EPISODE 651: Using AI to Enable Customer Acquisition and Revenue Generation with Jennifer Ives

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Today’s show featured an interview with Jennifer Ives, Co-Founder & CEO at Watering Hole AI.

Find Jennifer on LinkedIn.

JENNIFER’S ADVICE:  “There are AI revenue generators, and that’s what we focus on. I am a revenue generator. Before I co-found this company, generating revenue, in addition to making sure that your customers are happy and satisfied and getting what they need from you, generating revenue is your next goal. You cannot be in business if you’re not generating revenue. That’s where we focus, and that’s what makes me really excited. It’s all about who’s around your watering hole, where are your like watering holes, and how can we help with use cases that help you generate revenue in your company.”


Fred Diamond: My guest is Jennifer Ives. You’re the co-founder of Watering Hole AI. Jennifer, we’re doing a lot more shows in 2024 on AI, artificial Intelligence. I’m excited to talk about the Watering Hole platform and how you made this career shift into running this company. It’s very exciting what we’re doing. We’re also going to be talking about some of the challenges that sales leaders are facing right now as it relates to AI. What I’m going to do is I’m going to ask you a very general question, and then I want to talk a little bit specific, to put this in context, about Watering Hole AI.

First off, it’s great to see you. Jennifer Ives, you’ve been very involved with our Women in Sales programs over the years. You’re on our Women in Sales board of advisors. You’ve been a podcast guest, you’ve been a frequent participant at Institute for Excellence in Sales Programs. I’m excited with what you’re doing. Well, I’ve been following you for years, but specifically recently on what you’re talking about as it relates to AI. First answer the question, what is AI and what isn’t AI? Then I want to talk about what you’re doing at Watering Hole.

Jennifer Ives: Fred, thank you so much for having me today. You’re one of my favorites. I love the podcast and you’re right, I participate in many ways with you and the Institute. I just think the world of what you put out into the world. So, thank you. I love being with you today.

I get this question a lot, what is AI and what isn’t AI? Actually, to be honest, I wish I got the question more because I think there’s a lot of confusion out there. AI is simply math applied to data. It’s been around a long time. It isn’t something new. What is new is that ChatGPT hit the scene about a year ago, and then everyone started talking about AI. You and I started talking about AI professionally when it comes to business and kids are talking about AI, grandparents are talking about AI. ChatGPT really laid the groundwork and put the topic of AI out into the world in a way that we hadn’t seen it before. That’s wonderful.

However, ChatGPT is one form of AI, and AI is a spectrum. There are many, many pieces of AI and many parts to AI. To get stuck in the ChatGPT conversation is a real missed opportunity. Again, AI, it is math applied to data. There are two forms of AI that I think it’s really important. Just as we’re talking today, there’s generative and there’s predictive. Generative is your generating something new from something that hasn’t been around before. Predictive is you are looking at data to predict what might happen in the future. I always like to not only talk about a quick definition of AI, but also the world talks about generative and predictive.

To put it into real simple terms, an easy way to think of AI is that it is like a super-powered party chef. It’s not a mystical mind reader. It can whip up incredible dishes based on your recipe, it can gather the ingredients from mountains of data, but it can’t invent a new dish, and it doesn’t taste what you’re craving. It can do that. Unlike a genie in a lamp, it doesn’t magically know your desires. It needs very specific instructions and feedback to create your version of the perfect AI-powered feast. In this case, we’re using food as the analogy, and it also doesn’t think or feel on its own. It simply executes tasks with remarkable speed and precision, and it’s based on the instructions that you’ve given it. The real easy version of that is when you type instructions into ChatGPT. The other version of that is when a data scientist actually is creating algorithms maybe for a predictive model or some other use. But I do like the food reference, and I hope that that painted a picture of what AI is and what it isn’t.

Fred Diamond: That’s actually an excellent analogy. I’ve been spending a lot of time on ChatGPT just for fun. I’m amazed at how many times it comes back with, “I can’t help you with that,” with some of the questions that we might be asking. I want to ask you a question before we talk a little bit about what brought you to Watering Hole. Where do you think we are, on a scale of one to a hundred, with AI in sales? Are we at the hundredth point where everything’s been figured out, or are we at the 1% mark? It’s just a general question, we don’t need to spend a whole lot of time, but where do you think we are in the journey, the evolution of how we’re going to be eventually adapting or adopting AI?

Jennifer Ives: At the one or two.

Fred Diamond: Wow. That is fascinating. I’m glad to have you here today. You’re the co-founder of Watering Hole. Give us a brief intro on how you got from where you’ve been to Watering Hole, and what are some of the things that Watering Hole is doing with its platform as it relates to helping sales professionals. Then for our listeners, we’re going to get into some details about how you as a sales professional can and should be using AI in 2024.

Jennifer Ives: My background is engineering. I moved over to the go-to-market side of the world years ago because I became very interested in product market fit, how technology is put out into the market, whether it’s a product or a service. Really fell in love with the revenue generation side of companies, and as I mentioned, product market fit. I often say that you can have the best product or service in the world, but if the market doesn’t know about you, it doesn’t matter. It’s like a tree falling in the woods. If no one is there to hear it, does it make a sound? That’s the question we often ask. I became really interested and really excited about that side of the business in technology companies, in product and service technology companies.

I’ve been helping companies at inflection points. I’m usually called on by the CEO, or the board, or investors to come in and help companies at different inflection points. I have a real passion for helping hypergrowth companies. That’s generally a company under $250 million in annual revenue, who’s growing maybe from 5 to 35 million, or from 35 to 100 million, or from 50 million to 150 million or 250 million. That’s really my passion. I have had the pain point that Watering Hole solves. As a revenue generating executive, I have needed to tap into, wonderfully over the last number of years, into a marketing and sales tech stack that continues to grow. A lot of that was analytics based, and that’s wonderful. That was the technology that we all had, even the companies that have those platforms that we all had at the time.

AI comes to bear. I’ve advised a couple of AI companies over the last 10 years, knowing that at some point this was going to happen. This was going to hit the mainstream. The costs were going to come down, the compute costs were going to come down, and a number of factors were going to come together at the same time to put AI into the world in a much larger and bigger way than it had over the last 10 years. In particular, as we mentioned about a year ago.

As I mentioned, this is a company that when my co-founder, the amazing Julie Holdren, who’s a computer scientist, cryptographer, and AI specialist, she had been working on some R&D for the prior two years to us co-founding Watering Hole. It was all around how do you help companies market more effectively and drive revenue, so drive sales, drive new revenue faster? I’ve known her for many, many years, she’s an expert technologist, very well respected. When she called with the technology that she was working on, I said, “This is a solution to someone like me, a revenue-generating executive, C-suite executive, leadership team executive, this is the solution to that challenge.”

We rebranded the company and we went forward with Watering Hole. We named it Watering Hole because as we were validating in the market the technology, and the platform, and the AI modeling, with CEOs, board members, and many chief growth officers, and I’m going to talk about chief growth officers in terms of sales, marketing, whomever is the responsible executive in that company for revenue generation, so chief growth officers. It can be a number of different titles there.

As we were validating it, we kept saying, “It’s like a watering hole. Your market is the watering hole. Who’s around your watering hole? Do you have zebras, lions, gazelles? Do you care that you have all three? Do you only need one? Are you spending money on all of them?” More importantly, where AI comes into play is not only identifying that, but the AI piece is the predictive, where are the like watering holes so that you can attract, if it’s gazelles, you can attract more gazelles to your watering hole. You can do that in generative and predictive ways.

All anyone needs to know about our company is that we help revenue-generating executives and businesses market faster and more effectively and generate revenue more effectively. We are in the business of making sure that the companies and our clients are generating revenue. That’s what we look for. When we’re talking with potential companies that we’re working with, we’re always looking for what’s their pain point, their use case, and does it have a generation of revenue attached to it?

There are many AI tools that are out there. There are two boxes of tools. You’ve got your efficiency creators. ChatGPT is an efficiency creator, and there are many tools, and it’s wonderful. You create efficiencies, you type it in, maybe it’s a content creator, you put in an idea, you put in a draft, and some form of tool will create content for you. That’s just one simple example. That’s an efficiency creator. There are many other efficiency creators outside of marketing and sales across companies.

There are those revenue generators, and that’s what we focus on. I am a revenue generator. Before I co-found this company, generating revenue, in addition to making sure that your customers are happy and satisfied and getting what they need from you, generating revenue is your next goal. You cannot be in business if you’re not generating revenue. That’s where we focus, and that’s what makes me really excited. It’s all about who’s around your watering hole, where are your like watering holes, and how can we help with use cases that help you generate revenue in your company.

Fred Diamond: Obviously, the listeners of the Sales Game Changers Podcast are concerned about generating revenue and finding opportunities. Tell us a little bit about what they’re saying to you. When you get a chief growth officer, or you get a sales leader, what are some of the things that they’re telling you? You don’t need to tell us the specific company names, but what are they telling you that they’re challenged with as it relates to AI?

Jennifer Ives: Some of the things they’re telling us that they are challenged with, and this is where AI can come in and help, are things like, “We don’t understand the dark funnel. We don’t understand what’s actually happening in our marketing funnel. We have advanced analytics, we have a marketing tech stack that says it’s AI driven. Now it is not. What is actually happening? Where are the decisions being made?” Then as those potential clients are coming through to the sales funnel, because it’s all one thing. Any growth leader today really needs to understand and understand in their bones that it’s not marketing and it’s not sales. It’s together. It’s marketing and sales. It’s one flywheel. By the way, I would bring in strategic partnerships to that, so marketing, sales, strategic partnerships. Those are your revenue generators.

The companies that tend to call us and talk with us about AI tend to have some of the same challenges that any company had eight months ago, two years ago, 10 years ago. “What’s happening in my marketing funnel? Where are people? Who’s around my watering hole? Who’s in my market? Who’s looking at us? Where are the like markets? Where are the like watering holes so that I can attract that gazelle to my product or my service?” They’re very similar. Then there are also efficiencies. We did talk about generation of revenue. There are also many efficiencies that can be created. Some of the top things that people talk with us about are sales leaders in general, lead scoring and targeting, predictive insights, hyper-personalized experiences, so that you can craft and tailor messages and content for customers. That boost in engagement and conversion rate is as much as 30%. That’s a Marketo number that’s out there. We’re finding in our company that they’re even higher numbers.

We worked with a technology company, a SaaS EdTech company, and they really needed to get cost of acquisition, which is a really big number for every size company. You could be small business, mid-size, or you could be a Fortune 50 company. That cost of acquisition, you’re trying to get it as low as possible. In a good day, or with technology in the past, Gartner says all the time, if you’re able to adjust and reduce cost of acquisition by 6% to 12%, you’re getting a huge bonus, you’re getting a raise, you’re getting a C-suite title. We were able to reduce that cost of acquisition by 80%, by applying and having them on our platform. That’s just one example.

Sales growth executives are looking at AI for all of the examples that I just gave you. Social listening and competitor analysis, churn prediction. That’s a really big one. Another example, another really interesting use case is churn prediction. Someone came to us with, they thought they had a marketing, kind of, “What’s happening on our marketing funnel? Can AI and predictive AI help us there?” The more we talked and the more we asked good questions and found out about their real pain point, it was actually once they were in the sales funnel, this was a SaaS company where they had 30-day free trial and some were going through and becoming clients right away, customers right away. Some were churning out and they were in the sales funnel churning out not at the marketing level, in the sales funnel churning out.

You can really start identifying, just from analytics, why they’re churning out, when they’re churning out, how they’re churning out, pulling together all the disparate sources of data, and then you can apply AI modeling on top of that to start predicting and getting ahead of it so that they don’t churn. That then increases the number of customers you have, and it brings new revenue into your company faster. They were looking at 2023 revenue, and I asked them about their 2024 revenue, and after we did a back-of-napkin assessment and return on investment, we were able to predict and suggest a certain amount of revenue that they could pull in from 2024 into 2023. Now, how happy do you think that C-suite is and those investors are when they hear, not only are you overachieving, you’re pulling revenue that we thought was 2024 into 2023? That’s the power of AI applied to marketing and sales.

Fred Diamond: When I asked you, you said we’re at the 2% mark, if you will. Talk about ease of implementation of the various types of technologies, and who are you typically working with? Is it traditional IT, or are you working specifically with the sales and marketing organization? Tell me again, the ease of implementing the solutions we’re talking about here to get these amazing results. I think one thing that everybody will agree on is that the potential of AI to produce amazing results is there. It’s just fascinating that this is actually alive as we speak. But talk about those two things, the challenge of implementing and who implements.

Jennifer Ives: The challenge of implementing. Anytime someone talks about AI, even if it’s an off-the-shelf tool that you’re trying to implement or pull into your company for sales and marketing, or in any other division, but anytime you talk about AI, the CEO is generally involved. We are generally so. At Watering Hole, we’re working with mid to large companies, so 100 million in ARR to 2 to 3 billion in ARR. We can work with companies larger than that, but that’s generally who we’re working with. When we first went to market, we thought we would be working with B2B companies all day long. They’re taking much longer to implement. I’m speaking in general terms, generalized terms. They’re taking much longer to be creative, to be agile, to test and learn. You have to test and learn with AI, you start small.

Where we are seeing, and where the industry and sales and marketing is seeing across industries is you start to see those who value their data and really value their data. Large global retailers, consumer CPG companies, B2B media companies, financial services companies. These are companies who not only are leaning into it now, but they leaned into it before ChatGPT all of a sudden, again, we’ll go back to ChatGPT, the before and after moment where people started talking about AI, not just in small circles. That’s who tends to be leaning into it in a very big way. They know that their competitors are doing so, and they’re looking to do so as well. By the way, B2B companies and sales leaders, your competitors are as well. Don’t take my discussion of B2B is a little slower to mean that they are not doing it. They are, and your competitors are doing it. Please be aware of that and really start to test and learn. That’s a little bit there.

Again, when you’re talking about AI, companies will have the CEO involved, no matter how large or small the company is. We have talked with a $7 billion customer and the CEO is involved from the very first call. We generally, to be honest, get the calls from board members and CEOs. Then because it is a technology, whomever is responsible for technology in that company, whether it be a CTO, a CIO, a Chief Data Officer, he or she is involved as well.

Our main customer in companies at Watering Hole, so our main customer, is going to be the Chief Growth Officer. That might be the Chief Marketing Officer, it might be the Chief Sales Officer, Chief Revenue Officer. It could be someone with the title Chief Growth Officer, Chief Commercial Officer. There are so many titles today. It is the person in that company who owns revenue generation for the company, so fill in the blank on what that C-suite title could be. I just gave you some examples. Those are generally the three voices at the table, and they need to stay at the table throughout.

The work that we do is broad-reaching. The CFO is also someone that we tend to bring in because a CFO loves to hear, you’re going to decrease the amount that I’m going to spend on a particular technology and increase the revenue. When we are working with clients, we are really looking for revenue return rate, a return on investment, not one to two or one to three, but we’re really trying to work with companies and help companies realize a revenue of the 1x to 5x, the 1x to 10x. CFOs love to hear that. They don’t ultimately make the final decision. However, it’s been a really important person in the conversation.

For the sales leaders out there, it is a complex sale. If you are selling AI, you do need to have a number of folks in those conversations. For what we do, which is not an off-the-shelf tool, you have to have some custom work upfront. We have to understand your data corpus. We have to understand what your data is and isn’t. Do you need additional data? Do you not need additional data? By the way, you don’t need as much data as you’re used to. The conversation of data lakes from two and three years ago, not really a conversation any longer. With 20% of your data, you can get about 80% of the way there, and then you’re going to test and learn, test and learn, test and learn anyway, because that’s what AI is. You put models in place, you test and learn, and it is human assisted. There are human beings all the way along. We have to work with those sales and marketing leaders all the way along because it is a prediction. There can be hallucination of the AI tool, and it is a human being who says, “That is not right,” as you’re testing and learning, as you’re refining those models.

Fred Diamond: Before I ask you for your final question, what are some of the things to be aware of? You maybe alluded to some of them a second ago, but what are some of the things that people should be concerned about as they really start implementing AI solutions to help generate sales and find revenue opportunities and understand their customers? Does it go back to the data as pretty much the fact that the data may not be adequate for implementing these solutions? I don’t mean to put words in your mouth, but what are some of the gotchas that you’ve seen or some of the things that you would recommend people to be conscious of?

Jennifer Ives: One of the gotchas is that people assume that they don’t have enough data, or their data is messy, or their data isn’t right. Don’t make that assumption. Let us or let a partner that you’re working with help you understand what kind of data you have. Because in today’s day and age, you can do so much more with so much less data. That sometimes is one of the first conversations we have. This is the other piece that I would highly recommend as an executive, is understand what your business strategy is, overlay and identify where the pain points are, and then start to think about where to apply AI to those pain points. Don’t just say, “I went to a conference and they were talking about this, and I think we should use this AI solution.” Really understand what your strategy is in 2024, overlay, identify where your pain points are, and then start to ask the questions around AI. I just wanted to say that really quickly as we were talking about the pain points.

Those are some of the things that you want to think about. When you are applying and you’re looking at AI, do not get caught up in, “I don’t have the right data,” or, “My data is so messy.” Let a professional have a conversation with you too, because nine times out of 10, we can bring that anxiety level way down. Because again, even where we are from two years ago, where the world is from two years ago around data and AI, let us ask the questions and help you determine. Don’t make assumptions.

As sales leaders, as executives in companies, as growth leaders, don’t make assumptions. Do understand where your pain points are and what it is that you’re trying to drive. Is it brand new revenue? Is it existing client revenue? Is it a marketing challenge that you have in your funnel? Really understand where the pain point is so that you can better focus where you apply the AI, and then also be an educated consumer. Listen to AI related podcasts, AI sales related podcasts. I highly recommend listening to AI related business podcast, because when you are in that conversation, do not lose the conversation, the C-suite conversation. When your CEO or your board turns to you and says, “What are we doing about AI and generating more revenue?” Don’t immediately turn to the technical person in the room and assume that he or she knows more than you do, because likely they don’t.

In terms of business applications of AI, you’re likely at the same level if you have been educating yourself, if you’re going to conferences, if you’re doing online learning, if you are listening to podcasts daily, this is happening so quickly. That is something that sales leaders and C-suite leaders around the world in all different industries need to be doing. When you’re exercising in the morning, put on your podcast. Put on a podcast around AI and sales, AI and business. Follow Allie K. Miller on LinkedIn. She’s one of my favorites for AI conversations across the board, business across the board. Those are three things that I would have C-suite sales leaders really pay attention to when it comes to AI.

Fred Diamond: Wow, there’s so much. This is great. It’s so accessible. It’s there. Before I ask you for your final action step, you’ve given us so many great ideas, give us the one-minute pitch on Watering Hole AI. Don’t go 10 minutes long, but if I were to see you at a networking event and if I were to say, “Tell me about your company and tell me why I would go,” you’ve already explained the company, but give us the pitch. Why would I engage Watering Hole AI specifically? Let’s say I’m the customer you’re working with. I’m the chief growth officer of a mid-market company who has been tasked with utilizing more “AI” to help us achieve our strategic revenue goals, whatever it might be, give us a 30, 45-second pitch on why I would bring you in.

Jennifer Ives: You’d bring us in to generate that revenue much faster. You can do it 10%, 50%, sometimes 80% faster when you apply AI. When someone talks to me and they say they’re the chief growth officer at a company, I usually ask them, “Well, what is your biggest pain point?” They more than 75% of the time will say, “Generating new revenue.” I’ll just say, “Do you know who’s around your watering hole? Do you know who’s in your market? Do you understand where they are and what they’re doing and how they’re making decisions?” Instead of looking at backwards-facing data, which is the data that you’re looking at in your CRM and others and online and through analytics, have you looked at forward-facing data? It’s usually around, do you want to generate revenue in terms of an ROI of 1x to 5x or 1x to 10x, and do you need to do it this year?

Fred Diamond: Jennifer, give us your final action step. Something specific people should do right now to take their sales career to the next level.

Jennifer Ives: I might go back to one of the three tips that I just shared. At any level in your sales career, whether you’re the first year or you’re 30 years in your C-suite executive, you’re Chief Revenue Officer, you have got to make yourself smart around artificial intelligence and what it is, what it isn’t across the board when it comes to business in general, and then how it’s being applied in sales today. Again, I would be following Allie K. Miller, I would be listening to some podcasts. Your podcast, Marketing AI Institute has a great podcast for growth leaders. MarTech Podcast is another. Me, Myself, and AI is another podcast. I just gave your listeners some very specific, educate yourself around AI, business AI, and growth AI, and there’s some podcasts that you should listen to in addition to your amazing podcast as well.

Transcribed by Mariana Badillo

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