Philipp Stelzer: Alright. Welcome to the RevOps Lab Podcast. I'm Philipp, and I'm here together with Janis. And our guest today is Lauren Silvers. Lauren, hello.

Lauren Silvers: Hi. Great to have you.

Philipp Stelzer: To you on the show. Really excited about the next thirty minutes or so.

Janis Zech: Yeah. I think the reason why I wanted to definitely talk with you is you gave a talk at RevOpsFest in New York recently. And yeah, we'd love to dive deeper into it. The topic was buyer-centric revenue operations. But maybe before we go deeper into that, who are you? What do you do? And why are you even thinking about a topic like that?

Lauren Silvers: Great. Thanks so much. So I lead go to market programs at Ironclad. And in that role, I'm really uniquely focused on driving productivity, pipeline, and cross functional excellence. So very specific focus for our sales organization in partnership with the BDRs, with marketing, with PMM, with enablement, and I sit under the RevOps team. So this is top of mind for me because my background is in enablement and sales strategy. And I've only recently in the past two roles been kinda reporting into RevOps and really seeing it from the perspective of, I would say, like an enablement professional who is very, very focused on the rep experience. And seeing how all the time RevOps, obviously they're anchored around a sales process that needs to be consistent and predictable. And it's usually at the expense of reps having to kind of shoulder the burden of integrating across different tools, context switching, doing a lot of the administrative burden. And I've always been thinking about how do we fix this, right? So a lot of the tools that we ask them to use and work in every day were built to solve point problems. They weren't necessarily designed with interoperability as a first principle. They weren't designed to activate key workflows. So I'm sitting here building all these key workflows and doing it in a way that creates friction and, you know, introduces a lot of context switching and makes it really hard. Like, it should be really easy. I'm trying to get everything down to like three steps from twelve steps, but it's really hard when you have these structural limitations with these systems. So buyer centric RevOps is really top of mind for me. I'm seeing with the advent of signal based selling with new tools like Clay, Common Room, Pocus, and, you know, PLG and product led growth and product led sales go to market models, they're already starting to pull RevOps toward a more buyer centric vision. So I was thinking, how do we even take this further in my talk?

Janis Zech: Got it. Got it. So I would also argue, I mean, probably AI plays a major role because, like, the way I understand you talking about this topic basically means what you wanna do is you wanna enable the different revenue functions that actually are part of the buyer journey to whatever extent. Right? So, like you mentioned, marketing, customer success, sales obviously plays a huge role here as well, and really give them the power to actually be more focused and adjust as to where the customer currently is in the buyer journey, to be more flexible in regards to how to react to that or how to be proactive around that. That's sort of like how I understand you. Is that a fair assessment?

Lauren Silvers: Absolutely fair. In fact, it's a perfect assessment and capture of this vision. So I think people are starting to think this way with the advent of new AI solutions and tools, but there's an opportunity to really reorient around a buyer journey that is actually changing. You know, it's not just about taking the sales process and aligning it to an inflexible, rigid buyers process. The buyers are changing. Right? And they're changing rapidly. So it's really about building an adaptable, flexible process that creates more of a dynamic ecosystem versus, like, a rigid and inflexible system. And how do we make sure that the ecosystem, you know, can continue to adapt to changing buyer behaviors? So that flexibility is really a key.

Janis Zech: That you mentioned. Maybe one question from my side. So, I mean, obviously, I think we've all experienced these, let's say, seller centric processes. Right? So maybe could you allude to what you think is broken right now? And yeah, what are some specific examples?

Lauren Silvers: Yeah. So I would say, as far as broken, I wouldn't say everything's like broken, right? It's not like a, you know, a crisis that we have to solve for. It's more of a future risk, I would say. So, yes, we have a sales process that basically treats all buyers as the same, but buyers have never been more educated than they are today. And buyers are now educating themselves with the help of AI. So whether that's like they're starting to find, you know, probe their problems and challenges and find viable solutions via ChatGPT or they're using some other way to, you know, truly understand what's out there to solve their problem, they are starting to use AI. So in the talk, I really tried to step into the future and say, what does it look like when we have, you know, essentially buyer GPTs? Right? That's a whole different architecture for buying. Right? And maybe buyers are so educated that they connect up to — their buyer GPTs are even connecting up to seller GPTs in this very automated way. And maybe we have digital sales rooms pulling us into the future where the human element of a sales process is not even introduced until very, very far within the sales process. That is possible. I think there's a risk if we continue to route buyers through the old sales process where we're qualifying them through the use of BDRs or SDRs, and then we're giving them a meeting and we're doing discovery and we're even, like, layering in value selling, right, motions, kinda slowing them down, that they may continue to be totally frustrated with us. And I think that the more that companies or businesses really think through how they're gonna meet buyers where they are in the near future, those are going to be the businesses that are much more competitive and able to maintain some deal velocity, better deal velocity.

Janis Zech: Yeah. I think this resonates really well with me. I mean, I think we're living through it ourselves with Weflow. People come into the demos with, like, two, three people, very much know what they're looking for, know exactly what they want. They have very specific questions. I think they wouldn't accept a thirty minute discovery call and then a demo. Right? Like, they basically want to jump right in. So I think obviously, I think we've had the evolution of product led, but not every product can be so product led. I mean, we sit, for example, in the email server. We record meetings. We connect to the CRM data. So obviously, we need to go through security before we do that. But with that said, I think what this means is you wanna give as much information outside before the demo is actually happening so that people can educate themselves. And this is something we see every week. Right? This is not yet buyer GPTs or seller GPTs, but I think it's already happening. Right? And then you can clearly tell that sometimes people come into the meeting and they're actually just in the exploration phase. They don't really know. Like, there's not a consensus around, like, okay, I have this problem. This is the, you know, kind of impact the problem has on our business. And we've, as a group, made a decision that we actually wanna solve it. But, like, it's more like an exploratory talk versus, you know, other situations where they come in and you'd exactly know, you know, they're in market and they really need to solve it ASAP. So it's a reality we've been living in for a while and not every, or, like, yeah, some companies do a better job adhering to those processes and others don't. So long story of like, okay. What would you say are some, you know, like, things that are slowing reps down, like, really from a rep perspective today? I mean, you mentioned the, like, structure of how tools are built in your talks. Curious. You know, what are some of those things that, you know, people really — like where's the structural problem?

Lauren Silvers: Yeah. I think reps are slowed down so much right now, and they don't have to be with the advent of new AI capabilities that I think RevOps teams are a little bit afraid of. So AI has completely solved the CRM hygiene problem. But are most companies adopting those solutions where, you know, your Gong calls are automatically choosing the right option from a drop down in a pick list or, you know, writing to CRM notes? I think we just went through this — when I was at Intercom, we piloted this tool called Win dot ai, which, you know, it does two things. It delivers in call coaching, which is really helpful based on your qualification framework or your sales methodology. But then it also automatically writes to the CRM using the customer voice. So number one, you're basically eliminating the translation of that customer voice into crappy data, but you're actually capturing it perfectly in the CRM using AI and large language models. But you're also eliminating the CRM hygiene problem just completely. And a lot of companies are just not — they think they're gonna get garbage in the CRM. But we ran a pretty rigorous POC and actually the data was a hundred percent accurate. You know, when we looked at and did quality checks, it was accurate. So I feel a hundred percent confident that, you know, CRM automation, CRM hygiene is one really great opportunity to take that off the rep's plate. I also looked at a Salesforce report recently for twenty twenty four that said reps only spend thirty percent of their time every day actually selling, doing customer facing kind of revenue generating activities. That means seventy percent of the time they're doing administrative activities, or they're in meetings that are not revenue generating. And that to me seems like a huge liability. Like, can we use AI to get that up to fifty percent or sixty percent? Because that's where we really need reps to focus. So like I said, they're switching between a ton of different tools. RevOps owns those tools, and they're introducing new tools all the time. And then enablement's meant to enable on those tools. Right? But it's just a lot of it is taking up a lot more of their time that they could be spending with customers.

Janis Zech: Yeah. I mean, but people aren't, I think, talking to one another.

Lauren Silvers: Yeah.

Janis Zech: I think this resonates so well. I mean, obviously, Philipp and I, we founded Weflow to fully automate Salesforce data capture, right, from emails, meetings, the context that are being added to your email threads and calendar that never make it into Salesforce. Right? Like mentioning the other tool. But, like, I think the conversations, right — the LLMs really make it possible to use the unstructured data structured and then ensure that this works across all your different Salesforce field types and objects. And then I think your point of like, okay, this is one workflow that every rep has to go through. I think we've had so many different versions of let's introduce it into the comp plan, Salesforce hygiene, or let's have this weekly Friday meeting and kind of put pressure on them. Right.

Lauren Silvers: Let's fire somebody in front of everybody so that people actually know you have to do it. Right.

Janis Zech: There were so many versions of this that were so bad. And now finally, it's actually possible to fully automate it with a human in the loop that can control it and really, you know, also control the efficiency and effectiveness. So I think this is a great example where, like, we shouldn't spend time — and this is pretty much the solved problem. Fully agree. The adoption is not yet entirely there, but this is changing fast, at least from our experience here. So I think that's quite cool. I'm super curious about another topic you mentioned. Right? Like, not the tool side, but actually the signal side. Right? Like, I think that was a big topic in your talk. Right? And obviously, I think the visibility into signals is a huge challenge. So yeah, curious what do you think about that aspect to become more buyer centric.

Lauren Silvers: Yeah. So obviously, if you have a product led growth or product led sales go to market motion, you are already having to use signals, or I hope you are. But, Philipp, you mentioned in our prior conversation that, you know, there's this opportunity to have more of a unified go to market view where it's not just funnel metrics like MQLs, SQLs, and closed won, but really trying to capture signals from buyers. So engagement, intent, you know, usage behavior if you do have a PLG motion, and really trying to orchestrate the data around the signals that are most likely to convert. And I even am in favor of, like, not just using one signal, but, like, layering in signals, like doing signal clusters. That's what we did at Intercom. It was very, very successful. And so you can obviously have a feedback loop where you're constantly looking at what your highest converting signals are and then routing those to BDRs or AEs respectively to make sure that they are paying attention to those signals and acting on those signals. So there's this gap between intention and action that I often see with account executives, not so much with BDRs because that's their whole job. But again, when the systems are difficult to navigate, when the ecosystem in which they're operating is, you know, very complex. Right? Then when you're also asking them to drive pipeline and, like, go and look at all the intent signals and all the engagement signals and put everything together on their own — the reps have to be the integration layer. Right? They have to translate all those signals. So the more that we can be buyer centric and set it up in a way where we're orchestrating around those signals and taking that complexity out of the equation and giving them the insights that they need to share in their outreach, that's a highly efficient pipeline engine. And, you know, that's where you get a lot of efficiency and productivity.

Janis Zech: Yeah. I think this basically hits home for me in regards to, like, a key challenge I would see with the whole, you know, buyer centric approach. So like, what you're basically saying is let's create a culture, maybe, where, you know, everyone is sort of, like, given more flexibility, which means that you get more trust, you get more autonomy, or you need to make more of these decisions ad hoc by yourself, which means, like, you know, that's one playbook, you know, that time is over. And then you need to be, like, able to interpret, like, that specific buyer's signals now. Right? So, I mean, I think there's one way where you can basically create these more generic signals that generally, I think, you know, can work pretty well across different ICPs and would need to be adjusted and segmented and sliced and diced and so on. But then you also need to sort of, like, give the rep the time and the possibility to actually, you know, do that themselves also, like, to take these signals, react to them individually. So we're basically talking about, like, a whole new level of sales rep complexity that we're also introducing with this. Right? So that's the one thing, you know, where I think I would assume that this is probably something that can work well if you are, like, a sales rep that has, let's say, twenty to thirty deals in their pipeline at any given time. I wonder and I'm curious if you have any experience with this. How would you think this can be scaled also for, like, more high velocity? You know, what if you have, like, you know, every week your pipeline changes, or every two weeks your pipeline changes. Right? If you don't have these longer sales cycles, will reps still be able to do that? Or are we then, again, more talking about, like, pushing them into, like, a very rigid, static framework where they have to follow very specific steps?

Lauren Silvers: Yeah. I think it's very dynamic, actually, and totally doable, maybe even more doable on the transactional side. That's what we did at Intercom. And so what we did is we started with the absolute strongest signal clusters where they're almost like scenarios, right, for, let's say, cross selling, upselling, and conversion from product led to sales led. And we looked at the data and said, these are the highest indicators, and then we made them predictive. We used machine learning to kind of validate that these were the three to four signals — I struggle to call them signals, signal clusters because it was a mix of intent data, third party data enrichment, and product data that we were kind of rolling up into these specific scenarios. Then what I did as an enablement slash RevOps person, I said, okay, for each of these signal clusters, we're going to route it to a little page in Coda. You could use Notion. You could even do Slack. And basically say, you know, this is a scenario. Here's all the data you need. Here are the insights that you need to share in your outbound. Here's some additional light qualification that you may need to do in order to further qualify this potential opportunity. And all the links and everything they need, including the outbound sequence delivered in the flow of their work. So it's a high priority action that they need to take, and they know exactly why they need to stop what they're doing and take action. They know exactly what insights to share with the prospect, and they know exactly what to do. So it's very much like we're quarterbacking it for them. Right? And so it's not — you don't wanna bombard people with signals. Like, I think that's kind of where you were going. Like, if you have too many, you know, they're just gonna move into more decision paralysis, but you need to come up with a sweet spot. For us, it was like four to five, and they were constantly asking us for more because, you know, I think when we rolled out the cross sell, upsell initiative, it drove a two hundred and forty seven percent increase in pipeline in one month, and then that smoothed out to about one hundred and ten percent year over year. So it was very successful. And the reps are like, I want more of this. This is so easy for me. Because otherwise, I have to go hunt and put all this — I have to do more, actually, more work to get to the same result. And even then, I want these to be all prequalified for me. Right? So that's what we were able to do.

Janis Zech: Yeah. Yeah. For sure. No. That makes a ton of sense. Thank you for elaborating more on it. I'm sold, also for the high velocity or, like, more high velocity, very transactional approach. And then yeah. No. Like, the other thing I was curious about. Right? So I think milestones — like, there's still, like, these different stages, I think, that a deal typically goes through. And I think that still makes sense because, like, mentally, as a buyer, I'm also sort of, like, thinking about buying software in stages. Right? I wanna go — like, depends on the software, obviously, but I do wanna go through, like, okay. Maybe not always discovery. I do discovery myself nowadays. Right? But I do wanna go for, like, a short demo. It's just, like, worth actually spending more time on where I can ask some very technical questions. I wanna have, like, a little POC. I wanna have, like, a trial after that where I can self-service or do it with, like, somebody else. And for sure, like, if it's a bigger piece of software that I'm buying, I wanna go into a procurement process because I do wanna negotiate and wanna, you know, get the price down. So I'm interested in at least those three stages. So plus the closing part of it. And so I still would think, you know, there needs to be signals around when would you actually, you know, need to push the buyer, you know, over the finishing line of the next stage and the next stage and so on. Like, is that something that, you know, you've collected experience with? Have you seen signals that work really well? I think it's maybe a bit easier on the later stages where they're actually engaging with the product, but I think a bit harder early on.

Lauren Silvers: Yeah. There's this, I would say, old concept that is very underutilized but is very relevant to what you were just talking about called customer verifiable outcomes. Have you heard about this? CVOs?

Janis Zech: Yeah.

Lauren Silvers: I've always been a huge fan of this, especially when you are, you know, an enablement professional launching a sales methodology and you want it to be customer and buyer centric. And you're also trying to get frontline managers to coach really using the evidence from the customer versus like, yes, I know this deal's gonna close because I feel like it's gonna close. Right?

Janis Zech: Right. I feel it. It feels good. I've done it before.

Lauren Silvers: So the idea of customer verifiable outcomes is like, well, how do you know? Right? How do you know we're at this stage? Right? And then that changes rep behavior because then they know that their manager's gonna ask them, how do you know? Or what's the evidence? So they're trying to get the evidence in the call. Hey, do you have stakeholders aligned? Who else is in the buying committee? Who has final sign off? Right? So I'm a rep. I'm asking those questions because I know that's what's gonna be expected of me from my manager. And then my manager says, who has the final sign off? How do we know that's the person? And I say, well, here's the evidence. Right? So I think this old idea of customer verifiable outcomes — it's not so much signal based. Maybe there's a way. I haven't really wrapped my head around that idea. It's an interesting and provocative one, but I think it's more about getting the signals from the reps themselves in their conversations and changing behavior around how they're actually, you know, executing a buyer centric sales process well. I don't know. Do you have any ideas on that?

Janis Zech: I just wanna add, like, I think this is exactly where then the AI piece comes back in. Right? So because then you would actually be able to verify that. Right? So if you have the coach in the call, right, it would remind you to ask these questions. You could have fields corresponding to it where, like, the voice of the customer could immediately, like, be filled into it. Right? All of this is doable. Right? Like, we know because we already do that. So it's definitely possible, and it is accurate. I think it's, like, amazingly accurate.

Lauren Silvers: So AI assisted forecasting based on data from the customer calls, from the prospect calls?

Janis Zech: Exactly. Right. So, I mean, like, if I think about, like, on a more technical level — like, how would you actually execute it? Right? You would just need to have, like, a validation for, like, let's say, like, five different signals that you wanna have — paper process, decision process, you know, stakeholders, champion, and so on. And then you have, like, a Boolean field, yes, no, or, like, true, false. And then the AI could make an assessment whether this was discussed or not and could then, in addition, have, like, a long text field, long description field where below there's actually, like, an excerpt, like, of the transcript, like a quote that would provide additional information around it that the manager could then use to actually evaluate whether this is good enough or not. So you could even add these check ins and so on. Right? So I think — can you automate this? Hundred percent. Should you automate it? Hundred percent. Otherwise, it just doesn't happen. Right? I think that's our observation. Right? Like, I think we've all seen so many MEDDIC, MEDDPICC, SPICE fields that are just not populated. And I think the general challenge we see is you need an integrated tool that automatically captures the data and then makes sense of the data. Right? And if you think about for opportunity signals, right, like, often the very strong signals actually lie in the activities, lie in the contacts you're in contact with, lie in the conversations and the CRM data. But often the CRM data is fed by these three buckets, I would say. If you then think about contacts, right, top of funnel where you have an account based motion and you wanna understand the contact signals, right, it's very much centered, a lot more centered around intent data, website data, product data from product led, where you then try to score, overlay different signals to make decisions. Where should I engage and where should I not engage? Right? I think the future where we are going is, to your point earlier, Lauren, like this needs to be orchestrated from RevOps and enablement. It's not something that can be done by the reps. It shouldn't be done by the reps. And it needs to be simplified in a way that the outcome is like, look, here's something you need to take action on. And if you think about opportunity management, right, the way opportunity management is done is often you sit in front of a long list, and you actually don't even see when you sent the last email or when the next meeting is. And you just basically go through it again and again, and then you try to remember what's actually going on. I think the future is that an AI will tell you, look, you know, you're having a meeting here next week. Send a quick, you know, email there. I already prepared the email. You know, I saw that you had a meeting yesterday. There's no email that went out to your people you had a meeting with. You should send the follow-up email. Right? And I think that is a reality. Like, companies like us are building that. Right? Then there's Clay and Common Room that are more doing the content and account scoring on the top of funnel side. But all these things, I think, will lead towards what you're basically alluding to, like, bringing more light into the dark of where the buyers are actually. Because I think that's often a huge problem. Right? Like, folks don't know who actually visited their website and visited their pricing page or their product tools or their deep down security page. And if you knew that, that would be probably very interesting. And if you can combine it with other signals like, oh, that person also signed up. And by the way, you had ten of those folks and the company is NVIDIA. Let's go and try to convince them. This is essentially like there's something going on at NVIDIA. They still haven't booked the demo, but probably they are thinking about it. And we actually know who is thinking about it. So let's give them a call with a very specific message. And then it becomes, you know, not like cold, spammy outbound that people hate, but it's actually, oh, cool. You're actually thinking of what we are thinking. Great. Let's have a conversation and let's explore. And I think that's a pretty cool future I think you're laying out here. I really like it. And now I just kept on rambling. I think I'm so excited about the topic. So, you know, I can't stop talking. Sorry.

Lauren Silvers: No. It's such a great topic. I just feel like I've just tried to ride the zeitgeist. You know? It's not necessarily a revolutionary idea. It's one of these ideas that it's like, oh, okay. Revenue operations has been very, very focused on systems, like, repeatable static processes, and it's changing so much. So we have the opportunity to rethink it, and we're already starting to do that. So obviously, with the help of tools like Weflow and, like, Clay, I mean, there's just so much innovation out there. But I don't personally, being part of Ironclad, like, we are not there yet. Right? We are not capturing, leveraging signals. We are very much, you know, using the legacy tools that don't really — you know, they're in silos and they don't really help reps do their job better. You know? They're just those legacy tools. And the other issue is that, you know, the first wave of AI, all of those legacy tools bolted on sub par AI to all of their products, and they're all kind of duplicative. Right? So they're not really helping the reps do their job better. You've got, like, Outreach giving summaries of accounts and contacts. You have Sales Navigator now doing the same thing. You know, you have Gong, you know, delivering call summaries, but then, you know, again, they're not automated back to the CRM. And it's just a lot more noise and a lot more complexity versus, you know, the opportunity we have now to, like I said, rethink the systems to activate workflows. That's how I think is the future state. Right?

Janis Zech: Yeah. Yeah. I think — sorry, Philipp.

Philipp Stelzer: No. I mean, like, I think what you said with, like, zeitgeist, I think that was, like, the keyword for me, basically. Because I think that's what we're talking about here. Right? Like, it's — I mean, it's not a revolution. I think we're all moving, or we're trying to move into that direction. Sometimes this can be very hard, like, going from, like, a very siloed system to, like, a system where the data is more unifiedly stored, which then enables you to do what we are talking about. Because I think, you know, there's a lot of technical prerequisites to actually getting there. And I think working through these can sometimes be very hard depending on the resources and, again, also culture of the company. Right? So not every company has a culture to actually do this. Let's face it. And or may just, like, take them a really long time. But I think it's key to have these discussions around, you know, like, where should we be, like, you know, x months or years in the future from here. Because yeah. I mean, these are all defining aspects of how sales are changing. And if you cannot keep up, right, it's very dynamic as we all know, then, you know, yeah, it's gonna be a problem for you. And I think both Janis and I, we are big proponents of believing that it's very good to have a trustworthy system of record to create that, to maintain that, and then to use that to leverage all of the things that we talked about, like using AI to write into that system, using AI to pull, you know, information out of that system, and also to turn the modern seller into, like, a ten x person. Because, I mean, in the end, that's what we're talking about here. Right? Like, you give them more autonomy. You give them more trust. You move away from these rigid systems. Like, you move away from, like, these, I don't know, sometimes bit toxic, you know, sales cultures that exist, and you move to a place where you actually trust the people to do a good job. And that comes with its own challenges. No question, you know, that this is, like, its own challenge. But I think, like, as an ideal space, would I want to go there? You know, do I agree with this vision? Hundred percent. Right? So I appreciate it. I appreciate it for you too, you know, for laying out, you know, your thinking and thought process.

Lauren Silvers: Yeah. Yeah.

Philipp Stelzer: Alright. Sorry. Do you wanna?

Lauren Silvers: No. I was gonna say, in my talk, I kind of recommended like three areas to start if you wanted me to share those.

Philipp Stelzer: Great. Absolutely. Yeah. Yeah.

Lauren Silvers: So just to break down the whole signal based selling opportunity, you know, I think it really comes down to auditing your signal to system to action loop. Right? Like, where are you — do you have signals, first of all? And if not, you need to kind of set that up. Like, what are the signals? Where are you getting the data? What do they look like? Why are you choosing those signals? How is your system routing or orchestrating them? And what actions do you need the reps to take? That's number one. Number two, with the advent of AI, you need to get your data ready. Right? So a lot of data is not ready. It's super unstructured. I mean, there are tools that will help you structure that data. But working with PMM to tag a lot of the resources and content with metadata is going to help, you know, with MCP servers really understand context and why something is more important at a certain moment versus not. And then finally, I think to your point, Philipp, earlier around reps feeling bombarded, like really just trying to train reps to be more context aware and also understand, you know, again, what they should pay attention to, what their workflows look like. And I think, you know, AI is just going to create a lot more noise for them. So really having enablement really think through that ecosystem. Right? But it's not just behavioral. It's also giving them an understanding of context and how to be just aware of what's happening in their environment in a totally different way.

Janis Zech: Lauren, this was awesome. Thank you so much for coming here, sharing all this. We'll definitely join RevFest next year in Brooklyn or wherever else it will be. I think still not getting the tattoo, but let's see. Maybe that changes. Philipp, a little face tattoo moving back to Berlin. I see them here all the time these days.

Philipp Stelzer: It's a new — but before you go, any book you would recommend for the audience?

Lauren Silvers: