Customer Analytics

Customer analytics is a graphical representation and analysis of the entire customer management systems. The customer management systems contains, customer data management and integrity, customer segmentation and valuation, consumer data profiling and data quality, and finally customer loyalty management.

Customer data is collected from various sources, directly or indirectly.

• Data collected directly are from Surveys, Google forms, feedbacks pages, etc. The customers are aware of the data they provide to the firm. This data is used to improvise the customer satisfaction.

• Data collected indirectly are from ad-clicks, page clicks, website tracking, etc. The customers won’t be aware of the automatic background processing and analysis of these data. This data is used to analyze and give recommendations to the customers.

Let us take an example for indirect customer data sources. Customers buy products from various online sources such as Flipkart, Amazon, Snapdeal, etc. We get automatic recommendation of products, and they are according to our liking. How is this possible? All the movement of the customer buying pattern is recorded and processed in the backhand of the software.

• Credit card transactions

• Customer loyalty programs

• Ratings and reviews of the customers

• Recently viewed items

• The number of times a specific product or a category of product is viewed by the customer.

All these data’s are stored and processed by the backhand AI and ML systems.

These data are processed and used for

• Descriptive analytics

• Predictive analytics

• Prescriptive analytics

This will yield in better understanding of customer interests and tastes, and the companies can cater to the customer in a better way increasing the overall customer satisfaction.