Salesloft on Salesloft: Identify Metrics that Matter

Okay. So I'm I'm happy to get things started. Thanks everybody for joining.

Today, we're gonna identify metrics that matter, and I'm joined by Chris and Tim.

Learning objectives for today are, prioritizing key metrics used to measure team performance, regularly measure performance at scale, demonstrate alignment with your revenue organization with cross functional partners, and, lastly, we want you to be able to confidently document and deliver those metrics to leadership.

So, I'm gonna pause here and, let the team introduce themselves.

But just to kick things off, my name is Kayla Pepperell, and I am joining you today from BOL Agency along with my colleague, Tim, and I'm the director of partner enablement and implementation at BOL.

Can maybe you Thanks for that, Kayla.

And, like Kayla said, I'm Tim. I'm the senior director of growth at BOL Agency, so really focusing on all things rev ops and, helping our clients with strategy as well. Now I'll kick it over to Chris.

Thanks, Tim. And I'm Chris Dankowski. I'm a strategist here. So that's consulting role where I work with our, our larger accounts, and I help them align their high level business objectives, initiatives, and sales methodology to our platform to better support them in driving those those outcomes that they're looking for.

Okay.

And, just to keep moving things forward, in the very top right, I believe, you should have a little question mark that you can click, where you can add in questions.

We'll try to answer those throughout. If we don't get to all of your questions, before the end of the session, we'll definitely be answering them, after the session later today.

So just to to give you some context, so, as I mentioned, Tim and I are both joining today from BOL agency.

And to give you a little background on on who BOL is, we like to refer to ourselves as the b two b growth experts.

We are a digital marketing agency.

We specialize in driving b two b success through innovation, data driven strategies, that really focus on targeted lead generation.

Our services range from ABM strategy to demand gen to SEO, orchestration, and analytics.

And we like to define our approach as really, strategy minded, brand obsessed, and results driven, which is kind of why we're all here today.

For our engagements, personally, we really like to make sure that we're setting, you know, clear expectations and goals upfront to create value for both, our customers and for BOL. And we see a lot of value, in aligning on what success looks like and how to quantify that success upfront.

So on that note, I'm gonna pass it over to Tim to talk a little bit about some key metrics.

Alright. Thanks, Kayla. So, you know, Kayla went over the overview for the topics that we're gonna dig into today, and I really want to kick off this conversation about key metrics with, a way of looking at your metrics that I think of as being sort of what what I like to call deterministic versus correlative.

So I just wanna define those because we're gonna use those throughout this conversation. But for starters, I I call deterministic metrics metrics that are sort of absolute.

Things that are just easily definable.

Level one metrics is sort of another way of phrasing this. Things that are quick and easy to gauge. They're helpful. But when we look at finding deeper meaning within our metrics and using that to actually drive growth within our metrics and using that to actually drive growth within our organization, these things are sort of like, the the leading indicators more than those gold nuggets that are gonna really help you, accelerate what you're trying to do.

So, on the marketing side of the fence, it's sort of similar to this idea of last click where if somebody converts and the channel that they last came from was a certain paid campaign, sure. That's gonna get the credit in last click attribution. But in reality, there's a lot of other touch points and things that contribute to that. So sort of that surface level measurement, again, still important, but, we also wanna look at the other side here, which I call correlative.

This is where a lot of the fun stuff lives when it comes to metrics.

And these are things that have a less obvious or at least a less easily measurable impact on goal attainment. But if you're able to pull these out, there's a lot of magic that can happen from understanding what correlates with your best outcomes and simply doing more of that as much as you can.

So, you know, those relationships take time to pull out, but they're worth it. They're worth the time. And that's what I really wanna talk to you guys about today is how to find some of those things, give you some examples of correlative metrics. Here's just a quick one.

You know, let's say that, pushing an upsell on a given quarter succeeds in raising your average contract value, but it actually results in a ten percent lower close rate across all your opportunities. You do the math. You actually net out worse than if you hadn't done that at all. So it's correlative metrics are really about understanding that activities don't happen in a vacuum, and we wanna be very sensitive to an understanding of what things impact, other metrics downstream, other outcomes downstream.

Alright. And so I wanna really highlight four metrics. Of course, there's things that we could many, many things we could talk about, but I wanted to keep it pretty simple to four.

I'm gonna give you one marketing one, and then I promise the other three are sales metrics. But hear me out on this first one, touch points. Okay? Specifically, marketing touch points. And so, you know, as sales professionals, you would certainly know that marketing softens up your target accounts that are coming in to talk to you. And the better job that marketing does upfront to support those accounts with what they need to be informed and educated and, you know, primed to have those conversations, the better your outcomes are gonna be. So, really, this is, like, the oldest cliche in the book, but it's it's so true, and I see this across all the clients I work with.

Client teams at our agency, we find that when their teams have aligned marketing and sales organizations, the best results come from that. And so these marketing touch points are really the first step in terms of that alignment and understanding how what marketing is doing is making a salesperson's job easier or where it could be even easier in the future. So a good benchmark for this is just there's this classic Forrester study, that came out a couple of years ago where they found that it requires twenty seven touch points, branded touch points on average, to generate a true marketing qualified lead. So whether that's ad impressions, whether that's page reads from SEO, you really have to start racking those up in order to get a a really good qualified lead to come your way that, hopefully, you can convert to SQL and opportunity.

So a great correlative metric opportunity here is, on the sales side, are you really understanding, number one, how many touch points on average your leads have been accumulating before they land on your desk?

And, also, doing a little bit of a thought experiment in terms of how would some additional touch points potentially soften up those leads for you even further or maybe the inverse too. Maybe there's ways for marketing to save a few bucks here and there because we actually dig into it and find that, you know, the folks are getting way more than twenty seven touch points, and they're already soft. Like, there's no more softening to do there. Right? So you wanna be aware of this dynamic and feel like, marketing and sales are teammates here so that we're we've dialed in the right amount of touches before, that first sales interaction.

So when we think about the account journey, you're gonna hear us talk, quite a bit about this, really understanding the buyer journey, the buying group journey, all the way from awareness to closed won. What we're talking about with these touch points is really that very, very first column there. And in that crucial awareness phase, not only the raw number of touch points that are being accumulated, but what is the nature of those touch points? Is it messaging in the right way to where you can spend less time on sales conversations, asking, you know, follow-up question after follow-up question for an angle that might kinda be implied by the nature of the touch points they're consuming? So, for example, there's a specific use case for your product or services, and you can see that an account has been all over those pages. And exclusively those pages gives you a big shortcut for what to, you know, dig into in your conversations. I'm gonna talk more about that as well in a sec.

Yeah. And, you know, marketing and sales alignment, it's kinda like making out in junior high. You know? Like, everyone's talking about it, but no one's really doing it. And, a big reason that's not happening is because if you go into an organization and you ask them, you know, you ask the head of sales, you ask the head of of, marketing, you know, what metrics do you do you share with marketing? Do you share with sales?

They're drawing a blank. There's nothing there. They don't have any kind of diagram like this. And so just as Tim was talking about, you know, correlative, or, you know, lagging indicators, you hear it you're referred to sometimes.

You know, when you're looking at sales outcomes, like we mentioned, a lot of those correlative, metrics and touch points, they're happening further down, further up in the marketing funnel. So, you know, the entire customer journey, if you were looking to do something tactically to align marketing and sales better, you would you would map out the entire customer journey from from the time when they're, like, a stranger. They've never even heard about you until the time when they're actually renewing, and they're so happy that they're referring people. And then within each of those different lanes, like in the, in the example we have here, just pick out, like, one, two, or three metrics that are gonna tell you, at least directionally how well you're performing during that stage of the buyer's journey.

So like Tim was saying with the twenty seven touch points and you look in, you know, the purple columns here, website visit visits, impressions, engaged, you know, with the chat, lead capture rate, those types of things, Those are all gonna feed into, how many people a rep is actually touching. So you figure, you know, what's gonna generate a closed one deal. The rep actually has to reach out to someone, then they have to actually establish two way communication with them, so you're going to be looking at things like reply rate and connected call rate. They have to generate a meeting, so you're going to look at meeting booked rates, meeting held rates, meeting to opportunity rates, and then once they're in your sales funnel, you could start to look at some correlated things like, you know, number of stakeholders on each opportunity and how that affects pipeline velocity and time to close and average sales price and things like last touch or how many touches were made on each opportunity during each stage and how that, you know, speeds up the the sales cycle and adds more pipeline velocity and also increases, average sales price.

So this on the screen here, this is just like a directional example, but it's best practice really again to map out that buyer's journey from all the way from marketing all the way through sales and renewals. Look at each of those different stages, pick out a couple metrics that are really gonna tell you how you're performing in those stages, and if you're supporting the next stage and moving that that buyer to the next stage in their journey.

Tim, I'll hand it back over to you.

Awesome.

And, you know, you just mentioned velocity. We're gonna talk a bunch about this, but a lot to say here. You know? It's a classic sales KPI.

In fact, the next three key metrics are all gonna be the classics. Nothing earth shattering there, but it's really about looking at these in a different way. So it's sort of a misconception, I find, that just more speed is better. You know, know, pump velocity at all costs.

Yes. Of course. We wanna find ways to make the entire deal cycle be as efficient as possible. And the faster they close, the more you can dedicate your your focus to new revenue generating activities.

But understand that, you know, more speed isn't always better here. And what you really wanna be doing is looking for ways to find the things that are improving healthy velocity, but also making sure that you're not just, you know, turbo boosting opportunities out of your pipeline because you move too fast. And so there's definitely a scenario where you could be losing winnable deals on speed. So a great example here, company x tells all the reps, hey.

We gotta really focus down on velocity this quarter. These deals are just moving too slow. We need to, you know, bring revenue across the finish line to meet our goals. So the entire sales team gets cracking, moves as fast as they can, and, boom, they succeed fastest quarter ever for Velocity, but they underperformed on actual closed won revenue.

So the reality here is that and and I'm speaking from real world data driven experience here with our clients, and we've seen this over and over again.

A lot of times, especially if you have a more complex or longer deal cycle on average, I'm thinking, like, plus ninety days, These accounts need support to stay in market. They simply can't make some of these decisions that quickly. And to Chris's point, depending on the nature of your buying groups, if you have a larger buying group, understand that there's multiple stakeholders that all need to come to different, determinations about whether what you're offering is a good fit for them. So the way that we like to think about velocity, at least at BOL, is in terms of a band, there's like a sweet spot, in terms of the optimal number of days that a deal should take.

And, yes, you might be able to inch the front end of that band a little bit further towards the zero end of the the spectrum, right, to try and move things faster. But do understand that these accounts need support. They need to continue their self guided research. All of the latest Gartner and Forrester data suggests that buyers, especially younger buyers these days, prefer to do self guided research for the majority of their buying experience.

Right? It's this term that's bandied about buyer enablement. Right? We wanna make the smoothest possible experience for a buyer, make it as easy as possible for them to close, and part of that is understanding realistically what that velocity band looks like for you and really aiming to keep deals within that band.

Okay. And so the next one, another classic is average contract value. And so knowing that, of course, pure volume, not the only path to victory. If we make the average deal size larger, that, of course, cuts down on the total number of deals that need to be closed.

And, of course, we all want to close larger deals in general. But we really wanna take a closer look at average contract value at scale to look at this from both a deterministic standpoint as well as that correlative standpoint. So I think of this as a band as well where, you know, you really have to look at your company's data to understand what that ideal band is. So it stands to reason most of the time that if you push a lot of upsell during the initial sales process, sure, you may succeed in pumping up average contract value.

But what is that doing to two things in particular? Your closed won percentage, because it also stands to reason that, you know, the the more you pump up the sticker price, the more price objections you may get, but also just in terms of the lifetime value of that client. Right? So you may find, which we have seen for some of our clients, that when the initial deal size is more reasonable, those clients tend to churn less.

They tend to be much more receptive to upsell and cross sell, and you might squeeze more dollars out of that account over the lifetime of that account in general. That may or may not be true for your organization, and it's really important for you to understand for your company what that looks like and really look at this to know, hey. It does make sense for us to try and pump ACV upfront, or, hey. Actually, we we win more in the long term if we don't do that.

So you wanna think about several hypotheses here. Number one, the general sort of consensus is that, okay, a smaller deal probably should theoretically require less effort. It should have a faster velocity because it's just less of the commitment and investment from the prospect.

And because it's a smaller deal, theoretically, the sales team might not need to work that one with the same level of intensity, let's say, or or depth of a larger deal.

Has that been true historically for your organization?

You definitely wanna be looking at things like that. Are the hours invested equally on a hundred k deal and a two hundred k deal? And if so, does that make sense for your organization? Maybe, maybe not.

Definitely worth looking at. Also, understand the closed won percentage across deal size cohorts. So to what I was mentioning earlier, very helpful to understand, hey. Actually, yeah, it's true based on our data that when we do try to push more dollars into the initial contract, we close a significantly smaller percentage.

And what does that mean in terms of our sales strategy overall? So you really wanna understand close one rate, again, correlatively, not just in a vacuum, but against buckets of deal sizes.

And to that point, you also wanna understand in terms of forecasting, knowing if the sales team invested time in fewer but larger deals, what would that do from a projection standpoint versus the opposite, a pure volume play versus a mix? Right? And to that point is that last bullet point, thinking about do you have the right pipeline composition, a mix of those deal sizes, taking into account these considerations of velocity of close won rate, all those things so that when you forecast that out, you're gonna meet your goals in a realistic and sustainable way.

So a lot to unpack there with ACB.

And so the last key metric to talk about before we jump into the next bit is, of course, close rate.

And another another classic here, but super important and super important to look at in correlative relation to the other ones that we've talked about. So this is a simple, really helpful exercise that you might be doing already, and if you're not, definitely strongly recommend this, and that's to model out what different close rate scenarios can look like for your company and doing that across average contract value buckets.

And what this does is it really helps a sales team set expectations throughout an organization and also just sort of sanity check what's coming through, onto your plate currently and whether that's realistic towards achieving your goals. So what we're looking at here is, you know, if a company has an annual goal of one point five million in new business and, you know, you have historically a seventeen percent close rate, you can see really the SQLs required for you to work based on the different average contract values.

And so what you really wanna do is look at your historic close rate to understand what you're tracking towards currently, but also modeling slightly above that, maybe aspirationally a good bit above that, and also maybe a little bit underneath that, to see sort of like a worst case scenario. And, again, this is all about transparency.

It's all about showing your due diligence to really look at, okay. I'm really only getting three really good SQLs per month, but I've been given a goal of x.

And based on our historical close rate, this is really realistically what we're tracking towards. What do we need to do in order to either get more SQLs or improve close rate, or do we need to push more upsell, to bump up that ACV?

So really helpful exercise just to set expectations, maintain that transparency, and share organizationally so it doesn't, you know, feel in other areas of the business like the sales team is just in a vacuum, but that you're really in this together, and everyone can see what you're tracking towards and in different scenarios as well.

Cool. So those are our key metrics. Now we wanna talk about just measuring these things at scale and some of these considerations. So the most helpful way to think about this, I think, is in these three main buckets here, deterministic and correlative, which we talked about, as well as forecasting. So starting with deterministic, some of the things that you're likely already looking at and that SalesLoft can help you with, individual sales rep performance, knowing, you know, where folks are on the leaderboard, so to speak, the output of, sales team members just from an outbound standpoint or a deal working standpoint.

Also, looking at your existing average contract value, close won rate, and velocity. I'm sure, most of you are are currently looking at that already. Your total SQLs, which I was just talking about. Also MQL to SQL ratio, another key area that what I see with my clients, to Chris's point earlier that he was talking about, this is just a huge low hanging fruit opportunity for people to level up their rev revenue organizations, right, is if you're getting a lot of junky MQLs that you're having to reject on the sales team, you don't wanna just live with that reality as, sort of the the situation that you find yourself in.

You wanna find ways to work together to improve that because sales team's life is simply going to be easier if marketing can fine tune what they're doing. And to that matrix we're just looking at a second ago, if you know that you need x SQLs per month in order to hit your targets, based on a close rate assumption, you can potentially work with marketing to improve the quality of the leads coming through so that you can bump up that total number that you're getting, make it much more likely that you're gonna hit those those targets that you've set.

And then also couple more deterministic metrics, just looking at things like open rate from your outbound email communication and, of course, pipeline revenue. I'm sure you're all looking very closely at that. But then going a a layer deeper into the correlative side. So I've spoken to a couple of these already, but, certainly, average contract value on deals, based on market segment. So understanding how enterprise deals move through your pipeline and the types of deals, the size of deals that they tend to bite on versus, you know, mid market or SMB depending on what you sell into.

Definitely understanding things like velocity on deals when the sales team has access to what I'm calling enriched ABM sales enablement. So another kind of fancy buzzword that, a lot of folks think that they're doing but can definitely be improved, if your organization is an ABM focused organization and you are really doing account based marketing, it's not really true account based marketing if the sales team isn't sharing in the incredibly valuable intel that is a natural result of ABM motions. And by that, I mean things like knowing key accounts. If you've got a whale account that's like a dream target account for the sales team to close, you really wanna have marketing share with you the data that they've pulled on what that account cares about.

How many people are in the buying group? What titles are the stakeholders? What content are they consuming on the website? I mean, how much easier is a salesperson's job if you know let's say you sell a product that has, you know, five different use cases and your dream account is just all over one of those use cases.

You can see them poking around that page on your site every day.

That's a huge, huge, card for you to play as a salesperson because you know what they care about the most. You can really emphasize that, focus on that. And if that intel isn't being shared with you, you definitely want to knock on some doors and do what you can to keep that flow of information coming in a repeatable, scalable way, so that you can really take your best shot at having the best close rate possible.

And, certainly, one of the main areas that we see that intel sharing level up is velocity because the more you're tuned in to what a given account cares about in relation to what you're selling, the faster that that deal process should go because you're able to emphasize the right things from the start and speak to what those buyers actually care about the most.

Some other correlative gems here to really focus on, things like closed one rate based on the number of presales or essentially marketing touches, and so that hearkens back to that Forrester stat earlier, the twenty seven touch points to to get that really warmed up lead for you. You wanna take a look at that occasionally and see well, it turns out that, you know, if an account has fifteen touches before they land on sales' plate, We're closing those at a a clip of ten percent, but when they have forty touches, we're closing them at, like, thirty percent. That's a huge, huge piece of information. And in order for the sales team to hit their goals and just crush it, it might be a larger revenue organization conversation between marketing and sales and all those stakeholders to do what you can to pump up those presales touches so that these leads are warmer for you. By the time you're having that sales interaction, you're simply gonna close more of them.

And, you know, thinking along those lines as well is, like, total sales touches and what that does to velocity and closed one rate. Again, as I mentioned earlier, a lot of the most recent research shows that buyers, particularly younger buyers, like to do a lot of self guided googling around, poking around online to find out what they can before they have that sales interaction.

So, you know, if sales is jumping on an opportunity a little too quickly when the ABM intel suggests that, folks are still accumulating those touches, that could potentially harm your closed won rate and also potentially velocity, might just drag things out longer because they're still evaluating, the use case or whether it's a good fit for them and all those things. So you really wanna look at that and see what the total number of sales touches does to a couple of those other key metrics.

And then, last one there, and, of course, there's many, many of these, but these are some of the the top ones, I think, is close won rate on deals and segmented by the size of the buying group. And this can give you super valuable information about, are you speaking to all the needs, all the pain of your buying group? Now some companies, their buying group is quite small, and you might have that pretty dialed in. Other companies, it's fairly large, and, you know, I know Sixense talks a lot about this in their research.

They find, especially for larger deals, larger organizations, the buying group keeps swelling. It keeps getting larger and larger, and so it's easier and easier as you hit the top end of those types of deals and companies to miss messaging to a key stakeholder, in that buying group. And, you know, classic one here is if you're familiar with the, the MEDDPIC style of selling, you know, the e in MEDDPIC stands for economic buyer. And, what we sometimes see a lot is folks get the the functional leads onboard with what they're selling.

And then at the very end of the deal process, turns out, you know, there's an economic buyer hidden, that's waiting in the wings to shoot things down because they have an objection that just wasn't sufficiently addressed during the sales process. And so, you know, looking at that closed one rate across the across deals based on the size of the buying group, very valuable for you to understand. If you have a super high closed won rate against a smaller buying group, that might just be due to the size of the deal, the ACV, things like that. But it could also be because you've got all the messaging covered for those stakeholders, but when it's a larger buying group, there's personas x, y, and z that you haven't accounted for.

You're missing messaging, and they're just rapid firing objections internally that end up killing your deal. So very valuable thing to look at.

Last column here is just forecasting metrics. Of course, as a sales org, super important to be doing this. And so thinking back to that matrix that we were looking at a second ago, really looking at what you can expect from a pipeline to revenue perspective broken down by close won rate scenarios, by ACB, scenarios, and really looking at that from a conservative standpoint, a likely standpoint, and a best case standpoint.

Also, that MQL to SQL conversion point that we talked about, looking at that quarterly or annually to understand how are we doing it at accepting, a lot of those marketing leads coming through. And if there's a big discrepancy there, if there's a problem there, doing something about it so that you're not, you know, starving with just crumbs of the SQLs that you actually get to work. You want to make sure you're having that dialogue in a way that sets you up for success, and you're actually getting more SQLs over time.

Performance by territory, pretty straightforward. And then, of course, a b testing or a b c testing approaches. So things like I was talking about earlier, thought experiments around, hey. What if we really focus down on one of these correlative outcomes that we see, like an ACB scenario where, you know, we actually think based on forecasting and modeling that we really could work fewer but larger deals, and it should put us over what we would do revenue wise if we didn't do that, testing that out with a cohort of deals to see if that actually holds true in the real world and then modeling from there.

Alright. So talking about some cross functional revenue alignment. And as you can probably tell by now, this is one of my favorite soapboxes, and this is this idea of account intelligence. And so already spoke to this a little bit, but, you know, it's this idea of sharing business intelligence between marketing and sales.

If you can master this admittedly, very often overlooked or underutilized, area of opportunity, you will be ahead of the game. You will be a top performer for sure because knowing what these accounts are doing, having that intel simply is going to improve at a minimum velocity and close one rate, if not average contract value as well. So if you are part of an ABM organization who has a tool like a sixth sense or any sort of de anonymization tool, anything like that, you have a massive advantage here, and that's going to allow you to understand what your prospects are most interested in. You

can get a head start on some of their most likely objections. Common one here is when we see, buying group members, like, all over the pricing page every day where they're clearly having some sort of internal discussion there.

That can prep you for all sorts of levers that you can pull to nullify that objection.

And, ultimately, by the way, you know, this isn't just beneficial for the sales team. This is beneficial for the buyer. Buyers want a smooth experience. They want to focus on the things they care about.

They want to cut to the chase, and, you know, they wanna have a buying process that feels right and natural and, you know, pain free to them. So this really is that idea of buyer enablement. I kinda see it as a win win here. Sales team gets intel.

The buyer gets a more tailored buying experience. Everybody wins. So some specific things you wanna look at here are themes. What products and services are they checking out on the site?

What angle, or or value prop are they really eating up based on what you can see from their content consumption? So if you have a certain value prop and that's highlighted in your blogs or, certain pages on your site or even a paid campaign that you're running and you're getting good engagement there, again, that's real world data and proof that they care about those things. That helps you tailor what you're going to talk to them about and the way that you frame up your approach to selling them.

Same thing is true for pain points. You know, we all know that buyers buy, if if not primarily, then certainly, quite a bit based on the pain that they're currently experience experiencing and how your offering solves that pain. So if you can back into the exact nature of that pain based on the intel that you're getting, from your ABM efforts, that's huge for you because you can just poke and poke at that pain, in a way, of course, that's helpful that shows that you're focused on helping them solve that pain.

It's gonna be huge for you. That's certainly going to have massive effect on your close won rate. And already mentioned this a moment ago, but likely objections. Getting a head start on that, understanding, are they price sensitive, are they comparison shopping, and really, you know, looking into competitors. Sixense is a great tool for that where you can see if they're researching one of your direct competitors.

Is there, you know, pain alignment in terms of, like, product market fit for what you offer and what their pain is? And it you know, if you need to tweak that a little bit to make it more relevant to them, maybe you can do so. If they're continually looking at case studies, use cases, trying to suss out if this is the right solution for them, you wanna be able to understand that based on their activity.

So really can't stress this enough, this account intelligence. If you can figure out a way to connect these dots between marketing and sales, trust me, both sides are gonna be happy. The whole organization is gonna do better, and the buyer's gonna have a better time too.

Alright. And our last section here is around confidently sharing these insights throughout your organization.

Heard me talk about this a little bit on the matrix slide, and I really think this is quite powerful for sales teams. So let's jump into this one.

So a lot of your ability to actually measure and report on and analyze and evaluate all the things that I've been talking about is sort of predicated on having a pretty solid analytics setup in play. And some of this really does fall a little bit more on the marketing side of the fence traditionally, but I think it's important for sales teams to have access to these analytics to have a a seat at the table when it comes to talking about the analytics investment that your organization is making because the stronger that your analytics setup is, the more confidence you're gonna have in your metrics, the more ways you can look at the data, and the more you're gonna be able to execute on some of the strategies that we talked about.

So at our agency, we use an analytics model that we call closed loop. And the idea there is we really wanna be able to see the entire buying journey for accounts from start to finish, from the very first impression that they ever have of your organization all the way through to that closed won moment, and understand that account level engagement at a very, very granular level across individual buyers within that buying group.

So, you know, we look at this both in aggregate to understand, okay, at an account level, let's look at all the channels that we have in market to see what they're consuming and what they care about and what's pushing folks to actually become an MQL.

And, you know, talking before about MQL to SQL conversion, this is so important to make sure that this is, firing on all cylinders and doing what it needs to do to set a sales team up for success, but it also helps us understand the themes of what these accounts really care about. So, for example, if you have a display campaign, like a Six Senses programmatic campaign running, and that's segmented down into different campaign themes, and there's one theme that's absolutely crushing it, it's important for everyone to know. It's also very important for a member of the sales team to understand what campaign drove that prospect to become an SQL because that sets you up for success with that whole process.

So, really, what we are able to do is look at this in aggregate as well as, specific buyers, as well as within that account, every single last touch, which is kinda you see a little snapshot of that in the green square there, and seeing every single one of those touches, the nature of those touches, when they occurred. And a a very sort of interesting thing that often comes out here and that people forget is that those touches continue to accumulate even after prospects become an MQL, an SQL, an opportunity. I mean, we see deals that are way late stage in the pipeline. They're still consuming things on the website.

They are still engaging with ads. They are still researching things that we can see on the sixth sense.

The journey, you know, the the touch point journey or the the marketing journey, if you will, doesn't just end once they become a deal that's being actively worked. It does continue, and being able to con continue seeing that and strategizing around that, is crucial. Right? So maybe, you know, a a bunch of touches result in a lead being generated. They're accepted as an SQL, and you have one or two of those first sales interactions.

And, you know, you go, man. You know, this this would be a great account for us to have. I think this is a winnable deal, but they're really, really price sensitive. I'm a little worried about that.

And if the account merits it, maybe you go back to marketing and be like, hey. Is there anything we can do on an account level to hit these guys with a a campaign theme around the value versus, you know, the price concerns or, like, a competitive takedown of, you know, how much your offering costs in relation to your competitors. Or, you know, there's a million things that you can do there broken down by potential objection. And if you're able to keep that flywheel of information going back and forth between marketing and sales, marketing can give you the assist even while you're working a deal.

So a lot of the best results that we see include that level of specificity in terms of working these deals and that passing the ball back and forth between marketing and sales. And it's very gratifying when you see these accounts respond well through this engagement data, based on those efforts. So I strongly recommend that. And, of course, as I mentioned at the top of this slide, this is all predicated on having a pretty solid analytics setup in place where you're able to reliably see these things, with one central source of truth for for all teams.

And so zooming out for a sec, just looking at this idea of closed loop analytics, it's really about, you know, you asking yourself the question, do I know what a full account journey looks like from the first moment of discovery all the way through to closed one? Do I know what that looks like historically, and how does our ideal state stack up against the reality of what that journey looks like historically, and where are the opportunities to improve that journey, again, for the benefit of your team, but also for the benefit of the buyer as well. So you really wanna know on an account level, and this is doubly true if you're an organization that sells into fewer but larger deals. It's you really wanna have a a good handle on these things, on a per account basis, starting with discovery and entry points. How did this account become aware of our company? What was the channel that first drove them to the site?

And, you know, does anything about their entry point give us crucial information about their needs, their pain? How many touch points were required to get them in the door.

All very important things for you to have a handle on at that discovery stage moving into research and engagement, which is one of the the beefiest stages in terms of there's just so much gold that you can dig out if you're an ABM organization. If you have a solid analytics setup, this is really more of an art than a science because there's so much data you can pull in terms of what type of content is the account engaging with, at what point in the journey. Do we see them moving down the funnel from a content standpoint in a way that we would expect as they get farther along in the deal process? Are they now, you know, going back after sales conversations and consuming content that makes sense for where we suspect they're at?

What things are they engaged with the mo the most, not from a volume standpoint, but from a time standpoint. Are they really sitting through a fourteen minute long video on this very one this one very specific value prop? It's huge for you to know that.

The content that triggers them to become an MQL, that's often very important. You know, that's all else being equal, there's a lot you can unpack there.

And, of course, if you have, like, a six sense or something like that, understanding, do we have enriched third party intent data to give us extra insight that we can't infer just based on site engagement, that's very valuable as well.

And, of course, how many unique users or presumably members of that buying group are engaged, and are we penetrating that buying group, thoroughly enough throughout the marketing process as well as the sales process?

Then from there, number three, the part you probably have the best handle on at the moment, those sales interactions, I mentioned a second ago, seeing if after a sales interaction, is that prospect returning to the site? Are they moving down funnel as we expect? Are they progressing in their their readiness to close?

And is marketing occasionally or always, depending on the the number of deals you typically work, stepping in to assist with deals that have already made it through into the pipeline and sales is actively working them? It's a a very underutilized spot there. And then finally, deal close. So doing that closed won analysis, doing it regularly, really digging into your analytics, looking at, are there any correlation as correlative metrics?

Can you draw any of those from your best deals to back into, hey. Here were the touch points. Here were the steps. Here was the velocity. Here was the deal size. All of those things.

Here was all the way down to the deterministic stuff, like, you know, how many phone calls it took to get that, that POC on the line. Right? So doing that analysis regularly and trying to find commonalities between your best deals so that you can at least form a hypothesis of what's gonna generate these best outcomes.

So you wanna do that. You wanna do it regularly, but, also, very important to do it by banded cohorts. So whether that's, market segment, whether that's deal size, all of those things very important to segment because there's hidden, hidden opportunities and hidden correlations, within those those banded buckets as well.

And so with that, I believe that brings us to a close. Thanks so much for for joining, and if there's any questions, happy to to jump into that now.

Looks like no no questions in the tool. Give it another sec.

I know, Mimi mentioned in the chat that we will be, sharing the deck, probably closer to the end of week. We'll send out a follow-up just so that everybody has access to that.

And at any point, if you do have questions, after the session, you're more than welcome to respond to that email, and we can definitely, get you some answers there.

Awesome. Thanks for the feedback, Joyce. Happy to hear it.

Cool. Alright.

But I think maybe we can can finish up here if there are no questions. Again, we'll send a a follow-up by end of week. And if any questions arise after the presentation or as you're going through the deck, just let us know. Thanks everybody for for spending some time with us today to go through these things, and, thanks to our presenters as well.

Awesome. Thank you, guys. Have a great week.

Bye.