[APPLAUSE] How's it going everybody?

So I hope everybody's have been enjoying their

talks today, is that is that the case?

Yeah, no?

>> Nobody.

>> Yeah.

>> Okay.

>> All right, we're hopefully gonna ruin that for

you today so, let's get this train wreck started.

>> Yeah, actually just a second, how many people out there are developers?

Mostly, mostly developers?

Has anybody ever traded stocks at all?

Ooh, okay.

>> All right.

>> Cool, cool.

>> Awesome.

>> Alright, so our talk, as you can see here is Lean startup and Micro ideas.

So I'm Greg Winn, by the way.

Winn.

>> And I am Jim Mayes.

And we're basically developers who are who specialize

in building products and we're also occasional day traders.

>> Yeah, nice transition.

>> Yup.

[LAUGH]

>> So we've been working together for probably about ten years.

In the last four years, we're doing something kinda interesting.

We've been going into tech start-ups and building their actually

ideas and making them products and getting them to the market.

So it's a, it's a lot of building building brand new products.

>> Yep.

So you, you've probably heard of the new

thing going around, which is the entrepreneur residence.

So we're kind of like technical co-founders in residence.

So we come into a start-up to provide the technical operations side of things

for them, and we're on our third start-up doing this, working as a team now.

>> So one thing that we found to

do this very efficiently is actually The Lean Startup,

>> Yep.

So, so how many people have heard of The Lean Startup method?

Okay.

>> Oh boy.

>> How many people have actually read the book?

>> [LAUGH] >> okay.

>> Excellent.

>> All right, so we're gonna talk a little bit more about lean here in a minute.

But first, we wanna give a little bit of a little bit

of back story about us, and, why we're standing up here today.

>> So actually last year, like, Ian said, we had won the

the App it out contest, it's it's like a pitch-off, for start-ups.

So, basically, everybody submitted their, their pitches, and

it went to, in like an online vote.

And then the three best actually got to come here in

Vegas and present in front of a giant audience like this one.

>> [LAUGH].

>> And then then there was actually three judges and they voted on the winner.

And so we actually won with a near perfect score.

>> Which is which is right there.

That's that's Jeff Atwood in the middle, who just put down his 9

vote and ruined our opportunity to have a, perfect photo of our score.

so, but, really all the judges were great.

It was, it was a good experience, we got some really good feedback from them.

They asked a lot of really good questions.

So we're, we're up here because we are the reigning App it Out champions.

>> Actually the, first app it out champions for two consecutive years.

>> Right.

Undisputed, mainly because there's no contest this year.

So part of the prize for winning the pitch

off was the opportunity to come back here this year.

Get on stage again, and talk in front of a, a giant audience.

[LAUGH] so, we though the the App it Out contest was a good opportunity for

us because we had an idea that we had been working on as a side project for a while.

>> So, at the time, we had seen a change

in, news media and, social media and their interaction together.

And so the way things used to work is, news media they'd go

out and they'd, they'd see an event and they would report on it.

Well, actually, what we had started seeing was a reverse

in that, so we had started seeing where people were

going and actually at the location the event was happening

and started posting on Twitter or Facebook, hey this is

going on and then the news would actually go on

your Twitter account and say hey there's something happening, going

on, so that actually become more of the actual story

coming from social media instead of just your standard news.

>> So social media was kind of becoming the source for news events.

>> So this is an example of one of the things that happened.

Captain Sully Sullenberger landed on the Hudson river here, like a damn boss.

>> Right, right.

>> Yeah.

>> Everybody remembers when that happened, anybody, okay.

>> All right.

>> So this is, this is an example of an event that, broke first on Twitter.

And then, traditional news media picked the story up from there.

So there's this other thing that, it was news related

that we were also aware of from our trading activities.

And that said the stock market is influenced by

news events as well which makes a lot of sense.

But there's this branch of study in economics called behavioral economics.

And one of the main concepts that comes out of behavioral economics is

the idea that markets are not rational because markets are made out of

the actions of people and people are not rational, so in a ideal

world, people would base their buy or sell decisions on hard facts or data.

>> So, but in reality people aren't that rational, right?

They're they're making their decisions based on their

current mood or what's going on around them.

So, people were reacting, more than they actually act.

And so, yeah, so what we're reacting to is mostly news, right?

sorry.

>> Yup.

So basically, people were like, you know, freaking out

about stuff that's happening in the world all the time,

and that's, that impacts, how they buy or sell

things and that activity actually is what moves the market.

So with those two things in mind, our thought was that

if the market movements are a product of people's reaction

to the news and the news is now coming from social

media, then it stood to reason that social media would

not have the same types of indicators, towards predicting the market.

But more importantly social media was closer to the source.

So it was more real time and that meant that if it

had this predictive power, then it would lead the market more in advance.

>> So the next thing is that the

content on social media is much more accessible, right?

And it's actually in a better format for us to look at.

So it's possible to aggregate this content and then kinda decipher basically

the mood from which everybody's, you

know, having these conversations around these events.

>> Right.

And actually this this piece of code here is open source if anyone wants that.

>> There's the just.

>> yep.

[LAUGH] So we thought this was a pretty interesting idea.

We've been messing with it for a while, and then the App It Out came along

and that gave us a good hard deadline to accelerate the work that we were doing.

But also gave us the opportunity to begin thinking about this idea

in the form of a product, and how it could become a product.

And most importantly, it gave us a really big

opportunity to put that product out there in front of

a bigger audience, and try and get validation for

it, and see if it generated any interest for people.

>> Montage here.

>> Yeah.

>> All right.

[LAUGH] So, so to get ready for the App it Out contest we started pulling

together all the stuff that we actually had

had been putting together for a couple years.

We started building a compelling interface for the tool.

I also started thinking about what would soon become the actual product Cignal,

so it actually went down to the wire and we actually got everything done.

>> Yeah, we probably everything submitted just you

know an hour before the deadline, for the competition.

But what we had at that point was a very

clear vision for what the product was going to be.

>> So we know now the market's are more complicated than ever, so

one constant in making foreign investment decisions,

is the importance of understanding market sediment.

So that's really just the mood of the market.

>> [LAUGH] I'll do this one, you do that one.

>> Okay, thanks man.

We got notes separated on different computers.

>> Once again, we told you, we're not pros.

>> Yeah, yeah.

>> We warned everybody.

>> So [LAUGH] so for years the strategy has been to basically research

mainstream media for in, indicators of market mood, but recent studies have shown

that social media is actually more effective with this, so in fact most

high frequency trade systems are now using this in their their trade strategy today.

So we actually just saw this last year and this happened with the AP Twitter hack.

The Dow was down 140 points and, wow, and

200 billion in US stock market would just, had vanished.

>> This is all just two minutes.

What?

Yeah, that guy.

>> That's a lot of money.

A lot of money just disappeared.

>> So we know industries are using this

technology to make quick decisions, and actually Thompson Reuters

just reported this back in 2012 in their annual

report and Bloomberg just added Twitter sediment last year.

So, Derwent Capital, is the first that,uh, actually validated

the use of this and predicting the overall market.

So, they started a hedge fund around the technology.

It ran for about a month and did really, really well.

but, for a fund that beat the market

in it's first month, it was actually shut down.

And that's because one of it's largest investors told them that they could make

a hell of a lot more money keeping this in the hands of private investors.

So, if you're an individual investor, you have a few problems.

You have no access to market sediment, you've got no clear indicators,

no trusted sources and expert opinions

are often uninformed, ambiguous and manipulative.

The guy, walking dead frame so.

>> Okay, so, we decided that we wanted to try and change all of this.

So we created Cignal to read social networks in

real-time and interpret the mood of the conversations that

was happening there and then use that data to

try and predict what would happen in the market.

And we're seeing over 86% accuracy in predicting

the market up to three days in advance.

So pretty, pretty impressive results from just

a simple algorithm that we were using.

But most importantly unlike the technologies that

the financial institutions were keeping to themselves.

We wanted to make a product that

would be for everybody, whether you're making hundreds

of trades a month or if you only made one single trade ever, we didn't want

you to be an investing pro or

pay thousands of dollars for the research tools,

we wanted to make access to the sediment

data, sourced from the crowd, affordable and accessible.

Because the goal we had for Cignal was to empower all investors to

be able to make decisions independent of

a reliance on the traditional financial institutions.

>> So, we had some pretty ambitious goals for the product.

And when in the App it Out contest, I actually

kind of validated some of our core product ideas, right?

But now the real work actually had to start.

So, we needed to build the product and build the business.

and, wow, yeah, so we've, so we've been working on, doing that.

So the past four years we've been working at, you know,

random start-ups and, and helping them get their product to market.

And so we knew that the only way to do that is lean start up method.

Which we just talked about quickly.

>> So so we saw quite a few of you are familiar with Lee, but those of you who.

>> That one guy who read the book?

>> Yup.

But anybody who's, who's interested in building a product or

running a start up really should check out the book.

The problem with start-ups is that they operate in

an environment of high uncertainty and that makes them risky.

Risky like a new business is, but also

more risky because they have so much more uncertainty.

So a lot of that risk comes from all of the assumptions that we have

to make early on in a product before it gets in front of real customers.

So we make assumptions about that a person has a problem first of all.

We make assumptions about those people who have that problem.

We make assumptions about knowing the best way to solve their problem for them.

And then finally we assume that they're going

to pay for our solution to their problem.

So that's, that's a ton of, of assumptions

that, that have no real backing, at that point.

so, what the Lean Startup method does, is, it attempts to minimizes

risks as soon as possible, by testing them as early as you can.

And that testing process is what we call the build, measure, learn cycle.

And that's really just applying the scientific method to product development.

So you start with one of those assumptions, and you

think about it like it's a hypothesis in the scientific method.

So you build an experiment to test that assumption in front of real users.

You measure the results, and then you

learn whether the assumptions were correct or not.

And, from there you decide whether you need to go back to

the drawing board with something or whether you're on the right path.

So you just kind of repeat this cycle over

and over again until you've reached success or until you've

reached the point where you know that you need to

change your direction or just throw in the towel totally.

So that change in direction is what in Layman's is called the pivot.

And even even if you're not familiar with lean

you've most likely heard the term, product pivot before.

And you've likely also heard the term MVP, or Minimal Viable Product.

So the MVP is just that experiment, right?

It's putting your product together in its most minimal form, so that way you can

go out into the world and begin to

validate some of those assumptions that you have.

>> So we took really a lay of the land and what should be in RNVP.

So we had done this kind of thing before but usually the business

and marketing side of it had kinda been handled for us you know.

We mainly focused on the technical side.

So we recognized that we were gonna need some help.

So we actually contacted two other guys that we worked for or worked with

in the past and had a lot of experience in financial marketing and technical

analysis and we actually asked them to

become the additional co-founders of Cignal, but

anyway we still had no budget, a crap ton of work to get done.

And a lot of assumptions about how our

retail in, retail investors are gonna use our products.

So no money, That's an understatement, But

there's basically three paths we can go down.

We can we can seek investment, we can bootstrap, or I guess we can do both.

Well, we figured that was the smartest thing to do, so we went both.

So we're gonna bootstrap while we pursued investment.

But seeking investment actually gave us a different take on things.

It validated our concept, one.

And it actually gave us a lot of feedback by talking to these people.

We also learned a lot about how funding works.

You want to give up a lot of your company long term

[LAUGH], to get a lot of cash for, your short term needs.

[CROSSTALK] Yeah, very little cash.

>> So at the same time we began to build, the product on a bootstrap budget.

And what we found out was that we could actually

get a lot farther with the idea than we initially thought.

So we leveraged things like Digital Ocean, for cloud

hosting stripe for, a payment gateway that's very affordable.

And, there's just a ton of goods and services out there that, now,

that are, really very affordable, and ver, very easy to implement into solutions.

So we decided to pursue that model of

bootstrapping as far as we could possible take it.

>> So we would do all the work we

possibly could ourselves, even things that were really kind of

outside our typical area of focus, and this was really

to avoid going outside and have to hire additional resources.

>> Yeah, just trying not to spend any money that we didn't need to.

So we still had a ton of work to get done as well.

And in order to get all that work done we

knew that we were going to have to keep things simple.

And really that meant removing any roadblocks

to the process that might slow us down.

So the first thing that we did to approach this was put off making

any decisions that we didn't have to make right then in that point in time.

And by that, we don't mean just putting things off, We mean being able

to recognize when a decision actually has to be made, And when you can

put it off until you have enough information to make the decision well, So

for example, with our architecture, we got the service that we needed for right now.

We didn't try and build the architecture that we

thought we would need months down the road because,

at that point in time, we really didn't know

what months down the road was going to look like.

secondly, we always try to keep a very clear picture of what our MVP was.

So we would try to avoid getting caught up

in solving any edge case problems that would complicate

things or building any of the nice app features

before we had built all of our must have features.

>> So typically the lean techniques can be applied to scaling up,

but they can actually be applied to scaling down into small products.

So, micro ideas are the things that are in your head,

that you might not think are big enough to be an

actual product, but your product ideas, you know, they don't have

to change the world, right, they just have to solve the problem

>> The other good thing about smaller ideas is

that they are not as intimidating to get started on.

A lot of times with a, with an idea it seems bigger to you.

You feel like you have to get all your ducks in

a row before you can even start work at all on them.

So the reason that we're, we're bringing up this

idea of these smaller ideas is that while we were

bootstrapping development on Cignal, we had an opportunity to

execute on a micro idea basically fallen into your lap.

And the micro idea that we had we turned into a service called lnkdto.

This idea came out of a conversation that we

had with a friend who worked at another company.

And this company that he was working with was a publishing network.

And this guy had just been in a, this conference call with

some outside vendors trying to get a solution for problem they were having.

And what they were trying to do is just surface which articles within

their network across their, you know, this network is like 200, 300 websites.

They wanted just a way to surface which

one of those articles were trending in popular.

So the conversation that he was having with the vendor and

the solution that they were suggesting didn't really feel practical to

him because it was gonna require them to go to all

of those site owners to get the solution integrated into their sites.

>> So hearing that, we, we instantly thought,

ok, there has to be a better way, right?

And so what when into pathing is that,

actually what ended up bugging this guy so much

is, is that we, we gave them this new

solution like, okay, you know, here, here it is.

This is what we thought of, right.

He is really mad because he, he knew that

this company would not be able to execute on that.

It just, don't get me wrong, they had a great dev team, it's just

that their, their company was kind of stuck in, corporate tar if you will.

So they're unable to make quick decisions and move, you know, like a, like

a start-up, basically textbook case for a start-up to pop up and solve the problem.

So we created lnkdto, a customisable widget that

displays content on your website or by social shares.

Actually also has an API that you can send one or

many URLs too and get back JSON result of other shares.

>> So so we were able to build a

proven concept of this idea over a single weekend.

We spent the next week productizing it, building the marketing site for the MVP.

Within another week, we had sold our first subscription for it.

Then the next month, we were able to up-sale a customer on it.

So just the first two months, we had brought in enough

revenue to fund operations of the service for the next three years.

So anything after that point is just pure profit.

>> So why did we do this?

I mean, besides the obvious So the easy is quick and easy, right?

It's small and manageable idea we can execute on really quickly.

It also had an immediate market fit, right?

We knew, you know, there is somebody that needs it, yeah.

So, and we also wanted to kind of prove we could execute on

an idea as a start-up at a large corporation with a bunch of resources.

Couldn't get together and and, and execute on it.

But most importantly, is that it actually fed our development of Cignal.

So all, all the profit went towards our main goal.

>> So what we're kinda hoping to to get across to

everybody today with these examples that we're giving you is that.

By leveraging the lean methodology you know,

there's, you can really reduce the barrier of

entry to, beginning to start to build your own products or own start-up today, right.

So you don't have to have this like, next game changing idea,

you don't have to always risk it all to build a product.

You can gain a lot of experience, from building starter small, or smaller

start-ups or smaller products, before you go out there and swing for the fences.

The barrier, again the barrier for entry is low.

There's a lot of services out there that can reduce cost.

The risk is low if you use a meth, you use a lean methodology.

And the rewards of doing this can be disproportionally great.

Like the instance with with lnkdto.

It was very easy, very low effort and it

had brought in a great amount of revenue very quickly.

So if, if you have an idea that you're uncertain how

to get started with, you know, look, look to the lean methodology.

Start with the part of it that you know, and then

figure out ways to test to learn the things you don't know.

So as for Cignal, we're continuing to basically follow that same process.

the, the lean strategy and experiments of do

more experiments around the value of our product.

And one of the things that we're still trying to understand, even better, is how

individual investors can put the information that we

have to use in their personal trading strategies.

So, to do that, we've actually just rolled out a new

feature in Cignal, that adds a gamification layer to the product.

So now we're letting users come in and

look at the sediment against the NASDAQ market.

And then make predictions about what they think is

gonna happen to the price over a period of time.

Then we award points based on how accurate your predictions are.

>> So, you can also actually share that on Facebook or

Twitter and kinda brag about your results or your, performance really.

As you see here, I shared one mistakenly,

I lost seven points in my awesome prediction but.

>> So don't follow his stock tips.

But even more exciting we're also finally opening the

door to our free membership tier, in the product.

And that's been a big part of the vision for Cignal from the beginning.

We wanted to really make this stat accessible to people.

So now, anybody can go and sign up for the free account and

get access to the cinema data, and also, you know, make these predictions.

So thank you guys very much for letting us ramble on today.

If you want to know anything more about Cignal, or you want

to talk about Lean, feel free to get in touch with us.

Follow us, on Twitter or anywhere >> As well as email.

>> Yup >> Or you could also fax us.

>> Yup.

>> Thank you very much we appreciate it.

>> [LAUGH].

[APPLAUSE]