Big data analytics: how data analysis can improve customer service strategies

Where does the real value of big data lie? For many the answer would be in attracting new customers. It’s undoubtedly true that many enterprises use big data analytics in order to attract new customers and extend the reach of their brand. However, a significant number of businesses are increasingly using the power of big data to improve their relationship with their existing customers.

Companies are now using big data analytics to improve customer service. It’s understandable when you consider that most customers today demand prompt, reliable and professional answers to their questions. What’s more they want these answers delivered through the right channels, whether that’s phone, email, social media chat or mobile application. The customer is still king, and it’s therefore incumbent on businesses to offer solutions and answers through the customer’s preferred communication channel of choice.

So how can big data analytics transform customer service strategies? Well, according to Michele Nemschoff, vice president of corporate marketing at Hewlett Packard, the answer is by giving businesses a real-time insight into the demands and expectations of their customers. The onus is now on businesses to say abreast of technology and adapt to the ever-changing tech landscape in order to ensure that the customer gets what the customer wants:

“Let’s face it – the Internet has changed customer expectations forever,” Nemschoff wrote on her corporate blog. “In order to gain a competitive edge, companies need to find new and better ways to improve the customer experience on all levels.”

Nemschoff added that companies have never been in a better position to analyse the desires and expectations of their customers than right now. Thanks to the millions of blog posts, tweets, “likes” and comments submitted through CRM systems every day, companies now have the unprecedented ability to uncover a great deal of information about how people like to receive customer service. Businesses can, and must, use this data to devise predictive analytics in relation to each demographic within their client bases. What’s more, they can also use this information to market more products and services to their most loyal customers.

However, the success or failure of such endeavours is entirely dependent on data quality. If the data is suspect or inaccurate, then predictive analysis is of little or no value and will do nothing to improve the business/customer bond. She believes that although all businesses are looking to improve their analytic capabilities, their efforts will be fruitless unless they are gathering precise, accurate and relevant information on each of their customers.