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Business Intelligence for eCommerce Made Easy With Mark Miano, Executive VP of Sales at Glew.io

Mark Miano 6:48

So would you mind if I tried to give it a shot to kind of explain this to your use? Your, your

Joshua Chin 6:54

Yeah, for sure. educate me as well.

Mark Miano 6:58

So you know, when there is for everybody, there is going to be a time in your business where you need a single source of truth. It might be a million dollars a year, it might be half a million dollars a year, it might be 20 million. That’s your judgment, in my opinion. It’s $0 a year. But hey, I’m biased, right? I sell reporting and analytics for a living. So let’s be real. But what what is the best kept secret in this space, it is what you said is called ETL, extract, transform and load and not to be picky. But for the technical people out there we do the new version, which is ELT extract, load and transform. Either way, the key word is transforming data. Here’s a couple examples. Let’s say I’m selling on Shopify and Amazon. And I have two values of revenue. Right? I’ve revenue from Shopify, I have revenue from Amazon, you cannot sum those values together. One might include taxes, one might include shipping, one might be in pounds, one might be in dollars. So those two values need to be transformed into a singular structure first, before we have the luxury of calculating your true profit. Another really simple example, where your audience is timezone. Okay. Shopify, is in London timezone. And its subscription partner Recharge, which I think just got evaluated for like $3 billion or something. Yeah, that’s an Eastern timezone. Well, that’s a huge problem when you’re trying to analyze your world when we have a four or five hour difference between the beat when we’re measuring the behavior of your customer. Yeah, I want to take it a step further. Where we really shine is by actually enriching these tables and fields further with data which aren’t available out of API’s. So, for example, for the operations people out there trying to order the right amount of product to sell, we don’t want to over order under order product for obvious reasons. You sell through rates. and sell through rate is a ratio. It’s the amount sold in a time period divided by the amount on hand at the beginning of that time period. Like the last t shirt, in the warehouse was the basically the last t shirt that was in demand by my customer. Basically, what you’re measuring right over the top of that the amount you sold in a time period that lives in Shopify. that denominator, the quantity you had available at the beginning of the time period, that doesn’t live anywhere. It’s the glue system that is proactively archiving and holding the exact quantity Available of every skew every day for you, as a reference point, so we can run that ratio. In fact, one of my very first clients was actually Amazon. But believe it or not, called blink for home, it makes home automation equipment, like a cameras for your doorbell. And, you know, you know, security systems, stuff like that. Well, this guy had a real big pain point, because he was ordering chips, and all kinds of high end electronic equipment from China. And his lead time was constantly changing, it would maybe be 100 days to get a chip, it might bump up to 250 days. And that sell through rate ratio was so important and vital for him, because if he over ordered or under ordered it one bad order would literally put them under. Yeah, it was our system that was able to in budget, provide him that ratio in whatever date range she needed. As things changed. And, you know, the world became more and more unpredictable, which allowed him to actually get acquired by Amazon. So hopefully that answers your question.

Joshua Chin 11:07

Huge. That’s huge. Now let’s, let’s talk a little about no post reporting. What, you know, you look at a ton of accountants, and you look at a ton of data over the 12 years that you’ve been in SAS. Now, what are some of the first couple of KPIs or metrics that you look at, or a brand that just installed Glew, for example?

Mark Miano 11:31

Absolutely. So there’s going to be, I’ll call the three layers that you’ll use, at least in the first 100 days, approaching your data, the first layer is profitability. I mean, that’s normally the goal is to maximize profitability, and it’s normally not being measured. And when you’re looking at your dashboards, well, we want to repeat what makes us most profitable and stop what is losing this month. So that will be the first thing. I’m talking about profitability at a company level, at a sales channel level, like POS marketplaces and DTC I’m talking add channel level, at a campaign level and at a customer level, lifetime value minus customer acquisition costs. Right? After we cover that, we’re then going to look into customer behavior. And that really is identifying, first of all, especially on customer segmentation, it’s very quickly identifying what characteristics do the best customer share? Where do they live, what channels first campaigns first, they buy their average order value that stuff, we also want to understand what characteristics to the worst customer share, I think all of your audience members can relate that you don’t have all the time in the world. So we have to discontinue doing in order to replace it with what we want to repeat or, or augment a day to day after we have some sort of game plan wrapping our hands around the behavior of the customer, then we move into operations. So every company has a limited amount of physical capital in the flow that Fitzpatrick through the company needs to be managed very carefully. And then usually, from there things start splintering off into more niche type of company specific KPIs like loyalty programs, or scripted data or stuff like that.

Joshua Chin 13:38

Huh, got it. I have a very specific question. And I guess a use case in this instance. Shout out to Rick, Rick Kostik, from 100%pure.com. I’ve had it on him on on the show. And one of the problems that we talked about, that he was facing at his business was around product life cycles. And knowing when to end a product and announce its end of life is essentially now they’ve been around for a long time. So they have a ton of skews and a ton of categories and a ton of different products essentially. So what how can apply? How can business intelligence in general help with a decision like that when on one hand, you want to be moving on to more profitable products, and shifting like resource allocation to more useful means. And on the other hand, you’re having like loyal customers that have been with you for a long time, like years and years buying that same product, relying upon that same product for a very long time. And if you discontinue that product, it will create a ton of dissatisfaction and unhappiness and that very specific second people How do you reconcile problem like that?

Mark Miano 15:04

It’s such a cool question. And it actually folds directly into I think the the bit, specifically for e commerce data and e commerce strategy. It’s it’s actually getting marketing and operations to, to, a lot of times they’re in conflict with each other, and actually getting them to cooperate with each other. And let me give you an example of what I mean for your, for Rick, right? How do I go about making that decision? Well, let’s, let’s understand what the end goal is. The end goal is to attract and keep the best customers, and to avoid and lose the worst customers. sensible couple of KPIs that we can use in order to make that judgement. One of them is the lifetime value of the customers that bias or if that number for this set of skews that you’re talking about is strong and growing, then in my opinion, we should err on the side of keeping that product. Hmm. Second KPI, I think that we’ll talk about is inventory velocity, which is the amount of skews for this specific, this specific skew? The amount of units you sell per day, right? Is that how is that trending? Is it going up? Is it constant? Is it falling super hard. That’s a great understanding of, you know, my opinion forecasting out if more customers are going to be coming that are looking for that product, or if it was a fad, or a trend, and we should sunset it. Now, in addition to I’ll stop there with the KPIs, but from a strategic side, what I would recommend to Rick is, look, if you are if let’s say this thing is not profitable for you, or maybe you’re not even making money on it to the point where you want to waste your time with it. Don’t be afraid to make it worth your while and ask your clients for what you want something like this, hey, customer, I know you really like this product. And I am thinking about discontinuing it. You’re like the only person that’s buying it. If you provide me three new customers in the next year, then I will keep the product. If you don’t, then I’m going to have to discontinue it. Don’t be afraid to ask your customers for something in return for the value that you’re giving them, especially if that value is not profitable for you make it

Joshua Chin 17:50

Gotcha. I like how you think and I tend to err towards the side of let the data guide our decisions. But a lot of the times these decisions are tied to the a lot of emotion as well, can be as simple as discontinuing the product that has been that means a lot to the founder or the team to to deciding to stop servicing a certain segment of customers all together. I think that there is a I guess, a balance between emotions and acknowledging that there’s a softer side to making decisions and the hard data and hard science behind making decisions. Where do you stand on this spectrum? And how do you kind of think about this,

Mark Miano 18:36

the ultimate fallacy that you’re talking about is something called a sunk costs. Nothing is put more businesses under than then being emotionally attached to a sunk cost. And let me define that. A sunk cost is something that you’ve spent in the past that you’ll never get back. And what in the end, then what ends up happening is let’s say Rick, let’s imagine pick on right, but let’s say Bob goes out, and he has this really awesome sheet of patterns, buttoned down shirt. Okay, and this thing was all the rage five years ago, and he went ahead and spent $100,000 wholesale prices to get all these leopard printed shirts. That is a sunk cost. With the worst thing Bob can do is look at his data and see that no one wants to buy leopard printed button down shirts, but continually invest in promoting that product over Facebook or over Klaviyo or whatever, because he’s emotionally attached to his decision that he made to buy those shirts and we’ll do whatever he can to sell it. Whether or not to last now. What Bob should do every single day is look at his data and seeing Hmm, should I go ahead and Just use these as rags to clean my factory, because no one wants them and I can pull more utility out of them. Yeah, it is that part where you needed you need the data to help you pull yourself out of your emotional attachment to these decisions. So that you can, you can do what’s best for you and your employees.

Joshua Chin 20:24

I love that. But I’m going to counter that again with another example. Sure. What if that, I guess that emotional dilemma or sense decision stems from the fact that I know if I pissed off this tiny group of people who are may not necessarily be my most profitable customers, that could result in the ripple effect on my brand, when they speak to their friends and families about my brand. How do you judge something like that? Can you quantify that? Or how do you account for that in a decision like this?

Mark Miano 21:06

You know, quantifying, quantifying your customers. thoughts, instead of actions, very hard to do, right? actions are the order button, the amount of money they spent with you, the clicks, the visits to the site, those things are, are quantifiable because they are measured in quantity. The emotional side of it, and the thoughts are qualitative. It’s really hard to put represent those in a number, usually, or we’re looking at words or explanations or conversations, right? You know, I have a, I have a, I have a client very successful in the CPG. space space. Okay, I got a chance to watch this guy, speak at this conference called the IRC, internet retailers conference for your audience out of America. Right. And, and he was giving this really great presentation. And someone asked them, hey, how did you do such a good job of growing your business? So quick, any advice for an entrepreneur? He was like, Well, you know, every week, what I mess up every, every year, I spend a week of my time as the CEO, identifying my best and worst customers, and literally calling them up on the phone, and asking them, why they like me, why they don’t, what I’m doing great, and what I can do to improve. And he and he, although it was a time suck of his day, that is what gave him the information that he need needed in order to make really tough decisions, which are emotionally charged. out, that’s one way to qualify that qualitative data. Yeah, but you might want to go out with surveys, loyalty programs, you know, it does cost the customer more time in order to provide you the information, which means you need to make it worth your customers while to get the information. But nonetheless, gathering the information is still a date, it needs to be driven by a data driven approach, even though it might be a little bit although that data might not be in spreadsheets.

Joshua Chin 23:23

I love that. And that there reminds me of something and, you know, part of what we do at Chronos is to turn the seemingly unscalable to scalable, and one on one interactions with customers and creating that relationship, creating that at scale with email, SMS and push. So one of the things that we have experimented very recently is in post purchase surveys to type form and then crafting out a much more robust customer profile of their preferences, their need to hear about what they dislike what they like. I’m interested in what that means for a platform like Glew when you have the warehousing capabilities across platforms from Klaviyo from SMS tool, and how do you aggregate data? That is so I guess, qualitative? Or is there a way to make that binary in a way that’s meaningful?

Mark Miano 24:25

So you know, we you know, in order to capture the data and then analyze it, decisions do you have to be made in terms of the questions asked and how you’re gathering it but let me give you like, a good example. So one of my close partners is a gorgeous okay on the like, custom gray two. Yeah. shipmanagement and Zendesk is there too. And there’s a bunch of well think about this. I am a customer service manager, you know, answering tickets and trying to service the customers Mr. Icahn and I got a long queue of take I got some tickets I got to get. But I’m also getting a score every single time a ticket is that one to five stars, one stars crappy five stars is perfect. Yeah. Well, here’s a quote. Here’s a rhetorical question, which I’ll answer right now. What is the star rating that this customer service rep should be aiming for five stars? One star, remember, he’s got 1000 tickets to get through? Hmm. Well, the way that you’re going to approach this is correlating a lifetime value to a star rating. One of my clients found, he’s in the men’s clothing, area, tailoring suits and jackets and stuff, kind of a cool company. That it was actually three stars, three stars three, three out of five, three stars is where the lifetime value of the customer peaked to get four or five stars actually hurt the business, because they were wasting valuable time and not getting paid in return for it, he could actually serve more customers with fewer customer service managers, if he settled just for three stars out of the five. interesting how on earth would he have been able to find that out and maximize the use of his manpower or woman power? And the clients? employees time if you didn’t have the data to help them make that unemotional decision? Hmm.

Joshua Chin 26:38

That’s really interesting. That’s a really cool case study.

Mark Miano 26:43

To tie back to your question, though, with like, the, like the feedback afterwards, something like that, where maybe you have like, hey, like, like, you would have to come up with some type of survey, right? And then you’d probably want to have a ranking of like, hey, what was the open up the box experience? Like? What was the quality of the material? When you opened it up? Feel like like, was your customer experience? Great, from one to five? You’d have to quantify it in some type of numerical fashion in order for us to easily provide you something insightful.

Joshua Chin 27:17

That makes sense. What is some of the more more interesting use cases that you’ve seen? being done? From a bi perspective? for eCommerce?

Mark Miano 27:30

Oh, man? Yeah. So I think the funnest part of one of the more fun parts of what I get to do is not just show you, I’m share with you the data. But one of the unique things that working with here at Glew is we’re specialty system for one industry, eCommerce multichannel. Most analytics tools cannot claim that like Tableau and Looker, they serve everybody from hospital systems to weather channel, Weather Channel, eCommerce, we do just, yeah, what’s so exciting about what we provide you is we don’t just provide you like the visualization or the report. But I can provide you what that visualization or report should look like. What should your lifetime value to customer acquisition cost ratio be? Should your lifetime value look like as it’s trending over time? What should your sell through rate be in specific time intervals?

Joshua Chin 28:33

And what is that? Is that a? Is it kind of like a an aggregate of industry trends and industry averages? Or is it an extrapolation of existing data?

Mark Miano 28:45

It’s, it’s both. So you know, a lot of these you don’t need to do a ton of work? Well, first of all, let me just say, Glew does not sell your data or use your data for any other purpose other than to hold it and maintain it for you. Right. But at the same time, me and my team have been doing this for like 10 years. And I’ve seen the guts of like six or 6500 Shopify accounts, I can easily tell you if your lifetime value curve looks good or not just about the land. So extrapolating it, I mean, sure, you could, but it would be totally unnecessary. Like we were talking very, very basic benchmarks, which are still incredibly valuable for someone who’s new to the whole reporting game.

Joshua Chin 29:32

It’s incredible. Mark some personal questions for you. skiing. Tell me about that. Why is that? Why is that such an obsession? Taking 23 days out of the year? out of state just to ski?

Mark Miano 29:46

Yeah, it’s a great question. No one. No one’s ever asked me that before. I think at first, it’s nostalgia for me. My father and I, I’m very, very close to my parents. And the one thing me and I grew up in New Jersey. The one thing My dad and I always did either one on one or with my sisters, we went skiing as much as we could. So it brings back a lot of like, warm memories on that front. Second part, I think is just like the personal challenge. I mean, don’t get me wrong, I love working in teams. But I’m more of an individual contributor when it comes to the sports area, like I used to play basketball, that was cool. But like, yeah, to be something super dangerous and accomplish it myself without any help, I think is pretty adrenaline rush and kind of scary. Yeah. And the third thing is probably the scenery. So I’m not a big golfer. Whether that’s good or not, and really, the only way for me to see like, some beautiful scenery, if I’m not golfing is going to be through going, going skiing. Very cool.

Joshua Chin 30:48

Do you see any, any parallels drawn to business and I find that I learned a ton from just being out of working. This is I learned 10 from poker, for instance. Any principles that you apply to work from skiing?

Mark Miano 31:03

Yeah, I would say that. I loved risk. So in business, I think we all can agree, especially for your clients who own their own businesses, you’re not going to get that reward, unless you take massive risk. And I have huge respect, I think I get along with I’ve always worked for entrepreneurial companies. This is the second company I’ve worked for. And I’m usually the first person hired. With great risk comes great reward, you’re not gonna be able to look back up that slope and say, I did that unless you had the you know, the, the fortitude and the courage to go and want to do it and no one’s gonna do that for you. Right? When you own your own company, like you Josh like, no one’s if you get sick one day, they’ll say, hey, Josh, you know what, Stan? Like? episode of chicken soup? Like, I’ll go ahead and run your business for you. That’s neurosis. Entrepreneurs work. Yeah. I think that answers your question.

Joshua Chin 32:04

It’s very cool. risk. And is this really interesting because I look at Glew and I think Glew as risk management platform, not necessarily something that allows for more risk taking necessarily with smart I guess, smarter risk, taking smarter risk management. What this reminds me of a, um, the I forget the name of the My First Million podcasts with the hustle, sandbar, and Sean. They interviewed the CTO and Co-founder of HubSpot, Dharmesh Shah. And Dharmesh mentioned that one of his, in a certain period of time, one of his biggest jobs in the company, is because objective is to maintain what he calls boldness in the culture of the company. And he defines boldness as taking risks, are they taking enough risk in the company because they’re huge, massive public company, right? The IPO they’re worth like $25 billion in valuation. So it’s easy to kind of come to a point where Alright, I’m comfortable and not going to take any more risk. I’m just gonna cruise along. And part of his job is to make sure that the people on his team are taking enough risk,

Mark Miano 33:27

which is super interesting thing about just random youth that when you and, and the right risk, right, it’s like, you have to cultivate a culture that encourages the lowest guy on the totem pole, as well as the highest guy on the totem pole to offer the best ideas that they have, without worry of getting an ego damaged without reprimanding them because it might not be the best idea. It’s probably one of the toughest things to do. And that’s really I’m not surprised by HubSpot is the juggernaut that it is with that type of culture for sure.

Joshua Chin 34:07

What are some brands or companies that you personally look up to?

Mark Miano 34:14

Oh, that’s a great, that’s a really great question. Um, specifically in software or just like in general

Joshua Chin 34:24

software or DTC or anything else in general.

Mark Miano 34:29

bVc software, I think, you know, I’m so close with some of them in the DTC world. I think one of my favorite ones is this company called Native Deodorant. militia. Yeah, they think they have such an interesting story when it comes to just approaching a marketplace, which was obviously crowded, right, dude, right. I mean, like, it’s been done for Hundreds of years or whatever, and you have all these, all of these huge companies on their heels, and carved out a new way of doing things through the lens of an experience. I think, I think that falls in line with my mantra of selling things, right. Like I’ve sold things, or analytics for 10 or 12 years, but you can sell anything. And people buy things for three reasons. And I always remind even my clients as they buy things for three reasons. It makes the money. It saves them money. Or it makes them feel good. And that third one, it makes them feel good. We’ll crush the other two, every single time. I think that needed. It doesn’t make them money. It sure doesn’t save them money. Yeah, just the experience of getting the deodorant, opening it up, reading what’s in it, why it’s better than the other Procter and Gamble theater and never smelling it. You know, the feet, the whole experience is why people are willing to pay double for their deodorant, which I think should open up everyone’s eyes to why people are actually buying from, you know, the next time you want to offer a discount. Instead of offering a discount, why don’t you take the extra step to think critically about what you can do for your customer. Besides giving them your profits, there’s so many other things that you can do to grow your business, I think, which is why I like that native brand. So

Joshua Chin 36:34

that’s amazing. Mark, that’s a great place to end our conversation. But if people are interested to connect with you, or get to know Glew, and test it out for themselves, where should they go to,

Mark Miano 36:47

um, you can go to Glew.io that’s our GLew.io. Or you can email me Mark.Mia and as Nancy o @glew.io and really excited to to meet with you and and help you with your business.

Joshua Chin 37:08

Awesome. And as usual, links will be in the show notes. Or you can go to Chronos.agency forward slash podcast to get the show notes. Mark, thank you so much for being on the show.

Mark Miano 37:21

Thanks, Josh.

Thanks for listening to the e commerce profits podcast. We’ll see you again next time and be sure to click subscribe to get notified of future episodes.

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