Meeting Title: Javvy Coffee Planning Date: 2025-01-28 Meeting participants: Nicolas Sucari, Uttam Kumaran, Payas Parab, Robert Tseng
WEBVTT
1 00:00:28.780 ⇒ 00:00:29.739 Nicolas Sucari: Hey, Robert.
2 00:00:31.080 ⇒ 00:00:32.020 Robert Tseng: Hey? Nico.
3 00:01:30.340 ⇒ 00:01:31.340 Payas Parab: Oh, what’s up, guys?
4 00:01:34.300 ⇒ 00:01:35.050 Nicolas Sucari: You pay us.
5 00:01:35.050 ⇒ 00:01:35.800 Robert Tseng: Class.
6 00:01:36.030 ⇒ 00:01:45.060 Payas Parab: Just met with Nico. And Dan, too. My bad brain’s a little fuzzy. Sorry.
7 00:01:45.060 ⇒ 00:01:46.000 Nicolas Sucari: That’s fine!
8 00:01:46.690 ⇒ 00:01:50.460 Robert Tseng: What happened you got you got knocked down by a sickness.
9 00:01:51.390 ⇒ 00:02:10.820 Payas Parab: Dude. I don’t even know what it is. I’m like I like, it’s like, it’s like, I almost feel like, I wish I was like completely knocked out. It’s like sort of this, like halfway bullshit, where it’s like I can’t. I’m like kind of sick, and then can’t sleep, and then it like cascades and like, I don’t know if, like right now, I’m just like out of it, because I’m sleep deprived, or if I’m like, actually sick, does that make sense.
10 00:02:10.820 ⇒ 00:02:12.160 Robert Tseng: Yeah, I got you.
11 00:02:14.980 ⇒ 00:02:18.090 Payas Parab: Yeah. Anyway, how are you guys doing.
12 00:02:19.470 ⇒ 00:02:20.100 Uttam Kumaran: Long time.
13 00:02:20.100 ⇒ 00:02:20.780 Robert Tseng: Go ahead!
14 00:02:24.330 ⇒ 00:02:26.479 Uttam Kumaran: We just talked like 10 min ago.
15 00:02:27.610 ⇒ 00:02:29.280 Uttam Kumaran: I’m still doing well. Bias.
16 00:02:29.540 ⇒ 00:02:32.819 Payas Parab: That’s good to hear. Glad to hear. Things haven’t changed on the ride home.
17 00:02:33.875 ⇒ 00:02:39.040 Uttam Kumaran: Yeah, I’ve just parked the car successful parking.
18 00:02:40.030 ⇒ 00:02:44.659 Payas Parab: That’s good dude in person, man, that’s the the old school way of doing things. I like it, man.
19 00:02:45.080 ⇒ 00:02:45.800 Robert Tseng: That’s the way.
20 00:02:46.040 ⇒ 00:02:47.769 Payas Parab: I love that old school shit.
21 00:02:47.770 ⇒ 00:02:51.050 Uttam Kumaran: Have any Martinis, or there was no drinks, but
22 00:02:51.500 ⇒ 00:02:55.419 Uttam Kumaran: we broke bread, but it was sushi. But yeah, you get the thing.
23 00:02:55.830 ⇒ 00:02:56.380 Payas Parab: It’s okay.
24 00:02:56.380 ⇒ 00:03:00.639 Payas Parab: One day one day we’ll bring it back to like Wall Street in the eighties, you know. It’ll just be like
25 00:03:00.990 ⇒ 00:03:01.700 Payas Parab: me.
26 00:03:01.700 ⇒ 00:03:03.320 Uttam Kumaran: Is there any Martinis.
27 00:03:03.320 ⇒ 00:03:08.549 Payas Parab: Dustin skyscraper, and I’m on just doing blow at lunch. You know. The good old days.
28 00:03:12.770 ⇒ 00:03:14.939 Uttam Kumaran: Yeah, with a lot.
29 00:03:15.500 ⇒ 00:03:19.890 Payas Parab: Dude. I actually feel like I’m on rages, low key like parties like.
30 00:03:20.116 ⇒ 00:03:26.459 Uttam Kumaran: I do. No dude. He’s he seems pretty cool, I mean. Yeah, he seems pretty cool. I want to get to know him more. I would like to.
31 00:03:26.460 ⇒ 00:03:32.000 Payas Parab: Literally. Besides, J, money like they’re actually like a dope team of like chill people like that’s that’s the sense of.
32 00:03:32.000 ⇒ 00:03:34.779 Uttam Kumaran: Pretty sure a month that he ran an agency before, or something.
33 00:03:34.780 ⇒ 00:03:35.770 Payas Parab: Really.
34 00:03:35.770 ⇒ 00:03:38.599 Uttam Kumaran: Yeah, like, I don’t know something about that. But.
35 00:03:38.600 ⇒ 00:03:51.148 Payas Parab: Like I remember at some point like vaguely mentioned, is like we just came back from like the Vegas offsite or something. And I was like, Yeah, yeah, he’s like, I’m still recovering like, 2 days later, I was like dude. That must have been a fucking Bender.
36 00:03:51.410 ⇒ 00:03:53.559 Uttam Kumaran: So much coffee, dude, so much coffee.
37 00:03:53.560 ⇒ 00:04:03.650 Payas Parab: So much coffee. Just everything is a mixed Javi coffee drink that’s espresso Martinis, Javi. Coffee espresso.
38 00:04:07.460 ⇒ 00:04:12.909 Payas Parab: No, I I think it’s also they’re like young, too, right? Like I mean, Justin Justin is like, roughly our age. I’m pretty sure.
39 00:04:14.130 ⇒ 00:04:16.510 Uttam Kumaran: Interesting. Okay, I have. No, I have no idea.
40 00:04:16.519 ⇒ 00:04:17.529 Robert Tseng: Younger. But yeah.
41 00:04:17.529 ⇒ 00:04:21.739 Payas Parab: He might be younger. Yeah, he might be younger. And same with the other guy. Not
42 00:04:21.849 ⇒ 00:04:26.260 Payas Parab: who’s the other? Guy Brandon’s on the younger side, right.
43 00:04:26.260 ⇒ 00:04:29.070 Robert Tseng: No, Brandon’s actually older. I think he’s in his thirties.
44 00:04:29.410 ⇒ 00:04:33.584 Payas Parab: Brandon’s in his thirties. Okay, I love like our benchmark, for, like older, is in his thirties.
45 00:04:35.930 ⇒ 00:04:36.630 Robert Tseng: Yeah.
46 00:04:37.180 ⇒ 00:04:37.730 Payas Parab: Okay.
47 00:04:38.280 ⇒ 00:04:44.432 Robert Tseng: Alright guys, let’s give Joby some love. What’s what’s going on? What do we gotta do for the future?
48 00:04:45.480 ⇒ 00:04:47.646 Robert Tseng: let me see, I guess.
49 00:04:48.570 ⇒ 00:04:51.229 Robert Tseng: I’ll I’ll drive the call this time.
50 00:04:52.360 ⇒ 00:04:58.149 Uttam Kumaran: Yeah. And I think we all know sort of what’s the gross margin, and and I don’t want to talk about portable at all
51 00:04:58.430 ⇒ 00:05:04.569 Uttam Kumaran: after this week. So like, let’s after all, that I kind of want to know what the future vision is like.
52 00:05:04.910 ⇒ 00:05:23.439 Robert Tseng: Yeah, cool. I mean, I didn’t really get into. Do all the clicking around. I wanted to yet. Gonna do that. Now, I’ve actually started it now. But maybe we’ll start here from these objectives, because this is what amaz looking at, he looks at this every week. And he’s like these are the projects we told him. We’re working on, and like the things that are
53 00:05:23.780 ⇒ 00:05:32.650 Robert Tseng: that will and some rough estimate of, like the timelines he understands now that these hours are kind of flexible. And you guys have a
54 00:05:32.770 ⇒ 00:05:40.459 Robert Tseng: good enough dynamic with him that he’s kind of redirecting the time, which is fine. But this definitely needs to track with what we’re doing.
55 00:05:40.750 ⇒ 00:06:00.359 Robert Tseng: I don’t think this really lines up with our tickets right now. So, Nico, I think this is kind of a call out to you to make sure that we have this kind of sorted out like first, st I don’t really know why everything got moved to February. We’ve been working with them for a month. So it looks like we basically did nothing for a month. And I don’t want Jared to come in here, or and just be like, what the hell.
56 00:06:00.360 ⇒ 00:06:08.870 Nicolas Sucari: No, I I was not aware they were looking at this. But yeah, well, I I can move the dates just to make it as real as possible.
57 00:06:09.130 ⇒ 00:06:13.630 Robert Tseng: Yeah, so it’s just like these, are we call projects here. But these are really like.
58 00:06:14.060 ⇒ 00:06:18.020 Robert Tseng: yeah, sure, we can call them projects. But the tasks to roll up to the projects.
59 00:06:18.590 ⇒ 00:06:33.758 Robert Tseng: I mean, we call them objectives here. So whatever we call them, let’s just keep that consistent. And yeah, I think for me. I have to be looking at this weekly, and I want to make sure that we’re calling these projects right. What? Whatever it makes sense to them. So
60 00:06:34.170 ⇒ 00:06:50.679 Robert Tseng: yeah, I think when when Aman looks like this, I wanted to be able to see what are the like things that are happening in parallel to have a clearer sense of like when things are wrapping up. So that’s that’s the purpose of this. So I think we definitely need to make this more clear.
61 00:06:52.460 ⇒ 00:06:53.300 Nicolas Sucari: I mean.
62 00:06:53.300 ⇒ 00:07:10.879 Nicolas Sucari: we can. We can create like different projects with these kind of titles, and build the like the tasks to to that project. What do you think? Like we? We have the data, the data and AI dashboard, where we can create projects for each of these.
63 00:07:10.880 ⇒ 00:07:11.570 Robert Tseng: But I guess like
64 00:07:11.570 ⇒ 00:07:15.480 Robert Tseng: about how these relations will work. I’m just saying like we should make it happen. That’s the.
65 00:07:15.480 ⇒ 00:07:20.579 Uttam Kumaran: Yeah, I guess, like, I don’t know. Yeah, even looking at this, too, like we’ve been working since the 10th
66 00:07:21.050 ⇒ 00:07:23.919 Uttam Kumaran: like, why isn’t the start dates for these, the 10.th
67 00:07:24.760 ⇒ 00:07:38.620 Nicolas Sucari: No, because this is something like it was static just to show some timeline. But this is has no relation with every other task that we’re working on. I mean, this needs to be manually changed every time we need to do something. That’s why that’s what I’m saying.
68 00:07:38.620 ⇒ 00:07:40.080 Nicolas Sucari: Yeah, I agree.
69 00:07:40.080 ⇒ 00:07:47.380 Nicolas Sucari: if we wanna if we want to build these like automatically, with with all of the tasks that we have, we can do that. But we need to create like.
70 00:07:47.380 ⇒ 00:07:51.049 Uttam Kumaran: No, we don’t need to build. We don’t need to build automatically. Just drag it.
71 00:07:51.510 ⇒ 00:07:53.610 Nicolas Sucari: Okay, yeah, just okay, okay.
72 00:07:53.610 ⇒ 00:07:57.070 Uttam Kumaran: Yeah, just drag it because we just want this to be accurate.
73 00:07:57.330 ⇒ 00:08:01.029 Uttam Kumaran: And like, hopefully, ideally, this, this shouldn’t change. But again, like
74 00:08:01.440 ⇒ 00:08:08.079 Uttam Kumaran: this is as easy as being like the message I sent to Jared, which is like, What do we get done? We wanted to make it a little bit easier. So
75 00:08:08.250 ⇒ 00:08:10.209 Uttam Kumaran: yeah, we can just have this
76 00:08:11.040 ⇒ 00:08:13.750 Uttam Kumaran: be accurate with what’s going on so far.
77 00:08:13.890 ⇒ 00:08:18.770 Uttam Kumaran: And then, yeah, I mean, you should link the tickets. There should be a relation from ticket to project. Basically.
78 00:08:19.300 ⇒ 00:08:20.640 Uttam Kumaran: Okay, you can do that. Yeah.
79 00:08:20.640 ⇒ 00:08:38.169 Robert Tseng: Yeah, that way, Nico, with the weekly updates as we’re taking that back up like, you don’t have to create a new template every week. You could just be like project task task task whatever like. And you can give them like a percentage bar like a sense of completion on these projects. And that’s that’s the weekly update we send them like it should.
80 00:08:39.000 ⇒ 00:08:44.990 Robert Tseng: If this is maintained well, like it’ll it’ll we could just use it for multi. We could multi purpose it.
81 00:08:45.290 ⇒ 00:08:49.660 Nicolas Sucari: I’ll create the the way of doing this. But yeah, I’ll I’ll do it. Don’t worry.
82 00:08:49.860 ⇒ 00:08:58.470 Robert Tseng: Okay, great. Let’s talk about planning kind of future planning. I mean, first, st I want to kind of source ideas from you guys. So maybe especially pious, like.
83 00:08:59.199 ⇒ 00:09:07.009 Robert Tseng: yeah, I honestly haven’t been looking at like super granular. How how things have been moving along here. So I want to know?
84 00:09:07.472 ⇒ 00:09:13.917 Robert Tseng: Like, yeah. Sounds like we still are kind of wrapping up the gross margin Etl stuff we’re still working on.
85 00:09:14.240 ⇒ 00:09:14.649 Payas Parab: Thank you.
86 00:09:14.650 ⇒ 00:09:23.019 Robert Tseng: We’ve gotten new metrics develop. And then we have no progress on the user acquisition. That’s on me to kind of build out that scope with them. So
87 00:09:23.451 ⇒ 00:09:35.990 Robert Tseng: is that right? Is there? Am I missing anything I know? We took a deep. We took a side quest to do the the Zip code matching, which is great. That’s a big win. I want to throw that on our account management deck. But yeah.
88 00:09:35.990 ⇒ 00:09:48.839 Payas Parab: Not to. Once I get that Google Collab, it’s running right now in Google Cloud, we will have the finalized results. And he asked me a question about it, so I think he got a chance to look at it. His question doesn’t make a ton of sense to me, so I probably gotta just fire back. I don’t know
89 00:09:49.000 ⇒ 00:09:58.759 Payas Parab: what to do there. But like that, that side quest, I think, is like, just in use cases. Actually, it seems like it’s like engineering side, too, which, like, maybe there’s a chance to penetrate there as well, because.
90 00:09:58.760 ⇒ 00:09:59.350 Robert Tseng: Yeah, exactly.
91 00:09:59.350 ⇒ 00:09:59.900 Payas Parab: Like some of these.
92 00:10:01.070 ⇒ 00:10:15.700 Payas Parab: They’re not like. It’s not like an engineer. Couldn’t have figured out what I figured out. It’s just like it’s just like tedious to do that right. It’s like, here’s all the edge cases we need to like. Convert all the Sts to street right? Like we need to just do like some sort of like data cleaning stuff. So there’s probably some sort of like
93 00:10:15.870 ⇒ 00:10:19.600 Payas Parab: engineering related tasks that maybe are also part of
94 00:10:19.700 ⇒ 00:10:39.323 Payas Parab: the future state as well, you know. So if they’re like, Hey, cool. This like really did solve a problem. We sent a cleaned up Csv cleaned up, excel to the the engineers on their side. Then they can do better matching and things like that better targeting. So maybe there is options on the engineering side that’s 1 like new thing that came out of the side quest. I think.
95 00:10:40.190 ⇒ 00:10:42.740 Payas Parab: I think, Justin, if we can get his
96 00:10:42.950 ⇒ 00:10:49.060 Payas Parab: be responsive and just like be working with him on these side quests. I think that those will just be in general more valuable than
97 00:10:49.450 ⇒ 00:11:08.210 Payas Parab: whatever like the other like. You know what I mean, like he, he’s just like he’s kind of the main guy like it’s it’s like becoming increasingly clear to me. Engineering is one area. I think now that the marketing I just saw I’m still catching up on all the messages, but it seems the marketing data is now being kicked off. Access has been given for North Beam, as well.
98 00:11:09.030 ⇒ 00:11:09.810 Robert Tseng: Oh, to us!
99 00:11:09.810 ⇒ 00:11:12.080 Nicolas Sucari: Yeah, yes.
100 00:11:12.080 ⇒ 00:11:22.640 Nicolas Sucari: yes. Utam already set that connection up through portable. I think we need to understand if the data is coming correctly with the endpoints needed, or we need to do something else there right.
101 00:11:23.070 ⇒ 00:11:32.369 Uttam Kumaran: Yeah, I’m gonna yeah. I’m gonna get a timeline from them soon, but should be done this week, probably for the portable data. But yeah, we’re gonna be bringing in north beam data.
102 00:11:33.880 ⇒ 00:11:45.580 Payas Parab: I think that’s that new and it seems like Aman is also like pushing new projects. So I think Amazon amplitude, recreation, right? Something like that. I I saw I I still have to review. Sorry. But Nikki.
103 00:11:45.580 ⇒ 00:11:49.650 Uttam Kumaran: Something like that. Yeah, he wanted like, he wanted some sort of Amazon based report.
104 00:11:50.910 ⇒ 00:11:58.159 Nicolas Sucari: He has an yeah, an Amazon based reporting apple 2 that he wants to move to metabase. So yeah, we need to check that one.
105 00:11:58.450 ⇒ 00:12:03.979 Robert Tseng: Yeah, he sent it to me before, but I didn’t really get much context with it. Okay, so
106 00:12:05.260 ⇒ 00:12:17.440 Robert Tseng: I’ll send these message. This message to him, don’t worry about whatever the ideas we’re throwing out here. Okay, great. So and then I think we were, was the guy named Mark, the Ops Guy, who, like takes forever to do stuff that we tell him to do on the.
107 00:12:17.840 ⇒ 00:12:19.530 Payas Parab: How is that, Jonathan.
108 00:12:19.996 ⇒ 00:12:20.930 Robert Tseng: Okay. Yeah.
109 00:12:20.930 ⇒ 00:12:27.619 Payas Parab: That’s Jonathan. We actually need to ask something of him, too. So I gotta send that message out as well. That Ryan flagged to me.
110 00:12:28.520 ⇒ 00:12:31.039 Nicolas Sucari: About Amazon. Right. Some Amazon orders.
111 00:12:31.040 ⇒ 00:12:32.280 Payas Parab: Yeah. Amazon.
112 00:12:32.280 ⇒ 00:12:32.660 Nicolas Sucari: Cheers.
113 00:12:32.810 ⇒ 00:12:34.336 Payas Parab: Thank you.
114 00:12:35.290 ⇒ 00:12:38.989 Robert Tseng: Yep by adding Amazon skews to the.
115 00:12:38.990 ⇒ 00:12:39.899 Payas Parab: The sheets. Yeah.
116 00:12:39.900 ⇒ 00:12:46.250 Robert Tseng: Master master product. Yeah. Sheet. Okay, cool. So while we’re at that, you know, we might as well ask
117 00:12:47.430 ⇒ 00:12:50.799 Robert Tseng: ask Jonathan like some what else he’s looking at, too, like.
118 00:12:51.620 ⇒ 00:12:54.619 Robert Tseng: okay, that’ll be. I’ll I’ll add him in the Channel.
119 00:12:55.950 ⇒ 00:12:57.460 Robert Tseng: It’s kind of alright.
120 00:12:57.700 ⇒ 00:13:03.839 Payas Parab: Yeah, it’s it’s Jonathan Martin. I don’t know if there’s another Jonathan I can’t remember. But Jonathan Martin is the Ops guy.
121 00:13:07.010 ⇒ 00:13:07.630 Robert Tseng: Yeah.
122 00:13:09.048 ⇒ 00:13:17.409 Robert Tseng: yeah. I even just like went into amplitude today. Or I did it right before this call. And I’m looking through like what their
123 00:13:17.830 ⇒ 00:13:26.080 Robert Tseng: what their most commonly used reports are. This is new stakeholder, Jacob Karen. This guy is their paid ads. Guy.
124 00:13:26.930 ⇒ 00:13:30.439 Robert Tseng: Seems like he’s pretty active in amplitude right now.
125 00:13:30.840 ⇒ 00:13:39.846 Robert Tseng: And yeah, something that Justin’s thinking a lot about is like Justin has like this.
126 00:13:41.140 ⇒ 00:13:44.110 Robert Tseng: yeah, he’s he’s he’s deep in the pack right now.
127 00:13:44.350 ⇒ 00:13:50.480 Robert Tseng: It’s like I see, like 4 or 5 reports that were last modified in the past day on like
128 00:13:51.910 ⇒ 00:13:58.130 Robert Tseng: new subscriber pack by product so
129 00:13:58.250 ⇒ 00:14:05.830 Robert Tseng: kind of a similar problem to what we’re seeing on Eden side. Looks like they also have been paying attention to
130 00:14:10.810 ⇒ 00:14:13.370 Robert Tseng: launched like Canada
131 00:14:16.700 ⇒ 00:14:20.410 Robert Tseng: recently, I’m assuming, because they have like all these.
132 00:14:21.640 ⇒ 00:14:26.179 Robert Tseng: they’ve all these like Aov, like kind of reports and stuff.
133 00:14:26.740 ⇒ 00:14:32.509 Robert Tseng: I guess, on that note for okay, gross margin that’s like the financial dashboard for for
134 00:14:33.190 ⇒ 00:14:36.335 Robert Tseng: I guess. For for Jared.
135 00:14:37.700 ⇒ 00:14:40.000 Robert Tseng: we did build this kind of like
136 00:14:40.130 ⇒ 00:14:47.230 Robert Tseng: profitability reporting thing for their us, products, right before
137 00:14:48.650 ⇒ 00:14:56.050 Payas Parab: Like a per product that was, it was based on the underlying incorrect data. But like it was, we did build like.
138 00:14:56.420 ⇒ 00:14:58.330 Payas Parab: yeah, it was like per product.
139 00:14:58.790 ⇒ 00:15:15.139 Payas Parab: profitability, like analysis and amplitude, I think. Well, it was like it was hard to get it in amplitude. Now it should look look nicer in metabase. So I think that actually could be like a high value, like thing that we can move to Meta Base faster rather than later, sooner rather than later.
140 00:15:15.450 ⇒ 00:15:16.120 Robert Tseng: Yeah.
141 00:15:16.120 ⇒ 00:15:36.059 Payas Parab: That was cause I was like it was like, it’s just like a nightmare to put that in amplitude in a really meaningful way. But Meta Base is like the right software for that, right? Like the bars that are like very clear and like broken up by product. And you can filter like if we can add that in there and get that to them sooner rather than later. I think that would be product, level profitability.
142 00:15:36.180 ⇒ 00:15:41.592 Payas Parab: We have all the key components now and then the
143 00:15:43.830 ⇒ 00:15:50.719 Payas Parab: the product level profitability we have. And then, yeah, like the Cac, I think, is also, if we get north beam data in there. That was another
144 00:15:51.230 ⇒ 00:16:00.350 Payas Parab: like per product, including the product cost plus the cac, getting the profitability. Still trying to like get that sorted out. I think.
145 00:16:02.730 ⇒ 00:16:04.280 Robert Tseng: Yeah, like, I said.
146 00:16:04.280 ⇒ 00:16:08.250 Payas Parab: Oh, full net margin view, not just gross margin, margin, view.
147 00:16:13.890 ⇒ 00:16:22.129 Robert Tseng: Do we think we’ll unlock that with the work that we’re doing with the gross margin dashboard? Can I go to Justin and be like great like. We did this. And hey, we can also move.
148 00:16:22.310 ⇒ 00:16:25.709 Robert Tseng: We can also give you like a deeper view of, like your
149 00:16:26.310 ⇒ 00:16:29.789 Robert Tseng: whatever product profitability reports that you have an amplitude.
150 00:16:31.930 ⇒ 00:16:35.465 Payas Parab: Like, I wanna see the north beam data before we say that.
151 00:16:35.760 ⇒ 00:16:36.430 Robert Tseng: Okay. Sure.
152 00:16:36.430 ⇒ 00:16:39.649 Payas Parab: I would want to see the North Beam data first.st So I think if there’s like
153 00:16:41.360 ⇒ 00:16:43.900 Payas Parab: I don’t know like where we’re at you said. Utam said something.
154 00:16:43.900 ⇒ 00:16:49.890 Uttam Kumaran: Well, can you? Can you? Can we? Can we take a just a second? Just look at the Northeam data together about like what I’m getting
155 00:16:50.000 ⇒ 00:16:57.770 Uttam Kumaran: well, actually, not about what I’m getting, but what we could get. Cause I, the portable guys, are great cause they just didn’t have the connector. And he’s like, Yeah, I’ll just whip it up for you.
156 00:16:57.930 ⇒ 00:17:01.070 Uttam Kumaran: just sick, because it’s like way more love than we got from a 5 tran.
157 00:17:01.250 ⇒ 00:17:04.469 Uttam Kumaran: although the product is a little bit jankier than Fivetran, but.
158 00:17:05.380 ⇒ 00:17:06.240 Payas Parab: Yeah, do you want to.
159 00:17:06.700 ⇒ 00:17:09.400 Payas Parab: Should I be looking in Snowflake for.
160 00:17:09.842 ⇒ 00:17:12.497 Uttam Kumaran: Wait one second. Let me just
161 00:17:16.050 ⇒ 00:17:16.720 Uttam Kumaran: me today.
162 00:17:16.720 ⇒ 00:17:21.329 Payas Parab: Yeah, I think, Robert, we we could say that if we just take a look at like what that North beam data is.
163 00:17:21.430 ⇒ 00:17:22.450 Payas Parab: And
164 00:17:22.640 ⇒ 00:17:28.149 Payas Parab: my main concern is like, does it tie to? Because I think we were looking at this before Robert with like
165 00:17:28.260 ⇒ 00:17:29.129 Payas Parab: one of the
166 00:17:29.610 ⇒ 00:17:40.740 Payas Parab: pro cost, like the Cac analysis Justin was doing is just taking the aggregated Facebook campaign data and dividing it sales right? And like, that’s like, there’s no way. That’s right. But I’m just like.
167 00:17:40.930 ⇒ 00:17:46.479 Payas Parab: I’m not sure if we’re going to get anything better from the way we’re get, we’re going to get the North Beam data. Does that make sense.
168 00:17:46.670 ⇒ 00:17:47.330 Robert Tseng: Yeah.
169 00:17:47.920 ⇒ 00:17:51.690 Payas Parab: And then it’ll sort of be like this. We don’t want to. Also like, I want to caution against
170 00:17:52.170 ⇒ 00:17:58.469 Payas Parab: doing a dance that like might yield them something. And then, ultimately, okay, it’s like harder in practice than in theory.
171 00:17:58.630 ⇒ 00:18:06.910 Robert Tseng: Yeah, let’s so let’s be clear that, like whatever new report we do, it’s gonna have a more accurate calculation or something something that’ll like.
172 00:18:06.910 ⇒ 00:18:07.580 Payas Parab: Yeah.
173 00:18:07.580 ⇒ 00:18:18.250 Robert Tseng: It’ll it’ll move the inertia, because, like, if it’s gonna be the same thing just in a different format, they’re probably less inclined to give us the that? Yeah.
174 00:18:19.360 ⇒ 00:18:22.110 Uttam Kumaran: I just sent the I sent the Api link in the Zoom chat.
175 00:18:23.580 ⇒ 00:18:25.569 Uttam Kumaran: Basically, we can get spend.
176 00:18:26.030 ⇒ 00:18:39.280 Uttam Kumaran: which is like spend by campaign ad ad set and then orders, which is I believe just
177 00:18:40.150 ⇒ 00:18:42.170 Uttam Kumaran: I mean, it doesn’t even have like.
178 00:18:43.440 ⇒ 00:18:44.929 Robert Tseng: Sorry I don’t. I don’t see it in the chat.
179 00:18:44.930 ⇒ 00:18:47.589 Payas Parab: Do you want to share your screen at your Tom? Just so. We’re looking at.
180 00:18:48.013 ⇒ 00:18:48.860 Uttam Kumaran: Yeah, yeah.
181 00:18:49.440 ⇒ 00:18:56.149 Payas Parab: It’s the ad ad campaign level data. So that’s spend it out.
182 00:18:56.670 ⇒ 00:19:02.290 Uttam Kumaran: Do this, guys? Yep. So we have these like spend records, which is like.
183 00:19:03.318 ⇒ 00:19:10.060 Uttam Kumaran: we could get a list of the date platform ad set spend impressions, clicks.
184 00:19:10.670 ⇒ 00:19:13.990 Uttam Kumaran: This is great on the order side.
185 00:19:14.180 ⇒ 00:19:20.790 Uttam Kumaran: We basically oh, this is for fetch a list of orders.
186 00:19:21.410 ⇒ 00:19:22.729 Uttam Kumaran: This doesn’t tell me.
187 00:19:22.730 ⇒ 00:19:24.170 Robert Tseng: We don’t. We don’t need this.
188 00:19:24.690 ⇒ 00:19:25.970 Uttam Kumaran: Oh, you don’t need. Okay.
189 00:19:26.340 ⇒ 00:19:38.760 Robert Tseng: I think the orders like, basically, that’s where they’re trying to do attribution. But we already do like attribution on the orders right? With every order that comes in. We have, like some utm that comes in and does that already. So we don’t need that.
190 00:19:39.310 ⇒ 00:19:42.669 Uttam Kumaran: And then on the the data export. This is something like
191 00:19:43.590 ⇒ 00:19:48.150 Uttam Kumaran: that’s a data export result. We would need an export Id, though
192 00:19:49.240 ⇒ 00:19:52.289 Uttam Kumaran: this is. Probably there’s probably like something in.
193 00:19:53.340 ⇒ 00:20:04.190 Uttam Kumaran: And then there’s also these like metrics, attribution models like, I think these are like sort of like in platform assets that you can create. And if we want to export that out, otherwise, I’m just gonna get spend.
194 00:20:08.240 ⇒ 00:20:12.889 Uttam Kumaran: I guess I don’t know. I’m not in Northfield. I don’t know what these are. I’m sure I think these are probably like
195 00:20:13.290 ⇒ 00:20:17.220 Uttam Kumaran: you can set up your own reporting in North Beam and get. This is what I’m guessing.
196 00:20:18.370 ⇒ 00:20:19.040 Robert Tseng: Yeah, yeah.
197 00:20:19.040 ⇒ 00:20:19.989 Payas Parab: Nice. Yeah.
198 00:20:20.210 ⇒ 00:20:26.320 Robert Tseng: So with the spend. I guess bias like it. It already goes deeper than what we saw. An amplitude right? Cause they you have
199 00:20:26.600 ⇒ 00:20:32.069 Robert Tseng: platform channel ad set, add, and like, if we can kind of do attribute.
200 00:20:32.070 ⇒ 00:20:32.720 Payas Parab: My only.
201 00:20:32.720 ⇒ 00:20:33.290 Robert Tseng: To, the.
202 00:20:33.290 ⇒ 00:20:50.269 Payas Parab: I I agree we get more at the ad, like definitely at the ad level, like the ad campaign level. And like that, what Ad said. At like we can do a whole bunch. My only concern there is that like that, the target we’re going for is this like, spend number like, and I don’t know if they like. Don’t have the right attribution like
203 00:20:51.460 ⇒ 00:20:57.539 Payas Parab: like, if that works correctly, does that make sense like like it’s like, Are we gonna rely on North Beam to have.
204 00:20:57.540 ⇒ 00:20:58.020 Uttam Kumaran: Yes.
205 00:20:58.020 ⇒ 00:21:15.109 Payas Parab: Spend metric, because then it relies on their attribution to the shopify order in an ideal world I would love is like an order. Id. That was. You know what I mean. Like an order. Id is generated from the campaign, or something like that, some sort of like direct attribution. I know that’s.
206 00:21:15.110 ⇒ 00:21:16.910 Robert Tseng: That’s what the orders is for. Yeah.
207 00:21:16.910 ⇒ 00:21:17.500 Payas Parab: That that’ll.
208 00:21:17.500 ⇒ 00:21:18.440 Uttam Kumaran: We already do that.
209 00:21:18.710 ⇒ 00:21:20.329 Payas Parab: They they already do. That is, that.
210 00:21:20.330 ⇒ 00:21:23.729 Uttam Kumaran: Not this, not through here. We, the orders we get.
211 00:21:23.920 ⇒ 00:21:27.149 Robert Tseng: From them. I believe we get. We have the attribution there.
212 00:21:28.480 ⇒ 00:21:34.319 Robert Tseng: don’t we have like some utm that’s like last. I mean, it’s probably at least it’s probably last click. But like.
213 00:21:35.560 ⇒ 00:21:37.739 Robert Tseng: yeah, we we must have.
214 00:21:37.740 ⇒ 00:21:46.240 Payas Parab: That last click, and that last click has like my. My question is like, How would you bind that order to what we’re seeing here like, that’s the part I’m I’m just wanna make sure.
215 00:21:47.970 ⇒ 00:21:52.779 Payas Parab: Also spend is spend miles. My bad spend is like spending on the ad itself. Right? So you get your.
216 00:21:52.780 ⇒ 00:21:53.320 Uttam Kumaran: Correct.
217 00:21:53.853 ⇒ 00:21:58.270 Payas Parab: But like the if we get the clicks and the impressions right
218 00:21:58.660 ⇒ 00:22:03.559 Payas Parab: then like, how did that convert to sales like like that aspect.
219 00:22:04.650 ⇒ 00:22:06.680 Payas Parab: I’m not sure how we would join that.
220 00:22:08.880 ⇒ 00:22:12.680 Uttam Kumaran: I’m just trying to look through the model right now to see. So we have
221 00:22:13.640 ⇒ 00:22:17.860 Uttam Kumaran: the offer. Blah blah! Blah!
222 00:22:21.680 ⇒ 00:22:27.320 Uttam Kumaran: I don’t think we have it in here. We just basically know whether it’s from Tiktok or not. And we have.
223 00:22:27.659 ⇒ 00:22:31.730 Robert Tseng: We have offer name coming through. I mean they have it. Offer.
224 00:22:32.630 ⇒ 00:22:38.260 Uttam Kumaran: Off dot offer, which is from the offer.
225 00:22:38.640 ⇒ 00:22:39.879 Payas Parab: Yeah, I recall we we did. We.
226 00:22:39.880 ⇒ 00:22:41.729 Uttam Kumaran: Order, note, attribute.
227 00:22:41.730 ⇒ 00:22:51.200 Payas Parab: We have a offer name, but, like what I mean is like that offer. Name may not tie to campaign id campaign, name, or like ad name, or any you know what I’m saying.
228 00:22:51.350 ⇒ 00:22:58.499 Robert Tseng: No, I mean every every campaign should be should be tied to an off, and we can validate this Amon, but, like I don’t, I feel like the
229 00:22:58.650 ⇒ 00:23:01.819 Robert Tseng: it’s probably more straightforward than what you realize. It’s it’s just like.
230 00:23:01.820 ⇒ 00:23:03.350 Payas Parab: That’s fair. That’s fair. Yeah.
231 00:23:03.690 ⇒ 00:23:11.030 Payas Parab: do we? Do? We maybe want to just like fire, fire out a message, someone, and be like, How do you guys currently look at like we’re seeing we’re able.
232 00:23:11.030 ⇒ 00:23:13.830 Uttam Kumaran: I’m fairly certain they probably just rely on the North beam data.
233 00:23:14.470 ⇒ 00:23:16.800 Uttam Kumaran: But to guess for attribution.
234 00:23:16.800 ⇒ 00:23:19.040 Payas Parab: Our team is reporting.
235 00:23:19.040 ⇒ 00:23:24.929 Uttam Kumaran: North beam, triple whale. These are just pixel companies. So you just they just put a pixel on your site. And then they basically start.
236 00:23:24.930 ⇒ 00:23:25.500 Payas Parab: Sure, sure.
237 00:23:25.500 ⇒ 00:23:31.689 Uttam Kumaran: The answer right like, and they’re probably using it just to look at. We spent this much, and it drove this much in row app.
238 00:23:31.690 ⇒ 00:23:35.239 Payas Parab: In the in the Api thing right right here in like the response. I don’t see.
239 00:23:35.240 ⇒ 00:23:35.580 Uttam Kumaran: Okay.
240 00:23:35.580 ⇒ 00:23:38.000 Payas Parab: Where, like row as I don’t see.
241 00:23:38.200 ⇒ 00:23:39.930 Uttam Kumaran: No, we have to calculate that.
242 00:23:40.660 ⇒ 00:23:44.700 Payas Parab: But from what like, from like that campaign, we know what sales came from that campaign.
243 00:23:44.700 ⇒ 00:23:49.440 Uttam Kumaran: So if we get the orders right, the orders will have basically like a list of
244 00:23:49.920 ⇒ 00:23:53.580 Uttam Kumaran: it’ll basically have the list of the order. And then
245 00:23:55.340 ⇒ 00:24:07.489 Uttam Kumaran: you basically look at how much you spent on the platform on that campaign versus the yeah, I assume there’ll be a campaign Id that basically is in this order data. Some reason there’s nothing like I don’t. I don’t know what this looks like right now.
246 00:24:07.960 ⇒ 00:24:09.580 Uttam Kumaran: but I can.
247 00:24:10.260 ⇒ 00:24:13.609 Uttam Kumaran: I can log in and just check what we’re getting while we’re talking.
248 00:24:14.460 ⇒ 00:24:15.540 Robert Tseng: Trying to log in.
249 00:24:17.620 ⇒ 00:24:19.649 Payas Parab: You log into north theme, or are you logging into.
250 00:24:19.650 ⇒ 00:24:23.189 Uttam Kumaran: Yeah, Antonio, I’m gonna I’m gonna see whether I could just like
251 00:24:23.330 ⇒ 00:24:26.399 Uttam Kumaran: fire these fire. One of these requests off.
252 00:24:41.670 ⇒ 00:24:42.790 Robert Tseng: Oh.
253 00:25:15.230 ⇒ 00:25:16.139 Robert Tseng: the heck!
254 00:25:21.940 ⇒ 00:25:24.927 Robert Tseng: Yeah, I already think I have North main access.
255 00:25:27.500 ⇒ 00:25:34.359 Robert Tseng: and not ever along in the north. Being for Joby, I found it hard to. Yeah. I feel like they always like didn’t let me go into North Main.
256 00:25:35.360 ⇒ 00:25:38.120 Robert Tseng: so maybe we can is the only one that has the North.
257 00:25:38.120 ⇒ 00:25:40.939 Uttam Kumaran: I don’t have it. I just I just got the codes.
258 00:25:41.350 ⇒ 00:25:45.620 Robert Tseng: Oh, I see. Yeah, okay. So none of us have access to their actual.
259 00:25:45.875 ⇒ 00:25:49.710 Uttam Kumaran: Yeah, let let’s just let maybe let’s just let the data come in. And then
260 00:25:49.900 ⇒ 00:25:54.859 Uttam Kumaran: can you? We just ask them bias like, what are how they? How do they doing attribution today?
261 00:25:56.770 ⇒ 00:25:57.890 Uttam Kumaran: No, I’m just
262 00:25:58.010 ⇒ 00:26:03.770 Uttam Kumaran: I got a subset of the data. I’m just gonna try to see like, what did I even get today?
263 00:26:09.520 ⇒ 00:26:18.669 Uttam Kumaran: yeah, I have to wait if they’re working on it. But I’m just gonna tell them to give us. I told him to give us orders and spend. That’s really all there is. Anyways, my assumption is we’ll get.
264 00:26:20.669 ⇒ 00:26:25.279 Nicolas Sucari: I think I have access to North name. Do you want me to share my screen? I think I mean.
265 00:26:25.280 ⇒ 00:26:25.990 Payas Parab: That would be great.
266 00:26:25.990 ⇒ 00:26:26.660 Nicolas Sucari: Yes.
267 00:26:32.050 ⇒ 00:26:40.800 Nicolas Sucari: so this should be it right like this is Jabby.
268 00:26:41.680 ⇒ 00:26:45.559 Robert Tseng: How does Nico have it? None of us have it.
269 00:26:47.240 ⇒ 00:26:49.500 Nicolas Sucari: Do you know what you need to check?
270 00:26:49.620 ⇒ 00:26:50.609 Nicolas Sucari: But yeah.
271 00:26:51.010 ⇒ 00:26:51.370 Uttam Kumaran: This is.
272 00:26:51.370 ⇒ 00:26:51.760 Robert Tseng: Yeah, I mean.
273 00:26:51.760 ⇒ 00:26:54.719 Uttam Kumaran: Oh, roulette dude! You should look at my gmail like so.
274 00:26:54.720 ⇒ 00:26:56.960 Robert Tseng: Yeah. If you go to orders, go to orders on the left.
275 00:26:56.960 ⇒ 00:26:57.420 Payas Parab: Okay.
276 00:26:57.876 ⇒ 00:26:58.790 Robert Tseng: Tab. Yeah.
277 00:26:59.580 ⇒ 00:27:00.390 Nicolas Sucari: I’m here.
278 00:27:01.860 ⇒ 00:27:08.029 Robert Tseng: Yeah, just let’s just look at an order and see what it’s like. I’m sure, like the attribution is. Probably it’s probably probably
279 00:27:08.890 ⇒ 00:27:13.170 Robert Tseng: let’s just scroll down a bit. Just click on one of these one of these order Ids.
280 00:27:13.390 ⇒ 00:27:20.709 Payas Parab: Yeah, maybe I made this a bigger thing than it, like I’m sure it’s there. But I just wanted to make sure before we like are like, let’s go cut this data.
281 00:27:22.040 ⇒ 00:27:22.960 Payas Parab: Oh.
282 00:27:24.280 ⇒ 00:27:27.599 Robert Tseng: Okay, yeah, let’s also get this into the one pass so that we can all go in here.
283 00:27:28.561 ⇒ 00:27:36.749 Robert Tseng: Discount. Okay, yeah. So they have their discount code. Here is there Amazon scroll down.
284 00:27:38.300 ⇒ 00:27:40.910 Payas Parab: And there was an ad id there. If I recall if I just saw.
285 00:27:40.910 ⇒ 00:27:41.270 Nicolas Sucari: No.
286 00:27:42.260 ⇒ 00:27:43.360 Robert Tseng: There wasn’t.
287 00:27:44.620 ⇒ 00:27:47.030 Nicolas Sucari: Don’t. I haven’t seen it. But let me check.
288 00:27:47.030 ⇒ 00:27:53.200 Robert Tseng: Well, they they have to that. They’re they’re bringing orders in here. So these orders are all linked to some. Some like.
289 00:27:53.730 ⇒ 00:27:59.850 Robert Tseng: if if yeah, if they’re running their campaigns through north beam, like North Beam, has to be matching to orders in order to pick.
290 00:27:59.850 ⇒ 00:28:00.969 Payas Parab: To, yeah.
291 00:28:01.330 ⇒ 00:28:01.760 Robert Tseng: They’re not like.
292 00:28:01.760 ⇒ 00:28:03.619 Uttam Kumaran: Click on one of these orders again.
293 00:28:04.250 ⇒ 00:28:06.289 Robert Tseng: Yeah. So one that’s 1 that’s not like 0.
294 00:28:06.560 ⇒ 00:28:07.140 Nicolas Sucari: Yep.
295 00:28:10.720 ⇒ 00:28:17.129 Robert Tseng: Yeah, I’m seeing customer. Id. We should like match one of those customer ids what we have in the in the orders, and see if it’s the same thing.
296 00:28:24.390 ⇒ 00:28:27.030 Payas Parab: Okay, so then, okay, add click, there.
297 00:28:27.030 ⇒ 00:28:28.180 Uttam Kumaran: Yeah. Good.
298 00:28:28.180 ⇒ 00:28:28.690 Robert Tseng: Champion.
299 00:28:29.930 ⇒ 00:28:31.860 Payas Parab: We have email attribution to here.
300 00:28:32.640 ⇒ 00:28:34.619 Robert Tseng: Yeah, well, I mean, yeah, so.
301 00:28:35.200 ⇒ 00:28:37.610 Uttam Kumaran: This is great. Yeah, that’s all. That’s all solid.
302 00:28:38.260 ⇒ 00:28:49.809 Payas Parab: As long as this all comes through via Api. Then then we should be good. I just I I just like remember at Tiktok we ran into this issue, where, like like companies like North Beam wouldn’t share some of this like customer attribution data or.
303 00:28:49.980 ⇒ 00:28:50.340 Uttam Kumaran: Yeah.
304 00:28:50.340 ⇒ 00:28:56.130 Payas Parab: Id via Api, because then you have the person’s activity tied to
305 00:28:56.450 ⇒ 00:28:59.420 Payas Parab: their address right like that whole thing.
306 00:28:59.980 ⇒ 00:29:00.330 Uttam Kumaran: Yeah, yeah.
307 00:29:00.330 ⇒ 00:29:00.680 Robert Tseng: Yeah.
308 00:29:00.680 ⇒ 00:29:01.270 Uttam Kumaran: Sense.
309 00:29:01.270 ⇒ 00:29:02.210 Payas Parab: But that’s that’s right.
310 00:29:02.210 ⇒ 00:29:03.910 Robert Tseng: Through a lawsuit on this right. Now.
311 00:29:04.780 ⇒ 00:29:05.330 Payas Parab: What’s up?
312 00:29:05.330 ⇒ 00:29:06.350 Uttam Kumaran: Oh, yeah.
313 00:29:06.350 ⇒ 00:29:07.080 Robert Tseng: Yeah.
314 00:29:07.950 ⇒ 00:29:12.741 Payas Parab: Dude. I can’t get any more, boys. I’m I’m I’m cooked already, fucking.
315 00:29:13.720 ⇒ 00:29:16.370 Uttam Kumaran: No dude. Yeah, please don’t get sued for anything.
316 00:29:16.820 ⇒ 00:29:22.627 Uttam Kumaran: But tell me, if you’re thinking about that, there’s opportunity for you to get sued on something.
317 00:29:22.950 ⇒ 00:29:26.549 Payas Parab: Not not related to here. It’s actually it. Well, it could be soon, because we’re gonna.
318 00:29:26.550 ⇒ 00:29:29.140 Uttam Kumaran: No dude, it can be soon. It won’t be soon.
319 00:29:29.140 ⇒ 00:29:34.899 Robert Tseng: Please do not give Lee’s this person. Lee’s not like info to anybody. That would be.
320 00:29:35.010 ⇒ 00:29:38.019 Robert Tseng: That’d be case for us, being out of business soon.
321 00:29:38.320 ⇒ 00:29:45.580 Payas Parab: Alright. Well, okay. So I. So I think as long as we can confirm this comes through Api. Then we have the order. Id. It looks like they even have like
322 00:29:45.680 ⇒ 00:30:03.450 Payas Parab: some of the items it’s just like in my in my world, like in an ideal world, right like in this journey. You see that purchase like it would be really nice to just tie that directly to something in order. Line right? You tie that into order line. Now we have, like the total Cac, the total product cost for that order and the revenue.
323 00:30:04.890 ⇒ 00:30:09.600 Payas Parab: So I just wanna make sure that that like we can stitch all that together. It seems like we can here.
324 00:30:09.840 ⇒ 00:30:19.189 Robert Tseng: Well, look this this one campaign. Bpa concentrate. I don’t know the naming set, but the ad set. Bpa concentrate. There’s 4 line items here.
325 00:30:19.741 ⇒ 00:30:27.900 Robert Tseng: Yeah, like, we’re not gonna be able to do get a clean attribution down to the line item, level. The same thing that we run into it. Even.
326 00:30:28.440 ⇒ 00:30:36.660 Payas Parab: I think that’s okay. This is this is at least like you, said Robert. It’s more granular than what they have right, which is like total sales of campaign, divided by whatever
327 00:30:36.660 ⇒ 00:30:37.889 Payas Parab: yeah, like. At least
328 00:30:37.890 ⇒ 00:30:42.700 Payas Parab: here we could break out like ad set used and like, whether there was an increased
329 00:30:43.060 ⇒ 00:30:46.100 Payas Parab: like cart value, right or increased.
330 00:30:46.550 ⇒ 00:30:48.099 Payas Parab: What do you call it?
331 00:30:48.520 ⇒ 00:30:55.680 Payas Parab: You know what I mean like increase for a certain ad set, or a certain whatever it’s like some sort of additional granular data.
332 00:30:56.170 ⇒ 00:30:56.790 Robert Tseng: Yeah.
333 00:30:57.680 ⇒ 00:30:59.280 Robert Tseng: Okay, cool.
334 00:31:01.060 ⇒ 00:31:03.480 Nicolas Sucari: I’m gonna share these with you guys.
335 00:31:04.740 ⇒ 00:31:05.560 Robert Tseng: Yeah.
336 00:31:05.560 ⇒ 00:31:07.020 Nicolas Sucari: The access. Sorry.
337 00:31:08.620 ⇒ 00:31:14.019 Robert Tseng: Yeah, let’s just drop it in the the the shared one pass, and we can all use it.
338 00:31:14.020 ⇒ 00:31:14.410 Nicolas Sucari: Yeah.
339 00:31:14.681 ⇒ 00:31:21.470 Robert Tseng: Okay, cool. I mean, I think I feel like I got enough to kind of cobble together some some next steps on how I’m gonna
340 00:31:22.030 ⇒ 00:31:25.990 Robert Tseng: I’m gonna just like, add a bunch of those people and try to chase some of these leads.
341 00:31:26.483 ⇒ 00:31:30.429 Robert Tseng: But yeah, I mean for you, for you guys just kinda keep focusing on getting
342 00:31:30.590 ⇒ 00:31:36.480 Robert Tseng: the outstanding things done. And then hopefully, like, this is good context for me to try to queue up some more stuff.
343 00:31:37.910 ⇒ 00:31:39.780 Payas Parab: Awesome. Alright guys, cool.
344 00:31:39.780 ⇒ 00:31:40.110 Robert Tseng: Alright!
345 00:31:40.740 ⇒ 00:31:44.119 Uttam Kumaran: Yeah, I’ll follow up with Tom on the stuff we discussed on pool parts, too.
346 00:31:44.120 ⇒ 00:31:45.049 Uttam Kumaran: Yes, please. Okay.
347 00:31:45.050 ⇒ 00:31:46.870 Robert Tseng: Alright sounds great thanks, chance!
348 00:31:47.010 ⇒ 00:31:47.560 Robert Tseng: See ya.
349 00:31:47.560 ⇒ 00:31:48.290 Uttam Kumaran: Thanks guys.
350 00:31:48.680 ⇒ 00:31:49.400 Nicolas Sucari: Thanks.