The End of SEO?

In this episode of "Full Tech Ahead," Amanda Razani interviews Ryan Johnson, CPO of CallRail, about how Artificial Intelligence can benefit small and medium-sized businesses (SMBs). Johnson explains CallRail's evolution into a conversation intelligence platform and advises business owners to use AI to solve long-standing "legacy problems"—such as managing after-hours calls or handling peak call volumes—rather than inventing new problems to solve. 

He emphasizes the importance of starting small, setting realistic expectations, and securing leadership buy-in to avoid the high failure rate of AI projects. Finally, the discussion touches on the future of AI, including the rise of agentic AI and its potential impact on search engines and SEO.

Key Quotes
"Where can AI solve the gaps that you've probably had for many, many years?"
"The most important thing about AI is it's not this like light switch that this happens. You actually have to invest time into it from a lot of different angles."
"Start small, start somewhere, don't be afraid of it and, and just learn."
Takeaways

Target Legacy Problems: AI is highly effective at filling gaps in daily operations, such as handling peak-hour calls, answering queries after traditional business hours, and conducting initial lead qualification.
Start Small and Be Realistic: Avoid overwhelming implementations. Begin with a narrow, focused use case to get comfortable. Set realistic expectations, as AI is not magic and often requires fine-tuning to achieve high accuracy.

Leadership Buy-in is Crucial: To avoid the common pitfall of AI project failures, businesses must define clear, measurable goals and ensure full support from the executive team and business owners before implementation.

The Future is Agentic AI: The next major evolution will involve AI agents communicating with one another to execute complex tasks, which will likely redefine consumer search experiences and the future of SEO.

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Transcript

SPEAKER_00 0:19

Hello, and welcome to Full Tech Ahead. I am Amanda Razzani, and with me today I have Ryan Johnson. He's the CPO at CallRail. How are you doing?

SPEAKER_01 0:29

I'm doing great. Thanks for having me.

SPEAKER_00 0:31

Happy to have you on the show. Can you share with our audience a little bit about CallRail and what services you provide?

SPEAKER_01 0:38

Sure. So CallRail is almost 15 years old. It started originally as uh a call tracking company. Um, and what that means is really focus on tracking online to offline conversions for small medium businesses that rely on inbound phone calls as their primary lead source. Um so, in simple terms, you know, we all utilize Google and now maybe OpenAI and some of these other searches. Uh, we look for those businesses. Um, and as soon as uh we find them, a lot of times we place those calls, and that's uh what CallRail uh uh thankfully attributes to all that marketing spend that happens uh digitally, you know, whether that's um on Google or or social or or beyond. And so that's how the company started. Kind of fast forward to today, we've taken that other steps further from a lead engagement platform to focus on what's actually happening during the conversation. So conversation intelligence. So being able to analyze um utilizing AI. How did the conversation go? Simple things like sentiment, summarizing it, what are the next best steps, uh, helping the company um with like auto generation of text message and email follow-up. Uh, and then most recently, we just launched our voice AI uh product to help our customers make sure that they never miss a lead. So if it's after hours or overflow um or lead qualification, we can lean on um AI to basically make sure that revenue gets captured and never gets lost.

SPEAKER_00 2:12

Wonderful. Well, that's a good segue into our topic of the day, which is how AI can benefit small businesses and why it should be top of mind this year. So can you share a little bit about uh you work with different business leaders? Where can AI most help small businesses?

SPEAKER_01 2:31

That's a great question. I think, first off, it can be very overwhelming, right? Um, for small and medium businesses. Um, they have a lot going on. Um, a lot of the the owners wear multiple hats. They're the marketer, they're the owner, they're the person actually doing the work. So I think really the biggest unlock is how do you use AI to fill those gaps? Uh, we know hiring people is really tough to get them uh trained up and have all the context. Um and so, you know, what I say from a more generalized standpoint is where can AI solve the gaps that you've probably had for many, many years? I think a lot of times companies focus AI and solving new problems. Guess what? There's a lot of like legacy problems that small and medium businesses have, like having enough people to answer the phone during a peak, you know, uh part of the season, or at six o'clock at night, um, you know, uh the ability to have something interact with customers that may not be on traditional hours that your mis your business may be on, or just being able to handle things like uh triage and and and lead qualification up front. We know a lot of these businesses can get, you know, spam calls and people selling things to them. And so if you think of time as that commodity that's really important, I think AI can help, you know, multiple AIs, whether it's front of the house with like conversational AI helping or even like kind of post um, you know, say analytics is, you know, of all the things that are happening in your business, how can AI do things in a much quicker fashion so you can get to the data that you need uh versus spending all the time uh you know manually doing this stuff? I think it's been a really big unlock for a lot of these businesses.

SPEAKER_00 4:12

So I think preparation is really important before any sort of AI implementation. So what's your advice as far as what are the first steps when it comes to choosing what's the most important uh problems that they want solved and how to find the right solution and then the implementation phase? Yeah.

SPEAKER_01 4:32

So I always say start small, right? I think right now a lot of times um if you you know read on a daily basis all the new innovation, you can kind of go to the nth degree of like, I can solve this, I can solve this, I can do that. Um, where it's just like pick pick a very narrow thing so that you can get comfortable with that um and learn from it. Because the the most important thing about AI is it's not this like light switch that this happens. You actually have to invest time into it from a lot of different angles. Um, certainly businesses that help reduce that time. That's what CallRail kind of focuses on. We've been like a self-service business since we started because again, we got to make it easier for small, medium businesses. I think when looking to partner with companies is like, how can they get that time to value down as quickly as possible? Um, and some of these things can be really complex and overwhelming, you know, just setting up an agent, like where do I start and how do I make sure it does the right things and those types of things. So my advice is start small and also know that you have to invest some time to make it uh a good representation of your company or do what it needs to do. And I think the last thing I would tell uh businesses is um figure out what your expectation bar is. I think a lot of people read in the market, hey, AI is you know perfect and and it can do all these things magically, and it can, but relate that back to human if you're kind of comparing it to human performance, even on basic things like transcription or summaries, you know, don't don't go out of the gate and say AI is gonna be 99%, you know, accurate and precise. Um, you may have to fine-tune it to get there. And I think over time it will get better as these new models come out. Um, but I think giving yourself a realistic expectation is really important too, because I think a lot of folks just shoot way beyond that. Uh and then they get frustrated and then they say, well, I'm not gonna use it. Um and so I think it's it's really just kind of defining those success metrics before you dive into um implementing any new technology or tools.

SPEAKER_00 6:32

Yeah, I was going to ask, um, how big a problem is AI acceptance and adoption still within businesses?

SPEAKER_01 6:40

I think it varies, and you'd be surprised. And it surprises me all the time if you look at data, especially for um the smaller businesses and their ability to adopt it. It varies by vertical and industry. And I think some of them that you would assume um would be hesitant are the ones that are diving, you know, feet first. And you kind of see it all over the place right now. I think the stats, though, every single month it's like SMBs or businesses, you know, it's like, was that 30 and 40 and 50% utilize AI in some way? You know, I think behind the curtain, you don't really know what that means. Are they just playing with you know, Chat GPT or perplexity or anthropic, or are they actually truly implementing new technology into their process? You know, on the flip side, you see, um, especially at the enterprise level, like all the headlines, 90% of AI projects fail, right? Like these big um, you know, kind of attention-grabbing headlines. Uh, so I think you see it kind of all over the place right now. It's so new, it's moving so fast. You know, again, I think for any company, it's kind of focusing on realistic expectations, onboarding, investing into that to make sure that it's successful. But it's all over the place. And I've tried to do my own research to say, well, what if you went into rural America and this city? Like, there's no way like your customers would interact with AI, and then someone disproves me, you know, the very next day, where it's like, oh, Domino's release their, you know, AI order taker and it performs the best in the middle of Iowa. And you're like, Wait, what? That makes like no sense whatsoever. So I think that makes it fun and exciting, certainly where I sit in my role, uh, but also very challenging because we just don't have enough data yet and and it's just moving at at lightning speed.

SPEAKER_00 8:25

So, in regard to that, you know, those headlines, 90% of AI projects fail. Um, so how do we ensure that that's not correct and and doesn't play out in that way? What advice do you have once it comes to that AI implementation stage to ensure that they have success?

SPEAKER_01 8:42

Yeah, I I think setting like goal expectation setting is really big out of the gate. I think that's part of the problem. I think a lot of companies and people just react like, okay, I got to implement AI. What's truly the goal that you're going after? Picking the wrong goal, like the the wrong ROI is a big piece of that, right? You know, people go into this and say, well, I want to reduce, you know, increase productivity by 30%, or I want to do these things. Sometimes it's really hard to measure. Um, and sometimes they blow out the scope of all the different things they're trying to measure and they implement too many things at once. I also think the uh the piece of adoption is I hear a lot of companies, it's just like if you don't have buy-in from leadership team, executive leadership team, other individuals, and and that even goes down to the the smallest companies. Like if you're trying to implement AI and the business owner doesn't want to do it, like it's probably gonna fail, right? So I I think you know, picking those goals um and being reasonable about them, also while you know, making sure you have buy-in to to what those goals are. And you know, I don't think it's those ideas are not novel. I think it's for like any technology project, AI or new process or any of that type of stuff, you have to do it. I think again, people get too enamored with with AI and they think it just is the magic button and it solves it. And um, just like any other thing in the past, um, some of those things don't go away because of its AI. It's actually more important to track the progress and what your actual goals are before you ever decide to implement it um uh in in your business.

SPEAKER_00 10:17

So we see AI advancing quite rapidly. What do you envision is the future? Give some use cases that you imagine might be popular in the next year or so.

SPEAKER_01 10:29

Yeah, I think 2025 was certainly, I would say, the you know, get prototype and show what it can do year. Um, and and even the smallest companies can do it really quick, and that makes it exciting and it gives uh buyers lots of optionality out there. I think over the next couple of years, especially when it comes to like agentic AI and and and AI agents, um, how they communicate with each other efficiently, I think is a is going to be a big deal. I think a lot of the initial implementations were this agent has this context that can do this. Uh, but now with things like MCP and and you know just other contexts and knowledge sharing, it becomes really powerful, right? So another agent can talk to another agent over here and and that agent specialized. So the you know, the architecture and the setup isn't as burdensome. So I think the interconnectivity of how these things interact will be uh really important on the business level, but also on the consumer level. If you think of, you know, comment um, you know, with perplexity coming out with their browser, and you kind of have these agents on the side that can help you as you browse, I think my hope is that they really start to pan out and help out, right? As us as consumers, it really goes to that next level where I hear anecdotes of people that've been able to do amazing things like plan their vacation and and do all this type of stuff. But when you get into it, it can be really difficult. Like if you didn't experience it and you're like, how the heck did these people over here do this whole thing when I'm doing this and it's not working out in the same way? It didn't find the best prices and it didn't give me the the exact uh information. So I I think the the sense of like a consumer co-pilot in your browser will will change search. Um, I think that goes to a lot of the like AEO and GEO, you know, the next um gen of of SEO. I think that will continue to take off because none of those uh LLM search has done anything paid yet. Uh but we we think it's coming. We we we thought we saw OpenAI do a little test and they pulled it back. We don't really know for sure. But I I think those are the things in the next year or two, you know, search will be redefined and hopefully be better for all of us as consumers connecting with businesses. And I think overall, I think the models will just continue to dramatically get better, which I hope because a lot of the stuff that happens today, it's a little bit of a black box. A lot of this technology is all built on three or four players. And when it you know hallucinates or has a small issue, every time they they update the model, it seems like those get less and less um prevalent. And so I also hope that just in general, those kind of why did this agent decide to say this out of the blue um without any prompting, like I hope those things will continue to go away where you know it will just work way better than than we even thought.

SPEAKER_00 13:19

It will be interesting to see what unfolds. It's really fun to watch.

SPEAKER_01 13:23

Yeah, absolutely. I think the the other one, you know, that I go back and forth on, but any of the AI robot stuff, um, you know, this this whole concept of you know it helping out either in the workforce or in your house, um, it's kind of interesting because I feel that's the one that's gonna take a little bit longer, you know, just the we just don't have the data sets of like human touch to be able to train these things um in different different types of things. Um it's also exciting one for for me as well to say, okay, where does this go? Which is completely outside of the you know the box that you and I are in right now, um uh on our computers. So um I think that will be another one. How fast we go though, that's that's like the big question mark for me.

SPEAKER_00 14:08

Yeah, I'd love to be uh selected to be a physical trainer of uh a robot in my house and try to train it to do all the different chores, wash shits.

SPEAKER_01 14:21

Yeah, exactly. And then you know, you have like iRobot that just went bankrupt with the Roomba, and you're like, how does that happen now? I was waiting for like the next Roomba that would, you know, fly around the house and be able to mop and uh vacuum and do everything, but I guess we'll have to wait for that.

SPEAKER_00 14:38

All right. Well, if there was one key takeaway you could leave our audience with today, what would that be?

SPEAKER_01 14:43

For me, the biggest thing is I think just start small, start somewhere. Um, don't be afraid of it and uh and just learn. I think a lot of people um don't want to miss the boat and and you know, the train hasn't left the station, the boat hasn't left, but it's coming. And and so, you know, in order for you to be a part of the change that will happen in many different ways, um, just figuring out little ways to um continue to understand and utilize it um in your business, in your personal life, I think that's the biggest thing to me. It's just little bits all the time. Um, and then over time you'll get you'll get comfortable and and be a pro as as we all go through this together.

SPEAKER_00 15:26

Yeah. All right. Well, thank you so much for coming on the show and sharing your insights with us today.

SPEAKER_01 15:31

Yeah, thanks for having me.

SPEAKER_00 15:32

And thank you to our audience. Share what was the most interesting in the comments. Where do you envision AI going in the coming year? All right, and until next week, have a great day.