Will Spendlove: AI for GTM Isn't About Automation—It's About Control

Welcome to Go to Market, a podcast for revops, sales, and marketing leaders to dive deep into industry insights and best practices. Go to Market is sponsored by Fulcast and Silicon Slopes. My name is Amy Cook, and I am so excited to welcome my good friend Will Spendlove, who is the VP of Product and Solutions Marketing at Alterix. Will, how are you today?

Amazing, Amy. How are you?

Good. Thank you so much. You know, for everyone listening, we prerecorded this. It's 2 days before Christmas, and Will is taking time out of his vacation to meet with me today. That's so nice of you to do.

Of course, I'm happy to do it.

Well, Will, tell me a little bit about your background and let's just get started with your revenue journey.

Yeah. Yeah. I'd love to. So I have been in marketing roles for the bulk of my career. So I've, I've been in product marketing or growth marketing roles since the early 2000s. I did actually spend 2 years in 2004 as an AE at Symantec. So I actually had named accounts in the San Francisco Bay Area. I was living in San Francisco. I currently live in Salt Lake City, but I was in San Francisco for 20 years. And so carried a bag for a few years, but most of my time has been in either product marketing or sales enablement or growth marketing. So my experience really around sort of revenue ops and sort of the, the, the go-to-market lifecycle really is around the ownership of pipeline target that traditionally marketing would share pipeline with sales and, you know, I was at Salesforce for 6 years in the, you know, from 2011 until around 2018, had a little break in between if you do the math, but yeah, I was there twice for 6 years. And it was interesting just kind of engaging with that pipeline ownership. And at Salesforce, they called it the Four Horsemen model, right? So with the pipeline, you have marketing owning part of the pipe generation, sales owning part of the pipe generation, sales development, business development, XDRs owning part, and then partners. So. It was always understanding, you know, we own part of that, that pipe creation in marketing. But then also a lot of the companies I worked for had solutions for people on the revenue side. So I was at SteelBrick, which got acquired by Salesforce. So that was CPQ. That's actually where I met you, Amy Cook.

That's where we became friends, which was awesome. First time I met you, Will, I was like, this is my people. Like, this is, I love it. It's really fun. And you made our Salesforce experience experience as a partner so much.

It has been great. Yeah, I feel great. One of the fun part, I mean, you were working at Simplex at the time.

That's right.

So you were one of our system integrators for CPQ, which was great to sort of work together, which was—

Yes, and you were so nice when we would come and hit you guys up for business all the time. You were so nice about it.

What I loved, and it's something I've actually experienced at multiple companies since, I was at DocuSign prior to Alteryx and we call, you know, we call us company like Simplex, Simplex, an RSI or regional system integrator, which doesn't really, it's, it's, it's sort of a misnomer because you were global. Simplex was a global company, but you know, they call it GSI or global system integrator. That, that's when you usually refer to like the Deloites or the Accentures or E&Y.

The massive companies.

Right, right.

And we ended up selling to Infosys, so then we became global.

That's right.

That's right.

What I loved about that was just your interest, you personally, but also, you know, Ryan Westwood, you know, and that he was the CEO at the time, was the interest in really looking at use cases, right? And us breaking it down to what are the jobs to be done for a seller, or what's the jobs to be done for someone who's at a deal desk or in sales ops? And then really understanding how do we turn that into strategic engagement at an organization, right? I think that was really fun, right? As rather than just sort of like randomly coming with marketing or selling sales plays, it was like, let's look at a really specific use case or job to be done and figure that out. It just made it so much more tangible for a customer.

Yeah. That's exactly how I feel about it too. When you look at something, like I think of myself as the Chief Problem Solver Officer, not the CMO, because really it, Like you're, you're a good CMO if you can actually take a problem and be able to market to solve that problem, right? It's not, we're not trying to convince anybody to do something. We're just trying to offer solutions to help them solve the best. Yeah. I love the way that you characterize that where like you're breaking it down into the jobs to be done. And that's such an important perspective when you're talking about like a partnership. And that's one of the reasons I think you were such a good partner.

Yeah, that was, that was why it was fun is you, you, we both sort of had the same vision of what needed to be done. So that's, I think that was why we connected. And, you know, by the way, we're just like soulmates, you know?

That's right. You know, we are. Yeah.

It's like, yeah. So I joined Alteryx 4 months ago and one of the reasons I joined Alteryx and I, I'll tell you what Alteryx is in a bit, but when I was at Salesforce my first time around 2014, I joined 2011, so, you know, my third year at Salesforce, I met this incredible woman named Michelle Huff, who is now my CMO at Alteryx. And she was the Data.com CMO, and it was an acquisition that Salesforce had done. And since then, they've actually transferred that to be, I think it was called Data Cloud for a while, and I believe they just relaunched it the last Dreamforce to be called Data 360. But it is the, the sort of the, the data behind Salesforce, right? So it's the data systems and database and the way it stores it and, you know, the, the way that it manages that data and, you know, pulls analytics from that. So Michelle was part of the, you know, introduction of that in the Salesforce world and her, her boss and her basically best work friend, Annie MacMillan, they, he was the CEO of Data.com and now he's the CEO at Alteryx. So, I was ready for a change and I reached out to Michelle and I said, hey, are there opportunities in, on your, or on your team? And she's like, I actually have an opening right now for a leader of product solutions marketing. So, that's, I'm in Alteryx now and just so you, for, for people who aren't familiar, Alteryx, it's actually a really, it's been around for a long time. It's over 25 years old. And we were the original company who really created ways for non-data scientists and non-SQL experts and non-Python coders to be able to get analytics out of complex data systems. So whether it was a database, whether it was, you know, system of record, whether it was even a spreadsheet, like an Excel spreadsheet or a Google Sheet, right? Taking that data and modifying it through visual workflows with just drag and drop functionality to allow them to pull that data in. We used to call it prep and blend. So it'd prep the data, it'd blend the data, and then it would push out analytics and it would push out visualizations, or it could be sent to a visualization platform like Tableau or, you know, Domo. Or you could take the— it would produce a CSV file of that blended prepped data and it would pull in things like geolocation information. It would pull in, you know, if it was a sales or a RevOps, it could pull in sales rep data from Salesforce. It could pull data in from Workday. It could pull in data from the revenue or the financial systems to see which territory is the most successful. Why is it successful? Which deals am I getting, you know, the most impact, you know, or even prepping for a QBR, it would let business analyst in RevOps be able to run those reports without having to go to IT and have them help. So that was really the core of what we were, and now we've moved into pulling, leveraging AI as part of that process. So workflow steps and pulling LLMs to help to, you know, to create those enhanced workflows with AI. And then actually the output, taking that output and leveraging it not only in reporting, but also actually being able to send those updated metrics back into the LLM. So imagine a lot of times LLMs, whether you're, you know, using Gemini or ChatGPT, the information is very generalized because it's looking at all of this data from, you know, everywhere, but it doesn't have the business logic, right? It doesn't understand your policies. It doesn't understand your specific data, and even if it does tap into the data, maybe that data is not speaking to each other. So we're able to take that, make it into a usable dataset, and then inject it back into an LLM. So for instance, a sales leader could just go into ChatGPT and say, what are my highest performing territories? Or they could ask, you know, which reps are the most effective? Or where's the highest risk of churn? And because you've built that, you can ask ChatGPT, And, you know, it's within the firewall of the company, so it doesn't ever leave the organization.

Yes, of course.

But they're able to ask those questions without saying, hey, you know, RevOps, we'd love— we need you to run this report. I mean, RevOps still has the power to use permissions in order to give people access, but then you don't need to go to IT. You don't need to, you know, you can have the business users sort of serve themselves. So, that's really where we see the future.

That is beautiful. Fascinating. And I see, Will, potentially another partnership coming on because our copy product does the exact same thing only with copy. So we will take and we will ingest an LLM and then we will have what we call is our brand brain where it's like all private brand data. It's almost like a digital asset management system, but only it stays within the walls of the company and it is able to ingest all that public data and then using workflows be able to create something much better using our private brand data as well. So it's really good for brand management, but it leverages all of the LLMs and it prevents that quote-unquote AI slop from taking over your marketing content. So anyway, we should explore this more later.

Let's talk about it, because actually I think both of our examples creates a data output that you can leverage in other workflows just like yours, right? I mean, so it's— can't even imagine, because for marketing we also, ours is really based on that raw data and, you know, it sounds like yours, does it use OCR to do that? How does it, how does it, you know, pull that data?

How does it pull it in? So what it does is we have the ability to, within the chat option, to use either Gemini, ChatGPT, Claude, and you can, you can toggle back and forth between any of them. And so it pulls that in and then you're able to upload all of your assets. And it's very easy. It's a no-code solution. And then build a workflow that is just like a drag and drop, like a HubSpot thing.

Yeah.

And it just pulls it all together and it creates beautiful stuff. So we've actually completely revised the way that we go to market within our own marketing department. We went from 5 blogs a week to 30 blogs a week. In one month, we've increased our AI visibility by 10 points. Like it's a phenomenal, it's a phenomenal tool.

All right, we gotta talk to you about this to not only partner with, but potentially to use.

That's right. So, but I think like what we're both talking about is being able to combine the public and the private, being able to leverage all of the amazing work of AI that's already been done and use it in a way that's usable and awesome for the brand. And I think it's amazing that the DNA of Alterix was that already. So then when AI came along, you're like, oh, well we can just do the same thing we've been doing. We can democratize data. Data, only now we can do it even better.

That's right. That's that exactly. That's exactly how we see it as well.

That's really cool. I love it. Well, so, you know, with all of this talk of data, with all of these workflows, with AI coming, you know, coming down and really infusing itself into every piece of go-to-market, what is one area that you are seeing that is maybe affected more than others, or there's some controversy around it.

Yeah. Yeah. It's, it's, it's the first thing that when you said that popped into my mind and let me, I'll share a little story and then I'll, I'll kind of tell you what I'm seeing now. I was in London last year, actually earlier this year, it was in June for, I was at DocuSign and I was doing our customer event there and I was in one of the tube stations. And I'm sure, you know, you've been in London many times, you know, a lot of people spend time in London who, you know, work internationally and they do these takeovers. If you, you know, remember Piccadilly, they'll take over. I remember the, um, the, the play, The Book of Mormon took over Piccadilly Circus tube station one month. And then I went back the next month and the LDS Church had taken it over and they were both talking about The Book of Mormon. It was hilarious that they both did takeovers of the same station, but there was a station I was in and this AI assistant for business development or SDRs, or some people call them XDRs, had taken over one of the stations. And I was fascinated because one of my friends was actually currently hiring for a few, you know, sales development reps or business development reps. And I took a video of it and I sent to him and I said, well, have you considered, you know, using technology to do this? And then all of a sudden I started talking with some sales leaders and sometimes, you know, the inbound reports through marketing rather than sales, but I started talking to some leaders and they said, we're actually seriously considering using, not just for the chat function on a website, which is pretty common now. A lot of companies use the chat function on a website. They'll use AI for that. But they started saying, hey, is this something we could leverage for taking inbound calls? So it's an interesting trend that I'm seeing where people are starting to look at like, how do we leverage AI to, you know, we talked about workflows, right? Well, AI can actually, as we all know, I mean, it can reason to a certain extent, right? Based on a response, it'll reason between multiple pathways in a workflow based on what the response is. So conceptually, it's, you know, that's what in some respects an inbound rep does, right? They do discovery, and based on where a customer takes the conversation, they will respond with a series of other questions that get them to either creating a meeting, or some of them are even able to create an opportunity that needs to be accepted by sales, or it might go into a nurture path. With marketing based on what the outcome of that call is or engagement. And it's just fascinating to see that AI is being looked at to do that. And I just think it has the potential to totally change, not just that function, but a career pathway.

It is so fascinating to me. That one in particular, I think is going to change the most. And the question for me is, you know, you have these people on LinkedIn trying to grab views going, SDR is dead, everyone, all of you SDRs go find a new job. And then you have other people saying, oh, I really hope that everybody goes in all in on this AI SDR motion because it is going to fail and we're going to go back to humans only. And so like, where are you on that? Spectrum?

You know, it's, I actually feel like it depends. If the buyer doesn't require personal touch, and what I mean by that is, I mean, anytime you ask, for instance, I use ChatGPT personally. Also, I, um, Alteryx has used that as our corporate standard for LLMs. And when you ask ChatGPT a question, it will, or if you choose to use a voice, you know, if you actually choose to converse with it rather than, you know, keyboard, they will always give you a positive response and say, you are so smart. It'll make you feel a certain way, you know, right? I'm asking really smart questions. And unless you tell it, don't do that. Do not give me that. Actually challenge me. It'll just automatically give you the, you know, a positive response. So the assistant itself would have to be knowledgeable enough that if a customer didn't want that engagement, they wanted it to be more Challenger selling type of a model, the model would have to understand how to modify the way that it's engaging with the customer in order to do that. And I think that's really complicated. And, and I haven't seen that obviously in the way that I engage today with ChatGPT. It could get there, but it's the nuance of a human and it's emotion. It's almost understanding the emotion of a person and understanding how they're emotionally coming to it in order to modify the way they're engaging. And my understanding is, as of now, AI models don't understand human emotion. They don't understand the nuances of an emotion. So I have a friend who's an SDR at Retirement. So they basically take people's retirement accounts and they invest and help them to leverage them the best. So he takes inbound calls and he said a lot of the inbound calls, they just need to talk because they're at the retirement age and they need a person to listen to them. And he's like, oftentimes they'll spend 5 minutes just talking about their grandkids or what, you know?

Yeah.

And he he has to have that human element. He has to listen and use that right side of his brain to know the right way to approach it. And I'm not sure we're ever going to get there with—

I love that you said that. I totally agree. So I actually, in a former life, I ran a marketing agency and we actually did customer service calls for people who finished their nursing home stay. And so we would get on there and they would just talk and talk and talk and talk and talk. But what's interesting is not only was it fulfilling because, you know, you made somebody's day, but it also can greatly influence your customer success score. And that is fascinating to me too. So I'm like, we're going to see pretty soon how well AI does in that customer success measure. And then, and it also is helping me understand how truly complicated our brains are because you're right. Like when you try to replicate the AI, like try to replicate the motion for pipeline generation or whatever with AI, you cannot replicate the nuances that happen when people talk to each other. That's right.

That's right. Which is why I think, I mean, you know, you and I prior to hitting record, we're talking a little bit about just COVID and you know, how that impacts us personally and as, you know, society and That was what a lot of people said is when we weren't in person with each other, there was something lost. And that's why I think a lot of organizations are doing these return to work because they recognize that there is something about the human interaction and even in-person interaction that can't be replicated.

I agree with that. And I don't think that you and I would have the same rapport even virtually if we had not already met many times in person. And there's just I mean, we call it a vibe, we call it like whatever we call it, but there's something between people when you meet in person that connects you. And it's very, it's very interesting to notice and appreciate that even in the stark contrast of us trying to replicate it in AI.

So that's right. That's right.

Very interesting. Well, thank you so much for joining us on this. I will be very curious to see what you guys decide to do with SDRs and Alterix. And what our whole ecosystem decides to do. It is definitely a rapidly evolving place, you know, job description too. But my last question for you is, you know, you have had such an amazing career. It has required you to sustain like a very high level of engagement and work and everything throughout, you know, the years. How do you do it? How do you stay at the top of your game?

That's such a, that's such a funny question because I was just chatting with someone about this yesterday. I, I actually think some people, it is natural for them just to be positive. Like, I think it's just, it comes naturally. And that I'm one of those lucky people that, that positivity has always been something. Even when I was a little child, my parents said, you always were, you always woke up on the right side of the bed right now, whatever that means. And I think it was just something that it was part of who I was and who I am. But that doesn't mean that like things don't frustrate me or get me down, or I have to have hard conversations sometimes. So for me, it really is just having a big picture view of my career, having a big picture view of my role, having, you know, clear understanding of what success looks like and knowing that there's a really good chance I'm never gonna hit that, what I believe is that, you know, perfection. And so giving myself and my team and my organization grace to, you know, make mistakes or stumble and Knowing that that is part of the process really to me has helped me to continue to drive not only myself, but my career and my teams. So I think that's really, like I said, I love that. Yeah. I just believing, first of all, just leaning in with positivity as much I can and then giving people benefit of the doubt. I think that's probably my two.

I think that that is so needed, especially today. And it is harder to do than a lot of people think. And I really appreciate that. And I think that, you know, I know that you're naturally a positive person, but I know it also takes discipline and it takes reframing your mind and in a moment of frustration going, okay, how can I say this in a nice way? Thank you so much, Will. Thank you for who you are and everything you're doing and how you're helping the ecosystem.

Well, and thank you for doing this. I, this is such a, a great podcast and I loved being part of it. So thank you.

Thank you so much. Business. Yes, that's business. Business. Yes, that's business.