The Future of Operations: Harnessing AI for Predictive Insights

Brandi Starr [00:00:35]:
Hello, hello, hello, and welcome to another episode of Revenue Rehab. I am your host, Brandy Star, and we have another amazing episode for you today. I am joined by Tracey Fudge. Tracey is the driving force behind AI by Thrive, a consultancy that is revolutionizing how marketing, marketing operations and data analytics teams leverage artificial intelligence to achieve revenue breakthroughs. Tracey's career has been focused on bridging the gap between fragmented data manual workflows and disconnected systems that are killing revenue growth. And at AI by Thrive, she's putting, putting that expertise into action every day. Tracey, welcome to Revenue Rehab. Your session begins now.

Tracey Fudge [00:01:32]:
All right, thank you so much for having me.

Brandi Starr [00:01:36]:
I am excited to talk to you. And before we dive into our topic today, I like to break the ice with a little WOOSA moments that I call buzzword banishment. So tell me, what industry buzzword would you like to get rid of? Forever.

Tracey Fudge [00:01:56]:
Collaborate.

Brandi Starr [00:01:58]:
Ah, tell me why you don't like that one.

Tracey Fudge [00:02:03]:
It's just so overused.

Brandi Starr [00:02:06]:
It definitely is. But man, I love a good collaboration.

Tracey Fudge [00:02:11]:
I do too. I do too.

Brandi Starr [00:02:16]:
Yeah, I can definitely say I am one that overuses collaborates. So at least for our discussion today, we will put that in the box, throw away the key, and we will not talk about collaborating. So now that we've gotten that off our chest, tell me what brings you to Revenue Rehab today?

Tracey Fudge [00:02:40]:
Well, I really wanted to come in and talk about. Everyone's talking about AI and it's almost like everyone's having an existential moment with it and a lot of leaders are sort of freaking out about it and not knowing what to do, and the news is blowing up and it's just, are we all going to lose our jobs? So it just was sort of to come in and say, hey, we've had AI for a long time and it's, it's just doing things faster now with AI. And there are some core things that, that people could go do and steer the ship in this, in this haze of craziness.

Brandi Starr [00:03:24]:
Awesome. And I, you know, I believe in setting intentions. It gives us focus, it gives us purpose, and most important, it gives our audience an understanding of what they will take away from our discussion. So what's your best hope for our talk? What would you like people to walk.

Tracey Fudge [00:03:41]:
Away with just a better understanding of what can be done today to make sense and to get out of the, of the unknown. That's really it. And I've got a few ideas of things that people can do right now.

Brandi Starr [00:03:56]:
Awesome. Well, I know marketing operations is your primary background and you and I have had some conversations about AI for marketing ops and so I'd love to hear your take and ideas share with us ways that marketing ops professionals and those that are more in an operations function how they can tap into AI and how leaders can really support that for them.

Tracey Fudge [00:04:26]:
Well, it is and it's to the marketing ops and rev Ops. I see them as one, you know, they, they all collaborate and the systems even talk and the teams are very close to each. So when I think of marketing ops, I also think of revenue ops as well. You know, it's, it's automation is no longer an option. That is one thing. And we've got tools that are, that we have right now that we can do. But the issue becomes the data. And that is the problem with in my opinion, all of this.

Tracey Fudge [00:05:00]:
AI is useless if the data does not make sense. So it is, there's a few things that people can do to, you know, clean your data and make sure that it is centralized in one place, a data warehouse and that tools can action on that data quickly and live.

Brandi Starr [00:05:20]:
Okay, and I do agree like with, I mean since, I'd say honestly since marketing technology started growing, the data has been such an important component because you know, segmentation, personalization, all of the awesome things that we can do with these tools are dependent on having the data and so centralizing the data, you know, into. And I'm definitely not an expert on the text there, but I know we've got data warehouses, we've got CDPs, we've got different places and methods of aggregating that data. How does AI play a role in that?

Tracey Fudge [00:06:03]:
So assuming the data is in the right place, let's assume that it's kept, it's clean, it's up to date. Well, it can do several things. One, it can predict who's going to buy and when they're going to buy. And the old times we called this lead scoring. And you know, the whole joke is the MQL is dead. So it is honestly adding, not just scoring, but knowing. It is testing the algorithms of past behaviors of taking a segment of the population and understanding how they buy and when they buy and what they buy. So that is one part that AI can do and it can go beyond that as well, but I think that's probably the most important part because we, you know, every business needs to grow pipeline and if you can predict when and how a company or a person is going to buy from you, that that solves a lot of problems.

Brandi Starr [00:07:04]:
Yeah. And thinking about that, one place that I think that a lot of confusion comes in is the difference between leveraging predictive analytics, which falls more in the realm of data science versus AI, to do these things. Because you are right. Way back in the day it was lead scoring and the models were very static and what we were looking at and how they were being analyzed. And then now we've got predictive analytics, we've got intent data, and then you throw AI in the mix and it can be kind of confusing to understand how these things work together, how, you know, AI plays a different role. Do you have any insights into like, where, where people are leveraging AI versus other approaches in, you know, being able to predict that revenue and better target and all the things that you just mentioned?

Tracey Fudge [00:08:09]:
Well, let's, let's say for a moment we've, we've got the data and we've got the tools and we, we've been sitting on these tools and I will pause and say that marketing, we caused this problem because we added so many tools, stacks and so many platforms. You've got a platform for every single thing now. Sales has got their platform, marketing has theirs. And so the data has been in these different places. But to answer your question, AI has been there. It's there right now. It's there with Sixth Sense, it's there with Chili Piper, it's there with all of these tools it do. We just never called it AI, but now we're calling it AI and we think it's something else that's coming in.

Tracey Fudge [00:08:51]:
And while these large language models are something that are new, that's something that's distinct. And I think that gets a lot of these buzzwords, DeepMind, OpenAI, all these. But the tools that we use, they've been there the whole time. And it is, it is just getting that data the correct way. Lead routing is another thing. You know, you can't afford 24 hours to send a lead to a sales rep. You've got minutes sometimes and there's tools out there that do that. It's just how it's structured and set up.

Tracey Fudge [00:09:25]:
And if the fields aren't mapped between the databases, they can't route. So again, it just goes back to the data and getting that right. And that's where people don't take the time they get these, these new tools. These big software companies do a great job of selling more tools and there you are, you've got a big shiny tool that you just spent millions of dollars on.

Brandi Starr [00:09:47]:
Yeah, I definitely agree. Like connecting data is so important. One of the things that we talk about often is the importance of looking at and reporting on data in context of the other things that are happening. Because I've seen scenarios where people will look at the outcomes of their PPC and paid ads and they will assess the effectiveness just based on how many people are clicking. Whereas when you further engage to look at how many of those turn into real leads and opportunities and revenue, you may see that none of those ads really worked in generating revenue or the same thing for content syndication or email or social. You know, it's like when you have everything siloed, you see performance of a channel and how well that channel is doing at what it does, but you don't really see how it impacts in revenue. And I think that's a key place where operations professionals come in. And I am like you, I think of Revops as one team.

Brandi Starr [00:10:55]:
It should be all of the go to market functions under one umbrella, looking at the operations of all of them. And so when we think about that data is definitely at the core of it. And so I'd love to hear a bit more if you know, those listening are trying to identify, you know, where they need to lean in. You know, let's assume like some of the dirty data like that is kind of like if your database is a hot mess, we know you need to lean in and address that. But beyond the basics, what are some considerations that people should make when it comes to, to the data?

Tracey Fudge [00:11:37]:
Well, a good place to start is the CRM. And I know that sounds like an obvious thing, but a lot of times marketing does want to go in and clean out the CRM and sales won't let them touch it. So there's one thing. So those teams need to communicate. Probably a large part of the data needs to be thrown away and you just start new with modern, with, with a modern approach. And when I say modern, I don't mean 2025, I mean current data. So cleaning out the CRM, finding out what fields are ne. I don't.

Tracey Fudge [00:12:08]:
If you look at some of these CRMs, they've got fields, they've got thousands of fields with all this data, you know, and it doesn't map. So cleaning out a CRM is a great, a great first step to getting a hold of the data and then if that's your source of truth, then map the data, the rest of the data tables in the other systems to that source of truth. Does that make sense?

Brandi Starr [00:12:33]:
It does. And I think a key thing that it makes me think about is when we're talking about data, we need to ask why, like why are we collecting this? You know, why does it exist? How are we going to use it? Because I have seen the same thing where there's, you know, all these fields and nobody that's still in the organization knows why they exist. And in some cases I've seen where sales is expected to complete certain data and there's no clear understanding of how it's going to be used. And so I do agree that that is like what data is necessary and useful and which contacts should be retained versus purged. I have definitely fought that battle a number of times is so important and even going back to your point and reviewing all of that periodically because our businesses change and sometimes there's fields that get created that totally made sense at the time. They were created for the way that that organization is doing business. But as those things evolve, nobody goes back and says, okay, we're not using this anymore.

Tracey Fudge [00:13:45]:
Right. People add forms to websites for landing pages. Well, guess what? All those fields in the form have to map somewhere. And you've got a new team that comes in in the new year and they've got these ideas of these fancy forms, but the fields go and they're just, it's duplicated data or unnecessary data that just clogs the system.

Brandi Starr [00:14:05]:
Yeah, and it's, it's one of those things and this is why the operations function is so important. Because having people who can strategically think about form, strategy, data, strategy, all these things so that you do have the tracking, reporting the lead, routing, all of those things working seamlessly takes someone in operations with that operations mind to connect all of those dots. And so I know when you know, I know as a consultant when working with companies you are really looking at AI and how that is used to, you know, achieve revenue breakthroughs. And I know just from our earlier conversation, you've got some use cases that you've worked through and so I'd love to hear more about that as well.

Tracey Fudge [00:15:00]:
So the easiest use case of all and the easiest company to work for is a SaaS company. And because everything happens on the web and it's easily, I should say it's more easily trackable. The data is trackable. And if you could take that use case and you could handle the lead routing, you can make it so much faster. And I worked with a company a couple of months ago and we, we increased the conversion rates by 25 or 26% just by getting the lead routing under five minutes. That was it. That's all we had to do. So that's a great example right there.

Tracey Fudge [00:15:43]:
And it didn't, it took a while to get up. But it started with a data conversation. And even prior to that, it started with IT and marketing and sales coming to the table and agreeing that this was important. You know, the old school and the old mindset is the, you know, it's very siloed, siloed departments and siloed data. So that conversation had to happen. And because it was a SaaS company, I think the conversation was easier. People couldn't get away from it. I've been in some scenarios, I was actually with an AI company, believe it or not, last week, and they, they still have the mindset of, well, this is my data and that's your data.

Tracey Fudge [00:16:30]:
And we, we want to control that versus everybody controlling it. It was still siloed and, and by team. So it was, it was an interesting scenario to be on, to be in.

Brandi Starr [00:16:44]:
Yeah, you know, people being territorial over data has always been one of those things that is really interesting to me because I understand some of it in terms of data health and being able to keep it clean. You don't want, you know, to let it get out of control. The ways that it can be updated and who can update it and in what scenarios, things get overwritten. And so I do understand from that perspective, but I just never understand that my data, your data sort of mentality, because when we look at the picture, and I mean, this is another way that AI plays a role is as humans trying to look at these different data sets. It's really difficult to glean those insights. But when you, you know, when you put AI on it and have it look for pattern recognition or, you know, different insights that it can pull from looking at the overlapping data. It's like there is so much there. And I'm curious if you have seen, like the power of AI starting to be a catalyst for breaking down some of the silos and being a little more friendly with information.

Tracey Fudge [00:18:07]:
That is a great question. And I was just having this conversation, I'm involved with, with a cohort right now, and we were just chatting with that, that AI is leveling the field. But it is, it's humbling all of us, to be honest. We're all wondering what is going on. And of course you want to say everything's going to be okay, but everything will change. It's changing fast and things are happening faster. And I think when that happens, you tend to, at least what I'm seeing is people tend to lean on each other a little bit more as one cohesive team, wondering what all this is about. Because if you miss a minute, your competitor, if they're one step ahead, it's game changing and you could lose market share.

Tracey Fudge [00:19:01]:
So things, I think it's humbling, it's frightening, it's humbling. But I do think it's working to make teams more cohesive.

Brandi Starr [00:19:11]:
Yeah, I think I generally when it comes to technology, am an early adopter. And you know, I, I wouldn't necessarily call myself early with AI, but you know, I'd say probably in the second wave, so to speak. And one of the things that I have noticed is that the hardest part with this is the speed at which everything is moving. Because if I think about other major changes in our industry, I mean, you think about when the Internet first became big. Like when I started my career, I was doing design work for marketing. That was marketing via fax machines. And you know, the Internet existed then, but it wasn't, you know, as popular. And then we look at when marketing automation first became big, you know, that was a game changer.

Brandi Starr [00:20:06]:
And it's like, so we've had these moments in marketing that have changed the game forever, but none of them have moved this fast. And I think that is the part that is scary because larger organizations tend to move so slowly that, you know, like I can think of just when I started consulting almost 10 years ago now, like I can remember companies who were just adopting marketing automation, which, you know, was probably about 10 years behind. And so if you think about companies that are, you know, if they end up being 10 years behind, operate adopting AI, it's like you truly have been, you know, left in the dust. And so as you've been talking to customers, have you seen that hesitation? And how have you helped clients to like, get over that hurdle and move forward with embracing AI?

Tracey Fudge [00:21:08]:
So it's ironic because the industries that need AI the most are the most afraid of AI. And let's go to the type of industries building, the building industry, the construction industry, things like that. They are very old school in their systems, but they're answering the phone or responding to emails, things like that. So I'm, you know, if you step away from the data side of AI and go more into this agentic side of Automation and things like that. Those are the companies that need it the most. And you just remove the word AI because some of these folks don't want to hear it still. And, you know, I will not have AI in my business. Well, guess what? You already do.

Tracey Fudge [00:21:58]:
We're just not calling it that. But let's, let's speed up these processes. I'm working with a client now who cannot get back in touch with their scheduling. So their scheduling is a hiccup and sometimes they cannot get to everybody. And if they just were able to tighten that up a little bit, it's more revenue. And once they see that, then it makes sense. And I think it's an easier conversation to have while people are just getting used to this new paradigm of AI.

Brandi Starr [00:22:31]:
Yeah, I mean, and it very is similar to when the Internet came out. Like I can remember, you know, people being fearful of the Internets and, you know, oh, that's going to be a fad. And you know, just all of the things that came with something that was so new and unfamiliar and we're, you know, we're seeing that same thing today. And so my last question really is a. I don't know what I don't know. And so I want to know, is there anything I haven't thought to ask you about and the work that you're doing and how companies can better leverage AI that you think is important to share with the audience?

Tracey Fudge [00:23:17]:
I think the amount of education that's out there is enormous and it's growing daily. I think the world as a whole is really trying to educate on AI and what it is. And even in my sphere of friends, my mom's people, sometimes I have conversations and they just, they don't know what to go do. But I would just say there's so much free stuff out there to learn and understand, just to get a comprehension of what is going on, just to become educated. It's there and it's not costly and it's fast and you can learn right away. And I think education is very, very key for everybody right now is to learn, learn the lingo, learn what you can do and learn that it's there to help to. Instead of, you know, replacing it just, it's just going to make you better if you learn.

Brandi Starr [00:24:16]:
As I say, that is so true. And there is, I mean, there is a lot of resources out there. There are a lot of resources out there and various AI. You know, I always hesitate with the word experts, but people like yourself who are really leaning in to learn and understand and stay ahead of the curve. And so talking about our challenges is just the first step. And nothing changes if nothing changes. In traditional therapy, the therapist gives the client some homework. But here at Revenue Rehab, we like to flip that on its head and ask you to give us some homework.

Brandi Starr [00:24:55]:
So I love to have people walk away with a one thing. And so for you, for anybody who's listening, if what you've said has resonated with them, what's the next action that they should take?

Tracey Fudge [00:25:08]:
I think from a business standpoint, I think look at a few tasks that people do that are mundane and repetitive and outline those and then figure out how to automate those to make things faster. I think look at the things that people don't want to do and see if you could automate that. That's kind of a fun exercise too. And you can, to use my word, work with others and collaborate on that. I think that's a fun thing to do. And then figure out how to make that work. And then research and learn that. And that you would have learned.

Tracey Fudge [00:25:51]:
You would have earned an MBA by then. By the time you fig figure that out, I think that would be a fun exercise.

Brandi Starr [00:25:57]:
Ah, pretty awesome. Well, Tracey, I have enjoyed our discussion, but that's our time for today. But before we go, tell our audience how they can connect with you and definitely do the shameless plug for AI by Thrive.

Tracey Fudge [00:26:14]:
Yeah, so my website is AI by Thrive. That I had an agency, Thrive Agency. And then when I started my AI world, I just said, well, it's AI by Thrive. So I'm Tracey T R A C E Y at AI by Thrive. I've got some good information on my website and if you all just want to email me or catch me on my website, you can schedule time to talk.

Brandi Starr [00:26:36]:
Awesome. Well, we will make sure to link to your site. So wherever you are listening or watching this podcast, check the show notes so that you can connect with Tracey and AI by Thrive. Tracey, thanks so so much for joining me. I have enjoyed our discussion.

Tracey Fudge [00:26:54]:
Thank you so much, Brandy.

Brandi Starr [00:26:56]:
You are welcome. Thanks everyone for joining me. I hope you have enjoyed my discussion with Tracey. I can't believe we're at the end. Until next time. Bye. Bye.