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Now before getting into everything else, let’s acknowledge first :



Customer data encircles a wide range of facts about the people and businesses via your website such as mobile applications, social media, surveys, marketing campaigns, and other online and offline routes.

Customer data is a vital asset for recognizing your customers and their goals.

For a successful business strategy, customer data is a cornerstone to it.



Names and job titles, Email addresses, online reviews Support ticket records. Transactions.

Customer data shapes into many sizes and shapes and from many sources too.

Without having the right perspective, and can seem overwhelming when customer data makes sense.

Creating some appearance of clarity and structure, customer data is often designed into groups. And here are four customer data groups.


1. Identity Data

This investigates the core of database marketing.

Basic personal customer data forms an organization’s fundamental understanding of each relationship.

In CRM, many or if not most standard data fields could be considered basic data.

A few examples are a contact’s name, e-mail address, phone number, job title, account information, and linked organization.

This allows you to determine your target demographic when you give a clear picture of what kind of people are interested in your products and services.

2. Interaction Data

As interaction data also referred as engagement data, the customers having many touchpoints with your brand includes the interaction data.

It is often anonymized and aggregated for high-level reporting.

Such as website and mobile app interactions, social media engagement as posts likes, shares replies native video views, etc.

Email engagement, customer service information, and paid ad engagement.

To track where each customer came from.

Some marketing platforms provide user-level reporting.

3. Behavioral Data

It offers insight into the customer’s experience with the actual product or service.

Behavioral data helps you uncover underlying patterns, your customers reveal during their purchase journey.

Engagement data may or may not be a part of this data.

Browsing habits, online activity, social media usage, and buying behavior are tackled by behavioral Data.

From social ads compared to search engine ads, you can see if your business is getting more revenue.

The effectiveness of various touchpoints your customers interact with tracking tools like Google Analytics or Kissmetrics can help you measure doing that.

4. Attitudinal Data

The data helps you to understand what customers perceive about your company and the solutions you provide to them.

Attitudinal data deliver first-hand accounts of what customers actually think.

Online reviews, support ticket comments, and satisfaction surveys are sources of this data.

Preference data, opinions, desirability, branding, and sentiments usually captured in surveys. Usability tests and focus groups.


And now coming back to the topic let’s talk about the topic itself, here are some ways to extract value from customer data.

Understanding Big Data

Well, large companies are going to have access to lots of data that can feel overwhelming.

The ability to swift through massive amounts of data requires a specialized team to understand what is useful and what isn’t.

And accepting the fact that suitable data is buried somewhere in the pile is essential to beginning to glean helpful information.

People tend to ignore big data because its volume is doing so at the risk of their own business.

Recognizing that good data is “in there somewhere” and being willing to explore it is the first step in extracting valuable customer data.

Invest in Analytics

Using big data, once you get to know its potential, is having the right tools and the talent to drive into the sea of information and come back with data that makes the most sense to you.

The data reader’s job indescribably easier through analytical tools manually sorting through information and trying to group it together to draw conclusions is tedious and time-consuming, which costs the business money.

And the best way to save time and ensure accuracy for a company is to invest in analysis tools.

Historical Data

A company is working in a field with case-studies from previous years, conclusions can be made by previously tracked historical data to predict current and future trends.

Customer satisfaction and acquisition are based mostly on psychology, and what has worked before will likely work again.

People often think of data as a way to predict the future, but some of the most important lessons we learn from data come from the past.

To analyze historical data a good long-term plan Is essential for using customers’ insight data.

Data must be Accessible

Every time You should make sure that digital data is shared and accessible to those who need it.

Access data must be shared between your company.

When a customer calls into a contact center to raise a concern, some organizations are able to update that in real-time.

If you are knowing something about a customer’s need or behavior, but someone who could actually use that data doesn’t have access to the particular information and which leads to hurting the business.

Information is only useful when people know what to do with it and can get there.


Hence, more data is generated on a daily basis than humans or groups of humans can keep track of it.

However, only through strategy and sensitivity in choosing the right data, analyzing it, and using it in a correct way can improve its business revenue.

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