Latest / Content, Briefly / Sacra: Jan-Erik Asplund's process for creating content worth paying for

Transcript

Sacra: Jan-Erik Asplund's process for creating content worth paying for · Content, Briefly

• 0:00
  [music] I spend a lot of time thinking about the same kinds of things that I thought about when I was doing content marketing like, "What's a good title? How do I, like, earn someone's attention with each bullet?
• 0:11
  How do I make sure that there's juicy data points in the whole thing so that it both bolsters the credibility and, like, keeps people's attention?"
• 0:18
  [music] Hey, and thanks for tuning in to another episode of Content Briefly. Today, I'm chatting with my old coworker, Jan-Erik Asplund. He's the co-founder of a company called Saqra.
• 0:30
  They create research for investors who buy and sell in private businesses. From a content marketing perspective, content is the product.
• 0:39
  Jan and his team are responsible for creating content that people are willing to pay at least $50 a month for, which is their starting tier. We talk all about what goes into creating that content.
• 0:49
  There's a heavy data component, there's a heavy interview component, and I think that even though this is not creating content for a B2B SaaS company, which is I know what most folks do who listen to this podcast, I think there's some really interesting takeaways here, including how to create content that someone would care enough to pay for.
• 1:05
  I mean, we talk a lot about getting people just to pay attention, but imagine taking that a step further and getting them to put in a credit card number so that they could get access to it.
• 1:13
  So we talk quite a bit about that. We talk also about content repurposing.
• 1:17
  If you're gonna go to the lengths that Jan goes to to create this content, you really have to repurpose it, and we get into some of the ways that he goes about that.
• 1:24
  And then also we talked about creating repeatable formats.
• 1:27
  Saqra's repeatable format is fairly extreme, but there's a lot of different ways that I think SaaS companies can come up with ways to create content in a repeatable high-cadence way that may be subtle for SEO, but really is designed to be just very useful to the reader so that they can capture a few quick takeaways, much in the same way that we do this podcast, right?
• 1:44
  Roughly the same format each week. We plug new guests in and get new and interesting output each and every time.
• 1:49
  And so we talk about some ways that we think SaaS companies could do that type of thing, but with text content. I'll get out of the way. I really hope you enjoy this episode.
• 1:56
  One of the things I'm trying to do with this podcast is explore content in the B2B space beyond just SaaS. So the Ben Bradbury Workweek example is a good one. Today's conversation with Jan from Saqra is another.
• 2:07
  So I think there's quite a few takeaways in here. I'll get out of the way, let you enjoy it. Also, just a quick reminder to check out the new and improved Superpath Slack group. It's now 20 bucks a month.
• 2:17
  You can also get an annual discount. Your employer should probably cover it for you, since it definitely counts as professional development. And I think what you'll find there is gonna be really exciting.
• 2:26
  There's some really interesting high-level strategy discussions, in-depth conversations on things like people management and career development. Honestly, it's awesome. I'm enjoying being in there more than ever.
• 2:36
  I think you will too. If you wanna check it out, just go to superpath.co/community and sign up there.
• 2:49
  [music] Hey, everybody. Jimmy from Superpath here. Really excited for today's chat with Jan.
• 2:59
  You know, Jan, I was just gonna give you, like, a proper intro, but I realized I've known you for seven years, I've never said your full name. I've only ever referred to you as Jan. [laughs] Whoa.
• 3:06
  [laughs] So maybe you could do the intro for us. That's okay. Yeah, it's... Most people have only [laughs] ever called me Jan or Jan, so- [laughs]... yeah, no sweat. Yeah, so I'm Jan. I'm the co-founder of Saqra.
• 3:17
  We're a private markets startup research platform. Been doing this for about three years. Before that, I worked at Animalz with Jimmy, worked on content with the best of the best for a year, and really excited to chat.
• 3:28
  I told Jimmy before I broke out all the podcasting equipment that I put away when the Animalz content marketing podcast with Jimmy, when we stopped doing that, so it's good to get back on the, on the airwaves with you.
• 3:38
  Yeah, yeah. It's not our first rodeo. [laughs] I was, just before this conversation, listening to the first couple episodes that we did, which were, uh, they weren't bad.
• 3:46
  It was September 2018 when we launched the Animalz podcast, and sort of funny listening to it now, realizing so many of the topics that I feel like still are quite relevant to content marketers, you know, like how to run an audit, how to prune your site.
• 4:00
  Like, some of these things are truly evergreen. So if you've never listened to us and you want it more like, kind of like strategy talk, which we don't go super deep in on this podcast, might be worth checking out.
• 4:08
  Maybe, Jan, could you talk to us a little bit about Saqra and just kind of explain the business model, how it works, who the customers are, and how you generate revenue? Yeah.
• 4:17
  So I'll sort of step back a little bit in time to when we started Saqra. So we kinda started with this, the idea of facilitating liquidity in private markets using research.
• 4:27
  The crux of that idea was that these private market startups are very opaque. You know, there's very little data out there.
• 4:33
  In the US, there's no disclosure requirements for private companies, so it's hard to really understand what's going on.
• 4:39
  And what we wanted to do was kind of help out this burgeoning market of private liquidity, so companies that will buy employee stock, companies that will buy stock from founders and sell it to investors and create liquidity in startups to kind of help those companies help this industry with research by basically creating bespoke research on startups.
• 5:00
  So that's kind of the original idea.
• 5:02
  What we've kind of emerged into is more of, like, a private markets information, knowledge, data, and trends for not just investors, but also startup founders, employees, operators, a little more of a broad approach.
• 5:15
  I think we've sort of seen the, the liquidity industry. It's done okay, and we have most of those big platforms as customers.
• 5:22
  But yeah, where we're at today is kind of, like, a private markets research, data sets, expert interviews, and yeah, we sell across that map.
• 5:30
  So-VC firms, hedge funds, down to solo capitalists, angel investors, and founders. Got it. Maybe this is a dumb question, but can anyone invest in a private company?
• 5:39
  If the shares are for sale, I assume there's marketplaces. Like, I think that's what Carta X is for, right?
• 5:44
  Like, if an employee or an ex-employee at a company has shares that they wanna sell, you could get your research from Saqqara, and then go through some marketplace like that to actually, like, facilitate the transaction.
• 5:53
  Yeah, yeah. It depends a bit.
• 5:54
  To an extent, yes, through platforms like Republic or Wefunder, virtually anyone can go, and, you know, I'm not even sure if there's a minimum, maybe fifty dollars, a hundred dollars on some of these platforms to invest, and there are some pretty legit companies raising on some of these platforms, Replit, Customer.io, a few others that we've covered in accordance with a crowdfunded raise.
• 6:15
  So that's kind of the bottom end of accessibility for anyone, and then the top end that's kind of the most inaccessible and where the most money is exchanged is these kinds of internal tender offers and liquidity programs run through platforms like Carta X and others, and those are for accredited investors, large funds that wanna buy in serious size.
• 6:36
  So it kind of runs the gamut. For most people, most startups are not investable, but there are opportunities at the lower end of check size. When Customer.io did this a couple of years ago, I invested a hundred dollars.
• 6:48
  Nice. So I'm waiting for their IPO so I can go out to dinner or something. [laughs] Yeah, a really nice dinner maybe. Yeah, hopefully. Hopefully. Maybe. [laughs] So it's interesting, as you frame up...
• 6:57
  Essentially, you're creating information and selling that to a customer.
• 7:00
  What I'm kind of hearing is content is the product, and you all have a subscription mechanism for this, so you can sign up, pay a monthly fee, you get access to... There's...
• 7:09
  Well, there's a freemium version of it, right? Like, so anyone can sign up and get the newsletters, which are quite good.
• 7:14
  Those are kind of, like, summary, TLDR style, quick hits, and then when you pay, you get access to a lot more. Could you just kind of separate for us what's free and then what's behind the paywall? Yeah, yeah.
• 7:25
  So we've been experimenting with this a lot since we started the company, really.
• 7:28
  It's, like, finding the exact place to start kind of monetizing the content, what should be free, what should be paid, what's valuable enough to whom to charge for.
• 7:37
  So you kind of pointed to the first free unit, which is the email.
• 7:41
  So subscribe to our email, saqqara.com, and you get a roughly weekly email that is about seven to nine bullet points on either a startup or some kind of trend, and this email is completely free, like I said.
• 7:57
  But behind that email is various content units on the site. So there's a few different types. Uh, there's company one-pagers.
• 8:05
  So if you go to saqqara.com/c/ company name, you'll find our one-pagers where we go through a company's product, business model, competition, what are the TAM expansion opportunities, what are the key risks, and then we do sort of a revenue analysis based on public data that we've aggregated, plus any back channeling that we've been able to do to confirm those numbers.
• 8:27
  So that's all free as well. Then there's the dataset, which is sort of the Excel spreadsheet that goes deeper into the numbers.
• 8:33
  That is paid, so you have to sign up if you wanna be able to get and use and share the spreadsheet of revenue data.
• 8:39
  And then there's the expert interviews, which inform the bullet points that we put together in the email.
• 8:44
  These expert interviews are forty-five minutes to an hour long, generally around, you know, seven, eight thousand words, and those are also paid. So sign up for a Saqqara membership, fifty dollars a month.
• 8:54
  You get access to all the datasets and all the interviews that are behind the emails and company reports. Okay, got it. That's really interesting.
• 9:02
  I was just looking at a couple of the emails right now that I have in my inbox, and they're really detailed. Like, I'm looking at the Wingspan one. The subject line is, "Wingspan's nine hundred and ninety-two x growth."
• 9:12
  There's just so much information in here. Like, if you're in the payroll space, like, you would definitely wanna read this.
• 9:18
  Whether you're an investor or not, this is probably quite interesting to you because you can learn a lot about the growth of the company. You know, there's talk about some of the competitors, key trends in the industry.
• 9:27
  You guys do a really good job with these cool graphics as well.
• 9:30
  All this sort of, like, leads up to this question of, like, how do you identify the business that you wanna analyze, and then what does the research and writing process look like? Yeah.
• 9:39
  So I'll start with how we choose the companies, which Walter and I hung out, my co-founder Walter, CEO Walter, hung out and drew a two-by-two diagram on the board when we started the company, and the two axes of the two-by-two were basically how big is the company, revenue, valuation terms, and then the other axis was basically how contrarian of a viewpoint can we produce in this company, how counter to the typical narrative about this company do we think we can get?
• 10:05
  And then we sort of identified then that the sweet spot for us was going to be trying to, uh, maximize both contrarian-ness and size of company.
• 10:14
  You wanna analyze the largest private companies, but there's a ceiling on them, right? I mean, if they're pre-IPO or have chosen not to go that route, they're probably smaller.
• 10:24
  M-meaning, like, you're not gonna write about Intuit, but you can write about Zapier. Yes, the largest possible private company.
• 10:30
  So basically, if you look at the top most valuable private companies, it's companies like ByteDance, SpaceX, Shine, Stripe, Canva, Revolut. So these are all companies that everyone cares about because they're really big.
• 10:42
  So if you put SpaceX in the title of your email or write a report about Stripe, you're gonna get a certain number of people reading it- Yeah... just because it's about this company. That's your keyword research.
• 10:52
  Yeah, [laughs] exactly. Exactly.
• 10:54
  Whereas if you just write about some random startup, which is, like, ninety-nine percent of startups and almost every startup for Series C or D, no one will care about it just on principle.
• 11:03
  So you just mentioned Wingspan. Wingspan's cool, but no one really cares about the name Wingspan.
• 11:08
  It's not really a big enough draw.So you do wanna write about the biggest possible companies, and we have written about some of those companies that I mentioned, but only when we've been able to carve out some perspective that's not just the sort of typical one.
• 11:21
  And Stripe we still haven't really done because it's just so hard to write a contrarian thing about Stripe. Right. That makes sense.
• 11:27
  At some point, like, you have to sort of carve out your niche, tackling the longer tail, and then you sort of build up to the shorter tail stuff over time. Maybe that's too cheeky of an analogy, but...
• 11:35
  Uh, maybe that's right because, I mean, we started with companies like Front. We tried to write something interesting about Front, was our first big report and one of our best performing ones.
• 11:43
  And I think with that one, we knew that Front wasn't this huge name. It wasn't gonna drive a lot of clicks on its own.
• 11:49
  But through a lot of our own usage of Front, we had felt like we sort of developed some interesting things to say about the company.
• 11:56
  We titled the post, like, "How Front Is the Nine Billion Dollar Company," I believe it was, uh, "Slack-ifying Email."
• 12:02
  Just trying to come up with a kind of oddball take or, or interesting take on it was mostly the way that we did our first many reports and continue to do now, I think.
• 12:11
  The weighting of the company size is a little bit less important than whether or not we can say something interesting.
• 12:16
  And say something interesting also, I put a lot of emphasis on the contrarian-ness of the argument, but that's maybe not the right word.
• 12:22
  Like, with Zapier, our framing was that they were sort of the Netflix of productivity, which is kind of a strange thing to say, but then it made sense sort of in the narrative of the piece.
• 12:32
  I think we referred to Airtable as the Roblox of the enterprise. Maybe not as enlightening as Netflix of productivity, but again, trying to come up with interesting framings.
• 12:40
  And then with the Wingspan email, you know, obviously it's one thing to mention a company called Wingspan.
• 12:45
  It's another to mention 992x growth, which is a lot of growth and also the specificity of the figure makes you think that we have something proprietary, which we do. So that is what I think ultimately drives the click.
• 12:58
  Yeah. And also, those titles make for excellent subject lines. Like, the framing of it makes these things quite clickable. In Wingspan's case, how much work do you have to do to get to the 992x number?
• 13:10
  I assume that's not obvious when you start the process of doing this. Yeah, it's not. I mean, we're pretty good at this point at pulling together data from public sources.
• 13:19
  In the case of Wingspan, and we've done this a handful of times, we worked with the company on the report, so they shared some data with us. It wasn't too much of a hassle.
• 13:27
  It was basically, um, they formatted the data export for us to be able to quickly analyze. Oh, that's awesome. I did wanna ask you about that. Do these companies want to be analyzed? Yeah.
• 13:37
  For the most part, we don't work with companies, but that's also equally as much a function of the fact that it's easier for us to do what we do if we're not working with companies a lot of the time.
• 13:47
  Because for us to give sort of objective third party analysis, it helps to not be working with the company.
• 13:54
  Plus, when you start working with companies on stuff like that, it turns into a mess with legal getting involved and marketing getting involved, communications getting involved, so everybody wants to have a little mark on it, so.
• 14:04
  That makes sense. I'm really curious about this.
• 14:06
  I'm actually very intrigued by the answer that you mostly don't work with the companies as well, because I think that using data in whatever form in content marketing, whether it's to make a benchmark report or weave it into a narrative, or you wanna make stuff for social, whatever way you're gonna use it, I'm just kind of intrigued that there's enough public data available that you can mostly do what you need to do to analyze these companies with the constraint that it has to be pretty darn accurate if it becomes investment advice for someone who's gonna put down real money on this.
• 14:34
  You know, and for the content team that's thinking about ways to stand out, and I think content teams at the moment really do need to be thinking about this because there's a lot about the future of search that is very uncertain.
• 14:45
  And so, like, finding new ways to reach people by creating better content and probably putting a lot more effort into that content, I think is gonna become very important.
• 14:52
  So maybe, um, could you just talk a little bit about public data sources? Like, I mean, if you're able to share, like, where do you find stuff? Do you analyze it yourself? Do you have a data analyst?
• 14:59
  Like, what goes into that part of it? And then once you have data, I would love to hear how you go about finding the stuff in there that's really interesting that becomes the 992x growth subject line snippet. Yeah.
• 15:11
  I mean, the data collection really is not, for the most part, not rocket science because companies do disclose this stuff. They disclose revenue, they disclose... well, mostly revenue, and then how fast they're growing.
• 15:22
  They talk about this stuff all the time, and if you sort of collect all the public data points that are out there, especially for larger companies, you can put together a good data set just based off of things that have been publicly said.
• 15:33
  I mean, a lot of it is just being very good at Google and persistent at Google.
• 15:37
  And then there's also interpolation and extrapolation of figures based on what's been said, based on market growth, looking at comps to other private companies, but also public companies.
• 15:47
  Like, some of the larger privates, you can really start to look at public companies who have to disclose all their data, and you can sort of, you can sort of use those to triangulate things better as well.
• 15:58
  And then the second part of it is kind of over time, as you do this, you build up a decent arsenal of data that you can use to then compare to past data points that you've collected.
• 16:09
  You know, you start to get a sense for what the gross margins of a payroll company are, and you can sort of reuse that data that you've generated.
• 16:16
  So the way that we turn it into emails and stuff, we have this phrase, golden nuggets, which is basically the little bits of both qualitative and quantitative information that kind of connect the narrative to some kind of fundamental truth.
• 16:30
  So we do a lot of expert interviews. Every interview will have a handful of these golden nuggets, things that just jump out at you, quantitative data points or qualitative claims and qualitative facts.
• 16:41
  The way we think about it is that there are two levels of story or narrative. One is kind of the top down. You're trying to impose some kind of narrative, tell a story.
• 16:50
  The bottom layer is the quantitative, what are the actual facts, and you're trying to connect these two to make it viable and to make it actually make sense to people.
• 16:57
  So golden nuggets kind of bridge-To us, they bridge the gap. It's like the quantitative data point that drives the story home is kind of what we're looking for. Yeah, no, that does make sense.
• 17:07
  How long does it take from the time that you've selected the company to analyze to a published email dataset and all the other paywalled stuff to be published? Uh, like four days. Oh, really? [laughs] Yeah.
• 17:19
  Oh, I thought you were gonna say like four weeks, if not longer. Yeah. We have been whittling it down.
• 17:24
  So when we started with like Front and like Zapier, those were long reports obviously, but they would take six weeks or more.
• 17:31
  And what we've gotten to now is we had a realization, which was cadence is so big with email, and getting emails out is so big, and so we aim to do one per week.
• 17:41
  So roughly four or five days is what it takes to get an email out. Starts with figuring out the company.
• 17:47
  Either we've already done interviews or we need to do an interview or two with people who know the company well or founder, CEO.
• 17:53
  And then at the same time, I'll be drafting the email bullets, working with Walter on those, and also gathering data. It's challenging, but yeah, we're, we're four or five days or so. I'm really impressed.
• 18:03
  [laughs] I mean, I can, I can imagine that it gets easier as you do it more. So you mentioned the golden nuggets thing.
• 18:08
  I'm sort of curious to unpack that a little bit because it tells me that you have sort of a philosophy on going about this. Like, okay, you choose the company based on the two by two.
• 18:16
  You know, you're looking for the golden nuggets, which become the subject line or the clickable social post. That becomes kinda like your tip of the spear.
• 18:22
  How much of this is formally documented or is it just that you're doing this so much that you kind of have like a mental checklist of like, you know, "I need this piece of data for the email.
• 18:31
  I need this type of anecdote- Mm. "for the fifth bullet point," et cetera, or is there like a template that you essentially fill in? Yeah, it's a good question. There is sort of a template.
• 18:40
  Every time I approach an email thinking, "Oh, I'll follow sort of the template I have in my head," it totally falls apart, and I realize that I've just wasted hours creating something that ends up not really working.
• 18:51
  Because every company is different, and every email, in order for it to be interesting, I think has to take a different tack.
• 18:58
  It, it can't be like if I'm writing an email about, like we're working on an email about Gamma, which is the sort of AI slides creator, and we previously talked about slides creators when we were writing about like Figma and Canva.
• 19:12
  So there's a temptation to kind of skip a step, go look at what we did then for a similar company, and kind of try to copy what the bullets are, what the sort of narrative arc is, all that kind of stuff.
• 19:22
  But every time I've done that, it totally fails because each company, really for it to work, there's a different story afoot.
• 19:28
  But at the same time, there's like certain types of things that I'm picking up on that should be there. Especially when I go into the interview, I'll look for stuff about business model.
• 19:38
  I'll look for like a really crisp explanation of product market fit, where it got traction, and what it does better than other products.
• 19:47
  I'll look for like, do they say anything about kind of expansion, where they see the product going, what they see it becoming?
• 19:53
  So those are some of the key when it comes to, uh, going through an interview, trying to find golden nuggets, I think.
• 19:58
  Yeah, I've always kind of wanted to make things go faster with templates, but yeah, not really having much luck with it with emails. What about AI?
• 20:06
  Are like, are there AI tools that you can use to speed up your workflow, where you can throw a bunch of data, you know, at an AI tool or GitHub Copilot, or can you dump an interview transcript in?
• 20:14
  And have you found that things like that speed up your workflow at all? Yeah, I... From time to time.
• 20:19
  I wouldn't say I'm in ChatGPT all the time, but I've been pretty impressed with what I can get, you know, if I plug in the entire transcript of a expert interview and then ask ChatGPT questions about it.
• 20:31
  I found that useful for as I start writing an email, questions will come to me and I'll... I could go ask Google, and I could go search Google, and I could probably find an answer.
• 20:40
  But more and more I've started to ask ChatGPT, especially when it's a... We cover like a new subject every week practically.
• 20:46
  I mean, we touch on things that we've covered before, but I might be trying to understand like how customer data platforms work on a Monday, and it'll be sometimes, yeah, ask ChatGPT for sort of help with some of the finer points.
• 20:58
  I've actually found that to be useful.
• 20:59
  The second part is kind of when doing the company reports, the point is to put together, somewhat consistent from company to company, a bunch of information on what the product is, who it's for, what it does, what the company's business model is, like how they make money and what that implies.
• 21:15
  If they make money as a per-seat SaaS, you know, how do they expand that? What's the natural motion there? What the competition landscape looks like, TAM expansion.
• 21:24
  Some of that content is quite similar from company to company, and that's where AI has been most useful for like generating content. It can't be copy and paste it in.
• 21:34
  You know, it's not quite that good yet, but it can certainly help take some of the initial thinking out. It can sort of solve the blank page problem a little bit, so that's been cool.
• 21:43
  And then we're, yeah, we're building a AI chatbot to chat with all Sacra documents and interviews and datasets, so I think that'll be cool.
• 21:52
  I mean, I feel excited about the progress from GPT-3 to, to 4, and I think it'll be great.
• 21:57
  It sort of levels the playing field in a way where anyone can produce crap content now, so the opportunity is so much greater to produce something better. [laughs] That's a great point.
• 22:07
  You know, one of the things I was gonna say as just like a takeaway to some of the things you were saying is that-I think there's a lot of room, particularly for the SAS content marketing crowd, to think about repeatable content series as a potential lane within your broader content strategy.
• 22:20
  And what I mean by that is, like, what Saakru's done is taken this idea to an extreme, but it's like the concept is you pick a business, you run the analysis, and then there's this handful of different outputs.
• 22:29
  Some are free, some are paid. I think that there's a way for SAS companies to do something similar. It's like the way that most podcasts are run, right?
• 22:36
  Like, there's a concept and you're just continually plugging in, usually new interviewees into the same framework, the idea being you get slightly different output each time and you sort of learn something.
• 22:45
  It's very familiar to the reader, and it allows you to do a very high volume of them. I mean, that's what this podcast is, right?
• 22:50
  Like, with the exception of this episode, actually, we ask [chuckles] basically everybody the same list of questions, but we get something new and interesting each time.
• 22:57
  And I do feel like there's a way to bring that to text, kind of in the way that Saakru has, but on a much, much smaller scale.
• 23:03
  So, like, as an example of that, like one of the things that we do for Superpath Pro members is that every week, we publish a new content strategy teardown.
• 23:09
  So I pick a SAS company, and I create a ten-minute loom video, quote unquote, tearing down the content strategy. We find new things every time we do that. It's really interesting. So we call them ten-minute teardowns.
• 23:20
  It's not that difficult to do. You know, I learn a lot by doing it, and people like it because they get a couple quick takeaways from their ten minutes of time.
• 23:28
  There's a guy named Samuel Hulick who a few years ago, or probably ten years ago actually, created this site called useronboard.com, where he would do these, like, onboarding teardowns, and it's, like, an infinite number of companies that he could sign up for, run through the onboarding experience, and leave his commentary on it.
• 23:42
  I've talked about this on a few podcasts, so I apologize for people who listen regularly.
• 23:45
  But the point I'm getting to is I feel like there's versions of this for every company where if you can find the right concept, the right hook, it becomes pretty easy to pump new entities through that same framework and get interesting output every time.
• 23:57
  There probably is an SEO play to it, but it doesn't have to be just that. I think that the content is quite useful on its own, which is not usually the case, where SEO content is kind of like a means to an end.
• 24:07
  Anyways, all this just sort of to say, like, you're kind of inspiring me to think of some new ways to get high volume content out the door in a way that doesn't just rely entirely on Google.
• 24:17
  Now, all that said, I do want to ask you about Search, because as you're creating really interesting content where, like I sort of joked earlier, that your keyword research is the company name, I would imagine there's an opportunity to get branded search traffic for those particular companies.
• 24:31
  You know, whether or not it's, like, super relevant to Saakru or not, you'll take it, I assume, right? Have you guys thought about that?
• 24:37
  And then in addition to that, you read about Wingspan, that gets you into the payroll space. You know, does that lead you further down so that there's, like, a payroll industry report later on?
• 24:45
  Do you then do breakouts where you do an analysis of Gusto and Deal and whatever, some of these other companies in that space, or is that getting too far outside your goals with the business? No, I think that's good.
• 24:55
  I mean, one of the framings for this was, like, content as product versus content marketing, and I think we are sort of doing both. You literally pay for some of our content.
• 25:04
  Other of our content is there to kind of market the paid content. And so I think, yeah, it's not outside the realm of possibility. One big thing we're thinking about is, like, how to repurpose our analysis and facts.
• 25:17
  So, like, if we spend days doing a teardown of Deal, like a one-page report, and we put energy into the analysis, and we do interviews with people who work there or whatever, it is fine if that's just for a Deal report, which people might pay us for.
• 25:30
  But it's even better if we can take what we learned and wrote and repurpose it and use it to more quickly create a report on Gusto or Panther or other companies in the back office, finance, payroll, B2B space, right?
• 25:45
  So there is kind of a natural SEO play. I mean, we are ranking already for a fair number of revenue, company name, valuation.
• 25:52
  We've put, like, close to zero effort into optimizing for that to this point, but we've seen pretty decent results just from, like, trying to make good stuff and then filling a hole that wasn't there, you know, in the search results, which is, like a meaningfully put together piece of research around those ideas versus just, like, a guess.
• 26:11
  And then, of course, once you do a bunch of company reports on companies in payroll, yeah, we've then accumulated quite a bit of internal knowledge and also literal writing about that.
• 26:21
  And a category report, you know, kind of like a payroll report or a unified payroll report or global payroll report is not at all outside the realm of possibility I think.
• 26:31
  Something we definitely want to do more of and possibly use AI to help with is finding ways to take across different pieces of content and then fit it together and create new pieces of content that can also rank for search and can also bring in more top of funnel.
• 26:46
  You know, I think you and I did a podcast about the idea of cross-cutting on the Animals podcast, probably, like, late twenty eighteen.
• 26:53
  So we hung out in New York a couple of weeks ago, and you were talking a little bit also about some of your plans for programmatic SEO as a way to repurpose content.
• 27:00
  I think one of the examples you cited was you have an interview. You, it's like an hour long.
• 27:04
  You know, you have a transcript, and there might be some ways to pull snippets of that out and then take that content, give it a dedicated page as a way to potentially capture some long tail search keywords.
• 27:14
  Maybe I'm not explaining that exactly right, but could you kind of talk about... There's sort of a repurposing angle there and then also a programmatic angle. Yeah, yeah.
• 27:22
  Each interview lives in our CMS as a series of Q&A, question and answers.
• 27:27
  So the idea was basically take every single interview on our website and take each Q&A from those interviews and turn each Q&A into its own page, which can be open to the public and also rank for search and ideally drive ten thousand new pages with which to bring people in from Google.
• 27:44
  What was kind of interesting was that was actually the first usage of AI that we did, because often the questions as transcribed, they don't exactly work out of context.
• 27:53
  Like, the way that you ask a human being a question in the middle of an interview, you're not phrasing it in the most broadly accessible way necessarily.
• 28:01
  You look at the transcript and you're like, "Okay, this doesn't really make sense on its own."
• 28:05
  What we did was basically ask ChatGPT to rewrite the questions for all, you know, ten thousand pairs.By looking at the answer.
• 28:12
  So training it on the answer to then rewrite the question to be something that you can more easily understand if you're just arriving at that lone Q&A pair on a website.
• 28:23
  So that was, yeah, that was the first thing we did with AI, and was kind of a cool use case.
• 28:26
  And most of Q&A pairs on our site are now up as standalone pages, and we're starting to notice some SEO traffic coming into those, which is cool.
• 28:34
  And, and then each one links back to the interview, each one links to the expert who we interviewed and their company. That's really cool. I really like that.
• 28:42
  So then if someone does a search and lands on that page, it almost looks like a Quora page. I've thought about that for Superpath a lot.
• 28:48
  Like, I would love to find a way to turn the Superpath Slack four-year history into essentially, like, a Quora-esque site to drive growth. You could do it. I looked into it. It's definitely possible.
• 28:57
  But the barrier there is that it's a community. Like, people didn't, you know, they didn't ask the questions and provide the answers in a search indexable way. Like, privacy is expected, right?
• 29:07
  So we're not ever gonna do that. But it reminds me too of the chatbot, because you mentioned the chatbot earlier.
• 29:11
  So you're gonna basically, like, take all the data, sort of make your own mini LLM, and make it accessible via chatbot.
• 29:17
  And when you told me about that a few weeks ago, I actually went down that rabbit hole for Superpath and tried to figure out if we could do that. Same idea, make it for the Slack group. Mm-hmm.
• 29:24
  So you could pull four years of information and make it really easy to sift through, or really just get, like, the ChatGPT style summary out of it instead of having to comb through, like, 1,000 threads on a certain topic.
• 29:35
  Is that gonna be for paying customers only, or is that gonna be, like, a lead gen type tool? Yeah, I think for paying customers only. Yeah, it'll be interesting to see how folks use it and what they use it for.
• 29:44
  That makes sense.
• 29:45
  There's been a lot of talk on this podcast actually about, we've used different terms, like mini LLM, or, like, subject matter expertise database, basically different ways that content teams can collect a lot of information through...
• 29:57
  Like, an example would be a company runs a podcast, they do webinars, they have a blog, they have internal discussions and notes.
• 30:04
  Like, how could you pull all that together in one place so that you hire a freelance writer, and they want a quote or a data point that is very easily accessible to them through a chatbot?
• 30:13
  Some companies have kinda figured this out, but it's kinda duct-taped together too. Like, Zapier interfaces is gonna make this a lot easier.
• 30:21
  There's a tool called Dovetail which is meant for customer research, which you kinda use. I really do hope, though, that somebody builds, like, a kinda simple SaaS product to do exactly this for content teams.
• 30:31
  Not, not necessarily that you could sell it, but just to make the folks who are writing, like, make their life a lot easier so that you're not starting from scratch every time you write an article about a topic that's very similar to every other article on the website.
• 30:42
  Yeah, yeah. It's gonna be interesting, too, what it does to blogs to the degree that a chatbot trained on all your documentation can sorta answer people's questions and create that knowledge. Yeah. Really cool.
• 30:53
  I have a couple of takeaways from this conversation for the content marketers listening.
• 30:56
  I get the sense, Jan, that you don't think of yourself as a content marketer anymore, and I do, maybe because that was the context that we worked together in. Mm-hmm.
• 31:03
  But maybe also, I'm, you know, because our audience is primarily SaaS content marketers, I'm looking at it through that lens to think about the ways that what you're doing at Sacra is applicable to their work, and there's a couple takeaways, I think.
• 31:12
  One is making content that's good enough to pay for, even if you're trying to drive trials or demos or whatever other kinda SaaS metrics you're looking at.
• 31:21
  Another is finding repeatable formats so that you can work relatively quickly. Like, I think four days is amazingly fast for the type of content that you all put out.
• 31:30
  But looking for repeatable formats that allow you to create a high volume of content without coming up with a novel approach every single time. And then lastly is repurposing.
• 31:38
  Like, you mentioned a few different ways you're repurposing. One is, in your case, like separating free versus paid. There's newsletter, there's datasets.
• 31:44
  But then there's also some of this programmatic stuff, there's the Q&A thing. Like, there's a bunch of cool ways that you're repurposing stuff.
• 31:50
  So I think those would be, like, my three main takeaways from what we talked about today for the in-house folks.
• 31:55
  Anything you wanna add based on your experience as someone who now creates content that is sold directly versus your experience creating content for SaaS companies?
• 32:03
  I think just a lot of continuity, and I think our experience, Walter and I's experience doing content, was definitely helpful in, like, getting the conviction to do Sacra, 'cause, you know, we just sort of looked at what the state of private markets research and also public markets equity analysis was, and it was, like, really poor.
• 32:20
  You know, kinda like good from, like, a perspective of collecting data, and obviously in the public markets it's a very long tradition, sell-side research, equity research.
• 32:29
  In the private markets less so, but the people who are doing it who came over from the public markets, like, they know what they're doing when it comes to, like, the financial analysis.
• 32:37
  I think where they were not as Internet native was figuring out how to write stuff that gets distribution, and I think that that was one of the things that we brought to it from doing Animals, was how do you create research that people actually want to read?
• 32:50
  So I would say I spend a lot of time thinking about the same kinds of things that I thought about when I was doing content marketing, like, "What's a good title? How do I, like, earn someone's attention with each bullet?
• 32:59
  How do I make sure that there's juicy data points in the whole thing so that it both bolsters the credibility and, like, keeps people's attention?"
• 33:06
  Then with interviews, you know, I think this is a big one that, that you talked about a bit and that I see a lot of companies doing as far as, like, repeatable formats of content, is, like, a lot of interviews with practitioners and stuff like that.
• 33:17
  Each interview that we do, we spend hours coming up with the questions, and I think that's one of those things that I will often read other people's interviews with someone as I do prep, and what I'll see is the most banal questions, very short interviews, very, like, softball questions that you could ask anyone.
• 33:33
  And I think that's one place that I think SaaS companies, B2B companies could do more, is, like, conduct interviews with people and, like, really drill into the sort of finer points of what that person knows about, what they're a practitioner of, and in a way that will educate fellow practitioners.
• 33:49
  I think that's maybe a missed opportunity with some interviews. But something that, you know, we try really hard to do is talk to people and get to insights that are monetizable, that people will pay for, so.
• 33:58
  Really cool. I think that's a great takeaway. Yeah, I really appreciate it. It's been good to chat. It's good to catch up. I'm glad that we could do it in this format, because I learned a lot.
• 34:06
  I hope other people have learned a lot, too. One of the things I would like to do with this podcast is explore B2B content from other angles. So we recently talked with Ben Bradbury from Workweek.
• 34:14
  He runs audio and video production for a media network targeted at B2B readers. Sacra, another very different way, like, content as product company also in the B2B content space.
• 34:25
  And I feel like these different perspectives can really inform the way that SaaS content marketers are thinking about their work. So thank you for doing it. We will obviously point people to Sacra.
• 34:34
  Good domain, by the way. Sacra.com seems like a pretty solid domain. Thank you. [laughs] And I would encourage people at the very least to go sign up for the newsletter, because, well, one, it's free.
• 34:42
  But two, if you work for any SaaS company, you will learn a lot about what is happening in SaaS right now, and it's worth reading.
• 34:49
  It's worth having a better understanding of what's happening in the industry in which you work. So at the very least do that. But can we send folks anywhere else, Jan?
• 34:55
  Twitter, LinkedIn, personal sites or, or anywhere else? No, that's great. I mean, definitely sign up for the newsletter. Check out the website. We're also hiring, so we'll put that in the description, jobs.sacra.com.
• 35:06
  Yeah, I think that's about it. Thank you so much. Cool. Thanks, Jan. Talk soon. All right, bye. [outro music]