A segment is built by analyzing data and grouping (clustering) elements that share similar characteristics (in the case of retail demographic, expenditure, lifestyle and media preference information). Segmentation is essential for cost effectiveness and accurately targeted direct marketing.
Attitudinal segmentation is commonly employed through market research data in the retail industry to gain insight into the customer attitudes, wants, views, preferences, and opinions about the enterprise and the competition. In addition to external / market research data, transactional data can also be used for development of effective segmentation solutions. It can be used to identify high-value customers and prioritize their handling according to their measured importance.
Behavioural segmentation is also based on transactional data and separates customers according to attributes that summarize their shopping habits. Such as:
1. Frequency and recency of purchases
2. Total spending pattern
3. Relative spending amount per product group
4. Size of basket
5. Preferred payment method
6. Preferred time/period/day of purchase
7. Preferred store / channel
The derived segments can be used for the development of differentiated sales, and marketing strategies and tailored to their recognized consuming habits.
The POS (Point of Sale) data is usually tackled by introducing a loyalty program which assigns an identification files to each transaction and permits the tracking of the purchase history of each customer and aggregation of the transactional information at a customer level.
RFM (Recency Frequency Monitory) analysis is a common approach for understanding customer purchasing behaviour. As the name suggests it involves the calculation and examination of three - recency, frequency and monetary that summarize the corresponding dimensions of the customer relationship with the organization. This model identifies the customer purchasing patterns and respective customer types of interest (infrequent big spenders or small but frequent purchases etc).
Market basket analysis identifies customer purchasing behaviour. Market basket analysis discovers relationships between pairs of products purchased together. It provides insight into the combination of products within a customer's basket. Market basket analysis can be used in deciding the location and promotion of goods inside a store.
Consumer have different preferences for the product and services offered on a market or respond differently to marketing actions. Companies can increase profits by using a commercial strategy differentiated by segments. In the dynamic competitive environment, enterprise need to try to understand its customers by gaining insight into their needs, attitudes and behaviours. Hence, segmenting helps to target appropriate marketing strategies to the most profitable shoppers.
