Meeting Title: DE-AE-AI Standup Date: 2025-11-20 Meeting participants: Mustafa Raja, Ashwini Sharma, Uttam Kumaran, Zoran Selinger, Rico Rejoso, Robert Tseng, Awaish Kumar, Amber Lin
WEBVTT
1 00:00:43.500 ⇒ 00:00:44.759 Ashwini Sharma: Hey, Mustafa.
2 00:00:47.400 ⇒ 00:00:48.539 Mustafa Raja: Hey, how are you?
3 00:00:48.760 ⇒ 00:00:50.169 Ashwini Sharma: I’m good, man. How are you?
4 00:00:50.660 ⇒ 00:00:51.649 Mustafa Raja: Yeah, doing good.
5 00:00:59.950 ⇒ 00:01:01.100 Uttam Kumaran: Hello!
6 00:01:01.540 ⇒ 00:01:02.100 Ashwini Sharma: Hey, what tempo.
7 00:01:02.100 ⇒ 00:01:02.770 Mustafa Raja: Ayy.
8 00:01:02.910 ⇒ 00:01:04.200 Uttam Kumaran: Hey, how are you?
9 00:01:04.319 ⇒ 00:01:05.500 Uttam Kumaran: Nice shirt.
10 00:01:05.840 ⇒ 00:01:06.500 Ashwini Sharma: Are you?
11 00:01:07.490 ⇒ 00:01:09.109 Uttam Kumaran: Good, I like the design.
12 00:01:10.510 ⇒ 00:01:11.590 Uttam Kumaran: Your shirt.
13 00:01:11.930 ⇒ 00:01:14.050 Ashwini Sharma: Oh, okay, okay.
14 00:01:19.460 ⇒ 00:01:24.120 Uttam Kumaran: I’m just gonna go make a coffee, but I’ll be on video in a sec. Yeah, I’m gonna have a…
15 00:01:24.370 ⇒ 00:01:29.079 Uttam Kumaran: I mean… Let me ping Awash and see if he can just… if he can join as well.
16 00:01:29.080 ⇒ 00:01:29.630 Ashwini Sharma: Sure.
17 00:02:15.810 ⇒ 00:02:17.090 Robert Tseng: Hello.
18 00:02:18.450 ⇒ 00:02:19.360 Uttam Kumaran: Hello.
19 00:02:19.610 ⇒ 00:02:20.710 Uttam Kumaran: Where you at?
20 00:02:21.690 ⇒ 00:02:26.510 Robert Tseng: I’m… I’m in Hong Kong. I’m at my, my in-law’s place.
21 00:02:28.040 ⇒ 00:02:29.230 Uttam Kumaran: Nice, how is it?
22 00:02:30.250 ⇒ 00:02:30.660 Awaish Kumar: required.
23 00:02:30.660 ⇒ 00:02:31.460 Robert Tseng: here.
24 00:02:33.640 ⇒ 00:02:37.010 Uttam Kumaran: Are they in a house, or are they in one of the big skyscrapers?
25 00:02:37.010 ⇒ 00:02:39.459 Robert Tseng: Yeah, it’s been a big, big,
26 00:02:39.790 ⇒ 00:02:45.580 Robert Tseng: big building, small unit, but I guess I’ve… I’m used to that now, living in New York.
27 00:02:45.990 ⇒ 00:02:50.350 Robert Tseng: But they’re not really in the main island. They’re,
28 00:02:50.830 ⇒ 00:02:55.650 Robert Tseng: They’re, like, closer to the Chinese border than they are to the island.
29 00:02:57.120 ⇒ 00:02:59.750 Robert Tseng: Yeah, but it’s nice, there’s, like, a river…
30 00:03:00.050 ⇒ 00:03:06.429 Robert Tseng: they’re, like, it’s, like, right next to a river. Chinese university in Hong Kong is, like, right across the river.
31 00:03:06.560 ⇒ 00:03:11.169 Robert Tseng: Yeah, it’s like a very, like, quiet part of Hong Kong.
32 00:03:13.980 ⇒ 00:03:16.239 Awaish Kumar: Nice. Are you in Hong Kong?
33 00:03:16.520 ⇒ 00:03:18.290 Robert Tseng: Yes, I am.
34 00:03:19.490 ⇒ 00:03:19.860 Awaish Kumar: Okay.
35 00:03:19.860 ⇒ 00:03:21.640 Robert Tseng: I’ll be here for the next week.
36 00:03:22.820 ⇒ 00:03:24.790 Awaish Kumar: So you are near Pakistan.
37 00:03:25.050 ⇒ 00:03:32.800 Robert Tseng: Yeah, yeah. I was telling Mustafa, I was like, I’m in your time zone, I know what it feels like to be working your guys’ hours down.
38 00:03:33.940 ⇒ 00:03:42.779 Uttam Kumaran: Hey, you guys can do stand-up whenever you guys want, I don’t mind. Nobody… If you want to shift times, don’t shift it.
39 00:03:43.150 ⇒ 00:03:47.760 Uttam Kumaran: That’s awesome, dude. Yeah, I wanna see some pictures.
40 00:03:48.370 ⇒ 00:03:53.430 Robert Tseng: Yeah, I will. I… I guess,
41 00:03:53.640 ⇒ 00:03:58.639 Robert Tseng: When it’s brighter, I’ll take some photos, and… yeah.
42 00:03:59.970 ⇒ 00:04:00.690 Uttam Kumaran: Nice.
43 00:04:02.120 ⇒ 00:04:07.910 Robert Tseng: Alright, well, I’ll kick things off, and then… yeah, sorry if my, like…
44 00:04:08.050 ⇒ 00:04:12.219 Robert Tseng: Brain is still kind of slow. Been on a 16-hour flight, so…
45 00:04:13.770 ⇒ 00:04:17.230 Robert Tseng: If I fumble my words, just, ask me to clarify.
46 00:04:19.730 ⇒ 00:04:32.710 Robert Tseng: Okay, so let’s kind of go through things, let’s start with… I see Zoran on this call as well. I know Henry’s not going to be here, Demi’s not here, but let’s just kind of talk through Eden’s stuff. So,
47 00:04:34.000 ⇒ 00:04:36.100 Robert Tseng: Yeah, so I guess I’ll…
48 00:04:37.000 ⇒ 00:04:47.640 Robert Tseng: Prefer to start with, by status, but that’s okay. No, we’ll just jump down. Alright, Zorwan, do you wanna, do you wanna give your, kind of, your updates first?
49 00:04:48.750 ⇒ 00:04:52.680 Zoran Selinger: Sure, sure. So I, I just, did,
50 00:04:52.820 ⇒ 00:04:59.990 Zoran Selinger: the… the estimates for NordBIM, and we are barely missing anything, so it’s…
51 00:05:00.220 ⇒ 00:05:14.700 Zoran Selinger: That’s one point discrepancy between what we have in Norbim and what we have on the edge. The touchpoints are a little bit lower, so for first touchpoint, we are, like, 83% accurate.
52 00:05:15.270 ⇒ 00:05:24.550 Zoran Selinger: And for… for the last, we are at 67%. Out of… I just randomly picked 27…
53 00:05:24.920 ⇒ 00:05:32.290 Zoran Selinger: orders that I was manually looking at and kind of seeing what, what touchpoints they have.
54 00:05:32.400 ⇒ 00:05:42.660 Zoran Selinger: So, I think, basically, my conclusion is it’s worthwhile investing a little bit of effort into… into Norbeam. And that’s also gonna be…
55 00:05:43.030 ⇒ 00:05:48.620 Zoran Selinger: a little bit more visible now… now that we… when we activate the meta, because it’s…
56 00:05:48.770 ⇒ 00:06:02.390 Zoran Selinger: It looks weird, because basically Google is almost our only channel at the moment, right? Everything else fails in comparison when it comes to the volume. So, wait.
57 00:06:02.390 ⇒ 00:06:08.710 Robert Tseng: Are you telling me we did the edge layer, and then we basically got, like, less than 5% improvement?
58 00:06:09.180 ⇒ 00:06:10.750 Robert Tseng: Than what we have in North Beam.
59 00:06:12.110 ⇒ 00:06:21.909 Zoran Selinger: Yes. So, we, however, we do have issues with, with touchpoints. So, we are covering all the transactions.
60 00:06:22.200 ⇒ 00:06:24.999 Zoran Selinger: So that’s 1.1% discrepancy.
61 00:06:25.290 ⇒ 00:06:29.070 Zoran Selinger: But… I’m telling you the touch points
62 00:06:29.540 ⇒ 00:06:35.959 Zoran Selinger: So how people got through to the transaction, we are missing quite a bit.
63 00:06:36.180 ⇒ 00:06:41.450 Uttam Kumaran: Yeah, that was the original reason, right? That was the original reason we didn’t consider Northbeam.
64 00:06:41.450 ⇒ 00:06:42.299 Robert Tseng: He said, what’s fine.
65 00:06:42.400 ⇒ 00:06:50.120 Zoran Selinger: Most of it is, though, just channels that are… that are not defined in Norbim.
66 00:06:50.290 ⇒ 00:07:00.229 Zoran Selinger: it’s mostly email. So, we have this option of defining a non-integrated channel in NordBIM, and I would like to do it.
67 00:07:00.750 ⇒ 00:07:06.900 Zoran Selinger: And then C, see, See how we go.
68 00:07:07.700 ⇒ 00:07:10.280 Zoran Selinger: It looks like we should be…
69 00:07:10.400 ⇒ 00:07:17.030 Zoran Selinger: We should be, you know, within 90-95% of accuracy there.
70 00:07:17.380 ⇒ 00:07:18.669 Robert Tseng: What were we at before?
71 00:07:19.970 ⇒ 00:07:30.240 Zoran Selinger: Like, right now, we are at, like, for the first touch, at 82, I think, and yes, 82, and for the last touch, we are at 63.
72 00:07:35.070 ⇒ 00:07:46.060 Zoran Selinger: So that’s… those are the two metrics that I was looking at, basically. First touch is, depending on the attribution model is important, and the last touch is depending on the attribution model is important.
73 00:07:47.370 ⇒ 00:07:55.829 Zoran Selinger: Okay, alright, I mean, yeah. So, and why it’s more on the last touch is because… because email plays a bigger role?
74 00:07:56.040 ⇒ 00:08:02.069 Zoran Selinger: in the last touch, and we don’t have that properly integrated in Urban yet.
75 00:08:08.080 ⇒ 00:08:19.649 Robert Tseng: Okay, so your recommendation, then, is to try to work with Northbeam, see if… we’re not really addressing transactions, trying to get more touchpoints into Northbeam.
76 00:08:19.950 ⇒ 00:08:24.499 Zoran Selinger: Exactly. So, two things, two actions there.
77 00:08:25.240 ⇒ 00:08:27.029 Zoran Selinger: implementation audit.
78 00:08:27.420 ⇒ 00:08:30.849 Zoran Selinger: Second one is define non-integrated channels.
79 00:08:34.039 ⇒ 00:08:37.270 Zoran Selinger: And I did create tickets for both of those.
80 00:08:40.750 ⇒ 00:08:43.779 Robert Tseng: Okay, and those are…
81 00:08:43.980 ⇒ 00:08:49.689 Zoran Selinger: I have it in the… I have a project, specific project for… oh, so I didn’t put it in the cycle yet.
82 00:08:50.310 ⇒ 00:08:53.450 Zoran Selinger: Okay, no problem. Yeah, so it’s in a project.
83 00:08:53.600 ⇒ 00:08:54.470 Zoran Selinger: Mmm…
84 00:08:55.600 ⇒ 00:08:56.110 Robert Tseng: Oops.
85 00:08:56.110 ⇒ 00:08:57.910 Zoran Selinger: Right, in insomnia.
86 00:08:58.630 ⇒ 00:09:00.820 Zoran Selinger: So, it’s under.
87 00:09:00.820 ⇒ 00:09:01.350 Robert Tseng: here.
88 00:09:03.370 ⇒ 00:09:04.130 Zoran Selinger: Mmm…
89 00:09:05.080 ⇒ 00:09:08.870 Zoran Selinger: No, no, Norby should have a separate… North Peak.
90 00:09:09.010 ⇒ 00:09:09.850 Zoran Selinger: Yes.
91 00:09:10.360 ⇒ 00:09:12.360 Robert Tseng: And I have two tickets here, yeah.
92 00:09:15.090 ⇒ 00:09:15.530 Robert Tseng: Got it.
93 00:09:15.530 ⇒ 00:09:18.149 Zoran Selinger: Both of those, yeah. They’re already there, yes.
94 00:09:19.980 ⇒ 00:09:22.120 Zoran Selinger: So that’s the… that’s the idea there.
95 00:09:22.620 ⇒ 00:09:25.489 Zoran Selinger: That’s what I’d like to do.
96 00:09:25.490 ⇒ 00:09:27.419 Robert Tseng: As soon as possible.
97 00:09:28.140 ⇒ 00:09:44.489 Zoran Selinger: Good thing is that I can do all of that, I don’t have to, I don’t think I have to, take any of Havisha’s time or Henry’s time, so they can do other things, like, meta setup and catalysts and all that stuff.
98 00:09:44.560 ⇒ 00:09:51.099 Zoran Selinger: So, I don’t need to worry them with, with Norbin. I can take… take that on.
99 00:09:51.100 ⇒ 00:09:54.249 Robert Tseng: Do you think we’ll get this done this week. Is this something you want to work on this week?
100 00:09:55.590 ⇒ 00:10:01.310 Zoran Selinger: But you mean today and tomorrow? No, it’s… it’s not… I mean, I can…
101 00:10:01.310 ⇒ 00:10:02.850 Robert Tseng: And this would be for next cycle?
102 00:10:03.170 ⇒ 00:10:04.789 Zoran Selinger: Yeah, but definitely next cycle, yeah.
103 00:10:04.790 ⇒ 00:10:15.310 Robert Tseng: Well, I mean, you were on the call with Mitesh yesterday, right? So he’s like… I mean, ultimately, we’re, like, we already… once again, we got to the point of, like, we evaluated all these tools, we said, go ahead with Wicked.
104 00:10:15.630 ⇒ 00:10:25.900 Robert Tseng: we already negotiated pricing with Wicked, and then we stalled, because we were gonna go and validate some things. Now it looks like we’re backing away from that decision, which…
105 00:10:26.300 ⇒ 00:10:30.650 Robert Tseng: Yeah, I mean, I just… I just want… they’re gonna… I just want to be able to, like.
106 00:10:31.570 ⇒ 00:10:40.499 Robert Tseng: communicate that. I… yeah, I mean, I’m not gonna preemptively say anything to him now, until you finish this part, but, like, that… that’s… that’s.
107 00:10:40.500 ⇒ 00:10:58.680 Zoran Selinger: I mean, I’m writing the messages in the analytics channel, it’s already there. Mitesh knows, we talked about it yesterday, he understands our reasoning. You were on the call, weren’t you? You were on the call. Yeah, so we had that conversation, he’s fine with how we want to proceed.
108 00:11:00.000 ⇒ 00:11:13.060 Zoran Selinger: like I said, the effort we invested in Wicked, I still believe that that might be an eventuality, so that project is ready and we can activate it when we need to.
109 00:11:13.420 ⇒ 00:11:13.800 Robert Tseng: I see.
110 00:11:13.800 ⇒ 00:11:17.760 Zoran Selinger: I also suggested, I suggested,
111 00:11:18.360 ⇒ 00:11:26.019 Zoran Selinger: that we do this analysis that I just did, maybe once every quarter. It’s just for 2-3 hours.
112 00:11:26.020 ⇒ 00:11:27.869 Robert Tseng: Yeah, just to see if there’s any drift, yeah.
113 00:11:27.870 ⇒ 00:11:36.430 Zoran Selinger: Yes, yes. And then if there’s… if the drift is increasing, and we… it’s… we cannot fix it, it’s due to, you know.
114 00:11:36.870 ⇒ 00:11:56.750 Zoran Selinger: tracking prevention and stuff like that, we can always reactivate the VK project. Now we know how it works, how we would… I know exactly how we would implement it, I know what the tables, like, what we need to merge to send the data in, I know all of that is ready, basically. Yeah. So, yeah, we can always activate that.
115 00:11:57.300 ⇒ 00:12:11.139 Robert Tseng: Okay, got it. And you’re aware that Cutter’s main goal is just to be able to spend on Facebook, right? So, I don’t know how much this really blocks him from spending in Facebook, but is that… is that still kind of… are you still on…
116 00:12:12.400 ⇒ 00:12:13.770 Robert Tseng: Like, I… I don’t know…
117 00:12:14.690 ⇒ 00:12:19.509 Zoran Selinger: Cutter wants to, wants to activate Facebook and TikTok.
118 00:12:21.160 ⇒ 00:12:36.969 Zoran Selinger: that’s kind of two things, and obviously affluence and… and things that we already have in place, we just need to… need to credit them properly. Yes, I understand. And now, then, like, NordBeam will look
119 00:12:37.230 ⇒ 00:12:45.890 Zoran Selinger: NordVim and all the other analytics tools that we have will look more natural when we have a few more… few more channels in there.
120 00:12:46.440 ⇒ 00:12:47.060 Robert Tseng: Okay.
121 00:12:47.260 ⇒ 00:13:01.739 Robert Tseng: I mean, I haven’t heard anything from him directly on, like, concerns around the channel themselves, but I just, you know, as far as, like, priorities, like, face… turning on Facebook is obviously the biggest priority. It’s the biggest channel that they can spend on, so…
122 00:13:01.740 ⇒ 00:13:02.210 Zoran Selinger: Yes.
123 00:13:02.270 ⇒ 00:13:10.209 Robert Tseng: if we can… however soon we can get him to turn that back on, I think would be… would… would look… would look better for us.
124 00:13:10.750 ⇒ 00:13:16.330 Zoran Selinger: So it’s… it’s on us right now, so I… I was talking to Avaesh.
125 00:13:16.460 ⇒ 00:13:33.690 Zoran Selinger: two days ago, and we set a clear priority on activating Facebook, so we need to figure out… I need his help to figure out, okay, this is how we… basically, we need… we need a table of transactions that we’ll credit back to
126 00:13:33.840 ⇒ 00:13:37.499 Zoran Selinger: Oh, a ratio here, so we need… we did a table with…
127 00:13:37.500 ⇒ 00:13:41.220 Awaish Kumar: I have a ticket for that, and yeah.
128 00:13:41.220 ⇒ 00:13:41.620 Zoran Selinger: microphone.
129 00:13:41.620 ⇒ 00:13:44.110 Awaish Kumar: It will be done today. Yeah. I told you, this is.
130 00:13:44.110 ⇒ 00:13:44.580 Zoran Selinger: this week?
131 00:13:44.770 ⇒ 00:13:46.130 Awaish Kumar: We will be done with that.
132 00:13:46.760 ⇒ 00:13:48.600 Zoran Selinger: Okay, excellent, excellent.
133 00:13:48.840 ⇒ 00:13:59.749 Zoran Selinger: We… I mean, we can… we promised the end of the month, so we have a little bit of time, we… we don’t… Yeah. Like, we are… we’re still comfortable there on the… on the timeline.
134 00:14:01.640 ⇒ 00:14:16.750 Awaish Kumar: I just had one question regarding ads data. Like, Henry wanted to get, like, the spend data from these, all these platforms, like Google, Facebook, which right now we are getting from Northview.
135 00:14:17.040 ⇒ 00:14:23.959 Zoran Selinger: We don’t have to do it right now. If you’re not getting rid of NordBeam, then that stays. We don’t have to do that work.
136 00:14:24.980 ⇒ 00:14:27.510 Awaish Kumar: Okay, okay, so we don’t need it right now, okay.
137 00:14:27.630 ⇒ 00:14:28.400 Zoran Selinger: Yeah, don’t…
138 00:14:28.400 ⇒ 00:14:45.209 Robert Tseng: If we need to at that point, we’ll just plug it into Corral. They already have Corral set up. We’ve talked about this months ago. We tried to get them off North Beam and to just use Corral, but I mean, we have options, so I’m not worried about the speed of being able to turn… to go direct to those platforms.
139 00:14:49.180 ⇒ 00:14:52.010 Robert Tseng: Okay, cool. And then…
140 00:14:52.170 ⇒ 00:14:57.199 Robert Tseng: So that… I guess that’s… that covers it. Anything else on your end, Zoran, or is that… is that it?
141 00:14:59.030 ⇒ 00:15:11.699 Zoran Selinger: No, no, I still… I’m still a little bit late with updating the Edge, because Basque had a session ID upgrade, and I will also use that opportunity to add a few
142 00:15:11.840 ⇒ 00:15:23.110 Zoran Selinger: a few more identifiers, like, I want to get, like, segment anonymous ID and GA4UID in the tables as well, just in case.
143 00:15:23.950 ⇒ 00:15:38.970 Zoran Selinger: So I’m gonna use that opportunity to do both, both of those things. Haven’t had a chance yet, but I’m expecting it to do it tomorrow. I don’t think anything will discred me from tomorrow. I think I’m ready to do that now.
144 00:15:40.040 ⇒ 00:15:40.440 Robert Tseng: Okay.
145 00:15:40.440 ⇒ 00:15:43.560 Zoran Selinger: That’s the one ticket that’s overdue, basically, yeah.
146 00:15:43.560 ⇒ 00:15:44.130 Robert Tseng: Yeah.
147 00:15:46.160 ⇒ 00:15:50.259 Awaish Kumar: Yeah, we also just assigned a few tickets to Ashwini.
148 00:15:50.260 ⇒ 00:15:51.640 Robert Tseng: Yeah.
149 00:15:54.150 ⇒ 00:16:04.610 Awaish Kumar: Yeah, so, like, 1183 can be closed, because I already reviewed it and approved it, so that’s kind of done.
150 00:16:06.160 ⇒ 00:16:06.860 Robert Tseng: Oops.
151 00:16:07.730 ⇒ 00:16:08.830 Awaish Kumar: Oh, man. Okay.
152 00:16:09.800 ⇒ 00:16:22.060 Awaish Kumar: But the 1152 can be done by Ashwini. It’s like, we have a pipeline in Dexter which currently have hard-coded slugs for URLs.
153 00:16:22.170 ⇒ 00:16:24.600 Awaish Kumar: And
154 00:16:24.830 ⇒ 00:16:41.869 Awaish Kumar: Like, to make it general purpose, we added a table in BigQuery, which is filled by Zoran, and then we just need to update that pipeline to read from that table all the slugs, related to Catless, and then just use that.
155 00:16:44.220 ⇒ 00:16:44.860 Robert Tseng: Okay.
156 00:16:45.060 ⇒ 00:16:53.920 Awaish Kumar: I never entirely, yep, so… So, table will be updated by Zoran when he, like, gets the.
157 00:16:53.920 ⇒ 00:16:55.099 Zoran Selinger: Yeah, my… myself…
158 00:16:55.100 ⇒ 00:16:56.359 Awaish Kumar: You said… Yeah.
159 00:16:56.360 ⇒ 00:17:00.820 Zoran Selinger: Or Ryan, or Ryan will direct you to it as well. Yeah, so…
160 00:17:01.380 ⇒ 00:17:10.930 Awaish Kumar: Yeah, for this ticket, we just need to update a pipeline to read that… from data from that table, and use that in the pipeline, in Dexter. Okay.
161 00:17:11.770 ⇒ 00:17:15.470 Robert Tseng: Okay, and then this is the meta… meta stuff we were just talking about, right?
162 00:17:15.970 ⇒ 00:17:18.670 Awaish Kumar: Yes, yes, that I will be working on.
163 00:17:19.099 ⇒ 00:17:25.529 Robert Tseng: Alright, so I’m gonna say that’s in progress. We’re still gonna end for end of week, so…
164 00:17:25.949 ⇒ 00:17:36.429 Robert Tseng: that… Okay. Casey, I guess, did you end up setting up session replays?
165 00:17:39.119 ⇒ 00:17:39.809 Robert Tseng: Is he on this call?
166 00:17:39.810 ⇒ 00:17:41.459 Uttam Kumaran: I don’t think Casey’s on…
167 00:17:41.860 ⇒ 00:17:45.360 Robert Tseng: Oh, okay. Fine.
168 00:17:45.740 ⇒ 00:17:49.720 Robert Tseng: Then, I mean, I know the spike is for tomorrow, so we’ll kind of review that then.
169 00:17:49.920 ⇒ 00:17:52.869 Robert Tseng: Save a lot of these, still a lot here, so we’ll skip those.
170 00:17:52.990 ⇒ 00:17:58.290 Robert Tseng: And Henry’s not here. I mean, I would have liked to hear what happened with the Pharmetica stuff.
171 00:17:59.380 ⇒ 00:18:04.360 Uttam Kumaran: Yeah, so on Pharmedica, I talked to him briefly, he got…
172 00:18:04.470 ⇒ 00:18:09.789 Uttam Kumaran: One, we worked on, a Gantt chart, well, we worked on it. Yeah, I just see that.
173 00:18:09.950 ⇒ 00:18:20.210 Uttam Kumaran: Yeah, so that has a lot of… and he got some, API-related information. He basically… he sent a note in the Eden channel regarding, like, updates on this API.
174 00:18:20.440 ⇒ 00:18:31.960 Uttam Kumaran: So, there was… Yeah, it’s in here somewhere. He also pinged it to me, so…
175 00:18:35.090 ⇒ 00:18:36.990 Uttam Kumaran: Yeah, he said…
176 00:18:41.110 ⇒ 00:18:48.020 Uttam Kumaran: Yeah, he said he’s gonna get some API information and then send it in the channel, so I said, yeah, send it to the channel, anyone can work on that.
177 00:18:48.700 ⇒ 00:18:49.340 Robert Tseng: Okay.
178 00:18:51.400 ⇒ 00:19:01.580 Robert Tseng: Yeah, one more thing I want to highlight to this team, I’m not going to add everyone here, but… so this is a chat between Surf, Josh, Beluga, their main pharmacy, and then Cameron Remo.
179 00:19:01.860 ⇒ 00:19:10.000 Robert Tseng: they are urgently trying to move off of BASC, and so I’m basically trying to scope out a one-time, kind of, like.
180 00:19:11.210 ⇒ 00:19:19.730 Robert Tseng: project fee for Josh, that’s gonna be high bill… Yeah, I’m gonna basically try to charge him very high, and
181 00:19:19.960 ⇒ 00:19:23.899 Robert Tseng: Yeah, like, this is something that we may scope out for the next month, but .
182 00:19:23.900 ⇒ 00:19:27.529 Uttam Kumaran: Who do you need for that? Like, are you just planning on looping in surf, or what do you think?
183 00:19:27.530 ⇒ 00:19:33.989 Robert Tseng: I told Surf, I mean, the demo’s gonna happen, quote-unquote demo’s gonna happen on Friday, and then I already kind of
184 00:19:34.910 ⇒ 00:19:44.380 Robert Tseng: asked him some capabilities things, can he just intake the code from Cameron, and then basically, like, just…
185 00:19:44.760 ⇒ 00:19:59.600 Robert Tseng: duplicate it on his own… on his own infra, and just run with it from there. And then I feel like I need to just be the one to grab, like, 30 minutes with Josh, and just, like, figure out exactly what the acceptance criteria are.
186 00:19:59.630 ⇒ 00:20:08.689 Robert Tseng: I think, to me, like, at that high level, it’s one, be able to, like, lift 60% of their customers out of Basque and move it over to Remo.
187 00:20:08.810 ⇒ 00:20:15.379 Robert Tseng: So that’s gonna be a purely, kind of, hopefully, like, Surf will be able to handle that.
188 00:20:15.440 ⇒ 00:20:34.040 Robert Tseng: Once he’s able to get Cameron’s code. And then I have to talk to this Jonah guy, he’s Beluga, make sure that this connector is up and running. I mean, sounds like we still have to work with Cameron to make sure this is happening, but any, like, workflow or process things, like, I think this is just, like, getting the… like, this is just, like.
189 00:20:34.530 ⇒ 00:20:50.010 Robert Tseng: BizOps or PM kind of work to go and get it done. And if we can set up that connector, I think that… that would be… that would be enough. There’s a couple other, like, ad hoc things that are kind of gonna be thrown into that mix.
190 00:20:50.010 ⇒ 00:20:56.269 Uttam Kumaran: So I don’t know if I necessarily need more people, but, like, it’s just gonna… I wonder… I think you should at least go for a PM, dude.
191 00:20:58.230 ⇒ 00:21:00.510 Uttam Kumaran: A dedicated PM to the project.
192 00:21:00.510 ⇒ 00:21:01.829 Robert Tseng: Yeah, maybe we should.
193 00:21:02.160 ⇒ 00:21:06.649 Uttam Kumaran: And then maybe that person rolls off and just stays outside Eden, TM.
194 00:21:07.220 ⇒ 00:21:08.969 Robert Tseng: Hmm… I see.
195 00:21:08.970 ⇒ 00:21:10.990 Uttam Kumaran: like, I’m… yeah.
196 00:21:12.010 ⇒ 00:21:15.249 Robert Tseng: Well, yeah, okay, then maybe, Tom, we can talk later on.
197 00:21:15.250 ⇒ 00:21:16.190 Uttam Kumaran: I mean, I can’t…
198 00:21:16.790 ⇒ 00:21:19.370 Robert Tseng: It’s gotta be, like, a senior person. Yeah.
199 00:21:19.370 ⇒ 00:21:21.370 Uttam Kumaran: Yeah, yeah, yeah, yeah, like…
200 00:21:21.370 ⇒ 00:21:24.189 Robert Tseng: I want to charge them, like, a hundred grand for this.
201 00:21:24.490 ⇒ 00:21:29.190 Uttam Kumaran: Yeah, and I also don’t… like, it’s a tough project, it’s… I don’t hate it.
202 00:21:29.190 ⇒ 00:21:30.509 Robert Tseng: It’s gonna be, like, yeah.
203 00:21:31.100 ⇒ 00:21:34.149 Uttam Kumaran: I want to make sure there is, like, a, actual
204 00:21:34.640 ⇒ 00:21:40.129 Uttam Kumaran: You know, product manager or someone there that has, like, senior technical expertise, and then…
205 00:21:40.250 ⇒ 00:21:43.970 Uttam Kumaran: If, if, like, if it works out, that person can just stay on.
206 00:21:44.490 ⇒ 00:21:47.140 Uttam Kumaran: the Eden client, you know, and start to take this over.
207 00:21:47.560 ⇒ 00:21:48.140 Robert Tseng: Yeah.
208 00:21:49.820 ⇒ 00:21:56.649 Uttam Kumaran: But, at least in that case… and then, yeah, depending on the price, like, I have other engineers, really senior people you could talk to that would be…
209 00:21:57.530 ⇒ 00:22:07.479 Robert Tseng: Yeah, I mean, part of our fee’s gonna go to Surf and, like, who he decides to put on that project, so I’m kind of letting him kind of come back to it. I don’t know how we’re gonna price it out with him, but I’m…
210 00:22:07.700 ⇒ 00:22:08.979 Robert Tseng: But yeah, like, I…
211 00:22:10.040 ⇒ 00:22:15.989 Robert Tseng: Okay. Well, I guess that’s more between you and I to kind of figure out, so that’s something I’m thinking about for Eden.
212 00:22:16.910 ⇒ 00:22:18.400 Uttam Kumaran: Okay, yeah, record and get it.
213 00:22:18.400 ⇒ 00:22:28.029 Robert Tseng: for this team is just that, like, and I think it’s just that if… if they don’t get off Basque, and Basque somehow catches wind, like, they shut down one of their other, like, kind of…
214 00:22:28.090 ⇒ 00:22:48.010 Robert Tseng: customers already, like, that would put, Eden in a cash crunch, because they would… they would basically have to halt operations until they can actually move off of it. So, that would mean that our contract with them would have to be paused, and, like, it’d just be kind of annoying for us. So that’s the… that’s the risk, that we’re… that we’re facing by
215 00:22:48.600 ⇒ 00:22:55.220 Robert Tseng: I mean, I don’t want to say that we have to take it on, but if… if this doesn’t… if this doesn’t go well, like, that’s… that’s what… that’s what could happen.
216 00:22:56.270 ⇒ 00:23:04.140 Uttam Kumaran: Yeah, I at least have, like, Surf, and then… yeah, I mean, I’ll do… I mean, I used to work with Surf, so once you get scope, we can all talk, and then we can figure it out.
217 00:23:04.600 ⇒ 00:23:05.549 Robert Tseng: Okay. Yeah.
218 00:23:05.940 ⇒ 00:23:06.680 Uttam Kumaran: Cool.
219 00:23:07.760 ⇒ 00:23:08.620 Robert Tseng: Alright.
220 00:23:08.830 ⇒ 00:23:15.069 Uttam Kumaran: We’ll move on to insomnia. I guess that’s Sweeney, are you, are you, are you clear on your…
221 00:23:15.280 ⇒ 00:23:16.969 Uttam Kumaran: On your task for today.
222 00:23:17.540 ⇒ 00:23:23.420 Ashwini Sharma: No, I’ll, I’ll get, you know, sync up with, Avesh after this call to get more details here.
223 00:23:23.970 ⇒ 00:23:35.170 Uttam Kumaran: Okay, and the only other thing, you know, bonus ticket is we have Metaplane, for alerting. I think it’s also good as you go through and you understand, like, what the core reporting tables are.
224 00:23:35.360 ⇒ 00:23:43.769 Uttam Kumaran: Going back to our interview conversation about reliability, that would be great, if you can take a look at establishing that for Eden.
225 00:23:43.770 ⇒ 00:23:46.729 Robert Tseng: Alright, I’ll reassign this to Eshini then.
226 00:23:47.610 ⇒ 00:23:52.750 Robert Tseng: And I just default set everything to 2, so… Okay.
227 00:23:52.870 ⇒ 00:24:00.259 Robert Tseng: Alright, let’s move on to insomnia. So… because I… sorry, I’m just trying to speed through this,
228 00:24:01.620 ⇒ 00:24:05.719 Robert Tseng: Yeah, I guess it was really, Amber, everything’s kind of in your court here, so…
229 00:24:05.720 ⇒ 00:24:06.050 Amber Lin: Yeah.
230 00:24:06.050 ⇒ 00:24:06.670 Robert Tseng: start.
231 00:24:06.670 ⇒ 00:24:13.050 Amber Lin: Yesterday, I had to do honeysitting and stuff, so there’s no progress here.
232 00:24:13.310 ⇒ 00:24:13.960 Robert Tseng: Okay.
233 00:24:14.180 ⇒ 00:24:14.940 Amber Lin: Yeah.
234 00:24:18.190 ⇒ 00:24:19.929 Robert Tseng: Alright, then,
235 00:24:20.270 ⇒ 00:24:26.589 Robert Tseng: we move on, I guess, what’s… what’s, like, what’s the… what’s the up… is there anything for me to review? Update we’re sending by the end of the week?
236 00:24:27.680 ⇒ 00:24:46.119 Amber Lin: Yeah, I looked at… so I limited it to the past, I think, 12 weeks, and I looked at the spikes in PO orders, because I… I think the core question is, how do we better predict big spikes in PO orders so we can actually fulfill them?
237 00:24:46.120 ⇒ 00:24:47.180 Robert Tseng: Talk about insomnia.
238 00:24:47.520 ⇒ 00:24:53.880 Amber Lin: Oh, Insomnia, I can do the follow-up today.
239 00:24:54.080 ⇒ 00:24:57.020 Amber Lin: And then send something by end of week.
240 00:24:57.210 ⇒ 00:25:00.940 Amber Lin: And I do want to finish the segment, so probably those two.
241 00:25:01.090 ⇒ 00:25:10.030 Amber Lin: So that would be… Let’s see… Yeah, Insomnia 232.
242 00:25:10.570 ⇒ 00:25:15.099 Amber Lin: And… and then the 214.
243 00:25:19.410 ⇒ 00:25:20.390 Robert Tseng: Hmm…
244 00:25:24.630 ⇒ 00:25:26.379 Robert Tseng: 2, and 4…
245 00:25:30.820 ⇒ 00:25:33.920 Robert Tseng: Okay. Alright.
246 00:25:36.300 ⇒ 00:25:39.230 Robert Tseng: We could move on to Honey Stinger, since you were talking about it.
247 00:25:41.420 ⇒ 00:25:45.549 Robert Tseng: I did look through your Notion doc,
248 00:25:47.710 ⇒ 00:25:49.789 Robert Tseng: Yeah, do you wanna try to…
249 00:25:50.370 ⇒ 00:25:56.289 Robert Tseng: distill it down a bit more, like, I… what I gathered was you looked at
250 00:25:56.320 ⇒ 00:26:05.209 Robert Tseng: PO purchase cycles by SKU or ASIN, and there’s a couple that there’s a big gap where
251 00:26:05.210 ⇒ 00:26:16.400 Robert Tseng: big POs were placed, and the inventory doesn’t look like it was… it was, there to meet that demand, and so, like, that’s kind of where I feel like you left things off.
252 00:26:18.280 ⇒ 00:26:23.019 Amber Lin: Yeah, I looked at the major spikes appeal orders.
253 00:26:23.120 ⇒ 00:26:34.790 Amber Lin: And looked at the traffic and sales and highly available inventory, around the spike time to see if there’s anything that can predict it.
254 00:26:34.790 ⇒ 00:26:45.810 Amber Lin: believe the traffic… there’s usually a traffic spike right before the PO spike, so that could be a good indicator for them to predict PO spikes.
255 00:26:46.020 ⇒ 00:26:49.970 Amber Lin: And then I started to look at…
256 00:26:50.230 ⇒ 00:27:05.590 Amber Lin: around those PO orders, are we actually fulfilling them? And the finding is most of our rejected or that were unable to send, the orders that we were not able to send were around those spikes.
257 00:27:05.790 ⇒ 00:27:10.750 Amber Lin: And so, that’s where I left off.
258 00:27:11.080 ⇒ 00:27:12.430 Amber Lin: Yesterday.
259 00:27:14.610 ⇒ 00:27:15.360 Robert Tseng: Okay.
260 00:27:23.380 ⇒ 00:27:29.940 Robert Tseng: So what do you think the next step is here? Like, how do you really answer? Like, I don’t think this is the… like, what’s…
261 00:27:30.170 ⇒ 00:27:35.779 Robert Tseng: does the question change here? Does the takeaway change? Like, do you need more time? Like, what’s… what’s the…
262 00:27:36.430 ⇒ 00:27:40.350 Robert Tseng: What, what, what, what do you, what, what are we going to tell Byron?
263 00:27:43.530 ⇒ 00:27:45.880 Amber Lin: Let’s see…
264 00:27:49.500 ⇒ 00:28:03.820 Amber Lin: I was more focusing on if there’s any specific ASINs that they should look at. There was a few SKUs that had multiple spikes in PO orders in
265 00:28:04.090 ⇒ 00:28:19.510 Amber Lin: past, like, 3 months, and if they… if they spike that often, and they’re among the 10 biggest spikes, we should watch for them again, because the demand seems to be coming in waves.
266 00:28:20.040 ⇒ 00:28:27.279 Amber Lin: So, that’s a… that’s a list I do want to give him and say, hey, please watch for this, just in case.
267 00:28:27.440 ⇒ 00:28:41.579 Amber Lin: I also do want to look at how they plan or forecast inventory. I haven’t thought about the next steps yet, I… it was pretty late last night, so I…
268 00:28:41.980 ⇒ 00:28:57.019 Amber Lin: put down the insights so far. I could also start looking at the different platforms and seeing, taking a look at the highly available inventory and seeing how it might differ from the actual demand.
269 00:28:58.580 ⇒ 00:29:11.760 Robert Tseng: Okay. Well, I feel like it’s Thursday. At this point, I want to take what we have and put it into… I want to synthesize it. So, I think what would be helpful… I’ve gotten, like, the questions that Henry’s answered, I’ve gotten
270 00:29:12.120 ⇒ 00:29:13.529 Robert Tseng: and pieces from you.
271 00:29:13.660 ⇒ 00:29:21.249 Robert Tseng: If you don’t feel like you have the wherewithal to put it together, you can let me know. I’ll put together the deck for this week.
272 00:29:21.450 ⇒ 00:29:23.869 Robert Tseng: But, yeah, I… I think…
273 00:29:24.500 ⇒ 00:29:27.920 Robert Tseng: Yeah, I just… I just need to know, like, where do I… when, like, at what point do I…
274 00:29:27.920 ⇒ 00:29:28.930 Uttam Kumaran: Amber, you have it.
275 00:29:28.930 ⇒ 00:29:29.480 Robert Tseng: Yeah.
276 00:29:29.820 ⇒ 00:29:37.390 Uttam Kumaran: Amber, I think you have it. Take… take, like, everything you’ve done, pick… Pick 5 to 7 slides.
277 00:29:37.720 ⇒ 00:29:39.780 Uttam Kumaran: And then… rip them.
278 00:29:40.000 ⇒ 00:29:42.529 Uttam Kumaran: And then send it to Robert to cut it down.
279 00:29:43.400 ⇒ 00:29:44.170 Amber Lin: Okay.
280 00:29:44.490 ⇒ 00:29:45.240 Amber Lin: Yeah.
281 00:29:45.240 ⇒ 00:29:59.780 Uttam Kumaran: I think you’re close, like, I think you have… you have info on the spikes, and look, if you… I would say if you feel like one or more slides is, like, light, then put that in the comment, being like… because we can still leave it there, and then that can lead to more discussion. But I think…
282 00:29:59.920 ⇒ 00:30:05.360 Uttam Kumaran: you kind of have a bunch of info now, I think go for the slides.
283 00:30:06.540 ⇒ 00:30:07.470 Amber Lin: Cool, okay.
284 00:30:08.000 ⇒ 00:30:14.649 Robert Tseng: Yeah, I mean, and then regarding forecasting, Henry already looked at that, so Amazon does their own forecasting,
285 00:30:16.090 ⇒ 00:30:21.510 Robert Tseng: Yeah, so I’m not expecting all five slides to come from your work. Like, I can… you can…
286 00:30:22.270 ⇒ 00:30:24.629 Robert Tseng: you can tell me, like, what you’re… I mean…
287 00:30:24.890 ⇒ 00:30:32.210 Robert Tseng: that’s more of an art than a science at this point, but I… I don’t really… like, I see a couple points. You’re gonna highlight the…
288 00:30:32.390 ⇒ 00:30:37.739 Robert Tseng: I mean, he’s gonna know what PO spiked. Like, he was talking to us in our call, saying, like, he was.
289 00:30:37.740 ⇒ 00:30:38.150 Uttam Kumaran: Yeah.
290 00:30:38.150 ⇒ 00:30:50.020 Robert Tseng: surprised that fruit smoothie shoes, like, kind of came out of nowhere, and they were totally unprepared to… to send it to them, which is why you see… or I guess I’m not sharing my full screen.
291 00:30:50.640 ⇒ 00:30:54.789 Robert Tseng: Which is why you see this… this situation right here, where…
292 00:30:55.000 ⇒ 00:31:04.809 Robert Tseng: orders increased, and then they just, like, didn’t fulfill those orders, because they didn’t expect there to be a spike in… in smoothies.
293 00:31:05.060 ⇒ 00:31:07.189 Robert Tseng: I don’t really… I think…
294 00:31:08.130 ⇒ 00:31:16.340 Robert Tseng: Well, anyway, so, like, there’s certain points like that, whether or not traffic was a leading indicator, like, I think you could even just pick that as, like, one example.
295 00:31:16.650 ⇒ 00:31:32.189 Robert Tseng: Like, I don’t need… you don’t need to go through and do the 10 SKUs, right? So you can be like, here’s an example of one where, like, we were unprepared for it, and just, like, break it down for him. There were some leading signals, we didn’t catch it. As a result, these orders spiked, and then we
296 00:31:32.610 ⇒ 00:31:36.730 Robert Tseng: fill these orders, da-da-da. Like, that’s… that’s, like, one or two slides there.
297 00:31:36.950 ⇒ 00:31:45.279 Robert Tseng: Here’s an example of something that’s more consistent. The volume kind of is ebbs and flows every four weeks. I don’t really think this visual really shows that.
298 00:31:45.410 ⇒ 00:31:55.469 Robert Tseng: And I know you don’t have that much historical data, you have, like, probably limited to 3 months max or something, so you can kind of, like, bend that as you will, but, like.
299 00:31:55.810 ⇒ 00:32:03.689 Robert Tseng: I don’t think he’s gonna look at this, like, I’m saying, like, maybe there’s a… there’s, like, one more step past this in order to get it into the story, right?
300 00:32:03.690 ⇒ 00:32:06.230 Amber Lin: Okay.
301 00:32:06.230 ⇒ 00:32:13.270 Uttam Kumaran: But also, if you get something to him today, and say a bunch of stuff, he can… he can answer a bunch of the questions that we’ll probably go through.
302 00:32:13.860 ⇒ 00:32:14.900 Uttam Kumaran: Tomorrow.
303 00:32:15.210 ⇒ 00:32:21.340 Uttam Kumaran: But… Yeah.
304 00:32:23.800 ⇒ 00:32:24.340 Robert Tseng: Okay.
305 00:32:24.860 ⇒ 00:32:26.570 Robert Tseng: So, how do you feel?
306 00:32:27.200 ⇒ 00:32:36.980 Amber Lin: I’ll have this… I’ll work on the slides this morning, and then send it for you to review, and in the afternoon, I’ll probably work on some, yeah.
307 00:32:37.180 ⇒ 00:32:39.030 Robert Tseng: Okay.
308 00:32:40.410 ⇒ 00:32:43.390 Robert Tseng: Alright, then I’ll let you do that.
309 00:32:43.650 ⇒ 00:32:59.159 Robert Tseng: I already went through README with, Mustafa, so there’s not much more to say, but I will just kind of say, since that call’s probably kind of late for me, Tom, so I don’t know if I’ll join. Basically, the takeaways are… am I still sharing everything here?
310 00:32:59.850 ⇒ 00:33:07.010 Robert Tseng: Yeah, so Mustafa created this summary table, great, like, great. This is what I was like.
311 00:33:07.210 ⇒ 00:33:17.059 Robert Tseng: I was just asking for this for a while, so I’m glad he was able to put it together. Basically what we’re seeing is, like, okay, at the top of the funnel, with signups, there’s, like.
312 00:33:17.170 ⇒ 00:33:23.380 Robert Tseng: Obviously, you could see it’s like a… it’s off by… it’s off by, like, 40… like, 60%.
313 00:33:23.810 ⇒ 00:33:28.549 Robert Tseng: Mongo just, like, captures a lot more signups than Amplitude does.
314 00:33:28.560 ⇒ 00:33:47.599 Robert Tseng: And it’s like, okay, well, there’s, like, maybe some additional filtering that we need to do in order to cut it down, so doing email verifications brings it down to 5K, maybe there’s a couple more things, but… so that’s… that’s, like, at that… at that level. Projects created, like, we’re already pretty close. It’s, like, within 5%, so, like, I wouldn’t really… that directionally is… is… is good enough.
315 00:33:47.600 ⇒ 00:34:05.509 Robert Tseng: Attempted launch was also something that was, like, kind of pretty… directionally pretty close, but I will say that this is, like, that event that we have firing at amplitude is… is the problem, for why, like, the subscriptions are off by 60%, or 70… what is 65%.
316 00:34:05.750 ⇒ 00:34:15.429 Robert Tseng: If you look at… I have it screenshotted here. This is the original funnel that we’re validating, just those four steps in the month of September.
317 00:34:15.449 ⇒ 00:34:27.690 Robert Tseng: If I remove attempted launch, we look at the subscription success, it matches. So, the subscription… the payments, the payments, the valid payments are, like, they’re…
318 00:34:27.900 ⇒ 00:34:43.609 Robert Tseng: like, this… this is the true… this… this is a true number. Like, what’s breaking this funnel is attempted launch, and we’re not having the right filters on the user side for Mongo, which is fine. Like, amplitude can have… can have fewer, that’s not… that’s not a huge risk, but it’s just that…
319 00:34:43.610 ⇒ 00:34:50.089 Robert Tseng: this whole, like, launch… this concept of launching projects is a little bit misguided. So…
320 00:34:50.130 ⇒ 00:35:09.059 Robert Tseng: I tried to, like, articulate what those call-outs were here, so I would just kind of bring those things up. I can help you anticipate some of the questions. They’re gonna… I don’t think they’re gonna care so much about the top of the funnel, they’re gonna try to understand, okay, well, what are… what are the proxy… what’s… what’s, like, a better proxy that we can use leading up to a successful subscription?
321 00:35:09.070 ⇒ 00:35:13.560 Robert Tseng: Maybe it’s a managed plan events, maybe there’s, like, other things, so we just have to, like.
322 00:35:13.580 ⇒ 00:35:18.609 Robert Tseng: Just say that there’s, like, some adjustments we can make here, but overall, like, directionally.
323 00:35:19.170 ⇒ 00:35:34.669 Robert Tseng: the number of projects that are created and the subscriptions, they… we… like, this is… this is pretty… this is… Amplitude has it. Like, it’s… it’s… it’s good enough to use. So, I think, like, that’s… that’s kind of what we can say. Like, we…
324 00:35:34.670 ⇒ 00:35:35.230 Uttam Kumaran: Okay.
325 00:35:35.370 ⇒ 00:35:35.940 Robert Tseng: Yeah.
326 00:35:36.360 ⇒ 00:35:37.900 Robert Tseng: So…
327 00:35:38.140 ⇒ 00:35:51.489 Robert Tseng: I think we validated the most important parts. Obviously, there are some caveats to it, but, like, I think there is enough here for us to move forward with the other analysis. So, I would try to, like, steer it back after we get past the validation conversation.
328 00:35:51.750 ⇒ 00:36:09.970 Robert Tseng: If they want to know how we’re making adjustments to the funnel, you can, like, kind of… like, you can call out what I just mentioned. If not, then, like, kind of try to steer them back into the analysis and try to get them to pluck off what’s… what’s important. I think, obviously, with the reshuffling, with Ashley’s… Ashley not being there.
329 00:36:10.050 ⇒ 00:36:26.270 Robert Tseng: I think we just need to hear it again, like, what’s the next thing to go after? It doesn’t seem like they’re a client that cares so much about us, like, parallelizing, like, doing a bunch of different things, they just want us to go after one thing at a time. So, you know, I think they’re… we’ll just let them say what the next thing is.
330 00:36:27.740 ⇒ 00:36:37.300 Uttam Kumaran: I guess my question is, what are the odds you could make that meeting? Oh, yeah. Because, I feel like the CEO may be on…
331 00:36:37.440 ⇒ 00:36:39.230 Robert Tseng: Yeah, I think Greg will be on there.
332 00:36:39.850 ⇒ 00:36:43.419 Uttam Kumaran: I think, Greg, a few people. I feel okay to…
333 00:36:43.620 ⇒ 00:36:45.540 Uttam Kumaran: I want to have a conflict.
334 00:36:45.860 ⇒ 00:36:46.370 Robert Tseng: Oh, okay.
335 00:36:46.370 ⇒ 00:36:53.600 Uttam Kumaran: stuffs. Second, I feel like this is, like, we… there’s just a bunch of change right now, so…
336 00:36:53.860 ⇒ 00:36:54.180 Robert Tseng: Yeah.
337 00:36:54.180 ⇒ 00:36:56.609 Uttam Kumaran: I can take it… I can take it next week.
338 00:36:57.490 ⇒ 00:37:02.520 Uttam Kumaran: Or if there’s fastballs, we can get it out, but, like, if you can be there, that would be…
339 00:37:03.100 ⇒ 00:37:04.989 Uttam Kumaran: Like, really helpful today.
340 00:37:05.500 ⇒ 00:37:06.320 Robert Tseng: Okay.
341 00:37:06.510 ⇒ 00:37:07.690 Robert Tseng: Let me see…
342 00:37:13.050 ⇒ 00:37:15.420 Uttam Kumaran: You can also ping them and see if they can do earlier.
343 00:37:16.530 ⇒ 00:37:19.190 Robert Tseng: Yeah, I might try to ping them to do a bit earlier, but…
344 00:37:19.190 ⇒ 00:37:26.439 Uttam Kumaran: The other… the other benefit, Robert, is if we get… if we get fast follows, Mustafa can take that on today.
345 00:37:26.780 ⇒ 00:37:27.590 Robert Tseng: Yeah.
346 00:37:31.960 ⇒ 00:37:34.230 Robert Tseng: Alright, I’ll handle the messaging with them.
347 00:37:34.230 ⇒ 00:37:43.269 Uttam Kumaran: Okay. Alright, sorry, dude. I have, like, 4 meetings stacked in that hour, and I’m, like, moving things around, so it’s the only time I’ve got with the lawyers.
348 00:37:43.490 ⇒ 00:37:44.170 Robert Tseng: Sure.
349 00:37:45.530 ⇒ 00:37:47.050 Robert Tseng: Alright.
350 00:37:47.050 ⇒ 00:37:50.139 Uttam Kumaran: We also have the other analysis to present.
351 00:37:50.550 ⇒ 00:37:52.750 Robert Tseng: Yeah, yeah, the linter things, yeah, yeah.
352 00:37:53.040 ⇒ 00:37:55.879 Uttam Kumaran: I mean, they… it looks like those… they suck.
353 00:37:56.700 ⇒ 00:37:58.520 Robert Tseng: Yeah. Like, nobody’s eating this.
354 00:37:59.010 ⇒ 00:37:59.520 Robert Tseng: Yeah.
355 00:38:00.820 ⇒ 00:38:03.250 Uttam Kumaran: So they just fired their CPO, she was CPO?
356 00:38:04.250 ⇒ 00:38:05.700 Robert Tseng: The head of product, yeah.
357 00:38:08.150 ⇒ 00:38:09.310 Uttam Kumaran: Damn.
358 00:38:09.310 ⇒ 00:38:22.539 Robert Tseng: It’s… it’s a… it’s a messy situation. I mean, they’ve just been shipping a bunch of stuff, and it’s all, like… it’s all… Greg… Greg’s too controlling, I think, is kind of the gist of it, but… I don’t know, I think we have to…
359 00:38:23.850 ⇒ 00:38:26.580 Uttam Kumaran: No, I mean, it’s not what I mean, we don’t… we… we work…
360 00:38:26.880 ⇒ 00:38:32.829 Uttam Kumaran: on behalf of trying to get them to succeed. So, I mean, I think… I don’t know what Phoebe’s play is here.
361 00:38:33.230 ⇒ 00:38:34.710 Uttam Kumaran: But yeah, like…
362 00:38:34.940 ⇒ 00:38:39.589 Uttam Kumaran: Clearly, but also, even just not having, like… there’s clearly some red flags on, like, how they…
363 00:38:39.700 ⇒ 00:38:42.369 Uttam Kumaran: Think about data and, like, this… the internal…
364 00:38:42.640 ⇒ 00:38:44.220 Robert Tseng: Yeah. Expertise.
365 00:38:44.740 ⇒ 00:38:48.620 Uttam Kumaran: So… So be it.
366 00:38:51.000 ⇒ 00:38:56.779 Robert Tseng: Okay, cool. Well, that’s it. I have to… I have an interview to jump to.
367 00:38:56.960 ⇒ 00:39:02.099 Robert Tseng: Yeah, anything else? I mean, I guess I’ll be on for another hour or so.
368 00:39:03.370 ⇒ 00:39:06.220 Uttam Kumaran: Yeah, maybe Ashwini or Wish, if you want to stay on, I can stay on.
369 00:39:07.110 ⇒ 00:39:08.470 Robert Tseng: Okay, I’ll…
370 00:39:08.470 ⇒ 00:39:09.020 Awaish Kumar: I don’t yep.
371 00:39:09.020 ⇒ 00:39:11.220 Robert Tseng: I’ll deal.
372 00:39:11.970 ⇒ 00:39:14.170 Awaish Kumar: Okay, alright, thanks, guys.
373 00:39:15.860 ⇒ 00:39:19.899 Uttam Kumaran: Or if you guys were gonna meet later, that’s also fine. I’m just doing some work, so…
374 00:39:21.310 ⇒ 00:39:24.699 Ashwini Sharma: I was about to sync up with Avesh after this call.
375 00:39:24.700 ⇒ 00:39:25.250 Uttam Kumaran: Okay, okay.
376 00:39:25.250 ⇒ 00:39:26.690 Ashwini Sharma: I think this is fine, yeah. Cool.
377 00:39:27.190 ⇒ 00:39:29.969 Ashwini Sharma: Feel free to drop if you have something else.
378 00:39:29.970 ⇒ 00:39:34.200 Uttam Kumaran: I’m just gonna listen, I’m just gonna listen in, I’m… Alright. Sending emails and stuff.
379 00:39:34.890 ⇒ 00:39:36.210 Ashwini Sharma: Okay, Avish.
380 00:39:36.210 ⇒ 00:39:37.050 Awaish Kumar: You know, sister.
381 00:39:37.050 ⇒ 00:39:39.150 Ashwini Sharma: Want to go back to the ticket?
382 00:39:39.820 ⇒ 00:39:44.519 Awaish Kumar: Yeah, Utam does actually have access to Dexter, like, 1Pass…
383 00:39:45.720 ⇒ 00:39:46.909 Ashwini Sharma: Hold on a second, Lyd.
384 00:39:48.250 ⇒ 00:39:48.710 Ashwini Sharma: One buck.
385 00:39:48.710 ⇒ 00:39:49.480 Uttam Kumaran: tablets.
386 00:39:50.710 ⇒ 00:39:51.660 Ashwini Sharma: on buses.
387 00:39:53.160 ⇒ 00:39:54.639 Uttam Kumaran: Let us make sure.
388 00:39:55.330 ⇒ 00:39:59.389 Ashwini Sharma: Oh, one bus, one bus, one bus, where’s one bus?
389 00:40:01.720 ⇒ 00:40:04.140 Ashwini Sharma: One plus account…
390 00:40:10.020 ⇒ 00:40:12.439 Uttam Kumaran: Let me, I’ll… I can check the vaults.
391 00:40:21.120 ⇒ 00:40:23.500 Awaish Kumar: For dashboarding… okay.
392 00:40:24.320 ⇒ 00:40:25.419 Ashwini Sharma: Let me share my screen.
393 00:40:25.420 ⇒ 00:40:39.910 Awaish Kumar: So once you have access to OnePass, I have sent you an email, engineering at rainforest.ai. You can see the username, password of those… that email in OnePass. Using that, you can log in to Daxter.
394 00:40:40.100 ⇒ 00:40:43.320 Awaish Kumar: Or I can send a link to the Dexter as well.
395 00:40:43.760 ⇒ 00:40:46.840 Ashwini Sharma: Yeah, I’m in one bus, and
396 00:40:47.660 ⇒ 00:40:50.239 Ashwini Sharma: What do you… what do I need to see? Which world.
397 00:40:50.240 ⇒ 00:40:54.189 Uttam Kumaran: Ref… refresh your… refresh now, you should see it.
398 00:41:01.360 ⇒ 00:41:02.710 Ashwini Sharma: This one? Shared World?
399 00:41:03.130 ⇒ 00:41:03.820 Uttam Kumaran: Eden.
400 00:41:04.610 ⇒ 00:41:05.710 Ashwini Sharma: Eden, okay.
401 00:41:06.670 ⇒ 00:41:11.559 Awaish Kumar: Yeah, it’s an engineering email. It should be in the brain forge, maybe?
402 00:41:12.330 ⇒ 00:41:13.240 Uttam Kumaran: Oh, okay.
403 00:41:15.800 ⇒ 00:41:19.999 Awaish Kumar: Yeah, and you can just search for, like, engineering in the top.
404 00:41:20.520 ⇒ 00:41:21.200 Ashwini Sharma: It’s gonna…
405 00:41:21.320 ⇒ 00:41:22.430 Awaish Kumar: search section.
406 00:41:28.300 ⇒ 00:41:29.590 Awaish Kumar: Brain For Shared World.
407 00:41:30.120 ⇒ 00:41:32.810 Ashwini Sharma: Rainforest shared world, okay.
408 00:41:38.380 ⇒ 00:41:40.680 Awaish Kumar: Yeah, just search for engineering.
409 00:41:45.420 ⇒ 00:41:46.260 Ashwini Sharma: This one?
410 00:41:47.420 ⇒ 00:41:49.420 Awaish Kumar: normally just enter so I can…
411 00:41:49.630 ⇒ 00:41:49.990 Ashwini Sharma: Okay.
412 00:41:49.990 ⇒ 00:41:52.839 Awaish Kumar: There’s, like, the Google account for engineering, yeah.
413 00:41:52.840 ⇒ 00:41:53.290 Ashwini Sharma: Yep.
414 00:41:53.290 ⇒ 00:41:56.350 Awaish Kumar: You can use that to log in to Dexter.
415 00:41:57.200 ⇒ 00:42:03.180 Awaish Kumar: Dexter, like, is an orchestration tool. You must be familiar with the name.
416 00:42:07.540 ⇒ 00:42:15.670 Awaish Kumar: external.io, and in that, you can see our pipelines, and I can also share the link for GitHub.
417 00:42:17.850 ⇒ 00:42:19.309 Ashwini Sharma: I’ll do your sign-in.
418 00:42:22.830 ⇒ 00:42:25.520 Awaish Kumar: Next to us, password, copy.
419 00:42:26.070 ⇒ 00:42:31.990 Awaish Kumar: Okay, and also, can you make sure you have access to this, repository I’ve shared in the slide?
420 00:42:31.990 ⇒ 00:42:35.610 Ashwini Sharma: Oh, where did it go?
421 00:42:36.860 ⇒ 00:42:47.749 Ashwini Sharma: when I tried to log in, right, it just sent an email to an inbox, but I didn’t use my email ID. I used something else. Is this the email ID that I used?
422 00:42:49.040 ⇒ 00:42:50.570 Awaish Kumar: But when signing in…
423 00:42:50.570 ⇒ 00:42:51.090 Ashwini Sharma: You didn’t.
424 00:42:51.090 ⇒ 00:42:53.309 Awaish Kumar: Kenny, can we try again? Can I see that?
425 00:42:54.460 ⇒ 00:42:55.269 Awaish Kumar: So, yeah.
426 00:42:55.700 ⇒ 00:42:56.400 Ashwini Sharma: Yeah, so…
427 00:42:56.400 ⇒ 00:42:59.800 Awaish Kumar: Sorry, FedEx.
428 00:43:01.150 ⇒ 00:43:04.499 Awaish Kumar: Sign in with Google? No, no, no, don’t write the email.
429 00:43:04.500 ⇒ 00:43:06.570 Ashwini Sharma: Occupin, not Google.
430 00:43:09.110 ⇒ 00:43:09.750 Ashwini Sharma: Alright.
431 00:43:09.750 ⇒ 00:43:13.689 Awaish Kumar: You can use a… you can sign into engineering, use another account, yeah.
432 00:43:20.340 ⇒ 00:43:25.650 Awaish Kumar: You can install the Chrome extension for one pass, and that will be easier.
433 00:43:26.720 ⇒ 00:43:28.650 Ashwini Sharma: Yeah, I will do that.
434 00:43:41.380 ⇒ 00:43:43.020 Ashwini Sharma: Oh, is this?
435 00:43:44.750 ⇒ 00:43:50.800 Ashwini Sharma: One second… This is what, with the authenticator app, right? With the camera, okay.
436 00:43:52.210 ⇒ 00:43:54.720 Ashwini Sharma: No, I don’t think I have that.
437 00:43:56.030 ⇒ 00:43:57.320 Awaish Kumar: Keep moving.
438 00:43:58.310 ⇒ 00:44:03.250 Uttam Kumaran: Also, if you install the 1Password extension, it should help.
439 00:44:05.100 ⇒ 00:44:05.720 Awaish Kumar: Yeah.
440 00:44:09.640 ⇒ 00:44:13.029 Awaish Kumar: On identical equipment and stuff…
441 00:44:13.030 ⇒ 00:44:14.130 Ashwini Sharma: Oh, I’m sorry.
442 00:44:14.960 ⇒ 00:44:16.519 Ashwini Sharma: Chrome extension…
443 00:44:19.780 ⇒ 00:44:21.120 Ashwini Sharma: Is this the one? No.
444 00:44:34.290 ⇒ 00:44:34.980 Awaish Kumar: So…
445 00:44:43.020 ⇒ 00:44:44.370 Awaish Kumar: Yeah, Nick.
446 00:44:45.700 ⇒ 00:44:46.999 Ashwini Sharma: Where is the extension?
447 00:44:48.730 ⇒ 00:44:51.100 Awaish Kumar: We’re gonna write Chrome extension…
448 00:44:52.890 ⇒ 00:44:53.810 Ashwini Sharma: That’s what it says.
449 00:44:53.810 ⇒ 00:44:55.260 Awaish Kumar: I’ll send you the…
450 00:44:55.260 ⇒ 00:44:56.160 Ashwini Sharma: choose to.
451 00:44:56.160 ⇒ 00:44:56.980 Awaish Kumar: Absolutely.
452 00:44:57.500 ⇒ 00:44:59.069 Ashwini Sharma: Send me the link.
453 00:44:59.350 ⇒ 00:45:00.710 Awaish Kumar: On… in Slack.
454 00:45:00.710 ⇒ 00:45:02.070 Ashwini Sharma: This one? Okay.
455 00:45:05.010 ⇒ 00:45:06.330 Ashwini Sharma: One password, okay.
456 00:45:16.450 ⇒ 00:45:18.839 Ashwini Sharma: Alright, sign in…
457 00:45:20.370 ⇒ 00:45:21.110 Awaish Kumar: Okay.
458 00:45:21.590 ⇒ 00:45:29.559 Awaish Kumar: But yeah, once that’s done, you can choose your engineering Gmail account to log in, and…
459 00:45:30.080 ⇒ 00:45:36.770 Awaish Kumar: Also, I’ve shared the link for GitHub account, if you can… GitHub repository, if you can just take…
460 00:45:37.530 ⇒ 00:45:40.789 Awaish Kumar: On the link, and make sure that you have access to that repository.
461 00:45:40.990 ⇒ 00:45:42.449 Ashwini Sharma: Hold on a second.
462 00:45:45.850 ⇒ 00:45:47.989 Ashwini Sharma: Let’s do one thing at a time,
463 00:45:51.050 ⇒ 00:45:53.500 Ashwini Sharma: Whoa, okay.
464 00:45:54.080 ⇒ 00:45:55.310 Ashwini Sharma: Tutorial.
465 00:45:57.860 ⇒ 00:45:59.310 Ashwini Sharma: Alright, none.
466 00:45:59.310 ⇒ 00:46:02.109 Awaish Kumar: In the meantime, let me open one box.
467 00:46:02.110 ⇒ 00:46:05.119 Ashwini Sharma: Click this one in your browser toolbar, alright?
468 00:46:05.910 ⇒ 00:46:10.679 Ashwini Sharma: Okay, so what I was trying to do was trying to log into this one, right? Daxter?
469 00:46:13.590 ⇒ 00:46:18.079 Awaish Kumar: Yeah, try logging into a Gmail Next account again.
470 00:46:18.080 ⇒ 00:46:18.770 Ashwini Sharma: Okay.
471 00:46:21.490 ⇒ 00:46:22.960 Ashwini Sharma: Next.io.
472 00:46:23.290 ⇒ 00:46:26.280 Awaish Kumar: Yeah, yeah, you can just say, try again here.
473 00:46:26.490 ⇒ 00:46:26.980 Ashwini Sharma: Okay.
474 00:46:26.980 ⇒ 00:46:27.970 Awaish Kumar: 21st.
475 00:46:30.370 ⇒ 00:46:32.190 Ashwini Sharma: Okay, sign in with Google.
476 00:46:33.110 ⇒ 00:46:35.379 Ashwini Sharma: And… what is this? No.
477 00:46:35.830 ⇒ 00:46:36.350 Ashwini Sharma: Who’s okay.
478 00:46:36.350 ⇒ 00:46:37.320 Uttam Kumaran: Engineering.
479 00:46:37.920 ⇒ 00:46:40.960 Uttam Kumaran: Yeah, so engineering at Brainforge, so you’ll see it here.
480 00:46:40.960 ⇒ 00:46:42.630 Ashwini Sharma: Yeah. Oh, okay.
481 00:46:43.480 ⇒ 00:46:48.640 Uttam Kumaran: So, yeah, it’ll just… it’ll automatically kind of go through and then hit continue.
482 00:46:49.520 ⇒ 00:46:52.910 Ashwini Sharma: Or try another way, because… okay, let’s…
483 00:46:54.700 ⇒ 00:46:55.499 Uttam Kumaran: And hit sign in.
484 00:46:55.500 ⇒ 00:46:56.830 Ashwini Sharma: Oh, okay.
485 00:47:02.630 ⇒ 00:47:04.499 Ashwini Sharma: Use Chrome without an account.
486 00:47:09.170 ⇒ 00:47:09.850 Awaish Kumar: Thank you.
487 00:47:29.370 ⇒ 00:47:30.340 Ashwini Sharma: Alright.
488 00:47:30.910 ⇒ 00:47:34.129 Ashwini Sharma: Okay, what do we have over here? Some pipeline.
489 00:47:39.060 ⇒ 00:47:41.809 Ashwini Sharma: What is the name of the pipeline that we are looking at?
490 00:47:41.810 ⇒ 00:47:47.099 Awaish Kumar: I have sent you the link of the GitHub pipeline. If you can open that, I can…
491 00:47:47.260 ⇒ 00:47:48.629 Ashwini Sharma: Get up this one.
492 00:47:48.630 ⇒ 00:47:49.180 Awaish Kumar: Excellent.
493 00:47:49.500 ⇒ 00:47:58.469 Awaish Kumar: And on the Slack? In the Slack. Yeah, this one. There’s another link for the repository itself, for the pipeline itself.
494 00:48:02.650 ⇒ 00:48:03.960 Awaish Kumar: Alright. Yeah.
495 00:48:04.580 ⇒ 00:48:18.169 Awaish Kumar: this is the pipeline, it says Catalyst Orders Pipeline, and right now, what it is doing is basically, it just reads data from a table called order…
496 00:48:18.460 ⇒ 00:48:21.810 Awaish Kumar: Affect orders, and then there’s some…
497 00:48:24.470 ⇒ 00:48:33.109 Awaish Kumar: joins and, and, filters out on… on some slugs, and uses the rejects for that. And that’s, like.
498 00:48:33.820 ⇒ 00:48:35.209 Ashwini Sharma: Sorry, what’s a slug?
499 00:48:36.100 ⇒ 00:48:40.979 Awaish Kumar: Slug is just a sub, what you say, in a URL, you have a…
500 00:48:41.200 ⇒ 00:48:45.029 Awaish Kumar: It’s a part of URL, so it’s just, like, a substring.
501 00:48:45.180 ⇒ 00:48:45.960 Awaish Kumar: Individuality.
502 00:48:45.960 ⇒ 00:48:46.450 Ashwini Sharma: Okay.
503 00:48:47.100 ⇒ 00:48:51.509 Awaish Kumar: But that is an identifi- like, identification for…
504 00:48:51.630 ⇒ 00:49:00.400 Awaish Kumar: Identifying the… the channel from where basically.
505 00:49:01.100 ⇒ 00:49:10.110 Awaish Kumar: kind of… it’s a way to figure out from where this URL got hit, like, either got clicked, So…
506 00:49:10.110 ⇒ 00:49:10.750 Ashwini Sharma: DM.
507 00:49:11.260 ⇒ 00:49:15.199 Awaish Kumar: kind of UTM, but not exactly the UT YAM, it’s more like a…
508 00:49:15.300 ⇒ 00:49:24.810 Awaish Kumar: We have some forms. You can think of them as Google Forms. So, we have some forms from… specifically for some
509 00:49:25.250 ⇒ 00:49:32.320 Awaish Kumar: partners, partner channels, and when they click… when any customer come through that URL,
510 00:49:32.510 ⇒ 00:49:36.399 Awaish Kumar: That means we are going to assign a reward for that.
511 00:49:36.710 ⇒ 00:49:46.590 Awaish Kumar: channel. And, and we identify that using the slug, which is a substring of the URL.
512 00:49:46.840 ⇒ 00:49:51.530 Awaish Kumar: And if you just maybe search for slug, You can find it.
513 00:49:51.640 ⇒ 00:49:54.020 Awaish Kumar: rejects in this code.
514 00:49:54.380 ⇒ 00:50:04.510 Awaish Kumar: Which… which is, like, hard… hard-coding 4 or 5 different slugs. And now, what we want to do is, we want to make it general purpose, so instead of
515 00:50:04.770 ⇒ 00:50:09.420 Awaish Kumar: hard-coding those slugs, we are going to read it from a table in BigQuery.
516 00:50:09.740 ⇒ 00:50:14.360 Awaish Kumar: And I can share you also the… Is this a.
517 00:50:14.360 ⇒ 00:50:18.329 Ashwini Sharma: standalone pipeline? Like, is there any dependencies on other files?
518 00:50:18.330 ⇒ 00:50:21.970 Awaish Kumar: as a standalone pipeline, all India.
519 00:50:21.970 ⇒ 00:50:23.350 Ashwini Sharma: Yeah.
520 00:50:24.180 ⇒ 00:50:26.389 Ashwini Sharma: I didn’t find the text slug over here.
521 00:50:27.630 ⇒ 00:50:36.790 Awaish Kumar: Oh, okay, oh, sorry. So that’s… yeah, you’re right. So this is…
522 00:50:38.280 ⇒ 00:50:43.459 Awaish Kumar: Yeah, we don’t have… like, this pipeline… okay, so you don’t have to make any changes in this pipeline.
523 00:50:43.460 ⇒ 00:50:43.810 Ashwini Sharma: Okay.
524 00:50:43.810 ⇒ 00:50:45.900 Awaish Kumar: So we have a…
525 00:50:45.900 ⇒ 00:50:47.820 Uttam Kumaran: A table here in this…
526 00:50:47.820 ⇒ 00:50:50.930 Awaish Kumar: pipeline, which is called Catalyst Successful Orders.
527 00:50:51.790 ⇒ 00:50:52.365 Ashwini Sharma: Mmm…
528 00:50:52.940 ⇒ 00:50:57.219 Awaish Kumar: Source table. When we are saying read, yeah, this one, source stable.
529 00:50:57.350 ⇒ 00:51:10.139 Awaish Kumar: Yeah, so this table is part of an analytics DBT project, where I’m using those slugs to identify, basically, doing some transformation and identifying,
530 00:51:10.140 ⇒ 00:51:17.900 Awaish Kumar: the orders which we really want to assign to Catalyst. Catalyst is a marketing channel, and
531 00:51:18.670 ⇒ 00:51:25.680 Awaish Kumar: So, for that, you have to go into the, aiden’s, analytics repository.
532 00:51:25.850 ⇒ 00:51:29.210 Awaish Kumar: So, I can also send you the link for that.
533 00:51:29.210 ⇒ 00:51:29.650 Ashwini Sharma: This one?
534 00:51:29.650 ⇒ 00:51:32.160 Awaish Kumar: He didn’t…
535 00:51:32.770 ⇒ 00:51:42.279 Awaish Kumar: Yeah, that’s the table name, which is being… which is a result of that dbt model. I can just share you with the repository.
536 00:51:47.030 ⇒ 00:51:56.840 Awaish Kumar: Yeah, it’s called Triadian Analytics, and I’ve sent you the link in the swag, this one.
537 00:51:59.590 ⇒ 00:52:00.630 Ashwini Sharma: Alright.
538 00:52:00.630 ⇒ 00:52:04.659 Awaish Kumar: In the dbt project, sales, I think, model sales.
539 00:52:06.970 ⇒ 00:52:07.730 Ashwini Sharma: Models…
540 00:52:07.730 ⇒ 00:52:15.910 Awaish Kumar: March sales, yeah. And inside of that, you can find out that same Catalyst Explorers model.
541 00:52:17.460 ⇒ 00:52:19.569 Ashwini Sharma: Is this different from this one?
542 00:52:21.290 ⇒ 00:52:21.740 Awaish Kumar: Which one?
543 00:52:21.740 ⇒ 00:52:24.849 Ashwini Sharma: Yeah, this is the same repo, yeah, I have it, okay.
544 00:52:26.130 ⇒ 00:52:27.840 Awaish Kumar: Search for Caterpillar Successful Order.
545 00:52:27.840 ⇒ 00:52:31.039 Ashwini Sharma: Oh, sorry, you’re not able to see my screen right now, right?
546 00:52:31.500 ⇒ 00:52:31.939 Uttam Kumaran: No, we can.
547 00:52:31.940 ⇒ 00:52:35.300 Awaish Kumar: You can just click on Catalyst Successful Order Model.
548 00:52:35.830 ⇒ 00:52:38.069 Ashwini Sharma: Oh, we…
549 00:52:38.070 ⇒ 00:52:39.110 Uttam Kumaran: Here in GitHub.
550 00:52:39.430 ⇒ 00:52:43.340 Ashwini Sharma: Oh, sorry, sorry, one second, let me share the,
551 00:52:44.500 ⇒ 00:52:47.369 Ashwini Sharma: Let me share the desktop itself, yeah.
552 00:52:48.510 ⇒ 00:52:49.280 Ashwini Sharma: Yeah.
553 00:52:50.000 ⇒ 00:52:54.840 Awaish Kumar: So, we are seeing your… Code, okay.
554 00:52:54.840 ⇒ 00:52:56.690 Ashwini Sharma: Yeah, I’m in Khasar.
555 00:52:56.690 ⇒ 00:52:57.580 Awaish Kumar: With that. Okay.
556 00:52:58.030 ⇒ 00:53:03.999 Awaish Kumar: So now this rejects… yeah, now line number 23 has these slugs.
557 00:53:05.520 ⇒ 00:53:05.980 Ashwini Sharma: Okay.
558 00:53:05.980 ⇒ 00:53:20.920 Awaish Kumar: So this is basically the hard-coded part. We want to update that model to basically not hard-code it here, just read from the table, which is called, the…
559 00:53:21.480 ⇒ 00:53:28.970 Awaish Kumar: attribution page URL slugs, which I’m just sending you in the Slack Shannon?
560 00:53:30.720 ⇒ 00:53:38.029 Awaish Kumar: So instead, what we are going to do, we are going to read slugs from this table for channel…
561 00:53:39.800 ⇒ 00:53:45.450 Awaish Kumar: catalysts, and then use those slugs for
562 00:53:46.090 ⇒ 00:53:51.430 Awaish Kumar: Like, for that rejects XP filtering part.
563 00:54:00.460 ⇒ 00:54:05.290 Ashwini Sharma: Okay, what’s there in the table? These are the slugs, only 5 slugs that you have?
564 00:54:06.720 ⇒ 00:54:24.959 Awaish Kumar: Yeah, right now, we only have 4 catalysts, so these are only 5 ones, which are already hard-coded, but we just want to make it general purpose, so that if tomorrow we have more slugs for Catalysts, or we… even if we have slugs for some other channel, we can… the pipeline just works.
565 00:54:24.960 ⇒ 00:54:29.040 Ashwini Sharma: As… Got it. How are you populating this table?
566 00:54:29.520 ⇒ 00:54:37.440 Awaish Kumar: This is being populated by… the Zoran, like, it’s… like, the different team, you can say. Like, the…
567 00:54:37.580 ⇒ 00:54:41.840 Awaish Kumar: the Aiden team, which are basically responsible for creating those slugs.
568 00:54:42.330 ⇒ 00:54:43.559 Awaish Kumar: The clientele.
569 00:54:44.240 ⇒ 00:54:49.950 Ashwini Sharma: Okay, is he doing a manual update on this, or is there a Which does it, or…
570 00:54:49.950 ⇒ 00:54:59.109 Awaish Kumar: I’m not sure, like, right now, he, he is doing manual update, but maybe they have something on their site, some scripts or whatever.
571 00:54:59.110 ⇒ 00:55:15.940 Ashwini Sharma: So what you’re saying is, like, I need to remove this one and replace this thing, whatever is there, I mean, 5 or 10, you know, in future, it might grow or reduce, right? Just use the values in that, and get rid of this hard coding, right?
572 00:55:16.790 ⇒ 00:55:28.459 Awaish Kumar: Yeah, yeah. Just use the values from there, but make sure to have a filter on channel catalysts. So we are… we know that we are only… we are using slugs for catalysts. Right now, it’s only for catalysts.
573 00:55:28.460 ⇒ 00:55:28.900 Ashwini Sharma: God.
574 00:55:28.900 ⇒ 00:55:29.330 Awaish Kumar: So…
575 00:55:29.330 ⇒ 00:55:29.880 Ashwini Sharma: Right.
576 00:55:29.880 ⇒ 00:55:32.789 Awaish Kumar: Tomorrow, it can be another channel as well, here.
577 00:55:41.150 ⇒ 00:55:41.750 Ashwini Sharma: ordered.
578 00:55:41.930 ⇒ 00:55:42.780 Ashwini Sharma: Alright.
579 00:55:43.730 ⇒ 00:55:45.310 Ashwini Sharma: Yeah, that’s Leaky Monkey.
580 00:55:48.120 ⇒ 00:55:57.029 Ashwini Sharma: Cool. Alright, I got this, I’ll take care of it. And, the other thing is…
581 00:55:57.920 ⇒ 00:56:06.039 Ashwini Sharma: So, okay, give me a little bit of introduction on, on the workflow of how you
582 00:56:07.840 ⇒ 00:56:11.710 Ashwini Sharma: push code into broad, like, I just saw one…
583 00:56:11.710 ⇒ 00:56:12.190 Awaish Kumar: DVD?
584 00:56:12.190 ⇒ 00:56:12.770 Ashwini Sharma: pool.
585 00:56:13.480 ⇒ 00:56:31.859 Awaish Kumar: So, in this repository, analytics for even, what you have to do is, basically, you will basically just create another branch, make the changes, create a PR. On the PR, we have set up some validations, so GitHub Actions will run, it will initiate a
586 00:56:31.970 ⇒ 00:56:40.250 Awaish Kumar: a GitHub run, and we are going to see if it works fine on the staging. It will create some tables in the…
587 00:56:40.490 ⇒ 00:56:50.170 Awaish Kumar: staging, in BigQuery, and if it all goes okay, we can just… we will review it. You can assign it to me, or Damilare.
588 00:56:50.360 ⇒ 00:56:53.319 Awaish Kumar: Yeah, and we can review…
589 00:56:53.320 ⇒ 00:56:59.480 Ashwini Sharma: How do I test this thing locally? Like, is there any way I can test it locally before I push in the PR?
590 00:57:00.280 ⇒ 00:57:11.440 Awaish Kumar: So you can basically set up the repository locally, you can install dbt code, and you can run commands like dbt run with the target flag as a tab.
591 00:57:11.470 ⇒ 00:57:22.649 Awaish Kumar: So we have, like, you have to… you will need a profile, like, set uptheprofiles.yml in your local repository, where you are going to set it up using,
592 00:57:23.450 ⇒ 00:57:29.490 Awaish Kumar: You’re… Like, we have a JSON file service account.
593 00:57:29.780 ⇒ 00:57:32.010 Awaish Kumar: Key for the service account.
594 00:57:32.240 ⇒ 00:57:35.069 Awaish Kumar: And I can share it with you, and then,
595 00:57:35.260 ⇒ 00:57:40.279 Awaish Kumar: using that, you will set up your profiles.yml, and we have set up the
596 00:57:40.690 ⇒ 00:57:53.850 Awaish Kumar: the repository in a way that if you provide target flag dev, it is… it is all going to write into the… only in the dev tables. So if you go in the…
597 00:57:54.470 ⇒ 00:57:58.880 Awaish Kumar: BigQuery, and search for dev underscore, you will see…
598 00:58:03.680 ⇒ 00:58:05.900 Awaish Kumar: some dev schemas.
599 00:58:09.240 ⇒ 00:58:12.459 Ashwini Sharma: Where was the thing to reduce the size? Yeah.
600 00:58:12.540 ⇒ 00:58:14.170 Awaish Kumar: So…
601 00:58:14.170 ⇒ 00:58:15.610 Ashwini Sharma: Eden Warehouse.
602 00:58:16.960 ⇒ 00:58:19.579 Ashwini Sharma: And everybody does it over here?
603 00:58:20.620 ⇒ 00:58:21.460 Awaish Kumar: Sorry?
604 00:58:22.060 ⇒ 00:58:22.980 Ashwini Sharma: Everybody…
605 00:58:22.980 ⇒ 00:58:23.410 Awaish Kumar: This is a…
606 00:58:23.410 ⇒ 00:58:24.899 Ashwini Sharma: It’s the table? Yeah.
607 00:58:26.090 ⇒ 00:58:33.050 Awaish Kumar: So dbt raw is a… basically, it has all the raw tables for all of our sources.
608 00:58:33.150 ⇒ 00:58:50.119 Awaish Kumar: data is being ingested, in… so it depends how it goes. Like, right now, it’s not going all into dbt raw, it’s… so we have some data coming from Bask, which is, like, has its own schema, then we have some data from,
609 00:58:50.750 ⇒ 00:59:06.439 Awaish Kumar: polyatomic, so it says polyatomic underscore something. Like, the raw data is spread across different schemas, but for the staging and production, we have these… and then the development for the dbt project. We have dev dbt mods, like, prod dbt mods.
610 00:59:06.630 ⇒ 00:59:14.100 Awaish Kumar: And, prod, dbt intermediate, so all these, these are the schemas, basically, you are going to use for dev staging, and production.
611 00:59:15.760 ⇒ 00:59:17.449 Ashwini Sharma: Okay, but when I…
612 00:59:17.450 ⇒ 00:59:18.890 Awaish Kumar: Consents on the topic.
613 00:59:19.290 ⇒ 00:59:19.780 Ashwini Sharma: Yeah, yeah, yeah.
614 00:59:19.780 ⇒ 00:59:27.649 Awaish Kumar: If you run it locally with a target flag dev, these will going to end up in dev underscore Mars, dev underscore dbt intermediate.
615 00:59:29.360 ⇒ 00:59:30.150 Ashwini Sharma: Okay.
616 00:59:31.620 ⇒ 00:59:37.929 Ashwini Sharma: And that is common across multiple people, right? So, basically, if you run locally, and if I run locally.
617 00:59:38.140 ⇒ 00:59:45.169 Awaish Kumar: Yeah, it’s the same for all the devs. We are… we are going to use same schema for all the developers.
618 00:59:48.130 ⇒ 00:59:49.630 Ashwini Sharma: Okay, got it.
619 00:59:52.900 ⇒ 00:59:58.750 Ashwini Sharma: Alrighty, can you share me that, profile, configuration for BigQuery?
620 01:00:01.060 ⇒ 01:00:02.730 Awaish Kumar: Oh, yeah, okay.
621 01:00:09.440 ⇒ 01:00:11.640 Awaish Kumar: I will… I will just share in the Slack.
622 01:00:12.400 ⇒ 01:00:13.060 Ashwini Sharma: Yep.
623 01:00:15.240 ⇒ 01:00:19.789 Awaish Kumar: Yeah, if you need just anything else, just let me know.
624 01:00:21.200 ⇒ 01:00:22.660 Awaish Kumar: Oh, yeah.
625 01:00:26.800 ⇒ 01:00:30.409 Awaish Kumar: Well, yeah, Ashwini, if you get blocked by running dbt locally.
626 01:00:30.450 ⇒ 01:00:31.439 Uttam Kumaran: Send a note.
627 01:00:31.720 ⇒ 01:00:36.959 Uttam Kumaran: Yeah, give it a go. This one, we’re running dbt Core.
628 01:00:37.200 ⇒ 01:00:42.219 Uttam Kumaran: Honestly, Awash, we should… maybe we can even consider moving them to cloud.
629 01:00:43.640 ⇒ 01:00:44.380 Uttam Kumaran: Next year.
630 01:00:44.380 ⇒ 01:00:45.359 Awaish Kumar: Oh, okay.
631 01:00:45.520 ⇒ 01:00:46.340 Awaish Kumar: Yeah, we can.
632 01:00:47.660 ⇒ 01:00:49.170 Uttam Kumaran: Yeah, check it out.
633 01:00:52.110 ⇒ 01:00:53.900 Uttam Kumaran: Okay, I’m gonna drop, guys.
634 01:00:55.280 ⇒ 01:00:56.769 Awaish Kumar: Okay, I think we are also done.
635 01:00:56.770 ⇒ 01:00:57.250 Ashwini Sharma: Honestly.
636 01:00:57.250 ⇒ 01:01:00.470 Awaish Kumar: I’ve shared you the profiles.weimer file.
637 01:01:00.990 ⇒ 01:01:07.400 Awaish Kumar: it uses an environment variable for Google credentials, and I’m just going to share the…
638 01:01:07.550 ⇒ 01:01:10.419 Awaish Kumar: The service count, key file, yeah.
639 01:01:14.270 ⇒ 01:01:16.189 Ashwini Sharma: Is it the BigQuery adapter that you’re using?
640 01:01:17.340 ⇒ 01:01:18.350 Awaish Kumar: Yes, yes.
641 01:01:20.370 ⇒ 01:01:23.970 Awaish Kumar: So, I think Rapo will have some requirements.txt or something.
642 01:01:24.230 ⇒ 01:01:31.369 Ashwini Sharma: Requirements.txt, it’s that.
643 01:01:36.580 ⇒ 01:01:37.740 Ashwini Sharma: on it.
644 01:01:38.640 ⇒ 01:01:39.929 Awaish Kumar: Okay, thank you.
645 01:01:40.320 ⇒ 01:01:42.209 Ashwini Sharma: Okay, thanks. Thanks, Alish.
646 01:01:42.210 ⇒ 01:01:42.990 Uttam Kumaran: Thank you.
647 01:01:43.440 ⇒ 01:01:44.780 Uttam Kumaran: deal with them. Bye. Bye.