Uncovering customer insights in the age of information overload
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 over $3.7 trillion annually. That’s a number to pay attention to.
Further, there are now countless ways that customers can interact with different brands – from traditional avenues like phone calls to newer options like SMS and chatbots powered by the latest artificial intelligence (AI) advancements. While this increase in communication channels is to meet customer demand and deliver positive CX, it’s also creating more data than ever before.
Most organizations know that this customer data contains a wealth of insights, such as how frontline employees are performing, the issues that your customers are reaching out to you about, how customers feel about your products or services, and more. It’s no surprise then that customer service leaders have increased their focus on improving CX by 19% in the last few years. Yet, many still struggle to pull that intelligence out of this mess of data.
In fact, a recent Salesforce survey found that 33% of business leaders can’t generate meaningful insights from their data and 30% are overwhelmed by the sheer volume.
But with today’s technology advancements, particularly in AI, turning data into actionable insights is getting easier and more efficient – insights that can drive improvements in your customer service center and beyond. Here’s how.
CMO at CallMiner.
Diversifying your data collection strategy
Despite these ever-increasing communication channels, data collection is often still siloed or incomplete across organizations. On the one hand, many CX departments have continued to focus their data collection on solicited mechanisms like surveys or online reviews – in other words, asking customers for their feedback. CX leaders have been relying on these methods for decades, and we don’t see them going away, but using them as the only customer data source is keeping CX in the dark ages. That’s because, while valuable, we know solicited feedback is incomplete. For example, post-interaction and traditional NPS/CSAT surveys have consistently low response rates and often capture responses that fall on the extreme ends of the emotional spectrum (really happy or really upset).
On the other hand, many contact center departments are collecting call recordings or interaction transcripts simply because it helps them meet compliance requirements – missing out on the power of what’s in those interactions, which is unfiltered, unsolicited customer feedback. In other words, feedback that customers share without being asked. This unsolicited customer feedback has the power to fill in the holes of solicited feedback – those interactions in the middle, where customers might not be emotionally charged one way or another, but are sharing immensely valuable feedback on their experiences, your products and services, whether they’re leaving to go to a competitor and more.
Organizations need to diversify their data collection methods, collecting 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 across key indicators like agent performance and customer emotion to better understand CX and make data-driven decisions that improve customer outcomes. This comprehensive approach is key, knowing customer intelligence has the potential to drive businesses forward.
Leveraging emerging AI technologies to scale
Let’s say your organization is collecting all the data you need to get a complete view of your customers; it would be nearly impossible for you to analyze all of that data manually. Within the contact center alone, manually listening to calls or reviewing interaction transcripts would result in reviewing around 1-2% of all customer interactions. Is this a true representation of what’s happening in 100% of your customer conversations? Probably not.
Further, 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 work performance and 30% say it’s affecting their overall job satisfaction.
The advancements in AI, particularly in the last 18 months, have changed the game for scaling analytics capabilities when it comes to collecting, analyzing, and uncovering insights in customer conversations. So much so that 86% of US technology and data decision-makers anticipated their organization’s investment in AI capabilities would increase in the first half of 2024.
These AI investments haven’t just helped scale analytics capabilities, they’ve also helped to eliminate or reduce repetitive, manual tasks, empowering customer service and other frontline employees to focus on delivering better customer outcomes. And when employees are happier and more satisfied in their roles, they deliver better CX.
Driving enterprise-wide change
Without elevating these data insights across your organization, CX satisfaction (or dissatisfaction) remains stuck in a vacuum. Customer insights can impact and benefit nearly every department, enterprise-wide – and most business leaders already know this, with 90% of CEOs believing customers have the greatest impact on their business.
But organizations need to put this belief into practice, including leveraging customer insights to improve decision-making in marketing (such as improving campaign effectiveness), for specific products or services (such as identifying product issues or making smarter product development decisions), in sales (such as identifying language that results in deals closed) and more.
When enterprises strategically orient around CX – and the technology investments needed to achieve those goals – they’re able to do more than just improve individual metrics, like agent performance or efficiency. Instead, when entire organizations operate with the goal of being more customer-centric, meeting customers where they are, and using what customers are telling you to drive better business decisions, that’s when real progress is made.
While CX in the digital age often means more feedback from customers than ever before, it’s critical to sort through the noise and uncover the actionable insights that truly move the needle for your business. The alternative? Missing out on the intelligence that helps you adjust, improve, better meet customer expectations, and ultimately drive revenue.
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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 over $3.7 trillion annually. That’s a number to pay attention…
