Meeting Title: Poolparts <> Brainforge - SKU Next Steps Date: 2025-02-13 Meeting participants: Nicolas Sucari, Daniel Schonfeld, Payas Parab, Bo Yoon
WEBVTT
1 00:01:57.400 ⇒ 00:01:58.260 Daniel Schonfeld: Hello!
2 00:03:34.290 ⇒ 00:03:35.914 Nicolas Sucari: Hey, Dan, how are you?
3 00:03:37.140 ⇒ 00:03:39.029 Daniel Schonfeld: Hey? Guys? Good! How are you.
4 00:03:40.860 ⇒ 00:03:42.480 Nicolas Sucari: Doing good. Yep.
5 00:03:43.410 ⇒ 00:03:46.709 Daniel Schonfeld: Excellent. Are we waiting for anybody else.
6 00:03:48.390 ⇒ 00:03:59.100 Nicolas Sucari: So Bo is here. I don’t know if Ian was gonna join. But yeah, maybe we can go ahead and just start showing what we have. 1st of all, I’m gonna introduce. Bo is joining
7 00:03:59.290 ⇒ 00:04:00.420 Nicolas Sucari: our team.
8 00:04:00.830 ⇒ 00:04:01.280 Daniel Schonfeld: It’s gonna be.
9 00:04:01.280 ⇒ 00:04:10.850 Nicolas Sucari: Taking over all of the analysis. Work ahead with, pay us on on what we are doing for everything for you guys and pull parts. So, yeah, that’s it.
10 00:04:11.200 ⇒ 00:04:12.660 Daniel Schonfeld: Great nice to meet you both.
11 00:04:12.660 ⇒ 00:04:14.070 Bo Yoon: Hi, Dan! Nice to meet you.
12 00:04:14.610 ⇒ 00:04:32.330 Nicolas Sucari: I I’ve been telling him a little bit about pool parts, about everything, what you told us, or what I could remember, and and tell him about the company. But yeah, it will be. I think we will have some other questions regarding these different companies, connections, and that kind of stuff that you can help us also answer today.
13 00:04:32.740 ⇒ 00:04:34.190 Daniel Schonfeld: Sure ask away.
14 00:04:34.190 ⇒ 00:04:34.940 Nicolas Sucari: Yeah.
15 00:04:35.430 ⇒ 00:04:47.520 Nicolas Sucari: okay, so Bo, do you, wanna do you wanna share what we’ve we have on this queue analysis and start the meeting with that, and then, ask Dan all of the questions that we were wondering about all those files.
16 00:04:47.520 ⇒ 00:04:51.220 Bo Yoon: Yeah, sure. Let me share my screen first.st
17 00:04:55.990 ⇒ 00:04:58.480 Bo Yoon: is Pius joining us as well.
18 00:04:59.640 ⇒ 00:05:02.309 Nicolas Sucari: Mature. So let’s go ahead. And yeah.
19 00:05:22.740 ⇒ 00:05:26.050 Nicolas Sucari: Okay, Dan, do you remember what we
20 00:05:26.240 ⇒ 00:05:49.510 Nicolas Sucari: we’ve been doing with the top 20 skews? We got the list from Ian’s files and all the sales details, and what we tried to do is get all of the costs that we have from your file the one you shared with us grab everything and put it here, and also go to the sales. Details from quickbooks that Ian share with us and try to identify the unit cost per for all of those
21 00:05:49.510 ⇒ 00:06:04.099 Nicolas Sucari: skews right? And the only issue is that when we talk to Ian, Ian told us that it was like difficult to have that like skew at the cost at at the skew level, because they sell like a, you know, large quantities right?
22 00:06:04.439 ⇒ 00:06:14.950 Nicolas Sucari: So like they sell like like in bulk. And we try to identify that unit price. And that’s what we have in the blue columns there with the blue header. Okay,
23 00:06:16.360 ⇒ 00:06:31.749 Nicolas Sucari: we based all, all of those costing on the say in the Asia connection sales details, because, we understand that pool parts is buying from Asia, right? So the sales details from Asia should be like pool parts cost right for these queues.
24 00:06:33.240 ⇒ 00:06:38.230 Nicolas Sucari: Excellent. Okay, so that’s like the Intro, Paul, I can let you. Now continue, if you want.
25 00:06:38.650 ⇒ 00:06:49.760 Bo Yoon: Yeah. So from what I understand is that the wholesale price margin of 7%, this column will be the price that you’ll be selling online. Is that correct?
26 00:06:50.260 ⇒ 00:06:50.730 Bo Yoon: Ben.
27 00:06:52.990 ⇒ 00:06:56.719 Daniel Schonfeld: No wholesale price margin.
28 00:06:58.610 ⇒ 00:07:01.329 Daniel Schonfeld: Where’d you get that number from? That’s from me.
29 00:07:02.050 ⇒ 00:07:02.710 Nicolas Sucari: Yeah.
30 00:07:05.580 ⇒ 00:07:14.119 Nicolas Sucari: Do you want to share also? Oh, maybe the sheet that says, or do you know by us, where is the dance file costing in this sheet?
31 00:07:14.120 ⇒ 00:07:17.450 Bo Yoon: Yeah, they’ll they’ll be coming from this sheet here.
32 00:07:18.620 ⇒ 00:07:19.240 Payas Parab: Yeah.
33 00:07:20.160 ⇒ 00:07:21.929 Daniel Schonfeld: All right. Where’d this data come from?
34 00:07:22.600 ⇒ 00:07:26.481 Payas Parab: This is the original spreadsheet that was kind of shared.
35 00:07:26.870 ⇒ 00:07:27.280 Daniel Schonfeld: Front of me.
36 00:07:27.280 ⇒ 00:07:29.169 Payas Parab: Costing stuff. Yeah, from you.
37 00:07:29.710 ⇒ 00:07:34.740 Daniel Schonfeld: Okay, yeah. So that’s the let me think for one second.
38 00:07:38.110 ⇒ 00:07:45.270 Daniel Schonfeld: Alright. So there, there’s a couple of things happening with pool parts to go. And the most important thing is what’s going to be happening going forward.
39 00:07:45.740 ⇒ 00:07:49.120 Daniel Schonfeld: But in the past, Asia connection
40 00:07:49.440 ⇒ 00:07:55.759 Daniel Schonfeld: or blue torrent would buy, always buys the goods. Okay, that’s the company that works with our factories.
41 00:07:55.940 ⇒ 00:08:00.490 Daniel Schonfeld: It buys the goods at an fob price, which is the china price.
42 00:08:00.720 ⇒ 00:08:07.939 Daniel Schonfeld: and then all the tariffs, duty freight, everything else is added in, and the shipping to come up with the landed cost.
43 00:08:08.500 ⇒ 00:08:11.400 Daniel Schonfeld: and then it sells it in the past
44 00:08:11.880 ⇒ 00:08:15.439 Daniel Schonfeld: to Island recreational, which is our retail stores.
45 00:08:15.840 ⇒ 00:08:24.879 Daniel Schonfeld: and in the past, because pool parts to go couldn’t buy in bulk and didn’t know which products to buy in bulk. We bought it off Asia connection, I mean off island recreational.
46 00:08:25.650 ⇒ 00:08:29.380 Daniel Schonfeld: So it went from Asia, buying it from the factory to our retail
47 00:08:29.940 ⇒ 00:08:37.699 Daniel Schonfeld: recreational, and we would buy ones and twos out the back door of their inventory. That’s historically how it would go.
48 00:08:38.200 ⇒ 00:08:41.569 Daniel Schonfeld: and we would buy it off of island
49 00:08:43.750 ⇒ 00:08:47.619 Daniel Schonfeld: at their cost, plus 7%.
50 00:08:47.860 ⇒ 00:08:54.449 Daniel Schonfeld: So essentially, if it’s a pass through in theory, it should be the same thing as us buying it from Asia
51 00:08:54.590 ⇒ 00:08:56.279 Daniel Schonfeld: plus 7%.
52 00:08:56.950 ⇒ 00:09:00.560 Daniel Schonfeld: So I think what you have there is probably pretty accurate.
53 00:09:01.220 ⇒ 00:09:06.410 Daniel Schonfeld: I just don’t know if it’s connected to the landed cost that wholesale price margin.
54 00:09:10.130 ⇒ 00:09:25.859 Nicolas Sucari: We should take a look at that. But if if I hear you right, is you so pull parts? Is buying from island. Rec. Right? So why, in the sales detail from Asia connection, you have, like Island, Rec as as like a customer, and also pull parts to go.
55 00:09:26.000 ⇒ 00:09:27.300 Daniel Schonfeld: Okay, so have both.
56 00:09:27.300 ⇒ 00:09:40.570 Daniel Schonfeld: Right? So historically, we’ve bought from Island Rec, but starting this past year, or in 2024, we started buying direct containers from Asia connection directly without buying it through island
57 00:09:40.890 ⇒ 00:09:43.940 Daniel Schonfeld: for certain goods, including these pumps
58 00:09:45.610 ⇒ 00:09:48.749 Daniel Schonfeld: going forward. That’s gonna going to be the relationship. Also.
59 00:09:49.830 ⇒ 00:10:02.009 Nicolas Sucari: Okay? So we, it’s it’s okay. If we base the price of these queues from the from those latest cost that we are finding from the Asia sales details to pull only to pull parts. Not 2. Island. Rec. Okay.
60 00:10:02.260 ⇒ 00:10:02.850 Daniel Schonfeld: Yeah.
61 00:10:03.430 ⇒ 00:10:07.850 Nicolas Sucari: Okay. So we should look at the at the at the orange one. Then I think.
62 00:10:08.610 ⇒ 00:10:11.139 Daniel Schonfeld: Average or order, quantity, total quantity.
63 00:10:12.040 ⇒ 00:10:28.830 Nicolas Sucari: The orange. The orange one was only when we filter the sales details from Asia connection with the pull parts to go like kind of customer the blue one was pull parts to go and island break, as we were not sure about which one of those we should, we should use. Okay?
64 00:10:33.960 ⇒ 00:10:34.590 Nicolas Sucari: Okay.
65 00:10:35.130 ⇒ 00:10:53.469 Nicolas Sucari: So having having these costs, I mean, this is the cost that Asia connection is selling to pool parts. So you’re saying that with this cost, we need to add the 7%. So that we understand that that is like the sale price that you want for all of these queues, or how do you come up into the sale price for this queues? Then.
66 00:10:54.460 ⇒ 00:11:07.689 Daniel Schonfeld: Okay, so this is from a perspective of Asia connection correct, like the average sales price you’re assuming with Asian, is that just taking into account what Asia sells it internally like to pull parts of our island? Or is that total throughout the business.
67 00:11:09.150 ⇒ 00:11:13.969 Nicolas Sucari: We feel you can. Can you show both the sales detail from Asia connection.
68 00:11:17.612 ⇒ 00:11:18.550 Bo Yoon: This chart here.
69 00:11:18.550 ⇒ 00:11:25.840 Nicolas Sucari: Yeah, yeah, yeah, exactly. So this is the file that we got from from Ian on the sales details from Asia connection.
70 00:11:27.130 ⇒ 00:11:35.349 Nicolas Sucari: we. This is right. Okay, right now, it’s filtered down to one skew. But you, as you see before, like in, I think it’s column B, or, yeah, go to all.
71 00:11:35.840 ⇒ 00:11:43.979 Nicolas Sucari: Yeah, where it says, name, yeah, there we have island Rec, but then we have other one that says, pull parts to go. So maybe you can filter down to 4 parts to go there. Both.
72 00:11:46.880 ⇒ 00:11:48.050 Daniel Schonfeld: Okay. Let’s see.
73 00:11:48.220 ⇒ 00:11:49.109 Nicolas Sucari: Okay, we give you.
74 00:11:49.110 ⇒ 00:11:59.270 Nicolas Sucari: And if you go, yeah. So we have, like all of these, these are these are all the sales from Asia connection to go. So that’s what we understood is that you are buying like these are all the
75 00:11:59.270 ⇒ 00:12:21.409 Nicolas Sucari: the the product that you’re buying directly from Asia connection, and if you go to the right, you have this queue there the description, and then you have the quantity that you’re getting from them like the entire containers, I think, with the sales price. And that’s like an a unit price in terms of the total amount that you’re paying right. But that’s the number that we are using to understand the cost of what you’re buying from Asia connection directly
76 00:12:21.910 ⇒ 00:12:22.799 Nicolas Sucari: for those queue.
77 00:12:23.120 ⇒ 00:12:24.799 Daniel Schonfeld: So that should be accurate. Yes.
78 00:12:25.110 ⇒ 00:12:33.449 Nicolas Sucari: Okay. But that cost we. So for that cost, we need to include also the tariff duty, freight and everything. Or how do you feel the.
79 00:12:33.450 ⇒ 00:12:35.600 Daniel Schonfeld: No, that’s that’s already in there.
80 00:12:36.070 ⇒ 00:12:48.239 Nicolas Sucari: Okay, this is already in. So so tariff duty freight. Everything regarding those costs is what you’re adding to the Asia connection when they buy from the manufacturers. Right.
81 00:12:48.770 ⇒ 00:12:49.510 Daniel Schonfeld: Yep.
82 00:12:50.350 ⇒ 00:13:15.980 Nicolas Sucari: Okay, perfect. So we can stick only with this number. As the cost of what pool party is buying from Asia connection. And up from this number, like, what should what what else should we kind of include into the cost of these products like so that we can like, understand what is like the total cost of the cost of the total cost of goods sold for pool parts?
83 00:13:17.800 ⇒ 00:13:20.460 Nicolas Sucari: Or or is there is nothing else. Maybe there’s nothing else.
84 00:13:20.610 ⇒ 00:13:30.549 Daniel Schonfeld: No, there’s nothing else. As far as us purchasing those goods, if that’s what Asia selling it to us, for that’s a delivered cost to one of our warehouses.
85 00:13:31.700 ⇒ 00:13:36.399 Daniel Schonfeld: I don’t know. I’d have to go through like one item like the best way to check it
86 00:13:36.790 ⇒ 00:13:47.759 Daniel Schonfeld: is to go back to the original like the way that we price stuff on pull parts to go is that original sheet I shared with you on Google Sheets. It was like mask. Not master skew copy.
87 00:13:47.760 ⇒ 00:13:52.320 Nicolas Sucari: Yeah, I heard, yeah. Copy of 2024, your official skew, I think.
88 00:13:52.320 ⇒ 00:14:00.380 Daniel Schonfeld: And when you click on the landed price you could see all the formulas of how I what I use to calculate it as long as it checks. With that
89 00:14:00.550 ⇒ 00:14:01.780 Daniel Schonfeld: you’re good to go.
90 00:14:02.320 ⇒ 00:14:06.459 Daniel Schonfeld: But again, there’s there’s been updated pricing since you probably got this. I’m not sure.
91 00:14:07.650 ⇒ 00:14:15.861 Nicolas Sucari: Yeah, maybe. Because, yeah, the one that we have is from, I think it’s from August 2024. But that’s fine. I mean, maybe we can check
92 00:14:16.470 ⇒ 00:14:22.910 Daniel Schonfeld: Look. The the end goal is to get a master skew list. That’s accurate, not even down at the moment
93 00:14:23.080 ⇒ 00:14:30.050 Daniel Schonfeld: to the cost and all the pricing but more distinct skews.
94 00:14:32.010 ⇒ 00:14:35.189 Daniel Schonfeld: That are active really across the business.
95 00:14:35.550 ⇒ 00:14:41.619 Daniel Schonfeld: and using that list to then fine, tune it to figure out what the true cost is for 2025, really.
96 00:14:42.620 ⇒ 00:15:00.540 Daniel Schonfeld: And then how much we’re charging everyone, because ultimately, right now there’s no rhyme or reason, particularly how my father-in-law takes the cost of an item and then prices it out to, not just internally to pull parts, to go and island, wreck our companies, but to 3rd party companies that buy from us.
97 00:15:00.820 ⇒ 00:15:09.990 Daniel Schonfeld: And so I’d want to get an active skew list and then come up with a percentage for internal costs, or or what Asia is, gonna sell it to
98 00:15:10.230 ⇒ 00:15:25.200 Daniel Schonfeld: pool parts to go or island. Rec, and then another, where we do different percentages for what Asia connection will sell to other 3rd parties based on multiple factors. And so that’s my ultimate goal. With this
99 00:15:26.493 ⇒ 00:15:31.020 Daniel Schonfeld: but obviously, 1st and foremost, we need to have a distinct list of skews.
100 00:15:32.700 ⇒ 00:15:44.649 Daniel Schonfeld: and there’s also, as you guys found, there’s multiple see? Like right there, 1, 1, 37 m heat pump, 1, 37 M. Oh, those are 2 different skews. But the cft 1, 25 right there at the bottom.
101 00:15:45.410 ⇒ 00:15:47.660 Daniel Schonfeld: There’s 3 different right there.
102 00:15:48.910 ⇒ 00:15:49.560 Nicolas Sucari: Yeah.
103 00:15:49.910 ⇒ 00:15:50.350 Daniel Schonfeld: It wouldn’t.
104 00:15:50.350 ⇒ 00:15:51.120 Nicolas Sucari: You go to the right.
105 00:15:51.120 ⇒ 00:15:51.810 Daniel Schonfeld: Good morning!
106 00:15:52.810 ⇒ 00:15:57.729 Nicolas Sucari: No, no, but that’s fine, because this is this is like the sales detail from Asia connection.
107 00:15:58.260 ⇒ 00:16:04.220 Nicolas Sucari: The price is the same as you see those one? This means that they are selling. Yeah, they are selling.
108 00:16:04.220 ⇒ 00:16:04.760 Daniel Schonfeld: Yes.
109 00:16:04.760 ⇒ 00:16:10.819 Nicolas Sucari: 3, 3, or maybe 3 different customers or 3 different orders to you guys. Yeah, but yeah, like, it’s the same. This is the sales.
110 00:16:11.153 ⇒ 00:16:17.830 Daniel Schonfeld: Okay. But do you feel confident you’ve whittled it down to a distinct list of skews, and we can dedupe.
111 00:16:18.570 ⇒ 00:16:24.270 Nicolas Sucari: We have that in the if you go to skew table with price above, yeah.
112 00:16:25.360 ⇒ 00:16:26.730 Nicolas Sucari: and go to the left.
113 00:16:26.890 ⇒ 00:16:53.120 Nicolas Sucari: This is what we originally did we get all of the Asia list skew. We match that with the platform skew that we get from only pull parts. Go information from Amazon ship station, Walmart. Shopify right? And and we have that clean skew list that that includes everything from pull parts, and every if you scroll down a lot, you’ll see that there are, only there are some that only has, like Asia list, skew and not a platform skew on their side.
114 00:16:53.450 ⇒ 00:17:08.200 Nicolas Sucari: You see, like all from a list here. And then we have, like a lot of different skews from Asia connection files that we’re not including here. But we can add also to if you want and have, like this unique list of skews and check the latest orders from
115 00:17:08.510 ⇒ 00:17:34.170 Nicolas Sucari: like that. And that should be my question like if we got all the the disks from Asia connection from pull parts, different tools in one list, which last order date. Should we look at the last order days from customers from pool parts that are buying in shopify Amazon or Walmart, or the latest orders that Asia connection is selling to anyone else independently. If it is, pull parts island Rec, and other other customers.
116 00:17:34.350 ⇒ 00:17:41.780 Daniel Schonfeld: Yeah, it’s gonna be too hard to look at all the orders across pool parts to go. So I would say, 2 pool parts to go from Asia to pool parts, or Asia to island.
117 00:17:41.780 ⇒ 00:17:45.329 Daniel Schonfeld: You said right 3rd party. Any Asia sales I would go by.
118 00:17:46.280 ⇒ 00:17:49.780 Nicolas Sucari: Okay, yeah, we can take a look at that. What do you think? I asked.
119 00:17:50.010 ⇒ 00:17:53.284 Daniel Schonfeld: Yeah, it’s gonna be too hard to go through every pool parts to go order.
120 00:17:56.680 ⇒ 00:17:57.620 Daniel Schonfeld: Okay.
121 00:17:58.960 ⇒ 00:18:05.810 Bo Yoon: So instead of taking the average price, it will be better to just look at the the latest invoice
122 00:18:06.480 ⇒ 00:18:10.010 Bo Yoon: that is going to pull ports to go, or island.
123 00:18:10.310 ⇒ 00:18:16.779 Daniel Schonfeld: The latest effort. What are you trying to accomplish, though, with get a universal cost? What do you? What’s what’s the goal of what you’re trying to do.
124 00:18:17.157 ⇒ 00:18:22.070 Bo Yoon: To get the cost. That purpose to go is paying to Asia.
125 00:18:22.280 ⇒ 00:18:23.260 Bo Yoon: Yes, sir.
126 00:18:23.520 ⇒ 00:18:27.079 Daniel Schonfeld: Yeah, I would. I would actually just go by probably last.
127 00:18:27.710 ⇒ 00:18:28.569 Bo Yoon: The last.
128 00:18:28.820 ⇒ 00:18:35.799 Daniel Schonfeld: Yeah. But I mean, when we actually use these tables to do in the future to do proper reporting, it really should be
129 00:18:36.020 ⇒ 00:18:40.470 Daniel Schonfeld: well, they’re not serialized so you wouldn’t know which batch it came from. But yeah, I guess an average.
130 00:18:41.510 ⇒ 00:18:45.789 Nicolas Sucari: Yeah, that’s that’s the problem. Because we don’t have like at the skill level. So yeah.
131 00:18:45.790 ⇒ 00:18:48.099 Daniel Schonfeld: Yeah, that’s fine. An average is fine.
132 00:18:50.520 ⇒ 00:19:00.049 Nicolas Sucari: Okay? Or maybe we can, we can look at the data. And if the average change so much or some skew change the order, the order price change across time. We we can. Yeah, just discuss that.
133 00:19:00.170 ⇒ 00:19:04.140 Nicolas Sucari: Okay, okay, yeah.
134 00:19:04.200 ⇒ 00:19:27.839 Nicolas Sucari: great what else? So we we’re gonna try, get all of that information into one, into the master list. Queue. Get the cogs that we are getting from the Asia sales details to customers, and try to come up with that master list with that column, with all of the costs for all of the skews. Not only the top 20, I think it’s a it’s a just a formula that we can replicate for everything that we have there.
135 00:19:28.127 ⇒ 00:19:51.710 Nicolas Sucari: And yeah, we will share that to you, Dan, so that you can take a look with adding the latest order, or the latest sale from Asia about that skew so that you can check and decide which ones are active or inactive. I in the past exercise that we did, we just aim for if if it was, if there wasn’t an order in the previous year that was active. If it was longer than that, it was inactive.
136 00:19:52.418 ⇒ 00:19:55.639 Nicolas Sucari: We can. Can we still use that like logic?
137 00:19:57.730 ⇒ 00:19:59.350 Daniel Schonfeld: Yeah, I think so.
138 00:19:59.490 ⇒ 00:20:04.480 Daniel Schonfeld: Are you are. Is the plan to get this out of Google sheets and into like real or one of those.
139 00:20:05.480 ⇒ 00:20:07.060 Nicolas Sucari: Yeah, we can do that. Yeah.
140 00:20:07.180 ⇒ 00:20:21.369 Nicolas Sucari: I mean, ideally. First, st we we understand, like all of the logic with the costs, and that and and all of the formulas that we have here. Once that is ready, we can create a pro, a process to have that in Snowflake, and ultimately in real yep.
141 00:20:22.030 ⇒ 00:20:31.130 Daniel Schonfeld: Yeah, eventually what I’d like to. I’ll come back to you, probably in the next month or 2 and say, I’d like to see like. Here’s an ideal world I’d like to see on the skew level
142 00:20:31.810 ⇒ 00:20:39.780 Daniel Schonfeld: what margin did Asia connection make across all 3rd parties, not island or pool parts to go take those out
143 00:20:40.460 ⇒ 00:20:44.739 Daniel Schonfeld: on a skew level. How much margin did we make per customer
144 00:20:45.180 ⇒ 00:20:51.440 Daniel Schonfeld: on a skew level? And so what I’m trying to do is come up with a a bottom
145 00:20:51.580 ⇒ 00:20:59.149 Daniel Schonfeld: on a skew level of the margin that we need or must make, and then start to go from there, where I can pick a skew.
146 00:20:59.460 ⇒ 00:21:01.830 Daniel Schonfeld: I can see all the 3rd parties.
147 00:21:02.000 ⇒ 00:21:12.230 Daniel Schonfeld: and I can say, here’s the average of what we made across the board. If you blend it all those together, and then I can pick for each one how much I want to charge them for the next year.
148 00:21:12.770 ⇒ 00:21:18.140 Daniel Schonfeld: and then it’ll and I’ll keep going across and do that exercise on every skew
149 00:21:18.270 ⇒ 00:21:22.020 Daniel Schonfeld: that way. When we send them pricing one day in the future
150 00:21:22.470 ⇒ 00:21:29.179 Daniel Schonfeld: it’ll automatically know exactly how much we should charge them based on the predetermined margin percentages.
151 00:21:29.720 ⇒ 00:21:31.050 Daniel Schonfeld: Does that make sense.
152 00:21:32.800 ⇒ 00:21:46.970 Nicolas Sucari: It makes sense at some point like trying to identify all of the margins. But when you’re talking about what is the Asia margin? So you’re trying to understand also, like, at what cost is Asia buying from the manufacturers, or or I’m misunderstanding.
153 00:21:47.130 ⇒ 00:21:53.520 Daniel Schonfeld: Yup, the the Delta, the difference between what Asia buys the product for all the costs
154 00:21:53.670 ⇒ 00:21:55.459 Daniel Schonfeld: it takes to land it.
155 00:21:55.850 ⇒ 00:21:56.260 Nicolas Sucari: Yeah.
156 00:21:56.260 ⇒ 00:21:56.950 Daniel Schonfeld: And then.
157 00:21:56.950 ⇒ 00:21:58.230 Nicolas Sucari: And how, and what they.
158 00:21:58.230 ⇒ 00:22:07.279 Daniel Schonfeld: What’s the difference between that and what we’re charging the customer for that skew. And there’s going to be a percentage anywhere. I’m assuming right now. It’s probably around 10 to 20%.
159 00:22:07.450 ⇒ 00:22:16.470 Daniel Schonfeld: But I need to know that blended number across all 3rd parties. And then I’m going to go pick per customer how much I really want to charge them
160 00:22:16.780 ⇒ 00:22:18.220 Daniel Schonfeld: on a skew level.
161 00:22:18.540 ⇒ 00:22:26.250 Daniel Schonfeld: And then, after that, I should be able to run a query and say, like I saw company eagles whatever, when you, when you cleared out all the filters for name
162 00:22:27.420 ⇒ 00:22:31.750 Daniel Schonfeld: I saw there were 3rd parties in there, I would be able to
163 00:22:31.880 ⇒ 00:22:41.669 Daniel Schonfeld: very quickly figure out exactly what their costing should be when they ask me, Hey, can you send me a price list for 2025, or 26,
164 00:22:42.320 ⇒ 00:22:47.059 Daniel Schonfeld: it’ll know, because I already predetermined it in the table, what my margin should be on the product.
165 00:22:47.570 ⇒ 00:22:58.019 Daniel Schonfeld: So that way in the future all we have to do is add the new cost of the product. Let’s say it goes up 10%. Or there’s a tariff just went up on China by 10%. I’ll go into the tariff column
166 00:22:58.130 ⇒ 00:23:07.669 Daniel Schonfeld: up it by 10%. But all the numbers should spit out differently based on the predetermined margin that I’ve I’ve input for each customer per skew.
167 00:23:07.920 ⇒ 00:23:11.450 Daniel Schonfeld: I know that’s a garbled mess, I just said, but do you do you follow what I’m saying?
168 00:23:12.430 ⇒ 00:23:15.009 Nicolas Sucari: I think. Yes, I think I followed you guys.
169 00:23:15.522 ⇒ 00:23:19.647 Payas Parab: I think I might need some clarification. There. It’s a broke my brain a little bit. There.
170 00:23:19.890 ⇒ 00:23:20.580 Daniel Schonfeld: Sorry.
171 00:23:20.580 ⇒ 00:23:21.200 Payas Parab: No, it’s okay.
172 00:23:22.930 ⇒ 00:23:23.410 Payas Parab: So
173 00:23:23.889 ⇒ 00:23:33.960 Payas Parab: yes, like Asia connection from the costing we know. And when you say 3rd parties, what are you referring to there. It’s like it’s like all the people like the like customs, and like shipping partners.
174 00:23:33.960 ⇒ 00:23:34.739 Daniel Schonfeld: No, no.
175 00:23:34.740 ⇒ 00:23:37.219 Payas Parab: Okay, like other clients.
176 00:23:37.430 ⇒ 00:23:40.319 Daniel Schonfeld: Yeah, customers who buy product from us.
177 00:23:40.320 ⇒ 00:23:41.260 Payas Parab: Got it. Got it.
178 00:23:43.114 ⇒ 00:23:52.079 Nicolas Sucari: The ones that are done. List that are not full parts or island. Rec. That those all of them are like 3rd parties, the one that.
179 00:23:52.080 ⇒ 00:24:05.639 Daniel Schonfeld: You have 2 sides of this. You have, like the fixed and variable cost of a of a skew. That’s not gonna change it. It’ll change. But the price we’re gonna pay for a skew for a given year is not gonna change. We’re gonna pay X amount for certain pump.
180 00:24:06.240 ⇒ 00:24:13.340 Daniel Schonfeld: And all those little things to get it. Here are the things that are going to change a bit. The tariffs might go up, the shipping might go up for freight.
181 00:24:13.890 ⇒ 00:24:18.090 Daniel Schonfeld: The duty will probably stay the same. All those things.
182 00:24:18.200 ⇒ 00:24:19.919 Daniel Schonfeld: I’d love to have a table.
183 00:24:20.710 ⇒ 00:24:22.270 Daniel Schonfeld: Where I put in the cost.
184 00:24:22.420 ⇒ 00:24:24.904 Daniel Schonfeld: We put in all the tariffs all that stuff,
185 00:24:25.580 ⇒ 00:24:29.900 Daniel Schonfeld: rate, etc, which is also going to be a bit dynamic, but we can get an idea.
186 00:24:30.080 ⇒ 00:24:50.149 Daniel Schonfeld: and we can put in a set one if we want for freight what it costs per cubic foot, and then you have a number. It spits out per skew at the end of the day to land that product in the United States from China. When we buy that skew there’s a certain number to get it here. That’s not gonna doesn’t affect what people pay for it. It just affects what we
187 00:24:50.500 ⇒ 00:24:52.120 Daniel Schonfeld: we pay to get it here.
188 00:24:52.370 ⇒ 00:24:52.850 Payas Parab: Yep.
189 00:24:52.850 ⇒ 00:24:58.349 Daniel Schonfeld: Then there’s a certain price we charge to all the customers for that particular skew.
190 00:24:59.080 ⇒ 00:25:02.040 Daniel Schonfeld: What I’d want to know is, what’s the blended margin.
191 00:25:02.270 ⇒ 00:25:04.119 Payas Parab: Gross margin that we make.
192 00:25:04.260 ⇒ 00:25:09.759 Daniel Schonfeld: From that landed cost to what we charge. All these 3rd parties or customers.
193 00:25:10.850 ⇒ 00:25:17.149 Daniel Schonfeld: And then going down the line, I can pick for each customer what I how much gross margin I want to make.
194 00:25:17.690 ⇒ 00:25:37.319 Nicolas Sucari: So that line. That line is what we have here. It’s all the sales details from Asia connection. What we need to dig into is the purchase details from Asia connection, and try to identify the actual cost of each of those queues, buying back from China and apply all of the other costs that you have landed tariff duty, freight everything like that right?
195 00:25:37.840 ⇒ 00:25:46.550 Daniel Schonfeld: That’s exactly right. And in the future, once now, we have a set skew list that we feel very comfortable, with a high probability that it’s accurate and distinct.
196 00:25:46.820 ⇒ 00:26:01.080 Daniel Schonfeld: Then all I have to do in the future is come into a table and say, Okay, our price went up by 5 bucks, I added into the skew level, and all the other numbers kind of change for each customer, because I’ve already predetermined my margin level for each one.
197 00:26:01.580 ⇒ 00:26:23.060 Daniel Schonfeld: and let’s say that the tariff goes up again by 10%. I can go in and add 10% across the board on all products coming in. And again, all those new numbers will spit out as an output based on these predetermined margins and and formulas that we have set up. It’s basically what I can do now in Google sheets in my own document.
198 00:26:23.460 ⇒ 00:26:26.950 Daniel Schonfeld: It’s what I do now. The tariff goes up 10%. I just go in
199 00:26:27.100 ⇒ 00:26:37.040 Daniel Schonfeld: and all the numbers change, but that’s only for me. Pull parts to go when I’m trying to figure out my cost on it. What I’m trying to do is figure out for everyone in the business
200 00:26:37.820 ⇒ 00:26:42.049 Daniel Schonfeld: what we need to charge them to get the gross margin we we desire.
201 00:26:42.940 ⇒ 00:26:45.350 Daniel Schonfeld: So it’s almost replicating my sheet
202 00:26:45.620 ⇒ 00:26:52.029 Daniel Schonfeld: that I shared with you for everybody. There’s gotta be a simpler way to make it universal where it’s almost in reverse.
203 00:26:52.030 ⇒ 00:27:04.529 Payas Parab: And and that’s where we’re taking it from the Asia connection, like the cost data there, right and like at the customer level, or we’re trying to get it to the skew level. I think one of the things we ran into with Ian, though, is like Nico. Correct me. If I’m wrong here. It’s that like
204 00:27:04.930 ⇒ 00:27:30.939 Payas Parab: on an order level or like a skew level. It’s really hard to do that when you match like, it’s like it can only like it’s like, customer level is like, basically, it’s like, okay, like, if there’s like a bunch of the cost to get it here, right? That’s like, kind of like what you’re trying to think for everyone, right? Not just full parts to go that cost to get it here you like. There’ll be like a bunch of tariffs. There’ll be like the shipping costs. There’ll be all these additional things that like come in that thing, and
205 00:27:31.050 ⇒ 00:27:47.930 Payas Parab: it’s really hard like to. Apparently it’s very hard to like match that to the actual skew. It’s like at a customer level, where it’s just like, Hey, here’s Eagles Pool and Spa, and like, here’s a bunch of tariffs they paid. Boom like that’s logged is like like for the accounting. So I’m curious if you have
206 00:27:48.050 ⇒ 00:27:49.609 Payas Parab: a view on like.
207 00:27:49.730 ⇒ 00:27:59.179 Payas Parab: if we really aren’t able to like match that right like, from like a customer level to the is there like a customer level margin view that we could do is basically like, Hey for this customer?
208 00:27:59.560 ⇒ 00:28:06.090 Payas Parab: Here’s all the tariffs you paid last year. Here’s the total number of you know, total costs, and then we’ll look at
209 00:28:06.471 ⇒ 00:28:11.058 Payas Parab: is there another way to do that that isn’t at the skew level is kind of my question to
210 00:28:11.300 ⇒ 00:28:12.662 Payas Parab: yeah, I know what you’re saying.
211 00:28:14.210 ⇒ 00:28:17.410 Daniel Schonfeld: You, we use averages basically.
212 00:28:17.410 ⇒ 00:28:18.130 Payas Parab: Okay.
213 00:28:18.130 ⇒ 00:28:21.460 Daniel Schonfeld: Like, for we’ll say, you know, we’re predicting
214 00:28:21.980 ⇒ 00:28:43.730 Daniel Schonfeld: that freight is, gonna be, you know, it used to be $2,500 to ship a 40 high cube, massive like Merce container that you see on the back of those trucks. It used to cost 2,500 bucks 4 years ago. At 1 point it went up to 25,000 bucks, and now it goes to 10,000. It’s it’s a it’s a dynamic number. And so we try to do is get ahead of it, be very conservative.
215 00:28:43.850 ⇒ 00:28:47.049 Daniel Schonfeld: and we apply that rate across all
216 00:28:47.470 ⇒ 00:28:50.109 Daniel Schonfeld: customers as far as figuring out their cost.
217 00:28:50.730 ⇒ 00:28:54.470 Daniel Schonfeld: And then we true up with them. When we actually build them
218 00:28:54.670 ⇒ 00:29:13.299 Daniel Schonfeld: for the goods. We say you paid 5 grand a container. It actually went to 10. So we had 5 grand at the time of billing. And then we look back and say, Okay, do our our freight costs our tariff. Do they still hold true when we go to the next round of pricing for everybody? Because you you can’t predict what’s gonna happen.
219 00:29:14.277 ⇒ 00:29:35.540 Daniel Schonfeld: But you can. You can at least get your best guess, and then make up the difference by billing them at the time of sale. And so we are working with a company called Flexport in the future, which we will integrate with that that it’s not like a paper document that comes from China. They actually have. You can book freight in real time. There’s Apis.
220 00:29:35.764 ⇒ 00:29:35.989 Payas Parab: So.
221 00:29:35.990 ⇒ 00:29:52.400 Daniel Schonfeld: Ultimately it would. We’d want to feed that in to our system one day where it’ll update boom real time. This one customer just paid X amount for tariffs, and it’ll start to keep a history. And then when I go push a button, or I or I try to do an analysis on a customer level.
222 00:29:53.340 ⇒ 00:30:00.780 Daniel Schonfeld: It’ll give me some kind of an idea when I I can at least eyeball it for now. Wow! We undercharged them a lot for tariffs last year, and.
223 00:30:00.780 ⇒ 00:30:01.460 Payas Parab: Yeah, yeah.
224 00:30:01.460 ⇒ 00:30:05.849 Daniel Schonfeld: I don’t know. We we’ll have to figure that out when the time comes. I don’t think it’s something we’re gonna solve in the moment. But
225 00:30:06.290 ⇒ 00:30:10.990 Daniel Schonfeld: you’re you’re exactly right in the way you’re thinking about it. It nothing’s impossible.
226 00:30:11.658 ⇒ 00:30:20.009 Daniel Schonfeld: Sometimes, you know, like with Ian and some folks, even Ben, sometimes guilty of it, you know. They just say, Oh, we can’t do it, just can’t do it. And.
227 00:30:20.010 ⇒ 00:30:20.720 Payas Parab: Okay.
228 00:30:20.720 ⇒ 00:30:28.410 Daniel Schonfeld: A lot of times. We just want to get as close as possible, because anything’s better than probably what we’re doing now, which is just guessing.
229 00:30:28.590 ⇒ 00:30:29.270 Payas Parab: Sure, sure.
230 00:30:29.270 ⇒ 00:30:30.870 Daniel Schonfeld: Father-in-law goes on, feel
231 00:30:31.270 ⇒ 00:30:42.049 Daniel Schonfeld: of what he thinks he should charge them without any real data. And so the idea is, let’s let’s get an accurate list online. Like, literally, there’s nothing that exists today like this.
232 00:30:42.790 ⇒ 00:30:47.660 Daniel Schonfeld: He can go down and actually look at previous orders other than going into quickbooks and trying to figure all this crap out.
233 00:30:48.000 ⇒ 00:30:48.380 Payas Parab: Yeah, yeah.
234 00:30:48.380 ⇒ 00:30:49.420 Daniel Schonfeld: All together.
235 00:30:49.650 ⇒ 00:30:56.770 Daniel Schonfeld: At least we’re putting it in a table where it’s in front of us, saying, this is the truth of what this skew costs us to land like he doesn’t even know that.
236 00:30:57.140 ⇒ 00:31:02.720 Nicolas Sucari: Yeah, he’s guessing on what it could be. But we can look at past history and what the current rates are.
237 00:31:02.990 ⇒ 00:31:16.750 Daniel Schonfeld: We can look at a table and put those rates in, and it’ll spit out your probable, very probable, likely cost to lend a product in the United States and based on that truth or that almost truth.
238 00:31:16.900 ⇒ 00:31:24.679 Daniel Schonfeld: Here’s if you want to make a 25% gross margin with this particular customer. Here’s what we should charge them for these that they’re ordering.
239 00:31:24.950 ⇒ 00:31:36.040 Daniel Schonfeld: And then, at least, we’re closer rather than finding out a year later that you actually only made 8%, not 25. And you forgot to, Bill. And that’s what’s created. The whole disaster of this company.
240 00:31:36.440 ⇒ 00:31:36.870 Payas Parab: M.
241 00:31:36.870 ⇒ 00:31:44.450 Daniel Schonfeld: Is the lack of data at your fingertips to make solid, informed decisions. And
242 00:31:45.060 ⇒ 00:32:03.330 Daniel Schonfeld: you know right now, just to be open and honest with you guys. For the last 6 months I’ve been going through due diligence. We’re in the final stages of an acquisition from a major private equity firm. Whether it happens or not. We’re still going to go this route. But things are about to get a lot bigger and a lot more complex in a good way.
243 00:32:03.670 ⇒ 00:32:06.720 Daniel Schonfeld: because we’re gonna have major money behind us. But also
244 00:32:07.240 ⇒ 00:32:15.030 Daniel Schonfeld: through this acquisition, we’re going to be opened up to about almost 2,000 retailers immediately
245 00:32:15.170 ⇒ 00:32:22.870 Daniel Schonfeld: to be selling to 2,000 more customers. And so that’s why I’ve really put you guys on this, because it’s super important that we have this data readily available
246 00:32:23.070 ⇒ 00:32:33.510 Daniel Schonfeld: so that I can call you guys and just say, I, I gotta run a report for all 3rd parties that bought these 20 skews in the last year or 2. I need to understand what our margins were.
247 00:32:33.720 ⇒ 00:32:39.409 Daniel Schonfeld: and what I can charge them in the future, because I can’t all of a sudden go back to a customer and say, I’m charging you a hundred percent more.
248 00:32:39.410 ⇒ 00:32:39.980 Payas Parab: Yep. Yeah.
249 00:32:39.980 ⇒ 00:32:44.240 Daniel Schonfeld: Figure out what I’ve charged them in the past and kind of go incremental to lead to a certain
250 00:32:44.400 ⇒ 00:32:52.180 Daniel Schonfeld: gross margin. And so that’s why, I don’t want to say ulterior motives of doing this like we have to have a proper skew list and a way to analyze data.
251 00:32:52.380 ⇒ 00:33:03.629 Daniel Schonfeld: But the end of day pretty damn soon. I’m gonna need to understand those those facts. And I think even with the data you have here, I’m sure we can. We can probably pull, pull that data on a customer level.
252 00:33:03.800 ⇒ 00:33:29.140 Payas Parab: That. That’s the the customer levels. It seems it’s the easier grouping where we can like quickly, like, let’s say, like, let’s take this. Let’s take our like that costing data. Let’s figure out like, if we can classify what those memos are. Right is like, this is a tariff. This is that. And there’s been some categorization that’s done in quickbooks. We’ll just have to validate that. We could probably pull like a customer level like roughly what you know what was pulled. I think it has like a quantity, and this so we can kind of.
253 00:33:29.140 ⇒ 00:33:29.820 Nicolas Sucari: Yeah.
254 00:33:29.820 ⇒ 00:33:44.150 Payas Parab: There’s maybe like a guess of what the product was like like. There’s a there’s a way like, I think it’s just that we, now that I know that that end goal is the customer kind of that customer view, that is, that’s really helpful context, right? Like, I think that makes it that makes it the ask a little bit
255 00:33:44.630 ⇒ 00:33:50.310 Payas Parab: easier than at the skew level, getting that exact margin from the Asia connection. Yeah.
256 00:33:50.310 ⇒ 00:33:51.690 Daniel Schonfeld: Yeah, the skew levels.
257 00:33:52.070 ⇒ 00:33:58.360 Daniel Schonfeld: I, yeah, I see what you’re saying. The skew level is not as important. It. It’s important, you know. It depends which way you look at. It’s like.
258 00:33:58.360 ⇒ 00:33:58.850 Payas Parab: Sure, sure.
259 00:33:58.850 ⇒ 00:34:06.919 Daniel Schonfeld: Depends, but it’s at the end of the day I just want to know what my gross margin is on a particular customer, and what I should be charging them
260 00:34:07.140 ⇒ 00:34:10.099 Daniel Schonfeld: in order to to get to the desired.
261 00:34:10.100 ⇒ 00:34:30.019 Payas Parab: Right? What would like a helpful output be like? It’s like, Hey, like, here’s Eagle, Spa, and whatever and like, right now, just based on like just pure costing data, right of, like the overall picture, like, not even at the unit level, you should be charging them 10% more like, would that be like a like a an output? That’s good enough, or would it be have to be like, okay, this skew needs to go up. This skew needs to go up.
262 00:34:30.239 ⇒ 00:34:44.179 Daniel Schonfeld: Yeah, because I cause they’re gonna say, I need a pricing list and they they’re determining what they’re gonna order based on the skew, and how much it costs, so they may come back and say, I can buy that skew somewhere else for 5 bucks less.
263 00:34:44.179 ⇒ 00:34:44.869 Payas Parab: Yup! Yup!
264 00:34:44.870 ⇒ 00:34:47.409 Daniel Schonfeld: Just apply to 10% like a lot of customers.
265 00:34:47.530 ⇒ 00:35:00.089 Daniel Schonfeld: I’ll even lower the cost, and they’ll say, shit. We can order 4 400 more if you lower it by 10 bucks, but I’ll go apply that difference to another product where they think it’s so low
266 00:35:00.300 ⇒ 00:35:18.599 Daniel Schonfeld: and they don’t. These people don’t think about this things that way. It’s a very old school business. You got a lot of old family guys that are buying stuff. They just think of things as a pump should cost this much. A filter should cost that much. Yeah, they’re not looking the same way that we’re in that same predicament where we’re not
267 00:35:18.760 ⇒ 00:35:23.469 Daniel Schonfeld: looking at margins properly. Everyone’s looking at things on a skewed level.
268 00:35:23.750 ⇒ 00:35:24.729 Payas Parab: Yeah, okay.
269 00:35:24.730 ⇒ 00:35:30.709 Daniel Schonfeld: For me to make a decision. Yes, overall I it would be helpful to say you need to charge them 10% more overall.
270 00:35:30.710 ⇒ 00:35:31.240 Payas Parab: Yeah, yeah.
271 00:35:31.240 ⇒ 00:35:35.489 Daniel Schonfeld: How I do it. You know I gotta do that at the skew level.
272 00:35:35.490 ⇒ 00:35:37.560 Payas Parab: That that makes sense. Okay.
273 00:35:37.560 ⇒ 00:35:46.220 Daniel Schonfeld: Nickbooks, does I? I know that when we build customers we don’t just say, Hey, all your goods cost 20 grand. We say
274 00:35:46.560 ⇒ 00:35:55.410 Daniel Schonfeld: you owe 20 grand, and here it every invoice that we send them has a breakdown of every skew, and then there’s an extra line item for an additional tariff.
275 00:35:56.920 ⇒ 00:36:09.419 Daniel Schonfeld: So there! There’s the 1st thing we do with the customers we send a I don’t know what the nomenclature is, but it’s a deposit’s a request for deposit. So if a customer buys a hundred grand worth of goods, and there’s let’s just say there’s 5 skews.
276 00:36:09.980 ⇒ 00:36:16.689 Daniel Schonfeld: we’ll send them an invoice, and this usually happens in September. When this pool season just ends, we’ll say
277 00:36:17.460 ⇒ 00:36:26.300 Daniel Schonfeld: we’ll we’ll send them something for 20 grand. So if it’s a 20% deposit on a hundred $1,000 order. They’ll just get something in September that says you owe 20 grand.
278 00:36:26.530 ⇒ 00:36:32.389 Daniel Schonfeld: and it it’ll probably list out the products, I think, and maybe this is what Ian was talking about. You’ll have to get a copy.
279 00:36:32.540 ⇒ 00:36:35.490 Daniel Schonfeld: and then when the goods are ready to ship in March
280 00:36:36.210 ⇒ 00:36:50.330 Daniel Schonfeld: literally, they’ll buy it in September of of 2025, and in March of 2026 is when it will, the products will be made and shipped from China to the Us. That’s when we build them for the other $80,000
281 00:36:50.470 ⇒ 00:36:54.790 Daniel Schonfeld: and all the skew levels in there. And then, if we got it wrong on the tariff.
282 00:36:55.110 ⇒ 00:37:01.389 Daniel Schonfeld: We said, Oh, that the price is based on a 5,000, not tariff freight on a $5,000 freight.
283 00:37:01.550 ⇒ 00:37:07.820 Daniel Schonfeld: It actually went up to 8. You’ll see an extra $3,000 at the as a line item at the bottom of the invoice in March.
284 00:37:08.500 ⇒ 00:37:09.819 Daniel Schonfeld: Does that make sense?
285 00:37:10.720 ⇒ 00:37:15.580 Daniel Schonfeld: That’s the that’s the billing cycle with a customer. Take deposit 1st
286 00:37:15.920 ⇒ 00:37:18.419 Daniel Schonfeld: Bill. The difference when the goods ship.
287 00:37:21.930 ⇒ 00:37:22.590 Payas Parab: Okay.
288 00:37:22.970 ⇒ 00:37:28.864 Payas Parab: that makes sense. Bo, any questions on that is that like, based on some of the data, you’ve looked like the data now to
289 00:37:29.350 ⇒ 00:37:31.480 Payas Parab: is that kind of making sense we meet.
290 00:37:31.480 ⇒ 00:37:31.870 Bo Yoon: All right.
291 00:37:31.870 ⇒ 00:37:34.149 Payas Parab: Who can huddle on this and, like figure out best steps.
292 00:37:34.150 ⇒ 00:38:01.480 Daniel Schonfeld: Yeah, don’t. Don’t be afraid to ask a lot of questions. I don’t expect it took me like a year or 2 to even like, understand all of these things so literally. Don’t be afraid to ask any questions. No, there are no dumb questions. I rather you ask a million of them than just do so, and I can always get on with you and keep explaining and explaining until you fully get it. It’s not that complex, but it’s there’s a lot of moving parts that have to go right in order to do it. So I would actually suggest to
293 00:38:01.640 ⇒ 00:38:05.180 Daniel Schonfeld: go through like a use. Case of a Customer.
294 00:38:05.180 ⇒ 00:38:05.850 Payas Parab: Okay.
295 00:38:05.850 ⇒ 00:38:12.799 Daniel Schonfeld: And like go like, experience it yourself, like what like? How do they even place an order?
296 00:38:12.970 ⇒ 00:38:18.099 Daniel Schonfeld: How do they send a purchase order? What comes from Asia connection to actually bill for that.
297 00:38:18.440 ⇒ 00:38:31.740 Daniel Schonfeld: you know. And then are there packing slips that come to them. So they know what’s on the container like I would go through a use case and experience it firsthand. So maybe you can get a better vantage point on this whole thing of how it actually happens.
298 00:38:32.290 ⇒ 00:38:48.039 Payas Parab: And and that’s like, like, via the like, quickbooks, data, right? Like we’d look at like, okay, so this customer wants this, there’s like an order placed via Asia connection. They may not be like pool parts to go, so it won’t be reflected on the sales sheet, but we’re looking at the cost sheet we’re saying, Hey, this is
299 00:38:48.370 ⇒ 00:39:09.310 Payas Parab: the like. This is what like this customer purchased right? And then there’s a bunch of line items. There’s like, maybe, like a deposit like you mentioned, like some like, we’d look at that like specific customer, that specific order, try and figure out like, okay, here’s all the things that like went through. Here’s like a tariff invoice. Here’s like a whatever. Here’s the deposit. And then here’s the total billing.
300 00:39:09.510 ⇒ 00:39:14.759 Payas Parab: And then, if we look at that example, we should kind of get a sense of like, what’s what’s actually transacting is that.
301 00:39:15.080 ⇒ 00:39:21.510 Daniel Schonfeld: Yeah, I think a lot of questions will come from that from you like, just pick a customer that has a decent value of what they ordered in the last
302 00:39:21.720 ⇒ 00:39:22.900 Daniel Schonfeld: 12 months, or whatever.
303 00:39:22.900 ⇒ 00:39:24.040 Payas Parab: Okay. Okay.
304 00:39:24.280 ⇒ 00:39:33.890 Daniel Schonfeld: And just ask the questions that confuse you and like, how did they even like if I was on your side like how the hell. They even place this order. How do you even know to invoice them for that?
305 00:39:33.890 ⇒ 00:39:34.270 Daniel Schonfeld: Sure, sure.
306 00:39:34.270 ⇒ 00:39:40.859 Daniel Schonfeld: But they how did they get a price list? And we’ll figure that out for you, because there is a weird excel sheet that goes out to them
307 00:39:41.420 ⇒ 00:39:48.079 Daniel Schonfeld: that’s got all this pricing on, and my father-in-law created a pretty smart excel sheet that every time you pick a product
308 00:39:48.240 ⇒ 00:39:56.240 Daniel Schonfeld: on the next tab, it tells you how much space you have left in a container to fill. So they keep going back and adding product. They’re like, okay, I filled it.
309 00:39:56.380 ⇒ 00:40:03.260 Daniel Schonfeld: Sometimes they’ll just pick products because they’re not at the Max. You got to fill the whole container, they’re paying for it, so they might as well fill it
310 00:40:03.610 ⇒ 00:40:04.150 Daniel Schonfeld: bye.
311 00:40:04.810 ⇒ 00:40:13.919 Daniel Schonfeld: And so you might have a question on that like, how do you even come up with those prices? And it? Everything’s gonna come full circle on this. And I think it would be helpful for all you guys to go through one use case.
312 00:40:13.920 ⇒ 00:40:14.570 Nicolas Sucari: Yeah.
313 00:40:14.570 ⇒ 00:40:15.580 Daniel Schonfeld: Independently and.
314 00:40:17.850 ⇒ 00:40:29.876 Nicolas Sucari: Yeah, we’ll we’ll. We’ll then understand why Ian was saying that it’s kind of difficult to get to this to this queue costs, because they are filling the the freight differently every time. Right?
315 00:40:30.220 ⇒ 00:40:30.550 Nicolas Sucari: yes.
316 00:40:30.550 ⇒ 00:40:35.569 Nicolas Sucari: Costs associated to this queues is kind of it. Kind of depends on each order.
317 00:40:36.030 ⇒ 00:40:39.479 Daniel Schonfeld: Yeah. And I’m the reason I’m also there’s there’s other like
318 00:40:39.640 ⇒ 00:40:46.039 Daniel Schonfeld: hidden meanings in doing an exercise like this, because there’s so many products my father-in-law offers to them
319 00:40:46.100 ⇒ 00:41:13.580 Daniel Schonfeld: that maybe we don’t have to offer to them in the future. Sometimes, like he, he gives them a thousand options, so they’ll just fill up the container with the cheapest thing they can find. But maybe that’s not the best way to do it. And I I rather you guys be thinking outside the box when you’re doing this stuff, and maybe you’ll come up with something smarter and better rather than just being mechanical and just looking at data from 1 point to another. I’d like for you to think about the business. You know. Maybe maybe there’s a smarter better way to do it than I’m thinking about.
320 00:41:13.740 ⇒ 00:41:35.600 Daniel Schonfeld: So I think it’d be helpful for you to even just all go through one exercise, pick a customer, and then see also if it matches in your sheets here and see if there’s any costs missing, or you know there, there’s a there’s a maybe we’re missing something. Maybe we’re not charging enough. Maybe they’re over paying. I don’t know, but I think going through that process will help you to to understand what quite what are the right questions to ask.
321 00:41:35.880 ⇒ 00:41:45.180 Payas Parab: That’s super helpful. Yeah, I think we’ll do that. We’ll kind of pick a customer and kind of do that as a homework, and then see what follow up questions we have from there, and then we can keep it. Keep it moving. Okay.
322 00:41:46.430 ⇒ 00:41:58.950 Daniel Schonfeld: And all data is available to you. I can make all sorts of people available to you. This is definitely a big. This is the backbone of the whole business is getting this data right is what’s going to drive everything because we’ve just had junk data.
323 00:41:59.050 ⇒ 00:42:03.150 Payas Parab: And also just down to the the nomenclature or the descriptions.
324 00:42:03.500 ⇒ 00:42:08.049 Daniel Schonfeld: I’ve had a problem like last year. I had one with the filter base on Black and Decker.
325 00:42:08.390 ⇒ 00:42:18.530 Daniel Schonfeld: where my father-in-law told me a description, and said, Oh, it comes with a base, a hose! It’s a filter that, you know, like a pump filters water. It could. It goes through a filter, and it comes out.
326 00:42:18.760 ⇒ 00:42:24.749 Daniel Schonfeld: We assume that there was cartridges inside of the filter, which cost $150.
327 00:42:25.650 ⇒ 00:42:26.650 Daniel Schonfeld: There were not.
328 00:42:26.800 ⇒ 00:42:34.239 Daniel Schonfeld: or maybe it was vice versa. They were in there, but I didn’t charge for them, and that’s only because I got a description that said that there were in there.
329 00:42:34.410 ⇒ 00:42:37.239 Daniel Schonfeld: So the and that cost us like 3, 4 grand.
330 00:42:37.590 ⇒ 00:42:53.939 Payas Parab: Yup, and so like in the in the scenario of like, we’re like calculating skews. That’s like the added cost that like we have to kind of incorporate like like that would be like another invoice we might see on the costing sheet that would be like, here’s this additional order related to that customer that would then drive up that overall kinda.
331 00:42:53.940 ⇒ 00:43:00.100 Daniel Schonfeld: Yeah, yeah, you might see in an order like, yeah, like an additional line item, you’ll be like, why the hell is that? There.
332 00:43:00.100 ⇒ 00:43:00.740 Payas Parab: Yep.
333 00:43:01.130 ⇒ 00:43:10.140 Daniel Schonfeld: And you may ask that question. I’ll be like shit. You’re right. We we forgot to build them for that, and that should be included in the skew level like, I just think a lot of questions will come from it. I actually did this.
334 00:43:10.290 ⇒ 00:43:11.617 Daniel Schonfeld: If you go
335 00:43:13.480 ⇒ 00:43:19.910 Daniel Schonfeld: If you look at my Nicholas, the the copy of the Master Skew list I gave you from the pool parts to go side.
336 00:43:21.030 ⇒ 00:43:24.359 Daniel Schonfeld: If you look at the black and decker filters.
337 00:43:24.480 ⇒ 00:43:29.179 Daniel Schonfeld: You can see, I added, an extra line item underneath, because I had to now calculate.
338 00:43:29.570 ⇒ 00:43:32.879 Daniel Schonfeld: Here, you know what the is this the original one.
339 00:43:33.670 ⇒ 00:43:38.600 Daniel Schonfeld: Yeah. Go down stop
340 00:43:40.990 ⇒ 00:43:42.760 Nicolas Sucari: Wait! Let me make it bigger.
341 00:43:42.760 ⇒ 00:43:46.720 Daniel Schonfeld: Yeah, look, see? It says, number fit line 50, if sold with cartridge, I think.
342 00:43:48.080 ⇒ 00:43:51.149 Daniel Schonfeld: Yeah. Go across to the pricing. The like.
343 00:43:51.330 ⇒ 00:43:53.749 Daniel Schonfeld: Try to find the the cost for me
344 00:43:54.130 ⇒ 00:44:00.030 Daniel Schonfeld: online 50. I think it is. Yeah, I think he’s yeah. There you go, 2 packs.
345 00:44:00.030 ⇒ 00:44:00.820 Daniel Schonfeld: So like we.
346 00:44:00.820 ⇒ 00:44:01.450 Nicolas Sucari: Exhausting.
347 00:44:01.715 ⇒ 00:44:14.439 Daniel Schonfeld: We sold it to them at 20. Let’s just say it was 27 bucks. I assumed it was 27 bucks my cost, but my real cost was 33, but I if you keep going across, I sold it to them without charging them for that.
348 00:44:14.770 ⇒ 00:44:16.049 Daniel Schonfeld: So there it is beat.
349 00:44:16.190 ⇒ 00:44:19.289 Daniel Schonfeld: Go back wholesale retail price. I think it.
350 00:44:20.810 ⇒ 00:44:26.759 Daniel Schonfeld: wait. I’m losing it. Line 50. Yeah, yeah, there you go. So look at the difference
351 00:44:27.110 ⇒ 00:44:30.260 Daniel Schonfeld: in the in the wait. Let me see.
352 00:44:30.580 ⇒ 00:44:36.090 Daniel Schonfeld: 50, 50. Yeah, there you go. So I sold it to them at 76 bucks.
353 00:44:36.960 ⇒ 00:44:39.810 Daniel Schonfeld: Oh, well, that’s the price I did sell to them, anyways.
354 00:44:40.260 ⇒ 00:44:42.869 Daniel Schonfeld: but I I should have sold it.
355 00:44:45.100 ⇒ 00:44:47.039 Nicolas Sucari: 89, maybe this one.
356 00:44:47.040 ⇒ 00:44:48.839 Daniel Schonfeld: Bd. Wholesale retail price.
357 00:44:49.290 ⇒ 00:44:50.890 Nicolas Sucari: 24 and 25. Here.
358 00:44:50.890 ⇒ 00:44:52.620 Daniel Schonfeld: Whatever. It’s the difference between
359 00:44:52.810 ⇒ 00:44:58.740 Daniel Schonfeld: they’re 50 sorry line 49, and 50. So I sold to them at 56. I should have sold to them at 89.
360 00:45:01.120 ⇒ 00:45:03.579 Daniel Schonfeld: That’s what I’m talking about, like I didn’t.
361 00:45:03.950 ⇒ 00:45:10.970 Daniel Schonfeld: I didn’t know that the cartridges were already in there because the description hadn’t said it before. That’s why it’s super important for me to get the
362 00:45:11.130 ⇒ 00:45:22.570 Daniel Schonfeld: this, the the data of the skews correct. And I know you guys can’t figure that out, we have to. So we need to do a process whereby, at least for starting with Black and Decker, because that’s the highest value
363 00:45:22.960 ⇒ 00:45:28.819 Daniel Schonfeld: is you guys gin up what you think is a distinct list of black and decker items. Anything starting with a Bd
364 00:45:29.080 ⇒ 00:45:35.760 Daniel Schonfeld: and say, Dan, you have to go through and verify that these descriptions are a hundred percent accurate of everything you have in here. And I’ll come back
365 00:45:35.950 ⇒ 00:45:40.619 Daniel Schonfeld: in a Google sheet and say, this one’s a hundred percent verified a hundred percent, you know.
366 00:45:40.730 ⇒ 00:45:50.620 Daniel Schonfeld: And then you’ll say, Dan, which which cost? Do you want to use this? 79, or the 89 for line 49, 50, or whatever the number is 46, or 56, and I’ll say 56 is the right one.
367 00:45:50.790 ⇒ 00:45:53.419 Daniel Schonfeld: and so you’ll get rid of that 46 number.
368 00:45:53.530 ⇒ 00:45:59.090 Daniel Schonfeld: And from now on I don’t have to worry. Of which line I which line I’m using for that specific skew.
369 00:45:59.090 ⇒ 00:46:17.220 Payas Parab: Part of like what we were doing, Nico and some of the like analysis, right where we were trying to like average. And we were finding like duplicate rows or like skews that have different prices. Right? We had actually tagged some of them. Maybe we like clean up that sheet from that we’ve just like. Then flip that over to Dan and be like these are the ones you need to check right like. Here’s ones where
370 00:46:17.220 ⇒ 00:46:30.470 Payas Parab: I found 4 prices. For, like, basically, I found 4 prices for the same skew. There were situations where it’s like, okay, I have 2 rows of the same skew with different descriptions, like we’d actually done sort of that exercise. I think we just never cleaned it up.
371 00:46:30.470 ⇒ 00:46:38.160 Payas Parab: Maybe we can like clean that up, Nico, and just like Flip that to Dan and be like, here are the like, the problem skews that, like we found something funky and like.
372 00:46:38.160 ⇒ 00:46:42.260 Payas Parab: can you verify for this specific thing? What is the best cause.
373 00:46:42.380 ⇒ 00:46:46.199 Daniel Schonfeld: If you can chunk it by priority. Because there, I’m I’m gonna guess there’s hundreds of those.
374 00:46:46.200 ⇒ 00:46:47.160 Payas Parab: Yeah, yeah.
375 00:46:47.423 ⇒ 00:47:01.390 Daniel Schonfeld: I don’t know if I’d go by, maybe by dollar value of what’s sold in the last year. If you can use that as a as a gauge, and then we can just prioritize which ones to go after first.st But I know for sure Black and Decker should be the highest priority.
376 00:47:02.100 ⇒ 00:47:14.830 Payas Parab: Decker. Okay? And then, and because, like, we did do this exercise kind of like looking at the top 20 right? Like trying to figure out what the top 20. We just want to make sure we’re looking at that right? Is like we looked at it, for, like all sales, like all sales. Is that the right? The right approach.
377 00:47:15.010 ⇒ 00:47:25.140 Daniel Schonfeld: Yeah, I mean, it is. For now, I guess, because well, in the future, just because we sold something like there are products like a ladder, I think, is probably the top one of the top ones.
378 00:47:25.140 ⇒ 00:47:25.540 Payas Parab: -
379 00:47:25.540 ⇒ 00:47:31.180 Daniel Schonfeld: It’s it’s only a high value because we basically gave it away for less than it costs.
380 00:47:31.910 ⇒ 00:47:32.350 Payas Parab: Okay.
381 00:47:32.350 ⇒ 00:47:40.890 Daniel Schonfeld: So it’s gonna be look like holy shit. We sell a lot of ladders, but we make no money or lose money on it. So, and it’s only because we had so much inventory. My father-in-law just wanted to sell it off.
382 00:47:41.020 ⇒ 00:47:50.759 Daniel Schonfeld: So that’s why. Sometimes it’s a good thing, but not but that’s why I’m saying I would pull apart and focus on black and Decker products as 1st priority to get through that list to make sure it’s tight.
383 00:47:50.920 ⇒ 00:47:54.169 Daniel Schonfeld: and then we can go by dollar value of everything else.
384 00:47:54.170 ⇒ 00:47:56.289 Payas Parab: Okay, that’s helpful. Alright.
385 00:47:56.580 ⇒ 00:48:16.360 Payas Parab: but we can kind of noodle on that. But we’ll kind of look at the the skews. We had looked at the issues we’d identified and like, let’s see if we can isolate the list of black. And and I can go over this with you both offline. It’s like. And then let’s look at Black and Decker specifically, and see like what errors we can call out to Dan. And then he can like fill it in for us.
386 00:48:17.010 ⇒ 00:48:25.320 Daniel Schonfeld: Yeah, exactly. If you just want to like, give me a Google sheet or a link to something and say, Hey, there’s but I would just keep it, you know. Like to 2030 skews to start.
387 00:48:25.320 ⇒ 00:48:28.430 Payas Parab: Yeah, like, here’s the top. Here’s the biggest black and decker ones.
388 00:48:28.430 ⇒ 00:48:28.770 Nicolas Sucari: Yeah.
389 00:48:29.028 ⇒ 00:48:35.999 Payas Parab: I mean, like an issue again. Maybe it’s just like a quick summary of like, hey, there’s multiple rows for the same thing with different prices. Boom!
390 00:48:36.000 ⇒ 00:48:36.400 Daniel Schonfeld: Yeah.
391 00:48:36.400 ⇒ 00:48:37.830 Payas Parab: We need to verify that.
392 00:48:38.030 ⇒ 00:49:03.290 Daniel Schonfeld: Yup. And then I think, once we have that top 50 or so skews like, we’re like, Okay, this is the the top 50, and they’re so accurate like the the model number. Some don’t have some have spaces in them like we’ll correct that and say there shouldn’t be a space, and you can get rid of the other one, and then we’ll go through, and I’ll say with my father-in-law, and say I need to see the actual purchase orders unless you guys have them of what you paid for this product.
393 00:49:03.400 ⇒ 00:49:10.119 Daniel Schonfeld: and that will go into my calculation on the sheet sheet you were looking at before of the fob price.
394 00:49:10.840 ⇒ 00:49:22.519 Daniel Schonfeld: and that dictates like in my sheet. Yeah, go back to that. Everything is driven off the fob right there. I see it? N, maybe. Or yeah. So that price is what we’re paying the factory for that unit.
395 00:49:23.150 ⇒ 00:49:25.870 Daniel Schonfeld: So when we go down that everything else
396 00:49:26.110 ⇒ 00:49:32.400 Daniel Schonfeld: there’s a few variables in here as you go across like tariffs and all that like explained before, but it all starts with the fob cost.
397 00:49:34.380 ⇒ 00:49:38.660 Nicolas Sucari: So the fob is what Asia is buying from the manufacturers. That’s fine.
398 00:49:38.660 ⇒ 00:49:39.399 Daniel Schonfeld: Yes, that’s.
399 00:49:39.400 ⇒ 00:49:42.139 Nicolas Sucari: You are the landed freight. Yeah.
400 00:49:42.140 ⇒ 00:49:45.860 Daniel Schonfeld: You forget all the freight, everything. That’s literally what the factory says. Hey?
401 00:49:46.030 ⇒ 00:49:50.209 Daniel Schonfeld: When you day one, when you pick it up at the factory. This is what I’m charging you.
402 00:49:51.020 ⇒ 00:49:56.549 Daniel Schonfeld: And then if you go to landed and click on the formula.
403 00:49:57.160 ⇒ 00:50:00.429 Daniel Schonfeld: if you double, click it, just double, click any box with numbers in it.
404 00:50:00.860 ⇒ 00:50:04.559 Daniel Schonfeld: You’ll see those are the things I’m adding to get to my landed cost.
405 00:50:05.120 ⇒ 00:50:05.900 Daniel Schonfeld: So it’s the.
406 00:50:05.900 ⇒ 00:50:06.360 Nicolas Sucari: And then.
407 00:50:07.460 ⇒ 00:50:08.630 Daniel Schonfeld: Plus the.
408 00:50:08.630 ⇒ 00:50:10.460 Nicolas Sucari: Tariff duty, freight.
409 00:50:10.460 ⇒ 00:50:10.810 Daniel Schonfeld: Great.
410 00:50:10.810 ⇒ 00:50:12.679 Nicolas Sucari: All of these ones, and load.
411 00:50:13.280 ⇒ 00:50:14.280 Daniel Schonfeld: Exactly
412 00:50:15.836 ⇒ 00:50:24.059 Daniel Schonfeld: and then ultimately to get to the pool parts to go. Price. We add in the black and Decker license fee that we pay Black and Decker, we have to include that which is in there.
413 00:50:24.060 ⇒ 00:50:24.740 Nicolas Sucari: This one
414 00:50:24.990 ⇒ 00:50:29.320 Nicolas Sucari: Yup, and that’s just based off a true percentage which is in in column A. H right? There.
415 00:50:30.871 ⇒ 00:50:34.130 Daniel Schonfeld: Each product has an assigned royalty value. We have to pay them.
416 00:50:34.360 ⇒ 00:50:39.390 Daniel Schonfeld: and that all kicks back to pool parts to go wholesale price all the way to the left, somewhere.
417 00:50:39.600 ⇒ 00:50:40.540 Daniel Schonfeld: right there in green.
418 00:50:40.540 ⇒ 00:50:41.220 Nicolas Sucari: Decent.
419 00:50:41.630 ⇒ 00:50:56.489 Daniel Schonfeld: Yup, and if you double click that you’ll see it’s the landed plus the Bd margin. Yup landed plus Bd margin. And that’s a 7% right there back to your other sheet of what’s added on top of the cost to get to pool parts to go price.
420 00:50:59.770 ⇒ 00:51:00.920 Nicolas Sucari: Okay. Yeah.
421 00:51:04.750 ⇒ 00:51:05.530 Nicolas Sucari: Okay.
422 00:51:06.160 ⇒ 00:51:08.040 Daniel Schonfeld: Alright! That should be enough to be deadly.
423 00:51:10.810 ⇒ 00:51:11.780 Nicolas Sucari: Yeah.
424 00:51:11.780 ⇒ 00:51:12.719 Daniel Schonfeld: Alright cool. Any questions.
425 00:51:12.720 ⇒ 00:51:13.300 Nicolas Sucari: That’s great!
426 00:51:13.470 ⇒ 00:51:14.649 Daniel Schonfeld: Just give me a shout!
427 00:51:15.040 ⇒ 00:51:15.570 Payas Parab: Awesome. Thank.
428 00:51:15.570 ⇒ 00:51:28.910 Nicolas Sucari: Yeah, thank you very much, Dan, for this. Yeah, we’re gonna circle back with the team and try to understand this. For that kind of list from Black and Decker. Maybe we can start with that get back to you and see how we can then continue. Okay.
429 00:51:29.200 ⇒ 00:51:30.240 Daniel Schonfeld: Awesome thanks guys.
430 00:51:30.240 ⇒ 00:51:40.579 Bo Yoon: Just to make sure. Sorry. Just one more and so we’re now thinking in terms of Asia, not not in terms of pull parts to go right, pull parts to go.
431 00:51:40.580 ⇒ 00:51:46.239 Daniel Schonfeld: Yeah, I would think terms of Asia, because pool parts to go. Just treat us. Another customer of Asia.
432 00:51:46.580 ⇒ 00:51:49.290 Bo Yoon: Just another call. Okay? Got it? Yeah.
433 00:51:50.170 ⇒ 00:51:59.809 Nicolas Sucari: So okay, but just this, this costing sheet that you have. This is all skews from Asia, or are just only ones that will participate uses? Or is everything.
434 00:52:00.090 ⇒ 00:52:02.939 Daniel Schonfeld: No, you should if you got it from me, and and I saw other.
435 00:52:02.940 ⇒ 00:52:03.280 Nicolas Sucari: No, no.
436 00:52:03.280 ⇒ 00:52:03.900 Daniel Schonfeld: Okay.
437 00:52:04.050 ⇒ 00:52:08.589 Nicolas Sucari: The the one that we got from you, the one the official.
438 00:52:08.590 ⇒ 00:52:13.130 Daniel Schonfeld: From my perspective. But that should give you a perspective on how we think.
439 00:52:13.130 ⇒ 00:52:14.040 Nicolas Sucari: Yeah, yeah.
440 00:52:14.270 ⇒ 00:52:16.449 Daniel Schonfeld: What goes into charging a customer.
441 00:52:16.660 ⇒ 00:52:26.430 Daniel Schonfeld: If you look at it from the from that perspective, that’s how I get to a sell price where I add margin on it, like basically the pool parts to go wholesale column, that one in green
442 00:52:26.780 ⇒ 00:52:31.009 Daniel Schonfeld: where it said 7% imagine that was every other customer.
443 00:52:31.140 ⇒ 00:52:37.719 Daniel Schonfeld: And I just changed that point 0 7 to point 10 point, you know, that’s most basically what I’m trying to get to.
444 00:52:38.290 ⇒ 00:52:47.680 Daniel Schonfeld: And I do that on a skew level. So all I would have to do in the future just change that number at each skew level, and it would spit out what I need to charge each customer on a skew level.
445 00:52:48.410 ⇒ 00:52:48.940 Nicolas Sucari: Yeah.
446 00:52:49.510 ⇒ 00:52:59.650 Daniel Schonfeld: The all. The formula should be the same for everybody. It’s the that’s our side of the table, what it costs us to land it. What we want to charge should be different for each customer.
447 00:53:00.520 ⇒ 00:53:01.510 Daniel Schonfeld: Alright.
448 00:53:02.540 ⇒ 00:53:03.290 Payas Parab: Much.
449 00:53:04.040 ⇒ 00:53:05.859 Daniel Schonfeld: Alright guys, thank you so much. I appreciate you.
450 00:53:06.680 ⇒ 00:53:07.210 Nicolas Sucari: Thank you. Then.
451 00:53:07.610 ⇒ 00:53:08.350 Bo Yoon: Have a nice day.
452 00:53:08.700 ⇒ 00:53:09.490 Daniel Schonfeld: Like.
453 00:53:09.490 ⇒ 00:53:10.439 Nicolas Sucari: See you. Bye-bye.