Why Enterprise AI Deals Die After the Buyer Says Yes

0:00 Today, I'm joined by Scott Sinatra, CRO at WISC, the company building what they call the world's first AI HR generalist. Before we even started recording, Scott and I had an incredible conversation about what's actually happening in enterprise AI sales right now. He's at one of the most interesting AI companies out there, founded by the team that built Glint and sold it to LinkedIn, and he's selling an AI that promises to automate 80% of routine HR work. But here's what makes Scott especially interesting to talk to. He was on the team that developed Medpik. That's right, one of the most widely used sales qualification methodologies

0:44 in enterprise software. And Scott was on the team that created it. So when he says the basics still matter, even when everything else is chaos, he literally put into practice from its early inception. We're going to dig into what's really happening with enterprise AI deals right now, why they're stalling, where the friction is, and how to actually get them closed. Scott, you were just at Deloitte University for a provider conference. What is the vibe right now in enterprise AI? Is it hype? Is it fear or something else? Anthony, good to be with you. It's a combination of all of the above, actually. AI is a bit

1:26 of the Wild West as it pertains to marketing, as it pertains to adoption. I truly empathize with the buyer of AI solutions today because the rate of change is happening so fast. And every provider or vendor selling an AI solution is trying to manage the chaos. And so I think it was really an interesting opportunity for me to learn from some of the biggest and best AI companies in the world at Deloitte University. And the chaos really stems from, there's a lot of tourism, there are a lot of mandates that are coming down from on high, be it the C-suite or be it from investors, to try to really make each department

2:22 or each organization within a company more efficient. And the panacea has been to lean into AI. But from a practical standpoint, what's real and what's market texture is really difficult for the buyer to understand. And this makes it incredibly important to understand that that's happening, first of all. And secondly, the foundation of selling and sales process matter even more today, I believe. And I can get into some particulars as it relates and pertains to what we're doing at WISC. But it's pretty amazing. There was a speaker at the event who, it was really fascinating. My company WISC, we were one of two native

3:09 AI companies in the audience. The other 98 or so were all SaaS companies that were layering AI on top of old architecture. And the question came from the speaker to the audience. How many of you have heard of and are fearful of this whole idea of the SaaS apocalypse? And 98 hands were raised. And then the speaker says, how many of you are the ones that are causing the fear in these guys in this room? And of course, I raised my hand because we're a native AI solution that has built on a native AI architecture. And we really believe that matters. What's the best way to help the buyer understand the difference? Because people are being bombarded

3:54 with the architecture of, hey, we're AI first. People are throwing out that they're AI native. But how do you help the buyer understand the difference of what AI native really is versus a wrapper around a SaaS platform? Proof points and proof in customer environment is more important today than ever before, I believe. The buyer, as I said, is confused and can be confused really easily in terms of all the great things that companies are saying about what their AI can do and then the practical realities of implementing it and also how to use it and how to get value out of it on use cases.

4:32 So I think proof points are super important. And shared risk is really important. One of the things that came out of Deloitte University really across all companies was this idea that we're having to think about and do more proofs of concepts than maybe we've ever had to do before. Because although we can demo and we can show value to some extent based on something we've built in the back office, customers want to see how these things actually work and how their humans in their companies actually work with it to get value out of it. And so POCs are a way to do that. And I think you're going to see this as a pervasive go-to

5:23 move for a lot of companies to help the customer really get into the solution and then expand from there. So that's one thing. There's also a lot of conversation about pricing models. You know, the old traditional SaaS model that suggests you sell a platform fee and you sell a service fee and an implementation fee and it's an annual contract or a three-year agreement or whatever that might be, that's a very SaaS thing to do. But we're all now starting to experiment with outcome-based pricing and value-based pricing. And a lot of this has to do with, again, shared risk.

6:06 Pay us for the work that we're actually doing. And I really actually like that value stream a lot. And so I'm all about meeting the customer in the middle and we at WISC, we are more than happy to jump into the ring, show what we're able to do, prove it, and we're more than willing to take that POC deal and expand from there. And I think the way we've architected our solution, we can prove it very quickly and our LAN and expand opportunity is fairly rapid. So I'm comfortable in saying that I'm comfortable doing that if you understand what I mean. But, you know, every company is going to figure out if that's the thing for them.

6:48 I'd like to dive deeper a little bit on the value-based pricing, if we can, because I know a lot of companies that are trying to get to that point. You think every AI company has the opportunity to implement value-based pricing, and how do you even go about assessing what your mechanisms should be? That's a great question. I'll get to that one in a second. Look, I think that, I guess first of all, customers aren't demanding outcome-based pricing. They like to see it, though, as an option. It has its strengths, but it also has its pitfalls. Traditionally, a buyer or an organization wants some predictability in terms of the

7:32 budget they're going to spend year on, year in, year out for their contracts and the agreements they have. Outcome-based pricing eliminates that to a degree. Unless there's a firm ceiling and a firm floor in the pricing model, predictability of how much you're going to be spending isn't as predictable. That's something that has to be considered, and the customer is going to have to wrestle with. We have one client who's entertaining it now, and it'll be an interesting experiment to see if they actually follow through with it, or if they just want to go with it traditional in a budgeting model, if you will.

8:16 The particulars, though, of what gets measured, how it gets measured, which then leads to an outcome, which then leads to payment, that's a negotiation in and of itself. You as an organization, we as an organization, have to have a clear understanding of our value points. For example, we measure deflection rates. We take inquiries from the employee population off of the hands of human beings within the HR department, and we can deflect 40% to 80% of those inquiries really quickly. That's valuable, and customers are willing to pay for that value, and deflection rates, as an example, can be measured quarter in

9:05 quarter out, month in, month out, et cetera. You have to be pretty discreet in what you're negotiating for and against, but when you introduce outcome-based pricing, you're also introducing a whole bunch of negotiating levers with the customer. This could actually delay or prolong the sales process, if you will. There are pluses and minuses to all these different models. I think as an industry, we are only experimenting with it now, specifically related to AI. I think by 2028, 2029, something like that, we might have some instances of success using it. I think it's going to be

9:50 a crawl walk run thing into this kind of outcome-based pricing modeling. Some organizations are out there publicly saying they won't do it, too many things to negotiate, too many things to be held accountable to. That could be an opportunity to sell against somebody that won't do it, but this is all part of the chaos, Anthony. This is what's happening out in the field. That Deloitte conference, this was a big topic conversation. Nobody has this nail. There is no standard. Every company is figuring it out now on the fly. Well, and I may be asking for selfish reasons, because I've been trying to rack my brain

10:32 around how LeanScale could do value-based pricing. I was hoping to have a clear cut. This is exactly what to do answer, but that's okay. I'm so sorry. I wish I could give you that clean cut answer. When you find it, let me know. I'm not going to be all yours for it. It's such a difficult problem to solve for, and if you don't own the entire life cycle of the outcome, start to finish. There's a clean end to it, a clear start, a clear end, and you can own it. It's really, really hard to do. For us, GTMOps as a service company, we've done a lot of things where we've become 10x more efficient. We've adopted Cloud Code ourselves. We're embedding

11:15 our own apps and agents into everything we do, and when you're selling hours, really, we're just selling less hours because we're getting better. We've been racking our brain around that, but I haven't really come to the conclusion and really just saying, "Hey, at the end of the day, I don't think we can solve this problem, at least not right now, so we're just going to give more value and be more competitive," and that's how we're going to compete. The outcomes need to be clear and definitive. There can be zero ambiguity. Otherwise, you're going to get into a conversation at the end of a billing period that you don't want to

11:49 be getting into. A customer might be saying, "Well, you didn't do this and you didn't do that. We think we did," and that is probably more hassle than it's worth, unless you can be really definitive in what outcomes you're actually measuring and willing to put up against an outcome-based model like this. In these scenarios, a lot of these buying committees, departments, they have top-down mandates to go get AI. They may not even know what they're looking for. My gut is telling me that qualification is becoming even more important in this environment than before. Are you feeling the same thing?

12:28 I think you know where this is going. Yes, of course. I wholeheartedly believe that, but let's really lean into this topic because things have changed dramatically in the sales profession, I think, as it relates to selling enterprise software. For example, back in the day, five years ago, we sold an HR solution at Glint, and we were able to sell that solution to a small subset of buyers. Ultimately, the economic buyer would be the CHRO. The CHRO would then be able to earmark their budget for the spend and take us straight to procurement. That world has changed dramatically.

13:21 The concept of yes, qualification, but also multi-threading in an account is more important today than ever before because even though, for example, we are selling an HR solution, that's only the first step for us is to get the HR team convinced that we're the right solution for their problem and their need. However, there are other constituents and other stakeholders in companies today specific to AI adoption that also have to weigh in on the decision. For example, there could be an AI committee, so the CHRO might have to present to the committee to get approval. That committee could be made

14:05 up of all sorts of different constituents from all sorts of different parts of the business. IT is definitely involved in every selection process that we're seeing. One of our lessons learned in the early days of what we're doing is that we've sold HR, HR goes to get the deal done, IT has blocked the deal at the end of the process because they weren't included in the process itself. That wasn't a nefarious thing. It was because IT owns essentially the AI strategy and/or the transformation strategy of the business. They're the ones that have to implement and make everything work together. They need to understand what

14:54 the heck HR is wanting to buy. Does it fit into the overall architecture of their strategy? How does it work and integrate with all these other systems? What are the resource requirements from the IT team in order to implement and adopt it? There's all sorts of variables now that we never really had to deal with before. The message for my team and probably for others out there is multi-threading as far as account coverage and as a part of being a sales professional is very, very important today. Let's go back to qualification. First of all, there's a ton of tourism. We have a great

15:45 marketing team and we get a lot of publicity. We win awards and we've done some things as executives here at this company. We get some attention. With that attention comes a lot of interest, but interest doesn't equate to qualified sales opportunities. We have to be really diligent in separating the tourists from the ones that have an initiative and a problem to solve and with a timeframe to solve it. We're blessed with a lot of top of funnel activity. It also can be a curse if you're not doing a great job qualifying what's real and what isn't. We're very diligent in the early stages of our funnel to make

16:34 sure that what we're dealing with are in our ICP that they are prepared to enter into a formal sales process with an end game in mind. Our sales team is very well trained to do that. That's just the beginning. We have to be multi-threaded in HR. This is really interesting. We have to sell to the generalists and HR folks that are managing all of the tasks that are coming in that we actually help automate. We are a helping hand for them. We're not a replacement for them. That's a very important part of our messaging. We're not replacing them. We're aiding them to be the best version of themselves as an HR practitioner

17:30 doing the best work of their lives. That's part of our message. It's part of our value system. We have the HR generalists that we're going to be assisting with. We have the ops team. There's an HR operations team that sits between IT and HR that deals with the human capital management system, the payroll system, all the other systems that HR deals with. That's a more technical conversation for us to have and need to have related to integrations related to how things interoperate, how Harper, our product works and will work with other systems. Then we have the leadership of HR. I really think about it as a threefold intra-department

18:26 process for us. We have to check these boxes. That's just stage one. We have to win HR, which can take two to three months, let's say. We're also, though, in parallel now working with IT once an opportunity is qualified because we want to at least neutralize their concerns. If they have any concerns about our architecture, about what we're doing, how we'd work with other solutions, how we map to their overall AI strategy, et cetera. Really important for us to do that earlier in the process just to make sure there are no gotchas that can catch us at the end. Security is super important. One of the things that came out of the Deloitte

19:14 Provider Conference was these POCs that are being implemented now tend to actually not convert to full enterprise deals because of risk compliance and governance. Now, these are very large enterprises. Caveat that. Risk compliance and governance has a lot to say about AI adoption in companies. If you're not covering that in your sales process in some way, shape, or form, you really have a qualification gap that needs to be tied down to be able to accurately forecast your business. We do that through a trust portal that we've built. We absorb tons of security questionnaires and compliance questionnaires

20:05 and things like this that are automated responses, for the most part, managed by a human being. You start to see how complicated things have gotten. The most prepared organizations that understand this complication and codify their process to cover all of these elements will be the ones that I believe will be successful. It has become immensely complex. I think a lot of the areas are nascent. Like you mentioned, cybersecurity component of this, it's all new. There's not a lot of AI cybersecurity platforms out there. I think that's going to be a whole space. That's just going to

20:45 absolutely explode. Also, one of the things that I'm seeing is a trend. The sales cycle has become very complex. Then the post sales process has become very complex as well to make sure they're getting the full value out of what you're offering is. One of the things a lot of the companies are doing are taking forward deployed engineers and betting them into the team, embedding them into the company. Do you see that in the environment you're in? Do you see that trend staying around or does this feel like a band-aid for the time being? No, this is not a trend. This is a requirement. Again, big topic of conversation at this Deloitte

21:31 University Provider Day. Forward deployed engineers are in every one of these organizations. We have something similar. It's just really important to be the technical front-end on the implementation team to be able to manage all of the customer complexity that will come our way during the implementation cycle. That's not going away anytime soon. No way. What is it about this moment that feels different than SaaS, where SaaS would give, "Here's a light implementation team. Here's a customer success team that's going to help you if you have questions." In general, we're really passing it off to you to make it a success.

22:17 Why does it feel so different now? I think because AI is so new, there are so many nuances that can create some serious chaos, if not well-managed, with guardrails. If you let a customer just have at it with a set of LLMs, the rate of change of those LLMs and how they behave is pretty jarring. Unless you have somebody who's up on the changes, who understands how to build guardrails around those changes so that the solution is not hallucinating, which is a thing, I just really think it's important that a customer needs to be handheld through this early adoption

23:03 phase of AI, especially at the rate of change that we're seeing in terms of the models themselves. Does that make sense? It does make sense. I'm just thinking of the significance of needing to build this infrastructure into your company, taking that account with the unit economics of how everything operates. I think it's something a lot of these companies may not be prepared to make that investment in, but I'm with you. At least at this point in time, it's a necessary investment for your customer to be successful. I would highly encourage anybody out there selling an agentic solution or an AI solution

23:43 to deploy a forward engineer for at least the early innings of the deployment for your customer, no question about it. Every at bat, we're learning something. We're iterating on our playbook and our process. We have a very scripted implementation procedure that we've learned over many implementations now in terms of best practices. I don't see us getting away from that anytime soon. We're building into our headcount planning and in our models, kind of a gearing ratio of number of accounts for our CS team and for our forward deployed engineers. I don't see that changing anytime soon.

24:26 Yeah, I think if anybody's leaving that out of their growth model, it's a big miss right now. Because ultimately, look, ultimately, not to belabor the point, but customers have been burned by some of these POCs or these early AI tests. If you have somebody in your company that can guide them through a proper test, a proper implementation, a proper way to measure success, your chances of whole company adoption go way, way up. Some of this is just white glove treatment to make sure that the customer is very well handled, taken care of, guardrails are set, and we knock off different phases of the implementation process to ensure continued success.

25:15 One of the things that I keep preaching to our company is stacking wins, this concept of stacking wins. I went to Indiana University, by the way. I'm a proud Indiana Hoosier, national publisher. Oh, you've had a great year then. Yeah, great time to be here. Did I ever say that? Kurt Signetti talks a lot about stacking days, stacking wins. That's true for an implementation cycle for what we're doing. What's important about that is the team that we're dealing with, the buyer, the HR team, wants to be able to continue the drumbeat of great stories that they can tell internally about the adoption, about

25:57 the metrics, about the success of the deployment. This drumbeat can go on for a long, long time. Staying wins, I think, is a really important concept. I love that. Might have to steal it for a lean scale, if you don't mind. Feel free. I don't own it. One area I'm hoping we can dive into a little bit, especially with complexity of the sale, really increasing over time. Before I ask, I think there's so much hype about how to leverage AI and go-to-market for top of funnel. If you go on LinkedIn, you'll see the 10th thousand step workflows for how to get leads and how to get everything into your system.

26:42 I think what is really under-discussed is how to leverage AI for mid-funnel. You have the lead, great. In your case, you have a high volume of demand. It's more about qualification and moving it through a complex sale. How are you leveraging AI to go from opportunity to close? We've created a few things that help us with, again, qualification and information about customers and accounts that we're targeting. One is a purchase and intent signal that I actually coded in CLOD that gives us any sort of signaling from the executive team and anybody in a company where AI is being discussed and/or objectives have been discussed. This is proven

27:38 really interesting, actually, because there's a lot of meat on that bone. There's a ton of information that you can get really quickly now about a particular customer, a particular account, in terms of how they're thinking about AI, how their business is organized around it, who's helping them with it. For example, one company I put into this purchase and intent signaling thing that I built kind of pulled out that Deloitte is a big consulting partner for their technology purchases. I didn't know that. Well, I also have a relationship with Deloitte, so now I have an opportunity to go to Deloitte and say, "Hey, there's an

28:18 interesting opportunity for us maybe to work together at X account." I would have never have seen that had I not popped account name into this purchase and intent signaling thing that we built. That's kind of a rudimentary thing. Have you heard of this thing called a go-to-market engineer now? Have you heard about this role? Of course. Yeah, we have him here at LeanScale. I want to learn from you on this. If we can have a conversation about it. Great to share. Because, again, the world of top of funnels also changed. We're doing the traditional sprinkling money around all the different

28:55 kind of paid advertising sources and all of these different things, but I want to learn from people that are actually practitioners of how to use AI for the very top of the funnel, and I'm super interested in that conversation. I think that we're only touching the subject. We're not experts at it yet, for sure, and I'm all ears. Yes, so a few different definitions of go-to-market engineer, and I think people will put that label on a few different set of tasks and roles and responsibilities. The common one is going to be the top of funnel engineer, if you will. They're doing everything they

29:39 can to get the right contacts, understand intent signals, turn those intent signals into hyper-personalized outreach, and I'll give you some examples of what's working and what's not working, because I'm sure your inbox is getting hit with a bunch of stuff that's not working, and I'll tell you the difference, and then integrating the systems to move it along into the sales process. Now, our term of go-to-market engineer takes it a little bit further than that. Yes, top of funnel activities, but we think there is so much opportunity in the middle funnel, and I actually think there's more opportunity

30:14 for AI here, and we're using it for ourselves as an example. On the top of funnel side, because you can do so much research, like you mentioned, you can learn so much about what their pain points are, what they're likely going through right now, what are some buying signals, and what I think a lot of people are missing is you have an opportunity to really put together a POC, give you an example. We will put together an entire personalized go-to-market infrastructure roadmap for a company after they've raised around, so we can see what their GTM motions are before we even talk to them. Now, bad

30:58 personalized outreaches. "Hey, I saw that you like Scott's LinkedIn by my product." That's horrible, and everybody's getting-- I thought you raised 50 million. Talk to me. Yeah, congrats on the fundraise, and I'm sure they're getting that a million times too. Now what's a little different is congrats on the fundraise, I built you a personalized go-to-market infrastructure, thought you would be interested, take a look, and I can get their go-to-market buying motions. I understand the product they're selling. I can probably put together a pretty good ICP personas, build a TAM analysis for them. I can tell them what

31:34 tools they should be using at the stage they're in. I can go see how many salespeople they have and what problems they're likely experiencing, and I can put together an entire roadmap for them. Automate it. I don't have to do that. A good GTM engineer on the top of Funnel side is going to help. I think there's the art and science to it. The science is automating the signals, automating the development of this, and then getting the outreach teed up so that somebody can send. And then the art is what would actually be valuable? What would actually get their interest? I don't want to just show that I'm running some script.

32:09 I want to actually give them something valuable. Yeah, interesting. That's top of Funnel stuff. But the middle? I get more excited about that. I think there's SOWs. What's your definition in the middle? I think opportunity to close. Okay, so sales qualified opportunity to close. Okay. Sales qualified opportunity to close. There's so much logistics that need to happen during this time and so many things that you can create, especially if you have a POC process. So a couple of big wins, automated SOWs, take the transcripts from the calls you've been having automatically put together the SOW, especially if you have a SOW for a POC, if

32:50 there's going to be value-based pricing things baked into that, all the conversations you're having, you can build the skill to follow your guardrails, get your design, and then get that out. We get SOWs turned around in minutes. Now, that's one area. The other one is deal coaching. You can get some generic stuff from Gong and other tools, but if you develop your own, you know what your reps need to be coached on, and you know the very specific nuances of your company. So that's a huge one too. And then if you're running any type of POC process, for us, it's a GTM diagnostic. So we plug into Salesforce, HubSpot,

33:29 Adio, whatever CRM they're using, and then we will tell them, "Hey, this is the infrastructure you need to implement, so you can report on XYZ. These are the tools we don't see connected," but we built a platform that can automate that whole process. Something that would normally take us about two weeks to do, we can now do in about an hour. Yeah, that's pretty cool. Yeah, we just went through a pretty fantastic RevOps Pro that I get to work with every day. And one of the pain points that I deal with day in, day out, is, and this has been going on for 25 years, is keeping the CRM clean and keeping it updated. It's a never ending job.

34:08 Yeah, it's never ending job. But there's opportunities to take some of that work off the hands of the AE's and auto populate some really important information based on signaling that we're getting. So for example, I came to our RevOps guy, Tyler, and I said, "Hey, is there a way for us to be able to auto populate Medic from Gong transcripts?" And sure enough, after a long period of time, back and forth with Gong or whatever, we actually got it syncing and working. It's fabulous. But what I did is I also kept rep input for Medic, and then I also used Gong input for Medic in HubSpot, and I do a compare and contrast

34:55 just to triangulate information to see what's actually happening in the accounts. It's fascinating though, the opportunity that I think that we have with the amount of information we have access to really get hyper focused on the important bits to help run our businesses. You know what I mean? But Medic, as you mentioned in the opener, is something that I obviously prescribed to have been a practitioner of it for my whole career. I think it's more important today than ever before. And because of the amount of chaos we're dealing with in sales profession, specific to B2B sales, I should say, qualify that. But I'm happy

35:36 to kind of open that kimono too if you want to talk about it. Yeah, I think it's more relevant than ever to have a methodology of qualification. And I love that use case. We've deployed that use case through Gong and through just Claude and Salesforce or HubSpot too, to automate that information flow. Because before, if you implemented Medic or MedPick, you'd be relying on the reps entering accurate information. And it's completely biased, especially your bad reps. They're going to be leading some of it sometimes. But now, it's pretty objective. One, which I think is a unique thing of the

36:18 environment right now, for the most part, sales conversations are being recorded. And there was a long period of time where that wasn't even the case. Or if it was a high profile one, you'd kick the recorders out. But I think just culturally, I assume every time I'm talking, it's being recorded or filmed or going to get posted on TikTok somewhere. So now, it's like, wow, we have not just gold, but diamond value in those transcripts that make qualification methodology even more valuable. Yeah. Yeah. And you're right. I don't want to be spending time an hour a week with each rep digging into these things. So if I have

37:08 a way to capture it based on conversations they're actually having with prospects, that's a gold mine for me. It helps me with coaching, but it also helps me with how to develop a sales process that actually works for our business. It's really important. And see where we have gaps and see what we need to tie down and see where we need to enable better. And information is power. And I'm a big proponent of leveraging all of the data inputs we have and getting it into a place that's well organized and that's usable, fast. I think speed's really important. So yeah. Maybe for those listening, why med pick over another methodology? Because

37:55 there's a few others that are out there, but why do you think it's had such a strong dominance and if somebody's not using it, why should they? Well, for me, it's all I know. It's all I've used. I think about it every day in business and in life. So it is a practical way to qualify anything. Interestingly, one of the exercises we're going through right now as a sales function is again, meeting the needs of the buyer. Okay. Keep the buyer's interest and have empathy for the buyer in mind. So I get asked a lot like, okay, tell me about medic and what's the most important acronym or what's the most important letter

38:36 and medic in your eyes? And they're all relevant. They all matter. They can all come back to bite you when it comes to closing a deal if you don't have them covered. But obvious answers can be no champion, no deal. If you don't have a very strong champion who has power and influence to sell for you when you're not there, never ever has a software contract been awarded without a champion, a true champion. Okay. Just keep that in mind. So that's an obvious one, but maybe a less obvious one is one of the D's, which is decision criteria. So in this world of chaos that we're dealing with in AI, again, with empathy for the buyer,

39:22 they don't know how to buy, you know, these kinds of solutions. We have to be commercial teachers, you know, as a profession and we have to help educate, you know, okay, what's the best way to evaluate one vendor against another vendor as it relates to the business problem you're trying to solve. That's the basis for decision criteria. So by definition, decision criteria is the shopping list of things that the capabilities you need in order to solve business problem. So for example, we've created now a scorecard with all a long list of critical capabilities required, right, to solve the things that we're solving for

40:04 in HR, making it completely editable. We're making it a weighted scoring system so the customer can create, you know, can prioritize the scoring system the way they want to based on priorities and the capabilities they really want and need in their business. And having a scorecard like this does a couple of things. One, it saves probably 45 to 60 days of the buyer's time trying to figure out how the heck am I going to evaluate company A versus company B versus company C. Like how do I even do this, right? So we're leading from the front from that perspective and just giving them an idea how to do this. Secondly, when

40:46 you do this, you're creating a truly objective measurement opportunity. It's a weighted scoring system and its capabilities that you believe are important to solve a business problem, okay? And when you remove all subjectivity out of the equation and you kind of rely on these critical capabilities that are part of the decision criteria, now you have something that you can convey, discuss, talk to, talk about with other stakeholders in your business in terms of here's how we evaluated these three vendors for the problem we're trying to solve, here's the scoring system we used, completely objective, and here's who won.

41:30 And the rep that influences decision criteria, right, successfully can't lose. Think about that. I believe the reps that influence decision criteria are the best reps, period, right? Developing champions is a given, right? If you haven't done that or you can't do that, you shouldn't be in the profession. The next level though is how do you help the customer with the shopping list? And how do you manage the list? And how do you give them a way to objectively measure and compare vendor A, vendor B, and vendor C? You will be thought of as a thought leader. You will be thought of as somebody that's helping the buying community

42:22 figure out how to evaluate these things. And by the way, you know, this scorecard we've developed is completely editable. It doesn't have WISC's name on it. It just has a whole bunch of critical capabilities, a weighted system, and an opportunity for you as a customer to use it however you want. But we're giving you the things that you should probably consider as far as critical capabilities as part of your purchasing process. Does that make sense? This is so smart. And I'm taking notes because I think a couple assumptions I make as a seller. And I think I've done okay in this area, but I'm like, okay, I'm getting some coaching

43:06 from Scott right now. This is where I think I can improve myself. I think people give the buyer too much credit that they know how to buy and that they have a sound decision criteria. And I think it's more than often they would think, okay, extracting what is your decision criteria. And then I'm going to try to play to that. I love how you completely flip the script and say, I'm going to develop the decision criteria. And I think it does put you in that position, one of confidence to say, Hey, there are other alternatives. If these other things are important to you, you should probably go with them. But we know

43:44 we dominate this lane. And if you're in this category, we're going to be a good fit for you. And I think that's fantastic because I can, I can think of a number of deals where I know the buyer didn't make a good decision and I don't think they were equipped to make a good decision. And then they have failed and then come back said, Oh, it didn't, this didn't work out. And it's like, I could have guided them better at the front end of that process. It's likely Anthony, they were influenced by somebody else, something else they heard, some demo they saw somebody they talked to at a conference, some third party that gave

44:22 them, you know, you know, the advice. I tend to try not to leave those kinds of things to chance, you know, so help the buyer, the rep that sits and waits for the buyer to give, to give them the criteria is a sitting duck. How, I mean, think about it. How, how does a buyer actually gather information on how to make a decision? They're talking to us. They're talking to advisors. They're talking to peer groups. They're, they're reading information online. They're doing chat GPT now searches, you know, Google searches. There's a lot of information available that can help guide a buyer today in terms of what's available.

45:16 But that doesn't necessarily help them understand actually like what's really important to look for in these solutions that map to your problem and your pain. You know, and I just, I firmly believe that the best companies are going to do a great job of helping the buyer kind of avoid the landmines, lead from the front, be confident, like you said. And, you know, I just, I'm just a huge believer in influencing decision criteria as best as you can. Yeah. Well, I think after this conversation, I'm hopping in a cloud code to build our decision criteria card. So you're leaving me inspired. Are there any other, I use plot to build the

45:56 first version of what we're using. It was incredible. I gave it a pretty specific prompt and the output was like, wow, this is unbelievable actually. And we're obviously now iterating on kind of the first version of what it spit out. But gosh, you know, how much time did that save me? Yeah. How much time? And then would you get to the level of quality? I think that's something that AI is really unlocked. Like even if I spend the same amount of time, I'm going to walk away with something much better than if I just manually did it. Yeah, exactly. Really cool. Are there any other counterintuitive or non-obvious insights like

46:39 that? I'm in the sales student seat right now. So are there any other parts of the qualification process that people underestimate? A couple of things. So one, understanding who the economic buyer is, is more important today than ever before. For us back in the day, CHRO was our economic buyer. And the definition of economic buyer is discretionary use of money. Can say yes or no to your deal. Okay. So by definition, CHRO in terms of what we were selling previously was our economic buyer. They had the authority, they had the budget, right? And could move money around to make it happen. Today, I think that that has shifted a bit. Now, this doesn't

47:30 lessen the importance of meeting and being with the CHRO every step of the way. I mean, that is like they are our customer. We hold them dear. IT is, I believe, in what we're doing truly making an impact to the point where I believe in some cases, if not in many cases, they are the new economic buyer, even for an HR sale. So just understand the shifting landscape of how decisions are being made in an organization. The old tried and true of mapping an account and understanding the power base in an account still holds true. But you have to understand all of the different constituents involved in the selection process

48:14 for AI. And it has definitely gone horizontal, right? It is traversing different organizations. And it's really vital to understand. So where you think you may have covered kind of the economic buyer rung of the medic ladder, don't be surprised if IT isn't really involved in saying no to the deal. We've seen it actually at our own company. So that's one. The other is decision process. So again, customers don't necessarily know how to buy or what to look for or what capabilities actually exist that are real. So decision criteria is super important to help them with. But how are you going to go about actually purchasing a solution? And

49:05 what we're finding is sometimes they don't know or sometimes they're feeling it out themselves. I feel like most of the time they don't know. I don't know if you run into that. It's very rarely, oh yes, we have a quarterly committee meeting and this is where we're going to approve the funds and then we're going to deploy. Right. Rarely found that. We've been in situations where customer says buck stops with me. This is where it goes. I just need to go to legal. Probably have a security review. IT might want to have a conversation. It turns out it required AI committee approval. It required two other steps that even the buyer didn't

49:47 know existed. So this is part of the chaos right now of selling an AI solution into businesses is because there are no standards and there is no standard purchasing process either. So just know that going in that there's going to be some ambiguity here that you're going to have to mitigate and understand as much as you possibly can and try to be helpful. Is there anything in this process where you can provide leadership and guidance if they don't know what their process is or is this still kind of left to the customer? It's a good question actually. We've gotten in front of this a little bit, especially

50:29 with our HR buyers and CHRO. We're just kind of telling them, here's what we've seen come around the corner that you may not be aware of in terms of actually getting to a contract on what we're doing here. IT is coming. In some cases, maybe HR tried to avoid the IT conversation. We're saying, no, no, no, no, no. Do not avoid it. Let's get ahead of it. We have answers to all their questions. Just bring us in. Understand that there are committees that are getting organized and each one of the people on that committee has a different set of needs that they need to check a few boxes. The internal selling that your customer

51:16 actually has to go through today is more complicated than it used to be. I preach to my team all the time that we have to prepare our champion for all of these different conversations. We build champion decks. We anticipate the objections and the questions they're going to get in the contracting process. Anthony, what we've seen, interestingly, is back in the day, we could get selected and then move right into legal and we'll close the deal 15 days later, 30 days later, whatever. Moving from selected to contracts today is double that at least. Yes, you guys are who we want to do business with. We're really excited.

52:00 Let's go. Then there's delay, delay, delay, delay. It's because there's a whole bunch of conversation happening internally about how the solution maps to what they're trying to do and all these other things. It's very complicated for the consumer of your products today. Just recognize that and be helpful to them. Help them see around corners. That's one of the things we're doing is we're trying to guide our champions to say, "Here's what we've seen through multiple deals now. Here's what you're probably going to be faced with." We can help prepare you for those conversations. It's pretty wild, pretty amazing actually

52:42 what's happening. Well, you can send me the invoice for the coaching session. I really appreciate it because I am learning a ton and I think this is going to be relevant to anyone listening to this as well. We're working with B2B SaaS and AI companies. We're working with a lot of infrastructure AI companies where they're early amazing technologists of course but getting into this level of sophistication of selling, it's very difficult to do. One last question and maybe I can pick your brain on, get some guidance on. This is maybe going to be for my founders out there. As they're getting traction, post the seed stage,

53:27 maybe they're prepping for a Series A or just had a Series A, they're at that earlier stage. Usually a lot of founder-led sales stuff going on. What is your thesis on building out the go to market team and investments? Do you like to bring on serious leadership first, executors first, certain roles you'd like to bring on? What's the build order if you will? Sales, marketing, customer success, that whole thing. How do you stage that as a company scaling? I'll tell you what we did at Glint and what we've done here. Jim Barnett, fantastic founder-CEO. In both cases, starts with the leader of the function first and builds around the leader.

54:11 Once the leader comes in, so for example, I come in to manage the revenue and go to market, I have non-negotiables. I have to have RevOps, I have to have it, and I have to have enablement. Those are usually my first two hires. I tend to be early stage. I just really love the thrill of the build process of an early stage company. I'm doing some selling, but I'm building the function to be able to support hiring AEs and getting them up to speed and ramp as fast as I possibly can. I want to clarify that just to abundance of clarity. When you come in CROC, RevOps first hire. This is all before you bring on a single agent.

55:02 When you hire me, there's an expectation you're also hiring somebody in RevOps and somebody in enablement. That's my team because that's where the function gets built, and then we add AEs. Now, we can do it in parallel. Say the plan calls for adding one or two AEs in a quarter or two quarters, great, hire them, but let's have RevOps and enablement ready to roll. That's worked really, really well for me. I want AEs coming in, hitting the ground running. We're a well-oiled machine. We know what we're doing. We know who our market is. We know who our buyer is. We know our message. My

55:49 job at that point is to ramp an AE as fast as they possibly can and get them to productivity as fast as they possibly can. That's my job. If I don't have RevOps, if I don't have enablement, there's a time lag to productivity. It's proven. When you start to think about investing in your go-to-market function, getting away from founder-led sales, it's far more of an investment than you might realize. It's more than just hiring an AE. You have to build an ecosystem around them to support them to be successful. That's an expectation that I've set through my career. That's worked really well. Does that help you?

56:30 I think it's really very sage advice. Even though I had glimpses of this, because I ran RevOps for three companies before starting LeanScale. I knew the importance of having the infrastructure before bringing on an AE. When I started LeanScale, the first thing I did was bring on an AE, and it didn't work. Sometimes, some of those lessons you have to learn the hard way. You see this gray hair? You see what's going on here? I was like, how did I do this? I've seen this movie. What am I doing? I think that's excellent advice. For companies that are really getting into that stage, I love the idea. Let's set

57:12 the foundation. Let's keep that AE team lean. Let's keep them full of pipeline, full of resources to help close, and just get them crushing their quota every single quarter. We're lean here. We keep it lean, but I've got really great sellers. We've done a really good job hiring great people to a profile based on what we're selling. Enterprise experience, multi-threaded sales, chaotic environment, all those things, early stage experience, it all really matters. Let's set them up for success. That is vitally important. When AEs ramp fast, the whole company gets energized, by the way. Invest in the infrastructure to

58:00 get them up to speed and get them going. That's my big advice there. Will Scott, this has been fantastic. Thank you so much for diving deep on all of the complexities that the world of AI is bringing, giving me a lesson on helping the customer make the decision and navigating that decision-making process. Then I love your advice on the build order of going from founder-led to making those early investments. I think it makes a ton of sense. I appreciate everything you're doing and I hope to follow all of your content and things that you're doing in the future and just see everything that you accomplish

58:38 next. Thanks, Anthony. Back at you. It's a good conversation. I appreciate it.