Meeting Title: Javy-Data-Engineering-Weekly Date: 2024-10-22 Meeting participants: Nicolas Sucari, Aman Nagpal, Brian Pei, Payas Parab, Robert Tseng
WEBVTT
1 00:03:20.490 ⇒ 00:03:21.580 Payas Parab: Everyone. How are you?
2 00:03:22.010 ⇒ 00:03:23.670 Aman Nagpal: Good. Good. How about how about you?
3 00:03:23.670 ⇒ 00:03:25.059 Payas Parab: I’m doing all right.
4 00:03:25.870 ⇒ 00:03:27.070 Aman Nagpal: Good to hear.
5 00:03:29.340 ⇒ 00:03:32.290 Aman Nagpal: Okay, just give everyone a few minutes.
6 00:03:32.290 ⇒ 00:03:32.989 Payas Parab: You sure.
7 00:04:04.310 ⇒ 00:04:05.200 Nicolas Sucari: Hi guys.
8 00:04:06.150 ⇒ 00:04:07.100 Aman Nagpal: Hey! How are you?
9 00:04:08.330 ⇒ 00:04:09.620 Nicolas Sucari: I’m doing fine.
10 00:04:10.320 ⇒ 00:04:11.300 Nicolas Sucari: How are you?
11 00:04:12.550 ⇒ 00:04:13.619 Aman Nagpal: Doing. Well, thanks.
12 00:04:22.190 ⇒ 00:04:24.410 Nicolas Sucari: If I do, we wait for Robert.
13 00:04:25.550 ⇒ 00:04:30.820 Payas Parab: Yeah, I think Robert said he would be joining but I’m not sure exactly. Yeah.
14 00:04:33.680 ⇒ 00:04:34.969 Payas Parab: yep, there he is.
15 00:04:52.350 ⇒ 00:04:53.220 Nicolas Sucari: Hey, Robert.
16 00:04:54.110 ⇒ 00:04:54.959 Robert Tseng: Hey, guys.
17 00:04:55.710 ⇒ 00:04:56.680 Aman Nagpal: Hey? How’s it going.
18 00:04:58.120 ⇒ 00:04:59.829 Robert Tseng: Good long time to see.
19 00:05:00.490 ⇒ 00:05:02.100 Aman Nagpal: Yeah, how was your trip?
20 00:05:02.800 ⇒ 00:05:07.062 Robert Tseng: Trip was great, but good to be back and settled, so.
21 00:05:15.340 ⇒ 00:05:17.600 Nicolas Sucari: Cool. Do you wanna start by us.
22 00:05:18.020 ⇒ 00:05:19.880 Nicolas Sucari: Ryan? Are you around? Yes.
23 00:05:25.240 ⇒ 00:05:27.100 Nicolas Sucari: you’re on mute. If you’re talking.
24 00:05:30.250 ⇒ 00:05:33.139 Brian Pei: Yeah, I’m here. Sorry. Did you say piastigo or me?
25 00:05:33.830 ⇒ 00:05:37.470 Nicolas Sucari: Oh, yeah, yeah, I asked. I asked to start, but I wanted to check if you were here.
26 00:05:37.470 ⇒ 00:05:38.569 Brian Pei: Oh, yeah, I’m here.
27 00:05:39.070 ⇒ 00:05:39.645 Payas Parab: Great
28 00:05:40.910 ⇒ 00:05:57.779 Payas Parab: So, mon, the 1 1 big thing that we like chatted about last week was like the different tools that you want to use. We decided to kind of just like move forward with Meta Base. We spoke with Robert, and we’re just like, let’s just choose a tool. Make it simple for you guys. And we’re setting up Meta base now so that you can
29 00:05:57.780 ⇒ 00:06:14.820 Payas Parab: you, and like your future sequel analysts can kind of run queries. So we’re in the process of getting that set up. That’s where we’re going to start to display a lot of this like data that’s coming out. Nico is also set up real, which will be a self serve tool. So we’re putting together a document which we’ll share with you shortly, which is just like
30 00:06:14.820 ⇒ 00:06:32.020 Payas Parab: all of the tools, you know. I spoke with Brian and Nico. We just want to make sure another deliverable. Here is just going to be all of the tools that we’re using and like, what do you use for what? So progress updates on my end is just like that’s the main thing that we’re working on now is like migrating the analyses from like the sequel based analyses
31 00:06:32.020 ⇒ 00:06:46.770 Payas Parab: into Meta base. We’re just gonna roll forward with that for you guys. If that’s okay. I laid out the options in the message. I can bump it again from last week. But we figured it would just be good to just get started. Get the thing connected and just get rolling with like the outputs.
32 00:06:47.015 ⇒ 00:07:03.430 Payas Parab: So we’re in the next day or 2. You’re gonna see, like an output from metabase that you can like. See what types of dashboarding and stuff is available. And then the real self serve tool, which we also believe you guys should implement again whether you guys keep it or not. It’s up to you. But we’re gonna implement it. Nico and I discussed
33 00:07:03.676 ⇒ 00:07:26.869 Payas Parab: so that you guys can play around with it. I’ve already shared that with Jared. I haven’t gotten any feedback from him on that. But the self serve tool. I wanted to get it in his hands as well. So those are the main updates from our end. We’re still doing some data validation. Other things. We’re also flagging for Nico. And Brian is like data sets that we’re gonna want in the data warehouse. It’s best, you know as much as possible while we have the brain forge guys to
34 00:07:26.870 ⇒ 00:07:53.360 Payas Parab: be proactive about all the data we’re gonna want pipelined in. So Brian’s working on a few of his work streams. So you know, we don’t want to jam him up, but we want to make sure all the data you might want is in that warehouse to make the future easier for you. It’s sinking. It’s in there. We wanna make sure that’s in there as well, so I think that’s why Nico flagged the north beam thing. And then I want to just flag to you that Meta base. We’re just gonna roll forward. It’s the most cost effective, we think, and it’s the simplest
35 00:07:53.639 ⇒ 00:08:19.269 Payas Parab: and so you’ll start to see. We’ll start making some visualizations in there for you, and then rill as well. Nico is like kind of the expert Nico and Brian there. But like, if you have any questions around that, we want to just get these data visualization tools in your hand. And then we’re gonna keep moving forward on the warehousing stuff. I flagged the marketing data, which is why Nico sent the message about north Beam so wanted to check on that as well. But that’s everything on my end.
36 00:08:19.503 ⇒ 00:08:41.419 Payas Parab: Yeah. And then that document we’re working on. I’m having Brian update any tools he’s using. We have like this like Google, Doc, where we’re just adding, like, what is the tool. How much does it cost? How much might it cost you in the future? So that you’ll also have that right of like, what the hell is this like 5 tran? Dbt, what do they do? What do they cost? We want to make sure you’re ready to answer questions around that. So that. That’s all the updates on my end.
37 00:08:41.663 ⇒ 00:08:55.560 Payas Parab: We’ll pause with any questions concerns. Yeah. And then, you know, once Meta base, I get some of these visuals up in there, and I have Robert just double check them and make sure things are looking right. You’ll you’ll start to have some of those like custom queries as well that you can see.
38 00:08:56.350 ⇒ 00:09:16.099 Aman Nagpal: Yeah, I think that sounds good. That Doc will be super helpful. So thank you. I’m good to, you know, if you guys recommend real and metabase, for now then, we can always change it later. So let’s go ahead with that, you know. If you guys think that’s best. I hadn’t sent it over to Jared and Justin just yet, just because last time we spoke I think we had to publish
39 00:09:16.150 ⇒ 00:09:20.470 Aman Nagpal: the final version live. So I was waiting for that is that completed.
40 00:09:20.470 ⇒ 00:09:24.010 Payas Parab: The final version of the which one, the real right.
41 00:09:24.010 ⇒ 00:09:50.079 Nicolas Sucari: The tables. Yeah, yeah, I think I need to change the tables. Yeah. But the call, the the data is not gonna change. I mean everything is the same. We are only gonna change the name of the tables where we are tracking. But yeah, I can do right in after this meeting. I thought, we wanna check the dev tables before doing that. But I think that’s fine. Okay, we can do it is the same information. Columns are not gonna change. So yeah, we’re gonna keep the same, just changing the name of the tables.
42 00:09:50.410 ⇒ 00:10:01.019 Aman Nagpal: That’s perfect, so I’ll send that over to. I know you already sent Jerry, but I’ll send it to them again. Him and Justin, access to Real, which I already have Meta base. I guess you’ll get set up. So whenever that’s done.
43 00:10:01.020 ⇒ 00:10:01.380 Payas Parab: Yup!
44 00:10:01.380 ⇒ 00:10:02.500 Aman Nagpal: Said that as well, and then.
45 00:10:02.500 ⇒ 00:10:05.709 Payas Parab: Get you something by the end of the week. So you have something as as well there. Yeah.
46 00:10:05.710 ⇒ 00:10:11.540 Aman Nagpal: That’s perfect. Yeah, Justin’s traveling so he’ll be back by then, anyway. So that lines up
47 00:10:11.855 ⇒ 00:10:20.949 Aman Nagpal: and then real. I know we went over already. So that makes sense for Meta Base. You showed me a screenshot last time, but that would be used more for what purposes? Again.
48 00:10:21.970 ⇒ 00:10:45.160 Payas Parab: So yeah, so like, it’s basically like, Hey, I have a sequel question. It’s like a SQL based question, I need to like, you know, like, create like a custom, quick dashboard. Real real is like meant to be a self. Serve tool right? So we don’t want to manipulate that you won’t need a SQL analyst, we wanna make sure that’s in your hands. But then, when you want something, custom right where it’s like whether it’s your data analyst, whether it’s you guys or any of your engineering team.
49 00:10:45.160 ⇒ 00:11:00.329 Payas Parab: They want to put together a sequel query, and they want to visualize that data somewhere and make a dashboard that’s like really easily shareable. I’ve been sharing with Jared so far for his questions like interim updates and snowflake. But those aren’t like very like aesthetically pleasing. They’re not like really dashboard like.
50 00:11:00.330 ⇒ 00:11:27.869 Payas Parab: and you kind of have to like open the query and then hit run, which he even flagged as like kind of an issue which makes sense. He just wants to like log in, get a link. So yeah, if you have your SQL. Analyst. And or you’re having us put together like we’re doing some of the the revenue metrics and things like that. The gross margin metrics like you need somewhere to put it and something somewhere that’s more aesthetically pleasing than Snowflake. And then they have like easy sharing capabilities and auto refresh capabilities. Yeah.
51 00:11:28.200 ⇒ 00:11:34.619 Aman Nagpal: Got it. So is this mostly financial data that would not make sense to have an amplitude. Is that what we’re putting into.
52 00:11:34.620 ⇒ 00:11:59.427 Payas Parab: That’s that’s exactly it. It’s like, it’s financial data as well as like like, complex joins between data. If that makes sense like it’s like, Hey, we have some data sitting in one area. And then, like, we want to like, manipulate it and like, cut it a bunch of different ways like to combine all of that. It’s best done using snowflake tables and then displayed in Meta base. Yeah. So some of those like complicated queries. Right? So,
53 00:11:59.780 ⇒ 00:12:08.129 Payas Parab: yeah, if you have, like, 2 data sources of something, and you want to like, kind of combine them. This this is much easier than amplitude, because amplitude is a little bit more
54 00:12:08.200 ⇒ 00:12:16.799 Payas Parab: drag and drop, and you have to know the tricks to get exactly what you want versus like. Feel like, hey? I want this like you can get that quickly in sequel.
55 00:12:17.370 ⇒ 00:12:41.909 Aman Nagpal: Yeah, I think with amplitude. Like, we said, you know, like you just said, complexity isn’t there? But also it’s just not made for financial data which we’ve discussed in the past. So I think again, if most stuff lives in amplitude. But the financial stuff isn’t something else like, you know, metabase, whatever it is. That’s fine. I know last time I brought up that we’ve been working with Iris AI. I don’t know if you had a chance to look at them. But what would Meta base
56 00:12:42.310 ⇒ 00:12:43.960 Aman Nagpal: serve as
57 00:12:44.100 ⇒ 00:12:51.809 Aman Nagpal: kind of like a visualization tool like that? Or would we get something else on top of metabase or in, you know, instead of metabase, how would that work.
58 00:12:53.220 ⇒ 00:12:54.293 Payas Parab: Yeah, so
59 00:12:55.250 ⇒ 00:13:09.820 Payas Parab: so that one. So I looked into like what that tool does right? I think ultimately, we’d need to like. See what it do you know where that’s pulling from? Is there like? Is it like quickbooks, data? Or is it like pulling from a bunch of different sources like.
60 00:13:10.440 ⇒ 00:13:13.669 Aman Nagpal: I would think a bunch of sources. Jared kind of
61 00:13:13.700 ⇒ 00:13:18.099 Aman Nagpal: Jared would know the answer to that, but I think from shopify Amazon directly.
62 00:13:18.921 ⇒ 00:13:22.570 Aman Nagpal: And then just decide, you know, taking the data from there.
63 00:13:23.125 ⇒ 00:13:24.499 Aman Nagpal: But he would know better.
64 00:13:24.970 ⇒ 00:13:36.870 Payas Parab: Okay. I think that’s something we’ll we’ll want to like, keep keep a lookout for just to see if, like, how that data like whether it’s something we pipeline and I find it unlikely. It’s kind of a newer tool. From what I can tell.
65 00:13:36.870 ⇒ 00:13:37.210 Aman Nagpal: So.
66 00:13:37.210 ⇒ 00:13:42.930 Payas Parab: It’s very unlikely that they have the data pipelines, Nico and Brian, can. We can check afterward and
67 00:13:43.010 ⇒ 00:13:51.180 Payas Parab: correct me on that. But I I doubt there’d be like some data pipelines. It’s likely that whatever data it’s pulling in, we have those sources in our
68 00:13:51.200 ⇒ 00:13:52.280 Payas Parab: warehouse.
69 00:13:52.420 ⇒ 00:13:52.920 Payas Parab: So.
70 00:13:52.920 ⇒ 00:13:56.220 Aman Nagpal: Yeah, yeah, I guess I mean more from the visualization aspect of it.
71 00:13:56.730 ⇒ 00:13:58.220 Payas Parab: Oh, I see, okay, yeah.
72 00:13:58.900 ⇒ 00:13:59.930 Payas Parab: yeah, we can.
73 00:13:59.930 ⇒ 00:14:00.730 Aman Nagpal: Similar.
74 00:14:01.110 ⇒ 00:14:16.450 Payas Parab: It, it should be similar. Yeah, it’s just that the Meta base would be more custom, I think, like Iris is, it’s similar to real where it’s an out of the box like like. From what I can tell, it’s kind of like a out of the box like Fp. And a tool for an e-commerce company, or like some type of compass company.
75 00:14:16.970 ⇒ 00:14:18.480 Payas Parab: like this is like.
76 00:14:18.740 ⇒ 00:14:22.406 Payas Parab: it’s more generalized so it can be more custom long run.
77 00:14:22.760 ⇒ 00:14:28.629 Payas Parab: But yeah, I I think it’s it’s it’s think of it, very similar to like a finance version of real
78 00:14:28.760 ⇒ 00:14:51.480 Payas Parab: and rail is made more for like Ecom operations and things like that. And you know, this is more the Fp and a use case. But yeah, you can add any tool on top. But, like Meta Base will be your best place to do like super custom queries. And like, really like more complicated data joins and stuff like that. It’s it’s likely, Iris, you can’t customize as much. I’ve never used the tool directly, but I looked into it after after you kind of brought it up.
79 00:14:51.800 ⇒ 00:14:55.959 Aman Nagpal: And once we have whatever main dashboards reports that we want set up in metabase.
80 00:14:56.030 ⇒ 00:14:59.870 Aman Nagpal: Then Jared can just go in and click between the reports and see whatever he wants to see right.
81 00:14:59.870 ⇒ 00:15:01.160 Payas Parab: Exactly. Yep.
82 00:15:01.160 ⇒ 00:15:11.629 Aman Nagpal: Okay, yeah, I’m good with starting with that. And then I know you’ve sent over some other options. We can see what else is out there for visualization tools if we want to switch, you know, in the near future. But for now I think that makes sense.
83 00:15:12.830 ⇒ 00:15:13.530 Payas Parab: Excellent.
84 00:15:17.220 ⇒ 00:15:17.850 Nicolas Sucari: Cool.
85 00:15:17.950 ⇒ 00:15:29.509 Nicolas Sucari: Okay. So Aman, after working on these dashboards. We want to bring the north beam data into into Snowflake, too. So if you can share any access
86 00:15:29.873 ⇒ 00:15:40.509 Nicolas Sucari: so we can start looking. How we can do that connection would be good. And then, Brian, I don’t know if we have any other update on the data side, if you want to share.
87 00:15:44.640 ⇒ 00:15:49.160 Brian Pei: nothing crazy for me. No, I I set up the Dbt
88 00:15:49.720 ⇒ 00:15:52.503 Brian Pei: cloud like job orchestrator, basically.
89 00:15:53.170 ⇒ 00:15:56.189 Brian Pei: where the the prod tables. They’re not dev anymore.
90 00:15:56.220 ⇒ 00:15:59.899 Brian Pei: They run once a day. And
91 00:15:59.990 ⇒ 00:16:04.130 Brian Pei: it ran successfully, I think, for 7 days in a row now.
92 00:16:04.440 ⇒ 00:16:07.240 Brian Pei: and the snowflake cost
93 00:16:07.430 ⇒ 00:16:12.840 Brian Pei: associated with these daily runs went up by like 30 or $40. So
94 00:16:12.860 ⇒ 00:16:15.000 Brian Pei: that’s just all good stuff.
95 00:16:15.551 ⇒ 00:16:18.680 Brian Pei: Low cost on Snowflake, and the
96 00:16:19.780 ⇒ 00:16:24.250 Brian Pei: orders and customers and products, and all the tables that we’ve been working on are are updating daily. Now.
97 00:16:27.550 ⇒ 00:16:29.089 Aman Nagpal: Sweet. Thank you.
98 00:16:29.750 ⇒ 00:16:31.210 Nicolas Sucari: Excellent. Okay.
99 00:16:31.683 ⇒ 00:16:33.900 Nicolas Sucari: I don’t have anything else
100 00:16:34.380 ⇒ 00:16:38.349 Nicolas Sucari: for me, so I don’t know, Aman. If you have any any question.
101 00:16:39.770 ⇒ 00:16:47.460 Aman Nagpal: Yeah, let me do the north theme stuff. Now let me make sure you have what you need. So do you just need to get added as a user. Do you need an Api key?
102 00:16:48.959 ⇒ 00:17:01.429 Nicolas Sucari: I’m not sure. Maybe you can give us access, and we can look into what we need in order to bring the data. I think an Api, yeah. Api key would be would do it. So that we can connect that
103 00:17:01.480 ⇒ 00:17:03.210 Nicolas Sucari: try to see if we can bring.
104 00:17:03.220 ⇒ 00:17:04.400 Nicolas Sucari: What do we count? There.
105 00:17:05.290 ⇒ 00:17:08.750 Aman Nagpal: Sounds good. Who should I add? I can add the emails right now.
106 00:17:09.349 ⇒ 00:17:11.439 Nicolas Sucari: Add me and Brian, if you want. Yeah.
107 00:17:12.159 ⇒ 00:17:14.619 Nicolas Sucari: I can share the email here in the chat.
108 00:17:20.480 ⇒ 00:17:22.880 Aman Nagpal: Okay, added you, let me add, Brian.
109 00:17:28.140 ⇒ 00:17:30.686 Nicolas Sucari: Brian is Brian. Yeah, Brian, I’m Brian.
110 00:17:31.850 ⇒ 00:17:32.700 Nicolas Sucari: Cool.
111 00:17:32.960 ⇒ 00:17:34.369 Aman Nagpal: So those 2 are all set.
112 00:17:35.610 ⇒ 00:17:36.370 Nicolas Sucari: Excellent.
113 00:17:37.500 ⇒ 00:17:39.275 Aman Nagpal: Cool. So it seems like
114 00:17:41.120 ⇒ 00:17:46.759 Aman Nagpal: a lot of the I mean, like you said Prod, is live so table side. Most of that stuff is done. So what’s
115 00:17:46.860 ⇒ 00:17:49.540 Aman Nagpal: I guess? Next in, you know.
116 00:17:50.237 ⇒ 00:17:52.560 Aman Nagpal: The process! What’s remaining? What’s next?
117 00:17:54.880 ⇒ 00:17:57.609 Nicolas Sucari: In the process of creating the dashboards or.
118 00:17:58.160 ⇒ 00:18:16.130 Aman Nagpal: Just so, you know we did. We pulled in all the data right? So that was Step one. We put it in Snowflake. We set up. Dbt, all the tables are live so in that this whole you know long term process. And now it’s dashboards is that is, that we’re working on now. Anything after that.
119 00:18:17.140 ⇒ 00:18:41.979 Nicolas Sucari: I mean, ideally, we can start looking into the dashboards and see if we can answer any question you have to for off the business. And also we are bringing more data sources in, I mean, we’re gonna start with north beam. And then if you have any other data source that we want to bring. I know we talked about tiktok shops maybe we can work on something custom for that or any other data source that you have around that we can that we want to bring into Snowflake. We can do that. And after that
120 00:18:41.980 ⇒ 00:18:47.290 Nicolas Sucari: continue to create dashboards. And yeah, start doing some analysis on all of the data.
121 00:18:47.890 ⇒ 00:18:52.479 Aman Nagpal: That sounds good. Yeah. So I guess now is the point where, while we figure out, you know, play with these tools.
122 00:18:53.092 ⇒ 00:19:00.409 Aman Nagpal: Work in the dashboards bring in additional data like you said, maybe tweak anything that we need to change with the existing data that’s coming in.
123 00:19:00.410 ⇒ 00:19:01.190 Nicolas Sucari: Exactly.
124 00:19:01.555 ⇒ 00:19:16.159 Aman Nagpal: Just a reminder. We did turn on netsuite and are phasing out of extensive. So extensive is no longer syncing orders. So just wanna throw that out there. And then we are changing our domain in the next
125 00:19:16.540 ⇒ 00:19:17.930 Aman Nagpal: 2 or 4 weeks.
126 00:19:18.541 ⇒ 00:19:22.470 Aman Nagpal: I don’t think that’ll make a difference, but just want to throw that out there as well.
127 00:19:23.211 ⇒ 00:19:31.750 Aman Nagpal: But yeah, I think all that at this point, just thinking of additional data that we might need. I know we’ve spoken about O. Kendo. That would be good data to start pulling in.
128 00:19:33.700 ⇒ 00:19:34.930 Aman Nagpal: you know, and maybe we.
129 00:19:34.930 ⇒ 00:19:35.500 Nicolas Sucari: Yes.
130 00:19:35.500 ⇒ 00:19:37.619 Aman Nagpal: To. Yeah, gorgeous would be great.
131 00:19:37.650 ⇒ 00:19:39.160 Aman Nagpal: All the
132 00:19:39.520 ⇒ 00:19:42.300 Aman Nagpal: performance marketing data
133 00:19:42.410 ⇒ 00:19:45.520 Aman Nagpal: that where I guess that’ll be maybe the next
134 00:19:45.990 ⇒ 00:19:47.640 Aman Nagpal: big bucket
135 00:19:48.047 ⇒ 00:19:52.509 Aman Nagpal: where, instead of sending directly to Amp, we send it to this to Snowflake first, st
136 00:19:52.570 ⇒ 00:19:59.249 Aman Nagpal: and then send from there to amplitude whatever we need. I think that might be the next logical buck. Big bucket right.
137 00:20:00.970 ⇒ 00:20:02.130 Nicolas Sucari: Yeah. Robert.
138 00:20:03.420 ⇒ 00:20:06.039 Robert Tseng: Yeah, just wanna kind of yeah
139 00:20:06.110 ⇒ 00:20:11.220 Robert Tseng: gonna tie tie this conversation that we’re we’re kind of. We’re we’re talking about
140 00:20:11.430 ⇒ 00:20:26.819 Robert Tseng: like, kind of progress in the engagement we’re talking about. Okay with the data pipe lining work. We’ve already gone. All these initial sources in. We have some initial reporting pies is troubleshooting with Jared right making sure that that 1st deliverable and financial reporting is is tightened up for him.
141 00:20:27.271 ⇒ 00:20:40.390 Robert Tseng: I guess Aman can continue to support us by giving us the priority. For what are the other sources that we need to add? So Nico and Brian can continue to keep getting those getting those in so that work stream will stay active.
142 00:20:40.740 ⇒ 00:20:46.679 Robert Tseng: But yeah, as far as like, what’s next? Like, I think I would like to see Pius and I get back with
143 00:20:47.270 ⇒ 00:20:49.700 Robert Tseng: I guess Justin and the in the
144 00:20:49.990 ⇒ 00:20:52.570 Robert Tseng: I, yeah and and guys to
145 00:20:53.650 ⇒ 00:20:58.870 Robert Tseng: yeah, we want to like be able to do more analysis for you guys. Right? So we don’t. I know it.
146 00:20:58.910 ⇒ 00:21:13.080 Robert Tseng: I I hope that we’re not just. I mean, I we these reports that we’re doing like, we’re gonna yeah. They’re they’re gonna result in dashboards. But ultimately we wanna come away with like month 2 and month 3, being able to tell you how we impacted
147 00:21:13.398 ⇒ 00:21:37.910 Robert Tseng: particular, like very specific analyses that we did that help decisions. Right? So I would like to see us kind of have a tighter feedback loop with those guys. Now that the foundational work is done. So I think that’s kind of why I’m jumping back in at this point because I’d like to see what we can do to get in on. Those conversations have regular check ins with Justin and guys again, like we did in the beginning before we started all this
148 00:21:38.456 ⇒ 00:21:40.790 Robert Tseng: data engineering work as well.
149 00:21:41.118 ⇒ 00:21:45.090 Robert Tseng: But yeah, I think that’s kind of all I wanted to add to this so far.
150 00:21:45.560 ⇒ 00:21:56.119 Aman Nagpal: That I think that’s perfect. Yeah, I think we can start back into the loop and start getting back to. You know the analysis. Now that a lot of this foundational setup is, you know, kind of on the way.
151 00:21:56.731 ⇒ 00:22:02.870 Aman Nagpal: And as we mentioned that one more thing popped into my head that maybe we can do soon.
152 00:22:03.225 ⇒ 00:22:22.119 Aman Nagpal: You know. Maybe even this week I don’t know what the you guys bandwidth is, but we were looking into. Finally, we’ve spoken about this matching up our Amazon customers to our shopify customers. So you know, we’ve tried exporting the sheets and doing all that, but the sheets are so massive. Is there a quick way to.
153 00:22:22.120 ⇒ 00:22:35.550 Aman Nagpal: or you know what we can set up to match those customers up, and that way we can get them, maybe into Klaviyo as a list and email out, you know, specifically to people who have purchased on Amazon and on the site. Let’s say things like that.
154 00:22:43.090 ⇒ 00:23:03.920 Nicolas Sucari: So, yeah, the the issue with Amazon was that we cannot get list of users because they are encrypted. Right? So, yeah, I think there might be a turn. I I don’t know if there is a workaround on that one. Maybe, Brian, I can help us there if we can try to match those users. But the yeah, I I don’t know if if we
155 00:23:03.920 ⇒ 00:23:20.100 Nicolas Sucari: use the Amazon list into clay into Klavia, and then export that I don’t think I I’m not sure if we’re gonna get that like that data of the users from Amazon from there. But yeah, I think we can take a look. I mean, I’m not sure about it. But we can take a look. Yeah.
156 00:23:20.410 ⇒ 00:23:20.900 Aman Nagpal: Yeah, I think.
157 00:23:20.900 ⇒ 00:23:23.874 Robert Tseng: Have all the shopify. Sorry.
158 00:23:24.740 ⇒ 00:23:30.879 Robert Tseng: yeah. I just want to know, like how which users are in your clear view campaigns right now, is it just a shopify.
159 00:23:30.880 ⇒ 00:23:31.450 Nicolas Sucari: Bye.
160 00:23:31.790 ⇒ 00:23:43.320 Aman Nagpal: Yeah, I don’t think we’re doing anything with Amazon customers yet. So I mentioned before, the data we’re pulling right now from Amazon. Api directly. Seems a lot more. What’s the word?
161 00:23:43.717 ⇒ 00:23:47.930 Aman Nagpal: Like a lot of the information is is hidden compared to what you guys are getting directly.
162 00:23:48.276 ⇒ 00:23:52.859 Aman Nagpal: So I think you guys are getting the street address. Is that correct? For Amazon sales?
163 00:23:53.130 ⇒ 00:23:53.550 Nicolas Sucari: Yes.
164 00:23:53.550 ⇒ 00:23:54.749 Robert Tseng: Yeah, but we can.
165 00:23:54.750 ⇒ 00:23:55.629 Nicolas Sucari: I think. Yes.
166 00:23:55.630 ⇒ 00:23:59.730 Aman Nagpal: Reader dress and maybe name if they give it to us. I think that would be ideal.
167 00:24:07.440 ⇒ 00:24:07.780 Robert Tseng: So.
168 00:24:07.780 ⇒ 00:24:08.939 Nicolas Sucari: Sounds like that, sir.
169 00:24:08.940 ⇒ 00:24:14.509 Robert Tseng: Someone wants, like an enriched data set of like the customers that we get from Amazon.
170 00:24:14.944 ⇒ 00:24:25.629 Robert Tseng: We may not be able to tie them to email. I guess that’s something we can look into. But if not, is that still helpful? Just to give you what we do have like name, email, whatever or address.
171 00:24:26.240 ⇒ 00:24:45.050 Aman Nagpal: Yeah, whatever we can match up. Right? So, Amazon, if they have that fake, you know, at marketplaces, whatever email for Amazon customers, we can’t really use that. But if we have the street address and we have them as a customer within shopify. But then we have their email and shopify. We can kind of connect everything that way. I don’t know if this is a separate table or how you wanna do that. But
172 00:24:45.397 ⇒ 00:24:52.880 Aman Nagpal: that way. We just know the all these customers that we have emails for have purchased on Amazon. Then we can market them a separate way.
173 00:24:54.240 ⇒ 00:24:56.262 Brian Pei: I can do that. Yeah, it’s
174 00:24:57.540 ⇒ 00:24:59.108 Brian Pei: Yeah, like what the team said.
175 00:24:59.800 ⇒ 00:25:01.140 Brian Pei: the emails are hashed
176 00:25:01.510 ⇒ 00:25:02.749 Brian Pei: but I’ll make an
177 00:25:03.820 ⇒ 00:25:06.360 Brian Pei: I’ll make an Amazon customers logic table.
178 00:25:06.860 ⇒ 00:25:09.140 Brian Pei: and then I’ll do a
179 00:25:09.700 ⇒ 00:25:13.679 Brian Pei: full outer join on the spotify customers and give you a
180 00:25:15.080 ⇒ 00:25:16.869 Brian Pei: dim customer improd. I guess
181 00:25:17.200 ⇒ 00:25:19.709 Brian Pei: I’ll I’ll start working on that
182 00:25:20.805 ⇒ 00:25:21.640 Brian Pei: today.
183 00:25:22.540 ⇒ 00:25:24.500 Aman Nagpal: Sweet. So that would just be a separate table.
184 00:25:24.710 ⇒ 00:25:32.859 Brian Pei: The Amazon will be a separate table. Yeah, and then I’ll try to Fuzzy join them with shopify. But I think that the Amazon might be enough
185 00:25:34.270 ⇒ 00:25:36.260 Brian Pei: sure to start to start, anyway.
186 00:25:36.440 ⇒ 00:25:39.549 Aman Nagpal: Is that separate from the Amazon table we already have.
187 00:25:40.258 ⇒ 00:25:46.079 Brian Pei: It would be separate. Yeah, the this fuzzy, joining Amazon customer thing. I I haven’t
188 00:25:46.740 ⇒ 00:25:48.010 Brian Pei: done yet.
189 00:25:49.410 ⇒ 00:26:14.650 Aman Nagpal: Okay, yeah. Keep me posted. If if there’s any other info I can provide but I think this will be really good, because we are trying to do that soon. So I can go back to the guys and say, Hey, look, we can. You know, this is an immediate thing, you know, since they haven’t been involved in this data warehouse process as much yet. They will be now. But it’s like, Hey, that you know, we have this right away. Just from having all this data available right?
190 00:26:15.200 ⇒ 00:26:15.930 Brian Pei: Right?
191 00:26:17.160 ⇒ 00:26:20.259 Brian Pei: Yeah, I’ll share something in a in our slack channel.
192 00:26:20.850 ⇒ 00:26:25.390 Brian Pei: cause I I have started on it. So I just need to go back and and see if I can productionize it.
193 00:26:25.800 ⇒ 00:26:27.320 Aman Nagpal: Thank you. That sounds great.
194 00:26:30.290 ⇒ 00:26:37.589 Aman Nagpal: But otherwise I think that’s it for me. I mean, you know, we’re making a lot of progress. Things are looking good. I will
195 00:26:37.650 ⇒ 00:26:43.029 Aman Nagpal: share real. And once metabase is set up with Justin and Jared.
196 00:26:45.400 ⇒ 00:26:49.169 Aman Nagpal: And yeah, I think I just sent over North theme.
197 00:26:49.320 ⇒ 00:26:53.060 Aman Nagpal: If you, I can get you access to Okendo. Gorgeous
198 00:26:53.340 ⇒ 00:26:57.850 Aman Nagpal: we’ll try to think of any other data sources, and you know, we can just keep moving onwards.
199 00:26:59.130 ⇒ 00:27:08.539 Nicolas Sucari: Excellent. Okay, can you share me the emails Justin’s and Jared email so that I can add them to real, so that they can see the dashboard.
200 00:27:09.150 ⇒ 00:27:10.609 Aman Nagpal: I’ll shoot that in slack.
201 00:27:11.210 ⇒ 00:27:16.439 Nicolas Sucari: I think we already, added one of them. I don’t know who else but yes. Do you remember Justin or Jared.
202 00:27:17.335 ⇒ 00:27:18.520 Payas Parab: Jared, I think.
203 00:27:19.130 ⇒ 00:27:19.730 Nicolas Sucari: Okay.
204 00:27:20.470 ⇒ 00:27:22.579 Nicolas Sucari: So then I need Just Justin’s email.
205 00:27:24.640 ⇒ 00:27:25.220 Nicolas Sucari: terrific.
206 00:27:25.220 ⇒ 00:27:26.629 Aman Nagpal: Just sync it in slack.
207 00:27:27.520 ⇒ 00:27:28.710 Nicolas Sucari: Excellent. Okay.
208 00:27:30.070 ⇒ 00:27:42.599 Nicolas Sucari: great. One more question. Once you change the domain. I I think it was from Javi with one B to double d right you will change the emails and everything, too, or just.
209 00:27:44.280 ⇒ 00:27:54.810 Aman Nagpal: Right now. We’re just going to do it as an alias. So that’s how we’ve been setting that demo up. So the initial email will still be the primary email, the single V
210 00:27:55.104 ⇒ 00:27:58.690 Aman Nagpal: maybe down the road. We’ll change right now. It’ll just be an alias to double B.
211 00:27:59.620 ⇒ 00:28:00.810 Nicolas Sucari: Excellent bye
212 00:28:01.470 ⇒ 00:28:15.029 Nicolas Sucari: cool. So I’ll give access to them to rail, and I’ll change the tables to bring the data from Broad. And I, I am gonna check. If we can create any other table regarding the data, the data that we have so that we can have like a further
213 00:28:15.090 ⇒ 00:28:19.249 Nicolas Sucari: analysis or more dashboards. There’s in order to look into specific things. Okay.
214 00:28:19.950 ⇒ 00:28:22.750 Aman Nagpal: That sounds good. And then I think next week
215 00:28:23.170 ⇒ 00:28:25.260 Aman Nagpal: we can try to find a time.
216 00:28:26.920 ⇒ 00:28:29.579 Aman Nagpal: with Jared and Justin, and kind of
217 00:28:30.000 ⇒ 00:28:30.650 Aman Nagpal: go over there.
218 00:28:30.650 ⇒ 00:28:31.719 Nicolas Sucari: Yeah, show them
219 00:28:33.510 ⇒ 00:28:45.050 Nicolas Sucari: cool. Yeah, I think that that’s gonna be useful for them. And if we can find that time, I can also record a long video explaining a little bit of the features of Real, and we can share it to them too.
220 00:28:45.400 ⇒ 00:28:55.749 Aman Nagpal: That would be really helpful, too. I just checked. I am out Thursday, Friday next week. So if we end up having a call. We can do it earlier. But I think that really helpful as well.
221 00:28:56.100 ⇒ 00:29:01.350 Nicolas Sucari: I’ll I’ll do it anyway, so that we can have that one just for anyone who needs it. Okay.
222 00:29:02.120 ⇒ 00:29:03.730 Aman Nagpal: You got it. Thank you.
223 00:29:04.440 ⇒ 00:29:05.150 Nicolas Sucari: Excellent.
224 00:29:06.080 ⇒ 00:29:08.319 Nicolas Sucari: Okay, anything else. Guys.
225 00:29:14.790 ⇒ 00:29:31.550 Robert Tseng: No, I think this is good good check in yeah. Hope we can catch Justin Jared next week. Wanna give him give them a progress update on where we’re at, so we can get them engaged again and hopefully start to turn out more stuff quickly through through the next. The next month.
226 00:29:31.900 ⇒ 00:29:33.956 Aman Nagpal: Yeah. And oh, one last thing, the
227 00:29:34.470 ⇒ 00:29:37.880 Aman Nagpal: the higher. So I gotta look at all the
228 00:29:37.900 ⇒ 00:29:41.950 Aman Nagpal: if any application that came in through Linkedin. I know.
229 00:29:42.453 ⇒ 00:29:47.149 Aman Nagpal: You know we we kind of clarify that. So you know I’m getting as many
230 00:29:47.775 ⇒ 00:29:50.780 Aman Nagpal: applicants as I can. I’ll go through them.
231 00:29:51.162 ⇒ 00:29:56.489 Aman Nagpal: You know, we can set up interviews. And you know, if you guys are available to take the interviews, then we can kind of
232 00:29:56.760 ⇒ 00:30:03.210 Aman Nagpal: do that as a next step, and of course, any candidates, if you happen to have pop up, we’ll stick with who we find.
233 00:30:03.390 ⇒ 00:30:16.740 Robert Tseng: Yeah, I’ve I’ve I’ve opened that up. So I have, like probably 20 candidates that have come in just like through the 1st round of us like reaching out to our partners overseas, and then
234 00:30:17.466 ⇒ 00:30:22.449 Robert Tseng: I’ll probably shortlist down that down to 5. And so I think I contribute 5 applicants to that.
235 00:30:23.500 ⇒ 00:30:27.430 Aman Nagpal: That’d be great, would it? Would it be helpful for me to send over
236 00:30:27.770 ⇒ 00:30:31.259 Aman Nagpal: the Cvs that we’ve gotten? Or do you want me to just
237 00:30:31.430 ⇒ 00:30:33.169 Aman Nagpal: set up some interviews. What do you think.
238 00:30:33.387 ⇒ 00:30:46.849 Robert Tseng: Yeah, I actually think it’d be good if we do this kind of like blind test where you kind of come up with your list, and then I’ll come up, and we I short your short list, and then, as we kind of evaluate candidates, we’ll see like you know, if there were any gaps in the way that we evaluated them.
239 00:30:47.356 ⇒ 00:30:53.610 Robert Tseng: And then maybe that’ll inform like, how we evaluate the next round. I suppose.
240 00:30:54.240 ⇒ 00:30:55.050 Aman Nagpal: That sounds good.
241 00:30:55.050 ⇒ 00:30:55.610 Robert Tseng: Yeah.
242 00:30:57.350 ⇒ 00:31:00.230 Aman Nagpal: Cool. That’s it for me. Thank you guys so much.
243 00:31:01.660 ⇒ 00:31:02.890 Aman Nagpal: Thank you, man.
244 00:31:02.890 ⇒ 00:31:03.490 Robert Tseng: Alright! Thanks.
245 00:31:03.490 ⇒ 00:31:04.270 Nicolas Sucari: Great week.
246 00:31:04.270 ⇒ 00:31:05.779 Aman Nagpal: Have a good one, guys. Bye.
247 00:31:06.140 ⇒ 00:31:06.810 Nicolas Sucari: Bye-bye.