Supporting customer service phone calls via a Toll-Free Number is a standard business practice used to engage with customers. But have businesses considered the possible goldmine of revenue-driving customer information that these calls could hold?
Of course, businesses continue to exhaust the tried-and-true methods of customer data collection, including tracking purchasing patterns, conducting surveys, keeping email lists, combing through social media, analyzing web exit rates, and just plain observing their customers. But the customer service call is still the most widely used method used by consumers to resolve customer service issues. And these calls are a relatively untapped resource for data collection.
From learning more about individual consumer preferences, to spotting overall market trends, to identifying problems with specific agents, companies can glean a lot of valuable insights from consumer phone calls. And with the recent technological improvements to speech analytics, these millions of customer service calls are now easier and cheaper than ever to analyze.
Add all these factors together and it’s clear that companies that are willing and able to invest in speech analytics are poised to make a big leap in call center intelligence, customer satisfaction and improved profitability.
How Does Speech Analytics Work?
Speech analytics is a relatively new frontier. With speech analytics, a call center relies on a speech recognition platform that, in addition to recognizing a large vocabulary of speech, can also analyze tone of voice, identify relevant phrases and words, and even estimate the age of a caller.
That platform then aggregates this inbound audio conversation data and converts it into digital analytics, which can be parsed for information and indicators such as:
- Identifying recurring service or product issues
- Analyzing problematic customer interactions
- Identifying whether agents are being proactive
- Recognizing customers who need particular attention
Based on this data, businesses can implement informed solutions oriented toward improving call center performance, raising customer satisfaction and reducing enterprise costs.
All of this may seem fairly self-evident. So why haven’t businesses been listening to and analyzing these phone calls all along? Two familiar reasons: cost and technology. But thanks to remarkable improvements in speech recognition technology in the past few years, the age-old problem of cost is less problematic than it once was.
The same technology that today fuels improved speech recognition on your phone, in your home and in your car is also driving improvements in the automated call center realm. And as large companies like Apple, Google and IBM compete to increase the accuracy of these speech recognition technologies, companies that operate call centers can benefit from this innovation. These technological advances, plus the widespread availability of large server farms and cloud-based data storage, mean businesses can cost-effectively gather and analyze call center data more efficiently and effectively than ever before.
And as innovation accelerates, return on investment improves. Research by DMG Consulting indicates that speech analytics in call centers pays for itself in less than one year, and Techtarget reports that it pays for itself in as little as three months. So it’s no surprise that businesses are adopting speech analytics at a healthy rate. In fact, the market has grown from a mere 24 customers in 2003 to more than 3.5 million in 2015—around 20 percent of businesses that have contact centers. And adoption is increasing as technology improves, with up to 36 percent of businesses that do not use speech analytics saying they plan to implement it in the near future.
The rise of third-party organizations that offer speech analytics solutions, such as Ignite and CallMiner, promises to propel the market even further. These businesses offer the knowledge and experience needed to implement and manage solutions, and to integrate them with existing software and call center productivity systems.
Why Do I Need Speech Analytics?
Quite simply, speech analytics helps you deliver better service to consumers more efficiently. Specifically, speech analytics can help you train and curate your team of agents so that they are more consistently achieving performance benchmarks and improving customer satisfaction. It can help your strategy team gain a deeper understanding of customer behaviors, desires and pain points. And it can provide valuable insight into customer journey analytics, helping you understand and improve the customer experience like never before.
By analyzing agents’ performances and interactions, you can identify:
- Agents’ adherence to scripts and regulations
- Agents’ upselling and service performances
- Which specific agents need more training and in which service areas
- Opportunities for improving operational flow
- Which situations can be addressed through new or established best practices
And by analyzing what customers are saying during service calls, you can:
- Categorize calls effectively
- Gain a deeper understanding of your customers’ needs
- Identify consumer pain points
- Pinpoint recurring issues with products or services
- Determine which agent strategies work (and don’t work) for satisfying unhappy customers
- Spot potential customer losses
- Detect and prevent fraud by matching callers’ voice patterns
What Do I Do With Speech Analytics Data?
After you have identified all of these analytics-based data points, you can start to come up with the good stuff—the solutions that will help you improve customer service, increase consumer retention, inspire brand loyalty and reduce operational costs. These are the solutions and strategies that your team will create based on the unique insights gleaned from speech analytics. Such solutions may include:
- Strategies to streamline service quality, which can reduce call volumes, shorten call times and boost first-call resolution rates—all of which reduce operational costs
- Trainings and retraining’s that improve agent performances based on analytics-identified weaknesses
- Action plans to retain customers that analytics has identified as at-risk
- Procedures to exploit analytics-identified cross-sell or upsell opportunities
- Protocols that pass frustrated callers on to more experienced agents, based on real-time analytics-based emotion detection
- Tweaks to targeted marketing strategies, based on analytics-identified responses from specific demographics
- Real-time responses to changes in the market or to customer concerns, including updated agent scripts and immediate marketing and press responses
- Changes to products, pricing, services, or marketing and call center processes based on recurring customer dissatisfaction
Of course, solutions and improvements don’t need to stop in the call center. Speech analytics-based data and insights can be shared across your organization to improve productivity, service and collaboration. In a study done by Ventana Research, organizations reported analytics-derived benefits that included:
- Improved analysis of overall business performance
- Better collaboration between customer-facing business groups
- Improved alignment of decisions and actions across business units
What Is the Future of Speech Analytics?
As more and more businesses employ speech analytics, and as the technology inevitably improves, analytics is expected to transform organizational efficiency and boost customer satisfaction and revenues.
And despite the relatively slow adoption and innovation of text-based analytics, these solutions are expected to gain in prominence and use, as well. Many vendors are beginning to weave into their products solutions that analyze text message and social media interactions using similar technologies as speech analytics.
Of course, for businesses that utilize Toll-Free Numbers, these analytics solutions can prove to be extremely valuable. Because your brand identity and consumer connection are so intimately tied in with your Toll-Free Number, you have a strong base of incoming call data with which to build a robust analytics dataset. From there, the solutions—and the benefits—are yours to reap.