Go-to-Market Trouble Shooting - "Growth's" Methodology

Live from Schenectady, New York, it's SAS Talk with the Metrics Brothers, Growth and CAC.

And I'm Growth, better known as Ray Reich, the founder and CEO of Benchmarkit.

And I'm CAC, better known as Dave Kellogg, independent consultant, EIR at Balderton Capital, and the author of CalBlog.

And together we are the Metrix Brothers.

And we go together like Chris Farley and David Spade in Tommy Boy.

Ah, one of my favorite movies, a cult film favorite that highlights that there's multiple approaches to hitting revenue goals and no one is the right way.

Well, I thought you'd appreciate the opportunity to analyze what made Chris Farley, otherwise known as Tommy Callahan, uh, made it work in the movie.

Well, speaking of analyzing, moving back to SaaS, I just finished analyzing the data from our 2024 benchmarking research. We did the last episode on that.

Just 10 minutes ago, right? That was only 10 minutes ago. I know it feels like a lifetime.

It appears based upon some of the unit economics and lower growth that we have a go-to-market problem. So I thought, why not do an episode about troubleshooting GTM problems led by CAC and growth.

Okay, so what we're going to do today, it's a great topic, Ray. We're going to hear about Ray's Troubleshooter, and I'm going to weigh in with color on it because Ray is the inventor of this methodology. I agree with most of it, so it'll be fun. It's a great topic. But before we dive in, Ray, let's hear a word from our presenting sponsor.

The Metrics Brothers is proudly sponsored by Benchmarkit, the B2B AI and software industry's largest, broadest, and most contextualized benchmarking index. Dave Kellogg and Ray Groth Wright have put the Metrics Brothers podcast on hiatus for remainder of 2026. All episodes we have ever recorded are still available on your favorite podcasting app. You can reach Dave at Kellogg and Ray on LinkedIn at Ray Reich. Thank you so much for listening to the Metrics Brothers podcast. Okay, take it away, Dave.

So in the last 2 episodes of SaaS Talk, we basically, as Ray has just talked about, discovered kind of the SaaS industry increasingly has a GTM problem, that CAC ratios are increasing, growth is decelerating, NRR is now, you know, flat is the new up, uh, in NRR. Jamin Ball posted about software weaknesses across the board. 6 out of 40 companies saw ARR shrink. Q2 guidance of 54% below Q1. Q2 Consensus. So, the industry has basically got some troubles right now, and a lot of those troubles come back to GTM. So, in this episode, we're gonna talk with Ray about how he troubleshoots GTM issues by the numbers, as we'd expect, using SaaS benchmarks. So, Ray, is that a good intro? What did I miss?

It's a great intro. And honestly, this is why I actually founded the predecessor company to Benchmarkit called RevOps Squared. Because I truly believed if you looked at all the data, the processes, the organizational integration across customer acquisition, retention, and expansion, you could be more efficient. But when I then got into trying to really identify where we have problems at each stage of that customer lifecycle, I really started with the acquisition. So I wanted to look at and analyze pipeline generation efficacy. Then I moved to pipeline conversion, looking at how we take those marketing qualified leads and get them all the way to a new customer. Then I wanted to specifically analyze in that qualified opportunity funnel, our win rates from that stage 2, which is a sales qualified opportunity, all the way to a closed one and the associated ACV. But then I took it 2 steps further. Dave, I wanted to look at customer retention and I wanted to look at those customers that we closed and spent $1.76 of sales and marketing to get $1 of ARR from them. I wanted to look at, do they stay 1, 2, 3, or 4 years? 'Cause to me that helps define the ICP. And then of course I wanted to look at that same cohort of customers and see how they performed as measured by expansion. So those were the 5 areas I like to analyze So let me comment and summarize.

So first, Ray's 5 areas are first pipeline generation, pipeline conversion, win rates and ACV, customer retention, and customer expansion. The first 2 really cover the kind of the capstone to me. And the way I talk about that particular issue is 2 things. One, are we giving ourselves the chance to hit the number? And are we hitting the number? Meaning specifically, if we don't generate enough pipeline, if we can't start every quarter with 3.0x coverage, which is the typical rule of thumb, thumb required coverage ratio, then we're not giving ourselves a chance to hit the number. And I know a lot of companies that are failing to hit their numbers, but they're starting with 2.0x pipeline coverage, and they're kind of trying to blame sales for bad salesmanship. And I say, hey, wait a minute, we're not even giving ourselves a chance. Very few people convert 50% of their pipeline, uh, in a quarter. So we need to have this separate of like, did we give sales a chance to deliver for us? And then is sales delivering? Those are the first 2. And then when Ray drills into it, he says, hey, part of delivery, very important, is how big are the deals and what percentage are we winning? Because a lot of times if you're just doing count-based stuff, hey, the win rate's holding solid, but oh gosh, the ACV came down. Why? Because customers are more price sensitive right now. We're seeing this all over the place with the companies I work with. So if you did a count-based logic, you missed your number because ASP came down 20%. Then customer retention. Basically, I always say, okay, we won them, what happens to them then? And then did we keep them and did they grow? So, so With that summary, Ray, why don't we jump in and have you do the first area, which is pipeline generation?

Okay. And here it is, a former kind of more sales than marketing talking about pipeline generation, but I think it's a team sport between marketing and sales. So, the first thing I look at is I look at marketing contribution by the 4 Horsemen, right? The 4 Horsemen being, you know, what is marketing contributing to the pipeline? What is sales development, business development, What is direct sales contributing? And then what is partners and channels? And then I want to look at how has that trended over the last 1, 2, 4, 6, and 8 quarters. And then I'll also look at benchmarks, Dave. And I'm like, well, if my self-directed AEs only generated 8% and that went down from 15% 2 years ago, maybe I should look at what we can do to have the direct sales function, the AEs, contribute a greater percent. Same with marketing, same with channels. So that's the first place I start is pipeline contribution by source, the trend lines, and how we can improve them. What say you?

Yes, 2 things, Ray. So one, not that I'm geopolitically correct, but you use the old Salesforce term horseman, which is both gendered language and increasingly out of fashion. I say pipeline source now across the 4 pipeline sources. The other reason horseman was a bad phrase is that the 4 horsemen were of what? Oops, the apocalypse. So it was never really a great metaphor to begin with. So yeah, first we look by the 4 pipeline sources, which to be clear are in my mind, because people define them slightly differently, marketing/inbound, SDR/outbound, sales/AEs, partners. Those are the 4 in my world. I'd love to know if you define them the same. And the very first thing to do is to look at the contribution by pipeline source. Kidding. By pipeline source. And then look at your historical contributions. Also ask if you're leveraging all the sources. Some people don't use partners. which is like, you know, not like, it's like not using one of your hands or something. Partners can be a great source of pipeline generation. So, any thoughts back to you, Ray, on that, or are you going to go to the next one?

No, I think we're very aligned on that. And once again, I'm a little old school sometimes. The other thing I would say though, in pipeline generation, all 5 of these that we're going to talk about, you do need to develop something I believe you called Numeracy culture. And that is everything in each one of these 5. We need to make sure that we have well-defined definitions of what everything is, including what is marketing/inbound, what is really going into that bucket versus SDR outbound. We need to set the goals and then we need to see how we're performing against those goals. And the best way to incent performance is to compensate against those goals. Not meaningless goals that— what do they call it? Vanity metrics. But these metrics that we say is important to the organization.

So we don't do vanity metrics here on the podcast, right? No vanity metrics on this, on SaaS Talk. Come on. Okay.

So let's go to pipeline conversion. 'Cause I think one of the things you once told me was marketing's job is to develop leads that result in wins, right?

Make sales easier is usually the way I say it, but okay. Part of that would be sending opties ideally that become winners for sure.

So the next thing I want to do in pipeline conversion is number one, I want to make sure that I have well-defined stages in that customer acquisition lifecycle. That's going to start— maybe we have leads. What is a lead? Then we have marketing qualified leads or marketing qualified accounts. What are those? How are they defined? How are they measured? How are they scored? And then how— what percent convert from leads to marketing qualified leads or marketing qualified accounts? Then sales qualified leads or sales qualified accounts, how are they historically converted from MQL to SQL? And then how do sales qualified leads, if you use that, some people will go right to a sales qualified opportunity, how do they convert? And really understand not only the conversion rates, but I also like to know the timeframes. Because if we have an MQL And it's been there for 90 days and most MQLs that end up in an SQO and close, it's done in 10 days, then I'm automatically maybe going to cleanse those out. So that's some of the things to analyze in pipeline conversion, Dave.

Yeah, look, stages are the foundation of all analysis. So just, I'd say definitions in general are, if we're going to do a stage-weighted pipeline expected value, then the stages need to mean something. If we're going to try and forecast using stages, they need to mean something, as do forecast category, opportunity close date, and value. We call those the 4 core fields. And you need to have clear definitions. Otherwise, you're just counting angels on pinheads. You're analyzing stuff that changes. If every time you hire a new VP of sales, they change the stage definitions, then we can't do historical analysis. So totally agree, Ray. The other point you raised with stages is the velocity through them. I always say that a lot of companies will say, my gosh, we're still generating the right number of opties. Our close rate is still good. What happened? And the answer— we talked about one earlier, ASP may have dropped, that'll break your model. And the other is velocity may have slowed. And by the way, both ASP dropping and velocity slowing are 2 things that happen in a downturn.

Yeah, you're exactly right. And that's why my 3rd one, which is win rates— and I define win rate as once we have a sales qualified opportunity, I think you and I both use kind of that stage 2 as a qualified opt-in. Right, to closed won. To me, number one, I want to see what that win rate is. I want to see how it's trended over time, and then I do want to compare it to benchmarks if they're available. Now, if the win rate's been 20 to 22% for the last 8 quarters and the benchmark says 21% is median, I'm not going to get too hung up in stage-by-stage analysis. But if I'm at 15% win rate and it's trending down, that's when it's going to be really important to look at stage-by-stage conversion rates in the opportunity funnel— not in the lead funnel, opportunity funnel. And it's going to be really important there that I have well-defined stages that everyone knows, that everyone follows. And that means there should be some gates or certain criteria that we don't go from stage 2 to stage 3 unless these criteria were met. Otherwise—

Yeah, I mean, look, part of the basic definition of stages is exit criteria. In my mind, the fewer the better. The fewer exit criteria, the better, and the more strictly enforced. I've literally had a joke once. I saw a customer that had like 8 exit criteria per stage. And I was like, I think I could win the deal before I can get out of stage 3. It might be easier. Can I just go win this? Because it's going to be easier than the stage 3 exit criteria. So, agree, you must have exit criteria. The other comment I wanted to add there, I think it was 3 episodes ago, Ray, we talked about is pipeline coverage the inversion of your win rate? And I think we discovered that, you know, Ray and I are metrics brothers, but from another mother, because Ray defines win rate, what I would call close rate. That's not what I call win rate. Hear that episode or see my blog if you want to get the difference. But Ray is basically saying for effectively what I would call a cohort of opportunities generated in a given timeframe, what percentage of them eventually close? And that's what he was talking to. And it's a great metric. to track. It's just, in my mind, different from win rate.

Yeah, but where we are aligned, and that is that the stage-by-stage conversion and the ultimate what percentage of qualified opportunities result in a new customer, is that velocity. Because I want to know not only the velocity end-to-end— so it's a 90-day sell cycle from qualified opportunity to close one— I also want to know stage by stage. Because what I have found, Dave, A lot of times, if something hangs out too long in one of the earlier stages, stage 2 or stage 3, the probability of that resulting in close won is much lower. So I want to analyze my opportunity funnel and look at velocity through each stage. And the other thing, I actually build my opportunity funnels to have higher drop-off rates earlier because what I don't want to do is move something from a stage 2 to a stage 4 thinking it's now on a weighted average Forecast and it's bullshit because I should have gotten rid of it at stage 2 or stage 3.

Yeah, look, I agree with you on stage aging, as I might call it. What's the age of opportunities at a stage? How long have they been there? The only thing I disagree with what some people say, and you never said this to be fair, is I'm not sure it's causal. Like, I'm not sure, oh, we let it sit too long in stage 3, therefore we lost it. Or is it the other way around that we lost it and therefore it sat too long in stage 3, right? There's, there's some people make an assumption that just, just because all the ones we lose were more than 60 days in stage 3, that if we apply all this energy to get them out of stage 3 in 58 days, we're going to win them. And I'm not sure that's true. They may be stuck in stage 3 because they're not calling us back on purpose, or the reps stop working on it because they don't think it's good. So just be careful and ready to not do this, but some people do, about kind of inferring causality. All I want to do is observe. If it's been in stage 3 more than 60 days, only 1 in 100 of those get won, and therefore Let's go either get it out of the pipeline or put it in stage 4, or actually validate that it still belongs to stage 3.

Now, before I go to that 4th GTM troubleshooting category, the other thing here, and maybe this is 201 or 301, but when I do this analysis of all 3, pipeline generation, pipeline conversion, and win rates, I will want to do this on a segment-by-segment basis when it's appropriate. And that might even be, hey, my core ICP is mid-market. I want to understand what my conversion and win rates are in mid-market. But even if I have 10% of my deals in enterprise, I want to look at that separately, Dave, because one can bias the other. And I might say, hey, man, we really suck at this enterprise thing. Maybe we should double down on more mid-market focus.

Yeah, there's no question to me that if your business has multiple segments, just to pick an example, say you sell to both enterprise and mid-market. and say you use a field team in enterprise and a telephone team in mid-market, that you should say you have different average deal size, different sales cycle length, you should segment those metrics. Obviously, at the board slides, you're going to need to present the integrated picture, but you very quickly want to click through and go, here's the overall picture, and boom, now let's look at the segment analysis, because that's, that's where the reality of the business happens. Like I would say, Ray, nobody— some people have no kids, some people have 3 kids, Nobody has 1.5 kids. So, the mean is not meaningful.

Totally agreed. Okay. Last 2 in these last 5 minutes. So, customer retention. Now, the reason I chose customer retention as the 4th area of go-to-market troubleshooting isn't just because retention is important, but I actually like to look at what are the attributes and the shared attributes of the customers who are Retaining at the highest level. Now, I would hope that if I have one core ICP, let's say that's mid-market customers and the high-tech business, that not only do I have quicker win rates, better win rates, but I also have higher retention. But Dave, so many times a head of sales will say, well, I'm closing a lot of deals over here, and they forget to look at, oh yeah, but 30% of those deals are churning because I'm closing the wrong customers. So I really like to troubleshoot by starting with my retention by segment, starting with my core ICPs. And then I like to start looking at things like onboarding satisfaction, product activation engagement, CSAT scores, and even verified customer outcomes to see if there's any correlations to retention rate and some of those post-close activities.

Yeah, totally agree. I mean, ultimately, I've never done a blog on this, but I want to. If the ICP is about replicating our most successful customers, what's your definition of success? Is it renewed, renewed once, renewed 3 times, expanded, right? Has a high NPS? It's elusive. But look, ideally, the best ICP is around who are the people that we sell quickly, win a lot, and then they expand, right? That would be like kind of ring zero.

Yeah. And that's exactly why the 5th category that I always look at for go-to-market troubleshooting Is customer expansion performance? Same thing. I want to look at those customer cohorts or segments, define it how you want, that only have the highest retention but also seem to be growing the fastest. And the other thing I'm going to start looking at is what do each of my organizations, how are they impacting customer expansion? Simple example. If my customer success manager manages, you know, all the customers, how is she or he performing as far as expansion? Are they being motivated to create customer success qualified leads? Do they have any incentive to be able to help close upsells or cross-sells in existing customers? But I wanna start with understanding by customer cohort who's got my best expansion rates.

Absolutely. Absolutely.

Anything else on, on customer expansion that you would look at that I'm kind of missing?

I don't think so, Ray. I view the expansion as part of the ICP problem, basically, which is when you're troubleshooting GTM, you want to know if you're selling to the right people. And the first test is, are they all churning, right? Or are they— look, are they onboarding successfully, as you mentioned? Are they all blowing up in 3 months so I don't have to wait for the churn? I know they're failing. And then are they renewing? And then are they expanding? I think it's a systematic way to look at it. As long as they're not churning, it's probably a decent customer, right? Hey, If I buy you for $1.30 or $1.50 and you stick with me for 5, 10 years at a dollar, that's fine. I don't need you to expand to make money on you. I just need you to stick around as a customer longer than the CAC payback period. And now I'm basically making money to cover other costs off you. So on expansion, I think you could break it down by new products versus more seats. Those are the 2 fundamental types of expansion. And I would definitely be doing analysis. I mean, look, most companies today are trying to expand their product line to drive growth. So tracking the expansion of, okay, this type of customer tends to buy product 2, this type of customer only buys product 1, then obviously we would want to target, if we're trying to tune up a GTM org, basically people who we think are going to buy product 2 and then product 3, because over time, basically we're turning that into expansion CAC. Basically, that product 2 sale and that product 3 sale is expansion CAC, not new customer CAC, meaning it should cost us, at least in a better world than we live in today, 60 cents. In today's world, sounds like a dollar, but in a better world, 60 cents as opposed to maybe almost $2.

Totally agree. And then the last thing, at the end of another episode, Dave, they go so quick, but my bonus advice is when I'm looking at customer expansion, I'm also bringing the product team into that analysis and looking for near-adjacent product add-ons, because I believe in this macroeconomic environment, there's going to be acquisitions of near-adjacent product add-ons that you can get for pennies on invested VC dollars that might be a built-in expansion mechanism for you.

Yeah, so you triggered a story, Ray. I know we're getting up on time here, but, um, one of the oddest board meetings I ever attended is we had the VP of Product standing up in front of us and somebody asked them about NRR. And he basically said, there's nothing I can do about NRR. That had about a 45-minute heart attack from the board ensued on terms of additional products, product packaging, pricing. There's all kinds of things you can do to either drive big expansion opportunities, little expansion opportunities, or kind of what I call offset anticipated churn, where somebody goes, oh, I had 100 seats, but I only want to buy 80. If you've got another product in your pocket to preserve the ARR, You go, hey, we just had this new thing, and I'll keep your contract the same value, but you'll only have 80 seats, right? That's all stuff product people can do to try and help with the NRR problem.

Yeah, totally agree. Hey, this was a fun episode for me. I love GTM troubleshooting. It's, it's what I did for 30-plus years. So thank you for the dialogue here, Dave.

Thanks, Ray. Great episode.

See everyone later. Bye-bye now.

The Metrics Brothers AI, SaaS, and More is a production of The Metrics Brothers Growth and CAC. And a member of the Benchmarket Podcast Network. By accessing this podcast, you acknowledge that the Metrics Brothers make no warranty, guarantee, or representation as to the accuracy or sufficiency of the information provided or the humor content of the jokes told.

Ray.

Information, opinions, and recommendations presented are, according to our spouses, probably wrong and provided for information purposes only. This podcast should not be considered professional or, for that matter, unprofessional advice. We disclaim any and all liability for any direct, indirect, indirect, misdirect, incidental, special, ordinary, consequential, inconsequential, or other damages arising out of any use of, or God help you, reliance upon the information presented here. Ray Grothreich is based in New York City and available on X at Ray Reich. Dave Kellogg is based in Silicon Valley and available on X at Kelblog. Schenectady, which is French for unspellable, is not our actual production location. Thanks for listening.