Kristin Swindle, Manager, Enterprise Sales Engineering, shows us how Salesloft AI, including their new product Rhythm, can be the AI co-pilot sellers need to be more effective.
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[MUSIC]
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>> Hello, everyone, and welcome to Go to Market AI,
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the future of your Go to Market tech stack.
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I'm your host, Thera McConnell.
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These days it seems like every company has AI,
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but on this show, we want to go a level deeper so you can see firsthand how
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businesses are actually applying AI to solve your business challenges.
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We're going to go deep into the use cases and showing you live demos of
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the latest and greatest in AI technology.
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Today, I'm joined by Kristin Swindle, manager of Enterprise Sales Engineering
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at Sales
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Loved. Kristin, welcome to the show.
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Thank you so much for joining us.
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>> Thank you so much for having me.
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I'm really excited about today.
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>> Awesome. So first thing,
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can you tell us a little bit about who is Sales Loved?
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What do you guys do and then who do you guys help?
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>> Yeah. So Sales Loved is an AI-powered sales engagement platform where we're
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actually serving every member of the revenue team.
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So you can build pipeline,
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close more deals, coach reps to success,
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but ultimately it's to better serve your customers.
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What I think is really interesting is historically,
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I feel like Sales Engagement has gotten this reputation of just being focused
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on
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prospecting or the SCR motion.
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While that is definitely very important still,
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Sales Loved really wanted to focus on getting out of the mold,
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breaking the mold there,
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which is why we introduced Rhythm in July,
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which we'll talk about today.
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That's the, you'll hear me say a lot, the nucleus of our AI.
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So by leveraging that AI and Rhythm,
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we've seen a significant increase in the impact for our AEs and our other
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revenue
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teams, including our STRs,
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by having that buyer behavior turned into seller action from all the signals
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with the tech stack. So it's really helped them focus on the right prospects,
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the right accounts at the right time to get to those outcomes.
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We're already hearing such an impact of,
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you know, seller saying they're getting more meetings with less or the same
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amount of
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activity. So really pumped about that.
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Yeah, that's awesome.
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I know I'm really excited to see your demo for them because I've heard a ton
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about it.
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I feel like when you guys launched it back in June,
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it, did you say it was June? I remember July, July.
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Okay. I remember just seeing a ton of news about it in my LinkedIn feed.
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So I'm really excited to see the demo.
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So because you touched on a very good point, which is the impetus of the show
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was we're hearing a lot about AI and how you kind of mentioned it.
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It's making sellers and go to market teams better at their jobs with the less
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of an
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effort. And I think seeing that in action during the demo just makes it come to
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life.
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It really starts to connect the dots of like, okay, this is going to make me
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better.
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I job with less time, but how and what does that look like?
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So that being said, I would love to transition into a demo.
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So you can show us sales off the AI functionality, especially sales off rhythm.
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Yeah. So what you'll see in the demonstration today is that we have weaved
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a AI throughout the entire sales off platform from the administrative side to
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the workflow side
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to managing opportunities and forecasts and to the data and analytics.
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So I do want to start at the beginning as we think about where our customers
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start their journey,
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which is usually the configuration building out the processes and the content.
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So one big piece of AI we introduced was our generative AI with our email
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templates
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that really focus on helping to draft email templates for more of those high
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volume outbound
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motions. You'll see here, I put in some inputs as far as the role type I'm
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going after,
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my company name, and any sort of inputs, I just did a write up on sales off,
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but this could be
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value propositions. And then finally, what do I want that call to action to be?
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So as I'm generating this, this is actually going to give me three different
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options that I can
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choose from to either utilize as is, or if I want to make any changes to this,
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I can obviously
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make any adjustments to fit my business or change up the language. But really,
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the goal with that
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was to give a foundation to help ramp our teams quicker and make sure they're
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starting with some
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powerful messaging straight out of the gate. That's really, I really like this.
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I think something
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we've seen a lot with generative AI. And what I love that you've built into
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sales lot is the like
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prompt assist is that there's already pre-built text options that you just have
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to plug in. So
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it helps one, I think, rests with prompting. And some I've seen someone, it sp
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its out three different
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options, which I love. So it's not just one thing that you have to edit. You
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can go through three and
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like kind of mix and match or see what really fits your tone. So giving three
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options, I think,
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is really, really interesting. Yeah, we wanted it to be guided, but to your
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point with having
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some flexibility there with some options to choose from was definitely our goal
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to make sure
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we're matching as closely to give you more of that foundation than you're after
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Very cool. Very cool. So this is really where a lot of it begins, right? It's
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like we're
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we're focusing on the processes, we're pulling in the content. And then once we
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have that,
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then that's where we start having the reps pull people in, start engaging with
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them through the
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workflow. So I want to transition over to the workflow side of things. And
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before I get into
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rhythm, which you've heard a lot about and really again, our center of the AI
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here,
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one thing that we introduced was having what we call focus songs because, you
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know,
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kind of talking about the content, we want to make sure we have that
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flexibility with how people
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like to approach their day. So we still have more of what we're calling our
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structured workflows.
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So maybe focusing in on my cadences for those kind of predefined processes to
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reach some sort of
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end goal that I'm after prospecting, renewal, whatever it may be. And then my
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close, which is
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really it's in the quarter. I want to be hyper focused on just the
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opportunities themselves.
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And then finally, that's where we have rhythm coming to play, which is more of
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that unstructured
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workflow where as we talked about, it's really bringing in all of the signals
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of the ecosystem
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and pulling it into a prioritized workflow here. Very cool. Yeah, so I want to
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talk a little bit
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more around what is making up rhythm, what is feeding it, how is it priorit
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izing? So what we've
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done is we wanted to make sure we were looking at as many different signals as
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possible to prevent
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all that different swivel chairing. So we pulled one of the main things that I
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think a lot of our
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teams have been excited about is third party integrations, taking advantage of
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the tech stack
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you already have. So you'll see DocuSign in here, G2, vidyard, seismic, high
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spec, there's tons of
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others that we have now and that we're rolling out through the end of this year
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and beyond.
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Our goal is really to kind of open that up down the road to have more signals
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ingested.
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And then on top of that, we're also looking at your CRM information. So looking
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at some of the
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opportunity information you have, we're also going to be looking at your buyer
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engagement,
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which is taking action on your emails, what kind of engagement are you having?
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And also the seller
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activity, right? I have a meeting coming up or I just wrapped a meeting and I
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need to be prompted
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for a really thorough follow up. And what it's doing is AI is looking at the op
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information like
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you see here and the buyer engagement and it's ranking those due actions based
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off of the immediacy
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and the impact and prioritizing them on the likelihood for me to get a booked
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meeting,
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an opened opportunity, as well as that deal importance. And I think what's
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really critical to
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call out here that sales off focus is in on is making sure we have that explain
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ability in the
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workflow. So as we're hovering over maybe this opportunity, this is letting me
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know the key factors
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that our conductor AI used to prioritize this at the top from our deal
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engagement score, which
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will talk more about the ARR, the closed day. And then similar with that, with
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the buyer side of
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things, why is Dylan at the top of our priority list from a buyer engagement
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perspective? So I'll
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have all of that insight pulling in here. And this really ultimately helps the
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reps prioritize their
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due activities to help them book more meetings and close more of those deals
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faster.
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That's very cool. I think two things here I really, really love seeing is one.
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I think the use
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case I immediately think of with sales loft and rhythm in particular is you
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mentioned earlier reps
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is this helps SDRs. But I have to imagine there's such a good use case here for
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ops, like a sales
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off team revenue ops where I'm like, oh, you need to build this in dashboards
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anymore. You don't
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have to go into multiple systems to have these dashboards of prioritization. It
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just exists in
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the system that you're already spending a lot of your time outbounding in. So I
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feel like this has
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to stable up not only for rest, but for the ops teams that are helping build
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normally the dashboards
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that they would need from a prioritization standpoint. Yeah, absolutely. And
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then I really do, I've not
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seen the ability to hover and see why something is prioritized. Like, I think
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AI is very cool.
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And it's like, okay, I know it's helping me be better and faster. But to be
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able to see why it's
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sort of unsealed, like, okay, yes, AI is telling me that I should fall with
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Dylan now. But if I'm
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like, I don't know why, like, I'm just, I can jump in and see like, okay, this
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is, it does make sense.
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So unveiling a little bit more behind the why AI is telling you to do that is
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very interesting.
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Yeah, I think another thing too is when you were talking about the rev-offs,
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one thing that I
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particularly seen as kind of feedback is that we think about, you know, the
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buzz is like tech
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consolidation, right? And I think a lot of times we think about tech
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consolidation, sometimes it's
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not necessarily removing something from the tech stack, which does play into
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that. But to your point,
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I think it's like, let's go ahead and take advantage of the tech stack you do
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have. So you do have that
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adoption. I think that's another piece that ops really likes is we bought these
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tools. I want to
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make sure my team's adopting it. And this prevents me from needing to jump to
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those different tabs
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to take advantage of all those different signals. Yeah, and I have to imagine
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even the, the hover
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and telling you why has to help with adoption. Like, I know as a human, if I am
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understanding the
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why behind it, why you're telling me to prioritize one deal over the other or
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one contact over the
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other, that's going to help me from an adoption standpoint, because I trust it.
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I trust a little
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bit more understand why it's asking me to do something or why I am doing
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something. So I have,
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your team did a really good job here, I think, from building in features from
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an AI perspective
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that are going to help with adoption, which is great. I love to hear that. And
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so we'll our product
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team. And the other thing too, that I think is nice about this, as you're
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looking at the why and
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that prioritization is doing it real time. So as things are happening, it's
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constantly adjusting
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that prioritization. Yeah. So I want to show you what it looks like to kind of
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action upon
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some of these different things, specifically in the the rhythm flow here. So
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one that I know has
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been a huge kind of value add for our teams, we've heard a lot about this will
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start introducing
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some of our conversation. AI that we have is the meeting follow up or the
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meeting reminder.
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So let's just say I've already had this meeting with this particular off. And
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based off of the
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prioritization, this is letting me know I should go ahead and send that follow
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up to them right away.
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So when I go to click to action this, those that are maybe already familiar
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with sales
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often confusing just the cadencing functionality previously, we still wanted to
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keep that same
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sidebar experience. But again, this is now looking at everything across the
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ecosystem and prioritizing
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that. So you see it's pulled up my template here, I have my opportunity to
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reference in case I want
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to personalize further. But I specifically want to talk about where we're
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pulling this from. So
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this is where we'll expand a bit into our conversations here and get an
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understanding of what AI capabilities
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we have there. So right now that is located in our I'll tab this down, our
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recap section. So we have
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two main areas here, we have our summary, and we have those action items. So
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the AI is providing
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all of this information. And then we have automation to automatically pull
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those action items into
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this template. So one, making those follow ups really seamless and making the
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rep more efficient.
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But two, where I really think a lot of this adds value is thinking about
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collaboration with either
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handing off to other teams, or maybe as a manager, you know, you don't have the
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time to be everywhere
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at once. So this kind of allows you like a real quick glimpse into how did this
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go? And what is
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the expectation of what my team is supposed to live on as a follow up. So it
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could be really
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impactful from from that point of view. Yeah, I do. I love the use case of AI
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for like summary,
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because I do think there is a great use case for any managers who have larger
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teams.
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Where it's hard to scroll through things, it's hard to digest through all this
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information.
11:50
You're already so busy as it is, I think using like generative AI to have that
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recap is so helpful.
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Yeah, absolutely. I think it's just as we talk about productivity and
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efficiency,
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the more things that you have that can help just say I can focus on the selling
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part,
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right? And more of that human aspect, the better. Yeah, that's awesome.
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Well, let's show it from, you know, we looked more from the opportunity
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perspective. So I'd
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love to show you what it looks like for maybe that Dylan person we saw earlier,
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and we have this
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prompt for the call. So you'll see it's kind of changing my environment based
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off of what that
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action is. So I have my call now prompting. Now it's been replaced with a
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profile.
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And there's a lot of information I won't dig into everything that we have here,
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but there's a lot
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of ways that we can manage our contacts in less time and using the AI to make
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those tasks
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at this list. So as I'm thinking about preparing for this call, some things
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that we'll have in here
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is we'll have out of office detection. So if they're prompted to be on my cad
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ence,
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it'll actually automatically move the due date based off of when they're back
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in the office.
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Oh, that's cool. Yeah. We also have some jobs in your day, which kind of does a
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macro job title,
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says we're thinking about that messaging we saw earlier, we can make sure we're
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aligning it at
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more of that macro parent level to have that consistency. And then we also have
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some other
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things like data enrichment, which is pulling from the person's signature and
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enhancing the data that
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we have. So we always have those up to date information. And then finally, as
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we're thinking
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about, I'm ready to engage with Dylan now that I have this other insight, we're
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also going to be
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able to showcase email sentiment not only in here, but also in our analytics.
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So you kind of know
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how should I be approaching this conversation? Has it been positive as of late?
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Am I getting
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some objections? So it truly helps me restrict strategic point of view. Oh,
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that's super interesting.
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I do really like the sentiment aspect of it. I think especially if time has
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passed after a call,
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you might even forget what the sentiment was. So having that sort of automated
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and AI helping
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me understand like, do I need to approach this deal with a little bit more
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finesse? Is it something
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where they're like really gone, ho, and we know we can push this forward
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quicker? That would be,
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I can see where that's really useful for a seller. Yeah. And the other piece
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too, is as I mentioned,
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it pulls into the analytics. So maybe for that particular seller and that
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particular relationship,
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but I can see how that's trending across my team to see, are there themes we're
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getting a lot of
14:13
objections? Or maybe this individual as a whole is getting a lot of positive
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interactions or
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objections. So it really kind of helps to hone in from a coaching perspective
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too. Yeah.
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Yeah. See, from a manager's perspective, being able to look at rep level and
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say, like,
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hey, are there really common trends with this rep where like there's negative
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sentiment or we're
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not seeing like next actions and all of their calls and being able to use that.
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And then even to
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what you just showed right before this, going into the calls themselves and
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having a recap,
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would help someone like a coaching perspective, a manager perspective, you can
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just get that data
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so much faster and hopefully catch on to any like negative trends that are
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happening and address
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them sooner before it makes a larger impact. So that's, that's great. That is
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actually a amazing
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segue to the next piece of the AI, because just like you're mentioning.
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Yeah. Yeah. There are no, this is, the whole goal here is that this is where we
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're
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making, sending emails, making dials, things along those lines that we're doing
15:09
all of those to drive
15:10
to the outcomes, but particularly to your point, that's really where we can
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start kind of providing
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some insight to leaders. Because as we think about the outcomes that they're
15:19
driving towards,
15:20
you know, you have your goal, you have an idea if you're working towards that
15:24
goal.
15:24
But what I think is really critical is being able to have more of that
15:27
objective insight into like,
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how is this truly trending? So as we think about all that information we just
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talked about earlier,
15:35
helping managers, this is kind of a pulse point, right? Of how am I trending
15:39
towards those overarching
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things I'm trying to accomplish? So for example, I'm in our outcomes dashboard,
15:44
but you'll also see
15:45
this in our, in our deals as well. But you'll see I have meetings booked,
15:49
opportunities created
15:50
and closed one. And each of these have not only a goal, they have what I've
15:54
achieved, but you'll see
15:56
we now have this projected piece in there. So that is actually looking at the
16:00
expected result of this
16:02
particular outcome, if I continue that same daily effort through the rest of
16:06
the current period I'm
16:07
looking at. So this really helps to your point to kind of catch early on any
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trends of like,
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am I am I trending positively towards my goal? And if I'm not, I can see that
16:16
earlier on and start
16:17
to focus in that area of like, let me dig into my opportunities in this example
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and kind of take
16:23
that a step further to see if I can get this back on track and work towards the
16:26
goal we're trying
16:27
to work towards. Yeah, this is really cool in that I know we talked about like
16:31
the manager use case
16:32
here, but I'm circling all the way back to, I feel like ops, like I think about
16:36
our sales ops
16:36
and then the team trying to forecast concrete of like, where are we standing
16:40
and what like,
16:40
what is the outcome going to be? And it's like constant work for them to have
16:44
to do this in excel
16:46
to be able to have in the back end of a system that you're already using,
16:50
helping using AI to
16:52
forecast these things and tell you, hey, you might be coming up shorter, you're
16:55
doing really well
16:55
and not have to have that constant burden on ops, just freeze them up to do
17:00
other more important
17:02
things. Absolutely. And that's really what we're aiming to do is as we think
17:07
about, you know,
17:08
all the various teams, like it's not just the efficiency in the workflow, it's
17:11
making sure
17:12
we're having efficiency from the data from the focus on the coaching standpoint
17:16
, from a focus on
17:17
what needs you, you need to dive into strategically without needing to kind of
17:21
to your point use all these spreadsheets to determine where that focus should
17:24
be.
17:24
That's awesome. So let's take it up of this one where, you know, I'm looking at
17:29
, again,
17:30
these opportunities that are close one. So this is a nice transition into our
17:35
opportunity
17:35
management and our forecasting piece. So I'm in our deals component here, and
17:40
this is our pipeline
17:41
view that's pulling in all the opportunities that a rep is working tons of
17:45
different filters and
17:46
things I can do in here. But staying with our AI vein that I want to hone in on
17:50
is we do have
17:51
something called a deal engagement score. So this is the AI is providing
17:56
insight and the likelihood
17:57
for this deal to in as a closed one based off of recency, frequency,
18:01
progression and engagement
18:03
of the buying committee that I'm working with. So this is a great way to remove
18:07
that subjectivity
18:08
and truly kind of pressure test if this is really going to close. And it's also
18:13
a really great way for
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not only sellers, but managers to prioritize where their focus should be as
18:20
they're trying to get
18:20
things to hit that goal that we showed earlier and our outcomes here.
18:24
I really like this scoring. It's so relevant because I was just talking to
18:29
someone on our
18:29
sales team and they were talking about like when something's in commit versus
18:32
best case and
18:32
I might be like, well, what's the threshold? Like when does something move and
18:36
they're like
18:36
gut feeling? Sometimes it's like I open a prayer and they're just like moving
18:41
from commit to best
18:42
case to have a score that's telling you it just takes that pressure off the rep
18:46
of having to,
18:48
like I'm going to say this is in commit or in best case, but then you have this
18:51
score to like gut
18:52
check in and say like, hey, based on the engagement of this op, we think this
18:56
should
18:56
in commit or alternatively like you're committing this, but like based on this
18:59
engagement score,
19:00
does it feel like this deal is progressed far enough and it's at risk? Just
19:04
like a nice other
19:07
data point that you're not relying on kind of human subjectivity on where it's
19:11
at.
19:11
Absolutely. And you know, that's a good point to bring up. I think that's still
19:15
important, right?
19:15
It's like you've been in the conversations, you have the relationship, but it
19:19
does help to kind
19:20
of balance that like you still want that rep in sight. But to your point, you
19:23
said it perfectly.
19:24
It's a gut check, right? Like, I think it's going well, but this is not lining
19:28
up. So maybe let's dig
19:30
into why it's not lining up and again, start working to come strategize to get
19:34
ahead of potential
19:35
things that are indicating that it might not land where we want it to. And as
19:40
we talk about
19:41
explainability, that's also something we offer with the deal engagement score
19:45
is when I dig deeper
19:46
into this opportunity, I have the deal site that show me why it's been scored
19:50
the way that it has.
19:52
So to your point, you know, I can kind of have, oh, well, I have had
19:55
conversations or I have been
19:56
doing this. I have not been doing this, which we know that does impact that
20:00
likelihood for it
20:01
to close. So it just really helps to be a bit more prescriptive of where that
20:04
focus should be.
20:05
And whether that be from the manager coaching their rep or the rep seeing this
20:09
themselves,
20:10
it kind of gives them some guidance of saying, okay, well, maybe I should reach
20:13
out to my current
20:14
stakeholders about some of these things going on. And then something else that
20:19
sales up will do is
20:20
it will actually recommend suggested stakeholders based off of people you've
20:23
already been engaging
20:24
with and sales off. So you can make sure that you're having like a
20:27
comprehensive look into the
20:29
opportunity and the entire buying committee and really where everybody fits in
20:33
that, in that
20:34
buyer cycle. So nothing's fallen through the cracks here. This part is really
20:38
cool. I feel like using
20:39
sort of like a recommendation AI, especially as buying committees have gotten
20:43
so much either bigger
20:45
or they're changed. Like I know we're hearing from sales all the time, buying
20:48
committee is
20:48
at what it used to be. There's more people. They have different use cases.
20:53
Having a system in the
20:53
back end that's learning this as you have more opportunities and digesting that
20:57
information and
20:57
then being able to say like, Hey, you're missing this person in your deal and
21:00
you haven't engaged
21:01
with this person. I think it's so useful as times are changing so quickly, like
21:06
things have just
21:06
changed so fast, having AI on the back end to help keep up with that. This is
21:10
so useful.
21:12
Yeah, I think even keeping up with them like pulling them all in, but I think
21:17
it's also you can
21:17
kind of see if interactions are trending one way or another with the
21:21
individuals to like, Hey,
21:23
this is supposed to be my champion, but they dropped off or this is my decision
21:27
maker.
21:27
And you can kind of see as a hover over it, it disappears, but right above you
21:30
can kind of see
21:31
meetings or calls I've had or whatever it is, what it allows you to kind of get
21:36
that really
21:36
granular focus on the stakeholders as well. Very cool. So really the I wanted
21:43
to start with
21:44
the pipeline because the importance of having this up to date and really make
21:48
sure that you're
21:49
aligned with all the notes and what's going on is critical because that is
21:52
ultimately what is
21:54
feeding our forecast here. We're ingesting that opportunity information to
21:59
really kind of align
22:00
those numbers that we're using to make our call. So there's a lot of insight in
22:04
here from a
22:05
forecasting perspective that you can utilize, but the one that in particular I
22:09
want to focus in on
22:10
is, hence the name, our AI forecast. And this is actually using the AI to score
22:15
the probability
22:16
of a deal being a close one during this current quarter based off of how
22:20
similar ones have
22:21
behaved in the past that you've had. So when you think about forecasting is one
22:26
of the most
22:27
difficult things to do in getting it right. So by having this come into play
22:30
and like that gut
22:31
check we talked about earlier and removing the finger in the air, I do have
22:35
some triangulation
22:36
metrics. So this is a really nice insert here just to make sure that again, I
22:40
have a more subjective
22:41
metric in the triangulation. So I'm feeling really confident in whatever call
22:45
that I'm making on my
22:46
forecast. Yeah. So I'm hoping that you saw that we really focused on making
22:54
sure that AI is again,
22:56
we've threw all out the platform, but it's small ways as well as in Lord ways,
23:00
because ultimately,
23:01
we want to make sure that this is all helping to get to whenever outcomes you
23:04
're trying to achieve,
23:06
but making sure it's in the most impactful and efficient manner that you
23:09
possibly can.
23:10
Yeah, this was great. I really appreciated this demo, Kristen a lot because you
23:15
mentioned the
23:15
very beginning of the call. I think sometimes there's a perception that sales
23:19
loft is like for SDR
23:21
teams to prospect, which obviously it is and you guys have AI functionality
23:24
like that generative
23:25
AI email builder that's going to help them. But being able to see all the ways
23:28
through and see
23:29
how it's managing entire deal cycles. I knew based on what I'd heard that you
23:33
guys had some really
23:34
cool AI stuff for like the entire sales process. So it was great to see it in
23:37
action and I appreciate
23:38
you showing it to us. Yeah, of course. Thanks for letting me spend the time to
23:41
show y'all.
23:42
Yes. So with that being said, demo is wrapped. I want to move into our
23:46
lightning round Q&A.
23:47
So Kristen, I have a couple questions for you if you're ready. Yeah, let's do
23:51
it.
23:52
So the first is how long have you guys been building AI into sales loft?
23:56
Yeah, so we've actually been building AI in the platform for years. 2018 is
24:04
when we introduce
24:05
hot leads, which I should have showed you the demo, but it's basically using
24:09
scoring through
24:09
the email interactions and the live website tracking to provide notifications
24:13
that, hey,
24:14
you have a hand raiser, you're more likely to get a meeting with them. Go ahead
24:17
and give them a call.
24:18
But as we think about just any AI that we're introducing into the platform, we
24:23
've always thought
24:23
about jobs to be done. So how does AI help a user do what they need to do to be
24:29
successful in their
24:30
job? How do we see better outcomes? But I think the most important thing as we
24:34
think about
24:36
all the AI that we built and we're building is that we always want it rooted
24:39
around value,
24:41
explainability in the workflow, like you saw earlier. But most importantly,
24:44
that we're grounding
24:45
it in the AI ethics and responsibility. That's critical to us. That's awesome.
24:50
You guys have
24:50
been thinking about it for a while. And I think with the explosion in
24:53
popularity as of late,
24:54
but you guys have been thinking about it for a long time and that you've
24:56
already,
24:57
it sounds like you're a step ahead of the game and you're thinking about this
24:59
ethically from a
25:00
use case perspective. So that's amazing to hear. Yeah. And then Kristin, what
25:06
you showed today in
25:07
the demo with Sales Off Rhythm is this generally available now for customers?
25:11
Yes. Everything that
25:12
we have shown is GA right now to all of our customers. Awesome. And speaking of
25:17
customers,
25:18
who are a few of your customers that are benefiting from Sales Off's AI
25:21
functionality?
25:22
Yeah. We have a ton of different customers. As I said, we've had AI for a while
25:28
in all these
25:28
kind of little or large places. But I would say, when it comes to rhythm, which
25:33
is that main release,
25:35
again, we had in July, all of our Sales Off customers are now on the rhythm
25:40
experience using
25:40
that conductor AI. And the crazy thing is, is I kind of talked about getting
25:45
the meetings with
25:46
more or I'm sorry, with less or the same activities. But we've already been
25:50
hearing improvements from
25:51
sellers across saying that they're saying a 20% decrease in their sales cycle.
25:55
They're seeing a
25:56
25% increase in their closed one ops. And we've had a bunch of different quotes
26:02
, but one of them in
26:02
particular, a Moody's Analytics rep said, you know, cadence equals prospecting
26:08
rhythm equals
26:08
making money. And I thought that was a really nice way to think about why we
26:12
focus on rhythm is,
26:14
again, it being outcome driven and prioritizing those things to do so. Totally.
26:18
So if you're a
26:19
sales off customer, you're benefiting from AI. It's been in the product for a
26:22
long time. You
26:22
have access to it. You're going to get the benefits. Yes. Exactly. And then
26:28
Kristen, what is next in
26:29
your AI roadmap at Sales Off? Yeah. So we just announced our vision for the
26:35
future at our sales
26:37
love on tour in London. And really it's connecting the data insights to actions
26:41
in the platform. So
26:42
again, thinking about rhythm, that created an action engine, which was that
26:46
better AI powered
26:47
workflow more for those individual contributors, like our SDRs, our AEs, our
26:51
customer facing teams.
26:52
But wherever we really start pivoting in owner focus, as we look ahead, is an
26:56
insights engine that
26:58
empowers the middle lines, look, our sales managers, so they can better use the
27:02
data to impact their
27:03
team. So to give you an example, let's say that the data shows that when there
27:08
's less than four
27:09
stakeholders on a deal, there's a 30% lower win rate. So the AI could then
27:14
suggest, hey,
27:15
with these calls you have coming up, they have less than four stakeholders. We
27:19
recommend you add
27:19
these particular stakeholders to increase that likelihood. Or maybe the rep is
27:24
bringing up
27:26
budget in a discount in a budget conversation. And maybe the data showing that
27:31
his pricing is
27:32
usually 12% lower. So the AI could then recommend for him to get a refresher
27:37
enablement training
27:38
on pricing and discounting in general. So really, the next evolution is taking
27:43
that data set of
27:43
that buyer seller interaction we were talking about across the ecosystem. The
27:48
resulting outcomes
27:48
that we're getting and really understanding what's driving those outcomes. But
27:53
I think the critical
27:54
part here is we think about that evolution is that this really only works if
27:58
our sellers are
27:59
behaving in the right way to get that meaningful insight, because if they're
28:02
doing the wrong things,
28:03
that insight's not going to be very meaningful. So that's where rhythm is
28:07
really coming to play,
28:08
kind of being the catalyst is because it's guiding the sellers to have the
28:12
consistent good
28:13
behavior that we want. That's enabling that insight to determine what works,
28:18
which is then being fed
28:19
back into RITA. That's amazing. And then last question, Kristin, are there any
28:24
other AI-powered
28:26
products that your go-to-market team is using that you want to give a shout out
28:29
to? Yeah, so I
28:31
think what a lot of people are using, we definitely use chat GPT a lot as a
28:35
brainstorming partner.
28:37
I've seen our teams use it as maybe revamping some discovery questions or maybe
28:42
even holding
28:43
it further based off of persona and maybe how you can reframe things there, or
28:47
maybe even getting
28:48
further inside it, to specific personas in specific industries. So that's
28:52
really helped to write some
28:53
granularity there as we're thinking about the discovery side and continuing
28:57
that. I know a few
28:59
have also used perplexity to help summarize like we use 10Ks and really trying
29:04
to grab those key
29:05
items. Again, as we're coming with a strong point of view as to how we're going
29:08
to benefit them,
29:09
that's been a really big one to help with the efficiency. And then some tools
29:14
to help beef
29:14
up the emails. We show our agenda of AI, but I think there are some really
29:18
great partners like
29:20
Lavender that uses AI to recommend how you can tweak and clean it up further to
29:25
make sure,
29:26
again, you're having most impactful emails. So you have the data and now we use
29:30
that to kind of
29:30
shave it down, tweak it, change up some of the verbiage of what usually lands
29:34
from an AI perspective.
29:36
That's awesome. I think perplexity. I've heard our sellers say that that's been
29:39
a huge benefit to
29:40
them as well as they're thinking about what to send and summarization. So it's
29:43
great to hear
29:44
your teeth is benefiting from that as well. Well, Kristin, thank you so much
29:49
for joining us on
29:50
GoToMarket.ai today. I did really enjoy this demo. I learned a ton. So I
29:53
appreciate you being here,
29:55
and thank you so much. Of course, thank you for all the time.