Meeting Title: US x BF | Standup Date: 2025-07-28 Meeting participants: Caio Velasco, Amber Lin, Emily Giant
WEBVTT
1 00:00:23.590 ⇒ 00:00:24.650 Amber Lin: Hi.
2 00:00:25.200 ⇒ 00:00:26.080 Caio Velasco: Hello!
3 00:00:27.280 ⇒ 00:00:28.180 Caio Velasco: Morning.
4 00:00:28.400 ⇒ 00:00:30.330 Emily Giant: Hi, how’s everyone doing?
5 00:00:32.350 ⇒ 00:00:33.869 Amber Lin: Good! How are you?
6 00:00:33.870 ⇒ 00:00:35.580 Amber Lin: They began.
7 00:00:39.850 ⇒ 00:00:46.380 Emily Giant: I I’m good. I’m back home. I was in South Carolina all last week, and it was pretty.
8 00:00:47.080 ⇒ 00:00:58.319 Emily Giant: Sometimes. You just need to be back on your routine like I wasn’t even that far from my routine. And just that little bit made me like lose brain cells. So I’m glad
9 00:01:03.340 ⇒ 00:01:05.820 Emily Giant: the Demo lot is out the whole week right.
10 00:01:06.835 ⇒ 00:01:12.940 Amber Lin: He should be out until the first, st which is, let’s see.
11 00:01:13.880 ⇒ 00:01:19.240 Amber Lin: Yeah, I think he’s out and like, I guess he’s back on Friday.
12 00:01:19.550 ⇒ 00:01:19.920 Emily Giant: Okay.
13 00:01:19.920 ⇒ 00:01:21.870 Amber Lin: But he will be away.
14 00:01:22.768 ⇒ 00:01:31.940 Amber Lin: Yeah, let’s go through what we have here. And then, Emily, I wanted to see if we can book, the meeting with the
15 00:01:32.360 ⇒ 00:01:36.790 Amber Lin: with a few people that Zach and Alex brought up.
16 00:01:37.330 ⇒ 00:01:48.821 Emily Giant: Yeah, that that’d be good. I their calendars are such dumpster fires that we might as well just split them into groups and do it, because I don’t know how we will. Otherwise
17 00:01:50.350 ⇒ 00:01:51.360 Amber Lin: Okay.
18 00:01:53.899 ⇒ 00:01:55.219 Amber Lin: Let’s see.
19 00:02:00.310 ⇒ 00:02:01.020 Amber Lin: Okay.
20 00:02:06.040 ⇒ 00:02:08.780 Amber Lin: is there anything I can close here.
21 00:02:13.400 ⇒ 00:02:26.563 Emily Giant: So the 2 26. I didn’t write an email for meeting with all of them. I thought we would just like talk to them about. We weren’t initially gonna meet with Kristen. But now that we are
22 00:02:27.430 ⇒ 00:02:38.049 Emily Giant: I think it be better to hash it out during the meeting, unless you feel otherwise. I’m fine either way, but I wouldn’t close out any of these otherwise.
23 00:02:39.230 ⇒ 00:02:52.239 Amber Lin: Because I think in the meeting we wanted to get what type of analysis they need, and I don’t know if we can get it during that time, especially.
24 00:02:52.240 ⇒ 00:02:52.650 Emily Giant: Okay.
25 00:02:52.670 ⇒ 00:02:54.530 Amber Lin: It’s gonna be 30 min.
26 00:02:54.750 ⇒ 00:02:57.339 Emily Giant: Yeah, that’s fine. I’ll I’ll reach out then.
27 00:02:57.845 ⇒ 00:03:01.204 Emily Giant: But none none of those can be closed just yet. Unfortunately.
28 00:03:02.140 ⇒ 00:03:03.320 Amber Lin: Sounds good.
29 00:03:04.056 ⇒ 00:03:06.560 Amber Lin: Kyle, what about these?
30 00:03:07.520 ⇒ 00:03:13.880 Amber Lin: I know we’re still, are we still waiting on the technical design document to be reviewed.
31 00:03:15.320 ⇒ 00:03:17.875 Caio Velasco: I think so. I watched the meeting you mentioned.
32 00:03:18.580 ⇒ 00:03:29.259 Caio Velasco: It was a good meeting. I think from that meeting it was clear that a lot of things have to be, let’s say predefined before. We can move forward like to the modeling part of revenue.
33 00:03:29.761 ⇒ 00:03:33.389 Caio Velasco: So I I schedule a meeting with with them, but I think it was busy.
34 00:03:33.590 ⇒ 00:03:39.099 Caio Velasco: so I’ll try again. Maybe I’ll be able to talk to him tomorrow morning
35 00:03:39.580 ⇒ 00:03:56.739 Caio Velasco: and see how can I already start helping with with the modeling part? As I mentioned, I already I did like a dim customers. I have like them products, or even like affect orders, but still very, very simple ones from my discovery.
36 00:03:57.188 ⇒ 00:04:02.561 Caio Velasco: So then, I think, after I talk to him, I’ll have like a better idea of how to move forward.
37 00:04:03.340 ⇒ 00:04:08.589 Caio Velasco: But yeah, I think on my end, for now it’s a bit chill. Let’s say.
38 00:04:09.320 ⇒ 00:04:29.299 Amber Lin: Okay, I see. I know he would take over the rest of parts. So I think we’ll. What we need to do is we need to make sure that this meeting is ready, and then I’ll ask zack and Alex when we can do the review. I think
39 00:04:29.490 ⇒ 00:04:39.419 Amber Lin: so hopefully. We can grab meeting time before Thursday. Let me see who the people were.
40 00:04:40.650 ⇒ 00:04:42.640 Amber Lin: So we have.
41 00:04:44.090 ⇒ 00:04:50.070 Amber Lin: Let’s see, I think it would be
42 00:04:50.970 ⇒ 00:04:53.920 Amber Lin: these people also I did not see
43 00:04:56.930 ⇒ 00:05:04.970 Amber Lin: So Tuesday and Friday 12 to 1230 Pm.
44 00:05:07.550 ⇒ 00:05:10.525 Amber Lin: Es es t you mean
45 00:05:17.350 ⇒ 00:05:18.689 Amber Lin: Hi, Emily.
46 00:05:20.100 ⇒ 00:05:27.050 Emily Giant: Hi, Hi! Sorry! Say it again. So I was writing the email, and totally like blanked out.
47 00:05:27.800 ⇒ 00:05:31.779 Amber Lin: No worries sorry here. It’s
48 00:05:32.830 ⇒ 00:05:35.650 Amber Lin: these 4 people, Christine Sashi, salmon.
49 00:05:35.650 ⇒ 00:05:36.020 Emily Giant: Only.
50 00:05:36.020 ⇒ 00:05:36.530 Amber Lin: Okay.
51 00:05:36.880 ⇒ 00:05:41.479 Amber Lin: Tuesday. Do you mean 12 to 1230 Pm. Est.
52 00:05:41.770 ⇒ 00:05:42.680 Emily Giant: Yes.
53 00:05:43.010 ⇒ 00:05:45.510 Amber Lin: 12. That would be
54 00:05:47.580 ⇒ 00:05:52.500 Amber Lin: 1230 is, gonna be this one, right? 12.
55 00:05:52.730 ⇒ 00:05:53.590 Amber Lin: Okay?
56 00:05:54.260 ⇒ 00:05:56.859 Emily Giant: 12 to 1230. Okay, that works.
57 00:05:57.120 ⇒ 00:06:00.180 Amber Lin: Okay, I will go. Grab.
58 00:06:02.020 ⇒ 00:06:19.819 Emily Giant: And then Sashi may or may not be able to come. But her calendar is like booked out until Friday, so I’ll just touch base with her. On slack, and say, like, I don’t, your calendar is really blocked. If it’s possible for you to attend, please do
59 00:06:20.698 ⇒ 00:06:31.529 Emily Giant: looks like some of it’s like focus time that she had written into her schedule, and maybe an actual meeting. But she doesn’t like give that visibility. But the other 3 are are available.
60 00:06:31.530 ⇒ 00:06:35.109 Amber Lin: I see awesome. Can you send me their emails?
61 00:06:35.110 ⇒ 00:06:35.630 Emily Giant: Yes.
62 00:06:43.460 ⇒ 00:06:45.560 Amber Lin: Yeah, I think that would be off
63 00:06:46.970 ⇒ 00:06:58.490 Amber Lin: cause I know we’re we’re a little bit stalled until we do the revenue part. I’m gonna go ask Bhutan if he’s okay with our progress being stuck.
64 00:07:06.820 ⇒ 00:07:12.509 Amber Lin: Okay? Sounds good. I think once you send me the email, I’ll go book that meeting.
65 00:07:13.048 ⇒ 00:07:15.629 Amber Lin: And I know there was a few
66 00:07:15.840 ⇒ 00:07:23.100 Amber Lin: tickets that you were doing. So. Let us know if you need any help, and I can ask you, Tom, to help you, because definitely is away.
67 00:07:23.450 ⇒ 00:07:30.545 Emily Giant: Okay, I do have one kaya that we can go over tomorrow. It’s just with products. Xf,
68 00:07:31.170 ⇒ 00:07:47.839 Emily Giant: essentially like integrating some of the improvements that Demo a and the team made and pushing it downstream through some deprecated models that were becoming a problem last week. So I’ll tag you in that Pr today and
69 00:07:48.550 ⇒ 00:07:56.060 Emily Giant: gonna be a bunch of models that you won’t have looked at since. It’s all like product related. And I do a lot of the managing of that. But
70 00:07:56.400 ⇒ 00:08:00.059 Emily Giant: it it’s not those they’re not like terribly complicated models.
71 00:08:00.290 ⇒ 00:08:15.809 Caio Velasco: No problem, no problem. Yeah. Anything that you see that it’s related to potential them customers or them products, or I don’t know them whatever in terms of revenue are you contact me? And I can take a look and continue building the those more simple models.
72 00:08:16.290 ⇒ 00:08:25.835 Emily Giant: Okay. And if it’s like too unfamiliar, I can ask Alex, too. I don’t want to waste your time trying to like figure out a model you haven’t looked at, but it’s like the logic’s pretty straightforward. It’s just
73 00:08:27.070 ⇒ 00:08:33.729 Emily Giant: some product category stuff that we fixed in the inventory tables. But you’ll see. I can always talk you through it tomorrow, too, if it’s.
74 00:08:33.730 ⇒ 00:08:43.720 Caio Velasco: Okay? And a quick question, although I know that there has been migration and other things in the past. From, for example, for that question that I sent you for products.
75 00:08:43.720 ⇒ 00:08:44.100 Emily Giant: Team.
76 00:08:44.100 ⇒ 00:08:53.759 Caio Velasco: I know that we have a hevo table, and we have also the the shopify table. And but I also saw some postgres things in there.
77 00:08:53.760 ⇒ 00:08:54.100 Caio Velasco: Yeah.
78 00:08:54.100 ⇒ 00:08:55.979 Caio Velasco: Had some difference of sources.
79 00:08:56.370 ⇒ 00:08:59.619 Emily Giant: It is so, postgres. We have 3 major, like
80 00:09:00.110 ⇒ 00:09:16.412 Emily Giant: time defined migrations and postgres is our legacy table, but every now and then customers in that Postgres table will still update. It’s infrequent, but we don’t want to lose that visibility. So it really is like all 3 tables that
81 00:09:17.280 ⇒ 00:09:19.944 Emily Giant: should be time bound.
82 00:09:21.810 ⇒ 00:09:36.720 Emily Giant: and certain customers like legitimately don’t exist in the shopify table yet. It’s it’s so. Yeah, it’s postgres. I know. Postgres hevo and shopify shopify is the current one for customers that started
83 00:09:37.600 ⇒ 00:09:41.050 Emily Giant: post November 7, th 2024.
84 00:09:41.730 ⇒ 00:09:49.220 Caio Velasco: Okay, okay, no, no problem. But I can use all of them. And then, as I did, for for those 2 build like, mapping table, also.
85 00:09:49.220 ⇒ 00:09:49.630 Emily Giant: -
86 00:09:49.840 ⇒ 00:09:56.080 Caio Velasco: Maybe based on name and and something else. But okay, that’s good to know. I’ll try to bring everything, and then we see.
87 00:09:56.700 ⇒ 00:10:04.580 Emily Giant: Okay, yeah, that’s perfect. And everything is kind of like that where there’s like a Postgres table, then a hevo table, then a shopify table.
88 00:10:04.840 ⇒ 00:10:11.380 Emily Giant: But if you do the 1st 2 you’ll be like I get this. I know, like kind of the general times that these were relevant.
89 00:10:12.140 ⇒ 00:10:13.603 Emily Giant: It took me forever.
90 00:10:13.970 ⇒ 00:10:15.959 Caio Velasco: No problem, no problem. Thank you. Thank you.
91 00:10:18.860 ⇒ 00:10:19.600 Emily Giant: Alright
92 00:10:20.510 ⇒ 00:10:26.640 Emily Giant: Amber. I sent you the emails, I think. Oh, Sam Shield, I still have to send Sam Shield, but that’s the last one.
93 00:10:27.470 ⇒ 00:10:29.920 Emily Giant: because I didn’t know if she used Sam or Samantha.
94 00:10:32.290 ⇒ 00:10:35.150 Emily Giant: Yep, Samantha, okay, I’ll send it to you right now
95 00:10:35.370 ⇒ 00:10:39.360 Emily Giant: and then. I’ll CC. You on the revenue definitions, email, both of you.
96 00:10:39.360 ⇒ 00:10:41.420 Amber Lin: Hmm, okay, that would be great.
97 00:10:41.420 ⇒ 00:10:44.820 Emily Giant: Alright. Cool. Okay. Thank you.
98 00:10:44.820 ⇒ 00:10:45.979 Amber Lin: Alright. Thank you both.
99 00:10:45.980 ⇒ 00:10:46.829 Caio Velasco: Thank you.
100 00:10:48.440 ⇒ 00:10:50.310 Amber Lin: Alrighty bye.