Lenny's Podcast: Product | Growth | Career: M&A, competition, pricing, and investing | Julia Schottenstein (dbt Labs)

M&A is always about creating plan Bs. And the way I would think about it is for any one company,

there's only ever two to three buyers that find what you're building to be extremely strategic.

And the strategy that I would do in how do you get noticed is I would figure out the area that you

bring a competitive advantage, and I would inflict pain on that potential buyer, make it impossible

for them to not notice you because that's when they're going to have their ears perk up and say,

well, what's going on with this company? The really important piece here is you want to do that in a

way that's still friendly and open. I see a lot of founders get this wrong. And they prematurely

will shut down a conversation or they won't talk to an incumbent or a potential future buyer because

they take too competitive of a stance. But that's a mistake because M&A is all about creating plan

Bs. And you don't want to shut that door down prematurely because you don't know if you can

really go the distance and be an independent company. So you want to have optionality.

Welcome to Lenny's podcast, where I interview world-class product leaders and growth experts to

learn from their hard-won experiences building and growing today's most successful products. Today,

my guest is Julia Schottenstein. Julia is a product leader at DBT Labs, where she leads the

DBT Cloud product. She's also the co-host of the DBT Labs podcast called Analytics Engineering

podcast, a show about data trends that impact analytics engineers work. As you'll hear in

this episode, Julia actually led the acquisition of a startup that I'm an investor in called

Transform from the side of DBT Labs. And in our conversation, we dig into the M&A process and get

into a bunch of advice to improve your odds of having a good outcome and just approaching M&A

broadly. We also dig into the story of DBT, which is one of the most successful startups out there

that you probably don't know about. And we talk about what they did right to get to where they

are now. We also cover how to best think about competition, a bunch of frameworks for thinking

about product, and advice on how to approach pricing, and also open source. Enjoy this episode

with Julia Schottenstein after a short word from our sponsors. This episode is brought to you by

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Julia, welcome to the podcast. Super excited to be here.

So you have a really interesting career path in that you went from

VC into product management, usually it's the other way around. Usually PMs become VCs,

and it's rare to see this kind of version of it. And so I wanted to start with just a question of

just how did that come to be? I do have an unusual background, but it doesn't surprise me that people

who are interested in product are also interested in investing and vice versa. For me, I've always had

three interests broadly, and that's an interest in business, an interest in technology, and an

interest in markets. And I get to express those interests both in investing and in product, but

just with different weights. So in product, you go a lot deeper on the tech and markets is less of

a focus, but you still get to do all three. So I have an unusual background, and I used to be a

professional investor at NEA. I did all of about all my time investing in early stage startups that

built for technical audiences. So I think dev tools, infra data companies. And in 2019, I first

discovered DBT, which was an open source data transformation framework. And I got really

very, very excited about DBT because when I talked to people that were using it, the way that they

described their experience on DBT was unlike anything I had heard before. It was much more

of an identity for them than just a tool that they were using to get their job done. And that

really struck me. And as I kind of thought about what was happening in the market, there was a lock

going on in 2019. The markets were changing quite a bit. Cloud data warehouses were starting to

explode. Like this was the year where Snowflake went from a $4 billion company to a $12 billion

company. And I thought to myself, if DBT worked, it could work in a really extraordinary way.

And I naturally tried to spend all my time getting close to Tristan, who's the CEO and founder,

and I wanted to invest.

Okay. So at this point, you're a specie at NEA. You're trying to invest in DBT.

And okay, keep going.

Yeah. So I was very, very excited. I thought if this worked, it could work in a really

extraordinary way. And I spent all my time trying to get Tristan to like me,

so that I could invest in the company. And then in 2020, I finally got the call that I was waiting

for Tristan said, we're going to raise some money. He had a term sheet from a firm that he liked. It

was a good venture fund. But he also liked me and he wanted to give me a shot. And I was like super

excited to get that message, like, this is my chance. And unfortunately, I ended up losing

that deal to Sequoia. It's a formidable partner.

Reasonable.

Reasonable.

I was just so convicted that it was going to be a special company that I asked to even put my

personal money in. And I asked to put like a very irresponsible, irrational amount,

nearly like 20% of my liquid net worth into DBT, because I was so convinced that this was special.

And you know, sometimes when deals don't work out as an investor, you can create this like

narrative in your head, like, Oh, good, you know, I dodged a bullet or, you know, that

better off without them or, you know, screw them. But for me, like, that was quite the

opposite with DBT. I really felt like DBT was this runaway train. And it was special. And I

wanted to jump on board. So a few months later, I ended up calling Tristan and asked him if I

could be a part of the company company that built the product that I thought was so special.

So that was my kind of unique path into product and into DBT.

So you invested in DBT and then you ended up,

there are an opportunity opened up where you can end up working there.

No, I think if I was was able to invest, I wouldn't be here. So I got a no, the board

ended up vetoing my personal investment. But it's okay, because I ended up dedicating all

of my personal time to building the company.

Awesome. Okay, so something you touched on there that was really interesting of what

you saw about DBT that was so interesting. And I think this is maybe a broader question of just

in your time investing and finding a company like DBT early. What have you learned about just

picking well, finding companies early, especially what are signs in your experience of just

that this is going to be something really interesting that you might want to join.

And this is more for people listening that are thinking about joining a company early on,

wouldn't think they should look for.

So the way I would look at joining an early stage company would be the same way I would

evaluate investing in one. And so there are four things that I care about when I'm looking

at really early stage companies. And it's people, market, product, and distribution.

And I'll touch on each of those four to say a little bit more about what specifically

I'm looking at. So people, this is really the CEO, the founder of the company put simply,

do you trust this person to lead? And for me, Tristan had this really rare ability to paint

a very compelling future of the industry and how DBT was going to be a part of making that

vision a reality. But he also was really, really detailed in the day to day work

of the analytics engineering work. And it was that range and scale that made me feel like

this is a founder that's very rare and compelling. The next is markets. We touched on it a little bit.

But what I'm looking for in markets is like, is it growing? Is there space for a new

entrant to make its mark? And when it came to DBT, it was an explosive time in cloud data

warehouses. And it was that chaos that was really the opportunity for DBT, because they created

some orderliness and structure to the way that people worked with their data in the cloud data

warehouse. So that was very compelling. The next is product. Everyone who's listening,

hopefully either is interested in products or has a product background. So I won't say too much

there. But can you talk to users or customers, potential customers? Are they building something

that's really special, unique? Can you hear that spark, that enthusiasm, and figure out if this

is going to be special? And then the last, I think this is more important, arguably, than

if they have a good product, but is distribution. Do they have an advantage on how are they going

to get to market? Because that's really, really hard. And think about how they think about their

competitive advantage on either the ecosystem or distribution, and how they're going to ultimately

sell the product. You're not going to get a 10 out of 10 on all four dimensions. And so when

you're joining a company, you also have the benefit of dedicating your time. And so try to think,

you know, if they're weaker on one dimension, what is it that you bring to the table or what are you

special at that could potentially de-risk the success of the company? In terms of spark with

a product, I'm doing a post right now on product market fit and how do you know if you have product

market fit? And a lot of it often comes down to like, there's like an emotional reaction from

someone you're talking to about the product you're building. They're just like, holy shit, I want,

I want this now. Is there anything even more specific you've seen of just like, what is a sign

that there's a spark that people are just like really enthused? You talk about people made

dbt kind of part of their identity? Is there anything else there? Yeah, it's can they not stop

talking about it? And that's this like the chatter about a product, they want to share it with like

their teammates or to other people at different companies. That just top of mind love and wanting

to share what they've found with others is really a great sign that you're on to something. And then

that spark will help do a lot of the work on how do you get to market because your evangelists are

really your users of people that love what you're building. What about in terms of the distribution

bucket? What are some examples of just really important, I don't know, unique or effective

distribution strategies or, I don't know, unfair advantages you've seen maybe with dbt,

maybe other companies like what are some examples of that? So dbt had an ecosystem advantage and

they were open source and this helped really dramatically for lots of people to have low

barrier friction to just try it out and spread kind of organically. They first got started with

very horizontal people could just get started without ever even talking to sales and think

that was a competitive advantage. But you know, not all companies need to be product led. Some

companies are enterprise top down sales. And so in those situations, think about like does the team

really know how to land a complex enterprise sale? Do they have a background in that particular

space? Do they have a network of connections? Can be different depending on what the company is

selling. But you either want to see someone who's a company that's really strong at enterprise or

really strong at the bottoms up. Okay, cool. So I want to shift a bit to talking about an area

that you have a lot of experience in, which a lot of people are also really interested in right now,

which is M&A. I've invested a lot of companies and maybe, I don't know, once a month, I'm getting

an email from a startup. I've been an investor and they're just like, we're looking at maybe selling

the company things aren't working out the way we were hoping. And you've been on, I think,

maybe all sides of the table of M&A transactions, including I think you led the acquisition of

a company I was an investor in that dbt acquired that I think is public company called transform.

And so my question is just for founders who are currently thinking about M&A, M&A meaning

acquisition, essentially, what's your best advice for them for how to be most successful in M&A kind

of outcome for themselves? When it comes to acquisitions, the time to start thinking about

an M&A strategy is hopefully when you don't need one. And the best strategy that I could give a

founder is to have a really strong offense in building their company. And when founders start

their businesses, they don't usually set out to start a company to sell it to another business.

They start it to be an enduring independent standalone company. And if you have that path,

then you'll have the upper hand in absolutely every single M&A conversation because you have

a viable alternative, which is do nothing, stay the course you don't have to sell. But of course,

that's not the case for most companies. Most companies don't have a viable path to being

an independent company forever. And so they have to think about M&A. And so M&A is always about

creating plan Bs. And the way I would think about it is for any one company, there's only ever two

to three buyers that find what you're building to be extremely strategic. And the strategy that I

would do in how do you get noticed is I would figure out the area that you bring a competitive

advantage, and I would inflict pain on that potential buyer. Make it impossible for them to

not notice you because that's when they're going to have their ears perk up and say,

what's going on with this company? We just bought this company Transform. They were playing a

really good playbook here. And the really important piece here is you want to do that in a way that's

still friendly and open. I see a lot of founders get this wrong. And they prematurely will shut

down a conversation or they won't talk to an incumbent or a potential future buyer because

they take too competitive of a stance. But that's a mistake because M&A is all about creating plan

Bs. And you don't want to shut that door down prematurely because you don't know if you can

really go the distance and be an independent company. So you want to have optionality.

I love this term of pain on your potential acquirers. What are some examples of that?

Like, how, who's done that well? Or what's an example of that?

Yeah, I mean, I can share the Transform story. So the company we just acquired,

we announced it in February. So DBT Labs, we build transformations. That's our main product. And we

were venturing into a new product area that we call the semantic layer. And to describe what that

is quickly, it's allowing companies to define their business metrics. And so that whenever

anyone queries it, we always serve back consistent data on those business metrics.

And Transform, they were a peer play company only in this metrics layer, semantic layer.

And they had a really strong product. They had figured out some of the technical challenges

and they had solved it early on. They had the benefit of having worked at Airbnb,

which you know, and Airbnb in the data world is famous for having a really successful,

like semantic layer, metrics layer called Minerba. And what we had at DBT Labs is really

good distribution and ecosystem, but we were a little behind in bringing a product to market.

And we felt that pressure from Transform because they were doing such a great job at

being vocal and loud about how their semantic layer solves these really hard technical problems.

But they didn't have any distribution. And so that was really tough for them.

And they were putting pressure, but they were still positioning their company as a partner to us,

because they wanted our community to be excited about what they were building and hopefully

get, lure them over to use their product. And so because they had positioned themselves as a

friendly partner, when really we weren't, we were trying to compete for this similar use case.

When it came time to do an acquisition, we were really excited because we knew their

product was good, and they had already done a lot of the work to make integrating with DBT

possible. And that helps us post acquisition, do the integration much more easily.

How do you just think about either as a startup or even an incumbent about how to think about

competition, how much emphasis, how much energy to put into thinking what competitors are doing

and just how that informs your strategy? So we recently codified our philosophy when it comes

to competition. And I'll give Nick Handel, the founder of Transform, who led this exercise at

DBT Labs. But we really have like three pillars when it comes to competition. So the first is

hold true to our vision. We're really excited about the path and the journey that we're going on

at DBT Labs. And we don't want the distraction. So occasionally, you'll have competitors maybe

throw shade or throw stones. But most of that is just noise. If you have a lot of conviction that

you're going in the right journey, you want to just keep your eyes straight ahead and run your best

race and not be too distracted by what maybe some critics are saying. The second philosophy we have

is really a grow the pie philosophy. So we want to work with our partners and our ecosystem to

make the opportunity set even larger. And we see that today, like we mostly serve reporting and

BI use cases, we're seeing lots of companies start to operationalize their data. Now with this big

wave of ML, clean transform data assets are being used to train machine learning models. So the

pie continues to grow. Let's focus on that as our target and work with people to make the opportunity

set really attractive and not try to slice it up too thinly. And then the last one is we want to

lean into our strengths. So we have an ambition to be a platform company. And we know what we're

good at, but we also want to leave space for our ecosystem to offer solutions to our users that

help them out. And we really want to foster an ecosystem where we can partner with lots of

companies in the modern data stack. And generally speaking, when it comes to competition, we take

a really long term view. And there are a few areas that we do want to hold our ground. And that's in

our transformation standard, as well as our semantic standard, because we believe those two

are better served together for the user's sake. But for everything else, we really feel like we

can work with our ecosystem and accomplish what we want to accomplish and also help them accomplish

their goals too. It's maybe a good time to just chat about dbt and the success the companies had.

So many startups have tried to become a standard default layer of what's now called the modern

data stack. And I don't know any startup that doesn't use dbt or doesn't think about

planning to use dbt. It's just like an incredibly rare success story.

Some are just snowflake where it's just the default for building large data startups. And

most startups these days work with a lot of data. So my question is just like, what do you think

dbt did most right to win in this and continue to win? So I think dbt did a lot of things, right?

But I'll point out two that really stick out to me. And the first is just power and simplicity.

And the second is a commitment to being open. And I'll touch on what I mean by those two

things. So when dbt was first getting started, you would hear a lot from companies like, I don't

understand, like, what's so special about dbt? We have a sequel templating tool at our company,

we built one in house, like this is really straightforward and simple. And it's true,

like dbt is really simple, but that is the power of it. And so our founders Tristan, Drew and Connor,

they had a belief that the people who do data analysis work that really work closely with

their business stakeholders should also be the ones to contribute to creating clean data assets

in production, because that data prep work is a necessary prerequisite for any analysis that you

do. And so dbt was really this belief that if you know SQL, we want to invite you to do these

workflows that were traditionally held by data engineers. But you know, you had to earn that

right. And so dbt has this nice framework where it's harder to mess up, keeps data quality really

high. But it is pretty simple to get started and learn. And that was really the unlock in the

industry, they were definitely solving a pain point at the right time. And then the second

thing is this commitment to being open. So dbt is open source. And that's the main kind of

guts of dbt where you write your business logic. And it helps in a number of ways.

Specifically, it helps with flywheel, keep the flywheel running and also with network effects.

And I'll explain what that looks like. So dbt is really easy to get started with at your company

with reduced friction, you know, we're building a product that people like. So they talk about it,

they want to share it, both at their organization and with other companies,

other companies get started with dbt, again, with reduced friction, we now get to see this

really diverse set of use cases for dbt across company sizes across industries, and it allows

us to build a truly horizontal company. As our company grows, we get to invest back into our

community and our product and the flywheel begins to spin faster. And then, you know,

meanwhile, we have a really large user base. So we have 20,000 companies using dbt every

single week. And that attracts partners to want to build for dbt. So they share best practices,

build workflows. And now if you're a company and you've standardized on dbt, you've really unlocked

an integrated modern data ecosystem that wasn't available for you before. So that has a flywheel

and also kind of benefits everyone that decides to be on the standard. And so it's those two

really important trends that made dbt so powerful today.

So what I'm hearing there is essentially the product was right for what people needed to solve.

There's also like a product led component open source free self serve kind of piece that people

adopted, used, start working and then kind of scaled and start paying for it. And then there's

kind of like an alignment of the vision of where this was going and how it fit with how people

wanted this to work for them. Is there anything else? Because a lot of startups do that and that

all sounds really smart and good. But a lot of startups try to do those things and no one cares.

Maybe their product isn't necessarily what people are looking for. Maybe they don't get the right

distribution. I don't know. Is there anything else that you think they did really well that

helped them kickstart this to even be a thing? Like is it timing that was really great? Is it

like specific influences early on? I think timing was really important with the success of dbt that

they were there when the cloud data warehouses were really exploding and growing in an enormous way.

And you know, dbt labs started as fish town analytics, a consulting firm. So they worked

really, really closely and hands on with all of their consulting partners to get the pain point

and really solve first-hand challenges that they saw. I think that combination of

being at the right place at the right time and also getting to work really closely with people's

day-to-day problems created a really special experience. I didn't know that. That's a really

important element of the story is basically they were focused. Like how long did they do that

in a fish town analytics consulting? Consulting part of the business was almost two years.

Okay, so they basically spent two years solving this problem like basically manually for people.

And that's such a great way to understand real pain and figure out how to solve it.

Totally. Awesome. Okay, so that's a really interesting insight. Just like

spend a few years just like it sounds like it was almost manual, right? Like manually

helping people transform their data using whatever tools already existed.

Yeah, well they were building dbt and using dbt to help them do their jobs better in supporting

their clients. And whenever they encountered paper cuts or friction or the workflow was taking

longer than they expected, they would build that into dbt. And that really matured the experience

of the product because the people who were building it, the founders were also day-to-day working with

these customer or clients that had pain points. That reminds me of a story you told me about how

you made your Eng team do some manual work of an algorithm involved in transformation. Can you

share that? Okay, so I'm going to prep this story by sharing that I'm a huge math nerd and

one of my favorite books on logic is called Girdle Escher Bach. And in this book there's a

fun scene where there's an ant farm that bands together to do the work of a computer flipping

bits from zero to one to solve logic gates. And so this chapter of that book was really the

inspiration for an exercise that I ran my team through. So about a year ago, we were doing a

big zero to one new project at dbt labs and we were going to change the algorithm for how we

built customers data transformation graphs. And I needed a way for the team to really internalize

all of the changes that we were going to make and I needed them to own it because otherwise

they wouldn't be able to anticipate all of the edge cases. It wouldn't be quite as durable. You

couldn't copy paste the algorithm. So I showed up to a team offsite with a spool of rope and sticky

notes. And I think my team looked at me crazy went with two heads when I started to tie people up

to create a graph. So each note of the graph was an engineer and I the rope was kind of the

edges of the graph to connect them. And then we worked through the new algorithm extremely

slowly step by step. And it was a way that you couldn't leave that exercise without knowing

exactly what was going on because everyone had a role to play. So I think a lot of times when

you're starting something new, you get into a situation where a few people really understand

it and they're running way ahead of the rest of the pack. But I needed a way for the whole team

to go along for the journey. So I'm constantly trying to create these important moments or

memorable moments for the team so that it's centered around our mission and they can have the

ownership of taking the project and making it successful. And so it was perhaps a overly

creative or kooky way to spend the day but it was really successful.

What was the actual algorithm you were trying to implement?

We were trying to figure out how to make kind of a flipping the way that we run people's

DAGs from an imperative way to a declarative way. So instead of like running things left

to right when data arrived in your warehouse, you think about it as a reverse like what would

need to happen to make your data SLAs dematerialized in time.

Awesome. And it sounds like the team found that valuable.

Yeah.

Okay. Reminds me of a clip from this last season of Ted Lasso where they have

used red strings and they, I won't get into it, but if you've seen it, you will know what I'm

talking about. I want to come back to your chatting about open source versus not open source.

So some part of DBT is open source and some isn't. I'm curious how the team decides what is

open source and what should be open source, what isn't open source and what to charge for.

We think about DBT open source. It's really the guts of the data transformation. It's where you

describe your business logic. And then on the cloud side, you'll rebuild proprietary software

that supercharges the development lifecycle and the productionization of DBT at scale.

So what we think about as leaving for our cloud offering is we deal with state,

so stateful interactions and also any kind of cross team or structural collaboration.

We want to reserve that for our proprietary offering. I think it's really important to have

that distinction of what you believe should be open source or what is the open standard that

really matters. And ecosystem to us is really important. So it's important that that remains

open source. But then we want to supercharge that experience with kind of an open core model

and build proprietary software that makes people much more successful at using DBT.

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their no code playground. That's assemblyai.com slash Lenny. I know you also spend a lot of time

thinking about pricing and willingness to pay and things along those lines. Is there anything

you could share about what you've learned about how to think about pricing to like this or even in

general? Pricing and willingness to pay is such a hard conversation, and lots of startups don't

do this early enough in their company journey, likely a side effect of zero interest rates

where investors were happy funding GitHub stars and usage and companies never thought about how

am I going to make revenue or make money, which is it's important. So for us at TBC Labs, I don't

claim to be perfect at it, but we're trying to get a better muscle around it. And I always think

about Madhavan, who wrote this book, Pricing Innovation. I know you've had him on the show

before, but he shares that you don't get to decide if you're going to have a pricing or willingness

to pay a conversation. You only get to decide what. So it's much better to have that conversation

before you build the product, then have it when your sales team is trying to sell something and

people aren't excited about what you've built, aren't willing to pay for it. And at DBT Labs,

we have this value. It's one of our core values that says we're more concerned with value creation

than value capture. And we really mean this. When we talk about what is the value of DBT Labs to

our customers, they often talk about how it's either 20 to 35% as valuable as what they spend on

their cloud data warehouse. But what we charge our customers is a very small fraction of that 20

to 35%. And that's by design. And last year, we did our first ever pricing change in the company

history. And you learn a tremendous amount when you have that event, because you get to test the

price elasticity of your customers. And it's so important to learn that lesson while the company

is still smaller or the stakes are lower, because pricing is always evolving. It's not a fixed thing.

It gets more complex over time. And so we have to think about it quite a bit because

my team builds proprietary software for DBT Cloud. And when we lose a deal, we most often lose it

to DBT open source. And we like it that way. We're happy to lose to ourselves. But we have to

really think very deeply about what are people willing to pay for and what moves the needle for

them and focus on that. I'm so curious what that pricing process was like to figure out what to

change. Is there anything you could share about just like what that was for you? Or what are some

just surprises that came out of that process or just like, oh, wow, we didn't expect that in these

conversations? It's really like an all hands on deck conversation. It's pricing is so cross-cutting

because it's a finance discussion as well. You're kind of modeling out things in spreadsheets and

figuring out how that might impact the business. But you can't just solve these problems in

spreadsheets. You have to go talk to customers, test the waters, understand where people's

appetites are and sussing that out is really hard. And then of course, there's a product

piece to it too, where you have to affect it and communicate it as well. So it was very cross-cutting.

We learned a lot. We track our conversion rates really carefully. We track our turn rates very

carefully. And I think largely we were happy with the change that we made. And we felt like

one of the big things that we were trying to solve for was have our pricing catch up to

how people valued the tool. How many people did you end up talking to? Who is doing these

conversations? And is there anything really important you learned about the how to ask

these questions and these sorts of willingness to pay conversations? We talked to dozens. It was

combination of product and product marketing, having the conversations. And people aren't

very willing to share explicitly what they will pay. But there's some tools that we use on

relative value. People most think about what is the relative value of DVT in their cloud warehouse.

And we also tried to employ some of the tactics that we tried to suss out. What do people view

as very inexpensive? What's a price point that's very cheap or a no-brainer? What price point is

maybe fair or comfortable for them and what would be too expensive? And then we had all

the data back to figure out where we landed. I want to come back to M&A for a bit. I had a

few more questions there and I kind of moved on from that. And so again, you've done a lot of

work within M&A Realm. Something that I saw recently, and this connects to the fact that a

lot of startups now are looking to get sold. This VC Hunter Waugh, he's a founder of Home

Proof Ventures, had this interesting blog post where he basically suggested you should actually

think about being public about the fact that you're selling your company, which is kind of crazy,

because in the past, you never want to come across as too silly. I don't want people to think I'm

desperate. And his point is like, many startups are desperate right now and it's okay to be public

about that. And then in theory, it creates more of a bidding situation where many people know

versus keeping it secret and kind of in closed rooms. So my question is just, what do you think

of that? Do you think that's an effective strategy? Is it not? I think it's good advice. If you're in

a Hail Mary situation where you're looking for a home or you need an exit for your business,

it's better to be transparent and cast a wider net. And you're right. And like previous times,

founders tried to be a little bit cute or obfuscate that they were evasive. The situation that they

were in because they wanted to drum up some competitive interest when there really wasn't any.

But you know, unfortunately, in today's climate, too many companies are in that spot. So it's

impossible to hide it. And so the better approach is just to be transparent. And I see it pretty

regularly and there's absolutely no shame in sending a note that says something like,

hey, we're looking for an exit for our company X, Y and Z and pan out as we expected. We built a

really interesting product and we want to keep the team together. We're running a process. Are you

interested? Really just as simple as that. I've seen a lot of companies put together these really

detailed decks or even websites of just like, here's the team, here's what we built,

to be very kind of promotional about it. Is that something you've seen? Is that something you'd

recommend? Yeah, usually in these situations, people are acquiring the teams. And so having your

data room together, really the most important thing is these are the team members that are

going to come along with the acquisition is the biggest motivator for why a buyer would get excited.

You made this point earlier that a lot of the seeds need to be planted early for you to have

the best outcome. And this reminded me, so I had a startup local mine that we sold to Airbnb.

And I met Airbnb initially at a year before we actually started exploring the process

at a random party at South by Southwest where I actually have no memory of this party,

but the head of product at Airbnb, Joe bought or remembered it and came back to us a year later

and just like, hey, what are you guys up to? Maybe we can collaborate on some stuff and

I'll let you in acquisition. So I think that's just, just wanted to touch a ban on that point of

just the power of the way I thought about is let a thousand flowers bloom, just like meet everyone,

get the word out that you're around and what you're doing so that in the future when someone

has that problem, like, oh, that company, maybe we should talk to them. Yeah, you want to make

sure that the buyer knows you are before the acquisition moment. And hopefully that's because

you've made an impact and they like what you're building. Maybe you've inflicted some pain

on them. But yeah, certainly creating those connections while ahead of an exit event is

important. And specifically there, it's like meet people at your competitors potentially.

For us, like Airbnb was never even a potential company we would sell to you because it had

nothing to do with it, but it ended up making sense down the road. What's like the realm of the

companies and people that you think people should think about meeting? If the company is buying

a lot or they're active, they often have corp dev teams. And so use that corp dev team to your

advantage. Like it's their job to meet absolutely every company that could be potentially interested.

So take that meeting, say you're not interested in an acquisition just yet, but push them to

make an introduction to someone that could sponsor the deal. So usually that's someone in product

or maybe a GM and use that as a starting point for maybe just a conversation, maybe something

more like a partnership. But get the corp dev team to work for you.

What if you're at the other end of the spectrum and you're in kind of dire straits right now

and you're just like, oh man, what do we do to potentially sell this company? I know,

odds are not going to be great, but just what do you suggest folks do in terms of, I guess,

finding connections to potential companies that might be acquirers?

Yeah. I mean, use your network. Usually your venture capitalist has a really big network.

And one of the things that I hear founders feeling the most nervous about is a duty to return the

money to the investors. And maybe this is an unpopular thing to say on a podcast, but your

investors understand that they're not making their money back. And what they want to do instead is

have you end up at a really great company like an Airbnb because that will help them down the

road. So it's all about the long game. But use your investors to help you find connections at

different companies that could be buying. And don't worry so much about disappointing them or

being really realistic about where you are in your company journey.

Yeah, to build on that. Like I'm just an angel investor. I'm not like the lead fund and I don't

they feel differently, I imagine. But the last thing I want for founders to get stuck at a company

they hate and just so that they could return some money or have some kind of outcome, like I'd

rather they just just give up, move on, like life is short.

Yeah. I think founders forget that it is so risky investing in early stage companies that

portfolios, 50% of portfolios don't return, investments don't return anything. And that's

just part of the game. And it's a very acceptable path where, you know, hey, we gave it our best

shot. It didn't work out and moving on. Which is tough for a lot of times for founders that are

told like it's all about grit and not giving up and don't quit. Sometimes, sometimes you should

quit. Oh gosh, yeah. I don't want to be, I don't want to say that. I love that, you know, people,

I think being founders, it's extremely lonely role sometimes and it is

very hard to know what your next chapter will look like or what the journey will look like.

And sometimes you really are out of cash and you do have to find a home. But, you know,

I hope, I hope that you can continue to fight and find a way forward.

Agreed. Specifically for people thinking about selling their company. Are there any companies you

think are good companies for people to look at right now that are actively acquiring or open

to M&A? This is a tough one. I think a lot of companies are on the sidelines for a number of

reasons. And they could be on the sidelines because they just did an acquisition and they're

trying to digest or integrate that company. They could be on the sidelines because they're not

growing headcount as much. And M&A is often a work chart gymnastics of folding the target

company's headcount into your budget and plan and maybe just don't have a lot of space.

Or probably more common right now is there's just a general uncertainty about the future. And

in highly volatile markets, people want to take care of their own and even the best M&A deals

at a level of complexity that a lot of buyers are just not looking to take on right now.

And so there are a number of reasons why people might sit out. But what I would do if I were

in a position of wanting to sell my company is I would come up with a buyer set of maybe a dozen.

And really, there aren't more than a dozen companies that will find what you're doing to be

a very good fit. Start with your buyer set and then start calling the list by looking at some of

the criteria that might count people out. And then go have those conversations. And if you're in a

Hail Mary situation, be very transparent about it. Maybe open up the buyer list. But if you still

have some room, I would maybe focus on two to three partner buyers and really play a different

playbook, which is inflict pain, make it really hard for them to not notice you, but do it with

a smile and be friendly while you do that. Sometimes with M&A discussions, there's a lot of

subtlety to the way you communicate where you don't come out and be like, please, we'd love to sell

our company to you. Any advice on just the phrasing and how to approach it? Or do you think

it's fine? Just tell us. We're looking to sell our company. Are you interested in being a buyer?

Yeah, I just wouldn't be too clever here. Everyone understands, oh, I'm evaluating

strategic alternatives. It means you're looking to sell your company. And it depends. Do you have

time? If you have time, yeah. Don't come out and say, hey, I'm for sale. That's not going to end

up in a good outcome, but depends where you are in your company journey. If you have time,

then don't talk about M&A at all. That's the last thing that you want to speak about. Instead,

you're talking about maybe collaborating or partnerships, how to work together, knowledge

sharing, and M&A is a dirty word if you have a lot of runway and you're going to try to

continue to pursue an independent path. But if you're out of time, you're out of time.

That's such good advice. I remember the term we used was, we want to explore strategic

partnership. And everyone knows what you mean by that, but you just kind of don't want to say it.

Yeah, it's like everyone in the room is kind of looking like, oh, yeah, yeah, okay. Strategic

partnership or strategic alternative. It's like, we all know these code words and we understand

the situation you're in. Yeah. When do you think that M&A market might pick up again? I know it's

impossible to predict. Do you have any sense? Yeah. I wish I had a magic ball. That'd be

pretty sweet. I think what is happening, though, is we're far enough out from the peak of the markets.

So the peak was really like November of 2021. And why does that matter? Two things. One,

founders are coming to terms with valuations that they maybe received at the highest of the market

are no longer going to hold in this market. And companies are out of cash or maybe out of options.

There will be better assets entering the market soon. And at a certain point, the opportunities

will just be too great that that will incentivize a lot of the buyers that have been on the bench

to start participating again in the M&A market. And I don't know exactly when that will be,

but I think we're pretty close. I think we're pretty close.

And you mentioned a value that you have at DBT. I forget exactly what it was, but I'm curious,

what are the other values that you have at DBT, whatever you can share. I'm always curious

what principles and values companies come down to to help drive the way they think.

The value that I shared is we are more concerned with value creation than value capture. And that

really drives everything that we do. We try to put a lot of good out into the world and it pays back

kind of slowly. The whole mission of DBT Labs is to help analytics engineers disseminate

organizational knowledge through data. So we really believe in also being participants of

sharing that information and getting more people knowledgeable about all sorts of things.

Transparency wins. We're a really transparent company. We share our board decks. We have

lots of communication and participation in all of our stocks. We're a writing culture.

We have hard conversations in the open. So that's another big one, transparency always wins.

We are humble. We don't ever feel like we're successful. We kind of come at this from a

very humble space where we feel like we have to serve our community and our users.

And that really motivates us. And then another one has just worked on well as its own end and

it's really focusing on the journey and not the end destination.

Awesome. I want to do a post someday of just like, here's the values, all these different

successful companies have come to and see if there's any patterns. I'm actually doing a post

right now on Snowflake and on Figma. And what you touched on, there's such a connection and a

threat of obsessing with your users and making sure they're happy at Figma. I forget exactly what

it is, but it's just like, they're just like, in this article, it's going to come out tomorrow

actually. So you people get a sense of when we recorded this, where they think of their company

as software as a service, where service is their number one goal. They actually provide service

and software is just a way to do that. And then it's Snowflake. Their number one core value

is put customers first. And they talk a lot about how they just actually informs of their

privatization and all their thinking. And so it's interesting that also comes up a lot in

what you're talking about, which I think it's easy to say, but I think what actually separates

companies that succeed is they actually put this into practice. It's really interesting too because

a lot of the people who work at DBT Labs came from the community. So they feel this real ownership

in making the experience an excellent one because they were so compelled to come join DBT Labs

because the product changed the way that they work or changed their lives. And so that commitment

to the community and product experience is really, really strong. This is another thread. Maybe we'll

go down real quick and work in a different post around Reddit and how to work with really

opinionated users that strong opinions about changes to the product and the way they described it.

These guys were there for five years working with the community on the product is that

like to your users, the product is their baby basically. It's like they think it's theirs versus

the company's. And I'm curious, having a really strong opinionated community is what it sounds

like you also have. What have you learned about just working with them to build product that makes

them happy and avoid, you know, revolts and really upsetness? It's hard as you grow. I think it's

just a challenge because our community gets bigger. You can't service like everybody's needs.

But I think what we've done is like everyone is very deep in our own product. I think one of the

cool stats is at DBT Labs, we have over 30% of our employee headcount has contributed to our data

transformation workflow. And so that's across like every discipline, it's in obviously product,

obviously in our data team. Like our marketing team also contributes to data transformation and

our engineering team will also contribute to our internal DBT analytics project and that sense of

like really understanding what the experience is like and then soliciting as much feedback as we

possibly can. We have a DBT Slack community of 50,000. And all of our employees are like in that

Slack channel regularly and can feel when we like mess up or we don't quite deliver

an experience that we're proud of, like you will just see like dozens of people trying to jump on

board and try to make it better. Is there any other frameworks or just general processes that you

found to be really useful in building awesome product running teams? I'm not a big framework

person, but there's kind of two sayings that I find myself repeating or either to myself or to

others. And it's worse is better. And tech debt is a champagne problem. And what do I mean by that?

It's really to help me combat this perfectionism because perfect doesn't exist. And you should

instead go with good enough because when you ship, that's the moment when you get to learn a lot

from your users. And you just can't anticipate it. You try very hard to understand exactly how

people will use the product and get all the edges ironed out, but you can't until you ship.

And I'll share an example. So my team helps supports the DBT cloud scheduler. And

the initial version of the DBT cloud scheduler was pretty naive. Like we were a little embarrassed

by it. It was a big old for loop over a big old jobs table. And so we would look like,

is this job, is it time for this job to run? Okay, yes, run this job. Okay, it's not time

for this job to run. Next, continue on. Like, is it time? Yes, run this job. And it would just

loop over. And it's extremely naive and very simple, but it got the job done. And I try to

remind the engineers, like, we would be so lucky to have tech tech debt, because that means people

are using the product. And, you know, now we've had to rebuild our scheduler several times over

because we do have meaningful scale, we have 8,000 companies using our scheduler, we have to manage

10 million runs per month. But what we didn't need at launch was a distributed scheduler with

go workers and rabbit mq, we just didn't need it because we had no users. And so these two

sayings that worse is better and tech debt is a champagne problem just really reminds people

like, let's ship, let's get it out into the user's hands. And then we'll learn and iterate,

and it'll be a better experience for them. That's a good segue to my last question.

So you weren't a PM before this role, you have a strong experience in investing,

investment banking, business in general. I'm curious what you think product managers should

maybe focus on more or learn more or lean into to become stronger product leaders

based on experience you've had moving into product?

So I pull a lot on my experience, or some of the things that I did was as an investor in my

current role in product. And maybe I'll touch on like, what is the skill of a venture capitalist

might be a little bit foreign for people, but venture capitalists, they spend all their day

meeting lots of different companies, context switching, they have to know like a little bit

about quite a lot of different things. And they do this to like refine their investment taste or

refine their investor judgment. And they're also investing a lot in their network and connecting

people, supporting people and mining people for ideas that are way smarter than they are.

And so you do that all the time in venture. And I've brought a lot of those skills with me into

product and it translates really well. The first is I still spend a lot of time investing in my

network. And I think it's an underrated way for a PM to spend their time. And I try to build a

network of operators at other companies that are like DBT Labs, that are growing nicely, maybe a

little bit ahead of where we are. And I asked them questions, like, how did you navigate open

source? How did you navigate pricing? How did you navigate acquisitions? And I take kind of the best

ideas, figure out which ones I can apply and bring it back to DBT Labs. The second thing is I really

think my specialty or my superpower is that I'm a T shaped generalist. And so I know a lot about

I know a little about a lot of things from from finance to business to product, I have to go a

lot deeper in product in the areas that I specialize in. That's where the kind of tail of the T comes

in. But it's precisely because I've had a diverse background that makes me more effective when I'm

trying to get things done within the organization because I have just more credible experiences

that I can pull from. And then the last thing that I think maybe doesn't show up day to day in my

product work, but in investing, you're constantly thinking about risk and the power laws. And we

touched on this before, but like most investments don't work out, you lose the dollars that you put

in. But all the returns come from these rare events that make up for all the losses. It's

you have to think about what are the uncapped upside opportunities in investing. I think in

product, you still have to do the same thing, like you can't if 50% of the things I worked on went

to zero, like we'd have a problem. But it encourages me to continue to make bets for the company that

has the chance of bending the trajectory of our business. We've reached our very exciting lightning

round. I've got six questions for you. Are you ready? Yeah, let's do it. What are two or three

books that you recommended most to other people? Okay, so two books that helped me learn a lot

about myself range. It's a book about generalist and also quiet. It's a book about introverts.

And then I like a lot of biographies. So a few of my favorites are Snowball about Warren Buffett,

Made in America, about Sam Walton, and Leonardo da Vinci.

What is your favorite recent movie or TV show?

Okay, so I almost watched a movie in preparation for this podcast, but I really don't watch things

except during the holidays. I like Succession, but I have not seen the latest season.

Wow, you're in the store for a treat. Favorite interview question you like to ask?

When's the last time you had to teach yourself something new and how'd you do it? And I like

to test for a growth mindset and a thirst for learning. And then also, why DVT Labs? I think

a lot of people who come to DVT Labs have very authentic reasons why they're drawn to the company.

And in moments when things are tough, it's the answer to that question of why are you here?

It's going to make all the difference. And sounds like what you look for is just genuine

enthusiasm. Yeah. Awesome. What are some favorite products you recently discovered that you really

like? I like Belly. It's a consumer social app that lets you find and discover restaurants and

rate them. And with your friends, it's been a lot of fun looking at the New York City restaurant scene.

I've not heard of that. Awesome. What is something relatively minor you've changed in the way you

all do product that has had a lot of impact? Do fewer things and try to single-thread the

team as much as possible. And single-thread meaning like one main priority. One mission. Yeah. We're

all working, rowing in the same direction. Final question. You have a podcast. First of all, tell

us what it's called. But second of all, what's a favorite podcast of yours other than this podcast

and your podcast? Yeah. It's called the Analytics Engineering Podcast. So if you want to learn

more about the data industry, I host it every other week with our CEO Tristan Handy. It's a lot

of fun. Check it out. Other podcasts that I really like are in-depth. It's first round's podcast by

Brett Berson. He interviews a lot of operators about how they do their very best work. And another

podcast that I really like is the Logan Bartlett Show, which touches on timely trends in tech.

And in-depth, I think Todd Jackson actually hosts a lot of the episodes too. Also,

he's ran the podcast. Definitely check it out. And then say your podcast again and how can folks

find it. It's called the Analytics Engineering Podcast. And it's just in podcasting apps.

Yes. Amazing. Check it out. Julia, we've talked about inflicting pain and strategic partnerships

and why worse is better. Thank you so much for being here. Two final questions. Where can folks

find you online if they want to reach out and how can listeners be useful to you?

You can find me on Twitter, J-underscore, Shot and Steen. And you can also find me in the

dbt community Slack, also Julia Shot and Steen. Send me a note. Reach me there. And I'd love to

hear from you. If you have data problems or we can help serve your needs better, we'd love to chat.

Thank you so much for being here, Julia. Awesome. Thanks, Lenny. Bye, everyone.

Thank you so much for listening. If you found this valuable, you can subscribe to the show on

Apple Podcasts, Spotify or your favorite podcast app. Also, please consider giving us a rating or

leaving a review as that really helps other listeners find the podcast. You can find all

past episodes or learn more about the show at Lenny's podcast.com. See you in the next episode.

Machine-generated transcript that may contain inaccuracies.