PODCAST: The Digital Era of Product Testing with Bold Labs' Chad Bingle

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Transcript

Chad: A lot of conventional research partners, all they do is tell you, this worked, this didn't. But with bold, we bring that growth and builder mentality. We actually dig into it and we go, here are the drivers and drainers of performance for this test, and we can help dissect where it went wrong, where it went awry, and also what to do next to fix and iterate on your product to get that fit with the consumer. You're listening to CPG launch leaders, the show where we interview new product trailblazers. Get ready for inspiration and secrets from the front lines of CPG innovation. Now, here are our hosts, Darcy Ramler and Alan Peretz.

Darcy: Hello, everyone, and welcome back to another episode of the CPG Launch Leaders podcast. I'm, um, your host, Darcy Ramler. And today I am thrilled to have a very special guest with me. He not only shares my passion for all things CPG and innovation, but also happens to be my brilliant colleague at Bold, Chad Bingle, our, uh, vp of, uh, product management and labs innovation. Chad and I have collaborated on countless projects, and I can tell you his insights into product testing and development are truly groundbreaking. As I like to say, he truly is the brains of our operation. Today, we're diving deep into a topic that's crucial for CPG brand innovators, how smarter product testing can dramatically improve the way we launch new products. Chad, it's fantastic to have you join me today. I'm looking forward to unpacking your perspectives on innovation and testing. So let's get started and shake up some traditional models.

Chad: All right, thanks, Darcy. Excited to be chatting today. We've been doing a lot of fun things here at bold on the innovation front. So, uh, yeah, it's a fun topic.

Darcy: So to get us started, I think a really good place to start is kind of getting your opinions on, um, why our current innovation funnels. Missing the mark is kind of something that's out there. I know we've talked a lot about it when we meet with prospective clients, and it's always really an intriguing topic to dive into. Maybe we start a little bit with the traditional methods versus modern needs and where that miss is today.

Chad: Yeah, well, this is a really, really challenging topic to dissect, but some of the big themes that we see with a lot of our clients we work with are really that tension between the traditional and the new digital approaches to. To testing. So you look at the traditional models, they're slower, they're thorough, um, but they tend to go slower. And the more stage gates you put in innovation, the slower you go to market on the digital front, you have some amazing, really agile tools at your disposal. The, uh, digital landscapes really changed how brands look at, uh, product ideation, uh, trend discovery and, um, product testing. But with that, it's really hard to figure out. How do you bridge the gap? How do you bring these two together into, ah, a new model for innovation that is both fast and thorough and has the agility that's required to keep up with the consumer?

Darcy: I think as the digital landscape is changing in so many aspects, even in the last, let's just say even the last three to two years is there's so much more that is accessible. And we've had the pleasure of having so many brands on that have even just said a lot of their innovation comes out of consumer feedback or social comments or kind of figuring out your next steps. There is this gap of where traditional methods used to be and a lot of it being more of a modeling base or going that direction to now we have all these resources and front of us that can provide us real consumer insights, fast feedback, and can, you know, so it's efficiency, it's real insights, and then it's also very, you know, cost efficient as well. Not only time efficient, but cost efficient for brands that are maybe don't have these large innovation teams or looking to refine the way they look at innovation and push forward.

Chad: Yeah, yeah, I think it's a good observation. I mean, there are countless brands that have really, uh, shifted how they go generate new ideas. Right. Um, looking at social content, looking for trends, uh, in those micro communities, looking at search behavior. And what tends to happen is in addition to kind of those silos we talked about between traditional and digital methods and teams, uh, you get a similar thing often with your testing methodologies and you could have ten, uh, different testing methodologies. And if there's no common link bringing them together, you've got, you still don't have a house. You need to really build that connectivity across your testing. Um, I think a lot of where labs, plugs in is helping brands connect the dots and find out how. Okay, we found this trend in social. How do we tie it to our machine learning predictive model in a way that's explainable and compelling and, uh, de risks us in meaningful ways that we can sell into leadership, into retailers. Uh, and so I think there are plenty of good tools out there. You have to know how to connect them and do so in a really compelling way. And I think bold is in a great position to do that for brands because we live on both sides of, uh, the traditional, uh, brand strategy, CPG strategy, and we live in the weeds of e commerce execution. We keep our pulse on the consumer. And it's rare that you have a team that has both, but I think that's so critical.

Darcy: Absolutely. And I think there's something to even be said about at the end of the day, you're looking at the digital landscape. Uh, we talk about a lot of this and like our base, you know, when we're helping brands in our base business. But you often see the beauty of the digital space is you can see category disruptors, brands, products in the digital space before you ever see them at shelf. And it's always that aha moment where you realize who's taking some share and it can start on an Amazon or it can start in a different matter and then, you know, you're going to be seeing them at shelf very soon. And I think because that is predicting a lot of what a brand or a product can do these days. And obviously, depending on the category, depends on specifics. There it is. Also, why wouldn't you use it as a space to really test and really work through the tweaks that are needed before you roll something fully to market and really bet on it as your best bet, your big bet for the season or for the year.

Chad: Absolutely. And with those first to market innovators that are going online, and there are so many of them, there's so much data too at your disposal. It's not just like, oh, uh, I saw a new product today, but there's this whole fingerprint, uh, of bringing that product to market that you can analyze from ratings and reviews to, uh, the sales estimates, to, uh, search share of search trends, uh, paid media estimates. And you can really start to understand, um, as other brands are dipping their toe in the market, which of these trends have longevity, which of these are going to materialize in one to three years that we should get after? So there's so much with, uh, how the consumer helps you validate those new trends, um, online. And so that's what I think is so compelling is you just have to find a way to string it together.

Darcy: Absolutely. Like you said, I mean, and stringing it together, there's ways you can have with ideation. And really the digital space can help there. There's parts that can help when you're looking at concept, there's parts that can look, you know, as you work through that full funnel, you can really use that digital space. And as you said, it's pairing the right tools at the right time to be able to refine, refine, test, refine, so that when you really get to that end product, you know, I think the big goal for us and really where labs started is going back to that staggering number of 70% of all products fail within CPG within the first two years. To me that number says something's broken. It does not say that we collectively, all of us as CPG launch leaders are knocking it out of the park. There has to be a way that we can refine and we can continue to improve this process so that we are, you know, we can get that number down to, you know, you know, it's never exciting when, you know, you've got less than a third of a chance to really survive out there. So, you know, what is, what does that look like? And, you know, kind of jumping in and ahead is let's talk about that e commerce landscape and how it's made testing, if you utilize correctly, how it really makes innovation, testing smarter and faster, in your opinion?

Chad: Yeah, yeah. I think you look at a lot of the ways that brands, as they get their idea closer to production, um, and they're kind of going through those final due diligence steps. The way they've historically de risked themselves is through um, surveys, actually going out and building a targeted survey and asking customers, would you buy? At the end of the day, there's a lot of other things that go into that, but the output of it is trying to get to stated consumer intent. One of the huge downsides to that is one there's a behavioral gap between what you say you'll do and you'll ah, actually do. Sometimes it turns out great, uh, especially with safe bets like safe products, with really innovative stuff, uh, the variability and the gap there between what consumers say they'll do, um, and what they actually do is quite significant. The other big downside of those traditional methods, uh, is the consumer knows they're being tested and that really affects the psychology of the test results. How the user is going to respond when you go bring your product to the digital landscape, to the native, uh, habitat of the consumer and they don't know they're being tested. Uh, whether it's a social ad or a simulated PDP or a digital shelf, ah, experiment that you're running, um, you can get some really invaluable behavioral feedback and that's what the, the reason you want that behavioral indicator is. You're letting consumers vote with their wallet. Right. And what better way to get to uh, that final stage gate in your innovation cycle than to say, well we've got great reason to believe that versus our current products or a competitor. We've got some really strong indicators of stopping power on social, um, stopping power and find ability in search of um, of recall and of course add to cart purchase intent. And when you can really tell that story, you bring not only a high degree of confidence, but a story. And you can't just rely on machine learning, um, models, black box models that don't tell you the why. Um, and some of how we test gives you both, it gives you the quant and it gives you the story.

Darcy: And I think I laugh when we always talk about real life purchases. Right. It makes me think of my kids when they get a gift certificate and it's like, it's not real money. I'll just spend it on like, sure. Why? It's not real money. So I think you bump up against that with a consumer if you give them $40 to spend. Or hypothetically, would you buy this for $40? Sure, why not? It's not hitting their bottom line, it's not hitting their wallet. There's really no, if you really wanna like work through the psychology, there's no decision tree that's being made there, right? They're saying, does this sound good to me? Sure, why not? Now, if you have $40 and you've got to spend it of your own money, you're debating, you know, what does that look like? Are you going to purchase it? What are uh, the reasons to believe you're digging way, way deeper into that product to understand what you're spending your own personal $40 on, or $20 or whatever it may be. You, you know, yes, there's impulse buys, but a lot of, you know, me being a psych major, I love to get into the psychology behind consumers and why they do the things that they do. Um, I just think there's so much more to putting them in a real life simulated environment. You're getting more of that raw consumer feedback. And I always say, I know we pair qualitative and quantitative, but my part on the quantitative of some of what we do when we get the research and the free, speaking of consumers, is the aha moments where they go off script and we find, you know, we're drawing together insights that they're making off the cusp or off script. And those are always, I say, the golden nuggets for our clients, because it's usually things that weren't necessarily in our questions going into it, but it's something they've brought to life.

Chad: Yeah, absolutely. I think what that raw feedback gives you, especially if you're testing in the right way, you're putting the right things, the right experience in front of the consumer from a digital path to purchase perspective, right discovery and consideration and, okay, I'm exploring this product detail page and thinking about buying. When you put the right things in front of the consumer, they're going to tell you a lot more, ah, about their purchase journey and gaps along the way. Um, but traditionally testing is all about, it's very product centric. And just tell me, do you like this lead benefit or not, right? Or, uh, uh. Which color is your favorite and why? Which one gives you the feels? And I think you have to get the whole story of how people shop. And a lot of times that doesn't happen in traditional testing until you're often in market. And it's very hard to adapt and make corrections once you've printed, you know, you've gone to production and you've got thousands of units on your hands.

Darcy: Absolutely. And I mean, and you see it all the time. Right. It's why we track the consumer journey. It's why we track, you know, the funnel, if it's d to c, is you need to see where they are falling out in that consumer journey. And it's a shame when you find that out when you've launched and you see, okay, this is where we're losing traction. And then you have to scramble and you have to pivot. Your marketing team has to pivot. Uh, you know, you're trying to coordinate what, what changes need to be made from your agency partners. There's just a lot of costs of coordination and quick coordination. And if you're already set on the shelf, it's not that easy anymore either. You know, I always say the old school way of, uh, back in the day of testing things was kind of selling it into the retailer. You have a relationship you're relying on there, so you have to get the retailer to buy in. Then it's what doors am I going to be in? Are they the right doors for the product? We're not sure where we're going to be on shelf. And then you have to kind of set it and let it do its thing to prove its way out. So to me, it's about before you even rely on that relationship with that retailer, which can be very damaging if it doesn't work. Right. Right. When you ask them to invest in it, is go ahead and be able to show them the process. You went through to refine this and the feedback you've received from consumers and the buy in that they have now there's a lot easier selling story internally and externally when people know the due diligence you've put in to refine the product idea, concept, packaging, all of that?

Chad: Oh, absolutely. There's something that just gets a retailer's, uh, attention when the thing you tested looks like their channels, looks like their search results, looks like their actual, uh, assortment on the in store shelf. And yeah, I think there's that credibility piece that, um, it's both the data side, it's also the soft side feeling like, yeah, this is contextualized to my realities as a, uh, you know, a pet specialty or as a Walmart. And so I think that's so key. Uh, the optics there.

Darcy: And let's talk about just a little bit agility, right? You know, I said old traditional model of selling into a store, but there's such an agility to testing, like, and then, and launching. Can you kind of break down a little bit about where you see that agility or even like a lot of the tools we use, whether it's fast feedback or whether we're looking at packaging, I mean, a lot of times we can go through those in one, two weeks and time to get results back to brands to make changes.

Chad: Yeah, well, uh, one of the things we do differently is we build a product hypothesis and narrative at the outset. And I, we poke holes in it throughout the whole journey rather than seeking to validate it. And it's a static, you know, well, we had a good idea, we got it blessed by the consumers, so we're running with it. And, uh, you know, from there the process becomes really just refining it to fit the mold, which, you know, that, that's one way to do it. But you can miss, uh, you can, you can still miss the mark and have some fundamental problems with your product's positioning and differentiation if you don't have that agility break built into your process. And one of the ways you build agility into your process is don't just ship it through your testing program. Make sure you break down your tests into a specific set of learning objectives. So what we do is we give our brand, our clients a learning plan and we updated after every test based on what we learned or didn't learn, um, to build in that agility and that willingness to go, let's revisit the fundamental assumptions we had when we got this cool idea. Um, and when you do that and you focus your testing around laser focusing it rather than scope creep, because a lot of conventional surveys, it's like we're going to do a conjoint and put 500,000 variations of this product formulation in front of the consumer and the winner takes all. And it's like, okay, I'm not downplaying that methodology, um, but if you put all your eggs into one basket and you bloat your test and it's not laser focused on, what are we trying to learn? What one thing is going to move us forward in the innovation journey right now, the most important thing that really, that type of thinking, instead of just, I want to know all the things, um, that focus is so key to agility and I think that gets, that gets missed when you have so many, uh, established ways of, um, running innovation testing. So, um, I think that's key. It allows us to do lots of smaller tests in a short time frame. So I think one bit of feedback we always get that's a very affirming of our approaches. I can't believe you've got this much feedback and this many results in such a short time frame. You know, to be able to conduct, say, eight distinct live tests, quant tests in a month or two, um, accelerator.

Darcy: And with their target market. Right, that's, that's the beauty of it all, is like, it's not just feedback, it's their target market. It's a being able to break out and sometimes, you know, against competitors, sometimes against a different segment that they may be looking to go after as far as a consumer. So I do think that I always laugh, um, when hearing you talk about, I remember when we introduced and launched labs and we brought it to our core business team and one of our heads at CST, our client service team, I just remember them raising their hands and they're, you know, they're so used to growing brands and they're so used to. The mentality is a growth mentality for brands. And at bold, we really do say, you know, we become owners of your business, we're there with you. We are true team members. But so they have this growth mindset because they're coming in, trying to grow brands, and this individual raises their hand and says, so labs, you're trying to not grow things, you're trying to break things. And I said, well, that's one way of looking at it, is like, yeah, we're nothing. Uh, we don't want to just see, I mean, great, if it's just out of the box, flies off the shelf, but that's probably not going to happen. So, yeah, we are trying to break down in little segments, you know, and find the why behind it and find the insights so that we can refine the concept. So it just always makes me laugh of the mentality when you're in, it has to be a little, you know, we're so used to a growth mentality over here and it is a bit of, okay, how do we break this?

Chad: That is so true. I mean, and I think that balance is important. A lot of conventional research, uh, partners, all they do is tell you, you know, this worked, this didn't. But with bold, we bring that growth and builder mentality. So it's not, it's not a, you know, it's broken. You go figure it out. We actually dig into it and we go, here are the drivers and drainers of performance for this test and we can help dissect where it went wrong, where it went awry, and also what to do next to fix and iterate on your product to get that fit with the consumer. And so I think that brand building aspect is powerful because we keep that. It's great if you say, I want agility in our testing process, but you need to bring, uh, that ability to build, um, as you're breaking it into the process.

Darcy: And I think one of the white spaces we fill at Labs too, is on our base business. We have an amazing creative team, right? Very strategic. Um, I think one of the problems some brands dive into is great. We work with people, they're testing, they're giving all this feedback. Now we have to iterate. Do we have a team that can do that fast when we have to do x amount of ads, when we have to do x amount of PDP's, different things. So at, uh, labs, we saw that as a major pain point and a barrier to always sometimes using alternative test models, right? So we went ahead and creative is a part of our service. Like we offer that complete service where yes, we're going to do the qualitative and the quantitative, but when it's time to iterate, our creative is giving you those versionings. And that to me really is a added value to our clients because first of all, a lot of times innovation teams don't have, if they have an internal creative team, they may not have the capacity or innovation doesn't have access to that. So being able to provide that service and do it quickly, again, we know everything is against a clock as we're testing and we have a date that we're trying to reach to. So I always find that, like, when clients come and say, oh, but the creative is coming with it and you guys are going to concept it and move it fast. It is something that I think allows us to really be nimble as we get feedback, to be able to pivot as well, because we all know a hypothesis is just a hypothesis until we've actually proved it to be correct. A lot of times there are going to be, again, I go the aha moments where we say, okay, that did not come out as expected. How are we going to pivot and how can we do that quickly? And a lot of times it may require new assets for that next round of testing.

Chad: Yeah, that's it. Brings to mind a recent example. Um, we were working on, we were in the shelf testing phase of a pack, redesigned and really the overall objective was get a new, strong packaging design, um, online and in store. Um, and one thing we noticed was your pack is really strong on a retail store shelf, but you haven't optimized the design for search result visibility, that little thumbnail. Like, we need to blow up the text on your pack for Serp results, for search engine result pages, um, for discoverability, um, if you really want that share, uh, of search click throughs. Right. And, um, so we tested it, um, got an updated version of the pack, did a controlled test versus the old, and we saved them months of headache because we gave in one day of just rapid iteration. Leveraging our creative team's expertise in this digital space, we gave them a, uh, 30% lift in click through rate on the Amazon search result page. And that's huge, right? So it's really getting those little wins along the way to, uh, the actual things you change about your go to market.

Darcy: And I think what we're tackling here, too, is, listen, if you're a large brand, the topic of conversation is incrementality, household penetration. Like, you know, we've gone away from the antiquated term of roas, not to say it doesn't matter. So I don't insult any media people out there, but there's bigger, you know, we're looking at lifetime value, we're looking at share of voice, we're looking at a lot of different metrics than we used to. And why I bring that up is the ECOM portion. Not only, like, for me, launching a product is you've got to look at it, it's got to be parallel path, right? It's got to be ready and what it looks like in the shelf, in store packaging, all of that. But then how do you also launch and be digitally ready? We know nowadays over 70% of consumers engage with products or brands for the first time in that digital space. So to your point, what is it if you have a great package in store, but it's awful when you have those 3 seconds to capture in an MPI to capture a consumer. And two of your biggest, well, your three top biggest retailers are one being obviously Amazon, but being completely pure play, right? So you're only getting sales digitally to being your Walmart and your target of the world who have trained their consumer to shop through an app. OPD has become such a huge purchase vehicle for them and a source of where, especially in CPG, the digital shelf is becoming more important of how you're showing up to that consumer and that packaging and the iterations that you need to make or the tweaks you need to make of really, uh, what does that, what does your package look like in store and how does it translate on that digital shelf? Is becoming in my mind even more important than it ever was because we just continue to push that way. You see it right now in some of the results from some of the big retailers of certain sales being down is that consumer is no longer walking the square. Like this is a big topic of conversation for me right now is. So what is to your point, what does discoverability look like? A lot of it looks like in the digital space. So refining, uh, that, getting those lifts, that's your incrementality, that's where it's going to come from. So, you know, I think, yeah, to your point is at labs, you guys are, you're not only refining it for launch in store, on shelf, but you're also checking that box of what does it look like on the digital shelf as well, which not many true testing methods can say they can do.

Chad: Yeah, I'm glad you brought up incrementality because that question comes up a lot and it should. Um, how does your testing help us get at new growth? Um, and when we do our quant testing on social, one of the beautiful things is the way we structure our audience. Targeting, um, is really intentional to both, you know, separate outlandish existing customers and lookalikes from the new to category, new to brand opportunities, uh, and rigorously test that. So, um, it's equally important in the testing to go are we actually reaching a net new audience or are we just getting head nods from an unknown customer base on, uh, yeah, this looks like a cool product and you're sort of trying to figure out, uh, at scale, does this represent a true growth opportunity or is this just, uh, going to result in portfolio shifting behaviors and no incrementality? So that's one thing I think, so. Cool.

Darcy: There's nothing worse than launching a product and knowing you're just trading dollars. So find it out early on before you're going there, because when you make something your big bet, and then you just realize, okay, this is just the same consumer. And now they've, now they've just decided to buy this product instead of the other product. You know, it is. And it happens. It does happen all the time. Listen, people are brand loyal, but it doesn't always mean that is going to, you know, the next product is going to basket build or is going to provide that incrementality. So understanding how your, your consumer right now sees it and that segment, but then trying to figure out who is that additional consumer that you can bring in, um, to the brand is a big part of what we discover as we go through this. And I always love, you know, I love the term stopping power because we, it means more now than ever. All of us are consumers. Even if we work in CPG, we're still consumers. Right? And we know, and I am always guilty of this. Like, I'll be in there and I'll be on Instagram and I'll be scrolling. I see an ad and I know, like, I know you're targeting me. I should not press this, like, in my head. I know what's going on. I know the psychology behind it, but there will always be things that intrigue me. And then it's like you're down the rabbit hole. Uh, but I love the notion of stopping power because to consumers, it is what has enough power behind it. What concept idea has enough power that it really, truly taps into that audience for enough for them to stop, click into it and want to learn more. Then you've, then you've got something there, right? Then you've been able to say, all right, they're on the hook. Let's start refining.

Chad: Yeah, yeah, absolutely. And the cool thing is you have benchmarks to your existing portfolio already because you're already advertising there. And if you don't, you can easily build that control of, you know, to measure that stopping power, strength compared to the current, uh, portfolio to see if this is additive. Um, yeah. And we intentionally, uh, test in social, one of many reasons is the noise. Like you said, there's so much noise, there's so much competition. So, yeah, it's not a lab, you know, sanitary setting like a survey, which we do those too, not knocking those but you also need the noisy, chaotic setting of social because that's where your brand, you know, survives or falls by the wayside.

Darcy: And I think that's uh, you bring up a key topic because we never rely on one individual testing method. Right. For us at labs it is what we've been able to build is that learning plan that really ebbs and flows through a lot of these methods and what they output is like where we find that success is the combination of them and how we iterate and how we move back and forth with them is really what's leading to consumer success on the other end and really the savings of what it, you know as they say, once you go to shelf, what is it? Three times is more to fix a mistake or fix an issue once it's hit shelf. Um, and I would probably argue that's conservative considering the marketing and everything you've pushed behind it before it was ready. But um why not spend the time and a lot of people's. I know there's disruptor brands that move fast in innovation today so this doesn't, what we're doing doesn't disrupt that but there's also a lot of enterprise brands that innovation is very rigorous process so being able to bring some more speed to that process and be able to be more disruptive, it allows them to now compete with some of these smaller and mighty brands that are being disruptive and taking share I think becomes key to some of the enterprise brands that are out there and companies. Hey CBG leaders. For decades product launches have relied too heavily on what consumers say theyll do rather than what they actually do. The result? 70% of new products fail within the first two years. Needless to say its a tough market out there. But dont worry, bold labs can help. We use transactional shopper data to help you better gauge size of the prize market, viability and consumer perception. All before your new product ever hits the shelves. How? By combining the best traditional and digital testing methods to engage with shoppers already in the buying mindset. These real world interactions yield actionable data. Thats right. No more guessing, no more surprises and most importantly, no more costly innovation fails. Bold Labs has saved brands millions by optimizing every stage of the product lifecycle. So are you ready to de risk your next launch? Make your innovation decisions with confidence, reach out for your custom learning plan@boldlabs.com. dot so I know we're going to jump in a little bit. Just let's dive one click deeper into what testing, um, can add to the innovation funnel and really help brands launch with confidence. So for me it's, it's kind of diving, double clicking into what do we feel? I know we've mentioned things here from a social, certain things, but let's just kind of highlight some of those things, starting with rapid prototyping.

Chad: Yeah. So um, one of the first things you need to do is get a lot of good ideas out there and rapidly screen them down to uh, the ones you want to spend more, uh, energy on. And so rapid uh, prototyping really simply is like, it helps you avoid that bias towards anchoring on the initial idea that came up in the brainstorm or in a workshop or uh, a listening session with um, a workshop with consumers even. And um, so recognizing that there are so many possible expressions and so rapid prototyping for us is uh, creating a really low fidelity mock up of what does this look like, what's the name of it? Give it, and now let's give it 20 names or 50 names and do a rough, uh, at some point in the process, a rough mockup of what it could look like and just a few reasons to believe, a few lead benefits, um, just not even above the fold, but a really low fidelity of what you might see above the fold and test as many as you can get. Rapid feedback, uh, from, from consumers, uh, that raw recorded feedback, that raw reaction, you get the why of how those are testing. And then another, um, thing we do during rapid prototyping is put it out there in a quant poll and put it out there on social to really narrow down on the handful of most viable concept variants that you can actually get after and um, actually afford to.

Darcy: Spend more time on going out of rapid prototyping. We also like to talk about native testing. And so I know I'm going to kind of hit you on a few of the things that, that to us really stand out with what we do at labs. But let's expand on that and native testing a little bit.

Chad: Yeah, some of it is like we talked about going where the consumer is going to social and Amazon, uh, search results, Walmart search results, and testing in the native environment in which they shop. Another piece of it is working, um, with the data that our partners have. They have custom social audiences, lookalike audiences, retargeting audiences that represent their core or proxies to their core business. They have CRM data, they have uh, robust d to c sites in many cases. Um, and we use that data to really understand the consumer and their native habitat. And like uh, we were talking about, that's how you um, get the raw, uh, true reaction from consumers allowing them to vote with their wallets, but then also something actionable, uh, in the form of, well, how do I make this product more refined, more targeted to this new to market or new to brand rather audience, um, so that I get the incrementality. So I just don't, that I don't waste time making it appealing to my core, hypothetically. And so I think that native pieces is just as much about going where consumers are as it is, um, leveraging the data you have on your current consumers and your new to brand, uh, prospects, um, to your advantage. Like why wait? Why wait till you launch, right? So many brands, they're waiting till the first year and that's their test period. And our perspective is do that now. You know, do pull that up in the process and do as much as you can now.

Darcy: Well, and you're at such a sprint when you launch, right? And it's every month matters. You know, you can make projections of what you're going to hit from a sales goal, from consumption, from a lot of things, and you're already in a sprint at that point. And it's hard to be sprinting and pivoting and the team being on the rails of doing all of this at the same time is. And to your point, if you can reduce that friction, why not take the opportunity to do so? I know we've talked a little bit about sentiment and listening to the consumer and how we approach that. I am such a fan of all that we're doing. I know we have some proprietary tools that we are able to dig in deeper into really understanding the consumer. But we know the power of ratings and reviews. We know the power of the search bar these days. I think there is so much to be said to listening to the consumer, listening to how they're searching, what they're searching for. And half of the time it can also lead to your next innovation, your next, like adding to the pipeline of where you should be even looking at your competitors or the category and being able to synthesize that into, okay, what are consumers loving about products that are succeeding out there? And then what are those white spaces that are missing those ingredients? Certain things. I mean, we've been able to do a lot of work and to me this affects every, every portion of the funnel. Right. I mean you're really digging into this. But we know consumers these days, they're not afraid to leave a review or to talk about their experience. My husband last night was having a bad experience where he was getting no response on a product that came and was open. And I go, well, what are you going to do if they don't respond? He goes, I'm going to leave a bad review. I was like, oh, you go get them, buddy, go get them. But it's, you know, that is, consumers love to know that they have a voice, and that voice is really important and it shouldn't be, you know, it should be utilized. And I think we are doing that. And you can expand on this in such a way that we're actually looking at, how does that help refine current innovation and find new ideas?

Chad: Yeah, the ratings and reviews piece is so valuable. Not only do we use it in our growth phase with clients to unlock opportunities to optimize, uh, what is in market, but we really see ratings and reviews as our first user listening session. And the reason is, like you said, they're going to be honest in ratings and reviews, brutally honest at times. Uh, and one of the benefits, uh, we've been able to unlock is analyzing hundreds of thousands of ratings and reviews, um, at scale across the category to really paint the semantic picture of, uh, how the consumer feels, who's, um, winning that loyalty, uh, who's got detractors, what's the nature of the unmet needs which represent untapped opportunity for product innovation? And, um, the amazing thing is you have with that ratings and reviews data, not just a lot of richness and, um, voice of the consumer, you have quantitative, you can translate it into quantitative indicators around sentiment to see how severe is this problem, not just how frequently does it come up, how strong of a sentiment is behind this statement? And you can, um, and how many, you know, how many brands are struggling with a similar thing, like is this a brand specific or a category pervasive opportunity, uh, that we need to exploit? And the cool thing is consumers are honest in ratings and reviews. They're also honest in their searches. And, uh, that's also both a quantitative indicator of where the market's going. It's also an insight into the psychology of those more bottom funnel or mid funnel opportunities for, uh, maybe more micro innovation in the next year to two, uh, to perhaps refresh your portfolio. Um, and pairing those two together, you get just tons of insight. There's so much, um, that's often where we start because it's free research.

Darcy: Absolutely. And I know we've talked so much about a lot of what we do really in the innovation process. But I do not want to leave without just touching on testing and learning is not something that just stops in innovation, right. It's something post launch. You need to be monitoring, you need to iterate, as we say. Maybe it goes away from iterating to optimizations. Is that what we want to say? We pivot to, but it is something that we need to ensure that you're always doing, you're always looking. The beauty of the digital space is we're always learning and we can learn quickly and we can move and we can make changes. So just love to hear how you feel like, yes, we have this great toolbox, this suite of things and services that we're giving at labs. But I think the most interesting thing as we developed labs was how many of our now clients on our base business, our true CPG, you know, digital agency business, are now utilizing also the tools for, like you said, their optimizations to learn for growth. Maybe, maybe they do have a launch coming. But you know, let's, let's just talk a little bit about in your mind what that looks like on the other side once, once you've launched.

Chad: Yeah, like post launch, I think it's, it's really challenging to one, a lot of teams that are handling the execution are already strapped, so it's hard for them to do too much more beyond that. So, um, I understand the bias towards make it work and just pour more marketing on it that'll, you know, pour some more lighter fluid on the fire.

Darcy: And more fuel on the fire.

Chad: Yeah, right, yeah, more lighter fluid on the fire doesn't always fix, you know, make for a better fire. It might be a big flash and sear your hairs off, but it doesn't mean you fixed the fundamental, uh, issues with your, with uh, your product, just that you fire up marketing. Um, we all know that. Um, so what we do is, uh, you know, we use that marketing as a feedback tool itself. So we structure from day one, uh, all of the paid search, ah, keywords in a very intentional way, um, based on what we learned pre market, pre go to market. So everything, um, we believe to be true about the keywords and lead benefits, um, and opportunities, uh, for this product as it goes to market. We're constantly listening through the way we structure, um, keywords from day one. And so we actually call it the testing phase, which is great, but it's so important because a lot of marketers are so used to thinking, I'm going to set up my keywords in a way that's awareness, mid funnel, bottom funnel and a little bit it's more segmented, it's totally appropriate to a more mature product that's already off the ground. You have to structure your whole paid media, which is often one of your bigger investments upfront, um, so that you learn from it. And so we do that. We learn which conquesting opportunities are most viable. We learn, um, how to gendered searches or uh, specific ingredient searches. Um, actually, where's our right to win? Um, and so we really decompose the keyword strategy in a way that enables us to learn. And a b testing the whole time is key. Um, I think as your marketing materials get flushed out, you have to, a b, test those and get the live user feedback. You have to, uh, leverage d two c as your test ground. Every time you do something, um, big on a retailer, find a way to test it on d two c. First, understand, um, both the transactional side and the qualitative side. Why are they, why are they, uh, resonating with this new campaign that we're about to invest millions in with this retailer or which direction is more compelling? So I think getting ahead of those things, you work out so many problems in that first year by, uh, really that continuous optimization. Don't assume your work's done just because of everything you did before you went to market, because you're just going to learn different things once that product is in, um, in the market.

Darcy: Yeah, I mean, that's where you can just continue to get that lift right. And if you, you never just settle with it, how high is up? You're never going to know it until you just continue to test, learn, optimize. It's a continuous cycle, without a doubt. Well, I'm sure you can tell that I could talk about this stuff all day, all night, and I could talk to you, chad, about it all day and all night, but we'd probably better get this episode wrapped up. Chad, I want to thank you for coming on today to talk about creating more successful product launches with smarter, faster testing from bold Labs. I hope you're leaving inspired to integrate these transformative techniques into your next launch and to keep fearlessly innovating, staying inspired, and continue to redefine the world of CPG innovation. We appreciate you, Chad Ize.

Chad: Thanks, Darcy. It's been fun. You've, um, been listening to CPG launch leaders, a show from bold strategies Incorporated. Don't miss the next thrilling launch story. Follow the podcast on your podcast player now. Please give us a rating, leave a comment, and share episodes with your friends. Until next time.