Meeting Title: Eden Analysis and ABC Modeling Check-in Date: 2026-01-28 Meeting participants: Amber Lin, Robert Tseng
WEBVTT
1 00:04:01.400 ⇒ 00:04:02.370 Robert Tseng: Amber.
2 00:04:07.800 ⇒ 00:04:08.820 Amber Lin: Hi there!
3 00:04:15.270 ⇒ 00:04:17.060 Amber Lin: What are you having for lunch?
4 00:04:28.370 ⇒ 00:04:30.710 Amber Lin: Wait, I can’t hear you. Are you talking?
5 00:04:34.130 ⇒ 00:04:36.560 Amber Lin: - that’s weird.
6 00:04:48.620 ⇒ 00:04:49.880 Robert Tseng: Can you hear me now?
7 00:04:49.880 ⇒ 00:04:51.059 Amber Lin: Yeah, I can hear you now.
8 00:04:51.220 ⇒ 00:04:51.700 Robert Tseng: Okay.
9 00:04:51.700 ⇒ 00:04:52.330 Amber Lin: Okay.
10 00:04:53.310 ⇒ 00:04:55.429 Robert Tseng: Oh, I was saying, how was Portland?
11 00:04:56.120 ⇒ 00:05:12.010 Amber Lin: It was pretty good. I went, I met Annie on Friday, and she’s doing pretty well, she’s not working. She wants to… I think that’s probably the reason she left, is I think she wanted time for…
12 00:05:12.100 ⇒ 00:05:19.640 Amber Lin: to explore, like, her interests and stuff, so… it sounds like she’s having fun. .
13 00:05:19.640 ⇒ 00:05:22.489 Robert Tseng: I mean, I don’t know if you can… what’s she doing? I’m curious.
14 00:05:22.490 ⇒ 00:05:33.570 Amber Lin: I think she’s… she’s… Let’s see… she wanted to do some crocheting, she’s volunteering at some shelters.
15 00:05:36.080 ⇒ 00:05:50.470 Amber Lin: And then, I think she’s just chilling. I asked her, like, hey, do you want to go back to work? She’s like, nope, not for now. She was thinking… I think she was joking that she wanted to open…
16 00:05:50.640 ⇒ 00:06:04.589 Amber Lin: like, a bake shop, a coffee shop or some sort? I wasn’t sure, like, I don’t really remember, but I think she said, like, she’s almost 30, and she wants to think about, like, if she want to keep working.
17 00:06:05.380 ⇒ 00:06:05.890 Robert Tseng: Yeah.
18 00:06:05.890 ⇒ 00:06:06.560 Amber Lin: Yeah.
19 00:06:07.620 ⇒ 00:06:12.169 Amber Lin: So, it’s interest… it’s nice to see her at a good time.
20 00:06:12.590 ⇒ 00:06:15.720 Robert Tseng: Good! Yeah, I’m glad that, I’m glad that worked out.
21 00:06:17.140 ⇒ 00:06:20.640 Amber Lin: Yeah, and then I went snowboarding, and I’m still sore.
22 00:06:21.510 ⇒ 00:06:29.870 Amber Lin: Like, I fell front and back, and I felt shook. It’s like I jumped off a cliff into the water, and I got smashed.
23 00:06:30.010 ⇒ 00:06:30.420 Robert Tseng: Yep.
24 00:06:30.420 ⇒ 00:06:34.699 Amber Lin: On the snow, I was like, oh, my whole body is so… is sore.
25 00:06:35.380 ⇒ 00:06:37.879 Robert Tseng: Yeah, you’re not used to taking impact like that.
26 00:06:37.880 ⇒ 00:06:38.960 Amber Lin: -
27 00:06:39.600 ⇒ 00:06:40.520 Amber Lin: Yeah.
28 00:06:40.650 ⇒ 00:06:46.590 Amber Lin: Well, how was your flight? Did it get delayed at all, or were you able to get back in time?
29 00:06:46.950 ⇒ 00:06:53.499 Robert Tseng: Yeah, no, I was supposed to land yesterday morning, but, things got delayed, and, like, I was like.
30 00:06:54.660 ⇒ 00:06:58.300 Robert Tseng: I was already, like, kind of meh about the red-eye, and so…
31 00:06:58.620 ⇒ 00:07:05.910 Robert Tseng: Anyway, they offered, like, me to take a different flight in the morning, so…
32 00:07:06.230 ⇒ 00:07:17.470 Robert Tseng: I was like, you know what? I think I’d rather just sleep a little bit more. Yeah, I mean, it definitely helped me, like, I didn’t… I didn’t have to nap or anything. I’m already back to normal here, so…
33 00:07:17.470 ⇒ 00:07:18.020 Amber Lin: Yeah, that’s.
34 00:07:18.020 ⇒ 00:07:26.549 Robert Tseng: But it wasn’t convenient to reschedule all these meetings, and the Wi-Fi on the plane sucked, so… yeah. I mean, I think only Delta has good Wi-Fi, to be honest.
35 00:07:26.550 ⇒ 00:07:27.340 Amber Lin: Philly!
36 00:07:27.610 ⇒ 00:07:29.429 Robert Tseng: United Wi-Fi is so bad.
37 00:07:29.430 ⇒ 00:07:35.919 Amber Lin: Okay, I’ll try next time. Yeah, I even… I think Alaska’s seats are better than United, and…
38 00:07:35.920 ⇒ 00:07:39.310 Robert Tseng: Alaska has the best seats, Delta has the best Wi-Fi.
39 00:07:39.310 ⇒ 00:07:40.630 Amber Lin: Oh, okay.
40 00:07:41.340 ⇒ 00:07:42.450 Amber Lin: Okay.
41 00:07:42.510 ⇒ 00:07:47.209 Robert Tseng: Well, I’ve been only flying budget for the past few years, so I wouldn’t even know.
42 00:07:47.370 ⇒ 00:07:49.350 Robert Tseng: Oh, okay. Yeah, no, I mean, that’s.
43 00:07:49.350 ⇒ 00:07:52.420 Amber Lin: Here it has good nothing, except for prices.
44 00:07:52.960 ⇒ 00:07:56.080 Robert Tseng: I fly Spirit to Texas, so I’ll be doing that.
45 00:07:56.080 ⇒ 00:07:56.410 Amber Lin: Yeah.
46 00:07:57.360 ⇒ 00:07:58.020 Robert Tseng: Hmm.
47 00:07:58.430 ⇒ 00:08:00.950 Amber Lin: Cool. I, I think…
48 00:08:00.960 ⇒ 00:08:18.559 Amber Lin: On my plate, I have… I want to talk a little bit about the Eden analysis, to see if I can get some inspiration for next steps from you. And then if we have time left over, I would like to talk about the ABC modeling, but I don’t think we’ll have time for that.
49 00:08:18.640 ⇒ 00:08:19.640 Amber Lin: Okay.
50 00:08:20.190 ⇒ 00:08:39.340 Amber Lin: So, on the Eden side, I can talk and you can just keep eating. I, I wanted to start… like, it took a while for me, because I needed to go through the different fields, because I mainly was using orders and order sum… Order summary, but…
51 00:08:39.549 ⇒ 00:08:47.560 Amber Lin: There’s also other, other fields, like cancel, I think order with canceled that I also checked.
52 00:08:47.650 ⇒ 00:09:04.229 Amber Lin: And I think to start with, the data range on orders is, is limited. I think it’s only from 2023 to March 2025, so I actually… I really wanted to look at new orders, because I know you said they changed the…
53 00:09:04.300 ⇒ 00:09:08.869 Amber Lin: Monthly subscriptions to, like, the different set.
54 00:09:08.990 ⇒ 00:09:09.550 Robert Tseng: Yeah.
55 00:09:09.550 ⇒ 00:09:12.459 Amber Lin: I wanted to look at that, but,
56 00:09:12.840 ⇒ 00:09:24.419 Amber Lin: But the order summary doesn’t have, like, the order status, it doesn’t have, the order was abandoned, it was, it was canceled, or it’s an error, so…
57 00:09:24.550 ⇒ 00:09:34.880 Amber Lin: I wasn’t able to use that, and just using refunds and cancellations, the difference was very minimal. It was, like, 1%, 2% difference.
58 00:09:35.360 ⇒ 00:09:40.909 Amber Lin: In terms of margins, so I… but when I used,
59 00:09:41.050 ⇒ 00:09:53.980 Amber Lin: When I filtered out the orders that was abandoned, that was, had an error or was canceled, the margin was very different, when I used the orders table.
60 00:09:54.600 ⇒ 00:10:08.029 Amber Lin: So, I think my first question is, is there any way to, get that field also in order summary, or is there a way to expand the date range for the orders table?
61 00:10:09.740 ⇒ 00:10:11.200 Robert Tseng: Yeah,
62 00:10:17.050 ⇒ 00:10:20.619 Robert Tseng: Wait, by expanding date range in the orders table?
63 00:10:20.620 ⇒ 00:10:26.600 Amber Lin: The orders table, I only found, the data goes to March 2025.
64 00:10:26.600 ⇒ 00:10:30.280 Robert Tseng: Yeah, it was because when that’s when we started doing it, yeah.
65 00:10:31.090 ⇒ 00:10:35.659 Amber Lin: Sorry, it, like, stops at March 2025. I’m not sure if I’m looking at the right.
66 00:10:35.660 ⇒ 00:10:37.149 Robert Tseng: Oh, what? Oh, wow.
67 00:10:37.270 ⇒ 00:10:41.359 Robert Tseng: Have you looked at the data platform documentation? Is it just not good?
68 00:10:41.590 ⇒ 00:10:43.519 Amber Lin: Let me see…
69 00:10:53.180 ⇒ 00:10:54.130 Amber Lin: Mmm.
70 00:11:06.080 ⇒ 00:11:08.299 Amber Lin: Okay, checking right now.
71 00:11:12.780 ⇒ 00:11:13.265 Amber Lin: Mmm…
72 00:11:19.610 ⇒ 00:11:28.690 Amber Lin: I mean, like, if you’re sure there’s… there’s… it’s gotta be somewhere, I can just go check with, like, Demulio or away. I don’t have to take your time for that here.
73 00:11:28.690 ⇒ 00:11:32.890 Robert Tseng: Yeah, all good. I mean, like… Yeah, product sales summary.
74 00:11:33.580 ⇒ 00:11:39.330 Robert Tseng: order sum… order summary is the main table. You should be able to drill down, yeah, so…
75 00:11:39.330 ⇒ 00:11:49.660 Amber Lin: Yeah, I’ve been using that, it’s just I don’t think it has the field of, like, order status. There’s… I don’t remember seeing, like, there’s abandoned orders in there.
76 00:11:51.090 ⇒ 00:11:58.989 Robert Tseng: Yeah, it’s been a while since I’ve been in these tables, but what… the way that I think order summary is structured is that you have…
77 00:12:02.090 ⇒ 00:12:06.940 Robert Tseng: Every time there is a status, like, there’s duplicate rows in order summary, because it’s, like, every, every status.
78 00:12:06.940 ⇒ 00:12:08.679 Amber Lin: 70%, yeah.
79 00:12:09.160 ⇒ 00:12:15.529 Robert Tseng: Yeah, so… like, that’s how you would signal, like, if there’s a… if there’s been a status change. So…
80 00:12:15.530 ⇒ 00:12:16.670 Amber Lin: Mmm.
81 00:12:18.600 ⇒ 00:12:36.760 Robert Tseng: Yeah, I mean, obviously, BASC order statuses don’t really mean much, because, like, every order starts at abandoned, pending could… like, 70% of pending orders end up becoming real orders. There’s all these, like, kind of, you know, things that we’ve… that we’ve, like, learned about order statuses, so I wouldn’t just use… there is no clean order status field that you can use.
82 00:12:37.000 ⇒ 00:12:39.540 Robert Tseng: You have to just look at, like, when…
83 00:12:39.870 ⇒ 00:12:49.480 Robert Tseng: I think order summary captures when every order moves into the next stage. It’s not by status, but, like, it’s assumed… it’s an assumed status, and .
84 00:12:50.340 ⇒ 00:12:53.649 Robert Tseng: At least in, like, the product drill-down dashboard, or…
85 00:12:53.870 ⇒ 00:13:06.840 Robert Tseng: Is that even what it’s called? Like, yeah, in some of the Tableau dashes, there’s an ops dashboard where… like, a farm ops dashboard, where, you can see us breaking out orders by, like.
86 00:13:07.350 ⇒ 00:13:07.940 Amber Lin: Fair enough.
87 00:13:08.330 ⇒ 00:13:15.269 Robert Tseng: then, like, however that is modeled, like, that’s… I mean, that’s what I would assume is the best way to look at stages.
88 00:13:15.720 ⇒ 00:13:17.000 Amber Lin: That works.
89 00:13:17.300 ⇒ 00:13:19.550 Amber Lin: That works.
90 00:13:19.550 ⇒ 00:13:31.820 Robert Tseng: Yeah, I need to go back and clean up this data platform documentation. This is just… nobody on this team has ever really done anything with it, so I need to, like, actually do it. Especially if Jasmine’s gonna come in, she’s gonna have no clue what’s going on.
91 00:13:31.820 ⇒ 00:13:32.360 Amber Lin: Yeah.
92 00:13:34.010 ⇒ 00:13:40.750 Robert Tseng: Yeah, so, I mean, that’s more of, like, kind of an end-of-week task for me, like, I’m just gonna… I’ll probably redo this.
93 00:13:41.250 ⇒ 00:13:53.869 Amber Lin: Okay, so I’ll figure out how to use it, use the order summary table instead. I think that was, like, that was, like, that sentence was very helpful that they are just different statuses, because I thought they were just duplicates.
94 00:13:53.930 ⇒ 00:14:09.190 Amber Lin: So that’s very helpful, and I’ll try to use that to deepen analysis, but I do think I’m on the right track. Like, I’m using, I’m seeing what makes a difference when I exclude, like, orders of certain statuses.
95 00:14:09.190 ⇒ 00:14:10.159 Robert Tseng: Yeah, yeah.
96 00:14:10.160 ⇒ 00:14:18.150 Amber Lin: Okay. And I know from when I was working with Annie, like, way back then, when she made that dashboard, yeah.
97 00:14:18.450 ⇒ 00:14:32.490 Amber Lin: like, they’re… they receive the order, and then they, like, they send it to pharmacy, and then pharmacy has to send it out. So there’s each step of the way. But I… I remember we were talking about, of…
98 00:14:33.110 ⇒ 00:14:38.999 Amber Lin: Like, orders that… Get abandoned at that stage, or…
99 00:14:39.100 ⇒ 00:14:40.620 Amber Lin: like,
100 00:14:40.760 ⇒ 00:14:47.949 Amber Lin: Can you tell me a little bit more about, like, abandoned orders? Like, is it just people abandoning it, or is that the default.
101 00:14:47.950 ⇒ 00:14:48.280 Robert Tseng: Yeah.
102 00:14:48.280 ⇒ 00:14:49.770 Amber Lin: Everything starts with.
103 00:14:50.190 ⇒ 00:14:53.060 Robert Tseng: It’s the default stage everything starts with, but, like…
104 00:14:55.090 ⇒ 00:14:58.740 Robert Tseng: Yeah, because an order goes through, and it doesn’t…
105 00:14:58.870 ⇒ 00:15:04.980 Robert Tseng: like, you… but you still have to get, like, doctor approval. If the doctor approval doesn’t come.
106 00:15:05.240 ⇒ 00:15:05.729 Amber Lin: It doesn’t like that.
107 00:15:05.730 ⇒ 00:15:08.109 Robert Tseng: order never materializes.
108 00:15:08.110 ⇒ 00:15:08.500 Amber Lin: sweet.
109 00:15:08.500 ⇒ 00:15:12.750 Robert Tseng: It could get approved, and then it goes to…
110 00:15:13.000 ⇒ 00:15:15.389 Robert Tseng: It’ll be sent to the pharmacy.
111 00:15:17.000 ⇒ 00:15:22.380 Robert Tseng: But then the pharmacy could cancel it, for whatever reason. Like, that’s another reason why it could stay abandoned.
112 00:15:22.380 ⇒ 00:15:22.830 Amber Lin: Good.
113 00:15:22.830 ⇒ 00:15:29.480 Robert Tseng: They could also go to the pharmacy, and they decide to It’s like…
114 00:15:29.840 ⇒ 00:15:39.109 Robert Tseng: Because by the time it’s at the pharmacy, or, like, once it gets to the doctor stage, the doctor prescribes a treatment. The treatment is a sequence of orders,
115 00:15:39.400 ⇒ 00:15:46.649 Robert Tseng: But, like, the treatment may be different from what the order they came in on. So that means the first order is, like, no longer
116 00:15:46.860 ⇒ 00:16:01.129 Robert Tseng: relevant, like, the treatment will set them on a different… I mean, that’s very rare, I would say. But, like, the point is, like, there’s all these edge cases after you place the order to when, like, once the farm… like, the pharmacy actually starts working on it.
117 00:16:01.130 ⇒ 00:16:04.680 Amber Lin: It could be abandoned in so many points at that point, so…
118 00:16:04.680 ⇒ 00:16:15.349 Robert Tseng: Yeah, like, I wouldn’t, like, kind of bother sifting through the noise of all of that right now. I think, we kind of pulled up a spreadsheet last time, and we were thinking more of, like,
119 00:16:15.760 ⇒ 00:16:27.319 Robert Tseng: what are all the different components of margin, right? Making sure that we know what that is. And I think if you just have, like, a high level… it’s not… well, you could always… the point is, you could always drill down into this more, but at least
120 00:16:27.620 ⇒ 00:16:43.730 Robert Tseng: order creation, order processing, order shift, like, you know, those are, like, the three, like, conceptual buckets, and, like, kind of figuring out, like, what do we actually have? Like, what, like, you’re trying to get, like, a true order funnel, right? Like, of all the different steps of the order.
121 00:16:43.850 ⇒ 00:16:45.010 Robert Tseng: I… I…
122 00:16:45.580 ⇒ 00:16:57.650 Robert Tseng: yeah, I think it’s… you may not be able to answer all the questions yourself. I think you could pull Dave Milade into a call and have him, you know, just talk you through it. If he doesn’t know, then we just need to go to the client and.
123 00:16:58.140 ⇒ 00:17:05.310 Robert Tseng: I mean, I’m going to be meeting with Brad, like, right after this call, and so I’m kind of, like, taking a fresh, fresh look at all of this, too, so hopefully I’ll be.
124 00:17:05.310 ⇒ 00:17:05.710 Amber Lin: Okay.
125 00:17:05.710 ⇒ 00:17:07.670 Robert Tseng: more helpful as I’m coming back into this data.
126 00:17:07.670 ⇒ 00:17:24.930 Amber Lin: Okay, okay, makes, makes sense. So just to repeat back to you to make sure, like, I understand. So, it starts with abandoned, but then as I move through the phases, things might still fall back into abandoned. So, essentially, abandoned includes, like, multiple stages
127 00:17:24.930 ⇒ 00:17:28.509 Amber Lin: Yeah. There might be abandonment happening.
128 00:17:28.510 ⇒ 00:17:30.520 Robert Tseng: There’s many reasons why it could be abandoned, yeah.
129 00:17:30.520 ⇒ 00:17:38.500 Amber Lin: Makes sense. So, I think it’s… it’s still accurate to use… to exclude everything in the abandoned…
130 00:17:38.540 ⇒ 00:17:51.959 Amber Lin: status? Is that correct? Because, like, the revenue hasn’t occurred yet, even if it’s a new order, it hasn’t occurred yet. But I think the next step what I can do is I need to find those,
131 00:17:52.030 ⇒ 00:17:58.440 Amber Lin: the funnel, like, I mentally understand, but I don’t know what fields they are, so I need to find those, and.
132 00:17:58.440 ⇒ 00:18:07.040 Robert Tseng: Yeah. So to be a little bit more precise, an abandoned order, like, the transaction could have been… could have already gone through, so…
133 00:18:08.150 ⇒ 00:18:16.820 Robert Tseng: But, like, obviously, if it doesn’t end up being a real order, then the payment will be canceled, so… and there’s, like, a 60-day supply.
134 00:18:16.820 ⇒ 00:18:17.400 Amber Lin: refund.
135 00:18:17.400 ⇒ 00:18:33.669 Robert Tseng: So, yeah, I mean, Jonah and Zoe, they look at transactions, they recognize transaction revenue, so they would be considering abandoned orders, like, revenue, when it really operationally is not, like, they will never be fulfilled. But they don’t know that until, like, 2 months later.
136 00:18:33.970 ⇒ 00:18:38.590 Robert Tseng: So, I think that’s, like, one of the disconnects, why, like.
137 00:18:38.880 ⇒ 00:18:47.439 Robert Tseng: You know, we should not be… you should not be running a business off of, like, finance’s definition of margins, because they’re always going to be behind the rest of the business.
138 00:18:47.440 ⇒ 00:18:48.150 Amber Lin: Oops.
139 00:18:48.150 ⇒ 00:18:52.420 Robert Tseng: They only see money in, money out, and they don’t have all the other context.
140 00:18:52.820 ⇒ 00:19:06.369 Robert Tseng: yeah, they don’t really understand the whole abandoned workflow, either. That’s kind of why this exercise is helpful, because it’s gonna be, like, what the company uses to understand operational margin. It’s not… this is not a finance margin. This is not, like, what they’re gonna look at.
141 00:19:06.550 ⇒ 00:19:17.109 Amber Lin: I see, okay. And when I was looking through, they had a lot of, different revenue and COGS metrics. There’s, like, realized revenue and realized.
142 00:19:17.860 ⇒ 00:19:21.330 Amber Lin: And then there’s transaction revenue, and then transaction.
143 00:19:21.330 ⇒ 00:19:30.060 Robert Tseng: realize it’s supposed to be their, like, time-adjusted, like, value that’s closer to the operational margin. I don’t fully remember exactly how that’s calculated. I’m sure it’s not, like…
144 00:19:31.180 ⇒ 00:19:35.209 Robert Tseng: like, it’s… I think it excludes…
145 00:19:36.880 ⇒ 00:19:48.169 Robert Tseng: It has some assumptions. It excludes abandoned orders, and assumes that pending, like, 70% of pending orders end up becoming revenue. I mean, I don’t remember all the different criteria, but, like.
146 00:19:49.400 ⇒ 00:19:51.210 Amber Lin: You can think of it like…
147 00:19:52.090 ⇒ 00:20:07.419 Robert Tseng: So, at the transaction level, it looks like there’s 100, how much of that actually will become real revenue? Maybe it’s only, like, 70%… $70.
148 00:20:07.480 ⇒ 00:20:19.970 Amber Lin: I see. So, if I were to redo this, abandonment and actually have a more granular take, I wouldn’t be using Realized Revenue, because there’s already assumptions built in there.
149 00:20:19.970 ⇒ 00:20:34.409 Robert Tseng: Yeah, I mean, your number might get close to that one, but yeah, the realized revenue is, like, the early attempt at, like, this operational margin thing. I mean, in our business, in Brainforge, I built something similar, too. It’s like, for the sales team.
150 00:20:34.410 ⇒ 00:20:34.830 Amber Lin: Yeah.
151 00:20:34.830 ⇒ 00:20:45.410 Robert Tseng: they have pipeline, I have, like, pipeline adjusted revenue, where I assume that, like, of the 10 today, because, like, it’s…
152 00:20:45.660 ⇒ 00:20:46.380 Amber Lin: In my case.
153 00:20:46.380 ⇒ 00:21:03.129 Robert Tseng: assumptions, like, I assume 90 of the $100 that are in our pipeline will never become real revenue. Is that… but that’s, you know, that helps me to, like, see, like, the weekly performance of our team to know, like.
154 00:21:03.310 ⇒ 00:21:06.889 Robert Tseng: Hey, based on our pipeline, if it’s only $10,
155 00:21:07.150 ⇒ 00:21:22.469 Robert Tseng: like, in, pipeline adjusted revenue, and we’re spending $20 on people, then, like, we are losing money week to week, and I have to make a decision on, on life on that. So, it’s not, like, a perfect operational metric. Like, I think.
156 00:21:23.110 ⇒ 00:21:37.770 Robert Tseng: then there’s, yeah, you know, at the end of the month, which, yeah, we recognize revenue that way, like, I’ll have the actual revenue number, and like, so I have, I have pipeline, I have pipeline adjusted revenue, and I have actual, like,
157 00:21:38.010 ⇒ 00:21:55.490 Robert Tseng: revenue. And I look at those three things, and I triangulate it to decide, like, what… what to do next. So, there’s a similar concept to this, to Eden. They have, like, pipeline, which is just their transactions, like, that’s… that’s, like, pretty qualified pipeline, like, at least 70% of it is probably true.
158 00:21:56.010 ⇒ 00:22:13.549 Robert Tseng: then they have, like, the realized revenue, which is their assumptions, like, how much of this is actually supposed to be revenue, and then what you’re doing is you’re finding the actual, which they don’t have. So, I think that’s kind of, like, why what you’re doing is still different from what already exists.
159 00:22:13.550 ⇒ 00:22:17.970 Amber Lin: Cool, okay. Yeah. Yeah, I think my next step, I’m gonna…
160 00:22:18.060 ⇒ 00:22:34.969 Amber Lin: I’m just gonna do a high level, I need to identify those fields first, and then later on, I might layer in specific, like, monthly pans and this and that. I think that’s a lot easier to layer in. Yes. I need to figure out, like, what the funnel is.
161 00:22:35.250 ⇒ 00:22:49.640 Robert Tseng: Yeah, by product, by status, makes sense, or like, yeah, by product, or by stage, whatever you want to call it, I think that makes sense. And then, you know, we were talking about, like, COGS last time, being like, well, we don’t really know what’s in COGS.
162 00:22:49.640 ⇒ 00:22:50.190 Amber Lin: Is it…
163 00:22:50.190 ⇒ 00:22:57.569 Robert Tseng: just… is it just, like, the cost of the emergency? Is shipping cost a little hickens in there? We looked at the spreadsheet, so there were, like.
164 00:22:57.570 ⇒ 00:22:57.940 Amber Lin: Yeah.
165 00:22:57.940 ⇒ 00:23:00.920 Robert Tseng: bits and pieces to it that didn’t really make sense, like… Yeah.
166 00:23:00.920 ⇒ 00:23:01.390 Amber Lin: Totally.
167 00:23:01.390 ⇒ 00:23:05.880 Robert Tseng: So, yeah, we need… just needed… yeah, you were gonna basically figure out, like.
168 00:23:05.880 ⇒ 00:23:06.840 Amber Lin: Yeah, and…
169 00:23:06.840 ⇒ 00:23:07.450 Robert Tseng: from, yeah.
170 00:23:07.450 ⇒ 00:23:08.250 Amber Lin: And I think…
171 00:23:08.310 ⇒ 00:23:19.619 Amber Lin: COX would come after I figure out the funnel, but I think each step of the COX would map to each of the stages, in the funnel, like, for example, like, creation, the credit card fee goes, like.
172 00:23:19.620 ⇒ 00:23:32.889 Amber Lin: earlier on, and then the shipping fee goes in there, and then the pharmacy has some fees. So once I understand, I can go to their team and say, like, hey, this is what I need, but right now, I don’t even know what I need from them.
173 00:23:33.280 ⇒ 00:23:33.800 Robert Tseng: Yep.
174 00:23:34.430 ⇒ 00:23:40.790 Amber Lin: Cool. Okay, that’s good, and that’s… I’m much clearer on this now.
175 00:23:40.890 ⇒ 00:23:46.690 Amber Lin: Okay, I probably… let’s see…
176 00:23:46.800 ⇒ 00:24:03.729 Amber Lin: ABC’s not as urgent. I think it, like… like, it’s relatively easier to do than… than this. It’s less, like, complicated feels involved. So I’ll probably… I can do this this week. Do you have a certain deadline you need this by?
177 00:24:04.060 ⇒ 00:24:19.650 Robert Tseng: No, no deadline on this. I think it’d be good to get, like, a progress check by the end of the week. I mean, I’m hoping by the next ELT update, we’ll be able to report more on this out, so kind of, like, have two-week, two-week, like, runway.
178 00:24:19.850 ⇒ 00:24:20.930 Amber Lin: Oh, okay.
179 00:24:20.930 ⇒ 00:24:21.340 Robert Tseng: Yeah.
180 00:24:21.340 ⇒ 00:24:31.969 Amber Lin: So, let me… I can definitely… let me aim for figuring out the funnels, this week, and then, like, the COG stuff, and then…
181 00:24:32.100 ⇒ 00:24:35.240 Amber Lin: layer in the products, I’ll probably for next week.
182 00:24:35.840 ⇒ 00:24:39.550 Robert Tseng: Yeah, can you reshare that spreadsheet that we went through together again?
183 00:24:39.550 ⇒ 00:24:40.490 Amber Lin: Like, I might flash it.
184 00:24:40.490 ⇒ 00:24:41.910 Robert Tseng: to Brad later today, and.
185 00:24:41.910 ⇒ 00:24:42.450 Amber Lin: audience.
186 00:24:42.450 ⇒ 00:24:43.410 Robert Tseng: as many questions as I can.
187 00:24:43.410 ⇒ 00:24:47.069 Amber Lin: It should actually be in our DM, so the last two links I sent.
188 00:24:47.070 ⇒ 00:24:48.430 Robert Tseng: Oh, okay, got it.
189 00:24:48.820 ⇒ 00:24:49.580 Amber Lin: Yeah.
190 00:24:50.750 ⇒ 00:24:52.270 Robert Tseng: Okay. Cool.
191 00:24:52.610 ⇒ 00:24:53.550 Robert Tseng: Anything else?
192 00:24:53.750 ⇒ 00:25:06.620 Amber Lin: I think on ABC, of… I think this is more of, like, a general market size and creating models question. I think I don’t have enough experience in there,
193 00:25:06.620 ⇒ 00:25:15.339 Amber Lin: like, I have the mental model of how these are done, but I don’t really… I don’t really pick the right variables, as you’ve seen on the ABC models.
194 00:25:15.590 ⇒ 00:25:28.789 Amber Lin: Is there any, like, resources or things you recommend me check out? Because, like, you can help me with this specific task, but then when it comes again, which it definitely will, like, I will still fumble. So I…
195 00:25:29.210 ⇒ 00:25:35.460 Amber Lin: They need some help with, like, market sizing, with mental models, like, with… Like, this… Thank you.
196 00:25:35.600 ⇒ 00:25:47.600 Amber Lin: more consulting work? Is there any resources you would recommend, or should I just go back to, like, the consulting cases and do that?
197 00:25:48.290 ⇒ 00:25:49.940 Robert Tseng: Yeah,
198 00:25:50.150 ⇒ 00:25:55.559 Robert Tseng: It’s tough. Like, I do think a lot of it is subjective, too, but I… there’s a lot of taste involved.
199 00:25:56.760 ⇒ 00:26:13.659 Robert Tseng: Yeah, I mean, I… I just kind of learned through trial and error, I guess, so I didn’t really read any great resource that taught me, to be honest. So, there might be something out there, I’m not… I’m not sure, I don’t… I didn’t… Okay. But yeah, best thing I could do is kind of walk through it with you, and yeah.
200 00:26:14.100 ⇒ 00:26:21.569 Amber Lin: Makes sense, okay. Then, if we get time later this week, I’ll ask. If not, I’ll try to…
201 00:26:21.740 ⇒ 00:26:29.700 Amber Lin: I’ll maybe ask if Clarence has time, because he’s also very integrated on that client, so I’ll see if I can grab his time.
202 00:26:29.700 ⇒ 00:26:32.670 Robert Tseng: Yeah, hopefully Clarence can help you there.
203 00:26:33.340 ⇒ 00:26:38.490 Robert Tseng: What I’ve noticed about Clarence’s strength is he… I mean, he’s… he’s a UX…
204 00:26:38.660 ⇒ 00:26:46.339 Robert Tseng: designer. Like, that’s his specialty. So, he’s not really, like, that into finance, and
205 00:26:46.940 ⇒ 00:26:52.669 Robert Tseng: stuff like this. Like, market research, he kind of knows, like, the basic, basic things, like, as you saw on the ABC side.
206 00:26:53.590 ⇒ 00:26:54.680 Robert Tseng: But, like…
207 00:26:54.680 ⇒ 00:26:55.699 Amber Lin: I… I felt.
208 00:26:55.700 ⇒ 00:26:56.790 Robert Tseng: Modeling, assumptions.
209 00:26:56.790 ⇒ 00:27:02.859 Amber Lin: Very high level of the advice that I got, and I’m needing, like, the more tactical, like, how do I.
210 00:27:02.860 ⇒ 00:27:06.049 Robert Tseng: Yeah, so I’m not really sure if he will be able to give it to you.
211 00:27:08.350 ⇒ 00:27:13.510 Robert Tseng: Yeah, so I mean, I’ll try to meet with you, and we can talk through it. I mean, I will say, like, it’s…
212 00:27:13.630 ⇒ 00:27:20.880 Robert Tseng: what AI helps with is it gives you a lot of variables, but yeah, like, figuring out how you can simplify it is probably, like, that’s the challenge.
213 00:27:20.880 ⇒ 00:27:29.490 Amber Lin: I haven’t had luck with AI on this, like, it repeats what I think, and, like, I’m having challenge thinking about it, so it doesn’t help.
214 00:27:29.880 ⇒ 00:27:30.440 Robert Tseng: Yeah.
215 00:27:31.970 ⇒ 00:27:36.260 Robert Tseng: Okay, I mean, that’s good. I’ll note that down. I mean, that’s not my priority yet.
216 00:27:36.360 ⇒ 00:27:40.269 Amber Lin: And I’ll have some stuff on ABC I’ll do, but…
217 00:27:40.270 ⇒ 00:27:40.860 Robert Tseng: Okay.
218 00:27:41.580 ⇒ 00:27:42.700 Amber Lin: Okay, sounds good.
219 00:27:42.700 ⇒ 00:27:43.270 Robert Tseng: Alright.
220 00:27:43.670 ⇒ 00:27:44.350 Amber Lin: Right.
221 00:27:45.580 ⇒ 00:27:46.280 Amber Lin: Bye!