Meeting Title: [Javvy] Daily Standup Date: 2025-04-10 Meeting participants: Annie Yu, Robert Tseng, Awaish Kumar, Caio Velasco
WEBVTT
1 00:00:09.030 ⇒ 00:00:10.510 Annie Yu: Morning, Robert.
2 00:00:26.840 ⇒ 00:00:28.250 Annie Yu: Hello. Kyle.
3 00:00:28.530 ⇒ 00:00:29.680 Caio Velasco: Hello, Wendy!
4 00:00:29.820 ⇒ 00:00:30.930 Caio Velasco: I’ll remember.
5 00:01:39.830 ⇒ 00:01:43.519 Robert Tseng: Alright. No cost today. So we’ll just jump into it.
6 00:01:52.280 ⇒ 00:01:53.345 Robert Tseng: Okay,
7 00:01:59.560 ⇒ 00:02:02.320 Robert Tseng: So I mean, I guess one thing I’ll say is like.
8 00:02:02.900 ⇒ 00:02:12.140 Robert Tseng: yeah, I think because it’s hard for us to kind of schedule time to meet. I mean, I want this stand up to be less of just about like
9 00:02:12.450 ⇒ 00:02:19.060 Robert Tseng: giving status updates because you could do that over slack. And I want to do some more problem solving on these calls. So
10 00:02:19.290 ⇒ 00:02:20.620 Robert Tseng: yeah, I think like.
11 00:02:21.150 ⇒ 00:02:40.236 Robert Tseng: we’re as I filter for things like I’m not gonna be asking to go over every all, everything in the list, like I I think when we go one by one we’ll just whatever whatever you’re blocked by. Let’s talk about that first, st and we’ll try to problem. Solve on the call. If we can’t, then then we’ll try not to take it offline. But
12 00:02:40.800 ⇒ 00:02:43.139 Robert Tseng: yeah, I think that’s like something that
13 00:02:43.260 ⇒ 00:02:53.570 Robert Tseng: I would like to see more of from these standups. Yeah, this feedback there.
14 00:02:54.218 ⇒ 00:02:59.299 Robert Tseng: So okay, I think with that in mind, like, I’ll just model, I’ll go off myself. So
15 00:03:00.920 ⇒ 00:03:04.019 Robert Tseng: yeah, I think. There’s a
16 00:03:05.130 ⇒ 00:03:13.348 Robert Tseng: Vlad. Is asking about how to do something. We more or less have, like what he’s asked for there. But
17 00:03:14.110 ⇒ 00:03:15.969 Robert Tseng: yeah, I guess like the
18 00:03:16.650 ⇒ 00:03:25.629 Robert Tseng: the sales tab in the gross margin dashboard any had built doesn’t exactly answer that question. So I’ve been doing some modifications here.
19 00:03:26.560 ⇒ 00:03:35.179 Robert Tseng: yeah, I think he just wants to see gross sales, and that sales in the same the same view. He doesn’t know how to do it. So yeah, I’m like having to
20 00:03:36.790 ⇒ 00:03:42.900 Robert Tseng: build out in Meta Base. But I think this is becoming a recurring request, and I think
21 00:03:43.480 ⇒ 00:03:51.812 Robert Tseng: I haven’t wanted our team to go and spend modeling time to go and and and fill it. But maybe I’m gonna start tickets to do that. So
22 00:03:52.330 ⇒ 00:03:57.290 Robert Tseng: yeah, I think that’s kind of the main thing that I needed to respond to urgently.
23 00:03:59.960 ⇒ 00:04:10.849 Robert Tseng: Other than that I think we’re. I’m still blocked on the things that I that I wanted to do, and we haven’t pulled anything new into cycle. So I feel like that’s pretty much it. From me.
24 00:04:12.343 ⇒ 00:04:20.419 Robert Tseng: Okay. So I’ll just jump to Annie. You. Wanna let’s what’s kind of yeah, what’s going on on your side.
25 00:04:21.571 ⇒ 00:04:25.239 Annie Yu: Yeah. So for the amplitude dash.
26 00:04:26.859 ⇒ 00:04:27.699 Annie Yu: I was
27 00:04:27.849 ⇒ 00:04:35.209 Annie Yu: able to build that views. I think we talked about this yesterday. The numbers are not aligned with the
28 00:04:36.116 ⇒ 00:04:43.769 Annie Yu: they’re amp up to dash. But I think Akash said, That’s okay. And I think he tagged you. I’m not sure if we should
29 00:04:44.409 ⇒ 00:04:46.819 Annie Yu: shared this out yet.
30 00:04:47.950 ⇒ 00:04:50.050 Robert Tseng: Yeah, let’s pull it up. Yeah.
31 00:04:50.940 ⇒ 00:04:52.809 Robert Tseng: is there a link? Okay, there you go.
32 00:04:58.720 ⇒ 00:05:00.239 Robert Tseng: Well, this is the amplitude.
33 00:05:00.400 ⇒ 00:05:01.030 Annie Yu: Oh, yeah.
34 00:05:09.711 ⇒ 00:05:15.019 Robert Tseng: yeah. Can you tell? Could could you tell me like what? What exactly is different here.
35 00:05:16.955 ⇒ 00:05:20.129 Annie Yu: So as a note there.
36 00:05:22.340 ⇒ 00:05:34.350 Annie Yu: So for both concentrate and protein, the numbers are different than the amplitude, but especially for concentrate the the data. Just look fairly low.
37 00:05:36.068 ⇒ 00:05:39.200 Annie Yu: So it’s that blue line on the left side.
38 00:05:39.200 ⇒ 00:05:39.840 Robert Tseng: Yep.
39 00:05:40.840 ⇒ 00:05:46.290 Annie Yu: Yeah. And for that one I just, I can’t put a finger on like what’s
40 00:05:46.980 ⇒ 00:05:50.129 Annie Yu: going on, or if that’s expected.
41 00:05:55.120 ⇒ 00:06:01.669 Robert Tseng: So we need subscriber tech. Are these the same chart that they’re looking at? What is the difference between this.
42 00:06:02.210 ⇒ 00:06:09.909 Annie Yu: One is for weekly. One is new subscriber, and one is new customer.
43 00:06:10.770 ⇒ 00:06:11.700 Robert Tseng: I see.
44 00:06:12.080 ⇒ 00:06:18.100 Annie Yu: And I think the the colors for their charts didn’t stay consistent. For some reason.
45 00:06:18.100 ⇒ 00:06:26.259 Robert Tseng: Yeah, it’s just like an ordering thing. Okay, so they have coffee and protein.
46 00:06:27.420 ⇒ 00:06:35.480 Robert Tseng: Yeah, I mean, their cac is pretty different. Yeah, I mean, I don’t believe that concentrate Cac is $0. So clearly something is off there.
47 00:06:41.510 ⇒ 00:06:42.870 Robert Tseng: let’s see.
48 00:06:43.200 ⇒ 00:06:48.406 Annie Yu: Yeah, I know. Yesterday Akash asked me to share what’s
49 00:06:49.820 ⇒ 00:06:54.040 Annie Yu: What’s done? And then what’s my
50 00:06:54.290 ⇒ 00:06:58.350 Annie Yu: concerns? So I did in the ticket, and I’m not sure
51 00:06:58.910 ⇒ 00:07:03.119 Annie Yu: the the next step, because I feel like he was saying.
52 00:07:04.290 ⇒ 00:07:11.350 Annie Yu: it’s ready, because the numbers won’t be aligned precisely. But.
53 00:07:12.820 ⇒ 00:07:14.010 Robert Tseng: Yeah. Well, I mean
54 00:07:14.250 ⇒ 00:07:24.460 Robert Tseng: to some extent like 50 versus 0 is probably not fine, like.
55 00:07:25.050 ⇒ 00:07:25.414 Robert Tseng: Oh!
56 00:07:25.780 ⇒ 00:07:32.068 Annie Yu: Yeah. And I think the setup here is pretty straightforward. So I I’m not sure what’s
57 00:07:34.590 ⇒ 00:07:37.920 Annie Yu: What’s there to be test on my on my end?
58 00:07:39.140 ⇒ 00:07:39.840 Robert Tseng: I’m glad.
59 00:07:51.070 ⇒ 00:08:05.440 Robert Tseng: Yeah, I mean, I think this is just like another investigation that you have to do with whoever built this model like something. Something’s off like there’s no way it’s $0 like. So we we can’t, we can’t ship it like this is Aman is immediately. Gonna look at that, and he’s gonna
60 00:08:06.000 ⇒ 00:08:07.879 Robert Tseng: it’s not. That’s not right.
61 00:08:07.880 ⇒ 00:08:08.670 Annie Yu: Yeah.
62 00:08:11.410 ⇒ 00:08:30.030 Robert Tseng: So I mean, if I were, if I were doing this like I would just go, and I’ll I would look at the models like. If I had questions I would ask the Aes. Whoever built it like I would try to figure out like what is causing. I mean, if if it’s 0, and it’s not undefined. I mean, maybe if I take off the coalesce here like.
63 00:08:31.550 ⇒ 00:08:36.229 Robert Tseng: I wonder if it would break, because that would mean that there’s not 0 values or something.
64 00:08:47.630 ⇒ 00:08:56.970 Robert Tseng: Nope didn’t break, so I guess whatever the numerator is for concentrate is 0 so total spend on
65 00:09:03.940 ⇒ 00:09:08.999 Robert Tseng: I guess I could just drill into these orders. See what is going on here.
66 00:09:12.180 ⇒ 00:09:15.390 Robert Tseng: Total spend order, count.
67 00:09:17.630 ⇒ 00:09:20.360 Robert Tseng: I mean, it doesn’t look like it should be 0.
68 00:09:22.610 ⇒ 00:09:23.140 Robert Tseng: Should.
69 00:09:23.400 ⇒ 00:09:25.320 Annie Yu: But the total spend is
70 00:09:30.450 ⇒ 00:09:32.899 Robert Tseng: Like 5, 50, over 5, 50.
71 00:09:34.360 ⇒ 00:09:41.299 Annie Yu: No, that’s the total spend is smaller than the order. Count right?
72 00:09:41.300 ⇒ 00:09:41.990 Robert Tseng: Yeah.
73 00:09:42.300 ⇒ 00:09:45.090 Robert Tseng: So that’s that seems weird. Yeah,
74 00:09:52.210 ⇒ 00:09:58.119 Robert Tseng: even if we do, new order counts, it’s Hi. So
75 00:10:19.490 ⇒ 00:10:24.117 Robert Tseng: I mean, I would kind of just look at this. What’s what’s it saying? The spend is
76 00:10:26.650 ⇒ 00:10:27.480 Annie Yu: Hmm.
77 00:10:31.090 ⇒ 00:10:32.909 Robert Tseng: Oh, that’s not what I wanted.
78 00:10:34.080 ⇒ 00:10:38.650 Robert Tseng: It’s very hard to get tabular data from this data table.
79 00:10:39.980 ⇒ 00:10:48.930 Robert Tseng: Internal north beam by total spend. And I wanted to group by.
80 00:10:51.020 ⇒ 00:10:55.620 Robert Tseng: okay, well, anyway, I think you could probably see what I’m trying to do. Like, I’m just trying to see.
81 00:10:55.730 ⇒ 00:11:10.520 Robert Tseng: Okay, well, if can we get a daily view of what the amplitude is saying? I mean, I I feel like this is too low, based on how I know how much they’re spending. They’re not spending $500 a week. There’s like no way. They must be spending more. So
82 00:11:10.800 ⇒ 00:11:19.944 Robert Tseng: is that an issue on our connector side we’re not able to get. Are we? Filtering ad spend incorrectly like I I think there’s some questions around that. But
83 00:11:20.450 ⇒ 00:11:25.269 Robert Tseng: I don’t know even just by looking at these numbers that are filtering through.
84 00:11:26.900 ⇒ 00:11:36.019 Robert Tseng: yeah, I’m seeing really big numbers here. So like, I don’t i i what is 207,000 like, really right? Like I don’t. I don’t know. I don’t.
85 00:11:36.590 ⇒ 00:11:38.698 Robert Tseng: I don’t think so. But
86 00:11:39.540 ⇒ 00:11:44.709 Robert Tseng: yeah, I’m I. I think it should be a wider range than just like in the 4 hundreds or 5 hundreds.
87 00:11:44.930 ⇒ 00:11:51.626 Robert Tseng: Yeah, I’m not. I’m not sure. Then we also have north beam as a source, so we can go and we can fill. I don’t think they do it by
88 00:11:53.030 ⇒ 00:12:01.760 Robert Tseng: by, by, by product, type. That’s kind of our own modeling. But I don’t know something. Something’s off there that we need to probably figure out.
89 00:12:07.920 ⇒ 00:12:13.630 Robert Tseng: Yeah, okay. So other than that, what was what was the other issue?
90 00:12:15.030 ⇒ 00:12:15.430 Robert Tseng: I love you.
91 00:12:15.430 ⇒ 00:12:16.050 Robert Tseng: Edit.
92 00:12:16.720 ⇒ 00:12:18.479 Annie Yu: Yeah, that’s it for that one.
93 00:12:19.806 ⇒ 00:12:25.640 Robert Tseng: Yeah, new customer, new kind of subscriber. I see, maybe spend.
94 00:12:26.210 ⇒ 00:12:27.279 Robert Tseng: It’s been no problem.
95 00:12:28.870 ⇒ 00:12:35.750 Robert Tseng: Yeah, like this is basically saying, like, 90% of your spend. 98% of your spend is protein.
96 00:12:35.750 ⇒ 00:12:36.710 Annie Yu: So.
97 00:12:36.710 ⇒ 00:12:37.500 Robert Tseng: I. Just
98 00:12:37.990 ⇒ 00:12:42.428 Robert Tseng: when we look at that, we just have to think about it like, does that make sense?
99 00:12:42.990 ⇒ 00:12:45.470 Robert Tseng: like? And we have to. We have to validate that.
100 00:12:53.550 ⇒ 00:12:59.599 Robert Tseng: Yeah. Also, I think this is this feels kind of misleading
101 00:13:00.910 ⇒ 00:13:05.750 Robert Tseng: this range $1 to 100 k like, and then
102 00:13:06.120 ⇒ 00:13:11.289 Robert Tseng: like a 10 K. Jump here, and then a hundred like a 90 K. Jump there like
103 00:13:14.040 ⇒ 00:13:20.139 Robert Tseng: I don’t know. Maybe you need to like impose it onto 2 separate axes or something, but like I feel like this, axis is kind of
104 00:13:20.530 ⇒ 00:13:21.850 Robert Tseng: confusing to me.
105 00:13:23.420 ⇒ 00:13:26.160 Robert Tseng: It makes it look like concentrate, is
106 00:13:26.900 ⇒ 00:13:32.479 Robert Tseng: close to protein or whatever. But is that true? I,
107 00:13:32.880 ⇒ 00:13:38.819 Robert Tseng: when I hover over the numbers it doesn’t look like it like a thousand, is nowhere near 40, 46,000.
108 00:13:39.830 ⇒ 00:13:48.869 Annie Yu: Yeah, I think that it automatically did like a power or a log on the scale. But I I believe I set on linear.
109 00:13:50.037 ⇒ 00:13:55.600 Annie Yu: So I’m not sure if that’s something I can fix if it’s done automatically.
110 00:14:00.030 ⇒ 00:14:12.349 Robert Tseng: Yeah, I mean, if that’s the case, you either just split it up into 2 charts or, like you, you put each each one on a different axis, so one will be on 100 k. 1 will go up to a thousand.
111 00:14:13.070 ⇒ 00:14:18.480 Robert Tseng: So you can still compare the shape. But like, yeah.
112 00:14:19.540 ⇒ 00:14:28.119 Robert Tseng: But anyway, the the underlying issue is the data quality here, like I don’t. I don’t. I don’t believe it concentrates a thousand is is kind of what I think here.
113 00:14:28.120 ⇒ 00:14:30.959 Annie Yu: Yeah, that’s my thought, too. So I brought it up.
114 00:14:32.100 ⇒ 00:14:37.830 Robert Tseng: Okay, so do you feel like you’re blocked, and you you don’t know how to do the investigation. You want me to do it, or like.
115 00:14:39.084 ⇒ 00:14:44.199 Annie Yu: I think this is something. I if I am too investigator, I will have to look at the
116 00:14:44.320 ⇒ 00:14:50.200 Annie Yu: probably the the query behind this, and that’s something I probably have to work with the wish.
117 00:14:51.270 ⇒ 00:14:58.979 Robert Tseng: Okay, yeah. Well, I think we should do that because we’re gonna we’re supposed to ship this out this week. So we should try to get to the bottom of that.
118 00:14:59.433 ⇒ 00:15:04.536 Robert Tseng: If you do get blocked like, just let me know, like I’ll end up doing the investigation. But
119 00:15:04.950 ⇒ 00:15:05.670 Robert Tseng: yeah.
120 00:15:07.540 ⇒ 00:15:08.890 Annie Yu: Yeah, sounds good.
121 00:15:08.890 ⇒ 00:15:09.550 Robert Tseng: Okay.
122 00:15:14.500 ⇒ 00:15:18.520 Robert Tseng: yeah. Sorry. I think, like, with these comments like I,
123 00:15:19.320 ⇒ 00:15:33.269 Robert Tseng: it doesn’t signal to me that there’s something like really wrong with it, like, I just see, you know, definitions, people asking me for like a quick look. So I mean, I feel like I only have capacity to review a few things per per day, and then
124 00:15:33.440 ⇒ 00:15:39.810 Robert Tseng: I guess I it didn’t. I did. This didn’t signal to me how like how off it was, so I think I just
125 00:15:39.810 ⇒ 00:15:43.560 Robert Tseng: I did include that concentrate is $1.
126 00:15:45.640 ⇒ 00:15:50.099 Annie Yu: I think that’s where it’s like showing. That’s off.
127 00:15:51.110 ⇒ 00:15:58.759 Robert Tseng: Yeah, I mean, sounds like you could probably put this in after standup. So by the time I go through, both of like the 3 standups for clients like I
128 00:15:59.220 ⇒ 00:16:17.370 Robert Tseng: I mean, this is just like for future when when you kind of come with tickets. If you could have the comments in earlier. So by stand up like, I have a sense of like what I need to prioritize. So like, I kind of just went and only solved the problems that I felt like were the most important based off of what I saw during stand up.
129 00:16:17.550 ⇒ 00:16:18.220 Annie Yu: Yep.
130 00:16:18.470 ⇒ 00:16:21.120 Robert Tseng: Yeah, okay, cool.
131 00:16:24.680 ⇒ 00:16:38.429 Robert Tseng: yeah. I mean, I I should be looking at these inboxes all the time. But I I just I’m not. So I think it just it’s just help more helpful for me if I can really get a sense of what I need to ask, what I need to focus on after after these standups.
132 00:16:39.360 ⇒ 00:16:43.299 Robert Tseng: Okay, yeah. Let’s let’s go to the contact link.
133 00:16:43.430 ⇒ 00:16:50.930 Annie Yu: Yeah, I I think a wish will give us an update on the tickets here. But
134 00:16:51.800 ⇒ 00:16:58.769 Annie Yu: there are 3 sub issues here, but really just one that needs to be prioritized. And I
135 00:16:59.030 ⇒ 00:17:03.870 Annie Yu: I think once that’s updated, I can move forward with this.
136 00:17:04.349 ⇒ 00:17:04.679 Robert Tseng: Okay.
137 00:17:05.031 ⇒ 00:17:07.140 Awaish Kumar: Are we talking about? Distinct customer?
138 00:17:07.310 ⇒ 00:17:08.060 Annie Yu: Yeah, yeah.
139 00:17:08.069 ⇒ 00:17:10.941 Awaish Kumar: Yeah, that I opened a pr yesterday, and
140 00:17:12.226 ⇒ 00:17:15.619 Awaish Kumar: it should be merged soon. It’s in review, and.
141 00:17:19.500 ⇒ 00:17:20.150 Robert Tseng: Okay.
142 00:17:20.900 ⇒ 00:17:21.939 Annie Yu: I got it.
143 00:17:24.359 ⇒ 00:17:26.009 Awaish Kumar: Basic. I can merge it here.
144 00:17:27.319 ⇒ 00:17:31.649 Robert Tseng: Yeah, I guess. Can can someone give me like a 1 sentence of like, what was the issue.
145 00:17:32.750 ⇒ 00:17:36.980 Annie Yu: So right now, the distinct customer is based on.
146 00:17:37.220 ⇒ 00:17:44.939 Annie Yu: I’m not 100% sure, but it’s not fixed on the cohort month where they place the 1st order.
147 00:17:45.100 ⇒ 00:17:47.239 Annie Yu: So we wanted to fix that
148 00:17:47.950 ⇒ 00:17:53.690 Annie Yu: to each cohort month and app source. So like the mock up table there.
149 00:17:53.970 ⇒ 00:18:00.550 Annie Yu: if it’s the same cohort month and same app source. The distant customers should stay the same.
150 00:18:03.790 ⇒ 00:18:13.301 Robert Tseng: Okay, yeah, I mean, I I understand. I just I don’t know what the change of which pushed. I don’t see a Pr here, so I can’t really like look at it, either.
151 00:18:14.200 ⇒ 00:18:15.120 Robert Tseng: so
152 00:18:15.630 ⇒ 00:18:26.110 Robert Tseng: I mean, I guess you guys are in Github a lot. But like, I, I kind of just use linear more. So if if you wish. Next time, if you push a Pr, can you just like add it to this comment,
153 00:18:27.120 ⇒ 00:18:27.880 Awaish Kumar: Yeah, sure.
154 00:18:27.880 ⇒ 00:18:38.570 Robert Tseng: Okay, thanks. I know there’s like stuff that comes up in in slack. We have the slack integration or whatever. But it’s so noisy in these channels like, I’m not looking at it all the time.
155 00:18:40.180 ⇒ 00:18:42.749 Robert Tseng: Okay, what? What else? Wish.
156 00:18:45.890 ⇒ 00:18:56.143 Awaish Kumar: Okay, so distant customer, this is kind of done and the other one was,
157 00:18:58.020 ⇒ 00:19:00.210 Awaish Kumar: yeah, I pushed the Pr for this one.
158 00:19:00.760 ⇒ 00:19:03.530 Robert Tseng: Yeah, yeah, I know, I’m just changing.
159 00:19:05.430 ⇒ 00:19:12.629 Awaish Kumar: And then there was, this is in progress. I haven’t really went into this
160 00:19:12.770 ⇒ 00:19:17.740 Awaish Kumar: because I was working on this subscribe and save thing.
161 00:19:18.130 ⇒ 00:19:18.830 Robert Tseng: Okay.
162 00:19:19.410 ⇒ 00:19:24.570 Awaish Kumar: If we can open that ticket. Yeah, I actually, I found data
163 00:19:24.710 ⇒ 00:19:29.600 Awaish Kumar: that we can actually get subscribe and save information for the orders.
164 00:19:32.090 ⇒ 00:19:32.490 Robert Tseng: Okay.
165 00:19:35.140 ⇒ 00:19:39.184 Awaish Kumar: So, yeah, so it was an investigation about
166 00:19:40.620 ⇒ 00:19:48.880 Awaish Kumar: Oh, about replacement, Api. But I commented that from replacement
167 00:19:49.020 ⇒ 00:20:09.470 Awaish Kumar: replacement. Api, we cannot get this information. But in our existing orders data, we have this promotion id and using that field, basically we can get the subscribe and save information if we get can find that ticket. I have posted some screenshots. Also, like it’s number 200.
168 00:20:09.780 ⇒ 00:20:13.800 Awaish Kumar: I I think that’s the one ticket number 200 in the list.
169 00:20:15.400 ⇒ 00:20:23.489 Awaish Kumar: Yeah, I have posted like data here. So with this promotion, Id, we can get the orders which are linked to subscribe and save discount.
170 00:20:25.200 ⇒ 00:20:26.050 Robert Tseng: I see
171 00:20:26.912 ⇒ 00:20:41.819 Robert Tseng: I mean, I don’t wanna dwell too much on it. But like we were talking about proxies for subscribe and say for like 2 weeks. And, like, you know, I had a solution. I had. Annie had a solution. I guess you kind of found something. Is this just we did. We miss this just because you didn’t look at it until like yesterday.
172 00:20:41.820 ⇒ 00:20:45.769 Awaish Kumar: Yeah, no, actually I it was not assigned to me, and that’s why I didn’t look to it.
173 00:20:45.890 ⇒ 00:20:52.089 Awaish Kumar: It was the kyo and the any like they did all of investigation, but
174 00:20:52.451 ⇒ 00:20:57.219 Awaish Kumar: I was assigned some other tickets, and I was looking at those. I haven’t looked into it. This one.
175 00:20:57.220 ⇒ 00:21:00.060 Robert Tseng: So you, just like randomly found this on.
176 00:21:00.060 ⇒ 00:21:14.530 Awaish Kumar: No, no, this is this is assigned to me yesterday. By Akash about this replacement Api investigation. And while doing investigation about that Api. I just went into the existing data as well, and I found this.
177 00:21:17.380 ⇒ 00:21:18.390 Robert Tseng: Okay.
178 00:21:19.930 ⇒ 00:21:35.880 Robert Tseng: yeah. I mean, we’ve been like telling Javi. We can’t do this for like 2 weeks. And then, now we’re gonna tell them we can do it is, I don’t know just not a good look for us, so I mean, it’s fine, like I’m glad we found it. But this is like.
179 00:21:37.650 ⇒ 00:21:43.260 Robert Tseng: I mean, we’re gonna I’m we’re gonna see where where things broke down later on, like, why we were able to find this earlier
180 00:21:45.780 ⇒ 00:21:56.150 Robert Tseng: cause. It looks like this is just like an existing field. I mean, I think this is just the we should be looking at what data we have coming in, and we should, we should have found. This is kind of what I what I think
181 00:21:56.648 ⇒ 00:22:00.549 Robert Tseng: right like. It’s not like nothing new is added. It was just there, though.
182 00:22:00.550 ⇒ 00:22:01.740 Robert Tseng: No, no, okay.
183 00:22:01.740 ⇒ 00:22:16.859 Awaish Kumar: Yeah, it is in the raw, raw data. So I think in our current modeling work, it was not there. And maybe someone who was investigating, looking into the modeling work, but not in the raw data. So this field is available in raw
184 00:22:17.260 ⇒ 00:22:19.099 Awaish Kumar: order. Amazon data.
185 00:22:20.240 ⇒ 00:22:21.010 Robert Tseng: Okay.
186 00:22:21.860 ⇒ 00:22:47.619 Robert Tseng: yeah. I mean, I think this is like where the line needs to be drawn. We’re like, yeah, I mean, Annie should not be expected to be looking through the raw data like she doesn’t know what’s in there, and she should. She should know what she needs to use to build what she’s building. But like, it’s kind of the it’s the responsibility of the Aes to figure out like what data we have available. So I think we need to tighten up that process because it feels like we just spun around for 2 weeks. On this.
187 00:22:51.170 ⇒ 00:22:54.033 Robert Tseng: That’s okay. I’m gonna bring that up to Akash later.
188 00:22:54.770 ⇒ 00:23:06.350 Robert Tseng: alright, let’s just kind of keep going through. Yeah. So I mean, you marked it as done and like. So your investigation is done. You’ve handed it off to Kyle. So is the next step, Kyle, or like, what’s how are you? Gonna get.
189 00:23:06.350 ⇒ 00:23:07.509 Awaish Kumar: No, I.
190 00:23:08.600 ⇒ 00:23:19.080 Robert Tseng: Because that is the most urgent thing that Joby has been asking for for a while. It’s been blocking me from doing Amazon reporting work like, you know, there are a lot of things that have been have been waiting on that for a while.
191 00:23:21.000 ⇒ 00:23:23.580 Awaish Kumar: So what? I’m saying that, yeah.
192 00:23:25.670 ⇒ 00:23:33.859 Robert Tseng: Yeah, like, I’ve been blocked on this since April second. So it’s been actually more since 20 days ago. Pretty much. Yeah.
193 00:23:37.780 ⇒ 00:23:43.160 Robert Tseng: So so, yeah, I guess. What what ticket are you? Are you? What is is tied to the next step here.
194 00:23:44.050 ⇒ 00:24:01.400 Awaish Kumar: So there’s like no nest like I was asked to spend 2 h to investigate this if I can find something, and I found the investigation. I put the results. And now, like it’s on on your or the Akash to like, like to create tickets for implementation part.
195 00:24:02.270 ⇒ 00:24:02.840 Robert Tseng: Okay.
196 00:24:03.370 ⇒ 00:24:03.970 Awaish Kumar: Yeah.
197 00:24:05.710 ⇒ 00:24:12.689 Robert Tseng: Alright. I wish I’m just gonna assign it to you. So a wish to add or add subscribe
198 00:24:13.610 ⇒ 00:24:21.989 Robert Tseng: and save 2 Amazon orders model.
199 00:24:22.270 ⇒ 00:24:25.920 Robert Tseng: It’s at the order level I’m assuming, and not like the line item level.
200 00:24:28.690 ⇒ 00:24:34.639 Awaish Kumar: Basically, I think it is available to us on the light line item level as well.
201 00:24:34.640 ⇒ 00:24:40.430 Robert Tseng: Oh, it is okay. Yeah. I’ll.
202 00:24:43.230 ⇒ 00:24:47.939 Awaish Kumar: So we can connect, subscribe, and save with. We have Amazon, id, and we have a
203 00:24:48.400 ⇒ 00:24:54.370 Awaish Kumar: order line item Id, and using that, we can connect directly with the line. Item.
204 00:24:56.750 ⇒ 00:24:57.450 Robert Tseng: Yeah.
205 00:25:02.010 ⇒ 00:25:06.160 Robert Tseng: okay, well, basically, it needs it needs to be available in both models is kind of my point here.
206 00:25:06.710 ⇒ 00:25:07.420 Awaish Kumar: Okay.
207 00:25:11.440 ⇒ 00:25:20.429 Caio Velasco: Quick thing. I I see I have a tick, an issue, a ticket, whatever also related to subscribe and save
208 00:25:21.080 ⇒ 00:25:24.660 Caio Velasco: I don’t know if it’s kind of the same thing at the end of the day, but
209 00:25:24.800 ⇒ 00:25:25.910 Caio Velasco: just to check.
210 00:25:29.450 ⇒ 00:25:36.569 Robert Tseng: Okay, I mean, Akash created this and then assign it to you. Yeah, I’m gonna move it. I’m gonna move it to a wish.
211 00:25:36.960 ⇒ 00:25:39.150 Robert Tseng: I guess it’s the same thing. But.
212 00:25:40.640 ⇒ 00:25:44.520 Awaish Kumar: So we just need a flag right to identify if it’s a safe subscribe and save right.
213 00:25:44.680 ⇒ 00:25:45.590 Robert Tseng: That’s it.
214 00:25:46.150 ⇒ 00:25:46.840 Awaish Kumar: Okay.
215 00:25:47.870 ⇒ 00:25:48.480 Robert Tseng: Okay.
216 00:25:52.410 ⇒ 00:25:56.390 Robert Tseng: Alright. I know we’re coming up, so I’ll just anything else. I wish.
217 00:25:57.800 ⇒ 00:25:58.149 Awaish Kumar: No.
218 00:25:58.500 ⇒ 00:26:02.030 Robert Tseng: Alright. Let’s look at Kyle.
219 00:26:04.230 ⇒ 00:26:12.980 Caio Velasco: Yep. So basically, I spent yesterday and a bit of today on the Klavio
220 00:26:13.110 ⇒ 00:26:16.879 Caio Velasco: issue that Akash told me that that was the priority.
221 00:26:17.688 ⇒ 00:26:26.890 Caio Velasco: And well, I’ve been learning a lot about it try to like document everything. And I built some them tables
222 00:26:27.010 ⇒ 00:26:33.910 Caio Velasco: also with descriptions that are now in March in Snowflake, because we didn’t have a feature in Dbt. That would
223 00:26:34.030 ⇒ 00:26:40.690 Caio Velasco: also push the descriptions to the table in Snowflake, so that it can help downstream, for example, any or you.
224 00:26:41.060 ⇒ 00:26:43.820 Caio Velasco: So I think now it’s a bit more organized in that way.
225 00:26:44.000 ⇒ 00:26:50.200 Caio Velasco: and and then I push the Pr. It’s approved. I just merged it. So we have at least something
226 00:26:50.802 ⇒ 00:26:54.959 Caio Velasco: to check. Now the the next idea would be.
227 00:26:55.140 ⇒ 00:27:02.010 Caio Velasco: I will have to take a look in and see, you know, since we had an idea of a business question in the issue
228 00:27:02.240 ⇒ 00:27:07.579 Caio Velasco: in the description, then I have to check. Now, if we can
229 00:27:08.970 ⇒ 00:27:14.229 Caio Velasco: like, I would say, like, join that with orders and revenue. Because yes, it’s the it’s the end goal.
230 00:27:14.350 ⇒ 00:27:21.960 Caio Velasco: But before that there’s a lot of exploration. So then I would try to like, you know. Extend this for like a next step
231 00:27:22.996 ⇒ 00:27:23.930 Caio Velasco: and then
232 00:27:24.760 ⇒ 00:27:35.879 Caio Velasco: would be like finishing the the main idea to ensure that this can be joined with orders and revenue, because it’s a it’s a lot of work. And one of the
233 00:27:36.500 ⇒ 00:27:47.679 Caio Velasco: one of the the main sources in Kavio. The segments table has a lot of crazy J’s on with like crazy logic that had never been seen before. But at least now there’s something.
234 00:27:47.810 ⇒ 00:27:53.350 Caio Velasco: so I would just like continue the work, although my hours are mostly done for the week. But
235 00:27:53.490 ⇒ 00:27:58.140 Caio Velasco: I’m sure that I can talk with you, Tom, about that and then there’s also
236 00:27:58.850 ⇒ 00:28:06.610 Caio Velasco: the the other one, the cogs one that I saw the Blake yesterday answered, and I was gonna take a look at at it now, to see
237 00:28:07.310 ⇒ 00:28:10.569 Caio Velasco: if we already have the answers that he shared like a
238 00:28:10.690 ⇒ 00:28:16.250 Caio Velasco: a Csv which I assume he just got from Amazon, or something. I’m not
239 00:28:16.250 ⇒ 00:28:19.210 Caio Velasco: so staying on the klaviyo. So yep.
240 00:28:19.550 ⇒ 00:28:24.618 Robert Tseng: Is, are we like? Is this, can we see this or like, I guess, what’s in the model?
241 00:28:25.730 ⇒ 00:28:35.750 Robert Tseng: I was trying to like pull it up, but I don’t have it. There’s no reference. And of like, I mean, I’m not gonna click into the I don’t know if I’ll be able to tell from clicking into the VR.
242 00:28:35.750 ⇒ 00:28:38.119 Caio Velasco: Oh, you can check Snowflake on the on.
243 00:28:38.220 ⇒ 00:28:41.390 Caio Velasco: on broad Mark, on Broadmart is probably already there.
244 00:28:41.890 ⇒ 00:28:49.559 Robert Tseng: Yeah, okay, well, I mean, I would like to do it live. So I can. Just I mean, but I I mean, we’re gonna go over time. I have to like, go and log in.
245 00:28:49.810 ⇒ 00:28:52.199 Robert Tseng: Okay, fine, I can do it.
246 00:28:53.740 ⇒ 00:28:55.883 Caio Velasco: It’s it’s more it’s up to you.
247 00:28:56.640 ⇒ 00:28:57.150 Robert Tseng: Oh, yeah.
248 00:28:57.150 ⇒ 00:29:02.530 Robert Tseng: I mean, I just I don’t. I don’t wanna just like talk over the ticket like I want to actually see what was done. So.
249 00:29:02.700 ⇒ 00:29:03.240 Caio Velasco: Yeah.
250 00:29:09.200 ⇒ 00:29:16.370 Robert Tseng: But yeah, I mean, I think this would help if you just left the staging, or whatever whatever model is in next time. So I can go and just look.
251 00:29:17.480 ⇒ 00:29:20.590 Robert Tseng: okay. So what? Broad marts?
252 00:29:26.730 ⇒ 00:29:28.580 Robert Tseng: Dim? Klavio?
253 00:29:28.750 ⇒ 00:29:30.840 Robert Tseng: Okay, you have a few tables here.
254 00:29:34.300 ⇒ 00:29:36.010 Robert Tseng: I don’t know what Meta plane is.
255 00:29:37.650 ⇒ 00:29:38.739 Caio Velasco: You too late!
256 00:29:39.190 ⇒ 00:29:48.270 Robert Tseng: Send time campaigns. Okay? So yeah, we have some campaign like metadata. Here. We have.
257 00:29:49.520 ⇒ 00:29:57.920 Caio Velasco: These contacts come from a table called profiles. But I think contacts make more sense and the sources profile today. So basically contacts.
258 00:29:58.490 ⇒ 00:29:59.250 Robert Tseng: Yeah.
259 00:29:59.250 ⇒ 00:30:02.549 Caio Velasco: Lot of things like subscriptions and other things.
260 00:30:02.900 ⇒ 00:30:05.660 Caio Velasco: And segment is the the more difficult one.
261 00:30:06.540 ⇒ 00:30:07.200 Caio Velasco: Yeah.
262 00:30:07.810 ⇒ 00:30:11.780 Robert Tseng: Okay, but we have no way to join it to revenue for order data right now.
263 00:30:12.400 ⇒ 00:30:27.600 Caio Velasco: Yeah, I’m I’m that would be the next step. So at least it could ship something. And now I would say, well, given that we have order data. I’m assuming that we would be joining with email or something along those lines.
264 00:30:27.910 ⇒ 00:30:31.289 Caio Velasco: But yeah, that would be the next step next step.
265 00:30:33.400 ⇒ 00:30:33.980 Robert Tseng: Yeah.
266 00:30:35.170 ⇒ 00:30:42.910 Caio Velasco: I don’t think we need another source from what I was checking, so it might be easy, let’s say, but that’s just a 1st impression.
267 00:30:47.030 ⇒ 00:30:56.260 Robert Tseng: Okay. Yeah. I know we’re a bit over. So rest, you guys can drop if you’re if you’re if you’re done. But, Kyle, if you want to stay on for your last last one, or whatever you were trying to.
268 00:30:57.150 ⇒ 00:30:57.610 Robert Tseng: Yeah.
269 00:30:57.610 ⇒ 00:31:04.863 Caio Velasco: Perfect. Yeah, for the last one. So I saw that yesterday Blake posted something.
270 00:31:05.830 ⇒ 00:31:13.390 Caio Velasco: and it’s interesting because well, he could have said the same thing like a week or 2 weeks ago. But he just shared the
271 00:31:13.760 ⇒ 00:31:25.229 Caio Velasco: yes, yes, we find that I haven’t looked at it yet. I just opened and and took a quick look. Apparently they have some things in there, not sure if covers everything we want. But he he gave some answers, at least
272 00:31:25.350 ⇒ 00:31:29.299 Caio Velasco: I’ll I’ll get that, and compare to what we have in shopify.
273 00:31:29.540 ⇒ 00:31:37.719 Caio Velasco: And if those things, those assumptions, are the only thing they they have for Amazon like to calculate cops. Then I think we should be fine.
274 00:31:39.870 ⇒ 00:31:43.780 Robert Tseng: Okay. So basically, you haven’t looked at it yet. And we don’t know. You’re just gonna look at it.
275 00:31:44.540 ⇒ 00:31:45.779 Caio Velasco: Yes. Okay.
276 00:31:47.870 ⇒ 00:31:52.729 Robert Tseng: Yeah. Well, I mean that. No, I I don’t. I can’t take any action off of that. So.
277 00:31:53.300 ⇒ 00:31:54.329 Caio Velasco: No, that’s okay.
278 00:31:54.480 ⇒ 00:31:55.000 Robert Tseng: Yeah.
279 00:31:55.600 ⇒ 00:32:07.200 Robert Tseng: Okay. Well, yeah. I think that’s it. I’m gonna try to push a bit harder on on the next couple of days, because we haven’t shipped anything to Java yet, and I think Aman will probably be upset if we don’t. So.
280 00:32:07.390 ⇒ 00:32:08.590 Robert Tseng: Danny, you were. Gonna say.
281 00:32:09.330 ⇒ 00:32:15.350 Annie Yu: Yeah, I do have a ticket that’s ready and need feedback from your Akash.
282 00:32:16.090 ⇒ 00:32:17.250 Robert Tseng: Oh, yeah. Okay.
283 00:32:18.600 ⇒ 00:32:21.950 Annie Yu: The a tentative basic data. So there’s.
284 00:32:21.950 ⇒ 00:32:22.800 Robert Tseng: Attentive.
285 00:32:22.960 ⇒ 00:32:23.630 Annie Yu: Bye.
286 00:32:23.860 ⇒ 00:32:37.649 Robert Tseng: Okay, yeah, I’m gonna kinda support a North Beam review attentive. And then I’ll kind of, I need to get new requirements to Kyle for the klaviyo stuff on what the next version like next version is.
287 00:32:38.190 ⇒ 00:32:44.629 Robert Tseng: and then a wish once to the subscribe and save is implemented, let us know, so we can kind of get unblocked on that stuff.
288 00:32:47.830 ⇒ 00:32:48.850 Awaish Kumar: Okay. Sure.
289 00:32:49.720 ⇒ 00:32:51.930 Robert Tseng: Okay. Alright. Thanks. Everyone.
290 00:32:52.140 ⇒ 00:32:52.570 Annie Yu: Thank you.
291 00:32:52.570 ⇒ 00:32:53.020 Caio Velasco: Thank you.