A New Model for GTM Execution in the Age of AI and Buying Networks

Jim Bell

01:16 – 07:35

Hello, and welcome to today’s webinar, a new model for GTM execution in the age of AI and buying networks. I’m really excited about our guest, Katie Fabiszak from Forrester, who’s gonna be with, with me on this, and I’ll introduce her in a minute.

And I really appreciate this topic, so I think it’s gonna be a great session. For an agenda, we’re gonna, I’ll introduce Katie in a minute.

She’s gonna talk about about fragmented go to market challenges, about AI and the buyer’s journey, and she’s gonna introduce this concept of the connected go to market framework, all this based on some recent, research from Forrester that they’ve released. And then we hope at the end to have a little time for some discussion and to talk about how this is impacting their clients and and what we’re seeing.

So, Katie will be joining me shortly. She is the VP and principal analyst at Forrester.

And I did wanna share before I bring her kind of on stage, what we’re hearing from our customers, here at LeanData. And so we recently, commissioned and sponsored a, a research report with Harvard Business Review Analytics Services, just asking people about their go to market process, their strategy, and their execution.

And one of the big findings that we saw was that 83% of those people who are surveyed, this was a global survey focused on mid market and enterprise companies, felt that go to market strategy was very important to to their growth, and to executing their strategy. But most of them said they weren’t effective, and so the strategy tended to really break down when it was translated into action, or the execution of the strategy.

What we’re hearing from those customers kind of across the board in discussions even, even recent conversations last week with folks I was talking to is that AI is really disrupting every part of go to market. If it’s not directly, impacting it, there’s certainly a lot of pressure from leadership and management to leverage AI more.

But without coordination, it just means more activity, more signals to deal with, more noise in the system, and not necessarily more revenue because it still requires a certain amount of discipline, rigor, around that mission critical process of driving revenue, and that’s really where intelligent orchestration, becomes more critical than ever. With that, I’m gonna, bring Katie up on stage, and she’s gonna talk about some of their research, and then I’ll we’ll come back later for more discussion.

Katie Fabiszak

07:35 – 38:05

Well, thank you, Jim, for that great setup. I could not agree more that go to market strategy is very important, but the reality is that b to b teams are not doing it effectively, and in fact, everybody is losing.

Buyers and customers are certainly feeling the tension. In fact, Forrester data shows that 85% of buyers report dissatisfaction with the winning provider in at least one aspect of the buying experience.

So that means that winning the deal does not necessarily mean that a great experience was delivered. And those poor experiences that happened in the buying cycle, those carry forward into customer onboarding and delivery, which leads to lower trust and also higher potential future churn.

When we think about partners, they account for a large share of revenue for many b to b organizations. And yet research shows that many companies fail to deliver a consistent end to end partner experience across the partner’s journey from the time they are onboarded as partners to enablement to selling and even co selling.

So these disconnected go to market practices really create friction that erodes partner confidence which leads to weaker collaboration, lower partner engagement, and certainly increased risk to partner sourced revenue. And and the final thing is that companies themselves are losing.

Right? Misaligned go to market efforts directly impact revenue, as fragmented go to market processes really lead to not just inefficient spending, but underperforming sales and marketing teams. So we really cannot minimize the importance of go to market strategy decisions because it impacts absolutely everything.

So this this is exactly why it’s so important. If we think about those go to market strategy decisions impacting everything in an organization, we can start with resourcing.

Right? Like allocation of budget dollars, but also the people allocation, the mix of technologies and systems that are required to execute against a go to market strategy. Go to market strategy feeds marketing campaigns, programs, tactics, messaging.

It also drives enablement to ensure that go to market teams and revenue teams, everybody has the insights that they need to successfully execute the go to market strategy. In order to do this well though, something that is absolutely critical to effective go to market efforts is you have to understand your buying audience.

So I’m gonna spend a little bit of time walking through buyer insights. I think it’s, it’s fair to say we all know that business buyers are changing.

Every year for the past decade, Forrester conducts the Buyer’s Journey survey. It is the largest business buying survey of its kind.

In this latest, survey, almost 18,000 people participated globally. So for this next little while, I’m going to share some of the most interesting findings, including the impact that AI is having on the buyer journey.

Generative AI tools are really central to how buyers research and evaluate options, But the thing is that trust is remaining a little bit of an issue. So if if we think about AI assisted search, our data tells us that the majority of buyers, in fact 94% of them, they’re using some sort of Gen AI tool as part of their purchase process.

AI was also the top rated interaction when we asked buyers how they’re researching and gathering information, but we also see that it’s accompanied by mistrust. I think you can probably relate to this.

Right? As we all know, we’re using AI in our everyday lives. AI results are not always a 100% reliable.

So we’re gonna take a look at how buyers are coping with that and how AI is having an impact. The first thing that we’ll look at is digging a little bit deeper at what day the data is telling us about the role that GenAI plays in the purchase process.

Now I know this is a busy slide, but we’re gonna kinda break it down and and walk through it. One of the things that we asked buyers in the survey is to tell us the most meaningful interactions that they have, And this includes a mix of both personal and self guided interactions because we always need to be aware that buyers are conducting their research and they’re gathering information in many different ways.

Certainly, they’re using GenAI a lot. It was clearly number one, but you can see that they also still find other meaningful interactions, things like attending conferences and events or talking to product experts and sales representatives.

Those are still important and should not be neglected. And one thing to actually keep in mind, when we’re looking at these numbers, this does not reflect the number of times that a buyer is doing these things.

We know that self guided interactions, let’s think about using GenAI or even a classic Internet search, Those are interactions that are likely happening many, many times throughout a buying process versus maybe there’s only a few conversations that are happening with a product expert. That’s why we intentionally ask the question about what the buyer finds most meaningful, not how many times that they’re actually doing an interaction.

So if we think about this particular view, it’s looking at the aggregate of what buyers are doing across all phases of the buyer’s journey, from gathering information early on in the discover phase to supporting what decisions get made in that final commit phase. And one thing to just point out is look at that difference in the numbers.

87% of buyers cite GenAI as their top meaningful interaction versus the next second one at 51% where social media is a meaningful source. So so for just a moment moment, if we take, you know, looking outside of GenAI, when you look at the rest of the things that people are doing, the numbers are are pretty close, which really tells us that buyers are doing a lot of different things.

They’re finding many interactions meaningful to support the buying process. So you can’t fixate on just one or even a few interactions.

You really need to understand what your buyers find most meaningful and make sure that you’re showing up to engage with them in those areas. But GenAI is definitely the most important thing.

So let’s go ahead and dive into just GenAI to see how buyers are using that. We specifically asked how are buyers using or planning to use GenAI tools in their purchasing process.

And the data shows that buyers are using GenAI to support them in quite a few different ways. They’re certainly gathering information about products and solutions.

They’re gathering information about different vendors and providers. They’re using GenAI to analyze data that they’ve already collected, and they’re also using it to compare offering strengths and weaknesses across the different providers.

In fact, sometimes they’re specifically looking just for pricing information, which also means that providers need to be a little more transparent with pricing so that buyers can find that. So this is a very wide and and varied list, and it’s kind of a tight grouping of responses.

So so as revenue teams, as revenue operations teams, as we’re starting to make go to market decisions and strategies and plan things, you need to think about how you’re feeding and supporting these AI engines. It’s really important for us to know what buyers are doing because that’s going to inform what information we prioritize as marketers and revenue teams.

The next thing that that we asked had to do with the actual results. So so great.

You know, buyers are using all of these things. They’re using GenAI for these things throughout the purchase process.

What do they actually think they’re getting as a result of doing that? So we asked a specific question about the results of the use of GenAI. What did that create during the purchase process for the buyer? And this has been an interesting question to track, and we’re gonna continue to track these in future surveys.

More than half of buyers said they considered more or different vendors by using Jet AI tools. So it’s almost like they’re discovering new vendors that they didn’t have in mind when they started their process.

So think of that as it’s it’s kind of opening up the playing field a bit, which could be good for vendors that that maybe aren’t high on the radar. We also see that respondents indicate they are spending less time with vendors or less time conducting research or that they purchased more quickly.

So if you think about those three responses kind of aggregated together, GenAI has effectively sped up the process for for those buyers. And then we also see that some folks indicate, that they either wasted their time or they were less confident in their decision.

So, you know, the takeaway is buyers love AI assisted search. They’re certainly using it a lot.

But as I mentioned earlier, they’re not necessarily trusting it implicitly. So we need to make sure that we put ourselves into the shoes of our buyers.

We need to understand that they’re using GenAI, they’re expecting results, but they’re also probably going to look for validation from what they get from GenAI so that they can mitigate any purchase decision risk. So I wanted to just kinda share some very specific insights around JennyI, but we also have other information, that we can glean from the survey that we do.

So we’re gonna move into very specific insights about the size of buying groups, what is the concept of the buying network, and then some very particular buyer preferences. So one of the things that buyers tell us is that the average buying group consists of 13 people inside their own organization and nine people outside the organization.

And also that those buying groups involve three or more departments. That is a lot of people that we as providers need to to know about.

So it may be easy sometimes to figure out who the buyer’s working with within their own department, but they’re also dealing with a lot of influencers and ratifiers in other departments throughout their organization. Maybe there’s an IT influencer, finance or procurement might be involved in some way.

Sometimes depending on contractual obligations, legal might be involved. And there could be teams involved from other departments if the offering under consideration has super wide enterprise implications, that’s gonna impact the whole company.

We also think people outside the organization have a very big hand to play when it comes to, helping these buyers mitigate risk. That may include analysts, partners or peers of the buyer.

You need to better understand who buyers are talking to and relying on to make their decisions, and that’s why we need to understand the concept of the buying network. A b to b buying network is the complete web of internal and external individuals, groups, and organizations involved in a business purchase.

While buying groups focus on internal stakeholders, so that that circle in the middle, that internal buying group, those are your decision makers, users, champions, ratifiers inside of the buying organization, but there’s also this whole entire ecosystem that are influencing those internal members. So it extends beyond that internal buying group to include providers, customers, influencers, partners, all of this kind of ecosystem surrounding, their own organization that buyers are connecting with for information, advice, and support throughout the whole customer life cycle, not even just the buying purchase, but once they become a customer.

And AI plays a role in the buying network too. The majority of buyers are now using generative AI tools during the buying process as well as AI agents that are becoming a more formal participant in this network alongside human stakeholders.

So if we dial into just thinking about that internal buying group at the center, one question we explored in the survey data was whether the size of the purchase would have an impact on the number of people involved inside of the organization. So I already shared a moment ago that on average, 13 people inside the buyer’s organization are involved in making a purchase decision.

But the larger the purchase and the more strategic the purchase, the buying group gets bigger. So for everybody joining us us here today, you need to think about your specific offerings that you’re marketing and selling.

Not everybody, you know, has offerings in the $1,000,000 or more range, but you have to think about the price and what impact that may have on the buying group. For a purchase price of less than $50,000 there are still nine people involved.

There are 14 people in that kind of middle price range and then the buying group swells to 18 internal people for purchases over $1,000,000. So why are these buying groups so big even seemingly for smaller purchases? Well, buyers are under pressure to justify spending and reduce risk, especially for those strategic or high value purchases.

No single buyer wants to take on the risk of making a bad decision for their organization. So what do they do instead? They’re building consensus.

They’re getting other folks on board to inform and defend the purchase decision. And that’s why we’re seeing such large buying groups even in those smaller deal sizes.

So one question we asked for buying groups, and and this question was specifically for buying groups of six people or more. And we were curious what the result was of having that many people involved in the buying group.

And a common theme was the reduction of risk. Having more people involved helped buyers understand the impact the purchase would have on their organization that they might not have otherwise thought of.

It also helped distribute the work to confirm the solution single or a couple people confirming that this solution meets their needs, they’re spreading that across a a number of different people that can help out. So sometimes you need to get users involved, right, to trial an offering.

You may involve people who will vet security requirements cause that’s not your specialty as the buyer. The involvement of buying group members really helps that buyer reduce the risk of making a poor decision.

So if we if we think about those top three answers, they’re all about that idea of reducing risk. When you’re developing buyer messaging and value propositions as a vendor, you need to provide the right information that gives the confidence to build a business case for the purchase so that the buyer can really defend and use that across the buying group.

At the end of the day, you’re just helping them tick all the boxes. Right? Answer their questions, so that you come out as the trusted provider on top, when they’re making a selection.

And you might be thinking that a large buying group might be slowing things down, making the purchase more difficult, But, actually, the majority of these answers from this question show there’s a positive impact of having a buying group involved to help secure the budget, to help gain approval. And that makes sense because if you leave important people out of the buying group, that’s when you start to hit obstacles and think the deals can stall and take much, much longer to close or even never close at all.

And if you we look at those answers, responses on the bottom, there was a relatively low number of people who said that there was a negative impact of having a buying group of six or more people. But I still wanted to acknowledge it because some buyers certainly are saying that the buying group added complexity, made it more difficult to build consensus, or it slowed things down.

But that’s the minority of of buyer respondents who cited those negative impacts. The big takeaway is that when you’re thinking about buying groups, focus on the positive aspect.

Understand that the buying group is representing the right people in the organization that are coming together to build the business case for making the purchase. So now that we’ve talked a little bit about buying groups, the buying network, you know, how those drive consensus and mitigate risk, we’re gonna switch gears and look at the insights related specifically to buyer preferences.

And we’ll start with information needs because one thing that’s always interesting is marketers always wanna know what content buyers are most interested in so they can go and build all the right content assets. But just as important are the information needs.

That’s what you’re actually putting into the content. What questions are buyers seeking to get answered? Because the information needs provide the context to develop messaging that’s going to go into that content that will resonate with buyers.

Now these are the most important information needs that buyers seek throughout the purchasing process. Not surprising to see price topping the list.

We are living in price sensitive times and budgetary concerns are top of mind. We also see offering specific information requirements at the top, features and functions, performance specifications, the product or solution options that are available.

When we think about those kind of third parties, you know, those people in the buying network outside of your own organization, peer and third party expert validation are important aspects here from an information need as well. And buyers are still seeking help defining the problem that they have, that the purchase is going to solve for them, and how the offering integrates into the current way that their organization is doing business.

So integration into their business process, or systems. And rounding out the top 10 most important information needs are customer support options and use case examples.

So most of this information is gonna be packaged up and delivered in the form of some form of content. So we do still want to know what buyers prefer in terms of content assets, and we ask that question as well.

Now, again, all of these results are aggregated across discover and evaluate and commit phases. We also can can cut our data to show specific phases, but these are the ones that rise to the top across all phases.

So a preference related question we ask is related to the types of content that are most meaningful throughout the buying process. And one of the things to keep in mind is some of this content is not even being produced by you as a provider or a vendor.

Right? It’s being supplied or produced by influencers or third parties. So one of the things we’ve seen rise to the top are analyst, research, and executive reports.

Even success stories, you know, here at at number six, the hires are looking for someone to help them understand why it’s important to solve the problem now, why they need to invest in in solving the problem today, and how it has worked for others. So so even if the vendor is the one offering or supplying the report or the content, it’s backed up or validated by third party experts.

Buyers want that that external point of view and validation. We can even see independent third party videos make the top 10 list here.

So buyers are getting lots of good information as they’re going out and doing all their research, especially AI assisted research, and then they’re moving to ways to validate that research. They’re looking to do that through their buying network.

So they’re expecting to receive good information from vendors, but they’re also validating that with other trusted sources that we will find in that extended buying network. And then the final insight I wanted to share, I I already shared that kind of large table of the interactions that that chart that showed all the percentages, but this data kind of curves it down and just shows the top 10 interactions that b to b buyers said are most meaningful across their purses purchasing journey.

And the thing that I think is fascinating, if you look really closely, seven of the top 10 are self guided, So the the dark green. That means buyers are researching, learning, evaluating, and they’re deciding long before they ever wanna talk to anybody.

And so from last year’s survey results, you know, we saw some differences here. Product experts last year were the number one most meaningful interaction.

They’re down to number five in this year’s survey with generative AI, of course, being number one. Social media and industry conferences, those moved way up from last year’s survey.

Another interesting shift. Sales representatives last year were the third most meaningful interaction.

They’re all the way down to number 10 this year. So I I think what this tells us, you know, the the uncomfortable truth, most go to market motions are still built around how we as vendors want to market and sell.

They’re not built around how buyers actually buy. We need to change that and we need to make sure that we have a deep understanding of our audience so that we can build the right information, the right context, the right asset types, and the execution requirements.

So with all of that, let’s let’s assume we’ve done a good job of capturing insights and intelligence about our audience. How do we actually translate that into effective go to market execution? The reality is that most go to market strategies fail for one simple reason.

The strategic decisions made do not ever make it into execution. A connected go to market approach is needed to provide the structure to unify decisions, align stakeholders, and operationalize strategy.

At our recent, b to b summit, we launched the Forrester Connected Go-to-Market Framework, and it was exactly developed to help b to b leaders and their teams connect what they decide, what they plan, and what they execute across product, marketing, sales, customer success, revenue operations, and revenue enablement. And at the very center is the buyer because everything that we do should be about delivering a connected, coherent experience for buyers, not disjointed handoffs between internal teams, certainly.

Revenue operations and revenue enablement, the reason they’re kind of in that middle, you know, white band, they play a critical orchestration role across the entire framework. But success only happens when they’re pulling in product marketing sales and customer success and making sure that those leaders and teams are also engaged.

Now the framework is organized into five connected phases from strategy all the way through to measurement and optimization. But for the time that we have today, I’m just gonna be focusing in on phases two and three, go to market planning and execution requirements.

So in phase one, once the go to market strategy has been determined, revenue leaders have to co develop an integrated revenue production plan. This is where revenue operations leadership is absolutely critical and required.

They take the go to market strategy clarity, so which market segments, which offerings, and which buyers to focus on, and they translate that into operational planning. So if we think about the key stakeholders that are involved, revenue operations is kinda leading the charge.

But too often, it’s this planning phase where disparate team plans get created. So each functional leader goes off and builds their own plans, and that just sends go to market leaders in different directions and off course.

So this is where revenue operations leaders are working across functional leadership teams to evaluate direct and indirect financial goals, budget allocation, resource coverage, partner relationships, if they’re in scope, and then shared performance metrics. And a crucial input to this phase two is something we call the go to market pathway.

It’s the core artifact that gets produced at the end of phase one, and it’s something tangible that captures the strategic choices that the business has made. Now depending on the complexity of the offerings you have in your portfolio or the number of strategic revenue objectives that your organization might have, you may have more than one go to market pathway that you’re developing.

But today, I’m just gonna share a simple pathway example so you can see what it looks like in practice. So this represents a completed go to market pathway for an HR product line within an organization.

The green boxes represent the prioritized go to market strategy choices that were made by the leadership team, decisions that were made to optimize where the organization should focus to generate revenue with existing customers. Now this pathway could look completely different, with different green boxes highlighted, for example, a new customer acquisition motion, but we’re gonna focus on that existing customer.

And if you look at what’s on the screen here, every single one of these dimensions and segments represents a universe of potential. And too often, what happens? Well, our leaders wanna go after all of it, right? All industries, all organization sizes, every region, all routes to market, all offerings, and all personas.

And that’s really not realistic from an execution standpoint. Instead, leadership teams have to make evidence based trade offs.

In this pathway example, where the strategic objective is to expand within the existing customer base, leaders intentionally prioritize high technology and professional services organizations rather than attempting to target every industry. And this is the power of the go to market pathway.

Revenue operations, enablement, product, marketing, sales, and customer success teams, they all now have one shared source of truth. So those pathways are inputs to phase two planning, and and then revenue operations leaders are working with functional leaders to develop core artifacts such as go to market strategy on a page.

There’s kind of a roll up of those pathways, revenue goals by channel segment and offer, and the revenue production plan. So I wanna kind of look at just one example artifact here.

This is where we can see a detailed plan for those booking goals. So whatever targets were set by the organization, but we start breaking it down against the go to market pathway choices.

So this example shows how goals are split across new and existing accounts as well as the opportunity type, acquisition, upsell, cross sell, or retention renewal efforts. It shows the expected breakdown of revenue by the route to market, direct, indirect, or ecommerce, as well as the segment and the offering specific expectation.

This is really the level of depth that’s required to support downstream execution plans, and these artifacts become inputs to the next phase, which is phase three. So let’s just take a a look at what happens in phase three.

So imagine that the strategy and the planning from phases one and two are perfect. But if you do not specify the roles that are required to do the work, the systems and the processes that are needed to support the work, and any dependencies that exist, execution is going to fail.

And and here’s what happens. Most go to market teams jump from planning straight into execution tactics, and they miss the moment where they need to actually build the execution requirements.

I personally feel like phase three, like this is truly where the magic happens because it’s where shared understanding turns into coordinated action. Once again, revenue operations leaders are the ones that are leading the charge at this particular phase.

I think that a lot of times if we think about execution breakdowns, they’re not happening becomes because teams are disagreeing. They happen because the wrong people are in the room building the requirements, from the start.

So phase three is about aligning the people who define execution and whose teams are going to be doing the actual work. And by the way, that work is likely a combination of AI and human capabilities.

So so revenue operations is absolutely critical here. They’re the orchestrators pulling together leadership teams across sales, marketing, product, customer success, as well as partners, enablement, and portfolio marketing leaders.

And and if you miss this phase, if you miss this step, execution is going to be chaos. But get it right, and strategy and planning inputs will finally translate into systems, technology, processes, data, and the day to day decisions that individual contributors and teams need to make to be effective.

So we we have to take a look at the core artifacts from phase two that are required inputs here at phase three. We don’t I think what happens at phase three, we don’t just take these artifacts.

They’re not just artifacts anymore. They’re what I would consider commitments.

Right? So this is where those go to market teams, they’re gonna be held accountable to the same revenue reality. So those are those artifacts from phase two are critically important, but we’re getting commitments across them from all of the individual contributing teams that have responsibility for execution.

But one thing that tends to happen is companies drown in multiple functional plans. They’ve got lots of different marketing plans and subfunctional plans, sub submarketing plans, sales plans, customer success plans, enablement plans, and yet we still are not executing effectively and and hitting our revenue targets.

So the missing piece cannot possibly be to go develop more plans. Instead, we need a single integrated go to market playbook that orchestrates the experience of our buyers and customers from end to end and then disciplined functional plans that bring that playbook to life.

So I thought I would share just a couple of elements of of a go to market playbook. And, again, this is where revenue operations really facilitates the creation of an integrated cross functional go to market playbook.

This is not something that a single team is putting together because quite frankly, no single team owns responsibility for the end to end, execution of the go to market strategy. So here’s an example of what core information is required to include in that go to market playbook.

Those go to market pathways are the first element because that shows the prioritized market segments, offerings, and buyers. We also need to include specific buyer persona details.

That’s going to help all of our buyer facing roles understand the target audience. Journey maps, that connects the information needs, the content assets, and the interaction preferences of buyers so that everybody in the organization knows what those buyers what we need to do to meet and engage with those buyers.

And then messaging guides that are going to inform campaign themes and campaign strategy and content development. These are the core elements that will be used by functional leaders and their leadership teams to develop roles and responsibilities documentation to make it crystal clear which teams have to engage with buyers at different touch points and milestones across the journey.

And those disciplined functional plans get developed with detail, you know, the programs down to the tactics that have to be deployed. And certainly metrics, we can’t forget about metrics.

We shouldn’t be developing isolated tactical metrics that each team is tracking. Instead, we need to set a shared metrics that should be established that track back to those go to market pathways, back to those specific segments and offerings and buyers that were prioritized.

And when this is done well, every single team across the go to market engine knows what audience they’re serving, what role they play, and how their work connects back to the go to market strategy. So, Jim, I know that was a lot of information to unpack, the impact of AI on the purchasing process, the many buyer insights that help us understand, you know, the importance of the buying group and extended buying network and all the specific expectations, The idea that future go to market success requires a framework that leaders and their teams can use that connects strategy to planning to execution.

So at this point, I think I’ll turn things back over to you for some, you know, additional and final thoughts.

Jim Bell

38:05 – 38:08

Alright. Switching over.

Katie Fabiszak

38:08 – 38:13

Is anyone else hearing background noise, or is that just me?

Jim Bell

38:13 – 38:15

I have it on my end. Are you are you hearing that?

Katie Fabiszak

38:15 – 38:20

I heard it sounded a little bit like talking in the background. I don’t.

Jim Bell

38:20 – 38:25

Let me just pause for a second and see if I get people to move away from this room.

Katie Fabiszak

38:25 – 38:53

sorry. I I I was I wasn’t sure if it was just me, but oh, okay.

Oh, okay. It wasn’t just me then.

Okay. Good.

Yeah. It was just me.

I think when I just stopped and maybe that was the only reason is because it picked up.

Jim Bell

38:53 – 46:11

Yeah. And I I was I was muted, so I think, and I was worried about the same thing.

So I appreciate you pointing that out. So okay.

Let me get my screen ready. Great.

Thank you, Katie Fabiszak. Yes.

There is a lot, that you shared there. You know, as as marketers, as rev ops people, etcetera, I think it’s, it’s our job to take that sort of, revenue production plan, that table of of dollars that we need to deliver on, and try to make that a reality.

And it just is can be challenging to do because I’m beginning to think I’ve been at this a long time. I just don’t know if the buyers are really gonna follow this nice process we’ve laid out for them of what they’re supposed to do.

So I will say on behalf of the rest of the industry, we’re so grateful for the the work that you all do, in studying the buyer behavior just to help us make sense of it because it is constantly changing. It is getting more and more complex despite all technology designed to make it simpler.

So I would like to give just a brief overview of lead data for those of you who aren’t familiar. Our focus is helping turn that strategy, that revenue production plan into revenue and to do it in a way that you have confidence that all the actors in that process, those can be people, those can be your systems, those can be agents, are sort of playing the role you need them to play and that you’ve got smooth handoffs across those, those different players and that you’ve got a dataset that is trusted enough, for you to be able to, yeah, begin to turn more and more of that into agentic processes and to trust AI.

So, at LeanData, we automate, we go to market across the entire revenue life cycle. Katie talked about both sort of existing customers as well as new customer acquisition.

So we have a number of different use cases in place that we help people run. On the acquisition side, most of our customers come to us first to do things like inbound lead management, account based marketing, increasingly buying group automation, trying to manage that increase in group, folks who are involved in the buying process, but also, beginning to incorporate more things like agentic SDR processes and things like that.

And then they tend to grow over time across the different elements of the revenue life cycle, expanding into things like customer onboarding and, handoffs from presales to postales, partner implementations, which Katie also talked about, as well as retention use cases, even involving things like service case routing, etcetera, and onto, expansion processes as well. And what we do in that process is we kinda start out typically by helping people sort of manage the their data and make sure that it’s trusted to be able to act on across, the process as things get handed off from system to system and team to team.

So that different, signals that come into the go to market process, whether that’s from an SDR agent, a buyer intent signal, or some data gets enriched that gives us some new information or somebody changes jobs, whatever that might be, that those agents are turned into actions, on the on the go to market, side of things. So that could be anything from simple notifications.

It could be from, scheduling meetings to move the process faster, through our our scheduling, product BookIt, as well as things like identifying opportunities and then really driving across, the go to market process. One of our one of our larger customers just last week told us, you know, at LeanData, you guys sit on that wall in in between marketing and sales, not to mention the wall between sales and customer success.

And it provides an incredible amount of value for two teams that don’t often work that well together, don’t often coordinate the work that they do. We are that connective tissue across the go to market teams.

We’re really proud to have some of the world’s most respected brands, as customers, including even, AI companies that use us because they need a trusted, revenue process that’s going to work and be a deterministic, outputs that are gonna drive revenue and handle really complex types of go to market processes. And we got a sense of that from what Katie shared of how just how complex those things can get as you look across the revenue life cycle.

I’ve highlighted Rockwell Automation here. They recently won a Forrester return on integration award.

I want to just quickly, I won’t do it full justice, tell a little bit of their story. So Rockwell is a hundred and twenty year old multibillion dollar company, and they really shifted from, sort of manage it managing this process, on a you know, sort of working through IT, very much of an sort of older school, you know, SiriusDecisions or Forrester, you know, revenue waterfall to a much more modern, process to to support this.

So they partnered with IT to give them more business agility, and that allowed them to orchestrate sort of enterprise wide across a single CRM, to create that transformation to implement the revenue waterfall from Forrester to establish clear governance and shared data so that they could, give teams in different regions globally, the right level of, customization to manage their own processes, but to align on a single, unified reporting platform and to be able to handle sort of, and execute globally. And they saw some really great results.

So they moved from a very much of a lead centric system to more of an opportunity based system where they’re compiling buying groups and passing those off to the sales team. Just even matching new leads or new contacts into the right accounts was a manual process with, you know, 10% match rate automated in their system, so they moved that up to 85%.

We certainly see customers in the high nineties on that on that metric. They’ve gotten more agile and fast, so less than five minutes to get to opportunity creation, which usually take them seven days.

Some really great results in terms of accelerating the, the sales cycle and opportunity progression through the stages, particularly the early stages, and also an increase in marketing source pipeline that have really helped them sort of rev up that, that engine on the go to market process side. So with that, I wanna sort of bring you back up, Katie.

There’s a lot of information you shared. I particularly love that you had the buyer in the center of that model.

I think it’s so important to remember. So as you think about and and and talk with people and, certainly, the data is showing that AI is now everywhere, and, it’s amazing to see how that ranking has changed of how much people are using it.

Where where do you see AI impacting how go to market and revenue teams work together to engage with b two b buyers?

Katie Fabiszak

46:11 – 48:28

Yeah. Wow.

That is a that is the question of the century, isn’t it? Big question. I mean, the reality is buyers are getting answers without necessarily visiting or talking directly to a vendor anymore.

Right? Especially in the early part of of their journeys. And I think that requires go to market teams to rethink engagement, accountability.

I think that’s gonna be the biggest impact, but certainly, AI is undoubtedly gonna play a role. I do think the degree to which it plays a role could differ, and I think this is why it’s so important that we as go to go to market teams and revenue teams, we have to understand the audience.

It’s it’s absolutely critical. So, you know, just a quick example, if your go to market strategy decisions prioritize buyers who indicate self serve interactions and heavy reliance on generative AI to support their decisions, then b two b teams have to build execution requirements to make sure they’re delivering the experience those buyers expect.

Right? And that could be a combination of things. One, like, ensuring the right information shows up to support the research that buyers are doing within GenAI search tools.

But two, maybe leveraging AI agents that will directly engage with the buyer as they move through their purchasing process. And three, how do those teams use AI internally to facilitate workflows across teams to make that that seamless for that kind of self-service, delivery to the that buyer.

But you might contrast that with maybe you’ve made your leadership team, made go to market strategy decisions where the prioritized buyer, expects more personal interactions. So in that case, those b to b teams, those go to market teams, they have to make sure they’re building execution requirements that favor more of a human engagement and delivery of the experience.

So I don’t think there’s any doubt AI will be required, but I think what the the biggest impact is really gonna be the mix of human involvement and AI assistance, and that could vary greatly depending on the target audience. So I think I mean, this is where I think revenue operations folks really are are gonna be the, the magic that makes that happen.

Right? So I know there’s a lot of rev rev ops folks joining us today. I think for you all, the biggest opportunities, how do you help your human colleagues pair with AI to orchestrate what’s required across marketing, sales, and customer success to really deliver the outcomes that buyers are expecting? That’s that’s gonna be the challenge.

Jim Bell

48:28 – 50:09

Yeah. Absolutely.

I think, that reminds me of sort of a customer spotlight at that same summit, with Uber for Business, one of our customers talking about how they’re deploying agents in the go to market process. And to your point about, you know, sort of the, you know, the map of the segments that you’re going after and sort of the, the segmentation part of this, you know, they were very careful about picking where they were deploying those those agents and leveraging AI.

So in their self-service funnel, they are using it pretty heavily for customer onboarding, and and really driving that process to take out the, you know, the human element where they don’t need it. But then, if the agent is unable to resolve a customer issue, which which might be something about a credit card or or something else, then it, integrates with our scheduling system so they can find the right onboarding agent, the right human onboarding agent, and to schedule a meeting right in line, right, with the chatbot, or with the emails that they’re sending from that agent to continue that process and get the human innovation where there’s higher value add or need from a customer standpoint.

And then they’re they are using agents more fully in other segments, but those are ones that are not at that top level of what’s gonna deliver against that revenue production plan. So it might.

be the education market where there have an agent doing sort of all of the outbound, to that to that segment. And then if it bubbles up enough, right, it gets assigned to a rep, etcetera.

So I think it’s a really important point you make of it’s still you know, great execution still comes back to that strategy and that plan,.

Katie Fabiszak

50:09 – 50:09

Yeah.

Jim Bell

50:09 – 50:30

to get there, and it has to be cross functional. So.

absolutely. Yeah.

And then that sort of go going back to now that connected go to market framework that you you talked us through, I mean, where do people struggle with that? What phase is toughest? Any advice you have for people trying to get their arms around it?

Katie Fabiszak

50:30 – 52:21

Yeah. I had a lot of conversations about the connected go to market framework, and here’s what’s interesting.

Everyone has a different opinion of which phase is most difficult and where the breakdowns occur. I think it depends on who you talk to.

The folks setting the strategy think the strategies, you know, phase one is going perfectly well and they point to execution, like we’re just falling down in execution. And then the folks responsible for execution point to earlier phases and cite lack of strategy or planning.

Right? We’re not doing well in phase one or two. I I personally think the measurement and optimization phase five is quite difficult for teams, especially since we’ve historically been measuring in silos, and we really need to break that mold.

Like, we have to evolve and modernize how we measure. Revenue teams are still relying on legacy metrics.

Right? But AI search and self serving buying, it it reduces the the need to measure those things. Right? So we need to kind of think a little bit more, modern and into the future and what we need to measure.

And I think revenue operations is gonna lead the charge for that. Right? They’re gonna make sure their organization’s measuring both business outcomes and customer value outcomes.

I mean, at the end of the day, if we do a really good job with the customer value outcomes, the business outcomes will come. But we don’t think about things that way.

Right? But I do tend to see the biggest challenges when working with clients in phase three. Because those execution requirements, that’s where teams have to integrate and align systems, workflows, data, and enablement so that the execution is effective.

And I think too many teams skip that critical phase, right, or they rush past it. Right? They go straight from planning into execution tactics.

So, I I would say, you know, probably phase three is if we do that really well, and it’s, of course, we have to set the strategy and planning, in motion to do that. But if we get phase three, if we do that really well, we’re setting ourselves up for success to execute and and to meet, you know, buyers where they are.

Jim Bell

52:21 – 53:06

Yeah. Yeah.

Absolutely. And, I agree with you.

I think that is what what we see as well is that challenge of just trying to when once you get down into the execution, people tend to sort of move into their silos and then sort of, just operate within that their own echo chamber, etcetera. And I think it’s always been the case that people that sort of work across the revenue life cycle better and have shared shared KPIs and metrics and look at stage progression and less about attribution and those kinds of things have been more successful.

How do you think that changes with AI and certainly agentic processes coming into that, as we go forward? Does that increase or decrease the level of coordination needed?

Katie Fabiszak

53:06 – 53:57

I think it increases the level of coordination. Right? But I think that that’s why revenue operations become such a critical team.

They’re the ones connecting the data. Right? They they’re the ones that can align the incentives.

I mean, sub functional teams are still gonna have to your point, like, right, they have very specific things that they are being measured on. But we need to get to an alignment of incentives and shared metrics tying back to the go to market strategy so that every individual contributor across those teams can see the role that they have to play against that strategy.

But, again, I think revenue operations is critical for connecting the data, aligning those incentives, enabling kind of optimization across those core teams that are delivering, like the go to market engine. Right? So sales, marketing, customer success.

And we need that kind of cross functional player to make that happen and orchestrate success.

Jim Bell

53:57 – 54:41

Yeah. Completely agree.

I think the this is a is a great time a terrifying time in some ways, but a great time to be in revenue operations because, never has there been a higher need for that level of coordination, for taking that strategy and that plan and putting into execution in a way that, leverages the AI and the efficiency and hopefully the better outcomes that leadership is demanding, requiring, you know, pushing for. But while maintaining the confidence in the system, right, and the trust that things aren’t gonna get, sort of spin out of control with agents or acting on bad data or things getting, you know, leaks in the system.

And, again,.

Katie Fabiszak

54:41 – 54:41

Absolutely.

Jim Bell

54:41 – 55:27

that’s why I think, certainly we have seen even some of the the biggest AI leaders in the world, still leaning on us to didn’t mean to make a pun there, to, to to create that trusted system that can handle that complexity, and make sure that they have a leak proof system, in particular, in our case sometimes, and also not having to make a gazillion API calls into the CRM, like, for every every decision that they can do along the way. So I’ve been doing this.

side. Katie, thank you so much.

I think really some, just appreciate all the work that you’re doing and that Forrester is providing to help us make sense of the world that we’re in. Everyone, I think, has their own challenges in trying to address it, but, thank you so much for giving us some very helpful guidance in that process.

Katie Fabiszak

55:27 – 55:30

Of course. Thanks for having me.

It’s been a pleasure.

Jim Bell

55:30 – 55:41

Alright. Thanks so much.

With that, we’d like to say thank you to everybody who joined us today, and thanks again to Katie, and the team at Forrester for all the great work there. Have a great day.