Ep 14: SAMPS Boston Spectacular

Transcript

Transcript

Matt Wilkinson and Jasmine Gruia-Gray reflect on the SAMPS Boston conference, exploring how AI is transforming life science sales and marketing while amplifying the need for genuine human connection.

Welcome and Event Overview

Speaker 1 [0:04]

Hey, Matt, how are you? I'm good. Thank you, Jasmine. How you doing good?

Jasmine Gruia-Gray [0:09]

Good. Welcome everybody to another episode of Splice of Life Science Marketing. This is actually going to be our last episode for the year. I can't believe how fast the time is gone.

Matt Wilkinson [0:21]

I know 14 episodes in I think it is. And you know that'll draw to the end season one, and we'll start Season Two at the beginning of 26 which will be really exciting.

Jasmine Gruia-Gray [0:31]

We should have confetti flying around now to celebrate.

Matt Wilkinson [0:34]

Or we should be wearing Christmas jumpers. All right, I've

Jasmine Gruia-Gray [0:38]

got my reindeer earrings. That's as close that as I'm going to get right now.

Matt Wilkinson [0:42]

That's fair enough. As you can see, I'm still wearing grey, so I need to go and grab a red jumper. If we're going to do anything, I'll spare myself the embarrassment of that.

Jasmine Gruia-Gray [0:53]

So today we wanted to talk about an event that you and I were at last week, that's the SAMPS or Sales and Marketing Professionals in Life Sciences annual conference that took place December 3 and fourth in Boston, and the theme was about the human AI advantage. And you were one of the speakers and also one of the workshop facilitators.

Matt Wilkinson [1:22]

Yeah, it was a fantastic event. And I know that you did a lot of work putting together the agenda and working to put it together. It was so well organised. The room was fantastic. We had views over the Charles River and sunset just from up the top of that the hotel, the Hyatt Regency, was just phenomenal. But, yeah, it was really, really good event. Had so many exciting conversations, and the sorts of conversations that you couldn't have with a nail that was, that was exciting to get out of this little room here and get to see you in person, but also so many people in person. It was a really great event. And ever since, my LinkedIn has certainly blown up with just how much positivity from the event and how much people enjoyed the whole the whole day. It was really, really good.

Jasmine Gruia-Gray [2:05]

I agree, the energy was really, really high. The buzz in the room during the networking event, as well as during the breaks, during after the presentations, was just so palpable. And in fact, there were times when I had trouble getting everybody to get back into their seats to kick off the next presentation. And I think similarly, those kinds of conversations don't happen over Zoom or over Teams meetings, those kinds of opportunities where you can listen into some other conversation and join another conversation doesn't happen when we're all working remotely. So there's a lot of power still, even today, in meeting in person and coming together as a community.

The Growing Need for Human Connection

Matt Wilkinson [2:54]

Actually, I think it's probably going to increase the need for those I think as we see more AI generated content and the quality of video, the quality of imagery that AI can create, we may even see AI avatars joining meetings and being a digital twin of us and having some knowledge of what we you know what we're doing, and being maybe able to ask questions at least, about the status of projects and things like that. The need for that human to human connection is probably going to increase.

Jasmine Gruia-Gray [3:23]

I hope so. Also, thought where you were going to go with this is, you know, as people are starting to not trust what's real or what's AI created, the only reality, in fact, is when you meet in person.

Matt Wilkinson [3:42]

I think that's going to be a huge part of it. I think there's already a bit of a backlash in some places about what is, what is real, what isn't. And while I think there are huge advantages of using AI and applying AI to solve challenges, I think that there's going to be a big distrust of certain media as well. So I think it's a case of those face to face interactions becoming more and more important.

Jasmine Gruia-Gray [4:05]

Over time. I certainly hope so. I enjoy that. Was there anything that you found surprising over the day and a half?

Surprising Learnings About AI Adoption

Matt Wilkinson [4:15]

I thought, what was really surprising? I know that you started off by sort of asking people's opinions about AI, and where they sort of sat on a scale of being an AI sceptic to being all in most people kind of had the same sort of opinion of cautiously optimistic about AI, the same sort of thing that we found it when we're interviewing people at ELRIG. So I thought that was that was interesting. I think the other thing that was interesting was that a few people changed their opinions and became a little bit more positive about AI. But I think what really surprised me was the number of people that sort of thought I need to do a little bit more now, and how the talks and the day really opened their eyes to what was possible and what we could be doing with AI, if we, if we just look around it. So that was, that was what's interesting at companies that are so on the cutting edge. What they do, and yet maybe not cutting edge at applying the tools that are available to them.

Jasmine Gruia-Gray [5:06]

Yeah, what was surprising for me was how wide eyed everybody was at what was possible, you know, during your workshop, and especially during Andy Crestodina's workshop, where he would talk about a particular use case and then give folks prompts to try that particular use case in their own situation. And it was almost sort of like this childlike Wow, oh my God, look at this. I just built a castle out of Lego kind of feeling in the room, which I found surprising. I somehow thought that more people would have had had those experiences already. I think

Matt Wilkinson [5:53]

that there's a level of adoption of AI where people are quite comfortable using it for writing text, but I don't think people are using it in the same way, as, you know, in a create persona, Persona AI, and then I'm going to use that to check my work, to check what's on the website, to use it to create content. I don't think people are putting disrupting entire processes that they're looking at kind of point solutions. And I think that, I think a lot of people are still using AI as very narrow tools rather than sort of seeing the systemic disruptive effects that it really can have.

AI Reveals Deficiencies, Not Just Efficiency

Jasmine Gruia-Gray [6:26]

Yeah, I like the way Andy Crestodina summarises this. It's not so much about the efficiency, it's about the deficiencies that AI can point out and help you resolve.

Matt Wilkinson [6:41]

Oh, absolutely. And I think it shows as well the deficiencies in the existing processes. You know, one of the things that I absolutely love about AI is, you know, when we're talking about persona, we struggle to put ourselves in the shoes of the customer and understand whether that's whether that's the persona, or actually the person that we're speaking to at the other end of a call or in a meeting, we struggled to be able to bridge that gap. And so I think that with AI, we can really show, well actually, here's the spectrum of all space. This is where our personas sit. We, you know, within our ICPs, here's where their personalities are. And let's look at how we can get closer to them. And I think it really helps us to show that deficiency of our understanding, of our ability to move towards the customer and really be able to solve their problems and their needs and really be able to communicate how they want to be able to communicate it too. And I think the other thing that I learned through trial and error and quite an embarrassing public failure that I showcased was how even when you build an AI role-play for a sales that even though you've built it and you've specified the targets that you can miss them so wildly, because I only scored 50% on that test the first time I did it, and that was not made up. That was me genuinely trying to do a sales pitch and see how I did. And I'd created the persona and the scenario within Claude AI, and yet I missed the mark by so much on that pitch and and I showed the snippet of the best bit, which still showed a failure. But I think to me,

Jasmine Gruia-Gray [8:11]

that was a hugely valuable example of how you need to go back and forth. It's not just you know prompt, get the right prompt, and out comes the answer, and off you go to generate the next set of tasks. It's really a dialogue and and it there's a continuous improvement loop that I think a lot of people have been missing out on, that you really brought to the fore with your example?

Learning Styles and Cognitive Offloading

Matt Wilkinson [8:42]

Yeah, I think there's also the false comparison as well. We look at AI, and if AI doesn't give us the right answer first time, it doesn't work, it's not good enough, which is fair. But then there's the human in the loop that's maybe not giving it the right information either. But then I think we also have to look at ourselves and how many humans are perfect. I know I've certainly never written anything myself before, AI that didn't need some spell checking. In fact, when I was writing my PhD thesis, I somehow managed to add an extra character. So it was it apostrophe s, it was the wrong version of the word, and I had to go and do a global change, because I'd made this mistake time and time again, because my fingers just somehow made a mistake. Now that's pure human error, but we expect the AI to be better than that. And that's what's really interesting, that kind of we expect those outputs, and I really hope to show is that we can use AI, not just to create things for that are outputs that are better, but actually how we can help use AI to help ourselves get better, both from role playing, but also how to learn better and more in our own modes as well. And that was something that really struck me, was that by getting all this information about account intelligence and buyer intelligence and personalities, I could get all of this massive data and I could overwhelm myself with just too much information that I couldn't absorb. And even though I'd read it and think I've understood it, I haven't actually taken that in. You know, we talk about cognitive offloading quite often, that we give that the AI jobs to do, but then we're not really absorbing that information ourselves. We haven't done the hard work. And I think that's something that I really noticed by through that, through the creation of that talk, that actually by creating that, that scenario where I was going to go out and pitch as to a potential customer of theirs, and I was going to go through this process, that what I realised is, actually I don't learn as fast as maybe I think I do, and that really being able to absorb that level of detail, you have to go through different learning modes to really absorb it, to be able to get better at this stuff. And you can't just expect to, oh, the AI's got all this information for me. It's at my fingertips, yes, but it's not on the tip of my tongue. I've not learned to, I've not absorbed it. And I think that's something that's going to be that's going to be really, really interesting as we go forward into this sort of Age of AI where real expertise is going to show by the ability to actually absorb and communicate that information.

Jasmine Gruia-Gray [11:04]

I've had the same, same experience about learning about myself and my learning style, and through learning about that, I actually am prompting differently. I'm asking for it to provide more combination information, both written and visual, those are my learning styles, not as much auditory. And I think, I think you're right, there's so much power, yes, in the education system, but even as professionals, in having AI understand our learning abilities and customising to that so that in turn, we actually elevate ourselves as professionals.

Matt Wilkinson [11:50]

Yeah, I mean, I know that I learn by doing one of the best things that I do I could Yes, I can learn by reading and I can understand, but I learn best just by doing and experimenting and and that side of things. So I find that if I can combine different modes of learning, so reading, listening, maybe watching a video or something, and getting those, those different combinations, and then being able to practise as well, that's really where I get the most value. So I love experimenting and learning from the experiment. I mean, I guess that speaks to the scientist in me, but yeah, that that kind of feels that that's where that combination of modalities really, really benefits. And of course, with AI now and tools like Notebook LM, you can create those other modalities. You can create the quizzes, and AI gives us tools that we didn't have even just three years ago. And that's, to me, is just such so powerful, and something that I think we're, you know, this getting overlooked in so many of those conversations about, oh, AI is going to steal our jobs. Maybe get better at our jobs.

Jasmine Gruia-Gray [12:52]

I agree. The quizzes have been fascinating. The flashcards, I really like, the flashcard function in Claude and in ChatGPT, those, those flashcards, have taken the place of the post it notes I used to have on my desk and on my wall. So, yeah, I think there's, there's so much potential that you and Andy Crestodina surfaced at the SAMPS meeting the the other learning I had was from Stacey Sherman, who was the keynote speaker, and she spoke about customer experience or CX, and her point is that there is a role for AI in CX, but keep in mind that there has to be a workflow connection between that AI and the ultimate human. They're not two separate departments, two separate entities.

Customer Experience Across the Entire Journey

Matt Wilkinson [13:52]

Yeah, when you when you look at service design and service design theories, I think that one of the big problems that we the organisations, typically face, and Stacey did a great job of highlighting this and sort of bringing it to life. But I think one of the challenges is that we often have discrete departments where information doesn't flow across those those areas. And I think very often what we find is that with AI, at the moment, AI doesn't have the agency that a human can have. But very often, we get frustrated with customer service if we find customer service because they don't have the agency to fix the problem either. And so one of the challenges, I think, is with organisations, is making sure that we're able as customers to get through to somebody that has agency to resolve the problem. And actually that resolution or problem may only to be, be to make you feel heard. I think there's a great example from Simon Sinek who says it doesn't matter that he can or can't fix the problem, but can you make it feel like you've heard and that somebody's tried to do it and try to solve your problem? And that's a big difference, you know, rather than just getting the sort of computer says no response, but let me have a look and see what we can do. I'm so sorry we can't book you on another flight. There's just nothing else we can do today. But here's this, and let me see if I can do something for you, and really just sort of being able to sympathise and understand the human condition behind the problem, that can make all the difference in how we feel about the situation we've encountered.

Jasmine Gruia-Gray [15:25]

Yeah, I think it's also around the handoffs from AI to the human, while years and years ago, those handoffs from one human to another were not efficient. Over time, they became more efficient. And so the customer's expectation now is that the handoff between AI, your chatbot, whatever, whatever form of AI you're using, and the human is going to be efficient. There's there's no longer a customer understanding that, okay, there's a gap. There. We get it. You know, technology is technology? No, no, that's that's not an excuse anymore. And I think she really surfaced that customer pain point quite highly that I think a lot of people in the audience may have either forgotten or didn't realise was happening.

Matt Wilkinson [16:22]

And I think it's really interesting, because you made me think of some stories I've heard of Jeff Bezos, CEO of Amazon, who would say that you can look at data, or you can look at the anecdotes, and quite often it's the anecdotes are correct that there are problems that the data doesn't show, or the aggregate data doesn't show, but the anecdotes really will show up. And sometimes it's really important for us to try and be our own customer, to try and phone up the helpline and see what happens. And I wonder how many CEOs in our space have ever done that, have ever actually phoned up and said, Hey, I've got a problem with this, what's going on, and actually being able to try and resolve a problem on it. So I think that sort of undercover boss, that undercover experience, as it were, is so important. Because actually, I think often the aggregate data that gets reported up doesn't surface those challenges. And so I think that there's a real opportunity for us through AI, just really focusing on who is our customer and what is important to them, is going to be really, really important. And in the age of AI where information is going to be democratised and shared, and where experiences are going to be spoken about, and the AI that we use to do our searches is going to find out about those experiences, we actually need to be far more focused on customer experience. And what does it mean to be a customer, and what does it mean to our customers, to be a customer and for that loyalty? So I think there's a huge opportunity for us now to really focus on making those experiences not just okay, but really something magical, as Stacey said. And you know that that's going to be more and more important.

Walking in Your Customer's Shoes

Jasmine Gruia-Gray [17:59]

It's walking in your customer's shoes. I know that's a really, really old saying, but it's never been more relevant as it is today. What is that experience? Whether it's a new workflow or whether it's an old workflow, walking in those shoes and putting your customers hat on is so, so important. You know, what I've done in the past is divide my team up into Team A and Team B, and once there is a new workflow, have one of those teams experience that new workflow, you'd be surprised how many times you press a different button than what you intended to press when the workflow was designed, or you don't see a certain section on the menu when you thought, Geez, this is a no brainer. It's obvious when you're looking at it through a different lens.

Matt Wilkinson [18:56]

I think it's really interesting to do that exercise and really be able to understand, you know, what are those behaviours? I did quite a bit of hidden needs research during my MBA, and we and we looked at what those behaviours were, and tried to understand some of those customer needs. But also, what are those customer work around? And one of my favourite stories was that a European manufacturer called Miele, and they make, you know, home equipment. And one of the things that they did was they studied asthmatics and people with dust allergies. And so they actually watched them vacuuming their hurt their houses. And what they realised was that people would be cleaning the same spot over and over again because they didn't know when it was clean. Dust particles are charged. And so they did a very simple to a charge metre within the within the airflow, so they could see when the spot was clean or not. And so by doing something simple like that, you could really change your customers workflow, because rather than them having to clean the floor 10 times, they could clean it once and go, Oh, it's clean. Now you. And just those little things can make such a big difference. And so I think really being able to focus in on those customer needs across the entire service journey, from understanding what the product needs to be to actually understanding how service delivery should be is so important. You know, I did some research and when I was leading a big e-commerce transformation, and one of the things was, was that when people were ordering oligonucleotides, that there was a huge amount of stress involved in actually copying the sequences from one document to another for placing orders. And partly that's because, particularly when you were selling into diagnostics labs, and that these are bigger, big orders, if they got one letter wrong, that was a big expense. But also could be a long time to get the manufacturing right, to then be able to get through the validation, the testing and everything else, it was a big deal. And so by simply making reordering easy, we got rid of that stress for them entirely. And so there was sort of this, these things where you can, you can look at those needs and those sort of service experiences and go, You know what? We're making this really difficult for somebody without intentionally doing so, even though it's easy to think, Oh, we've just copy and paste a cell, well actually from one Excel sheet to another, or one Excel sheet to an ordering system. But actually, some of those transformations can be incredibly difficult to do. And so if we can make sure that we understand what our customers need and that whole service journey, we can make life so much easier and build so much customer loyalty and and brand affinity.

Three Key Takeaways

Jasmine Gruia-Gray [21:32]

So speaking of making things easier, let's, let's round out this conversation by making it easier for our audience to understand what were the three take home messages that you got from SAMPS last week?

Matt Wilkinson [21:46]

Well, I think that the first one has to probably come from Stacey, which would would have been the customer experience. Is the entire journey. We know, we all know this, but the way that she articulated that in a beautiful example and sort of case study was really, really powerful for me. So that was the first the second, it was probably from my own talk and and that you almost have to earn the right to educate. So by trying to bring humour and entertainment into that journey, I really felt that made a big, big difference. And it's something that I've worked on a lot this year, thanks to Mark Schaefer's public speaking course really sort of taught me to try and be as audacious as possible, but also to try and make sure that you're breaking things up to earn the right to educate. So that was something that I thought was really important. And then I think finally, my last takeaway would be probably from Andy's workshop, which was just seeing people light up, seeing the potential of being able to use AI in different ways. So those were probably my three big things, apart from, of course, just the fact that you'd organised a fantastic event and that connecting with people is just incredibly important.

Jasmine Gruia-Gray [22:53]

Yeah, yeah. For me, my takeaway with Stacy was that it's everybody's job to think about customer experience, from the CEO to the intern. You don't have to have a specific title. You don't have to be in a specific department. It's everybody's role to put that customer hat on and look at it through the customer's eyes. From you. It was all about the power of workshops and the power of learning and practising what you learn. The whole idea and the scenario you created around a competitor has just launched a new product a little bit before you're going in to make a major sales pitch. Was such a real world experience that I've had many of my colleagues experience and the way you involved everybody by rolling up their sleeves and creating a value proposition, redefining the pitch felt very real world, and to me, was a take home of we should all be doing these workshops on a much more routine basis. From Andy, it was about the word engineering in the term prompt engineering, it's always tweaking, it's always refining. It's going back and forth with your LLM. It's using it and then realising, no, that wasn't quite right when you you try and implement it and go back to the LLM was, was a real take home message for me. Yeah.

Matt Wilkinson [24:38]

And that's interesting, because, you know, we saw people talking about prompt engineering being the big next job, and I think that that that sort of drive has disappeared maybe, maybe it's just fallen out the news, but it's something that certainly I took to heart very early on, about trying to engineer and optimise the process of using AI so I'd get repeatable outputs. And so it's been really interesting for me to sort of watch a room full of people kind of come to that real same realisation. AI is, is incredibly intelligent, for wonderful word, I mean, it's artificial intelligence, but it's also incredibly stupid. So if we give it bad prompts, it's going to give us bad outputs. So it's, you know, garbage in, garbage out, but if you give it sort of repeatable, really helpful inputs, and you're choosing that the most appropriate model, you'll get pretty repeatable outputs. And I think that's a really powerful takeaway for me, that there's still a lot of AI adoption, there's a lot of lot of learning for organisations to go through and sort of that adoption and adaption, or, you know, journey agreed.

Jasmine Gruia-Gray [26:10]

And there is no perfect prompt, and that's often why I end almost every one of my prompts these days with Ask Me Anything before starting, because it will know what gaps it needs to fill before delivering the output you want. That's that's my, my little tip for the for this episode.

Matt Wilkinson [26:10]

Yeah, I love that. And then I go back and recycle multiple times Exactly.

Closing

Jasmine Gruia-Gray [26:17]

Well, this has been super fun. Thank you so much Matt, not only for being my partner in crime on this podcast, but for just a spectacular presentation and workshop at the SAMPS event last week.

Matt Wilkinson [26:32]

Well, thank you so much, Jasmine. It's been it's been fun, and thank you for the invite to go to Boston. It was great to be a Britain Boston and to to misquote the late great Paul Revere, with the bots are coming. The Bots are coming, and I think we can say that they're already here. So thank you so much.

Jasmine Gruia-Gray [26:48]

And thanks everybody. Looking forward to seeing everybody in the new year on another episode of a Splice of Life Science Marketing. Bye for now. Happy holidays. Everybody. Happy holidays.

Q&A

How do I start using AI role-play for sales training without overwhelming my team?

Pick one upcoming high-stakes pitch and create a simple persona in Claude using your customer research. Have your rep practise the pitch against the AI, then review the transcript together. Start with 15-minute sessions once a week. The key insight: expect to score 50-70% initially - that's where the learning happens. Document what the AI catches that you miss, then incorporate those patterns into your prep process.

What's the fastest way to identify deficiencies in our current workflows using AI?

Choose one repetitive process your team complains about - proposal writing, competitive battle cards, lead qualification. Feed the entire current workflow into Claude and ask it to identify friction points and unnecessary steps. Then ask for a redesigned version. Compare the two outputs with your team in a 30-minute workshop. You'll surface 3-5 concrete improvements within the first session that can be implemented immediately.

How can I avoid cognitive offloading and actually learn from AI-generated intelligence?

After AI generates account or buyer intelligence, force yourself to synthesise it in your own words. Create a one-page summary by hand or record a 2-minute voice memo explaining the insights. Then use Claude's quiz function to test your retention. Schedule this review 24 hours after the AI generates the brief. This multi-modal approach - reading, synthesising, testing - ensures the intelligence moves from fingertips to tongue.

What's one practical way to improve AI-to-human handoffs in customer experience?

Map your current customer journey and identify every AI touchpoint. For each handoff to a human, test it yourself as a mystery customer. Record where context gets lost. Then create a simple handoff protocol: AI must pass three pieces of information to humans - customer intent, conversation history, and specific pain point mentioned. Implement this in your CRM notes or ticketing system. Test monthly with real scenarios.

How do I get my team to move beyond using AI for text generation to more strategic applications?

Run a 90-minute workshop using Andy Crestodina's approach: identify one strategic challenge your team faces - persona validation, competitive positioning, or content strategy. Then work through it together live with AI, showing the iterative dialogue. Let people experience the "aha" moment of AI revealing deficiencies in their thinking. Follow up with office hours twice weekly where people can bring specific use cases and work through them collaboratively.