Clustering is implemented through data collection and analysis. Here are the steps involved:
Data Collection: Gather data from various sources like sign-up forms, purchase history, and engagement metrics. Feature Selection: Identify key attributes such as demographics, past purchase behavior, and email engagement. Algorithm Selection: Choose from clustering algorithms like K-means, Hierarchical Clustering, or DBSCAN. Model Training: Use the chosen algorithm to train your model on the collected data. Validation: Validate the clusters by checking their relevance and usefulness. Application: Use the clusters to tailor your email campaigns.