How to reduce Customer Churn using Power BI
Customer Churn

How to reduce Customer Churn using Power BI

Sep 16, 2020 | Blog, Service |

Businesses rely on their ability to gain and retain customers in order to thrive and generate income; but what if a business is losing customers? This should sound an alarm because it will result to reduced profitability, the need for more marketing and re-acquisition costs among other unfortunate outcomes.

You will lose customer if they lack confidence in quality of service, consistent disappointed in unmanaged expectations or violated core values. There is a high risk of losing customers if the perceived risk of owning the relationship is higher than the reward to stay, which in simple terms means that the customer is disconnected from the company.

Loss of clients is referred to as customer churn or customer attrition. This loss can be voluntary or involuntary. Voluntary loss means that clients have shifted their interest from your services and chosen to consume those that are offered by another company.

Involuntary loss on the other hand, occurs when circumstances beyond a customer’s control occur. This can be death, relocation or an ailment. When calculating the churn rate, analyst will focus on voluntary churn because it is influenced by factors that are within the company’s control and they affect the customer-company relationship.

The first step in reducing the churn rate is calculating it. It is important that you understand what you are trying to reduce. This can be done in two ways; customer and revenue churn. Customer churn refers to the number of contractual subscribers that leave over a certain period of time while revenue churn refers to the amount of revenue that is lost in a given period.

 How do you calculate the churn rate?

Start by selecting the time frame for which you want to calculate the churn rate. For example, if you decide to work with a time frame of a month, divide the number of customers lost by the number of customers that you had at the beginning of the month. The answer you get is your customer churn rate. Avoid including new subscriptions that occurred within the month.

The revenue churn rate is simply calculated by diving the revenue lost from existing customers by the total revenue that you had at the beginning of the month. This is referred to as gross revenue churn rate.

Alternatively, you can decide to take into account an increase in revenue due to up-sells resulting to high cost subscriptions. This will be referred to as net revenue churn rate. It is calculated by subtracting revenue gained from up-sells in a certain time frame from revenue gained from existing customers in the same time frame. The answer you get; divide it by the revenue at the start of the timeframe.

In net revenue churn rate, strong negative numbers are good indicators while positive ones are bad. When there’s a strong negative number, it means that a company’s revenue will continue to grow even if there are no more sales within the month or given time frame.

 How to reduce customer churn using analytics on Power BI

Now that you have understood what customer churn rate is and how to calculate it, how do you reduce it through analytics on Power BI? Well, apart from providing analytics in real time, Power BI has gone a notch higher and enabled us to determine the number of lost customers. More specifically, it helps to:

Identify the At-risk customers

They say prevention is better than cure and so, you can use customer journey analytics to understand customer behaviour that will in turn increase your ability to identify at-risk customers and thereby reduce the churn rate. This is made possible by getting a data-driven understanding of customer preferences and the best way to reduce friction. The valuable data helps companies to easily identify and prioritize opportunities for improvement hence turn the situation around.

Focus on the entire journey rather than the period before the churn

With Power BI, it’s easy to map out the customer journey and analyse the complete end-to-end experiences in the shoes of the customer. You will visually be able to see the experiences of each customer, the descents and the actions that were taken.

Poor experiences can result from time to time. Analytics can help you discover these poor experiences whose causes can range from poor installation to poor customer service. Getting to understand the entire customer journey and not just the last interactions, will help you discover causes of poor customer experiences.

Customer journey analytics can pinpoint what are the key drivers of customer satisfaction. Once you understand and quantify what matters to your customer, you then seek to provide a consistently superior customer experience and measure the impact on customer churn.

Discover your most profitable customers and focus on keeping them

All customers are important but not equal. In as much as you would want to retain all of them, sometimes, resources may not allow you to. The most important thing to do is give first priority to the most profitable ones.

Using customer journey analytics, it is possible to group your customers in segments defined by profitability, readiness to leave, purchasing behaviour and a lot more. With this information at hand, it is possible to reduce the churn rate because you are able to predict far ahead on a possible churn and avoid it.

[Read: Why it is Time to Adopt Customer Analytics Solutions for your Business]

Target the right customers

Right customers in this case refers to the ones who are less likely to churn. If you want to retain your most profitable customers, make sure to target those who are best-fit for your product, see value and believe in it. These customers are less likely to churn.

Segmenting your customers on Power BI based on behaviour, demographics among others, will help you discover the most predictable paths and the key attributes of prospects who eventually turn into long term and profitable customers. With such information, you can target the right audience as well as set the appropriate customer expectations significantly reducing the churn rate.

Enhance Customer Experience

Poor customer experience or unmanaged expectations can drastically increase the churn rate. Flawed and inefficient process in customer experiences, lack of personalized service among other things will definitely cause customers to churn. From analytics on Power BI, you can find the best approach that can help you identify, predict and turn around poor customer experiences.

Create a Customer-Centric culture

Put resources aside and create a customer-centric culture. This is the culture that ensures that everything is done with customer satisfaction in mind. It gives direction to the effort of the employees and ultimately results to customer retention and higher monetary gains. This involves listening to customers, understanding their needs, advocating and acting on those needs.

Reducing the customer churn rate requires consistent effort and focus. Power BI can help you identify your customer trends. Talk to us here: to get set up on Power BI.

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