Meeting Title: US | Grooming Date: 2025-10-07 Meeting participants: Awaish Kumar, Amber Lin, Emily Giant, Demilade Agboola
WEBVTT
1 00:00:11.910 ⇒ 00:00:13.260 Amber Lin: Hello!
2 00:00:13.990 ⇒ 00:00:14.640 Awaish Kumar: Hello.
3 00:00:19.000 ⇒ 00:00:20.250 Amber Lin: Alright.
4 00:00:22.780 ⇒ 00:00:26.569 Amber Lin: This is just us two right now. Oh, hi Emily!
5 00:00:26.780 ⇒ 00:00:27.600 Amber Lin: Inc.
6 00:00:28.110 ⇒ 00:00:33.230 Amber Lin: Let’s go through these.
7 00:00:34.790 ⇒ 00:00:45.220 Amber Lin: Anything unclear on this one? Me and Emily’s grooming later, but if you need to start work on this immediately, we can give you some pointers.
8 00:00:46.570 ⇒ 00:01:01.599 Awaish Kumar: I know, like, we have this field in somewhere, and I and Demonade already worked on that… that part, so I can basically, bring that in… in the… maybe in the fact orders or something.
9 00:01:01.880 ⇒ 00:01:08.449 Awaish Kumar: Right? Because we need attribution for individual orders, so if that comes into the perfect orders.
10 00:01:08.450 ⇒ 00:01:22.449 Awaish Kumar: That basically just does what we would need here, but I’m… that was for Shopify. I’m just con… wanted to know, like, do we want to do a similar exercise for OMS as well? Because…
11 00:01:22.570 ⇒ 00:01:27.449 Awaish Kumar: I understand that some orders are also coming from OMS.
12 00:01:29.860 ⇒ 00:01:38.250 Amber Lin: Maybe, Emily, do you know about what we should do about the OMS data?
13 00:01:41.280 ⇒ 00:01:42.839 Amber Lin: Oh, you’re muted.
14 00:01:44.080 ⇒ 00:01:49.310 Emily Giant: I’m not totally sure I understand, so you’re saying there’s stuff in OMS that you need?
15 00:01:50.130 ⇒ 00:02:08.089 Awaish Kumar: So, like, we actually discussed this, like, a few days back. Like, we were getting a field called UTM Parameter Source, which basically gives us the referral link, right, where the order is coming from.
16 00:02:08.479 ⇒ 00:02:14.150 Awaish Kumar: In the Shopify, you could see if it is coming from Google Ads, Instagram.
17 00:02:14.330 ⇒ 00:02:24.039 Awaish Kumar: or Meta, or, like, or any other source, right? But, like, that was for Shopify, right?
18 00:02:26.350 ⇒ 00:02:28.450 Emily Giant: Yeah.
19 00:02:28.450 ⇒ 00:02:30.580 Demilade Agboola: There is tools from Shopify.
20 00:02:31.730 ⇒ 00:02:37.450 Awaish Kumar: Yeah, so I’m just… I just, like, had a conversation with you, Damilade, as well.
21 00:02:37.500 ⇒ 00:02:56.910 Awaish Kumar: That you also mentioned that OMS is a platform which is also running parallelly, right? So, we might be getting some orders on order management system, right? So, what… like, how to identify the referral site for OMS orders?
22 00:02:57.340 ⇒ 00:03:01.859 Emily Giant: There’s not such a thing as OMS orders, those are historical orders.
23 00:03:01.860 ⇒ 00:03:02.250 Awaish Kumar: Oh.
24 00:03:02.250 ⇒ 00:03:04.240 Emily Giant: So you don’t need to worry about that.
25 00:03:04.800 ⇒ 00:03:08.479 Awaish Kumar: Okay. So, is… Omos…
26 00:03:08.740 ⇒ 00:03:14.199 Demilade Agboola: it’s sort of, like, downstream of Shopify, so all others pass through Shopify.
27 00:03:14.440 ⇒ 00:03:22.809 Demilade Agboola: But they go through OMS as well, where sometimes the care team and other teams can add all that information to the orders.
28 00:03:23.790 ⇒ 00:03:24.610 Awaish Kumar: Okay.
29 00:03:25.210 ⇒ 00:03:26.569 Demilade Agboola: It’s all the same orders.
30 00:03:26.740 ⇒ 00:03:29.430 Awaish Kumar: So that means the…
31 00:03:29.710 ⇒ 00:03:38.960 Awaish Kumar: Shopify is the only platform from where customers place order. After that, it might pass through order management system, right?
32 00:03:39.510 ⇒ 00:03:47.879 Emily Giant: It will pass through. So, one is the… one’s the website that’s customer-facing. OMS is for our fulfillment teams.
33 00:03:49.350 ⇒ 00:03:53.970 Emily Giant: So that’s how they know to, like, what to put in the box when they pack it.
34 00:03:55.560 ⇒ 00:04:14.189 Awaish Kumar: Okay, from Shopify, everything goes to Amazon. I understood. So everything is going to basically come from Shopify. So I now just have one question, like, we, investigated Shopify data, and there is a lot of different orders where we don’t have, we don’t know the source, like, it’s null.
35 00:04:14.370 ⇒ 00:04:17.120 Awaish Kumar: It’s, like, it’s unknown, basically.
36 00:04:17.290 ⇒ 00:04:20.169 Awaish Kumar: So, for those orders, what do you wanna do?
37 00:04:21.980 ⇒ 00:04:29.709 Emily Giant: If it’s not known, it’s not known. They might have, like, a private browser or something like that, so it’s not totally surprising. Demolati, what were you thinking?
38 00:04:30.490 ⇒ 00:04:49.440 Demilade Agboola: I was gonna say, I think we could look into the Shopify configuration, if there’s anything we can tweak to maybe reduce the number of nulls. If there isn’t, that’s just all we have, or that’s what we have. But if there’s something else we can do in Shopify configuration to allow us to be able to get, you know, more
39 00:04:49.500 ⇒ 00:04:51.750 Demilade Agboola: QTM sources, that would be helpful.
40 00:04:53.170 ⇒ 00:04:57.410 Awaish Kumar: So… Yeah, like, I have one…
41 00:04:57.870 ⇒ 00:05:09.449 Awaish Kumar: One thing to say here is that I also, like, while during that spike, I looked into the North Beam, and there are some orders, basically, which are…
42 00:05:09.560 ⇒ 00:05:18.429 Awaish Kumar: In North Beam, they, like, UTM source says, for example, Facebook, and…
43 00:05:18.840 ⇒ 00:05:26.470 Awaish Kumar: And basically, that’s not available in… in the Shopify UTMs data, So…
44 00:05:26.610 ⇒ 00:05:42.640 Awaish Kumar: For this ticket, I think I will just work with Shopify UTMs and see if we can… what… whatever we can bring in into the fact orders. But then, yeah, if we wanna… and as a step two, could be that we want to get export from North Beam.
45 00:05:42.640 ⇒ 00:05:52.609 Awaish Kumar: And, like, take a union from both to match, like, to get the attribution for as much as…
46 00:05:53.030 ⇒ 00:05:55.089 Awaish Kumar: Like, odd as possible.
47 00:05:58.800 ⇒ 00:06:03.039 Demilade Agboola: Yeah, I also think… yeah, I also wonder if, like, if…
48 00:06:03.800 ⇒ 00:06:21.130 Demilade Agboola: Because I know the nulls have reduced over time. I’m wondering if it’s a configuration that was done in Shopify, if there’s something that we can do to ensure, because if we don’t have any, you know, Facebook or Meta, I don’t think that’s really… I don’t think that’s realistic. I think there are definitely going to be some Facebook.
49 00:06:21.890 ⇒ 00:06:27.039 Awaish Kumar: I can explore that, if in shop, like, if we can have, also have a ticket for that.
50 00:06:27.310 ⇒ 00:06:32.879 Awaish Kumar: Explore Routium configuration in Shopify.
51 00:06:35.610 ⇒ 00:06:45.819 Amber Lin: Yeah, I currently put the export from Northbeam in next week. I can put the UTM Explore UTM config… this one in this week.
52 00:06:46.180 ⇒ 00:06:47.970 Amber Lin: Okay. What do you think? Okay.
53 00:06:49.200 ⇒ 00:06:51.259 Amber Lin: I’ll say 1 point.
54 00:06:56.900 ⇒ 00:06:57.840 Amber Lin: All right.
55 00:07:00.440 ⇒ 00:07:10.039 Amber Lin: Great, makes sense. And then for these… What are the status of…
56 00:07:11.390 ⇒ 00:07:14.759 Amber Lin: These tickets… did we push the PR for the test?
57 00:07:16.510 ⇒ 00:07:23.270 Demilade Agboola: No, so for the test, for the event, a fact of orders model itself.
58 00:07:23.700 ⇒ 00:07:30.460 Demilade Agboola: We’ll build the facto borders model fully, and then add the test on top of that.
59 00:07:30.670 ⇒ 00:07:33.099 Demilade Agboola: But it’s not high priority based off…
60 00:07:33.100 ⇒ 00:07:33.710 Amber Lin: Oh.
61 00:07:33.710 ⇒ 00:07:35.940 Demilade Agboola: 376 and 282.
62 00:07:36.180 ⇒ 00:07:46.669 Amber Lin: I see, I see. I just thought we had the model, and I thought, I remember you said, oh, we’re just gonna push the PI, but if we have a lot of time left, in that, I’ll push it to next week.
63 00:07:47.650 ⇒ 00:07:49.220 Demilade Agboola: Okay, sure, sounds good.
64 00:07:49.580 ⇒ 00:07:57.640 Demilade Agboola: So right now, my focus is 282, because what that helps us do
65 00:07:57.760 ⇒ 00:08:07.310 Demilade Agboola: is provide a bit more information that we can use for 376 with some of the test scenarios for, like, bundles and kits and strikethrough.
66 00:08:08.370 ⇒ 00:08:12.570 Demilade Agboola: And that would help with being able to validate 376.
67 00:08:13.070 ⇒ 00:08:27.370 Amber Lin: Okay, when do you think we should book the meeting with Perry? Is it okay if we book, say, this Thursday or this Friday? Does that work? Because we only have 2 weeks left with Perry.
68 00:08:28.260 ⇒ 00:08:30.689 Demilade Agboola: I got you. Can we do Friday?
69 00:08:30.910 ⇒ 00:08:33.379 Amber Lin: Yeah, I’ll see. Okay.
70 00:08:33.539 ⇒ 00:08:42.059 Amber Lin: Emily, let’s find a time on Perry’s calendar after we go through stand-up.
71 00:08:43.419 ⇒ 00:08:46.459 Amber Lin: And then I’ll save the stuff for PK Weekend.
72 00:08:47.020 ⇒ 00:08:50.500 Amber Lin: Hold off a little bit and focus on these two first.
73 00:08:50.760 ⇒ 00:08:53.980 Amber Lin: Any updates here?
74 00:08:54.970 ⇒ 00:09:05.499 Emily Giant: I think I updated all of them. I marked the ad hoc one as done. The subscriptions, I, reviewed UTAM’s
75 00:09:05.600 ⇒ 00:09:09.350 Emily Giant: Models, and made changes, and…
76 00:09:09.490 ⇒ 00:09:16.609 Emily Giant: pushed, requested a PR review, so now I’m just working on, historical subscriptions.
77 00:09:16.880 ⇒ 00:09:20.850 Emily Giant: And then Update Fact Subscriptions is added to… that’s done.
78 00:09:21.130 ⇒ 00:09:25.630 Emily Giant: But he can’t use it till… The bottom one, 299.
79 00:09:27.650 ⇒ 00:09:35.410 Emily Giant: it’s done, but it’s not gonna be usable to him until he deploys, the changes I made to his models in dbt.
80 00:09:35.410 ⇒ 00:09:44.299 Amber Lin: Gotcha. Okay, so I’ll just leave it at that status. Did we find the scenarios for the subscriptions QA?
81 00:09:48.340 ⇒ 00:09:52.040 Emily Giant: I’m not sure…
82 00:09:52.170 ⇒ 00:09:57.509 Emily Giant: like, is that for Utam, or… like, I know it’s my ticket, but, like, does he want the…
83 00:09:57.720 ⇒ 00:10:01.500 Emily Giant: the scenarios? Like, I don’t totally know what that means.
84 00:10:01.700 ⇒ 00:10:02.540 Amber Lin: Just, like…
85 00:10:02.540 ⇒ 00:10:03.250 Emily Giant: What to test?
86 00:10:03.250 ⇒ 00:10:06.150 Amber Lin: going to QA the subscriptions?
87 00:10:07.450 ⇒ 00:10:08.950 Demilade Agboola: Yeah, I think…
88 00:10:09.120 ⇒ 00:10:16.020 Demilade Agboola: with the QL subscriptions, the idea is the same way we have, like, for revenue QA, where there’s scenarios where
89 00:10:16.230 ⇒ 00:10:23.020 Demilade Agboola: They’re troublesome, and if we can assure that the revenue is aligned in those scenarios.
90 00:10:23.670 ⇒ 00:10:36.890 Demilade Agboola: we’re fairly certain about the revenue calculation. I think the idea is the same thing with subscriptions, and how we’re going to calculate the revenue based off subscriptions. If there are any scenarios in which things happen, things get paused, things…
91 00:10:36.890 ⇒ 00:10:44.209 Demilade Agboola: you know, happen within the subscriptions that can affect how revenue is derived from that. It would be very helpful to those scenarios listed.
92 00:10:44.390 ⇒ 00:10:50.569 Demilade Agboola: And so we can go through what we have as subscriptions and use that in our revenue forecast, the new
93 00:10:51.400 ⇒ 00:10:51.880 Demilade Agboola: model.
94 00:10:51.880 ⇒ 00:10:55.659 Emily Giant: Okay, no, that’s not done yet.
95 00:10:55.910 ⇒ 00:11:04.879 Emily Giant: I’ve been working on the other tickets that I mentioned, but everything is updated. So, those are… those are urgent.
96 00:11:06.240 ⇒ 00:11:12.180 Amber Lin: My ques… I put them as urgent because I thought we need Perry to review them, but if not.
97 00:11:12.280 ⇒ 00:11:14.640 Amber Lin: Then they don’t have to be urgent.
98 00:11:15.810 ⇒ 00:11:18.599 Emily Giant: Well, there’s nothing for her to review right now, is there?
99 00:11:18.600 ⇒ 00:11:19.170 Amber Lin: Okay.
100 00:11:19.170 ⇒ 00:11:27.130 Emily Giant: problem. So it’s like… I wouldn’t even call them blocked, it’s just not time yet. Utam hasn’t been able to test
101 00:11:27.740 ⇒ 00:11:35.810 Emily Giant: his subscriptions in Looker, so I would think that, like, there are several, like,
102 00:11:36.100 ⇒ 00:11:39.190 Emily Giant: fields that haven’t even been created yet, so…
103 00:11:39.190 ⇒ 00:11:39.790 Amber Lin: Okay.
104 00:11:39.790 ⇒ 00:11:40.309 Emily Giant: She wouldn’t be…
105 00:11:40.310 ⇒ 00:11:40.900 Amber Lin: Yup.
106 00:11:40.900 ⇒ 00:11:41.950 Emily Giant: the Tesla scenarios.
107 00:11:41.950 ⇒ 00:11:54.519 Amber Lin: So these will be next week. I think we can focus on getting the subscription stuff done, and then having the scenarios of what we need, and we can do the actual QA next week.
108 00:11:54.640 ⇒ 00:12:00.830 Amber Lin: And then we’ll book another session with Perry next week, before she heads out. What date?
109 00:12:01.520 ⇒ 00:12:03.770 Amber Lin: Is her last day, what date is that?
110 00:12:03.770 ⇒ 00:12:05.780 Emily Giant: 22nd is her last day.
111 00:12:05.780 ⇒ 00:12:07.370 Amber Lin: Second. Okay.
112 00:12:08.080 ⇒ 00:12:08.680 Amber Lin: Mmm…
113 00:12:09.280 ⇒ 00:12:14.049 Emily Giant: And a lot of subscriptions QA will be part of revenue, because,
114 00:12:14.800 ⇒ 00:12:22.289 Emily Giant: Essentially, like, the subscriptions have a set pricing when it comes to, like, top-line revenue, and…
115 00:12:22.680 ⇒ 00:12:29.909 Emily Giant: Those need to be incorporated into the revenue… er, yeah, into the revenue models in order for QA to happen.
116 00:12:31.390 ⇒ 00:12:41.280 Emily Giant: So, it’s kind of like… A balance of Demolade’s ticket that’s due on Friday, Utam adding those,
117 00:12:41.760 ⇒ 00:12:46.949 Emily Giant: fields that are still missing, and, like, at that point, we can QA, but…
118 00:12:47.710 ⇒ 00:12:53.180 Emily Giant: That can be the same time, or should be the same time as…
119 00:12:53.280 ⇒ 00:12:56.359 Emily Giant: the revenue QA, the portions that Perry would help with.
120 00:12:58.440 ⇒ 00:13:00.159 Amber Lin: Oh,
121 00:13:00.270 ⇒ 00:13:05.540 Amber Lin: What does it take for UTM to add the fields that’s missing? Is it just a PR review?
122 00:13:06.400 ⇒ 00:13:12.280 Emily Giant: No, there are fields called, like…
123 00:13:12.970 ⇒ 00:13:20.009 Emily Giant: next subscription send… subscriptions remain… or, these aren’t going to be exact. Hold on, let me look.
124 00:13:21.250 ⇒ 00:13:23.479 Amber Lin: So I don’t think that’s a ticket for him yet.
125 00:13:24.230 ⇒ 00:13:37.000 Emily Giant: Okay, I added them all as notes to the PR he’s reviewing. It was basically, like, they’re in there, they just don’t do anything, and I added comments in the PR for him, so…
126 00:13:37.510 ⇒ 00:13:42.719 Emily Giant: I don’t know if he’s planning to, like, create that ticket once he reviews those, but,
127 00:13:44.240 ⇒ 00:13:46.609 Emily Giant: Let me see what those are called.
128 00:13:59.080 ⇒ 00:14:04.250 Emily Giant: Okay, they’re called… Subscription SKU.
129 00:14:08.120 ⇒ 00:14:12.230 Emily Giant: Total deliveries.
130 00:14:13.890 ⇒ 00:14:18.750 Emily Giant: Prepaid sentence remaining.
131 00:14:22.310 ⇒ 00:14:25.039 Emily Giant: And prepaid cycles.
132 00:14:26.640 ⇒ 00:14:30.790 Emily Giant: I believe those are all the ones that are not currently… working.
133 00:14:35.220 ⇒ 00:14:37.009 Emily Giant: And then, oh, sorry, next.
134 00:14:41.760 ⇒ 00:14:46.980 Emily Giant: There’s one that’s, like, next subscription date, but I can’t remember what it’s called. It’s called… next billing date.
135 00:14:51.930 ⇒ 00:14:54.030 Amber Lin: Okay. Oh, date.
136 00:14:54.910 ⇒ 00:14:59.610 Amber Lin: So, I’ll… we can ask him in a bit.
137 00:14:59.760 ⇒ 00:15:06.740 Amber Lin: And so, should we book the review this week?
138 00:15:07.740 ⇒ 00:15:10.260 Amber Lin: If we’re not gonna get these done.
139 00:15:10.950 ⇒ 00:15:16.389 Amber Lin: It’s gonna take a while to actually complete the subscriptions.
140 00:15:16.540 ⇒ 00:15:21.269 Amber Lin: QA and stuff, right? Before we can ask Perry to review.
141 00:15:22.840 ⇒ 00:15:34.980 Emily Giant: I think it would be better to book one session where we review the line item and bundle scenario and subscriptions, since they’re, like, currently, they’re in the same model.
142 00:15:35.180 ⇒ 00:15:36.409 Emily Giant: In, like, our…
143 00:15:36.410 ⇒ 00:15:36.760 Amber Lin: Thank you.
144 00:15:36.760 ⇒ 00:15:40.679 Emily Giant: what’s going to be archived? Because it all…
145 00:15:41.280 ⇒ 00:15:44.989 Emily Giant: comes together to create correct revenue, so…
146 00:15:45.900 ⇒ 00:15:52.640 Emily Giant: I would think one one-hour session would… Probably be better than…
147 00:15:54.990 ⇒ 00:15:57.530 Emily Giant: A complete one, and then a more complete one.
148 00:15:57.530 ⇒ 00:16:12.040 Amber Lin: Yeah, I would like to do that, it’s just I want us to be unblocked next week to do more modeling work, because we’re blocked on modeling before… until we review that. Do you still think Friday’s a possible date?
149 00:16:12.400 ⇒ 00:16:14.480 Emily Giant: How are… how are we blocked?
150 00:16:15.070 ⇒ 00:16:25.209 Amber Lin: So we have these… revenue summary tables, we have the subscriptions revenue summary table. So these…
151 00:16:25.510 ⇒ 00:16:27.600 Amber Lin: All these tables are blocked.
152 00:16:28.500 ⇒ 00:16:29.520 Emily Giant: Bye.
153 00:16:30.520 ⇒ 00:16:32.360 Amber Lin: Demlade.
154 00:16:33.040 ⇒ 00:16:37.339 Demilade Agboola: And so, it’s, like, for us to be able to calculate the revenue.
155 00:16:37.600 ⇒ 00:16:45.600 Demilade Agboola: We want to be sure that the models that we have as base tables are, like, our fact orders, fact subscriptions, all of those models.
156 00:16:46.040 ⇒ 00:16:47.909 Demilade Agboola: handling the…
157 00:16:48.480 ⇒ 00:16:55.229 Demilade Agboola: Use cases properly, so that when we sum them, and we say, hey, the revenue on this day is this amount.
158 00:16:55.550 ⇒ 00:17:02.959 Demilade Agboola: we’ve handled those use cases well. Basically, we just want to be sure that the summary tables are
159 00:17:04.760 ⇒ 00:17:07.300 Demilade Agboola: Accounting for every single scenario.
160 00:17:08.329 ⇒ 00:17:11.949 Emily Giant: But I… so, what’s blocking them, though?
161 00:17:12.950 ⇒ 00:17:15.939 Demilade Agboola: Of the QAs, basically. The African QA…
162 00:17:16.170 ⇒ 00:17:26.479 Demilade Agboola: the revenue, and be sure that, hey, we’re actually handling those use cases properly. Same thing with subscriptions, and we’re handling the use cases… the different use cases and edge cases properly.
163 00:17:26.599 ⇒ 00:17:32.989 Demilade Agboola: Then, we can… Build out these summary tables where we put everything together.
164 00:17:34.600 ⇒ 00:17:40.859 Emily Giant: Okay. I’m sure if those are ready for her to QA, then definitely go for it.
165 00:17:40.990 ⇒ 00:17:42.250 Emily Giant: On Friday.
166 00:17:45.200 ⇒ 00:17:49.669 Amber Lin: Sounds good. So, are we splitting it up? So, we’re doing the…
167 00:17:50.660 ⇒ 00:18:00.470 Amber Lin: whatever’s blocking these models, we’ll do that on Friday, and then another 30-minute session next week, and what will we be reviewing in that?
168 00:18:02.440 ⇒ 00:18:03.360 Demilade Agboola: Understood.
169 00:18:03.360 ⇒ 00:18:04.240 Amber Lin: Items?
170 00:18:05.350 ⇒ 00:18:09.139 Demilade Agboola: Yeah, so I think for Friday, I think just us being…
171 00:18:09.570 ⇒ 00:18:16.590 Demilade Agboola: On the same page where we were able to go through the models, and we’re able to see that the numbers that we’re getting match the numbers that
172 00:18:17.050 ⇒ 00:18:24.629 Demilade Agboola: Every, you know, expects, and how things also… how we handle different edge cases and use cases match the same way.
173 00:18:25.060 ⇒ 00:18:29.709 Demilade Agboola: It would be ideal to do it for both revenue and subscriptions, but even if
174 00:18:29.830 ⇒ 00:18:32.250 Demilade Agboola: We can handle it for revenue, mostly.
175 00:18:32.610 ⇒ 00:18:46.010 Demilade Agboola: Next week, it will just mean that we can just go over subscriptions and then put everything together to be able to have, like, a good summary table of, hey, this is revenue this month, last month, over this week, and then we can build out those models.
176 00:18:46.440 ⇒ 00:18:49.049 Demilade Agboola: We can start feeding into Looker.
177 00:18:51.900 ⇒ 00:18:58.540 Amber Lin: Okay, so I’ll ask her for the time. Any updates on Pico’s tickets? Has he started yet?
178 00:19:02.820 ⇒ 00:19:07.359 Emily Giant: No updates on my end. I’ll connect with him and see if…
179 00:19:07.820 ⇒ 00:19:10.040 Emily Giant: Let’s see if he’s made any progress.
180 00:19:10.680 ⇒ 00:19:15.190 Amber Lin: Are you guys still having daily working sessions with him, or what’s the cadence?
181 00:19:15.420 ⇒ 00:19:18.840 Emily Giant: We just didn’t today, because we needed time, but usually we do every day.
182 00:19:18.840 ⇒ 00:19:24.249 Amber Lin: Okay, okay, gotcha. Let me know what, what he says, and Emily, I’ll see you later.
183 00:19:24.630 ⇒ 00:19:25.680 Amber Lin: Alrighty.
184 00:19:25.800 ⇒ 00:19:27.000 Amber Lin: Thanks, all!
185 00:19:27.240 ⇒ 00:19:28.050 Emily Giant: Bye!
186 00:19:28.050 ⇒ 00:19:28.960 Amber Lin: Bye!
187 00:19:29.200 ⇒ 00:19:29.800 Awaish Kumar: Right.