Getting Optimized: Where Data Meets Content

I do think it’s worth calling out that most people suck at tagging and taxonomy today, and it’s one of the biggest problems with doing digital marketing and digital attribution well and getting content intelligence. As boring and as annoying because it learns from our metadata. This is Revenue Makers, the podcast by Sixense investigating successful revenue strategies that that pushed companies ahead. So, Saima, we’ve got something that is a collision, a collision of our interests and strengths. We’ve got data meets content. I mean, I like the adjectives you use. So we had Christine Polivacek, who runs she’s SVP of product marketing and research at PathFactory. And for any of those who know, PathFactory is a content engagement platform that lets you sort of bring in all of your content, understand who’s viewing it, how it influences pipeline opportunities. You can use it for promotion. It’s a really powerful platform. And she’s got a really interesting background running their product marketing team and research, like I said, but came from SiriusDecisions and Forrester as an analyst and stepped back into a practitioner role. So interesting perspective on things. She takes kind of all of what she’s learned through her analyst’s time, you know, working with so many clients, but also just I think she lives and breathes and is so passionate about content and optimizing content and putting rigor around it through content operations, which, you know, a lot of our listeners might not have in place today. And so I think everyone will at least walk away with something, even if it’s a tip and trick on how to start to get more intelligent about the data that you are putting out there around your content, some quick tips and tricks on what to be doing as a first step. And so I hope it’ll be good. Let’s dive in. Let’s do it. Christine, thanks so much for joining us. Looking forward to the conversation. So, wanted to dive in a little bit about you because the story is interesting about you’re running research and product marketing a software company, and we’re gonna talk about content from much more from a data perspective. But can you tell us a little bit about, like, how you got to where you are? Because, again, it’s a fun, interesting story. Oh, gosh. I could spend hours, but I’ll try not to I’ll try to do the short versions. So I’m currently senior vice president of product marketing and research at PathFactory. I’ve been here about two years. But prior to that, I had spent about seven and a half years as an analyst starting at SiriusDecisions and then Forrester after the acquisition of Sirius by Forrester. And I led the content strategy and operations practice there, team of analysts and, you know, ran the research agenda and whatnot. So at Forrester, I ran the b to b content strategy and operations team, and we advise b to b CMOs and their marketing teams as well as often even sales organizations about how to advance content engine maturity with the recognition that it’s a huge and critical aspect of overall digital transformation. And most b to b organizations are even still now behind in terms of upgrading those things so that they can use things like data and automation and AI to drive better business outcomes and create more efficiencies for the marketing teams. There’s still a lot of manual things happening in the content life cycle in a lot of organizations. For sure. Christine, I feel like there’s a cohort of analysts who were doing the analyst thing for many, many years, right? You were at SiriusDecisions and then Forrester, our own Carrie Cunningham, And I’ve seen a little bit of a shifts of then moving back into a practitioner role. Talk to me about that and how you’re taking your learnings from working with so many clients and taking that to your new roles. I love that part of being an analyst. It was a great opportunity for me. I loved the job. I learned a lot. Even, like, younger folks who would come into Sirius or Forrester would say, like, it’s a free MBA, right, when they get to sit in on these advisory calls that we’re doing and such smart b two b leaders that we’re talking to and are exposing their strategies, their data, their political challenges, everything, all the warts. So I’ve learned a lot from that and have been able to apply it now in this role, which I’ll speak to in a minute. But the reason I wanted to come back into the practitioner world is because, one, I had been doing that for seven years, And I do and then this is not any flack on any of my former analyst colleagues, but I do feel like there’s almost like a skill apathy that can happen if you’re not actually in the action and doing the work and actually solving the problems. It’s there is a lot of value to analysts and consultants, but they get to walk away. They don’t have to stay and really deal with the ugly. And I’ve always said I have this passion and consider myself a professional problem solver. So with everything that’s been happening in the market and all the change around the criticality of content and the content engine, I wanted to be able to actually have an influence over that in a product and see if I could bring to life the things that I think we need as we move into the future as marketers. So I had a passion around that. But, you know, just as an aside, not to go on too long, but I was a practitioner before Sirius and Forrester too. Right? I started way, way back early in my career at, like this isn’t even on my LinkedIn because it’s so far back. I’m, like, dating myself. You know? But as a PR assistant in a high-tech firm, I even did some investor relations for a while, and then I finally landed at TechTarget as an assistant editor doing tech media. Right? And I’ve I say I was doing content marketing there before they called it that. Driving traffic, using organic search, getting subscribers, working with content experts to create valuable relevant content for people, and then measuring all of that, eventually, then eventually then running global campaigns field marketing for a language technology company, doing content strategy work for a couple other big tech companies, and then helping others figure out how to apply that too in the analyst role. So I’m very passionate about content. You’ve been in it. You have been in it for a while. We’ve talked about content a lot. And you mentioned content engine maturity. But what is content engine maturity? Maybe that’s where we start from. Yeah. Yeah. We evolved it over time. When I started at Sirius, there already was something called the content model, which was basically describing the phases of a content life cycle and then the key deliverables and process or activities that are associated with those stages of that life cycle. We evolved that over time as I officially launched a content strategy and operations research practice and built that team there and basically landed at renaming the phases for the four p’s. So planning, production, promotion, so the distribution and activation of the content, and then performance management, which is really all that content ops stuff, the metadata and taxonomy, audits and inventories, curation, the tech rationalization and in integration piece, all of that. For Forrester people, it’s still available to you where you can see that we have a content engine maturity framework and the content life cycle model. Both are important to educate yourself about as marketers and educate other cross functional stakeholders on as well because a lot of the friction and content does come with a lack of understanding internally about the complexity of how it runs. But I would really look at maturity in those four buckets or phases and say, where are you in terms of in the planning phase, having your audience framework defined, understanding, and go into the creative and the copywriting and all of that. And even in the production phase, it’s really important to have more structure and better tools than most people have today, honestly, and have rigor around that. Like, how often do we adhere to forcing people to fill out a creative brief or a content brief in the production phase so we’re not cycling over and over again on expectations and objectives and things like that? Promotion is really where at PathFactory, I’m focused now on activation and insights in the performance phase and how that goes back and feeds planning because you get all that rich data. We’re not as focused on the production piece except for the auto generation of the experiences that use those assets. But that’s really where, you know, my focus is on how mature are you from, first of all, just having an integrated view of your channel mix, understanding what’s performing, what’s not, having good attribution, personalization. What is your maturity around AI and automation there? I also think of distribution is where I say, like, well, maybe it’s planning, but moving away from the buyer journey and really thinking full customer life cycle as you’re going through all these phases. And then the performance management, which is that content ops piece, Adam, that you were talking about, you know, I’ve been evangelizing about it for literally over a decade now because as we become digital marketing centric, you cannot do it well if you don’t look at content ops like you look at marketing ops. All your content is tagged and has good metadata. You manage your repositories. That engagement data, even the internal utilization data is all feeding into your data models, and you understand. When I was at Forrester, I think it was twenty twenty two, Phil Stavids and I did the future b to b content, time travel, and transformation. And I predicted that by twenty thirty, like, I estimate that about fifty percent of the b to b content engine by the end of the decade will be run by AI and automation. And it looks and I didn’t even know ChattGPT was gonna show up in November. I said that in, like, May. So thank you, OpenAI. But at any rate, there’s just the content ops piece with where we are now with b to b buying behaviors and with everything being so digital centric, it has to become a core discipline within marketing, and it has there have to be actual roles that do that those jobs. Yeah. So that’s you have to look at your maturity across all four of those. And where I often see the biggest gaps are in that performance optimization, performance management bucket because content ops is still a low maturity. Oh, because measurement goes in there too in that piece, and that is still pretty immature. I mean, I did the state of b two b content study three or four times at Sirius and Forrester, and that was always the lowest maturity item, measurement and attribution for content, which is something we’re trying to solve for now. So Yeah. And I almost wanna go deeper on that because I feel like there is such a rush to plan for this content, get it out the door, move on to the next thing that teams aren’t taking the opportunity. Or just putting that rigor in place to go back and say what is working, what’s not working. And you spoke about the tagging and the data and making sure that you’re setting yourself up for success when you are pushing it out. But can you talk about how data is helping shape content strategy on the back end, like that closed loop? And I’d love to get a little bit tactical on that and get your recommendations on, number one, what teams should be doing, but how often should they be doing it, it? And what sort of KPIs and measurements should they be considering? So I’ll start with the last question. So in terms of, like, frequency or cadence, I think it’s going to depend on who’s doing it, who it’s for, because I always think this is like a common theme I keep saying in, like, in analytics and personalization. I’m really thinking of these, like, altitudes or layers of broad granularity we need as marketers to be effective based on kind of the current realities there may be constraints. Right? Like, I wanna do personalization, but I can only really do it at the industry level right now because of the inventory I have or whatever. You know? I think that in terms of what people need to focus on from a data perspective is one, you need to be capturing all of your content engagement data, which is obviously something PathFactory does. So I don’t mean that to be a self serving statement, but you do. And I don’t just mean, like, from your web analytics tools. And sixth sense is a big part of this too. Right? Because we’re partners, and we’re using sixth sense data within PathFactory as well for customers. And they can use sixth sense customers can use custom segments to drive personalization and whatnot, but you also get the back end data around that. And what is the effectiveness of the content and the experiences we’re delivering? Are you looking at your content management, you know, your ops stuff, and tagging your content for things you want to be able to measure by? Campaign, topic, industry, persona, journey stage, and you can assume journey stage, but you may be wrong. But it’s interesting to look at assumptions versus reality as well. But first, it starts with tagging your content really well. For all the attributes, you want to be able to look at performance through that lens and understand what’s going on and see patterns. Second, as you activate your content, you wanna make sure obviously that you’re able to track whatever engagement that’s gonna work through other systems and UTM codes and all that kind of stuff. When you bring it back into and look at it, though, there’s this content strategy element of, like, classic content strategy where I’m looking at my inventory and I’m looking at where I have gaps or imbalances of what I have to support an audience across journey stages or a buying group across journey stages for a specific offering, for a specific industry. Depending on how sophisticated your team is, you may be thinking of a very simple scenario or a very complex one in terms of how you wanna look at the data. But you really do need to formats are working, for what audiences, in what channels, in what sales cycle stages, what really moves things. And it and there is technology out there that lets you see that in out of the box dashboards now. Oh, and the other piece, and this is the six cents part, we have to do that at the account level for anonymous and known. Like, we need to understand the full picture and see as many of the buying signals as we possibly can and not wait, as you guys and Carrie says so often, right, is, you know, we can’t wait for that MQL anymore because we will not be effective at driving growth and pipeline for our businesses if we keep taking that approach. Content data to me in this world, we talk about buying groups, buying signals, the death of the MQL. The anonymous buyer, the fact that so much of that journey is happening before the MQL, and how can you make sure that you are front and center and giving them all the assets and the information they need as they’re educating themselves along that journey. So Yeah. Fully aligned. Yeah. I’m preaching to the choir, but it’s exciting times. I think, you know, sometimes marketers can feel overwhelmed because we’re all under pressure, right, with budgets and deadlines and, you know, resource constraints. And now you want me to deal with my content engine maturity too? Like, I’m just trying to, you know, keep the wheels on the bus kind of thing. Yeah. And that’s that was gonna be my next question for you too. Right? Because I’m sure somewhere in the world today, someone started a job. Maybe it’s Friday. Maybe they’ll start on Fridays. But Monday, maybe somebody’s gonna start a job running a content team or building a content team or they’re coming in and there’s, yeah, we write some stuff and it’s up there and all that. And what you just walk through, you know, there’s so many angles to to it. There’s so many ways to measure. There’s so many ways to go by attribution. Where do you start? Like, okay. Like, the physical, I can create content. Is that hard now? Like, you get some talented folks and you and, obviously, we have tools and all. You can start building the content pretty quickly. But where do you start to actually bring in the vigor and and start to figure out the metrics that are most important? Again, it’s gonna be different for everybody. I just think it would be like, it’s an ocean. Where do I start? It’s absolutely cross functional in nature, and it’s dependent on the team and what they’re working on. So if you’re talking about, you know, like a product marketing team, they’re gonna be trying to use data to inform go to market strategy and and plan. If it’s a production team, it’s like a centralized content team or something like that or an agency that you outsource to. The metrics that they’re going to look at are are just going to be different. They’re probably gonna be looking at more process metrics, first of all, utilization, product to you know, volume of requests, output, things like that. And they’ll wanna look at engagement metrics as well. Although I have to say in a lot of the enterprise that I used to advise, the centralized content teams rarely got data back that was helpful to them. It was like a black hole, and it was almost even territorial sometimes, like people saying, no, you can’t have my data, which is weird. It was just like silos, you know? I think that anyone who’s responsible for activation, demand, and digital teams, field marketing teams, things like that, That’s where you really get into channel performance and account penetration and new accounts engaged and things like that. Have we been able to increase pipeline within specific segments, that sort of thing with our paid ads and all that kind of stuff? Right? And then if you talk to, like, an ops team, it’s gonna be the metrics that they’re measuring themselves by are one, am I able to deliver all these metrics that all these other teams need, and do that effectively and well? But, also, what is my understanding of how well oiled this machine is and what we need to do to improve integrations between these two tools and pass this data between the system and that system. And those become more like operational metrics. It’s more holistic, and I think it depends on the team what they need to focus on. But I hope that actually illustrates the fact that, yeah, one, it’s complex, but two, it’s very strategically important because it affects so many aspects of everything and everyone. Right. Okay. I have a very simplistic question, and I’m trying to have this for the audience to just be a simple takeaway. You look at a lot of content. You look at a lot of content data. Is there any sort of thing that you just see work it works consistently. You do this, you’re gonna get results. Is there some sort of takeaway that if you’re not doing it today, just do this as a starting point? Mhmm. One, in the planning phase, if you need one takeaway, it’s if you are not clear on who the audience is and what the go to market objective is, do not proceed downstream without that clarity. Get what you need to be effective as you move into the other production, promotion, performance, etcetera. In production, I would say the question is, what’s the one thing you can do to mature this area? I mean, honestly, this is where, again, I would have clear processes, creative brief, SLAs agreements on certain turnarounds for certain content types. I would absolutely be using generative AI to support efficiency and drafts and things like that. In promotion, I say the key takeaway right now and is start looking and capturing engagement data so that you can get better at promotion and increase the performance of that for known anonymous and tying that at the account level. That should be the priority if you’re not doing that today. And then using that to drive further personalization as people continue to engage. In the performance phase of the life cycle, I would say it is, like, so old school. I’ve been preaching it forever, but do a content audit and inventory. Go clean up your content. Clean up your tags. Make sure that you’re empowering and enable your enabling yourself for success. You know? So that’s my takeaway. Love it. Really, really easy takeaway, so thank you. Four takeaway. Bonus. So content operations, because this is you know, this one is interesting to me. One, just because, like, at different points in my career having had larger content teams versus smaller content team and just, like, keeping up with just volume. And then sort of seeing over the last couple years as well, this sort of every software company’s got something they’re going after this, Suddenly, content operations platforms that are popping up and all that. Like, when you break it down to its most basic form, you talked about taxonomy and tagging and kind of all that. But what are some of the key areas? Like, I think it become pretty clear when you you need content operations even in small teams because things can get out of control. But, like, what are some of the core focuses outside of just that? It’s obviously moving from step a to b to c and so forth. But what else is there? So bucket content ops as content audit and inventory, metadata and taxonomy, library management or repository management, which is a rel relating to the first two, as well as the the infrastructure. Right? So really understanding, like, what are the tools that we need? What are the integrations that we need to be effective at running this content supply chain, this content engine, whatever you wanna call it? I do think it’s worth calling out that most people suck at tagging and taxonomy today, and it’s one of the biggest problems with doing digital marketing and digital attribution well and getting content intelligence. So that’s, like, my clearing call to the world. As as boring and as annoying as it is and laborious and whatnot, you have to do it, especially as we move into scaling AI because it learns from our metadata. Not just our metadata, but it is a very important element. So all of that, I think content ops, it’s interesting. When I did, you know, a feature vision presentation years ago at serious decision summit, I was talking about I foresee in the future this idea of, like, a content engineer. That’s what I was calling it at the time, although I don’t think that’s what the name will maybe be. But we’re seeing that now, right, where we’re in this world where I can see in ten years from now, marketing in general, the jobs that we do are going to look very different. AI will probably do fifty percent of things we’re doing today, and we’ll replace those with doing cooler things and training the AI. I actually said in a conversation recently, right now, AI is our assistant. Right? In the future, we will be AI’s assistant. It will flip. You said that AI becoming we becoming their assistant. I started thinking about Terminator two, but that’s probably Well, I don’t think Terminator two will happen in media marketing, hopefully. Oh, no. Some days, it could feel like that. No. Just kidding. So let’s go to AI now because how could we not? What and again, like, there’s generative AI started. I mean, it’s like that was, like, the first sort of marketing use case. What’s going on there now versus what you think you’re gonna see in six months in terms of just the evolution of content teams, how they’re using AI, how they could be using AI, and maybe what’s next? I mean, I think over the next ten years, it’s gonna like, I don’t even know what I can’t imagine where we’ll be that far out. But in six months, I don’t know how much it will move necessarily, like, in some sort of dramatic way, but I think there will just be this gradual evolution like a normal technology adoption curve. I think we will hit some point where the innovation reaches the next level of wherever we are. Right? And then there’ll be, like, an acceleration that happens at that point into, you know, ending early majority into late majority adoption. But I don’t think that it’s going to replace everything we’re doing as b to b marketers over the next few years, if I I’m being realistic. I think we’re gonna be living parallel lives for a little while. I don’t know if that’s the right way to describe it, but no one’s moving off MQLs and ripping everything out to replace it with generative AI overnight. That’s just not realistic for any of us. I think there’s going to be this land and expand experimentation and also everyone’s existing stack. Like, all those vendors are innovating with generative AI right now, so they’re gonna have it to some extent, already in their ecosystem, and they already do. There’s already been offerings released. We have a new generative AI product. So it’s happening. You know, I would love to see more, especially on the production side. I think that’s an very easy place to start using generative AI comfortably. I even think there are opportunities in product marketing. Like, I think Liza Adams in CMO Coffee Talk has talked about a lot of the ways that she uses ChatGPT to help her accelerate product marketing work, and all of it’s fascinating. And I think we all just need to be embracing it and experimenting and also looking for what our existing tech stack vendors are doing and we trust the work they’re doing, and we wanna partner with them to bring them in and choose those initial pilot projects and start just getting comfortable. And then at some point, it’ll take off. Right? You you’ll get comfortable. The market will continue to mature, and we’ll get wherever we’re all going together. You know? It’s an adventure. Fascinating stuff, Christine. We have a question that we ask every single guest, so we’re gonna put it to you as well. What is the most ridiculous thing that you have been asked to do in your career? Good or bad? Gosh. Can how far back can I go? You can go as far back as you want. That summer job that you took in high school, you can go. Honestly, because I thought we were beyond it by the time I did this very early on in my career. I worked in investor relations, and one of the top executives asked me to go get his wife’s dry cleaning. And I thought that was outside of the job description personally. So I thought that was a little bit ridiculous. I could tell you more examples from that job, but I didn’t last there that long. Yeah. That’s pretty ridiculous. I don’t think that was in the job description. I mean Yes. Investor you said analyst relations investor relations? An investor oh, and balancing his wife’s checkbook. Yes. That’s random. Remembered that as well. Very real. Wild. Very random. Yeah. Well, that qualifies. It’s the first thing that you Well Thank you guys for having me on. Thanks so much for joining us. Really appreciate it. You’ve been listening to Revenue Makers. Do you have a revenue project you were asked to execute that had wild success? Share your story with us at six cents dot com slash revenue, and we might just ask you to come on the show. 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