Experts predict a 180% increase in the amount of data consumed globally from 2020 to 2025, according to Statista. That’s a growth of 116 zettabytes in five short years. At the same time, there will be an enormous disruption occurring across the customer support industry. Users continue to increasingly prefer and often prioritize digital interactions over voice-based interactions. Digital interactions happen in channels like mobile app and web chat, and also instant messaging, social media and community forums. These interactions generate a wealth of structured and unstructured data at scale: Numeric, video, audio and text.
Customer support organizations that maintain practices of an era long gone are rightfully scared. Big change brings big uncertainty, and there are some leaders who may feel a sense of dread. What savvy professionals understand is that disruption isn’t necessarily bad – with the right perspective, it’s an opportunity to take the lead.
While it’s true the digital revolution is occurring with no signs of a slowdown, it doesn’t mean we’re approaching an era where live agents are wholly replaced by automated, data-driven counterparts. If anything, the reverse is true. Customer support providers must maintain quality voice-based interactions in addition to digital interactions to best serve customers and maintain a competitive advantage. Using big data effectively is a great way for any support organization to achieve both goals at the same time.
What Is Big Data?
Big data refers to large, complex datasets created from new data sources that are too big for traditional data processing software to manage. It encompasses structured and unstructured data formats that are ingested and analyzed rapidly – often in real time. Unstructured data requires an extra step before processing and analysis can begin; namely, to convert it into a format usable to statistical and other analytics packages.
As industries begin embracing data-driven insights as a competitive advantage, the term big data has become more mainstream. With the advent of advanced software packages designed with untrained audiences in mind, big data has evolved from a capability only the largest companies could leverage to being a part of the daily vernacular of many innovative industries. By overlaying these massive data warehouses with unstructured analytics tools and predictive modeling, data-driven projections can inform every facet of a business.
All of this is based on the universal truth that data, on its own, is meaningless. So much of it is being created daily that it’s virtually impossible to glean anything meaningful from it on a surface level. Big data, along with solutions like business analytics and business intelligence, allow organizations to dive beneath those 1s and 0s to uncover the story hidden underneath. Insights represent actionable intelligence that, when applied properly, allows even the smallest support organizations to unlock their full potential.
Why Big Data Matters in Customer Support
Big data enables and empowers customer support by providing ways to dramatically improve both agent performance and customer experiences. Big data analytics uncovers opportunities to streamline processes and improve interaction quality, cutting costs while also improving outcomes. Insights help deliver improved products and services based on real, actionable customer preferences. Big data-provided intelligence recognizes strong and weak aspects of a company’s performance, both of which are critical to long-term health.
Analytics leveraging big data sources help to accomplish these things by not only highlighting important intelligence but by also uncovering trends in complaints, customer satisfaction and even product issues over time – all of which can be used to make meaningful improvements quickly.
Although data volumes are increasing exponentially, something a lot of people don’t realize is that this data is getting easier to collect as the use of digital interactions increases. That’s especially true when interactions are paired with the right software-based solutions. Artificial intelligence, for example, can be used to highlight key words during conversations as they’re taking place. If a large volume of customer interactions all contain keywords that highlight the same issue, you have an opportunity to track agent responses to ensure those customers get a viable solution. You also can identify the root cause of the problem and take corrective action to prevent future issues from occurring.
Now that digital data is readily collected at scale, companies are able to predict interactions most likely to happen in the future and proactively improve resolution steps even before the situation occurs. And when it comes to voice of the customer, companies can gauge sentiment by analyzing tone and keywords. When businesses better understand not only what customers are saying but also how they think and what they want, they’re able to fix problematic processes, do more targeted training and identify the most efficient and satisfying customer approaches.
The disruption taking place in customer support represents an enormous amount of potential just waiting to be taken advantage of. Although it signifies a major change from traditional operations, newer environments are still built on the quality of customer interactions - albeit more proactively. Rather than waiting for someone to call with a problem, thanks to big data customer support now delivers personalized, empathic interactions with less effort than ever before.
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