Hi Jeff, please tell us about your current role and the technology you handle at CallMiner.

As the CTO of CallMiner, I oversee research, language development, and future product direction. CallMiner has come a long way since I founded the company almost 20 years ago — today, we’re focused on delivering the most comprehensive speech and interactions analytics platform that enables organizations to more effectively understand and extract insights from the conversations they’re having with customers, and use those insights to drive meaningful business improvement. Those interactions span phone calls, chats, emails, and more.

For me, this means making sure we’re staying on the cutting edge of how we leverage advanced technologies, like artificial intelligence, machine learning, acoustical analytics, and more, in our platform to help power real-time alerting and automatic trend identification to improve conversation outcomes as they’re happening and future performance.

How much of your roles and responsibilities evolved through the pandemic crisis? What did you learn from these months?

The strength of a true leader is revealed when he or she is faced with a crisis. It’s safe to say 2020 was an intense testing period for leaders in all industries. The term ‘responsible leadership’ takes on a deeper meaning as employees and customers try to settle into our new digital economy.

Leadership teams had to work quickly to redistribute disrupted supply chains, safeguard employees, empower a remote workforce, and more with no time to ease people into it. All of these things were added to leaders’ “to-do” lists, while also working to inspire confidence and motivate their employees. It has been no different for me, and I’m proud of the hard work that went into keeping CallMiner on the right track.

Growth may have looked a little different for a lot of organizations in 2020, but the most successful leaders as we move ahead will be the ones who shifted their mindset during the pandemic and focused on laying the groundwork for 2021 and beyond.

Tell us more about a CTO’s remote workplace technology stack? Any advice for your CTO colleagues in the industry?

CallMiner’s remote stack is very MSFT focused, with Teams as the collaboration platform and OneDrive and Office behind that. This has worked very well for what we need.  My advice for other CTOs is to pick a platform that is more than video sharing — look for collaboration tools that facilitate meetings, document sharing and are surrounded by good security.

Tell us what it means to be part of the revolution that states “automating the call center assembly line”. What does it imply for call center agencies and telecallers, in general?

Twenty years ago, a customer would call a brand to complain about a bill, and they’d be put in touch with a product engineer. Several years later, businesses smartly began creating an assembly line for specific questions. Over the last few years, we’ve moved to automate that assembly line.

Organizations are now leveraging automation to solve simple issues without human support, and if an issue does require human attention, it’s routed directly to the right person. The pandemic has accelerated the automation of that assembly line even further. For CallMiner, it’s about providing organizations with the insights they need to meet the ever-evolving demands of the consumer, while also fundamentally shifting and transforming how they operate and make decisions.

In terms of the implications, this will have on contact centers, I believe automating the CX assembly line is going to get even easier and more personalized, which will only make agents’ jobs more seamless, while also helping drive ROI and business growth.

Contact centers will have access to data that will identify customers by name, know everything about their account and service plan, and quickly address the issue at hand. This kind of interaction is being called “anywhere operations” and according to Gartner, it will be used by 40% of organizations by 2023. Moving into our next normal, delivering optimized and blended virtual and physical customer and employee experiences is key in separating the winners from the losers.

How much have AI & ML influenced the adoption of ticket-based call center services? Any prominent case study you would like to discuss here for our audience?

We have found that the use of strong knowledge management, tied to good analytics, leads to machines getting into the real-time loop with the customer. This then allows for prediction and next best offers, which can all be more accurate and more available with these AI-influenced systems.

Tell us more about your work in the field of AI-based speech and interaction analytics?

I began building the foundation for CallMiner 20 years ago. I got my start working at a hardware startup creating high-density media servers to bring voice applications into telephone networks. Back then, everyone was trying to figure out how to leverage voice-over IP, and during a sales pitch with a big financial services company, I thought of voice mining.

Since then, more and more organizations are realizing the power that exists in understanding all customer interactions – not just the big ones. With CallMiner, brands can listen to 100% of customer interactions, including call, email, chat, and more, which enables them to better understand how customers are feeling or what they think of a new product, as well as capture what’s working and what’s not on the agent side to improve performance. With those insights, brands came to make better decisions and drive business improvement, whether it’s improved CX strategies, agent training modifications, and more. We turn customer insights into action.

Your predictions for AI-based consumer insights and how CMOs can benefit from these insights?

The U.S. hasn’t fully grasped the concept of customer vulnerability. The Covid-19 pandemic has shined a light on just how many customers are vulnerable — due to financial hardship, illness and more — and one of my predictions for 2021 is that businesses will start to care more about deeply understanding customer vulnerability and customer emotion than they do about sentiment, which can only generally identify if a customer is happy, sad or neutral.

While many brands are leveraging sentiment analysis to understand their customers, their attitudes, and beliefs, it’s more important to understand the “why” behind feelings. Using AI, machine learning, and natural language processing (NLP) technologies, brands can identify vulnerable customers in real-time, assess their emotions, and guide employees with communication tips and the next best steps for successful outcomes. Success here can help organizations build a brand that’s known for stellar customer service and responsible business practices. Plus, these insights can alert the organization to trends among their entire customer base in order to adjust strategy, positioning, and action.

While these types of customer insights can be valuable enterprise-wide, they are a treasure trove for CMOs. These insights can help CMOs more effectively market to customers and deliver services that better meet customer needs. For example, imagine if a CMO could use conversation analytics to learn that an influx of customers were having trouble finding the brand’s customer service number — that CMO could make informed changes to the ‘Contact Us’ page, or place that number more prominently in email campaigns and social profiles.

Having the right technology can mean the difference between truly understanding your customers and simply flying blind — and I believe that leveraging the actionable insights from customer interactions to inform business decisions and drive growth is going to be a defining factor in whether organizations succeed or not.

Thank you for answering all our questions!