Invictus Guild Summit: Harnessing Data for Your GTM Motion

So the basis of today’s conversation is why, more than ever, data hygiene and knowing the right data to track, the right KPIs to track around a deal, both won and lost, is really, really important and is a differentiator. Because obviously, data in to these tools that are AI- enabled is a really, really important factor. And so a lot of that work can be done, not just from sales leadership, but from product, from finance, from all areas of a business. And we’ll get into the weeds on that.

So before we get into the main crux of today’s presentation, actually, let me introduce myself first. It’s probably best. So I’ve been involved in the Guild for a little over a year now. I’m technically tied to Fund2, although I’ve met with many of the portcos in Fund1. And I’ve just been really impressed with not just each individual portco’s journey, but also just the collaboration and alignment. Whenever I’m on site at these summits, there’s just a lot of best practices that are shared.

And while I come to you today from a pretty large, notable public company, you might be saying, well, how does this pertain to my business? You know, for perspective, I run a commercial org within S& P Global Market Intelligence, which is a division of S& P Global, that manages approximately about 650 million in ARR. But that wasn’t something that I adopted. I’ve been here for 14 years. About seven years ago, we stood up our first corporates vertical.

So we moved to a segment vertical model, which again, I’ll tie into the importance of data, data hygiene and tracking the right data. But in terms of my journey, it’s been steeped in growth through acquisition and integration. And so that’s where hopefully my experience in scaling teams that we’ve acquired, some of whom had as little as 2 million in revenue, were all inbound, didn’t have a sales team. Others, we’ve acquired around the 60 million mark, obviously, with the goal of growing them to 100 million in short order.

And so a lot of my day to day isn’t just running, you know, a core base of revenue for S& P. It’s actually an integrating and scaling acquisitions that we’ve made. And we’ve actually just made another acquisition with intelligence. So that’s a private markets, private company data provider specializing actually in private equity and working with private equity firms. And we beat out potentially BlackRock, we believe, to acquire this firm. And I’m actually onboarding them right now. So the journey continues.

But I’m excited to get into the conversation with Mark here. Mark, I know that everyone knows who you are and the work that you do. But I’d love to turn to you for a quick intro, and then I’ll kick off.

Thanks, Jack. So hi, I’m Mark Chiamnis, partner and head of data science at Invictus. I’ve been doing this thing called machine learning or data science. Now it’s called AI for about 30 years. And I’ve been doing a lot of sales automation with it since my days at EMC. Back in 2010, I implemented a data driven process very close to what we’re going to talk to today. And that was a fully automated process for upsells at EMC that resulted in $ 100 million in annual sales. And then that’s when the switch went on in my head.

And I realized by using data and machine learning algorithms and automation and integrating those with the human process in Salesforce, and having kind of this continual feedback was a really powerful mechanism. And that led to my journey here at Invictus. Thank you.

Perfect. So Mark and I will be having hopefully an engaging conversation about data. Mark and I both love data. Mark comes from a very technical side. And it’s interesting because my job as a commercial leader, I run sales and account management, but also work closely with marketing.

My job and the drum that I beat every day is for the sales teams I lead to care about data, to care about CRM hygiene, to care about asking that extra question at a presale when you’re diagnosing a client’s problem, to obviously hope that there’s a fit or identify a fit for a solution, whatever that solution is. Commonly, the desire of a sales professional, and I’m definitely one of those, is to get to close as quickly as possible.

But along that journey, there are really valuable opportunities to gain insights that go beyond just whatever it takes to close a deal. That could be reaffirming your value proposition for whatever solution you’re positioning. It could be better understanding the competitive landscape. It could be understanding why a prospect or a client has even taken the call.

What’s going on in their journey, what events are impacting their desire to meet with you, and a lot of that information is kept if you have a really engaged and bought- in sales team. Through your CRM it could be a call note, it could be you’re recording calls and you’re transcribing them. All of those things are present. They’re records for reference. But how you actually collect and aggregate and then share that data across an organization mark- and I really connected on this- that this sits outside of just sales.

This should be a product vested interest, this should be a finance vested interest. Obviously executive leadership have a vested interest. And so when you think about pipeline, when you think about deals that are in motion, constantly going back to ensuring that you’re collecting the right data around a deal to understand why you’re in the deal in the first place, beyond just budget and product features and functionality- has a really strong impact in being able to constantly revise your go- to- market.

If aggregated and aligned internally and everyone’s bought in, to be able to evolve your go- to- market effectively and then better identify tier one targets. And Mark’s gonna get into this. Obviously anyone who’s an Invictus port co has the benefit of leveraging Mark and Diane to be able to tier your TAM and have a very prescribed target list, and that’s great. But also understanding what goes beyond that in terms of why you’ve lost and why you’ve won, I think is not something that is talked about enough. You can find lots of books on Medic.

You can find lots of books and technology on the sort of the AI- driven go- to- market motion. Now outbound is being flooded right now. The clients are being flooded with outbound across all of these platforms.

But actually figuring out how and why you’re differentiated in a conversation beyond product really comes back to just being bought in to data hygiene within your CRM and then making sure that it’s a conversation that unifies product marketing finance all together, so you understand where to allocate resources, how to make hires and scale teams effectively and, most importantly, not go down the rabbit hole of chasing companies that aren’t ready to buy, and I think that that’s a sales professional’s worst nightmare.

You spend three, six, nine months on a deal and the data may have shown in the first month that they’re not in a position to buy, and while they’re having a conversation with you, they’re not at a point in their journey where they can make that commitment. And understanding what those factors are and what those indicators are is a real differentiator. So we’ve touched on a couple of these topics. I just wanna quickly go through the agenda.

So, again, I’m not here to say you should change the way that you go to market, but I am here to say that data should be a leading factor in how we all collectively, regardless of whatever evolution, whatever stage your company’s at- getting a shared dialogue and vocabulary around data as a unifier across functions is really important, and I think it matters more than ever in the age of AI, where it’s really easy to deploy messages out to a market and flood your prospects with messaging, I think, understanding again the importance of data hygiene and then, obviously, leveraging the tools like Diane to be able to constantly iterate or go to market.

This isn’t something that should be done in Q1 and you set it and forget it.

If it’s a constant feedback loop where data’s at the forefront of those conversations internally, your go to market’s gonna evolve over time and I think that that’s a really effective way to make sure that you can successfully pivot from inbound to outbound without making hires maybe in the wrong area or over indexing on a certain sector or vertical with the assumption that it’s a great fit and while that can play out, I think more than ever everyone’s being asked to do more with less.

That’s natural in this market cycles that we’re in, and so being really ruthless about how you spend your time, how you set marketing’s focus, how you set sales focus on a specific target- all ties back to data and data hygiene.

So, challenging the conventional wisdom. Again, I’ve seen some really great presentations where product has been at the forefront, great product, obviously, clients, that’s why they’re ultimately gonna purchase, that’s why they’re gonna do business with you, you need great product, and that’s assumed. And I think product- led growth and go- to- market, certainly in early stages, I’ve seen this as I’ve integrated for startups within the S& P ecosystem. You can experience a high level of growth purely on inbounds.

Obviously, if you have great market fit, great product, but there becomes a point in which, especially if you want to sell to the enterprise, which Heather and I have been discussing prior to this presentation, the outbound motion is critical. And the type of go- to- market motion when it comes to outbound is obviously gonna be very different than a largely inbound motion centered around product features, functionality.

And so a lot of that really is gleaned from conversations that sales or your account management team or customer success are having in the marketplace. But seldom do I see that there’s a rigor and commitment to sharing that information internally on a cadence basis, could be a monthly basis, could even be a weekly basis, depending on where you are in your evolution and the importance of sharing this information.

But a big factor is understanding that product needs to know when a conversation isn’t going well, just as much as they want to celebrate a win. And when it comes to diagnosing and having these client conversations, obviously recording them are great, transcribing them is great, uploading them into GCRM is important, but actually buying into this notion of a shared data language, understanding that every touch point with a client, good and bad, has value.

And sharing that internally can really help shape what your go- to- market looks like in real time when it comes to outbound motions. And Mark and I will touch on this. He’s been doing some great work, obviously with Diane, which many of you are on the receiving end of, but there’s still work to be done in terms of buying in to, especially for tier one, where we see the data supports that odds are that you have greater odds of winning a deal if you’re focused on tier one.

And so as Diane evolves with the data that consistently is put into the machine and the outputs are obviously actionable, it’s important that Mark and others within Invictus are obviously getting or a part of that feedback loop as well, so we’re gonna get into that later on in the presentation. A couple of other things, just in terms of when I talk about data, I’m not just talking about deal- specific data. So company- level information, is a prospect or a client, have they gone through an acquisition? Have they had a rounds of funding?

Have they recently gone public? Have they had executive- level changes? A decision- maker that you would profile and target based on title? Are they new to the role? Within the industry, is the sector up or down? Has there been competitors on the prospect’s side who have made maybe investments or commitments that might align with whatever go- to- market motion that you’re executing on? A lot of that information is in the era of AI, ChachiBT is really easy to attain now. In the past, you used to have to go and pay for subscriptions.

Capital IQ is actually a flagship product of ours. A lot of firms use it for go- to- market. Business development, it has over 50 million companies, private and public. Profile, there’s a lot of useful information in there. But in the era of AI, you can also gain this information really, really easily.

And so, making sure that there’s an established understanding on what data matters across function, whether it’s marketing, sales, finance product, a lot of that should be just as centered in my mind around company- level attribution of those targets, as much as it is around the individuals that you’re trying to target and obviously the workflows and personas that your solutions support.

And that’s a relatively new evolution, I would say, in obviously going beyond just individual engagement attribution and broadening your data warehouse to include company- level information to that level.

Just in terms of challenges when it comes to outbound, I think one of the things we’re all inundated with, with messaging, we use sales loft here at S& P, there’s outreach, there’s these great tools out there, but personalization, I think it’s hard to dispute, is really a differentiator. And that could be in messaging around the value that you add in a given market. I know that we’ve had some really good summits around cyber and the talk has been just as much about what’s going on in that space as it is about products and features and functionality.

So understanding how to personalize messages, how to be able to connect with key decision makers. Obviously, you can do that at scale, but really understanding the attribution at the company level, at the individual level, why they’re willing to take a call, why they didn’t buy from you previously. And then obviously tying that back into the personalization is a real differentiator.

And that’s how we’ve successfully been able to stay differentiated from some of our main competitors, whether that’s AlphaSense, which has a really, I would say, aggressive sales motion. They’re out there really transactional in our space. Definitely tech forwards in what they do, but understanding how we can stay differentiated through personalization. Again, this all goes back to data, data that you track, data that you keep, data that you share across your enterprise.

The other thing in terms of being able to scale for outbound, I think there’s just natural limitations when you have product- led growth. Obviously, customer insights are really gonna center around the product and product fit versus where they are in their journey, in their life cycle in terms of a willingness to buy. And so with outbound, again, taking it beyond just establishing or diagnosing product fit, collecting that data, making sure that it’s kept with high hygiene within your CRM, really, really important.

And the last thing is we’re in a challenging market. I don’t think there’s any industry clients that I speak to every day where they’re not going through something. It could be tariffs, trade. It could be hiring, retention. It could be geopolitical. There’s a lot of factors out there impacting businesses. And obviously with the outbound motion, understanding where you’re meant to be spending your time, making sure that you’re focused primarily on your tier ones, understanding why a company is tier one, all of that, again, ties back to data.

Mark, anything to add in terms of, as we’ve switched the conversation to data- led go- to markets, anything that you’d like to share?

Yeah, I think that, really, the punchline is that what worked six months ago is not gonna work going forward. And that Jack mentioned data and personalization. Six months or a year ago, sending out bulk emails and kind of a generic go- to- market motion just isn’t gonna work anymore. It’s become such a more intense competitive landscape. There’s all these new tools that are out there that doing what you used to do just is gonna see diminishing returns. And Jack and I have looked at some data that show that.

And so, really, we’re kind of at this point where your competitors are using AI and doing personalization and leveraging the data that Jack mentioned. And so, that’s just gonna become table stakes going forward.

Yeah, there’s some great research out there. Gong is at the forefront of a lot of this. Obviously, their product is very well- positioned to get really granular in terms of what’s working and what’s not because of just the volume of sales calls that they are transcribing, but also able to aggregate. And one of the stats that they talk about is organizations that leverage AI have seen a 29% revenue growth and 11% greater go- to- market efficiency. And obviously, that banner of AI, that’s the technology, that’s what you leverage.

But actually, the value of AI is really around the data that you put in. And so, Diane’s a great example of that. But in terms of your go- to- markets as well, there is a real drive, certainly at S& P here, to be able to go that extra mile to collect this data, to understand the value of data in and around a deal, but also for retention, for churn, or it goes beyond just point- of- sale data.

And a lot of that can be leveraged as you refine, you go to markets, leverage AI tools, just like building a prompt, go to market is no different. And that should be constantly fed with updated information. And then obviously shared across the organization, not just harbored within commercial. And so a lot of that is really just have to be intentional about it. And so in my case, I’m meeting monthly with product and we’re sharing a lot of this information. And we’re asking in return, that they evolve prioritization for products enhancements.

We’re asking that they join more client calls. I think that’s really important to be able to affirm the value proposition or the messaging that we’re hearing. So again, I invite products or I encourage my team to invite product to calls where there’s friction, where there’s pain, where it’s not a clear win. And a lot of learnings can occur through that, just as much as involving them in the presentations where things are going well and there’s line of sight for purchase. And I think that’s a real mindset shift.

I think generally speaking, we’re all over prescribed in meetings and there’s this notion of better time management, trying to be in less meetings. But I really believe that having this be a part of your weekly or monthly motion and committing an organization across function to buy in to everyone’s, all of this data is important. It’s not just about a sales motion. It’s not just about a marketing motion. product, go to market motion in a vacuum. It should be the connector and that should become a shared language.

And that’s definitely something that Mark and I agree on, align on. And I think having the resource of Diane, having the resource of Mark to be able to leverage and extend to that conversation, I think is really, really great. I actually don’t have a data scientist that I can leverage. So a lot of this work we’re doing ourselves and it takes time. It takes longer than it should. We don’t have a system like Diane. So a lot of this is being built within our own limitations of off the shelf tools.

But I’ve still seen the level of impact for outbound motion to be able to go and get those multi six figure, seven figure deals. And a lot of that has been in understanding very clearly what tier one targets are, why they’re a tier one target and then being ruthless about disqualifying, tier two and three, where it’s not an obvious fit, even if they fit the old profile of they have X amount of employees or X amount of revenue. If they’re not where they need to be in the journey to make a purchase.

And a lot of that information’s out there that could be in earnings calls if they’re a public company, an executive may be making statements around cost cutting measures or budgetary constraints or they’re about to make an acquisition. What they’re about to make an acquisition, are they really gonna make an enterprise technology purchase during that phase? And so having all of that information, whether it’s textual data or point of sale data, being able to bring that back and have a 360 view of a prospect is really, really important.

So we’ve touched on this, the key takeaway here is, top performing SaaS companies are tracking this information. I mean, the most obvious ones, Salesforce, they happen to have a CRM as their product, but they equally are putting a ton of time and effort and resources into making sure that they’re capturing data to be able to analyze and stay differentiated in a competitive market.

I think the other piece is customer feedback, customer insights, when it’s going well, customer insights when it’s not going well, but having your clients commit to providing a level of information, especially if it’s around the renewal, if there’s friction in a renewal motion, a lot of that isn’t just down to budget, there could be other factors, there could be other key stakeholders that you’re not engaging with that are making budgetary decisions or influencing renewal decisions for a certain product, maybe they wanna get a competitor product in.

A lot of that just comes from having these conversations, but once those conversations are had, being able to tie that back to your CRM, collect the necessary data to be able to evolve, you go to market, really, really important.

And then the last one I touched on it before, but market events, news, industry- specific, regulation- specific, all of that matters, and being able to share that across your organization to understand that that’s gonna have an impact on targets, it’s gonna have an impact on retention and clients, being able to share that information across the enterprise really, really important, but it should live and breathe in a centralized function so that everyone can leverage it and action it.

It shouldn’t be ideally through emails or Teams messages, it should be within your CRM. And then from there, Mark and team can be able to take that information and obviously continue to feed Diane and make informed recommendations moving forwards.

Mark, anything to add on this one?

Yeah, I think the 360 data view is really important. And, you know, as mentioned, sometimes, you know, in sales, people win and aren’t necessarily aware why. And it’s kind of the question behind the question of, you know, not only closing the deal, but understanding, you know, what were the significant factors? And I’ve seen where it wasn’t until after the contract was signed. And then a few weeks later, there was a dinner and they explained, we actually had no interest in going with your competitor at all. We were never gonna buy from Accenture.

We hated those folks, but we just kept them in play. And so eventually you peel back later the layers and found out what were the true motivations of that prospect. And that informs you going forward of, okay, this is the real dynamic that’s going on with these customers. And we can leverage that strategically across our go- to- market motion.

That’s a great segue, Mark. I think one of the, you know, areas of discussion that we’ve had and we’ve discussed is obviously the distinctly different motions from inbound to outbound. And when you make that transition, obviously, Diane is a great tool to be able to tier targets. And to be able to focus your outbound motions. But I’d love to turn to you to talk about some of the great work and sort of what great looks like for a portco in terms of leveraging, you know, Diane for go- to- market, especially when it comes to outbound.

Sure. So one of the things that we help to, or I work to do is to help define the ICP. And many times, you know, a company has gotten to a level of success and has had a lot of inbound interest. And so coming from different industries, coming from different company sizes. And so there comes a moment where, who are we and who do we sell to? And so some of that comes from intuition. Salespeople have a lot of intuition, a lot of experience and understanding from, you know, hundreds of conversations. But in addition, it’s data- driven, right?

So by pulling the existing customer base and analyzing over hundreds and hundreds of customers, what are the signals? And some of those signals are simple firmographics in terms of number of employees, geography and industry. You know, where do you win, right? And comparing that to, you know, the wins versus the losses. But a lot of that is more subtle, right? In terms of picking up information from the description, picking up information from the company’s website, or perhaps earning calls.

So there was a interesting example where I mined the data from Cypher Learning and found out one of the most important signals was, if it was a, you know, higher ed, if they mentioned that they were forward thinking in technology. And so there were signals from their LinkedIn page where they had initiatives to be more technology- focused and they obviously had some initiatives and that was an important signal for identifying their customers.

And so that was interesting that, that was more important than other factors like geography, in general, you know, as long as they were in North America. And now we’re seeing a lot more of that in the industry. So there are companies that mine earnings calls and try to figure out, are there strategic initiatives mentioned in these earning calls that align with their product? And all of you have access to ChatGPT, Perplexity, all these tools.

I mean, if I was, you know, in sales today and I was targeting an account, I would say, I would just go into ChatGPT and say, hey, I’m in sales, I’m looking at this company, you know, do they have any strategic initiatives mentioned in their earning calls that align with, you know, the LinkLive product and that are, you know, significantly, you know, important to their roadmap going forward.

And it’ll come back with, you know, in half an hour, having scraped all that information and either with a yes or no, this, you know, given their initiatives, they are, you know, heading in that direction. And here is why. And then in those outbound emails or phone calls, you can say, you know, I’m calling you because you have an initiative this year to do upscaling or to do automation. And that’s exactly what we do.

Right, and so there’s complete alignment from from the first conversation. Um and and so a lot of the young people today don’t use search, they use chat to bt to do their homework. I know my kids do um and i know their teachers do um, and so it’s becoming more and more pervasive. But um and so that’s why i mentioned this change in the past six months. It’s not just this generic email, it’s very strategic, very data- driven and informed um, and whether you have the information or not, well, number one, i think everyone’s got data right.

Everyone’s got data on who they sold to in the past. Number one, uh, and i think everyone’s got access to these tools today. You know, even the enterprise chat gpt license is 50 bucks a month, so it’s not a heavy lift. And these things crawl the web, can go out and find all these signals for you, and if you’re not doing it, your competition’s doing it and they’re gonna find talking points and even if that um prospect is in a buying cycle, they’re gonna find reasons why their product is better than you.

And give you, give three solid bullet points from chat gpt that’ll cause the customer to ponder and whether they should actually sell to you. So, um, all these, all these things are. You know, there’s certainly gong and a lot of other tools out there, but, um, all this is being done at scale and through automation. Um, and you all have, all of you have- a tremendous amount of data that is can be leveraged in this process, that these tools can learn from and can be accelerated going forward.

So you’re in ideal, you know, position to benefit from all these changes. Um, it’s just a matter of you know, kind of it’s, it’s cultural change, uh, and it’s it’s a different mindset going forward, and um, and i get it, i struggle with that too, and um, and so, you know, the dan process has evolved greatly in the past year.

Um, and so, starting to uh experiment, using kind of this automation and signal generation from the internet to try to, you know, try to distinguish the signal from the noise, you know, find that needle in the haystack of what is a perfect fit for um, you know, for our technology and the right target right now.

Mark, could you speak um on some of the statistics that you have in terms of, uh, you know portcos of, of successfully been able to convert your tier one recommendations, and what does that look like? I think one of the the daily struggles that i have- and and i say it with a smile is- is getting sales reps who are being poured in a lot of different directions.

They want to sell, they want to make money, they want to close deals, but getting them to care, um about uh, prioritizing, you know, the right targets and taking, you know, asking the extra question and doing a a post- sale interview to extract the information. You gave the dinner example um, you know, earlier. I think a lot of that takes time and commitment and intention and i think getting people to care is obviously a big in a leadership role. That’s a big part of my job today.

But could you speak about some of the success uh stories and the statistics that you’ve seen?

Yeah, so you know what we’ve seen. You know, after implementing diane a um, you know, and then going forward six to nine months, we’ve seen a 94 increase in direct sales conversion for high scoring leads and so it’s a simple conversation, you know, with the bdrs: do you want to double your income? Do you want, do you want the? You know your conversations to result in nearly twice the conversion um.

In addition, even from you know the initial outbound um, we’ve seen a three times increase in the email response rate by the high scoring dan companies versus the ones that are low scoring um, and so, um, you know it’s, it’s a better use of everyone’s time, better use of your, of your time, better use of of the prospects time, and it’s it’s can, you know, significantly make impact on on on the business, um, and it’s not- i also need to emphasize, it’s not one and done.

As you know, we continually learn and collect more data, um, but you know it’s efficient use of resources. All of you have very small go- to- market teams and have to figure out how to be capital efficient with those teams and have have the biggest impact, and the data we have shows that, um, you know this, being a data- driven process, has a, you know, kind of a significant impact going forward, or, and it hasn’t has also in the past, and so that’s been my experience.

Yeah, and I think that the natural sort of, again, you mentioned sort of the small or limited commercial resourcing, you know, depending on where a company is in their evolution. And so obviously the need here is to be optimal, to optimize not just the targets that you’re chasing and make sure that they’re the top tier targets so that obviously you increase win rates. That’s really important. But there’s also, I think, an advantage of being nimble and maybe, you know, a smaller team in a sense that you can connect more effectively.

And one of the things that I’ve really instilled in sales teams, large and small, that I’ve led is it’s just as important for us to meet and talk about pipeline and forecast. And that’s a pretty standard motion, regardless of whatever firm you’re at. But actually taking the time to recap, you know, a week or a month and actually dig into the data and align on what data matters and what we’re trying to, you know, clean from these engagements, prospect engagement, renewal conversations, product support related conversations.

All of that, what I’ve found is, as you evolve the categorizations that you track, it actually leads to way better client experience in terms of the buying experience. Because if you’re thoughtful about, you know, what matters to them in terms of where they need to be in their journey to make a purchase, you naturally are going to prepare for those meetings in a more effective way.

You’re going to engage in those conversations more question- led than, and this is ironic as I’m talking at all of you, but, you know, the best engagements are the ones where you’re leading with great questions. And again, committing to, you know, categorizing your data in a way that allows you to scale, but also ensures that you’re asking the right questions at the right time. Really, really, really important.

And so I’m doing a lot more work right now on upskilling my team in terms of how to run an effective meeting, just as much as I’m, you know, asking them to join product training. And a lot of this ties back, Mark, to the information that you’re going to from Diane, but also the information that we can take from a CRM and continue to feed down so that it’s, you know, more effectively making these recommendations.

Yeah. And I’m not going to candy coat it. Outbound is hard. And when you get inbound, a customer already has a pain point. They already know that they need a solution. Whereas when you’re doing outbound, you’re trying to discover that pain point. And so the first conversations are not about, hey, here’s our product. It’s, you know, what can we solve? And what are the issues that you’re facing in your organization?

Right.

So it’s a different conversation. They’re a different animal. And so as a previous slide show, it is a big transition. Yeah. Yeah.

And I think just understanding, again, if you’re categorizing data in a way, um, you know, that that allows you to then see trends across a respective pool of prospects or pool of clients or within a certain sector, you’re naturally going to be able to lead with more, um, relatable questions. And it doesn’t matter what industry, um, your customers are going to want to know what their competitors are doing. Your customers are going to want to, um, have an advisor type, you know, trusted advisor type relationship with you.

They’re the best, um, experiences for clients. And it’s not just about being really knowledgeable on, on your products, features and functionality. It’s actually being able to be, um, you know, uh, smart and relatable in terms of the, the, the sectors that they operate in, the problems that they’re facing, the problems that their peers are facing. Um, and all of that marries back to the level of profiling. Um, obviously that Mark and I, um, you know, are committed to and are encouraging everyone else to be committed to.

Um, I just want to summarize a couple of points here, Mark. So you’ve took, you’ve talked about ICP and that’s, that’s ever evolving. Um, I know that your engagements with port goes, that’s going to constantly be a topic of conversation. Um, what have you seen in the last six months in terms of how you’re evolving your view of ICP and sort of.

Has any of that data changed in terms of, you know, the inputs into Dianne, are you acquiring new data sets? How has that evolved for you?

Yeah, so one of the big insights to me was that for some companies, the employee count doesn’t matter at all. Initially we were looking for, hey, we want to look at large enterprises, 5, 000 or greater employees. And then we found out that they had existing customers that had 150 employees. And so once again, it comes back to distinguishing signal from the noise. In the case of, you know, channel scalers looking at large partner programs.

And so found out that if they have a, you know, MDF, marketing to development funds, mentioned on their website, you only do that if you have 50 or more partners, right? And so it’s not public information, how many partners they have. If they have five partners, then it’s not a fit for the product. But if they have 50 partners or more, then it is a fit. So once again, it goes back to having these more nuanced or subtle signals where they’re mentioning certain things in their website.

And from that, we can often infer, hey, this is a fit given what’s described here. And now you can actually run, you know, these tools and analyze their website, but also analyze other websites to find out what’s going on. In the case of Binary Defense, I went to Palo Alto Networks and had ChatGPT crawl their website and I found their customer icons and determined who got in a generated list of all the customers of Palo Alto Networks automatically.

Right, and Palo Alto Networks doesn’t publish, hey, here’s an Excel spreadsheet of our customers, but it was able to analyze the actual icon images and to identify them. So there’s a lot of more kind of deeper analysis that can be done to figure out, and you have to be creative, right, and try to figure out what are these different signals. And another way is just talking to the team. When you look at a prospect, what is it you’re looking for? What are the types of things that identify?

And when it gets back to the question behind the question, okay, employee hidden account and geography, what else? Oh, well, I saw MDF mentioned on their website. Aha, okay. And so a lot of those signals become really important. So it gets back to, you know, marrying kind of the human knowledge and that tribal knowledge from the team along with these modern tools and be able to use them together. And that’s something the competition doesn’t have, right?

Today, I was at Google headquarters last night, and it’s just create an AI agent, throw it at the wall, and it’s gonna magically solve their problem. And think of an AI agent as a really bad intern. It’ll do exactly what you tell it to do and no more. So if you tell it to write a piece of code, it writes exactly what you told it to do, but it doesn’t think about, hey, it’s gonna fail in production. It only did what you said.

And so we really need this interplay between the human experts, who you all are, and these AI agents to really enable them, okay, I think about in this way, I think about in this way, and now you need to start embedding that knowledge in these prompts so that they can actually, and then there’s this kind of cycle going back of improving what you have, and that builds up kind of this kind of knowledge base. And that’s really what people are gonna start using going forward is how do people think and how can we automate that at scale?

Yeah, I think it really lends itself to having really productive internal conversations around whatever your ultimate goal is. It could be from taking your firm to 10 million revenue to 20, and you’re gonna do that through shifting from inbound to outbound. It could be in establishing position in a new sector.

And so you’re trying to make a market or disrupt a market, but all of that should be a continued evolving cycle, where you’re gonna figure out what works, but you’re also gonna commit internally to aligning around what matters most when it comes to data.

And I think just the simple act of committing at a minimum a monthly call with all of the internal stakeholders where you reiterate what’s our ultimate goal, typically that will be revenue, but it could be something else, launching a new product, getting product adoption, whatever that ultimate goal is, and then tying it back to the data that actually matters most to achieve that goal. And I think you’ll find very quickly that it goes beyond just the sales engagements.

There’s marketing, there’s customer success, having really good conversations around solving a problem for a client. Maybe it was a problem that we couldn’t even solve.

but there’s still a lot of learnings that are gleaned from those types of engagements and then being disciplined to be able to tie it back, centralize it within your CRM. And then from your CRM, it’s going to continue to feed Diane and get these really valuable outputs.

Yeah, and on that note of the ultimate goal, sometimes we all get on a call to discuss the ICP and halfway through, I realized everyone’s got different goals. And what does ideal mean? One person thinks it means the highest win rate. Another person thinks it’s the shortest sales cycle. Another person thinks it’s the largest deal size or maybe the highest LTV. And so we all come to that meeting saying, hey, let’s define our best ICP, but everyone’s got different goals. So alignment on that ultimate goal, what is it that the team wants to achieve?

And then once you have that, then the conversation can move forward.

Yeah, and that’s, I think having an open and honest conversation about the differences internally around what that ultimate goal is, I think is really healthy. And I think data, going back to data, data should be able to unequivocally support wherever you land in those conversations, right? And you may come in with a different perspective, but if you can get to that alignment on ultimate goals, then obviously the next question should be, well, how quickly can we achieve that goal? And data is a differentiator. Diane is certainly a differentiator.

I’m very jealous that I didn’t get to leverage a tool like that and obviously Mark’s expertise, but it was very clear to me, even though we’re coming from different lenses, obviously I work for S& P, we’re a large public company, but a lot of the problems are very similar in terms of scaling commercial teams, successfully executing on a go- to- market, being able to achieve your ultimate goal. Technology is the equalizer now. These tools are being used at scale.

And so really now the differentiator in my mind is how disciplined you are at tracking data, managing your data and executing on the outputs, which obviously all of that is data. I’m conscious of time. Heather, I don’t know if we wanna open up for questions or knowing that this is obviously being recorded and will be cascaded down. We’ve covered the call to actions. I think hopefully there’ll be some follow- on conversations either with Mark or myself.

I’m happy to go through and open up the data that I’m tracking that I think is important, but again, it should be very unique to each business, to each market that you’re operating in. But it does take buy- in. One thing is clear, it takes buy- in from across the entire world. This isn’t just a sales ask. Everyone needs to be aligned.

Yeah, thanks for that, Jack. We can definitely open it up to questions at this point in time. Feel free to jump in and ask Jack and Mark. Eric, feel free to unmute and ask or I can read your question.

Yeah, I’m just curious. Thank you for taking the time. You talked a lot about the transition of Inbound and Outbound, mentioned Gong a few times and yeah, KickSafe because that business a few years ago wasn’t great, but now with all this data now, it’s awesome. What are other things you’ve seen that you think are super relevant from the Outbound perspective in terms of third- party apps? You mentioned you use Sales Loft, but what are other ones?

Yeah, ZoomInfo is a good one for company- level information. For Capital IQ, it’s a proprietary tool within S& P, but there are other tools out there. I think any application that gives you company- level information pertaining to things like M& A or executive- level changes, you can get that from AlphaSense, you can get that from CapIQ, you can get that from Bloomberg or FactSet. These are quite expensive tools, but yeah, company- level information I think is the biggest one.

I think historically when I was building and scaling teams, it was all centered around the contact, who to reach out to. And so ZoomInfo is a great tool for that. But more increasingly, it’s getting that demographic information and tying that back in. And then Mark talked about this a lot, but shifting messaging out around problems that you solve or sector- specific trends or issues, there’s a lot of that just has to be leveraged through research that you do in AI on these applications.

And so we’re using all of the ones that I’m sure you’re using, ChatGBT.

you know, and the like. So, yeah, that would be my recommendation. Zoom info, if you don’t have it, is great. There are other tools like that. So that’s for people- level information. And then, you know, establishing a platform that can get you access to, you know, any of this. Alphacent’s not unplugging a competitor now. This is strange to do. But, you know, they have access to transcript information. It’s actually our transcripts, by the way. But that’s coming from conferences, where executives are speaking at conferences.

That could be expert network calls. All of that is textual analytics. But then how you tie that back into your outbound go- to- market motion, I think is really, really important. And I’m seeing a lot of individuals that I’m hiring, they’re not adopting that coming in. And so that’s the first thing that we do. We expose them to textual analytics and company- level information. It’s a good question, Eric.

We’re seeing more tools like Sabre that I put in the chat that kind of does real- time signals for your go- to- market teams, where it’s continually kind of scraping the web, looking for signals that would be important. Like somebody mentioned something at a conference or their LinkedIn profile. They post something that kind of aligns with what you’re doing and can help craft an email for you. And there’s dozens of these out there now.

Yeah. Another one that I don’t think gets leveraged enough, but you can get tools that scrape LinkedIn. So any user of your products, whether they’re the decision maker or not, you obviously want to track that. And when they move companies, obviously you want to be timing that correctly. And ideally you’re the first one to give them a call. Simple as congrats on the new role. Tell me about it. What kind of tools are you going to be leveraging in the role?

And that seems pretty basic and rudimentary, but I still see a lot of sales folks being really reactive and not prioritizing alerts around people movement. It’s natural in the inclination. You start a new job, you want it to go well. You’re going to make sure you get the tools to do the job well. And so timing that, I think is really, really important. I think we can wrap here. I’m going to share the deck. A couple of the, we’ve already gone through sort of the key takeaways here.

Again, I think this is not a one size fits all assumption, but I think one of the shared sort of takeaways for Mark and I, when we’re having this conversation is data discipline matters. Gone are the days where I’m standing over the shoulder of a sales rep, just demanding or requiring that they put core notes into CRM. It needs to be more synced up across your organization.

And some of the best decisions that we’ve been making commercially and from a product standpoint are as a result of getting people aligned around common data, a common language around data and making sure that we’re all trying to collect and aggregate and manage to the same data standards that then we can obviously make product commercial marketing decisions off of. So I appreciate your time. My intention was not to go the full hour.

I welcome any follow- up conversations. This is a new journey for you, going from inbound to outbound. You can teach me a lot about inbound. I’m really impressed with the scaling of each company that I’ve had exposure to in terms of being able to scale with inbound. We’ve made some acquisitions of really successful inbound- led companies, but the outbound motion is increasingly becoming more complex and more competitive. So I’m here, I’m a resource, and I know Mark is too. And if there’s any takeaway, it’s use, leverage Diane, leverage Mark.

You have a really good thing going there and a tool that I think will be a difference maker for you guys in the next wave of growth. Thank you so much.

Thank you.