Decoding Your Paid Media Data: What Matters (and What to Do Next)

Alex Jonathan Brown
00:04 - 01:06
It's 11AM in the Bay Area, 2 PM on the West Coast, and also 2PM in Milan, Indiana, home of the nineteen fifty four state champs that were the basis of the movie Hoosiers. And wherever you are, grab a cup of your favorite caffeinated beverage. It's time for a coffee break. 
I'm Alex Jonathan Brown, senior content strategist here at Iron Horse, and there is more data available maybe than ever to marketers, which does make turning those pretty numbers and graphs into actual, like, actionable data, may be trickier than it's ever been.
And whether you're the one generating the reports or you're the one who gets them showing up in your email inbox, today, we're gonna do our best to help make sense of all of it. And to do that, we've got some guests.
Making her return to coffee break after a bit of being away, it is Iron Horse director of marketing Ellen Smoley. And maybe a debut, Hannah, have you joined us before?

Hannah Jordan
01:06 - 01:06
First timer.

Alex Jonathan Brown
01:06 - 01:14
Great! From Demandbase, their director of digital marketing, Hannah Jordan. Hi, everybody.

Ellen Smoley
01:14 - 01:17
Hello. I'm happy to be back.

Alex Jonathan Brown
01:17 - 01:31
We're so glad to have you back. So before we get started, Hannah, first time, tell us a little bit about yourself and Demandbase and kinda get us up to speed on what y'all are doing over there.

Hannah Jordan
01:31 - 02:18
Yeah. Let's do it.
So my name is Hannah. I'm based in Austin, Texas where it's gonna be 80 degrees this week. So very sorry to everyone up north because I've heard the same is not for you. 
But Demandbase is essentially an account based platform that helps you go to market much more efficiently. So it's gonna give you a lot of insights and data about what your accounts are doing out in the digital space, pull all those insights into one place, and then connect to your CRM and marketing automation platform and really give this holistic view of what the heck is going on. So that way you can take these insights and all this data and actually action on them, and bring your marketing strategy, your sales approach to life.
So I get to call myself customers here at Demandbase. So I use Demandbase myself in my day in and day out, and then I get to use it to run all of our digital campaigns. So it's a pretty fun job that I do every year.

Alex Jonathan Brown
02:18 - 03:25
Awesome. The reason why you kind of came to mind early when we were brainstorming this idea is if you're a person who thinks there is such a thing as too much data, Demandbase is a culprit.
The amount of stuff you can get out of that is vast. So that's why we wanted to bring you in, because we've spent a lot of time looking at Demandbase info on our own.
So I know we've got some charts, some reports that we're gonna look at. But before we get into that. And we're kind of just thinking about marketing campaigns in general and really using this data to, like, point us toward our goals: What do you see as, like, a good starting point for we're doing a campaign, we know we want it to be successful. How do we define that success? What is that goal gonna be for us? Like, how do we go about kind of picking what that's gonna be before we hopefully, before we start the campaign, but definitely before we start looking at data to, like, decide how well we're doing?

Hannah Jordan
03:25 - 04:24
Yeah. Absolutely. And you set up my soapbox perfectly for me to get on. Essentially, everything I say that you brought, it always has to go back to the audience.
And so one thing that I talk to our customers a lot about is they'll take an audience that has never engaged with them before. They just essentially found these accounts.
They were great at accounts, and they ran a campaign against them and wanted to drive leads, which is fine and all. But if the first time that a company always going to interact with you and they click on an ad and it go right to a form, they're probably not gonna fill it out yet because they don't know you. They're not comfortable sharing their information, getting all the emails after that. So I would say look at where your audience is, how warmed up and receptive are they to you, and kind of use that to base your goal.
So if it's the first time, you know, an account is ever gonna see an ad from you is hoping for a lead the best outcome, probably not. So really thinking about that account journey, where that account is in those journey stages, and then mapping your metrics based on what makes sense for that journey stage.

Ellen Smoley
04:24 - 04:48
And I think when we talked to you, Hannah, we were asking, you know, how many campaigns are you running at one time? And the number was wild. And so tell us a little bit about that.
How many campaigns do you have launched at one time? And then it goes to your point about the segmentation getting targeting. So I think that leads into the why you have so many running, but tell us a little bit about that. And it really shows the vast experience that you have in this topic.

Hannah Jordan
04:48 - 06:15
Yeah. Definitely. So in display alone, so in Demandbase display, we have 156 campaigns live right now, which always kind of, like, terrifies people. The reason that we have so many is because to your point, we get very segmented with our audiences.
And this kinda ties back to how much data we have available in the platform where we are segmenting audiences by the account segment. So, basically, different revenue bands because that is gonna tell us kind of the number of impressions that are needed, kind of the messaging.
We look at journey stage then, so where they're at in that buying journey, typically top, middle, and bottom of the funnel. We look at what product they're engaging with or showing intent on and use that to kind of define these different messaging tracks.
We look at the persona based on the products. So we have ABX that both a salesperson can use and a marketing person can use. So based on the different personas within, our people targeting, we also segment by that. And then finally, just geo, so breaking out by America and EMEA.
All of that breaks down into 156 different campaigns. So that we have some customer campaigns, factored into that too. So it sounds like a lot, but, really, the way we set it up is, essentially, we can kind of set it and not forget it, but accounts are going to run through these different campaigns as they progress in that buying journey without me having to do anything manually. So it's a big lift upfront, but I would say, like, once you have that strategy in place, then it kind of runs for you.
Ellen Smoley
06:15 - 06:43
I'm super interested to get into some of the data and look at some of that to help us understand if you're seeing certain things. Do you change it? Do you let it happen? Do you let it ride? Like, what does that look like? And we'll talk about that. But one of the one thing that we wanna talk about is, what paid media metric often goes overlooked? Like, what are people not measuring that you think they should be?

Hannah Jordan
06:43 - 07:28
Oh, that's a great question. I would say one thing is this idea that goes a little bit beyond just a lead, right? And so we call it our unqualified responses or a QR. And, essentially, what it looks at is, okay, what leads did you generate that were in our ICP? So there are certain revenue bands, certain industries, have certain technologies at them.
And then also within that, are they our target persona? Because if I generate a lead that is from a company that's never going to buy from me when a role that has no purchasing power to buy from me, it's really not that helpful. Like, what is sales really gonna do with that? So it's looking beyond, are we targeted enough in our campaigns to actually get people that matter from accounts that matter for to us.

Ellen Smoley
07:28 - 07:40
Yeah. I think we get really excited about seeing numbers, but sometimes those numbers don't really matter. And so let's look at some of those charts and kinda dive into that.
Alex Jonathan Brown
07:40 - 09:10
This is me. It's my responsibility to figure out the screen share, so I think I've got it, but we'll hold for a second.
And while I work on that, I think that the thing that's so interesting being on the marketing side of the table, which all of us are, is we do get really interested about numbers because to some extent, that's our job. We're gonna I'm gonna show these KPIs here in a second.
Show these KPIs right now. But for the organizational, like, the success of the organization, the KPIs, none of that sort of matters, right? And that it's a means to an end, the end being a sale and someone wiring us a giant check, hopefully, right? So as we're kind of looking at KPIs, I know Ellen asked earlier about what are the things that people aren't looking at, but this is, I think, maybe larger than some of the, some of the numbers that our attendees are seeing.
But my first instinct as somebody who's not super, like, numbers oriented is like, oh, a lot of green, a lot of numbers moving in the right direction. I think that's good. But, like, from the next level of kind of dealing with data, where are the places that I should start looking to see if I can't get a little more insight to kind of what's really happening even at, like, this basic KPI level?

Hannah Jordan
09:10 - 09:51
Yeah. So I would typically say, like, this is the dashboard that I go and look at. Typically daily, right? This is the “make sure nothing is horribly broken” kind of dashboard.
And so what I also really like about it is it's actually comparing period over period because kind of to your point, like, yeah, numbers are great. So if I went to my CMO and I said, our cost per conversion is $97, $98. She'd be like, okay. Well, is that good? Is it bad? Like, in reference to what? Last quarter ,was it, you know, $20, and now it's gotten really high? Like, is this an improvement? So I think having the context really helps to kind of drive some of this, you know, relevancy into what these metrics are actually telling you.

Alex Jonathan Brown
09:51 - 12:26
I think there's a great point in there too. I, at least, I think most of us have been in that conversation where somebody asks you, like, is this good? Especially if you're at an agency that's working in multiple industries.
And so the thing that you do is you Google finance industry benchmark ads stuff or whatever, and then you get this random number that comes from Google and you say, yeah. That's our benchmark.
But, Hannah, the point that you're making is the thing that's most important is how are you moving compared to where you were? Like, are things getting better, or are things getting worse? And kind of using yourself and data like, making sure you're doing a one to one comparison on that data, especially at this kind of higher KPI, like, trends level, kind of stuff. Anything else we wanna hit on while we're here before we move to, y'all, strap in these graphs get more complicated from here. This is the easy one. We're about to do some really involved work. We have a question in the chat: Does three thirty, 330k for 2,000,000 impressions seem like a really high CPM? Listen. First off, this data is randomized, or anonymized, we'll say.
But the other thing is that all of this is so dependent upon so many things that especially at this level, that's why we're saying it's so important to kinda track those trends. Because doing a one to one comparison to anything else in any other industry doesn't work.
Like, if you've ever worked in finance, in medicine, in law, any of those kind of areas, the CPMs are wildly out of range from what you would expect anywhere else because the competition is so high. And in a lot of those, there's so many things or so few things that organizations can legally target ads to. And so it's just, oh, yeah. We're all bidding on the same six keywords. So it's $500 a click or whatever it is.
So okay. With that, I think we'll pivot to the next kind of look at our at our graphs here. First instinct Hannah, we've got a little more look into time. I'm still kind of looking at those KPIs, but we've got some trends.
So as this data kind of comes on your radar or shows up in your reporting, what are the things that we kind of start to look for, and then how do we use that to define where we wanna go? Obviously, we've got LinkedIn and Google across the top there. But, yeah, take kinda take us through this a little bit.

Hannah Jordan
12:26 - 13:52
Yeah. Definitely. So, basically, the question that I'll get asked is, you know, on any given week, what were the conversions? And I can go get that data from the, you know, report we were just looking at. And then it's, “Okay, great. What's the breakdown between channels”? And so that's what this will start to kind of show you is, okay,o f the 3,300 leads that we drove, two almost 300 of those were from LinkedIn and the rest were from Google Ads. So this kind of gives us direction like, okay, if we're looking to drive leads, like, let's say, in a funnel review call that we a lot of our accounts are sitting at top funnel. We don't have great database health for them. We need more contacts. We need more leads from these people.
Would we wanna go invest it into something like a LinkedIn, or would we wanna turn that volume approach more with Google Ads? Versus, if maybe we get kind of like a better CPM from something like a LinkedIn, maybe there's specific audiences out there that we can't necessarily reach with Google. So maybe it's, hey, we have accounts that are, you know, in the middle of funnel. They're engaging with us really well, but we wanna push that a step forward.
You can't get that targeted on Google Ads, so that is where we might wanna go with something like LinkedIn. So this just kinda gives you that next level down view to you into, okay, here's overall performance. Now what are the actual channels that are driving that? And performance over time is just because I do get asked weekly kind of what's the impact that digital campaigns have had. I can kinda go and show like, oh, okay.
Here's some of our trend data. If, you know, responses are down, that makes sense because we're down in our lead, volume that we're producing.
Ellen Smoley
13:52 - 13:59
Hannah, between LinkedIn or Google Ads, pick one of those and help us understand how do you stand out from the noise? 


Hannah Jordan
13:59 - 15:12
Gosh. Such a good question. I'm gonna pick Google Ads because I am very passionate about this idea of sanity versus vanity, and the sense around, like, our competitor terms and kind of bidding on it. And so I get messages from reps all the time that says, “Hey, Googled Demandbase and I saw other ads that, you know, popped up above it.” And I said, “Yes. That happens. Sometimes you get outbid.They have different budgets, you know, all these different factors that will go into it.” 
But then I asked them, okay, let's say you Google something like, I don't know, hamburgers, and an ad for, you know, sausages comes up on the top. Are you gonna click on that or you're gonna click on the one that you just Googled? You know, like, that happens to us all the time. I Google Airbnb. I see Vrbo that comes up. I'm still gonna click on Airbnb because that's what I Googled in the first place. And so, yes, I get it. It's someone else above your brand, and that isn't awesome. But there's still a level of sanity to it, or don't blow your budget trying to kind of, like, outbid your competitors, try to save that number one space for yours.
Because in the end, people are typically going to, you know, still click on the actual brand name that they looked at in the first place.

Alex Jonathan Brown
15:13 - 16:37
I think the other part of that too, and I love that sanity versus vanity dichotomy, is if you are in a situation where there's someone maybe a little higher up on the org chart than you who's like, no. This is what we're doing and this is the direction that we're going in.
That's when, like, your copy approach on that ad gets really important. Right? Like, there are ways to go about doing that, and it's not just, “Hey, we're Vrbo.”
Right? So, like, there are ways to work around that, but  I love the point that you're making of, like, make sure that this is really the thing that makes sense to do and not that you're just getting you're leaning so hard into, like, this is where we should be. So, you might have touched on this a little bit, but if I'm putting on my my, like, “Hey, you're showing me this report, and I'm not super familiar.” 
Why? Okay. With the cost per conversion being so much cheaper than Google, you mentioned it before. It's worth just saying again.
Why is there any money at all going to LinkedIn if I'm, like, controlling the budget here? Like, is it just that the targeting is so much better in that space that you can really hone in on those? And then how do you, maybe the better question, how do you determine that mix and how much of your budget is worth going after that more targeted audience?

Hannah Jordan
16:37 - 17:33
Yeah. Definitely. I think it will not surprise anybody on this call that, you know, Google Ads, you just can't get as targeted in it. Right? So I might have a much cheaper cost per conversion, cost per lead.
I'm basically probably gonna need five or six leads to come in for one of those to be from an account that I care about with a title that I care about because I just don't really have control over who's coming in and converting on it. With something like a LinkedIn, I can specifically say, “Hey, target this account and these seniorities with these job titles with these interests, you know, get very specific.” So when we start to think about I need five leads from Google Ads to get a quality of one lead from LinkedIn, then the actual cost per becomes pretty much the same between the two channels.
So that's a little bit of, you know, how you have to take it that next step further kind of look. So, again, like, yes, you got more leads for less cost on Google Ads, but not all leads are created equally.

Alex Jonathan Brown
17:33 - 17:54
And that's where it's so important to, like, have conversations or include these explanations in your reports, especially the first time you're creating them and not just throw data at people. Because then you get questions like the ones I ask, which aren't always helpful for everybody. Anything else we wanna do here before we move on to the next kinda our next little reporting look?
Hannah Jordan
17:54 - 18:00
No. I think we can jump into the next.
Perfect.

Alex Jonathan Brown
18:00 - 18:14
So I told y'all it was gonna get more complicated. Hannah, kinda walk us through everything that we're seeing here and help us start making sense of all of these lovely little trivial pursuit pies.

Hannah Jordan
18:14 - 19:13
Yes. If it's not obvious. I love data. I could no nerd out about it all day long. I like to ask questions. So, like, yes, we had this many leads. Okay. Well, then what channels were really driving those? What did that channel breakdown look like? Once we understand that, it's okay what content within those channels is actually starting to drive this performance.
And so this can really give us an idea of, you know, what content is performing well in one channel versus another. If we think about Google's typically like a lower funnel intent, versus something like a LinkedIn can be kinda more, you know, people aren't necessarily on LinkedIn to get your content, so keeping it a little lighter.
Even looking at, you know, what types of assets seem to be resonating. Like, do we see blogs, ebooks, you know, webinars, and even just between all the segments? So this to me gives kind of like another layer to the slide that we just looked at before, like, you know, this is channel performance. But, like, within that channel, what is the specific components that are making that up?

Ellen Smoley
19:13 - 19:37
And I think this is where you can get super surgical about your targeting too to help understand if we're gonna target on LinkedIn to a certain segment, then here's what the asset types are that work better. So having this data, I would totally nerd out over this as well of just understanding what types of assets work really good and we should spend our money on to advertise to that group.

Hannah Jordan
19:37 - 20:03
100%. And I think too, like, this helps where if we were looking at, you know, the data that we looked at before and we saw, you know, there were way less leads this quarter versus the next.
If we then drill down to the tactics, it's like, oh, well, we did way more and spent way more on brand awareness last quarter and less than they just do that total sense. So also kind of looking at just the performance map down to how the campaigns themselves are actually set up to perform.

Ellen Smoley
20:03 - 20:19
So would you take this to your content team and say, you know, we've seen some really good success with our ebooks here. We should create more ebooks. Or do you know, how what is what, how do you work cross functionally in departments to share this data?

Hannah Jordan
20:19 - 21:05
Yes. So that's kind of exactly what we do, where we look at what's working and how do we replicate more of that.
So we'll go and kind of take either, like, the actual content itself or even the asset type. Right? Like, if all of a sudden we notice, like, hey, ebooks and, you know, reports are making up quite a bit of it, but we just really don't have much other content to put in.
So that's kind of why most of it is being spent on these. Can we develop some other types of content that then we can try to incorporate and see how they do performance wise? We'll also kinda break this down even by the different segments.
So if I'm looking at enterprise, how does that content consumption change in LinkedIn versus a mid market sized account? So really kind of trying to pull in all these different data components to understand what's gonna resonate most with these audiences.

Ellen Smoley
21:05 - 21:34
I think, next month, we are gonna talk about on our Coffee Break repurposing and reusing content. And having this data to understand what your audience is interested in and what's converting and what's working is a great place to start when thinking about how to repurpose your content.
And so if you're needing something that came from an ebook, then perhaps you create a webinar from that. And so you've got the data to back up why you are creating specific pieces within, that associate to that really good working piece of content. So this is interesting.

Alex Jonathan Brown
21:34 - 22:31
So this might be a little bit in the weeds, but the kind of costs that we're looking at here are for spend. So are you, if, are these campaigns set up in a way where if you would have thought about these charts before the month, you would know this is basically what we're expecting.
And then there's like, oh, did we really spend what we were planning on? Or are these numbers defined by the way the campaigns are set up? And then if, you know, 20 more people than you expected clicked on you need b two b ad tech, we see that number go higher, and then we're making decisions on how we balance that moving forward. So, basically, is this data that we use to look forward, or is it data that we use to look back and decide how well the things that we're doing have been working? I worded that really poorly.
Hannah Jordan
22:31 - 23:44
No. You're good. It's a great question, and it's set to spend right now. It's kinda hard to see, but, like, it says optional metrics under the top. So you can actually like, what I'll do is flip this for spend, and then I'll look at clicks, for example. And so let's say, okay, we spent what looks like, you know, a pretty decent amount on whatever that category is right there, like ebooks. But then we didn't actually see clicks on that.
So then it was kind of like, okay, well, then do we need to change our spend? So that's a little bit how we use it to look forward to where, like, if I do change these versions or impressions, am I seeing that same percentage shift of spend, equally? Because if I'm not, then something's kind of off there.
And then how do we use it to kind of essentially do it the other way? It's really, I plan out my campaign's content by looking at the pipeline attributed to specific pieces of content as well. And so, hey, did this generate pipeline last quarter that we ran it? Yes. No.
If yes, was it a high enough percentage? Then we'll use it in this one going forward. So it's a little bit of, like, using the pipeline data to kind of guide it, and then I use this to make sure, like, okay, is that piece of content still performing in the quarter, and make changes as needed.

Alex Jonathan Brown
23:44 - 24:37
Got it. Okay. I think we're moving on. Y'all, it gets more complicated from here. Look at all this data. So we got a lot going on. I think we've got slides to break out some of these individually. But just from what the kind of huge overview we've got, attributed pipeline by quarter, attributed close won by quarter, total qualified responses by channel, total total qualified responses and investment by channel, total qualified responses by tier, person records acquired by channel, and person records acquired by qualification.
Hannah, what? I know it's all valuable. I know it's all important. I know there are lenses through which I can make decisions based on all of this. But, like, who is seeing this and where do you hope they start?

Hannah Jordan
24:37 - 26:30
So, typically, I and my team are looking at this. And the reason that so, like, the two charts that you see at the top, those are my screenshot charts that I'm gonna take to the CMO.
Essentially, what those are saying is how much pipeline that was generated in a given quarter was attributed to our digital touch points, and that's broken down by channel. As long as it's going up, that means I'm doing my job, and I get to keep my job, essentially.
It also helps me argue for more budget because, look, it's going up. Give me more money to invest, and it'll keep doing that. So this is great shot charts for the CMO. The next ones are really more of an efficiency metric. Right? Because let's say, you know, we had a record breaking Q4, and we drove all these qualified responses, which again are the right people at the right accounts. But it cost me three times as much money to drive two times the QRs.
We're really not being efficient with our marketing spend at that point. So that's kinda what the next level of charts are telling me as well. Once we get down from there, tier is really how we're doing our ABM motion. So, like, our tier one accounts are our best in class top accounts that sales has identified and the marketing team is gonna surround and go after as well.
Tier two, next best, tier three, so on. So, typically, like, because we do operate a account-based model, they want to know that we do have coverage and are driving things within our most important accounts that we've identified.
This is kind of my sales metric. When sales is like, are we actually supporting these tier one accounts? I can go back and say, yes, sales. We are. Here's all of the qualified responses we gotten within your accounts.
And then the bottom one, again, is just looking at database health. So personal records acquired just means net new into the database. So we can kinda see, like, one, are we growing our overall database with new contacts? And then two, are those contacts qualified? Yes or no? So top level CMO, as it starts to get down, that's a little bit more like efficiency, and then finally, sales metrics.

Ellen Smoley
26:30 - 27:13
Yeah. I think we zoom in into the total qualified responses by channel, on the next which is part of this big report. So we just wanted to kinda zoom in here and take a look at this one. Because what I love is that we could throw a bunch of money at a specific channel.
We've got a bunch of leads for it. But like we mentioned at the beginning of the call, if they're not qualified, it doesn't really matter. So we wanna make sure that this is something that we're all looking at and the total qualified responses to really understand the quality of those channels. So I love how this one gets broken down a little bit more, and that's this. The metric that you mentioned at the top of this call is that's really overlooked. So that's why you've got it broken down here.

Hannah Jordan
27:13 - 27:33
Yep. Exactly. This also helps us too if we think about, like, yes. We started to do content syndication, and then we can kinda understand, like, okay. It's great at driving QRs. Do we now see that converting to pipeline in the next quarter with the chart at the top? So kind of a good way to understand and see, like, what's actually going to converge to overall what I'm going on is pipeline.

Ellen Smoley
27:33 - 27:52
Sure. And then the last one that we have here is the pipeline by quarter. So you were saying it kinda flows into that to understand, okay, content syndication, maybe it's not the biggest on this chart. Maybe page search is, so we should put some more money behind there. But tell us, how do you look at this? What are some decisions you make when looking at this chart?

Hannah Jordan
27:52 - 29:05
Yeah. So this kind of tells me, earlier, I think you asked a really great question too. Like, how do you decide the different investment by channel? A lot of it got does kinda come down to this data where based on basically the total percentage that gets made up from digital, like, here we can see, you know, 2.3 or 4.2 was from paid search. So paid search does get a pretty solid amount of our budget. I wanna say it's, like, 45%. Then we can kinda see, like, okay. If paid social was, you know, 785, we'll just run up to a million, then that would get, like, 25%.So kind of understanding if we invest x, is that going to translate into pipeline, in a way that also makes the investment make sense? So that's a little bit what I use this data for as well. And then also just kind of understanding too, like, what is your overall business impact? You know, pipeline's a big one for sales.
So really being able to show, hey, here are all the different levers we can pull if we're behind maybe in overall pipeline. If we need to be more targeted and specific, then let's maybe pull in, you know, more of a per paid social where we can get to that account in person level targeting. So just a bunch of different ways to kinda slice and dice it and understand what's working and what's not.

Alex Jonathan Brown
29:05 - 29:34
Ellen, we both did that. I'm about to say something at the same time, so I'll go first. So one thing we haven't talked about is, obviously, we've got attributable pipeline based on all these different channels. Where are you attributing this? Is this first touch? Is it where and how do you decide which one kind of winds up in which? Because I assume some people are both, you know, interacting with content syndication and display at some point.

Hannah Jordan
29:34 - 29:55
Oh, we need a whole another coffee talk for that. But, I'll say at a high level, we're doing a custom multi touch attribution model in which we look at six months prior to the opportunity opening. And then each touch point will get an attributed value based on how close it was to the actual opportunity opening.

Alex Jonathan Brown
29:55 - 30:45
Math is fun. And it's it really has been wild over the last little bit to see so many people figure out that, like, hey, first touch probably isn't the, like, holy grail that you want it to be. And also, frankly, last touch, a lot of the time, it doesn't paint the full picture. So it's always interesting to see how people are are creating maybe their own sort of proprietary solutions to, to doing the math and figuring out what works best.
Those are the end of the charts that we have to look through. Ellen, any, how do we wanna wrap this up, I guess? We've covered so much ground. Anything we wanna any discussion we wanna wrap things up with?

Ellen Smoley
30:45 - 31:17
Yeah. I mean, I think if I am watching this, there's a ton of data that we went through, and it gave us some really good ideas on what to take to different departments.
And so, Hannah, just give us one or two tips on how to really think about simplifying this because what we looked at was a lot of data. So at the beginning, we talked about really honing in on those qualified responses. Do you have another tip for the audience just to say, okay, this might be really overwhelming, but start here first.

Hannah Jordan
31:17 - 32:15
Yes. I would say oh, gosh. One tip. I really like to base it on historical performance. So any past data that you can have to kind of, like, drive those future decisions. Again, I'm going on pipeline. So, like, the biggest thing that I look at is I really don't look at lead volume. I am really not as focused on, like, you know, QR even.
I focused on what actually drove pipeline because what we've seen is, essentially, I can have five downloads of an ebook, and all five of those people then actually convert to an opportunity versus five twenty people that download this white paper and one of them converts to an opportunity. The white paper might look better because it's driving a higher volume of leads.
But the conversion from lead to opportunity is really, on the ebook gonna be, like, what matters. So I would say, like, that's the other metric that I would really encourage people to look into is not just kind of, like, lead quantity quality, but also, like, how is it actually converting to the next stage.

Ellen Smoley
32:15 - 32:16
Love it.

Alex Jonathan Brown
32:16 - 33:21
I think that really ties back into your vanity and sanity note from the start of this too. Right? Like, it's so easy to get wrapped up in, like, our sort of vanity KPIs.
And, yeah, we want we wanna make sure as many people as possible see our stuff always. But the check at the end is really what this is all about, and it's finding the places that are gonna do that.
And would you rather have an email that 50% of people open and one person buys from, or 5% of people open, two people buy, and they spend a hundred times with that other person's time? It's the second one. So we are up against time.
Hannah, this has been a whirlwind tour of data. Thank you so much for walking us through kind of your reporting and what you look at and how we can make sense of it.
Obviously, you're at Demandbase. Maybe tell people a little more about where they can follow you, find more about what Demandbase does, and if there's anything coming up or coming down the pipeline for you or a great blog post or something that you think people should check out.

Hannah Jordan
33:21 - 33:55
Oh, yes. So connect with me on LinkedIn. You can find us, you know, obviously, if you Google Demandbase, don't click on our ads. Scroll past it. That's gonna cost you money. 
And that's it. But I always say open door policy. I love to connect. I love to talk about this stuff, talk about the data, and things coming up.
I know our team will be at the Adobe Summit if anybody is going to that and then also Forrester, at the March. So whether it's in person, whether it's online, we are always happy to connect. And, yeah, just thank you everybody for joining and listening to us talk all about data.

Alex Jonathan Brown
33:55 - 33:58
Awesome. Thanks, Hannah. Ellen, what about us?

Ellen Smoley
33:58 - 34:20
What about us? Yes. You can find us at ironhorse.io
And I think next month, I already kinda plugged it, but next month, we're gonna talk about repurposing and reusing content and what's the right way to do that. So look forward to, you know, another Coffee Break soon, which our wonderful host, Alex, will be doing that again next month. So we hope to see you all here.

Alex Jonathan Brown
34:20 - 34:40
We do hope to see you here. Again, we do this once a month. It's always a super chill time. Thanks for hanging out.
Those of you who did today, if you missed parts, you can catch the replay, at our website, ironhorse.io. And until next month, when hopefully you join us again, Coffee Break's over. Let's get back to work. Bye, everybody.

Ellen Smoley
34:40 - 34:41
Goodbye.