Customer Retention means keeping the existing customers loyal towards the business. Retaining customers helps businesses in repeat orders, profitability, and goodwill which attracts more new customers. Today businesses use your data to formulate strategies to retain you as a customer. So, if you want to know how Data Science is used for customer retention, this article is for you. In this article, I will take you through how Data Science is used for customer retention.
The Traditional Way of Customer Retention
Before understanding how Data Science is used for customer retention, let’s first understand how businesses used to retain their customers when the use of Data Science was not mainstream in the industry.
When Data Science was not mainstream, many businesses used to offer and highlight their after-sale services. People used to be loyal to the brands because of their after-sale services. It was helpful for businesses to expand in the market as the loyal customers always promoted their products among their family and friends.
For example, Apple is known for its after-sale services for a very long time. In the 90s, Apple was known for its dedicated customer support to troubleshoot problems faced by customers using Apple products. Apple’s products are also less vulnerable to malware compared to windows products. It also helped Apple retain customers and encouraged customers to use the complete ecosystem of Apple products.
So after-sale services were one of the most popular strategies for customer retention when Data Science was not mainstream in the industry.
Now Here’s How Data Science is used for Customer Retention
Today businesses have their customers’ data. They can easily find your interests and preferences by analyzing your data. So in this section, I’ll introduce you to some ways in which the use of Data Science has helped businesses solve all the problems based on customer retention.
Today, the way you interact with an application or your buying habits on a specific platform tells a lot about you. Businesses analyze your activities and screen time on their applications and websites. It helps them analyze and predict the segment of customers who may uninstall their application or stop visiting their website soon.
It helps in the early identification of customers who may leave soon. So once you are classified as a customer who may leave, businesses plan to retain you by understanding your interests, preferences, and buying behaviour. It helps offer discounts and offers on the products you may be interested in.
For example, as a fitness lover, I am highly active in the gym, which requires me to consume supplements. Whenever I visit Myprotein’s website to buy supplements and exit without purchasing anything, they send an email (titled “is this what you were looking for”) showing all the products related to my search query so that I don’t purchase from any other platform.
It helps Myprotein in retaining customers using Data Science techniques. They record your data, analyze your search queries, and recommend products to help you buy what you were exactly looking for.
So I hope you have understood how businesses use Data Science for customer retention.
Summary
Today, the way you interact with an application or your buying habits on a specific platform tells a lot about you. Businesses analyze your activities and screen time on their applications and websites. It helps them analyze and predict the segment of customers who may uninstall their application or stop visiting their website soon. It helps in the early identification of customers who may leave soon, and focus on them to retain them before they leave. I hope you liked this article on how Data Science is used for customer retention. Feel free to ask valuable questions in the comments section below.
