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Data analytics can help in business growth by driving customer engagement and enhancing customer experience in the long run.
Fremont, CA: It is usually beneficial to comprehend how new technologies might benefit a firm before determining which technology to acquire. Customer lifetime value is a simple justification for using data, data analytics, and data-driven solutions to improve customer experience (CX) in your firm. Customers are a company's lifeblood, and a smart customer experience will keep them interested and satisfied. But what matters most is your Customer Lifetime Value (CLV), which is the sum of all the money you earn from a customer throughout their engagement with you.
Improving Customer Lifetime Value (CLV)
Profitability is only possible when the lifetime value of customers exceeds the initial cost required to acquire them. Positive CLV results from healthy customer retention rates: if you can maintain more customers for longer, they will create more revenue, higher returns, and greater profits. Customers desire an agile, automated, personalized, multichannel experience powered by data. It enables you to comprehend who your consumers are, how they shop, what they buy, and how they prefer to interact, allowing you to create more intelligent and effective tools to serve and keep them.
Additionally, improved data security can enhance the customer experience for new and existing clients. You should consider the most effective methods for protecting consumer accounts and data. It follows that secure consumers are satisfied customers, who are thereafter devoted customers. And often, the most profitable customers are those who are most loyal.
Data analytics for customer experience
CX innovators begin by collecting and integrating data from all possible sources—websites, in-app browsing, marketing interactions, chat, social media, customer support, and in-store—to provide a comprehensive, 360-degree perspective of each consumer. Some businesses will compile this data in customer-centric dashboards that can be seen by all departments when addressing customer needs. Others will employ machine learning and user-friendly interfaces to answer client inquiries using natural language in the context of ordinary business transactions.
An intelligent Interactive Voice Response (IVR) system, for instance, can modernize a restaurant chain's automated reservations systems, allowing consumers to rapidly confirm or modify a reservation while delivering valuable data to the business. A smartphone app for real estate uses data insights to facilitate meaningful relationships between buyers and sellers. And an online international money transfer business has discovered that providing consumers with real-time transaction progress updates that include all transaction details has improved the customer experience and maintained customer loyalty.