Meeting Title: [Javvy] Daily Standup Date: 2025-04-14 Meeting participants: Aakash Tandel, Annie Yu, Robert Tseng, Awaish Kumar, Caio Velasco
WEBVTT
1 00:00:30.600 ⇒ 00:00:31.560 Aakash Tandel: Hey, guys, how’s it going.
2 00:00:34.067 ⇒ 00:00:35.020 Caio Velasco: How’s it going.
3 00:00:37.280 ⇒ 00:00:38.190 Robert Tseng: Hello!
4 00:00:39.100 ⇒ 00:00:41.320 Aakash Tandel: Robert, are you back in New York, or.
5 00:00:41.320 ⇒ 00:00:43.860 Robert Tseng: Nope, I’m in Austin. We have a
6 00:00:44.040 ⇒ 00:00:48.879 Robert Tseng: we have a conference tomorrow. So the
7 00:00:49.900 ⇒ 00:00:52.069 Robert Tseng: I’m I’m at Utam’s place now.
8 00:00:52.420 ⇒ 00:00:53.080 Aakash Tandel: Nice.
9 00:00:53.840 ⇒ 00:00:54.440 Robert Tseng: Yeah.
10 00:00:54.600 ⇒ 00:00:57.168 Aakash Tandel: Just hopping around all the all the houses.
11 00:00:57.490 ⇒ 00:01:02.206 Robert Tseng: Yeah, no, I’m I’m a bit homesick. I’m ready to go home.
12 00:01:03.020 ⇒ 00:01:11.150 Aakash Tandel: Get that cool. We’ll give Andy no wish another minute, but.
13 00:01:18.340 ⇒ 00:01:19.620 Annie Yu: Hello! Everyone.
14 00:01:20.050 ⇒ 00:01:21.029 Aakash Tandel: Hey, Eddie, how’s it going.
15 00:01:21.030 ⇒ 00:01:21.630 Robert Tseng: Any.
16 00:01:26.760 ⇒ 00:01:31.739 Aakash Tandel: Yeah, we’ll give a wish another minute or so just so we can kind of go through this
17 00:01:31.860 ⇒ 00:01:33.420 Aakash Tandel: list.
18 00:01:35.830 ⇒ 00:01:38.155 Aakash Tandel: There he is. Yeah. So
19 00:01:39.210 ⇒ 00:02:00.058 Aakash Tandel: we’re gonna be kind of just talking through the roadmap that we had kind of promised to joby. That’s gonna end this week. So as you kind of saw in the slack channel. Robert had put a basically a notion document that he’s gonna walk them on through next or tomorrow, I guess so we will have
20 00:02:00.400 ⇒ 00:02:09.400 Aakash Tandel: theoretically new work coming down the pipe once that contract gets renewed. But this is kind of the stuff that we want to make sure we’re closing out at least
21 00:02:09.620 ⇒ 00:02:20.566 Aakash Tandel: for the end of this week. So that’s the main goal we wanna make sure all these are, you know, through the finish line and we’ll start from there.
22 00:02:21.880 ⇒ 00:02:30.965 Aakash Tandel: oh, I know that the incremental refresh is basically ready to go. I’m haven’t heard back from Mon on whether or not he wants to do that.
23 00:02:34.870 ⇒ 00:02:43.220 Aakash Tandel: Did you get any information from the portable team on how much it was gonna cost. I feel like he might ask that question, but I don’t know.
24 00:02:43.910 ⇒ 00:02:49.679 Awaish Kumar: I don’t know like I I missed them on slack, and they haven’t replied yet.
25 00:02:50.300 ⇒ 00:02:51.100 Aakash Tandel: Okay.
26 00:02:51.648 ⇒ 00:03:03.339 Aakash Tandel: that’s fine. We will wait a second, but it sounds like that’s ready to go. If they do want to go forward with those refreshes. Is it simply like you just have to like flip a switch? Basically, it’s fairly straightforward.
27 00:03:05.711 ⇒ 00:03:10.318 Awaish Kumar: Yeah, like the incremental. Actually, right? Now, I have
28 00:03:11.690 ⇒ 00:03:19.209 Awaish Kumar: scheduled almost all the connectors and except the one sheet, because the current plan
29 00:03:19.380 ⇒ 00:03:22.740 Awaish Kumar: doesn’t allow us, like we don’t have enough
30 00:03:23.567 ⇒ 00:03:37.919 Awaish Kumar: connectors to schedule. So yeah, except one sheet. Every everything is scheduled right now. But if any time. Aman says, okay, we want to have sheets on manual or something. We can move back very quickly.
31 00:03:38.260 ⇒ 00:03:41.839 Aakash Tandel: Okay, yeah. And I know that the
32 00:03:42.100 ⇒ 00:03:52.119 Aakash Tandel: we can turn these refreshes on. But the Dbt modeling would need to happen. So that’s not really included in this. Yet? Which I think is fine. Is that correct?
33 00:03:54.065 ⇒ 00:03:54.570 Awaish Kumar: Yes.
34 00:03:54.870 ⇒ 00:03:59.483 Aakash Tandel: Okay, alright, that makes sense. Okay, cool. So that sounds good.
35 00:04:00.410 ⇒ 00:04:30.170 Aakash Tandel: Witham said, he’s going to be working on the data training stuff. So the videos for vlad, so that sounds good. I think it might be worth all of us to like watch that at 2 xp. Just so we have like better knowledge of I mean away. She probably have a lot of contextual knowledge already. You probably don’t need it, Robert. You obviously don’t need it but for me, Annie and Kai, who have done the project a little bit shorter. I think it might be good for us to watch those. So once he does that I will circulate those in
36 00:04:30.170 ⇒ 00:04:32.150 Aakash Tandel: provide slack so we can do that.
37 00:04:34.398 ⇒ 00:04:37.822 Aakash Tandel: Cool. So I think that kind of leaves.
38 00:04:38.520 ⇒ 00:04:51.790 Aakash Tandel: this is like the same thing as the other one. That kind of leaves our 3 dashboards that we’re working on. Those are klaviyo attentive. And then north beam. I know those are in various stages of
39 00:04:52.382 ⇒ 00:04:55.680 Aakash Tandel: like completion, for at least v 1
40 00:04:55.950 ⇒ 00:04:58.070 Aakash Tandel: Do we want to start with?
41 00:04:58.310 ⇒ 00:05:01.800 Aakash Tandel: Attentive, I know, is probably the furthest along. Is that correct? Danny?
42 00:05:04.116 ⇒ 00:05:10.919 Annie Yu: I would say the I can you clarify which one is the klaviyo? One.
43 00:05:11.160 ⇒ 00:05:13.151 Aakash Tandel: Yeah. The Klavia one is
44 00:05:13.840 ⇒ 00:05:16.120 Aakash Tandel: I don’t think we have.
45 00:05:16.370 ⇒ 00:05:24.259 Aakash Tandel: I think it’s just been Kyle. You’ve been working on the modeling of that one. I think the actual hold on it’s not the right ticket
46 00:05:30.188 ⇒ 00:05:33.679 Aakash Tandel: I think this is the one that’s probably the least moved on because.
47 00:05:33.680 ⇒ 00:05:34.500 Annie Yu: Yeah, yeah.
48 00:05:35.288 ⇒ 00:05:46.715 Aakash Tandel: I think we’re Kyle, I know you did the modeling for this. So hopefully, we can answer kind of these basic questions with the version, one
49 00:05:52.120 ⇒ 00:06:01.170 Aakash Tandel: ticket. But yeah, this is kind of probably the one that’s next up. But I know it’s probably the least visualized so far in metase.
50 00:06:01.370 ⇒ 00:06:04.620 Annie Yu: Okay, yeah. And then back to the
51 00:06:09.600 ⇒ 00:06:13.310 Annie Yu: attentive one. That one, I think
52 00:06:13.630 ⇒ 00:06:22.630 Annie Yu: I just really just now sent some notes about the model adjustments needed.
53 00:06:23.100 ⇒ 00:06:32.609 Annie Yu: And one thing I would say that has to be done is convert message id from numeric to
54 00:06:33.040 ⇒ 00:06:40.979 Annie Yu: variable character, because right now I can’t do like light charts with with that being numeric.
55 00:06:41.920 ⇒ 00:06:46.960 Annie Yu: And yeah, yep, that one.
56 00:06:48.030 ⇒ 00:06:51.839 Annie Yu: And then there are 2 other things I know that
57 00:06:52.280 ⇒ 00:06:54.071 Annie Yu: I think you mentioned that.
58 00:06:54.760 ⇒ 00:07:22.120 Annie Yu: I think. First, st we wanted to see okay, like revenue or orders within 5 days of a sent date. And with that we can do with our current state of the data. But if we want flexibility, if we want people to be able to filter on, we want to see 7 days or 10 days after a sent date, I will need a new column that could be like days to order to support that filtering. But if we are okay with sticking with 5 day. I think we can.
59 00:07:22.380 ⇒ 00:07:24.229 Annie Yu: We can skip that.
60 00:07:24.850 ⇒ 00:07:38.570 Annie Yu: And then another question here would be, I cause just looking at message Id. I don’t know what text is there, and I think this is a question, probably, for, like your client, do we want to show message
61 00:07:38.750 ⇒ 00:07:42.909 Annie Yu: content for them to reference, which message is
62 00:07:43.390 ⇒ 00:08:01.350 Annie Yu: like, which message, id and if so, we probably have to clean that message text by removing some personalized info, because here we have that same Id, but there’s different names. So we see all the different text contents.
63 00:08:02.190 ⇒ 00:08:05.683 Aakash Tandel: Yeah, that makes sense. Yeah, I think.
64 00:08:08.850 ⇒ 00:08:15.268 Aakash Tandel: yeah, cause the only the only difference here is gonna be the little hey name, basically.
65 00:08:15.955 ⇒ 00:08:16.240 Annie Yu: Yeah.
66 00:08:16.440 ⇒ 00:08:20.540 Aakash Tandel: I think, including message. Id makes sense, and then
67 00:08:20.900 ⇒ 00:08:41.720 Aakash Tandel: we’ll have a table of unique message, id example message like the first.st Maybe the 1st example. Message, does that make sense so like, if the message Id is this one, we just show a table at the bottom. That’s like, Hey, this 1st row and then, if it’s unique, a different message it’ll have like an example. One second row.
68 00:08:42.970 ⇒ 00:08:43.970 Annie Yu: Okay.
69 00:08:47.850 ⇒ 00:08:53.049 Awaish Kumar: Yeah. And in this table is the message, Id is not a primary key for this table.
70 00:08:54.620 ⇒ 00:09:04.869 Awaish Kumar: message. Id is associated with a specific text which is sent file by Javi. And the same text can be sent to like
71 00:09:05.150 ⇒ 00:09:10.559 Awaish Kumar: thousands of people, and that those all messages have same message. Id.
72 00:09:11.480 ⇒ 00:09:12.159 Aakash Tandel: Make sense.
73 00:09:13.010 ⇒ 00:09:15.590 Aakash Tandel: Yeah. So I think if we can do like a unique
74 00:09:16.183 ⇒ 00:09:43.800 Aakash Tandel: like a table that just looks at the unique message ids. And one message text like, maybe the 1st or last, or a random one doesn’t matter. I think that would be good. Just so they know what they’re looking at and I wouldn’t. I wouldn’t really worry about the pii here like the these names. Because they’re just gonna be their 1st name and also within metabase. I think we can. We can have Pii. I don’t think there’s a problem there. We’re not using it in
75 00:09:44.163 ⇒ 00:09:49.329 Aakash Tandel: ad campaigns and stuff like that by a meta base. I think it should be fine.
76 00:09:50.360 ⇒ 00:09:57.000 Annie Yu: Okay, and I am not a hundred percent positive. If I can show only one
77 00:09:57.480 ⇒ 00:09:59.538 Annie Yu: cause, it’s a not an
78 00:10:00.610 ⇒ 00:10:20.679 Annie Yu: numeric. I’m not sure if I can show like just min or Max of a text message probably like Robert, would know this. But I will try, and if not, I think I’ll just add, like maybe like a search bar on the top, so they can. Manual manually type in the message. Id.
79 00:10:21.270 ⇒ 00:10:25.629 Aakash Tandel: Okay, yeah. That sounds like a good alternative. Cool. Okay.
80 00:10:25.630 ⇒ 00:10:33.419 Annie Yu: But yeah, we will need to convert that message id from numeric to variable character
81 00:10:33.520 ⇒ 00:10:36.350 Annie Yu: for sure that that one’s needed.
82 00:10:37.900 ⇒ 00:10:47.070 Annie Yu: And then yeah. Yeah. And then the for the second bullet. I think I’ll leave that up to you. If we’re okay with sticking with only 5 days
83 00:10:47.280 ⇒ 00:10:49.250 Annie Yu: we don’t have to change anything.
84 00:10:49.610 ⇒ 00:10:51.305 Aakash Tandel: Okay, yeah.
85 00:10:52.630 ⇒ 00:11:03.649 Aakash Tandel: I think, for now I’ll probably have a ticket in the backlog for us to work on if we have time for stuff. But it won’t be a top priority. Item, I think that’s probably what makes sense. Yeah.
86 00:11:04.050 ⇒ 00:11:06.539 Aakash Tandel: cool. Alright. So I’m gonna write.
87 00:11:10.960 ⇒ 00:11:17.119 Aakash Tandel: You’re right. 2 tickets for add the one and 2.
88 00:11:17.980 ⇒ 00:11:21.139 Aakash Tandel: This item to being
89 00:11:31.100 ⇒ 00:11:37.600 Aakash Tandel: cool. That sounds good. Awesome anything else on attentive.
90 00:11:38.430 ⇒ 00:11:40.069 Annie Yu: I think that’s it.
91 00:11:40.070 ⇒ 00:11:40.690 Aakash Tandel: Awesome.
92 00:11:41.040 ⇒ 00:11:43.620 Annie Yu: And then there is north beam.
93 00:11:43.770 ⇒ 00:11:55.940 Aakash Tandel: Yes, North Main. I know we have a question in the main North. Be ticket to the client.
94 00:12:00.830 ⇒ 00:12:03.779 Awaish Kumar: Okay. So one of the question we got
95 00:12:04.030 ⇒ 00:12:07.700 Awaish Kumar: within in North Grim is that the spend for
96 00:12:08.100 ⇒ 00:12:11.790 Awaish Kumar: concentrate looks odd. And I verified from
97 00:12:12.464 ⇒ 00:12:19.230 Awaish Kumar: on the north wind dashboard, and it does look look look very off
98 00:12:20.021 ⇒ 00:12:23.090 Awaish Kumar: but I haven’t haven’t found the
99 00:12:23.420 ⇒ 00:12:26.950 Awaish Kumar: the solution yet, so I will be working on that today.
100 00:12:27.690 ⇒ 00:12:28.470 Robert Tseng: Yeah, hopefully.
101 00:12:28.470 ⇒ 00:12:36.079 Robert Tseng: The I guess you already took the script. And you said that like we’ve already used it in our north beam modeling. Is that what you said.
102 00:12:37.030 ⇒ 00:12:38.190 Awaish Kumar: Sorry, what.
103 00:12:38.430 ⇒ 00:12:47.049 Robert Tseng: Like I guess, in that ticket, if you scroll up a bit, that is basically a man’s former wait, that is it. Wait not.
104 00:12:49.220 ⇒ 00:12:58.909 Awaish Kumar: Yeah, like in in the date, the data which is coming from, we are using the correct filter. But the data we are getting from North Main is not complete.
105 00:12:59.120 ⇒ 00:13:00.680 Awaish Kumar: That’s the issue.
106 00:13:02.190 ⇒ 00:13:02.700 Robert Tseng: I see.
107 00:13:02.700 ⇒ 00:13:12.699 Awaish Kumar: So we are getting the incomplete data. There is some issue in the configuration or the connector somewhere, so that so we are using the correct
108 00:13:12.850 ⇒ 00:13:25.260 Awaish Kumar: filter. But the the data is not complete, and I’m looking at where we are. We are missing that data like, is it in portable connector? Or is it in Northweam configuration or Api
109 00:13:25.430 ⇒ 00:13:32.249 Awaish Kumar: setting like wherever somewhere there, there is something where we are missing out on some rows?
110 00:13:32.400 ⇒ 00:13:34.640 Awaish Kumar: So yeah, I’m finding out that.
111 00:13:35.210 ⇒ 00:13:36.010 Robert Tseng: Okay.
112 00:13:38.950 ⇒ 00:13:45.940 Aakash Tandel: Okay, that sounds good. So yeah, so you confirm that the data in north beam looks different than the data that we have right now, that’s kind of what your 1st statement was.
113 00:13:45.940 ⇒ 00:13:46.940 Awaish Kumar: Yes, yes.
114 00:13:47.230 ⇒ 00:13:50.705 Aakash Tandel: Okay, cool. Alright. I’m following now. Okay, yeah.
115 00:13:51.700 ⇒ 00:13:58.579 Aakash Tandel: So this is, do we have a ticket outlining your kind of investigation into that?
116 00:14:07.240 ⇒ 00:14:08.829 Aakash Tandel: Is that this one? No.
117 00:14:10.050 ⇒ 00:14:15.020 Awaish Kumar: Yeah, this is the one which is in progress. Yeah. But.
118 00:14:17.530 ⇒ 00:14:18.960 Aakash Tandel: Okay, so this is the thing.
119 00:14:19.610 ⇒ 00:14:24.369 Aakash Tandel: Yeah, okay, alright cool. So I’m gonna say, the other one is
120 00:14:24.770 ⇒ 00:14:30.950 Aakash Tandel: blocked by this one. So I’m gonna say that that ticket?
121 00:14:33.270 ⇒ 00:14:43.180 Aakash Tandel: Okay, blocked by Oasius. Investigation and solution on this.
122 00:14:47.550 ⇒ 00:14:51.430 Aakash Tandel: Okay, this in blocked
123 00:14:51.922 ⇒ 00:14:59.180 Aakash Tandel: how does the rest of the dashboard for north beam. Look, Annie, how have you been able to do most of the other stuff?
124 00:15:00.290 ⇒ 00:15:04.849 Annie Yu: I would say so. But also, it’s really about that. Cag.
125 00:15:05.150 ⇒ 00:15:08.650 Annie Yu: Yeah, so many views have that Cag. And I,
126 00:15:09.090 ⇒ 00:15:13.930 Annie Yu: I think, bef like until we get that validated.
127 00:15:14.130 ⇒ 00:15:17.000 Annie Yu: I think it’s not a great idea to share yet.
128 00:15:17.470 ⇒ 00:15:20.040 Aakash Tandel: Yeah, that’s like the that that.
129 00:15:20.040 ⇒ 00:15:22.848 Annie Yu: That’s the kind of the meat of the dash.
130 00:15:23.160 ⇒ 00:15:27.420 Aakash Tandel: Yeah, okay, that sounds good. Okay.
131 00:15:28.449 ⇒ 00:15:35.730 Aakash Tandel: okay. So that means, so this guy is in progress.
132 00:15:36.140 ⇒ 00:15:39.929 Aakash Tandel: This guy, I’m just gonna put this as red because we just can’t do it.
133 00:15:40.870 ⇒ 00:16:04.570 Aakash Tandel: That’s not not gonna happen. This guy is gonna I’m gonna basically close that one out, close that one out today that one out. And then, yeah. And then, Clayvio, these things, are working. Okay, cool. That sounds good. So yeah, a wish. I think your highest priority item. And now I’m just gonna look at the ticket directly the tickets directly, so that we know what everyone’s working on. Primarily.
134 00:16:04.700 ⇒ 00:16:06.960 Aakash Tandel: let’s do that real quick.
135 00:16:07.662 ⇒ 00:16:14.529 Aakash Tandel: So yeah, this is your, obviously, it’s the only thing in progress. It’s your highest priority for Javi. Let us know
136 00:16:14.850 ⇒ 00:16:17.930 Aakash Tandel: when that happens. And then, yeah, these are
137 00:16:19.230 ⇒ 00:16:25.799 Aakash Tandel: these are ready for development after this. So yeah, we can go to that tomorrow.
138 00:16:27.660 ⇒ 00:16:29.949 Aakash Tandel: let me check Kyle’s
139 00:16:32.560 ⇒ 00:16:41.749 Aakash Tandel: Kyle. This is still in progress annoyingly, because of the clients like that. Are we? I know we decide to move forward with the assumptions. How’s this going.
140 00:16:43.020 ⇒ 00:16:49.520 Caio Velasco: Yeah, I saw it, I guess, last Friday. And then today, I started working on it like, not long ago.
141 00:16:49.994 ⇒ 00:16:58.430 Caio Velasco: So I’m checking. And I already deleted some of the tabs we had on the spreadsheet, because clearly we are not using using those
142 00:16:59.547 ⇒ 00:17:03.960 Caio Velasco: and I I think this is, did you just purchase this or.
143 00:17:04.642 ⇒ 00:17:06.250 Aakash Tandel: This is no.
144 00:17:06.250 ⇒ 00:17:06.660 Caio Velasco: What is it?
145 00:17:06.670 ⇒ 00:17:10.990 Aakash Tandel: 3 days ago, but this is a screenshot from slack, so.
146 00:17:11.560 ⇒ 00:17:22.579 Caio Velasco: So yeah, I’m just working through the models now to see, we can like, just finish the Amazon part, because the shopify is very clear
147 00:17:23.179 ⇒ 00:17:24.979 Caio Velasco: but yeah, I’m I’m on it.
148 00:17:25.500 ⇒ 00:17:55.049 Aakash Tandel: Okay, awesome. I will probably assign the things I just said. I’m gonna make tickets for for Annie, for the turning that one variable into a text field. So maybe we’ll just create another field. That’s like the text version or the bar chart version of that numeric message. Id. I’ll assign that to you. And then I will probably also sign the other thing to you. But that’s obviously not prioritized until I guess this, the current stuff on your on your plate is tackled.
149 00:17:56.670 ⇒ 00:17:58.720 Annie Yu: And then, did you mean me?
150 00:17:59.806 ⇒ 00:18:03.330 Aakash Tandel: No. So I was saying, the yeah. Kyle, yeah.
151 00:18:03.330 ⇒ 00:18:04.420 Annie Yu: Okay. Cool.
152 00:18:04.420 ⇒ 00:18:08.930 Aakash Tandel: Yeah. The the ticket that the where did that guy go?
153 00:18:08.930 ⇒ 00:18:11.419 Annie Yu: Yeah, yeah, yeah, that that one for attentifier.
154 00:18:11.420 ⇒ 00:18:13.454 Aakash Tandel: Yeah, the attendant modeling work I’m assigned to Kyle.
155 00:18:14.190 ⇒ 00:18:14.910 Annie Yu: Cool.
156 00:18:14.910 ⇒ 00:18:15.800 Aakash Tandel: Cool
157 00:18:17.080 ⇒ 00:18:24.189 Aakash Tandel: and I know you have these so that we already talked about this one the lifetimely stuff. I feel like I was, did I miss something I was supposed to do on this.
158 00:18:24.837 ⇒ 00:18:30.209 Annie Yu: No, I think I was gonna outline like the the current state.
159 00:18:31.433 ⇒ 00:18:36.416 Annie Yu: And I think honestly, I think v. 1 is ready. But
160 00:18:37.900 ⇒ 00:18:41.349 Annie Yu: just one thing is that Cac, because I think
161 00:18:42.210 ⇒ 00:18:46.089 Annie Yu: for for this dashboard to be like really effective.
162 00:18:46.530 ⇒ 00:19:00.260 Annie Yu: It would mean that we want to see the Cac versus kind of the customer lifetime value to determine like, how long does it take for a new customer to become profitable? And right now I think we do have that views
163 00:19:00.480 ⇒ 00:19:01.750 Annie Yu: without pack.
164 00:19:01.960 ⇒ 00:19:07.230 Annie Yu: So I I feel like we are.
165 00:19:07.980 ⇒ 00:19:13.759 Annie Yu: I feel like it’s it’s I would say. We can ship the v 1 without Cac.
166 00:19:13.990 ⇒ 00:19:16.210 Annie Yu: So at least people can still see
167 00:19:16.470 ⇒ 00:19:20.710 Annie Yu: how much profit does each cohort generate over time.
168 00:19:25.975 ⇒ 00:19:27.879 Annie Yu: But I will.
169 00:19:28.060 ⇒ 00:19:44.300 Annie Yu: I will add you, and probably Robert, to, because I added some kind of just text notes for some nuances to the dash, and I would love for you to kind of see if the explanations are
170 00:19:44.300 ⇒ 00:19:45.130 Annie Yu: clear.
171 00:19:45.580 ⇒ 00:19:50.450 Robert Tseng: I’ll I can share my screen. Akash so we can actually look at what she’s talking about.
172 00:19:50.450 ⇒ 00:19:52.199 Aakash Tandel: That’s what I was trying to do. I just can’t get into.
173 00:19:52.200 ⇒ 00:19:57.720 Robert Tseng: Yeah, yeah, sorry, Annie. Yeah, I I look, I was looking at this this morning.
174 00:19:58.994 ⇒ 00:20:03.020 Robert Tseng: I mean, I think 1st reaction was just like.
175 00:20:03.510 ⇒ 00:20:11.930 Robert Tseng: I feel like this is okay. I mean, I feel like margins bit seems a bit low. I don’t think it’s low sixties and high fifties.
176 00:20:12.140 ⇒ 00:20:23.269 Robert Tseng: so I don’t know. I haven’t. I haven’t clicked into these calculations yet. But yeah, I mean, I hear you on the Cac thing, and then, sorry. Sorry. What what were you saying before I pulled this up?
177 00:20:24.810 ⇒ 00:20:29.659 Annie Yu: I was just saying would love for you to see those kind of text notes
178 00:20:29.910 ⇒ 00:20:32.490 Annie Yu: up there to see if the
179 00:20:32.870 ⇒ 00:20:38.039 Annie Yu: it’s clear at all. And one thing I know, that awaits built that
180 00:20:38.300 ⇒ 00:20:51.080 Annie Yu: 1st month since months since 1st order label. So the 1st order would be 1st order instead of minus one. But with that, when I sort that
181 00:20:51.280 ⇒ 00:20:56.939 Annie Yu: the 1st month will actually come after all the numbers. So I’m sticking to this minus one.
182 00:20:57.960 ⇒ 00:21:07.139 Robert Tseng: Got it. Yeah, honestly, when I pulled this up with no context, I was a bit confused because I was like, Huh! I have to filter this by previous 13 months, and then or whatever. And then I was like.
183 00:21:07.720 ⇒ 00:21:17.559 Robert Tseng: Okay, so yeah, like I, it wasn’t super clear to me how to use these 2 filters together like, I think I understand what you’re trying to do. But I’m just
184 00:21:17.870 ⇒ 00:21:33.279 Robert Tseng: trying to role play as the person who’s like, I don’t know like they’re some non technical person who’s never seen this. So I guess it’s not super clear to me like kind of how we use these 2 filters together. So if that’s important, I would say, maybe like, make a note of that.
185 00:21:33.720 ⇒ 00:21:42.149 Robert Tseng: I feel like this is not actually happening on the user side. I think it’s a good definition to make. But like we also
186 00:21:45.010 ⇒ 00:21:51.390 Robert Tseng: yeah, maybe we just kind of, we have to separate out these comments as well. It’s kind of some a section that’s more like.
187 00:21:52.000 ⇒ 00:21:59.219 Robert Tseng: yeah, I mean, like the key definitions, assumptions. And then there’s another one that’s like how to use. So I feel like that’s
188 00:21:59.490 ⇒ 00:22:08.870 Robert Tseng: like one part, like the logic the user never touches. But it’s just maybe if they want to understand how it works like it’s there. The other one is. The other section is more. For like
189 00:22:09.220 ⇒ 00:22:18.820 Robert Tseng: this is how you actually use this dashboard and what the steps. You need to take the filter, or whatever. So I feel like that could. If that if you could break it out
190 00:22:19.340 ⇒ 00:22:22.358 Robert Tseng: that way, I think that could be a bit clearer.
191 00:22:23.271 ⇒ 00:22:30.109 Robert Tseng: Yeah, I’m gonna go and kind of double click into these metrics just to make sure that these numbers seem
192 00:22:30.430 ⇒ 00:22:38.030 Robert Tseng: right. Yeah, I think the margin seems a bit off to me. So if margin is a bit lower, then I would I would assume that.
193 00:22:40.180 ⇒ 00:22:47.050 Robert Tseng: yeah, probably these others are impacted as well. So I’ll I’ll just take a look. I have nothing concrete to say about it yet, though.
194 00:22:48.470 ⇒ 00:22:56.440 Annie Yu: Okay, okay, so in the meantime, I will do that kind of 2 separate sections, one about
195 00:22:56.720 ⇒ 00:23:00.619 Annie Yu: how to navigate the stash and filters, and then the other. One is
196 00:23:01.110 ⇒ 00:23:07.319 Annie Yu: probably a little more technical, but like consumption and definition of the metrics.
197 00:23:07.560 ⇒ 00:23:17.200 Robert Tseng: Yeah, maybe it’s like a technical summary to key definitions, assumptions, or something. And then there’s like a how to use section, I guess, open to kind of how you however, you wanna display that so.
198 00:23:17.590 ⇒ 00:23:18.920 Annie Yu: Yeah, yeah.
199 00:23:19.470 ⇒ 00:23:26.010 Robert Tseng: Okay, okay, that’s that.
200 00:23:30.920 ⇒ 00:23:34.839 Aakash Tandel: I can share my screen real quick, but I think that pretty much wraps us for
201 00:23:37.140 ⇒ 00:23:46.069 Aakash Tandel: day. Going back to okay. So this one. I put it as internal feedback. Robert, you’re gonna
202 00:23:46.190 ⇒ 00:23:53.579 Aakash Tandel: look at some stuff, Annie, you’re gonna make some modifications. But it sounds like we can definitely get this out to them. I don’t. It’s not in our.
203 00:23:54.530 ⇒ 00:23:57.249 Aakash Tandel: This is not really in our roadmap. That’s okay. Let’s.
204 00:23:57.630 ⇒ 00:24:09.979 Robert Tseng: Yeah, cause it was like in our last cycle. So I mean they probably I mean, I don’t think they forgot about it. Justin asked about it every every week, but like I’m on probably is just not organized about it.
205 00:24:10.180 ⇒ 00:24:10.760 Aakash Tandel: Okay.
206 00:24:11.299 ⇒ 00:24:17.940 Aakash Tandel: That’s fine. That sounds good. And yeah, I think that’s it for you, Annie. I think that’s your main.
207 00:24:18.690 ⇒ 00:24:23.170 Aakash Tandel: Yep, cool. Okay, yeah. And then I think, once
208 00:24:23.490 ⇒ 00:24:27.720 Aakash Tandel: you make those modifications, I think, getting some sort of
209 00:24:28.430 ⇒ 00:24:40.795 Aakash Tandel: basic information like this here for the v, 1 on play video is going to be the next important thing. Just because we want to get some sort of v 1 over to them by
210 00:24:41.430 ⇒ 00:24:42.619 Aakash Tandel: ended this week.
211 00:24:43.430 ⇒ 00:24:44.110 Annie Yu: Okay.
212 00:24:45.580 ⇒ 00:24:50.560 Aakash Tandel: Cool. Okay? And then actually, I’ll pull up you 2, Robert. Just so we
213 00:24:50.820 ⇒ 00:24:53.340 Aakash Tandel: make sure that you don’t have anything to.
214 00:24:53.940 ⇒ 00:24:55.780 Aakash Tandel: Is this.
215 00:25:01.870 ⇒ 00:25:04.789 Aakash Tandel: This is great. 4 weeks ago. Okay, I’m gonna assume.
216 00:25:05.260 ⇒ 00:25:08.569 Aakash Tandel: Do you know what this is? This seems like it’s a combination of other stuff.
217 00:25:08.570 ⇒ 00:25:11.559 Robert Tseng: Yeah, I we can just get rid of that. I guess
218 00:25:14.370 ⇒ 00:25:20.940 Robert Tseng: that was when we 1st got the request for Amazon. Like cogs stuff. I guess.
219 00:25:21.220 ⇒ 00:25:22.155 Aakash Tandel: Okay,
220 00:25:24.320 ⇒ 00:25:34.689 Aakash Tandel: And I’m doing that. Then to the market, okay, cool. Okay. Does anyone else have anything else for
221 00:25:35.240 ⇒ 00:25:36.140 Aakash Tandel: Big group.
222 00:25:37.080 ⇒ 00:25:43.840 Caio Velasco: I do? So I was checking out the the last tab like the product plus one.
223 00:25:44.060 ⇒ 00:25:48.860 Caio Velasco: And well, the thing Blake updated. And and
224 00:25:49.320 ⇒ 00:26:06.232 Caio Velasco: apparently it’s not the same thing as shopify, but they were basing and copy and pasting the other one. So I was being confused. So for that one since we use it in the calculations in the fact orders table, and then also other tables. Maybe that one has to be brought in to
225 00:26:08.124 ⇒ 00:26:16.149 Caio Velasco: snowflake via portable because we have one for shopify, and then we either have to bring a new one or
226 00:26:16.350 ⇒ 00:26:32.719 Caio Velasco: add to that one then, and for that part I wouldn’t know like if that should be a wish or something, because I’ve never dealt with portable before, or you’ve done, or something, but just for that part, for the other ones, because there are other fields. Those are okay.
227 00:26:33.830 ⇒ 00:26:53.209 Aakash Tandel: Yeah, I think if you can sync up with a wish, if that’s something you can teach to Kyle like how to sync up that via Portable. I think that’d be good for you to learn or if you away want to just record a loom. If it’s that, if that’s easier for you then. That’s also an option. But yeah, I think that would be great if you can like, learn how to do that.
228 00:26:54.580 ⇒ 00:26:59.490 Awaish Kumar: Yeah, like. But what was the issue? Like, I didn’t delegated.
229 00:26:59.490 ⇒ 00:27:06.539 Caio Velasco: Sweet, so that spreadsheet that we have for the cogs fields each tab.
230 00:27:06.540 ⇒ 00:27:06.910 Awaish Kumar: Okay.
231 00:27:07.300 ⇒ 00:27:15.559 Caio Velasco: As a as a raw table in in Via Portable in into Snowflake. So we need to bring a new one, because now we have a new one for housing.
232 00:27:15.750 ⇒ 00:27:17.199 Caio Velasco: for for that part.
233 00:27:17.200 ⇒ 00:27:23.480 Awaish Kumar: Okay, sounds like it’s updating an existing connection to that spreadsheet. And then just
234 00:27:23.809 ⇒ 00:27:29.760 Awaish Kumar: yeah, sure we we do. We have to make new new connectors. Yeah, okay, okay, perfect.
235 00:27:29.760 ⇒ 00:27:31.660 Awaish Kumar: Can think of about that.
236 00:27:33.560 ⇒ 00:27:34.100 Aakash Tandel: Awesome.
237 00:27:34.930 ⇒ 00:27:53.080 Robert Tseng: I have a question, do we know? Like with portable? If it’s multiple Google sheets? I mean, I got, how do they price that like. I mean, they know they do price by single connector. But if you’re pulling from multiple tabs on a Google sheet, does that does that count as the same connector. Is it multiple? I don’t really understand.
238 00:27:53.080 ⇒ 00:27:54.680 Awaish Kumar: It’s a separate connector.
239 00:27:55.350 ⇒ 00:27:56.999 Robert Tseng: So we pay for each one of those.
240 00:27:57.730 ⇒ 00:28:04.510 Awaish Kumar: Yeah, like each sheet is is going like, is syncing the data into an individual table.
241 00:28:05.090 ⇒ 00:28:07.000 Awaish Kumar: So it’s a single connector.
242 00:28:07.280 ⇒ 00:28:15.990 Awaish Kumar: And so like. If if a single sheet has 10 single Google Sheet has 10 different tabs, then we are paying for in every tab.
243 00:28:16.780 ⇒ 00:28:17.910 Robert Tseng: Interesting.
244 00:28:19.880 ⇒ 00:28:27.810 Caio Velasco: Okay. So since we have the same format, we can just put in the other one, maybe, and add the new column to say what is shopify and what is Amazon.
245 00:28:30.090 ⇒ 00:28:39.480 Robert Tseng: Yeah, I mean, this is my dumb question. But like is, is that the price of a tab is the same as like the price of connecting to like Clayview.
246 00:28:44.480 ⇒ 00:28:49.110 Awaish Kumar: I think so, because they they just charge by connectors and
247 00:28:49.670 ⇒ 00:28:55.870 Awaish Kumar: doesn’t care about the data, or how many rows are coming in, or things like that.
248 00:28:55.870 ⇒ 00:28:56.300 Aakash Tandel: Yeah.
249 00:28:56.300 ⇒ 00:29:00.919 Robert Tseng: Okay, yeah, seems like we should probably consolidate wherever we can cause.
250 00:29:01.340 ⇒ 00:29:02.130 Robert Tseng: Yeah.
251 00:29:02.520 ⇒ 00:29:08.609 Caio Velasco: Yeah, because of that. Yeah, because it’s just like a hundred new Rollovers, a hundred 70 new roles like.
252 00:29:08.900 ⇒ 00:29:09.620 Caio Velasco: yeah.
253 00:29:13.120 ⇒ 00:29:18.262 Aakash Tandel: We might want to do that iteratively. Robert, like next part of next
254 00:29:19.250 ⇒ 00:29:24.349 Aakash Tandel: sow, or whatever. Maybe that’s like a consolidation thing like, get all of our data into one.
255 00:29:24.570 ⇒ 00:29:26.709 Aakash Tandel: Yeah, one per sheet is, yeah.
256 00:29:27.090 ⇒ 00:29:27.790 Robert Tseng: Okay.
257 00:29:28.940 ⇒ 00:29:29.710 Aakash Tandel: Awesome.
258 00:29:30.360 ⇒ 00:29:31.349 Aakash Tandel: How are y’all?
259 00:29:31.920 ⇒ 00:29:37.930 Aakash Tandel: Thanks, we’ll keep in touch on slack. See? You all later. Have a good Monday.
260 00:29:37.930 ⇒ 00:29:38.570 Robert Tseng: This is right.
261 00:29:38.840 ⇒ 00:29:39.110 Annie Yu: You.
262 00:29:39.630 ⇒ 00:29:40.080 Caio Velasco: I agree.