Meeting Title: Brainforge Data Standup - Group 1 Date: 2025-02-17 Meeting participants: Nicolas Sucari, Uttam Kumaran, Bo Yoon, Robert Tseng, Sahana Asokan, Awaish Kumar, Caio
WEBVTT
1 00:03:24.810 ⇒ 00:03:25.630 Uttam Kumaran: Hey!
2 00:04:12.830 ⇒ 00:04:13.960 Bo Yoon: Hey! Good morning!
3 00:04:14.570 ⇒ 00:04:15.329 Uttam Kumaran: Good morning!
4 00:04:16.370 ⇒ 00:04:17.220 Caio: Good morning!
5 00:04:21.810 ⇒ 00:04:25.696 Uttam Kumaran: Cool. Let’s let’s get into it.
6 00:04:30.930 ⇒ 00:04:34.916 Uttam Kumaran: So in this meeting, I wanted to talk about
7 00:04:35.530 ⇒ 00:04:40.339 Uttam Kumaran: we basically are trying to split into 2 groups. So I want to talk about Eden. I want to talk about
8 00:04:40.713 ⇒ 00:04:46.789 Uttam Kumaran: cool parts, and then we want to talk about our helper, and then I think we have another meeting after this for some folks
9 00:04:47.030 ⇒ 00:04:49.809 Uttam Kumaran: where we’ll talk about Javi and some of the other clients.
10 00:04:50.645 ⇒ 00:04:53.569 Uttam Kumaran: So I’m just gonna sort of walk through
11 00:04:54.151 ⇒ 00:04:57.868 Uttam Kumaran: tickets and get a sense of how things are going.
12 00:04:58.430 ⇒ 00:05:03.990 Uttam Kumaran: I did a little bit of organization. But let’s talk about Eden 1st
13 00:05:04.570 ⇒ 00:05:07.330 Uttam Kumaran: and then we can go from there.
14 00:05:09.470 ⇒ 00:05:17.160 Uttam Kumaran: cool. So I think the big things I wanted to sort of get a sense of is probably with Sahana. How can I help
15 00:05:17.310 ⇒ 00:05:18.190 Uttam Kumaran: with
16 00:05:19.200 ⇒ 00:05:34.970 Uttam Kumaran: sort of some of these that are related to strategy, like the mix panel rollout the dashboard mock ups and some of these dashboard tickets like, Give me a sense of like where we’re at on these. I’m coming in a little bit
17 00:05:35.210 ⇒ 00:05:40.349 Uttam Kumaran: fresh in terms of the reporting side. I have a good understanding of, like all the data and things like that.
18 00:05:40.802 ⇒ 00:05:46.139 Uttam Kumaran: But yeah, if you can give me a sense of where we’re at with everything and sort of what’s top of mind for you.
19 00:05:46.410 ⇒ 00:06:01.152 Sahana Asokan: Yeah. So I think for this week top of line is, I think the 1st thing that we were really kicking off is the look at tableau migration. So I would say, like, P. 0, priority is getting an executive dashboard built in tableau
20 00:06:02.068 ⇒ 00:06:10.429 Sahana Asokan: with respect to the Member experience teams as well as farm Ops. That’s where you see, like the mock up tickets
21 00:06:10.750 ⇒ 00:06:13.590 Sahana Asokan: and all of that stuff with the notion.
22 00:06:14.365 ⇒ 00:06:15.030 Sahana Asokan: For
23 00:06:15.140 ⇒ 00:06:33.620 Sahana Asokan: for that I’ve just finished drafting out requirements for what the dashboard will essentially look like. And then the second priority for this week is getting mockups done for both teams and their respective dashboards and figma. I will take the one blocker
24 00:06:34.200 ⇒ 00:06:40.910 Sahana Asokan: between dashboard mockups and dashboard execution for Member Experience and
25 00:06:41.425 ⇒ 00:06:55.470 Sahana Asokan: Farm Ops Zendesk data, because both of those teams need. They both want a lot of they’re interested in a lot of data around like solved tickets and agent performance, so
26 00:06:55.500 ⇒ 00:07:14.170 Sahana Asokan: I don’t plan on kicking off, building out those dashboards till we have everything. I know you had mentioned that we already have bask. I just haven’t had a chance to like. Look and see what we actually have versus what we don’t have. I? That exercise will probably start after I’m done with the executive dashboard.
27 00:07:16.060 ⇒ 00:07:26.299 Uttam Kumaran: And so I noticed. So there’s so there’s these 2 dashboards. There’s a looker to tableau. There’s also some things around event tracking implementation. The mix panel.
28 00:07:26.300 ⇒ 00:07:26.960 Sahana Asokan: Yeah.
29 00:07:26.960 ⇒ 00:07:34.201 Uttam Kumaran: Roll out. Give me a sense of how those 2 are also like, I guess. Give me a sense of where we are on those and
30 00:07:34.630 ⇒ 00:07:39.130 Uttam Kumaran: And then also, I I noticed there’s some stuff in plan, but I guess most of my concern is
31 00:07:39.300 ⇒ 00:07:48.900 Uttam Kumaran: anything that you were kind of like, okay, I can help with this strategy or things here. That’s some stuff I can probably take. But I guess. Give me a sense of like how these these 2 are.
32 00:07:49.090 ⇒ 00:07:57.830 Sahana Asokan: Yeah, I’m gonna be honest, I think the event tracking implementation and the strategy mixed panel rollout was something kicked off by Robert. It’s just more like
33 00:07:58.140 ⇒ 00:08:02.440 Sahana Asokan: we have data in mixed panel. No one’s really using it.
34 00:08:02.580 ⇒ 00:08:03.120 Uttam Kumaran: It’s a.
35 00:08:03.120 ⇒ 00:08:22.460 Sahana Asokan: Opportunity to kind of like, create a more robust data model. So I’m not leading that one. To be quite frank with you. So I would. I would probably sync on Robert with that to see like, if that’s something we’re still trying to push forward this week. There’s just a lot happening, I think, with Eden. So that’s kind of like
36 00:08:22.810 ⇒ 00:08:28.240 Sahana Asokan: the why, it’s a little getting a little unorganized. Because it’s like
37 00:08:28.700 ⇒ 00:08:33.769 Sahana Asokan: cause cause we’re doing separate initiatives with, you know, specific business operations, teams.
38 00:08:33.770 ⇒ 00:08:34.110 Uttam Kumaran: Yeah.
39 00:08:34.110 ⇒ 00:08:43.439 Sahana Asokan: Like customer experience and pharmacy, etc. So I’m leading those 2. So that’s 1 task. The other task is working with executives.
40 00:08:43.440 ⇒ 00:08:44.240 Uttam Kumaran: You’ll see. Okay.
41 00:08:44.240 ⇒ 00:08:56.069 Sahana Asokan: Building out, you know, high level dashboards. I think me and Beau are doing that. He’s working on marketing. I’m working on the executive one, and then the last piece to this is their entire data model. To begin with.
42 00:08:56.070 ⇒ 00:08:56.760 Uttam Kumaran: Yes.
43 00:08:57.170 ⇒ 00:09:06.959 Sahana Asokan: So I think traditionally, we would have fixed the data model. But before doing any of this, but I think we’re kind of in a spot where we’re trying to give them what they want, but also fix
44 00:09:07.260 ⇒ 00:09:08.899 Sahana Asokan: their data model.
45 00:09:08.900 ⇒ 00:09:09.310 Uttam Kumaran: You’re right.
46 00:09:09.310 ⇒ 00:09:11.599 Sahana Asokan: So it’s just kind of messy.
47 00:09:11.600 ⇒ 00:09:15.820 Uttam Kumaran: So that makes a lot of sense. I think anything that’s sort of around.
48 00:09:15.960 ⇒ 00:09:34.199 Uttam Kumaran: There’s a problem here. What’s what do we do? I can take, so I’ll take that and sort of build out the roadmap. For what do we do with mixed panel stuff like that? I think anything where you you can keep working on a dashboard, mock up and buy a little bit of time on like that side
49 00:09:34.440 ⇒ 00:09:43.909 Uttam Kumaran: in order to build the reporting you need. I want to get a sense of like, what’s the 1st set of requirements for the, for the, for the analytics that we would need for
50 00:09:44.523 ⇒ 00:09:51.710 Uttam Kumaran: and this is this Px, is this pharmacy, or is this yeah pharmacy? And then for customer.
51 00:09:51.850 ⇒ 00:09:53.650 Sahana Asokan: Yeah, experience. Okay?
52 00:09:53.650 ⇒ 00:09:56.023 Sahana Asokan: Cause like, the the thing is right now.
53 00:09:56.760 ⇒ 00:10:02.719 Sahana Asokan: I can’t really see all the data that they have in Zendesk, because it doesn’t really help like help. You look at it like that.
54 00:10:02.720 ⇒ 00:10:03.270 Uttam Kumaran: Yeah, yeah.
55 00:10:03.270 ⇒ 00:10:10.760 Sahana Asokan: So I was hoping that once we get it all in, then I’ll actually know, like what we have versus what we don’t have. So that’s kind of the blocker there.
56 00:10:10.760 ⇒ 00:10:14.740 Uttam Kumaran: I can also, like we have Zendesk for several other clients.
57 00:10:14.740 ⇒ 00:10:15.280 Sahana Asokan: Yeah.
58 00:10:15.280 ⇒ 00:10:22.415 Uttam Kumaran: I can give you a sense of like what that data model is gonna look like, and maybe give you a snippet that way. You can see that.
59 00:10:23.060 ⇒ 00:10:30.600 Uttam Kumaran: I think ultimately, also, this may be just like getting do. Are they like pretty good at like telling you exactly what they want, or they more like you tell us, okay.
60 00:10:30.600 ⇒ 00:10:35.770 Sahana Asokan: No, it’s it’s pretty self explanatory, like, I actually don’t think I need to know what data we have, because.
61 00:10:35.770 ⇒ 00:10:39.859 Uttam Kumaran: Yeah, it’s a ticket. Resolution times. Who’s assigned to how fast is it? Yeah. Okay.
62 00:10:39.860 ⇒ 00:10:48.070 Sahana Asokan: That’s why I was just gonna build out the dash like mock up like visuals this week. And figma just kind of be like, hey, like this is what the agent performance dashboard is. Gonna
63 00:10:48.070 ⇒ 00:10:48.520 Sahana Asokan: right?
64 00:10:48.520 ⇒ 00:11:04.060 Sahana Asokan: This is what the operational efficiency dashboard is gonna look like and then once they approve of it. Then I’ll probably start building those out next week, but I think the biggest priority for this week is rebuilding that executive dashboard.
65 00:11:04.060 ⇒ 00:11:20.119 Uttam Kumaran: Okay. Okay, so keep keep going on the mock ups. That was, gonna buy some time. We’ll build a pretty classic Zendesk data model for you, which has all that stuff, and then there may be a couple of tweaks that you need, but then I don’t think I think that’s on our plate to
66 00:11:20.260 ⇒ 00:11:30.310 Uttam Kumaran: finish up Zendesk ideally. Try to get that available to you in the warehouse this week. Take that on. Tell me like, how does this look like
67 00:11:30.570 ⇒ 00:11:31.480 Uttam Kumaran: for
68 00:11:31.730 ⇒ 00:11:40.149 Uttam Kumaran: this looker to tableau like I’ve done a lot of stuff in tableau. Are you using just like tableau cloud and sort of building it
69 00:11:40.320 ⇒ 00:11:43.409 Uttam Kumaran: there and like, I guess, give me a sense of like, how
70 00:11:43.640 ⇒ 00:11:50.070 Uttam Kumaran: what your migration plan is like. Are you creating connections there and then? Sort of building out views. Or how’s how’s this gonna work?
71 00:11:50.310 ⇒ 00:12:20.229 Sahana Asokan: Yeah, this is where I’m not really like. I’m not really sure what they’re doing on the Eden side, like, I like this should be done in desktop right? And I know Robert, the license. I. If the integration between bigquery and tableau is already set up, then it should be pretty self explanatory. Just because we already built this and looker. So I already know what fields to use. But I’m hoping that we can actually get this done by the end of this week. But it’s done in tableau desktop. It’s published to Tableau Cloud.
72 00:12:21.120 ⇒ 00:12:27.210 Uttam Kumaran: So I guess, Robert, do we already have tableau license? Is there anything there right now?
73 00:12:27.660 ⇒ 00:12:35.169 Robert Tseng: Yeah. So I I I set up tableau. I mean, they give us a 14 day trial. I mean, it’s tied to my account. So I don’t know if
74 00:12:35.310 ⇒ 00:12:43.477 Robert Tseng: we all have to share the same credits for it for that trial. But yeah, we have one creator seat for the Eden entity right now. And
75 00:12:44.020 ⇒ 00:13:02.660 Robert Tseng: yeah, I already. I mean, I downloaded desktop. And then I connected bigquery. And I I like I’ve made like a couple reports just to see that it works. So it works, and I I think at least that’ll unblock Sahana from. She can use the same account like kind of creds to to get in and and use it so.
76 00:13:02.940 ⇒ 00:13:06.579 Uttam Kumaran: Yeah, so can I. If we can get those creds in one password.
77 00:13:06.580 ⇒ 00:13:07.569 Robert Tseng: Yeah, they’re all one pass.
78 00:13:07.570 ⇒ 00:13:10.329 Uttam Kumaran: Okay, cool. Then I’m just gonna go in and
79 00:13:10.837 ⇒ 00:13:17.979 Uttam Kumaran: I’m just gonna go make sure that, like the connections are there and the tables are necessary. And it’s connected to prod marts, basically
80 00:13:18.572 ⇒ 00:13:21.649 Uttam Kumaran: and you have the core tables that we’re building
81 00:13:22.150 ⇒ 00:13:24.619 Uttam Kumaran: the performance and ult stuff from.
82 00:13:24.940 ⇒ 00:13:27.940 Uttam Kumaran: I think at that point. I don’t think there should be any
83 00:13:28.170 ⇒ 00:13:30.400 Uttam Kumaran: other blockers on the De side
84 00:13:30.570 ⇒ 00:13:36.179 Uttam Kumaran: to make that happen. I think you mentioned 14 day free trial. I don’t know how far we are on that already, if but.
85 00:13:36.180 ⇒ 00:13:38.570 Robert Tseng: No, no, I just. I just turned it on to this morning. So.
86 00:13:38.980 ⇒ 00:13:57.319 Robert Tseng: starting from today. And no, Sahana, we don’t have like, I mean, I didn’t use the license and activation key because we didn’t pay for it yet. I just use the O off from like the my my Eden Google account or whatever. So I think, if you just use my credits like you’ve been using for other stuff, it should be should work.
87 00:13:57.320 ⇒ 00:14:04.279 Sahana Asokan: So what is their plan here? They want to basically see what it looks like. And then, if they like it, they wanna actually purchase seats.
88 00:14:04.630 ⇒ 00:14:21.139 Robert Tseng: Well, I mean, they said that they’d be down to purchase it, but I’m kind of like hesitant, because I’m like, well, they only do annual plans, and so that’ll be. We’ll be committing like a thousand per per year already for just one user and they haven’t seen anything yet, so I’d rather just do the.
89 00:14:21.140 ⇒ 00:14:21.610 Sahana Asokan: Yeah, yeah.
90 00:14:21.610 ⇒ 00:14:41.019 Robert Tseng: They give us full functionality. So I feel like that’s enough time to show them what it’ll look like. And these 2 dashboards on this ticket are, I think, the ones that we would probably move into tableau. And just yeah, we’ll, we’ll hopefully, I mean, yeah, just get those to them. And then we can pay. After that.
91 00:14:41.270 ⇒ 00:14:49.940 Sahana Asokan: And you tagged me in 2 different tickets on in notion there was one where it was just executive. And then there was one executive cogs.
92 00:14:49.940 ⇒ 00:15:03.790 Robert Tseng: Oh, yeah, I forgot we had the executive cogs ticket. I mean, this is when we had broken out the executive dash into every section before. So I kind of already moved that one. We created a new ticket. That’s just exec
93 00:15:05.641 ⇒ 00:15:09.010 Robert Tseng: yeah, it’s in. It’s in planned, I think.
94 00:15:09.010 ⇒ 00:15:11.125 Sahana Asokan: Yeah, I’m just gonna follow that design. And figma.
95 00:15:11.810 ⇒ 00:15:17.649 Robert Tseng: Yeah. So I I it’s your design. I just like, kind of rearranged and like, edited a couple of things just to.
96 00:15:17.760 ⇒ 00:15:19.900 Robert Tseng: But yeah, you’ll you’ll see. Yeah.
97 00:15:19.900 ⇒ 00:15:22.689 Sahana Asokan: Yeah, I would say, like, between that and
98 00:15:23.170 ⇒ 00:15:28.589 Sahana Asokan: the other figma. Mockups like, those are kind of my main priorities for this week, because I think that’ll take a lot of time.
99 00:15:30.530 ⇒ 00:15:32.010 Robert Tseng: Yeah, that makes sense.
100 00:15:32.010 ⇒ 00:15:34.279 Uttam Kumaran: Yeah, I’m still like.
101 00:15:34.860 ⇒ 00:15:40.910 Uttam Kumaran: I don’t want to rehash the are we gonna do tableau conversation. But I but like, let me know if we should. Because.
102 00:15:41.750 ⇒ 00:15:53.440 Uttam Kumaran: yeah, I guess my concern is like, do we want to maintain tableau? It’s a lot of work definitely. And I guess I want to know what was the main reason why we went with tableau. Is it mainly just because of like
103 00:15:53.650 ⇒ 00:15:56.509 Uttam Kumaran: how flexible the executive reporting is for the stuff they wanted?
104 00:15:58.820 ⇒ 00:16:03.150 Sahana Asokan: Yeah, I think it was. It was made like, I think, from an analytics use case. It was just
105 00:16:04.030 ⇒ 00:16:08.240 Sahana Asokan: even like analytics functionality and looker studio kind of sucked.
106 00:16:08.240 ⇒ 00:16:08.650 Uttam Kumaran: Yes.
107 00:16:08.948 ⇒ 00:16:26.530 Sahana Asokan: So that’s definitely like a big part of it, like for some of the calculations they want like moving averages. Whatnot. You just don’t have as much flexibility in looker studio as you would in tableau, and I think the other parts of it, too, is just, you know, from like a ux perspective, right? Like it’s right now.
108 00:16:27.290 ⇒ 00:16:44.556 Sahana Asokan: They it’s they have a bunch of dashboards. But I think we can get it a lot more or organized with for different like business units within tableau like different folders, for, like customer experience versus farm Ops versus executive, like, each team can just click on their respective folders and access what they need.
109 00:16:45.246 ⇒ 00:16:50.573 Sahana Asokan: So I think those are kind of the main things I was thinking about. And I think also, just from
110 00:16:51.130 ⇒ 00:16:57.929 Sahana Asokan: creation perspective. It’s just easier. But I didn’t think about the main maintenance like maintenance, is not something we were considering.
111 00:16:58.240 ⇒ 00:16:58.810 Uttam Kumaran: Okay. Cool.
112 00:16:58.810 ⇒ 00:17:27.540 Robert Tseng: Yeah, we don’t, we? We I mean, I let kind of the team kind of advise which tool to go. Obviously local studios trash. So we just needed anything that’s better. But then Bo and Sahana both have tableau experience. Yeah, I mean, I guess the risk that we have is just that. Yeah, I mean, it’s a more specialized tool, like if both and are no longer here, we’re gonna have to get somebody who’s like a tableau specialist. And they typically Bill more than like a power bi or look around person.
113 00:17:27.540 ⇒ 00:17:33.140 Uttam Kumaran: I think it’s fine. I mean, I think my only suggestion would be we should look at Sigma also.
114 00:17:33.300 ⇒ 00:17:33.960 Uttam Kumaran: I did.
115 00:17:34.298 ⇒ 00:17:51.211 Robert Tseng: To them, but none of one. No one on their exact team has ever seen it before. So when I gave them options of like, you know, we we I put down. I put up 3 options for them. It was Sigma, real and tableau. They were just like tableau.
116 00:17:51.550 ⇒ 00:17:55.810 Uttam Kumaran: Were they like? Was it like soft? Or were they like we just heard of that? So let’s go with it.
117 00:17:55.810 ⇒ 00:18:00.879 Robert Tseng: No, it was just oh, we’ve heard of that. We don’t know what the other 2 are. And yeah, just like, let’s.
118 00:18:00.880 ⇒ 00:18:07.300 Uttam Kumaran: Let’s let’s still continue with it. Let’s still continue with this. This is gonna be an endless rabbit hole.
119 00:18:07.780 ⇒ 00:18:13.729 Uttam Kumaran: I do agree that we should get out of Looker. It sucks, I think we should decide.
120 00:18:15.500 ⇒ 00:18:26.979 Uttam Kumaran: what we want to do otherwise, this is more, a little bit more complicated than a lot of the dashboards we’re building out for other clients. But I would like to think about what is our enterprise dashboard solution of choice.
121 00:18:27.390 ⇒ 00:18:28.550 Uttam Kumaran: I’ve heard
122 00:18:28.770 ⇒ 00:18:39.714 Uttam Kumaran: really like in terms of all the options. I’ve heard really good things about Sigma. I’ve done a lot of work in tableau, so I feel like I feel pretty good about going with tableau as well.
123 00:18:40.210 ⇒ 00:18:51.910 Uttam Kumaran: so let’s just let’s just run through this exercise, and then, if we do have a little bit more time. We can try, Sigma. If they’re good with tableau, then we’ll call it, and then we’ll try Sigma for them for another client. But this is fine, I guess. How do you feel about
124 00:18:52.170 ⇒ 00:18:56.400 Uttam Kumaran: like the work associated with this for the performance marketing.
125 00:19:02.050 ⇒ 00:19:05.590 Bo Yoon: Not sure. So so, for the for the tableau task.
126 00:19:08.170 ⇒ 00:19:35.840 Robert Tseng: So, Bo, this is just like, instead of asking you to rebuild in the update in Looker studio. I’m just like we should just do it in tableau. So I know you were like clicking around and looker studio last week. But if you’re gonna be using the the data that we created in the staging looker, studio, dashboard and updating, we might as well not touch that, that the production dashboard and looker studio and just build a new. Just build it in tableau.
127 00:19:36.580 ⇒ 00:19:41.599 Bo Yoon: Yeah, yeah, so so basically, we’re just copying what we have on Looper studio to tablet. Right?
128 00:19:41.720 ⇒ 00:19:48.049 Bo Yoon: Yeah. So I, yeah, I already have tableau desktop in my computer. So
129 00:19:48.160 ⇒ 00:19:54.590 Bo Yoon: maybe I can just connect it to bigquery and build my own dashboard and then share the file with you.
130 00:19:55.330 ⇒ 00:20:17.169 Robert Tseng: Yeah, I think that would work, but also both just copying over like, I kind of walk you through the production dashboard. It has like 5 or 6 tabs. Maybe half of them aren’t being used. So I was thinking, if we’re gonna do this migration, we might as well just like make the adjustments to the either sunset a couple of the tabs, and nobody uses in that dashboard.
131 00:20:17.870 ⇒ 00:20:20.650 Robert Tseng: I don’t know. I don’t know if you remember that we had kind of chat.
132 00:20:21.068 ⇒ 00:20:26.090 Bo Yoon: Yeah, can we? Can we have another meeting for that? Yeah.
133 00:20:26.090 ⇒ 00:20:33.729 Uttam Kumaran: Yeah, I think like, let’s just focus on these 2. And then whatever you can take from others that needs to get packed in here
134 00:20:34.140 ⇒ 00:20:36.770 Uttam Kumaran: or fix. Let’s just do it as part of this exercise.
135 00:20:36.920 ⇒ 00:20:42.429 Uttam Kumaran: I sort of want to box this to like this week, though, because it’s not worth us spending
136 00:20:42.790 ⇒ 00:20:50.609 Uttam Kumaran: more time on tableau if we if we’re not sure. So Bo, just try to rip as much stuff in tableau as possible for performance marketing.
137 00:20:51.382 ⇒ 00:20:59.609 Uttam Kumaran: That way. We can send something to them this week about like, here’s a look and feel, because if they don’t like it, then it’s not gonna matter if we go the distance so
138 00:21:00.305 ⇒ 00:21:02.980 Uttam Kumaran: ideally just clone. Whatever is there
139 00:21:03.110 ⇒ 00:21:05.209 Uttam Kumaran: in terms of sunsetting other stuff?
140 00:21:05.480 ⇒ 00:21:20.339 Uttam Kumaran: I sort of think about them separately. I think the sun setting and stuff we can totally do. I don’t know how much of an impact that’s gonna have on like this. This sort of looker. This sort of is tableau the right thing. Can we get it paid for the next 2 weeks?
141 00:21:20.871 ⇒ 00:21:24.959 Uttam Kumaran: So I’m gonna split. I’ll split these 2 up into tickets for these 2.
142 00:21:25.458 ⇒ 00:21:31.690 Uttam Kumaran: Do you guys feel good about like getting some version of this this week and tableau.
143 00:21:33.160 ⇒ 00:21:33.690 Bo Yoon: Yeah.
144 00:21:34.860 ⇒ 00:21:35.290 Sahana Asokan: Yeah.
145 00:21:35.290 ⇒ 00:21:46.539 Robert Tseng: There are tickets already here. For for I mean I didn’t. I didn’t link them. But this is just like the high level. This is what phase one looks like, and then there are tickets for each of these dashboards.
146 00:21:46.790 ⇒ 00:21:49.790 Uttam Kumaran: Okay. Okay. Then I’ll find them and just make sure they’re here. Okay, great.
147 00:21:49.790 ⇒ 00:21:50.350 Robert Tseng: Yeah.
148 00:21:51.490 ⇒ 00:21:52.370 Uttam Kumaran: Okay, cool.
149 00:21:53.186 ⇒ 00:22:04.540 Uttam Kumaran: Okay. I feel good. I I don’t see a wish on here, but I’m gonna push the Zendesk thing forward in terms of Zendesk. There was conversation about not having
150 00:22:04.910 ⇒ 00:22:07.519 Uttam Kumaran: Api keys last time.
151 00:22:07.520 ⇒ 00:22:20.150 Robert Tseng: I think I think away she was just like I mean that that’s already handled. But then he said that he didn’t see any like portable doesn’t support it, or something. I don’t know what he said in the thread, but it looked like we were blocked by whatever connector he was looking at.
152 00:22:20.150 ⇒ 00:22:24.870 Uttam Kumaran: Okay. But we did get Api keys from, or admin thing from somebody right?
153 00:22:24.870 ⇒ 00:22:27.179 Robert Tseng: Yeah, it’s in. It’s in. It’s in one pass.
154 00:22:30.540 ⇒ 00:22:34.270 Uttam Kumaran: Oh, okay, yeah, alright cool. I see what he, I see what the problem was. Yeah, I’ll
155 00:22:35.250 ⇒ 00:22:44.040 Uttam Kumaran: I’ll get that pushed. Okay. Cool Robert, anything else on even I mean, we have.
156 00:22:44.050 ⇒ 00:22:47.578 Robert Tseng: Yeah, couple couple of things in the plan. Section,
157 00:22:48.800 ⇒ 00:23:05.689 Robert Tseng: and yeah, for the Geo lift. Bo. I want to make that recommendation this week. I want to tell them to to start that experiment. So for you like between the dashboard and getting this Geolift test going. I think last week I asked. Just like for, like a clear like.
158 00:23:05.790 ⇒ 00:23:31.290 Robert Tseng: Hey, we want you to turn off these campaigns for how long? And then we kinda we can send them this this readout if they want to go and understand what we’re trying to do. But I’m I imagine people will freak out when we say it, but we just need to make sure that it’s you know, if we we can, if we have a if we have good documentation for it like I think the execs will buy in, even if the rest of the marketing team freaks out.
159 00:23:32.760 ⇒ 00:23:48.289 Bo Yoon: Okay, I mean, I I wrote down the options in another ticket. But however, for the Geo leaf test we still need the locations to pick out the regions to conduct the testing we I can. I can’t pick out the regions unless we have location data.
160 00:23:50.451 ⇒ 00:23:57.830 Robert Tseng: I thought we were applying the similar method to the incrementality thing where we’re trying to.
161 00:23:58.060 ⇒ 00:24:02.549 Robert Tseng: Am I conflating them? Aren’t those 2 separate are those 2 separate things?
162 00:24:04.460 ⇒ 00:24:18.509 Robert Tseng: we have the Geo lift which requires location. But then we’re also trying to look do like a causality analysis. For, like the UN for like branded campaigns, right? Because right now, with what you had demonstrated, with
163 00:24:18.996 ⇒ 00:24:24.219 Robert Tseng: kind of the what what he you know all all we all we saw was like
164 00:24:24.550 ⇒ 00:24:32.580 Robert Tseng: strong correlation between spend and like product revenue, right? And so we were trying to do like a specific
165 00:24:32.790 ⇒ 00:24:35.399 Robert Tseng: test for branded search campaigns.
166 00:24:37.130 ⇒ 00:24:39.989 Bo Yoon: Specific tasks for for Brandison.
167 00:24:40.910 ⇒ 00:24:41.770 Bo Yoon: I don’t.
168 00:24:44.530 ⇒ 00:24:55.880 Bo Yoon: I don’t think that will be something that we can do unless we have when hmm!
169 00:24:58.160 ⇒ 00:25:03.819 Bo Yoon: No, i i i thought we were doing the Geo Leaf test separately. For these I
170 00:25:04.280 ⇒ 00:25:06.240 Bo Yoon: to do the the call
171 00:25:06.520 ⇒ 00:25:13.400 Bo Yoon: causal effect analysis on the on the brand search. I will still need the the locations.
172 00:25:13.720 ⇒ 00:25:15.959 Robert Tseng: Okay? Yeah. So it’s still a deal with, okay?
173 00:25:15.960 ⇒ 00:25:16.920 Bo Yoon: Yeah.
174 00:25:16.920 ⇒ 00:25:20.599 Robert Tseng: Yeah. That’s why I updated. Okay, you know, that’s that’s why that’s why.
175 00:25:20.600 ⇒ 00:25:24.190 Uttam Kumaran: Is this that incrementality one? Or is there? There’s another one right.
176 00:25:26.181 ⇒ 00:25:32.350 Robert Tseng: No, it’s it’s in a solutions review. Actually, this was like, kind of yeah.
177 00:25:33.030 ⇒ 00:25:44.679 Robert Tseng: So basically, both takeaway was Rob’s method of spreading the ad spend across products was like the best we can do. But I kind of pushed back on it because it’s like, well.
178 00:25:44.880 ⇒ 00:25:59.099 Robert Tseng: it’s not. It’s not. He’s not proving causality here. He’s just saying that. Yeah, wherever we spend our ad dollar, that’s what that’s the product that ends up. We end up getting revenue for, which is true. But that doesn’t really help. I don’t. Yeah, I mean, so I wanted to take it.
179 00:25:59.100 ⇒ 00:26:03.860 Uttam Kumaran: Okay. But this proved this proved that it wasn’t right. Basically.
180 00:26:03.860 ⇒ 00:26:07.610 Robert Tseng: So this this proved that. Well.
181 00:26:07.610 ⇒ 00:26:08.320 Uttam Kumaran: Yes, you can hear.
182 00:26:08.320 ⇒ 00:26:16.529 Robert Tseng: Different ways. But I think it. It does show that that Rob’s previous method was
183 00:26:16.910 ⇒ 00:26:36.849 Robert Tseng: the best that we can do right now, but that I don’t want to go back and just say we’re just going to go back to Rob’s methodology, because I do think that we can push this a bit further and prove causality for the Brand search campaigns. If we, you know, run the Geo lift test. And yeah, like, I don’t want to just go back and do the same thing that Rob did.
184 00:26:37.750 ⇒ 00:26:42.459 Uttam Kumaran: But the thing Rob did it. This is still we’re talking about the Utm stuff right.
185 00:26:42.980 ⇒ 00:26:47.919 Robert Tseng: No, no, this is just we’re not. This is not using utms. This is just
186 00:26:49.270 ⇒ 00:26:53.739 Robert Tseng: allocate spend that’s uncategorized. And it’s like, well.
187 00:26:53.860 ⇒ 00:26:58.119 Robert Tseng: yeah, and and yeah, so that’s he’s trying to link it to product revenue. And yeah.
188 00:26:58.190 ⇒ 00:27:03.499 Uttam Kumaran: Great. Okay, I see. So then tell me, what’s what? What’s what is this location problem?
189 00:27:04.390 ⇒ 00:27:15.719 Robert Tseng: Well, he needs like location data at the order level, which I don’t think we accurately have from bask. We need it through shippo but the ship data and the bask data is not like.
190 00:27:15.900 ⇒ 00:27:17.129 Robert Tseng: I mean, we’re we’re
191 00:27:17.500 ⇒ 00:27:28.809 Robert Tseng: every ship, oh, transact or order, or whatever should be tied to a bask order. But we don’t have a data model where shipbo location data is available. At the order level.
192 00:27:30.111 ⇒ 00:27:32.859 Uttam Kumaran: You need a shipments. Okay. Is there a thing for that or no?
193 00:27:35.140 ⇒ 00:27:36.509 Robert Tseng: No, there’s no ticket for that.
194 00:27:36.510 ⇒ 00:27:37.060 Uttam Kumaran: Cool.
195 00:27:37.370 ⇒ 00:27:40.470 Uttam Kumaran: Okay, great, nice. Alright. Let me.
196 00:27:45.190 ⇒ 00:27:54.630 Uttam Kumaran: can I ask a few questions on this? So one can orders have multiple?
197 00:27:54.940 ⇒ 00:27:58.190 Uttam Kumaran: Can one order, have multiple shipments. Yes, right?
198 00:28:02.240 ⇒ 00:28:03.570 Robert Tseng: likely not.
199 00:28:04.500 ⇒ 00:28:05.500 Uttam Kumaran: Okay. Cool.
200 00:28:05.840 ⇒ 00:28:06.470 Robert Tseng: Yeah.
201 00:28:07.610 ⇒ 00:28:26.540 Robert Tseng: because the order, right, the order transaction model. One transaction can be for multiple orders. But then the orders will be shipped out at separate times, if it’s monthly quarterly, 6 months, or whatever. So every order should just have one shipment. But I’m not entirely sure. I think
202 00:28:26.870 ⇒ 00:28:37.389 Robert Tseng: I don’t. I don’t know what the gap is on. Why, vast data is not enough. I don’t haven’t looked into too much detail, but I think when I had originally looked into it.
203 00:28:38.300 ⇒ 00:28:44.160 Robert Tseng: Why, I mean, both probably would know like, why he wasn’t able to get the location data so far right.
204 00:28:44.609 ⇒ 00:28:48.650 Sahana Asokan: I will also say this ticket is relevant to
205 00:28:50.250 ⇒ 00:28:58.279 Sahana Asokan: The Basque data needs that both pharmacy and customer experience wanted for like understanding a transactions
206 00:28:58.440 ⇒ 00:29:00.469 Sahana Asokan: like journey over time.
207 00:29:00.580 ⇒ 00:29:08.960 Sahana Asokan: so I might. I don’t know if it would be helpful for me to look into it, too, but I just realized. It’s also something I’m going to need.
208 00:29:09.700 ⇒ 00:29:12.329 Uttam Kumaran: I’m gonna try to get shipments in there
209 00:29:13.130 ⇒ 00:29:18.319 Uttam Kumaran: at the shipment, all the address information tied to an order, and we’ll start using.
210 00:29:18.320 ⇒ 00:29:25.619 Robert Tseng: We only have order statuses to Sohana’s point up to the point that it’s shipped
211 00:29:26.860 ⇒ 00:29:38.959 Robert Tseng: to the where it’s sent to the pharmacy. After that it’s dependent on 3rd party data that’s not bask and that that’s the part of the order journey that’s like. Not
212 00:29:39.540 ⇒ 00:29:43.100 Robert Tseng: that we don’t really have visibility into without Chippo.
213 00:29:48.130 ⇒ 00:29:48.790 Uttam Kumaran: Right
214 00:29:52.810 ⇒ 00:29:56.710 Uttam Kumaran: awesome. Great cool.
215 00:29:57.480 ⇒ 00:30:00.939 Uttam Kumaran: There are a bunch of other items here.
216 00:30:02.066 ⇒ 00:30:04.640 Uttam Kumaran: I know these are on pause for tableau work.
217 00:30:05.950 ⇒ 00:30:07.620 Uttam Kumaran: Does this look like.
218 00:30:07.820 ⇒ 00:30:20.350 Uttam Kumaran: I think the only things I’m gonna speak with. Away, Shawn. We’re gonna move Zendesk forward gonna move shipments forward. And we’re gonna talk this week about what the product, what the overall data model is gonna be for the warehouse
219 00:30:21.034 ⇒ 00:30:23.470 Uttam Kumaran: and then we’re just gonna start to, basically.
220 00:30:24.780 ⇒ 00:30:44.509 Uttam Kumaran: we’re gonna need to have a plan around the bi tools about one which dashboards we’re gonna sunset. And then which ones we want to do 2 things to do. We wanna consolidate? Or do we wanna move to our march model? So I think we’re gonna sort of look at all the active connections and sort of plan out like a migration plan there.
221 00:30:44.980 ⇒ 00:30:50.610 Uttam Kumaran: basically moving from Rob’s models to ours that live in Prod Mart’s.
222 00:30:50.870 ⇒ 00:30:53.629 Uttam Kumaran: So I wish we’ll we’ll sort of meet and talk about that today.
223 00:30:55.610 ⇒ 00:30:56.220 Awaish Kumar: Sure.
224 00:30:57.060 ⇒ 00:31:00.510 Uttam Kumaran: Cool, anything else.
225 00:31:03.210 ⇒ 00:31:11.730 Robert Tseng: Yeah, I mean, any anything strategy or Hipaa related that I’m tagged on. Don’t worry about it. It’s just I have to do some stuff to keep moving those forward.
226 00:31:12.480 ⇒ 00:31:13.280 Robert Tseng: Yeah.
227 00:31:15.390 ⇒ 00:31:20.360 Uttam Kumaran: Okay, let’s talk about. What else are we gonna talk about pool parts?
228 00:31:21.536 ⇒ 00:31:23.570 Uttam Kumaran: Let me just look through.
229 00:31:27.280 ⇒ 00:31:30.060 Uttam Kumaran: Yes. So let’s go to pool parts.
230 00:31:31.030 ⇒ 00:31:36.827 Uttam Kumaran: And this is good. We’re gonna sort of we’re building from the Bi side we’re building, from the modeling side. And I think we’ll try to
231 00:31:37.540 ⇒ 00:31:41.800 Uttam Kumaran: how to meet in the middle and and just get the March model all set up this week.
232 00:31:42.880 ⇒ 00:31:49.070 Uttam Kumaran: Yeah, I guess for the cool parts, guys, I guess. Nico, tell me where we’re at with
233 00:31:49.800 ⇒ 00:31:50.850 Uttam Kumaran: with stuff.
234 00:31:51.970 ⇒ 00:32:05.979 Nicolas Sucari: So we met with Dan last week with Bo and pay us, and we discussed about next steps about this queue and all this stuff we are moving our focus on to more Asia connection
235 00:32:06.110 ⇒ 00:32:18.370 Nicolas Sucari: data. And we’re trying to focus more on customer level from Asia connection. So we are starting to there. There is a task there that both created Asia purchase data, exploration Q. And a.
236 00:32:19.080 ⇒ 00:32:20.130 Uttam Kumaran: You can check.
237 00:32:20.270 ⇒ 00:32:20.660 Uttam Kumaran: Yes.
238 00:32:20.900 ⇒ 00:32:38.609 Nicolas Sucari: Yeah, okay, so actually, that’s the only active stuff that we have right now, everything else regarding skew. We already closed that we shared that with Dan and and Ian, and yeah, we need to look deep into the purchase details that we file that we get from Ian trying to understand, and and toggle a little bit
239 00:32:39.108 ⇒ 00:32:49.059 Nicolas Sucari: like the cost that we have per skew, because there is no an exact way to assign the costs there to each skew. So we’ll need to
240 00:32:49.080 ⇒ 00:33:00.179 Nicolas Sucari: like to work on some logic. We met with Payas and Bo. We tried to discuss that, and we have some questions for for them. We’ll send the email today and we are waiting for the response. And ideally, we’ll
241 00:33:00.180 ⇒ 00:33:20.230 Nicolas Sucari: get another touch point with them this week so that we can keep discussing that. Okay, apart from this queue stuff, we don’t have anything else ongoing. We should be able to start working on real related stuff. If you want to try exploring the canvas feature and try to like, improve the dashboards that we have there. If you want.
242 00:33:20.910 ⇒ 00:33:21.530 Uttam Kumaran: Okay? Great.
243 00:33:23.390 ⇒ 00:33:25.180 Uttam Kumaran: Yeah. That’s this one. Okay. Great.
244 00:33:25.730 ⇒ 00:33:48.440 Nicolas Sucari: The the other thing that we have there is the doc that pay us created on the 2 weeks prints to explore new projects. We shared that with them. We didn’t hit. We didn’t heard anything about that yet, but we should be yeah, maybe we should like ask them, or, yeah, send some projects that we can.
245 00:33:48.440 ⇒ 00:33:55.370 Uttam Kumaran: There’s no way they’re gonna spend any time on this without exactly exactly without us in the meeting. Yeah.
246 00:33:56.180 ⇒ 00:34:01.279 Uttam Kumaran: And and honestly, I thought we talked about having me give us the ideas for this.
247 00:34:02.040 ⇒ 00:34:04.230 Uttam Kumaran: Yeah, yeah, that’s why that’s what I’m saying. We
248 00:34:04.476 ⇒ 00:34:06.199 Uttam Kumaran: gonna say, you guys already know everything.
249 00:34:06.650 ⇒ 00:34:12.359 Nicolas Sucari: Yeah, that’s that’s what I’m saying. We already shared these dogs like sharing with them that we are. Gonna start this process
250 00:34:13.060 ⇒ 00:34:18.679 Nicolas Sucari: discuss internally which projects should we start moving into this process.
251 00:34:19.500 ⇒ 00:34:25.390 Uttam Kumaran: Okay. I mean, my calendar is up to date. So grab time with me, I’m ready to talk about this.
252 00:34:26.120 ⇒ 00:34:28.830 Nicolas Sucari: Okay. I don’t know if Payaz is here. But yeah, okay, let’s do that.
253 00:34:28.830 ⇒ 00:34:30.860 Payas Parab (TikTok): I’m here. Yeah, I I could throw time on.
254 00:34:31.020 ⇒ 00:34:36.069 Uttam Kumaran: Cool, please. Yeah, I’ll I’ll brain dump. And I like this format.
255 00:34:36.699 ⇒ 00:34:44.169 Uttam Kumaran: and yeah, ideally, let’s come up with 2. Let’s come up with like, I’ll give you like maybe 2 to 4 ideas.
256 00:34:44.500 ⇒ 00:34:49.779 Uttam Kumaran: I’ll give my sense of priority. We can send it to them, or when we meet with them. Be like we’re going after this.
257 00:34:50.060 ⇒ 00:34:52.370 Uttam Kumaran: Get a yes, and then
258 00:34:52.739 ⇒ 00:35:04.390 Uttam Kumaran: we’ll go. Ben will also help. Once we get 2 to 4 of these, I’ll shoot it to Ben with like sort of like one or 2 line explanation, Nico, of like what this is and like what our thoughts are, he’ll be like
259 00:35:04.720 ⇒ 00:35:14.499 Uttam Kumaran: that’s that. Don’t worry about that. Try this. Try this. So that’s what we’ll get to. If we get to this by Wednesday. I would love to start to try to try to get something over.
260 00:35:15.590 ⇒ 00:35:21.320 Nicolas Sucari: Okay, yeah. And on this queue stuff, Bo, I think I said everything. But if you need to add something, let me know.
261 00:35:23.070 ⇒ 00:35:27.103 Uttam Kumaran: Yeah. So we sent this email to them, like, are we?
262 00:35:27.750 ⇒ 00:35:32.199 Uttam Kumaran: we’re just gonna wait for a response. But is it? Who’s on the hook for this like, is it, Ian?
263 00:35:34.410 ⇒ 00:35:48.840 Nicolas Sucari: So it’s Dan. Dan is our main, our main point of contact here. And yeah, with Ian, we just met once. He provided those files and explained a little bit, but we I’m not sure if we are able to meet with him like free more frequently, or we should ask Dan that.
264 00:35:50.550 ⇒ 00:35:51.170 Uttam Kumaran: Okay.
265 00:35:51.490 ⇒ 00:35:52.780 Uttam Kumaran: Okay. Yeah.
266 00:35:52.780 ⇒ 00:36:05.779 Payas Parab (TikTok): We, Nico? We cleared up some of the like accounting nuance, and there might be more. But I think it’s like actually just understanding their business model and the business entities and their relations is like more of Dan questions than they are Ian questions.
267 00:36:05.780 ⇒ 00:36:08.150 Payas Parab (TikTok): If we ran some of the accounting stuff.
268 00:36:08.970 ⇒ 00:36:15.659 Uttam Kumaran: So he’s he’s definitely not gonna respond to that email with like of everything we need. So just ask. So just put an hour.
269 00:36:15.890 ⇒ 00:36:18.439 Uttam Kumaran: Oh, yeah, okay, just do that
270 00:36:18.610 ⇒ 00:36:23.140 Uttam Kumaran: like that meeting that we had. La, you guys had last week. We want those to go like that.
271 00:36:23.320 ⇒ 00:36:33.250 Uttam Kumaran: Dan is the CEO of the company. And we are a much smaller company, and I wouldn’t. I couldn’t. There’s no way I would even respond to that, so we we should just bet time with him.
272 00:36:33.900 ⇒ 00:36:34.580 Uttam Kumaran: Yeah.
273 00:36:34.580 ⇒ 00:36:40.750 Uttam Kumaran: and that’ll be good, like. The more facetime we get the better this whole project will go. So see if we can. Just.
274 00:36:40.870 ⇒ 00:36:43.159 Uttam Kumaran: I wouldn’t put a weekly on, but just like
275 00:36:43.860 ⇒ 00:36:51.710 Uttam Kumaran: keep trying to hit him and get him on meetings like that’s it. You’ll come, spend time with us. He’ll give us all the answers that’ll make our demo process way easier.
276 00:36:51.840 ⇒ 00:36:58.139 Uttam Kumaran: Right? I feel like for this sort of client. It’s gonna be a lot less, Async. It’s gonna be more just like trying to get them on the on the loop.
277 00:36:58.830 ⇒ 00:36:59.450 Nicolas Sucari: Okay.
278 00:37:01.420 ⇒ 00:37:05.659 Uttam Kumaran: And then our helper. I know we pause so. Nothing there. Is there anything else across
279 00:37:07.150 ⇒ 00:37:22.530 Uttam Kumaran: Eden or pool parts that we talked about on the Eden side. Yeah, I want to start to build at least an like a 2 weeks worth of roadmap. There we have a lot of stuff on the march. We have a lot of stuff on new dashboard creation.
280 00:37:24.060 ⇒ 00:37:29.749 Uttam Kumaran: I will kind of, I think, throughout the week I’ll sort of give you give my sort of hypothesis on like
281 00:37:29.930 ⇒ 00:37:31.710 Uttam Kumaran: what’s worth biting off.
282 00:37:31.870 ⇒ 00:37:36.859 Uttam Kumaran: I feel like we are doing a lot for them, including thinking about migrating bi tool
283 00:37:37.710 ⇒ 00:37:41.339 Uttam Kumaran: it may be my gut instinct is that it’s too much.
284 00:37:41.870 ⇒ 00:37:44.530 Uttam Kumaran: but I can. I’ll kind of have a better sense by Wednesday.
285 00:37:47.240 ⇒ 00:37:49.720 Uttam Kumaran: But anything else we want to discuss in this meeting.
286 00:37:52.260 ⇒ 00:37:59.799 Nicolas Sucari: No, just for pull parts the real stuff with them. I don’t know if we wanna like, I can create a task and explore a little bit on that canvas feature, but.
287 00:37:59.800 ⇒ 00:38:06.129 Uttam Kumaran: Yeah, I see that right here. I think this one I’ll just take because I’m gonna go through and do these for all of our existing real clients. So.
288 00:38:06.810 ⇒ 00:38:07.400 Nicolas Sucari: Okay.
289 00:38:12.290 ⇒ 00:38:13.550 Uttam Kumaran: Okay. Great.
290 00:38:13.550 ⇒ 00:38:14.179 Nicolas Sucari: That’s it.
291 00:38:14.650 ⇒ 00:38:20.210 Uttam Kumaran: Thanks, guys, please slack me if if anything else, and then I’ll make sure. All the tickets we talked about are up to date.
292 00:38:22.250 ⇒ 00:38:23.060 Nicolas Sucari: Thanks, for time.
293 00:38:23.210 ⇒ 00:38:24.310 Caio: Bye, bye, guys.
294 00:38:24.670 ⇒ 00:38:25.190 Uttam Kumaran: Nice one.
295 00:38:25.670 ⇒ 00:38:26.360 Bo Yoon: Thank you.