Learn from Customers

3 broad methods can be effective:

1. Descriptive analysis provides a summary of numerous customers at a specific moment.
2. Predictive analysis helps draw insights that may not be directly observable in the data.
3. Prescriptive analysis recommends actions and indicates likely outcomes.

Interesting patterns and outliers found in analysis can point to behavioral insights. You may need to hire a data scientist to perform these types of analyses, or outsource this function.

It’s ideal to have skilled staff to analyze customer information, but there are simple ways to understand data on your own. 

Start by trying one (or all) of these tools:

• After talking with at least eight customers, create personas. Each persona combines attributes of similar individuals into a single description to use whenever you discuss that type of customer. 
• Create a customer journey map for each persona. Journey maps reveal what customers would most likely do, think, or feel when using your products and services.
• Use a quantitative research method like segmentation to understand sub-segments. 
• Launch a quantitative survey to draw out statistical patterns in sub-segments. 

To uncover new opportunities, it’s important to have a solid understanding of your target market. A segmentation exercise looks at your market base and helps you figure out which products or strategies fit certain customer segments. Details about sub-segments can further enhance product development, service delivery, and customer satisfaction. 

Try some of the practical experiments and tools in the CGAP Customer Segmentation Toolkit. Identifying the right innovations unlocks value for your organization and for customers, especially low-income households that may not have access to formal financial services.