Chris Arnold is the VP of Contact Center Strategy at ASAPP. He works with customers like JetBlue, Dish, and others to implement technology to improve engagement, lower costs and increase agent efficiency. Prior to ASAPP, Chris spent 20 years leading contact center strategy and technology implementation for Verizon and Alltel, leading staff operations, and managing desktop automation and augmentation
I have spent virtually all of my professional career working with CX and IT leaders in Fortune 500 companies. These companies are investing millions of dollars annually in speech analytics that have maxed out the benefits they can deliver in improving quality management.
Many companies only transcribe a small fraction of their calls and only score a smaller number of those. And often the recordings are batched and stored for later analysis. Having to sift through the data, trying to pull out relevant information, and coaching agents after-the-fact with that information is cumbersome, incomplete, and moves the needle incrementally in terms of improvement.
When I was leading technology operations at contact centers, a consistent theme when re-evaluating our speech analytics toolset was “There are no new insights into what customers are contacting us about. We get reports—but there’s nothing really actionable—so nothing changes.”
We should be asking more from our speech analytics and transcription technology.
Now we can. Advancements in artificial intelligence (AI) raises the bar for what we should expect from our sizable annual investment in this technology.
AI-driven transcription and analysis of every call helps you optimize performance—and gives you a wealth of customer insight.
AI quietly powers transcription and speech analytics in real-time and enables us to use the results in hidden ways we did not even realize possible. Examples include:
Empower agents with coaching support and tools to resolve issues faster
Get voice of the customer (VoC) insight from 100% of calls
Analyze customer sentiment in real-time and use machine learning to predict customer satisfaction scores as a call transpires
Supercharge your agents using real-time transcription
Real-time transcription can serve as fuel for your voice agents and accelerate CX performance. Since the majority of customers still contact companies by phone—and voice is the most costly channel—isn’t this where we should be focused?
While it is important to optimize your operations through both live agent and self-serve digital channels, phone calls will continue. Let’s use AI to super-power our agents to make the high-volume voice queues as high performing as possible.
Real-time transcription paired with real-time AI-driven analysis makes it possible to prompt agents with suggested responses and actions based on machine-learning. Additionally, real-time transcription enables automation of thousands of micro-processes and routine tasks, like call summaries.
One of the largest communications companies in North America uses AI to automate the dispositioning of notes at the end of agent calls and realized a 65% reduction in handling time for that specific task. At ASAPP, we have seen large CX organizations who leverage this modernized approach to transcription at scale, reduce their overall CX spend by 30% which translates into hundreds of millions of dollars annually.
Fuel CX operations with voice of customer analysis for 100% of calls
In and of itself, transcription doesn’t make front page news. Very often it’s an expensive component of contact center technology that’s not providing a return on that investment. For instance, most companies are only transcribing 10-20% of their calls due to costs and as a result, business decisions are made without data from more than 80% of customer interactions. That’s not even close to a complete representation of everything happening across the totality of their CX operations.
Today, it’s realistic to transcribe every word of every customer interaction. You can leverage AI to analyze those transcriptions and make real-time decisions that empower agents and improve customer experience in the moment. Highly accurate transcription, coupled with closed-loop machine learning takes the customer experience to another level.
Predict CSAT/NPS with real-time customer sentiment analysis
Every CX leader strives to delight customers—and wants to know how they’re doing. Most use Customer Satisfaction (CSAT) or Net Promoter Scores (NPS) surveys to capture feedback. Yet average survey response rates are between 5% and 15%, depending on the industry. With machine learning, you can now use your transcriptions and speech analytics to predict the sentiment (CSAT or NPS) of every conversation. It’s the equivalent of having the silent 90% provide feedback for every interaction.
Real-time analysis of transcription can discern intent and automatically categorize each customers’ reason for contacting your company. This will give you a deep understanding of exactly what customers are calling in about—and how that compares over time. You can also apply real-time trend and anomaly detection to identify issues and quickly address them before they become catastrophic.
This real-time capture of the voice of the customer is massively valuable to not just contact center leaders, but also Product, Marketing, and Sales teams as well.
Conclusion: Let speech analytics lead the way
Artificial intelligence makes our transcription and speech analytics investment actually meaningful and allows us to make material improvement in CX operations.
If you don’t know the specific drivers behind the interaction metrics within your company, it’s hard to make anything other than incremental changes in your CX programs.
AI lets us analyze every detail from the tens of millions of interactions that occur every year. Not just the metrics—call duration, wait times, etc. but the key drivers behind those metrics. What were the reasons for unexpectedly long handle times… were agents clicking around the knowledge management database trying to find answers? Or how about unbiased opinions on cancel rates… were they due to a product flaw or issues with customer service? Could better save approaches have been used? Or what may have caused the customer sentiment to shift during the interaction?
Imagine capturing 100% of every single customer interaction, whether voice or digital. Imagine having objective insight into drivers behind your contact center metrics. Imagine being able to do that in real-time.
You no longer have to only imagine. No more waiting around for partial transcripts and partial answers. No more manual, subjective scoring of a tiny sampling of your total interactions. The future is here, and we can find it in real-time, automated transcripts and speech analytics:
Supercharge agents with real-time desktop intelligence
Identify coaching needs in the moment—get it right for the customer the first time
Predict CSAT and NPS on 100%, of your interactions
Gain real-time insights—at a glance understanding of why customers are calling
Real-time transcription, AI-driven analytics, and the ability to quickly act on insights can be your hidden weapon to accelerate transformational change in your contact center.
In recent weeks, I’ve had the opportunity to discuss technical innovation with CIOs at several Fortune 500 organizations. I’m always fascinated to hear the story these leaders report how their corporation’s technology and operating framework came to be. Inevitably, every CIO notes how much time and energy their teams have invested in their technology stack, working through many levels of complexity. And they share their frustration at how difficult it is to gain anything more than incremental improvements year over year.
“They’ve been telling me the same thing for five years”
A common challenge faced by most senior leaders is the absence of new insights into what’s driving their CX outcomes. While there are terabytes of data flowing through these businesses, the use of legacy reporting and analytics methodologies renders scant new actionable insights. One CIO told me he no longer asks his teams to provide insights into customer contacts because, “I already know what they are going to tell me because they have been telling me the same thing for the last 5 years.” Antiquated methodologies can be used to report historical performance, but fall very short of providing the customer insights needed to deliver material value.
There’s gold in your data
Intelligent data processing translated into actionable insights can enable even the largest organizations to respond rapidly to ever-changing market dynamics. Most Fortune 500 companies are sitting on a mountain of data and extracting little more than information for historical scorecard reporting. This data is a valuable asset that could drive significant business efficiencies through the application of well-developed artificial intelligence.
Data from all your interactions with customers is a rich source of insights that can significantly improve performance across your organization.
ASAPP helps companies mine this gold
Leveraging native, self-learning artificial intelligence enables the largest companies in the world to gain new actionable insights into what’s driving their business outcomes. The ASAPP AI platform provides insight into contact drivers, customer intent and sentiment, trends, effectiveness of promotional offers. and opportunities for enhanced automation and self-service. Machine learning models deployed in both voice and digital environments offer real-time as well as historical insights that lead to double-digit OPEX savings, incremental revenues, and enhanced customer and agent experiences.
Turning insight into action
I work with F500 customers daily in modernizing how they use real-time and historical data to reimagine their CX operations. By deploying the ASAPP AI Native® platform, they are immediately able to identify common topics raised by customers, understand root cause, and see what actions were taken by agents to resolve customer issues.
Sales and Marketing teams can use these insights to drive upsell/cross sell initiatives, promotions to improve loyalty and retention, and enhanced personalization. The Data Science team can leverage agent insights to inform automation flows that will reduce the level of effort for customers to get answers to questions. And, the digital team can use them to update self-service content.
These insights also help contact center operations directly. Leveraging data-driven AI, one customer has more than doubled their productivity, with 2.2X increases in resolutions per hour while also realizing a 7 percentage point increase in CSAT. Rather than simply using data for historical reporting, this F500 company is using data to create a leapfrog moment at a very challenging time globally.
Believing there are no new data-driven insights within the CX environment is a costly mistake. Continuing to leverage legacy methodologies will lead to outputs that offer little to address new business challenges. Actionable insights are there, often hiding just below the surface. Identifying and taking action on these insights across the entire organization will result in employees working on critical areas of opportunity rather than old assumptions.