Gather Actionable Customer Insights

In the previous blog, we discussed about what is data analytics and in what business functions it can be used practically for any B2C or Retail Companies. So here comes the first actionable insights to be gathered from customer data analytics. 

The purpose of business is to create and keep a customer. This statement was made by Peter Drucker, the acclaimed 20th-century management consultant. A simple statement that reveals in just a few words that the long-term viability of a company is not just about maximizing revenue and minimizing costs. Long-term viability is about understanding what it takes to attract customers by continuing to meet and exceed their physical and psychological needs.

What Is Customer Analytics

Customer Analytics is understanding of Use of Data to understand Composition, Needs, Behaviour, Attitude, Satisfaction of the Customer to undertake targeted marketing & sales decisions in online and offline mode. 

Why customer data analytics is required :

Marketing & service differentiation :

• Improve marketing focus having different tastes,values and reasons to purchase 
• Build loyal customers and create personas as representative customers

Product and lifecycle :

• Predict future purchasing patterns
• Customise products to different individual groups 

Price :

•   Price products or promotions differentially to increase sales
•   Willingness to pay for optimal price.

What has to be the outcome of customer data analytics 

How to Do Customer Analytics in 4 Simple Steps 


1.Customer segmentation : 


Mainly can be divided only on the basis of

• • Geography
  • Demography
  • Behavior
  • Psycho-graphic

There are different models like RFM (Recent Frequency Monetary Value), Clustering, ABC Customer Analysis, Clustering, Factor Analysis

2.Measuring Key Operations Metrics : 


It will improve the understanding of the customers and health of the customers organisation from the customer’s point of view.

• • • Customer Acquisition Cost 
    • Customer Lifetime Value 
    • Customer Churn Ratio
    • Net Promoter Score Card

 

3.Customers need/want :


It has been analysed from the perspective of  Why, Where, How, and When is buying or engaging with the products or services. 

Collecting the right data through feedback, surveys, market research, competitor mapping and transaction data will ensure answers. 

4.Marketing Mix models like :


Above-the-line media activity (TV, print ads, digital ads, promotions, and discounts, etc.)   

Below-the-line factors (temporary selling prices, sales promotions, discounts, social media, direct mail marketing campaigns, in-store marketing, events, and conferences, meetings.)

A/B testing models can be applied to understand the effectiveness of each marketing campaign.

Conclusion:


Data is a new oil engine for any business which has to be effectively collected, measured and monitored to gather actionable insights for business decisions. Customer analytics helps drive in customer acquisitions at lower costs, able to retain customers more effectively with personalised targeting and recommendations. One example of best customer retention is Groccery Shop (Pan ki dukaan) who has maintained loyal customers through years and years by providing the personalised customer service with great experience. We all can use Customer Data to provide the same with minimum human interaction.