Use Of Data And Analytics To Ensure Customer Retention

Customers are the key to a business’s success. Therefore, an entrepreneur must prioritize customer acquisition as well as retention over other business activities. The former refers to gaining new customers, the latter involves containing the existing customers by keeping them satisfied and convincing them to make repeat purchases. Customer retention helps businesses to measure their customers’ loyalty over time and assess overall growth. It is about building and maintaining a close bond with customers, who look to engage with brands that are reliable and always aware of their changing needs and priorities. By using effective customer retention strategies, businesses can make sure their existing customers continue choosing their products/services over that of their competitors.

To improve customer retention, a business owner must consider enhancing the entire customer experience, which is, essentially, the perception customers have about a brand. Extensive customer interactions often contribute immensely to customer retention. Therefore, a company must offer enhanced customer support, and sustain a strong relationship with the customers. Also, it needs to conduct periodic market surveys to stay updated on the changing needs and wants of the customers to be able to meet the same and acquire more loyal customers with its amended offerings. To gain customers’ trust, companies must have specific teams or automated systems that can aptly solve all technical queries/problems and ensure the best possible customer experience. But, hiring an in-house customer support team is not always viable for a small or medium-sized company.

Hence, outsourcing customer support services to reputed BPO companies has become a common practice among SMEs. BPO companies are equipped with teams of skilled executives, trained to communicate with customers on multiple channels and nurture the brand-customer-relationship. Also, they use different metrics like customer retention rate, customer churn rate, and customer lifetime value to measure the customers’ loyalty over a period. The customer retention rate is calculated by analyzing the number of customers at the beginning and end of a given period and the new ones added over time. Customer lifetime value measures the total revenue a company can expect from a customer, during his/her lifetime. Also, it helps businesses to identify their loyal customers.

4 strategies BPO companies use to ensure maximum customer retention:

  • Convenience
    Deliver fast support
    Research says customers tend to switch to a different brand when they are not delivered quick support. BPO companies, backed by a huge team of customer support executives and AI-enabled chatbots, can promptly reply to the queries of customers. Also, customers are provided with an estimate for the time required to solve their problems. As a result, customers tend to wait willingly instead of disconnecting the call or closing the chat frustrated.
  • Personalize customer interactions
    Customers often get thwarted when the on-call or on-chat customer care executives seem to have less or no idea about their raised queries. BPOs provide their support agents with the tools they need to extract customers’ information and stay updated on the raised issues. These tools help the support agents to view customers’ previous conversations as well. Sending personalized emails, with information about discount offers on previously purchased products/services, to existing customers often lead to repeat purchase.
  • Offer omnichannel support
    BPO companies these days use omnichannel support to enable customers to communicate on their convenient platforms like chat, call, email, social media, etc.
  • Gather feedback
    Customer feedback is one of the crucial tools used by support agents to get an idea about customers’ opinions. Testimonials and feedback are analyzed to understand customers’ changing needs and modify the offerings accordingly.

4 ways data is used to improve customer retention:

  • Convenience
    A data roadmap is developed.
    Firstly, corporate KPIs(key performance indicators) are automated, made scalable, and repeatable. Then key stakeholders are gathered and the primary business problems are defined. Post that, the technical feasibility of the plan is assessed. The progress is reassessed every 3 months. BPO companies are equipped with highly experienced executives who can take a firsthand approach to customer analytics.
  • High-quality leads are prioritized
    When enough data is available, algorithms are applied to compare the features and characteristics of existing and potential customers. This helps to identify the ones that are less likely to churn. The prospective customers who have characteristics (FTE size, annual spending, etc.) similar to that of the existing customers tend to like the company’s offerings and stick around for a longer time. Each customer segment offers unique features that help identify prospective customers.
  • Different customer retention analytics are used.
    Customer data is analyzed using different types of analytics like prescriptive, predictive, descriptive, diagnostic, and outcome analytics. The prescriptive analysis focuses on answering a specific question and helps to choose the best possible solutions among many. It also suggests how to illustrate the implications of each decision to improve decision-making. In the case of customer retention, it helps to analyze the next best action and offer. Predictive analytics uses models to anticipate future incidences in a specific situation. Descriptive analytics provide insight into past occurrences and offer patterns and trends, to enable detailed investigations. Summary statistics, clustering and association rules, etc. are examples of descriptive analytics. Diagnostic analytics is used to take a look at a past event and identify the reasons it took place. Outcome analytics provide insight into customer behavior that drives specific outcomes. It helps to better understand how and why customers are using the products/services of a particular company.
    Among the 5 above-mentioned analytics, predictive analytics is often used to create impactful customer retention strategies.
  • Machine Learning is used to create prognostic models
    Analyzing a huge number of variables, manually, sometimes turn out to be difficult and time-consuming for even highly skilled data analysts. This is when machine learning is used to create the best predictive models of retention. Machine learning uses math, statistics and probability to promptly reason why customers are churning or why they are sticking to a particular brand. Machine learning algorithms are repetitive and continue getting better as they consume more data. Text analytics is used to get data-driven insights. Customer grievances can be identified with a text analytics tool that uses sentiment analysis. Today, AI algorithms are being used to analyze free-text feedback in surveys, with the help of machine learning and natural language processing.


Data analytics is widely used, these days, to segment people into multiple groups and understand how each segment engages with a particular brand. Data like customer demographics, lifestyle, purchases, frequency of purchase, etc. are analyzed to understand customers’ needs, and priorities and retain them by meeting their unique requirements, and maintaining a close bond through enhanced customer support.

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