Name: RevOps, reinvented: How AI is changing the game
Uploaded: 2025-05-14T18:31:11.427Z
Duration: 59 min 32 s
Description: RevOps, reinvented: How AI is changing the game

Transcript for "RevOps, reinvented: How AI is changing the game": Hi, everyone, and welcome to today's session. I'm delighted to introduce Ken Babcock of Tango and Cliff Simon of Carabiner Group. He'll be giving today's talk on RevOps Reinvented, How AI is Changing the Game. Without further ado, I will pass over to you both. Awesome. Thanks, Will. Thanks, everybody, for joining today. We're we're psyched to have you just as a way to kinda bring everybody together, do some quick intros. My name is Ken. I'm a cofounder CEO of Tango. We started Tango in 2020. You may have heard of us initially as a documentation solution, but we're here to talk a little bit more about also what we're gonna, what we're gonna what we've launched in the last month and what we're gonna be doing to help you with your CRMs and help you kinda reinvent the RevOps function. I'm pumped to have Cliff here. Cliff, do you wanna do a quick intro? Yeah. I'd be happy to. Hi, everyone. Cliff Simon. I'm the CRO of Carabiner Group, a part of SBI Growth. Been in the RevOps space for a bit now. Actually, Carabiner got started in 2020 as well. Had a nice little ISA last year, and now we are continuing to help companies when it comes to how you think about revenue operations and how that actually gets executed. Awesome. In the, in the lead up to this event, Cliff, I feel like all the promotion and all the registrants were like, oh, I know Cliff. I have to go see Cliff. I was like, oh, man. This guy's like this guy's a legend. So excited to hear more from Cliff as we get going. We're gonna make this interactive today, but I just wanna go over a little bit of of what we're gonna cover. You know, I think, ultimately, how this is gonna flow is we're gonna sort of survey the scene. We're gonna set the stage of, like, where rev ops is today, what it is that a lot of you who are in this role are feeling, are are hoping for, are wishing for the future of, you know, your function, your role, your careers, and how we've kind of identified at a uplevel that a lot of the things associated with systems, tooling, collaboration. Big thing that we talk about a lot at Tango is the precision problem. So we're gonna go in detail on that. Cliff's gonna walk us through, you know, the traits of of high functioning rev ops teams, and then we're gonna talk about a little little bit of the Tango solution and where we play. At the very end, we'll leave some time for q and a. But I encourage everyone to stay active in the chat, ask questions of each other, answer questions that we're gonna ask. And then for those big heavy hitters, you know, you can save those at the end, and we'll we'll answer those live. So just to to get everything started, we have two questions here on the screen. What I'd what I'd love to do is, you know, feel free to answer one for both of those in the chat. We're monitoring the chat. We see the chat. But the first one being, which process in your CRM is most prone to error? You know, and if you can define that discrete process, that helps us a lot too. And then two, how many ancillary tools support your CRM? If the CRM is like the nucleus of all your tooling and systems, what are all the tentacles and what are all the things that that sort of come into that? So I actually wanna ask Cliff, you know, based on your experience and based on, you know, the the help that you provided companies, which processes within the CRM are are most prone to error? I think the ones that we see the most are the places where you have a hand off between different go to market teams. So marketing to sales, I think everyone knows about, in sales and to CS or the implementation team. I think those are the places where we see the biggest amount of friction because you're going from one person within the organization to another. Sometimes there is a process for that. Sometimes there aren't. Sometimes you've tried to create systems and automations around those processes, but then people leave or something breaks and, never quite know how to get it right or how to fix it. Yeah. Totally agree with that. I think, you know, this, like, collaboration across teams, which is really common, You end up having different vocabulary. You end up talking different languages sometimes, and, you know, what one side needs maybe doesn't reflect what the other side needs. And so it's sort of this, like, translation. And maybe you're maybe you're working across tools. It can get really complicated really quickly. So I'm I'm taking a look at the chat. We we see some of those. Right? Marketing attribution, forecasting. Forecasting. That's a big one, that we've heard a lot, you know, where sort of your systems maybe aren't talking to each other in the right way, and then all of a sudden you have this forecast based on all those, you know, data quality issues or those systems that aren't talking perfectly. And your forecasts is just really hard to trust. Matthew says lead sources. Good stuff. Well, we're gonna keep moving along. I think we'll we'll talk a little bit more about each of these things. For us at Tango, you know, what we have seen is a a tremendous amount of impact when organizations are leveraging AI powered sales automation. And I think some of these issues that we're talking about, some of these broken processes, some of these data inconsistencies can be solved in that way. But before we even get to the solution, I wanna talk a little bit about, you know, where it stands across orgs. We see kinda two things, and I and I'd orient you to, like, two sides of the slide, mindshare and opportunity. In terms of mindshare, you've probably all seen or felt this. Executives, sales leaders are, you know, be beating the drum of AI pretty loudly and pretty consistently. They know they need to adopt AI. They know they need to invest in it. They know that it's it's not just a threat to, you know, how they run their internal operations or, you know, what might come and replace, like, kinda what they're doing. But it's also a competitive element. You know? The the companies that they compete with that adopt AI and are able to move faster. They're able to, you know, interact with customers more frequently, more comprehensively. Like, that that is a huge threat. So the mindshare is there, but the opportunity still exists. We are by no means saturated. You know, half of enterprises are saying we deployed at least, you know, maybe one model or one solution in a function. That's still, in my opinion, pretty low. And then a stat that you'll see us sort of flip on its head a couple times is that within sales organizations, only 28% of a sales rep's time is spent selling. And, you know, the flip of that is this 72% of time spent on nonselling work. So what is that? Administrative tasks, reporting, follow-up research. Some of that stuff is necessary, but a lot of that stuff can be be replaced by, you know, the right AI solutions with the right guardrail. So you're all here because you've opted into this conversation. We're gonna talk more about what that can look like for you. More on the current state, you know, particularly for these rev ops folks, leaders like yourselves, there's sort of this contradiction. Right? You're expected to be strategic. You're expected to push your organization forward, really rethink how you're leveraging data, how you're understanding your accounts, how you're progressing opportunities and managing your pipeline. But the reality is is, like, you're stuck fighting fires. Fighting fires is the is the term that I've heard so many rev ops leaders talk to us and describe their day to day. And so that strategic stuff, like, it's put by the wayside because you're you're solving support tickets, you know, for your sales reps. You're adding fields, you know, to your Salesforce instance. And so this rebalancing and what what we're hoping that Cliff Simon and I can talk to you about today is, like, what will it take to sort of rebalance so you have a healthy mix of, like, making sure all the tooling and systems are working together, but also you can get to the strategic prod projects. Cliff Simon, I'd love to hear from you. You know, as a CRO, you know, we talk a lot about we we chat even prepping for this. You know, the playbook has changed, with regards to AI. How would how would you characterize that? I think it's interesting if you're just going back to some of the stats that you laid out. Right? 50% of companies are using AI in what some way, shape, or form. Most of that's in marketing. Right? Just constant generation. The people buying or did not scratch the surface on this. Our CEO is at an event, with a bunch of other CEOs of, you know, larger sized companies, hundred million plus. Right? And there was someone there from the, innovation lab over at Accenture talking about how they're doing all these amazing things with AI. Mind you, it's like a 30,000 person part of their organization. Right? And when asked about how they're using AI, it's like, yeah. We've we've got some marketing use cases. Right? Like, wow. You're you're driving innovation. You're supposed to be at this massive firm. But, most people, even at the highest levels, haven't figured out how to get this to be something that they're actually enabling their teams to do, how to set up processes around it, and how to be able to measure the ways and the ways that that's actually helping drive the different parts of the go to market and the value creation story that those companies are trying to tell. So yeah. Just quick aside there. As far as, like, how the playbook's changed, it's changed quite a bit. Right? We're no longer in a growth at all cost moment. Money's not free. So how do we think about getting the most out of the teams we have, and how do we get the most out of the people that we're onboarding? I think AI is an incredible tool to build up that foundational layer. From a RevOps side, most early companies don't have the capability to go out and get all the pieces that they need. Right? Even from a personal perspective, I can't have a strategist and an architect and a data person and system admin, let alone across the entire stack. Right? You guys talk about how many tools there are. I think on average, our customers are using something like 74 pieces of technology that that touch the CRM and that hub and spoke kind of model. Right? And it's usually several hubs and several, several wheels that are all come together like, more like a set of gears. Right? Really challenging to be able to have one step of processes that manages all of that and to have one strategic vision that pulls that all together because there are so many different stakeholders. And even if you get it figured out from a technological perspective, you still have all the politics that go back forth within the organization, who owns what, who's in charge of what process, who gets the final say. Right? So there's all that interpersonal stuff that you have to worry about too. But when it comes to, like, the actual adoption, whether it's forecasting, you're using it for pipeline management or deal execution, there are ways to be able to use AI to help you drive all that in a much more consistent basis, which for most teams is what they really need. Right? You just need the consistency of thought and, the actual repetition same thing over and over again to start building those really good habits. And once you've built those habits, it becomes a lot easier. And the AI solutions that I just say are really good for that. I think about, like, if I was to come into an org brand new as a CRO, what could I help affect within the first ninety days? Right. Tenure of a CRO is pretty damn short. You know, fourteen to eighteen months, typically. So the things that I do within my first ninety days are really gonna set me up for what I'm expecting to see. Again, based off of your sales cycle and your ACV, what I'm gonna hopefully be driving within the business in around month six to month nine, all of the all the foundation for that needs to be set in my first ninety days. And I think with the AI capabilities, I can get around for forecasting and help level up the team. I can help drive better data entry within the CRM. So now those fields are being filled out. We can have meaningful discussions about where my rec should be spending their time and energy. We can help get deals out of the pipeline. Winning is really important. I think it's even more important to understand where you're not winning and where to stop wasting your time so you can focus on the customers that actually matter. Right? There there's so much that we can do from just a foundational layer that that helps drive really good behavior sets and and good outcomes for the people that work for us. Yeah. I love that, Cliff. I think we've all probably encountered the, you know, the overly optimistic rep that you know, where the deal results in the long no. And there's an opportunity for us to also just get more objective, like you were saying. Like, what's what's working? Let's double down on what's working. Let's double down on the customers that make the most sense for us and not let subjectivity get in the way of what we're doing. I think it's a really good point. As it relates to AI, I think I think one of the things that, contributes to the fact that maybe you're only seeing this in marketing or maybe you're seeing a lot of but not a lot of execution is, there tends to be kind of this this polar ends where we we see companies coming in. They're like, well, in order for me to adopt AI, I have to, you know, adopt one of these AI first CRMs. Right? I gotta rip out Salesforce. I gotta go the the Klarna path and rip out Salesforce and build our own thing or rip out HubSpot and build our own thing or adopt one of these tools like Attio or DayAI, that's a really high hurdle. Like, there's a lot of super valuable content and insight living in your CRM. And so that high hurdle, I think, prevents teams from really thinking about, okay, is there an approach that's maybe less than that? And, you know, we're not here to advocate for the status quo, so we'll just we'll just throw that out entirely. I think this middle ground is where where a lot of rev ops folks can make an impact adopting AI tools. It's really what we call layered AI, tools like Tango, what we've built, where you're working within your existing CRMs, your existing workflows, and streamlining those in a way that gets you sort of immediate benefit, not just so not something where you have to completely rethink everything that you're doing. And then eventually, you know, that helps you hit the building blocks to to build something really meaningful. So I wanna pause. We've been we've been talking on a lot. But on a scale from one to 10 and just throw a number in the chat. If you wanna elaborate, that's great too. How well is your CRM serving your sales process? And if if, if you're also not shy and you wanna share your CRM, that's great too. We're gonna go from a scale of one, you're struggling. CRM is the the bane of your existence. And 10, you're optimized. Everything is fully aligned. We have this incredibly unique sales process, and it comes through. It shines through in our CRM. That's kind of the scale I want you all to operate at, and and give us give us a number and give us some detail. We got an eight. I'm seeing six, four, five. We got a one. We got a one out there. Nice. Okay. Okay. So yeah. Fair yeah. Probably extremely honest. A lot of stuff kind of in the middle ground. And so, you know, I think this also plays into what I was sharing earlier where, you know, you're not gonna get rid of these systems, but you know there's a tremendous opportunity to to get more out of them. And so, you know, with the exception of of the person who shared the one, which I'd love to talk more about that too, we have an opportunity to take these things from a five, six, seven, maybe up to an eight, nine, or or even a 10, right, if we adopt this sort of layered AI. Cliff, I'm curious. Where would you say, you know, most of the customers you work with? Where where do they kinda fall on this scale? Is it reflective of what we're seeing in the chat? Just just looking at, Craig's comment there in the chat, you know, it's a data repository. Salesforce was designed for the executive lay level. Right? It's designed to be a reporting structure so that the people who run the business can have the data that they need to run the business. It was never designed for the front line. And where you see sales teams executing well, by and large, it's because the people within the business have said, we want to set the tools up in such a way that it actually serves the people that are using them. Right? If you think about user adoption and the workflows that people go through on a day to day basis and you start delivering solutions for them to do their job better so that they're not spending three hours a day doing admin in Salesforce, you're gonna get a happier rep. You're gonna get a rep that can actually go out and do the thing that you've paid them to do, which is to go and build the relationships, go out and understand your product, understand your customer's need for that product, and to be able to go out and articulate how those things come together. Ken. When you ask across the spectrum here, we do health assessments for most of our customers around where their staff is today, not just CRM. But I'd say, you know, obviously, CRM is the biggest linchpin in it. On this scale, most of them would typically fall somewhere in a three or four. Yeah. Yeah. Which is wild. Right? We've done a really good job as an industry of stitching together middleware. And not only that, but, like, you know, you talk about any other category of software. If you were in the three or four, you know, routinely in that range, you wouldn't have the market share that some of these companies have. I mean, it's really unbelievable. We've been kind of, like, tolerating, the chaos that it's creating for our orgs, and and I just I I feel like there's there really is. I keep coming back to the opportunity. There's such an opportunity to make this even functional. Right? Even just get it to a five for a lot of folks. We're gonna keep moving. I I think, you know, there's a lot of numbers on this slide, obviously. We had a lot of numbers shared in the chat on the last question. You know? But I think the reason that a lot of folks are saying it's a three, it's a four, it's a five, maybe a six, is because you know you know how it's impacting or maybe you haven't seen these stats before, but you've seen kind of this impact maybe intangibly. I mentioned that stat upfront. You know, 2028% of time sales rep's time is actually spent with customers. That's this is the flip of it. Right? Non selling task, 72%. And, you know, there's other stats too that support this. You know? Data is incomplete. Companies are losing revenue. And what we've seen at Tango, if you actually look kind of at the bottom left, you know, we've seen over a million workflows built on tango, even just on the documentation product within CRMs. These workflows are super complex. Some have more than 50 steps. We even have data kind of around how people have been able to successfully apply those workflows and whether they've been able to replicate them. Those numbers are low, and so that to us was sort of a a signal to say, hey. You know, these are complex. The adoption is low. How do we actually start executing some of these workflows on p a lot of those those ratings you gave out are kinda systemic from from what you're seeing here. And I just wanna paint a picture of, like, what that actually looks like. You know? What what do you mean when you say 44% of companies are losing 10% or more of their revenue? Let's look at this in real life. Imagine, you know, we take that kind of, that sales rep. Let's jump in the shoes of the sales rep. You just get off a call, then you go to the CRM to actually update the opportunity. You know, your notes are not going to be fully representative of the conversation that was had. It's not gonna be fully objective. It's gonna be largely subjective. There's there's some great stats from Gong out there. You know, the average sales call is 6,000 words, and then we expect the sales rep to come in and summarize it in six words. Right? And so you're missing stuff. And what happens when you miss stuff? Things progress when they shouldn't. You know, that optimism sort of takes over. Your forecast are not based on an objective assessment of the opportunity, and you prioritize in a way that doesn't actually represent what has the highest likelihood to close a deal for your business. And then, you know, some of those will get through. Some of those deals will get through anyway, and then you have kind of this chaos where, you know, maybe the use case that was captured in the CRM doesn't actually reflect what was the most burning for the customer. Maybe it was something they just mentioned offhand. And, again, coming back to Cliff's point, we have these go to market handoffs where you go from sales to success or sales to implementation. That's another layer where the CRM does us a disservice. So it's very real. These aren't just numbers we're throwing at you. You've probably all seen this fallout play out in real time. Cliff, I know you wanted to ask a question of the group. So so maybe maybe give a little bit more context to this slide, and and I'd love to see people's responses in the chat. Yeah. I'm always curious. Right? There's a significant amount of friction within CRM, but we get varying responses from folks that, well, where does that actually come from? Is that because your team doesn't actually know how to use it? Is that because they refuse to? Is it because you've got bad data quality and you have a really hard time even doing simple things like territory segmentation and then using that ultimately, like, to create coding plans, or is it just too difficult to use? Right? Do you have an overly complicated CPQ set up? Do you have difficulty when it comes to how your lead driving works? Like, I'm just curious. Like, what are the things that make your lives miserable? Yeah. So if you could jump in the chat, data quality is one, complex workflows is two, adoption issues is three. What's what's the biggest source of friction for for folks out there? Alright. We got a one and a three. One and three. And oh, we got a two. Okay. We're all represented. Lots of one. Lots of data quality issues. One one one, two, three. I love that. The full the full pie chart. Amazing. Well, let's you know, Cliff, I know this is something that you're pretty passionate about. And and the reason why if I jump back a slide, the reason why people are saying one, two, and three, you know, again, coming back to the current state, like, where are we starting? Where do we need to go? Can you talk a little bit more about this slide? Yeah. I mean, I I know. I don't even have to ask this question. But how many of you out there today feel like all you're ever doing is fighting fires? You're putting out tickets that are coming in from your sales leader, your marketing leader, your CS. You're trying to stay on top of it. You've got random Slack messages coming in from different AEs. All the while, you have a road map of things that you agreed to from an OKR perspective or an MBO perspective that you're gonna get done this quarter or this half of the year. They never actually get the time. I've seen it more more times than I can mention. And what ends up happening is there is a misalignment inside of the organization as to what the role of RevOps is. RevOps is not a ticketing system. RevOps is not just the person that fixes stuff. The role of RevOps is to be the interstitial connecting tissue that actually drives an organization together. Now your your Switzerland, I mean, there's so many different metaphors. Right? And what happens is when you're on that firefighter mode all the time, you can't actually do the things that matter. You can't help when it comes to that long term strategy, you know, the architect here. Right? You can't be the one that goes out to the team and says, you shouldn't be doing these things and coming to them in a what's the word? Like, a a glossier kinda way. Right? You you you win more with Honey than you do with vinegar. Right? Okay. You get to you get to help drive behavior changes because you're not coming in as the bad guy. But when you're stressed, we all come off as the bad guy. And when you're overworked, you come off as tired and you can't actually get to the things that matter. So, yeah. It it's really hard to be a rev ops professional and to get to the strategic piece, but you have to have a come to Jesus moment with your with your executive team and say, if we are trying to grow this company, if we have these strategic objectives, there's only so much time that I have available to be able to drive things forward from a day to day perspective. I need to be able to save, you know, 20% of my time to focus on these strategic goals. Otherwise, we're never gonna get to the place that we need to. We're always gonna be putting Band Aids on on situations. We're always gonna stop solve for the symptom and not for the underlying disease. It takes a little bit of courage and a bit of business understanding to have those conversations. But those are the really important conversations that need to happen so that rev ops stops being this tactical ticketing system that just gets shit done and actually becomes a business partner. Yep. I love that, Cliff. You, you know, you also had some some sort of traits, you know, not to steal from the book, you know, the the traits of highly effective people, but really, like, these are the traits of highly effective rev ops systems. You already alluded to some of them. Right? Like, get ahead of things, you know, be proactive, be the thought partner, you know, make things feel more streamlined. Are there specific ones that you'd call out here that, you know, in working with customers you felt have been absolutely critical to making that transition from reactive to proactive? Yeah. %. The eliminate the travel knowledge one is interesting when you put it in context with put the rep first. Again, way too often the system was not built for the reps. And far too many times, I see rev ops teams because they're overworked, because they're trying to serve the executive team, put things into the system. They never drive enablement. They never get buy in from the the people in the field. If you can do those things, right, talk to the reps, get their opinion on how things are gonna go, make them feel like they have agency and ownership of the systems, you're going to get better data quality. You're gonna get better user adoption. And once you have those two things figured out, now your trustworthy data is no longer a problem. You've already fixed the behavior issue. You're putting systems in place and processes in place so that the tribal knowledge no longer just lives with you. It's being disseminated throughout the rest of the organization, and now you can worry about trying to actually drive that into real documentation. But a bunch of these things start coming off the off the board as soon as you start driving, real ownership for the front end users. Yep. Love that. And, you know, we had a great question in the chat that was effectively like, okay. Well, what happens if I inherit a mature organization that is inherently react you know, probably has a lot of headcount. Right? The inertia of all of that can be can be really challenging. And so we're gonna start getting a little bit more prescriptive. We're we're telling you a lot of what you already know in the first thirty minutes here, but now it's really identifying where those problems exist and where a solution might be. And so, what I wanna start with, you know, we asked a little bit of, like, where's the source of friction. Right? So you're seeing data quality come up here again. Maybe maybe that's also your biggest opportunity, but we wanted to add a couple other options here too. So in the chat, let us know where do you see the biggest opportunity for more precision. However you define that precision, whether it's discipline, accuracy, you know, reliability, frequency. Is it data quality? Is it process consistency, forecast accuracy, or customer handoffs? You got a forecast accuracy? The above. I hear you, Samara. I mean, in a lot of ways, like, data quality is either, like, downstream or upstream of some of these too. So, you can forecast accuracy. Wow. Cool. Process. Process. Process. Awesome. Good mix. So at Tango, you know, the way we think about, you know, precision and and why teams are missing the mark and and, yeah, I think this lack of sales precision really does live in the CRM. And it's and it's probably, like, for some teams, the elephant in the room. It's probably the thing that, you know, we've just grown accustomed to accepting that, you know, we have a lack of operating on the best information that we have. So this is a little bit reflective of the story that I told earlier, but, you know, you have reps, you know, inputting inconsistent data. You have rules being ignored. You have, you know, these carefully crafted pipeline stages that you care so dearly about. But a lot of times, you know, people are taking shortcuts or they're claiming they have, you know, one of your criteria to progress an opportunity, but they don't. And so a lot of these signals are getting muddled. And so a lot of you said forecast accuracy. You know, when you start doing that, when rules are ignored, when data is incomplete, when your stages lose meaning, you just don't have an accurate depiction of your business. And we all know that delivering unpredictability, delivering to your exec teams, you know, what they can expect for a given quarter is critical. And so, you know, this is kinda how those dominoes fall and why precision just rarely exists in a lot of sales orgs. And that's not to say that you know, I mentioned discipline earlier. That's not to say that reps aren't disciplined. You know? They're they're they're bogged down. Yeah. They're trying to meet with customers. They're trying to complete things in between calls. They're trying to, like, call back to something from a call earlier in the day where they're like, I don't actually remember what they said. How did they say this? Okay. Well, let's put it in CRM. And so you have reps, what we say is, like, fighting the CRM, spending hours on it. They're not, you know, doing it at a time where, you know, whatever they input is gonna be totally reflective of the conversations that they're having. And instead of pursuing precision, they're they're moving for convenience. And that convenience actually creates then issues for ops and enablement where you are auditing your data quality. You're trying to triangulate, you know, why a rule was ignored or why an exception was handled in a certain way such that, you know, you can have confidence in that forecast, but it's just this vicious cycle. And that's where complexity in the CRM actually creates a lot of inefficiency. So simply put, precision is clarity. We wanna have clear expectations. You know, we wanna have those handoffs that make sense. We wanna have clear process that ultimately leads to objective, not subjective data that makes its way into the CRM. And then validation at the point of action. This is a big one. This is one where, you know, as time goes on, you know, it's harder and harder to audit the CRM and understand why an opportunity progressed when it shouldn't have. And so having validation sort of in the moment, whether that's rules that you built into your Salesforce instance or within those layers on top of your CRM, how do you make sure that the communication is happening in real time? Okay. If I wanted, you know, override a rule, am I giving feedback in real time that helps someone understand why I did that? And so that level of clarity, that level of understanding, that level of communication is what we define as precision. We think Tango has a pretty unique offering around hybrid automation. And so what does hybrid automation mean? You know, I think some folks have said to us, well, what is it a hybrid between? For us, the way we define hybrid automation is this idea of automating with a human in the loop, giving the sales rep, giving the rev ops person an opportunity to validate what's happening in real time, build trust and confidence in the automation, in the agentic workflow. And so for those of you who experimented with legacy automation, you know, maybe RPA or, like, a UI path or an automation anywhere, it can be really powerful, but it it has a lot of gaps. It works for simple linear repeatable processes, kind of the lowest hanging fruit of of tasks. It doesn't handle the complex stuff. And so what we've built with tango is something that is gonna help you handle those complex, messy processes because maybe you're not automating end to end, but you're designated, okay. Here's three decision points where I need a human to intervene, and I need that oversight. I need what we call real time visibility over how these automations are happening, and I need it to connect. I love what you said, Cliff, kind of the hub and spoke. I need it to to focus on my CRM, but I need it to also expand out to those 74 other tools that we use to pipe some sort of data into the CRM. And so that's where hybrid automation is very different, and that's why I think legacy automation for folks have said, well, you know, if we have the low hanging fruit taken care of, why would we, you know, why would we pursue automation any further? And so I am curious if you've experimented with automation in rev ops. And so give us a yes or a no if maybe help us understand how that's been going, if there's any tools you've been using, if you've been disappointed or satisfied with those solutions, we'd love to see what people are using and what they're doing. While people type their responses, Cliff, you know, where do you see your customers, you know, applying automation today? Is it is it sophisticated, or, you know, do you see it more in some of those, like, linear workflows? There's there's a mixture. I think the one of the easiest places to go is lead routing. Right? Being able to do that by product, by segment, by by geo. Great automation that I see a lot of folks doing too is always that hand off piece right from sales to the CSC. Part of part is do you actually have all the right data inside of the CRM to then be able to give a really good executive level brief to the the folks that you're handing that information off to. Totally. I think that's a really important one. Being able to drive the automation around ticket creation and setting the expectation for the customer. Like, this is what the next steps are. Right? The more that you can do as an organization to make them feel like they're working with your organization instead of working with this person, then that person. Right? Guide them through their journey. So anytime that you have the opportunity to use automation, to help them feel like they're on a journey, I think that's really, a way to win. So Yeah. Awesome. So we're we're about seven minutes away from from live q and a. Cliff, we have a couple more slides that that, that you're gonna cover, and I think, you know, what what we talked about in the prep session is, you know, what does rev ops actually need to execute on this? We're we're sort of painting this picture of these pie in the sky solutions, but, you know, maybe they're not so much pie in the sky. Maybe they're actually achievable. And I think RevOps is often promised like, oh, if you just do this thing, it's gonna solve all these issues. Help ground us in, like, what the RevOps function really needs. So it's interesting. We recently did a large, study on agentic CSM and SDR tools. Right? For the funnel funnel from back of house, what's real? What what is the state of the technology today, and how can that actually be implemented? And we looked at things like enterprise readiness, the, propensity for those particular technologies to affect the role, the level of capability around the LLM, and how much you could train it. And I think the long and short is there isn't a single silver bullet that exists. Right? And it's usually gonna be a stitching together of three to four different pieces of AI from a either point solution or platform perspective that will allow you to get to the place of automating all the things that you need to do to to run an effective go to market motion. But in almost every single case, there's a lot of homework that you need to do as an organization beforehand. You have to have set ICP. You have to really understand your personas. You have to understand the positioning, messaging, pain points for each one of those personas, and those personas may be different at each segment. Right? The way that I sell to it, you know, at a finance, an SMB company is very different from the conversation I have with the CFO and a billion dollar company. And you need to be able to teach the tools how to interact with that and then how to walk that forward. If you don't do those things, you're you're trusting the AI to figure it out for you and that's not what it's for. AI Yeah. Is for taking over the things that computers can inherently do infinitely faster than human beings can. Right? It still requires a person to validate. It still requires a person to maintain. It still requires a person to understand why it's being used. I think that's where RedOps can really step in and say, these are the systems that we can use in order to either drop down the time from lead to, sales qualified opportunity. This is how we can use AI to help our customers implement faster or onboard faster. This is how we can use AI to take the things that we're hearing from our customers and drive better customer marketing for cross sell and off sell upsell opportunities. The opportunities here for AI are endless, but we have to be creative in the ways that we think about how to use it. And we have to be very prescriptive about what we're feeding the AI in order to get it to do what we want it to. Yeah. So so what I'm what I'm almost hearing from you, you know, we we had some folks chime in and say, hey. Process consistency is the is the biggest opportunity for us. There's an underlying assumption there that, like, the process is defined. And so it has to be defined. Yeah. It has to be defined. And so that's oftentimes, that's, like, where we start with a lot of our customers is, like, what what is the process? You know, the AI can't do anything if if there's not sort of a baseline foundation of, like, where we need to automate and what we need to turn into an agentic workflow. So I think that's a really salient point. I'm busy. Like, all this foundational stuff needs to be put in place. Right? You have to have agreement on what your exit entry criteria are. You have to have an internal glossary of what things mean because this something it means qualified to the marketing team and it means something different for sales. That's a big problem. Right? And everyone has to be aligned, again, back to what drives the business. And if you could understand what levers you need to pull within your organization to make your business more successful and to drive value for your customers, then you're gonna be in a much better position. %. In terms of RevOps strategy, just maybe a few points here as we wrap. You know, in some of this, we've already talked about, Cliff, but, you know, maybe are there are there some tactical things that people in the audience can kinda take away and and sort of put in the back of their minds as they're as they're thinking about reshaping their their rev ops org? Yeah. I mean, one of the things we talked about the time. Right? One of the things that we do is do a time study with our customers when we get involved, right, and get benchmark data. This as far as, like, where are you today when it comes to your conversion rate, your sales velocity, your ACD, where your reps are spending your time. And then as a rev ops team, it's really hard to go and say we had this amount of effect on revenue. Right? Because you don't sell or we have this, amount of effect on leads being generated. Because you're not that one's actually executing a paid strategy. But what you can go back and do is say, because we implemented this tool, we can see this progression over time of how much faster we've gotten when it comes to qualifying. We've gotten this much better at putting things through, the the sales process. We've dropped less clients when we go over the hand off. Right? But you can start measuring all those different places that RevOps has, that soft influence. And I think being able to articulate that story back to your executive team will, again, allow you to get out of the weeds and focus on the strategic side and maybe even say, oh, these guys are actually having a an effect on the business. It's their job to put that into dollars. But yeah. Can I get more resources to do more? Yeah. Absolutely. So maybe, Cliff, you know, you hit on some huge points. Maybe just in summary, you know, what what should people think about as they as they head out today? If you can get access to your board, get access to the board. I would definitely take the time to build one on one relationships with everyone in your executive team. Again, if you can start with what drives them and what drives their objectives, it's a lot easier for you to come back and craft a a narrative and help them understand how rev ops can help them. There's a new brand of leader out there right now in the GTM space. You know, rev ops as a term as we know it today is still fairly new, and there's been a lot of education around it. But we we have to be a good business partner to that executive team. In many cases, they want to get to a a better place when it comes to data, when it comes to forecasting, when it comes to process adherence. But they don't necessarily know how. So they're typically looking for their rev ops team to come in and be able to have those conversations and be able to be that thought partner. So and no more way for you to do that is to really understand where they're coming from. Yeah. Well, thanks everybody. That wraps up Cliff and I's, you know, sort of presentation here, but we are gonna stick on for q and a for the next fifteen minutes. I wanna offer everyone here to connect with Cliff and I. Our LinkedIns are tied there. Also Tango.ai. If you wanna learn more about tango. For the LinkedIn request, just add in a little note that says, you know, rev rev ops alliance, the revenue alliance webinar. That'll help us know, where you're coming from, where we where we met, where we shared information. Otherwise, you know, Cliff and I get a lot of lot of requests every single day, so that that helps us. We're gonna switch over to to q and a. We have a few questions in the q and a. I know there's some questions that also, came through in the chat, and so we're gonna pull those as well. But I'll I'll start with actually, Andre asked a question about thirty minutes ago, put it in the q and a, and, it's a good one. So I'll I'll read this one out. My firm is resistant to change with some amazing turnkey solutions such as pipeline inspection tool. How would you approach driving change to get management buy in? This is I mean, Cliff, this kinda ties back to your point on developing some of those executive relationships. Where do you where do you see rev ops being most effective at at getting that buy in? I mean, I would take it a step earlier when it comes to, like, the tool. Is the tool even necessary in this particular case? Have you tried doing this manually in Excel? I know it's a pain in the ass. I know there's somebody in finance that you have to work with on this in most cases. But if your team hasn't been doing it in a manual fashion today and doing that consistently with weekly forecasting reports that we set the ELT, it's gonna be really, difficult to get people on board right away just because you got a new tool. Right? I I the tool isn't the thing that fixes it. It's the behavior set. So what I would suggest is making sure that those behaviors are there first and you start seeing the fruit of it. And then you can say, hey. This is working. We're getting much better at pipeline generation. We're hitting our pipeline numbers. We're seeing that move to close one. Right? Now can we get that off of our plate? We've proven it out. Can I replace that with with a technology piece that makes sense for, from where whatever that might sit from a financial perspective, or can we get a forecasting bolt on to one of the platforms that we're already using? That that's the approach I would typically take. Yeah. I think I think it's challenging to start with the tool and sort of back into the justification like you're saying. Like, let's do, like, a proper assessment and then, you know, define the problem, define what the ideal solution would look like, and then ultimately move towards the tool. But, Andre, thank you for thank you for asking that. Zahir has got a few. So I'll start with the one that he first put in. AI outpacing humans in task execution can create a bottleneck of a human validation stage, especially in a hybrid automation mode. How can we manage that? So here, I'm glad you asked this. I I think that's absolutely what some organizations feel with with AI, where, they want the controls, they want the ability to validate, they want the human in the loop, but it's a little bit of a black box. It's happening sort of asynchronously in the background. There's not sort of a timeliness associated with, like, bringing the human back in, or there's not a clearly defined validation stage as you as you described it. What we've done with Tango is, we've actually allowed you to define what those stages are and define how far you want the automation to go before you need that human validation. And so, you know, there's no instance where the AI will outpace you. Maybe maybe you'll feel like a human becomes a bottleneck perhaps, but, you know, the thing that we're sort of mitigating risk around is making sure that in those high complexity decision context rooted moments, AI is not making a call that's actually gonna put you, at a disadvantage rather than rather than something that's actually accruing value to your organization. So, you define those human validation steps. You intervene at the right moments. You set the pace for how quickly you want that that AI to work. So here also oh, yeah. Go ahead, Cliff. Sorry. I was gonna say, I love the question that Vivian asked. Now when you inherit a mature a mature org that's reactive, where where do you start? Because we run into a lot of these. And the the place where you typically start is with some type of audit or assessment of the existing technology, the existing processes, where do they sit on the maturity curve, how does that technology tie into the KPIs. And then the other piece that I typically look at with our team is what are the different go to market motions that the customer has? How do those go to market motions line up with the different activities that underpin those motions? And then on technology side, which of those activities are supported by the technology? Because now you have two heat maps. Right? You can overlay that. And now I can see very clearly what technology I have that supports the go to market activities and motions that we're doing today. Where do we have our gaps and where do we have our redundancies? And it really helps you identify places that you can cut cost, places that you can add tooling. But again, from an activity perspective, like, what things actually are the jobs that need to get done to drive the business forward? Yeah. I love that. Sarah asked a good one too. What are the potential issues when integrating AI into existing systems? Which is a great question because it just demonstrate not that you're that you're putting into this, and and, you know, wanting to make sure that everything that you've built today isn't gonna be, you know, ruined by by something you layer on top. I think the biggest issue, at least, that we see with with customers, is they've integrated AI. And and I would even say integrated is is kind of a lofty word to describe what they've done, but they've they've interjected AI at some point in the process. And there's just not a level of understanding of, how frequently that AI is executing on their behalf, where it's running into issues, who's responsible with, you know, with auditing it or even, you know, sort of redefining a process that will will serve as, like, the bedrock for the AI to, like, act on. And so I think the most important thing and maybe the biggest issue that people overlook is they do kind of assume there's, like, a silver bullet calling back to what what they've said. And so as as soon as you add the solution to your tech stack, you know, it's sort of like a set it and forget it. You really need to be able to audit and understand what it's doing, you know, measure and making sure that it's at a success level that you're okay with. You know, for some organizations, they need a % success on the process that AI is handling. Right? Think about, you know, things in the health care field or, you know, something where the risk is much higher. Some organizations will say, hey. You know what? We're happy with 90%. We get, you know, 90% execution success rate. Like, that still is a big win for us because it's maybe a lower risk internal workflow that can easily be reversed. But that's what I encourage a lot of folks to think about. Do you have that visibility into what AI is doing? David asked, where should I start with implementing AI as a small org with limited funding? It's a good question. I mean, I like, again, I would come back to kinda what we talked about with, like, process inventory. Don't implement AI for the sake of implementing AI. Don't implement AI because your board or your investors says, like, you need to have an AI initiative. Do it because you've identified a process that needs streamlining. You've identified a process that actually, in the non AI world, is highly prone to error or low adoption. So doing that inventory is where I would start. Yeah. If you implement a process or, AI without a process, you're gonna have a bad time. Bad time. Guaranteed. Yes. Every every org has limited funding. Yeah. Just about. Right? Find the find the friction points where it's something that could easily be handed off. Right? That doesn't require critical thinking. Those are prime places to be using AI. Right? Whether it's something like a lead like, rerouting, being able to take the conversation, the words that we're we're we're sharing more on Zoom calls and have that automatically be put into your CRM. Right? Simple things that are very time consuming for a human being to do, but that a AI can do instantaneously. Or web scraping, being able to go out and look for signals. Right? I wanna know when my when my potential prospects change their pricing page. I wanna know when new folks have been added to their about page because they've added a new c suite number. Right? Those are the things that you can use AI to do very effectively, but it would take a person forever to go out and do. Yeah. And, David, I would even say, like, start you know, if it's not a process inventory, work with your reps to understand how they're spending their time and, of those categories of how they spend their time, what causes them the most pain, what is the what is rid ridden with friction. It's almost like how the, you know, The US Census asks us to do, like, a time use survey every ten years. It's the same thing. You know, let's let's categorize how we spend our days and, and and what what do we dread? What do we look forward to? That's a good place to start too. Maybe we had a couple minutes left. Any other questions? Any thoughts? Right, everybody. Well, I think we got through the q and a. If we missed if we missed anything, I'm sorry. Oh, we got one maybe from Andre. Cliff, you mentioned benchmarking processes. How are you assessing this? So when we go into a company, we're doing a diagnostic on their marketing automation platform, their CRM. We're looking at how that gets handed off to their CSP or, in some cases, how that's even translating over to their ERP. We're taking a look by team, by rep, by product type, by segment, by geo the the benchmark data. Right? So what is my conversion rate across all of those different ways of cutting it, from my TAM into a lead, from a lead into an opportunity, from an opportunity through the different sales stages that we've as we've got them defined. Right? Where because we wanna be able to understand where the gaps are there or where there is friction, or where there's places to drive enablement for the sales team. Right? Earlier on, we wanna figure out if we have the right positioning and messaging. Are we even targeting the right people? Take that all the way through to CS. We wanna be looking at hand off. We wanna look at NRR. We wanna look at GRR, churn rates, cohorted. Once we've gotten that put together in the first, like, five, six weeks that we're working with somebody, now we can start showing the incremental adjustments that are happening on those conversion rates as we're making changes in the system, as we're driving changes in user adoption. That that's how you end up measuring the efficacy. Ultimately, can we get more ARR out of the same team or smaller team than we have now? But you have to start looking at it piece by piece because if you start looking at it holistically, it's really hard to be able to understand the effect that you're having. You have to break it down into the split parts. Alright, everybody. I think we will wrap. We've got about a minute left, but, I think we answered everything we we caught. So I'm sorry if we missed maybe one or two, but, thank you everybody for sticking with us, and, I'll hand it off to Will. Yeah. Just wanna say, a massive thank you, to to self care and Cliff for your contribution today. I think everyone can agree that was really, really valuable. Thanks to everyone who attended and, you know, contributed with your questions. And, yeah, look forward to seeing everybody at the next one. Thanks so much. Thanks so much for having us.