We're so excited to
spend our time with you
And I'm joined with my
amazing colleagues here.
And we're going
to tell you
some stories about
Salesforce on Salesforce
and how we use CRM,
data, and AI to power
I already said
thank you, but let
me thank you again for
attending this session.
I really hope
that you'll get
practical and
actionable things
that you can do
within your company
Also, just want
to thank you
for being customers
and partners.
We're really
glad you're here.
Salesforce is a
publicly traded company
and some of the
things we're
going to talk about today
have not yet shipped.
So we want to make sure
that you make your buying
decisions based off of
products and services that
As I said before, my
name is Andy White.
I'm in IT and
I'm responsible
for our go-to-market
technology.
And these are some of
my amazing partners
that I get to work
with every day.
I'll let them
introduce themselves.
And I lead what we call
the Decision Science
group in Marketing
Technology,
doing things like
using our Data
Cloud to help make our
marketing more effective.
My name is Scott Barghaan.
And I'm responsible
for our global seller
experience here
at Salesforce.
My name is
Katherine Sullivan.
And I'm responsible
for education services.
So amazing enablement
skills and training
for everyone in
the ecosystem.
So a little bit
of a roadmap
of what we're going
to cover today.
My partners here
represent the areas
of sales and marketing
and customer success,
so you're going
to hear stories
We're going to have a
specific focus on data
and AI, and we're
going to give you
some best practices
that we've
One of the things that
we all represent here
And that means that we are
Salesforce on Salesforce
and we use our
own technology
This is grounded
in our values
and we are here to provide
the best technology
And one of the
ways we do that is
by releasing the products
and services to ourselves.
A specific example of
this is the 252 release
that we received
internally two weeks ago.
There is a major
issue with that
that we uncovered
internally,
and we were able to work
with tech and product
to solve it before we
released it to production
to all of you, which
was painful for us,
but good in the long run.
And that's a
big part of what
It's also about giving
really direct feedback
to our product teams
so that our product can
get better for ourselves
and for all of you.
We ultimately see that
driving customer success.
And we want to prototype
the path for all of you
so that we can
show you the way.
A great example of that
is agents and the work
that we're doing to
deploy those internally
so that our customers can
learn from our example.
This is all about
the Customer 360.
And that means that
we're leveraging
all of the
Salesforce products
to drive meaningful
outcomes for our employees
And I honestly
feel like this
is an unfair
competitive advantage
that I have as
a technologist,
because when you take
Sales Cloud and Service
Cloud and combine
that with Data
Cloud and Tableau
and Slack,
it's really,
really amazing.
And the cool thing is
it's something all of you
And so we'll share more
specifically about that.
But even though
we have all
these amazing capabilities
and technology
that we can use, we
have [INAUDIBLE].
And it's no
different from you.
We have data and
organizational silos.
We're being challenged
to do more with less.
We want to release
AI quickly,
but also safely
and securely.
We want to reduce the
administrative burden
that our employees
have to do every day.
I heard an amazing
stat yesterday,
which is five weeks a
year is general knowledge
worker employees are
spending on swivel chair
experiences of copying
and pasting information
from one system to
another five weeks.
I'd much rather
be spending
my time on vacation than
copying and pasting.
So these are the things
that we think about.
And I know they're the
things you think about,
And we're going to talk
about them today and give
some real-world
examples, and starting
And I work in our
marketing technology team.
And we do a
lot of our work
to essentially the
Salesforce side.
How can we actually use
Salesforce to both run
marketing but also
support the whole business
And so let's talk a little
bit about marketing.
So when we think
of marketing,
we think of marketing as
a way to create demand.
Now, I think all of you
today are experiencing
So you having a good
time at Dreamforce?
It's a pretty good
experience, right?
Some good speakers,
some good events.
You're going to go see
I think Pink tonight.
So in marketing,
we're trying
to do a lot of things that
create interest and drive
But there's coming to
an event like this,
coming to our website,
trying out our products,
attending a
webinar, all of this
to create demand and
interest to then explore
And then when a customer
says, hey, I'm interested,
our marketing automation
then takes that interest
and gives it to
our sales teams.
Now, of course, we're now
a big global organization.
I think we have
15,000-plus sellers around
the world, all kinds of
industries and verticals.
So, of course, we had to
build a lot of complexity
to manage that
demand and to make
sure we can
connect all of you
to the right folks
in the company.
But as we have
grown, we ourselves
started to have
challenges.
We have our own kind
of fragmented view
with data being
trapped in systems.
Some of this is because
we bought big companies.
We bought Tableau, we
bought Slack, MuleSoft.
They have their
own data systems,
their own marketing
automation.
And so over
time, we started
to have a fragmentation
of the customer.
We sort of have
bottlenecks
to being able to use this
data to really, again,
And just again,
as we scaled
more and more
complex business,
that starts to
bring challenges
of how do you manage
these experiences really
And so our
strategy and vision
has really been to put the
customer at the center.
We say, build
the Customer 360.
That's what our job is
to do for ourselves.
And so we brought
together a view
for every single
individual,
we want to know
their identity.
So think of it
like their account.
Or when you all signed
up for Dreamforce,
you signed up what's
called Trailblazer ID.
Behind the scenes,
that's Okta, where you're
authenticating,
you're giving us
But then we need
to marry that
with what are all the
things that our customers
So are you completing
a trail in Trailhead?
Maybe you're talking to us
with our new Agentforce.
Maybe you're doing a
trial of our products.
Maybe you're subscribing
to the newsletter
These are all the
different engagements.
All of that data
is ultimately
It's stored in many
Salesforce systems.
Org 62 is where we
manage our sales,
Org CS is where our
service agents work.
We have Marketing
Cloud, but then we
have many
third-party systems.
Again, Okta with
Trailblazer ID.
We have Snowflake for
enterprise data warehouse.
We have a data
lake on Amazon.
So pretty much we get
every possible probable
system that we had
to bring together.
And what we've
done is said,
let's bring it
into Data Cloud.
Harmonize that
data and then
use Einstein to build
intelligence like scoring
every lead, scoring
product interest.
We sell 55 SKUs
and many sub-SKUs,
we've got to figure out
what our customers are
interested in, and
bringing the customer
success score so that we
can then help our customer
success team, again,
better create success
And then if you have all
that data and signals,
they then go
into the channels
where you can manage
the experience
with the customer, whether
it's an email, website,
Then, of course,
you use Tableau
to visualize
and see the data
and get all the
benefits of the trust
and the security
of the platform.
This is where
we are today.
So we have built
our own Data Cloud.
We call it the Customer
360 Truth profile.
It's just our
internal branding.
But essentially, we now
have a few hundred data
streams of data coming
from Salesforce,
from Marketing Cloud, the
zero-copy with Snowflake,
We've ingested more
than 15 billion records
of many different
data sources
from our website
engagement,
And again,
everything in CRM.
And then partners
like Demandbase
who help us with
third-party data signals
All of that comes
into Data Cloud,
which then harmonizes
and resolves
what we think of as
primary data or master
So we are now resolving
about 124 million
unique individuals,
something 40% to 50%
So this means
we're duplicates
that were in systems
that now were
And so we have a view
of the individual.
We actually have a
view of the individual
different than the contact
because we hope you
Maybe you change
companies,
maybe you become
a trailblazer.
We want to
understand that.
That's a little bit
different than your role
in an account
when you have
a commercial
relationship with us.
We also look at
what's the right lead
What's the right account?
And how do we again match
companies to accounts?
So we're building
more and more
trusted data assets the
whole company can use
in Data Cloud that turns
into hundreds of segments
and that turns
into activations
that go to channels
like advertising.
It goes for Google Ads,
partners like LiveRamp.
It goes back into
Marketing Cloud.
And then ultimately,
we activate it
across all the channels
I showed before.
So let's show
some examples
So the first is we run
a lot of paid media
And lately,
we've been using
the Ad-Tech
partnership built
in Data Cloud, for
example, with Google Ads,
And this enables
us to take
our proprietary
first-party data,
but in a secure way
and a secure clean room
match our audiences
to Google's audiences
so we can find
more people who
may be interested
in our products.
And we're seeing
amazing results.
More than a 5x increase
on pipeline return when
we're able to use our
first-party data signals
to find the
best audiences.
And of course, we
run a lot of email.
I'm sure you probably got
a lot of these emails,
too, once you signed
up for Dreamforce.
We send more than 350
million emails a year.
211 countries,
55-plus products,
12 languages and
growing, and now hundreds
And one of the
key innovations
is now with Data
Cloud, we can
take all of those
signals and automatically
push it to Marketing Cloud
so that these attributes
can help us make our
messaging more relevant.
And of course, we're
always getting better.
So if we don't
get it right,
This is part of the work
is a lot of complexity,
but we're
increasingly trying
to use what we
understand and listen
at scale with
data and then use
that to make our marketing
more personal, more
relevant, and ultimately,
more engaging for all
Once you're interested
and I know you are,
you say, all right,
I want to learn more
about my products,
then we have
to get that demand a sale.
So we have our sales
development reps,
which really take
the inbound, business
development reps, which
work with accounts
and take both
outbound and those
who are in an account
who maybe are interested.
And then of course, we
have some customers who
think they're not
quite ready to buy yet,
let's nurture them,
both with things
like automated emails
and with Agentforce
I think pretty
soon we're going
to be deploying our own
SCR agent to help qualify
customers who may be
earlier in their journey.
And now I want
to show you,
we have over time built
our own very custom stack.
So we had built our
market automation
with more than 2 million
lines of custom code built
over a decade ago, we're
starting to get a bit long
And we said, could
we re-platform
And so in the
past year, we
rebuilt this using Data
Cloud, Einstein, and Flow.
So that for every single
customer response,
we can now look at that
profile, that individual,
understand their intent,
use Einstein to score
and evaluate
their interests,
and then use Flow to get
them to the right person.
So do you want
to see a demo?
So let's say you're a
customer, like Jessica,
who's one of our wonderful
product directors
And you come and
you say, I really
want to find out what's
going on with marketing.
Can you send me the
eighth edition state
Of course, I'm sure
you all want this.
[LAUGHS] And
you fill it out.
Well, it comes
into Salesforce.
And we create
what's called
a rule of
engagement request,
where we essentially
evaluate that response
and look at the
data and metadata
to say, where should we
route this in the world?
What segment are they in?
What's all the
information we know?
But of course,
we don't just
want the information
they gave us that time,
we want to know
what else do we
know about this customer.
And this is a view
into our data model
on Data Cloud that
for every individual
we're mapping
into our account,
we're mapping them to
website engagements,
we're mapping
them to email,
really building
this full resolve
And just an example
of that, we're
able to take analytics
from Google Analytics
for the website
behavior and map that
So that when you
fill out a form,
we can also say,
well, what else
did you do on the website?
What were you doing all
the previous sessions?
What products were
you looking at?
How can I now use
that to also inform
And that turns into
something like this.
And this is by
the way real.
This is a CRM application.
You could build
this yourself,
showing a unified
profile, unified consent
And then that
triggers Flow.
And so this is our
automation engine
that is assessing
for everybody.
My setting to BDR and SDR.
It's basically
we're logging
every step of the
flow, which gives us
And then Flow is
amazing because you
So this is our
SCR subflow.
We have a branch, we
have global minimums.
Again, we have a
lot of custom rules,
embargoed countries,
all kinds of fun stuff
when you're a massive
global company.
Flow executes all
of this logic.
And very simple visual,
but mostly no code,
but a little bit of code.
And then it ends up
sending a lead back.
So we write all this
data back into Org 62
and you can
see the record.
And now we have
the information
scored with
machine learning
And so what's been
amazing about this
is since we did it,
it's been about a month
We're able to
take our speed
to lead from 20
minutes to 20 seconds.
We're now to 16
to 20 seconds end
to end, taking it,
matching with Data Cloud
scoring and
having it appear
in our inbox in Salesforce
for our sales teams.
And the biggest thing
is because we built it
on Flow and Salesforce,
in the past, whenever
we wanted to
make a change,
we had to have a developer
make that change.
We again had more
than 2 million lines
We've had a 90% plus
reduction in code.
Now I think it only has
10,000 lines of code
because Flow is doing
most of the work.
And that means most
changes that our sales
team wants or our
marketing team wants
are just a
configuration change.
It's just an approval
Flow in Salesforce.
So now we're able
to make changes
in days instead of weeks.
And the biggest
thing is this really
Now with using
Einstein in scoring,
we call the lower
scoring leads to sales.
If we don't think
you're ready
and you don't want to
talk to us yet, that's OK.
We'll send you
some more content,
invite you to
some more events,
and then when
you're ready,
then we'll get you
over to our sales team.
But of course, to talk
about how our sales
team really helps
to manage and build
partnerships, I want
to hand over to Scott
And first of all,
phenomenal work.
So as I explained
earlier, my role
here is to look after our
global seller experience.
And that's inclusive
of 15,000 sellers,
5,000 solution engineers,
5,000 customer success
managers, and 5,000
operators that support
our business each
and every day.
Now, prior to
taking this role,
I spent 23 years in
the field carrying
a bag, the last
eight of which
here at Salesforce
as a first, second,
And before I say
anything further,
I want to thank
everyone up
on this panel for
helping make all of you
as customers
and my business
both grow and help you
all to be successful.
Now, with
everything that--
With everything
that Michael said,
it is but the start of
the process for sellers.
And today, as many of you
know, growth isn't easy.
And that's primarily
because the amount
of buyers that are
involved in every B2B
buying cycle has exploded.
And those buyers
have turned
into buying committees,
all of which
need to say yes and only
one needs to say no.
And within
those committees
of interested folks,
we have new personas
that are often new
to our sellers that
take more time to come
up to speed and make sure
that we're meeting what
their questions are.
And at the same
time, we're
seeing a risk-averse
buying environment
which is driving more
POCs, more research, more
Even the first human
action is now over 70%
through the process where
by average it takes place,
and all of this while
sellers are trying
to make activity,
pipeline, and quota goals
each and every week,
month, and year.
Now, our approach
to this is
to apply tech
as a teammate,
because across
our organization
we have sellers
that are coming
from different
backgrounds,
calling on different
customers, different sales
motions, different
parts of the world.
And we need to make sure
that the technology meets
their needs wherever
they may be.
And we apply it in
two relatively simple
counterbalancing
ways, starting with,
how do we reduce
the burden?
And often cases this
is by the explosion
of those buyers and the
explosion of activity that
in many cases is
what's filling all
the queues that
Einstein is helping
us to prioritize through.
So whether that be
automation, whether that
be summarization,
we're trying
But that only works
to help drive growth
if we then return
that time to raising
And that means
spending time
poring through that
information, the ones that
are prioritized, and
summarizing the most
key points so
that we can focus
on how to be competitive,
how to be differentiated,
and how to drive our
companies forward.
Now, the way
that this works
in very similar
fashion why I'm so
thrilled to partner
with everyone here
on this stage
is that we're
operating from the
same data environment
because data is
the fuel to sales
And that starts by taking
a really intentional view
And that starts
particularly
by flipping the paradigm
that CRM has been based on
Well, frankly,
the value of CRM
is the function of
how many reps put data
And what we've
done-- thanks
to Michael's work
and Andy's work,
has been to
re-platform, make
certain key
decisions, which
I know Andy called out as
a huge part of this story
of how did we all squeeze
together to make decisions
in the benefit of the
company, not maybe
our individual
project program
or even part
of the company.
Make decisions about where
we put technology, rethink
some of our
governance rules,
and then perhaps the
biggest thing of all
is reimagine how activity
gets into the platform,
take advantage of
technologies that allow us
to stream in that
data, bring in data
that people were swiveling
back and forth the five
weeks Andy would
like to get back.
And then equally
look at all
of those digital
footprints that
align to how you as buyers
want to work with us
and bring those into
CRM and then apply data
to summarize, help me
find what I should know
about that before
I edit, not author
the primary data and CRM.
And this is how we're
aiming the paradigm
to give value to sellers
before we get anything
Now, I'm going to tell
a little bit of how
this story plays
out through three
One about how we started
with this foundation
to build our account
planning product,
how we then layered
on great activity
and summarization with
conversation intelligence,
and then last but not
least, how we brought
the power of
Salesforce data, AI,
and CRM to every seller
on the go and Slack Sales
Now, we all know that
account plans are often
the bane of the existence
for every seller
because they're written
once and used never.
But what if we actually
reimagined that process,
put it back into CRM
in the place where
all of that activity
already existed?
Now, account plans are
great to bring in data
from other systems,
other places,
but they're also
a place where
I want to bring in
information about people.
Especially when you think
about that explosion
of buyers, I need to
know more and more
And thanks to
Einstein, not only
am I bringing this
together in one place,
but also making
interesting correlations,
able to annotate the
contacts to make that 360
Now, what's the
best part of this
is that I was
able to do this,
thanks to bringing
this all on platform
and automating
through partnerships,
especially those
that are associated
Now it's time to
do some real work.
Now let's go meet
with customers.
Now, one of the
biggest challenges
we have is with this
explosion of activity
But what if I brought
Einstein to every call,
where he could record
exactly what happened,
summarize for me,
find the action items,
and allow me to
be that hero back
to the customer that got
hopefully one of the 16
meetings they did that day
with a summary and action
items before they
left the day?
This is a key part
of differentiation,
but equally, how do
we keep the whole team
I love getting an
hour-long recording, said,
But if I could ask the
question to the call,
hey, did I miss something
about my particular area?
Now another win
is stepping out
of that meeting and
being able to jump
right back into context,
notably on my phone.
And this is where we
partnered with the Slack
product organization to
build Slack Sales Elevate.
And that started with
the simple concept of,
I need to come
out of a meeting,
update opportunities
without having
to perhaps open my
laptop or get too deep.
And in this
case, you see me
going through a very
simple update where we've
been able to cut 50% out
of the time in which we
were asking
sellers to update
opportunities and help us
have accurate forecasts,
There are tons
of information
that goes on around
the business.
How do I know where
to spend time?
Where are these
correlations
Thanks to
notifications that
are both coming out
of Data Cloud and ones
where programming top
down are helping sellers
find those diamonds
in the rough.
And then take
action directly
in the record channel
or Salesforce channels.
And in this case,
as I can see,
Give them a quick
emoji and off they go.
What you just
saw here is truly
how Salesforce runs
on Sales Cloud.
What you saw
in front of you
is a handful of products
that were brought together
around key jobs to be done
that sellers do every day.
And this is where I'm so
proud that the way we've
built the organization is
to listen to our sellers.
And that's making sure
that the jobs that
are important to them are
ones that we're taking on
And equally for both our
sellers and our operators,
we're thinking about
equally the qualitative
And perhaps the thing
I'm the most proud of
is this is not only
making their lives better,
but it's driving
real results.
In Q2, we saw the
sellers that were leaning
into these new
methods, in particular,
conversation
intelligence, closed 50%,
5-0 more than
those who didn't.
And so speaking of
results and the things you
all expect of
us as a company,
I'm going to turn
it over to Katherine
As we start this
conversation, what
I want to point
out here is
you think about all
the amazing work
that Mike and
Scott both do it's
in that pre-sales motion.
And then when you think
about customer success,
you will say it's really
in the post-sales motion.
So one of the
biggest questions
I get when I meet
with customers is,
And then I'm going to
transition and start
talking about what
customer success looks
But I want to reemphasize
customer success is
We have a
dedicated team that
is focused on
our customer's
expertise, our customers
realizing those values.
In the
organization, I want
to break it down a bit
because at every company,
customer success may
look differently.
Here at Salesforce,
we are 9,000 deep.
And that's
interesting when
you think about the number
of certifications we have.
We have over 30,000
certifications within that
In that organization,
we have over 5,000 team
members dedicated
to customer support.
And then we have
architects, instructors,
guides, phenomenal success
managers across the board.
There are some
interesting numbers here
that I want to
double-click on.
First and
foremost, when you
think about the
number of cases
that the team
supports every year,
we have over 2
million support cases.
In a few minutes,
I'll walk you
through how we are
successful in handling
In addition, all of the
engagements we have,
the human and the
digital engagements
equal up to over
176 million touches.
What's important
to call out here,
as we've talked about
throughout today's
discussion, is we're
leveraging our own tech.
You can see there in this
nice view of the 360,
all of the
technology we're
using to power
customer success.
When you look at how
our customers are coming
to receive
assistance, there
are three primary
portals for
We have the Help portal,
we have Trailhead,
and we also have the
Trailblazer community.
What's phenomenal
about that
is you think about the 172
million touches I noted
earlier, 162 million of
those are digitally-based.
We recognize that you
and our other customers
are looking for a
digital engagement.
They are going
to go to Google,
they are going to
search, they're
going to go to
our help portals,
they're going to want
to engage and try
So we invest
efficiently in
And you can see
here, we also
leverage our ecosystem,
our partners to power
Now with that in
mind, let's talk
about how we're
going to take
that digital experience
to the next level
Now, I'm going to give
you a little inside scoop.
We were preparing for this
video and one of my team
members said, why don't
we create basically an AI
And I thought,
oh, interesting.
Well, they took
a script of mine
from another discussion
and then created
an AI version of me
for this conversation.
So let's hope we're
going to actually get
that in this demo
because we had some tech.
All right, let's
start this.
- This is the Help portal
where customers like
Before, our
customer, Jasmine,
would have to search
for an answer and comb
through the
relevant Salesforce
content on the Help
site to find an answer.
Now, Jasmine can ask
her questions directly
to an AI agent
powered by Agentforce.
The AI agent
greets Jasmine
by collating her on
her Trailhead Ranger
accomplishment
and thanks her
for being a
premier customer.
When Jasmine asks the
same question here,
the AI agent gives her a
list of steps to follow.
Unlike traditional
chatbots,
the AI agent is grounded
on all the content
Yes, that's all of
Salesforce's 140,000-plus
knowledge articles,
help documents,
and release notes so it
can find the right content
before generating a
personalized response.
Jasmine can even ask
follow-up questions
like she would
with a live person.
This is a simple example
of how AI agents can
provide a faster
resolution and an easier,
more personalized
customer experience.
I am pretty impressed
with my new AI voice.
Let's talk about
the next step.
And we're going to
go back a slide here.
We are, as you
can imagine,
grounded in using
Service Cloud.
Now, we talked about
it a few minutes ago,
how we've had different
reflection moments when
we look at how
we're implemented,
we had that same in
customer success.
So about three and
a half years ago,
we had to take a
hard stop and all
of the technical debt
we had accumulated
in our implementation
of Service Cloud.
We were at a point
that we weren't
able to take full
advantage of all
the amazing features that
were being delivered.
So what we did is we
completely re-implemented
And what we
were able to do
is emphasize no
customizations,
lean into the amazing
innovation that we are
continually shipping,
and that actually powered
a lot of great successes.
What you're going
to see here is we
saw overall an
82% decrease
We also saw a 61%
faster time to resolve.
But let me spend a little
bit of time on the CSAT.
Before this
implementation,
Now moving up those three
points, as we all know,
And what we heard
from our customers
from this new
experience, you're
You're getting me
the right answers.
They had a better
experience.
And they were able to give
us feedback that really
powered that we
had and gave us
that confirmation-- we
had done the right thing.
Now, it's not always
easy to make a big pivot
like that, but
it was an option
that we are seeing
results from.
I'm a little
trigger-happy,
We've got system
challenges.
Leave it to the end to
have the system moments.
This is another
area that I
want to spend a few
minutes on because we
Many of you in the support
side of the business
will have heard
of swarming.
One of the big challenges
that we had in the past
was, how do you do
swarming with technology?
How do you capture
that great insight
that when you do
a swarm you want
What we've implemented
is a swarming methodology
So within Service
Cloud, let's say,
for example, a
support engineer
is unable to resolve
an issue because it's
In the past, you may
have been transitioned
to a different
support engineer
to answer that
question and you would
But with swarming,
what we're able to do
is right within the case,
that support engineer
clicks a swarming button.
It triggers an
event into Slack,
where the team
supporting that engineer
is able to help them
answer that question.
An important piece
here is swarming.
What you're
getting is you're
capturing the questions
that the team members are
You're capturing
the answers.
Now, all of this, when
the swarm is closed,
is then put back
into the case.
So we bring that right
back into Service Cloud
And now we have a
grounded insight,
as you can say, on the
answers to that question.
The other great
benefit of swarming--
this was kind of
an a-ha for me,
was that we are at every
moment doing enablement.
So when you
think about when
you swarm with that
support engineer,
you're spending time
helping them learn
So great success on that.
We saw faster onboarding
times with this model.
An easy transition there.
Let's talk about
proactive services.
Everything is grounded,
as we've talked
We use the same
Data Cloud instance.
We are all using
the same data.
And what we are
looking at is
how we are measuring
customer success
We've created an
award-winning customer
This is going to help you
as a customer understand
your technical health,
understand your team's
expertise, but
also understand
how you're leveraging
your solutions.
This also is going to feed
the technology in the AI
to help you understand
how to improve
any one of those
categories.
We're going to be
able to provide you
in a proactive
manner insights
to different
things that you
can do to improve your
technical health, what
Let's say, for example,
an instructor-led course
you might want to take, or
a hands-on workshop that
would be of value to you.
We want to present
that to you
and contextualize it
and give you insights
This is all
grounded, again,
using Data Cloud and
on our customer success
Once again, we're going
to re-emphasize this.
It's so important around
your data strategy
and the understanding that
we're using the same data.
When you think about
customer success,
we are similar to
marketing in the sense
that we have to
be very mindful
We are looking at
those insights.
We are wanting
to personalize
and contextualize
our engagements.
When you come into
our health portal
or when you have a
conversation with us,
we need to be
informed on all parts
What were the last cases
that you had submitted?
What were the last
engagements you did?
In order to do
that, to personalize
and contextualize,
we need that grounded
in Data Cloud to
feed and personalize
This is all how we're
leveraging the power
I also want to
emphasize, again,
like we do in customer
success and marketing,
I look at my
communications
I look at, for
example, are they
opening the
communications?
Are they actually taking
the calls to action?
How do we improve
our communications?
All of this is
powered and insightful
for us to be more
successful, and making
sure we reach you
and provide you
the right type
of assistance
to help you with
achieving your outcomes.
And with that, I'm going
to hand it back to Andy.
So I want to share a
few takeaways with you.
I'm calling these
the CIO playbook,
but it's really our
team's playbook.
And number one is
take calculated risks.
And this means for us
thinking about our trust
Each of you need
to understand
your key vendors
and partners
that you're working
with and what
And with Salesforce,
everything
that's touching AI is
going through our trust
And that's looking
for toxicity.
It's looking for
hallucinations.
It's ensuring that your
data stays your data,
and it's not being used to
tune any models, not ours
But this has allowed
us to go fast.
It's allowed us
to say, let's
explore what we can do
with Einstein Conversation
And it's honestly been
a negotiation sometimes
with our own legal
and privacy team where
we had to push
on this and say,
we can do this because of
the Salesforce platform.
So I really want
to encourage
you to explore that
with us or with whatever
Next up, one team and
having a deep partnership
And this shows up in a
bunch of different ways.
We talked a lot
about Data Cloud.
And I'll use that
as an example
where we could have
gone faster, arguably,
if we had a Data
Cloud for sales.
And Scott was able
to stand that up.
And I could work
on that with him
in a Data Cloud
for success
and a Data Cloud
for marketing
because they could have
each stayed in their silos
and gotten done the things
where they're priority.
But instead, we took
a step back and said,
as a team, we need to
have one Data Cloud,
one source of truth where
everything comes together.
And we need to be going
across all of our data
silos, wherever
they may be,
and bringing them into
that so that we will all
So it's one of those
slow-down-to-speed-up
And also make sure
as an IT technologist
that I'm putting my feet
squarely where my business
partners are and
really thinking
about what are the
outcomes that they're
We don't win if we
ship the widget.
A perfect example is the
customer success score.
That's such a
cool technology
and that was a lot of
work from a lot of teams.
But releasing that
doesn't matter
if it doesn't improve
customer success
And those are the
goals as technologists
that we need to hold
ourselves accountable--
the outcomes, not
the technology.
We talked about data and
unlocking trapped data.
But the other
thing is Salesforce
is full of technologists.
When I meet with other
companies and they say,
yeah, my business
partner thinks
they're a technologist,
and I'm like, well,
my business partner
is a technologist.
And so we have a bunch
of amazing, smart people
But one of the things that
we've been working hard on
is focusing on
process first and not
It's really easy
to jump to--
let's use AI to do
this, and let's use
this technology
to do that.
But instead, we need to
take a step back and say,
well, why do we have that
process to begin with?
And Katherine shared about
how we took a step back
and said we're going
to re-implement Service
Cloud three and
a half years ago.
That gave us the
opportunity to say,
we've got a bunch
of processes
And they've also
opened the door to us.
We just had this
conversation two weeks ago
about agents where, why
aren't we using this
out-of-the-box capability?
And they've said,
challenge us
I mean, what a great
business partner that
says, I want to make
things harder for my team
and drive change so that
we can leverage technology
that will scale more
effectively instead
of deploying
custom solutions.
But focus on process
first and not tech.
And last but not
least, effort is nice,
I talked about it before.
I hold my teams
accountable to driving
the outcomes
that we're trying
to do with our
business partners
not deploying
the technology.
It's a pet peeve
of mine when
one of my team members
comes to me and says,
the business decided this.
And I'm just like,
well, who are you?
Are you not part
of this company?
And so like, you
are the business.
And so I would just
really encourage
you all to
think about some
of those
application points.
And what we've done
here is hard work,
And I deeply believe
you can apply it
If you haven't been to the
Salesforce on Salesforce
Campground over
in Moscone North,
I would encourage you
to check that out.
All of our
teams are there.
And you can go much deeper
on all of these areas
that we talked about
today, plus everything
that you saw in the C 360.
You can talk to our teams.
We'll show you
what we're doing.
We'll answer
your questions.
Go over there
and check it out.
Also, you can
take a picture
or scan this QR code
and that will show you
all of the Salesforce
on Salesforce sessions
that we have at
Dreamforce as well as
trails that you can take.
So I'll give it a
second so you at home
can screenshot that
and everyone here can
take a photo if you want.
And then I want to
close with thank you.
We hope you learned
something today.