What types of predictive insights have you gained through AI that were previously unattainable, and how have these insights influenced your strategic decisions?

Churn Prediction: AI models can predict which customers are at risk of churn by analyzing a variety of factors, including emails, usage patterns, support ticket frequency, and customer feedback. This insight allows the team to proactively engage with at-risk customers through targeted retention strategies, personalized communication, and enhanced support, ultimately reducing churn rates.

Product Usage Trends: AI can identify trends and patterns in how customers use different product features, highlighting which features drive engagement and which are underutilized. This insight guides product development and enhancement decisions, ensuring resources are allocated to features that maximize customer value and satisfaction.

Sentiment Analysis throughout the customer journey: AI-driven sentiment analysis tools can gauge customer sentiment from various communication channels, including emails, chats, slack/team channels and support tickets. Understanding customer sentiment in real-time help in adjusting strategies promptly to address negative feedback and get cross-functional buy-in to reduce the friction points in the customer journey.

Support Ticket Resolution Time: Predictive analytics can forecast the time required to resolve different types of support tickets based on historical data. This helps in better resource planning, ensuring that the support team is adequately staffed and equipped to handle varying levels of demand, and improving response times and customer satisfaction. It also helps get buy-in from the product when you can show, through data and sentiment analysis, which problem areas are generating the most tickets.

Customer Health Scoring: AI creates dynamic customer health scores by continuously analyzing various data points, including engagement levels, product usage, support interactions, and survey responses. These health scores help prioritize which customers need immediate attention, allowing for more effective and timely interventions to improve their experience.