Meeting Title: Eden | Standup Date: 2025-09-23 Meeting participants: Awaish Kumar, Demilade Agboola, Amber Lin, Henry Zhao
WEBVTT
1 00:02:19.460 ⇒ 00:02:20.400 Demilade Agboola: Hold on, bro.
2 00:02:22.080 ⇒ 00:02:27.520 Amber Lin: Okay, so… mostly just want to see if we can give due dates.
3 00:02:28.340 ⇒ 00:02:31.469 Amber Lin: Do these things, or move anything out of here.
4 00:02:32.280 ⇒ 00:02:39.319 Amber Lin: I wish for these tasks, when do you think you’re going to do them this week?
5 00:02:45.050 ⇒ 00:02:46.679 Awaish Kumar: Yeah, thanks.
6 00:02:47.300 ⇒ 00:02:54.409 Awaish Kumar: I… 811, I… I will finish it, like.
7 00:02:55.080 ⇒ 00:02:56.999 Awaish Kumar: By the end of day today.
8 00:02:58.080 ⇒ 00:02:59.790 Awaish Kumar: Mutual, yeah.
9 00:03:01.090 ⇒ 00:03:03.569 Awaish Kumar: It, it will be available for…
10 00:03:05.750 ⇒ 00:03:06.810 Amber Lin: Okay.
11 00:03:06.810 ⇒ 00:03:09.490 Awaish Kumar: For Henry to lose, like, print tomorrow, basically.
12 00:03:10.330 ⇒ 00:03:11.040 Amber Lin: Mmm.
13 00:03:11.540 ⇒ 00:03:17.780 Amber Lin: Okay, and then, great, and then I’ll save this for Friday.
14 00:03:18.000 ⇒ 00:03:25.010 Amber Lin: So, for, 891, That’s when I’ve sent…
15 00:03:25.410 ⇒ 00:03:29.510 Demilade Agboola: send the PR in, so once it’s reviewed, I will merge it.
16 00:03:30.590 ⇒ 00:03:31.160 Demilade Agboola: clean.
17 00:03:31.850 ⇒ 00:03:32.610 Demilade Agboola: Oh, God.
18 00:03:32.610 ⇒ 00:03:34.700 Amber Lin: But that’s for a wish for… a wish to read.
19 00:03:34.700 ⇒ 00:03:38.689 Awaish Kumar: Is it just in PR review, or you are also… Testing the data.
20 00:03:40.130 ⇒ 00:03:41.440 Demilade Agboola: It’s in peer review.
21 00:03:42.370 ⇒ 00:03:44.510 Awaish Kumar: It’s music too.
22 00:03:45.610 ⇒ 00:03:46.579 Demilade Agboola: Okay, that’s fine.
23 00:03:47.410 ⇒ 00:03:49.600 Demilade Agboola: So it’s in peer review.
24 00:03:49.810 ⇒ 00:03:57.830 Demilade Agboola: then I’ve done Aiden 900, I’ve reached out to… Back, waiting for a response.
25 00:03:58.600 ⇒ 00:04:01.449 Demilade Agboola: I’m currently working on 805.
26 00:04:01.550 ⇒ 00:04:07.800 Demilade Agboola: I had to get some information from Kota, he’s responded. We’ll send the PR within the hour.
27 00:04:08.330 ⇒ 00:04:08.770 Amber Lin: Okay.
28 00:04:08.770 ⇒ 00:04:16.139 Demilade Agboola: And then… Sorry. Also, I just wanted to point out that
29 00:04:16.579 ⇒ 00:04:21.969 Demilade Agboola: There are a couple of tickets that have been assigned to me. I know Henry reached out for something.
30 00:04:21.970 ⇒ 00:04:22.400 Henry Zhao: Yeah.
31 00:04:23.700 ⇒ 00:04:25.729 Amber Lin: Yeah, there’s, there’s the…
32 00:04:25.750 ⇒ 00:04:30.009 Henry Zhao: There’s these two that just go outside, I just noticed.
33 00:04:30.010 ⇒ 00:04:30.420 Demilade Agboola: Yeah.
34 00:04:30.630 ⇒ 00:04:32.340 Henry Zhao: Remodeling, that’s all.
35 00:04:32.970 ⇒ 00:04:36.490 Amber Lin: Yeah, so let’s see…
36 00:04:37.580 ⇒ 00:04:42.649 Demilade Agboola: And also, there’s a request from Qatar that came in today.
37 00:04:42.650 ⇒ 00:04:43.020 Amber Lin: Hmm.
38 00:04:43.020 ⇒ 00:04:50.709 Demilade Agboola: He would like us to be able to make a dashboard for the volume… of new orders.
39 00:04:51.510 ⇒ 00:04:54.370 Demilade Agboola: from the state of… or to the state of California.
40 00:04:55.080 ⇒ 00:04:56.510 Demilade Agboola: So we’ll need to model that.
41 00:04:56.510 ⇒ 00:05:00.380 Amber Lin: Wait, just a second…
42 00:05:00.590 ⇒ 00:05:02.529 Demilade Agboola: I’ll tag you.
43 00:05:03.690 ⇒ 00:05:07.970 Demilade Agboola: in… I just tagged Jane.
44 00:05:07.970 ⇒ 00:05:08.880 Amber Lin: This one?
45 00:05:10.600 ⇒ 00:05:11.530 Amber Lin: Huh.
46 00:05:12.100 ⇒ 00:05:12.870 Demilade Agboola: Yes. Okay.
47 00:05:12.870 ⇒ 00:05:18.860 Amber Lin: So that’s for… It’s tough… Does staff need modeling?
48 00:05:20.240 ⇒ 00:05:29.700 Demilade Agboola: Yes, because we don’t… so what he needs is an replica of the product for us dashboard, but without any of the… basically, he just needs a dashboard that shows
49 00:05:31.080 ⇒ 00:05:35.119 Demilade Agboola: But that’s for Pride. All the orders, because operating California orders are tricky.
50 00:05:35.310 ⇒ 00:05:41.469 Demilade Agboola: So, orders go into California, the new customer, As well as
51 00:05:41.860 ⇒ 00:05:44.110 Demilade Agboola: what’s that thing called? The revenue.
52 00:05:44.250 ⇒ 00:05:50.790 Demilade Agboola: And then, over the last 30 days as well. That’s kind of how we have it in the product for us dashboard.
53 00:05:56.050 ⇒ 00:06:08.079 Demilade Agboola: But then, this wouldn’t be… so, if we add the filter, because… I mean, we could make it known for everything, if that’s what… because the… they don’t care about NPAC and ROS, they don’t care about ad spend.
54 00:06:08.380 ⇒ 00:06:11.320 Demilade Agboola: They just only want to see the numbers.
55 00:06:11.540 ⇒ 00:06:14.219 Demilade Agboola: of orders that are going to California, basically, so…
56 00:06:15.020 ⇒ 00:06:15.870 Amber Lin: Hmm.
57 00:06:17.420 ⇒ 00:06:18.350 Amber Lin: Okay.
58 00:06:25.010 ⇒ 00:06:27.439 Amber Lin: Okay, so how long would this one take?
59 00:06:29.270 ⇒ 00:06:34.579 Demilade Agboola: Modeling part of it should take maybe 2 points, shouldn’t… shouldn’t be…
60 00:06:35.600 ⇒ 00:06:38.399 Amber Lin: Is there any dashboarding tasks after that?
61 00:06:39.580 ⇒ 00:06:40.670 Demilade Agboola: Yes.
62 00:06:41.380 ⇒ 00:06:42.090 Amber Lin: Okay.
63 00:06:42.520 ⇒ 00:06:46.589 Amber Lin: So, let me create that, and let me create a…
64 00:07:08.150 ⇒ 00:07:10.670 Amber Lin: Okay, and then…
65 00:07:16.190 ⇒ 00:07:22.739 Amber Lin: Okay, and then on the finance side, Jonah is asking.
66 00:07:23.110 ⇒ 00:07:28.859 Amber Lin: Can we get aspen by day, and if we adjust scroll bar for
67 00:07:28.900 ⇒ 00:07:43.740 Amber Lin: dates, we can pull new orders per day. Can I get in an Excel spreadsheet each day going back to April? And then second column would be ad spend, the third column would be new customer acquisition.
68 00:07:43.820 ⇒ 00:07:46.899 Amber Lin: Just for Sama.
69 00:07:47.380 ⇒ 00:07:50.119 Amber Lin: Can someone pull the data for him?
70 00:07:50.570 ⇒ 00:07:55.499 Henry Zhao: Do you guys know if this is just in, cohort user… spend summary?
71 00:07:59.520 ⇒ 00:08:00.220 Demilade Agboola: Pardon?
72 00:08:00.440 ⇒ 00:08:02.109 Henry Zhao: I can look into this, Amber.
73 00:08:03.210 ⇒ 00:08:06.400 Henry Zhao: But I might need to ask Demolade or Awash questions.
74 00:08:06.900 ⇒ 00:08:08.429 Henry Zhao: In order to get this done, actually.
75 00:08:09.070 ⇒ 00:08:14.919 Demilade Agboola: To be fair, if we want to make it a… the cold.
76 00:08:16.290 ⇒ 00:08:20.639 Demilade Agboola: want to do as quickly as possible. I think it might just be faster to pull it directly from BigQuery.
77 00:08:20.870 ⇒ 00:08:24.409 Demilade Agboola: If we pull up the table, that powers this dashboard.
78 00:08:24.630 ⇒ 00:08:31.149 Demilade Agboola: by day, where it’s injectable summer. We can get that… we can get that done pretty quickly.
79 00:08:32.120 ⇒ 00:08:33.960 Amber Lin: Okay, so…
80 00:08:33.960 ⇒ 00:08:36.939 Henry Zhao: I’ll write a query. If one of you can help me check it, that would be great.
81 00:08:38.049 ⇒ 00:08:39.039 Awaish Kumar: Oh my gosh.
82 00:08:39.039 ⇒ 00:08:39.699 Demilade Agboola: concept.
83 00:08:39.880 ⇒ 00:08:41.600 Amber Lin: Who would do this?
84 00:08:41.669 ⇒ 00:08:42.409 Henry Zhao: Let’s do it.
85 00:08:43.320 ⇒ 00:08:44.080 Amber Lin: Okay.
86 00:08:44.690 ⇒ 00:08:46.610 Amber Lin: Do you have enough time?
87 00:08:46.850 ⇒ 00:08:47.650 Henry Zhao: Yeah, it should be one point.
88 00:08:50.340 ⇒ 00:08:50.770 Awaish Kumar: Okay.
89 00:08:50.770 ⇒ 00:08:59.819 Henry Zhao: I have a lot of time this week, I’m just worried about giving Demolade, like, more modeling tasks and things like that, but once I’m, like, caught up on this finance stuff, I can help with the modeling.
90 00:09:00.990 ⇒ 00:09:04.160 Amber Lin: Okay, and then when is some… This one?
91 00:09:05.490 ⇒ 00:09:16.260 Awaish Kumar: Yeah, like, I just had to say something on that. If you could use this… I think product sales summary by transaction table, it has exactly the same thing he’s asking for.
92 00:09:16.330 ⇒ 00:09:18.889 Henry Zhao: Okay. It has the date, it has the…
93 00:09:19.050 ⇒ 00:09:25.700 Awaish Kumar: At a span, it also has the order count and new customer count.
94 00:09:25.840 ⇒ 00:09:26.950 Awaish Kumar: byproduct.
95 00:09:27.980 ⇒ 00:09:32.519 Henry Zhao: Okay, thank you. Yeah, I’ll take a look, and then I just need somebody to quickly check it for me, just be like.
96 00:09:32.940 ⇒ 00:09:33.980 Henry Zhao: Does this look right?
97 00:09:36.110 ⇒ 00:09:38.529 Henry Zhao: Because I know the columns say what they are, but…
98 00:09:39.420 ⇒ 00:09:43.060 Henry Zhao: Just want to double-check that the, like, backend modeling
99 00:09:43.460 ⇒ 00:09:46.690 Henry Zhao: logic, there’s not something that I’m forgetting, you know what I mean?
100 00:09:49.220 ⇒ 00:09:49.940 Henry Zhao: Thank you.
101 00:09:50.310 ⇒ 00:10:00.409 Amber Lin: Okay, let’s help prioritize, the tasks here. So, low priority, and then for…
102 00:10:00.410 ⇒ 00:10:11.320 Henry Zhao: Before we prioritize, real quick, is Demolade, I gave you some new modding tasks, but I’ve told the stakeholders that these might take a while, just to give you extra time, like, I don’t want… I just wanted… I already prepared them that these might take a while.
103 00:10:14.200 ⇒ 00:10:14.960 Amber Lin: Okay.
104 00:10:16.280 ⇒ 00:10:18.919 Amber Lin: Growth.
105 00:10:20.630 ⇒ 00:10:23.800 Awaish Kumar: Who’s ruling, like, that transaction?
106 00:10:25.920 ⇒ 00:10:32.449 Demilade Agboola: Yeah, I was gonna ask the same question, too. Is there any reason why we need standard products in… seamless products in 5 transactions?
107 00:10:34.940 ⇒ 00:10:40.960 Henry Zhao: Just because I’m using fact transactions to get the revenue based on the last UTMs.
108 00:10:41.440 ⇒ 00:10:46.240 Henry Zhao: But they need to then group by… GLP-1 and non-GLP-1.
109 00:10:46.860 ⇒ 00:10:48.489 Awaish Kumar: Yeah, we actually…
110 00:10:48.770 ⇒ 00:10:57.030 Awaish Kumar: We… we did this on purpose, right? In the transaction table, we want to keep mainly the… transactions.
111 00:10:57.220 ⇒ 00:11:07.199 Awaish Kumar: And most of the, like, dimensional data, we want to keep it separate. So we just have the, a column called Artificial Product ID,
112 00:11:07.390 ⇒ 00:11:13.759 Awaish Kumar: You can use that to combine it with DIM products, and you will get the standardized product name.
113 00:11:14.320 ⇒ 00:11:15.610 Henry Zhao: Okay, great, I will do that.
114 00:11:15.610 ⇒ 00:11:24.010 Demilade Agboola: Alright, so I will… let me just add it to the ticket. I’ll add a comment right now. So this is a sample join that I just added it to the ticket.
115 00:11:24.470 ⇒ 00:11:25.910 Henry Zhao: Okay, I’ll do that, perfect.
116 00:11:27.120 ⇒ 00:11:29.980 Henry Zhao: then you can assign this back to me, Amber, and it was just one point also.
117 00:11:29.980 ⇒ 00:11:30.690 Amber Lin: Okay.
118 00:11:31.470 ⇒ 00:11:31.900 Henry Zhao: Google.
119 00:11:31.900 ⇒ 00:11:41.649 Amber Lin: Okay, so this is to-do… Okay. And then what about this one? How… what’s the estimate for this?
120 00:11:43.130 ⇒ 00:11:45.480 Henry Zhao: Yeah, Damlad, is this something that you can do? So…
121 00:11:45.750 ⇒ 00:11:56.100 Henry Zhao: If it’s not possible, let me know, I can push back on to Judd, but he wants to break down now the cohort revenue retention summary by first order date instead of first order month.
122 00:11:56.540 ⇒ 00:12:06.259 Henry Zhao: If you want, like, I don’t know if we even want to do this, if we want to just add the column name, I can go into Tableau and just check if the calculated fields still add up properly.
123 00:12:11.060 ⇒ 00:12:16.370 Demilade Agboola: I mean, we could do the first holiday, but it would be such small chunks, I’m not sure if it makes a lot of sense.
124 00:12:17.290 ⇒ 00:12:25.560 Demilade Agboola: like, part of the reason why, like, we use MOMP, I believe, is because, like, you get a decent chunk, and you can start to see what’s happening.
125 00:12:25.780 ⇒ 00:12:29.319 Demilade Agboola: Over, like, a sample size of, say, 500 people.
126 00:12:29.680 ⇒ 00:12:37.569 Demilade Agboola: If you do it by day, on some days it’s maybe 50 people, some days it might be 10 people, some days it might be 100 people.
127 00:12:38.010 ⇒ 00:12:43.920 Demilade Agboola: I don’t know if that retention is as… it feels more noisy, in my opinion.
128 00:12:44.360 ⇒ 00:12:45.879 Demilade Agboola: Well, we could do it.
129 00:12:47.180 ⇒ 00:12:50.660 Demilade Agboola: It’s doable, it’s just… it’s just how we’re truncating the data.
130 00:12:52.730 ⇒ 00:12:58.810 Henry Zhao: Yeah, or if we want to make this, like, a temporary thing just for him to do his analysis, like, maybe just duplicate this model.
131 00:12:59.320 ⇒ 00:13:00.569 Henry Zhao: as, like, a…
132 00:13:01.020 ⇒ 00:13:05.310 Henry Zhao: Chunks by first order date, or maybe we’d even just do it by week and say, this is the best we can give you.
133 00:13:05.420 ⇒ 00:13:10.859 Henry Zhao: he just basically says, like, the monthly is not enough detail for him to do his analysis. He needs to, like.
134 00:13:11.040 ⇒ 00:13:13.649 Henry Zhao: Get a better understanding of what it looks like by day or by week.
135 00:13:14.150 ⇒ 00:13:20.199 Henry Zhao: So if we want to just, like, make this a temporary, like, a few months thing so he can do his analysis and then kill it, I think that works also.
136 00:13:21.460 ⇒ 00:13:31.380 Demilade Agboola: Alright, sure, I’ll do, cohort revenue retention for me. Weekly or daily, which one do you want me to do? I could do both, but, like, what’s the priority?
137 00:13:31.710 ⇒ 00:13:42.470 Henry Zhao: First, let’s do daily, like he asked, but if it’s, like, way too detailed, or, like, we get 17 million rows, 17 billion rows, we… we can just say, like, the best we can give you is weekly.
138 00:13:43.970 ⇒ 00:13:45.020 Demilade Agboola: Correct. Sounds good.
139 00:13:45.290 ⇒ 00:13:48.060 Amber Lin: Okay, so this would taste like one, one…
140 00:13:49.540 ⇒ 00:13:53.779 Demilade Agboola: Yeah, it should take about a point or two, depending…
141 00:13:53.990 ⇒ 00:14:00.970 Demilade Agboola: With how things… so the problem with this sort of task is not really the actual logic, is some things might not just make sense once you’re done.
142 00:14:01.570 ⇒ 00:14:04.729 Demilade Agboola: Except errors might pop up. So it should be a one-point task.
143 00:14:05.450 ⇒ 00:14:09.150 Demilade Agboola: Priority, I think… is this low priority or median priority?
144 00:14:09.960 ⇒ 00:14:11.710 Henry Zhao: Medium.
145 00:14:12.090 ⇒ 00:14:15.090 Amber Lin: I think it’s medium before our internal stuff.
146 00:14:15.340 ⇒ 00:14:21.940 Amber Lin: Let’s see… for Qatar, let’s say… .
147 00:14:21.940 ⇒ 00:14:24.509 Demilade Agboola: Corda would like this as soon as possible.
148 00:14:24.730 ⇒ 00:14:30.790 Amber Lin: Yeah, I’ll mark this as high. And then…
149 00:14:31.230 ⇒ 00:14:35.410 Amber Lin: For atoms, I’m also going… this is a spike?
150 00:14:35.800 ⇒ 00:14:48.060 Amber Lin: So, I think we should… we should prioritize doing this back so we can go… go on to the modeling. I did move the modeling out to next week, but it’s just been there for a while.
151 00:14:49.270 ⇒ 00:14:58.000 Demilade Agboola: Yeah, I… will… like, it’s the messaging part that I keep forgetting. I will do that right now, like, that I don’t forget.
152 00:14:58.240 ⇒ 00:15:02.189 Demilade Agboola: Yeah, that’s okay.
153 00:15:03.110 ⇒ 00:15:03.850 Amber Lin: Okay.
154 00:15:03.980 ⇒ 00:15:11.490 Amber Lin: So, let’s say… how long would this one take for a cutter? Like, 2 hours? An hour?
155 00:15:13.200 ⇒ 00:15:24.209 Demilade Agboola: This should also be, like, an hour or two. It’s basically just joining it back to order, shipped, and then getting the… the state it was delivered to.
156 00:15:25.440 ⇒ 00:15:26.599 Amber Lin: Okay.
157 00:15:27.220 ⇒ 00:15:33.660 Amber Lin: I’ll say this is… Today… And then…
158 00:15:36.470 ⇒ 00:15:41.670 Amber Lin: For the internal task, I’ll say…
159 00:15:41.920 ⇒ 00:15:45.969 Amber Lin: So this week, for Adam Spike.
160 00:15:46.070 ⇒ 00:15:48.239 Amber Lin: When do we want to finish this?
161 00:15:49.930 ⇒ 00:15:53.970 Demilade Agboola: Today, I’m trying to see the initial messages so I can just go there and respond.
162 00:15:54.860 ⇒ 00:16:03.659 Amber Lin: Okay. And then for Judd’s dashboard fix, maybe we should do… Like, tomorrow or Thursday?
163 00:16:04.880 ⇒ 00:16:07.499 Demilade Agboola: Yeah, I think Thursday will be… will be a good…
164 00:16:09.730 ⇒ 00:16:15.260 Henry Zhao: And if you need me to push back on him, like, I have a decent relationship with him right now that I can push back if you really need to.
165 00:16:17.240 ⇒ 00:16:24.189 Amber Lin: have enough capacity. We have 4 days left, we have 5 points.
166 00:16:24.680 ⇒ 00:16:35.670 Amber Lin: So I think we should be fine. I do expect, that Henry, once you do your scoping out for Brad, there will be more modeling tasks, but I think that’s… that’s it.
167 00:16:36.310 ⇒ 00:16:41.129 Henry Zhao: Or took notes. If you have any notes, if you can send me those.
168 00:16:41.530 ⇒ 00:16:42.649 Henry Zhao: That’d be good, just for me to.
169 00:16:44.390 ⇒ 00:16:46.360 Demilade Agboola: Yeah, I think I sent it.
170 00:16:46.540 ⇒ 00:16:52.850 Demilade Agboola: the bulk of the notes… like, it was really short notes, just to be able to say, the client wants this, the client wants…
171 00:16:53.400 ⇒ 00:16:56.120 Demilade Agboola: It basically helps as it’s… yeah.
172 00:16:58.290 ⇒ 00:17:03.869 Amber Lin: Yeah, I think Robert did send, the granola recording.
173 00:17:04.119 ⇒ 00:17:08.529 Henry Zhao: Yeah, yeah, I have that too. I’m just gonna double-check some things with Katie before I…
174 00:17:08.700 ⇒ 00:17:10.280 Amber Lin: Okay.
175 00:17:10.960 ⇒ 00:17:12.480 Amber Lin: So…
176 00:17:12.480 ⇒ 00:17:14.369 Awaish Kumar: I have converted my partners.
177 00:17:14.730 ⇒ 00:17:15.460 Amber Lin: Yeah.
178 00:17:15.589 ⇒ 00:17:25.730 Amber Lin: I think… Overall, let’s see… The 10 points on Demulade.
179 00:17:26.089 ⇒ 00:17:33.940 Amber Lin: I think we can manage 15 points total, so maybe something will come out of this one.
180 00:17:34.100 ⇒ 00:17:38.380 Amber Lin: Okay, here, let’s look at your task, there’s a lot here, huh?
181 00:17:38.380 ⇒ 00:17:44.209 Awaish Kumar: Yeah, for the Henry, like, Because there are some tasks which can be moved over to me.
182 00:17:44.470 ⇒ 00:17:48.999 Awaish Kumar: We can move, like… There’s a lot of, a lot of fun.
183 00:17:49.460 ⇒ 00:17:50.760 Awaish Kumar: Yeah, Les…
184 00:17:50.870 ⇒ 00:17:59.470 Amber Lin: Yeah, let’s look at this. Let’s move Judd’s dashboard out, because the modeling we’re saying we’re doing on Thursday.
185 00:18:00.760 ⇒ 00:18:05.339 Henry Zhao: Those are really easy, though. So this 899 is not blocked anymore because of what we just talked about?
186 00:18:05.850 ⇒ 00:18:07.030 Henry Zhao: Oh, okay.
187 00:18:08.060 ⇒ 00:18:09.369 Henry Zhao: This is the two…
188 00:18:09.800 ⇒ 00:18:13.920 Amber Lin: Okay, so I’ll… Mmm…
189 00:18:14.280 ⇒ 00:18:18.829 Henry Zhao: So that will be done once the modeling from Demolade is done.
190 00:18:19.290 ⇒ 00:18:27.229 Amber Lin: Yeah, so I’m going to… move that out. We can pull it back in if needed.
191 00:18:31.230 ⇒ 00:18:34.629 Amber Lin: That one, we need to do this week.
192 00:18:35.220 ⇒ 00:18:39.069 Amber Lin: Okay, what can we push out?
193 00:18:39.420 ⇒ 00:18:41.579 Amber Lin: There’s a lot of stuff here.
194 00:18:42.390 ⇒ 00:18:44.780 Amber Lin: What’s lower priority?
195 00:18:44.890 ⇒ 00:18:47.150 Amber Lin: I think that’s very important.
196 00:18:48.320 ⇒ 00:18:51.749 Amber Lin: In the UTM stuff, I don’t think we can push out.
197 00:18:52.490 ⇒ 00:18:57.400 Henry Zhao: Yeah, that’s just the meeting with, Zoran right after this call that I will…
198 00:18:57.930 ⇒ 00:18:59.239 Henry Zhao: Need to follow up on.
199 00:19:03.240 ⇒ 00:19:06.590 Amber Lin: Okay, so that we will do today.
200 00:19:07.690 ⇒ 00:19:08.610 Henry Zhao: Sure.
201 00:19:10.240 ⇒ 00:19:11.050 Amber Lin: Okay.
202 00:19:13.180 ⇒ 00:19:14.849 Henry Zhao: That, I’m gonna finish today also.
203 00:19:15.620 ⇒ 00:19:22.689 Amber Lin: Today… Is the spike 2 hours? Is that accurate? I just found the number and put that on.
204 00:19:23.900 ⇒ 00:19:24.520 Henry Zhao: Yeah.
205 00:19:24.930 ⇒ 00:19:29.020 Amber Lin: Okay, is there something we should move out, or should we…
206 00:19:29.020 ⇒ 00:19:31.589 Henry Zhao: No, this I’m waiting on. So, Wish, I gave you a pull request.
207 00:19:31.760 ⇒ 00:19:35.619 Henry Zhao: I needed to make my own version of standardized product names.
208 00:19:35.950 ⇒ 00:19:41.280 Henry Zhao: to fit into the way that, Judd is doing treatment follow-up reminders.
209 00:19:41.490 ⇒ 00:19:45.220 Henry Zhao: So, if you can take a look and just see if that looks good, I can implement that.
210 00:19:46.520 ⇒ 00:19:52.639 Awaish Kumar: Okay, okay, so product naming convention is different for him?
211 00:19:53.260 ⇒ 00:19:53.840 Henry Zhao: Yeah.
212 00:19:55.580 ⇒ 00:19:56.029 Awaish Kumar: I’ll leave…
213 00:19:56.030 ⇒ 00:19:56.490 Demilade Agboola: Oh.
214 00:19:56.490 ⇒ 00:19:58.740 Awaish Kumar: Are we gonna have that?
215 00:19:59.760 ⇒ 00:20:01.130 Demilade Agboola: That’s very good.
216 00:20:01.740 ⇒ 00:20:06.059 Henry Zhao: The reason why we have a standardized product name is so that we have a standard.
217 00:20:08.320 ⇒ 00:20:11.080 Henry Zhao: Yeah, but this is how they do things in Customer I.O, basically.
218 00:20:13.090 ⇒ 00:20:15.849 Henry Zhao: And to prepare for future rollout products.
219 00:20:17.060 ⇒ 00:20:22.250 Awaish Kumar: I understand, that, but thing is that we want to standardize across
220 00:20:22.680 ⇒ 00:20:28.319 Awaish Kumar: everything across Eden. So whatever it is, maybe, like, what you have done is much more accurate.
221 00:20:28.560 ⇒ 00:20:31.750 Awaish Kumar: Then we can adopt it, like, everywhere.
222 00:20:31.890 ⇒ 00:20:33.370 Awaish Kumar: So that’s the point, like…
223 00:20:33.620 ⇒ 00:20:39.360 Awaish Kumar: I just want to, like, make sure that whatever we are doing, we all are doing the same thing.
224 00:20:41.960 ⇒ 00:20:46.690 Henry Zhao: I can meet with Bobby and just say, like, can we standardize?
225 00:20:47.820 ⇒ 00:20:49.490 Henry Zhao: Yeah, if so, I will just…
226 00:20:50.550 ⇒ 00:20:51.700 Awaish Kumar: Yeah, that’s okay.
227 00:20:51.700 ⇒ 00:20:52.460 Henry Zhao: what we have.
228 00:20:52.720 ⇒ 00:20:54.760 Henry Zhao: But if not, we’re gonna have to have this.
229 00:20:55.670 ⇒ 00:21:00.370 Amber Lin: Okay, so this is… .
230 00:21:00.930 ⇒ 00:21:02.510 Henry Zhao: Henry, yeah.
231 00:21:03.410 ⇒ 00:21:04.740 Amber Lin: Okay.
232 00:21:04.740 ⇒ 00:21:06.520 Henry Zhao: Well, the master test is keep this.
233 00:21:07.760 ⇒ 00:21:14.719 Henry Zhao: maybe just add a sub-issue, Henry, check with… Bobby on… Standardized product names, zero points.
234 00:21:30.980 ⇒ 00:21:34.060 Amber Lin: Say this… I’ll keep it in PR review.
235 00:21:34.180 ⇒ 00:21:35.040 Amber Lin: Okay.
236 00:21:35.920 ⇒ 00:21:45.640 Amber Lin: For… Oh my… for all of these, I’m gonna say this will be… Today…
237 00:21:45.810 ⇒ 00:21:51.689 Amber Lin: For Judd’s Hack Fix, we’re doing that this week, or are we pushing it down?
238 00:21:53.360 ⇒ 00:21:55.330 Amber Lin: Oh.
239 00:21:55.560 ⇒ 00:21:56.909 Henry Zhao: Bookmark that as today, also.
240 00:21:58.150 ⇒ 00:22:03.730 Amber Lin: I’m just thinking in terms of priority of what we’re going to do first, is that very important to him?
241 00:22:05.180 ⇒ 00:22:08.509 Henry Zhao: I just feel like some of these are, like, low-hanging fruit, I just want to get it out of the way.
242 00:22:09.940 ⇒ 00:22:12.690 Henry Zhao: And it’s not… yeah, it’s not gonna block my other work.
243 00:22:13.180 ⇒ 00:22:13.540 Amber Lin: Okay.
244 00:22:13.840 ⇒ 00:22:18.739 Henry Zhao: Because I’m completely free today. So I’d rather just get rid of these and clean things up.
245 00:22:19.600 ⇒ 00:22:20.310 Amber Lin: Okay.
246 00:22:20.810 ⇒ 00:22:28.350 Henry Zhao: Not to mention some of these bigger ones, like, I sometimes need people to respond to me, so I don’t want to be… while I’m waiting for people to respond, so…
247 00:22:28.350 ⇒ 00:22:29.120 Amber Lin: Okay.
248 00:22:29.120 ⇒ 00:22:31.669 Henry Zhao: Looks like a lot, but it’s still very manageable.
249 00:22:32.130 ⇒ 00:22:36.499 Amber Lin: Yeah, are you going to be able to complete.
250 00:22:36.500 ⇒ 00:22:39.110 Henry Zhao: Yeah, do we have to cancel those, I just need to…
251 00:22:39.430 ⇒ 00:22:43.940 Amber Lin: Oh, okay. You have 35 points… Total.
252 00:22:44.340 ⇒ 00:22:46.600 Amber Lin: It looks like a lot, but it’s slightly less.
253 00:22:46.970 ⇒ 00:22:54.559 Amber Lin: Okay, okay, okay. 30… 32 left. That means we have 4 days.
254 00:22:54.630 ⇒ 00:23:01.220 Henry Zhao: The 752 originally scoped by Annie, was supposed to be 10 points, so I’m actually, like, reducing points and trying to do them even faster than.
255 00:23:02.040 ⇒ 00:23:03.509 Henry Zhao: Points it is right now, so…
256 00:23:03.510 ⇒ 00:23:04.640 Amber Lin: Okay.
257 00:23:05.120 ⇒ 00:23:11.220 Amber Lin: Okay, so let’s see if we can complete this, all of this, this week. You have a lot of time.
258 00:23:11.220 ⇒ 00:23:17.310 Awaish Kumar: Yeah, if you want, like, you can move, for example, 920, or… Alright.
259 00:23:18.140 ⇒ 00:23:20.259 Awaish Kumar: 911 to me, if you want.
260 00:23:20.260 ⇒ 00:23:24.180 Amber Lin: I think that will… that will work. Let me assign this to a wish.
261 00:23:24.480 ⇒ 00:23:30.219 Henry Zhao: Can I do it, but have a wish be the one that checks my work? I think it’s… this is better, so that I can…
262 00:23:30.420 ⇒ 00:23:35.160 Henry Zhao: like, start learning more from Awash. So, like, I will need Awash’s help.
263 00:23:36.310 ⇒ 00:23:38.280 Henry Zhao: But I want to do it so I can learn.
264 00:23:40.040 ⇒ 00:23:42.410 Henry Zhao: Like, just make sure that my modeling knowledge is correct.
265 00:23:44.170 ⇒ 00:23:46.989 Amber Lin: What else can we move to Oishi?
266 00:23:49.450 ⇒ 00:23:52.250 Henry Zhao: A lot of these I’m gonna need Oasis help on, like, the PR stuff.
267 00:23:52.660 ⇒ 00:23:56.239 Henry Zhao: So… I can assign it to a wish after I’m done.
268 00:23:56.720 ⇒ 00:23:58.429 Henry Zhao: So he gets the credit for it, but…
269 00:24:04.650 ⇒ 00:24:13.690 Amber Lin: I don’t think we care that much about the credit, but I don’t… I just want… I just… which has capacity, and you are so busy today, because you have…
270 00:24:13.820 ⇒ 00:24:15.500 Amber Lin: The… this…
271 00:24:15.500 ⇒ 00:24:20.889 Henry Zhao: The thing is, I need Oasis to, like, confirm a lot of these things and get PR requests and things like that.
272 00:24:21.370 ⇒ 00:24:29.819 Amber Lin: Okay, okay. I mean, as long as we can get these done today… Okay, 6 minutes left…
273 00:24:33.700 ⇒ 00:24:38.959 Henry Zhao: But yeah, what I really need right now is the help on the documentation stuff with,
274 00:24:39.210 ⇒ 00:24:41.689 Henry Zhao: Like, all… where all of our data’s coming from.
275 00:24:42.000 ⇒ 00:24:43.460 Henry Zhao: Because that’s going to be vital for.
276 00:24:43.460 ⇒ 00:24:48.929 Awaish Kumar: So, we already, so, like, we already have a documentation, like, we have a Google Sheet.
277 00:24:49.050 ⇒ 00:24:53.180 Awaish Kumar: If you go in there, like, I can share it with you afterwards.
278 00:24:53.240 ⇒ 00:24:54.769 Henry Zhao: So it basically has…
279 00:24:54.770 ⇒ 00:24:58.449 Awaish Kumar: All these sources and what data is coming from there.
280 00:24:58.580 ⇒ 00:25:16.510 Awaish Kumar: For marketing work, we are missing that, because, like, I know, like, we are using Northbeam for marketing, but how we are doing attribution on Northbeam, so we haven’t been doing it until, like, you and Zoran or Andrew came and the team.
281 00:25:16.640 ⇒ 00:25:20.950 Awaish Kumar: So now, like, you three have worked on that, so… I have created a…
282 00:25:22.450 ⇒ 00:25:25.579 Awaish Kumar: So, I have created a Notion database.
283 00:25:25.690 ⇒ 00:25:30.890 Awaish Kumar: For the client, Eden. It’s called, like, Marketing, Taking, and Tracking, and…
284 00:25:31.080 ⇒ 00:25:41.479 Awaish Kumar: And basically, I have put some placeholder pages, but these are, like, if you can… if you, or, like, if you can, like, ask.
285 00:25:41.600 ⇒ 00:25:49.410 Awaish Kumar: Zoran or Andrew, whoever worked on it, to, like, fill in the details. Like, for example, not real pixel.
286 00:25:49.770 ⇒ 00:26:07.270 Awaish Kumar: how they are using it, and how the traditional logic works there. And same for, like, different other platforms, how CIO is set up, like, if you are, pushing, like, multiple models into CIO, then what these different models are, and
287 00:26:07.430 ⇒ 00:26:10.280 Awaish Kumar: how they are set up, or configured, and CIO, like.
288 00:26:10.480 ⇒ 00:26:12.599 Awaish Kumar: These kind of things we are missing right now.
289 00:26:13.820 ⇒ 00:26:23.499 Henry Zhao: Okay, but just the important question is to confirm, right now we do not have every Trident page view being sent to BigQuery from Segment, correct?
290 00:26:25.530 ⇒ 00:26:32.209 Awaish Kumar: Like… So, for that, we… basically, we do have… we have a…
291 00:26:32.930 ⇒ 00:26:36.710 Awaish Kumar: connected and segment. I have shared the link in the… in my message.
292 00:26:36.890 ⇒ 00:26:42.459 Awaish Kumar: If you click that, we can see that we are getting a lot of different
293 00:26:43.100 ⇒ 00:26:46.929 Awaish Kumar: like, events data from… they tried in, like.
294 00:26:47.230 ⇒ 00:27:03.860 Awaish Kumar: website, right? So, it can be a click, or it can be a page view, or it can be anything, right? So that is coming to us. So, I’m just saying that the page views are coming to different… from two different sources. We are getting it from segment.
295 00:27:03.980 ⇒ 00:27:07.340 Awaish Kumar: And we are also getting it from GF4.
296 00:27:07.620 ⇒ 00:27:09.479 Henry Zhao: I don’t think we should be getting it from J4.
297 00:27:09.800 ⇒ 00:27:19.729 Awaish Kumar: like… but, like, we are, like, basically… last time I worked with GF4 data, I see there are some events called GF page views, and that’s basically…
298 00:27:19.730 ⇒ 00:27:27.090 Henry Zhao: I’m just saying, we might want to turn that off. I think if we’re implementing edge layer and server side, we probably want to do some segment.
299 00:27:27.480 ⇒ 00:27:29.840 Henry Zhao: Or whatever pixel that Zoran implements.
300 00:27:29.840 ⇒ 00:27:34.529 Awaish Kumar: That’s, like, that is for someone who is maintaining GF4, like, I…
301 00:27:34.880 ⇒ 00:27:36.810 Awaish Kumar: Like, it can be maybe Zoran.
302 00:27:37.060 ⇒ 00:27:38.400 Awaish Kumar: To, to pause it.
303 00:27:38.650 ⇒ 00:27:41.409 Henry Zhao: Okay, I will… I will talk to Saran right after this. We have a meeting.
304 00:27:44.540 ⇒ 00:27:45.760 Amber Lin: I have…
305 00:27:45.760 ⇒ 00:27:48.939 Awaish Kumar: We can basically work together on, like, if you wanna…
306 00:27:49.220 ⇒ 00:28:07.099 Awaish Kumar: debug more onto data, like, coming from segment. We can just go into the Webflow dataset in the BigQuery and see, like, what different event… events are coming in, and if we are capturing all the page views, or if we are missing any sequence, or what.
307 00:28:08.830 ⇒ 00:28:09.430 Henry Zhao: Okay.
308 00:28:12.460 ⇒ 00:28:18.140 Henry Zhao: Another one I wanted to go over, Amber, is there’s one that’s the actuals dashboard. Can you open that one?
309 00:28:18.830 ⇒ 00:28:22.489 Amber Lin: That is… That one.
310 00:28:22.630 ⇒ 00:28:23.640 Amber Lin: Yes.
311 00:28:23.640 ⇒ 00:28:29.519 Henry Zhao: I do want to double check that this is pretty much done, I just need to make sure that all the stuff that Annie put in is working, right?
312 00:28:31.320 ⇒ 00:28:32.880 Amber Lin: A lot of things.
313 00:28:33.970 ⇒ 00:28:36.459 Henry Zhao: Non-modeling stuff is done, but the modeling stuff.
314 00:28:36.570 ⇒ 00:28:41.589 Henry Zhao: was needed to be done, which was pause, and then Milati finished the modeling part. So I just needed.
315 00:28:41.590 ⇒ 00:28:42.320 Amber Lin: Yes.
316 00:28:43.230 ⇒ 00:28:48.389 Amber Lin: Yeah, just the part that needs modeling, which I don’t know which one… which part that is.
317 00:28:48.790 ⇒ 00:28:52.390 Henry Zhao: Okay, so leave us two points, and I might downgrade it to one, if it’s all good.
318 00:28:52.610 ⇒ 00:29:11.050 Amber Lin: Okay, okay, sounds good. I have a question, because right now, we have these for today, because the first one’s a data poll, he wants it today. The second one is pretty important, because that’s the breaking it down by the Aspen channels.
319 00:29:11.610 ⇒ 00:29:12.310 Henry Zhao: helpful.
320 00:29:13.960 ⇒ 00:29:15.220 Amber Lin: 903.
321 00:29:16.870 ⇒ 00:29:18.780 Amber Lin: OS, do you know Tableau?
322 00:29:19.730 ⇒ 00:29:20.490 Awaish Kumar: God, no.
323 00:29:21.310 ⇒ 00:29:21.780 Henry Zhao: No, I can do it.
324 00:29:22.630 ⇒ 00:29:22.990 Amber Lin: Okay.
325 00:29:23.230 ⇒ 00:29:25.389 Henry Zhao: This is blocked based on the modeling, right?
326 00:29:25.390 ⇒ 00:29:28.750 Amber Lin: Yeah, but I think that will be done very soon.
327 00:29:28.930 ⇒ 00:29:31.120 Amber Lin: Because we… we just need to merge it.
328 00:29:32.260 ⇒ 00:29:36.090 Amber Lin: And then you have a meeting with Zora to send a message.
329 00:29:36.420 ⇒ 00:29:41.400 Amber Lin: And then… maybe I can move… I think I’ll move… borrow.
330 00:29:41.630 ⇒ 00:29:42.200 Amber Lin: Sorry?
331 00:29:42.580 ⇒ 00:29:46.820 Henry Zhao: Make it tomorrow, but I’ll finish it today. Because them ladder sent me the join, I just need to fix it.
332 00:29:50.900 ⇒ 00:29:58.970 Amber Lin: I just… I just think you have so much work to do today. I feel like we should move one or two to tomorrow.
333 00:29:58.970 ⇒ 00:30:01.950 Henry Zhao: Plus, a lot of these are just messages and meetings, so I can do those.
334 00:30:02.280 ⇒ 00:30:04.640 Henry Zhao: Like, simultaneously, so… No, don’t worry.
335 00:30:04.640 ⇒ 00:30:08.219 Amber Lin: We’ll see you tomorrow. Okay, okay. I’m just worried, but we’ll see tomorrow, then.
336 00:30:08.220 ⇒ 00:30:09.949 Henry Zhao: What’s the Clutter Brad one, real quick?
337 00:30:10.700 ⇒ 00:30:16.679 Amber Lin: That one is the drop-down filter that he just sent.
338 00:30:16.680 ⇒ 00:30:19.080 Henry Zhao: You need to add a filter once Demade finishes the modeling, right?
339 00:30:19.080 ⇒ 00:30:19.740 Amber Lin: Yeah.
340 00:30:20.020 ⇒ 00:30:21.249 Henry Zhao: I appreciate you too.
341 00:30:21.250 ⇒ 00:30:27.599 Awaish Kumar: For the… I’m seeing two different PRs from Hani,
342 00:30:28.180 ⇒ 00:30:35.519 Awaish Kumar: Like, one is for CIO, I understand. The other one, do you need my review on it, or… I don’t know why.
343 00:30:35.790 ⇒ 00:30:37.770 Henry Zhao: The other one you already reviewed, so…
344 00:30:37.770 ⇒ 00:30:40.699 Awaish Kumar: There’s one for CIO also, right?
345 00:30:41.250 ⇒ 00:30:44.239 Henry Zhao: These are both for CIO. They’re both for CIO… they’re both the same thing, basically.
346 00:30:45.010 ⇒ 00:30:46.759 Awaish Kumar: When is this afternoon macro?
347 00:30:49.520 ⇒ 00:30:51.630 Awaish Kumar: Sorry, sorry, what is the other one for?
348 00:30:52.280 ⇒ 00:30:55.860 Henry Zhao: It’s the new macro for the standardized product names, which you guys told me to check.
349 00:30:55.860 ⇒ 00:30:59.649 Awaish Kumar: Oh, it’s just, it’s just a micro there, okay.
350 00:30:59.930 ⇒ 00:31:04.540 Awaish Kumar: Okay, it was okay to… we could have pushed it in the same PR, but…
351 00:31:04.710 ⇒ 00:31:08.270 Awaish Kumar: That’s okay. I will just, review it now.
352 00:31:10.830 ⇒ 00:31:14.140 Henry Zhao: Okay, that way Bobby says no, then we will… we need to do that.
353 00:31:15.260 ⇒ 00:31:18.079 Amber Lin: Okay, sounds good.
354 00:31:18.080 ⇒ 00:31:24.520 Henry Zhao: Or actually, if Bobby says no, maybe I add it to the original standardized, where it’s like, oh, no, nevermind.
355 00:31:26.080 ⇒ 00:31:27.330 Henry Zhao: That’s probably overcomplicated.
356 00:31:28.170 ⇒ 00:31:28.960 Amber Lin: Okay.
357 00:31:29.570 ⇒ 00:31:38.949 Amber Lin: And then, let me know what Joran’s task will look like. Also, we’ll need… when you guys need, I would need a, estimate.
358 00:31:39.600 ⇒ 00:31:43.630 Amber Lin: I don’t know that account, by the way.
359 00:31:44.140 ⇒ 00:31:49.170 Amber Lin: Does anyone know… That…
360 00:31:50.530 ⇒ 00:31:52.600 Henry Zhao: I’m gonna meet with.
361 00:31:54.510 ⇒ 00:31:56.829 Amber Lin: Let me grab Matt Schwartz.
362 00:31:57.030 ⇒ 00:31:59.660 Amber Lin: In the channel, I don’t know him.
363 00:31:59.850 ⇒ 00:32:03.100 Henry Zhao: Okay. Okay, that’s all.
364 00:32:03.660 ⇒ 00:32:05.390 Amber Lin: At Matt…
365 00:32:08.430 ⇒ 00:32:09.300 Amber Lin: Hmm?
366 00:32:10.190 ⇒ 00:32:11.310 Amber Lin: Okay.
367 00:32:13.360 ⇒ 00:32:15.290 Amber Lin: Alright, thank you guys so much.
368 00:32:15.670 ⇒ 00:32:16.989 Henry Zhao: You guys, take care.
369 00:32:16.990 ⇒ 00:32:17.910 Amber Lin: Alright, bye!
370 00:32:17.910 ⇒ 00:32:19.300 Demilade Agboola: Thank you, bye.