Calculate Customer Lifetime Value and Improve Customer Service
Why Is Customer Lifetime Value Important?
One of the important goals of any business is to keep increasing the value of the customers. Companies calculate Customer Lifetime Value which is a crucial metric that can accurately predict how much each customer is worth. A high Customer Lifetime Value means a customer has been retained by the company and generates substantial revenue, and is likely to bring in more revenue for the company. Each customer, if successfully retained, becomes more valuable with time. As their purchase frequency & value tends to increase, thus retained customers tend to generate more revenue for a company than the new ones and often require very less marketing to do so. Further retained customers bring in more new customers by word of mouth by voicing their good experiences, which helps improve the brand value in addition to increasing sales.
So calculating and monitoring Customer Lifetime Value for each customer is essential. It helps to identify high-value customers for companies to focus on these customers by providing them with facilities like better deals and offers, better customer support to increase their sales further.
Customer Lifetime Value Can Be Calculated As:
Average Order Value = Total Sales / Order Count
Purchase Frequency = Total Orders / Total Customers
Customer Value = Average Order Value x Purchase Frequency
Customer Lifetime Value = Customer Value x (average customer lifespan)
Can You Improve Customer Service Using Customer Lifetime Value?
Yes, Customer Lifetime Value can be a key metric to judge the effectiveness of the customer service of a company. A higher overall Customer Lifetime Value would indicate that the businesses are retaining more customers, and they are regularly purchasing with high ticket sizes. This would indicate that these customers have a pleasant experience with the brand and can be attributed to excellent customer service being provided. In the same way, a low Customer Lifetime Value can be used to identify that the customer service needs improving. Also, if the CLV data is made available to the customer service team and chatbot software that is used, then they can provide customised support to the customers focus on ensuring that the high-value customers remain happy. The low-value customers also get excellent support and can be retained further.
Challenges Faced By Businesses to Provide Good Customer Service
Monitoring customer service is often a daunting task for companies due to the lack of real-time data. Usually, the people who are in charge of monitoring and managing customer service and the team need to manually compile reports from various sources like IM services, Social media platforms, Emails, SMS, Chat systems, Cloud Telephony services to accurately track the efficiency and identify issues with the customer service. This compiling of reports is a difficult task in itself, and it takes a lot of time to prepare reports which are then analysed, based on which, steps for improvement can be taken. This time lag is one of the biggest challenges that companies face.
Due to manual reporting of data from various sources, it is not always possible to get detailed insights like :
a. How many customers are not happy and have issues that need to be addressed?
b. How many customers were assisted where they left with a positive impression
c. How many of these customers churned?
d. Are higher priority customer service tickets being addressed on time?
e. Is a high-value customer treated the same as a low-medium value customer?
f. Is the team being efficient with resolving issues?
g. Are issues being addressed on time?
h. Is the CLTV increasing with improved customer service if not, then why?
As a result of the lack of the above insights, companies fail to address critical points like :
a. Identifying if the customer service team is adequately trained or if further training is required
b. Whether the Customer Service team is understaffed and needs to be reinforced
c. What should be the frequency in monitoring the team and creating reports?
d. What type of customers are raising more tickets?
e. What are the most common issues being brought up? Is it a technical fault or a vendor fault? f. Is it necessary to address customers with specific problems, or High-value customers, uniquely or differently?
How Daton Helps in Calculating Customer Lifetime Value?
When it comes to improving customer service, daton can integrate with various tools that you may use to provide customer service like Zendesk, Freshdesk, Zohodesk, Intercom Tawk.to, LiveAgent, Freshservice, Salesforce your social media platforms like Facebook, Twitter, Linkedin, your cloud telephony services like Exotel, Knowlarity your email tools like Mailchimp, Moosend along with your google analytics or website analytics data. Thus valuable data such as purchase history, customer behaviour, cart abandonment, wishlist data can be easily consolidated and analysed to calculate Customer Lifetime Value effectively. Then make that data available to the customer service team so that they can quickly identify and give better support to high-value customers. Further Daton helps you easily generate reports so that you can analyse customer service experience of your customers and quickly generate accurate reports so that the time lag in analysing is reduced and the overall customer service is improved.
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