Consumers today are becoming more selective about the businesses they support and where they spend their money. This makes it essential for companies to develop a deep understanding of their customer base in order to tailor their services and marketing strategies more effectively. Customer segmentation is the process of dividing customers into smaller groups that share similar characteristics or behaviours. In the case of a food delivery company for instance, some groups may prioritise convenience and quick delivery, while others might focus on price or healthy options. Recognizing these differences will allow the company to better customise their products, services, and marketing efforts to meet the specific preferences and needs of each segment, enhancing customer satisfaction and ultimately boosting retention and revenue.
This perspective leverages data on customers' purchasing patterns and preferences. The features you've chosen provide a holistic view of customer engagement:
- Cuisine Preferences (CUI_American, CUI_Italian, CUI_Asian): These variables help identify cuisine-specific clusters, aiding in targeted promotions or menu curation.
- Order Frequency: Indicates customer loyalty and engagement. High-frequency customers may belong to a "loyal" segment, while infrequent customers could be re-engagement targets.
- Average Spend per Order and Total Orders: These monetary metrics highlight customer value, supporting value-based segmentation (e.g., high-value vs. low-value customers).
- Customer Duration: Captures how long a customer has been active, distinguishing between new and long-term customers.
This perspective introduces variables that reflect lifestyle and demographic characteristics:
- Activity During Weekdays vs. Weekends: Shows variations in behavior based on the day type, potentially reflecting work schedules or leisure habits.
- Peak Order Hours and Day of the Week Peak: Indicates when customers are most active, useful for time-based marketing campaigns.
- Customer Age: Basic demographic data that can correlate with cuisine preferences, spending patterns, or activity trends.