Latest / The Prompt / Ep. 556 | AI and ABM: How to Build Smarter Target Account Strategies

Transcript

Ep. 556 | AI and ABM: How to Build Smarter Target Account Strategies · The Prompt

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  This is on base your one stop shop for solving your most
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  pressing B to B go to market challenges.
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  Each week, host Chris Moody and Paul Gibson talk to sales and
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  marketing leaders to get you in depth insights and creative
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  strategies to set your revenue teams up for success.
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  Hey, everyone. Welcome back to the Home Based
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  Podcast. I'm Miros Chris Moody, and today
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  I'm very excited to have Jillian Wellis with us to talk about
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  AIABM and the secret to unified target account strategies.
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  Jillian, thanks for joining us today and welcome to the show.
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  Thank you. I'm happy to be here.
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  Well, it's good to see you. We were talking before we hit
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  record. I've seen your name pop up and
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  very great circles at Demand Base about the incredible work
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  that you're doing with your account strategies and
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  everything you're doing in marketing.
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  But before we get into that, we like to start with you telling
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  us a little bit about your journey and what led you to what
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  you're doing today. Yeah, so my journey is kind of
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  unique. My undergrad is and graduate
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  degrees are from Texas Tech. I have an undergrad in
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  advertising and business, and then my masters is in mass
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  communications, which it is basically data analytics before
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  it was a field of study. So that's kind of how I ended up
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  in like the data world. So when I started my career, I
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  actually was at heavy equipment, so I worked at two different CAT
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  dealerships doing data and analytics.
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  I always sat in the marketing team, but I got a lot of
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  exposure to different sides of the business.
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  And as I grew in my career from heavy construction, then I
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  transitioned into a fintech, I was always the only person in my
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  role. So like I got to build on and
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  I'm when I say only person, I mean the first person.
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  Like nobody had ever had that job before.
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  So I got to build on what was working, what wasn't working,
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  and kind of pivot. And then I was at the fintech
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  for about 3 years doing all things data science, analytics
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  for products, marketing and sales and operations has always
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  been a part of my role, but it was never my job.
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  Like it was always like, oh, we need to report on this, but the
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  data doesn't work, so how can you fix it?
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  So when I transitioned over to Al Golia, I was joining a much
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  larger team where we had specific people that would do
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  specific jobs. So my role when I came on here
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  was to be like the manager of all of our marketing data, which
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  transitioned more into an operational role.
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  And so I kind of went away from doing data science and more into
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  what's underneath the hood. Like you can't do data science
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  unless the data underneath it is good.
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  So I kind of, I felt like I just rambled a little bit there.
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  No, that's perfect. I mean I'm curious about kind of
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  two angles with that. The first is the intersection of
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  account based go to market strategy and AI because it can
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  be blurry these days. So I'm curious about your
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  interest in that. And then the the second part of
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  that is about alignment. So with data and looking at
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  analytics, we know that the metrics that matter drive the
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  behavior. So if the we have the wrong
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  metrics for sales, we may not be getting sales to do what we
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  want. If we have the wrong metrics for
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  marketing, we may be high fiving at the bar, hitting weed goals
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  when nothing is qualifying down. So I I'm curious about those
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  two. So it's kind of the the
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  intersection of account based go to market in AI and what makes
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  you passionate about that and then how that pulls through into
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  solving alignment. OK.
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  So let me tackle the first one, which is actually kind of an
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  interesting story because I originally was not supposed to
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  be doing anything with a BMABX anything.
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  And it was like we had kind of a shifting of priorities.
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  People were promoted into different roles.
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  And me being like the operational data person, it was
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  just like a natural transition. Hey, we're switching from an XQL
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  model to an ABX model. How do we do this?
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  How do we structure it? Can we get the right people
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  involved and can you build out the journey stages?
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  So for me, it was, I'm always trying to grow and learn and it
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  was new. Every single other company I've
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  worked for has not been account based.
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  It's always been how many leads do we need to meet our, our
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  goals? How many, what's our conversion
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  rates? It was never OK, there's X
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  people at these accounts that we need to close.
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  So we need to go after accounts like this.
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  Like the account always plays part of the strategy.
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  But you know, traditional marketing is more focused on
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  people and their roles and personas.
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  And then I kind of transitioned over to as a company, we moved
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  from XQL to ABX and qualified accounts, which was a really,
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  really interesting and fun journey.
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  And it also had a lot of change management involved.
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  And so you asked me about the alignment between sales and
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  marketing. And you can't do it without
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  that. You just can't.
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  Marketing can try to set all these goals and all of these
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  things, but sales is the one selling the thing.
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  They're doing the actual work, you know, So you have to be
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  aligned with them, and it's really critical to have that
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  alignment. Yeah, I totally.
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  And that brings me to target account list.
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  Let's talk about Tao. Oh man, my brain went salt and
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  pepper. Yeah, like let's talk about
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  there's a remix there. Let's talk about Tao.
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  So OK, the the the Tao target account list often is terrible.
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  Sometimes it's just sells saying here are the 100 biggest
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  accounts in the world, let's go get them.
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  And then other times there's no collaboration at all and
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  marketing just says, here's the list, go get it.
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  Not aligned in either of those scenarios.
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  But I'd love to hear your thoughts around target account
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  list and why that is so critical for account based and go to
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  market success. Yeah.
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  So you're right. A lot of times there's very,
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  very different opinions on what a target and countless is and
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  what the approach that we took was.
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  Basically, let's look at our historical data, what accounts
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  are we winning with, what do they look like?
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  And that's kind of your basis for your ICP.
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  And so typically I hear people use ICP Intel interchangeably,
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  but it's not really the same thing like the base of it, your
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  ICP is all right, these are good fits for us, but then your
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  target account list should be a subset of that and everybody
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  should agree on it. So we're a big, we go after
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  e-commerce companies. That's just part of our bread
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  and butter. So it's no surprise that that's
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  part of our ICP when you get down to the actual target
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  account list. Now we've definitely iterated
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  and I highly recommend iterating to anyone going down this path
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  because you're going to learn a lot of things and you're going
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  to think, OK, well, maybe these aren't the best fit accounts.
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  So the best way to do this is get in front of sales early.
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  Make sure that before you're officially going live with your
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  list, they approve it. If they don't approve it, if
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  they're not on board with the strategy that marketing puts in
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  together, then then they're going to be like whatever
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  marketing is doing a thing again, let's let's do our own
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  thing. We don't care.
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  So I think making sure that they're alliance is really
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  critical. And also we have sales OPS and
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  then we have marketing OPS. We all sit under Rev OPS, but
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  what I learned during this entire iteration process is that
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  you don't have to stay in your own lane.
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  In fact, my counterpart in sales OPS, he doesn't want to be the
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  middle man. He's like, you own the towel,
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  you talk to sales, I don't want to do this, you get it done.
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  So I'm not the bottleneck for you.
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  So typically what I recommend doing is is you got to have a
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  kick off call. Everybody hates a kick off call,
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  but you kind of have to, you got to bring them along.
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  You got to make sure that everybody is on board and you
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  got to listen to their ideas and then bring the data.
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  So bring a list. These are the ones that we think
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  should be on the target account list.
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  Give us feedback. The more feedback the better.
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  We've implemented a lot of ways that our sales can also
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  contribute to the towel by operational fields and
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  Salesforce. If they're going through their
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  accounts, they're scoring them, they're doing whatever they
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  need. They can check a box that'll
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  then tell me, hey, this account needs to be on our Tel list next
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  quarter. Yeah, I love that.
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  And you know, I have a follow up on the kick off call because I
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  do think there's that moment of anxiety for a lot of marketers
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  when they actually do try to facilitate or organize a kick
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  off call. And then it's we're going to go
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  in, they're going to throw tomatoes at us, you know,
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  whatever that feeling is. But what does a good kick off
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  call look like? I don't if are there any kind of
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  agenda items that you need to hit every time or a tone that
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  you need to set or something you send out ahead of time to set
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  context. Just knowing that we usually
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  have sales and marketing that's they aren't talking enough in
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  any organization and then they're coming together on
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  whatever cadence for a kick off call.
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  What should that look like? Yeah.
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  So I think honestly a project plan whenever you're doing any
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  kind of big role roll out, whatever it is.
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  But for, for this, for us, rolling out ABX was huge because
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  it was a big change. We're going to be qualifying
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  accounts. We're not going to be counting
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  how many XQLS we get anymore. So it's huge.
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  So the earlier you get that in front of them, the better.
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  So yes, project plan with clear, we used to do racing, now we do
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  rapid but clear roles and responsibilities of who's doing
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  what, who is going to look at the list and approve it?
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  What eyes do we need on these? Like who's doing the next step?
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  I always say failure to plan is planning to fail.
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  I'm that kind of person. So with the kickoff call, I put
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  an agenda in the kickoff call. Hey, this is what we're going to
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  do. We're going to talk about goals.
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  We're going to talk about the stakeholders involved.
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  We're going to also talk about, hey, am I missing any
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  stakeholders? Like are there other people that
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  need to be a part of this? And I'll get to that more later.
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  When if we talk about like customer strategy, because we do
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  have a different strategy for prospects versus customers.
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  And for prospects, we don't really talk to CS teams.
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  We talk to sales like because they're the ones typically like
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  they're the ones that are selling, right?
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  So an agenda, yes, if there's any data that like say I have an
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  idea or hey guys, I think this should be our ICP.
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  This is the data that I've pulled.
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  Here's the reports here in dashboards.
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  Send as much of it out as possible beforehand, with the
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  caveat that you know that people probably aren't going to read
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  the e-mail beforehand because, I mean, we live in this corporate
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  world where most people don't really read the emails.
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  I don't know, is that bad to say?
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  No, I think it's true. We're letting AI do that now.
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  It's just where where we're headed next.
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  But yeah, we used to have pal, it was purpose, agenda, outcome
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  that we used when I was at Topo. So very similar to your set up
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  there, like make sure everyone understands what we're trying to
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  accomplish, what we're going to talk through and what we're
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  working towards and then having those data-driven conversations.
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  So I think that's a great approach.
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  Love that. Not the biggest fan of project
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  plans, but we see their importance.
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  I'm a. Messenger.
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  Nobody likes them until you're on a project that's going to
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  crap and you're like, where's the?
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  Project plan. Yeah, yeah, it's kind of a thing
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  where you know, you have to do it.
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  It it's it's like the it's stretching before you play a
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  sport, right? Like not the most exciting thing
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  in the world, but once you get hurt a few times, you're like,
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  yeah, that's pretty important. So I'm with you on that for AI,
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  how is AI changing the way you approach and we approach account
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  based and go to market strategy. So this could be the positive
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  and the negative, either or both, however you want to tackle
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  it. I mean, I think it's changing
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  the way we work and and many different aspects because it it
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  helps us prioritize accounts better, it helps us within
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  demand base. You can build a bunch of
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  different predictive models that use AI and our, our sales teams
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  are utilizing them for prioritization.
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  Like if our models say that they're more likely to become
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  pipeline or a better fit for a customer, then we've we've
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  trained the sales reps on going after those accounts first.
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  It also helps with our journey stages.
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  And I feel like we're probably only scraping the surface of
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  what we can do because AI coming to organizations is kind of
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  newer. I mean, I'm very, very grateful
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  that I work for an organization that is fully supportive of AI.
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  Like I'm on the Velocity Squad where we we have meetings that
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  we talk about, OK, how can we use AI internally?
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  Like our product, yeah, it's already got AI, but we
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  internally, how can we use it to help our workflows?
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  How can we use it to not just prioritizing accounts for sales,
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  but also from the operational side, how can I make sure that
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  sales knows what they're doing in an strategic manner?
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  So documentation, I tell ChatGPT, this is what my journey
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  stages are in demand base. This is what I'm doing.
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  Help me come up with a how to guide for sales like it's great.
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  Yeah, I love that too. I've used AI tools to also help
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  with meeting prep and tell me what this person's typically
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  motivated by. Give me a little bit about their
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  personality. Just a lot of the context
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  setting that I think is really important.
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  One thing that that I worry about a little bit, as we talked
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  about this, we need to tackle how we're staying aligned as the
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  technology evolves with AI. The thing that I can sometimes
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  be concerned with is if there's a tendency to put infinite trust
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  into technology, I worry that many marketing and sales teams
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  are going to fall in the trap of talking less, even though we
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  should be talking more about how this is changing.
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  Because that's the thing, right? Like, yes, we can get a better
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  prioritized list. Yes, we can get more efficient
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  work flows. Yes, we can automatically build
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  campaigns based on desired outcomes.
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  All of these things are great improvements.
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  We're helping to drive that, you know, this, we work together.
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  So that part is awesome. But I, I do worry about the
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  human element a little bit. So I, I'm curious how you're
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  tackling that to keep sales and marketing together knowing that
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  we might not talk as much based on getting things solved auto
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  automagically? Yeah, well, and you, you also
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  brought up a really good point about too much trust in AIAI can
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  be wrong. Like my boss always says trust
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  but verify. And that's what you have to do.
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  Anything that you run through AI, you can't just blindly trust
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  it because it could be very, very, very wrong.
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  It has pulled random data from you before.
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  And I'm like, where did you get this data?
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  And OK, so one example I and it's kind of hilarious and scary
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  at the same time. I gave a very specific task.
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  I said give me this thing. It said the nearest Sonic to you
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  is in the colony. And I was like, I'm not really
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  sure why you're giving me a Sonic.
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  And then I said, I think you misinterpreted the ask.
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  And then it said maybe we need to work on your expectations of
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  my output. And I was like, it's passive
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  aggressive to me now. Like, OK, so I closed it out.
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  I started a new model, I started a new chat and then it gave me
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  what I was asking for. But that's just one example of
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  when it can be off. So yes, you can't not
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  communicate with sales just because you're using AI.
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  So we have meetings with them. We have check in calls.
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  The way our business is segmented, we have Amia and Amir
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  and there's different different leaders of each org.
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  Like I need to make sure that I am aligned with them before any
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  huge marketing effort goes to say, hey, have you seen this?
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  Are you good with this? Because AI and just quite
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  frankly, data enrichment, it can also be wrong.
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  Like you got to make sure you are looking at the correct data
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  point and you're validating it and you're not just blindly
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  trusting. Yeah, I think the notion trust
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  but verify is a really good one. I've run into those situations
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  too doing account research. We have some that's in the tool,
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  but I, I was doing a little bit of a test to see what I could
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  get from Gemini versus Chat GPTI was just comparing the two at
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  the time. And one of them told me, here's
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  the CMO, here's what they care about.
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  That person had never worked there and there was no
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  explanation of why it was a direct competitor.
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  There was no explanation of why. And then I say, hey, I think you
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  missed that they actually work here.
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  And it was, you're exactly right.
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  We fixed that. But you're going, oh, man, what?
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  How many other things are we assuming are correct and we're
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  not taking the time to go through and verify?
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  And even last night I, I got in a fight with one of the AI tools
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  and it was telling me that my request was violating their
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  content policies. And there was nothing
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  controversial at all about the content policies.
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  So I was trying, pretty curious and stubborn.
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  I was trying to understand what am I doing wrong and it wouldn't
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  tell me. And it said I can rephrase that
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  for you. I said great, rephrase and
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  rephrase. Content policy, potential
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  violation. OK, rephrase it where it's not a
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  content policy violation. Content policy violation.
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  I think you're mistaken. This is not a content policy.
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  That's great. You could report that here.
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  Okay, just start over. Make me an image that I can use
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  on a slide that has creativity and big words.
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  Content violation. I'm like, I can't use the word
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  creativity. So it's like me yelling at the
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  wall, which there are times where those things are going to
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  happen. But if we're not doing that but
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  verify step, yeah, it can be very problematic to walk into
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  that kick off meeting. So we found some great data and
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  then you have all the sellers looking at each other and going.
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  That never happened. Yeah, absolutely.
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  Now you you can challenge it and be like, this does not violate
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  it. I've had that before and I'm
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  like, it doesn't violate it. And it's like, Oh yeah, you're
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  right. Here's your Studio Ghibli
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  picture. Yeah, I couldn't get around it
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  last night. And then I, you know, I did have
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  that moment where I stare at the clouds and just think, man, I
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  could have built this 50 times over by myself.
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  So like, I love using AI tools to help me with creativity, but
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  every now and then you'll run into one of those loops.
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  And if you don't know how to circumvent it and.
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  And it just makes me think of, you know, quotes we've had from
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  customers where I don't ever want sales to come to me and
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  say, why'd you pick this account?
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  Right? To your point about the Tau, you
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  have to do the verification step and make sure.
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  So I think that's a a great lesson for all of us.
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  Let's talk about leaders. So for the leaders who are
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  listening, how should everyone be approaching the integration
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  of AI into their strategies without over complicating the
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  process and making sure that we're taking full advantage of
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  what AI can help us do? I think that you got to start
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  small, like don't try to boil the ocean, start with a use
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  case. Honestly, what I really like
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  about what Algolia has done is as we have organized a velocity
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  squad so people can start bouncing ideas off of it.
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  We can start pilot groups. We can get people that are
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  really passionate about learning new tools and figuring out new
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  things and just you got to start with the basics, whether it's a
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  specific use case, you get your hypothesis, you run it through
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  and then you see if it's successful.
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  Don't try to use AI to automate all the things when you can't do
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  that yet. You know what I mean?
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  Does that make sense? Yeah, it totally does.
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  And I mean my personal gripe, which I think we're doing a
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  solid job to make sure this is not the case internally at
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  demand base. So, you know, demand base
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  excluded from my personal rant, I think that many instances when
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  we talk about AI as marketers, we're really talking about
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  efficiency and solving things that we don't want to do.
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  So it's how can I fast track these things?
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  Or man, I need to be more prolific on LinkedIn.
• 20:06
  Write me this great post. And then they all look the same
• 20:09
  and they all have the same emojis and they all have the M
• 20:11
  dash and the poor M-I mean, talk about a victim and the evolution
• 20:15
  of AI, the M dash, which is such a great.
• 20:19
  It's a great character. Yeah, I know maybe this is the
• 20:24
  movie script we write, the revenge of the M dash or
• 20:27
  something. But I think there needs to be
• 20:30
  more of an emphasis on the creativity and the strategic
• 20:35
  side of how we use AI. Because it's certainly going to
• 20:38
  check a lot of boxes for solving for efficiencies and saving US
• 20:41
  time and doing things easier and getting rid of clicks in any
• 20:45
  tool. But at the end of the day, it's
• 20:48
  going to be harder and harder to win.
• 20:50
  I mean, I, I just recorded one this morning about how no one's
• 20:52
  clicking on anything in search now the zero click research
• 20:56
  that's starting to happen. So if we think about that, my
• 20:59
  brain is wanting to solve for creativity.
• 21:01
  So I didn't ask a question. This is a very poor job as a
• 21:05
  podcast host. But if you have any reaction to
• 21:08
  that, it's just something I think about a lot, right?
• 21:11
  Like I, I think for our audience, especially if we're
• 21:14
  selling to anyone similar to people like us, great creative
• 21:18
  stands out, impactful messaging stands out, visually compelling
• 21:23
  design stands out. And those things aren't talked
• 21:26
  about as much with AI in the circles I'm in.
• 21:29
  No. And I also think that one of the
• 21:31
  things that's kind of missing is the acknowledgement that you
• 21:36
  can't automate something or you can't fix something if there's a
• 21:41
  broken process. Even before AI was as widely
• 21:45
  used, every company I've worked with, there's always been one
• 21:48
  leader who's like, there's a tool for this.
• 21:50
  There's a tool for this, Let's implement this tool.
• 21:52
  You can't buy technology to fix something if the underlying
• 21:57
  foundation of it is crap. You know, like if tools aren't
• 22:00
  going to fix your broken processes, you have to make sure
• 22:03
  that you have everything established in a way that makes
• 22:06
  sense and that you stand before you can tell an AI tool to fix
• 22:11
  it. Does that make sense?
• 22:12
  Oh, it makes a ton of sense. Yeah.
• 22:14
  I was just writing in my notes. Grab sound bite that ends in
• 22:17
  crap. Yeah, Yeah.
• 22:21
  It's such a good point because the notion of garbage in,
• 22:24
  garbage out, I think we treat that like it's antiquated, you
• 22:28
  know? Oh, we moved past that.
• 22:29
  You know, that was back in the CRM days and when we were only
• 22:33
  using marketing automation. But it's the same thing if we if
• 22:36
  we don't solve anything. I mean, all the AI inferences
• 22:39
  are going to be based on the wrong data if we don't fix it
• 22:42
  first. Absolutely.
• 22:43
  Like I feel like, I mean, my entire job is dealing with data
• 22:47
  and the quality of the data and it's not a sexy job.
• 22:51
  It's absolutely not. But it's it's necessary because
• 22:54
  all of these other cool things that can happen like you need a
• 22:58
  found aid. It's like building a house just
• 23:01
  on a whole. Let me just plop a house on this
• 23:03
  hole and see what happens. Like, well, the whole house is
• 23:06
  going to just go down, you know what I mean?
• 23:08
  But we can have such a cool basement, I mean so much space
• 23:13
  like. This.
• 23:14
  Yeah, so much space. OK.
• 23:16
  I'd love to hear your favorite example of sales and marketing
• 23:19
  collaboration at Algolia. I know you've done some
• 23:21
  incredible stuff there, but hit us with your favorite example of
• 23:25
  working together and what the takeaways are for everyone
• 23:28
  listening. Within the Velocity squad that
• 23:31
  I'm in, we have a lot of use cases.
• 23:33
  And one of my coolest examples is one of my sales managers was
• 23:36
  like, hey, I'm trying to build something, can you help me?
• 23:40
  And so he came up with a project.
• 23:42
  What he wanted to do is, is use an AI tool to help prioritize
• 23:46
  the people. OK, so Demand Base tells us
• 23:49
  these are your qualified accounts, right?
• 23:51
  We train our reps on, let's look at them when they're engagement,
• 23:55
  so then we can push them into qualify.
• 23:57
  So what he was trying to do is like, okay, well, what's the
• 24:00
  best way for me to go after the people?
• 24:02
  So he came up with this tool using another AI tool and he was
• 24:07
  like, how, how can we do this? And so it was sales, marketing
• 24:11
  OPS and sales OPS. And we came up with this pilot
• 24:14
  that we as operations, we're like, OK, this is the structure.
• 24:18
  If you want this, we need to make sure that, OK, can we pull
• 24:21
  the data points for you? Does it match our CRM?
• 24:23
  Are we adding people to the CRM? If you're going to provide this
• 24:26
  tool to have contacts of prioritize, do they already
• 24:30
  exist? Do we need to add them?
• 24:31
  Like what is the process behind that and just kind of getting to
• 24:34
  build out that now It is, it is very new.
• 24:37
  It's a project we're still piloting, but it's just really
• 24:41
  cool to have. You know, typically sales
• 24:43
  people's, I don't, I don't find that they're like going out and
• 24:46
  looking for new ways to innovate.
• 24:48
  But this guy really did and I was very impressed with him.
• 24:51
  So I think it was a really fun project to be part of.
• 24:54
  Yeah, I love that. And anything to breakthrough the
• 24:57
  noise, you know, soapbox moment. Before I ask the the last
• 25:01
  question before we move into some of the faster lightning
• 25:04
  round style, I need a sound effect like, you know, we'll
• 25:07
  have to figure something out for that.
• 25:09
  But yeah, I mean, we just recently had several open roles
• 25:14
  that I was involved in helping to make selections on, and 1
• 25:18
  specifically was on my team. I will not name the role because
• 25:22
  I don't want to candidate Bash or anything.
• 25:24
  But I did say very specifically we're looking for someone who
• 25:28
  can show their creativity and you know, really bring that to
• 25:32
  the role because we need it. So try to stand out when the
• 25:35
  job, right? Because if you want a job, go
• 25:38
  get the job and there's such an opportunity to stand out.
• 25:42
  So to your point of a seller being creative, out of all the
• 25:46
  candidates there were 1000 plus candidates.
• 25:49
  I had almost 600 LinkedIn messages and about 3 did
• 25:55
  anything above normal expectations.
• 25:59
  So the person who won the job did a personalized video, kind
• 26:03
  of said what they'd be like to to work with.
• 26:06
  I mean that was literally part of the role.
• 26:08
  It's not asking you to do a project, it's just saying if
• 26:11
  this is the job you want, go take it.
• 26:13
  So yet another nudge for curiosity, creativity.
• 26:17
  I think it's going to define success and some extent.
• 26:21
  It's hard to put a metric around it, but I I do feel like it's
• 26:24
  going to stand out. Well, and also, I think you have
• 26:26
  to be, you can't be afraid to fail because AI is relatively
• 26:31
  new for, for marketers and we're just trying all sorts of
• 26:35
  different things. And yeah, some stuff is going to
• 26:37
  suck. It's not going to work.
• 26:38
  But you have to just be able to continue to iterate and, and it
• 26:43
  might not work in the way that you had originally thought it
• 26:45
  would, but it could allow you to innovate in another manner.
• 26:50
  So we were trying to use AI to do this.
• 26:52
  One thing wasn't working. So we switched and we used, we
• 26:56
  were like, OK, rather than using ChatGPT, what if we try a clod,
• 27:01
  which I find clod is better for coding.
• 27:03
  And so we were able to use clod to then build us a program in
• 27:08
  hex to then do the thing that ChatGPT was not able to do.
• 27:13
  So it's you have to be able first.
• 27:16
  Don't be afraid to fail and try new things.
• 27:20
  Yeah, love that this is a very loaded question, but we're going
• 27:25
  to pretend it's not and try to have a very simple precise
• 27:28
  answer. What are the biggest ways that
• 27:32
  AI is changing an account based go to market strategy?
• 27:35
  Oh, that is a very, very loaded question.
• 27:38
  I mean, I think honestly the account scoring used to be you
• 27:43
  would use data to build out your account scoring.
• 27:46
  All right, Like are we doing an RFM model?
• 27:48
  Are we doing what are we doing? But now you can use AI to also
• 27:53
  look at a bunch of different metrics with maybe data that you
• 27:57
  don't have in your system to begin with, right?
• 27:59
  So you can use it to to blend a bunch of different metrics with
• 28:03
  with enrichment and all of these other things to come up with,
• 28:06
  with account prioritization. I don't know if it's going to
• 28:10
  change it or if it's just going to help it.
• 28:14
  Like, I don't feel like it's going to take our jobs because I
• 28:17
  do still feel like there's a huge need for humans involved.
• 28:22
  But I think it's going to help us be more efficient and test
• 28:26
  new things that we might not have been able to before because
• 28:28
  we just have access to more data.
• 28:31
  Yeah, that's a great answer. And I mean, hopefully it creates
• 28:35
  some of that extra margin that we can spend on being more
• 28:39
  strategic, more creative, more experiments to your point.
• 28:42
  So I, I love that one. We have a few quick hitters
• 28:45
  before we get to the end of our time.
• 28:47
  I'm watching the clock. I know we have some hard stops
• 28:50
  very, very soon. So the first, this is very quick
• 28:53
  Family Feud style session for these.
• 28:56
  What is the biggest challenge in B2B sales?
• 28:59
  I think sales and marketing alignment, if you look at across
• 29:02
  the board, if you look at every company, all of my friends, if
• 29:05
  there's always that marketing is not given enough pipeline, sales
• 29:09
  is not closing enough deals, sales and marketing alignment
• 29:12
  across any, any industry in the B to B space, I feel like that's
• 29:16
  just at the heart of it. Yeah, awesome.
• 29:19
  Favorite tools or technology that you're using today?
• 29:22
  Oh, hex Hex, ChatGPT and Cloud. Awesome, good look at that.
• 29:27
  That was bang. Steve Harvey would be proud.
• 29:29
  Good reads. So we're generous with reads.
• 29:32
  It could be book, blog, newsletter, podcast, video, any
• 29:35
  consumption format. But what are the most
• 29:37
  inspirational things to you today?
• 29:39
  I mostly listen to like true crime podcasts, so that's not
• 29:42
  good. I'm like, I don't know.
• 29:45
  I feel like I don't have any good books lately.
• 29:47
  Best true crime podcast? Let's pivot.
• 29:50
  Morbid. All right, Morbid put it on our
• 29:52
  list. All right, good people.
• 29:54
  Who are some folks who inspire you and B to B specifically?
• 29:57
  So I will give you their Linkedins, but I think Sarah
• 30:00
  McNamara, I don't know how to say her name.
• 30:03
  She's really good in the B to B space.
• 30:06
  I also really love Carly Taylor. She's more of a data person, so
• 30:10
  she does do B to B, but it's on the data side.
• 30:13
  So she was a chemist and then like, she's kind of my girl
• 30:15
  crush, but maybe don't put. That on, now we're weaving it
• 30:19
  in. That was even better.
• 30:20
  No, that's awesome. I love that.
• 30:22
  That's a great 1. So we'll check those out.
• 30:24
  And I see Sarah's content too. She's really, really good.
• 30:27
  So that's awesome. And then the most important
• 30:30
  question of all for everyone listening, how can they get in
• 30:33
  touch with you after this episode?
• 30:36
  And find me on LinkedIn and I can give you the link or you
• 30:39
  e-mail me jillian.lellis@agolia.com.
• 30:42
  Outstanding. Well, Jillian, thank you so much
• 30:44
  for your time. We crushed it.
• 30:45
  Thank you, hopefully that was entertaining all.
• 30:48
  Right. It was great.
• 30:49
  We'll talk to you soon. Thank you.
• 30:51
  Thank. You bye.
• 30:54
  Thanks for joining us for On Base.
• 30:56
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• 30:58
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• 31:03
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• 31:05
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• 31:08
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