Customer Retention and Loyalty

Increase your revenue by taking a data-driven approach to building customer loyalty and achieving high retention rates

Customer Retention and Loyalty

Why you need to care about customer retention and loyalty

Keeping retention and loyalty at the center of any marketing strategy is essential to keep customers satisfied, happy, and spending. A recent Gartner report also reveals that 80% of a company’s future revenue will come from just 20% of its existing customers.

These reports make it clear that paying no attention to retention marketing and solely focusing on customer acquisition can result in customer churn, which ultimately affects the bottom line. Coming up with loyalty programs to increase the retention rate and reduce the customer churn is not enough, until these programs are personalized according to your customer’s expectations.

How Softweb helped a retailer increase customer loyalty

Our client, one of the leading online retail stores in the U.S., was facing a huge loss in revenue as its customer retention rate was decreasing. The client was focused more on acquiring new customers, instead of taking measures to retain existing ones.

Softweb’s data scientists gathered data from the client’s website to monitor customers’ behavior and buying patterns. Customer segmentation was done based on their previous purchases and how frequently they visited the client’s website. Our data science team then used machine learning algorithms to analyze a bulk of unstructured data that was gathered through text messages, e-mails, voice recordings, surveys, and social media.

After getting insights from customers’ data, the client’s website is now capable of sending personalized promotional messages and building customized loyalty programs for customers, based on the segment they belonged to. Also, the client is now able to adopt a more personalized approach to address customers’ issues.

Outcomes

  • The client is able to gain insights about customers’ buying patterns and predict when the next purchase would be made.
  • The client is able to retain more customers every quarter, after personalizing promotions for particular customer segments. In the previous quarter, the figure was 7 precent.
  • The overall revenue of the client increased by over 15% than before.
  • Increase in retention rate and reduced customer churn.

How online as well as brick-and-mortar retailers can benefit from data science-driven retention strategies

  • Improved customer retention and an established loyal customer base.
  • Ability to predict future purchases by analyzing customer buying behavior.
  • Ability to plan promotions for reactivation after detecting inactive customers.
  • Enhanced shopping experience for customers as clients suggested products based on customers’ taste and preference.
  • Happy and engaged customers.
  • Increase in sales and revenue, as the number of customers increases consistently.
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