Customer Data means the data of existing customer or may it be prospective customer that gets generated while transacting, approaching, browsing your business on various platforms like your website, mobile application, social media networks, marketing campaign or specific objective surveys. 

Customer Data Analytics is a process wherein customer data used to understand their behaviour through visual analytics or predictive MIS and ultimately used by businessman to make strategic decisions.

Objective for doing customer analysis could be enabling exceptional experience to customer through exceptional employee behaviour and advocacy, provide regular service but better every time, setting up expectation and minimize problems through ensuring that ”Everything just Works”.

KPIs for Basic Level Customer Data Analysis –

Types of Customers

Loyal Customers:

Loyal Customer by its very basic meaning such customers who are committed to your product or service. It may be possible that it comprises of small or very small portion of your Customers base, loyal customers are the most likely to generate majority of fixed income. It is very much required to keep Loyal customers involved, engaged & feeling highly valued by your company.

Instinct Customer:

Instinct customers have no thought for their exact need, they are just browsing products & services. This type of customer buys the product or service, if Products or services meet their choice or requirements. This type of customers have high potential to become loyal customer.

Bargaining Customers:

This type of customers are just looking for exceptional deals or finding such time when they will get most benefits. Such customers can’t be convinced by upselling techniques. The only effort through which such customers can be attracted is “Advertising Bumper Sales”/”Festival Dhamaka Sales” etc. There are very rare chance that such customer can become Loyal Customer. 

Wandering Customers:

This type of customers are just roaming in the market. There are very less possibilities that they will make purchase. If one can identify their interest, definitely he can try once but there are very rare chance that sale finally done.

Need based Customers:  

This type of customers buy the product or services very quick once they find it as per their requirement. Often there are chances that such customers get converted as Loyal Customers.

If there are any issues or queries to such customers then same can be taken care through proactive social media presence.

Types of Customer Data

Looking to the current situation when we are creating data at every minute and in near future also it seems that there will be more increased volume and variety of data. Out of this identifying  which data is most valuable to you is key point on which your overall Analysis depends.

Personal Identity Data: 

Any details that uniquely identifies individual and differentiates from other are Personal Identity Data. Such details are Naming details, Person details, Postal details, Contact details, Mailing details, Social Media Network details, Job/Occupation details etc.

Engagement Data: 

Any data that gives information of your customers while they are interacting with your business brand via different marketing media. This data includes customers engagement while using your website and interaction on social media.

Behavioural Data:

Any data that helps you to identify behavioural pattern of your customer during their transaction journey with your business is behavioural data. Mainly such data are of two types Transactional Data, Product Usage Data.

Attitudinal Data: 

This type of data is more affected by feeling & emotions of customers. It is more beneficial if this qualitative data combined with quantitative data.

Strategies for Customer Journey

Acquire/Target New Customers

  • Brand Awareness
  • Market Intelligence
  • Product Management
  • Marketing Strategy

Understand Customer Behaviour 

  • Customer Segmentation
  • Customer 360 View
  • Survey Analytics
  • Customer Experience

Increase Customer Experience

  • Pricing & Promotion
  • Personalization
  • Customer Life Time Value
  • Up-Sell/Cross-Sell

Retain Existing Customers

  • Customer Experience
  • After Sales Services
  • Reputation Management
  • Continuous new development in Products
  • Increasing Supply basket as per Demand

Advantages of Customer Analytics services

  • Consultancy in identifying KPIs for Customer Analytics 
  • Analytics for encouraging changes in Customer Behaviour
  • Analytics for New Customer and Retaining Customers
  • Analytics with Insights – sharing to Customers
  • Consultancy in setting up Internal Controls 
  • Consultancy for Deep Listening through Customer Life Time Value

Customer analytics become backbone of business wherein it creates pro-active path for business. This can be used most for right marketing audience at right time. Too much data will be of no use but 360 degree customer analysed data can be used for decision making. Today Customer Analytics perspective has changed to overall improving Customer experience and not just limited to marketing for churn.


Customers are “speaking” to vendors through data, but data volumes and complexity can drown out their voice without sophisticated analytics.