Meeting Title: Brainforge Data Standup - Group 2 Date: 2025-02-17 Meeting participants: Luke Daque, Nicolas Sucari, Uttam Kumaran, Caio
WEBVTT
1 00:00:39.520 ⇒ 00:00:40.490 Nicolas Sucari: Hey! Luke!
2 00:00:42.540 ⇒ 00:00:44.789 Luke Daque: Everyone hey, hey, guys.
3 00:00:48.800 ⇒ 00:00:51.850 Uttam Kumaran: Okay, cool.
4 00:00:54.320 ⇒ 00:00:57.360 Uttam Kumaran: So let’s talk about Javi first.st
5 00:00:58.092 ⇒ 00:01:05.549 Uttam Kumaran: I’m sort of getting the understanding around all the projects and sort of the key things we’re doing.
6 00:01:06.960 ⇒ 00:01:11.499 Uttam Kumaran: I guess, for me, I wanna 1st understand.
7 00:01:12.960 ⇒ 00:01:17.319 Uttam Kumaran: Is this still the priority for this week getting the 2 dashboards out?
8 00:01:18.680 ⇒ 00:01:24.120 Uttam Kumaran: I guess maybe we can start there and talk about any active tasks related to that, as like the highest priority thing.
9 00:01:26.130 ⇒ 00:01:49.390 Nicolas Sucari: Yes, I don’t know if Robert’s here. But yeah, we should close those 2 dashboards early this week, if not, yeah. Tomorrow. Wednesday. I met with a man earlier before. We go through, like all of the other stuff that we have moving forward. And there is a lot of stuff that we can start working, but we need to close the the Amazon. Dash at the net margin. Dashboard! Yep.
10 00:01:49.990 ⇒ 00:02:08.160 Nicolas Sucari: for the Amazon dash. I I think it’s already done. Robert, just need to confirm if that last fix that Jacob was working on is ready, and we can ship that. And for the net margin dashboard, I think. Jacob is still working on some update from the from the feedback.
11 00:02:09.570 ⇒ 00:02:13.220 Uttam Kumaran: Yeah. So what is the what is that? What are the actual like
12 00:02:14.680 ⇒ 00:02:17.779 Uttam Kumaran: updates for the feedback for the gross margin.
13 00:02:19.340 ⇒ 00:02:23.629 Nicolas Sucari: Okay. There was a thread in the slack channel. I can copy paste that into the airwave.
14 00:02:28.630 ⇒ 00:02:33.870 Nicolas Sucari: But yeah, there were like these messages. Do you want me? Okay, let me copy the link.
15 00:02:34.340 ⇒ 00:02:39.719 Uttam Kumaran: Or, yeah, I just want to talk. Yeah, I just want to know, what exactly are these things.
16 00:02:47.980 ⇒ 00:02:54.558 Nicolas Sucari: So we would need it to like implement breakdown for gross margin percent front revenue
17 00:02:54.970 ⇒ 00:02:56.999 Uttam Kumaran: Can you send me the link to? I’ll just bring it up.
18 00:02:57.290 ⇒ 00:02:58.650 Nicolas Sucari: Yeah, yeah, of course.
19 00:02:59.940 ⇒ 00:03:05.030 Nicolas Sucari: All of a sudden they didn’t 100 to you directly.
20 00:03:20.120 ⇒ 00:03:31.939 Nicolas Sucari: But the priorities are, we have those 2 dashboards? Then we have the address matching the recurring task there with them. I know if I ask you, been working on your script, your python script.
21 00:03:31.940 ⇒ 00:03:37.300 Uttam Kumaran: Let’s let’s just close this out. I just let’s just talk through this. Address, matching and stuff I’m okay with.
22 00:03:37.530 ⇒ 00:03:40.150 Uttam Kumaran: This is like, this is like our.
23 00:03:41.140 ⇒ 00:03:44.899 Uttam Kumaran: I wake up thinking about getting these 2 dashboards out one day, you know.
24 00:03:45.837 ⇒ 00:03:46.819 Uttam Kumaran: That’s my dream.
25 00:03:47.100 ⇒ 00:03:49.649 Uttam Kumaran: So I wanna find out how we can get this done.
26 00:03:49.910 ⇒ 00:03:57.060 Uttam Kumaran: So I want to talk very specifically about like, what actually, are these changes?
27 00:03:57.240 ⇒ 00:04:08.100 Uttam Kumaran: Because I built a lot of dashboards, too. And I want to know. Like, are we waiting 3 days to like change a color here, or like what that? What? What? What the F is actually like taking a lot of time.
28 00:04:08.240 ⇒ 00:04:10.709 Uttam Kumaran: So I’m gonna open. I wanna open up metabase
29 00:04:10.960 ⇒ 00:04:15.000 Uttam Kumaran: and kind of just like, see what? Like.
30 00:04:15.670 ⇒ 00:04:20.819 Uttam Kumaran: I kind of just want to walk through like what these changes are and like what’s.
31 00:04:21.730 ⇒ 00:04:23.729 Nicolas Sucari: Use Javi with double double B. Now.
32 00:04:23.890 ⇒ 00:04:25.230 Uttam Kumaran: Oh, sorry. Sorry. Okay.
33 00:04:39.850 ⇒ 00:04:46.459 Uttam Kumaran: So is it? This one, this one?
34 00:04:50.690 ⇒ 00:04:52.500 Uttam Kumaran: Oh, that’s 17 days ago.
35 00:04:59.220 ⇒ 00:05:00.670 Uttam Kumaran: is it? This dashboard.
36 00:05:01.170 ⇒ 00:05:07.409 Nicolas Sucari: Should be this one, I think. Yes? I asked. Maybe you can. You can. Yeah. Or I don’t know. Robert’s not here. Yeah.
37 00:05:07.410 ⇒ 00:05:09.920 Uttam Kumaran: Okay, okay, that’s fine. So refund percentage.
38 00:05:12.280 ⇒ 00:05:14.250 Uttam Kumaran: Okay, let’s just look through this thread.
39 00:05:18.160 ⇒ 00:05:19.320 Uttam Kumaran: Let’s fine.
40 00:05:21.330 ⇒ 00:05:23.330 Uttam Kumaran: Okay, so
41 00:05:39.900 ⇒ 00:05:43.730 Uttam Kumaran: this this is related to shipping. This is related to shipping.
42 00:05:56.930 ⇒ 00:06:00.310 Uttam Kumaran: This one is on ae team. We should figure this out.
43 00:06:05.750 ⇒ 00:06:10.610 Uttam Kumaran: Orders for tag and amplitude, using the logic of order contains one of those items order line we can.
44 00:06:11.380 ⇒ 00:06:14.989 Uttam Kumaran: Yeah, this is that would be okay.
45 00:06:31.950 ⇒ 00:06:35.980 Uttam Kumaran: Okay. And Jacob says he’s gonna work on gross margin. So
46 00:06:36.110 ⇒ 00:06:42.050 Uttam Kumaran: I’m just gonna I wanna find out. And I know Jacob’s not on here. I just wanna find out
47 00:06:42.560 ⇒ 00:06:47.179 Uttam Kumaran: what he what this means like. Which item is he working on? Because
48 00:06:47.670 ⇒ 00:06:51.260 Uttam Kumaran: I don’t know this. Still, seems like it’s open.
49 00:06:52.090 ⇒ 00:06:56.709 Uttam Kumaran: I sort of understood the shipping revenue problem.
50 00:06:56.970 ⇒ 00:07:03.390 Uttam Kumaran: but I also think that that’s like a little bit that’s like a little bit
51 00:07:04.080 ⇒ 00:07:07.389 Uttam Kumaran: to do. Still, so I need to figure that out.
52 00:07:07.720 ⇒ 00:07:15.090 Payas Parab (TikTok): Shipping revenue thing. I I told Jacob we had solved that already, like before, with like the d with Brian.
53 00:07:15.290 ⇒ 00:07:23.609 Payas Parab (TikTok): there’s like sort of like shipping. They charge for shipping. So sometimes it’s a revenue. But then from our cogs table we’re building out shipping, as like.
54 00:07:23.910 ⇒ 00:07:38.580 Payas Parab (TikTok): you know, like a cost. So I think these 2 aren’t actually related. You know what I’m saying like at the order level at the end, certain customers there’s charging them for shipping. And most of them they’re not so like, it’s actually a source of revenue when they do charge for it.
55 00:07:39.280 ⇒ 00:07:42.030 Payas Parab (TikTok): Does that make sense? So it’s it’s like just like a little
56 00:07:42.180 ⇒ 00:08:03.940 Payas Parab (TikTok): like. There’s nothing to solve there in terms of like like, it’s just use the shipping, discount prices, revenue and the cogs is like what it costs them on the back end. It’s just like a clarification. So I think that one’s fine. The only one that’s like Tricky is that like like I said Number 9, and like, maybe there’s a work stream there. But like who? Tom? One thing I’ll I’ll call out, there is that like we’ve tried to like, build out logic like that before.
57 00:08:04.311 ⇒ 00:08:11.550 Payas Parab (TikTok): It’s really hard, because they sort of have, like every one of their offers, is sort of like a rogue thing that like doesn’t quite make like. There’s no like
58 00:08:11.730 ⇒ 00:08:41.080 Payas Parab (TikTok): systemic way. That’s why, with amplitude, they were feeling like they had a lot of errors where they’re like. Sometimes they include like 2 quantity of this, one quantity of that, and they call it like a buy. 2, get one free, but it’s like, not quantity 3. It’s really like 2 and one of their smaller ones. If that makes sense like, there’s sort of like that analysis in my mind has to be done at the order line level. We can, like sort of tag, make some clever tags of like this, has this many bottles, or whatever, but, like every offer, is sort of like its own rogue thing, which kind of makes it a little more challenging.
59 00:08:41.309 ⇒ 00:08:43.280 Payas Parab (TikTok): So I have an order, level tag.
60 00:08:43.289 ⇒ 00:08:47.599 Uttam Kumaran: And is that that’s related to like this graph in particular.
61 00:08:48.481 ⇒ 00:08:50.390 Payas Parab (TikTok): Can I see which one.
62 00:08:50.400 ⇒ 00:08:57.370 Uttam Kumaran: Product category cause I don’t, or is that by order in general.
63 00:08:58.250 ⇒ 00:09:04.130 Payas Parab (TikTok): That that’s like one category they have in amplitude, like they have like quantity, like bottle quantity.
64 00:09:05.740 ⇒ 00:09:19.989 Payas Parab (TikTok): But it’s like not right, because, like bottle. Quantity itself like isn’t. Sometimes it’s like like I said. There’s like a weird combinations of it. So that would be an additional view. But this category roughly looks right to me in terms of like byproduct category.
65 00:09:21.370 ⇒ 00:09:29.910 Uttam Kumaran: Okay, I guess, like, there’s there’s a couple of things happening. One. Yeah, there’s gonna be a problem where orders have multiple items in them. I don’t see why we can’t
66 00:09:30.580 ⇒ 00:09:35.899 Uttam Kumaran: ladder up the order items cogs into like, what is the cogs for? The order? Right.
67 00:09:36.440 ⇒ 00:09:38.399 Payas Parab (TikTok): Yeah, that’s and that’s what we’re doing. Yeah, yeah.
68 00:09:38.400 ⇒ 00:09:40.350 Uttam Kumaran: Okay. So that’s what we’re doing.
69 00:09:40.580 ⇒ 00:09:46.070 Uttam Kumaran: And then I guess the what
70 00:09:47.400 ⇒ 00:09:50.389 Uttam Kumaran: you’re saying that what they did in amplitude.
71 00:09:50.540 ⇒ 00:09:51.730 Uttam Kumaran: Yeah, I guess, like.
72 00:09:52.410 ⇒ 00:09:58.094 Uttam Kumaran: I can pull up the amplitude thing, but but like give it to me like a little bit. Can you say one more time, just in a different way?
73 00:09:58.290 ⇒ 00:09:59.550 Payas Parab (TikTok): Yes, yes, sorry.
74 00:10:00.210 ⇒ 00:10:01.210 Payas Parab (TikTok): So
75 00:10:01.520 ⇒ 00:10:09.119 Payas Parab (TikTok): like the business question that Justin’s thinking about right is like, what is our profitability by product and like
76 00:10:09.440 ⇒ 00:10:36.670 Payas Parab (TikTok): by. Let’s say, if we put make up like a bundle of like 2 bottles versus one bottle, right? Like one of those things will be more profitable than the other. That’s what they’re trying to get to the bottom of. And like in the example of like by category. It’s like the protein coffee is new right. So they have a shit ton of offers. And it seems that it’s cogs is a little higher. So they’re trying to figure out like, is this a profitable thing we’re doing? Are we doing this currently profitably right with all this like offer? So they’re just trying to see, like
77 00:10:38.010 ⇒ 00:10:49.569 Payas Parab (TikTok): or like how how they’re structuring these things right where they have like. Hey? If you buy 2 concentrates, we’ll give you one protein free, right? And like. Is that a profitable thing. I don’t know right? That’s kind of what’s on his mind.
78 00:10:49.870 ⇒ 00:11:05.980 Uttam Kumaran: Okay. So then, there has to be something that’s like more like a product combination related profitability, which is like what what we could do is basically show you like for a given order what products are in the order? Right? I can make sure there’s an array there and then.
79 00:11:05.980 ⇒ 00:11:06.510 Payas Parab (TikTok): Sure.
80 00:11:06.510 ⇒ 00:11:11.539 Uttam Kumaran: But you can look at like products with one order versus products, with 2 orders products. With these combos.
81 00:11:11.540 ⇒ 00:11:12.550 Payas Parab (TikTok): Sure, sure.
82 00:11:12.840 ⇒ 00:11:28.069 Uttam Kumaran: Alright, and then I mean, of course, like I don’t know how the discounts you you mentioned it. It’s like some discounts like, buy one get one. Some discounts are probably flat rates, but, like that may be the best way to handle this where you can look at combination of products, and then the profitability associated with those orders.
83 00:11:28.070 ⇒ 00:11:37.640 Payas Parab (TikTok): Sure. Sure, I think I think my only issue with that is like creating rules, for that is like versus like, what is the product like that is top of mind for you, right and like, let’s look at the product
84 00:11:37.760 ⇒ 00:11:42.800 Payas Parab (TikTok): at the order line level. We can tell the profitability per product. For the most part.
85 00:11:44.710 ⇒ 00:11:55.030 Payas Parab (TikTok): it’s like that. That alone is like good enough in my mind, right like it’s just like, Here’s this product. Here’s your protein coffee. Here’s all the orders it’s in. Here’s all the cogs and the pack out cost for it.
86 00:11:55.370 ⇒ 00:11:58.060 Payas Parab (TikTok): And like this is how profitable that unit is for you.
87 00:11:58.460 ⇒ 00:12:02.080 Uttam Kumaran: Yeah, I mean, I agree. If they don’t know that, then that should be the 1st thing.
88 00:12:03.000 ⇒ 00:12:05.260 Payas Parab (TikTok): I think they don’t know that. Right? I think, like.
89 00:12:05.370 ⇒ 00:12:13.230 Payas Parab (TikTok): yeah, I think I think that. And that’s part of like when we’re trying to do it at the order level. We’re gonna get into these like weird situations where it’s like
90 00:12:13.960 ⇒ 00:12:21.550 Payas Parab (TikTok): like you said, like, there’s multiple of different categories in an order. Right? What do we tag that as right? What do we tag like? Situations where it’s like
91 00:12:21.720 ⇒ 00:12:25.730 Payas Parab (TikTok): 2 bottles and one freebie, 2 bottles and 2 freebies? Right?
92 00:12:25.870 ⇒ 00:12:26.930 Uttam Kumaran: Yeah.
93 00:12:27.170 ⇒ 00:12:41.110 Payas Parab (TikTok): It’s like creating order. Level tag is really, really challenging. And so I think there’s just an element of like. And maybe it’s just context that I didn’t give Jacob, which is on me like is like, maybe we just do some of that analysis at the order line level, then trying to boil it up to the order, level.
94 00:12:42.000 ⇒ 00:12:45.539 Uttam Kumaran: Okay, yeah, okay, okay, makes sense.
95 00:12:45.580 ⇒ 00:12:54.969 Payas Parab (TikTok): But that that like, by the way, like gutam, your question is fair, is like, what takes so long is like, well, we do that like product categorization. And then it’s like revenue looks like 5 x bigger than it should be right. And.
96 00:12:55.465 ⇒ 00:12:55.960 Uttam Kumaran: Yeah.
97 00:12:55.980 ⇒ 00:13:02.122 Payas Parab (TikTok): Why is that, you know? And they’re like, Okay, wait. We can’t tell them they have a hundred 1 million in revenue this month when they don’t right.
98 00:13:04.710 ⇒ 00:13:06.019 Uttam Kumaran: Yeah, yeah, it makes sense.
99 00:13:22.250 ⇒ 00:13:25.240 Uttam Kumaran: Okay, okay? Understood?
100 00:13:25.500 ⇒ 00:13:26.429 Uttam Kumaran: Cause I’m.
101 00:13:26.840 ⇒ 00:13:44.570 Payas Parab (TikTok): I. I think also, what makes sense is like if we can get these things to just make sense at the order level, and then we sort of do an order line level dashboard. You know what I’m saying like, where it’s like, Hey, we’re not gonna like, try and create these clever tags that like will not happen right like in amplitude. We saw. It doesn’t really work the way you want it to.
102 00:13:44.570 ⇒ 00:13:57.110 Payas Parab (TikTok): Let’s do the analysis at the order line level and come up with views that make sense. And I think, even like Justin, I don’t know about Jared, but Justin will understand what we’re saying here, and I think we can get some insight from him about like.
103 00:13:57.120 ⇒ 00:14:02.330 Payas Parab (TikTok): what is the question you have in mind? Right? It’s like, is it prop protein. Coffee is not profitable, is it that.
104 00:14:02.370 ⇒ 00:14:10.130 Payas Parab (TikTok): like, I think there’s almost like we flip this overall gross margin, because in general we’re like pretty close to tying everything out right?
105 00:14:10.420 ⇒ 00:14:25.239 Payas Parab (TikTok): And then it’s like, sort of like, okay, at the product level. What type of an analytics we can now provide you, now that we have this granular order line data. Not just what amplitude gave us. I think it’s like, it’s like a second dashboard. Does that make sense where we don’t want to like spin our wheels too much on this order level.
106 00:14:25.240 ⇒ 00:14:31.120 Uttam Kumaran: No, this is what this is the same problem we did with pool parts dude. So it’s just basically you have to get it into people’s heads that like, there’s
107 00:14:31.220 ⇒ 00:14:36.199 Uttam Kumaran: order level discounts. There’s order item, level discounts. We just need to like separate these things.
108 00:14:36.602 ⇒ 00:14:57.470 Uttam Kumaran: Like most data teams, they will succumb to the requirements of the org. But then you you will end up with like random duplication issues. We’ll have to deal with these other things. We should start with the core fundamentals. Can they understand product level profitability like, without any like order, level characteristics, and then sort of move up from there.
109 00:14:57.500 ⇒ 00:15:07.060 Uttam Kumaran: So I think that’s pretty clear. So then I’m gonna just see how I can get this all pushed today. And then sort of catch up with Jacob on like, what else is necessary there.
110 00:15:08.850 ⇒ 00:15:09.916 Uttam Kumaran: Okay, amazing.
111 00:15:10.870 ⇒ 00:15:15.620 Uttam Kumaran: So then talk to me about we have those 2 dashboards. I feel good about
112 00:15:16.238 ⇒ 00:15:21.229 Uttam Kumaran: these ones we’re still working with with them on
113 00:15:24.300 ⇒ 00:15:27.108 Uttam Kumaran: same with the Tiktok Api
114 00:15:27.840 ⇒ 00:15:28.430 Nicolas Sucari: Yeah.
115 00:15:28.430 ⇒ 00:15:36.000 Nicolas Sucari: for the for the Tiktok Api. Should we ask a man for the credentials and start looking into that tool that away proposed.
116 00:15:36.912 ⇒ 00:15:40.910 Uttam Kumaran: I have to look at this and give a sort of sense of what we’re gonna do here.
117 00:15:41.090 ⇒ 00:15:41.880 Uttam Kumaran: Not sure.
118 00:15:41.880 ⇒ 00:15:43.160 Nicolas Sucari: If you go to the bottom
119 00:15:43.380 ⇒ 00:15:49.140 Nicolas Sucari: you’ll see. Yeah, the recommendation that’s winter. AI.
120 00:15:49.850 ⇒ 00:15:55.440 Uttam Kumaran: Yeah, yeah, yeah. I’ll have an answer on what we’re gonna do for this.
121 00:15:57.180 ⇒ 00:15:57.950 Nicolas Sucari: Okay.
122 00:15:58.090 ⇒ 00:16:21.929 Nicolas Sucari: then we have another task on the Etl stuff that is missing data from macros in gorgeous data. That was from before that once. The 1st time we use portable to bring in gorgeous data. We were missing micro data, but I think with like the latest sync from them that’s already fixed. But we need to check that. I asked the wish to. Yeah, take a look at the data and see if we have all of the macros there. Okay.
123 00:16:22.550 ⇒ 00:16:23.280 Nicolas Sucari: right?
124 00:16:24.360 ⇒ 00:16:26.565 Uttam Kumaran: This I get like, I
125 00:16:27.480 ⇒ 00:16:31.079 Uttam Kumaran: this is totally fine. this is. I feel like we just
126 00:16:31.880 ⇒ 00:16:35.330 Uttam Kumaran: oh, we’re just gonna get Css. From them and spit this out. So that’s okay.
127 00:16:36.210 ⇒ 00:16:42.630 Nicolas Sucari: Yeah. But there is another task for the recurrent script. If you go to, I don’t know why it’s not there. Okay, yeah. Maybe in the backlog.
128 00:16:45.601 ⇒ 00:16:54.399 Nicolas Sucari: They. Yeah, that one exactly. That’s the one I created for this the Geo matching. I don’t know if if it was something different.
129 00:16:56.200 ⇒ 00:16:58.280 Payas Parab (TikTok): The recurring one is the geomatching.
130 00:16:58.530 ⇒ 00:17:03.100 Nicolas Sucari: Oh, okay, okay, we can. We? Okay, maybe we can.
131 00:17:03.100 ⇒ 00:17:29.199 Payas Parab (TikTok): Today’s today’s black. Today’s run. I ran it. It seems there’s some sort of error I can actually send a note to them being like, Hey, we’re trying to like rerun it again. There’s just some sort of error. I think it’s just like the address that we have in Snowflake is not the same format as what they sent, because they get it from a different source. So I think I just have to like tweak the code, rerun it because I got 0 matches. So I’m going to do that. That’s gonna be my top priority this morning. So we and I’ll send them a note that just says like, Hey, today’s
132 00:17:29.607 ⇒ 00:17:42.040 Payas Parab (TikTok): but once that’s once I fix it hopefully, we can just pull the data from Snowflake and just run it easily in a single slide. Single line like Tom recommended, like Python dot whatever Csv. New load. Csv.
133 00:17:44.740 ⇒ 00:18:04.559 Nicolas Sucari: Once, once you know that by us, maybe. Can you estimate like how long it’s gonna take? Every time we need to rerun it? It should be like Super, quick or like. How many hours will take for for us to do that? Because Aman is asking, like every task that we have like to have estimate some amount of hours, and once, like a detail report, and what we’re doing.
134 00:18:05.320 ⇒ 00:18:06.719 Payas Parab (TikTok): Sure. Yeah, I I like
135 00:18:07.400 ⇒ 00:18:16.409 Payas Parab (TikTok): my only fear on that is like this, this task like, if I build it like or what I have right? It’s like it can work in theory. As long as the format of the data doesn’t change like.
136 00:18:16.880 ⇒ 00:18:17.350 Nicolas Sucari: Like.
137 00:18:17.350 ⇒ 00:18:28.189 Payas Parab (TikTok): Hopefully, it won’t in the future. But it did even like this time around, does that make sense like? So I worry. It’s 1 of those things will be like, it’s a quick thing for us. But then, if something’s wrong, they’re not. Gonna and we’re gonna have to like
138 00:18:28.350 ⇒ 00:18:47.219 Payas Parab (TikTok): tweak it because data format change, for whatever reason from them like I don’t know. Like I, it should be. It should be like a python. Run this right that in theory. That’s what that’s what we’re working towards, Nico. But I just want to like Caveat that with like, however, you want to communicate. That is like that sounds good in theory, but like in reality, it’s like.
139 00:18:47.220 ⇒ 00:18:47.690 Nicolas Sucari: Okay.
140 00:18:47.830 ⇒ 00:18:48.490 Payas Parab (TikTok): Yeah, we are.
141 00:18:48.490 ⇒ 00:18:59.240 Uttam Kumaran: Can you? Can you run? Can you run whatever you need to do to run it today? Just figure it out. But then send me all of that python stuff, or or push the latest.
142 00:18:59.500 ⇒ 00:19:05.730 Uttam Kumaran: I’m gonna put this in a place where? Yeah, it’s it’s easier for honestly, Nico, I’ll show you how to run this, and you can probably run it.
143 00:19:05.730 ⇒ 00:19:06.360 Nicolas Sucari: Okay.
144 00:19:07.420 ⇒ 00:19:09.899 Uttam Kumaran: Can I close these 2, these 2 spikes.
145 00:19:10.630 ⇒ 00:19:14.176 Nicolas Sucari: Yeah, I think we can close that. We I already talked about that with
146 00:19:14.660 ⇒ 00:19:33.579 Nicolas Sucari: with a man he gave me some some amplitude dashboards that we can start like moving into Meta base but first, st before doing that, he wants the estimation of how long that will take and see if he approves. So if you if you’re in the let me see if you’re in Javi coffee page, yeah.
147 00:19:33.800 ⇒ 00:19:49.009 Nicolas Sucari: we created like this new process with the man today, like we discussed that every time we need one of these new projects start, he wants us to estimate before, and then move that into like an approved status, so that we can start working on okay.
148 00:19:52.200 ⇒ 00:19:54.469 Uttam Kumaran: And then so beyond these.
149 00:19:55.300 ⇒ 00:20:00.889 Uttam Kumaran: all of these are gonna basically be done. I mean, some of them this week. What’s next? Past
150 00:20:01.050 ⇒ 00:20:04.299 Uttam Kumaran: the 2 dashboards. So you mentioned that some of the new dashboards?
151 00:20:04.300 ⇒ 00:20:08.640 Uttam Kumaran: Yeah, can you? Can you click into the client view page.
152 00:20:08.900 ⇒ 00:20:09.610 Nicolas Sucari: Yeah.
153 00:20:09.830 ⇒ 00:20:15.659 Nicolas Sucari: yeah. If you go to on the top autumn, you scroll up a little bit. You have the client view. Javi Coffee page. There.
154 00:20:15.850 ⇒ 00:20:24.230 Nicolas Sucari: exactly. There, you scroll down a little bit where it says, where the table that our estimates so all of the ones that are pending there, you see.
155 00:20:24.774 ⇒ 00:20:49.229 Nicolas Sucari: he wants all of that to, and like us to estimate how many hours we’re gonna take. And he’s gonna be approving so that we can start doing that. We have the Okendo and North beam metrics there, dashboards at the bottom that those are the 2 dashboards that he sent from amplitudes that we can start moving into metabase and we added, like other stuff there, so that he knows everything that we are doing. And we need to estimate all of that. Okay.
156 00:20:50.890 ⇒ 00:20:51.580 Uttam Kumaran: Okay.
157 00:20:52.650 ⇒ 00:21:10.600 Nicolas Sucari: So this should be like our roadmap for the next few weeks. If we are getting any other requests from Jared or Justin pay us. Please let me know, or anyone else. If you’re getting any other request, let me know, so that we can add here, and the man is aware of everything that we have for them. Okay.
158 00:21:15.930 ⇒ 00:21:17.480 Uttam Kumaran: Makes sense, great.
159 00:21:17.900 ⇒ 00:21:42.719 Nicolas Sucari: Yeah, he wants to know, like exactly this, like, how many hours are we estimating for each of the tasks? And then what are the actual hours spending on all of these tasks. Every project will be added here. Then, if we need to create like 10 tasks to, I don’t know to move the Uk and the dashboard from amplitude to Meta Base. We can do that in our in our board, and we can tag them with the tags that that I created there. And then we can discuss if that’s a better way to to do it. But he saw that, and he liked that. Okay.
160 00:21:47.630 ⇒ 00:21:48.983 Uttam Kumaran: Okay, great.
161 00:21:52.370 ⇒ 00:21:58.689 Uttam Kumaran: the last client? That’s on. Is there anything else on Javi side? So I think I want to start to
162 00:21:58.840 ⇒ 00:22:04.639 Uttam Kumaran: get through the couple of things for the next 3 days. And then I want to build out the next 2 weeks of roadmap. Basically.
163 00:22:04.850 ⇒ 00:22:07.450 Uttam Kumaran: So is there anything else on the Javi side.
164 00:22:10.390 ⇒ 00:22:22.989 Nicolas Sucari: I don’t think so. We moved. Yeah, we moved the portable account into the scale plan. That’s fine. We moved the metabase environment away from Payas personal account to them. So that’s okay.
165 00:22:23.574 ⇒ 00:22:27.840 Nicolas Sucari: We just need to get north theme. And yeah. And then Tiktok, I think.
166 00:22:28.370 ⇒ 00:22:32.849 Uttam Kumaran: Okay. So I think, last client, we started with urban stems today.
167 00:22:33.245 ⇒ 00:23:01.200 Uttam Kumaran: There is no work right now. I’m basically sort of getting the download from their team. I may decide on having one person sort of come with me on as I like. Spend kind of the next 4 weeks sort of dissecting the. They’re like analytics strategy, basically. I’ll probably make a decision. I think maybe I may include you to come with me on on everything and sort of help to build out. We have a month with them where we’re basically gonna propose.
168 00:23:01.300 ⇒ 00:23:04.450 Uttam Kumaran: like a 3 to 6 month roadmap on analytics as a whole.
169 00:23:05.760 ⇒ 00:23:10.620 Uttam Kumaran: but I just kicked off today. So I’m starting to get a sense of like what they may need.
170 00:23:11.598 ⇒ 00:23:14.410 Uttam Kumaran: But I think that’s probably it
171 00:23:14.980 ⇒ 00:23:17.059 Uttam Kumaran: otherwise. So I’m gonna follow up.
172 00:23:17.180 ⇒ 00:23:22.540 Uttam Kumaran: I’m gonna try to get on the phone with Jacob or something today and see how I can help move gross margin.
173 00:23:22.830 ⇒ 00:23:27.759 Uttam Kumaran: I’m gonna ping and let’s try to get Robert to approve the Amazon and call that done.
174 00:23:28.250 ⇒ 00:23:33.778 Uttam Kumaran: And then we have a couple of things to move forward on also building out the data model for
175 00:23:34.710 ⇒ 00:23:51.339 Uttam Kumaran: for for jobbing, too. So I think, Nico, I may start to loop in Kyle on some of these activities sort of deciding between this and and Eden. But I’ll sort of make a decision today, I think, for the Ae. Team for me, Kyle wish and, Luke, I think we’ll
176 00:23:51.540 ⇒ 00:23:54.329 Uttam Kumaran: we’ll talk later today as well.
177 00:23:54.729 ⇒ 00:24:02.549 Uttam Kumaran: I think the last thing I want to talk about was for Stack Blitz. I guess, Luke, any updates there on like what we want to get done
178 00:24:02.750 ⇒ 00:24:03.680 Uttam Kumaran: today.
179 00:24:03.890 ⇒ 00:24:06.529 Uttam Kumaran: I know we’re we’re meeting with him on Wednesday.
180 00:24:06.930 ⇒ 00:24:08.347 Luke Daque: Yeah, just the
181 00:24:09.500 ⇒ 00:24:11.020 Luke Daque: Those metrics
182 00:24:11.290 ⇒ 00:24:17.289 Luke Daque: a mapping. 1st of all, I created the the ticket for the mapping the the sources to
183 00:24:17.730 ⇒ 00:24:20.840 Luke Daque: each of the metrics that we we wanted.
184 00:24:21.030 ⇒ 00:24:23.500 Luke Daque: We were looking at and then create the basic
185 00:24:24.741 ⇒ 00:24:27.049 Luke Daque: like data model for those.
186 00:24:29.900 ⇒ 00:24:34.130 Luke Daque: Yeah, that’s like the highest priority for me before Wednesday.
187 00:24:35.060 ⇒ 00:24:43.530 Luke Daque: for the things that, like the the initial users and subscriptions data model that we created should we
188 00:24:43.660 ⇒ 00:24:49.549 Luke Daque: close that out and maybe just create another one once, which gives us more context, yeah, cool
189 00:24:50.320 ⇒ 00:24:55.200 Luke Daque: sounds good. Then I’ll close those ones. Since we already merged the Prs for those
190 00:24:56.630 ⇒ 00:25:01.430 Uttam Kumaran: It’d be great to have before our Wednesday meeting.
191 00:25:02.030 ⇒ 00:25:02.740 Luke Daque: Which one?
192 00:25:02.970 ⇒ 00:25:07.270 Luke Daque: Oh, yeah, yeah, yeah, that one. That’s what I’m working on at the moment.
193 00:25:08.180 ⇒ 00:25:19.989 Luke Daque: And yeah, I didn’t really start the architecture for stack bits yet, because we weren’t like all the sources weren’t complete. But maybe I can start working on that one as well. Once after this.
194 00:25:20.290 ⇒ 00:25:20.840 Luke Daque: Okay.
195 00:25:20.840 ⇒ 00:25:24.900 Uttam Kumaran: Yeah, we can do this one by Friday. Now that we have everything that would be great.
196 00:25:25.640 ⇒ 00:25:30.520 Luke Daque: Yeah, so yeah, that’s basically it for staff. Let’s
197 00:25:31.130 ⇒ 00:25:33.690 Luke Daque: hopefully, we don’t run into any issues. But yeah.
198 00:25:35.200 ⇒ 00:25:35.780 Uttam Kumaran: Okay.
199 00:25:35.980 ⇒ 00:25:40.648 Uttam Kumaran: Okay. Great, I think. Between the a squad, I’ll also probably grab time. And just
200 00:25:41.290 ⇒ 00:25:43.829 Uttam Kumaran: an hour or 2 here. And we can all
201 00:25:44.010 ⇒ 00:25:47.719 Uttam Kumaran: we can all talk about sort of data modeling activities across the board.
202 00:25:49.950 ⇒ 00:25:50.870 Uttam Kumaran: But cool.
203 00:25:52.940 ⇒ 00:25:59.850 Uttam Kumaran: yeah, I guess. Slack me if you need anything but let’s try to get the joby stuff. I’m really gonna try to push the next 2 days to get as much out as possible, so.
204 00:26:01.000 ⇒ 00:26:03.360 Nicolas Sucari: Perfect. Yeah, okay.
205 00:26:03.360 ⇒ 00:26:06.310 Uttam Kumaran: Okay, thanks guys.
206 00:26:06.820 ⇒ 00:26:08.479 Nicolas Sucari: Well, thanks. Thanks.
207 00:26:08.870 ⇒ 00:26:09.650 Caio: You. Bye-bye.