Name: Symend at Fintech Meetup 2024 – Putting an end to “zombie engagement”
Uploaded: 2024-04-11T08:14:39.123Z
Duration: 825.36

Symend_1.mp4

Symend_1.vtt

ENGLISH

{{00:00:02}}
Personalization has changed so
much over the last several years.

{{00:00:05}}
It's an area where it's not what
it was a couple of years ago and

{{00:00:09}}
Symend has had a big place in that.

{{00:00:11}}
So why don't you start off just
introducing yourself and telling

{{00:00:13}}
us a little bit about the company.

{{00:00:15}}
Yeah, so Symend is a
seven year old company.

{{00:00:18}}
We founded it with a really basic premise
and it's really taken off more recently

{{00:00:22}}
because of some major innovations
that we've been the beneficiary of.

{{00:00:25}}
But the idea was simple, which
is that at the end of the day,

{{00:00:29}}
big companies communicate with
their end customers for a reason.

{{00:00:33}}
They're trying to relay some
information, change their behavior

{{00:00:37}}
and make them take actions.

{{00:00:38}}
The reason why those things,
they're trying to do those things

{{00:00:41}}
is that ultimately if you can do
those things well, you're either

{{00:00:44}}
going to make more money, improve
lifetime value or reduce costs.

{{00:00:48}}
That's so they're doing
it for a business reason.

{{00:00:53}}
If that's the case, then behavioral
science can play a really big role

{{00:00:56}}
because it's really the science of,
especially when delivered in a very

{{00:01:00}}
personalized way, it's the science of
nudging people towards an outcome and

{{00:01:04}}
controlling for the emotional coefficient
of how they interact with communication.

{{00:01:08}}
So we had a belief that, hey,
these big companies have millions

{{00:01:12}}
of customers to engage with.

{{00:01:13}}
The reason why they're engaging with
them is because they're trying to nudge

{{00:01:16}}
their behavior because it's in their
economic advantage to do so we can build

{{00:01:21}}
a product where that behavioral science
is delivered in a hyper personalized

{{00:01:25}}
way, nudges people towards those
outcomes, and then gets better over time.

{{00:01:31}}
Now, seven years ago when we started,
that was a very, difficult job.

{{00:01:35}}
But over those seven years, we had
this belief, and I can't believe it

{{00:01:39}}
happened the way we thought it did.

{{00:01:41}}
That everybody was
moving towards the cloud.

{{00:01:43}}
People were centralizing their
data in data lakes and data clouds.

{{00:01:47}}
Companies like Databricks
and Snowflake took off.

{{00:01:50}}
And so an orchestration system that
could take advantage of all that data and

{{00:01:54}}
then leverage it into these personalized
campaigns that get better with every

{{00:01:58}}
interaction would become more and
more possible for a large enterprise.

{{00:02:02}}
So today we run like 400
million notes a month.

{{00:02:06}}
We work with some of the
biggest companies in the world.

{{00:02:09}}
And the impact that they can see very
quickly from going to what we call a

{{00:02:13}}
zombie campaign is like this one size
fits all, you're not measuring, you're

{{00:02:17}}
not learning, you're not getting better.

{{00:02:18}}
You're you're not personalizing
really, not truly.

{{00:02:23}}
Going from that to this kind of like
conscious engagement where you're

{{00:02:26}}
understanding people for their human
characteristics and then targeting them

{{00:02:30}}
in a very prescriptive way with science.

{{00:02:33}}
That has, we've been able to deploy that
scale for large enterprise, and we've been

{{00:02:38}}
able to deliver really, profound impacts,
both in terms of one of the things that's

{{00:02:43}}
like people don't talk about in customer
engagement, your goal is to engage less.

{{00:02:48}}
If you have to have a lot of touches
to get to an outcome, that's a

{{00:02:52}}
terrible customer experience.

{{00:02:53}}
The best customer engagement solutions
should be able, instead of with 15

{{00:02:57}}
touches to get to the outcome, you
should be able to get there with three.

{{00:03:00}}
If you know how to talk to people, you
should be able to have an effective

{{00:03:03}}
conversation with far few words.

{{00:03:06}}
And that's what Cement
ultimately can achieve.

{{00:03:09}}
The less friction, the more of
a result you're going to get.

{{00:03:13}}
Okay.

{{00:03:14}}
And talk to me specifically
about financial services.

{{00:03:16}}
What does this market need to
know as you get into a more

{{00:03:19}}
amplified personal communication?

{{00:03:21}}
It's interesting.

{{00:03:22}}
We, started in telcos and there is a
belief in financial services, mostly when

{{00:03:27}}
we first started talking to banks and
FinTechs and lenders that their business

{{00:03:33}}
is completely different than telcos.

{{00:03:35}}
We tried to convince them that, listen,
some of the biggest lenders in the world.

{{00:03:39}}
are telcos that will
finance devices, right?

{{00:03:42}}
Like the three of the top five banks in
the world are actually telcos because

{{00:03:48}}
of the, how expensive devices have
become and the fact that they have

{{00:03:51}}
to finance all those devices to be
able to sell you a cell phone plan.

{{00:03:55}}
So true enough, when you look
underneath the hood of a telco.

{{00:03:59}}
A lot of what they do to adjudicate
customers, to assess them for

{{00:04:02}}
creditworthiness, to give them
financing on devices and stuff, all

{{00:04:06}}
of that technology and infrastructure
looks very similar to what a bank

{{00:04:10}}
does to, for example, give you a
mortgage or a loan or a credit card.

{{00:04:15}}
So that was our thesis going
into the banking sector.

{{00:04:18}}
It took some convincing to tell career
long bankers that, Hey, what we did

{{00:04:22}}
here and had a tremendous impact in
telcos is going to work in banks.

{{00:04:26}}
But once we got a couple of people
believing and we showed them not

{{00:04:30}}
only how big the impact could be,
but how fast they could get to that

{{00:04:33}}
value, it's, starting to snowball now.

{{00:04:36}}
The other thing that I've noticed is that
because the innovation cycle in startup

{{00:04:41}}
land with cloud and data, and now gen AI,
the innovation cycles accelerated so fast.

{{00:04:48}}
Banks and financial services companies
have become more willing to give up

{{00:04:53}}
the idea of we can build this all
ourselves and partner with start ups

{{00:04:58}}
and technology companies to solve
their problem because the faster the

{{00:05:02}}
economy, the ecosystem, the better.

{{00:05:04}}
innovates, and the faster innovation
cycles are, the less likely it is that a

{{00:05:09}}
company will be able to keep up with it
if they try to build everything in house.

{{00:05:13}}
Absolutely.

{{00:05:14}}
So their willingness to partner with
technology companies just in the last

{{00:05:18}}
two years has completely shifted.

{{00:05:20}}
Which, again, companies like us
have been able to benefit from.

{{00:05:23}}
So go into detail with me in
what we have known as zombie

{{00:05:28}}
engagement now, thanks to you.

{{00:05:30}}
And when you get into a true conscious
engagement, what exactly does that look

{{00:05:33}}
like and how are, how personalized is it?

{{00:05:35}}
So it becomes So one of the things that
we've always believed in is that you

{{00:05:41}}
need to build, you need to start simple,
create value, and make your life more

{{00:05:47}}
and more complex in a data driven way.

{{00:05:50}}
And so what that means is that typically
when we start, we work with the

{{00:05:54}}
customers, we understand what they're
doing today, we help them set up.

{{00:05:57}}
Based on all the experience and the 5
billion rows of data that we've already

{{00:06:01}}
accumulated and all the insights and
the existing IP and playbooks that we

{{00:06:05}}
have on our solution, we map one of
those existing playbooks to their needs.

{{00:06:09}}
Where the system really creates
value is that the baseline is great.

{{00:06:14}}
Our IP is great.

{{00:06:15}}
The starting point is basically a
synthesis of what they were doing,

{{00:06:19}}
their brand, their values, and
the IP that we already have on top

{{00:06:22}}
of the platform that creates the
baseline, which is really valuable.

{{00:06:26}}
But it's actually not
the most valuable thing.

{{00:06:28}}
The most valuable thing is starting
with that baseline and then running

{{00:06:33}}
these hyper personalized campaigns
and then measuring because you're

{{00:06:38}}
tagging everything along the campaign.

{{00:06:41}}
Tagging things means that they're, values.

{{00:06:44}}
When they're values, it means that as
you run a job like a campaign, you're

{{00:06:48}}
generating a ton of second party data.

{{00:06:51}}
When you generate second party
data and you flow it back into

{{00:06:53}}
your data and analytical systems.

{{00:06:55}}
You can learn and iterate in a very
agile and high velocity manner.

{{00:07:01}}
That data, that cycle, and that
feedback allows you to get Better

{{00:07:07}}
and better, but also more granular.

{{00:07:10}}
So go from segments to micro
segments to segments of one.

{{00:07:14}}
So we never start with micro
segments and segments of one.

{{00:07:17}}
We get there through the data and
the engagement from their base,

{{00:07:21}}
so that there's a high degree of
attribution between the iterations

{{00:07:25}}
and the optimizations and outcomes.

{{00:07:29}}
So when you say that we're doing this and
it's part of the ecosystem where you're

{{00:07:32}}
able to help the financial services
companies do this, Tell me exactly what

{{00:07:36}}
it looks like when working with SimEnd.

{{00:07:38}}
How do you engage with the company
and what roles are on them?

{{00:07:42}}
Yeah, that's a good question.

{{00:07:43}}
So it really depends on the organization.

{{00:07:45}}
So we built a fairly decent size
professional services group.

{{00:07:51}}
The reason why we've done that is because.

{{00:07:54}}
We wanted to, what we learned as
we engage with large enterprises is

{{00:07:58}}
that there's two bookends and the
truth is always somewhere in between.

{{00:08:02}}
On the one bookend is companies where
they have strong human capabilities

{{00:08:06}}
in house on even like their behavioral
science teams, their data science

{{00:08:10}}
teams, and all these things.

{{00:08:12}}
And what they really want
is better tooling to enable

{{00:08:15}}
and empower those groups.

{{00:08:16}}
For those types of companies where
they don't, they want very much

{{00:08:21}}
to get into a self serve mode.

{{00:08:23}}
We still start by onboarding them,
understanding what they want, and

{{00:08:28}}
partnering with them to fine tune
the playbooks to what they're

{{00:08:31}}
looking for, and hold their hand a
little bit initially, up until those

{{00:08:36}}
internal teams become power users.

{{00:08:38}}
And then over time, we take a step back.

{{00:08:40}}
So that's one model.

{{00:08:41}}
It's you're basically, your professional
services are really just onboarding

{{00:08:46}}
an initial enablement, and then
you're phasing into the background.

{{00:08:49}}
In other examples, it's no,
we don't want to build up all

{{00:08:53}}
these capabilities in house.

{{00:08:54}}
We want to leverage like all
the experience you have from a.

{{00:09:00}}
So we are going to, not only are we
going to leverage your professional

{{00:09:04}}
services to onboard and enable, but
to to be an extension of our internal

{{00:09:09}}
teams and continue to support us in
the learning and iteration journey.

{{00:09:14}}
The truth is always somewhere in between.

{{00:09:16}}
And sometimes people start with a full
professional managed service initially.

{{00:09:20}}
And then over time, they start
to build internal capabilities

{{00:09:23}}
or their priorities shift.

{{00:09:25}}
And I've seen companies go self serve,
but then have reorgs and restructures.

{{00:09:31}}
And so now all of a sudden, because of
that, they want to move to a managed

{{00:09:33}}
service because they don't have the
people in house to do it anymore.

{{00:09:36}}
Or alternatively, the other way, which
is they go for a full managed service at

{{00:09:39}}
Forbes, but then as they interact with
us, they get excited, they get good.

{{00:09:43}}
And their teams learn from our teams.

{{00:09:45}}
And then eventually they're
like, okay, we're good now.

{{00:09:47}}
We're going to move the other way.

{{00:09:48}}
So we built a delivery organization that
could accommodate anything between those

{{00:09:54}}
two bookends, because every company is a
little different and there is no one size

{{00:09:58}}
fits all when you sell to enterprise.

{{00:10:00}}
Spend a moment diving deeper
into the learning and iteration.

{{00:10:04}}
You're looking at results, seeing
if they were successful and then

{{00:10:07}}
deciding your next step on that.

{{00:10:08}}
What in detail?

{{00:10:10}}
Normally, what people do on
optimization is they think about

{{00:10:15}}
it as vectors of optimization.

{{00:10:17}}
You can optimize your segments,
or you can optimize the channel,

{{00:10:23}}
or you can optimize the message.

{{00:10:26}}
And normally, because those are all
discrete systems, like in a very deeply

{{00:10:30}}
covered, low latency way, People don't
look at it as a single system with

{{00:10:35}}
multiple vectors of values where now
you're trying to optimize that entire

{{00:10:41}}
multi dimensional layer of data.

{{00:10:43}}
Yes.

{{00:10:43}}
We don't do that.

{{00:10:44}}
We do, we optimize the
entire system end to end.

{{00:10:48}}
So instead of this traditional A B test
or I'm going to optimize this because

{{00:10:52}}
all of those nodes are interdependent.

{{00:10:54}}
It's like the butterfly effect.

{{00:10:56}}
Yes.

{{00:10:56}}
If you pull on this string.

{{00:10:58}}
That you're not just optimizing that,
there's all of these poorly understood or

{{00:11:03}}
not understood at all interdependencies
on everything that happens upstream

{{00:11:07}}
and downstream of that decision.

{{00:11:09}}
A simple example would be, hey, I've
optimized the communication, but

{{00:11:13}}
then I change my adjudication and a
bunch of people switch risk segments.

{{00:11:18}}
Now, all of a sudden, the wrong
people are getting the message.

{{00:11:21}}
So there's all of these kind of like
interdependencies where if you try

{{00:11:25}}
to string them out and optimize them
separately, it doesn't quite work.

{{00:11:28}}
So we basically built a system where
everything that's part of building

{{00:11:32}}
an end to end engagement playbook is
optimized all at once in a multivariate

{{00:11:38}}
way, which makes us fairly unique.

{{00:11:40}}
Absolutely.

{{00:11:42}}
It's been a good conversation.

{{00:11:43}}
Is there anything I didn't ask
about that you'd like to add?

{{00:11:46}}
A lot of large financial
institutions are moving towards

{{00:11:51}}
maturing their data posture, right?

{{00:11:55}}
It used to be that a whole bunch of
integration would have to happen from

{{00:11:58}}
app to app, That's no like, everybody's
somewhere on this journey, but if you

{{00:12:03}}
fast forward five years, 10 years from
now, everybody's going to be probably

{{00:12:07}}
at this correct ideal state, which is
that apps don't talk to each other.

{{00:12:11}}
All apps, there's going to be some
sort of data management system or

{{00:12:15}}
data cloud system like a snowflake
sitting inside of a cloud instance

{{00:12:19}}
like AWS or Microsoft Azure.

{{00:12:21}}
And then all the apps will connect
to it and will feed it back, right?

{{00:12:24}}
So there'll be a, back and forth
ingress, egress flow to all the

{{00:12:28}}
apps, to the data layer, right?

{{00:12:31}}
In this future world, and everybody's
somewhere on that journey, right?

{{00:12:34}}
It's not binary.

{{00:12:34}}
So they start to break
down the silos one by one.

{{00:12:39}}
As companies mature their data posture,
the next logical thing is, okay, great.

{{00:12:44}}
I've monetized my, I've
harmonized my data.

{{00:12:47}}
It's all centralized.

{{00:12:48}}
Why did I do this?

{{00:12:50}}
The reason why I did it is because I
wanna unlock the value of the data.

{{00:12:53}}
Cement is a capability to unlock that
value, and if you are on a path to

{{00:12:59}}
modernizing, which means you're in the
cloud, you have things like snowflake

{{00:13:03}}
onboarding, something like a cement.

{{00:13:06}}
is incredibly fast and easy and is a
horizon zero way of unlocking value and

{{00:13:12}}
creating more revenue and saving costs.

{{00:13:15}}
So if anybody's already thinking
down that path and wants to try this,

{{00:13:18}}
it's a very low risk, low friction
way of trying and unlocking value.

{{00:13:24}}
So anybody who's interested in
that should definitely come to us.

{{00:13:27}}
I like it.

{{00:13:28}}
Thank you.

{{00:13:29}}
We look forward to seeing what comes
next and it's been a great conversation.

{{00:13:32}}
We appreciate the insights.

{{00:13:33}}
Thank you.

{{00:13:33}}
Hope you have a great show.

{{00:13:34}}
Cheers.

{{00:13:34}}
Thanks.

Personalization has changed so
much over the last several years.

It's an area where it's not what
it was a couple of years ago and

So why don't you start off just
introducing yourself and telling

Yeah, so Symend is a
seven year old company.

We founded it with a really basic premise
and it's really taken off more recently

because of some major innovations
that we've been the beneficiary of.

But the idea was simple, which
is that at the end of the day,

big companies communicate with
their end customers for a reason.

They're trying to relay some
information, change their behavior

The reason why those things,
they're trying to do those things

is that ultimately if you can do
those things well, you're either

going to make more money, improve
lifetime value or reduce costs.

That's so they're doing
it for a business reason.

If that's the case, then behavioral
science can play a really big role

because it's really the science of,
especially when delivered in a very

personalized way, it's the science of
nudging people towards an outcome and

controlling for the emotional coefficient
of how they interact with communication.

So we had a belief that, hey,
these big companies have millions

The reason why they're engaging with
them is because they're trying to nudge

their behavior because it's in their
economic advantage to do so we can build

a product where that behavioral science
is delivered in a hyper personalized

way, nudges people towards those
outcomes, and then gets better over time.

Now, seven years ago when we started,
that was a very, difficult job.

But over those seven years, we had
this belief, and I can't believe it

That everybody was
moving towards the cloud.

People were centralizing their
data in data lakes and data clouds.

Companies like Databricks
and Snowflake took off.

And so an orchestration system that
could take advantage of all that data and

then leverage it into these personalized
campaigns that get better with every

interaction would become more and
more possible for a large enterprise.

So today we run like 400
million notes a month.

We work with some of the
biggest companies in the world.

And the impact that they can see very
quickly from going to what we call a

zombie campaign is like this one size
fits all, you're not measuring, you're

You're you're not personalizing
really, not truly.

Going from that to this kind of like
conscious engagement where you're

understanding people for their human
characteristics and then targeting them

That has, we've been able to deploy that
scale for large enterprise, and we've been

able to deliver really, profound impacts,
both in terms of one of the things that's

like people don't talk about in customer
engagement, your goal is to engage less.

If you have to have a lot of touches
to get to an outcome, that's a

The best customer engagement solutions
should be able, instead of with 15

touches to get to the outcome, you
should be able to get there with three.

If you know how to talk to people, you
should be able to have an effective

And that's what Cement
ultimately can achieve.

The less friction, the more of
a result you're going to get.

And talk to me specifically
about financial services.

What does this market need to
know as you get into a more

We, started in telcos and there is a
belief in financial services, mostly when

we first started talking to banks and
FinTechs and lenders that their business

We tried to convince them that, listen,
some of the biggest lenders in the world.

are telcos that will
finance devices, right?

Like the three of the top five banks in
the world are actually telcos because

of the, how expensive devices have
become and the fact that they have

to finance all those devices to be
able to sell you a cell phone plan.

So true enough, when you look
underneath the hood of a telco.

A lot of what they do to adjudicate
customers, to assess them for

creditworthiness, to give them
financing on devices and stuff, all

of that technology and infrastructure
looks very similar to what a bank

does to, for example, give you a
mortgage or a loan or a credit card.

So that was our thesis going
into the banking sector.

It took some convincing to tell career
long bankers that, Hey, what we did

here and had a tremendous impact in
telcos is going to work in banks.

But once we got a couple of people
believing and we showed them not

only how big the impact could be,
but how fast they could get to that

The other thing that I've noticed is that
because the innovation cycle in startup

land with cloud and data, and now gen AI,
the innovation cycles accelerated so fast.

Banks and financial services companies
have become more willing to give up

the idea of we can build this all
ourselves and partner with start ups

and technology companies to solve
their problem because the faster the

innovates, and the faster innovation
cycles are, the less likely it is that a

company will be able to keep up with it
if they try to build everything in house.

So their willingness to partner with
technology companies just in the last

Which, again, companies like us
have been able to benefit from.

So go into detail with me in
what we have known as zombie

And when you get into a true conscious
engagement, what exactly does that look

like and how are, how personalized is it?

So it becomes So one of the things that
we've always believed in is that you

need to build, you need to start simple,
create value, and make your life more

And so what that means is that typically
when we start, we work with the

customers, we understand what they're
doing today, we help them set up.

FinTech Futures

Expert Insight

At the Fintech Meetup 2024 conference in Las Vegas, FinTech Futures sat down with Hanif Joshaghani, CEO and co-founder of Symend, to discuss the challenges of digital communication with customers and how financial services firms can put an end to “zombie engagement” - automated, generic interactions that lack the personal touch customers want from their service providers.

Watch the video to discover:

· The biggest challenges financial service providers face today when it comes to customer engagement.

· How financial service providers can avoid zombie engagement and interact with customers as individuals.

· How Symend’s Conscious Engagement solution works and how it differs from other customer engagement tools on the market.