Episode 127: Amy Kramer of Level Equity on Go-To-Market Benchmarks, Outbound Efficiency and AI Visibility

Episode Transcript   

 

Shiv Narayanan (00:10.672)

All right, Amy, welcome to the show. How's it going?

 

Amy Kramer (00:12.642)

Good, great to be here, Shiv.

 

Shiv Narayanan (00:14.222)

Yeah, excited to have you on. And obviously we've had some past guests from Level Equity as well, but why don't you start with your role in Level Equity and then let's go from there.

 

Amy Kramer (00:22.038)

Awesome. So I'm Amy Kramer. I head up the go-to-market group within Level's Value Creation Team, Next Level Operations. Level Equity, we're growth equity investors. We invest primarily in B2B SaaS, industry agnostic, typically invest in companies anywhere from 5 to 20 million in ARR and have about 50 portfolio companies under management that our team works across.

 

Shiv Narayanan (00:42.18)

Yeah, and one of the reasons why we wanted to have you on is obviously your role at Level Equity, but you guys have written this go-to-market insights report for 2026 that I think would be very relevant to other PE operators and managing partners and even portfolio companies. So why don't you set the stage on that a little bit for us?

 

Amy Kramer (00:59.34)

Yeah, so this has been a long-time labor of love. We started this five years ago when I first joined and I was really trying to get my bearings to understand—where can we best help our portfolio companies? What are some of the key trends and commonalities of common pain points? So it kind of started out of necessity to just get my better arms around the portfolio. And it's really evolved over the last five years to provide key insights, benchmarks and trends, as well as compensation insights across go-to-market. And so we really look at full funnel metrics to really help companies better understand benchmarks. How do they compare? What's working well, what's not?

 

Compensation—a lot of times companies are asking what's market for account executives, how to think about different compensation splits. And even looking at quota attainment is really helpful just to understand key trends. So a lot of things when we're working with companies will feel like we're seeing a lot of pain or grumbles in certain areas. But this benchmark report really helps us to validate that in the data—or prove or disprove that. And also helps us to better understand what tech stack folks are working with, what they like and what they don't. So that we're not just going off the anecdotal—some voices are louder than others—to really understand not only what are they using, what's making the biggest impact, how are different tools impacting certain metrics, and also what do they like and what they don't like.

 

Shiv Narayanan (02:23.354)

And so what were some of the biggest takeaways as you ran this study?

 

Amy Kramer (02:26.879)

Yeah. So this year, every year there's a couple of interesting insights that come out of it. This year, of course AI was a big theme. It's hard not to be. So I was really curious to see what folks are using and how they're using it and the impact it's causing. That's been one—I'd say the biggest area that was interesting. I'm always curious about outbound performance—as a former sales leader, that was always a pain point of mine, running a large SDR team and the constant drumbeat of trying to book outbound meetings. And so over the last years it's felt harder to book meetings. And it's interesting to see how the data validates that or not. This year we saw that with our teams using so many more AI tools and functionality in their existing tech stack, the average meetings per SDR are increasing year over year. But what was interesting is that the number of prospects they need to reach out to in order to book a meeting has gotten higher. So they have to reach out to more companies to book the same meeting. But because they're using all these different tools, they're able to reach out to more. And that didn't shock me. There's so much noise in the market. People are getting bombarded. It's kind of table stakes. But so what do you do about that? How do we advise our teams on how to book more meetings since outbound is a core lever for a lot of our companies.

 

Shiv Narayanan (03:55.608)

Yes, let's pause on that one. With outbound efficiency decreasing and needing more volume, does that concern you? Because at some point, you can also saturate your market, especially if you're in a high ACV type of market where there's a limited number of targets. How do you look at that?

 

Amy Kramer (04:17.579)

Definitely. It's definitely concerning to me. We don't want to be spraying and praying and just burning through our leads, especially some of our portfolio companies have a much more targeted ICP—like, I only have a thousand target accounts that I'm going after. I can't just keep reaching out. And so we're partnering with our teams to work much smarter in their outreach. There are a couple of things in the data that we saw that validate some of our assumptions, and then there are also a couple of things I'll share on what I think our most cutting-edge teams are doing to break through the noise.

 

So one, not surprisingly, is your teams need to be calling more. We saw companies that required 200-plus dials a week on average book three times more meetings. Their conversion rates being that much higher—we need to be thinking about how do I leverage AI to gamify, to get my teams out of email and on LinkedIn, automate that as much as possible so that they can spend as much time on the phone as possible. And then there's really cool calling intent data that we're seeing our teams starting to test—when to reach out, who's most likely to pick up the phone. To be more thoughtful about when they're reaching out versus just using power dialers doing more volume. And then it also comes down to the list of who you're reaching out to. I've always been a big fan of rev ops or marketing creating the outbound lists and not just having reps self-prospect. We're seeing that validated in the data. And now there's such better signal data—our companies that are reaching out to companies showing some sort of engagement or intent signals are seeing better results.

 

Shiv Narayanan (06:08.491)

Yeah, totally. And that's what we see as well. Intent data is super important to figure out who are the best prospects to reach out to. Actual behavior signals—figuring out who's coming to the website or interacting with something on social, feeding that into your outbound pipeline. The third thing we're always encouraging companies to invest more into is customized content. A lot of companies, even with intent data and signals, the approach isn't really customized—maybe one or two lines are changed, but then it's outreach at scale. The way to really drive up results is to have content that's customized, especially when you get into higher ACVs and limited target markets. And then the fourth thing we've seen is where customers are co-creating content with their prospects. This podcast is a great example—we work with private equity firms, we interview them, and that turns into business for us. Companies that have figured that out are using prospects in advisory councils, webinars, podcasts. On the backend, there's some sort of sales process, but by that time you have a much deeper connection with that prospect.

 

Amy Kramer (08:07.051)

I couldn't agree more on the content side. The companies seeing the best results are providing real tangible value to their prospects. Not just, I know who you are and I know your pain, let's have a meeting. They're reaching out with real proprietary data or insights or examples of the pain point. For example, one of our companies is around brand compliance. In the past, they might have thought about highlighting brand inconsistencies. Well, now by leveraging AI, you can scale that and build custom examples to show a prospect: here are examples of where your content is misaligned with your brand. Or proprietary data—I'm encouraging all of our leaders to really think about what's insightful data your company has that would be really helpful to share. One of our other companies created a self-audit around compliance in financial transactions—I think using Claude Code—where companies can take this self-audit, share their practices, and the company provides back key benchmark data and insights. And then how we're doing it ourselves—this go-to-market report—we took it to the next level this year. We're having our associates offer companies a customized go-to-market diagnostic report using these benchmarks, providing how they compare and helpful recommendations. Offering real tangible value and showcasing what it would be like to work with us.

 

Shiv Narayanan (10:32.611)

Yeah, I think the data point is a great one, especially with AI, because that's proprietary and it's defensible and you can add value to those prospects. Talk about the next one—you started with outbound, what were some of the other takeaways in the report?

 

Amy Kramer (10:49.471)

Yeah. So one of the most interesting things—we looked at the full funnel metrics across the board. They've improved. And while I was like, amazing—I think the truth is we've spent a lot of time working with our portfolio companies on getting much more targeted on their ideal customer profile, which in turn translates to better results. How do we make sure that if we're going to focus on outbound or even spend dollars to drive more inbound, it's with the companies most likely to convert? So that was another big trend.

 

Shiv Narayanan (11:26.019)

Yeah, that's an interesting one. In terms of using intent data to drive more nurturing for prospects that are interacting with the business and in the right stage.

 

Amy Kramer (11:36.157)

Yeah, definitely intent data, but also really challenging companies to think about—what are the things when your sales reps get on a call with a customer that make them get excited? Like, I heard they just bought this platform. What are the things that, if you could know anything about a potential prospect, would make them a good fit? Data enrichment has gotten better than ever. There's a lot of custom scraping you can do now. So doing those brainstorm exercises with our portfolio companies. One example is a company that sells software for equipment management. How can we figure out which companies would have this equipment? Instead of having it be a 50-50 chance—well, if you have this equipment, what else do you have? You have rack space, you have certain insurance. And so now we're starting to challenge ourselves to think about how we can get access to this data to more effectively target.

 

Shiv Narayanan (12:47.649)

Yeah, I completely agree. One of the things we tell companies is that everybody wants more top of funnel, but there are so many things that can be done in between all of those different funnel stages that companies are not optimized for. Something as simple as—a customer has certain follow-ups or questions or objections after a demo. Do we have assets to address all of those? In a lot of cases, we find gaps. Maybe companies don't have enough case studies. Maybe the reps don't have enough battle cards. That is such an underappreciated lever, especially now because it's harder to get customers to close.

 

Amy Kramer (14:02.797)

100%. One that might seem minor but that I've seen is really under-optimized is meeting show rates. We work so hard to get a lead to book a meeting. And then we see a big drop off between when they booked and prospects showing up. It used to be like, I'd say good with 80%. I'd say it's probably more like 75% across the portfolio now. But closing the gap—using your calendar invite as marketing real estate, sending them case studies ahead of time, really optimizing the invite to remind them of why they even wanted to take this meeting—optimizing that lever can significantly boost pipeline within your ICP. But also, when we do these go-to-market diagnostics, you have to look at all the funnel metrics together. For example, sometimes we'll see meeting win rates are really high and I'm like, sounds amazing—except that if your disco-to-demo rate is really low, are we over-qualifying? You really have to look at all the funnel metrics together to better diagnose what needs to be done.

 

Shiv Narayanan (15:31.087)

Totally. And if your close rates are too high, it could be that you could afford to increase your prices. So I'm curious—in terms of channels, how are you seeing companies deploy their budget now? Has that changed?

 

Amy Kramer (15:55.277)

All right, you've kind of teed up my third insight pretty well. We have seen a shift this past year in companies spending more on top of funnel and brand awareness. So five years ago when I first joined, I was like, brand awareness—let's not spend it all there. It's all about demand gen for this stage of growth businesses. But now for a couple of reasons, we're seeing that shift. One, with so many competitors and so much noise in the market, brand trust and brand affinity are really important. Two, getting found in LLMs—there's a lot more that's going to matter in terms of thought leadership content, PR, media mentions. These become a lot more important in order to get found. And then also, because folks are getting tighter on their ICP, you can't just focus on the bottom of the funnel. You have to meet buyers throughout the buyer's journey starting as early as possible so that when they are ready to buy, they've got that trust and they know who you are.

 

Shiv Narayanan (16:59.887)

Yeah, that's one of the things I completely agree with. Building the brand and standing out in a commoditized marketplace is more important than ever. Even on LinkedIn, you see a sea of commoditized content. Companies investing into the brand in a thought leadership capacity, or building their position as the ideal fit for a particular customer type or vertical, see better metrics across the board—better paid media performance, better inbound traffic, lower cost of acquisition, better payback periods. And I think now brand is the ultimate differentiator. The best companies we encounter—their best pipeline sources are often direct traffic or branded keywords. Even when prospects do click on SEO links, they're clicking competitors' links too. So they need a reason to choose you over the other.

 

Amy Kramer (18:45.633)

Yeah, it was interesting at our recent annual meeting with our investors—we had one of our CEOs speak and he brought up a great point. The biggest threat is not these AI pop-up competitors, because building a go-to-market motion and a business is really hard. It's not just about building a product. But your biggest threat is a competitor or adjacent who, instead of buying a company, can now potentially build that product pretty easily. And so I think—again, because they've got the brand and customer awareness—it is something we're thinking about working with our portfolio companies around. What are the other products you could be building to continue to sell into your customer base since you've got that strong brand and it's easier to build products now?

 

Shiv Narayanan (19:27.374)

How are you seeing marketing budgets change in light of this? Are companies starting to spend more or less?

 

Amy Kramer (19:36.373)

It's kind of a mix. There's a lot of experimentation with different AI tools currently. And not all of it is going to stick. We're not seeing a reduction in headcount. If anything, our marketing teams are having to work overtime right now. More content is needed, more training, especially on product marketing. So even though they're leveraging a lot more tools to make content creation easier and faster, it's not necessarily reducing spend. Spend is not increasing as significantly as you would expect in line with growth, because you can be much more effective today. 

 

Shiv Narayanan (20:31.297)

Yeah, we're seeing companies potentially reducing headcount, but then also trying to figure out how to ramp up pipeline. It's a bit of a tricky balance. How are you looking at program spend? What we're seeing is that Google Ads or paid social have become less efficient because there's just so much more competition.

 

Amy Kramer (21:15.221)

Yeah, traditional channels are not necessarily delivering the same results. So a lot of testing right now. We've also seen still a lot of in-person events and in-person experiences—what's old is new again in sales. A lot more relationship building, not just showing up at events, but folks hosting small dinners or doing road shows to get more customers and prospects together in the same room. Direct mail is another one we've seen folks test and have some early signs of success with. But really just testing different channels to break out from the noise and get in front of prospects.

 

Shiv Narayanan (22:08.471)

Yeah, and we've seen a rise with channels that previously felt harder to scale—customer communities, things where there are relationships to invest in. And then on the online side, one of the things we're seeing is a decline in inbound volumes because people are searching for the same queries on platforms like ChatGPT or Gemini or Claude. And when they get those queries answered, they come in the form of direct traffic—and then we see higher close rates because they've come pre-educated. So what are you seeing in terms of sales cycles and win rates?

 

Amy Kramer (23:06.381)

So anecdotally, I'm hearing more recently that prospects are coming in earlier in the sales cycle, which was interesting and a little counterintuitive. I think it goes back to—we've gotten a little bit better at our targeting, and because we're going higher up the funnel and investing more on top of funnel and brand awareness, we're reaching out to folks more proactively earlier on. But I think that's shifting how you think about discovery. Not just qualifying—do you have budget now? In some of these cases, we need to educate on why they need to make this decision earlier and why this pain is costing them money the longer they wait. And also partnering with marketing to make sure we're continuing to nurture these leads. Just because they're not ready to buy doesn't mean we can't demonstrate our value and educate them along the way.

 

Shiv Narayanan (24:17.903)

Is that in terms of outbound or inbound demos? I guess outbound, you're trying to catch them with intent signals and maybe they're not in a buying window, but inbound they're coming in more ready to buy.

 

Amy Kramer (24:32.789)

It depends if you're considering inbound purely hand raisers—someone ready to talk to a sales rep. But a lot of folks consider what qualifies as an MQL to be a lead that's engaged, maybe visited the website several times or has been spiking in intent. So those warmer leads is what I'm referring to—they're probably earlier in the buying cycle.

 

Shiv Narayanan (24:52.015)

Yeah, I can totally see that. Part of it is—with the way sales cycles are going, you might need to invest more time upfront because people are moving through the early stages of the funnel slower. And then when they're ready to buy, they might move faster.

 

Amy Kramer (25:08.821)

We are seeing that. I don't have the data yet for this year to show that. But anecdotally, I'm hearing from folks that once prospects enter a buying process, it's either faster or the same. It's definitely not longer—because the last two years, long sales cycles have been a real challenge.

 

Shiv Narayanan (25:27.055)

Right. And so with that, it's even more important in the earlier stages to be educating and building relationships and staying top of mind. Part of that is through sales, part of that is with in-person connection, and part of that could be through inbound traditional channels and then also AI platforms where they're self-serving their way to learn.

 

Amy Kramer (25:48.435)

Yeah, exactly. And I think that's where it's really important for our teams to be able to track where a prospect is in that lifecycle, either through lead stages or opportunity stages, so that marketing can nurture appropriately and sales knows what to do.

 

Shiv Narayanan (26:04.079)

Talk about the AI side—how much are you guys tracking visibility on LLM answers or queries that relate to what a company might be selling? Is that a thing that companies are prioritizing at the moment?

 

Amy Kramer (26:20.727)

So right now we're tracking and looking at the traffic coming from LLMs, and comparing that alongside their overall traffic and their organic traffic to say—do we need to be investing more here? If they're not spending time there and our LLM traffic percentage is small and overall website traffic is trending down—that's definitely an area we want to invest. I also think we're trying to look at it for each company in the market that they're in. There's optimizing for organic, there's optimizing for LLM, and some overlap. And I think it depends on the market and where your buyers are and how sophisticated they are. Do you want to be an early adopter? If no one else is winning here, maybe you want to really double down. Or maybe this is really competitive and not an area to focus as much. So you've got to look at each unique dynamic of the business and the market.

 

Shiv Narayanan (27:36.513)

Yeah, on that front, one of the things we've been encouraging companies to do is think about the full set of queries a prospect might have—from fully unaware to problem aware to solution aware to actually making a decision. What percentage of those are they making on AI platforms, and what percentage of time are you coming up as an answer? Because the way AI platforms are indexing answers is based on who has the best possible answer or the highest level of expertise. We're finding that a lot of B2B companies don't come up enough because it's something they just haven't prioritized to track. And this isn't about first-page Google rankings—AI is indexing answers in a very different way. Companies showing up 70 or 80% of the time in AI answers versus 20 or 30%—that makes such a huge difference in pipeline generated in that market.

 

Amy Kramer (29:13.237)

Yeah, I think that's very similar to what we're seeing and some of the things that we're working on. But I'd say we're still pretty early here. A lot of our companies have this as a core focus—how do we get more traffic from LLMs? Because they're seeing traffic coming down across the website, but better converting when it gets there. And so doing audits, working with outside consultants—we're excited to have you lead a webinar for our team on optimizing for AI visibility—is definitely a core focus for us right now. But we're really trying to think about it as each individual company and market, of what they need and what's important.

 

Shiv Narayanan (29:50.659)

What about on the org side? Are you seeing teams reshuffle roles or structure themselves differently now, especially with AI emerging?

 

Amy Kramer (30:05.093)

I'd say most prominently on the marketing side, and for rev ops—probably a bigger investment there. We have seen some of our companies have dedicated AI experts within the team working cross-functionally or specific to go-to-market. But in general, just investing more in rev ops support, because some of our companies are still needing to work on the foundational infrastructure to get really good data to be able to better leverage AI. And a lot of that takes a heavy lift from rev ops. So folks that maybe would have invested later in rev ops—that's an area where we've probably seen some of the biggest shift. Because the thing that's most interesting that I think AI is causing is—it's creating a different pace, a go-to-market rhythm. Releases are happening that much faster. Our customers' needs are changing that much faster. And so that feedback loop and that connection and that new rhythm is the thing that we're really focused on with our teams.

 

Shiv Narayanan (31:27.692)

Yeah. How are you helping your teams keep up with that? From a development standpoint, from an education standpoint, also from a hiring standpoint?

 

Amy Kramer (31:44.621)

So from marketing leadership and talent, I think you're always looking for someone who's willing to test and who's metrics driven. And I still want somebody who is heavily focused on demand gen because that's still going to be a core need for the business. And having product marketing—some companies invest too late in product marketing. Especially right now as products are evolving so quickly, that hire becomes that much more critical. Content creation hiring—we're seeing that scaled back, and folks being more thoughtful about where they can leverage external consultants to stand up some of these new channels they're testing. But this culture of testing—I'm looking for that in the DNA of a marketing leader. Someone who's really collaborative. The holy grail is always someone who's got both demand gen and product marketing chops, but we're still seeing most prominently demand gen leaders.

 

Shiv Narayanan (32:39.916)

Yeah, we see that 200%—somebody that understands the data side, can run campaigns, can also think through how to leverage content. But sometimes you do need two different skill sets.

 

Amy Kramer (32:50.541)

The other thing I think is an opportunity is—because of this rhythm of connecting the customer to product and marketing, not just keeping it at sales and CS—really being thoughtful about how you're leveraging your call intelligence data and creating these ongoing feedback loops and trackers and listening for changes in pain and need. Because I think the biggest thing is—you can be losing product-market fit right now. You need to constantly be testing and evaluating. A pain point they had in the past—are they solving it in a different way? Are they able to build something internally? And new pain points are arising as a result of the uptick in AI usage. So hearing that from customers now is so critical. We had one of our portfolio companies recently who just redid their ICP to be really smart about how they leverage their call intelligence data to get hyper-focused on the value they're providing each of those different ICP segments—right out of the customer's mouth.

 

Shiv Narayanan (33:50.957)

Yeah, that's fantastic. And how is that connecting to the retention side? How are you seeing a change in how companies are prioritizing retention campaigns, expansion, growing lifetime value and even cross-selling or upselling?

 

Amy Kramer (34:09.633)

Yeah, so expansion is an awesome use case of how we're seeing folks better leverage signal data. Both always using product adoption and usage, but now also understanding what are some of the other pain points or intent they might have outside of their existing usage within the product itself. To be really smart about focusing account managers or sales reps—whoever is dedicated there—on the right accounts for expansion. And we've tested different tools related to that that are automating triggers based off of signals that have been effective. I do think we're also pushing our teams to drive more product adoption and engagement within the product itself and automate that more. And I think it's a great use case for AI. In an ideal world, we'd only be focused on expansion and eventually we won't need customer success managers to help customers get value out of the product—more of that should be built into the product and self-usage. Think people are also—customers themselves are going to be much more used to self-help and self-usage the more they become native to AI. And so we need to build those functionalities into the product so that they can help themselves.

 

Shiv Narayanan (35:17.036)

Yeah, that's fantastic. I know we're coming up on time here, Amy, but for the listeners, if they want to learn more about this report and look at all the data inside, what's the best way to get a hold of it and also get in touch with you?

 

Amy Kramer (35:28.447)

Yeah, so you can go to levelequity.com/report/go-to-market-insights-2026. It's also available on our LinkedIn page. So you can see all that, get the full report and download that. And then if you're interested in doing a benchmark report for your company to see how you compare to these benchmarks for companies that are a similar cohort to you, go ahead and reach out to me at [email protected].

 

Shiv Narayanan (35:55.534)

Awesome. We'll be sure to include that and all the links in the show notes. With that said, Amy, thanks for coming on and sharing all these great benchmarks and data points, because I think a lot of PE investors often are wondering what's the right benchmark for their companies. I appreciate you doing this.

 

Amy Kramer (36:10.687)

Awesome. Thanks so much, Shiv. Great chat.