Several techniques are commonly used in data manipulation for email marketing:
Data Cleaning: Removing duplicates, correcting errors, and filling in missing values to ensure data accuracy. Segmentation: Dividing the email list into smaller groups based on demographics, behavior, or preferences. Normalization: Standardizing data formats to make it easier to analyze. Aggregation: Summarizing data to view trends and patterns. Transformation: Converting data into a different format or structure for better analysis.