3 Steps to Customer-centricity through Insights & Analytics

3 Steps to Customer-centricity through Insights & Analytics

Key Points

  • A paradigm shift from a traditional product-centric strategy to customer-centric.
  • Most of the customer data is in different silos hindering interoperability across the businesses.
  • Tapping into data that generates integrated insights can place the customer experience at the center, to make every touchpoint personal.

The wave of the digital revolution is actively pushing businesses to grow into digital enterprises in the next five years. An attention-grabbing question that should make us pause at this point – what exactly is becoming digital all about? Today, we live in a hyper-connected ecosystem where customer information is the commodity and the internet is the supply chain. To add to this, advanced analytics have ushered in an era of highly evolved strategies to innovate, engage and provide unique value to the customer. Customer-centric companies are 60% more profitable than companies that aren’t.

A majority of the organizations see digital transformation more as a competitive break and focus less on customer-facing necessities. Whereas, the reality is that in all business transformational practices, the customer experience is a key driver.


Data analytics empowers businesses to construct a 360-degree view of the customer, based on evidence-based user behavior and expectations. Predictive analytics can give seamless guidelines that can help businesses delight customers. By using actionable insights based on the identification of past trends in buyers’ behavior, the organizations not only create an opportunity to distinguish areas of improvement but also evolve innovation and offering diversities.

 “Place customer-centricity at the center of analytics” 



To achieve customer-centricity, firstly identify what customer data you hold, where it resides, and to what category does it belong. Data resides in numerous places in your organization and potentially falls into multiple categories. Go through unifying, identifying, transforming, standardizing, labeling, and organizing customer-related data stored in different structures.

Clean enriched customer data can also be acquired from sources outside your company. Ensure they possess the following types of information about your customers:

  • Age
  • Name
  • Email
  • Location
  • Phone number
  • Purchasing behavior
  • Facebook/LinkedIn/Twitter user
  • Attitudes and motivations
  • Products choice
  • Commuter patterns
  • Preferences

The above list is purely indicative and by no means exhaustive. The deeper your understanding of your consumers, the better your chances are to find and retain loyal customers. The power of data analytics can help you deliver the most relevant communication or support or offer, at the right time, which will, in turn, evoke a positive action from the consumer. Invest in reliable customer data points & save on customer acquisition and retaining costs.

“If investing in customer data, insights, and analytics seem too huge an investment, you will soon realize that lack of a 360-Degree customer journey view proves to be way more costly!”


The overall picture of building the quality of data revolves around achieving consistent, complete, accurate, and uniform customer data throughout the organization. Often customer data is collected without consistent governance, authentication, verification, or standardization. This makes it difficult and potentially costly to use data that lacks confidence around its reliability, accuracy, and compliance.

Simple data governance and metadata management initiatives can help tackle this challenge. Every enterprise generates user data from its business activities and operational transactions. Time to unravel the potential of your undiscovered & unused data.

Building data governance can be prolific in many guises. It can ensure that your organizations follow new data privacy regulations and rely more and more on data analytics to help optimize business operations.

For example, if customer names get registered differently in sales, logistics, and customer service systems, not only does that hinder data integration and but also creates data integrity issues. As a result, data errors might not be identified nor fixed on time, further affecting BI and analytics accuracy.

Breakthrough the data silos to harmonize your data in a collaborative manner. Here is where your data governance efforts will truly pay off.


Using trusted data and a single source of rich, reliable customer profiles, you can now start to capitalize on customer-centricity. If you have done Step1 & 2 right, you will eventually develop customer-centric programs, interactions, campaigns, and more, pivoted on the newly acquired information. 

Let us take for instance the healthcare ecosystem. While healthcare tech actively continues to evolve in the direction of AI-augmented care pathways, tools, and technologies, the industry itself has begun to realize the importance of the customer journey. Major healthcare outfits have started offering personalized, data-driven, tailored care pathways which have a higher success rate compared to generic programs. Understanding the customer’s/patient’s data and improving their clinical outcome is one of the best examples of applying customer-centricity.

AI and Machine Learning could provide great value by analyzing medical data and history to make predictions more accurate and impactful. Consequently, data coupled with AI can help healthcare institutions shift gears to a proactive approach, leveraging data & analytics to help determine which patients might be at risk for certain conditions, allowing doctors to proactively intervene and shorten recovery times.


Customer loyalty drives organizations to rise above the noise and chaos of competition. Customer-centricity is not just a shift in technology investment, it is the new normal to gain competitive advantage. 76% of customers expect companies to proactively understand their needs.

When technology, customer behavior data, and intelligent analytics come together, a business’ relevance to the customer is shaped. And this occurs when a business studies the customer journey entirely from the customer’s perspective. Good luck with your initiatives! At any point, if you feel the need to summon a quick-start team to get customer-centric analytics on road, feel free to reach out to us at

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