Using AI Analytics to Assess Effectiveness of Prospective Patient Calls

How Peerlogic conversational intelligence and call analytics improves patient communication and leads to practice growth.

DSOPro: Tell us about your background and what brought you into the dental industry.

I’ve worked in enterprise technology for the last 20 years, most recently for a company that provides a hosted voice phone service. We used a lot of cool sales technology, such as Salesforce and Outreach. We knew exactly what every piece of data looked like when we were out there closing deals or prospecting.

My wife, Kristen Miller, works for Patterson Dental, so naturally, we come home and talk about work. One day I said, “A lot of our friends are dentists. Who’s in charge of revenue for their front office?” The dentists and hygienists have their roles in dental treatment, but the top of the funnel—where people call in—no one really took ownership of that.

I had never worked in the dental or service industries and never had front office staff. However, my previous work led to endless technology designed to improve and manage revenue generation. I realized that front office dental staff may get some training on how to answer calls appropriately, but they weren’t really viewed as a sales arm. The calls coming in took them away from their day-in-day-out work, and no one was taking advantage of opportunities to close on more business. Plus there was no supportive technology.

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Dental practices have no visibility into what the top of the funnel looks like or what leads are being driven by marketing. How are you tracking if your marketing is working, or a referral came in from a current customer? What happened if they didn’t book an appointment? There were no good data points to be driven from that information. My wife and I went back and forth talking about it. I brought everything I knew from enterprise technology into the conversation, and that’s where Peerlogic came from.

I started building this idea out and after coming up with the design, tested it in the market. I needed to find someone to help us develop it and started looking for somebody local in Arizona. Through our startup community, I found a handful of developers, and gave them all a test to see “Who can solve this one coding riddle?” And Ana Tomboulian was the only one to do it. So, she came onboard working part-time to help me get the initial program built. A few months later I brought her on as a co-founder and CTO. She’s been amazing. She’s a coding savant.

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Alex Maskovyak was Ana’s former boss. When she quit to work at Peerlogic, Alex quit to come work with her as chief data scientist. He is a genius. He has advanced degrees in computer science, and he’s just a hell of a leader.

As a tech company, we’re totally product-generated and coding is a constant process. Everything revolves around how well our product works. Ana and Alex are the product team—they’re creating something from nothing every day.

DSOPro: What are conversational analytics?

We record the phone calls that happen between a patient or a prospective patient and the practice. That call recording is sent through our machine-learning pipeline, and our AI models analyze the recording contents. We identify whether the call was from a new patient and note whether the patient did or did not book an appointment. The AI picks that all up just from listening to the calls like a human would. That data is then added into a dashboard.

We track and pull a lot more information from those calls, like the insurance company they’re using and the sentiment or tone of the call to analyze how they were feeling. We can also look at measurements like hold times. If a new patient is on hold for 30 seconds the first time they call a dentist, are they more or less likely to book with them? We can tell you the answer to that just by having listened to millions and millions of calls.

Now, when I say “listening,” I mean analyzing it through machine learning. We’re just collecting data and bringing it all back into a dashboard. Staff doesn’t have to be worried about being listened to. However, if the front office, office manager, or the practitioner, whoever is operating the practice, wants to go back and review the calls, they can do that.

For example, if I own a group and want to see if a new marketing campaign worked, I can say, “I want data on every new patient who called but did not book an appointment, and whether the word ‘whitening’ was mentioned because we just ran a big whitening campaign to our existing patients.” You can run that report and see all the raw data numbers. And you can listen to calls to analyze if this is a problem with your team or a problem with your marketing.

Listening to every call is not really a feasible thing to do. We are that second set of ears, so to speak.

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DSOPro: Does this software integrate with other practice management software offices are using?

We don’t need to integrate with any of them to get our data. Our data comes back 90% accurate in its current state. If we do integrate with a practice management system, like Dentrix, we can improve accuracy because now we’re not just using machine learning to identify existing patients, we can look in Dentrix to see if a phone number is associated with an existing patient to obtain additional data.

DSOPro: How does Peerlogic reduce call times or otherwise help the front office?

We don’t just analyze inbound calls. We’re helping on the outbound side, too. Let’s say you want to call Delta Dental. Our platform will tell you their busiest time of the day and how much longer you’ll spend on a call if you make it during that time, as well as times with the lowest phone traffic. On average, we save customers a little over 6.5 hours a week in handling insurance calls.

Our platform has a voice side, too. Our own phone system can make and take calls, as well as send out messages. We can do automated messaging and back-and-forth SMS messaging. Depending on the customer, if a call is missed, we can send out a message saying, “Sorry we missed your call. We’ll be in touch with you shortly” or something like that so the patient doesn’t feel ignored.

We also can alert the front office when hold times exceed a certain level. We know a good patient experience happens when they get to a team member within 30 seconds. If hold times, or those handle times, are exceeding 30 seconds, we alert the practice that, “Right now, it’s taking a minute for a front office person to talk to a customer. Because of that, you’re going to see patients’ sentiment lowered, and that experience is going to be affected.”

This may lead to re-evaluating staffing, but more likely the office manager would help pick up calls during that time.

DSOPro: Can you share any statistics on how many calls we’re talking about in a busy office?

Peerlogic rates and runs millions of minutes a month through our platform. An average practice has about 3,000 minutes per month and converts about 23% of their new patient opportunities. The conversion rates can vary based on how the call was handled, the quality of the conversation held with the front office, and how long patients waited on hold. It could be you don’t take their insurance, or maybe they’re asking for pricing on a crown, or for many other reasons.

Our average customer converts closer to 50% of all their new patients and in the highest performing practices, we’re up in the 70s and 80s percentage of conversions.

DSOPro: Is that because of special training?

There is the training element and, especially in group practices, there is often a lot of attrition in the front office.

Most practices don’t have a good training model for properly handling calls. Our platform data can sort through and pinpoint what a properly handled call sounds like. The manager can say, “Okay, here’s how our best front office member handles somebody who has a pricing objection” and use it for training purposes. Once teams start getting that training and do some role-playing using best practices, you start to see uniformity amongst the group, and they become more successful.

We are developing a library of role-playing that clients will be able to use to train their teams.

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DSOPro: How often do practices look at the data your system is generating?

Daily. They’re diving in there every day. I think the most interactive element of our platform is the call performance feature. If you are responsible for the performance of your individual practice, you’ll want to know how many missed opportunities you had every day. Our system can also send alerts when an opportunity is missed. If a patient called and didn’t schedule, it alerts the office manager or the practitioner, whoever in the food chain needs to know, and advises them to call the patient back. We know that with a call back, they have a 30% to 50% better chance of converting patients. If an office manager calls back, they convert those about 30% of the time. If a practitioner calls back that missed opportunity, they convert about 50% of the time.

The scenario may go like this: “Hey, Ryan, I see that you called in asking about a crown. This is Dr. Smith. I just wanted to follow up with you personally and say, ‘To be honest, we can’t give accurate pricing over the phone. We take a more holistic approach to dentistry. We want to see what your optimal health looks like,’” and so on. When a patient receives a call back from a practitioner, that’s a powerful tool. It’s not that much additional work to add a few call backs, especially if you’re only missing two or three opportunities a day.

There’s a respect that we have for our practitioners. When they reach out to us directly, it’s a great feeling, because a connection is built immediately. It just works.

DSOPro: Are your customers primarily DSOs, or a combination of DSOs and private practices?

We’re about 60/40 right now—60% DSOs, 40% private, which includes solo and multilocation practices.

DSOPro: Tell us about your referral calculator feature.

Often, when customers call in, you don’t know what drove them to do that. Our machine learning can pick up from the call what the referral source was, if they say a family member referred them, they saw an ad, etc. When you know where you’re getting your patients from, it’s easier to determine what marketing efforts are working best and helps you calculate where to spend more of your time.

DSOPro: What do you see as the future of this type of technology?

Analytics are the future. As competition grows, people are becoming savvier and the competition for individual customers is going to get tighter. Every group practice that wants to be successful needs some type of metric adherence.

DSOs need to understand what is going on at the top of their funnel. If they’re not paying attention to that, they’re losing business to practices that are doing whatever they can to ensure every opportunity is converted.

One thing we’ve done that’s different in the dental space is build our own speech-to-text algorithm. We built it and trained it. I like to think of AI as a child. You’re teaching it things and every time you teach it something, it learns and remembers it forever. But you still have to initially provide all these data, all these learning events. We have to continually give machine learning information. The only world it knows is dentistry.

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We plan to we go out to cosmetic surgery next year so we’re going to have to introduce it to a whole new world. While it will know a little bit about how dentistry works and how that conversation works, there’s still a lot of words, challenges, sites, and conversations it’s never heard before that we’re going to need to train it on.

While the usefulness and importance of AI is increasing exponentially, there is the big misconception that AI is going to replace humans. That’s not at all why it was built. It was built to supercharge humans. Our machine learning, our artificial intelligence, should be used as a tool to help everyone’s lives, to do repetitive things that will free people up to focus on more important elements.

Using AI to identify the best time to call a dental insurance company is not replacing a human. No, we just gave the office manager or front desk back six hours to follow up on patients, do post-treatment reviews, and other things that really matter to the health of the practice. Waiting on hold for Delta Dental doesn’t help the health of the practice. Our entire platform was built around the needs of a dental office.


Executive team photo from left to right: Ana Tomboulian CPO (standing), Alex Maskovyak CTO (middle), Ryan Miller CEO (right), and Jaquelyn Tallarico COO (seated).


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About Ryan Miller


Ryan Miller is the Chief Executive Officer (CEO) and co-founder of Peerlogic. With 20+ years of technology and sales leadership, Ryan created Peerlogic with the vision of helping business owners while disrupting the dental industry through conversational AI. He’s an established founder, successfully building BlackStar Networks through the mid-2000s. Ryan enjoys spending time with his wife, Kristen, family, snow skiing, and traveling.


Peerlogic is the first conversational intelligence platform built for dental offices. The analytics platform provides detailed conversational insights between the practice and the patient.

Conversational analytics, also known as call analytics, is the process of analyzing data points captured from human speech. It helps to identify trends, predict revenue outcomes, and provide best practices. The result is actionable intelligence that improves the dental practice’s bottom line.

Conversational analytics can be used to adjust business strategy. Data provides the “why” behind what’s working, and what’s not. By understanding the “why,” practice owners are empowered with data-driven information that can be used to adjust business goals, objectives, and tactics.

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