Paul Davis Of Metropolis Corp On How AI Can Improve The Customer Experience For Saas Products
An interview with Maria Angelova
Rapid Application Deployment
AI helps SaaS companies to better serve customers through self-service/low-code tools. These tools reduce the time to deploy new products and customize them for their needs. Visual interfaces, guided by AI, facilitate component design through drag-and-drop features, while intelligent code generation automates manual coding.
It’s obvious by now that AI tools can be leveraged for huge cost-savings in contact centers. They’ll definitely impact the bottom line, but how will they impact the customer experience? That’s the question that will be front and center for many years to come. As a part of this series, we had the pleasure of interviewing Paul Davis.
Paul Davis is an expert at the crossroads of AI, customer service, and unified communications. Ten years ago, Paul started out at Metropolis Corp in a technical sales position and his knowledge in analytics and practical expertise in AI have propelled him to a prominent position within the organization. Paul is the driving force behind Metropolis’ advanced UC analytics solutions that utilizes natural language processing (NLP) and sentiment analysis to equip businesses with insights to optimize customer interactions and elevate their communication.
Thank you so much for doing this with us! Before we dive in, our readers would love to “get to know you” a bit better. Can you share your personal backstory with us?
Thanks for the opportunity!
I’ve been working in tech most of my career and for the past ten years, I’ve been at Metropolis diving into Unified Communication (UC) and collaboration data. I started using AI three or four years ago as an early adopter when Open AI launched Chat-GPT. It began as a productivity tool to help me to write better emails and tailor it to the audience I was working with.
But I saw the potential in it. From there, I started using Power BI and learning about machine learning and how to use AI to uncover sentiment analysis. Sentiment analysis is where AI detects the likely emotion of a speaker or writer, positive or negative, which is extremely important for customer service.
None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful for who helped get you to where you are? Can you share a story about that?
My stepdad was instrumental in shaping who I am. He instilled in me my work ethic, my desire to learn, and taught me to be prepared. He would quote Louis Pasteur, and say, “Chance favors the prepared mind”. He told me not to fear being overly prepared, or to ask questions. He especially emphasized the importance to say, ‘I don’t know.’
I think admitting that you don’t know the answer and having the humility to ask for clarification is a valuable skill.
From a work perspective, I had a couple of great mentors. There are different types of salespeople; those that are technically good and those that are good at customer relationships.
My first job out of college I worked for George Gordon and he took me under his wing. I didn’t know anything about sales, and I even looked down upon it as something I wouldn’t want to do. He taught me that sales is the lifeblood of any company, and it feeds everybody else. He helped me face my fear of getting into sales and taught me how to talk to people, how to prepare presentations, write agreements, etc. The second person would be Denise Luquer, she’s the sales manager at Metropolis. She taught me how to really build relationships with people and how important that is.
Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?
“Dream as though you’ll live forever, and live as though you’ll die today.”
It’s a James Dean approach to being imaginative and breaking the rules. You have to be innovative. Just because someone says you can’t do something doesn’t mean you can’t. If we don’t try new things, we will never grow. I firmly believe in visualization and dreaming.
Can you share with us three strengths, skills, or characteristics that helped you to reach this place in your career? How can others actively build these areas within themselves?
Number one is the relentless pursuit of learning. You have to be open to continuously learning. If it’s not challenging, and you become complacent, you won’t improve.
Secondly is a skill I am still working on. The skill is asking for help and not trying to do it all yourself. I struggle with this but it’s always in the back of my mind.
Finally, I think the last skill is to have patience with others and patience with yourself. You won’t become a master at something overnight. It’s an iterative process and practice makes perfect.
Which skills are you still trying to grow now?
I am learning how to take advantage of AI, specifically generative AI and language models, to become more productive in my life. I also need to discern which technology is helping to advance our productivity and customer service, and which features or tools are just taking up more time.
Which metrics were you looking to improve? Have you seen results?
I’ve been focused on improving two key metrics in my work. First, I’ve dedicated my efforts to quantifying time management, both for myself and our team. The most significant results have come from optimizing my own time and by better understanding how language models work. I’ve also learned the crucial importance of prompt orchestration. I wish I had realized earlier that if you prompt the right way, you will get the response you are looking for.
For customer service, we look for KPI’s such as average call waiting time, statistics on calls answered/abandoned, and overall sentiment score of these customer interactions. I rely on our AI tools to analyze this data, especially sentiment analysis scores, to determine if we were successful in delivering a positive customer experience.
Prior to the implementation, how did you evaluate potential CX impacts?
Before the implementation of AI-driven solutions, we evaluated CX through traditional metrics such as customer satisfaction scores, sales numbers, customer retention, and first call resolution rates. Those numbers don’t lie. Consistently having strong sales quarters is always a metric, and that is still a strong indicator of success. The same applies for customer churn. Building and nurturing long-term relationships with partners and clients is a direct result of a positive customer experience.
To further enhance customer service and support our team, we wanted to empower our agents with more efficient, accurate, and timely support tools. This led to the development of XeekAI, an AI copilot tool that, for now, is used internally. XeekAI has been trained on a comprehensive library of Metropolis-produced resources, as well as resources from partners and interoperability notes from other channels. Our team is able to ask XeekAI questions using natural language queries and receive an answer informed from an extensive knowledge base. Not even our best and most knowledgeable employees could match it.
What effects (positive and negative) did the implementation have on CX?
Implementing AI has changed the entire way we communicate. We now have the ability to perfectly craft the right message to a specific audience in the terms that they understand; this has been instrumental.
It used to take me, personally, a long time to craft an email that would be suited to an engineer versus one to a business analyst or someone with no technical knowledge at all. Now, within just a few clicks, I can tell AI to make this a technical email or alter it for a layman, and it is done.
The same is true for our other departments. In service and support, our first call resolution rates have increased, largely in part to the XeekAI copilot, and we were able to use the predictive AI in our UC analytics tools to optimize our call queues and hunt groups, so we’ve seen a reduction in customer wait times.
Even in our sales department we are using AI scripts to put together better demonstrations based on the exact buyer persona, their buying behavior traits, and so on. Before AI implementation, it took our team a lot of time to do research to gather that information. Now we use a prompt to prepare a presentation outline exactly specified to our customer’s needs so we can better help them.
What was the biggest CX challenge you faced before, during or after implementation?
Recently, Metropolis had a challenge meeting customer needs and the use of AI helped immensely.
We had a very large client that wanted to use one of our UC analytics products to report on communication in multiple locations and across multiple platforms in their enterprise.
Our product met most of their needs, but they needed custom integration with their contact center software that was specific to their business. We were able to use AI to rapidly develop a custom data connection method and to deliver what the customer wanted in a short amount of time. Our XeekAI copilot also helped navigate us through that project. In the future, having an interactive assistant to guide our customers through their software will greatly improve user adoption rates.
How do you foresee AI tools impacting a contact center’s staffing costs? How will they impact the mix of different agent roles?
I think slowly the contact center agent will disappear until there is not a human agent involved at all which will change call center costs from salaries to technology. Chatbots are already speaking clearly and providing answers even better than humans. These chatbots can operate as customer-facing support tools, offering 24/7 self-service support with sentiment analysis capabilities to better understand and address user emotions and needs. Eventually, this will eliminate contact center’s altogether.
Another more immediate way contact centers will change is their quality assurance department. With humans scoring the quality of a call, there is always human bias. Ten different supervisors can score the same call and deliver ten different scores. With AI and a sentiment score, the criteria for good vs bad is the same so you get consistency.
I participated at a round table discussion on AI at Microsoft Build this year and part of the discussion was how AI is displacing the whole ecosystem around the physical agent. At some point, you won’t even know if you are talking to AI. Queues will disappear, wait time will disappear, and everyone will have their own personalized AI agent to assist them.
But as agent jobs get displaced, there will be new jobs that replace them. I attended a business class recently and the professor was teaching students how to use prompting to create applications. Those are the types of skills that will become the jobs of the future.
Can you please share your “5 Ways That AI Can Improve The Customer Experience For Saas Products.”
- Instant Support
SaaS companies can use AI to give customers access to instant, self-serve answers. Chatbots have been steadily growing in usage and gaining popularity for over a decade, but the new generation of 24/7 AI-driven chatbots use machine-learning to answer questions from an internal, private knowledge base tailored by the SaaS manufacturer to deliver accurate, thorough answers. Customers will gain instant, self-serve answers. - Personalization
AI can analyze user behavior and preferences to deliver personalized features, tailored communication, and recommendations specific to their individual needs. This type of personalization will build customer loyalty by creating a more engaging and satisfying customer experience with your business. - Proactive Service Delivery
AI analyzes data to predict future user behavior. SaaS companies can use predictive analytics to address customer needs before users realize them, as well as prevent potential issues which reduces support tickets and saves time. Not only will this result in more satisfied customers, it also provides an efficient use of resources. - Rapid Application Deployment
AI helps SaaS companies to better serve customers through self-service/low-code tools. These tools reduce the time to deploy new products and customize them for their needs. Visual interfaces, guided by AI, facilitate component design through drag-and-drop features, while intelligent code generation automates manual coding. - Insights and Recommendations
Because AI can analyze large amounts of data, it can provide insights and recommendations that might not be noticed by humans reviewing data alone. This can help customers make informed decisions and get the most out of the SaaS product. For instance, Metropolis products use AI to analyze user data and provide insights into usage patterns, performance metrics, and potential areas of improvement. Our software measures metrics such as average call waiting time, statistics on calls answered/abandoned, and overall sentiment score of customer interactions. AI examines this data to provide insights, pinpoint data anomalies, and offer explanations for potential causative factors. These insights enable businesses to deliver a better customer journey.
Are there any underrated skills or qualities that you encourage others not to overlook?
I would encourage others not to underestimate the power of silence. The world is moving quickly, especially with AI, but the ability to be silent, to listen and absorb information without an immediate response will help you understand the nuances of a situation. Listening is a very beneficial skill.
You are a person of great influence. If you could inspire a movement that would bring the most amount of good for the greatest number of people, what would that be? You never know what your idea can trigger.
If I could inspire a movement, I would encourage everyone to reskill and encourage them not to be afraid of what they don’t know. I would promote AI literacy and suggest everyone embrace continuous learning. I would suggest people exercise patience and adopt an adaptive mindset.
Ideally, I would create ‘Paul’s AI’ that enables anyone to learn and achieve any goal just by asking for it. ‘Paul’s AI’ would teach you how to accomplish whatever you wanted step by step.
We are very blessed that some very prominent names in Business, VC funding, Sports, and Entertainment read this column. Is there a person in the world or in the US with whom you would love to have a private breakfast or lunch, and why? He or she might just see this if we tag them.
There are a few people I’d love to meet, but if I had to choose just one, I’d say I’d like to sit down with Elon Musk. I’d like to ask him about his initial fears regarding artificial intelligence and inquire about his strategies to prevent the emergence of a superintelligence in the world, particularly in the context of AGI (artificial general intelligence) where AI surpasses human intelligence. We already have autonomous agents achieving IQ levels of 160 and chatbots outperforming lawyers on the LSAT, so, how do you quantify intelligence at that unprecedented level?
I’d also want to understand his original mission while working with OpenAI and learn more about why he decided to break away from it.
Thank you for these fantastic insights. We greatly appreciate the time you spent on this.
