Meeting Title: Demilade Agboola’s Zoom Meeting Date: 2025-06-17 Meeting participants: Demilade Agboola, Annie Yu
WEBVTT
1 00:00:27.620 ⇒ 00:00:29.180 Annie Yu: Hello! Damaty.
2 00:00:31.430 ⇒ 00:00:32.770 Demilade Agboola: Hi! I mean, how are you?
3 00:00:33.130 ⇒ 00:00:34.560 Annie Yu: Hey! How are you?
4 00:00:34.960 ⇒ 00:00:36.620 Demilade Agboola: I’m all right. Hold up!
5 00:00:36.820 ⇒ 00:00:39.349 Demilade Agboola: I see you just woke up to some of the chaos.
6 00:00:41.247 ⇒ 00:00:43.759 Annie Yu: Yeah. Yep.
7 00:00:44.850 ⇒ 00:00:54.270 Annie Yu: Oh, yeah, pinged me. And asking me, he said, we are bringing some interns on board.
8 00:00:56.090 ⇒ 00:00:56.800 Demilade Agboola: Okay.
9 00:00:57.240 ⇒ 00:01:12.126 Annie Yu: And he’s asking me if I like would be up for like being a mentor, which I don’t know. Like I I yeah, I need to know, like what responsibilities and like, how long I’ll last, because I’m not really sure if I have the capacity to commit.
10 00:01:13.300 ⇒ 00:01:17.759 Demilade Agboola: That’s fair. I mean, it’s important to know how much
11 00:01:18.880 ⇒ 00:01:23.459 Demilade Agboola: like room you have for stuff like that. And so you don’t over commit to it.
12 00:01:24.120 ⇒ 00:01:27.019 Annie Yu: Yeah. And I’m like, I, I’m pretty set
13 00:01:27.160 ⇒ 00:01:34.376 Annie Yu: that like, I never wanna be a people manager or things of that sort. I like being. I like being an IC, so.
14 00:01:35.730 ⇒ 00:01:38.819 Demilade Agboola: That’s fair enough, fair enough, at least you know your strength, so
15 00:01:39.000 ⇒ 00:01:46.799 Demilade Agboola: it makes it easy to like push what you don’t want to do versus like just being forced to do stuff that you don’t enjoy doing.
16 00:01:47.260 ⇒ 00:01:51.378 Annie Yu: Yeah, we’ll see. We’ll see. Sounds fun, but we’ll see.
17 00:01:55.320 ⇒ 00:01:59.310 Demilade Agboola: So couple of things.
18 00:02:02.550 ⇒ 00:02:08.829 Demilade Agboola: I just saw that case is asking if you can switch the refine summaries to Cs instead of Pdfs.
19 00:02:10.639 ⇒ 00:02:12.569 Annie Yu: Which one you’re fresh.
20 00:02:12.570 ⇒ 00:02:13.210 Demilade Agboola: Sorry.
21 00:02:14.050 ⇒ 00:02:14.820 Annie Yu: Okay.
22 00:02:16.037 ⇒ 00:02:18.780 Annie Yu: Okay, that should be doable. Right?
23 00:02:19.140 ⇒ 00:02:20.379 Annie Yu: I I’ll just.
24 00:02:20.380 ⇒ 00:02:25.359 Demilade Agboola: I don’t think so, not knowing the current setup on it unless we have to rethink how we’re doing it.
25 00:02:25.600 ⇒ 00:02:30.770 Annie Yu: Oh, so it’s not just like the same way as we. How we subscribe to Pdf.
26 00:02:31.190 ⇒ 00:02:32.579 Demilade Agboola: No, no, it’s not.
27 00:02:33.840 ⇒ 00:02:39.820 Annie Yu: Okay, so should should I, so that the the answer is no right.
28 00:02:45.320 ⇒ 00:02:56.220 Demilade Agboola: I’m not sure how much of the high priorities cause like for me to change the process means. I’ll need to sit down and think of a new process and all of that. And if it’s high priority in terms of like
29 00:02:56.520 ⇒ 00:02:58.120 Demilade Agboola: this is something needed.
30 00:02:58.540 ⇒ 00:03:07.820 Demilade Agboola: Well, we could say that we’ll work on it, but, like we’re working on it, but like there’s no for for now it would still have to be Pdfs.
31 00:03:08.960 ⇒ 00:03:10.130 Annie Yu: Okay. Okay.
32 00:03:12.260 ⇒ 00:03:20.870 Demilade Agboola: Or you could just say no, I don’t know, since it wouldn’t be possible to say no, but we’ll we’ll look at, I say, like right now. No, but we’ll see what we can do about it in future.
33 00:03:21.310 ⇒ 00:03:23.570 Annie Yu: Okay, okay, that’s fair.
34 00:03:30.830 ⇒ 00:03:31.410 Demilade Agboola: Alright.
35 00:03:31.970 ⇒ 00:03:35.290 Demilade Agboola: As for the as for the
36 00:03:37.440 ⇒ 00:03:45.660 Demilade Agboola: the numbers, I think we might have to like, see, we won’t need to be won’t be able to do dynamic filters for total counts.
37 00:03:47.990 ⇒ 00:03:49.510 Annie Yu: Because.
38 00:03:50.010 ⇒ 00:03:52.420 Demilade Agboola: Because if we’re gonna make it dynamic.
39 00:03:53.370 ⇒ 00:03:56.929 Demilade Agboola: we’re gonna end up a session on where every day
40 00:03:57.990 ⇒ 00:04:00.930 Demilade Agboola: we’ll have a count with every other day.
41 00:04:02.120 ⇒ 00:04:03.370 Annie Yu: Yeah, yeah.
42 00:04:03.370 ⇒ 00:04:10.310 Demilade Agboola: For every single product. That’s a very large table. I even tried to run it, and it didn’t run like it timed out
43 00:04:11.930 ⇒ 00:04:17.130 Demilade Agboola: so and obviously for every day, every day that passes that extra day.
44 00:04:18.730 ⇒ 00:04:23.520 Demilade Agboola: for every product gets multiplied by every day in the past.
45 00:04:28.430 ⇒ 00:04:33.220 Demilade Agboola: for every new day that we pass like every new day that we go forward in time.
46 00:04:33.450 ⇒ 00:04:40.880 Demilade Agboola: So for tomorrow’s day, we need to now find the combination from each product with on each day
47 00:04:41.070 ⇒ 00:04:43.480 Demilade Agboola: back to every single point in time
48 00:04:46.080 ⇒ 00:04:52.179 Demilade Agboola: to get my point. So what like if we’re going to do that? We’ll say, Hey! On the 16th of June.
49 00:04:52.570 ⇒ 00:04:52.970 Annie Yu: Hold on!
50 00:04:52.970 ⇒ 00:04:59.370 Demilade Agboola: What is the distinct count of people who have taken who have bought semaglutide
51 00:04:59.850 ⇒ 00:05:03.160 Demilade Agboola: on every single day from 6th of June back into time
52 00:05:04.320 ⇒ 00:05:07.579 Demilade Agboola: right? But then we’ll also do from the 15th of June as well.
53 00:05:07.790 ⇒ 00:05:19.450 Demilade Agboola: and then the 14th of June, so that at the end of day, if someone wants to look at it. Now, what’s the difference? What’s the the distinct count of users from the 8th of May to the 10th of June?
54 00:05:20.000 ⇒ 00:05:28.829 Demilade Agboola: That’s it. That’s an entirely unique combination. That’s what I’m trying to say. So like every single combination that can be accounted for. For, every product must be accounted for.
55 00:05:28.980 ⇒ 00:05:31.770 Demilade Agboola: and then every day that we get a new number.
56 00:05:31.890 ⇒ 00:05:37.669 Demilade Agboola: that calculation has to happen again for every single combination of days, including that new day.
57 00:05:39.190 ⇒ 00:05:40.820 Annie Yu: Yeah, that’s fair,
58 00:05:44.770 ⇒ 00:05:47.860 Demilade Agboola: That’s just one time you made. Yeah.
59 00:05:47.860 ⇒ 00:05:57.720 Annie Yu: But on that note, how how is it that we can have returning customer account like what we have now? Isn’t that also?
60 00:05:58.800 ⇒ 00:06:03.869 Annie Yu: Doesn’t that also mean we might be over counting returning customers.
61 00:06:05.700 ⇒ 00:06:07.300 Demilade Agboola: So.
62 00:06:09.040 ⇒ 00:06:14.840 Annie Yu: Because we do have a returning customers in that table.
63 00:06:15.460 ⇒ 00:06:18.939 Demilade Agboola: But they’re not going to be distinct, though, so potentially we’re not. We’re going to be.
64 00:06:19.440 ⇒ 00:06:22.340 Demilade Agboola: Yes, potentially, we are over counting returning customers as well.
65 00:06:22.470 ⇒ 00:06:29.599 Demilade Agboola: because I mean, since we’re summing up on individual day. So hey, 10 people return today, 20 people return tomorrow.
66 00:06:29.750 ⇒ 00:06:37.810 Demilade Agboola: 15 return to the after. Therefore you have, 45 people returning. Yeah, 5 people returning.
67 00:06:38.110 ⇒ 00:06:38.490 Annie Yu: But in my.
68 00:06:38.490 ⇒ 00:06:40.859 Demilade Agboola: Yeah, that’s what they’re again.
69 00:06:41.260 ⇒ 00:06:42.400 Annie Yu: Customers.
70 00:06:42.420 ⇒ 00:06:44.270 Demilade Agboola: Yeah, exactly.
71 00:06:44.910 ⇒ 00:06:45.340 Annie Yu: Okay.
72 00:06:45.340 ⇒ 00:06:47.570 Demilade Agboola: There’s not a distinct number right now.
73 00:06:48.810 ⇒ 00:06:49.940 Annie Yu: Got it.
74 00:06:52.550 ⇒ 00:06:57.819 Demilade Agboola: So I think for this for this chart. I don’t know if we can just pick the filters to be
75 00:06:57.960 ⇒ 00:07:03.779 Demilade Agboola: like based off the last 10 days, or least, based off the last 20 days, or whatever
76 00:07:04.180 ⇒ 00:07:06.080 Demilade Agboola: like like. The idea is.
77 00:07:06.380 ⇒ 00:07:07.150 Annie Yu: Yeah.
78 00:07:07.330 ⇒ 00:07:09.310 Demilade Agboola: You can’t just pick a dynamic theme.
79 00:07:10.950 ⇒ 00:07:13.640 Demilade Agboola: You have to start from today and go back in time
80 00:07:14.190 ⇒ 00:07:18.809 Demilade Agboola: also last 7 days last 20 days, last 3 months, whatever like, that’s fine.
81 00:07:19.140 ⇒ 00:07:29.770 Demilade Agboola: But if we’re going to start going all the way like doing a diff like the same count across multiple days, that’s when it starts to get really messy, not messy. We just get heavy.
82 00:07:30.690 ⇒ 00:07:36.199 Annie Yu: Yeah, yeah, and for for cutter’s dashboard.
83 00:07:36.330 ⇒ 00:07:43.469 Annie Yu: So I know that we the folded the bottom parts to 30 days.
84 00:07:43.920 ⇒ 00:07:54.129 Annie Yu: Is that, do you happen to know is that also, like the main use case that he’ll he’ll need like the last 30 days.
85 00:07:55.420 ⇒ 00:07:57.070 Demilade Agboola: Believe so.
86 00:07:58.010 ⇒ 00:07:59.460 Annie Yu: Yeah, then, and
87 00:08:00.160 ⇒ 00:08:07.820 Annie Yu: maybe we can. I I can always like add a note on that column saying, this is like the last 30 day.
88 00:08:09.790 ⇒ 00:08:10.790 Annie Yu: Count.
89 00:08:13.540 ⇒ 00:08:19.720 Annie Yu: Yeah. But I’m also wondering. And this is might not. Only this is
90 00:08:20.000 ⇒ 00:08:33.799 Annie Yu: like, it’s probably a broader question. Is there any way, or does it make sense if we ever have something similar to order. Summary, but then only one.
91 00:08:34.940 ⇒ 00:08:39.300 Annie Yu: you know, like only one row per order, order, number.
92 00:08:42.037 ⇒ 00:08:44.709 Demilade Agboola: I’m not sure I understand what you’re trying to say.
93 00:08:44.710 ⇒ 00:08:52.400 Annie Yu: Because right now, in order summary, we have multiple rows for each order number right? Because there are multiple
94 00:08:52.560 ⇒ 00:08:53.370 Annie Yu: delivery.
95 00:08:53.370 ⇒ 00:08:54.110 Demilade Agboola: That’s.
96 00:08:54.110 ⇒ 00:09:04.739 Annie Yu: And all that. Yes, we do have like de duplicate sometimes, and I’m wondering if it will make sense to have something similar to that model in terms of the
97 00:09:05.010 ⇒ 00:09:07.350 Annie Yu: yeah, like the like.
98 00:09:07.730 ⇒ 00:09:09.270 Annie Yu: You know what I mean. I.
99 00:09:09.270 ⇒ 00:09:11.320 Demilade Agboola: Yeah, yeah, I get what you’re I get, what you’re.
100 00:09:11.450 ⇒ 00:09:18.939 Annie Yu: Yeah, I feel like that kind of model will work well
101 00:09:19.800 ⇒ 00:09:31.849 Annie Yu: in these use cases when we have to count order, count, or a customer account.
102 00:09:33.100 ⇒ 00:09:37.029 Demilade Agboola: Okay, that’s fair. I think that might be what we will do.
103 00:09:40.870 ⇒ 00:09:47.529 Demilade Agboola: that’s fair. So we’ll have like a so kind of like, how we have facts and products combination for
104 00:09:48.090 ⇒ 00:09:55.200 Demilade Agboola: for the josh. We could have something like that. For this as well.
105 00:09:55.850 ⇒ 00:09:59.060 Annie Yu: Yeah. And we just don’t need that.
106 00:09:59.060 ⇒ 00:10:00.860 Demilade Agboola: Like, yeah, all the information.
107 00:10:00.860 ⇒ 00:10:02.900 Annie Yu: Status, all that. Yeah.
108 00:10:02.900 ⇒ 00:10:11.319 Demilade Agboola: Yeah. Yeah. Or even if we do, we’ll ensure that everything is just remains on that granularity. So, for instance, is deliver true false.
109 00:10:11.961 ⇒ 00:10:15.479 Demilade Agboola: So like it just takes the latest status from
110 00:10:15.710 ⇒ 00:10:20.179 Demilade Agboola: doing shipment and gives us if it’s been delivered, if it’s been delivered. Yes, if not, no.
111 00:10:20.410 ⇒ 00:10:24.950 Demilade Agboola: Things like that like we don’t. We don’t need to like find it out. We just keep it on that same
112 00:10:25.180 ⇒ 00:10:26.190 Demilade Agboola: blind.
113 00:10:27.080 ⇒ 00:10:32.449 Annie Yu: Yeah. Yeah. So, so, one order number will only have one row. Right?
114 00:10:32.450 ⇒ 00:10:33.550 Demilade Agboola: Exactly. Yeah.
115 00:10:33.550 ⇒ 00:10:35.709 Annie Yu: Yeah, I feel like that that will work.
116 00:10:36.590 ⇒ 00:10:37.290 Demilade Agboola: Okay.
117 00:10:37.290 ⇒ 00:10:37.670 Demilade Agboola: All right.
118 00:10:37.670 ⇒ 00:10:45.820 Annie Yu: And so one more question is about the fact transactions. So fact transaction doesn’t work like that, does it?
119 00:10:46.660 ⇒ 00:10:47.869 Demilade Agboola: Like what sorry.
120 00:10:47.870 ⇒ 00:10:52.789 Annie Yu: Like 1 1 one order number per row.
121 00:10:53.360 ⇒ 00:10:59.650 Demilade Agboola: It is, it should be one other number which is kind of why we noticed an error today. And we’re trying to fix, or we just try to fix it now
122 00:10:59.760 ⇒ 00:11:02.139 Demilade Agboola: where we had multiple for one
123 00:11:02.798 ⇒ 00:11:13.949 Demilade Agboola: apparently the products we’re having issues where they’re duplicates of the product in the products mapping sheet. So when we’re joining, based on variant Id to find out because there are multiple cogs.
124 00:11:14.090 ⇒ 00:11:15.120 Demilade Agboola: image.
125 00:11:15.420 ⇒ 00:11:16.300 Annie Yu: Yeah.
126 00:11:16.300 ⇒ 00:11:21.539 Demilade Agboola: Yeah, that’s just so. But ideally, no, we don’t. We don’t want to have duplicate order numbers in there.
127 00:11:22.080 ⇒ 00:11:31.199 Annie Yu: Yeah, that makes sense. Okay? And I’ll I’ll let you decide what to do as of now, because I guess this one is urgent. So
128 00:11:31.700 ⇒ 00:11:39.999 Annie Yu: let me know which one works better if we wanna just do like the 30 day as like, for now that works too.
129 00:11:40.440 ⇒ 00:11:47.300 Demilade Agboola: Okay. But yeah, try. Try to say, if I if I build out the facts transactions with the products
130 00:11:47.410 ⇒ 00:11:49.160 Demilade Agboola: that’s fine for you to do it.
131 00:11:49.780 ⇒ 00:11:55.399 Annie Yu: Yeah, but then we have to make sure we have all the fields that we want to show in that dashboard.
132 00:11:56.660 ⇒ 00:11:59.249 Demilade Agboola: What field, what fields do we want to show in that dashboard.
133 00:11:59.976 ⇒ 00:12:01.963 Annie Yu: The other ones like
134 00:12:07.300 ⇒ 00:12:12.430 Annie Yu: like aspen order revenue cogs.
135 00:12:13.680 ⇒ 00:12:16.290 Demilade Agboola: And there’s that.
136 00:12:16.690 ⇒ 00:12:20.619 Annie Yu: Yeah, cause that’s the only way they can sit in the same table.
137 00:12:21.510 ⇒ 00:12:25.340 Demilade Agboola: Yeah, I mean, we could do other revenue being transactions.
138 00:12:25.760 ⇒ 00:12:29.860 Demilade Agboola: I’m not sure about ad spend ad spend comes from not being
139 00:12:30.380 ⇒ 00:12:33.009 Demilade Agboola: so. That’s an entirely different like.
140 00:12:33.250 ⇒ 00:12:35.700 Annie Yu: Yeah, and it’ll take more time, too.
141 00:12:35.700 ⇒ 00:12:36.570 Demilade Agboola: Yeah.
142 00:12:41.690 ⇒ 00:12:45.800 Demilade Agboola: alright. So let me just push this fix this quick one of just like
143 00:12:46.671 ⇒ 00:12:51.199 Demilade Agboola: we can just do from every day we can count based off the previous days.
144 00:12:51.988 ⇒ 00:12:55.119 Demilade Agboola: And then we’ll see. We’ll take it from there.
145 00:12:55.120 ⇒ 00:12:58.559 Annie Yu: So that’s the one that you you share yesterday, right? The same one.
146 00:12:58.560 ⇒ 00:12:59.750 Demilade Agboola: Yeah, yeah.
147 00:13:00.480 ⇒ 00:13:03.990 Annie Yu: Okay, okay? So you’ll add that to product sales summary.
148 00:13:10.440 ⇒ 00:13:20.450 Demilade Agboola: I’m trying to think, unless no, it it can’t be added to product sales, summary planets.
149 00:13:21.690 ⇒ 00:13:22.470 Annie Yu: Hmm.
150 00:13:22.710 ⇒ 00:13:25.392 Demilade Agboola: Because unless we’re gonna go by.
151 00:13:26.340 ⇒ 00:13:28.150 Annie Yu: Yeah, no, probably not.
152 00:13:28.150 ⇒ 00:13:31.200 Demilade Agboola: Yeah, no, it has to be its own unique model.
153 00:13:31.630 ⇒ 00:13:41.770 Demilade Agboola: because if you add it to product sales summary, it would either either we’re gonna find it out across the different like granularity. So the different membership plans, for instance, or
154 00:13:41.870 ⇒ 00:13:51.070 Demilade Agboola: what potentially could happen is if we then have to group it by the different membership plans. It becomes harder for each day it becomes when you know you would have to
155 00:13:51.430 ⇒ 00:13:56.259 Demilade Agboola: again, and we’ll have the same issue that we run into it has to be some unique model.
156 00:13:57.274 ⇒ 00:14:02.839 Annie Yu: okay, okay, that makes sense. So that that means I might still have to have a separate
157 00:14:03.450 ⇒ 00:14:07.980 Annie Yu: a small table to show that in the dashboard.
158 00:14:10.050 ⇒ 00:14:15.079 Annie Yu: Okay, yeah, th, that’s fine. That’s fine. I think that that’s the best solution we have. Now.
159 00:14:15.450 ⇒ 00:14:19.230 Demilade Agboola: Yeah, but I mean, I don’t. If we know the revenue
160 00:14:19.340 ⇒ 00:14:22.820 Demilade Agboola: attributed to you know whatever product.
161 00:14:23.300 ⇒ 00:14:27.220 Demilade Agboola: and we know the count, can’t we then, like, find a way to
162 00:14:27.360 ⇒ 00:14:29.940 Demilade Agboola: you. Get like, kind of how we’re doing this new product
163 00:14:30.160 ⇒ 00:14:35.650 Demilade Agboola: accounts that we’re using right now where we have the new product 1st time product users count.
164 00:14:35.950 ⇒ 00:14:36.440 Annie Yu: Yeah.
165 00:14:36.440 ⇒ 00:14:40.059 Demilade Agboola: How we do want to do something similar to what we’re doing with that, though.
166 00:14:40.710 ⇒ 00:14:50.929 Demilade Agboola: So we, the revenue is still fine. It’s just what we just want to be giving them the accurate number of these accounts. So when they’re doing and nav, it’s, it’s it’s fine.
167 00:14:51.890 ⇒ 00:14:57.400 Annie Yu: Okay. Okay. Yeah. Well, I’ll let you. I’ll I’ll let you go through it, and then I’ll
168 00:14:58.150 ⇒ 00:15:00.224 Annie Yu: I’ll I’ll review it once.
169 00:15:00.740 ⇒ 00:15:01.969 Annie Yu: You pay me.
170 00:15:02.640 ⇒ 00:15:04.610 Demilade Agboola: Alright. Sounds good. I’ll start working now.
171 00:15:04.950 ⇒ 00:15:06.679 Annie Yu: Yeah. Thanks. Somali.
172 00:15:06.680 ⇒ 00:15:08.020 Demilade Agboola: Alright! Thanks! Have a good day.
173 00:15:08.190 ⇒ 00:15:09.370 Annie Yu: Have a good one. Bye.