Philippe Gamache  0:00  
What's up everyone. Today we have the pleasure of sitting down with Ezra Fishman VP of growth at Wistia as he started his career as an engineer developing devices to help treat diabetes and obesity gi dynamics. He later had a short stint as an operations manager at an investment firm that was dedicated to funding health tech startups. After completing his MBA as rejoined a video tech startup called Wistia as their director of marketing, and after four years, he transitioned to leading business intelligence. And today as VP of growth at Wistia, where he's now spent over 12 years seeing the company grow from a handful of customers to over 375,000 customers and becoming one of the top V pass tools on the planet. Ezra, thanks so much for your time today. Really appreciate it. Yeah,

Ezra Fihsman  0:47  
absolutely. Thanks for having me.

Jon Taylor  0:50  
So I want to start with, you know, as your journey in Wistia. So as Wistia is first customer, and then later on as an early team member, you've seen the company from both sides of the lens. What was your aha moment when you realize you needed to switch from being a client to actually joining the clean team? And once inside, did you have a moment of revelation or a bold move that completely flipped the script on how Wistia operated or approached his business strategy?

Ezra Fihsman  1:15  
Yeah, solid, solid questions. So yeah, the origin story, my origin story for Wistia is, is an interesting one. So So Wistia is founded, Chris Savage, and Brennan Schwartz, they were actually both good friends of mine. So we were all living together in Boston, when they quit their jobs and said, Hey, we're gonna go start a company. We don't know what it's about. We don't know what it's going to do. But we're going to start a company and I said, I was working medical devices. I said, Good luck, Godspeed. They came back after a few months, we're like, we're gonna do something with video. We don't know what it is, or they were thinking around like, a like thinking about artists and people that need portfolio sites. And we're sitting around talking like, there's not a lot of money in artists aren't intended to spend a ton of money. And I was working at this company. And we were doing medical procedures. We were doing endoscopic procedures, and the scopic procedures all end up with video at the end, because you have the endoscope and the craters video. And so we were doing these procedures all over the world, and mailing DVDs around the world, to different doctors that needed to watch the video, the recordings and share their feedback. And so we're sitting around one day and was like, hey, Brendon, Could you could you make Could you do something here that would just make this easier, and this company will pay you money for it in real money for tomorrow, if you can help us do fix this? And he was like, yeah, that's That's easy. That's, that's no problem at all. And that was that was obviously it was born Wistia kind of was born out of that became a private video sharing, and collaboration platform. Jed dynamics was customer number one, we I brought them into the office, and we had a meeting with my boss, and this was another startup and we were like, hey, instead of mailing these DVDs around, what if we could just upload them? And have the doctors comment on the website? And it was like, You mean, like YouTube was like, Yeah, but not on YouTube? These are surgery procedures, maybe it'd be private. And, and yeah, so that's, that's what we're seeing is born. I, you know, the company, the Wistia found some more customers, kind of, in that vein, you know, some medical device companies, some people that were, you know, production houses that wanted to do, you know, share their proofs of videos and, and kind of give feedback, not not put it out in the wild. And kind of that yeah, that's how that's how it all began. I didn't. I went to business school. It was five years before I finished business school just had a just went to get lunch with Chris. And Brendan was like, Hey, how's it doing? How they're asking me, What are you doing next as around like, I don't know, gonna gonna find something probably in the healthcare space. That's where I was interested in. And yeah, we started talking. And they were like, well, we're at an interesting place. Now we're like, we think we're finally getting some momentum. And we can use some help on the marketing side. Would you be interested in that? And I was like, Well, I don't know anything about marketing. You don't know anything about running a company. our powers combined, this will probably be great. And so yeah, so then I joined Wistia and yeah, we made a pivot to focusing less on the like, internal, private video, and more on putting video out onto your website. This video embeds tracking performance. And that was, I would say that was the pivotal shift in the Wistia journey was from kind of this private internal tool to use Video for marketing, put it on your website, track how it's performing. And kind of shortly thereafter, obviously, because I had joined, we started grow a lot. So we started we unlocked kind of customer growth and got a free plan out the door. Kind of just started to get, you know, tons more users tons more people on the platform. And yeah, and then the company is, you know, it's we are not a VC backed, firm. We're not like, Go big or go home. It's been a you know, slow, steady rise. But yeah, now we're lots of customers, lots of users. You know, we're big company now. Over 200 people. That's, that's huge.

Philippe Gamache  5:59  
Supercool story. Yeah, I feel like 200 people probably feels massive compared to the early days. So like, you were employee What, like less than six? Yeah, six or seven. Nice, very cool. Surgical story. I feel like I heard pieces of that. From listening to some of the different co founders I know they're big on like other video podcasts. And I checked out the podcast series that Wistia does, as well. Such an amazing production ourselves on our side, we have a lot to learn from, from you guys there. But we joked before recording that you're pretty dark on on the socials. And usually for our interviews, we go deep on social research and poke questions about some of the posts that our guests made those a bit hard for us to do for you. But on the plus side, you've written a ton for for Wistia. On on their blog. And there's one article I wanted to start by poking you about I read through it. And I guess it felt like prophetic in a sense. You called it beyond Funnel Vision. In the article, you advocate for this idea of focusing on building an audience rather than just capturing leads way before this became the norm for many companies feel like some folks listening right now might be like, Yeah, well, obviously, like, that's core to marketing, you want to build an audience. But you know, 12 years ago, that was crazy. It was a crazy idea. Like I remember, it started my career two years ago. And this idea of like capturing leads and having gated content everywhere, like that was the goal of b2b. Right? So how were you able to foresee the shift and marketing focus? And what influenced your early realization that there was a huge importance in building an audience first, before capturing leads? Yeah, for

Ezra Fihsman  7:44  
sure. And you talked about the shift. But there's a lot of people that are still on that other side. There's a lot of there's a lot of marketers out there that are, you know, and a lot of CEOs that are asking their marketing team, you know, well, how many, how many qualified leads did you get this month? And, you know, forget this audience stuff that that's BS. So So yeah, I think for us, it was, honestly, it was, it was see what was working for us at Wistia. And what we were finding was that we were making content, you know, in the early days, making a lot of content about how to how to create video, how to use video kind of more effectively, how to create video on a on a budget. And we were getting lots of engagement, lots of people that were you know, commenting on blog posts, commenting on Twitter, really just kind of engaging with the brand. And then they were telling other people about the product. And it was it was kind of spreading, and we could see, we could see, you know, it's hard to measure that behavior. But we could see when we put out content, we could actually see the number of website visits. And the number of signups go up in the days following that we couldn't say like, Hey, George, over there, shared it. But we could see that behavior happening. And then when we started to kind of lock things down and say like, Hey, you have to put in your email to get access to anything. Just the number, the number of people engaging with our content went way down. And, you know, the trade off, the trade off just started to become pretty obvious to us of like, hey, just get more people engaging and engaging more deeply. And it put pressure on, you know, what the content has to be good because you have to, it's not about getting like people to download one thing, and then pestering them with sales. It's like you got to create good stuff, that then they want to consume another thing. And then another thing, and I want to opt into that, and then start telling other people about the company. And so it became clear it was, you know, a quality, a quality game, more than a quantity game. And that was like another thing that was like, I think controversial at that time. I mean, I remember having conversations in the marketing team being like, hey, it's it's not about putting out 30 more blog posts this month, you know, there's an element to that there's an element to, you know, ranking in search and being relevant. But qualities, quality is just much more important. And yeah, that's how we started to just picture, picture our audience as like, this behemoth thing that we were growing, and we're really, you know, trying to get fans. And that that really started to shift how we approached marketing.

Jon Taylor  10:37  
I feel like there's, there's a lesson here good marketing metrics can make good marketers do really bad things at times and your own career growth. At Wistia, I've actually find very fascinating from director of marketing to director and VP of Business Intelligence to your current role of VP of growth. So you understand the data picture inside and out, no doubt. And I don't think I'm going out on a limb here and saying that you probably put a lot of stock and data, but just based on that last question, in response, it feels like you also put a lot of stock into the qualitative elements of marketing, and building quality, you know, engagements with your audience, not just measuring everything to grow. So maybe walk us a little bit about how your tenure in business intelligence helped you prepare you for your role as VP of growth at Wistia?

Ezra Fihsman  11:23  
Yeah, yeah, absolutely. Yeah, I like to say that I have had different roles warn different kinds of responsibilities weren't different hats. But also, it's like, a lot of the same stuff, you know, marketing, bi growth, there's, there's, there's a lot of overlap in those circles, of kind of, you know, how are we how are we attracting people? How are we converting them? How are we using data to make better decisions? And yeah, I think I joke about kind of, I'm a data guy, I like data, I'm comfortable with data, I like using data. But I'm also a data skeptic, I've seen all the ways that data has failed. And, you know, I, you know, data is not that is not the Holy Grail. For me, it is a useful tool. It is a useful input to decisions. But people have to make decisions. And, you know, I think, at times, at times people fall in love with data, you know, say like, oh, data is the data is going to tell me what to do. And, you know, I think that's bullshit. You're not, you're not going to be very successful. I think, if that is your mantra, talk a little bit about like, data informed decision making, rather than data driven. And, and, yeah, I think data can tell you a lot of things. But it also is not going to reveal the answers. We, you know, we talk a lot about I think there's a tendency, when you've got a problem, to say, well, let's go collect all of the data. And like, let's go, let's go on, uh, you know, collect all the books for this research project, collect all the data and see what the answer is. That my experience is like, tends to be wild goose chases, you're just kind of collecting looking for patterns, you can convince yourself of almost any pattern. I'm a much bigger believer in taking action, or having a hypothesis and saying, Hey, does the data prove or disprove that? So I believe that our best customers spend, you know, only a little bit of time on the website. Because I've talked to a handful of customers, and they're not interested in doing a bunch of research online, they want to get right into the product and start using it. So I've got some intuition about that. I have this belief, I can go use data now to test that. And to say, like, Hey, is that right? Is that wrong? Which sets of customers that right, it's never gonna be right or wrong completely. There's always gonna be like a little bit of both. But you can go use that and test and like test that hypothesis, you can put them out in the world and test a hypothesis. And that's, that's how I see kind of the most effective use of data is when you have like a specific question that you're trying to answer a specific thing that you can kind of say like, yes or no or kind of, in which case, is this true? And kind of, at the root of your question is, you know, can you misuse data? And yes, I think I think that is honestly more common than using data, I think effectively misusing data.

Jon Taylor  14:48  
It's, it's pretty fascinating. I was employee number eight at a business intelligence and dashboarding company and grew up very much like the messaging around data driven, and all of this so our See what you're saying really resonates quite a bit from my own kind of first, my my real world experience working with customers who do deploy dashboard and BI in their company. And probably my number one takeaway from my tenure in that company was that unlocking the value of data is really about that human connection, you can build all the cool dashboards and reports and analytics at the end of the day, it's really about being able to use this information and communicate it to the humans who are making decisions. Talk to us, and you kind of touched on this, but I'd like you to talk us through a little bit of the soft skills required to work with data and have your organization be data informed, because I don't think you're saying, don't look at the data, you're saying, make really good decisions, but use the data to back it up. Just don't rely extensively on it. So maybe you can talk a little bit about the soft skills around this. Yeah,

Ezra Fihsman  15:51  
yeah, I think there's, there's a ton of there's a ton of soft skills. You know, I think it starts at the very beginning with just like trying to understand what people are hoping to learn what what they're trying to get from the data. All the time, this is like, I think, very similar to like, the classic like product manager role of like, well, customers are saying this thing, but what are they really saying? And so the same thing applies with data with bi with kind of market data, you know, the ask from the internal customer is, you know, can I have a dashboard that tells me this, this and this, and it's like a long list of things. But the real challenge is like, well, what are you actually trying to find out? What is the what is the question that you have? What are you looking for input on? And, and then the answer to that is often related, similar to what you asked for, but not exactly what you asked for, or, you know, hey, we can we can get you the data. But it's not going to tell you exactly what you're going to look for what you're expecting. And I would say like, a classic example of this is we're often looking at distributions of behavior at Wistia. And so how long does it take people to purchase? How long does it take them to upload their first video? What? How many videos do people upload when they start uploading video and kind of questions like this, and what we found is, I can tell you what the distribution is gonna look like without doing any work is, you know, there's this same pattern of kind of exponential decay, where most people are going to do nothing at all. A few people are going to upload one video, a few other people are gonna upload two, three, and then on down the line. And doesn't matter what the behavior of the question is. That's what the distribution is going to look like. So if you just want the distribution, I can already tell you what it's going to be. There's like another question behind that. That is like, what are the like, what are the outliers doing? What is it? What does it take for people to be motivated enough to upload two or three videos? And, and those things that data is not going to necessarily tell you or the simple distributions not going to tell you? Or the other fun one that everyone loves to ask is like, what's that magic number? You know, that that magic number? How many? How many pages of the website does someone have to look at before they're going to convert? How many uploads do they have to do before they're going to become a long term customer? Also be yes, there is no magic number, there's, there's going to be a distribution, the magic number is for ease of communication, for telling the story internally so that we can all remember it. That's what the magic number is. The people that upload two videos, people that will have three are gonna be better than those people that will look forward and be better than those five is gonna be better than those. We make up the stories of kind of magic numbers, magic things, to give ourselves something to run after, and to make the world simpler. And again, it's not. You know, it's not to say that there there aren't, at times, like differences in the data where like the difference between inviting five friends and six friends is meaningful and there's something there. Sometimes there is but it's never it's never a black and white. That's like Well, five is great. Six is meaningless. Four is meaningless. That that is not I've never seen that to be the case.

Philippe Gamache  19:49  
Yeah, definitely not black or white. It makes me think of some of the conversations we've had around PQ ELLs, like product qualified leads with this whole shift with like product lead Mark Getting like, everyone needs to drive to this number like I forget what the what the one was for slack like number of team members invited like, it's like our Northstar like we get to that number. And we're good for that person like it's obvious a distribution. So I like how you you broke that down and totally agree I want to ask you like what, what other growth metrics are kind of top of mind for you when when I asked you like what what are the most misunderstood growth metrics and you've written a lot about LTV to CAC and payback period, like just Just curious your take there?

Ezra Fihsman  20:34  
Yeah, yeah, I mean, there's so many there.

Philippe Gamache  20:43  
We can have our own bucket that sort of Yeah, yeah,

Ezra Fihsman  20:45  
I think the, if you zoom out a ton, this is like the, again, the fun magic numbers like this, this rule of 40 business metric of like, hey, you know, what is your growth rate? What is your EBITA? And there's, there's something magical about 40. That's, that's not true. There isn't, there isn't anything magical about 40? It's a range, it's a distribution. It's, you know, a nice round number, which, again, is helpful. I'm not disputing that, like, a sense of like gray and ranges is like, hard to understand. But I think, I think if we acknowledge that part of it and say, Oh, here's how we're simplifying it, then I think we'd be more intellectually honest. And like, it's easier to know that, like, 38, is also just as good as 40. There's nothing magical. Yeah, I think LTV CAC are like, nice, nice ratios Nice. Again, this like magical, you know, three to one ratio is not really magical. About three to one. CAC is like, really messy. Every every single organization I've seen measures differently, what things do they throw in the bucket versus what things don't they? You know, I think, I think that is really hard and challenging. I think that we've used, which I think is like a little bit unusual, unusual, not unusual. We are, you know, we're SAS business. And we talk a lot about kind of monthly active users, weekly active users and those things. And I think that is most More typically, you know, something with an ad based business, where they are thinking about, you know, active users on the platform matter a ton. Because you're filling it via advertising. We've started to talk more and more in the last couple of years about kind of some of those metrics as just basically a measure of like, How valuable is the platform? How sticky is the platform? And I think, I think that's probably a an underutilized measure. I get NPS, I think NPS is a very crude measure of what, what it is, we, we prefer to look at, like, hey, are people actually in the platform using it? And use that as like a more consistent measure of like, are they finding value? What is that action, say? In terms of where they're seeing value.

Jon Taylor  23:43  
So when Phil was talking about Slack, and like the number of messages sent as being kind of a true north growth measure for product, lead marketing, or product lead growth, like I can tell that there's maybe a little bit of a opinion that you may have, I want to route into that. And I guess my question here is, how would you approach something like product lead marketing, from like a product measurement standpoint, like a lot of people like to have that true north to be able to drive to like, hey, I'll set my automation up to try this action. And it's really clean, it's really easy story to tell internally. But as you've outlined here, the real growth story doesn't happen through a bunch of metrics, it happens through people doing things in your product and engaging with your with your brand and your product. So maybe walk us through how you would set up like a true north metric for a product like, obviously Wistia or slack. Yeah,

Ezra Fihsman  24:34  
yeah, I think. I think there's just like, some amount of like, acknowledging the, the imperfections of it. And so, you know, we, we use OKRs here at Wistia. A fair amount, not novel, but but we when we're doing that we talk a lot about the objective being the thing that we're trying to do. So, you know, we want to Make Wistia, the most beloved video software company we want to make. We want to make a real dent in the market share over this year, things like that, and then talk about the key results as being often imperfect measures of that thing that we're after. And saying, like, we're gonna look at them a lot, we're gonna measure our performance based on that, but they're also imperfect. And so there's, you know, they're like, We don't want to fully put the blinders on and say, like, hey, just go optimize for this one thing. Kind of everyone in this business as adults, that we can understand nuance a complication and say, like, Hey, here's what we're going after, as an objective, think about your work, and whether it serves that objective, how we're going to measure progress, is kind of these numbers. And, and honestly, also saying, like, trying to be upfront about like, hey, how imperfect are some of these, you know, some for sometimes, if we're trying to grow the business, we can invest more revenue is a pretty darn good measure of that. And then on the same time, we have brand OKRs, and we're trying to increase the perception of Wistia, or the amount of word of mouth. And, you know, organic search volume for the Wistia term is not not a perfect measure for that, but it's okay. And, and just acknowledging, like, when each is the case, I think is pretty critical. So I like I like true north things like we simplicity is a big is a value here at Wistia. I think it is, like helpful to have some simplicity and kind of things that you're focused on. The one thing that we talked about is like, on that front is simplicity, but not papering over a thing that we're like actually trying to balance. So we as a business are often talking about, we're an independent business, we're talking about, hey, like the growth in customer number in market share, is very important to us, but also revenue, and like making growing a sustainable business is very important to us. And at time, we've said, well, for simplicity, we're going to pick one of those things and say, that's what our focus is. And you know, having one focus is nice. But this year, we were like, That's not true. We're actually trying to balance these two things. And so let's, let's be honest with ourselves, and be honest with the company and say, Hey, these are the two things that we're telling and trying to keep it balanced. And we're prioritizing this one over this one. But that's how we're thinking about it. And I think I think there's something to be said for. Yeah, I'm diverging from your question a bit. But like, there's, there's value and simplification. There's also downsides of oversimplifying to the point where you're not really representing kind of what the leaders of the company are thinking and feeling. And you're so when it gets to that point, we say, well, let's see what we're thinking instead. Instead of trying to oversimplify and get to this nice, beautiful Northstar metric

Philippe Gamache  28:38  
I love the I love the the balance that you're you're pulling out there, it's it's easier said than done. You want that simplified Northstar metric that the whole company can rally behind. But also speaking to the nuances behind that number and how it's not just one number. There's so many like metrics that are leading indicators to that number, and you're devaluing the work that maybe another team is doing that doesn't directly impact that number. So yeah, OKRs Northstar metrics. There's there's a bunch of different ways of doing it. But I like the transparency approach that you're, you're pulling out there as an independent business, I think that's a super important have having been in BI, I guess, like, one question I have for you is, like, how big was the BI team when you like, quote, unquote, left marketing, but still work kind of marketing and went over into Bi? How big was that team? How closely were you working with the data team? Like I think of my startup experience, 12 years ago, and like, there, there were no engineers that worked on data, like marketers were stuck learning API's and, and SQL scripts and trying to figure out how to get data into the tools that we care about. But I'm curious to wonder, I'm curious to ask you like, how, how was the evolution of the data team at Wistia? And what role did you play in the

Ezra Fihsman  29:57  
Yeah, yeah, exactly. So it So there was no data team, that that was kind of my transition from marketing to bi was to start the data team. So it was a data team of me as we started. And then we grew that to a team of three, there's three of us. And we often had an intern. And, and that was like the right size, just like, you know, Whiskey was probably 5075 people. And so yeah, so so we started off. Yeah, just really looking at where, where the biggest priorities were in, in the business in terms of like, where we were flying blind. The, you know, the senior team, obviously got like, a lot of attention at the outset. And then quickly went towards like, marketing, because marketing was Yeah. Yeah, didn't have a lot of visibility, had a lot of a lot of disparate systems. A lot of things that just kind of needed to be wrangled and simplified. So yeah, started out started out as a kind of team of one, it was, you know, started out very scrappy, I was, you know, writing, writing SQL, putting it into spreadsheets, sharing Google sheets with people. And then as we hired kind of the second or third person, we kind of built out RBI infrastructure, built out the systems and tools to actually scale it. And And yeah, that that was kind of the the evolution of the team.

Philippe Gamache  31:41  
Very cool. Talk to us about that tech stack that activates the data for marketing and growth and, and how that's evolved over time, I was looking at some of the code on the site, and I can see some five trans stuff going into the warehouse. We're big fans of census obviously sponsored the show, and then that's pushing data into your marketing automation tools. Like, yeah, curious about that journey on the on the tech stacks, though.

Ezra Fihsman  32:06  
Yeah, yeah, we were very, we were pretty early on the on the five Tran side. So we, you know, we, we quickly went to a centralized data warehouse. So have kind of redshift on the back end, quickly went to, you know, in the early days of forming that BI team, adopting five Tran to just do the ETL just get get all the data from all of our different systems into one place. And then through mode analytics on top of that. So that was that was kind of the base of our BI infrastructure, probably for the first three or four years, just kind of throw everything into a data warehouse, throw a BI tool on top of it, be able to create dashboards, single source of truth, be able to look at reporting, and that kind of served us well for a while. And then you inevitably run into the next set of challenges where it's like, well, I want that same data in all the other tools. And yeah, it took us a little while to find census. But but then found census and said, Okay, well, here's the missing ingredient, here, which is now take all that stuff that we are that the BI team owns, and has organized in this data warehouse has put has put kind of rules on top of that. So big shout to DBT, the early early adopters of DBT big fans of the platform and the team there, which just for folks that don't aren't in the data world. It's basically just a semantic layer, a way of kind of putting your business rules on the data. And so it helps you kind of organize your data, organize the different tables in a way that's kind of much more much easier to then consume, kind of as an analytics platform or in other tools. And so, so yeah, combining that and then using census to then take all that data that's kind of BI has kind of organized and kind of put their stamp of approval on and then send that out back into the, into the tools. So back into HubSpot back into Salesforce. And that that continues to be our kind of our stack up today. And works pretty well. Cool. Awesome.

Philippe Gamache  34:25  
I appreciate the detail there. It's not totally surprising, but I guess like what I find interesting is that you almost went down the redshift data warehouse centralized road pretty early on. Like, I feel like a lot of companies even back in the day like a decade ago, we're still on the train of debating what is that source of truth? Like where are we going to put all that data and there was debates about the CRM being the source of truth or the marketing automation platform and then your connecting mode or your BI I tool through individual API's through all of the third party tools that you're using. But you guys kind of like were ahead of the curve there and foreseen this idea of having this centralized data warehouse and redshift kind of from the ground up. So I guess that that saved you a lot of time, several years down the road. But yeah, curious if you can share any details on that decision? Pretty early? Yeah,

Ezra Fihsman  35:23  
no, we were, we were very happy about that decision, kind of looking back. I think one of the key drivers for us was we realized that we wanted to just own all the data. And so we we looked at kind of other ways to approach it and realize that we were going to get potentially stuck in other tools. And either kind of from like a, from a pure, just like pricing perspective, being like, hey, well, you know, our, our database, or this stuff is this size today. And it could be 10x In the future, and we want to have flexibility, or just like having the the ability to move data around, do exactly what we want to do with it was like a priority for us early on. And so that's, that is kind of that drove our decision to kind of have this central data warehouse that we had a lot more control of, like, hey, we can see exactly what the data is, we can move it around exactly how we want we're not held captive by other tools or platforms, or by other schemas. You know, so that was that was a big factor, kind of in, in our, in our early choices. And then yeah, we we asked around a few folks kind of what their advice is for building this stuff out. And then we've since it both in the BI role in growth, like to talk to other teams, just be like, hey, what, what are you doing? What does your tech stack look like? What is What are you struggling with? And that was one that we found very consistently, we were like, Oh, we're so glad we're not in their shoes. And so I continue to do that as again, the head of the growth team tried to get our growth team talking to other one other teams, if nothing else, just to commiserate and realize that like the same shit that you're struggling with, Everyone is struggling with. Nobody has figured this out. Other people have worse situations worse at abs, you know, there's conflict with sales and marketing. And it's like, yeah, that's not unique that everyone faces that. So that's been good.

Philippe Gamache  37:32  
becomes a big therapy session.

Ezra Fihsman  37:35  
Exactly.

Jon Taylor  37:38  
I want to switch gears a little bit and ask some questions around growth marketing. So like, when I was coming up in marketing in the early 2010s, growth, hacking and growth marketing was so new, I remember everybody was like, so in vogue of, you know, all this quick shift that you could do to get your first 100 customers 1000 customers. But since then, we've seen like the product lead movement come out where I think there's a much more mature approach to growth teams. And, you know, we're seeing this as like a multifaceted discipline like yourself, like you're integrating business intelligence and data along with your Mar tech stack, to achieve growth. And I'm sure also working with other folks within your organization, maybe you can talk to us a little bit about what is growth look like at Wistia with like a, as a more mature organization with more customers and, you know, thinking about market share problems. And how does that contrast necessarily to even like a smaller startup and that early growth stage? Yeah,

Ezra Fihsman  38:34  
yeah, absolutely. I mean, I've always hated the the growth hacking, we're talking about who, but But yes, so I always prefer scrappy over over that. And I think there's there's plenty of room for scrappy approaches, scrappy tactics. Yeah, we are, you know, we are, you know, more mature, you know, we've been around for a while we, you know, have solid customer base solid revenue. And so I think we are at the place where, like, we talk about growth as like, a portfolio approach, where we are doing some amount of optimization, and then some amount of kind of total exploration, big bets. And so, I think, you know, that is the right call for where we're at, you know, that there's always room for optimization. And there's only there's only so much upside to optimization. And so we're, you know, looking at the the journey of the website, looking at the purchase journey, and looking at, you know, hey, how can we get a little bit more out of that, but also kind of what are the what are the big opportunities that could be step changes for us, in terms of you know, acquire Hiring a ton more customers acquiring a ton more bigger businesses, things like that. And so I think, yeah, I think that's where kind of some of the more mature kind of growth comes from, I think in the, in the early stages. There's a version where it's like, you're so scrappy, that you are literally Yeah, just trying to get the first few customers in the door. The first 20. We talked a lot about, like, don't worry about how this thing scales. It's like, it's easy to get caught up in like, well, we could do this now. But what's gonna happen once we, you know, get the first one, and it's like, okay, we'll get the first 20. And then we'll worry about that problem. So I definitely would advocate that believe in that generally, as like a as an approach. And then yeah, there's like, we, we do things like pretty cross functionally, we have a more mature, like product design, engineering, or more mature marketing work. It is kind of more important, though, not critical, that like all of those things stay in sync. Again, we're only 200 people, we're not that big. But But yeah, we make kind of make those efforts to make sure that we're like, totally consistent story have a consistent brand voice, there's a little bit more of the coordination side. In a smaller company. Coordination is just not as important. It's just not there's not as there's not as many people have to coordinate across. And you know, you're starting with you starting with nothing. And so like, Don't go crazy on that on that from

Philippe Gamache  41:46  
haven't been at Wistia. For for as long as you have, like, I'm sure. on the growth side, there's been a wealth of memorable experiments and tests that you've ran, I'd love to hear maybe some of the successes that come to mind right away, but also, the failures or maybe like some of the surprising outcomes. Yeah, the

Ezra Fihsman  42:06  
failures are more interesting. Okay. There's, we did a, we did an experiment. We, so as a video platform, we have this, I guess it's not, it's not that new now. But at the time, we were introducing it, we were going to charge for bandwidth. And we realized that like, this is a weird thing, like how many gigabytes are consumed by video, customers will have no intuition about how much how many gigabytes they'll use, or what they'll use or anything like that. And so kind of we knew that we thought about different ways to present that we, yeah, we kind of played with like a calculator to calculate it. And then, you know, tried to translate it in the number of views per month and do all these things. And then we eventually ran a test. We had a, I guess, we had it and we had just like, not very prominent on the site of, you know, there's some limits, but they're, they're kind of buried, they weren't very prominent. And we were getting questions kind of in support about like, Hey, what is this complaint? So we said, Okay, we're going to, we're going to be like, very customer centric, we're going to be as transparent as possible. So then we, we've made the bandwidth, this much bigger thing on the website, we put in this calculator. We tried to explain as much as we possibly could about how bandwidth works, what you would get charged for it. And the number of questions went through the roof, the conversion rates went way, way down. And it was just, it was just a disaster. And we were so sure, we were like we all are like looking at this. And I was like, Oh, we got this awesome calculator. We got like all this q&a. This is like, good on us. We're like doing so right by the customer. And it just led to more confusion, more questions, and went back and just buried it and raised some of the limits and said, like, Hey, we're gonna try to like, make this not be a thing that you have to worry about very much. But yeah, really did not go did not go as we expected at all.

Jon Taylor  44:33  
We've talked a little bit about like the difference between data informed versus data driven. And I think I think some of our listeners are probably feeling the way I feel a little bit of a relief to hear somebody talk about data this way, right using using data to inform your decisions, but not necessarily always being led by the nose. When you're talking about setting up these, these tests and a B testing, how do you approach it at Wistia to test your bets in market like what is the test Learn experiment process kind of look like on your team? Yeah,

Ezra Fihsman  45:04  
yeah, totally. Next step will the step one is the most important, which is like, can we actually run this as an experiment and AB test and like, everyone skips that step. And that's the single most important stuff there is. If you have 20 visitors a month to a page, you cannot run an AB test for this, you just can't. So forget it, like, make a call, decide what's best. Run with it. And so there's a lot of parts of our website, a lot of parts of our flows, we can not run a B tests in any timely manner, to get information. And so we don't. And then there's, then there's the homepage, then there's some of the signup pages, and we haven't have a good amount of volume on our website, and so we can run some A B tests, and we do, and we still try to test bigger items. And start with, you know, a strong hypothesis that, you know, hey, we think we think people don't care about this part of the platform, we think, you know, they are really coming with kind of several different problems in mind, versus like, one clear problem in mind. And then, and then we kind of design a test and run that. And, you know, I think that that first step is critical, having like, a clear hypothesis, and like saying kind of what you think, is very important. The other, the other important thing is, for us, we also use, we use some A B tests, when we think the differences might be just like, pretty hard to measure. And so when we think when we're not sure about kind of the size of the impact, or the scale, the impact, we may run an AV test and say we're gonna run it for like, two weeks, we're not worried about statistical significance. We're not worried about those things. We just want to use this as a way to have a control. And so I've actually, we've actually started to talk about that more as a business, which I think is a helpful framing, instead of talking about a B tests, as a framing, talk more about having control groups. And so like, if we're going to make changes or do things, can we do it with a control group? And measure the impact? Because that's what we're doing the whole time, right, is we're we're trying to make changes to the website, the product, we're trying to have an impact. And all we're doing is saying like, hey, is there a way we can take a control group and show what impact we're having? And I think that is like a healthier way to think about it healthier way to say like, Hey, we don't have enough concurrent traffic, that we're going to do that. But we're going to use the past three months as our control group, and it's imperfect. But that's what we're doing. That's what we're able to do. And, yeah, I think that that has generally been our kind of approach to AV testing. It's, again, it's another tool that is at our disposal. It is not like some magical answer that solves our problems.

Philippe Gamache  48:39  
Yeah, love the philosophy there. I guess the takeaway is not everything needs to be a test, especially not when you have 20 viewers on that landing page. And you should always start with that question of like, do we can we even run this as as an AV test before you go down the rabbit hole of like putting together your hypothesis and deciding what the minimal detectable effect is going to be? So yeah, great advice. As I feel like there's there's so many threads, I would want to double down on and, and pull from your brain and learn more from you. But yeah, the this is this is flown by, we ask this question to all of our guests right at the end, you're a VP of Marketing at board advisor, a dog, Dad iski aficionado, you're also a Boston sports maniac. One question we asked all our guests, like I said, How do you remain happy and successful in your career? How do you find balance between all the things you're working on while staying happy?

Ezra Fihsman  49:33  
Yeah, it's a it's a very good question. For for me, it's figuring out kind of what, what excites me and optimizing for that. Again, you. I think it is early is easy early in the career to be like, Hey, this is all about like, how do I progress in my career? And that's kind of what you're optimizing for, like how do I how do I get up to the next level and the next level the next level. And I think at some point, realizing that, you know, that that may be important. That's an important element. But what else drives you? And for me, that thing's different for everyone. For me, it's, it's all about kind of learning, learning new things, and, and kind of, yeah, getting getting new knowledge getting tested in new ways. And so that has been kind of the key to me, thinking about my career and thinking about what I do next and my job and is like, Hey, is what I'm doing interesting. Am I learning a bunch? And if that's true, I'm gonna keep doing it. It's not true. Maybe I need a new role within this company. Maybe I need a new role entirely. But just to I just go back to that question, and kind of ask myself that, you know, because then because I'm there's like that intrinsic motivation for doing doing my work, and then finding balance outside of it, where, you know, work isn't work isn't the only thing. It's important to me, but spending time with my family spending time skiing, also very important, and I prioritize those things to and that's obviously pretty critical for me.

Philippe Gamache  51:18  
Awesome, great answer simple question, but very powerful question to make sure you're finding that value in what you're doing. So thanks so much for your time, really appreciate it. I think a lot of folks like me hopefully got a ton of value added this will link to all the stuff that Wistia is doing and feel like you guys are coming out with new content, new video production series all the time. So thank you again for your time. This yeah, thanks for having me. This is great.

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