All right, let's get going. Welcome everybody to the latest episode of Stacking Growth Live. I'm Cassidy, Chief Growth Officer at Refine Labs. I'm excited to have Sydney with us today.
I think you're all here for a specific reason, and that's a here at Sydney dive into the next level of detail of our pipe go-to-market framework, which I'm actually excited to hear about this as well, as well as all of you. So Sydney, welcome to the show. Hi everyone, nice to be here. Sydney Waterfall, VP of Demand at Refine Labs, and come to talk about this.
I'm kind of a data Salesforce reporting analytics nerd at heart. So that was a fun fact about why I love this topic so much. I actually have to jump in here. Sydney, is it VP of Demand?
It is. It is. It is VP of Demand right now. Sydney's on our way to being promoted, everybody.
So congratulations there. Obviously, she doesn't want to introduce that to all of you on this call. So the way we're going to run this today is, Sydney's going to delve into the show some slides, delve into the pipe framework in more detail, what it is, why we built it, and kind of one of the next steps. We want all of you to kind of obviously listen to this, but then start asking questions.
So we're going to make this very much like any live session, a dialogue back and forth. So now Sydney goes through this. I'll be asking questions, but I'll also be moderating all of you. So as you hear things that you want to know more about, feel free to pop into the chat while I'm asking for you or we'll have you come on the show.
So with that, why don't I turn it over to Sydney and we can get started. All right, let's do this. Today, here to talk about pipe, which is a new framework we've been working on here at Refine Labs, and specifically Hero Pipeline, and what that is. And we'll get into this.
So first, I wanted to talk about not all pipeline is created equal. So I'll still find a little exercise here, some examples, but I would love for you guys to blow up the chat. What is your definition of pipeline at your company? We'll assume like most of us are B2B SAS marketers here.
I know this will be different based on other companies, but what we hear a lot is a lot of varying answers. It's opportunity opened. Okay, that's what we count as pipeline. We counted as pipeline when the opportunity has, or the sales team has completed a full product demo.
And that's when we take the opportunity amount and count as pipeline. We got some chat over here, stage one pipe, sales accepted pipe. Look, this number of opportunities has been accepted and qualified by the sales team. So all similar in theory definitions, but slightly different for every company.
I know this has been the same when I've worked at different companies. There's slight differences in each of these definitions. It's we counted as pipeline when it hits SQL. Okay, what does SQL mean?
SQL means the amount on the opportunity after the sales team fully accepted it. Okay, makes sense. We say stage three opportunity is pipeline at our company. Okay, what does stage three mean?
Right? So that's kind of to my point here, the chat is kind of blowing me up right now about all the funny things that people are putting in here. But that's kind of what we mean is everyone has a slightly different definition of pipeline. So that comes with this challenges.
Obviously with pipeline comes opportunities. So what does an opportunity mean at your company? Here's four different examples that we typically hear. And it really depends on your sales cycle, right?
When in your sales process and how you have set that up internally, which is personal to your company and your business. So some companies say, all right, we want, we create opportunities right when the meeting is first booked by the SDR. A.E. has the name talked to them yet, but we're gonna create the app to start trapping it.
Awesome. After the first call, A.E. has to prove it, that they're in a buying cycle. Like what does that really mean?
It's a little subjective, right? After the A.E. has completed a full demo, you know, the demo might not be the first call, might be the second call or tailored to your process. Or there's a thousand different variations.
So that's what I mean by pipeline is not created equal here. And when we go into this, you remember these definitions on the next slide, but we're gonna go into some examples here about how this kind of breaks down when you start looking at overall pipeline inbound versus outbound pipeline and this concept of pipeline source. So pipeline creation and win rates are greatly different based on what we call a pipeline source. So here's some examples of pipeline sources.
These are the go-to-market functions in your business that are driving results. So kind of like your go-to-market engines. And you might have a couple in your business depending on how you have things structured and how you should have things structured. So we have what we've termed pipe, which is kind of our declared intent, which is what we talk a lot about here at Refine Labs is, you know, your high intent, the people are asking and wanting to have a raising their hands asking for a sales conversation to talk about buying your services or product.
So that's like one go-to-market function, one pipeline source. You also might have outbound, that's also pretty common, kind of lumped ABM into here, highly debatable topic. That's probably a whole nother episode to be honest with you. You have events, right?
Events, field marketing, that's gonna be, it's probably own pipeline source. And then you also have low intent lead gen, if you're still doing that, you know, totally fine, but we need to break it out separately. So one of the key things with pipeline sources is you're actually able to see the efficiencies through your go-to-market functions where historically you probably look at your funnel inbound versus outbound, marketing source versus sales source. But that really doesn't align to true go-to-market initiatives that I would say in the newer buying era that we actually do marketing today.
So this is a chart is kind of an example of like looking at the unlock here is when you actually look at opportunity win rate by pipeline source, you start seeing things that you might have not seen before, that can lead to better decisions, better prioritization of your internal resources, budget, focus, all of that. So that's kind of one of the main things that I've learned and we've learned here at Refine Labs by working with a lot of different companies. You can see here on the chart, we've got our four different companies. And our last slide had four various different definitions for how they create opportunities.
So because they have very different definitions and there's not a standardized way to look at the data is very hard to benchmark, hey, company one, you're at 16% win rate on your pipe declared intentional. Company two's at 48%, oh, company one, you're below the benchmark, you're not doing that good. But you can't really say that because if you remember opportunity one, they create opportunities before they still see them even talk, they create opportunities that mean booked. So that makes sense why their win rate is gonna be a little bit lower, right?
Versus a company three, they create opportunities after they use how to full demo. Totally makes sense why this 48% conversion rate. Also, these are totally, this is made up data, this is sample data, this is not actual data. So yeah, curious on your thoughts, Cassidy too, the unlock from looking at it from more of a pipeline source versus a blended view and like what your experience there is.
Yeah, I mean, for a few things, we're talking about this earlier. When we think about just what makes up pipeline and opportunities, we went through this in my last company shifting from what a lot of people said here, which was an AE kind of qualifying an opportunity and putting that in the pipeline too, just capturing new conversations and starting that in pipeline. So if you think about what that goes to your, to these numbers on the start, that dramatically changes it. So if you don't have like a structured way of thinking about that, it throws out your pipeline dramatically.
What I like about this is that there's a lot of debate about what's a marketing source and sales source and kind of who gets credit for what. And when I, I think the power of pipeline source is just it kind of gets that out of there and it talks about like, what, where did the pipeline come from in terms of the source and what's the performance of each one of those? And how do you really compare, at least in this chart, you start comparing apples apples across pipeline sources, which I think is ultimately what, you know, as a business leader, you want to do, because you want to determine where you need to be investing your money and time and effort across those sales and marketing. So I think we've all faced this scenario where we're trying to compare what you do to some other company, whether that's your VC doing that, what cost or portfolios or what have you.
This paints a picture of the complexity of that. Definitely, I'm going to go into a quick story of literally how we got here and what we learned before we then talk about the nuts and bolts of the pipe framework. So we work with a lot of SaaS companies here at Refine Labs, various industries, various stages, different complexities in our business. So we thought, okay, we need a better way to understand and give our customers more data on like, is this good?
That's a question we get all the time. Is this good? Is our pipeline growth good? Is our, how are we tracking?
Everybody loves benchmarks. And that's the problem is that without standardized data, the benchmark is challenging. So we set out to do this. There's a kind of internal task team.
We're like, all right, we're going to audit and collect all of our customer data. And we want to look at trends and then like, give those insights to our customers. Like, hey, you're above average on your pipeline growth quarter of the last year or last six months, or even book meeting growth, different metrics. We want to be able to find that.
So we go into all the CRMs and we're looking at data. And like, we learned a lot through this exercise. We learned that there's a lot of challenges because we are comparing opportunity create and pipeline creation, even if you want to go step up and say, high intent inversion. So demo requests grow for things like that.
We collected it, we were looking at the data, we're looking at the trends and we're like, this is not apples to apples. And this is not helpful for customers. And if it's not helpful for our customers, it's not going to be helpful to anybody. Any marketers, any go-to-market leaders, when people ask for benchmarks and things like that.
So we kind of try to figure out, can we make this work? How do we make this work? Like, what's a system that's better for not only our customers, but essentially the industry. And that's really what we wanted to figure out.
So that project got kicked off in Q3 of last year. We spent like a quarter digging into it and we learned a lot. And that's kind of what we want to talk about next. So I will- Yeah, I would say my Cindy pulls that up for folks.
Keep the questions coming. I'm kind of categorizing those. I'd like her to walk through this next. I think that will help set up how we answer a lot of the questions that I see in the chat right now, which are very good, by the way, so people come.
Yeah, the chat's like going up. I can't even keep up. It's great. So here's what we learned from getting all that exercise.
Most companies forecast model and optimize using all pipeline or maybe just inbound and outbound pipeline. So it's kind of like a blended approach. Just like when we talk about splitting the funnel and forecasting, you shouldn't forecast all your M2Os and leads the same, right? They're very different conversion rates.
Same thing when you get to the pipeline level. It's super challenging to compare benchmark companies and give them like actual actionable data because there's no standardized definition. A lot of it is very subjective. So and it's tailored to the internal process, which makes total sense from an internal company standpoint.
So that's kind of what we learned. And we said, mmm, like there has to be a better way. So we figured out and this is kind of what we put all of our heads together at Refine Labs. There's a ton of smart people here.
There has to be a better way. We've got to create a new solution. So insert our pipe, go to market framework. We've been chatting about this a lot on the other podcast, our state of demand gen.
So I'm super excited to kind of walk you through some nuts and bolts of it. And then we can dive into questions and things as well. So first before I go into what the framework is and the key steps of the framework, I want to kind of go over like, what is this? So it's something that we developed at Refine Labs that we use to understand the performance of our go to market source, which is pipe.
We've branded that and that's essentially our high intent website convergence. High intent, someone asking you to come in, they've declared the intent, they've personally told you their intent, not the intent software, again, the whole other episode. They've personally said, I want to talk to the sales team and they came to you and asked for that. So that's this go to market funnel.
And that's what this is going to be kind of centered around. And the reason why we call it pipe is instead of a funnel, it's the sales velocity of this source is probably your highest sales velocity channel or go to market channel depending upon but it's one of your highest. So definitely pipeline versus a wide, wide, wide funnel all the way down. So let's go and check it out.
Okay, so here's kind of the nuts and bolts of the go to market framework. So we started off at the top of the funnel, top of the conversion here with what we call pipe conversion. So these are declared intent form bills on your website that someone is asking to speak to your sales team. Most commonly a demo request, a pricing request, you know, a book of consultation for us on our websites that's our high intent conversion.
That's when someone is asking to speak to your sales team. And one caveat here that I want to talk about is right now for this conversation, what we're going to talk about today, it's centered around like a sales lead motion. We'll probably have more iterations of this that works in product lead as well. That will be coming.
For the conversation today, it's more of like a sales lead funnel, or if you have a product lead and sales lead, it's that high intent conversion where they're actually asking to speak to your sales team and not asking to try your product or look at your product. So that's the main top of funnel conversion point. That's the entry point into here. There's a lot of other things going on above this, a lot of marketing activities that we talk about all the time around creating demand, capturing demand to push people into here.
The next stage is pipe qualified meetings, what we call PQMs. So this is firmographically fit, so not any kind of spam or unqualified type of form submissions that book a meeting with the sales team. And we like to level on this metric because it's a quality control metric of your pet conversions. If you're getting a lot of pet conversions and they're not converting to meetings, there's a problem.
And then what you probably heard a lot of talk about is what we call high intent revenue opportunities. Well, we all hear of this. This is an opportunity that has a six month trailing win rate of greater than 25%. And this is the real game changer, is because we are standardizing this stage across data, not across subject, subjectivity, or what means qualified or what doesn't mean qualified.
It's around win rate. So that way you can compare across different pipeline sources, across different sources in your business, different go-to-market functions, and it's not as subjective as what people are currently using. And then obviously close one is close one, customers. So that is the overall framework.
And how we think about it and how we've been trying to honestly like simplify it. Like at a business level, these are the four main like KPIs we look at and we believe everybody should be looking at it. There's going to be other sub metrics, like meetings attended or sub steps in here, but in order for business level reporting of how this go-to-market function is doing, this is what we believe is the best way to simplify this and standardize this across. This is something you educated me on.
I pushed back and said, why do we have pipe qualified meetings? Why is it not pipe conversions? And we had a good discussion about why we need this PQM stage. I'd love you to kind of share that with the audience.
Cause a lot of us were like, oh, somebody raised their hand. It's a demo request. I'm going to count that. And I'm going to go write the pipeline creation.
I'm going to look at my hero. And we've kind of put the step in between. And it wasn't, it was qualified meetings. It wasn't necessarily meetings held.
And we went through that whole discussion. Maybe some of that is going to people's mind now, to be great if you just like elaborate on that. Yeah. I see some other questions in here around thermographically fit and convergence as well.
Like, why do we level up thermographically fit at the meeting level? So the top is pipe conversions. Those are essentially like besides tests, leads, or spam leads. Like what are the total conversions that you're getting in from your declared intent, the conversions on your website?
We don't understand that total. And then if we just jump straight to pipeline or heroes, we miss a quality control metric that I think is really important. And marketers can game the system a little bit. Just like sales can game the system at their stuff too.
It's like, it's pretty easy if you say, okay, I just need more. I'm going to see more conversions. All right. I'm going to run maybe performance marketing or I'm going to do some lead gen retargeting for demos or I'm going to get really creative with the language on the landing page here to get people to fill out this form.
So we get more of those type of conversions. But if they are not actively dedicating a time to speak to your sales team, that's the first step. But they are not saying like, I want this and here's time on, I'm giving you my time. I'm willing to schedule my time as the prospect or potential buyer.
That's boom. That's what we want to center around because that's harder to, you know, gain the system a little bit here. It's a harder metric to get. It also is a very good metric to center around because it's a metric that is more shared between sales and marketing.
So I think it's a good metric to think about. When I think about go to market, I don't really think about like, with this framework, marketing does this and sales does this. It's like, we're one team and like, how do we drive ultimately revenue in these four steps? So I think that's one of the reasons we advocated and decided on qualified meetings.
And then yes, of course, you should be tracking, you know, meetings, attended or meeting sat, of course, that's a metric that you need to look at. The other reason we didn't initially go out the gate with that is because you be surprised at how many people don't even track that right now. And like, it's very surprising. It seems like a very easy metric to track.
Some companies don't even actually track like meetings consistently, I would say, in a non manual way meetings booked with their sales team. So when we think about rolling this framework out, we also are thinking about how do we put like, how do we roll this out? And so you get historical data into these stages as well. So we could see what what did the past year look like and how are we going to improve that?
Moving forward with thinking about implementing this new framework. Hey, there's a couple of questions here. I just, and I think you just clarified that. But it was PQM is that a definition of kind of qualified meetings.
So to happen before the meeting or after the meeting, what you just said is, we like to think of it as before the meeting. One of the practical reasons why is because I heard you correctly, is like a lot of companies don't track whether the meeting actually was held or not. Yeah, I guess another one would be if there's a declared intent, they won't have a meeting and they're qualified and we can't get them in the meeting. That's a point of friction that you want to kind of measure over time and figure out how you close the gap on versus if you just went with only meeting held and you're missing a granularity other, it's probably important.
Anything else I missed on that in terms of that decision? Yeah, it's that meeting booked. And to clarify too, like, this is like the first meeting for the prospective customer. So regardless of what your sales setup is internally, whether they go to an SDR first or an AIFRS or they have a discovery call or as a demo call, like that's all subjective and that's going to change.
We want to know what did they book a meeting with your sales team? So and additionally, I'll just say shout out, like since these are your most high intent declared intent leads, they have the highest win rate normally and the highest sales velocity. These should be going to your best salespeople and you should think about actually sending these section of your business to your A. But that's again, another podcast episode in itself.
So but that's definitely something we recommend. One of the questions in here, I think might be a good place to answer this. Or I think it was what you're going to talk about next. And that's just this notion of is hero only used on kind of the high intent kind of pipe framework as we're talking about or is this hero something you can use across other pipeline sources and like what does that work like?
Definitely. It's so quickly answer the question that I'll jump into the next slide, which is centered around hero. It's something that you can use across all go to market functions. The reason being you can use it across go to market functions is because it's standardized on win rate.
So you could have a pipe high intent revenue opportunity. And the reason we specifically called it like revenue opportunity is because it's centered around win rate, which is greater than 25%, which is one in four should close, right? So it's got a consistent proven predictability to revenue, right? And that's what we wanted to standardize around the 25% the one in four.
So let's just jump into here while we're here. Okay, so one thing to note here, kind of revenue opportunities. You will see this and this kind of how we can explain this concept is a, we've already mentioned it's a standardized definition of a win rate. So boom, apples to apples.
You could compare a hero from company one to company five and you could actually start benchmarking and understanding trends. You could also do that across your go to markets. So you could have your heroes for pipe. You could have your pipe heroes.
You could have outbound heroes that fit that definition partner events, what have you, right? And then you would have, okay, how much actual qualified pipeline that we describe as hero is coming in. And the reason you can do that is because it's standardized. So one thing to note here is if for some reason our definition is typically six month trailing win rate, there are one new ones.
Like if you have a 12 month cell cycle, we might look at a 12 month trailing win right here. But this graph on this slide kind of demonstrates, okay, every company has their own stages. Typically we see between like five and seven stages. I hope you don't have more than seven stages.
Your hero stage will vary by company, but it will also within your company is going to be very, is going to likely be different by pipeline source. So here's an example. Again, this data is kind of just like sample data to explain the concept here, but you have three, this could be three different companies or three different go to markets and you're gonna have your different stages. So let's just take this first line as an example here.
Stage three has a win rate of 25%. So that's when we know when it hits stage three, we know it's considered a hero. And that's actually typically what we see around stage three ish around for pipe across the work across our customers. Well, maybe in outbound, it's stage two.
That's it's higher. It's 27%. So in outbound, it would be your stage two. Or maybe in your low intent lead gen or your webinar stuff, like the opportunity actually has to get the stage four for it to increase across that 25% threshold.
So you can kind of see how you can use this definition across different companies, to benchmark, and also internally across different pipeline sources. Another thing to caveat here is a lot of these different pipeline sources have different go to market needs, different go to market processes and just different tactics overall, both on marketing and sales. If you think about events or field when opportunities are created, how they're created, the marketing tactics and the spend that goes into that is much different than low intent lead gen or outbound, right? Outbound, sometimes they have a whole different sales process for outbound as you probably should.
So those are some things to consider there with the hero pipeline. Anything else that is good to call out here, Cassidy, from your perspective? I just want to reinforce this point. I think this is, from my opinion, the most powerful part about the hero concept and that is the ability to standardize across what we call pipeline sources, but it's really good to market strategies.
Very good examples. And what's ironic, I think, and I'm going to jump in with what's ironic is like we haven't actually done this really as an industry. Yeah, this is the thing that's missing to be able to compare effectiveness about bounds in bounds, your classical NQL model, et cetera, et cetera. Does somebody kind of standardize this across your company?
Yeah, this is the game changer. I think this is the unlock, right? We're starting to do this and I see a lot of other companies and marketers going in this direction and even go to market teams, not just marketing, like sales leaders and revenue leaders. We're starting to do this at the top of the funnel.
I see a lot of customers and people that we help. They're reporting on like, okay, here's our high intent goals. Here's low intent. We're moving resources and we're focusing on this high intent.
Okay. So it's still like the opportunity in pipeline. It kind of goes back to the line today. It's like we got to do this all the way down throughout the entire go to markets and then treat them as almost like many separate business units.
Like you might have a team dedicated to each go to market differently. Like I know a lot of people have outbound separated or they have events and field and yes, all the teams are still working together, but the needs of each go to market is going to be very different. You also might have like partner affiliates in here as well. That's a whole other beast and strategy as well.
So that's one thing that is good to call out here. I think it's the game changer and talking about, I'm going to probably stop sharing here in a little bit, but talking about like, okay, like how do you actually like implement this? Like cool, we get the idea. Hopefully you're, you know, getting some unlocks going.
How do you actually operationalize this? So spoiler alert, we are working on releasing some information on how you actually implement this in your Salesforce instance. And the key here is like you don't have to change your stages. You don't have to change kind of your lead flow process and what you're doing.
The ways that you can take the data that's in your system and we can essentially report on this go to market level on top of your existing data structure, right? We get it. It's not realistic to come in and overhaul your entire go to market functions and your lead routing and your everything. That's a beast.
So there are ways that you can operationalize this. And that's one thing why I put your, your hero stage date, if you're going to be measuring this across all your go to markets, you're going to need a dedicated field to track what is that standardized hero date across your go to market systems. And so that's stuff that we're actively working on. We're hoping to, we'll be releasing it in the beta of our VOLTS product, which we'll be launching soon and hopefully we'll be, depending on how that goes, we will be launching commercially to everybody sometime after that towards the end of the year, early next year.
So that's just a little teaser, but I want to talk about, you can, there's a couple of key things that you can set up in your Sierra and the Trapless regardless. Some of the key fields are your conversion source and your conversion, when we say source, we're thinking about source that captures the demand, right? Like, is it a demo? Is it a webinar?
What is the source that conversion? And then you also have your traditional, where did that come from? What marketing channel, like what attribution? You should have your self-report attribution, obviously, and you should have that.
And then you can map that to the opportunity and then you can kind of create this conversion funnel in your CRM. And obviously I'm happy to like keep going and geeking out on that. Like this is the part that I love of like, how do you personalize this? But there are ways that you can take that, what's going on and map it to the opportunity.
And then you will be able to build some of this reporting yourself as well. Cindy, how is the question in here? I just want to put you on the spot. How do you, what happens to terminology like MQL, SQL, SAL in this model?
Because I think people can, I think pretty self-explanatory, you're doing a good job explaining the power of this, but it's on a different stage of what we normally measure marketing as a different set of terminology and what happens to the old terminology. So when you're going to change how you're reporting at like a business level and go to market level, one, like that is a not an easy task. So I think there's kind of a phased approach to this, to be honest with you. I think of MQL and SAL and SQL as that is like the lead flow.
That's how we trigger people to do certain actions in the CRM. And that's how they know what to do when, right? This framework is layered on top of that. That says, how is the business actually reporting and how is the business doing that shows all attribution sources, not just what you can track in your CRM.
So it's like a simplified version of that. I think over time, and we work on this with our customers, is over time there is no MQL report. There's a pipe conversion report because that's the main metric that we were focused on at the top of the pipeline, right? So from your team reporting, your metrics, this becomes the main source of truth and the main source of how everything is working.
Of course, there's going to be as marketers, there's a lot of other metrics, channel metrics, sub metrics, you can still look at all of that data and make decisions on it. But we know that there's flaws with some of that data from a macro perspective when you're making decisions on channel level attribution, for example. So that's kind of how we phase people into it. And then over time, this is literally what a few of our customers use to report on how everything is going.
How is this, what is our cost per hero? That's what we should be caring about, not what's our cost per lead, for example. Yeah, what's interesting and maybe to share some thoughts about how our customers have made this, this shift, and that is we're talking to largely a bunch of marketing leaders. And this is a, for lack of their work, business metrics system, meaning you're really trying to change how sales, the CEO, the executive committee, the board looks at the performance of your company, and it's kind of coming from the marketer.
So how do you have that conversation within a company or how have our customers had that conversation? Yeah, I think it starts with mindset first, right? When you're changing your go-to-market strategy, you got to make sure your go-to-market leaders are have a similar mindset, or at least generally understand, maybe not as deep as you do as a marketer, marketing leader, but generally understand, okay, we're going to be shifting and going into more creating demand, and we're shifting our strategy to actually drive the business and demand. In order to do that, we need a new measurement model.
And this is the measurement model that we recommend. We found to work really well. And so there, we can also, you can get this data backdated too, so you can have historical data on some of these stages in your CRM, you might need some help with that, but we can. And so the business now becomes, what are our main KPIs that we're gold off of, that we are tracking, and that's where this model comes in, and I think truly gets adopted, is what is the CMO accountable to?
What is the VP of Sales really wanting, or CRO? We want more hero pipeline generated, hopefully from pipe, but honestly, from whatever source we can get it, we want more hero pipeline, because it's going to drive the revenue growth. So it takes a lot of the top of funnel metrics that a lot of people give in the leads, their own channels and leads out of it, and aligns perfectly aligns everybody to be driving towards the same goal. So that's one of the big benefits of this type of model is that really perfectly aligns sales and marketing.
Good question here. I'm going back through the chat, so keep on coming, folks. It's a good point from John. The hero definition is kind of an outcome-based attribute.
You have data, you can look at six-month trailing win rates, you can factor that into the stage, et cetera. What do you advise folks to look at for incoming attributes or leading indicators into that from a qualification perspective? How do you continually rethink PQM as it flows to hero and so forth and so on? That's what's happening in the market.
Obviously, you can look at the converse rates between those stages, but we also look at what's our pipe conversion to win? What is our PQM to win? Because those can be some leading indicators of total, but what is our pipe conversion to meeting booked ratio? Right?
And when you first start off shifting your strategy, I would say that's the first 90 to 120 days, whatever that time period is depending on your sales cycle, before you can expect a C pipeline come in. Center around how many meetings PQMs should be your main metric that you're trying to drive as a leading indicator before it actually hits pipeline? Okay. I'll add right to that.
We ran a similar model at my last company. And to your point, Sydney, we would look at PQMs coming in and then we would look at how did those flow stage to stage, how did they convert? And then we'd go back and redefine the PQM number and tighten that up as we went, because what you're looking at is the efficiency of the sales team and so forth and so on. And so I think you're kind of using this data all the time to iterate on definition process qualifications and so forth and so on, as you said.
Any thoughts on how this leads to standardization of sales processes across individual reps or teams? And so this kind of this classic dilemma that we all face in that we'll have a set of qualification criteria and have a sales process, but every team and every individual kind of runs it somewhat differently. Maybe it's too early to tell us how the standardization changes definitions of stages and criteria in and out of a stage as we move forward to kind of more standardize what sales is doing or is that just too far out there? I think your win rates and things can change based on what sales is doing, what initiatives they're doing, how they're working and how they're closing as a sales team too.
And as a sales leader, if you're going to update your sales process and update some stages, that might affect some stage win rates. So I think we're going to learn that a little bit more as we work with this framework on more customers, but we have one customer who their sales org has matured. Their sales org is getting better. Why?
Why do I know that? At the bottom of the funnel, lower level stages are increasing year-to-year, quarter-to-over quarter. Also, of course, we were saying it's a testament to the lead quality, which is true. We're driving good demand, but we still have a close-up for a higher ACV deal.
So that's one instance where for that customer, it was their stage three was the stage that it would convert at X amount, and that was above the 25%. And then their sales standardization and their sales maturity up a little bit, and then we're seeing stage two is actually converting and becoming their hero. So I think that's a testament to the go-to-market function working and working together. One question we had a while ago, I'm going to take it back to the beginning, and that is we defined this concept of pipeline source, which drives this something to talk about quite a bit.
What is the relationship between pipeline source and this kind of channel? This came off of LinkedIn or came off of TikTok or came through a different channel. How do we think about the relationship and differences between channel and source? I think at a source level, that's what you really understand what's going on with this go-to-market function.
So, at a channel level, I would advise that you look at your standard attribution, which is your capture demand attribution, and then your, hopefully you have self-reported attribution, that's talking to your creative demands. What's going on there? So it's a little bit of a hybrid model, but it is definitely something that we look at. Where are we seeing growth?
We look at both because we know they work together in a hybrid fashion. But same thing, we're going to underneath that pipeline source, you can slice and dice the data in a bunch of different ways depending on what you're trying to look at. Are we looking at, okay, certain segments are growing faster than other? Are we hitting our goal for certain gos?
This is just kind of the global look at that. Are we hitting certain goals for marketing investments or not? But I would advise you not to get to in the weeds at the channel level, just because we know a lot of the issues with software attribution is only incentivized to look at capture demand channels. So, if you're actively investing in a create demand strategy, it's going to look like direct and organic and Google search are going up.
And your LinkedIn and your Facebook and your podcast is probably not even a channel in your room. But all of that is not going to get the credit it serves. So we look at it blended as well. But again, you can slice and dice it segment, mid-market enterprise versus SOB versus geo.
That's where you can slice and dice the data to understand what's going on, but at a high level to answer business questions. Are we hitting our goals? Are we doing the right things from an investment perspective? You should be looking at that blended from a go to market approach.
We have a few minutes left. So if anyone has any last minute questions, toss them in the chat. I will ask one that has come up. And that is, it's obviously early days and part of why we're doing this is so we can help bench mark across our customers in the industry conversion rates through this framework.
Any rules of them, what you've seen early on in terms of pipe conversion to PQM, PQM to hero, obviously from hero onwards, we have a standard, anything up funnel that we've kind of seen as far as what people should strive for if they go and implement this. Yeah, what we've seen so far in our data, and again, we're always trying to get more data, but what we've seen from our customers is from a pipe conversion, it's going to convert to revenue around six to 10% usually. So pipe conversion to close one. That's typically a range.
Obviously we've got outliers a little bit on each side. And then a PQM, so meeting booked, that can convert normally around eight to 15%, depending on the industry and sales process and all that. And that's why again, we centered around that 25%, a one in four, predictable. We feel good about forecasting around that.
Now if you're underneath that, the conversion rates between stages is where it gets a little different, I think depending on the stage of company that you are at. If you're a series B versus that has a more junior sales org versus a series DE, who knows that is kind of a well-oiled machine, those conversion rates between stages will look a lot different. And that's something that we hope to have more data on and actually be like publishing frequently for the market. I can attest that those conversion rates are what we see as well as we run this model on our own pipeline.
I had a question here. Good. They're coming in. I know so many.
We'll try to also make sure we produce content or have follow up episodes to get to all your questions. We know this is kind of a big topic. Yeah, this is a good one. What I think I'm hearing is that the attributes you might use to identify hero opportunities as a mix of standard attribution, so demand capture, account attributes, behavioral attributes, and tech-based attributes.
Do I have this right? So how are we thinking about the hero opportunity, the qualification, it's got a little bit of everything. You want to elaborate on that? Yeah.
I mean, when I'm looking at customer data and we're making recommendations, I'm looking at is our total hero, pipe heroes, and pipe the actual number, like the number of heroes, and then the pipeline associated with that. How are we trending? And then after I answer that question, then I'm digging into, okay, is there anything that I can correlate to why this is going on? Why it's going up, why it's going down, why we're ahead of goal, why we're short of goal, what should we be doing more of, what should we be doing less of?
And that's when I start digging into, all right, let's look at campaign level data. Let's look at software attribution and create demand attribution, see if there's any insights there that we can put our foot on the gas if we see something working, or maybe something that we are investing in and we're not seeing it come through in self-attribution, self-report also, I think a lot of people have segments and geo goals and that's where you can really get into that as well. So that's kind of how we understand if our mix and our marketing mix is working with the customers. Yeah, we're going through this now, I mean, just to give a real example, we have a hero conversion rate increasing in our company, but PQM to hero decreasing.
And so we're looking at that, is that a stricter qualification on our side, is that a difference in the type of customer coming in with the quality of the inbound, etc, etc. So it's nice to have the standardization because you can look back in time, you can look at what you've done in the sales process, you can look at the mix of people coming in and try to assess like what has been changing in your pipeline across the standard approach to the metrics. So super powerful from somebody who uses a day in and day out. One last question for you, Sydney, just because I can't, I got to put you on the spot one more time.
Here we go. How do you think this plays out as you think through PLG versus sales lead? I know it's something that you've been thinking about, John's been asking us a few times in the chat, so I want to kind of bring it up and have you kind of weigh in on like, where do you think this might end up as you move forward with the framework? Yeah, we are actively exploring this.
So if anyone wants to chat one to one, you know, DM me or if you have any questions, feel free to reach out. We're actively trying to solve this because we know it's the issue in the market. How I think about it currently is if you have a freemium product, you know, a PLG model, that's essentially like a subscription funnel. It could be a touchless funnel that you can drive revenue on, right?
So that's one go to market or one subscription revenue portion. You want to drive people in there, you want them to subscribe, but also the people in there in your free trial or free product or freemium. There's so many different types of trials these days or PLG subsets. If they're in there and they want to speak to someone about purchasing your product or getting more information about purchasing or upgrading your product, that to me is a declared intent.
I'm, hey, I'm in your trial or I'm in your product and I want to talk about X and a lot of people have conversion points in there. Then I would say that's a declared intent and we can look at that funnel in combination. Those are like my early thoughts. We're still literally in like brainstorms and I've been meeting with a lot of people who run both or who won one versus the other just to get a lot of market research.
That's essentially how I'm thinking about it. I think the current way of like having a growth team that only looks at driving product led growth signups and product led growth activations and another team that's focused on sales led doesn't work. So we have to adopt our funnels to make sure that we can capture both wishes, something that we don't have solved yet. Excellent.
Good question, John. Thanks, Sydney. All right, everyone. One parting shot or call to action all of you is we'd love you to go away and think about how would you actually implement this within your company?
What are the obstacles? What are the challenges? What should we be aware of that we can make this process as it continues to evolve easier and better, more complete PLGs, a great example. So we'd love to hear from you.
You can reach out to myself or Sydney at any time with any thoughts, challenges, more questions, keep them coming. We appreciate all of you on this call today and thanks for taking the time to listen to us and thank you, Sydney, for walking us through this. I really appreciate it. Thank you guys so much.
Have fun at chat. Have a good day, everyone.