How to Simplify eCommerce Data Without Drowning in Numbers | Jeff Sauer

If this is your first time with us, lemme, there we go. Sorry. It's just in my seat. Uh, shout out if this is your first time with us. It's great that you are here. Hope you like the show. Hope you get a lot out of it. Uh, and if you are like me, you run your own e-com businesses. I would genuinely love to hear from you. Come check me out on social media. You can find me on LinkedIn to search for Matt Edmondson. Uh, and I will be there.

The link will be in the show notes, uh, which is usually on your podcast app. But come find me, come say hello, tell me your story. We are doing this thing, uh, where we are actively now seeking more founders to come on the show and tell their stories. We've got quite a few lined up, which I'm very excited about. Um, but if you are a founder, if you run your own e-com. Business.

You know, you've got your own store, whether you are running it as a part-time side hustle, whether this is your full-time gig, whether you've turned over a hundred grand, whether you've turned over 10 million, I would love to talk to you. Would love to find out your story, and if you're up for it, come share it on the podcast. I promise. I'll be kind. I'm always kind as you know, if you're a regular to the show. Um, but it would be genuinely great to hear from you. So do get in touch.

Come find me on LinkedIn or you can reach out to me through the website eCommerce podcast.net. There's a little thing on there. Just fill that in, uh, and get in touch. We'd love to hear from you. So that's the plug over with. Let's talk about today's guest, uh, and jump into it, shall we? Jeff Sauer is the Data Whisperer, which I just, Jeff, I dunno if that's your general title, but actually I really like it.

The Data Whisperer of Digital Marketing and Founder of Measure Holding Group, where he has transformed thousands. Of marketers into analytics ninjas through his training and consulting. So we're in the dojo today, ladies and gentlemen, when he's not jet setting around the world as a digital nomad. You can find this top 25 PPC expert spreading the gospel of data-driven marketing at major industry conferences, uh, helping businesses turn numbers into gold. That was a good intro that Jeff.

I like that. How you doing?

And that might sound like the craziest thing you've ever heard, but hopefully by the end of this episode, we all feel the same way. We feel empowered to look at this stuff and turn it into a positive versus just something that doesn't make sense or intimidates you.

Uh, I'm sure someone will let me know, but, um, but there's a, a quote that I've heard that goes, that says something like this. I think it was Einstein that said it. If I was given a problem, I would spend 95% of my time defining the problem and 5% on the solution. Now the percentage may have changed. It'll be different. There is this, this idea, I think of.

When you are faced with a problem devoting a large amount of time to clearly understanding the problem and defining it gives you the majority of the solution that you need. And this is where, for me, data and analytics can actually be your friend, especially in the world of e-commerce, because we measure absolutely everything. Um, well, it seems we measure absolutely everything. Uh. So, yeah, I'm, I'm kind of curious with the whole thing.

You said you've got a passion for it, you've gotta look for it. Was that just from birth? Was this as a result of some cosmic coincidence, or was it because actually something happened and you needed to start getting your head around data?

habits, wasn't it? The seven habits. Yeah. But yeah, so

Mm-hmm. And just making websites for people 'cause I could do that and I. Was decent at it, but not great. Mm-hmm. And, but it was paying the bills. And then finally I made a website for somebody who said, Hey Jeff, thanks for the website, but I don't really think it's, I'm not gonna pay you because I'm not making any money off of it. Oh, wow. Help me make money off this thing so I can pay you for the website. Yeah. And I was like, well, how do you do that?

So I looked into things like paid it, paid ads. Mm-hmm. SEO. Mm-hmm. Um. Finally arrived at this thing called stats, which eventually became analytics. And ultimately that was the only thing I could use that would help me figure out how to make this guy money in order to get paid. And so that this was, yeah, that was sort of the, the whole background was it, is that I couldn't, nothing else was accountable. The only thing that was accountable was looking at the numbers.

I. Seeing what the numbers said and then using the numbers to leverage it so you could get more of the result you were looking for. Yeah. Basically saying, this is positive, this is, this is not working so well. Let's put all of our effort into this. Which, um, even though the Pareto principle has been around forever, the idea of 80 20, um, that was my first introduction to 80 20 being a real thing. Mm-hmm. And being something that was. Shifting that, that actually could make money, right?

Like you can read about something in math and that sounds cool, but when you're actually talking about somebody making money off their website because you 80 20 something, because you had the numbers to point it out, that was magical. And so it was the first time that I really felt accepted and that I belonged in that world because, um, I took this, this technical thing and turned it into something that made somebody money.

And it turns out that I'm a lot better at making people money than I am at being technical. So, um, and so that's where I ended up finding a career. A career. Mm-hmm. Let's just call that a career. And then there's been a lot of phases in the career. I'll, I'll love to get into those, but, um, that's sort of the genesis story of how I became a numbers guy.

Um, even though, and, and I had the, you know, I, I had the education to become a numbers guy, but it was really in the field that got me there.

The reality is that 80 20 is just like a never ending thing. It's everywhere around you at all times. And that is that most of the things you do aren't gonna work. You gotta grow a thick skin in order to understand that. And then the few things that do work. They work extremely well. Mm-hmm. And they, they end up being your payback on payback on everything you do. So it could be a couple skews that perform well for you. Yeah. It could be any one of those things. That's usually how it is now.

We all want things to be different. We all want it to be more sustainable. We want to have a portfolio play. We wanna hedge our bets. And there's, there's merit in doing that. But the reality is that it's still gonna be, uh, a handful of things that, that work really well and analytics just helps you get there faster. Um, and now we're getting better to the point where it can actually predict what's gonna happen. It can predict behaviors.

There's all kinds of things that are happening where if you feed the data into these. Um, machine learning algorithms into this, into the big data Yeah. Pipeline, into meta's algorithms, into, you know, into their, their systems, into Google systems. It's ultimately, they're, they're gonna use all the power to find 80 twenties that you never even dreamed of.

Yeah. That, to find the things that are working and that's, that's ultimately how the entire ecosystem works of advertising and, and analytics now, is that you are constantly feeding your results and then they're constantly trying to get you more of the same results.

Um, Google Analytics you're looking at, whether it's a dashboard from the platform. I'm a big fan of a platform that's done by sweet analytics guy called Oliver Sparks been on the show, um, British guy who's created that problem. Uh, problem created that platform problem and platform. Mm-hmm. Um, so we, we've used that in the past. Um, and still use that today. I guess my, my observation is now because it is so easy to measure everything. We do measure everything.

How do we avoid the overwhelm of data? Because it, it, I sometimes I just look at things and go, I just dunno where to start. Yeah.

And that was pretty much every conversation we had. Um, thankfully that's not really necessary anymore. There's lots of ways to get the code on your site and to track things and, and it's easier to collect data than ever before. Mm-hmm. Now that's, that's positive from a not as intimidating. Yeah. But then it just creates another level of intimidation. Yeah. And that is now data overload. Mm-hmm. Data deluge, just so much of it. Big data, right?

Yeah. Yeah. Um, just so much to choose from that you don't even know what matters anymore. These dashboards have all these indicators. Mm-hmm. Almost like an airplane. Mm-hmm. Plane cockpit as opposed to like the dashboard of a car. Yeah, right. A car dashboard. It's pretty obvious. You need to put gas in the car, you're going, your engine's too hot and you're going too fast. Mm-hmm. Um, an airplane one has, you know, it's, it's much more than that.

And so that's, that's what ends up happening right now. Mm-hmm. Um. The thing is most people aren't driving airplanes. They're not flying airplanes. And, and you know, if you get into e-commerce, uh, you know, just as a, as a business, you don't, you didn't get into this thing to fly airplanes. You got into this thing to, to drive a car, right. To drive from one point to the other. And so one thing is.

Instead of having the airplane dashboard and having everything possible, all these instruments that you don't need realize that you're, that you're in a car and, and, and simplify it. And so, again, I, I hate to say 80 20 all the time, but it ends up usually being about the ratio. Yeah. Um, I always tell people that in Google Analytics, I. You think you need a hundred percent of the data, you'll only ever look at 2010 to 20% of the data you collect.

And, and I'd rather have you spend time configuring that 10 to 20% mm-hmm. To give you exactly what you need as opposed to spending that time trying to understand all 100% of what you have. Yeah. And so the way that we help people with that is we, we actually developed our own framework called the Measurement Marketing Framework at Measure U. And that basically tells you. Ask the right questions about what you want this data to do. What are, what is what, what do I need this thing to tell me?

Mm-hmm. Is it that you're tracking like a product detail page and you wanna see where people drop off and whether they're looking at it or not? Is it that you wanna track your cart and if they're dropping off in the cart, is it like how you, you have to basically figure out what behavior you're trying to track, get to that level. Like what am I trying to solve? Now the good news is that you need analytics in order to know that you have a problem.

Like if you look at your, your card abandonment rate is 98% and you're expecting it to be 60% that all the, the data is telling you where to focus. Yeah. So it's already telling you where to go. Then within that area, there's, if, once you identify the problem, it's actually pretty easy to solve it. Hmm. It is. When you're trying to solve everything, uh, all at once, that, that becomes a problem. So is your problem, your homepage?

Is your problem, your traffic source is your problem. The product detail page is your problem, your cart, is it checkout? Is it all these different things? Ultimately using data will help you to decide where things are. It could be everything. Mm mm Chances are it's not everything. It's usually one thing that's a lowest hanging fruit and, and usually, you know, the analytics tool helps you identify the low hanging fruit for your business. Mm-hmm. Then you just keep on picking it.

I've never actually had to get a ladder out, you know what, you know what I mean? Never have to get a ladder out at all. Yeah. If you just keep on picking that fruit. 'cause the next thing's gonna keep on coming down. Yeah. The next can get ripe at the same time. And so that's where I look at it not being intimidating. Look at it as being empowering for your business.

Um, in your example, the abandoned cart, you know, if, if, if that's going wrong, um, you can then use the data to sort of highlight that from your experience. Um, Jeff, I dare say haven't done this with a fair few people, uh, around the world. In the world of e-commerce. What are some of the common. Issues that you are seeing in the data, sort of some of the common problems that keep coming up over and over again that we could maybe think about starting with those in our own analytics. Yeah.

It's like different, I like the letter I, so it's like, um. You know, did it, and it's, and it, you just basically look at a pa and we're talking about an individual page, but this, this could be your whole site, but it starts with a page. Like, did they get past the, the fold? Mm-hmm. Did they, did they scroll? Did they get 50%? Did they see your call to action button? And then did they take the action you wanted them to do? Right. So we, we basically focus on the different areas. Mm-hmm.

And then we see what percentage of people should have been doing that. Mm-hmm. What percentage of people should get past the full, what percentage of people should be doing that? And it gives you a nice, clean dashboard that tells you whether or not you're in an acceptable range. Mm-hmm. And then it, it automatically tells you, I. Whether that's work, you know, whether you're in the right spot or not. Does that make sense? Yeah, it does. So basically we tell you where the drop off is. Mm-hmm.

It does take some configuration. It's, it's minimal. Um, but that will tell you, okay, here's what your problem is. As opposed to, um, most people don't really know what problem they're trying to solve because they don't either, don't do any configuration at all. And they don't really understand like, Hey, my bounce rate's high. Mm-hmm. That means that I need to fix my bounce rate. Or I have a lot of returning visitors. How do I get more new visitors instead of returning?

Yeah. It's like, that's, that, that's not really a thing. That's just like a default. So moving beyond defaults, but not going too complicated where you're like, say, where you're just, you know, trying to, to create this thing that doesn't, isn't necessary. The ultimate id, the ultimate concept here is that. These are real people mm-hmm. Who are trying to buy your products.

They have real problems and usually if you just understand where they're coming from and, and their, what they went through. You can start to say, oh yeah, this is why a real person didn't complete this. Because I, I failed them on my headline. I didn't have enough, uh, images. The images weren't very good. I had the highest price on the internet. I was not competitive.

Those types of things I, I offer, I put a coupon code in the checkout when, when I actually don't want to offer a coupon code, and that's where they dropped off. So ultimately you're, you're using the data to, to tell you. What you need to pinpoint. Mm-hmm. And then pinpointing it, it goes back to the human element is like, why did this human, why do these humans not do that at the rate that I wanted them to?

'cause it does add really, you know, high quality data to the mix. And also the integration with Google is, is as tight as it gets. Integrating with Search console, integrating with your Google Ads campaigns, integrating with different Google products. There's nothing that has that tight of an integration that can give you that data. Yeah, that can use it to train their advertising algorithms. That can let you do remarketing, that can do all the segmentation. Um, so.

It. If you don't do it, you're missing out a lot. Especially if you are using Google Ads as a primary traffic driver or Google a organic search. Yeah. Which I mean, you're

Uh, my general response to this is they're watching everything anyway. You know, it's, don't really think it's gonna make a massive difference, but you're right, the integrations seem to be getting better and better with Google. Yeah. Uh, in, in, in so many ways across their platforms.

You do own that data and that the reason why is it's the reason why they still are. Able to run in European Union because of that. So like, they basically had to take data privacy really seriously on that product. Yeah. And then you, you actually own the data Google does and they just store it for

If you don't configure it at all, it, it's, it's worthless. Mm-hmm. There's no point in using it. If you don't do some configuration, you can set up, like things like custom events. You can, you can set up e-commerce tracking necessary. Yeah. You can set up your key events, what we used to call conversions, but that would be the same with Adobe. Yeah. Like if you're gonna put Adobe in place and you don't configure it to, to help your store make sense, it's you're gonna.

It's just telling you clickstream data, which clickstream data is not, not really that important. 'cause it doesn't tie to a result. Mm-hmm. It doesn't tie to the language you speak. So that's one. Um, amplitude is getting a lot of, um. People who left GA 360, specifically the, the paid version of Google Analytics have moved over to Amplitude.

They're just like drinking from a fire hose now because a lot of e advanced e-commerce stores did want to have, uh, they, they're not gonna just ride with Google 'cause the initial release just didn't have everything they needed. Mm-hmm. So those are the two that are taking a lot of market share away from, from Google. Well,

And then it's all about your configuration. Now, if you did something that was more aligned with. An e-commerce specific tool. Mm-hmm. You already have a market that, that understands your language. Right. So that, that's, that's the main advantage to it, is that these are these specialty tools. They are geared towards your outcome. Mm-hmm. Versus every outcome for everybody on the internet. And so Google will never be able to compete in that same way as a specialty tool can. Um, yeah. But also.

That integration and that tightness with, with other Google products, it's like, maybe make it one B then maybe it's not your mm-hmm. One A system, but it could be your one B 'cause how are you gonna find that? Otherwise, that's really cool.

They probably spend to marketing advertising maybe 20% of their budget. Mm-hmm. I, I don't really know you, you know that better than me, but let's just say they spend 20%, most companies spend between one and 2% on their analytics tools and the team. Mm-hmm. And so if you're a hundred million dollars store, you'd be putting a million to 2 million into that.

You would definitely have the capacity to pay a hundred thousand dollars for Google Analytics for 360, that version, or the Adobe Analytics, and you'd have money left over to train your team and to get things going. Mm-hmm. If you're a million dollar store. You're talking about maybe $10,000 for that. Mm-hmm. That's where you hire a consultant to tag your site, to do it one time and to build you a dashboard. Mm-hmm. That's pretty much all you can afford at that rate.

And so it really comes down to where you're at. Um, Avinash Kashic, who's a guy that I, I. Followed as I was learning. Um, Occam's razors, his blog, he called it the 10 90 Rule. Mm-hmm. 10% goes to the people or to the tools, 90% to the brains. And so at a hundred thousand dollars for your analytics tool, that would mean that you need to add that million dollar budget. That means that you're in the a hundred million range.

So most of these tools that the paid ones are priced towards 50 plus million dollar entities. Yeah. And so that, and ultimately you can sort of self sortt based on that. Um, and, and I've, I've actually worked with companies that do. A hundred million plus in revenue and they still don't wanna pay Google for their paid tool. They get by on the free one. Um, um, and then that's just, that's just where they, they maybe they think that money should go elsewhere.

Maybe they look at it as an expense where they could put that money into media, which is working for them, or they don't wanna pay for a configuration. But that's, you can self sort based on just the tool price and then that one to 2% of revenue being your entire function for

Mm-hmm. You're probably not even, you're probably going to Upwork and finding somebody to really do it as a one-off, doing it as the install, the technical piece of it. You're not even really able to afford an analyst at that point. You're sort of your own analyst, but you're, you're just getting somebody to get you the, you know, to cut down on the learning curve on time.

Yeah. Um, when you're a million plus, I think you might start looking at, at a, a true analyst or somebody who's giving you recommendations. That person usually pays for themselves because they're, they're telling you the pockets where you have revenue missed opportunities and stuff like that, where your ad spend can be more effective. I. Um, and then, you know, like that we, we do exist for a reason and we do have customers for a reason.

And that's because there's stores, I mean, there's a lot of people who wanna self-educate, right? And the, and what they, what the value we have at Measure U is we have the courses, we have unlimited support. Mm-hmm. We have mentors, people, we have dozens of mentors who have gone through our materials, who have been doing this for five, 10 years and they're ready to help. And so you sort of pay for that community that, that will support you doing these things on your own.

Um. And so that's, that's really where we fit into the puzzle as well.

Gemini is my favorite AI engine. Mm-hmm. I think it's, I think it's the dark horse and I think it's gonna win, um, to a certain extent because of its integration with Google Suite and stuff like that. Yeah. Once that gets plugged into the Google Analytics, and they can do that, that level of, of ANA analysis, it's like game over for, for some of the old way of doing things. Mm-hmm. Um, it's only, it's inevitable like it will happen.

I don't know when, um, it could be that it's already out there, you know? Um, but the reality is that. AI as long as it has access to the data set. Mm-hmm. And as long as it understands the data, it will be really good at finding trends and patterns out of it and giving recommendations. And so that's that, you know, with it, I think a year from now that that'll be pretty much guaranteed to happen. Mm-hmm. I'm actually quite surprised that it hasn't happened already.

Um, I think a lot of it has to do with just the. I don't, I don't wanna get into a technical explanation, but it has to do with excess, excess of the a of the APIs that mm-hmm. Pull the data in. And then just, just integration among teams and then just the extensibility of, of these models. Um, but I, I think that Google having what I think is gonna be the winning. Large language model mm-hmm. In Gemini, and then the best integration, you already see it integrating into G Suite.

It's gonna happen, um, relatively soon. I can only imagine into Google Analytics and into the entire advertising product. And they're doing it already. It's just that, it's not like you can't, you can't, like, it's not your assistant. It's more of like, it's, it's their assistant.

And yeah, Gemini goes away and goes, of course I can. Here it is. And you're like, holy cow. Um, this is quite an extraordinary new feature that, um, you now see on the G Suite with the docs and the spreadsheets and all that sort of stuff. And so I. Um, I, I'd like you, I think it's a bit of a dark horse, but the fact it is so well integrated in Google Yeah. Uh, is the most extraordinary thing. And so yeah.

Whe when it comes out, who knows whether you'll be able to do this, uh, on your analytics. Um, I. But I am, I, I mean, I know that I can, I, I've done it before with large data sets as I've just given it to chat, GPT and gone. Tell me what you think. Um, I, I tend to be a little bit more creative, I suppose, in my prompt engineering. Uh, but in essence that's what you're asking for, isn't it? And it, and it can help you, um, analyze data.

I guess the thing that I'm thinking of here, Jeff, is as a very good friend of mine. Um, Chris Ivers, who's a beautiful lady. Uh, I've just, actually, I need to, I need to get, lemme just make a note, contact Chris. I've not spoke to her for a while. Um, anyway, she has this great phrase that you, you don't know what you don't know.

What you don't know. It's hard to look at the, it is hard to get that information out, if that makes sense. Yeah. I think you've gotta have a sort of, an interesting starting point along the right track. Um, and I guess it'll be, that'll be the interesting thing when you, when AI in effect becomes. Your permanent data analyst, you know? Um, and that can tell you what you don't know. Yeah. I've I've not seen that yet.

And so you can train this thing to just keep on getting better. Mm-hmm. And just keep on challenging it and it will self-heal and self-improve. And so, I mean that, that, that's, you could do that with analysis too. The question is, how big of a pain in the butt is it to get the data out? That's really the problem, is like, you have to get to download it into a flat file and then do this. Mm-hmm. And then get another file.

That, that's the challenge I think right now is just that it's, it's actually getting it. The then what you need to feed it in there. Um, but that again, that that'll be solved relatively quickly. Yeah. And so then never say, yeah, like, we don't know what we don't know. And then also, like, I would never answer a question about whether AI can do something with the word never. It's just when it's, it's when, yeah. Yeah.

of curious, you know, we've. With your course. So let's say I, I do a half a million a year, I think. Well, I'm, I'm gonna go do Jeff's course. I'm gonna figure the whole analytics thing out. Um, I dunno if you've got any ironic, uh, data around this, but I tend to find, and this may be a personal thing, Jeff, uh, where I might go and do that, or I might ask one of the team members to do something like that course, and they go through it, they get it, they understand it.

So we start off strong, right? As in, oh, we found this, this, and this. Let's go fix that. But six months later, everybody's forgotten about everything because there's just the normal run of day-to-day life, um, going on. So how important is it for me as an e-commerce entrepreneur to think about having someone maybe dedicated just to data analysis?

There's, there's way more things to do. Right. And that might be you wearing all those hats, right? Mm-hmm. You might get that point. Usually it's when you get to that. Ten-ish people. Mm-hmm. Like when you have two people in marketing, the third one should be an analyst, I think. Yeah. Um, or you, there's more, there's more value in analyzing inventory, analyzing product choices and stuff like that. But at some point. Literally it'll pay for itself 10 times over by not wasting money on ads.

Mm-hmm. By not wasting money on traffic, however you generate it, that just isn't efficient. That goes away. Having an eye on the site and that customer experience and tying it all together, eventually you lose money by not doing it versus gaining. So, um, a lot of like. I've been in this industry for long enough that it's treated as an expense center for most companies. Mm-hmm. But those who treat it as a profit center and can see the light are the ones who are at the cutting edge.

Yep. They're the ones who are compounding the value of doing this, and they're the ones who are growing versus the people who are like, I don't see the value in investing in that. Or it, you know, it's not worth it. They end up just staying in the same spot because they don't have the data in order to tell them how to improve. They can't see the patterns because they're not addressing it. So it's not an expense center, it's a profit center when yielded properly.

But at some, I mean, if you're too young, too early in this thing, it's just an expense. Yeah. But if you invested in, in our courses, learned our framework, implemented it, and then had somebody who, and you loved it and you made it part of what you're doing, that'll be a reason why you double your revenue year over year.

In the long run, you know?

Then we have done with you, that's the majority of our customers where they're in a community, they're asking questions and that's, that's more geared towards the freelancer slash agencies that you work with and the employees. Not to the business owner. And then we also do done for you services, which is where the, the owner wants the result and they're like, I just wanna pay for the result from experts. That's, that's our done for, for you service. Where, where you can get to that point.

At no point. Really is, would I recommend that the business owner themselves get heavily into the technical pieces of analytics because, um, they have other things to solve usually, and if you can allocate money towards it, that that's something where, where there, there's people who will excel at that. Very rarely does somebody start a e-commerce store and then want to become the master at analytics.

No fair play. Fair play. How important is it? And, and I've heard, and I appreciate just hearing the question in my head. It sounds a little bit silly, but I have heard both sides of the, the, the argument here. I'm curious to see where you sit. How important is air AB testing? So we, that's funny 'cause we. Are now pioneering what we teach as the anti AB testing. And, and I'll be qualified for a second, but, um, no,

let's just leave it there. Yeah. No, sorry, go. Yeah, no, no. Actually you can just leave it there. But, um, AB testing is a, is this whole I idea that. It comes down to just one subject line versus the other one. Image versus the other button. Color yellow versus orange. Mm-hmm. And ultimately that is, that only works if you have so much traffic and so many people coming in that you can see statistical significance in doing that.

Mm-hmm. Versus I mentioned the eyes and the journey, the different, the five different points where you can lose somebody. Mm-hmm. On a page. If you just look at that and you say, okay, normally we lose. 30% of people after the headline are above the fold and you're at, you're losing 60%. What will happen is that'll tell you, this is where you need to focus. If you can't fix this thing, nothing else matters. This is the biggest leak in the funnel. Then all you need to do is go fix that thing.

Now, one way you can fix that is through an AB test. Yeah. Another way to do it is if it's at 60% and you know it's failing, is to do a complete. Overhaul. You don't need to test the old crappy one that's not working. Yeah. You, you know exactly where your problem is. Hmm. So would you ab, if you have like a funnel, like in real life, if you have a funnel and oil's just spitting all over the place, you know, would you ab test whether you should plug that hole or not?

Or would you just plug the hole? I think AB testing is something that buys people time. Yeah. And it makes them feel smart. But ultimately the reality is it only is reserved for traffic, high traffic sites that get that. You know, if you're Best Buy or Google, you can AB test and you can actually have significant weight in a couple days.

If you're a small store, you should just plug that hole and figure out how to, and figure out the fastest way to plug that hole so you can keep on going live another day.

It's almost like a procrastinator's dream because I don't have to make a decision right now. I can put it off and test it against this other thing over here. I'm smart. Put on my lab coat. I'm smart. Yeah. Yeah. Smart procrastination. I, I, I, I've not heard that argument before, so I'm, I'm gonna remember that one Jeff. Um. Right. This is a stage of the, the show where I, uh, ask you for a question for me, Jeff, while I remember. Yeah.

Jeff. If people wanna find out more about the stuff that you are doing, um, you know, maybe about the course, maybe about the done with you service or the done for you service, where's the best place to go?

Lots of free resources. Plus workshops, tons of workshops you can use in order to do, um, there, there are 10, 10 to 20 minute videos that tell you to do a single task. How do you do this thing? And that's our free community. We have a little, we have a, a student lounge in there too. Thousands of people are in there asking questions about the different platforms around analytics. So our free community has more value than most paid communities. I can promise you that.

And um, and then if you like that. You'll get on our mailing list and then we'll talk to you about what other offers we have. You can buy individual courses. You can get all of our courses for one lifetime fee, which a lot of people don't do, but you, you know, we have, um, dozens and dozens of courses that you can get for one charge. We also have coaching.

We. Um, through our accelerator program where we'll, we'll actually, um, multiple times a week, about 200 times a year, you can jump on with a live call with one of our mentor experts and instructors to get your question answered. And then, um, we do the done for you service as well. That's not for everybody, not for most, but if you really just want this thing done from the people who invented the frameworks and who know how to do this thing, that's where we can help you out as well.

And so that's a little bit of your background of, of how you can take advantage of what we do at Measure U.

Uh, so Measure U we would of course link to that in the show notes. Um, are you on LinkedIn? Do you do that whole thing or is it just on the website?

Um, and yeah, we always are just talking about the new trends and what's happening, um, with, with your tools and, and how to get the most of it. And then how to think about measurement in general. Mm.

Um, and so the links will be of course, in the show notes on the app as well, which you can get us by scrolling down, which is a beautiful thing. Uh, Jeff, listen, uh, great to meet you, man. Really excited about what you guys are doing. I. Thanks for coming on the show and clearing up a few things, a few questions that I had in my head. Um, but uh, genuinely lovely to meet you. Thanks so much. Yeah, Matt, this is great. Thanks so much for having me. No worries.

Listen, we have to do that huge round of applause thing. Yes. There we go. Yeah. There we go. Uh, not too much, but that, that was enough. Brilliant. That's fantastic. Well, huge thanks again to Jeff for joining me today. Now, be follow, uh, short for be follow. No, no. Just be sure to follow, uh, the e-commerce podcast where you get your, wherever you get your podcast from because we've got some more great conversations lined up. And of course, I don't want you to miss any of them.

And in case no one has told you yet. Day, let me be the first. You are awesome. Yes, you are created. Awesome. It's just a burden you have to bear. Jeff's gotta bear it. I've gotta bear it. You've gotta bear it as well. Now the E-Commerce podcast is produced by Podjunction you can find our entire archive of episodes on your favorite podcast app.

The theme song was written by Josh Edmundson, and as I mentioned the show notes, the access to the newsletter and all that sort of stuff is available on our website. eCommerce podcast.net. But that is it from me. That is it from Jeff. Thank you so much for joining us. Have a fantastic week wherever you are in the world. I will see you next time. Bye for now.