Speaker 1: This is the Full Funnel bTB Marketing podcast, brought to
Speaker 1: you by full Funnel dot io.
Speaker 2: Let's starve well join us of course.
Speaker 1: Yeah, thank you so much for having me. I'm psyched
Speaker 1: to dive into anything account based.
Speaker 3: Absolutely. One thing that I would love to kick off
Speaker 3: with is the fact that I have seen you mentioned
Speaker 3: on your linked and profile. So when you are leading
Speaker 3: the Global Enterprise Demand GAN at Google, you were able
Speaker 3: to increase SCL quality score from such a five percent
Speaker 3: to age of five percent in under one year by
Speaker 3: partner with the SDR team right developing the shared okayrs
Speaker 3: and also create this cross functional alignment what I feel
Speaker 3: and I feel this is kind of the universe problem
Speaker 3: for most bit of B companies, right, but simply don't
Speaker 3: have this cross functional alignment. Not just to say that
Speaker 3: we often fight for the credit, right, because this is
Speaker 3: kind of the typical bit of the setup. Looks like
Speaker 3: marketing needs to prove the marketing so are traving, the
Speaker 3: sales needs to prove the sales aurce aving to kind
Speaker 3: of measure everything by the last click attribution, and that's it.
Speaker 3: So well, I would love to dive deeper and understand
Speaker 3: The first thing is how do you define SQL quality score?
Speaker 2: Yeah, good question.
Speaker 1: So SQL quality score, think about your your typical score
Speaker 1: is going to be probably driven off of a band
Speaker 1: like budget, authority, need timing, and it's going to be
Speaker 1: driven by your SDR team. When I was at Google,
Speaker 1: you know, granted, this was you know, probably four or
Speaker 1: five years ago now, and we were doing this, so
Speaker 1: we didn't have all of the fancy AI stuff.
Speaker 2: That we have today.
Speaker 1: But quality was a combination of marketing data and sales data.
Speaker 1: And one of the particular metrics we've looked at obsessively
Speaker 1: was the what was called a rejection reason, so other
Speaker 1: companies might call it like disqualification reason, but it's a
Speaker 1: basically a sub field in salesforce. When an SDR was
Speaker 1: on the phone talking to a marketing qualified lead, they
Speaker 1: had to market as you know, for six different stages
Speaker 1: to either progress it forward or you know, disqualify it.
Speaker 1: And so one of those was disqualification, and then we
Speaker 1: had a whole sub field of reasons that they had
Speaker 1: to select for why they disqualified it. And that data
Speaker 1: alone became the most important part of this SQL quality
Speaker 1: score because we could see, you know, if marketing registered
Speaker 1: a lead as a market and qualified lead, meaning they
Speaker 1: met the marketing scoring criteria of you know, ICP fit
Speaker 1: or right job title or really right persona, and then
Speaker 1: they hit some kind of behavioral engagement score. Marketing thought
Speaker 1: it was good, right, And so this is where you
Speaker 1: get humbled because marketing said we created the MQL.
Speaker 2: Here you go sales.
Speaker 1: But then when you get a feedback loop from sales
Speaker 1: that says, we just qualified this because it's the wrong persona. Now,
Speaker 1: all of a sudden, that data got us thinking, well,
Speaker 1: what happened because on our side it was the right persona.
Speaker 1: And so, you know, small example, but you know, let's
Speaker 1: say in this case, they were selling to a purely
Speaker 1: it right, nothing engineering, nothing infrastructure, nothing data, just pure
Speaker 1: information technology. When we would send them a VP of infrastructure,
Speaker 1: our MQL scoring would pick up and see VP technology
Speaker 1: title cool MQL. But then sales would come back and say,
Speaker 1: we can't sell that person. We can never sell that person.
Speaker 1: They don't buy you know, chromebooks in this particular case.
Speaker 1: So that that feedback loop was really key. And you
Speaker 1: know t L d R there is you know, my team,
Speaker 1: and we ended up going through thousands and thousands of
Speaker 1: m q ls manually based on all of these rejection
Speaker 1: reasons from the sales team and and basically figured out that,
Speaker 1: you know, our m QL scores weren't as good as
Speaker 1: we thought they were, and we had to, you know,
Speaker 1: kind of take one on the chin and say, okay,
Speaker 1: we've got to go back to.
Speaker 2: The drawing board and fix some stuff on the marketing
Speaker 2: side lot.
Speaker 3: And was the hindsight what would you say, is the
Speaker 3: road treason? Is the road problem of all of this? Right,
Speaker 3: because it doesn't start, let's say, when we have the
Speaker 3: fight for the for the even for the quality of
Speaker 3: that specifically, right would say that? Is it kind of
Speaker 3: the default GM playbook or anson else?
Speaker 2: Yeah, it's a question.
Speaker 1: I think two things come to mind, and one is
Speaker 1: the the traditional enterprise marketing and sales, you know, the
Speaker 1: GTM motion I think is fundamentally.
Speaker 2: Not broken, but flawed. Right. I think the idea of marketing.
Speaker 1: Services this first half of the funnel and they work
Speaker 1: towards a metric like an MQL, and then they throw
Speaker 1: it over the fence to sales and then you know,
Speaker 1: sales takes it from there and they own the back
Speaker 1: half of the funnel. And then you can even think
Speaker 1: about customer success. If we're talking about a software company,
Speaker 1: I think that that linear progression is not it's flawed, right,
Speaker 1: because it allows the teams to just get focused on
Speaker 1: that one thing that they're responsible for and then they
Speaker 1: can forget about it. And so in this case, you know,
Speaker 1: I was I was guilty of doing that, right, Like
Speaker 1: I had to actually humble myself as a market leader
Speaker 1: and say what I'm doing is wrong.
Speaker 2: I've got to.
Speaker 1: Trust my peers on the sales side. I've got to
Speaker 1: take their feedback, and then I have to do something
Speaker 1: about it. And so at a macro level, I think
Speaker 1: that is present. And then at a micro level, especially
Speaker 1: in enterprises or more mature go to market teams where
Speaker 1: let's just say you're you're dealing with, you know, thousands
Speaker 1: of leads on a monthly basis like five ten, you know,
Speaker 1: even more, some of these enterprise teams are dealing with
Speaker 1: millions per quarter, and so when you have that much volume,
Speaker 1: it's easy to just like sit back and hide behind
Speaker 1: all the screens and the dashboards and the trends and
Speaker 1: the graphs and not actually get into the data. So
Speaker 1: one thing I advise all time is whether you're dealing
Speaker 1: with a thousand leads or a million. Just go into
Speaker 1: the data, like you've got to go in and look
Speaker 1: at the lead profile. You have to look at the
Speaker 1: sales notes. You have to look at the behavior of
Speaker 1: those contacts that they conducted with marketing and the different
Speaker 1: activities and that sort of thing. Like you have to
Speaker 1: get close to it because that's where the real insights are.
Speaker 1: I think, like the ones we're talking about that really matter,
Speaker 1: and you'll notice you'll notice the good, the bad, and
Speaker 1: the ugly.
Speaker 2: If you do that, love it.
Speaker 3: And they're saying AI can help with this, I know
Speaker 3: that you go and maybe just a quick announcement for everybody,
Speaker 3: So we'll hostile as Savans Annual Virtual Full Funnel signment
Speaker 3: next week where Still would be one of the speakers
Speaker 3: and he'll be talking exactly about the topic of AI
Speaker 3: workflows for each stages of your ABM funnel. So we'll
Speaker 3: leave it for that part, right, But anyhow, I would
Speaker 3: love to ask you, considering your experience of playing with
Speaker 3: A either think AI can help with this initial qualification
Speaker 3: and score them?
Speaker 1: I do, Yeah, And to give everybody a quick sneak peek,
Speaker 1: that's one of the workflows we'll talk about just in general,
Speaker 1: the idea of using AI for account scoring, leads scoring,
Speaker 1: intense scoring, really scoring in general is incredible And if
Speaker 1: you think about it, you know, even when I was
Speaker 1: at Google, right, one of the biggest companies on the planet,
Speaker 1: I was restricted by resources that were technical to build
Speaker 1: things like propensity models, you know, dynamics scoring and things
Speaker 1: like that, which are based on statistics and machine learning.
Speaker 1: And now we all have access to that skill set
Speaker 1: at our fingertips, right, especially if you've used even.
Speaker 2: Just general prompting.
Speaker 1: Right, Like my first introduction to call it like statistical
Speaker 1: analysis was was.
Speaker 2: Just with chat GPT. Right. I don't really know that much.
Speaker 1: I'm fairly technical as a marketer, but I could go
Speaker 1: back and forth with chat GPT and basically build you know,
Speaker 1: a machine learning expert, right, and then started to push
Speaker 1: further and say, okay, well, what kind of machine learning
Speaker 1: methods could you use?
Speaker 2: Which ones are.
Speaker 1: Best for things like lead scoring or finding trends within data?
Speaker 1: And then you can go and you know, build that
Speaker 1: base of prompts and put that off to the side,
Speaker 1: eventually evolve that into more of like an agentic use
Speaker 1: of AI, where you can feed data in more real
Speaker 1: time and dynamically and then you can get an output
Speaker 1: at that point in time.
Speaker 2: And so it's incredible because I don't.
Speaker 1: Know too many off the shelf software programs today that
Speaker 1: have that level of customization and can deliver lead scoring
Speaker 1: at that at that scale and that level of personalization, right,
Speaker 1: And so I think that's that's the really the most
Speaker 1: amazing thing to me is we can we can We're
Speaker 1: pretty close to being able to build our own ABM
Speaker 1: tech stacks that are completely unique to our team, our product,
Speaker 1: our market, our motion, and we can, like you know,
Speaker 1: execute a lot of the steps that we use traditional
Speaker 1: software for we can now do with AI.
Speaker 3: Yeah, that makes perfect sense. I totally agree. And just
Speaker 3: to wrap it up, so one of the solutions what
Speaker 3: I have heard from you and just correct me if
Speaker 3: I'm wrong, kind of to make the first step towards
Speaker 3: alignment with sales, even if we play let's say the
Speaker 3: MCL playbook and we can't do anything, is just manually
Speaker 3: qualifying all like, really do the market and lead qualification
Speaker 3: before transferring innocent to sales. Right, So this is the
Speaker 3: first thing and the second one, and you can do it,
Speaker 3: say yeah, you can do it manually whatever you prefer,
Speaker 3: but also what I feel is really important and I
Speaker 3: would like to get your take on this. When we
Speaker 3: do this qualification, we just need to think about that
Speaker 3: this is just an individual contact, right, and this content
Speaker 3: might have completely different journey compared to the account. Right,
Speaker 3: So if we want to make sense of that engagement,
Speaker 3: we need to pair the signal, right, or the engagement
Speaker 3: that we captured it with that content was the historical
Speaker 3: interactions with the account, all the signals, so all the
Speaker 3: information that is available about this account, account research, et cetera, right,
Speaker 3: engagements with other Buying Committee members and then together with sales,
Speaker 3: make sense of that engagement. Right, what could it mean
Speaker 3: in terms of like account activities and strategic initiatives they
Speaker 3: have and what could be our best next action that
Speaker 3: would add value for this specific individual? Right? What do
Speaker 3: you think about this? I'm just complicated to my chance.
Speaker 3: Oh you need just to say, hey, guys, you got
Speaker 3: to buy and commit to member engaged, go get them?
Speaker 2: Yeah no, no, this.
Speaker 1: Is fantastic because you've actually just set the stage really
Speaker 1: well for what the talk next week will be about.
Speaker 1: And so I know the title is you know AI
Speaker 1: workflows for ABM.
Speaker 2: But really what we're going to go through in that.
Speaker 1: Session is my philosophy on ABM and how it's evolved.
Speaker 2: And you now hear contact.
Speaker 1: Based marketing right, So there we actually need to sort
Speaker 1: of reinvent what the demand creation and capture process looks
Speaker 1: like and map that to account based funnels and contact
Speaker 1: based funnels. And when we do that, we can then
Speaker 1: look at the intersection of signals and data and activity
Speaker 1: between accounts and contacts, and I think that's really where
Speaker 1: the where the magic is. And so so one, if
Speaker 1: you if you have the infrastructure and the architecture to
Speaker 1: collect that data, and you do are able to collect signals,
Speaker 1: you now have the sort of m VP for AI.
Speaker 2: In my mind, you need to have a good.
Speaker 1: Base of data that you're that you're building any of
Speaker 1: these AI workflows off of. So that's number one, which
Speaker 1: is fantastic. Number two is you now have extremely unique
Speaker 1: data across third party, first party owned operated sources that
Speaker 1: you can use for personalization, which is which is also
Speaker 1: exciting because we've all gotten those messages that are like
Speaker 1: half personalized, like they they scraped something from our most
Speaker 1: recent LinkedIn post. And then slapped it in an email
Speaker 1: and blasted it out to us. That's not personalization.
Speaker 2: We need. We need we need.
Speaker 1: Dozens of signals at a contact level, so we can
Speaker 1: build a profile of who that person is, what their
Speaker 1: pain points are, and what they care about, and then
Speaker 1: come up with a completely unique message that you know,
Speaker 1: almost gives them that aha moment at that point in
Speaker 1: time when we deliver something to them. And with those
Speaker 1: two things in place, then the third is that next
Speaker 1: best action piece, which is something I remember I heard
Speaker 1: that term like six or seven years ago. I was
Speaker 1: talking to a machine learning engineer. It's fairly common in software.
Speaker 2: Right.
Speaker 1: You think about you buy a hat on Amazon, it's
Speaker 1: then going to show you a product for hat cleaners
Speaker 1: or hat storage or hat hangars. Right, that's just next
Speaker 1: best action, Right, it's taking your existing behavior and trying
Speaker 1: to predict what you'll do or buy or need next
Speaker 1: based on that historical behavior.
Speaker 2: So we can now do that.
Speaker 1: We can now do that dynamically based on the scoring
Speaker 1: that we.
Speaker 2: Can evolve when it comes to an account and.
Speaker 1: Contact level, and then again bringing those two data sources
Speaker 1: together so we can get a view into what is
Speaker 1: generally happening in this account, and then who within the
Speaker 1: account is most likely driving that decision, and then we
Speaker 1: can act accordingly and leverage all of the data that
Speaker 1: we have from prior customers and prospects to say, Okay,
Speaker 1: this is the next best thing we should do, right.
Speaker 2: And that's when you.
Speaker 1: Get tactically into the effectiveness of AI. Right and thinking
Speaker 1: about a recommendation engine that your marketing team is now
Speaker 1: powered by. I just get pretty fired up thinking about that.
Speaker 1: That's pretty cool, right, and we can you can build
Speaker 1: that now exclusively for teams.
Speaker 3: Love it? Thank you? By the way, guys, Yeah, welcome
Speaker 3: to ask us any questions. As always, we'll do this
Speaker 3: whole final life. We're going to cover all of them,
Speaker 3: so feel free to drop them in the chat and
Speaker 3: I will pick them up. And what I would love
Speaker 3: to move next is to ask you about the process
Speaker 3: you used to create this share OKAYRS with SDRs, right
Speaker 3: of course, I mean this is the first step to
Speaker 3: the cross functional alignment. But I assume that you need
Speaker 3: to do a lot of change change management internally, right
Speaker 3: of course. Typically you have different incentives, different processes, and again,
Speaker 3: as we poke, you can even have this credit conflict,
Speaker 3: so can you walk us through the entire process and
Speaker 3: just explain how did you do this?
Speaker 2: Sure?
Speaker 1: Sure, Yeah, it's a disclaimer. Is easier said than done.
Speaker 1: Uh I would. I think of it in two components, right,
Speaker 1: there is the change management piece that you mentioned. That's
Speaker 1: like the people side, and then the other side is process.
Speaker 1: And I think a lot of go to market organizations
Speaker 1: they jump right into process. So i'll share that first, Right,
Speaker 1: that's your typical Okay, we're going to use HubSpot for
Speaker 1: lead scoring. We're going to have a demographic score, we're
Speaker 1: going to have a behavioral score, and oh, you know
Speaker 1: sales has these s LA's and they're going to run
Speaker 1: a band script or use spin methodology, and you know,
Speaker 1: all these teams they have all of these wonderful processes
Speaker 1: in place, but then they don't have the people aligned
Speaker 1: and that will break.
Speaker 2: And then in.
Speaker 1: Other cases, which I think is better, is you get
Speaker 1: the people aligned and they don't have the process yet,
Speaker 1: and that's okay. We got to get the people aligned
Speaker 1: first and then we can build process around that. And
Speaker 1: so for me, like one of the let's see, this
Speaker 1: probably took me.
Speaker 2: This took me like.
Speaker 1: Eight months to be honest, of getting an enterprise sales
Speaker 1: and marketing team aligned, but a couple of the key
Speaker 1: components that were really critical, where I had autonomy and
Speaker 1: ownership of the entire demand generation process, the budget, the activities,
Speaker 1: the resources, the channels, you know, the website like those things, right,
Speaker 1: So I do think that is important. You don't, as
Speaker 1: a marketing leader need to own it, but you at
Speaker 1: least need to get alignment with your peers so that
Speaker 1: everything that demand generation touches or is adjacent to.
Speaker 2: Is complete, completely aligned. Right.
Speaker 1: Without that, you're going to run into problems where you
Speaker 1: might have the best LinkedIn campaign on the planet, but
Speaker 1: your landing pages are terrible because your because your web
Speaker 1: team isn't bought in and they're just giving you like random,
Speaker 1: random stuff that doesn't quite fit.
Speaker 2: So you've got to get that alignment first.
Speaker 1: The other piece was the person I worked with on
Speaker 1: the sales side was basically a mirrored version.
Speaker 2: Of me, but on the on sales. So so she led.
Speaker 1: The SDR team and her ownership was really on you know,
Speaker 1: think of like SQL too, like stage two opportunity. And
Speaker 1: then depending on the deal side, there was an account
Speaker 1: executive or you know, maybe a senior sponsor or executive
Speaker 1: sponsor or something like that involved. But her role was
Speaker 1: on that core piece of SQL to opportunity creation and
Speaker 1: then progression into an actual qualified deal. And so we
Speaker 1: were both completely incentivized to work together because I essentially
Speaker 1: owned the steps prior to SQL and she owned all
Speaker 1: the steps after SQL.
Speaker 2: So when we got together, you know, one we aligned
Speaker 2: on like.
Speaker 1: Overall principles like okay, marketing is going to be a
Speaker 1: you know, a generator of revenue. We're going to generate meetings,
Speaker 1: We're going to generate opportunities. We're going to connect that
Speaker 1: to revenue. We're going to be data driven in how
Speaker 1: we analyze the effectiveness of marketing campaigns and channels and tactics,
Speaker 1: that sort of thing.
Speaker 2: And so we came together at that level.
Speaker 1: But then the other piece was we started by saying,
Speaker 1: what is the single most important metric that we should
Speaker 1: both be accountable for? And when I say accountable, I
Speaker 1: mean going on to a bi weekly pyce line review
Speaker 1: with the GM of Product, the VP of Sales, the
Speaker 1: head of marketing, and like going into the fire and
Speaker 1: together owning why sqls.
Speaker 2: Were what they were.
Speaker 1: So that was the metric we picked that was the determinator,
Speaker 1: so I was held accountable to SQLS, so was she.
Speaker 1: And then the next level was what I talked about
Speaker 1: with the quality metric, was we first looked at SQLS
Speaker 1: going up or down, what was the delta, what was
Speaker 1: the change, and then why and then we used all
Speaker 1: the data to figure that out. So so that's one
Speaker 1: is like align on the like the ownership and the
Speaker 1: accountability of like your team and your area. Then choose
Speaker 1: a metric, become jointly accountable for that metric, and then
Speaker 1: you know the third thing is I actually like Google
Speaker 1: used the like the Smart Goal system.
Speaker 2: Which I probably forget it now.
Speaker 1: It's like specific, measurable, attributable, I think, et cetera.
Speaker 2: So you can look it up.
Speaker 1: But smart system was the like criteria we use to
Speaker 1: create the okayrs and then OKRs themselves. It's objectives and
Speaker 1: key results, so you had to write those in a
Speaker 1: way that were pretty descriptive. Like basically it was like
Speaker 1: I'm going to or my team is going to do X,
Speaker 1: and it's going to produce Y by this timeframe. So
Speaker 1: that's where you use that smart system to write these
Speaker 1: goals that will will live you know, throughout the year
Speaker 1: if you're doing like quarterly planning, so then all of
Speaker 1: those things come together, right and when you have bi weekly, monthly,
Speaker 1: quarterly pipeline reviews, this is very clear what you're reporting
Speaker 1: on and what you're accountable to.
Speaker 3: A lot of I guess how much? So uh, what
Speaker 3: I would love to where I would love to pre seeds,
Speaker 3: and what I would love to touch Next is the
Speaker 3: account precression right kind the parts I have described from
Speaker 3: the beginning. I know you've been working a lot on
Speaker 3: this and on the framework that you have established out.
Speaker 3: Try to pull it in hopefully it will be visible
Speaker 3: for everybody, but guys, just in case you have a
Speaker 3: button two zoom in. Obviously, if you're watching this from
Speaker 3: the smart one, it won't be very convenient, but if
Speaker 3: you sit with your laptop you can try to zoom
Speaker 3: in and see the framework itself. I also Steve published
Speaker 3: it on LinkedIn, so you can download it from his
Speaker 3: LinkedIn profile. So I would love to ask you a
Speaker 3: couple of questions around this, right so, as we spoke
Speaker 3: with you one day. Account progressional account velocity is one
Speaker 3: of the most important metrics to track ABM efficiency for
Speaker 3: the long sales cycles. For a simple reason, you have
Speaker 3: a delayed revenue outcome. You can't just expect if your
Speaker 3: Selle cycle ankss eighteen months, you can't expect revenue from
Speaker 3: a single program that you are run in for the
Speaker 3: first month of months number two. Right, But you need
Speaker 3: some leading indicators in place that kind of tell you
Speaker 3: that we are doing the right things.
Speaker 1: Right.
Speaker 3: This is why the account velocity helps because it kind
Speaker 3: of shows how the accounts are procressing from one stage
Speaker 3: of the bar journey to another. Right, And I will
Speaker 3: impact on this as a team or no. So what
Speaker 3: I would love to ask you is, maybe, first of all,
Speaker 3: can you walk us through the entire framework and explain
Speaker 3: if I wanted to build or implement this framework from myself, right,
Speaker 3: how to do it step by step?
Speaker 2: Yeah? Yeah, yeah, Let's.
Speaker 1: Let's get into it and I'll share first this framework
Speaker 1: actually came from some of the pain points I experienced
Speaker 1: with attribution conversations. And you mentioned it, Andrea at the
Speaker 1: beginning to call was you know, we become really obsessed
Speaker 1: with you know, multi touch, last touch, incrementality, and those
Speaker 1: things are all great, They're wonderful, especially at a more
Speaker 1: mature company that's perhaps spending a lot on demand generation.
Speaker 1: But I sat back and I thought, from an ABM perspective,
Speaker 1: what are we actually trying to do here?
Speaker 3: Right?
Speaker 1: Like we're trying to take accounts from one stage in
Speaker 1: the journey and move them along. Like it's that simple, right,
Speaker 1: And that's what account progression is. And so in this framework,
Speaker 1: there are three components. There's one which is your account
Speaker 1: progression table. This is basically like the inputs you're going
Speaker 1: to need from an account perspective to be able to
Speaker 1: produce this. And then the second is what I call
Speaker 1: the event layer, which this is really the kind of
Speaker 1: the dynamic real time data that you'll be collecting for
Speaker 1: each account and that's what you're going to use.
Speaker 2: Ultimately to build your reporting.
Speaker 1: And then the last component is the impact and the
Speaker 1: velocity through reporting. And so when you have the like
Speaker 1: core table dynamics in place and then you're tracking those
Speaker 1: events real time, you can now report on what's happening
Speaker 1: within a select group of accounts. And importantly, you can
Speaker 1: go back and look at what the you know, like
Speaker 1: the origination or the originating place was, or the originating
Speaker 1: stage of that account was, and then you can compare
Speaker 1: it to baseline, So we now have the ability to
Speaker 1: report on, you know, just purely what is happening within
Speaker 1: an account, but second, what has been the impact of
Speaker 1: the events and the activities we ran and how does
Speaker 1: that compare against baseline? And then we can look at
Speaker 1: and are we are these accounts progressing as quickly as
Speaker 1: we'd like?
Speaker 3: Is?
Speaker 2: Are they stuck somewhere? How do we? How do we
Speaker 2: fix that? Right? So those are the three components. And
Speaker 2: then next you have the stages.
Speaker 1: So these are the common ones that that I see
Speaker 1: and we use all the time with clients, but these
Speaker 1: can really be whatever you want them to be. So
Speaker 1: you have in a stage like on the left side,
Speaker 1: this is completely cold, right unaware, and then you move
Speaker 1: and you make an account aware and they become engaged
Speaker 1: and qualified and sales ready, customer growth, expansion, et cetera.
Speaker 2: Can keep going.
Speaker 1: But for you, for anybody really, you could you could
Speaker 1: simplify this down into three stages, four stages. You can
Speaker 1: change the names of the stages. What's most important is
Speaker 1: how you define the stages. And this is where a
Speaker 1: little bit of data analysis comes into play and where
Speaker 1: you can actually use AI as your friend to do this.
Speaker 2: Analysis.
Speaker 1: But as an example, like an unaware account, if you
Speaker 1: were to go and let's say you have a target
Speaker 1: account list of seven hundred and fifty accounts or five
Speaker 1: hundred accounts, and you're able to export and get let's
Speaker 1: say LinkedIn ad data or you know, Google or.
Speaker 2: Meta ad data, and then you have.
Speaker 1: Maybe some web data, and then you have like email
Speaker 1: service data from like a HubSpot or you know, you're
Speaker 1: like a marketo. You could export all of that data
Speaker 1: and then essentially map it to each account and then
Speaker 1: you can start to index those accounts by stage. And
Speaker 1: so unaware, for example, for your definition, might mean that
Speaker 1: they have zero engagement.
Speaker 2: In the last ninety days.
Speaker 1: So any accounts last ninety days no engagement, they get
Speaker 1: applied to label as unaware versus aware.
Speaker 2: They might have you might like we.
Speaker 1: Typically use like ad impressions and clicks and website visits
Speaker 1: kind of like top of funnel, some kind of vanity
Speaker 1: type metrics that are important to show that they might
Speaker 1: be aware. And the same process, you go and you
Speaker 1: index all of that and then you map it to
Speaker 1: that stage. And then when you do that across all
Speaker 1: of these stages, what you have at this step in
Speaker 1: The process is a complete indexing of where your accounts
Speaker 1: currently sit today, and this becomes your baseline. Everything builds
Speaker 1: on top of this. And what we typically see is
Speaker 1: we run this report and it's humbling for clients because
Speaker 1: it's like eighty ninety percent are unaware, whereas they thought,
Speaker 1: you know, they had made more more effort with these accounts.
Speaker 1: But when you when you time constrain it, because awareness
Speaker 1: is fleeting right when you look at it within ninety days.
Speaker 2: We often find, hey, a lot of these accounts are unaware.
Speaker 1: And with that insight we can then we can change
Speaker 1: our tactics and our strategy quite effectively. And yeah, and
Speaker 1: then I can we can dive into this little bit more.
Speaker 1: But I've had I did some kind of high level
Speaker 1: steps for how you could go about implementing it, what
Speaker 1: some of the core data needs are, and then how you.
Speaker 2: Can actually look at success through metrics from this reporting.
Speaker 3: I have seen a question from LUSA Ojen and she
Speaker 3: asked about the tools that's being utilized to implement this
Speaker 3: general let's speak and if you can maybe highlight how
Speaker 3: a good stack that kind of enables implementation of that
Speaker 3: framework looks like that would be helpful.
Speaker 1: Yeah, yeah, of course it's it's it's always fun to
Speaker 1: talk about the tools.
Speaker 2: So for something like this, like there's different levels of complexity.
Speaker 2: Let's say one of my favorites, which is can be
Speaker 2: really simple, but you can also build some complexity on it.
Speaker 1: Is you've got Clay or a similar tool like a
Speaker 1: common room or.
Speaker 2: U you know, zoom info, like something.
Speaker 1: That is is robust with building lists and then mapping
Speaker 1: data to those lists. I think Clay is the most
Speaker 1: flexible currently. So clay on call it like a component one, right,
Speaker 1: like your progression table, so you'd have all of your
Speaker 1: target accounts in there, you'd have all of your basic demographic,
Speaker 1: firmographic type data in place in a tool like that,
Speaker 1: and then next would be think of it as like orchestration,
Speaker 1: like where do you execute marketing and sales activities? So
Speaker 1: on the marketing side, if you're using you know, just
Speaker 1: straight in the channel, it could be in a you know,
Speaker 1: Google Meta LinkedIn, et cetera, where you're targeting at an
Speaker 1: account level, or you might have a tool in place.
Speaker 2: There's a tool I've looked at called Primer.
Speaker 1: There's a few others that have popped up that will
Speaker 1: allow for basically like LinkedIn grade targeting, but in Google
Speaker 1: Meta and Reddit, so you might have some data living
Speaker 1: in a tool like that which is going to get
Speaker 1: you that awareness level data at the account level. Then
Speaker 1: I would say your CRM and whatever your email service
Speaker 1: provider is. So if you are sending emails from HubSpot
Speaker 1: or marketo or active campaign, you're going to want to
Speaker 1: get access to all of that data. And then your
Speaker 1: CRM is going to be where all of your sales
Speaker 1: activity is. So whether it's Salesforce, a t O pipe drive, like,
Speaker 1: there's so many of these that you know now can
Speaker 1: can even you can API connect or you can just
Speaker 1: export data. But for building the actual report, I've yet
Speaker 1: to come across a tool that can do this out
Speaker 1: of the box. So when we build these for clients,
Speaker 1: it's actually completely through AI and you can do it honestly.
Speaker 1: You can do this with a twenty five dollars a
Speaker 1: month cloud or cloud subscription where you can have a
Speaker 1: dynamic dashboard produced in HTML bi weekly every month, whatever
Speaker 1: you want, and then you can just you know, create
Speaker 1: create all the underlying context and skills and information so
Speaker 1: that it's it's repeatable. But yeah, those those right there
Speaker 1: is is kind of all you need because the the
Speaker 1: customization of the definitions of the stages and like even
Speaker 1: the with the sources of the data. It's it's usually unique,
Speaker 1: Like every company is different. Their mix of channels is different,
Speaker 1: their mix of tools is different, and so you know,
Speaker 1: maybe it's an opportunity for somebody if you've got an
Speaker 1: engineering background, go build this tool, uh, and then hit
Speaker 1: me up when you do, I can help you sell it.
Speaker 2: But yeah, right now, it's it's custom.
Speaker 3: A lot of and just maybe your mansion cloned. Do
Speaker 3: I think, uh, one day it's just the ultimate solution
Speaker 3: to manage it all. And we probably just maybe talking
Speaker 3: a little bit of about trends because well I'm absorbing.
Speaker 3: Probably we all have heard about clase evaluation, right and
Speaker 3: all the tools that kind of appeared and martech and
Speaker 3: sales take landscape because of AI. But if I just
Speaker 3: think about the development of cloud and cloud cowork and
Speaker 3: the integrations with your CRM, with your proprietary data, et cetera,
Speaker 3: I think I feel at least it's just a matter
Speaker 3: of time when they will either acquire or partner with
Speaker 3: the huge database platforms like think about domain for European
Speaker 3: providers right, and then they will have access to ever
Speaker 3: and then basically they just kill everyone. So when I'm
Speaker 3: heading with this, maybe I see it in completely wrong quay.
Speaker 3: But even despite of this, well I'm thinking, isn't it
Speaker 3: better to kind of simplify Everson for yourself and indeed
Speaker 3: start playing, for example Claude or any software that you'll
Speaker 3: select for example Google Build right, and especially if your
Speaker 3: organization is on Google right, and try to time that
Speaker 3: creates that solution internally, compare to develop let's say text tech,
Speaker 3: which you still need to integrate right. There is still
Speaker 3: a learning curve and you need to train your people
Speaker 3: to leverage all of this assorts.
Speaker 1: Yeah, yeah, yeah, I mean here's the I think the
Speaker 1: reality is when you go on LinkedIn or you know,
Speaker 1: you look at Reddit, or you follow the news in
Speaker 1: the trends, it seems like the whole world is building
Speaker 1: completely unique applications with cloud code, and they just aren't right.
Speaker 1: There are if you're in SaaS and like software and
Speaker 1: kind of emerging tech, sure, I think it's something to
Speaker 1: pay attention to, but there is a whole universe of
Speaker 1: companies that honestly they don't even have subscriptions to AI.
Speaker 2: Right, you have sort of like shadow.
Speaker 1: Use of AI within the company and people just using
Speaker 1: free accounts to play around and do stuff, and they're
Speaker 1: still you know, trying to create content or write emails
Speaker 1: or landing page copy for websites and things like that.
Speaker 1: So I think, you know, one thing is like don't
Speaker 1: I think for folks, I say, don't don't feel behind,
Speaker 1: but don't wait too long, like start playing around, start
Speaker 1: start trying some things, and the other pieces that what
Speaker 1: I've found is the differentiator for how good your output
Speaker 1: is is what you put into it and the thought
Speaker 1: that you put into your inputs. So the phrase garbage in,
Speaker 1: garbage out is like so true. Everybody knows that, right,
Speaker 1: It's really really prominent engineering circles, and it's it's true
Speaker 1: for us too as marketers. And so it's you know,
Speaker 1: don't get caught by opening up.
Speaker 2: A chat window in Claude or Gemini or.
Speaker 1: Whatever and you know, writing your single prompt and then
Speaker 1: you get an output and you're like, cool, it's great,
Speaker 1: Like that that single shot kind of prompting isn't going
Speaker 1: to get you to like the complex strategic outputs with
Speaker 1: some of the stuff we're talking here. You know, you're
Speaker 1: going to have probably anywhere from like ten to twelve
Speaker 1: artifacts or like input documents that are going to go
Speaker 1: into your final workflow. These are things that you need
Speaker 1: to build to train you know, that agent, that project,
Speaker 1: that specific chat to do exactly what you want. And
Speaker 1: this is where the real marketing work happens, right, Like,
Speaker 1: this is your core stuff, this is your ICP, these
Speaker 1: are their pain points, These are the value props of
Speaker 1: your product and service.
Speaker 2: This is your your buying motion.
Speaker 1: Jobs to be done, Like, this is all of that
Speaker 1: information that has to be really good to get these
Speaker 1: things right. And then the third piece here, I think
Speaker 1: is that most marketers today are not opening terminal and
Speaker 1: running you know, cloud code or like a you know
Speaker 1: a companion AI that's helping them write and edit in
Speaker 1: QA code.
Speaker 2: It's it's incredibly.
Speaker 1: Complex, and and even for me, like I'm lucky I
Speaker 1: have resources in my company that are really good at
Speaker 1: this stuff.
Speaker 2: And are like pushing me along to learn more.
Speaker 1: But I think it's it's worth trying, right, Like it's
Speaker 1: worth going in and experiencing it and and fail and
Speaker 1: like break things and see what happens. And that happens
Speaker 1: to me all the time. I was just doing something
Speaker 1: yesterday and you know, I had all this code on
Speaker 1: my screen and I don't even know what the heck
Speaker 1: any of it says.
Speaker 2: But Claud's helping me figure it out. And you know,
Speaker 2: prompted this error is like line once and two has
Speaker 2: an error with this and that. I'm like, what the
Speaker 2: heck does that mean? Right? And then you go and.
Speaker 1: You work through the process of fixing that, and then
Speaker 1: it breaks something else, and you know, sometimes you.
Speaker 2: Get into these loops.
Speaker 1: But you know, that experience I think is pretty valuable,
Speaker 1: especially today, to just become familiar with the tools and
Speaker 1: how they work.
Speaker 3: I love it. Thank you. I just want to ask
Speaker 3: you one practical question, if you'll If I look at
Speaker 3: this framework, and more specifically on the dashboards section. In
Speaker 3: one of the sections, I mean, why you explain the
Speaker 3: four types of dashboards. One dashboard is about the forecast support,
Speaker 3: So I think this is one of the most problematic eras,
Speaker 3: right if you have the long sale cycles. So I'm wondering,
Speaker 3: how do you use this framework for forecasting on pipeline
Speaker 3: or revenue. And also you mentioned in that deskboard sounds
Speaker 3: like stage health wardance. So I think just highlights how
Speaker 3: the use for it for fort a custom and how
Speaker 3: do you define this kind of stage health wardance I
Speaker 3: think would be cool.
Speaker 2: Yeah, yeah, that's a good one. So it's it's uh,
Speaker 2: it's it's it's based.
Speaker 1: On two parts of the initial data gathering process.
Speaker 2: Right.
Speaker 1: So one thing that's cool about this framework is you
Speaker 1: can you can retroactively put this into place, meaning if
Speaker 1: you have a bunch of unstructured data across marketing and sales,
Speaker 1: you can build the the the progression stages and that table,
Speaker 1: and then you can take all your existing data and
Speaker 1: map it into that that progression framework, and then you can.
Speaker 2: Understand some key metrics that'll.
Speaker 1: Be useful for forecasting, right like how many accounts you
Speaker 1: know typically fall per stage, what is the delta or
Speaker 1: the velocity of how frequently they change? So you know,
Speaker 1: in simple terms, the questions of how long does it
Speaker 1: take to get an account from unaware to aware? You
Speaker 1: can answer that question by doing that retroactive analysis, and
Speaker 1: then you can you can peel back the onion further
Speaker 1: and say, okay, how many touch points did those accounts have?
Speaker 1: What was the average number of touch points? Per week,
Speaker 1: What channels were those touch points in, what content did
Speaker 1: they engage with, Who were the contacts that engaged at
Speaker 1: what point in the journey, And so you can start
Speaker 1: to map all of these things across that progression journey,
Speaker 1: and so that that's one thing. So you can retroactively
Speaker 1: go back and do this analysis, and then you'll get
Speaker 1: an output of that, which.
Speaker 2: I usually called the baseline.
Speaker 1: Like, this is your baseline right where you now as
Speaker 1: a GTM team, you know it takes fifty five days
Speaker 1: on average to get an account from unaware to aware.
Speaker 1: You know it takes thirty eight days to get them
Speaker 1: from aware and engage.
Speaker 2: You know that.
Speaker 1: Targeted Google ads are the best way to get them
Speaker 1: into an aware stage and the most cost effective, and
Speaker 1: you know that running webinar replays on LinkedIn is the
Speaker 1: best way of getting them from aware to gauge. So
Speaker 1: you now have all of these insights that you can
Speaker 1: build from, and you have a baseline of how things
Speaker 1: progressed in the past. So with that we can now
Speaker 1: forecast and know forecasting in a simple way is just
Speaker 1: looking at the past and predicting that the same thing
Speaker 1: will happen in the future. So let's say, like I said,
Speaker 1: this many days, it costs this much budget, is this channels,
Speaker 1: these campaigns, this creative, this content, etc.
Speaker 2: That's what we had to do historically to.
Speaker 1: Move you know, X number of a counts from aware
Speaker 1: to engage and you know, all the way through to
Speaker 1: a customer. You can use all of that data now
Speaker 1: to then forecast what the next quarter will look like,
Speaker 1: the next half, the next year, the next three years,
Speaker 1: five years, et cetera.
Speaker 2: So that would be like the simple way.
Speaker 1: I think if you wanted to make it a little
Speaker 1: bit more advanced, you could you could apply some like
Speaker 1: some compound and growth indicators, like if you know, you
Speaker 1: can assume that you know, quarter after quarter, you'll get
Speaker 1: better at qualifying leads, the lead quality will get better,
Speaker 1: or sales will get better at running their discovery process,
Speaker 1: Like you can build that into your forecast model and
Speaker 1: that'll help, you know, increase the growth output substantially. Another thing,
Speaker 1: probably the more advanced way to look at it would
Speaker 1: be if you if you're good on the.
Speaker 2: Data side, and you do have all of that data
Speaker 2: and you have.
Speaker 1: A robust account progression framework in place, you can actually
Speaker 1: then apply a more predictive layer to that, and you
Speaker 1: could use like more statistical modeling to try to show
Speaker 1: what that forecast could look like based on all of.
Speaker 2: That historical behavior.
Speaker 1: And that's not too just difficult with either if you
Speaker 1: have data science resources or you're capable of building a
Speaker 1: data science and machine learning agent with AI.
Speaker 3: I love it. I guess so much for super detailed answer.
Speaker 3: I think it's super helpful. I would actually try to
Speaker 3: replicate with my team what you have said and kind
Speaker 3: of crete an actionable step by step guide. So again
Speaker 3: then lay a shape as everybody because I think it's
Speaker 3: really really helpful. Thank you. Uh, maybe just to wrap
Speaker 3: it up, I would love to ask two questions that
Speaker 3: I received from from our community. One is from me no,
Speaker 3: the question about best final metrics to track a BM
Speaker 3: at account level.
Speaker 1: Best funnel metrics for yes, yes, yeah, good question. It
Speaker 1: may be too small on the on the chart here,
Speaker 1: but I think for aware think mostly about like what
Speaker 1: are the first touch.
Speaker 2: Points that a your your I c P has to
Speaker 2: engage with you and your brand?
Speaker 1: Right, So if you're running ads, you can look at impressions, clicks, reach,
Speaker 1: if you're sending emails.
Speaker 2: It might be.
Speaker 1: You know, maybe opens or clicks like kind of depends
Speaker 1: on how you want to define these things.
Speaker 2: Uh.
Speaker 1: And then the other more prominent source would be your website.
Speaker 1: I like when you break down web into multiple kpi right,
Speaker 1: because like a visit to the homepage is very different
Speaker 1: than a visit to a pricing page or a visit
Speaker 1: to a conversion page or like a demo page, et cetera.
Speaker 1: So having some kind of hierarchy there on the website
Speaker 1: is important. So think of those those typical like top
Speaker 1: of funnel metrics.
Speaker 2: For that like aware and engaged stages.
Speaker 1: And then for like engaged towards qualified, I would think
Speaker 1: about what are the actions that your ICP can take
Speaker 1: to become known known to you?
Speaker 2: Right?
Speaker 1: So they go from you know, basically like anonymous to identified.
Speaker 1: That's things like registering for a webinar, downloading a piece
Speaker 1: of content, you know, a booth scan at an event,
Speaker 1: you know, any of those mechanisms where you're able to
Speaker 1: capture contact information for a lead is topically what I'll
Speaker 1: associate with with engaged and then and then qualified is
Speaker 1: actually usually more just like the volume of those activities, right,
Speaker 1: So qualified is like kind of think of it like
Speaker 1: your typical MQL score. It's like, Okay, the ICP fits
Speaker 1: this demographic criteria, great, Now what.
Speaker 2: Was their behavior?
Speaker 1: And this is the one you can fine tune a
Speaker 1: little bit because it depends on your company.
Speaker 2: But for example, you know.
Speaker 1: Ad impressions don't mean you're qualified, but if there is
Speaker 1: enough of them and it's combined with ad clicks, website visits,
Speaker 1: content downloads, webinar registrations, all that stuff, right, then okay,
Speaker 1: now they are starting to show some qualification there. And
Speaker 1: you know the cool thing about this is like what
Speaker 1: we're talking about is at the account level, right, so
Speaker 1: you have a you can't just apply take your lead
Speaker 1: scoring and apply it to an account, right, You're going
Speaker 1: to see a lot of activity at an account level
Speaker 1: if you are.
Speaker 2: Executing a b M properly.
Speaker 1: So you know, keep that in mind, and then you
Speaker 1: know sales ready is going to be you know that
Speaker 1: point in time when that i c P has like
Speaker 1: basically raised their hand and said, you know, hey.
Speaker 2: I'm interested in talking to your team. So you know, a.
Speaker 1: Demo, a trial, contact, sales form, that sort of stuff
Speaker 1: is most important.
Speaker 3: There, perfect, thank you, and maybe just the last question
Speaker 3: from John McCree. He asked what about the main differences
Speaker 3: between working at Google Cloud and your agents in terms
Speaker 3: of being able to roll out such a successful demand
Speaker 3: gen process.
Speaker 1: Oh man, that's a cool question. Thanks for asking it,
Speaker 1: because I think about this all the time.
Speaker 2: Google. To be honest, Google was a was an amazing place.
Speaker 1: The culture there was was so rich and innovative, and
Speaker 1: and the people that I worked with really are are
Speaker 1: what made it.
Speaker 2: So. I was luckily lucky to be a part.
Speaker 1: Of a big team, and I had a team myself,
Speaker 1: and I still stay in touch with a lot of them.
Speaker 1: And I imagine there are so many companies that are
Speaker 1: have tried to like replicate their culture off of you know,
Speaker 1: big tech like like Google and Meta and those sorts
Speaker 1: of companies.
Speaker 2: So so that was one part.
Speaker 1: But I will say as a an agency operator and
Speaker 1: having a team of you know, strategists and technical folks
Speaker 1: that are really experts in in what they do, whether
Speaker 1: it's like running ads or you know, building revops, workflows
Speaker 1: and that sort of stuff, I am learning at a
Speaker 1: speed unlike anything I've experienced in the past. I mean,
Speaker 1: I feel like every day I'm learning something, I'm getting pushed.
Speaker 1: And when you work with you know, all kinds of
Speaker 1: different clients. They're always asking different questions, and everybody's unique
Speaker 1: and different, and so you know, there's a lot of
Speaker 1: cool things that.
Speaker 2: I'm able to see and we're able to do now
Speaker 2: that that wouldn't.
Speaker 1: Fly at a company, a big company like Google or
Speaker 1: big tech. So that speed is really important. And then
Speaker 1: you know the ability to test and try things out right,
Speaker 1: especially when you have happy clients that are wanting to
Speaker 1: test as well, and we can bring ideas like like
Speaker 1: this account progression dram works or dynamic intent scoring systems
Speaker 1: and say, hey, we've got an idea, can we try
Speaker 1: this out.
Speaker 2: Let's do it together.
Speaker 1: So I think that's kind of the pros and cons
Speaker 1: when you work in a big company get to work
Speaker 1: with a lot.
Speaker 2: Of great, smart people.
Speaker 1: Things move a little bit slower, though, and you can't
Speaker 1: be as agile and scrappy as you want.
Speaker 2: And you know, working with smaller company.
Speaker 1: Really the opportunities to kind of seem endless these days.
Speaker 3: I can't just say it's kind of so much as
Speaker 3: a night's with my own experience, as I've been in
Speaker 3: consultant nine years already, after being eleven years in the
Speaker 3: corporate world as well, like you were at enterprises, but
Speaker 3: I was not in the tech space but at Kimberly Clark.
Speaker 3: And the truth is, right now you can connect the
Speaker 3: core frameworks that you kind of established in the enterprise,
Speaker 3: and then you have clients from multiple industries with different challenges, right,
Speaker 3: with different companies, they are target in different market conditions.
Speaker 3: And then basically what happens is just strengths and your
Speaker 3: core framework. As I'm reflecting a lot about, I'll love
Speaker 3: to read Charlie Monger and what he says what is
Speaker 3: really important is to learn from multiple disciplines, right, and
Speaker 3: then connect the dots, because then you can see the
Speaker 3: big picture. The same is here.
Speaker 2: Right.
Speaker 3: Then when you have this experience from this verticle, you
Speaker 3: know this is how it kind of applies in healthcare.
Speaker 3: But then you see the challenges, you can immediately see
Speaker 3: them from different angle in another space. Right. This is
Speaker 3: what kind of helps to kind of strengthen your frameworks.
Speaker 3: See the gaps, follows them and prove and I think
Speaker 3: this is kind of the beauty of it. Maybe the
Speaker 3: last fun question from my side. I have never been
Speaker 3: at Google, but I watched the movement the in township
Speaker 3: was Oh, Wilson if the experience exactly like I was
Speaker 3: described in the moment, Oh.
Speaker 2: No, I love that. Yes, and no. What's funny is the.
Speaker 1: The in the movie, you know the remember the scene
Speaker 1: at Vince Vaughan's like ordering a coffee in a pastry.
Speaker 2: So I mean.
Speaker 1: That's true, right, Like you go up to a barista
Speaker 1: in your office and it's like, what do you want?
Speaker 1: You can have anything like coffee, you can have you
Speaker 1: can make a flat white with cinnamon and this and that,
Speaker 1: and you can get whatever you want. And then on
Speaker 1: the shelf is uh, you know, chocolate pastries, strawberry pastries,
Speaker 1: peach pastries.
Speaker 2: So you can it's going to test your your discipline.
Speaker 2: So that's true. But I think too, like the.
Speaker 1: Movie if I remember, you know, not every day is
Speaker 1: like hackathons and like innovation, like it's it's still a
Speaker 1: regular company at the end of the day, and you.
Speaker 2: Deal with a lot of bureaucracy and stuff like that.
Speaker 1: But I do think, especially my early years there when
Speaker 1: google Cloud was not as big and prominent as it
Speaker 1: is today, there was a real innovative, scrappy mindset to things,
Speaker 1: and I think, you know, Google has a lot of
Speaker 1: internal principles that help people and teams like be innovative,
Speaker 1: you know, use like design thinking. It was a big
Speaker 1: one to just produce like really amazing outputs. And h
Speaker 1: you know their marketing I think is you know some
Speaker 1: of the best, right you look at the certain marketing
Speaker 1: and like the year in search video that they put
Speaker 1: out every year. You know, so there there's a there's
Speaker 1: a process, there's an equation behind the scenes to get
Speaker 1: to that level.
Speaker 2: So like that that stuff was cool, love.
Speaker 3: It, Thank you so much, really enjoyed our conversation and
Speaker 3: looking forward to your keynote at our signed next week.
Speaker 3: And as you guess, guys, next week we won't have
Speaker 3: a full final life. Well, we have the entire sign
Speaker 3: at three days, fifteen keynotes, fifteen great speakers, so make
Speaker 3: sure that you have signed up. It's free. We keep
Speaker 3: it deliberately free because we're once in the era of
Speaker 3: AI slap of the kind of really really really bad content.
Speaker 3: We want to bring the practitioners who can share their
Speaker 3: actionable workflows have similar conversations like we had today with Steve.
Speaker 3: You guys welcome to join and ask any questions because
Speaker 3: probably this is the only way to help our community
Speaker 3: to stay sane in the world of the nonsense that
Speaker 3: we are all experience and today, so thank you so much, Steve.
Speaker 3: Excited to have you on board on our signment next
Speaker 3: week and see you all guys. Have a good fest
Speaker 3: of the week, take care.
Speaker 2: Thanks everyone,