Machine learning has experienced exponential growth in the last few years. The International Data Corporation (IDC) projects that by 2020, machine learning and artificial intelligence spending will hit $47 billion, up from $8 billion in 2016. Eighty-nine per cent of chief information officers (CIOs) are either using or planning to use machine learning in their businesses. Ninety per cent of CIOs believes that the incorporation of machine learning in their organizations will improve decision-making, thus driving revenue growth.
But what is machine learning? Is machine learning different than artificial intelligence?
What is Machine Learning?
Machine learning and artificial intelligence are related, but they’re not the same thing. Artificial intelligence is the ability for machines to learn tasks normally completed by humans, such as speech recognition and decision-making. We often think of these machines as “smart machines.” Think of Google maps. Google maps can tell you the fastest route by car, foot, or bike, for example.
Machine learning, on the other hand, is part of artificial intelligence where machines teach themselves through experiences. In other words, the machine or computer thinks and learns for itself. Machine learning takes artificial intelligence to the next level of capability. As an example, think about Netflix. Netflix uses machine learning to analyze your entertainment consumption and spot trends. Then, Netflix suggests certain shows or movies based on your habits.
Pretty cool. But, how does machine learning help customer service call centers?
Handling Big Data
We’re creating more digital data now than ever before. Daily, 2.5 quintillion bytes of data are created. Google processes over 40,000 searches per second. Every minute, we send 16 million texts and send 156 million emails. Monthly, eight million people use voice control, such as Siri or Alexa.
Businesses receive, process, and store an enormous amount of data daily, even smaller companies. Machine learning can handle the big data thrown at organizations faster and more accurately than humans. Through machine learning, data can be organized and categorized much like a human brain; however, the technology does not share biases or bad days like humans do.
Machine learning can sift through the thousands of customer communications per day and comprehend whether a customer is upset and making a complaint or whether a certain offer would make a customer happy. It can also make predictions, such as whether customers would like to purchase a specific item or would rather terminate services.
Machine learning can sift through the data created by customers, while learning how to predict spending trends or satisfaction with the company. It can provide personalized service to customers based on past interactions, and make decisions and predictions with a degree of certainty while modifying its approach as it learns.
Incorporating Natural Language
The purpose of machine learning is that computers can act more human, with all the benefits of computing. Take, for example, natural language processing. Here, computers talk more like humans, instead of in that annoying techno voice.
Through natural language processing, computers can communicate with customers as naturally as a human customer service representative. Natural language capabilities can understand the nuances of human language, such as mispronunciations, pauses, or accents. The computer can process not only human language trends, but also emotion, such as if a customer is upset or mad. Machine learning serves as a significant component in natural language processing as the computer learns to talk and listen more similarly to a human.
Machine learning can also help to drive revenue and company success. By analyzing massive amounts of big data, machine learning will be able to solve consumer issues, predict spending patterns, and contribute to overall sales numbers. A recent study indicated that 38 percent of machine learning early adopters more than doubled their sales key performance indicators (KPIs) and 41 percent more than quintupled their KPIs. This included new leads and upsells, all critical to the customer service industry.
With machines gathering and processing data on customers, companies can analyze customer profiles and develop new sales campaigns. Machine learning can inform companies about which customers are most likely to purchase additional services or products, while anticipating customer needs.
Seventy-six per cent of companies uses machine learning to achieve sales growth. Forty per cent do so to improve sales performance. On the consumer side, two-thirds of customers will opt to pay higher prices to companies that offer superior customer service, thus increasing revenue.
Further, machine learning helps companies determine which customers they’ll retain and which ones will leave. By identifying unhappy customers through data analysis, companies can launch proactive campaigns to convert unhappy customers into happy, loyal customers, thus increasing revenue.
Encouraging Continued Improvement
Through customer analytics created by machine learning, businesses can focus on continually improving their customer service. Machine learning can learn from past experiences and adapt how it approaches future interactions.
Machine learning can analyze customer information before a human agent communicates with the customer, giving the agent the ability to understand the customer’s history before ever getting on the phone. Fifty-nine percent of consumers claim that a tailored interaction based on past history is key to winning their business.
By understanding and processing customer data, companies can focus on providing the most relevant content to that specific consumer, through machines or human agents.
Machine learning, as part of artificial intelligence, is not only helping industries like customer service call centres, it’s revolutionizing them. Never before have businesses had access to the information they have now through the assistance of machines and computers. By understanding how to incorporate machine learning into your call centre, while producing staggering growth and customer satisfaction results, companies can take their businesses to the next level. And customers will be happier and more loyal as well. After all, everyone wants to be treated like someone who matters.
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