XM for Customer Experience

The Predict iQ feature utilizes advanced machine learning and neural networks to analyze historical customer data and identify those at risk of leaving. It assigns a churn probability score to individual customers, which allows teams to prioritize retention efforts. This proactive approach helps businesses intervene at the right moment to save valuable relationships.

Text iQ applies natural language processing to unstructured data found in open-ended survey responses and social media comments. By automatically categorizing feedback into topics and assigning sentiment scores, this feature uncovers the root causes of customer dissatisfaction. It transforms qualitative noise into quantifiable insights to reveal trends that standard metrics might miss.

This feature automates the follow-up process by triggering alerts and creating support tickets in external systems based on specific feedback criteria. Whether a customer leaves a low NPS score or reports on a specific issue, the software ensures immediate action is taken. This systematic response mechanism helps repair broken experiences and builds trust.

The platform provides highly customizable, real-time data visualizations tailored to specific roles within the organization, from frontline staff to executives. These dashboards ensure that every stakeholder sees only the metrics relevant to their performance and goals. By democratizing access to insights, the platform facilitates faster, more informed decision-making across all departments.

XM for Customer Experience capabilities capture feedback directly from websites and mobile apps using targeted intercept surveys and feedback buttons. It combines operational data with experience signals to help teams understand the "why" behind digital behaviors like cart abandonment. This supports product teams to optimize user journeys and remove friction points effectively.