Development of an Automated Customer Satisfaction Monitoring and Risk Prediction Platform

The client faces significant challenges in effectively capturing and monitoring B2B customer satisfaction levels, leading to reactive instead of proactive management. Existing methods do not enable early risk detection or automated insights, resulting in potential reputational damage and lost opportunities for timely intervention.

A mid-sized B2B enterprise specializing in providing customer experience solutions, aiming to proactively manage client relationships and satisfaction through data-driven insights.

• Develop a scalable web-based platform to automate the collection, measurement, and monitoring of B2B customer satisfaction data.
• Implement data science modules to analyze historical customer data and predict potential risks or emerging issues.
• Enable stakeholders to view real-time insights, dashboard visualizations, and alerts for proactive customer relationship management.
• Improve client retention and satisfaction scores by enabling early intervention based on predictive analytics.

• Automated data collection module for aggregating customer satisfaction metrics from multiple sources.
• Analytics engine utilizing data science techniques to learn from historical data and predict potential customer risks.
• Interactive web interface for displaying analysis results, dashboards, and alerts.
• Real-time monitoring and notification system for early risk detection and issue escalation.
• Backend integration with client data science modules to facilitate model deployment and updates.

• Customer feedback and survey systems
• Historical customer data repositories
• Data science and predictive modeling modules provided by the client

• Scalability to handle increasing volume of customer data with minimal latency.
• High system availability and reliability to ensure continuous monitoring.
• Security and compliance measures to protect sensitive customer information.
• Performance metrics targeting real-time analytics updates and response times under 2 seconds.

The platform is expected to significantly enhance the client’s ability to proactively identify and address customer satisfaction risks, potentially leading to improved retention rates, increased customer trust, and early detection of issues before they escalate. Based on prior similar implementations, measurable improvements in customer satisfaction scores and risk mitigation effectiveness are anticipated within the first year of deployment.