The AI Stack That Makes Our Product Marketing 10x Faster

Summary

Marketing Against The Grain: The AI Stack That Makes Our Product Marketing 10x Faster

Released on July 10, 2025, by HubSpot Media

In this insightful episode of Marketing Against The Grain, hosts Kieran Flanagan and Kip Bodnar delve deep into the transformative impact of artificial intelligence (AI) on product marketing. Featuring Rachel Lies, HubSpot’s Product Marketing Leader, the discussion unpacks how AI tools can exponentially enhance product positioning, storytelling, and competitive intelligence, enabling marketers to achieve world-class results swiftly.

---

1. Introduction to Product Marketing and AI Integration

Kieran Flanagan kicks off the episode by highlighting the critical role of product marketing, especially in the age of AI. He introduces Rachel Lies, who emphasizes the essence of product marketing:

“Product marketing is really, at the simplest level, telling people what your product does, why it's important, how it will help the customer, and also doing that consistently across channels.”
(02:06)

Rachel underscores the necessity of maintaining a unified message across diverse channels, particularly as content proliferation and multiple platforms make consistency increasingly challenging.

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2. Essential AI Use Cases for Product Marketing

Rachel outlines several pivotal AI use cases that have revolutionized HubSpot’s product marketing strategies:

a. Building Ideal Customer Profiles (ICPs)

By leveraging AI models like Claude and ChatGPT, Rachel explains how HubSpot creates comprehensive ICPs by integrating internal data (e.g., customer interviews, research decks) with external insights. This process ensures a nuanced understanding of target audiences.

“If you're just getting started... you will have a pretty robust, like, ideal customer profile and Persona pretty quickly. Right. That'll be way better than what most people have.”
(04:57)

b. Content Refinement and Personalization

AI tools assist in refining content to resonate more effectively with customers. Rachel shares her practice of using custom GPTs to evaluate and enhance marketing materials based on customer feedback.

“What would you specifically change? What would you keep? And so that not only improves the content, but it also teaches me the simple things that I need to be including when speaking to the customer.”
(05:23)

c. Competitive Intelligence with NotebookLM

HubSpot employs NotebookLM to manage competitive intelligence, enabling sales teams to access detailed battle cards and competitive insights seamlessly. This tool allows for real-time responses during sales calls, enhancing the effectiveness of sales pitches.

“We have a ton of market research... you're on a call with a prospect who is concerned that they won't grow with HubSpot. What should I say? And that's going to come back with what to respond with.”
(15:00)

d. AI-Powered Customer Interviews at Scale

Rachel introduces Outset, an AI-driven platform that conducts customer interviews at scale. This tool automates the interviewing process, allowing the team to gather extensive customer insights without the logistical constraints of traditional methods.

“We are getting great data at scale. So it's been really, really great for the team.”
(27:38)

e. Creating Tailored Product Pages for Micro Audiences

The hosts discuss the innovative approach of using AI to create personalized product pages targeting micro audiences derived from specific customer pain points. This strategy leverages AI to dynamically generate content that speaks directly to individual company needs, significantly boosting conversion rates.

“This is gonna be the whole thing. The whole thing is going to be understanding that pain that the Swift company has and then activating it on a personal webpage, a personal ad, personal email...”
(34:22)

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3. Tools and Technologies in Focus

The conversation highlights several AI tools integral to HubSpot’s product marketing:

• Claude: Used extensively for creating and updating positioning documents based on comprehensive data inputs.
• ChatGPT: Increasingly utilized alongside Claude for specific AI-driven tasks.
• NotebookLM: Facilitates competitive intelligence and provides sales teams with instant access to crucial information.
• Outset: Automates large-scale customer interviews, accelerating data collection and analysis.
• Genspark: Assists in transforming AI-generated responses into dynamic presentations and slides.

Rachel also praises her team’s efforts in organizing data to maintain flexibility across different AI platforms, ensuring the most effective tool is used for each task.

“I just can't imagine my life without it.”
(37:22)

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4. Insights and Impact of AI on Product Marketing

The episode underscores the profound efficiency and effectiveness AI brings to product marketing:

• Speed and Scalability: AI drastically reduces the time needed to create and refine marketing materials, enabling rapid iteration and scalability.
• Personalization at Scale: Marketers can now offer highly personalized experiences to individual customers, enhancing engagement and conversion rates.
• Enhanced Competitive Edge: With tools like NotebookLM, teams can stay ahead of competitors by accessing and utilizing up-to-date competitive intelligence.
• Operational Efficiency: Automating customer interviews and content refinement frees up valuable time for marketers to focus on strategic initiatives.

Kieran and Kip emphasize that the integration of AI in product marketing is not just an advantage but a necessity in today’s fast-paced market landscape.

---

5. Conclusion and Takeaways

As the episode wraps up, Rachel encourages product marketers to embrace AI tools wholeheartedly:

“If you're a product marketer, you absolutely, absolutely have to spend time using these tools. Find the time lock off your calendar. You get deep into them. It will make you so much better at your job and allow you to do so much more than you ever thought was possible.”
(37:22)

Kieran and Kip echo this sentiment, highlighting that AI-driven product marketing not only enhances efficiency but also enables a level of personalization and precision previously unattainable. They hint at future episodes that will delve deeper into tailored AI strategies, promising listeners even more actionable insights.

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Key Quotes:

• Rachel Lies: “Product marketing... telling people what your product does, why it's important...” (02:06)

• Kieran Flanagan: “You can actually have real conversations with your customers... train an AI model to act like a customer.” (05:45)

• Kip Bodnar: “There is a version of that. Companies are able to build synthetic versions of your customer...” (23:30)

• Rachel Lies: “Try to find your unlock. I found my unlock and then it led to all these other things...” (37:22)

---

This episode of Marketing Against The Grain offers a comprehensive look into the future of product marketing, showcasing how AI is not just a supplementary tool but a fundamental component driving innovation and efficiency. Marketers looking to stay ahead would be well-advised to heed Rachel Lies’ advice and integrate these AI strategies into their workflows.

Transcript

[Kieran Flanagan]

It's never been a more important time to have an incredible story about your product. On this episode, we have Rachel Lies, the product marketing leader for HubSpot. And she is going to show you three AI tools that can transform your product position and your product story overnight. And how to go from average to world class in a very short amount of time. All of that and more on this episode of Marketing against the Grain.

[Kip Bodnar]

Before we get into today's show, here's a quick word from HubSpot. Cutting your sales cycle in half sounds pretty incredible, but that's exactly what Sandler training did with HubSpot. They used Breeze, HubSpot's AI tools to tailor every customer interaction without losing their personal touch. And the results were pretty incredible. Click through. Rates jumped 25%, qualified leads quadrupled, and people spent three times longer on their landing pages. Go to HubSpot.com to see how Breeze can help your business grow.

[Kieran Flanagan]

All right, on this episode, we're going to talk about something we have not covered as much, and that is product marketing. But because it's the marketing against the grain show, we have to do it from an AI perspective. We have Rachel Liest, who is the fearless product marketing leader at HubSpot. Everything good that comes out of HubSpot in relation to product marketing is her and her team. Welcome, Rachel, to the show.

[Rachel Lies]

Thank you. What an introduction. So happy to be here.

[Kieran Flanagan]

Okay, so you're not just a great product marketing team. You're also a team that has adopted AI across all of the things you do. And so we're going to be able to show people some practical use cases of how you use AI for product marketing. But first, because Kip and I have not covered product marketing marketing a whole lot on the podcast in the last couple of months. Why don't you give people a refresher on product marketing and why it's important?

[Rachel Lies]

Absolutely. So product marketing is really, at the simplest level, telling people what your product does, why it's important, how it will help the customer, and also doing that consistently across channels. So it's so, so, so important to make sure that whenever a customer is interacting with your company, they are saying the same message and the same value. Props and think age of AI. This is becoming more and more important as there's more content out there and more channels that people are using.

[Kieran Flanagan]

So, Rachel, why don't you tell us about some of the must have AI use cases for product marketing?

[Rachel Lies]

So I think there's a couple of things that we have really thought about when using AI so first, all the customer contacts you have, interviews, research decks, transcripts with your customers, anything you can get your hands on that helps you understand the customer. Then there's product, you have one pagers, you have again decks, there's positioning docs, there's research, and then of course you want to pull in some internal context, like think about LinkedIn posts that have done really well, or just tone of voice, and then market context. So there's all these materials that really you can use to make your product marketing even stronger. And we have a couple examples, as you mentioned, to go through, where we show how you use that to create your positioning docs and your sales decks, your one pagers, your talk tracks. It's really incredible what we've been able to do.

[Kieran Flanagan]

Yeah. One of the cool features of OpenAI or even Claude is their ability to basically ingest internal data and then pair that with external data. So, like, one of the things you can do to right off the bat, if you're listening to this show and you have not done a lot of product marketing or you're just not really sure how to even get started, you can literally just ask Claude to build you a ideal customer profile. And you can just say, like, use all of the documents in my G drive that are related. Look at my emails. And then you can say, pair that with external data that's like really powerful. I was doing that over the weekend. And it will actually build you some pretty great ICPs, which are for our audience, ideal customer profiles.

[Kip Bodnar]

And Kieran, we did this in the HubSpot and OpenAI show.

[Kieran Flanagan]

Right.

[Kip Bodnar]

Because we have the deep research connector with HubSpot and ChatGPT. If you're a HubSpot user, you can literally just ask ChatGPT what it thinks your ICP is and break it all down based on your existing data too. Right. So you can do that. And then once you have a rough ICP, you can ask the LLMs to go and embellish it with more information. And let's say you're just getting started. You don't have a team of people doing product marketing, just record some of your customer calls, put that with the data you have, and you will have a pretty robust, like, ideal customer profile and Persona pretty quickly. Right. That'll be way better than what most people have.

[Rachel Lies]

Yeah. I think one of the things I do on a daily basis is I take some content that myself or my team has written, I plug it into one of our cloud projects or custom GPTs that have again, those customer transcripts. And interviews and say, does this resonate with the customer? What would you specifically change? What would you keep? And so that not only improves the content, but it also teaches me the simple things that I need to be including when speaking to the customer.

[Kieran Flanagan]

Right. The ability for AI to mimic people if you, if it's given enough information is pretty powerful because you can actually start to have real conversations with your customers. Which for an introvert like me, I can now just train an AI model to act like a customer, like a voice model, speak with it for a long time and never have to actually talk to a human, which is like, really exciting.

[Rachel Lies]

It's actually funny. One of our first iterations of one of our Personas was training AI and then asking it questions like, where do you want, like to eat? Where do you want to shop? Just to get to know the Persona more. So definitely with you on that one.

[Kieran Flanagan]

You know, there was this weird app that Kip and I wasn't weird, but like there was this pretty fast growth AI company. I think Fate was it. Meta bought a Kip character that AI Google.

[Kip Bodnar]

Google bought it.

[Kieran Flanagan]

Google bought it. And so they had this like, you were able to go and create fictional characters or you could go create characters in comic books or whatever. And it was actually really popular with kids. They would go speak to their favorite comic book heroes or people in shows and they can have a conversation with them. There should be something like that for people. Just like aggregate and everyone who has different pain points and you have entrepreneurs can go there and speak to different people with different pain points and figure out what products they actually want to build for them. But that's a lovable slash replic idea because then you could actually pair that with your new and growing 5 code and entrepreneurs. But why don't you show us maybe one of the use cases your team uses day in, day out for AI and product marketing?

[Rachel Lies]

Definitely. I'll start with the one that was really the biggest unlock for me with AI in general. Like, I think everyone has their moment where things click and all of a sudden it works. And this was mine. So this first one is a Claude project. So on the product marketing team, we have Claude projects for all of our products, for all of our customer proof, our competitive intelligence. And this is our growth Gabby project, which is essentially our customer Persona. And so in here we have details that you know, again, this is what Kieran was talking about a second ago. You're an A with extensive data about growth Gabby in your database. Like pull in from customer call transcripts. The Profile all this research that we have, everything. And then we have some details on what your role is again, how to create that vision doc. So I am going to use our operations hub positioning from 2020 and ask it to essentially update that based on the research that is in this project. So I want to update this positioning DOC from 2020. Since then, we have updated our Personas. Can you take a first pass at updating the positioning using the following framework? And the framework I want to use is what's actually in the project details here. So sometimes it actually just does this automatically. But just in case, I'm going to outline this and this is really how we organize our positioning. So soon as I run that, it's going to start looking through all the project details and pull up just a new version of positioning. And while it does that, the other thing that to mention that I love doing with this project and again our other product projects is using current positioning that we're working on and saying, hey, tell me exactly what resonates with this Persona, what doesn't resonate, and provide me very specifics on what to change. And we've actually saved a ton of rounds of feedback and reviews because of this. And Kip can talk to that as well because he helped us with this.

[Kip Bodnar]

Well, first of all, I love that we built this. I use it all the time. Like I was just using it last week, Rachel, and I was like, it just gives me such good feedback because there's a level of depth to it because it has all that context about here is the type of person we're talking to, here's what they care about. It has all those conversations that it can go and reference. And what's pretty amazing is it tells you exactly what to make better.

[Rachel Lies]

Yeah.

[Kip Bodnar]

And the magic in something like product marketing versus maybe other parts of marketing, it's an iteration game. Can you keep refining it and making it more interesting, clearer, simpler? Anytime you're talking about your product initially, it's like it's a little foggy and you don't know what to focus on. And going through this like changes that dramatically and changes it like in minutes instead of like hours or days. Right.

[Kieran Flanagan]

Could you give the listeners an idea of what content you've put into the Claude project?

[Rachel Lies]

Definitely.

[Kieran Flanagan]

To make it so accurate in terms of its feedback?

[Rachel Lies]

Yeah. So we have a ton of market research that is first, foremost. Then we have customer interviews and we make sure they're representative of different company sizes, different regions, just different perspectives. And then we also include one pagers or Sales tax, just like anything that has been an output. One of the things that is the most important that I will stress is we do make a habit of every quarter we update what's in the project because things are changing rapidly, especially right now, and we want to make sure that as customer expectations are evolving, as we get new research in, we have the latest in there.

[Kieran Flanagan]

That was going to be one of my questions, as in like if you were creating a cloud project, is it like swap out data to keep the freshest data in there?

[Rachel Lies]

Yeah, it's usually swapping out data, I would say on the customers. It's just, it's adding to it, but it is so important and we do that across again all the product cloud projects we have as well. But I think this has been an unlock for not just me, as I was saying earlier, using AI, but a lot of people on the team. Because if you're writing an email or you're creating a landing page, running it through this to really understand if it resonates, it'll again give you these specific feedback and add in some data and quotes and it's really phenomenal.

[Kip Bodnar]

And you can do this in a ChatGPT custom GPT or in a cloud project. Rachel, I think you've done both, is that right? And like, what do you like better? Like give people a little tool and technology recap if they were doing this.

[Rachel Lies]

Okay, so I tend to run the same prompt through both to see what responses I get, which I think are better. But one of the things I was more dependent on CLAUDE when I could not choose the model in custom GPT.

[Kieran Flanagan]

Yes, yes.

[Rachel Lies]

But now that I can use O3.

[Kieran Flanagan]

Exactly that I don't know.

[Rachel Lies]

I've started using ChatGPT more, but most of our projects actually live in Claude. I like have this internal battle over it.

[Kieran Flanagan]

I just want to make sure we emphasize that for the listeners that feature because I've waiting for that feature forever. If you were in projects or you were in custom GPT in OpenAI, you couldn't specify the model to use for that product or custom GPT. And they seem to have updated that like two weeks ago, which was really awesome because it makes all of those things much, much usable. And I agree. I think that for even me, everything has gravitated across the OpenAI because of that.

[Rachel Lies]

Yeah, I feel like I'm cheating on Claude and I feel guilty saying this, but I do feel like I've been using ChatGPT more now because of O3 of our projects do still live in Claude, but one of the things that I would recommend to everyone is, you know, different people in your company have access to different things. So we have also organized all the docs just in our Google Docs and organized folders so that in the future we will have the flexibility to do it in Claude and chatgpt and Gemini, wherever it is. And huge shout out to Jess, Davis and Tim on my team who did all that work.

[Kieran Flanagan]

Well, one of the things that might get you back to Claude, and we're going to cover that on an episode over the next week or two, is Claude released a new feature that allow you to build hostable apps. And so you can build an app and then you can integrate your cloud API. So theoretically, actually you could have an internal tool that does all that position and they can just upload a document. It will actually give them a PDF in return. And so the ability to turn all of these projects and things into lightweight internal apps is actually going to be really interesting. So I think we're going to build a couple of those for our listeners.

[Rachel Lies]

Yeah, it's one of the reasons I like having it in both places, because every week one might be better than the other and I just like to be able to Compare it.

[Kip Bodnar]

Right.

[Kieran Flanagan]

GPT5 will come in July and just do all of this. You just say, go do it and just do it all. So we'll gravitate between both.

[Kip Bodnar]

What I will just say for everybody watching Rachel, that I think you're kind of getting at, is that the models in ChatGPT seem a little better, especially O3 right now. The user experience of managing the content, the project, and maybe getting custom app output is way better in cloud. Right. You almost need to do a little bit of both of them if you want the absolute best outcome if it's like a really important project. Look, if you're doing this episode with Rachel, you're going to love this. We just dropped the AI interview arsenal. You'll get an interactive demo where you can actually experience what it's like to be interviewed by AI. Go through it yourself right now and see how surprisingly smooth it is. Plus, Rachel's throwing in her go to AI prompts that'll help you automate the whole customer interview process. No more scheduling nightmares, no more transcription headaches. This will give you real insights from real customers. Fast click the link in the description below. Now, let's get back to today's show.

[Kieran Flanagan]

Okay, so you have a product position in done. I want to give you a quick demo a little bit later in this episode of A fun thing I did around product positioning, but why don't you take us through another use case?

[Rachel Lies]

So one of the most exciting use cases we have worked on is around competitive intelligence. So we have been, you know, using other software throughout the years to host all of our competitive intelligence, all of our battle cards, and now it's all in NotebookLM. Ben Conti put this together. I'm gonna demo in a second, but I will say usage has spiked. People just like love interacting with it more. Our sales reps love it in this.

[Kieran Flanagan]

So this is awesome.

[Rachel Lies]

It's very exciting. So there are so many, so many different things you can ask this. I know our reps are using it on calls to basically ask, well, you know, this objection just came up, what do I say? And it immediately comes back with the answer. If I have a couple of sample prompts with like give me one punchy success story, I can quote, provide the sentence, then the stat.

[Kieran Flanagan]

So just to explain this to the listeners, one of the things product marketing do is they create these kind of competitive guides. And so anytime a competitor comes up on a sales call or as part of the buy in process, you are able to kind of give all of the talking points around that. And what you've done here in NotebookLM is you've built individual notebooks per competitor.

[Rachel Lies]

Yeah. So for example, I can say I'm going up against competitor X. Pull in the top three reasons that HubSpot would win in these scenarios. Or someone saying like HubSpot doesn't grow with. Let's actually do that one. I'm on a call with a prospect who is concerned that they won't grow with HubSpot. What should I say? And that's going to come back with what to respond with. It's going to come back with sources that it pulls from and so then you can ask follow up questions as well. So here's not only like some key talking points, here's some stats, here's the customer proof here. There's just a ton of things here. I love this at the end as well. That has again, like what to really emphasize. There's just so much information in here.

[Kieran Flanagan]

What kind of information have you added into each of these battle cards? Like if I was a person watching this and I wanted to start to create some of these competitive battle cards, what is the data I want to add into my notebook LLM to get this?

[Rachel Lies]

Yeah, I would say top talking points, the feature comparisons between like yourself and your competitors, any type of customer proof, anything around what has happened when You've switched from a competitor to your own solution.

[Kieran Flanagan]

Where does that information come from?

[Rachel Lies]

All of our research, so market research, customer research, like anything you can have in there and then it's. Or we organize ours by competitor.

[Kieran Flanagan]

You can talk to NotebookLM. Right. You could have a conversation with it, you can have an audio overview and you can create podcasts about all your competitors.

[Rachel Lies]

Yeah, so one of the things that we do whenever there's like a big announcement from a competitor is we essentially create a podcast. We've called it internally Hot Takes before and where the different competitive analysts talk through it. But again, you can create that podcast to just listen to a lot of information in a much easier way. And again, we've seen usage with our sales team skyrocket using this because it's just so much more accessible and easy to quickly get your answers.

[Kieran Flanagan]

Kind of while that this is being built through NotebookLM, it's probably replacing SaaS apps and the sales team are all using it.

[Rachel Lies]

Yeah, this is probably my favorite example because it's so accessible, it's so easy to use. And of course, as you mentioned, the podcast functionality.

[Kip Bodnar]

Well, especially if you are a Google Workspace customer and like you, all of your company is using Google tools already for work. This is just like a very natural extension of that. And like Kieran, I think you're right. There are people who are paying 30, 40, 50, 60 grand a year for this type of functionality. That was worse, you know, like a year or two ago that is now just kind of like free and baked in to NotebookLM. It's wild.

[Rachel Lies]

Yeah, I would say even way more than that.

[Kip Bodnar]

Oh yes.

[Rachel Lies]

Like this is such a great free solution. Again, if you are using Google anyway, and it's. I think it's more powerful.

[Kip Bodnar]

I agree with that.

[Kieran Flanagan]

You could also do a version of this, which is there's like seven or more different buyers in any B2B buyer committee, like above a certain average sale price. And so you could imagine that if you're a company watching this, like one of the things you could do is have a version of this, but it's all for the different buyers, like the selling points for those make sure the sales team have all that collateral, you know, the kind of pain points they have, the solutions they have. It's a great way to actually build enablement for sales because they have the ability to chat with the data, they have the ability to like have an audio overview. They have the ability to turn it into a podcast and ask the podcast question. It just like works for. However you want to retrieve that information.

[Rachel Lies]

Yeah. One of the hardest things for sales is that they have so much information to use. They're just inundated. They don't know where to go. They don't have to worry about this here. They just can quickly get the answers. It's amazing.

[Kip Bodnar]

Yeah, well, and it's very personalized was the point I was going to make. You know, one of the things that if you're a regular watcher of the show that we're hitting at is like AI is making kind of this one to one bespoke personalized experience finally real. And that's both external to customers and prospects, but it's also internal. To your point, Rachel, before a sales rep would have had to look through a bunch of kind of generic content and then like figured out how to shoehorn it for a given prospect where like they can just go to that notebook, say, here's the customer. Here their problem. Find me somebody or tell me exactly what I should tell them, whatever it may be. And the AI is going to give them a pretty good answer.

[Rachel Lies]

Totally. And they can even use the responses that we saw there, throw it into genspark and get some awesome slides to show up. There's just so many cool things to do. I'm a huge fan of genspark.

[Kieran Flanagan]

That's a good one, actually. Yeah, you could just take all of that, put it into genspark and start to create presentations. Go look at the episode. Kip and I both showed you how to do that in genspark. Okay. So you're doing your positioning and you have all of your team making sure they kind of put the position in through the cloud project that is a representation of your customer, has all the data. So it's able to say like, this is the way you speak to the customer. Turn the email into that, turn the product page into that. Make sure everything is uniformed, which is actually really good. Because in a lot of companies everything gets like different flavors of how people think who your customer is. And so it all kind of sounds different. Your website sounds different, your email sounds different, and then you have all these battle cards and notebooklm that your sales team can use and make sure that they're speaking about competitors in the right way. And we know how to win against competitors.

[Kip Bodnar]

Hey everyone, we'll be right back to the show. But first let me tell you about a podcast that I love. It's a podcast called I Digress. It is hosted by my friend Troy Sandage. It's brought to you by the amazing HubSpot Podcast Network, the audio destination for anyone in business. And Idygress is great. It's got 30 minute episodes and the podcast is all about helping you eliminate complexity, complications and confusions in your business. It's really heavy in frameworks and strategies to help you scale and sustain your success. And recently Troy had a really great episode. It was called Branding Secrets Leveraging Style to change the narrative, boost, influence and profits. And that was with his guest toy, Sweeney. It's really good. You should check it out and you can listen to that or all the episodes of I Digress anywhere you get your podcast.

[Kieran Flanagan]

What is another use case that you're using AI for?

[Rachel Lies]

So this is a new one we've been using, but this is one where we're essentially doing customer interviews at scale using AI.

[Kieran Flanagan]

Oh, this is a cool. Actually I'm about to use this tool.

[Kip Bodnar]

Yeah, we saved the best for last.

[Rachel Lies]

I did. I think this tool is so, so, so cool. So this is company called Outset and I'm going to show you how to create a study and some of the cool things that this can do. So you can basically do video interviews using AI. So in here you can essentially on your left hand side add different questions. So you can add conversational multiple choice. But I'm going to use an example about what are your current wellness goals your aiming to achieve? Please describe.

[Kieran Flanagan]

Kip and Karen can solve them with AI wellness. And that's what we're here for, wellness and nutrition.

[Rachel Lies]

Listen, you're gonna get some cool information here, but then you can choose your question type again. And then there's different probing. So you can say oh, like only probe a couple times or you can say like probe a ton of times if you're not getting the right answer.

[Kieran Flanagan]

Jesus. Are these real people you're gonna put into the abyss mode? I don't want to put in, I hope someone never tries to put me into the abyss mode.

[Kip Bodnar]

But Rachel, is this people or is this this a synthetic twin of people? That's what I want everybody to try to understand.

[Rachel Lies]

So yeah, so right now this is AI asking you questions. But and like you're being given a video interview, but it's more like an audio interview that you're being asked that.

[Kip Bodnar]

A real person's being asked.

[Kieran Flanagan]

A real person?

[Rachel Lies]

Yeah, real person's being asked. So like I as like the market researcher can interview hundreds of real customers without doing it myself.

[Kieran Flanagan]

Right.

[Kip Bodnar]

That's a game changer for any kind of growing company.

[Kieran Flanagan]

Right.

[Kip Bodnar]

You can get very specific feedback.

[Kieran Flanagan]

There's a Version of that that I think most people would say it would be a horrible version. And I do agree. But there is a version of that. There are companies that are able to build synthetic versions of your customer and they're used within sales, actually. So sales sell to that synthetic version of your customer and it teaches new reps how to sell to your customer. And you can program the customer to have different pushback. I don't have the budget, I don't have the time, whatever it may be. And the sales rep tries to figure out how to navigate around that. It records that and helps the sales rep. You can coach the sales rep how to do better this. You could actually build synthetic different versions of your customer and then have AI interview the AI representation of your customer.

[Kip Bodnar]

Correct. That's what I think will happen, which.

[Kieran Flanagan]

Is like a horrible future to think. Like, I think that's where you were going. I think that will happen. And I think that is the abyss.

[Kip Bodnar]

But no, but in all seriousness, imagine this is important for everybody to understand. We could do this right now, right? Like we could go and Rachel could do like some very detailed broad questions with 50, 100 customers using this tool. Right. And then we could go into ChatGPT and build digital twin versions based on all of that real life interview feedback for them and then do follow up questions that were just AI to AI.

[Kieran Flanagan]

Right? Exactly. It's like I'm in my own simulation really, because this is like the perfect moment for me to start building products. I was a software engineer way back in college and tried to be a software engineer for a number of years. And now we've come full circle to I can build product with AI so I don't need to talk to humans. I can build professional AI representations of my customers and then have AI interview AI so I don't have to talk to anyone there either. So it's like the world is engineering humans out of the loop for me. So I can just do all of these things without ever having to talk to someone. It's just incredible.

[Rachel Lies]

I want to show you like an example of what this will actually look like for the customer. But one thing on probing you can say exactly, like make sure to ask about exercise goals, eating habits, and so it knows what to probe on, which is very cool. And one more thing I do have to show you is this language setting, like look at all the languages you can do this in, which is unbelievable. If like you're like me who can only speak English and but want to get like that global sample, you can do as many questions as you want, but I'm just gonna do this one. You're gonna get to hear about my exercise habits.

[Kip Bodnar]

I love this.

[Rachel Lies]

I am looking to get more exercise, do more workouts and eat better. You see, this is where the probing is coming in.

[Kieran Flanagan]

Yes. Ah. Okay. Nutrition or wellness goals you're aiming to achieve? Please describe what they are.

[Rachel Lies]

I'm hoping to work out three times a week and rest of the time I'm gonna chase my kids.

[Kieran Flanagan]

That sounds like a great plan. Could you tell me more about the types of workouts you're aiming for? They've used a clever hack here. How often you have. They have a very well spoken English person conduct the interview. There you go. That's how you know you're going to get better responses.

[Kip Bodnar]

Yeah, except they should be using a better 11 labs model than that. The voice quality isn't as good as I would have thought it would be.

[Kieran Flanagan]

I love that balance of planned workouts and active time with your kids.

[Rachel Lies]

So I have two market researchers on my team. We have a ton of products, a ton of needs, and they're able to just do so many more customer interviews and then it also will run the analysis for you. So this is something cool where if you have different questions, you can then click in and get like a bunch of your, like, customer samples. And these are like some of the best quotes that your customer said during the interviews. They also kind of have this highlight reel at the end where they compile everything. So not only is it doing the interviews, but it's doing your analysis at the end as well. It's just super cool and it's really helped us on the team.

[Kieran Flanagan]

Have you found the engagement to be good? Like, people are pretty happy talking to an AI assistant.

[Rachel Lies]

Yeah. That's why I wanted to show how it was. Like, it's not a person that you know is AI or isn't. Like, it's very clear that you know AI interviewers. So people are really engaging with it and we're getting great data at it and at scale. So it's been really, really great for the team.

[Kip Bodnar]

How much more efficient is it, Rachel? Like, because a lot of people watching this probably do an occasional survey, but maybe they don't do really in depth interviews like this. And they're really historically very manual and time consuming. Like, so how much faster is it?

[Rachel Lies]

Yeah, here's the thing. I think this is becoming more and more important because as we talked about with the quad projects and the custom gbts, you need more customer interviews and transcripts and if you can't take the time to do, like it might take one full day, you might be able to, if you're lucky, do 10 interviews. And I say if you're lucky because you have to deal with schedules and people not responding by email and not wanting to take all the time. But this is able to do like, like hundreds in that period of time. So I think it's saving a tremendous amount of time.

[Kip Bodnar]

Just way faster.

[Kieran Flanagan]

Yeah, Yeah. I think the ability just to get data and use that data AI just speeds that up so much. I wanted to give a close out with one little fun thing to show you to see if you think it's cool or not.

[Kip Bodnar]

Not a show unless Kieran's showing something he built.

[Kieran Flanagan]

It follows a theme that Kip and I have going on on this show, which is we kind of believe marketing is going to be much more tailored, much more personalized. I did a show last week, it was all around how to build these kind of micro audiences. So, you know, the theory there is we build product marketing for an ideal customer profile. That ideal customer profile has to be pretty broad because if it was like really, really small, we couldn't afford to hire that many marketers to market to these small audiences. But with AI, you can do that. And so one of the interesting things to kind of think about is, does product marketing actually become one of the teams that help you appear in LLMs? Because what LLMs are really doing is looking to see all of the different ways people talk about your product and. Right. Lots of niche ways. And if you have content for that, you're more likely to appear in the LLM. And so let me just give you a little, like side by side competition I did here between O3 and perplexity, because Perplexity is my new, like, fun toy at the moment. Stevenson, you both like bets. And so what I basically did. So what would be a micro audience for product marketing? Well, in this case, it's like, how would you divide up that ideal customer profile that you've been shown how you market to? Like that cloud project in this way, we were doing it based upon people who had left reviews on G2 or reviews on any review site. So we went out, we took a competitor and we said, look at the Reviews that are 3 stars or less across these platforms. And then based upon the feedback that they give, we're going to divide those up into a little audience and then we're going to market, create product positioning for that audience based upon the problems they have and how Husband solved them. So this is a little example that it's like going across. It's finding the different reviewer roles, it's talking about the pain points they have with this specific competitor that we have. And then in caps letters 10 times longer to complete anything. People really have issues here because they caps things just doesn't save what you're working on, meaning you have to redo things all the time. Price increase, where is this? They charge 5x as much as the former basic plan, blah blah, blah, no imitation, no emails about these seven. Okay. A lot of price stuff. And so it themes them. Right. It creates these little audiences. Okay. There's busy marketing professionals and small business owners who need efficient, reliable tools to execute campaigns quickly without constant troubleshooting. So this is like what I picked up on. And people leaving negative reviews about that platform. And then the job they have to be done. Because to your point, product marketing is really how do I market the benefits, not the features, the benefits of my product. I need marketing automation to just work smoothly so I can focus on strategy, not fighting with the software. So what we did here is we took this micro audience, we paired it with your ideal customer profile and then based upon that, we created a prompt that had, you know, how do you do great product positioning. It kind of goes and looks to see what are the best people in the world and what do they do really well. And then comes back and says this is how you do it. And then we give that prompt to lovable. And I want to show you the kind of two examples it did in Lovable. So you can see if you think that this is pretty good or not. So this one was done by O3. So again, remember that it's doing the micro audience. It's a smaller version, a subset. So it's the one who really struggled with the the fact that the tool was not making them more productive. So it has a pretty good like header here. I thought like launch multi channel campaigns in minutes, not days of duct taping. It's pretty good tools. Everything from first click to qualified leads live inside marketing hub. And then I love the fact that it starts making up numbers.

[Kip Bodnar]

I love some good fake return on investment stats.

[Kieran Flanagan]

Grab the like typical B2B image here. I look why is my day hijacked by marketing tools? And then it will tell you why it's doing this right. It surfaces the productivity killer pain verbatim to build awareness. So this is again coming back to the micro audience talking about time drain data silos, heavy enterprise suites so you can See what it's done here, right? It's crafted all of the content for your icp, who has that specific cluster of problems. And this is just one shot, right? I created this page in one shot. Like campaigns live before your next coffee. All of the stuff you can do to get migrated, all of the fake data around, how you actually increase leads, all of the stuff you can do around real time data attribution and so on and on and on and on. But like I thought for the very first attempt, this was pretty good at bringing the product to life through a product page.

[Kip Bodnar]

Kieran, I think that's good. I think what you would have is you're going to want to dynamically spin this up for each individual company that has this problem.

[Kieran Flanagan]

Exactly. Exactly.

[Kip Bodnar]

That's the big thing I want people to take away.

[Kieran Flanagan]

This would be for a product page targeting that competitor and everyone who comes in through that competitor, which you can get through data. Like you can actually, once you have their domain, you can actually figure out their tech stack. And so you would direct people dynamically change to this page, which is specific to that pain points that people have around that page.

[Kip Bodnar]

But what I'm saying is we'd even render it for that specific company's pain. So not just the competitor, but the company who's using that competitor and the problem they have, that's where you're gonna get real transformational conversion rate change.

[Rachel Lies]

The thing that's so cool to see about that is I feel like years ago we tried to do something even with kept to your point, with company names on such a smaller scale, but it was just impossible. And now you this and it's even better than what we were doing manually. It's just so cool.

[Kieran Flanagan]

So you're right, Kip. So basically you're saying take this first row, which is a company who left a review that is one or two stars.

[Kip Bodnar]

Yep.

[Kieran Flanagan]

And they were like, everything's taking 10 times longer to complete anything.

[Kip Bodnar]

Yes. We're going to parrot their words back to them.

[Kieran Flanagan]

We build a page for these.

[Kip Bodnar]

Exactly.

[Kieran Flanagan]

We actually have an agent that dynamically builds campaigns per.

[Kip Bodnar]

Exactly.

[Kieran Flanagan]

I think that's actually something we should do. I think we can do that.

[Kip Bodnar]

This is what I thought we were doing. You and I are talking after this. But like that's what's going to be the whole thing. The whole thing is going to be understanding that pain that the Swift company has and then activating it on a personal webpage, a personal ad, personal email, to the point where you're like, this is exactly how we can solve it for you and why it's so good for you. And that's how you're going to transform conversion rates in a world where website visitors are much harder to get.

[Kieran Flanagan]

Right.

[Rachel Lies]

Well, the cool thing I think about product marketing's role here is it's becoming more and more important because you have all these pages, you have to have that consistency and messaging and voice. And now product marketers for the first time have the ability to do that at scale, which they've never had before. So it's just a whole evolution of the product, product marketing role.

[Kieran Flanagan]

You can just be way more tailored. So perplexity, very similar. Like it's all around productivity. Not a great, I think above the fold experience here. What do you notice about perplexity compared to the O3 one right off the bat, what don't you see here? And then what do you see? Lots of here? Something that the older models do.

[Kip Bodnar]

Emojis, I was gonna say it's a lot of text different. And then yes, the older models love emojis, love a good emoji.

[Kieran Flanagan]

O3 moved past emojis, it's graduated, it's got a little bit older. It said, you know, I've grown out of my emoji phase. I have to grow up. I'm not allowed to do that anymore. Perpekxi is like, no, I'm still into this emoji phase. It's pretty good. But it's, you know, has hidden costs of broken automation. That picked up on one of the reviews that talked about that said this automation doesn't work, gives you some stats, meets the platform, that just works. So again it just shows you how quickly you can go from your ICP and then some additional data to actually pretty much good first shot of like product marketing collateral.

[Kip Bodnar]

Yeah.

[Kieran Flanagan]

So the main thing here is just the amount of tailoring and personalization you can do because of AI tools is just like different from anything you could have done in the past.

[Kip Bodnar]

We're going to do a whole tailor episode campaign coming up. Kieran, because you and I are cooking on a bunch of stuff here. But I think what is dramatic to me about the show today is that product marketing is I think more important than ever, first of all, especially because how AI is changing, especially the technology market. Product and feature commodization is happening much faster. So the story you're telling and your ability to articulate the pain and value matters much more. So that's one thing that's happening. Two, there's great product market fit with these AI tools and product marketing. There's really cool use cases, Rachel, that you showed us that literally anyone can go out and do for like zero to $20 a month. Right. You're not talking like hundreds or thousands of dollars a month. And the third thing is it's clearly going to get way more personal and we'll be continue to be talking about that on upcoming shows. Rachel, Kieran, what else would you want to add before we close out today's episode?

[Rachel Lies]

I think if you're a product marketer, you absolutely, absolutely have to spend time using these tools. Find the time lock off your calendar. You get deep into them. It will make you so much better at your job and allow you to do so much more than you ever thought was possible. Possible. Try to find your unlock. I found my unlock and then it led to all these other things and I just can't imagine my life without it.

[Kieran Flanagan]

Awesome. I think this is a great show for any companies that even don't have product marketing teams. Want to do better positioning, want to do better competitive insights, want to one shot a page to be tailored to their audience. You have practical use cases. That is what we try to do in this show. And until next episode, we will see you all then.

[Kip Bodnar]

See everybody. Sam.