Latest / What is Business Development? / Episode 154: “The Buyer in the Loop” with Dr. Matt Wilkinson

Transcript

Episode 154: “The Buyer in the Loop” with Dr. Matt Wilkinson · What is Business Development?

• 0:03
  Speaker 1: Welcome to the Business Development Podcast, brought to you by
• 0:06
  Speaker 1: the Global Business Development Association, delivering the strategies and tactics
• 0:11
  Speaker 1: to boost your career and corporate growth.
• 0:14
  Speaker 2: Hello, BD pros, and welcome to the BD Podcast. It's
• 0:25
  Speaker 2: the official podcast of the Global Business Development Association. And,
• 0:30
  Speaker 2: you know, let me ask you guys something. Have you
• 0:33
  Speaker 2: ever been in a situation where you've done the research,
• 0:37
  Speaker 2: you've done 15 interviews, coded transcripts, you even have a
• 0:42
  Speaker 2: brief written plan and a voice of your customer in
• 0:47
  Speaker 2: their own words, and you reach out to these prospects
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  Speaker 2: and they just disappear? Not all at once. But one
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  Speaker 2: reasonable approval at a time until the message that ship
• 1:01
  Speaker 2: sounded like it was written for somebody completely different. The
• 1:06
  Speaker 2: voice of the customer disappears the moment nobody preserves it.
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  Speaker 2: And we're going to talk about voice of the customer
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  Speaker 2: and how we can preserve that with our guest author today,
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  Speaker 2: Matt Wilkinson. But before we jump into that, let's jump
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  Speaker 2: into this book. It's the Business Development Body of Knowledge.
• 1:24
  Speaker 2: This is the universal guide for business developers around the globe.
• 1:29
  Speaker 2: And it enables all of us to speak one common
• 1:32
  Speaker 2: language as business developers and move forward in our careers.
• 1:37
  Speaker 2: And one great step to help move you forward in
• 1:40
  Speaker 2: your business development career is to go to the GBDA
• 1:45
  Speaker 2: website at gbdassociation.org. and learn more about how you can
• 1:51
  Speaker 2: get your business development professional certification online after you read
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  Speaker 2: the book. Okay, now, let's take a look at this book.
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  Speaker 2: This is Matt's new book. It's The Buyer in the Loop,
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  Speaker 2: How Synthetic Customers Stop Your Buyer Disappearing Between Research and Market.
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  Speaker 2: And this interesting concept of a synthetic customer I really
• 2:20
  Speaker 2: want to dig into, but let me tell you a
• 2:23
  Speaker 2: little bit about Matt's background. He helps life sciences companies
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  Speaker 2: win the AI marketing game by training algorithms with content
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  Speaker 2: and building brand authority that makes customers ask for you
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  Speaker 2: by name. He has over 15 years bridging scientific research
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  Speaker 2: and commercial strategy. He's generated 9X increases in marketing qualified leads,
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  Speaker 2: delivered ABM campaigns producing six-figure sales, and pioneered Persona AI.
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  Speaker 2: It's an AI tool that transforms static buyer personas into
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  Speaker 2: queryable assistants. And Matt Wilkinson has coined the term for
• 3:06
  Speaker 2: a new force, and it's called organizational gravity. It's where
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  Speaker 2: every commercial message is. starts to pull away from the
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  Speaker 2: buyer truth and toward internal consensus. I know we've all
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  Speaker 2: been there in that situation, sitting around the conference room table,
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  Speaker 2: but there's a fix. It's not the one that most
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  Speaker 2: teams reach for. It's actually a synthetic customer. It's an
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  Speaker 2: AI representative of your buyer built from your own interviews,
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  Speaker 2: your sales calls, and the things buyers say in forums
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  Speaker 2: when no vendor is listening. So, wow, this is going
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  Speaker 2: to be another interesting AI podcast. And Matt Wilkinson, welcome
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  Speaker 2: to the show.
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  Speaker 3: Thank you for having me, Tony. Great to be here.
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  Speaker 2: That's great to have you, Matt. Now, I always like
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  Speaker 2: to ask our guests, how did you get into business
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  Speaker 2: development and why did you write the book?
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  Speaker 4: Well, I fell into business development. I actually started my
• 4:02
  Speaker 4: career as a scientist, so I'd like to think I'm
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  Speaker 4: a recovering scientist. And I moved out of that into
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  Speaker 4: science and business journalism before ending up in marketing and
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  Speaker 4: communications for a while. And while I was doing that, twofold. One,
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  Speaker 4: the start of this book happened, and this is more
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  Speaker 4: than 10, 15 years ago. But also, I started realizing
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  Speaker 4: I loved selling. And so that was how I fell
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  Speaker 4: into business development. I just enjoyed being able to try
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  Speaker 4: and understand a customer's problem and being able to help
• 4:35
  Speaker 4: them find the right solution. And so that was really
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  Speaker 4: how I got into business development.
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  Speaker 3: It was just, I like solving problems.
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  Speaker 4: And I just realized that by selling people, you know,
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  Speaker 4: by sales is all about helping people to solve their problems.
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  Speaker 4: And so that was really how I just got into it.
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  Speaker 4: And I've loved it ever since.
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  Speaker 3: Yeah. Well, that's it.
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  Speaker 2: We're business developers.
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  Speaker 3: We help people.
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  Speaker 2: That's what we do. We're champions for our prospects and
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  Speaker 2: our customers.
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  Speaker 3: All right.
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  Speaker 2: I love that origin story, Matt. Now, folks, if you're
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  Speaker 2: just listening in, we're talking about Matt's new book. It's
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  Speaker 2: called The Buyer in the Loop, How Synthetic Customers Stop
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  Speaker 2: Your Buyer Disappearing Between Research and Market. So, Matt, I
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  Speaker 2: can't wait to jump into the first takeaway or tactic
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  Speaker 2: from your book that you would like to share with everybody.
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  Speaker 4: Yeah, so I think the first thing is to look
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  Speaker 4: at the information you have about your customer already. You
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  Speaker 4: don't have to do too much to turn it into
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  Speaker 4: something that is actually already really, really helpful. Take all
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  Speaker 4: of those insights, throw it into a custom GPT, a project,
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  Speaker 4: whatever it is that your favorite AI tool of use.
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  Speaker 4: And then start asking it questions about your customers.
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  Speaker 3: And that can really, really help.
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  Speaker 4: And one of the things I think is really, really
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  Speaker 4: important is that Challenger earlier this year published statistics that
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  Speaker 4: showed that 38% of purchase attempts end with no decision.
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  Speaker 4: That's not because we've lost deals because a competitor's done
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  Speaker 4: a better job. We've lost deals because we actually haven't
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  Speaker 4: helped them answer the questions that helped them move from
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  Speaker 4: their current state to a resolved state where the problem is.
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  Speaker 4: The fear of resolving the problem of making the wrong
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  Speaker 4: decision is bigger than the actual pain of not solving
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  Speaker 4: it at all. And so one of the things that
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  Speaker 4: I've been doing now for a few years is to
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  Speaker 4: try to model the buying group using our insights into
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  Speaker 4: each of those customers and then being able to try
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  Speaker 4: to understand, well, what are each of those members of
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  Speaker 4: the decision-making unit going to need to hear? And if
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  Speaker 4: we can do that, we can start making sure that
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  Speaker 4: even if they're not in the room when you're actually
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  Speaker 4: pitching to them or you're talking to them, and make
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  Speaker 4: sure you've got the right sales enablement tools and strategies
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  Speaker 4: in place to be able to enable them to do
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  Speaker 4: the internal selling for you.
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  Speaker 2: And how are you collecting all of those conversations that
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  Speaker 2: have been assembled in the past, whether those are cold calls,
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  Speaker 2: those are engagements with prospects and customers? How do you
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  Speaker 2: do that?
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  Speaker 3: Well, that's a great question.
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  Speaker 4: In some places, you're able to just record a call.
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  Speaker 4: Other places, you're not so easy to do so. But
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  Speaker 4: on most calls these days, people bring in AI note takers.
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  Speaker 4: So that can be a really helpful way of just
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  Speaker 4: getting a sense of who people are, what's interesting to them.
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  Speaker 4: The important thing to note is that we're not looking
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  Speaker 4: at anything as an individual. We're trying to get an
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  Speaker 4: aggregate of customers, build out what you might call archetypes
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  Speaker 4: from across companies. you know, a group of customers to
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  Speaker 4: try to be able to better understand what are those
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  Speaker 4: different customer needs so that we can really try to
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  Speaker 4: really build something that helps us answer all the problems,
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  Speaker 4: you know, all the questions that people might have.
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  Speaker 2: Okay, great, great. Yeah, I think it's exciting where we're
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  Speaker 2: going in our profession. You know, there have been for
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  Speaker 2: a long time the recordings of the cold call systems.
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  Speaker 2: You know, you can get those call logs. And there
• 8:16
  Speaker 2: have been tools to analyze those calls and things like that.
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  Speaker 2: But a lot of business developers, we're having face-to-face conversations.
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  Speaker 3: We're doing virtual meetings.
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  Speaker 2: And so as we're able to log those calls better,
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  Speaker 2: I think it's going to add a lot more data
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  Speaker 2: that can help in what you're talking about, which is
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  Speaker 2: really assembling the database, the corpus of knowledge about the
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  Speaker 2: different personas involved in the buying committee, whether it's your champion,
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  Speaker 2: your economic buyer, your decision maker, and really understanding what's
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  Speaker 2: important to them, how they think, how they talk. These
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  Speaker 2: are all critical pieces of information. And I assume you're
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  Speaker 2: using AI to analyze that vast data set. It seems
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  Speaker 2: like it's almost impossible for an individual to probably do that.
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  Speaker 2: You could probably do it on a small scale if
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  Speaker 2: you have a small agency or something and you're having
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  Speaker 2: very few discussions in a year, but I think that
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  Speaker 2: leads to probably the key takeaway number two, would it not?
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  Speaker 3: Well, potentially, but it does a little bit.
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  Speaker 4: So I was going to say, audit your last five
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  Speaker 4: losses against the buyer, you know, what happened, what went wrong.
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  Speaker 4: But when you're doing that, absolutely, the way to do
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  Speaker 4: that is to use these reasoning models to conduct what,
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  Speaker 4: you know, and ask it to do a thematic analysis. And,
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  Speaker 4: you know, a great example of this was actually some
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  Speaker 4: interviews I was doing as part of a study about
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  Speaker 4: AI adoption with some friends and colleagues of mine at
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  Speaker 4: the University.
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  Speaker 3: Of Leicester in the UK.
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  Speaker 4: And we'd run some interviews. They'd gone away and they
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  Speaker 4: were painstakingly analysing this data by hand. And then showing
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  Speaker 4: its age here, this was just after 01 had launched
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  Speaker 4: in ChatGPT, which feels like a lifetime ago. I know
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  Speaker 4: it was only, I think, 2004. And I woke up
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  Speaker 4: one morning with this idea, I've got to thematically analyse this.
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  Speaker 4: And it took 15 minutes. That was two or three
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  Speaker 4: weeks work for two trained researchers. And I did, and
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  Speaker 4: the AI did it in 15 minutes. Even better, it
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  Speaker 4: looked that it took the, it took the matrix that
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  Speaker 4: we were trying to thematically analyze against. And they said, hey,
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  Speaker 4: I've done this, but I've also found these other themes
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  Speaker 4: that you might be interested in.
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  Speaker 2: Yeah.
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  Speaker 3: And I was like, okay.
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  Speaker 4: Just my mind was blown at that moment. And since,
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  Speaker 4: you know, from that point on, it's changed the way
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  Speaker 4: I think about data and you know lots of data
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  Speaker 4: fantastic give me more of it you know let me
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  Speaker 4: analyze it let me get the ai up its way
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  Speaker 4: with that context data and that can then help us
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  Speaker 4: really really understand the world that we live in.
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  Speaker 2: Better okay great and again folks we're talking about matt's
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  Speaker 2: new book it's called the buyer in the loop it's
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  Speaker 2: available on amazon okay matt let's jump into key takeaway
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  Speaker 2: number two from your book.
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  Speaker 4: Yeah so i think that that's really then when we
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  Speaker 4: When we do look at those sort of win-loss stories
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  Speaker 4: and looking at actually what is it that we can
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  Speaker 4: use to predict whether something's going to be successful or not.
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  Speaker 4: So as human beings, we're having a great conversation today,
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  Speaker 4: but we're often biased by the fact that we're enjoying
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  Speaker 4: the conversation. So we might have a great conversation, but
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  Speaker 4: we may not ever identify that there's a real business
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  Speaker 4: need there. But sometimes we come away and go, yeah,
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  Speaker 4: they loved it. It was a great conversation. They're going
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  Speaker 4: to buy it. Yeah, they might love the idea. There
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  Speaker 4: may not be the pain there that we're trying to resolve.
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  Speaker 4: And so the AI is really good at getting rid
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  Speaker 4: of that emotion. AI is really not very good at
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  Speaker 4: reading emotion and sarcasm, but it's very good at looking
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  Speaker 4: at what are those signals and building up patterns of
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  Speaker 4: what people have said and then looking at, well, what
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  Speaker 4: does this predict that we're going to be able to
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  Speaker 4: take this further or not? And so being able to
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  Speaker 4: look at that, that can do a ton of help
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  Speaker 4: in actually looking at Or maybe what are the things
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  Speaker 4: that we should be talking to these people about or
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  Speaker 4: not as we go forward?
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  Speaker 2: Yeah, I really like that ability of AI to identify
• 12:30
  Speaker 2: next best actions. And based on the data that it
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  Speaker 2: has presented to it, objectively, without emotion. And it is
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  Speaker 2: very easy to get caught up in the emotion of
• 12:42
  Speaker 2: the conversation as a business developer. And I did that
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  Speaker 2: last week. I was talking to a former client of mine,
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  Speaker 2: hadn't seen him in ages, met him at the airport.
• 12:52
  Speaker 2: We were talking about one of the business issues I
• 12:55
  Speaker 2: was trying to help him with. And I completely forgot
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  Speaker 2: about what I wanted to talk to him about, which
• 13:02
  Speaker 2: is another solution set that we have that could solve
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  Speaker 2: another need for him. And I started to walk away,
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  Speaker 2: I was about 20 feet away. And I finally, you know,
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  Speaker 2: once I kind of was out of the emotional bubble,
• 13:15
  Speaker 2: I realized then I went back to him and I said,
• 13:16
  Speaker 2: oh yeah, by the way, we also have this capability
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  Speaker 2: and actually turned into a new opportunity. So I love
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  Speaker 2: the fact, and I'm really excited about the prospects of
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  Speaker 2: AI almost in real time. As we're having discussions as
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  Speaker 2: business developers, it can be prompting us with next best
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  Speaker 2: actions so that we as the human in the loop
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  Speaker 2: aren't getting overwhelmed by the purely emotional. It's just giving
• 13:45
  Speaker 2: us that nudge of, oh, by the way, you know,
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  Speaker 2: you may not have noticed this in your discussion for
• 13:51
  Speaker 2: the past hour or, you know, the days that you've
• 13:55
  Speaker 2: had engagement with your prospect or your customer, but hey,
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  Speaker 2: here are three next best actions you should pursue. Great.
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  Speaker 2: I love that. I love that because we're all fallible
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  Speaker 2: as humans.
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  Speaker 3: Absolutely.
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  Speaker 2: That's really exciting, Matt. I'm Okay, great. Well, let's move
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  Speaker 2: on to tactic or key takeaway number three. And again, folks,
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  Speaker 2: we're talking with Matt Wilkinson. He's the author of the
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  Speaker 2: new book, The Buyer in the Loop. Okay, Matt, let's
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  Speaker 2: roll on to key takeaway number three, please.
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  Speaker 4: So this is my absolute favorite takeaway. So I saved
• 14:30
  Speaker 4: the best till last, and that's bringing the buyer into
• 14:33
  Speaker 4: those internal meetings.
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  Speaker 3: I heard that Jeff.
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  Speaker 4: Bezos, when he was you know, early days of Amazon,
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  Speaker 4: you would always leave an empty chair to represent the
• 14:41
  Speaker 4: customer in any of those meetings. And I think it's
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  Speaker 4: so important that we do something similar, but now we
• 14:48
  Speaker 4: have a tool that we can use. And so we
• 14:50
  Speaker 4: don't just have an empty chair. So we've kind of
• 14:52
  Speaker 4: remembered not to forget the customer, but we've actually got
• 14:55
  Speaker 4: a tool that we can use to represent the customer.
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  Speaker 3: And so by building, you.
• 15:00
  Speaker 4: Know, synthetic customers based off of everything we know about them,
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  Speaker 4: we can then ask them questions. So if we're having
• 15:06
  Speaker 4: a conversation, well, I wonder what the customer would say
• 15:09
  Speaker 4: about X or Y. Well, we can ask them, is
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  Speaker 4: it perfect? No, it's never going to be perfect, but
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  Speaker 4: it's going to be based off everything we already know.
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  Speaker 4: And it's going to take away a lot of our bias,
• 15:20
  Speaker 4: at least in terms of the individual conversations we've had.
• 15:24
  Speaker 4: You and I may deal in different markets. And by
• 15:28
  Speaker 4: being able to bring that together and ask our whole
• 15:31
  Speaker 4: corpus of customers, all of a sudden we get a much,
• 15:33
  Speaker 4: much stronger answer. So that's something that really excites me
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  Speaker 4: about what this technology can do to really help us
• 15:41
  Speaker 4: keep the customer as the focus of what we do
• 15:43
  Speaker 4: as organizations.
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  Speaker 2: Yeah, Matt, this is music to my ears. I can't
• 15:48
  Speaker 2: tell you how many times I've been frustrated. And I'm
• 15:50
  Speaker 2: sure a lot of folks listening in on this as well.
• 15:53
  Speaker 2: You've been in a proposal room, you've been in the
• 15:56
  Speaker 2: conference room, and you're trying to decide your next best actions.
• 16:02
  Speaker 2: You're trying to decide your strategy, your tactics. And it's
• 16:06
  Speaker 2: usually the loudest corporate voice in the room that makes
• 16:11
  Speaker 2: the decision and sways the entire group, as opposed to
• 16:16
  Speaker 2: the loudest customer voice in the room. You know, you
• 16:19
  Speaker 2: get some of these folks and senior executives in particular,
• 16:23
  Speaker 2: and they think they know the customer. They've been in
• 16:25
  Speaker 2: the industry 30, 40 years. Don't tell me. I know
• 16:27
  Speaker 2: what's best for the customer. You know, it's kind of
• 16:29
  Speaker 2: one of these situations that I'm sure people have been in.
• 16:34
  Speaker 2: And I've been in that situation. I've looked at these
• 16:37
  Speaker 2: people like, you haven't even talked to the customer. You
• 16:40
  Speaker 2: haven't been at a customer location or talked to a
• 16:43
  Speaker 2: prospect in 10 years. You're so out of touch.
• 16:46
  Speaker 1: How do you know?
• 16:48
  Speaker 2: So now we actually have an objective third-party element that
• 16:53
  Speaker 2: is AI that truly listens to every customer, listens to
• 16:59
  Speaker 2: every interaction, and can provide that kind of de facto
• 17:05
  Speaker 2: customer representation, that customer voice to us in almost real
• 17:10
  Speaker 2: time to say, this is what the customer would say.
• 17:13
  Speaker 2: There's no emotion. There's no ego involved in any of this.
• 17:18
  Speaker 2: I'm really excited about it, Matt. How do you actually
• 17:21
  Speaker 2: implement this with your customers? Do you actually, during meetings,
• 17:27
  Speaker 2: are you consulting with the AI?
• 17:28
  Speaker 3: How does this work?
• 17:30
  Speaker 4: Yeah. So, I mean, there's two phases to this. One's
• 17:32
  Speaker 4: building them and delivering them. And then there's the, you know,
• 17:35
  Speaker 4: how do you advise people to use them? We've been,
• 17:38
  Speaker 4: you know, we've been taking data from across, you know,
• 17:42
  Speaker 4: voice of customer research from across 10 year spans, building
• 17:46
  Speaker 4: that into synthetic customers that can help not only kind
• 17:49
  Speaker 4: of in the business developments to face it, but also
• 17:51
  Speaker 4: in the R & D phase. So when you're actually
• 17:53
  Speaker 4: thinking about ideation and starting to look at how do we,
• 17:56
  Speaker 4: you know, if we're going to build two or three capabilities,
• 17:58
  Speaker 4: what's important to So it's really trying to turn that
• 18:01
  Speaker 4: insight into something.
• 18:02
  Speaker 3: That's really actionable.
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  Speaker 4: Because if you've got 300 pages of data transcript, you
• 18:10
  Speaker 4: can't hold that in your head as a human being.
• 18:12
  Speaker 4: And so that's something that we do. But I think
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  Speaker 4: it's just really important to have something that you can
• 18:16
  Speaker 4: then say, let's ask the customer. And one of the
• 18:19
  Speaker 4: things that we can do is that with tools like
• 18:22
  Speaker 4: Claude and ChatGPT, you open up whatever tool it is
• 18:25
  Speaker 4: and you put the prompt in using the microphone. So
• 18:27
  Speaker 4: you can actually ask it. The response might be via
• 18:33
  Speaker 4: text message rather than read out loud. Sometimes it's a
• 18:37
  Speaker 4: bit harder using the whispersync thing with these synthetic customers.
• 18:43
  Speaker 4: But you've got something that represents your customer right there
• 18:46
  Speaker 4: and then. And so if you're getting to those difficult decisions,
• 18:49
  Speaker 4: you absolutely can just ask them in the meeting.
• 18:52
  Speaker 2: Yeah, and what I like, Matt, is you're saying that
• 18:54
  Speaker 2: this could be used across the enterprise. And business development
• 18:58
  Speaker 2: spans the entire customer journey from the awareness phase, the
• 19:05
  Speaker 2: activation phase where business developers typically get involved to the
• 19:08
  Speaker 2: conversion phase where you typically have salespeople to the customer
• 19:13
  Speaker 2: success phase and then the growth phase where you're identifying
• 19:15
  Speaker 2: new products, new upsells, new capabilities. And these are all,
• 19:21
  Speaker 2: you could use these tools across that entire customer journey.
• 19:26
  Speaker 2: And that's what I'm really excited about to see where
• 19:29
  Speaker 2: this is going, Matt. And I'm glad you're really exposing
• 19:32
  Speaker 2: everybody to a little bit of the future of what
• 19:35
  Speaker 2: business development looks like. I think this is what business
• 19:38
  Speaker 2: developers have wanted for so long. So it's not the
• 19:43
  Speaker 2: loudest corporate voice in the room. It's the loudest customer
• 19:45
  Speaker 2: voice in the room. I also think it's exciting from
• 19:49
  Speaker 2: just a role play scenario standpoint. Let's try our pitch.
• 19:53
  Speaker 3: Okay.
• 19:54
  Speaker 2: Let's ask the AI decision maker persona. Great. Now let's
• 20:00
  Speaker 2: ask the champion.
• 20:02
  Speaker 3: Okay.
• 20:02
  Speaker 2: What are they thinking? What are they doing? This is
• 20:04
  Speaker 2: really exciting. Okay, Matt, let me summarize everything we talked
• 20:10
  Speaker 2: about here today. And please jump in if I miss
• 20:12
  Speaker 2: something or misstate something. But key takeaway number one, first,
• 20:17
  Speaker 2: gather all of that data that you have available, all
• 20:20
  Speaker 2: those customer conversations, those prospect conversations, and really assemble your
• 20:25
  Speaker 2: data set so that you can start to move into
• 20:29
  Speaker 2: key takeaway number two. And that's where you assemble your persona,
• 20:35
  Speaker 2: if you will, your AI synthetic customer or your AI
• 20:39
  Speaker 2: synthetic prospect that now analyzes all of that data set
• 20:45
  Speaker 2: objectively and it understands, it can speak essentially on behalf
• 20:52
  Speaker 2: of all of those prospects that you're pursuing, all of
• 20:57
  Speaker 2: those customers that you have. And then finally, is using
• 21:02
  Speaker 2: that tool, engaging with it. Engaging with it as if
• 21:05
  Speaker 2: you would have them seated at the conference room table,
• 21:08
  Speaker 2: not like Jeff Bezos used to do and just have
• 21:11
  Speaker 2: a placeholder there with an empty seat, but actually virtually
• 21:14
  Speaker 2: fill that seat with the best voice of your decision maker,
• 21:21
  Speaker 2: your champion, your economic buyer, all those folks that are
• 21:25
  Speaker 2: in that buying committee so that you can achieve success. Matt,
• 21:29
  Speaker 2: I'm excited because I think so many people listening to
• 21:32
  Speaker 2: this will achieve some success with your book and the
• 21:37
  Speaker 2: few pieces of information that you shared with them today.
• 21:40
  Speaker 2: But how can they learn more about you, connect with you,
• 21:44
  Speaker 2: get a copy of your book?
• 21:46
  Speaker 4: Yeah, so the book is available on Amazon and Lulu,
• 21:49
  Speaker 4: so it should be available worldwide. They can connect with
• 21:52
  Speaker 4: me either through LinkedIn, just search for Matt Wilkinson. In fact,
• 21:56
  Speaker 4: Matt Wilkinson, all one word at the end of the
• 21:58
  Speaker 4: Bing will get me there. Somehow I seem to have
• 22:00
  Speaker 4: been on LinkedIn for a long time. Or they can
• 22:03
  Speaker 4: find me at striven.com, S-T-R-I-V-E-N-N.com, which is the company website.
• 22:10
  Speaker 3: All right.
• 22:10
  Speaker 2: Well, Matt Wilkinson, we all strive to achieve AI excellence
• 22:16
  Speaker 2: like you. Thank you for sharing all of your knowledge
• 22:19
  Speaker 2: with us today. And thank you for everything that you
• 22:21
  Speaker 2: do to take business development into the future.
• 22:26
  Speaker 3: Thank you for having me, Tony. It's been great.
• 22:30
  Speaker 1: Thank you for listening to the Business Development Podcast. Join
• 22:34
  Speaker 1: our free community of corporate partners and business development professionals
• 22:38
  Speaker 1: advancing the art, science, and ethics of the business development
• 22:43
  Speaker 1: profession at gbdassociation.org.