Once you've created the audiences,
you can share them amongst your team,
so you know what you're targeting for different programs
for each of these marketing and sales channels.
Welcome to another episode of "Powered by Snowflake,"
where I interview technology leaders,
building the applications and businesses on Snowflake.
Today, we are learning how Flywheel has built a first-party data platform
that enables customer driven data.
With me is Chris Sells, CEO of Flywheel,
and Tameem Iftikhar, CTO of Flywheel.
Folks, how are you today?
Great.
Thanks so much for having us, Daniel. I appreciate it.
Happy to be here.
Yeah, the same.
And you know, to really kick this off, I want to learn more
about both of you, kind of your backgrounds.
Why and how did you kind of start this company
and build it to where it is today,
and tell me a little bit more about the company and its history.
Absolutely.
Yeah. So Flywheel, the origin story goes back about a decade, actually.
So my co-founder and I, David,
worked at Google and Google Ads marketing at the intersection
between data and how they activate it and their marketing sales, customer service channels.
And as we were working there,
the big "Aha" moment was
we saw the company starting to
centralize data about customers.
But the next question was how do you
activate that and all the tools you use?
For marketing, sales, customer service
to build a better customer experience?
And we saw this big gap in between the two.
So we saw this Data Warehousing becoming very important to the company.
But then there was all of the tools that they used on the separate side
and a big gap in the middle.
And so a few years later, as David and I ventured off
from Google, we decided, "Hey, this is a space we'd like to get involved with, and dive in deeper.
And that was the genesis of Flywheel.
That's awesome.
And for the viewers who aren't familiar with the term first-party data,
tell me what that means.
Yeah, absolutely.
So it's become a very popular term lately, I think, largely because of
folks like Apple starting to do restrictions on privacy and regulation.
So typically what you see is third-party data and first-party data.
First-party data is the data you're actually collecting about your customers.
So when they sign up for a newsletter, you get their email address.
When they make a purchase on your website, then you actually track that transaction.
That's first-party data. It's the data that your customers have given you
express consent to actually track.
Third-party data, on the other hand, is what you hear about in the world of cookies and advertising.
And in that world, you're actually tracking the users, but they're
usually anonymous and you're trying to figure out a way to track
them without having direct access and consent on those cookies.
So the world is starting to shift towards tracking more first-party data to grow their businesses and enterprises.
That's awesome.
And so a better part of a decade is how long...
you've been building up this platform. This application.
Tell me where you are today. What's the size of Flywheel?
The number of employees and funding and things like that?
Yeah, absolutely.
So we call ourselves, like you said, a first-party data platform built for enterprise.
And so we really focus on an enterprise customer base.
We work with folks like Indeed. We actually work with Google First Republic Bank,
And we are about 40 employees, now across San Francisco, Chicago, New York.
And then there's several folks that are remote as well.
And we've actually bootstrapped the company.
So we're bootstrapped, we're a profitable company.
And what that allows us to do is mainly just focus on the client use cases on top of Snowflake,
and have our whole focus there.
That's incredible.
To be able to bootstrap with the background and everything that you have.
I mean, you've got some pretty amazing experience that's relevant to this space.
So it's awesome to see that.
I always like to have a hands-on demo to really bring home what the solution is that you built.
Can we see that today?
Yeah, absolutely.
And we can also run through
where I-- usually a lot of technical leaders ask,
where do you sit in a stack relative to Snowflake,
and how do you enable it?
So we can kind of walk through where it fits into a holistic picture as well.
So we'll do that. And we'd love to walk through a demo on how it works.
That's perfect.
So to start, we want to give you an overview of how Flywheel and Snowflake fit
in the overall data stack.
So this is usually what we ... when we talk to analytics leaders at various companies.
This is the typical stack we're starting to see be built around Snowflake as the center
and how Flywheel fits into it.
So if you start on the left-hand side, you have the ingestion piece to the stack.
So this is how you start to centralize your raw data in Snowflake.
Now, there's several ways to do this.
Obviously, there's a lot of fast transfer services out there
And then there's the event collector services that are collecting
event-driven data from mobile apps and websites to Snowflake as well.
So on that side, we'll see Snow Cloud. We'll also see Segment, Particle and others.
And then once that data gets to Snowflake,
that really serves as the data warehouse and the center of a data universe for a lot of our clients.
And so what they're doing in Snowflake is we're seeing a lot of them use Open Source tools
to start to organize that customer data.
Typically, they're putting together customers tables,
transactions and purchases, as well as event data like, " What are they doing in our mobile app?"
And they're using tools--we've seen a lot around Airflow, as well as DBT, picking up a lot of steam.
And then they'll have the visualization-- BI Layer, Power BI, Looker, Tableau--
to be able to get insights into the data.
And then their running machine learning workloads to say, "Hey, I want to predict something like
customer churn. Is my customer at risk of churning?
And they're doing a lot of that work in Google Cloud as well as AWS on top of Snowflake.
And so where Flywheel fits into that stack is,
once a company gets to the point where they've brought in their customer data
and they're starting to attract customers and their purchases,
we see the new spaces called the Data Activation Layer.
And that's really what Flywheel serves.
So what we try to do on top of Snowflake is,
if you've already centralized your data there,
we want to make it super easy to democratize that data
for your marketing and sales teams, so you can build audiences and customer segments
and then actually activate them to those marketing, sales, and customer service tools
that you already use.
So these are things like Google Ads, Facebook Ads, Salesforce, Marketo.
So if you're trying to actually influence the customer experience
based off the insights and customer data you have in Snowflake,
we've built a software to sit on top of Snowflake to activate that data out.
And so this is what we're calling, holistically, is kind of the modern customer data stack
with Snowflake at the center of it and then Flywheel helping with the activation phase.
That's powerful.
Tameem, you were talking about earlier before this, the architectural diagram
of how you have actually stitched these different pieces together.
Can you talk more about that?
Yeah, I can dig a bit into the details here.
So in this architecture diagram,
it's essentially how Flywheel works behind the scenes.
A little bit of a peek behind the curtain.
And in the middle, you'll see Snowflake.
And just like the other diagram on the left side,
you've got your ingestion layers, which could be AWS, GCP.
It's really cloud agnostic in a sense, because Snowflake is.
So the platform can also be cloud agnostic.
And we're running data pipelines using Air Flow, the Open Source tool that Chris mentioned.
And from there we start to export that data to those marketing tools we talked about.
So all of this is happening in Snowflake,
powered by Snowflake's performance and the querying power we have there.
And then everything else is built around it.
And so why did you choose Snowflake to be the core piece of this architecture?
Can you talk a little bit more about that?
Yeah, absolutely.
So for this to work well, the way I usually put it is , we want to make it so that people can be like wizards with their data.
They can just do whatever they want very quickly.
And for that, you want performance.
So Flywheel has a web UI that you will see in the demo.
It has to work fast. It has to work quick. And Snowflake gives us the raw power.
And the second thing is security.
With governance and all the privacy concerns and things going on.
Snowflake has all of that built in, which allows the team to really manage their data well.
So it made sense for us to build on Tableau Snowflake.
And just a quick other thing is ... people in the industry also settled on Snowflake.
So you can see the community around Snowflake.
So because people are already centralizing in there, it makes total sense.
That's awesome. And so, from here, let's see a demo.
That sounds great. We'll pull that up.
So I think the thing to just stress up front,
and Tameem did this in the architecture diagram,
is this is a very deep integration with Snowflake.
A lot of what we do rests on, and this speaks to your question, Daniel, of why build on Snowflake.
Well, as folks are starting to centralize their customer data there,
it's the perfect logical jump off point because we want to make it
as easy as possible to activate that data without extra work.
We don't want you to send your data out of Snowflake.
We want it to be in Snowflake and then activate straight from there
to lessen the work on the customer.
So really, the demo starts out in the Snowflake UI.
Usually, our customers have started putting their customer data
into a single place in this source's database within Snowflake itself.
So here you can see there's a customer's table, transactions table,
which is all the purchases the customers have made.
And an events table. And the events table shows things like,
what are they doing in the mobile application?
So this is kind of a typical data arrangement you'll see in Snowflake.
And I'm going to show you how you hook that up to Flywheel
in under five minutes and actually start creating customer segments without using SQL.
So we're going to go over the data sets panel within Flywheel.
And what I'm going to show you is how to hook up those data sets we were just looking at in Snowflake.
So I'm going to choose ... in this case, I want to load a transactions data set that you just saw.
And so we're going to select the database that that's within.
Now we're going to select the transactions table.
This the exact name you saw on Snowflake.
And then we're going to provide some configuration,.
You can give it a name quickly. So you can see that in the application to make it easier on users.
And then we're going to put what the unique key is,
and what fields you want to show by default in Flywheel
to make it even easier on your business users
to leverage this data when they're creating their customer segments.
And then we tell you behind the scenes how to actually join this purchase data to the customer table.
This is kind of a key point because you don't want business users to even know what a join is.
You just want to have all this SQL automated behind the scenes.
And that's the key to it.
So we'll go ahead and press Create.
And now we can actually go ahead and start creating audiences on Snowflake data. It's that simple.
So we're going to go over and select New Audience,
and you can see right away ... I can see there's
a million customers in my Snowflake instance that I can be targeting,
And then I can actually see filters that are columns on my Snowflake tables
and start filtering on them.
So I can add in that I want to actually target customers that are spending over a few hundred dollars.
It's a simple field to target my high-spending customers.
And then as I do that, we're actually running a query
in Snowflake and providing an updated count.
And you can see that on the right-hand side. It's 438,000 customers
have spent a few hundred dollars with our business.
So the whole goal here is to make it very easy on the marketing and sales team
to start creating those customer segments on the Snowflake data and go on from there.
So this is a pretty powerful platform.
You know, it really seems like you're able to do a lot on Snowflake and directly query the data.
Does the data have to move out of Snowflake at any point during this process?
Yeah, that's a key poin.
Really what's happening here is
we're generating SQL running in your Snowflake instance.
And that's kind of the beauty.
Instead of having to take all your data from Snowflake and send it to another platform,
you don't have to do that.
So if you've already done the work in Snowflake,
you're able to set this up as fast as we just did and actually query the data in place.
And so from there, you can save this audience.
You can share it with other people on your team.
But really, the key is you can activate it.
So you can actually go ahead and press export and choose a destination channel
that you've set up within Flywheel.
In this case, we have MailChimp.
So if you want to send an email to all these high-spending customers,
you could go ahead and export the data to MailChimp.
You can export it to Facebook Ads, Google Ads, Marketo...
the destination marketing and sales tools that you're going to actually leverage that customer data with.
to improve the customer experience.
And then finally, once you created the audiences, you can share them amongst your teams,
so you know what you're targeting for different programs for each of these marketing and sales channels.
And one of the key things that's going to be happening behind the scenes is...
we're still leveraging Snowflake.
We're actually doing two things here: as you export to MailChimp, in this instance,
we're actually going to be updating that segment.
So everybody that is spending a few hundred dollars...
people are spending a few hundred dollars and being added to that audience in Snowflake.
And so we actually export that audience every hour to
MailChimp and run that query on Snowflake to do it.
So it's always up-to-date in your destination platform.
And then the second piece is, we're actually writing the audience back to Snowflake.
So if you want to know who's in this high-spender audience,
it's actually sitting in an audiences table in Snowflake,
so your BI team can leverage it. Individualization.
That's incredible.
I mean to see such a tight integration between your platform and the capabilities of Snowflake.
It's exciting from my side. During your process of leveraging Snowflake,
what's next for Flywheel?
A lot of questions that I get, for example, is how can customers of Snowflake
join data from the Data Marketplace to even have better insights.
What's next in the line for Flywheel?
Yeah, we see a ton of potential
in exactly what you just mentioned
on the Data Marketplace side
is, if you think about it, you're staring to centralize your customer data,
and what you know about what they purchase
and what they're doing with mobile applications in Snowflake,
the next question is, "Well, can I get demographic data?"
"Can I get other data that's going to augment what I have about the customers
so I can create even more targeted segments
so I can give them a better experience in the marketing, sales, customer service channels?"
So Snowflake Data Marketplace, in terms of adding that data easily to your customer data model
to service in Flywheel, has been a huge boon.
And it's something we're talking to a lot of our customers about.
That's exciting.
Tameem, what is next in the roadmap from a technology perspective for the platform?
Yeah, in terms of technology, we want to get more into intelligence--audience segmentation, eventually,
So if you have your data, can we give you machine learning models
you can run off it and other types of regression models that we can run on it
to give you more insights into your segments and your users
and that's kind of where we see it going.
And also on the reporting side. If you run a campaign on a segment of users,
was it successful or not?
Because you're using Snowflake and you're bringing back
all your revenue, metrics, events data back,
you can actually make the correlation, which is not usually possible in other tools.
Exciting. Chris and Tameem, for our viewers today that want to learn more about Flywheel and the product that you built,
where should they go?
Yeah, you can go to our website at FlywheelSoftware.com,
or just reach out directly to Tameem or myself or solutions@FlywheelSoftware.com.
And we can get a Flywheel engineer to kind of talk through the modern data stack.
A lot of what we do up front is just free consultations around, "Hey, where's my data stack today?
How am I putting that data into Snowflake so that I can activate it?"
And we're happy to be a friendly advisor and help out on that front.
Perfect. And for everybody else watching this video today,
if you're looking to build your application on Snowflake,
check out developers.Snowflake.com
Thanks.
Yeah. Thank you, everybody for your time today. Appreciate it, and thanks for watching.