To implement a next-best-action model using machine learning, businesses can follow these steps:

• Collect data on customer interactions and behaviors using Snowplow's event tracking
• Clean and prepare the data for modeling, ensuring that it includes relevant features such as previous purchases, page views, and engagement patterns
• Train a machine learning model (e.g., decision trees, random forests, or neural networks) to predict the next best action based on historical data
• Deploy the model to generate real-time next-best-action recommendations for individual customers, and continually improve the model as more data becomes available