Meeting Title: Eden | Standup Date: 2025-09-04 Meeting participants: Amber Lin, Demilade Agboola, Awaish Kumar, Henry Zhao
WEBVTT
1 00:00:14.130 ⇒ 00:00:22.749 Amber Lin: Oh, did I end the… oops, I think I ended the Urban Stems meeting. Let me let them know.
2 00:00:37.150 ⇒ 00:00:39.419 Amber Lin: Hello, Oisha, how are you feeling?
3 00:00:46.540 ⇒ 00:00:49.070 Awaish Kumar: Not really done.
4 00:00:49.670 ⇒ 00:00:53.800 Awaish Kumar: Maybe just uttering… Oh, phew.
5 00:00:54.130 ⇒ 00:01:00.499 Awaish Kumar: meeting, or look at something urgent, but yeah, otherwise I… We’ll be off.
6 00:01:01.140 ⇒ 00:01:07.059 Amber Lin: I see, I see. I’ll try to keep tasks away from you. I think we can survive.
7 00:01:08.000 ⇒ 00:01:17.029 Amber Lin: Let me pull things up… And let me make sure Harry’s in the invite. Yes, he has.
8 00:01:20.340 ⇒ 00:01:22.580 Amber Lin: Okay, share screen.
9 00:01:23.950 ⇒ 00:01:25.739 Amber Lin: Boop, boop, boop, boom.
10 00:01:29.770 ⇒ 00:01:30.630 Amber Lin: Okay.
11 00:01:34.460 ⇒ 00:01:38.210 Amber Lin: Are we connected to QuickBooks?
12 00:01:40.250 ⇒ 00:01:46.349 Awaish Kumar: Like, we are, but the pipeline isn’t working because we need admin access.
13 00:01:46.350 ⇒ 00:01:46.870 Amber Lin: Mmm.
14 00:01:46.870 ⇒ 00:01:54.369 Awaish Kumar: And, the Aiden team don’t want to give Aiden the edible access. I already asked Polyatomic
15 00:01:54.670 ⇒ 00:01:58.429 Awaish Kumar: To check, like, with the correct account,
16 00:01:58.610 ⇒ 00:02:02.850 Awaish Kumar: We already have an account set up, right? So I already asked Polytopic to see if
17 00:02:03.080 ⇒ 00:02:12.090 Awaish Kumar: They can manage a pipeline without admin access, and they haven’t responded yet, but, yeah, I’m waiting on their response.
18 00:02:12.390 ⇒ 00:02:19.450 Awaish Kumar: If… if they don’t provide… If they are not able to it, then, yeah, like…
19 00:02:19.450 ⇒ 00:02:19.960 Amber Lin: Then we can.
20 00:02:19.960 ⇒ 00:02:25.749 Awaish Kumar: So he can do it with the current credentials, so they need to upgrade it.
21 00:02:26.160 ⇒ 00:02:27.410 Amber Lin: I see, I hear you.
22 00:02:27.640 ⇒ 00:02:29.820 Amber Lin: Alright, I will let them know.
23 00:02:30.340 ⇒ 00:02:34.260 Amber Lin: And then on the GHL side…
24 00:02:35.340 ⇒ 00:02:38.819 Awaish Kumar: so, we already got the…
25 00:02:39.030 ⇒ 00:02:49.539 Awaish Kumar: invite, and we are in the platform, but we… and also, it’s pretty easy to generate an API key there. The only thing is writing that
26 00:02:50.430 ⇒ 00:02:55.629 Awaish Kumar: Reverse serial part. It’s really been kind of a script to do that, and I haven’t done that.
27 00:02:55.940 ⇒ 00:02:56.670 Amber Lin: Okay.
28 00:02:56.670 ⇒ 00:03:00.149 Awaish Kumar: I still hope, maybe I will do it tomorrow.
29 00:03:00.150 ⇒ 00:03:04.709 Amber Lin: I see. So, I can close this one, the authentication, right?
30 00:03:05.650 ⇒ 00:03:06.230 Awaish Kumar: Yeah.
31 00:03:06.390 ⇒ 00:03:13.010 Amber Lin: Okay, awesome. Skip issues. And then, what data needs to be sent?
32 00:03:13.220 ⇒ 00:03:14.530 Amber Lin: Okay, I can…
33 00:03:14.530 ⇒ 00:03:16.230 Awaish Kumar: It’s an independent thing.
34 00:03:16.660 ⇒ 00:03:17.090 Amber Lin: Oh, sweet.
35 00:03:17.090 ⇒ 00:03:22.119 Awaish Kumar: Like, can we… Sort of, like,
36 00:03:26.410 ⇒ 00:03:28.840 Awaish Kumar: Okay, yeah, I will figure out what…
37 00:03:29.440 ⇒ 00:03:33.520 Awaish Kumar: data we can send through GHL APIs, and
38 00:03:36.660 ⇒ 00:03:37.860 Awaish Kumar: Henry Kevin.
39 00:03:38.560 ⇒ 00:03:43.500 Awaish Kumar: Basically… look at university portfolio.
40 00:03:44.470 ⇒ 00:03:47.229 Henry Zhao: Okay, do you want to have a meeting for that, Awash, or…
41 00:03:47.530 ⇒ 00:03:48.430 Henry Zhao: How do we want to.
42 00:03:50.100 ⇒ 00:03:57.170 Awaish Kumar: Yeah, like, I’ll let you know, because it’s… if it is… it’s… if I’m writing the script, then, yeah, I, like…
43 00:03:57.430 ⇒ 00:04:02.579 Awaish Kumar: I just send it, like, I will just need your kind of QA.
44 00:04:02.980 ⇒ 00:04:05.030 Awaish Kumar: Okay. I will need your help to QA and the changes.
45 00:04:05.030 ⇒ 00:04:07.939 Henry Zhao: You’re gonna write the script to send me the GHL data?
46 00:04:09.490 ⇒ 00:04:14.379 Awaish Kumar: I’m going to write a script, and possibly, like, if it is… if it’s not, like.
47 00:04:14.520 ⇒ 00:04:17.640 Awaish Kumar: Way time-consuming. I’m going to do that.
48 00:04:17.779 ⇒ 00:04:27.509 Awaish Kumar: by tomorrow, and if that’s done successfully, I will just send you help to QA. The data is going, like, in the right format and things like that, like.
49 00:04:28.260 ⇒ 00:04:31.900 Awaish Kumar: as a… As someone, like, marketing…
50 00:04:32.610 ⇒ 00:04:37.170 Awaish Kumar: Leader, like, how… like, you… you are seeing the data as you…
51 00:04:37.500 ⇒ 00:04:42.859 Awaish Kumar: like, if it looks good for UTM or whatever tracking, it is being utilized.
52 00:04:43.210 ⇒ 00:04:48.769 Awaish Kumar: For that reason, I need… I will be needing your help, but otherwise, I will write the script and…
53 00:04:48.940 ⇒ 00:04:50.020 Awaish Kumar: Push the data.
54 00:04:52.130 ⇒ 00:04:53.820 Henry Zhao: Where are you getting the JGL data from?
55 00:04:57.230 ⇒ 00:04:59.950 Awaish Kumar: We are not, like, GHL is a…
56 00:05:00.680 ⇒ 00:05:05.200 Awaish Kumar: Platform where we are… we will be sending some data.
57 00:05:06.110 ⇒ 00:05:07.050 Awaish Kumar: It’s a…
58 00:05:07.570 ⇒ 00:05:08.490 Henry Zhao: From where?
59 00:05:08.490 ⇒ 00:05:12.199 Awaish Kumar: It’s a kind of a customer I.O. kind of platform, right?
60 00:05:12.390 ⇒ 00:05:16.289 Awaish Kumar: Because… and which basically sends SMS
61 00:05:16.750 ⇒ 00:05:23.809 Awaish Kumar: to customers. So we will be figuring out the… For the customers.
62 00:05:24.200 ⇒ 00:05:27.540 Awaish Kumar: To whom we should be sending the messages, and then
63 00:05:27.680 ⇒ 00:05:36.059 Awaish Kumar: We’ll be pushing the data for those customers, like name, email, or mobile number, to the GHL.
64 00:05:37.330 ⇒ 00:05:38.919 Henry Zhao: Or from the dbt model, right?
65 00:05:41.960 ⇒ 00:05:53.770 Awaish Kumar: It’s not, like, not really a dbt model, because dbt model is… will be just, will be getting the data, but I will be writing a Python script to basically push using GHL APIs.
66 00:05:56.480 ⇒ 00:05:59.159 Henry Zhao: I still don’t think I fully understand.
67 00:06:00.500 ⇒ 00:06:16.259 Awaish Kumar: Yeah, but it’s like a pipeline. I will be writing the pipeline, it’s not a problem. I will just need your help when the data is already in the GHL. I will need to have a QA, the data is… you can see there, it’s what you can maybe utilize, or something like that.
68 00:06:17.130 ⇒ 00:06:17.560 Henry Zhao: Who’s gonna…
69 00:06:17.560 ⇒ 00:06:18.620 Awaish Kumar: useful or not.
70 00:06:18.620 ⇒ 00:06:20.309 Henry Zhao: We’re gonna be utilizing this data.
71 00:06:20.600 ⇒ 00:06:24.259 Amber Lin: Ryan asked for that task, so probably Ryan.
72 00:06:24.410 ⇒ 00:06:26.929 Henry Zhao: Okay, so I’ll probably sync with Ryan, just see.
73 00:06:27.070 ⇒ 00:06:27.580 Amber Lin: Okay.
74 00:06:28.920 ⇒ 00:06:29.970 Amber Lin: Sounds good.
75 00:06:30.520 ⇒ 00:06:37.239 Amber Lin: Let’s see… Am I checking on…
76 00:06:37.370 ⇒ 00:06:41.389 Amber Lin: these. I saw the PR in the data channel.
77 00:06:41.520 ⇒ 00:06:43.530 Amber Lin: How are these tickets?
78 00:06:44.390 ⇒ 00:06:51.210 Demilade Agboola: So PLTV, I have a final PR for that. This should be done once that PR is matched.
79 00:06:52.430 ⇒ 00:06:53.220 Amber Lin: managing that.
80 00:06:53.220 ⇒ 00:06:58.779 Demilade Agboola: So I… I’ll do that first thing. So the initial one I did.
81 00:06:58.980 ⇒ 00:07:04.009 Demilade Agboola: it kind of worked, but then it solved one of the problems of the PLTV.
82 00:07:04.240 ⇒ 00:07:11.659 Demilade Agboola: Not showing, but the numbers were not accurate, so this PR fix will ensure the numbers make more sense.
83 00:07:12.090 ⇒ 00:07:13.740 Demilade Agboola: So there’s that.
84 00:07:13.810 ⇒ 00:07:15.360 Amber Lin: And then…
85 00:07:17.320 ⇒ 00:07:23.780 Demilade Agboola: for… I did the thing yesterday for, Adam’s modeling.
86 00:07:24.540 ⇒ 00:07:26.580 Amber Lin: Okay, for the acquisition cost, so the.
87 00:07:26.580 ⇒ 00:07:32.359 Demilade Agboola: That was not… that wasn’t… that wasn’t Adams, it was… I can’t remember whose task it was, it… the…
88 00:07:32.710 ⇒ 00:07:34.380 Demilade Agboola: The one for the offer.
89 00:07:34.930 ⇒ 00:07:38.469 Amber Lin: Oh, yeah. Yeah, I see, I see it here.
90 00:07:38.470 ⇒ 00:07:45.670 Demilade Agboola: Yeah, so today, today my focus will be the modeling for acquisition, as well as Mitesh Cox.
91 00:07:47.010 ⇒ 00:07:47.780 Amber Lin: Okay.
92 00:07:48.090 ⇒ 00:07:53.480 Amber Lin: Did Zoe get back to you on the… let me check…
93 00:07:53.810 ⇒ 00:07:59.550 Demilade Agboola: Yeah, so Zoe did say that, you know, we should still do everything through QuickBooks, which, obviously, with QuickBooks…
94 00:07:59.550 ⇒ 00:08:01.570 Amber Lin: Can’t connect to QuickBooks.
95 00:08:01.570 ⇒ 00:08:07.559 Demilade Agboola: Yeah, so I was going to point out that, you know, Salish just told us about the QuickBooks issue.
96 00:08:09.260 ⇒ 00:08:09.980 Amber Lin: I see.
97 00:08:09.980 ⇒ 00:08:17.669 Demilade Agboola: But we need to get… we need to get resolution on that. Like, I don’t know if we need to talk to Josh, or we need someone on the executive to just make an executive decision.
98 00:08:18.040 ⇒ 00:08:19.360 Amber Lin: Yeah.
99 00:08:19.360 ⇒ 00:08:24.720 Demilade Agboola: Yeah, but something needs to be done. So how about Joshua Adams, someone who can make backhaul.
100 00:08:28.120 ⇒ 00:08:30.029 Amber Lin: Oh, I’m gonna shut.
101 00:08:31.320 ⇒ 00:08:32.360 Amber Lin: Josh…
102 00:08:36.710 ⇒ 00:08:37.659 Amber Lin: Okay.
103 00:08:38.280 ⇒ 00:08:43.379 Amber Lin: Sinclair books. If not, do you think we can survive with some…
104 00:08:43.570 ⇒ 00:08:48.990 Amber Lin: data downloads. Zoe usually responds really quick, so I think we can survive.
105 00:08:49.390 ⇒ 00:08:50.160 Amber Lin: If we just…
106 00:08:50.160 ⇒ 00:08:56.570 Demilade Agboola: I mean, yeah, if we need it, like, right now, we can get the data download, and I can start working on something.
107 00:08:56.690 ⇒ 00:09:06.920 Demilade Agboola: So that I can push something to Harry, and Harry can have that. I’ll be able to do some, work. So that’s the manual part. But obviously, if we want to just make things more, like.
108 00:09:07.860 ⇒ 00:09:14.700 Demilade Agboola: like, easier in the future, and just more, like, automated, yeah, we should integrate QuickBooks, that’s… that’s very important.
109 00:09:14.860 ⇒ 00:09:27.350 Amber Lin: Yeah, I think we would be able to download data from QuickBooks, because we do have an account. I’m not sure what we can get, because I haven’t logged in there yet, but…
110 00:09:28.130 ⇒ 00:09:39.469 Amber Lin: let’s go explore what we can get… oh, I’m not sharing my full screen. Here. So, it’s available in QuickBooks. There’s a chart…
111 00:09:39.620 ⇒ 00:09:43.990 Amber Lin: with the name chargeback slash refunds.
112 00:09:44.150 ⇒ 00:09:50.700 Amber Lin: I can share… I think the login is in the Eden… is shared to Eden.
113 00:09:51.120 ⇒ 00:09:56.849 Amber Lin: Data… Always, did you store it in 1Pass when you logged in?
114 00:09:58.650 ⇒ 00:10:00.360 Awaish Kumar: For what QBO?
115 00:10:00.950 ⇒ 00:10:02.410 Amber Lin: For QuickBooks.
116 00:10:03.290 ⇒ 00:10:04.920 Awaish Kumar: Yeah, it’s in OnePlus.
117 00:10:04.920 ⇒ 00:10:06.000 Amber Lin: Okay, sounds good.
118 00:10:07.790 ⇒ 00:10:14.050 Awaish Kumar: But, but, like… What do you need? Do you want to go in and download something, like, annually?
119 00:10:14.640 ⇒ 00:10:20.330 Amber Lin: Yeah, I want to see if we can download it, if not, I’ll ask Joe to download it.
120 00:10:20.790 ⇒ 00:10:22.880 Awaish Kumar: Yeah, you can check, but,
121 00:10:23.080 ⇒ 00:10:28.399 Awaish Kumar: I… yeah, we can download some of the data. We are, like, very restricted… we are very restricted,
122 00:10:28.930 ⇒ 00:10:31.770 Awaish Kumar: something to get, like, the axis.
123 00:10:33.040 ⇒ 00:10:37.379 Amber Lin: Yeah, I don’t think we can automate it, but we might be able to.
124 00:10:40.130 ⇒ 00:10:40.960 Amber Lin: Yeah.
125 00:10:42.610 ⇒ 00:10:47.360 Amber Lin: 2… Mmm…
126 00:10:50.440 ⇒ 00:10:57.390 Amber Lin: I can also check, actually… I’ll… I’ll… I’ll check if I can log in.
127 00:10:58.490 ⇒ 00:10:59.380 Amber Lin: Okay.
128 00:11:00.020 ⇒ 00:11:04.840 Amber Lin: And then… did you send a message to Mitesh on the cog stuff?
129 00:11:05.450 ⇒ 00:11:09.829 Amber Lin: Since I also don’t know what Josh is exactly asking for.
130 00:11:10.600 ⇒ 00:11:15.890 Demilade Agboola: No, I’ll just actually… I’ll do that right now, so I can sync with Natasha.
131 00:11:17.360 ⇒ 00:11:18.090 Amber Lin: Okay.
132 00:11:22.560 ⇒ 00:11:28.569 Amber Lin: I feel like that might have to get pushed out. The internal one probably has to get pushed out, we only had 2 days.
133 00:11:31.500 ⇒ 00:11:35.020 Amber Lin: Okay, I’m gonna push that one.
134 00:11:35.750 ⇒ 00:11:41.810 Amber Lin: And then… Probably that one as well.
135 00:11:42.750 ⇒ 00:11:43.800 Amber Lin: Okay.
136 00:11:44.250 ⇒ 00:11:57.040 Amber Lin: So, Adam asked again… Adam asked Robert about the finance dashboard, so that would be a priority for us. I think Judd and Devin marked theirs as
137 00:11:57.530 ⇒ 00:12:04.310 Amber Lin: medium priority? Henry, do you know if they’re okay with their dashboard being done next week?
138 00:12:05.600 ⇒ 00:12:13.050 Henry Zhao: I can ask, but let me do a little bit of digging around today and see if I can finish it this week, and then I’ll let them know maybe towards the end of the day.
139 00:12:13.920 ⇒ 00:12:14.620 Amber Lin: Okay.
140 00:12:14.770 ⇒ 00:12:16.010 Henry Zhao: Sounds good.
141 00:12:16.280 ⇒ 00:12:24.659 Amber Lin: So it’s these… This is done, right? Once done, I’ve fixed it, this is done.
142 00:12:28.780 ⇒ 00:12:34.649 Demilade Agboola: So, yeah, I’ve done, like, I’ve done my part. I don’t know if Kerry has been able to put things together.
143 00:12:34.840 ⇒ 00:12:38.549 Henry Zhao: It’s done on his part, but the numbers don’t match what Jonah says.
144 00:12:38.730 ⇒ 00:12:40.860 Henry Zhao: So that’s why I said need stakeholder response.
145 00:12:41.580 ⇒ 00:12:44.859 Henry Zhao: No, it’s already done on his part, so just… we need stakeholder response.
146 00:12:47.040 ⇒ 00:12:48.639 Amber Lin: Oh, I see.
147 00:12:50.670 ⇒ 00:12:51.760 Henry Zhao: Numbers match.
148 00:12:52.390 ⇒ 00:12:54.650 Amber Lin: Gotcha, okay.
149 00:12:55.720 ⇒ 00:13:13.539 Amber Lin: I have one thing… one thing here, remember when Josh joined our session on, I think, Tuesday? He asked us to check the actual marketing spend to the Tableau dashboard, and Jonah responded,
150 00:13:14.050 ⇒ 00:13:15.319 Amber Lin: I think…
151 00:13:18.740 ⇒ 00:13:21.469 Demilade Agboola: So Jenna did send a response today.
152 00:13:21.770 ⇒ 00:13:28.569 Demilade Agboola: As well, if you go to… yeah, basically, he said, yeah, That it was quite close.
153 00:13:29.480 ⇒ 00:13:32.400 Demilade Agboola: I mean, we’re, like, the delta is 46K right now.
154 00:13:33.430 ⇒ 00:13:39.779 Demilade Agboola: And the other… dashboards, except for the snapshots one, which is why I don’.
155 00:13:39.780 ⇒ 00:13:45.720 Henry Zhao: The thing is, in that dashboard, in that spreadsheet, it was 480K.
156 00:13:47.560 ⇒ 00:13:50.090 Demilade Agboola: It’s 3179K.
157 00:13:50.320 ⇒ 00:13:51.390 Demilade Agboola: Yeah, both weeks.
158 00:13:53.760 ⇒ 00:13:57.080 Henry Zhao: So we need to get from the stakeholders what exactly is the affiliate spend?
159 00:13:57.590 ⇒ 00:13:58.589 Henry Zhao: Because that’s what I was confused about.
160 00:14:02.560 ⇒ 00:14:03.510 Awaish Kumar: Sorry, the…
161 00:14:05.980 ⇒ 00:14:11.960 Demilade Agboola: Can we at least… can we at least integrate it so we have some… visualization.
162 00:14:12.080 ⇒ 00:14:13.880 Demilade Agboola: Of what the disparity is?
163 00:14:15.740 ⇒ 00:14:20.519 Awaish Kumar: Yeah, sorry to, interrupt. I have a, like, noise here.
164 00:14:20.620 ⇒ 00:14:27.309 Awaish Kumar: But I want to just say that, like, for the offer, like, are we looking at, like, all the data, historical?
165 00:14:27.610 ⇒ 00:14:29.920 Awaish Kumar: Historically, or is that data range…
166 00:14:30.250 ⇒ 00:14:33.200 Awaish Kumar: For this diff… like, the discrepancy.
167 00:14:34.650 ⇒ 00:14:37.729 Amber Lin: And I think doing spend data.
168 00:14:37.730 ⇒ 00:14:42.590 Demilade Agboola: Yeah, so we’re looking at, we’re trying to look at all marketing spend last month.
169 00:14:42.980 ⇒ 00:14:50.679 Demilade Agboola: And we are trying to use last month as a gauge of how accurate we are to, like, finance.
170 00:14:50.980 ⇒ 00:14:59.280 Demilade Agboola: The issue is… I think we might also need to include other spend.
171 00:14:59.610 ⇒ 00:15:10.010 Demilade Agboola: Because I’m only using the offer for this dashboard, because I integrated it. We have… because we have snapshots of the changes every day for the product sales summary by transaction.
172 00:15:10.180 ⇒ 00:15:22.999 Demilade Agboola: And so we integrated the data from the offer into this as the affiliate spend, but there’s still some other affiliate spend sources, like NTN and a couple others, which are not integrated.
173 00:15:23.000 ⇒ 00:15:30.250 Awaish Kumar: All, all… All the spend is in the… like, if you look at channel, spend summary table.
174 00:15:30.250 ⇒ 00:15:31.600 Demilade Agboola: summary.
175 00:15:31.600 ⇒ 00:15:39.850 Awaish Kumar: channel spend somewhere. It has all the spend from the offer, MNT and Y… And the influencers.
176 00:15:40.570 ⇒ 00:15:45.840 Demilade Agboola: Yeah, so I think that’s what… that’s what Joanna can see, and that may be where the disparity is. I know, like.
177 00:15:46.210 ⇒ 00:15:50.939 Demilade Agboola: I know I asked, like, if it was just the offer, and I was told, like, let’s just use the offer.
178 00:15:51.060 ⇒ 00:15:54.979 Demilade Agboola: But if we need to include the other sources, I can also integrate that.
179 00:15:55.730 ⇒ 00:15:57.549 Demilade Agboola: So I think that’ll move us a bit closer.
180 00:15:58.410 ⇒ 00:16:10.759 Awaish Kumar: Okay, you are… so you are saying that this dashboard has filters on, the… which… which… where the data is coming from, like the offer, or MNTN, or whatever, right?
181 00:16:11.310 ⇒ 00:16:20.339 Demilade Agboola: Yes, so the… the model that looks… that looks at the dashboard that Jonah is referring to, that says it’s only $46K off.
182 00:16:20.600 ⇒ 00:16:25.130 Demilade Agboola: I believe it has the China Spend Summary Model, where all the sources are there.
183 00:16:25.380 ⇒ 00:16:29.210 Demilade Agboola: But the current, like, snapshots, which is what Harry’s referring to.
184 00:16:29.210 ⇒ 00:16:29.970 Awaish Kumar: Oh, okay.
185 00:16:29.970 ⇒ 00:16:34.589 Demilade Agboola: Where I only integrated the offer, because I was asked to only integrate the offer.
186 00:16:34.590 ⇒ 00:16:35.240 Awaish Kumar: Oh, okay.
187 00:16:35.240 ⇒ 00:16:37.219 Demilade Agboola: I could also integrate the other sources.
188 00:16:37.220 ⇒ 00:16:42.490 Henry Zhao: only integrate the offers, so I’m gonna… that’s what I’m clarifying, is do we need to be integrating other spends?
189 00:16:43.390 ⇒ 00:16:48.850 Demilade Agboola: Yeah, so if we integrate all that spend, it will move us closer to these numbers that Jonah has.
190 00:16:49.410 ⇒ 00:17:00.060 Demilade Agboola: And I think that might help us get, like, you know, much closer. But I think what we should do right now is, I think we can… can we add a column in the dashboard for the snapshot data for…
191 00:17:00.460 ⇒ 00:17:07.549 Demilade Agboola: the affiliate spend. So as we keep integrating all the sources, we can see how close we are getting to
192 00:17:08.170 ⇒ 00:17:10.470 Demilade Agboola: You know, the desired numbers.
193 00:17:11.609 ⇒ 00:17:12.179 Henry Zhao: Sure.
194 00:17:12.980 ⇒ 00:17:14.340 Demilade Agboola: Okay, thank you.
195 00:17:15.460 ⇒ 00:17:25.150 Amber Lin: Yeah, I have a ticket for this one. We… I know we have… 40k gap, and…
196 00:17:26.170 ⇒ 00:17:30.649 Amber Lin: And this… Who should I assign this ticket to?
197 00:17:32.780 ⇒ 00:17:33.540 Awaish Kumar: What?
198 00:17:34.800 ⇒ 00:17:35.480 Awaish Kumar: I agree.
199 00:17:35.480 ⇒ 00:17:35.900 Demilade Agboola: fair.
200 00:17:35.900 ⇒ 00:17:36.450 Awaish Kumar: appointment.
201 00:17:36.450 ⇒ 00:17:37.290 Demilade Agboola: I think…
202 00:17:37.750 ⇒ 00:17:49.539 Demilade Agboola: Yeah, I think this is basically low par… I would say it’s low priority. 46K, when we’re talking 2.0 million, is not that serious, to be honest. It’s… the current gaps… the current gaps we’re seeing is… is…
203 00:17:50.050 ⇒ 00:17:51.069 Demilade Agboola: Is the larger…
204 00:17:51.070 ⇒ 00:17:52.370 Awaish Kumar: I mean, I didn’t, I…
205 00:17:52.810 ⇒ 00:18:08.019 Awaish Kumar: For this, I see, like, a really simple message to Jola, asking on a Slack, like, asking him, do we want to include only the offer or other sources as well, like, why we maintain, etc. And whatever the answer is, like, we just…
206 00:18:08.060 ⇒ 00:18:13.960 Awaish Kumar: use that in the model, and it will remove this gap, right? It will be a very quick fix.
207 00:18:18.030 ⇒ 00:18:19.289 Henry Zhao: I can talk to Jonah.
208 00:18:19.560 ⇒ 00:18:25.369 Amber Lin: Okay, okay, sounds good. This is so important.
209 00:18:25.890 ⇒ 00:18:26.960 Amber Lin: Mmm…
210 00:18:30.220 ⇒ 00:18:30.990 Amber Lin: Okay.
211 00:18:36.110 ⇒ 00:18:36.930 Amber Lin: Okay.
212 00:18:37.100 ⇒ 00:18:43.529 Amber Lin: Robert said he was gonna look at the rest of the finance dashboards.
213 00:18:43.530 ⇒ 00:18:45.789 Henry Zhao: Then he said he can’t… but then he said he can’t do.
214 00:18:45.790 ⇒ 00:18:48.620 Amber Lin: Oh, that’s… that’s true.
215 00:18:50.300 ⇒ 00:18:51.450 Henry Zhao: as much as I can.
216 00:18:51.840 ⇒ 00:18:52.170 Amber Lin: Yeah.
217 00:18:52.170 ⇒ 00:18:53.490 Henry Zhao: But let me… let me, let me work on mine.
218 00:18:53.490 ⇒ 00:18:54.140 Awaish Kumar: Farm?
219 00:18:57.020 ⇒ 00:19:04.269 Awaish Kumar: Apart from that, like, Damilade, you were mentioning there’s other gap as well in the marketing span, or…
220 00:19:04.410 ⇒ 00:19:06.549 Awaish Kumar: Are we okay with that?
221 00:19:07.420 ⇒ 00:19:12.369 Demilade Agboola: So, so I, I want to… I think I want us to clear, there are two gaps in the marketing side.
222 00:19:12.880 ⇒ 00:19:13.580 Awaish Kumar: Okay.
223 00:19:13.580 ⇒ 00:19:23.249 Demilade Agboola: There’s the 46K, which is when Jonah looks at the other dashboards, and he sees that marketing spend is $46K difference.
224 00:19:23.540 ⇒ 00:19:25.960 Demilade Agboola: Which I don’t think is a huge problem.
225 00:19:26.330 ⇒ 00:19:34.889 Demilade Agboola: The other huge gap, which is where I think we need to focus on, is where we’re looking at the product’s LTV snapshot data.
226 00:19:35.230 ⇒ 00:19:41.110 Demilade Agboola: Right, so that data only included, ad spend without affiliate spend.
227 00:19:41.240 ⇒ 00:19:43.719 Demilade Agboola: So that’s where the… there’s a huge gap.
228 00:19:43.880 ⇒ 00:19:45.340 Demilade Agboola: And then now…
229 00:19:45.650 ⇒ 00:19:53.069 Demilade Agboola: I’ve only integrated the offer as the only affiliate spend, not the other sources as well. So right now.
230 00:19:53.250 ⇒ 00:20:10.300 Demilade Agboola: I think there will be a huge, like, a larger gap than for the other dashboard. So now, I think we need to ask Josh, like, for the snapshot data, did that also integrate other sources? Because then, I think it will get us closer, and we’ll also be probably at $46K.
231 00:20:10.690 ⇒ 00:20:14.309 Demilade Agboola: as well, like, for the 6K gap. Makes sense. As well, for, like…
232 00:20:14.310 ⇒ 00:20:24.859 Awaish Kumar: So these both… I think these both issues just requires us to get some client feedback, just clarity, on what
233 00:20:25.170 ⇒ 00:20:30.530 Awaish Kumar: Spend they want us to include in all their dashboards.
234 00:20:30.680 ⇒ 00:20:39.260 Awaish Kumar: That’s all, right? All you know, it’s really quick fixes. It’s not a big modeling changes, these are more of a, like.
235 00:20:39.720 ⇒ 00:20:42.780 Awaish Kumar: Requirements, clarity, tasks.
236 00:20:43.540 ⇒ 00:20:58.089 Demilade Agboola: Exactly. And once we get that 46K, I think the 46K isn’t a huge issue, like, obviously we would like to get it to zero, but if we’re talking, like, you know, 2.87 million or 2.8 million, a 46K gap is really not that serious.
237 00:20:59.200 ⇒ 00:21:12.180 Awaish Kumar: Okay, so anyone who is handling the, like, like, for the last one, Henry said he will do it. I would like only one person, if anyone from Henry or Damlare, just write it, like.
238 00:21:12.530 ⇒ 00:21:15.179 Awaish Kumar: Message asking for both the things.
239 00:21:15.570 ⇒ 00:21:16.530 Awaish Kumar: And the…
240 00:21:16.650 ⇒ 00:21:21.359 Henry Zhao: I can own this. I want to just create a single source of truth for ad spend.
241 00:21:21.820 ⇒ 00:21:29.680 Awaish Kumar: So we know, if they require spend data going to all the dashboards,
242 00:21:30.390 ⇒ 00:21:42.579 Awaish Kumar: is, like, including all the sources, offline and online everything, or is it… if they want us to filter out for any dashboards. So, I would love to have the answer, like, why…
243 00:21:42.990 ⇒ 00:21:46.350 Awaish Kumar: Tomorrow, so we can make the changes.
244 00:21:55.450 ⇒ 00:21:56.250 Awaish Kumar: Yeah.
245 00:22:07.820 ⇒ 00:22:08.420 Amber Lin: Okay.
246 00:22:08.590 ⇒ 00:22:18.070 Amber Lin: And then… I think… Henry, on your side, if we…
247 00:22:18.490 ⇒ 00:22:21.169 Amber Lin: Probably these two are the ones we’ll…
248 00:22:21.660 ⇒ 00:22:23.390 Amber Lin: Put as medium, and find it.
249 00:22:23.390 ⇒ 00:22:25.120 Henry Zhao: Another person next week, yeah.
250 00:22:25.140 ⇒ 00:22:27.420 Amber Lin: The Judd and Devin one, we’ll definitely have to push it next week.
251 00:22:27.420 ⇒ 00:22:31.120 Henry Zhao: Because I need to do some, like, scoping on… I already did the scoping, but…
252 00:22:31.150 ⇒ 00:22:32.559 Amber Lin: I need to find the data.
253 00:22:32.750 ⇒ 00:22:36.419 Amber Lin: Okay, sounds good. Do you need any modeling help there?
254 00:22:36.640 ⇒ 00:22:40.420 Henry Zhao: No, no, no, not at all. It’s, the, like, requirement… oh, you mean, like, in dbt?
255 00:22:41.350 ⇒ 00:22:41.920 Amber Lin: Yeah.
256 00:22:42.190 ⇒ 00:22:45.359 Henry Zhao: I’ll figure it out, and then ask a waste or Demolati if I need any help.
257 00:22:45.360 ⇒ 00:22:58.430 Amber Lin: Okay, I’ll push that to the upcoming cycle. Let me send… Chad…
258 00:23:03.300 ⇒ 00:23:06.280 Amber Lin: I mean, they just told us about it a few days ago, so I think it should be okay to push back.
259 00:23:12.200 ⇒ 00:23:13.150 Awaish Kumar: So, right?
260 00:23:15.150 ⇒ 00:23:17.519 Amber Lin: Most of them are, like…
261 00:23:18.090 ⇒ 00:23:22.510 Awaish Kumar: blockers, right? What… But actually, like…
262 00:23:22.510 ⇒ 00:23:23.020 Henry Zhao: It’s modeled.
263 00:23:23.020 ⇒ 00:23:28.920 Awaish Kumar: One is the message, sending the message, and then the other one is modeling the dashboard task.
264 00:23:29.360 ⇒ 00:23:31.080 Awaish Kumar: So you’re willing to…
265 00:23:31.080 ⇒ 00:23:40.210 Amber Lin: What are the main dashboarding tasks? So, for finance, and for Adam, the tasks that rolled over from last cycle.
266 00:23:40.820 ⇒ 00:23:48.119 Awaish Kumar: And that’s… That requires some clarity on, it’s like, requirements killinity, which we just discussed.
267 00:23:48.240 ⇒ 00:23:49.960 Awaish Kumar: For the spent data, right?
268 00:23:50.520 ⇒ 00:23:53.949 Amber Lin: Yeah, and then on the bottom, the spend data.
269 00:23:54.300 ⇒ 00:23:56.119 Amber Lin: Are you able to see my screen?
270 00:23:56.120 ⇒ 00:23:59.379 Awaish Kumar: Okay, 801 is also, kind of…
271 00:23:59.700 ⇒ 00:24:04.499 Awaish Kumar: There’s… so is that, like, dashboard?
272 00:24:04.890 ⇒ 00:24:07.599 Awaish Kumar: Question, Demar, do you, like…
273 00:24:07.910 ⇒ 00:24:08.420 Amber Lin: talking about…
274 00:24:08.420 ⇒ 00:24:10.579 Awaish Kumar: Two things here. Numbers don’t match.
275 00:24:10.850 ⇒ 00:24:18.630 Awaish Kumar: And… Dashboard. So, is there any dashboarding work there, or is it just the investigation?
276 00:24:19.700 ⇒ 00:24:20.220 Demilade Agboola: KLTV.
277 00:24:20.980 ⇒ 00:24:24.470 Amber Lin: For Jonah’s task, so for the marketing…
278 00:24:24.470 ⇒ 00:24:25.090 Awaish Kumar: I don’t know.
279 00:24:25.360 ⇒ 00:24:26.560 Amber Lin: Right?
280 00:24:26.560 ⇒ 00:24:29.899 Awaish Kumar: This task requires… this task requires…
281 00:24:30.540 ⇒ 00:24:40.829 Awaish Kumar: data discrepancy investigation, and we need them to send this length message, right? For A to Z… I’m talking about 801, where the demilade says.
282 00:24:41.070 ⇒ 00:24:50.549 Awaish Kumar: Also, the numbers don’t match because maybe all the spend is not making to the last model, right?
283 00:24:50.940 ⇒ 00:24:55.059 Amber Lin: Oh, I thought he sent a PR to fix it, so…
284 00:24:55.060 ⇒ 00:25:06.239 Demilade Agboola: No, so this… so this one was actually because of, all the ad spend. So this was because, some of the logic was just not working well, to be honest. The…
285 00:25:07.140 ⇒ 00:25:15.410 Demilade Agboola: Because in situations where things were breaking even in the first month, the logic to calculate PLTV was not working properly.
286 00:25:16.120 ⇒ 00:25:35.879 Demilade Agboola: So for that, I’ve been able to, fix that, and I’m just testing it, and once I do that, LTV should be fine. But I don’t believe the ad spend integrates, affiliate spend as well, so going forward, after this, like, after this fix, I think the next level will be to integrate affiliate spend.
287 00:25:36.680 ⇒ 00:25:40.520 Demilade Agboola: And then it will be much closer to the final numbers that we all want.
288 00:25:41.560 ⇒ 00:25:48.630 Awaish Kumar: Okay, so for you, Amber, let me summarize. For PLTV, he… Demolari…
289 00:25:48.750 ⇒ 00:25:51.450 Awaish Kumar: Metafix, we are going to see,
290 00:25:51.570 ⇒ 00:26:03.399 Awaish Kumar: Like, have that fixed, but also he’s saying that the… we might be… this dashboard might start looking like having a discrepancy in spent data.
291 00:26:04.020 ⇒ 00:26:08.259 Awaish Kumar: Because the affiliate spread is not making to this…
292 00:26:08.650 ⇒ 00:26:13.820 Awaish Kumar: dashboard as well. And we need to clarify…
293 00:26:13.980 ⇒ 00:26:29.080 Awaish Kumar: Like, the fix is done, like, we can mark it done, maybe start a new ticket, where… which is, like, asking for clarity on spend, like, what, for all the dashboards.
294 00:26:29.160 ⇒ 00:26:47.759 Awaish Kumar: Do we want to include all the ad spend from, online, and offline sources, which are, like, data coming from Northstream, and then the data coming from, MNTNY, the affiliate influences, all these sources?
295 00:26:48.200 ⇒ 00:27:02.100 Awaish Kumar: And we just need their answer on clarifying us, like, if they want to include for all the dashboards, or they want to have any, kind of, like, dashboard, specific requirements, or…
296 00:27:02.260 ⇒ 00:27:08.910 Awaish Kumar: filters, and that’s all. After that, killerity, we can make those changes and
297 00:27:09.670 ⇒ 00:27:11.890 Awaish Kumar: Yeah, and then we moved from there.
298 00:27:13.190 ⇒ 00:27:17.549 Amber Lin: Okay, so… Cherry is on hold, so…
299 00:27:18.370 ⇒ 00:27:24.700 Amber Lin: What are the dashboards currently affected? I think Adam’s dashboard is one of them, and then…
300 00:27:24.930 ⇒ 00:27:35.629 Amber Lin: I guess most of our dashboards are affected. Okay, so I’m gonna close… I guess one question is, is there anything that needs to be edited?
301 00:27:36.260 ⇒ 00:27:37.400 Amber Lin: Another point.
302 00:27:37.900 ⇒ 00:27:43.499 Amber Lin: This is only… Then we need to go build a chart.
303 00:27:43.830 ⇒ 00:27:48.040 Amber Lin: We’d still need to go build a chart using those PLTV values.
304 00:27:49.960 ⇒ 00:27:51.120 Demilade Agboola: Yes.
305 00:27:51.530 ⇒ 00:27:52.469 Amber Lin: Yeah. I agree.
306 00:27:52.470 ⇒ 00:27:58.980 Demilade Agboola: But the data would just be… it would still be the same dashboard, but the data would just be available. The issue was the data was not available.
307 00:27:58.980 ⇒ 00:27:59.840 Amber Lin: Gotcha.
308 00:28:00.430 ⇒ 00:28:02.670 Amber Lin: Chart.
309 00:28:03.110 ⇒ 00:28:08.680 Amber Lin: Oh, okay, and then I’m going to send the message…
310 00:28:09.530 ⇒ 00:28:19.200 Amber Lin: I have one message I’ll send about the QuickBooks, and then I’ll send the dashboard question separately. Okay.
311 00:28:20.450 ⇒ 00:28:21.190 Amber Lin: All right.
312 00:28:21.190 ⇒ 00:28:30.990 Awaish Kumar: So… what I’m saying is that there’s no dashboarding work here on this ticket, because
313 00:28:31.690 ⇒ 00:28:43.710 Awaish Kumar: what Demolata is saying, the dashboarding work is only done, data is not being shown because the model does not have the data, so when… once the data is there, it will start showing up in the dashboard as well.
314 00:28:44.200 ⇒ 00:28:46.059 Amber Lin: Sure, I see. So this is…
315 00:28:46.060 ⇒ 00:28:47.369 Henry Zhao: I’ll just check it when it’s done.
316 00:28:47.820 ⇒ 00:28:59.089 Amber Lin: Yeah, this is blocked. Okay, so it’s just finance, and then… Finance, and this… Investigation. The finance one is…
317 00:28:59.390 ⇒ 00:29:03.370 Amber Lin: I don’t know, it seems pretty big, so we’ll focus on getting that done.
318 00:29:04.560 ⇒ 00:29:07.190 Amber Lin: Okay.
319 00:29:07.590 ⇒ 00:29:09.720 Awaish Kumar: That one…
320 00:29:11.020 ⇒ 00:29:18.190 Amber Lin: It’s a modeling task. Okay, gotta jump to the Tableau conversation, Tracy.
321 00:29:18.640 ⇒ 00:29:19.719 Henry Zhao: Okay, see you guys there.
322 00:29:19.720 ⇒ 00:29:21.659 Amber Lin: Yeah, thank you, thank you guys.