Meeting Title: [Eden] Standup and Weekly Sprint Retro-Planning Date: 2025-05-02 Meeting participants: Annie Yu, Demilade Agboola, Robert Tseng, Rob, Awaish Kumar
WEBVTT
1 00:03:48.270 ⇒ 00:03:49.090 Awaish Kumar: Such a.
2 00:03:51.210 ⇒ 00:03:52.200 rob: What’s old?
3 00:03:52.800 ⇒ 00:03:54.420 rob: How you doing, man?
4 00:04:06.380 ⇒ 00:04:13.070 rob: Hey? Demolante? I actually really only came in because I have questions for you and Robert so
5 00:04:15.090 ⇒ 00:04:16.699 rob: Can you hear me, de mulatti.
6 00:04:16.709 ⇒ 00:04:18.429 Demilade Agboola: Yes, we can. I’m all ears.
7 00:04:18.600 ⇒ 00:04:34.780 rob: Alright. So I was just curious, because Josh had a concern up that some of the new variants weren’t being categorized properly, and I know Robert said they should be, but I don’t see them on the list. So I was just wondering
8 00:04:35.280 ⇒ 00:04:39.940 rob: when the last time you synced up the product list was.
9 00:04:41.512 ⇒ 00:04:47.919 Demilade Agboola: Alright. So we we do have them in like theme products.
10 00:04:48.608 ⇒ 00:04:55.599 Demilade Agboola: But also what we do is that we look at the the product name coming in on the transaction.
11 00:04:55.970 ⇒ 00:04:58.669 rob: Okay, you’re looking at the bask product name.
12 00:04:58.670 ⇒ 00:05:00.239 Demilade Agboola: Yeah. And then we do we?
13 00:05:00.240 ⇒ 00:05:07.580 Demilade Agboola: Oh, okay, that assigns. It’s based off that. So like Ollie, for instance. It’s a it’s.
14 00:05:07.580 ⇒ 00:05:08.480 rob: Yeah, yeah.
15 00:05:08.852 ⇒ 00:05:13.699 Demilade Agboola: We use that to fend, like to assign it to Sama? Injectable Samar.
16 00:05:13.700 ⇒ 00:05:19.700 rob: Gotcha. Okay, that’s what I was curious about. That’s actually the only thing I had. So I’ll probably bounce. But
17 00:05:19.870 ⇒ 00:05:21.759 rob: that’s what I wanted to make sure of.
18 00:05:22.230 ⇒ 00:05:35.879 Demilade Agboola: Yeah, it’s all good. But obviously we also have like a a patch. So if we have new orders that come in that don’t fit any of our current reject rules, we it flags it, and we can kind of look at it and ensure that.
19 00:05:36.347 ⇒ 00:05:40.950 Demilade Agboola: We know what that new type is, and like we can converse with the Eden team.
20 00:05:41.710 ⇒ 00:05:48.259 rob: Okay, cool. So the logic do you have that matches? Should that be in the Dbt project
21 00:05:48.260 ⇒ 00:05:50.470 rob: that is currently in Dvt. Yes.
22 00:05:50.840 ⇒ 00:05:55.399 rob: okay, I’ll look in there again. I didn’t see it, but I must have just missed it.
23 00:05:56.400 ⇒ 00:06:01.970 Demilade Agboola: Yeah. So it’s it’s a it’s something called a macro in Dbt.
24 00:06:01.970 ⇒ 00:06:05.330 rob: Yeah, I did. I did see your macros. Okay? So it’s in the product.
25 00:06:05.760 ⇒ 00:06:06.790 rob: Macro.
26 00:06:07.720 ⇒ 00:06:19.010 Demilade Agboola: Yeah, it’s a standardized product name Macro and standardized marketing name Macro. But yeah, we just use it to to get like standard product names. And that’s kind of those things.
27 00:06:19.420 ⇒ 00:06:20.810 rob: Okay, cool.
28 00:06:20.960 ⇒ 00:06:26.989 rob: Hi, Robert. I just had a question about the products, but Demote just answered them for me. So I’m gonna bounce.
29 00:06:27.590 ⇒ 00:06:29.719 Robert Tseng: Wait. Actually, Rob, can I ask you a couple of questions?
30 00:06:29.720 ⇒ 00:06:30.809 rob: Yeah, sure.
31 00:06:30.810 ⇒ 00:06:34.639 Robert Tseng: Yeah, yeah, one. So we’re like.
32 00:06:35.020 ⇒ 00:06:53.730 Robert Tseng: I, I saw that you’re like helping Bobby, bring some stuff I I just don’t understand, like kind of how Bobby’s getting all the stuff that he needs in customer. I/O, I mean, just context is like with the segment renewal looming like we’re like, I’m like trying to downsize the segment bill. And like also like evaluate like.
33 00:06:53.800 ⇒ 00:07:21.609 Robert Tseng: seems like we’re bypassing segment a lot of the time, anyway, like, why, why do we even like the whole? There’s like the premium feature of like audiences right like this is something we pay like 15 grand a year for it, and Bobby doesn’t use it at all. So he builds all the audiences he needs in in in Customer I/O, and like any trade that he needs. He seems to just go to you, and you just kind of bring it in through a web hook or some other direct integration that just bypasses segment is that kind of a.
34 00:07:21.610 ⇒ 00:07:31.160 rob: I’ve only done that with one thing. But yeah, we did a it’s a reverse Etl out of bigquery.
35 00:07:31.700 ⇒ 00:07:34.970 Robert Tseng: Okay, yeah. I mean, I think I saw that before. So I, yeah.
36 00:07:34.970 ⇒ 00:07:35.480 rob: Yeah.
37 00:07:36.140 ⇒ 00:07:38.290 Robert Tseng: Okay? And then
38 00:07:38.400 ⇒ 00:07:47.499 Robert Tseng: well, if it’s the reverse, Etr of bigquery, I mean, yeah, that’s and those are the that data is coming into bigquery from segment, because that’s from the web hook stuff, right? But we.
39 00:07:47.500 ⇒ 00:07:48.089 rob: That’s really.
40 00:07:48.400 ⇒ 00:07:55.819 Robert Tseng: Need it. Cause. Yeah. I mean, we don’t really need like, what segment doesn’t.
41 00:07:55.960 ⇒ 00:07:59.339 Robert Tseng: The web hooks don’t need to come into bigquery through segment is what I’m saying.
42 00:07:59.340 ⇒ 00:08:06.840 rob: No, no, they don’t. You’re right. Yeah. And I had never worked with segment before. So I I didn’t really didn’t like it at 1st
43 00:08:07.480 ⇒ 00:08:21.379 rob: but I don’t know like I I can see why Adam likes it so much, but the idea was it would standardize everything for us, and we don’t use it like that at all. We don’t use the protocols or anything like that. They would help us do that.
44 00:08:22.450 ⇒ 00:08:25.880 Robert Tseng: Yeah, I mean, protocols is just like
45 00:08:26.630 ⇒ 00:08:30.769 Robert Tseng: there’s no real like tests that are happening there.
46 00:08:31.805 ⇒ 00:08:41.600 Robert Tseng: you kind of get around. You kind of get around that, despite having like Dbt tests like that, we that we run in the warehouse, anyway. So yeah, I mean.
47 00:08:42.700 ⇒ 00:08:49.650 Robert Tseng: So I guess what I’m I mean the. It’s not the renewals coming up in July. So it’s not exactly happening yet, but
48 00:08:49.980 ⇒ 00:08:57.149 Robert Tseng: I want to even recommend that we don’t continue with segment is kind of my my thought, but.
49 00:08:57.150 ⇒ 00:09:03.480 rob: Great man. What would we use for the the web hooks like, where where do you want to catch them?
50 00:09:03.860 ⇒ 00:09:08.340 Robert Tseng: Yeah. Well, so you know, we’re obviously we’re moving off of bass.
51 00:09:09.750 ⇒ 00:09:11.590 rob: Oh, really that quickly.
52 00:09:12.230 ⇒ 00:09:14.000 Robert Tseng: Yeah. Well, I josh.
53 00:09:14.340 ⇒ 00:09:18.520 Robert Tseng: they should. They should be done. I mean, they should be done by July. So like
54 00:09:18.690 ⇒ 00:09:26.110 Robert Tseng: assuming that that happens, then, you know, the only connectors that are really running in segment right now are the basketball.
55 00:09:28.790 ⇒ 00:09:29.820 rob: That’s great man!
56 00:09:30.260 ⇒ 00:09:43.659 Robert Tseng: Yeah. So I mean, I just feel like the timing and everything like it kind of might align there. But okay, that was a good. Yeah, that’s that’s helpful. I know you’re trying to send over some stuff regarding like influencer and the other offline
57 00:09:44.283 ⇒ 00:09:48.310 Robert Tseng: reporting. I guess any more. Updates there.
58 00:09:48.910 ⇒ 00:09:54.047 rob: No, I got. I got it in incrementals. Tab. I’m not pulling it into big query, though.
59 00:09:54.700 ⇒ 00:10:00.159 rob: I can do that. I’m just going straight from the Vibe Api directly into
60 00:10:01.295 ⇒ 00:10:06.839 rob: it’s just an app script that’s running in that incremental seat that they’re pulling.
61 00:10:06.990 ⇒ 00:10:10.739 rob: So I okay, I can do it. You tell me how important it is.
62 00:10:11.270 ⇒ 00:10:22.400 Robert Tseng: Okay, yeah. I mean, could we get that into bigquery? Because, we’re trying to give Mattesh like a full like mer. Calculation, which.
63 00:10:22.670 ⇒ 00:10:23.230 rob: Yeah, sure.
64 00:10:23.230 ⇒ 00:10:25.170 Robert Tseng: More than the the paid performance. Yeah.
65 00:10:25.480 ⇒ 00:10:27.350 rob: Okay, yeah, I’ll bring that in.
66 00:10:27.790 ⇒ 00:10:30.280 Robert Tseng: Okay, cool. Yeah.
67 00:10:30.280 ⇒ 00:10:31.990 rob: Anything else you guys have for me.
68 00:10:32.940 ⇒ 00:10:43.082 Robert Tseng: Yeah, that’s the I guess one more thing a heads up is not to be done yet, but I mean, we we’ve been evaluating whether or not to remove north theme
69 00:10:43.680 ⇒ 00:10:47.419 rob: Oh, yeah, I thought that was a done deal. We were moving away from them.
70 00:10:49.060 ⇒ 00:10:54.720 Robert Tseng: Yeah. Well, I mean, seems like the contract isn’t up until July as well, like
71 00:10:55.904 ⇒ 00:11:04.059 Robert Tseng: I thought we were gonna turn it off today. But then I just like Mattesh finally sent it over to me, and he says like they can’t do anything until July, so
72 00:11:05.840 ⇒ 00:11:09.659 Robert Tseng: I don’t know, like maybe I I have heard differently. What! What have you been hearing.
73 00:11:11.940 ⇒ 00:11:16.330 rob: Yeah dude. So I don’t know I’m I’m fine to lose it whenever.
74 00:11:18.350 ⇒ 00:11:29.650 Robert Tseng: Okay, yeah. Well, so the one thing that Northeam does that I’m not confident we do is the they have like a 1st party pixel tracking thing
75 00:11:30.100 ⇒ 00:11:36.969 Robert Tseng: that it’s like a really niche use case. But basically, like, sometimes, like cutter, you know, we we run like
76 00:11:37.320 ⇒ 00:11:48.343 Robert Tseng: view based campaigns that don’t really translate into clicks, but we still want to be able to attribute back to them. So like if somebody sees the product on a tiktok reel but doesn’t actually click
77 00:11:49.082 ⇒ 00:11:50.380 rob: Like display ads.
78 00:11:50.380 ⇒ 00:12:07.139 Robert Tseng: Yeah, display ads and stuff so apparently north beams. Pixel, I can help give them like, which makes sense. They just probably just like plant like a hidden session. Id, that just gets persisted. So we kind of need to replicate something like that where? Yes, we have the session id that generates a web flow.
79 00:12:07.518 ⇒ 00:12:23.089 Robert Tseng: But there isn’t a re a way to really map it to like a vast conversion event, unless we inject the same session id into like the best web hook or something, and that that part to me is a bit hazy. I I wonder
80 00:12:23.190 ⇒ 00:12:48.310 Robert Tseng: would you be able to help with that. Like, if we could isolate which I know we can, we can. We can. We can take the session Id from the web from website. It’s basically just like 1st utms from the web web flow session of somebody who finally goes through the flow and and makes the checkout or whatever like. But we need to be able to inject the the session id there, so that we can actually stitch it in the warehouse.
81 00:12:48.700 ⇒ 00:12:49.620 Robert Tseng: Does that make sense.
82 00:12:49.620 ⇒ 00:12:51.470 rob: I could definitely help with that. Yeah.
83 00:12:51.800 ⇒ 00:12:59.319 Robert Tseng: Okay. Yeah. I’ve never like edited web hooks, I guess, I suppose, or done it. These injections on, I mean, I’m sure it’s not
84 00:12:59.740 ⇒ 00:13:05.270 Robert Tseng: impossible. I just have not done it myself personally. So I think when just ask that, okay.
85 00:13:05.270 ⇒ 00:13:06.389 rob: Cool. Yeah.
86 00:13:07.790 ⇒ 00:13:15.183 Robert Tseng: Yeah, okay. So I I think that’s probably what I’m gonna pitch to them today when I catch up with Elt. But
87 00:13:15.880 ⇒ 00:13:17.400 Robert Tseng: okay, cool.
88 00:13:17.930 ⇒ 00:13:21.680 rob: Okay. Alright guys, hey? Have a fun meeting.
89 00:13:22.560 ⇒ 00:13:23.220 Robert Tseng: Thank you.
90 00:13:23.220 ⇒ 00:13:25.750 rob: Alright. See, you guys have a good weekend. Bye.
91 00:13:25.750 ⇒ 00:13:26.420 Robert Tseng: Hi, Rob!
92 00:13:29.550 ⇒ 00:13:30.550 Robert Tseng: Hello!
93 00:13:31.719 ⇒ 00:13:36.330 Robert Tseng: Welcome back a wish for hope you had a good holiday.
94 00:13:40.646 ⇒ 00:13:41.640 Awaish Kumar: Thank you.
95 00:13:42.420 ⇒ 00:13:45.430 Awaish Kumar: Alright, yeah. It was a good taste.
96 00:13:49.330 ⇒ 00:13:50.175 Robert Tseng: Okay,
97 00:13:51.650 ⇒ 00:13:57.707 Robert Tseng: So let me just talk through. We’ll just kind of clear out everything that we have in flight, and then
98 00:13:58.800 ⇒ 00:14:01.970 Robert Tseng: we’ll, we’ll get to that the like, the retro later.
99 00:14:02.280 ⇒ 00:14:07.300 Robert Tseng: So do let’s see.
100 00:14:08.810 ⇒ 00:14:22.950 Robert Tseng: Yeah, we should know you’re still paused on this ticket, because, I mean, the corral trial is up as of yesterday. Actually. So I’ve been in negotiations with corral on whether or not we wanted to keep them like or like what we wanted to keep with them.
101 00:14:24.670 ⇒ 00:14:29.789 Robert Tseng: I would appreciate your kind of take on this, too wish, but my opinion is that, like
102 00:14:30.140 ⇒ 00:14:41.489 Robert Tseng: well, we did this trial for 2 weeks, and there was no real custom modeling that was like requested from the marketing team like it doesn’t like the benefit of going with corral was that
103 00:14:41.750 ⇒ 00:15:07.540 Robert Tseng: we would not have a black box of, like, you know, North Beam Endpoint just giving us like daily spend data. But we would get all of like, you know, the the full. You know the full data, all the data model, like the the data models that come with modeling the performance, add data. And then we could bring that into our models and like, have have a higher level of customization, right? But
104 00:15:07.640 ⇒ 00:15:13.920 Robert Tseng: it just doesn’t seem like we need it like. So is it even really worth it to.
105 00:15:14.060 ⇒ 00:15:29.240 Robert Tseng: you know? Get the team off of North Beam and move to this. If we’re not getting any more functionality out of it today, like, maybe that changes later on. And this is the better future decision. But just from what I saw from the past 2 weeks, like
106 00:15:29.440 ⇒ 00:15:37.789 Robert Tseng: we didn’t really have to. We didn’t. We’re asked to do anything. So I’m not really sure if this is like a wise decision.
107 00:15:39.582 ⇒ 00:15:43.240 Awaish Kumar: I. I agree with you here, because what
108 00:15:43.540 ⇒ 00:15:53.160 Awaish Kumar: but the schema we have shared with the coral to get the data to have something similar which we are already getting from notes beam.
109 00:15:53.300 ⇒ 00:15:58.480 Awaish Kumar: We are not able to provide more of any like any
110 00:15:58.870 ⇒ 00:16:05.489 Awaish Kumar: more features or or the more class category segmentation, using coral like
111 00:16:05.820 ⇒ 00:16:09.029 Awaish Kumar: span by gender or span by
112 00:16:09.340 ⇒ 00:16:16.190 Awaish Kumar: order, level, or something like that. Then it’s kind of we are at the same stage as we were with North Beam.
113 00:16:18.470 ⇒ 00:16:19.160 Robert Tseng: Yeah.
114 00:16:20.720 ⇒ 00:16:21.610 Robert Tseng: Okay.
115 00:16:23.570 ⇒ 00:16:26.660 Robert Tseng: Yeah. So I might even tell them, don’t
116 00:16:26.760 ⇒ 00:16:43.049 Robert Tseng: don’t switch off north beam, I guess. Unless they’re like, really decided, they will like, I, I just, yeah, I don’t really know if I see a point in that for the for the Zanodi data, which is their Med Spa data. I think that makes sense. We could. We could probably
117 00:16:43.450 ⇒ 00:16:47.480 Robert Tseng: see we should just keep that like keeps us from having to do that work.
118 00:16:47.987 ⇒ 00:16:50.250 Robert Tseng: So I might just end up
119 00:16:50.780 ⇒ 00:16:54.110 Robert Tseng: reducing the scope and telling them to just use
120 00:16:56.230 ⇒ 00:17:06.159 Robert Tseng: just use the zanodi connector. And then then they we can reverse Etl, that back into our our warehouse later on. But yeah, okay.
121 00:17:06.160 ⇒ 00:17:06.760 Awaish Kumar: Okay.
122 00:17:07.400 ⇒ 00:17:09.951 Robert Tseng: That’s my opinion. There.
123 00:17:10.869 ⇒ 00:17:34.709 Robert Tseng: yeah. And then that would also save us from having to do a bit of what I was talking about with Rob, before we dropped off the call. It’s like North theme is not just an attribution platform for them in terms of like aggregating ad spend in this way. They they also have, like a 1st party, pixel that like helps them to track like conversions in a deeper way than
124 00:17:34.880 ⇒ 00:17:36.810 Robert Tseng: actually what we could do
125 00:17:37.776 ⇒ 00:17:44.700 Robert Tseng: with with like, right now, if we just go direct with these sources, they only show you click spaced attribution.
126 00:17:45.138 ⇒ 00:18:05.810 Robert Tseng: But yeah, you can’t actually do view based or impression based attribution. So it would just be an additional project which I scoped out earlier today, like I, I spent some time thinking through like, Okay, well, what do we actually have to get to do this? And it’s quite a lot like I. If you look at this I set up like a bunch of tickets.
127 00:18:06.950 ⇒ 00:18:07.770 Robert Tseng: It’s
128 00:18:08.336 ⇒ 00:18:15.720 Robert Tseng: yeah, it’s like, okay, well, this is, this is the amount of work it would take to replace north beam is kind of what I was trying to plan out.
129 00:18:17.170 ⇒ 00:18:22.610 Robert Tseng: And I’ll leave it on them to decide if they want us to do that. But yeah.
130 00:18:24.490 ⇒ 00:18:25.160 Awaish Kumar: Okay.
131 00:18:25.980 ⇒ 00:18:26.580 Robert Tseng: Yeah.
132 00:18:27.020 ⇒ 00:18:36.849 Robert Tseng: okay, well, then, we’ll just keep going through this. So yeah, I mean, this is really just renegotiating with corral after today. After this call.
133 00:18:37.230 ⇒ 00:18:40.559 Robert Tseng: Yeah, Tim Lotte, do you want to talk about these 2.
134 00:18:44.056 ⇒ 00:18:48.020 Demilade Agboola: So for the 1st one, the ticket customer ticket model.
135 00:18:48.887 ⇒ 00:18:51.622 Demilade Agboola: I lit. I just sent
136 00:18:54.820 ⇒ 00:19:01.410 Demilade Agboola: like on an update like the how do I put it? The sample of what the data would look like?
137 00:19:02.000 ⇒ 00:19:10.659 Demilade Agboola: And I just basically asked Danny, if did I send it? Oh, actually, no, I didn’t hit send my bad so I.
138 00:19:11.410 ⇒ 00:19:20.829 Demilade Agboola: I basically just put up a sample of the columns. And then I think the idea is just like, what do we need? What do we need to streamline? And then, if
139 00:19:22.020 ⇒ 00:19:27.578 Demilade Agboola: because I know Annie doesn’t necessarily like having too many columns or too much data. So like, okay, what do we streamline into.
140 00:19:28.040 ⇒ 00:19:38.070 Demilade Agboola: And also just basically figuring out, if there anything, if there’s any other thing she needs that is absent in the model like this, this is just what the sample attribute is, and if
141 00:19:38.490 ⇒ 00:19:42.409 Demilade Agboola: that once she tells me what she needs, I can always make that tweak.
142 00:19:42.630 ⇒ 00:19:47.159 Demilade Agboola: and I will send them like the model will be sent in today. So it’s a it’s a quick.
143 00:19:47.480 ⇒ 00:19:48.469 Demilade Agboola: quick fix.
144 00:19:49.430 ⇒ 00:19:54.849 Robert Tseng: Okay, I just pulled it up in case you guys wanted to just kind of talk through that now.
145 00:19:55.228 ⇒ 00:19:59.609 Robert Tseng: Or I don’t know. Maybe it’d be help, and you could look at on your own. But I guess this is
146 00:19:59.710 ⇒ 00:20:03.159 Robert Tseng: this is the streamlined version from Dimade. I guess right.
147 00:20:03.160 ⇒ 00:20:08.689 Demilade Agboola: No, no, this is the wide version. So like if you want to streamline it if we’re like, Oh, I actually don’t need this columns.
148 00:20:08.690 ⇒ 00:20:09.759 Robert Tseng: Oh, got it! Got it!
149 00:20:09.760 ⇒ 00:20:10.680 Demilade Agboola: Yeah, so
150 00:20:10.910 ⇒ 00:20:19.249 Demilade Agboola: we can just streamline it. And then, if there are things that we she does actually need, but they’re not in here like again. She could just tell me, and I’ll figure out how to get in here.
151 00:20:19.600 ⇒ 00:20:24.139 Demilade Agboola: and then, once that’s done, the model can be will be pushed to priority.
152 00:20:24.610 ⇒ 00:20:25.200 Robert Tseng: Okay.
153 00:20:26.970 ⇒ 00:20:43.319 Robert Tseng: yeah. I mean, I know there’s a lot here. It’s kind of like tedious. I mean, honestly, when I get a white table like this these days. I just like throw the schema into Chat Gpt. And I talk about the fields that I do need, and then it’ll just it’s pretty good at pattern matching whatever I I mean. I don’t want to tell you what to do, but like, in case
154 00:20:43.620 ⇒ 00:20:49.850 Robert Tseng: you run into the same frustration that I do in trying to find the fields that I need. That’s typically what I do.
155 00:20:50.120 ⇒ 00:20:57.419 Annie Yu: Okay, okay, I’ll I’ll have to take a look. And then for on this part of the dashboard I actually haven’t
156 00:20:57.710 ⇒ 00:21:03.939 Annie Yu: made any changes. So I probably would have to go in and see what fields are used.
157 00:21:04.572 ⇒ 00:21:19.499 Annie Yu: Yeah. So I’ll go from there. And also, like I want to clarify on. Don’t worry about too many columns here, I think the other day I was trying to say was, I saw that people like updated
158 00:21:20.069 ⇒ 00:21:24.110 Annie Yu: they added some customized fields and then updated the
159 00:21:24.240 ⇒ 00:21:36.013 Annie Yu: published data source. So when I’m making a new dashboard, I actually don’t need those customized fields built for other dashboard. So that’s what I was trying to say.
160 00:21:37.360 ⇒ 00:21:37.840 Robert Tseng: Got it.
161 00:21:37.840 ⇒ 00:21:38.730 Demilade Agboola: Gotcha gotcha.
162 00:21:38.730 ⇒ 00:21:53.650 Annie Yu: Yeah. Yeah. So I think going forward, it’s good to just keep whatever original fields from from the model table and then not update any customized fields from a a dashboard.
163 00:21:53.850 ⇒ 00:21:55.040 Robert Tseng: That makes sense.
164 00:21:56.730 ⇒ 00:22:03.079 Robert Tseng: Okay, that makes sense. Do we think we’ll get this fixed today?
165 00:22:05.453 ⇒ 00:22:15.589 Demilade Agboola: I mean, it shouldn’t be hard to fix. I think it will just be once we push it. If all the columns that I needed are in there. It should just be like a swap of the
166 00:22:15.790 ⇒ 00:22:17.640 Demilade Agboola: sources, so it should be fine.
167 00:22:18.010 ⇒ 00:22:18.630 Robert Tseng: Okay.
168 00:22:22.140 ⇒ 00:22:28.252 Robert Tseng: Alright, yeah. So I think once that’s done, then I’d like to close out that dash.
169 00:22:29.090 ⇒ 00:22:33.400 Robert Tseng: yeah, on the embeddable side. I will know. But
170 00:22:33.640 ⇒ 00:22:40.169 Robert Tseng: so I’m like working with Ryan. Ryan uses a different. They use monday.com for his his stuff. So
171 00:22:40.550 ⇒ 00:22:52.089 Robert Tseng: I’m like having to read through all of his tickets and try to understand, like what what he’s trying to say. And then I’m trying to translate that into more requirements for us here. So
172 00:22:52.320 ⇒ 00:22:58.579 Robert Tseng: I I feel like you’re waiting on details for me here. But I’m not sure like what any any updates on that.
173 00:23:01.268 ⇒ 00:23:13.789 Demilade Agboola: Not yet, to be honest. I’m still like trying to put piece it together. Figure out the Ids to join on that sort of stuff kind of like, put the structure in what’s needed.
174 00:23:14.478 ⇒ 00:23:21.979 Demilade Agboola: So yeah, like, that’s still kind of what I’m doing for now. So I don’t necessarily have any feedback yet, but once I do, I’ll let you know.
175 00:23:22.440 ⇒ 00:23:28.859 Robert Tseng: Okay, no worries. Yeah, I think I need. I need today to really, just like, understand what’s going on with his board as well. So
176 00:23:29.720 ⇒ 00:23:35.289 Robert Tseng: I will update this ticket if I need, if I get anything else out of it.
177 00:23:38.010 ⇒ 00:23:49.410 Robert Tseng: okay. So I I think, like, as far as the spike goes, we are pretty much. There’s nothing we can do about it now, right? So we we’ve already expressed limitation like the client knows that. So
178 00:23:51.080 ⇒ 00:23:57.610 Robert Tseng: limitation is that you know 30 to 50% of orders don’t
179 00:23:57.720 ⇒ 00:24:09.530 Robert Tseng: of transaction ids. We cannot do a true customer funnel from the moments of purchase to shipment delivered.
180 00:24:10.210 ⇒ 00:24:14.280 Robert Tseng: We only have confidence in order shipped
181 00:24:15.070 ⇒ 00:24:24.580 Robert Tseng: or order updated, say, system generated event to when the order it was delivered.
182 00:24:27.150 ⇒ 00:24:32.859 Robert Tseng: This is an order funnel. Not a customer funnel.
183 00:24:33.790 ⇒ 00:24:41.179 Robert Tseng: Right? I think that’s that, was our conclusion, for now is that right?
184 00:24:43.350 ⇒ 00:24:44.940 Demilade Agboola: Yes, that’s our conclusion.
185 00:24:45.440 ⇒ 00:24:46.660 Robert Tseng: Okay, cool.
186 00:24:49.970 ⇒ 00:24:55.830 Robert Tseng: Yeah. Mixed panel embeddable. So ran into a couple of roadblocks. But I think it’s okay, like.
187 00:24:56.130 ⇒ 00:25:04.470 Robert Tseng: I mean, I between this and then, yeah, Embeddables is all I’m thinking about for this client today. So I will continue to follow up on that.
188 00:25:07.430 ⇒ 00:25:11.592 Robert Tseng: I haven’t touched Josh’s roadmap. I think I’m just gonna do that next week.
189 00:25:12.430 ⇒ 00:25:13.910 Robert Tseng: and pull it out.
190 00:25:14.300 ⇒ 00:25:15.810 Robert Tseng: And then.
191 00:25:17.700 ⇒ 00:25:33.200 Robert Tseng: yeah, I know ways. You were out. And then our Zendesk data you’ve been. We’ve been doing a manual re-sync, if we need to update that. But yeah, right for now we’re just doing manual re-sync, so that hasn’t changed. I think I’m just gonna leave that there. It’s the same thing.
192 00:25:33.320 ⇒ 00:25:37.530 Robert Tseng: I should just cancel one of these. So I will delete that.
193 00:25:38.355 ⇒ 00:25:52.990 Robert Tseng: Yeah, I think this one is probably the one that the team cares about since they’re launching 13 new skews today or next week. So I know you just talked with Rob about some stuff regarding products mappings.
194 00:25:53.578 ⇒ 00:25:57.080 Robert Tseng: I don’t know if you guys talked about the whole like.
195 00:25:57.970 ⇒ 00:26:02.129 Robert Tseng: should Olympia be a different product, category or not, like.
196 00:26:02.130 ⇒ 00:26:08.659 Demilade Agboola: Yeah, so he, that’s what he asked, actually. And and so I, I basically explained how we’re able to cause map it
197 00:26:08.940 ⇒ 00:26:13.860 Demilade Agboola: as injected with Sema, that’s that’s that was basically his question.
198 00:26:16.270 ⇒ 00:26:17.070 Demilade Agboola: Oh, yeah.
199 00:26:17.070 ⇒ 00:26:18.229 Robert Tseng: Should be bar. Okay.
200 00:26:18.770 ⇒ 00:26:26.899 Demilade Agboola: Yeah, so how? No, no, he it is, Sema. But he just wasn’t sure how we were able to figure out that it was Sema. So I kind of explained our process to him.
201 00:26:32.200 ⇒ 00:26:32.830 Robert Tseng: Okay.
202 00:26:33.010 ⇒ 00:26:40.409 Robert Tseng: Good. Good to know. So I think, yeah, we we were. We were. We were handling it correctly, and he was maybe not in the loop.
203 00:26:41.110 ⇒ 00:26:44.920 Demilade Agboola: Yeah, so for med kits, I mean.
204 00:26:45.680 ⇒ 00:26:52.342 Demilade Agboola: the splitting part isn’t hard like the the split isn’t hard. I think I will just
205 00:26:53.110 ⇒ 00:26:57.420 Demilade Agboola: basically for every plan that is picked.
206 00:26:58.176 ⇒ 00:27:02.839 Demilade Agboola: I will look at the make it plans, and I’ll let you know. But like for every plan that is picked. I’ll pick the 1st month I start.
207 00:27:03.080 ⇒ 00:27:18.129 Demilade Agboola: and then the start variance will be assigned that, and then subsequent month. I would just use the maintenance variance, so based on the number of months left. So a 3 month plan, or a quarterly plan or 6 month plan. Would you know the remaining months. We like tag as maintenance.
208 00:27:18.750 ⇒ 00:27:21.160 Demilade Agboola: Okay? Yeah, I’ll just kind of figure that out.
209 00:27:21.410 ⇒ 00:27:27.299 Demilade Agboola: But then I noticed and you mentioned something about a refills. I will look at that as well, and see if that also applies to medkit.
210 00:27:27.840 ⇒ 00:27:31.910 Demilade Agboola: If there’s a kind of refill column to use as a ticket.
211 00:27:32.410 ⇒ 00:27:35.871 Robert Tseng: Okay, yeah, I I found I found that in the web hook.
212 00:27:36.430 ⇒ 00:27:42.809 Robert Tseng: yeah, I I guess. I hope that I think that unblocked you, Danny, but maybe we should talk about that as well.
213 00:27:42.930 ⇒ 00:27:46.460 Robert Tseng: Is that in the that’s in this ticket? Right?
214 00:27:49.780 ⇒ 00:27:53.490 Robert Tseng: So maybe we’ll jump to this one. Yeah, I think I.
215 00:27:57.470 ⇒ 00:28:01.349 Annie Yu: Yeah, it’s all all over the place. I do have a few questions here.
216 00:28:01.350 ⇒ 00:28:02.749 Robert Tseng: Okay, let’s talk about it.
217 00:28:02.750 ⇒ 00:28:07.780 Annie Yu: That is fill is refill is helpful, that that one’s clear.
218 00:28:08.950 ⇒ 00:28:09.610 Robert Tseng: Okay.
219 00:28:10.393 ⇒ 00:28:15.590 Robert Tseng: and then as far as file sizes and stuff. So oh, you gotta sorry I didn’t see this question.
220 00:28:16.107 ⇒ 00:28:19.229 Robert Tseng: How do we determine how many refills they’ve had.
221 00:28:19.920 ⇒ 00:28:21.393 Robert Tseng: Oh, man!
222 00:28:23.550 ⇒ 00:28:27.830 Robert Tseng: Well, oh.
223 00:28:31.920 ⇒ 00:28:35.389 Robert Tseng: okay, for quarterly that it makes.
224 00:28:35.390 ⇒ 00:28:40.069 Annie Yu: So what this means like 6 months plan quarterly. What does that mean?
225 00:28:44.690 ⇒ 00:28:45.859 Robert Tseng: I’m not sure.
226 00:28:56.980 ⇒ 00:29:12.620 Annie Yu: Yeah. So that’s that’s 1 question. But I think, yeah, to get the vial size or doses that you mentioned as well as the remaining we would probably have to extract from product names. I’m not sure if there’s a better way.
227 00:29:12.730 ⇒ 00:29:17.250 Annie Yu: But yeah, and the follow up question is. But then, if we do know, someone’s on
228 00:29:19.440 ⇒ 00:29:22.200 Annie Yu: a 6 month plan, how do we determine
229 00:29:22.360 ⇒ 00:29:25.900 Annie Yu: how many refills they’ve already got, and how many left.
230 00:29:29.200 ⇒ 00:29:34.989 Demilade Agboola: I don’t think we have a membership plan column, though I know we’ve figured out how to calculate the membership plan.
231 00:29:37.370 ⇒ 00:29:42.560 Demilade Agboola: Which I think the the way we’ve we calculated it was. The default was the
232 00:29:43.168 ⇒ 00:29:48.319 Demilade Agboola: variant like how the variant is, but then sometimes we there can also be
233 00:29:49.169 ⇒ 00:29:55.560 Demilade Agboola: it selects like membership plan. But the question about yeah, how to like, assign, how many
234 00:29:56.550 ⇒ 00:30:05.700 Demilade Agboola: like, what stage they are in like, how many months like one month, that is, if the 6 month plan is this 3rd month, for instance, yeah, something we need to like, figure out.
235 00:30:08.230 ⇒ 00:30:09.900 Demilade Agboola: that is something like
236 00:30:10.060 ⇒ 00:30:14.413 Demilade Agboola: is not, I think, again. That’s why I want to look at the refill column that, like
237 00:30:15.040 ⇒ 00:30:23.910 Demilade Agboola: Robert mentioned, or proper flagged, so I can see if that serves as a is refill like, if we can figure out that that is what the refill looks like, we, then we can use it instead.
238 00:30:34.110 ⇒ 00:30:37.909 Robert Tseng: Okay. I just asked the question for you hopefully.
239 00:30:38.230 ⇒ 00:30:40.580 Robert Tseng: this will get us the answer we want.
240 00:30:42.690 ⇒ 00:30:48.199 Robert Tseng: Oh, my dude, please don’t say that everyone’s gonna freak out that we’re moving away from segment.
241 00:30:48.834 ⇒ 00:30:58.866 Robert Tseng: Okay. But anyway, okay, any. So I I think that was the right question. But you know, feel free to read it, and if I said something wrong, just let me know.
242 00:30:59.480 ⇒ 00:31:03.726 Robert Tseng: yeah, I know I didn’t give you the look of the dashboard.
243 00:31:04.604 ⇒ 00:31:09.519 Annie Yu: So does that mean as a demo audit that will
244 00:31:10.200 ⇒ 00:31:15.259 Annie Yu: look into the how to get the vial size and then.
245 00:31:16.100 ⇒ 00:31:19.166 Robert Tseng: Yeah, the file size is this quantity? Really?
246 00:31:20.600 ⇒ 00:31:23.710 Robert Tseng: yeah, like, I think you can tell like
247 00:31:24.230 ⇒ 00:31:31.969 Robert Tseng: 1.7 milligram like this, is there. There isn’t like a clear mapping like we would have to create it. But I guess
248 00:31:32.751 ⇒ 00:31:40.460 Robert Tseng: Rebecca looks at the quantity and she’s like, okay, 1.7 means one vial, like, I don’t actually know if that’s the right
249 00:31:40.590 ⇒ 00:31:48.499 Robert Tseng: like model. But like she, she just uses, she just looks at quantity to determine file size. So I could ask her like, Hey, like.
250 00:31:51.170 ⇒ 00:31:52.870 Robert Tseng: okay, yeah. You know what? I’ll just ask her
251 00:31:53.430 ⇒ 00:31:58.300 Robert Tseng: if it’s helpful to have file size
252 00:31:59.060 ⇒ 00:32:02.690 Robert Tseng: actually have file size and not a proxy.
253 00:32:03.480 ⇒ 00:32:08.550 Robert Tseng: You see, one second I grab one, I’m sure.
254 00:32:10.780 ⇒ 00:32:11.530 Robert Tseng: What?
255 00:32:16.480 ⇒ 00:32:18.839 Robert Tseng: Otherwise we’re gonna assume.
256 00:32:19.180 ⇒ 00:32:22.380 Robert Tseng: Wow, side, please.
257 00:32:23.370 ⇒ 00:32:28.500 Robert Tseng: It’s just p by milligram.
258 00:32:30.810 ⇒ 00:32:34.320 Robert Tseng: Okay, is that fair? Yeah.
259 00:32:34.630 ⇒ 00:32:40.560 Annie Yu: And the one thing I’m just gonna make sure I’m following. So
260 00:32:40.960 ⇒ 00:32:44.810 Annie Yu: can you help me understand again? How do we understand?
261 00:32:50.850 ⇒ 00:32:54.570 Annie Yu: I guess someone’s on a 6 month plan or so.
262 00:32:56.100 ⇒ 00:32:58.800 Demilade Agboola: Yeah. I do not have.
263 00:33:00.800 ⇒ 00:33:04.430 Annie Yu: Is that also something you have to look into those product name.
264 00:33:04.430 ⇒ 00:33:11.050 Demilade Agboola: Oh, no, no like yes, I think beside bundle id right there in the sheet, you can see like membership plan.
265 00:33:11.450 ⇒ 00:33:15.850 Demilade Agboola: So we kind of have a column that we’ve calculated for membership, and
266 00:33:17.130 ⇒ 00:33:20.339 Annie Yu: But isn’t that just quarterly or monthly.
267 00:33:20.750 ⇒ 00:33:25.400 Demilade Agboola: No, this is just a sample, but it it can be quarterly monthly. It can be 6 months.
268 00:33:25.400 ⇒ 00:33:26.459 Robert Tseng: Next month, and annual.
269 00:33:26.460 ⇒ 00:33:27.569 Demilade Agboola: Annual. Yeah.
270 00:33:28.440 ⇒ 00:33:33.319 Annie Yu: Wait. But what I’m saying is so 6 months or annual that would just mean
271 00:33:33.560 ⇒ 00:33:38.049 Annie Yu: they refill every year or every 6 months right.
272 00:33:39.090 ⇒ 00:33:40.230 Demilade Agboola: That I’m not sure of.
273 00:33:40.520 ⇒ 00:33:40.980 Robert Tseng: I didn’t.
274 00:33:41.260 ⇒ 00:33:43.000 Demilade Agboola: What we need to figure out like.
275 00:33:43.350 ⇒ 00:33:51.160 Robert Tseng: Not necessarily Annie, so like, I think. I think the shipping schedule, like the of the
276 00:33:51.320 ⇒ 00:34:12.179 Robert Tseng: so like a 6 month plan, could be shipped like, you know, all at once, like 2 times or 6 times over, like monthly. Alright, I’m not entirely. I think it’s it’s we have to delineate it a bit like the doctor determines what plan you’re on. Because, depending on your weight, like I don’t know. Like, if you’re super overweight, you may be like.
277 00:34:12.350 ⇒ 00:34:39.799 Robert Tseng: They may give you an annual plan or something, and then you you decide your shipping schedule how how much you want it broken up by, or I think there’s like a trade off between patient preference and getting it all at once and paying upfront versus like. Also, Eden has some restrictions to like. Obviously, they’re not gonna ship you something every week, because the shipping costs are super high. So they have, like some minimums, based on the the product value. If it’s like a
278 00:34:39.960 ⇒ 00:34:53.809 Robert Tseng: more expensive drug, they probably let you ship it monthly. If not, then they probably, you know, let you ship it frequent less frequently. So. Yeah. The membership plan is determined by the doctor, and then the shipping schedule is more determined by like
279 00:34:54.110 ⇒ 00:35:03.100 Robert Tseng: the pharmacy. I guess. Slash the patient like there’s so I I kinda I don’t know hopefully that helps you to decouple that
280 00:35:03.290 ⇒ 00:35:09.490 Robert Tseng: this doesn’t mean that it’s shipped 3 times. And this doesn’t mean it’s shipped every month, or like
281 00:35:10.270 ⇒ 00:35:20.279 Robert Tseng: for monthly. It it does. It probably means that they shipping it once a month. But like an annual plan may not be 12 monthly shipments. It could be 2
282 00:35:20.560 ⇒ 00:35:23.790 Robert Tseng: sit. That’s 6 months apart from each other. Possibly.
283 00:35:24.226 ⇒ 00:35:31.200 Annie Yu: But don’t we need that visibility to know how many remaining orders remaining refers.
284 00:35:31.980 ⇒ 00:35:45.140 Robert Tseng: Yeah, I think that’s why there’s like the way that this is answered like, dose one dose 2, like I feel like that’s posted like the variant number itself. There’s like a series of variants.
285 00:35:47.170 ⇒ 00:36:04.269 Robert Tseng: I think this is, I forgot who was on the call with me yesterday. Maybe it was, yeah, I think everyone was on this call when when Cutter was talking about med kits and how like, yeah, some patients will transfer from other plans into these med kits, but they don’t all have to start from the 1st dose.
286 00:36:04.380 ⇒ 00:36:11.302 Robert Tseng: And so that kind of like made things a bit confusing. Do you remember that conversation? I think. Dam a lot of you were asking about it?
287 00:36:11.740 ⇒ 00:36:31.740 Demilade Agboola: Yeah, I I remember the conversation. He did mention that we we can just discard that logic because it will make it unnecessarily complicated, and he said, It’s just like a very small portion of them. But yes, I figuring out what the 1st dose is, and like what the refill orders are is something that I don’t think we necessarily have done.
288 00:36:32.740 ⇒ 00:36:36.670 Demilade Agboola: And I mean, it’s something I can definitely look into and just trying to see what the
289 00:36:36.950 ⇒ 00:36:46.449 Demilade Agboola: 1st order is, how we identify that and how like subsequent orders are tracked, basically, and how we know which order is a, you know, refill order
290 00:36:46.610 ⇒ 00:36:48.869 Demilade Agboola: versus the actual 1st daughter.
291 00:36:50.100 ⇒ 00:36:54.172 Robert Tseng: Yeah, okay, so let’s let’s keep following up on that.
292 00:36:54.990 ⇒ 00:37:09.089 Robert Tseng: I don’t know if you like. Okay, I can. I can help. And I’ll just like, take this, and I’ll drop it into another channel into the farm Ops Channel. As well to try to get people to follow up on this. But okay, I will. I’ll keep following up on that.
293 00:37:09.560 ⇒ 00:37:15.024 Annie Yu: Yeah, and one, just one more question. So the melody, can you
294 00:37:15.750 ⇒ 00:37:24.890 Annie Yu: help me? Understand? I I think I’m still confused with that. How to interpret that total order total in order. Summary.
295 00:37:27.527 ⇒ 00:37:30.450 Demilade Agboola: I believe so. The order total is.
296 00:37:31.120 ⇒ 00:37:36.360 Annie Yu: If we look at that screenshot that I share, evolve.
297 00:37:40.170 ⇒ 00:37:40.870 Robert Tseng: Sorry. Yeah.
298 00:37:42.910 ⇒ 00:37:44.718 Annie Yu: It’s a little bit. Oh.
299 00:37:45.580 ⇒ 00:37:46.270 Robert Tseng: A more.
300 00:37:46.460 ⇒ 00:37:48.020 Annie Yu: Yeah, that one.
301 00:37:49.660 ⇒ 00:37:50.370 Robert Tseng: Okay.
302 00:37:50.600 ⇒ 00:38:00.530 Annie Yu: So yeah, we are on like one customer Id, and there’s different order numbers. And that order total is consistent across rows. So I’m
303 00:38:00.670 ⇒ 00:38:05.979 Annie Yu: I don’t really know how to think of that, like what granularity that is on.
304 00:38:09.410 ⇒ 00:38:11.029 Demilade Agboola: One second?
305 00:38:13.700 ⇒ 00:38:16.840 Demilade Agboola: Oh, no. So this is because this is the order. Summary right.
306 00:38:17.180 ⇒ 00:38:17.890 Annie Yu: Yeah.
307 00:38:18.130 ⇒ 00:38:22.499 Demilade Agboola: Yes, because Order Summary found out the same order. Total that was on one order
308 00:38:23.090 ⇒ 00:38:29.990 Demilade Agboola: will spread right? Oh, oh, you’re talking about the different customer. I same customer, but different orders.
309 00:38:30.800 ⇒ 00:38:34.090 Annie Yu: But then they still have the same order, total.
310 00:38:35.100 ⇒ 00:38:42.340 Demilade Agboola: Yeah. So, Mike, I’ll I’ll dig in and just try and confirm. But my guess is, it’s sort of like how like they pay like they.
311 00:38:42.620 ⇒ 00:38:48.610 Demilade Agboola: If you’re making monthly plan, you will probably be paying the same amount every month for the same thing.
312 00:38:50.230 ⇒ 00:38:55.389 Demilade Agboola: So I think it’s like I would have to just confirm. But it’s based on the order itself. And like
313 00:38:55.830 ⇒ 00:38:56.740 Demilade Agboola: what?
314 00:38:56.900 ⇒ 00:39:06.150 Demilade Agboola: How much you’re paying for that particular month like in this case, it’s a monthly order. So every month this person is paying 3, 46.
315 00:39:06.390 ⇒ 00:39:09.130 Annie Yu: Oh, so that’s a a dollar. That’s a
316 00:39:09.560 ⇒ 00:39:12.080 Annie Yu: that. The unit is in dollars.
317 00:39:12.330 ⇒ 00:39:14.020 Demilade Agboola: Yes, yes, it’s a dollar amount.
318 00:39:17.530 ⇒ 00:39:23.479 Annie Yu: Oh, okay, so okay. So in this case it could be the same because
319 00:39:24.988 ⇒ 00:39:33.609 Annie Yu: okay. But then, if we look at, let’s say, row 3 to row 9. That’s 1 order number.
320 00:39:35.140 ⇒ 00:39:40.500 Annie Yu: So does that mean? And all the order total is duplicated across.
321 00:39:41.300 ⇒ 00:39:45.969 Demilade Agboola: No, so that that’s the issue with the dim shipments that I was talking about.
322 00:39:45.970 ⇒ 00:39:46.290 Annie Yu: Awesome.
323 00:39:46.290 ⇒ 00:40:06.690 Demilade Agboola: Steam shipments when you, when we did the join from like the transactions, like the orders to shipments, because one, it’s a 1 to many relationship. So now the order total has found out across the different states of the shipments, when in reality it’s just, you know, one order total for that you know.
324 00:40:06.930 ⇒ 00:40:09.499 Demilade Agboola: for that particular order.
325 00:40:13.740 ⇒ 00:40:16.250 Annie Yu: So it’s just, it’s for the one order
326 00:40:17.310 ⇒ 00:40:20.370 Demilade Agboola: But because the shipment has different states.
327 00:40:21.130 ⇒ 00:40:21.740 Annie Yu: Yeah.
328 00:40:21.740 ⇒ 00:40:24.610 Demilade Agboola: When we did a a join from the orders
329 00:40:25.130 ⇒ 00:40:33.199 Demilade Agboola: from fact transactions to dim shipments, because that shipment has multiple different states. Like, you know it’s
330 00:40:33.340 ⇒ 00:40:36.020 Demilade Agboola: shaped to be delivered all that stuff
331 00:40:36.230 ⇒ 00:40:59.340 Demilade Agboola: now it has found out across all of them. So the same order. So it’s only one actually in reality, but because of the joint it appears across multiple. Which is why I said so. We can either pivot like deem shipments, so that every state appears in just the row the same row, or we can, if we pick the last status. Only then we lose out on like previous information about what’s going on.
332 00:40:59.520 ⇒ 00:41:02.609 Annie Yu: We make them dull right the
333 00:41:02.770 ⇒ 00:41:06.050 Annie Yu: for the same order. We just keep the last, the latest one.
334 00:41:06.050 ⇒ 00:41:20.090 Demilade Agboola: Latest. Yeah, we could pick the latest. So we lose all the previous dates, like any information about the previous dates, which is useful for things like if we want to know the time from when it was ordered, when it was shipped to. When was how long was in transit? So how long it was delivered.
335 00:41:20.210 ⇒ 00:41:28.269 Demilade Agboola: That’s useful. So if we want to keep that which means we have to give up the table, the shipment table, so that every order number
336 00:41:28.380 ⇒ 00:41:36.719 Demilade Agboola: only have the different states of shipments all in one row rather than across multiple rows, which would create this funnels that we are seeing.
337 00:41:36.880 ⇒ 00:41:52.809 Demilade Agboola: No, that’s why you’re. That’s why the revenue looks much higher. Because, you add, you’re adding multiple values that actually just the same. So you either have to select only one order id like the each distinct other id, and then do the summitation.
338 00:41:54.260 ⇒ 00:41:58.049 Demilade Agboola: Or we would have to create a new table where
339 00:41:58.280 ⇒ 00:42:00.420 Demilade Agboola: this shipment status is just based on one rule.
340 00:42:01.330 ⇒ 00:42:04.110 Demilade Agboola: which is kind of what I was asking in linear yesterday.
341 00:42:04.530 ⇒ 00:42:06.869 Demilade Agboola: Oh, no, we’re talking about in slack. Wasn’t linear.
342 00:42:07.347 ⇒ 00:42:12.269 Annie Yu: I think there’s a different. Yeah. We were using the same table for a different dashboard.
343 00:42:12.270 ⇒ 00:42:13.380 Demilade Agboola: Exactly.
344 00:42:13.380 ⇒ 00:42:14.910 Annie Yu: Same issue.
345 00:42:15.310 ⇒ 00:42:24.409 Demilade Agboola: Yeah. So that’s why the the realized revenue. The revenue was 6 times or 5 X because it was adding the multiple times. It appeared in different like
346 00:42:24.560 ⇒ 00:42:25.890 Demilade Agboola: shipment States.
347 00:42:26.160 ⇒ 00:42:26.710 Annie Yu: Hmm.
348 00:42:26.710 ⇒ 00:42:32.020 Demilade Agboola: As yes, it would, it would, you know, add the sum 3 times, or 4 times, or 5 times.
349 00:42:33.370 ⇒ 00:42:45.689 Annie Yu: Then, is it? And bear with me if I’m not knowledgeable enough? But is it? Is it possible to have just a separate column here, so we will have like 3, 46. No, no, no, no. 3, 46,
350 00:42:46.980 ⇒ 00:42:47.560 Annie Yu: and then.
351 00:42:48.090 ⇒ 00:42:51.209 Awaish Kumar: Can we just create 2 tables like
352 00:42:51.370 ⇒ 00:42:56.570 Awaish Kumar: one, which only has the latest status from shipment
353 00:42:56.700 ⇒ 00:42:59.179 Awaish Kumar: which can be used for all things of
354 00:42:59.680 ⇒ 00:43:03.300 Awaish Kumar: calculation of order, like revenue, and things like that
355 00:43:03.420 ⇒ 00:43:06.100 Awaish Kumar: and other one which is more
356 00:43:06.572 ⇒ 00:43:13.460 Awaish Kumar: shows the order journey. And we we can name it like that like order journey. Somebody something like that.
357 00:43:14.810 ⇒ 00:43:18.959 Demilade Agboola: Yes, so we can do that. And also.
358 00:43:19.170 ⇒ 00:43:27.025 Demilade Agboola: if we really want to have just one table, something we can do is we can do like an order, rank
359 00:43:27.660 ⇒ 00:43:32.549 Demilade Agboola: pick the 1st one or the latest one and every other one that is still.
360 00:43:32.760 ⇒ 00:43:34.629 Demilade Agboola: that is not the 1st one.
361 00:43:34.950 ⇒ 00:43:37.080 Demilade Agboola: The the order total can be 0,
362 00:43:37.740 ⇒ 00:43:42.809 Demilade Agboola: which is kind of what Amy seen so that way every every single order to solve just appears once.
363 00:43:43.090 ⇒ 00:43:53.449 Demilade Agboola: but also, like I, I also pointed out that the the model, the dashboard they’re using one of the sources is product summary by transaction. And if you just want, revenue product summary by transaction.
364 00:43:53.450 ⇒ 00:43:53.850 Annie Yu: Yeah.
365 00:43:54.330 ⇒ 00:43:55.160 Demilade Agboola: Where? That’s.
366 00:43:55.160 ⇒ 00:44:08.249 Annie Yu: Yeah, for that one. I did reply. For the product. Drill down dashboard. I think for that one the the caveat would mean we have no gender filter across the entire dashboard.
367 00:44:09.300 ⇒ 00:44:17.499 Demilade Agboola: Okay, okay, so for revenue. So for revenue, that’s fine. So for the order total, I will make that change. So it would only assign
368 00:44:19.047 ⇒ 00:44:21.140 Demilade Agboola: an order total
369 00:44:21.480 ⇒ 00:44:30.520 Demilade Agboola: to all of this on my revenue to the maybe the very 1st one or the very last one. I think we’ve always very last one, like the very last status of every order.
370 00:44:31.180 ⇒ 00:44:32.739 Demilade Agboola: like the shipment status.
371 00:44:33.790 ⇒ 00:44:40.299 Annie Yu: Okay, okay? And you said so we can’t do the same thing for revenue is that it? Or we can.
372 00:44:40.300 ⇒ 00:44:54.350 Demilade Agboola: No, we we can so everything will be 0. But the the very last shipment status would have assigned the revenue. So when some of the column of revenue everything will be 0,
373 00:44:54.540 ⇒ 00:45:03.480 Demilade Agboola: but the only one that would count is, you know, only we only have one rule that will count rather than having like multiplication like it’s multiplying.
374 00:45:03.800 ⇒ 00:45:09.980 Annie Yu: Got it, got it so we will have 2 2 new columns once for order we.
375 00:45:10.270 ⇒ 00:45:11.130 Annie Yu: This is.
376 00:45:11.260 ⇒ 00:45:16.879 Demilade Agboola: It will still with same columns. But I will just make that change so that we don’t have like. It wouldn’t count the duplicates
377 00:45:17.530 ⇒ 00:45:20.939 Demilade Agboola: as part of it, it would just. It’s replacing with 0.
378 00:45:22.870 ⇒ 00:45:27.690 Annie Yu: Okay? So I can get both revenue and order count right?
379 00:45:28.160 ⇒ 00:45:31.710 Demilade Agboola: Other counts won’t work, though, unless you do distinct.
380 00:45:33.350 ⇒ 00:45:40.519 Annie Yu: Distinct order number. I think that’s what I’m doing now. Okay, okay, so the order should be fine as it is.
381 00:45:40.740 ⇒ 00:45:43.080 Annie Yu: So okay, we are just changing our revenue.
382 00:45:44.860 ⇒ 00:45:48.420 Demilade Agboola: Yes, I’ll do it fixed for the revenue, revenue and order total.
383 00:45:48.990 ⇒ 00:45:56.949 Annie Yu: Okay? And okay, now, I’m confused. So for the product dashboard, I think I use.
384 00:45:57.050 ⇒ 00:46:03.140 Robert Tseng: Another field called revenue transaction revenue. So is that the wrong one.
385 00:46:04.710 ⇒ 00:46:05.209 Demilade Agboola: I would have.
386 00:46:05.980 ⇒ 00:46:06.599 Demilade Agboola: I don’t know.
387 00:46:06.600 ⇒ 00:46:07.290 Awaish Kumar: All right.
388 00:46:07.900 ⇒ 00:46:11.249 Awaish Kumar: So basically, it is the same thing actually.
389 00:46:11.740 ⇒ 00:46:12.989 Annie Yu: Oh, transaction! Revenue!
390 00:46:12.990 ⇒ 00:46:21.759 Awaish Kumar: Yeah, it was so audited. The total and the transaction revenue came like we just brought in all the fields which were
391 00:46:22.090 ⇒ 00:46:28.230 Awaish Kumar: in the client’s tables, but in the in the back end they do similar calculation.
392 00:46:28.580 ⇒ 00:46:30.470 Awaish Kumar: So it doesn’t really make any
393 00:46:30.590 ⇒ 00:46:33.739 Awaish Kumar: difference if you use transaction revenue or order total.
394 00:46:37.370 ⇒ 00:46:38.639 Annie Yu: Okay, got it.
395 00:46:46.460 ⇒ 00:46:53.809 Annie Yu: Okay? So that’s really helpful. Thank you so much. So I’m not sure if you will need another ticket
396 00:46:54.070 ⇒ 00:46:56.630 Annie Yu: for that? Or do you already have one.
397 00:46:58.018 ⇒ 00:47:02.291 Robert Tseng: Sorry. I think I’ve I’ve been multitasking if if you could.
398 00:47:02.800 ⇒ 00:47:05.240 Robert Tseng: well, what ticket do you want me to add.
399 00:47:06.780 ⇒ 00:47:10.430 Demilade Agboola: I’m not sure which one it says, but it’s the one we’re talking about, the
400 00:47:13.250 ⇒ 00:47:17.150 Demilade Agboola: the 5 x like the fact that, like things are. This revenue is 5 x.
401 00:47:17.500 ⇒ 00:47:19.450 Robert Tseng: Oh, right right
402 00:47:20.100 ⇒ 00:47:21.650 Annie Yu: Product, drill, down.
403 00:47:21.650 ⇒ 00:47:22.649 Robert Tseng: Or dig it all back.
404 00:47:22.650 ⇒ 00:47:27.029 Robert Tseng: Yeah, I think.
405 00:47:27.200 ⇒ 00:47:32.309 Annie Yu: It’s in the internal wait, not internal pending client, feedback.
406 00:47:34.290 ⇒ 00:47:37.510 Robert Tseng: Product launch. Dashboard. Yeah, okay,
407 00:47:39.950 ⇒ 00:47:42.840 Robert Tseng: yeah. Can we just bring this back into site, like
408 00:47:43.870 ⇒ 00:47:45.489 Robert Tseng: So we need to.
409 00:47:46.920 ⇒ 00:47:49.390 Robert Tseng: You’re gonna change the model, is it basically what you’re saying.
410 00:47:51.100 ⇒ 00:47:54.729 Demilade Agboola: In summary. Yes, I will make the model.
411 00:47:54.930 ⇒ 00:47:59.009 Demilade Agboola: and you see, for like submission on that, on that on that column.
412 00:48:05.760 ⇒ 00:48:07.779 Robert Tseng: I think Jim should. Let’s just
413 00:48:11.510 ⇒ 00:48:12.729 Robert Tseng: okay. Cool.
414 00:48:14.410 ⇒ 00:48:23.249 Robert Tseng: alright. Yeah. So if we get that really, yeah, we we fix that. And then we fix the customer journey. I think that’ll set us up to finish out this week. Strong.
415 00:48:23.624 ⇒ 00:48:36.595 Robert Tseng: Yeah, I know we did. We’re at. We’re at. We’re at time. So I don’t really wanna drag this out too much longer. So a couple of things that are in flight that I mean, I’m assuming we just didn’t get to. So like v, 2, I don’t think we’ve got to this.
416 00:48:37.560 ⇒ 00:48:42.552 Robert Tseng: I mean, maybe we’re answering some of the questions with the file size and refills and everything. But
417 00:48:43.130 ⇒ 00:48:44.730 Robert Tseng: yeah. And then.
418 00:48:45.476 ⇒ 00:48:51.913 Robert Tseng: yeah, I mean, this will. We’ll just. We’ll be revisit this next week. So overall, I I think we’re okay.
419 00:48:52.460 ⇒ 00:49:02.419 Robert Tseng: I’m gonna go and call they even CEO, whatever. Now, I gotta ask him some questions. So alright, thanks everyone. Sorry. That was kind of an abrupt end.
420 00:49:04.220 ⇒ 00:49:05.740 Annie Yu: Yeah, thank you so much.
421 00:49:05.740 ⇒ 00:49:06.980 Demilade Agboola: Thank you. Bye.
422 00:49:06.980 ⇒ 00:49:07.700 Awaish Kumar: Right.