In some ways, we know everything and nothing about our customers at the same time. 

We have mountains of data at our fingertips for every customer interaction. 

But we can’t see our customers. 

We don’t really know what they love, why they buy, or what they’re into—even insights into why they bought from us or how they first learned about us are muddy. 

Even when we think we know, our view is incomplete. 

That’s where KnoCommerce comes in. 

Sure, you have a few different attribution tools. They can be helpful but also confusing. 

And they have biases. 

Sure, you know conversion rate optimization best practices, but every brand and every customer is slightly different. 

Getting customer insights through post-purchase or abandon cart surveys can provide clarity into what your attribution or CRO data is telling you…or, more importantly, what it’s NOT telling you. 

The good news is you don’t have to use Kno to get great customer insights. Any survey tool can work. 

In this episode with Kno Founder and CEO Jeremiah Prummer, we discuss the following:

• 40% of your shoppers buy in less than 1 week of learning about your brand. 60% take longer than 1 week. (This probably contradicts what GA and your attribution tools tell you).
• The biases in surveys and how to work around them?
• The biases in the attribution model.
• How abandoned cart surveys can be a game changer in addition to email flows.
• What questions to ask your customers for the most actionable insights
• And More!

Transcript:

Jeremiah:

And so the number one use case on our platform is attribution. It's 80 to 90% of the usage of our platform, to be honest. Well, 80 to 90% of the brands on our platform are using that use case. A lot of them also have other use cases they're addressing too. But I would say that almost all the brands that use our product are doing are addressing attribution in some form or not.

Brett:

Well, hello and welcome to another edition of the e-Commerce Evolution podcast. I'm your host, Brett Curry, CEO of OMG Commerce, and I am super excited about today's guest and today's topic. This is one of those guests that I met on the LinkedIn. I started following this guy's content. A lot of my friends were commenting on his posts and I'm like, this is a super smart dude. So we connected and then we were talking. I'm like, how do we not know each other already? And so delighted to Welcome to the show, Jeremiah Prummer. Jeremiah, how's it going man? And welcome to the show and thanks for taking the time.

Jeremiah:

Yeah, thanks man. It's really good to be here. Hopefully you didn't oversell it too much, but yeah, it's good to chat. I know we've been chatting for a while on LinkedIn. I don't know, probably like six months. So anyway, it's good to finally get to actually meet, and there's something always different. There's three layers. You've got the text chat layer and then you've got the video chat layer, and then you've got the in real life layer and each one feels pretty different.

Brett:

It does. And you get maybe even before that is the comment layer I'm commenting and sending you different emojis about your posts and things like that. Yeah, exactly. And so where we got to the video chat level in person's going to be next, and so we'll just have to wait for that. But for those that don't know, Jeremiah is the CEO and founder of no KNO commerce and used by a lot of the fastest growing D2C brands. Everybody that uses it loves it, knows it, no pun intended, talked about a lot. And so we're going to dig into some really interesting topics around customer insights and we'll talk a little bit about attribution and talk about just what are the things you need to know to be able to improve your marketing, your product, your customer relationships, and should be a ton of fun. I'm super excited. And so we'll dive right in. For those that don't familiar with the story, tell us kind of the quick background of no, why did you start it? What was the original mission? Yeah,

Jeremiah:

Absolutely. So I'm going to go back a little bit earlier to just kind of give a little bit of context and then start with the actual founding of the business. So I've been in the e-commerce space in some capacity since 2012. I started building WooCommerce extensions, so that was kind of woo

Brett:

Nice. Yeah,

Jeremiah:

Back in the day it was WooCommerce, Shopify, Magento were all kind competing. It's kind of a different story now, but at the time WooCommerce was really hot and it was open source software. So really cool experience. Honestly, it's very different than what I'm doing now I'd say. But I loved that and it was just, there's something about getting to build something that you just are browsing a random website and you see the technology you created being used. It's pretty cool. So I kind of got my first taste of that in that time and then did a few different things. I had my own brand for a little bit, did agency work, and then in 2020 pandemic hits. And one of my good friends, Pearson kras is his name runs an agency called Lunar Solar Group. And Pearson and I had been talking for years about building a tech companies together and I, he'd been a merchant using my WooCommerce extensions back in the day and I'd helped him with website builds at his agency.

So we'd worked together in some capacity for a long time. And so it just made sense. So we actually launched no commerce from within his agency. They had some internal tools. We basically just revamped into a really lightweight surveys product that was kind of our pilot application. And then we started building our platform on the side. So we launched that just so I could get some experience in the Shopify ecosystem and learned a lot over that first year while we were building the main platform. And then we launched that main platform in September, 2021. We split the company out into a separate entity and that was kind of the genesis of everything. So it's really been just over two years since we actually launched the full platform. That

Brett:

Is wild.

Jeremiah:

So yeah, it's been kind of fast, I dunno. So days I'm like, I just want this to slow down a little bit, just get some rest. But it's also fun. So there's that trade off, right?

Brett:

Totally. And no rest for the weary, especially not in this environment, but really, man, I would so much rather do something that I love than to be bored. And so absolutely, as long as you can find little bits of rest in the chaos and speed, then you can probably keep going, which you guys have done. That's wild. I actually did not know that it was just in 2021 really that you started to gain traction. So that's even faster than I expected and pretty amazing. So what was the original mission and the idea? So start with a lightweight survey tool then. How has it progressed since then?

Jeremiah:

The problem ultimately is that it's really hard for brands to understand who their customers are, what motivates 'em. I like to look at it from a standpoint of in-person retail versus online and how different they are. So I grew up in a small business. My parents owned a health food store and I worked in that from the time I was, well every summer from the time I was 10 years old on. But even before that as a kid I was around a lot. And so you see the same people walking in the door and at the time it was nothing was digital, so it was literally just punching the numbers. So we actually didn't know what people were buying necessarily, but

Brett:

You knew a lot about them. You knew what they were interested in and why they were there and you could see them and interact with them. And that's such a valuable data set that we

Jeremiah:

Don't have. You knew about their dietary preferences, you knew about the type of vehicle they drove sometimes, what kind of clothing they wore, what their style was, all these kinds of things that you just cannot see in a digital context. And I don't know that you can honestly ever replicate that, right? It's just different. It's a different context, but is there a way to bring some of that context into the digital world? And that's really been the mission. And I would say, honestly, I actually posted something about this earlier today, but we started with surveys as the foundation of that because the reality is you have to ask people. That's the only way you can actually get some of that data. But the real vision goes much beyond surveys and I'm excited to dive into that more. I think honestly it's just been getting to the point of we got to build a foundation. We have about 3000 brands we work with now, so kind of got to get the foundation in place, you got to know what you're doing and then you can build on top of that. And that's really been the entire approach.

Brett:

That's so awesome. And you really talked about, I read a post recently that you made on LinkedIn, that first ever customer insight platform. We have data, we have attribution tools, we have different analytics, but customer insight platform, I think you've already talked about it, but anything else you would add to that or any other ways you would explain that to kind of shed light on what you guys are trying to accomplish?

Jeremiah:

So there's a lot of really great products out there that are focused around understanding things like lifetime value of your customer. What types of products cross-sell well together? If somebody buys product, if they buy a pair of shorts on order, number one, they're likely to buy a pair of socks on order number three, that kind of stuff, which is all really great information and there's some amazing tools that do that. And so we're not really trying to replicate that. That's not our goal. Our goal is to build a layer of data that enhances that. And so we are, it's honestly a really hard problem. The reality is that if you have every order exactly what somebody bought, the timing of the purchase when their last purchase was, you can see all of that data. There's no question about the accuracy of that data. There's no question about the completeness of that data.

It just exists. Collecting survey data about those same people is a lot harder because you're never going to get a hundred percent response rate. You're never going to know exactly what to ask that person until you have a little bit more context about them. There's so much more nuance there that I think it becomes a really challenging problem. And so we do a decent job right now of helping with that, but I think there's so much more that we need to do in the future to actually fully, we'll probably never fully solve that problem, but actually get to the point where it's significantly more meaningful than what it's

Brett:

Today. Yeah, it's so interesting when you look at a tool like this that really uncovers some customer insights or even attribution tools or analytics, it can seem simple on the outset, like, oh, we're just asking questions. But then as you dig a little bit deeper, it's pretty complex and it's nuanced, and the way you ask a question is important. How do you collect the data and how you analyze it and what did this actually mean? And so yeah, lots to unpack there. I do want to dive in and just understand what are some of your favorite questions to ask, because I think this is one of those things that we talked to a lot of merchants as an agency and everybody's got some sort of attribution tool and they're measuring in platform and things like that, but still, we know a lot of companies that are not serving their customers or not running anything like no in their tech stack. So what are some of your favorite questions to ask and why?

Jeremiah:

Well, so just one step higher level than that. I think the use cases can differ quite a bit, right? And that's one of the beautiful things about surveys is you can kind of do whatever you want to with it. And so the number one use case on our platform is attribution. It's 80 to 90% of the usage of our platform, to be honest. Well, 80%, 80 to 90% of the brands on our platform are using that use case. A lot of them also have other use cases they're addressing too. But I would say that almost all the brands that use our product are addressing attribution in some form or another,

Brett:

Meaning they're asking an attribution related question in addition to maybe other questions, 80, 90% are asking attribution questions.

Jeremiah:

Exactly, and there's some that aren't, but most of 'em are. And so in that context, there's some really great questions and I'll dive into those a little bit more, the set of questions that I feel the best about because we see so much of that, right? Beyond that though, conversion rate optimization is a really cool use case. So asking questions like what motivate not what motivated you? Sorry, what about this product made you want to buy it today? That's a really interesting question. And so brands will ask that kind of a question and that can give you a ton of insight into things like ad copy and what kinds of angles somebody may be interested in looking at. The negative side can be really interesting too. So asking somebody a question, how was your shopping experience today? If they gave you excellent or great, maybe ask them to leave a review if they're a repeat customer or push them to some other thing that they may be interested.

Hey, join our Facebook community, whatever it is, give them some sort of additional way to engage with you positively. And then if it's a negative response, then asking them what about their experience today was not a good experience and just let them give you that open-ended feedback. Those kinds of things are really, really valuable, especially for brands that are having problems with their conversion rate brands that are just getting started and don't quite know if you haven't found product market fit yet and you're not able to just scale ads, there's levels to this game for sure. I mean, some of the brands we work with are spending a hundred million a year on paid ads and they'd consider that a success and others are spending a hundred thousand a year on paid ads, and that's a success for them. So no, I can't give you a specific of what that looks like in terms of product market fit, but once you feel like you're at that point where you can just kind of scale your ads, I think that's when you start looking at attribution.

And prior to that, you're looking at those kinds, purchase motivations, those kinds of questions. So that's all really interesting. Demographic type data can be really interesting too, especially if you're trying to understand personas, who's buying what products, what kind of messaging is resonating with different demographics, that all can be really valuable. So a good example of that, just broadly speaking, we see that men between the ages of 25 and 44 spend a lot of time on YouTube and high rating and reviews of products has a major impact in their purchasing behavior. So if you're showing ads on YouTube, that's probably a good thing to have in the back of your pocket. Okay, if men in this demographic are typically the best audience and they're looking for this type of product, they're spending a ton of time on YouTube, maybe that's where I should start and then iterate from there.

So that kind of stuff can be really, really valuable. And then on the attribution front, so I'll dive into a set of questions that we really like to see brands ask. So question number one, how did you first hear about us? And we actually have a survey template that we recommend here, which gets that question alone, sees about 1.3 million responses per month on our platform, people using that specific question. So question number one, how did you first hear about us? Then usually some follow-up questions. For example, if somebody said that they found you on Google, ask them what they searched for, that can be a really valuable way to get some keywords that you can then go target maybe some longer tail stuff you weren't thinking about. What you find that's super interesting in that context is people will literally type in what they typed into Google.

You can tell just based on the response, you look at that and you would never type that unless you were doing a Google search. So it's kind of cool to see that data. So we'll usually suggest some follow-up questions to that. How did you first hear about us? And then ask, what brought you to our site today? And what we're looking for is the difference between a discovery channel and a purchase driving channel in those two. So discovery channels are the places where somebody is going to find your brand for the first time, Google, Facebook, Instagram, TikTok, word of mouth, retail store. Those are the kinds of things that are driving that top level discovery. But then the purchase driving channels are more focused on, I saw an ad, I searched on Google, I received an email, I received a text message, those kinds of things because your email is not actually a discovery channel unless you're doing email swap stuff, which then add that to your top level question.

But otherwise, that's actually a purchase driving channel and it's a nurture channel. It should not be part of your, how did you hear about us question. And so I think where a lot of brands go wrong in the attribution side is they ask, how did you hear about us? And they don't get specific into those different touch points and it muddies the data a little bit. And so it becomes harder to understand. You're asking the customer to interpret the question when you ask that specific question of how did you hear about us? And the reality is a lot of customers have multiple touch points. So if you split them out, then you're actually going to get a clear better view. And then the last one that we like to layer in there is how long did you know about us before placing your first purchase? And that gives you some really incredible stuff. I think you were saying something about this post that I put out there where we were looking at time to basically the contribution to Black Friday, cyber Monday revenue based on how long a customer knew about a brand before making their first purchase. And this is really fascinating information.

Brett:

Let's dig into a few of those things really quickly and then let's go right to the Black Friday seller money. I love that data. What's so interesting is I remember when I first saw this study as a user and as a shopper, I'm also a marketer, so I get a little different lens here as I look at this stuff, but I'm confident it was a no commerce survey because I remember I looked because I was very interested. I was buying, I think it was a shirt. What I have on here is a shirt brand that I've been following or seeing on social media forever, but just hadn't purchased. And I went through the survey and I thought, when did I first hear about it? Because such an important question. It's all the quality of the answer you get is directly tied to the quality of the question you ask.

And so yeah, when did I first hear about it? So I went back and I'm pretty sure it was Instagram in this case. And then how long ago? How has it been since you heard about it for this one? And we're talking about a T-shirt here. I didn't need to deliberate over this a long time, but as I thought about it, I was confident it was months, it was like three or six months, maybe a year. I was like, I don't know, just didn't need a shirt, wasn't really motivated, but I know that I've been seeing stuff forever. And as I posted that, I was like, man, I'm a marketer. I talk about YouTube ads, Google ads all the time, but this's just a different lens. And it flipped it for me and I was like, dang, look at my own behavior. I had to learn about this brand months ago T-shirt brand before I actually purchased. And so yeah, super interesting

Jeremiah:

Insights. I think, and I don't mean this to be negative at all, but I think of in the marketing world, the platforms have kind of trained marketers to think of things on a seven day conversion

Brett:

Window, right? Yes.

Jeremiah:

Some of that's

Brett:

Being generous. Sometimes people are like, well, I really want a one or three day, but we'll loosen things. We're looking at seven day now.

Jeremiah:

Exactly. And I see we were just talking about Taylor earlier Taylor Holiday, so give shout,

Brett:

Shout out to Taylor Holiday. What's up buddy?

Jeremiah:

So Taylor, I love Taylor and one of the things he's talking about, and actually before I say this, I want to say I really, really appreciate the way he's always talking about profitability first, right? Yes.

Brett:

Contribution margin profitability, dude. It's like it's what people need to hear. Yes,

Jeremiah:

For sure. So coming from that lens, a hundred percent respect to what he talks about in terms of optimizing on one day click. And so I get that angle and that side of things, but at the same time, what we know from the data that we see is that the people who you are getting to convert in a day are either already warmed up to your brands or they're in market for the product that you're selling. Those are the only people who are buying the same day and there's nothing wrong with that for sure. But the risk that if you are in a small category and you are at scale, the risk that you run of optimizing for that is that you're not actually feeding the funnel and looking at the longer tail. And you probably always are to some extent. The reality is that if it shows, if Facebook shows an ad to a thousand people and one of them buys, you're warming those thousand people to some extent.

But this is where we see, I think Connor from Hex Cloud was on a podcast actually with Taylor and I listened to this one, and Hex Cloud's a customer of ours, they're awesome. And they asked these questions and so they look at, I don't want to misquote Connor, but I believe what he was saying is that for TV specifically, they were looking at time to first purchase for people who found them on TV, and they saw that that's months. And so in that context, Connor was saying they know Black Friday, cyber Monday is November, so they started spending heavier on TV in August, September, October gearing up for those purchases that they know are going to come through in November because they have the data to show that it takes people months to purchase. The other thing that we know about asking survey questions is that it's not a hundred percent accurate, and you compare that against Qlik data.

Qlik data is also not a hundred percent accurate. There's problems in every type of data, but it's about understanding the bias of the data. And so the bias of the data in surveys is memory, and that's the thing that impacts most of it. And we've done some studies around accuracy and just looking at the way that people respond. The reality is the vast majority of people try to answer these surveys accurately. And there's ways to help with that too. Don't force 'em to take it, those kinds of things. So we are not so worried about the accuracy. What we're worried about is the memory. And so what we're doing when you ask somebody how did you first hear about us is we're asking them to tell you what they remember as the first touchpoint may not actually be the first touchpoint, but it's the one they remember and that has tremendous, it's the one they remember.

Yes. And so for you, you said Instagram, maybe it was Facebook, maybe it was an article on some website somewhere, but you remember Instagram, and so Instagram had some sort of impact on that purchase. And then what we also know is that people think time is shorter than it actually is. And so there's this idea of I think about something I'll be like, oh yeah, that was last week and it actually was three weeks ago because life is busy and things go fast. And so what we also know to be true is that if somebody tells you, if they say, I discovered your brand and I bought today, that's probably true. They probably remember that they know it was today, not yesterday. If they said it was less than a week, they're probably pretty accurate on that. They say it was less than a month.

Well, it could have actually been two months ago, but they think it was less than a month. If they say it was one to three months, it may have been six months ago, but they thought it was three. And so that time what we actually report to our customers and that the responses that their customers are giving them, we know that the reality is even longer than that. And so that's something that I always try to communicate to brands too is that you're looking at this and you're less than a week bucket. People that say they found your brand and bought in less than a week is probably pretty accurate, but the others are actually going to be a little bit longer. And so it's just about, yeah, surveys are not perfect, but if you understand the bias and the data, then it actually helps you really understand and lean into it more than you would be able to by just saying it's worthless.

Brett:

Yeah, it's so good. And I think we get hung up, and I made a post on LinkedIn about this not long ago where really the obsession about getting accurate attribution is a bit misleading and it is kind of a false aim that should not be your goal. You want data and attribution insights that are actionable that will help you make decisions because it's all going to be flawed and it's all going to be biased, and that's okay, that's just the nature of it. But if you can learn things that give insight and then you make decisions on those insights that make you more money, that's what you want. I love the way you frame that. Yeah, we do often forget what we do or win or whatever, but understanding that it still sheds tremendous insight because yeah, maybe in this case I did see an Instagram ad in an article and maybe I saw a friend wearing the shirt, but I forgot what I remember is Instagram.

And so we should give more credit to Instagram in that case because that's what I remember. So that's accurate. And then knowing the biases towards the way we view timelines also helps. But yeah, I think that the big eyeopener here is I remember seeing data because we report through a lot of Google analytics and Google ad reports and Amazon and things, seeing this report for fairly expensive, relatively speaking, it was like an aftermarket auto part, but it was kind of expensive for the average consumer. And I remember seeing the report that most of the purchases were in seven days and I'm like, I don't buy it. I just don't buy it. I think this is something you would have to see and see again and talk to somebody maybe and research before you bought it. And I really think it was kind of the bias towards click data and recency and cookies dropping off and other things that led to that insight. I would love to have seen that company run surveys because I bet it would've confirmed what you already see that the timeline is much longer.

Jeremiah:

Well, and I think that's one of the things that I don't know that people know about or can start with Google Analytics is that it's session based data. So Google is telling you based on the session data that they have that this took a day or I mean usually if you look at Google Analytics, it's telling you that most your purchases are happening in 48 hours, which is true for some brands, but it's actually very rare. In aggregate, we see about 40% of people saying that they discovered and bought from a brand in less than a week, and 60% say that that journey took longer than a week. And so again, going back to what I was saying earlier about that timeline, that time, the actuality of that timeline gets longer and longer the further away that person is from the actual discovery event. And so I've seen it where a brand has 70% of people buying a day.

That does happen for sure, and that's where it is actually valuable to ask those questions for yourself. You don't know unless you ask, but a lot of times what they're doing in that is it's usually a commodity sort of product. It's usually trendy and it's usually something that has a viral sort of appeal. That's what allows it to be bought in that sort of timeline. And most companies, that is not the reality for your product or your market or you're not following a trend. And so outside of those types of companies, it's pretty rare that most of your people are actually buying less than a day.

Brett:

And I think the point about it being trendy and that can help feed into an impulse purchase because back to what you said before where really the only people that are buying very quickly are those that know your brand and know you, or they're actively shopping, so they've got education. This has been in their mind or at least in the back of their mind for a while that they want a product like yours. Otherwise it doesn't. It just takes more time. It just takes more time than a week.

Jeremiah:

Absolutely, and this is one of the things about Google that I think is really interesting, and I think we're going to see a lot of this with AI soon too. I just was talking to somebody about this yesterday, but with Google, you are in active problem solving mode. And so when you are searching for something on Google, it's because you're trying to solve a problem. If you're trying to solve a problem, you're likely to buy a product or buy some sort of solution to that problem. And so really at that point, you're just looking for the right fit to solve your problem. I think that's really, really compelling about each channel has its advantages and disadvantages. Something like TikTok, even YouTube actually, if you want to split Google search and YouTube is completely the opposite. If I'm on YouTube, sure, show me that ad, but I'm not going to click on your ad and go buy something.

Right now I'm in the middle of watching my sports commentary video or this gaming thing or whatever it is, listening to my favorite podcast. I'm not going to stop what I'm doing. I may not even be looking at it. Sometimes that behavior's pretty common on Google too. And so in that context, it's very different than somebody searching and clicking and buying and we see the data that we see backs that up. If you look at, I haven't published this yet, but I actually will soon. Cool information. We looked at TikTok specifically, so same set of orders that have a survey response of how did you first hear about us? The percentage that are attributed to TikTok by a survey response is five times higher than the first click data, first survey data response data and YouTube is the same as our behavior. And then as you go, those are somebody called me out on this on social, and this is a fair call out that channels are not necessarily high versus low of funnel, and that's true, but there are channels that lend themselves more towards top of funnel versus bottom of funnel.

And so in the context of TikTok, YouTube, connected TV, even those are usually more of a top of funnel orientation. You're usually oftentimes showing your ad to somebody who isn't familiar with your brand. And actually it's even less about that. It's about the intent of the person at the time that they're being shown the ad that actually is really what matters the most. What is the behavior of that person at that moment? And so at that moment they're in entertainment mode and then you look at that versus a channel like a Twitter or Instagram or Meta, I actually think part of this is just META'S algorithms. They've figured out how to get the ad in front of the right person at the right time better than anybody else, but those are, when you look at those, the click and the response are more closely aligned. And then you look at something like Google and it's actually the complete opposite. Google gets a lot more clicks than the responses indicate, and so they all have their advantages and disadvantages. It's just really about understanding the behavior of each and the people that are on each and looking at survey responses and click data in light of that. And that's kind of what we try to educate people on,

Brett:

And this is really good insight that there's no top of funnel medium per se and bottom of funnel medium, right? Users just use platforms. I don't choose to get on TikTok when I'm at the top of the funnel. That's not a thought. I'm just going to consume content, but the mode that someone's in the messaging and kind of the way we view it as marketers does shift. And I love that data from TikTok because yeah, 100% YouTube is in the same boat and we spend millions a month on YouTube for our clients and it's one of our favorite channels, but people don't click that much. We even saw this report that showed that the click-through rates on Facebook ads are more than double what they are on YouTube because I'm not on YouTube to click your ad, I'm on YouTube to watch a specific thing where on Facebook, maybe I'm just kind of hanging out and so I'm more likely to click and explore and wander and things like that.

I know the same is true for TikTok. And so yeah, we can't measure, and I was just on a call the other day with this really nice brand and they're big and they were talking about last click attribution, and I'm like, guys, so let's unpack this a little bit. How can we hold every channel to the same standard? How do we do that? Yeah, one click works great. Then I'm all searching performance max and shopping, which I know that world really well. So if I'm all last clicked and let's stop Facebook and let's stop YouTube, but then you don't grow. You

Jeremiah:

Can make that look really good too. You

Brett:

Can make, I can shine man, and I'm a Google guy, so I can make that look really good. Yeah. But eventually you dry up, so really good stuff. So let's then kind of click into that Black Friday Cyber Monday data. And I know when folks are watching this, it's past Black Friday, so Monday, but it's either in IT or analyzing it the holiday or we're prepping for the next one. So this is still good data. So yeah, what did you guys learn in the correlation on how much people spent around the holidays related to how aware they were of a brand, how long that relationship had been going?

Jeremiah:

Yeah, for sure. So what's really interesting there is that we saw, so we looked at the data for, we looked at a bunch of different things, but what I thought was most compelling was looking at what we call the consideration window. So asking the question, how long did you know about us before placing your first purchase? And then looking at that by average order value. And so for the week of Black Friday, cyber Monday, I want to say it's 225,000 people answered this question during that week. And so looking at their data, so it's statistically significant and we didn't necessarily break down industry that's going to have an impact. There's some things there that the data's going to look a little different for every brand, and this is why it does help to ask this for your brand and understand Hex CLA looks different than Ali Pop as an example of one of our other customers we work with, right? It's just different. One of 'em is a thousand dollars cookware set and the other one is a, I don't know, I think it's like 35 or 40 bucks to buy a case of soda off of a website. So it's just different. Ali Pop

Brett:

Is, it's the gut healthy soda, right? Or whatever. It's got some probiotics and stuff in

Jeremiah:

It. Yeah, exactly. So it's just different and consideration windows are different. And so what we saw is that the people who said that they knew about a brand for less than a day had basically about a 25% lower average order value than the average of all people who bought for Black Friday Cyber Monday. And then it climbs up pretty well from there. But basically what you see is that from the lowest A OV is that less than a day, second lowest is less than a week, then you got less than a month, it just trickles down. And basically once you get to call it three plus months, there's really no meaningful difference in a OV. And actually honestly from one month plus there wasn't a whole lot of difference. It's really that less than a month bucket. But what's interesting about that is that your, and this is to be clear, this is first time buyers, which is really cool data too.

So it's people that have bought from your website for the first time and how long they knew about your brand. Those people who had a longer relationship with the brands were more likely to spend a larger amount of money, which I think is really interesting data. There was that there was also just the total percentage breakdown, largest bucket of buyers was people who knew about the brand for one to three months and the second largest, and they're almost equal, was people who knew about the brand for less than a day. But when you look at all of it, the bucket that contributed the highest amount of total revenue was people who knew about a brand for one to three months. And so I think that's just really compelling and it makes, if you think about consumer behavior, again, it makes sense. Let's say I find something really cool in September and I'm thinking about it for myself or as a gift for someone else, I might wait to buy that until November because I know that it's likely going to be on sale. I'm actually doing this right now with a mattress. I need a new mattress. I'm not buying it right now. I've wanted to buy it for the last couple of weeks.

Brett:

Are you going memory foam? Are you going high tech adjustable cooling those things, or what are you thinking here? I'm just interested.

Jeremiah:

I don't know. So I actually haven't figured out exactly which one yet, but I know that we're making our decision over the next week or so and then we're going to look to buy in November and we maybe won't actually buy too. That's the other thing is there will be if we decide the price isn't right, and turns out we actually swapped out our mattress with another one that we had from our guest room and it's a few days ago, and we're both sleeping way better. So we might just stick with that. You're

Brett:

Like, maybe this is good, maybe this is enough,

Jeremiah:

Maybe this is fine. But regardless, we're doing our research now. We are looking into all of this now, but we're definitely not buying before Black Friday. That's when we're going to buy. And so that is normal behavior for this time of year. And so you're actually, you're just prepping people. That's the downside of something like a Black Friday is one of the things we don't really know for sure is how much of the demand are we just delaying and then discounting as an entire industry. That's hard to say, but I do think that that's an angle we didn't look at with this research, but we actually should.

Brett:

We've trained people to wait for Black Friday, cyber Monday. It's not going to change. It's ingrained in our minds, our behavior as consumers who will keep doing it. But what's so interesting is looking at those two major categories of people that spent money on Black Friday cyber Monday for first time customers, it was about equal number of people that had known about it. You said less than a day or less than seven days. What was that first

Jeremiah:

Bucket? Yeah, reported less than a day versus reporting one to three months,

Brett:

One to three months, but the one to three month category produced more revenue, more valuable customers, higher A OV and then would likely lead to, I'm assuming, and I'm guessing you didn't really break this down, but probably better and other things like that.

Jeremiah:

And that's actually a good follow-up research on this too. And I actually was just thinking about this morning, I need to talk to a couple of brands we work with and say, Hey, let's study the LTV of your Black Friday Cyber Monday customers based on how long they knew about your brand. I think that's pretty compelling. But yeah, that's not something we have data on right now. And I think it's really interesting, and this is off the top of my head, so it may not be exactly accurate, but I want to say that one to three month bucket was about 35% more revenue than less than a decade and total significant.

Brett:

I think when you understand that, then you're willing to make the right decisions that feed overall profitability and healthy revenue and good customer acquisition where if we get too obsessed with the one day click, we may be tempted to go down a path we shouldn't go down. Where if we realize that a little bit of cultivation of that one to three months actually leads to higher AOVs and probably more valuable customers, it at least shifts the perspective. It shifts our patients for sure it, but it's likely going to shift our media mix just a little bit and may even shift our discounting approach and several other things, but we got to see this data to be able to have that

Jeremiah:

Insight. Yeah, absolutely. And what I hope with sharing these kinds of things too is that a marketer can go to their, especially with the brands we're working with that are say 50 million a year plus in revenue, you got your marketing team, you got your finance team, and they don't always agree on how you should be spending the money. And so I'm always hopeful a marketer can go to the finance union and say like, Hey, check this out. There is an impact in feeding this. You're still making a bet at the end of the day. Maybe it doesn't pay out the way that you expected it to, but usually it helps in being able to make those kinds of betts when you have that kind of data to be able to show.

Brett:

For sure. You also brought up questions around CRO or conversion rate optimization, and I do think this is something that brands are going to continue to lean more into, especially as they grow and especially as the economy remains uncertain or we get into a recession or other difficulties, then we know we got to get the most out of every opportunity we create, every person we get to visit the site, we got to get more from them. Ideally, what are some of your favorite questions or insights from CRO related

Jeremiah:

Questions? So there's kind of a couple different categories of insight that I see come out of there. There's really three, there's the obvious. So you see things like price, so I'll use Ali Pop as an example. Somebody will buying, I think it's like $35 for a 12 pack that's significantly more expensive than a 12 pack of Pepsi off the shelf at Safeway. So when they see somebody, if a brand like that, I actually don't even know what they asked those questions, but in a context like that, a brand will look and they see people saying price was a reason that they almost didn't buy. That makes sense. So there's the obvious category and most of what you see is going to come through as obvious. And then you've got the technology problem category, which I think is really interesting. I see things like your Affirm and I clicked to pay with Affirm and then I couldn't get back and I decided I didn't want to pay in four installments and I couldn't find a way to get back to only pay one off.

So that in a single response maybe doesn't make you change your behavior. When you start to see patterns and things like that, then you look at it and say, okay, people are having problems with navigation or people are having problems with a specific tool we're using, we should make some changes here. So that's sort of the technology side. And then the last piece is the messaging side of things, and I think that's probably the most, it's the one that takes the most research and understanding, but it's also probably the most impactful one. And looking at what is it about your, are people confused about the value propositions? Are they confused about why your product is compelling versus other products in the market? Those kinds of questions I think are probably where the greatest value comes in, or not questions, but those kinds of responses that you see come through are where the greatest value comes in my opinion.

But again, it just takes a little bit more dissecting understanding. One thing that can be great is just throw that into something like chat GBT and just have it help you analyze it, ask chat GBT questions with that data. And we see some really cool stuff with that. So hopefully that answered the question. But yeah, from a CRO side, that's the three categories I look for. And then obviously you can have pretty open-ended questions to get that data, but you can also start to dive deeper into specifics around that if you feel the need to.

Brett:

And you can have follow-up questions too, right? Ask an open-ended question or ask a relatively vague question, then have some follow-ups then based on that answer.

Jeremiah:

Yeah, exactly. You can do text base is a little bit harder. You basically are searching for a keyword and then asking a question based on the keyword, but that's possible. And then starting it off with a, we actually do this a lot with abandoned cart surveys where we'll ask a question, just ask somebody, Hey, is there a reason you didn't buy today? And you give them a few preset options, and that is a really nice one because then you can guide them down a specific path based on what they answer. So you may, one brand we work with, they have to do hazmat shipping, which I think starts at $40 and that's their number one. It's their number one. They're literally selling a $15 product and it's $40 shipping. And so that's the number one issue for them. And they know that's the issue. They communicate it everywhere, but people still have problems with it.

And so what was really interesting for them is they ran an abandoned cart survey. I think they're still doing this, but basically they have that as one of the options of why somebody didn't buy. And then when they click on it, all they do is educate them about why the shipping is the way, and they don't give 'em a discount or anything. They just educate them and then take them back to the website. And that's one thing that you can do with surveys too that I think is really powerful is just find out why somebody isn't buying, find out what it is that's holding them up and then give them an actual solution to their problem. Don't just assume everybody's not buying because the price was too high because that that's only the issue for a fraction of your customers. Yeah,

Brett:

It's so interesting. Sometimes that solution may be offering a discount or offering something to the customer, but sometimes it's not. Maybe it's not really that 40 bucks is a deal breaker. It's that I was not expecting $40 in shipping and that just feels wrong and it will crazy and shocking and it didn't meet my expectations. But if you educate me and show me why you have to do that, why that's required, because it's hazmat or whatever, then maybe I'm like, okay, that's fine. Yeah, now that you explained it, I'll do it. I really want the thing. And 40 bucks isn't a big deal, but it is when my frame of references free shipping or $5 or $10 or something, not 40.

Jeremiah:

And so for that brand specifically, one of the big use cases is gender reveal parties. And so you can go on Amazon, you can find for 15, 20 bucks, you can find a gender reveal smoke bomb, but it's not actually a smoke bomb. It's a powder thing, like a shoot powder in the air. And so that's a good opportunity to be like, Hey, look, this is a real smoke bomb, this is a hazmat, it has to be shipped in a certain way, and there's just nothing I can do about that with my brand. They do a lot of founder forward messaging, which I think is really powerful in that context too. But yeah, that's one of

Brett:

Those environments too where we were doing a gender or a gender reveal, and I don't know if you probably know this about me, Jeremiah, but I've got eight kids, my wife and I have eight kids, which is shocking. A lot of gender reveals. And that's one of those things where usually you invite people and people are there, and so would I be willing to upgrade and of spending 15 bucks, spend 65 if it was really going to make a difference, yeah, that'd be fine. This is a big deal, but I wouldn't do it unless you really educated me. And so that's so powerful about being able to automate that and one, get the answer to why they didn't buy, and then two, either educate or provide some kind of solution. Super smart

Jeremiah:

If that has to go through customer service, they've already bought the thing off of Amazon by the time you get back,

Brett:

Right? Yeah, really good point. So yeah, I think all of those are really great, and I love the use case of using AI to unpack, okay, here's all our results. Let's make sense of this and categorize this and synthesize it and whatnot. But yeah, some of these you're just not going to know unless you ask. And once you ask and get these insights, it's going to trigger all kinds of solutions and ideas in your brain. And so you got to ask, you just got to do it. We are coming up against time, so I want to be mindful of that, respectful of that. What is next for no commerce? And I know some of that may have to be kind of hush hush or closed lip, but what are you excited about?

Jeremiah:

One of the things I really focus on a lot is the problems in our way of solving the problem we're trying to solve. So what are the ways in which we fall short in solving the problem we're trying to solve? And there are a couple of big props using surveys. Number one is you've got a response rate issue. You're never going to get a hundred percent of the people to answer a question. So you've got that issue. You also have the issue of you're limited on collecting data by when you started asking it. So if you want to know about your customers from three years ago and you want to know something specific, even if it's something like demographics, right? It's really hard to go back in time and ask that question. And so there's those. And then the last piece is really it's most brands just don't have the resources internally to be able to put a lot of time and attention into what to ask, how to break down the data, all of those kinds of things.

And so that is really, we've been working on this kind of behind the scenes for over a year now, this new concept called Automated Insights, which is going to be coming out here shortly. By the time this episode's out, it should be available for beta for some of our customers, public beta. It's been in private beta for basically most of this year. So I'm pretty excited about that. The idea is that basically we manage the questions that are run. It's not AI powered. I think there's some pretty big flaws still in ai. And being able to actually, AI doesn't know what to ask and actually have it be meaningful. That's just my honest opinion on that.

Brett:

Yep, totally

Jeremiah:

Agree. So there's nothing wrong with using AI to try to tune questions and do all those things, but we're just not going to go open season on ai. It's just not going to happen in our business. Not anytime soon anyway. But we know based on the data that we have, we have 1.3 million responses a month to how did you first hear about us? That's just one question on our platform in total, we see over 8 million responses a month. And so with all of that insight that we have, we can build a pretty good structured system around collecting data that we can do at scale for brands, and that's really what's coming next. So yeah, I've been keeping it kind of close to the chest. It's still not fully out today, but it should be in a couple of weeks. So I'm excited about that.

Brett:

Automated insights, check it out. And so what are the best ways for people to connect with you? Obviously they can follow you on LinkedIn and I highly recommend that that's how we met, but then how else can they learn more about, no.

Jeremiah:

Yeah, so LinkedIn, myself slash Jeremy Prime, I forget what they all are, but it's just my first last name together. Same with Twitter now X and then no commerce is the same thing. Just K-N-O-C-O-M-M-E-R-C-E. Yeah, so follow me. We also have a bunch of team members in different roles in our company who like to talk about things and share cool findings on LinkedIn and Twitter. So I feel like they're more LinkedIn usually, and I'm more on the Twitter side, so we've got both going on. But yeah, definitely would love to connect with you there. You can send me an email too, just jeremiah@nocommerce.com if you have any questions. I'll be honest, my email is the last thing I'd check every day, so

Brett:

Stick to the socials, be respectful of the inbox. Stick to the socials you get.

Jeremiah:

Yeah, socials and slack is kind of where most of my communication actually happens, and then I get once a day email check, so

Brett:

Yeah, totally get it. Jeremiah primer. Ladies and gentlemen, Jeremiah, this was super fun, very insightful. We'll definitely have to do it again sometime. Really appreciate it. Yeah,

Jeremiah:

Man, really appreciate you. Thanks.

Brett:

Awesome. And as always, thank you for tuning in. We'd love to hear your feedback. What would you like to hear more of on the podcast? And hey, check out no commerce, check out Jeremiah Worth the follow. You got to dig in. I believe this was one of those next phases, next steps of growth for D two C brands is getting these deep customer insights that I think only surveys can unlock. So check it out. And with that, until next time, thank you for listening.

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