Data For Business: Customer 360° for Customer Value Management (CVM)

Imagine you are standing on top of the highest mountain in the world where you can see the waters, streams, trees, valleys and animals all around you. What would you do? My guess is you will absorb yourself in the view to make the most out of your time.

Same logic applies to Customer 360° for CVM as it entails having an all-round view of customer activities in relation to your business in order to make the most out of customers and your business. It means every data, report, queries and requests on your customer in relation to your business are tracked and monitored.

I recently took on a Customer 360° project with a telecoms company. In this article, I am going to share (in sequels of course) my experience, challenges, results, lessons learnt and recommendations.

This piece will focus on:

1. The need for a Customer 360° approach.

2. How Customer 360° can be achieved.

Seat tight and let’s enjoy the ride!

What is Customer 360° as it relates to CVM?

Customer 360° or Single View of Customers (SVC) as it is sometimes called, is a holistic customer profile record that captures specific types of customer data from various touch points across channels and systems, aggregates that data to comprehend what is important to customers and applies those insights to deliver personalized and engaging customer experiences as well as achieve the company’s performance objectives.

Why do you need Customer 360°?

1. Build and Improve Customer Relationship: Creating lasting relationships with customers is crucial to any business. To do this, the business needs to have accurate, rich and meaningful data or information about a customer regardless of the medium used. The use of Customer 360° ensures that the right customer data is captured and seamlessly accessible by stakeholders in the company to effectively connect with the customers.

2. Know Your Customer (KYC): Customer 360° view shows how to make the customer happy, cross sell, upsell and retain the customer, deliver relevant personalized and contextual products to the customer. All these comes from knowing your customer.

3. Predictive Analysis: By collecting and aggregating various pieces of customer journey, a business can start to get a clearer picture of how a customer may act. For example, if a customer has not carried out any transaction on the network in 60 days, that customer is predicted to soon churn. This prediction would call for an intervention to ensure the customer is not lost to a competitor by offering a discount or flash sale. A customer 360° approach captures every customer’s interaction history and calculates a score for each event to know if the customer meets a particular metrics or not.

Now that the benefits of customer 360° is clear, the next question is HOW?

How can Customer 360° be achieved?

When embarking on the project, I read an article that says, “The 360-degree customer view is the idea, sometimes considered unattainable…” and I said to myself “Common guys, how hard can it be?” Now, I can confirm it is true.

According to Gartner, fewer than 10% of companies have a 360° customer data and only about 5% are able to grow their businesses systematically with this data.

Achieving customer 360° is a complex process guided by asking questions, formulating scenarios, re-visiting the objectives to mention a few — making the pursuit of 360-degree a never-ending quest.

My team and I started by splitting the project into 2 phases: Design phase and Implementation phase. We will cover the (how) design phase while the next article will cover the implementation phase.

The design phase also called conceptual design had us creating a framework by categorizing the type of customer data we wanted to capture. Namely:

a. Customer Personal Data (CPD).

b. Customer Transaction Data (CTD).

c. Customer Behavioural Data (CBD).

d. Customer Social Data (CSD).

Every data requirement was created, analysed and recorded. This served as the skeletal framework of the result expected.

Customer Personal Data such as name, location, phone number, email etc provides the initial basis for uniquely identifying every customer. While CP Data are a common starting point, they are relatively static and not good predictors of customer behaviours or contributors to key performance measures. They are simply identifiers as these data was provided by the customers themselves when they were getting on the network. The next step was to append customer personal data with their transaction, behavioural and social data.

Customer Transaction Data captures every transaction carried out by each customer. The transactions were grouped into Voice, SMS, Data and Top-up (remember this is a telecom company). The CTD is such an important data to the business as it captures key performance metrics like the most profitable customers for the network, customers that are likely to churn, customers that have churned already etc. From this data, we asked critical questions such as:

  • What 20% of customers generate 80% or margins and profits?
  • What 10–15% of customers have contributed the least to the business?
  • What is the average spend of a customer within a specific period? Etc

Companies can use the insights from this data to invest the bulk of their focus and services towards the most profitable customers and create intervention plans for the not so profitable customers.

Customer Behavioural Data: Customers are far better defined by their behaviour than anything else. While almost every other data are explicit, behaviours are implicit data. For example, explicit data such as gender, age, location and total spend of a customer show only how interested the company is in the customer. Implicit data such as type of data bundle purchased with a specific period, frequency of purchase, rate of data consumption are far more influential as it can show how involved the customer is with the company. This data is crucial for segmentation and product marketing.

Customer Social Data: Customers are becoming more active and engaging with social media channels and companies can listen and act upon data from their customer’s social channels to engage and build relationship with them. Customer complaints and expressions of the company can be aggregated and analysed to understand customer needs and improve the company’s services. This part, I am still working on.

So far, It has been a challenging, yet interesting and rewarding project and I am super excited to see where it leads. One thing I have learnt is that the Customer 360° never ends. As new customers are acquired, existing customers carry out transactions, new products are launched, the database is updated everyday.

Next article concludes the design phase with the creation of a data dictionary. I would also cover the implementation phase as well.

In the meantime, keep being customer-oriented!


  1. Chuck Schaeffer June 9, 2017 — How to design your 360-degree customer view.
  2. The What, Why & How of the 360-Degree Customer view. (2018, February 27). Retrieved from
  3. Vamsital July 22, 2016 — Demystifying Digital — Why Customer 360 is the Foundational Digital Capability.

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