HomeWebinarsHow to Use Lapse Point to Drive Customer Retention

How to Use Lapse Point to Drive Customer Retention

Overview

There are two things an ecommerce business can do to drive sales: acquire new customers, or retain existing ones. Ideally, you're doing a combination of both - but it can be easy to focus on new customer acquisition at the expense of retention. 

In reality? Retaining loyal customers costs way less - and can be much more valuable.

Enter lapse point. Defined as the number of days that can pass before a customer is likely to never make a purchase from you again, lapse point tells you where your customers fall on that timeline - and which ones you need to focus on retaining before they're lost. 

In this webinar, we'll cover everything you need to know about lapse point and how you can use it to boost your retention strategy, including:

  • What is lapse point?
  • How Glew calculates lapse point
  • How you can use lapse point to define customer segments like active, at-risk and lost
  • Retention marketing strategies for those customer segments
  • How to use Glew to understand the value of those segments

Plus, see Mark's slides from the webinar.

Full transcript

Mark Miano: Testing. Testing. One, two, three. Very good. Hi everyone. My name is Mark Miano. I'm our VP of sales and partnerships here at Glew. Very excited to meet everyone for I think, I think it's the fourth, well, fourth or fifth webinar series. Man, they're getting so many, I can't even keep track. We're going to give about 30 to 60 seconds for everyone to attend. I know that some people are breaking out of meetings and such. A couple of things. Number one, for everyone who is a client, um, we're going to be talking about lapse point today. And by the way, if you're not a client too, we'll be talking about lapse point today as well. But just note that this is designed to help you get the most out of your current subscription, but also if you're not a Glew client, the methodologies here are just as important for you.

Mark: If you can get to the data yourself without us, by all means do so. So just to make sure that whether you are Glew client or not, you get the most out of your data. One last thing before we get started too, is we'll be fielding questions, but I will be fielding those questions at the very end. Just because there's so much to get through. This particular webinar should take about 10 to 15 minutes, but we'll, we'll try to save those questions for the end and we'll just give another 30 seconds. What's up Joe? It's a great name. I just named my son Joe. True story. All right, so quick check here. Can you see my screen, everyone? That would probably be helpful, huh? Then you can see my screen. Right? Today we are going to be talking about lapse point, one of the most important, what we call diamond metrics inside the Glew system.

Mark: recording yet

Mark: All right guys. So what lapse point is, is the the amount of time in days that a merchant or store has to upsell it's customer before that customer most likely is not going to come back. Wow, okay. So thinking about that, it's the amount of days that you have to upsell a current customer of yours before that customer most likely isn't going to come back. Wow. How do we get to that data? Well, what we do is we focus on all the customers in your account or in your store that have purchased more than once. And this only applies to your repeat repeat purchasers. What we do is we take the average distance between every repeat purchase for each unique customer that you've had in order to understand what the average distance in days between repeat purchases actually is. Now I could go into the algorithm itself. Maybe, maybe we set up some time to talk about that one on one, but just think of it this way. Come back into the Glew system. I am in Customers, Future Value. Okay, got to share my screen again.

Mark: I'm in Customers, Future Value. And you'll see that we have your customers broken out by the number of orders that they have placed with you. Okay. Now, very specifically, you'll see that there's a zero purchase slice and there's a one purchase slice. We are not going to be taking into account your zero purchase or one purchase customers. They haven't bought more than once from you. There's no way for us to determine what the average distance is between the upsell with these two groups of people. Right? So instead what we're doing is we're focusing on the two, three, four and multiple purchasers and we're, in short, without getting into the algorithm, basically taking the distance in days between these repeat purchases in order to identify this number down here, which is called your lapse point. Why is lapse point important? And let me do this again. I have to share my screen again guys, I'm sorry.

Mark: You can see why lapse point is important. Okay, this is the fun part. I'm not going to switch back and forth too much. Why is this important? Well, timing is so important to ecommerce and multichannel. We don't have the luxury of people walking directly into the brick and mortar store, right? If we're too late to the party, right? We're too cautious when it comes to the upsell? A competitor's going to swoop in and take your next purchase away from that customer. If you're too early. Well, we all know what the unsubscribe button is for. It's for people who are too eager and too early. What's going to happen is you're going to burn your customer because they don't want to get their inbox crowded with things that they're not going to want to see, especially when they're not ready to buy yet. So let's review this for a moment, right?

Mark: Number one, we're focusing on repeat purchasers only in order to provide you a meaningful window of time to upsell your customer base. Two, this is very specific to your particular store. We're not imposing another store's window on you. This is your own data. Number three, your lapse point has the ability to change over time. Now, obviously, if you're selling food, we don't want to see that lapse point move too crazy, right? A lot of times I get asked about statistical significance. Like for example, how often will it change? From experience, if you have six months of data in your system, that lapse point is probably not going to go anywhere. Also, if you have about half million bucks, maybe even less than that, maybe even closer to 100 or 200K - as long as you're in the six figures, that lapse point should also be pretty crystal clear and actionable as well.

Mark: Also note that lapse point is only going to apply to a company whose goal is to get the customer to buy more than once. Right? We've covered this back in a few other webinars, that if you're expecting this one major purchase, well, timing isn't as much of an issue for you relative to some other companies. And the only way we can get to this lapse point is in fact if you have more than one purchase, of course. So let's think of a couple of things, right? Case study one, makeup companies. I can't think of a more time sensitive type of strategy than someone who is selling makeup, because the whole point is, we get the particular customer to run out of makeup only to come back and buy on their own. Case study two, phone cases. Even a phone case company is going to care about lapse point.

Mark: One very big pitfall for a lot of phone case companies is assuming your lapse points like, one or two years. That's not always the case. No pun intended. Case study three, stereo companies, right? You might actually think that this is like, a one big purchase company. Even a stereo company is most likely going to have a lapse point, because you're going to want to buy some of the electronics and some of the peripheral purchases to the main stereo system unit in order to upsell your customers since they might've forgotten to buy a few knick knacks and odds and ends when they got that very high expense, high end, expensive piece of equipment up and running. So I guess what I'm trying to say here guys, just for some context - we're looking for people who have more than one purchase, but this lapse point could apply in many different varieties and ways depending on your business.

Mark: Once we calculate that lapse point, we're going to place a customer into one of three statuses. You can either be an active customer, an at risk customer, or a lost customer. These are mutually exclusive to the customer, meaning John Doe, a unique customer cannot be more than one of these more than one of these statuses at once, right? I can only be active, at risk or lost as I move down the pipeline. The way that we place a customer into one of these statuses is dictated by the length of time it's been since they've purchased from you, right? So for example, active customers, they bought less than 80% of the way through lapse point ago. Or if my lapse point in this case as a clothing company was 85 days, I would have bought 68 or less days ago from you, and I'm going to be treated in a very certain type of way, which I'll get to in a minute. And an at risk customer is over 80% of the way through lapse point, right?

Mark: In this particular case, if my lapse point is 85 days, that would be 69 to 85 days ago since I bought from that that clothing store. Lost customers, quote unquote lost, aren't lost forever. It's a little depressing. It's just what we label it. They are now over the lapse point. They are beyond that optimal window. These are segments that live in Glew. Guys, you'll see them. I would flip back to the tool without sharing my screen again. But the point is these are predefined segments inside the Glew system and you'll find them sprinkled around through the entire product, with this active, at risk and lost customer segment status.

Mark: Let's think about this. I think this is probably the most important slide of the entire demonstration. So let's walk through this very, very slowly. The upsell window, value versus time. I want everyone on this call to know - even I'm in sales, right? I sell something. I sell Glew. Is that this bell curve, this overall shape is going to apply to any sales cycle. Now the actual shape of the curve itself will obviously depend on many different variables in your business, but the overall concept is the same, which is the value versus time constraint on the Y axis. What we have is the value that the customer is experiencing, right? You know, they just took a chance on you and you'll see here, right where the Y and X axis meet, that is when they actually bought the product, right? They just bought it.

Mark: They took a chance on you and they're waiting for that product to arrive in the mail. And what you're going to see is over time, the value that the customer is experiencing from you is going to grow, right? Maybe here they're super excited that they just bought it from you and it's on it's way in the mail, and maybe right here they just get it in the mail and they open it up. Maybe it's a piece of clothing. They open it up and put it on and wear it to dinner and maybe they wear it two or three or four times, but eventually what's going to happen, right is that value is going to peak someplace. I mean, that's called diminishing marginal returns. That's the whole game.

Mark: And when that value peaks is when you're going to have the highest probability to get that customer to buy again, right? Right. When they're the happiest they possibly can be with the product would most likely be when you want to go ahead and ask for another sale.

Mark: However, you're then going to find this red zone, right? This lost customer status, this red zone, this is when that value starts declining. Maybe that piece of clothing got a hole in it or maybe it got stuck in the back of the closet in no man's land. I know my wife has a bunch of clothes that she never wears and that's where this last curve here is. Right now, what you're going to see again, just to slowly walk through this, is there's an active phase where the customer just bought from us and the value's being built. The idea here is we want to build value. We want to give without necessarily asking for anything in return, right? We want to make it the client's idea to buy from us without us having to ask for that sale. Think of a makeup company.

Mark: I come back to that, they're gonna, they're gonna love that makeup so much that they're going to run out of it only to be like, aw man, I have to buy it again only to come back and buy again. We're an at risk customer. They need to be reminded or pushed in the at risk phase, right? We're not going to just push in any old way. We'll talk about strategic pushing in a moment, but here is the last call, right? We need to capitalize where value's highest. And then lost customers is going to be the tougher play, right? Our conversion rate's going to tank pretty hard as we pass this really important lapse point line. By the way, this line right here is in fact lapse point, but that lost status is going to be more of a defense against the unsubscribe button. Note: time kills the probability of the upsell, as you become less and less meaningful and you're taking up less and less headspace inside the client's world or the customer's world at this lost status.

Mark: All right, so let's talk about active customers. Okay? Again, these guys are less than 80% of the way through lapse point. This group of people just bought from you like I had stated before, so please do not ask them to buy again. We want to make it their idea to buy again. So how about this? Let's get them the product as quickly as we can. Let's check in and make sure that their expectations are not just met, but exceeded. Let's maybe show them how to use it more effectively depending on what it is that you're selling. Add value to their life outside of the physical product that you're providing.

Mark: Create emotional bonds and community. That could be showcasing a big influencer that you've invested in. Maybe Dwayne the Rock Johnson showcases your laundry detergent and now's the time to tell them that, I don't know. Build a community around your particular product. I know, for example, I work with a company that sells clothing for wiener dogs. Maybe what we do is we provide a wiener dog thread and everyone with wiener dogs can showcase all the clothes that they're just seeing their wiener dogs dressed up in, right? That would be a good driver, but the whole point is we're not asking for the sale. We're adding value to the customer's life to make it their idea to buy again. For example, I work with a laundry detergent company, okay? In this active phase and this green phase here, they get you the detergent. They make sure that you're happy. They tell you what permanent press means. They show, you know, Kim Kardashian, throwing Tide Pods into the laundry, whatever it might be. That's what we're doing in the active status is building that bond and building trust forever.

Mark: All right. At risk arguably is the most important status in the entire Glew system. We're going to push these people to buy it. Again, I might email them every single day. I might offer them a discount. I don't know what I'm going to do, but I'm going to push the heck out of them for three very specific reasons. Reason number one, you've earned the right to push, right? You haven't asked them to buy yet. You've been building value this whole time and that is why we're cresting in value, is because of the fact that you haven't just let the product speak for itself. You're trying to do whatever you can to build that trust in the active phase, which is why we've earned the right to ask and ask a lot to buy again in this at risk phase.

Mark: The second reason why we do this, let's say I had a first purchase at risk customer and I'm going to flip back here and I want to show you guys this. Okay, first purchase at risk customer. I'm going to Customer List and I'm going to say number of orders equals one. And then I'm gonna say customer status is at risk. So looking right here in Glew, a first purchase at risk customer. The reason why I'm pushing here and asking is not for the second purchase, right? I need the second purchase. But the real reason why I'm doing this isn't the expectation that they buy a third time on their own. Right? I'll give you an example. I work with a company that sells jewelry, she sells gold necklaces. When she sells a gold necklace, she gets you the product, shows the celebrities using it, what outfits to wear with it, et cetera.

Mark: But when her customers are first purchase at risk, she'll then push the customer to buy something for free. The links that make her necklaces longer to wear low cut dress. She'll actually push these people to just pay for shipping and hit the order button to receive a free product. And the reason why she's doing that is not for the second purchase, right? Yeah. She makes some money on shipping, but the reason why she's doing this is for the purpose of building habits inside the psyche of her customer. Think about that. Now the person has pushed the order button twice, not once, and that dramatically increases the probability of this person, of that customer when they do want to buy a real piece of jewelry for a second time to come back to that specific store, because they're so comfortable clicking the order button and they have the confidence that they're going to be happy with that purchase, if that makes sense.

Mark: All right, I'm going to, hey, can you do a quick check? We're good. All right. The third reason is if they pass the lapse point, right? They passed this lapse point right here, which is this red line. Well, they were lost anyway and that's profound. You haven't actually lost a customer. You actually haven't burned a bridge because based on your data, they're not coming back anyway. So we might as well go as hard as we possibly can. Either get them to buy or get them to unsubscribe would be the goal here in the at risk area.

Mark: Now, lost customers, oh man, lost customers. Pretty, pretty sad, right? They are lost now. They're not lost forever. It's just going to be more of a defensive strategy against that unsubscribe button. Right? A lot of people on this call are probably used to running lost campaigns across the entire customer life cycle, which we're not going to do anymore, but this is those one year anniversary campaigns, new product launches, their birthday, any excuse to provide a high profile touchpoint to make it their idea to come back to us in an artful, an artful and tasteful way.

Mark: Great. So just a couple of things to talk about lapse point to button up some loose ends and we'll open up for some questions. The first thing is that this is arguably the most important funnel the upsell strategy. There are three of these funnels, guys. There's the time based funnel, the activity based funnel and the strategic funnel. I have many webinars and these are tools I also encourage you to look at and other parts of the website, but this time based funnel is arguably the most important funnel of the entire pipe. The second thing is that it is possible to operate artificially off of another lapse point. So you can go into Glew store settings and you can actually override your lapse point to a lapse point that you want to operate off of if you don't agree with your true lapse point that we've calculated for you.

Mark: Let me give you an example. I work at a company out in LA that sells perishable foods and when we looked into their system, their lapse point was 30 days. Now, they weren't happy about that and kind of came at me and I was like, hey guys, like this is your data. This isn't me suggesting 30 days, this is your lapse point. And they had to digest that for a moment because their goal as a business was to get people to buy every week. They're a perishable foods company. They deliver milk, eggs, cheeses, things that are perishable. So what they did is, they lowered their lapse point from 30 days to 10 days inside the Glew.io system, which you can do in Glew store settings, lapse point in the left hand navigation bar. But my point is they now operate off of a 10 day lapse point and over time have watched that 30 day actual lapse point fall closer and closer and closer to their goal. I believe they're at right about 14 days now, which is really exciting.

Mark: Okay, the third action point suggestion would be to match up the right customer segment in Glew, in this case, a time based segment with the right product segment. What do I mean by that? So let's take a couple of examples. The most important segment, like I mentioned before, is definitely the at risk segment, right? So you'll see two examples here that I suggested. Maybe the first one.

Mark: Okay. I have overstock products in the back. Maybe I go ahead and discount those products and send directly over to my at risk customers. I activate a group of people that wasn't going to buy, move them back into active status, right? I get rid of product, I was going to discount anyway and I save full price products for full price customers. Or here's that jewelry example I gave you, right? Where maybe we just put a little bait on the hook, just enough for them to pay for shipping in order to build loyalty and to build habits in your client's psyche, just to get them to buy that, hit that order button one more time so that you're the default vendor for whatever it is that you're selling those customers. You'll see maybe new product launches would be great for lost customers, since you want to have a really strong and valuable touch point given that you're now in the lost status and playing defense against the unsubscribe button. And you'll even see here, here's a curve ball for active customers. Don't ask these people to buy, but definitely build value here. Maybe when you're building value, you showcase your highest lifetime value product. If you don't know what that is, please take a look at our other webinars, but maybe we showcase some of the more expensive higher end products in the active customers campaign to make it the client's idea to come back to you, without you having to push them. I'm going to stop there, and we'll open it up for questions if there are any.

Abby Healy: Yeah, we have a couple of good ones. And feel free to keep adding questions. We'll tackle everything you guys have posted so far. First question was actually on this graph, I believe, so that's good. Margaret asked, where is your lapse point on this graph?

Mark: Your lapse point is right here. The lapse point is the difference between the active and risk phase and it's at that point where the customer passes this line, based on your data, they're most likely not going to be coming back. Cool. Great question. I should have labeled that. Thank you Margaret.

Abby: And let us know if that doesn't make sense. George just asked where can we find the lapse point in the Glew app, and he replied that he found it. But that might be a good idea to show for anyone else who might be wondering.

Mark: All right George, you got it. And I'm going to, can you still see? Yup. All right, great. So couple of places you're going to find lapse point, the first is future value and you're going to see we crawl through all the repeat purchases up here and then you'll see the customer status and you'll see the default lapse point calculated here. And then you can switch and look at your active, at risk and lost customers and you can see how your active at risk and lost customers ebb and flow over time. So for example, if I come into the at risk area and I see that it's January and I have a big, big spike in my at risk, well it's cheaper to keep a current customer than to buy a new one. So all things are going to be all hands on deck, are going to be focusing obviously on my at risk customers. Given the big spike here, if you want to override your lapse point, you can. I'm at store settings and you can go to lapse point and you can see right here, you can see I overrode my lapse point of 104 days, but I want to increase the urgency because it makes sense for my business.

Mark: If I come back over here to Customer List, you'll see the status next to each customer. You'll see them as predefined segments in Glew, look active and at risk. And if I click into the customer detail, I'll even get what literally what I just communicated to you. We've annotated in Glew for you so you can see down to the nitty gritty how to take advantage of this really important metric. Cool.

Abby: Cool. Next question from Daniella. Is it possible within Glew to exclude certain items like bundles or bulk items that are designed to have a longer life cycle? When the algorithm calculates what your lapse is.

Mark: It's a great question. And this goes to my stereo example. So we work with a stereo company and for them, their lapse point is - it's a high end stereo company. Their last point is literally, I think it was like 20 days. These are the thousand dollar stereos. So they knew that that 20 day lapse point was not for a second stereo. It was for the wires and all the things that people buy after they made the grandiose purchase to make sure that the stereo works. To answer this person's question, no, there's only one lapse point that lives throughout all of Glew, but you as the owner of your business should be able to understand how to use this lapse point for yourself. So what I mean by that, is that stereo company isn't using the lapse point to sell a second stereo to a customer. It's using that lapse point to understand the window of time it has to upsell its new customer with other gadgets and gizmos that connect to that major purchase. If you want to find that lapse point for every single product and such, we have that capability with Glew Plus, it just requires a little bit more work.

Abby: Cool. Really good question. A couple other quick questions in the chat window, and feel free to keep adding them here. Tim asked, and this is an interesting one. Wouldn't you argue that the customer is happiest soon after the purchase? Not at the pivot point on your chart. The more time that elapses, the less likely the customer is to reorder.

Mark: It's a great question. Um, my screen, am I sharing? So it's a great question and in the beginning of the call you might have heard me say, I know I'm getting a lot in, but this overall curve, right? Like the physical geometric shape of your lapse point curve is going to be very different across different industries. So for this guy's example, maybe for a food company that lapse point is a little dramatic, maybe it goes like this, maybe it's like a big spike, then it crests and then it fizzles out really fast. Or maybe for a stereo company, right? Maybe that stereo company, maybe that's super, super long and shallow as he appreciates the integrity of his Bose system over time. So whatever utility that your customers see, like what's underneath this curve guys, if you're wondering, this is an economics utility curve and for every business, the utility that the customer receives from each unique business is going to vary a great deal in terms of the amount of the utility as well as the time that utility is pulled in.

Mark: Right. Food, like I said before, if I'm selling candy bars, the utility experience from that candy bar is going to be immediate. I eat the candy bar and I'm done. Whereas the utility from my water bottle here, that might be slow and shallow over 10 years because it's the titanium water bottle. So I think it's a very, very insightful curve. Excuse me, an insightful question. I think what might be beneficial is to talk about utility curves. Maybe on a separate webinar and maybe I'll provide a few different bell curves and explain what different utility curves mean to different industries and have some fun with it.

Abby: Yeah, I think that's a really good question. A couple of other questions in here. Sam: Mark mentioned, lapse point is one of the golden trio KPIs. What are the other two?

Mark: Oh, great question. There's actually four. So I'm just going to switch over as I pull up the PowerPoint just because you asked.

Abby: Everyone ignore Mark's really messy desktop.

Mark: So these are the four. Can you see my screen?

Mark: You'll notice it's who, what, where, and when. Okay. And you're going to notice here that on the timing optimization side, we're talking about lapse point and how to operate off of it. But the other three main metrics are going to be customer segments. Like what percentage of your business is coming from certain segments of your customer base. So you know which particular chunks of customers that you can rely on for the upsell and when you have to acquire, when you have to upsell, we have another webinar on that. The second one is the buying order spectrum. What products are used to acquire the right customer? And what products are used to upsell the customer. And the fourth metric is going to be around attribution modeling. So understanding the lifetime value of your advertising strategy is going to be the fourth major metric out of what I call the four cornerstones. Cool.

Abby: Two more great questions in here. Do you have anything outstanding? Feel free to throw it in there now. Margaret asked a really good one, can you create email segments in Klayvio based on these three groups?

Mark: You absolutely can Margaret. And if I am, can you see my screen?

Abby: You can see your face right now.

Mark: No one wants to see my face. You can, Margaret. And it works like this. So I'm in Customer Segments and you'll see my active, at risk and lost segments in this area. When I click on one of these active segments, any segment, frankly, you'll see this sync settings button right here. If you have Klayvio integrated and I click this edit button, there's going to be a light switch that you can toggle on and off. And every night what Glew is going to do is it's going push all of whatever segments you have integrated with Klaviyo, including active at risk and lost, so that you can program and run with all of that intelligently and seamlessly.

Abby: And that's true for MailChimp as well.

Mark: Yeah, MailChimp too. Yeah.

Abby: Last question I'm seeing in here, Tim asks, the suggested lapse point is based on real data from your store, correct?

Mark: That is real data. Again, if I go to Customers, Future Value, that is pulled from your repeat purchasers. Okay. We average out all the distances between every repeat purchase for each unique customer of yours. In order to identify that number of days, you have to get the upsell in there.

Abby: I think that's it for questions. If anybody has any more, feel free to throw them in there quickly.

Mark: Yeah. We'll wait like another couple of seconds.

Mark: I think if I may just give a shout out to the utility curve. That was one of the biggest things I was trying to, you know, there's so many utility curves to pick from that I decided on the bell curve that everyone is so familiar with, on its own. Can you see that? Sorry guys, I'll figure this out next time. You can see it now. Yeah. I think I would suggest to people that, which might not be clear, let's see the value customers experiencing? That's utility, right. How much value am I getting out of a good or service? And if you go back to economics class, back in university, if I shade it in, all the area underneath this bell curve, that would be the amount of utility that my customer is physically receiving from my product or my service. And that utility curve can be all kinds of different things. That's kind of like economics, is visualizing that type of stuff and I just picked the regular old bell curve, to make people feel comfortable introducing this new idea.

Abby: We had two quick last questions come in. Um, maybe three. Tim followed up. What about a lapse point that is based on the individual's cycle rather than an average?

Mark: Like a lapse point for each individual person?

Abby: Yeah, I think.

Mark: I could see, I could see you doing that. Especially if like you have a super high end sale like for like a B2B play or something.

Mark: You're hearing me think. I think we would have to take that offline. I would need more, you know, I'll say this - lapse point is here to provide efficiencies for you. Right. Ecom and multichannel. We're, we're segmenting out the customer as opposed to typically providing such a personalization. Obviously the more personalized we can be, the better. Yeah, and I'm just rambling. That's a great idea. If it were possible, you know, what's, what's the cost benefit analysis I guess? Like what's the marginal return you are going to get on treating each person individually? The same for how expensive that probably going to be. Okay.

Abby: Two last ones. Margaret followed up - if my lapse point is at 37 days, when should I switch from active to at risk?

Mark: Well, that's just 37 times 0.8. Can you do that real fast? That's 37 times 0.8, guys. 29, 29 days. So yeah, again, if I go back up here, okay, this is the way we calculate it. So just take whatever your lapse point is and you're going to multiply that by 0.8, and then the window of time that that gives you is going to lump you into the active, at risk or lost status/

Abby: And this will happen automatically in your customer segments.

Mark: Yeah, it happens automatically.

Mark: And these, some of these answers are also on our FAQ page, like the calculations for our active at risk and lost customers. We have an FAQ for that as well, at glew.io/faqs. One last question I'm seeing here: is the future revenue simply based off order averages?

Mark: Yeah. So your future revenue is, can everyone see my screen? So yeah. So future revenue, actually I'm going to come back here. Oh man. Future revenue. Oh, excuse me. Okay. All right.

Mark: This is a good question guys. So when you're looking at your future, uh, can you see my screen? When you're looking at the future revenue calculation, that's a really awesome calculation and it's surprisingly accurate. What it's gonna do, it's going to take the lifetime value of your store, which is a dynamic number. We're going to divide that number by X, which I'll get into in a moment multiplied by the number of new customers in a specific time based segment. Right? Does that makes sense? The lifetime value of my story divided by X multiplied by the number of new customers in that specific segment. X, what is X? That would be helpful to know. Remember the people that we're talking about in these active at risk and lost statuses have already bought from you. Think about that. They are repeat purchasers. So because of that, what we have to do is we have to dampen down your stores overall LTV with a certain governor in order to make the future revenue left in that time based segment significant or at least statistically significant.

Mark: That governor is going to depend on multiple purchases. How likely, given the amount of customers in your store, and given the amount of second, third, fourth, and multiple purchasers you have, how likely and how often can you expect another purchase will help dictate whatever X is. Now, sadly, guys, I'm not going to tell you what X is because that is our intellectual property, right? That's why we want you to subscribe to Glew.io. But it helps to understand at a high level how we got to such an aggressively accurate ability for you to forecast how much money you can expect out of each one of these time based segment groups. Good. All right guys. It's been a blast. It's always a blast to be speaking with you. I bet it's been really funny watching me say, am I on, am I on? So next time we're going to fix that a little bit more. Abby deserves a shout out. Thank you to our marketing director, Abby. She's always really great and we're looking forward to maybe talking in person and see you on the other side.