When companies first approach your team, what are some questions they initially have?
Business strategies, user needs, and vision drive all our development decisions. That’s why, before anything else, we seek to understand our clients’ business goals as well as understand how their users interact with them—meaning we’re usually asking the questions! When our clients come to us, they’ve been drawn to our extensive experience in delivering real business outcomes and the richness of our capabilities and real-world, validated intents. We then align those capabilities with the business outcomes they’re looking for.
How long does it take to get up and running with your solution?
We recommend that companies take the time they need to deliver the experience their users deserve. There’s a lot of hype around getting these solutions out fast, but as an enterprise you can’t afford to have a bad or wrong experience. You can speed things up – without sacrificing quality – by working with proven vendors who have experience in your space and working with complex enterprises. Given our history and experience, we typically have solutions up and running very well in about 4 months.
What are a few of your favorite use cases?
I have to mention our first IVA that we developed for the U.S. Army, Sergeant Star. Although nearly 12 years old now—and certainly still evolving—the experience of building that recruiter persona for a client as iconic as the Army was unique, interesting, and trailblazing. For me, it’s a great reminder that AI can help a brand solidify their company values and voice while also driving business results.
To be honest, we’ve had so many great companies. We’ve seen a lot of success from customer engagement IVAs, such as Alaska Airlines’ “Jenn,” Charter’s “Ask Spectrum” and Dell’s “Ava”. And, of course, even now we’re continually developing new ways for our assistants to support customers and build value for them, even enabling our customer teams who are typically made up of customer care teams, so that they’re able to take over the continued training and development of their intelligent assistants.
For financial services and healthcare companies, what kind of ROI are they seeing? What are they most excited about?
Financial Services and Healthcare both have a lot of opportunity for impact. Right now, Healthcare is all about driving engagement with consumers and providing precise, quality service anytime. If you think about it, most people only get a couple hours with their doctor annually and they typically research illnesses or chronic disease outside of normal business hours. So the technology makes sense. It allows people to ask questions in their own words, when it’s convenient for them, get valuable answers, and even help them keep track of medications and treatment. Deploying an IVA, like Novo Nordisk is in the process of doing with “Sophia” for diabetes, gives these healthcare companies an advantage in patient care and satisfaction. They are getting never-before-seen, real-world data on the unmet and unarticulated needs of their patients and consumers. This data and the rich insights it provides these businesses not only improves services, but it also betters patient care.
On the Financial Services side, there is a lot of excitement and buzz around personal banking bots. And rightfully so—as a consumer, I want an easy, helpful experience, and there’s nothing easier than having a conversation on my terms.
However, there’s also an incredible opportunity within these organizations for Conversational AI to support their employees. These large organizations have the most powerful tools in the world sitting on their employees’ desktops, but the employees are spending way too much time learning and navigating different systems to get the information they need. We’ve deployed Conversational AI internally for large financial institutions that is integrated to all the backend systems and products. For example, Financial Advisors can simply say “Has Rosalie funded her account this quarter?” and the IVA will provide the correct, personalized information in real-time, allowing the employee to stay focused on delivering value for the company.
How has the customer experience changed for companies who are using Verint? What has the feedback from their customers been like?
Customer experience hasn’t necessarily changed much, but customer expectation has changed a lot. When some of our earliest customers were deploying IVAs, Siri hadn’t launched and the term “mobile-first” didn’t exist. Fortunately, our customers are proof that we’re now at a point where IVAs have proven ROI and that they can grow and evolve with consumer needs.
After our clients have worked with us, they have a much better understanding of IVAs’ capabilities and how they can think beyond the initial specific deployment to be a strategic element that grows with their businesses. This, in turn, allows us to hone in on building more integrated AI strategies across the entire organization with them.
Culturally, we’ve actually heard that our client’s customers are beginning to prefer customer service interactions through assistants as much if not more so than human agents.
Where do you see conversational AI in a year from now?
What may have started as small initiatives with chatbots and messaging, will become ubiquitous service channels through conversational AI. The conversational AI technologies that build chatbots will become a driving force for Enterprises as they propel themselves into the intelligence age, becoming AI-first and intelligence-centric organizations.
The shift from traditional IVR to NLU is already happening, broadening the scope of today’s conversational AI to encompass voice and digital in a single platform. Enterprises that have already started to embrace the intelligence age are restructuring their business models around their data and will differentiate themselves by it.
For companies who are considering a conversational AI solution, what questions should they be asking in their search?
They shouldn’t just be looking at conversational abilities of a system, as NLP and NLU ensures that most conversational intelligence technologies are fully capable today. Instead, they should be looking at the resolution of actions. Specifically, they should examine how conversational assistants move engagement to resolution through understanding of intents. And how they grow and manage that understanding over time.
Additionally, clients need to reflect on their own processes for resolving issues and achieving results. Only then can an IVA be effectively plugged in to facilitate an organization’s workflow and achieve specific business priorities and goals.
Aside from your own solutions, what are a few AI-powered tools used within Verint?
Grammarly is one of my favorite AI tools. I use it daily.
Outside of Verint, what are some AI use cases that you’re personally excited about?
I grew up on a wheat farm, so I’m personally excited about the AI use cases surrounding agriculture, from gathering and applying data to precision farming, and even servicing the equipment.
