Although the term “Big Data” has actually been around since the 1990s, it was only in the last decade or so that it became common terminology in the contact center industry. Big Data originally referred to data sets that were too large or complex for traditional data processing applications software to deal with, like recorded conversations between a contact center agent and a calling customer. While unstructured data such as these recorded conversations held a wealth of customer data and business intelligence, the quantities of data were more than modern technology at the time could process into usable information.
Analytics in the contact center changed everything in the early 2000s. New algorithms allowed data scientists to use big data to predict customer behaviors and likely outcomes based upon the analysis of unstructured recorded conversations between customers and customer service representatives. Advanced data analytics methods provided a means of extracting previously unused data in the form of word correlations to identify business trends and other business intelligence. The contact center industry was undoubtedly on the vanguard of the Big Data movement.
Analytics in the contact center changed everything in the early 2000s.
As revealed by the results of the 2019 survey of contact center executives conducted by my company, Saddletree Research, in conjunction with the not-for-profit National Association of Call Centers (NACC) at Middle Tennessee State University, about 32% of U.S. contact centers are already using analytics for both quality management and to uncover business intelligence in their operations. Another 11% have funded speech analytics for purchase in 2019 while an additional 32% will seriously evaluate analytics solutions for purchase in 2019. This data provides further proof of the leadership role the contact center industry has taken in the Big Data movement.
Today, big data is everywhere. If you think you’re not already part of big data getting bigger, think again. Commonly used virtual assistants such as Google Home, Amazon Alexa and Apple Siri are constantly gathering data about users that help data scientists understand consumer behaviors, attitudes and preferences. Following the lead of the contact center industry, some of the biggest companies in the world are now gathering data that allows them to make predictions based upon unstructured spoken data.
Like everything else in the contact center today, big data and analytics are being impacted by what is commonly referred to in the contact center industry today as artificial intelligence (AI). I still struggle with the juxtaposition of the complexity of AI and how the term is being tossed around so casually by vendors and analysts in the contact center industry, but it’s true that machine learning, a subset of AI, is having a huge impact on the industry today.
Big Data relies on analytics to create value from data of all sorts, and analytics’ superpower is to detect patterns. It doesn’t ask what is driving those patterns or why patterns are appearing, it just detects them. In its earliest iterations, analytics required human intervention to make sense of the patterns that analytics and big data identified. While some intervention by data scientists is still required today, machine learning is changing the game.
Marketing and Big Data teams are discovering that the richest source of customer data they have is transcribed customer conversations. —Daniel Ziv, Vice President of Customer Analytics, Verint
The term “artificial intelligence,” to me at least, implies that some degree of cognitive learning is involved. Cognitive learning means that there are problem-solving abilities and reasoning occurring during the learning processing. Human beings possess cognitive learning and, in my opinion, we’re a long way away from cognitive learning-powered artificial intelligence in the contact center. Don’t be fooled by the buzzwords.
Analytics and big data actually rely on machine learning to get smarter. Rather than problem-solving and reasoning, machine learning relies on algorithms and statistical models to perform specific tasks. These algorithms and mathematical models are continually refined by the analysis of data, the recognition of patterns, decision-making based upon those patterns, and learning from the feedback it gets. That’s how Alexa, for example, continually gets smarter regarding your likes and dislikes in such a wide variety of lifestyle choices and preferences.
Today, the Big Data revolution is being driven by a desire to do even more with existing data. According to Daniel Ziv, Vice President of Customer Analytics at Verint, “The speech analytics market is evolving. Traditionally, contact centers were leveraging speech analytics applications that helped them improve operational efficiency, quality and compliance. Now Marketing and Big Data teams are discovering that the richest source of customer data they have is transcribed customer conversations. These teams are now leveraging this unstructured data to predict NPS and loyalty, to forecast and reduce customer churn, and increase upsell conversion rates.
“The next step is leveraging transcribed customer conversation and combining it with additional customer data points, such as lifetime value and previous purchases,” Ziv continued. “Transcribed customer conversations can unlock deeper insights, issues, pains and opportunities for improving the customer experience, providing significant positive impact within the contact center and throughout the organization.”
Like so many other technologies of the last three decades, Big Data has become an integral part of our personal and professional lives. Big Data is not only accessible to everyone, it is something many of us rely on daily in the form of virtual assistants in the home and office that do everything from entertaining us to providing instant information on almost any topic.
In the contact center, and in the enterprise as a whole, Big Data continues to improve in both capabilities and value. Refinements simplify the process and analytics make it accessible to contact centers of all sizes and budgets. Big Data and analytics are unlocking a world of customer experience possibilities and if you think Big Data is a big deal now, wait until you see what will be possible when Big Data gets, well, bigger!