Meeting Title: [Eden] Daily Standup Date: 2025-10-01 Meeting participants: Fireflies.ai Notetaker Joshua, Henry Zhao, Demilade Agboola, Awaish Kumar, Amber Lin
WEBVTT
1 00:05:39.580 ⇒ 00:05:40.390 Amber Lin: Peter.
2 00:05:41.140 ⇒ 00:05:43.570 Amber Lin: Good morning.
3 00:05:46.170 ⇒ 00:05:47.050 Awaish Kumar: By the way.
4 00:05:49.520 ⇒ 00:05:50.590 Amber Lin: I want to…
5 00:05:56.490 ⇒ 00:06:00.769 Amber Lin: So… That is for the source.
6 00:06:03.220 ⇒ 00:06:05.060 Amber Lin: Okay.
7 00:06:05.600 ⇒ 00:06:14.760 Amber Lin: Question first here, can we cancel the… These tickets?
8 00:06:15.130 ⇒ 00:06:17.030 Amber Lin: for TikTok setup.
9 00:06:18.750 ⇒ 00:06:21.410 Awaish Kumar: I… yeah, for…
10 00:06:22.160 ⇒ 00:06:25.360 Amber Lin: This question, even for Henry, is that, like.
11 00:06:26.140 ⇒ 00:06:34.739 Awaish Kumar: But TikTok is spiking. I understood from, Qatar’s conversation was that we want to reverse ETL, but then you mentioned that we
12 00:06:34.920 ⇒ 00:06:51.280 Awaish Kumar: basically are tracking it through the UTM, the attribution, and then it will come into our orders data with UTM source as TikTok, right? We don’t need to do any extra reverse detailing there.
13 00:06:51.280 ⇒ 00:06:52.209 Henry Zhao: Yeah, I don’t think so.
14 00:06:53.400 ⇒ 00:06:53.850 Amber Lin: Okay.
15 00:06:53.850 ⇒ 00:07:04.300 Awaish Kumar: Okay, but, like, Ayush… So… For the TikTok, how… So, any…
16 00:07:05.230 ⇒ 00:07:08.160 Awaish Kumar: from… we are using TikTok ads, and…
17 00:07:09.090 ⇒ 00:07:15.959 Awaish Kumar: and somebody clicks on this, and then it gets converted, and we get from Luteum sources TikTok.
18 00:07:16.850 ⇒ 00:07:25.789 Awaish Kumar: And you are saying we, would not be missing any… like, what Carter said, basically, was that, we are…
19 00:07:25.910 ⇒ 00:07:36.480 Awaish Kumar: Basically, overly… like… Marking them as… Coming from…
20 00:07:36.910 ⇒ 00:07:44.280 Awaish Kumar: like TikTok, like, I don’t know. But he said something like that. On TikTok, he sees that there’s a lot more conversions where it is.
21 00:07:44.280 ⇒ 00:07:45.030 Amber Lin: All the others.
22 00:07:46.230 ⇒ 00:07:47.860 Henry Zhao: Say that last sentence again?
23 00:07:48.260 ⇒ 00:07:54.749 Awaish Kumar: Yeah, like, for TikTok, like, he said the platform shows a lot more conversion than there really is.
24 00:07:54.750 ⇒ 00:07:55.780 Amber Lin: Pretty good.
25 00:07:55.780 ⇒ 00:07:58.209 Awaish Kumar: For example, if TikTok shows, like, we have
26 00:08:00.200 ⇒ 00:08:08.160 Awaish Kumar: like, 100 conversions from TikTok, but actually we only had maybe 20 real orders, something like that.
27 00:08:08.160 ⇒ 00:08:10.469 Henry Zhao: Yeah, that’s what the data stitching will do.
28 00:08:11.410 ⇒ 00:08:14.100 Henry Zhao: Yeah, we don’t need any reverse ETL at this point.
29 00:08:14.590 ⇒ 00:08:16.740 Henry Zhao: Because Zaran will be sending me that data.
30 00:08:17.630 ⇒ 00:08:18.550 Henry Zhao: Through the internet.
31 00:08:18.550 ⇒ 00:08:32.799 Awaish Kumar: I mentioned that when we stitched that, in the orders data, we could easily see that, right? How many orders were actually converted. But the thing is that, do we want to upload that data to somewhere, or we don’t need to, by now?
32 00:08:32.970 ⇒ 00:08:35.690 Henry Zhao: We don’t need to. Ken, when we have the data.
33 00:08:35.880 ⇒ 00:08:36.690 Awaish Kumar: Yeah.
34 00:08:37.500 ⇒ 00:08:39.239 Amber Lin: So I’ll close the spike.
35 00:08:39.559 ⇒ 00:08:52.310 Amber Lin: So mark it as done. Yeah. And then… that’s blocked. I noted that Allison will give us that, I just haven’t heard… I haven’t checked this morning yet. So we have…
36 00:08:53.270 ⇒ 00:08:58.619 Amber Lin: This one. So this one, do you have context?
37 00:08:59.500 ⇒ 00:09:11.159 Awaish Kumar: I just want to know, like, I just have… I’m just a little bit concerned about the data we have, spend data, for example.
38 00:09:12.210 ⇒ 00:09:16.810 Awaish Kumar: For an account ID. So, in the product sales summary, we have data for a product.
39 00:09:17.160 ⇒ 00:09:17.710 Henry Zhao: Huh, yep.
40 00:09:17.710 ⇒ 00:09:26.199 Awaish Kumar: When I… if I’m for a product, same… is it the same product on… being advertised on different account IDs?
41 00:09:26.840 ⇒ 00:09:29.150 Henry Zhao: If we want to make this a separate table, that’s fine too.
42 00:09:30.550 ⇒ 00:09:32.089 Henry Zhao: If we want to not interfere.
43 00:09:32.090 ⇒ 00:09:44.529 Awaish Kumar: We want a separate table, but then what is the… then I would need exact modeling requirements. What… what fields do you need in that table, and what is the purpose of that table, and things like that.
44 00:09:44.960 ⇒ 00:09:49.140 Henry Zhao: Yeah, I also wonder why he can’t just look at this in Ads Manager,
45 00:09:50.600 ⇒ 00:09:52.439 Henry Zhao: Let me talk to Kumar about this.
46 00:09:53.880 ⇒ 00:09:55.700 Awaish Kumar: It is grooming, so yeah.
47 00:09:56.210 ⇒ 00:09:56.800 Henry Zhao: Cuz…
48 00:09:57.090 ⇒ 00:10:01.249 Henry Zhao: Because if he just wants to look at BM Digital Campaigns, he should probably just look into Ads Manager, right?
49 00:10:02.280 ⇒ 00:10:03.380 Henry Zhao: What do you guys think?
50 00:10:03.580 ⇒ 00:10:12.510 Awaish Kumar: Yeah, yeah, he can look into it, but he wanted to add in production summary. I don’t know why, right? We need to understand the reason behind that.
51 00:10:14.060 ⇒ 00:10:19.279 Amber Lin: I know that he wants to see it in the ROAS, Prada ROAS dashboard,
52 00:10:19.410 ⇒ 00:10:22.029 Amber Lin: But I… that’s as far as I know.
53 00:10:22.030 ⇒ 00:10:24.319 Henry Zhao: But, but why? Yeah, I want to know why.
54 00:10:24.820 ⇒ 00:10:25.950 Henry Zhao: Like, he didn’t give me much content.
55 00:10:25.950 ⇒ 00:10:30.449 Awaish Kumar: In the product, like, my only concern is that then the…
56 00:10:30.750 ⇒ 00:10:34.380 Awaish Kumar: Like, the current table structure is in a format that
57 00:10:34.830 ⇒ 00:10:39.769 Awaish Kumar: We’ll complicate things, maybe. Or maybe we need to add more,
58 00:10:40.370 ⇒ 00:10:46.420 Awaish Kumar: We will have… how to take… take a few things from the Tableau side and the Internet side, like, it will…
59 00:10:46.620 ⇒ 00:10:52.190 Awaish Kumar: Just to require more work, and without any reasoning, we don’t want to do it.
60 00:10:52.190 ⇒ 00:10:54.460 Henry Zhao: I agree with you guys, so I’m gonna talk to him.
61 00:10:55.060 ⇒ 00:11:01.650 Henry Zhao: and see, see what the best way forward is. So you could put this as blocked for now, Amber, or need stakeholder response.
62 00:11:02.780 ⇒ 00:11:03.570 Amber Lin: Okay.
63 00:11:06.910 ⇒ 00:11:07.940 Amber Lin: Alright.
64 00:11:09.450 ⇒ 00:11:16.060 Amber Lin: So, OWISH has… This one was just not high priority, and the cons.
65 00:11:16.240 ⇒ 00:11:19.999 Amber Lin: the other stuff is blocked. Yeah. So let’s go look at the…
66 00:11:20.000 ⇒ 00:11:25.280 Henry Zhao: Awish has bandwidth, there’s, yeah, there’s urgent modeling needs that we can give to a wish.
67 00:11:25.510 ⇒ 00:11:29.590 Amber Lin: Oh, okay. Where are the urgent modelers?
68 00:11:29.590 ⇒ 00:11:33.180 Henry Zhao: Like, 974. Can you move 974 to urgent? Yeah.
69 00:11:33.420 ⇒ 00:11:34.560 Amber Lin: Yeah.
70 00:11:34.940 ⇒ 00:11:36.440 Henry Zhao: Brad’s been asking me about it.
71 00:11:36.440 ⇒ 00:11:37.040 Amber Lin: Oof.
72 00:11:37.150 ⇒ 00:11:38.060 Amber Lin: Okay.
73 00:11:38.060 ⇒ 00:11:38.610 Awaish Kumar: List.
74 00:11:39.640 ⇒ 00:11:43.580 Amber Lin: okay, Melody, how’s progress?
75 00:11:44.220 ⇒ 00:11:45.919 Amber Lin: For yesterday.
76 00:11:48.850 ⇒ 00:11:52.739 Demilade Agboola: So Progress on Yesterday is…
77 00:11:54.710 ⇒ 00:12:02.429 Demilade Agboola: We handled the ad hoc stuff, so that was… that’s done. I started 9-7-1, so 971 is in progress.
78 00:12:05.240 ⇒ 00:12:08.280 Amber Lin: Is there some epox tickets I didn’t capture?
79 00:12:09.670 ⇒ 00:12:15.159 Demilade Agboola: There’s just stuff around the dashboard issues yesterday that we had the emergency call about.
80 00:12:15.710 ⇒ 00:12:25.660 Demilade Agboola: that… because Cutter was, like, the dashboards are not adding up, there was just a whole conversation about that, so there was that. Also…
81 00:12:26.390 ⇒ 00:12:36.519 Demilade Agboola: 963, I don’t necessarily see… I don’t actually understand the ticket, it appears the dashboard seems.
82 00:12:36.520 ⇒ 00:12:39.629 Amber Lin: Oh, I see, this is… this is the dashboarding.
83 00:12:40.770 ⇒ 00:12:50.410 Amber Lin: forwarding errors. This was what you worked on, so the cutter said, oh, these two were, like, separated, and then…
84 00:12:50.930 ⇒ 00:12:56.370 Amber Lin: So, essentially, he was like, oh, injectable, there was a combined simmer, and then there was, like.
85 00:12:56.370 ⇒ 00:12:58.240 Demilade Agboola: Yeah, so this is done normally.
86 00:12:58.240 ⇒ 00:12:58.680 Amber Lin: That’s what you were…
87 00:12:58.680 ⇒ 00:12:59.449 Demilade Agboola: This is all fine.
88 00:12:59.450 ⇒ 00:13:00.260 Amber Lin: Okay.
89 00:13:00.610 ⇒ 00:13:02.740 Amber Lin: So I’ll say this is done.
90 00:13:03.750 ⇒ 00:13:13.010 Demilade Agboola: And then… So today, just trying to finish up 971, as well as 974.
91 00:13:13.230 ⇒ 00:13:21.569 Amber Lin: Okay, do you think 974, we can move to a wish? In a wish, what do you think? I think this is…
92 00:13:21.730 ⇒ 00:13:24.849 Amber Lin: Small stuff left?
93 00:13:26.340 ⇒ 00:13:28.000 Henry Zhao: I think my first line…
94 00:13:28.210 ⇒ 00:13:29.270 Amber Lin: got…
95 00:13:29.270 ⇒ 00:13:31.969 Awaish Kumar: And I can basically click it, no problem.
96 00:13:32.290 ⇒ 00:13:37.340 Henry Zhao: Amber, can you just add my first line back? It was, add these columns to order summary table.
97 00:13:38.090 ⇒ 00:13:39.610 Amber Lin: Let me…
98 00:13:41.930 ⇒ 00:13:44.589 Awaish Kumar: Auto status?
99 00:13:44.790 ⇒ 00:13:49.789 Amber Lin: Add wood to order some rain table… add what?
100 00:13:49.790 ⇒ 00:13:51.050 Henry Zhao: Yeah, those 3 columns.
101 00:13:51.300 ⇒ 00:13:52.610 Amber Lin: Oh, oh, okay.
102 00:13:53.730 ⇒ 00:14:03.599 Awaish Kumar: So, order status, we should already have, and then we have delivery status. But, like, don’t… like, what is the pharmacy status?
103 00:14:04.960 ⇒ 00:14:09.040 Henry Zhao: That’s… yeah, I don’t know, but it’s from the orders report in Basque.
104 00:14:09.630 ⇒ 00:14:22.689 Awaish Kumar: Yes, but, like, when we have the status, we are saying, like, this is pending abandoned, or it’s in the center of messy, or where it is, so we already have all these things.
105 00:14:24.400 ⇒ 00:14:27.049 Henry Zhao: Let me share with you what those values should be.
106 00:14:27.300 ⇒ 00:14:27.990 Henry Zhao: We can double check.
107 00:14:28.890 ⇒ 00:14:34.420 Demilade Agboola: Because also, some of the things available in the Basque Web UI are not available via the.
108 00:14:34.420 ⇒ 00:14:35.370 Henry Zhao: Oh, really?
109 00:14:35.790 ⇒ 00:14:36.969 Henry Zhao: Oh, wow. Yeah.
110 00:14:38.790 ⇒ 00:14:47.719 Henry Zhao: So I will share with you, Awash, the orders report that Brad and Katie look at, and you can just check if those are there, available in the webhook.
111 00:14:47.990 ⇒ 00:14:49.960 Henry Zhao: If not, we have to push back and just say.
112 00:14:50.260 ⇒ 00:14:50.960 Awaish Kumar: Yeah.
113 00:14:50.960 ⇒ 00:14:54.960 Henry Zhao: Like, yeah, if that ticket needs grooming, then.
114 00:14:54.960 ⇒ 00:14:56.730 Awaish Kumar: Amber. Ultra.
115 00:14:58.330 ⇒ 00:15:00.739 Henry Zhao: But this meeting is the grooming meeting, right?
116 00:15:00.740 ⇒ 00:15:05.370 Amber Lin: Yeah, partly, yes. So, let’s say… .
117 00:15:05.550 ⇒ 00:15:14.510 Awaish Kumar: So we wanna… Groom it, and along with the other ticket, and maybe we can see others as well.
118 00:15:14.900 ⇒ 00:15:20.460 Amber Lin: see if Katie’s… Pretty important.
119 00:15:20.950 ⇒ 00:15:32.670 Amber Lin: That’s what… Data is in the… Bask… webhook.
120 00:15:33.570 ⇒ 00:15:35.959 Amber Lin: If yes, we would push back.
121 00:15:37.690 ⇒ 00:15:48.359 Awaish Kumar: No, no, first of all, it needs grooming, like, what is needed, right? And, yeah, what you’re writing is okay also. Yeah. And then…
122 00:15:48.590 ⇒ 00:15:49.740 Awaish Kumar: Don’t even know if he…
123 00:15:49.740 ⇒ 00:15:53.130 Demilade Agboola: Yes, we will do the task, but if no, we will push back.
124 00:15:53.130 ⇒ 00:15:53.730 Awaish Kumar: Goodbye.
125 00:15:54.040 ⇒ 00:15:54.730 Amber Lin: Hmm.
126 00:15:55.490 ⇒ 00:15:56.530 Amber Lin: I see.
127 00:15:59.180 ⇒ 00:16:00.120 Amber Lin: Okay.
128 00:16:01.200 ⇒ 00:16:02.530 Amber Lin: So…
129 00:16:06.430 ⇒ 00:16:09.730 Amber Lin: And then, Henry, you would send the KD’s report, right?
130 00:16:09.730 ⇒ 00:16:11.660 Henry Zhao: Yep, I’m already gonna send it around now.
131 00:16:15.000 ⇒ 00:16:16.310 Henry Zhao: What the heck happened out here?
132 00:16:29.360 ⇒ 00:16:30.360 Amber Lin: We’ll see.
133 00:16:30.720 ⇒ 00:16:46.109 Amber Lin: Alright. And then, remember yesterday from the meeting, there was the dual spend issue? Who is going to be tackling that? Or is that still something that we need to work on?
134 00:16:47.120 ⇒ 00:16:50.409 Demilade Agboola: what’s the door spend issue right now? I think that.
135 00:16:50.730 ⇒ 00:16:52.040 Demilade Agboola: Hold on one task.
136 00:16:52.380 ⇒ 00:16:57.869 Amber Lin: So yesterday, I think when Stuart, Cutter, and Matthias was talking.
137 00:16:58.320 ⇒ 00:17:05.159 Amber Lin: I think one of their websites, people were purchasing some things, but they’re…
138 00:17:05.160 ⇒ 00:17:07.490 Awaish Kumar: That’s alright.
139 00:17:07.490 ⇒ 00:17:08.579 Amber Lin: different thing.
140 00:17:10.410 ⇒ 00:17:16.579 Demilade Agboola: Yes, but I thought it was based off what they had set up in their… Atlas.
141 00:17:16.839 ⇒ 00:17:19.529 Demilade Agboola: These things were being pushed as…
142 00:17:21.210 ⇒ 00:17:30.100 Demilade Agboola: it was being categorized, but it basically was based on how they had set up the catalyst, not necessarily what we need to do. I just want to clarify.
143 00:17:30.100 ⇒ 00:17:30.860 Awaish Kumar: Yeah, brother.
144 00:17:31.480 ⇒ 00:17:37.419 Awaish Kumar: That’s what I’m saying, like, the… from our team, Henry and Zoran are helping them with the…
145 00:17:37.630 ⇒ 00:17:40.559 Awaish Kumar: attribution, right? That seems like…
146 00:17:41.880 ⇒ 00:17:52.079 Awaish Kumar: From in-tech forms, then it goes to pages which are not really the… the… for that product, so things like that.
147 00:17:53.060 ⇒ 00:17:56.960 Awaish Kumar: They can better respond on this.
148 00:17:57.810 ⇒ 00:17:58.630 Amber Lin: Hmm.
149 00:17:59.040 ⇒ 00:18:09.380 Amber Lin: I… from my understanding, I thought yesterday they said this was something that we need to help them on. Henry, did… I mean, did I hear it correctly? I might have just… I might have just…
150 00:18:09.380 ⇒ 00:18:21.079 Henry Zhao: I think they maybe just wanted us to make sure… I don’t know. Yeah, I think Demlade asked if we need to do it, like, backfill any data. I don’t know what they responded. Demlade, do you remember when you asked what they said?
151 00:18:21.220 ⇒ 00:18:23.050 Henry Zhao: They want us to fix it.
152 00:18:23.050 ⇒ 00:18:27.340 Demilade Agboola: Yeah, so… yeah, so cause the… the… the spend…
153 00:18:28.260 ⇒ 00:18:40.760 Demilade Agboola: has been attributed to, to TES, and TES is not one of the things that they had set up. I’m like, do you want us to change the spend back to SEMA? And they’re like, no, we should leave it that way. So…
154 00:18:40.760 ⇒ 00:18:41.290 Henry Zhao: Okay.
155 00:18:41.290 ⇒ 00:18:44.979 Demilade Agboola: So that’s why I’m like, I’m not sure what the task is here.
156 00:18:45.870 ⇒ 00:18:47.690 Henry Zhao: Okay, leave it that way, then I think we’re good.
157 00:18:48.150 ⇒ 00:18:49.740 Henry Zhao: We can cancel this one.
158 00:18:51.140 ⇒ 00:19:01.470 Amber Lin: Okay. I… I’m just a little worried, because yesterday, they called us into the meeting. I thought it was just for a task, and then…
159 00:19:01.810 ⇒ 00:19:04.219 Henry Zhao: No, no, they called us to, like, keep us in the loop.
160 00:19:04.580 ⇒ 00:19:05.350 Amber Lin: I see.
161 00:19:05.350 ⇒ 00:19:13.889 Demilade Agboola: Yeah, and also, yeah, some of the numbers weren’t, like, adding up prior to, like, that meeting, so that’s part of what I worked on, so I was just ensuring that
162 00:19:14.120 ⇒ 00:19:24.339 Demilade Agboola: Because we had to duplicate affiliate spend, we had some issues going on, so I just fixed that, and then the meeting, we’re able to all get on the same page, and everything seems fine now.
163 00:19:24.340 ⇒ 00:19:26.150 Amber Lin: Okay, I see.
164 00:19:26.260 ⇒ 00:19:30.729 Amber Lin: Let’s look at tests here.
165 00:19:32.330 ⇒ 00:19:33.240 Awaish Kumar: Okay.
166 00:19:33.650 ⇒ 00:19:39.189 Amber Lin: Mama, do you know the require… do you know enough to do this ticket?
167 00:19:40.060 ⇒ 00:19:58.420 Demilade Agboola: Yes. So, I’m working on it. It’s basically adding pharmacy to the product sales summary by transactions. I will say, I think we need to add a ticket for just reworking product sales summary by transaction. Doesn’t have to… it doesn’t have to be… it’s medium priority, it’s not the most important thing right now.
168 00:19:58.420 ⇒ 00:19:59.529 Amber Lin: Let me…
169 00:19:59.530 ⇒ 00:20:00.190 Demilade Agboola: But…
170 00:20:00.540 ⇒ 00:20:01.930 Amber Lin: I think, like…
171 00:20:02.330 ⇒ 00:20:09.979 Demilade Agboola: As things are right now, it’s only going to get more, like, convoluted if we don’t, like, create an easy.
172 00:20:10.380 ⇒ 00:20:11.650 Amber Lin: 2…
173 00:20:12.040 ⇒ 00:20:13.170 Demilade Agboola: Three wall kits.
174 00:20:13.870 ⇒ 00:20:33.449 Awaish Kumar: similarity, like, we don’t need to add everything that they ask for in the product sales summary. We might create separate tables to support some of the work, because, like, if in product sales summary, if we add pharmacy, that means the revenue is going to be divided between pharmacies, but then spend doesn’t
175 00:20:34.020 ⇒ 00:20:38.720 Awaish Kumar: like, doesn’t make sense. Like, we are not spending based on is he?
176 00:20:39.100 ⇒ 00:20:42.630 Awaish Kumar: So, it doesn’t even make sense to be there.
177 00:20:43.670 ⇒ 00:20:54.080 Demilade Agboola: Yeah, so that’s… that’s part of why I said, like, we need to rework it, but, like, I agree, like, so for this task, I might end up just having to do a different model entirely, just to answer that.
178 00:20:54.250 ⇒ 00:20:56.459 Demilade Agboola: Because they just basically want to see.
179 00:20:57.030 ⇒ 00:20:58.030 Amber Lin: That’s why I’m gonna do.
180 00:20:58.030 ⇒ 00:21:01.329 Demilade Agboola: What’s going on. No, no, don’t cancel that one.
181 00:21:01.330 ⇒ 00:21:02.920 Amber Lin: Oh, okay.
182 00:21:02.920 ⇒ 00:21:05.569 Demilade Agboola: We still need… we still need SaaS to rework it.
183 00:21:06.010 ⇒ 00:21:07.250 Demilade Agboola: Because France…
184 00:21:07.250 ⇒ 00:21:09.679 Awaish Kumar: Yeah, ask his.
185 00:21:09.680 ⇒ 00:21:11.249 Demilade Agboola: But this is not…
186 00:21:11.630 ⇒ 00:21:13.450 Amber Lin: This is a different, like, this is…
187 00:21:14.120 ⇒ 00:21:23.979 Amber Lin: internal ticket, I suppose. What are we trying to do for when we rework it? Because I know that we’ve been adding quite a few stuff to it.
188 00:21:24.950 ⇒ 00:21:31.339 Demilade Agboola: Yeah, just cleaning up. So, for instance, we’re pointing to, like, our legacy… some legacy tables.
189 00:21:31.630 ⇒ 00:21:34.520 Demilade Agboola: We point to some of our newer tables, things like that.
190 00:21:34.990 ⇒ 00:21:49.810 Awaish Kumar: Yeah, to be, like, I already, when Vashti was here, we already tried, to add some intermediate table with him. I basically added a few, few of our
191 00:21:50.770 ⇒ 00:21:56.669 Awaish Kumar: CTs, which are in this table, are already… we already have them as intermediate tables as well.
192 00:21:56.780 ⇒ 00:22:00.599 Awaish Kumar: But we end up making a final, an extra
193 00:22:01.500 ⇒ 00:22:04.999 Awaish Kumar: table there, instead of, utilizing this because of some.
194 00:22:05.000 ⇒ 00:22:05.850 Amber Lin: Huh.
195 00:22:06.070 ⇒ 00:22:16.059 Awaish Kumar: channel level, channel feed, maybe, like, he was not able to add that, and then… But we can build on top of that, and then…
196 00:22:16.150 ⇒ 00:22:29.500 Awaish Kumar: create intermediate table, and finally create product sales summary. So one ticket is… is this reworking? Another ticket, what I meant was, regarding that pharmacy thing, whatever… whatever the requirement is.
197 00:22:29.520 ⇒ 00:22:36.550 Awaish Kumar: Based on that, we might create a ticket, and maybe for… to support that functionality, we might add a new table.
198 00:22:37.400 ⇒ 00:22:41.189 Awaish Kumar: But we might not add that into product sales summary itself.
199 00:22:41.620 ⇒ 00:22:42.290 Amber Lin: I see.
200 00:22:42.720 ⇒ 00:22:59.840 Amber Lin: It doesn’t specify we need to add to product sales summary, so whatever you guys think is the best, I’ll put as the requirements, because this is just… he needs this… he needs a duplicated dashboard. He doesn’t even need it in the original one, so we can totally make a new model and have it support his…
201 00:22:59.840 ⇒ 00:23:01.070 Demilade Agboola: Awesome.
202 00:23:02.160 ⇒ 00:23:03.570 Demilade Agboola: Did we discuss this?
203 00:23:05.040 ⇒ 00:23:13.050 Demilade Agboola: So, because Brad is focused… Brad is focused more on, supply chain, he doesn’t really care about… spend.
204 00:23:13.320 ⇒ 00:23:16.960 Demilade Agboola: So all the, like… All the, like.
205 00:23:17.560 ⇒ 00:23:27.949 Demilade Agboola: yeah, he just cares about how many orders, what pharmacies, what’s the… like, he doesn’t, like, his supply chain, so I could create a different model.
206 00:23:28.220 ⇒ 00:23:32.400 Demilade Agboola: That answers what he needs without having all the return on average.
207 00:23:32.400 ⇒ 00:23:33.170 Awaish Kumar: Wow.
208 00:23:33.540 ⇒ 00:23:50.199 Awaish Kumar: For that, maybe you could utilize one of our intermediate models, basically where we have all the data coming from orders. We already have there, right? Like, in the product sales summary, what we are doing is we are getting sales data and orders data and joining it.
209 00:23:50.200 ⇒ 00:23:59.530 Awaish Kumar: So whatever we are getting sales from sales data is already in those intermediate tables. Maybe you can utilize that, and maybe add in pharmacy fields there as well.
210 00:24:01.260 ⇒ 00:24:07.640 Demilade Agboola: Yeah, sure, but again, another issue would also be the pharmacy, should that, you know, has been flagged to be masked.
211 00:24:08.150 ⇒ 00:24:15.000 Demilade Agboola: So that would affect the quality of the report, but yeah, we can always do what we have so far and see, see how far that goes.
212 00:24:15.170 ⇒ 00:24:16.310 Awaish Kumar: Oh, okay.
213 00:24:19.920 ⇒ 00:24:24.659 Amber Lin: Okay, what, what intermediate model you said we were gonna use?
214 00:24:25.220 ⇒ 00:24:28.619 Awaish Kumar: I don’t remember the name, but, like… That’s fine.
215 00:24:28.620 ⇒ 00:24:30.870 Demilade Agboola: Oh, I’ll look into it. Yeah.
216 00:24:33.380 ⇒ 00:24:34.280 Amber Lin: Okay.
217 00:24:34.690 ⇒ 00:24:41.700 Amber Lin: I don’t know if it’s still 2 points or not. I’m gonna set this as high, but… is it 2 points?
218 00:24:43.940 ⇒ 00:24:46.699 Demilade Agboola: I’ll say it’s a simple 2, 2, or 3.
219 00:24:46.700 ⇒ 00:24:58.949 Amber Lin: Okay, okay. Yeah, let me know if it needs to be updated. And then I’ll say this is by end of week, or maybe next week. How many points does the rework take? How many hours?
220 00:24:59.890 ⇒ 00:25:02.069 Demilade Agboola: I would say about 3.
221 00:25:02.420 ⇒ 00:25:03.010 Amber Lin: Okay.
222 00:25:03.790 ⇒ 00:25:04.810 Demilade Agboola: Yeah.
223 00:25:05.120 ⇒ 00:25:10.300 Amber Lin: Okay, right. And then, Henry, on your side.
224 00:25:10.620 ⇒ 00:25:15.690 Amber Lin: These are blocked. Is this one… is this one done?
225 00:25:15.690 ⇒ 00:25:19.979 Henry Zhao: No. That’s caused by one of the modeling tasks. I don’t think we talked about it, did we?
226 00:25:20.830 ⇒ 00:25:25.580 Amber Lin: Don’t? Oh. LTV and ProS?
227 00:25:25.580 ⇒ 00:25:26.710 Henry Zhao: Unassigned.
228 00:25:26.710 ⇒ 00:25:27.699 Amber Lin: Is it…
229 00:25:29.660 ⇒ 00:25:30.250 Amber Lin: No.
230 00:25:30.250 ⇒ 00:25:33.480 Demilade Agboola: What’s the… what’s the modeling task for that? What’s required for that?
231 00:25:33.790 ⇒ 00:25:34.310 Henry Zhao: What that?
232 00:25:34.310 ⇒ 00:25:35.000 Amber Lin: one…
233 00:25:35.000 ⇒ 00:25:39.839 Henry Zhao: We just need to add two more breakdowns. That one, wait, yes, wait, no.
234 00:25:39.840 ⇒ 00:25:41.280 Amber Lin: How am I about that one.
235 00:25:42.540 ⇒ 00:25:45.849 Demilade Agboola: I think rather catalyst spent, right? I think I wish I did that.
236 00:25:46.230 ⇒ 00:25:50.909 Henry Zhao: Yeah, it was total orders, and total or returning…
237 00:25:50.950 ⇒ 00:25:54.239 Amber Lin: Orders and customs.
238 00:25:54.240 ⇒ 00:25:59.730 Awaish Kumar: Like, do you mean, the, like, if you can go back to the…
239 00:25:59.730 ⇒ 00:26:00.300 Henry Zhao: Done.
240 00:26:00.300 ⇒ 00:26:01.620 Awaish Kumar: The host crew?
241 00:26:01.730 ⇒ 00:26:06.070 Awaish Kumar: And, if we can scroll up a little bit.
242 00:26:07.490 ⇒ 00:26:09.640 Amber Lin: Part of… Are you talking about…
243 00:26:09.640 ⇒ 00:26:10.520 Henry Zhao: That one, yeah, 97.
244 00:26:10.520 ⇒ 00:26:11.270 Awaish Kumar: 17.
245 00:26:11.270 ⇒ 00:26:11.810 Amber Lin: Bye.
246 00:26:11.810 ⇒ 00:26:14.190 Awaish Kumar: 972, and I… I just…
247 00:26:14.320 ⇒ 00:26:24.409 Awaish Kumar: I just… yeah, you added those. You can see that. But I didn’t edit total. What we now have is a new order count for offer and revenue.
248 00:26:25.450 ⇒ 00:26:30.080 Awaish Kumar: New customer count for offer and revenue, and then… returning…
249 00:26:30.080 ⇒ 00:26:35.939 Henry Zhao: Yeah, for total, I can just add them. Yeah, that’s why I said, or returning, yeah, I can add.
250 00:26:36.180 ⇒ 00:26:40.560 Awaish Kumar: For both, like, new and returning customer in order for both.
251 00:26:40.560 ⇒ 00:26:43.549 Henry Zhao: So, yeah. Yep, I can add. Okay, so this is ready for me to do.
252 00:26:43.550 ⇒ 00:26:46.520 Amber Lin: Okay, so this is how blocked, great.
253 00:26:46.990 ⇒ 00:26:50.869 Amber Lin: Is this still 4 hours for that one?
254 00:26:51.130 ⇒ 00:26:53.189 Henry Zhao: Yeah, I already spent three and a half hours on it, so…
255 00:26:53.190 ⇒ 00:26:57.960 Amber Lin: Gotcha. Okay, so I’ll say… I say, like, tomorrow…
256 00:26:58.240 ⇒ 00:27:01.450 Amber Lin: Thursday? Thursday? I’ll leave it tomorrow, yeah.
257 00:27:01.450 ⇒ 00:27:02.230 Henry Zhao: today.
258 00:27:03.250 ⇒ 00:27:06.350 Amber Lin: And… He says…
259 00:27:11.010 ⇒ 00:27:12.219 Henry Zhao: Yeah, I just haven’t done this yet.
260 00:27:12.400 ⇒ 00:27:13.299 Amber Lin: I see.
261 00:27:13.300 ⇒ 00:27:14.300 Henry Zhao: I look at it today.
262 00:27:15.050 ⇒ 00:27:15.740 Amber Lin: Okay.
263 00:27:15.740 ⇒ 00:27:17.920 Demilade Agboola: Just checking… Also, just a quick question.
264 00:27:18.830 ⇒ 00:27:21.109 Demilade Agboola: What’s… what’s blocking 935?
265 00:27:21.990 ⇒ 00:27:24.360 Amber Lin: 9… 3…
266 00:27:24.360 ⇒ 00:27:25.740 Demilade Agboola: Just to cut a spike.
267 00:27:26.790 ⇒ 00:27:32.710 Henry Zhao: Zaran’s… Zaron’s work on, the edge layer stuff.
268 00:27:45.800 ⇒ 00:27:50.259 Amber Lin: What specifically? You just need catalyst data in the edge layer, and then we can do it?
269 00:27:50.260 ⇒ 00:27:52.580 Henry Zhao: Then I need to stitch… do the… the segments.
270 00:27:53.170 ⇒ 00:27:55.070 Henry Zhao: So I would move… yeah, move this to cycle 18.
271 00:27:55.980 ⇒ 00:27:57.130 Henry Zhao: Not gonna happen this week.
272 00:27:57.130 ⇒ 00:27:58.199 Amber Lin: Yeah, I see.
273 00:27:58.200 ⇒ 00:28:00.189 Henry Zhao: And Scott already knows.
274 00:28:00.190 ⇒ 00:28:07.740 Amber Lin: Yeah, I remember you said so. Okay, and then we have… that’s in testing…
275 00:28:08.500 ⇒ 00:28:11.389 Amber Lin: This is low priority, I’ll let it be.
276 00:28:11.390 ⇒ 00:28:18.139 Henry Zhao: Is it, though, Wish, did you see the responses I made about the CIO directly to BigQuery? Did you have any additional concerns?
277 00:28:23.020 ⇒ 00:28:28.419 Awaish Kumar: No, I don’t, and the thing is that if we have the data in now in BigCary, so…
278 00:28:29.880 ⇒ 00:28:33.019 Henry Zhao: So we can… can we turn it off to send it… stop sending it to segment?
279 00:28:35.810 ⇒ 00:28:43.600 Awaish Kumar: So, like, when we have this CIO data in BigQuery, that means we have… We can…
280 00:28:45.550 ⇒ 00:28:51.450 Awaish Kumar: like, disconnect, like, the pause the connection in segment, but what I’m concerned is.
281 00:28:51.970 ⇒ 00:29:01.860 Awaish Kumar: about identity stitching that, is happening, or, like, like, that customer…
282 00:29:02.360 ⇒ 00:29:13.560 Awaish Kumar: enriched profile cable, for example. That is based on, for example, segment Productionify thing, and all that data
283 00:29:13.920 ⇒ 00:29:26.840 Awaish Kumar: Then, segment wouldn’t be able to, like, if some customer comes from a browser, and he didn’t log in, he didn’t do anything, but browser just…
284 00:29:27.110 ⇒ 00:29:32.379 Awaish Kumar: Based on cookies, we identify him if he comes back again, and maybe segment.
285 00:29:35.880 ⇒ 00:29:36.520 Amber Lin: Hmm?
286 00:29:37.470 ⇒ 00:29:39.309 Henry Zhao: Is he dropping, you guys?
287 00:29:39.310 ⇒ 00:29:42.560 Amber Lin: I lost him at if segment, and then…
288 00:29:42.560 ⇒ 00:29:43.240 Henry Zhao: I’ve seen it.
289 00:29:43.630 ⇒ 00:29:44.470 Amber Lin: Okay.
290 00:29:44.470 ⇒ 00:29:45.879 Henry Zhao: Oh, Wish, we can’t hear you anymore.
291 00:29:46.300 ⇒ 00:29:54.170 Awaish Kumar: But we don’t have that… Kind of implementation on our side for,
292 00:29:54.400 ⇒ 00:29:57.380 Awaish Kumar: for identity stitching. We can do this based on…
293 00:29:57.440 ⇒ 00:30:09.460 Awaish Kumar: email address, like, somebody comes in 3 times and uses the email, then we can connect them together. If he uses his phone number, we can connect them, and if we have user ID, we can connect it.
294 00:30:09.460 ⇒ 00:30:22.509 Awaish Kumar: But otherwise, we can’t. But Segment may be able to do it because of some identity staging algorithm, which basically, he can use IP addresses and browser signatures and cookies to figure that out.
295 00:30:22.510 ⇒ 00:30:25.680 Henry Zhao: I agree, but I think we can do it by based on the UTM campaigns.
296 00:30:27.910 ⇒ 00:30:28.630 Henry Zhao: Right?
297 00:30:31.010 ⇒ 00:30:37.189 Henry Zhao: Like, right now, we’re already analyzing email campaigns, but we’re not even using CIO data, we’re using the UTM campaign value.
298 00:30:37.610 ⇒ 00:30:38.320 Amber Lin: Huh.
299 00:30:39.110 ⇒ 00:30:46.000 Awaish Kumar: Yes, but that’s what I’m saying, like, if somebody… Like, comes through some…
300 00:30:46.780 ⇒ 00:30:50.269 Awaish Kumar: some… some links, right? Where we already have…
301 00:30:50.540 ⇒ 00:31:02.919 Awaish Kumar: way to add UTM campaign or something, then obviously we can use that. But that’s… that’s my point, like, if somebody does not give us things which we know, like.
302 00:31:05.210 ⇒ 00:31:21.629 Awaish Kumar: Like, he just… I come in, open a Basque website, right? Yeah. And then I come in after a week, and I then log in. You don’t know if I… when I visited first, but Segment might be able to do that based on my signature for the…
303 00:31:21.630 ⇒ 00:31:26.210 Awaish Kumar: My browser, and maybe cookie that was installed in the browser.
304 00:31:26.960 ⇒ 00:31:33.030 Henry Zhao: Yeah. The question is… that’s true, but the question is, is it worth spending Millions of events in segments.
305 00:31:33.030 ⇒ 00:31:36.269 Awaish Kumar: That’s… that’s not… that’s… I don’t know. I don’t think so.
306 00:31:37.140 ⇒ 00:31:51.229 Awaish Kumar: like, how, like, how… how much we will be missing? I don’t know. That’s… that’s the question for your answer, like, if we… if we ignore that part, and we say, okay, some, like, we will be using UTM campaigns, using…
307 00:31:51.440 ⇒ 00:32:04.090 Awaish Kumar: email, phone number, and user ID. Will we be able to identify the visits from customer for maybe, like, more than 90% of the customers? Can… will we be able to do that?
308 00:32:06.860 ⇒ 00:32:07.570 Henry Zhao: I don’t know.
309 00:32:07.890 ⇒ 00:32:12.049 Henry Zhao: Maybe we need to just give this proposal and see what ELT thinks.
310 00:32:12.350 ⇒ 00:32:13.100 Amber Lin: Thank you.
311 00:32:13.100 ⇒ 00:32:13.850 Awaish Kumar: Okay.
312 00:32:19.320 ⇒ 00:32:26.330 Awaish Kumar: Yeah, but we… we can figure that out, right? Like, we can see how many people who
313 00:32:26.720 ⇒ 00:32:27.550 Awaish Kumar: I don’t know.
314 00:32:30.800 ⇒ 00:32:31.890 Awaish Kumar: I got this one.
315 00:32:32.300 ⇒ 00:32:36.430 Awaish Kumar: That’s tough, sorry, I… I’m just collecting my notes,
316 00:32:37.690 ⇒ 00:32:45.319 Awaish Kumar: Yeah, how many people actually visit us if the order is completed and they’ve been done? Like, we can
317 00:32:45.700 ⇒ 00:32:49.629 Awaish Kumar: etched all that together, but the only problem… problem is with…
318 00:32:49.950 ⇒ 00:32:55.119 Awaish Kumar: Users who just visit and don’t do anything, and just leave, and then come back.
319 00:32:56.140 ⇒ 00:32:59.369 Awaish Kumar: If that’s really important or not, we just have to figure that out.
320 00:33:04.650 ⇒ 00:33:05.550 Awaish Kumar: Yep.
321 00:33:07.520 ⇒ 00:33:20.799 Amber Lin: Hi, I have one last question for the one minute we have. I am looking at here, so first, is… which ticket is this supportive?
322 00:33:20.900 ⇒ 00:33:23.099 Amber Lin: I know, Karen, you already responded.
323 00:33:24.210 ⇒ 00:33:25.330 Awaish Kumar: Yeah, that…
324 00:33:25.330 ⇒ 00:33:27.299 Henry Zhao: That was the one that we just talked about.
325 00:33:27.560 ⇒ 00:33:29.730 Henry Zhao: That was finished, and I just need to…
326 00:33:29.960 ⇒ 00:33:31.709 Amber Lin: Oh, great, awesome.
327 00:33:32.240 ⇒ 00:33:36.589 Amber Lin: So I’ll just… Put that screenshot in there.
328 00:33:38.300 ⇒ 00:33:47.569 Amber Lin: And then, I wish I saw your note on… That there’s no end up…
329 00:33:48.030 ⇒ 00:33:50.180 Amber Lin: What channel was this in?
330 00:33:50.500 ⇒ 00:33:57.369 Amber Lin: Marketing analytics? Yes. This one… Are we… Yep.
331 00:33:57.580 ⇒ 00:33:59.770 Amber Lin: It’s billed separately, though.
332 00:34:00.350 ⇒ 00:34:01.850 Amber Lin: So, do you mean you want…
333 00:34:01.850 ⇒ 00:34:02.560 Awaish Kumar: The opening is…
334 00:34:02.560 ⇒ 00:34:03.020 Amber Lin: added.
335 00:34:03.020 ⇒ 00:34:04.019 Awaish Kumar: If you’re open.
336 00:34:04.540 ⇒ 00:34:07.029 Awaish Kumar: if you open that Notion doc.
337 00:34:07.470 ⇒ 00:34:12.719 Awaish Kumar: We can see, like, there are 3 things we are talking about.
338 00:34:12.719 ⇒ 00:34:13.879 Amber Lin: Vimeo.
339 00:34:13.880 ⇒ 00:34:26.350 Awaish Kumar: When I… whenever we go to these data migration talks, Remo comes up, right? And I just want to keep that separate, because we already… we are already starting that as a separate project.
340 00:34:26.350 ⇒ 00:34:26.790 Amber Lin: It’s the same place.
341 00:34:26.790 ⇒ 00:34:34.689 Awaish Kumar: declined, so we don’t need to discuss that in meetings. So that’s… I’m just mentioning that in my
342 00:34:34.870 ⇒ 00:34:45.099 Awaish Kumar: status notes that we are not going to talk about that. Second and third, these are two projects which are going to support data migration work.
343 00:34:45.360 ⇒ 00:34:49.279 Awaish Kumar: That will include. That’s for Eden, that’s not for Raymond.
344 00:34:50.810 ⇒ 00:34:51.959 Awaish Kumar: If we can open.
345 00:34:51.969 ⇒ 00:35:06.279 Amber Lin: Gosh, okay, I see, I remember. So only Remo separate, the 2 and 3 is part of Eden. I got, I got that. Sorry, I think, I think Henry has to hop. I’ll include your task, as a ticket, so we track your work,
346 00:35:06.280 ⇒ 00:35:13.549 Awaish Kumar: These are projects, not just tickets. This one, the last one, I… yeah, I already added the tickets, so don’t…
347 00:35:13.550 ⇒ 00:35:14.070 Amber Lin: Oh, okay.
348 00:35:14.070 ⇒ 00:35:15.060 Awaish Kumar: Right.
349 00:35:15.060 ⇒ 00:35:20.740 Amber Lin: Alrighty, that’s all. We have, we have to jump, I think they’re in the other meeting.
350 00:35:21.220 ⇒ 00:35:21.980 Henry Zhao: Okay, bye.
351 00:35:21.980 ⇒ 00:35:23.009 Amber Lin: Alright, Joni’s off.
352 00:35:23.010 ⇒ 00:35:23.389 Demilade Agboola: Sounds great.
353 00:35:23.390 ⇒ 00:35:23.970 Amber Lin: I…