How Next-Gen Commerce Experiences Simplify Shopping

Robert Gash: Everybody knows in commerce the easier it is to purchase something, the higher your conversion rates typically are. But that works mid funnel too. So going from moment of inspiration into lower funnel kind of research and doing that as seamlessly as possible with fewer open tabs and fewer searches, maybe in the middle, is a key way we can play a real role in making that journey easier and faster for folks.

Kailey Raymond: Hello and welcome to Good Data, Better Marketing. I'm your host Kailey Raymond. Every day, we're discovering innovative strategies to enhance consumer experiences in e-commerce, from AI driven curation to integrating various media formats. These next gen strategies are all about enabling consumers to have a personalized and frictionless experience when shopping online. Intentional product design is making that journey faster and easier for consumers, helping them advance from the moment of inspiration to purchase without being bogged down with research in a jumble of open tabs. Hearst's, Robert Gash and I discuss strategies for making purchasing decisions easier for consumers, reducing informational friction, and how AI is redefining commerce experiences.

Kailey Raymond: Today I am joined by Robert Gash, Chief Consumer Commerce Officer at Hearst. Robert is a software and product development executive with extensive experience, leading software development, product strategy, research and design. Prior to joining Hearst, he served as VP of engineering at Perks and Symphony Commerce, and as the VP of operations technology at Grove Collaborative. Robert, welcome to the show.

Robert Gash: Thanks a bunch, Kailey. Happy to be here.

Kailey Raymond: I am excited for you to be here and hear a little bit about your evolution. You've worked for quite a few companies, mainly in technology, you know, and product roles. And you have a fun title now with customer or consumer right in the center of it. So Robert, tell me about your career journey.

Robert Gash: Yeah, I mean, you know, trained as a software developer and engineer back in the day, but one of the things that's kind of at a through line, even from my first roles, was really the commerce and logistics wing being a huge problem space. You think about it, it's something that enables our daily life, but I've had the opportunity to work everywhere from the websites to the warehouses and kind of back again, and both big and small. So started at bigger companies, GE and Amazon actually for a really long stint. But as you had just mentioned there, spent some time in kind of emerging growth companies as well. Companies that were looking for either new markets, trying to create them, looking for kind of that classic product market fit, and work with them through that journey and figure out what role data and insights from your audience can play, and also help scale those experiences so they're reliable and trustworthy. The things that kind of we expect as consumers from companies that we visit a lot. And so that's been product at times, that's been engineering leadership at times, that's been data and program management, kind of has taken me all over the globe and all over the kind of functional org chart.

Robert Gash: But here at Hearst, really all of that comes together. My role is focused on how do we make it easier for consumers to use our advice to make purchasing decisions? You think about magazines, people have shopped magazines for generations. It's not new. As we've shifted online and there's so many more voices kind of in the mix, how do we make all of our expertise easier to use and how do we reach new audiences that are looking for that same advice? It takes a slightly different lens than it used to when it was just on the printed page, and that's really what my team and I are really here to help with as part of that journey.

Kailey Raymond: That's great. And you know what's really interesting is I feel like at least in your title and some of the description of your role, there's this unique little trend that I've seen emerging over the past five or so years, which is the rise of this like chief customer, chief consumer officer, which really just focuses and puts the customer at the center of every decision that you're making, which really does seem like what your role is enabling. Tell me about how you're wearing the customer's shoes at Hearst.

Robert Gash: You know, a lot of my role is really focused on the e-commerce and the commerce adjacent side of what we cover in our content already. So we have other customers, we have advertising clients, we have people who are enjoying our content more for kind of entertainment purposes. They may not be buying something kind of at the end, and we think of those as different personas, right, as different audiences we need to ultimately serve. So my team spends a lot of time focused on, you are trying to make an informed decision about something that you may not be an expert at, right? You can imagine we bump into these things all the time. You have a life stage event coming up. We were just talking prior to the show around, I've got a new puppy at home. There's all these things you need in your life to kind of get ready for that, and you're often not an expert at which products to pick. The brands may be completely unfamiliar, and if you're lucky, maybe you have a friend that can tell you. But a lot of people are looking for kind of that independent expertise and it's getting harder to find as brands have become more global. Every possible competitor from every region is now present in most countries.

Robert Gash: And so you've got a harder time filtering through all those choices and it could be a lot of work. We jokingly talk about the need to become an unpaid investigative journalist when you're thinking about doing this research, and there are some decisions in our life where we may enjoy that that, but there's a lot of things where we don't have that kind of time where we don't want to be that. And that's really the unique role that a lot of our content and our editor's expertise can play in that decision making process. But we have to think about how do we package that up and make it easier to consume so it's not 12 different searches you have to run? We want to figure out how can we take you in that moment of inspiration that might be happening in our content and help you transition into those purchasing moments as well, and do that as quickly as we can, but also at the right moment. Like there is a time for building ideas and kind of basket building your head and kind of thinking of an idea and then there's a time for purchasing and doing that lower funnel research, and that's the role that the consumer commerce organization really focuses on.

Robert Gash: So it's research tools, it's how do we provide good guidance about not just what to buy but when and where to buy, and do that from a customer's perspective. It's one of the beautiful things about being a journalism organization is we are really focused on helping you and taking your side, and that's something that's somewhat unique. Retailers have a different role in this universe and it's not always kind of based on what's better for the consumer and the decision they ultimately need to make. It's based on how do they get more sales, and we have a bit of a hybrid role in that regard.

Kailey Raymond: Beautiful. Adding value to the consumer experience and making sure that your consumers don't feel like they need to have a journalism degree to be able to decipher what's going on and what products they might need to purchase for any of these kind of big events or even small ones coming.

Kailey Raymond: One of the things that you had mentioned is almost this concept of reducing friction for folks and making sure that they can find the right content that they need and information that they need. I'm wondering if you have identified any kind of consumer trends over the past couple of years that are impacting the way that you think about this consumer engagement in commerce.

Robert Gash: One of the things that we talk a little bit about internally from a design perspective is information density, right? There is such a thing as too much scrolling when you're trying to do a particular topic and infinite scroll is really great when you're being entertained and you're kind of bouncing around between topics. But infinite scroll might be bad if you're just trying to figure out, is there an ingredient in this that I'm allergic to, right? And so we think a lot about what are the key questions that someone would need to know when they're making one of these purchasing decisions and what are the right ways to elevate those kind of data points in the design itself. So one of the things that we have launched in the past couple of quarters is bringing some of what classically you would think of as a detailed page experience into an article.

Robert Gash: So if you're shopping a product that's available in some of these new marketplaces we've been launching, and we've got details about the sizes and maybe the other colorways that aren't really part of the story we're covering here, right? If you like red or green, it's not the editor's choice here, but you may care before you decide to buy that product. And so instead of encourage you to open up 20 tabs to the right of whatever you're reading and then go figure it out later, can we bring you into that kind of research context before you kind of leave the article itself? We found that that's actually pretty good at driving more engagement. People are leaning into that relative to the offsite links at a much higher rate. And that's kind of just a vignette of the sort of question we think about from a design perspective, which is simplify it. Everybody knows in commerce, the easier it is to purchase something, the higher your conversion rates typically are. But that works mid funnel too. So going from moment of inspiration into lower funnel kind of research and doing that as seamlessly as possible with fewer open tabs and fewer searches maybe in the middle, is a key way we can play a real role in making that journey easier and faster for folks.

Robert Gash: So that's kind of one I would say in terms of it's easier to connect those dots than it ever has been, which is good, supported by great technology out there that just didn't exist a decade ago when you would've had to do all this yourself. And so that's kind of one trend. I'd also say that it also carries into the way we're thinking about video. I mean one of the things that just personally was really fascinating was talking to someone about how they were using TikTok to do restaurant research, and they were searching basically and looking at in like store videos essentially of what's the vibe like, what's it decor like? Is it busy, is it not? What is the food actually looking like? And you can get so much more in a very short clip than all of the traditional kind of static research you might see. And that's, I think, just very early days in kind of where that sort of interaction is going. We all know that video-based platforms are absolutely kind of eating the internet right now, and I don't think that trend fully reverses, but there's still a ways to go into how do we tap into that and actually bring that same information density into other research experiences, right? 

Robert Gash: Is there a clip about that product in the real world that helps you understand, is that stroller fit all your kids and stuff that you wanna lug? You know, is there a better way to kind of go about car research where we can actually show you some of the nuances that don't make it onto the printed page but might be easier to explain in video form when you're doing a tour around the car? Those are all the sorts of things that we think about when we think about bringing some of those questions and answers that we may have, but just don't see the light of day into the current experience.

Kailey Raymond: That's really interesting. So you're thinking about integrating, you know, different formats of media into articles to be able to further engage people how they want to, with video of course being one of the richest forms of media? 

Robert Gash: Can be, it has limits, right? You can't shoot detailed reels of everything, but it's part of the what are the things that you are looking at and might actually be able to answer other questions, and how do we bring those into the content when you're reading it, right? So that you can understand, hey, this is the hot new trend or here's why you need this product. But now you need to make the decision over the color, the size. You may have some personal preferences there that aren't gonna be in the article itself. That's how we're trying to kind of keep you thinking about how this would fit into your life before you end up having to go off and do async research essentially to make the decision.

Kailey Raymond: This is interesting. I'm also like, there's a consumer and, there's an advertiser side to this, and one of the things that popped into my brain related to some of these trends in the market is the death of the cookie. We can't even say that anymore, fits emerge...

Robert Gash: I think the debate is how it dies. Maybe not does it die, you know? 

Kailey Raymond: Exactly.

Robert Gash: But I think it, all the back and forth around is it going, is it not going? But I think there is kind of a subtext around it helped us think more about contextual targeting perhaps than we were in the past. And there is a great deal of signal about what you might wanna show from an advertising perspective in the content that you're reading now, right? And it doesn't require knowledge of every single thing you've ever shared on social media to be targeted effectively. And so I think that's another very helpful and I would say consumer friendly evolution in how we think of advertising, that the cookie debate did kind of bring to the surface. I'm personally optimistic that that goes much further because I think better targeted ads are better for everybody. It doesn't feel as distracting to what you're reading and content. Those are the most delightful kind of advertising experiences, at least to me personally, when they get me curious about something adjacent to a thing that I'm already curious about. They encourage me to go deeper but aren't necessarily like jumping into kind of odd parts of personal life, like some of the other targeting models might. Still early days and a lot to do there. But I think a very good thing as we think about the evolution of kind of how advertising works online.

Kailey Raymond: Yeah, it's a win-win hopefully is, you know, you make sure that you're providing really great targeting capabilities and also delivering back privacy over to the consumers, which is something that they've been begging for for quite a long time and there's quite a lot of law about as well. So, and a lot of what we're talking about right now is, obviously around the launch of your shoppable media model. And so what I'm wondering I guess is you mentioned that there's a couple of different phases of that research. Maybe somebody's more kind of exploring a concept not necessarily ready to convert. There might be then some folks that are really high intent and are actually gonna convert on the page. Walk me through some of those kind of different use cases and how you're thinking about those within that model that you're developing.

Robert Gash: It's a good question. The way we look at it is kind of different modes, right? All of us have probably worked in commerce before, understand the behavior of shopping carts is kind of wishlists and then a lot of things get deleted from the cart before purchase is made. And a lot of carts just get abandoned 'cause it was more of like an idealist. Well, that's true in content too. Say you're reading about one of those life moments and there's two or three dozen products on the page, it kind of speak to different parts of those use cases. You may want to essentially create a wishlist, not of articles, but of the products in the article, right? And so we've built this experience so that you can basket build when you're in content, but you can also jump over to what is a much more traditional commerce experience.

Robert Gash: And what exists in that storefront is only product and brands that our editors have vetted. So when we sit down and think about building a marketplace, it's not let's cover everything, it's gated. It's only by invitation. We're only purchasing ideally directly from brands, but if it, the brand doesn't do that, we can go through one of their authorized distributors. So they're also from known and trusted and reputable sources. And so let's say there are products from brands that just don't ever make it into articles, but the brand does a good job. They build high quality products, it gives us a place to surface those. And in an environment where it's filtered, it's curated. So you're not having to kind of weed it out from a lot of the really large online marketplaces. They can just be overwhelming realistically. And so curation is a big part of it, but we think of it as an evolution, right? We've always had a lot of content that spoke to things you could purchase even before the affiliate models really became giant over the past decade or so. But these will always coexist. There are some types of products that make sense to purchase on another site. You think about heavy, bulky is a great example, and there's a tremendous amount of logistics that go into buying a dishwasher or a mattress, and we don't really benefit by trying to recreate all of those.

Robert Gash: So those are good examples where we're always gonna wanna partner out. Our job is as curator, help you understand which of those mattresses are worth purchasing, or how does it integrate into your life? And if you have a choice of five, how do you narrow it? But this sits adjacent because sometimes that purchase is still too hard to do or you can't build the basket you want because it's on five or six different sites. And that's an interesting opportunity for these marketplace models adjacent to media to sit, is it makes it easier to go in and shop that entire look from the brands that are in the content in the article without having to leave that moment of inspiration of like, "Yeah, I really wanna look or dress that way for this coming season." That's a really powerful opportunity that can sometimes be really hard to replicate in the retail world.

Kailey Raymond: And really, what you're kind of describing is you're building probably quite different experiences depending on the type of product somebody might be looking to shop for. So if it's a little bit of a higher purchase price perhaps, there might be a little bit more research. It's probably not something you're gonna work with folks directly within your platform itself. You might send that out and you know...

Robert Gash: That's right. I mean...

Kailey Raymond: Make sure that you have partnerships.

Robert Gash: The best example is cars. We have a really healthy automotive division, car and drivers kinda one of the titles there, and they are some of the most engaged and in-depth experts around cars you could possibly imagine. And they have the benefit of having driven all of those cars, right? And so that's just an experience that even if you have a passionate friend in your life, you're not gonna know somebody who has driven every single model of the SUVs that are on market today and has done so for a decade, right? And so when we think about high consideration, some of those do take time. Buying a car is a multi-day process. We still think it's too hard and there's too many steps involved and it takes too long to kind of parse through some of the industry nomenclature around how they segment the market. And so that's where we can play a real role is help be a guide. You've got two kids, a dog, and you live in a snowy place. What is the best car for your family under a certain budget? That is a very real question that many of us have, is one that can be very complicated to answer.

Robert Gash: But the way we would help you do that research, would start from a different place, right? You know, do you have the financial ability to purchase the car? Do you need to lease the car, right? Do you have a budget constraint? If so, how do things like your credit factor into that? There's a lot of stuff that you kind of have to do homework on before you can really start doing the research. And we see those as opportunity. Those are knowable answers. You can put the right tools together, but a lot of it is not in the same place today. So you have to kind of keep a notes file on the side and you have to kind of become expert at these processes. And that's where we see ourselves as a guide. So we understand the cars that might fit your use case, we can then learn a little bit more about you so we can help narrow them into ones that you might be able to afford and then we can help arm you with the data. You're gonna need to think about the long-term ownership of that vehicle too around, yes. Is it reliable? Huge question, right? And then we might hand you off to someone who can actually help you buy that car, right? 

Robert Gash: We're not building an online car dealership. That's not part of the ambition, but we can go far enough to say, "Look, here are the dealers that have cars that are like the one that you might be interested in that also intersect with the prices you can afford." So we've shortened that list now from thousands of options that might be on five or six websites to a very narrow range that you can then go have educated conversations about before you make your final decision. And so that's kind of the other example. The car in a web, article is kind of one that's for products we might buy kind of without as much research and thought. And there's still value in having that research available. But there are other really high consideration purchases where the model is gonna be different. And we wanna support both.

Kailey Raymond: I could have used you in March. I purchased a car then. And I can tell you it wasn't my favorite experience in the world because the way that I think probably isn't the way that a lot of car people think when they're telling me terminology that I don't quite understand or I don't know what I don't know. And so I love that you'll be able to kind of decode that. And something that kind of popped into my brain here is there's this value exchange and making sure that you're giving them the right recommendations based on that information. And so are you also leveraging like surveys, zero party data, once you have built that trust and people are logged in so that you actually besides gathering all of these little traits that people are clicking around and giving you some of these signals that they're literally telling you what they want. Is that a part of your strategy, too? 

Robert Gash: It's part of the things we're looking at. I won't say we have a ton of great examples live, but I also can't say categorically we don't either 'cause we have so many different titles all over the world. And so there have been some good experiences like that where it might start as something that looks a little more like a quiz, for example. But the answers you're giving in that process are actually helping narrow the decision down. And it's gonna depend a lot based on what you're trying to buy. You could imagine an article that's about a kitchen appliance where there may be a dozen things that are in the meaningful consideration set and you need two or three questions to really get down to the one or two that really matter. That's where quizzes make tons of sense. For a car, I actually think it's a little more nuanced because of the price challenge. And what you can afford matters a great deal with all this inflation and costs going up. And even what your living situation looks like as you think about the EV question, can you charge it at home? 

Robert Gash: So the way we get to those answers and the point in the research where we ask them, that's the sort of thing that our product and design teams are really always debating. Try to be thoughtful about only ask enough to provide the next right step. And there will be a moment later for us to get more detail before you have to make the decision. So it doesn't become overwhelming. I think all of us have gone to a site that's like, answer these 98 deeply personal questions, and then we'll give you some answer. And too many of those end in like, give us an email and we'll call you, sort of an end point. And we wanna be a lot more thoughtful about educating as we go and doing that increment.

Kailey Raymond: Yeah, we have all been there. I won't name names, but I've had that experience.

Robert Gash: I'm not either. And sometimes that is the right answer.

Kailey Raymond: One of the things that we haven't talked about yet, which I'm shocked by, it's amazing to make it 30 minutes into a conversation without uttering the name AI yet, but we'll do it.

Robert Gash: Well, there we are. Now we've done it, so.

Kailey Raymond: Cats out of the bag, AI. Okay. We can now breathe a little bit easier now. So how does AI help power her shoppable media model? 

Robert Gash: In shopping, there's still kind of a lot of open questions around what is AI really gonna do? Some of the things we are most excited about is how do we build more context in information density kind of conversation on a detail page? So if we have four or five editors who've covered that brand or that product, and they may have different points of view, I may not have excerpt ready statements from all of them. AI is something that we could potentially go through and say, though, what should this person know about this brand? Giving it all of that context is a starting point. So it's still speaking in our voice. It's kind of exerting information we know, but we're doing that at scale in a way you could never do with tens of thousands of items in any given commerce experience. Those are the places we're excited about taking AI. But I will say we're trying to be very pragmatic about it because of exactly what you alluded to, all of the hype that surrounds it. It is still very much in many use cases, a tool looking for a job to do. And you can make a lot of very expensive mistakes if you jump on that bandwagon too quickly. And there's been a lot of good survey data out there around the difference between people who are experimenting with AI, of which everybody should be, and we are, and people who have real production at scale use cases for AI.

Robert Gash: And that number, the latter number is much lower. And so we're trying to find where those things are. But for me, comparisons, exerting kind of editorial opinion on something so that you get enough to know, do I want to go deeper? That's really kind of the point for us. And we see a lot of really interesting opportunities there around compare and contrast these two things for me, using data that we've already curated that we know is trustworthy, not just like general opinion you can scrape on the internet. That, I think, will ultimately be quite powerful.

Kailey Raymond: Very interesting. I'm also like, I don't know, cross-sell audiences with predictive capabilities.

Robert Gash: Even seeing some of the patterns in behavior that you may not see, I think on the data front to the spirit of kind of this conversation, there is a lot of really interesting application where absolute precision is not as critical. So just personally, I think that if you look at it as something that can get you an approximate answer really quickly and can be a great thought partner in a sense, and have you take different perspectives on data and patterns you might see, also tremendously powerful. So recommendations, even the antonym version of recommendations, you don't like this but you're curious about other things, that can be tremendously powerful with AI. We've seen some interesting benchtop experiments around that. So I think there are gonna be some other embedded use cases. And truly, I think that's where AI writ large as we're talking about it today, and the market really lands, is specific use cases where you can tune them that have real utility and may not be an everything search box or kind of the everything answer machine. Yeah, but they are much better at generating specific answers. And there's a lot of fascinating research out there that has shown some of the early promise from classical recommender systems to LLM-backed kind of recommendation algorithms.

Robert Gash: The skill that the newer models show with less tuning and input is really astounding. And those are, I think, some of the real interesting ideas that we're looking at in the commerce space that we wanna bring to bear based on our expertise, 'cause we do have a point of view. We have things we like and things we don't like. And so bringing all that together and finding a way to kind of do that at higher scale than we can today is a real opportunity for us.

Kailey Raymond: That concept of that kind of blank text box is so real. I love that you articulated that. It's not always the most helpful way to engage.

Robert Gash: Look, search has been a hard problem for a lot of companies to solve, not at web scale, but even internally. And I think there is a lot of really interesting applications of kind of LLMs writ large in the searching context. And for anybody who's listening who hasn't been playing with this, you need to be playing with them because they are some interesting, fascinating ways to engage in a problem space, things that at times really surprised me at how useful they could be. Finding kind of specific and arcane answers that you might've found as a human, but would take you a little while. But when we think about applying it in our audience and we think about how do we make it more useful for them, we try to be really specific about what is the job we're doing. What is the thing that it makes easier for a consumer? And is it doing that accurately enough to kind of earn the next interaction? And if the answer is yes, then let's go. But if the answer is I'm not sure in my world, points are not awarded for just being curious. Points are awarded for actually like having an impact on a consumer. And that's the way we try to look at that landscape.

Kailey Raymond: I really like the way that you're also positioning this with using the word earn. I oftentimes think that folks can be a bit presumptuous and figuring out how close they are to their customer and how much value they're providing back. And so being so intentional with your language is also mimicked into the product that you're building. And so I really appreciate that. So what challenges have you seen in really making sure that you are building this great experience for your customers? What's been hard about it so far? 

Robert Gash: There's a lot of work to kind of extract meaning and structure from the vast archive that we have. Hearst is a company that's been around for generations. These titles have been around for a very long time, and they have a tremendous amount of accumulated expertise that isn't necessarily visible to most of us on the internet each day. Answering these questions and going really deep on that two kids and a dog problem with cars, it takes a lot to do well. And so one of the challenges is just kind of thinking of that incremental roadmap. So start simple. Some of the stuff we've talked about is already live on many of our titles today, and it's kind of growing by the day. Some of it's aspirational that we know we can't deliver it the quality we want yet because we've got to make some kind of behind the scenes investments. Long term, those data assets become really, really powerful and valuable for the company. But in the short term, it can be daunting as anybody knows who's tried to go off on one of these programs before. So it's always a balancing act. And that's the thing that I think we are always kind of internally debating is don't let perfection get in the way of progress in a lot of cases and understand that the current state is in some cases really bad.

Robert Gash: And so any little incremental improvement is actually a huge benefit for people, even if you know you can go much further than that. And so that's kind of the tension in these like curious cultures is also not over rotating on the problem and really making sure that you're thinking thoughtfully about how good is good enough for today, and then how to earn like the next increment in productivity or whatever it is tomorrow, gives you the opportunity to pivot to go work on other things that you haven't solved yet. But I would argue that constellation of trade offs is really one of the most difficult things for us on a routine basis. Because there are so many things we could do. And you have to choose 'cause you can't do all of them at once, not with a small team.

Kailey Raymond: Yeah. It seems sometimes it's just not being afraid to ship it, even though it's not exactly at the point where it's going to be a month, a year or whatever from now. One thing that kind of just struck me was we've been talking a lot about this vast library of content that you have and how you're making sure that you're able to leverage that to build enough context and research for your consumers and build confidence and value with them. I also feel like there's probably a reverse where you have a lot of information about what particles and where people are engaging those. I'm wondering about that feedback loop and how much the data that your team is collecting and creating is being fed back to editorial teams and journalists to actually invest more in the content that people are really excited about and engaging with? 

Robert Gash: Yeah, it's a great question. And it's one that like many things, it kind of varies based on where we are, we have places where there is really good feedback where we're looking at how the audience is consuming content. And that is shaping strategy and really quick, short time. But when you think about some products, that speed can also be detrimental if you're not careful. And so there is another kind of back pressure, if you will, around don't go too fast and make short-sighted decisions. Do we really know if that nonstick pan really holds up? You have to have that thing on a stove in real world examples for a little while before you can really tell. Even if it's beautiful and everybody on social loves the thing. And so it is a question of when do you think fast and when do you think slow? And it is one of the things we aspire to do more. The basket example is one that we have not done yet. That is very much still on our aspirations list. But one where we can go back and educate both advertisers and our editors alike around here's the advice that customers really acted on and took.

Robert Gash: Here's the advice they looked at and didn't. If we can know what they did instead, we'd love to. So we can also think about how that changes coverage strategies and what that can tell us about the audience as the audience's preferences change. But it's always attention. There is no kind of yes or no sort of answer here. It's more of context and making sure you can share it and then lean on the experts, our editors and our journalists, to really kind of filter through those facts and come up with their opinion.

Kailey Raymond: So interesting what you're doing. I feel like I keep thinking of all of these kind of new thoughts and use cases. And really a lot of what you're talking about is just built on this really vast mountain of data. And the most part, it's unstructured data. You're, of course, gathering structured data with how people are on the logged in experience, especially. But I'm wondering, with making sure that you're defining those use cases, we've talked about that a little bit here today. How do you define good data? What does good data look like to you? And then how do you achieve that at your organization? 

Robert Gash: For me, when I lead data organizations, good is it's insightful and it can survive at least three of the five whys. You always wanna be able to go a little bit further each time. And one of the things I'll talk about internally and kind of culture conversations is you really wanna stop the... I don't know and I can't tell mentality. And it's okay to not know. That's not the part of it, but it's the, I don't have access to the tools or the data to go any deeper. And storage has gotten so cheap online these days, but the thing I constantly remind teams is keeping even semi-structured data, maybe it's not fully transformed and cleaned up in a way that's easily consumable. But where the raw facts are available. So if you do get really curious about a question, you can later go back and look at it. That has gotten cheaper and cheaper and cheaper. And yes, there are horror stories of people who spend way too much money on logs that don't matter. So there's always a tension here. But try to record everything that happened at the time for every session, for every person, so that when you do need to go back and understand what happened, you can try.

Robert Gash: And out of that comes insightful analysis and other data points you may choose to kind of bring up to production grade, where it becomes part of your operating framework, where it becomes a KPI for a team to drive on. But if you end up in a world where every single new question is a cold start problem where you've got to go build the instrumentation, then start collecting the data, and there's a lag of like when the data is finally available, you're always six to nine, if not more months behind the problem. And so good data is one that you don't run into those walls as quickly as many of us do. And again, this is a journey, you don't do it overnight. But it is more of a culture of saying, let's record all that context. So when we do sit down at a room and be like, gee, why aren't people converting in this part of the experience to the same way? We don't immediately run into the hard wall like, "Whoops, that's all we know. I don't know. Can't go back. Can't study history." And so you're doomed to kind of repeat the problem until you can add enough instrumentation. So it's almost like a mindset, like good engineers try to build software that does not break. You cannot test quality into software.

Robert Gash: Good teams should also think of the data you should be collecting and capturing and how to store it in an economical way so that when you get curious in nine months, you have some data you can go look at and understand. And you cannot wait until the question presents itself. So long answer to a very short question of what is good data, but survives the three whys is maybe the nice little snippet for the summary and the show notes later. And ideally, the five whys. That's the real gold standard 'cause the truth is often further than that. But for a lot of us, we're not even getting to the one why. And so getting to three is a really nice step along that way.

Kailey Raymond: And I feel like if you are answering all of those whys, then hopefully there's this inherent trust within the data.

Kailey Raymond: Who do you think is doing it right as it relates to consumer experience? Are there any brands or experiences that you really love and admire? 

Robert Gash: This is a recency bias here, but I think they've done a good job for a long time. So I'll shout out to Chewy. We're talking earlier before the show around.

Kailey Raymond: New dog dad.

Robert Gash: New dog, yeah, new dog, dad problem going on here today. But in terms of just they are very, very forgiving and accessible. So you're gonna make mistakes in these purchasing experiences. You buy a thing that in our example, it literally didn't fit in the car, even though we thought it would. And just the way they treat the customer in those touch points of, yeah, okay, it is a return. It's one of those things that could cost a bunch of money but they make it accessible. They're not hiding behind a million different kind of call deflection techniques or trying to fool you into doing something you don't really wanna do. And I think that that's the thing we all have to remember is try to do the thing that's right for your customer to the earning the ability to get a login or to provide some utility in exchange for that value. We always need to remind ourselves that that must be earned and it can be lost in an instant. And so I give credit to Chewy as kind of one of a couple of companies out there that has really gotten that right over a long period of time? 

Kailey Raymond: You really have. One of the things that really strikes me is the, and I've heard this experience from a few folks now, so I know that it's not a rumor. I know that it's true, which is if one of their pets dies and then they have something on the way for that pet, food, whatever, they immediately reimburse it. And then they also send you a handwritten note, which is a really beautiful practice as a company and provides a lot of empathy to this customer. In a sense, that might not be a customer because they might not have a pet anymore. It's just a really interesting, it's something that you've been a loyalist for a long time, but you're gonna recommend Chewy for the rest of your life to any pet owner that you know. It just makes a lot of sense. My last question for you today, Robert, is if you were to do this again, if you were to restart your journey, what advice would you give yourself? 

Robert Gash: If I was to speak to myself personally, I would probably say, listen more and figure out what those feedback mechanisms need to be early in the process. I think all of us can probably think of projects in our world where we got stuck in a rut too long, and you look back and you're like, "Wow, that was really clear, but gee, I didn't see it in the moment." And look, that's part of your learning journey as a professional, but I would say, "You can think of those data sources now. How much time should this problem be given? Can you actually fix this? Or is the environment and circumstances that surround the problem you're trying to solve not really winnable in the time horizon you've got?" And so that's not specific to Hearst here, but I think just as a professional listening, think of that in every program. It's something I have to remind myself of as well. And it kind of helps you make sure you don't get stuck on a problem too long. You don't invest way too much time on this perfect little thing that didn't really matter 'cause you're gonna get it wrong in some cases. But that would be the thing. And wherever you can, link it with data, like invest in that early and make sure that you believe in that data is kind of, Kailey, the subtext of some of your questions earlier.

Robert Gash: When you've got five different conflicting metrics, it means you don't really believe in it. And so pick a few, two or three at most, that you do believe in, that if they go sideways would tell you you need to change direction. And it's not just a work thing. It's probably a good life practice as well, be it finances or otherwise. But I would say, wish I had known as much about that then in my earlier career as I do now. Probably would have saved me some time and some late nights along the way.

Kailey Raymond: Great advice. Robert, thank you so much for being here. It has been a pleasure.

Robert Gash: Yeah, I've really enjoyed the conversation. You have a great afternoon.

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