Philipp Stelzer: Welcome to another episode of the RevOps Lab. We're here with Cristina. Well, great to have you. Yeah. Maybe for the audience, can you do a quick intro?

Cristina De Martini: Absolutely. Hi everyone, I'm Cristina De Martini. I am the vice president and research director at Forrester. And I lead a team of analysts that are focused on a product line that's called Forrester Decisions for Revenue Operations Leaders. So in this product line, we offer best practice research, models, frameworks, assessments, diagnostics, etcetera, to revenue operations leaders, sales operations leaders, marketing operations leaders, go to market operations leaders, all of the revenue ops leaders that you can think of within your organization. All of the analysts on my team have practitioner experience. So I personally also have practitioner experience. I've been with Forrester for about nine years. And before that, I led marketing operations for a multi billion dollar global organization. And for, I don't know, about thirty years or so, I've held roles in, or within the past thirty years or so, I've held roles in market and competitive intelligence or research analytics, process optimization, channel program development. I actually was a quota carrying vertical alliance sales rep for a little while. Went to club a couple of years, the two years that I was eligible. I have some experience in vertical marketing, particularly in healthcare and in product marketing. So thanks for having me.

Philipp Stelzer: Well, that's quite the resume. Congrats on a successful career. And today we're gonna dive into basically what you and your team find out and discuss with RevOps leaders every week. And the way I understand this is you basically have a lot of conversations and essentially conversations about different topics. And there's like seven main topics you typically cover. So what we want to do today is go through these seven topics. We won't cover all of them. You'll quickly describe what those seven topics are and then we'll basically go through what you deem as most important. Yeah, I'm actually quite excited about this because this is basically taking the reality of the market and bringing it out here. So thanks for doing that.

Cristina De Martini: Of course, I'm happy to. So, as you were saying, the Forrester Decisions product line is one where we get on phone calls with operations leaders every single day through what we call guidance sessions. We also do in person consulting and advisory. We speak to operations leaders through events. We do certification programs. So we're literally having thousands of conversations and engagements with operations leaders every single year across myself and my team. And what we have found is that operations leaders, whether or not you're a revenue operations leader, marketing operations leader, or sales operations leader, you tend to have a select group of focus areas that really matter to you. And so these are the seven that you were referencing, Janis. I think if I were to put them in a particular order, I would start with what we call planning and budgeting. So this would be where an operations leader is bridging the — becoming the bridge between an organization's marketing or sales strategy and the execution by helping their chief of sales or chief marketing officer plan for their function and plan for how they're going to bring revenue to their organization and align the budgets accordingly. The reason I'm starting with that one is because all of the other focus areas that operations leaders tend to have really don't matter if you don't know what the plan is. So even if an operations leader is not responsible for working together with their chief of marketing, chief of sales, they still need to know what the plan is so that they can do the other six. The other six would be aligning revenue ecosystem processes and managing change for the organization. Driving actionable insights and performance measurement for the organization. Establishing an operational competitive strategy through data. And data here meaning the contact and account database that you have in your organization. So knowing who the people are that you're targeting, who your customers are, how they've engaged, what their email addresses are, phone numbers, etcetera. What products that they own. Making sure that that data is centralized or unified in some way so that both marketing and sales can use it in their respective roles. Delivering value through revenue technology. And then I'm gonna skip one and come back to it. But the last one that's universal across all operations leaders would be, or the leaders themselves, like designing their operations team. So making sure they have the right head count in place, the right competencies, the right charter for their function so that they're delivering the best value to their stakeholders. The one that I skipped is a pretty big one, but it's specific to sales operations or those revenue operations leaders that have more of a sales focus, and that would be sales compensation. So ensuring that you're incentivizing and motivating your sales performance by designing and managing an effective compensation program.

Philipp Stelzer: Yeah. I mean, we've had episodes on most of these topics, I would say. Not all of them. And we won't go through all of them today in detail, but I'm curious, what are the topics that are mostly asked for or discussed on these conversations?

Cristina De Martini: From a quantity perspective, probably the biggest topic that we have is around that process optimization and specifically optimizing the revenue process. So managing the flow of revenue through your waterfall or pipeline, the opportunity management life cycle, if you will. We get a lot of process questions though. And oftentimes people can't quite articulate what it is, what problem it is that they're facing. And when we dig into why they're having the issues that they're having, it almost always falls back to either a process issue that needs to be resolved or something earlier upstream in a process that hasn't been addressed. So we're very regularly talking about the aligning that revenue process and managing change. And the reason that's such a big topic is because in B2B specifically, the buyer behaviors and preferences and market conditions are complex and consistently changing. So that's probably — do you want me to talk about, kind of give you an overview of some of the hot topics or do you want to dive into that one in particular for a while?

Philipp Stelzer: I mean, if this is the one you want to start with, like in terms of just like sheer numbers, right? Like you said, quantity, right? I think it's a good one to start with. So why not? Let's dig deeper into it. One immediate thought I had with revenue management process and sort of like why this is like the number one topic that people ask for is because I think this is one that is maybe like one that can become quite big because a lot of stuff can be included in it, right? Like process. So what does it mean? It can also include, I assume, things like deal decks. I guess it can touch also into compensation. It can touch also in the organizational design of a team because depending on how you organize your team, this can have an impact on the sales process that you are able to facilitate for the rest of the organization as well. So that was sort of like the first thing that came to mind, like process. There's so much in that term. So basically asking you now, how would you closely define — what would you say really is part of this revenue management process?

Cristina De Martini: Yeah. So the entire gamut of the revenue ecosystem that you were just referencing is what we call revenue life cycle management. And to your point, people really are struggling with it because it's so big. There's so much into it. There are so many processes, technology, people, roles, responsibilities, which would be the organizational design and data, all have to be integrated in that process in order for it to run smoothly. And quite frankly, it is the primary job of revenue operations. It's in the name. Revenue operations is supposed to operationalize that revenue process. So of course, that's where we get the most questions and where they're focused. I think one of the things that we tend to redirect operations leaders on is rather than getting worked up about the revenue process or generating revenue or helping your sales team or marketing team generate revenue for your organization, you first need to back up and think about the customers that you're serving and what preferences or needs that they have before you can start to think about how to operationalize and optimize the revenue process. You know, the B2B buyers, the whole buying process is absolutely complex. There are multiple buyers involved in the process. Even in addition to the buyers, so you have your decision makers, your champions, your influencers, your ratifiers, etcetera, within an account. But even outside of that, you have a broader buying network that's made up of those buyers that I just mentioned, their customers. So they're being influenced by their advocates and those advocates are influencing their customers, forums, communities, etcetera. You have the whole external partners to your organization, like resellers, integrators, service firms, marketplaces. You have your own internal viewpoints, so your own sales reps, your product experts, your customer service agents, etcetera. You have external influencers like review sites and social influencers and analysts like myself. And then you have this whole new concept of AI with GenAI tools helping people buy, agents helping people buy, chatbots helping people buy. The opportunities to improve processes throughout that entire buying cycle is, feels unlimited and overwhelming and people just need help. And I think where we try to direct people is rather than focusing solely internally and on the revenue number that you're trying to generate, it's important to take a step back and think about who those buyers are, what their needs are, how you can address those needs. Because your job as an operations leader is to help your sellers and help your marketers help those buyers make smarter purchasing decisions. And if you don't know who those buyers are, you can't help your sellers and marketers help their buyers make smarter purchasing decisions. So while operations is, you know, internally focused on helping our sellers and our marketers, we have to understand the end customer that they're working with in order to do our jobs. And that's where, like you said, data comes into play because you have to understand what it is that buyers value.

Philipp Stelzer: Yeah. No, this is great. Thank you so much. I think this is a much better and much clearer definition. Definitely is helping me. And yeah, for sure, just like earlier today I had a meeting where the person that heard about us was actually coming through ChatGPT. Unfortunately, ChatGPT said something completely wrong about us, but I guess that happened. One question I have here is sort of like, this can also go pretty broad now. What I was thinking about now when you were describing this was, okay, basically my first step is I take a step back. That's my first step. And then basically I draw down the whole process and include everything that potentially is relevant for my sales process, how basically buyers make the decision making process, how they find us, they make the decision making process and so on. That can also be like a huge, huge undertaking. Do you have any, like, you know, best practices on, like, how someone should tackle this huge topic?

Cristina De Martini: Yeah, we actually just launched a whole body of research on process optimization that is answering exactly what you're asking for. So like I said a minute ago, it's very often that organizations or individuals will come to us with questions and they're not quite sure what the problem is that they're facing or where to start and how to prioritize. And so what we help them to do is first articulate what problem it is that they're facing. And then what I would recommend is using like a five why exercise, which is where you take the problem that you're facing and ask yourself, why are you facing that problem? Try to get to the root cause to determine what's causing that problem. And so some of the tools that we have available, we actually have a problem statement template that you can use to articulate exactly what it is that you're facing and link what it is that you're facing to a particular part of that process. So processes are multifaceted. You know, there's a process within a process within a process within it. It's almost like it can be infinite. And you can get down to a very narrow scope, but you wanna start fairly broadly and think, I'm struggling with a challenge to retain customers, for example. And then you wanna use this five why exercise to ask yourself the question, well, why am I struggling to retain customers? Is it because I don't know what products that they have? Well, that's a data issue and that's gonna take you down a process of fixing a data issue. You know, is it because we're not delivering the right messaging to them? Well, that's a whole, you know, campaign planning process and program planning process that you would dive into. So it's really important to articulate what problem that you're facing and get to the root cause of why you're facing that problem. And just as important is to link that problem to a business case. And we have a business case template that can help here. A business case that articulates why you need to address that problem. Like, will addressing that problem really help you reach the strategy that your organization has in place to meet their revenue number? Is it going to move the needle for you? Or is it better served to kind of put that problem aside for now and focus on something that's greater? So you have to prioritize the problems that you're facing and what you're going to go after.

Philipp Stelzer: You mentioned also data earlier, right, as part of actually understanding what your current management process looks like or how the ideal process would look like. This is like what I was thinking is basically data can be the solution, but it can also be the underlying problem that you need to solve first to actually help you understand what your revenue management process actually looks like at the moment. Not always is that so clear, as we also know from speaking to our own customers, data remains like a huge, huge topic, starting with just like the simple capturing of an email or a meeting, which still poses a huge challenge to many organizations. So curious how you are thinking about the topic of data measurement and where you see it sort of like in terms of like priority. Is this sort of like the second highest priority topic that you typically see?

Cristina De Martini: Yeah. When I was talking to Janis before this meeting, I mentioned that according to our data, all organizations are having problems with data. I actually got an old colleague who said, her name was Caroline Robertson, she said, B2B organizations are drowning in data, but they're starved for insights. The problem that people are facing with data is that it's everywhere. They don't know who needs it. They don't know if it exists. They don't know where it exists. They don't know how to access it. They don't know how to make sense of it if they do have it. And it's operations' job to fix all of that. So, you know, one of the ways to think about how you would go about fixing it is by first starting with, again, who is your customer? So who is it that needs information? And how can you best speak their language? You have to understand what is it that your stakeholders need internally? What is it that they're trying to deliver to their customers so that you understand their customer needs? And where, you know, what system is going to be housing that data, where are you going to access that data so that you can start to manage it and strategize around it. You really wanna configure the data in a way so that it tells a connected story between marketing and sales. So we have a lot of people that say that they're wanting to unify data. But unification of data doesn't always mean bringing it all together into one system that everybody accesses. You want people to use the system of record that is applicable to their function. But you want to connect that data in a way that it tells a consistent story between marketing and sales so that they have some consistency and can advance buyers through that buyer's journey over time.

Philipp Stelzer: Yeah. I mean, I think that's such a big topic as well, right? We see it all the time that you have a lot of siloed data that sits in different systems that don't integrate well with each other. I'm curious, when you think about the data challenges companies face, what would you say are the top three challenges?

Cristina De Martini: I'm gonna use the term unification. Meaning the data is scattered all over the place. But the answer to that, like I said, is not always bringing it all together into one system. But you do have to unify a view of it so it tells a connected story. So I'd say unification is a big one. Quality is a second big one. So you have a lot of data that is duplicative. When I ran research at the organization that I was at before Forrester, I was leading the healthcare market and healthcare in our database could have been written healthcare as one word, healthcare as two words or HC. And when you're pulling reports, that shows up as three different industries. So you have to not only connect the data, but you have to clean it so that it can be used in a consistent fashion across the organization as well. And then the third area I would say, which is people don't ask about this enough, but I would say data enablement. Meaning what data does my organization have available to me for me to do my job better? Product management is a great example of a function that really relies on operations leaders to provide them with the data that they need to do their jobs to develop product and manage product and launch product. But they don't know what data operations has at hand. They don't know how to access it. They don't know what systems it's in. They don't even know what questions to ask. So one of the important responsibilities of operations is to break down that silo and reach out to them and proactively notify them and help them and identify things that you have access to that you know that they need so that they can do their jobs better speaking in their language. So it's up to us to understand who our stakeholders are and what their needs are and understand how to speak to them so that they can get the best use out of the data that we have the access to.

Janis Zech: I mean, it's a topic we spend a lot of time with. We've basically developed an Opportunity 360, which gathers data from different sources and unifies those. I think when you talk about unification, it's very much centered around unique contact and account IDs that basically span across your martech, CRM, and ERP systems, production databases, right? So that you can essentially have a connecting tissue that spans across all your technology stack. I'm curious about the way we see data. There's a new angle of data which is very much centered around — you have a lot of unstructured and structured data typically in a go to market technology stack. And so how do you actually store that data so that you can use it for LLMs and AI purposes? What's your view on that?

Cristina De Martini: You dropped out on me a little bit, Janis. I heard the way we see data and then I heard the question, but can you go back and tell me?

Janis Zech: Yeah. So the way we think of data right now is that you have a lot of unstructured and structured data that is ideally living in a central data storage to make use of it for AI purposes, right? So LLMs or also predictive purposes, machine learning purposes. I'm curious, what's your take on that? Is that something that comes up in the conversations? Is it even widely understood or is that still a new frontier?

Cristina De Martini: I would say it's mostly a new frontier. We definitely have a lot of questions that come in on AI and we have research reports written about structured and unstructured data and how to get your data ready for AI. But we actually did a couple of presentations on that at our big event. It's called the B2B Summit in North America last year. And we didn't get a lot of people asking us about it. Like not a lot of people attended those sessions. So the people that were attending those sessions were a little bit more matured or advanced with their AI pilots and approaches that they were taking and a little bit more engineering focused. So less of your ops leadership and more of your tactical, you know, implementers. I think that when I think about AI in general, we get a lot of questions about where people should be using AI. So there are many of the organizations that we talk to that are trying to take an AI first approach, which I would not recommend. I would recommend, as I said at the very beginning during my introduction, that you should really focus on what it is that your organization is trying to accomplish, what is your strategy, and attach your technology based on your strategy rather than going after AI as a technology. It's a technology category. It's a solution that will help you accomplish something that you're trying to do faster or better or more efficiently. And AI can be used in a bunch of different ways, but just doing AI for the sake of AI isn't productive. So we have a lot of organizations coming to us asking us about what AI technology specifically they should use, what use cases they should put them in, why prioritize those use cases? And we can't answer those questions because it's dependent organization to organization to organization, depending on what your strategy is, what it is you're trying to accomplish at your organization as to which use case. I mean, we can tell you what the most popular use cases are, but what difference does that make to your organization? So anyway, most of the conversations that we're having on AI are around what use cases are people doing, where should I prioritize, how can I get involved. A lot of them are trying to educate themselves on AI. So some education sessions on AI and less about the data and what to do with the data and how to get the data ready. Although we think that they should be having those conversations, of course.

Janis Zech: I mean, look, I like this so much because you go back to first principles of revenue operations, which is, okay, there's an annual plan. There's a goal we want to hit. How do we operationalize our revenue lifecycle management process across the board to make that happen? And yes, AI can be one way to help do that, but there's probably, and in our experience, many underlying issues that have nothing to do with AI that are probably on the higher priority list because, right, and this is something we talk here a lot about. It's like it's always about trade offs. You can't do everything. And so you have to prioritize and you need to understand what problems are worth solving for. And then, right, you start with a problem. You start with a customer. You find the problems. You identify the right problems. You prioritize them against each other and then you go execute. And I think this is great you saying this because I think there's a lot of pressure from the boardrooms to basically have an AI first strategy. But is that the best thing for the companies actually? And I think very few boardrooms seem to ask that question. And I don't think it's a healthy development. I think it will even itself out over time. I think that we're going through this hype cycle, right?

Cristina De Martini: Yeah. Also another thing with AI is that a lot of companies and individuals have a fear of missing out. You know, if they're not doing something with AI, they're afraid that they're missing the boat or they're doing something wrong. But AI is a hot topic right now because of GenAI. But AI has been around forever. And people have already been using AI in a lot of their native systems for years. And so sometimes when we have calls with customers who are looking to implement AI, they get a little bored with us because they're like, well, what are people doing? And we share what people are doing in AI. And they're like, well, of course they're doing that. It's like, yeah, because that's AI and you can do it too in your systems. And many times it's a matter of, of course you wanna start with the customer and the strategy that you're trying to deploy and align the right technologies to that strategy. But once you align the technologies to that strategy, you want to look at the functionality of the technologies you already have in place and see what AI capabilities they already have. There are a lot of different types of AI. You know, AI is used for a lot of different things and GenAI is just one of them. So look and see where, if you are wanting to extend your usage of AI, look and see what your current opportunities are within the technologies that you have today. It could be you already even have the technology turned on, you just haven't adopted it in your organization. So it's more about adopting and creating the use case for something that you already have available rather than recreating everything that needs to be done in a particular area that's not even of the biggest, most important priority for your company.

Janis Zech: Yeah. You mentioned technology now, right? And AI itself is like a technology topic. But I'm curious, maybe shifting gear here and steering away from the big topic AI. What are some other common challenges in terms of tech strategy, revenue technologies that you're seeing that revenue leaders are struggling with or that are, you know, like the questions they ask around it?

Cristina De Martini: Yeah. When we do interviews with RevOps leaders asking like, what are their focus areas? Where are they struggling? What challenges do they face? I almost always hear two words and that is tech debt. We have tech debt. We have a huge significant tech debt. So what does that mean? It means they have a lot of technologies that do the same thing. So they have a lot of redundancy. They may have overspent. They have a lack of integration. They have a lack of adoption. So maybe they've purchased something that sounded great and it's something that they need to do and it's up there in their prioritized list, but nobody is using it. So the technology is just sitting there without getting the return on the expense that they had from that piece of technology. So I would say reducing the tech debt or getting your arms around the tech debt is probably where most people need to focus. Similar to the AI first approach, before AI was a big buzz, we had a lot of people, especially in operations, taking a tech first approach. Many operations functions are only responsible for technology. And so they take this, you know, they have their blinders on and they're only looking at the technology that they have. They're designing the best roadmap and coming up with the coolest next features for their organization. So what we tend to guide people to do is to really just take inventory of your current tech stack. What do you have today? Who's using it or who's not using it that you were intending to use it? How does that adoption look? What redundant functionality do you have in place? Of course, you'll wanna ask what AI capabilities you have available. And then once you've taken that inventory, do a gap assessment of what it is that you have today and compare it to your strategy. Rather than taking that tech first approach, take a strategy or what we call an outcomes focused approach to technology, where you identify what strategy you're trying to deploy, what are the priorities that you have to do in order to meet that strategy, how can you automate that, what tech categories align to that automation. You know, you intentionally want to go through that very structured process so that you are identifying the technology that your company needs. Not what's the coolest or the most fun or the most exciting to work on, but what does your company need to go after that strategy? You know, if you have a retention strategy, the technologies that you need are very different than if you have a net new logo strategy. You're gonna need a whole bunch of advocacy and customer success technologies and things that understand what your customers have versus demand and intent and other types of technologies that you would need for a new logo strategy.

Janis Zech: Yeah, I think that's great. I mean, that basically really, you know, I see sort of like a theme here. Like taking a step back, thinking about what you want to do, like measuring the gaps and only taking an action, you know, once you have those gaps identified. Suddenly it all starts to make sense.

Cristina De Martini: Well, it's a no brainer. Everybody knows to do it, but we're all moving so fast. It's easy to just be like, oh, this isn't working. Let me go put in a solution and fix it. But if you don't stop, you're gonna be putting in garbage that isn't going to resolve the issue because you weren't able to articulate what the issue was.

Janis Zech: Yeah. Absolutely. And I mean, I think tech debt also is such an interesting topic. Again, it's so huge. I mean, just thinking about CRMs, right? Like a company working for since ten years or fifteen years in Salesforce in one CRM. The amount of tech debt that is accumulating there and is slowing down processes, slowing down salespeople. In itself is a huge topic. Checking the licenses, huge saving costs you can generate. I mean, IT spending. I don't have the exact number in my head, but I think it was something north of fifteen k in annual software spend on an average AE. I think it was something in the ballpark. Keep me honest if you know the actual number.

Philipp Stelzer: I don't know. I've never looked at it per AE. Actually, that's an interesting way. I'm gonna go back and think about that. Because, I mean, that's insane, right? That's an insane overhead. And then you have all these systems and then they don't speak with each other. Then, like Janis said, universal identifier to bring it all together. Then what is it worth? So, yeah, I think that's like a really, really, really good point. So, yeah, thanks for bringing this up. Really, really highly appreciate it.

Cristina De Martini: Yeah. My last thing is, thinking about tech debt, there are organizations that — think about the culture of your organization from a technological perspective. There are organizations that wish to be, you know, leaders in particular markets and wanna be innovative and always be thinking about the next big thing. And if that is your strategy, maybe you do need a lot of solutions that are really niche that provide this or the other, but you need to think about how to connect them. Whereas other organizations, if your culture is more best of breed, you know, like big platform solutions and you wanna hone in on those platform solutions, you might, again, it's a give and take. You might have to give up some of the functionality that those big platform solutions don't have yet or haven't acquired yet, but that's maybe worth it for you, you know, if you're a mature enterprise organization where a lot of people have adopted the technology within your organization. You may want to give up some functionality so that you can keep them focused on that platform and not have all these random things that they're constantly having to learn throughout the organization. So again, going back to who it is that you want to be, what it is you're trying to accomplish and aligning your tech strategy to that organizational strategy is absolutely critical.

Philipp Stelzer: So I think we actually covered a lot. I feel we could continue talking for probably another at least thirty five minutes. Maybe we just have to invite you back to go through some of the other topics. But yeah, let's leave it here for today. I would love to thank you for coming on, sharing this with the community. But before you go, what's a book you would recommend or a report or anything you feel could be important for the community?

Cristina De Martini: Yeah. So I'm a big book reader. I think I read four or five books a month. And I tend to alternate between like personal books and business self-help. I'm really big on positivity, like staying positive. There's so much negativity in the world and people get down pretty easy and get down a rabbit hole. So one of my favorite books that I've read recently, and it's kind of an older book, I just read it, is The Power of Positive Leadership by Jon Gordon. And it does just a fantastic job inspiring leaders on a way to lead that builds motivation for your employees. And when your employees are happy and excited and engaged in what it is that they're delivering, they're going to want to produce for you and for your company. And I just found it fantastic to listen to. You know, you can potentially engage your employees. And by engaging your employees, you're gaining more revenue and delivering a better experience to your customers if you start with that employee experience. So The Power of Positive Leadership.

Philipp Stelzer: Sounds like a win, win, win. Thank you so much.

Cristina De Martini: Thank you. I appreciate the time. I hope to be back again.

Philipp Stelzer: Absolutely. Thank you so much.