The evolution of the Customer Insight management system

By: Omar Abdul-Hafiz

The term “customer insight” has been trending widely in recent years as other terms such as “data analytics” rose to fame. As such, the idea of gaining deep customer insight originated (or evolved) as a result of years of experimenting with ways to better understand customers’ trends and needs. What emerged is the ability to get a 360-degree view of your customers’ behaviours through the strategic analysis of qualitative and quantitative data.

But how did this evolution come about? Let’s discuss this in some detail.

Post-sale feedback assessment

Before the emergence of customer insight as we know it, businesses depended primarily on something we can call direct “post-sale” feedback. As the name suggests, it’s the basic procedure of ‘surveying’ your customer after they have used your product or service for good enough time, to simply know how they found it thus far. That’s why another name for this can be “late feedback” assessment.

Yet despite its simplicity, it sure has its drawbacks. For one thing, it can easily be misused, by giving customers long and too detailed surveys which they might find boring and time-consuming. Another issue is that customers may not trust that the answers they provide in the survey will be honestly reviewed and taken seriously to begin with. Therefore, chances are that customers might either ignore the survey completely or take it and fill it up with inaccurate answers.

So, are we to say that these drawbacks make post-sale feedback assessment worthless? Of course not! In fact, it can still be quite effective if implemented correctly. You can read more about post-sale feedback and how to use it in this article that we published earlier.

Behaviour-based assessment

Moving away from post-sale feedback, we arrive at the behaviour-based assessment method. This method uses a more analytical approach to gauging customer sentiment and satisfaction. It works by collecting data about your customer’s behaviour from multiple sources, analyzing them, and presenting them to you in rich and detailed representations of different aspects of your customers’ experiences with your brand, as well as their beliefs or needs.

That being said, behaviour-based assessments do not depend on asking the customer direct questions to have their opinion about a certain issue. Instead, it focuses on collecting different types of data as your customers continue to use the product/service thus allowing you to take actions based on them.

And despite its thoroughness, the main drawback of the behaviour-based assessment method is its dependence on raw data or research. In other words, it only gives you pieces of raw statistics and information from which you may derive the facts that you need.

Pro-active customer insight

This is the point where things get quite exciting. The pro-active customer insight method builds on the behaviour-based assessment method and takes it one step further. To explain it, it’s best to have a brief real-life example.

Let’s say you have a customer named John. John is a middle-aged man who, according to data collected from his usage history, appears to be an avid fan of the Manchester United football club. In order to earn his loyalty to your brand, you can act proactively by offering him a free or discounted subscription with the local Premier League broadcasting channel where he can watch his favourite football team play!

As you can see from this scenario, you have taken the information you collected from your customer’s data and used them for keeping your customer engaged.

But one thing that we should mention here is that the pro-active customer insight method is implemented by using a dedicated software tool known as a customer insight management system.

What is customer insight management system and how does it work?

Similarly to a behaviour-based assessment system,  a customer insight management system integrates with a wide variety of different APIs and interfaces including your ticketing system, customer surveys, social media pages, email, SMS, IVR, and more. Then, it represents them in a variety of graphs, charts, and tables to reflect different pieces of information gathered. One example could be the sentiment gauge, which reflects an estimation of the customer’s overall satisfaction with the products and/or services they are using. Another example is having a graph depicting the propensity of churn as estimated from your customers’ payment history, among other data.

So, in short, a good customer insight management system can shift your CRM proposition from being primarily responsive to being proactive. In other words, instead of having to wait for your customers’ direct feedback before you can decide how to serve them next, a powerful customer insight system gives you a full omnichannel view of your customer interactions. With this view, you will have the power to predict, to a very close extent, what your customer is going to need or want next, and therefore provide them with it before they explicitly ask for it.

For more information, check out our products for customer feedback management, ESKA Voice of Customer, and customer insight management, ESKA 360 Insight.