The Marketing Metrics Everyone Misunderstands with Emily Popson, VP of Marketing at CallRail | Ep. 376

0:00Proving your marketing ROI shouldn't be a guessing game, but when results are hard to track, it's difficult to know if your marketing strategy is working. Meet CallRail. In a few clicks, you can connect every conversation to the exact campaign that started it, so you can focus on what works and drive better marketing outcomes, all in one platform. Try it free today at callrail.com slash prove it. Welcome to the Marketing Millennials, the no BS marketing podcast. I'm Daniel Murray and join me for unfiltered conversations with the brains behind marketing's coolest companies. The one request I tell our guests, stories or it didn't happen.

0:48Get ready to turn the f*** up. We are back with another episode of the Market Millennials Podcast. I am here with Emily, the VP of Market at CallRail, and we're going to talk about some BS that is on LinkedIn, some myths we need to bust. Emily has some hard feelings about the way things are really said online that are not the full truth or partial truth, and we need to get into them. But I want Emily, could you give a little background of who you are and how did you get into marketing? And then we can go bust those myths. Yeah. Thanks, Daniel. Great to be here. They are hard feelings, aren't they?

1:27You know that everyone else is about to learn that. My name is Emily Popsin. I'm the VP of Marketing at CallRail. I've been in marketing my entire career in B2B SaaS. I've worked at large scale enterprises. I've worked at five-person startups and most recently here at CallRail developing marketing analytics solutions and AI solutions for marketers of small businesses and the marketing agencies that support those. We provide lead intelligence to those businesses and really democratize lead intelligence for businesses of all sizes so that any marketer can market with confidence. I found my way into marketing really accidentally.

2:05And that's the short and easiest version of the story. I always wanted to be a lawyer. I got into law school, saw how much it costs to go to law school, and said, I think I'm going to go make some money first before I do that. And just got really fortunate to wind up at a marketing-focused software startup in New York City and really got the SaaS bug from there and have never left the game. That's actually a funny story because my wife is actually a one-semester law school dropout and then she got into e-commerce. So she has the same background. Yeah. So she went to law school. Actually, she hated it and was like, I need to go do something else with my career.

2:43So she has no regrets either. No regrets at all. But I want to get into this. I think the first myth I want to talk about is around the MQL. So what are you seeing online that you want to debunk that people are saying? Here's the thing. I'm sure you've seen it. You're very active and aware of what happens on LinkedIn. You are one of the best in the biz. For the last five years, there has been this war on these three little letters. And it's been so curious to me to watch. And the longer it's got on, really the more concerned I've gotten for the marketers out there who built MQLs into their MarAub systems to measure something.

3:36and are now sitting here going, well, gosh, do I have to go redo all of that? Am I a terrible marketer because I just shipped a report to my CMO or my CFO or my head of sales reporting on how many MQLs I delivered last month? And I think it's causing such unnecessary confusion. And I understand where it comes from. We got into a bad place as marketers maybe 10 years ago where everything was measurable. And so the bar kept dropping. You know, well, we measured a click here. We measured an email read here. We measured a touch point here. And the bar for MQL went lower and lower and lower. And sales confidence in those MQLs got lower and lower and lower.

4:21And frustration got higher and higher and higher. And it's perfect fodder for LinkedIn commentary. but I think leaving it as MQLs are worthless and so are you as a marketer if you measure them or even say the letters or type the letters somewhere it's just not productive because marketers need to measure something MQLs are nothing but a delivery system for what should be a quality revenue opportunity for your business and so what the way I like to think about this and reposition it for marketers is it's a delivery system. You are in control of it. The MQL is not worthless. Your definition of it is.

5:01Go back to the definition. It is not the letters. It is not the fact that you have a delivery system. It is how you defined it. Instead of an MQL being, we've all seen this, five points for opening the email, whatever, five points for visiting any page on your website, 20 points because they spent half a second on pricing, but even though they didn't mean to. Sales go follow up. Redefine it as it's someone in your ICP, perhaps, who has read every single email that you've sent to them over the last however long, has started a free trial, or has called a couple of times. Whatever it is, get it, bring it closer to what your sales team or your business needs.

5:47At my team, my team is an inbound PLG company. Their primary KPI is driving free trial. So to us, an MQL is synonymous with someone ready to utilize the product. It is not synonymous with someone who is somewhat aware of our brand and sales should go spend time, because ultimately that's not efficient for our business. It's not efficient for our resources. It erodes credibility in marketing. But we need marketers to go back and redefine, take the reins back to MQLs and rebuild that credibility and just change, have a more nuanced conversation about what's really wrong here and be more specific about how to fix it.

6:28You've worked in ops before, you know, to go back through all your go-to-market systems, to change those three little letters, it's not really the most productive thing marketers could spend their time on or the ops teams could spend their time on. Yeah, that's why I always think I hated the scoring system that people build. I always say go off of your ICP and always look, is your ICP changing or not? Because I think the problem is if you do it off those little numbering system, that is not telling you if that person is a great person. Because someone could read a thousand emails and they're not in your ICP, and you can consider that.

7:10I think having a clear definition of what is a quality lead, um also someone who raises their hand usually that starts a free trial or clicks request the demo or is is very high intent i don't care what anybody says so if they filled out the form and clicks a demo that is a high intent thing i i get worried when people and i think it's definition i think that's what you said from the beginning i get worried is when it's someone in your database that hasn't shown any like clear signs of intent and is just opening emails. And then now like sales goes. Right, or they have some ABM tool. They've actually done nothing other than like their company raised some funding.

7:56And so now they're an MQL or whatever it might be. Like it's not even their own behavioral. It's redefining it. And it's not relying so much on these old scoring models that are really the root cause of the problem, to your point. And I think that if you just use it as a directional metric, because you have to measure it and use, like, are they converting into pipeline? Are they converting into revenue? And use it that, I think the problem is when marketers' only metric is MQL. And then, like, it's easy for a marketer to game an MQL. And that's where I think the problem started happening is that people start gaming like an mql because that was their only metric i think the problem is usually there's no alignment internally of like what an mql is and there's no alignment on like we are all responsible for revenue and pipeline and let's go at it and then an mql is just something that directly tells marketing and it should only be a marketing metric to be honest like i i couldn't agree more.

9:04Yeah. Like on my team, we don't even send MQLs to sales. We generate MQLs and then we do things with them through marketing systems, but we also don't report on them. They are an indicator to us. We use them to inform the journey and the experience that we're executing and creating. But they're not even in our list of KPIs. We just use them as a delivery system to signal that something else in the buying journey is ready to occur or a different experience is ready to be delivered. And we orchestrate all of that through marketing. We don't hand a basket of MQLs and say happy birthday to sales every month.

9:47Yeah, and I think it's just what I used to look at is every channel has a different value system of somebody coming. but you have to measure like if someone fills out a form coming from facebook you have to measure how much that person it costs to generate that form fill from that channel like i it has to be measured somewhere because you need to know cost just for a marketing team directionally that facebook is trending higher for a cost or met whatever events are trending higher or lower so you directly know how you're spending as a marketing team i think that's where i where i because then if you're spending more on quality it doesn't really matter if you're spending more on junk then it matters um so uh i think the next part of this is which which kind of goes hand in hand with mql is like reporting attribution a lot of people a lot of people say let's just throw it out marketers.

10:54It sucks. Don't think about attribution. But so what is your opinion on attribution? Yeah, I think attribution is garbage has been the headline floating around and it just really grinds my gears a little, Daniel. Because again, it leads marketers astray and it's not productive because first of all, marketers, and your podcast talks a lot about this. For marketers to be most successful, they need to directly attribute their role and their work to revenue. It comes down to revenue. Are you delivering revenue growth for the business? Attribution is the act of attributing your efforts to revenue, to units, to growth.

11:38There's never, ever, ever, ever, ever, ever going to come a time when marketers don't have to answer the question is what you're doing, is what you're investing in delivering revenue growth for our business? And how do you know that? I think where attribution has gone astray is, well, it's a couple things. It's when marketers rely too much on in-platform metrics or last touch or first touch attribution and they attempt to oversimplify the role of their investment, it undermines the credibility of the data that they are reporting on. And it leads everyone to feel inside like, is this just garbage?

12:31Should we abandon this? But the truth is the next month will come around and you have to answer the same question. So we need to find a different way of doing it, not abandon attribution altogether. My personal opinion is that attribution is entering a bit of a renaissance and it's just time to approach it differently, starting with collecting more data. Most marketers, I'm sure most of your listeners are relying on solely some form of software-based attribution, whether that is just their in-platform click attribution, whether that's GA4, whether that's something like Marketo Measure, Visible of old, or something like CallRail for small businesses.

13:17We're all in the attribution game. The problem with only utilizing those data points is it's trying to only use, it's using software and the data points software can collect to simplify and attribute a single lead, a single unit to a dollar of revenue. I think as AEO takes on more and more space in our worlds, I think as dark social has become a greater part of buying journeys, as the landscape at large has changed, those practices have become largely outdated. We need to connect more data sets to really understand what our buying journeys look like and get away from this single unit to single channel to single dollar methodology and get closer to unlocking insights about common buying journeys.

14:19And AI has made that easier than ever. Like the simplest version of this, if you like get out of like traditional B2B marketing world, right? If you, maybe you have all those tools available, pretend you have nothing. You're day one in marketing and you want to answer the question to your CFO, CEO, CMO, is anything you're doing working? Take all your click data, get your GA4 sessions, download those. Do you have a form somewhere, either from sales or on your website or somewhere where you're collecting answers to the question, how did you hear about us? How did you find us? That's self-reported attribution.

14:58That is really valuable data. If you're using any type of conversation intelligence tool, which marketers absolutely should be doing and we should talk about that, if you're using anything like that, can you have your tools listening for signals like that about, you know, maybe I'm like, yeah, I'm using your tool because Daniel referred. me to you, you want that data point because maybe I just went and Googled you and you're going to attribute me to branded search. But really, I'm here because Daniel. I'm not here because of branded search. That made it easy for me to connect with you. That made it easy for you to capture me.

15:31But the influence of my buying came from Daniel, came from a personal slash business referral. If you're not collecting these data sets together, self-reported attribution with software-based attribution and even session data and using AI to uncover insights, you're going to be stuck in this old way and it's getting more outdated every single day that we remain in the game. Yeah, I love that. We used to, and this is before AI, I would say, we used to, because I used to run marketing ops, we used to have a Friday audit on attribution and we would have a report of okay here's all branded a branded search report because always branded search is some other channel usually um because someone heard about you somewhere to be able to know it's branded search and i i love google's still helping there but sure and then we would have another and then we would go through like what you said like what did you hear how did you hear about us compared to and if there was any conflicts we would then make the changes in the system that need to be made but we had a flagging system to be like because we also had people on our team like flag like oh there was a call and the call said like in the transcript said someone said they heard about us here um that should be flagged right um so we had a flagging system that like either an SDR said something different as he said something different when they asked the question like where did you hear about us so I think that that's the thing but with AI now it's even better and I also I also go back to like the e-commerce is doing it way better and I used to do it way worse because they have increment incrementality testing where it's like they know that if I did a big LinkedIn campaign.

17:25I'm going to put that into the dashboard as an event and look at how it's affected other channels when I did like a dark social thing or I had an influencer post go out or I had this go out and see increment. Yeah, like, but we don't do it in B2B. We do this. Okay, it came from visible, visible is the end all be all it came from Facebook, Facebook's end And instead of data should be put into an unbiased system and then reported on, not on something that's trying to make you money. Right. And it's redefining. I'm sorry. I think the marketing gods are coming for me. The sun has gotten so bright in Atlanta.

18:07Do you see like the orb? Yeah. I think they're coming for me. The halo effect right now. I think Jay's presence is here or something. He's angry. It's okay, Jay. It's going to be okay. And it's redefining the question that we're answering. I think the old way, the visible way, and listen, we're visible users. It's providing really, it allows us to collect the software-based data I'm looking for, but it's no longer, we no longer report on that by itself. It's not insightful enough. It's redefining the set of questions we're answering. It's no longer, what is the single channel you can attribute that dollar of revenue to?

18:46It's what is the common buying journey? What are the commonalities across the revenue that you've generated? What versions of those are driving the greatest return on investment? And can you replicate that? That was idealism like 10 years ago, I think, in attribution. We would have these conversations with our MarOps teams. Could we ever get there? And it was so complex. But again, as we've said, AI is changing that. I mean, you can simply take all this data, upload it into your AI tools and prompt it to look for these trends for you. So we're moving our platform in that direction to support small businesses as well.

19:31But I think it's table stakes because even with AI, you can really only get – like the LLMs, you can only get directional, somewhat influential attribution data on the role they're playing. You're never going to capture all that in the archaic attribution methodologies. You're just not. I mean, for example, there are ways that we could talk about right now of capturing, let's say, off-platform ways of attributing. Like, for example, CallRail, like having numbers on flyers, having numbers on billboards, having numbers like at a booth. That's one way to capture off-platform. there's qr codes we're getting pretty good of like at least having directional and all this all this to be said is we need to know where someone like came from it doesn't mean that they that was their first um interaction with that brand i think separating those things and then also like i used to used to say is like i used to like stabilize metrics before i used another the channel and then say like is is blended cacks like still going trended in the right direction are we dropping planet cat and like we're still having blended cack at where i like it i still i'm going to invest in that channel for a long time but if i my my cack number but yeah i want to how do you so like you see let's go on how you guys use it so you're visible tracking some of the things, what other, how are you, how do you look at data and decide I want to invest in this channel versus this channel, this channel is working, that channel is working?

21:24Yeah. In terms of the data sets, we're looking at our session data. We're looking at the visible attribution data, which through a W-shaped model works for us really well because I'm trying to distribute the influence of the channels there. But then we've introduced this concept of influence reporting, which takes essentially that broad set of touch points, which is the visible language, right? It's you, Daniel, and my system have 17 touch points, and six of those are across various versions of search, and five are across various social platforms, and the rest are an email and a call and whatever.

22:04So I have this like touch, this view of the various touch points and through the W-shaped model, right? It's distributing those touch points and ultimately divvying up Daniel across the channels. It's giving like 25 % of you here and et cetera. But what I've, what we've built is take the whole of the touch points and tell me which channels show up at the highest rate across our unit, our new units and our revenue. So it's like, and then we use both data sets. What's the attribution data telling us, the software-based attribution data? What is the influence data telling us about the rate at which channels are showing up on our revenue generating our new units?

22:45And then bringing in the conversational insights, the self-reported attribution and then the trial data signals. So like my team, the demand generation team is organized by vertical. So each vertical marketer is watching their trial volume every day. And while they can't attribute that the day they were at this event or that this big influencer launched with us, we can't see it invisible that that drove that trial spike that day. They know that was the differentiation that day in the market. And so then we bring those data points in as well. And then we've changed. We show the data, but they are responsible for reporting on what that means for the business and what that means for where we should invest.

23:31And we look at we call it, we have CAC, which obviously brings in the cost of sales, whole cost of sales and marketing. And then we look at marketing acquisition costs. We call it MAC internally by channel. And how is that trending? How is the blended trending? How are conversion rates trending? Did any of them create downward pressure on convert? You got to look at all of it. You know what I mean? And this goes back to what we're saying. You can't, the old way stopped working five years ago where you're just relying on the output of a single set of attribution data. You need to be attempting to move in the direction of triangulating larger sets of data about what's actually influencing buying and what investments are actually moving the needle and generating revenue because that's how you build credibility with your CFO.

24:17We have my demand gen team, the director demand gen, her whole team goes in front of our CEO and CFO once a month. They have it on this coming Monday. They dry run it with me this morning and they go, this is what's happening in every channel. Here is qualitative insights. Here are the quantitative insights. And here is what it means. They show their data, they show their path, and then they translate it. And then they make their case for what their investments are to come. And it's all rooted still in data, but a different type of data that's evolved with the way buying has evolved. As marketers, we're all trying to answer the same question.

24:52Which investments are actually driving revenue? And too often, the honest answer is an educated guess. CallRail replaces that guesswork with proof. With the help of AI, you can connect every lead to the exact campaign that drove it, analyze your conversations, and capture leads around the clock. That's why over 220 ,000 businesses use CallRail to market smarter. Stop estimating impact and start proving it. Try CallRail for free at callrail.com slash prove it. And I also think that, which I think people confuse, there's marketing only dashboards and like attribution, and then there's the attribution you show publicly.

25:41I think and that's like something that people conflate to is like like there's like marketers should collect as much data points as they need to make the best decision possible but the best decision shouldn't all those data points shouldn't be shown to everybody because then it's going to confuse the hell out of the business like you diagnose those points and then like your demand jet team's probably like taking all those points saying like okay this influence this influence It was, now I'm going to make an executive decision that this channel drove this, this channel drove this, this channel drove this.

26:14We should invest more here because this is happening, this is happening, this is happening. But it's also what you said. It's like we only are doing this because we're judged so hard on results, which is fair. But we have to report to show that to get more money. Otherwise, we're not going to get more money. I know. I tell my marketers all that all the time. They're so lucky that they're able to tie every move they make to revenue. That's where you want to be as a marketer. You don't want to just be seen as a cost center. You want to be seen as an investment center that delivers revenue growth.

26:52And you need to be able to do these things to maintain that standing, I think, in both the executive spaces, but also broadly at your company. and i think i mean the next level of this i think um we all want to talk about is i mean we are in the era of like conversational data first party data how we collect first party data what is important of that so you want to go over a little bit of like what people say in the market versus what is actually true um what you or true to you um and let's go down to yeah i'm convinced this is truly actually reverse psychology being used on all of us, but I'm happy to be wrong.

27:31This is like an unspoken myth. It's that like tools like Gong or other conversation intelligence tools, we make one for small businesses, but there's so many of them out there. Go to G2 and you can see all of them, that those are really like sales tools. And this to me is like this secret unlock that my marketing team seems to have figured out and many marketing teams we work with have figured out. But broadly, when I'm especially in the B2B space, I do not see this being utilized enough. I see maybe they have their product marketing teams logging into Gong to, you know, say they listen to calls or make sure sales is talking about some offer or whatever it might be.

28:08But conversations in general, AI in general, and some of these AI tools, whether it's like AI SDRs or it's conversation intelligence tools are not just for sales. Marketers, I would argue need to care just as much, if not more, about what's happening with these different pieces of software that are increasingly available. On the conversation intelligence side, a couple of the ways I think marketers tomorrow should be using this and should go find whatever tool works for them. There's many that are industry specific. If you're smaller, call rail is a great one. If you're bigger, gong is a great one.

28:45There's a lot in the middle as well and around the French areas. But one, conversion signals. You can be, to your point earlier, having your systems listening to conversations for indicators of a variety of things, readiness to buy or booked appointment if you're in the trades or book demo if you're in SaaS and sending those signals automatically back to Google from the conversation or to your various ad platforms. Like this is just like a no brainer. Everyone should be doing this and they should be doing this for like a year. And if you're not doing it, start today. But there's more nuanced things that I think are going to help differentiate marketers and marketing execution.

29:31Segmentation and personalization. you can be using these tools to extract unique details that help make your emails more personalized and more engaging and drive more reply rates that make your segmentation more, more immediate and timely. Like imagine if all your conversations, there's no way for you as a marketer to know, did everyone in my segment, in my base, just have a positive or a negative conversation with sales or a success or no conversation. If you have data on like someone just had a really bad conversation, their sentiment just dropped, and you have triggers set up to automatically scrub them from your email list, that automatically can improve your persona and your standing with that customer or prospect.

30:17Or maybe you set up a trigger or and to not only scrub them, but now put them to trigger another automation that tomorrow you send them for marketing a little like moment of delight somewhere, like a$5 Starbucks. We know you had a tough call yesterday or don't acknowledge it, but something that like meets them where they are a little bit more and connects those dots. Without conversation intelligence tools, there's no way to scale that type of insight from every conversation. But you could also use it for like really simple things like keyword research, create keyword bubbles on common words being used across your conversations.

30:55Use it for offer research. Like we have this one great example where like a business kept getting calls asking if they were doing anything for this upcoming holiday. And they were like, oh no, we've never even thought about that. And then they launched an offer because they realized through this word, this word bubble kept getting bigger that people are asking, are you doing, do you have a small business Saturday offer? I forget the specific holiday that it was tied to. But by having that data instantly being generated from AI analyzing your conversations versus you going through transcripts and looking for insights.