How to Find Product Market Fit - Stanford CS183F: Startup School
Stanford Online2017-05-17
Stanford#Y Combinator#How to Find Product Market Fit#CS183F#CS#Computer Science#Innovation#Product#Market#Product Market Fit#Peter Reinhardt#Segment#entrepreneurship#entrepreneur#SOE#Sam Altman
150K views|7 years ago
💫 Short Summary
The video discusses the importance of achieving product-market fit for startups, highlighting the challenges and evolution of Segment's journey. It emphasizes the need to focus on customer feedback, iterate on ideas, conserve resources, and pivot towards a broader market once a foothold is established. Examples of failures and successes in finding product-market fit are shared, along with the significance of understanding real customer problems. The video stresses the iterative nature of finding product-market fit, the emotional toll it can take, and the transformative power of meeting customer demands to drive success in business ventures.
✨ Highlights
📊 Transcript
✦
Importance of Product-Market Fit Process
00:49Understanding customer needs is crucial for success, rather than focusing on a future vision.
Inductive process of working with customers to discover what works is key.
Building something that customers do not want should be avoided at all costs.
The challenges and critical nature of the product-market fit process are emphasized for startups.
✦
Challenges faced by startups in finding product-market fit.
03:5080% of founders fail to achieve product-market fit due to focus on futuristic ideas rather than current customer problems.
Emotional toll of startup failure can lead to severe physical and mental health issues.
Success is possible through perseverance and ability to pivot towards broader market after establishing a foothold.
Solving one customer problem can lead to more opportunities as customers seek solutions from the same provider.
✦
Importance of conserving resources and extending runway before finding product-market fit.
07:43Emphasize on focusing on customer feedback and iterating on ideas rather than premature spending on sales or marketing.
Shift in momentum after achieving product-market fit with increased customer interest and team growth.
Challenges and benefits of transitioning to a successful product, stressing the importance of continuous iteration.
✦
Importance of category leaders in business world.
10:09Building a platform that other businesses can leverage is crucial to becoming a category leader.
Examples of successful category leaders include Amazon, Facebook, and Salesforce.
Revenue milestones from $10-100M require a sustainable and compelling platform to capture customer base percentages.
Jason Lumpkin emphasizes the challenging but inevitable path to reaching $100 million in revenue.
✦
Challenges of running a business include attracting a world-class management team before reaching ten million in revenue.
13:19Founders often struggle with zero to one million in revenue due to the difficulty of finding market-product fit.
Learning from failure is crucial, with research showing similar success rates for first and second attempts if the first attempt fails.
Success in finding product-market fit significantly increases the likelihood of success on the second attempt.
Positive examples of product-market fit are essential for understanding and identifying success in a business.
✦
Failure to Achieve Product-Market Fit at MITA.
17:14Despite initial enthusiasm, professors and students did not find value in the tool for tracking student confusion in class.
Forcing customers to use a product does not indicate true market fit, emphasizing the importance of solving real problems for customers.
The failure led to retracting investor funding shortly after receiving it, highlighting the challenge of finding true product-market fit for founders.
✦
The team shifted from their original idea to building an analytics tool due to a lack of product-market fit.
21:55Despite positive interactions with potential customers, they were unable to achieve product-market fit.
Six months were spent coding and adding more features in the belief they were close to success.
The failure highlighted the importance of validating ideas with customers early on.
✦
The creators faced setbacks and reevaluated their approach after realizing their product was not resonating with users.
23:20Meeting with Paul Graham highlighted their lack of progress despite significant investment.
They made a final push with remaining funds and shifted focus to developing an analytics tool.
Leveraging existing code, they addressed customer objections and offered a unique solution.
This strategic pivot resulted in their product gaining traction and overcoming initial challenges.
✦
Implementation of growth hack to drive customer adoption of tool results in positive feedback and success.
27:07Decision to create a landing page leads to increased visibility on Hacker News and GitHub, generating substantial interest and demand for beta access.
Transition marks a significant improvement in product-market fit, with metrics showing strong validation and providing guidance for future feature development.
✦
Importance of Product Market Fit
29:27Emphasizes the shift from pushing products to customers to having customers eagerly adopt them.
Evolution of analytics and lecture tools based on market demands rather than initial vision.
Examples of misjudging product market fit with previous products.
Significance of recognizing when a product has achieved product market fit and the market's power in driving success.
✦
Challenges with open source library in solving marketing tools problem.
31:24Engineers viewed the library as the right abstraction but still needed to create new tools for marketers.
Importance of understanding real-world problems and perspectives for finding product-market fit.
Blue plane symbolizes a new perspective for innovative problem-solving.
Segment collects data from apps and websites, distributing it to tools like Amazon S3, with customer visits revealing popularity of S3 integration.
✦
Importance of Identifying Product-Market Fit Early On.
34:55Connecting data from S3 buckets to Redshift resulted in significant revenue and user adoption.
Customer enthusiasm and rapid implementation demonstrated clear product-market fit.
Presenting innovative ideas that resonate with customers is crucial for building a successful company.
Finding product-market fit creates urgency for delivering solutions that meet customer expectations.
✦
Importance of honesty and eliminating bad ideas in business ventures.
39:11Codecademy founders went through multiple ideas before finding success.
Pricing products accurately based on their true value is crucial.
Accumulating customers before experimenting with pricing strategies is key.
Sales advisors play a significant role in guiding pricing decisions for larger companies.
✦
Importance of early fundraising and product value testing.
40:59Finding the right audience for a product is challenging, along with achieving product-market fit.
Being honest about whether to shift the audience or the product when making changes is necessary.
Codecademy's experience in trying various audience segments before settling on programmers.
The iterative nature of finding product-market fit is emphasized.
✦
Importance of Customer Engagement in Product Management.
43:52Train product managers to listen to customers, understand their problems, and provide solutions rather than pitching existing ideas.
Build a foundation for successful sales by asking questions and digging deep into customer issues.
Initially, find customers through hustle with cold emailing, networking, and introductions.
Once customers are established, focus on inbound interest to maintain a steady stream of engagement.
✦
The challenges of sales involve sending numerous unanswered emails, with rejection being a common occurrence.
47:08Rejection is expected in a business-to-business environment.
The focus is on stream processing and data collection to provide a platform for various tools to build upon.
Segment aims to be the platform for tools such as email marketing, push notifications, analytics, help desks, CRMs, payment systems, and fraud detection.
Segment acts as the integration connection layer, exposing data for partners to innovate upon.
00:11Today we have Peter Reinhardt, he's
the CEO of Segment, went through YC when?
00:16>> 2011.
00:17>> 2011, and
now Segment is doing extremely well.
00:21Peter is going to talk about product
market fit, sort of this magic concept or
00:25word people use.
00:26I don't think they really understand it,
certainly,
00:28the first job to get right in any startup.
00:30Peter, thank you very much for
coming to talk to us, and
00:32I look forward to hearing this.
00:33>> My pleasure, all right, so
00:35I'm going to talk about finding
product market fit today.
00:37Segment is a B2B company,
00:38so that's probably why none
of you have ever heard of us.
00:41But just to give you a little sense,
we're about 150 people, and
00:45grew from about 4 people,
3 and a half years ago.
00:48So growing quickly, and
00:49hopefully I can shed some light on
finding product market fit for you.
00:53I thought I'd just start by sort of
looking back to Alan K's lecture
00:56last week.
00:57I think he had some pretty
incredible advice around how to do
01:00really amazing research by sort
of looking into the future and
01:04imagining what that future might be like.
01:06And in particular, he had this diagram
of sort of exploring the pink plane,
01:09and sort of testing out
different ideas there.
01:12And then at some point, having a
breakthrough and realizing that, actually,
01:15there's a blue plane, right, and you can
sort of go explore an entirely new space.
01:20And that's a key breakthrough for
01:21sort of understanding how you
can really invent that future.
01:25And in particular, he had this idea
of sort of going into the future and
01:29imaging yourself there.
01:30So he had this Wayne Gretzky idea of
skating to where the puck should be or
01:34will be, and sort of going there,
grabbing that future,
01:36and then pulling it back to the present.
01:40And the way that he talks about doing
this is, I think, amazing for research.
01:44He talks about basically going and
sort of imagining that future world.
01:49But I'd actually wager that
01:51not a single successful company has
actually been founded by doing that.
01:55I think that's, again, awesome for
research, but when it comes to founding
01:58companies, it actually has nothing to do
with sort of imagining your vision for
02:01the future and what that future could be.
02:03It's not about sort of how
you wish the world was, but
02:06it's actually about what customers want.
02:08And I think a lot of companies
get marketed post facto, of hey,
02:11we have this great idea, and
here's how we deductively logic out what
02:15customers were going to want,
and then we built the thing.
02:18But in reality, that's not how it
works at all, right, in reality,
02:21it's a very inductive process.
02:23You're going back and
forth with customers, and
02:25you eventually find something that works.
02:27And so I wanted to talk a little
bit about that process today, and
02:30just how critical it is, and
actually, how difficult it is, too.
02:35So one of the most common mistakes that
startups make is to build something that
02:39no one wants, right, or
solve problems that no one has.
02:42And so that Wayne Gretzky method for
sort of going into the future and
02:47imagining what that future might look
like, again, is a good idea for research.
02:51It might even be a good idea for
02:52venture capitalists to sort of imagine
what the future is like and sort of put
02:56startups into different buckets of what
building that future might look like.
03:01But actually, I think it's a really
bad strategy for founders.
03:05And the reason is that most founders can
actually pretty easily build something
03:09that looks like it's from the future,
or is from the future, to some extent.
03:13It's easy to solve the technology problem
there, but it's actually really difficult.
03:18That's not really what you need to do,
right,
03:20you don't need to build something
that is your vision of the future.
03:22You actually need to solve a specific
problem that customers have today,
03:27here, now, and
most startups actually fail to do that.
03:31Most startups actually build something
that looks vaguely futuristic, but is not,
03:36in fact,
a real problem that people have today.
03:38And it will kill the company every time,
right,
03:41the market always wins, so we're going to
dig into that a little bit more.
03:46And this sort of problem of finding
product market fit is that 80% of
03:50all founders fail to
find product market fit.
03:55So four out of five attempts to found a
company just fail at the sort of earliest
03:58stage of even finding a problem
that you can solve in a unique way.
04:03And the last one out of five are going to
sort of struggle through the remainder of
04:05actually building that company out
from there, but that's just the stats.
04:11I'll share our own story of
finding product market fit.
04:13But the short version is that when
you're not finding product market fit,
04:19it feels like sort of
a bottomless emotional free fall.
04:23Not to get too dark, but
when you're failing to find it, it sort of
04:26becomes a strange obsession, and
it could really make you sick, actually.
04:30To get, maybe, too personal for
a second, in 2012,
04:34in the midst of our search for
product market fit, I lost ten pounds in
04:39three weeks, and then went to
the hospital twice for panic attacks.
04:44I haven't had a panic attack before or
since then, and I think it's not just me,
04:48actually.
04:49I think Sam, I don't know if I
should show this or not, but
04:52when he was founding Loot, I think he
basically forgot to eat properly and
04:56ended up with scurvy,
if I remember correctly.
05:00Sam is back there somewhere.
05:02So basically, be warned, finding product
market fit is, very emotionally, a grind.
05:09And the reason it is is that you really,
really desperately want to find that fit,
05:13right, you really want to figure
out what is going to work.
05:16What is something that customers want?
05:17We're all wired to want to succeed and
help people like that.
05:20And so you're so intent on finding this
thing that you sort of convince yourself
05:23into seeing mirages of it.
05:25And basically, you convince yourself,
this is the thing, we're almost there,
05:28it's like this is something
that people really want.
05:32And so this is a picture of myself with
my three co-founders, Elliot, Calvin and
05:35Ian, in the summer of 2012, I think.
05:37And this is in the midst of
sort of our deepest false hopes
05:41that we had found something.
05:42So I'll dive into that story, and
05:44obviously, I'm here today
because it worked out.
05:46I wouldn't be speaking if we had
just disappeared into the darkness.
05:48But yeah, today we're about 150 people,
and growing rapidly, yeah?
05:53>> How can you make sure you're
finding a big market, and
05:57not just a small niche [INAUDIBLE]?
05:59>> Yeah, that's a good question, so
[COUGH] I think PD's advice on this is
06:03good and valid, which is that it's
actually harder to find the first problem,
06:07and solve any problem well,
than it is to find a route out.
06:10So finding a route out from some initial
foothold into a broad market is actually
06:15not that hard.
06:16It sounds hard, but once you find any
foothold, you can pretty much find
06:20something, and I can cover that
a little bit in a bit, but yeah.
06:24>> Is that because you have more
leverage with the customer?
06:28>> Yeah, it turns out that once you
solve a problem for a customer,
06:31they'll keep bringing you more problems.
06:32All right, the most efficient thing for
them to do is just say, well,
06:35I have this other problem that's also
adjacent to it, can you solve that?
06:38And you're like, sure, and you solve that,
06:39and you just keep solving
adjacent problems.
06:43So once you find one thing, it's actually
almost trivial to find the next thing, and
06:46the next thing, and the next thing,
especially in selling to other businesses,
06:50where you have someone who
can just tell you more stuff.
06:53Much harder in consumer,
06:54I'm the wrong guy to talk to you
about consumer stuff, I don't get it.
06:59Cool, but back then,
we were just four dudes in an apartment,
07:02we were failing to find
product market fit.
07:04We were convincing ourselves that maybe we
had it, or we were on the cusp of it, and
07:08we were writing a lot of code.
07:10I saw someone back there who
was writing code earlier.
07:12We were writing a lot of code,
and we had no customers.
07:16That's the wrong order of operations, and
so we were tricking ourselves into this.
07:21In reality,
the good thing that was going on here,
07:24the reality was that we were
a bunch of cockroaches.
07:27And the reason is that
it's very important,
07:30pre-product market fit, to basically
save as much cash as possible,
07:34spend as little as possible and
extend your runway as long as possible.
07:39So a lot of founders make a mistake of
spending a bunch on sales, or marketing,
07:43or other things as soon
as they have an idea.
07:45But in reality, until you find product
market fit, until you find something
07:50that people want, you shouldn't
be spending any time on that.
07:53You should just be spending time
talking with customers and iterating.
07:56And you really want to constrain your
runway, or constrain your burn so
07:59that you can have a really long runway.
08:00So that's what we did,
we kept our burn really low.
08:03I think we paid ourselves like,
08:04the minimum allowable amount by law,
which was 20 or 30k a year.
08:09We lived in our apartment/office and
like the company paid for
08:12part of it as an office,
as it was the minimal thing.
08:16And we stretched out our runway
through as many ideas as we could.
08:20And so to sort of make this process a
little bit more explicit, step one is that
08:23you build, launch, and sort of
iterate on several different ideas.
08:26And this is where it's really
important to be a cockroach,
08:29where you're sort of conserving
everything you have.
08:32Then suddenly something magical happens,
we'll talk about that.
08:36And this is product/market fit and
it really does feel magical.
08:39Hopefully, I can illustrate to you and
help you feel that.
08:42And then,
three product/market fit, sort of,
08:45suddenly turns you into
a unicorn/cockroach.
08:50And rather than just surviving,
08:51after product/market fit,
everything gets suddenly easier, right?
08:55You can, not easy but easier.
08:59Customer show up and buy your thing,
people want to join your team.
09:03You're still pushing
the boulder uphill if you will,
09:05but you're not totally
constrained on progress, right?
09:08You can actually feel forward momentum for
the first time, it's not like
09:11one step forward at the product idea, full
step back when a customer doesn't care,
09:15you actually can keep iterating on
a product that's starting to work.
09:19So, let's take that middle portion and
deconstruct it a little bit.
09:22First we are going to deconstruct
what we call category leaders.
09:25These are really large companies
that have been very successful.
09:29Then we'll get to the heart of
why product market fit is so
09:33important at the very beginning.
09:35And we'll talk about
what bad fit feels like.
09:38Bad product market fit.
09:38And then we'll talk about what good
product market fit feels like.
09:41And we'll try to do that through
stories because the goal here is to for
09:44you to walk away and
09:45be able to more easily identify
which is which, with your own ideas.
09:51So category leaders.
09:52The reason we care about category
leaders is that they're much,
09:54much larger than basically the rest
of the companies out there.
09:58So I'll give you an example.
10:00Amazon and Facebook are sort of consumer
companies that you might be familiar with.
10:04Salesforce is a company that sells
to other businesses that provide
10:07sales software basically.
10:09And the reason that we're interested
in them is that they're huge, right.
10:12They're often ten or
10:13a thousand times larger than
the next competitor in the space.
10:18So, Salesforce for example you've
probably heard of SugarCRM and
10:22Zoho, are probably companies
you've never heard of.
10:25They all do roughly the same thing.
10:27And so, we want to dig into how
can you build a category leader,
10:32what's the layer underneath that.
10:34And basically what it comes down to is
building a platform, where it's not
10:39just a product that you're selling, but
where the data inside of your product
10:44is actually useful for other businesses
to build their business on top of yours.
10:48And that's what Salesforce has done,
that's what Amazon has done,
10:50that's what Facebook has done.
10:52If you look at Salesforce, they have
something called the appexchange, and
10:55the appexchange sort of reveals all
of the data inside of Salesforce and
10:59allows other companies to build marketing
and sales products on top of that.
11:02Similarly, Amazon has
the reseller program, right?
11:06Where now there's ton of other businesses,
built on top of Amazon.
11:11And so, the key here is having some sort
of platform, eventually, when you get
11:15the scale having some sort of platform
that other companies are building on.
11:19Selling, and by nature that pulls
people into your ecosystem.
11:22But, how do you build
a platform like that?
11:26I know Peter Thiel may not be
the most popular right now, but
11:30his opinion is to build a sustainable and
compelling platform.
11:34You really need to get to
100 million in revenue.
11:35And the reason is just that you need to
be at a scale, where someone actually can
11:40capture a couple percentage
points of your customer base and
11:43build a real business themselves.
11:45So if they can capture a couple
percentage points, say, 2 or
11:473 million in revenue,
that's a real business.
11:50You can build something on top of that.
11:53So the sequence I weigh here,
you want to build a category leader,
11:55to do that you need a platform, to do
that you need a 100 million in revenue.
11:58So let's keep digging.
11:59100 million in revenue is tough, right?
12:01So, let's keep digging down.
12:03I think you met Jason Lumpkin
a couple of weeks ago, am I right?
12:07Maybe he is coming soon.
12:09He's written some amazing stuff about
building software as a service businesses,
12:14would highly recommend reading
all of his answers on Quora.
12:17And he basically breaks down the path
to 100 million in revenue in sort
12:20of three different steps.
12:22He says zero to one million is
impossible $1-10M is improbable and
12:27$10-100M is inevitable.
12:28And he says the $10-100M is inevitable,
12:32because at that point there is so
much momentum.
12:35You have customers out there who
are singing your praises, they're buying,
12:38their companies are going to buy more.
12:40And it might take you a while, but
12:42eventually you're going to
get from $10-100M.
12:45One to ten million I think is
basically always a brutal grind for
12:49the founders, and the reason is that
you're running a real business.
12:52You have real customers.
12:53You have some scale.
12:55Your customers have reasonable
demands about sort of how,
12:58the quality of service that
they expect from the product.
13:01But the problem is that
pre-ten million in revenue,
13:03you have a really tough time attracting
a world class management team.
13:07because you can't hire
a great exec team yet
13:08because the large enough
market isn't there.
13:10And so, what you have is basically all the
early crew sort of like holding the ship
13:14together and trying to make
sure that it's going to work.
13:16So, that's a very tough period, I think,
for most founders to go through.
13:19And then, zero to one million
isn't possible because this is
13:23finding market product fit and 80% or
more of people fail at that first step.
13:30And so the question is, how can you become
not and how can you actually make it
13:33through that impossible section and
become one of the ones that succeeds?
13:37And one of the things that people
talk about as investors or
13:40founders is how important it
is to learn from failure.
13:46And I recently read a pretty good study
talking about the stats of, sort of,
13:50the actual analysis of failure and
success in startups and
13:53finding product market fit.
13:57And basically the research shows that
you're actually no more likely to succeed
14:01the second time around if
you failed the first time.
14:03So if you fail in finding product
market fit the first time,
14:06your odds of success are still 20 or
22% the second time around.
14:10But, if you succeed in finding product
market fit, the chances of your success
14:15the second time around go from 22%
to 34% which is still miserable.
14:20But, it's at least 50% better.
14:21And so what I think that means is
there's actually not that much
14:24information encoded in failing
to find product market fit.
14:28Like you don't actually worry that much.
14:30But it's actually quite a bit encoded
in feeling the success of actually
14:33understanding what did work.
14:37And so when we were struggling to find
products market fit in 2011 and 2012,
14:42I felt this really acutely.
14:43We had failed multiple
times at this point, but
14:46I still didn't feel like I really
knew what I was looking for.
14:48What is this mystical
product market fit thing?
14:51So frustrating.
14:53We kept seeing glimmers of hope.
14:54We kept convincing ourselves that this,
that or the other thing,
14:56like a visitor chatting with us on
our site whatever was a big deal, or
15:01a vaguely interested sales
prospect was product market fit.
15:05And so without any positive
product market fit examples,
15:09we didn't really know what it looked like.
15:11And so we could sort of convince
ourselves of everything.
15:14And the way I think about it now is I
really desperately if you imagine like
15:17a machine learning model, I had a bunch
of negative training set examples but
15:21I had no positive training set examples.
15:23And so of course my machine learning
algorithm was like I don't know.
15:27And so I'm not going to
walk through three stories.
15:30But I'm going to show you
two examples of failure,
15:32actually five stories, two examples
of failure, and three examples on
15:36the positive side of times that we
actually did feel product market fit.
15:40And again, my goal is for you to
actually feel what this feels like so
15:43that you can identify
it in your own product.
15:47So today's segment is a customer data
platform, but, we actually started as
15:50an education tool, and it was actually
designed exactly for lectures like this.
15:54So, this is us coding in our Mountain View
apartment, on a summer of 2011.
15:58And the idea was that, as a professor
standing up talking up to a class,
16:02you have no idea if anyone in the audience
actually understands what you're saying.
16:07And so we are students at that time
at MITA renounce school design.
16:11And we said we really want to do this it
gives students a button to push where
16:14they can say, I'm confuse, right?
16:17Or I get it, either one.
16:18And the professor would see this graph
overtime of how confuse the students were,
16:23might be helpful to me right now.
16:26And so, we built this.
16:28We were at hundreds of thousands of
lines of code it had like commenting and
16:31notes and all sorts of crazy stuff, and we
actually came to Stanford's campus, we've
16:36convinced them, it might have even been
in this hall Convinced some professors.
16:39We would like run up to them after class.
16:41This is a picture from Berkley, we pounced
on this professor right after class, and
16:45we were testing for
product market fit, right.
16:47We were trying to convince.
16:48Hey professor like did you get
any feedback from your class
16:51during this class?
16:52No.
16:52Okay well we have a solution for you.
16:55So, we were hustling to try to get
people to actually use this tool.
16:59But we we're mostly sort of ignoring any
test of real product market fit there.
17:04And so professors would agree to test it
out for a few lectures sort of out of
17:09pity, maybe, for some students
from MIT who were trying to help.
17:14And so basically we thought this was
product market fit but it really wasn't.
17:17And I'll show you why.
17:19Because if you stand in
the back of the classroom and
17:20look at what people actually
had on their screens,
17:23none of them were using the product.
17:24Right, like people were using
all these different things.
17:26This is that same class at
Berkley the next week by the way.
17:30It was horrifying, and
basically the students,
17:34as soon as students opened their laptops
they all went and did other things.
17:38And so basically putting
a laptop into the classroom was
17:41the most distracting thing
you could conceivably do.
17:45So as you can imagine,
this was pretty horrifying.
17:47One of the more embarrassing
things that could have happened.
17:50We had just raised 600k coming out of why
Commonator Demo Day, and we had sold this
17:55vision of like, this is how the future
of classrooms is going to work, right?
17:58Like, it's going to be digital, it's going
to be online, much as this is a moot, etc.
18:04And it was a great vision, but
again the market wins every time.
18:09It doesn't matter where vision is,
it matters what the market actually wants.
18:12And in this case,
the students didn't care.
18:14All right, the students didn't actually
get that much value out of using the tool.
18:18And actually if you go back,
we should have had an even earlier warning
18:21sign which was that the professors didn't
really want to use the tool either.
18:24Right?
18:25I mean you go and talk to the professors,
18:26they would sort of out of pity agree
to test it for a few lectures.
18:30But that is not the same thing as
product market fit where they're like
18:32holy crap that solves
this problem that I have.
18:37Bullying customers into using your
product is not anything close to
18:41product market fit,
even if they reticently agree to do it.
18:45I think that being dismissive of users and
having your
18:47clear vision of the future that isn't
necessarily solving a problem for
18:51your customers is a pretty stunning
failure on our part, and is a key thing
18:55that founders do again and again and again
in their search for product market fit.
19:01So then we had to the awkward thing.
19:03Which by the way is the right thing of
calling back all the investors and saying.
19:08This was like four weeks after
they sent the checks right.
19:11By the way, turns out this is a terrible
idea we are going to do something else.
19:15Do you want your money back?
19:17And in most of the cases
the investors did take.
19:20Or sorry, did not take the money back.
19:22Instead, we invested for the team,
like go find another idea.
19:24We believe in you guys.
19:26Go find something else.
19:28So he said, okay, let's do it.
19:31And we were all very committed to working
together as team or four founders.
19:37So we shut down the lecture tool.
19:38We went and sort of shut down all
the classrooms, and then we went back to
19:41the whiteboard and we said, what is
something that is sort of interesting
19:44here and we had always felt like we should
have been able to determine that we didn't
19:48have product market fit, that the product
usage wasn't there from our actual data.
19:53The way that we actually figured this out,
right?
19:55Was we went and we stood in the classroom,
back where Sam is.
19:59And looked at what was on
all the laptop screens.
20:02And that was how we figured out whether
we had product market fit or not.
20:05But we should have been able
to do that with the data.
20:07We should have been able to
just look at the analytics and
20:08figure out not only are people using it or
20:10not, but are anthropology classes using it
different than computer science classes?
20:17And so we decided to build
basically an analytics tool,
20:21which it turns out as bad idea,
in case anyone was considering that.
20:27And so the way that we approach this is,
20:29how many of you have read
the book Lean Start Up?
20:33Wow, that's actually awesome.
20:35You all are way far ahead.
20:36So as talks about you want to
get out of the building and
20:40actually talk to customers, right.
20:42So we read that right around this
moment and we're like, okay,
20:44we're going to go out and
talk to customers.
20:47So we did that, and
we tried to validate our ideas.
20:50So we'd take people out for coffee and
we'd pull people from companies and
20:53try to figure out if they were
interested in analytics products.
20:57And I'd say again and again,
they were vaguely interested, right?
21:00And they had willingness to meet and
chat with us.
21:02And they said they wanted product
updates as things came out.
21:06And so we thought this must be it, right?
21:08This must be product-market fit.
21:09People are interested in what we're doing.
21:12Again, this is not product-market fit.
21:15This is idle interest.
21:17Very, very big difference and so based
on this sort of we got very excited and
21:21we spend about the next six
months just writing codes and
21:24now this is in a new office, that's my
co-founder as you can see there's lots of
21:28code on our screen again,
wrong order of operations.
21:33I had gone on one sales trip
to visit potential customers.
21:37They were all pretty happy with mixed
panel and Google Analytics, but
21:39that had these edge case features that
they were hoping that we could solve.
21:45So, I sort of tricked myself into
believing that these little edge cases
21:47that we might be able to solve were
21:49actually a really wide gap
we could fill as a product.
21:53And so I came back, and
I would sort of pitch my cofounders, and
21:55we would keep sort of believing
that we were almost there.
21:57If we just ship one more feature,
one more thing,
21:59we're going to get to product market fit.
22:03Again, bad idea.
22:06Give you another one, we used lots of
little positive interactions like this.
22:10You can also read this not as a positive
interaction, but every once in a while,
22:14some stray person would visit our website,
and they'd open a chat.
22:17This is idle interest.
22:18Hey, what segment?
22:21And there's a complete
transcript of that website chat.
22:24You can see it's 3:00AM,
so we're up late coding.
22:28And, yeah, this person is interested.
22:33So maybe this is product market fit.
22:36Again this is not what it looks
like this is ideal interest.
22:42So it's now December 2012,
we've been at this for a year and
22:45a half and
we decided that something was wrong.
22:48Right, clearly this was not working.
22:51And so we went back to YC, we emailed.
22:53A Paul Graham.
22:55And we said.
22:56Hey, we think we should catch up and
22:57sort of explain what's happened
over the last year and a half.
22:59And so, okay, great.
23:00So we go.
23:01This is us in front of
the old YC building, and
23:04we're walking around the little
cul de sac by YC on Pioneer Way.
23:08We bring him up to speed.
23:08Okay, we've spent half a million dollars.
23:10Here's everything we've been through
over the last couple of years.
23:13And as we walk around, he comes to a stop.
23:16Aand looks at us, and he says, "so,
just to be clear, we spent half a million
23:20dollars and you have nothing to show for
it." totally accurate.
23:26And super fair and sort of like shocked us
into, ****, yea, we gotta do something.
23:31And that was the moment where we
realized we had hit rock bottom.
23:36But we still have a 100k left so
we still got one more shot, right?
23:39Alright, so that was all
the product market failure cases,
23:41now you're going to see some successes.
23:43But let's rewind.
23:44Let's go all way back to
the first week of YC.
23:48And in that first week, we have been
like well, we have this class and
23:52lecture tool and
we should have analytics on it, right?
23:55So, we looked at the different
analytics tools, guest metrics,
23:59Google analytics, mixed panel.
24:01And we were looking at
what's similar here and
24:03we saw basically they have different
graphs and different APIs.
24:07But it's actually the same data going
into all these tools it's just that
24:10they give you different
stuff out the other end.
24:12And we were like, well, we don't really
want to make a business decision here
24:15about which tool we want to use.
24:17So we'll just solve the engineering
problem because we're engineers and
24:20we'll just build some code that
sends data to all three and
24:22does this automatic translation.
24:24So we put one data point in,
24:25gets translated into three API calls
that go out to all three services.
24:29Cool, this was like 100 lines of code
in the hundreds of thousands that
24:32we wrote, right?
24:33Set that aside.
24:35And then now four months later, it gets
improved a little bit, four months later,
24:38it gets improved a little bit.
24:39At that point we are trying to sell
our own analytics tool, right?
24:43Akin to Mixpanel and Google Analytics.
24:45And we keep encountering the sales
objection when we're trying to sell it,
24:48which is I already have
Mixpanel installed and
24:51I don't really want to install your
tools it seems like a lot of work.
24:53So my co-founder Ilya has this great idea,
he says, what if we take that little
24:58library we wrote a year ago that
we've totally forgotten about and
25:02we add ourselves as the fourth
service that it can send data to.
25:05And then every time someone hits us with
that objection, we hit them back with
25:08the open source library and we say, okay,
great now you can try both in parallel.
25:12And we use this like a growth hack,
25:14basically, to get customers
to start adopting our tool.
25:18Okay great, we start doing that, start
setting it up, people start replying.
25:22This is awesome.
25:23I love the library,
I'm definitely going to use it.
25:25A few weeks later we follow up.
25:28Hey, we saw you're not still sending any
data to segment.io, what's going on?
25:31And they're like well,
the library is fantastic.
25:33I just don't really want to
use your analytics service.
25:37Should have taken note right then.
25:39But a few months go by,
people start storing this on GitHub.
25:43Maybe it gets up to, it was a big deal for
us at the time, like 30 stars.
25:47And I think there was maybe
one pull request issued.
25:50And then, fast forward some more,
people keep sort of paying attention.
25:54It's the first time we'd ever felt pull.
25:56People were just finding this thing and
doing something with it.
25:59And so fast forward,
we have this conversation with PG, and
26:04the next day we sit down and we're like
all right, we need a new idea, right?
26:10And so my co-founder Ian,
he's like, you know what?
26:13I have an idea,
26:14you remember that analytics JS library
that has been sort of idling on GitHub.
26:19I think that could be a big business.
26:22And I was like, you've got to be kidding
me, that's the worst idea I've ever heard.
26:25First of all, it's open source, and
second of all, it's 580 lines of code so
26:29who the heck's going to pay for that?
26:30Right, how do you build a business
around that, it makes no sense.
26:33And so we were like fighting and
fighting and fighting and I went home and
26:35I was wracking my brains so
like, how can I kill this idea?
26:38It's really bad.
26:39And it's going to sink us,
we only have one more shot.
26:43And then, so I came in the next day and
I was like, all right,
26:45guys, here's what we're going to do.
26:46We're going to build a landing page.
26:48It's going to be awesome landing page.
26:49It's going to be beautiful.
26:50We're going to put it up on Hacker News.
26:51It's going to push the product and we'll
have an Email sign up form at the bottom.
26:55And we'll use this to just test
whether it's a good idea or not.
26:58They agree.
26:59Okay, great.
27:00Some I'm like, all right, totally done.
27:02We get ready to launch on Hacker News.
27:03I'm starting to think about other
ideas and it goes straight to the top.
27:07So it gets about 300 up votes on Hacker
News, gets a few thousand stars on GitHub.
27:12We have people reaching out to us on
LinkedIn demanding access to the beta.
27:16Like this guys says,
27:17what does a brother have to do to
get bumped up on your beta list?
27:20And there were others like this, right?
27:22Like holy crap, so full stop, right?
27:25Compare this to everything previously,
everything changed.
27:29This is what product market fail looks
like, where it's not just a single metric,
27:33slowly starts moving,
it's not just a few random conversations
27:36where people express vague interest,
right?
27:39Literally every single
metric went totally haywire.
27:44And with our lecture tool and
our analytics tool,
27:46we've been sort of searching in the dark
for what features to build next.
27:51We did not have that problem any more,
right?
27:53There were thousands of
people who had signed up.
27:54And they're like, your seven integrations
are good, but I need these ten more.
27:58I'm like, I"m like deploying it tomorrow,
I'm like blah, blah,
28:01blah, we're like, holy crap.
28:02Like, okay, slow down.
28:04And that's one of the key things.
28:05One of the key things is it flips from
being something that you're like pushing
28:09against the customer to all of a sudden
the customer's running away with it.
28:13And you're like, but like hold on,
wait it's not quite ready yet.
28:17And so another example,
with our analytics tool,
28:21we had this sort of sad
unanswered questions and chats.
28:25No one really seemed to care
about what we had built.
28:27But now all of a sudden we
had thousands of stars,
28:29people were issuing pull requests.
28:30We got like ten pull requests in the first
48 hours or something like that.
28:36And I guess the other key thins is with
the lecture tool and our analytics tool,
28:40we had had this huge vision, right?
28:41We have a vision of like here's how
the classroom should operate early.
28:44Here's company should do analytics.
28:46And then we went about trying to
build a product that fit that vision.
28:50But this was the total opposite, right?
28:51This is like a little tiny
library that we built for
28:53ourselves that solved the real problem.
28:56We had no vision associated with
it whatsoever at the beginning.
29:00Now it does because we have something
that we really want to go accomplish.
29:04But at the beginning, it literally solves
the tiniest of tiny problems and so,
29:07to your question earlier, right?
29:08Like, this is that tiny little foothold.
29:10And again, it's an open source
library with 580 lines of code.
29:15That's a foothold, right?
29:16And since then now we've expanded greatly
into doing all sorts of things and
29:19solving adjacent problems for customers.
29:22But the key is that, again,
29:23the market doesn't care at all
what your vision of the world is.
29:27The market wants what it wants,
and it will win every time.
29:31So if you walk away with sort of one thing
today, I think it's, let's be incredibly
29:35clear that basically product market fit
doesn't feel like vague idle interest.
29:39It doesn't feel like sort of a glimmer
of hope from some early conversation.
29:43It doesn't feel like a trickle
of people signing up.
29:46It really feels like sort of everything in
your business has gone totally haywire.
29:50There's just this big rush of adrenaline
from customers starting to adopt it, and
29:55sort of ripping it out of your hands.
29:56And it really feels like the market
is dragging you forward.
29:59I think that Dropbox founders
said this best actually,
30:04that product market fit feels
like stepping on a landmine.
30:08And you really, you can't mistake the two.
30:10So if you are at all questioning
whether you have product market fit or
30:13not, you don't.
30:17So, obviously that didn't stop
us from making this mistake.
30:19So just to make sure that this
is [INAUDIBLE], no, all right.
30:27So, I thought ClassMetric for
sure had product market fit, right?
30:31Big vision.
30:32Market said no.
30:33Like, market doesn't care what you think.
30:35I thought Segment.io for
sure had great product market fit.
30:38Again market said no,
market doesn't care, market wins.
30:42And even on our third attempt when we did
find a product market fit, I thought for
30:46sure they were like,
this is too tiny to matter, right?
30:48But actually it solved the real problem,
and
30:51the market demanded it and
sort of ripped it out of our hands.
30:55Either that goes to show
sort of how obtuse I am or
30:57how hard it is to actually
find product market fit.
31:00>> So how come people for
something that was open source and
31:04only a couple lines of code?
31:05>> That's a good question.
31:06So it turns out that
the open source library by-
31:08>> [INAUDIBLE] Repeat the question.
31:10>> Sorry, the question is why
would someone pay anything for
31:14an open source library
that's 580 lines of code?
31:17It's a good question.
31:19It turns out that the open
source library by itself
31:22doesn't totally solve the problem.
31:24So the actual problem that we found out
that we were solving after we launched it
31:28was that marketing teams keep coming
to engineering departments and
31:31saying I just signed a contract with
a exact target in marketing tool or
31:35I just a contract with W Analytics and
here's the docs.
31:40And engineering team says,
what the heck, I have a road map.
31:43Like, I need to be
executing this whole thing.
31:45I can't do this analytics implementation.
31:49And so what really needed to happen and
sort of what analytics suggest
31:53could solve the problem, that we could
solve the hosted version it was allowing
31:56engineers to do a single implementation
of collecting that data once.
31:59And then letting marketers just
push buttons in our interface and
32:01send the data wherever they need it.
32:03But the open source library
doesn't quite solve that problem.
32:05Engineers saw that it was
the right abstraction, but
32:08if a marketer needed a new tool and
there is an open source version,
32:10the engineer still has to go compile it.
32:13So, in some ways we got lucky,
32:14that the open source version
doesn't fully solve the problem.
32:21Cool, so I'm going to steal gratuitously
from Allen K's slides again.
32:25And I think finding product market fit
feels like finding the sort of blue plane,
32:30when you're in the pink plane.
32:32And I want to give some other examples
of finding product market fit,
32:35after finding that initial
product market fit.
32:38And so the key difference from that
initial breakthrough from what
32:41Alan Kay was talking about, is that rather
than removing yourself from the world and
32:45trying to imagine what the future is like,
you actually need to go out
32:48into the world and
research what problems people really have.
32:52But then once you find that product,
once you find that sort of blue plain,
32:56then things actually
get enormously easier.
33:00That blue plane is basically a foothold
into a totally new perspective.
33:05And I think Allen K talked about
the value of perspective and context.
33:07sort of get this foothold into a whole
new way of thinking about the world, and
33:10new way of solving this problem for
someone.
33:13And so, not only do you know
what good fit feels, like but
33:16you are now operating in
sort of green pastures.
33:19And you are approaching problems in
ways that all the encumbrance and
33:22the pink plan don't think
about in the world.
33:26So I wanted to give you two examples
of finding product market fit,
33:30since that initial a win for us.
33:33A short intro to what Segment does,
33:36we basically help you collect data
from mobile apps and websites,
33:39we pull it up to Segment and we fan it out
to all the different tools that you need.
33:43And, that's all you really need to know.
33:46One of the places we could
send data was Amazon S3, so
33:49this is basically just a place
to put all of your log files.
33:54And we started to notice that all
of our business to customers,
33:57were using this one integration.
33:58They were all sending their data to S3,
34:00like you have to do
something with the data.
34:03You don't just like collect log files,
do something with the log file and
34:06you're like what the heck
is going on here.
34:08And so we went and visited five of our
largest customers in New York about three
34:12years ago, and we said okay,
you're using this integration, but
34:16what the heck are using it for?
34:19And for five out of five customers
in a row they said "well,
34:22we have a data engineering team"
that's taking data from the S3 bucket,
34:26converting it into CSV files and
managing all the schema translation, and
34:29then uploading it into a data warehouse.
34:31Red shift.
34:32And the first time I heard that
from a customer I was like, okay,
34:34that's interesting and I took a note.
34:36Went to the second meeting,
customer said exactly the same thing.
34:38I was like, that's weird,
okay, take a note.
34:40Third conversation I was like,
all right, this is getting ridiculous.
34:43Did you guys talk ahead of time or
what happened here?
34:46And by the fifth time it's like, okay,
well obviously I know what we need to
34:49build, we need to build a connection
from this straight to red shift.
34:55So then the question is,
we went and built that.
34:59And just to show you now,
35:00now we have a company that axis here
in millions of dollars in revenue.
35:04And so we have a real product
that real people are using.
35:10And so what does product market
fit look like at that point?
35:12So we're introducing
a second product basically.
35:15Well, it looks like this.
35:17So you can tell when we
introduced red shift.
35:19And basically again, almost every
metric in the business goes nuts.
35:24So, it's very, very clear whether or
not you have something,
35:26that is really transformative for
your customers or not.
35:32One more story and
then I will open it up for Q and A.
35:35So, this is maybe about five months ago,
we had
35:41five ideas for products that we thought
might be exciting to our customers.
35:45So I went to visit the customer up a large
company, up in the Pacific Northwest.
35:51And, I sat down with a data architect
there and I said okay, here are the five
35:55ideas that I want to run through and
see if they're interesting to you.
35:58So I went through the first idea and
he was like, yeah, you know what?
36:03I totally get it.
36:04That sounds super valuable.
36:06And I went through the second one and
he's like, that's really cool.
36:08That's cool that you can do that.
36:09And like, that makes a lot of sense.
36:11And then third idea,
fourth idea, same kind of thing.
36:14And so this is how I would summarize that,
that's great,
36:17I totally understand what the value is.
36:19It means, yeah, that would be great.
36:22Doesn't care is what that is code for,
that's someone being nice.
36:26And then on the fifth idea I said,
hey, here's what we can do,
36:29blah, blah, blah, blah.
36:31And he said "wait sorry, you can do what"?
36:34>> [LAUGH]
>> And I re-explained it and he said,
36:37" interesting".
36:39He turns to his friend and says can you
set up a follow up meeting with this team,
36:41this team and this team.
36:43We also need to tell Joe about this,
because it could affect this other thing.
36:48That is the feeling of product market fit,
which is like, you're like wait, wait,
36:52wait, no, no, no it doesn't exist yet,
these are ideas we might
36:55like all of a sudden the customer
is just going to rip it out of you.
36:58And so now you're on a tight timeline
because the customer expects that it
37:01already exist.
37:03So again, that's what product
market fit actually feels like.
37:09And I think if you want to
find product market fit and
37:13build one of these category leading
companies, become one of the one out of
37:16five founders that actually
does succeed in finding this.
37:18I think you just need to be
really honest with yourself.
37:21That the sort of glimmers of false
hope that you have are not the same,
37:24as customers actually ripping
something out of your hands.
37:27And so yeah, you just need to be honest
with yourself, that's the message.
37:33So, questions?
37:37Yeah, Sam.
37:39>> I certainly agree, and
37:40it's been my experience that that
is what product market fit is like.
37:43But when you're trying to find it,
[COUGH] how do you even like have for
37:47what kind of ideas to try?
37:52When you're just sort of casting
around looking for ideas.
37:55>> I do think that the bigger problem
is not necessarily having the ideas.
37:58I think that everyone has
lots of interesting ideas.
38:00I think the bigger problem is not
killing the bad ideas fast enough.
38:04I think,
actually I have the most respect for
38:06the Codecademy founders in this respect.
38:09I think they tried 12 ideas in 7 weeks or
something like that in the summer of YC,
38:13something totally absurd.
38:15But they legitimately tried them and
they killed them so fast, and
38:18the four days before demo day, they
started a new idea which was Codecademy.
38:24And then it worked.
38:25And on Codecademy on launch day,
on demo day they had 300,000 users or
38:28something like that.
38:29Where like again, that's the landmine
effect of nothing, nothing, nothing,
38:32nothing, nothing and they were so
good about killing the ideas that weren't,
38:36they had no problem throwing out
something that wasn't going to work.
38:41So yeah, I'm not sure yet.
38:42I don't think there's any magic
to finding the right idea.
38:45If you just kill the bad ideas fast
enough, you'll probably find something.
38:52Yeah.
>> Talk a little bit about so
38:54this seems like
a [INAUDIBLE] lines of code.
38:57And it's solving a significant but
relatively small, significant but
39:00small problem, I don't know if
that's the way to describe it.
39:04How do you go about pricing
something like that,
39:06when you're doing that customer discovery?
39:08>> Yeah so we didn't, the question is
how do you go about pricing something
39:11like this where it's
just 500 lines of code,
39:13it seems like it solves
a small problem for people.
39:17We thought it was a small problem for
people, and
39:18we under priced hugely for a long time.
39:22It turns out that that problem that we,
39:24the 500 lines of code solves
is actually really valuable.
39:27There are, we have lots of customers now
that pay over $100,000 a year to solve
39:31that problem.
39:32And there's more to the product now
than the 500 lines of code, a lot more.
39:39But, it's nevertheless is, the size of the
business problem has almost nothing to do
39:44with the amount of code written.
39:47And I think it did take us a little
while to revalue things in that respect.
39:51But to answer your question,
39:53most directly we spent the first
year just accumulating customers.
39:56So we just had lots of people adopting it,
39:58we got to maybe 1,000 or 2,000
companies sending data through Segment.
40:01And then we tried
experimenting with pricing.
40:04And then I'd say the biggest kick in the
**** we had to actually get to the right
40:08point here is we had a sales advisor.
40:10Who said, there were reasonably
sized companies using us like
40:16Live Nation and Party O and
stuff like that.
40:19And so we would go to sales
meeting at these companies, and
40:23the sales advisor would basically
get me pumped up ahead of time.
40:25And he'd be like,
Peter you have to ask for $120,000 a year.
40:28And I'm like, that's crazy,
what are you talking about?
40:31And he's like, Peter,
if you don't ask for $120,000 a year,
40:34I'm quitting as your sales advisor.
40:36It's like, well all right,
here we go, right?
40:40And so I would ask, I'd turn beet red and
40:42then they would negotiate
it down to 18k a year.
40:44But if you keep doing it,
eventually someone is like,
40:46well that seems reasonable, and so.
40:48>> [LAUGH]
>> And
40:50you have to keep testing
the value like that, right?
40:54because you don't know how much value
you're delivering until you start
40:57asking for money.
40:59So I think if I had to do it over again I
would start asking for money earlier, and
41:02I'd be a lot more comfortable with it.
41:03If you're solving a real business
problem people are going to be
41:06happy to pay for it.
41:08I'm not sure I totally answered
your question but, yeah
41:10>> How do you know
41:11you're asking the right
people about your product?
41:14What if there should maybe be a just
a small shift in who you should be asking
41:18that you're not realizing, how did you?
41:21>> Yeah, so the question is,
41:22how do you know whether you're
asking the right people?
41:25And how do you know whether you should
slightly shift who you're talking to
41:28versus shift the product?
41:30Yeah, this is actually why it's so hard to
find product market fit the first time.
41:33And why it's so
much easier the second time,
41:35once you have some product market fit.
41:38Because once you do have a defined
customer set that you sell to,
41:40you'll pretty easily figure out by going
back to those same people whether or
41:44not you're solving an adjacent problem for
them.
41:46But its really hard,
41:47the thing that makes it super hard at the
beginning is its like you have two things.
41:52And you can either slide the product or
41:54you can slide the market by
talking to different people.
41:57And I'm not sure that there's a magic
rule to know when to slide which.
42:04But I think founders get
slippery with themselves,
42:07they aren't totally honest with themselves
about which thing they're doing when.
42:12So I think it's most important
just to recognize that okay,
42:16if we make this shift, we are shifting
the audience versus shifting the product.
42:22because I think otherwise you
can shift the product and
42:24the audience simultaneously, and
think you're doing well, but
42:27then realize you're not.
42:28So I'm not sure there's a slam-dunk
solution to that, other than just being
42:31really honest with yourselves about
which thing you're moving when.
42:39Any other questions?
42:44Last chance, yeah.
42:46>> So you mentioned that you guys
were trying to find proper markets.
42:50That before you guys found it there
was a lot of moments that like
42:53kill this product, kill this product.
42:54How do you encourage people on your
team to be like let's keep focusing on
42:59discovering the next thing?
43:01What do you self-talk, and
what do you talk about as a product?
43:05>> Yeah, so I think there's a pretty big
difference between finding that first
43:09product market fit,
where you can kill a product,
43:12immediately move to
a totally new audience.
43:15Codecademy tried a whole bunch of
different stuff, with a whole bunch of,
43:19speaking of switching audiences,
they went from S and B, to programmers,
43:23to [SOUND] restaurants,
all over the place.
43:25Later on, when you actually are building
a company around it, and you have product
43:29managers, and each product manager is
sort of searching for a big breakthrough.
43:34It's a little bit easier in that you
can't shift the audience anymore,
43:37the audience is fixed.
43:38And so now it's a slightly more
straightforward problem for
43:43sort of helping a product manager
understand how to go talk to customers.
43:46And sort of reveal what problems
those customers have, and
43:49then actually solve them.
43:51So it's most training in that loop.
43:52And it comes from talking to either larger
customers, or your best customers, or
43:57your worst customers.
43:58And sort of trying to push the boundaries
around the core of very happy people have,
44:02to what other problems you can solve for
them.
44:05Yeah?
44:06>> When you talk to your customer,
what do you ask them?
44:08What's your script?
44:13>> You basically just, the question is,
when you're talking to customers and
44:17trying to sort of understand what
their problems are, what's the script?
44:22I think the biggest mistake is,
44:23trying to pitch your existing ideas,
there's a place for that.
44:29Right, when you have some
product market in fit, and
44:31you want to test some of this things.
44:33But I think most founders, and
certainly we made this mistake early on,
44:37of pitching and trying to sell.
44:40Rather that actually trying to
understand what their problems were.
44:43So now when I talk to a customer,
44:45I just start by asking what their
business problems are, right?
44:49Hey, person at retail company,
do you spend a lot on Facebook?
44:53They're like yeah, yeah, yeah,
we spend a lot of Facebook.
44:55I'm like how do you measure whether
that spend is efficient or not?
44:59And they're like well,
we don't really know.
45:01Okay, well is that a problem?
45:02They're like yeah,
yeah that's a big problem.
45:04Well okay,
tell me why you haven't solved it.
45:05And they're like well, we haven't
solved it because blah, blah, blah.
45:09And you just start digging
in to these problems, and
45:11then you're actually really set
up to do a sale then, right?
45:15You're like well,
I have just the thing, right?
45:17And then they're like, holy crap.
45:19But if you don't have a product yet,
45:22now you know exactly what
problem you can fix, right?
45:25So I think it's more about listening and
digging than it is about pitching an idea.
45:33Yeah?
>> How do you find these customer?
45:34How do you be like hey, this is my
customer, this company or is company?
45:39>> Yeah, so the question is how
do you find these customers?
45:42At the beginning, it's hustle,
it's just emailing people cold,
45:46it's getting interest
through everyone you know.
45:47It's scratching and clawing your
way through your social network and
45:51through introductions.
45:52After you have customers in an area,
then it gets easier,
45:56because you have people coming to you
all the time, mostly if you're inbound.
46:01And so then there's a steady
stream of people to talk to.
46:04But the initial piece, that's why people
talk about hustle being such an important
46:08founder quality,
is because no one's going to help you.
46:11You've just gotta go find them, right?
46:14LinkedIn, investors, friends,
it's whatever you can claw together.
46:20Yeah?
>> So at the beginning,
46:21when you lectured for these customer,
when you're cold emailing them,
46:25how many percentage of people
actually come back to you?
46:29The question is,
when you cold emailed customers,
46:31what percentage of
people come back to you?
46:35I don't remember, that was awhile ago,
very low, single digits percentages maybe.
46:42You're going to send a lot
emails that are unanswered.
46:45But that's the nature of sales.
46:45Honestly, if you're in a business
to business kind of environment,
46:48you're going to send a lot of
emails that go unanswered.
46:52Sales is basically the exercise of getting
the door slammed in your face nine
46:56times out of ten, right?
46:58Yeah?
47:00>> What sort of second,
where do you think would be in five years?
47:05>> Go back to diagram.
47:08So what we have today is basically
sort of stream processing.
47:14So we have both the ability
to collect data across some
47:17broad section of stuff here.
47:18As well as the ability to fan it
out to a bunch of different places.
47:21And so what we want to do is basically
provide a platform that all of these tools
47:25can build on top of.
47:26That's the super short version.
47:28So you can imagine basically every team in
a company needs access to customer data.
47:31And we want to become the platform
on which those tools are built,
47:35whether that's email marketing, or
push notifications, or analytics, or
47:39help desks, or CRMs or
payment systems, fraud detection, etc.
47:43All of those things operate on
a core set of customer data, and
47:47that's the customer data that already
flows through Segment by nature of us
47:50being that integration connection layer.
47:52And so we just want to expose that data
to partners to build on top of it.
47:55So when I talked about building
a platform, at the beginning,
47:59that's the next step for us.
48:00>> Peter, we are out of time,
thank you very much.
48:04>> [APPLAUSE]
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