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Ed Fry, SaaS growth consultant, on the future of data to personalize experiences
   

Ed Fry, SaaS growth consultant, on the future of data to personalize experiences

For the past 6 years, Ed Fry has been working in B2B companies such as HubSpot, Hull.io, and Inbound.org.

Shortly after our interview, Ed started working as a SaaS growth consultant and now works as the Head of Growth at Paddle, a UK-based SaaS for subscription and E-commerce. 

Our conversation with Ed covers the role of data in 2019. While data is becoming ever more available, the sheer volume of data at your disposal can also be frustrating.

  • Where do you start?
  • What do you do with all this data?
  • How does data impact important growth metrics? 

In January 2016, Ed went on a journey to really get into data and data strategy to create more personalized experiences for customers. In this episode, Dave talks with Ed about how to use data to scale your startup, how to use data to personalize experiences for users, and why some B2B startups are  doing wrong with data. 

Listen in and get some free growth consulting from Ed! 

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In this episode you’ll learn: 

0:00 Introduction
3:57 Ed’s 2016 deep dive into data
11:56 Where most B2B startups are getting it wrong or getting stuck when it comes to data
14:06 Ed describes his time at Hull.io
24:07 Listens to Ed’s advice on the practice of using personalized data to scale your startup
26:14 If every piece of data was available — what would we do?|
31:28 The Salty Six

Full Transcript:

DR: Today, we’ve got a new friend, I feel like I always say it’s a new friend, but you really are a new friend that I met at SaaStr about a month ago. We have Ed Fry, who has been working with particularly in B2B SaaS for the last six or seven years here across a couple different companies.

Hull.io

He was at inbound.org, at HubSpot, and most recently was the I guess Ed of Growth is what you say? The Head of Growth at Hull.io and now is working as a consultant with other B2B SaaS companies.

Ed loves talking about data, underlying data, but then I think more importantly, what we’re gonna talk about today is kind of what can you do when you’ve got a good data strategy in place. What are some of the most cutting edge companies doing when they actually are able to sync up all their data, get rich customer profiles and what’s the power that comes from that?

So Ed, welcome. I’m excited to kind of nerd out and talk about data and a bunch of cool stuff.

EF: Yeah, very excited to be here.

DR: So, before we kinda get I guess into like currently what you’re working on and what you’ve been seeing here, you were at HubSpot. And before we started filming, you said kind of the consulting you’re gonna be doing is kind of a combination of what you were doing at HubSpot but then also what you were doing at Hull.

And I guess tell us like what were you doing at HubSpot? What’d you kind of learn there? What’d you kinda pick up there as a marketer? How’d that kinda transition into Hull? And kind of where are you at today?

EF: Sure, so when I was at Inbound, that started as a like a side project piece. So, by Rand of Moz and Dharmesh at HubSpot. And although that was a side project for them and we kind of kept that going, it was originally, “Ed, here’s 500 bucks a month” for your time and $12,000 to last indefinitely “to like manage this side thing.”

DR: Not really a job.

EF: No, so this was actually before university, before college.

DR: That’s awesome.

ER: Like, yeah, a month before first going to Bristol, I was doing this which was great because that paid my beer budget through university.

But about halfway through my time in university, we had this discussion when all three of us were together in Seattle in July 2013 for MozCon. Like this is going all right, like, it’s you know but it needs either Moz or HubSpot or just more resources to go into it. And that wound up with HubSpot acquiring Inbound.org.

And so that was great because we had all the resources of HubSpot put in not just the tools and tech, but also like the financials to it. And for me that also gave eyes into the Big Orange company about a year before they were going public and all their B2B SaaS playbook and everything which was put on there. But as we grew, particularly post that acquisition, like acquisition for us was no longer really an issue. Like once we connected to this ecosystem, we had a bunch of members coming in.

DR: What did you sell at Inbound.org?

ER: So inbound.org is a community for marketers, like Hacker News for marketers. You’d go there, be able to submit links, ask, post questions, et cetera.

When it started, it was mostly Rand’s followings. It was mostly SEOs who knew each other talking about SEO. But, if you’re talking the acquisition thing, which was coming in particularly post acquisition, better acquisition, that value proposition really began to change.

People didn’t see people they recognized talking about subjects they recognized. And what this did for us is a big decrease in engagement, a big decrease in engagement and ultimately like our attention curve just began to drop off totally.

DR: Because it used to be this like tight-knit, raving fans, this is our crew. You guys sold out to the man!

ER: You could say that, but also all your top-line metrics, your vanity metrics, begin to look amazing. But actually the fundamentals behind the scenes, you weren’t actually joining up and delivering the same value as you were back in the day.

And it became to the beginning of 2016, where this all came to a halt. And these charts were shown. And okay we need to fundamentally change our strategy. So away from new users and away from like amount of content and this kind of thing to focusing on weekly active users and what really drives that and understanding how to pull together kind of value proposition. And it was January 2016 where my journey really into like data and data strategy and how you can create better experiences, how you can do personalization, how you can get into this, how that really started. 

DR: Did it start just out of you just had to?

Like you had to dig in and start figuring out how do we turn this ship around?

ER: Exactly. It was not a sustainable situation.

DR: So it wasn’t like you were just looking to be all about data and loving data. You were like, “I’m a marketer. I need to figure out how to turn this thing around.”

ER: It was a resource-eating thing which wasn’t generating value, like value in the same way. And so yeah, that’s a good question.

Like this is either gonna be turned off or we need to figure the way out. So that really, like starting to think through that set of problems.

Like how do people get value from this community? What were they doing? And this is very similar to SaaS companies. Like how are people using your product?

And all those answers aren’t in your email tools. They aren’t in the things which marketers traditionally have access to. They’re in your backend database. So what we did is connected that backend database to our HubSpot portal so that we could really understand and take action on how people were using the platform, how people were engaging, how people were using the product, if you like.

So me as a marketer, me as a community manager, I could then email people based on who they were, the actions they were taking, the timezone they were in, all that rich context, which I would know if I were face to face with them, but I wasn’t able to join the dots otherwise.

So by getting access to that data, I could suddenly start to pinpoint where the opportunities were. From there, we started to figure out, okay, where are the opportunities? So working backwards from what drives weekly active users, really it came down to a function of the number of discussions and the number, like the number of things which you could engage with each week and that also tied it together with the number of contributors.

We had two very common types of interaction. One was like submitting an article link. One was posting like a discussion question.

Discussions drove like four times the amount of engagement as posting an article. There was some like back and forth. So the strategy, okay, we are gonna focus on discussions, on Q & A. We’re gonna try and seed as many questions as possible, get as many answers to that as possible.

That was gonna drive the number of contributors up, which was gonna drive the number of weekly active users up. So how do we join the dots here? So we have, like a question, we weren’t short of people asking questions in the community. That was great. But how do we find people to answer that stuff?

Say “How do you put together a content strategy?” or like “I’m new.”

I’m the first hire in a B2B SaaS company. “What should I do?”

These kinds of questions which a lot of people would answer and with unique, interesting answers. So who are the types of you could ask? And who can answer that question, based on their skills, based on their recent engagement, based on their timezone because you want to be able to wrap this up within a couple of hours.

Because you could think of the, over the course of a week, you’d have I mean, you’ve got five business days, but also over the day, you want to be able to drive engagement through morning hours. So being able to leverage Europe and European members. So by the time the East coast woke up, which is the key peak of the day, we’d have a thriving set of discussions and community activity. So by joining the dots there, like so building this model so that where we could focus on. And then it came how do turn that model into a process which we could run with. So remember we had all the insights in the backend database. We had this then put into HubSpot, where we were gonna manage all this kind of stuff. So how do we systematically set up a system of emails to reach precisely the people we wanted to answer those particular questions?

And so we set that up. And that was a very manual process. Every single new question, they’d go in and from our prebuilt set of segments, email those precise number of people.

DR: So a question would come in and then you would email people that could potentially answer it?

ER: Yeah.

DR: Is that what you’re saying?

ER: And it would be like a plain text email, a Gmail type thing, something where I always find with anything that’s kind of data-driven or based on like you’re trying to personalize the experience, try it manually, try it one-off, and then try and scale that experience.

But for email, for asking a favor, you wanna send that like as a Gmail thing. You wanna send it written from like a person to another person. But then maybe just send that through an email marketing tool to many other people. That became the trick. That, by sending those hyper-personalized emails.

Hey so and so like Gus has asked about who else is going to Inbound this year. It’s his first time. You’ve been a couple times before. What would your advice be? Here’s a link.

Appreciate if you could pop an answer in this afternoon. Those kind of emails drove four times the click rate, i.e., for every 10 emails we’d send, we’d get four times the number of people actually back on the site than anything else we’d send. But it’s only because we had all that context, all that to be able to join the dots there.

DR: You saw, did you see things start to change there pretty quickly?

ER: Yes. So by, because of that growth model, which we, so we hypothesized if we’d increase the number of contributors by like focusing on Q & A, we’d increase the number of weekly active users, which drove the community metrics along the right direction. The platform would become this valuable destination again. But, despite having access to all the data, despite having this growth model, despite having this process, despite having all this set down, it was an incredibly manual process.

We didn’t get to a point where we could fully automate our way out of that. And so really this is where the kind of realization that yes, you need to get all those steps. You need to know where to aim, how to leverage that data, but you then need to be able to turn it into a system that will automate and assist in the rules.

And so the fastest growing startups and the fastest growing strategies we see with data tend to be around getting all those steps in order, but then be able to turn into some other business rule, some kind of if this then that logic, something which is, doesn’t require manual intervention each and every time.

DR: So if person has these traits, then do this thing?

ER: Yeah, exactly. So whatever that kind of sort of thing might be.

Now, with customer data, that might be something like how to send an email, but systems of rules expand much larger than that.

Something like pricing, pricing affects every single customer. Pricing is an incredibly powerful rule within your system, within that kind of system within a company. The guys at Profitwell ran a study comparing acquisition versus retention versus monetization, which is gonna be the most powerful set of levers?

And they found, I don’t remember the numbers exactly or how they measure it, but for a 1% increment in performance in acquisition, they would find a four to 8% increase with monetization.

I.e., pricing is four times more effective than acquisition and twice as effective as our working retention. Two times in my career have we done like radical pricing experiments without like much care. Like just doubling pricing and that just doubling revenue.

Now if you try and do the same thing with like acquisition, like you don’t just double acquisition. It’s just one of those business rules. It’s not something which can immediately deliver an impact versus how do you double search traffic? How do you double social traffic? How do you double the amount of paid acquisition?

Like it’s a different kind of thing. And so you need to think about okay what are the rules? What are the systems that’s fundamentally behind the growth, behind everything we’re working on.

DR: Well you when start working with these B2B startups that you’ve been consulting with or working with, you know, with Hull or wherever, where are people most stuck or getting it wrong or missing opportunities that you see and you come and you say, “Hey, let’s change these things?”

ER: So typically amongst, before you got product market fit, there’s a whole, you need to get that whole kind of set of problems sorted out.

So after that, once you’ve got like a first marketer in, you’ve got leads are coming in, you have a method of doing that, you have a method of closing that, that general funnel doesn’t look too bad. How do you scale from there? So people go and hire the best people they can find. They buy the best tools in the market. These are all very commonly well understood things. But the same amount of care and attention is not put into your data. And that becomes a drag on your teams and on your tools. Whereas the fastest growing companies think about their data on the same level. There’s a hierarchy to it.

Like teams own tools. Tools own data. And as teams buy more tools, like Proof, like email tools, like CRMs whatever, to do the jobs they have to do in order to grow, this creates a system of silos. Unless you actually think how to join this up and how to leverage all that and how to build rules and how to build systems across that, it becomes a drag on the entire company.

DR: You’re really only as good as the data that you have.

ER: Exactly, exactly.

DR: It really becomes frustrating. Because you have all these different pools, all these different audiences that you’ve rebuilt over and over. And like we did our daily huddle yesterday and someone running our customer success is like, “Hey, can I get these like two events sent in?”

Or like, “Hey, who even knows where the events are?” You know it’s like what are the names? It’s like this whole thing that is just hard to do across teams.

ER: Yeah, exactly so the companies aren’t then really short of data or like adding tracking for those events. Like that’s typically not the hard part.

The hard part is how to make sense of it and pull it all together into a system which is accessible. You can derive the growth, model the growth equations behind it and you can turn that into a process and turn that into business rules and like automation and so on and so forth.

DR: So I guess that kind of leads you into Hull.

ER: Yes.

DR: And I guess why’d you join up there? And like what were you guys doing there at Hull?

ER: So, I mentioned when, back at HubSpot, the data-driven insights came from connecting our platform, our backend, our MySQL database to HubSpot and being able to join the dots in that way.

Not just like literal data, but also join the dots in our heads. Like ah, this behavior is enforcing this. That took a lot of engineering time. We did happen to have those engineers. But most companies don’t.

DR: I’ve found even when you have them, you still don’t want to use them. It’s like, I’ve got a bunch of engineers back there. I still don’t want to talk to them if I don’t have to.

ER: Sure, so all right, I’ll get to that in a second. Right, so when I saw Hull, which had just pivoted to become this B2B platform, this was gonna provide the answer.

Sure it takes a lot of the effort away from engineering. It also empowers engineers. But this was gonna be the future. Everyone needs to be able to join their dots. Everyone needs to be able to understand their customer journey.

Everyone needs to be able to bring all that context to provide a better experience. So I joined there, again as employee number one. We began to figure out who are we selling to. Is this like what kind of area of the market? We knew we wanted to be B2B. We knew we wanted to be mid-marketish.

But was thing gonna be very small or was this gonna be like later stage? Is this selling to marketers or marketing ops or engineering or I don’t know?

So it was kind of like the customer development type stage. And we became to settle on a kind of direction. And I think, particularly 2018 onwards, we really settled on understanding the profile within these sorts of companies, which how they structure their teams to structure their data. And really the profile we see that’s emerging most is a growth engineer. It is an engineering role which doesn’t roll up to a CTO, which does not fall under product, which does not care so much about things like uptime and sprints or whatever, but rolls up under a COO, a CMO.

They care about supporting sales and empowering marketing and sitting all on that side. And the kinds of things they will be doing, you have data engineering, like sorting this data behind the scenes. It’s a bit more like a dev ops type role for the marketing space, for the marketing stack, and pieces around that.

DR: And is that a growth engineer as opposed to maybe a growth marketer, maybe a semi-type of a growth marketer? Is it an engineer only because it’s still too technical for a non-engineer to kind of run with that whole strategy?

ER: So, you could say if it’s the ability to code or not or things like that. I think there’s quite a lot of tooling which enables you to just parametrize things. Like you can quite a long way with tools like Salesforce and HubSpot just by fiddling around with parameters.

Key thing is really understanding how your data flows and what affects something else and the impacts that various different things can have. Understanding how data flows and what data you need, that’s the key piece there. And typically that involves, like you said, more technical skills.

Like you should be able to write a SQL query. You should be able to maybe write some JavaScript, whatever to manipulate stuff. But that’s like more kind of the skillset. In terms of that profile, so that growth engineer might not be like a VP growth. It might not be a managerial type position. And so who then goes and buys these things?

Who organizes these projects? Might be like a VP of Marketing, a VP of Demand Gen or like VP of Growth that brings this kind of in and has a data engineer. But really the trend we’re seeing in the fastest growing companies is that doesn’t even sit with marketing.

All sales, all CS, or anything like that, it falls under Ops. It falls under operations. So for better or worse, it goes through one service and that becomes the source of truth, both in terms of tooling and data and team for everything else in the company.

DR: Well you said there is operations that is saying “Here’s all the data “that’s true about our company.”

Every team is free to consume it, and we’re gonna make that available and clean.”

But it’s not marketing data. It’s not product. It’s just here’s the company data. Everyone use it.

ER: Yup. And so that should then be propagated to your system of choice. So marketing might be using a marketing automation tool, all their ads, their whatever. So that whenever they’re using it, they’ve got the most complete, most accurate, most up to date data at any one time. And they don’t have to worry about that. Like that’s someone else’s job.

Versus marketing having to try and hire a developer and try and manage this all themselves. And sales do the same and CS and products or whatever. So anytime a sales rep is on a phone or looking in CRM, anytime you’re putting together a campaign, anytime that you should have reliable, most complete, most accurate, most up to date data. And that tends to be how teams organize.

Not just in terms of tools, but also data. That’s how they structure themselves. And then growth engineers sit with that. Typically as companies are growing, projects like data warehousing and BI and like all that kind of analysis comes in. And that’s been something which has been around for a while. Like tools like Tableau, et cetera.

And what we’re seeing teams building the business case for this is that resource already exists. Can we do this kind of data engineering to empower marketing? It’s not just about pulling insights from like the Tableau dashboard and that maybe filtering through some report at management level and then eventually effecting change through some meeting. No, it’s about the real-time sync with the tools that those teams are using.

DR: So once companies kind of get some level of this set up in a relatively clean, relatively consumable, what have you seen these like companies that are most cutting edge able to do with that?

ER: So, B2B SaaS companies generally will fit into either like one of two camps. So if you’re very like low ACV, a lot of the automation around sales or like even cutting out sales. So like the freemium, free trial, how do you optimize that?

And on the other end, where you’ve got a much higher ACV, it’s how do you focus those resources around an account? It’s all about account-based marketing and account-based orchestration. So those are the kind of two big flavors.

DR: Let’s start with like the account-based market. Like what have you seen?

ER: Well so there’s a common set of things which ties all that together, which is okay how do you use and enable this data. Really we kind of think of it in terms of a set of six questions.

  1. Like who are you talking to?
  2. What are you trying to say?
  3. When are you trying to say it?
  4. Where are you trying to say it?
  5. And why?
  6. What’s the kind of reason through the funnel?

So who, segmentation, that rule is defined somewhere.

What, which tends to be something like, what is the content? What is the messaging? But also what is the templating?

Again, it’s defined by data. When, what’s the trigger? Events. Again, it’s defined by data.

Where, the tool, the channel, that’s defined by data. And why, where is it in the customer journey map? What is the experience through that? And then the final piece of that is how. How are you gonna really, really tie that all together?

So when you’re comparing like free trial optimization, it’s those set of questions applied to, okay, you care about people within their free trial.

The messaging, which is gonna move them forward. When, well based on the actions they’ve just taken. Where, we’ll probably take a scalable channel like email. So a good email tool like customer.io. Et cetera, et cetera. ABM, it’s the same story.

You’re just putting different answers to those types of questions. Which means that kind of the data management is often pretty much the same. We’re just working with slightly different sources and slightly different methods there. But the strategy and the questions you’re asking are exactly the same.

DR: Yeah, yeah, I’ve seen I think I was on or am on the email list from Hull. And after I got back from SaaStr, you were sending out these emails.

And they were all like personalized with all these different merge tags. And at the bottom, you’d kinda say, check out this link. Like see the personalization you know behind this.

What are the results of like those kinds of emails versus if you just sent out, you know, just a regular email that’s unpersonalized?

ER: Yeah so the, going back to what I was doing at HubSpot, sending those like personalized emails, I did a post on this including sharing the full numbers for the basically three types of emails we sent.

So we had a normal newsletter, which wasn’t really personalized at all. We had fake notification emails to try and bring people back. And we had these personalized emails. We found about 2.5% click through rates, or click rates, sorry, on the just normal newsletter. So that’s kind of a benchmark.

About 5% on the fake notification emails. 10%, i.e., one in 10 people would be back on the site that we emailed, which is pretty good when you send four million of those.

DR: Now, that is good.

ER: So that’s the kind of benchmark. If you think of like a really good SDR, or a level of personalization they would want to put into sending something out to get a response, that’s what you want to be aiming for with all your email, not just your, not just like the email where you can put the resource in to put the time together.

So yeah, that’s been kind of the answer to the question. So at Hull, because they, those emails were more like a newsletter style or like here’s content to consume versus me asking for a specific, you to do a specific action. So we see about like 5%.

So it’s still twice as good as maybe the newsletters we hope for. We didn’t send nearly the volume I did previously. But, yeah, 5% of people coming back to the site is not too bad. Definite room for improvement there.

DR: So I’m curious. I wanna get some free consulting for Proof here.

ER: Sure.

DR: Now if you think about us as an example. If you were to come in, you know, for a month, knowing what you know about us, taking what you’ve seen out there working with so many different companies, what would be like the tips or like the steps that you would want to put in place in order to help us kinda get to the next level as far as what data we have, what we’re able to do with that in order to grow quicker and grow faster here at Proof?

ER: I think there’s two sides to it.

One, in terms of kind of getting your kind of data in order, setting everything up. If you’re like a chef in a kitchen, get everything, like everything set up.

And then two, what are the flavors of rules which we could then build off that? So in terms of getting your data in order, what is the data model which you want to represent, build and represent across all your systems?

Who is your ideal customer profile? How would you describe them? What’s the data which you’re gonna need for that?

So things like industry, job titles of people and so on. What’s the context of how those people have engaged with you?

So based on their previous actions, what’s life cycle stage, et cetera? How do you represent that across your whole system? What’s your tracking plan? What’s the, so how are you building that whole kind of system of data that you’ve tracked in? And once you’ve got all that, and you have that all standardized across your system, then we can talk about, okay, what kind of things we can start to optimize.

DR: Here’s a question for you.

So an example, we’re personalizing our marketing funnel based on different industries as a kind of an initial starting point. You know, we’ve got basically four different industries. We’ve got SaaS, e-commerce, agencies (coaches, consultants, courses), and then other kind of has a you know separate bucket.

What’s hard is Clearbit doesn’t have all of the exact things we need, you know? So it’s like where do we get the right data to fit the buckets to actually have good marketing?

ER: To identify that ideal customer profile to identify whether someone fits that or doesn’t. So someone’s already hitting the website. You’re capturing their email and you’re sending that to Clearbit and getting that enrichment data back. But you’re not getting the match right. Is that what you’re saying?

DR: Yeah, well I mean, some of them, it’s like, okay Clearbit has a certain way that they describe things. You know, but they don’t have coaches, consultants, courses maybe in the same definition that we have. 

Or we may call you know, I don’t think they have like marketing agency as a tag.

ER: There’s some combinations of tags, yes. So there’s frustration.

DR: Yeah so it’s kind of like are we using it as we’ve talked with other customers. We’ve kind of helped them think through like personalization strategy. It’s like don’t want to start with okay what data is available and then build from there.

ER: What’s the question you’re trying to answer?

DR: Yeah, but there’s a big gap there a lot of times.

ER: So, imagine if your entire website, if you think of your entire website as a form and every interaction you can use for profiling, one of the things which we’ve found kind of interesting is building out sets of landing pages, sets of, around those types of topics, around those types of things.

So for instance at Hull, what integrations do you have? So we would also use data enrichment services, like Clearbit and Datanyze to identify this.

But one, well that’s not gonna get everything. And two, we wanna know what you’re interested in right now. So by building out those sets of pages and understanding how you’re clicking through the site, where you’re landing from, what other kind of messages you’re engaging with, helps to build that picture.

So besides the enrichment data, which is coming in, you have those kind of signals of intent, signals of interest from that stuff. But then also being like explicit.

Like asking people in the page. Like what integrate, are you looking to integrate with Salesforce? And then rolling that data in.

Then to keep all that clean and tidy and actually make sense, you then need to have a means of building what we call fallback strategies.

So of all the tools which you’re interested, from all these data sources, how do you prioritize which one is the most true?

So that when you do your messaging with your sales guys reaching out, he’s not got this like complete mess of data to work with, he’s got like here’s just the two things which you need to be talking about.

DR: You kind of weight different actions? Can I say okay there? Because like, so even with the industry deal, we kinda know, you know, you kinda tag different blog posts. Okay, if they’ve read seven agency blog posts, and three e-commerce blog posts, you know, which one are they?

ER: Yes, but then you have some level of intelligence

DR: Yeah, how do you kind of weight that to say you know is it the most recent one? Did they kind of switch from agency to e-commerce? Like how do you kind of know that what you have is true?

ER: Often the best thing is to leave that up to like the sales rep or leave that up to the person who’s gonna be managing that piece of the campaign. But to have that summarized.

Often systems in the past, like Salesforce, like HubSpot, were not built for this amount, like today’s amount of data. And so they force you to do things like have one field for one thing and tidy things up in that way.

Or otherwise limit and constrain your view on that. Whereas modern tooling, you can have everything or have everything expanded and linked and referenced. So for instance, like what’s the first page you looked at?

What are your interests there? What’s the first campaign you came in versus the last campaign. This is a classic multi-touch, multichannel attribution problem. You’re really limited by like first touch, last touch, fields, and that kind of thing. Rather, show me a summarized timeline of all things that they’ve done and then begin to deduce how their story from there. If you don’t have like a timeline or something like that to understand the context of how some people are moving through the cycle, then yeah you’re

DR: A lot of times you’re still kicking it to human intelligence to say, “We’re gonna give you a concise summary. “We’re gonna help condense it.

“You gotta kind of make some decisions.” Or maybe ask some questions there. But this is gonna give you a huge head start.

ER: Yes. And bring that all into their tool of choice. So they’re not digging into Mixpanel. They’re not like digging into LinkedIn. They can stay focused in their tool of choice, but you are gonna bring that complete summarized view. So they have everything there.

Think like a, like an Air Force pilot where they’ve got all of like the data coming into where they’re at. Like that’s what you’re aiming for. And that’s why you need that operationalized system in the middle. That’s why you need to join the dots, if you like, from the backend.

DR: Yeah, yeah, very cool. This is fascinating stuff. You know, and it’s complex, but the thing is you kind of, as it starts to make sense, you start to realize everything else just became so much more powerful.

And even as we’re like you know personalizing sites, like yeah, I mean, a piece of it is, you know, the actual tooling to do this, whether its email or on the page or whatever. Piece of it, you know a bigger pice of it’s probably the actual strategy, like do you have the strategy right?

But then you’re only as good as the data that you have available. And if you don’t have it, you’re just stuck in the water. Or you’re gonna be optimizing like 1% of your emails or traffic or whatever. And it’s like, this is cool. It makes a cool blog post. But I didn’t really make anymore money here. And I think that’s the hard part when it comes to doing it. How do you do it in a way that actually moves the metrics?

ER: So I think that comes from having access to the data like understanding the customer lifecycle, building a model, building an equation so you can describe not in conjecture or opinion but know these are the key levers.

Things like pricing, things like, I mean, for a larger company, it might be acquisition.

Acquisition by which channel? Or how do you convert XYZ people? And what’s the key lever there?

Things like segmentation. If you go and look at the conversion rates by industry. So you mentioned like looking at industry and what the spread of the different kinds of dimensions.

Maybe, industry is not the thing with the widest spread. Maybe people, there’s a bigger difference in how people convert by, you know, company size. And that bigger difference indicates one message is working far better and you can probably then even optimize and improve that. And you have the scope to have the others catch up. So where you can build a segmentation strategy based on where you’ve got the widest spread.

That’s, those are the kind of things. But it starts with access. It starts with getting that full picture.

DR: Yeah, totally. All right, I wanna hop into the salty six. But one last question before I do. I’ve just piqued your interest in the salty six.

ER: Yeah.

DR: But what are you excited about for the next few years of B2B SaaS? What are you, what trends are you watching?

What shifts in the market you know have you kind of seen? Like what are you gonna be personally watching and excited about?

ER: I think, okay, I’ve been in the marketing to marketers about marketing for a long time and the tech is getting particularly interesting. I think whilst there’s like big roll ups, there’s also like more and more interesting new niche players.

And how they grow and the directions they’re going. That’s very cool. But it’s what’s the profile?

Who owns that and how is that role gonna develop over time? So whoever figures that out and how to nurture and support that community and that group of people, I think that’s gonna be the next most exciting thing. Not just for the next five years, but the next 10, 50, 100 years. Like marketing, sales, it’s not become less data-driven. Whoever owns that.

DR: And who do you see doing that well right now?

ER: I actually think it’s a bit of a land grab. The thing about marketing to marketers about marketing, most of those companies are going for like higher level or less technical audience because it’s bigger. But the influence the people who are operating at the data layer have is far, far larger. And so yeah, I think there’s an out-sized return in the companies who can figure that out. So I think that’s the next, that’s the next gold rush.

DR: Yeah, totally, very cool! All right, Ed, the salty six. The six rapid fire questions for me to just get to know you a little bit better. Some about business, some outside of business. Sound good?

The Salty Six

ER: Sounds good.

DR: Number one, outside of raking data silos, what do you do for fun?

ER: What do I do for fun? So I like to cook and I like to fly. I like to go see places, like Austin. This is, yeah, those two things.

DR: What’s your favorite place in the world you’ve ever been?

ER: Home

DR: London?

ER: Yeah, like it’s fun to go visit places. But it’s that feeling of seeing the red, white, and blue tail and the cup of tea and the welcome back, yeah. That’s a good one.

DR: That’s awesome.

Okay, cool, do you have a morning routine, and if so, what is it?

ER: Oh boy. Yes I do have a morning routine, but it’s probably a little lazy and a lot of room for optimization. I’m definitely more a late night person than a morning person. I’ll put it that way, but yeah.

DR: Cool, cool, cool.

How do you focus during the day?

ER: How do I focus during the day? Turn things off. Yeah so, like for context, at Hull, it was in Paris and Atlanta, and I was the only person in London. I worked from an office that can be more distilled. So I wouldn’t be disturbed. You’re surrounded by people. You need the buzz. But yeah but so that’s kind of ideal. So to turn things off.

Having recently left Hull, I’ve taken Slack off.

DR: Yeah, I saw you turned Slack off.

ER: So, that is amazing! That is literally like coming off like a whole bunch of addictive things all at once. Like it’s amazing how addictive that kind of technology is.

DR: What do you think it is? Just all the different notifications like?

ER: Every channel

DR: Always got something.

DR: Whenever I’m slumping during the day, I just hop on Slack. It’s a little hit of.

ER: Yeah, and because it’s work, it feels okay. You wouldn’t do the same on Facebook. You wouldn’t do the same on like Instagram.

DR: I feel like I’m being a good team member by like being addicted to Slack.

ER: Exactly, so

DR: I’m just helping everyone out.

ER: It doesn’t have the negative feeling. So like turn things off. Delete apps. So things like LinkedIn, delete it unless you’re going to say like a conference or something like that.

DR: I don’t think anyone’s ever downloaded LinkedIn in the first place.

ER: It can be useful for like messaging around like a conference or something. But then, get rid of it. So delete stuff. Less.

DR: Cool, I like it.

Okay, what’s a book that has impacted you deeply in the last few years?

start with why

ER: It’s actually good, like “Start with Why.” I mean it’s not in the past few years, but like a little earlier on. Because you need to understand the Simon Sinek talk and then reading the book. Yeah, everyone knows what they do. Some people know how they do it. Few people understand why. Doing the reverse, much more reason to get up in the morning.

DR: And what’s the best purchase you’ve made recently under 150 bucks?

ER: So the best thing, so I do travel a little bit, and as a Brit, I’m very fond of my tea. You mentioned Early Grey earlier, and actually, you can pick those things up for free in all airport lounges. But Earl Grey and British tea needs to be served with milk, of course. We’re not savages. And so to bring proper milk, which comes in these little sachets. I say proper milk.

DR: What’s a sachet?

ER: You know just like a little. Pouch.

ER: Yeah, and you can get these like individual portions of that and that totally transforms the taste of tea. Couple of pounds and it totally makes your day.

DR: You bring those with you?

ER: Yeah, I’ll show you in a minute.

DR: I love it. I can’t wait.

ER: That’s probably the best happiness hack.

DR: Okay. Perfect, okay, then finally, number six, what’s a trait or characteristic that you have that’s led to your success today?

ER: Trait or characteristic, I think like always asking why. And maybe, maybe not really letting go on that. I think it must be a bad habit. But like from like an early age having like pretty senior people to work with and maybe not, respect is probably the wrong word, but like seeing people as kind of equal. Reason and whatever.

DR: Is that curiosity? Is that skepticism? Or is it just?

ER: So curiosity, yes. Skepticism is like I want to believe, but help me understand why. Like that’s searching whereas cynicism is something else. I’m not a cynic, but skeptic.

DR: Skepticism is like I’d like to get there.

ER: Healthy.

DR: If you can help me get there.

ER: Yeah and you like to have like a good working relationship with people where skepticism is a very healthy thing. You need to be able to have and exchange a difference. I don’t do very well with hierarchy, top-down stuff.

DR: You just break in, say, “I’m here to ask questions.”

ER: Yeah, forgiveness, not permission.

DR: Yeah, yeah, yeah, very cool. Well, Ed, this has been awesome, man. Thanks so much for geeking out with me over all things data. Thanks so much for watching Scale Or Die. And Ed, if people want to find out more about you, see what you’re doing in your next stage of your next venture, where can they find you?

ER: Sure, Twitter’s good, @edfryed. And LinkedIn and you can also check out behindthegrowth.com for the next big move.

DR: You’ve got some good tweets. I’m a recent follower. I’ve been following the Twitter. I recommend it. Check Ed out. Awesome guys, thanks for watching. We’ll see you in the next episode.

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This interview has been edited and condensed.