Meeting Title: Weekly-Data-Review Date: 2024-01-19 Meeting participants: Ben Iphone, Uttam Kumaran
WEBVTT
1 00:01:27.770 ⇒ 00:01:30.089 Uttam Kumaran: What’s up? Hey, Ben?
2 00:01:30.970 ⇒ 00:01:32.549 ben iphone : How are you?
3 00:01:32.890 ⇒ 00:01:36.020 Uttam Kumaran: Good! How are you? How was the trip?
4 00:01:36.670 ⇒ 00:01:39.989 ben iphone : Oh, it was great! It was really
5 00:01:40.680 ⇒ 00:01:42.940 ben iphone : Iceland’s like extreme.
6 00:01:44.210 ⇒ 00:01:49.509 Yeah, it sounds like stream. I’ve only I don’t know much about the country, but
7 00:01:50.970 ⇒ 00:02:02.899 ben iphone : it’s it’s like Hawaii, but frozen. So they have, like black and beaches, ball volcanoes, all sorts of things like that. I was like, I could. I have my, I’m I’m in my office. But I joined from my phone.
8 00:02:03.390 ⇒ 00:02:07.910 ben iphone : I’m a little sick. II came home with an ear infection. So
9 00:02:07.980 ⇒ 00:02:10.660 ben iphone : today’s lecture the first day, I don’t feel terrible.
10 00:02:10.789 ⇒ 00:02:12.470 Uttam Kumaran: Okay.
11 00:02:12.670 ⇒ 00:02:18.940 ben iphone : that’s awesome. I know. I just have a couple of friends that have been there. They’ve gone to like Reykjavik, and I think that’s the
12 00:02:19.040 ⇒ 00:02:26.090 Uttam Kumaran: you should go. It’s it’s it’s it’s it’s really, really. It’s really special. Yeah.
13 00:02:27.060 ⇒ 00:02:31.819 ben iphone : it’s really something. And you can do it in like 3 nights, 4 days.
14 00:02:32.170 ⇒ 00:02:35.669 ben iphone : Cause it’s it’s an easy flight from New York. It’s close
15 00:02:35.730 ⇒ 00:02:44.030 ben iphone : and, like you take a red eye, and you land there at like 6 in the morning. You just go. You just, you know, full send, you know you just go for it.
16 00:02:44.280 ⇒ 00:03:04.219 ben iphone : is it? Is it like what? It’s a sun coming up at the same time, or is like one of those places where like this, it’s a light all day, or what was the vibe in the winter? It’s dark a lot, and then the summer. It’s light all day. So it was dark a lot, but the thing like they told us it was like 5 h of sunlight, but it was more because, like.
17 00:03:04.670 ⇒ 00:03:15.349 ben iphone : I think, that counts like full sun, not like sunrise and sunset, which are so. The only thing I would say that I noticed was like like
18 00:03:16.670 ⇒ 00:03:24.820 ben iphone : like 9 30 in the morning when we’d walk to like our like van to like get rocket and roll, and it was pitch pitch, I guess if it was like 6 am. Here.
19 00:03:25.010 ⇒ 00:03:38.320 ben iphone : But like then you start driving, and you start seeing in the distance. The sun’s rising and it’s beautiful, and it illuminates everything. It’s it’s it wasn’t really like a
20 00:03:38.520 ⇒ 00:03:46.079 ben iphone : wasn’t the thing we did everything we like snowmobiles on a glacier. We did Atv. We, you know it was no. It was no problem.
21 00:03:46.390 ⇒ 00:03:50.770 Uttam Kumaran: Okay, cool. Yeah, I have to. Yeah, that sounds awesome.
22 00:03:50.980 ⇒ 00:03:59.949 ben iphone : Yeah, I. It’s a, it’s a you can do it like couples trip, family trip. bachelor party like the the versatility is there?
23 00:04:00.150 ⇒ 00:04:02.040 Uttam Kumaran: Okay.
24 00:04:02.180 ⇒ 00:04:18.100 Uttam Kumaran: you gotta be you gotta work. You gotta work for like a travel agency something you’re I like. The pitch is really good. I don’t. I think the old. The only place I’m planning this year is I’m planning on going to Dubai in April,
25 00:04:18.930 ⇒ 00:04:29.049 Uttam Kumaran: and then I’m going to go visit some family in India. So I’m just going through Dubai for a bit. so I’m excited for that. But
26 00:04:29.410 ⇒ 00:04:33.379 ben iphone : I’ll be really sick. I want to visit that.
27 00:04:34.460 ⇒ 00:04:44.680 ben iphone : that’s for sure. Alright, let’s make this. We can make this quick. I think it’s just me. Dan’s also sick. I don’t know how we both manage that, especially with the train show
28 00:04:44.710 ⇒ 00:04:50.240 Uttam Kumaran: trade show this coming week. But yeah, I was. I was talking to him about that last week.
29 00:04:51.060 ⇒ 00:04:55.069 Uttam Kumaran: I’m excited to see pictures and stuff. I mean, the way you described
30 00:04:55.500 ⇒ 00:05:01.229 Uttam Kumaran: what you are planning is kind of crazy. I wish I was there to kind of see it. So
31 00:05:02.130 ⇒ 00:05:05.569 ben iphone : I mean you’re welcome. Are you headed over there?
32 00:05:05.860 ⇒ 00:05:06.760 ben iphone : What
33 00:05:06.900 ⇒ 00:05:08.590 Uttam Kumaran: are you headed over there?
34 00:05:09.230 ⇒ 00:05:12.600 ben iphone : Yeah, yeah. Yeah. Sunday morning.
35 00:05:14.240 ⇒ 00:05:15.060 Uttam Kumaran: Nice.
36 00:05:15.310 ⇒ 00:05:17.230 ben iphone : I mean, it’s really not.
37 00:05:17.540 ⇒ 00:05:28.179 ben iphone : It’s not like a Ufc fight, but I don’t know. It’s it’d be cool. So for sure.
38 00:05:28.380 ⇒ 00:05:34.919 ben iphone : for sure I will. Let’s get into. We. Let’s make this like a 5 min thing. Well, you know, we’ll do a quick, yeah.
39 00:05:35.000 ⇒ 00:05:41.790 Uttam Kumaran: cool. So the so me and Dan went through a bunch of different stuff.
40 00:05:42.260 ⇒ 00:05:50.050 Uttam Kumaran: last week. So I’ll kind of just describe some of the things that we talked about, and I have some questions
41 00:05:50.500 ⇒ 00:06:08.549 Uttam Kumaran: for you as well. So we’ve been working on doing the auditing process every day. Everything’s been lining up really? Well. The only thing that I noticed are 2 issues, one
42 00:06:09.930 ⇒ 00:06:17.470 Uttam Kumaran: shop ship station measures things by the shipment date. and we’re measuring things by the order date, meaning
43 00:06:17.790 ⇒ 00:06:29.819 Uttam Kumaran: we have shipping costs come in tied to when the order was made, and of course the shipment doesn’t happen at the same time. So one of the main areas, aware, the dashboards don’t match
44 00:06:29.870 ⇒ 00:06:39.400 Uttam Kumaran: is not because the money isn’t the same. It’s actually just the date. The transaction happened for the company. So my question was gonna be, what’s
45 00:06:39.720 ⇒ 00:06:55.639 Uttam Kumaran: better? Because, on one hand, it’s really nice to be able to look at all of the orders like, for example, if I were to go down to say, Here’s like here’s all of the orders, but you can see several of them don’t have shipment costs yet.
46 00:06:55.750 ⇒ 00:06:57.809 Uttam Kumaran: because they haven’t been shipped
47 00:06:57.910 ⇒ 00:07:04.490 Uttam Kumaran: And but then again, if you go all the way down to look at like reconciled
48 00:07:04.580 ⇒ 00:07:16.320 Uttam Kumaran: days, where all the costs are baked in. You do see shipment costs that are accurate. So good. My question was, gonna be whether it’s helpful to look at shipment costs by
49 00:07:16.530 ⇒ 00:07:20.759 Uttam Kumaran: the date to shift, or whether to look at it. Associated with the order date
50 00:07:21.350 ⇒ 00:07:23.010 Uttam Kumaran: in particular.
51 00:07:23.130 ⇒ 00:07:27.939 Uttam Kumaran: associated with like this section, which is like just yesterday’s shipping cost.
52 00:07:31.430 ⇒ 00:07:32.280 It’s
53 00:07:33.030 ⇒ 00:07:42.670 Uttam Kumaran: it’s tough. Because yeah, cause II don’t know, cause I’m now. I don’t want to introduce like 2 numbers. But of course, like we do have.
54 00:07:43.050 ⇒ 00:07:47.750 Uttam Kumaran: Yeah, I don’t know. Like, I wonder whether this, maybe we just don’t even put this section in.
55 00:07:47.890 ⇒ 00:07:52.049 Uttam Kumaran: And we look at. We look at the shipping costs once they’re baked at the end of the week.
56 00:07:52.450 ⇒ 00:07:53.320 ben iphone : Yeah.
57 00:07:54.590 ⇒ 00:07:58.220 ben iphone : maybe that. Yeah, it’s tough, because it’s.
58 00:07:59.560 ⇒ 00:08:09.499 ben iphone : I guess. Listen, shipping is less of a thing right now, because we have such a reduction. So we like, there’s a little bit of a lid on it, and it’s not gonna kill us anymore.
59 00:08:09.880 ⇒ 00:08:11.000 Uttam Kumaran: But
60 00:08:11.020 ⇒ 00:08:12.870 we do want to know
61 00:08:14.680 ⇒ 00:08:15.879 ben iphone : how we’re doing.
62 00:08:16.970 ⇒ 00:08:21.729 Uttam Kumaran: Yeah. My, my my thinking is that we have this
63 00:08:22.100 ⇒ 00:08:28.700 Uttam Kumaran: weekly. but like dashboard, and we reserve looking at all the shipments for a given week
64 00:08:28.980 ⇒ 00:08:32.900 Uttam Kumaran: at maybe at this point, because it’s tough. I don’t know.
65 00:08:32.980 ⇒ 00:08:40.449 Uttam Kumaran: It takes like it takes a few days to all bake in. And then that was like kind of wrapping my brain. I like what? And then finally figured out like, Oh, it’s a ship date.
66 00:08:40.470 ⇒ 00:08:44.110 Uttam Kumaran: but it doesn’t help to look at like
67 00:08:44.680 ⇒ 00:08:54.620 Uttam Kumaran: you. You wanna look at it in contact. We’ve always looked at in context of the order volume ever like, just like, what did we spend? So it’s
68 00:08:55.120 ⇒ 00:08:59.620 Uttam Kumaran: these are always gonna be like, it’s gonna be a little bit of on a lag.
69 00:08:59.690 ⇒ 00:09:11.240 ben iphone : Yes, I wonder if it’s a matter of messaging. And we say, like, this is expected or estimated shipping against it. So, okay, okay, okay, how does this?
70 00:09:11.480 ⇒ 00:09:14.700 ben iphone : Today? We sell $10,000 of stuff.
71 00:09:15.200 ⇒ 00:09:18.640 ben iphone : We estimate that today’s expense
72 00:09:18.960 ⇒ 00:09:20.370 ben iphone : of shipping is
73 00:09:20.880 ⇒ 00:09:30.480 ben iphone : $2,010. that’s enough to be dangerous with regard to health
74 00:09:30.490 ⇒ 00:09:40.199 ben iphone : and knowing how, generally speaking, profitability. And then we can have a tighter roll up on a less frequent cadence. I think that would make sense.
75 00:09:40.690 ⇒ 00:09:41.690 Uttam Kumaran: Okay.
76 00:09:42.200 ⇒ 00:10:06.039 Uttam Kumaran: so why don’t I try to do that? Yeah, I know. I think that’s great, and I’ll just use the like. I’ll I’ll figure out the the most accurate shipment average. I mean, we have the zones we have like. We have enough data, I think, to make a really good estimation. So let me do that and say, and I’ll just change it. I’ll just have it be estimated shipping costs. And I’ll communicate that in an email to both of you
77 00:10:06.040 ⇒ 00:10:13.430 Uttam Kumaran: and I think we do that because it’s that’s like it was just like, Oh, no, Brainer. But
78 00:10:13.750 ⇒ 00:10:22.509 ben iphone : it’s like it just looks really bad on the dash. So? Yeah, yeah, no, that that’ll I think the messaging.
79 00:10:22.570 ⇒ 00:10:25.429 ben iphone : And if you hover over and it explains.
80 00:10:26.200 ⇒ 00:10:35.879 ben iphone : you know that cause that’s really, this is not meant to be an accounting system. It’s meant to give us to be accurate and dangerous enough.
81 00:10:36.200 ⇒ 00:10:37.010 Uttam Kumaran: Yeah.
82 00:10:37.300 ⇒ 00:10:44.970 Uttam Kumaran: so that’s good. Okay, perfect. So the next thing is, there are some Amazon orders
83 00:10:45.220 ⇒ 00:10:55.960 Uttam Kumaran: that the payment forum looks like it’s happening and delayed. And that’s also been some areas where
84 00:10:56.140 ⇒ 00:10:57.930 Uttam Kumaran: Amazon has been lower.
85 00:10:58.210 ⇒ 00:11:10.479 Uttam Kumaran: Other other than that. Everything we’ve been looking at every single day has been lining up really perfectly. Even the Amazon orders. It’s it’s working, and we’re getting all the orders. Just some of them aren’t giving back
86 00:11:10.850 ⇒ 00:11:13.970 Uttam Kumaran: payment information because they haven’t been paid.
87 00:11:14.060 ⇒ 00:11:24.800 Uttam Kumaran: That’s the last item that I’m looking into but apart from that, everything on the dashboard has been pretty consistent and accurate.
88 00:11:24.950 ⇒ 00:11:36.110 Uttam Kumaran: the one the couple of things that I wanted to share, that we that we made changes of one. We were dealing with an issue of duplicated shipping costs because of multiple items
89 00:11:36.350 ⇒ 00:11:49.649 Uttam Kumaran: per order. And when you do multiple items per order. And then you look at shipping cost per order. Of course you’re gonna get duplication. What we decided to do is split up the shipping cost by the proportional weight of the item.
90 00:11:49.670 ⇒ 00:11:52.329 Uttam Kumaran: So that way, when we look at
91 00:11:52.400 ⇒ 00:12:02.290 Uttam Kumaran: shipment cost by item, we actually get a very accurate estimation previously. If there’s a bundled orders, then we can’t like split up that shipping cost.
92 00:12:02.480 ⇒ 00:12:05.180 Uttam Kumaran: So I think now that’s settled.
93 00:12:05.270 ⇒ 00:12:11.549 Uttam Kumaran: and we’re splitting the shipping by weight to give you to give you a sense of like what
94 00:12:11.590 ⇒ 00:12:13.910 Uttam Kumaran: that means.
95 00:12:13.920 ⇒ 00:12:19.030 Uttam Kumaran: In the shipping, in the shipping dashboard.
96 00:12:19.050 ⇒ 00:12:26.009 Uttam Kumaran: We have the ability to look at like shipping costs by product class.
97 00:12:26.100 ⇒ 00:12:28.910 Uttam Kumaran: Wait for it to load.
98 00:12:29.990 ⇒ 00:12:42.619 Uttam Kumaran: and there are sometimes where like a brush maybe gets sent with another thing, and if we were to calculate a shipping cost, we’d be duplicating because and we look at each item. So now we’re splitting up the cost based on the weight of the item.
99 00:12:42.820 ⇒ 00:12:43.880 Uttam Kumaran: Yeah.
100 00:12:44.150 ⇒ 00:12:49.659 Uttam Kumaran: And I thought that was the most accurate way of kind of doing that split. So we can actually accurately see
101 00:12:50.400 ⇒ 00:12:54.100 Uttam Kumaran: cost by item shipping cost by item.
102 00:12:54.810 ⇒ 00:12:56.349 ben iphone : I think that makes sense
103 00:12:57.930 ⇒ 00:12:59.070 the.
104 00:12:59.570 ⇒ 00:13:04.009 Uttam Kumaran: And then I’m just gonna walk through each of the dashboards. So
105 00:13:04.250 ⇒ 00:13:17.630 Uttam Kumaran: this dashboard. Ha! Not much. A couple of things have changed. The one thing is, we were we quick, we continuously did this year to day comparison. And the one thing that I wanted to
106 00:13:17.820 ⇒ 00:13:28.450 Uttam Kumaran: put in here was actually we, me and Dan talk about how there’s always gonna be less because we’re in January. But instead, what I wanted to do is a comparison versus the same time last year.
107 00:13:28.550 ⇒ 00:13:33.049 Uttam Kumaran: So where are we across all these Kpis on January nineteenth.
108 00:13:33.350 ⇒ 00:13:47.800 Uttam Kumaran: for to January first versus January first to January nineteenth, last year. And so that’s actually what we’ve added here. So, for example, this is the actual percent change in sales, gross sales versus last year we’re we’re within one
109 00:13:48.370 ⇒ 00:13:56.369 Uttam Kumaran: However, on the profit side we’re down, but on the shipping cost side.
110 00:13:56.380 ⇒ 00:14:10.490 Uttam Kumaran: we’re we’re down on the shipping cost side, and we’re down on the marketing cost side, meaning. this is pretty much like, if you were like January first to January nineteenth. What where were we on these Kpis? So that I thought was a much better indication of like
111 00:14:11.020 ⇒ 00:14:15.200 Uttam Kumaran: progress versus looking. It’s the opposite of year to date, basically, but
112 00:14:15.420 ⇒ 00:14:17.159 Uttam Kumaran: framed a little bit better.
113 00:14:17.710 ⇒ 00:14:21.930 Uttam Kumaran: where I think that’s most helpful is looking at
114 00:14:21.970 ⇒ 00:14:28.009 Uttam Kumaran: discount and refunds. So, for example, we’re we’re about 60
115 00:14:28.320 ⇒ 00:14:30.610 Uttam Kumaran: down on refunds, meaning.
116 00:14:30.670 ⇒ 00:14:42.580 Uttam Kumaran: like, we have 60% less refunds at the same time. Last year versus the same discounts, we’re about 30% higher. So this is, I think a lot better framing. And II think it’s lot
117 00:14:42.700 ⇒ 00:14:52.189 Uttam Kumaran: closer to what you guys have been talking over we talking about same month last year. But this is actually we were just look first, the nineteenth, first, the 19 apples apples. We have
118 00:14:52.630 ⇒ 00:14:53.940 Uttam Kumaran: those figures.
119 00:14:54.230 ⇒ 00:15:00.939 Uttam Kumaran: and you can see they’re not all consistent, which is like, there’s there’s, I think, some analysis to do. So.
120 00:15:02.590 ⇒ 00:15:06.859 ben iphone : Yeah. I think it’s it gives context, that’s helpful.
121 00:15:07.900 ⇒ 00:15:14.039 Uttam Kumaran: Yeah, so hopefully, it’s like that number we could see like, of course, we want sales to be higher. We want
122 00:15:14.270 ⇒ 00:15:27.829 Uttam Kumaran: refunds to be low. We want discounts to be low like, so that we could see. Kind of the key levers. The only the changes here is I like Consolidated Amazon Shopify Walmart. It’s a one chart, and that’s a bit easier to see
123 00:15:28.040 ⇒ 00:15:35.800 Uttam Kumaran: and that’s the big thing there. On this weekly dashboard. I’ve added
124 00:15:36.000 ⇒ 00:15:41.630 Uttam Kumaran: a daily year over year tracker. So what you’re actually able to see is a sales
125 00:15:41.670 ⇒ 00:15:51.190 Uttam Kumaran: for every day versus the same day last year. And again, this is kind of like a just, a visual indicator of like how we beat most days last year.
126 00:15:51.900 ⇒ 00:16:03.159 Uttam Kumaran: and so I think this kind of framing I’m able to add to most dashboards this year. We’ll see like on the first. We did way better than last year, but there are a few days in between that we are
127 00:16:03.340 ⇒ 00:16:10.079 Uttam Kumaran: not a head on and so that’s kind of like what I wanted to bring into here. So
128 00:16:10.870 ⇒ 00:16:18.909 Uttam Kumaran: I guess any thoughts on like a on expanding this, or like anything else to do kind of like tracking year over year.
129 00:16:19.400 ⇒ 00:16:22.029 ben iphone : No, I think that that’s as
130 00:16:22.150 ⇒ 00:16:25.730 ben iphone : any more granular than that. It’s probably
131 00:16:25.820 ⇒ 00:16:28.330 Uttam Kumaran: difficult. Yeah.
132 00:16:28.980 ⇒ 00:16:31.250 ben iphone : let’s no, I think, let’s let’s
133 00:16:31.290 ⇒ 00:16:35.589 ben iphone : keep it there for now, you know. Get to use it, you know. Really?
134 00:16:36.190 ⇒ 00:16:37.180 Uttam Kumaran: yeah.
135 00:16:37.420 ⇒ 00:16:38.850 ben iphone : that’s kind of the thing.
136 00:16:39.520 ⇒ 00:16:57.190 Uttam Kumaran: Okay? So I mean again. I think it’s helpful. Any any Kpi we have, we can measure how we’re doing versus the same day last year, really, easily. Now, so hopefully, that’s something we can lean on, and then the last thing is on the shipping side. So I think that shipping dashwards is a really good place.
137 00:16:57.670 ⇒ 00:17:08.669 Uttam Kumaran: I’ve I’m now like so ingrained into understanding all the shipping stuff. Just good. But it’s a little bit nerve wracking. The only thing that’s tough about this is anything that’s Amazon fulfilled
138 00:17:09.260 ⇒ 00:17:23.249 Uttam Kumaran: doesn’t have a shipping cost associated with it, which means we also need to take out the Associated sales from this dashboard. That’s the only Major Caveat is that the sales numbers here and the order numbers are not gonna match
139 00:17:23.280 ⇒ 00:17:35.329 Uttam Kumaran: because we’re removing those Amazon fulfilled ones. Just just make like a big notation in words somewhere at the top, so that I will. I will make this way bigger.
140 00:17:35.660 ⇒ 00:17:48.529 ben iphone : I know it happens Dan doesn’t, though, even if you tell him he doesn’t remember, and he looks at him. He’s like it’s not, you know. These don’t match it all disagrees, and then he’s like I can’t use the dashboard because it doesn’t all agree. And then we go. We, you know.
141 00:17:48.660 ⇒ 00:18:03.750 Uttam Kumaran: Yeah, I’ll make this massive. But other than that, I actually think this is like, really, really accurate. And we’ve been looking at this for the past week. We’re getting all the data from all the major sources we’re able to see price per pound by provider
142 00:18:03.770 ⇒ 00:18:07.229 Uttam Kumaran: by week. and you can see that
143 00:18:07.500 ⇒ 00:18:13.720 Uttam Kumaran: like ups is now less than Fedex and ups is now our our cheapest about a dollar 30
144 00:18:13.750 ⇒ 00:18:17.999 Uttam Kumaran: per pound, and we’re gonna see how this week kind of comes out.
145 00:18:18.160 ⇒ 00:18:22.480 Uttam Kumaran: usps is still the most expensive
146 00:18:22.580 ⇒ 00:18:25.840 Uttam Kumaran: at like between like 3 and 5 bucks per pound.
147 00:18:25.980 ⇒ 00:18:33.740 Uttam Kumaran: but that’s that’s the trend on like price per pound. The other thing we’re able to do is actually look at
148 00:18:34.340 ⇒ 00:18:37.329 Uttam Kumaran: product class and like shipment cost by class.
149 00:18:37.380 ⇒ 00:18:52.110 Uttam Kumaran: So you can see for things like brushes. It’s about 40% of the sales is going to the the shipping costs as opposed to heat pumps. It’s only like around 12 so this is really helpful just to look at like proportion
150 00:18:52.190 ⇒ 00:18:56.760 Uttam Kumaran: of shipping costs of like the total product costs.
151 00:18:57.290 ⇒ 00:19:03.680 Uttam Kumaran: but, for example, pumps like, yeah, we’re we’re selling like we spent 3 K on shipping
152 00:19:03.760 ⇒ 00:19:18.879 Uttam Kumaran: on 12 k. Of sales, you know. So brushes it’s about. It’s about half, but
153 00:19:19.040 ⇒ 00:19:26.050 Uttam Kumaran: brushes is only about 3 k. Per week, but on the cover pumps it’s around 20 of the sales volume
154 00:19:26.150 ⇒ 00:19:37.089 ben iphone : is going to. Can you send that insight to Chuck? Because it might mean that we officially need to move to a different supplier, I mean a different
155 00:19:37.330 ⇒ 00:19:45.699 ben iphone : shipper. Well, it is a supplier of something it could cause for a while up Usps was the best option.
156 00:19:46.400 ⇒ 00:19:52.580 Uttam Kumaran: We have share posts now through ups. So I wonder. yeah, it’s worth yeah, that try.
157 00:19:52.610 ⇒ 00:20:01.090 ben iphone : I think it might be that that now would be better, because we could sell more anyway.
158 00:20:01.390 ⇒ 00:20:03.010 ben iphone : Okay.
159 00:20:04.210 ⇒ 00:20:15.030 Uttam Kumaran: great. And then the other thing I looked at is we, you know, I look at a lot of stuff around zones. But the zones all map to a state. So we’re actually now able to look at
160 00:20:15.140 ⇒ 00:20:21.449 Uttam Kumaran: shipping is a percent of sales by the State that we ship to. And so
161 00:20:21.550 ⇒ 00:20:26.100 Uttam Kumaran: what I’ve done here is, I’ve looked at all of the 1,000 per month
162 00:20:26.720 ⇒ 00:20:32.529 Uttam Kumaran: states that we shipped to, or we spent more than a thousand dollars shipping there. And where
163 00:20:32.680 ⇒ 00:20:35.919 Uttam Kumaran: 10%, at least 10% of the shipping cost is going.
164 00:20:36.020 ⇒ 00:20:58.200 Uttam Kumaran: 10% of the sales cost is going to shipping, and you can see that pretty consistently. In a few States, especially in the summer. We have really high ratios, things like Oregon, Washington, Kansas city. We’re spending almost 20 to 30% of this of the sales volume on shipping
165 00:20:59.320 ⇒ 00:21:04.200 Uttam Kumaran: in the summer months. Yeah. So I thought, this was
166 00:21:04.220 ⇒ 00:21:08.889 Uttam Kumaran: we. I see this in the zones and like Zone 6. But actually, now that I
167 00:21:08.910 ⇒ 00:21:16.660 Uttam Kumaran: broke it up by state. you can see in the really, clearly in the summer months. We’re really getting grid
168 00:21:17.150 ⇒ 00:21:25.139 ben iphone : But the question is, the question is, will we given this year? I, you know.
169 00:21:25.300 ⇒ 00:21:27.880 Uttam Kumaran: Yeah. All because the deal that
170 00:21:28.050 ⇒ 00:21:31.170 ben iphone : we we all put together
171 00:21:31.940 ⇒ 00:21:34.620 ben iphone : is even better as it gets crazier.
172 00:21:35.390 ⇒ 00:21:46.979 Uttam Kumaran: Yeah. So I just wonder whether there’s beyond that. Or maybe we can ask Kelly to say like, Hey, this will be thinking about doing what? Asked her to maybe calculate like, what’s an estimated cost?
173 00:21:47.050 ⇒ 00:21:58.889 Uttam Kumaran: I just wanna know whether there’s anything else we can do. Especially given. It’s so. It’s so concentrated during the summer months outside of the summer months. It’s pretty stable. There are
174 00:21:58.900 ⇒ 00:22:01.900 Uttam Kumaran: some states that are kind of high, like
175 00:22:02.030 ⇒ 00:22:12.720 Uttam Kumaran: but for the most part it’s those are not that common. It’s really in the summer months, in those concentrated like zone 6 zone, 7 zone, 8 states
176 00:22:12.750 ⇒ 00:22:19.580 Uttam Kumaran: right? Right? And those are all like those are all called co-located. Right? So I don’t. Maybe there’s something else.
177 00:22:19.690 ⇒ 00:22:29.830 Uttam Kumaran: Similarly, I’m looking at high price for Pound States. and there’s states like Arizona, like California,
178 00:22:30.130 ⇒ 00:22:38.520 Uttam Kumaran: like Colorado. And then, of course, in the summer months, Oregon, Washington, where the price per pound gets above like 3 bucks.
179 00:22:39.180 ⇒ 00:22:45.730 Uttam Kumaran: And to give you context like again, our our ups price per pound right now is about a dollar 30.
180 00:22:46.190 ⇒ 00:22:50.640 Uttam Kumaran: So everything ramps up in the summer, but
181 00:22:50.670 ⇒ 00:23:05.589 Uttam Kumaran: even the say, even the shipment costs ramp up to a degree that’s not linear meaning, even though our sales increases, the shipping costs are increasing at a higher.
182 00:23:06.460 ⇒ 00:23:16.530 ben iphone : We can, if we can. I think this is important. If we get ahead of this with Kelly now, and just say, Listen, by the way. here’s how things have played out in the past.
183 00:23:16.810 ⇒ 00:23:17.549 You know
184 00:23:17.660 ⇒ 00:23:26.990 ben iphone : we know the deal we made, but we do not want this to happen. Can what can we do to show it to be like? Listen, it’s it’s all off to a good start. But this is a really big concern.
185 00:23:27.970 ⇒ 00:23:31.839 ben iphone : Yeah, she’ll get. She’ll do something for sure.
186 00:23:32.170 ⇒ 00:23:46.939 ben iphone : Let’s do that, and that I think that’s I think it’s I think that’s perfect, and we’ll put in her court. We have the data. I just don’t want to spend another week figuring it all out.
187 00:23:47.350 ⇒ 00:24:02.520 ben iphone : You know. I wanted to bring it to your attention. And you see see me. There’s a disproportionate nonlinear escalation of shipping fees as sales ramp up in the busy season, and we it. It’s it doesn’t work. So what can we do?
188 00:24:02.750 ⇒ 00:24:04.380 Uttam Kumaran: Yeah, okay, let’s do that.
189 00:24:04.790 ⇒ 00:24:19.299 Uttam Kumaran: And then again, this is looking at the past. So what I’ll be like, I say, we’re moving. All of on view. Is this gonna happen? And then, is there anything else we could do to mitigate this? And let’s see. But again, it’s I would be okay if, like in some places it just increases like a little bit.
190 00:24:19.570 ⇒ 00:24:24.980 Uttam Kumaran: But these are almost double. you know. And again, it’s like Oregon, Washington.
191 00:24:25.600 ⇒ 00:24:40.340 Uttam Kumaran: Oklahoma, Colorado. So it’s all Z1607. It’s all the far States. So then it’s like, I. Also, I know you guys are mentioning Unis and other things like that. So that’s where I’m a little bit out of context. But I’ll put this all in like a little email, and then we can have it.
192 00:24:40.390 ⇒ 00:24:42.469 Uttam Kumaran: cause it’s all historical data, anyways.
193 00:24:43.780 ⇒ 00:24:49.890 Uttam Kumaran: We also should be cost by month. So again, a lot of it is in the summer.
194 00:24:50.050 ⇒ 00:24:53.310 Uttam Kumaran: is where we’re spending a ton
195 00:24:53.660 ⇒ 00:24:54.500 of
196 00:24:54.650 ⇒ 00:24:56.389 Uttam Kumaran: on the on shipping.
197 00:24:56.480 ⇒ 00:25:04.159 Uttam Kumaran: Almost like it’s someone’s like 30 40 k by zone. so it really gets bad
198 00:25:05.010 ⇒ 00:25:09.320 Uttam Kumaran: and bad meaning. There’s a ton of red in in Zone 5 and Zone 6.
199 00:25:09.660 ⇒ 00:25:15.209 Uttam Kumaran: We’re spending almost 50 k. Per those zones in that. In those given months.
200 00:25:15.990 ⇒ 00:25:19.980 Uttam Kumaran: So almost 20% of the sales for those months are are going to.
201 00:25:20.590 ⇒ 00:25:30.399 ben iphone : I think this is a very easy situation. We just lay it out, and we can’t have this. It doesn’t work. We’ll have to actually throttle down sales.
202 00:25:30.790 ⇒ 00:25:31.590 Uttam Kumaran: Yeah.
203 00:25:31.780 ⇒ 00:25:40.370 ben iphone : which we will. I mean, you know, we can’t take Ellis this like this anymore. So I think it’s one thing is, you know, we scale to a degree that we’re proud of. But
204 00:25:41.030 ⇒ 00:25:49.970 ben iphone : there was damage done that we didn’t have the eyes, for we didn’t even consider we didn’t like. Imagine that there’d be a nonlinear escalation.
205 00:25:50.290 ⇒ 00:26:00.089 Uttam Kumaran: Yeah, it doesn’t really make sense if anything, you would think that they would just automatically give you a lower rate like dynamically
206 00:26:00.270 ⇒ 00:26:04.089 ben iphone : big for more volume. It it just doesn’t. It’s it seems like
207 00:26:05.270 ⇒ 00:26:20.099 Uttam Kumaran: it almost seems it’s real life. Yeah. And it’s really concentrated to those zone. 6 like regions, right? So it’s it’s really easy for us to see on our end like. And then it’s again. It’s good because we could see on our end like, Hey, if now, if any, if anything goes beyond
208 00:26:20.350 ⇒ 00:26:27.499 Uttam Kumaran: okay, we’re spending about 20 of sales on shipping. It’s not flagged, right? So we can see that really
209 00:26:27.640 ⇒ 00:26:28.580 Uttam Kumaran: clearly.
210 00:26:28.720 ⇒ 00:26:36.909 ben iphone : Yeah. So just, I think, just just laid out. There’d be like zones. 5 and 6 are are are an enormous problem in these 4 months.
211 00:26:37.490 ⇒ 00:26:48.400 ben iphone : you know, it’s an issue because we cannot. We will not repeat this again, we will just throttle down sales which we’d like not to do. We just need shipping to be in a certain range. She’ll do it.
212 00:26:48.800 ⇒ 00:26:49.720 Uttam Kumaran: Okay.
213 00:26:50.840 ⇒ 00:26:51.670 Uttam Kumaran: okay.
214 00:26:51.810 ⇒ 00:27:00.799 Uttam Kumaran: cool. I think that’s all I had to go through. So everything is ready and accurate and running. We have a ton of tests. So I’m really confident
215 00:27:01.110 ⇒ 00:27:11.510 Uttam Kumaran: that we can start using stuff. The shipping stuff, I think, was all in a really good place. So I’m gonna start to kind of move towards marketing. I need to get back with Kim
216 00:27:11.910 ⇒ 00:27:15.660 Uttam Kumaran: next week and kind of chat about. If she’s been able to use a dashboard. It doesn’t
217 00:27:16.030 ⇒ 00:27:27.970 Uttam Kumaran: look like it. So I wanna kind of get back with her. And yeah, I’ll write. I’ll write up a little email summarizing this stuff and then I’ll send one to you and Dan, and then I’ll send one to
218 00:27:28.560 ⇒ 00:27:34.480 ben iphone : us 3 and chuck about the brushes. And then the third one was to Kelly, so you nailed it perfect
219 00:27:35.910 ⇒ 00:27:36.980 Uttam Kumaran: perfect!
220 00:27:37.050 ⇒ 00:27:39.869 Uttam Kumaran: Alright! Good job. Have a good weekend.
221 00:27:39.880 ⇒ 00:27:41.980 Uttam Kumaran: Thanks, man. Talk soon bye.