Anticipate customer needs, elevate digital experiences and drive product engagement by leveraging granular, personalized insights.
Design hyper-targeted campaigns that reflect prospects’ multi-platform consumption.
Determine thousands of drivers of churn to recommend highly accurate, CLV-driven retention actions.
Pinpoint marketing efforts with a centralized view of budget-spend, with ongoing omnichannel analysis across all channels and devices.
Use granular customer insights to accurately predict the most effective product or service.
Accurately identify customers at the highest risk of lapse for effective, personalized retention campaigns.
When machine-learning systems produce ideas, not just test them.
Here’s how a global retailer equipped their analytics team with AI to find answers hidden in large, complex and disconnected data sets, massively reducing time to value.
AI analytics helps major banks stay connected to their customers – especially during the dramatic rise of online financial management use. As leading banks apply a range of strategies to navigate the new normal, AI analytics is opening greenfield opportunities to raise profits, combined with agility and ethical responsibility.
Nearly all existing models have been invalidated by the coronavirus pandemic. They will presumably be invalidated again as the situation evolves as the world recovers. Even after recovery, it is unlikely that we will return to where we started before the crisis began. So how does that affect our data models?