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Clearbit: Analytics Expert Julie Beynon on Measuring Content · Content, Briefly

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• 1:20
  [upbeat music] Hey, everybody. Jimmy here with another episode of Content Briefly for you. Very excited for today's guest. Kind of a, a change in pace from our normal episodes.
• 1:30
  We have Julie Beynon, head of, uh, analytics at Clearbit. I was about to say head of content, 'cause that's usually who we talk to. Julie, thank you so much for doing this.
• 1:37
  We're gonna talk about data, analytics, attribution, stuff like that today. Would you mind just first kinda introing yourself? Tell us a little about who you are and the work that you do. Sure. Yeah.
• 1:46
  So, um, it's funny that I'm on a content podcast because, uh, I started my career in marketing and writing some of the content, and, um, I was so bad that my boss would line 99% of my work.
• 1:59
  Um, so I needed to find another career. So lots of respect for those of you that kept on that path and are good at it because it's very hard. Um, so based in Toronto. I've been with Clearbit for past almost five years.
• 2:12
  Uh, I work directly with marketing chiefs a lot on the analytics function, so it's my favorite role is really supporting marketing 'cause there's lots of requests, there's lots of curiosity, and the data really can drive quick decisions.
• 2:23
  It's been an experience. Mostly worked with marketing. I'm now branching out more in engineering, uh, but still stay close to the marketing team.
• 2:31
  And could you give us an overview, [clears throat] excuse me, an overview of Clearbit for folks who aren't familiar with the, the product and the company?
• 2:38
  I like to say you give us a little data, and we fill out the rest. So Clearbit is, is that data enrichment platform that helps marketers really use their data in powerful and meaningful ways.
• 2:48
  So we give the tools, the UI, the way that you can take that piece of data and use it for prospecting or use it at any stage in your funnel. So it, it makes your data go to work for you. Cool. I love it.
• 2:58
  We use Clearbit for a few things. We use, um, Reveal to, like, it basically shows you which- Love Reveal... you know, people are, or it basically shows you the company, otherwise anonymous visitor is who's on your site.
• 3:08
  And then Clearbit Connect is an awesome Chrome extension for finding email addresses, and I think there's a couple other kind of engineering as marketing apps out there that are quite useful on their own but also sort of give you a sense of, like, how you might use Clearbit in a more kind of, like, higher scale way.
• 3:23
  We do a ton of work with Reveal, so I'm glad that you brought that up 'cause that's a big part of the attribution and how we know what's working and what's not. Oh, interesting. Okay, cool.
• 3:31
  You know, we ask everybody on the show about reporting, analytics, attribution.
• 3:35
  We've had some really fantastic answers, but one thing that does come up regularly is, "Oh, we have a data team or a data person that helps us with that."
• 3:43
  So it's like we give them the hard questions, and then they're able to give us answers back, which is great, but there's like a kind of a whole black box around that.
• 3:52
  Since the audience here is, like, primarily content marketers who are like, "Maybe we can use spreadsheets," you know, but, like, probably not much beyond that, could you give us like a primer on, like, what does analytics look like at a company like Clearbit?
• 4:02
  Kinda like what does your day-to-day job function look like? Yeah. So we're on the smaller side on the analytics, so my job, uh, stretches across a lot of pieces.
• 4:10
  And I think the first piece and the most important is tracking and tracking correctly.
• 4:14
  So I have my hands in that and making sure that we're collecting the data for the, you know, if we do a new e-book, have we tracked it properly?
• 4:21
  And then getting that data from the tools to a place where I can actually do something with it. So we can track it. It needs to get into... For us, we use Redshift.
• 4:29
  So we need to get that data from that, that code segment into Redshift, and then from Redshift, that's where I really start to do my work, uh, 'cause once we get the tracking, that's sort of the initial setup.
• 4:41
  Once the tracking is set up and it's getting into Redshift, I don't usually touch any offers from there.
• 4:45
  We do a lot of work on transformation, so my job is to make the data that our marketing teams sees a lot less techy. [chuckles] Like- Yeah... a lot ugly underscores and snake case and make it sort of more human friendly.
• 4:59
  Do a little bit of the combination of joining four or five different sources of data into one, so it's much easier for the end user to access that data and to really get the answers that they need.
• 5:09
  So I do a lot of transformations in, in tools like DBT.
• 5:12
  You know, depending on where the person wants to work with the data, I either send it to their tool, so we have ways in which we can take that pretty data that we've made a little more user-friendly, and we can put that into the tools where our marketing team is.
• 5:24
  So I put a lot of data into Salesforce so that our content demand team can access that information, um, on a per contact, per account record and see what they've done, what they've read, or if they want a more in-depth analysis, we just do it in Mode, uh, which is our BI tool.
• 5:41
  Got it. Okay, cool. I have so many follow-up things, uh, to ask you there. [laughs] So let's say, so the content team is working on a new campaign.
• 5:48
  Like, I'll actually, I'll call out Clearbit's, uh, data-driven marketing and data-driven sales as, like, really wonderful examples of, like, large content projects, really good stuff. Yep.
• 5:56
  So, like, say they're gonna do data-driven whatever the next thing is. They, do they come to you and say, "Okay, this is the project we're working on, and we wanna trackYou know, what- whatever the primary metric is.
• 6:06
  Like, in that case, it might-- maybe it's a, it's a newsletter subscriber or a, a PDF downloader, whatever. And then do you have like kinda like a list of questions you run through? You know, like where will it live?
• 6:16
  What other, like, accessory metrics you wanna keep track of? Yeah, that's a great question. So I think it depends on the offer type.
• 6:22
  Um, so what I mean by that is if it's a new-- it's just an additional e-book, we sort of, we have the playbook for tracking it down. Here's the fields that I need you to set up.
• 6:30
  Here's examples of how we've set it up in the past. And then they work with someone on engineering to make sure it gets tracked properly.
• 6:35
  So if it's an existing offer, if, let's say, you know, we've been doing webinars for a while, but when we started with webinars, that's where I was heavily involved of how does this work? Where does it start?
• 6:47
  And really making sure I understand what it is that they're doing, and what are the components of it that make it unique. So, you know, do we need to add an additional field to track something that's different?
• 6:57
  You know, one example is they attended or not, right? That doesn't- Mm-hmm... exist in e-book.
• 7:01
  So very simple, straightforward things of just understanding what is this offer and what happens when someone does it, because I may not know all of those cases. Um, and then working through like, what do you wanna know?
• 7:11
  What questions do you wanna ask? Okay, well then I need this data. Okay, well then I need that field. But once we've done it once, they don't usually call me beside to say, "We, we have a new offer."
• 7:19
  And then they get like a dashboard or something where they keep track of this? Or I guess I'm kind of assuming that part.
• 7:24
  And then is there a way for them to like slice and dice data on their own as well, or is that something they would come to you for?
• 7:31
  So it depends how deep they wanna go, and a lot of that, um, actually has been pushed into our CRM. I've built a model using DBT of all our attribution touch points.
• 7:39
  So let's say that John at Acme, uh, he's done all of these things, then we, we, we take a look at what was his first touch. Okay, his first touch was he downloaded the Chrome extension. Great. Where did that come from?
• 7:50
  Oh, that came from, uh, Google. He searched in this word. Great. So we know, we know how we got John in our world. And then John downloaded an e-book 17 days later. Okay, interesting.
• 8:00
  So they have all of that data that they can use Salesforce to slice and dice. Let's say that he closed-- it became an opportunity, and he ended up becoming a customer seven months after that initial first touch.
• 8:11
  They're able to look at all of the things he did prior to that, that instant. And so they can look at influence, because a lot of the time, content doesn't usually, isn't the one that pushes them past the post- Right...
• 8:23
  necessarily. They can see, oh, they continue to go to our blog once a week.
• 8:27
  That never converted them, but they continue to go to our blog once a week, and we can look at the impact of specific blog articles on any milestone that's interesting, whether they became, you know, a net new lead or an MQL or whatever definition that we care to use at the time.
• 8:42
  They, they became a milestone, and here are the things they did prior to that milestone. That's super cool. That's super cool.
• 8:47
  I can only imagine the, like, folks listening who just feel like, "I wish, I wish I had that." What makes a marketing team easy to work with versus difficult to work with?
• 8:54
  Like, I'm trying to think through, like, for folks who are listening who are in the content space specifically, I find that most content teams, like myself included, are like quite limited on the data front, because, like, we probably use Google Analytics.
• 9:04
  Like, I probably use like 10% of Google Analytics capabilities anyways. I'm mostly just looking at, like, page views and organic traffic and stuff like that.
• 9:11
  So, like, in an ideal world where I have access to someone who could help me with this, like, I don't even know how I would begin.
• 9:17
  So are there things that you find in marketing folks that make it easier for you to, to do your job, which kinda like ultimately helps them achieve whatever marketing goals they have?
• 9:26
  No one's ever asked me that question. That's a great question. There's the temptation to ask for the world. Yeah. [laughs] Talk to a data person, right? It's, it's tempting to ask for everything.
• 9:35
  Mostly what I try and do with someone that's asking for everything is understand why, and a lot of the times what they think they want versus what they actually- Yeah... maybe need, I don't know, isn't the same.
• 9:46
  I like when people come to me with a problem, and they haven't already tried to solution it themselves, because then we can solve it together on that call.
• 9:52
  And having ideas of how you wanna solve the problem is not, that's not an issue.
• 9:56
  Uh, but it's, if you've already gotten the report perfectly in your head, I'll just do that, and I've found in the past that that doesn't actually answer the questions, and that doesn't- Ah...
• 10:05
  actually give them the evidence that they're looking for, 'cause, you know, if you say do X, that takes me five seconds. Fine, I'll do X, right? But what you really wanted was Y.
• 10:14
  So yeah, I think really being open-minded, understanding the problems that you're trying to solve, the questions you're gonna ask, and people tend to use those more, right?
• 10:21
  When someone says do X, they use it one time, and then I go and look in our reporting tool, and they haven't opened it since I sent it to them six months ago, right? [laughs] Right.
• 10:30
  I like someone that's wants this on an ongoing, like, really understands the problem they're trying to solve, um, and starts with the simple problems instead of trying to boil the ocean.
• 10:39
  So, like, be okay with, "I just need, this is the most important metric for me to go," okay, cool. Now we add this. Now we add this, now we add this.
• 10:46
  And so that works with me in more in an iterative process than a I need it all at once. Yeah, yeah. Okay. That makes sense.
• 10:53
  Do I understand, right, that it, it sounds like Clearbit has an attribution model that includes- Yep... content but is not limited to it.
• 11:00
  So then when content has a campaign to run, it, it's fitting into this larger model where, where you can track touchpoints across multiple channels. Is that right? That's correct, yeah.
• 11:11
  We have everything that we offer and all of the sources, channels, UTMs, all of that is just kinda combined into one big box. Got it, got it.
• 11:20
  Is there-- I've just, like, never had access to a real analytics person, so [chuckles] like, some of these questions are, like, so beginner, but is there, like, documentation?
• 11:28
  You know, like, if a new person joins a marketing team, is there documentation that they're reading through on, like, how to, how to work with you? Yeah, so we've done actually internal and external documentation.
• 11:36
  So for this particular model, there's documentation how to work with me. We just sorta have a channel. There's a form. You fill out the form. We work through it. We talk through that.
• 11:45
  So I'm, um, essentially available to most of the GTM, the go-to-market team, so marketing and sales and customer success.
• 11:51
  And then when we build up bigger models like this, um, we document exactly how it's built, all of the tools involved, and then we do like to showcase that to our customers, so we put that on the blog so that we can see how we built it-How we've, um, how we've made it work.
• 12:08
  So, uh, Janet actually wrote my, uh, my attribution. She was our head of content, and so she wrote, she wrote it for me. So all of those words are not mine.
• 12:15
  It says my name on it, but she's [laughs] the one that wrote it for me. Oh, that's, that's interest- Okay, I'll have to go check that. So Janet is Janet Choi. I've known Janet for a long time.
• 12:22
  I used to work at this company Vero, and, uh, I ran content there, and Janet ran content at Customer.io, and we sort of, we were enemies essentially. But, but then we... 'Cause we kinda, like, had the same job- Yeah...
• 12:32
  at, like, very similar companies and anyways became friends later. Do you have regular meetings with sales, marketing, content, anyone else?
• 12:41
  Like, we ask this to everybody on the content side because we just wanna understand, like, their sort of cadence of communication and kind of what those meetings might look like.
• 12:48
  Do, do you have that, or is taking the data, build the dashboard, and then there's not really a need for it to be sort of discussed on an ongoing basis? So I have weekly, bi-weekly meetings with, um, our marketing ops.
• 12:59
  So I kind of consider marketing ops as that extension, um, to the analytics team. Um, our marketing ops, we're very lucky, um, is incredibly talented and incredibly analytical.
• 13:09
  He's able to handle a ton of the stuff that I would normally handle. Yeah, I work very closely, pretty closely with him, and then the requests come in and, um, join the weekly marketing meeting.
• 13:20
  So I'm there if there's any questions or new campaigns. So I just like to keep a pulse on what's going on and, and I can jump in if I need to. [laughs] Is there a such thing as too much data?
• 13:29
  Like, I, I'm wondering from, like, the creative perspective. You know, like, some of the things that- Yeah... Clearbit has done are, like, I... Out there is not the right term.
• 13:35
  But, like, you know, when, uh, Clearbit launched data-driven marketing, which was, I, I think the first, like, huge content project that you all did.
• 13:42
  You may not have an expectation of what's gonna happen, and you sort of have to let the creative juices flow and just, like, see what comes out of it.
• 13:47
  Do you find in your work that there's sometimes too much, or is part of your job kinda, like, reigning it in so that you can focus on the things that are actually important? Yeah.
• 13:55
  So I have a problem where I love to, like, build really cool things that maybe we're not ready for. [laughs] So as, as I've grown in my career, I've learned that simple is best, less data is best.
• 14:07
  For me, a litmus test that I've done a good job is when people are asking. They've gotten enough data to not be confused, and then they wanna know follow-ups.
• 14:14
  So they now know the answer to this, this simple question that they didn't know before, and now they have a follow-up question and want another sliver of data, and that's when I think it's successful.
• 14:24
  So I, I have found giving too much data, nobody asks questions 'cause they're just c- they're looking at it confused. Mm. They don't understand it. It doesn't make sense.
• 14:32
  And then when you just sort of, you just spoon-feed little bits, works for the brain, right? I got this data, now I wanna know this. Okay, now I know this. And they start asking me for the data.
• 14:40
  So it's more collaborative than I'm telling them what it is you need. That makes sense. That's really cool. Kind of a follow-up to that, there's this common trope in the content marketing world.
• 14:49
  Go something like content marketing is really hard to measure, you know. Therefore, we need to wait six months, or we need to do this or that, and I myself am hugely guilty of that.
• 14:58
  Like, I used to do sales for a content agency. Like, a common question on a sales call would be like, "How do we know if it's working?" Mm. Have, like, a kind of a workaround answer for that.
• 15:07
  A- and part of that is because, like, I personally am not able to give you the data to tell you that.
• 15:11
  Do you think content marketing is hard to measure, or is that cliche developed because content marketers are just limited in their ability to do the analysis themselves? That's a great question.
• 15:19
  I think there's elements of content marketing that are quite easy to measure. We're actually coming into a new problem, which I'm, I'm excited to learn how to do this, is ungating really big pieces of content.
• 15:31
  Oh, interesting. So gated content, like form fills for e-books, super easy to measure, right? Uh, they fill it out. We know they did it. Great. We can look at that. Done.
• 15:40
  Now that we're gonna have a ton more ungated content, that's where I've started building Reveal, which is our product that sort of helps track anonymous.
• 15:49
  And we move less to a contact version and more to an account-based version to track the impact of content by influenced on account level and see the, the kind of progression that the content takes for, for a different account.
• 16:03
  So n- when you gate the content, super easy.
• 16:06
  Like, I can tell you to the penny how much money, uh, an e-book has directly influenced, and that's because it's the one that they signed up with, they became a lead, and then they ended up becoming a customer.
• 16:16
  I can tell you. That's direct, and there's always more dollars attached to that. Like, the direct- Mm... impact is the lowest number.
• 16:22
  That's, that's the least impact because some people do an e-book download after they've done a free trial. The e-book doesn't get the money for that one.
• 16:31
  We just get the, the number of names we got from that form for that e-book. Easy.
• 16:36
  So influence is gonna be more on the account level, less on the kinda direct dollar value, but we will be able to tell which ones are best at driving opportunities, best at driving customers because we have, we have that domain level tracking pre-form fill.
• 16:53
  Right. Yeah, that's interesting.
• 16:55
  I, I've talked to many, many content marketers over the years who have gone down the attribution rabbit hole, and, like, each one kinda comes up with a new way that they feel is, like, the way to measure.
• 17:09
  But inevitably they fall a little bit short, and I think part of what those folks are trying to do is, like, justify the spend. You know, like, content marketing is a creative pursuit.
• 17:18
  It's fairly expensive, and so they're, they're trying to justify it in that way. The, the pattern that I notice there is that they all fall short. Like, is there a correct way? You know what I mean?
• 17:28
  Like, in your mind, is there, like, one, like, correct way to measure content?
• 17:32
  Or, like, something I have certainly recommended to folks, which I'm sort of curious to hear your take on, is, like, a good data point is one that everybody agrees is pretty darn close.
• 17:40
  But, like, everybody has to be on the same page that that's a good data point to shoot for. Yes. Yeah. I think the first is that you're not gonna get it accurate, and to your point, it's like it's close enough.
• 17:52
  That is one of the hardest things to drive in. Yeah. 'Cause you can get-80% of what you need with quick 20% effort. It's that last 20%, that's where it's not good enough unless it's 95 or 96 or 97. But if I...
• 18:08
  I'm happy enough with 80. 80 to me gives us direction, especially with all the tracking issues and the privacy. You're never going to get to 100%, um, so you're going to be spinning your wheels and frustrated.
• 18:19
  That agreement on 80, 85%, whatever, where- whatever you feel you can get being good enough is the first key. [laughs] Yeah. Yeah.
• 18:27
  That has taken a long time for me to get comfortable telling people, "I'm not going to get you this answer perfectly."
• 18:34
  We're lucky because we're able to tie a lot of, like, pre-known sessions, so, like, unknown sessions to once they become known into our world, we can tie those nicely together. We tend to quickly agree on the metrics.
• 18:44
  The one thing is I like to do direct, and what I mean by direct is I can say link it with a very linear line. Um, a lot of people want influenced.
• 18:53
  And so, uh, when we're doing a lot of the global, like, global company-wide stuff, we do direct. Like, I, I know that this direct number is the lowest number that I'm gonna give you. It's probably higher.
• 19:04
  And then influenced helps us kind of more on a smaller team basis decide, like, okay, this tiny piece of content actually influenced $150,000 of net new pipeline this year or whatever, right?
• 19:16
  And so we start to decide and work on new ideas.
• 19:20
  Uh, but we would never put that in the company because you would have, you know, $17 million of pipeline was generated by content, but that's, you know, a lot of overlap and it's not consistent. Yeah.
• 19:32
  That's so interesting. Is content harder than other channels? Like, in my mind, uh, paid ads are just easier because it's just like- It is easiest... there's a dollar in... Yeah, okay. So that's true.
• 19:41
  'Cause content marketers say that a lot, and, like, I think it's true. [laughs] Paid is the easiest, and content touches paid, right?
• 19:46
  Content, content helps with a lot of the paid work and houses the content that some of the paid ads are being sent to, right?
• 19:52
  So the paid is sort of a source that drives people to the offers, and then content builds some of the offers, not all of the offers, and then content does a lot of the website work.
• 20:02
  So content's involved in all of it, kind of how I feel trying to justify more dollars for analytics, right? [laughs] Mm-hmm. Content is just required for all of those campaigns to go and the website to work.
• 20:15
  So when, you know, direct dollars by content is the absolute lowest, I probably multiply it sometimes by like five or six. [laughs] Yeah. Yeah.
• 20:23
  But when- whenever possible, if you can gate the content, if you can find some way of, like, grabbing some form of email or doing it, that is how you will get the most.
• 20:33
  That is the easiest way, and it's, it's as easy, in my opinion, as paid. It's an ungated content. That is where content marketers struggle and where, where I myself do struggle as well.
• 20:42
  There's a little bit of manipulation in the data, uh, to make it work. Yeah. That makes me feel a lot better actually. [laughs] Is, um, is Google Analytics part of your tech stack?
• 20:53
  Like, do data professionals look at that and be like, "This is so oversimplified, built for a non-technical person. Like, we need something, you know, we need a better, a better way to, to get this data and look at it"?
• 21:04
  Yeah. I personally don't use Google Analytics, but I love it, and our team does. And for me, it is a great, uh, troubleshooting tool. So when our, our team works pretty heavily in Google Analytics, they're self-serving.
• 21:17
  Nothing is, you know, reported to the whole company from Google Analytics, but they can get their day-to-day understanding. I work really hard to match my data to Google Analytics. Okay.
• 21:28
  So I don't want to be too far off of that. And I've told our team, "If you're seeing a report that I'm sending out versus Google Analytics and they're very far apart, something's wrong. That shouldn't be the case."
• 21:38
  Got it. So I have a love relationship with Google Analytics that it sort of keeps me honest. Yeah. Yeah. That's really interesting.
• 21:45
  Are there other tools in your tech stack where the con- a content marketer might be an end user, like Google Data Studio, or, you know, any other tools that, like, the content team is actually interacting with?
• 21:57
  So our content team is quite technical and, and they, they use Mode. Okay. Very technical BI tool. It's not, it's not a Tableau. But we usually do it collaboratively.
• 22:07
  So I'll help them build out the query, I'll get them the data set, and then they'll dig in and do a ton of the work themselves.
• 22:13
  And maybe it takes two or three hours with me for them to get comfortable, but then they have that data set and they...
• 22:18
  You know, I've watched, um, in one of our newest pieces of content that's gonna come out shortly, it's all about data, and our content person blew me away with how much she was able to solve on her own, and I went and just validated the data for her, obviously, to, to check.
• 22:31
  If it's mission critical and it's a task and they need to get the data, I'm happy to sit with them, and then it seems to be learned a lot faster. Got it.
• 22:39
  So part of that is just, like, learning curve of the tools themselves, I'd imagine.
• 22:43
  Is the ability to write SQL queries, like, is that the next thing if you're a content marketer that wants to be able to wrangle data a little bit, or is there something else that you might recommend for, like, the content marketer who's like, "Okay, I don't have a data person or a data team, let alone that."
• 22:55
  So, like, maybe it's tools, maybe it's skills they could start to develop that would help them do some of this on their own. Yeah, I think you can get a lot of answers with Google Analytics. I j- I genuinely do.
• 23:04
  I think, um, a really sophisticated setup with goals and conversions inside of Google Analytics gives you a lot of good insight, and like I said, I like to make sure, keep myself honest and our, our goals and conversions are close enough that it does indicate, you know, the number from one to five match, right, of the best performing- Yeah...
• 23:23
  pieces.
• 23:23
  Maybe we, maybe this one says 50, and this says, you know, 37, but we know that those discrepancies are gonna exist because one is on a server side, which is our own data that we own, and one is a third-party tool, and it's just not gonna match, but it gives us the same answer.
• 23:38
  Right.
• 23:39
  So I think really setting up a Google Analytics or whatever web analytics tool that you have, the Mixpanels of the world allow you to kind of set up your own tracking code on certain events, and you don't need to spend a ton.
• 23:49
  I know those tools are more expensive. Google Analytics, I used to only use Google Analytics and Excel [laughs] to- Oh, wow. That's cool... really answer my questions.
• 23:58
  I do think if you have a data person, then all of the data should be in your data warehouse, like a Redshift or a Snowflake. But if you don't have that, Google Analytics is a great way to start.
• 24:07
  I'd always say as soon as you can own your data, which is owning it in a data warehouse, do that.
• 24:12
  It makes life a lot easier, um, making sure it's all kind of first-party data.Helps with the accuracy and helps with a lot of, um, the reporting.
• 24:21
  And as you grow and you transition tools, you own all of that historical data, and you can move it where you need it to go. So... Got it. Okay, cool. That also makes me feel a lot better, actually.
• 24:30
  [laughs] I wanted to ask you about AI. How is AI gonna affect all this or, or already affecting it?
• 24:35
  Is there a future where the content person just, you know, writes a query like they would in ChatGPT that queries the data? Every data team that I talk to or that I've been on, 80% of our queries are pretty similar.
• 24:48
  Um, so I don't think it's hard to program a lot of that, and you just kinda input, "This is the webpage, this is this, this is this." Yeah.
• 24:56
  I don't think that that's that far-fetched to see a tool maybe not necessarily super AI, but a UI where you can pre-build, um, your SQL based on a lot of standard queries that everyone does. Right.
• 25:09
  It could, it could work. I think the, the one thing that people forget is that data literacy, like, there's learning the actual tech, right?
• 25:15
  There's learning how to s- do SQL, but then every single data storage-- Clearbit's data is not the same as Customer Data, not the same as, you know, Sale- Salesforce's internal data. They all are set up differently.
• 25:27
  They're all configured differently. They're all tracked differently. You have to learn that, and that takes a lot of human-based learning. So I, I don't know how that would work.
• 25:36
  I'd be impressed to see someone do it and have it be accurate. Be more often wrong than right. [laughs] That's very interesting. Okay, cool. No, that, that's very interesting.
• 25:44
  I had kinda mentioned in the beginning, like, I don't know what I don't know.
• 25:47
  Are there things that are, like, top of mind, especially related to, like, you know, our audience, content marketers, but the things that are top of mind related to, like, the way that you might work with a content team that I don't even know that I should ask you?
• 25:58
  I enjoy when content teams, uh, would like to dig in themselves and have that curiosity. So I like when the teams view data as part of the research and digging in. And so you research the topic, you understand the topic.
• 26:11
  Data can seem intimidating, but you're truly just researching, but on the other side, right? Like, you're just research- Yeah, yeah...
• 26:17
  the same things on the other side, and I'm always happy to facilitate a bit of the research. But I love when someone asks those curious questions because they've done all the work.
• 26:26
  And so working with the content person who asks maybe what they think are embarrassing questions, but I don't think that way, right?
• 26:33
  And so they've asked me a question to ask the data that gets us the whole answer that I wouldn't have gotten myself.
• 26:38
  So yeah, just that openness to exploring and researching the data as if it's part of the content or, or however a content person researches. Just- Yeah... same curiosity. Super cool.
• 26:49
  One, one thing that we talk about a lot in the content marketing world is this kinda like loose, loose idea of, like, content marketing culture. Like, some companies have it, and some companies don't.
• 26:58
  It can be manufactured, but essentially what it is is top-down buy-in on content so that the team can flex their creative muscles, like, do really cool, bold work without somebody constantly being like, "Well, how much did that cost?"
• 27:10
  And like, "How are you gonna justify this and that?" You know? Like, some companies can do it, some companies can't. Is there an equivalent in the analytics world?
• 27:18
  You know, like, it sounds like Clearbit is quite bought in to, like, making data-driven decisions.
• 27:22
  Like, I'm assuming that more and more companies are kind of heading that direction, but do you find that there's this, this similar thing of, like, kind of like a culture around a company being really data-driven? Yeah.
• 27:33
  I think given that we're a data product, [laughs] that certainly helps. Yeah.
• 27:37
  I've been very fortunate that every company I've worked at has boughten into data and found it valuable, and so that's why I've been lucky enough to have those roles. It's hard to justify the value of the data team.
• 27:47
  I would actually say it's even a bit harder than the content team, 'cause at least there's data on the content team. The, the data on the data team is a little bit hard to track.
• 27:56
  I think to get the company is you have to sort of show yourself as a multiplier of the work, right? So the work I do helps person A, person B, person C be more effective. They get to answer their question.
• 28:07
  And so building a system and a kind of process where I don't have to be involved in everything, and people can get the answers at some level.
• 28:17
  I've built enough of the work that five people benefit from my one effort, so then I've multiplied my work by five. How to build that culture, I think if it doesn't already exist, is really hard.
• 28:25
  The tech in analytics is incredibly expensive to be- Yeah... in my opinion, to be successful, it's incredibly expensive, right?
• 28:31
  You can start free with Google Analytics, but then once you move to Redshift, then you need something to read on top of, like a Redshift or a Snowflake. And then you, you...
• 28:40
  So you need a BI tool, and BI tools aren't cheap.
• 28:43
  And then if you wanna get the data from your data warehouse into another tool, you need a reverse ETL, like a Census, that takes all of that data and puts it into your Salesforce or into your Customer.io or into your Marketo or HubSpot.
• 28:56
  And so, yeah, it's, it... The cost of an analytics team is expensive, and you can't always prove out the ROI. For sure. That sounds familiar.
• 29:06
  That sounds probably familiar to a lot of our listeners who are thinking kind of the same thing about content marketing. But still, companies make the investment, and it pays off. You know?
• 29:14
  Like, you could point to tons of examples in the content space of businesses that have made huge investments in content, and it's paid off extremely well, and I'm sure the exact same is true for data.
• 29:22
  And like I said, I imagine, like, we're only getting more data-driven as it's, like, at, well, one, as there's just more data to track, and two, as, like, world is, seems fairly uncertain these days.
• 29:33
  Like, to have really good, reliable data to use to support some of the probably tough decisions a lot of companies are trying to make would just be, like, massively beneficial, I would think. Yeah.
• 29:43
  And, and the risk of getting it wrong, so you need, you need tools that are reliable and tracking it as close to 100% as you can. Yeah, yeah. Really cool. Julie, thank you so much for doing this. I...
• 29:53
  To, to be totally honest with you, I'm envious of what you can do. I wish I could do all the things that you've talked about over the last half an hour or so. Really not that hard.
• 30:02
  [laughs] I don't have a technical background. I started as a content marketer and then had to, as I said, get my way out of there because it wasn't my skill, and it didn't take long. It really didn't take long.
• 30:12
  I don't have a background in any c- any computer science or anything, uh, just all on-the-job training, so. That's so cool. That's so fascinating. I- is there somewhere that we can send folks to follow you and your work?
• 30:23
  Twitter, LinkedIn, a personal website, or anywhere else? I'm on LinkedIn. That's it. I'm not a, I'm not a Twitter girl. [laughs] Okay, cool. That's good. You're saving yourself a lot of time there.
• 30:32
  Um, and truly, thank you so much. Just, like, what a, what... It's such a nice change of pace for us. Uh, so much, so much good information, and we really appreciate your time. Thank you for having me, Joey.
• 30:42
  Yeah, take care. All right, awesome.