Meeting Title: Uttam Kumaran Date: 2025-02-05 Meeting participants: Uttam Kumaran, Robert Tseng, Awaish Kumar
WEBVTT
1 00:00:48.380 ⇒ 00:00:49.140 Awaish Kumar: Hello!
2 00:00:50.800 ⇒ 00:00:51.760 Uttam Kumaran: I wish.
3 00:00:52.900 ⇒ 00:00:54.000 Awaish Kumar: I, yeah.
4 00:00:55.684 ⇒ 00:01:01.959 Uttam Kumaran: Yeah, let me send you the thing to often. So I run this
5 00:01:04.190 ⇒ 00:01:07.419 Uttam Kumaran: I run this G cloud auth command
6 00:01:17.990 ⇒ 00:01:20.680 Awaish Kumar: Okay. By the way, I was in the
7 00:01:21.030 ⇒ 00:01:27.620 Awaish Kumar: who was running, trying to run the carry and using the Ui, and
8 00:01:28.420 ⇒ 00:01:31.609 Awaish Kumar: it just seems like this email doesn’t have the.
9 00:01:33.170 ⇒ 00:01:38.539 Uttam Kumaran: Yeah, you need to use robert@tryeden.com. It’s in one password.
10 00:01:40.040 ⇒ 00:01:44.029 Awaish Kumar: Yeah, I I use that I’m already in. I’m using that email.
11 00:01:44.640 ⇒ 00:01:45.000 Uttam Kumaran: Wow!
12 00:01:45.000 ⇒ 00:01:48.459 Awaish Kumar: But when I’m trying to run this full query, I get this error.
13 00:01:49.910 ⇒ 00:01:51.390 Awaish Kumar: I’m not sure what.
14 00:01:51.580 ⇒ 00:01:53.730 Uttam Kumaran: Oh, yeah, yeah. Here, you need to run this.
15 00:01:54.560 ⇒ 00:02:01.150 Uttam Kumaran: have you? Ins? Yeah, you need to run did you? Did you install like G. Cloud at all in your laptop.
16 00:02:03.190 ⇒ 00:02:04.209 Awaish Kumar: Oh no!
17 00:02:04.340 ⇒ 00:02:06.410 Uttam Kumaran: Okay, here, follow these.
18 00:02:07.310 ⇒ 00:02:17.519 Awaish Kumar: Steps just run the follow like the carry from using the Dbt compile in the cloud.
19 00:02:17.780 ⇒ 00:02:22.709 Uttam Kumaran: Yeah, I don’t know you’re it’s you’re you’re missing. Just one
20 00:02:23.020 ⇒ 00:02:26.330 Uttam Kumaran: thing. So follow these steps really quickly.
21 00:03:46.973 ⇒ 00:03:52.259 Awaish Kumar: But can’t we run that carry in the Ui.
22 00:03:55.190 ⇒ 00:03:59.380 Awaish Kumar: basically. I wanted to like debug it.
23 00:03:59.500 ⇒ 00:04:03.549 Awaish Kumar: And then the way do is to like, break
24 00:04:04.170 ⇒ 00:04:09.189 Awaish Kumar: the query and see what’s on the in the intermediate steps right.
25 00:04:09.520 ⇒ 00:04:14.210 Uttam Kumaran: Yeah, you can. But you can run like you’re not able to run dbt on locally.
26 00:04:15.440 ⇒ 00:04:20.719 Awaish Kumar: Like when we run Dvt commanding, it will create a model. Finally, right? A final.
27 00:04:20.720 ⇒ 00:04:26.589 Uttam Kumaran: But you can run staging like. Use. The staging profile, the Cicd profile.
28 00:04:30.460 ⇒ 00:04:36.430 Awaish Kumar: Okay, and it will still create, like in the end, final table.
29 00:04:36.940 ⇒ 00:04:39.330 Uttam Kumaran: Yeah, or you can run compile to get the.
30 00:04:40.910 ⇒ 00:04:42.749 Uttam Kumaran: you know, to get whatever you need.
31 00:04:43.730 ⇒ 00:04:45.689 Awaish Kumar: Yeah, I. I have the queries.
32 00:04:45.880 ⇒ 00:04:46.520 Uttam Kumaran: Yeah.
33 00:04:48.310 ⇒ 00:04:54.100 Awaish Kumar: I I want to run like don’t want to run a full query. I want to see, for example.
34 00:04:55.004 ⇒ 00:05:01.169 Awaish Kumar: what is what is the data coming in in the, for example.
35 00:05:01.420 ⇒ 00:05:03.460 Awaish Kumar: Wow, you see, see.
36 00:05:05.430 ⇒ 00:05:06.399 Uttam Kumaran: Yeah, but I guess like, why?
37 00:05:06.400 ⇒ 00:05:07.710 Awaish Kumar: In these transactions.
38 00:05:07.710 ⇒ 00:05:11.350 Uttam Kumaran: Not able to run that in bigquery right now.
39 00:05:12.810 ⇒ 00:05:17.600 Awaish Kumar: Yeah, that’s what I’m saying when I’m trying to run in the victory. I’m getting this error.
40 00:05:18.280 ⇒ 00:05:21.940 Uttam Kumaran: Can you? Can you just show? Can you show me your screen cause I don’t
41 00:05:22.040 ⇒ 00:05:25.169 Uttam Kumaran: like? I don’t know why you shouldn’t be getting that error in the ui.
42 00:05:26.630 ⇒ 00:05:29.030 Awaish Kumar: Let me just share.
43 00:05:29.710 ⇒ 00:05:32.900 Uttam Kumaran: You’re gonna get that error in the cli, but you shouldn’t get in the Ui.
44 00:05:36.930 ⇒ 00:05:38.830 Awaish Kumar: Why is this one.
45 00:05:39.040 ⇒ 00:05:39.560 Uttam Kumaran: Yes.
46 00:05:39.560 ⇒ 00:05:43.600 Awaish Kumar: So if we, for example, I was trying.
47 00:05:43.600 ⇒ 00:05:46.380 Uttam Kumaran: But if you click on the top right, what you.
48 00:05:46.380 ⇒ 00:05:51.499 Awaish Kumar: I was trying to see this. Now this is the total spam coming in from
49 00:05:52.040 ⇒ 00:05:54.519 Awaish Kumar: campaign is spend spend free right.
50 00:05:54.520 ⇒ 00:05:55.230 Uttam Kumaran: Yes.
51 00:05:56.770 ⇒ 00:06:01.159 Awaish Kumar: And when I go in here, and this is a full carry, and
52 00:06:01.840 ⇒ 00:06:05.939 Uttam Kumaran: But then can you click on the top right, just confirm which user they’re using.
53 00:06:07.200 ⇒ 00:06:08.410 Awaish Kumar: This one?
54 00:06:09.560 ⇒ 00:06:10.779 Awaish Kumar: Yeah, can you click on that.
55 00:06:12.570 ⇒ 00:06:16.460 Uttam Kumaran: Can you try? Can you try using a different one?
56 00:06:21.060 ⇒ 00:06:22.030 Awaish Kumar: Can I?
57 00:06:22.960 ⇒ 00:06:24.350 Awaish Kumar: It was a.
58 00:06:29.000 ⇒ 00:06:34.299 Uttam Kumaran: If you type in Robert Robert, I try Eden.
59 00:06:34.300 ⇒ 00:06:34.880 Awaish Kumar: Will look like.
60 00:06:34.880 ⇒ 00:06:36.360 Uttam Kumaran: The 4th one.
61 00:06:37.280 ⇒ 00:06:43.359 Uttam Kumaran: this Google one. Yeah. If you use this one and log in with this, you’ll have bigquery access.
62 00:06:45.690 ⇒ 00:06:46.380 Awaish Kumar: Okay.
63 00:07:48.160 ⇒ 00:07:49.170 Awaish Kumar: no.
64 00:08:02.760 ⇒ 00:08:05.670 Awaish Kumar: Want to do so, then
65 00:08:11.920 ⇒ 00:08:14.010 Awaish Kumar: very useful.
66 00:08:34.630 ⇒ 00:08:38.539 Awaish Kumar: There’s any other way to get around this.
67 00:08:43.549 ⇒ 00:08:46.950 Uttam Kumaran: You don’t. You can’t use a passkey.
68 00:08:50.780 ⇒ 00:08:53.209 Uttam Kumaran: You can’t use your the pass key doesn’t work.
69 00:09:03.690 ⇒ 00:09:07.099 Uttam Kumaran: yeah, so just have it. Have it. Try. Have a login with like your
70 00:09:07.300 ⇒ 00:09:09.380 Uttam Kumaran: your chrome passkey does that work.
71 00:09:10.230 ⇒ 00:09:15.000 Uttam Kumaran: Maybe I don’t know. I don’t know how you’re I don’t know what, how the how windows pass. Key works.
72 00:09:19.300 ⇒ 00:09:20.513 Awaish Kumar: It won’t.
73 00:09:22.390 ⇒ 00:09:24.630 Uttam Kumaran: Cause. The pass key is saved in one password.
74 00:09:33.640 ⇒ 00:09:35.030 Awaish Kumar: Yes, I do.
75 00:09:35.950 ⇒ 00:09:39.009 Awaish Kumar: It’s not taking automatically from one password.
76 00:09:40.270 ⇒ 00:09:41.530 Uttam Kumaran: Oh, it’s not okay.
77 00:09:43.080 ⇒ 00:09:44.880 Awaish Kumar: You try it here? Maybe.
78 00:10:17.270 ⇒ 00:10:21.619 Uttam Kumaran: If it’s not working, then I can
79 00:10:23.750 ⇒ 00:10:25.760 Uttam Kumaran: try to see what’s going on.
80 00:10:29.756 ⇒ 00:10:32.370 Awaish Kumar: These are the only options I can use
81 00:10:32.710 ⇒ 00:10:36.640 Awaish Kumar: using the phone or computer. Maybe you have.
82 00:10:41.940 ⇒ 00:10:44.090 Uttam Kumaran: Okay, wait. Give me one sec. Let me try this.
83 00:10:47.440 ⇒ 00:10:49.149 Awaish Kumar: Do you have this account open.
84 00:10:55.090 ⇒ 00:10:56.140 Uttam Kumaran: Yeah, one, second.
85 00:11:00.590 ⇒ 00:11:01.840 Awaish Kumar: Make this one, then.
86 00:11:20.200 ⇒ 00:11:21.620 Uttam Kumaran: Okay. I just clicked. Yes.
87 00:15:07.640 ⇒ 00:15:08.499 Awaish Kumar: Something new.
88 00:15:12.280 ⇒ 00:15:13.530 Uttam Kumaran: Oh, it’s not working.
89 00:15:14.670 ⇒ 00:15:16.549 Awaish Kumar: It’s just loading. I don’t know.
90 00:15:20.966 ⇒ 00:15:22.120 Uttam Kumaran: Try refreshing.
91 00:15:41.710 ⇒ 00:15:43.220 Uttam Kumaran: You should be good. Yeah.
92 00:16:12.580 ⇒ 00:16:13.869 Awaish Kumar: So it’s working.
93 00:23:46.950 ⇒ 00:23:49.499 Awaish Kumar: Okay, okay, are you? Are you? There?
94 00:23:50.950 ⇒ 00:23:51.650 Uttam Kumaran: Yes, I’m here.
95 00:23:52.820 ⇒ 00:23:56.830 Awaish Kumar: Yeah, it seems like, Hmm, customer.
96 00:24:01.040 ⇒ 00:24:03.460 Uttam Kumaran: Yeah, I just don’t know what like.
97 00:24:03.460 ⇒ 00:24:07.200 Awaish Kumar: Some dates are like data on some days are missing.
98 00:24:08.310 ⇒ 00:24:14.810 Awaish Kumar: So like when we see from customer spend for campaign, expand table
99 00:24:15.720 ⇒ 00:24:18.400 Awaish Kumar: for the 1st month of 2024
100 00:24:18.730 ⇒ 00:24:21.629 Awaish Kumar: for all the days there is some spent.
101 00:24:24.850 ⇒ 00:24:25.260 Uttam Kumaran: Okay.
102 00:24:25.260 ⇒ 00:24:25.860 Awaish Kumar: Right.
103 00:24:26.010 ⇒ 00:24:26.460 Uttam Kumaran: Yeah.
104 00:24:26.460 ⇒ 00:24:32.769 Awaish Kumar: But when we go into this and I, I just try to take this table daily product metrics.
105 00:24:33.400 ⇒ 00:24:37.199 Awaish Kumar: And when I try to carry this table like this city?
106 00:24:37.871 ⇒ 00:24:44.140 Awaish Kumar: We are not getting the data for all the days like with the spend is like
107 00:24:44.510 ⇒ 00:24:49.120 Awaish Kumar: after the joint we are missing out on some spans in the total span.
108 00:24:49.250 ⇒ 00:24:51.089 Uttam Kumaran: 1st of January is not.
109 00:24:53.030 ⇒ 00:24:54.530 Uttam Kumaran: But what do you think is happening.
110 00:24:55.500 ⇒ 00:25:04.870 Awaish Kumar: Gross right dance what I’m looking. I think it’s
111 00:25:05.130 ⇒ 00:25:08.699 Awaish Kumar: there is some issue with the dates, or
112 00:25:11.920 ⇒ 00:25:16.770 Awaish Kumar: like, let’s let’s comment out something here.
113 00:25:18.250 ⇒ 00:25:18.950 Awaish Kumar: Great
114 00:25:37.670 ⇒ 00:25:38.440 Awaish Kumar: M.
115 00:27:03.215 ⇒ 00:27:07.009 Awaish Kumar: Still we do have.
116 00:27:30.430 ⇒ 00:27:33.769 Awaish Kumar: Oh, so what’s happening could be.
117 00:27:34.640 ⇒ 00:27:38.170 Uttam Kumaran: So to give you a sense of like what the logic is is basically
118 00:27:38.630 ⇒ 00:27:42.791 Uttam Kumaran: we have, can’t we have orders that we can add to
119 00:27:45.660 ⇒ 00:27:47.580 Uttam Kumaran: We have orders that
120 00:27:50.900 ⇒ 00:28:10.790 Uttam Kumaran: We have orders that do have a campaign associated with it, meaning we can attribute them to a marketing campaign. However, we also have a bunch of marketing spend that we can’t attribute to an order. So what I’m doing is I’m finding out which products I can attribute, spend to for all the other ones. I’m trying to just distribute it equally across
121 00:28:11.440 ⇒ 00:28:18.270 Uttam Kumaran: all of the products in a given day, based on the proportion of sales for that day.
122 00:28:20.010 ⇒ 00:28:20.420 Awaish Kumar: Okay.
123 00:28:31.610 ⇒ 00:28:42.140 Awaish Kumar: here we are basically missing the data on, like, just join with customer
124 00:28:43.396 ⇒ 00:28:47.589 Awaish Kumar: on this product name. This, there is the issue.
125 00:28:52.570 ⇒ 00:28:56.440 Uttam Kumaran: So you’re saying we’re missing. Oh, so you’re saying there’s there’s product names.
126 00:28:57.150 ⇒ 00:28:57.990 Awaish Kumar: Yeah.
127 00:28:58.170 ⇒ 00:28:59.690 Uttam Kumaran: That aren’t being joined.
128 00:29:03.700 ⇒ 00:29:12.700 Uttam Kumaran: So let me look to see which. If any of the campaign spend pre
129 00:29:14.293 ⇒ 00:29:17.359 Uttam Kumaran: standardized product names are uncategorized.
130 00:29:45.630 ⇒ 00:29:48.289 Uttam Kumaran: See? But there’s nothing here that’s uncategorized.
131 00:29:48.710 ⇒ 00:29:51.589 Uttam Kumaran: So then I guess I should see whether.
132 00:29:55.970 ⇒ 00:30:00.060 Uttam Kumaran: Or should it be on date and product name otherwise just date?
133 00:30:01.350 ⇒ 00:30:06.100 Uttam Kumaran: Maybe it should be on it should be on date, and proc names or just pro or just date
134 00:30:09.200 ⇒ 00:30:13.839 Uttam Kumaran: cause. Potentially, there may be days where that product wasn’t sold, but we spend ads on it.
135 00:30:14.440 ⇒ 00:30:15.650 Awaish Kumar: Yeah, yeah.
136 00:30:18.580 ⇒ 00:30:19.360 Uttam Kumaran: Right.
137 00:30:20.710 ⇒ 00:30:21.720 Awaish Kumar: Yes.
138 00:30:25.820 ⇒ 00:30:31.610 Awaish Kumar: because this is a combination of clear product, and seems like on the
139 00:30:32.250 ⇒ 00:30:35.460 Awaish Kumar: on that specific day. Some products
140 00:30:37.600 ⇒ 00:30:42.039 Awaish Kumar: don’t have a value, and that’s why they it. It becomes now.
141 00:30:54.060 ⇒ 00:30:57.349 Uttam Kumaran: Okay, I just made the change. Let me see if that does anything.
142 00:31:02.970 ⇒ 00:31:06.500 Uttam Kumaran: I think it gets us a little bit closer, maybe.
143 00:32:58.650 ⇒ 00:33:00.914 Uttam Kumaran: No, that didn’t work.
144 00:33:03.710 ⇒ 00:33:06.460 Uttam Kumaran: Let me think about it a little bit more.
145 00:33:21.650 ⇒ 00:33:25.109 Awaish Kumar: They have the same product name, standardized product, name.
146 00:33:28.650 ⇒ 00:33:32.550 Uttam Kumaran: Yeah, maybe one thing you can check is that all the standardized product names
147 00:33:33.260 ⇒ 00:33:38.249 Uttam Kumaran: are the same like they’re they’re like, basically, the list is the same, although
148 00:33:38.710 ⇒ 00:33:40.760 Uttam Kumaran: don’t think that should be the problem.
149 00:33:41.040 ⇒ 00:33:44.400 Uttam Kumaran: Basically, it’s maybe helpful to isolate. One day.
150 00:36:48.760 ⇒ 00:36:49.930 Robert Tseng: Hey, guys.
151 00:36:49.930 ⇒ 00:36:50.730 Uttam Kumaran: Hey!
152 00:36:54.230 ⇒ 00:36:57.859 Robert Tseng: The new model. Don’t look right, Bro, it’s like
153 00:36:57.990 ⇒ 00:37:04.780 Robert Tseng: I don’t know what happened to the ad spend, but it’s like showing 3 50 million in January. We’re like.
154 00:37:04.780 ⇒ 00:37:05.790 Uttam Kumaran: Just change.
155 00:37:06.240 ⇒ 00:37:07.100 Robert Tseng: Yeah, in the most.
156 00:37:07.100 ⇒ 00:37:07.910 Uttam Kumaran: Oh, okay.
157 00:37:08.040 ⇒ 00:37:11.879 Uttam Kumaran: yeah, it’s it’s probably I think it’s just me. I’m I’m just. We’re trying to clear up like
158 00:37:12.630 ⇒ 00:37:17.180 Uttam Kumaran: a few days of missing spend. But I can just revert this.
159 00:37:20.170 ⇒ 00:37:28.300 Robert Tseng: Okay, well, I mean, look, I’m fine with you guys pushing changes. But like every time you do it, look, I have to manually change your feel. I feel like I’m just like.
160 00:37:28.540 ⇒ 00:37:31.260 Uttam Kumaran: No, I’ll I’m gonna stop. I’ll I’m gonna stop. I’ll stop.
161 00:37:31.610 ⇒ 00:37:36.239 Uttam Kumaran: I think, where we got to was good. I think oasis basically diagnosing the last few.
162 00:37:36.550 ⇒ 00:37:43.160 Uttam Kumaran: There’s just some days where we spent on ads. But there were no products that got sold for that day.
163 00:37:43.330 ⇒ 00:37:47.350 Uttam Kumaran: And so when we join on day and product name to do the distribution.
164 00:37:47.540 ⇒ 00:37:48.689 Uttam Kumaran: It’s not working.
165 00:37:49.810 ⇒ 00:37:52.540 Robert Tseng: Okay, so that wouldn’t work for same day. That’s fine.
166 00:37:54.450 ⇒ 00:37:57.200 Robert Tseng: I mean, what if we just expanded the window to like
167 00:37:57.350 ⇒ 00:38:01.369 Robert Tseng: rolling 2 days or something. Maybe there was just like a bit of a delay or something.
168 00:38:04.160 ⇒ 00:38:06.525 Uttam Kumaran: We can do that, I think.
169 00:38:07.680 ⇒ 00:38:12.194 Uttam Kumaran: I just don’t think it like, yeah, I think we’ll have to do something to capture that
170 00:38:13.480 ⇒ 00:38:17.010 Uttam Kumaran: I’m not 100% sure what that is. Yeah.
171 00:38:17.010 ⇒ 00:38:24.540 Robert Tseng: Okay. But I thought we were on the same page that, like the aggregate ad spend, wasn’t gonna be impacted like we. If we it should.
172 00:38:24.540 ⇒ 00:38:28.739 Uttam Kumaran: No look at it now we’re fine. Look at it now we’re fine. I’m I’m just like
173 00:38:29.820 ⇒ 00:38:32.999 Uttam Kumaran: I just, I’ll stop making changes to staging. I’m just gonna stop.
174 00:38:33.440 ⇒ 00:38:34.430 Uttam Kumaran: Sorry.
175 00:38:35.580 ⇒ 00:38:36.024 Robert Tseng: Okay.
176 00:38:36.470 ⇒ 00:38:40.949 Uttam Kumaran: Okay. I’m done. I’m done anything I do. I’m gonna run in bigquery.
177 00:38:41.415 ⇒ 00:38:44.340 Uttam Kumaran: I’m not touching this gonna push. The latest
178 00:38:47.290 ⇒ 00:38:50.999 Uttam Kumaran: sorry. It’s I know it’s frustrating. That’s that’s my bad.
179 00:38:51.960 ⇒ 00:38:57.230 Uttam Kumaran: But hopefully new customer revenue returning customer, revenue order account, new order account.
180 00:39:02.030 ⇒ 00:39:03.000 Uttam Kumaran: Yeah.
181 00:39:06.660 ⇒ 00:39:11.410 Robert Tseng: Okay, so we’re back to 1.2 million. So we’re off by 300 K on the ad. Spend.
182 00:39:11.850 ⇒ 00:39:18.459 Uttam Kumaran: Yeah, we isolated where the what the issue is like oasis just doing it right now.
183 00:39:19.990 ⇒ 00:39:20.790 Robert Tseng: Okay?
184 00:39:28.850 ⇒ 00:39:37.489 Robert Tseng: Well, I guess while he’s doing that, then I want to get to the bottom of this cacking. So I basically created a staging board. I added you in a waste to it, and I’m like.
185 00:39:37.750 ⇒ 00:39:43.280 Robert Tseng: it’s this. It’s the one table that everybody uses been using the Qa. I just stripped away everything else.
186 00:39:43.280 ⇒ 00:39:43.800 Uttam Kumaran: Yeah.
187 00:39:44.990 ⇒ 00:39:56.079 Robert Tseng: yeah. So like all the new, the new stuff like new order calculations. Okay, I get it. I think I think we’re cool there. It’s the on the total order stuff.
188 00:39:56.540 ⇒ 00:39:59.749 Robert Tseng: Okay, you changed the model. Everything broke. Okay, whatever. I’ll just
189 00:40:01.440 ⇒ 00:40:05.790 Robert Tseng: okay. I’m not gonna create another visual. I just we can talk through it.
190 00:40:09.280 ⇒ 00:40:14.309 Robert Tseng: Total revenue over aspen. Okay, fine. Ltv, Ltv calculation.
191 00:40:14.960 ⇒ 00:40:16.060 Robert Tseng: How does that?
192 00:40:16.270 ⇒ 00:40:17.430 Robert Tseng: Yeah, I’ll take.
193 00:40:18.710 ⇒ 00:40:28.249 Robert Tseng: Ltv is just total revenue for the customer within that product. So that’s a customer product kind of metric that doesn’t.
194 00:40:28.550 ⇒ 00:40:30.640 Robert Tseng: That’s not impacted by the orders.
195 00:40:33.150 ⇒ 00:40:35.169 Robert Tseng: At least, that’s what I think.
196 00:40:35.460 ⇒ 00:40:37.990 Robert Tseng: Yep, and then.
197 00:40:39.630 ⇒ 00:40:46.380 Robert Tseng: yes, row as is fine, Aov will be fine blended. Aov is just total revenue over total orders
198 00:40:46.720 ⇒ 00:41:00.039 Robert Tseng: all of a sudden. Yeah, it’s really just cac. So we have, we have. And then Zack’s that she has this blended cac thing and this blended cac thing like what the heck is that blended Cac
199 00:41:01.390 ⇒ 00:41:10.750 Robert Tseng: blended cac is just average of a field called Cac. So yeah, whatever right?
200 00:41:10.750 ⇒ 00:41:12.639 Uttam Kumaran: Yeah, but that was not. I don’t think that’s right.
201 00:41:13.940 ⇒ 00:41:17.089 Uttam Kumaran: I gave him Cac by day before, and he just averaged it.
202 00:41:18.920 ⇒ 00:41:20.730 Robert Tseng: Okay, yeah, that doesn’t make sense.
203 00:41:21.200 ⇒ 00:41:21.840 Uttam Kumaran: Yeah.
204 00:41:26.900 ⇒ 00:41:35.880 Robert Tseng: Okay, then forget what he did. We need to think about our a different way to do the blended cap and calc makes sense. It’s just ad spend over new customers
205 00:41:36.000 ⇒ 00:41:42.239 Robert Tseng: blended. Cac would not just be spend over all customers, because that wouldn’t make any sense.
206 00:41:43.630 ⇒ 00:41:47.850 Robert Tseng: That’s just spreading your ad spend across all your customers.
207 00:41:48.570 ⇒ 00:41:50.065 Uttam Kumaran: And what is so
208 00:41:51.170 ⇒ 00:41:54.079 Uttam Kumaran: Sorry if you wrote this in slack. I can go read it for blended cac.
209 00:41:54.310 ⇒ 00:42:04.790 Robert Tseng: No, no, I don’t. I don’t think we had a definition that we’ve a working definition we’ve been using. So that’s why I was like surprised. We had it in there last time, and I didn’t. Didn’t really know what it was.
210 00:42:08.920 ⇒ 00:42:10.360 Uttam Kumaran: I’m gonna ask Chat gp.
211 00:42:20.700 ⇒ 00:42:21.320 Robert Tseng: Okay, I guess.
212 00:42:21.320 ⇒ 00:42:23.049 Uttam Kumaran: But how is that different than New Cac.
213 00:42:25.140 ⇒ 00:42:28.309 Robert Tseng: New cock is just for cu ad spread over new customers.
214 00:42:31.510 ⇒ 00:42:40.300 Robert Tseng: But yeah, or or the the ad spend that we show for total and versus 1st time. It’s the same, because we’re always just paying to acquire new customers.
215 00:42:40.580 ⇒ 00:42:42.609 Robert Tseng: So the blended cac metric just
216 00:42:44.100 ⇒ 00:42:48.159 Robert Tseng: just takes the same ad spend numerator, and then
217 00:42:48.490 ⇒ 00:42:50.970 Robert Tseng: it puts it over total customers.
218 00:42:51.860 ⇒ 00:42:53.940 Robert Tseng: So I guess that’s more of like a.
219 00:42:53.940 ⇒ 00:42:54.480 Uttam Kumaran: Oh!
220 00:42:55.160 ⇒ 00:42:55.830 Robert Tseng: Yeah.
221 00:42:55.830 ⇒ 00:43:00.260 Uttam Kumaran: Yes, new and returning customers. Yeah, so just just divided by everything.
222 00:43:02.180 ⇒ 00:43:06.150 Uttam Kumaran: Oh, but you you want I guess you don’t wanna sum.
223 00:43:06.650 ⇒ 00:43:11.550 Uttam Kumaran: Yeah, I mean all. Actually, you’re fine with just adding new and
224 00:43:12.170 ⇒ 00:43:15.030 Uttam Kumaran: new and returning, because that’s all the customers in that period.
225 00:43:15.480 ⇒ 00:43:16.910 Robert Tseng: Yeah, okay.
226 00:43:21.060 ⇒ 00:43:25.130 Uttam Kumaran: Yeah, that’s all the customers across all time. So yeah, you’re fine with that.
227 00:43:27.484 ⇒ 00:43:28.500 Robert Tseng: Okay.
228 00:43:33.930 ⇒ 00:43:43.650 Robert Tseng: new customers, customers, orders, customers. Yeah. Needs to be. It has to be on customers, not on orders.
229 00:43:44.170 ⇒ 00:43:50.289 Robert Tseng: So I guess what’s the difference between end orders and end and end customers. If
230 00:43:50.630 ⇒ 00:43:55.790 Robert Tseng: we’re if every new order is only one customer, wouldn’t those numbers be the same.
231 00:43:59.670 ⇒ 00:44:01.439 Uttam Kumaran: No because customer can have multiple orders.
232 00:44:04.960 ⇒ 00:44:07.299 Robert Tseng: But they wouldn’t be in the new.
233 00:44:09.810 ⇒ 00:44:11.240 Robert Tseng: Oh, new.
234 00:44:11.240 ⇒ 00:44:13.739 Uttam Kumaran: You can be a new. You can be a new customer.
235 00:44:14.180 ⇒ 00:44:15.589 Robert Tseng: With multiple new orders.
236 00:44:15.590 ⇒ 00:44:19.480 Uttam Kumaran: Borders. Yeah, not multiple new orders.
237 00:44:21.910 ⇒ 00:44:26.799 Uttam Kumaran: but the number isn’t the same meaning. One customer can place 10 returning orders.
238 00:44:27.450 ⇒ 00:44:30.940 Robert Tseng: Yeah, yeah. But I’m saying, like, because we have a new customers.
239 00:44:31.200 ⇒ 00:44:31.800 Robert Tseng: The only way.
240 00:44:31.800 ⇒ 00:44:33.329 Uttam Kumaran: But yeah.
241 00:44:34.290 ⇒ 00:44:42.349 Robert Tseng: So if new orders is just the 1st order of a 1st time customer, then wouldn’t that just be the same as the number of customers.
242 00:44:48.510 ⇒ 00:44:49.709 Robert Tseng: You know what I’m saying.
243 00:44:52.250 ⇒ 00:44:54.970 Uttam Kumaran: Yeah let me think.
244 00:44:57.130 ⇒ 00:45:03.699 Robert Tseng: I mean, I get we. I get that one customer can have multiple orders. That’s how we capture more. Yeah, for all the returning orders.
245 00:45:05.330 ⇒ 00:45:08.539 Robert Tseng: but in the new custom in the new order, count
246 00:45:08.890 ⇒ 00:45:12.669 Robert Tseng: Metric. That should just be the 1st
247 00:45:12.850 ⇒ 00:45:15.010 Robert Tseng: order of a 1st time customer.
248 00:45:15.650 ⇒ 00:45:21.320 Uttam Kumaran: But let me look at what new means. New is based on the rank
249 00:45:38.770 ⇒ 00:45:41.969 Uttam Kumaran: Product sales from orders new.
250 00:45:48.210 ⇒ 00:45:53.130 Robert Tseng: And I’m not clear on where the transaction comes to play here, because we had this conversation about
251 00:45:53.470 ⇒ 00:45:54.290 Robert Tseng: when we’re seeing.
252 00:45:54.290 ⇒ 00:45:59.639 Uttam Kumaran: I’m just taking the for I’m taking the revenue from the 1st transaction for every order.
253 00:45:59.970 ⇒ 00:46:02.710 Robert Tseng: And yeah, you’re calling that revenue. Yeah.
254 00:46:02.710 ⇒ 00:46:03.380 Uttam Kumaran: Yes.
255 00:46:04.280 ⇒ 00:46:10.959 Robert Tseng: Yep, I don’t think this is gonna map that well, to the orders, because.
256 00:46:12.520 ⇒ 00:46:14.450 Robert Tseng: let’s say, I buy a bundle.
257 00:46:18.770 ⇒ 00:46:28.299 Robert Tseng: One transaction, 2 orders, because if I buy like a bundle on a quarterly plan.
258 00:46:29.557 ⇒ 00:46:34.920 Robert Tseng: that’s gonna be 4 orders over the total year. Maybe I only have one transaction.
259 00:46:38.020 ⇒ 00:46:40.460 Robert Tseng: and that would mean
260 00:46:46.700 ⇒ 00:46:51.669 Robert Tseng: we’re we’re counting the revenue the right from the from the start.
261 00:46:52.379 ⇒ 00:46:59.119 Robert Tseng: That’ll be the expected revenue, or what we don’t. We don’t even have the concept of expected and actual right now, we’ll just that’s the revenue
262 00:47:01.400 ⇒ 00:47:07.080 Robert Tseng: and then we’re only gonna count one order for now, because only one order is being
263 00:47:07.880 ⇒ 00:47:11.400 Robert Tseng: process. Now and then in a quarter there will be another order.
264 00:47:11.580 ⇒ 00:47:21.640 Robert Tseng: but because it’s a bundle, it has 2 variants, and so how variants show up is. It’s a duplicate same order, same transaction, but 2 separate variants.
265 00:47:23.960 ⇒ 00:47:30.559 Robert Tseng: We are still only counting that as one order, even though there are 2 variants, and when we’re splitting the revenue
266 00:47:31.200 ⇒ 00:47:34.359 Robert Tseng: between those 2 variants on that 1st order.
267 00:47:38.350 ⇒ 00:47:38.990 Uttam Kumaran: Yeah.
268 00:47:44.170 ⇒ 00:47:45.580 Robert Tseng: Does that make sense.
269 00:47:47.440 ⇒ 00:47:48.500 Uttam Kumaran: I mean, right?
270 00:47:48.500 ⇒ 00:47:53.359 Uttam Kumaran: I basically skipped that problem because I’m aggregating to the to the product.
271 00:47:55.520 ⇒ 00:47:58.200 Robert Tseng: Skipped these like the.
272 00:47:58.510 ⇒ 00:48:01.240 Uttam Kumaran: You won’t see variant in that in the table because
273 00:48:01.670 ⇒ 00:48:04.480 Uttam Kumaran: I’ve removed it because we were starting a duplication
274 00:48:05.070 ⇒ 00:48:06.790 Uttam Kumaran: because you could have multiple. We had
275 00:48:08.000 ⇒ 00:48:11.180 Uttam Kumaran: different variants, same order, so orders would come in twice.
276 00:48:12.890 ⇒ 00:48:13.710 Robert Tseng: Okay.
277 00:48:14.432 ⇒ 00:48:19.999 Robert Tseng: I suppose if somebody wanted to drill down into variance, that would have to be a different thing that we have to figure out.
278 00:48:20.000 ⇒ 00:48:24.480 Uttam Kumaran: I would. Oh, yeah, we we would create a, I’ll create a basically, we’d create a variance
279 00:48:24.900 ⇒ 00:48:28.089 Uttam Kumaran: like an order variance table where you can see down to the variant level.
280 00:48:30.020 ⇒ 00:48:33.170 Uttam Kumaran: But like, yeah.
281 00:48:36.350 ⇒ 00:48:39.500 Uttam Kumaran: and then to answer a question about 1st time order.
282 00:48:40.200 ⇒ 00:48:48.639 Uttam Kumaran: So the way I do it is, I look at a partition by Customer Id. And I order by the order, completed Timestamp to get their rank.
283 00:48:51.730 ⇒ 00:48:52.550 Robert Tseng: Okay.
284 00:48:53.080 ⇒ 00:48:58.130 Uttam Kumaran: So I find the first.st I find the 1st order for a given customer based on the timestamp. It’s completed.
285 00:48:59.300 ⇒ 00:48:59.990 Robert Tseng: Yeah.
286 00:49:00.550 ⇒ 00:49:11.290 Robert Tseng: I mean, I suppose I could answer my own question just by counting the number of new customers and new orders. I mean to the way that you’re telling it to me. I feel like they should probably match.
287 00:49:15.100 ⇒ 00:49:16.189 Robert Tseng: Let me see.
288 00:49:17.790 ⇒ 00:49:19.210 Uttam Kumaran: I guess if
289 00:49:19.630 ⇒ 00:49:25.200 Uttam Kumaran: the only reason it would should be different is, if a customer has a has a 2 orders, the exact same timestamp.
290 00:49:27.070 ⇒ 00:49:29.720 Robert Tseng: Yeah, let’s just let’s just take a look.
291 00:49:31.780 ⇒ 00:49:38.909 Robert Tseng: New customers have new order out might be.
292 00:49:40.550 ⇒ 00:49:43.430 Robert Tseng: Actually, I don’t need. But I don’t need my date by month. It’s fine.
293 00:49:44.790 ⇒ 00:49:48.120 Robert Tseng: Okay? Yeah. It’s exactly the same.
294 00:49:48.420 ⇒ 00:49:49.380 Uttam Kumaran: Oh, great!
295 00:49:49.820 ⇒ 00:49:50.290 Robert Tseng: Yeah.
296 00:49:51.095 ⇒ 00:49:51.900 Uttam Kumaran: Okay.
297 00:49:52.080 ⇒ 00:49:54.860 Uttam Kumaran: Fuck, nice.
298 00:49:59.520 ⇒ 00:50:14.270 Robert Tseng: Okay. But then, when we do total customer account sum of new plus in some money earning
299 00:50:32.680 ⇒ 00:50:37.480 Robert Tseng: 3, 6, 9, yeah. Then we start to see some differences.
300 00:50:37.870 ⇒ 00:50:59.739 Robert Tseng: Because, yeah, I mean as scroll order counts as total oh, or customer count
301 00:51:12.520 ⇒ 00:51:13.355 Robert Tseng: and
302 00:51:52.060 ⇒ 00:52:01.209 Robert Tseng: I haven’t. Oh, and God, these are like so small. Okay, so
303 00:52:02.675 ⇒ 00:52:06.559 Robert Tseng: what I’m seeing here is, maybe I’ll just.
304 00:52:08.220 ⇒ 00:52:09.879 Robert Tseng: I’ll show you my screen.
305 00:52:14.570 ⇒ 00:52:21.408 Robert Tseng: sorry I didn’t. I didn’t number any of these. I was just label these total customer account total order, count
306 00:52:22.830 ⇒ 00:52:26.829 Uttam Kumaran: Yeah. But dude, there’s gonna be a couple like these are, there’s a there’s gonna be a
307 00:52:27.370 ⇒ 00:52:34.389 Uttam Kumaran: there are already. There’s like, probably like 8 or 9 orders that have 2 orders each that I haven’t deduped yet.
308 00:52:34.570 ⇒ 00:52:38.990 Uttam Kumaran: because there’s just like a there’s just like one or 2 issues.
309 00:52:39.410 ⇒ 00:52:45.999 Robert Tseng: Yeah, no worries. I mean, I’m like, I’m just scratching my head. I’m like, I don’t expect these to match. I think.
310 00:52:46.390 ⇒ 00:52:47.140 Uttam Kumaran: Why not?
311 00:52:49.340 ⇒ 00:52:50.980 Robert Tseng: Because.
312 00:52:52.900 ⇒ 00:52:56.710 Uttam Kumaran: Wait. Oh, yeah. Total. Cut.
313 00:52:58.110 ⇒ 00:52:59.050 Uttam Kumaran: Yeah. Why not?
314 00:52:59.810 ⇒ 00:53:06.769 Robert Tseng: Cause. I think there should be more orders, more total orders, than more than total customers.
315 00:53:07.710 ⇒ 00:53:10.059 Robert Tseng: I’m actually surprised that the difference is so low.
316 00:53:10.060 ⇒ 00:53:18.459 Uttam Kumaran: Total customer account is new customer account plus returning customer account, total order, count.
317 00:53:26.250 ⇒ 00:53:33.199 Robert Tseng: Like, I basically just total order count minus total customer count without me creating another like sub query, being lazy about it.
318 00:53:33.750 ⇒ 00:53:36.730 Uttam Kumaran: I see what you mean. So let me look at order, rank.
319 00:53:37.280 ⇒ 00:53:40.769 Uttam Kumaran: and then let me look at where I did. The logic for order, rank.
320 00:53:41.030 ⇒ 00:53:46.649 Robert Tseng: Because what this is telling me is that in the month of January only.
321 00:53:50.310 ⇒ 00:53:56.950 Uttam Kumaran: I. So basically, it’s like, if the order rank is one, then it’s true. Otherwise it’s false.
322 00:53:57.390 ⇒ 00:54:02.950 Uttam Kumaran: as is 1st time order, and then
323 00:54:07.880 ⇒ 00:54:11.580 Uttam Kumaran: and then if I go to sales summary.
324 00:54:14.450 ⇒ 00:54:17.039 Uttam Kumaran: yeah, I mean his 1st time. Order is false.
325 00:54:20.250 ⇒ 00:54:24.069 Uttam Kumaran: If it’s 1st time, or if it’s not the 1st time order. Then it’s a returning.
326 00:54:26.050 ⇒ 00:54:26.700 Robert Tseng: Yeah.
327 00:54:27.920 ⇒ 00:54:32.150 Uttam Kumaran: And then if it’s a yeah.
328 00:54:34.600 ⇒ 00:54:37.259 Uttam Kumaran: if the rank is one, then it’s yeah.
329 00:54:37.990 ⇒ 00:54:39.910 Uttam Kumaran: I mean, the logic seems okay.
330 00:54:44.210 ⇒ 00:54:49.990 Uttam Kumaran: Oh, you’re saying so this is showing that there’s not that many returning customers.
331 00:54:50.540 ⇒ 00:54:51.190 Robert Tseng: Yeah.
332 00:54:52.450 ⇒ 00:54:54.769 Uttam Kumaran: Can you look at what the returning customer counts? Are.
333 00:54:57.940 ⇒ 00:54:58.730 Robert Tseng: Yeah.
334 00:55:12.910 ⇒ 00:55:18.390 Uttam Kumaran: You can also query the actual orders, new table, where I’m calculating his 1st time order
335 00:55:18.750 ⇒ 00:55:23.720 Uttam Kumaran: and the order rank like I have. I have. For example, here.
336 00:55:24.590 ⇒ 00:55:30.429 Uttam Kumaran: Yeah, I’m gonna look, I’m gonna look at one example of someone who has a returning order. But that was an example.
337 00:55:31.811 ⇒ 00:55:38.080 Uttam Kumaran: Is 1st time. Order. Okay, cool. So for this person, it’s not their 1st time order.
338 00:55:38.430 ⇒ 00:55:41.229 Uttam Kumaran: Let’s go ahead and take their customer. Id.
339 00:55:42.070 ⇒ 00:55:44.560 Uttam Kumaran: So where.
340 00:55:44.560 ⇒ 00:56:01.230 Robert Tseng: I want to just compare it to like mask. And just look at like from the raw data. If we look at a customer, you know, like how many orders are returning customer orders like, I, I feel like what we have showing here is too low like. I don’t believe that less than 10 orders a month are
341 00:56:01.910 ⇒ 00:56:03.319 Robert Tseng: returning customers.
342 00:56:10.960 ⇒ 00:56:15.230 Uttam Kumaran: I don’t know. I mean, look, I’m looking at this one. I’m looking at this one customer
343 00:56:15.400 ⇒ 00:56:18.070 Uttam Kumaran: they ordered once in.
344 00:56:25.340 ⇒ 00:56:28.389 Uttam Kumaran: they ordered. Once on March on March 10, th
345 00:56:28.660 ⇒ 00:56:30.549 Uttam Kumaran: and they they had an order on
346 00:56:30.770 ⇒ 00:56:33.709 Uttam Kumaran: the 30.th Then they had an order. On the 18.th
347 00:56:34.870 ⇒ 00:56:37.110 Uttam Kumaran: Out of that one is abandoned.
348 00:56:39.180 ⇒ 00:56:41.399 Uttam Kumaran: The order status is abandoned.
349 00:56:41.770 ⇒ 00:56:46.300 Uttam Kumaran: So then let me look at here. Current status. Yeah. So I’m using current status.
350 00:56:47.650 ⇒ 00:56:49.089 Robert Tseng: Which screen am I looking at.
351 00:56:49.980 ⇒ 00:56:51.340 Uttam Kumaran: It’s probably weish.
352 00:56:51.520 ⇒ 00:56:52.340 Robert Tseng: Oh, okay.
353 00:56:52.750 ⇒ 00:56:57.149 Uttam Kumaran: Current status from product cogs base.
354 00:56:58.210 ⇒ 00:56:59.399 Uttam Kumaran: And then this
355 00:57:04.050 ⇒ 00:57:08.599 Uttam Kumaran: yeah, current status from orders, new current status from
356 00:57:08.990 ⇒ 00:57:15.099 Uttam Kumaran: transactions. If I go to transactions and current status is coming from
357 00:57:25.420 ⇒ 00:57:29.409 Uttam Kumaran: this bask, this weird bask order, updated logic
358 00:57:30.330 ⇒ 00:57:35.870 Uttam Kumaran: status rank. And then this one is coming from
359 00:57:40.330 ⇒ 00:57:42.000 Uttam Kumaran: transaction source.
360 00:57:46.270 ⇒ 00:57:46.810 Awaish Kumar: Hmm.
361 00:57:50.570 ⇒ 00:57:51.660 Uttam Kumaran: I mean.
362 00:57:55.610 ⇒ 00:58:02.360 Uttam Kumaran: okay, well, this one should make it in because these, both these orders oh, current status is null.
363 00:58:03.310 ⇒ 00:58:05.160 Uttam Kumaran: I guess I’m letting those pass.
364 00:58:10.290 ⇒ 00:58:12.550 Uttam Kumaran: and I don’t think this is a good example.
365 00:58:15.590 ⇒ 00:58:24.080 Uttam Kumaran: Alright, let me just look up customer id, and then count distinct order. Id.
366 00:58:25.480 ⇒ 00:58:26.330 Uttam Kumaran: Where?
367 00:58:28.900 ⇒ 00:58:34.490 Uttam Kumaran: Yeah. Here, let’s do this customer. Id is 1st order.
368 00:59:22.900 ⇒ 00:59:27.430 Uttam Kumaran: Okay, there’s this customer with 24 orders. Right? So let’s look at this person.
369 00:59:48.780 ⇒ 00:59:55.720 Uttam Kumaran: So this person, 8, 3, 1, 5, 4 has a ton of orders. Their order number is eaten. Something.
370 00:59:56.620 ⇒ 01:00:01.599 Robert Tseng: It’s probably like one of the the internal users, because it’s probably like invalid orders.
371 01:00:03.720 ⇒ 01:00:09.160 Uttam Kumaran: Yeah, all the current. Stat. Oh, I mean.
372 01:00:10.910 ⇒ 01:00:14.130 Uttam Kumaran: I thought at this point this would. This would make it in.
373 01:00:17.700 ⇒ 01:00:21.689 Uttam Kumaran: I mean, the the current status is all sent to pharmacy for this one.
374 01:00:22.580 ⇒ 01:00:23.310 Robert Tseng: Okay.
375 01:00:23.980 ⇒ 01:00:28.229 Uttam Kumaran: And then this one here, I can share my screen.
376 01:00:31.390 ⇒ 01:00:35.640 Uttam Kumaran: So this 1, 8, 3, 1, 5, 4
377 01:00:37.920 ⇒ 01:00:44.180 Uttam Kumaran: They have a bunch of these orders. The timestamp is here.
378 01:00:48.740 ⇒ 01:00:51.780 Uttam Kumaran: So yeah, 1st time order, and then all these are are new.
379 01:00:53.810 ⇒ 01:00:56.399 Uttam Kumaran: All these are all these are not 1st time
380 01:00:59.030 ⇒ 01:01:03.209 Uttam Kumaran: you’re just saying, it’s odd that it like the math adds up, Yeah, I agree.
381 01:01:09.080 ⇒ 01:01:11.563 Robert Tseng: The hell wrong? My query.
382 01:03:22.080 ⇒ 01:03:30.390 Robert Tseng: I already forgot my order. Status. Comment. What? What order? Status filter using again? Sorry. I don’t know. Off the top of my head. I already lost my.
383 01:03:31.550 ⇒ 01:03:41.200 Uttam Kumaran: I’m using abandoned, cancelled and error.
384 01:03:45.150 ⇒ 01:03:46.790 Robert Tseng: Abandoned.
385 01:04:08.280 ⇒ 01:04:17.469 Robert Tseng: can you? Can you just drop me? Can you just drop me that filter so I can add it in? Because when I just include all orders. It’s not right. It’s just like I’m seeing 90% of orders or repeat customers.
386 01:04:21.690 ⇒ 01:04:23.659 Uttam Kumaran: Yeah, I’ll send it here.
387 01:04:31.870 ⇒ 01:04:35.819 Uttam Kumaran: I mean, this is, yeah. So this is what I’m pulling from the orders table.
388 01:04:36.500 ⇒ 01:04:37.070 Robert Tseng: Yep.
389 01:04:43.260 ⇒ 01:04:45.179 Robert Tseng: this is the orders. New table.
390 01:04:45.180 ⇒ 01:04:45.840 Uttam Kumaran: Yes.
391 01:04:46.590 ⇒ 01:04:51.910 Robert Tseng: Okay, I was just going back further and using even your Dbt. Mart orders table. Is that.
392 01:04:52.720 ⇒ 01:04:55.380 Uttam Kumaran: Yeah. So Dbt. Mart orders.
393 01:04:55.810 ⇒ 01:05:02.759 Uttam Kumaran: I can tell you where the returning thing is coming from. So it’s coming from bask order. So that’s coming from Basque
394 01:05:03.540 ⇒ 01:05:07.750 Uttam Kumaran: is 1st time order, which I don’t have any insight into.
395 01:05:11.740 ⇒ 01:05:15.150 Uttam Kumaran: That’s bask telling us that it’s a repeat order.
396 01:05:15.440 ⇒ 01:05:18.080 Robert Tseng: No, no, I I’m like I just wrote some.
397 01:05:18.360 ⇒ 01:05:21.400 Robert Tseng: I don’t think I’m I didn’t even know there, that was a field there for them.
398 01:05:22.770 ⇒ 01:05:23.810 Uttam Kumaran: Yeah, it is.
399 01:05:24.000 ⇒ 01:05:25.660 Robert Tseng: Yeah, yeah, I’m not. I wasn’t even using.
400 01:05:25.660 ⇒ 01:05:26.430 Uttam Kumaran: Oh, okay. Okay.
401 01:05:26.430 ⇒ 01:05:30.649 Robert Tseng: Who’s counting it myself? But I’ll I’ll send you my query. One sec.
402 01:05:31.160 ⇒ 01:05:42.990 Robert Tseng: Let me just add, in the right order status things something alright, so
403 01:06:00.160 ⇒ 01:06:02.419 Robert Tseng: may limit this to the past.
404 01:06:08.780 ⇒ 01:06:12.140 Robert Tseng: What? What’s the date? Field here?
405 01:06:12.880 ⇒ 01:06:15.039 Robert Tseng: Order completed Timestamp.
406 01:06:15.630 ⇒ 01:06:18.319 Robert Tseng: I don’t know. Whatever this use. I don’t.
407 01:06:42.700 ⇒ 01:06:45.869 Uttam Kumaran: Okay, yeah. See, I’m seeing 1st time. Orders is 81
408 01:06:46.710 ⇒ 01:06:49.000 Uttam Kumaran: non. 1st time orders is way higher.
409 01:06:50.540 ⇒ 01:06:51.210 Robert Tseng: Yeah.
410 01:06:51.340 ⇒ 01:06:55.290 Robert Tseng: So that tells me that what we were showing in our other model doesn’t really make sense.
411 01:06:56.120 ⇒ 01:06:58.390 Uttam Kumaran: What the fuck is going on here. Then.
412 01:07:22.620 ⇒ 01:07:25.129 Uttam Kumaran: if it’s the 1st time ordinance falls.
413 01:07:27.440 ⇒ 01:07:30.490 Uttam Kumaran: if 1st time order is false, then it’s returning.
414 01:07:30.710 ⇒ 01:07:36.239 Uttam Kumaran: If not, it’s not returning, and then I calculate
415 01:07:37.330 ⇒ 01:07:44.280 Uttam Kumaran: this based on when case when this, then customer, then order id
416 01:07:52.700 ⇒ 01:08:00.120 Uttam Kumaran: count, just in case one is returning as false. Then Css. Order id as a new order account.
417 01:08:03.350 ⇒ 01:08:05.070 Uttam Kumaran: So when the order
418 01:08:11.210 ⇒ 01:08:12.760 Uttam Kumaran: Oh.
419 01:08:26.270 ⇒ 01:08:29.509 Robert Tseng: Oh, you already have. Okay, yeah, I mean, yours is much cleaner than what I was doing.
420 01:08:29.881 ⇒ 01:08:33.650 Robert Tseng: Is 1st time order. That’s not the best one you may. You made that already.
421 01:08:34.340 ⇒ 01:08:38.070 Uttam Kumaran: Yeah. His 1st time order is coming from transactions.
422 01:08:41.090 ⇒ 01:08:41.649 Robert Tseng: Okay.
423 01:08:53.899 ⇒ 01:08:56.499 Uttam Kumaran: Wait. So is 1st time. Order
424 01:08:57.009 ⇒ 01:09:04.569 Uttam Kumaran: from source sources from bask order completed is 1st time order.
425 01:09:06.359 ⇒ 01:09:08.579 Uttam Kumaran: and where the fuck am I getting?
426 01:09:10.479 ⇒ 01:09:12.449 Uttam Kumaran: Move this over here
427 01:09:18.609 ⇒ 01:09:22.579 Uttam Kumaran: from orders new. And where is orders? New orders? New?
428 01:09:22.679 ⇒ 01:09:28.069 Uttam Kumaran: Yeah. His 1st time orders should not be coming from transactions. It’s coming from.
429 01:09:33.409 ⇒ 01:09:37.979 Uttam Kumaran: I wonder if, like, there’s some sort of fuck up because I named it the same thing.
430 01:09:44.969 ⇒ 01:09:46.939 Uttam Kumaran: Just gonna ditch this in this.
431 01:10:01.300 ⇒ 01:10:09.679 Robert Tseng: Yeah, but we can easily just like sum these 2 columns and get the monthly like order counts and compare it to what we have in the product sales summary. I’m pretty sure it wouldn’t match that.
432 01:10:17.560 ⇒ 01:10:19.569 Uttam Kumaran: It’s like unclear to me what the
433 01:10:19.710 ⇒ 01:10:26.999 Uttam Kumaran: like. Why, this isn’t matching, because I’m pulling the exact right thing, and then I’m dialing. The
434 01:10:27.480 ⇒ 01:10:30.120 Uttam Kumaran: is 1st time order, and then
435 01:10:30.640 ⇒ 01:10:33.769 Uttam Kumaran: I’m saying, when it’s false, then it’s returning.
436 01:10:35.650 ⇒ 01:10:36.789 Uttam Kumaran: And then
437 01:10:55.610 ⇒ 01:10:59.049 Uttam Kumaran: I feel like these ad spends are much closer, though. Right?
438 01:11:05.360 ⇒ 01:11:08.750 Uttam Kumaran: Okay? This 1st time. Order.
439 01:11:18.730 ⇒ 01:11:21.520 Robert Tseng: Bro. Maybe we over engineered this. We should just.
440 01:11:21.890 ⇒ 01:11:30.039 Robert Tseng: I don’t know like call it. Just go back to. I don’t know. Is it too back too late to revert. Just go back to what Rob had.
441 01:11:32.610 ⇒ 01:11:34.470 Uttam Kumaran: Dude. Rob shit was wrong.
442 01:11:41.850 ⇒ 01:11:45.443 Uttam Kumaran: Okay? I mean, I can. Just I can start to back into it.
443 01:11:47.170 ⇒ 01:11:59.910 Robert Tseng: Okay. So let’s just be clear on, like, what what’s right? So like ad spend, I think oasis working on, we’re we’re still. We’re still a bit off there. The order counts, I think I’m pointing out, is like something was off about the new repeat order thing.
444 01:12:01.940 ⇒ 01:12:08.069 Robert Tseng: yeah. And then, as a consequence of that, I’m sure the revenue got is is probably off of that, too.
445 01:12:08.070 ⇒ 01:12:09.730 Uttam Kumaran: Oh, I know what it is.
446 01:12:10.460 ⇒ 01:12:12.512 Uttam Kumaran: I got it. I got it. I got it
447 01:12:12.740 ⇒ 01:12:13.420 Robert Tseng: What?
448 01:12:14.720 ⇒ 01:12:16.470 Uttam Kumaran: This line is wrong.
449 01:12:16.610 ⇒ 01:12:20.390 Uttam Kumaran: I don’t think these are right or
450 01:12:32.700 ⇒ 01:12:33.950 Uttam Kumaran: okay, never mind.
451 01:13:07.610 ⇒ 01:13:09.300 Uttam Kumaran: Okay, I’m gonna take.
452 01:13:10.580 ⇒ 01:13:13.660 Uttam Kumaran: I’m gonna take an order that is
453 01:13:20.570 ⇒ 01:13:24.358 Uttam Kumaran: like, I’m gonna take one of these one of these orders and then
454 01:13:31.170 ⇒ 01:13:32.790 Uttam Kumaran: take it all the way back.
455 01:14:03.150 ⇒ 01:14:07.900 Uttam Kumaran: Okay, so
456 01:14:21.040 ⇒ 01:14:24.569 Uttam Kumaran: and then we have our order. Id here.
457 01:14:25.820 ⇒ 01:14:29.990 Uttam Kumaran: So one, let’s trace this order all through this thing. So
458 01:14:39.210 ⇒ 01:14:47.590 Uttam Kumaran: cool! Let’s 1st look at it in customer status.
459 01:14:51.980 ⇒ 01:14:55.930 Uttam Kumaran: So we should be seeing this as a returning order.
460 01:14:58.440 ⇒ 01:15:00.530 Uttam Kumaran: And it’s not in here at all.
461 01:15:01.900 ⇒ 01:15:02.630 Uttam Kumaran: Fuck.
462 01:15:06.670 ⇒ 01:15:07.810 Uttam Kumaran: Okay.
463 01:15:09.920 ⇒ 01:15:15.390 Robert Tseng: Is it something to do with the way that we we excluded orders when we ranked.
464 01:15:17.340 ⇒ 01:15:20.979 Uttam Kumaran: Oh, because we didn’t rank on.
465 01:15:22.920 ⇒ 01:15:26.499 Uttam Kumaran: See? For this one this one would have been kicked out because it’s pending.
466 01:15:28.600 ⇒ 01:15:31.979 Robert Tseng: Pending, we’re saying, is a valid order status.
467 01:15:35.960 ⇒ 01:15:37.849 Uttam Kumaran: Oh, what the fuck!
468 01:15:39.020 ⇒ 01:15:42.410 Uttam Kumaran: Oh, this is the order status, not the current status.
469 01:15:46.930 ⇒ 01:15:49.329 Uttam Kumaran: What is current status, what the heck
470 01:15:49.330 ⇒ 01:15:55.559 Uttam Kumaran: order status is what we get when the order is created. Current status is our ranking from the web hook.
471 01:15:55.720 ⇒ 01:15:59.569 Uttam Kumaran: So if you look at this, the current status will be different.
472 01:16:00.190 ⇒ 01:16:00.640 Robert Tseng: Oh!
473 01:16:03.000 ⇒ 01:16:04.310 Uttam Kumaran: So
474 01:16:08.470 ⇒ 01:16:11.839 Uttam Kumaran: where does where did I even put the current status?
475 01:16:13.520 ⇒ 01:16:16.329 Uttam Kumaran: Oh, I just added it to the wrong one.
476 01:16:42.960 ⇒ 01:16:44.660 Uttam Kumaran: Current status canceled.
477 01:16:52.040 ⇒ 01:16:54.621 Uttam Kumaran: So you’re right in that. I’m not
478 01:17:00.610 ⇒ 01:17:05.489 Uttam Kumaran: I mean, I can. I can try like one thing. Let me try to. One thing I’m gonna look at.
479 01:17:05.720 ⇒ 01:17:11.030 Uttam Kumaran: I’m gonna try to do the splits again, but eliminate the ones where the current status is.
480 01:17:11.820 ⇒ 01:17:13.060 Uttam Kumaran: What I said.
481 01:17:13.430 ⇒ 01:17:16.870 Uttam Kumaran: So like this.
482 01:17:24.380 ⇒ 01:17:26.580 Uttam Kumaran: hey? That didn’t do anything. Never mind.
483 01:17:36.680 ⇒ 01:17:49.490 Robert Tseng: Okay? I mean, I I think I was wrong in using order status. But using, I think, current current status is the one that we get from the web hook. And it doesn’t actually update orders. I don’t understand what updates order status.
484 01:17:49.820 ⇒ 01:17:53.329 Uttam Kumaran: Order status. I’m gonna delete like we shouldn’t have order status.
485 01:17:53.760 ⇒ 01:17:54.390 Robert Tseng: Okay.
486 01:17:54.990 ⇒ 01:17:58.079 Uttam Kumaran: Current status is the live, the live status.
487 01:18:16.250 ⇒ 01:18:19.210 Uttam Kumaran: Where was the query I just wrote.
488 01:18:30.930 ⇒ 01:18:35.140 Uttam Kumaran: yeah, so this customer Id, I mean, I don’t. Maybe this is not a good one.
489 01:18:45.420 ⇒ 01:18:47.120 Uttam Kumaran: These are all.
490 01:18:53.550 ⇒ 01:18:56.150 Robert Tseng: You’re picking a customer with multiple orders.
491 01:18:56.150 ⇒ 01:18:57.020 Uttam Kumaran: Yes.
492 01:20:01.790 ⇒ 01:20:05.890 Uttam Kumaran: okay, okay. I tried some of those. So let’s just try one of these guys.
493 01:20:06.970 ⇒ 01:20:07.930 Awaish Kumar: Hello!
494 01:20:13.470 ⇒ 01:20:14.460 Awaish Kumar: Hello!
495 01:20:14.460 ⇒ 01:20:15.060 Uttam Kumaran: Hey!
496 01:20:16.350 ⇒ 01:20:20.789 Awaish Kumar: Hey? I I think at this point I have fixed that thing.
497 01:20:21.540 ⇒ 01:20:23.869 Uttam Kumaran: Oh, okay, what’s the fee?
498 01:20:25.560 ⇒ 01:20:26.780 Awaish Kumar: Actually.
499 01:20:35.490 ⇒ 01:20:43.539 Awaish Kumar: yeah. So here, I just try to use a full joint.
500 01:20:45.110 ⇒ 01:20:46.200 Awaish Kumar: Oh, God.
501 01:20:46.890 ⇒ 01:20:49.410 Uttam Kumaran: And separate out it from the.
502 01:20:49.920 ⇒ 01:20:52.699 Awaish Kumar: Like into a separate city. So
503 01:20:52.950 ⇒ 01:21:00.310 Awaish Kumar: here it was, like, you know, join because we were using joins from we were using doing 2 joins
504 01:21:00.510 ⇒ 01:21:13.040 Awaish Kumar: in the same table, and it was using date column from different places. I don’t know. Something was being getting mixed up or separated out and then use the full join, and here, like for a month.
505 01:21:13.980 ⇒ 01:21:18.580 Awaish Kumar: 1st month of 2024, we have, like from 300 k.
506 01:21:18.880 ⇒ 01:21:20.630 Awaish Kumar: 315 k.
507 01:21:21.280 ⇒ 01:21:28.595 Awaish Kumar: At a spend which is correctly being calculated here. But I have noticed that
508 01:21:29.520 ⇒ 01:21:37.190 Awaish Kumar: in in the later stages you’re all again doing join here to find to spend
509 01:21:39.650 ⇒ 01:21:44.680 Awaish Kumar: So here, here again, if we are doing left join, and it is going to break again.
510 01:21:44.680 ⇒ 01:21:45.420 Uttam Kumaran: Yes.
511 01:21:47.300 ⇒ 01:21:50.179 Awaish Kumar: So why we are not using that totally spent
512 01:21:51.110 ⇒ 01:21:55.890 Awaish Kumar: that we calculated, which is already in the daily product matrix table.
513 01:21:57.210 ⇒ 01:22:03.139 Uttam Kumaran: We can do that. So what do we end up? We end up with all the values like once we, we change it to a full join, and then bring that in.
514 01:22:07.340 ⇒ 01:22:14.249 Robert Tseng: I wish. Can we look at January 2025? I don’t. 2024. I don’t. I can’t even validate that at this point.
515 01:22:16.080 ⇒ 01:22:16.810 Awaish Kumar: Alright!
516 01:22:17.430 ⇒ 01:22:21.522 Uttam Kumaran: Yeah. Just just like, see if you can select the sum of the
517 01:22:22.130 ⇒ 01:22:26.059 Uttam Kumaran: ad spend and revenue for just Jan. 2025, with your logic.
518 01:22:52.850 ⇒ 01:22:56.549 Robert Tseng: Oh, there’s a waste using my bigquery lot creds.
519 01:22:56.550 ⇒ 01:22:57.970 Uttam Kumaran: Yeah, we all we all are.
520 01:22:58.400 ⇒ 01:23:03.090 Robert Tseng: Oh, no wonder Looker was like freaking, breaking all the time.
521 01:23:03.090 ⇒ 01:23:03.960 Uttam Kumaran: Why?
522 01:23:04.570 ⇒ 01:23:13.470 Robert Tseng: Because, like, I would try to save. And then it would just like exit out. And I think it’s because you guys are like running queries. They can’t do it in multiple. I don’t know like.
523 01:23:15.200 ⇒ 01:23:16.450 Awaish Kumar: Yeah, is it? Right?
524 01:23:16.650 ⇒ 01:23:17.190 Uttam Kumaran: But.
525 01:23:18.054 ⇒ 01:23:24.039 Robert Tseng: It’s closer 1.6. It’s a bit higher. Let me let me just. I’ll check.
526 01:23:24.040 ⇒ 01:23:25.959 Uttam Kumaran: I think that’s right.
527 01:23:26.920 ⇒ 01:23:28.969 Awaish Kumar: If I do this here.
528 01:23:30.940 ⇒ 01:23:32.369 Robert Tseng: I would say.
529 01:23:32.890 ⇒ 01:23:40.219 Robert Tseng: it’s yeah, 1.5 6. It’s it’s close enough. But like, I don’t know if that was a fluke on just on just that one.
530 01:23:41.150 ⇒ 01:23:44.980 Uttam Kumaran: Yeah, try December. One of them is like 1.3 7 or something like that.
531 01:23:46.260 ⇒ 01:23:47.050 Awaish Kumar: We just.
532 01:23:50.900 ⇒ 01:23:56.360 Robert Tseng: Yeah. So 1.5 6 was January.
533 01:23:57.560 ⇒ 01:24:00.520 Robert Tseng: December was 1 point what the
534 01:24:02.540 ⇒ 01:24:04.959 Robert Tseng: hold up! Hold up! Hold up! Hold up!
535 01:24:05.270 ⇒ 01:24:11.330 Awaish Kumar: The yeah, this is also what we have in the campaign. Spend table.
536 01:24:15.730 ⇒ 01:24:18.290 Awaish Kumar: This table called.
537 01:24:20.270 ⇒ 01:24:23.210 Robert Tseng: Yeah, I’m okay with it being pilot
538 01:24:25.400 ⇒ 01:24:31.390 Robert Tseng: like, why would it even be office coming from northeast? It should all roll up the same shit.
539 01:24:32.210 ⇒ 01:24:32.890 Robert Tseng: Okay.
540 01:24:33.290 ⇒ 01:24:34.090 Robert Tseng: What?
541 01:24:36.110 ⇒ 01:24:36.880 Robert Tseng: Okay. Sorry.
542 01:24:36.880 ⇒ 01:24:38.410 Uttam Kumaran: Customer, account.
543 01:24:38.950 ⇒ 01:24:46.280 Robert Tseng: 1.6 3. You’re right on, I think 1.6 3 is right. And then, if we just look at January or December 2024.
544 01:24:47.840 ⇒ 01:24:50.630 Robert Tseng: I’m assuming it would be 1.4 6
545 01:24:51.560 ⇒ 01:24:53.930 Robert Tseng: 1.6 3, I think is is right.
546 01:24:57.350 ⇒ 01:24:58.840 Awaish Kumar: Let’s find out.
547 01:25:00.260 ⇒ 01:25:02.469 Awaish Kumar: December 2024.
548 01:25:21.020 ⇒ 01:25:22.060 Robert Tseng: Yes.
549 01:25:26.150 ⇒ 01:25:27.230 Robert Tseng: great.
550 01:25:28.710 ⇒ 01:25:31.855 Robert Tseng: But Job’s not done.
551 01:25:32.830 ⇒ 01:25:34.180 Uttam Kumaran: Is, that is, that it?
552 01:25:34.980 ⇒ 01:25:36.639 Robert Tseng: That’s it. That’s it. That’s right.
553 01:25:36.640 ⇒ 01:25:37.260 Uttam Kumaran: God.
554 01:25:37.590 ⇒ 01:25:44.809 Robert Tseng: If we can get the spends to roll up like, I mean, yeah, like this. Then I think that that’ll
555 01:25:45.010 ⇒ 01:25:49.539 Robert Tseng: that’ll help us. Yeah, anyway, which obviously we still have to get. The order counts down.
556 01:25:49.680 ⇒ 01:25:52.190 Uttam Kumaran: Yeah, yeah, I’m, yeah.
557 01:25:53.010 ⇒ 01:25:58.320 Robert Tseng: Yeah, but yes, this. This solves it. We finally matched ad, spend.
558 01:26:00.050 ⇒ 01:26:05.610 Uttam Kumaran: Dude. We’ve tried every trick in the book. Aish! What do you think like looking at? Query dude? I’ve tried everything.
559 01:26:06.140 ⇒ 01:26:06.730 Robert Tseng: I don’t know what.
560 01:26:06.730 ⇒ 01:26:07.080 Awaish Kumar: Can you.
561 01:26:08.270 ⇒ 01:26:10.450 Uttam Kumaran: I did everything except for a full join.
562 01:26:10.940 ⇒ 01:26:11.440 Awaish Kumar: Okay.
563 01:26:13.260 ⇒ 01:26:20.739 Uttam Kumaran: I swear, dude, I look at the query. It’s it’s like I’ve tried everything. The last option was a full join. I just haven’t.
564 01:26:21.220 ⇒ 01:26:25.430 Uttam Kumaran: You know, we don’t write sequel every day anymore. So I’ve been a little rusty, forgot.
565 01:26:27.260 ⇒ 01:26:31.828 Awaish Kumar: Yeah. But now, the point is to get it to the bottom.
566 01:26:33.100 ⇒ 01:26:38.920 Uttam Kumaran: Yeah. So I just pushed the my, you can. Actually, if you want to check out my branch, you can make that change if you want.
567 01:26:39.400 ⇒ 01:26:41.341 Awaish Kumar: No, I I’m in
568 01:26:43.328 ⇒ 01:26:48.830 Awaish Kumar: can we? This this place like it? It is updating the respect.
569 01:26:54.200 ⇒ 01:26:56.089 Awaish Kumar: Can you see my screen.
570 01:26:56.090 ⇒ 01:26:57.120 Uttam Kumaran: Yeah, yeah, yeah.
571 01:26:57.480 ⇒ 01:27:02.889 Awaish Kumar: Yeah, in final final metrics. Pre, you are again using campaign. Spend Pre table.
572 01:27:03.060 ⇒ 01:27:03.740 Uttam Kumaran: Yes.
573 01:27:03.750 ⇒ 01:27:12.150 Awaish Kumar: So I’m not sure why? Because we already daily product metrics already have a advertisement.
574 01:27:13.576 ⇒ 01:27:19.379 Uttam Kumaran: Because I needed the ad spend that wasn’t on the daily level. I needed that one that was also on the
575 01:27:19.630 ⇒ 01:27:21.400 Uttam Kumaran: standard product name level.
576 01:27:22.360 ⇒ 01:27:26.329 Awaish Kumar: Okay. So now, now we have a fully join. We don’t need this right.
577 01:27:26.770 ⇒ 01:27:27.790 Uttam Kumaran: Yeah, ditch it.
578 01:27:29.190 ⇒ 01:27:34.240 Uttam Kumaran: keep ditching it, and then just see if the sums as long as the sums go up. As long as the sums. Match.
579 01:27:35.120 ⇒ 01:27:37.020 Uttam Kumaran: Delete my logic. It’s fine.
580 01:27:38.745 ⇒ 01:27:41.799 Awaish Kumar: Let’s okay. So.
581 01:27:43.650 ⇒ 01:27:46.940 Uttam Kumaran: Yeah, I don’t think you’re gonna have. Yeah, you’re just gonna have to delete some of these. Yup.
582 01:28:24.370 ⇒ 01:28:26.419 Uttam Kumaran: okay, I’m running a select.
583 01:28:37.150 ⇒ 01:28:44.609 Uttam Kumaran: I’m just gonna pick up. I’m gonna pick a day and I’m gonna find out which orders are getting marked as returning that aren’t returning in orders.
584 01:28:46.080 ⇒ 01:28:53.160 Uttam Kumaran: So select this from daily product metrics. Where is returning
585 01:28:58.130 ⇒ 01:29:06.160 Uttam Kumaran: and do Dpm and Dpm dot order id not in.
586 01:29:10.170 ⇒ 01:29:14.980 Uttam Kumaran: And we’re gonna select order id
587 01:29:24.660 ⇒ 01:29:31.440 Uttam Kumaran: where this and is 1st order
588 01:29:32.170 ⇒ 01:29:35.330 Uttam Kumaran: and not his 1st time. Order.
589 01:29:36.200 ⇒ 01:29:38.030 Uttam Kumaran: Alright! Let’s rip it.
590 01:30:07.580 ⇒ 01:30:10.290 Uttam Kumaran: Product, cog, space.
591 01:31:47.860 ⇒ 01:31:50.249 Uttam Kumaran: css.is returning.
592 01:32:05.640 ⇒ 01:32:07.500 Awaish Kumar: Do we need this now?
593 01:32:12.070 ⇒ 01:32:17.199 Awaish Kumar: Do we need this logic to spread out the cost.
594 01:32:20.440 ⇒ 01:32:25.229 Uttam Kumaran: Like. Why do we need it, or do we need it?
595 01:32:25.230 ⇒ 01:32:30.820 Awaish Kumar: Like do do we need it? Because now it is just increasing the spend?
596 01:32:31.160 ⇒ 01:32:34.249 Awaish Kumar: Because right now now, we all have all the.
597 01:32:36.200 ⇒ 01:32:38.339 Uttam Kumaran: I guess we don’t but like
598 01:32:38.480 ⇒ 01:32:40.390 Uttam Kumaran: when you do a full join.
599 01:32:41.160 ⇒ 01:32:44.689 Uttam Kumaran: it just comes in as null right? And then, just to spend values. Are there.
600 01:32:46.770 ⇒ 01:32:54.100 Awaish Kumar: Yeah, wherever there is an expand, value it for the date and product there will be some value. And if
601 01:32:54.320 ⇒ 01:32:55.290 Awaish Kumar: if there’s more.
602 01:32:55.639 ⇒ 01:32:56.690 Uttam Kumaran: It’ll be null.
603 01:32:59.140 ⇒ 01:33:03.340 Uttam Kumaran: But then, if we have a sum, if we have a sum in the next Ct, we’ll be okay. Right?
604 01:33:07.160 ⇒ 01:33:10.480 Uttam Kumaran: My group in the next Pt. Will be okay.
605 01:33:13.880 ⇒ 01:33:16.660 Awaish Kumar: Yeah. But this is a date on a product name. Right?
606 01:33:20.560 ⇒ 01:33:22.480 Uttam Kumaran: Yes, data and product name.
607 01:33:23.030 ⇒ 01:33:26.890 Awaish Kumar: My question is that right now, when we are doing a join?
608 01:33:27.365 ⇒ 01:33:33.919 Awaish Kumar: I’m getting the data on a date and a product name base on like, based on a date and a product name.
609 01:33:34.160 ⇒ 01:33:41.820 Awaish Kumar: And then the this logic, which is where you are trying to like, spread out the cost
610 01:33:42.450 ⇒ 01:33:45.579 Awaish Kumar: right. This is increasing. Some of our arrangement.
611 01:33:46.550 ⇒ 01:33:47.330 Uttam Kumaran: Yes.
612 01:33:48.250 ⇒ 01:33:54.030 Awaish Kumar: So I am asking, is this necessary now? Because because.
613 01:33:54.030 ⇒ 01:33:55.940 Uttam Kumaran: Because we’re not split. We’re not doing a split.
614 01:33:57.040 ⇒ 01:33:57.790 Awaish Kumar: Yeah.
615 01:34:00.470 ⇒ 01:34:02.600 Uttam Kumaran: Yeah, I guess it’s not.
616 01:34:08.490 ⇒ 01:34:12.749 Uttam Kumaran: But like, where like does it? Does it get attributed to any date?
617 01:34:15.530 ⇒ 01:34:16.200 Awaish Kumar: Date, yeah.
618 01:34:16.200 ⇒ 01:34:21.319 Uttam Kumaran: Like when you do the query, and you aggregate it when you, when you, when you aggregate this table.
619 01:34:21.420 ⇒ 01:34:26.260 Uttam Kumaran: does that spend? What does it get attributed to null product, name.
620 01:34:27.390 ⇒ 01:34:32.410 Awaish Kumar: Yeah, it will get attributed to like date and a product name, right?
621 01:34:33.010 ⇒ 01:34:36.070 Uttam Kumaran: But even though even the ones that you did a full join for.
622 01:34:36.990 ⇒ 01:34:38.410 Awaish Kumar: Yeah, yeah, that is also.
623 01:34:38.410 ⇒ 01:34:38.840 Uttam Kumaran: Okay.
624 01:34:38.840 ⇒ 01:34:39.340 Awaish Kumar: Hey! I do!
625 01:34:39.340 ⇒ 01:34:44.910 Uttam Kumaran: Then, yeah, then we’re good as long as we end up with the marketing category name, and then no nulls.
626 01:34:45.120 ⇒ 01:34:46.399 Uttam Kumaran: Then we’re fine.
627 01:34:48.030 ⇒ 01:34:50.090 Awaish Kumar: This one. Like, when we do this.
628 01:34:52.130 ⇒ 01:34:57.510 Awaish Kumar: yeah, when we are doing a full join, this is also takes care of
629 01:34:58.220 ⇒ 01:35:01.699 Awaish Kumar: because the join is basically on this, these 2
630 01:35:02.590 ⇒ 01:35:05.140 Awaish Kumar: things date and a product name.
631 01:35:05.670 ⇒ 01:35:07.969 Awaish Kumar: So these 2 are the key.
632 01:35:12.600 ⇒ 01:35:16.040 Robert Tseng: I’m lost on how we’re spent or we’re splitting the ad spend. Now.
633 01:35:16.861 ⇒ 01:35:19.589 Robert Tseng: if we take out that logic from before.
634 01:35:28.050 ⇒ 01:35:31.279 Uttam Kumaran: Yeah, I guess I want to see what the final table looks like a wish meaning.
635 01:35:31.650 ⇒ 01:35:34.799 Uttam Kumaran: I want to see marketing category
636 01:35:35.260 ⇒ 01:35:38.379 Uttam Kumaran: revenue ad spend. Can you run like a select like that?
637 01:35:39.230 ⇒ 01:35:41.000 Uttam Kumaran: That’s good. Then we’re okay.
638 01:35:46.570 ⇒ 01:35:47.190 Awaish Kumar: Well.
639 01:35:48.380 ⇒ 01:35:54.930 Robert Tseng: Like the logic that oasis trying to remove was to handle when there was no product.
640 01:35:55.100 ⇒ 01:36:01.849 Robert Tseng: category or like when there was no product category for the spend right? And then we would be using that to.
641 01:36:05.810 ⇒ 01:36:07.640 Uttam Kumaran: Yeah, that’s my question is like.
642 01:36:08.470 ⇒ 01:36:14.110 Uttam Kumaran: when this join doesn’t happen. The stuff that does go through with the full join Aish.
643 01:36:14.470 ⇒ 01:36:17.679 Uttam Kumaran: What are the other dimensions for those records.
644 01:36:21.050 ⇒ 01:36:22.170 Uttam Kumaran: You know what I mean.
645 01:36:22.170 ⇒ 01:36:25.449 Awaish Kumar: It. It has all these dimensions. Right? This is the.
646 01:36:25.730 ⇒ 01:36:30.879 Uttam Kumaran: I know. But just so just can you? Can you just run us a like meaning. But when you do a full join
647 01:36:31.040 ⇒ 01:36:34.670 Uttam Kumaran: the reason you’re doing a full join is so you’re bringing in results that don’t join.
648 01:36:35.510 ⇒ 01:36:36.500 Awaish Kumar: Right.
649 01:36:37.440 ⇒ 01:36:39.360 Uttam Kumaran: Those results that don’t join.
650 01:36:39.550 ⇒ 01:36:41.920 Uttam Kumaran: What are the dimensions for them? Are they all null?
651 01:36:44.830 ⇒ 01:36:47.020 Uttam Kumaran: Because then we’re then we’re not. We’re still not there.
652 01:36:50.680 ⇒ 01:36:51.750 Uttam Kumaran: see what I mean?
653 01:36:53.700 ⇒ 01:36:54.250 Awaish Kumar: Yes.
654 01:36:56.460 ⇒ 01:36:57.979 Uttam Kumaran: That’s why I split it up.
655 01:36:58.620 ⇒ 01:36:59.539 Uttam Kumaran: That’s why I basically.
656 01:36:59.540 ⇒ 01:36:59.870 Awaish Kumar: Okay.
657 01:36:59.870 ⇒ 01:37:03.569 Uttam Kumaran: Contributed all the remaining spend.
658 01:37:05.260 ⇒ 01:37:08.090 Uttam Kumaran: It’s just even beyond the ones I distributed.
659 01:37:09.790 ⇒ 01:37:11.889 Uttam Kumaran: There’s still some remaining.
660 01:37:12.460 ⇒ 01:37:13.130 Robert Tseng: Yeah.
661 01:37:15.360 ⇒ 01:37:18.300 Uttam Kumaran: Because there wasn’t any product or date that matched
662 01:37:19.080 ⇒ 01:37:22.740 Uttam Kumaran: other. The last thing yeah, the last thing you can do
663 01:37:23.820 ⇒ 01:37:30.660 Uttam Kumaran: is you can, you may, you may have luck writing a cte, that basically selects all the date. Add the date
664 01:37:30.930 ⇒ 01:37:37.860 Uttam Kumaran: product, spend combos that don’t join somehow weaving that back in.
665 01:37:39.970 ⇒ 01:37:44.499 Uttam Kumaran: And then, Robert, I found some ids that didn’t match. So I’m I’m just diagnosing.
666 01:37:45.810 ⇒ 01:37:46.430 Robert Tseng: Okay.
667 01:37:52.380 ⇒ 01:38:04.240 Uttam Kumaran: So this id is marked as true as returning, and then in order new
668 01:38:08.480 ⇒ 01:38:12.140 Uttam Kumaran: in order new, it’s marked as
669 01:38:13.630 ⇒ 01:38:16.189 Uttam Kumaran: returning. So what is this so
670 01:38:16.470 ⇒ 01:38:20.099 Uttam Kumaran: select? Where is returning, and the order id.
671 01:38:21.120 ⇒ 01:38:25.460 Robert Tseng: You want to share yours your time. I think it’s gone away so.
672 01:38:26.040 ⇒ 01:38:28.829 Awaish Kumar: Yeah, this. This is how it will look like after a full join.
673 01:38:28.830 ⇒ 01:38:31.720 Robert Tseng: Oh, okay, okay, yeah.
674 01:38:32.130 ⇒ 01:38:33.060 Robert Tseng: So.
675 01:38:33.910 ⇒ 01:38:34.700 Uttam Kumaran: We’re not there.
676 01:38:35.790 ⇒ 01:38:36.440 Robert Tseng: Yeah.
677 01:38:41.110 ⇒ 01:38:45.639 Awaish Kumar: Right now, like we want to. This, this is ad spend for these.
678 01:38:45.640 ⇒ 01:38:47.050 Uttam Kumaran: Yeah. But the thing is.
679 01:38:47.180 ⇒ 01:38:52.189 Uttam Kumaran: we’re looking at the summary, so we can’t have nulls in these product name categories.
680 01:38:59.370 ⇒ 01:39:04.680 Uttam Kumaran: The other thing you could do. Aish is, you can make sure that we have
681 01:39:06.170 ⇒ 01:39:12.630 Uttam Kumaran: a date and a product name for every category, for every day that way the join happens.
682 01:39:15.150 ⇒ 01:39:17.270 Robert Tseng: Yeah, I don’t care too much about doing like.
683 01:39:17.270 ⇒ 01:39:19.190 Uttam Kumaran: Actually, let’s do that. Yeah.
684 01:39:19.190 ⇒ 01:39:23.130 Robert Tseng: Let’s get it. If we just get this, at least for the past 6 months, I think that’ll be fine.
685 01:39:23.340 ⇒ 01:39:26.510 Uttam Kumaran: A wish. Can you try this? Can you make sure like.
686 01:39:26.780 ⇒ 01:39:32.090 Uttam Kumaran: can you create a spine? That’s date, product, name, and
687 01:39:32.360 ⇒ 01:39:37.230 Uttam Kumaran: have every product name available for every date, and use that as a spine. This will work, then
688 01:39:40.130 ⇒ 01:39:41.069 Uttam Kumaran: see what I mean.
689 01:39:42.900 ⇒ 01:39:46.490 Awaish Kumar: For every day. If we have the product names
690 01:39:50.040 ⇒ 01:39:53.390 Awaish Kumar: and then join with ads, so it will have a.
691 01:39:54.650 ⇒ 01:40:00.920 Uttam Kumaran: Make sure that every every product, name, and date combination is covered for the last like 3 years.
692 01:40:02.030 ⇒ 01:40:11.870 Uttam Kumaran: and then use that, join onto that. Join everything onto that that’ll work.
693 01:40:11.870 ⇒ 01:40:15.498 Awaish Kumar: These 2. There’s 2 tables like
694 01:40:19.390 ⇒ 01:40:25.269 Awaish Kumar: the ads campaign table and the orders table have different product names.
695 01:40:26.410 ⇒ 01:40:29.329 Awaish Kumar: Like this one. So we want to. How do we want to.
696 01:40:30.380 ⇒ 01:40:35.359 Uttam Kumaran: Then we need to update the we need to just update the Regex. Then.
697 01:40:41.540 ⇒ 01:40:43.380 Awaish Kumar: Okay, which which one is.
698 01:40:44.750 ⇒ 01:40:51.920 Uttam Kumaran: If you look at the you we would want. I thought we would want to update the Regex in product sales, summary
699 01:40:54.580 ⇒ 01:40:55.600 Uttam Kumaran: product sales summary.
700 01:40:55.600 ⇒ 01:40:55.930 Awaish Kumar: Doing.
701 01:40:55.930 ⇒ 01:40:57.959 Uttam Kumaran: Rejects to make the campaign name
702 01:40:58.890 ⇒ 01:41:05.120 Uttam Kumaran: match to the product sale product. So just make sure that anything that’s uncategorized gets matched. Yeah.
703 01:41:07.290 ⇒ 01:41:15.739 Uttam Kumaran: because the campaigns are not. Yeah. The campaigns are all over the place. So I just use the default, Regex, that we’ve been using.
704 01:41:17.930 ⇒ 01:41:18.680 Awaish Kumar: Okay.
705 01:42:05.780 ⇒ 01:42:09.039 Robert Tseng: Alright, I think this is gonna be done today.
706 01:43:15.670 ⇒ 01:43:18.170 Uttam Kumaran: I’m not seeing any missing ones.
707 01:43:40.950 ⇒ 01:43:45.109 Uttam Kumaran: and these are matching 0 0 1, 1, 1 1 0 0.
708 01:43:46.440 ⇒ 01:43:50.879 Uttam Kumaran: Everything’s going to new customer revenue. Everything’s going to 1st order.
709 01:43:54.430 ⇒ 01:43:55.380 Uttam Kumaran: I don’t know.
710 01:44:01.550 ⇒ 01:44:03.569 Uttam Kumaran: Feel like this. Looks pretty. Okay. I don’t know.
711 01:44:24.725 ⇒ 01:44:31.219 Robert Tseng: Mean what we saw. We saw where we are. We were where we were off.
712 01:44:36.410 ⇒ 01:44:38.580 Uttam Kumaran: New order account returning order account.
713 01:45:03.980 ⇒ 01:45:07.309 Uttam Kumaran: Oh, I mean, look, I don’t know. What are we talking about? Seems fine.
714 01:45:27.060 ⇒ 01:45:28.710 Uttam Kumaran: I mean, this looks okay.
715 01:45:30.300 ⇒ 01:45:41.850 Robert Tseng: Oh, yeah. Well, we were looking about the difference between the orders. So if you do that, okay, yep. And then. Now look at the sum of the new order count and the new or the returning order counts.
716 01:45:42.860 ⇒ 01:45:51.840 Robert Tseng: We were looking at the difference between the order counts and the customer counts and it and it was it looked pretty much the same, so that kinda
717 01:45:52.650 ⇒ 01:45:56.010 Robert Tseng: that kind of was seemed kind of off to me.
718 01:46:13.250 ⇒ 01:46:14.430 Uttam Kumaran: Oh, dude!
719 01:46:14.650 ⇒ 01:46:18.900 Uttam Kumaran: What’s the what’s the average order per that gap?
720 01:46:22.140 ⇒ 01:46:24.259 Uttam Kumaran: Are people ordering more than one thing.
721 01:46:34.310 ⇒ 01:46:35.070 Robert Tseng: Well.
722 01:46:35.070 ⇒ 01:46:35.790 Uttam Kumaran: Fine.
723 01:46:36.190 ⇒ 01:46:36.780 Robert Tseng: I don’t remember.
724 01:46:36.780 ⇒ 01:46:40.690 Robert Tseng: Imagine people are ordering more that often.
725 01:46:45.150 ⇒ 01:46:47.030 Uttam Kumaran: What this is saying is that
726 01:46:48.390 ⇒ 01:46:53.689 Uttam Kumaran: people order one. Most people are ordering one order.
727 01:47:00.970 ⇒ 01:47:02.459 Uttam Kumaran: This is what this is saying.
728 01:47:03.280 ⇒ 01:47:06.070 Uttam Kumaran: This doesn’t. This doesn’t indicate anything about like
729 01:47:06.350 ⇒ 01:47:13.150 Uttam Kumaran: this is showing that you’re only people ordering. What do people are doing? One order per per month.
730 01:47:16.060 ⇒ 01:47:20.739 Uttam Kumaran: whether they’re new or returning? Okay, I think I don’t think this is an issue.
731 01:47:23.030 ⇒ 01:47:24.138 Uttam Kumaran: Do you want me to?
732 01:47:25.490 ⇒ 01:47:26.869 Uttam Kumaran: Do you want me to walk through it?
733 01:47:27.760 ⇒ 01:47:30.020 Robert Tseng: I’m trying to process this.
734 01:47:30.750 ⇒ 01:47:40.269 Robert Tseng: Yeah, the new customers and matches the returning customers. It’s maybe off by a couple, because there will be like one or few customers that do place more than one order.
735 01:47:40.270 ⇒ 01:47:41.999 Uttam Kumaran: Correct in a given period.
736 01:47:42.000 ⇒ 01:47:50.219 Robert Tseng: But it’s not but that. Yeah, that make. Most people will not do that. Obviously, because they’re on a quarterly or or 6 monthly.
737 01:47:51.110 ⇒ 01:47:51.740 Uttam Kumaran: Yes.
738 01:47:55.100 ⇒ 01:47:58.790 Robert Tseng: Okay, yeah, I can. I can buy. I I think I would buy that.
739 01:47:59.160 ⇒ 01:48:00.389 Uttam Kumaran: It’s old.
740 01:48:00.974 ⇒ 01:48:05.439 Uttam Kumaran: But yeah, that’s that’s what it is. But I’m glad we went through the exercise. Okay, I was like.
741 01:48:06.210 ⇒ 01:48:11.140 Robert Tseng: Okay, no, we. We got confused because.
742 01:48:11.140 ⇒ 01:48:11.900 Uttam Kumaran: Yeah, yeah.
743 01:48:11.900 ⇒ 01:48:14.350 Robert Tseng: That was different. And we saw that.
744 01:48:15.246 ⇒ 01:48:21.069 Robert Tseng: Well, yeah, we knew that. Well, yeah, this is also saying that majority of orders are for maternity customers.
745 01:48:22.470 ⇒ 01:48:27.499 Robert Tseng: So that’s not that concerning that’s yeah. Okay.
746 01:48:27.770 ⇒ 01:48:32.199 Uttam Kumaran: It’s very close. But that’s because, like, yeah, people are only ordering one thing.
747 01:48:32.450 ⇒ 01:48:35.089 Robert Tseng: Okay, okay, I can buy that.
748 01:48:35.605 ⇒ 01:48:38.864 Uttam Kumaran: Okay, I wish, I think this is the last thing.
749 01:48:41.740 ⇒ 01:48:45.240 Uttam Kumaran: basically. What I said is, yeah, create the date spine.
750 01:48:46.640 ⇒ 01:48:49.269 Uttam Kumaran: Oh, yeah. The way you have it.
751 01:48:51.950 ⇒ 01:48:53.120 Uttam Kumaran: Good work.
752 01:48:56.910 ⇒ 01:48:59.130 Uttam Kumaran: I don’t think it’s I don’t know if it’s gonna work.
753 01:49:00.650 ⇒ 01:49:01.530 Awaish Kumar: Sorry, which.
754 01:49:01.530 ⇒ 01:49:03.770 Uttam Kumaran: To join to join it. Still isn’t gonna happen.
755 01:49:08.340 ⇒ 01:49:09.680 Uttam Kumaran: See what I mean. Like.
756 01:49:14.800 ⇒ 01:49:17.280 Awaish Kumar: Sorry. Where are you? Pointing.
757 01:49:17.509 ⇒ 01:49:20.720 Uttam Kumaran: If you scroll down like, if you go all the way to the end.
758 01:49:24.190 ⇒ 01:49:26.819 Uttam Kumaran: This join is still not gonna happen.
759 01:49:27.390 ⇒ 01:49:32.540 Uttam Kumaran: which means, even if you coalesce this, it it won’t matter.
760 01:49:33.010 ⇒ 01:49:36.200 Uttam Kumaran: What I’m saying is we should make make a cte. That’s.
761 01:49:36.200 ⇒ 01:49:37.860 Awaish Kumar: I just did that. I just did that.
762 01:49:37.860 ⇒ 01:49:39.079 Uttam Kumaran: Oh, okay. Yeah. Yeah. Perfect.
763 01:49:39.080 ⇒ 01:49:39.789 Awaish Kumar: This one.
764 01:49:40.080 ⇒ 01:49:40.770 Uttam Kumaran: Yeah.
765 01:49:41.120 ⇒ 01:49:44.009 Uttam Kumaran: So then, oh, okay. So then, okay, cool.
766 01:49:44.270 ⇒ 01:49:46.829 Uttam Kumaran: So then, date products fine, and you’re bringing it down here.
767 01:49:46.830 ⇒ 01:49:51.190 Awaish Kumar: Yeah, customer. Yeah, I’m trying to find this.
768 01:49:52.510 ⇒ 01:49:56.139 Awaish Kumar: Why, I’m getting an error of customer status.
769 01:49:56.850 ⇒ 01:49:58.230 Uttam Kumaran: Customer, success.
770 01:49:58.940 ⇒ 01:50:00.749 Awaish Kumar: I don’t know if I’m the wrong name.
771 01:50:04.430 ⇒ 01:50:06.170 Uttam Kumaran: Yeah. Yes.
772 01:50:06.170 ⇒ 01:50:07.600 Awaish Kumar: Custom status.
773 01:50:07.600 ⇒ 01:50:08.760 Awaish Kumar: See you, there’s no.
774 01:50:09.680 ⇒ 01:50:10.710 Uttam Kumaran: Let’s see it.
775 01:50:29.470 ⇒ 01:50:31.160 Uttam Kumaran: Are you still doing a full join?
776 01:50:32.750 ⇒ 01:50:35.221 Uttam Kumaran: Oh, this is 2020. Okay, yeah. So
777 01:50:35.880 ⇒ 01:50:39.159 Awaish Kumar: Yeah, but it shouldn’t matter, because I just.
778 01:50:39.910 ⇒ 01:50:42.789 Uttam Kumaran: No, no, but these, these are all old. So this is fine.
779 01:50:43.330 ⇒ 01:50:44.750 Uttam Kumaran: Just order this the other way.
780 01:50:44.750 ⇒ 01:50:46.060 Robert Tseng: Yeah, let’s order it the other way.
781 01:50:48.910 ⇒ 01:50:52.300 Uttam Kumaran: Yeah, okay, can we see this? Can we do the
782 01:50:53.070 ⇒ 01:50:57.699 Uttam Kumaran: can we do some day? Trunk month on the whole thing
783 01:51:03.460 ⇒ 01:51:10.604 Uttam Kumaran: like, instead of. So yeah, instead of select star, I just do select a trunk month, and then I just want to see revenue. And
784 01:51:12.180 ⇒ 01:51:12.900 Awaish Kumar: Yeah.
785 01:51:13.530 ⇒ 01:51:14.410 Uttam Kumaran: Yeah.
786 01:51:20.380 ⇒ 01:51:21.020 Awaish Kumar: Yeah.
787 01:51:28.930 ⇒ 01:51:30.250 Uttam Kumaran: Come on
788 01:51:33.760 ⇒ 01:51:35.420 Uttam Kumaran: Christmas miracle!
789 01:51:39.450 ⇒ 01:51:43.640 Robert Tseng: Wish I didn’t know you were based in Eastern Standard time. Sorry not to distract you.
790 01:51:46.800 ⇒ 01:51:49.580 Uttam Kumaran: Well he was now he’s back now he’s in Pakistan.
791 01:51:49.960 ⇒ 01:51:51.020 Robert Tseng: Oh, okay, okay.
792 01:51:51.020 ⇒ 01:51:53.920 Robert Tseng: God God knows what time it is.
793 01:51:55.870 ⇒ 01:52:01.479 Awaish Kumar: It is early 6 7 Am. In the morning. Now.
794 01:52:02.070 ⇒ 01:52:07.670 Uttam Kumaran: We caught you on a jet lag just what we needed. I needed the help today, Dude. I’ve been looking at this for 2 days.
795 01:52:09.890 ⇒ 01:52:11.470 Awaish Kumar: We can help
796 01:52:23.434 ⇒ 01:52:24.160 Awaish Kumar: fine.
797 01:52:27.340 ⇒ 01:52:28.299 Uttam Kumaran: You’re from.
798 01:52:36.410 ⇒ 01:52:37.070 Awaish Kumar: Long brother.
799 01:52:37.070 ⇒ 01:52:39.800 Uttam Kumaran: And then can you? Can you order? Can you order by one descending.
800 01:52:41.150 ⇒ 01:52:43.019 Awaish Kumar: Yeah. It’s just one month.
801 01:52:44.020 ⇒ 01:52:46.880 Uttam Kumaran: Oh, sorry. Sorry. Sorry. I didn’t know I didn’t see this. Okay, you’re good.
802 01:53:03.610 ⇒ 01:53:09.469 Uttam Kumaran: all right, can we? Can we get rid of the filter for a month.
803 01:53:12.960 ⇒ 01:53:15.699 Robert Tseng: And this just go back this one back to what it was before.
804 01:53:19.330 ⇒ 01:53:21.880 Uttam Kumaran: Why, this is 1.1 7 right?
805 01:53:22.210 ⇒ 01:53:25.009 Robert Tseng: Yeah, that’s what you were. That’s what we are at before
806 01:53:26.370 ⇒ 01:53:31.329 Robert Tseng: we’re trying to get 1.5 6, or what whatever.
807 01:53:31.440 ⇒ 01:53:32.980 Robert Tseng: Okay? Fine with me.
808 01:53:38.000 ⇒ 01:53:38.670 Robert Tseng: Yeah, we should.
809 01:53:38.670 ⇒ 01:53:41.349 Uttam Kumaran: Let’s just see all the let’s just see all the values.
810 01:53:41.350 ⇒ 01:53:44.550 Awaish Kumar: Yeah, okay, yeah, I’m.
811 01:53:47.460 ⇒ 01:53:51.619 Robert Tseng: Yeah, it should be 1.6 3 for January 2025.
812 01:53:52.910 ⇒ 01:53:56.779 Robert Tseng: That’s what a wish showed showed before. And that was right.
813 01:54:01.110 ⇒ 01:54:03.710 Robert Tseng: 1.1 7 was what you had in the.
814 01:54:03.710 ⇒ 01:54:07.089 Uttam Kumaran: Yeah, you, but I guess
815 01:54:12.070 ⇒ 01:54:14.090 Uttam Kumaran: you may have some null.
816 01:54:16.490 ⇒ 01:54:17.909 Uttam Kumaran: I don’t know. Let’s see.
817 01:54:25.770 ⇒ 01:54:29.680 Awaish Kumar: Right here. It’s getting the program name default
818 01:54:35.470 ⇒ 01:54:37.050 Awaish Kumar: this time.
819 01:54:41.230 ⇒ 01:54:44.980 Awaish Kumar: Okay, here is, I think, is probably what we are doing wrong.
820 01:54:46.380 ⇒ 01:54:50.279 Awaish Kumar: You should join, join it also with the product name. Now, right.
821 01:55:04.520 ⇒ 01:55:06.139 Uttam Kumaran: And give it a shot.
822 01:55:10.490 ⇒ 01:55:11.979 Awaish Kumar: Will basically join me.
823 01:55:12.150 ⇒ 01:55:13.920 Awaish Kumar: The rows where it is.
824 01:55:28.193 ⇒ 01:55:33.086 Robert Tseng: I’m sorry. I’m just like I’ve been. I’m hallucinating.
825 01:56:21.760 ⇒ 01:56:23.729 Uttam Kumaran: Oh, wait! Can you send me this query, too?
826 01:56:43.434 ⇒ 01:56:48.999 Uttam Kumaran: If you go, if you click on the plus on the bottom left, you can add like a
827 01:56:49.410 ⇒ 01:56:58.119 Uttam Kumaran: snippet text snippet. Yeah, yeah. You just paste and send it. It’ll be okay.
828 01:57:10.680 ⇒ 01:57:11.290 Awaish Kumar: Alright!
829 01:57:11.948 ⇒ 01:57:13.540 Awaish Kumar: Here we don’t have.
830 01:57:42.890 ⇒ 01:57:46.859 Uttam Kumaran: I mean, Robert, would they be pissed if we just put into unattributed.
831 01:57:54.100 ⇒ 01:57:56.229 Robert Tseng: It’s 20% unattributed.
832 01:58:01.470 ⇒ 01:58:08.209 Robert Tseng: Let me, how would we defend it? Basically saying, like, there is no campaign
833 01:58:08.350 ⇒ 01:58:12.010 Robert Tseng: that was on that day that we could map these the spend to
834 01:58:15.500 ⇒ 01:58:17.400 Robert Tseng: how would that make sense, though, you know.
835 01:58:17.720 ⇒ 01:58:20.910 Robert Tseng: or like the spend here? Like, yeah, like.
836 01:58:21.320 ⇒ 01:58:24.190 Uttam Kumaran: Well, there were no products sold on that day.
837 01:58:25.700 ⇒ 01:58:28.300 Uttam Kumaran: Yeah, there were no products sold on that day
838 01:58:28.710 ⇒ 01:58:32.329 Uttam Kumaran: that matched the campaigns that we were spending on that day also.
839 01:58:34.630 ⇒ 01:58:35.190 Robert Tseng: The other.
840 01:58:35.568 ⇒ 01:58:41.999 Robert Tseng: Not every campaign, not every dollar we spend gets, like, you know, spent to the right place.
841 01:58:54.210 ⇒ 01:58:57.779 Robert Tseng: 20% can I live with 20%
842 01:58:57.990 ⇒ 01:59:01.709 Uttam Kumaran: The other thing we can do awaish is, maybe we can.
843 01:59:06.700 ⇒ 01:59:13.619 Uttam Kumaran: No. Can we increase the date range that we do the join for.
844 01:59:18.840 ⇒ 01:59:19.840 Awaish Kumar: Okay.
845 01:59:20.730 ⇒ 01:59:24.250 Uttam Kumaran: Like, can we join on like the last 3 days worth of data?
846 01:59:26.390 ⇒ 01:59:28.699 Uttam Kumaran: I don’t know if that really solves anything.
847 01:59:48.980 ⇒ 01:59:51.940 Awaish Kumar: I’m not sure. Why is it missing? It should not.
848 01:59:54.190 ⇒ 01:59:57.269 Robert Tseng: Yeah, guys, let’s let’s just let’s just call it unattributed.
849 01:59:58.860 ⇒ 01:59:59.480 Uttam Kumaran: Okay.
850 02:00:00.090 ⇒ 02:00:00.720 Robert Tseng: Yeah.
851 02:00:02.290 ⇒ 02:00:12.280 Uttam Kumaran: I think that’s best, and I think it’s worth having the conversation to to figure out. At least we’ll get all the sums away. Can we just do? Can I? Can we just do the full join?
852 02:00:12.790 ⇒ 02:00:13.900 Uttam Kumaran: And then
853 02:00:16.150 ⇒ 02:00:16.840 Robert Tseng: How you doing
854 02:00:17.320 ⇒ 02:00:24.240 Robert Tseng: if if we could have the one where the version that a wish had before, I don’t know if it was actually.
855 02:00:24.490 ⇒ 02:00:31.150 Robert Tseng: yeah, we’re we did like, actually assign every dollar versus what happens when we when we leave some unattributed.
856 02:00:31.260 ⇒ 02:00:35.129 Robert Tseng: I wanna be able to show that comparison and be like.
857 02:00:35.740 ⇒ 02:00:38.329 Robert Tseng: this is how the yeah, like.
858 02:00:39.190 ⇒ 02:00:39.840 Uttam Kumaran: Yes!
859 02:00:40.770 ⇒ 02:00:42.549 Robert Tseng: Yeah, if you can.
860 02:00:42.550 ⇒ 02:00:44.739 Uttam Kumaran: Wish. If you send me both versions.
861 02:00:45.540 ⇒ 02:00:52.600 Uttam Kumaran: I’m gonna I’m gonna I’m gonna publish the one that puts it into uncategorized, and then I can keep the other one.
862 02:00:55.270 ⇒ 02:00:58.439 Awaish Kumar: I’ve sent this one, I can send you the other one.
863 02:00:59.100 ⇒ 02:01:01.569 Uttam Kumaran: Yeah. If you just want to send me
864 02:01:02.240 ⇒ 02:01:07.639 Uttam Kumaran: which one where I can do the full join or just highlight, like what I need to change to enable the full join.
865 02:01:08.440 ⇒ 02:01:09.710 Uttam Kumaran: I can do that.
866 02:01:13.950 ⇒ 02:01:17.690 Uttam Kumaran: or should I just full join on it right now and then just coalesce.
867 02:01:19.350 ⇒ 02:01:20.919 Awaish Kumar: Think. Yes, it will do that.
868 02:01:22.100 ⇒ 02:01:34.080 Uttam Kumaran: Right like I’ll full join campaign, spend Pre, and then I’ll coalesce product names to uncategorize.
869 02:01:34.080 ⇒ 02:01:38.519 Awaish Kumar: It’s just here. I think we can do this full joint.
870 02:01:39.930 ⇒ 02:01:46.270 Uttam Kumaran: Yeah, and then I’ll coalesce. I’ll coalesce I’ll coalesce everything.
871 02:01:47.840 ⇒ 02:01:51.630 Uttam Kumaran: Okay, let me try it. I’m gonna do in staging, and then just tell me what it looks like.
872 02:02:32.520 ⇒ 02:02:33.210 Uttam Kumaran: Okay.
873 02:02:40.050 ⇒ 02:02:43.910 Uttam Kumaran: alright. Let me let me do the. Let me try to get the sums.
874 02:02:48.550 ⇒ 02:02:49.080 Awaish Kumar: Oh.
875 02:03:47.897 ⇒ 02:03:49.870 Awaish Kumar: share the Kerry.
876 02:03:51.030 ⇒ 02:03:54.720 Uttam Kumaran: Yeah, let me just run this. See if I get anything.
877 02:03:56.260 ⇒ 02:04:00.360 Uttam Kumaran: Is this, was this, was this it or no? This isn’t it?
878 02:04:01.060 ⇒ 02:04:02.751 Uttam Kumaran: This is what I did.
879 02:04:03.920 ⇒ 02:04:09.289 Uttam Kumaran: Oh, wait! Never mind marketing product. Name not found with side css, so.
880 02:04:09.380 ⇒ 02:04:10.668 Robert Tseng: Write this message and.
881 02:04:10.990 ⇒ 02:04:12.049 Uttam Kumaran: So less
882 02:04:14.040 ⇒ 02:04:15.319 Robert Tseng: Sorry. I’m just talking to myself.
883 02:04:16.630 ⇒ 02:04:18.710 Uttam Kumaran: Uncategorized
884 02:04:25.010 ⇒ 02:04:26.859 Uttam Kumaran: like this. Right? Oish.
885 02:04:28.150 ⇒ 02:04:32.310 Awaish Kumar: Actually, I did this separately. I don’t know.
886 02:04:34.200 ⇒ 02:04:36.429 Awaish Kumar: I can share it.
887 02:04:36.760 ⇒ 02:04:37.440 Uttam Kumaran: Yeah.
888 02:04:45.410 ⇒ 02:04:46.930 Awaish Kumar: That is inclusive.
889 02:05:04.010 ⇒ 02:05:19.110 Awaish Kumar: Sorry it’s just scroll down it’s daily metrics inside of a yeah manage.
890 02:05:25.520 ⇒ 02:05:26.770 Awaish Kumar: does it have.
891 02:05:27.640 ⇒ 02:05:28.610 Uttam Kumaran: How does this look.
892 02:05:35.640 ⇒ 02:05:37.300 Awaish Kumar: I’m not sure I.
893 02:05:41.290 ⇒ 02:05:43.129 Uttam Kumaran: Robert, what do you think about this.
894 02:05:45.570 ⇒ 02:05:49.510 Robert Tseng: Yo sorry I was just writing. What’s up.
895 02:05:49.830 ⇒ 02:05:51.140 Uttam Kumaran: I think this is. I think this is it?
896 02:05:55.374 ⇒ 02:05:59.509 Robert Tseng: Yeah, this is it, for if you were to attribute everything right.
897 02:06:01.120 ⇒ 02:06:01.770 Uttam Kumaran: Yeah.
898 02:06:01.990 ⇒ 02:06:03.740 Uttam Kumaran: So if we break it down
899 02:06:17.090 ⇒ 02:06:17.890 Uttam Kumaran: alright.
900 02:06:25.150 ⇒ 02:06:26.810 Uttam Kumaran: did I just lose this?
901 02:06:36.700 ⇒ 02:06:38.360 Uttam Kumaran: Oh, my God!
902 02:06:40.840 ⇒ 02:06:42.049 Uttam Kumaran: T. Okay.
903 02:06:48.800 ⇒ 02:06:50.030 Uttam Kumaran: Revenue
904 02:06:55.150 ⇒ 02:06:58.569 Uttam Kumaran: 60, thou 60,000 to uncategorized.
905 02:07:02.310 ⇒ 02:07:04.179 Uttam Kumaran: That’s not because
906 02:07:07.320 ⇒ 02:07:10.709 Uttam Kumaran: okay, I think, like the way it is will work.
907 02:07:11.000 ⇒ 02:07:12.599 Uttam Kumaran: I think we’re good.
908 02:07:15.830 ⇒ 02:07:16.430 Robert Tseng: Yep.
909 02:07:21.150 ⇒ 02:07:25.540 Uttam Kumaran: Oish! The only thing I’m noticing here is there’s there’s a standardized product name
910 02:07:32.800 ⇒ 02:07:41.949 Uttam Kumaran: like, there’s something in this query that’s not working out.
911 02:07:46.080 ⇒ 02:07:51.219 Uttam Kumaran: I’m just gonna check this one last time, and then we’ll call this a day.
912 02:08:49.440 ⇒ 02:08:54.630 Uttam Kumaran: So what I’m doing here is looking at the campaign names that are uncategorized.
913 02:09:09.890 ⇒ 02:09:13.970 Uttam Kumaran: All of these are uncategorized. What the fuck are these?
914 02:09:21.980 ⇒ 02:09:22.924 Uttam Kumaran: Okay?
915 02:09:26.960 ⇒ 02:09:29.380 Uttam Kumaran: yeah. I guess I don’t even know how to. I don’t know how to categor.
916 02:09:29.380 ⇒ 02:09:38.730 Robert Tseng: Some of these campaigns are probably Hella old, and that’s fine. We just like, you know, there’s not a real those. Those are not like account. Creation. Welcome flow! That’s not a re. That’s not a recent campaign.
917 02:09:39.460 ⇒ 02:09:41.269 Uttam Kumaran: No, I think some of these are recent.
918 02:09:46.710 ⇒ 02:09:52.089 Uttam Kumaran: Let’s see, can tell you when the spin happened
919 02:09:58.470 ⇒ 02:10:00.320 Uttam Kumaran: 2025, 1, 19.
920 02:10:01.020 ⇒ 02:10:05.109 Robert Tseng: That’s like Reddit, I mean, we probably we put like nothing into Reddit, right?
921 02:10:06.070 ⇒ 02:10:08.280 Robert Tseng: They’re just testing that out like whatever.
922 02:10:11.750 ⇒ 02:10:13.589 Uttam Kumaran: Okay, well, let me. Here.
923 02:10:32.170 ⇒ 02:10:34.289 Uttam Kumaran: video winners.
924 02:10:35.290 ⇒ 02:10:40.310 Robert Tseng: We can’t categorize. Some of these, like some of them, have the product names in there ter Sam. I see.
925 02:10:41.180 ⇒ 02:10:43.339 Uttam Kumaran: Yeah. So that’s what I’m gonna I’m gonna
926 02:10:45.640 ⇒ 02:10:47.479 Uttam Kumaran: Okay, well, here’s what I’m gonna do.
927 02:11:21.750 ⇒ 02:11:31.450 Uttam Kumaran: 935, okay, and spend greater than let’s just say 10 k.
928 02:11:34.760 ⇒ 02:11:42.199 Uttam Kumaran: okay, so can you just tell me real quick what these are gonna go to like. So this one.
929 02:11:47.020 ⇒ 02:11:50.499 Robert Tseng: That should be ters terzepatide and and semaglutide.
930 02:11:59.660 ⇒ 02:12:01.709 Uttam Kumaran: We just have them separately.
931 02:12:04.190 ⇒ 02:12:10.700 Robert Tseng: Yeah, like, I guess that’s 1 of those campaigns that it had 2 products in it like, can we not split it up?
932 02:12:18.320 ⇒ 02:12:26.380 Robert Tseng: It’s fine. We don’t have to worry about it. I will just put it out as like, hey, these are the 3 campaigns that are like that go into uncat that are not categorized.
933 02:12:29.850 ⇒ 02:12:35.909 Uttam Kumaran: Okay, I’m gonna give you this list. This would be everything. Above is everything above $1,000. That’s not categorized.
934 02:12:36.170 ⇒ 02:12:39.460 Uttam Kumaran: All of these look like either weird or.
935 02:12:42.300 ⇒ 02:12:48.049 Robert Tseng: Well, Comp Sema is compound semaglutide. That’s just the injectable semaglutide. We should be able to categorize that.
936 02:12:48.050 ⇒ 02:12:51.239 Uttam Kumaran: Let me hold on. Let me make. Let me just make that happen then.
937 02:12:56.042 ⇒ 02:13:00.790 Uttam Kumaran: So it’s it’s it’s just.
938 02:13:00.790 ⇒ 02:13:04.060 Robert Tseng: Not injectable. Sorry it should be oral, then. Yeah.
939 02:13:04.830 ⇒ 02:13:05.970 Uttam Kumaran: This, one, okay.
940 02:13:06.160 ⇒ 02:13:06.690 Robert Tseng: Yep.
941 02:13:09.780 ⇒ 02:13:10.500 Uttam Kumaran: Oh.
942 02:13:18.130 ⇒ 02:13:22.730 Uttam Kumaran: then terzapatide.
943 02:13:28.820 ⇒ 02:13:29.360 Robert Tseng: Yep.
944 02:13:32.220 ⇒ 02:13:33.140 Uttam Kumaran: Oh!
945 02:13:39.860 ⇒ 02:13:41.760 Robert Tseng: I have a question, but I don’t want to distract you.
946 02:13:41.920 ⇒ 02:13:42.830 Uttam Kumaran: Yeah, please.
947 02:13:43.526 ⇒ 02:13:50.439 Robert Tseng: We. We looked at something earlier today where I was like you corrected me, and it wasn’t. We weren’t at. It was like we were like, 50%
948 02:13:50.710 ⇒ 02:13:57.849 Robert Tseng: of spend was not like, Oh, 50% of orders don’t have you last to Utm.
949 02:13:58.710 ⇒ 02:13:59.549 Robert Tseng: Was that what it was.
950 02:13:59.860 ⇒ 02:14:04.640 Uttam Kumaran: Yes, don’t have a last utm. Yep.
951 02:14:05.730 ⇒ 02:14:13.540 Robert Tseng: Yep, and to. And and so what we’ve done, which basically narrowed it down.
952 02:14:14.110 ⇒ 02:14:20.489 Robert Tseng: So we went from 50%. And now we we have 20% uncategorized revenue. So we cut it down by 30%
953 02:14:21.120 ⇒ 02:14:29.430 Robert Tseng: by using, like our approach to matching on campaign date.
954 02:14:29.810 ⇒ 02:14:34.749 Uttam Kumaran: Matching on product names, matching on campaign names and dates.
955 02:14:35.500 ⇒ 02:14:37.169 Uttam Kumaran: And then basically likes.
956 02:14:39.010 ⇒ 02:14:40.789 Uttam Kumaran: Yeah, that’s basically it.
957 02:14:41.810 ⇒ 02:14:43.400 Robert Tseng: Yeah, okay.
958 02:14:59.010 ⇒ 02:15:00.810 Uttam Kumaran: What is what is drip?
959 02:15:01.320 ⇒ 02:15:02.299 Uttam Kumaran: Oh, okay.
960 02:15:02.300 ⇒ 02:15:06.630 Robert Tseng: That’s an agency. That’s that’s those are the guys that are hounding us.
961 02:15:07.296 ⇒ 02:15:11.259 Uttam Kumaran: Yo, what the fuck get your own fucking data? Fuck.
962 02:15:11.880 ⇒ 02:15:12.460 Robert Tseng: Yeah.
963 02:15:20.750 ⇒ 02:15:23.810 Robert Tseng: Handling orders.
964 02:15:49.980 ⇒ 02:15:52.000 Uttam Kumaran: Alright! Let’s see where we’re at.
965 02:16:13.320 ⇒ 02:16:14.320 Robert Tseng: Bless you!
966 02:16:17.670 ⇒ 02:16:19.300 Uttam Kumaran: Okay, yeah, we got better.
967 02:16:23.210 ⇒ 02:16:24.340 Robert Tseng: How much left.
968 02:16:25.350 ⇒ 02:16:26.260 Uttam Kumaran: Like.
969 02:16:27.420 ⇒ 02:16:30.709 Uttam Kumaran: Hold on! Let me just show you exactly what’s left
970 02:16:33.889 ⇒ 02:16:35.849 Uttam Kumaran: injectable, Sema. All the way.
971 02:17:20.520 ⇒ 02:17:28.610 Uttam Kumaran: Eden Brand search exact sf, drip Asc. Ter Sema. Comp. Sema.
972 02:17:30.510 ⇒ 02:17:31.410 Robert Tseng: I’m semi.
973 02:17:31.410 ⇒ 02:17:34.120 Uttam Kumaran: Make sure that anything with someone needs to get in here.
974 02:17:34.730 ⇒ 02:17:35.370 Robert Tseng: Yeah.
975 02:17:35.910 ⇒ 02:17:37.900 Uttam Kumaran: Sent to oral. Semi. Right? Okay?
976 02:17:38.580 ⇒ 02:17:39.150 Robert Tseng: Yep.
977 02:17:44.440 ⇒ 02:17:46.509 Robert Tseng: Yeah. Comp. Sema should be oral.
978 02:17:47.780 ⇒ 02:17:48.879 Uttam Kumaran: Oh, really.
979 02:17:49.790 ⇒ 02:17:51.360 Robert Tseng: Right? Isn’t that what we said.
980 02:17:55.200 ⇒ 02:17:57.030 Uttam Kumaran: As long as it gets in somewhere. It’s.
981 02:18:03.110 ⇒ 02:18:07.080 Robert Tseng: Yeah. And then we’re, I guess gummies would be important. We’re missing gummies here.
982 02:18:07.440 ⇒ 02:18:09.100 Uttam Kumaran: Yeah, we got gummies here.
983 02:18:14.990 ⇒ 02:18:16.000 Uttam Kumaran: cool.
984 02:18:17.180 ⇒ 02:18:20.589 Robert Tseng: Wait. The the Regex previously didn’t catch this. What the heck.
985 02:18:21.190 ⇒ 02:18:30.239 Uttam Kumaran: Regex is. So it’s just like I will convert these to better later, because it’s a Regex is kind of hard for documentation. It does a good job.
986 02:18:30.340 ⇒ 02:18:33.129 Uttam Kumaran: and then sometimes it doesn’t catch it all.
987 02:18:33.940 ⇒ 02:18:37.119 Robert Tseng: It’s possible that we were not catching as much as Rob’s did, because that.
988 02:18:37.120 ⇒ 02:18:41.009 Uttam Kumaran: No, no, no, no, no way. Our regex is way. Beefier.
989 02:18:41.730 ⇒ 02:18:47.569 Uttam Kumaran: Yeah. Our all our edgics is way beefier, like I have so many cases that I’m that I’m going after.
990 02:18:48.360 ⇒ 02:18:49.370 Robert Tseng: Okay. Okay.
991 02:18:49.379 ⇒ 02:18:55.849 Uttam Kumaran: And we did a little dude. We did a I did a lot of work on this product mapping sheet. Oh, it’s filtered now, but like.
992 02:18:56.169 ⇒ 02:19:02.239 Uttam Kumaran: yeah, no, ours is ours is much more robust. There’s just always going to be like a couple that just trickled out.
993 02:19:02.499 ⇒ 02:19:03.699 Robert Tseng: Okay.
994 02:19:04.499 ⇒ 02:19:12.469 Uttam Kumaran: So anything with Sema. I’m going to put into injectable Sema at the end. Here
995 02:19:15.959 ⇒ 02:19:18.179 Uttam Kumaran: it’s a last ditch resort.
996 02:19:23.459 ⇒ 02:19:25.269 Uttam Kumaran: Why, the fuck is this? Not
997 02:19:31.239 ⇒ 02:19:32.379 Uttam Kumaran: what?
998 02:19:41.979 ⇒ 02:19:42.789 Uttam Kumaran: Oh.
999 02:19:47.599 ⇒ 02:19:48.459 Uttam Kumaran: I know.
1000 02:20:00.869 ⇒ 02:20:04.949 Uttam Kumaran: Alright, cool couple more, any of these.
1001 02:20:07.190 ⇒ 02:20:20.659 Robert Tseng: So I think, for the uncategorized ones like I see brands exact search up there, so that to me is like a just a more general brand awareness campaign that may have led to orders. So that’s like a good way to like
1002 02:20:21.190 ⇒ 02:20:23.675 Robert Tseng: give attribution to the brand side.
1003 02:20:24.270 ⇒ 02:20:32.980 Robert Tseng: and I’m assuming like lead, retargeting, and whatever like I mean, we could just every day, plus it should have gone into everyday plus obviously.
1004 02:20:32.980 ⇒ 02:20:34.030 Uttam Kumaran: Which? Where is that?
1005 02:20:34.970 ⇒ 02:20:36.030 Robert Tseng: Row, 20.
1006 02:20:38.150 ⇒ 02:20:38.700 Uttam Kumaran: Okay.
1007 02:20:39.160 ⇒ 02:20:39.890 Robert Tseng: Yeah.
1008 02:20:40.110 ⇒ 02:20:45.916 Uttam Kumaran: Yeah, it’s okay. I wanna let me. I want to take care of all the low hanging fruit ones. And then I’m gonna give you.
1009 02:20:47.840 ⇒ 02:20:51.900 Uttam Kumaran: and then I can. You can pick the rest for examples.
1010 02:20:52.370 ⇒ 02:20:53.020 Robert Tseng: Okay.
1011 02:21:03.920 ⇒ 02:21:04.580 Robert Tseng: Nope.
1012 02:21:43.310 ⇒ 02:21:44.540 Uttam Kumaran: Ters.
1013 02:21:47.600 ⇒ 02:21:48.910 Uttam Kumaran: take that.
1014 02:22:20.490 ⇒ 02:22:22.340 Uttam Kumaran: any of these ring a bell.
1015 02:22:27.940 ⇒ 02:22:32.559 Robert Tseng: I’m only really looking at the big buckets here. I don’t really care about the $1,000 ones at this point.
1016 02:22:34.200 ⇒ 02:22:37.270 Uttam Kumaran: So it’ll be, Sema. That’s it. Looks like that’s it.
1017 02:22:39.450 ⇒ 02:22:43.049 Robert Tseng: Yeah, let’s let’s give that to Sema, or else we go to Sema.
1018 02:22:43.050 ⇒ 02:22:43.780 Uttam Kumaran: Okay.
1019 02:22:45.930 ⇒ 02:22:49.610 Robert Tseng: The hell is Dpa? I don’t know off the top of my head, and I don’t really care.
1020 02:22:50.190 ⇒ 02:22:51.080 Robert Tseng: Alright. That’s fine.
1021 02:22:51.080 ⇒ 02:22:52.340 Uttam Kumaran: Alright cool.
1022 02:22:52.960 ⇒ 02:22:54.640 Uttam Kumaran: I’m gonna push this.
1023 02:22:54.640 ⇒ 02:23:03.590 Robert Tseng: What’s the total on that or or this is all time. Huh? Okay, now, I want it to be like, okay, this is now uncategorized, 10% or 15%.
1024 02:23:04.880 ⇒ 02:23:06.659 Uttam Kumaran: I mean, I can. Yeah.
1025 02:23:59.790 ⇒ 02:24:04.899 Uttam Kumaran: yeah, this is gonna be the one top brand campaign. But otherwise we look really good.
1026 02:24:06.620 ⇒ 02:24:09.539 Uttam Kumaran: There’s some sort of lingering stuff. But
1027 02:24:57.080 ⇒ 02:25:01.610 Uttam Kumaran: okay, we are still very solid on the numbers.
1028 02:25:03.619 ⇒ 02:25:04.469 Uttam Kumaran: So.
1029 02:25:04.470 ⇒ 02:25:07.083 Robert Tseng: Okay. Sorry I didn’t see the number for
1030 02:25:08.850 ⇒ 02:25:13.260 Robert Tseng: What are we at now? Oh, oh, yeah, I mean, it adds up, okay, but sure.
1031 02:25:15.170 ⇒ 02:25:20.071 Robert Tseng: And the F 0 is okay. Does that? How much we didn’t? No, that’s not. That’s just
1032 02:25:20.510 ⇒ 02:25:21.889 Uttam Kumaran: No, that’s nothing. Yeah.
1033 02:25:22.100 ⇒ 02:25:24.099 Robert Tseng: Okay, basically, everything’s in there.
1034 02:25:25.273 ⇒ 02:25:34.610 Robert Tseng: Okay? Well, I’ll I’ll find out what or it’d be great to just see of January. What was uncategorized like is, what share of that.
1035 02:25:35.500 ⇒ 02:25:36.006 Uttam Kumaran: I can.
1036 02:25:36.260 ⇒ 02:25:38.209 Robert Tseng: I’m doing that in my write up.
1037 02:26:41.760 ⇒ 02:26:44.060 Robert Tseng: Oh, you’re running that for me. Oh, okay, thanks.
1038 02:26:45.320 ⇒ 02:26:47.010 Uttam Kumaran: No problem.
1039 02:26:50.340 ⇒ 02:26:55.500 Robert Tseng: 3, 7, 1 damn!
1040 02:26:56.850 ⇒ 02:26:59.585 Robert Tseng: That’s like 20%.
1041 02:27:00.270 ⇒ 02:27:00.940 Uttam Kumaran: Basically.
1042 02:27:01.410 ⇒ 02:27:02.020 Robert Tseng: Yeah.
1043 02:27:05.260 ⇒ 02:27:07.050 Uttam Kumaran: Well, this is wait, hold on
1044 02:27:10.410 ⇒ 02:27:12.699 Uttam Kumaran: alright, these are not in order anymore.
1045 02:27:20.120 ⇒ 02:27:20.920 Uttam Kumaran: Yeah.
1046 02:27:21.900 ⇒ 02:27:22.480 Robert Tseng: Yeah.
1047 02:27:28.590 ⇒ 02:27:32.969 Uttam Kumaran: I will. I’m gonna send you the screenshot, and I’ll also thread the query. So you don’t.
1048 02:27:33.830 ⇒ 02:27:34.470 Uttam Kumaran: So you have it.
1049 02:27:34.470 ⇒ 02:27:34.990 Robert Tseng: Thanks.
1050 02:27:45.390 ⇒ 02:27:48.649 Uttam Kumaran: And then I’m also going to send you
1051 02:27:49.180 ⇒ 02:27:54.150 Uttam Kumaran: the queries that we couldn’t categorize that are over a thousand dollars.
1052 02:28:04.430 ⇒ 02:28:05.500 Uttam Kumaran: Come on
1053 02:28:45.590 ⇒ 02:28:49.470 Uttam Kumaran: alright. And then the this code is all in Npr, basically.
1054 02:28:50.690 ⇒ 02:28:51.310 Robert Tseng: Okay.
1055 02:29:20.330 ⇒ 02:29:25.729 Uttam Kumaran: I said, this looks great. You’re like this doesn’t look great.
1056 02:29:27.360 ⇒ 02:29:30.320 Robert Tseng: Well, yeah, I was like it. Just okay, whatever.
1057 02:29:32.150 ⇒ 02:29:32.870 Robert Tseng: And then.
1058 02:29:32.870 ⇒ 02:29:36.609 Uttam Kumaran: I called Jacob. He didn’t. He didn’t indicate that he had any clue about. Like
1059 02:29:38.290 ⇒ 02:29:42.179 Uttam Kumaran: he he! I think he just added random shit like. I think he just added what he felt like.
1060 02:29:42.480 ⇒ 02:29:45.140 Robert Tseng: Yeah, he has no idea. But whatever it’s fine.
1061 02:29:46.200 ⇒ 02:29:48.671 Robert Tseng: it’s not fine, but like I’m not saying.
1062 02:29:49.730 ⇒ 02:29:50.360 Uttam Kumaran: Okay.
1063 02:29:54.470 ⇒ 02:29:57.129 Robert Tseng: Okay. So you pushed it to staging or to production.
1064 02:29:57.560 ⇒ 02:30:01.310 Uttam Kumaran: Than staging fuck. Okay, all right.
1065 02:30:01.310 ⇒ 02:30:02.750 Robert Tseng: Why do you want me to do it?
1066 02:30:03.670 ⇒ 02:30:09.206 Robert Tseng: Well, no cause I’m gonna have to go and build out that station. Dash, and then, blah blah! I’m just like
1067 02:30:10.560 ⇒ 02:30:11.710 Uttam Kumaran: I can.
1068 02:30:12.410 ⇒ 02:30:15.220 Robert Tseng: It’s gonna take me like another 30 min, probably.
1069 02:30:17.640 ⇒ 02:30:20.500 Uttam Kumaran: I’m not. I just don’t really don’t want to touch anything.
1070 02:30:23.790 ⇒ 02:30:26.835 Robert Tseng: No, no, I’ll I’m gonna do it. I know how to do it.
1071 02:30:29.280 ⇒ 02:30:39.199 Robert Tseng: okay. But but once it’s in staging and I approve it. Then we’re gonna push to prod. And then we need to update the prod. One, too, which I don’t want to do. That which is, I’ll just have Zack do that? Okay, yeah.
1072 02:30:39.750 ⇒ 02:30:40.570 Robert Tseng: alright.
1073 02:30:41.370 ⇒ 02:30:47.950 Robert Tseng: Alright. I’ll suck it up and just finish this. Yeah, there we go.
1074 02:30:48.600 ⇒ 02:30:49.380 Robert Tseng: It’s good.
1075 02:30:50.270 ⇒ 02:30:50.980 Uttam Kumaran: Okay.
1076 02:30:53.530 ⇒ 02:30:56.890 Uttam Kumaran: Alright, I’m gonna I’m gonna leave the house for the 1st time today.
1077 02:30:57.320 ⇒ 02:30:58.500 Robert Tseng: Yeah, you should.
1078 02:30:59.910 ⇒ 02:31:03.180 Uttam Kumaran: Okay, I mean good progress on this.
1079 02:31:03.670 ⇒ 02:31:12.309 Uttam Kumaran: I behind on some other stuff. But you know, it is what it is.
1080 02:31:13.260 ⇒ 02:31:16.009 Robert Tseng: Yeah, dude. Just go go for a walk or something.
1081 02:31:16.210 ⇒ 02:31:16.920 Uttam Kumaran: Yeah.
1082 02:31:17.220 ⇒ 02:31:22.220 Uttam Kumaran: Alright. Alright. Thanks away so much, you know. Big help appreciate it.
1083 02:31:22.812 ⇒ 02:31:24.770 Awaish Kumar: Hey, guys, yeah.
1084 02:31:24.770 ⇒ 02:31:26.049 Uttam Kumaran: Alright. Take it easy, guys.