“Information is the oil of the 21st century, and analytics is the combustion engine.” – Peter Sondergaard, Senior Vice President, Gartner Research.
Metrics is the new mantra in business today. Organizations, having realized the great potential of data, are putting greater emphasis on it to reach better business outcomes. After all, ‘you can only manage what you can measure’ and it is data that makes this measurement possible. Data can provide quantified insights into different areas of business functions and give valuable insights into how to make the functionality better. Customer Service is no different. Big Data is giving organizations the opportunity to understand their customers’ needs better and helping them respond to these needs better.
Data growing faster than ever before – by the year 2020 our digital universe of data will grow from 4.4 zettabytes today to around 44 zettabytes, that is approximately 44 trillion gigabytes and growing as the number of communicating devices increase. It is estimated that by 2020, we will have over 6.1 billion smartphone users globally. There will be over 50 billion smart connected devices in the world, all developed to collect, analyze and share data. Smart companies are therefore looking towards data to provide better customer service and build long-term relationships.
Better Insights = Effective Decisions
Companies today have access to a vast amount of unstructured data that can be found in emails, social interactions, survey comments, blogs etc. By converting this unstructured data into structured data and analyzing it effectively with the help of a unified view of all data information and interactions, companies can gain valuable insights into the customers’ mind and their decision-making process. When analyzed on time, this data can identify patterns of customer dissatisfactions or product failures so that corrective actions can be taken in a timely manner. With the help of Big Data analytics, companies can combine transaction data with other data sources and make effective business decisions that are in tune with what the customer demands.
Identify what the customers want – before they ask for it
Big Data is giving companies valuable insights into not just what customers have purchased but also their consumption habits, interactions with the company and their preferences. Big Data analytics can give valuable insights into data sets for predictive behavior and offer more personalized solutions to their customer base. Companies can promote the right products to the right individuals through the right channel only with the help of Big Data. Amazon is a great example of how Big Data can be leveraged to improve customer service by fine tuning their recommendation engine. Other great examples would be Spotify, Netflix, and Pinterest to just name a few.
Improve Customer Interactions
Today we have come a long way from the time when the only way to connect with a company was through the customer service executive or relationship manager. The customer has more than one way to reach out to and connect with a brand. Big Data is giving companies the opportunity to make interaction with their customers more individualized by providing them targeted information. Further, collecting data and utilizing customer data in context, helps in conveying the right amount of information, helps in building a rapport with the customer, and facilitates better conversations. For example, Southwest Airlines used Big Data to provide better customer service by providing more tailored offers and promoting the right products with their clients. They are also using speech analytics to extract important data rich information from live-recorded interactions between the company personnel and their customers to gain a better understanding of their customers.
Having a ton of data and not using it has no business value. At the same time, having access to real-time data and having the ability to analyze it and action what is required is equally essential to building lasting customer relationships. The Social Habit research shows that 42% of consumers complaining in Social Media expect a response in 60 minutes! In the world of real-time marketing, it is essential that actions are almost immediate. Organizations want to analyze customer feedback faster to identify potential issues on time and address the problems before they escalate into bigger problems. Big Data can give valuable insights into customer behavior and also recommend actions to take in response within a given period of time – all of this eventually leads to a better customer service and greater customer satisfaction.
Organizations can use Big Data to gain insights into the pain points plaguing their customers. By taking the data dive, organizations can solve the difficulties and improve customer experience. Since the big data universe is replete with customer conversation, social interactions, reviews and feedback, organizations can utilize big data analysis to understand their customers’ sentiments and respond to both positive and negative comments. This keeps the company connected to the customer and gain competitive advantage. For example, banks such as RBS have used sentiment analysis to identify new customers and make specific changes to their offerings by identifying trends. Delta Airlines have also used sentiment analysis to identify the greatest pain point of their customers – lost baggage, particularly when there are delayed or during missed connections. On discovering this, Delta invested approximately $100 million in airport baggage systems to track and improve its baggage handling. They have used big data analytics to identify causes and trends in mishandled bags and have implemented effective solutions for the same. Further, Delta leveraged sentiment analysis in amalgamation with other advanced data to carefully tailor promotions and make customer interactions more personal.
While companies do understand that data is an important contributor to business success, it becomes essential to note that not all data is relevant. William Bruce Cameron quite eloquently opines that “Not everything that can be counted counts, and not everything that counts can be counted.” Learning to separate the good data from the bad, filtering out the irrelevant information and sorting through the white noise of data and then drawing careful insights via analytics are essential when companies want to use big data to improve customer interactions.