Development of a Machine Learning-Driven Next Best Action System for Customer Engagement in ECommerce

The client faces difficulties in maintaining high customer engagement levels and reducing churn across their global platform. They lack a personalized system to determine the most effective communication and incentive actions for individual customers in real-time, risking decreased platform usage and profitability.

A large-scale, global eCommerce platform serving millions of customers across multiple countries, focused on increasing customer engagement and reducing churn through personalized communication and incentive strategies.

• Implement an automated machine learning pipeline capable of analyzing customer behavior data to recommend optimal next actions.
• Develop an extensible system that can deliver targeted communications such as vouchers or messages through existing APIs and communication channels.
• Enable the system to learn and improve its recommendations over time through continuous feedback and analysis.
• Integrate the solution seamlessly with existing infrastructure, minimizing disruption and ensuring scalability for future actions and functionalities.
• Create a data-driven platform that supports dynamic action assignment, including discounts, vouchers, and personalized messages, to foster regular platform use.

• Data collection module for gathering customer interaction and behavioral data
• Feature engineering and calculation layer to prepare data for modeling
• Predictive engine utilizing machine learning models to suggest next best actions
• Reward calculation component to evaluate action efficacy based on outcomes
• Reporting dashboard for monitoring predictions, actions, and outcomes
• API integrations for executing actions such as messaging, vouchers, and notifications
• Extensible action framework allowing addition of new incentives or messages
• Automated learning mechanism that updates and refines recommendations over time

• Customer Relationship Management (CRM) systems
• Incentive and voucher management systems
• Push notification and messaging platforms
• Existing data warehouses and analytics dashboards

• High system scalability to handle millions of customer profiles
• Low latency predictions to enable real-time decision making
• Robust security protocols to protect customer data
• System uptime of 99.9% to ensure continuous operation
• Automated model updates with minimal manual intervention

The implementation of this Next Best Action system is expected to significantly boost customer engagement, leading to higher platform usage and retention rates. The client aims to automate personalized communication efforts, resulting in increased revenues via targeted incentives and reduced churn. Early results demonstrate the capability to deploy new actions rapidly, with the system continuously improving its recommendation accuracy over time, ultimately enhancing profitability and customer satisfaction.