Meeting Title: Zoom Meeting Date: 2025-06-17 Meeting participants: Robert Tseng, Awaish Kumar, Demilade Agboola, Tigran Sahakyan, Annie Yu
WEBVTT
1 00:02:37.680 ⇒ 00:02:38.900 Robert Tseng: Hey awaii.
2 00:02:40.800 ⇒ 00:02:41.560 Awaish Kumar: Come on!
3 00:03:07.240 ⇒ 00:03:13.739 Robert Tseng: I know you just got back. But can you help them a lot in some way, like I don’t know how much clearer I could have made it like
4 00:03:14.870 ⇒ 00:03:36.949 Robert Tseng: there, I mean, there’s there’s multiple issues. I think my document and my investigation really clarifies what we needed to do to get the customer accounts correct. I think the cogs issue is separate, but I think I think things are on completely on fire. We have not solved this problem. And it’s this is, we cannot go through another day like this. I’m gonna I’m gonna go. I mean.
5 00:03:37.800 ⇒ 00:03:43.040 Robert Tseng: yeah, I just okay, everything needs to go into this.
6 00:03:44.450 ⇒ 00:03:49.659 Awaish Kumar: Oh, okay, I I can work with the military, and I think we can
7 00:03:50.010 ⇒ 00:03:53.789 Awaish Kumar: like pair to pair program together
8 00:03:53.970 ⇒ 00:03:56.429 Awaish Kumar: to investigate and fix the issue.
9 00:03:58.540 ⇒ 00:04:06.770 Robert Tseng: Okay, I mean, I did damage control all day yesterday, and now I wake up with like 20 more messages, because people are saying it’s still not fixed. And I just
10 00:04:08.023 ⇒ 00:04:09.630 Robert Tseng: can’t like
11 00:04:10.030 ⇒ 00:04:14.260 Robert Tseng: this. This. This is the ha. This is the highest part. We have to get this data right.
12 00:04:15.590 ⇒ 00:04:17.250 Awaish Kumar: Yeah, yeah, okay, sure.
13 00:04:23.010 ⇒ 00:04:25.630 Awaish Kumar: actually, like, I just opened up
14 00:04:25.960 ⇒ 00:04:30.640 Awaish Kumar: this so yeah, from yesterday. And I will
15 00:04:31.160 ⇒ 00:04:35.179 Awaish Kumar: go over what whatever was done, and I will.
16 00:04:35.920 ⇒ 00:04:40.039 Awaish Kumar: He’s here as well.
17 00:04:52.020 ⇒ 00:04:52.424 Robert Tseng: Hey?
18 00:04:56.770 ⇒ 00:05:02.980 Robert Tseng: Okay? So yeah, can you? Before, yeah, where- where are we? With everything.
19 00:05:04.020 ⇒ 00:05:10.485 Demilade Agboola: So I have 2 models, basically, or 2 ideas that are modeled out. I just need
20 00:05:11.450 ⇒ 00:05:16.039 Demilade Agboola: and to be able to decide what works for the dashboard that we are building.
21 00:05:16.590 ⇒ 00:05:18.320 Demilade Agboola: So there are 2 ways.
22 00:05:18.320 ⇒ 00:05:20.579 Robert Tseng: So we haven’t updated the total customers.
23 00:05:21.410 ⇒ 00:05:22.439 Demilade Agboola: No, we haven’t.
24 00:05:25.110 ⇒ 00:05:25.700 Robert Tseng: Okay.
25 00:05:25.700 ⇒ 00:05:30.930 Demilade Agboola: Because, yeah, because if we just if I just do total customers
26 00:05:31.950 ⇒ 00:05:42.739 Demilade Agboola: because it’s a distinct, it’s a dynamic thing. It’s based off the filter that we change and say, Hey! Over the last 30 days. I want to see the unique customer. So that means we’re going to have to recalculate
27 00:05:42.940 ⇒ 00:05:55.760 Demilade Agboola: the distinct, the distinct count over the last 30 days. If someone wants to say over the last 14 days, that has to be a new distinct count, but being able to have a model that has those distinct counts ready
28 00:05:57.160 ⇒ 00:06:05.330 Demilade Agboola: is what is what the model is about. But I did the 1st one, which is what I sent to Anne. And I was like, this is the output of that model.
29 00:06:05.450 ⇒ 00:06:09.940 Demilade Agboola: And she’s like, okay. But if the person dynamically picks
30 00:06:11.610 ⇒ 00:06:25.340 Demilade Agboola: a date like just random. So picking, you know, the last 7 days or the last 30 days, they decide to pick from, you know, the 1st of January to the 28th of May, or something something dynamic like that. How do we like calculate with that?
31 00:06:25.830 ⇒ 00:06:30.470 Demilade Agboola: So I built the model out for that
32 00:06:31.021 ⇒ 00:06:40.500 Demilade Agboola: but I don’t know if it’s in the form that she’ll necessarily be able to use. So I was waiting for her to like, come, come online and we can quickly go over it, and then I’ll push the model.
33 00:06:45.250 ⇒ 00:06:45.990 Robert Tseng: Okay.
34 00:06:58.880 ⇒ 00:07:03.269 Demilade Agboola: But then we can decouple the part of calculating customers.
35 00:07:03.400 ⇒ 00:07:06.360 Demilade Agboola: The customer counts with the current model.
36 00:07:09.010 ⇒ 00:07:15.829 Robert Tseng: Yeah, I mean, yeah. The point is that our total customers calculation is is over calculated. I mean, I feel like I said
37 00:07:16.000 ⇒ 00:07:22.290 Robert Tseng: things that I did. I mean, if these queries that I wrote don’t help like I don’t. I don’t really know. I just.
38 00:07:23.680 ⇒ 00:07:28.809 Demilade Agboola: No, no like. If you look at the outspreet I sent the numbers match with the
39 00:07:29.240 ⇒ 00:07:34.969 Demilade Agboola: with what you sent like. They’re fine, the numbers are fine. But Anne’s feedback was just this.
40 00:07:34.970 ⇒ 00:07:38.219 Robert Tseng: Yeah, it’s not dynamic for the for the dashboard.
41 00:07:38.220 ⇒ 00:07:43.900 Demilade Agboola: Yeah. So if if she was fine with that I would have pushed that yesterday, we won’t have any issues. We’ll be fine.
42 00:07:44.581 ⇒ 00:07:48.599 Demilade Agboola: So I just want to run the new one by her this morning, and that’s it.
43 00:07:49.960 ⇒ 00:07:50.680 Robert Tseng: Okay.
44 00:09:37.250 ⇒ 00:09:38.949 Robert Tseng: what’s the issue with the cogs?
45 00:09:48.230 ⇒ 00:09:54.579 Robert Tseng: Or I having this open until we solve all the product problems like, can’t I?
46 00:09:54.800 ⇒ 00:10:12.700 Robert Tseng: Yeah, I don’t know what else to do. Like we just we have. We have to reestablish the trust here, and it’s urgent. I tried to bias time yesterday, and I did everything I could for damage control. But I wake up this morning and get a bunch of angry messages again. So like it, just it feels like we’re not there yet, so
47 00:10:12.940 ⇒ 00:10:16.559 Robert Tseng: I don’t really know what else you’re working on. But everything else needs to stop
48 00:10:17.020 ⇒ 00:10:33.940 Robert Tseng: like this. This. This is the highest priority, and I will. I will stay on, and just keep asking questions until we’re until we’re done. If I need to do another investigation and and drop and cancel my meetings to do it, I will. But, like I, I just need to know what’s going on. What are we aware of? Like, what are we? I just need to know what we’re doing.
49 00:10:37.100 ⇒ 00:10:43.560 Awaish Kumar: Yeah, the the other issue is within the fact transaction. And it’s maybe coming from product mapping sheet.
50 00:10:46.890 ⇒ 00:10:50.269 Demilade Agboola: Oh, so I’m looking at that now. I’m trying to see.
51 00:10:50.830 ⇒ 00:11:00.399 Robert Tseng: Okay, yeah, I’m on here. I’m responding to all the Eden angry messages you can just tag like tag me where I need to. But otherwise I have a bunch of things to respond to.
52 00:11:04.040 ⇒ 00:11:04.525 Awaish Kumar: Okay.
53 00:36:55.880 ⇒ 00:37:00.619 Demilade Agboola: Alright, Robert, what issues are the Eden seeing with the data today?
54 00:37:03.230 ⇒ 00:37:10.660 Demilade Agboola: Cause I saw Adam’s Adam mentioned? He couldn’t see. June 2025. In his report I saw that.
55 00:37:11.200 ⇒ 00:37:11.720 Robert Tseng: Yeah.
56 00:37:11.720 ⇒ 00:37:13.090 Demilade Agboola: Any other issues.
57 00:37:13.450 ⇒ 00:37:23.149 Robert Tseng: Yes, there are other things. There’s sales, by state
58 00:37:23.918 ⇒ 00:37:29.300 Robert Tseng: thing that we didn’t get right. And he had sent a query. So I’m gonna pretty much just
59 00:37:30.270 ⇒ 00:37:35.126 Robert Tseng: try to do that. So like for the on the accounting side, they need to know.
60 00:37:36.650 ⇒ 00:37:43.370 Robert Tseng: yeah, sales refunds discounts by state. I don’t really know if we’ve really taken that request before. So.
61 00:37:44.410 ⇒ 00:37:48.509 Robert Tseng: but whatever it’s, it’s urgent. The tax deadline is this week, or whatever
62 00:37:48.650 ⇒ 00:37:51.127 Robert Tseng: actually it was yesterday. And then,
63 00:37:51.890 ⇒ 00:37:56.470 Robert Tseng: yeah, Cutter is just giving feedback on the data he’s seeing. He’s saying that
64 00:38:00.860 ⇒ 00:38:14.030 Robert Tseng: some stuff just looks low. I’m like, I’m like trying to better understand like people don’t really give me much clarity. So I I think people are still questioning the data. And they’re just the total customers. Thing is like a big issue like.
65 00:38:14.230 ⇒ 00:38:37.109 Robert Tseng: how did you push a change? And customers are not fixed. Okay, I’m like explaining that. And then also the product revenues like, why, why would it be different? I mean, I just people are just not understanding how to read this chart and the logic behind it. So I just, I think we just need a way to. We just need to communicate how we’re calculating things. And
66 00:38:38.050 ⇒ 00:38:39.929 Robert Tseng: yeah, I mean, that’s that’s
67 00:38:40.240 ⇒ 00:38:52.780 Robert Tseng: what I’m doing. I don’t. I don’t know how much of it is. Just noise versus if there’s any signal and what they’re saying, I’m I’m trying to sort through it. But yeah, I mean, I’ve just been responding to messages. The impact the past like 2030 min.
68 00:38:54.460 ⇒ 00:38:55.585 Demilade Agboola: No. Okay. Okay.
69 00:38:58.160 ⇒ 00:39:16.279 Demilade Agboola: yeah. I think it does. We should clarify that the new numbers, for instance, will be different from the old numbers like clearly state that also, while addressing the double counting issue, that we have especially what the last like 30 days like once, it’s an extended period of time.
70 00:39:16.820 ⇒ 00:39:20.100 Demilade Agboola: The total customer accounts will be problematic.
71 00:39:22.270 ⇒ 00:39:25.660 Robert Tseng: Could you summarize what you just said? I’m not. I’m not really following. Yeah.
72 00:39:26.240 ⇒ 00:39:28.430 Demilade Agboola: I said, basically, we just need to communicate like
73 00:39:28.580 ⇒ 00:39:35.520 Demilade Agboola: for the new metrics that we’ve put out, which ones are the like. The new definition on, why, that’s different.
74 00:39:35.936 ⇒ 00:39:43.950 Demilade Agboola: And also for things like by states. I know that we have them, our dam shipments that we can use to be able to get that as well.
75 00:39:44.260 ⇒ 00:39:48.239 Demilade Agboola: Map it to the refunds that we have. Because we have refund.
76 00:39:48.570 ⇒ 00:39:54.679 Demilade Agboola: we can use the other Id to type back, or the other number to type back to these States, and we can try and use that as well.
77 00:39:55.600 ⇒ 00:40:19.260 Robert Tseng: Okay, yeah, my lead on you for that. I’m gonna basically, I’ve been asking, just give me stripe access, and I’ll try to use that as a source of truth. And then, yeah, we’re gonna have to come at it from 2 different angles. We need to see what stripe is saying. And we need to see what our data is saying, and then be able to come to a number, because whatever Andy shared with them first, st just I mean, I think it was like off by 80% of what they expected. So like.
78 00:40:19.630 ⇒ 00:40:24.730 Robert Tseng: I maybe she just queried it incorrectly. I don’t. I don’t really know I just I didn’t really check.
79 00:40:27.360 ⇒ 00:40:30.400 Demilade Agboola: Yeah. But then we updated it. Is it still off.
80 00:40:33.665 ⇒ 00:40:41.079 Robert Tseng: I mean, I’m talking about the accounting request right now, but I don’t. I’m I’m assuming. That’s what you were referring to when you’re talking about refunds and everything.
81 00:40:42.709 ⇒ 00:40:53.580 Demilade Agboola: No, we, you know we did. The Colorado states like the sales of Colorado. But then it was off, and then we made the fix, and then we send the new data.
82 00:40:53.780 ⇒ 00:40:55.620 Demilade Agboola: I think that was fine.
83 00:40:59.150 ⇒ 00:41:00.810 Robert Tseng: Because because if fine.
84 00:41:01.790 ⇒ 00:41:03.300 Demilade Agboola: Okay, that’s right.
85 00:41:03.850 ⇒ 00:41:04.329 Robert Tseng: If it’s fine.
86 00:41:04.330 ⇒ 00:41:08.800 Demilade Agboola: And that will be the basis for us to do things like refunds and sales by different states.
87 00:41:12.310 ⇒ 00:41:12.960 Robert Tseng: Okay.
88 00:41:15.200 ⇒ 00:41:17.450 Robert Tseng: Well, here, I’ll like.
89 00:41:47.890 ⇒ 00:41:50.439 Robert Tseng: Okay, I just sent you what Annie had sent
90 00:41:50.820 ⇒ 00:41:55.889 Robert Tseng: to the accountant saying like, this is what our total revenue was by state.
91 00:41:58.310 ⇒ 00:42:05.560 Robert Tseng: Maybe this is just June, or like I don’t know what I I just I just don’t know. Like, is this, is this like the right number. Like, I, I’m not.
92 00:42:06.900 ⇒ 00:42:07.690 Robert Tseng: Yeah.
93 00:42:08.270 ⇒ 00:42:09.540 Robert Tseng: Once again, like I,
94 00:42:09.910 ⇒ 00:42:17.139 Robert Tseng: I default to assuming what people are telling me is just noise, and I need to go and figure out what signal is actually in there. But like
95 00:42:17.330 ⇒ 00:42:26.039 Robert Tseng: this is this is the data set that’s in question. That’s causing the accounting team to Bro to blow up because they don’t. They don’t like. They don’t trust what we’re saying anymore from this.
96 00:42:27.020 ⇒ 00:42:27.420 Demilade Agboola: Andrea.
97 00:42:28.010 ⇒ 00:42:29.950 Robert Tseng: Don’t really know? Like, I,
98 00:42:30.700 ⇒ 00:42:35.159 Robert Tseng: yeah, okay, I haven’t. I’m just responding to things. I haven’t actually looked into it. So
99 00:42:37.770 ⇒ 00:42:50.509 Robert Tseng: yeah, so if you could just check like, Hey, is this what we’re seeing? If we’re Colorado like this? At least Colorado match what Eddie had said. If it does, then maybe that’s like, okay, well, maybe we did do it correctly, and we just need to.
100 00:42:50.920 ⇒ 00:42:57.209 Robert Tseng: I mean, I I would just. I would need to confirm at least that first, st like I don’t know how she built this.
101 00:43:05.150 ⇒ 00:43:16.239 Robert Tseng: but I mean, I think they’re the urgent thing is really just 75 units to 14 K revenue seems low. Okay, what? What does that even really mean? I’m just gonna share my screen. And we’re just gonna
102 00:43:16.990 ⇒ 00:43:21.310 Robert Tseng: you don’t have to look at it. But like just this is, this is literally what I’m doing. So
103 00:43:23.180 ⇒ 00:43:31.049 Robert Tseng: I’m like, what are you talking about? 14 k 17 like? I don’t know where these numbers are coming from. Just like
104 00:43:33.850 ⇒ 00:43:44.430 Robert Tseng: all I said was, okay, give us more time on the total customers. Number and yeah, 75 units to 14 K. Like. I don’t even know where those numbers are coming from.
105 00:43:51.000 ⇒ 00:43:56.450 Demilade Agboola: Can you check the dash up above that or I don’t. Okay. I didn’t put that lost today.
106 00:43:57.290 ⇒ 00:43:58.210 Robert Tseng: Oh!
107 00:44:00.650 ⇒ 00:44:01.660 Demilade Agboola: Gonna see?
108 00:44:03.340 ⇒ 00:44:05.489 Robert Tseng: Okay, he’s saying, this looks low.
109 00:44:07.680 ⇒ 00:44:08.750 Demilade Agboola: Yeah.
110 00:44:14.880 ⇒ 00:44:15.890 Demilade Agboola: Don’t know.
111 00:44:17.550 ⇒ 00:44:20.030 Demilade Agboola: 14 can schedule.
112 00:44:43.610 ⇒ 00:44:45.500 Robert Tseng: Sum of new product revenue.
113 00:44:45.640 ⇒ 00:44:49.920 Robert Tseng: That’s what I said, I said. This is should be some of new based off new product users.
114 00:44:53.030 ⇒ 00:44:53.820 Demilade Agboola: Hello!
115 00:45:09.460 ⇒ 00:45:14.061 Robert Tseng: I have to do this the hard way just gonna literally just go and
116 00:45:24.840 ⇒ 00:45:28.259 Robert Tseng: okay, our product
117 00:45:33.290 ⇒ 00:45:35.090 Robert Tseng: orders.
118 00:45:37.550 ⇒ 00:45:38.680 Robert Tseng: Now.
119 00:45:42.290 ⇒ 00:45:45.589 Robert Tseng: this is on what the past day, or what am I looking at?
120 00:45:46.660 ⇒ 00:45:48.200 Robert Tseng: Oh.
121 00:45:49.280 ⇒ 00:45:50.530 Demilade Agboola: Yes, it’ll be yesterday.
122 00:45:50.530 ⇒ 00:45:53.850 Robert Tseng: Yesterday. Oh, one day.
123 00:46:07.080 ⇒ 00:46:11.230 Robert Tseng: oh, stated, tried even not even really a
124 00:46:20.690 ⇒ 00:46:22.359 Robert Tseng: I think Tron has it?
125 00:48:01.370 ⇒ 00:48:05.167 Robert Tseng: Well, the best platform.
126 00:48:08.270 ⇒ 00:48:09.780 Robert Tseng: So
127 00:48:29.070 ⇒ 00:48:31.480 Robert Tseng: I mean, this is not really usable.
128 00:48:32.340 ⇒ 00:48:38.870 Robert Tseng: I can’t verify all of this. This is this conflates both new and returning users. There’s no way
129 00:48:44.970 ⇒ 00:48:54.010 Robert Tseng: Oh, yeah, I mean, maybe I would just use order, summary and go and query these these products, like.
130 00:48:56.740 ⇒ 00:48:57.290 Robert Tseng: Okay.
131 00:50:28.000 ⇒ 00:50:35.160 Robert Tseng: Okay, it’s definitely more than 14 K. And take me out.
132 00:50:42.030 ⇒ 00:50:43.730 Demilade Agboola: Oh, that’s going so easy.
133 00:50:46.220 ⇒ 00:50:48.499 Robert Tseng: Yeah. But this is just for the users.
134 00:50:51.140 ⇒ 00:50:56.079 Demilade Agboola: Right, like our 1st time is like this is the 1st time they’re purchasing.
135 00:50:56.640 ⇒ 00:51:02.580 Robert Tseng: Yeah, I know, I know. But like, I’m just eyeballing like, does that even make sense? Like.
136 00:51:03.510 ⇒ 00:51:11.909 Robert Tseng: yeah, I mean, there’s more than 75 here, and then there’s more than 15 and more than 14,000 here makes sense. Majority of our
137 00:51:12.640 ⇒ 00:51:22.600 Robert Tseng: looks like most of these, probably are new users. And yesterday, like, Yeah, I I could believe that the.
138 00:51:25.740 ⇒ 00:51:29.549 Demilade Agboola: For instance, med kids like Med kids exactly is the same.
139 00:51:30.370 ⇒ 00:51:32.360 Demilade Agboola: So everyone was new yesterday.
140 00:51:33.111 ⇒ 00:51:41.290 Demilade Agboola: Is there 2 diff like to repeat? We might look into that. But there seems to be
141 00:51:41.670 ⇒ 00:51:44.150 Demilade Agboola: just only 5 versus 7.
142 00:51:46.020 ⇒ 00:51:46.750 Robert Tseng: Yeah.
143 00:51:46.750 ⇒ 00:51:48.520 Demilade Agboola: Out like
144 00:51:58.310 ⇒ 00:52:04.389 Demilade Agboola: I don’t know just it doesn’t look that off to me like we could always do like dig deeper, but I don’t truly think he looks that off.
145 00:52:04.820 ⇒ 00:52:09.810 Robert Tseng: Yeah, I mean, I don’t. I’m not saying that is off. I think they’re just I mean, he’s pretty.
146 00:52:09.960 ⇒ 00:52:13.180 Robert Tseng: So like people. Gonna just
147 00:52:14.030 ⇒ 00:52:23.390 Robert Tseng: I mean, obviously, like Hunter would prefer that it’s higher. So if it’s lower than he expects, he’s gonna want to blame us, because, obviously like that’s
148 00:52:23.680 ⇒ 00:52:24.810 Robert Tseng: it makes them look back.
149 00:52:24.810 ⇒ 00:52:28.200 Demilade Agboola: And so he’s making his eyes. Kpis.
150 00:52:28.390 ⇒ 00:52:47.689 Robert Tseng: Yeah. So like, I think that’s just, we always kind of have to be able to defend these questions. People are always gonna be like, are you sure? Can you verify it? And like, I don’t know. Maybe we just need to have like a more like a quicker way to like I mean, I don’t think this is slow. I can already just like eyeball it and be like, Okay, look dude like.
151 00:52:47.910 ⇒ 00:52:55.019 Robert Tseng: yesterday we sold $20,000 worth of stuff. 14,000 of it came from new products, and these are the users like I.
152 00:52:55.320 ⇒ 00:52:59.639 Robert Tseng: I’m not. I’m not. I don’t seem off to me like I can. I can say that. But
153 00:52:59.830 ⇒ 00:53:03.820 Robert Tseng: so like, maybe that’s all I need. If he wants to dig more, I can dig more into it. Just fine.
154 00:53:05.850 ⇒ 00:53:08.270 Robert Tseng: Yeah.
155 00:53:16.070 ⇒ 00:53:16.850 Robert Tseng: okay.
156 00:53:37.920 ⇒ 00:53:44.310 Robert Tseng: Okay. Well, other people are about to jump on this call. So I mean, we’re gonna go through our regular stand up. I haven’t groomed any tickets. But
157 00:53:44.970 ⇒ 00:53:48.269 Robert Tseng: yeah, I think we’re we’re just gonna we’re gonna need to do that.
158 00:53:55.350 ⇒ 00:54:08.730 Robert Tseng: So can we like for what’s remaining to get to restore confidence. Are we like clear on, like what we need to do to restore confidence? One is fixing total customers that needs to be done. It needs to be communicated
159 00:54:09.050 ⇒ 00:54:14.380 Robert Tseng: to this cogs thing that we’re talking about transactions, duplicate transaction, whatever it is.
160 00:54:15.190 ⇒ 00:54:34.519 Robert Tseng: But yeah, I think that’s that’s that. That’s me. It’s like that that needs to be to be dealt with. And then, yeah, I think getting to the bottom of like, why can we not show sales by by state, like, I think you know, I think those are like the 3 3 main things that we need to to get right. Asap. So
161 00:54:36.490 ⇒ 00:54:38.369 Robert Tseng: yeah, like, I.
162 00:54:40.970 ⇒ 00:54:47.419 Robert Tseng: So, you know, when that is that fair like? Are we? Are we on track to do that?
163 00:54:49.356 ⇒ 00:55:00.709 Demilade Agboola: So we’re thinking about the custom accounts. Yes, as far as delivery by state will be its own, like model or like, we’ll look at how we want to do that. We want to integrate it into
164 00:55:02.830 ⇒ 00:55:04.890 Demilade Agboola: yeah, I didn’t get the second one, though.
165 00:55:05.720 ⇒ 00:55:07.770 Demilade Agboola: That was the 1st and 3.rd
166 00:55:09.190 ⇒ 00:55:09.890 Robert Tseng: Okay.
167 00:55:11.240 ⇒ 00:55:11.745 Demilade Agboola: Like?
168 00:55:13.240 ⇒ 00:55:14.860 Demilade Agboola: What was the second request?
169 00:55:16.100 ⇒ 00:55:21.150 Robert Tseng: Yeah. Well, I mean a waste flag like duplicate transactions, or something like what? I don’t know. Something.
170 00:55:21.550 ⇒ 00:55:22.040 Awaish Kumar: Oh, yeah, so.
171 00:55:22.410 ⇒ 00:55:24.320 Demilade Agboola: We’re we’re digging into that here.
172 00:55:25.050 ⇒ 00:55:45.840 Awaish Kumar: I have been looking into this, and we so some some duplicates. Rows were coming from raw data which I have deduplicated it like, I’m I’m pushing a fix for that. But like, the product mapping sheet which is filled by manually by by the item, team has duplicates, which, basically
173 00:55:46.915 ⇒ 00:55:53.850 Awaish Kumar: like is the reason our orders are getting duplicated. And like, one way is that we can just
174 00:55:54.358 ⇒ 00:56:10.730 Awaish Kumar: deduplicate those sheets as well. But the only issue is with the variant names. So I’m just sending an example in the slack channel. Like, we have the same variant id, but 2 different names for that. Although related but a little bit different.
175 00:56:10.950 ⇒ 00:56:15.909 Awaish Kumar: So if we do deduplicate it like we are going to pick one randomly
176 00:56:16.060 ⇒ 00:56:22.450 Awaish Kumar: using SQL, we will say like, Give, get the 1st row number whatever, and it will pick one.
177 00:56:22.580 ⇒ 00:56:32.900 Awaish Kumar: But like, do we want to deduplicate it? Or do we want to send this to Eden team, so they don’t fill out the different names with same variant Id.
178 00:56:35.944 ⇒ 00:56:42.779 Demilade Agboola: I think we can. I will say we’ll handle it. But the problem is, sometimes these 2 different variant ids have 2 different cogs.
179 00:56:43.210 ⇒ 00:56:44.519 Demilade Agboola: So that means
180 00:56:44.660 ⇒ 00:56:51.150 Demilade Agboola: because the cogs values change. So my guess is what’s happening is when they get these new values. You just kind of pasting it without checking
181 00:56:51.530 ⇒ 00:56:55.550 Demilade Agboola: to see what what is happening. Over.
182 00:56:55.780 ⇒ 00:56:58.379 Awaish Kumar: Like, but this has, like same variant id.
183 00:56:59.370 ⇒ 00:57:10.479 Demilade Agboola: Yeah. So the the id like the rent id will be the same. But like some differences would occur like in terms of maybe the numbers like in terms of cogs or something.
184 00:57:10.680 ⇒ 00:57:12.150 Demilade Agboola: That’s what I noticed.
185 00:57:13.300 ⇒ 00:57:19.249 Demilade Agboola: And so that’s the place so like at the end of the day we’ll need to either come back to them and ask them which of these cogs value should we delete?
186 00:57:20.080 ⇒ 00:57:24.119 Demilade Agboola: Or because, like that’s part of the the huge issue.
187 00:57:28.140 ⇒ 00:57:28.950 Tigran Sahakyan: Hey, guys.
188 00:57:29.750 ⇒ 00:57:30.710 Robert Tseng: Thank you. Grant.
189 00:57:31.410 ⇒ 00:57:32.240 Demilade Agboola: Hi Tigran!
190 00:57:35.531 ⇒ 00:57:39.840 Tigran Sahakyan: Usually Elt is also joining these meetings, or that’s just we.
191 00:57:40.670 ⇒ 00:57:58.500 Robert Tseng: Oh, josh comes whenever he feels like it. I mean Mattesh sometimes come, I mean, I like kind of we. We open it so if anybody wants to join, they can. But we were just meeting earlier today because we were dealing with some urgent stuff. So rather than moving rooms. We just stayed in this one.
192 00:57:59.230 ⇒ 00:58:08.730 Tigran Sahakyan: Okay. Okay, guys, you can, you can do your stand up meeting, because this is 1st time I’m here. And in the end I will ask questions is, how, if I will have any.
193 00:58:09.020 ⇒ 00:58:10.499 Robert Tseng: Yeah, sure.
194 00:58:11.810 ⇒ 00:58:12.590 Robert Tseng: Okay.
195 00:58:20.460 ⇒ 00:58:26.280 Robert Tseng: okay, yeah. So let’s let’s just finish. Let’s close the loop on what we’re saying there. So
196 00:58:26.820 ⇒ 00:58:36.149 Robert Tseng: okay, I hear, we have duplicate products. We have duplicate. You know, we have duplicate products in our mapping sheet that’s maintained by our team. And then also, we’re seeing duplicate transactions come in.
197 00:58:36.260 ⇒ 00:59:02.960 Robert Tseng: My question in a way should be, we need to make sure if those duplicate, because bask does sometimes fire duplicate transactions. We’ve looked at this before. Right? We’ve looked at what was it called like orphan transactions or orphan orders with duplicate transactions, or we’ve looked into something like that. So I think we saw that there was like a 14 to 10 to 1210 to 14 day window before the transactions really like settle
198 00:59:03.330 ⇒ 00:59:06.859 Robert Tseng: but like. I think there is some misfiring that happens right.
199 00:59:08.633 ⇒ 00:59:13.490 Demilade Agboola: Yes. But I think in this case, like what we’re looking at, the issues are
200 00:59:13.840 ⇒ 00:59:24.200 Demilade Agboola: because we’re trying to add folks information to the orders information so that we can easily have an idea of for each order what was the call associated with that order?
201 00:59:24.410 ⇒ 00:59:40.160 Demilade Agboola: The problem here is on the mapping sheets. There are 2 for the same variant. Id. There are 2 different rows with different cogs values, and so that fans out the orders that come in from desk. So now we’ll have 2 rows
202 00:59:40.280 ⇒ 00:59:47.290 Demilade Agboola: with the same order. Id. But the difference here is the cogs. Values are different, because the product sheet has 2.
203 00:59:49.250 ⇒ 00:59:59.489 Demilade Agboola: So that’s so, this is like a manual error, basically. And if we’re trying to dedupe, we will still need the Eden team because we don’t necessarily know which cogs value is the latest and correct one.
204 01:00:00.370 ⇒ 01:00:01.319 Robert Tseng: Oh, I see!
205 01:00:03.760 ⇒ 01:00:10.319 Demilade Agboola: So it’s it’s system design thing, where we need to think about how exactly.
206 01:00:10.320 ⇒ 01:00:10.870 Robert Tseng: Okay.
207 01:00:11.410 ⇒ 01:00:13.409 Demilade Agboola: This comes in, and what we need to do.
208 01:00:14.100 ⇒ 01:00:24.160 Robert Tseng: Yeah. So I mean, this doesn’t seem like an easy fix. So transaction, the dupe
209 01:00:28.770 ⇒ 01:00:31.659 Robert Tseng: for cogs, reconciliation
210 01:00:35.090 ⇒ 01:00:37.880 Robert Tseng: and model right? So
211 01:00:38.500 ⇒ 01:00:46.740 Robert Tseng: temporarily, just gonna assign it to you. Because this is kind of more in your in your camp. We should do that in cycle. Be high. I’ll fill the details more later.
212 01:00:47.401 ⇒ 01:00:52.869 Robert Tseng: This is going to be part of. So we’ve also talked about the amortization thing. So
213 01:00:53.750 ⇒ 01:00:59.379 Robert Tseng: and who who on this call is aware of the amortization ticket. I don’t think I’ve really talked too much about it.
214 01:01:00.110 ⇒ 01:01:01.889 Robert Tseng: I forgot who I talked about it with.
215 01:01:02.656 ⇒ 01:01:09.049 Demilade Agboola: With me, you it’s assigned to me, and I attended the call last week with the finance team.
216 01:01:09.440 ⇒ 01:01:16.535 Robert Tseng: Okay, yeah, so this is gonna impact that right? Because they’re trying to recognize revenue and and cogs.
217 01:01:17.680 ⇒ 01:01:24.400 Robert Tseng: well, yeah, like, in a way where they can actually advertise enterprises spend. So
218 01:01:25.210 ⇒ 01:01:30.489 Robert Tseng: yeah, I mean, do you see that as a dependency like kind of what? How do you? How do you connect the 2.
219 01:01:33.510 ⇒ 01:01:42.979 Demilade Agboola: I mean, we can always amortize the revenue itself. But obviously, when it comes to the cogs, the big problem now is, we need to have a way to get reliable cogs in
220 01:01:43.914 ⇒ 01:02:01.265 Demilade Agboola: for, like 2 in 2 different ways, one is, we need to be sure that we’re not getting duplicates of the same variants like so like what we have now. So the same variant Id has 2 rows with 2 different plugs. That’s a problem, and then 2 is we need to be able to ensure that
221 01:02:01.930 ⇒ 01:02:06.560 Demilade Agboola: for proper revenue tracking. We can also track when the cogs values change
222 01:02:07.070 ⇒ 01:02:23.480 Demilade Agboola: so we can create Dbt snapshots, so we can say from this day to this day. This was the cogs. And then from this day to this day this was the new cogs value, so that for each transaction we can assign the appropriate cogs. And that’s that’s will be useful, accurate revenue transaction or calculation. Sorry?
223 01:02:24.083 ⇒ 01:02:31.189 Demilade Agboola: So I think that’s those are the things we need to consider when we’re designing in the system to be able to accommodate like proper revenue tracking.
224 01:02:31.769 ⇒ 01:02:38.159 Demilade Agboola: handling dupe, handling dupes as well as handling the periods in which the cost values change.
225 01:02:40.920 ⇒ 01:02:44.800 Robert Tseng: Okay, I don’t.
226 01:02:45.020 ⇒ 01:02:55.119 Robert Tseng: I feel like I need more time to understand what you’re describing there. So I don’t know what would be helpful. Can you put together like a spike, Doc, or like something for me to read through like.
227 01:02:55.730 ⇒ 01:03:03.539 Robert Tseng: yeah, like, I don’t. I don’t fully understand the sequence there. So I don’t really know how to get that out. So I, this is gonna be, yeah, okay. If you could help me with that.
228 01:03:03.760 ⇒ 01:03:16.380 Robert Tseng: So I’m just gonna call it spike on our new amortization.
229 01:03:19.860 ⇒ 01:03:21.480 Robert Tseng: Yeah, whatever. And
230 01:03:26.320 ⇒ 01:03:52.029 Robert Tseng: okay. So I know this is really our 1st stand up for the day of the week, so I didn’t. With all the craziness going on, everything has been groomed. So few things I need from this team. One is in progress. Everything is on you to kind of move. I expect this to kind of be cleared out. There’s no way we’re doing 20 tickets. In in this cycle. A lot of these have been carried over from last cycle. So I want everybody to go and and takes
231 01:03:52.270 ⇒ 01:04:18.040 Robert Tseng: take a couple of minutes. We’re gonna just like pause. Take a couple of minutes, update your tickets in terms of like getting everything out of in progress. Nothing should remain here, because this is all carried over from last last cycle. So things that need to be escalated we can talk through. If not, things are done, then we should move it. So I think this is stale. So I I can’t really properly introduce new things in cycle until this is cleared. So let’s just take a couple of minutes to do that right now.
232 01:04:20.890 ⇒ 01:04:30.149 Robert Tseng: I mean, I’ll keep sharing my screen, because I’ll do the ones for myself, too. But I’ll I’m just setting a timer. We’ll we’ll we’ll meet back, I mean. Well, we’ll talk in a couple of minutes.
233 01:04:40.702 ⇒ 01:04:45.749 Demilade Agboola: The recurre recurrent ones? Do we have to move them from in progress, so we can leave them in progress.
234 01:04:46.242 ⇒ 01:04:58.359 Robert Tseng: Yeah, no, you have to move those 2, because, the way that I’ve set up the recurring it will. There will be a new ticket that basically replaces it every week or 2 weeks. So if you just leave it in progress, we’ll get like a random like duplicate.
235 01:04:58.980 ⇒ 01:05:01.809 Robert Tseng: Yeah, I just need to know whether or not you action it. Yeah.
236 01:05:07.630 ⇒ 01:05:14.900 Annie Yu: So for the once that’s done, should I close it out, or just leave a comment, saying, This done.
237 01:05:14.900 ⇒ 01:05:19.170 Robert Tseng: Yeah, you can close it out. It’s fine, I I and that would save me like an extra step.
238 01:05:19.690 ⇒ 01:05:25.540 Robert Tseng: Normally I will close it out. But I just, I’m we’re just behind. So okay,
239 01:05:31.040 ⇒ 01:05:32.560 Robert Tseng: down there.
240 01:05:34.630 ⇒ 01:05:37.570 Robert Tseng: Alright. So it is
241 01:06:48.390 ⇒ 01:06:49.780 Robert Tseng: they forecast.
242 01:07:10.860 ⇒ 01:07:13.119 Robert Tseng: Okay, ready.
243 01:07:13.510 ⇒ 01:07:15.909 Robert Tseng: We need a couple of minutes. I know some of you have a few more.
244 01:07:23.250 ⇒ 01:07:25.060 Robert Tseng: Let’s just do it. Then.
245 01:07:25.950 ⇒ 01:07:44.410 Robert Tseng: Okay. So I have tea ground on this call, Andy. I know I you guys just met. So here’s how T. Ground is going to support us. So in terms of anything that’s in terms of and waiting for client review, his job is. Gonna look at this. And the these are like we’re just waiting for client feedback. We’re kind of blocked until they give us some feedback right?
246 01:07:44.827 ⇒ 01:07:54.469 Robert Tseng: And so I think if you need us to kind of like, follow up with someone. Let’s just take this one cohort based heat map for Ltv, we kind of get some feedback from Mattesh.
247 01:07:55.100 ⇒ 01:08:00.160 Robert Tseng: I mean, I think we can close this out. We kind of know that he’s not using it. So maybe this one doesn’t need to be in client.
248 01:08:00.910 ⇒ 01:08:05.520 Demilade Agboola: Yeah, Hi, Robert, I I don’t think you’re you’re sharing your screen, or I can’t see your screen.
249 01:08:05.880 ⇒ 01:08:07.209 Robert Tseng: Oh, got it?
250 01:08:12.240 ⇒ 01:08:17.070 Robert Tseng: Yeah, sorry. So I was talking about client review. This is where you guys support us.
251 01:08:17.479 ⇒ 01:08:30.739 Robert Tseng: I’m just I just pulled this one as the example. Where? Yeah, he, he’s gonna be kind of helping us push this daily so that we can make sure that I’m not the bottleneck for you, getting in front of the stakeholder and and getting a response.
252 01:08:30.859 ⇒ 01:08:37.779 Robert Tseng: This one probably is not the best example, because I think we already met with Mattesh, and I think we’re good here. So I’m gonna close this out.
253 01:08:40.010 ⇒ 01:08:45.110 Robert Tseng: There is a discrepancy cohort base. Oh, there was a sub issue.
254 01:08:47.630 ⇒ 01:08:53.640 Robert Tseng: Hold on, then, this was this ever done?
255 01:08:56.069 ⇒ 01:08:57.269 Annie Yu: This is done.
256 01:08:57.450 ⇒ 01:09:01.150 Robert Tseng: Okay, I figured. But just yeah.
257 01:09:02.703 ⇒ 01:09:04.199 Tigran Sahakyan: Sorry guys. And as.
258 01:09:06.240 ⇒ 01:09:07.940 Robert Tseng: Yeah, I’ll be back in a minute.
259 01:09:09.430 ⇒ 01:09:10.340 Robert Tseng: Yeah, go ahead.
260 01:09:11.479 ⇒ 01:09:22.640 Robert Tseng: Okay? And then, so as far as like issues with Zack, this will still have to run through me, I don’t really know has the context to do that. So I mean, this is kind of persistent. There’s nothing really to say here.
261 01:09:23.428 ⇒ 01:09:29.170 Robert Tseng: We have. There’s 2 things we ask for him from daily. Now Rebecca wants us to go, and
262 01:09:29.630 ⇒ 01:09:39.019 Robert Tseng: wants us to ask about like time order, time to delivered.
263 01:09:39.580 ⇒ 01:09:43.120 Robert Tseng: How is that calculated? And why is that difference
264 01:09:44.220 ⇒ 01:09:48.260 Robert Tseng: from what we see in our reporting like?
265 01:09:48.689 ⇒ 01:09:55.980 Robert Tseng: I don’t really know if I’m gonna prioritize that it just seems like, not really something that we’re gonna get clarity on. So I’m gonna move this down.
266 01:09:58.990 ⇒ 01:09:59.810 Robert Tseng: Yeah.
267 01:10:00.660 ⇒ 01:10:15.966 Robert Tseng: Okay? And then yeah. So customer, I/O data capabilities. This one, I think. Yeah, we were here. We were looking for feedback from Cutter and from Bobby. We sent him the model. We told him to look at the table.
268 01:10:16.500 ⇒ 01:10:22.409 Robert Tseng: yeah, I’m not really seeing anything more here. So what what it? What are we waiting for? Feedback from.
269 01:10:25.330 ⇒ 01:10:28.120 Awaish Kumar: So we send the new model.
270 01:10:28.230 ⇒ 01:10:31.450 Awaish Kumar: They requested like adding 3 more fields.
271 01:10:33.430 ⇒ 01:10:38.050 Awaish Kumar: So that email conversion is based on email, click, link, click, right?
272 01:10:38.519 ⇒ 01:10:43.199 Awaish Kumar: I’ve shared the data. They will come back today or tomorrow on this
273 01:10:43.390 ⇒ 01:10:45.910 Awaish Kumar: with their feedback on the next.
274 01:10:46.400 ⇒ 01:10:46.920 Awaish Kumar: Let’s.
275 01:10:50.940 ⇒ 01:10:52.790 Robert Tseng: So.
276 01:11:02.100 ⇒ 01:11:20.070 Robert Tseng: yeah, okay, I saw that you had pushed the so yeah, we should. You could just kind of leave a comment in here. And then you can tag Tigran if you need him to follow up with with Bobby and and cut it right, because this was due 10 days ago we saw him close it out. So this is be an example of how I would leverage Tigran to kind of help with escalation here.
277 01:11:21.780 ⇒ 01:11:22.305 Robert Tseng: Okay.
278 01:11:24.230 ⇒ 01:11:47.570 Robert Tseng: alright. Weekly trend line daily Reports. We already fixed this you removed June. So I mean, this is somewhat tied to Adam’s issue, like Josh doesn’t like to see this stuff. He doesn’t like to see the most recent one, because he thinks it throws him off. But then Adam does. And so we’re always gonna get like one person is always gonna be unhappy with what they’re saying, because we didn’t build it for both of them like, it’s just
279 01:11:48.060 ⇒ 01:11:55.589 Robert Tseng: like, I think, for this one. We hit the most recent day, or most recent week, or whatever but it seems like
280 01:11:55.900 ⇒ 01:12:05.093 Robert Tseng: Adam is really insistent that he wants to see the current like month order order sales and all that. So I don’t know if you guys caught that. But
281 01:12:05.880 ⇒ 01:12:06.640 Robert Tseng: here.
282 01:12:07.380 ⇒ 01:12:20.820 Annie Yu: And this oh, and this is a site now for this one executive dashboard right now it’s actually defaulted to the most recent month. So I’m not sure if he’s using probably an old link
283 01:12:21.090 ⇒ 01:12:23.809 Annie Yu: or so. So it’s not showing.
284 01:12:26.890 ⇒ 01:12:27.780 Robert Tseng: I see.
285 01:12:28.110 ⇒ 01:12:36.259 Demilade Agboola: I mean to to be fair. I did check it because it’s the I checked the dashboard, and I couldn’t also see June, so I’m not sure if it’s an old link.
286 01:12:36.260 ⇒ 01:12:37.240 Annie Yu: Wait, really.
287 01:12:37.920 ⇒ 01:12:38.730 Demilade Agboola: Yeah.
288 01:12:40.360 ⇒ 01:12:42.630 Annie Yu: That’s so weird. Okay.
289 01:12:42.630 ⇒ 01:12:45.460 Robert Tseng: Is it because the mobile is different from the desktops.
290 01:12:47.410 ⇒ 01:12:49.330 Annie Yu: Oh! Could that be it.
291 01:12:52.070 ⇒ 01:12:54.369 Demilade Agboola: Cause. I I’m trying.
292 01:12:54.610 ⇒ 01:12:56.459 Demilade Agboola: It’s the retention does right.
293 01:12:57.013 ⇒ 01:12:59.980 Annie Yu: No! Oh, wait! Oh, is this retention?
294 01:13:00.343 ⇒ 01:13:02.160 Demilade Agboola: Yes, it is through Tasha.
295 01:13:02.740 ⇒ 01:13:08.349 Annie Yu: Okay. So I did not check that one. So, okay, I’ll I’ll update it.
296 01:13:09.720 ⇒ 01:13:10.400 Robert Tseng: Okay.
297 01:13:31.113 ⇒ 01:13:40.460 Robert Tseng: Okay. So let’s just get that fixed real quick. And then if you could follow up in that thread, Annie, and just be like, they’re done kind of thing like that’d be helpful.
298 01:13:41.610 ⇒ 01:13:42.320 Robert Tseng: Okay.
299 01:13:45.600 ⇒ 01:13:50.819 Robert Tseng: okay, but yeah, I think this is done. So we’re good.
300 01:13:51.480 ⇒ 01:13:58.539 Robert Tseng: Alright. And then, as far as like stuff that needs review on. Yeah, I think this is a big one. So I mean, we’ve we’ve been talking about
301 01:13:59.410 ⇒ 01:14:05.400 Robert Tseng: a lot of different product data related things. But this is still the Via level, like
302 01:14:05.500 ⇒ 01:14:07.119 Robert Tseng: logic that I need.
303 01:14:07.967 ⇒ 01:14:15.430 Robert Tseng: I know you mentioned. We have a staging model here, so kind of where we at with this this is still blocking me from forecast, so.
304 01:14:17.632 ⇒ 01:14:21.450 Demilade Agboola: Yesterday I wasn’t able to work on this, but I’ll push it out today.
305 01:14:21.850 ⇒ 01:14:22.520 Robert Tseng: Okay.
306 01:14:23.865 ⇒ 01:14:24.230 Robert Tseng: Alright.
307 01:14:24.420 ⇒ 01:14:28.709 Robert Tseng: So I’ll leave that in there.
308 01:14:28.970 ⇒ 01:14:30.060 Robert Tseng: So
309 01:14:35.640 ⇒ 01:14:36.155 Robert Tseng: okay.
310 01:14:38.436 ⇒ 01:14:45.523 Robert Tseng: yeah. The post hoc stuff wish, like, I mean, this is important. It’s just not never urgent.
311 01:14:46.390 ⇒ 01:14:49.789 Robert Tseng: yeah. So there’s a thing. I you know we have the
312 01:14:50.900 ⇒ 01:14:56.254 Robert Tseng: away. You’re you’re in this right? And so I I kind of need you to drive this
313 01:14:58.010 ⇒ 01:15:00.369 Robert Tseng: this effort we just need to like
314 01:15:00.710 ⇒ 01:15:05.020 Robert Tseng: they’re not organized like they’re just building whatever and not keeping us updated. And so
315 01:15:05.140 ⇒ 01:15:08.349 Robert Tseng: like, I don’t know what you need in order to kind of
316 01:15:08.680 ⇒ 01:15:14.010 Robert Tseng: if it’s an architecture diagram, if it’s some sort of like workshop like, I I think we need to
317 01:15:14.310 ⇒ 01:15:28.860 Robert Tseng: be able to show them what the roadmap is on our side from a data perspective like what we need, so that we can have milestones and check ins with them. Right? I can help you put together a doc. But like, I kind of need to know, like, what do you need to know.
318 01:15:29.050 ⇒ 01:15:36.409 Robert Tseng: based on your meetings with them already, like, how do we stay aligned with their their development side so that we can
319 01:15:37.240 ⇒ 01:15:39.309 Robert Tseng: do you understand what I’m driving at. Like.
320 01:15:39.680 ⇒ 01:15:48.069 Robert Tseng: yeah, like, I, I could get organized around this and start the outline and everything. But I think it would be helpful if if you could. If you could put that together first.st
321 01:15:49.837 ⇒ 01:15:56.450 Awaish Kumar: So is this only are we only talking about like this post hogue events
322 01:15:56.570 ⇒ 01:16:02.049 Awaish Kumar: for end intact data? Or is it more like all of the data we
323 01:16:02.690 ⇒ 01:16:04.840 Awaish Kumar: we are going to receive from Emr.
324 01:16:05.300 ⇒ 01:16:13.189 Robert Tseng: Yeah, it’s really all the data we need to see from Emr, so I guess to that point, yeah, this is only really about the post hog events. But then.
325 01:16:13.490 ⇒ 01:16:16.210 Robert Tseng: yeah, so these are the priorities for this week.
326 01:16:16.670 ⇒ 01:16:26.450 Robert Tseng: I’m honestly not sure if we have enough families to go and and take that on. So maybe this should be next cycle like. And that’s fine, like they’re not really close to being done.
327 01:16:26.980 ⇒ 01:16:28.369 Robert Tseng: And if we can.
328 01:16:28.700 ⇒ 01:16:33.450 Robert Tseng: and if we can get everything we need within 2 weeks, then, like, I don’t. I don’t think we need to start it now.
329 01:16:35.191 ⇒ 01:16:40.150 Awaish Kumar: Yeah. So so one of the thing like we discussed I and Utah met last week.
330 01:16:40.910 ⇒ 01:16:50.949 Awaish Kumar: And we discussed about like how we can move forward for this like, like modeling the data for coming from New Emr.
331 01:16:51.470 ⇒ 01:17:01.639 Awaish Kumar: So one of the way we agreed on was like. Like, 1st of all, we create a document like a notion, Doc, where we are basically
332 01:17:02.380 ⇒ 01:17:12.559 Awaish Kumar: documenting all the data and the table and the fields we are receiving from bask and then
333 01:17:13.500 ⇒ 01:17:21.120 Awaish Kumar: like, use this as our current stage, and then we map it out that what what we are going to need from
334 01:17:21.760 ⇒ 01:17:47.299 Awaish Kumar: from the team, like on the new Emr side. For example, we, we have order completed data coming in in a order completed table. Now we need all this data, obviously, and we are going to at minimum need all of the data which is coming in in order completed. But now, when we are mapping it out like, okay, what kind of tables we are going? We are going to ask from New Emr. Then we are going to maybe
335 01:17:47.360 ⇒ 01:17:53.599 Awaish Kumar: clean it out, and also put put. Give us some some better structure than the current one, like.
336 01:17:53.750 ⇒ 01:17:54.240 Robert Tseng: Yeah.
337 01:17:54.240 ⇒ 01:18:08.599 Awaish Kumar: We might ask them to give us like orders data. But in this format, where we have orders, and then we have a table with order. Item, where each product is is separated out like separately, in a like. In a in a way, we get from other e-commerce
338 01:18:09.130 ⇒ 01:18:11.479 Awaish Kumar: sources. So we are going to like
339 01:18:11.600 ⇒ 01:18:23.789 Awaish Kumar: right now. We have only one order completed. But now, in the New Year, we are going to get get all these fields plus this data in in, like, in kind of 2 different tables.
340 01:18:24.050 ⇒ 01:18:24.859 Awaish Kumar: Yeah. And then.
341 01:18:25.222 ⇒ 01:18:26.310 Robert Tseng: Think that’s great.
342 01:18:27.510 ⇒ 01:18:33.479 Robert Tseng: Yeah. And we, we should have all this like knowledge already. Right? Like we, we have other ecom clients like we.
343 01:18:33.620 ⇒ 01:18:52.449 Robert Tseng: you know, we know what the data looks like coming in from shopify from Amazon. From these other sources our Emr should be able to do at least that. And so, yeah, I think this is really for you to kind of create your dream state of like what the schema should look like. And we can make those expectations of like this is what how the data needs to come in.
344 01:18:53.010 ⇒ 01:18:57.249 Robert Tseng: And yeah, I think the earlier we put it in front of them, the probably the better we don’t wanna
345 01:18:57.490 ⇒ 01:19:17.620 Robert Tseng: well, anyway. So it’s like, Yeah, I mean, it seems like you and your time already met and like, kind of talked about this. So I’m gonna yeah, it’s it’s not an urgent thing to. There’s not a deliverable in the next in this sprint cycle, really. But, like I I think if you could just stay on top of and kind of keep this conversation going, I think that that would be important.
346 01:19:18.400 ⇒ 01:19:23.940 Robert Tseng: I don’t want Adam to be following up like a week later and being like, why haven’t? Why, why haven’t I heard anything.
347 01:19:25.924 ⇒ 01:19:37.249 Awaish Kumar: So like only 2 things which we which we are really which are going to impact us, one is all the data coming from bask and then the other one is this Utm data. Right
348 01:19:39.180 ⇒ 01:19:45.139 Awaish Kumar: previously, we are getting all the tracking data from past. Now, we will be getting all this tracking data from Emr, and then.
349 01:19:45.140 ⇒ 01:19:48.589 Robert Tseng: And intake data. So like, yeah, I mean.
350 01:19:49.600 ⇒ 01:19:57.949 Robert Tseng: I don’t know what other parts of the pro of the Mr. System. I mean, I feel like you should know, because you’ve also yeah.
351 01:19:57.950 ⇒ 01:20:02.089 Demilade Agboola: And another thing I I mentioned to Ryan, I believe.
352 01:20:02.280 ⇒ 01:20:14.589 Demilade Agboola: or I’m not sure who it was, but one of them was that we need to have like cogs data if we can get it directly from the pharmacy. So they’ve they’ve said that they would integrate that into their current path.
353 01:20:15.110 ⇒ 01:20:25.780 Demilade Agboola: But the current way in which you get cogs is that they have to reach out to the pharmacies. Pharmacies and the Csv Css. Are then updated in the sheets, and that’s kind of where, like all these issues, can start coming up.
354 01:20:25.880 ⇒ 01:20:31.969 Demilade Agboola: So, having an Api call for the pharmacies to get a directive from them would be very helpful. So they said, to integrate that.
355 01:20:32.440 ⇒ 01:20:39.109 Robert Tseng: Okay, yeah. I mean, I think it waste them if you tap them a lot of to put this together. I think this that’s important like.
356 01:20:39.270 ⇒ 01:20:59.360 Robert Tseng: I wanna I want this to be like, okay, we’ve given them the roadmap of what we need like dream state. If they don’t end up delivering on it, you know, that’s on them, or whatever. But like we can go and take that. And I think that’s that’s that’s a very important like strategy kind of like piece to what what we’re doing in preparation for the Emr work.
357 01:21:02.370 ⇒ 01:21:04.770 Awaish Kumar: Okay, okay, sure, like, how?
358 01:21:05.120 ⇒ 01:21:14.130 Robert Tseng: Plus. There’s like no code. Right? This is just purely strategy that we’re doing at this point. So I I think we can probably add it to cycle I want. I want us to be on top of this. So.
359 01:21:14.680 ⇒ 01:21:26.060 Awaish Kumar: Yeah, so like, this will be like, but this is not just like an Erd diagram, but it will be more detailed list of tables, along with fees and everything.
360 01:21:26.310 ⇒ 01:21:27.343 Robert Tseng: Correct. Yeah.
361 01:21:28.400 ⇒ 01:21:30.299 Awaish Kumar: I will start working on this.
362 01:21:32.270 ⇒ 01:21:35.710 Robert Tseng: Yeah, I’ll try to add. So I’ll add, so
363 01:21:36.310 ⇒ 01:21:40.960 Robert Tseng: yeah, I’ll I’ll try to break this down to more tickets later. So but anyway, I’ll put that in there.
364 01:21:42.090 ⇒ 01:21:48.179 Robert Tseng: Okay, so that ends up being another project that we have. That’s improv. That’s like kind of live.
365 01:21:48.460 ⇒ 01:22:00.559 Robert Tseng: I’m gonna put it as it’s not really high priorities for medium anything that happens. So there’s a couple of things on your plate. The circle community work is another important thing that we need to start this week, so
366 01:22:01.198 ⇒ 01:22:15.689 Robert Tseng: I’ve already kind of gone in. I don’t know if you’ve taken a look at this yet, but I went in and I broke it out. I wrote out the whole prd, and then I’ve broken it out tickets. So I think I understand everything we need in order to get what they’re asking for done.
367 01:22:16.347 ⇒ 01:22:21.000 Robert Tseng: Whatever etl tool we end up choosing, I think, is like like.
368 01:22:21.650 ⇒ 01:22:26.180 Awaish Kumar: When it’s but what what data we we need, right?
369 01:22:27.700 ⇒ 01:22:45.880 Robert Tseng: So on me. It’s true. Finalize the data fields that we’re required to get right. And then for you. At this point you’re trying to figure out like, what do we need to do to access the Api if we’re gonna use Etl tool? Or if we’re just gonna use segment like, whatever it is like.
370 01:22:45.990 ⇒ 01:22:54.430 Robert Tseng: I think that’s that’s your decision. But as far as like the data that we’re gonna go get first.st I think that’s that’s on me to get by the end of the day. So.
371 01:22:55.480 ⇒ 01:23:01.429 Awaish Kumar: Okay, like, after I have, like what data we need, I need to identify the endpoints. And maybe then we can ask
372 01:23:01.690 ⇒ 01:23:07.119 Awaish Kumar: polyomic if they can help us, or we should build, build our survey.
373 01:23:07.590 ⇒ 01:23:09.210 Robert Tseng: Okay, yeah.
374 01:23:12.090 ⇒ 01:23:20.660 Robert Tseng: great, all right. Anything else that we’re coming up on time. So anything else that was in progress that we didn’t talk to, but otherwise we’ll just kinda carry on
375 01:23:21.419 ⇒ 01:23:27.490 Robert Tseng: Annie and Damelade, if you guys could just make sure that you push out that change to total customers asap like.
376 01:23:27.870 ⇒ 01:23:38.390 Robert Tseng: I already kind of had to deal with a fire drill on that this morning. So I just want us to restore confidence in the product data that is the most urgent. But then there’s other stuff that’s in progress as well.
377 01:23:42.520 ⇒ 01:23:43.670 Demilade Agboola: Okay, will do.
378 01:23:46.470 ⇒ 01:23:47.060 Demilade Agboola: Okay.
379 01:23:47.750 ⇒ 01:23:48.125 Robert Tseng: Yeah.
380 01:23:48.500 ⇒ 01:23:51.120 Demilade Agboola: I mean, can you stay after? Can you stay on after this call?
381 01:23:51.320 ⇒ 01:23:52.459 Annie Yu: Yeah, sure.
382 01:23:54.100 ⇒ 01:24:03.280 Robert Tseng: Okay, cool. Alright, if not, if nothing else. Thank you. Keep keep kind of I’m gonna I’m gonna actually do a proper grooming today. I think I shouldn’t be spending as much time
383 01:24:03.490 ⇒ 01:24:06.070 Robert Tseng: doing all this investigative work. So
384 01:24:06.880 ⇒ 01:24:12.370 Robert Tseng: yeah. And then, Annie, like, I know, there’s like a whole thing outstanding with
385 01:24:12.630 ⇒ 01:24:16.010 Robert Tseng: this like I’ll I’ll handle it. You don’t have to worry about it.
386 01:24:16.910 ⇒ 01:24:17.580 Annie Yu: Okay.
387 01:24:18.810 ⇒ 01:24:20.230 Robert Tseng: Okay. Thanks.
388 01:24:20.520 ⇒ 01:24:22.139 Robert Tseng: Alright. Thank you, miss.