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Welcome to Release
Readiness Live
from San Francisco.
I'm Gillian Bruce,
Principal Admin
Evangelist in
Salesforce super nerd,
which means I
am so honored
to bring you Release
Readiness Live 'cause
this is where
we get nerdy.
This is where we
cover the new product
innovations coming your
way in the next release.
But before we get into
my happy nerd zone,
I need to make sure that
you only make purchasing
decisions based
on currently
available features
and functionality.
Now, with that
covered, I want
to thank you so much
for joining us today.
Thank you for investing
your time with us
to learn about what's
coming in Winter 24.
And thank you for all the
feedback you provide us.
Your feedback is what
help builds our technology
and helps our teams
build solutions centered
around your experience.
We've got a great lineup
of release-readiness
content for you.
We kicked off admin
and developer Release
Readiness Live
at Dreamforce
just a few weeks ago.
And yesterday, we covered
CRM analytics and sales.
Today, we're going
to get into service,
and later today,
we have flow.
Now, we're going to
spend the next hour here
together with our
product managers
in person in the studio,
who are going to give us
live demos highlighting
the top service features
in the Winter 24 release.
We're going to be covering
knowledge, Einstein
for Service,
Email-to-Case,
Omni Contact Center
Modality, Apple Message
for Business,
Service Intelligence,
and a lot more.
But it's not just about
us here in the studio,
it's about you.
We want to answer
your questions
about these new features.
And we've got a special
correspondent here
in the studio to ask
your questions live.
Well, Wassim,
how can people
ask their questions?
Thanks, Gillian, and what
is up, service stars?
I'm Wassim from the
Salesforce social media
team.
And today, I'm
here to help
you get all your burning
questions answered
about the new features
in our Winter 24 release
so that you can learn
how to use them.
So what do you want to
ask our product experts
today?
You have three ways that
you can submit a question
and get an answer live
right here right now.
You can, one, head over
to the Release Readiness
trailblazers community and
ask your question using
the #SalesforceRRL
or, two,
drop your questions
right here in Salesforce+
in our new Q&A
tab, or three,
join the
conversation on X,
formerly known as Twitter
and pose your question
using #SalesforceRRL.
We'll be pulling questions
from all three sources.
And please,
don't hold back.
Don't be shy.
Chances are, if you have a
question about something,
somebody else does, too.
And also, if you
have any memes, GIFs,
or funny screenshots of
a silly moments or fun,
exciting innovations
that you've seen today,
well, I want to
see those too
because we want
to hear what's
on top of your mind.
All right.
I'm looking forward to
seeing your questions
service stars.
Over to you, Gillian.
Thank you so much, Wassim.
Now, we're going
to kick things off
with Director of
Product Management Leon
Kempers, who's
going to talk
to us about knowledge
and Einstein for Service.
Take it away, Leon.
Thank you, Gillian,
and hello to all of you
admins at home.
My name is Leon.
I'm a product manager
here at Service Cloud,
and I'm going to start by
making a bold statement.
I think the
Winter 24 release
is one of the best
releases for knowledge
in the product's
15-year history.
We are closing over
25,000 ID exchange points
with the GA release of the
Lightning Article Editor
and Article
Personalization.
The Lightning
Article Editor
has been rebuilt
from the ground up,
offering you some of the
features you have been
asking us for the most,
like a full-screen mode,
advanced table editing,
and seamless copy
and pasting from
external sources.
The Winter 24 release
also sees the introduction
of accordions, a feature
you have been asking us
for a long time that
allows you to create
collapsible sections
within fields
of your knowledge
article, making it really
easy to increase
the readability
of long knowledge
articles.
And finally, there's
my personal favorite,
the Accessibility
Checker, which
allows you to
automatically flag
ADA and WCAG violations
within the editor itself
and then fix them with
a few easy clicks.
Especially for
all of you that
are trying to
make knowledge
content on self-service
portals accessible,
this is going to be
a real game changer,
and it highlights
our commitment
to accessibility.
Then, Article
Personalization
allows you to
customize which part
of your article
you want to show
to which audiences.
I spoke to a customer at
Dreamforce two weeks ago
that's using this
feature to have a GDPR
regulations field
that they only
want to show to their
European service agents.
And right before
that, I spoke
to a customer that
has a specific service
escalation procedure
field on their knowledge
article that
they only want
to show to their
three-- tier 3 agents.
With Article
Personalization,
the sky really
is the limit,
and we cannot wait to
see what you do with this
feature.
And then, finally, we are
bringing Data Categories
to experience
Cloud's LWR runtime.
Currently, on
the LWR runtime,
you have to use topics to
categorize your knowledge
content.
And you have told us
in sessions like these
that it can be quite
cumbersome to have
to maintain two
hierarchies.
So now that we
are completely
rebuilding the
self-service experience
from the ground
up for LWR,
we decided to bring data
categories to Experience
Cloud, meaning you
can choose which
parts of your
category hierarchy
you want to expose
to your site users,
and then you can use
those data categories
to classify both
your knowledge
articles and your
service catalog items.
The Winter 24 release
also sees the introduction
of our first
generative AI products
for Service Cloud.
And there are
two GA products
that I want to
highlight right now.
The first is
Work Summaries,
which automatically
creates
a summary of a case
once it's closed,
no matter on which channel
that case occurred.
It analyzes the
content of the case
and the entire
messaging interaction.
And then, Einstein's
generative AI
will not just
summarize the case
but also capture the issue
the customer reached out
about and the resolution
that the service
agent identified, meaning
that if an agent comes
back to that
case later, they
can see at a glance
what the issue was
and what the
resolution was
that the agent proposed
so they don't have
to dig into the whole
interactions of the case
boosting their
productivity
and allowing them to focus
on the complex cases that
really matter.
Then our Service Replies
product for Conversations
allows you to create
knowledge-grounded
service replies on all of
your chat and messaging
channels.
Because those servers'
replies are grounded
in knowledge, we add that
layer of trust, helping
you ensure that the
replies generated
are truthful,
accurate, and specific
to your organization.
And because the service
replies are completely
tailored to the
messaging interaction,
this feature allows
you to deliver
that personalized
service to your customers
have come to
expect in 2023.
So I think it's
a great time
to actually take a look
at a demo of that product.
So I'm going to
switch my screen here,
and we're going to take
a look at this chat
conversation that
just came in.
A customer is reaching
out because they
have an issue with their
field service product.
Since they haven't
given a lot of context
about the exact nature
of the problem yet,
serves replies will
suggest a reply
based on the
conversation context that
asks the customer to
provide more details.
As an agent, I can edit
the suggested reply
or post it directly
into the chat window.
The customer
responds, letting
me know more details
about their issue.
Now, we have
enough information
to ground service replies
in my organization's
knowledge base.
Einstein will use
the information
within the conversation to
find the right knowledge
articles and dynamically
generate a reply that's
both grounded in
knowledge and tailored
to the customer's issue.
I post the
knowledge required
to reply to the chat,
and hooray, the customer
lets me know that their
issue is now resolved.
Einstein will provide a
contextual service reply
again, and I'm able to
wrap up the conversation.
I can use our new gen
AI-powered work summaries
product to automatically
summarize the case
and capture the issue
and resolution that
were identified.
This shows how Einstein's
generative AI for service
drastically improves
your agent productivity.
Find the right
information,
writing responses
based on that,
and eventually
summarizing the case what
have normally been a
time-consuming process.
But Einstein made it as
easy as just a few clicks
while still keeping
a human in the loop.
That is what the future
of service looks like.
And then, before
I go, I want
to highlight that
this was really
just the tip of the
Winter 24 iceberg
because there
is so much more.
I would encourage
you to take
a look at our
release notes
to learn about
everything, but a couple
of my favorites that
I want to highlight.
First of all,
Einastein Management
now has proactive
notifications
that allow you to create
custom proactive Einstein
broadcast messages
to customers so you
can reach them before
they log a case.
In any size
organization, incidents
are bound to
happen, but it's
how you deal with
those incidents that's
going to impact how your
customers look at you.
Also, we have a thing to
celebrate because service
catalog is now
generally available,
meaning that you can
now use service catalog
in experienced
Cloud's LWR runtime
and use one integrated
user interface to build,
manage, and expose all
of your service catalog
processes.
And finally, I
just want to make
sure we haven't
forgotten about you Slack
for service users because
you can now share files
directly from the
Slack conversations
component in the
lightning experience,
and you can have mention
other users directly
within Lightning
experience
and also see their
status to know
if they're available.
This is going to
reduce swivel sharing
between both systems and
help your service agents
be more productive.
That was it for me.
Back to you, Gillian.
Thank you so much, Leon.
That was a lot.
There is so much coming in
knowledge with Winter 24.
I bet the chat has
a lot going on, too.
Wassim, let's
check in with you.
What's going
on in the Q&A?
All right.
There's a lot going on in
the chat and in the Q&A.
We have service stars
from all over the world,
from Ireland, Rhode
Island, Dallas, Cologne,
and beyond, who are
sharing their excitement
for Leon's demo.
Kim says, yay, for
data categories.
And I share that
excitement with you.
Now be sure to please use
the Q&A tab right here
on Salesforce+ to submit
your questions so you can
get it answered by
our product experts.
Now, one question Leon
that I'm seeing pop up
is how can I enable the
new Lightning Article
Editor and Article
Personalization?
That's a really
good question.
So we have a specific
release updates part
in the setup
where we show you
at a glance what new
parts of the release you
can enable for
your organization.
And you'll find the
Lightning Article Editor
and Article
Personalization
right in there.
So it's just a few clicks.
Go to Setup.
Go to Release Updates,
and then hit that button,
and you'll be all set
with the Lightning Article
Editor.
OK.
I can actually see people
doing that right now.
So another
question for you.
I already have a
full knowledge base,
can I add accordions to
my existing articles?
Absolutely.
I think we wanted to make
sure that customers can
apply these accordions to
their existing knowledge
articles as well.
So if you go to the
Winter 24 release,
you'll find that
new accordion button
right there
within the editor,
and you can just hit
it for your existing
knowledge
articles and then
break down your knowledge
articles within accordion
sections.
OK.
That sounds pretty easy.
Like that-- OK.
One more for you before I
let you off the hot seat
momentarily.
What is the benefit of
grounding service replies
in knowledge?
I mean, that demo
that you showed
was pretty powerful.
Yeah.
So I've spoken to a
lot of our customers
about generative AI
over this past year,
and I think
what I generally
hear are two concerns.
One revolves around trust.
How do I make sure that my
models don't hallucinate,
that the content that
they produce is accurate,
and the other revolves
around organization
specificity?
I can ask ChatGPT how
to reset my password,
but I want to know
how to reset it
for my company's website.
So by grounding your
grounded replies
in knowledge, we overcome
both of those concerns
because we add
that layer of trust
through your
knowledge base, which
is your repository
of human-verified
information, and
we help ensure
that the content
that's produced
is specific to your
organization service
processes.
I love that.
Making it actually
smarter, right?
Exactly.
Making it easier.
In this age of
generative AI.
Amazing.
Yeah, we know
how suspect some
of those generative
tools can be,
but not Einstein
'cause we've
got our trust layer.
Exactly.
All right.
Leon, thank you so much.
We're going to have
more questions for you,
and I-- keep
your questions
coming in the chat.
Also you can ask
your questions
in the trailblazer
community,
but we're going to keep
on going 'cause we've got
so much more to cover.
So now we're going to get
into Email-to-Case, Omni
Contact Center
Modality, Apple message
for business, and probably
even more than that
with the one and only
Raghu Suram Senior
Product Manager.
Take it away, Raghu.
Thanks, Gillian.
My name is Raghu Suram,
and I'm a product manager
in the messaging team of
Salesforce Service Cloud.
Today, I'm really
excited to bring you
all the enhancements
and innovations
for the Winter release.
First, let's look
at Email-to-Case
and Messaging In-App
and web enhancements.
Email summaries enhance
the agent and supervisor
productivity with the
new email work summary
component.
This component summarizes
the whole email
and gives a chance for
the agent and supervisor
to reply to the customer
queries within seconds.
Secure form is a very
powerful feature.
It enables
businesses to gather
sensitive information
from customers
and restrict its
visibility to the agents.
Terms and conditions is
a very simple yet very
powerful feature.
And it lets the businesses
ask their customers
to accept terms and
conditions before they
initiate a messaging
conversation.
Now, let's look at Omni
and Agent experience
features.
With Omni, we are bringing
in asynchronous inbox
experience using
which now agents
can keep a hold
of work assigned
to them with the unified
inbox experience.
With this experience,
we are also
introducing an
ability for the agent
to mark their work
as interruptible
which allowing other
work to route to top.
Proactive messaging--
proactive messaging
is a very
interesting feature,
and it has amazing
enhancements compared
to the standard feature
which is available today.
This feature enables the
agents and businesses
can reach out to users
proactively from anywhere
from any standard
object such as account,
lead, case for all the
channels such as Facebook
Messenger, WhatsApp, Apple
Messages for business
and messaging
in-app and web.
Now, let's take
a quick look
at contact
center modularity
and voice innovation.
Bring your own
messaging will
be pilot in
Winter release,
and this pilot will
enable business partners
to deeply integrate
and connect
with third-party
messaging services.
And this pilot will
enable businesses
to bring in various
channels that
are not available natively
in the Service Cloud
today.
Now, BYO partners
can onboard
their own conversation
intelligence signals
to Salesforce and also
leverage conversation
intelligence
rules framework.
Work summaries-- we have
looked at a detailed demo
from Leon just now.
It enables agents to wrap
up cases very quickly
with saves minutes
on every voice call
and messaging conversation
by summarizing.
Now, let's look at Apple
Messages for Business,
which is going to be GA
in the Winter release.
This is one of my
favorite channels
to work on in
the last year.
This channel delivers
effortless engagement
across every touchpoint
with AI data and CRM
features.
This channel
offers personalized
messaging, rich content,
and innovative features--
innovative features such
as authentication, pay,
et-cetera.
Rich content such
as like list picker,
quick replies, time
selector, et cetera.
Now, let's take
a quick look
with the demo for
the integration
between Apple Messages for
Business and Salesforce.
In this demo, we
have our user Lauren,
who would like to buy a
sofa chair for her home.
She goes to
[INAUDIBLE] website
to look for
this sofa chair.
As she browses
through the website,
she realizes that there
are so many options
out there, and
she is quickly
overwhelmed with
this list of options.
So she would like to
message the business
instead and complete the
sofa chair purchase right
away.
So she clicks on
the message button,
and then she is
greeted by the bot.
This bot is built using
the AI capabilities
of Salesforce
that provides
an enhanced experience
to users like Lauren.
As you can see,
this list picker
is built using the
component builder,
and it shows all the
available options
for Lauren.
Lauren would like
to buy a sofa chair
so she simply
inputs a message
and sends it to the bot.
Now bot understands that
Lauren would like a sofa
chair and transfers to
a design advisor who
can solve
problems of Lauren
and make the purchasing
decision very efficient.
The agent accepts
the notification
that comes from the bot,
understands what Lauren
is looking for,
and sends a style
quiz to understand the
preferences of Lauren.
Lauren clicks on
the style quiz
and looks at
all the options
which are available
for sofa chair.
She goes page
by page, clicks
on her preferences.
And, as you can
see here, she
selects mid-century
modern chairs.
So that's her favorite.
And she can also
select the upholstery,
which is like the
microfiber, which
is something which
she has been looking
for her home for a while.
She can also
select the price
range of sofa chairs
she would like to buy.
So she wants to be
within her budget.
Once she submits
the information,
all this information
goes to the AI
and which pulls in
all the sofa chairs
and adds them to
a list picker,
and sends it
back to Lauren.
Now, Lauren clicks
on the list picker
to see all the available
options out there.
So she looks
at the colors.
She looks at the
styling, and then she
selects one of
the options,
and sends it back
to the agent.
With the Salesforce
integration,
we offer an AI
model feature
using which now Lauren can
quickly look at the chair
and how does it feels
like in her home.
So, as you can
see here, Lauren
quickly taps the AR model
and sees how the chair
looks like in her home.
She rotates it.
She tilts it, and she
sees the exact placement.
And now she is
really, really excited
to buy the chair
because it looks
very perfect to her home.
The Salesforce
integration also
offers a payment
integration
to the Apple Pay natively.
So, as you can see
here, with the payment
integration,
Lauren can quickly
click on the payment
and complete the payment
with one tab
with the existing
cards on an Apple Pay.
And now she would like to
just schedule the service
to have the sofa chair
delivered to her home.
As you can see, this is a
time-selected component,
and using which you
can just tell she'd
like to go on September
27 at 3 PM and deliver it.
Lauren is really,
really excited
with the whole experience.
As you can see from here,
with the Apple Messages
for business and
Salesforce integration,
she can browse
the products.
She can give
her preferences.
She can see how
the product looks
at her home, and also
make the purchase
and get it delivered
to her home in no time.
Amazing.
That's it for me.
Thank you.
Over to you, Gillian.
Thank you so much, Raghu.
I wish it was that
easy to buy things.
I want that now
as an end user.
Great demo.
Great presentation.
Wassim, I bet there
is lots of reactions
happening in the chat.
Let's check back
in with you.
What's going on?
All right.
Raghu, you served
a killer demo
on all these new
service enhancements,
and our service stars
definitely agree,
and they're excited.
Now, one question
I'm seeing pop up
is, what are all the
messaging components that
are supported in the Apple
Messages for business?
It's a great question.
So we have over
seven types
of messaging
components varying
from pay, authentication,
list picker, et cetera.
And we're also building
like many more.
So in upcoming
releases, you
will see much
more components
that are coming to the
messaging components.
OK.
More is coming.
I mean, that
alone-- what you
showed was enough of
a teaser to get me.
But I love that
there's more coming.
OK.
So we've got some more
questions for you.
Next question is, what's
the process to create--
is the process to
create Apple Messages
for business self-serve?
It is self-serve.
So the admins can go into
the messaging settings
and click on New channel.
And we have completely
everything self-serve.
With a few clicks
of a button
can create a channel
and then set up queues
and start delivering
the channel
to your customers,
and they
can come in and make
the whole purchase,
as we have seen in
the demo right now.
So it sounds like it's a
declarative low-code way
to set up, right?
Exactly.
It's actually no
code way to set up.
I love hearing that.
That makes me happy.
That's great.
That's great.
OK.
We are going to
keep going 'cause
we've got a lot more
to get through today.
So stay here with me.
We're going to come back
and ask you some more
questions.
But for right now, we're
going to transition
into service intelligence.
So to do that,
we are joined
by Garrett Nixon,
Associate Product
Manager.
Garrett, take it away.
Thank you, Gillian.
I'm Garrett, and I'm
a PM on the service
intelligence team.
And here at
Salesforce, we believe
there are four key
components of delivering
great service insights.
It all starts with
having the right customer
data or, in other words,
a single source of truth.
Only when you have
the right data,
whether it's engagement
data, case data,
purchase data
can you really
begin to craft a holistic
view of the customer.
Next, you want to be
able to analyze that data
and visualize it
in an intuitive way
so that you can identify
trends, outliers,
and patterns
within that data.
You also want to
be able to drive
meaningful predictions and
intelligent insights all
using the power of
AI with that data,
and you want to embed
those insights directly
into the flow of your
customer-facing teams
work so that you get
the right insight
in the right context
at the right time.
And that's why I'm
excited to announce
Service Intelligence
coming this November.
Service Intelligence
is a collection
of out of the box
insights and data models
that enable service
organizations to operate
more effectively to
empower their employees
to be more productive
and to deliver a better
experiences to
their customers.
And with their
seamless integration
with Data Cloud
and Tableau CRM,
you can embed these
insights directly
into your engagement layer
where it matters most.
So with that,
let's see a demo
of Service Intelligence.
So this is the Service
Intelligence platform.
And let's explore
this platform
from the perspective
of Sharon,
a service leader who is
looking for key insights
to run her service
operations more
effectively.
Let's kick things off
with the Omni Channel
dashboard.
This is where
I go to get--
this is where I go
to get a pulse on how
effectively my team is
routing inbound contacts
to optimize for cost and
for customer service.
I can see several
detailed charts
showing work volume
by different metrics
like object type,
status, and queue.
I can also answer
important questions
such as how
effectively is my team
routing these inbound
contacts, how long does
it take to answer
and accept work,
and how does
the cost of work
change across
different channels.
I can also get
a sense of how
my agents are performing
through the agent
dashboard.
Here, I can see my top and
bottom performing agents,
their average handle time,
average speed to answer,
CSAT percent SLA,
and a lot more.
And lastly, I want to
divert your attention
to the conversation
mining dashboard.
So this is where the
platform autonomously
identifies important
topics from your customer
agent conversations
and communications
across different channels,
whether it's email, chat,
messaging, and in the
near future, voice
chat as well.
But the platform
doesn't just
stop at identifying
these important topics,
it also unveils the
underlying reasons
behind each.
So, for instance, drilling
into the invoice problem
unveils several facets
behind the problem,
from checking the
latest pricing
to explaining
and addressing
unexplained fees.
And this allows
me to craft
targeted data-driven
solutions
such as tweaking the
self-service website
or creating a new
knowledge article,
all in an effort
to increase
that overall
customer experience.
So now, let's switch
perspectives and step
into the shoes of
Patrick, an agent
using this platform.
Here, I can see
all of the cases
that are assigned
to me, as well as
what specifically
I should focus on.
I can compare my metrics
to my SLA metrics.
I can also compare my
performance to my peers.
I can see the average
time to close,
my total escalated cases,
average CSAT, and at
the bottom is where I can
see all of the cases that
are assigned to me.
And I can drill
in if necessary.
So, for instance,
let's open this case.
I'll use the case action
framework to do so.
And now I'm presented
with a case effort score
and a next best action.
So in this console view,
I can get a sense--
I can get information
about how much friction
my customer has already
experienced trying
to resolve this case.
And that's what
the case effort
score aims to capture.
And it does that based
on different factors that
are configurable
by my data admin.
So, in this
case, it's speed
to answer, agent
interactions,
email response time,
and escalation.
And then based on this
case effort score,
Einstein has recommended
that I acknowledge
the long email
response time
and send a 5% discount
to the customer
as my next best action.
And with that, that is
the Service Intelligence
platform.
Now, back to Gillian.
Thank you so
much, Garrett.
I'm blown away
by all the ways
that Einstein are included
in all these updates
coming with Winter 24.
It's pretty amazing.
Wassim, I bet there
are some people that
are blown away in
the chat as well.
Let's check back
in with you.
What's happening
over there?
All right.
People are definitely
chiming in about
your demo, Garrett,
on social media,
in the trailblazer
community,
and in the Q&A, and in
the chat on Salesforce+.
People are
excited about how
to perform great
service insights
and perform their
customer experience
with these new
enhancements
that you just shared.
Now, one question
that I'm seeing pop up
is for the Einstein
Conversation mining
dashboard does an admin
need to define what
the important topics are?
Can I leverage data
from multiple sources?
No-- so, well, yes,
you can leverage data
from multiple sources.
And that's really the
power of Data Cloud.
It takes in data from all
these external sources
that are all speaking
their own language,
and Data Cloud
combines all that data
so that they speak
the same language.
And that's how you
can leverage data
from multiple sources,
all using Data Cloud.
So the answer is yes.
I love that.
Well, yeah, I mean,
we have so much data.
And I think that's a theme
with all of Winter 24
enhancements, even with
what we saw yesterday
with sales and CRM is
with all of the data
that we have with the
power of Data Cloud
really unlocking
next-level innovations
for what people can build
and the solutions that we
can build to help serve
our customers better
which is pretty exciting.
OK.
Another question for you.
We talked about--
well, we're
going to talk about
my favorite community,
the awesome
admin community.
So can admins define
what the topics are
for Einstein to look at?
So fortunately, they
do not have to do that.
Einstein automatically
identifies these topics.
And as I
mentioned earlier,
it also automatically
identifies
the underlying
reasons behind each
without the admin needing
to do anything, really.
They don't need to
identify those topics
or identify other
reasons either.
I love that.
Well, OK.
So the follow-up
question is,
could if they
wanted to have
some control over that?
Could they-- I am
not entirely sure.
That's fair.
That's fair.
We can ask that question
in the trailblazer
community.
And so, as a reminder
for all of you
who are watching now,
thank you for watching.
We are taking questions
live in the Q&A right
here natively
in Salesforce+,
and your questions in the
trailblazer community.
So maybe you have a
very detailed question
or a question that--
well, we only have three
product managers here
who represent a huge
organization of very
talented people
who are building
these solutions for you.
So if they don't have the
specific answer you're
looking for, ask it in
the trailblazer community,
and that's where
we'll be able to get
your specific
answer 'cause
we'll make sure that
we get an expert answer
to your question there.
OK.
Well, I am going to
now include all of you
in the Q&A because you're
now all on the bench.
So let's go back to Raghu.
I have a question for you.
So what are all
the channels
for which secure
forms are supported?
That's a really,
really good question.
So today, the way
we have implemented
is like we have
two formats.
One format is for like
[INAUDIBLE] channels,
which is like messaging
in-app and web,
and the other format
is for Apple channels.
So these are
the two channels
which are
supported natively,
but if you want to use
a similar experience
for the other channels,
you can also do it,
but you need to use
some logic and some code
in there.
OK.
All right.
Well, we can use
a little code.
That's fine.
We can do that.
Now, Leon, you
mentioned something
that really
piqued my interest
in terms of accessibility
enhancements.
Can you give us a little
bit more detail, and what
is coming with
Winter 24 that
unlocks the next
level of accessibility
enhancements for
your product area?
Yeah.
So I think one
point of feedback
that we kept hearing
from customers
is that it sometimes
difficult to make
your knowledge content
accessible to people who
use screen
readers to people
have other visual
impairments.
So with this
new editor, we
wanted to make that
really easy for you.
So the built-in
Accessibility Checker
automatically flags all
of the WCAG violations
in your article.
So that's the framework
for Accessibility
Guidelines for
the Internet.
So it automatically
scans your article
for all those
violations and then also
gives you suggestions
for how to fix those,
making it really
easy for you
to make your knowledge
content more accessible.
That's super important.
I know it's something
we make a priority here
at Salesforce.
I actually heard
a little rumor
that we might be investing
more in accessibility,
which is really exciting.
So that makes me
personally very
happy as well.
Wassim, I am
wondering what
is going on in the chat.
So I want to check
back in with you.
What are people
saying what
about all these
innovations?
All right.
Service stars got a
lot to say about all
these innovations.
I'm looking on
social media.
Tom Ferguson on
X says that he
loves the work summaries
and service replies.
Garrett, you're getting
a shout-out, too,
for your demo and
for your fashion.
Candy on Salesforce+
is saying I love
the intelligent
analytics, and she loves
your jacket, too.
And Jeff on Salesforce+
says these knowledge
article improvements
really are game changers.
So lots of love
is coming in.
Now we also
have a question.
This one is from
Penny on Salesforce+.
She's asking are work
summaries reportable.
That's a great question.
Work summaries is that--
Raghu-- do anyone
want to take that?
Do you want to
take that question?
That's a good question.
Yes-- the answer is yes,
they are reportable.
The way it is
done-- to be honest,
I'm not 100% sure,
but something
which can get back to
what is our trailblazer
community can
answer that one.
OK, great question, Penny.
Make sure you ask that
in the trailblazer
community.
Like I said, we've got
three product managers
representing an entire
organization of folks who
work in develop these.
So we will do
the best we can
to get your answer
live, but if not, ask it
in the trailblazer
community,
and we'll make sure to get
an expert answer there as
well.
So I want to--
speaking of
jacket, by the way.
What is future for us?
I'm curious, Garrett.
Some people might be
tuning and be like,
I like that jacket,
but what is it?
Future Salesforce's
program for new grads
and for university
college students who
are interning
at Salesforce,
and they throw
tons of events
and really just
invest in all of us.
So I went through
the APM program
for two years right
after graduating,
and it's been
an amazing time.
Well, good.
I'm glad that's how
we got you-- got you
to be part of Salesforce.
Now, Leon, I know you
have been at Salesforce
for a while.
How many years have
you been at Salesforce?
It's six years now
as of this month.
Wow, congratulations.
Thank you.
Welcome to the
old-school club.
Yeah, I know.
The lines are
starting to show.
But-- so Leon,
you are in deep
working on knowledge.
Let's take a little step
back and talk about where
is the direction
that we're
going with knowledge and
what makes you really
looking forward to
what's next in that area.
Wow, I haven't paid you
to ask this question,
but I love talking
about that.
So I think overall, the
biggest transformation
with how we're thinking
about knowledge
is that we're
really switching
from delivering articles
to delivering answers.
And that's something
that we're finally
able to do now using
generative AI because,
let's be honest,
when you're
customer reaching
out with a problem,
when your service
agent or trying
to resolve a case, that's
what they're really
after.
They want to know the
answer to their problem
or issue.
So with generative
AI, I think,
serves reply
as you just saw
was a great example of
that are search answers
and bot answers product
that are coming up
in December are also
good examples of that.
We're basically able
to give your customers
direct answers to
their questions
that are grounded in
that knowledge base
to ensure we add
that layer of trust
but very specific and
tailored to the question
they reached out about.
I love that.
Yeah, I mean, it's
going to make it so much
quicker for people to
get the right information
at the right time.
Exactly, yes.
And I think this--
I mean, gosh, we
weren't really even
talking much about
generative AI a year ago,
right?
And here we have all of
these great enhancements
and innovations that are
incorporating general AI
to make the platform
more powerful,
which I think is
pretty exciting now.
Raghu, I'm going
to now give you
a similar question.
So I mean, first of all,
that Apple Messages demo
was next level.
I honestly-- I'm looking
at that and being like,
oh, I wish it was that
easy for me to figure out
what chair I need to buy.
Be a chair that my
kids wouldn't destroy.
Very different
requirements.
But what are you
looking forward
to in terms of
your product area
about what's coming in
the next few releases
the direction
things are going?
Awesome.
So the way we
are thinking here
is we want to bring
all the experiences
on the web to
the channels.
That's what we want
to do in simple terms.
As you can see
today, we are
giving the
ability to browse
and giving
ability to pay--
we are giving
ability to also--
what is it?
Deliver the products.
The one feature which
I did not use or show
in the demo is
authentication.
So if you want
to authenticate,
you can authenticate
within the channel
as well.
But we're also thinking
like many more features,
such as recommended
products based
on your past
purchasing options.
And there's many different
AI capabilities-- what
Leon was talking about.
We want to bring all those
capabilities directly
into the channel
so that you don't
have to go to the web.
You can just directly
go into the channel
and get all the best
experience of web
into the channel.
I like that.
Yeah.
So the channel experience
really speaks to me
because when you're
working on your phone
or whatever, you're
not necessarily,
oh, I have to go open a
web page and all that.
So that's really exciting.
That's excellent.
OK.
Wassim, I want to
check back in with you
because I want to see what
is going on in the Q&A
'cause I can't
see it right here.
I even got an iPad.
I can't see it.
So what's going on?
A lot of fun stuff is
going on in the Q&A. Ty,
I see that you're telling
people that you strongly
recommend that
everyone hit the Data
Cloud trails, and you're
also sharing your profile
on Trailhead.
And I suggest that.
Hit the trails.
Connect with each
other on Trailhead
'cause that's
a great place
to exchange
more information
and learn more about
all the features
and the innovations
that we're sharing.
Now, one question
I'm seeing pop up
is are you able to edit
the Einstein-generated
response, and what
were the cases that
made the terms and
conditions feature
a priority to
deliver for Winter?
So that's a twofold.
OK.
Who wants to take that?
Should I take the first
part of that question?
Yeah, Leon
[INTERPOSING VOICE]
Thing.
We got this.
We got this.
Yes.
So the answer is yes.
The human in the
loop philosophy
that you might have
read about in the news
is really important to us.
We want to make
sure, especially
in these early days
of generative AI,
that we still give your
service agents control
over what they're
sending out.
So service replies
will give you
recommendations
for replies to send
to your customers.
And if you look
back at the demo,
you saw that there
were two little buttons
right there one said
Post, and one said Edit.
Kind of speaks for itself.
One posted directly
to the chat
if you think
that's the best
reply I've ever seen.
The other one,
you click Edit.
You have the option
to change the contents
first.
Maybe to make it
a little bit more
personal to add some
details in there.
Excellent.
I like that.
OK.
Now Raghu to you about
terms and conditions.
So yeah, you could add
the terms and conditions,
as we have seen in
the screenshot there.
I couldn't show the demo
of terms and conditions,
but you could add clear
terms and conditions
regarding the
generative AI.
The security
aspects of it,
obviously, like
Salesforce,
has a clear
contract dimension--
what are the terms and
conditions-- regarding
the generative AI.
You can incorporate
all of them
in the privacy policy and
let users know about it
before they start
a conversation
with the business.
So it's all clear,
well documented,
and that's something which
is amazing, as you said,
right?
It's only been a year
since we have generated--
I mean, not even
a year actually.
To be honest, I think
December or January
that's when ChatGPT
is announced.
Yeah.
There are 3.5
version to everyone,
and it has blown up.
So now we are at
a pace talking
about how to
use generative
at every interaction and
also terms and conditions
and everywhere.
And I think that touches
on something that
is really important in
both of your answers
is that humans are
still at the center
of the experience, right?
So while Einstein will be
able to make it quicker
and easier to get
the information using
our trust layer to
make it more accurate,
it's really
important that--
I mean, the way I
view it is everything
that Einstein
creates is a draft,
and it's the human's
job to look through
that draft make
it personalized.
And then I think
to your point, too,
about terms and
conditions that to me also
makes it really important
to remind people
that you have to be honest
when you're using AI,
right?
'Cause-- how much
does it-- it's
not a good feeling when
you're talking to a bot,
and you're like,
oh, hey, Lisa.
How's it going?
And they're like, sorry.
I can't answer
that question.
Like-- OK, at this
point, we should probably
know that that's a
bot, but it's really
a way to establish
trust with your users
and your customers as
well being transparent
about when you're using
AI and when you're not.
So--
And if I can add one thing
to what you just said,
I think we've been testing
this generative replies
product with our
customers for months now.
And coming back
to the point you
made about humans
still being very much
in the center of this
whole experience.
I think that's
what we really
saw during pilot
feedback as well
is the reason
people were excited
about this product isn't
even necessarily just
because it's safe their
agents a bunch of time.
It's really
because it allows
them to deliver that
personalized service that
still has the human
agent in the center,
but is much more
tailored to the customer
interaction.
And I think that's
what resonated most
with our customers.
I saw customers
that said, well,
we have a service
center that is offshore.
English is not their
native language.
They never felt
super comfortable
about communicating with
customers in English,
but now they feel
much more comfortable
because they have
these suggested
service replies here
that are grammatically
correct.
So I think all of that
really just highlights
what you were just saying.
Oh, that's great.
At that point, I hadn't
even thought about that
use case of helping
people who are working
in a language that is
maybe not their native
language and making
them feel so much more
confident about the
work they're doing
and the experience they're
delivering that's--
I love that.
That's really incredible.
OK, Can I add one--
Yes, please--
More thing.
So if you have seen in
the demo when Lauren--
when the bot
starts creating,
Lauren says I'm
a Virtual Agent.
So there is a condition
across some countries
like you need to use that.
It's a Virtual Agent.
When you're
sending a message,
it has to happen in
the first message.
And there's a lot
of regulations
because bots have been
around for a while.
And we would probably
expect similar type
of regulation
that's coming in
into all the other
different types of AI
as well.
Well, and
Salesforce is really
leading the way
when it comes
to AI best practices,
especially when it comes
to building it within an
enterprise experience,
and that's why that
trust layer, which we've
heard about, I think, from
every single one of you
is so important in
all of our products.
And everything that we do
in the platform and trust
is our number one value.
I mean, so it's
coming through in all
of the way we're
innovating,
which is great.
OK.
Wassim, I'm going
to try and check
back in with you.
We can continue
to nerd out
about trust
and AI all day,
but I want to
include what's
happening in the chat.
Wassim, what is going on?
All right.
Lots of love, lots of
questions in the chat.
Gert loves the
work summaries
great AI feature.
And Amber is coming
in with a question.
She's asking could we get
a little more information
on how the Omni
Channel inbox is
going to function and
is it similar to a case
queue.
Raghu, I think that's you.
That's for me.
The way it works- the
thought process in there
is we want to have
the similar inbox
experience as an email
like your current Gmail.
That's the
thought process,
and that's how
it's going to look.
We-- as you know,
enhance Omni.
There needs to be
certain permissions
you need to get in order
to have the enhance Omni.
So once you do
that, you'll get
the similar experience.
And that's a
thought process.
And obviously, what
is every release
we're adding feature
to the enhanced Omni
the asynchronous
inbox experience.
So we're getting
there one by one
to give you exact
feel and manageability
as your current
email inbox.
That's the
thought process.
I like that.
Making that
consistent experience
is really important.
OK.
So, Garrett, I'm going
to come back to you.
So I actually
have a question.
So you talked--
what you showed
in terms of Service
Intelligence,
we saw a little sneak
peek of that yesterday
in the CRM
analytics section.
So what are some of
the initial pieces
of feedback or
things that you're
hearing from
testing or customers
about how it's
really helping them
out and getting
their job done?
Honestly, it just
makes everything
a little bit easier.
So, as I mentioned,
even just
having all of
that information
in one dashboard for
the different personas
is huge.
So if you're an agent, you
can see all of your cases
that are assigned to you.
You can see what you
should and shouldn't
be working on
where you least
and most productive.
All of that in just
one place, and the same
goes for the
service leader.
They had one
specific dashboard.
And then lastly, we had a
lot of positive reception
about the Einstein
Conversation mining.
That's been a
huge, huge help
for a lot of our customers
because, as I mentioned
earlier in the
prior question,
the platform automatically
does it for you.
It does everything.
It identifies
those topics.
It unveils the
underlying reasons,
and that enables--
that allows the service
leaders, the agents,
to focus on what
they do best
without having
to deal with all
of these other
minor things.
Yeah, I mean, it's like
getting a CliffsNotes
version of everything
that's happened.
So you're like, cool,
just give me the takeaways
so that I can take action
on the important things.
That's really great.
That's really great.
So we-- the other thing I
wanted to actually double
click not to use a term
that we way overuse
in this industry into
that is to what would
you have to do to
get that experience
get that dashboard before
service intelligence.
How would you
even approach
building that or getting
that information?
That's a great question.
It-- you would have had
to manually set everything
up on your own.
You-- even before
Data Cloud,
you would have had
to-- if you wanted
to bring in data from
different sources,
all of that would
have had to been
a manual effort
on the customer,
and each customer
would have had
to do that on their own.
So it would have been
a lot of upfront work
just to get the exact
same experience that we
have out of the box now.
Right.
A lot of customization.
A lot of iteration.
And yeah.
OK, just wanted to
highlight that 'cause it
is pretty great
that just comes now.
You can use that.
And I bet a lot of our
builders in the service
community are
looking forward
to rolling that out.
Absolutely.
Wassim, I want to
check back in with you.
What is happening
in the live chat?
We are flooded with
questions and curiosity.
A lot to keep up with in
the Q&A and in the chat
right now.
We got a question from
Weta on Salesforce+.
She's currently
using search
and replace Lightning
App for knowledge.
Should we uninstall it and
turn on Lightning Editor?
Leon, that's
definitely you.
I know, and it gets
into the nitty gritty
of things, which I love.
So thanks for asking
that question.
So I think they're
complementary.
The Lightning
Article Editor
has a built-in search
and replace feature,
and it works on
a field level.
So when you're editing
a specific field
with knowledge content,
you can use that search
and replace
function there.
The AppExchange
package works
across your entire
knowledge base,
so the use cases are
slightly different.
If you're authoring
one article,
and you want to
search and replace
a certain term in a field,
Lightning Article Editor
is going to be your
new best friend.
If you really have a
change like a one-term
that you want to replace
across your entire
knowledge base,
I would still
keep that AppExchange
package for that.
OK.
See, this is
why we have RRL,
and we get those
questions answered.
That's great.
It's always good to
know your best strategy
when you're
building and what
to use for which tool to
use for which use case.
So thank you for that.
Now, Raghu, I wanted
to come back to you.
We talked a little
bit about what
you're looking forward to
happening in your product
area.
I would also like to know
what's one of the number
one questions that you're
getting from folks when
you're developing these
features when you're
testing them out.
What's one of the
biggest questions?
So the biggest
questions are always
on the structured content
on the competent builder.
So the reason is
because it's new
and it's trendy it
provides great customer
experience.
And the question says--
questions are more of how
do we improve--
not improve but how
do you customize
and personalize
these components.
So the answer
to that is we
integrate these messaging
components directly
into the flow builder,
and flow builder
offers so much
personalization
capabilities.
So you can use all the
capabilities of the flow
and power these
components and provide
that personalization
to the customers
within the channel.
So that's the
number one question,
and that's one of the
things which have number
one feedback today.
I love that.
That's helpful.
And you also said
flow builder,
which is what we're
going to be covering
next in Release Readiness
Live, which, I'm very
looking forward to.
We're going to
actually get
to that in just a little
over an hour, which
is going to be fun,
and all the flownatics
are excited.
I would love to
know-- so Garrett,
I'm going to
come back to you.
So coming up through
our future force program
and our associate product
management program,
what's one of the reasons
that you like working
on Salesforce or in this
general space because you
probably had a few
options, and you're--
you've been-- you're--
in the middle of building
your career, I would love
to know what keeps you
motivated to keep
working on these kinds
of products?
Absolutely.
So what keeps me motivated
working on these products
is just seeing the impact
it has on our customers.
Salesforce has so many
amazing customers,
and seeing being
able to talk
to the customers
at Dreamforce
and understanding
how it improves
their day to day, just
really keeps me going.
That is why I come to
work every single day.
I love that.
You're feeling the impact.
That's really good.
That's excellent.
OK.
Wassim, I want to
come back and check in
with you and see what
is going on in the chat.
All right.
We're getting really,
really technical
in the chat.
We're talking
about AI, API,
CRM all the acronyms.
One question I'm seeing
that I'm curious about
is about APIs.
Our API endpoints planned
to leverage Einstein
by an external platform.
Raghu, is this your area?
I think--
Leon.
I am-- thank you.
So nice to give
me that question.
Yeah.
This is a really
good question.
So if I understand this
question correctly,
I think the
question is, can we
use Einstein's
generative features
in our third-party
applications?
Let's say I have a
web application that's
not built in
Salesforce, but I still
want to use Einstein
generative AI.
The answer is yes.
A lot of that is
not possible today,
but it is on our roadmap.
We realize that a
lot of our customers
have third-party
applications
that they want to
leverage generative AI
in, so yeah,
that's definitely
something we're
actively thinking about.
I love that
forward-looking
statement.
You know, it's
on the roadmap.
Thank you.
That's why we have you.
So great.
Well, I know that there's
lots of excitement
happening I would like
to come back and ask
some kind of
nerdy question.
So you're all
product managers.
You help build
our products.
You get challenges
sometimes, right?
Like there's things that
are really hard to build.
So-- excuse me.
Tell me about
something that's
been very hard to build
this last release.
Garrett, I'll
start with you.
Something that's
been very--
well, to be
honest, I recently
joined the Service Cloud.
So I've only been here for
about a month and a half.
Right now, we're
really focusing
on trying to
integrate and expand
Service Intelligence and
seeing exactly where GPT
and GPT-enabled
capabilities fit in
and maximizing
the value as well.
And so I think at
a high level that
has been a challenge
is just figuring out
all right what does
GPT AI unlocks so much?
What specifically
should we focus on
to drive that value?
I love that.
I love that.
OK.
I'm going to get
through this.
I am.
Raghu coming to
you with something
that's been especially
difficult to build.
During the demo, I
think I mentioned
that what is it's very
exciting to work on,
like Apple messages
for business
and at the same time,
it's really difficult
to work on the integration
because Apple--
I mean, Apple
Messages for business
is like the
messaging product
has so many features.
It's a great
channel to expose it
to your customers.
So we need to include
so many features
into the product--
I mean, especially,
let's say Apple pay.
So the payment
integration so it's
not only just providing
the simple experience
on the Salesforce
side, like we
need to integrate
directly into the payment,
and also we need to
think about so many error
cases.
And as you were talking
about trust as a number
one priority, so you need
to make sure like when
you launch a product,
it's completely tested.
Not only that like
authentication
is an amazing feature.
And the other
complexity which is here
is like whenever we
think about any feature,
we think about Omni
Channel experience.
When I say Omni
Channel, it's
different than the
Omni Channel feature
what I've shown today, but
if we want to think about
how does it work for
all the channels we are
supporting today, which
is like WhatsApp, Facebook
Messenger, messaging
in-app and web
and in the future SMS.
So that's the thinking.
So every feature has five
times the complexity,
and it's needed
for Apple, so it's
five times a complexity.
So that's one of the most
exciting things which
I've worked on, not
only at Salesforce
like probably
throughout my career.
Well, I love that.
Every good challenge
makes it fun, right?
We like to solve problems.
All right.
Leon, I'm going to
point that to you
what's something
that's been especially
challenging aside from
becoming-- overcoming--
It's just making
you emotional.
Let's just say that.
Yeah, I get it.
I'm going to say
generative AI.
I think this is
simultaneously
been like the most
exciting thing to work on
and the most challenging
thing to work on.
We actually switched
our release model
for our generative
AI features.
We normally have this
three release a year
[INAUDIBLE] but
for generative AI,
we're releasing
new innovations
to our products
every month
because the industry is
changing really rapidly,
but also we want
to make sure
that we iterate
really quickly based
on customer feedback.
That's been an engineering
challenge for us
for sure, but I think we
see that it definitely
does pay out also
because the way we think
about our generative
AI products is we
didn't just see where can
we easily apply like Gen
AI and call it a day,
we really started
by looking at the issues
that our customers were
facing.
For example, it's hard to
author knowledge articles
or sending replies
to my customers
takes a lot of
time, and then
created Generative AI
products that really
fit solve those problems.
So lots of research
went into it,
but I think really
proud of like the place
where we are right
now, and that's
truly a testament to our
amazing engineering team.
So I'm very, very
proud of them.
There's an incredibly huge
pool of talented people
at Salesforce, and
you are representing
an enormous organization.
And I so
appreciate the work
that you and your teams
have done and meeting
those challenges
and really
delivering amazing
innovations
for our customers, which
is pretty incredible.
So I think I finally
got over my cough,
but with all of
that, I really
want to thank all of you
for coming here today
giving us those
live demos.
I want to thank Wassim for
representing in the chat.
Thank you for all of
you for tuning in.
Now, if you've got a
question that did not get
answered, don't worry.
Please ask it in the
trailblazer community.
We'll make sure you get
an expert answer there.
Now, we've got more Winter
24 continuing right here
on Salesforce+ with
Flo at 11 AM PT.
You can catch all of our
Release Readiness Live
shows--
the ones that I wasn't
coughing into, including
developer and admin from
Dreamforce and the sales
and CRM ones from
yesterday right here
on Salesforce+ on demand.
Thank you so much
for tuning in,
and we'll catch you
next time in the cloud.
[SOFT MUSIC PLAYING]
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Service Cloud Winter '24
Watch product experts share the top features in the Winter '24 release. Learn about Core Service, Digital Engagement, Service Cloud Voice, and more.
Starring
- Leon KempersDirector, Product Management, Salesforce
- Garrett NixonSenior Product Manager, Salesforce
- Raghu SuramSenior Product Manager, Salesforce
- Gillian BruceSenior Director, Developer Marketing, Salesforce
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