Philipp Stelzer: Hello, and welcome to another edition of the RevOps Lab Podcast. Our guest today is Jeff Ignacio. Jeff, very warm welcome.

Jeff Ignacio: Thank you. Thanks, Janis. Hey. Thanks, Philipp. Appreciate you having me on, glad to be here.

Philipp Stelzer: Yeah. And you already heard it. Janis is on the recording as well. For the last couple of episodes, been focusing on the revenue lab podcast, more focused on sales leadership. Give that a listen if you haven't yet, but very happy to have him on for this episode.

Janis Zech: Yeah. Jeff, many people, I think, in RevOps already know you from your podcast, from your Substack, from LinkedIn, from the many courses, from the webinars you gave, or you're still giving, also in combination with RevOps Co-op, for example. So but maybe some people don't know you yet. So for the few listeners that we have who do not know you yet, who are you? What do you do?

Jeff Ignacio: Yeah. Well, I wouldn't say there's a lot of people who know me, but for the few who do, I appreciate them. The world of ops is pretty large. As I've learned, I was at a conference last week for the operator's guild, and there were a few people came up to me and then there were a lot of people who, quite frankly, it was first time meeting me. I'm pleasantly always surprised. The world is very large. But for those who don't know me, just a little introduction. I started off my career in management consulting and then wore a bag in terms of, you know, was in sales before going to business school. And then after business school, I focused my early part of my career, mid part of my career at FP&A, at Intel and at Google. At Google, I supported the sales organization, and that's where I partnered with sales operations hand in hand. And then I also made the leap to sales operations later on, running data and analytics at a company called Meltwater. So I have a SQL Python background, strong numerical background. Moved into operations in the form of sales operations. First company I ever joined outside of Google was a startup that was sub ten million ARR. We grew to seventy million in roughly two and a half years, and we did so without a growth at all cost mentality before it became fashionable. And then over the last couple of years, the last ten years, I've moved into revenue operations. So I've taken leadership of several different functions rolled into my team, whether that's sales development, SDRs — normally spin that off — marketing operations, CS operations, data analytics and sales enablement, all rolling into me. And then I am a full time operator today at a company called Regrow Ag. And then in my evenings and on my weekends, I write a Substack, publish weekly, and I have a large body of material that I've created into a course, which I distribute through the RevOps Co-op.

Janis Zech: Perfect. Yeah. Thank you so much for the introduction. You definitely do a lot of stuff, so it's very impressive. In today's episode, we actually wanna focus on some of the articles that you published on your Substack, well worth subscribing to — just wanna plug that as well here. And one more time, we're also gonna link to it in the show notes. And so what you did there — I think this was a few months back — you basically brought, like, a three part series on forecasting, and the way that you did it is you had seventeen questions. And then for each question, you did a bit of a deep dive, going deep on how you would answer that and what you think were some best practices around that. So our thinking was, like, let's just go through that. Maybe we could cover them all. Maybe we have to cut off at some point, but we'll try. So that's what we're gonna do. Focus on forecasting with Jeff.

Philipp Stelzer: Yeah. First one, I'll just kick it off, and then, Janis, you can take the next one. But, yeah, how often would you even do forecasting? What's like a good sequence here? Is it daily, weekly, monthly? What's your take on it?

Jeff Ignacio: Yeah. So let's remember that a forecast is meant to be a prediction of some sort of outcome based on your forecast. And so depending on your sales motion, the frequency is going to be very important. So if you have a high velocity sales motion, a forecast on a daily basis may make more sense. So I'll give you a real life example. I worked at a company where our sales cycle, as measured by create date to close date, that was an eight day sales cycle with about one seventh of the deals being a one call close. So if you look at the distribution of deals, the average would say eight days, but you'd see a little bit of a right skew beyond eight days. And then you see a large number of deals hitting at that first day. So a daily forecast would be appropriate there because if you wait a month, the whole month has passed you by essentially. Now if you have, like, a mid market selling motion, that's gonna be anywhere in the sixty to a hundred and twenty day range. A weekly forecast is appropriate. And in fact, it's probably the default standard for forecast all the way up to the enterprise. And the how you do your forecast will differ because, you know, if you have a two year sales cycle selling to fed or sled, any of these government type functions, week to week is not gonna make much difference. But for mid market and for enterprise, it's anywhere between like a nine to twelve month motion. Weekly can be important because most sales reps have anywhere between twenty to thirty deals in their pipeline. So the large majority of deals may not have a lot of movement, but you're gonna see maybe a third of their pipeline having some movement.

Philipp Stelzer: And, I mean, I think often we see in the market is folks combining a bottom up with a weighted and then also kind of a prediction or ops forecast. Like, I mean, do you use weighted forecast, and what are some of the pitfalls you've seen when using a weighted forecast?

Jeff Ignacio: So weighted forecast is useful in a couple of ways. Right? So in the beginning of a quarter or beginning of a period, you get an opportunity to take a basically a guess of your pipeline based on some characteristics. So weighted forecast could be used along stages, hygiene, the forecast category, maybe some other activity engagement signals. So you're gonna use all that information and apply some sort of weight to it. But we all know this at an individual deal level — you either win it all or you win nothing at all. So it's a one or a zero. It's very binary. But because you have a large composite of deals, your n is large in your pipeline, a weighted forecast can be useful. But towards the end of the quarter, a weighted forecast is not gonna be very useful. It's what you called at the beginning of the quarter, beginning of the period that makes a lot of sense. It's your way of making sense of the pipeline without having all the information and having the benefit of time pass by. But with the passage of time, you're gonna get more hand to hand combat with your deals, more diligent information with your deal inspection throughout the course of the quarter, particularly for the mid market to enterprise motions. For the high transaction, high velocity selling motions, a weighted forecast is probably gonna be the best that you can do because doing a line by line wouldn't make sense because you could use that time for the forecast call actually going out and taking calls and closing business.

Philipp Stelzer: Yeah. It's just too inefficient to have a roll up process or, like, a bottom up motion. Right? If you think about weighted forecast, I mean, do you see most folks doing that on the stage or forecast category basis? What's the typical mode? And then how do you do it well?

Jeff Ignacio: Yeah. Well, I think as long as you're consistent and you have enough history to back you up, then I think you can forecast on pretty much anything. But stage is useful because it's tied to your selling motion. And remember, good data is an output of good process and your selling motion is by definition probably the most important process to your entire selling team. And so if you have a good rigorous selling process and you have strong one on ones and deal review pipeline inspection, those operating cadences, then I think you can trust your stage forecast pretty well, especially if you have a lot of history. Now oftentimes I work at early stage companies, so I can't tell you how many times the very first project that we work on is, hey, let's redefine the stages. Let's redefine the selling motion. And so when you do that, you kind of mess up the whole opportunity to really do a lot of stage weighted forecasting. So at that moment, you move to, like, finger in the air. You're guesstimating the whole time along the way. Forecast category is highly susceptible to the same thing. It's a bottoms up mechanism. So the sales reps are often using like commit, most likely, best case, pipeline, omit. There's some — if you go into some organizations, they don't even have definitions around each one of them. So the rigor around it — and what I mean by rigor is the sales managers have two or three canned questions to help calibrate whether that deal is truly commit or best case or most likely. And if you get these fuzzy answers from sales reps or you have sales reps who, quite frankly, have either a conservative or optimistic disposition. Conservative — let's call them what they are. They're sandbaggers. Right? They have a deal that's progressing pretty quickly, but they don't put it into the CRM until the last moment. Then there's the rep who, oh, they called me back, this is totally a commit. It's like they take the faintest signal from the prospect that it's more positive than it should be. So it's highly susceptible to that. So, you know, give and take what you should weight on. I think stage is probably the better, more suitable option because it's probably the thing that is most defined in most businesses. But if you can triangulate across both with a matrix weight, that'd be even better.

Janis Zech: So the way I understand you is, you know, as long as your sales process is really compliant and adhered to, you know, entry and exit criteria are clear and not just documented but actually lived by the team, and there's a good cadence of deal reviews and some history, right, which is super important that you can back up. And maybe let's say the environment hasn't changed in the last three years, and so all your stage conversion rates haven't changed, that can be a very feasible way to look at, you know, one input factor for your forecast. Is that a fair summary?

Jeff Ignacio: Yeah. At the end of the day, what you wanna do is professionalize the function. Wherever you think you have some leaks in the boat and you think you're running a bit amateurish. Right? Like, for example, what does your stage mean? What does it mean in principle in terms of action for the buyer, for the seller? How do you test for that? How do you inspect it? How often do you get one hundred percent compliance from your team? You know, it's all about rigor and not to over process things, but you do it to some degree. You have to make sure that folks are following the team play and that information rolls up and feeds back. And at the end of the day, you can't go into forecasts with insufficient information.

Janis Zech: So I know Philipp is gonna hate me for that — I'm known for jumping questions, you know, we thought about — and I think it fits really well here. And as I'm now here, I can do it. So I think you had a really interesting aspect in your article about hygiene quality. Right? Like, almost kind of a way to measure pipeline hygiene. And it's something that we're talking to a lot of RevOps leaders and sales leaders every week, and it's something that I think a lot of companies are struggling with. And you laid out a really, I think, fantastic way of measuring hygiene. Like, do you do it, and what are your recommendations to that?

Jeff Ignacio: So with hygiene, you know, it's a checkbox at the end of the day. Right? So what's the checkbox? If I ask you to do something, I turn around — do you do the work? And I turn back around and the activity is completed, or, you know, I asked you to clean the table and the table's clean. Great. If I ask you to do something and turn around, you haven't done it and the table is still dirty when I turn back around. So it's about commitment from the entire team to work as a team. Sellers think that their only job is to sell. I would disagree. You have a responsibility to providing quality information to the entire organization because part of selling is forecasting and a sales rep is also part of that team and they make up one of the most important parts of the team in terms of forecasting because operations left to their own devices, we're just gonna apply a forecast. Right? We're gonna apply a weighted forecast with some sort of probability to it. And it sounds smarter than it is because it's simply just taking some sort of weight and then multiplying it against a number. But there's that anecdotal qualitative data that needs to be paired with the numerical empirical data. Those two together give us context and give us the opportunity to tell a narrative. So, you know, again, selling is a team sport. Forecasting is a team sport.

Janis Zech: Yeah. I would also say that, really, what you wanna do is you wanna enable the conversation between the manager and the reps where then the manager is actually able and enabled to really ask the right questions. Right? So basically that's the anecdotal data that the reps are giving. Then you have this clear process defined. You have signals that are clearly understood both by the manager and by the reps that are transparently communicated, that are embedded in the corporate culture or company culture or sales culture of that specific team. That just make it easy to have that conversation around whether, you know, that's a real deal or it's not a real deal, to quickly vet it. Right? I think that's in the end what you really wanna have. You wanna have a good conversation between the teams so they can end up with, like, a solid number.

Jeff Ignacio: I would agree. I think a lot of folks think that managers are there to, quote unquote, manage. But quite frankly, you know, they're there to also be leaders and coaches. And so, you know, it's a shared conversation at the deal level. And as a leader, as a manager, you hear the information and you understand this person's tendencies. They may over index. We all have biases. Right? And so reps might bring that bias to the table, and the leader can, you know, kinda cut through that noise real quick and assess it for what it is. And in my mind, two heads can be better than one, especially when thinking through how to derisk an opportunity.

Janis Zech: I love this. I love this so much. I think forecasting is not about the final number. It's a process. Right? And it should help to actually drive more revenue as a general revenue process. And, I mean, what we are seeing a lot, and I think some companies are doing a great job but many don't, is that these, you know, one on ones and deal reviews are spent on essentially hearing the same story and talking about the same deals, but actually not having the data to understand what's going on. And this is really baffling. Right? Like, everybody's talking about AI, but then these fundamentals, right, like entry exit criteria, MEDDIC SPICE fields, right, like the fundamental activity and deal velocity, and when you send emails, get emails back, or there's a next meeting scheduled, or you multithreaded it or not, right, like these core signals, they are fundamentally missing, and so the majority of the conversation is spent around understanding what's going on instead of strategizing, to your point, on how to essentially close those deals. Right? And I think that's so, so important to drive revenue.

Jeff Ignacio: Yeah. So I teach this in my RevOps course. You guys ever heard of systems thinking?

Janis Zech: Sure. Yep.

Philipp Stelzer: Sure. Yeah.

Jeff Ignacio: And so one of the primary tools in systems thinking is the feedback loop. So you wanna create many feedback loops all across your go to market motion. And the reason you do that is because, you know, when we talk about RevOps being a partner and advisor, it's because we wanna step up from being, quote unquote, order takers to someone that could help drive better decision making. Feedback loop helps you do that. Right? So you collect the feedback. You analyze the feedback. You synthesize the feedback, you create a recommendation, you act on it, and then round and round they go, you keep putting in that loop. A deal review, a pipeline call, a forecast call is a miniature feedback loop. Right? You're looking at some minute detail, and it's like the Toyota production system. Right? The Toyota production system, if everyone remembers, there's an andon cord. It's this cord on top of a worker station. And if a worker observes a defect or a flaw on the production line, they pull the andon cord, the entire production line stops across the entire production facility. And it's the same thing on a sales floor. Right? So if you can get to that level of rigor — I know a lot of folks use revenue leaks, revenue manufacturing as a visualization or metaphor. I don't fully believe in that, but I do believe in good process. It's not to be robotic and mechanistic in any way. It's just meant in the spirit of continuous improvement.

Philipp Stelzer: Speaking of process, so how would you do forecasting? Would you use a roll up forecast, sort of like a bottom up approach where each rep makes their own call, and then in the end, you take the sum and roll it fully up to the highest level of hierarchy?

Jeff Ignacio: So with the roll up forecast, the roll up forecast is useful in a couple of ways. So you wanna have a top down and a bottoms up forecast. With the top down forecast, that's where you're using stage weights, the probability. It loses some context unless the sales operations manager is really on top of the pipeline week on week, and that's why a snapshot's really important. A good sales ops manager, RevOps manager will quite frankly know the pipeline inside and out. Right? They'll know where the deal was last week and where it is this week. They'll have a pulse on it. They may not have the newest information. Like, if there was a sales meeting a day or two earlier, the RevOps manager, sales ops manager, they're not gonna know. But a roll up is gonna be useful because it's the process of the role that matters more. So let's say, for example, you have your forecast call on Tuesday or Monday, you wanna set up a forecast lock one business day or two business days prior. And the reason you do a forecast lock is because you wanna have enough sufficient time to review the data and pose a couple of questions. Right? This is where operators turn from tactical to strategic. They look at the pipeline, they look at it last week versus this week, they look at the deltas. They can come up with a narrative and a story, and the roll up should be more than just a number submitted. There should be some sort of next step update or commentary from the entire team. And that roll up is essentially about process. Again, forecast lock. And then one day or two days prior to the lock, you send the reminder or nudge. Right? So your forecast is actually a continuous process. It's not a once a week thing. It happens throughout the entire week. So after your forecast is done, you send out the action items, and then you follow up the next day. Two days later, you send the nudge to do the forecast all over again, and then you have the forecast lock four days after that. That's why it can feel for some sales reps like, jeez, we're just constantly forecasting. There's not a lot of change. But given a higher number of reps, higher number of deals per rep, you're gonna get some nuggets in there. Right? It's that twenty five percent of change in your pipeline week on week that really moves the needle for the entire organization.

Janis Zech: I would also say, I mean, this is one of the opportunities where I really think RevOps can have a big impact on making that a smooth process, because I think this is one of the good examples where, you know, the easier you make it on the reps — like, if the process is really clear and it's clearly communicated and there's clear ceremonies around it, and you can definitely do that. Right? Like, I mean, just make it a fixed calendar invite on day x of the week or month or however, whatever your forecasting cadence is, and then just, you know, try to embed that really in the company culture. And then it just becomes like a muscle. Right? Like, you're just gonna twitch automatically every Thursday at twelve, and you're just gonna enter the numbers or include the deals, and then it's done. I mean, it shouldn't really take more than five to ten minutes, I think.

Jeff Ignacio: That's the trick. Right? So for a sales rep, if you ask them what's in it for me, I think the core thing is, you know, like, it only costs you five to ten minutes of your time a week to update things, but what you get out of it is a honed in, sharper leader and manager ops team supporting you because they're operating with the very best information in mind. You're keeping them on their toes. So when the time comes, you have a support team and a leadership function around you that is at the top of their game. If they're constantly playing catch up, then I can tell you that when you need help as a sales rep, relying on a leadership and ops team that's behind the eight ball, you know, that's a hard place to operate from.

Janis Zech: I have a question regarding the roll up. So, I mean, you mentioned the cadence. Right? Let's assume it's a Tuesday forecast call where probably different folks come together, like CRO, VPs, ops, maybe marketing included. Right? And, you know, so would you recommend every rep to do a forecast call then managers to review and adjust? What should be the adjustment time? Should that be on a deal by deal basis or just, you know, a call and a comment? Like, you know, what do you think is best practice? Let's say, how does very good look like here?

Jeff Ignacio: So I think every organization's gonna operate it a little bit differently, but I've seen — let me give you some real life examples and pros and cons of each approach. Like, the first startup I joined where I was a director of ops — didn't have a team, it was just me, it was like a one person show. We were divided into an east and west region, right? So we were selling into North America, east and west, and we had eight sales reps on each call, and the CRO was leading that call. And each call was ninety minutes. So we had eight sales reps each, everyone would get maybe like six minutes of airtime, seven minutes of airtime, and they would go through their most important deals. That was it. Like, they didn't get to go through the entire pipeline. So late stage deals, big deals in terms of size and amount in descending order, and the ones that you said you're committing. So those are the only deals that got attention. The deals that didn't get attention — the deals that were early stage deals that were in pipeline or omit or best case, they're not in most likely, they're not in commit, and the deals of a smaller deal size — those deals just didn't get a lot of airtime. Now who does that disadvantage? It disadvantages the reps of smaller markets. It disadvantages the reps who are new, so they're not gonna get a lot of attention. There's not a lot of love there. So their attention is gonna have to spill into the one on one call with their manager. So hopefully their manager's paying attention to them. So that's the pros and cons of that approach. Second approach that I've had is a more structured one where you have five to ten minutes of slides and you're going over a lot of updates, right? So you're smashing sales call, pipeline management, and deal forecasting altogether into one call. And it's probably a typical end outcome for most organizations. Most organizations are going to smash all three of those conversations together, and depending on how much airtime you give, that meeting is typically sixty minutes — any shorter than that, you're just speeding through it, right? And you're making that feedback loop insufficient, in some ways inadequate. But if you give it enough airtime, timing is really important here. So sixty minutes, seventy five minutes, ninety minute forecast, depending on the depth of your team. If you have a wide span of control of eight reps per manager, and at the end of the day, you have to determine who's gonna run that call. Is it gonna be ops? Is it gonna be the frontline manager? A smaller organization, sure, the CRO can do it because it's a smaller organization. But a large company — you can have a regional VP sitting on four teams. That's a lot of airtime. Instead, you wanna delegate and trust down to the frontline manager and have them do a roll up. Right? So they're gonna apply some judgment and commentary around it. And so best practice, I think it differs for every organization. Again, there's a couple of elements. Do you smash a number of different topics together? Do you have a really structured agenda? How do you format which deals to talk about? It's not possible to talk about every deal, so you're gonna have to be judicious about how you filter it. How do you make sure that feedback loop — you get out of it what you believe you should be receiving in terms of quality information.

Janis Zech: Yeah. A hundred percent. I mean, obviously, it's all in the context of the size of the organization. And then, I mean, I think the beauty of a roll up is you can have different forums — to Philipp's earlier point, right — where you basically apply the same rigor and coaching and strategy discussion around deals, but just in different forums, then it finally rolls up across the organization. You mentioned the idea of logging basically the forecast calls at a specific date so ops can prepare. How many days do you typically do that before? Because obviously if you do that weekly, it can't be five days, I assume. Is it typically a day?

Jeff Ignacio: The forecasting process, a lot of folks think the forecasting is a one hour meeting per week, right? And for operators and sales leaders and CROs, I can tell you it's not one hour a week. Forecast is very much top of mind. It's almost like every minute of the week. But in reality, it's probably a four to five hour cadence, because you have the nudges and that can be automated. But you want to spice things up. You want to make sure that message isn't stale each week. Second is the synthesis, the analyzing and determining insights. That could take an hour easily. You're going to the pipeline. You're comparing deals. You're pinging reps, trying to get a little bit more information. Right.

Philipp Stelzer: Yeah. One more question that I had, I'd be very curious about is how you handle sort of, like, these really big deals that can completely shake up the forecast call. So let's say, you know, quota is, like, three million, and suddenly you have, like, a five hundred k deal in there or something like this. Like, would you include that in the forecast? How would you treat that? How would you handle that with the sales team?

Jeff Ignacio: So let's define big deals first. Right? So you're gonna have your average sales price, and hopefully you're segmenting your deals, first of all, and then you have your median sales price. I think a lot of folks will use average sales price more often than not, especially when they're reporting out to the street or to the board. But quite frankly, your median sales price is probably your typical deal. Right? And every once in a while, you have a bluebird, you have this huge deal that comes out of nowhere and skews everything up to the right. But, you know, these large deals have a way of galvanizing the entire organization. Everyone's set of eyes, everyone's discussion and questions start to center around this one big deal. Now, if you're an organization that sells like a thirty k average deal and all of a sudden you get a two hundred k deal, well, that's six x above your average. And I'm not a statistician by any means, but my guess is that's going to be above your standard deviation of closed business. And what ends up happening is that one deal is going to have lower probability to close for a variety of reasons. One, you're competing at a price segment where the feature request for your type of product is probably going to outstrip your current product's capabilities. And so you're selling against the big boys, right, or the big girls, and you're getting into the big leagues. And that customer is going to get the five star quality hotel experience attention from your support and your product team. So all of a sudden, is it 6x the amount of time? They're probably going to get 20x the amount of time. So for 6x the economic value, they're going to suck up twenty x the value of the entire organization. They also have a way of changing your roadmap. Right? You have this road that's moving in one direction, and all of a sudden you have this company come in with a steamroller and just start putting cones on the freeway and readjusting traffic and wreaking havoc across the rest of the deal flow. And so the way I'd like to think about big deals — first decide, should this be a type of deal that you should do in the first place? And not all revenue is good revenue, right? Because there's expense and costs associated to it, which I alluded to. But let's be real. Most CROs, most sales reps, and most CEOs are going to look at top line, top line, top line. They're gonna want that deal — a buck is a buck. And so the next thing you wanna do is, okay, well, we wanna give this deal the same amount of airtime in the team conversation as everyone else. We don't wanna treat it any differently. But you do want to treat it differently in some other ways. So you can set up something called a big deal review. Some folks might have, like, a deal desk function or an exec sponsoring function, and you're going to have sidebar conversations anyway. So you might as well put rigor and process around that as well, which is — this is a big deal. There's a minimum dollar threshold. You know that product is going to get involved because they're not buying the typical product. They're buying the potential of altering your product, right, because they're like, hey, look, you guys are a promising team. You guys are doing some really cool stuff, but your product's not quite where it needs to be. We need you to put more feature requests on you. So you're gonna need to bring in a product leader there. Also gonna have to bring in a customer service leader to some degree because they're not gonna take your random CSM. They're gonna want your very best CSM. Someone who's totally invested as an adviser and knows your vertical, knows your experience, knows your problems intimately. And so that big deals review is cross functional all of a sudden. Right? Because the forecast call is primarily going to be the sales team, but the big deals review is going to be everyone. It's going to be service. It's going to be product. It's going to be operations and sales. And so my thinking is segment your pipeline, put some rigor around your big deal review. Don't let it consume all the oxygen out of the room from your bread and butter, your normal business. So yeah, that's my thinking here on large deals.

Philipp Stelzer: Yeah. So the suggestion is basically before you even consider forecasting on this deal, do you even want to take the deal? Am I getting you right?

Jeff Ignacio: Yeah. But let's be real. No one's gonna say no.

Janis Zech: Yeah, exactly. I think it's such a good point because it has so many ripple effects. I think that's what you're alluding to, right? There are so many ripple effects, and you need other stakeholders than just the typical revenue team on the table to actually get those deals done. And so either you carve out, you know, in your weekly forecast meeting fifteen minutes where those stakeholders join, right? They might not want to join the full hour. Or you do a separate conversation where you really do big deal reviews and make sure that you put all the rigor you usually apply to all things, you know, pipeline management forecasting, but also on the big deal side. And yeah, I think that's a great way to look at it from my point of view.

Jeff Ignacio: Yeah. If you think about it, it's an accelerated TAM, SAM, SOM conversation, right? TAM, total addressable market, share of addressable market, share of obtainable market. You are who you are in terms of — you have a profile of customer you sell to. We call it an ideal customer profile. Then you have like random grab bag items, miscellaneous customers in there who aren't great fits. And you know they're not great fits for a couple of reasons. They spend a lot of time with your customer success team. They spend a lot of time with your product team. They don't have as great recurring retention metrics as core segments. Again, this is one of those sales versus CS type of conversations. Sales sells a deal, throws it over the fence to CS. CS opens the present. They're like, this is great. Wait, what is this? What did you promise? What is this? Oh, my God. Why is there fire inside this house that we bought? This is crazy. And sales answers, let me show you the ROI calculation. Yes. There happens to be a gravitational field around all customers. Right?