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Aaron:
We've invited marketing, finance, sales, and general management colleagues today. What you can do with an optimal funnel structure and timely reporting can help hone tactical demand gen spending and strategy, increase your customer acquisition, augment your top line forecasting and diagnose issues. We're super excited to partner today with Aptitude 8, a consulting firm whose expertise lies in implementing and improving demand gen tech stacks, reporting, and performance. They work with clients large and small. So while they have a view on what can be done with a gazillion dollars, they can also help solve the same issues for companies on a smaller scale. The goals for today are to baseline set, one, what are optimal funnel components and why? Two, what does good funnel reporting look like, and how can general managers, sales teams and finance act on the information, diagnose issues and potentially shift tactics?
Aaron:
Three, how can you use the components to help with long and shorter term forecasting? And four, what tech stack do I need? We're happy to have Connor Jeffers from Aptitude 8 to help guide us through these topics today. We're planning on an hour of presentation, followed up by hopefully a lively Q&A. You can ask questions by typing in during the call or raise hand during the Q&A itself. Connor, thanks for coming today, and the audience is yours.
Connor Jeffers:
Awesome. Thanks Aaron. Good to meet everybody. I'm Connor, I run Aptitude 8. As Aaron touched on, we are a RevOps and demand gen consulting firm. We are partners with HubSpot, Salesforce, InsightSquared, Outreach, and tons of different sales and marketing technology tools. And what we really do with the customers that we work with is systems implementations, integrations, helping people build out the tech stack that their business will run on, and primarily focused on both, how can we leverage automation to increase efficiency? As well as, how can you build out the right funnel reporting to make sure that you guys are delivering on the goals that you're looking to pursue and you can continue to optimize those strategies as you go?
Connor Jeffers:
Super excited to be here. And in terms of what we're going to go over today. There's be going to be two main sections. First, we're going to go through, what is a funnel and why is it important? We're going to define those funnel stages, go through demand gen, talk about tracking. We'll go through a bunch of different reports and examples of all of those items as well, we'll get pretty tactical. Talk through the demand gen life cycle and help you guys figure out where in that cycle your company sits today. And then finally gets to what tech stack is right for your team, based on both your size and your business model, and we'll talk through some quick how-to-get-starteds well.
Connor Jeffers:
And as Aaron mentioned, feel free to submit Q&A throughout the session and we'll tackle all of those at the top of the hour. So starting at the baseline here for what's a funnel and why is it important. We want to go through, what are the metrics you should be looking at at each stage of that funnel? What are the terms in those funnels? And what do we want to look at for them? And really get on the same page that when we talk about a funnel, what does that actually mean? Many of you have probably seen this before, but for anyone who hasn't, we'll go through these one by one, because it'll form the baseline for everything we're going to talk about today.
Connor Jeffers:
The first stage for funnels when we're talking about them is going to be our prospects, and this'll fall into two buckets. So one, if you're inbound and you're looking at the MQLs and site-driven traffic, that's going to be traffic on your website, the people that you could potentially capture, but you don't yet have their information. And if you're an outbound-driven organization, these are going to be cold lists of emails, contact information that's in your CRM that you could potentially be going after. We'll want to move those prospects into leads. And so our leads are going to be people that we have a warm pulse, we have information about them. They have engaged with us in some capacity, whether it's a form fill, they've opened an email, they've clicked on an email, they've engaged with us in some way.
Connor Jeffers:
And then we'll want to be moving those leads into everyone's favorite, which is MQLs. And really, the key here for the difference between these two is going to be our leads is anybody who has had some form of engagement. So perhaps that they've registered for a webinar, but they haven't yet attended, and your MQLs are going to be people who are interested in talking to you and interested in engaging with your sales team. So those are going to be book a demo forms, webinar attendees, people that you really want to be getting in touch with. And leads are going to be those top of funnels. So a core function for your marketing team is going to be how can they move all the leads that you have into MQLs so they can serve them up to that sales team.
Connor Jeffers:
Our SQLs or sales qualified leads are going to be MQLs that our sales team has interacted with and engaged with and has confirmed that this is somebody we would actually sell to. It's not an intern, it's not a low level employee, it's somebody who is actually somebody who's interested, it's the right type of company, they are in the market, they do have the right type of company to work with us. And then from there, we'll move those into opportunities, people that are interested in buying, we're working in active sales cycle with them, we're moving them through our entire process. And then down into purchase, which is of course our customers.
Connor Jeffers:
And so what's important here is when we talk about our funnel, we're going to go through each one of these stages, what you should really be tracking and managing at each stage, and how you're going to tie that back into your forecasting, your funnels, and how you look at the business overall. So let's start with what is demand gen, because we're going to talk about that term a lot. So when we talk about demand gen, it's really the data-driven marketing strategy to create awareness and interest in your company's offerings through technology, which is a really verbose way of saying the demand gen team at your organization is really building that funnel. And who's responsible for architecting it, driving people through it and measuring it falls onto demand gen.
Connor Jeffers:
Tons of different things that go into that funnel, you have paid media, any of your inbound marketing efforts, your sales enablement efforts, customer retention, web conversion analytics, all of this ties into the funnel measurement itself. But when we talk about a demand gen team and a demand gen responsibility, it's the group in your organization that's responsible for building, managing and maybe taking that funnel.
Connor Jeffers:
I want to jump into what should you be tracking at each funnel stage for the organization. And the important part of this is that we're really going to make sure all that reporting is done in a cohort. So when we're looking at our reporting, we want to be measuring month by month source by source, really isolating a particular audience, versus just getting pulse metrics as we go. That funnel is always going to be one particular cohort that's moving through the process. And in terms of how we actually do this, we're going to show tons of screenshots and tons of reports throughout this presentation, and all of these come from a variety of different tools, but some of it's going to be geared towards the marketing team and tactical and the demand gen team, but these are all the things that you should be looking at to measure that funnel.
Connor Jeffers:
And there's a couple of core technologies involved in order to make that happen. You're going to have CRM where all of your database and your contacts live, your sales engagement tool, which is how your sales team actually engages with the prospects, your marketing automation platform for all of your marketing side data, billing management, that where we're going to pull all of those ROI and where those customers are, and then a BI tool if you want to layer that on top to really aggregate all of that together. So if you're at the CEO level and you're looking for what's the summary and why do I care? And what should I be looking at? These are the things that we would say are the most important things you should be asking your demand gen team, asking your marketing leaders to bring to you.
Connor Jeffers:
And when you're looking at that weekly one-on-one meeting of evaluating the performance of the demand gen team, this is what we should be looking at. So what's our trending funnel, cohort performance? Is this up or down and why? And we'll go through tactically what this looks like. Our funnel stage conversion changes. So are we seeing people increase percentage conversion from stage to stage? Is that going down? And what's the reason? Our forecast based on that funnel. So we really want to answer, does our sales team have enough leads in order to feed the revenue goals that they're pursuing?
Connor Jeffers:
What was the performance from the last period? So how well did we perform last month? Is that getting better or worse? What's our current period trending? So is your team moving in the right direction? And what's the current period forecast? So are you going to hit your target? Are we going to hit our goals? And so when you look at this information, we're going to go through lots of reporting, a lot of content, a lot of specific examples, but for that CEO summary, this is what you should really be looking at when you talk to your demand gen team and this is what should be getting delivered to you in that regular meeting.
Connor Jeffers:
Let's jump into details on these. So for prospects, again, prospect is somebody engaged with your company, could become a customer, could become somebody that engages your sales team. When you look at your prospect reporting, you are going to want to look at your site traffic. So what's the overall people that are actually visiting your site? What's the on-site conversion rate? How many of those are giving you contact information? Total database size, and as that's growing, how many net new contacts are coming in, and what's the target account list size that you're able to work with? So are you adding more target accounts that you want to be able to sell to as time goes on?
Connor Jeffers:
We'll go into some specific examples. So this guy is going to be, what is the sessions and the traffic on your site? And this is a week-over-week kind of report. So what we want to evaluate is, what traffic sources are driving people to our site? And if you're spending money on SEO, if you're spending money on paid, if you're spending money on partners and webinars and different conferences and content, you should be seeing that reflected here and you should be seeing spikes. And so what you should be able to look at here is evaluate, are the marketing activities that we're engaging in and is the money that we're spending actually getting awareness and interest in the market for what we do?
Connor Jeffers:
And you want to look at that broken out by what source that traffic is coming from. So is it traffic that people are just searching for you? Is it traffic that you're buying? Is it traffic partners are sending your way? And this should be able to inform you whether or not the marketing decisions you're making are driving attention to the business overall. Drilling down into that, you really want to start to look at that conversion rate by each source. So not only what's your aggregate conversion rate. So you might be seeing 2%, 2.5% conversion across all traffic, but you really want to break that out by the source that that traffic is coming from.
Connor Jeffers:
So if you're seeing that your paid social traffic is converting at a much higher rate, that may be you where you want to be putting a lot of your attention and a lot of your spend, as opposed to investing in SEO or organic because you're not getting as much conversion there. And this will help you prioritize different channels and prioritize different sources for where you should be investing for the demands gen team. Similarly here, we want to look at, how many new contacts are we driving in? We want to make sure that the traffic we're getting isn't just noise, and you're not just getting people who come in, view a page or two and then bounce, but really looking at how many new contacts are coming into your CRM and your database from the traffic that you're investing in.
Connor Jeffers:
So this will tell you whether or not those strategies you are doing are reaching people who are interested in what you have to say, as well as telling you whether or not the messaging you have on your site resonates with people from where they're at in that buyer's journey. So if it's somebody who's coming in from remarketing or paid social, it might be somebody who has a little bit more knowledge about you and what you do. Whereas somebody who's coming in from organic may just be looking for a solution to their problem and they're hitting your site and saying, "This isn't something that's going to help me," and then bouncing back out.
Connor Jeffers:
And here we're really aggregating that together. So our stacked bars here are just going to say, what's our sessions, by which source that session's coming from. Our x-axis here is going to be over time. And then that line is going to say, "What's that conversion rate?" So this is a really helpful chart, especially when you're looking that conversion rate over time to tell you, if you did a new site change, perhaps you should moved it from your pricing page, showing your core pricing and switching it to contact our sales team. And this will tell you, is that actually getting more people to engage with you, or is that engagement going down?
Connor Jeffers:
If you change your messaging to, instead of being focused on product-centric messaging, you're now moving to more value-driven messaging, is that actually working? And it'll also help you spot where you're starting to either gain momentum or starting to surface gaps in your overall traffic sources. And so when you're looking at those prospects, you really want to focus on overall site traffic conversion, and then really breaking that out by individual source.
Connor Jeffers:
So jumping into leads, and this is one where there's sometimes a little confusion, we'll rehash it again for leads versus MQLs. But our leads are going to be people that have expressed interest in what you're doing. So it's not necessarily they're ready to talk to the sales team, they're not necessarily somebody who we want to go and book a demo with and pound on their door, but it's somebody who's filled out a form, they've opened an email, they've clicked on something, they've somehow shown us that they have interest in what we are doing, but we haven't yet said that they're somebody that sales absolutely wants to talk to.
Connor Jeffers:
Our lead reports will go through what will be qualified percentage. That's going to be, of the leads that we have, what percentage is actually people we want to talk to? That'll tell us if our marketing efforts are reaching the right folks. Our lead to MQL conversion rates. So how effective are we at getting somebody who has a pulse, has an interest to somebody who actually wants to engage with our sales team? What's our unqualified reasons? So why are the leads that we're saying, this isn't someone we want to talk to, what's the reason that they're unqualified?
Connor Jeffers:
This is something we think is really important to track because it'll help you flag, are we marketing to the wrong audience? Are we spending money on channels that produce people that aren't interested? Are we somehow servicing the wrong type of contacts? And also our unqualified percentage, so inverse of that qualified percentage. But again, you won't necessarily reach all of them, so typically, you're going to see a percentage is disqualified, a percentage is unqualified and a percentage is just unknown, because you never really got in touch with anybody. And ideally, you want to break this out by your sources as well. So you really want to be evaluating this by where these leads are coming from so that you can make decisions about each channel.
Connor Jeffers:
And a caveat here. Some of these are fuzzy. I'll speak to each one. They're pulled from a variety of tools and a variety of orgs. And so I'll speak to them and it'll look different your organization as well. So this guy is telling us in a stacked bar format, what are the total leads that we have coming in? That's the tallest bar. What's the conversion down to those actually being MQLs? And then how many are we converting up into opportunities? And what's really important when you look at this is you want to evaluate this on a cohort basis. So you don't just want to say, "Oh, we got 25 leads last week and we had 50 leads this week. And then here's our MQL number. Here's our opportunity number."
Connor Jeffers:
You really want to make sure you're looking at this as one whole audience so you can evaluate, of the records that we pulled in a month ago, how many of those are moving through? And this is also going to lag based off of the duration of your sales cycle. So keep in mind that if it takes you three months to convert something all the way through, you're going to have to look that far back to get that full funnel. But at each stage you should be getting a little bit more insight.
Connor Jeffers:
So again, this is that breakdown for one cohort. So this is just an example report out of something like Salesforce and we're looking at... So outreach here in our top left is going to be all the leads that came in. Everyone uses different terms when it gets down to the details, but these are all leads that came in. Of those leads, how many of them became a MQLs, and what are we processing back? And then how many of those were we able to convert up and actually have our sales team start engaging methods? So again, the important part here is to look at this conversions from each stage, but then breaking this out as much as you can by different campaigns and different initiatives so you can start to figure out that digital is a really good channel for you, events are very good channel, partnerships are a really good channel.
Connor Jeffers:
The more that you can break these out and isolate these, the more insight you're going to be able to derive and also the more direction that you'll have on which channels are actually yielding results. Similarly here, this will be more on the outbound side. This is pulled from a tool called Outreach, which we really like, but this is looking at all the leads that we're creating and responding to and all the people that we're reaching out to, so all those cold prospects. We have 637 that were created. How many did we get opens, clicks, replies? How many actual reaches are we getting of the leads that we're reaching out to?
Connor Jeffers:
And what percentage of that 637 are we actually getting in touch with? And so this will also help you optimize by the messaging that you're putting into some of your sales sequences, the two different cohorts that you're going after from sales and identifying industries or identifying title levels and comparing performance between each of those so you can start to string together that whole funnel analysis. And similar here, you want to be looking at your cost per lead and how that's trending month over month. So are you getting more bang for your buck this month than you were last?
Connor Jeffers:
But also breaking it out by each individual campaign and asset. So as you start to expand your paid efforts and as you start to expand the types of content that you're surfacing and driving traffic to, you may find that it is significantly less expensive to buy leads that are downloading your pricing guide versus buying leads that are direct book a demo. And so this will help you start to optimize for what types of content and what types of collateral you should be creating, and measuring that month over month. And not only your cost per lead on the actual channel level, so LinkedIn versus Facebook, for instance, but also looking at it on each individual asset and each individual thing that you're driving traffic to so that you're able to really analyze what it is that people are interested in and what's the most expensive attention for you too grab.
Connor Jeffers:
And here we're looking at our leads that were converted up for each first campaign touch. So this is telling us of the channels and of the initiatives that we're engaging in, what percentage of those leads are converting? So not just over a trending of how many leads from January were we able to convert, but also breaking that out by which campaign and which initiative they came through. So if you pair this with some of that cost-per-lead reporting, you can really get down to, how much does it cost me to actually generate an MQL from this particular source or from this particular channel and starting to measure and model that backwards as well.
Connor Jeffers:
Here when we talk about MQL, so our MQLs will be contacts that are sales ready. They're directly somebody that we want sales to reach out to, we want sales to sell to, we want sales to engage with. And when we're looking at our MQLs we want to look at MQLs by month, how we're trending or MQLs by channel, or MQLs is by campaign, these should be the initiatives that we're actually launching. What our response time is, how long does it take sales to get back to those MQLs? And then what's our conversion rate down to sales-qualified leads as well? So here's similarly, just like the traffic report or that new contact report, we want to understand, which channels that we're investing in are generating MQL, and at what level of frequency?
Connor Jeffers:
So if we're spending a ton of money on paid ads and we're seeing that spend go up, we should similarly be seeing a higher number of MQLs, and if we're not, we can either flag that worst case, this isn't a good channel for us, but perhaps our messaging on that channel isn't aligned, we don't have the right landing pages, we're not converting them down the rest of the pipe. But we want to look at this trending because it'll let us spot before we have issues at the tail end of our funnel, where we're decreasing bookings or having issues actually having demos. This should flag it way in advance so that we're seeing if our MQL numbers are trending down and we know our historical conversion rates, we can start to be proactive about solving that issue before it becomes something that impacts our actual bookings.
Connor Jeffers:
Similarly here, not just looking at what is the MQLS here bringing in? But also, how's our conversion trending? So on average, are we actually increasing the quality of MQLs so they're actually becoming SQLs? We're getting higher quality MQLs into our system, or perhaps you're investing in some of your sales messaging. You're investing in sales training, you're bringing on new sales leadership. You should be seeing a higher MQL conversion rate because you're more capable of taking somebody who has an interest in what you're doing and an interest in your business, to somebody that actually is a good qualified fit. We're asking the right questions.
Connor Jeffers:
And also starting to break this out by channel, becomes extremely important as well, which we'll show in some subsequent images here. But really evaluating, what's our conversion rate for those MQLs and how that trending over time so we can start to look at those cohorts and see, are we performing better or worse to where we were? And starting to diagnose that before it affects that bottom part of the funnel. Again, campaign cost reporting. So not just looking at... Everyone says, "Oh, it's the cost per click, it's your cost per lead." You really want to be measuring that cost to every single layer of the funnel and trickling it down. So it may only cost you a certain amount to get... In this example, they have campaign numbers as leads and then leads as MQLs.
Connor Jeffers:
But when we're looking at that cost per individual lead and engagement versus cost to be able to generate that MQL, and then also looking at the cost to generate any opportunities from that, and ideally breaking that out by campaign and by channel. What we really don't want to get towards in any particular cohort is in Q1 of 2020, how much did we pay for MQLs and how much should we pay for MQL by each campaign and each channel? And if we start to break that out by types, we can start to optimize that demand gen investment to the channels that actually are generating conversion later in the pipe.
Connor Jeffers:
And this guy here, a little fuzzy, but in our top left, we have our MQL this month by trends, similar to what we saw before. But what's important here is comparing this to our SQL. So we really want to know, what is that conversion from MQLs to SQLs? And if those lines are not in lock step, we change something that is having either a positive effect or negative effects on our conversion rate. And we want to be looking at those ratios. So your lines are going to be spaced apart, different amounts, depending on the effectiveness of some of the strategies you're engaging in, but you should see them parallel all the time. And if they start to divot in one direction or another, that's a change that you want to drill down into.
Connor Jeffers:
And you also want to look at that conversion. So, of those SQLs you're pulling in, how many of them are you moving back up? And again, looking at this by source, so that bottom chart there as on your Y axis, you have each individual lead source. What are the MQLs that are coming through? And what percentage of MQLs from that source are getting converted up into SQLs that are qualified and our sales team is now working? And so you will both want to know that on a total level trending month by month, but you also want to break that out by source as much as possible so that you can start to figure out which sources drive the highest quality records that your sales team says, "If people find us from Google search and they hit these pages, this is somebody who converts a lot higher." And that may convince you to start investing more in SEO as a strategy versus paid, for instance.
Connor Jeffers:
SQLs. So our SQLs will be people that the sales team has actually talked to, they've said they're qualified, they've said that there's somebody that they want to talk to, they've said they're somebody that they want to reach. And our SQLs, when we're looking at them, we always want that trend line. We also want, what's the percentage that we're converting those up in to opportunities? And what's the time that it takes to get somebody out of SQL and into somebody that's ready to buy?
Connor Jeffers:
So when we're looking at our SQLs, and this is a similar report here where we're looking across three layers. So here, leads is going to be those MQLs coming in, how many net new contacts are we actually adding into the database and saying, these are qualified? And then how many of those are target contacts? So of the MQLs that marketing team is servicing to us, how many of those are actually the target contacts that we want to sell to? And the important piece of this is to really understand, not just how many MQLs is marketing putting up, but how good are those? And this is both going to help you manage marketing both by channel and establish which ones are the correct fit, but also being able to start to optimize against each channel based off of which ones generate the types of people you want to sell to.
Connor Jeffers:
Something we see really common is people will talk about how cheap it is they can drive leads off of Facebook and they can get engagements and LinkedIn's really expensive, but when you look at that cost per SQL on a channel like LinkedIn, you're going to see that be much lower than your cost per SQL from something like Facebook because you're targeting as much better, and the quality of the contacts that you're able to generate are just significantly better than what you're going to get from channels where you can't do it as much targeting.
Connor Jeffers:
Here, we're going to look at that as that breakdown that we talked about before, which is the qualified and unqualified percentages. And so here, we're going to look at our raw MQL numbers. This is one cohort, one group, this is in one month. So sort of saying we have 216 MQLs, of those, 105 are not sales engaged. That's going to be people that are sitting in MQLs, sales hasn't been able to get in touch with them yet, sales hasn't made them in SQL, and it hasn't taken a look. And then our sales engaged are going to be those SQLs. So once the sales has talked to, sales has said, "Yep, this is real. They are a good fit. There's somebody we want to actually move into an opportunity and be pushing through our pipeline."
Connor Jeffers:
And then of those, how many are we moving into opportunities? And then how many are just moving into disqualified? So disqualified here is going to be, we reached them, they're not a good fit, they're the wrong type of company, wrong type of business, they don't have the budget, they're too small. And really the difference for that not sales engaged are the ones that we shouldn't be getting in touch with, and we haven't yet determined whether or not they're SQLs. And you'll see some atrophy here as well. So typically, you'll reach a percentage of the MQLs that come in and a bunch of them will just fall off because you can never get ahold of somebody. And you also want to be tracking that percentage as well.
Connor Jeffers:
So how effective is sales and actually reaching somebody and evaluating this is a good fit, or it's not a good fit versus it's just atrophying in the database. For opportunities and our customers here. So opportunities, qualified prospects, we're actively working them through the sales cycle. And obviously, customers are people who signed up. When we're looking at these metrics, we want to look at opportunities by our campaigns. So we want to look at how many opportunities is each initiative and each marketing plan that we're engaging and generating, what's that opportunities by sources. Source and campaign are different, source is going to be something like paid search, whereas campaign will be, we are promoting this particular ebook through paid search as a channel.
Connor Jeffers:
And so that's what the campaign is going to be the asset or the thing that you're actually engaging in, and how are our win rates by source, by campaign, by rep average days to close our sales stage velocities, how long does it take to get through that sales cycle? And ultimately, what's our campaign are alive, so that each campaign we're investing in has maybe multiple different channels of promotion, single asset, and multiple different leads and opportunities getting generated. How do we evaluate the actual ROI of that investment? Here, we want to look at our opportunities month over month seeing what are coming in, but also seeing what sources they're coming from.
Connor Jeffers:
So as we start to see some of these growth, we might be finding that certain sources are actually creating more opportunities for us, and really looking at this and staying ahead of it on a cohort basis, we'll also help you figure out where to be investing and seeing what's generating real opportunities. So very similar to what we looked at with some of the source data on the MQL level, but you want to pass that over to your opportunities to find out which prospects from which sources are moving further into that sales cycle. Here's where you're really going to want to be looking at your win rate and also how that's trending and really understanding over time, are you closing more deals or are you losing more deals and driving into that cause.
Connor Jeffers:
And this will help you surface some of those issues, whether it's on the sales process or the quality of those leads that are coming through as the demand gen can start to optimize as well so you can see where those are going from. This one, I won't spend too much time on because Aaron's going to expand on quite a bit, but what we want touch on is looking at our bookings trajectory and how we can start to forecast by taking our win rate that we're tracking on a quarterly and a monthly basis, what's our conversion and our stage velocity is how long is it taking for a deal to get closed. And then once that deal is actually moving forward, we can take that average amount and we can start to look at what we're forecasting for our bookings, if we're modeling everything in that whole pipeline.
Connor Jeffers:
I'll let Aaron expand on this quite a bit more later, but to give you a taste of what this could look like in a visual view prior to getting into more of a spreadsheet. Similar thing here, really looking at what we describe as sales math which is saying if we know how many opportunities we're generating, we know what the average deal size is, and we know what the average sales cycle is because we're measuring conversion at each stage. We can start to forecast out what our bookings are going to look, wholesale cycles out. And so if you aggregate that back up to the top end of the pipeline, you can do the same thing and you start to model backwards for what it costs you to generate something at each stage of that funnel, and then really tying that back into your overall forecast.
Connor Jeffers:
This is similar, the difference here is we're looking at this at broken out by where it sits in the overall stages. So are conversion rates going up? Are they going down? Are we getting stuck on any particular stage or any particular event? And so what we may find in a report like this and what we make glean is not only are we encountering issues when we get to the contract signature piece, but our conversion rate there is going down. And so it may make a lot of sense to invest in document automation tools or track things more tightly here, or maybe automate and improve our sales, the finance process for how we're actually getting contracts out the door.
Connor Jeffers:
And what this will tell you is how are you trending and are the changes you're making operationally to the robots component of your business, increasing the speed with which you're able to move deals through the pipeline, or are you making changes that are slowing things down? Here we see that aggregated. So we're going to see one cohort over one time period in the last 12 months, what's our conversion rates. And this is where we're really targeting if we see... We want to be targeting the lower numbers first, that's what we're investing time and attention, and where we're seeing things that are really high, we want to figure out what's the reason that we're driving those so intensely forward, and really just looking at that in one particular, one particular timeframe.
Connor Jeffers:
Here, this will be touched on quite a bit more on Aaron section, but to give a taste of it is really looking at what's that entire funnel, how long does it take for something to move from stage to stage, and also what's that conversion rate. And so if you total up the average duration across each stage of your overall funnel, and you look at your overall conversion rate from each stage, with those two pieces of information, you can start building really powerful forecasting. And ideally, you want to be looking at this not just in an aggregated level, but also drilling down into this by each source, by each campaign, and as your business expands starting to add more and more slices of that data as you go.
Connor Jeffers:
And what this will do is help you surface where are you lagging? Where can you be doubling down? What needs to happen in order to decrease either the duration or increase your conversion rate? Because ultimately, those are the two levers you have to pull along with your pricing and your deal sizes to actually impact the raw revenue numbers for the business. And finally, when we look at like individual campaigns and what you want to see here, we really want to break this down for that ROI in campaign. So we want to be saying, "Oh, when we launched this campaign, how many leads, how many did we actually generate? How many responses did we get from our database? How much did it cost us to get somebody to respond to this campaign?"
Connor Jeffers:
So that's cost per member and hierarchy, that 3.95 is saying, it costs us $3 and 95 cents for somebody to register for this webinar to download this ebook, to really get somebody in the top end. And then how many of those ended up becoming opportunities? So of the people that we got engaged through this campaign, how many of those actually ended up becoming an opportunity and how much did it cost us to get somebody there? And then ultimately, looking at how many won opportunities did we generate from this campaign, and then aggregating that back to cost. So really breaking down inside this campaign, what's its performance, not just on an aggregated level, but for each initiative that we're investing in, and how much are we able to convert things through, and what's the ROI back from it.
Connor Jeffers:
Cool. This is where we talk about the demand gen lifecycle. So you guys probably fall into one of these buckets and one of these phases. Phase one, if you're early on in your demand gen process, early on having the marketing team, the really big question is how do we get leads and how do we get MQLs? How do we get people interested? And in phase two, it starts to become an operational problem. So we're now generating leads, we're generating MQLs, people are interested in what they're doing, what we're doing, people are interested in what we have to offer, but how do we actually react to those records and how do we engage with them? And then phase three, you now have a sales team, they're working off the leads that you have, and the question starts becoming, how do we get good MQLs that become SQLs?
Connor Jeffers:
And how do we filter out all of the noise to find people that actually are worth us talking to? And then that last phase of how do we really pour gas on that fire and ramp this way up? So really looking at that in a full funnel basis. And so depending on which phase of this life cycle you're in, we'd recommend you really focus on that particular problem. So phase one is going to be, where do we invest for demand gen? Phase two is going to be, how do we build the right system stack to optimize and be able to track and manage these things? Phase three is really filtering back by channel and optimizing your overall strategy. And phase four is looking at conversion rates through each step of that funnel and starting to optimize each one of those and really focus on that sales process or sales marketing hand off all the operational side stuff.
Connor Jeffers:
We're going to jump into tech stacks and how you pull all of this together. I'm not sure, I got muted, but I think I'm back. So let me start over. Before you really start looking into what tech stack you want, you really want to start with what type of team do you have? And so we're really going to break this into two buckets. One is an inbound focused team, and one's outbound focused team. Inbound focused teams, typically, you're going to have a smaller ACV. You're really going to be marketing a product-driven company, and you're really going to be measuring your MQLs and your PQLs, just like your product qualified lead, free trial type stuff, are the lifeblood of your company.
Connor Jeffers:
So people that are fall into that category, you have people like Zoom, you have people like Clearbit, Notion, Dropbox, typically a freemium type of model that you're going to have a smaller ACVs, you can't spend as much on a sales team that's going to go out and get those deals. On the flip side, you're going to have outbound focus teams, so much higher average deal size, really a sales-driven culture and products, your SDRs are really heavy on your headcount in terms of your demand gen function. And your sales ops and your demand gen team is really supporting sales and not necessarily owning a revenue number that they're solely generating, that you have to really focus on that sales, marketing to sales handoff. And sales enablement is a core function of that marketing team.
Connor Jeffers:
And you're really going to be measuring like how many demos, how many top of funnel sales processes versus how many free trials did we have signed up. And that really becoming your guiding metric. In terms of the types of tech stacks that we typically like to recommend and mentor people on, if you're an outbound-driven team, you're going to want Salesforce, you're going to want Outreach. It's similar if you'd worked with SalesLoft. Outreach, we like a lot, we think that they have a better tool than SalesLoft, but they're an outbound prospecting tool. And then some list building component. So whether it is something like Sales Navigator, Clearbit Hunter, probably not something super robust just yet, or maybe you're using an offshore team, but you really need to get that core list of prospects that you're going to be going after to start generating those initial deals
Connor Jeffers:
And so this stack really what it provides you is you get a core CRM for lead conversion rate management. You can start tracking a lot of those conversion percentages. You get that automated outbound prospecting so you can both measure a lot of that top of funnel metrics as well as be able to make your sales team put up a lot of activities versus them having an annual email, or can you like call everybody? That retreat analysis, so when you're looking at that prospect to lead conversion rates, you really want to understand how many people do you have to reach out to in order to get a pulse and in order to find somebody who's actually interested. And then you're dealing in your pipeline management, so what's the tool that your sales team actually uses to move things through your overall title?
Connor Jeffers:
Once you get to a little bit bigger, a little bit more midsize, you start wanting to tack on two additional things. One of them is going to be contact database and enrichment tools like a ZoomInfo or DiscoverOrg, something that gets you better data on the folks that you're reaching out to and trying to acquire. And then something for that BI, pipeline velocity, analysis, multi-touch revenue attribution. InsightSquared is our favorite therapy either. I think they're rebranding, it's like a RevOps platform, but in terms of their sales analytics, we like them the most. And what you really get from this particular stack, we jump to our next slide here, is you're going to get everything in that small package, but also on create leading contact management.
Connor Jeffers:
So when you're super small it's very easy to take a lead that comes in or take a lead that you're prospecting into and go look it up on LinkedIn, find additional information. And as you grow, that starts to both A, take a lot of time, and B, you have a lot more reps, so the amount of time it takes compounds. And so if you add something like ZoomInfo or DiscoverOrg, when somebody finds an account, they can add it, they can add contacts from that account and they can prospect really easily into it. You'll start to be able to build that target account database. So actually defining, here are all the accounts we want to go after, here's information about those accounts, these are prospects in those accounts that we want to be reaching out to.
Connor Jeffers:
And also those prospecting tools so that your sales reps can go and find a target account, they can enrich that account with contacts and prospects with the right titles. And an InsightSquared is going to get you two pieces here. One is really, really good cohort analysis, so bucketing that data, looking at conversion rates for each individual cohort, where they came from, different slices of information. And then the funnel velocity reporting. So really looking at how quickly is stuff moving through our pipeline, which we can do with a lot of Salesforce, but being able to analyze, measure and iterate on it and look at it as a larger team, starts to become a challenge.
Connor Jeffers:
Once you're starting to get a fully robust, you have a full sales team, a full demand gen team, you've got a bunch of different functions, you start needing to tack on a couple of different, additional things. One of these is a billing management solution, whether it's NetSuite, Intacct, Zuora, or Chargebee, whatever it may be. And really looking at, how are you tying that back into Salesforce? You can figure out what's the ROI in a lot of these campaigns, how much are things actually looking like, whether if you are a marketplace model or something more complicated than just sending a contract, and that's what they pay you, tying back a lot of that payment information.
Connor Jeffers:
And then adding on document automation as well. So as you start to do a lot more contracts, bigger contracts, more complicated, you start to need to manage and optimize that process so that it stays inside of the balance we're trying to go into. And so what you're going to get into here is in CRM data for upsell, cross sell, empowering your account management teams and your renewal teams with the data they need to be guiding those customers in the right direction and helping increase your net retention and also add additional business back in, giving them product and utilization data. So one of the best things that you can get from your billing platform or your product, or however you're integrating this back is really servicing for the account management team, what products does this customer have?
Connor Jeffers:
How much did they pay for them last year that'll help them prioritize and manage their communication? Your renewal support some of the churn mitigation and then streamlined CPQ and contract management. So if anybody's a little later in this overall cycle, something that starts to become extremely painful is having the right packaging, making sure sales reps are selling things at the right prices and with the right support and add-ons and implementation costs and everything else. And also being able to get contracts out the door quickly. When you have a lot of sellers managing a lot of deals, it becomes really painful to have that go through a back office process to get approved.
Connor Jeffers:
And so a CPQ and contract management, something like Conga Composer or something like that will go a long way for making sure that what you guys are sending out, you can build rules engine around to start to increase that total pipeline velocity. On flip side, if you're an inbound-driven team you're probably going to want something like a HubSpot. HubSpot are awesome, they're one of our favorite tools in the market, especially on the marketing side. HubSpot has reporting in it, being able to tie everything together and really complex ways gets a little bit challenging, and so at that point, if you're more inbound driven, you can get really by something as simple as Excel or a spreadsheet until you have more tools later.
Connor Jeffers:
In terms of what you're going to get from this, well, how that's amazing at you, integrated traffic and on-site conversion analytics, all the things that you typically try to string together with a Google Analytics and landing pages tying back to the CRM, HubSpot does all of that more or less out of the box. You get seamless MQL management, so you can start to build cohorts off of that. So not just traffic sources generated leads, but really looking at tying that back, and also native life cycles. So that whole funnel, really evaluating the whole funnel. Something HubSpot is awesome for, their new CRM product is super powerful, but better, it has super easy sales rep tools.
Connor Jeffers:
So if you're an inbound driven team, you're probably don't have the ACV to justify really like a sales ops or RevOps requirement to be building out a lot of the tools for your sales team. And so HubSpot is super easy to use out of the box sales tools for those folks. So you don't need to add more head count or more costs there. You get that native marketing automation, so you can start to automate your nurtures, your upsells, getting people back into the funnel, building out trees and branches off of the behavior that they have. Also, integrated ads analytics. So when you have something like a HubSpot, it ties right into all of your ad accounts, it gives you your cost reporting, all of your ROI directly inside of HubSpot and then lead scoring.
Connor Jeffers:
So as you start to figure out where the people that we want to be focusing on, and who do we address, HubSpot does all of that out of the box as well. Once you get a little bit bigger and you're that midsize company, you're going to start to add sales reps. Those will be the reps that are going to go after that higher-end customer, a little bit more complicated, higher-end number of seats, or maybe a larger organization. And at that point, you're going to need to add more sales force. You can go two directions here. HubSpot has an awesome Sales Pro CRM products, their enterprise sales has come a really long way, or you're going to grab something like a Salesforce and wire them up together and integrate them.
Connor Jeffers:
And then you'll probably want to add on something like an InsightSquared as well, similarly to what we talked about for the outbound piece. And what you're going to get from here is really starting to get into that deep, deep cohort analysis, getting into multi-touch marketing attribution, starting to understand over the course of an entire deal cycle, which marketing initiatives are moving things over the finish line instead of just what's that first, center and last touch, understanding that whole customer journey, and also target account management. So you can start to get into tracking and managing who are the prospects you'd want to go after, and how effectively are we engaging with them?
Connor Jeffers:
HubSpot has some really cool out of the box target account tools, and you can build stuff out in Salesforce pretty easily as well. And then custom events. If you're an inbound-driven company, it's very likely that you have a product, a SaaS application, something else that you have some data for. And so with that, that HubSpot Enterprise Marketing tool, you can have custom events, so you can start piping into HubSpot pretty easily number of logins, last login attempts, how many times they ran a particular report, how many users they added. And you can start to use that data in the marketing platform to both do marketing automation and email communication to those folks, but also surface those top level, ideal customers to your smaller sales teams as they're going to go after those versus just those standard freemium or smaller touch users.
Connor Jeffers:
Once you get bigger, you're going to want to tack on one of two things, you're either going to need to add in some outbound function. So it's not enough for your sales team to just be picking the best MQLs out of the bucket, you're now need to start going and generating pipeline and generating interest. And so again, you can go up the HubSpot sales enterprise, they have lots of really cool CRM features. Or if you're on that Salesforce side, add on something like an Outreach. Outreach Salesforce and HubSpot is a really popular stack that we work with. You can do it all on HubSpot if your product is inbound driven.
Connor Jeffers:
And also you're going to want to add on some like billing management. So you're going to want to start to pull that in. And going into what this lets you do is you can start to... Next slide. I thought that was subtle, but maybe not. For our inbound driven large, you start to do a lot of automated upsell and cross sell. So if you pull that billing data back into your marketing automation and your CRM platforms, you can start to automate a lot of the processes that you guys are doing manually, or maybe not spending as much attention on today, you can feed that product data back to the CRM to help you prioritize, and you understand.
Connor Jeffers:
You also automate a lot of your renewals. So you can start to have automated cadences going out to folks prior to their renewal dates, move a lot of those renewables through so that you're only pulling in people on ones that are at risk or ones that are higher value. You also get access to new, starts to build out custom objects and custom events, so you start to integrate all that data back into your system, as well as add on additional business processes or additional business pieces that you may want to be managing now that you are a larger organization and you can build an object to store something like the billing relationship with your business, or any of products and data as well.
Connor Jeffers:
In terms of if you came into this and said, this is a ton of information, all this reporting, what's really cool, but how do we actually do that? What we recommend is going through this process, the first one is do a strategic audit of your current process. And what you really want to map out is how do people move through your funnel today, all the way from the start point of a lead first coming in, converting through, how does it go through your marketing platform? How does it get into your CRM? What stages of the funnel that we've been talking about are missing from your funnel? So what can't you report on? What data are you missing? What data point can't you get?
Connor Jeffers:
And then moving into that systems audit. So going through, now that we know our process, how does our tech stack support this? So can we measure everything that people move through, what data lives in and what tool? And what redundancies do we have in this overall tech stack and what things might we need to add? And then what we'd like to do is really that current state analysis. So now that you've had this together, of all the data that you can string together, what are the holes in the funnel? Where are things not converting? And how can you start to optimize those? And then what we look at is really that future state mapping.
Connor Jeffers:
How do you want your process to work? And what from what you've learned here, how ideally would everything function? And really look at that outside of the technology piece, really mapping it out, and then jumping into what technology tools do you need in order to help support that overall initiative. And so with that, I think we'll jump into Q&A and questions and some of this other stuff. For folks who've asked a lot of questions, we will send through the full recording. Also, you can reach me here. If you do have to go feel free to send me an email and I will get back to you, And Aaron and I will hang around for, I think another hour or so, and answer questions and Q&A from anybody here. But if you guys want to shoot me an email, I'm more than happy to chat about your stuff as much as you need me to.
Connor Jeffers:
I love talking about this stuff ad nauseam, and will be delighted to take the time, but we can jump into some Q&A, which people can start to send too.
Speaker 3:
We had a number come in throughout the webinars. The first question is what is the benchmark for a good MQL to SQL conversion rate?
Connor Jeffers:
I can take maybe a first pass at that, and Aaron, you're welcome to add anything. And unfortunately my answer is, I don't have much to tell you. It's really going to depend on your business, it's going to depend on the channels, it's going to depend on what stage you're at. I don't have a particular benchmark to be managing yourself towards, I'd probably look at other peers in your space. I'd imagine that there's probably research groups that are cranking stuff out for measurements, but what we really look to is really saying, how are we trending and are we improving that number
Connor Jeffers:
So there's definitely a point of diminishing returns, but overall, the important piece is to really be it consistently so that you can spot it changing prior to it becoming a problem at the bottom end of the funnel. And Aaron, if you have any benchmarks on that, you're more than welcome to share them as well.
Aaron:
Let's go to the next question.
Speaker 3:
Okay. The next one was about Salesforce. They asked, how are you getting the cost into Salesforce? Is this a manual input, or are you leveraging an integration?
Connor Jeffers:
On some of these examples, typically what we're seeing is, it gets manually added. And the reason for that is that the way that the demand gen team and the marketing team is looking at this data is typically a little bit different than how it's coming in from the finance side. So what we typically see is finance collaborating with the demand gen team, providing them cost numbers, and then the demand gen team assigning it to individual campaigns. If you're looking primarily at like ad spend or platforms that have really cut and dry costs, you can pull those automatically into a tool like HubSpot, or you can wire it back up to Salesforce as well from your Google ad platform with a pretty easy integration or API connection to pull those cost numbers back.
Connor Jeffers:
But typically, we're seeing those come in. And then Aaron, you had talked a little bit about how you could use that and map it back to your charter of accounts so you could do it outside of Salesforce as well.
Speaker 3:
Okay. The next one that came in says, "I viewed best practices as creating SQLs only after discovery calls, and that's the basis for their pipeline." They've heard that other people will create SQLs prior to, or during a discovery call, but still not knowing whether the sales lead is actually qualified to be included in their pipeline. Do you have a perspective on that?
Connor Jeffers:
I do. My opinion on this is twofold. I actually I'm of the mind that it is totally possible for a rep who knows the market and knows their space and knows about a company that you could move something into an SQL without ever actually talking to somebody. For instance, if Salesforce came through and you had a VP of sales at Salesforce filling out your form, and you sold some services that were applicable to them, you would be like, "Yep, this is exactly who I want to talk to." And so a simple LinkedIn search, or maybe even an enrichment from another platform, you could at least figure out if this is an SQL or not. But all of it is not going to be that cut and dry. So some of them is sales saying, "Yes, this is good, I do want to move this forward."
Connor Jeffers:
And some of them are going to require you to actually reach the MQL before saying that this is a sales qualified lead. It'll be a little bit based on that reps perspective, but the goal of that SQL it's primarily a measurement for sales to tell us, is this lead somebody that you want, and you would to sell to? And is this a good fit for what we're doing? And so some of the times sales can do that without ever needing to call anybody. And sometimes they actually will need to reach out and go to people. And so typically, when we're building out these systems or these processes, we'd like to do a lot of managing that data where sometimes they have leads and they'll just immediately convert them into contacts and opportunities. They'll be like managing and saying, "Yep, this is good. It's an SQL."
Connor Jeffers:
And other times they'll lead them in that lead database and say, "Hey, I'm trying to call them, but I haven't really been able to validate it. From a Google search, I can't quite tell that it's a great fit." And so it can be a little bit hybrid, but the way that I would look at SQLs is this is somebody that sales says, yes, this is the type of lead that I want. This is somebody good. It is qualified. And I do want to be able to work it.
Speaker 3:
Okay. The next one is more about technology. They noticed that you had grabbed some like screen grabs out of Salesforce and they were curious what other tools were used to compile this presentation?
Connor Jeffers:
We touched on a little bit, I think that this came in before we got to some of the tech stack stuff. A lot of the really sophisticated reports and charts you guys saw were primarily coming out of something like an InsightSquared. You can get really far with just Salesforce. We typically can help organizations scale up to like 80, 100 employees and a pretty sizeable go-to market team without needing to add on something like an InsightSquared yet, because you can get a lot done with Salesforce reporting. As you start to push past that, you can go from, I have a question that I want to be able to have an answer, but also be able to analyze that answer all in one sitting versus having a question going and building a report, looking at that report, having longer cycles.
Connor Jeffers:
That's where something like InsightSquared starts to become extremely valuable as more of an insight tool. It's a little redundant because it's their name, but an insight tool as opposed to something that just gives you reporting back.
Speaker 3:
Cool. In addition to all of the metrics that you've shown, shouldn't we be tracking the rate at which a channel produces closed deals? For instance, one with Facebook leads versus LinkedIn leads isn't the real bottom line, what it costs to result in a customer?
Connor Jeffers:
Yes, definitely. We absolutely want to be knowing how much we're getting for customers and how much those customers are worth. But the goal here is really to be looking at that further up in the funnel. So if you have to wait one whole sales cycle to have any idea what it costs you to generate a customer, you're going to be lagging pretty far behind, and you're not going to be able to iterate and optimize as quickly. And so if you can measure those core metrics higher up in the funnel, it's better, for sure. The other piece is you want to be able to know whether changes that you're making are having an impact without having to wait that whole sales cycle also.
Connor Jeffers:
So if you're launching LinkedIn ads, or maybe you change from using in feed to using something that's like the InMail ads directly, and you're seeing, whoa, we're getting way more MQLs for this at a lower rate, you want to know that without having to wait for that customer to actually close and pay you. And it's all about speed. And at the end of the day, you should absolutely be able to look back and say, "Here's our cost per opportunity for this strategy and this initiative."
Speaker 3:
Okay. Next, somebody wanted some help understanding what a PQL is.
Connor Jeffers:
Yes. So PQL stands for Product Qualified Lead. It's a fun term. Basically, is the difference between an MQL, somebody comes to your site, fills out a book or a demo form and is interested, a PQL would be somebody who is taking interaction. So if you have a freemium product or maybe you have like a super low cost tier, and a PQL would be somebody who starts to engage in the types of behavior that indicates that they're higher value. So an example could be, it's somebody who signs up for your cheapest level of your product that's like a freemium or self-signup model. They're looking at some of the advanced reporting, they're looking at some of the API documentation. They're like looking at some of your supporting documentation about Salesforce integrations.
Connor Jeffers:
That might be somebody that through that behavior, you might qualify them as a PQL because they're engaging in the types of behavior in your product that indicate they're someone you would want to actually go after and sell to. And so it's a product qualified lead, but it's behavior that someone expresses inside of a product itself as opposed to behavior on the site or downloading or interacting with a particular form.
Speaker 3:
Another one is asking for a little bit of insight into how they should decide whether they're an outbound model or an inbound model, makes more sense. And what the mix between outbound versus inbound should be. So it's like a two-part question.
Connor Jeffers:
Yeah. Good question, for sure. I would look at this as which one of those buckets you fall in. So if you have a large average deal size, you have a longer sales cycle, you can probably justify having a sales model. The other thing to keep in mind, especially if you're really early on, outbound, at a really early stage of an organization is a lot cheaper and easier to start with than inbound is. To execute on an inbound well, you need to create a lot of content, there's a lot of lag time. You need to be measuring and optimizing that and building funnels out of it, moving people through your buyer's journey. Whereas with outbound, it's really easy to spin something up, start reaching out to those target customers and see if you can convert them.
Connor Jeffers:
And so unless you have a really like a freemium or a product-driven type of experience, I'd probably start with some lightweight outbound, and then once you're gaining traction there, you can start to invest in inbound. I usually see organizations pretty lopsided in the beginning and then moving more to like a 50/50 model, and then over time one side of the house gets more traction than the other. And I don't have a lot of insight into the magic of why that happens, I think it just has a lot to do with the teams and the execution and the folks that are involved. But I would probably, if you don't know where to start, as long as your average size is high enough that you could have a contract, you could sign somebody and it isn't just, hey, sign up here and put in your credit card and we'll bill you 10 bucks a month, I'd probably start with outbound and see how that functions and then add on more of an inbound channel a bit later.
Aaron:
This is Aaron. I think we're set with all the questions. Just want to give a quick thank you to all of you who have carved out some time to join us, and for all your hard work in general for your companies in these unusual times. Also, thanks to Connor and his team for helping us to walk through the optimal funnel tracking and the associate tech stacks. As he said, feel free to reach out to him and the folks at Aptitude 8 for any follow-up. Also, feel free to reach out to me as a sounding board for any help with budgeting, forecasting, reporting, metrics, or finance tech stack questions.
Aaron:
A quick closing note, we're going to be sending out a quick survey on the webinar. If you could take 30 seconds to fill it out, that would be great. That's all for today. Thanks. And have a great day.
Connor Jeffers:
Thanks all. For those of you who just have a couple more questions, feel free to shoot me an email, I'm more than happy to chat with you.
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email@aptitude8.com