisticated campaigns based on predictions

Predictions create user groups that can be used to target content and messages in applications and services. You can engage users before they are on the move and associate with your users who are likely to make purchases in your service.

Insight into prediction inputs and performance

You have insight into factors that the ML model considers (such as incident, device, user data, etc.) to create each predictive segment. You can also see result measurements that help you understand how accurate each prediction is. With this knowledge, you can calibrate risk tolerance.