Meeting Title: Urban Stems Revenue Model Discussion Date: 2025-07-29 Meeting participants: Emily Giant, pk.arthur, Chris, Amanda Hutchinson Otero, Sam Sheil, saschi, Uttam Kumaran, Amber Lin
WEBVTT
1 00:00:25.040 ⇒ 00:00:26.250 pk.arthur: Hey! Emily!
2 00:00:30.030 ⇒ 00:00:31.430 Emily Giant: Hello! Again.
3 00:00:32.369 ⇒ 00:00:32.950 Emily Giant: Are you.
4 00:00:32.950 ⇒ 00:00:34.009 pk.arthur: Nice to see you again.
5 00:00:34.010 ⇒ 00:00:40.959 Emily Giant: Yeah, yeah, we should do this more often. This is great. Are you getting weird feedback from my computer?
6 00:00:42.570 ⇒ 00:00:43.630 pk.arthur: Sorry.
7 00:00:43.630 ⇒ 00:00:45.419 Emily Giant: Is my sound? Okay.
8 00:00:46.050 ⇒ 00:00:47.310 pk.arthur: Oh, yeah, no, it’s fine.
9 00:00:47.310 ⇒ 00:00:54.680 Emily Giant: Okay, I probably won’t be speaking too much. But whenever I’m in Zapier it does this like ripple thing.
10 00:00:55.119 ⇒ 00:01:11.290 Emily Giant: And I’m trying to set up an automation, so that, like, as I was updating your ticket in linear, I was like, I do not want to do this again in Asana. So I was trying to set up an automation. And it’s just whenever I speak. It sounds like it’s going through space.
11 00:01:12.740 ⇒ 00:01:15.460 pk.arthur: That sounds pretty fine to me, I think.
12 00:01:15.860 ⇒ 00:01:16.800 Emily Giant: Okay, good.
13 00:01:21.830 ⇒ 00:01:28.800 Emily Giant: Oh, wow! There are more people here than I thought would be available. Sashi and Sam. Your calendars are wild.
14 00:01:30.580 ⇒ 00:01:35.609 saschi: Oh, gosh! I know I’m sorry you had to see that it’s embarrassing. It’s like my dirty laundry, like, yeah.
15 00:01:35.610 ⇒ 00:01:36.080 Emily Giant: Oh, good!
16 00:01:36.310 ⇒ 00:01:37.950 saschi: That is what it looks like.
17 00:01:38.620 ⇒ 00:01:51.242 Emily Giant: I eventually just sent it to our project manager because I was like, I actually can’t like, I can’t. I won’t get anything done today if I try to find time that they have in common. So why don’t we just throw time out there and see what happens?
18 00:01:52.650 ⇒ 00:01:57.289 saschi: I made you a priority. I shifted things around. When I see your name show up. I say I’m there
19 00:01:57.540 ⇒ 00:01:58.780 saschi: for a good time.
20 00:01:58.990 ⇒ 00:02:05.320 Emily Giant: I feel the same, I feel the same hi utam.
21 00:02:05.730 ⇒ 00:02:07.490 Uttam Kumaran: Hey? How’s everyone doing?
22 00:02:10.880 ⇒ 00:02:11.610 saschi: Good.
23 00:02:13.370 ⇒ 00:02:14.070 Uttam Kumaran: Cool.
24 00:02:15.190 ⇒ 00:02:16.550 Emily Giant: I’m not sure if.
25 00:02:16.550 ⇒ 00:02:17.270 Uttam Kumaran: Join.
26 00:02:17.270 ⇒ 00:02:21.679 Emily Giant: Yeah, she’s gonna be really pleased with the attendance.
27 00:02:22.370 ⇒ 00:02:31.480 Emily Giant: most of these people did not actually have availability and prioritize this meeting. So thanks again for making this happen.
28 00:02:32.110 ⇒ 00:02:36.678 Uttam Kumaran: Yeah. And hopefully, we’ll make this worth everyone’s time. Let me just get
29 00:02:37.380 ⇒ 00:02:41.530 Uttam Kumaran: Get a notion Doc sent in here, and we can just jump right into stuff.
30 00:02:42.480 ⇒ 00:02:43.150 Uttam Kumaran: Oh.
31 00:02:43.680 ⇒ 00:02:49.800 saschi: I have been testing notion this week this month. I’m trying to get get into it. Do you like it?
32 00:02:51.175 ⇒ 00:02:56.739 Uttam Kumaran: I’m pretty. I’ve tried everything. It’s like the best, worst one
33 00:02:58.010 ⇒ 00:03:00.632 Uttam Kumaran: our whole our whole company runs on it.
34 00:03:01.350 ⇒ 00:03:03.190 Uttam Kumaran: I like it much better than like
35 00:03:03.450 ⇒ 00:03:07.999 Uttam Kumaran: random Google docs. But it also has, like, too, like too much stuff.
36 00:03:08.569 ⇒ 00:03:13.380 Uttam Kumaran: You can do a lot of stuff that’s kind of like, just too much.
37 00:03:14.120 ⇒ 00:03:16.590 Uttam Kumaran: So yeah, it’s nice, though.
38 00:03:17.120 ⇒ 00:03:21.230 saschi: Yeah, I went down that rabbit hole of trying to do too much. I think that’s where I went wrong.
39 00:03:22.024 ⇒ 00:03:28.795 Uttam Kumaran: Yeah, you could do like a lot. I don’t know. It’s just stick to writing, and then just have like simple databases. It’s
40 00:03:29.480 ⇒ 00:03:32.029 Uttam Kumaran: It’s not that bad.
41 00:03:34.998 ⇒ 00:03:38.410 Uttam Kumaran: Cool, so I will send in.
42 00:03:41.890 ⇒ 00:03:47.394 Uttam Kumaran: So for everyone here we’re in this document. I just sent it in the zoom chat this
43 00:03:48.860 ⇒ 00:03:55.339 Uttam Kumaran: urban stems revenue model? And really, the focus of this meeting is going to be on.
44 00:03:57.120 ⇒ 00:04:02.390 Uttam Kumaran: The questions, where am I?
45 00:04:02.540 ⇒ 00:04:07.950 Uttam Kumaran: Yes, under marketing sales, subscriptions.
46 00:04:10.200 ⇒ 00:04:12.060 Uttam Kumaran: And we noted down
47 00:04:12.330 ⇒ 00:04:18.170 Uttam Kumaran: some recurring questions and some wish list questions. And really we just wanted to get feedback
48 00:04:18.660 ⇒ 00:04:26.950 Uttam Kumaran: from everybody here that these were accurate. Still, if there’s anything else we want to try to make sure that as part of this.
49 00:04:27.130 ⇒ 00:04:28.980 Uttam Kumaran: the models that we’re working on.
50 00:04:29.170 ⇒ 00:04:36.880 Uttam Kumaran: you know, I don’t think any. Nothing’s like going away per se. We’re just re architecting some stuff. So it’s a good time for us to consider whether we
51 00:04:37.190 ⇒ 00:04:41.089 Uttam Kumaran: there’s questions that currently can’t be answered that we want to answer.
52 00:04:42.046 ⇒ 00:04:45.709 Uttam Kumaran: Does everyone kind of following here in this document?
53 00:04:48.120 ⇒ 00:04:48.950 Chris: Yes.
54 00:04:57.800 ⇒ 00:05:07.129 Uttam Kumaran: Okay, cool. So maybe just want to take a moment and look through this and feel free. You can just click on the bottom of each of the tables to add anything new.
55 00:05:07.270 ⇒ 00:05:10.590 Uttam Kumaran: Maybe we’ll give everyone like a minute couple minutes.
56 00:06:51.400 ⇒ 00:06:58.137 Uttam Kumaran: Also, if you have any comments on any of these. You can also just like highlight in notion and just click on comment.
57 00:06:59.540 ⇒ 00:07:04.460 Uttam Kumaran: give everyone another minute or 2, and we can just discuss.
58 00:07:43.758 ⇒ 00:07:59.510 Emily Giant: Kristen. Pk, I just added to the bottom of like in the wish list area. If you want to fill out any additional details that I may have misrepresented. The, how does inventory availability within a given delivery window impact, revenue achievement.
59 00:08:44.540 ⇒ 00:08:46.210 Sam Sheil: If if
60 00:08:46.350 ⇒ 00:08:51.619 Sam Sheil: we have a thought on something that should be added, should should we leave a comment or.
61 00:08:51.870 ⇒ 00:08:54.820 Uttam Kumaran: Feel free to add it. If you just cover, move your.
62 00:08:54.820 ⇒ 00:08:58.830 Sam Sheil: Oh, wait wrong section! But let me scroll down.
63 00:08:59.870 ⇒ 00:09:00.900 saschi: To adding it.
64 00:09:01.120 ⇒ 00:09:06.459 Sam Sheil: I was in the wrong section. Hold on, let me read and make sure that it is not included in here. Sorry. Go ahead.
65 00:09:07.610 ⇒ 00:09:13.450 saschi: I just was adding it under recurring questions. Is that right? Or should I add it under wish list? Okay, cool.
66 00:09:13.450 ⇒ 00:09:17.149 Uttam Kumaran: Recurring questions. It’s fine. Yeah. As long as it ends up anywhere in here, just wanna make sure.
67 00:09:23.080 ⇒ 00:09:34.750 Emily Giant: Yeah, this is probably gonna be the group with the most or with, like the largest wish list they’re like super under, represented in looker and Dbt, and they’re like
68 00:09:35.280 ⇒ 00:09:40.920 Emily Giant: keeping Google sheets afloat as a business to do a lot of.
69 00:09:41.440 ⇒ 00:09:44.069 Uttam Kumaran: Cross-referencing outside of our systems.
70 00:09:46.920 ⇒ 00:09:48.139 Emily Giant: Where are you?
71 00:09:49.460 ⇒ 00:09:57.690 Uttam Kumaran: I am in Austin just I was inside this coffee shop, but they’re blasting like punk music, so I just I’ll step out for a bit.
72 00:09:57.690 ⇒ 00:10:01.140 Sam Sheil: Oh, I think I need to make a notion account. That’s why I can’t
73 00:10:01.690 ⇒ 00:10:05.119 Sam Sheil: add. And so she can. Okay, that makes sense.
74 00:10:06.110 ⇒ 00:10:08.250 saschi: It’s cause I’m such an expert now.
75 00:10:08.490 ⇒ 00:10:10.620 Sam Sheil: We use notion, Internet cadence.
76 00:10:12.010 ⇒ 00:10:16.220 saschi: I like, really, I I really tried last week, I was like, I’m gonna get into this. And then.
77 00:10:16.220 ⇒ 00:10:19.619 Sam Sheil: Are you paying for it like? Are you doing the paid version, or are you doing this free.
78 00:10:19.620 ⇒ 00:10:23.929 saschi: There’s like a 30 day trial. So I’m still just doing the 30 day trial. But I think I
79 00:10:24.140 ⇒ 00:10:24.880 saschi: it’s okay.
80 00:10:24.880 ⇒ 00:10:27.650 Uttam Kumaran: Don’t pay for the AI stuff. It’s not that good
81 00:10:28.178 ⇒ 00:10:32.769 Uttam Kumaran: but yeah, like our whole company, like runs on it. So we have, like
82 00:10:33.090 ⇒ 00:10:35.649 Uttam Kumaran: all types of sections, for everything.
83 00:10:36.690 ⇒ 00:10:51.949 saschi: Yeah, I think it would make sense if the organization was on it. But trying to use it as a personal platform is like I could do that in Google sheets. So I use we use fellow here which I love. But it’s crashing everyone’s computers. So I have to move
84 00:10:52.150 ⇒ 00:10:53.969 saschi: move my life out of there.
85 00:10:58.040 ⇒ 00:11:02.609 Uttam Kumaran: Oh, okay, so maybe we can walk through a couple of these?
86 00:11:03.730 ⇒ 00:11:09.549 Uttam Kumaran: so does anyone want to start? Is there anything in the
87 00:11:10.477 ⇒ 00:11:15.769 Uttam Kumaran: in the top. Few that are like important, or these seem pretty standard.
88 00:11:16.130 ⇒ 00:11:18.520 Uttam Kumaran: or anyone want to sort of take the floor.
89 00:11:28.621 ⇒ 00:11:30.789 Emily Giant: Maybe let’s kick it off with Sam and loop
90 00:11:31.375 ⇒ 00:11:34.029 Emily Giant: since that’s gonna be like a net. New thing.
91 00:11:35.420 ⇒ 00:11:38.319 Sam Sheil: Yeah, sorry. I’m just adding things right now.
92 00:11:51.620 ⇒ 00:11:53.390 Emily Giant: But yeah, I know.
93 00:11:54.820 ⇒ 00:11:56.679 Sam Sheil: What is your question for me? Around loop.
94 00:11:57.173 ⇒ 00:12:05.659 Emily Giant: Revenue. So I can see the team. And this is really awesome, adding a lot to the marketing sales and subscriptions, because so many of those pieces will
95 00:12:05.860 ⇒ 00:12:23.760 Emily Giant: be used in the revenue mark. But I know specifically like there’s a lot of stuff that we cannot access in looker right now having to do with subscriptions and subscription revenue, and I think outlining some of your needs. A little more specifically
96 00:12:24.350 ⇒ 00:12:25.130 Emily Giant: so that we.
97 00:12:25.130 ⇒ 00:12:27.369 Sam Sheil: Where do you want me to put that.
98 00:12:28.350 ⇒ 00:12:32.689 Emily Giant: Hey, Tom, I have a track record for messing up documents.
99 00:12:32.690 ⇒ 00:12:35.409 Uttam Kumaran: You can just put anything in the wish list questions.
100 00:12:35.820 ⇒ 00:12:37.199 Sam Sheil: Yeah, that’s what I was. Just that’s.
101 00:12:37.200 ⇒ 00:12:38.080 Uttam Kumaran: Yeah, right?
102 00:12:38.080 ⇒ 00:12:42.100 Uttam Kumaran: Any question you have. You just toss it in there. And that way we we have it there.
103 00:12:42.440 ⇒ 00:12:43.680 Uttam Kumaran: Okay.
104 00:12:46.540 ⇒ 00:12:52.300 Sam Sheil: Yeah. So I’ll basically like, go through all of our reporting and put, like every random question that I get
105 00:12:52.510 ⇒ 00:12:56.309 Sam Sheil: and that I have to answer each week. Does that sound right.
106 00:12:56.310 ⇒ 00:12:57.140 Uttam Kumaran: Yes.
107 00:12:57.140 ⇒ 00:12:58.260 Sam Sheil: Yeah, cool.
108 00:13:05.210 ⇒ 00:13:10.220 Emily Giant: I’m gonna add one, Sam, for, like self selected versus mystery.
109 00:13:10.810 ⇒ 00:13:15.072 Emily Giant: I know that’s not necessarily revenue related, but maybe it is for forecasting.
110 00:13:15.780 ⇒ 00:13:20.900 Sam Sheil: Yeah, yeah, there’s gonna be a lot like a lot, a lot.
111 00:13:24.350 ⇒ 00:13:31.800 Sam Sheil: Subscriptions is really the forecasting process has probably like 70 different inputs.
112 00:13:34.370 ⇒ 00:13:38.259 Uttam Kumaran: So, yeah, maybe we can talk about subscription. Since that we spoke to spend a little bit of time yet.
113 00:13:38.260 ⇒ 00:13:39.759 Sam Sheil: Do you want me? So
114 00:13:40.590 ⇒ 00:13:47.499 Sam Sheil: I didn’t like prepare for this, because the 1st time I’m seeing this like, is it easier if I put it on the document, or like talk.
115 00:13:47.500 ⇒ 00:13:47.980 Uttam Kumaran: It is.
116 00:13:47.980 ⇒ 00:13:51.159 Sam Sheil: I don’t think I can talk through it and write it at the same time.
117 00:13:51.490 ⇒ 00:13:53.818 Uttam Kumaran: It is easier. I’d rather get a document.
118 00:13:54.110 ⇒ 00:13:54.795 Sam Sheil: Okay.
119 00:13:55.480 ⇒ 00:14:02.569 Uttam Kumaran: So maybe if like, I don’t know if Sashi or Pk, maybe we can talk through any of the other.
120 00:14:03.380 ⇒ 00:14:07.689 Sam Sheil: Yeah, why don’t you guys start somewhere else? I’ll write everything down, and then we can circle back.
121 00:14:08.020 ⇒ 00:14:08.400 Uttam Kumaran: Okay.
122 00:14:08.400 ⇒ 00:14:17.209 Emily Giant: You know, one of the large pieces here that we’ve really had trouble. Having a source of truth is discount logic versus promo logic.
123 00:14:17.210 ⇒ 00:14:17.600 saschi: Okay.
124 00:14:17.920 ⇒ 00:14:32.989 Emily Giant: Codifying it historically. So if Chris or Pk, if you want to like, speak to that, I know that would be really helpful for Kyle, who’s not here. His time zone is just not nice with our meeting time, but we’ll be able to pass it on.
125 00:14:34.450 ⇒ 00:14:36.789 Chris: You said with the the promo codes.
126 00:14:37.237 ⇒ 00:14:44.839 Emily Giant: And what you need out of looker, when it comes to that those impacts on revenue.
127 00:14:45.310 ⇒ 00:15:10.839 Chris: Yeah. So I think the big thing is being able to better categorize promo codes because we have different types. So we have, like our welcome flow, we have our like loyalty, point redemptions. Then we have different kind of like channel groupings, but at the moment, right now, especially like with loyalty. Each loyalty, redemption is a unique code, and sometimes.
128 00:15:11.130 ⇒ 00:15:21.570 Chris: like customers, could have multiple loyalty, point redemptions in one order, and that could have like 3 codes. So then, when you pull a promo code report, it’s like
129 00:15:21.740 ⇒ 00:15:35.299 Chris: 50,000 codes depending on the time period you’re pulling. So being able to group them into categories. We can better look at, you know, by fiscal, week by month, whatever it is that we’re, you know, trying to pull.
130 00:15:35.390 ⇒ 00:15:54.119 Chris: How much was each category contributing to the promo dollars we were, you know, giving away on orders, and then also being able to look at those categories and say, Hey, if we acquired a new customer through this promo code category. What’s their, you know? Return rate their Ltv.
131 00:15:57.160 ⇒ 00:16:03.999 Uttam Kumaran: So question there is, are, is there already? Sort of a sense for these categories we had? We’re the same thing yesterday
132 00:16:04.180 ⇒ 00:16:08.030 Uttam Kumaran: from finance. Like are? Do these categories exist.
133 00:16:08.570 ⇒ 00:16:10.669 Chris: Yeah, or is this something more? Okay?
134 00:16:11.430 ⇒ 00:16:17.150 Emily Giant: I actually have a I have the doc you shared y’all, so I can link that in this file.
135 00:16:17.420 ⇒ 00:16:19.210 Chris: The the biggest
136 00:16:20.120 ⇒ 00:16:34.279 Chris: challenge is, you know, when we add new promo codes for something, there’s some like like welcome flow. The promo code just rarely ever changes, and loyalty points. We now have, like a set
137 00:16:34.510 ⇒ 00:16:41.100 Chris: structure where a loyalty redemption code starts with L. Dash.
138 00:16:41.430 ⇒ 00:16:46.920 Chris: But there was a time and period really early on, when we 1st switched to shopify where it didn’t.
139 00:16:47.110 ⇒ 00:16:55.699 Chris: So it’s those historical ones that would be, you know, we just need to make sure we have those all kind of loaded in, but that should be in that spreadsheet, I think.
140 00:16:58.590 ⇒ 00:17:09.269 Chris: And then, anytime, we do, you know, like big peak holiday periods. And we, you know, create new codes. How do we? How do we create something where the team can go and categorize those.
141 00:17:09.900 ⇒ 00:17:10.490 Uttam Kumaran: Okay.
142 00:17:11.780 ⇒ 00:17:20.630 Uttam Kumaran: okay? Makes sense. Yeah, I mean, most likely in the past like this will either come from something we infer from a code name, or we will have to maintain.
143 00:17:20.869 ⇒ 00:17:30.009 Uttam Kumaran: you know, some type of Google Sheet or something. That’s it. Typically, the process will be like it all. Anything that’s not categorized, flows into uncategorized.
144 00:17:30.240 ⇒ 00:17:33.559 Uttam Kumaran: And then, if we basically have some process of
145 00:17:33.790 ⇒ 00:17:36.150 Uttam Kumaran: categorizing things on the same cadence.
146 00:17:36.430 ⇒ 00:17:44.490 Chris: Yeah, I think the other thing would be, is there any way from shopify?
147 00:17:44.610 ⇒ 00:18:05.250 Chris: So like we’re setting all these codes up in shopify. And you know they each code has like different rules. Whether it’s 15% off product order shipping, you know all I I don’t know. There’s probably like 10 different scenarios. Sasha could probably get better answers there. But is there a way to pull any of that information into.
148 00:18:05.250 ⇒ 00:18:11.309 Uttam Kumaran: We can actually pull the like, basically the property that’s affected. And then the
149 00:18:11.510 ⇒ 00:18:15.240 Uttam Kumaran: magnitude at which it’s affected. So like, if it’s a 50% off.
150 00:18:15.710 ⇒ 00:18:18.799 Uttam Kumaran: Well, we can see the properties of the discount code.
151 00:18:19.040 ⇒ 00:18:21.210 Uttam Kumaran: So that could be an easy way as well.
152 00:18:21.210 ⇒ 00:18:24.029 Chris: Amazing. So then we could pull a report that’s like.
153 00:18:24.210 ⇒ 00:18:32.730 Chris: Give me all the codes that were, you know, for 15% off your order, or give me all the codes that were discounted per subscriptions.
154 00:18:33.770 ⇒ 00:18:34.410 Uttam Kumaran: Correct.
155 00:18:34.770 ⇒ 00:18:35.420 Chris: Cool.
156 00:18:37.050 ⇒ 00:18:39.820 saschi: Can can I ask another question on that?
157 00:18:39.960 ⇒ 00:18:49.051 saschi: I think historically, what’s also been kind of mixed into this promo line has also been
158 00:18:50.610 ⇒ 00:18:54.969 saschi: markdowns right? So things that are on the site at
159 00:18:55.260 ⇒ 00:19:14.099 saschi: a lower aur. So at a discounted price. But there’s no code associated with that discount. It’s just that is the, you know, the ending basket price for a customer. So is there like a way to delineate between someone who’s used a code to receive a discount
160 00:19:14.870 ⇒ 00:19:21.310 saschi: versus I guess a markdown discount.
161 00:19:22.710 ⇒ 00:19:25.580 Uttam Kumaran: And then the markdown discounts like are those up?
162 00:19:25.760 ⇒ 00:19:30.080 Uttam Kumaran: Those are not like triggered by the customer.
163 00:19:30.800 ⇒ 00:19:31.709 saschi: They are not.
164 00:19:31.990 ⇒ 00:19:32.580 Uttam Kumaran: Okay.
165 00:19:34.010 ⇒ 00:19:37.120 saschi: They are, I mean, in what situation is a markdown.
166 00:19:37.480 ⇒ 00:19:40.699 Uttam Kumaran: Like enabled, you know, for a given product.
167 00:19:41.230 ⇒ 00:19:53.506 saschi: So for our doubles and triples. So our size, variance, or larger size variance, we have a a discount built into the pricing structure there. So a customer is
168 00:19:54.230 ⇒ 00:20:01.000 saschi: checking out at a seemingly discounted price, right? And the way we do that is within shopify, based on.
169 00:20:01.260 ⇒ 00:20:07.310 saschi: you know, variant price and compare at price. That’s like the mechanism in which we’re using to do the markdowns.
170 00:20:07.800 ⇒ 00:20:11.660 saschi: So the 2 prices are built into shopify.
171 00:20:12.060 ⇒ 00:20:18.079 Uttam Kumaran: Okay, yeah, so that won’t. That won’t show up as a coupon. Redemption will show up as something else.
172 00:20:18.463 ⇒ 00:20:21.100 Uttam Kumaran: I don’t know whether it’s a discount rule or something.
173 00:20:21.784 ⇒ 00:20:28.459 Uttam Kumaran: But yes, we will. We can delineate that. Probably the only piece that’s tougher is.
174 00:20:28.840 ⇒ 00:20:33.330 Uttam Kumaran: we may still, I guess this is, the probably debate we can have is like.
175 00:20:34.160 ⇒ 00:20:37.880 Uttam Kumaran: like, we may still populate like a discount amount field.
176 00:20:38.080 ⇒ 00:20:41.680 Uttam Kumaran: But we can either have a discount reason.
177 00:20:43.840 ⇒ 00:20:50.229 Uttam Kumaran: And again, I think the bigger complication is there can be stacked of these. So we’ll want to see like, what type of discount
178 00:20:51.077 ⇒ 00:20:58.579 Uttam Kumaran: was applied. How much did it result in? And that way you can see how much was going to Markdown versus how much is going from coupon
179 00:20:59.115 ⇒ 00:21:02.469 Uttam Kumaran: you know I I don’t know necessarily whether we will
180 00:21:03.590 ⇒ 00:21:07.309 Uttam Kumaran: basically create like a coupon discount.
181 00:21:07.880 ⇒ 00:21:15.630 Uttam Kumaran: and maybe in a specific model, we have a coupon discount, Markdown discount. But overall. I think the business categorize them both as discounts.
182 00:21:15.740 ⇒ 00:21:17.679 Uttam Kumaran: So, for some of the reports.
183 00:21:17.680 ⇒ 00:21:18.080 Chris: Ping him.
184 00:21:18.080 ⇒ 00:21:19.870 Uttam Kumaran: They may. Just, yeah, go ahead.
185 00:21:20.360 ⇒ 00:21:21.380 Chris: Because I think
186 00:21:22.480 ⇒ 00:21:31.350 Chris: I I want to get clarification from finance. I guess maybe on on some of that piece of it. I I think, though structurally, what you’re saying makes sense to be able to separate
187 00:21:31.460 ⇒ 00:21:43.229 Chris: the you know the Markdown from a coupon code, because I’m actually not sure that finance is calculating markdowns into gross revenue, reporting.
188 00:21:45.002 ⇒ 00:21:50.919 Uttam Kumaran: Like if we if if we sell a firecracker at a $4 markdown.
189 00:21:51.610 ⇒ 00:21:56.959 Chris: I think in like, let’s say it was 72, and we’re selling it at a, you know. $68.
190 00:21:57.210 ⇒ 00:22:01.369 Chris: I think Wilder’s only reporting the 68, not the 72.
191 00:22:03.590 ⇒ 00:22:07.709 Chris: Again, we should get clarification. But that’s my understanding of what he’s doing today.
192 00:22:08.190 ⇒ 00:22:09.330 Emily Giant: The gross.
193 00:22:12.370 ⇒ 00:22:15.800 saschi: But in the discount dollars, like, if you’re.
194 00:22:15.800 ⇒ 00:22:21.649 Chris: Show up in cart like when you do a markdown. Does it show the subtotal of 72?
195 00:22:28.060 ⇒ 00:22:29.001 Chris: I guess we can do.
196 00:22:29.190 ⇒ 00:22:29.600 Emily Giant: Good.
197 00:22:29.600 ⇒ 00:22:30.969 saschi: The double. But yeah.
198 00:22:31.310 ⇒ 00:22:31.650 Emily Giant: And.
199 00:22:31.650 ⇒ 00:22:32.470 saschi: Should.
200 00:22:34.080 ⇒ 00:22:42.180 Emily Giant: in my reporting like, and I’ve done a lot of revenue vetting with Perry and Dean because of all of the disruptions since the migration.
201 00:22:42.180 ⇒ 00:22:42.600 Chris: Okay.
202 00:22:42.780 ⇒ 00:22:52.959 Emily Giant: After 1, 2325, it should always show the parent price. As like your top line revenue. But.
203 00:22:54.170 ⇒ 00:22:58.270 Chris: So what I’m I’m saying is when you get to the cart, so I’ll just screen share real quick.
204 00:22:58.270 ⇒ 00:22:59.919 saschi: Yeah, I have. Yeah.
205 00:23:00.320 ⇒ 00:23:01.400 Chris: Oh, you! You got it!
206 00:23:03.000 ⇒ 00:23:04.519 saschi: I mean, I have a cart up.
207 00:23:05.410 ⇒ 00:23:07.869 Chris: So when you get into this cart here.
208 00:23:08.290 ⇒ 00:23:15.029 Chris: it’s still saying the subtotal is 1, 69, even though the original price was 1, 82, I think.
209 00:23:15.210 ⇒ 00:23:21.279 Chris: Hold on, or 1 88 was the original price when I added it to cart. And so it’s showing.
210 00:23:21.280 ⇒ 00:23:29.910 Chris: Oh, my God, yeah, it’s just showing there’s no discount applied here on a markdown.
211 00:23:37.720 ⇒ 00:23:39.029 Chris: So it shows my.
212 00:23:39.030 ⇒ 00:23:43.600 Uttam Kumaran: I can ask. I can ask them, yeah, I don’t know. I guess my my thing is like
213 00:23:43.760 ⇒ 00:23:47.699 Uttam Kumaran: it’s not showing in cart. I doubt it’s coming in as a discount amount.
214 00:23:47.990 ⇒ 00:23:48.480 Uttam Kumaran: Yeah.
215 00:23:48.480 ⇒ 00:23:53.039 saschi: In the order, like in the Json of the Order, you do have original
216 00:23:53.370 ⇒ 00:24:00.450 saschi: total price, and then you have total price. So you do have the value in the order.
217 00:24:01.850 ⇒ 00:24:03.540 saschi: like on the back end. I know what you’re saying.
218 00:24:03.920 ⇒ 00:24:05.950 saschi: Yes, I totally understand what you’re seeing here.
219 00:24:05.950 ⇒ 00:24:06.500 saschi: Yeah. Yeah.
220 00:24:06.500 ⇒ 00:24:17.100 saschi: So like the information does exist because the fields exist, they’re associated with that product in shopify as 2 separate price fields.
221 00:24:18.920 ⇒ 00:24:19.710 saschi: So.
222 00:24:19.710 ⇒ 00:24:22.730 Uttam Kumaran: Would be is changing the price field
223 00:24:23.130 ⇒ 00:24:29.510 Uttam Kumaran: doesn’t like. Is that getting calculated as like a discount? Or is that just like a
224 00:24:30.880 ⇒ 00:24:32.699 Uttam Kumaran: change in the price, you know.
225 00:24:33.130 ⇒ 00:24:33.680 saschi: Yeah, I.
226 00:24:33.680 ⇒ 00:24:34.290 Uttam Kumaran: Price.
227 00:24:36.700 ⇒ 00:24:38.019 saschi: I guess I don’t know.
228 00:24:38.020 ⇒ 00:24:43.100 Uttam Kumaran: So that’s something I can look at. I can take a specific order where there was this case. Basically.
229 00:24:43.600 ⇒ 00:24:43.940 saschi: Okay.
230 00:24:43.940 ⇒ 00:24:49.191 Uttam Kumaran: See how they’re how they’re doing it. So I can. I can find that out, I guess. Like, what is is there?
231 00:24:50.530 ⇒ 00:24:55.719 Uttam Kumaran: I mean one. We we totally should be looking at markdowns like the amount
232 00:24:56.310 ⇒ 00:24:59.939 Uttam Kumaran: going to markdowns. Does this team have an opinion on like
233 00:25:00.670 ⇒ 00:25:03.200 Uttam Kumaran: that should be counted as a discount.
234 00:25:04.290 ⇒ 00:25:25.940 Chris: I think I I really would like to get that clarification from finance, because my understanding is even like historically pre shopify. We never included Markdown as part of the gross revenue. Calculation, like whatever the so like. In the same instance, if the subtotal was 1 69, that was considered the gross product, revenue.
235 00:25:27.450 ⇒ 00:25:28.030 Emily Giant: Yeah.
236 00:25:29.865 ⇒ 00:25:34.609 Emily Giant: when you say finance, I just wanna make sure we’re on the same page, because I know what Perry and Dean
237 00:25:34.740 ⇒ 00:25:39.820 Emily Giant: Capel use are you talking, Dean? Mark and Wilder when you say, Okay, Gotcha.
238 00:25:39.820 ⇒ 00:25:40.600 Uttam Kumaran: That’s right.
239 00:25:43.020 ⇒ 00:25:44.390 Uttam Kumaran: Okay, that’s helpful.
240 00:25:45.100 ⇒ 00:25:47.827 Uttam Kumaran: I mean, either way, we’ll we’ll break it out.
241 00:25:48.600 ⇒ 00:25:52.359 Uttam Kumaran: But yeah, I I guess I I need to get that answered before we can
242 00:25:53.060 ⇒ 00:25:58.010 Uttam Kumaran: confirm that this makes it into whatever the final like. If it’s if it needs to be broken out.
243 00:25:58.180 ⇒ 00:26:05.760 Uttam Kumaran: because it’s not gonna show up for gross revenue, or if it has to be okay, that’s helpful.
244 00:26:06.360 ⇒ 00:26:16.379 Emily Giant: Tom, I have an email circulating right now, and I’m just gonna loop in anyone who’s not involved on it. That’s on this call. And it’s that this exact conversation. So, Dean, Mark.
245 00:26:16.380 ⇒ 00:26:17.580 Uttam Kumaran: Yeah, you can literally just say.
246 00:26:17.580 ⇒ 00:26:18.650 Emily Giant: I’ve already answered.
247 00:26:19.040 ⇒ 00:26:26.030 Uttam Kumaran: Yeah, you can just send exactly the screenshots, put in notion. You can just say, like, Hey, this is an example of where the Markdown price
248 00:26:26.330 ⇒ 00:26:34.099 Uttam Kumaran: is not exactly showing in in the customer checkout subtotal. Are we marking the difference as a discount, or
249 00:26:34.330 ⇒ 00:26:36.960 Uttam Kumaran: is the markdown price the gross revenue?
250 00:26:38.270 ⇒ 00:26:39.120 Uttam Kumaran: I can.
251 00:26:39.370 ⇒ 00:26:40.730 Uttam Kumaran: Yeah, I can help write that.
252 00:26:45.720 ⇒ 00:26:55.769 Uttam Kumaran: Okay, cool the other questions, what is the conversion by channel? That’s that’s something that we also got yesterday. So that’s fine percent of orders include promo codes. That’s fine.
253 00:26:57.570 ⇒ 00:27:01.049 Uttam Kumaran: Can we talk about the realignment of discount promo logic?
254 00:27:08.130 ⇒ 00:27:09.389 Emily Giant: Sorry. Can you repeat that.
255 00:27:10.150 ⇒ 00:27:15.410 Uttam Kumaran: The realignment of discount promo logic. I just see that in recurring questions.
256 00:27:15.410 ⇒ 00:27:17.459 Emily Giant: So I added that because,
257 00:27:18.090 ⇒ 00:27:36.119 Emily Giant: historically, we’ve changed that logic from like when we were using postgres tables to salesforce to now. And so it’s really difficult to do like a look back. And as we’re like refractoring
258 00:27:36.240 ⇒ 00:27:38.709 Emily Giant: these tables, if we could just
259 00:27:39.180 ⇒ 00:27:43.560 Emily Giant: make sure that historically, those categories persist.
260 00:27:44.960 ⇒ 00:27:45.530 Uttam Kumaran: Okay.
261 00:27:45.940 ⇒ 00:27:57.400 Emily Giant: And that might not be part of like your scope. I could do that. But just as long as Kyle and I are in lockstep on how he’s doing it, so that I can refractor the legacy tables, and they can have a really clean look back.
262 00:28:01.400 ⇒ 00:28:12.479 Uttam Kumaran: And then maybe just before I get to subscription. So ltv, okay, that’s that’s subscriptions. Promo code lift across channels. Okay, that makes sense.
263 00:28:13.080 ⇒ 00:28:19.940 Uttam Kumaran: How does order experience? Okay, it’s a good one. How does operating material within a given day?
264 00:28:24.910 ⇒ 00:28:27.870 Uttam Kumaran: So it’s not going. How much delivery not cover? Should we have.
265 00:28:30.130 ⇒ 00:28:33.869 Uttam Kumaran: Okay, yeah. I mean, the I would say, the bottom 3
266 00:28:34.070 ⇒ 00:28:40.290 Uttam Kumaran: are good. I think it just requires some stitching between some models. But that’s helpful to know.
267 00:28:41.214 ⇒ 00:28:47.270 Uttam Kumaran: Maybe. Yeah. Let’s just Sam, if you’re good to talk a little bit about subscriptions.
268 00:28:47.810 ⇒ 00:28:50.449 Sam Sheil: Yeah, we’re not gonna cover it in 1 min.
269 00:28:51.090 ⇒ 00:28:56.199 Uttam Kumaran: Yeah, yeah, I I just wanted to get. Maybe I’ll just walk through and see if there’s anything that I
270 00:28:56.200 ⇒ 00:28:58.440 Uttam Kumaran: yeah, I’ve done that a lot of subscription.
271 00:28:58.440 ⇒ 00:29:03.670 Sam Sheil: Do you know I am going to give birth any day?
272 00:29:05.530 ⇒ 00:29:18.649 Sam Sheil: So if you want, I can either stay on with you right now, if you have time after, or if you want to like schedule time in the next couple of days to like, go through this, we can but just for your situational awareness.
273 00:29:18.650 ⇒ 00:29:21.699 Uttam Kumaran: Yeah, if maybe if we could stay on for just like 2 more minutes, I’m just.
274 00:29:21.700 ⇒ 00:29:22.550 Sam Sheil: Yeah.
275 00:29:23.400 ⇒ 00:29:31.182 Uttam Kumaran: And I’m gonna see if there’s 1 or 2 that I have questions about. If not, I’m gonna take this back. And then because we’re looking at data.
276 00:29:31.460 ⇒ 00:29:31.830 Sam Sheil: And like.
277 00:29:31.830 ⇒ 00:29:32.359 Uttam Kumaran: So expired.
278 00:29:32.360 ⇒ 00:29:39.012 Sam Sheil: Other people on the team know about this of like Sashi Amanda, like are good resources, too. But just so, just so, you know.
279 00:29:39.660 ⇒ 00:29:43.630 Uttam Kumaran: Okay, so subscriptions active by status that makes sense
280 00:29:44.070 ⇒ 00:29:50.029 Uttam Kumaran: subscriptions. So the for the failure reasons are these like payment issues, or what what it.
281 00:29:50.380 ⇒ 00:30:19.789 Sam Sheil: Yeah. So there’s there’s a couple of different failure reasons that loop would put up. Most of them are payment failure reasons. There’s also, though insufficient inventory. Is a failure, reason, and something that has come up in the past and flags like an issue for us, and how we have our inventory set up. So it’s either payment or inventory related, basically like where loop goes to try to charge the recurring payment. And they can’t.
282 00:30:20.520 ⇒ 00:30:21.840 Uttam Kumaran: Okay, okay, cool.
283 00:30:22.350 ⇒ 00:30:26.450 Uttam Kumaran: And then what is this? What is Bop? Pay as you go.
284 00:30:27.010 ⇒ 00:30:30.630 Sam Sheil: Oh, Bop is just beginning of period.
285 00:30:31.370 ⇒ 00:30:31.589 Uttam Kumaran: So.
286 00:30:31.590 ⇒ 00:30:50.469 Sam Sheil: This one’s kind of interesting, and I don’t know if this would be in scope for you guys, because the way that you traditionally like calculate like cancel rate within a subscription program is like you’re taking the cancels over, like how many subscriptions you had at a period of time which I know, requires like snapshotting, and like.
287 00:30:50.470 ⇒ 00:30:54.539 Uttam Kumaran: Well also because people can cancel and then redo it. So
288 00:30:54.910 ⇒ 00:30:56.809 Sam Sheil: Yeah. So the way that I’m calculating it.
289 00:30:56.810 ⇒ 00:30:57.940 Uttam Kumaran: Periods, yeah.
290 00:30:57.940 ⇒ 00:31:06.030 Sam Sheil: Yeah, so like the way that I’m doing it right now is on like a weekly basis or a monthly basis. I will like.
291 00:31:06.140 ⇒ 00:31:16.300 Sam Sheil: take like I put the calculations in there for cancel. It’s just like cancels over how many active pay as you go. Subscriptions you had at like the beginning of the period.
292 00:31:16.730 ⇒ 00:31:37.049 Sam Sheil: and the reason I do it on pay as you go only is because you can’t cancel a prepaid subscription. It would come through as a refund, you’d have to like reach out to customer service and get it refunded. So if I include all subscriptions in there, it looks like we have like a really baller cancel rate. But like that’s not really fair, because, like, you can’t cancel half of them because they’re prepaid. You know what I mean.
293 00:31:37.500 ⇒ 00:31:53.080 Sam Sheil: whereas turn rate, I’m taking cancels plus ex expert, like expirations, like expired subscriptions. Because when a prepaid sub runs out, it’s becomes expired, and that would be over the total so like right now.
294 00:31:53.080 ⇒ 00:31:54.648 Uttam Kumaran: Pay as you go?
295 00:31:55.140 ⇒ 00:31:59.599 Uttam Kumaran: like. What is the mechanism? Because how is that? Just like? What is the subscription? Then
296 00:31:59.840 ⇒ 00:32:02.079 Uttam Kumaran: like? What are what are they subscribing to?
297 00:32:02.800 ⇒ 00:32:10.650 Sam Sheil: A pay as you go a pay as you go. Subscription. They’re getting charged on like a regular frequency, and we’re shipping them a product. So it’s more like.
298 00:32:10.650 ⇒ 00:32:14.450 Sam Sheil: oh, like a traditional yeah versus, like.
299 00:32:14.450 ⇒ 00:32:16.030 Uttam Kumaran: Pay upfront. Is there a discount.
300 00:32:16.550 ⇒ 00:32:30.470 Sam Sheil: So the thing that’s really different about our subscription program, at least right now, is that for people use prepaid as a gifting mechanism, and we don’t auto renew those subscriptions.
301 00:32:31.163 ⇒ 00:32:41.949 Sam Sheil: So they’re more like you’re but you’re essentially buying like a pack of deliveries where it’s like, oh, I’m gonna send you flowers for your birthday. I want to send you 3 bouquets over the next 3 months.
302 00:32:42.558 ⇒ 00:32:58.309 Sam Sheil: I think that that could change in the future. The reason we do that from like a business logic, perspective is like, because maybe we use it for gifting. And we actually make more money with the recurring. So there’s not currently like an incentive to prepay.
303 00:32:58.710 ⇒ 00:32:59.930 Sam Sheil: But I could see that change.
304 00:32:59.930 ⇒ 00:33:00.520 Uttam Kumaran: I see.
305 00:33:00.520 ⇒ 00:33:12.239 Sam Sheil: Feature. So for the from a data perspective, I think it’s like, it’s mostly important to be able to like kind of cut all this data by whether they like, did a prepaid subscription or a pay as you go, subscription.
306 00:33:12.860 ⇒ 00:33:18.390 Uttam Kumaran: I see. Okay, it’s not typical, like those aren’t typical, like competing products. Because I see what you mean.
307 00:33:18.390 ⇒ 00:33:20.899 Sam Sheil: Yeah, yeah, yeah, you’re not like.
308 00:33:21.300 ⇒ 00:33:29.029 Sam Sheil: like, there is the option to like, go on our website and subscribe to a particular bouquet. No one does that. It’s all through like.
309 00:33:29.280 ⇒ 00:33:34.390 Sam Sheil: it’s like a separate subscription program where, like, the product is different. Yeah.
310 00:33:34.390 ⇒ 00:33:44.790 Uttam Kumaran: Okay, okay, that makes sense. Yeah? And in terms of like, beginning of month, end of month. Yeah, we’ll snapshot basically numbers across categories. And then do the differences.
311 00:33:44.790 ⇒ 00:33:45.210 Sam Sheil: Okay.
312 00:33:45.210 ⇒ 00:33:55.419 Uttam Kumaran: And then, additionally, we I want to not only do subs by category, but also like the revenue. So you’ll see. You’ll see like how much active subscription revenue canceled
313 00:33:56.066 ⇒ 00:34:00.910 Uttam Kumaran: expanded like again I have to look at. If there’s downgrades upgrades within a.
314 00:34:00.910 ⇒ 00:34:01.250 Sam Sheil: Yeah.
315 00:34:01.250 ⇒ 00:34:02.130 Uttam Kumaran: Program.
316 00:34:03.340 ⇒ 00:34:07.659 Sam Sheil: We don’t have them right now. But it’s a feature that loops as they’re building.
317 00:34:08.159 ⇒ 00:34:09.009 Uttam Kumaran: Okay. Okay. Cool.
318 00:34:09.010 ⇒ 00:34:12.549 Sam Sheil: I wouldn’t hold my breath on that over the next few months, but.
319 00:34:12.889 ⇒ 00:34:13.719 Uttam Kumaran: Okay.
320 00:34:13.859 ⇒ 00:34:19.429 Uttam Kumaran: okay? And then, yeah, basically, all your subscription actions are exactly like the way we look at it. So
321 00:34:19.829 ⇒ 00:34:25.309 Uttam Kumaran: pause resumed, and then skipped is a concept.
322 00:34:25.690 ⇒ 00:34:29.130 Sam Sheil: Yeah, there’s some of the stuff they have in there like
323 00:34:29.260 ⇒ 00:34:31.460 Sam Sheil: to me, like a skip isn’t.
324 00:34:31.469 ⇒ 00:34:33.439 Sam Sheil: But do those affect financial?
325 00:34:34.280 ⇒ 00:34:35.380 Sam Sheil: No like? Honestly.
326 00:34:35.389 ⇒ 00:34:35.889 Uttam Kumaran: First.st
327 00:34:35.889 ⇒ 00:34:42.599 Sam Sheil: The only ones that I really report on, like on a regular basis are whether you
328 00:34:44.739 ⇒ 00:34:55.719 Sam Sheil: whether you cancel, pause, reactivate, resume, like anything that would change kind of like this. The active status of your subscription.
329 00:34:55.849 ⇒ 00:35:01.239 Sam Sheil: You can, like a customer, can reschedule, delay, skip.
330 00:35:01.409 ⇒ 00:35:11.199 Sam Sheil: they kind of all, do the same thing, and it just enables them to have more flexibility. Those actions are in loop. I do look at them occasionally, but it doesn’t.
331 00:35:11.369 ⇒ 00:35:13.489 Sam Sheil: It? It doesn’t impact like
332 00:35:13.879 ⇒ 00:35:21.709 Sam Sheil: are like active subscriber count, or like anything really, financially, just moving around the revenue. Basically.
333 00:35:22.870 ⇒ 00:35:23.450 Uttam Kumaran: Okay?
334 00:35:23.950 ⇒ 00:35:26.819 Uttam Kumaran: And then what is resumed versus reactivated is.
335 00:35:26.970 ⇒ 00:35:30.579 Sam Sheil: If you cancel, so if you cancel and then
336 00:35:30.800 ⇒ 00:35:34.489 Sam Sheil: uncancell, the uncancell action is reactivate.
337 00:35:34.820 ⇒ 00:35:39.620 Sam Sheil: If you pause and unpause, the unpause is a resume.
338 00:35:41.320 ⇒ 00:35:46.190 Uttam Kumaran: And then what is pause versus cancel like? Is there link.
339 00:35:46.970 ⇒ 00:35:52.580 Sam Sheil: Pause is when you pause, you can select like it’ll prompt you. Ha! Like. Do you want? You can pause up to.
340 00:35:53.030 ⇒ 00:35:55.020 Sam Sheil: 3 deliveries.
341 00:35:55.340 ⇒ 00:36:08.229 Sam Sheil: And so it’s like kind of like. Do you want to take a break as opposed to canceling your subscription altogether? But you can only, I believe, pause 3 quarters like at a time. So it’s like more of a temporary thing. Then cancels like you’re done.
342 00:36:10.210 ⇒ 00:36:11.019 Uttam Kumaran: Okay, okay?
343 00:36:12.230 ⇒ 00:36:21.030 Uttam Kumaran: Oh, cool. And then, yeah. Ltv.
344 00:36:21.602 ⇒ 00:36:25.349 Uttam Kumaran: yeah. Can you talk about how you’re thinking about that as well.
345 00:36:25.980 ⇒ 00:36:27.340 Sam Sheil: Which one is this.
346 00:36:28.570 ⇒ 00:36:33.899 Uttam Kumaran: For? Ltv, I guess we we’re we have like Ltv by cohort here.
347 00:36:35.370 ⇒ 00:36:39.620 Uttam Kumaran: Like, is that something that you guys are looking for or looking at in terms of subscriptions.
348 00:36:40.000 ⇒ 00:36:53.129 Sam Sheil: I think it’s I think that’s like an overall comment. But it is like one of the things that I do look at in north beam, specifically like the times that Chris and I are just kind of like checking on our like tax for the subscription program, or like
349 00:36:53.360 ⇒ 00:36:54.720 Sam Sheil: like, it would be
350 00:36:54.830 ⇒ 00:37:04.359 Sam Sheil: helpful to be able to cut Ltv. By like subscribers versus non subscribers, because the Ltv. Is very different between the 2.
351 00:37:04.360 ⇒ 00:37:13.020 Uttam Kumaran: Yeah, but for like non subscribers, are you guys like.
352 00:37:13.140 ⇒ 00:37:21.860 Uttam Kumaran: is there some certain logic? You know, I was just having this conversation this morning is because typically you want to back into like, okay, what is the average like order frequency.
353 00:37:22.230 ⇒ 00:37:22.840 Sam Sheil: Yeah.
354 00:37:22.840 ⇒ 00:37:27.960 Uttam Kumaran: How often they come back. You guys have a lot of it’s of data. So yeah.
355 00:37:28.380 ⇒ 00:37:30.690 Chris: Yeah, pk, has all those rules.
356 00:37:31.607 ⇒ 00:37:38.290 Chris: Basically. And the the short version is, we consider someone an active customer if they’ve placed
357 00:37:39.161 ⇒ 00:37:49.438 Chris: if they’re a new customer, or if they’ve placed 2 orders in the last 13 months, and then we consider somebody reactivated. Let’s say they
358 00:37:50.120 ⇒ 00:38:01.830 Chris: they purchased, you know, for mother’s day, 2023, and then came back and purchased for mother’s day 2025. They wouldn’t be considered an active repeat. They could be considered a reactivated repeat.
359 00:38:04.020 ⇒ 00:38:07.119 Chris: But Pk can send over that like the
360 00:38:08.230 ⇒ 00:38:09.829 Chris: like. The details of that logic.
361 00:38:09.830 ⇒ 00:38:10.490 Uttam Kumaran: Great.
362 00:38:11.200 ⇒ 00:38:12.040 Uttam Kumaran: Okay. Okay.
363 00:38:12.040 ⇒ 00:38:15.169 Chris: Where? Oh, how, how would you like to receive that information?
364 00:38:18.580 ⇒ 00:38:21.509 Uttam Kumaran: If you have it in a doc that I can reference that’d be great.
365 00:38:22.380 ⇒ 00:38:23.639 Chris: You just want it in the slack Channel.
366 00:38:24.750 ⇒ 00:38:26.319 Uttam Kumaran: Yeah, slack channel is perfect.
367 00:38:33.100 ⇒ 00:38:34.180 Uttam Kumaran: Okay.
368 00:38:40.590 ⇒ 00:38:41.380 Uttam Kumaran: okay.
369 00:38:41.550 ⇒ 00:38:49.020 Uttam Kumaran: I think that’s kind of all my questions, for now I’m probably have some more questions. Once we get to see the subscription data.
370 00:38:49.210 ⇒ 00:38:51.449 Uttam Kumaran: I get to see a couple of examples.
371 00:38:54.690 ⇒ 00:38:59.819 Uttam Kumaran: so, Sam, I will let you know. But I think that’s probably I don’t know, Emily. Is there anything else we want to cover.
372 00:39:00.050 ⇒ 00:39:11.450 Emily Giant: Last thing I sent just for Chris or Sashi in the chat. I want to get this email out to finance, so we can just have it documented. I wrote
373 00:39:11.840 ⇒ 00:39:19.247 Emily Giant: a description of Markdown. I wanna make sure I just captured all of like the cases where Markdown would be considered
374 00:39:19.890 ⇒ 00:39:22.169 Emily Giant: If you could just review and send any
375 00:39:22.700 ⇒ 00:39:25.410 Emily Giant: edits, or just say any edits. I can just write.
376 00:39:25.410 ⇒ 00:39:26.750 Chris: Put it in notion here.
377 00:39:27.090 ⇒ 00:39:28.402 Emily Giant: No in the
378 00:39:30.245 ⇒ 00:39:30.479 Uttam Kumaran: Chat.
379 00:39:31.720 ⇒ 00:39:32.610 Chris: Listen, to.
380 00:39:35.350 ⇒ 00:39:38.940 Uttam Kumaran: Yeah, mark down price and gross revenue. We use the price before.
381 00:39:41.450 ⇒ 00:39:43.750 Uttam Kumaran: Yeah, probably the only thing.
382 00:39:44.520 ⇒ 00:39:51.440 Uttam Kumaran: it’s also like, I would probably just say a different say, you can maybe say it again. A different way is like, is the Markdown
383 00:39:52.240 ⇒ 00:39:53.979 Uttam Kumaran: included in discounts?
384 00:39:54.480 ⇒ 00:39:57.649 Uttam Kumaran: Or is it like a separate? Are they thinking about separately.
385 00:39:58.340 ⇒ 00:40:03.780 Emily Giant: So to clarify a markdown is a sale on the site, ingress, revenue, or.
386 00:40:04.800 ⇒ 00:40:08.739 Uttam Kumaran: Oh, yeah, I guess the way, yeah, go ahead. Go ahead.
387 00:40:09.300 ⇒ 00:40:12.689 Chris: I would use the doubles and triples as like a good example.
388 00:40:13.680 ⇒ 00:40:17.440 Chris: because we show doubles and triples is marked down all the time.
389 00:40:17.850 ⇒ 00:40:19.989 Emily Giant: Is that Markdown Price.
390 00:40:20.110 ⇒ 00:40:24.120 Chris: Being calculated into gross revenue at all
391 00:40:24.770 ⇒ 00:40:36.630 Chris: is the original, like the the original price that we’re showing being calculated in gross revenue, or is only the markdown price being calculated, so does the mark marked down, discount.
392 00:40:36.860 ⇒ 00:40:42.660 Chris: show up with any of our financial reporting? Is it considered, when calculating gross revenue.
393 00:40:44.580 ⇒ 00:40:45.480 Emily Giant: Okay, gotcha. So.
394 00:40:45.480 ⇒ 00:40:53.140 Chris: Because if they if they answer for that for doubles and triples, then we’ll know the answer for singles, because singles is kind of like one offs, but doubles and triples. It’s always on.
395 00:40:55.010 ⇒ 00:40:58.999 Emily Giant: And then also like for bundles and kits, I would think that those are.
396 00:40:59.550 ⇒ 00:41:11.439 Emily Giant: I know that like snop calculates it at the percentage weight of the object in the order. That’s like the revenue revenue that’s attributed to it, not the
397 00:41:11.560 ⇒ 00:41:13.119 Emily Giant: price of each item.
398 00:41:14.000 ⇒ 00:41:15.769 Chris: That’s a great question. I don’t know.
399 00:41:19.870 ⇒ 00:41:24.319 Uttam Kumaran: Yeah, probably only add on is would be. If they do, they look at Markdown.
400 00:41:24.530 ⇒ 00:41:28.670 Uttam Kumaran: Do they have a carve out for Markdown at all because I’d be interested.
401 00:41:29.000 ⇒ 00:41:35.639 Emily Giant: Yeah, okay, I’ll use the double and triples, because I think that that’s a really like clear
402 00:41:36.360 ⇒ 00:41:39.920 Emily Giant: thing. I have a feeling that the bundles question will prompt
403 00:41:40.120 ⇒ 00:41:43.611 Emily Giant: another discussion, which is a necessary discussion.
404 00:41:44.560 ⇒ 00:41:50.289 Emily Giant: but yeah, y’all will be included in that email. So if there’s anything you want to add.
405 00:41:50.480 ⇒ 00:41:54.419 Emily Giant: once I send it, please do. I want to make sure that we
406 00:41:54.870 ⇒ 00:41:56.609 Emily Giant: get this right the 1st time.
407 00:41:59.150 ⇒ 00:42:00.650 Emily Giant: or at least the second time.
408 00:42:02.890 ⇒ 00:42:26.520 Sam Sheil: I’m sure I know finance knows this. I. The way that discounts kind of come through within subscription is also really weird. Because, yeah, you okay, you know. But I could see there being a world where, like the 1st pass of this is like holy shit. Look at all these discounts for subscription, and it’s all the discounted like 1st digital product. So.
409 00:42:27.040 ⇒ 00:42:35.619 Emily Giant: You should see the Frankenstein’s monster that have currently to like, try and rectify the discounts that are not discounts at all.
410 00:42:35.620 ⇒ 00:42:36.730 Sam Sheil: Yeah, okay.
411 00:42:36.770 ⇒ 00:42:37.799 Emily Giant: Call out, Sam!
412 00:42:37.800 ⇒ 00:42:38.865 Sam Sheil: Flagging.
413 00:42:39.930 ⇒ 00:42:43.989 saschi: Probably also have the free, the subscription shipping discount too.
414 00:42:43.990 ⇒ 00:42:44.870 Sam Sheil: Yeah.
415 00:42:45.380 ⇒ 00:42:49.850 Uttam Kumaran: Yeah, that’s why the biggest thing I want to look at is you’ll you’ll get a sense of like sub
416 00:42:49.970 ⇒ 00:42:58.689 Uttam Kumaran: discounted quantity, but also the discounted revenue. And that’s the balance, right? Like just that. Everything is discounted. If the value of the discount is
417 00:42:59.170 ⇒ 00:43:02.710 Uttam Kumaran: lower, then that will be like the normalization.
418 00:43:03.100 ⇒ 00:43:04.890 Uttam Kumaran: See how both.
419 00:43:05.470 ⇒ 00:43:15.469 Sam Sheil: Because, like, we really aren’t doing that much discounting of subscription, because it’s not like a product on our website like it, yeah.
420 00:43:20.230 ⇒ 00:43:21.050 Uttam Kumaran: I see.
421 00:43:21.050 ⇒ 00:43:25.819 Sam Sheil: Yeah, like, it’s, it’s its own thing.
422 00:43:26.470 ⇒ 00:43:30.590 Uttam Kumaran: Yeah, I mean again, I would say, in that case, it also comes down to finance, like, what are they doing?
423 00:43:30.590 ⇒ 00:43:32.350 Uttam Kumaran: Yeah, yeah, like.
424 00:43:32.350 ⇒ 00:43:32.680 Sam Sheil: Question.
425 00:43:32.680 ⇒ 00:43:42.029 Sam Sheil: Margin implications like that’s like what we’ve what we’ve been trying to get answered for a long time. But it’s not. It’s not answered through
426 00:43:42.360 ⇒ 00:43:43.960 Sam Sheil: a discount line.
427 00:43:44.380 ⇒ 00:43:45.050 Uttam Kumaran: Okay.
428 00:43:45.290 ⇒ 00:43:50.789 Sam Sheil: Yeah, it’s like a what what is like the
429 00:43:51.160 ⇒ 00:43:55.589 Sam Sheil: but it’s like the gross profit of the product that we ended up shipping within the subscription.
430 00:43:55.590 ⇒ 00:43:55.910 Uttam Kumaran: Yes.
431 00:43:55.910 ⇒ 00:43:57.120 Sam Sheil: Program. Yeah.
432 00:43:57.730 ⇒ 00:44:02.530 Uttam Kumaran: So basically, it’s like, is that what for me, I’m like, does that fall under cost of goods?
433 00:44:03.480 ⇒ 00:44:08.449 Sam Sheil: Yeah, I think, yes, yeah, like, it’s not really a marketing
434 00:44:09.450 ⇒ 00:44:12.910 Sam Sheil: data point, because it’s not going to come up in the discount line.
435 00:44:13.160 ⇒ 00:44:14.149 Uttam Kumaran: Yeah, yeah.
436 00:44:15.830 ⇒ 00:44:20.320 Sam Sheil: And if finance hasn’t asked for that, I’m formally requesting it as an okay.
437 00:44:26.490 ⇒ 00:44:31.618 Uttam Kumaran: Okay, great. I think that’s all I had today.
438 00:44:32.590 ⇒ 00:44:50.670 Uttam Kumaran: so one more of these meetings today, and then we’ll ideally. Our goal is to get to like a be one of the stock by Friday, and we’ll send it out. And again, we, the goal of this is like we’re gonna create a series of data models that basically can answer these questions on the granularities that we need.
439 00:44:51.214 ⇒ 00:44:56.889 Uttam Kumaran: I think this is probably the more complicated the subscription stuff is all fairly net new.
440 00:44:57.190 ⇒ 00:45:02.740 Uttam Kumaran: And then basically, all these carve outs for these like decisions to bucket things. I wanna make sure end up
441 00:45:02.840 ⇒ 00:45:04.149 Uttam Kumaran: documented as possible.
442 00:45:04.150 ⇒ 00:45:04.730 Sam Sheil: Yeah.
443 00:45:05.270 ⇒ 00:45:10.480 Sam Sheil: Well, Tom, congratulations! You already know more about subscriptions than 90% of the people that work here. So.
444 00:45:10.570 ⇒ 00:45:18.220 Uttam Kumaran: I just, I’ve I’ve worked with subscription logic for a long time, and it can be a different way of thinking about data.
445 00:45:18.220 ⇒ 00:45:20.350 Sam Sheil: It’s like, never the same. It’s just.
446 00:45:20.350 ⇒ 00:45:23.850 Uttam Kumaran: Yeah. And you have these like time. Bot, it’s the snapshot logic cause this.
447 00:45:23.850 ⇒ 00:45:26.690 Sam Sheil: Yes, it’s it’s status based revenue.
448 00:45:27.372 ⇒ 00:45:33.220 Uttam Kumaran: And you have like men. And like, I think the complicated piece is like, I’m not sure about
449 00:45:33.820 ⇒ 00:45:42.650 Uttam Kumaran: how we’re gonna we’re gonna have to think about supporting the week thing like, later on, we’ll aim for like, basically month over month changes. And then we’ll just need basically
450 00:45:43.290 ⇒ 00:45:49.949 Uttam Kumaran: snapshots and stuff. But yeah, it’s all it’s but subscriptions is a great product, like.
451 00:45:49.950 ⇒ 00:45:50.700 Sam Sheil: Yeah.
452 00:45:50.860 ⇒ 00:45:55.409 Sam Sheil: Monthly is a good place to start. Month monthly is like palatable.
453 00:45:55.620 ⇒ 00:45:59.020 Uttam Kumaran: When we do monthly and we get it right. It’s it’s easy to switch.
454 00:45:59.020 ⇒ 00:46:02.650 Sam Sheil: Monthly data than inaccurate weekly data. For sure.
455 00:46:03.140 ⇒ 00:46:03.870 Uttam Kumaran: Yeah.
456 00:46:06.250 ⇒ 00:46:06.910 Sam Sheil: Alright, cool.
457 00:46:07.670 ⇒ 00:46:11.160 Uttam Kumaran: Perfect. Well, thank you. Everyone. Appreciate the time. Thanks for going over.
458 00:46:11.840 ⇒ 00:46:12.550 Sam Sheil: Bye.