Using Data Insights to Increase Customer Retention
First of all, let us know what customer retention is?
It represents the number of customers who continue purchasing from a company after their first purchase in simple language.
So, of course, the customer retention rates should be higher, as, in this highly competitive environment, it is a bit hard to gain new customers. So one might not want the customers to leave and go to some other company for their product or service. Customer retention is a cost-effective manner to make more money for businesses.
For that, the companies will have to provide exceptional services and products which keep the current customers loyal and even get them to promote the business brand to others. That’s why most companies are paying massive amounts of money to the consulting companies to analyze their data and show them correct strategies to follow for customer retention.
In fact, as per McKinsey’s statement in 2014, the executive teams which make extensive use of customer data analytics across decisions observe a 126% profit improvement over companies that don’t.
What do you think these consulting companies do, which helps all the businesses so much?
Machine learning is the answer.
Machine learning does analytics on past customer data to predict future customer behavior. And when talking about past data, it can be anything like basic customer demographics, email/call history, purchase history, etc. What Machine Learning does is draws out correlations and patterns from the data which can be used to make predictions. And for all these machine algorithms to run, the consulting companies require all the client data to make accurate analytics and predictions and give out perfect data insights as a result.
One of the methods which are also common in the market, along with the machine learning algorithms, is text analytics. So the free-text responses to the open-ended survey questions asked by the businesses can be analyzed. This is also known as sentiment analysis. And most of the customer pain points can be spotted through it as we know that there are lesser good reviews as compared to the bad reviews. As when a product turns out to be fair, people might or might not write about it, but if it turns out bad, they will write about it on social media and the review page. That’s when sentiment analysis can help to show us what the customers are expecting from the business and how they are facing difficulties or problems. For this sentiment analysis, machine learning algorithms are used, too, along with Natural Language Processing.
Besides, the businesses followed other strategies to get correct data insights for customer retention purposes. Competitor analysis is one of them. Companies need to analyze their competitor’s marketing strategies online and look at what people are discussing on social media regarding the different brands. So the keywords can be picked up, and then maybe they can find out some message that they need to counteract.
Loyalty programs are another primary strategy that companies have started using for customer retention.
As stated by Oracle Responsys, whenever a business institutes a loyalty program, then they not only improve the customer appreciation but also increase the chances of existing clients sharing the joy with the people close to them.
There are several advantages to focusing on customer retention.
As per the Harvard Business Review, acquiring new customers for your business is between 5 to 25 times costlier than retaining an existing customer. And just by increasing the customer retention rate by 5%, the business can increase profits by 25% to 95%. Then the companies can reduce the costs of acquiring new customers. When the businesses keep the existing customers with them for long, it allows for more sustainable growth.
