Meeting Title: US x BF | Standup Date: 2025-10-29 Meeting participants: Awaish Kumar, Emily Giant, Amber Lin, Demilade Agboola


WEBVTT

1 00:01:50.070 00:01:50.830 Awaish Kumar: Hello.

2 00:01:51.210 00:01:52.620 Emily Giant: Hi, how are you?

3 00:01:53.890 00:01:55.130 Awaish Kumar: I’m good, how about you?

4 00:01:56.450 00:01:57.110 Emily Giant: Good.

5 00:02:07.830 00:02:11.140 Emily Giant: It’s chilly. What’s the temperature where you are?

6 00:02:12.430 00:02:15.390 Awaish Kumar: It’s around, I think 35…

7 00:02:17.230 00:02:19.970 Emily Giant: That’s cold. Celsius or Fahrenheit?

8 00:02:21.160 00:02:22.390 Awaish Kumar: Celsius.

9 00:02:22.990 00:02:24.910 Emily Giant: Oh, then I have no idea what that is.

10 00:02:25.950 00:02:27.499 Awaish Kumar: Oh, it’s pretty hot.

11 00:02:27.750 00:02:37.959 Emily Giant: Oh, haha! 32 is freezing in Fahrenheit. There’s, like, most things I can understand, like currency, for instance, easy to understand.

12 00:02:38.460 00:02:40.520 Emily Giant: Fahrenheit and Celsius.

13 00:02:41.070 00:02:45.530 Emily Giant: Doesn’t matter. Like, every time somebody tells me the calculation, my eyes go, like.

14 00:02:45.900 00:02:49.640 Emily Giant: different directions. Like, I just… I don’t get it.

15 00:02:50.080 00:02:52.540 Emily Giant: I have to get out my calculator every time.

16 00:02:53.970 00:03:00.059 Awaish Kumar: It doesn’t… Yeah, we are used to of using sensors much more than Fahrenheit.

17 00:03:00.650 00:03:04.529 Emily Giant: Yeah, I don’t know why America decided that, like.

18 00:03:05.270 00:03:11.040 Emily Giant: inches and Fahrenheit and all these things were, like, what we would do, even though nobody else does.

19 00:03:11.150 00:03:14.689 Emily Giant: It just makes us, like, more idiotic than we usually are.

20 00:03:17.960 00:03:18.840 Amber Lin: Hello.

21 00:03:19.120 00:03:20.100 Emily Giant: Hi!

22 00:03:21.220 00:03:23.499 Amber Lin: It’s new to see your hair down, Emily.

23 00:03:23.980 00:03:36.040 Emily Giant: Oh, I know, and it’s a totally different color, probably, than last time. I had to stop dyeing it. Like, I was dyeing it blonde for so long that it got really crispy, so I was like, just put me back in my original hair, and…

24 00:03:36.530 00:03:38.290 Amber Lin: Save the money.

25 00:03:39.320 00:03:42.699 Amber Lin: I mean, I didn’t even notice a difference, I think it suits you.

26 00:03:43.230 00:03:50.329 Emily Giant: Thank you. It definitely suits my, my bank account to not have to, like, color it.

27 00:03:51.890 00:04:02.969 Amber Lin: It does take a lot. I used to… when I… when I shaved my head, I dyed it blonde, but then… and then I… and then I realized I can’t really go to work like that.

28 00:04:02.970 00:04:03.350 Emily Giant: it’s.

29 00:04:03.350 00:04:03.780 Amber Lin: Oh, nice.

30 00:04:03.780 00:04:08.099 Emily Giant: expensive, too. You have to constantly, like, I bet.

31 00:04:08.100 00:04:08.700 Amber Lin: Yeah.

32 00:04:08.700 00:04:09.720 Emily Giant: Awesome.

33 00:04:09.930 00:04:10.670 Emily Giant: Did you.

34 00:04:10.670 00:04:14.510 Amber Lin: I did like it. I liked it, because washing my hair was super fast, but then.

35 00:04:14.510 00:04:15.419 Emily Giant: Oh, yeah.

36 00:04:15.420 00:04:21.720 Amber Lin: Like, I was trying to interview for stuff at that point, so I was like, no, I need my hair back.

37 00:04:21.720 00:04:23.990 Emily Giant: tired. They’re awesome.

38 00:04:25.610 00:04:33.300 Amber Lin: Okay, here, I have wishes issues here. Do we still need this?

39 00:04:36.500 00:04:39.840 Emily Giant: Perry Liquor Issue, CW… no, that’s not even.

40 00:04:39.840 00:04:40.290 Demilade Agboola: -Oh.

41 00:04:40.290 00:04:43.040 Emily Giant: it, like… Demolade and I both opened it, and we were like.

42 00:04:43.290 00:04:44.690 Amber Lin: This works.

43 00:04:44.960 00:04:46.530 Amber Lin: Okay, great.

44 00:04:49.040 00:04:59.820 Amber Lin: Okay. On Northbeam, I think last week we followed up and said there’s, like, a need for an upgrade. How’s, what’s the updates on that end?

45 00:05:01.580 00:05:06.980 Awaish Kumar: Like… For the North Beam thing, we got,

46 00:05:07.260 00:05:11.539 Awaish Kumar: Response from them that we need to subscribe for a service.

47 00:05:12.110 00:05:17.000 Awaish Kumar: And Utam said maybe on Friday we have a call, or something like that, to discuss.

48 00:05:17.000 00:05:17.630 Amber Lin: Hmm.

49 00:05:17.810 00:05:26.669 Amber Lin: I see, okay, great. They have a call on Thursday, so they’re gonna talk about… Well, this guy…

50 00:05:27.010 00:05:33.569 Awaish Kumar: Once we have that service, we can export, bring in, and… Work on this ticket.

51 00:05:38.080 00:05:43.780 Amber Lin: Gotcha. I’ll say this is… Watch.

52 00:05:43.780 00:05:44.620 Awaish Kumar: For now.

53 00:05:44.760 00:05:53.170 Awaish Kumar: 443 is done. Basically, IQA’d it and found out I shared my investigations, yeah.

54 00:05:53.170 00:06:01.029 Amber Lin: Okay. This one, we’ve been… we kept pushing it out. Is it… should we do this next week?

55 00:06:03.940 00:06:05.929 Awaish Kumar: I can do it this week.

56 00:06:07.170 00:06:13.449 Amber Lin: No, as in, like, Emily, do you think this is so very, very urgent and very important that we should do this week?

57 00:06:14.550 00:06:15.200 Emily Giant: No.

58 00:06:15.200 00:06:15.990 Awaish Kumar: No, no.

59 00:06:16.710 00:06:23.190 Emily Giant: Okay. I think also, like, Demolati, didn’t you already build one? Isn’t it part of the revenue mart?

60 00:06:24.420 00:06:28.840 Demilade Agboola: OMS refunds, specifically? I’m not sure.

61 00:06:28.840 00:06:33.799 Awaish Kumar: So, like… So… the table.

62 00:06:36.160 00:06:37.000 Awaish Kumar: Good evening.

63 00:06:37.000 00:06:37.630 Emily Giant: Open.

64 00:06:37.740 00:06:38.570 Emily Giant: Sorry.

65 00:06:41.260 00:06:47.479 Emily Giant: Let me read this. Yeah, okay, never mind, we do need to do this. And then… Yeah, because it’s historical.

66 00:06:49.780 00:06:51.530 Emily Giant: And then the tagging?

67 00:06:51.810 00:06:57.740 Emily Giant: I’m working on care tags, so that portion of it doesn’t…

68 00:06:58.570 00:07:03.059 Emily Giant: Oh, God. This is gonna be really hard for a wish to do, because of…

69 00:07:04.090 00:07:06.249 Emily Giant: I, I honestly think I should do this.

70 00:07:07.120 00:07:09.310 Emily Giant: Because it’s gonna take…

71 00:07:09.660 00:07:19.140 Emily Giant: knowing what IDs to pull out to make it compatible with the Shopify refunds and the care data, it’s really a mess.

72 00:07:19.680 00:07:27.189 Amber Lin: Gotcha. I mean, you can start on it, you can always ask Wish or Demola to hop in to help you with something.

73 00:07:27.610 00:07:29.579 Emily Giant: Why don’t I build out the…

74 00:07:30.250 00:07:34.600 Emily Giant: I’ll start the build, just so that, like, I can add notes, and then pass it back. Okay.

75 00:07:34.990 00:07:35.640 Amber Lin: Okay.

76 00:07:45.550 00:07:46.340 Amber Lin: Okay.

77 00:07:46.550 00:07:53.410 Amber Lin: That just gives the two items that we need to give to PK, and then similarly…

78 00:07:53.410 00:07:54.580 Awaish Kumar: here.

79 00:07:54.820 00:08:01.739 Awaish Kumar: Yeah, 444 is, like, kind of… can be done easily, but 445, I… it’s… we can say it’s blocked.

80 00:08:01.970 00:08:09.200 Awaish Kumar: on PK’s response that… He needs to send me the logic for channels, channel categorization.

81 00:08:10.590 00:08:11.850 Amber Lin: Gotcha. Okay.

82 00:08:13.140 00:08:15.900 Emily Giant: I have it. Oh wait, let me add it to that ticket.

83 00:08:16.160 00:08:16.780 Amber Lin: Oh.

84 00:08:22.040 00:08:25.259 Emily Giant: So it’s just the logic for historical tag categorization?

85 00:08:26.190 00:08:27.499 Awaish Kumar: No, like, in GF…

86 00:08:27.500 00:08:27.850 Emily Giant: promo.

87 00:08:27.850 00:08:30.290 Awaish Kumar: He showed me some logic.

88 00:08:30.430 00:08:34.850 Awaish Kumar: To change, like, if we have a Google…

89 00:08:35.059 00:08:40.130 Awaish Kumar: search, or some other search, and then it should be paid search, and Shopify…

90 00:08:40.500 00:08:44.630 Awaish Kumar: Being categorized as organic, or things like that.

91 00:08:45.130 00:08:47.199 Emily Giant: Got it. No, I don’t have that, sorry.

92 00:08:47.310 00:08:53.710 Emily Giant: I do have their, their forecast doc, and I think it has all those channels in it.

93 00:08:55.110 00:09:01.249 Emily Giant: And I… you could probably distill it down, since that’s what they’re using as the forecast, if he doesn’t get that to you right away.

94 00:09:01.250 00:09:04.319 Amber Lin: And that is actually in dbt.

95 00:09:04.660 00:09:09.100 Emily Giant: Already, as, like, FY26 marketing forecast.

96 00:09:13.950 00:09:17.769 Emily Giant: I can tell you where to find all the… here, I’ll send you the model name from dbt.

97 00:09:18.240 00:09:22.369 Emily Giant: Would that be helpful? It’s a question they made with those channels.

98 00:09:22.370 00:09:27.989 Awaish Kumar: like, I can get a, maybe, list of channels from that, but does that have a mapping? Like…

99 00:09:28.950 00:09:30.680 Emily Giant: Oh, God, it doesn’t, no.

100 00:09:30.680 00:09:32.999 Amber Lin: They are saying, like, purchase a channel.

101 00:09:33.130 00:09:33.969 Awaish Kumar: But would you…

102 00:09:33.970 00:09:34.520 Amber Lin: C.

103 00:09:34.520 00:09:37.240 Awaish Kumar: Trainers are included in that paid search category.

104 00:09:38.800 00:09:39.150 Amber Lin: name.

105 00:09:39.150 00:09:44.050 Emily Giant: for an hour this afternoon, too, and I can get that… I can just have him say it out loud to me.

106 00:09:44.050 00:09:44.430 Awaish Kumar: Okay.

107 00:09:44.430 00:09:46.400 Emily Giant: And right away so that you’re not blocked.

108 00:09:47.110 00:09:50.940 Amber Lin: Should I follow up? I’ll send him a quick note.

109 00:09:51.500 00:09:52.710 Amber Lin: PK…

110 00:09:58.610 00:09:59.310 Amber Lin: Great.

111 00:10:00.000 00:10:03.709 Amber Lin: I think that’s all. That was the main things.

112 00:10:04.040 00:10:05.570 Amber Lin: That we have here.

113 00:10:06.530 00:10:12.600 Emily Giant: Can I sh… do… oh, sorry. Do you need to do more with linear?

114 00:10:13.060 00:10:13.909 Amber Lin: No.

115 00:10:14.180 00:10:21.350 Emily Giant: Okay, Demolade, can I show you real quick, while we have minutes, some of the discrepancies I found in historical revenue?

116 00:10:21.700 00:10:22.810 Demilade Agboola: Okay, sure.

117 00:10:23.400 00:10:25.499 Emily Giant: Okay, because I think, first of all.

118 00:10:25.650 00:10:44.460 Emily Giant: The problem is way less than what we… way less. It’s that, we needed to be using piece revenue instead of piece-adjusted price. Piece-adjusted price is, like, the unit price. So if somebody ordered triple the firecracker, it will show the price of one unit of the firecracker, and that’s why it was so much less.

119 00:10:44.470 00:10:48.180 Emily Giant: So, once that’s switched out, the differences are…

120 00:10:48.620 00:10:55.109 Emily Giant: so we did the comp on that one day that we were like, oh my god, what is this? So if you look at it here.

121 00:10:55.400 00:11:05.719 Emily Giant: there’s, like, a one-cent difference with most of them if I subtract out shipping from the OMS calculations table, except for this.

122 00:11:05.720 00:11:06.319 Demilade Agboola: Yes. Yeah.

123 00:11:06.320 00:11:09.599 Emily Giant: In that case, in these cases where I highlighted it.

124 00:11:09.750 00:11:18.889 Emily Giant: OMS Comp XF base is actually correct. So, vast majority, It’s totally fine.

125 00:11:19.060 00:11:27.060 Emily Giant: like, in fact, OMS CompEXF base is correct, for all of the ones that are mismatched. And then…

126 00:11:27.310 00:11:33.640 Emily Giant: I went ahead and pulled, like, anything with a revenue difference greater than 20.

127 00:11:34.180 00:11:38.399 Emily Giant: I just pulled 100 to see… because, like, if you look at 100, it’s gonna be…

128 00:11:38.630 00:11:42.939 Emily Giant: It’s gonna cover what the problems are, to a degree, so…

129 00:11:43.190 00:11:57.800 Emily Giant: I’m putting the… what the subtotal is in dash here, and then writing down, like, what I’m finding. So, for example, a lot of what I’m seeing is that OMS Comp XF base is still counting

130 00:11:58.240 00:12:02.539 Emily Giant: forced upgrades as having revenue. So that’s one problem.

131 00:12:03.270 00:12:18.550 Emily Giant: the thing that’s weird is that it’s not always, so I’m like, do we even care? But, like, this one is actually only $165, but OMS CompactFBASE recognized the three crossed-out line items as having revenue, and that’s what.

132 00:12:18.550 00:12:19.570 Demilade Agboola: When you don’t.

133 00:12:19.570 00:12:20.310 Emily Giant: Dad.

134 00:12:21.130 00:12:23.920 Demilade Agboola: Yeah, that’s why I swing fluid. Gotcha, gotcha.

135 00:12:24.310 00:12:26.440 Emily Giant: And then there’s this other issue.

136 00:12:27.210 00:12:35.500 Emily Giant: Where? Okay, so actual price was correct in the suborder model, where… Suddenly, and only for…

137 00:12:36.000 00:12:37.040 Demilade Agboola: Sure, guys, I mean?

138 00:12:37.040 00:12:37.590 Emily Giant: Okay.

139 00:12:38.690 00:12:41.730 Demilade Agboola: Can you send me that ID number, or, like, can you share that sheet?

140 00:12:42.500 00:12:58.969 Emily Giant: Yes, it’s the same one that I shared with you this morning, where we were doing the prompts. Yeah, I’m just adding tabs. But the other issue that I found, which is, like, kind of sequestered in 2023, it looks like, I’ll have to do a little more research on this, but…

141 00:13:00.990 00:13:07.739 Emily Giant: So, it was a triple the clause. There was no touches on this order, everything went well, should have been 306.

142 00:13:08.310 00:13:16.640 Emily Giant: I can see, just from looking at this, that it did, like, 3 times Or, like, did too many…

143 00:13:16.640 00:13:22.180 Demilade Agboola: Because it’s triple the cause, it did 3 times the… actually, it did… Twice.

144 00:13:22.550 00:13:25.190 Emily Giant: Yeah, it doubled it for some reason.

145 00:13:26.380 00:13:30.079 Emily Giant: So I’m guessing, like, well, if I pull it up in the model.

146 00:13:34.530 00:13:37.330 Emily Giant: But they’re all, like, little things like that.

147 00:13:38.730 00:13:45.650 Emily Giant: in combo LMS, and that does seem to be the more stable model outside of these edge cases.

148 00:13:46.110 00:13:47.280 Emily Giant: from…

149 00:13:48.180 00:13:48.820 Demilade Agboola: Yeah.

150 00:13:49.030 00:13:51.780 Demilade Agboola: Yeah… does…

151 00:13:54.190 00:14:05.099 Demilade Agboola: Also, it just… it does also mean that, like, we should be looking at deprecating, like, suborder calculations, because, again, it feels very unnecessary to have two different models.

152 00:14:05.290 00:14:07.420 Emily Giant: It needs to go away. Yeah.

153 00:14:08.220 00:14:09.839 Emily Giant: For sure.

154 00:14:17.530 00:14:21.200 Emily Giant: So that’s why, like, I think this is why Perry is, like.

155 00:14:21.330 00:14:24.080 Emily Giant: what’s going on with these numbers? It’s,

156 00:14:24.710 00:14:28.609 Emily Giant: Okay, so this has two lines for the clause.

157 00:14:29.820 00:14:35.330 Emily Giant: And I don’t know why. Like, why would there be two? And they’re different keys?

158 00:14:36.650 00:14:37.920 Demilade Agboola: Okay, so…

159 00:14:37.920 00:14:38.890 Emily Giant: Yeah.

160 00:14:39.780 00:14:41.729 Emily Giant: Piece quantity, 3.

161 00:14:41.970 00:14:45.140 Emily Giant: And it’s correct, it’s just that the line is duplicated.

162 00:14:46.780 00:14:50.909 Demilade Agboola: Yeah, it’s a duplicate. So it’s a comp rank.

163 00:14:52.520 00:15:01.020 Demilade Agboola: Alright, I’ll look into that, and again, some of the logic in the models is just… enamas.

164 00:15:01.640 00:15:12.070 Emily Giant: Oh, it is? I’m kidding. So this component ID is the same, And It should actually have…

165 00:15:12.900 00:15:14.780 Emily Giant: Filtered that out.

166 00:15:18.310 00:15:21.539 Emily Giant: Yeah, because in the dbt model.

167 00:15:21.990 00:15:30.369 Emily Giant: you can’t filter on line items, or you can’t partition online items, but you can partition on component ID.

168 00:15:34.550 00:15:36.839 Emily Giant: So I don’t know why that’s… well, that’s…

169 00:15:44.400 00:15:48.630 Emily Giant: So… Yeah, I don’t know why that’s not partitioned out here.

170 00:15:51.470 00:15:57.020 Demilade Agboola: Alright, I’ll take a look at it, I’ll push a fix for that,

171 00:15:59.340 00:16:01.879 Demilade Agboola: Yes, petition by line item ID.

172 00:16:02.150 00:16:06.170 Emily Giant: Mmm… yeah, you wanna do… Component ID.

173 00:16:06.470 00:16:16.169 Demilade Agboola: Yeah, and then I’ll look at that, push a fix for that. Also, also look at the situations where it appears that

174 00:16:17.050 00:16:22.530 Demilade Agboola: like, the numbers seem inflated, and I would also, like, kind of figure out what the situation is with that as well.

175 00:16:23.060 00:16:26.869 Emily Giant: Okay, so if I keep adding to this sheet, will that be helpful?

176 00:16:27.280 00:16:27.910 Demilade Agboola: Oh yeah, yeah.

177 00:16:27.910 00:16:40.049 Emily Giant: Okay, cool. I’ll just… I’m gonna do the whole sheet, the whole hundred orders that… and then distill it down to what the issues are, because I think there are only 2 or 3 actual issues, and .

178 00:16:40.380 00:16:43.340 Demilade Agboola: Once we have those identified, and if there’s…

179 00:16:43.340 00:16:46.869 Emily Giant: Happening throughout history, or just during certain dates.

180 00:16:46.990 00:16:49.979 Emily Giant: If it’s just certain dates, I am inclined to say, like.

181 00:16:51.340 00:17:00.280 Emily Giant: don’t do anything about it. Like, don’t worry about it. Especially if it’s, like, before 2021. Because we don’t even generally look back that far.

182 00:17:01.690 00:17:12.249 Demilade Agboola: Fair enough, but if we can have fixes for revenue, it’ll be very helpful, at least to have an idea of, like, what the revenue is and what plays a role in that.

183 00:17:12.700 00:17:13.740 Emily Giant: Yeah.

184 00:17:14.250 00:17:19.310 Demilade Agboola: Alright, that’s… that’s been helpful. I would use this to figure out some of the…

185 00:17:20.260 00:17:37.780 Demilade Agboola: like, fixes I need to make in the models, so that we can ensure everything… the numbers make sense. For Amber and Awish, we’ve been able to get, like, the legacy numbers into our revenue models, but we’ve started QAing, and we’ve noticed some issues with it, so that’s kind of what this is about.

186 00:17:38.930 00:17:41.210 Amber Lin: Gotcha. Okay.

187 00:17:41.390 00:17:42.520 Amber Lin: The…

188 00:17:42.520 00:17:46.419 Emily Giant: Options are far less than we thought. Okay, awesome. We can opt to.

189 00:17:46.560 00:17:50.519 Emily Giant: I’ll keep filling this out. Thanks, everyone. We’ll let you know when we’re done. Bye!

190 00:17:51.190 00:17:51.780 Amber Lin: Bye.