Customer insight is about going deep into a customer and understanding him on the basis of his needs, wants, beliefs and experiences which drive his buying behaviour. Deriving customer insight requires the quantitative and qualitative analysis of the data of the customers. Here, even though the quantitative analysis is a just a superficial analysis, a qualitative analysis dives deep to derive the customer insight.

From where do we derive data for customer insight?

1. Customer complaints
2. Customer enquiries
3. Customer feedbacks
4. Competitive intelligence
5. Market research
6. Feedback from sales and service staff.
7. Social media
8. Call centre
9. Store/experience centres
10. Sales history
11. PR activities
12. Website visits and engagement
13. Surveys

 

The information or data collected is analysed to the best. The data analysis team with a big data system may consists of

1. Data scientists
2. Domain experts

The analysed information needs to be rightly interpreted, probably on the following parameters with respect to the customer

1. Needs and necessities
2. Desires and expectations
3. Habit of purchase
4. Key drivers for purchase

The interpretation may also be done with respect to the current customer centric activities such as

1. Profiling of customer
2. Usage of social media for promotions
3. Advertising in mass media and analysis
4. Targeting and Segmentation
5. The ROI on the promotions
6. Pricing aspects
7. Churning factors etc.

The right interpretation of the customer data helps organisations to respond to the customer and reposition themselves in accordance with the derived customer insight in order to

1. Provide a customised product to the core.
2. Provide them better value for money
3. Provide more channels for purchase, ensuring convenience.
4. Bring about creative and attracting promotions.
5. Give customers a better experience.
6. Surpass the expectations of customers.
7. To relate and build relationships with customers.
8. To build a force of ever increasing loyal customers.