Ep. 142 – SENTIMENT Analysis is a BIG DEAL! ➡️ GUEST: CALLRAIL CEO ==> Marc Ginsberg w/ Insights from 200K CALLRAIL Customers!

Foreign. Welcome to do this, not that, the podcast for marketers. You'll walk away from each episode with actionable tips you can test immediately.

You'll hear from the best minds in marketing who will share tactics, quick wins, and pitfalls to avoid. Also, dig into life, pop culture, and the chaos that is our everyday. I'm Jay Schwedelson. Let's do this, not that. We are here for do this, not that.

And this is the most unique guest I've ever had on this podcast. It's not even close. Okay, so we have Mark Ginsburg here. Now, Mark is the CEO of an amazing company called CallRail.

Now, you may know CallRail, you're like, is that the company that does phone call stuff? No. CallRail has over 200,000 businesses in this country that use them. And they're using AI and they're analyzing phone calls.

They're analyzing all the inbound opportunities that these 200,000 companies get to help them get more out of it, to drive more sales, more customers, more interactions. It's an amazing company. And. And Mark is the CEO of the company. All right, now, why did I say he's the most unique guest? Is because I have known Mark.

We went to college together, we hung out together. I have known Mark since back when. I mean, I didn't have a brain.

Maybe he had a brain I didn't know about, but now he definitely has a brain and he's leading this great organization, so it's exciting for me to have him here. Mark, welcome to do this. Not that well.

Thank you for having me. As my kids would say, facts.

We.

Go back quite a way. I knew Jay when his hair was dark.

Yeah, I'm trying to say. That's so wrong. No, we're gonna have to. We're definitely gonna leave. Yeah, right, exactly. And I wait a lot less.

So we'll have to leave some of our stories off to the side. But before we get into the chaos that is this podcast, Mark, give us every. Give everybody the kind of the. The quick origin story.

How did Mark become Mark?

Sure. Well, we both graduated. Me, I'm much older than you.

Yes.

Back in the mid. What's called the mid-90s, from the university of Florida and then did some graduate, got my MBA at UCLA and then fast forward about 25 years.

Most recently, I ran marketing for US small businesses for American Express back up in Jersey. And the company I had helped, I was CRO and helped start here in Atlanta called cardlytics.

When I was there, the CFO at Cardlytics a guy named Jim Morgan. He moved on to this company called CallRail, which has been around for about 14 years now.

And the founder and CEO at the time was ready to move on and start a new great business. And Jim. Jim brought my name into the mix. And here I am about three. I've been at CallRail for about three years now.

So I probably butchered exactly what Call Rail does and is. So I said it straight. What do you all do over there?

Yeah, so we, as you said, we work primarily with small and medium businesses and we help them connect all of the dollars they spend in marketing, whether that's digital, whether that's on AdWords, whether that's on a billboard, to their cost, to their lead, to every lead that comes in. Right. So they know exactly what the return on investment they're getting is. What.

Whether it's coming in through a phone call, through a form fill, through a text message. They get, through a chat, they get.

We tile that back, we can then analyze those conversations for them, pull out interesting insights, help them save time, and then go tell Google or Facebook, hey, send me more leads like this. Send me less leads like that.

That's awesome. To quote your podcast, that's a good idea. I'm glad you guys are doing that. Somebody should do that.

They came up with it.

Yeah.

Right.

So. So let's rewind a little bit.

We're going to be talking about AI stuff, and we're going to really get into stuff that I think that can save people a lot of time and get a lot of good out of it. But I feel like you've been on this AI journey your whole career, even though AI wasn't a thing.

Like, how did you wind up kind of leaving leading an organization that's so AI focused? Like, did you know that this was coming?

Right. So, yeah, I mean, when I was, you know, four or five years old, I thought, I want a career in AI. You know, it's funny, like, connecting with you.

I don't know if I actually even have a degree called Decision Information Sciences. And I was like, it was basically, it was new. Like, how do you use data and analytics to help run the business better?

And I actually learned to program in cobol. That's not super valuable anymore.

But we did things like conjoint analyses to try to figure out different levers that could drive the business and you know, and then moving on in my career, trying to think about regression analysis and marketing mix analysis, right.

I remember working at a company called Catalina Marketing and we had a, we were working with Campbell Soup and someone did an analysis for us that said every incremental can of soup was 40 cents. And then they changed providers of marketing mix analysis and they said every incremental can of soup is $72. And we lost that business. Right?

It was just like, it wasn't perfect, but it was like as good as, as the inputs that went into it, right. And it was like fairly rudimentary, especially as you think about what we're doing today.

And then like kind of fast forward to American Express, who I think is as good as anybody in leveraging machine learning and trying to predict the future using data, right? And give you one really quick example, petsmart came to us and said, hey, can you predict who's going to get a dog, a puppy?

Because that'd be really helpful for us. And so we did this big analysis. We analyzed 20,000 data points, spend data points at American Express, right?

So something the brain, the human brain couldn't do. And the number one, my wife, I wanted a dog. My wife did not want a dog.

The number one predictor of people who are going to get a dog was increased spend at summer camp. And we had just signed my son up for his first sleepaway camp. And then the next biggest predictor was increased spend at bike stores.

And I just got my younger son his first real bike. And then the third was increased spend in lawn services. And we had just moved into a new house with a yard.

And I called my wife and I said, the facts are in. We're getting a dog. Like, we are so ready. And she said, we're not getting a dog. We're not getting a dog.

And then about two months later, we were in Vermont, she saw a Bernese mountain dog, looked at me and said, I want one of those. He's now my favorite kid. Of course, no offense, if my kids are listening, but like, by the way.

What I got out of that is the number one indicator of if you're going to get a dog is if your significant other says, we're going to get a dog. Not you, any of your data.

Number one predictor.

Correct. Yeah, that is it.

You know, and now we find ourselves in AI, right? And like being able to take billions of data points, right. And use that to solve real world problems. Right.

I think we started out thinking about how to write poems about our friends, but the applications are becoming really meaningful and having a, I think a dramatic impact on business.

So let me ask you a question. Everybody's listening, like, okay, great. I know AI is a big deal and they're like, I go on ChatGPT, I try to write a prompt.

It tells me here's a recipe for how to make tuna fish differently than what I'm currently doing.

But how on a practical day to day basis without paying a boatload for some tool that I can't afford or whatever, how should people be doing things in their life, in their business life or whatever to leverage the power of AI to benefit themselves?

Yeah. Well, first of all, if you are going to write poems about your friends or your loved ones, that's certainly a great place to start. It gets you going.

But on the business side, you know, I think the first thing that we're seeing is like there are, there's real time savings happening.

I mean we work with a digital agency that they had 40 people that were just listening to phone calls from their clients and transcribing those calls and summarizing those calls. We do that in like seconds now, right?

So if you're listening to phone calls, if you're listening like going back and re listening to meetings, like you're completely wasting your time. Like you can like AI is amazing at summarizing what happens on a phone call, what happens in a meeting.

Pulling out sentiment, like you're trying to figure out unhappy customers versus happy customers.

Think about reputation management like how many times we send a, hey, can you fill out this Google review after, after someone just had a really not great conversation with someone on the phone. Right?

It happens or not a great experience like the ability to pull out, even to find coaching for some of your reps or some of the people talking on the phone, being able to like quickly understand the sentiment of a call or the positive side of that. Like try to get really good 5 star reviews in Google, right? If you know the people that are happiest, you're able to pull that out really quickly.

We have capabilities today where you can compose next steps from the call just to send to a customer. Here's what we agreed on, here's a summary of what we did and we're even starting to get into.

I'm seeing a lot, a lot of positive work around SEO and organic search is amazing.

There's no Mac with organic search and we're producing five times the amount of content today using AI, using it to help us figure out what are the words that we should be focused on what are outlines for content, how do we at least get the content started and the writing started? So we're seeing a lot of application there.

I think the next phase is really where you start to get into superhuman stuff, where it's beyond just automating tasks and saving time. Today we can take 100 hours of phone calls and pull out very specific insights from those conversations.

So we had a customer recently, they do driveways. They do new. They install driveways. And it turns out like one in every 25 calls, people are saying, do you fix driveways? Do you fix cracks?

And they just sort of didn't. Never thought about that. They said, no, we do new driveways and you do new driveways.

So when we came to them and said, hey, you know, there's a lot of people asking about fixing, you know, do you fix driveways? They launched a whole new group. They realized they had excess capacity in between these new driveways, and they created a whole new revenue stream.

Right. That they never could have pulled out. It's really like this superhuman.

They would have to listen to hundreds of hours of conversations to really pick that out.

Let me ask you a question, though. I'm curious about something. You talked about sentiment and using AI for that. And that's new to me. That's new to me. And what I'm curious about is.

So are you saying that people, marketers or business owners are having it applied to inbound phone calls or. And also maybe inbound emails or. Or. And also doing communication, and then they're able to categorize things and say, okay, this is.

Maybe this rep is not doing the job or this product line people aren't happy with or whatever it is. And, and then businesses are reacting to that sentiment, leveraging AI.

Yeah, we actually have. Correct. So I can do, I can sort by sentiment, right? And say, tell me, show me all the calls.

Almost like, you know, one star through five star and reviews. I can go listen or go read the summaries of all my negative sentiment calls or highly negative sentiment calls.

And we actually have it integrated into like a mailchimp and a constant contact where we actually can say, if sentiment is red, send them this email. If the sentiment is green, send them this email. Right?

And maybe the green one has a link to a Google review, whereas the red one has a link saying, hey, can we follow up and help you with whatever?

All right, now, now I'm super curious about something. So I, I, as a regular person, I call up and they go, this call may be Recorded by whatever. Okay.

And in my mind, I'm like, no one's ever really paying attention to that recording. I mean, like, where is that recording actually live?

And now you're saying, okay, AI really does it for us where it can summarize all of that and create these sentiment things. And I'm now concerned about the dude or dudette that is on the other side of the phone.

That's the rep. Are these reps all of a sudden being held much more accountable than they ever were? Or, like, is this a disaster for them? I'm, like, worried about them.

No, I. I think it actually is really helpful for them because, like, well, first of all, there's more accountability, right? So there's no more luck of the draw.

Like, I mean, I will tell you, even, like, less than a year ago, we have a QA team that listens to calls, and it was just luck of the draw. They just pick calls and.

Right.

Maybe, you know, whereas here, what if you get. What if your really bad call gets picked? Right. But they don't pick your good call.

Now it's like you're just living in this world of, they think I'm not doing a good job, but what about all these other really good things I did? And so I think this comes back to intent, Right? Like, if the goal of an organization is to help people get better and to find a balance. Right.

So, yeah, we can look at your tough call you had, or when a customer calls in and says, hey, I'm really frustrated. This rep wasn't good, we can then go look and say, wow, like, they have a pretty good track record.

Let's go dive in a little bit deeper and see what actually happened here and how we can help them. It's actually interesting because one of the really big capabilities that's come out also is call coaching. I'll tell you a really quick story.

I listened to a call recently where a customer called in.

A woman answered the phone and said she had a challenge with something she wanted to do with a phone number in Google, but there were regulatory reasons why they couldn't do it. And so the rep at CallRail did a great job, said, here's the reasons why, from a regulatory standpoint, you can't do it. I'm really sorry about this.

And. And that was the end of the call. And I listened to it and said, wow, that's a really great call.

And, you know, Google came back, or the call coaching came back and said, that was really good. You probably could have been a little More concise. Fine. No need to apologize. You didn't do anything wrong. It was a regulatory answer. Right.

So you talk about like, it never would have occurred to me to say that, but it's like it's gotten. You're talking about thousands, millions of heads. The, the, the collective intelligence of that, you know, so many people.

And to be able to pull that out and for AI to pull that out, and I think as a rep, it's really valuable. It's. It's not, oh, this person has it out for me. They're telling me this. I don't agree with it. It's, you know, a fairly and we could debate it.

Unbiased view of how they're doing.

Well, that is wild. And it is unbiased, which is good. There's like no filter. So. But on the email side, so our businesses.

Are you telling me that businesses are applying this kind of sentiment analysis to inbound emails that, that their team members are receiving and like, kind of almost doing, like, reading through the emails to see what the vibe is, is that happening?

If they're not doing it today, they'll all be doing it within the year. Right? I mean, it's. Because you're able to do, again, this is like the real practical right now, like qa.

And it's great for customers, too, to be able to dive in and go, how do I, you know, there's an issue here. How do I get on it quickly instead of, you know, I get emails probably once a month from some really unhappy customer. Right.

That usually the reason they're unhappy. And we, that, you know, we had a whole team at Amex that took those emails for the CEO there is.

Because they're not getting the answer they need quickly. It's not usually a product issue. It's a communications issue. And this way, it allows us to get to that quicker and, you know, and help everybody.

So. All right, before we get into the ridiculous portion of this podcast, I want to know.

You're very close to everything being developed in the world of AI. You're like so many. You're interacting with so many businesses. I want to know, Mark Ginsburg, what is the future look like?

Tell me what's going to be in, like, five years from now, ten years from now? What. Where is it all headed? It's your fault if you get it wrong.

It's a really good question. You know, I think this idea of, like, I don't, I don't, I'm not a believer in, like, you know, the AI is going to Run the world.

I think it's human assisted and I do think while we're seeing some really amazing things around automation and certainly being able to pull out superhuman tasks, I think it's going to free people up to do a lot more thinking. You know I talked about, I think we're sort of right in the middle of the time saving phase of AI.

I think we're at the early stages of this like superhuman insights of AI and remember, it's never going to be perfect. Neither are humans. Right. If a self driving car gets in an accident, people get in accidents too. Right.

I think we have to have a baseline but I think where it's going and there's a lot of talk about this is, you know, the automation of a lot of these tasks, right. Being able to say, oh this is negative sentiment. I need to go send an email to them that says X, Y and Z to make sure to get ahead of it. Right.

And how do you start to automate a lot of these insights that are coming out?

You know, But I'll say that like people are, we're finding like we're doing a lot of work with you know, voice, AI and the ability to like, you know, like we're going to get to a place where we don't have hold times, right. Because someone's going to avoid. It's going to sound very human, like it's already happening today.

Be able to answer questions that you need and then free people up to really spend their time thinking about innovation and where, where the business is headed.

Yeah, it's, it's interesting.

I think we're in this period of, I remember when Amazon first started a billion years ago, people like it won't work because no one will put their credit card in. Everyone's too scared about privacy and all this stuff. And that ship sailed obviously, who cares?

Now you put your credit card in everywhere and I almost feel like we're in that stage AI right now because like I'll get on meetings and people have their AI kind of thingamabob listening to take notes and then I've been in a bunch of meetings where be like somebody like well can you turn off the AI thing that's listening to us Because I don't feel comfortable with it kind of capturing all the information.

And I think that we're in this like beginning stage where everyone just has to get comfortable with sentiment analysis on emails and phone calls and, and all this stuff that's happening because it's going to be a huge benefit to all of us if. If we're not scared of it. So. So we're going to get there. So. All right, let's move into the ridiculous portion of this podcast.

You're stranded at a airport, right? Like, you could be on hold for an hour waiting for someone. Or like, you can have an AI, you know, engine help you. Right. Bot help you.

And you could yell at.

You're just gonna say, give me the bot, not the person.

Right? Give me the bot. Or give me. Actually, you might even prefer the bot over the person.

All right, let's get into the ridiculous portion of this podcast called since you didn't ask, we talk about nonsense. So I know way too much about Mark and about his previous existence or his current existence when he's not being a real deal executive here.

But he's had a lot of interesting jobs. Am I wrong in that one of your original jobs was like, didn't you sing show tunes at a restaurant?

Didn't you weren't in total embarrassment to the entire lineage of your family?

All right, so first of all, I didn't sing the show tunes. The restaurant was called the Burger Hop in Manalpa, New Jersey.

I was a short order cook, and whenever the hand jive played, I had to run out and, and, and dance with. With Dave Tave. And, well, the problem that, see, not all businesses are well thought out. Every time I ran out to dance, the burgers would. Would burn.

Yeah, I did have a radio show, which is amazing that you know that. Just because your brother might be one of the dumber people on the planet that I know, and he shares this information. I did have a radio show.

It was terrible. And people would call in and make requests, and they would also call in and say, can you tell this person I like them over the air?

I did anything I could to embarrass people, and that was amazing. What was another job that you had that was terrible?

I used to shovel snow, driveways whenever it would snow, and I went door to door and say, hey, it's snowing. You want me to fix your. You want me to shovel your driveway?

Well, I got smart and I said, why don't I go at the beginning of the year and Say, hey, give me 100 bucks every time it snows. I'll shovel your drive driveway for you. So kind of a, like a little bit of a sass model, you know. And.

Well, it turns out that year, if you go back and look, that was whatever the year was, they had record snowfall in Freehold, New Jersey. And about halfway through the summer, my dad made me go back and give everyone their money back because I physically couldn't remove any more snow.

So. Wow.

I mean, removed.

Yeah, did a lot, you know.

Well, you're actually probably lucky that happened because you may currently still be in the snow business. You like, it would be like Mark snowplow business years later. It's like that was what you were doing. That and your short order cook.

I mean, I can only imagine the sentiment analysis on your crappy burgers that you were.

Oh my God.

I mean, it was between.

Between the crappy burgers and the fact that people couldn't get their cards out because there was so much snow. I don't know. I'm sure my brother would had a much better idea for both. Obviously.

I doubt it. I doubt it seriously. Well, this has been amazing. Listen, I want to let everybody know a couple things.

First off, I'm actually going to be doing a webinar with the team at Call Rail coming up in a few weeks. So we're doing battle of the communications, email versus phone calls.

This thing's gonna be on July 23rd at 1pm we're gonna put the link in it in the show notes. It's free to attend. It's gonna be bananas. It's gonna be fun. You gotta check that out. Also you, you should follow Mark on LinkedIn.

You should check out CallRail. Mark, what else? How do they get involved with your world? Where can they find you and Call Rail and all of it.

Yeah. So CallRail.com on LinkedIn. Love to connect with folks.

I'm a big believer in networking and help out and obviously Jay, all jokes aside, this has been great to connect. We got to reconnect a couple years ago at Inbound, which was a lot of fun.

You know, it's not often you get to hear people singing, living on a prayer. I said that voice sounds familiar. That might be Jay.

So it's been great to reconnect and I think just shows, you know, the power of like, you know, building strong relationships over time.

Absolutely. All right, Appreciate you being here, man. Everyone check out Call Rail, connect with Mark and we'll see you on the next one. You did it.

You made it to the end. Nice, but the party's not over.

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