Stage Before Strategy: How PMM and AI Priorities Shift as B2B Companies Scale

Building a great B2B go -to -market engine starts with understanding what works and evolving it. I'm your host, Rob Karel, and this is a go -to -market perspective, where marketing and sales leaders share how they're transforming their organizations, foundational best practices, smart trade -offs, and practical AI delivering value and scale today. AI promises to make marketing faster, and it does. The problem is that speed without a strong foundation doesn't produce better output.

It just produces more of the wrong thing faster. We've all been hearing about the founders that use AI to craft messaging on their own. They're excited they no longer have to hire experts when they can focus on demand gen because that's where the real money comes from, right? And scaling companies pump out narratives that make no sense to their buyers, but they were doing it really, really efficiently.

And of course, now we're hearing stories about these same companies reinvesting in experienced product marketing leaders as the cleanup crew to repair the damage that this has caused. Today, I'm excited to be sitting down with Jonathan Pipek, CEO and founder of Blue Manta Consulting, who works across the full spectrum from early-stage founders establishing their first go -to -market motion to mid -market companies trying to scale it. to discuss what product marketing AI looks like at the different stages of growth and why the stage actually matters as much as the tool.

So Jonathan, welcome. Thanks so much for having me. I'm excited to be here. Well, let's get started by just talking a little bit about your background.

So walk us through your product marketing kind of career path and what led you to founding Blue Manta. Yeah, sure. So I spent over a decade in product marketing, working across kind of multiple industries and company sizes so everything from you know fortune 500 insurance mid -market hr tech and cyber security startup and a whole bunch of other startups and smbs and it really kind of gave me a front row seat to how product marketing operates across all kinds of scales from you know big teams that have really mature processes and super established brands to startups that are basically building everything from scratch And for me, I really love the startups phase and also the scale -up phase.

And so I built Blue Manta Consulting. And I kind of get the best of both worlds because I do advising with early stage startups, which is really exciting building from scratch. And then on the other hand, my team and I take on more fractional project -based work. for mid -market companies.

Last year, I also co -founded a second company, which is 3AM Recruiting with Yilin Pei, a well -known product marketing coach out of New York, to help early stage startups hire the best product marketing talent. That's great. And the good news is for 3AM, it looks like they're finally realizing they need that talent. So you guys, Yilin, are absolutely going to be helping them.

Let's get started. Let's just talk about product marketing for that earlier stage. companies. So what's actually needed?

So let's think of that founder that's pre -seed or seed stage. What does product marketing need to deliver, whether it's a full -time or fractional or whatnot? And what is it they're most often getting wrong? So at pre -seed and seed stage, the number one thing you're looking for is product market fit.

And really, from a product marketing lens, I view this as time being critical. So what I mean by that is You don't really have time to do like super fancy six month, three month or six month positioning and messaging exercises. Like you need to move quickly. Right.

And so what I tend to do or what my team and I tend to do is kind of light versions of everything. Right. You quickly research, you know, you create position messaging and you build sales collateral. And the reason why you do it quickly is one, you don't usually have a lot of data.

You don't have a lot of customers. You don't have a lot of buyers. You don't have a lot of close loss opportunities or close one, so on and so forth. And so you want to basically create something and test it, right?

If it's founder -led sales, like have them go and use this material, go and position a message and create a sales pitch so they can go and use. That way you can just continuously test, iterate, refine, and kind of repeat that cycle. And then in terms of mistake, the number one, I'm sure you've seen this too. Like the number one mistake is they fixate and fixate and fixate on the website and they want to get things right.

And I'm like, well, number one, unless you're an outlier of an outlier, you're getting like no traffic, right? Your website's getting like maybe a hundred views a month if you're lucky. And the other part is like product marketers hyper fixate on getting things perfect. And at that stage, like it's never going to be perfect.

Like just. Good enough is great. Get it out the door and iterate. I liked that, you know, founder -led sales is absolutely, usually the success or failure of any seed level is can the founder sell?

But what I often find, and I'd love to kind of hear your thoughts, is how often does the founder feel that their talking points is exactly what the website should say or is exactly what their sales reps should say? There's this... for me, I'll give you my editorial, is that the credibility of the founder is not always translated to the sales rep or to the website. What are your thoughts there?

Yeah, so I think you're pointing out two really important points, which are one, you know, founder -led sales means a founder's talking to a prospect, which is one -to -one. A website is one -to -many, right? So those messages should not be the same and can't be the same, right? It's just not, you can't personalize on a website the way you can, at least.

I mean, with AI, I'm sure. But today, at least, it doesn't make sense to. And then second, yeah, you're right. A lot of times we get founders who have 20, 30, even 40 years of experience in the industry.

They've been at their entire career. They know it like they're back in their hand. And then they get a early career sales rep and they expect him or her to be able to have the same examples, have the same gravitas, the same confidence, the same understanding. And that's just not realistic.

And so I think. The work of a lot of product marketers is, and I say this often, is you really need to democratize the knowledge in the founder's heads, which means making it accessible to the sales reps and honestly just to marketing. So from a marketing and from a sales perspective, we can approach prospects in a way that makes sense and is genuine. A lot of times it looks like talking to the founder and getting three or four really good stories or examples that the rep can adopt as their own.

But yeah, I mean, it's not realistic to expect. a sales rep to pivot as easily to questions and objections as someone who's been in the industry for decades and has been in the buyer's shoes. So definitely have to adapt it. Makes sense.

And I think, you know, as I teased in my opener that there are many founders that feel like they got messaging in hand, especially with AI. Maybe we don't need a product marketer just yet. And legitimately, way before the AI disruption and transformation started happening. Early stages often would just have product folks that also took on the role of product marketing.

So they were building out the requirements and the specs, and they were also doing the messaging and the lunch planning and the analyst briefings or whatever. How often are you seeing in this day and age where founders are delaying the need for a product marketing hire? And is there a cost associated with that? I think the good news is it's getting better.

So I'd say in the last five years, especially VCs have put a lot of, pressure is probably not the right word, but have kind of explained the importance of product marketing to early stage founders. So I think it's more prevalent. So I think it's getting better. But typically, like the most common scenario, just to be frank, that I see is usually a startup after six months or sometimes a year, they'll come to me and say, hey, I just spent 120 grand.

So 10 grand a month is pretty common. 120 grand. And I got literally zero out of it. And what it almost comes back down to is exactly what you just said, right?

The position messaging was either created by the founder or through AI oftentimes. And they were targeting the wrong people with the wrong message at the wrong time, especially if they're selling high ACV products. Like, realistically, an ad is not going to get a $5 million product sold. Like, that's just not.

it's just not going to work. So I think that's pretty common. The one thing I will say, and I think Elin and I have a pretty strong POV on this from the 3M perspective is, in some cases, I think the founder is right in not hiring a product marketer. I really think it depends on the founder.

Here's what I mean. We tend to bucket, and by we, I just mean 3M, we tend to bucket founders in one of two buckets. Either they are a founder who's very technical, so usually they have an engineering background or a product background. They've probably created the product themselves, at least the initial version.

That's kind of founder one. And then the other type of founder is usually more of a commercial -focused founder. So maybe they came from marketing or sales. They've thought about how to scale and what go -to -market looks like.

And typically, kind of the more tech -focused founder isn't great at messaging or pitching the product. When they go and do their one -liner, their elevator pitch, it's kind of difficult to understand. Versus commercial typically is good at that. Again, these are broad generalizations.

When you are a technical founder, or if you just identify with, hey, I can't really explain my value or the product's value in an easy way, 100 % of the time, I think you should hire a product marketer. However, if you're absolutely crushing founder -led sales, you're growing really well, positioning messaging, like when you go and pitch your product, it resonates, you're closing a lot of the deals at like 30 % to 40 % close rate, then sure, go ahead and hire a head of marketing or growth marketer.

and wait till your next level of growth and then hire a product marketer. So I think there is that important nuance, but typically speaking, I think the danger here is you spend a ton on advertising or a ton on demand gen efforts and it's wasted essentially. There's definitely all different types of founders and generalizations that make sense, but just we've all seen history repeat itself when messaging is skipped without the validation through. Right.

win rates and product market fit and other validation okay we're at this earlier stage and the decision is we do need product marketing help discussion so far we've really been focusing on the messaging and positioning piece of it but we know product marketers are often responsible for a much larger remit than just positioning and messaging, whether it's managing launches or market and competitive intelligence or analyst influence or enablement, et cetera, et cetera. So what are some of the foundational product marketing skills and competencies that really are the prerequisites of this stage?

Because not every stage requires all the same skills. Yeah, that's a good question. So early stage deliverables and skills. I guess I'll start with deliverable.

I think this is unique to startups and I think it's pretty difficult to do if you haven't been there, done that kind of situation. But I think it's combining kind of the founder's vision, which hopefully they have a strong vision. If not, you're in for a world of hurt. But combining the founder's vision and probably SME background, right?

They're probably a subject matter expert. with any kind of data you can find, whether it's customer data, buyer data, industry data, something, to basically make an educated guess, right? You're doing a lot of extrapolation and you're doing the bare bones in terms of positioning, messaging, and sales enablement just to be able to have something to test. And ideally, you're finding creative ways to test and iterate quickly based on the results, of course.

But generally speaking, I mean... You need the foundation, right? Positioning, messaging, sales enablement, cross -functional relationship building. Really important to manage your manager, right?

Because most of the time at the early stage, you're really reporting either to the CEO or to some C -suite. And in most of your leadership meetings, it's just going to be you and C -suite, right? Or maybe one rung below. And then the biggest thing I'll say is, in my experience, product marketers also fall into one of two buckets.

Bucket one is, hey, there's a blank sheet of paper or, you know. Blink Google Doc in front of me. I need to do it all from scratch. Let me go and do that.

That's one type of product market. And they thrive in that building from scratch. And then there's a second type of product marketer, which is, hey, you know, the process or the product or the position messaging, it's already established. We're already we're not zero to one.

We're at, you know, 10. But we need to go from 10 to 100. How do we do that? Right.

So. An analogy I always use is building a house, right? So there's some product marketers that look at the empty lot and they already envision the house and they start building the foundation and putting the electrical and the plumbing and the walls and the roof and so on. And they build you the house.

And then there's a second type of product marketer which says, hey, you've been living in this house 10 years. Isn't that great? But now you have a couple of kids. You're cooking more.

You know, should we renovate that kitchen? Right. It's 10 years old. Like, is it time?

And you come in, you renovate the kitchen, you make it much more functional, more beautiful, so on and so forth. And so I think being the first type of product market of that early startup stage is critical, because if not, like nobody's going to lead you to water. Nobody's going to tell you how to get from A to Z. They're not even going to tell you that you need to get to Z.

Like you have to define it all. So it's a very, very big difference between startups and none. Yeah, I love that distinction. And it's really those that excel at invention versus those that excel at continuous improvement.

And with scale -ups, there's the risk of throwing away the baby with the bathwater, so to speak. There's a lot of foundational brand recognition, expectation of... the brand and what you're delivering that you can't necessarily throw way down to the studs again. You have to build off of it.

So it is different challenges and different skills. I like how you frame that. So let's talk a little bit about AI. I'm not an AI hater.

I love AI. I'm spending way more on it than I probably should as an individual consultant, but I... Can't say I'm not getting value. It's a wonderful, wonderful tool, but we've all seen the damage and experienced it.

You know, the amount of times that I have to scold my AI for making these ridiculous assumptions, like we've been through this before, Claude, why are you making the same mistake again? So clearly governing your own AI usage and your organization's AI usage, we all know this is a commonly discussed. So let's talk about now the extremes of AI damage. When you and I were chatting about this episode, you brought up these two extremes that I thought were really, really fascinating about damage.

So let's talk about the one extreme you mentioned was about founders using AI as their strategy oracle. So what does it look like when the founder is using AI to validate and prove out that their strategy is going in the right direction? Oh man, that's a big one. And it can be really, really frustrating.

So it basically is when founders are running pretty much everything by AI, and AI will answer them, right? It'll give them a response. But the AI is either telling them, hey, something that's going to please them, right? I think ChadGBT is kind of notorious for that.

Or something so generic that it's kind of useless. In other words, it's not really strategic, right? And the one thing that AI doesn't do, and I think we're all aware of this, but it doesn't form a very strong point of view that's different, that's differentiated. What that means is that if you as a founder, let's say you have a cybersecurity startup and you solve, I don't know, endpoint security, right?

Endpoint cybersecurity. And you have another founder that does the exact same thing, like similar product enough, right? Unless the inputs that you provide that AI are wildly different. when your competitor asks the same thing you did, they're going to get pretty similar responses.

And so what ends up happening is it's not differentiated. And the other thing it does is, which again, we all know, AI does a really good job of making things sound good, but there's a difference between sounding good and actually meaning something. And so you'll get these websites that, again, all created by AI and it looks beautiful, but when you start reading it, you realize, huh, this sounds good, but I have no freaking idea what this product actually does. or who it's for.

It's just so nonsensical or it's so high level that you're like, okay, it increases efficiency. Great. Literally every SaaS product on the planet does that. So what does this product actually do and how is it going to benefit my business?

So I think we basically end up with very bland, non -pointy point of views, very generic, directionally correct strategy, but it doesn't actually make sense for your business. Exactly. And I think AI is great at affirmation. It's like, tell me I'm wonderful.

You are wonderful. Thank you for that. But even the best prompts of saying, challenge everything I say, which it's a good thing to do when using AI, is don't assume what I'm asking is the right question. Don't assume what I'm asking you to review is quality.

When you ask it, it might... give you some interesting thoughts of how to maybe do things differently. So it's a valuable exercise, but it's still not an expert point of view. It's not someone that's going to take a stand and challenge you as someone who's experienced in whether it's a discipline or a market or a technology could do for you.

But it's very attractive. It's like, you know, I just saw the Odyssey. It's the siren song, you know, allows you to kind of feel pretty good about what you're hearing. Right.

But I think to your point, right? So like, even when AI does challenge you, I'll give you a real scenario. Founder, ask AI, let's say Claude. Hey, Claude, I'm starting the founder -led sales process.

Here's my approach, critique it. And sure, it'll disagree with you, it'll give you feedback. But the thing it completely missed was that this founder has gotten zero sales, they've gotten zero product feedback, and they're not ready to go to sales. Right now, they need to be doing betas and pilots.

And so that's the part where, sure, if you ask it to critique, a predetermined decision or a predetermined process it will do that but it can miss like what's the expression miss the forest for the trees right like it'll miss completely that's totally the wrong decision to make period regardless of how good the sales process is Or another one, you know, a founder, this happens all the time. A founder will tell me, hey, I really want to go after, you know, insert Fortune 500 name here.

They're a perfect fit for our business, blah, blah, blah. And I'll say, okay, great. Just out of curiosity, have you sold any of these, whatever the product is? And they're like, no.

I'm like, okay, have you implemented this? Well, no, obviously not because we haven't sold it. And I'll say, okay, do you think, and do you have an implementation team? And they'll say, no.

I'm like, okay, so who does your implementation? They're like, oh, I don't know, probably product. I'll say, okay, have you established a product onboarding process or the implementation process? They'll say no.

I'll say, okay, do you think going from zero to Fortune 500, let's just assume you get the sale, which is already a bad assumption, but let's just assume. Do you have the internal team structure, the internal processes, et cetera, to handle a Fortune 500 onboarding needs from day one? Or would it make more sense to maybe target a much smaller client, figure out the sales process, figure out proof points, get case studies, testimonials? and figure out the implementation process and then go after the fortune 500 right it's i'm not a big you know baseball fan but the the example i always give is if you've never hit a baseball do you want to go and your first batting experience to be at the world series or should you probably go to little league first probably little league right and so those are the things that ai is just not going to at least not today right it's not going to help you think through and it's not going to push back from a from a macro lens versus uh is what i'm doing right now you know correct it's like should you even been doing what you're doing right now right it's like you wanna do you want a fortune 500 advocate or do you want a fortune 500 churn you know even if you somehow win the deal is there anything you've done to keep this customer happy and satisfied or is this going to actually This win is going to hurt your business more than a loss.

Oh, exactly. And we see that, right? We see that where they get the client and or the customer, and then they end up churning in 30 to 90 days because they couldn't even complete onboarding. And it's like, OK, well, and I mean, you're not going to sue them because you're a small startup and they pay the lawyer more than your entire ARR is.

And guess what? They talk amongst their peers and suddenly other organizations are of that scale are going to be like, well, they're not ready for us. So the other end of the spectrum of the AI risks that you mentioned I loved is the founder who uses, you know, they have all these trusted advisors and employees, co -founders and executives, but they use AI to validate every recommendation and option. So the analysis paralysis pattern where it's like.

Well, you've recommended this, but instead of trusting him to put it through AI, who has all these other questions that it's challenging. So I'm going to send it back to you because AI told me you haven't considered these things yet and that back and forth. Yeah, that's honestly, that can be almost just as frustrating for different reasons. I actually had to fire a client a few weeks ago because they would not make a decision because.

What AI does is it gives you so much information that it feels like you can make a really informed decision and never make a mistake. But that's just not reality, right? There's so many data -driven companies, Salesforce, SAP, et cetera, that hypothetically, if all we had to do was make data -informed decisions, then these companies would never make mistakes. And I mean, we're familiar with Salesforce and SAP and other companies that are data -informed that have made mistakes.

What ends up happening is these founders, to your point, they get stuck in analysis paralysis, which means they won't identify target audience or specific ICP. They won't agree to position messaging. They're constantly iterating their position messaging. They're constantly updating their website.

I talked to one founder who his co -founders banned him from updating the website because he had spent, I don't know, months and months and months and hours and hours on it. Sometimes you really can't break them out of the cycle, right? Just like the example I mentioned. But other times, just being frank and explaining the trade -offs really works.

What I've found is, you know, I'll say, look, you're welcome to ask AI for 14 versions of this email. But why don't we just try out two and see what the market does, right? See what prospects, do they respond or not? When it comes to the pitch, let's just try one of these 15 options that AI gave you.

And let's see where prospects, what resonates with prospects and what falls flat. And then we'll iterate. And that typically works well, but sometimes, you know, these founders, they don't want to make a decision because they don't want to exclude part of the market or they don't want to exclude, you know, a specific type of positioning or messaging or copy that will work well. And, you know, those are really tough situations because at the end of the day, especially positioning, it's all just decision making.

And if you can't make a decision, you can't do positioning. Yeah, and I had a recent engagement as well with a CEO who was, you know, kind of calling it a... ideal customer profile and use case whack -a -mole where you know this is where they're focused they're fully you know meeting number one intake number one this is what they're excited about they're seeing great validation from conversations and partners that this is where they need to go and so let's start building positioning and uh you know go to market strategies around that and then One conversation later, or they attend one event where they have a real good, exciting conversation with one individual at some company, the whole company strategy changes because this is what they're excited about now.

So again, it goes back to leadership is about making tough calls and gambles, and you've got to validate whether you're wrong before you switch it. It is a real challenge and product marketing. is often at the whim of leadership. Is there any way you've seen, especially from a consulting, one of the benefits of being a consultant is you're a little less worried about job security because it's a contract, it's temporary anyway.

You may have a little bit more freedom to speak your mind. How have you been able to effectively, like if you have some examples where you've been able to calm this analysis paralysis down? Have you been able to guide any founders or leaders to stability based on the fact that you're bringing in this expertise? Are you having good examples of where they've listened to you?

What I think I've tried to do is use actual data when possible. So sometimes, especially if you're brought in by the marketing leader or product leader, I'm not going to say you want to circumvent the founder, but sometimes you can test things. So what I've done before is said, hey, we think it's either icpa or icpb let's work with the growth marketing team or if they have a demand gen agency in this case it was a demand gen agency to just do a quick email campaign a quick ad campaign because you can get up to you can actually get statistically relevant results that way right for fairly low budget depending who you're targeting let's do a quick ad campaign see how many clicks we get we're not trying to get demos or anything but just literally see the interest in these ads What helps is it directionally gives us some guidance.

And then we follow that up with an email campaign. So, hey, we're going to email, and this isn't statistically significant, but it's directional. It's, hey, we're going to email 100 folks that fit ICPA versus 100 folks that fit ICPB. And then we're going to interview, you know, five to 10.

At the start of stage, early stage, I usually do five to seven. But, you know, the more the merrier. Five to seven, five to 10 interviews with customers, prospects, et cetera, buyers, and get a sense of what's important to them, their pain points. current solutions, jobs to be done, so on and so forth.

And when you combine all that, then you can go to a client and say, look, I know you don't want to make a decision. Fair. We went ahead and tested this anyway. And here's what we found.

And here's what we recommend. So for the next three months, can you trust me? Can we just go with this direction for the next three months? realistically the next six months, but you start them off at three months, see how it goes.

And then we'll pivot along the way. The other thing I do is I'll tell them I'm not a Jeff Bezos fan by any means, but I do like his one -way door versus two -way door analogy. For folks who aren't familiar, who are listening, basically the concept, and I'm sure I'm going to butcher this, but the concept is decisions are either one -way doors or two -way doors. So one -way door is it opens one way.

You can go through it, but you can't go back. A two -way door is like what you see at restaurants, right, where the door goes either way. So you can go in, make the decision, and then you can kind of retract your decision. So with position messaging, especially at the early stage, it's 100 % a two -way door.

So test it, iterate, see what happens. It doesn't work, great. Revert it back or change it to something else. And so...

Those are kind of the key concepts I try to work with founders on, which is let's get some data, let's test, let's iterate, and then we can always pivot. So you're not locking in a decision forever. You're trying it out, you're testing it out, and then you're going to make better decisions as you get more informed, as you talk to more prospects. Yeah, that's great.

And don't worry, I'm pretty sure Jeff Bezos is not yet a subscriber, so you're probably good. Fair enough. Okay, so we've given a lot of love to these early stage seed level startups. Let's talk about scale -ups now.

Let's talk about product marketing as your... growing series C mid -market, let's talk the 50 million to 250 million ARR, give or take. Clearly, you've built a mature business now. You're proven a whole lot of stuff about you're winning something.

So what is the product marketing set of responsibilities and mandate? How does that shift once you get to that stage? This is the area that... Blue Manta focuses on is like that bin market 50 to 250 mil.

And it is completely different than early stage. Because at this point, to your point, you already have an established brand. Prospects are more likely to have heard of you, maybe not 100%, but much more likely. And you're really kind of in scaling mode.

And so what that means from a product marketing lens is that you have to kind of guide the organization on making decisions on how to grow. So that could be, do you add another product to sell? That way, instead of selling one product, you're selling two. So you could maybe cross sell, upsell, et cetera.

You could launch a bundle or combine solutions into a platform. So maybe you have two or three independent products. Do you combine them in a bundle because everyone keeps buying them? So you increase your ACV.

Do you combine them in a platform so they're all integrated on the backend and now you sell a platform versus point solutions? That changes your competitor set. Do you potentially enter a new market, right? Maybe you're based in the US and you go to Canada or you enter Germany or France or whatever.

Those are the kind of strategic decisions that product market needs to work on with leadership to kind of figure out what's the right move based on company goals. And this really, really varies because we work with mid -market companies that are in the point where some of them are being picked apart with young AI upstarts that have just sprung up and they're destroying them, right? So in that case, they want to get market share as quickly as possible. They want to blitz the market and go, go, go and expand to other markets before these folks catch up.

Other times we work with mid -market companies that are established, right? They've been around 10 years. They've grown to, whatever, 250 million ARR, and they're well -known in the space. And they're not really looking to blitz the market because they already have a good percentage of the market.

What they're looking for is improving profitability because they want to get acquired or improving NRR. In which case, we're thinking about things completely differently, right? We're thinking about, okay, what can we automate from a product marketing lens to reduce costs? Onboarding is a very common one.

Or can we start charging for onboarding now to, again, to reduce our costs and increase our profitability? Oftentimes, companies initially roll out free onboarding. Then over time, they get paid or they go from paid to tiered paid onboarding rate. We all have those Fortune 500 clients that want white glove onboarding, so on and so forth.

And then for NRR, you think about cross -sells, upsells. What does that look like? Can we partner with? whoever the team is that's selling, maybe it's customer success, account management, sales, whoever it is that's selling to current customers, like how do we partner with them to identify the right customers to target and then also to upsell them the right thing if we sell multiple products?

So those are the kind of things that product marketing starts thinking about at that point. And then the other big one is positioning, right? So when you are at this stage, you're very oftentimes going from selling one to three products. Now you're selling.

five to seven. And the very big decision you have to make is how are you going to position that? Are you going to position that as a platform, as a set of bundled solutions, as a tiered offering, so on and so forth? And those are the kind of things that we love working on.

That sounds great. And I think you talk about profitability, net retention, EBITDA, if you've got some investors staring down your back. What we're seeing is to get to that profitability, headcount is frozen. Teams are being cut.

And there's clearly the AI mandate says, well, we feel super confident without any justification or proof that you can do a whole lot more with less now. So with that mandate, which everyone's dealing with, and as I hinted at my opening, we're starting to hear some rehiring as that, and certainly bringing in consultants like you and I to help fix some of the problem. But if you're in this situation where you're a product marketing leader or a marketing leader expecting to do a lot more with a lot less, when you're talking about product marketing at this stage, what are the things to focus on?

What do you do and what do you not do? Because a big part of leadership is choosing what not to focus on when you have these constraints. So what would be your top advice for folks at that stage that are dealing with this contraction of resources? Gotcha.

So you're asking for in -house leaders? Pretty much, because they're the ones that are owning the reduced budget and headcount. Gotcha. It's a tough reality, but it's something we're all experiencing.

Well, I'm not in -house, neither are you, but in -house folks are experiencing. What really helps is getting really clear, like you said, on priorities, but also identifying kind of where the gaps are that can be easily taken on by product marketing. So what I mean by that is, let's say you have one person who does the website. Right.

That's it. They do website. And for the majority of the time, they are inundated with requests from the demand generation team. And so you asking them to build an ROI calculator for the website is probably going to be priority number 5000 for them.

In that case, I think it makes a lot of sense for a product marketer to go into Lovable, Replit or whatever their AI tool of choice is and literally build the thing, hand the code over to the web person and have them implement. versus having to think through the entire strategy with them, give them the exact requirements and waiting, you know, three to six months to hear back. I would focus on a few things. One, what are your goals and priorities as a product marketing team?

If you don't have a product marketing team charter, great place to start. Two, what parts of those goals and initiatives that obviously ladder up to company goals and initiatives, but what parts of those are being stymied or being most impacted by these layoffs and these frozen headcount? And then what are the parts that makes the most sense for product marketing to take on? So analyzing CRMs, maybe in the past we had a data scientist or a demand gen person who did that.

Well, guess what? There's so much AI and CRMs now, it can basically do it for you, right? So that's something I've seen a lot of product marketing take on or building landing pages. Maybe the website person is so busy with demand gen, like go and build your own.

blending page. Like it's very easy nowadays. There's so many tools that do it. ROI calculators, interviews, right?

Maybe in the past you had a customer success person that could actually introduce you to current customers, source the interviews, set them up, so on and so forth. Now maybe you have to do that yourself, right? There are certain things, and again, with AI, you can analyze a CRM easily, figure out who's in good standing, who's your exact ICP or your future ICP, and target them directly and automate the email sequence, so on and so forth. So I think for me, it really comes down to starting with your goals and priorities, figuring out which of those are going to be most impacted or are most impacted by the headcount reduction or headcount freeze or so on and so forth, and then kind of adopting the parts of the process that you can that make sense to without overcommitting to like, coding a new product or something wildly out there.

And as you're saying, at this stage, while they may be dealing with contracted budget percentages of revenue, you're still expanding into new product categories, new markets, new use cases, new UICPs, new regions. So you do need to figure out how to leverage AI to scale your content. You're talking about ROI calculators or landing pages and whatnot. So how...

Can marketers, I'm not just going to leave it to product marketers because there's a lot of different marketers on the hook for creating different types of content for different reasons as you're expanding for demand gen or events or web or whatever. How can you expand your content quantity without sacrificing quality with buyer relevance and making sure it's aligning to what your actual goals of the organization are? In other words, How do you avoid the whole AI slop sea of sameness thing that we all have been talking about nonstop for two years now because it's clearly real.

Yeah. AISOP's the first thing that came to mind when you were saying that. So yeah, a lot has been said on this topic. I think it always comes down to the fundamentals, right?

So starting off with a strong outline in terms of what is it that I want to write about? Let's assume it's a written piece. If it's a video, same concept applies. So I think it has to start with a strong outline and a strong focus from a human, right?

A person actually doing this, adding key points and a strong point of view, again, from human SMEs. and letting AI synthesize. I think AI is good at synthesization, not necessarily at original thought. And so I think what's helpful there is adding as much information as you can.

So your ICP, your personas, your positioning, your messaging, your brand voice is really important. If you have brand guidelines, tone of voice, hero archetypes, et cetera, you can add all that to AI. That's usually helpful. And then the other thing, like I recently actually did this where I turned a webinar I did into a blog using AI.

And what was super helpful is I included the actual transcript of the webinar. And so it could see how I talked, how I speak. And so the blog it wrote was essentially in my voice. Like it wasn't perfect, but it was 85, 90 % of the way there in terms of tone of voice and how I speak.

So I still had to edit, but it wasn't too bad. I think that's all helpful. You don't want to overwhelm the AI, right? We all know that AI, there's been studies that show that AI doesn't take into account everything you give it.

But I think if you give it... If you start off with the human controlling, what are the goals of this piece of content? How is it going to be used? What part of the funnel?

Coming up with an outline, interviewing customers or SMEs or whoever it is that's going to be part of the piece, and then creating the key points that you want to make and then letting AI take it. As long as you give it the foundational elements, I think that's helpful. And then the last part is editing. You really have to commit to editing.

I've gotten emails, position messaging. applications, like job applications, et cetera, from folks that were clearly written by AI and they were terrible. I mean, just absolutely atrocious. I got a resume the other day that was written in a way that sounded great, but it told me absolutely nothing.

And so again, I think editing is super, super important. I think if humans are the beginning and the middle and the end and AI kind of fills the in -between parts, I think that's the goal. It's amazing actually to me how identifiable it is when the human has not been involved throughout those steps it's because ai looks and sounds really good but we're seeing so much of ai generated contact now whether it's linkedin or websites or sdr emails or whatever we are all seeing all of the uh hints of AI, which is amazing to me that I think our subconscious brain, you know, there's tells in terms of em dashes and words, but in general, just the overall approach where I think we're recognizing it more, which means that human edit and that human touch is going to stand out more.

Yeah. And look, there's definitely a witch hunt for AI written copy and whatnot and figuring it out and whatever. I don't think that's really what's important. What's important is if you have a brand voice and you have a strong point of view as a company and you want to share that, as soon as you turn over the keys to AI and you're not involved and you're not dictating what that is, you're not editing, you're not making sure your brand voice is present, but also your point of view is present, you've basically lost all the brand equity and all the trust that you're prospects and customers have in you.

And so it's sort of like if we're all big fans of a particular musical artist and they suddenly start outsourcing their lyrics and their musical beats and even their singing to AI, we've lost all connection. Like what's even the point of going to listen to them, right? And so it's the same thing here where, again, the point isn't don't use AI. The point is use AI in a way to speed up your processes, but you have to maintain the human element and you have to maintain what makes you differentiated and keeps you.

Someone who's your target audience should be able to read your blog or your announcement or your social media post and immediately tell, oh, this is this company versus this other one. And even if they can't because we're not all CRM lovers or cybersecurity software lovers, et cetera, you should at least be able to say, oh, this is clearly a different company than this other one. You should be able to tell. And that's, I think, the part that AI very easily can mess up.

So let's, as we're nearing the end of our chat, let's really talk about, you know, the reality that you and I are in business because there is a valid need for outsourced or contracted, you know, swoop in, swoop out product marketing or positioning, go -to -market strategy type consulting versus there's absolutely, depending on the stage, a need for certain full -time roles. And it's like silly to outsource, you know, as a consultant, I'd be the first one to say. This should not be always an agency or consulting thing.

This should be a full -time expert in -house. So in terms of the cleanup crew aspect, I think we're at the stage of our AI transformation where people have made mistakes and are now leveraging folks like you and I to maybe help clean things up and get things back on track. Are you seeing this happening, first of all? And do you expect to see this more or do you think that folks are going to figure out how to normalize this internally?

Yeah, I mean, we're definitely being brought in as cleanup crews quite often at this point, I would say. I think the most obvious sign is copy, right? Just because you read a copy or you read a website and it's just trying to sell 14 things at once and it's pretty terrible. It doesn't really work.

That's pretty common. But I think we also see it in, scarily enough, in big strategic decisions where you notice, hey, the copy sucks, but why does the copy suck? Or why is it unclear? Or why does it try to sell 14 things?

It always comes back to the fundamentals, which they haven't chosen their audience. They haven't really defined positioning. They haven't made decisions about who they're targeting, what they're selling, how they're differentiated, so on and so forth. And so that's the part that's scary.

And that's oftentimes where we're brought in and we highlight this and they're like, oh, yeah, you're right. We haven't made that decision. We just assumed we could just start selling and see what happens. And it's like, well.

You have to have a hypothesis. You have to go and test it and iterate, right, on the early stage. And then for mature companies, you know, they're using a lot to speed up processes, which is great. But oftentimes then, you know, you end up with a ton of content, which is, I mean, at mid -market companies, you do have a ton of pressure to create content like crazy.

And then what happens is none of that content converts. And so you're stuck with, hey, we need content to create, you know, to produce leads and to get more sales. You produce the content, the content sucks. And then they're back in the same point where they've done all this work supposedly, but it hasn't led to results.

And so a lot of times we're brought in for that, not necessarily to create the content because we're not content marketers, but to fix the foundation on which the content is built that clearly isn't resonating or isn't working. Always been a big fan of mapping content needs to both the buyer's journey and the sales cycle. And literally asking the question, not what content can I produce, but... At what stage of either the awareness journey or the lead to opportunity or opportunity to close cycle is being held up?

And is there content that we can create to help accelerate or overcome that blockade? So content has a purpose. And then to your earlier recommendation, AI generated by human guided content creation. is one of those things that absolutely should scale and you probably i hate to say it you probably don't need large content marketing teams anymore but you do need some expert content editors and strategists to actually understand why you're creating content and what its purpose is so is there any other roles and i could be proven wrong that content will have a resurgence.

Are there any other aspects of marketing or product marketing that you feel legitimately can be replaced with human guidance and expertise with AI versus the product marketing specific skills that just can't be replaced? So I think it's a tricky question to answer because I think it depends. So I'll give you an actual example of something we do at Bluemanta. So we do win -loss analysis fairly frequently.

And in the past, we would take however many interviews we said we did, let's say we did 15 interviews or maybe 16, right? Eight with close loss, eight with close one, maybe a few others with buyers from other companies that didn't even consider us, so on and so forth. And so let's say we have 20 interviews and in the past we would have spent, I don't know, five to seven hours analyzing all the interviews, finding the commonalities, whatever. Now what's nice is you can just throw it into Notebook LM, or I think it's Gemini Notebook now or whatever that's called, into Notebook LM.

And it'll do the analysis for you. The tricky part here is. If you've done win -loss analysis for over a decade, like you and I have, it's very easy to go in and say, hey, here's what I want you to look for. Like here are the exact bullet, like the exact types of data, the exact type of trends, the exact type of whatever.

Here are the questions I'm trying to answer from this win -loss analysis. Here's the point of doing that, right? So maybe the win rates for a specific product are low, or maybe a specific region is suffering, or maybe competitors are crushing us or whatever it is, right? So here's the goal of the win -loss.

Here's exactly what I'm looking for. Here are the trends you should look for. And, you know, some fail safe, like look for anything, any other trends I may have missed, et cetera. And so it's very easy for us to go in, do that with Notebook LM.

It automatically analyzes everything. We use a particular template and format for the output. So we upload that as well. And so in, you know, 30 seconds, you basically have the analysis done versus in the past, again, five to seven hours at the minimum.

And so what's really nice is for what I call synthesis of data or analysis of data, it's great. But you still have to have the foundation of what is it that I'm asking? Because it's very easy to give AI data, have it run an analysis, and it's not going to be most likely hallucinates. It's not that it's going to be wrong, but you could miss so much.

And so, you know, it's kind of like a cautionary tale, but also pro where. You can use it to synthesize data, and we have, but you have to be mindful of how to do it. The other one, we do a lot of CRM analysis. It's just so much easier to do with AI now.

Also, when we start creating proposals or we start creating pieces of content, we start with the AI transcript from the recorded call. That makes it much faster. I think we've cut down proposal. creation by like, I don't know, 60%.

When it comes to report, same thing. We probably cut it down 50 to 60%. So using AI note takers and leveraging that for content creation is huge. Win -loss analysis, again, huge.

Any kind of quantitative research. So when you're researching an industry for the first time, a buyer, a vertical, et cetera, we always start with AI. We validate, but we start with AI. It's so much faster.

Research in terms of competitive intelligence. is a little bit tricky i think ai is fantastic at servicing new things so new new developments so what i mean by that is like something that clue or crayon used to do where you know say hey competitor x just launched y or competitor z just entered this market or whatever ai is great for that i would never ask ai at least today to analyze a competitor and tell me their positioning their messaging their pricing etc because it always in my experience always hallucinates and so we'll use it for in -house Companies that want to do that, that want kind of to stay up to speed on competitors, but we won't use it for actual analysis of competitors like deep analysis.

And then the other thing we've started doing, which is really great, is we basically create like an operating system, an operating model for companies, especially at scaling companies where, again, like you said, you have limited headcount or frozen headcount. You need to continue to deliver even more so than last year, of course. So what we've done in those situations is we come in and we take whatever they have. So ICP, personas, position messaging, et cetera.

And then basically by product line, so let's say they have seven different products, we'll kind of standardize the content for each one. So each one will have ICP, personas, position messaging, specific aspects of sales collateral, product demo, you name it. And then what we do is we make it all machine readable so the AI can very easily parse it, read it, et cetera. So markdown files, et cetera.

We create a Slack bot so it connects. Any sales rep, customer success rep can ask the Slack bot, hey, tell me about XYZ or I'm meeting with XYZ persona. What should I emphasize? And then also for content creation, we've given the AI very specific parameters.

Like, hey, for any time someone asks you to create a one pager, here's exactly the size. Here's the brand. Here are the colors. Here are the fonts.

Here are the characters. Here are the different sections. Here are the character counts or limits in each section. And here's where I want you to pull from.

Like these customer calls, these customer transcripts. this position, this messaging, et cetera. And so what it does is it outputs something that's automatically product marketing improved and the sales rep can get 50 ,000 iterations without having to wait for us. So I think those are the kinds of things that from a product marketing lens, you want to try to automate, but not never the strategic direction, never the bets and assumptions that you're going to make so on and so forth.

Great set of recommendations. And, you know, and clearly. AI is not the devil yet. It's absolutely our businesses, scale -ups, startups.

It's creating massive efficiencies, in fact, in reality. But the difference between quality versus speed is simply how are you guiding it? How are you validating that the quality and usefulness is fit for purpose so you're actually achieving? your goals, which a lot of the early AI experimentation was efficiency for efficiency sake, but did not necessarily tie to actually delivering on company objectives.

So it's positive momentum and maturity for sure. Jonathan, this has been a really great conversation. Appreciate you participating. Yeah.

Thanks for having me. Excited we could get together.