Simplifying With AI Featuring Floqast And Gainsight
Explore developments in Digital CS, learn about AI's impact on customer teams and hear predictions on future enhancements from Gainsight and Floqast.
*Ding*
*Singing* When love is king, when boy meets girl, here's what they say.
When the moon hits your eye like a bigger pizza pie that's for more than...
When the world seems to shine like you've had too much wine that's some more
than...
Bells are ringing, tingling, tingling, tingling, you'll sing the beat of that
land.
Hearts are play tippy tippy tippy tippy tippy tippy tippy like a guitar on that
land.
When the stars make you drool or just like a pasta pie that's for that small
egg.
When your dance down the street with a clouded you'll feed your inner heart.
When you walk in a dream, but you know you're not dreaming sin your head.
Scores away, but you see back in old Napoli that's for more than...
When the moon hits your eye like a bigger pizza pie that's for more than...
When the world seems to shine like you've had too much wine that's some more
than...
Bells will ring, tingling, tingling, tingling, you'll sing the beat of that
land.
Bells will ring, tingling, tingling, tingling, tingling, tingling, tingling, t
ingling, like a guitar on that land.
Lucky fella, when the stars make you drool just like pasta pie that's for that
small egg.
♪ When you dance down the street with a clove ♪
♪ You'll feel your love ♪
♪ When you walk in a dream ♪
♪ But you know you're not dreaming ♪
♪ Sing your rest ♪
♪ Scoozing me, but you'll sleep back in whole life ♪
♪ Only that's the morning ♪
- Thanks everyone so much for joining us today.
Great song for us to kick things off with.
So welcome, thanks everyone,
for attending our final entry
in our Digital CS Chef's Kiss series today.
So excited to have everyone with us.
My name is Tori Jeffcoat,
and I lead the product marketing
and go-to-market team here at GainSight.
And before I kick things off with an icebreaker
and introduce my fellow presenters,
just a quick bit of housekeeping,
we would love for any questions any of our attendees have
to be submitted in the Q&A
as we go through our content today instead of the chat.
It's just helped us better capture those
and make sure we can address those questions
at the end of today's webinar.
So again, this is the last
in our amazing Digital CS Chef's Kiss series.
And we'll be focused today on how AI
will help us get more predictive
and effective in Digital CS.
If you're just joining us in this series,
you can catch all of our previous webinars on demand.
And if you've been here for every episode,
welcome back.
We're thrilled to be wrapping things up today
with this final webinar.
And so we are fully into the holiday season this time of year.
And with our cooking theme,
wanted to kick things off with an icebreaker,
asking everyone what your favorite holiday meal or food is.
Feel free to drop those answers in the chat.
And I will go ahead and ask our guest chefs
or guest presenters today
to answer this question as well.
My own answer to this question is
that I have a great recipe from my grandmother
for a hash brown casserole,
plenty of sour cream,
butter, all of the terrible for you things in there.
So that is both my nostalgic and delicious
go to holiday dish.
To introduce our speakers and ask them the same question,
we have with us today Tyler McNally,
who is the senior VP of Customer Experience
and Operations here at GainSight.
And has actually been one of the key hosts
of this entire series.
So excited to have Tyler back sharing his wealth
of knowledge on digital scale programs
and some of those tactics
that he'll actually be sharing with us today.
So Tyler, what is your favorite holiday meal or food?
- Whoops, I was meeting.
Honey beans, ham is the short answer
to your question, my favorite.
- Awesome.
I wasn't sure if that was just me or everyone.
So sorry about that Tyler, but thank you.
That does sound super delicious.
And we also have with us our amazing guest chef,
Julie Fox, who is the senior manager of CS at Flowcast.
I'll give her more folk thorough introduction in a bit here,
but she'll be sharing some amazing ways
that Flowcast is using AI for their CS teams.
So Julie, super great to have you with us.
What is your go-to holiday dish or meal?
- Thank you, excited to be here.
Can you guys hear me?
Yes.
Okay, perfect.
Just wanted to make sure.
I would say my favorite is pumpkin pie.
I also really love my mother is Jewish and so,
and father's Catholic.
So I've grown up kind of celebrating everything.
And we make like a traditional kubil,
which is like a traditional Jewish meal.
And we only do it really during the holidays.
So it's really a special meal.
- Awesome.
Well, thank you for sharing.
We have some really amazing answers in the chat as well.
Spinach dip in Hawaiian bread,
mashed potatoes is not a lame answer.
That is always a great one.
Cookies.
So before we all get too hungry,
but thank you all for sharing all those great answers.
I wanna walk us through what's on our menu for content today.
We'll be sharing a little bit about where digital CS
and AI stand as we look back at 2023.
And the impact AI in particular
is having on customer facing teams.
We'll then dive into our maturity model
and our final predictive stage,
sharing some tactical programs that have worked really well
and some new ways that we're getting more
and more predictive with AI.
And finally, we'll hear from Julie more about AI and CS
at Lookest.
And we'll also leave plenty of time for questions at the end.
So again, just a quick reminder to use that Q&A feature
to drop those questions in as we go.
But to kick us off talking about where digital and AI
have made massive impacts on CS this year,
as well as Will in the future,
I'll hand it over to Tyler.
- Thank you so much, Tori.
I am really excited to talk about two dishes
that were made for each other,
digital customer success and AI.
I'm gonna mix metaphors too.
It's the holidays.
I have my favorite sweatshirt on.
I like to think of digital customer success
as the unicorn Santa is the CSM.
And AI is this lightsaber.
And we're all going where we've never gone before into space.
Well, let's ground this again.
I wanna start with a stat from our 2023
customer success index report.
And what we were actually I think pleasantly surprised with
is nearly 50% of companies already have
some specific digital CS experiences running.
And when you dig into the data, what you see is it's even higher
for the lower end of revenue.
I just think companies with one to 10 million in revenue
and at the higher end, $100 million and plus.
And what my interpretation of that is,
is new companies are envisioning digital CS
from the beginning, just like a couple years ago.
It became table stakes to have customer success
as part of your company.
And then companies passing a 100 million ARR
and embracing digital at their scale and efficiency goals.
And now the middle group is catching up.
Let's talk about the other dish, generative AI.
And AI has been around for a long time.
It's generative AI that's blown up over the last 16 to 18 months.
But we see it as emerging as a really critical capability
for post-sale teams.
This is data from another report that we ran a survey
of 400 companies about what are they using
or exploring with gen AI.
And I can tell you customer support
is certainly the killer use case so far.
If you think about it,
large volumes of tickets with responses,
that's your training data.
The job to be done is a lot of summarization.
The port ticket answers are typically
emphasizing existing documentation to a customer request.
And there's already a notion of a chat UI.
You know, gen AI was kind of built for support.
We also believe that success
and the people we surveyed agree is very close behind
while the content may be different.
There's a similar workflow in that
a meaningful portion of what a CSM does today
is take a customer question,
go find the relevant resources,
and then summarize an answer and share back.
Gen AI is built for those kinds of jobs.
We were also excited by the level of interest
beyond support and CS.
And so you can see services, education and community.
And when you dig into the responses,
what they're most excited about
are things like content creation,
content recommendations,
and then bringing this experience,
this is where the combination with digital comes in
as close to the product or user as possible.
I spent a lot of time focused on AI and post sales.
And my aha moment was about 15 months ago.
It was pre-chat GPT.
It was called GPT-3.
And it was pure auto-complete.
You typed in something,
and then the AI would just try to predict what else you wanted.
And the results were far better than I imagined
for a free tool that just had kind of been put out there.
And I think the next point I wanna make
is the most important point.
So if you go to the next slide,
today is as bad as it gets.
When you look at Gen AI capabilities, it only improves.
And I wanna give you two examples to bring that to life.
Left-hand side is a company called Mid-Journey.
They do image generation.
This is the same prompt given to Mid-Journey
nine different times over the last year and a half.
And you can see it goes from what actually is really good,
in my opinion, amateur artist in the top left
to apply definition photo-realistic in the bottom right.
And that's in 18 months.
On the right-hand side,
this comes from the Journal of Internal Medicine,
and they had clinicians evaluate doctor responses
and chat GPT responses to medical questions.
And they looked at the quality of the response,
and they also looked at the empathy of the response.
And it's pretty astounding that clinicians
are already ranking chat GPT,
which wasn't tuned, wasn't designed for medical answers,
way higher quality, way higher empathy.
I believe it's only a matter of time
before your diagnosis will be aided,
not fully run, but aided by medical grade,
generative AI.
And if you go to the next slide,
again, this is some more data from our state of AI.
I think what's really important is that we
and other companies that we talk to,
they're seeing that generative AI
is not a replacement for CSMs.
It's gonna save tremendous time.
And the idea is that it'll create more hours
in the day for CSMs to be strategic,
value oriented, and be able to support more customers.
And you go to the final slide here,
think about how at each stage of the customer journey,
AI is taking on those important,
but either routine or lower value activities
so that CSMs support service
and develop stronger relationships across the journey.
And so I wanna pass it back to Tori now
who's gonna share a couple specific examples
of a weave infused generative AI
and why we're excited for AI
to enable the customer success motions.
- Thanks Tyler.
So one way that AI helps make
that customer's digital journey even better
is actually by helping CS teams
to better understand their customers
as quickly as possible.
Getting a new CSM or an executive up to speed
ahead of customer conversations
really helps make those interactions more meaningful,
do features like our just launch cheat sheet
which actually helps CS teams
to instantly sift through customer content
and surface the right summary points,
risks and priorities to have better customer engagement.
So we're also learning how AI will impact CS programs
and to help kind of uncover some of that
and paint the picture for what's possible with AI.
I wanna showcase a really quick video we put together
of what cheat sheet looks like in action.
Save countless hours preparing for customer interactions
with the new customer cheat sheet
powered by her eyes in AI.
With customer cheat sheet,
instantly analyze then surface key customer information,
timeline notes, renewal discussions, key changes and more.
Never miss customer risks with a fuller picture
of each customer's history,
highlighting their evolving needs and paying points
and elaborating when needed for more.
Easily summarize insights
and share with executives manually or by email
to key stakeholders.
Cheat Sheet makes it easy to summarize months of content
at the click of a button and stay ahead of customer needs.
- Yes, that is my voice.
You are still hearing from me in case anyone's wondering.
Another really amazing way though
that we're looking to use AI
is to make customer experiences more engaging and effective
through features coming soon for gain site like search assess.
This feature will let customers quickly find answers,
help them to summarize key content
and even link to those resources referenced.
So customers can really quickly and easily dive deeper
into that content and the on demand support that they need.
To show you how search assess works,
seeing is always better than talking through it, right?
So I have one more quick overview demo to play
to help everyone take a look.
- For both you and your customers,
navigating your resources, data and content just got easier.
With new search assist functionality,
gain site is harnessing the power of generative AI
to generate quick contextual answers from all or select sources,
then surfacing both summary content
and source resources for deeper browsing.
When your answer sparks more questions,
asking for more as a breeze,
making it simple for your customers to get to the content they need
while in your community.
And there's even more on the horizon.
You can help customers find answers in your product
via the Knowledge Center bot search,
guiding users to the right content
without having to leave your application.
And the icing on the cake,
you can even find your own answers better and gain site CS,
leveraging the same technology to quickly ask
and answer questions on your accounts,
ask for more information
and navigate your customer data with ease.
With search assist, get the answers you need without the hassle.
- The music definitely makes those videos
very exciting to listen to.
But I hope those have been helpful
in kind of bringing to life some of the data points and insights
that Tyler shared from some of the survey data
and help paint the picture of what AI can do in action.
To talk more about our maturity model
and walk us through how AI will actually impact the future of CS,
along with some of the great tactical CS program examples
from gain site, I'll turn it back over to Tyler.
- Thank you very much.
So as we talked about at the beginning,
this is the final of six part series.
We went through in previous episodes,
the full maturity model,
and it went deep on proactive.
Proactive was all about,
you don't need much data at all to get started
with digital success.
You can create accelerate time to value
by creating just in time resources.
And all you need to know is that somebody is new
to your product or a new customer.
The second stage was personalized,
and that was about using a little bit of data
to guide end users to adopt
in ways that are gonna generate our life.
And so think of confirming what somebody's role is
and the next time they log in,
having a personalized experience based on their role
or how they should use the product.
And so now we're gonna move into the final stage,
which is predictive.
And predictive has a couple key elements for me.
It's about only across the lifecycle,
and it's about omni-channel experiences.
I'm gonna break apart some of that jargon for you.
If you go to the next slide,
what we really believe this means is
that how you drive behavior change with campaigns
that are integrated.
And think of seeing the same message multiple times
wherever you live in the product or outside of the product.
Number two, it's about optimizing what you're doing
with digital success by using customer data.
Personalize those campaigns and put them in the lifecycle
where they'll have the greatest impact.
And then finally, by leveraging AI,
being able to provide directly to the customer,
think Search Assist, that's a direct digital enabled AI
experience that takes the load off of CSM
and enables a user to get value immediately.
I wanna go through a couple examples.
First up, multi-channel campaigns.
So here's an example where what we have found
is the more you can make these campaigns consistent
across the places your users are going to be,
the more likely you're gonna drive behavior change.
And a lot of this learning comes from marketing,
it comes from sales, and we're seeing this now adopted
in the post sales world.
So as an example, we have had tremendous success
with customer events.
One of the challenges of making sure the right people
show up to the right events.
And as we have standardized our campaigns
and gone up through a flow like this
where it starts with an in-app teaser,
trying to generate a little bit of awareness.
There's a follow up email that has more details to register.
And then ultimately everything lives in community
so people can self-serve.
And we've been able to see an increase
in the number of signups and the number of attendees.
Two, these one to many events,
which themselves take the load off of CSM
to have to have those conversations one on one.
Let's go to the next example.
So thinking about how you use customer data.
And this is an example of game site
where we combine three different types of data
and then always have this campaign in the lifecycle
because the results,
we can see results every time we run the campaign.
So what did we do?
We printed a pilot group.
In this example, it was customers who had scaled CS
as a goal in their success plan.
However, according to our usage data,
they were not using our email tool meaningfully
and they were three months post onboarding.
We ran it as a test campaign.
We had a control group and a test group.
And with the test group,
we saw just the people that opened the email.
We saw an adoption improvement of email automation
of 6 percentage points 10 weeks out.
And those that clicked on it, it was 7.5%.
Based on the results of the pilot,
we now embed this and it's part of every customer's lifecycle.
If they meet those criteria on the right-hand side,
they're gonna have this as part
of their ongoing adoption program.
So let's bring Tori back
to showcase two more AI features from GameSight
that'll help you generate automated insights
that you could potentially take action on.
Digital.
- Thanks Tyler.
So Tyler just shared some really great ways
that we're getting more and more predictive today.
But I wanna touch on two ways we're actually starting
to use AI to drive even better customer outcomes
and value realization moving forward.
One of the biggest ways that we can improve
overall customer experiences
is by capturing and taking action on the overall sentiment.
Either where things are working or running into friction.
So this image here is just an example,
not actual customer data points,
but by using AI to better capture the key opinions
customers might be expressing in surveys
and in timeline data, we can actually see
where positive and negative sentiment
is popping up at a glance
and then understand where we need to dig in
with AI generated summaries and quick hits.
This helps save tremendous manual time from our teams,
trying to assess text based responses
across the customer base and gather the right data points.
It also helps us understand where the noise is coming from.
So when you can see kind of the count
and the overall sentiment together,
you can help better understand if specific statements
are popping up for just one certain customer
with specific needs or if they're actually reflected
across your larger customer base.
And so while this AI ability with takeaways
is relatively new in gain site,
just released a couple of weeks ago in November,
we're already starting to see it make an impact
on our understanding of our customers' needs.
So I don't have any customer data or programs
to kind of point to here.
I do want to give one more video,
but a really quick overview of what takeaways
actually looks like and what it does
to help convey what this feature has already started to do
for our CS teams.
Analyzing survey, timeline and other data
to better understand where customers
are needing more support has never been easier.
In the new takeaways module powered by Horizon AI,
instantly analyze direct and indirect feedback
to summarize and surface common customer needs
and recurring opinions categorized by theme.
Understand the number of responses applied
to a specific statement,
the overall sentiment on each key opinion
and get an instant summary of what's working well
and what needs improvement.
They're deeper into a specific opinion
by simply clicking in to get an instant AI powered summary
of the overall feedback as well as sentiment score.
This lets customer facing teams quickly understand
deeper needs and click in for more details
to surface and follow up on individual responses
from any given source around the key opinion.
In short, takeaways will help you see at a glance
overall feedback trends and dive into detail when needed.
- Awesome.
So another great example of AI
in our own workflows here at GainSight
is using our new meeting assist feature.
This feature in GainSight CS has actually helped
our own CSMs to skip taking tedious meeting notes
and actually use the AI generated summary of calls
that they've recorded through GONG,
which is what we use internally at GainSight,
to better capture the highlights of conversations
as well as recommended action items
that can really quickly be turned into CTAs
as well as capturing the risk and issues
that might have surfaced during that call.
Again, what you see here is just example data,
but really similar to what's generated for real customers.
One of the big things here is that creating CTAs is optional.
So we're not adding work to anyone's plate automatically,
but really making sure they add the CTAs
that make sense for them.
A funny example that was shared in Slack at GainSight
is that someone had a CTA recommended
to re-book a customer's flight.
They've been talking about re-booking it on the call, I guess,
which certainly would have been going above and beyond
as a CSM, but maybe not a real CTA to capture there.
Otherwise, that this has made a massive impact
is in saving us just the GainSight users of this feature,
an estimated 1,223 hours of time
in just the last 10 weeks
since we started using this feature ourselves,
assuming that's about 15 minutes per call saved.
And if you estimate that out annually,
that's a really impressive over 5,800 hours
or almost three full-time employees worth of time saved.
I think it's really helpful to give a visual
of what these features look like
and how the AI actually works for CSMs.
So I have one final video
to showcase what meeting assist looks like
before we turn it over to Julie.
Enhance your team's productivity and efficiency
with GainSight's new meeting assist feature,
powered by Horizon AI.
Take capturing tedious meeting notes
off your CSM's plates,
letting meeting assist instantly generate
a detailed and comprehensive summary of your call
with recommended action items
and highlighted risks and issues
surfaced during the conversation.
Easily add any action item as a task,
editing the task information, due date,
and assigning it to the right team in.
Choose the task that makes sense for your customer
and eliminate any unnecessary recommendations
with a click of a button.
When you're ready to add the call and summary to timeline,
easily edit the generated notes, activity information,
and click log activity when ready.
With GainSight, capturing and logging meeting notes
just got easier, giving you more time
to focus on your customers.
Awesome.
And so we hope some of those great examples
that Tyler shared as well as some of those features
I just showcased really help paint the picture
for how predictive digital strategies can impact CS teams.
I'm super excited though to turn it over to you
and hear from Julie Fox at Flowcast,
combine both of those words,
and hear what she and her team have been doing around AI
in their own CS motions.
Just a quick introduction before Julie takes over,
she's a proven CS leader that has experienced building
and scaling CS teams.
Top 25 creative CS leader for 2023
and a top 100 CS strategist is incredibly active
in the CS community,
and again currently works as the senior manager of CS
at Flowcast.
And fun fact, she's actually co-authoring a book
on hiring and recruitment in CS.
So super excited to hear more about her learnings
on this topic,
and with that I'll pass it over to you, Julie.
- Thank you so much, Tori, excited to be here.
And I do feel like I need to give the disclaimer.
I did choose on purpose an AI generated headshot.
I felt like it was appropriate to the topic,
so just wanted to make sure that I was being honest here
that that's not actually me,
it's the AI version of me.
As Tori mentioned,
I am a senior manager of customer success at Flowcast.
Flowcast is an accounting operations platform
that enables organizations to operationalize
accounting excellence.
And I joined over a year ago
and really put a special focus and attention
on how we scale through leveraging
digital customer success strategy and programs.
If you wanna go ahead and go to the next slide,
I can tell a little bit of my story.
So when I joined the team at Flowcast,
the team was already a world class customer success team.
Early on, we were challenged with
how to scale exceptional customer experiences,
which historically had been more reliant
on one-to-one meetings and interactions,
and how we can help our team to become more and more outcome
versus output focused.
Taking a step back, literally by definition,
customer success should be centered
around the success of our customers.
It seems simple enough,
but what I have found is that companies get
consumed with the metrics of our business
that we forget the basics.
So what we did is to really bring the focus
back on our customers.
Ensuring customers are achieving value
in their desired outcomes,
it should be at the forefront of your interactions
with your customers.
And the good news is that what we found
is that the more that you focus on your customers
and them achieving value and reaching their goals,
the metrics are impacted really beautifully.
Digital CS, scaling efforts, AI,
it's not just about supporting the customers,
but it's also about supporting your team,
the team that you work with.
I talk to a lot of CSMs and CS leaders,
and there's a common theme that I've been hearing,
especially over the past couple of years,
and even more so this year, I would say,
is that teams feel very spread then.
They're pulled in a million directions,
maybe even feeling a sense of overwhelm or burnout.
And in my experience, a lot of this overwhelm feeling
comes from spending too much time
and energy on reactive tasks.
They feel like they're on this hamster wheel,
they're running, running, constantly moving,
but they're not really getting anywhere
or not getting where they need to be
or spending time on getting off the hamster wheel.
Leaning on AI and digital customer success
is really what transforms teams
to be able to be more proactive and predictive,
more focused and intentional,
which helps them feel better,
and it also helps the customers achieve more value.
So one thing that I did, or I guess we did,
this by no means was just me,
is starting to talk to my team around
kind of where they were spending their time and energy.
People on my team even did kind of more
of like a time management and time tracking exercise
where we really were able to understand
where our team was spending time
and if it was in the most productive value driven ways.
So what we found with that is that tons and tons of time
was being spent on preparing for calls,
preparation type activities, meeting notes,
following up, all of these different ad hoc administrative
tasks and projects that kind of get added and added
to the to-do list.
And now all of these are important activities.
None of this we were willing to say, okay,
these are low value tasks, we shouldn't be doing these,
all of them were high value and really important.
And so that's where we really started leaning on AI.
So if you wanna go to the next slide.
So we've done a lot with AI,
some of the most impactful to the customers
in the team are a couple of what I'll mentioned.
So when I think of the difference
between a good CSM and an exceptional one,
a few things come to mind.
Ownership mentality is a big one.
That's probably one of the biggest things
that I look for as I hire CSMs or as I look at promoting
my team members is that they're taking more
of an ownership mentality around their customers
and the value that we provide.
As part of that, it's incredibly important for CSMs
to know what is going on with their customers.
They should honestly be running their bucket business
like a CEO knowing exactly where the opportunities are,
exactly where the areas of risk are
and on top of all of them.
And so as part of that preparing is incredibly important.
There's a saying in sales, show me you know me.
And I think that kind of rings true here
for customer success.
I think whether it's an email or a meeting,
customers are drowning in content and in touches
and they wanna feel seen.
They wanna know that we know them
and understand what they care about
or how their business is run.
And the gain site cheat sheet is really just that.
It's our cheat code.
It's our ability to understand our customers
at a pretty deep level and how they're using our software.
One of the areas that they're focusing on
what's going on in their world and their business
and what they need,
this allows us to make better decisions
and have better quality and more focused calls.
And as I was talking to the gain site team,
it's interesting because it was mentioned
that Flowcast is one of the highest adopters of this test
as we are going through the beta test of this.
And it definitely made me laugh,
but honestly all joking aside,
like could we live without gain site cheat sheet?
Yeah, I'm sure we could, but would we want to?
Rather not.
I think as you get exposed to these different things,
you recognize just it's hard.
I guess it's once these things are peeled away,
off of your plate, you realize that not only
is that time that you're getting back,
but ideally the AI is doing a better job than we could have.
It's doing it in a more efficient way,
but also it's more effective.
We're getting more information
than what we were getting previously.
Now, the perfect call isn't perfect without documentation,
follow up and follow through.
So truly, I mean it,
I imagine having an amazing call with a customer,
but there's no notes,
meaning that there's a good chance
that a lot of the details are lost.
And there's not a great follow up on action items.
This would not be a good example
of that ownership mentality.
So this is an example of where AI has supported our team.
We use AI to capture meeting notes,
note the action items who's responsible for what
and help support sending follow up messages.
We've tried a handful of different technologies
with update AI, Sible,
Gong has built in capabilities,
game site now does as well.
Using AI continues to get easier and easier.
It's been really interesting,
kind of in the past six to nine months
as we've tried these different technologies,
just how good they are getting.
Just the, we were impressed at the beginning,
but now it's really capturing really, really well,
the action items, next steps and all that,
as well as making it very easy to follow up
with our customers in a really great way.
And I think that's something,
that's a point that I wanna make here
is that the technology is leveraging AI
or expanding the use cases.
So companies like Gong are building AI-fueled
revenue intelligence platforms,
game sites building in predictive AI capabilities
that will empower customers at every stage
to grow with omni-channel experiences,
which I absolutely love.
I have been spending a lot of time with my marketing team
and I'm really excited about ways
to make it easier to provide consistent messaging
across multiple platforms and in different ways.
These are things that honestly,
they're gonna help us to do better,
more meaningful work at scale.
Now, one thing that really excites me at PloCast
is how we are taking our own experiences
of needing to do better work at scale
and applying it to our own customers.
So we are harnessing the power of generative AI
to empower our customers to unleash their full potential.
So again, it's all about our customers
and what they can do.
Now, because we are in accounting operations platform,
data securities paramount as we evaluate both the risks
and benefits of new technologies.
And I think that's something that is worth mentioning.
But yeah, it's been really cool seeing that
kind of full circle moment of how the experience is that
RCS and other teams at PloCast,
the experiences that we're going through
of trying to do more and better work at scale.
It's the exact same thing that our customers are going through
and trying to make sure that we are investing in our product
that helps our customers achieve their goals
and achieves more and more value.
I think it's really important to kind of make that note
because part of the customer experience,
it's not just what we are doing
or how we're interacting with our customers,
but it's also how they interact with our product
and that our product is helping them achieve value.
All right, on to the next slide.
We started using AI really focusing on what we were doing
that we could automate or do better.
So more consistently with the help of AI,
but I think the next wave of AI is transformative.
So it's not just looking at what we're already doing
and making it easier, making it better,
but it's also helping us do better,
helping us do things that we haven't even considered.
As we focus on what's next,
we're focusing more than ever on the goals
and outcomes of our customers.
We're continuing to leverage data, segmentation,
personas, et cetera, to create personalized experiences
that bring our customers value,
while also supporting our team.
I think that's really important is that
we're looking at how these different tools
can create better customer experiences
and create better employee experiences.
All right, and then wrapping up on the final slide,
I will give us a couple of takeaways here.
So as far as a few takeaways,
before we open up to any questions,
there are three that I mentioned here.
One is focusing on outcomes versus outputs,
really understanding what our customers care about,
how they define value and making sure
that we're driving towards what matters to them.
Using AI to streamline manual tasks.
So this is kind of the today state that I mentioned
of how different ways through Gainsite cheat sheet,
through meeting, note capture,
and automated follow-ups, different things like that,
for us to streamline the manual tasks
and then delivering more value realization.
So especially as we look towards the future,
making sure that what we are building,
the ways that we're doing things
and leveraging these different technologies
is helping us to deliver more value.
- Awesome, thank you so much, Julie.
So much great content that you shared.
So super appreciate it.
We do have some questions that came in,
some we've answered in the Q&A,
some I got directly in chat.
So before I dive into some of these questions
and kind of feel these to you, Julie and Tyler,
final call for any questions anyone has
to go ahead and submit those in the Q&A feature,
or the chat, I see when they just came in.
So definitely feel free to continue to drop those in
as we go here.
One of the questions that we got early on,
I think around some of the programs
that you were sharing Tyler,
is how you coordinate across the different channels
for those predictive programs that you mentioned,
the in-app and community, et cetera,
is that one team that manages all of those?
Or is it kind of a cross-functional effort?
What does that look like at GainSight?
- Yeah, it's such a great question
because every company's trying to figure it out
and there's not one answer.
What has worked for GainSight is we have different teams
that are collectively supporting campaigns.
So marketing, product marketing and post-sale.
What it takes, it could be as easy as a monthly meeting
that you get together the stakeholders and say,
what campaigns is marketing running?
What campaigns is customer success running?
Often we find there's overlap in the campaigns
and so we try to combine them or connect them.
The other thing that we do,
I think of as like a, it's very tactical,
but it becomes very strategic
is we have a shared campaign calendar.
So customer success teams know
that we are running this digital success series
and we're doing our promotion of it
as marketing is reaching out to prospects.
And so there's, it's a good example
where there's not one like, the thing we're doing,
we're just talking to our cross-functional partners
and we're documenting what we're doing,
but that has enabled us to move and go a lot farther
by working together as opposed to kind of being slightly off
or slightly in parallel.
- Awesome, thank you, Tyler.
I think it's definitely one of those,
as one of those cross-functional stakeholders, I should say,
it's one of those things that we definitely collaborate
around, I think, to get that best final output
for our customers.
We have another question that actually just came in
for you, Julie, on some of the content you just shared
around how you manage the change within your team,
specifically was there any resistance to or fear
about using AI among the CSMs?
- Sure, I love that question.
I, first of all, quick disclaimer,
I'm lucky and I recognize that I'm lucky in the fact
that at Gaines at low-cast, we are a very innovative team
and a lot of this came from the top-down.
So we had executive leadership that was really excited
about some of these capabilities
and wanting us to explore what we could do with that.
And so we were early adopters in the sense
that we started having conversations almost immediately
and doing it in visible ways through Slack
and in different leadership meetings,
different things of what are we doing?
How can we use all of this stuff better?
And so I started having those conversations.
Of course, security is of the utmost importance.
And so that's something that has always been part
of the conversation.
Anything that we use that is customer facing,
that is impacting our customer data, our team's data,
anything has to be vetted by our IT and securities teams.
Like we can't just try things and go rogue
that wouldn't be the right thing to do.
And so that's something we've had to be very clear on.
But one tangible thing that I'll leave you guys with
that I really liked that we did at low-cast
is that as we have started adopting certain things,
so as things get the approval, as we start launching
things out to our team and start using
these different technologies,
what we have done is created different leaders
within the team.
So these are individual contributors, CSMs,
support people, implementation people,
and per each of the different teams
and geographical kind of pods,
we've selected different leaders on the AI front
so that they are constantly sharing and trying.
And they're kind of the ones champion in a lot of this.
I think that's something that's really important
is to constantly share, share the wiggle
or share the what good looks like of,
hey, here's what I'm doing and here's how it's impacting
my book of business or my customers.
Here's what I'm trying.
What we have found is that by selecting specific people
to tell those stories, it gets other people sharing to it,
gets them talking about their challenges
as well as their wins and creative ways
that they're trying all this.
- That's an amazing tactic.
I use that all the time as well.
It's so valuable to drive change
and identify those sparks that can help you do it.
Toria, I figured I could try and take
these two questions that are outstanding here.
So are these new features automatically rolled out?
No, they are not automatically rolled out.
We take data security privacy very seriously.
There is an opt-in process and then the company's admin,
the Gensite admin will go need to turn on the toggle
and there's we have instructions and your CSM
and support can help you.
But no, this requires that you want to use the AI features
and then an admin is in there.
After turning on the toggle, the nice thing is
there's not really setup that needs to happen.
The AI works, I answered another question in the chat.
It takes anywhere from a couple of days to a week or two
depending on how long you've been using Gensite.
After you do that training period,
you can generate a customer summary for any customer
in a matter of minutes or less.
And then Daphne on your question,
I have seen a lot of different models.
The model Gensite has and I'm thinking broadly here
is we have an AI council.
It has functional representation from across Gensite
led by our CIO and CFO and we're experimenting.
So do we want to use AI with our Red Ops team?
There's an experiment and evaluation going on.
For customer success, like I mentioned to the last question,
you don't need a big CS Ops team.
These features have been designed to turn them on
and they work.
There's very minimal setup,
which I think is something super powerful
about our AI functionality.
And again, we're trying to take the load off of you
and load off your companies to manage
some of this AI complexity.
- Yeah, awesome.
Thanks, Tyler.
And I think that question about the,
is it automatically turned on,
goes back to Julie's point, right,
around transparency, rolling it out effectively,
making sure everyone's on board with those programs.
One more question that came in earlier.
Julie, I'll ask this as our final question
as we're approaching the end of our webinar time here.
But one question that came in early was around using cheat sheet,
being an early beta tester, using it today.
Curious Julie to hear if you feel like those outputs
are valuable, accurate for your team.
Has that been, I know you mentioned it being something
you wouldn't want to live without.
But just curious on kind of your take
of actually using the feature,
what is it really like for the CSM team?
- Yeah, in preparation of this webinar,
I actually asked a few of my CSMs and was asking like,
"Hey, are you guys using this as a valuable?"
And it was interesting hearing kind of the different takes
from people being like, "Oh my gosh,
like this is the first place that I go to."
Like if somebody asked me a question about a customer,
I go there as my like way to understand
kind of what the situation and scenario is.
I'm depending on kind of team structures.
You have often like, I mean, you can have 25 to 100,
200s of customers depending on company structures.
And so being able to not feel like everything's in your head
or that you have to sift through data
and being able to get it really quickly
with the click of a button is huge.
It also really helps me on the leadership side.
So on my side, as I'm looking through our churn
or risk mitigation forecast or looking
at different expansion opportunities,
being able to quickly look at something
and use both the health data that we have in Gainsite
as well as the cheat sheet information
of what conversations have been happening
and going through all the different timeline entries,
all the data.
It just makes me do my job way faster
and much more effectively.
- Awesome, thank you Julie.
So I know we only allotted 45 minutes for this webinar.
So we're technically just a minute over time.
So I'll go ahead and end our Q&A there.
Such great questions and anything that we missed,
we'll definitely try and get back to you,
post webinar as well.
We will also share out this recording.
And again, I'm a bit sad to say
that this is the last webinar
and our Digital CS Chef's Kiss series.
So if you're just starting off,
this is the first webinar that you've attended with us
or you want to go back and revisit any of our past entries,
including this one,
we have all of these webinars available on demand
and I highly recommend catching up on some of them,
potentially a great way to binge watch these
over the holidays perhaps.
But with that, like any good webinar, any good meal,
it does come to an end.
So I want to go ahead and just thank our presenters
Julie and Tyler and our attendees today
for such great conversation and questions,
especially anyone who's been with us through this entire series.
This has actually been, I think,
one of our record breaking webinar series for us
and we've had such great interests, amazing guest speakers
and just so much excitement on this topic.
So super looking forward to providing
as compelling content, hopefully in the new year,
but want to just end us with wishing everyone
a very happy holiday season and a great new year.
So thank you all so much and have a great rest of your day.
Thank you all.
- I really thank you.
[silence]