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Fix Fragmented eCommerce Data: The SMART Framework with Tim Shea · Selling on Giants: The eCommerce Marketplace Podcast

• 0:11
  SPEAKER_00: Welcome back to Selling on Giants.
• 0:14
  SPEAKER_00: Most e-commerce brands do not have a data shortage.
• 0:17
  SPEAKER_00: They have data trapped inside Amazon, Shopify, Meta, Google, retail partners, financial systems, and more spreadsheets than anyone wants to admit.
• 0:27
  SPEAKER_00: At a certain point, the problem is no longer finding information, it is getting those systems to tell one useful unified story.
• 0:36
  SPEAKER_00: Today I'm joined by Tim Shea, founder and CEO of LatticeWorks Insights.
• 0:41
  SPEAKER_00: Tim has spent 25 years helping retail and direct-to-consumer brands use data to make operating decisions.
• 0:48
  SPEAKER_00: In this conversation, we discuss when brands outgrow spreadsheets and how Tim's smart framework examines speed, margin, attribution retention, and customer tiers.
• 1:00
  SPEAKER_00: Tim also explains why LTV to CAC is more of a story than a single number, how brands can identify high value points in the customer journey, and why retail expansion makes attribution more difficult.
• 1:14
  SPEAKER_00: Most importantly, we look at how analytics moves beyond another dashboard and becomes a system for testing ideas, aligning teams, and making better decisions.
• 1:24
  SPEAKER_00: Let's get into it.
• 1:25
  SPEAKER_00: Hey Tim, welcome to Selling on Giants.
• 1:28
  SPEAKER_00: I'm really excited to have you on to talk about how to fix fragmented e-commerce data and anybody in e-commerce who's on multiple marketplaces, not to mention all the systems to manage inventory, it can get really, really weedy.
• 1:41
  SPEAKER_00: So I'm looking forward to having you on and really understanding how you look at data and how you guys organize it at Lettuce Works Insights.
• 1:49
  SPEAKER_00: But before we get started, Tim, you got 25 years working in the intersection of data science and retail.
• 1:55
  SPEAKER_00: What changed most about uh what changed most about your roles as you've stepped into what you do now and kind of how you sowed your oats in the marketing world?
• 2:04
  SPEAKER_01: Yeah, no, no, no.
• 2:05
  SPEAKER_01: I love the question.
• 2:06
  SPEAKER_01: Um, so I think thanks for having me on the show, Will, um, and appreciate everyone listening.
• 2:10
  SPEAKER_01: Um, yeah, my name is Tim.
• 2:12
  SPEAKER_01: I'm the founder and CEO of Lattice Work Insights.
• 2:14
  SPEAKER_01: It's a data science agency.
• 2:15
  SPEAKER_01: Uh, I provide data leadership, right, that helps retail and DSC brands become elite retail DSC brands.
• 2:23
  SPEAKER_01: So I've been doing data science and working with technology uh for 25 years, deep in advertising, working with other retailers.
• 2:30
  SPEAKER_01: I got 25 years of domain expertise, really kind of seeing all different shapes and sizes of retailers, uh, different ways of approaching different problems.
• 2:38
  SPEAKER_01: Um, I really just focus on helping people see their business more clearly, right?
• 2:43
  SPEAKER_01: There's a lot of confusion out there, a lot of complexity.
• 2:45
  SPEAKER_01: Um, so I want them to be able to see their their uh their company through a new clearer lens and help them graduate to their next stage of growth and work with like NBA, UFC, Sweet Green, Princess Cruises, Reddit.
• 2:58
  SPEAKER_01: And um, the reason I do it is because I like it.
• 3:00
  SPEAKER_01: I like founders, um, I like working with individual brands.
• 3:04
  SPEAKER_01: Every brand is kind of a snowflake and uh I like trying to decode like what's gonna make them successful.
• 3:10
  SPEAKER_00: That's pretty cool.
• 3:10
  SPEAKER_00: What uh what brings you the most excitement about some of the projects?
• 3:14
  SPEAKER_00: I mean, do you have impress NBA UFC?
• 3:16
  SPEAKER_00: Like uh do you have one that sticks out as like your favorite uh project?
• 3:21
  SPEAKER_01: You know, it's fun like as a data scientist uh coming from an advertising background, I loved the like consumer brief.
• 3:27
  SPEAKER_01: You know, they come in and they'd be like, um, okay, we're gonna pitch Adidas.
• 3:30
  SPEAKER_01: And Adidas is different than Nike because uh Nike is all about the you know, just do it.
• 3:36
  SPEAKER_01: It's about the individual, you know, will you as the athlete compete against yourself and everyone around you uh to do your best.
• 3:43
  SPEAKER_01: Adidas is more about like the team, it's more about your community and your crew, your neighborhood, uh, the uniform you guys are all wearing together.
• 3:52
  SPEAKER_01: And you're like, oh, that's that's true.
• 3:55
  SPEAKER_01: It's like a real like consumer insight.
• 3:57
  SPEAKER_01: It's a something the brand has a sort of personality, and its personality is sort of how it goes to market and how it talks to people.
• 4:04
  SPEAKER_01: And I love trying to untangle that uh for every individual brand because everyone's got a little bit of a different personality.
• 4:11
  SPEAKER_00: Yep.
• 4:11
  SPEAKER_00: And that messaging and getting it right is so important.
• 4:13
  SPEAKER_00: You know, are you speaking to the right audience?
• 4:15
  SPEAKER_00: And that's where that's where the data science lives, right?
• 4:18
  SPEAKER_01: Yeah, yeah, that's right.
• 4:19
  SPEAKER_00: Beautiful.
• 4:20
  SPEAKER_00: So so now, so you have a lot of 25 years and you've worked with all types of brands.
• 4:26
  SPEAKER_00: I can tell you're pretty deep with it.
• 4:27
  SPEAKER_00: So when you use phrases like frag, when we talk about fragmented data, like what does that actually mean inside of daily operations of some of these e-commerce brands, whether they're they're mid-sized, they're small, or they're they're enterprise level and they're making billions of dollars.
• 4:42
  SPEAKER_00: Like what does that actually mean?
• 4:44
  SPEAKER_01: Dude, it's crazy.
• 4:45
  SPEAKER_01: I would say like in the last even like 10, 15, 20 years, the problems then and the problems now are very similar, even in the era of AI, right?
• 4:54
  SPEAKER_01: Uh, the main problem that we see is that people have their mission critical data stored in like 10, 20, 30 different databases, different platforms.
• 5:02
  SPEAKER_01: Uh, well, if you and I were to start a company tomorrow, we would immediately have our mission critical data in Meta, Google, TikTok, Shopify, Amazon, Sephora.
• 5:12
  SPEAKER_01: We'd have Clavio, we'd have Salesforce, and quickly you and I would be having conversations about like, how are we doing?
• 5:20
  SPEAKER_01: What's up with the company?
• 5:21
  SPEAKER_01: Is what we did last week is it working or not?
• 5:24
  SPEAKER_01: And the the big struggle that everyone has is that the answer to that question is an effort of like downloading 20 spreadsheets and jamming them together, figuring out how they stitch together.
• 5:36
  SPEAKER_01: How do you stitch together Amazon data with Shopify data?
• 5:40
  SPEAKER_01: How do we know which ad dollars cause which sales?
• 5:43
  SPEAKER_01: And is it causing users that have a really long lifetime with us?
• 5:47
  SPEAKER_01: Um, so it becomes really difficult.
• 5:50
  SPEAKER_01: And brands are really good at being Adidas and selling seltzer water.
• 5:54
  SPEAKER_01: They're not great at data integration.
• 5:56
  SPEAKER_01: In fact, they don't really want to be great at those things.
• 5:59
  SPEAKER_01: So I come in and try to help them out, try and make that problem really easy so they can focus on the business of growing their brands.
• 6:06
  SPEAKER_00: That is pretty awesome.
• 6:07
  SPEAKER_00: And uh, it's actually kind of interesting.
• 6:09
  SPEAKER_00: I had somebody on not too long ago uh who does a little bit of the finance stuff, and we talked a lot about the marketing mix model.
• 6:16
  SPEAKER_00: And I love what you're saying because as somebody in advertising who pitches the CFOs and uh, you know, gets budget but needs to justify the budget, like uh connecting all the dots can be really difficult and explaining to somebody who's very dollar in, dollar out driven the value of impressions and eyeballs and long-term effects.
• 6:36
  SPEAKER_00: So um being able to organize that data and presenting it to teams, I'm sure makes a big difference.
• 6:44
  SPEAKER_00: For you, is it always the CFO or is it the operator?
• 6:47
  SPEAKER_00: Like, is it always the owner?
• 6:48
  SPEAKER_00: Like, who are you making these for?
• 6:51
  SPEAKER_00: Or is it for everybody?
• 6:52
  SPEAKER_01: Yeah, no, it's a great question.
• 6:53
  SPEAKER_01: Uh, most of my clients tend to be in the like the 50, 100 million or a year in revenue.
• 6:58
  SPEAKER_01: Um, the person who reach out is usually the one who's feeling the most amount of the pain, right?
• 7:03
  SPEAKER_01: And more often than not, that data sprawl problem that you're describing tends to be like a COO or CFO.
• 7:10
  SPEAKER_01: Uh, there are CMOs that uh reach out to us, but CFOs and COOs have their finger on the pulse of the business, or they're trying to have their finger on the pulse of the business, and there's gaps.
• 7:21
  SPEAKER_01: Either that COO is spending five, eight hours every week downloading spreadsheets, or they're like, gosh, I just I'm struggling to measure how much I'm spending on uh duty and freight.
• 7:34
  SPEAKER_01: Like I don't really see clearly how Meta and TikTok are working in conjunction.
• 7:40
  SPEAKER_01: Uh, it's really unclear to me should we be discounting deeply on Black Friday so that we crush our numbers?
• 7:47
  SPEAKER_01: And are we just cannibalizing potential, you know, loyal customers?
• 7:51
  SPEAKER_01: Are we getting lots of flaky people in the door by discounting deeply?
• 7:55
  SPEAKER_01: And so I think those harder questions become really existential for those folks.
• 7:59
  SPEAKER_01: And they're like, dude, I'm trying to run the business.
• 8:01
  SPEAKER_01: I can't be downloading data into a snowflake data warehouse and building dashboards.
• 8:07
  SPEAKER_01: And they usually come to me with their hair on fire and they say, I just can't do it anymore.
• 8:11
  SPEAKER_01: I need an expert to come in and help us out.
• 8:14
  SPEAKER_00: I believe it.
• 8:14
  SPEAKER_00: It's interesting too, because like uh you've been in the game for a while.
• 8:17
  SPEAKER_00: When you work with a company that's like all on spreadsheets and they're like, we have everything here, and you're like, oh my God, this needs to be organized better.
• 8:26
  SPEAKER_00: I can't handle this.
• 8:27
  SPEAKER_00: Um, and then you can see the evolution because necessity is really what drives it.
• 8:31
  SPEAKER_00: It's like to your point, the CFO who has to run the finances are spending five to eight hours pulling data, and it's like, is that the best use of the time?
• 8:41
  SPEAKER_00: Um, something I want to ask you.
• 8:42
  SPEAKER_00: You mentioned about elite brands.
• 8:44
  SPEAKER_00: So before we get into the main topic, I gotta ask you, what makes an elite brand?
• 8:48
  SPEAKER_00: Like, what is how do you define elite?
• 8:51
  SPEAKER_01: Yeah.
• 8:51
  SPEAKER_01: So, so um, yeah, I think we talk about this like kind of five disciplines for becoming elite, kind of a mix of like money ball for all the sports fans out there, mix of like money ball and intuition.
• 9:02
  SPEAKER_01: Um, these are things that they must reckon with.
• 9:05
  SPEAKER_01: They have to solve this data sprawl problem that you're talking about.
• 9:09
  SPEAKER_01: Their data's in 20 different platforms.
• 9:11
  SPEAKER_01: And until they do that, until they solve that, they cannot calculate, let's say, LTV CAC, right?
• 9:17
  SPEAKER_01: A golden metric, which is more of a story than it is a number, right?
• 9:23
  SPEAKER_01: There's a sort of undercurrent of signals happening in the business that don't show up on the PL.
• 9:28
  SPEAKER_01: Um, and so to get that full story for them, I take them through this thing called a smart framework.
• 9:33
  SPEAKER_01: And so for customers, we look at their speed, margin, attribution, retention, and tier of customer.
• 9:40
  SPEAKER_01: And this is the money ball stuff where we help them pinpoint um really high-leverage metrics like on-based percentage in baseball.
• 9:49
  SPEAKER_01: But in e-commerce, it might be like time to second purchase or the value of retaining someone from third to fourth purchase.
• 9:56
  SPEAKER_01: And it gets people a real sense that there's a uh return on their analytics spend.
• 10:01
  SPEAKER_01: And we literally call it ROAS, where people should have a feeling that they're making money uh off of their analytics.
• 10:07
  SPEAKER_01: And if they can get to that point, then they can kind of address the sort of final frontier of becoming elite, which is the sort of data culture, right?
• 10:14
  SPEAKER_01: In many ways, the hardest problem.
• 10:17
  SPEAKER_01: Uh, it's not a data problem necessarily, it's a people problem.
• 10:20
  SPEAKER_02: Yeah.
• 10:20
  SPEAKER_01: Well, how do you and I get along?
• 10:22
  SPEAKER_01: How do we speak the same language and growing this brand?
• 10:25
  SPEAKER_01: And how do we drive the company into the future in a way that is elite, as opposed to arguing about, you know, hey, is today Tuesday?
• 10:32
  SPEAKER_01: And what are we trying to do again on marketing and what's going on?
• 10:35
  SPEAKER_01: Um, those are the biggest issues that we see people bump their heads up against.
• 10:39
  SPEAKER_00: That is pretty awesome.
• 10:40
  SPEAKER_00: And I like how you have the framework.
• 10:42
  SPEAKER_00: And um, it yeah, I love that there's these steps to follow.
• 10:46
  SPEAKER_00: Um, we're gonna jump into the main topic.
• 10:48
  SPEAKER_00: So, right now it's how to fix fragmented e-commerce data.
• 10:51
  SPEAKER_00: And you already kind of alluded to it.
• 10:52
  SPEAKER_00: So I want to have you break down of like, what does it mean to be fragmented?
• 10:56
  SPEAKER_00: It's data that lives in different silos, and we're we're putting them all together.
• 10:59
  SPEAKER_00: My first question for you guys, for anybody who's new to this, like generally, what size do we need to start looking at this?
• 11:07
  SPEAKER_00: You know, I'd imagine if I'm under$2 million, uh, I could probably live on spreadsheets and be okay.
• 11:13
  SPEAKER_00: But, you know, what have you found where it kind of makes sense for companies to start looking at their marketing marketing mix model?
• 11:20
  SPEAKER_01: Yeah, no, totally.
• 11:21
  SPEAKER_01: Um, I I love the money ball analogy because like uh it works great in like um major league baseball, but not so great in like little league.
• 11:29
  SPEAKER_02: Yeah.
• 11:30
  SPEAKER_01: You know, so if you're uh if you're making a million bucks a year uh with a retail and D2C company, you've you've cleared a huge hurdle.
• 11:38
  SPEAKER_01: You you just you've really risen above the pack.
• 11:40
  SPEAKER_01: But the insights for people making a million bucks a year, the insight is more often than not, like sell more, grow more, go attack the TAM.
• 11:50
  SPEAKER_01: Um, when people get into that like$25,$50 million range, all of a sudden those spreadsheets become unsustainable.
• 11:57
  SPEAKER_01: You know, I walked into a client uh a couple months ago, and they're I'm like, show me the spreadsheet.
• 12:02
  SPEAKER_01: And they're like, Oh, it's it's plural, dude.
• 12:04
  SPEAKER_01: It's like there's 200 of them, and this is the one this person created, and this one references the other one, and then this the thing, the references all break.
• 12:12
  SPEAKER_01: And we're like, well, do you guys want to upgrade to a data warehouse?
• 12:15
  SPEAKER_01: And they're like, bro, no, that's just sounds like an aircraft carrier.
• 12:19
  SPEAKER_01: Like, what how what do we do?
• 12:20
  SPEAKER_01: Is there any way AI can do this for us?
• 12:23
  SPEAKER_01: And so the answer is is nuance, right?
• 12:25
  SPEAKER_01: As they got to figure out, okay, like, what is the right solution for me at this stage of growth?
• 12:31
  SPEAKER_01: Um, and if it's a$50 million a year brand, the upside, their next stage is like a hundred million.
• 12:39
  SPEAKER_01: So now the dollar value of fixing that is enormous.
• 12:43
  SPEAKER_01: At the million dollar range, like it's it's hard to spend a lot of money on analytics, it's hard to spend money on data warehouses, on AI and technology.
• 12:50
  SPEAKER_01: And yeah, it's funny.
• 12:51
  SPEAKER_01: Like, more and more I see of those brands are like, just go, just get big.
• 12:56
  SPEAKER_01: That's the insight for you guys.
• 12:57
  SPEAKER_01: Just get all your kids on base, make sure they all get hits, and uh, and then maybe you got one slugger they can knock it out of the park.
• 13:04
  SPEAKER_01: Um, so uh, but yeah, usually for me, I hunt in the 50 to 100 million dollar range because I know I can find opportunities for them.
• 13:13
  SPEAKER_01: I can unlock things that'll get them another$100 million in revenue.
• 13:17
  SPEAKER_00: That's amazing.
• 13:18
  SPEAKER_00: So, outside of the revenue, like what are the benefits of having this integration?
• 13:22
  SPEAKER_00: So it sounds like I can understand my customer, I can understand the customer journey better, I can understand where I might have a leaky button bucket because I've been pushing to get sales and not really considering how much it costs to do sales.
• 13:34
  SPEAKER_00: Like, what I'd imagine you work with a lot of brands, like what are the kind of uh problems or what are the benefits of having my data all organized if I'm not stating the obvious?
• 13:44
  SPEAKER_01: Um, if you uh let's see uh you and I, Will, in our fictitious company, right?
• 13:48
  SPEAKER_01: We're like selling on five channels, maybe we're we're marketing on five channels, maybe we're selling on five channels, maybe we're selling on Shopify and Amazon, and we're a target, right?
• 13:59
  SPEAKER_01: So there's a question of like, well, how are our marketing dollars affecting all these purchases?
• 14:04
  SPEAKER_01: Uh, to what extent can we see repeat purchases between individual customers?
• 14:10
  SPEAKER_01: Um, are we advertising on television?
• 14:13
  SPEAKER_01: Are we advertising?
• 14:14
  SPEAKER_01: Are we trying to glue together the value of a dollar on Meta and a dollar on TV?
• 14:18
  SPEAKER_01: It's like it's not just a matter of like sticking them in the same spreadsheet, you know, on the right day.
• 14:23
  SPEAKER_01: It's like, how should we really be thinking about the value of television ads?
• 14:28
  SPEAKER_01: What's the lead time?
• 14:30
  SPEAKER_01: Um, you know, if we're marketing like crazy on Facebook and we do a big partnership with Sephora, like are we paying on Facebook to drive people into Sephora?
• 14:39
  SPEAKER_01: Is that measurable?
• 14:41
  SPEAKER_01: And I think a lot of these philosophical questions keep people up at night and they don't they don't have the the techniques.
• 14:47
  SPEAKER_01: Let's say that you might have these big, well-funded incumbents on Madison Avenue or thinking about building media mixed models and doing attribution and building customer lifetime value models.
• 14:58
  SPEAKER_01: Um, and so I try and bring those more advanced techniques and try to put them in like lay person terms and give people like a real simple lightweight framework for measuring their business so they could say, Oh, okay, I see what I should be worried about right now.
• 15:13
  SPEAKER_01: Maybe I should let the Sephora partnership just like go bananas.
• 15:17
  SPEAKER_01: And if we're if we're paying for people to walk into the store, then great.
• 15:20
  SPEAKER_01: At least we're selling tons of stuff and clearing it off the shelves.
• 15:23
  SPEAKER_01: Um, so yeah, just trying to get um custom stuff for people so that they feel like they have a custom way of looking at the world.
• 15:33
  SPEAKER_00: Is uh every project you guys work on?
• 15:35
  SPEAKER_00: Or you mentioned Snowflake, so is every brand pretty much unique in that sense, or generally like uh a$25 million shoe company is very similar to a$20 million supplement brand.
• 15:48
  SPEAKER_00: It's just a different audience.
• 15:50
  SPEAKER_00: So is a lot of that data gonna be the same?
• 15:53
  SPEAKER_00: Are you recreating models all the time?
• 15:55
  SPEAKER_01: Yeah, yeah, honestly, yes.
• 15:56
  SPEAKER_01: And I think if I'm not, then really you should go to a SaaS provider, go grab something off the shelf.
• 16:01
  SPEAKER_01: Um, I mentioned earlier that we have this framework called SMART, the SMART framework.
• 16:05
  SPEAKER_01: Um, and this really illuminates why every company is different.
• 16:08
  SPEAKER_01: So what we do is we look at speed, margin, attribution, retention, and tier.
• 16:13
  SPEAKER_01: And what we find is that like the speed at which your customers buy from you varies wildly.
• 16:18
  SPEAKER_01: If you're selling shoes, uh, if you're selling uh seltzer water, if you're selling automobiles, the speed at which they get to that second purchase is wildly different.
• 16:30
  SPEAKER_01: Um, and so you know, how much do I need to pay to get them in the door?
• 16:35
  SPEAKER_01: Most D2C brands tend to think of after they've done their paid their paid marketing to get the first purchase.
• 16:41
  SPEAKER_01: Well, now I can just email them.
• 16:43
  SPEAKER_01: All subsequent purchases are just they're basically free.
• 16:46
  SPEAKER_01: I'm not paying CAC for the second, third, and fourth purchase.
• 16:49
  SPEAKER_01: Um, and the big one is retention, is that there's we've seen these retention curves.
• 16:55
  SPEAKER_01: And I really think it's important for people to think deeply about the drop-off between the first and second purchase is usually something crazy, like 80%.
• 17:04
  SPEAKER_02: Wow.
• 17:04
  SPEAKER_01: And so everyone gravitates towards that problem.
• 17:06
  SPEAKER_01: How do we lower that?
• 17:07
  SPEAKER_01: How do we get how do we get more people to buy a second purchase?
• 17:10
  SPEAKER_01: The problem is, is like a lot of people don't like your product.
• 17:15
  SPEAKER_01: And a lot of people may never like your product.
• 17:17
  SPEAKER_01: And so you're in many ways, you're paying to, you know, your your uh it's a bit of a lottery ticket when you're getting these first customers.
• 17:24
  SPEAKER_01: Some people buy six, seven, eight, nine times, and getting someone from a seventh to an eighth, eighth purchase is like very low leverage.
• 17:31
  SPEAKER_01: They've already sort of told you that they are a loyal customer.
• 17:34
  SPEAKER_01: So maybe it's that like third or fourth purchase that is really meaningful.
• 17:39
  SPEAKER_01: Or we've seen uh situations where we say, listen, if you can increase the amount of people that go from a third to a fourth purchase by like one percent, it's like a million-dollar opportunity, million-dollar incremental amount of revenue to your company.
• 17:53
  SPEAKER_01: So can we maybe talk about like this churn problem upstream is is difficult and challenging.
• 17:59
  SPEAKER_01: But if we can get half a percent of these third order people to a fourth one, maybe now we can send them a beautiful color brochure in the mail.
• 18:10
  SPEAKER_01: Maybe we can give them a huge discount to switch to a subscription.
• 18:15
  SPEAKER_01: Um, because that's they're right on the cusp of becoming a very high value customer.
• 18:20
  SPEAKER_01: So this is the sort of money ball stuff.
• 18:21
  SPEAKER_01: It's just like, you know, shooting uh shooting 30% from three is better than shooting 40% from the mid-range.
• 18:28
  SPEAKER_01: You know, let's load up on three-point shooters instead of loading up on these uh uh these other folks.
• 18:34
  SPEAKER_00: That makes a ton of sense.
• 18:35
  SPEAKER_00: Let's stick to the framework.
• 18:36
  SPEAKER_00: I have some other questions about retail and digital, but before that, I I like the framework.
• 18:40
  SPEAKER_00: So speed makes a lot of sense, now measurable.
• 18:42
  SPEAKER_00: So let's keep this scenario.
• 18:44
  SPEAKER_00: So now we know there's different buying patterns based on what we're consuming, which makes a ton of sense.
• 18:49
  SPEAKER_00: So how about the measure?
• 18:50
  SPEAKER_00: Is the measuring usually the same?
• 18:52
  SPEAKER_00: Is it always customer lifetime value and cost per acquisition, or are there other KPIs that we should be considering if we're running a$30 million e-commerce business?
• 19:03
  SPEAKER_01: You know, it's a great question.
• 19:04
  SPEAKER_01: I I just saw an interview with the guy from Grun's, right?
• 19:07
  SPEAKER_01: That's a brilliant, right?
• 19:09
  SPEAKER_01: I know, right?
• 19:09
  SPEAKER_01: We don't agree with them.
• 19:12
  SPEAKER_01: And so they sell for like a billion dollars.
• 19:13
  SPEAKER_01: Yeah.
• 19:14
  SPEAKER_01: And a guy says, uh, well, what are you really focused on?
• 19:17
  SPEAKER_01: He goes, LTB CAC.
• 19:18
  SPEAKER_01: And he goes, if LTB CAC is three, then you're golden.
• 19:21
  SPEAKER_01: And I love that idea, but the problem is, is like, what if it's not three?
• 19:26
  SPEAKER_01: What if it's two?
• 19:28
  SPEAKER_01: Am I supposed to yell at my LTB CAC ratio?
• 19:31
  SPEAKER_01: Like just get larger, right?
• 19:32
  SPEAKER_01: Like, what what specifically should I do to increase it?
• 19:35
  SPEAKER_01: So it can't just be a sense that, like, oh, we gotta get to uh LTB CAC ratio of three.
• 19:41
  SPEAKER_01: Maybe our cost per acquisition has broken.
• 19:43
  SPEAKER_01: Maybe there's a particular channel where our cash protection is really high, but those customers have a really long customer lifetime value.
• 19:52
  SPEAKER_01: Maybe their churn rate is really low.
• 19:55
  SPEAKER_01: The classic Black Friday one is like, you know, we uh we just crushed it.
• 19:59
  SPEAKER_01: We made a million dollars in one weekend.
• 20:01
  SPEAKER_01: And it turns out none of those people are coming back until next Black Friday.
• 20:06
  SPEAKER_01: So we just murdered it, we gave them a huge discount.
• 20:09
  SPEAKER_01: Our margins were tiny, and we lost them.
• 20:13
  SPEAKER_01: So maybe we shouldn't have been discounted.
• 20:15
  SPEAKER_01: Maybe maybe we can afford to not have a massive Black Friday.
• 20:18
  SPEAKER_01: Maybe we should focus on the January people.
• 20:20
  SPEAKER_01: Maybe this is a templole in like May or April that is much more valuable to us.
• 20:25
  SPEAKER_01: So I think like identifying what that metric is in your company is like the most important thing.
• 20:30
  SPEAKER_00: I like that too.
• 20:31
  SPEAKER_00: And I like the different channels, uh, will have different shopping behavior associated with that person.
• 20:37
  SPEAKER_00: Because you're right, uh acquiring somebody on Amazon's bottom of the funnel.
• 20:41
  SPEAKER_00: But if you're on Facebook and you've educated them on the products, I'm making it up, but uh obviously there it might be stickier because they chose you where other platforms it might just be quicker to be on the purchase.
• 20:54
  SPEAKER_00: Totally.
• 20:55
  SPEAKER_00: Totally.
• 20:56
  SPEAKER_00: So we got uh we have the the timeline, sorry, smart.
• 20:59
  SPEAKER_00: What was that's the speed margin?
• 21:01
  SPEAKER_01: Margin, margin that yep, attribution is the third, which is like right, you're thinking about this media mix modeling kind of world.
• 21:08
  SPEAKER_01: It's just like uh are we doing multi-touch where we want to know deterministically where people have been?
• 21:14
  SPEAKER_01: Are we doing a sort of uh econometric view on the world where we don't really know?
• 21:19
  SPEAKER_01: Is it unemployment?
• 21:20
  SPEAKER_01: Is it the weather?
• 21:21
  SPEAKER_01: Like what's what's really affecting uh how people are how people are coming in.
• 21:26
  SPEAKER_01: Um, retention uh is the other one.
• 21:28
  SPEAKER_01: So we look really deep.
• 21:30
  SPEAKER_01: This is probably the biggest one.
• 21:31
  SPEAKER_01: Is like realistically, what is it that you're buying with your CAC?
• 21:36
  SPEAKER_01: What type of person are you buying with your CAC?
• 21:39
  SPEAKER_01: Is it someone that's gonna take another three months to get to a second purchase?
• 21:44
  SPEAKER_01: I had this client and they're like, Man, we send them like 50 emails between the first and second purchase.
• 21:50
  SPEAKER_01: And I'm like, I know those brands.
• 21:52
  SPEAKER_01: I bought a t shirt from them, and they got a helicopter flying over my house, like my second t shirt, you know?
• 22:00
  SPEAKER_01: Um, and like maybe we maybe we should uh lower the amount of emails we send so they don't unsubscribe and they don't cut off our access to them.
• 22:09
  SPEAKER_01: Right now we have no way of getting them out besides paid.
• 22:12
  SPEAKER_01: Um is is first a second purchase the thing, or is it third to fourth?
• 22:15
  SPEAKER_01: Or are we a subscription business or are we not?
• 22:18
  SPEAKER_01: Are we trying to get them to buy three purchases and then eventually upgrade to a massive purchase?
• 22:23
  SPEAKER_01: So that retention story is like the most important thing.
• 22:27
  SPEAKER_01: And um, and the biggest one is just like tier.
• 22:30
  SPEAKER_01: I know it sounds obvious that everyone's got multiple types of customers, but if I had a dollar for every time someone said, like, hey dude, we have this platform, we're using triple whale, it measures our LTV.
• 22:41
  SPEAKER_01: We actually use Google Analytics, but it has LTV.
• 22:44
  SPEAKER_01: I was on our first page, it tells us what our LTV is.
• 22:46
  SPEAKER_01: And I'm like, So it's so you're saying they give you one number.
• 22:49
  SPEAKER_01: So you have one type of customer, and they all buy the same type of year, right?
• 22:54
  SPEAKER_01: They don't buy like it turns out you maybe have like four types of LTV.
• 22:58
  SPEAKER_01: And so I think the the recognition that there are multiple types of people in your company, people that need a lot of encouragement, people that buy like a metronome, and people that buy once a year, if you don't have a good understanding of that, then that LTV CAC number gets a little bit, you know, sort of misleading.
• 23:16
  SPEAKER_00: So I hear I love the tier because it sounds like it's it's personas.
• 23:21
  SPEAKER_00: What if I came in and I'm a$25 million brand, I imagine I know my customers pretty well.
• 23:26
  SPEAKER_00: But do you have to do any exercises to further identify that persona, if you will?
• 23:33
  SPEAKER_00: Because I mean you you're pretty much right there if you're building these tiers.
• 23:36
  SPEAKER_00: Or am I misunderstanding what the tier is?
• 23:38
  SPEAKER_01: I think I think sometimes the numbers bear it out.
• 23:40
  SPEAKER_01: You can just see some people just buy they buy the premium thing, and some people just buy the candle every time.
• 23:45
  SPEAKER_01: Um, I think the Adidas Nike one is a really good example.
• 23:48
  SPEAKER_01: A lot of times brands are really smart.
• 23:51
  SPEAKER_01: Big big epiphany, right?
• 23:52
  SPEAKER_01: They're like they're crushing it, they know themselves really well, they know their customers really, really well.
• 23:59
  SPEAKER_01: The customer they they sell on drops primarily, and uh they're crushing it.
• 24:04
  SPEAKER_01: The drop business is insane.
• 24:06
  SPEAKER_01: And um, they're like, Yeah, like we'll we get these people that are just dying to get in on the drop in the first you know 30 minutes.
• 24:12
  SPEAKER_01: We get these other people that get the coupons, we send the coupons out to these influencers and they get early access.
• 24:18
  SPEAKER_01: And what happens is that a lot of those influencers they send that coupon out to like a thousand other people.
• 24:24
  SPEAKER_01: And I'm like, oh, so we should we should stop that.
• 24:26
  SPEAKER_01: And they're like, no, no, no, no, no.
• 24:28
  SPEAKER_01: That's another type of user.
• 24:30
  SPEAKER_01: People that get the code from influencers are a third type of person that are looking to kind of get in on the action.
• 24:36
  SPEAKER_01: I got people that like show up after they've seen all the action, they go to a retail store.
• 24:42
  SPEAKER_01: Once they see the trend, okay, cool, I'm gonna buy that one.
• 24:46
  SPEAKER_01: So, oh, that's interesting.
• 24:47
  SPEAKER_01: So, you guys already know you've got four types of users.
• 24:50
  SPEAKER_01: And then we help them kind of give a little bit more color and a little bit more quantitative rigor to it.
• 24:55
  SPEAKER_01: But it's always interesting we come in and they're like, Oh, you sell um you sell sparkling water.
• 24:59
  SPEAKER_01: So, what do you what's your customer?
• 25:00
  SPEAKER_01: People that are thirsty and they're like, No, no, no, no, no, no, no, watch this, Tim.
• 25:04
  SPEAKER_01: It breaks out like this.
• 25:05
  SPEAKER_01: I'm like, ah, I love that.
• 25:07
  SPEAKER_00: That's too funny.
• 25:08
  SPEAKER_00: And I think if I I work with a brand recently, and uh they they do really well on sales.
• 25:13
  SPEAKER_00: And I was surprised.
• 25:14
  SPEAKER_00: He was like, My audience is women between 18 and 60.
• 25:18
  SPEAKER_00: And I'm like, everyone, like, dude, that's such a huge audience.
• 25:21
  SPEAKER_00: How are we how are we doing advertising?
• 25:23
  SPEAKER_01: Yeah, yeah.
• 25:24
  SPEAKER_01: Look, I I had a I had a uh not a customer, he didn't sign up.
• 25:28
  SPEAKER_01: Um, he was selling like um baby formula, and I'm like, hey, have you thought about like LTV CAC?
• 25:33
  SPEAKER_01: And he goes, he goes, listen, he goes, the lifetime of my customer is 12 months.
• 25:37
  SPEAKER_01: And he goes, and the reason why?
• 25:39
  SPEAKER_01: He's like, they're not breastfeeding anymore.
• 25:42
  SPEAKER_01: Like after 12 months, we don't need a product.
• 25:43
  SPEAKER_01: And he goes, So I actually have a business where like I don't care about the lifetime because I the lifetime is fixed.
• 25:51
  SPEAKER_01: I'm like, ooh, she was like, I think about TAM.
• 25:54
  SPEAKER_01: I was like, ah, see, another example where this company is a snowflake, we have to treat them like a snowflake and not prescribe what works for a different type of business.
• 26:02
  SPEAKER_00: Can you define TAM for us?
• 26:04
  SPEAKER_00: I I actually haven't heard that.
• 26:05
  SPEAKER_01: Oh, sure.
• 26:06
  SPEAKER_01: So total addressable market.
• 26:07
  SPEAKER_00: Oh, total okay, I know what that is.
• 26:11
  SPEAKER_01: You know, uh, I I did a um another project for uh cannabis brands, and um we were doing all this L T CAC analysis, and they were loving it.
• 26:18
  SPEAKER_01: There was really helpful, but they're like, there's a sense, Tim, that like boomers consuming cannabis is a new tan.
• 26:28
  SPEAKER_01: Right?
• 26:29
  SPEAKER_01: You know, I was all the all the all the audience members out there that kind of are are deeply uh entangled to what I'm saying here.
• 26:34
  SPEAKER_01: Like, there's a lot of people in their 60s and 70s that never use cannabis and when they were younger, and now they're retired and they're like, sweet gummies.
• 26:41
  SPEAKER_01: I can go to a store and just buy a gummy.
• 26:43
  SPEAKER_01: They're like, dude, this is a huge tan.
• 26:46
  SPEAKER_01: It almost doesn't matter what the history says about previous buying behavior.
• 26:51
  SPEAKER_01: There's a new class of users graduating into retirement and they're playing golf, uh stoned, and they're they're loving life.
• 27:00
  SPEAKER_00: Good for them, they earned it, right?
• 27:03
  SPEAKER_01: And they're and that's a huge tan.
• 27:05
  SPEAKER_01: We want to go out, we want to quantify the tan.
• 27:08
  SPEAKER_00: I love that.
• 27:09
  SPEAKER_00: That's pretty cool.
• 27:10
  SPEAKER_00: I have one more question, and then I want to talk about Lettuce Works Insights.
• 27:13
  SPEAKER_00: I want you to tell us what it's like to work with you directly and your team.
• 27:17
  SPEAKER_00: Uh, but I gotta ask.
• 27:18
  SPEAKER_00: So I work with some brands that are in retail, and they uh, because we're pretty good at Amazon and Walmart, they have asked me before, like, can you do advertising to drive eyeballs and feet foot traffic in the stores?
• 27:31
  SPEAKER_00: And it's something we've never done.
• 27:33
  SPEAKER_00: So I've always had to be like, nah, we stick to digital.
• 27:36
  SPEAKER_00: Here you go.
• 27:37
  SPEAKER_00: Uh, but like, um how do you track that uh in-person behavior?
• 27:43
  SPEAKER_00: It must be super challenging.
• 27:45
  SPEAKER_00: Is it easy?
• 27:46
  SPEAKER_00: Do you guys assist with that type of uh data analysis?
• 27:50
  SPEAKER_01: Yeah, so maybe the let's think of like two different types of companies.
• 27:53
  SPEAKER_01: You have these D2C companies, you have e-commerce companies selling on Shopify for years who then go in store.
• 27:59
  SPEAKER_01: And it's a big shift in the way they think about things because they can't measure every individual transaction.
• 28:05
  SPEAKER_01: And it's they don't have a direct to consumer relationship, right?
• 28:10
  SPEAKER_01: They get a little spreadsheet from the store every about this is how they did, they don't get John Smith as a line.
• 28:16
  SPEAKER_01: Another way to look at it is like the truly big brands, auto dealerships.
• 28:21
  SPEAKER_01: So there's a case study that's uh you know, it was like uh BMW thinks that it takes 25 years of advertising to get someone to show up at a dealership and buy their first BMW.
• 28:32
  SPEAKER_01: And so they're thinking with this time horizon of like, okay, this kid needs to see something in a magazine, he needs to see the BMW in a movie, he needs to see it in a rap video.
• 28:42
  SPEAKER_01: And then at some point he's old enough to be like, I'm gonna lease a three series.
• 28:47
  SPEAKER_02: Yeah.
• 28:47
  SPEAKER_01: And now there's this a whole lattice work of advertising where they're like, okay, now the dealership advertising is different than the Super Bowl advertising.
• 28:57
  SPEAKER_01: And now we're trying to get the person on the dealership to sign the you know, financing deal.
• 29:03
  SPEAKER_01: And so what we do is we try and like, again, try and figure out like what is the right measurement mechanism for this company at their right stage.
• 29:11
  SPEAKER_01: We had a brand that was selling um perfume on Shopify, and they did a big Sephora push, and they had this question about like, are we paying for um we paying dollars on Meta to drive people in store?
• 29:27
  SPEAKER_01: Because our cost for acquisition is going through the roof.
• 29:30
  SPEAKER_01: Yeah.
• 29:30
  SPEAKER_01: Who uh for all those folks out there selling on Meta, you see these costs per acquisitions rising.
• 29:36
  SPEAKER_01: Are we paying an inflated amount of money for cost per acquisition?
• 29:41
  SPEAKER_01: Or are we now paying for people to go into Sephora where we don't necessarily see the conversion in the same way?
• 29:48
  SPEAKER_01: And so we did this model for them where we're like, okay, cool, let's put all the Sephores on a map, right?
• 29:54
  SPEAKER_01: And let's think about okay, cool, let's look at all the people to buy on Shopify.
• 29:57
  SPEAKER_01: We have their zip codes, let's look at all the Shopifies that are that are like are the all the Sephores that are outside of those ranges.
• 30:04
  SPEAKER_01: And we just built a different lens for them about like, okay, these people didn't see a Facebook ad.
• 30:10
  SPEAKER_01: Or these people have no Sephora anywhere near them.
• 30:13
  SPEAKER_01: So they have to buy on Shopify.
• 30:16
  SPEAKER_01: And it was just a different type of model.
• 30:18
  SPEAKER_01: It's not how Nissan is doing it, but it was something custom for them to measure, like, okay, cool.
• 30:23
  SPEAKER_01: Like, let's accept there's a little bit of fuzziness in this data, but we can we can measure these things really well and these things in a little bit more fuzzy manner.
• 30:31
  SPEAKER_00: And I know retail, the reason I bring it up too, retail is expensive to get into, you know, it's a lot of money up front, and a lot of the deals they make, they have to put advertising dollars down and stuff.
• 30:41
  SPEAKER_00: So I was always interested at like how they measure, and that makes sense too, in that specific example.
• 30:46
  SPEAKER_00: And to your point, Nissan is thinking about it differently.
• 30:49
  SPEAKER_00: The BMW for 25 years, that's crazy, right?
• 30:52
  SPEAKER_00: Yeah, it was so crazy.
• 30:53
  SPEAKER_00: Talk about a long view on things.
• 30:55
  SPEAKER_00: That's that's right.
• 30:56
  SPEAKER_00: That's right.
• 30:57
  SPEAKER_00: Awesome.
• 30:58
  SPEAKER_00: Well, this has been super great.
• 31:00
  SPEAKER_00: I want to talk a little bit about LatticeWorks Insights.
• 31:03
  SPEAKER_00: So uh I'm new to this.
• 31:05
  SPEAKER_00: What does it look like for the first 30 days?
• 31:08
  SPEAKER_00: So I I love onboarding.
• 31:09
  SPEAKER_00: It's like it really determines a good brand from a great brand.
• 31:12
  SPEAKER_00: So I come on board, I'm a$30 million supplement brand, and I'm like, let's rock and roll, Tim.
• 31:18
  SPEAKER_00: Uh, what does onboarding look like?
• 31:19
  SPEAKER_00: What is the what does it look like to get started over the first 30, 60, and 90 days?
• 31:23
  SPEAKER_01: Yeah, no, absolutely.
• 31:24
  SPEAKER_01: I love the question.
• 31:25
  SPEAKER_01: Um, so um I have a package called Lattice Work Basic.
• 31:29
  SPEAKER_01: It's where I try to start all my customers.
• 31:30
  SPEAKER_01: It's a 90-day package, actually.
• 31:32
  SPEAKER_01: And so think of it this way: for the first 30 days, we're listening really closely.
• 31:36
  SPEAKER_01: We are treating you like a snowflake.
• 31:38
  SPEAKER_01: We are making sure we understand all the nuances of your business, things you've tried, things that have worked, things that have not worked, all the metrics, all the data.
• 31:45
  SPEAKER_01: What have you built so far?
• 31:47
  SPEAKER_01: What would you like to build?
• 31:48
  SPEAKER_01: What are you afraid to build?
• 31:49
  SPEAKER_01: The whole thing.
• 31:50
  SPEAKER_01: We want to know everything.
• 31:52
  SPEAKER_01: The second month we're building, and we build fast.
• 31:54
  SPEAKER_01: We're in the era of AI, right?
• 31:55
  SPEAKER_01: So we're spinning off reports, we're spinning off insights uh for a whole month.
• 32:01
  SPEAKER_01: We're feeding them to the customer and they say, yes, no, yes, no, I like this, I don't know this.
• 32:07
  SPEAKER_01: The third month we're doing experimentation with them.
• 32:11
  SPEAKER_01: We're literally trying to operationalize these insights as the data culture piece I mentioned.
• 32:15
  SPEAKER_01: Is that we're literally saying to people, okay, cool.
• 32:18
  SPEAKER_01: Do you believe that this is the insight?
• 32:20
  SPEAKER_01: Third to fourth purchase.
• 32:21
  SPEAKER_01: Okay, cool.
• 32:22
  SPEAKER_01: Let's A B test against that hypothesis and see if it works.
• 32:26
  SPEAKER_01: Let's see if we can get all the team members firing on the same page, that they're pushing towards the same stuff, that they're not just doing like a A test, not just throwing spaghetti at the wall.
• 32:38
  SPEAKER_01: Um, and let's really make sure you guys can operationalize this process.
• 32:42
  SPEAKER_01: Let's say probably half my customers keep us on retainer, sort of indefinitely.
• 32:46
  SPEAKER_01: And half of them say, Okay, we're good, but we want to make sure they know how to fish at the end of the process.
• 32:51
  SPEAKER_01: And so, yeah, by that third month, we're like, you guys are doing the analytical work now.
• 32:56
  SPEAKER_01: You guys are running plays and seeing how the how it's impacting the business.
• 33:00
  SPEAKER_01: So it's an exciting process to see, just in 90 days to see a company really kind of start to turn up at an inflection point.
• 33:07
  SPEAKER_01: Uh so it's yeah, super fun.
• 33:09
  SPEAKER_00: I love the testing you guys do as part of it.
• 33:11
  SPEAKER_00: And so you're also kind of coaching these marketing teams because you're like, here's the data based on my experience, this is what it's telling me.
• 33:19
  SPEAKER_00: Do you guys agree or disagree?
• 33:21
  SPEAKER_00: And then they'll be like, we can get behind these two.
• 33:23
  SPEAKER_00: And then are you telling them, like helping them, like, all right, run a meta test?
• 33:27
  SPEAKER_00: Here's show me what you got, and they'll they'll do it essentially for you.
• 33:31
  SPEAKER_00: And then you kind of read the data.
• 33:33
  SPEAKER_01: I think if you ask any man on the street, like what analytics is, they're thinking about a dashboard with a number on it.
• 33:38
  SPEAKER_01: Yeah, like, hey, let's have that Monday morning meeting where everyone reads.
• 33:41
  SPEAKER_01: You've been in these meetings, they read numbers off of a big screen to all 10 people in the room, and everyone says, Okay, cool, that was a that was a fun meeting.
• 33:48
  SPEAKER_01: Yeah, you're like, No, no, no, no, no, no, no.
• 33:50
  SPEAKER_01: Like, is that number what you want it to be?
• 33:53
  SPEAKER_01: No.
• 33:54
  SPEAKER_01: Well, what's the theory?
• 33:55
  SPEAKER_01: Are returns a spiking?
• 33:57
  SPEAKER_01: Is it seasonal?
• 33:58
  SPEAKER_01: Do we have a lot of competition?
• 33:59
  SPEAKER_01: Is meta the cost prequisition on meta going up?
• 34:02
  SPEAKER_01: Okay, you know what?
• 34:03
  SPEAKER_01: Maybe let's try TikTok.
• 34:05
  SPEAKER_01: Maybe let's try different creative, maybe let's switch supply chain uh 3PL providers.
• 34:11
  SPEAKER_01: Um, let's see if this has an impact if we change the discounts from$10 to$12.
• 34:17
  SPEAKER_01: Let's actually see what happens on the other end, as opposed to just sort of like, you know, putting your finger to the wind and be like, I feel like it worked.
• 34:25
  unknown: Yeah.
• 34:26
  SPEAKER_01: So we really want people to have a feeling of like, okay, like lean into the numbers, have an opinion, and actually have a framework so you can test those opinions.
• 34:35
  SPEAKER_00: I love it.
• 34:35
  SPEAKER_00: I love the framework and I like how you guys put it together.
• 34:38
  SPEAKER_00: What is uh what is unique about LatticeWorks Insights compared to some of the other competitors out there?
• 34:43
  SPEAKER_00: Like um, obviously sounds like you guys are very custom, but tell me like what have your customers told you is your superpower?
• 34:51
  SPEAKER_01: You know, I've um been thinking about this a lot as I've been doing LatticeWork Internets for about a decade.
• 34:57
  SPEAKER_01: I think a lot about like uh what I call left brain, right brain, unicorn generalists.
• 35:02
  SPEAKER_01: So it's really important for me uh that people know how to write code, know how to do data science, understand the rigor and the technology, uh, but they also understand the domain.
• 35:13
  SPEAKER_01: They have domain expertise.
• 35:14
  SPEAKER_01: Um they need to be able to think through a creative problem.
• 35:18
  SPEAKER_01: They need to think through the customer.
• 35:19
  SPEAKER_01: They're like, what is the difference between Nike and Adidas?
• 35:21
  SPEAKER_02: Yeah.
• 35:22
  SPEAKER_01: And so I think uh having both of those things is super important.
• 35:26
  SPEAKER_01: There's lots of vendors that can do data science and build technology.
• 35:30
  SPEAKER_01: Um go with God, you know, best of luck uh to them.
• 35:34
  SPEAKER_01: There's lots of marketing agencies usually that talk about being data driven, that talk about being data scientists, but they're not.
• 35:41
  SPEAKER_01: Yeah, they're not.
• 35:43
  SPEAKER_01: And so we try to drive um kind of straight down the middle.
• 35:47
  SPEAKER_01: We say we've got both of these skills.
• 35:49
  SPEAKER_01: And a lot of customers are very surprised when they hear us thinking about like, hey, let's talk about LTV CAC, let's talk about the voice of the customer, let's talk about the creative units that you're using, let's talk about the multiple channels that you're advertising on.
• 36:02
  SPEAKER_01: And um, I think that's really sets us apart.
• 36:05
  SPEAKER_00: I could totally see that.
• 36:06
  SPEAKER_00: This conversation was so in depth that you know you never know what you're gonna get.
• 36:09
  SPEAKER_00: And I love as an owner, uh, you it wasn't like I do this awesome.
• 36:13
  SPEAKER_00: It's it sounds like you hire great people and you have a really good infrastructure and framework, and great people make really happy customers.
• 36:21
  SPEAKER_00: So, Tim, thanks for sharing that's pretty awesome.
• 36:23
  SPEAKER_01: Thanks so much, Will.
• 36:24
  SPEAKER_00: Well, uh, to wrap it up, Tim, thanks for joining and sharing your experience with us.
• 36:29
  SPEAKER_00: Before we wrap up, can you let our listeners know where they can find you?
• 36:32
  SPEAKER_00: And anything else you want to share?
• 36:33
  SPEAKER_01: Yeah, no, absolutely.
• 36:34
  SPEAKER_01: Uh yeah, check us out at um latticeworkinsights.com uh is the website.
• 36:39
  SPEAKER_01: There's a whole bunch of stuff there about like uh the five disciplines for becoming an elite uh retail brand.
• 36:44
  SPEAKER_01: Um, you can find me on LinkedIn.
• 36:45
  SPEAKER_01: Uh, my name is Tim Shea, S-H-E-A for people that don't live on the East Coast for everyone's name, Shea or Sullivan.
• 36:51
  SPEAKER_01: Um, I love to be collaborative.
• 36:53
  SPEAKER_01: If people have questions, I'd love to be like a sounding board to see if I can help.
• 36:56
  SPEAKER_01: Uh, if I can't, I'll try to find another place, another person to send them to.
• 37:00
  SPEAKER_01: Um, but yeah, love to chat on LinkedIn or um reach out to us on the website.
• 37:04
  SPEAKER_01: And um we'll really appreciate you having me on the show.
• 37:08
  SPEAKER_00: And just you know, the links and everything will be in the show notes.
• 37:10
  SPEAKER_00: Tim, thanks for coming on and dropping all that knowledge.
• 37:13
  SPEAKER_00: We appreciate it.
• 37:13
  SPEAKER_00: We'll see you next time.
• 37:14
  SPEAKER_01: Thanks, guys.
• 37:16
  SPEAKER_00: That wraps up today's episode of Selling on Giants with Tim Shea.
• 37:21
  SPEAKER_00: The biggest takeaway is that fixing fragmented data does not begin with purchasing more technology, it begins with understanding the decisions the business needs to make and identifying the information required to support that.
• 37:35
  SPEAKER_00: Tim's smart framework gives operators a useful starting point by examining speed, margin, attribution, retention, and customer tiers.
• 37:45
  SPEAKER_00: We also discuss why LTV to CAC cannot be treated as one universal score.
• 37:51
  SPEAKER_00: Customers acquired through different channels and promotions may behave very differently.
• 37:57
  SPEAKER_00: The most valuable opportunity may even sit between a customer's third and fourth purchase rather than the first and second.
• 38:06
  SPEAKER_00: Retail expansion makes attribution less precise, but the goal is not always to eliminate that uncertainty.
• 38:13
  SPEAKER_00: It is to measure what you can, acknowledge what remains directional, and build a model that fits your business.
• 38:20
  SPEAKER_00: Most importantly, analytics should not end with people reading numbers from a dashboard, yawn.
• 38:26
  SPEAKER_00: The numbers should produce a theory, the theory should produce an experiment, and the experiment should improve the next decision.
• 38:34
  SPEAKER_00: We're all little diet data scientists here.
• 38:37
  SPEAKER_00: To learn more about Tim, visit LatticeWorks Insights.com or connect with him on LinkedIn.
• 38:43
  SPEAKER_00: Both links are available in the show notes below.
• 38:47
  SPEAKER_00: If this episode helped, please follow, subscribe, and leave a review wherever you're listening in.
• 38:53
  SPEAKER_00: It helps more e commerce operators find the show and may earn us a little grace from the Apple Podcast Gods.
• 39:00
  SPEAKER_00: Thanks for tuning in, and we'll see you next time on Selling on Giants.
• 39:04
  SPEAKER_00: This is Mr.
• 39:04
  SPEAKER_00: Will signing off.