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Transcript
Our transcripts are generated by AI. Please excuse any typos and if you have any specific questions please email info@digitalshelfinstitute.org.
Lauren Livak Gilbert (00:00):
Welcome to Unpacking the Digital Shelf, where industry leaders share insights, strategies, and stories to help brands win in the ever-changing world of commerce.
Peter Crosby (00:22):
Hey everyone. Peter Crosby here from the Digital Shelf Institute. The e-commerce industry over the last decade has relied upon the connoisseur strangers, to paraphrase Tennessee Williams. People who on the path of their career share their discoveries, painful lessons, and future musings with the rest of their peers. One such person is our guest, Todd Hassenfelt. Todd is senior director, global digital commerce strategy and execution at Colgate Palmolive, who brings both his wealth of knowledge and optimistic perspective to this conversation about focusing, deprioritizing, and driving change management in what will no doubt be another truly transformative year in commerce. Welcome back to the podcast. Todd, we are so excited to have you here to kick off our 2026 season. So excited.
Todd Hassenfelt (01:13):
No, thank you for having me. Can I just say thank you to both of you for all you do for the DSA, the community, the industry as a whole, this podcast, the reports, snackable insights, so much that you all do. So thank you to both of you, the teams that are not on this podcast. But I just want to say thank you and start maybe the year with some gratitude that we should probably do more often.
Peter Crosby (01:40):
Oh my gosh. Let's just stop it right there because I think it's all day long. That's over. Thanks so much. No, well, we rely completely on folks like you that are willing to give back to the community and so gratitude back at you for all the thinking and sharing that you do. It's so important.
Lauren Livak Gilbert (01:59):
We're
Peter Crosby (01:59):
All in this together for sure. You're
Lauren Livak Gilbert (02:00):
Always willing to give your time, so we feel as grateful to you as you do to us.
Todd Hassenfelt (02:06):
Well, just try and be helpful. We are all learning together. And I will say as we talk through this podcast, I am at Colgate Palmolive, but my experiences today, they're from a wide range of my experiences at other companies, which includes brick and mortar, e-com, two startups, two big ones, one in between, but also share groups, conversations, advisory boards that I'm lucky to be part of. So it's kind of a combination of everything, just not a Colgate Palmolive perspective.
Peter Crosby (02:36):
So blame Todd, not Colgate Palmolive. That's what I'm hearing for anything that comes out in this podcast. So I feel like as we enter into 2026, it feels like we are in a whole new role of transformation when we're not even finished with the last one. And so there's so much change happening, so much transformation, but there's also, at the same time, a lot of noise, a lot of hype, a lot of people trying to drive urgency or panic or whatever towards new things. And you are so good at separating the wheat from the chaff and focusing on the right things and all the things that you talk about. So we want to dig into that. What are the things we should care about? What are the things we should all take a collective breath and relax about? Because I think we all need that going into this year to make sure we're focused on the right things.
(03:28):
And so with that, Todd, I would love you to just ... What are some of the things that hop into your mind about what we should be talking about, what should be on our minds?
Todd Hassenfelt (03:40):
Yeah. I mean, there is a lot going on and maybe the deep breath comment you made, let's level set. I'll put one prediction out there. Robots are not taking over our homes or doing all of our shopping in 2026. All is the keyword there. Oh, man. And listen, this is
Peter Crosby (04:00):
Where- Cancel our next podcast, Lauren.
Todd Hassenfelt (04:05):
Exactly. Exactly. I think there's a difference of what technology can do and then what people are comfortable with technology doing for them. And even I think we just saw in the last holiday season, a lot of people were maybe trying more of the AI assisted tools like Arufus or Sparky because they were looking for gifts for others, not only just looking at stuff for themselves. And so I think that what they can do and what they wanted to do is a lot different. Also, cameras and sensors in people's homes are a blocker to a lot. Think about some things that are similar to this whole agentic shopping and robots doing everything or bots. Driverless cars. I've used this example in the past. It's kind of a proxy for e-comm sometimes in a lot of ways. Did something with Amanda Wolf back in the day. But anyways, only 15% of people are comfortable saying that they would get into a driverless car.
(05:08):
The majority of people actually fear it. Well,
Peter Crosby (05:12):
Literally over the holidays, the lights went out in San Francisco and the autonomous cars just stopped, which I think is probably a good idea. But nonetheless, they stopped doing their job at the same time. So yeah, I'm with you that autonomous is not everything that's cracked up to me.
Todd Hassenfelt (05:29):
Yeah. And you think about just things, AI kind of tools in our house already or a lot of people's home, smart speakers, despite all the things they can do, most people are using them for weather, timers, and music. And there's so much more. If you want a fun story, next time you see me in person, I'll tell you how I taught my youngest during COVID how to be potty-trained using Alexa. But that's a side story for another day. And then if you go back to this shopping side story, I don't want to go down that one. But the shopping aspect, think about subscribe and save. Outside of Pet and a couple other categories, I know Dewey will be happy. Lauren's big dog Dewey hearing about Hills and Subscribe and Save there and Pet. But in all seriousness, Subscribe and Save is still not even a majority of consumers using that.
(06:22):
So these are a lot of hurdles that we haven't overcome as an industry, as consumers or whatever. So that's why I say the extreme robots are not taking over all of our shopping and are coming into our homes. Where I do think it doesn't mean agent to commerce or AI shopping isn't going to be a thing, it definitely is, but I think this is more like an AI-assisted sales will be more prominent or more likely to be adopted than the bot or the robot making the actual purchase.
(07:02):
And some data, there's data everywhere, but some of the things that you can find will say half of AI users are using it to influence purchasing decisions, but only a small, small portion is actually making purchases yet. And we might have a precedent with this one. This is kind of like social commerce or where yes, a lot of people see something and TikTok shop has gotten better here, but others in the past five, six years, but while maybe four times less, use actually the shopping mechanisms within the social commerce, they go to a different site that they want to go buy themselves. So I think this AI-assisted sales is more where we go, and maybe it's just AI doing that concept of personalized, frictionless shopping better than we all have done in CPG because it's the person, the human giving the signals in real time using AI to put in their prompts or their questions and now getting information back.
(08:14):
So I don't know. I mean, that's how I look at. There's a lot of different opinions out there, but I just think there's a lot of hurdles we haven't overcome and digitally influenced sales has always been something that's tough to track, but I think it's similar here. That's maybe why many are not yet talking enough about AI-assisted sales.
Lauren Livak Gilbert (08:35):
I agree with you, Todd. I mean, I don't think we're there yet. We're not in a world where you can just have an AI agent run your life would be really nice. I think we're like, I don't know, seven, 10 years away from that. If that, there's a lot of things that need to fall into place. But your point about AI enabled or AI assisted, I think is really important because it enables us to do so much that we haven't been able to do in the past more efficiently at scale. I mean, I just bought a house and I'm trying to price match a lot of stuff because it's very expensive and I'm using agents to do that and then it triggers when we should buy. So there's all those different pieces that I think are going to make the consumer experience much faster and easier and even more human.
(09:19):
But I love your kind of deep breath comment that it's not going to happen overnight and you still need to really focus on the fundamentals that you were focusing on before with digital and e-commerce in order for that to even be successful. Yeah.
Todd Hassenfelt (09:33):
Yeah. And the overnight one, I love this one and it's true, just happened over the holidays. I still am behind people in the grocery store writing paper checks every once in a while. And that's fine. Everyone's different, but we're not there yet.
Peter Crosby (09:51):
I can't remember the last time I wrote a check and thank God. I hate writing out that second line where you have to do the 2,500 and thing and 0.9. Zero,
Lauren Livak Gilbert (10:02):
Zero over. Yeah.
Peter Crosby (10:03):
Oh my God. I had to remind myself how to do it the last time.
Lauren Livak Gilbert (10:08):
Oh, man. Well, Todd, so what is something that brands should be spending time on outside of what we just talked about that really can make a difference in 2026?
Todd Hassenfelt (10:20):
It may seem obvious, but when you think about what we just talked about, I mean, it's data and measurement. And let me frame it maybe just a little bit different thinking about it because everyone's like, "Oh, of course, data and measurement." Well, okay. When you think about data, and again, hearing this a lot in share groups and everything, but the patterns that I see is with data, teams don't ... It's like one of four things are usually the issue. There is no source of truth of where that data comes from. And just to be clear here, while AI is a big part of it and maybe why we're talking this way, this is non-AI too.
(11:02):
So if you don't believe Agenttech commerce was coming or AI, this still matters. So there's no source of truth. No one knows where the information is. Maybe it's just stored in someone's head, whatever it may be. The second one would be competing sources of truth. Two teams, two people, they have different perspectives on what is right. Maybe it's something in the middle, maybe one is right, one's wrong, but we have different, this is the whole silo concept. So you have competing sources of truth, or you have the fun one like fragmented sources of truth where one team has this piece, another one has this, another one has the spend here, another one has the data for the consumer, but they all don't talk to each other or they don't know the other one's have it. So that's kind of like, okay, no source of truth, competing sources of truth are fragmented.
(11:53):
Even if we have all that figured out and we have one single source of truth, then it comes down to bandwidth. Who has time to action it, to visualize it, to assess it, to update it, all these different things. So that's a data part. And then even depending where you are in your source of truth journey, the data you have, again, this is not just AI but amplified because of AI. It can't be incomplete, inaccurate or irrelevant because now this is where the AI piece does come in. It gets amplified on how that matters in the consumer journey. So that's kind of the data piece. If you look at the measurement piece, we can look at the tools, and that's one that it's always talked about or what you have, but it really comes down to, are you asking the right questions and what does that mean?
(12:53):
Well, are people looking for the questions that they ask, are they looking for nods or are they looking for the nuances? And I think sometimes the nods can make the slides look good and everything goes smoothly, the easy button per se, but the nuances are actually the ones that change. It's kind of like the change management or change decisions or change course in a positive way.
(13:18):
I've said in the past, all green scorecards are actually not good because you would rather be showing where and how to get better, which will probably help you get more funding for what you need to do if it's the right thing to do versus showing, "Hey, everything's green." It's really hard to get funding when you do that. So go back to plan- I
Lauren Livak Gilbert (13:39):
Was just going to add, I remember in my brand days, I would say, I can make it green if you want me to make it green, but what is that going to do for us? Because people would always say, "Why isn't it green?" And I'm like, "Well, I can change the metric if you want it to be green, but what is that providing for us?" And to your point, what question is it actually answering?
Todd Hassenfelt (13:58):
Yeah, I mean, are we measuring what's messy or what's easy? And so it's the questions and the questions that you get and that influences maybe what your workload looks like and all this, but what are some examples we could do? Are we asking about still impressions? There's good and bad impressions, or are we more focused now on conversion rates? Because I think conversion rates is really interesting right now. If you look at from the AI agents and everything going on with bots, glance views and impressions could be and maybe are skyrocketing in some ways. I know there's a whole zero click crowd conversation too, but if you're just looking at that and not the conversions, you may change your ad spend for a false negative or a false positive, however you want to look at it. ROAS, how long have we been talking about ROAS that we should be looking a little bit more than that, but I would say what's the alternative?
(14:57):
Are you asking about ROAS or are you asking about market share? And then if we talk digital shelf, obviously big topic for your audience, but how do we move from quantitative measurements to more qualitative measurements? And that goes really the backend of the data like we've talked about, talking about data and measurement here, but also then the front facing, are those bullet points quality? Are the images quality in a lot of different things? So I don't know. And then does the industry have an opportunity for this? Well, again, just looking at some stats and you can find other ones, you can find something that proves anything nowadays. But looking at a recent one, it was 94% of respondents said, this is for brands, that customer experience strategy was important to the business success, yet 93% admitted that their CX needs a lot of improvement. And even our buddy Russ at Stratably recently put out one about are people optimizing PDPs for their AI assistant, Sparky?
(16:03):
And the survey said it's an internal urgency that's escalating, and yet 80% of the brands had taken zero action to date. So there's these barriers that we have to get better at the data quality and the measurement with the questions that we're asking, I would say. And it's all about getting better. It's not picking on the past, just how do we optimize it get better?
Peter Crosby (16:27):
Yeah. And so the things that are swirling around in my head as you talk about all this, and certainly with the Rufus example is, is it a problem of incentives of culture? Because Lauren, you were talking about your experience and where people just got tired of seeing your yellow or whatever and-
Lauren Livak Gilbert (16:51):
It was red, I'll be honest.
Peter Crosby (16:53):
Oh, okay. Even worse or better. I don't know which. But then also is it in the case of Rufus, which is farther out, people just are in a sort of a freeze moment for that where they don't really know what to do, but also maybe the incentives enough and put in place for that to become a priority because its impact seems smaller and then therefore really further out. And I know that's a lot to sort of, but that's what's swirling around in my head is that a lot of it seems more a struggle. If you get the data right, then you still need the people aligned on what is it that we're trying to achieve, what are our sort of golden metrics? How have you seen that?
Todd Hassenfelt (17:39):
Yeah, I think listen, every organization is different and there's different factors. So I think the culture part of leading the question there is going to vary and everyone knows their own themselves. But the incentive part you mentioned, I think is where it does come in. And there was a place in my past where I suggested that maybe we had interns in every department in the summers, and I was like, maybe they should redo the incentive plan because they know enough about the departments, but yet not tied to their biases or making sure they don't ... We're talking about bonus and money, and I mean, this is a big deal. It's why it's so hard to change. It was just an idea. I'm not saying everyone should go and do that. It was a while ago. But anyways, I think there is an opportunity to look at that and say, what are we really incentivizing and probably create a bridge or a cushion for, I don't know, a year, two, three, maybe it's part of a five-year plan, just spitballing here, but how do you get it to a point where you can enact real change with the balance of making sure that it's still, let's say, stretch goals, which bonuses should be, but yet not making it like, "Hey, no matter what you do, you're going to get your bonus anyways," type of thing, or it's so harsh, it's too hard to get that people now it starts impacting their personal bottom line.
(19:14):
So yeah, it probably comes down to incentive structure, but it also comes down to negotiation across internally and externally. And what are we all bringing to the table that can really help call it the greater good, I guess, in our CPG world, the brand, the retailer, the consumer, the environment, et cetera. But how do we really bring that together in a way that's negotiating positively and productively? But
Lauren Livak Gilbert (19:49):
To that point, Todd, it's a cultural shift. So I've been spending a lot of time thinking about agentic transformation, what's the next phase of transformation? And one of the things I keep coming back to is that it's moving from an I mentality to a we. Right now, each of us are incentivized on our role and our metrics. And a lot of times you're in a silo and you're like, "Hey, this is my box and I'm going to do it and I'm going to go home and that's it. " Which, I mean, that makes sense. We're humans, but when you transition to more of an agentic transformation, all of the knowledge is dispersed equally across the organization and also you have the ability to see all of the data and see all of the insights. It brings everyone to the same level playing field, so it actually could potentially make it easier for everyone to feel like they have the business owner mindset hat on and they're thinking about the collective, how do we win as a company versus how do I win as one individual?
(20:49):
But that also takes a lot of fundamental shifts in incentives and ways of working and success in your role and a lot of other things. But I do think it's a shift that we'll probably move towards. I would love your thoughts on that because this is something I'm working through in my brain.
Todd Hassenfelt (21:04):
Yeah. I mean, collectively overall, yes. Yes and. My favorite saying, Todd. I know. Has that been trademarked by you yet? I wish.
Lauren Livak Gilbert (21:18):
I was
Todd Hassenfelt (21:18):
Pretty sure Improv had it first.
Lauren Livak Gilbert (21:20):
A thousand percent, yes.
Todd Hassenfelt (21:24):
No, yes and, but I guess, I mean, I don't know if this is a nice come together here from earlier, everyone may have the data and democratize kind of piece. It's still the questions or what you are doing with the data that matters, and that could still be different. A team may be more looking at one way of looking at the data versus another. One team or person may spend more time looking at the data versus another that prioritizes something else.Maybe they're in too many meetings and they don't have time or whatever it may be. So I think there's still a mechanism that has to be ... Which is why, I guess coming back to the incentive, I think Jamie said it on the podcast when he ... My boss, Jamie Schwab, that was on the previous episode, but talking about what gets measured or what gets measured gets done in essence.
(22:21):
I know it's not his and I'm not going to have him trademark it, but in all seriousness, I think it does have to incentivize where people focus their time. And then is your company, and we're lucky at Colgate Pomalo, we have incredible training and learning departments, but overall, whether it's inside or you can go outside, and it's why we have the DSI community, how can you learn and look at different ways of doing things so that you do get better maybe at negotiating, at asking the questions, at figuring out what other teams are doing, how to bring it together. I mean, I think the recent, or a little bit ago, the DSI report with IT and commercial was a fantastic one overall of saying, okay, what are you doing? What are we doing? How do we work together? So yes, yes, and it's not easy, similar as everything with AI.
(23:18):
Just because we have AI doesn't mean it makes it easier because you can't automate a process that doesn't exist or is broken already.
Peter Crosby (23:27):
Yeah. And one of the things that, in addition to Lauren's, can you be a business owner? I think that one of the things that I've been thinking about recently is the move in e-commerce and digital shelf with hopefully the assist of AI and automation is to become an architect rather than an operator. The architect being the person hopefully that will be learning how to take this data and make something of it, do you know what I mean? And action it. Because in order to do that, one, you need the skills and you probably need some sort of data person at your elbow, but it really takes somebody that understands the business to decide what to do about it, but who has the time. But if you're actually freed up from some of this other stuff, the grind, the operations of it all, because put AI on that, put your brain on, okay, where are the opportunities here?
(24:26):
Some of the things I've been thinking about with that sort of operator versus architect thing.
Todd Hassenfelt (24:31):
I love that. I mean, agree. And listen, everyone's going to use AI differently, but if AI can do more of the execution, like you're kind of saying, and the humans do more of the thinking, that's probably the right balance. And not saying that you can't brainstorm or pressure tests. I like always taking ideas and doing bias and blind spot checks, but yeah, the execution is probably, I think you're describing, Peter, is where the focus maybe should be.
Peter Crosby (25:02):
Yeah. So next question, now that we've said, hey, here's the place where we ought to lean in and then figure out what is the role of new technologies and helping us do this better in addition to the change management stuff, we cut the head off robots in the beginning, so what else would be on your list of things we need to rethink? Certainly, I think everyone's looking at the investment in retail media, the growing ass. I'm sort of leading the witness here a bit, but I see that as one place where hopefully there's opportunity there because the spend can't go on the way it has unless we start seeing increasingly incremental growth from that spend, I would imagine. So I'm wondering if that's on your list of rethink stuff.
Todd Hassenfelt (25:54):
It is. And let's bring around the phrases I think was brought to an episode in the past about retail media, which is funny, AI has taken over that. We haven't talked about retail media yet, now Is AI, but glad you brought it back, but the phrase would be, and let's have the audience debate this in a fun and productive way, but the no data, no dollars kind of slogan we'll call it.
Lauren Livak Gilbert (26:25):
I have a T-shirt of that. Greg O. Murray from DCG. Nick claimed that and made me a T-shirt. It says no data, no dollars.
Todd Hassenfelt (26:34):
I love it. And it is fine. Conceptually, it's great and it has caused good conversation and probably better questions to be asked. I guess looking a little deeper, I always say look deeper than the dashboard, so I guess look deeper than the T-shirt in this case. But anyways, is it that because a couple things that are broadly out there, 90% of retail media spend, and this is based on eMarketer, is with two retailers, even though there's 200 networks at least, and most brands will say, Andrew Lipsman and others have put data out here, it's about five to seven retail media networks that people or brands, sorry, that brands and advertisers are investing in. So is it really that it's, again, no data, no dollars when 90% is going to two people? And now is there an opportunity? Absolutely. And there's been some other things talked about like federation or a bundle model for everyone outside of those two that get it.
(27:44):
Kiri has talked about that. Andrew, another podcast called The Middlemen with Tom Lomongello has talked about that. So if we go to that model as an industry and in some ways we are there, what does that look like for a no data, no dollars? Because then even does every retailer part of that federation have to provide the data? Can they even, is the provider just providing, but not telling you where it's necessarily coming from? There would be a lot of questions. And then again, we would go back to do brands or agencies, whoever's handling the retail media spend portion, do they have the bandwidth and the harmonize, visualize, and act on it fast enough to do something with the data? And is that really where the dollar allocation decision should sit? So I might have to make you a new T-shirt, Lauren, if you like this one, because you can't bring a problem and not a solution, right?
Lauren Livak Gilbert (28:42):
Ooh, I like it. Collection's going to be great.
Todd Hassenfelt (28:47):
Well, so instead of no data, no dollars, or maybe yes, and depending on where you are in your organization, either way is fine, but can we do aligned inside, agile, outside? So what does that mean? All right, aligned inside, are we all working together truly, making sure that the dollars are coming from multiple areas, we're planning multiple way, right? All the things with silos that have been talked about a lot. But I think the agile outside piece is more when you think about JVPs, another great report done by the DSI, kind of talking about that, but really, can you be flexible? Can the retailers be flexible so that money and following any rules and kind of pieces there, but money can be moved within the retailer where the action is happening, where the investment would make the most sense because I think that would be a model or at least a concept, the aligned inside, agile, outside, that's more realistic to where retail media and really everything else is right now because Agentic will come into this and other things, and we haven't even mentioned the whole standardization P MRC, IAB is doing great job there, but it's really unfair to think retailers need to solve standardization solo when the brands are siloed.That's a challenge.
(30:16):
So can we shift it so that we can get more aligned inside and agile outside? Because even the no data, no dollars has a bit of friction to it that maybe arguably isn't correct. Again, the 90% stats and five to seven networks. And two, all right, are we collaborating? Are we conflicting there? So I don't know, does that make sense or do I have to get you into
Lauren Livak Gilbert (30:47):
More? Yeah, no, it makes a ton of sense. And I think all of us need to come together to be successful. That's a big thing that the DSI talks about a lot. Brands, retailers, partners, technologists, brands. Everybody needs to come together in order for this to be successful. And I think you hit the nail on the head with the standardization as an example. It can't happen in a silo. You can't have silos internally, you can't have silos externally. Maybe that's my t-shirt, Todd.
Todd Hassenfelt (31:12):
Yeah. And standardization, we can all wait as an industry for it to happen. And I'm trying to think of a lot of different things. Where do we have this perfect standardization? I don't know either you are poker players, but for those that are, how do you win with a two and nine in your hand? Or do you have to always wait to bet when you have pocket aces? So really retail media comes down to how it's not just how much, but it's how well you are spending it based on your outcomes, JVP, agreed upon things. So again, yeah, let's work together and find ways of collaborating.
Lauren Livak Gilbert (31:51):
So Todd, let's think about, there's a lot of different ways that people can reach their consumer. We've talked about a lot of the hot topics, AI, retail, media. What's something that isn't talked about that could potentially drive a lot of growth for brands?
Todd Hassenfelt (32:05):
Quickly, I would just say subscribe and save or autoship, whatever it's called, depending on which retailer you're looking at. And we said, Hey, outside a few categories like pet, it's still not even close to half the consumers are utilizing this despite it's a discount, it's convenient. It hits on a lot of different things that consumers always say they want. I want convenience, I want cost savings. So I think subscribe and save is one of those things for brands to focus on for retailers, whether that's in your PDP content, whether that's signage. And listen, there are definitely examples out there, but where is still the friction point for the consumer that we don't have higher adoption for this? And if we bring in an AI aspect to it, it might be, we are all learning together, but subscribe and savever AutoShips might be a way for brands, whether it's a bridge or for a while, to negate any lack of recommendations of if your data's not there and now the LLMs or the roof is Sparky's, et cetera, are not recommending you at the rate or amount that you think is fair based on your share, whatever it may be, that subscribe and save could be the way to limit.
(33:28):
Nothing is extremes here, but limit the scope of the impact there. So that would be one. And then I would just think the other thing, I guess we've kind of alluded to it, is decision-making speed, quality decision-making speed. Can you do things faster in a way that's learned? Are you ingesting as much as you can of everything that's going on out there? And there's a lot, but are there ways you can have someone curated for you and take learnings and put it to your remit, to your job, to your department? And then how does this tie in? How do you really connect the dots? But in quality decision-making suite, I'm not saying being reckless here, but it's the quote I've loved for a long time and it seems like every year it just keeps getting more and more relevant, but change has never been this fast and it will never be this slow again.
(34:25):
And so can we use AI since where we are truly, this is something we are all learning together. How is this all going to work? Can that be a glue that brings us together to break down some of the silos and help us all make decision speeds, quality decisions faster? Because it's kind of like athletes. I mean, there's a reason some athletes make it to the pros and others don't. It's just how their mind and their body reacts faster to the game that they are playing. And part of that's also, if you want to bring an athlete, I guess example into it, it's like the decision making, quality decision making can be faster if you stop proving and start improving, going back to that green scorecard, but it'd be like saying lifting weights. Which rep made you so strong? Was it the eighth rep of the third set?
(35:24):
No, but because I did it consistently and that you just exercise regularly without overdoing it or overspending, there's some analogies here or there's a way of looking at this that can be, again, productive and collaborative.
Peter Crosby (35:40):
I mean, that's where, particularly with so much change happening right now, I think one of the biggest things is to make sure, and a lot of our listeners have them already, which is great, but find your people. Who are the people inside your organization, outside your organization? A friend of mine is in law school currently, and he was talking about his study group and how everyone's different personalities and they divvied things up and they came back together. And I was thinking about that for what we're talking about. Who's your study group to both capture the frustration, but also the joy of this discovery moment that not many people get. This is sort of a once in a generation transformation and as much of a pain in the womb as it is, it also is a lot of fun to figure it out together. And so yeah, find your people, I think.
(36:35):
And you do a great job of that, Todd. My God.
Todd Hassenfelt (36:38):
Well, I appreciate it. I love the study group analogy. I mean, I'm sure everyone has a great study group that they can relate to or a bad one or anything, but bringing it together with what we're talking, I guess it would be in a share group, or I'm sorry, not in a study group, you truly are sharing and soliciting. You're sharing best practices or information or whatever your project may be in a study group, but you're also, I think this is where we all have to get better in CPG is you have to solicit and say, "I don't know about this. I have some good questions I want to ask so I can learn more, not just prove I think I know it. " And I think that share and solicit really fits into a great study group analogy. I love that. There's something there with a report.
(37:33):
I mean, I'm serious, just the study- Get on that, Lauren.
Lauren Livak Gilbert (37:37):
I actually already have an idea, so I wrote it down. Of
Peter Crosby (37:40):
Course she does. Do be continued. So Todd, I'm going to do something really unfair to you. We have a couple minutes left. Just talk about Agentic Commerce. I have to ask, it's my podcast host thing, but in terms of 2026, is it a go all in moment or an experiment or watch moment or just wait, don't worry about it. Ready, go.
Todd Hassenfelt (38:05):
Well, probably one, since you both know me, and two, just for the audience hearing the answers, it's about balance. You still have to learn. You can't sit out necessarily and you don't have to go necessarily all in because it is changing so fast. So it's about balance. And it goes back to learn by asking those better questions, but there are some things like, okay, what are some ways to learn? Comes back to, Lauren knows I said this at the first DSI summit in Nashville, how much of our spend then gets directed to PDPs. But now when you think about Agentic, same thing here, it ties into the digital shelf and the data points we've discussed, but look at your PDPs and your content. And now it's not just, it still needs to have the human appeal, but now the machine input and how is it being read?
(39:10):
So what can you learn? What can you experiment with? Kind of mentioned, hey, AI also isn't going to fix everything just because it's AI or because someone sold you a tool or whatever it may be. Again, you can't automate a process that's broken.
(39:27):
AI will just make the mess messier if it's not there. I mean, there's a great Wall Street Journal story that recently came out. Joanna Stearns, who does a lot of great stuff with this, on a vending machine that was put in by one of the LLMs, you have to go read the story to see it, but in the Wall Street Journal offices. And as you can imagine, some people that are really good at asking questions in creative, the short version of the story is they pretty much got the vending machine to give away everything for free. It sold a live beta fish. The phish is okay. And Xbox Alcohol, I mean, there's even more to it. You have to go look at that story. But this is where it's like, all right, the process wasn't really there. The controls weren't there. They even brought in, or I know it sounds funny, but the LLM brought in a second agent to control the vending machine agent.
(40:18):
And even that got overruled because they were like, "Oh, the CEO agent told the other one that the board overruled it. " So I mean, it's a great story, but it's a great cautionary tale. And it's not like, oh, this isn't going to work. Again, it's a balance. It's like this is a great learning opportunity and that one is just a fun but real one. But end of the day, it's like consumer preferences and needs should be the priority and that's AI or not. You can leverage tools like a Notebook LM. I mean, when you think about content that you produce internally or get from external sources, leverage the Notebook LM, and I don't have enough time to go through all of it, but you can chat with it just with the sources you put in. You can create ... Sorry, you can create some podcasts, you can create reports, you can create infographics.
(41:07):
There's a lot. It's not as good as yours, of course.
Lauren Livak Gilbert (41:10):
Obviously.
Todd Hassenfelt (41:11):
But there's a lot of ways to disseminate information and allow people just to learn at their own pace as well. Kind of tying back to PDPs, I think FAQs and your process for those is hugely important for multiple reasons that you can think about how they do it. So hopefully I'm not dodging the question, but it's-
Peter Crosby (41:35):
No, no. I mean-
Todd Hassenfelt (41:37):
Yeah, experiment with intent.
Peter Crosby (41:39):
I'm quite encouraged by what you're talking about, which is I think in this moment, the things you need to figure out to drive more incremental growth from your PDPs are the same processes that Aggentic commerce will need, but with a whole lower iceberg of data that you need to figure out how to get and put together that can fuel an entire conversation with a consumer. And that's just a different set of data. And I'm not saying that's easy, but I'm saying you have the processes in place. It's just figuring out how to expand its scale and what is the other data that you need and where can you get it from or how can you make it and trust it that is sort of the next part. And you don't have to do all of that this year, but you have to think three years from now, where is my growth coming from and what portion of it will be from something attached to either Agentic or AI fueled or whatever you want to call it, and what do I need to do now to make sure that I'm capturing that growth three years from now?
(42:47):
At least that's how I've been thinking about it.
Todd Hassenfelt (42:50):
Yeah. I mean, just as you were talking, I don't know why it popped in my head, but an analogy might be learning to drive a car. There's a lot to it and you start off really slow and that's fine, but you're learning the basics, learning fundamentals, or as you get a little bit better in your learner's permit, you have some of the fundamentals down, but now you have to learn how to do it faster, which is where this analogy kind of popped into my head with everything you're saying. And maybe now it's like, oh, now you're going on the freeway, so there's all these different things to learn versus just the city, streets, wherever. But yes, it's okay, but to keep learning, keep experimenting, but ultimately probably everyone needs to get faster going back to that quality decision-making speed just like you would as you're driving a car.
(43:35):
Not saying you have to be on the Audubon wherever it's unlimited speed, but in all seriousness, if the processes and data are better, you have a better chance of going faster, most likely in a quality way.
Peter Crosby (43:49):
Well, Todd, this has been a mega episode. I call them megasodes, but it's totally worth it. I'm so glad that we were able to capture all of this with you. I would say to our audience, we were talking about things to lean in on. I would say lean in on Todd's LinkedIn account, please follow it because talking about study groups and people who learned how to share when they were kids, Todd is one of them and he's always sharing the thing, you are always sharing the things that come to your mind that strike you, that are useful and your generosity of spirit just comes alive on that feed every day. So yeah, please find Todd.
Todd Hassenfelt (44:34):
Thank you. And we truly are all learning together and I still feel a debt to everything so many people like you and others provide the industry. So yes, happy to help however I can, but thank you so much and I appreciate.
Lauren Livak Gilbert (44:47):
Thanks for kicking off 2026 with us, Todd.
Todd Hassenfelt (44:50):
Awesome. Let's have a great year, productive year. Yeah. Here
Lauren Livak Gilbert (44:52):
We go.
Peter Crosby (44:53):
Thanks again to Todd for his generosity of knowledge and spirit. We hope to see Todd and a host of other people like him and you at the upcoming Digital Shelf Summit in Atlanta in May. Don't miss out. More info at digitalshelfsummit.com. Thanks for being part of our community.
