- Analytics
- Churn / Attrition and Retention / Loyalty Models
- Clustering
- Customer Analytics
- Customer Life-Cycle Analysis
- Customer Segmentation
- Customer Value Models
- Data Analysis
- Data Mining
- Data Segmentation
- Decision Trees
- Market Analysis
- Market Basket Analysis
- Predictive Modelling
- Profiling
- Recency, Frequency, Value (RFV) Analysis
- Response Analysis and Models
Data Segmentation
Data segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing, such as age, gender, interests, spending habits, and so on. Using segmentation allows companies to target groups effectively, and allocate marketing resources to best effect.
Traditional segmentation focuses on identifying customer groups based on demographics and attributes such as attitude and psychological profiles. Value-based segmentation, on the other hand, looks at groups of customers in terms of the revenue they generate and the costs of establishing and maintaining relationships with them.
Data segmentation procedures include: deciding what data will be collected and how it will be gathered; collecting data and integrating data from various sources; developing methods of data analysis for segmentation; establishing effective communication among relevant business units (such as marketing and customer service) about the segmentation; and implementing applications to effectively deal with the data and respond to the information it provides.
Trying to understand the different characteristics of customers and prospects is a common challenge experienced by organisations today. Without this valuable information it is difficult to produce targeted and cost-effective communications. Marketing spend can be wasted on communicating with unprofitable customers and unlikely prospects. Resource can be ploughed into hitting the wrong target markets. Data segmentation can be used to overcome such issues.
Without data segmentation, an organisation can face various problems such as:
- General lack of knowledge about their customer and prospect base
- Untargeted communications producing low ROI
- Poor customer retention
- Incorrect messaging can lead to customer dissatisfaction
By segmenting your data, you will be able to identify different levels of your customer database and allow messaging to be tailored and sophisticated to suit your target market.