Even a novice user can use
a lot of powerful capabilities
to start to look at predictive analytics,
to dig down into different visualization types,
to look at custom metrics in their reports.
Hi, folks.
Welcome to another episode of "Powered by Snowflake."
Today, I'm talking with Trevor Kaufman, the CEO of Piano,
a digital experience cloud that empowers teams to understand
and influence customer behavior
that is powered by Snowflake.
Trevor, how are you today?
I'm great, Daniel.
Thanks for having me.
Awesome.
So to really kick this off,
I want to learn more about you, your background,
and what you're doing at Piano here today.
So Daniel, my background's actually
in the digital agency business.
I founded an agency called Schematic
that became part of WPP in 2007.
And after I sold it to WPP,
we eventually made it the cornerstone
of a larger global digital ad network for WPP
that was called Possible,
that's now part of Wunderman Thompson there.
And over the course of my time at WPP,
one of my colleagues came into my office one day and said,
we now have this thing called programmatic advertising.
And it means that CPMs are probably
never going to support the production
of premium content ever again.
Now that audience was addressable
instead of just buying adjacency on premium publishers,
ad rates were no longer gonna support on their own
the production of great content.
And he said, "I think everybody in the media business
needs to go behind a paywall at once."
And I didn't know that that was really the answer.
I thought probably there was a more nuanced solution
to the business model for content on the internet,
but I became interested in that space
and started looking at it.
And eventually, another colleague said to me,
"I just read this article on Business Insider
about a little company in Tribeca in downtown Manhattan
that's doing a lot of what you mentioned,
and helping companies charge for access to content."
So I started seed financing that business
and kind of fell in love with it.
And over the course of the next year,
transitioned out of my job at WPP
and into the job as the CEO of Piano.
That's awesome.
So for the folks viewing here today,
can you explain a little bit more, go deeper,
and what is a digital experience cloud?
What Piano is focused on is really two separate areas.
One is analytics.
Reporting on data.
And the other is activation--
how we set up rules so that any team can create
a logical behavior in the business,
so it can react to data in real time.
So really, we think about how we can merge
lots of different data sets together in one place
so they can drive that reporting capability,
and also that targeting capability.
We talk about analytics and activation
or insight and actioning.
That's awesome.
So it's very, very data driven, it sounds like.
Perfect, perfect fit for Snowflake.
Oh, absolutely.
We like to say that in a business-to-business context,
you tend to know your customers.
Most business-to-business folks
have a limited number of customers where their sales reps,
their client success teams,
actually build relationships with those people.
We're more of a business-to-consumer enabler,
and our clients are big media companies,
big financial services firms,
big travel firms who have millions of customers.
And so, the only thing they know about
those customers is their data.
So everything we do, whether it's analytics
to drive understanding, or whether it's activation
to drive business results is absolutely 100% built on data.
That's awesome.
So can you tell me more about the history of Piano?
When exactly did Piano start,
who are some of the most notable customers
that you have today?
So Piano works with a variety of big websites
around the world that are all focused on how to maximize
the value of every single visit.
So we think, oh, when I speak at conferences,
one of the things I tend to say is,
I have several first-party cookies
on every device in this room.
And I know that because you guys read articles.
There's no solution that's more deployed
against media customers in the world than Piano.
And now, we've started to grow more aggressively
into other industries and verticals as well.
Again, this is a slightly old slide.
We're now 18 offices with about 670 staff,
but it's a truly global business.
That's awesome.
It seems like explosive growth, really exciting to see.
So can you talk also a little bit more
about some of the data?
What is the data that you have,
and how are you using Snowflake to analyze that data?
So we like to think of our data store
within Snowflake as a multidimensional,
real-time data availability layer.
So for us, our clients may have other places
where they store data, but we use Snowflake
as a central repository for all the data in our business,
which is all about customer touchpoints.
So behavioral data is all the traditional data
that you would think of from web interactions.
And I really believe we're the best in the industry
at capturing accurate, privacy-first,
device-agnostic data across the digital ecosystem
for our customers, and many customers,
like, for example, the BBC have used Piano
as really their data infrastructure
to capture data across devices.
Then we have DMP data, as we think about it.
So segmentation that we do on customers,
CDP data, which is a variety of answers to questions
that we might ask on websites,
or data that our clients upload in their customer records.
We have transactional data, because we manage subscriptions
for tons of customers around the world.
We index all the content that our end users
read across sites.
So we can start to see within a site specifically
what they're interested in.
And then we're also leading organic
and paid social media posting company for our clients.
So we're getting a lot of data
about social interaction as well.
All of that data goes into Snowflake
and powers the applications we've built on top of it,
specifically, analytical applications
and targeting applications,
a kind of no-code rules engine
that enables our clients to orchestrate what goes on,
either within Piano or within other systems.
That's really powerful.
So can we see a demo of it today?
Daniel, one of the virtues of Piano analytics
is that we have a lot of pre-built
and opinionated reports built within our tool,
as well as a lot of powerful bespoke querying capability,
an in-page analytics tool that lets you see
how performance is going on the page that you're on,
as well as a lot of totally, really flexible,
almost infinite capability in terms of dashboarding.
So those four tools are data explorer,
data query tool, in-page analytics, and dashboards,
mean that our clients can really get their data
that is housed in Snowflake into Piano
and look at it in the ways that make the most sense to them.
In this, which is our Explorer tool,
it's really impossible to generate a bad report.
And in fact, even a novice user can use
a lot of powerful capabilities
to start to look at predictive analytics,
to dig down into different visualization types,
to look at custom metrics in their reports
that they might have created,
even to do these kinds of machine-learning,
analytical analyses where they might look at a day
or a month of data and start to see anomalies in that data
that they can then report on
and start to dig in and understand.
So you can see here where there's an anomaly in the data
where it falls outside of the expected range.
I can actually do some analysis and see precisely why.
What are the other data factors
that caused that data to be out of range?
So here, you can see, a lot fewer visitors,
for example, to a given set of pages, right?
Or a lot fewer visitors from a given device type
that caused a drop in a particular area.
And of course, the more data that we're putting in here
through Snowflake, whether that be social media data,
whether that be transactional data
around subscriptions or purchases,
or whether it be content-analysis data,
it really provides an increasingly
rich set of factors to correlate.
Where all the data that we talked about
and showed within the analytics environment
really comes to life is an environment
where you can set up rules
for specifically what happens based on that data.
So we have segmentation engines that enable you
to take your data and create custom segments
based on a whole variety of different factors,
whether that's geography, entitlement,
interaction with advertising,
browser, device, refer,
whether they have an ad blocker
or a particular payment mechanism configured.
And we use all of that data to enable our customers
to set up orchestration rules,
so that they can show specific offers
to specific users at specific times,
as well as to set up A/B tests without creating any code.
So there's a real advantage to our customers
so that they can set up these conditional logic sets
in their digital applications
without needing an IT team to do something
like set up a sophisticated or nested A/B test
or a new marketing tactic or promotion.
They can set that up very easily without outside IT support,
knowing that it's all data driven
and they can use the machine-learning models elsewhere
within their organization in that set of rules.
Making it easy for utilizing those machine models
is one of those things that's actually really powerful.
It's cool to see how easy it is to set up
those types of rules and leverage that type of technology
for somebody that, like you said,
you don't rely on IT teams.
You can build those things yourself.
So that's awesome to see.
So how is it that you're able to do this type of analysis?
It really seems like you have to have a platform
like Snowflake to power this.
Can you talk a little bit about why you chose Snowflake
to build this application on top of?
Snowflake really provides a lot of the power
that makes our solution possible.
First of all, Snowflake gives us a unified data model.
That means, for the kinds of large organizations
we deal with, they're able to have everyone in the company
have a single source of truth with regards to data.
That's critical for us.
But I think even, well, another factor
that I would say is very important
is the performance, right?
The fact that the data pipeline is as quick as it is
and queries come back as quickly as they do
is vital for us because we are working in sectors
where waiting 40 minutes,
or waiting two hours or even more, is just not acceptable
in terms of a time to get data returned to us.
So both the speed of the pipeline
and the performance of queries are really critical for us.
The power versus cost equation in Snowflake
also really does a lot to power Piano's solution.
Our data is unsampled, which makes us different
than every other analytics tool on the market.
And when you're looking at the types of behaviors
that we're focused on,
specifically understanding something
like how a particular segment converts,
you're looking at a very small slice of overall data.
And if our data was sampled,
we couldn't provide accurate reporting to our customers.
I think that the industry has sort of come to accept
a very low data quality.
But working with Snowflake makes it possible
for us to keep that data quality extraordinarily high,
but yet be performant and cost effective,
which is totally unique.
I would also say in today's very privacy-centric environment
and with the speed at which our customers work,
the ability to effectively pre-process,
but also post-process data once it's inside of Snowflake,
is critical for us, because if a customer data set
needs to be deleted or changed after the fact,
that's possible in Snowflake.
And it's possible in Piano analytics,
where it's just not possible
given our legacy competitors in the space.
And that really cripples, and frankly, puts our clients
at some amount of legal and financial risk
for not being able to do so.
Yeah, having that level of granular access
to that data really seems like a big needle mover
for Piano, in this case, and a big value for your customers.
That's really cool to see.
We build sophisticated queries on a regular basis
and let clients play with data in a way
that I don't think they could do
if we were built on a platform
that was not as performant to Snowflake,
where we can really enable them to play with data
to an extent that they just really couldn't achieve
if those queries were slow
or effectively expensive in another platform.
That makes a lot of sense.
So what is next for Piano?
Six months, one year down the line,
where do you see Piano as a product
and some of the capabilities that you're working on?
We really see the world, again, through this data lens.
And so, as Piano grows,
we have a tremendous amount of data across,
really, the internet ecosystem.
Because we work with so many media clients
who have very large sites, really billions and billions
of page views on a monthly basis,
well over a trillion of those a year,
that enables us to get real insight into content consumption
and conversion behavior around the world,
which is very exciting for us.
I think we're going to be putting a lot more data
into that Snowflake data store in the future,
which is gonna provide our clients with a lot more power.
I think, too, we're very focused on some data sets
that have not really been easily available to clients,
enabling them to share data
through data sharing in Snowflake.
Enabling them to use all the Piano touchpoints,
like understanding advertising revenue data
and users' interaction with advertising in a compliant way,
is very exciting for us.
So there's a lot.
Enabling our customers to exchange entitlement information,
so our customers can bundle together
offerings is very exciting.
So there's really a lot of ways
that we're connecting customers,
both on our own and through Snowflake,
that we think is very exciting.
Yeah, that is pretty amazing to hear.
I know data sharing within Snowflake
is one of those features that is a game changer,
because it allows your customers to have,
utilizing zero copy cloning of Snowflake,
be able to query and leverage that data,
both within Piano and themselves.
So that's really awesome to hear.
For folks that want to learn more
and connect with Piano moving forward, where should they go?
Well, hopefully our website, piano.io,
does a good job of both communicating
and showcasing our product suite,
but also helping people understand
how they can get connected with a team
from Piano in their local market.
And of course, we're quite well-connected
with the Snowflake sales and partnership team.
So to the extent people want to access us
through their Snowflake representative,
they can do that as well.
Awesome.
And for everybody here watching today,
if you want to learn how to build your application
on Snowflake, check out developers.snowflake.com.
Thanks.