The ROI of Jasper: How AI-Powered Content Pipelines Unlock Marketing Transformation

Welcome and Introduction

Loreal Lynch: Welcome everyone and thank you so much for joining us today. Now we are here to talk about one of the biggest shifts happening in marketing right now. How AI is transforming content from more of a tactical task into really the backbone of scalable growth. Now, the latest research shows that the impact isn't just about speed or individual productivity. It's about real business outcomes. That's kind of the holy grail, from higher ROI to faster campaigns, faster time to market, and really being able to measure that bottom line impact.

So I'm delighted to be joined today for this discussion by Lisa Gately and Sean Owens of Forrester Research. And before we jump in, just a couple of housekeeping items. I want to point out that there is Q and A here in the chat, so feel free to continue to add in your questions and we'll save time for those at the end. We'll run through some of those and also we will be distributing recording of this webinar afterwards.

So if you don't get a chance to answer your question, we can also follow up with you afterwards. So without further ado to kick us off, I'm delighted to introduce our first speaker, Lisa Gately, principal analyst at Forrester, who's going to share her perspective on why content is so central to marketing transformation and how AI is really unlocking its full potential. So I'll go ahead and toss it over to you, Lisa.

Industry Insights: Content as the Backbone of Marketing Transformation

Lisa Gately: Thanks Loreal. I'm really happy to be with you all. I want to make a few points grounding us in some of the data. When I look at some of our latest survey insights and findings, it's really important when you look at the context of content, where marketers say their top priorities fall in the next 12 months, it's really showing up how much marketers care about proving impact with measurement capabilities. It's also important that they are better at showing relevance to their audience.

So in looking at how you're able to scale with productivity, how you're able to customize content for the context of your audience, and the third area that we're seeing is how do you enable the business to use your content to advantage? Now these priorities, if you look at what it means, measurement's not a surprise to any of us. When you think about the scrutiny or the fact of we really are favoring the content, that which points to evidence. We're not just looking at programs that lead to activity. We want to show the business that we have some results and value. It's really got to be intentional from the start.

So you're thinking more clearly about what content you have and looking at some of your existing content performance as an indicator for what you're going to do next for a given audience. You're also looking at. It's not just creating more volume or variance, possibly because you can. It's looking at that productivity or the customization or personalization. You're doing that so that you are as relevant as possible for your audience. It really means that that that entails looking at possibilities of modular content, your tagging, your metadata, and how you're able to develop a repeatable system, which we're going to talk a lot more about. I think of that as it's this pipeline so that you're humans and AI audiences are finding you. You're not breaking the message or going off brand. Now, if these are our priorities, you really want to think about what's getting in the way of achieving them.

So if we go to the next slide, I really see this again and again, especially talking to clients. Our data shows it's really an issue more of the human problem, the friction. The topmost issue in the survey data and what I hear throughout. Any marketer who's talking to me about their content is inefficient creation and review cycles. It's also misalignment between sales and marketing and collaboration challenges across the business.

So this is not new. It's been happening for a while. But really think about how the delays, the rework, the missed handoffs keep you from any kind of system or pipeline. It's a signal to us as we think about our future with content. We need to redesign decision rights or think about this more as this pipeline, it's an operating model. How do you get on the same page in better alignment with others so that you smooth this out and you really are intentional and activating from the start. You're doing things like paying attention to this content and how other people across your business are helping get it out there.

And also you're reducing the back and forthing these painful approvals that marketers are always going through. There's a big cost to this. And I would say when you don't get the workflows and the alignment right, when you go to the next slide, this really points to the very same thing, these barriers to content performance. When you ask people what keeps your content from delivering what you expected, it really turns out these inefficiencies in how we handle content and the alignment with humans holds us back.

So this is on us to fix. I really talk a lot of times about how if you are designing or dooming your content performance from the start, you're being very intentional about briefs and working through the whole system with your content life cycle. You got to move really cleanly and have some kind of repeatable process that a lot of people across the business understand and use. You're treating content like a system, so you are standardizing on things and you're governing this pipeline so that more people understand. Here's your audience insight, here's your messaging, here's your branding, and that enables more people to hit that for an expectation.

So given all these findings, I know that tells us there's some operational and cultural barriers. L', Oreal, back to you. I'd love to talk with you more about how we see this as grounds for content transformation.

From Individual Productivity to Content Systems

Loreal Lynch: Awesome. This is very interesting, Lisa. And I love that the research that you share is the same thing that we see with a lot of our customers.

And in particular, one thing I wanted to touch on that I know you and I have chatted a little bit about, is you've noted that many leaders think of content as something kind of like, we use the word basic or very tactical. It's kind of the first thing that when people start to use AI, they use it for content generation. Any tool can create content, right?

So in that sense, you can think of it as basic. But one of the things that we've talked about is I was in the same camp a little over a year ago when I started at Jasper, and I actually tried to distance our positioning from content, you know, full disclosure, because I was like, content's basic. We don't want to be associated with something that's very commoditized in the AI space right now.

And so we talked more about marketing transformation more broadly. But the reality is, as I work with more and more customers, I know you've seen the same thing. You know, unlocking AI for content is actually the thing that you need to do first before you can really unlock AI transformation more broadly across marketing.

And so what I wanted to ask you about is, you know, how you see content as sort of the backbone of that marketing transformation? Like, do you agree with that note notion, first of all? And second of all, how are you reframing leaders when they think about this?

And maybe they might be glossing over it as something that's simple or, like I said, commoditized. How do you kind of reframe that conversation and. And get folks to understand that this is actually a big deal and it's central and it's not as easy as you might think.

Lisa Gately: Yeah, I wholeheartedly agree. I am biased, but I agree with you. When I talk to some leaders, it's amazing because I hear them say things like, it's so basic. That's just blogs or my campaign assets. It's a commodity.

And I think of that as no, you really see content is your connective tissue because so many people in your business and your audiences know you through your content. And also for marketing, content is a data layer. So you're really setting up in your AI systems or anything that you aspire to. You can learn from, train from, and really ground and deliver through some of your content. That is doing a lot of good for you, no matter what your aspirations are with other use cases.

So it's very foundational, or you call it a backbone. I think of that as it is really a training ground. It helps you get on track to achieve marketing transformation. I love it too, because it's very visible. Marketers know the pain of this and working on content. Any kind of transformation where people want to know, how are we doing this? Is going to be something that's very evident to different people. That's a good thing. I also think it will raise the bar on content.

So if I'm reframing it for leaders, I think of a couple things really quickly. That content we know is already shifting into distinctiveness. If you put a lot of the AI capabilities into so many people's hands, anybody can create anything now.

And that's also part of that. You know, that transformation is that thinking it's basic is how do we do this, but focus on what is really authoritative. It's unique to us and it really sets us apart. When everybody can create content, everybody can do everything. The other thing I talk about reframing for a leader is they may not realize how fragmented their content reality is. There is so much inherent waste, unintended duplication. There's a lot of friction, as that data I was just showing really revealed our operating model. There's a chance to simplify and get your whole team refocused on other things where you are not making more, you are orchestrating better and you're getting focused on more market presence, deeper account penetration or new audiences that you haven't been able to reach. That's where you want to take your marketing team.

Overcoming Bottlenecks and Scaling with AI

Loreal Lynch: Yeah, it's interesting and I think like, kind of along those lines. Another thing that I know you and I have chatted about is when it comes to adopting AI and starting to transform AI and especially your content machine people often start with tools and they will onboard tools and think that a simple solution and it's gonna be a quick fix. Just get everybody a license for ChatGPT or Cloud or whatever other tool and allow them to. They're off to the races and they're creating content.

But as we've worked with our customers, we've seen that the transformation doesn't happen from just having individuals create one off pieces. It's not a matter of improving individual productivity and being able to write a blog post a couple hours faster than it would take you otherwise. It's really about orchestrating systems. Content is really an entire campaign system that requires a little bit of a different way of thinking. It's thinking from, you know, from one offs to being a systems thinker and also revamping your processes around what the content production lifecycle and content operations look like today.

So I'm curious how you help leaders also think about that about you know, moving from individual assets to more of like content systems or content pipelines as we've been calling them.

Lisa Gately: Yeah, I love that because you know, you're right of we got so caught up in going faster and just the, the initial awe the past couple years of now thinking about how do you channel it so it's not an advantage just at the individual level, but your whole team, your whole organization. And so I also talk with a lot of leaders about yes, you can go out set people off to the races with a tool but you really want to show up as one company. You're really supporting your brand. You're really helping people see your best, your messages, the best of your stories and getting into reuse smart relevance and that that really entails, like you said, it's, it's all about systems rather than yes, we, we've been living through helping individuals get used to this new way of working and I think it's now you better be thinking more about how does the whole team, whole organization have a more standardized workflow from for this.

And it really gives you like you said, campaigns are a system. Once people make that leap to campaigns you want to have that reinforcement and presence so that you're building in a way that gives you broader presence in all the places and it's a lot more durable. You're not so fragile working at the individual level.

Loreal Lynch: And so double clicking like on the campaigns example. You know one thing that you kind of alluded to in your research at the beginning of the call is the inefficiencies and where Content presents a bottleneck. And so thinking about things like, oh, you know, I can only do one tier, one campaign a quarter or I can only accommodate so many campaigns because ultimately what it comes down to is not having the resources to be able to scale and people lean on, you know, having to scale with agencies. Or like you mentioned, personalization. I can only do so much personalization and everybody else gets just the basic, you know, just the basic messaging, but I can only personalize so many assets.

And so I think that's one thing that we're seeing AI be able to unlock is really that scale. But again, what, what skills do you think are required in order to break through with some of those bottlenecks?

Lisa Gately: Yeah, so this is a fascinating one. We've got data on this where I was looking at a cohort of leading adopters and I see this as two things setting people apart. First, there's the focus on upstream content strategy. A lot of people pick that apart and think, oh, we got that.

But it really reveals when you really talk to. And I see this again with clients, you've got some upfront focus and consistency of capturing, defining your audiences, your messaging, using a brief and having all of your work flow from some of that rather than such subjective bottoms up type of work. The other thing, the second area is really excellence in operations.

And there was some really rich data on this of things. You might expect that sometimes as marketers we get pieces of this right? Everything from like having a master calendar to using combination of systems and integrations, getting at a diverse set of metrics so that you understand relevance and quality. Not just are we counting activity or really trying to flip to, you know, the, the very basics of what we've done for years and years. Getting into finer grain about how you adjust things in your campaigns and content. I also look at this as the this. These are teams who had repeatable process. It was happening before generative AI, but they brought those good habits in.

So I think if many of marketers could learn from those habits, that's how you're going to enable decision making about. Don't just go bigger with variance and personalization because you can. You're going to figure out where are some cases to go do this and be precise, have that effort where it matters and you're really connecting. Everything downstream gets fueled and you've got some repeatability across the team. It's not left so that individuals are making decisions case by case.

Ensuring Quality and Resonance in AI-Generated Content

Loreal Lynch: I love that. And you just said a minute ago two of my favorite words with respect to content and especially AI generated content. You said resonance and quality. The keyword quality, which is a big one.

And I've already seen a couple questions come in here on the chat on how do you avoid AI slop when it comes to scaling content. And I think that's one of the big challenges is that as people are moving from this sort of one off content generation into scale, how do you make sure that you continue to build content that resonates with customers, resonates with target buyers and that also is high quality. That sounds authentic, that sounds like your brand.

So how are you seeing successful customers approach that?

Lisa Gately: Yeah, I love this one because right now we're seeing this big shift of anybody can say anything, that's the slope. You can accept that you're getting some really mediocre outputs and maybe people are under pressure with deadlines. But I see this as this is where the human shines. You can use AI as your thought partner. You should have drafts and briefs and there is some upfront thinking that fuels this.

And then you are instilling, I'll call it proof. Not just the promotion or mediocre type of content or images, just to get by. You really are going through rounds of concepts and tuning things. Ideally you're also understanding your audience enough.

So what makes it really distinct when you're going after different members of the buying group? How do you look at what different Personas or different roles need? Also you're looking at your customers. You understand your current customers really well if they're a proxy for things. All of those things we for all time marketers have talked about. We need more proof points, we need a lot more of the juice or the grit.

But now buyers can find things so much easier on their own. Help them, help guide the decision, give them some comparison content and be really clear about differentiation.

Loreal Lynch: Yeah, yeah, that makes a lot of sense. And another thing we talk about is, you know, how much the context matters. The more context your AI has, the better the output is going to be.

And so when you talk about things like audiences, like I know something that we put inside Jasper is we actually have the ability to map an audience Persona to a particular content output so that it understands who you're writing for. And it has all of the details of that demographic and, and I think that make those types of things make a big difference when it comes to scaling. So it doesn't just sound kind of generic, one size fits all, but it's really kind of customized to the audience so that it is more resonant and then kind of one of the pieces that I wanted to get to, which I know you alluded to, is on when it comes to the measurement. It's easy to say to a cfo, we'll be so much more productive with AI, But I think one of the things that you're, that you're really hammering home is that the bigger opportunity for marketers especially is growth.

And so what is your perspective on how CMOs and other marketing leaders can position AI not just as a little bit of like a productivity tool or a cost saver, but as a driver of true growth? Top line growth?

AI as a Driver of Growth, Not Just Efficiency

Lisa Gately: Yeah. The cost savings are becoming table stakes and it's, it's really hard talking to some leaders about time savings, particularly if they're not so close to the work. I know when we talk amongst ourselves as marketers, it is impressive, it makes a difference.

But you've really got to educate the CFO and all other leaders about how does this give you the possibility that you're going after some things that you weren't able to do? It is like you say, could we do an additional campaign or could we be very targeted about a new audience, a new Persona we need to go after. We're piecing together the data about how that engagement and how the, the presence in front of that audience or going into a new market for that matter, is going to make a difference for the business. I also look at this as so many, so many times over the years I've seen data points about marketers who focus on net new buyers, which we need to do, but they maybe aren't giving such attention to the growth and retention of existing customers.

So again, like you said, not one size fits all, but how you could manage to do those things and really quantify value of what you were able to do for leaders in a way that they understand that more as it's growth, it's protecting revenue. There are a lot of different levers from the financial point of view, beyond cost or time savings.

Loreal Lynch: Absolutely. And one thing that we've seen just more just very tactically in terms of how their kind of customers are transitioning from efficiency into growth is for example, like campaigns. Like if you're able to get a campaign and market 50% faster using AI to scale the content bill of materials, well, what does that 50% mean? Well, if you flip that to say Instead of just 50% faster time to market, what it means is that now instead of doing one campaigns, we can do two campaigns and then we get the top line growth from each of those campaigns.

And so that's a way of kind of flipping an efficiency story into a growth story. And we're seeing that happen more and more as marketers kind of get more sophisticated with the way they're looking at these efforts. And so I think that that's very compelling. Similarly, like, you know, we're seeing a lot of. One of our key use cases is personalization of email.

And so we're able to see that it's not just that you're able to personalize faster and you're able to do, you know, in a week what used to take you months. But if you flip that and you say but what is that getting us in terms of engagement or response? And we're able to see that, you know, it's 2 1/2 x response from customers.

And what is that? What does that actually mean for your pipeline? The fact that more people are responding, more people are engag.

So I think there's small pockets where we're seeing this start to emerge as kind of the norm, which is exciting.

Lisa Gately: It really is. We're flipping some of our habits or we're also seeing it the past year or two about like you say it has been for us as marketers, we want to see the months to weeks. That's exciting.

But now we've got to get to what's next and then the greater why for other leaders who maybe aren't as close to this work.

Loreal Lynch: Absolutely. So I have one closing question before we transition over to. To Sean, which is that, you know, what's next? Like, what's what's next on the horizon? Where do you see AI taking content and marketing over the next, you know, two to three years?

Because things are moving at lightning fast speed. So what are you seeing and you know, what are your spidey senses telling you?

Future of AI in Content and Marketing

Lisa Gately: Yeah, the wild ride is going to continue that we know with AI you'll have more creators across the organization and we'll step into everyone being a creator. And I see that as for a marketer, you can be a smarter orchestrator. That was kind of our opening thought, I think of that people throw around the term content intelligence. I see that opportunities if you're investing in the metadata, being able to capture and read signals and even putting in these efforts on governance. We were talking about some of these different things. You want to make sure your content has the right substance and structure because of how much both humans and AI are important in. Are we, are we surfaced? Are we even at the table? Are we in there for decisions, the way that our buyers and customers work. I, I see that as people keep talking about what does this mean, you know, in, in terms of your visibility. I see this as yes, you want to be visible, you want to be authoritative. That's going to eclipse volume that we as marketers have really thought about. How do we crank out more variants, go after more audiences. It's no longer about who can publish more and be faster. Like we were just saying, it's not the time story, it's can we do this with this quality and the relevance that we really show up with the proof and the perspective and precision?

Because that is going to help us. If we are showing that we're deserving of this for our audience, they start to trust us and we find ourselves being part of that shortlist or part of their preference. That's really going to be valuable for marketers.

Loreal Lynch: That's huge. Awesome. Well, amazing, Lisa, appreciate your insights as always.

And you know, we kind of were touching there at the end on measurement and roi. And how do you look at measuring the impact of some of these, you know, content operations efforts when you scale content with AI and you embrace AI for content generation. And so we recently engaged with Forrester and with Shift Sean on doing a study, a research study on what the ROI is using an AI tool like Jasper to scale content generation.

And so without further ado, I'm going to turn it over to Sean who's going to share the results and the impact of that study.

Forrester ROI Study on Jasper

Sean Owens: Thank you Loreal. Sorry, I couldn't find my share button there for a second. So here we are. Thank you so much and it's great to be here and thank you everyone for joining today. I'm Sean Owens, manager and principal consultant with Forrester's TEI Practice and part of the engagement team delivering the TEI of Jasper.

So today I'll cover a quick intro about TEI if you're not familiar some key to some key details about the study and then dive into some of the business benefits of Jasper in more detail so that you can consider your own business case of Jasper. First, just a couple of details. This is an abridged webinar based on a full case study. I won't be able to cover everything today, so the study will provide a lot more detail and I encourage you all to check that out. The study in this webinar were commissioned by Jasper but independently produced by Forrester.

So Forrester's TEI methodology is based on common cost benefit analysis tools that you're probably familiar with present value ROI analysis, but it adds the pillars of TEI flexibility and risk to help ensure more conservative and credible estimates in the analysis and identify, quantify, unquantifiable benefits or future strategic and process improvement opportunities. For example, a flexibility benefit might be an option to expand Jasper to other departments in the future, which is an example I'll I'll show for as part of this study. This provides a more complete view of the opportunity beyond immediate financial returns and help helps you with investment decision making.

So a TEI study is based on interviews with active Jasper customers. This firsthand information is summarized as a composite organization to simplify the explanation of costs and benefits, but also to allow the results to be published by Jasper in a public case study. As I said, we interviewed customers. We interviewed four customers all at organizations that have adopted Jasper. They are large organizations with global reach, billions in revenue and hundreds of employees using Jasper across their marketing teams. Based on these customer interviews, the composite organization is not exactly average, but a typical representative organization that we've used for the financial modeling in the study. It's a company with 46 billion in revenue, 53,000 employees, 300 users of Jasper and that are creating more than 31,000 content assets each year. Keep these composite numbers especially in mind as you consider the results that I'll go through this TEI and so that you can consider how Jasper might impact your own organization.

So kind of in summary, interviewees reported common issues such as and as Lisa showed earlier, content creation is a key measured pain from our survey data and interviewees agreed it was difficult and slow to create content largely from scratch and also some didn't always feel comfortable contributing. Brand reviews required a lot of rework trying to remember brand standards for memory or reuse a similar asset that would introduce errors because you're just replacing names and missing them. And the use of external agencies was expensive. They were used to help with content creation backlogs as well as other services like translations.

So these organizations saw an opportunity for improvement, implemented Jasper and have enabled key benefits such as content can be created faster and be more inclusive of people like sort of self described non writers or non native English speakers. Brand reviews require fewer approval loops with AI brand guidance and templates and agency costs can be avoided as efficiencies gained and Jasper features like AI translation help keep content creation in house without having to add more staff. So for our composite organization these are the benefit the results of benefits for the three year analysis period. Risk adjusted benefits range from 150k to over 2,150,000 to over $2,000,000 per year. Sorry, over the three year analysis period that equates to a present value of 3.4 million in total benefits again for the three year period and an ROI.

And an ROI of 342%. So that's great news, but I don't expect this to be actionable for any of you yet. So we're going to look at how the benefits are calculated so you can understand the context and how you might estimate the benefits of Jasper at your organization.

So first, as I mentioned, we quantify and financially measure benefits based on that composite organization. So let's look at first at faster content creation. So for the composite, creating each of more than 31,000 assets largely from scratch takes a long time and introduces errors that can lead to multiple rework cycles. Jasper enables marketing teams to accelerate creation by an average of 80 minutes per content piece. Automating repetitive and time consuming writing tasks, users can produce a high volume of content more efficiently. Efficiently, 80 minutes may sound like a lot, but most content pieces can take hours to develop.

So this doesn't mean automated creation and the result of AI slope, but it allows workers to shift their focus from repetitive tasks, routine production and looking up standards to the strategic, creative, interesting and impactful work. So for the composite organization, this adds up to over 2 million in benefits over the three year analysis period. And the 31,000 content pieces. That's a number along say with your average marketing employee salary that you might use to customize to customize and measure what more efficient content creation with Jasper might mean for your organization. A second benefit here.

So not every content piece requires a strict brand review, but when needed it could take hours and multiple iterations to review and get final approval. Jasper helps the composite organization enforce brand standards across teams and regions, reducing inconsistencies and the need for rework by 50%. By aligning content with templates and custom AI brand voices, Jasper minimizes the number of revisions.

And for the composite organization, this adds up to a three year present value of nearly $150,000. And outside agencies, as I mentioned, were used to keep up with schedules and provide specialized services. And I noticed at least one of you mentioned this issue in the Q and A.

So I hope this will be useful and actionable. But with Jasper, efficiencies and built in features such as AI translation help marketing teams to generate this content internally, maintaining both quality and speed. This shift reduces the need for outsourcing that cost $400 per content piece on average, adding up to nearly 1.1 million over the three year period for the composite. Those weren't the only benefits identified by our interviewees, but they're the ones that were most impactful and able to be measured. There are other benefits that they have experienced but haven't yet been able to measure or haven't tried to measure yet, as well as some future opportunities that have been identified but haven't been planned out yet. First, as I mentioned, non writers and non native English speakers can collaborate and create content at the same or nearly the same level as others. Greater brand consistency and quality can be achieved faster and potentially new campaign launches can drive growth and leveraging Jasper for more than just marketing content such as finance or customer success teams that create valuation reports and customer case studies can help expand the deployment and benefit and impact of Jasper at the organization. These are unquantified in this TEI study, but do look at the full case study for more details and you should add them to your own custom business case if you can gather data for any of these.

So every ROI result does need to include costs since that is a part of the equation and we have estimated cost for the composite implementation and ongoing management are relatively minimal. A few people for a few weeks initially and a few hours a week for things like keeping templates and AI tools updated with the latest standards on an ongoing basis. Annual subscription assumptions for the composites 300 Jasper users are estimated but do talk to Jasper for specifics for your own organization.

So the total 3 year risk adjusted present value of costs is a bit less than $800,000 for the composite. So all up here are the results for the composite. Now with I hope with a bit more context and understanding behind these totals. Again 342% ROI, 3.4 million in total benefits and a net present value which is benefits minus cost of $2.6 million. Again the positive results are based on those benefits involving time and cost savings, creating 31,000 content pieces plus reviewing brand standards for 2,500 of those and bringing 1200 back to in house development.

And these are metrics you can research and collect at your own organization. And again as I've talked about several times, building your own custom business case of Jasper as part of building your own custom business case of Jasper. So now to wrap up in case you wanted to come back, there are a few business case definitions and then I just wanted again to say thank you for all of you for your time. Please do make make time to go look at that full study and I'LL hand it back to l'. Oreal. Thank you, l'. Oreal.

Loreal Lynch: Great. Thank you, Sean. That's. It's awesome to see. Obviously, I love it.

But hopefully it's helpful for everybody on the call as well.

Audience Q&A: Human and AI Collaboration

Loreal Lynch: One question did come in just now, which I think is really interesting. They say Kelly says. One additional benefit I would think would come up is business continuity.

Because if you think about, you know, Jasper as a platform, that is kind of the, you know, the system of record for all of your context, your brand context, your sort of intelligence that gets infused into all the content that's generated as employees move to new roles. The brand knowledge is all kind of secure in one centralized platform. So I'm curious if that's discussed as one of the.

Sean Owens: Definitely. We discuss it as one of the platform benefits. I don't know if it came out specifically in the study or if it's something you want to speak to, Lisa, as a benefit that you're seeing with customers more broadly.

Lisa Gately: I see that that's a very astute observation, because when you talk about the pains of rework. You naturally have people moving around the organization or in or out. And it does take time to get up to speed of what already exists. What things? The nuance of how you talk to different audiences or getting up to speed on brand voice and messaging. That makes a lot of sense to have that continuity. That's also part of, like you said, it's the human side of how you're working with others and on your content.

Loreal Lynch: And so I actually want to, like, go a little deeper on the human side, because another. Another question that came in is kind of this misalignment across teams, which is interesting because I think everybody agrees that content is critical to driving revenue, that content is critical, critical to marketing. But yet there's still this misalignment sometimes between teams that persists, and it ends up being like a productivity drag.

And I think it comes down to just disconnects the way that, you know, teams are incentivized, systemic issues as well. So do you want to speak a little bit to that, Lisa?

Lisa Gately: Yeah, you hit it. I see this in many organizations, we know that you have perhaps complex portfolios or as people have moved through different roles, unclear decision rights. And many times I hear marketers tell me, more people get added, the more visible the content, the more you want different people involved.

But then you also encounter people don't have a common criteria. What are you reviewing for? What does good look like?

And I was recently talking to somebody about how she wished everyone in her organization knew what's good enough to ship. What's the baseline for what you, what are you really looking for? Instead of so many people going back and forth all the time. Those are all good things. Like you said about how do you clear up the misalignment? The other thing would be by the time your content, if marketing has worked on something, if sales or other functions persist in using their own content, you've really got to cross the aisle or talk to your closest teammates about what is it that they would rather have or what is it do they know about the content. We find that also unpacking some content waste issues. There's not one issue. A lot of times people can't find the content. They also may get something and realize it's too hard for me to take it and customize it. I have to almost rebuild something if I'm going out to a customer meeting.

So you also look at what are the ways that other people can take what you have and customize as they need to. They're not all working in the same systems. So that's another thing. These systems that don't talk to each other and as you said, they don't persist in having any intelligence about your audience, your brand voice, your message.

And so you keep seeing these spirals and it's happened for all time, but people will go off and almost redo or recreate some things that you then have an environment where there's close, if not duplicate versions floating around. So then you've got people who do want to look for what you have and they don't know which version to use.

Loreal Lynch: That's very interesting. And I have two questions related to humans and AI, which are always interesting. So one is, as marketers, should we be thinking about content for humans versus content for bots, or should we rely. It should be skewing towards one audience. I think, like, one thing that I just found recently because especially as we, as we think about, you know, SEO and geo and the new rules of search and discovery, one thing that I found really interesting as I was like kind of doing that research, is that AI engines prioritize credibility.

And you talked a little bit about this, Lisa. But all of the content in order to be discoverable by LLMs, needs to be evidence backed, transparent, clearly attributed to qualified authors. It needs to include, you know, original research, unique data.

And that's not dissimilar from also what humans like. And so in that sense, I think you can kind of Kill two birds with one stone. Although I do think that there's probably a more technical way that you structure your content outputs to make it more readable and indexable by indexable. I don't know if that's a word by LLMs, but I'm curious if either of you have thoughts on that, on how to, you know, if you're creating a marketer and you're creating content, who is your audience? Is it a bot now or is it it. Is it a human?

Lisa Gately: Yeah, that. That was a great one point. Because we're now looking at it's both. The reality is we're now in the stage of it's got to be both and you hit on the very thing of where we can add great substance and really do these things for all time. You're right. It's not different that we've talked about doing this. We haven't always been doing it. We haven't always been doing it.

But then also structure. So if once you have the quality, the credibility, you're doing these things that show off data, all the things that make something real, proof, not just promotional, fluffy content. It's very useful then for both humans and AI. AI, as you said, in crawling your site and going through all of this content, make it recognizable. If you're using schema markup, you're partnering with others across the business chunks of content. Think about lists, tables for all time. You know, we know our H1s, H2s are doing a lot of work for us, but having labels you start to see on a lot of client sites, I'm looking at, they've got key takeaways, or they've almost got this table of contents like way of showing what's on the page so that both humans and AI can recognize what's there. Is it what you'd expected or looked for?

And the tagging, again, we've known for all time that we should be doing this. It helps. So also you talk about like you're going out with, let's say, content across multiple formats because you're showing up in many places where your buyers are. That you show up with that level of consistency in all those places matters too.

So as you start thinking about the variance, we are not showing up very differently or flat, and we don't have gaps. If you talk about the audience, members of the buying group, different Personas and content by stage, I talk, I know marketers talk about having content that full funnel. In reality, lots of times you have gaps or you know that you need to refresh.

So it's also paying Attention to how consistent and comprehensive a story. I recently was talking with a lot of people about topic clusters. It's not a new topic, but in being able to have some kind of model, if you're putting that in action with your team, I'd encourage that way.

Loreal Lynch: It's interesting, I just on that as you were answering that, two follow up questions came in that are similar, which is, you know, if bots are now an audience, should we formalize them as Personas? And somebody else said they heard on a podcast this week that Our brains register LLMs as search engines, even though they're not. And as we prompt and work with LLMs, we should speak to them as we would with a person or like a new associate that you're trying to train.

So thinking of the full context, the key details that they're going to need to own. So it is a little bit different engaging and interacting and building content for an LLM than it is just for a search engine because there's sort of that reasoning aspect. And then another question that's like somewhat related has come in which I, I think I want to end on, which is what is the role of a human content creator or copywriter in this AI era?

And my perspective is it's more important than ever because they are the one, they're kind of the, you know, really the backbone. They're, it's not even human in the loop. It's human at the helm that's helping to be able to scale these content systems.

But want to turn that over to both of you just to see how you would answer that. And if you've seen this play out in organizations, let me take a crack at that first.

Sean Owens: Yeah, there was a recent report shared among our team about, I think it's McKinsey and Stanford and their, I think they coined the term AI slop. And, and there were some data and, and, and details and case study examples around how AI slop is impacting work. And what it really sounded like was poor training and, and maybe unengaged employees because they were allowed, you know, they were using AI and then just handing it to their next person in, in line.

And that person felt like they were having to deal with it. So, you know, I hope I highlighted that in, in my, you know, my examples that, you know, Jasper wasn't being used to automate the process, it was being used to help with some of the repetitive parts of the process. But it still required a, you know, a human to, to write, to create, to polish, to finalize and make Those decisions and you, you know, you can't just take what AI gives you and, and go with it.

Loreal Lynch: Yeah, yeah. It's so interesting. And I, I shared this story recently on my LinkedIn, at my LinkedIn, but I was actually hiring a copywriter for Jasper.

And it was interesting the, the process of evaluating candidates and what I was. Because everyone, I said, well, obviously this needs to be someone who's very AI centric and who's thinking about how to incorporate AI into their workflow. And so I asked that question, like, how are you using AI? You know, how are you incorporating AI into your workflow?

And I got a range of answers and some of them were more on the sort of individual productivity. And that's where we talked at the beginning about going from pieces to systems that create pieces. Because some individuals responded like, well, I use it to ideate or to overcome blank page syndrome.

And that's not bad. Like, that's great. It's a great way to use it.

But I think when thinking about, okay, well I'm going to create the gold standard and then we're going to scale this. What do we need in order to scale it? We need to make sure that we have the brand voice, the brand standards that we have, the audience, the key audiences that we know, the structure of the content that we have, the best practices baked in, that we have that institution, institutional knowledge and figuring out what is needed in order to build a system that can then be governed as it scales to maintain that quality bar across everything.

And I think that's a key skill and that's one way that I see the role of the sort of the copywriter, the content creator as a human evolving is being able to be more of that systems thinker. But yeah. Lisa, did you have anything that you wanted to add to this?

Lisa Gately: Yeah, I love that. And I would add that as a systems thinker also you know how your organization as a system works. So if you're thinking about where to get good interviews, where to get good review feedback, other experts in your company who have a point of view or can help you in discerning accuracy, fact checking always, but also developing this further, knowing what your audience wants to know so that you have really great answers for things, but also you're anticipating you are one step ahead and have a unique perspective in your marketplace, in your category. That's the real, not only your, your qualities of the best copywriters, but you think of that very systematically. All those tools at your disposal and all the people who also help you very exciting time for those of us in marketing and, and in content.

Closing Remarks

Loreal Lynch: And we could, I feel like we could go on forever talking about this, but we are at time. So I want to thank you, Lisa and Sean for Sarah sharing your valuable insights with us. Thanks to all of you who joined us today. What we've seen very clearly is that AI for content is not just about efficiency. It's really about driving measurable ROI and unlocking that growth across the entire marketing engine.