Meeting Title: Javvy Coffee Roadmapping Date: 2025-02-24 Meeting participants: Uttam Kumaran, Jakob Kagel, Payas Parab, Bo Yoon, Robert Tseng, Caio Velasco
WEBVTT
1 00:04:21.790 ⇒ 00:04:22.829 Payas Parab: What up dudes.
2 00:04:25.020 ⇒ 00:04:26.000 Jakob Kagel: Hey? How’s it going.
3 00:04:26.490 ⇒ 00:04:27.650 Robert Tseng: Hello! Everyone.
4 00:04:28.390 ⇒ 00:04:30.080 Payas Parab: How’s everyone’s weekend.
5 00:04:31.460 ⇒ 00:04:32.580 Caio Velasco: Hello!
6 00:04:34.660 ⇒ 00:04:37.990 Robert Tseng: We can, nice and warm.
7 00:04:39.100 ⇒ 00:04:39.720 Payas Parab: Specific.
8 00:04:40.180 ⇒ 00:04:42.982 Uttam Kumaran: Another hour of planning. Let’s go.
9 00:04:44.230 ⇒ 00:04:50.190 Uttam Kumaran: I’m hyped, and I’ve been walking for 4 h like 3 h now.
10 00:04:50.460 ⇒ 00:04:53.229 Robert Tseng: Well, yeah, what are you? You are you on a treadmill?
11 00:04:53.850 ⇒ 00:04:55.270 Uttam Kumaran: Yeah dude here. I’ll show you.
12 00:04:56.260 ⇒ 00:04:57.400 Uttam Kumaran: Let me see if I can.
13 00:04:57.400 ⇒ 00:04:58.910 Payas Parab: Did you just get that.
14 00:04:59.600 ⇒ 00:05:01.179 Uttam Kumaran: No, it’s my girlfriend’s.
15 00:05:01.180 ⇒ 00:05:01.720 Payas Parab: Okay.
16 00:05:01.720 ⇒ 00:05:04.140 Uttam Kumaran: You know she goes. She goes in in person now.
17 00:05:04.430 ⇒ 00:05:09.099 Uttam Kumaran: And yeah, instead of smooth point 6. I wish it was a little bit slower.
18 00:05:09.610 ⇒ 00:05:11.090 Uttam Kumaran: I’ll have to see if I can like
19 00:05:11.230 ⇒ 00:05:14.380 Uttam Kumaran: find out the firmware to like, try to do that. But
20 00:05:15.520 ⇒ 00:05:21.970 Uttam Kumaran: yeah, dude, I don’t know. Look, we’re out here I just saw on meetings all day and and walk.
21 00:05:22.080 ⇒ 00:05:22.850 Uttam Kumaran: you know.
22 00:05:24.230 ⇒ 00:05:27.310 Robert Tseng: Maybe sure how effective that was.
23 00:05:27.630 ⇒ 00:05:31.319 Uttam Kumaran: Yeah, I don’t know. I I kind of you think I think it’s cheating, but
24 00:05:31.650 ⇒ 00:05:36.230 Uttam Kumaran: I am walking so I feel like it should work.
25 00:05:36.850 ⇒ 00:05:41.539 Uttam Kumaran: I’m not getting the steps in like apple watch isn’t giving me much credit, but
26 00:05:43.190 ⇒ 00:05:47.109 Uttam Kumaran: like so I but I am walking technically so.
27 00:05:53.190 ⇒ 00:05:53.870 Robert Tseng: Nice.
28 00:05:55.980 ⇒ 00:05:59.210 Uttam Kumaran: Can I get edit access on.
29 00:06:01.790 ⇒ 00:06:06.269 Robert Tseng: Oh, yeah, alright. I didn’t realize that like I didn’t have any. Had access on anyone.
30 00:06:12.180 ⇒ 00:06:14.160 Payas Parab: Oh, are you a Yankees? Fan. Bro.
31 00:06:16.200 ⇒ 00:06:17.660 Bo Yoon: No, no.
32 00:06:17.660 ⇒ 00:06:18.920 Payas Parab: Are you a dodgers, fan.
33 00:06:20.170 ⇒ 00:06:21.423 Bo Yoon: Yeah. Okay.
34 00:06:22.050 ⇒ 00:06:24.599 Payas Parab: Alright dodgers game when you guys are in town, wait.
35 00:06:24.990 ⇒ 00:06:25.380 Uttam Kumaran: Okay.
36 00:06:27.110 ⇒ 00:06:27.940 Bo Yoon: Yeah.
37 00:06:32.160 ⇒ 00:06:34.840 Uttam Kumaran: I was an a’s fan, but rip.
38 00:06:41.110 ⇒ 00:06:43.560 Robert Tseng: Alright! I think everybody has access now.
39 00:06:53.910 ⇒ 00:06:56.039 Uttam Kumaran: I think I’m still waiting for access.
40 00:06:57.120 ⇒ 00:06:58.610 Robert Tseng: Oh, yeah. Got a refresh.
41 00:07:04.590 ⇒ 00:07:06.580 Uttam Kumaran: Yeah, still, same, same.
42 00:07:07.190 ⇒ 00:07:10.990 Robert Tseng: Okay, I just, I just flipped it to anyone can edit. So maybe try that again.
43 00:07:10.990 ⇒ 00:07:11.560 Uttam Kumaran: Okay.
44 00:07:16.850 ⇒ 00:07:21.069 Robert Tseng: Oh, you’re using a restricted account, are you not using your brain forge.
45 00:07:22.680 ⇒ 00:07:23.480 Uttam Kumaran: I am.
46 00:07:23.780 ⇒ 00:07:24.370 Robert Tseng: Oh.
47 00:07:24.480 ⇒ 00:07:28.529 Robert Tseng: cause I think you’re the only one. You’re the only one who can’t edit. Everyone else should be able to.
48 00:07:30.370 ⇒ 00:07:31.510 Uttam Kumaran: What the heck does that mean?
49 00:07:32.690 ⇒ 00:07:35.789 Robert Tseng: That’s just. That’s what I’m saying on my side. It just says
50 00:07:35.950 ⇒ 00:07:41.959 Robert Tseng: everyone can edit but like it says you’re using a restricted account, and you won’t be able to edit
51 00:07:42.180 ⇒ 00:07:44.040 Robert Tseng: unless your account is upgraded.
52 00:07:47.640 ⇒ 00:07:48.750 Bo Yoon: Big map, right now.
53 00:07:48.940 ⇒ 00:07:49.630 Uttam Kumaran: Yes.
54 00:07:53.320 ⇒ 00:07:54.080 Uttam Kumaran: Okay.
55 00:07:54.690 ⇒ 00:07:55.499 Bo Yoon: Sorry. Can can you see?
56 00:07:55.500 ⇒ 00:07:59.640 Robert Tseng: Yeah, I see Kyle and pious on here, and I don’t know who anonymous is, but.
57 00:08:00.460 ⇒ 00:08:01.190 Uttam Kumaran: That’s me!
58 00:08:01.430 ⇒ 00:08:02.660 Robert Tseng: Oh, okay.
59 00:08:15.070 ⇒ 00:08:16.840 Uttam Kumaran: Okay, let me just get the.
60 00:08:17.810 ⇒ 00:08:21.930 Uttam Kumaran: Let me get a couple of things from the other meeting into here.
61 00:08:25.290 ⇒ 00:08:30.400 Robert Tseng: We’re gonna run through the a similar exercise. Yeah, this one will be a lot more lightweight. But.
62 00:08:32.100 ⇒ 00:08:36.590 Uttam Kumaran: Yeah, basically same exercise.
63 00:08:36.940 ⇒ 00:08:37.285 Robert Tseng: Bye.
64 00:08:44.600 ⇒ 00:08:46.450 Uttam Kumaran: And let me get rid of these.
65 00:08:59.370 ⇒ 00:09:02.690 Uttam Kumaran: Okay, one more second bear with me.
66 00:09:06.770 ⇒ 00:09:09.820 Robert Tseng: I knew them. The the Pm. Guy rescheduled me to
67 00:09:10.010 ⇒ 00:09:14.059 Robert Tseng: like in 30 min, so I may not stay full time. Yeah.
68 00:09:14.060 ⇒ 00:09:14.940 Uttam Kumaran: Okay. Okay.
69 00:09:15.510 ⇒ 00:09:16.080 Robert Tseng: Yeah.
70 00:09:20.780 ⇒ 00:09:21.560 Uttam Kumaran: Cool.
71 00:09:23.760 ⇒ 00:09:25.100 Uttam Kumaran: Great. So
72 00:09:25.650 ⇒ 00:09:37.440 Uttam Kumaran: today and we wanted to basically run through a road mapping exercise for Javi. I have Bo here as well, but I know Jacob’s on the call. Pious are here.
73 00:09:37.820 ⇒ 00:09:41.249 Uttam Kumaran: Kyle’s here. This is basically the crew for Javi.
74 00:09:41.350 ⇒ 00:09:42.830 Uttam Kumaran: I actually think probably
75 00:09:44.240 ⇒ 00:10:05.370 Uttam Kumaran: most of the the workshop will probably end up landing on Bo, you and and Kyle, but I know there’s some transition work we’re working on. So I just wanted to make sure that everybody is on this call. Basically today, what we’re gonna be going through is one taking a look at all of the existing sort of open items for Javi.
76 00:10:05.973 ⇒ 00:10:06.980 Uttam Kumaran: I’m gonna
77 00:10:07.130 ⇒ 00:10:23.599 Uttam Kumaran: I’m gonna sort of walk through a little bit of what I see on the dashboard, and then let Robert get a give a sense of where we are now, and sort of what the next 2 months looks at. Looks like we’re then gonna do an exercise where we basically just like move all these to post its and do a basic like prioritization.
78 00:10:23.620 ⇒ 00:10:38.929 Uttam Kumaran: And so we can see on one clear screen, like everything that’s on our mind related to this client across analysis, data, engineering data, modeling and strategy. And then finally, we’ll spend the last, you know, 1015 min looking at exactly
79 00:10:39.160 ⇒ 00:10:43.229 Uttam Kumaran: what there is today, what there is for today and tomorrow.
80 00:10:44.710 ⇒ 00:10:45.743 Uttam Kumaran: I guess
81 00:10:46.740 ⇒ 00:11:12.661 Uttam Kumaran: I’ll just put a spotlight on me and we can talk through this. So I think, Bo, you’re new. And, Kyle, I think you’re you’re recently sort of looking at this client. We have. We’ve been working with them since, like late last year, mid last year. Basically, they’re a large e-commerce coffee company. They sell on multiple platforms primarily, Tiktok shopify Amazon and sort of have the more common you know, business domains.
82 00:11:13.090 ⇒ 00:11:19.170 Uttam Kumaran: I think really one thing that we’ve struggled with so far is moving Javi. From a place of
83 00:11:19.567 ⇒ 00:11:40.379 Uttam Kumaran: we see we are able to analyze your historical data to a place of Hey, we found things that you should make decisions on. We’re still in sort of just trying to finish up this reactive historical modeling. And we are stuck there. And so one of the things that will be the goal over the next 2 weeks is to sort of move us out of this like
84 00:11:40.850 ⇒ 00:12:09.249 Uttam Kumaran: small dashboard tweak sort of hell and move us towards areas where, yeah, we’re still working on dashboards. But we’re able to also find opportunities to give them analysis. That’s helpful, that’s timely. And that’s more forward, looking as well as for Kyle and the Ae. Team to be able to build out the data marks necessary. So Kyle, very will probably walk through very similar example to what we just did for Eden, but just making sure that we are able to to support this team on all those priorities.
85 00:12:09.512 ⇒ 00:12:24.990 Uttam Kumaran: I guess, Robert, we’re we’re all looking at this sort of data. Gantt chart. Maybe I’ll let you sort of give a little bit of an overview of like where we’re at. And again I’ll I’ll start making tweaks as I as I listen to you. But give me a sense of like where we’re at the current
86 00:12:25.350 ⇒ 00:12:35.430 Uttam Kumaran: priorities, the current things from your mind that we’re working on. And then sort of where? Where do you see teams that we, we currently don’t support areas we want to go to for the next, you know, 2 months.
87 00:12:35.970 ⇒ 00:12:45.869 Robert Tseng: Yeah. So I’ll kind of do a similar thing where I’ll just talk through like each function. The data from like data is just like stuff that’s just going on like in the background the entire time.
88 00:12:46.518 ⇒ 00:12:48.470 Robert Tseng: Yeah, I think we
89 00:12:48.700 ⇒ 00:13:09.240 Robert Tseng: we originally have them in in using 5 Tran as their main connector tool. But now we’ve moved them over to Portable. And so it looks like I don’t know from my perspective. We’re still running into roadblocks and getting some of the new data sources that we said we would get get in that we bring in for them. So I think that’s that’s like an ongoing effort.
90 00:13:09.240 ⇒ 00:13:19.419 Robert Tseng: I will say that this client is not like we have a we. Their their contract is up in March, and so I think whatever we need to do, we just have to soberly accept that like.
91 00:13:19.740 ⇒ 00:13:30.280 Robert Tseng: Well, this is how it went, and we have 2 weeks left to really like try to push for a renewal. So I’m not gonna be as ambitious and roadmapping the next like few months out, because I don’t even know if Javi is gonna renew.
92 00:13:31.070 ⇒ 00:13:38.339 Robert Tseng: But, like I think there are, I think there are some steps that we could take to kind of get us to a place where they’re comfortable. Renewing.
93 00:13:39.020 ⇒ 00:13:44.989 Robert Tseng: I think. Yeah, to be able to demonstrate all the the
94 00:13:45.410 ⇒ 00:14:01.276 Robert Tseng: if we can, if we can roadmap out like what does working together for the next 3 to 6 months. Look like that would be that would be huge. But a lot of it will be speculative, and they’re definitely not as engaged as a couple of our some of our other clients. So I think,
95 00:14:02.000 ⇒ 00:14:18.380 Robert Tseng: yeah, things. So that’s just kind of like setting the stage there. We’ve one of the big reasons we kind of even signed. This contract was to do this like tech migration, to move over from amplitude, reporting to Meta based reporting. And then also to like switch up the connectors to lower their data bill.
96 00:14:19.690 ⇒ 00:14:30.289 Robert Tseng: I don’t really feel like they’re adopting metabase. Yeah, I just feel like it’s just taken us so long to push out 2 dashboards that we’ve been working on since January.
97 00:14:30.762 ⇒ 00:14:34.149 Robert Tseng: I’ve yeah, I don’t. I don’t think anybody’s looking at it. So
98 00:14:34.440 ⇒ 00:14:48.310 Robert Tseng: I think if anything, a short term goal for me is to to really like push for like adoption of the dashboards that we’ve put put out and yeah, just continue to have a like
99 00:14:48.470 ⇒ 00:14:57.439 Robert Tseng: a backlog of additional reports that we’re moving from amplitude into Meta base. So. I’ll talk through that more specifically when I jump into each section
100 00:14:57.750 ⇒ 00:15:18.687 Robert Tseng: on the marketing side. I think that’s where there is like the biggest opportunity. Kind of like what we saw for Eden, where marketing is really what drives growth. For these companies like, yeah, us not having north beam data has been like a huge, honestly like like waste for us that, like we have not like been able to tap, tap into that.
101 00:15:19.200 ⇒ 00:15:23.079 Robert Tseng: yeah, we haven’t done any attribution reporting or anything like that for them. So
102 00:15:23.434 ⇒ 00:15:49.639 Robert Tseng: I would say, just being able to get marketing data in and to be able to give them a look at like, Okay, now that we have this in, this is the potential like we what we could do with it, we could reference a lot of the work that we’ve done for other clients as like performance marketing report. Ltv, like, kind of ad spend breakdown stuff like that we can like. I would like to be able to bring all of that kind of just all those ideas to them.
103 00:15:49.810 ⇒ 00:15:52.329 Robert Tseng: but I don’t. I don’t think we’re there yet
104 00:15:52.590 ⇒ 00:15:56.907 Robert Tseng: on the on the Cx side, we have gorgeous Okando data.
105 00:15:57.790 ⇒ 00:16:06.309 Robert Tseng: yeah, I know, you kind of lumped it into marketing. But you know, these are basically custom customer review data, so I would kinda consider it more like their their.
106 00:16:06.310 ⇒ 00:16:06.900 Uttam Kumaran: You’re right.
107 00:16:06.900 ⇒ 00:16:11.769 Robert Tseng: Yeah, it’s not a core revenue driver. And I I disagree that like
108 00:16:12.900 ⇒ 00:16:24.409 Robert Tseng: whatever I mean, it’s what Aman has told us is like the most important thing. But I really don’t think it’s the most important, like, I think if we get north beam data in like it’ll we’ll be able to
109 00:16:24.850 ⇒ 00:16:26.480 Robert Tseng: push it along more
110 00:16:26.928 ⇒ 00:16:35.379 Robert Tseng: but since we’ve already kind of done all this work to get Akenda and gorgeous in, there is like this idea of a gorgeous dashboard that we need to be able to put out
111 00:16:35.720 ⇒ 00:16:39.771 Robert Tseng: just some reporting around like customer feedback.
112 00:16:40.580 ⇒ 00:16:49.529 Payas Parab: Yeah, Robert, 1 1 thing I will add, I and I was actually just looking at the data to answer, how do I pronounce. Is it, Cal? Sorry I’m so sorry.
113 00:16:49.530 ⇒ 00:16:50.250 Uttam Kumaran: Kayak.
114 00:16:50.250 ⇒ 00:17:02.069 Payas Parab: Kyo my apologies Kayo’s questions, which were amazing, is, it looks like they have a lot of onshore resources, for like I checked the time zones of all their agents, and they have, like 15 agents that are like
115 00:17:02.190 ⇒ 00:17:31.400 Payas Parab: like us, based, which are probably costing them a lot. So I wouldn’t necessarily, since we have good data there, we we may not want to completely dismiss it, because it seems that there might be a big cost center for them. We don’t. I don’t know that for sure, but just based on seeing that they have, like 15 us based agents. And Justin loves to outsource. That part might be part of what makes that more important as opposed to like. It doesn’t move the needle on revenue right? Like marketing does. It doesn’t move the needle, as like financial reporting does in terms of reporting. But it does.
116 00:17:31.400 ⇒ 00:17:34.900 Payas Parab: I think they it’s a cost center for them, so it could be sort of like
117 00:17:35.050 ⇒ 00:17:36.840 Payas Parab: helpful for them in that regard.
118 00:17:37.190 ⇒ 00:17:52.160 Robert Tseng: Yeah, no, I agree. I mean, I’m not gonna be stubborn about it and keep fighting them on on whether or not it is a priority, he said. He wants the gorgeous dashboard. We’re gonna we’re gonna do it. So I think that’s like one output that we can get done in the next couple of weeks that we should be able to give them, like a good view
119 00:17:52.160 ⇒ 00:18:08.610 Robert Tseng: of like agent performance, like kind of all, a lot of a lot of the similar kind of Cx stuff that we’ve done for for Stella for, and other clients with with with with and and Eden as well like I think we can. We can give them that that kind of visibility into that
120 00:18:09.516 ⇒ 00:18:29.470 Robert Tseng: as far as like fulfillment Ops. I don’t think we’ve really touched order level data like, as far as like the the shipping fulfillment kind of piece. Marketplace Ops, I think, was was a great kind of new work stream that kind of pies help bring in during this past month, and the Amazon address matching and all that has been great.
121 00:18:30.480 ⇒ 00:18:35.060 Robert Tseng: So I think if we yeah, I I would like
122 00:18:35.500 ⇒ 00:18:38.509 Robert Tseng: kind of. Similarly, I would like us to start to
123 00:18:43.200 ⇒ 00:19:03.457 Robert Tseng: if if we were to kind of talk about like the 2 most important like functions here, I would still think it’s marketing, and then also marketplace Ops. And so when I’m thinking about renewals in a couple of weeks like, I wanna be able to give them a strategy for like how we’re gonna give them huge unlocks in those 2 areas. So just like continual
124 00:19:04.310 ⇒ 00:19:28.370 Robert Tseng: I mean through through the marketplace. They’re expanding into a bunch of different countries. They’ve you know, they’re they’re they’re continuing to go into more retail and doing omni Channel stuff. So like I, that’s kind of where I want to be knocking the door and and putting planting the seed that like we would like to be able to help help move, move them. Move towards supporting them in analytics in those areas. So I think
125 00:19:28.540 ⇒ 00:19:39.829 Robert Tseng: that’s that’s where, like as I’m thinking about account from my account account management perspective, like where I want to make my bet that like, that’s that’s what’s gonna give them the confidence to renew.
126 00:19:40.775 ⇒ 00:19:42.199 Robert Tseng: So I think
127 00:19:42.510 ⇒ 00:19:49.559 Robert Tseng: I I want to be spending my time like scoping more ideas out there, and like building a roadmap for those 2 functions
128 00:19:50.060 ⇒ 00:20:00.139 Robert Tseng: as far as like work that needs to be closed out. Obviously, the 2 dashboards that we’ve been talking about need to be closed out and and done, and then the Amazon address, matching
129 00:20:00.370 ⇒ 00:20:08.459 Robert Tseng: Aman, did say he wanted to like, turn that into a streamline app at this point, and make it easy for them to upload. I’m.
130 00:20:11.450 ⇒ 00:20:16.129 Uttam Kumaran: Yes, yeah, don’t worry about. I’ll tell you like I’ll tell them on.
131 00:20:16.310 ⇒ 00:20:20.420 Uttam Kumaran: I think the basically what I’ll do is I’ll give you a sense of how long it’s gonna take. And you can tell him.
132 00:20:20.850 ⇒ 00:20:23.630 Uttam Kumaran: is this a priority compared to everything else?
133 00:20:23.980 ⇒ 00:20:24.570 Uttam Kumaran: You know.
134 00:20:24.570 ⇒ 00:20:25.150 Robert Tseng: Yeah.
135 00:20:25.710 ⇒ 00:20:26.370 Uttam Kumaran: Yeah.
136 00:20:27.000 ⇒ 00:20:28.060 Robert Tseng: Okay.
137 00:20:30.061 ⇒ 00:20:35.610 Payas Parab: I already did. By the way, I pushed the the latest code, which is like more modularized, so we can like run it
138 00:20:35.800 ⇒ 00:20:41.070 Payas Parab: pretty easily like there’s like a running like, I basically like broke it out so we could build it
139 00:20:41.180 ⇒ 00:20:47.450 Payas Parab: quicker, or we can like rerun it locally, really easily. I just pushed out last night, so you may not have seen it yet.
140 00:20:47.450 ⇒ 00:20:48.000 Uttam Kumaran: Okay.
141 00:20:51.990 ⇒ 00:20:54.139 Robert Tseng: Yeah, so I think, yeah, yeah, go ahead.
142 00:20:54.140 ⇒ 00:20:54.670 Uttam Kumaran: No God.
143 00:20:55.040 ⇒ 00:21:02.884 Robert Tseng: I was gonna say, just to conclude, yeah, we have, like some stuff that’s in flight that we’re trying to close. And I mean a lot of it. This is aspirational.
144 00:21:03.400 ⇒ 00:21:04.449 Robert Tseng: but I think
145 00:21:05.540 ⇒ 00:21:17.949 Robert Tseng: I wanna like take a different tone, like a different angle with Aman for the rest of our engagement, like I think he’s been kind of the gatekeeper, for, like our work, and I disagree with the choices that he’s been making, and I.
146 00:21:18.630 ⇒ 00:21:21.669 Uttam Kumaran: We haven’t been strong. We haven’t been a partner in that decision making at all.
147 00:21:21.860 ⇒ 00:21:34.419 Robert Tseng: Yeah. So I think if anything, I want to be able to be more proactive in in yeah, I think going through this exercise telling him, Look, Amon, you you care about us spending like 5 to 10 h on building a stream of app. But like.
148 00:21:34.420 ⇒ 00:21:53.650 Robert Tseng: did this, this is the area that you need to focus on. You need to give us this opportunity to go after this kind of work, and I want to be more insistent on on pushing him in the direction that I I want us to be working in, not waiting for him to give us. Like to sign up on stuff. Because, yeah, I I think he’s he’s not really been setting us up for success in that way.
149 00:21:54.039 ⇒ 00:22:00.740 Robert Tseng: So yeah, I think that’s that’s kind of my assessment of like where we’re at with things with with right now.
150 00:22:02.100 ⇒ 00:22:07.100 Uttam Kumaran: Okay. So I think I know you have to. You have to run in what? 11 min.
151 00:22:07.240 ⇒ 00:22:07.880 Robert Tseng: Yeah.
152 00:22:07.880 ⇒ 00:22:10.849 Uttam Kumaran: Okay. So let’s just I, wanna talk about what’s on our plate.
153 00:22:11.710 ⇒ 00:22:15.680 Uttam Kumaran: do we do? We actually only have, like, one more week of work like just this week.
154 00:22:17.260 ⇒ 00:22:21.030 Robert Tseng: Yeah, we don’t really have anything queued up in the next month for the next couple of weeks.
155 00:22:22.090 ⇒ 00:22:23.448 Uttam Kumaran: I think one of the
156 00:22:25.630 ⇒ 00:22:27.730 Uttam Kumaran: One of the things I want to try to do
157 00:22:28.717 ⇒ 00:22:35.980 Uttam Kumaran: this week very urgently is to get out not only the 2 dashboards, but also get out
158 00:22:36.760 ⇒ 00:22:42.869 Uttam Kumaran: the go like a gorgeous dashboard and get out something around North beam data. I don’t see any
159 00:22:43.460 ⇒ 00:22:48.819 Uttam Kumaran: blockers. And getting that done, I saw the north beam data landed from portable
160 00:22:49.460 ⇒ 00:23:00.713 Uttam Kumaran: like, I basically can, I think with Bo Jacob and me, we can just try to knock out those 2 dashboards, or whatever needs to happen there and then we need to just finish up this gorgeous dashboard.
161 00:23:01.330 ⇒ 00:23:04.429 Uttam Kumaran: I don’t see why, we can’t try to get that done this week.
162 00:23:04.630 ⇒ 00:23:11.610 Uttam Kumaran: And basically, I think, Rob, you just have to go and say, like, we’re now way more organized
163 00:23:12.410 ⇒ 00:23:15.580 Uttam Kumaran: are bad, I mean, I don’t know, but like.
164 00:23:15.580 ⇒ 00:23:16.380 Robert Tseng: Yeah, I’ll try to.
165 00:23:16.380 ⇒ 00:23:21.589 Uttam Kumaran: I want to try to give you as many things that you can share
166 00:23:22.250 ⇒ 00:23:25.489 Uttam Kumaran: like within the next. Basically, like, 4 days.
167 00:23:27.190 ⇒ 00:23:33.760 Uttam Kumaran: Across this client otherwise. Yeah, I mean, I don’t. I’m with you. I don’t see them renewing.
168 00:23:34.111 ⇒ 00:23:39.209 Uttam Kumaran: If we don’t like push anything out like if we were to take this week just like we did the last 3 weeks.
169 00:23:39.470 ⇒ 00:23:50.900 Uttam Kumaran: We’re like, we’re we’re sort of. We’re sort of aft there. So I want to try to do a sea change within. We basically have, like probably 4 days, 3 days to give you that, and then for you to be able to send that and tee up.
170 00:23:51.850 ⇒ 00:23:54.310 Uttam Kumaran: What could be a renewal conversation?
171 00:23:54.500 ⇒ 00:24:03.720 Uttam Kumaran: So let’s just talk for 10 min about those the 2 dashboards. Right? What else needs to happen there. And I’m gonna just start to take some notes
172 00:24:03.920 ⇒ 00:24:13.450 Uttam Kumaran: like just like we did on the last client where I’m just gonna put some stickies on what needs to happen literally, probably within today and tomorrow. And then I also want to talk about
173 00:24:14.800 ⇒ 00:24:17.209 Uttam Kumaran: what needs to happen for the gorgeous
174 00:24:17.858 ⇒ 00:24:25.649 Uttam Kumaran: the gorgeous dashboard as well. And if there’s any other sort of short term analysis, things that we want to try to do within the next like few days.
175 00:24:26.960 ⇒ 00:24:27.660 Robert Tseng: Okay.
176 00:24:28.710 ⇒ 00:24:36.040 Uttam Kumaran: So, I guess. Talk to me about like the the Amazon dashboard and like work for work.
177 00:24:36.430 ⇒ 00:24:38.129 Uttam Kumaran: What else is remaining there.
178 00:24:47.690 ⇒ 00:25:03.749 Robert Tseng: I mean the animal dashboard. I pushed them. They just asked. They just came back with a round of changes. I sent that to the Channel, and it just kind of vanished like I don’t think any taken there. So there is. There’s like a round of changes that needs to happen there. Again. It seemed like it was just a quick fix.
179 00:25:03.750 ⇒ 00:25:09.519 Jakob Kagel: On one. I know one of the changes like that he asked for right was like the cancelled orders rate right.
180 00:25:10.290 ⇒ 00:25:15.520 Robert Tseng: This is the only one that I saw. Sorry. But for that one. I don’t think that
181 00:25:15.520 ⇒ 00:25:17.120 Robert Tseng: that’s the only thing he asked for. Yeah.
182 00:25:17.120 ⇒ 00:25:28.440 Jakob Kagel: Right that I don’t think that’s the I don’t think that we can implement that. Unfortunately, like, I mean, I looked through our like fact, orders, tables and fact order line. And I just there’s only one field that would be like
183 00:25:28.630 ⇒ 00:25:32.349 Jakob Kagel: reliable for it. It’s like, I think it’s like financial stuff.
184 00:25:32.350 ⇒ 00:25:36.370 Uttam Kumaran: Could you? Let’s just pop. Where? What could we find that in slack? And then.
185 00:25:36.510 ⇒ 00:25:37.340 Jakob Kagel: Sure.
186 00:25:37.340 ⇒ 00:25:41.910 Uttam Kumaran: Like, where is that? And then, yeah, i i 1.
187 00:25:41.910 ⇒ 00:25:43.130 Jakob Kagel: That’s a boy.
188 00:25:43.630 ⇒ 00:25:45.070 Uttam Kumaran: For? For? What? For void?
189 00:25:45.070 ⇒ 00:25:46.829 Jakob Kagel: Why this should come up. Yeah.
190 00:25:46.830 ⇒ 00:25:47.500 Uttam Kumaran: Okay.
191 00:25:48.300 ⇒ 00:25:49.080 Jakob Kagel: No.
192 00:25:50.130 ⇒ 00:25:51.640 Jakob Kagel: That’s the thread. Yeah.
193 00:25:52.100 ⇒ 00:25:52.730 Uttam Kumaran: Cool.
194 00:25:53.418 ⇒ 00:25:58.429 Uttam Kumaran: Yeah, I mean, we do. We? We definitely have this in Amazon data.
195 00:25:58.670 ⇒ 00:26:01.310 Jakob Kagel: Like, I know, because we did this modeling for pool parts
196 00:26:01.310 ⇒ 00:26:02.980 Jakob Kagel: might not be in the tables right now.
197 00:26:02.980 ⇒ 00:26:09.280 Uttam Kumaran: Yes, so that’s like, that’s the conversation I want to have here. So I think, probably, Kyle, one thing for us is to go
198 00:26:09.410 ⇒ 00:26:11.539 Uttam Kumaran: figure this out like, where.
199 00:26:12.160 ⇒ 00:26:18.919 Uttam Kumaran: like, where this data is basically and make sure that Jacob can can fix that. This is in Amazon somewhere.
200 00:26:19.160 ⇒ 00:26:20.880 Uttam Kumaran: Oh, yeah.
201 00:26:21.360 ⇒ 00:26:24.689 Uttam Kumaran: So I think that’s 1 thing. So that’s the only thing that canceled orders.
202 00:26:30.140 ⇒ 00:26:31.269 Jakob Kagel: Yes, that’s it.
203 00:26:31.270 ⇒ 00:26:33.420 Jakob Kagel: Only thing right, Robert. This only thing.
204 00:26:33.690 ⇒ 00:26:34.869 Jakob Kagel: Yeah, that was it. Cool.
205 00:26:34.870 ⇒ 00:26:37.319 Uttam Kumaran: Okay, okay, what about for gross margin?
206 00:26:40.080 ⇒ 00:26:46.340 Jakob Kagel: Yeah. So I left a couple of feedback items there. I think right like about the filters. And then.
207 00:26:52.130 ⇒ 00:26:54.250 Robert Tseng: Yeah, I mean, I feel like this one is like.
208 00:26:54.450 ⇒ 00:26:59.719 Robert Tseng: almost there. But like it, it just I mean, I just basically had this.
209 00:27:00.020 ⇒ 00:27:16.510 Robert Tseng: I always like compare the before and after. So I have like this dashboard up and the ample dashboard up, and I’m like I’m I’m recording a loom like talking through it. And like, I couldn’t really like, explain, like, what we did that like made it better. And I think I just like stopped because I was like.
210 00:27:16.630 ⇒ 00:27:32.068 Robert Tseng: yeah, we’ve like added some stuff here and there. And I, yeah, I mean, this is all like high level stuff, which is like blended metrics, but they want everything broken out by like product and by offer, and we just have it broken out by offer and
211 00:27:33.140 ⇒ 00:27:34.809 Jakob Kagel: We we have product on there.
212 00:27:38.850 ⇒ 00:27:44.509 Robert Tseng: Like cogs product. Yeah, I see that. I guess.
213 00:27:44.510 ⇒ 00:27:50.569 Jakob Kagel: Thing that’s tricky like about the product is like that has to come from order line. So
214 00:27:50.690 ⇒ 00:27:59.379 Jakob Kagel: it’s like we can do it. But it’s like the calculation is a little bit different than how it’s being done. In fact, orders. And I guess the part that I’m concerned about, or like
215 00:27:59.970 ⇒ 00:28:13.389 Jakob Kagel: hedging against a little bit is like the numbers not tying out well, because we can’t just use the like fact. Orders like margin calculation because of the one to many mapping.
216 00:28:17.320 ⇒ 00:28:21.890 Uttam Kumaran: Yeah. So we need to have like an product level, gross margin that doesn’t include the shipping. Basically.
217 00:28:22.440 ⇒ 00:28:40.039 Jakob Kagel: Right. I mean what I’m doing. I mean what I can do right now, or like what I put in the note right is like I’m doing the quantity like from the order line times the pretax price. And I’m taking that as like total line item price. And then I’m subtracting all the cogs like, you know, we went through this whole thing where we’re like up to head
218 00:28:40.670 ⇒ 00:29:06.100 Jakob Kagel: cogs fields. So I’m subtracting all the like total cogs, fields like from the order line. And that’s how I’m calculating it. But it’s just a little bit different, because the cogs fields that are in fact, order are not exactly the same as the ones that are in fact, order, fact, order, line, and fact order. They’re not. They’re just not exactly the same, and I can maybe put right in the Channel, or something sort of like what the difference is.
219 00:29:06.100 ⇒ 00:29:06.840 Uttam Kumaran: Yeah.
220 00:29:07.120 ⇒ 00:29:07.530 Jakob Kagel: Sure.
221 00:29:07.530 ⇒ 00:29:13.599 Uttam Kumaran: So I guess let’s make a decision on this route. One, I think if we paired on this for an hour
222 00:29:13.740 ⇒ 00:29:17.109 Uttam Kumaran: like we’ll just build whatever the fuck we need for this.
223 00:29:18.980 ⇒ 00:29:22.080 Uttam Kumaran: So like one, I can get you the
224 00:29:22.470 ⇒ 00:29:27.450 Uttam Kumaran: I can get you the the margin by product, and we’ll we’ll come up with a new margin calculation that.
225 00:29:27.450 ⇒ 00:29:32.720 Robert Tseng: Yeah, like, kind of like what we have this offer name breakout. I just need that for product. And like, I think that would be.
226 00:29:32.720 ⇒ 00:29:35.600 Uttam Kumaran: Sick. Okay, we’re gonna I’m gonna get. We’ll get you something like that.
227 00:29:35.800 ⇒ 00:29:36.520 Robert Tseng: Yeah.
228 00:29:36.520 ⇒ 00:29:44.190 Uttam Kumaran: I also I also think that like I mean, I don’t know. I’m opinionated about like how this looks to like. I think there’s just a lot going on.
229 00:29:44.340 ⇒ 00:29:49.429 Uttam Kumaran: It’s not super like I don’t. I think I’m with you, Robert, like the story isn’t clear.
230 00:29:50.052 ⇒ 00:29:51.169 Uttam Kumaran: I mean, like.
231 00:29:51.410 ⇒ 00:29:58.369 Uttam Kumaran: if you look at this. It’s like nothing’s happening. Nothing’s happening. Nothing’s happening. Nothing’s happening like what it like. What is that?
232 00:29:58.660 ⇒ 00:30:07.719 Uttam Kumaran: What do they want to see that like they’re making more, that they’re spending more on products over time, because they’re selling more like, what is the derivative that we’re getting from this? I don’t know right? And so
233 00:30:08.050 ⇒ 00:30:14.879 Uttam Kumaran: that’s the thing for me is like, what is the store like? I know you may not know the end of the story unless you see the data.
234 00:30:15.280 ⇒ 00:30:17.550 Uttam Kumaran: But like, I feel like, this isn’t enough
235 00:30:19.840 ⇒ 00:30:26.449 Uttam Kumaran: right? Like, what is the opportunity we’re sharing with them to lower their costs or make more money
236 00:30:27.000 ⇒ 00:30:28.280 Uttam Kumaran: with this dashboard.
237 00:30:29.190 ⇒ 00:30:42.440 Robert Tseng: Yeah, to me, this is like, this is the, this is the finance. The finance team is asked for this. It’s like, okay, they want to know? Like, yeah, you you’ve given them. We’ve given them like a blended margin, like, kind of like baseline.
238 00:30:42.610 ⇒ 00:30:43.810 Robert Tseng: And then.
239 00:30:44.300 ⇒ 00:30:58.509 Robert Tseng: yeah, they’ll they want to be able to look at. I mean, this is ultimately will lead into profitability, like kind of their view of product level profitability. But being able to break that out by offer, be able to break that out by product and then be able to see those trends over time to see. Like, okay, kind of like.
240 00:30:58.540 ⇒ 00:31:17.819 Robert Tseng: I said, built like a like a he had done an ad hoc ad hoc analysis before. And it was like, Hey, look at these 5 different products. This is what your cogs breakout looks like for this one product your cogs is heavily skewed towards like I don’t know was it was shipping. So maybe your shipping or logistics cost for this one product was like terrible. And you need to look into that
241 00:31:17.820 ⇒ 00:31:20.580 Robert Tseng: great yeah, that’s that’s the kind of like that’s.
242 00:31:20.580 ⇒ 00:31:21.400 Uttam Kumaran: I see.
243 00:31:21.400 ⇒ 00:31:23.220 Robert Tseng: We would we would break it out.
244 00:31:23.480 ⇒ 00:31:24.120 Uttam Kumaran: Okay.
245 00:31:24.440 ⇒ 00:31:28.870 Robert Tseng: Yeah, so and I, I don’t think we can really
246 00:31:29.100 ⇒ 00:31:34.590 Robert Tseng: make any kind of we can’t, really we can’t. We can’t run an investigation like that off of this.
247 00:31:34.590 ⇒ 00:32:00.750 Uttam Kumaran: But let me give you let me give you a sense like i i 1 i think I think maybe at least me. I think, Bo, I think today, probably this afternoon, probably like 2 or 3 o’clock, your time. We could just spend an hour on this dashboard. I want to do a couple of things. One. That’s the story. What Robert just said is like they want to look at the top level. We kind of have that. I think we should probably make this wider. The second thing is we want to look at components. This should be
248 00:32:01.310 ⇒ 00:32:03.730 Uttam Kumaran: stacked bar chart, like
249 00:32:03.870 ⇒ 00:32:16.220 Uttam Kumaran: probably entire thing filled out because they don’t really care that they’re spending more. It’s a what is it? As a percent of cost per category? That’s what really matters here. So that’s what we’ll work on ideally you want. We want to see
250 00:32:16.330 ⇒ 00:32:28.639 Uttam Kumaran: what is what is taking up the lion’s share of the cost. Second, we probably want to do a version of this by product meaning every product. We have the cogs breakout by product.
251 00:32:28.830 ⇒ 00:32:36.779 Uttam Kumaran: right? So literally, 5 of these per every single product. So I just want to throw like
252 00:32:37.460 ⇒ 00:32:44.190 Uttam Kumaran: I, we could just throw 10 other things in here. I think I have a pretty good understanding of what those things are. And then I want to clean up like
253 00:32:44.420 ⇒ 00:32:46.909 Uttam Kumaran: rounding table names.
254 00:32:47.080 ⇒ 00:32:58.510 Uttam Kumaran: standardize some of the views. So let’s spend an hour on this later today. And I’m just gonna give you one of this that’s like beautiful. And then you can. We should hopefully consider this like
255 00:32:59.700 ⇒ 00:33:06.610 Uttam Kumaran: ready, ideally, Robert, hopefully, you can take this after today and, like, go present something or like.
256 00:33:07.980 ⇒ 00:33:12.820 Uttam Kumaran: try to get ahead of the the end of the week. I don’t think I think we’re like 2 h away from this being done.
257 00:33:13.290 ⇒ 00:33:13.840 Robert Tseng: Yeah.
258 00:33:13.840 ⇒ 00:33:14.540 Jakob Kagel: I agree.
259 00:33:14.540 ⇒ 00:33:41.539 Robert Tseng: Yeah, I have my my Wednesday check in with them on. And I think between now and then I want to be building out that roadmap, for, like the next couple of months, I want to like, actually kind of do the exercise that we did for for Eden, and and like project out what like 2, 3 months work of work would would be like. And so I would like to be spending time on that. And so if you guys can just kind of clean this up and get ready for me to just, I’m gonna record a loom pretty much, and that’ll be just how I ship this.
260 00:33:41.540 ⇒ 00:33:42.590 Uttam Kumaran: Okay. Okay.
261 00:33:43.150 ⇒ 00:33:46.759 Robert Tseng: Yeah, okay, but I’ll be. I’ll let you keep going.
262 00:33:46.900 ⇒ 00:33:53.139 Uttam Kumaran: Okay, alright cool. So I think that I think this makes sense. I think our biggest. Probably
263 00:33:53.800 ⇒ 00:33:58.109 Uttam Kumaran: the core issue now is, yeah, there, I think, Kyle, the probably the biggest thing to notice is that
264 00:33:58.820 ⇒ 00:34:08.519 Uttam Kumaran: we do have questions from the analyst team about this metric is missing or this thing is missing. Those are things that I think, for Jacob Bo. Pious.
265 00:34:08.730 ⇒ 00:34:11.840 Uttam Kumaran: The initial answer for that is, we could do it.
266 00:34:12.030 ⇒ 00:34:17.429 Uttam Kumaran: We just need probably like a little bit more clarity on what the ask is right? Like I want to lead.
267 00:34:17.560 ⇒ 00:34:22.269 Uttam Kumaran: I don’t think there’s anything unless truly, we’re really confident that’s not in the data
268 00:34:22.429 ⇒ 00:34:46.369 Uttam Kumaran: we can make it happen. That’s the thing to lead with is okay. We’re just missing it. But I think the biggest thing is to be like, Hey, we just need to go find it right? So that’s the sort of stuff like before. Okay, we’re just missing one order status from Amazon. I know it’s there. We we have it somewhere in the pool parts. Repo. I can go find it. Same thing for this, I think. Anytime. I think we’re there’s a lot of dashboard work for this client where
269 00:34:46.480 ⇒ 00:34:53.720 Uttam Kumaran: it’s like, probably one or 2 h on the phone where we should just crush this. That’s what we’ll do today. So we’ll try to just ship both of these out today.
270 00:34:54.282 ⇒ 00:35:00.022 Uttam Kumaran: And sort of like, call a case closed. Let’s talk about
271 00:35:01.110 ⇒ 00:35:06.440 Uttam Kumaran: So this I think we’re gonna just gonna try to do our working session today.
272 00:35:06.640 ⇒ 00:35:08.560 Uttam Kumaran: And we can just nail this
273 00:35:09.038 ⇒ 00:35:26.339 Uttam Kumaran: what else are? What else is on the plate. I think. Probably pious. I probably have you sub in a little bit for Robert. Here. I know we have the gorgeous dashboard. I know Robert was a little bit careful on not filling out the next few months. But can you sort of assist and think about.
274 00:35:26.340 ⇒ 00:35:26.939 Payas Parab: Yeah. The joint.
275 00:35:26.940 ⇒ 00:35:27.620 Uttam Kumaran: Anything else.
276 00:35:27.620 ⇒ 00:35:52.072 Payas Parab: I was. Gonna say, the gorgeous one, I can do like a like help make some clear requirements for Kyle there, so he can focus on some of these other things. Can do it similar to like the financial dashboard, like the the model link exercise. So I can own that the other thing. I just wanted to flag as well, just because this could cause errors. There’s issue 94. I don’t know if we ever fix that, Tom. I saw you on assign me, so I it might have just gotten resolved.
277 00:35:52.330 ⇒ 00:35:54.559 Uttam Kumaran: There’s no way. I know what issue 94 is.
278 00:35:54.560 ⇒ 00:35:57.010 Payas Parab: Sorry. Sorry. I just sent it in the. I just sent it in the chat.
279 00:35:57.290 ⇒ 00:36:00.520 Payas Parab: Oh, issue 94. Yeah, like, I.
280 00:36:00.520 ⇒ 00:36:00.850 Payas Parab: Good night.
281 00:36:00.850 ⇒ 00:36:02.009 Payas Parab: I wake up thinking about.
282 00:36:02.010 ⇒ 00:36:05.159 Payas Parab: That’s a pretty clear identifier, all right, like that’s
283 00:36:06.180 ⇒ 00:36:13.030 Payas Parab: I’m not saying I’m not. I was expecting you to pull it up. I didn’t expect you to know off the top of your head, just to be clear.
284 00:36:13.250 ⇒ 00:36:14.870 Uttam Kumaran: Okay, okay. I know. I know.
285 00:36:16.290 ⇒ 00:36:17.000 Uttam Kumaran: Oh.
286 00:36:17.396 ⇒ 00:36:18.980 Payas Parab: Sorry issue issue issue.
287 00:36:19.140 ⇒ 00:36:20.969 Payas Parab: That one is just like the
288 00:36:21.640 ⇒ 00:36:25.729 Payas Parab: I don’t know if this got fixed somewhere else. So maybe I just wanna make sure, but it was like the
289 00:36:26.080 ⇒ 00:36:32.909 Payas Parab: we had to. The platform fees might be too high. I don’t know if you saw that error, Jacob or Robert.
290 00:36:33.140 ⇒ 00:36:36.000 Payas Parab: but we may need to. There’s just like one additional fix. It might be a.
291 00:36:36.000 ⇒ 00:36:37.900 Uttam Kumaran: What is? What is the 100? What is a hundred?
292 00:36:37.900 ⇒ 00:36:41.939 Jakob Kagel: That like, so that would pertain to like order line table right.
293 00:36:42.721 ⇒ 00:36:48.270 Payas Parab: Yeah. But we also need to do it. In fact, orders. I think I think the did you use platform fees in your margin, Jacob.
294 00:36:48.270 ⇒ 00:36:50.329 Jakob Kagel: Yes, I mean, yeah.
295 00:36:50.330 ⇒ 00:36:54.479 Payas Parab: Look like crazy. Maybe it is just fixed. I don’t know.
296 00:36:54.480 ⇒ 00:37:04.128 Jakob Kagel: I mean, there was issues when we refreshed like the table the last time, if I remember correctly, that I called out, I think, with, like some of the shopify fields.
297 00:37:04.440 ⇒ 00:37:06.199 Jakob Kagel: oh, yeah, here we are doing like this.
298 00:37:06.200 ⇒ 00:37:07.140 Payas Parab: Yeah, yeah.
299 00:37:07.400 ⇒ 00:37:33.542 Jakob Kagel: I mean, there was an issue, too, I mean, so I did do like a table view for gross margin that was by like products like category that had like gross margin dollars, gross margin percent, and all of that but I think the issue was, I think, why Robert took it out to is like some of the numbers were coming through like, for certain categories, like accessories and stuff were coming through like really negative, so that may have been contributing to that as well.
300 00:37:33.840 ⇒ 00:37:45.509 Payas Parab: That. That’s what I’m that’s what I’m thinking is these like the platform fees. I think there was like a error when it was pulled in. It needed to be divided by a hundred that we can just double check that. But if we can confirm that that might be some of the error.
301 00:37:46.070 ⇒ 00:37:51.059 Uttam Kumaran: And this is but like it’s already happening for Amazon. Is this, you mean that this needs to happen for shopify.
302 00:37:52.488 ⇒ 00:37:54.331 Payas Parab: It needs to happen, for
303 00:37:55.650 ⇒ 00:38:01.600 Payas Parab: should have been no, this is for this is specifically for shopify merchant fees. So this is shopify. Yeah.
304 00:38:03.800 ⇒ 00:38:08.509 Payas Parab: Fact orders. I think the shopify fees. I just wanted to confirm.
305 00:38:09.240 ⇒ 00:38:11.550 Uttam Kumaran: Well, there’s nothing coming in. Oh, this is for okay, yeah.
306 00:38:11.550 ⇒ 00:38:14.600 Payas Parab: That’s Amazon. That’s the Amazon. Join. You have the.
307 00:38:14.600 ⇒ 00:38:16.130 Uttam Kumaran: Shopify merchant fees. Yeah.
308 00:38:16.130 ⇒ 00:38:18.760 Payas Parab: Yes, I believe those might have to be divided by a hundred.
309 00:38:19.860 ⇒ 00:38:20.480 Uttam Kumaran: Okay.
310 00:38:24.750 ⇒ 00:38:26.619 Payas Parab: But we should just double check.
311 00:38:33.580 ⇒ 00:38:34.540 Uttam Kumaran: Where is it?
312 00:38:37.860 ⇒ 00:38:39.160 Uttam Kumaran: What?
313 00:38:39.680 ⇒ 00:38:40.450 Uttam Kumaran: Hold on?
314 00:38:47.670 ⇒ 00:38:50.810 Uttam Kumaran: Soc, oh, shopify order, cog, sorry.
315 00:38:56.260 ⇒ 00:38:57.180 Uttam Kumaran: This one.
316 00:39:01.320 ⇒ 00:39:02.150 Uttam Kumaran: Right?
317 00:39:03.940 ⇒ 00:39:07.029 Uttam Kumaran: So you’re saying that. Yeah, you’re saying, this is
318 00:39:07.510 ⇒ 00:39:09.840 Uttam Kumaran: like too high, basically right now.
319 00:39:10.630 ⇒ 00:39:11.070 Payas Parab: Yeah.
320 00:39:11.070 ⇒ 00:39:11.820 Uttam Kumaran: Coming in. It’s like.
321 00:39:11.820 ⇒ 00:39:27.180 Payas Parab: It’s the. It’s the multiply by plf dot fee. I think the fee as it’s written in the assumption table is like percentages. It’s it’s not written as a decimal, it’s written as like a full. So if you go to cogs 3 pl. Is what the the thing is called. I think
322 00:39:28.080 ⇒ 00:39:29.910 Payas Parab: cogs 3 pl.
323 00:39:30.676 ⇒ 00:39:31.390 Uttam Kumaran: It’s called.
324 00:39:36.350 ⇒ 00:39:38.719 Payas Parab: Yeah, there it is. Cogs, 3 pl assumptions.
325 00:39:40.622 ⇒ 00:39:42.909 Payas Parab: Platform fees, assumptions.
326 00:39:44.900 ⇒ 00:39:52.850 Payas Parab: net revenue percentage. I I don’t know why we did it that way. Maybe it’s but yeah, but I think it’s because it me. It’s not a decimal, so it has to be divided by a hundred.
327 00:39:53.180 ⇒ 00:39:54.080 Payas Parab: Was it.
328 00:39:56.130 ⇒ 00:40:00.830 Uttam Kumaran: Oh, jeez, that’s so stupid. Dude fuck.
329 00:40:01.690 ⇒ 00:40:02.420 Uttam Kumaran: Okay?
330 00:40:02.840 ⇒ 00:40:06.620 Uttam Kumaran: Alright. Great look, we’ve we basically figured it out. So,
331 00:40:12.070 ⇒ 00:40:14.650 Uttam Kumaran: alright, yeah, this is, we just resolve this.
332 00:40:26.402 ⇒ 00:40:30.690 Uttam Kumaran: Okay, alright, we’ll fix it in there.
333 00:40:35.630 ⇒ 00:40:37.420 Uttam Kumaran: We need to divide by a hundred.
334 00:40:39.130 ⇒ 00:40:40.400 Payas Parab: Yeah. Divide by 100.
335 00:40:47.640 ⇒ 00:40:53.810 Uttam Kumaran: Okay, this is like a 5 min one. I will. I’ll already do that after this call cool.
336 00:40:53.970 ⇒ 00:40:56.810 Uttam Kumaran: So that’s another item. Let me just put that in there.
337 00:40:58.170 ⇒ 00:41:00.029 Uttam Kumaran: This is way. Better than notion.
338 00:41:09.430 ⇒ 00:41:13.430 Uttam Kumaran: Issue 94 sounds like what’s in Star Wars, where they’re like order 66.
339 00:41:14.080 ⇒ 00:41:14.570 Payas Parab: Yeah.
340 00:41:14.570 ⇒ 00:41:15.200 Uttam Kumaran: Yeah.
341 00:41:17.100 ⇒ 00:41:19.739 Uttam Kumaran: Execute order 66. Okay.
342 00:41:20.365 ⇒ 00:41:21.844 Uttam Kumaran: Alright. Let’s go back to
343 00:41:23.560 ⇒ 00:41:25.467 Uttam Kumaran: Go back to the top. What else?
344 00:41:27.010 ⇒ 00:41:30.029 Uttam Kumaran: What else can you give us. I mean, I basically want to know.
345 00:41:30.770 ⇒ 00:41:34.740 Uttam Kumaran: My point of view is like, how like.
346 00:41:35.130 ⇒ 00:41:38.979 Uttam Kumaran: how much shit can we get done this week to try to get the client to renew with us.
347 00:41:39.720 ⇒ 00:41:46.430 Uttam Kumaran: So, Pius, if you have ideas just like throw like
348 00:41:47.060 ⇒ 00:41:51.800 Uttam Kumaran: cause, let’s say we do get the gorgeous thing out. We do get the Amazon gross margin, that’s all good.
349 00:41:54.810 ⇒ 00:41:55.150 Uttam Kumaran: Let’s say.
350 00:41:55.150 ⇒ 00:41:55.540 Payas Parab: Where.
351 00:41:55.540 ⇒ 00:41:56.020 Uttam Kumaran: Streamline.
352 00:41:57.330 ⇒ 00:42:04.829 Uttam Kumaran: The way I want to do it is like, I think, we should produce a report like, do you see the one that, like Nico had sent me the example that you guys have done before for pool parts.
353 00:42:04.830 ⇒ 00:42:05.250 Uttam Kumaran: Yeah.
354 00:42:05.250 ⇒ 00:42:19.530 Payas Parab: That Pdf. Like I made a deck for them, which is like what I think got us. The previous renewal was like we made like a deck that was like, Hey, here are the 3 main things for gross margin. It’s like it involved mostly like raw, dogging sequel. But.
355 00:42:19.790 ⇒ 00:42:31.580 Uttam Kumaran: I I actually want to do that. That’s what I’m saying. So you want to do a point analysis on gross margin. I mean, we’re basically, I’m going to produce all the ingredients you need for that analysis in our hour session. Later.
356 00:42:31.580 ⇒ 00:42:32.569 Payas Parab: Yeah, if you.
357 00:42:32.570 ⇒ 00:42:32.910 Uttam Kumaran: So.
358 00:42:32.910 ⇒ 00:42:39.680 Payas Parab: Yeah, I just sent it in the and just to give everyone if you want to, just quickly. I I just sent it in the slack. I also linked it in zoom.
359 00:42:41.640 ⇒ 00:42:44.779 Payas Parab: Basically like, can we create something like this
360 00:42:45.270 ⇒ 00:42:51.649 Payas Parab: was like the idea we like had, like, key insights of like, okay, here’s what this was. This was before we figured out that the data was all wrong.
361 00:42:51.760 ⇒ 00:42:54.909 Payas Parab: So we did a lot of work to like, analyze all this shit right?
362 00:42:54.910 ⇒ 00:42:55.819 Uttam Kumaran: Could you? Yeah.
363 00:42:56.310 ⇒ 00:43:20.170 Jakob Kagel: That that’s like exactly. I mean, I don’t know that that’s my concern, at least. And I mean, I think definitely sort of all the things that y’all pointed out about the dashboard where it’s like, okay, maybe it’s very high level, and it’s not that insightful or probably true. But it’s like we. I don’t know. I I just have. There’s like a lot of sort of like data concerns. And I’m like we can produce something like this for them, but
364 00:43:20.360 ⇒ 00:43:22.230 Jakob Kagel: I don’t know. I mean, maybe we don’t have an option.
365 00:43:22.230 ⇒ 00:43:28.970 Uttam Kumaran: But I guess, like I don’t know. But, like, tell me what the I want to know, what the data concerns are, because not having this field is is
366 00:43:29.290 ⇒ 00:43:33.120 Uttam Kumaran: totally fine. We fixed sort of duplication issues
367 00:43:33.260 ⇒ 00:43:38.910 Uttam Kumaran: like, hit me with all the data concerns. Because I’m gonna patch. We’re gonna patch everything. Yeah.
368 00:43:38.910 ⇒ 00:43:53.349 Jakob Kagel: The big one, and I think I mean y’all may have fixed it so. It’s like, I’m not sure. But I think it’s probably like these platform fees that we’re probably fucking up like all the gross margin calculations when we when I tried to do them like from order line. So I think that’s really just the biggest.
369 00:43:53.350 ⇒ 00:43:58.040 Payas Parab: Well, in in order line it should be fixed. I found this bug with order line. I want to know.
370 00:43:58.040 ⇒ 00:44:00.909 Jakob Kagel: Alright. Well, I’ll show you all the numbers here. After this. In a second.
371 00:44:00.910 ⇒ 00:44:01.429 Uttam Kumaran: Yeah, yeah, yeah.
372 00:44:01.430 ⇒ 00:44:14.730 Jakob Kagel: Right now, real quick. But I think my biggest thing is like, okay, what happens like when we do the okay, we say the overall like gross margin is like, you know, I’m just. I think this is around Ballpark. But you know, I’m just spitballing. It’s like, maybe.
373 00:44:14.730 ⇒ 00:44:20.470 Uttam Kumaran: It’s not gonna match. It’s not gonna match. Because how are we gonna do shipments right? Like, how are you gonna do shipments and order discounts?
374 00:44:20.810 ⇒ 00:44:21.959 Jakob Kagel: Okay, I mean.
375 00:44:21.960 ⇒ 00:44:24.789 Uttam Kumaran: So it needs to be a different. It needs to be product level.
376 00:44:25.340 ⇒ 00:44:32.039 Uttam Kumaran: right pies. It needs to be product level profitability that can’t involve and wall discounts.
377 00:44:32.040 ⇒ 00:44:33.889 Payas Parab: I attempted to join it, so like it.
378 00:44:33.890 ⇒ 00:44:34.240 Uttam Kumaran: But like.
379 00:44:34.240 ⇒ 00:44:35.380 Payas Parab: Use a pack out, weight.
380 00:44:35.380 ⇒ 00:44:42.599 Uttam Kumaran: Just just math. Just yeah. But just math it out with me, like, how does that work? Because if if there’s an order discount, how do you attribute it
381 00:44:42.710 ⇒ 00:44:44.620 Uttam Kumaran: to the underlying order lines.
382 00:44:47.740 ⇒ 00:44:49.789 Payas Parab: That’s fair. You don’t, you don’t but like.
383 00:44:49.790 ⇒ 00:44:54.380 Uttam Kumaran: If if it’s a shipment, you could separate it by the weight.
384 00:44:55.520 ⇒ 00:45:06.800 Payas Parab: The shipment. I did separate by weight. So I had like for each individual item. There’s like that amount of weight if you round up is roughly, how much? Oh, motherfucker, you’re right. That won’t work because it’s not. It’s not a linear scale.
385 00:45:07.540 ⇒ 00:45:12.150 Uttam Kumaran: Oh, yeah. So that’s you’re assuming that you pay linearly, which?
386 00:45:12.290 ⇒ 00:45:37.270 Uttam Kumaran: Yeah, I don’t know. So I think the best thing is just to say we don’t we? We’re not doing that. Why, like that’s a discussion we can have. And ultimately I think we’ll win. Is that you just don’t worry about shipments and ordered level discounts in your product level profitability. Because what are? How are they gonna optimize? They’re gonna say, don’t never discount any order with like this in there like that’s so derivative. Or what are they gonna say, like.
387 00:45:37.380 ⇒ 00:45:40.019 Uttam Kumaran: like, how are you gonna change this? How are you gonna like?
388 00:45:40.960 ⇒ 00:45:49.910 Uttam Kumaran: I don’t know like we’re gonna reduce the weight of something when it gets shipped, bundled like I don’t think they care. They want to look. They’re probably gonna want to look at lowering the fixed cost to produce the thing.
389 00:45:50.290 ⇒ 00:45:54.410 Uttam Kumaran: They’re probably gonna wanna look to see that they’re selling more throughput of that.
390 00:45:54.960 ⇒ 00:45:58.390 Uttam Kumaran: Yeah, I think that’s fair? Yeah, right?
391 00:45:58.890 ⇒ 00:46:02.740 Payas Parab: Why, why don’t we do this? What? Or Jacob might be? Because, Jacob, you did some like like
392 00:46:02.840 ⇒ 00:46:08.460 Payas Parab: sequel, or there’s some like like comparison to find the concentrates versus Protein versus whatever right like.
393 00:46:08.460 ⇒ 00:46:11.890 Jakob Kagel: Yeah, it’s like, I mean, it’s just like rejects. Basically, I mean.
394 00:46:11.890 ⇒ 00:46:17.839 Payas Parab: That’s so. What I’m what I’m thinking. Uta, maybe, is like we have flags in the order. Table that are like
395 00:46:17.980 ⇒ 00:46:21.279 Payas Parab: is protein is concentrate, is.
396 00:46:21.280 ⇒ 00:46:22.640 Jakob Kagel: And they can be multiple.
397 00:46:22.640 ⇒ 00:46:24.679 Payas Parab: Multi item, something like that.
398 00:46:24.680 ⇒ 00:46:28.220 Uttam Kumaran: So where? So where is that? Is that Regex? Somewhere right now?
399 00:46:28.500 ⇒ 00:46:33.399 Jakob Kagel: I mean, it’s just in right now. It’s just in Meta Base. It’s in like the the product type view.
400 00:46:34.560 ⇒ 00:46:45.710 Jakob Kagel: Well, I mean, it’s just, you know, when they contain basically like, it’s under the custom column product there up to the top. Go up. Sorry. The next one.
401 00:46:45.710 ⇒ 00:46:46.460 Uttam Kumaran: Oh, here!
402 00:46:47.090 ⇒ 00:46:49.160 Jakob Kagel: Right? Exactly. That’s all it is. Yeah.
403 00:46:49.160 ⇒ 00:46:54.499 Uttam Kumaran: So then it’s like, let’s so you need a okay. So here’s what you guys need. You’ll need a
404 00:46:54.640 ⇒ 00:47:03.080 Uttam Kumaran: product list for every order and for every order line, you need a product category right? Basically.
405 00:47:03.720 ⇒ 00:47:17.659 Payas Parab: For every orders we need, like a like a tag of like what what is contained short, like something like this, the string matching, that’s 1. And then order line. I think there’s just like only us, there’s very limited what we can actually analyze in order line. I think that’s the main reality.
406 00:47:17.930 ⇒ 00:47:21.569 Payas Parab: because there’s so much stuff done at the order level, whether it’s shipping. So I think.
407 00:47:21.570 ⇒ 00:47:22.109 Jakob Kagel: But we’re getting.
408 00:47:22.110 ⇒ 00:47:26.080 Payas Parab: The only thing we can do is like, determine, like.
409 00:47:26.080 ⇒ 00:47:29.720 Uttam Kumaran: No, but you can look at. You can look at single item orders.
410 00:47:30.170 ⇒ 00:47:41.419 Uttam Kumaran: and then you can basically not. You don’t. You don’t need to worry about the total again, you do single item versus multi item. And you then just look at just a cohort of single item orders. Here’s
411 00:47:41.630 ⇒ 00:47:42.910 Uttam Kumaran: the whole spread.
412 00:47:43.050 ⇒ 00:47:49.479 Uttam Kumaran: and then you could look at orders that contain one orders that contain another like the wider categories. Right?
413 00:47:51.850 ⇒ 00:47:58.480 Uttam Kumaran: Cause do it like figuring out a linearly split shipping costs, figuring out how to do the discount. It’s gonna take some time.
414 00:47:58.480 ⇒ 00:47:59.160 Payas Parab: Yep.
415 00:47:59.320 ⇒ 00:48:04.050 Uttam Kumaran: So I. So I sort of want us to build. Figure out what we can build in terms of the story, for
416 00:48:04.370 ⇒ 00:48:11.119 Uttam Kumaran: I think the number. One analysis we can do is look at the components of profitability and how they change across
417 00:48:11.280 ⇒ 00:48:32.469 Uttam Kumaran: client types, across product types, across Geos, things like that right? Look at the components, split it, and just see like, oh, shit! Every time we ship to this, for example, what we did for pool parts is, we noticed that because they’re not using a 3 pl. They’re shipping everything from New York. Everything on the West Coast and Texas is like mad, expensive. So we were like.
418 00:48:32.700 ⇒ 00:48:37.419 Uttam Kumaran: you guys need to open the 3 pl. Or have something on the West coast to supplement it.
419 00:48:37.420 ⇒ 00:48:38.280 Payas Parab: Sure, sure.
420 00:48:38.506 ⇒ 00:48:41.220 Uttam Kumaran: So that’s the thing you’ll clearly be able to see is like.
421 00:48:42.060 ⇒ 00:48:44.750 Uttam Kumaran: take the customer location and look at
422 00:48:44.920 ⇒ 00:48:48.160 Uttam Kumaran: for all the customers that order. From this we noticed that
423 00:48:48.350 ⇒ 00:48:52.119 Uttam Kumaran: the spread of cogs to shipping was way higher than
424 00:48:52.300 ⇒ 00:48:57.900 Uttam Kumaran: for the entire stupid. So things like that. So those are, I think the stories that are really really great.
425 00:49:05.730 ⇒ 00:49:06.790 Uttam Kumaran: this is one.
426 00:49:10.120 ⇒ 00:49:12.659 Uttam Kumaran: I mean, I think if you can think of
427 00:49:12.830 ⇒ 00:49:16.029 Uttam Kumaran: stretch goal of 5. But like 3 things that
428 00:49:16.160 ⇒ 00:49:24.109 Uttam Kumaran: you want to do here. And we just basically try to get you the data to do this, and y’all just rip like some pivot tables to produce something for this.
429 00:49:24.696 ⇒ 00:49:26.840 Uttam Kumaran: I don’t know, like I feel like
430 00:49:27.150 ⇒ 00:49:29.970 Uttam Kumaran: that’s a good outcome from the gross margin dashwork.
431 00:49:30.290 ⇒ 00:49:34.850 Uttam Kumaran: because ultimately what we learned across all clients is the dashboard is like
432 00:49:35.330 ⇒ 00:49:56.990 Uttam Kumaran: the dashboard is a representation of our ability to analyze. Nobody looks at dashboards like that’s why I really like it’s such a struggle for all of our clients to spend time in dashboards because they’re not us. They don’t even know what they’re looking at. It’s really really hard. In fact, most of the people that look at dashboards just look at it and make sure that they’re not going to get yelled at in like their next meeting.
433 00:49:56.990 ⇒ 00:49:57.340 Payas Parab: Yeah.
434 00:49:57.340 ⇒ 00:50:04.280 Uttam Kumaran: Nobody is doing this sort of analysis. So we have to pair every dashboard with the finding.
435 00:50:04.690 ⇒ 00:50:09.000 Uttam Kumaran: I think maybe you take on something for gross margin. Maybe pies. If I can get you
436 00:50:09.350 ⇒ 00:50:13.540 Uttam Kumaran: stuff across gorgeous stuff across Amazon.
437 00:50:14.540 ⇒ 00:50:18.880 Uttam Kumaran: I don’t know. Like I kind of. I’m like we should just do a version of this.
438 00:50:18.880 ⇒ 00:50:22.130 Payas Parab: Like, just rip like a like imagine. We’re like a just a.
439 00:50:22.130 ⇒ 00:50:28.679 Uttam Kumaran: Qbr, yeah, like, say, like, we, just, we just, we pushed really hard over the past month to get you this. Qbr.
440 00:50:29.100 ⇒ 00:50:34.809 Uttam Kumaran: that’s like what I we didn’t do that, but like we did in 3 days. And I’ll just make sure that you have all this data
441 00:50:34.920 ⇒ 00:50:45.309 Uttam Kumaran: if you want help coming up with ideas. Or if we want to agree on like 3, we we basically could agree on like 3 themes. And I can even help to put something like this together.
442 00:50:45.310 ⇒ 00:50:48.209 Jakob Kagel: Yeah, I mean, I’m happy to help, too, of just, you know, pulling.
443 00:50:48.210 ⇒ 00:51:00.350 Payas Parab: I think even Jacob Jacob, you’re running into the same thing I ran into, which is like there’s just like a whole shit load of data that’s like a mess that like getting it into like nice, usable dashboard format is just like a really, not trivial task. So we’re just like.
444 00:51:00.350 ⇒ 00:51:10.050 Uttam Kumaran: But I I wanna I just want to know what that means like, break that down for me, which is beyond the issues that we just talked about? What other issues are there.
445 00:51:11.130 ⇒ 00:51:22.290 Payas Parab: I mean 1 1 is that fundamentally, every single thing on a financial metric is based off of an assumption right? And it’s based off an assumption that we took like bottom up, so like every single one, if like
446 00:51:22.500 ⇒ 00:51:29.860 Payas Parab: like, when they filled out that spreadsheet they like didn’t quite do that correctly right? Like how it reflects. Then it’s like really easy for us to look
447 00:51:30.120 ⇒ 00:51:31.730 Payas Parab: dumb. If, like.
448 00:51:31.980 ⇒ 00:51:39.879 Payas Parab: Okay, like the disk like this, this assumption is too like high or low it, the entire margin will look really off.
449 00:51:40.150 ⇒ 00:51:43.319 Uttam Kumaran: But how like, I guess, tell like, tell me what like
450 00:51:43.840 ⇒ 00:51:45.979 Uttam Kumaran: this is like. I’m getting deja vu
451 00:51:46.270 ⇒ 00:51:52.310 Uttam Kumaran: kyle, because we just talked about some other thing which is like every one of our E-com clients, has a cogs
452 00:51:52.470 ⇒ 00:51:55.420 Uttam Kumaran: reconciliation process that they need to do.
453 00:51:56.156 ⇒ 00:52:07.600 Uttam Kumaran: Probably once a month where they they update what their product costs are. We’re doing this for pool parts. We’re literally doing this. We have a spreadsheet for Eden. We do this for these guys.
454 00:52:07.730 ⇒ 00:52:17.879 Uttam Kumaran: So, but at the same time, like, How do you force that conversation? Well, you force it with our analysis by saying, our profitability hangs
455 00:52:18.290 ⇒ 00:52:20.069 Uttam Kumaran: by this thread.
456 00:52:20.480 ⇒ 00:52:23.670 Uttam Kumaran: So is this accurate right like.
457 00:52:23.780 ⇒ 00:52:28.210 Uttam Kumaran: But what can we move with? We have to assume that this is accurate, right, unless you think like
458 00:52:30.360 ⇒ 00:52:34.880 Uttam Kumaran: like it’s not I don’t. Whose fault is it on the call that this isn’t accurate like, not mine, right.
459 00:52:34.880 ⇒ 00:52:36.420 Payas Parab: Yeah, yeah, that’s fair.
460 00:52:36.420 ⇒ 00:52:37.240 Uttam Kumaran: So.
461 00:52:37.240 ⇒ 00:52:39.909 Payas Parab: Okay, you’re right. I I think maybe it’s like.
462 00:52:40.380 ⇒ 00:52:52.059 Uttam Kumaran: Like that’s like a existential thing that you should put in like big letters on the slide. That’s like our cogs are coming from the spreadsheet, and there’s either like, what is the actual? Is there? Is there issue? Because there’s not up to date.
463 00:52:52.220 ⇒ 00:52:55.460 Uttam Kumaran: We don’t believe it’s accurate. And then you like.
464 00:52:56.460 ⇒ 00:52:56.919 Payas Parab: With that guy.
465 00:52:57.350 ⇒ 00:52:57.920 Uttam Kumaran: Yeah.
466 00:52:58.503 ⇒ 00:52:58.969 Payas Parab: Think it’s.
467 00:52:58.970 ⇒ 00:53:02.249 Uttam Kumaran: That’s that’s something existential. We can’t control, like, you know, on this call.
468 00:53:03.090 ⇒ 00:53:27.530 Payas Parab: Yeah, yeah, no, I I hear you. I think it’s just like, even if you’re looking at like, literally what we’re looking at here, right is like the skew. It’s like they do the same thing that, like pool parts does where it’s like some rogue skew notation that, like some of them are protein. Some of them are like a protein concentrate bundle. Some of them are like whatever so like. For example, if Jacob runs that like like, you know that sequel that, like Regex, like you may get that. It’s like both protein and
469 00:53:27.540 ⇒ 00:53:36.729 Payas Parab: this. But there may only be one skew, and like the only real way you would like figure that out is like, I’m in there rawdogging sequel and being like, why the fuck does this look off? Okay, let me.
470 00:53:36.730 ⇒ 00:53:47.839 Uttam Kumaran: But we’ll but we’ll we’ll figure this out in the model, too, that like. But that’s the thing it’s like I want to, even if that’s an issue. And fundamentally, we can solve this, then one, I want to know, like.
471 00:53:48.050 ⇒ 00:53:53.149 Uttam Kumaran: can I? Okay, when can I get us on a call with somebody to solve this by Wednesday.
472 00:53:53.750 ⇒ 00:54:07.110 Uttam Kumaran: or like cause. I’ll hop on a call with whoever I need to talk to there and rip through that like getting this stuff done. But is that something feasible? If it’s not feasible to fix this, then I’m gonna say, we run through the analysis with with these being
473 00:54:07.470 ⇒ 00:54:10.389 Uttam Kumaran: what we know is accurate, and you, caveat, really heavily.
474 00:54:10.560 ⇒ 00:54:11.600 Payas Parab: Sure. Okay.
475 00:54:11.750 ⇒ 00:54:15.879 Uttam Kumaran: Cause. I. What are what are told? What alternative do we have right.
476 00:54:16.190 ⇒ 00:54:18.159 Payas Parab: No, no, I agree. I.
477 00:54:18.160 ⇒ 00:54:20.680 Uttam Kumaran: Who’s like, who’s on the hook? Who did you work with this on.
478 00:54:21.987 ⇒ 00:54:23.840 Payas Parab: Elia and Jonathan.
479 00:54:25.160 ⇒ 00:54:25.920 Uttam Kumaran: Like.
480 00:54:26.670 ⇒ 00:54:34.549 Uttam Kumaran: Do you think I should propose like I can think about another format and sort of try to give you something to call them about like, do I don’t know. What do you think.
481 00:54:34.840 ⇒ 00:54:35.747 Payas Parab: I I mean.
482 00:54:37.740 ⇒ 00:54:45.440 Uttam Kumaran: Cause basically you’re I know what you mean. Meaning like, some of these are multi product skews. Some of these, some of these are multi product bundles. Some of these are single product skews.
483 00:54:45.440 ⇒ 00:54:46.030 Payas Parab: Yes, yes.
484 00:54:46.030 ⇒ 00:54:49.090 Uttam Kumaran: I need. I need a field here that basically indicates that
485 00:54:49.650 ⇒ 00:54:53.010 Uttam Kumaran: I mean, it looks like product name, we may be able to.
486 00:54:53.530 ⇒ 00:54:57.779 Payas Parab: But but that’s what Jacob’s doing right. But it’s like, when you finally like. Put do it it like.
487 00:54:57.780 ⇒ 00:55:01.307 Payas Parab: let’s take it. Let’s let’s let’s take an example.
488 00:55:04.360 ⇒ 00:55:07.059 Uttam Kumaran: So what’s 1 with multiple products.
489 00:55:10.700 ⇒ 00:55:11.250 Uttam Kumaran: Like
490 00:55:11.800 ⇒ 00:55:15.849 Payas Parab: Bobby bundles, original origin, 72 row, 72.
491 00:55:16.420 ⇒ 00:55:23.039 Uttam Kumaran: So why don’t I just classify this as a bundle product, right like, why can’t I just create a flag here.
492 00:55:23.060 ⇒ 00:55:26.000 Payas Parab: But like yes.
493 00:55:26.000 ⇒ 00:55:32.630 Uttam Kumaran: And then and then and then, Mike. But my next question to you is, of course, does the math math like? Is it? Does this truly
494 00:55:32.750 ⇒ 00:55:34.720 Uttam Kumaran: is, there are the cogs. Truly
495 00:55:35.350 ⇒ 00:55:43.860 Uttam Kumaran: the individual components added up to get this are there like other assumptions.
496 00:55:45.030 ⇒ 00:55:48.160 Payas Parab: Because for for fill out the assumption right?
497 00:55:48.160 ⇒ 00:56:11.369 Uttam Kumaran: For for Eden, for example, they have bundles, but it’s literally just this one plus this one. And I, I noticed that I’m like, okay, great cause. Now I can. Just, I added a flag in Eden which says, Is this a single product? Because they gave us the same sort of bullshit I went through and said, Is this a single product or not? And then for any bundled products, I take it from the single product to add it up.
498 00:56:11.980 ⇒ 00:56:21.739 Uttam Kumaran: So what? What we could do, I mean, look, there’s only there’s only 100. We could basically go through, create a flag that’s like, is this a single product for any bundles. I just need to know what the combination is.
499 00:56:21.980 ⇒ 00:56:22.530 Jakob Kagel: Yeah, I mean.
500 00:56:22.530 ⇒ 00:56:23.540 Uttam Kumaran: That’s right.
501 00:56:23.540 ⇒ 00:56:29.099 Jakob Kagel: Like when I was building the flag. I was just copying the logic that was existing in the amplitude dashboard.
502 00:56:30.830 ⇒ 00:56:33.730 Uttam Kumaran: Yeah for that Regex logic. Yeah. I mean, it’s gonna be.
503 00:56:33.950 ⇒ 00:56:34.690 Jakob Kagel: Yeah.
504 00:56:34.690 ⇒ 00:56:36.931 Uttam Kumaran: Yeah, it’s not gonna work.
505 00:56:37.920 ⇒ 00:56:42.309 Uttam Kumaran: I mean, pies like, is that something that like would help this like where
506 00:56:42.910 ⇒ 00:56:50.019 Uttam Kumaran: I just need to know that the original caramel, French vanilla mocha is actually the sum of each of one of these.
507 00:56:51.040 ⇒ 00:57:04.180 Payas Parab: I I right now, I just think that’s like not a worthy. If we’re thinking about the Friday deadline, it’s not a worthwhile exercise right now, I think it’s kind of like we’re like, we’re just getting so hung up on like building the right data models, in my opinion, that like we just need to like
508 00:57:04.280 ⇒ 00:57:05.400 Payas Parab: get a deck right like.
509 00:57:05.400 ⇒ 00:57:05.959 Uttam Kumaran: I’m with you.
510 00:57:05.960 ⇒ 00:57:07.910 Payas Parab: Think like we’re Deloitte and Mckenzie, and we like.
511 00:57:07.910 ⇒ 00:57:08.480 Uttam Kumaran: I’m with you.
512 00:57:08.480 ⇒ 00:57:13.390 Payas Parab: A pitch. That’s Friday, and we just got to like get something in front of them to win the money.
513 00:57:13.390 ⇒ 00:57:13.990 Uttam Kumaran: Yeah.
514 00:57:14.303 ⇒ 00:57:16.500 Payas Parab: I I don’t think like that is
515 00:57:17.440 ⇒ 00:57:21.090 Payas Parab: as helpful as like if we can just like, from what we have.
516 00:57:21.390 ⇒ 00:57:22.020 Uttam Kumaran: So then
517 00:57:22.020 ⇒ 00:57:31.460 Uttam Kumaran: I can. I just create. Can I like, can you tell me? Let’s just talk about this logic because this is going to be core, then. So this is like, not. I can’t even format this properly in fig jam. But like.
518 00:57:31.680 ⇒ 00:57:36.940 Uttam Kumaran: should I create a bundle like is like, do we want to update this like this logic.
519 00:57:44.120 ⇒ 00:57:45.479 Payas Parab: Let me think a lot.
520 00:57:47.170 ⇒ 00:57:51.960 Payas Parab: Jacob, do you have a view on this? Because you’ve been more in the, in the weeds on like these like order line data.
521 00:57:52.240 ⇒ 00:57:55.820 Jakob Kagel: Like if we should create a separate one that’s called bundle.
522 00:57:56.220 ⇒ 00:58:03.189 Payas Parab: Yeah, like in in orders, there’d be like, is Creamer is whatever and like is multi product is whatever.
523 00:58:04.720 ⇒ 00:58:11.151 Jakob Kagel: I mean, yeah, I think I can. Just I mean, run a query real quick, and just see how many would come back as bundle. I mean,
524 00:58:11.390 ⇒ 00:58:18.120 Uttam Kumaran: But I guess, just like, let’s look at we have this year. We have these. Our goal is to categorize these right, like very simply.
525 00:58:18.540 ⇒ 00:58:19.150 Jakob Kagel: Right.
526 00:58:19.820 ⇒ 00:58:26.560 Uttam Kumaran: Do right now? Where should wherever that that one like? Where should this go?
527 00:58:28.040 ⇒ 00:58:30.080 Uttam Kumaran: And and I guess, even before that
528 00:58:30.280 ⇒ 00:58:34.099 Uttam Kumaran: did do they have a perspective. Did they work on these categories or no?
529 00:58:34.470 ⇒ 00:58:35.920 Uttam Kumaran: We we proposed it.
530 00:58:36.420 ⇒ 00:58:38.189 Uttam Kumaran: Oh, this was there before, but, like.
531 00:58:38.190 ⇒ 00:58:40.999 Jakob Kagel: Yeah, I just took what was in amplitude, basically. And.
532 00:58:41.000 ⇒ 00:58:41.570 Uttam Kumaran: Okay.
533 00:58:43.345 ⇒ 00:58:46.799 Jakob Kagel: This is probably something we should own, which is like a product category.
534 00:58:47.070 ⇒ 00:58:48.459 Uttam Kumaran: Sort of definition.
535 00:58:49.430 ⇒ 00:58:52.250 Jakob Kagel: Right cause. This would probably fall into other right. Now.
536 00:58:53.090 ⇒ 00:58:53.690 Uttam Kumaran: Yeah.
537 00:58:54.600 ⇒ 00:58:56.579 Uttam Kumaran: So I feel like, I mean.
538 00:58:56.790 ⇒ 00:58:59.380 Uttam Kumaran: I don’t price if you want to go. Otherwise I can
539 00:58:59.820 ⇒ 00:59:02.160 Uttam Kumaran: try to like, give us the answers.
540 00:59:03.050 ⇒ 00:59:05.599 Payas Parab: No, no, I I’m I’m open to what you think is the right.
541 00:59:05.600 ⇒ 00:59:09.139 Uttam Kumaran: Then I then I think we should basically categorize as
542 00:59:09.340 ⇒ 00:59:15.840 Uttam Kumaran: one single versus bundle. There should be one thing that’s like single versus bundle
543 00:59:16.420 ⇒ 00:59:20.169 Uttam Kumaran: that’s like a flag. The second thing is for product type.
544 00:59:20.430 ⇒ 00:59:25.510 Uttam Kumaran: We basically want to make sure that bundles are categorized here.
545 00:59:28.620 ⇒ 00:59:33.920 Uttam Kumaran: And then, ideally, I have to look. Does the order line for this come in as 3
546 00:59:34.230 ⇒ 00:59:35.370 Uttam Kumaran: 3 items.
547 00:59:35.370 ⇒ 00:59:36.969 Payas Parab: No, it comes in as one.
548 00:59:36.970 ⇒ 00:59:42.050 Uttam Kumaran: Okay, sick. Then we just have one product type this, but that’s like A,
549 00:59:43.340 ⇒ 00:59:48.920 Uttam Kumaran: that’s another problem for them to tell us. Like, I see now what you mean. Where do they want us to split that up?
550 00:59:49.220 ⇒ 00:59:50.220 Payas Parab: Yeah, yeah.
551 00:59:51.200 ⇒ 00:59:51.620 Uttam Kumaran: So.
552 00:59:51.620 ⇒ 00:59:59.720 Payas Parab: You can do it at the skew level, right? Like you could quickly just be like, Okay, cool for every skew. What was my margin, but
553 00:59:59.980 ⇒ 01:00:05.309 Payas Parab: or like, if it contained this skew, what was the margin on that order? You could kind of look at that. But then.
554 01:00:05.570 ⇒ 01:00:07.359 Payas Parab: like, in some instances, yeah, like.
555 01:00:07.360 ⇒ 01:00:13.240 Uttam Kumaran: Fundamentally, we need product. You skew and order lines are one to one.
556 01:00:13.240 ⇒ 01:00:13.670 Payas Parab: Yes.
557 01:00:13.670 ⇒ 01:00:18.119 Uttam Kumaran: And then orders is multiple order lines. But we don’t have a dim products.
558 01:00:18.810 ⇒ 01:00:22.540 Uttam Kumaran: Dim products needs to be all single product items.
559 01:00:25.090 ⇒ 01:00:25.720 Payas Parab: Correct.
560 01:00:25.720 ⇒ 01:00:32.669 Uttam Kumaran: And ideally, we need to understand how every product rolls into a bundle. Them bundles.
561 01:00:34.010 ⇒ 01:00:38.009 Uttam Kumaran: So I need to know what is the cost of this.
562 01:00:38.120 ⇒ 01:00:40.099 Uttam Kumaran: And how is it? How is it different?
563 01:00:40.220 ⇒ 01:00:44.920 Uttam Kumaran: Then the 3 components like, is there a additional bundle cost
564 01:00:45.090 ⇒ 01:00:48.950 Uttam Kumaran: something like that? Right? So we want that. So we want dim products.
565 01:00:54.240 ⇒ 01:00:54.980 Uttam Kumaran: Great?
566 01:00:57.440 ⇒ 01:01:03.639 Uttam Kumaran: so let’s say we have everything here which is like bundle. All of these products. Are there anything we’re missing?
567 01:01:06.440 ⇒ 01:01:10.449 Uttam Kumaran: Creamer concentrate protein, I mean, I can ask. I’ll just probably throw this.
568 01:01:10.450 ⇒ 01:01:14.329 Jakob Kagel: How about a separate view? That’s like by flavor?
569 01:01:15.040 ⇒ 01:01:16.229 Uttam Kumaran: Oh, yeah. Okay.
570 01:01:16.230 ⇒ 01:01:19.850 Jakob Kagel: But that’s like, yeah, I mean, I I don’t necessarily think that has to be included.
571 01:01:19.850 ⇒ 01:01:20.750 Uttam Kumaran: Oh!
572 01:01:20.750 ⇒ 01:01:23.419 Jakob Kagel: I mean, you can do that grouping separately, I think.
573 01:01:24.370 ⇒ 01:01:28.929 Jakob Kagel: but it does get tricky, I guess if you have a bundle and you have 3 flavors like.
574 01:01:29.240 ⇒ 01:01:32.480 Jakob Kagel: but I guess it technically should get counted across each.
575 01:01:32.760 ⇒ 01:01:36.760 Uttam Kumaran: But like so by by flavor and product, we shouldn’t. That’s like a
576 01:01:37.030 ⇒ 01:01:40.589 Uttam Kumaran: product variant, right? Or like some sort of flavor. Yeah.
577 01:01:43.210 ⇒ 01:01:51.830 Uttam Kumaran: And I assume the cost changes right? So we don’t have that like I don’t. It’s not clear here how flavor affects the cost of a different product.
578 01:01:51.970 ⇒ 01:01:57.859 Uttam Kumaran: So we need to be. We need to basically try to get everything in that level. Until then. It’s it’s gonna be kind of hard.
579 01:02:06.650 ⇒ 01:02:16.889 Uttam Kumaran: see? Like, look caramel, protein, coffee, protein, coffee blend, French vanilla, protein coffee. You can see the flavor does affect the product cost, but doesn’t affect the weight
580 01:02:17.370 ⇒ 01:02:22.800 Uttam Kumaran: right? So my assumption here would be caramel is some price like
581 01:02:23.270 ⇒ 01:02:29.830 Uttam Kumaran: caramel? Looks like 47 cents. French vanilla looks like an additional 54 cents.
582 01:02:30.580 ⇒ 01:02:31.460 Uttam Kumaran: Right?
583 01:02:31.570 ⇒ 01:02:36.209 Uttam Kumaran: Can I? Can I go. Can I go that direction with my assumptions? Because then I’m just gonna build out.
584 01:02:36.430 ⇒ 01:02:39.690 Uttam Kumaran: I’m gonna build out dim flavors, dim products.
585 01:02:40.190 ⇒ 01:02:41.690 Uttam Kumaran: And we’re going to roll that up.
586 01:02:42.580 ⇒ 01:02:44.500 Uttam Kumaran: No, that- that makes sense your logic.
587 01:02:44.500 ⇒ 01:02:49.470 Uttam Kumaran: Sec. So then, is collagen a flavor. I thought, it’s flavorless.
588 01:02:56.290 ⇒ 01:02:58.660 Uttam Kumaran: okay, so how about? I’m just gonna I’m gonna go.
589 01:02:58.660 ⇒ 01:03:03.250 Payas Parab: 1 1. Sorry. There’s 1. 1 additional thing to dim products is free. Gifts need to be tagged.
590 01:03:05.090 ⇒ 01:03:06.050 Jakob Kagel: Yeah, what is a free.
591 01:03:06.050 ⇒ 01:03:06.840 Uttam Kumaran: Let’s do this.
592 01:03:07.350 ⇒ 01:03:11.600 Payas Parab: There’s a list that we Jacob actually found. I think, Jacob, you you have it somewhere. There’s like a list.
593 01:03:11.600 ⇒ 01:03:19.440 Uttam Kumaran: But like free free milk frother, isn’t that just a frother? Yeah, look, the numbers are the same. Oh, what the fuck about? Why is this heavier.
594 01:03:22.280 ⇒ 01:03:25.109 Jakob Kagel: I don’t know. Maybe it comes in a gift box or something.
595 01:03:25.110 ⇒ 01:03:29.780 Uttam Kumaran: Oh, shit, really. Okay. So the so like, the okay.
596 01:03:32.039 ⇒ 01:03:33.470 Payas Parab: I also do have to jump. I’m sorry, guys.
597 01:03:33.470 ⇒ 01:03:34.980 Uttam Kumaran: Okay, okay, that’s fine. That’s fine. That’s fine.
598 01:03:35.370 ⇒ 01:03:42.020 Jakob Kagel: Let me know. I mean I’m happy to help with whatever you all need help with. If it’s pulling data working on the dashboard.
599 01:03:42.020 ⇒ 01:03:47.989 Uttam Kumaran: Let me let me get organized. Let me get organized around this. I’m gonna I’ll probably send out a note.
600 01:03:48.150 ⇒ 01:03:50.710 Uttam Kumaran: or this afternoon, maybe between.
601 01:03:51.454 ⇒ 01:03:57.560 Jakob Kagel: Probably beau me, you and Jacob we can meet, and, Jacob, if you can make it. That’s fine. Otherwise we’ll probably just do a working session
602 01:03:57.560 ⇒ 01:04:00.959 Jakob Kagel: if you can do like I don’t know. Late afternoon is good.
603 01:04:00.960 ⇒ 01:04:02.409 Uttam Kumaran: Yeah. Late afternoon.
604 01:04:02.410 ⇒ 01:04:03.590 Jakob Kagel: Yep. Sounds great.
605 01:04:03.770 ⇒ 01:04:07.390 Uttam Kumaran: Okay, cool, I guess. Bo Kyle, any
606 01:04:07.880 ⇒ 01:04:12.909 Uttam Kumaran: thoughts on this? I know we didn’t get as far as we did on Eden overall in terms of organization. But
607 01:04:13.380 ⇒ 01:04:18.960 Uttam Kumaran: we have some like super specific stuff. I know, Kyle, it’s probably late your time.
608 01:04:19.090 ⇒ 01:04:23.429 Uttam Kumaran: But I think there’s definitely some broader data model organization we need to do.
609 01:04:24.040 ⇒ 01:04:30.700 Uttam Kumaran: But given the theme of this week, which is just like, try and get as much done like, how do you guys feel sort of seeing these items.
610 01:04:34.520 ⇒ 01:04:35.240 Bo Yoon: Yeah, I mean,
611 01:04:35.480 ⇒ 01:04:37.029 Caio Velasco: Well at the reason why.
612 01:04:37.220 ⇒ 01:04:38.210 Caio Velasco: Go ahead.
613 01:04:39.080 ⇒ 01:04:41.379 Bo Yoon: Oh, no. Okay, go ahead. Go ahead. Go ahead.
614 01:04:42.750 ⇒ 01:04:59.060 Caio Velasco: No, I was just gonna say that I’m still learning about everything, and I have to spend more time in the database to check things now that I have more information regarding gorgeous, I can also look into that. But I think I might a little bit of time to
615 01:04:59.230 ⇒ 01:05:00.689 Caio Velasco: to get there, I guess.
616 01:05:00.990 ⇒ 01:05:05.820 Uttam Kumaran: Eden, we Eden, we have a little bit of time. This one is like a Navy Seal Mission for this week.
617 01:05:06.110 ⇒ 01:05:09.570 Uttam Kumaran: so I’m gonna push and try to get as much as I can.
618 01:05:09.680 ⇒ 01:05:18.320 Uttam Kumaran: I would say, where I need help. Kyle is probably to get the gorgeous stuff like some something out that way. We can start to use that
619 01:05:18.590 ⇒ 01:05:26.409 Uttam Kumaran: I can handle working on this product category. I can handle those small little fixes. They need the gorgeous and okendo
620 01:05:26.660 ⇒ 01:05:29.370 Uttam Kumaran: data, Mart, we may just have to
621 01:05:29.920 ⇒ 01:05:32.430 Uttam Kumaran: try and get something out that we can work with.
622 01:05:32.750 ⇒ 01:05:35.060 Uttam Kumaran: I don’t know. I don’t think we have.
623 01:05:35.510 ⇒ 01:05:41.739 Uttam Kumaran: I don’t. I don’t think we’ll have a lot of time to basically go through the full dashboard requirements. Exercise
624 01:05:42.576 ⇒ 01:05:47.920 Uttam Kumaran: but it would be great to try to get something out for those items, and then
625 01:05:48.160 ⇒ 01:05:51.769 Uttam Kumaran: we just sort of I’m trying to set Robert up with like
626 01:05:52.050 ⇒ 01:05:56.579 Uttam Kumaran: 10 things that he could talk about to try to win us at least another month.
627 01:05:56.720 ⇒ 01:05:58.750 Uttam Kumaran: You know where we can get back on track.
628 01:06:01.210 ⇒ 01:06:06.809 Caio Velasco: Okay, okay, I’ll try my best here to learn everything about gorgeous and then see? See what can come out of it.
629 01:06:07.010 ⇒ 01:06:07.819 Uttam Kumaran: Okay. Cool.
630 01:06:09.800 ⇒ 01:06:16.359 Bo Yoon: For this company is the revenue coming from, I mean, most of the revenue is coming from Amazon or their shop.
631 01:06:16.360 ⇒ 01:06:19.390 Uttam Kumaran: Amazon, and shopify both account.
632 01:06:19.390 ⇒ 01:06:21.939 Bo Yoon: What’s the proportion like.
633 01:06:22.210 ⇒ 01:06:26.540 Uttam Kumaran: I don’t remember. I don’t know off the top of my head what the proportions are.
634 01:06:27.142 ⇒ 01:06:31.690 Uttam Kumaran: But I’ll make sure that you’re in metabase, and you can go poke around.
635 01:06:32.070 ⇒ 01:06:33.190 Bo Yoon: Okay.
636 01:06:33.400 ⇒ 01:06:34.230 Uttam Kumaran: Yeah.
637 01:06:34.230 ⇒ 01:06:45.590 Bo Yoon: I’m I mean one suggestion that I have. Probably I don’t know if you have done this already. But do we have like a dashboard, showing the the reason of the returns for Amazon.
638 01:06:47.550 ⇒ 01:06:50.320 Uttam Kumaran: No, I don’t think so at all like
639 01:06:50.440 ⇒ 01:06:54.639 Uttam Kumaran: let me show you what our Amazon dashboard looks like now.
640 01:06:54.860 ⇒ 01:06:55.990 Bo Yoon: Okay.
641 01:06:57.570 ⇒ 01:06:58.340 Uttam Kumaran: Yeah, cause I’m.
642 01:06:58.340 ⇒ 01:07:01.420 Bo Yoon: I was a I was an Amazon seller myself a few years ago.
643 01:07:01.420 ⇒ 01:07:01.820 Uttam Kumaran: Really.
644 01:07:01.820 ⇒ 01:07:03.380 Bo Yoon: And yeah, and
645 01:07:03.510 ⇒ 01:07:10.300 Bo Yoon: that that’s 1 of the main things that I was focusing like the reason of your return. Because
646 01:07:11.967 ⇒ 01:07:16.420 Bo Yoon: once your product gets
647 01:07:16.820 ⇒ 01:07:23.939 Bo Yoon: block or or gets taken down because of one of the reasons there it I mean, that’s 1 of the things that
648 01:07:24.740 ⇒ 01:07:28.220 Bo Yoon: a seller will have to get tracking of like.
649 01:07:28.540 ⇒ 01:07:33.099 Bo Yoon: It’s because some of the customer might be stating that.
650 01:07:33.460 ⇒ 01:07:39.523 Bo Yoon: for example, the product has been used. I mean, you you guys, that this this one of
651 01:07:40.030 ⇒ 01:07:47.100 Bo Yoon: very good reason for Amazon to take down the listing and.
652 01:07:47.100 ⇒ 01:07:47.700 Uttam Kumaran: Yeah.
653 01:07:48.740 ⇒ 01:07:55.199 Bo Yoon: Yes, I mean, that’s 1 of the examples that I think tracking. The reasons
654 01:07:55.410 ⇒ 01:07:59.389 Bo Yoon: of the returns will be a good thing that we can do.
655 01:07:59.930 ⇒ 01:08:03.510 Uttam Kumaran: Yeah, let me make sure that you you got your in here as well.
656 01:08:07.830 ⇒ 01:08:09.830 Uttam Kumaran: I’ll make sure that you’re here.
657 01:08:22.630 ⇒ 01:08:23.290 Bo Yoon: Okay.
658 01:08:35.740 ⇒ 01:08:39.627 Uttam Kumaran: Okay, yeah, I think,
659 01:08:40.220 ⇒ 01:08:51.809 Bo Yoon: I know we we’ve we’ve we’ve all been in meetings for a few hours, so maybe take a little bit of a break. But I think maybe. Well, I’ll hand you these 2 dashboards. You can take a look and think about like what the story could be.
660 01:08:51.960 ⇒ 01:08:52.770 Uttam Kumaran: And.
661 01:08:52.770 ⇒ 01:08:53.330 Bo Yoon: Okay.
662 01:08:53.330 ⇒ 01:09:01.249 Uttam Kumaran: I think I mean you like. I think you know a couple of the few improvements that we can make. I think they just don’t look great at all.
663 01:09:01.490 ⇒ 01:09:03.700 Uttam Kumaran: and like it’s really hard, like
664 01:09:04.399 ⇒ 01:09:20.129 Uttam Kumaran: we want to start to put the stuff like the second layer questions in front of them right like just looking at. Oh, our gross margin, 70% every day. They may want this. But this is a clearly example of customer doesn’t know what they want right? So you think of Steve Jobs? Nobody asked for the iphone.
665 01:09:20.340 ⇒ 01:09:27.070 Uttam Kumaran: He’s like, you want. You need the iphone right? But that’s what I want us to think, how do we solve their problem? We make sure there’s still a phone.
666 01:09:27.319 ⇒ 01:09:31.960 Uttam Kumaran: But like, how do we? I want to? Then say, I want, I want the the thing that shows the components
667 01:09:32.100 ⇒ 01:09:38.569 Uttam Kumaran: just like, Oh, yeah, I never thought to look of it as a components. Oh, then maybe I want to look at how the component percentages are changing
668 01:09:38.750 ⇒ 01:09:46.580 Uttam Kumaran: right? Like I. And then maybe I want to look at breakout of the component percentages by product at my Geo, so I want this to have everything around
669 01:09:46.720 ⇒ 01:09:51.790 Uttam Kumaran: the entire gross margin. And every a second layer question they’re gonna ask.
670 01:09:51.930 ⇒ 01:09:55.350 Uttam Kumaran: So I think there’s definitely room for this to improve and like, of course, like.
671 01:09:55.860 ⇒ 01:09:57.390 Uttam Kumaran: I think there’s just like.
672 01:09:57.640 ⇒ 01:10:03.309 Uttam Kumaran: where does the people’s eyes go? I think there’s still improvements. We could do an axes and rounding and stuff like that. So
673 01:10:03.420 ⇒ 01:10:08.330 Uttam Kumaran: that’s sort of what I’ll I’m hoping that we can at least crush through a couple of those today.
674 01:10:10.360 ⇒ 01:10:13.690 Bo Yoon: Okay, yeah. Fair. Let me let me take a look at this.
675 01:10:13.910 ⇒ 01:10:14.490 Uttam Kumaran: Okay.
676 01:10:16.010 ⇒ 01:10:16.920 Bo Yoon: As a.
677 01:10:18.160 ⇒ 01:10:18.720 Uttam Kumaran: Okay.
678 01:10:20.170 ⇒ 01:10:20.650 Bo Yoon: Okay?
679 01:10:20.650 ⇒ 01:10:22.716 Bo Yoon: So so focus on the
680 01:10:23.430 ⇒ 01:10:26.050 Bo Yoon: on the gross margin. Dashboard first, st right?
681 01:10:26.780 ⇒ 01:10:32.270 Uttam Kumaran: Yeah, I would say, both of those are priority. But the gross margin dash I wanted to close out today. The Amazon dash.
682 01:10:32.270 ⇒ 01:10:32.650 Bo Yoon: Gosh!
683 01:10:32.650 ⇒ 01:10:34.400 Uttam Kumaran: Is basically closed out.
684 01:10:34.540 ⇒ 01:10:38.020 Uttam Kumaran: I think throughout the week we’ll just continue to make improvements to that.
685 01:10:38.210 ⇒ 01:10:43.740 Uttam Kumaran: The next biggest priority. I have a couple of items on my plate. And then I hopefully, I I think, Kyle, by
686 01:10:44.280 ⇒ 01:10:48.339 Uttam Kumaran: sometime this week we can get some gorgeous data available in a mart.
687 01:10:48.470 ⇒ 01:10:53.549 Uttam Kumaran: and then probably, beau. I’ll probably hand over that dashboard work to you to just like again rip through
688 01:10:54.090 ⇒ 01:10:58.349 Uttam Kumaran: everything related to customer, and just put up a dashboard that that works.
689 01:10:59.990 ⇒ 01:11:02.239 Uttam Kumaran: And yeah, we’ll just kind of push through that this week.
690 01:11:03.160 ⇒ 01:11:04.660 Bo Yoon: Okay, okay, that’s good.
691 01:11:04.660 ⇒ 01:11:05.630 Caio Velasco: Okay.
692 01:11:06.040 ⇒ 01:11:08.480 Uttam Kumaran: Okay, thanks, guys, I know this is a hustle.
693 01:11:09.050 ⇒ 01:11:10.710 Uttam Kumaran: It is what it is.
694 01:11:11.201 ⇒ 01:11:20.249 Uttam Kumaran: There’s some fun and like trying to pick things up like this. But across the board, you know, we’re trying to get better. I think we’re making some strides in organization.
695 01:11:20.775 ⇒ 01:11:24.030 Uttam Kumaran: We’ll go through another round of road mapping next week
696 01:11:24.150 ⇒ 01:11:32.600 Uttam Kumaran: ideally. Try to do at least every 2 or 3 weeks. We’ll do one of these for every client. So I’m really happy. Thanks for staying focused on both of these. So appreciate it.
697 01:11:33.290 ⇒ 01:11:34.559 Caio Velasco: Thank you. I appreciate it.
698 01:11:34.560 ⇒ 01:11:39.020 Bo Yoon: That’s great. I’ll see you later today.
699 01:11:39.020 ⇒ 01:11:39.480 Caio Velasco: Bye, bye.