In today’s competitive landscape, customers are demanding more from the organizations they do business with, and a good customer experience (CX) can be the difference between strong brand loyalty and customer churn. In fact, poor customer service costs organizations more than $3.7 trillion a year. It’s a number worth paying attention to.
Additionally, there are now countless ways for customers to interact with different brands, from traditional avenues such as phone calls to newer options such as SMS and chatbots powered by the latest advancements in artificial intelligence (AI). While this increase in communication channels is aimed at meeting customer demand and providing a positive customer experience, it also generates more data than ever before.
Most organizations know that this customer data contains a wealth of information, such as how your frontline employees are performing, what problems your customers are contacting you about, what customers think about your products or services, and so on. It’s no surprise, then, that customer service leaders have increased their focus on improving CX by 19% over the past few years. Yet many still struggle to extract that insight from this mess of data.
In fact, a recent Salesforce survey found that 33% of business leaders are unable to generate meaningful insights from their data and 30% feel overwhelmed by the sheer volume.
But with today’s technological advances, particularly in artificial intelligence, turning data into actionable insights is becoming easier and more efficient – insights that can drive improvements in your customer service center and beyond. Here’s how.
Diversify your data collection strategy
Despite these increasingly numerous communication channels, data collection often remains siloed or incomplete in organizations. For one, many CX departments have continued to focus their data collection on solicited mechanisms, such as surveys or online reviews—in other words, asking customers for their feedback. CX leaders have relied on these methods for decades, and we don’t see them going away, but using them as the sole source of customer data is keeping CX in the dark ages. That’s because, while valuable, we know that solicited feedback is incomplete. For example, post-interaction surveys and traditional NPS/CSAT surveys have consistently low response rates and often capture responses that are at the extreme ends of the emotional spectrum (very happy or very upset).
On the other hand, many contact center departments collect call recordings or transcripts of interactions simply because it helps them meet compliance requirements, causing them to miss out on the power of what those interactions contain, which is unsolicited, unfiltered customer feedback. In other words, feedback that customers share without being asked. This unsolicited customer feedback has the power to fill in the gaps of solicited feedback — those in-between interactions, where customers may not be emotionally charged one way or another, but they share immensely valuable feedback about their experiences, your products and services, whether they’re going to leave for a competitor, and more.
Organizations need to diversify their data collection methods, gathering both solicited and unsolicited feedback, and combining those data points to gain a complete view of their customers. By analyzing all types of customer data, you can uncover insights into key indicators like agent performance and customer emotions to better understand the customer experience and make data-driven decisions that improve customer outcomes. This comprehensive approach is key, as knowing customer intelligence has the potential to propel businesses forward.
Leveraging emerging AI technologies to scale
Let’s say your organization collects all the data you need to get a complete view of your customers – it would be nearly impossible for you to analyze all that data manually. Within the contact center alone, manually listening to calls or reviewing transcripts of interactions would result in reviewing about 1-2% of all customer interactions. Is this a true representation of what happens in 100% of your customer conversations? Probably not.
Additionally, these types of manual processes mean employees can’t focus on other high-impact CX tasks, which can negatively impact morale and increase stress. In fact, another study found that 35% of workers believe data overload is having a detrimental effect on their job performance, and 30% say it’s affecting their overall job satisfaction.
Advances in AI, especially over the past 18 months, have been a game-changer for expanding analytics capabilities when it comes to gathering, analyzing, and uncovering insights in customer conversations. So much so that 86% of US data and technology decision makers anticipated their organization’s investment in AI capabilities would increase in the first half of 2024.
These investments in AI have not only helped expand analytics capabilities, but they have also helped eliminate or reduce repetitive manual tasks, allowing customer service and other frontline employees to focus on delivering better customer outcomes. And when employees are happier and more satisfied with their roles, they deliver a better customer experience.
Driving change across the enterprise
Without this data being disseminated across the organization, customer experience satisfaction (or dissatisfaction) will be left in a vacuum. Customer data can impact and benefit almost every department in the company, and most business leaders already know this: 90% of CEOs believe that customers are the biggest influencers on their business.
But organizations need to put this belief into practice, including by leveraging customer insights to improve decision making in marketing (for example, by improving the effectiveness of campaigns), for specific products or services (for example, by identifying product problems or making smarter product development decisions), in sales (for example, by identifying the language that results in closed deals), and more.
When companies strategically orient themselves around customer experience—and the technology investments necessary to achieve those goals—they can do more than simply improve individual metrics, such as agent performance or efficiency. Instead, real progress is made when entire organizations operate with the goal of being more customer-centric, serving customers where they are, and using what customers tell them to make better business decisions.
While customer experience in the digital age often involves more customer feedback than ever before, it’s critical to sort through the noise and uncover the actionable insights that truly make a difference for your business. The alternative? Missing out on the information that helps you adapt, improve, better meet customer expectations, and ultimately drive revenue.
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