How AI Is Changing the Role of Online Reviews in Orthodontic Marketing

Alison Werner (00:06)
Hello and welcome to the orthodontic products podcast. I’m your host, Alison Werner. Online reviews have always played a role in how patients choose an orthodontic practice, but the rise of AI is changing what those reviews actually do behind the scenes. Today, reviews don’t just influence perception. They’re increasingly shaping which practices show up and how they’re described across search and AI powered platforms. Joining me to talk about this shift is Jessie Pressman, head of consulting at People and Practice and author of the article, The New Influence of Patient Reviews in the Age of AI Search, which you can now find on our website. Jessie works closely with orthodontic practices on growth strategy, and she’s been on the front lines of how reputation management is evolving in an AI-driven search environment. Here’s our conversation.

Alison Werner (00:52)
Jessie, thank you so much for joining me today. I really appreciate it.

Jessie Pressman (00:56)
You’re welcome. I’m so glad to be here.

Alison Werner (00:58)
So just to get started, can you tell us a little bit about your role at People in Practice?

Jessie Pressman (01:03)
Absolutely. So I am the head of consulting at People and Practice. As I hope many of your viewers know, we are a marketing firm dedicated to orthodontists and dentists, as well as a number of other health care industries. And I’ve been with the company for about 11 years. ⁓ My focus is on growth consulting, managing our team, and helping our clients succeed in their goals.

Alison Werner (01:28)
Okay, well great. So you wrote this article for us. And so something I really liked about it is how you frame reviews as being about more than just marketing or star ratings now. It feels like they’ve taken on a whole new role because of AI and the way people are actually finding practices. So to kick things off, why do you see reputation management as one of the most powerful growth levers that doesn’t require more ad spend?

Jessie Pressman (01:54)
Yeah, absolutely. So I’m glad you picked that out of the article because I think it’s a really important piece. We’re coming out of an age where digital advertising was one of the most key drivers of traffic to a business. And I don’t think that’s changing, but I do think that the weight of reviews has spiked along with AI-generated search results. So we know ⁓ that reviews impact on conversion happens at every stage of the funnel. Strong reviews increase click-through rates from search results.

They improve conversion from inquiry to consultation. They reinforce trust before the first appointment. And now they’re influencing the AI visibility organically. unlike paid ads, reviews compound over time, similarly to like an SEO strategy. ⁓ Every positive experience that someone writes about your practice strengthens your digital footprint without increasing that cost per lead. So I think…

very strongly that it’s one of the few growth levers that improves both marketing efficiency and your brand credibility simultaneously.

Alison Werner (02:57)
Okay, so you say that reviews no longer just influence decisions. They influence visibility itself. What do you mean by that? And how is that different from how reviews worked like five years ago?

Jessie Pressman (03:09)
That’s a great question. ⁓ In the past, reviews were something that a prospective patient had to seek out. Yes, they were front and center on platforms like Google and, once upon a time, Facebook. But it took ⁓ active engagement and curiosity from a human to be surfaced as part of the data points for that decision. But now with AI summaries, the algorithms are doing that work and elevating the review narrative front and center in search results. So you said five years ago. ⁓ Five years ago.

Reviews absolutely influenced perception. Patients, though, like I said, had to actively go and click onto your profile, read those reviews, interpret them for themselves. And today, the AI-generated summaries are often displayed directly in those search results before the patient even clicks. So you run a search in Google, and Gemini is giving you that display up at the top that gives a general understanding of the practice. And that AI-driven summary is

Alison Werner (03:53)
Yeah.

Jessie Pressman (04:06)
analyzing patterns in review language, in sentiment, in consistency, and they’re generating a narrative about your practice. So that means that reviews are no longer just social proof. They’re an input for the AI systems to determine how visible and how credible a practice appears. So I think it’s really important to make sure that your review profile is consistently mentioning things that are really happening at your practice. So

Alison Werner (04:23)
Yeah.

Jessie Pressman (04:31)
Getting people to talk about your friendliness, your efficiency, your Invisalign expertise, or your flexible financing. Those are all becoming pieces that the AI summary is presenting. essentially, the narrative is now influenced not just by the star ratings, which might have appeared in a Google Map pack, ⁓ but it’s really pulling out a summary and a digest of what your actual patients are saying for you. And it’s creating that storyline for you.

Alison Werner (04:51)
Mm-hmm.

Jessie Pressman (05:00)
as opposed to people having to dig it out themselves.

Alison Werner (05:03)
OK, so you kind of talked a little bit there, but you emphasized that language matters, especially phrases like invisalign, flexible financing, shorter treatment times. Why is that natural language in review so important to ⁓ AI results?

Jessie Pressman (05:19)
Yeah, so we keep hearing this as we talk in marketing about AI content. And AI presumably knows what’s written by AI and knows what’s written by real people. And everything that we are hearing in the past few months is that AI wants real human content. And so that real human content, again, is being incorporated into those summaries.

Alison Werner (05:39)
Mm.

Jessie Pressman (05:44)
and the results, but it’s a synthesis of how your patients are talking about your practice and their experience. So the AI models are analyzing the language itself. So they’re also looking for recurring themes across multiple reviews. So when you get a patient to say something like, Invisalign treatment has been really fast, ⁓ you get multiple patients to say something like that. The AI is going to pick up on that and pull it out.

Alison Werner (05:48)
Mm-hmm.

Mm-hmm.

Jessie Pressman (06:13)
⁓ The thing that’s really key about this, though, is the authenticity. The language has to reflect real patient experience and not scripted prompts. I’ve heard of these systems out there that are giving a suggested phrase to people, and then people are just copying that AI-generated prompt, and you’re not getting that authenticity of what’s really happening. ⁓ And so the reviews are both important from a front-facing perspective and also the algorithm-facing perspective. ⁓

Alison Werner (06:20)
Hmm.

Yeah.

Right.

Mm-hmm. Mm-hmm.

Jessie Pressman (06:43)
And the reality is it’s the same feedback that’s building trust with families that also trains the II systems on what that practice represents. So, you know, I would say there’s no way to game the system, asking for real credible feedback and asking your patients to be specific is really going to help.

Alison Werner (06:49)
Mmm.

Okay, so it changes that conversation with the patient to get that review.

Jessie Pressman (07:06)
Yeah, just a little bit. I think that

often we coach our clients to say, could you give us some feedback? Could you leave us a review online? It sounds like you had a great experience, right? It’s just tweaking that message just a little bit. It sounds like you had a great Invisalign experience. Would you talk about it specifically?

Alison Werner (07:16)
Mm-hmm.

Yeah.

Yeah, yeah, I kind of wonder though. So I’ve heard a lot of people in my life are using chat GPT to do the simplest thing. I have almost kind of wonder like, will patients be like, I need to write this review. Let me just plug some things into chat GPT and have it spit something out.

Jessie Pressman (07:32)
I’m gonna hit you.

Yeah, I mean, I guess that’s always a worry. My hope is that for something so

short, ⁓ they wouldn’t necessarily feel the need to do that. Yeah, no, I definitely get that impulse. ⁓ I think the way to combat it is just being like, your thoughts to me were today were so genuine. Would you mind just jotting them down? It doesn’t have to be fancy, right? We think that is important, right? It doesn’t have to be like that. Yeah.

Alison Werner (07:47)
I know, I know.

Yeah, yeah, yeah, maybe that’s yeah, take the pressure off.

Yeah, absolutely. Okay, so a lot of orthotontists panic over negative reviews. So in your experience, does one scathing review really matter that much in the age of AI at this point? Okay.

Jessie Pressman (08:20)
No. ⁓

So emphatic, no. ⁓ Look, the reality is that if you have multiple scathing reviews, it’s going to be a problem. But one random review rarely defines a practice. ⁓ AI systems in this regard actually are working similarly to humans, right? In the past, if you had a bad review, it’s part of the puzzle.

Alison Werner (08:28)
Mm-hmm. Mm-hmm.

Jessie Pressman (08:47)
You’ve got one negative review and you’ve got 50 positive reviews. A human is going to look at that and go, okay, somebody had a bad day. Fine. Or let’s be honest, when people are writing a negative review and like, look, I’ve been there. I’ve had bad experiences. I want to tell everybody exactly what happened. I want to give them all the details. And because of that, that review ends up being so much longer. And so you could say…

Alison Werner (09:09)
Yeah.

Thank you.

Jessie Pressman (09:15)
Oh my gosh, the algorithm is going to pick up this longer review because there’s so much content. But the reality is if it’s only happening once, Google realizes that in the same way that a person who would look at that and go, oh, I’m not going to read that. That person, I read that. So I think that’s really important. The other thing is that because AI is looking for consistency and not isolated incidents, what matters more is about how the response is handled. So we often tell clients,

Alison Werner (09:27)
Mm-hmm. Yeah, yeah. ⁓

Hmm.

Jessie Pressman (09:42)
Please do your best to try and take it offline. Obviously, you know this person. They’re a patient at your practice. Give them a phone call. Don’t reply to a negative review publicly. It just opens up the possibility for all sorts of different reviews. The algorithm is going to think that it’s more important because you responded to it. It might pick up on what you were saying. It might lead to a public back and forth that could get met. You don’t want it. ⁓

Our advice is always to take it offline, have a conversation, see what you can do. The goal of the conversation should not be to remove it. The goal should be to assuage the problem, right? Like, address it. What’s going on? I saw this negative review, and I hate to think that you had this type of experience. Can you talk to me a little more? Can we see if we can resolve it? I think I mentioned in the article that we had a client out of Alexandria where they got a negative review. It happens.

Alison Werner (10:17)
Mm-hmm.

Mm-hmm. Yeah.

Bye

Jessie Pressman (10:37)
⁓ And they’re an outstanding practice, but someone had a bad time. And the team responded quickly. They picked up the phone, they took the conversation offline, they dealt with the issue. ⁓ It prevented the negative sentiment from lingering publicly and it showed, ⁓ and actually at the end, the person removed the review, right? They were like, ⁓ my problem was taken care of. I was really listened to, which I think is really what people want anyway when they’re leaving that negative review.

Alison Werner (10:56)
Mm. OK.

Yeah.

Jessie Pressman (11:05)
So yeah, I think that one negative review is not going to kill you in the age of AI in the same way that it wouldn’t kill you before it.

Alison Werner (11:12)
Yeah.

Okay. What about middling reviews? Like say the threes, you know, on a scale of one down to five. What if you’re getting threes?

Jessie Pressman (11:17)
Mm-hmm.

That was such a good question. I have to

be honest and say, well, I have seen very few threes. In my experience, and again, I’ve been doing this with people and practice for over a decade, specifically in the reputation front and looking at reviews, 99 % of reviews are ones and fives. There, I would say that other 1 % are fours. And the fours are either.

Alison Werner (11:30)
Okay. ⁓

Mm-hmm.

Okay.

Jessie Pressman (11:52)
This practice is great, but, or they are mistaken, stars It is so, so rare for, and look, I’m sure they’re out there that there’s twos and threes in this, but like, it’s really rare. Most people come to review places because they want to leave a glowing review or they want to leave a scathing review. It’s rare that people take the initiative for middling.

Alison Werner (11:58)
Hmm.

Okay.

Yeah, OK, OK, good to know. OK, so where, OK, for a practice that’s feeling overwhelmed by this idea of having to constantly monitor reviews, where is the technology at this point to help them? Is there any technology at this point to help them just kind of manage this process? you know, it sounds like you’re saying there needs to be consistency in how the practice communicates with patients and their reviews. So what what can they do?

to create a system or is there technology? What’s the process here?

Jessie Pressman (12:53)
Absolutely. So I do believe that automation is key to this. Asking, like I said earlier, like asking someone who just said something to you to leave a review. Great, wonderful. We call those like a sure thing. But you can’t catch everybody. And you’re seeing so many patients every day. And every experience they have at your practice is different. So putting automation in is really helpful, right? It takes the burden off your team. It takes the burden off you. People are used to getting asked for reviews these days.

Alison Werner (13:05)
Mm-hmm.

Mm-hmm.

Jessie Pressman (13:23)
⁓ And ⁓ not to sound self-serving, but we, at People and Practice, have a tool, it’s a piece of software, it’s software as a service, that we’ve developed called PatientCue that helps with this process. We integrate into patient ⁓ communication systems so that at the post-appointment moment, they get a link asking for feedback ⁓ and we…

we help work that towards a review so that practices are gaining those. And I have practices come to me and go, we have to ask every single time. And I said, well, the work isn’t on you. It’s on the technology. And they’re like, but aren’t people going to be annoyed by getting asked every single time? like, again, in the 10 years I’ve been here, I think I’ve had two people complain. And I’ve gone over hundreds of clients and probably hundreds of thousands of reviews at this point. And I think I’ve had maybe two people.

Alison Werner (13:51)
Okay.

Yeah.

Jessie Pressman (14:19)
complain and we were just like, ⁓ we’re sorry, we’ll unsubscribe you. No problem.

Alison Werner (14:22)
Yeah,

yeah, yeah, yeah. Well, for an industry that’s so focused on having systems for everything, seems like managing your reputation would need to have some kind of system or automation, especially since we’re talking about AI and how AI is automating things. There’s automation to that too. There’s automation to both ends.

Jessie Pressman (14:35)
Yeah.

Yes, absolutely. Definitely. Yeah, and I think

it’s important also to have a tool in place that notifies you of what’s going on. When you get something that’s a negative sentiment, being able to address it immediately is key. you don’t want to just check your reviews once a week or rely on Google to maybe send you a message if you’ve got something positive or negative. You want to have a technology that is doing that, and our Patient Cue System does that as well.

Alison Werner (14:49)
Mm.

That’s a good point.

Right.

Okay, okay. So if AI search continues to evolve, what does future proofing reputation really look like over the next five years?

Jessie Pressman (15:18)
Yeah, I think that it is consistent review cadence, ⁓ not bursts, steady momentum. And to be honest, that’s not very different from what I’ve said in the past either about reviews. I think they continue to be a really important touchstone for new patients trying to find their practice. ⁓ In terms of future proofing, think diverse review volume across platforms.

Alison Werner (15:25)
Mm-hmm. Mm-hmm.

Okay.

Jessie Pressman (15:44)
Google is still king, but there are definitely other platforms out there and trying to spread the wealth a little bit is important. ⁓ But we are still focusing heavily on Google because that’s where most people are searching. ⁓ I think that helping the algorithm understand that you care about your reviews is also important, as well as just humans seeing that you care about them. ⁓ And the way to show that you care is responding to them. So thoughtful responses to both those positive.

Alison Werner (15:55)
Okay.

Mm-hmm.

Yeah.

Jessie Pressman (16:11)
And if you need to, negative reviews. A negative review response is often just, please give us a call. We want to talk to you more about this. ⁓ And then aligning your patient experience in the brand narrative that you want to be reflected online. So it’s asking for those reviews from those people who are saying those great things. ⁓ You talked about automation, adding automation in so that you are ensuring consistency without having to align our staff. ⁓ And monitoring everything. Again, making sure that things are

Alison Werner (16:18)
Yeah. Yeah.

Jessie Pressman (16:40)
progressing in the way that you want them to, whether it’s from a cadence perspective, whether it’s from a sentiment perspective. If you’re adding, I don’t know, who knows what new technology is out there coming up. But let’s say you recently added new remote monitoring technology to your practice and you want people to talk about it because it feels really high tech and that’s what you want to be known as. Again, asking for those things in there is important. But I would say just overall, future-proofing means that

Alison Werner (16:55)
Mm-hmm.

Jessie Pressman (17:07)
you want to make your reputation strategy operational and not occasional. So pairing it also with a strong SEO AIO strategy can be important. And that’s making sure that your NAP information is clear across the board. That’s name, address, phone number. It’s making sure that you have a strategy that is focused on all of the different touch points that AI Search is generating from. ⁓ And I do.

Alison Werner (17:23)
Right. Yeah.

Jessie Pressman (17:35)
As we said at the beginning, think that reviews are one of the strongest levers there, but I think a holistic approach, as we do with everything at People in Practice from a marketing perspective, is important. ⁓ And having a strong SEO, AIO approach would be helpful there as well for future proofing.

Alison Werner (17:49)
Yeah, well, that was going to be my last question, but it brought something to mind. How often should practices be just checking what comes up in their AI summary, like Googling themselves? Is there value in that?

Jessie Pressman (18:00)
oooh

That’s great question and is the hardest question because I hate answering it. Well, I hate answering it because everybody’s disappointed, right? Here’s the thing. Googling yourself has always been not a great strategy. And I don’t think that has changed much with AI. And the reason behind that is because Google and any AI tool that you are using is constantly learning about you.

Alison Werner (18:07)
No.

Okay.

Mm-hmm.

See that’s the reason I was asking that.

Jessie Pressman (18:33)
Mm-hmm.

So they’re serving you the results that they think you want to see. And if you are an orthodontist, they’re either going to serve you your practice because they know you own it, or they’re not going to serve you your practice because they’re like, clearly this person wants to learn about something else. Maybe it’s about their competitor, right? They’re making assumptions about your search. There are tools out there that can give a less biased approach. But it also depends on

Alison Werner (18:38)
Hmm.

Right.

Yeah.

Jessie Pressman (19:01)
where you are, literally sitting when you do a search. Yeah, so there’s just so many factors that Googling yourself or, you know, Chat GPT-ing yourself, I don’t know, has that become a Google app? It’s just not a clear picture of where you’re actually showing up. And a more holistic SEO AIO type program will be able to show you.

Alison Werner (19:04)
Well, that’s that’s the other thing I was thinking about.

Right. ⁓

Mm-hmm.

Jessie Pressman (19:28)
how you’re showing up in different types of searches for different types of keywords in different places and help focus on the places that you are actually hoping to draw traffic from.

Alison Werner (19:39)
Okay, all right, well, thank you so much for ⁓ explaining all this. ⁓ Yeah, if anybody’s interested in learning more or working with you, where can they reach out to you?

Jessie Pressman (19:41)
Yeah, of course. Thank you so much for having me.

Absolutely, you can always find me at jessie at PPL practice com and it’s jessie with an ie

Alison Werner (19:57)
Great, well, Jessie, thank you so much and be sure to read Jessie’s article on our website. Thanks again.

Jessie Pressman (20:03)
Thanks so much for having me.