Meeting Title: BF <> PoolParts: SKU List Next Steps Date: 2025-01-03 Meeting participants: Luke Daque, Nicolas Sucari, Uttam Kumaran, Daniel Schonfeld
WEBVTT
1 00:04:34.900 ⇒ 00:04:36.970 Nicolas Sucari: Hey, guys, hey, dan.
2 00:04:36.970 ⇒ 00:04:37.789 Uttam Kumaran: Hey! Dan!
3 00:04:38.270 ⇒ 00:04:38.976 Luke Daque: Hi! Everyone.
4 00:04:43.430 ⇒ 00:04:45.021 Uttam Kumaran: Hey? You’re on mute
5 00:04:50.740 ⇒ 00:04:52.669 Uttam Kumaran: still. Can’t still can’t hear you.
6 00:05:04.060 ⇒ 00:05:04.899 Daniel Schonfeld: There we go!
7 00:05:05.160 ⇒ 00:05:06.240 Uttam Kumaran: Oh, there it is. Okay.
8 00:05:06.240 ⇒ 00:05:10.880 Daniel Schonfeld: Connected to my airpod. Max, how are you.
9 00:05:11.400 ⇒ 00:05:14.579 Uttam Kumaran: Good. How was how was the holidays and everything?
10 00:05:14.580 ⇒ 00:05:16.270 Uttam Kumaran: Good, happy New Year to you guys?
11 00:05:16.270 ⇒ 00:05:17.450 Uttam Kumaran: Yeah, happy New Year’s.
12 00:05:19.680 ⇒ 00:05:20.779 Luke Daque: Yeah. Happy. What do you guys do.
13 00:05:20.780 ⇒ 00:05:21.660 Nicolas Sucari: See you too.
14 00:05:22.070 ⇒ 00:05:23.070 Daniel Schonfeld: Anything good.
15 00:05:23.570 ⇒ 00:05:27.339 Uttam Kumaran: Feel like Nico out of us probably had the the coolest
16 00:05:27.960 ⇒ 00:05:34.529 Uttam Kumaran: sort of I don’t know. Maybe, Dan, you’ve been. I don’t know. I haven’t. I’ve never been to Uruguay. But yeah, I guess
17 00:05:34.530 ⇒ 00:05:35.360 Uttam Kumaran: I’m neither bike.
18 00:05:35.360 ⇒ 00:05:39.934 Nicolas Sucari: Under, but I mean it away right now.
19 00:05:40.530 ⇒ 00:05:49.370 Nicolas Sucari: I came here to spend some time with my family. We have like an apartment here. This was from my grandma, and we come all together to spend some time.
20 00:05:50.400 ⇒ 00:05:58.520 Nicolas Sucari: But yeah, the the weather was is not really good these past weeks, so we were not able to enjoy
21 00:05:58.910 ⇒ 00:06:04.710 Nicolas Sucari: the beach a lot. But yeah, I mean, it’s been. It’s been fun spending some time with the family altogether.
22 00:06:04.710 ⇒ 00:06:11.066 Uttam Kumaran: It’s like the nicest beach town in Uruguay. He’s very underselling it. It’s like the nicest place ever.
23 00:06:11.790 ⇒ 00:06:12.180 Daniel Schonfeld: Is that right?
24 00:06:12.180 ⇒ 00:06:13.349 Nicolas Sucari: It’s really nice. It’s really nice.
25 00:06:13.350 ⇒ 00:06:13.780 Daniel Schonfeld: That’s where you.
26 00:06:13.780 ⇒ 00:06:17.579 Nicolas Sucari: No, no, I’m I’m from no, I’m from Argentina, from Buenos Aires.
27 00:06:18.260 ⇒ 00:06:18.940 Daniel Schonfeld: Okay.
28 00:06:19.200 ⇒ 00:06:19.920 Nicolas Sucari: But it’s also.
29 00:06:20.150 ⇒ 00:06:21.929 Uttam Kumaran: License is so close, like.
30 00:06:21.930 ⇒ 00:06:22.310 Nicolas Sucari: It’s just.
31 00:06:22.310 ⇒ 00:06:23.869 Uttam Kumaran: It’s like, right? Yeah.
32 00:06:24.930 ⇒ 00:06:44.189 Nicolas Sucari: But oh, it’s 1 h in by boat, and then for our 4 h drive in Uruguay to get here. But yeah, I mean, it’s it’s really beautiful. It’s really nice town. With great beaches, and yeah places to eat.
33 00:06:44.350 ⇒ 00:06:57.649 Nicolas Sucari: They call it a little bit kind of the Ibisa from Latin America. Because right right now, like these, these weeks New Year’s week, Christmas, a lot of Djs come here to play
34 00:06:58.180 ⇒ 00:07:03.830 Nicolas Sucari: But yeah, I mean, it’s really nice. But the weather wasn’t not so good. I think that doesn’t matter. It’s fine.
35 00:07:05.240 ⇒ 00:07:08.869 Daniel Schonfeld: Yeah, alright interesting. Better than sitting in Connecticut in a cold.
36 00:07:09.318 ⇒ 00:07:10.349 Uttam Kumaran: Is that that’s that.
37 00:07:10.350 ⇒ 00:07:10.689 Nicolas Sucari: Was it.
38 00:07:10.690 ⇒ 00:07:12.200 Uttam Kumaran: That was your deal this year.
39 00:07:12.884 ⇒ 00:07:21.430 Daniel Schonfeld: We just party at a friend’s house. Kids were there, and then I convinced everyone to do a 3 mile run and run into Long Island sounds into polar, plunge.
40 00:07:21.920 ⇒ 00:07:26.179 Uttam Kumaran: Oh, nice, great! It’s a great way to start the year. I feel like.
41 00:07:26.640 ⇒ 00:07:35.209 Daniel Schonfeld: Yeah, I’ve done it a few times. I did it in Montauk, where the waves are like 7 7 feet high. You don’t realize. And then when you get in there like, oh, shit! But the water’s freezing. It’s like 30.
42 00:07:36.070 ⇒ 00:07:45.039 Uttam Kumaran: Yeah, I I’m out of the. I was doing a lot of like cold plunging last year early last year, but then I got out of it, and it’s just so bad
43 00:07:45.180 ⇒ 00:07:47.549 Uttam Kumaran: it does not get easy at all.
44 00:07:47.670 ⇒ 00:07:48.290 Daniel Schonfeld: Yeah.
45 00:07:48.290 ⇒ 00:07:50.590 Uttam Kumaran: And I should not have stopped because.
46 00:07:50.590 ⇒ 00:07:51.910 Daniel Schonfeld: Yeah, you just gotta keep going.
47 00:07:51.910 ⇒ 00:07:53.200 Uttam Kumaran: Yeah, yeah.
48 00:07:54.444 ⇒ 00:07:59.839 Uttam Kumaran: How does the how is the stuff with, you know the m and a stuff and everything like.
49 00:08:00.260 ⇒ 00:08:07.980 Daniel Schonfeld: Yeah, good. They gave us an offer. It’s okay. It’s really not up to me. Ultimately, it’s my father in law had this business for 50 years.
50 00:08:08.410 ⇒ 00:08:13.237 Daniel Schonfeld: So it’s really up to him, and you know he’s struggling
51 00:08:14.180 ⇒ 00:08:19.069 Daniel Schonfeld: with letting go. I guess it’s his baby, you know. He started it when he was 2021.
52 00:08:19.640 ⇒ 00:08:21.589 Daniel Schonfeld: He’s 74.
53 00:08:21.720 ⇒ 00:08:27.109 Daniel Schonfeld: So imagine just doing one business for that long, I mean, I can’t imagine. But
54 00:08:27.570 ⇒ 00:08:41.840 Daniel Schonfeld: it’s tough to let go, but he’s excited, I mean he. I had a meeting with financial advisors. He’s really old school, like money under the mattress. I’m like you can’t put this money under the mattress. You have to put it away. There’s tax stuff, and he’s like, all right, you know.
55 00:08:42.220 ⇒ 00:08:44.860 Daniel Schonfeld: We’ll put it under the oven.
56 00:08:45.670 ⇒ 00:08:50.637 Daniel Schonfeld: so it’s just been been interesting. I’ve really had a how to, you know. Walk everybody to
57 00:08:51.430 ⇒ 00:08:58.859 Daniel Schonfeld: to the water, but it’s it’s it’s been a fun process. I I dare. I say fun. I mean, it’s been brutal because it’s been since July.
58 00:08:59.260 ⇒ 00:08:59.590 Uttam Kumaran: Yeah.
59 00:09:00.070 ⇒ 00:09:06.390 Daniel Schonfeld: Even the even the Due Diligence Company, and the Private Equity Company said this was the most difficult
60 00:09:06.630 ⇒ 00:09:10.679 Daniel Schonfeld: due diligence they’ve ever done for the least amount of money.
61 00:09:11.160 ⇒ 00:09:13.632 Uttam Kumaran: But tell me, why? Tell me why, like, what’s the
62 00:09:14.090 ⇒ 00:09:19.249 Daniel Schonfeld: You know what? It’s the number one thing. Someone told me this when I started my 1st company.
63 00:09:19.680 ⇒ 00:09:23.400 Daniel Schonfeld: the number one most important person in your company is the accounting person.
64 00:09:23.780 ⇒ 00:09:27.960 Daniel Schonfeld: and then, and also to understand your books and don’t outsource it.
65 00:09:29.137 ⇒ 00:09:35.931 Daniel Schonfeld: And then number 2 is a personal assistant. But that’s from a different guy. Depends if you’re Adhd like me. But
66 00:09:37.100 ⇒ 00:09:48.929 Daniel Schonfeld: and it’s years and years and years of really poor systems process for accounting built up over decades, so much so that the best due diligence people in the world
67 00:09:49.210 ⇒ 00:09:52.210 Daniel Schonfeld: over 4 months could not get to a final
68 00:09:52.780 ⇒ 00:10:04.199 Daniel Schonfeld: place where they felt good about all the numbers which is crazy, because there’s not that many transactions. It’s just so convoluted inter company, because there’s 4 different businesses
69 00:10:04.420 ⇒ 00:10:13.679 Daniel Schonfeld: all owned by the same people with different fiscal years. It’s it’s wild, actually, like my mother-in-law forgot to bill a million dollars worth of stuff. She got her nails done forgot.
70 00:10:14.120 ⇒ 00:10:24.970 Daniel Schonfeld: you know. It’s it’s literally that, you know, when you deal with a family business. It’s that crazy, but it’s it was a learning lesson. But it really reiterates, it’s like, have your accounting and your financial shit like
71 00:10:25.350 ⇒ 00:10:26.040 Daniel Schonfeld: if it’s.
72 00:10:26.040 ⇒ 00:10:29.520 Uttam Kumaran: Because it doesn’t matter until it matters. You know, it’s like insurance exactly.
73 00:10:29.520 ⇒ 00:10:38.320 Uttam Kumaran: I feel the same way in that like I mean. And I I actually love. I like the accounting stuff like the financial planning. It’s a lot of data problems. But it’s very like
74 00:10:38.520 ⇒ 00:10:46.370 Uttam Kumaran: you could decide to go the distance. Or you could kind of like, be like, okay? Well, it’s looks the numbers look decent right now. Pay the just pay the tax bill and
75 00:10:46.840 ⇒ 00:10:48.239 Uttam Kumaran: get on with it, but.
76 00:10:48.770 ⇒ 00:10:54.986 Daniel Schonfeld: Done that over the years, and I still am guilty of it.
77 00:10:55.950 ⇒ 00:11:07.870 Daniel Schonfeld: But, man, my my only advice to young entrepreneurs know your know your numbers, do your own financial statements, and don’t take anyone’s word for it, because there’s so many tax benefits that when you pay an account person to do it. They don’t give a shit. They’re not looking for that. They just want.
78 00:11:07.870 ⇒ 00:11:09.210 Uttam Kumaran: So, yeah, that’s
79 00:11:10.040 ⇒ 00:11:25.490 Uttam Kumaran: yeah. I mean, I always say, the hardest part about this is just the whole business as a whole is just like context switching like, I don’t think necessarily that is like hard. But if that was what I was doing, if I if I was spending 2 HA day in quickbooks, we wouldn’t be doing anything, so
80 00:11:25.830 ⇒ 00:11:26.590 Uttam Kumaran: I.
81 00:11:26.590 ⇒ 00:11:28.079 Daniel Schonfeld: There’s a give and take. There’s a fine.
82 00:11:28.080 ⇒ 00:11:32.360 Uttam Kumaran: Give and take, and you kind of just catch whatever is on fire. But
83 00:11:32.470 ⇒ 00:11:37.849 Uttam Kumaran: I I feel lucky that I I’m an I’m an engineer, but I did a lot of finance in school, and I I love
84 00:11:37.990 ⇒ 00:11:39.859 Uttam Kumaran: finance and business so.
85 00:11:39.860 ⇒ 00:11:40.240 Daniel Schonfeld: That’s great!
86 00:11:40.240 ⇒ 00:12:03.469 Uttam Kumaran: I I kind of know I feel, but I also have some like for the accounting team, I’m like, why can’t I see Xyz Xyz. I’m like, it’s a ledger of transactions. Make sure that this goes in this bucket. And then I want to see the outputs like, I’m like, we’re a data company. Give me the give me the right data here, but also they don’t know whether the the meal I accidentally put on the card is like my meal, or like did I.
87 00:12:03.470 ⇒ 00:12:04.130 Daniel Schonfeld: Yeah.
88 00:12:04.130 ⇒ 00:12:05.971 Uttam Kumaran: And I’m like I can’t.
89 00:12:06.850 ⇒ 00:12:10.200 Daniel Schonfeld: I always pushed it. I mean the irs. I got one audit.
90 00:12:10.430 ⇒ 00:12:34.599 Daniel Schonfeld: and I was like, Oh, my God! I’m going to jail! I was like I. I put this meal on all this shit. I was so nervous I hired a law firm. I was like, just keep me out of jail. I’m so terrified I thought I was up every night of the week. The person like could give 2 shits. They’re like, I don’t know you. You overreported $2030,000 worth of stuff here, I was like, am I going to go to like? No, just like come up with a number, and we’ll
91 00:12:34.700 ⇒ 00:12:39.129 Daniel Schonfeld: split the difference. I was like, that’s it. I paid the legal firm more than I paid the irs.
92 00:12:39.130 ⇒ 00:12:40.070 Daniel Schonfeld: Oh, wow!
93 00:12:40.070 ⇒ 00:12:41.160 Daniel Schonfeld: I was so nervous
94 00:12:41.740 ⇒ 00:12:46.700 Daniel Schonfeld: it’s not as bad as you think you you only you only really get in trouble. If you’re really doing something nefarious, and you’re.
95 00:12:46.700 ⇒ 00:12:49.150 Uttam Kumaran: Or you’re not paying any, or like really not paying.
96 00:12:49.150 ⇒ 00:12:54.230 Daniel Schonfeld: Just not filing and not paying. You really got to be an idiot. To get in trouble with the Irs. You really.
97 00:12:54.230 ⇒ 00:13:00.439 Uttam Kumaran: I know some people, though, that are making some money in Crypto or 1099 don’t pay anything, and they’re like.
98 00:13:00.440 ⇒ 00:13:01.180 Daniel Schonfeld: Coming!
99 00:13:01.320 ⇒ 00:13:02.400 Uttam Kumaran: It’s common.
100 00:13:02.400 ⇒ 00:13:06.370 Daniel Schonfeld: It’s a hundred, you you it! You can never get away with it. You might.
101 00:13:06.370 ⇒ 00:13:15.890 Uttam Kumaran: Because it’s like they just the crypto companies are. Gonna give the whatever the W nines or whatever that they paid out. And they’re gonna just see whether you paid the tax.
102 00:13:15.890 ⇒ 00:13:16.850 Daniel Schonfeld: It’s not just like you’re.
103 00:13:16.850 ⇒ 00:13:24.139 Uttam Kumaran: You’re relying on the government’s inability to do that, and then, or maybe to do that and do anything about it right. It’s just simple. Join.
104 00:13:24.420 ⇒ 00:13:35.579 Daniel Schonfeld: Depends on your strategy. If you know you’re gonna have to pay it. And you’re saying, well, they might not come after me for 2 years. In that time I can invest that money and make 5 x, and then when they hit me, I’ll be fine, because I’ll just pay the bill.
105 00:13:35.580 ⇒ 00:13:35.920 Uttam Kumaran: Yeah.
106 00:13:35.920 ⇒ 00:13:39.090 Daniel Schonfeld: You know it’s a big roll of the dice. I don’t like to fuck with the.
107 00:13:39.090 ⇒ 00:13:40.780 Uttam Kumaran: I don’t either. Yeah.
108 00:13:40.780 ⇒ 00:13:42.220 Daniel Schonfeld: Not worth it ever I really.
109 00:13:42.220 ⇒ 00:13:47.580 Uttam Kumaran: I don’t do that at all. I’m like we can’t pay for it. And we we’re not gonna do this because that and legal.
110 00:13:47.780 ⇒ 00:13:53.240 Uttam Kumaran: I’m like, I like, I we just I got. We’re really good lawyer, and I’m like everything legal goes to this person.
111 00:13:53.460 ⇒ 00:14:04.279 Uttam Kumaran: I don’t want to do legal zoom for any of this stuff like when a lot of people come to me and they’ll be like, Oh, who do you use for a lawyer? I’m like this person. It’s like 400 bucks an hour. They’re like what I legal zoom, said 20 bucks for.
112 00:14:04.670 ⇒ 00:14:05.770 Uttam Kumaran: and I’m like
113 00:14:05.880 ⇒ 00:14:13.229 Uttam Kumaran: dude. I can only play a certain amount of games. This is not a game I’m interested in, like, I don’t know anything about this.
114 00:14:13.230 ⇒ 00:14:14.969 Daniel Schonfeld: 6 year old to watch a Youtube video.
115 00:14:15.240 ⇒ 00:14:27.040 Uttam Kumaran: No, but that’s it’s like people optimizing for the wrong thing. They’re like, how can you afford them like just you have to make some money dude. I don’t know. Things are cost money. What do you mean? Things cost money? Yeah.
116 00:14:28.180 ⇒ 00:14:28.830 Daniel Schonfeld: Perfect.
117 00:14:28.830 ⇒ 00:14:38.780 Uttam Kumaran: Okay, great. So I know it’s been a while. So we wanted to kind of just see what you know. Next steps are on the skew list. I have it up on my side. Maybe I can share or just get a sense from you on like
118 00:14:41.640 ⇒ 00:14:44.709 Uttam Kumaran: sort of we’re if we’re still good to keep keep working on it.
119 00:14:44.710 ⇒ 00:14:50.749 Daniel Schonfeld: Yeah, a hundred percent. Let’s look at where we are. Sorry. I’ve been really out of the loop, obviously for a while. So.
120 00:14:52.310 ⇒ 00:14:57.675 Uttam Kumaran: Cool. So basically, we have an instructions page here, it’s the A
121 00:14:58.590 ⇒ 00:15:25.870 Uttam Kumaran: we just go through. And here is what we’ve basically gathered. We looked at all the skills in the Asia file all the skews from shopify Amazon Walmart. We have a clean skew column which basically looks to do the matching between Asia and then the platform skews. We look at. If this, the skew is present in one or more of the platforms when the latest order. Date is what’s this? We basically create a status field which is like active or inactive.
122 00:15:26.040 ⇒ 00:15:31.790 Uttam Kumaran: Well, we last, we talked. We’re like we should just remove everything that’s like least that, like active, less
123 00:15:31.920 ⇒ 00:15:34.545 Uttam Kumaran: active, more than a year ago.
124 00:15:35.650 ⇒ 00:15:56.779 Uttam Kumaran: the reason for this. And then also, we basically provided like this is what we were going to send to you guys like go through and just check Mark. So just to walk through this again. This is our master skew table. We’re pulling from Asia skew list, and we have a master platform list. We create a consolidated skew table here. Each of these has what it is in Asia, what is in the platform
125 00:15:57.461 ⇒ 00:16:02.900 Uttam Kumaran: we talked about cleaning some stuff up with the dashes and some random stuff like that. We basically have a
126 00:16:03.340 ⇒ 00:16:08.590 Uttam Kumaran: of process to do that, and then basically give the status of inactive or active
127 00:16:08.930 ⇒ 00:16:14.910 Uttam Kumaran: what you know we were. Gonna ask for you to do first.st And I think we talked about this is basically give you the ability to say
128 00:16:15.439 ⇒ 00:16:29.739 Uttam Kumaran: whether we wanted to leave it as active, whether we wanted to delete it or any modifications to make. And then, of course, I think the larger goal was to sort of have this file or another interface that basically is the home for for all skew. So I guess I’ll stop there and.
129 00:16:29.740 ⇒ 00:16:30.070 Daniel Schonfeld: Yeah.
130 00:16:31.274 ⇒ 00:16:39.789 Daniel Schonfeld: Okay, let me just ask some questions, so I can orient Asia, the Asia list skew that came from from Ian from.
131 00:16:39.790 ⇒ 00:16:40.110 Uttam Kumaran: Yes.
132 00:16:40.780 ⇒ 00:16:42.970 Daniel Schonfeld: The what is platform skew again.
133 00:16:43.540 ⇒ 00:16:48.519 Uttam Kumaran: This is the skews we took from unleashed ship station and shopify.
134 00:16:48.900 ⇒ 00:16:50.799 Daniel Schonfeld: Okay? And has it been deduped.
135 00:16:53.450 ⇒ 00:16:54.070 Uttam Kumaran: You want to go to.
136 00:16:54.070 ⇒ 00:16:54.730 Nicolas Sucari: I mean.
137 00:16:54.880 ⇒ 00:17:01.709 Nicolas Sucari: Yes, I mean these these platform skill list. We get it from unleash shipstation, shopify Walmart and Amazon
138 00:17:01.790 ⇒ 00:17:29.850 Nicolas Sucari: are all of the skews we’ve identified in all of the platforms. We gather everything we put it here, and in the other table the skew table we match, which ones are there. So you you wouldn’t find duplicates unless unless there is like a difference between how they are written. Okay, if they have the same code. Yes, they should be duplicated. And we have that selling platform column where? Where? We are saying, Hey, we found this in Amazon, shopify analytics.
139 00:17:31.110 ⇒ 00:17:33.039 Daniel Schonfeld: The last part once again.
140 00:17:33.040 ⇒ 00:17:35.739 Uttam Kumaran: For for example, if you take this A/CIMP.
141 00:17:35.740 ⇒ 00:17:36.080 Daniel Schonfeld: Nope.
142 00:17:36.080 ⇒ 00:17:39.740 Uttam Kumaran: This is not only in Asia, but it’s also in Amazon. Shopify, unleash.
143 00:17:39.740 ⇒ 00:17:40.280 Nicolas Sucari: Exactly.
144 00:17:40.280 ⇒ 00:17:45.199 Uttam Kumaran: The last order was on December 4, th 2023.
145 00:17:45.810 ⇒ 00:17:46.690 Nicolas Sucari: 3, yeah.
146 00:17:46.690 ⇒ 00:17:48.649 Daniel Schonfeld: What about ones that there’s like.
147 00:17:48.900 ⇒ 00:17:53.009 Daniel Schonfeld: you know, like cf, bar 1, 5, 2, the 2 below where you are
148 00:17:53.820 ⇒ 00:17:59.310 Daniel Schonfeld: like there’s a space there. I know I’ve seen ones where it’s the same one in another platform, but there’s no space.
149 00:17:59.550 ⇒ 00:18:03.260 Daniel Schonfeld: But do you have any of those? Where did you keep those? Or did you dupe them out.
150 00:18:03.260 ⇒ 00:18:06.179 Uttam Kumaran: We’ve we’ve cleaned. I I guess.
151 00:18:06.370 ⇒ 00:18:09.010 Uttam Kumaran: Luke, can you talk about like what the actual matching.
152 00:18:09.562 ⇒ 00:18:13.289 Luke Daque: We did a little bit of cleaning, but it wasn’t.
153 00:18:13.600 ⇒ 00:18:20.572 Luke Daque: We didn’t do anything related to spaces. But it’s like when there’s a suffix, for example, like
154 00:18:21.390 ⇒ 00:18:26.523 Luke Daque: I can’t remember the exact stuff, but like, if there’s a suffix that’s
155 00:18:27.130 ⇒ 00:18:29.329 Luke Daque: different. But, like the 1st few
156 00:18:29.650 ⇒ 00:18:34.389 Luke Daque: characters are the same. Then we consolidated it. That’s 1 or something like that.
157 00:18:34.540 ⇒ 00:18:35.340 Daniel Schonfeld: Okay.
158 00:18:35.490 ⇒ 00:18:40.049 Luke Daque: Yeah, but in terms of spaces, I don’t think we did anything about that.
159 00:18:40.050 ⇒ 00:18:43.159 Uttam Kumaran: But that. But that sort of matching algorithm, we can change.
160 00:18:43.460 ⇒ 00:18:51.140 Daniel Schonfeld: Yeah, no, no, that’s fine, because I don’t know what the right one is. If there’s 2 conflicting
161 00:18:53.380 ⇒ 00:18:57.749 Daniel Schonfeld: yeah ways they’re being displayed. We we got to figure out which one is actually right.
162 00:18:58.440 ⇒ 00:18:59.010 Uttam Kumaran: Okay.
163 00:18:59.200 ⇒ 00:19:00.070 Daniel Schonfeld: It’s good that you didn’t.
164 00:19:00.070 ⇒ 00:19:00.540 Nicolas Sucari: You know.
165 00:19:00.886 ⇒ 00:19:01.479 Daniel Schonfeld: On, that.
166 00:19:01.530 ⇒ 00:19:04.694 Nicolas Sucari: Yeah, we we didn’t want it to like,
167 00:19:05.240 ⇒ 00:19:24.000 Nicolas Sucari: yeah, match everything and try to reduce the amount of skews, because we don’t know which ones you’re using, and how was the best way to write them? So that’s why we try to keep everything. We just clean some of the 1st digits that we have in some skews that were the same. But that’s the only thing we did.
168 00:19:24.400 ⇒ 00:19:31.930 Daniel Schonfeld: The only other thing is, you may have a skew that is active in should be active in one platform and inactive in another.
169 00:19:33.520 ⇒ 00:19:36.320 Daniel Schonfeld: So how did you go about?
170 00:19:36.990 ⇒ 00:19:41.409 Daniel Schonfeld: How did you get the last order date? What is? Where’s the last order? Date come from that data.
171 00:19:43.480 ⇒ 00:20:02.679 Nicolas Sucari: Look to answer. But yes, it’s coming from the selling platforms where we find where we’ve obviously the Asian list doesn’t have the latest order. So if we found an order with one of those skews from the selling platforms, we added the latest one that we have, so that we know the the latest day that someone ordered that product.
172 00:20:03.090 ⇒ 00:20:08.509 Daniel Schonfeld: Yeah, but you wouldn’t have it on the import side. So like on the Asia side, you don’t have that information, do you?
173 00:20:08.510 ⇒ 00:20:09.579 Nicolas Sucari: We don’t exactly.
174 00:20:09.580 ⇒ 00:20:10.609 Nicolas Sucari: No, we don’t.
175 00:20:10.610 ⇒ 00:20:13.639 Daniel Schonfeld: Okay, might make sense to have a status.
176 00:20:15.340 ⇒ 00:20:32.460 Daniel Schonfeld: It might make sense to have a a second status which would be Asia status. Because you want us to go in and say, inactive or active, and actually go go through that of what it should be. Something may be active in our system, but active, and should be active in Asia system.
177 00:20:33.110 ⇒ 00:20:37.720 Uttam Kumaran: So there are. There are several items here where there’s no, there’s been no match.
178 00:20:37.830 ⇒ 00:20:40.890 Uttam Kumaran: right? Or we couldn’t basically figure out how to do the match.
179 00:20:41.530 ⇒ 00:20:45.960 Uttam Kumaran: my question is, are like, and these are coming from the Asia list is like, are
180 00:20:46.550 ⇒ 00:20:54.000 Uttam Kumaran: like, yes, or either should these be deleted? But again, there’s like thousands and thousands of them. So I think, even broader, we’ll have to think about some
181 00:20:54.500 ⇒ 00:20:59.400 Uttam Kumaran: scheme that says like whether these are right, because that this will be quite a bit to go through.
182 00:20:59.770 ⇒ 00:21:00.589 Daniel Schonfeld: I think
183 00:21:00.590 ⇒ 00:21:07.830 Daniel Schonfeld: maybe it’s helpful for you guys to get well. A lot of these are just an Asia system. So these are all built up over the years
184 00:21:08.240 ⇒ 00:21:14.479 Daniel Schonfeld: on our side, the Amazon ship station unleash the E-com side. We we would never even touch those.
185 00:21:14.480 ⇒ 00:21:15.180 Uttam Kumaran: Okay.
186 00:21:15.445 ⇒ 00:21:26.069 Daniel Schonfeld: A lot of them, obviously. So you wouldn’t see a last order date or be able to match with anything because they wouldn’t have never appeared in our on the E-com side. We cherry picked what we wanted to sell.
187 00:21:26.230 ⇒ 00:21:29.530 Daniel Schonfeld: but that doesn’t mean that they’re not selling it
188 00:21:31.610 ⇒ 00:21:37.869 Daniel Schonfeld: at either the retail stores or to at wholesale to other retailers. So
189 00:21:38.050 ⇒ 00:21:49.119 Daniel Schonfeld: what we probably want to do is do a similar exercise where we get the lab. I don’t know what the what the sample size should be, but orders from the last year, 2 years.
190 00:21:49.510 ⇒ 00:21:49.980 Uttam Kumaran: 2 years.
191 00:21:49.980 ⇒ 00:21:52.559 Daniel Schonfeld: From the Asia side, so at least you can
192 00:21:52.790 ⇒ 00:21:57.220 Daniel Schonfeld: then show them, say, here are all the products. Same exercise you did with our side
193 00:21:58.540 ⇒ 00:22:00.530 Daniel Schonfeld: that have been active or inactive.
194 00:22:00.660 ⇒ 00:22:05.900 Daniel Schonfeld: and then they’ll go through on their end. Say, hey, anything that’s got inactive
195 00:22:06.140 ⇒ 00:22:08.979 Daniel Schonfeld: from the Asia side. You guys need to go through and just tell us
196 00:22:09.300 ⇒ 00:22:13.259 Daniel Schonfeld: can we get rid of it? But I know what they’re gonna say they’re saying, why do we have to get rid of it at all.
197 00:22:14.770 ⇒ 00:22:19.029 Uttam Kumaran: Yeah, I mean. Well, then, why keep it at all? That’s been my question.
198 00:22:19.350 ⇒ 00:22:23.349 Daniel Schonfeld: Yeah. Have an active list of skews somewhere.
199 00:22:23.350 ⇒ 00:22:36.930 Uttam Kumaran: But that’s fine. But then, at least there, we need to think about some way of tagging or some sort of method of saying it. But also it’s fine. If Asia wants to be like, we have all skews for all time, we still have opportunity to clean them out of the platform systems.
200 00:22:37.100 ⇒ 00:22:37.420 Daniel Schonfeld: Yeah.
201 00:22:37.688 ⇒ 00:22:41.180 Uttam Kumaran: And then basically again, begin. This is the way to show that, like
202 00:22:41.860 ⇒ 00:22:44.599 Uttam Kumaran: all the skews here are basically, yeah. So.
203 00:22:44.600 ⇒ 00:22:45.310 Daniel Schonfeld: I got it.
204 00:22:45.310 ⇒ 00:22:46.790 Uttam Kumaran: Let’s ask that from Ian.
205 00:22:48.400 ⇒ 00:22:56.779 Daniel Schonfeld: Yeah, just for the last 2 years. Fine! Just by skew, you could say anything with the dollar. Anything with a dollar or more. Just give me a list of skews that
206 00:22:56.950 ⇒ 00:23:00.180 Daniel Schonfeld: have some kind of sale in the last 2024 months.
207 00:23:00.400 ⇒ 00:23:01.549 Uttam Kumaran: Okay. Okay. Great.
208 00:23:01.550 ⇒ 00:23:09.240 Daniel Schonfeld: Thanks, and everything else we’ll assume is garbage and then from there.
209 00:23:09.670 ⇒ 00:23:11.219 Daniel Schonfeld: what do we do from there?
210 00:23:11.721 ⇒ 00:23:18.649 Daniel Schonfeld: We need to make sure we need to do the matching. Make sure that the actual skew. The way it’s written is correct.
211 00:23:19.460 ⇒ 00:23:19.960 Uttam Kumaran: Yes.
212 00:23:20.170 ⇒ 00:23:21.749 Daniel Schonfeld: So I don’t know if you want to have like
213 00:23:22.550 ⇒ 00:23:29.359 Daniel Schonfeld: different assignments as we go like one would be skew integrity or something like that.
214 00:23:29.600 ⇒ 00:23:34.939 Daniel Schonfeld: Then we need to do the description like, what is the skew, and do all those descriptions match up?
215 00:23:36.470 ⇒ 00:23:41.889 Daniel Schonfeld: There’s usually model numbers that go with each skew so like. Remember the sheet that I shared with you.
216 00:23:41.890 ⇒ 00:23:42.390 Uttam Kumaran: Yeah.
217 00:23:42.390 ⇒ 00:23:43.220 Daniel Schonfeld: System.
218 00:23:43.220 ⇒ 00:23:43.540 Uttam Kumaran: Yeah.
219 00:23:43.540 ⇒ 00:23:48.730 Daniel Schonfeld: We kind of have to go across the lane of the line and start filling in all that data.
220 00:23:48.910 ⇒ 00:23:49.520 Uttam Kumaran: Okay.
221 00:23:49.520 ⇒ 00:23:55.519 Nicolas Sucari: But model numbers is not like they are not different skews for each of the models.
222 00:23:57.040 ⇒ 00:24:00.210 Daniel Schonfeld: There’s a different model number for each skew. Yeah.
223 00:24:02.100 ⇒ 00:24:06.019 Nicolas Sucari: But the skew is the same same name, like same Id.
224 00:24:06.020 ⇒ 00:24:08.959 Uttam Kumaran: You could just think of model as like a skew alternative. Basically.
225 00:24:09.790 ⇒ 00:24:10.569 Nicolas Sucari: Oh, okay.
226 00:24:11.060 ⇒ 00:24:11.720 Daniel Schonfeld: Yeah.
227 00:24:12.010 ⇒ 00:24:15.260 Uttam Kumaran: But that’s something that I’m gonna look at. I’ll so I’ll get that sheet and tag it.
228 00:24:15.680 ⇒ 00:24:17.360 Daniel Schonfeld: And all that stuff.
229 00:24:17.360 ⇒ 00:24:18.200 Uttam Kumaran: Yeah.
230 00:24:18.406 ⇒ 00:24:26.063 Daniel Schonfeld: We’re not gonna be able to do every single thing, but at least we can start with a list that makes sense. But the the thing I actually care about the most at the end of this
231 00:24:26.440 ⇒ 00:24:37.469 Daniel Schonfeld: is looking at all the active skews and getting the right pricing costing in, because to me that’s where I move the needle. Nobody knows what anything really costs. It’s all different in every system.
232 00:24:39.070 ⇒ 00:24:41.979 Uttam Kumaran: So I know there is that that also exists.
233 00:24:42.604 ⇒ 00:24:47.490 Uttam Kumaran: In that other sheet, Nico. The cost also exist in unleashed.
234 00:24:48.540 ⇒ 00:24:48.950 Nicolas Sucari: Yes.
235 00:24:48.950 ⇒ 00:24:50.020 Uttam Kumaran: So unleash.
236 00:24:50.020 ⇒ 00:24:50.560 Nicolas Sucari: Okay.
237 00:24:50.560 ⇒ 00:24:53.420 Daniel Schonfeld: Let me just say one thing before we get too far different costs.
238 00:24:53.860 ⇒ 00:24:57.739 Daniel Schonfeld: There’s gonna be the fob China cost like what it cost us
239 00:24:58.430 ⇒ 00:25:00.300 Daniel Schonfeld: to buy it from the factory.
240 00:25:01.410 ⇒ 00:25:02.910 Daniel Schonfeld: Then there’s a cost
241 00:25:03.040 ⇒ 00:25:15.960 Daniel Schonfeld: of what? What? So Asia buys it from the factory right Asia connection, and then Asia is the hub, sells it to pull parts to go, sells it to island. Rec. The retail stores sells it
242 00:25:15.960 ⇒ 00:25:19.929 Daniel Schonfeld: yay different dealers, so that one number is critical.
243 00:25:20.650 ⇒ 00:25:24.089 Daniel Schonfeld: You don’t have to worry so much at this moment about what Asia.
244 00:25:24.090 ⇒ 00:25:24.490 Uttam Kumaran: Unleash.
245 00:25:24.490 ⇒ 00:25:25.380 Daniel Schonfeld: Support.
246 00:25:25.380 ⇒ 00:25:25.950 Uttam Kumaran: Okay.
247 00:25:26.540 ⇒ 00:25:34.059 Daniel Schonfeld: To and Unlea that that waterfalls down to shopify, unleash. Let’s forget about that for the moment. It’s like what is the true cost that we pay
248 00:25:34.460 ⇒ 00:25:42.370 Daniel Schonfeld: as an enterprise to the factory and getting that number in there and then from there we’re gonna do a simple formula
249 00:25:42.830 ⇒ 00:25:47.839 Daniel Schonfeld: across the board, which I’ll do. I’ll tell you what it is and say
250 00:25:48.810 ⇒ 00:25:56.029 Daniel Schonfeld: for black and Decker, and you can actually see it in my sheet. How I calculate it. There’s already a formula in there
251 00:25:56.180 ⇒ 00:25:59.229 Daniel Schonfeld: that it’s cost plus 7%
252 00:25:59.400 ⇒ 00:26:06.750 Daniel Schonfeld: plus the license fee for black and Decker. We include that in there. And that’s what we pay Asia for any skews they sell us
253 00:26:07.650 ⇒ 00:26:14.100 Daniel Schonfeld: because we buy from them, and then everybody else will come up with a standard wholesale price.
254 00:26:15.830 ⇒ 00:26:22.250 Daniel Schonfeld: and then, once all those costing and pricing all, all that’s in this sheet, we can share it
255 00:26:23.100 ⇒ 00:26:31.109 Daniel Schonfeld: with everybody across the company and say, Is this what you want to charge people. Is there any nuance, any discounts you want to apply to people.
256 00:26:31.890 ⇒ 00:26:32.570 Nicolas Sucari: I mean so.
257 00:26:32.570 ⇒ 00:26:32.960 Uttam Kumaran: Ian.
258 00:26:32.960 ⇒ 00:26:34.640 Nicolas Sucari: We all need to go.
259 00:26:35.100 ⇒ 00:26:37.889 Uttam Kumaran: Is Ian gonna have this this fob.
260 00:26:38.940 ⇒ 00:26:39.690 Daniel Schonfeld: Yes.
261 00:26:39.690 ⇒ 00:26:40.330 Uttam Kumaran: Okay.
262 00:26:41.480 ⇒ 00:26:42.570 Uttam Kumaran: Sorry. Go ahead. Nico.
263 00:26:42.950 ⇒ 00:26:48.279 Daniel Schonfeld: Yes, he’ll have that. He should also have what we’re currently charging everybody.
264 00:26:49.220 ⇒ 00:26:51.519 Nicolas Sucari: So we can see what the current price is.
265 00:26:53.290 ⇒ 00:27:01.100 Nicolas Sucari: Do do Asia? Or do you have, like orders, purchase orders to Asia or from Asia, that
266 00:27:01.590 ⇒ 00:27:04.949 Nicolas Sucari: when when you buy the product from them, so that we can check.
267 00:27:04.950 ⇒ 00:27:05.850 Uttam Kumaran: We’ll ask him for that.
268 00:27:06.660 ⇒ 00:27:07.910 Nicolas Sucari: Yeah, okay.
269 00:27:08.230 ⇒ 00:27:11.029 Daniel Schonfeld: I can get that from 0. Our accounting system, too.
270 00:27:11.290 ⇒ 00:27:11.990 Uttam Kumaran: Okay.
271 00:27:11.990 ⇒ 00:27:15.070 Nicolas Sucari: And that, okay? And my other question, my other.
272 00:27:15.340 ⇒ 00:27:19.939 Nicolas Sucari: yeah, what I’m thinking is, we we need after we have like these costs.
273 00:27:20.110 ⇒ 00:27:22.939 Nicolas Sucari: And yeah, what is the wholesale place that we wanna
274 00:27:23.050 ⇒ 00:27:42.189 Nicolas Sucari: sent to everyone? We will need to go back to all of the different selling platforms, shopify Amazon Walmart, and try to figure out how to include these new pricing for all these queues in there right costs and pricings. In that way we’ll have cogs for every product, and the correct price.
275 00:27:42.420 ⇒ 00:27:48.259 Daniel Schonfeld: Yeah, it typically starts with unleashed right? I think, pushes it all out. So I think if unleashed as well.
276 00:27:48.260 ⇒ 00:27:49.050 Uttam Kumaran: Correct.
277 00:27:49.050 ⇒ 00:27:51.450 Daniel Schonfeld: Everything else in theory should be right.
278 00:27:52.550 ⇒ 00:27:53.120 Daniel Schonfeld: So it’s weird.
279 00:27:53.120 ⇒ 00:27:55.439 Daniel Schonfeld: Yeah place to update it. I think.
280 00:27:55.740 ⇒ 00:28:01.179 Uttam Kumaran: I just don’t think it gets removed like I don’t think it syncs entirely
281 00:28:02.670 ⇒ 00:28:08.489 Uttam Kumaran: so we’ll have to check that. But again, I I know exactly where to go get that. I’ve talked to chuck about that a ton so.
282 00:28:08.620 ⇒ 00:28:09.410 Daniel Schonfeld: Yeah.
283 00:28:09.410 ⇒ 00:28:14.229 Daniel Schonfeld: Also, I, as long as unleashed, has the right number, and it’s kicking it up to
284 00:28:14.410 ⇒ 00:28:17.739 Daniel Schonfeld: 0. My accounting system. That means my numbers will be right.
285 00:28:17.740 ⇒ 00:28:29.099 Uttam Kumaran: And it’s at least getting billed that way. Because, yeah, it’s it’s honestly, the platforms just want to report on profit metrics. But they don’t. They’re not the source of truth. So even on our side, too, we can just ditch
286 00:28:29.260 ⇒ 00:28:34.160 Uttam Kumaran: like shopify’s notion of profit, and just use sub our costing.
287 00:28:34.540 ⇒ 00:28:44.999 Daniel Schonfeld: That’s right. It’s just this is all going to be in phases. We can’t do everything at once. There’s too much to do. So it’s really like data integrity first, st or the skews right? Or the descriptions right? Is the cost right?
288 00:28:45.460 ⇒ 00:28:47.779 Daniel Schonfeld: And then pushing that out
289 00:28:47.950 ⇒ 00:28:56.619 Daniel Schonfeld: to the 1st p to the largest buyers of those products which is internally us pull parts to go. Island Rec, which is the retail stores.
290 00:28:56.720 ⇒ 00:29:11.569 Daniel Schonfeld: and then we can start to go down the line of the of all the customers. Because I want to start pricing this right. A big part of how we’re gonna do. Well, if this transaction goes through is is an earn out. I can’t properly price people, if I don’t know what our actual cost is and what we’re currently charging them.
291 00:29:12.134 ⇒ 00:29:21.949 Daniel Schonfeld: And I need a place to go look at all that. And then I need to figure out what I’m gonna charge them over time over the next 2 years in order to get to the numbers I need to hit right now. I’m flying a bit blind.
292 00:29:22.340 ⇒ 00:29:25.469 Uttam Kumaran: Okay, perfect. And then, if I was just to bring in this
293 00:29:25.990 ⇒ 00:29:28.160 Uttam Kumaran: the 2024 official skew.
294 00:29:28.160 ⇒ 00:29:28.480 Daniel Schonfeld: Yeah.
295 00:29:28.757 ⇒ 00:29:32.090 Uttam Kumaran: Just cause. I know there is a lot. There’s a lot of
296 00:29:32.730 ⇒ 00:29:36.630 Uttam Kumaran: numbers on here, so mainly we’re looking at this.
297 00:29:37.020 ⇒ 00:29:39.300 Daniel Schonfeld: Yep, this is the fob costing.
298 00:29:39.840 ⇒ 00:29:40.270 Daniel Schonfeld: Yep.
299 00:29:40.270 ⇒ 00:29:41.800 Uttam Kumaran: And then we have, okay.
300 00:29:41.800 ⇒ 00:29:43.400 Daniel Schonfeld: That’s the latest that I have. Yeah.
301 00:29:43.400 ⇒ 00:29:44.480 Uttam Kumaran: Okay. Okay.
302 00:29:44.480 ⇒ 00:29:46.580 Daniel Schonfeld: I wouldn’t use that as the true North. It sure
303 00:29:46.580 ⇒ 00:29:51.050 Daniel Schonfeld: come from Asia and then pull parts to go right there. Column P.
304 00:29:51.620 ⇒ 00:29:52.630 Daniel Schonfeld: It should be.
305 00:29:52.630 ⇒ 00:29:58.460 Nicolas Sucari: That’s fob, plus the 7% plus the license. Right?
306 00:30:01.570 ⇒ 00:30:02.330 Daniel Schonfeld: So.
307 00:30:02.330 ⇒ 00:30:09.170 Nicolas Sucari: Yeah, I think this is the fob cost that we were seeing in the other column, plus the 7%.
308 00:30:10.430 ⇒ 00:30:11.910 Uttam Kumaran: Not really no.
309 00:30:12.380 ⇒ 00:30:12.700 Daniel Schonfeld: No.
310 00:30:12.700 ⇒ 00:30:14.679 Uttam Kumaran: This is, yeah.
311 00:30:14.680 ⇒ 00:30:20.070 Daniel Schonfeld: I would take a second when you guys have time and just follow it follow the formulas, but it goes.
312 00:30:20.530 ⇒ 00:30:22.018 Uttam Kumaran: It’s like freight plus
313 00:30:22.860 ⇒ 00:30:27.639 Uttam Kumaran: yeah, you, you basically calculate what the sell is, and then you back into what to pay.
314 00:30:27.640 ⇒ 00:30:28.100 Nicolas Sucari: Oh!
315 00:30:28.100 ⇒ 00:30:33.730 Daniel Schonfeld: Exactly. So we do the You. We figure out the landed cost is the number. One thing you want to figure out, which is W.
316 00:30:33.880 ⇒ 00:30:34.340 Uttam Kumaran: Yeah.
317 00:30:34.340 ⇒ 00:30:34.720 Nicolas Sucari: Yeah.
318 00:30:34.720 ⇒ 00:30:40.700 Daniel Schonfeld: That’s the one thing that it’s good to understand, which is the landed is just the raw fob cost
319 00:30:41.110 ⇒ 00:30:44.269 Daniel Schonfeld: plus freight duty tariff.
320 00:30:44.800 ⇒ 00:30:45.440 Nicolas Sucari: Okay.
321 00:30:45.440 ⇒ 00:30:54.889 Daniel Schonfeld: That’s really it’s freight duty, I think. And then you get to a landed number, and then we have to apply a black and Decker royalty fee to that number.
322 00:30:55.440 ⇒ 00:30:58.270 Daniel Schonfeld: And I think the 7% is what margin
323 00:30:58.881 ⇒ 00:31:03.739 Daniel Schonfeld: they want to make on it off of us. And then we come to a pool parts to go wholesale. Price.
324 00:31:04.160 ⇒ 00:31:04.830 Uttam Kumaran: Great.
325 00:31:04.830 ⇒ 00:31:06.279 Daniel Schonfeld: We work off the cost?
326 00:31:07.570 ⇒ 00:31:09.430 Daniel Schonfeld: We’re going to do things a bit differently
327 00:31:09.920 ⇒ 00:31:12.210 Daniel Schonfeld: when we charge other customers, though.
328 00:31:12.727 ⇒ 00:31:17.170 Daniel Schonfeld: not internal, is we’re gonna do it a bit reverse. Look at the market.
329 00:31:17.730 ⇒ 00:31:22.389 Daniel Schonfeld: What those rates are! What is a typical price for a pool pump in the market.
330 00:31:23.340 ⇒ 00:31:25.570 Daniel Schonfeld: and then go work that way.
331 00:31:26.260 ⇒ 00:31:34.599 Daniel Schonfeld: It’s this is a backwards way of doing it, the way we’re doing it now. It’s good for internal, because we don’t want to charge ourselves too much money. The money’s all going to the same place.
332 00:31:34.840 ⇒ 00:31:39.119 Daniel Schonfeld: Yeah. But when we charge customers, this is how he does it, which is not right
333 00:31:40.260 ⇒ 00:31:43.130 Daniel Schonfeld: you should he? He almost feels bad making money.
334 00:31:43.670 ⇒ 00:31:45.709 Daniel Schonfeld: which is not the right way to run a business.
335 00:31:46.220 ⇒ 00:31:47.529 Uttam Kumaran: Yeah, okay, makes sense.
336 00:31:48.940 ⇒ 00:31:51.685 Uttam Kumaran: Okay, great. I think we have enough. Let’s
337 00:31:52.870 ⇒ 00:32:04.280 Uttam Kumaran: so we’ll get back to you. I think we’ll we’ll probably just be able to make this all next week and then let’s hit Ian today, Nico, with the questions for these for this data, I know it took a little bit, so I want to give him some lead time.
338 00:32:04.400 ⇒ 00:32:09.360 Uttam Kumaran: If we need to hop on a chat with him, we should. The most critical thing is to just get
339 00:32:09.530 ⇒ 00:32:13.390 Uttam Kumaran: the last 2 years of sales by skew from Asia.
340 00:32:13.740 ⇒ 00:32:15.679 Uttam Kumaran: Then we can start to knock some of that off.
341 00:32:15.860 ⇒ 00:32:18.769 Uttam Kumaran: and then we’ll move in some of the items from the other sheet.
342 00:32:20.960 ⇒ 00:32:29.288 Daniel Schonfeld: Yeah, and then we can start sharing it with the rest of the team, and I’ll send it around and say, look, I’ll even call a meeting. I’ll go out to Long Island. We’ll all sit around it. Maybe we could do a call with you.
343 00:32:29.470 ⇒ 00:32:29.950 Uttam Kumaran: Okay.
344 00:32:29.950 ⇒ 00:32:36.170 Daniel Schonfeld: Start to bang through it. I think it’s gonna be important, though, because there’s so much data
345 00:32:36.770 ⇒ 00:32:41.540 Daniel Schonfeld: to start looking at. What are the the highest grossing skews.
346 00:32:41.790 ⇒ 00:32:44.120 Daniel Schonfeld: and we may have to prioritize by that.
347 00:32:44.380 ⇒ 00:32:44.940 Uttam Kumaran: Yeah.
348 00:32:44.940 ⇒ 00:32:48.569 Daniel Schonfeld: And say, Let’s alright. Let’s just knock out the top 20 at least to start.
349 00:32:49.050 ⇒ 00:32:51.899 Daniel Schonfeld: you know, so we can make some some big progress here.
350 00:32:53.062 ⇒ 00:32:59.130 Daniel Schonfeld: So I think a priority list would be important by revenue over the last year or 2 from the data that you get from Ian
351 00:33:01.028 ⇒ 00:33:06.600 Daniel Schonfeld: and then you could always pull that from shopify or Amazon, or if Ben can provide that from our side.
352 00:33:07.230 ⇒ 00:33:07.810 Uttam Kumaran: Okay.
353 00:33:08.020 ⇒ 00:33:08.380 Daniel Schonfeld: But it’s.
354 00:33:08.380 ⇒ 00:33:08.890 Uttam Kumaran: And then.
355 00:33:08.890 ⇒ 00:33:10.390 Daniel Schonfeld: Pecker from our side.
356 00:33:10.390 ⇒ 00:33:10.770 Uttam Kumaran: Okay.
357 00:33:10.820 ⇒ 00:33:12.080 Daniel Schonfeld: Meeting with Bd.
358 00:33:12.390 ⇒ 00:33:14.816 Uttam Kumaran: And then, Luke, I have one other way.
359 00:33:15.620 ⇒ 00:33:19.550 Uttam Kumaran: to do. Basically, this matching, you can basically do like a distance
360 00:33:19.890 ⇒ 00:33:22.950 Uttam Kumaran: sort of algorithm. If you look in Snowflake, there’s a thing called like
361 00:33:23.240 ⇒ 00:33:30.059 Uttam Kumaran: some German word, basically what it does. It looks like at all the characters and looks like the distance between all of them. I’ll show you how to run that
362 00:33:30.200 ⇒ 00:33:38.969 Uttam Kumaran: I think that’ll be a little bit better than just matching on the prefix or suffix and then that way for stuff we can’t match. We’ll at least have a priority ranking
363 00:33:39.390 ⇒ 00:33:46.529 Uttam Kumaran: of the the distance. Then we’ll sort it there, so we’ll sort by 1st gross sales. Second, we’ll sort by last order rate.
364 00:33:46.700 ⇒ 00:33:50.450 Uttam Kumaran: and then we’ll sort by like the matching distance for the rest.
365 00:33:50.720 ⇒ 00:33:53.449 Uttam Kumaran: and then that’ll I think that’ll give us enough to go with.
366 00:33:54.020 ⇒ 00:34:02.349 Uttam Kumaran: and then, at least once we have the 1st sort of bunch confirmed we could start to look into. How do we make updates in the in the actual platforms.
367 00:34:03.150 ⇒ 00:34:03.690 Daniel Schonfeld: Yeah.
368 00:34:04.170 ⇒ 00:34:05.150 Luke Daque: Yeah, cool.
369 00:34:05.970 ⇒ 00:34:09.169 Uttam Kumaran: Yeah. And even if we had to do it here and just manually go in and do at least.
370 00:34:09.170 ⇒ 00:34:09.710 Uttam Kumaran: yeah.
371 00:34:09.710 ⇒ 00:34:14.209 Daniel Schonfeld: Money. It would make already a huge difference just doing it manual to start.
372 00:34:14.219 ⇒ 00:34:14.839 Uttam Kumaran: Okay.
373 00:34:15.069 ⇒ 00:34:16.079 Daniel Schonfeld: But we don’t
374 00:34:16.080 ⇒ 00:34:21.429 Daniel Schonfeld: integration and all that. Let’s just totally let’s get to the true source of the data. The numbers.
375 00:34:21.620 ⇒ 00:34:25.080 Daniel Schonfeld: the costing, the pricing all that, and then we’ll be able to
376 00:34:25.260 ⇒ 00:34:27.940 Daniel Schonfeld: to start making at least decisions. Now.
377 00:34:28.940 ⇒ 00:34:29.480 Uttam Kumaran: Okay.
378 00:34:30.429 ⇒ 00:34:36.889 Daniel Schonfeld: Alright guys. Let me know. Ian’s not the best. With res being responsive. I would put him on, do it on an email.
379 00:34:37.406 ⇒ 00:34:40.999 Daniel Schonfeld: Cc. Me. He calls me like every day, so I can always push him.
380 00:34:41.189 ⇒ 00:34:41.699 Uttam Kumaran: Okay.
381 00:34:42.589 ⇒ 00:34:45.439 Daniel Schonfeld: So just let me know if you’re not getting responses.
382 00:34:45.599 ⇒ 00:34:54.209 Daniel Schonfeld: or if you need me to push him to get on a call or something. He’ll get you what you need to just be very specific in the email. Can we just get this very specific? He’ll do it.
383 00:34:54.489 ⇒ 00:35:00.139 Uttam Kumaran: Okay? So yeah, maybe, Nico, we’ll just give an example with some columns in like a spreadsheet. And just say, this is what we’re looking for.
384 00:35:00.140 ⇒ 00:35:04.539 Daniel Schonfeld: He detailed. He’ll he’s smart, he’ll he’ll do it quickly. It’s very easy for him to run these reports.
385 00:35:04.750 ⇒ 00:35:06.840 Uttam Kumaran: Okay, okay, perfect.
386 00:35:07.156 ⇒ 00:35:08.419 Daniel Schonfeld: Good stuff. Thank you.
387 00:35:08.420 ⇒ 00:35:11.069 Uttam Kumaran: Thanks, Dan. And then, yeah, let us know if there’s anything else.
388 00:35:11.440 ⇒ 00:35:15.680 Daniel Schonfeld: Okay, there will be once we get this out of the way. And I get this deal done. There’s gonna be a lot of shit.
389 00:35:15.870 ⇒ 00:35:16.430 Uttam Kumaran: Okay.
390 00:35:16.880 ⇒ 00:35:17.570 Daniel Schonfeld: Alright guys.
391 00:35:17.570 ⇒ 00:35:18.730 Uttam Kumaran: Alright. Thank you.
392 00:35:18.730 ⇒ 00:35:20.810 Daniel Schonfeld: Happy New Year. Everyone. Thank you.
393 00:35:20.810 ⇒ 00:35:22.490 Nicolas Sucari: Bye, sir, bye, bye.