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Thank you all so much
for joining us today.
If you're here,
you're here
to talk about how
to improve planning
and execution with data.
But before we
do any of that,
just a quick reminder
to please make all
your purchase decisions
based off of what
is currently
available today.
As you're going
to see a lot.
You're going to
see some demos.
You're going to hear
some conversations.
And some of that's
going to be talking
about some
future-facing features
and functionality.
So just keep that in mind.
I also want to
take a brief moment
to say thank you so
much for being here
with us today.
Thank you for joining
us on Salesforce Plus.
Dreamforce is a whirlwind.
Every minute
is spoken for,
and we're really
honored that you chose
to take a few
minutes of that time
to be here with us.
So thank you for
being our customers.
Thank you for
being our partners.
And thank you for
being our employees.
My name is McKee
Hornor, and I'm
a product marketing
manager here
at Salesforce.
Prior to my time
at Salesforce,
I spent a few years in the
consumer goods industry
across multiple
different roles.
And the common thread
through all of that
is data is king.
Data tells your stories.
Data helps you
build your forecast.
Data makes your marketing
and your activities
better.
Data is everything.
Now, in order
to understand
how data gets activated
in a meaningful, impactful
way in the consumer
goods industry
with our wonderful
co-presenters today,
I wanted to first
set the stage of what
is happening in data.
What does it look like
for consumer goods
professionals
specifically?
So I think the way
I like to think
about it is there's
good news and bad news.
The good news is consumer
goods has a ton of data.
Consumer goods, unlike
any other industry,
has more touchpoints
than ever.
So if you think about
all of our consumer
touchpoints, like
first-party data
resources, DTC,
commerce websites,
or even your ad campaigns,
and your retail media
partners.
But also think about our
B2B touchpoints as well.
You have your customers,
your channel partners,
your brokers,
your distributors.
Data is coming
from everywhere.
Now the bad news
is that makes
it really hard to
activate and make use of.
So clearly, a lot
of time and money
is spent trying
to crack that nut,
trying to make use
of all that data.
And that's pretty
evident in the numbers.
Right? $76 billion spent
on consumer research.
In my previous
life, I worked
in brand management,
and I know how hard
it is to understand
exactly what your consumer
at your retailer, at
the point of sale,
is thinking, wanting
and looking for.
And that money
is spent trying
to find that consistently
moving target.
Not only that, but
you're also spending
so much money trying to
promote your products.
So even if you have that
perfect product that
solves that
perfect problem,
you want to make sure
it's at the right price,
and the right place, and
with the right amount
of stock.
So trade promotion
management
continues to be one of the
top spending opportunities
for our customers,
number two on the P&L,
with $500 billion
spent annually.
And lastly,
salespeople's time
is still spent trying to
interpret, to manipulate,
to pull that data
together, to make
their jobs easier, make
their sales pitches
more impactful.
Now, all of this
time and this money
isn't spent for no reason.
There's a lot at stake
in consumer goods.
And that happens on
both the consumer
and the customer side.
So on the consumer
side, if you've
been going to any
of our CG sessions
today or yesterday you
know that consumers
are trading down.
They're more
willing to trade
to a lower priced good
or a different brand.
And so the
figure here to me
stands out, one
in three consumers
willing to trade
for a different
or for a bad experience.
That number has
gotten a lot higher.
So it used to
be one in four.
And I think that's
really evident because
of just the
price constraints
on everyday shopping,
smaller basket sizes,
and the consumer
is trying to be
more conscious about
their spending.
Now, customers are
not much different.
They also are
experiencing some
of the supply
chain issues,
the remnants of COVID.
And because of
that, they're
experiencing about
12% of out-of-stocks.
So just like consumers
are willing to trade down
or switch out brands,
so to our customers,
if they feel
that you're not
filling their shelves as
quickly and effectively.
Now, that sounds like a
lot of doom and gloom.
But the good
news is there's
a couple of solutions that
we at Salesforce have been
focused on delivering for
the past few years, things
connected data, real-time
personalization,
intelligent planning and
execution, which we will
get into in just a moment,
and automated processes.
So the answer
to us is clear.
Data transformation
is happening quickly
and you got to move
from the historical way
of doing things into
today's opportunity.
No longer can we work
with siloed data,
disconnected systems, or
just humans at the helm.
72% of customers still
sit in that world.
But those who are
trailblazers, those
who are here to
partner with us,
are able to achieve
today's opportunity, which
is unified B2B
and B2C data,
real-time actionable
opportunities in the flow
of work, and humans and
agents working together
to tackle this challenge.
So of course you're
asking yourself,
what is the solution?
How do I do that?
Data Cloud for
Consumer Goods
is our designed,
created product
to help you tackle
those challenges.
And you heard about it
in the keynote yesterday.
But I wanted to
highlight specifically
what that looks like for
planning and execution
here.
So on the
planning side, you
are going to be able to
build better customer
business plans, make more
profitable trade programs,
and more customized
store assortments.
Now, all of
these have been
focuses for people in
the planning practice
within consumer goods
for quite some time.
But they're considered
gold star opportunities,
something that you
hope to achieve
but maybe can't
do at scale.
Now, it's possible
with Data Cloud
for Consumer Goods.
On the execution
side of the house,
you are going
to want to be
better at your delivery,
faster, more efficient.
You want to make sure that
every selling opportunity
is guided by AI
when possible,
and you want to make
sure that you are giving
a single source of
truth for your stores,
creating a clear picture
of which stores do great,
which stores
need more help.
So this is planning
and execution,
intelligent
and integrated,
using Data Cloud
for Consumer Goods.
But I think it's always
most impactful to hear
the how by getting
into the product
and hearing from
customers, which you'll
see here in just a moment.
So to handle the planning
side of the house,
it's my pleasure to
welcome up Adria Cordova.
Hey, everyone.
I'm Adria Cordova,
a solution engineer
at Salesforce.
Now, it's no
surprise to any of us
here I'm sure that data is
important in the consumer
goods industry, especially
when it comes to planning
and execution.
I'm going to walk
you through a demo
of our Trade
Promotion Management
and optimization
solution to show you
how the power
of data and AI
can streamline the
planning process.
But before we get
started, let's
give a quick shout
out to Lu, who
will be driving our demo.
Almost there.
Almost there,
wouldn't be technology
if things don't
load correctly.
There we go.
At Alpine Nutrition,
cross-functional teams
leveraged Consumer
Goods Cloud to optimize
their sales operations.
Now, as the revenue
growth manager,
it's my job to determine
the optimal price,
promotion, and assortment
strategy at Alpine,
and I rely on
analytics to do so.
In the distribution
analysis,
I can understand
and get a read
of what's truly driving
revenue into the business.
I also have the ability to
analyze price elasticity
curves, which are
critical in determining
the price of our product,
both on and off promotion.
And in our Uplift and
Spend Analysis dashboard,
I have the ability to see
which tactics and consumer
offers are driving
incremental dollars
into each category.
And what's more
important is
that I can understand
which promotions are not
driving ROI, so that we
don't repeat them again.
But how does
this translate
into the key account
manager role?
Let's take a look.
Now as the KAM, I
focus on activities
that are going to drive
the business forward.
On my home page
here, I have
AI-generated analytics
that I can interact with
to get a deeper
understanding of how
my business is performing.
With the ability to drill
into specific metrics
like volume, I can
see a breakdown
of how the data
is trending,
but more
importantly even ask
questions to
understand the why
behind the performance.
So for example, I want
to ask and understand
which account has
increased or decreased
the most over the
course of the last year.
That way I can put a focus
on it in my planning.
And speaking
of planning, I
see an alert in
our sales bulletin
reminding me to submit
my annual forecast
for next year.
So let's take a look.
Now, I use my
customer business plan
to manage my baseline
volume forecast.
And thankfully, Einstein
predictive modeling
has provided me with
a strong foundation
to build off of,
now factoring
in historical data,
seasonality, as well
as product clustering.
But to take it a
step even further,
Einstein has removed
the baseline sales data
from the total
historical volume
to give me a true read
on the effectiveness
of my promotions.
Now with my
forecast submitted,
I can now take a look
at my Trade Calendar
to preview my annual
promotional plan.
Now, as a KAM, this used
to be my most dreaded
time of year, but
now it's actually
become one of my favorites
because of the time
savings I've gained with
intelligent data and AI.
Thankfully, I do
have the ability
to copy over my entire
promotional plan
into next year.
But before I do so, I want
to take a look at my P&L
just to make sure I'm
making the right decision.
In my P&L, I can see
a monthly breakdown
of my total spend,
net revenue,
gross profit of my
promotional strategy.
But to get a better
look at the data
that I need to
build my plan,
I'm going to switch to
the monitoring view.
And looking at the
latest estimates
of my actualized
volume, it
looks like there
are some areas that
need improvement, so I
decide not to copy over
my entire plan.
But instead of analyzing
each individual plan
and selecting which one to
copy over into next year,
I'm going to ask my AI
agent to help me out.
So in this case, I'm
going to ask my agent
to provide me
with a list of all
of the top
promotions that we
ran at NTO last
year that generated
an ROI above 30%.
And in just a
few seconds, it
generated a list for me
of my top promotions.
So with my top
promotions, now I
can leverage the mass copy
functionality and copy
them over into next year.
And just like that,
thanks to my assistant,
I was able to get
ahead of my plan
and confidently be
ready to hit my sales
goals for next year.
But let's take a look
at how this field sales
team is doing.
And I can do that by
referencing our promotion
and competitor
analysis insights.
I can see metrics like
store participation, store
compliance, as well as
competitive insights.
And because we're on
the same platform,
the field data
gets fed directly
into my dashboard,
allowing
me to build stronger,
more effective promotions,
and set
competitive prices.
Now, with my current
and future promotions
already set in
the system, I
can actually get a preview
of how my promotions are
currently tracking using
our trade effectiveness
dashboard.
Now I can see
metrics like ROI,
compare plan versus
actual results,
and even see which tactics
are performing the best.
So we just saw an
integrated planning
platform that leverages
data and AI to streamline
the planning
process, as well
as allow us to build more
effective promotions.
Now, we saw how our
Einstein AI allowed
me to take the
manual effort out
of my flow of work.
We also saw how our trade
promotion optimization
allowed me to
optimize promotions
to then allow me to build
more effective promotions,
leveraging our analytic
insights in our trade
effectiveness dashboard.
And now that we've covered
the planning process,
I want to introduce our
friends at RNDC, Bosman
and Marissa, to talk about
their retail execution
perspective.
[APPLAUSE]
Thank you, ladies.
Can you guys hear me OK?
It's always mics, great.
Good afternoon.
Thank you so much for
taking the time out
of your busy schedule.
My name is Marisa Garrett.
I lead our
sales operations
for Republic National
Distributing Company,
so a liquor distribution
for on and off premise
retail.
So go to the next slide.
So just a little bit
of history about RNDC,
we have built our
foundation on trust
and the Block family
goes all the way back
to the 1890s, and really
started kind of the liquor
industry and the
foundation there.
And over the years, we
have had multiple mergers
and acquisitions growing
into RNDC in 2007.
With that, we now cover
40 markets plus DC,
and so we are across
the whole entire US.
You want to jump
to the next slide.
And we really are built
on a foundation of trust
and our core values.
So while our history is
there and the foundation
of all of our family
legacies, everything we do
is based on our core
values of accountability.
Our family and service
and our customer service
is always at the
forefront of what
we do day in and day out.
And I bring up
our core values
because as we talk about
data planning, execution,
the trust that we put into
not only our sales reps,
but also our supplier
and customers,
it's making sure that
we're providing everything
to them at their
fingertips through data.
So who is our RNDC?
RNDC is really an
expert at our craft.
If we were a publicly
traded company,
we would rank 398th
in the top 500.
We do about $12 billion
worth of revenue.
We have 13,000 associates
that deliver an impressive
480,000 cases
every single day.
And we're the 25th largest
US privately held company.
We've seen a tremendous
growth over the last 13
years, 91% in revenue
from 2015 to 2023.
And with that,
it's all great.
But if we don't actually
use the data effectively
to drive our sales
reps in the market,
we're in an
ever-changing industry.
And we've seen a
lot of adjustments
that we've had to
make for our sales
teams to make sure
that we're giving them
all of that data
at their fingertips
to make the right
decision and share
the right products
at the right time
to the right customers.
So I'm going
to turn it over
to Bosman, our
director of CRM,
to walk you a
little bit more
through our journey
with Salesforce,
and how we've
partnered with them.
Awesome.
Thank you, Marissa.
So what are
our challenges?
So for MVP of our
Consumer Goods Cloud
implementation,
we really focused
on solving for chain
compliance management.
And this is truly dealing
with complexity at scale.
And there's a
variety of factors
that drive the
complexity that we
have to work through.
The most important
one is the fact
that the suppliers
we represent
can be very different from
one market or one state
to the next.
We can also
within a state,
there might be differences
in our product portfolio
from one warehouse
to the next,
and sometimes there's
even product exclusions
within counties.
So for chain compliance,
when we receive a program
from a chain corporate,
we have to then break that
down all the way down
to the store level
to say which
products do we
need to go check for
compliance in the store.
So as you all
can imagine, that
imposes a lot
of complexity.
To put a number
against that,
we at any point in
time manage around
1.5 million compliance
goals across the country.
And in terms of
our product set,
so we have around
250,000 SKUs.
But the minute you
apply the complexity
of the product
by the warehouse,
that immediately
multiplies and makes
it way more complex.
So up to this point,
it's been incredibly
labor intensive.
It's time consuming.
It's a very
expensive exercise
to run all of this if you
don't have a good system
to support this.
So we're very excited.
We're at the point of
our MVPs going out,
and we're solving for
this in a pretty big way.
So why did we choose
Salesforce Consumer Goods
Cloud?
So I'm going to touch
on a few things here.
And I'll talk a little bit
more about the data aspect
as well.
So first of all,
the data schema fit,
I think a lot of you
will agree with me,
this is arguably the
most important thing
that you need
to consider when
you make a platform
or a solution choice.
If the data schema
is a good fit
for the complexity
of your business,
then everything else
becomes so much easier.
Whether you're
building automation,
you're adding
on use cases,
if the data schema fits
around your organization,
it makes it very easy.
And we've been able
to predominantly use
the standard objects that
come with Consumer Goods
Cloud to wrap around our
complex chain business.
The second one, so this
is stating the obvious
because we're
at Dreamforce,
but faster value
realization.
I mean, if you build on
the force.com platform,
everything's quicker.
It's lightning quick
to get user experience
and apps out there.
It is automation,
complex automation
is fully configurable.
And now the added
benefit, since as
of a few years
ago is really
how Data Cloud came
to life, even making
data from
different sources
accessible within the
Salesforce ecosystem.
So all of these
factors makes
it possible to do pretty
extensive solutioning
in a short period of time,
and immediately starting
to get value back.
The next point is I almost
want to say just a bit
of a side note.
So there are some really
nice included features
that we of course get with
a Consumer Goods Cloud
subscription.
Basic example, one of my
favorite Salesforce tools
is Salesforce Inbox,
very quick and easy
to implement.
Our associate
does not even
need to do anything
differently.
And all of our
emails become visible
in the context of
Salesforce records.
There's insights
tied to those emails,
So just a great
additional benefit
to have with how
the licensing has
been packaged together.
And then greater
future potential,
so of course, because we
are using CG Cloud out
of the box as
much as we can,
we are very
tightly aligned
to Salesforce's
evolution of the platform
and we will
benefit from that.
And of course after
our implementation,
we have the
foundations in place
to now start the
road mapping.
When do we add on CPF,
TPN, and so forth?
OK.
Then I want to talk about
our implementation just
at a very high level, just
like a 30,000-foot view
of a few components about
our implementation that
really starts leaning into
how we're going to bring
data into play with
what we're doing.
So the first one, so
the enhanced data model
that we're
using, I'm going
to give a very
specific example.
So if I take the
complexity of our products
with we have this many
corporate products,
but then they
need to be related
to the specific markets.
So we've modeled
all of that
using standard
objects in CG Cloud.
And we use the
relationship
between those
objects to solve
for the complexity and
the automation of saying,
here's a program goal and
we can cascade it down
across all these
business rules by state,
by county, down to the
customer account level.
So when the rep walks
into the account,
they know exactly what
the compliance goals
are for that account.
So the CG Cloud
data schemas really
supported us with that.
Then Data Cloud, so we
subscribe to Data Cloud.
And Data Cloud
is going to help
us solve for things in a
pretty significant way.
Because ultimately
what we can achieve
with Data Cloud is it
can underpin our CRM
ecosystem.
And I'm talking
about ecosystem
because we have three
Salesforce orgs.
One of them is more geared
towards field sales.
One is more inside
sales and customer care,
and then of course, our
brand new CG Cloud org.
So, yes, would it be
a healthy decision
to say we want
to gradually move
to one single org?
Could be.
But at this
point in time, it
serves us really well
to have the three
different orgs with
very different use
because, we can
accelerate the development
of those orgs to be a
great fit for those use
cases while being able
to still exchange or make
data visible, usable,
using Data Cloud from one
org to the next.
So a good example
for that is
when I refer to the
compliance goals
that we generate in
the new CG Cloud org,
we can now make
those goals
visible at the account
level for the field sales
rep that's in the
field sales, Salesforce
org, or the inside
sales rep that's
in the inside sales org.
We can make it visible.
We can trigger action
to say for a week
from the end of
the program period,
we basically trigger a
task or something just
to give them a
nudge to say, hey,
here's a compliance goal
that's still outstanding.
So that's where
Data Cloud really
unlocks that for us.
Plus, of course,
we have the option
to bring data from
a variety of sources
into this ecosystem
that we want to use.
We can zero copy
from Snowflake
to bring sales
data in, so we
can start looking
at how does
our sales data compare
to our compliance metrics
by chain, by supplier.
And we've just opened
up and unlocked
a ton of value for
the organization.
And then finally, we use
MuleSoft Anypoint just as
the middleware to help
us manage the deltas
in our base tables
between Snowflake
and our Salesforce
ecosystem.
So it's a very kind of
baseline integration tool
that we use.
Of course, with a few
different Salesforce orgs,
it's really easy because
you build the mapping once
and then we kind
of replicate that
same mapping for
the other orgs.
And we have a very
simple, very quick
to implement way to
manage just our basic data
updates of our base
tables in Salesforce.
And then Data
Cloud really does
that horizontal
aspect for us
to say what data do we
need to see, where do we
need to take
action on there,
and that's how we
use Data Clouds.
So thank you for all of
Salesforce's support.
It is the type
of effort where
you need the
Salesforce team really
to enable you and help set
us down the right path.
Our consulting partner
has been phenomenal,
recommended to
us by Salesforce.
So it's been a
really good journey.
We're very excited
to be at this point
and to start seeing
the value coming back.
So at this point, I want
to invite McKee back
onto the stage and
he's apparently
prepared some tough
questions for us.
Thanks, Bosman.
Yeah, sorry, I just have
to rejoin the conversation
here because I do have
a couple of follow-up
questions for you both.
So why don't we just take
a seat, and chit-chat
for just a
little bit more?
So I'm curious.
I mean, this has been
a great opportunity
to see where you're at
in your orientation, what
you're focused
on right now.
Can we maybe zoom out
for just a quick moment
and orient the audience
on how you were operating
prior to Salesforce?
Yes.
So it might be a little
bit painful to hear,
but it's the truth.
So for our on-premise
business, so typically
our restaurant
chains, they
had a homegrown
system where you
can input the program.
But then we use
purely a BI tool
to show where we might
have compliance gaps.
And our sales reps don't
all even have access
to that specific aspect.
So what we found
was there was a lot
of manually pushing out
information of where
compliance gaps are.
And then of
course, the reps
will try and take
action on that
to help us close the gap.
But there was no
record of compliance.
So if we think about
it, if a BI tool just
helps us show
the gaps, there's
no record of the gaps.
And that's one of the big
things we're solving for,
for on premise.
Retail, that's where
the pain really is,
is we literally take
the chain program
as we receive it
from the chain.
We swivel chair
to the state,
and we tell the state,
here's the program.
They can look at that
and they know which
products do we sell.
They then have a manual
way of gathering feedback.
Some of it goes
into a CRM system.
Some of it is manual
depending on the chain.
And then we have
analysts that
get their arms around
everything that
comes back, and then
really break it out
to say provide for this
supplier, for this chain,
here's our level
of compliance.
So retail right
now is 100% manual.
So this is a pretty vast
improvement for them.
That's awesome.
I mean, to me,
I feel like I
hear buzzwords
like automation
and data all
day, every day.
But I think put it in the
context of these people's
everyday workflows, it's
huge gains for them.
You're not having
this whole chain.
You can actually spend
time doing your job, which
is so exciting.
Now, maybe to deconstruct
data from a buzzword
into something more
valuable, something
we can all relate
to, I'm curious.
We've talked a lot
about B2B data today.
It makes sense.
That's the name
of the game
when it comes to
planning and execution.
But I'm curious if you
see any value of B2C data,
consumer data,
flowing into this side
of execution as well?
Yeah, so McKee, I
think great question.
As we work with
our sales reps,
historically you heard our
sales reps receive stuff
from a million different
Excel files, all
the different data,
whether it's Nielsen, IRA,
there's all of
these components.
And so the importance
is how do we
pull that together for
our sales teams in a very
consolidated view,
so that they're not
having to go find all
of their accounts.
When they have a
universe of 100,
it becomes really hard.
So I think the value
of data and putting it
at the forefront
is a game changer,
and we cannot move
forward without it.
Because it's an
ever-evolving landscape
that we're having
to navigate through.
Completely.
I mean, giving your
execution partners
and your professionals
view into your consumers
is also super important
because they're in a way
responsible for the
customer experience
as much as anybody else.
Yeah.
So data is the
name of the game.
We talked a lot about
B2B and now B2C data.
And prior to our
conversation just now,
we heard from our
SEs about the role
of planning data.
So a lot of data is
flowing on that side
of the house as well.
How do you see, if
at all, any data
connecting from planning
through execution?
Yeah, so I think
there's a lot
of different
connection points.
From an RNDC perspective,
we have 11 ERPs,
so data connection
is really
how do we pull that all
together so that they
can go and execute.
Because every customer
that we have is different.
And so when we talk
about our consumers,
our consumers are
really our customers.
And we're representing
also our supplier partners
as a distribution house.
And so it's how we're
actually putting that data
in front of them as well.
So I think it's a lot.
So I think the
data connection
for us is really
pulling it
all so that we can
really give them
the right recommendations.
It is interesting for us
looking at this problem
we need to solve.
There's all these
different pieces
of information
that sales need
is every single time
it goes back to how
Data Cloud can
help us bring that
into a single layer
that we can pull
from relevant to the rep.
So that is
definitely going
to be a game changer
for us around what's
all the different sources
we need for planning.
Yeah.
Sounds like a lot of data
availability and clarity,
right?
Which is super crucial, I
think, to anybody's job,
but especially
to the folks
making RNDC
work every day.
So I'm curious.
You've done a lot.
We said you did a Data
Cloud, a Consumer Goods
Cloud, and a MuleSoft
implementation.
Any learnings from
that experience?
Any advice for
somebody maybe
who's just starting
on one or all three
of those things?
Yeah, I think our most
important learning was,
and I'm first going
to mention a positive
because it feels like it's
something we absolutely
got right.
Is getting everything
modeled the right way,
the way in which you
take CG Cloud, wrap it
around your
business, doing
that the right
way so you're
teed up for enabling
further feature sets.
Like for instance,
in our case,
we want to get to CPF,
we want to get to TPA.
And we're already
making sure
like, yes, that
foundation is in place.
It's now simply
a case of working
with our
implementation partner
to start enabling that.
So that initial modeling
and really understanding
of where you're
trying to go,
really important,
and again,
that's the part I feel
we got that right.
Then the part where we
did have a slight hiccup,
it wasn't an
expensive hiccup,
it was more a learning is
really understanding what
tool do you use
for what purpose,
like getting our data
integration figured out
to say, right, what is
the best methodology
to get our data
into the orgs,
to manage it in the orgs?
What is the ideal use
cases for Data Cloud?
How should we
think about that?
So we took kind
of a few weeks
just to get our
positioning right
around the tools.
And now that we
have that in place,
everything then since then
has been seamless, easy,
and we're on a really
good path where now we're
going to start enabling
using the tools.
But that was the
one learning,
is what tool do
you use in which
use case when it comes
to integration tool.
Like MuleSoft
and Data Cloud
is really that
connection layer,
but yeah, we're in
a good place now.
So.
Gotcha.
Starting off on the
right foot, very wise.
So I'm thinking,
looking forward,
I'd love to end on
maybe a high note.
What you're looking
forward to at RNDC.
I'm curious, what's
next for you all?
What are you thinking
about for next technology,
innovation, or investment?
So I think I'm
going to start
a little bit
narrower, just
with what we're doing
with Consumer Goods Cloud
and our chain organization
is, of course, when
we talk about
chain compliance
management, that's
what's coming out
of a lot of business
development activities.
So upstream
from that, we're
working with the
chains, we're
working with suppliers,
and really trying
to get our products
into contracts
so we can program
them out and go
kind of measure compliance
against the contract.
So getting our
chain organization,
really their
end-to-end process
into the Salesforce
ecosystem,
and bringing
visibility to that,
so we can start applying
some science to that--
I think that's really
exciting for me
for how we're going to
really broaden the scope
and then also making
the connection
between our chain
team and the field.
So for field
sales reps, they
have a very direct view
into chain programming,
chain goals, how
we're tracking
towards those, and right
in their hands in the tool
that they use every day.
I think that's something
I'm very excited about.
I know beyond that, we
are looking at CPF, TPA,
and we're going to enable
a lot more with CG Cloud.
But I think those
immediate next steps,
I think is just a
massive gain for us.
And I think it
ultimately comes down
to the adoption.
So when we say
like, hey, what
is the next technology,
if we don't have
the foundation
of what we're
doing with CG Cloud
ready for our teams,
we will struggle with
anything moving forward.
So that is for
us, something
I'm very excited about is
getting everybody on board
with what we're doing with
CG Cloud and the adoption
and development there.
Totally.
I mean adoption
and branching
into new channel
partners, both of which
are very important
priorities for you both.
Now, I know we have a
little bit of extra time,
so I'm just curious.
I'm going to
pick your mind.
I'm sure you've been
asked 1,000 times already.
AI, how do you
see this playing
a role in your
organization,
in your route to market,
even at a high level
thinking, aspirationally
about what it could
mean for your business?
So I think there's to my
mind, the two aspects that
speaks to us the most that
I see immediate value,
the one is being able
to very quickly get
to business insights.
So AI that can typically
surface analytics,
I can ask a question
and using CRMA,
it can basically
serve up, here's
a little graph
with the answer.
I think our
reporting right now
is very much centralized.
It's almost like a
very specialized thing
within the organization.
But unlocking that for
every single sales leader,
I think that will
be a game changer.
And that's where AI can
play for someone not
having the
analytical skills
or even the time to really
dive into the numbers,
just ask a question,
you get an answer.
So that's the one aspect.
And then the other
aspect is generative AI
and being able to, from
a summary perspective,
being able to very
quickly build summaries
of sales efforts.
So that's
typically something
that's always a
strong philosophy
for us is we don't want
sales reps to have all
of these manual
actions and then
you kind of input your
notes with everything
in there.
And then you take the next
step in the sales call
and it's all manual.
We want to find ways
that if I get information
into the system, whether
I use quick voice
or text after a call, or
maybe it's a virtual call
and I invite
the agent that
can do the summary
for me, that's
ways in which we can
start accelerating
our understanding of the
unstructured data that
comes with our call recaps
and things like that.
Yeah, I think for
us too, McKee, it's
that we have the
data out there
and it's about how do
we pull it forward,
so that they can ask
a simple question.
They're on the go, right?
Especially for
our sales reps,
they're out in the field
day in and day out,
and they're
walking into all
the different accounts.
So for me, it's
the simplicity
of actually just asking
a basic question.
We jokingly said
today, if our CEO could
go in and just type, hey,
why is supplier x down,
and what are the top 10
brands which it sounds
very simple, but
it's something
that I'm looking forward
to with the AI journey.
Yeah, I mean a huge
value unlock, 100%.
And I feel like
hopefully what
you got from
today's session
is that just like in
the planning session,
we saw how you can
talk to your data
and actually use
AI to make it more
of a conversational
experience,
just like your
ideal for the CEO.
So it's not so
hard to reach.
It makes the data more
approachable, more
tangible for everybody.
Yeah.
Well, I want to
take a moment just
to say thank you so much
for joining us today.
We really appreciate your
perspective lending today.
I just want to ask
everybody else also
to join me in giving me
a quick round of applause
for our friends at RNDC.
[APPLAUSE]
Thank you for having us.
Of course.
Thanks, McKee.
Thanks, everyone.
And the good news is the
fun doesn't stop there.
We have additional
sessions here
at Dreamforce
today and tomorrow.
And we also have our
Consumer Goods Cloud Guide
giving you a little
bit more detail
on how to achieve some
of the greatness you
saw in the demo and
in the RNDC story.
And if you have
any questions,
feel free to
come up and talk
to us after the session.
But thank you so much
for joining us again,
and have a good rest
of your Dreamforce.
Thanks.
[MUSIC PLAYING]
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Consumer Goods: Improve Planning and Execution with Data
Intelligent, integrated planning and execution are critical to success. Hear about innovations improving the route to market and how incorporating new data sources makes this even more powerful.
Starring
- Mason GoodmonPrincipal Solution Engineer, Salesforce
- Bosman du PlessisDirector, CRM, Republic National Distributing Company
- Devin KunyszSenior Director, Industry Advisor, Salesforce
- Jack GrennanPrincipal SE, Salesforce
- Marissa GarrettSVP, Sales Operations, Republic National Distributing Company
- Lu BaiPrincipal Solution Engineer, Salesforce
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