Philip Kibby of Moveworks showcases how AI capabilities simplify employee interactions, offering immediate time-savings and insights that drive productivity and improve customer outcomes.
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[Music]
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As you promised me that I was more than all the miles combined
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You must have had yourself a change of heart that had played through the drive
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Because your voice turned off exactly as you passed my exit sign
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Kept on driving straight and left our future to the right
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Now I am stuck between my anger in the plane that I can't face
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And memories of something even smoking weed is not in place
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And I am terrified of weather 'cause I see what it brings
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Talk told me to travel but there's COVID on the planes
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And I hover more and put it to see even other sticks
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And I saw your mom's chief forgot that I existed and it's half my fault
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But I just like to play the victim I'll drink
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And I'll go home and tell my friends come home for Christmas
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And I'm dreaming of some hurting you that I might not have
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But I did not lose now your tired tracks in one pair of shoes
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And I'm splitting half that I don't have to do
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[Music]
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So I thought that if I piled something good and all my bad
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Can't stop the darkness I inherited from that don't I am
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No longer funny 'cause I missed the way you left
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Once called me forever now you still can't call me back
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And I hover more and put it to see even other sticks
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And I saw your mom's chief forgot that I existed and it's half my fault
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But I just like to play the victim I'll drink
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And I'll go home and tell my friends come home for Christmas
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And I'm dreaming of some hurting you that I might not have
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But I did not lose now your tired tracks in one pair of shoes
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And I'm splitting half that I don't have to do
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Oh that I don't have to do
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My other half was you
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I hope this pain's just passing through
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But I've doubted the time of her mom
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But it's just to see even other sticks and I saw your mom's chief forgot that I
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existed and it's half my fault
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But I just like to play the victim I'll drink
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Good morning everybody I think we have a bunch of attendees here today
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Phillip if you could go ahead and share your screen for me
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Welcome everybody to our CS customer spotlight
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Today we are going to talk about scaling CS
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Using AI and fill up the next slide if you could
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Using AI and fill up the next slide if you could
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Using AI and automation and our special guest today is Phillip Kibbe who is a
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customer of mine at MoveWorks
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And Phillip as you're going to see in the next slide
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Has had an interesting career that brought him to this point
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So about 13 years ago he was working for the US Senate Ethics Committee
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And he was going to be a French wine importer and distributor
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And now he's working with MoveWorks as their director of CS operations
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And when he gets up in the morning he's super excited about streamlining
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everything for his CSM
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So that they have a lot of automation in our lives
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So they can focus on the higher value conversations that they have with
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customers
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So with that I'm going to turn it over to Phillip
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Keep those comments coming in the webinar chat
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And one more thing for Q&A
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Let's use the Q&A button on the Zoom meeting
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And I will keep an eye on those as well
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And if it's something that is pertinent to the conversation, Phillip will stop
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and answer
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If not we'll hold those to the end
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So Phillip I'm going to turn it over to you and thank you everybody for joining
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Awesome, thank you Denver
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Yeah, so again welcome everybody I'm Phillip Kibbe as in
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We're set I've been at MoveWorks for about three years now
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Starting as a CSM
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And it's been pretty amazing ride so far
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The team has grown from 15 or 5
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Yeah 15 people total in the CS to 75 in the three years I've been here
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So it's been pretty crazy
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And as Denver reference I have a pretty odd career
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This is my third career within a small one
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Started off in the US and ethics committee advising
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Senators on public financial disclosure laws and rules
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And then my wife and I put our jobs and moved to Paris for a year to study
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I studied wine, she studied pastry
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And then I started a wine import company before turning back to do some
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technology work
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And it's been a pretty cool ride
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And what I like is able to see all these different aspects of
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You know government and then you know hospitality in wine importing
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Which is huge implications for an application to customer success
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So we'll see someone that kind of weave through how we think about CS
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So moving on
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I wanted to go through today's agenda real quick
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So start off just introducing into what moveWorks is what we do if you've never
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heard of us before And we'll talk you through our gain site journey
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And then going into how that's layered into our own automation
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And internal efficiency initiatives
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And we'll kind of highlight four of them that we've done the last eight months
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That have quite a bit of impact
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And then I wanted to end my steps you can take today
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To really go and drive impact in your organizations
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And if any of these things resonate with you at all
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So moveWorks
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So moveWorks at its core is an innovative AI platform
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That unifies all enterprise systems
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We are huge technology leaders in the space
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We've been using large language models and GPT before
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They were cool for years now
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And as you know evidence by the fact we're in the cloud 100
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We've been I think four years running on AI
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For the AI 50 list
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Winning things like AI breakthrough awards
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And not just the technology side
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The company itself has won quite a few awards
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For just being a great place to work
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But on Newsweek's Best Places to Work List
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For a couple of years now
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As well as Forbes' Best Startup Employers List
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So it's been a great place to work
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And as you'll see given lots of freedom and resources
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To really drive lots of impact
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And the organization
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And what we do as a product
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Is we offer a conversational AI
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And generally AI platform
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That unifies employee services
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To a single chat interface
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So employees can access the information
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And query information form actions
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And really get the help that they need instantly
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Versus having to go through
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Kind of all the legacy ways
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To get help in an organization
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Where leaders in the organization
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We offer lots of advanced analytics
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So you can understand
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What your employee experiences like
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Where you can lean in and make things more
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Fishing and better for your team
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Some of which we used human and
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Identifying areas of opportunity
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In our own automation efforts
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And lastly, developer friendly workspaces
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To extend the product, right?
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We have offered lots of native integrations
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But we really want to make it to where
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You can build your bot for
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And now co-pilot, right?
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For what your organization really needs
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To help improve employee service
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And just real quick what that looks like
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Is functionally on the left
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All sorts of questions you may have
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About the help you need to get an organization
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From what's our 401k match
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What's the status of?
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This headset I requested
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How do I reset my multi-factor?
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We take that
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Those natural language queries
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Run it through a whole host of things
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Like different machine learning models
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Or own data
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Using things like your role in
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And then query lots of native integrations
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That we have into your system
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Before returning to an answer
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That solves your problem
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And it does all that
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Pretty instantly
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So it's a really cool platform
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And obviously now has more and more implications
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With the kind of the rise of copouts and GPT
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So that's a lot of what we do
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And you'll see the fact that we're so focused on
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Employee service and making sure that people
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Get the help they need quickly
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That really just is infused in all the things
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That we're going to be able to do
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And we're going to be able to do
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That with all that, we're going to be able to
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Get a lot of information
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And we're going to be able to do that
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With all that said
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Why do we end up using GAY
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Inside and using it as a platform
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That we want to integrate
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With our own platform to drive
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Efficiency and CS and automation
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And really when I started
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At Moverz, we had a team of about
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Seven CSM.
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And we had a team of the CSA team
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Who was doing support and
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Random operational things, so very small team
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But by the end of 2021
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That team had grown from seven CSM's to 19 CSM's
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Right around that time I started the CSOBS team
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Because we definitely needed operational support
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And you could start to feel the pain of a lack of a centralized system
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And ways to access information
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And then six months later by mid 2022
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We had 25 CSM's
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And we needed to procure a centralized system ASAP
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It was just really critical now
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That information was all over the place
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In the organization
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And as you can see here's a slide
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We actually used in our pitch to leadership
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To get known, not only by a CS platform
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But to recommend GAY
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Inside, which was like CS tools and platform
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And a process was all over the place
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Notes were being taken in five different surfaces
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Account info all over the place
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Customer issues were recorded in
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Zen desk, but they're also stuck in notion
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And Jira, not even Slack
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And so we didn't really have a way to
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Unify all this information
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Into one system that allowed CS to see
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The state of their accounts and take action on those accounts
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At scale, and that really necessitated the need for a platform
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And as we look through all the options in the market
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We landed on GAY insight for what I think is about four primary reasons
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The first of which is there's a robust
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You know the most robust data model we saw of all the CS platforms
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And this was a huge differentiator for us
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We deal with lots of data, we work on lots of data
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In a very data driven CS organization
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And so we needed a system that
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Would allow us to, you know,
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In just the data that we used to
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Day with how to do a bunch of new transformation
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Before it entered a platform
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And then once it's in a platform, transform it
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And combine with other data sets
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To create unique data for us to understand our accounts
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The second was total flexibility in configuring the product
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So this is also super important
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And we needed to conform the product to how our CSMs worked
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And manage their portfolios
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Not conform how CSMs worked to the software platform we purchased
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Absolutely critical that we met CS whether or not
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And then asked them to change how they worked
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We're very successful at the CS team
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Have really high GDR and we didn't want to mess with that process
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So we needed a platform that had lots of flexibility
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And with that comes integrations
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As you saw on the slide before
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There's actually quite a bit of
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Systems at how's information about customers
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That we needed to unify into one place
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And so having a robust native integration set
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Was really important
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And particularly native integration
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And things like snowflake
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Was kind of a no brainer for us
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That allowed us to move all this data
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About the product
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And all of our go-to-market data in snowflake
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To really give us a very easy way
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To get this information in front of CS
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And then lastly was just more robust account resources
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So throughout the whole sales process
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The team was really responsive
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And it was very clear that
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Gainsaw would be great partners with us
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And even now that we are
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Customer is you know, a slang dimmer for the webinar
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Apologies for how many requests we send
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His way and Ashish
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As our technical partner and both of them are amazing
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And always willing to blend a hand
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And so that since the partnership
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Was really really important
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And so these are the reasons we chose Gainsaw
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And you can see as I go through the rest
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Of the presentation
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How we layer all this stuff into Gainsaw
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Not everything is housed in it
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But it's used as a conduit to make things
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Easy to find and reference as well
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So this is really why we chose Gainsaw
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Which really helped us
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Kind of launch this
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Motion of efficiency and automation
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We purchased it in March or May of 2022
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And we went live with implementation in September
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And one thing I'll call out of
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We launched with a very like V1
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Not very robust systems
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We could build it
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Based on feedback that we got from CS
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And that was really the right call for us
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As we really ended up building something
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That CS really wanted to use
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Versus spending 8, 12 months on implementation
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And not actually landing it where we needed it to be
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So from here
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What I want to talk about is our
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Automation and efficiency journey
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So as was referenced in
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The sign up materials
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We ended up saving over 4000
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hours in the last 8 months
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And wanted to walk it through
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How we did it and I wanted to focus on the
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Fore highest impactful initiatives that we did
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On an automation and efficiency front
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In order to deliver against these goals
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Particularly as I'm sure everyone is aware in the last
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You know, years so the map environment for SaaS
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Has been difficult
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And a lot of startups had to shift from
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You know, hyper growth, grow at all cost models
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To something that was more efficient internally
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To start containing costs
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And that was really something we wanted to do as well
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We'd grown the CS team exponentially
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You know, in the span of
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12 to 18 months
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And now we actually needed to make sure
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That those people we hired
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Had all the tools and that they needed to
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Really manage accounts at scale
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And so this was really our focus
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And the last, you know, 8 to 12 months
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And it's an 8 month period I'll focus on here
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And all the things that we were able to deliver
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To meet those goals
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And from an impact perspective
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Over an 8 month period we, you know
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As I mentioned, saved over 4000 total CSM hours
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And we did that by
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Automating nearly 6000 calls
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Nearly 3000 emails
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I'll talk about this deck generation
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That's automated deck generation that we developed
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And we've seen almost 1500
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Over 1400 decks automatically generated
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In the span of 8 months
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Which resulted in a 3x improvement
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And joint success plans being developed
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For our customers, which was a massive win
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And our focus on customer success
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Or customer education
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Actually a 10x reduction in CSM time spent
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Directly educating customers
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And this resulted in an 8 month time frame
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Of CSM's increasing the AR
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They managed by 32%
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Which was just a super big win for us
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Because it, you know, made us realize
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That all these efficiency things allowed us to really drive
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Scale for our team
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And allow our CSM's to take on a bit more
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But do so in a way that wasn't overwhelming them
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And also generated and delivered customer outcomes
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That we were looking for
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And so I want to kind of talk about
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How we generated this impact
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And, you know, first I'll start with
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Call of Summarization, which was one of the first things
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That we did
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And the problem we were trying to solve
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Was, call notes were being stored
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In all sorts of locations across
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The, you know, our tools, right?
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Some were in Apple Notes, some were in Google Drive, some were in Notion
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And it was just becoming a mess. It's hard to reference
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If someone was out of office
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You didn't know where their notes were stored
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If the customer question that came up
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So we wanted to create, you know, that was a big problem we were looking to
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solve The second was just clear and consistent
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Call of Summarization
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And this is clear and consistent
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Call of Summarization
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Consuming to create, you know, as a CSM
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For many years and you're on a call
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You're trying to listen to your customer
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You're jotting down notes and they're often all in shorthand
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And so in order to, you know, create good notes
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You have to actually spend time in the day
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Just cleaning them up and making them readable
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For a third party
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You know, third was, as a result of this
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We seeing action items would get missed
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And we were talking about situations
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But missing some action items
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Because you're a so engaging conversation
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Resulted in an downstream customer impact
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Or the customer was like, hey, I thought we mentioned this
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But, you know, CS didn't quite grab it
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And so CSMs were often left with a choice
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Right, optimized customer calls for better customer interactions
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Or optimizer calls for taking better notes
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And action items and really the
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For us the answer was obvious
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We really want them to optimize for better customer interactions
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So what we did for a solution is we wanted to create a single repository
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Which is gain site
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For all call notes for customers
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Make it really easy for us to store them, search them
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And understand what's going on at an account
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The second is we wanted to leverage
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In an AI and automation to summarize those
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Call notes in a consistent format
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Right, this is a big time-sater for us
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And we wanted to overfit the language model
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For robustness and action items
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So that nothing would get missed
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And so the solution we created started back in January right after
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The release of a GPT 3.5
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Otherwise known as Chat TPT
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And something that we were able to deliver
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In about four to six weeks
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And on the left you can actually see
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What this looks like in gain site
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Of course I had to blur out the actual call information
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This is all custom, this is your real call summary
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But functionally you see that
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And we store in Salesforce the call summary
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We push it to gain site
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It has a summary of the call that's automatically generated
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A whole list of action items that are automatically generated
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And then we link out to the gong call
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And the Salesforce record
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And the way we did this was
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We realized we had all the gong audio files
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And gong, and we work with our go-to-market team
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On getting access to them
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And then we worked with our machine learning engineering
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And product management team to say
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Hey, how can we design a solution here
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That was in the end automated for CS
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So we write a script that grabs the audio files
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We use OpenAI's whisper
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Large language model to transcribe the audio into
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Text transcript
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And then we
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Supplement it with some of our own internal data
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Making sure that the model
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Before we go to summarize the models understanding
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Things like acronyms and customer names
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And because our product is typically white-labeled
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Our customers, it's not called Mover
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Set a customer, they design their own bot avatar
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And their own name for their product
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Those bots have lots of personality
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We wanted to make sure that the model understood
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Those names so that they didn't misinterpret it
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And then we summarize using GPT 3.5
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And then we push that summary of that transcript
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Into Salesforce using work-auto
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Which was in a partnership with our go-to-market ops
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And Biz systems team
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And then we use the native Salesforce to gain site integration
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To push that call-noted summary to gain site
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All this is done
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You know, generally within about four hours of the call ending
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We can always speed it up, but just from an engineering capacity perspective
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And we wanted to keep it about four hours
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But this is a hugely popular feature that we develop
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You know, getting over 6,000 calls
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Of an automatically summarized
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And probably between when I pulled this data and now
19:23
We're doing about over 100 calls a day
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And it just really took a load off of CS because now
19:27
Some, mostly, I still take their own notes
19:29
But I think that's a great thing to do
19:31
Because now, some, mostly, I still take their own notes
19:35
But now they can actually supplement them with something summarized for them
19:37
They can use as action items or write
19:39
Follow up emails and customers and do that very quickly
19:41
So it's just a huge time saver
19:43
And just something where it was a piece of mind of knowing that your calls
19:47
would be summarized There would be a history of them when we do handoffs
19:49
This is really huge
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Because you can really understand what's happened in previous calls
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And then we push summaries of quarterly business reviews into Slack
19:59
Automatically so that anyone who's following the account can see what happened
20:03
in the last QBR call
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So this was a huge win and produced quite a bit of time saving on its own
20:11
The next initiative we wanted to focus on was automatically sending emails
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And again, the problem we were trying to solve
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Was that programmatic emails were still being sent manually by CSMs
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Using email templates we created in Google
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And then sending them using those templates and still sending them manually
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Because we wanted to keep the emails personalized
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And even with email templates, this process is pretty time consuming
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If you even, you're copying from a template, you still want to double check
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everything
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It's probably three to five minutes in email
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And if you're doing this at scale, this just ends up taking quite a bit of time
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And it's still prone to error, right? You may copy the wrong template, you may
20:54
forget the swap out of customer name
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And then, you know, it's kind of a mess
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And also at its core, right?
20:59
Sending programmatic emails is just low leverage, right?
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It's not really something that's going to provide CS a lot of leverage
21:05
So we wanted to solve for that
21:08
And then also this last, at the beginning of this year, we spun up a new
21:12
commercial CSM team
21:13
To operate more at scale
21:15
And so that necessitated the need for more automated communications
21:19
So what was our solution here?
21:20
Well, we turned to GainSight for this
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Which was we leverage GainSight's journey orchestrator and email assist
21:25
functionality
21:26
To send programmatic emails at scale
21:28
And this allowed us to build more sophisticated email programs
21:32
And particularly to help the commercial team
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I want to say it's sophisticated, they're still quite simple as you'll see in a
21:37
second
21:38
But it allowed us to kind of chain together multi-week programs, which is
21:42
really important
21:44
So how this looks in practice is, you know, journey orchestrating
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Actually see an example of one of our journeys at the top of the page here
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And what we've learned is that simple workflows work best, right?
21:55
Nothing too complicated here
21:57
This is an example of a three-week kind of new customer after launch
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Campaign that gets sent on the commercial team
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We use query builder and contact attributes to create automatically recurring
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audiences and campaigns
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So these are often set it and forget it
22:13
So there's a lot of scale and leverage you can do by spending an hour or two
22:17
Setting this stuff up and then it just kind of run in the background
22:21
And some examples of campaigns that we send, we do welcome emails to services
22:26
like our academy and community
22:28
Customer onboarding as well as we call cohort based campaigns
22:32
So if the customer falls in a certain cohort, whether it's industry or product
22:37
or product performance
22:38
We can then automatically spin up a campaign for them and just get stuff sent
22:42
to them
22:43
Which is really great and something that we're scaling to all segments, not
22:47
just commercial
22:48
And the second thing was email assist
22:51
You actually see a real example here on the screen of an email assist we do for
22:55
NPS survey responses
22:57
So we send an NPS surveys and twice a year to our customers
23:01
And it's imperative that our CSMs follow up on every customer survey response
23:07
So that, you know, ultimately if you don't follow up and acknowledge and think
23:11
the customer for giving feedback
23:12
They're going to stop giving it so
23:14
But when this is a manual process, it's hard to get to be this at scale
23:17
And so we use email assist to send a CTA once a survey response comes in
23:25
And CSM will just pull up this, it's tokenized with their customer name
23:29
And then they can just insert any relevant comments as necessary and then
23:32
quickly send off the thank you and response
23:36
And that really increased CSM survey follow up from around 60% over 90% which
23:41
was a huge one for us
23:44
And then we also use email assist for promoting marketing events like webinars
23:48
like this or in-person events
23:50
As well to give a personal touch and not simply rely on sort of mass marketing
23:54
emails to do that
23:56
So these have saved quite a bit of time actually, it's kind of crazy to see 3,
24:00
000 get spun up over an 8 month time period
24:03
But, you know, again once you set them up and they run, it really just runs at
24:07
scale
24:08
And it's just a huge benefit to the team and the CSMs love it
24:11
It actually ends up engaging customers who don't, maybe they don't want to show
24:15
up on calls every week or every two weeks
24:17
But they will respond to these automated emails and that's been a big win for
24:20
us
24:21
One of the biggest things we did was deck automation
24:28
And this is something that I'll spend a bit of time talking about because this
24:31
was probably had the highest impact
24:34
It was from a time savings perspective, but I think quite a bit of customer
24:37
impact as well
24:38
Which the problem we're trying to solve here is taking CSMs on average 90
24:43
minutes to create a joint success plan
24:46
Or quarterly impact, which is our version of quarterly business review deck
24:50
respectively
24:51
And this really varied based on your 10 year and familiarity with our data
24:55
And if you were new to move works, one of these decks could take you 3 hours
24:59
It was a huge time suck
25:01
And that meant the decks were very inconsistent from CSM to CSM
25:04
So quality was quite hard to control
25:07
And it meant that customers were getting really inconsistent, you know, QIRs or
25:12
JSPs
25:13
And the success plans are the foundation of our CS model
25:17
We have to, you know, lower success plans to our customers
25:20
And they have to be really high fidelity
25:22
And live with this kind of really inconsistent quality
25:27
Building them was also compounded by internal dashboard or slow
25:30
If lots of CSMs were hitting the same data table to get data
25:34
Of course that table is going to operate a bit more slowly
25:37
And then there is no programmatic ways to insert slides promoting events or
25:42
product updates or customer stories into decks
25:44
Which meant that a lot of our decks were just missing critical things
25:47
Because CSMs, you know, didn't remember that it was stored in some random
25:50
marketing folder
25:51
And so, and you couldn't blame them, there was lots of places to restore it
25:55
And it was just hard to find
25:56
And so this allowed us to make sure that every deck had a certain, you know,
26:00
level of quality and announcements in it
26:03
And ultimately we were spending too much time building decks and not enough
26:06
time preparing
26:08
For these meetings with customers which meant pre-flighting all this
26:11
information with the customer
26:12
Working with them just to refine these plans and presentations to have high
26:17
impact
26:18
And so, you know, ultimately we needed to solve for this
26:21
And our solution that we built, which I'll talk about a little bit in more in
26:24
depth in a second
26:26
Is a fully built automated deck in less than 60 seconds
26:30
We wanted to just make this so seamless, we were able to deliver on this, which
26:34
was really amazing
26:36
We wanted to standardize our JSPs and QIRs, but also still leave room for CSMs
26:42
or customise them as they see fit
26:43
We really don't want you to take the automated version off the shelf and
26:47
deliver it
26:48
We'll deliver you something 80 to 90% complete
26:52
And then rely on you to kind of put that polish on it to make it really
26:56
customer-specific
26:58
We wanted to standardise, we were able to standardise on data and metrics
27:02
So that the standard story and narrative in these decks was quite strong
27:07
It didn't rely on you being an amazing storyteller naturally to deliver a great
27:11
presentation
27:12
And of course, increased the quality of visuals and the baseline storytelling
27:17
Which then freed up CSM time to spend preparing and pre-flating this
27:23
information with customers
27:25
And so, ultimately the solution offered us a significant improvement in
27:28
information and data that we could provide to our customers
27:32
And so, what this looks like in practice is actually quite complex and was a
27:37
huge cross-functional initiative
27:39
But we have a data science engineering team that built a tool called Lego Land
27:46
internally The idea was that each piece of data is a Lego block
27:49
If we could build a modular system of building Lego blocks any way we wanted to
27:54
We had a really powerful tool to operate and provide data reporting and scale
28:00
We then once the team built that solution
28:04
And I'll talk a little bit about how it came about and how we even figured out
28:07
there building something like this
28:08
We then use super blocks, which is like a no or low-code app builder
28:12
Functionally that we use a lot internally
28:14
And that was a partnership with data science, engineering, product management,
28:19
customer success And the screenshot you see is an actual example of what a CSM uses
28:23
They come into the super blocks and they select the org they want to generate
28:28
the report for
28:29
We automate a handful of different reports now, not just these two
28:33
And you select the report you want and click generate report
28:37
And there's like a time period that will come up
28:39
You'll select how long do you want the data to be analyzed for on the deck
28:43
And then it will generate the report for you
28:45
And the benefit is that everything is customized to your account from the
28:48
customer name to their bot avatar
28:50
All the data and charts and graphs are custom to what is at your customer
28:56
Even the configuration of the product changes what we recommend to the customer
29:02
to Do to improve performance of their product
29:05
So everything becomes this quite automated, elegant solution
29:08
And what ends up happening when you click generate report are two things
29:11
One is you get the fully built deck in Google Slides
29:14
And that you can then use to edit and refine
29:17
And then we also send a link to that generated deck into GainSight
29:22
And this last piece was really important as well because
29:25
Especially leaders in the organization were always looking for decks
29:29
They're like where is this QIR deck? Where is this JSP deck?
29:32
I wanted to take a look at this next one
29:34
If there was a customer escalation or a question that came up during an
29:38
executive meeting
29:39
With that account, you just wanted to make it really easy for a leadership team
29:43
to find information
29:44
And so you didn't have to go, you know, you have the whole history of decks
29:48
that are generated
29:49
Inside a GainSight that you can just click on and get instant access to the
29:52
deck
29:53
And this was a huge way and not only just from a time saving perspective of
29:57
generating decks
29:58
But also from a perspective of just finding information internally and being
30:02
able to reference them
30:03
Or even our own preparation that we were doing for accounts
30:07
So, you know, I'll talk in a little bit too
30:11
A little bit kind of how it's all came about
30:13
But this was a huge, huge win and I think there's tools you can buy, a SaaS
30:17
platform you can buy off the shelf
30:18
That do this deck generation as well
30:20
So if you don't have a team internally to build it for you, there's other
30:23
options
30:24
But I think this was a super high leverage thing we did
30:26
That's provided just a massive amount of impact
30:28
And also learned quite a bit on how to talk to customers about data and present
30:34
data to customers
30:36
Now that we have something standard and that we can now measure against it
30:40
So this has actually allowed us to build really great refinements to these
30:43
decks as well
30:44
And the last thing I'll talk about from an initiative perspective that we did
30:48
before getting into some tips on what you can do today
30:51
Is customer education, although not technically like automation per se
30:55
I think this is a digital CS motion that has just yielded massive results for
30:59
us
31:00
So the problem that we are having is depending on CSM knowledge and tenure
31:04
Customers were receiving inconsistent education about our product
31:08
This is natural, if a CSM has been here for two months, you're just going to
31:11
know less than someone who's been here for two years
31:14
And CSM was spending on average over five hours, like five and a half hours a
31:18
week educating customers on our product
31:21
Which was a huge time suck and we didn't realize we were spending this much
31:24
time until we did a time tracking initiative
31:26
And we're really blown away at how much time is being spent here
31:31
And there was no scaled way to teach customers about the product or best
31:34
practices
31:35
So what do we do to solve for this?
31:37
A solution was to build a dedicated customer education function, which was a
31:40
team of one until about two months ago
31:42
And which just became a team of two
31:44
And we wanted to build a multifaceted education approach that had a dedicated
31:49
academy
31:50
webinars, office hours and things that we'll talk about
31:53
In a second, and then we launched a live cohort based training program for new
31:56
customers
31:57
Which we shamelessly stole from Tim Van Luu at Beansite
32:01
With the accelerator program and Tim was very nice to even advise us on his
32:06
learnings Which allowed us to build a really successful program
32:09
And this will call moverx fundamentals
32:12
Bottom
32:14
And this cohort training program, we've done not four cohorts
32:17
And the attendance has grown 3x over time
32:20
So this has been a really strong offering for us
32:22
We get a lot of great feedback from our customers on this program
32:26
We also have a dedicated academy, which is the screenshot
32:29
You see as an actual screenshot of the academy as it looks like today
32:32
Which is important for self-paced learning
32:35
We have dedicated courses by persona, product, we do Quick Start
32:39
Which is kind of an automation that we've just introduced
32:41
Which is you can go from learning about the product to actually doing something
32:46
in it In about 5 to 10 minutes using these Quick Start courses
32:49
Which is really great
32:51
And we also host a series of product webinars in partnership with our PM team
32:57
And those are done on a weekly basis
32:59
And the benefit is that CSM time spent
33:03
Went from over 5 hours a week to half an hour a week
33:08
In the 6 months since launching academy
33:10
Which was just massive in terms of time savings
33:13
And just really up level the quality of education
33:16
Our customers are receiving our product
33:18
So CS education, although not traditionally an automation
33:23
Has done a huge for us to scale the CS team
33:26
And of course we send information about who's signed up
33:30
And who's using it into gain site using an integration there
33:34
And then we also just launched a community using the gain site
33:38
Inside a digital hub product
33:40
Which has some interplay with academy as well
33:42
So lots of ways we're trying to create automations
33:45
And efficiencies between these surfaces
33:47
So these are the four main initiatives that provided impact
33:51
And again I just wanted to throw the impact on the screen
33:53
And outside of just these numerical things and volume
33:57
The actual impact back to business was pretty big
34:01
All these things we calculated from a soft time savings perspective
34:05
In terms of putting a dollar value to an hour that CSM works
34:11
This is about $750,000 in soft savings back to the business
34:16
But more importantly it's reduced our customer retention cost
34:19
Over the over the eight months
34:23
And that customer retention cost reduction has given about
34:26
Two and a half million dollars back to the business
34:28
Meaning it's two and a half million dollars cheaper to retain our customers
34:31
Than it was eight months ago for the business
34:34
And then from there, although we've definitely improved
34:38
Automation and efficiency internally and given money back to the business
34:41
Which was pretty important from our operations perspective
34:44
We've also really improved customer outcomes in terms of now
34:47
We were more communicative to customers
34:50
Success plans are much stronger
34:52
Much clearer signal on what to do and how to do it
34:55
And so ultimately this has been a really successful initiative for us
34:59
What I wanted to end on before opening up for Q&A
35:03
Our steps you can take now
35:05
Obviously if anything is resonated with you
35:08
You may not have all the resources we were lucky to have been
35:10
A company and we have ML engineering on staff to help out
35:14
But there are things you can do today that even can drive impact
35:19
Before you get into things like building automated deck buildings and things
35:22
like that And so I wanted to leave you with six things that you can do
35:26
And the first three are get cross-functional and do it now
35:30
I think you absolutely cannot do this alone within CSOps or just customer
35:34
success You have to be cross-functional here to succeed
35:37
If you're in operations day or you're in customer success and you own these
35:42
initiatives
35:43
Just set regular check-ins with your cross-functional peers
35:46
And product and go to market ops, data science, marketing sales, etc
35:50
And just understand how you can solve business problems together
35:53
You can't really scale your impact unless you bring the whole company with you
35:59
And what's really important is also aligns the company towards customer
36:02
outcomes
36:03
Which is really, really critical anyways
36:05
And so this is actually how we found out our data science team was building a
36:09
deck builder
36:10
Is working with our product team, we're trying to figure out what to do
36:14
To solve some of these problems and we had a conversation with our data science
36:16
team
36:17
They mentioned they were building something for this very specific sales use
36:20
case
36:21
And we started chatting with them and next thing you know, they're building our
36:25
joint success plan on an automated basis
36:27
And developing that product for us, which was just huge
36:30
And we wouldn't have known that if we weren't talking consistently
36:33
So I spend almost half my time just cross-functionally now talking with other
36:36
people
36:37
And just making sure that everyone is aligned on the same outcomes we're
36:40
looking for
36:41
And you do that by figuring out customer pain and customer success pain
36:45
You know, speak with your CSMs and CSM leadership to understand pain points
36:49
There for sure will be open to telling you about it
36:51
And if you're in operations and you don't have regular one-on-one with CSMs
36:55
You should start them now
36:56
My whole regular one-on-one with a handful of our CSMs and not only, you know,
37:00
is it just great to chat with them
37:01
But I understand their pain really quickly and I can also probe kind of
37:05
We know what the pain is with customers and how we can figure out how to make
37:09
improvements to the process internally
37:12
And to our customers and it's really helped create this amazing feedback loop
37:16
That allowed us to improve our offerings and services much faster than if we
37:21
weren't having these conversations
37:23
And a big thing we did was track CSM time
37:26
This was quite controversial when we did it, no one likes tracking time
37:29
Especially if you're not in some kind of like fee-for-service model, which we
37:33
are not But we were able to kind of get the buy-in from leadership and the CSM team to
37:38
do it for four weeks
37:40
This gave us such an amazing data set of where CSMs were spending time
37:44
And that allowed us to translate that pain into business impact, which is the
37:48
third thing here
37:49
In order to secure resources internally, you must articulate the business
37:52
impact to leadership across your entire company
37:55
This is absolutely vital, and so what we did is we used CSM tracking and time
38:00
savings projections to bolster a quantitative argument for resourcing
38:04
And then we combined that quantitative argument with more qualitative
38:08
storytelling about how the pain that we were experiencing internally
38:12
Based on our processes not being efficient, we're actually impacting customers
38:18
And those two things together make a very compelling argument to act
38:21
And it really allowed us to secure resources, and this one time tracking
38:24
initiative, although quite painful for everyone involved having to do it
38:29
We were able to use this data for six plus months to continue securing res
38:33
ourcing to improve customer success sufficiency and automation
38:39
And the last thing I'll end with is just start with one conversation, all of
38:43
these things outside of education, which was separate
38:47
Just started with a single conversation with a PM at Mover, so one of my really
38:52
close colleagues, Andrew and I started having conversations back in August 2022
38:57
about CS sufficiency
38:58
And at the time we were talking things like automated call notes, automated
39:02
decks, sending thousands of personalized emails automatically or all of Patreon
39:07
, they were not in our frame of mind at all
39:10
And our original plan was just to build an easier to read dashboard for CS to
39:14
leverage to create these reports
39:16
And just the more you start having conversations, you just start inertia takes
39:21
over and one conversation begets another, begets another, and if you especially
39:26
if you expand that to cross functional conversations
39:28
You really end up getting a full vision of what you can do in your organization
39:34
and how you can impact both CS and customers in a positive way
39:39
So although this seems like a lot of stuff and it was quite a bit of work and a
39:43
huge cross functional initiative, it all started just with a single
39:47
conversation trying to ask questions and figure out how it can make an impact
39:50
And so you have to start somewhere and so just encourage you if this is
39:53
interesting or resonates with you at all, just figure out a good partner in the
39:57
organization it can be and even in CS and say, hey, how do we start this today
40:01
and start ideating
40:02
and figuring out what you can do? And what was important is that we prioritize
40:08
for quick wins and then use those quick wins to give us justification and
40:11
energy to build on that progress
40:14
So instead of trying to automate all the decks that we were doing, we just
40:17
focused on one at first, which was a joint success plan and we poured all of
40:22
our resources into doing that really well
40:25
Not only did we learn a ton by just focusing on that one deck and getting it
40:28
done really well, because the initial deliverable was such high quality and
40:33
resonated really well with CS, it made everyone really excited to do more and
40:38
made us really motivated to do more as well
40:40
And we could take those learnings and now we work much faster and automate
40:43
decks we probably have five or six different decks now that we automate and but
40:47
it all started with just focusing on one and prioritizing in that done as fast
40:52
as possible
40:54
So as you saw, most of our automated email campaigns are very simple workflows
40:58
and they can be spun up very easily. You know, those email assists can probably
41:01
be done today if you wanted to spend up one to promote something to your
41:05
customers
41:06
So we start simple and just provide lots of quick wins and, you know, wash
41:10
rinse repeats. And then we also focused on other quick wins and I really
41:13
focused on four really big impactful initiatives but we do lots of other small
41:19
ways to be a life improvement that people notice and they really love and that
41:23
's allowed us to continue doing more because we're just not always focusing on
41:27
these humongous things that take weeks or months to get done but we're also
41:31
within those timeframes
41:33
Shipping these small wins. So for instance, we integrate gain site within our
41:37
own product and chat interface so you can chat with our bot internally and ask
41:41
who's a CSM of this account or what's the top ten ARR customers
41:46
And when, you know, what are the all the renewal dates in the next month. And
41:49
that was just a big win. These aren't data points that take people forever to
41:51
find. You can go into sales course, get inside it and get, and get to them
41:56
within a few minutes but it's just so much easier to chat with it in, you know,
41:59
with our chat product. You can take this information and transform it and
42:02
And then we also do lots of automation and we use our Slack as little and
42:09
really every customer has their own dedicated channel the whole team in it. And
42:17
what we do is we use a tool called rattle to send all these notifications. So
42:22
you get reminders on, you know, hey, two weeks until your next QIR is coming up
42:28
or, you know, we send, you know, we have a big event on the website.
42:31
And so you have a big event on November and every person that registers from
42:34
your account, you get a notification on who registered, you know, they're like
42:37
a virtual person, etc. So all these things, you don't save like a ton of time
42:42
on their own.
42:44
But they're all not really a great quality of life wins and that just gives us
42:47
lots of, you know, juice and collateral to keep doing more.
42:52
So read back impact to your organization. You know, you must develop ways to
42:56
track impact of anything that you do and regularly update leadership on the
43:00
impact of those initiatives that you're working on.
43:04
And, you know, we do that using a lot of reports and gains I mean we take a lot
43:07
of data from all these systems or, you know, we're able to track the impact and
43:11
then I take those reports, download them and we do some, some custom
43:15
calculations and Google sheets to build this impact reporting and we make sure
43:19
that it ends up everywhere.
43:21
And it's not to like tutor on horn or say hey we're so amazing but it's to show
43:25
the organization that the investments that they've given and the faith that
43:29
they've given in our team to to go and drive impact is actually working.
43:34
It's not easy getting a machine learning engineer to help at a machine learning
43:38
AI company in the most sort of frenetic and sort of innovative time and AI
43:42
right but we're able to show the impact of having an engineer help us.
43:48
And so, you know, the science team there's lots of data science needs across
43:52
the whole organization not just in CS but our ability to articulate the impact
43:56
and say the resources that have been dedicated this have really been impactful
44:01
and really delivered on on results.
44:03
Just help so, you know, impact reporting makes us way into reports that we do
44:06
for leadership whether it's executive leadership or own sales leadership.
44:11
And channels dedicated to these initiatives with regular reporting. It's almost
44:16
impossible not to know how these things are doing and that's just our way of
44:19
saying look, when we're very appreciative for the resources that were given to
44:23
us, especially cross functionally.
44:24
And we've used those resources and really delivered on impact and that gives us
44:27
the ability, you know, other leaders in the company go oh yeah we definitely
44:31
don't mind giving you more resources because we know it's going to be used to
44:34
drive impact and also teams like working with us because
44:37
we know that we're going to share out the amazing results of the stuff that
44:41
they do.
44:42
So really encourage you to develop these kind of tracking mechanisms and figure
44:46
out ways to update your leadership.
44:49
So that is the presentation I think right on time here so I see some questions
44:53
have come through so Denver do you want me to go through one one you want to
44:58
read them out how to handle the handle.
45:00
So I'll read them out to you. So the first one is are you creating and sharing
45:00
success plans and EBR is the same time and what cadence are using for both.
45:09
Yeah, great question so we for success planning we set a standard to have them
45:15
be generated quarterly.
45:17
And the benefit of them being automated now is we're actually seeing success
45:21
plans being generated more than once a quarter so as a customer starts working
45:25
through the recommendations that we have.
45:28
It's simple for a CSM to spin up a new set of recommendations based on the most
45:32
recent data for that account.
45:35
So we have a standard of quarterly for both success plans and EBRs.
45:40
And typically at the EBR is a good sort of opportunity to generate a new plan
45:45
and kind of get that in place for the executive team at that account so you
45:51
know we plan for quarterly but we've seen since we've automated it we've
45:54
actually see success planning
45:55
be it's about twice a quarter now which is really great to see.
45:59
Awesome.
46:00
Next one is can you expand on your process best practice around contact hygiene
46:04
slash maintenance that facilitates your customer journey campaigns.
46:08
Yeah, this is this has been a topic we were in the middle of cleaning it up
46:12
actually at the moment.
46:14
We for now we have a very simple construct in each account a contact either an
46:20
executive contact or a what we'll call CS contact meeting they're part of our
46:25
court team.
46:26
And that work when we were small, and now there were a lot bigger that's not
46:29
quite working so we're actually working through changing our contact management
46:34
to where each contact gets assigned a persona that they have within that
46:38
company within their domain
46:40
with with a different domains at a company.
46:43
And then also some different granger check to say hey this contact is on our
46:47
court team and they should get an NPS survey but you know they don't want
46:51
access to academy or we can kind of select kind of what we want them to get
46:55
access to. And so I think today we've learned that contact hygiene is actually really
46:58
critical to run these campaigns at scale.
47:01
And so that doing it at scale allowed us to see the problems we had and now we
47:05
've worked to clean that up so actually this in October we have like the whole
47:10
month is dedicated to like new contact management systems are launching a new
47:16
one today for references.
47:17
And then just making sure that that will give us the opportunity to actually
47:20
run more of these automated campaigns. So it's very important we learned the
47:25
hard way of kind of keeping the hygiene okay really limits us here so we're
47:30
investing more there.
47:33
And I think this question is super pertinent not just for what you presented
47:37
but for a lot of AI and that's how did you manage to justify the cost of the
47:40
internal AI and data science teams.
47:43
Or were they already in place and you just utilize them and I guess that's a
47:47
very important question nowadays on how to pay for AI and moving forward.
47:52
Yeah this is where getting data to justify resources is really critical I think
47:56
time tracking for us was just huge because it allowed us one to see where
47:59
people are spending their time.
48:02
We realize that CS and spending lots of time on debt creation, educating
48:06
customers.
48:08
And what this is you can apply it you know it needs pretty easy dollar value
48:12
you know how much you pay your CSM is all in.
48:15
You know definitely use all in pricing kind of you know their bonus plus plus
48:19
benefits and say this is a real cost of business and say look if we actually
48:24
reduce time by three hours if we think this investment in AI can say three
48:28
hours per CSM per week.
48:30
You can scale that out and have a pretty good ballpark estimate of how much
48:33
money you could save and use that to justify new spend.
48:37
So we use it in two ways one is any spin that we have because obviously you
48:41
know call notes they do cost us ultimately we have to call and GPT and there's
48:45
a cost to that.
48:47
But we're able to say well the cost is actually quite minimal relative to the
48:51
benefit we're getting from the business and so having that data was actually
48:55
really critical if we didn't have that call the data for time tracking.
49:00
I think it would have been a lot harder to justify and actually provide you
49:04
know real estimates for the expense so definitely if you don't have those
49:08
figure out ways to get those those estimates because those really where you're
49:13
going to be able to say look here's where we're at today.
49:15
Here's where we think AI will get us that delta right there is going to be your
49:19
time savings and where you can actually show impact so we'll definitely
49:23
recommend you come up with those kinds of constructs to report to the
49:28
leadership team to justify.
49:29
Both the you know if you have to buy something the expense of it but also the
49:32
resource that you need to use internally.
49:34
We do that's why the reporting for us and impact reporting and all this were
49:37
really important.
49:39
We weren't able to deliver that I don't think we would have been able to get
49:42
those resources and understandably so right you know I mean ultimately
49:45
resources are scarce for a reason and there's lots of things people could work
49:49
on at all times so for us this was our argument to the organization to say hey
49:53
we think this is super valuable and here's why.
49:56
And we just consistently make that argument over and over again.
50:01
Excellent.
50:02
The next one is where do you load the slide decks in the game site.
50:06
Is it just the URL or and how are they surfaced to CS to edit.
50:10
Yeah so we the we use an API call from that super blocks app to just send the I
50:16
think we do it via API just send the link over using the gains that API to a
50:22
table that we built in games.
50:25
And so that what we just have a simple table that shows the customer name the
50:29
date the report was generated the report name since they're different reports
50:33
you can auto generate and then the link to the Google sheet the Google slides.
50:39
And then inside that super blocks app that I showed you I can go back to it
50:43
real quick.
50:45
Where it says generated reports here in the middle. That's where the CSM would
50:51
get their link to the slides and those slides are.
50:54
We set the permissions where they get the slides they can edit them directly
50:57
some edit the the deck that we just generate for them.
51:00
Some make a copy of it and edit the copy and then post the copy someplace for
51:05
us to reference but that's how we allow them to edit them directly.
51:10
Excellent the next one I think is wrong customer education how do you measure
51:14
the courses impact and did it really help product adoption the education piece.
51:20
Yeah this has been really interesting I think we haven't made that shift yet
51:24
this is where initially we looked at just getting content in there, making sure
51:28
there is a robust set of content for customers to reference, and then making
51:33
sure we drove adoption of academy.
51:36
I think the impact pieces harder and that's been one of the things that we've
51:40
been working on building which is an understanding of if a customer takes
51:44
certain courses does that have impact.
51:47
In terms of as you mentioned product adoption or awareness.
51:51
So what we did at first is we've been developing those metrics have been a bit
51:55
harder to operationalize is just ask CSM's you know just pulled them casually
51:59
say hey do you feel like your customers are asking more sophisticated questions
52:05
or having better conversations. Or if you sent them a link to academy did you get any follow up questions or
52:08
did you feel at that really helped them and that gave us some qualitative data
52:12
in some indication that we were on the right track so we're still in the middle
52:19
of providing like a full fledged business
52:22
and you know what is the like in downstream business and customer impact, but
52:27
we you know sent some in terms surveys to help us understand a bit that we're
52:31
on the right track so it's I guess for education it's been a little bit harder.
52:36
And something that we are you know our education team is really focused on this
52:40
half spent a big ask for them and so, you know I think we're confident that
52:44
will be some good results based on our you know kind of interim surveying of CS
52:48
M's but something that
52:51
we've got to kind of operationalize at scale.
52:55
There's there's a couple questions on this one fell of how you tracked CSM time
53:02
and was it automated or was it manual to base out for port or do you have some
53:06
sort of reports that spend x amount of time doing this y amount of time doing
53:10
that. Yeah so we just did it in Google sheets we wanted to choose the path of these
53:13
resistance but didn't want to teach people to use a new tool we didn't want to
53:16
buy a configure tool.
53:18
So what we did is we.
53:21
I created we work with the CS in leadership team and we define the categories
53:25
of time tracking customer meeting internal meeting you know deck preparation
53:30
customer education internal enablement you know all those things that CSM to do
53:37
And then it was probably ended up being like 10 or so categories but didn't
53:41
want it to be huge we don't want to like 10 to 12 categories.
53:45
And then we built a sheet that just allowed a CSM they gave them a sheet each
53:49
week and said you know we pre populated the dates in it so that it was really
53:53
easy to fill out.
53:55
And then we use some data validation rules to allow you just to select you made
54:00
a copy of the sheet for yourself.
54:03
And then each you know row is basically the date, whatever activity it was the
54:07
customer was attributed to that allowed us to see which customers are actually
54:12
taking up the most time.
54:14
And then it allows you some side analysis I think one CSM leader that a whole
54:17
analysis of his team and kind of like understanding which customers took more
54:21
time and why that helped with resourcing.
54:24
And then the activity and then the time and we track time and 15 minute
54:27
increments.
54:28
And you just said hey this took you know a quarter of an hour half an hour one
54:31
hour two three four five six seven, you know whatever it was and then you just
54:36
submitted that sheet at the end of each week over to the ops team.
54:41
And then we created that data to report back our goal here wasn't until like in
54:45
analyze any individual CSM it was really to analyze what was happening at scale
54:49
which I think helped us kind of get people bought in this wasn't like a back
54:55
you know back in a way to track
54:56
whether you're doing work and odd is really more like hey we don't really care
54:59
individually what people are doing we care actually in aggregate what the team
55:02
is doing and how much time is taking and so we just went to Google sheet route
55:06
and create a simple template and that
55:08
was to just like remove any complexities of new systems and change management
55:12
and things like that.
55:14
Cool. How did you handle scale given customers the ability to opt in or out
55:18
from having their confidential data sent to a third party AI services and data
55:23
processors.
55:24
So we, we sent out the data processor like a third party to processing
55:28
announcement saying hey we've like, sent it out you know we use open AI but you
55:35
know because of all these privacy rules you know talk you know walk them
55:40
through basically the what we're you know open eyes on using the state of the train
55:45
their models and things like that now in that you get the ability to opt out.
55:50
There are certain even our product uses a lot of these large language models so
55:54
if you opt out or certain features or certain products you have that you know
55:58
don't work or are not going to work as well.
56:00
And we have alternative models we can use based on you know what geography you
56:05
're in or so on so forth but you know we just went through the kind of our legal
56:08
team really handled that and security team handled those communication with
56:12
customers and allowing them to opt out.
56:14
There's a quick generate lots of questions and so our security team leaned in
56:17
quite heavily to hop on calls with customers this is a whole thing and they go
56:21
over the love of the summer where our security team is having lots of
56:25
conversations with customers and just you know letting them know how this
56:28
work behind the scenes that they did it was secure that we had all the security
56:32
things in place there did it was a major train and all those things so
56:37
you know it was a whole process we went through but something we're very open
56:40
with our customers and willing to hop on calls and answer questions and that
56:43
really help I think smooth over any concerns people had
56:47
because we are an product and we this is you know we use these models the
56:50
normal course of our product.
56:52
A lot of this stuff does get vetted during the sales cycle so
56:55
you know the customer goes to a pretty extensive or we go through a pretty
56:57
extensive security with the customer so
56:59
we do benefit in some ways of these questions being answered in the sales
57:02
process and those approvals being done there but
57:05
I think we had to get on the phone with customers quite often this summer and
57:07
just you know walk them through what these changes meant and how everything was
57:12
still secure and up to par and the ways that they had already approved.
57:18
There's a couple more about data privacy like is it HIPAA is what you're doing
57:24
HIPAA compliant.
57:25
If you had a customer who had the follow HIPAA rules would this be okay or is
57:29
that a different set of permissions that you would have to get.
57:33
The product is like in terms of automation stuff we don't really deal with any
57:38
like HR private data that's all stripped out and we are good at science team
57:42
may have lots of masking so the data that we get in CS is already masked and
57:46
remove all this information so we don't
57:48
typically I don't even think the CSC is like a name of a user and like that we
57:52
just see you know user IDs at any any that data is mostly aggregated anyways at
57:58
our level.
57:59
And on the product side itself yeah there's all these permission that gets put
58:03
in place and any integration we have is put on rails so we're only getting the
58:07
data that we need is properly masked that's but that's one of our product and
58:11
implementation team side to manage
58:13
and so all of them each those compliance rules and we make sure that you'll see
58:17
us just doesn't have any access to any any information they don't need to have.
58:22
And we have one minute left so I'm going to combine the last two that we have
58:26
here the first one is any automation ideas for scheduling meetings out of your
58:31
AIPs and also can you explain real quick that it's been creating email
58:34
templates with different tokens to personalize the email versus the automated
58:38
emails generated.
58:39
Oh yeah so the I think what you're asking the second one is like the difference
58:43
in email assist and journey orchestrator and essence right and we use.
58:48
So what we do is if we feel we need CS to make any edits to the email, for
58:53
instance like responding to NPS surveys we actually want you to, you know, a CS
58:57
M to say in that response, you know reference to actual feedback they got in the
59:02
survey. And so that's perfect for email assist we can do things I tokenize the name and
59:06
those basic things so it is personalized but then also, it's like pretty clear
59:11
in the email template that you need to go put in some information here.
59:15
And so, anything that requires any edits by the CSM we use email assist for,
59:21
and that way they get 80% of the template done for them and they just have to
59:26
go on and type us an answer to.
59:29
So if it's more something that we don't need any CSM input in more like these
59:33
like on winning programs are more like hey, it's your first weeks is going live
59:38
You know, please review this documentation or Academy or community or a GOC
59:41
site and come to the next meeting prepared with these things.
59:45
That doesn't need any CSM inputs this is a great example of a journey orchestr
59:47
ator that we can do because you're really just sending something personalized to
59:51
the customer and letting them know what they should do to prepare for a meeting
59:54
and then that way, you know, they show up to a meeting, typically most of them
59:58
do the homework. And we can have more of both conversations so ultimately we kind of bifurcate
01:00:01
them based on do we need CSM to make any edits or can we just like run this
01:00:05
thing because it's more announcement driven or generalized and that's how we
01:00:10
differentiate between the two programs.
01:00:13
Your other questions about call scheduling correct.
01:00:17
Yes.
01:00:18
Yeah, so we're pretty high touch so I think most CSM is managed about 12 to 13
01:00:23
customers on the enterprise side.
01:00:26
I think with our commercial team which are managing more like 25 to 30.
01:00:30
We're looking into, you know, we have some count we have count on the accounts
01:00:34
for them and right now it's just standard in there.
01:00:38
You know, they can send their customers in a normal way.
01:00:41
However, we do use it quite often to do office hours scheduling so in Academy
01:00:46
and also there's a dedicated page for the commercial team I think it's an
01:00:50
academy as well where customers can just go and sign up for office hours and
01:00:55
then they get access to their their CSM or another person that's asking to help them out and
01:00:59
maybe it's not really cool model but just an easier way to contact people if
01:01:03
you need help, you know, at that moment.
01:01:06
But we haven't because we're high touch.
01:01:08
We don't really have a need to do it because we typically have like a weekly
01:01:12
cadence but in these scaled motions like Academy as well as commercial we're
01:01:16
using it more for like an office hours type approach and self service.
01:01:21
Motion for the customer to sign up at their own leisure. So that's kind of how
01:01:26
we're managing it there.
01:01:28
Awesome. Thank you, Philip. This was fantastic. I want to thank everybody for
01:01:32
joining us today. The recording will be up here soon. I know that they'll be
01:01:37
sharing the deck via PDF at some point here to all participants.
01:01:41
Philip have a great rest of your day and we'll talk soon. Appreciate it.
01:01:46
Awesome. Thank you so much everybody. Thank you for joining me. And I think any
01:01:49
unanswered questions, I believe I'll go in the community and answer them so we
01:01:54
'll definitely be in there to answer anything else you have and happy to want to
01:01:58
contact me directly on LinkedIn or through the community
01:02:00
please please feel free happy to some more time chatting with you all.
01:02:03
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