Dear founder,
Many of the technical founders I know really don't like marketing. And it's not that they don't understand it. They know how important it is to run an effective business. But they don't really know how to do it right. They don't know how to leverage their technical skills to make marketing easier. And they just feel—it's evident and obvious to them—that their time would be better spent implementing product features and technical solutions than stumbling around the world of getting people to look at their product.
I get it. I've been there. For years, actually.
So today, I want to share a couple of ideas and learnings from my journey as a founder to show you how marketing can work for founders who hate marketing.
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The biggest learning for me in now almost twenty years of software entrepreneurship is this: if you don't like to do it, and you don't want other people to do it for you—at least you're not at that stage yet—well, then you let machines do it for you.
And the best and most obvious way of doing this is programmatic SEO. It's making most of the value that you and your business produce discoverable by people who are already looking for something like it.
For me, for Podscan, this was an obvious choice. One that I took way too long to implement, honestly. I made all the podcast and episode pages that I have internally—where people can see the transcripts and the metadata—I made them public. And I hid some of the information that people would find most interesting so that they would then sign up.
Ever since I made Podscan's internal data, this treasure chest of data, semi-public by giving some of this information away for free through generating these pages and linking them in the sitemap—generating tens of thousands of potential endpoints for people to find my product through—signups have been spiking. People have been finding exactly what they need. And then the group of people that found it and actually have an interest in purchasing my product is now coming to the product without me having to do any targeted outreach.
I think the first fifty percent of the MRR that I'm now at—low five figures—has been created entirely through my network and through building in public. But the second fifty percent, that second half, has been coming from people who just found Podscan through Googling for a transcript of a podcast. Or Googling for more information about a show. They found it through my programmatic SEO efforts.
So if you have something of value in your product that people really, really crave—maybe it's some kind of data that only you scrape, data that you extract or enrich—make some of it available. Trust that you have put enough of an example of value out there that people will sign up and find reproducible value in your product over time.
Now, here's something I've learned about this machine-based marketing approach that might surprise you.
With my programmatic SEO efforts, out of the hundreds of people that sign up for Podscan every day, only a handful is from my ideal customer profile. The majority just wants to see a podcast transcript from some show, and they will never sign into Podscan again.
Honestly? That's fine with me.
Because I know that even though these people are not my customer profile, they now have seen Podscan. They now know that they can go to Podscan and get the transcript of any episode of any show that they ever wanted to look at.
So if any professional person in their vicinity—for some random chance—ever mentions that they would like to do more with podcasts, because they know that the conversations their business might be interested in are happening there... now that person, that prior to this moment was not an interesting customer to me, becomes a magnifier for the value of Podscan.
Because they can tell them, "Hey, I was looking for a podcast transcript, and I found it here on Podscan. Have you tried that out?"
And now, if I have the trust between these two people because I provided help to one of them, they can have this recommendation benefit for my business. The non-customer becomes the word-of-mouth channel.
That's the beauty of letting machines do the heavy lifting. You're not just reaching your ideal customers. You're building brand awareness at scale, one helpful interaction at a time.
Now, if you don't have anything that you could show from the programmatic side of things—which to me means just building something that exposes existing data—you can go to the generative side of things.
This is where it becomes a bit murky, because auto-generated blogs on auto-generated websites suck most of the time. It's just not fun to read an article that was clearly written by an AI. Just as much as it's not fun to watch a video that was rendered by an AI, or listen to synthesized audio where you know no human being ever touched this.
But there is a subsection of generative SEO that is very interesting, and it ties back to where people go when they look for information. And that is pattern exposure.
For me, that means: the more customers you serve, the more data you ingest—either from your customers, from the projects that they're building, or if you do something for your customers and their customers interact with your product in a way—you get an insight into your industry.
And the more of that data you source, the more you have generalizable information that turns you from a simple product offering in the industry into a data aggregator. An industry insider. An actor in that industry with unique perspective.
Now, obviously, you have to juggle how much of the stuff that you know about your customers you're willing to—and are allowed to—share. But there is something really valuable in showing industry trends or behavioral patterns.
Let me give you some examples.
Let's say you're working in the tourism industry, and your software-as-a-service business facilitates bookings or scheduling. Now you can say, on a per-country basis, in this season, any trip is this-many-percent likely to be canceled. So you can create a chart—a worldwide, map-based chart of trip cancellation likelihoods. That's incredibly valuable information that nobody else could produce without your data.
Or if you're in the logistics industry, and you help people optimize the routes of their trucks between their warehouses, you can highlight traffic congestions and the likelihood for them to appear. Or which roads are barely used for long-haul traffic. And from your calculations, if somebody wants to have a vacation road trip, which roads to avoid.
All of a sudden, you can make a pattern visible that others, without your data, could not have made visible. And that, with proper search engine technical optimizations, can turn your almost sterile product into something that really helps somebody else find meaning and useful insights.
So the name of your brand, the name of your product, becomes something very positive. Something that they will share until it finds the right person.
Between letting machines create the output for you and letting machines help you find more and better customers, there's another powerful approach I want to share.
One of the tricks that I see so many founders do right now involves AI-assisted marketing, outreach, and sales. It works like this: take your existing customer base, usually by grabbing all the emails or all the domains of the customers who signed up to your product, throw them into a prompt somewhere and say, "Hey, these are my current customers. Who are they? What are similar businesses? What are the lookalikes here? And where do these customers communicate? Where do they hang out? What are the places that people from these companies find new things to learn from, or find community with others? Where are these people exchanging information?"
That will then allow you to find these places and see what kind of content is created there, which you can then put into your own content creation efforts. You can write these things yourself. You can outsource them to professional freelance writers. You can likely outsource some of this to AI-assisted writing tools.
But just figuring out where to speak and what to speak about? AI similarity and lookalike prompting is generally a great move if you have no idea how to do marketing. Because just knowing where people go and what they're interested in—we can always ask an AI. It will give you maybe not the perfect answer, but definitely a good one to start from.
I also recommend using something like this internally to allow you to focus on the high-likelihood-to-commit prospects. Whenever somebody signs up to Podscan, I score them a couple hours into their first activities on the platform. Once they sign up, they may or may not search for something. They may or may not check out the API documentation. They might set up an alert or something like that. I track these things internally.
And then at some point, I send over a prompt to an AI that has a couple of guidelines on how to score my customers, zero out of ten. The higher the score, the more likely I am to reach out to them with custom help.
And that is a way for me to figure out who my high-profile customers are. From there, I can try to talk to them and see: How did you come to the product? What are the social platforms that you usually go to? Where did you go before to find podcast information?
I can ask them, so I can see what kind of content and what kind of outreach I need to create to reach people like them better.
Another thing you could do as a technical founder is let your documentation do the talking.
A good, SEO-friendly knowledge base—and that is documentation both for people and for machines—I'm not just saying API docs. I'm saying any kind of documentation. FAQs. A knowledge-based system.
A good knowledge base like this is a marketing tool because it will also rank on Google. When people have questions about your product, right next to their query appears a very well-written and well-documented answer. This gives people not just insight into your product, but also hope that if they ever have a question, they will clearly and quickly get an answer to it.
Documentation is trust-building at scale.
And then finally, marketing is quite repetitive. Marketing is really just reaching the right people with the right message at the right time.
Since your competitors are doing a lot of the work already, maybe you should feel inspired by what they're doing. This won't always work—sometimes you need to stand out significantly—but tracking what your competitors do and finding ways to do it yourself is generally a good idea.
So think about social. Think about podcast tracking—Podscan might help you there, obviously. But also look at YouTube and TikTok and wherever people from your best ideal customer profile are being targeted and marketed to. You will likely find something there that will resonate.
For B2B software businesses, LinkedIn is still a great platform. It's still a great effort to do paid ads on. It's just a place where people hang out.
So let me bring this all together.
Between letting machines do it for you with programmatic SEO, letting machines help you score and reach out to the people who are already kind of on the hook, leveraging your documentation as a discovery channel, and doing competitor research to find the right routes—I would suggest if you're just starting out and want to just do something, one or two of these approaches might be highly appropriate and useful for you to implement today.
You don't need to love marketing. You don't even need to like it. You just need to build systems that do it for you.
That's what technical founders are good at anyway.
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