Meeting Title: Eden | Bi-weekly Grooming Date: 2025-07-23 Meeting participants: Robert Tseng, Awaish Kumar, Annie Yu, Demilade Agboola, Amber Lin, Henry Zhao, Henry Zhao
WEBVTT
1 00:00:34.520 ⇒ 00:00:35.670 Awaish Kumar: Hello!
2 00:00:38.900 ⇒ 00:00:39.620 Robert Tseng: Anyways.
3 00:00:40.690 ⇒ 00:00:44.174 Awaish Kumar: Hi, Robert! I just wanted to know
4 00:00:45.080 ⇒ 00:00:54.970 Awaish Kumar: like Andy was asking about like pushing s- something to customer. I/O!
5 00:00:55.492 ⇒ 00:01:00.070 Awaish Kumar: I’m I’m not sure of that platform like, how is that set up?
6 00:01:01.246 ⇒ 00:01:07.170 Awaish Kumar: Like, how like do you have any context to share with me? So for that.
7 00:01:07.570 ⇒ 00:01:17.039 Robert Tseng: Oh, that’s weird. I thought I said. Told him that he should. He could just use segment to do it. I don’t really feel like he needs to go through you
8 00:01:17.520 ⇒ 00:01:19.290 Robert Tseng: to push data into customer. I/O.
9 00:01:20.660 ⇒ 00:01:22.489 Awaish Kumar: Yeah, like, we already have a model.
10 00:01:22.640 ⇒ 00:01:23.205 Awaish Kumar: So.
11 00:01:36.040 ⇒ 00:01:42.139 Robert Tseng: Yeah. Sorry. I guess I’m I haven’t looked at it yet. I’m still needing to
12 00:01:43.110 ⇒ 00:01:48.900 Robert Tseng: update segment to route to the live pixel for Meta. So.
13 00:01:55.680 ⇒ 00:02:06.439 Robert Tseng: Yeah, I think like, I was expecting more like Henry to be technical enough to go and like, do some of this stuff. But
14 00:02:07.480 ⇒ 00:02:10.940 Robert Tseng: feel like he’s not as technical as I thought.
15 00:02:13.180 ⇒ 00:02:14.219 Amber Lin: Hi, there!
16 00:02:17.464 ⇒ 00:02:21.580 Amber Lin: I’ll share my screen. We have 30 min. We’ll go through
17 00:02:22.738 ⇒ 00:02:25.780 Amber Lin: some new tickets, we added.
18 00:02:26.580 ⇒ 00:02:29.679 Amber Lin: and also stuff in the cycle.
19 00:02:33.030 ⇒ 00:02:35.869 Amber Lin: Aiden is here.
20 00:02:37.600 ⇒ 00:02:42.349 Amber Lin: Yeah, I guess, Robert, we can start off with what you got from
21 00:02:43.140 ⇒ 00:02:49.469 Amber Lin: the meeting with them in person, and we can look at prioritization of the projects.
22 00:02:50.417 ⇒ 00:02:53.280 Amber Lin: Take anything out, put anything in.
23 00:02:55.995 ⇒ 00:03:00.280 Robert Tseng: Yeah, I don’t really think it impacts like the work that we take on. It’s more of just like.
24 00:03:02.420 ⇒ 00:03:10.750 Robert Tseng: Giving them. It’s kind of annoying because we have to like kind of Pm. Their work. Now I have to like. Tell them what changes to make. And
25 00:03:11.490 ⇒ 00:03:18.300 Robert Tseng: I mean, I don’t think it’s gonna be that hands on. But like they’re they’re they’re just not gonna do anything until
26 00:03:18.560 ⇒ 00:03:25.490 Robert Tseng: we brought up some concerns. I mean, I think this is more between me and Tim lauded to kind of flush out. But
27 00:03:25.880 ⇒ 00:03:27.829 Robert Tseng: yeah, we need to have like
28 00:03:29.160 ⇒ 00:03:34.420 Robert Tseng: examples of everything, we called out, so that they can go and reproduce the error like it’s
29 00:03:34.570 ⇒ 00:03:38.499 Robert Tseng: kind of annoying because they don’t. There’s no good error logging, but like we have to.
30 00:03:39.120 ⇒ 00:03:39.680 Amber Lin: Hmm.
31 00:03:39.810 ⇒ 00:03:46.239 Robert Tseng: Put some stuff in front of them, like, if if there’s a notion, Doc, that’s floating around, I think I’ve shared it with everyone here at some point so.
32 00:03:47.353 ⇒ 00:03:52.520 Robert Tseng: Let’s just getting that together and sending it over to basket.
33 00:03:53.700 ⇒ 00:03:57.820 Amber Lin: I see, so is there somewhere. We can track all of them.
34 00:04:01.100 ⇒ 00:04:01.880 Amber Lin: Requests?
35 00:04:03.270 ⇒ 00:04:03.859 Amber Lin: Or do we.
36 00:04:03.860 ⇒ 00:04:06.649 Robert Tseng: It’s it’s just in the national Doc.
37 00:04:13.250 ⇒ 00:04:14.870 Amber Lin: Sorry. Can you repeat that.
38 00:04:15.755 ⇒ 00:04:17.589 Robert Tseng: Yeah, it’s in a notion, Doc.
39 00:04:20.240 ⇒ 00:04:20.980 Amber Lin: Okay.
40 00:04:22.202 ⇒ 00:04:31.250 Amber Lin: I, I think I’m more meant of when you need to. It’s like a task. Oh, I need to track error and then put it as a ticket, so we won’t forget.
41 00:04:31.650 ⇒ 00:04:32.460 Robert Tseng: I.
42 00:04:32.460 ⇒ 00:04:32.950 Amber Lin: But I can.
43 00:04:32.950 ⇒ 00:04:41.120 Robert Tseng: I don’t know it should be a ticket, but I mean I just I can know why it’s not letting me share
44 00:04:42.410 ⇒ 00:04:52.090 Robert Tseng: click on here kind of strange.
45 00:05:22.303 ⇒ 00:05:24.070 Amber Lin: What are you sharing, Robert?
46 00:05:27.180 ⇒ 00:05:34.240 Robert Tseng: I just I feel like I’m just trying to drop the notion link, and everybody has contributed.
47 00:05:34.240 ⇒ 00:05:35.309 Amber Lin: Oh, okay.
48 00:05:35.310 ⇒ 00:05:36.679 Robert Tseng: Whatever that you’ve
49 00:05:36.790 ⇒ 00:05:51.879 Robert Tseng: but in there, just add an example to it like I don’t really think I want to add a ticket for that I think that should have been done. Everything that I put in there had a toggle, and you can click into it and see the example that I I put in there. So I think that’s just what I that’s what everybody should be doing.
50 00:05:54.440 ⇒ 00:05:55.130 Amber Lin: Okay,
51 00:05:58.390 ⇒ 00:06:03.086 Robert Tseng: Yeah, notions kind of funky for me. I’m not able to share things right now. I don’t really know why, but
52 00:06:03.610 ⇒ 00:06:05.340 Robert Tseng: I can sometimes have to reload it.
53 00:06:05.340 ⇒ 00:06:06.720 Amber Lin: I see no worries.
54 00:06:08.500 ⇒ 00:06:12.730 Amber Lin: So everything in a project.
55 00:06:13.355 ⇒ 00:06:17.270 Amber Lin: Is this still the right priority for the projects.
56 00:06:25.910 ⇒ 00:06:27.360 Robert Tseng: yeah, I can pull it up.
57 00:06:27.560 ⇒ 00:06:37.700 Robert Tseng: But yeah, I think I’ll just take that notion, Doc. I’m gonna just last. I’m just gonna add everybody in the slack channel and keep pinging until it gets done, and then I’ll shoot it over like I think that’s that’s just
58 00:06:38.050 ⇒ 00:06:39.570 Robert Tseng: that’s what we’ll have to do
59 00:06:40.029 ⇒ 00:06:46.140 Robert Tseng: regarding like the in progress projects. Cdp implementation. Yeah, I think we’re stalling here. It’s kind of
60 00:06:46.700 ⇒ 00:06:51.250 Robert Tseng: yes, the model of ready. I think there’s some confusion around like, where
61 00:06:51.640 ⇒ 00:07:01.000 Robert Tseng: my next steps are. I think we need to get data into customer I/O, and be able to send a message to the team, letting them know that, like, Hey, we are able to. We have these capabilities now.
62 00:07:01.467 ⇒ 00:07:09.229 Robert Tseng: Before X, we had XY and Z available in customer I/O. Now we have a B and C, so I think that messaging is still missing.
63 00:07:09.975 ⇒ 00:07:18.169 Robert Tseng: And then, I think, other than that we can. We can pretty much close out that project, I think, like the evaluation is done. We can.
64 00:07:18.811 ⇒ 00:07:22.460 Robert Tseng: We can write a message sharing that.
65 00:07:25.100 ⇒ 00:07:30.390 Robert Tseng: Yeah, we’ve we’ve decided to stick with segment. And yeah, I think like, that’s
66 00:07:31.400 ⇒ 00:07:32.979 Robert Tseng: that’s that. Like, I,
67 00:07:33.110 ⇒ 00:07:37.984 Robert Tseng: I think the next step is really to just kind of align with marketing and
68 00:07:38.940 ⇒ 00:07:44.840 Robert Tseng: they don’t have a backfill for their lifecycle marketer yet. So I’m okay that this is not moving super quickly. But
69 00:07:46.200 ⇒ 00:07:48.540 Robert Tseng: yeah, I think there’s there’s just like a
70 00:07:49.660 ⇒ 00:07:55.210 Robert Tseng: I think we can. We can close that out. The yeah. So there’s some stuff that’s.
71 00:07:55.210 ⇒ 00:07:55.800 Amber Lin: So.
72 00:07:55.800 ⇒ 00:07:59.750 Robert Tseng: There that’s in progress and in cycle that like is not.
73 00:08:01.360 ⇒ 00:08:07.570 Amber Lin: So let’s see, Spike, reduce redundancy, rebuild and bled the user
74 00:08:10.330 ⇒ 00:08:12.160 Amber Lin: where we can close them out.
75 00:08:14.385 ⇒ 00:08:21.144 Robert Tseng: Yeah. So reducing redundant, we can go one by one reducing redundancy and data flow. Yeah, I think that’s
76 00:08:22.230 ⇒ 00:08:45.770 Robert Tseng: I I don’t think we have a like a solution. Yet I think this is something, I called out. Where, like there are duplicates in Customer I/OI haven’t really seen us like kind of fix that problem yet. But I mean, I’m aware of like what it is. I just I’m not like, I don’t really know if we if we’ve created like a a follow up ticket there to kind of actually deal with it. So
77 00:08:46.252 ⇒ 00:08:48.370 Robert Tseng: maybe the spike is done. But like.
78 00:08:48.480 ⇒ 00:08:51.659 Robert Tseng: I think we just need to create new tickets here on
79 00:08:52.840 ⇒ 00:08:56.889 Robert Tseng: what specific actions we’re taking to to deal with it.
80 00:08:57.590 ⇒ 00:08:58.350 Amber Lin: Okay.
81 00:08:58.350 ⇒ 00:09:00.880 Henry Zhao: Yeah, that’s 1 of the things I wanted to meet with. Away Sean tonight.
82 00:09:01.430 ⇒ 00:09:02.040 Robert Tseng: Okay.
83 00:09:04.236 ⇒ 00:09:06.779 Amber Lin: Okay, so let me.
84 00:09:09.790 ⇒ 00:09:11.539 Amber Lin: can. I just make this ticket.
85 00:09:13.660 ⇒ 00:09:14.260 Robert Tseng: Sure.
86 00:09:16.560 ⇒ 00:09:17.330 Amber Lin: Okay.
87 00:09:19.330 ⇒ 00:09:23.920 Amber Lin: Rebuild top 3 custom bio trades and ebt.
88 00:09:23.920 ⇒ 00:09:32.739 Henry Zhao: Yeah, that I’m probably not going to be able to get done before I head out. So I need to meet with a wish tonight also to just talk about
89 00:09:32.900 ⇒ 00:09:38.259 Henry Zhao: what our models are like in Dbt, to get a sense of that. And I’ll probably have to resume this when I come back in August.
90 00:09:43.420 ⇒ 00:09:44.290 Amber Lin: Okay.
91 00:09:46.645 ⇒ 00:09:50.920 Amber Lin: Pilot. Reverse. Etl to customer.
92 00:09:54.270 ⇒ 00:09:56.339 Robert Tseng: Yeah, I guess. So. This is just like
93 00:09:56.740 ⇒ 00:10:01.890 Robert Tseng: it’s fine. If it’s not fully in there like this week. I know that Henry is going to be out
94 00:10:02.560 ⇒ 00:10:08.259 Robert Tseng: and they also need to get their backfill to come in. But we we should.
95 00:10:09.030 ⇒ 00:10:23.010 Robert Tseng: They’re kind of what I was just mentioning, like, we need to show showcase that we have this capability. Now, I don’t think anybody really knows. And I think it’s it’s really just like, we have to communicate this to the client.
96 00:10:23.987 ⇒ 00:10:26.750 Robert Tseng: It would be great if we could show like.
97 00:10:27.050 ⇒ 00:10:38.199 Robert Tseng: Here you go into segment. You you can look at this destination. It’s connected to customer I/O, and these are the fields that are pulling in from this model like, just like a video like loom. I would kinda just
98 00:10:38.320 ⇒ 00:10:46.580 Robert Tseng: would would be sufficient, I think, just to show that this is possible now. But the context is important, too, of like.
99 00:10:46.920 ⇒ 00:10:54.969 Robert Tseng: before we were at Xyz. Now we’re at ABC, so like I, I think that’s like I’m I feel like I’m a broken record. I said. I just said this earlier.
100 00:10:57.040 ⇒ 00:11:01.720 Amber Lin: Yeah. Who is going to be fun?
101 00:11:05.540 ⇒ 00:11:07.460 Henry Zhao: It should be me, and probably.
102 00:11:12.775 ⇒ 00:11:15.040 Amber Lin: Yeah. The waste.
103 00:11:16.130 ⇒ 00:11:17.100 Amber Lin: Hello.
104 00:11:20.500 ⇒ 00:11:21.300 Amber Lin: Okay.
105 00:11:22.770 ⇒ 00:11:28.440 Amber Lin: Current differences, capabilities.
106 00:11:29.140 ⇒ 00:11:30.160 Amber Lin: All right
107 00:11:33.600 ⇒ 00:11:35.570 Amber Lin: as the current cycle.
108 00:11:37.810 ⇒ 00:11:47.530 Amber Lin: Okay, is this a, is this a which one
109 00:11:47.720 ⇒ 00:11:51.510 Amber Lin: to add data to Customer I/O. Is that the same as the.
110 00:11:51.830 ⇒ 00:11:54.830 Robert Tseng: Yeah, I think it’s the same. We can take that out as in delete. It.
111 00:11:55.000 ⇒ 00:11:57.330 Amber Lin: Okay, my bad.
112 00:11:59.280 ⇒ 00:12:03.020 Amber Lin: Okay, are these still valid tickets?
113 00:12:04.560 ⇒ 00:12:08.759 Robert Tseng: Yeah, those are for next cycle, I think. That’s probably
114 00:12:09.060 ⇒ 00:12:21.180 Robert Tseng: so. Piloting audiences in bigquery for lifecycle use. I mean, we’re not going to necessarily deal with that next cycle. But we can start talking about the treatment journey. Summary model like, I want that to come into the next cycle. Then melody will probably be more involved there.
115 00:12:21.896 ⇒ 00:12:27.600 Robert Tseng: And then, yeah, presale customer contact info and segment. Yeah, we can, we will. We can.
116 00:12:28.320 ⇒ 00:12:29.360 Robert Tseng: Well, yeah.
117 00:12:29.860 ⇒ 00:12:35.079 Robert Tseng: we we can. We can do that next cycle. So like to me, the next milestones here is like, Okay, we’ve
118 00:12:35.230 ⇒ 00:12:47.669 Robert Tseng: we. We chose the vendor we set up testing or like, we set up the basic pipeline. We’ve shown that the capabilities are there. Now, we can actually go and make some of these decisions and like continue to build on stuff so like
119 00:12:48.060 ⇒ 00:12:57.840 Robert Tseng: the treatment journey, summary model is important, because that will help us to that will enable us to build audiences. And then those audiences can go into customer mile later
120 00:12:58.000 ⇒ 00:13:13.859 Robert Tseng: and then presale customer contact. It’s like, Okay, well, what are the other things that we can enrich our already enriched customer data model with. It’s not super urgent, like. I think we’ve already kind of leveled it up. In this past cycle. So. But it is a question that
121 00:13:14.020 ⇒ 00:13:21.759 Robert Tseng: they’re actively trying to answer. So that’s kind of the continue. That’s how we’re gonna continue to iterate on that work.
122 00:13:22.780 ⇒ 00:13:23.300 Amber Lin: Hmm.
123 00:13:23.300 ⇒ 00:13:38.689 Robert Tseng: Tracking plan implementation less relevant. I think I’ll I’ll probably add some stuff into or bring some of the mixed panel work back into the cycle. And Andy can start getting involved there, because it’s a matter of like taking our
124 00:13:38.870 ⇒ 00:13:46.943 Robert Tseng: yeah, like leveling up the existing mix panel reports, using the models that we now are able to to bring into mixed panel. So,
125 00:13:47.630 ⇒ 00:13:52.019 Robert Tseng: yeah, the core modeling work. It was the customer enriched profile
126 00:13:52.960 ⇒ 00:13:58.400 Robert Tseng: that is available. It just has not been synced to customer I/O or mix panel So
127 00:13:58.850 ⇒ 00:14:05.109 Robert Tseng: like the next cycle is about, actually, you know, pushing it into these tools and and building stuff on top of that.
128 00:14:07.930 ⇒ 00:14:08.670 Amber Lin: Okay.
129 00:14:11.260 ⇒ 00:14:12.780 Amber Lin: I see.
130 00:14:18.850 ⇒ 00:14:20.030 Amber Lin: Alright.
131 00:14:21.170 ⇒ 00:14:22.300 Amber Lin: Yeah, I think
132 00:14:22.850 ⇒ 00:14:32.519 Amber Lin: I think I’ll probably just for my own understanding, I’ll have to sort these tickets based on what you said of what milestones they are.
133 00:14:33.064 ⇒ 00:14:40.090 Amber Lin: I think you guys understand. I’m just a little confused. Then I’ll just rewatch this video and get back on track.
134 00:14:42.090 ⇒ 00:14:53.480 Robert Tseng: No, I mean, I don’t. I don’t assume that everyone understands like I get that for most of you. This is probably your 1st time doing this type of project, so we can answer questions or anything. But that to me is kind of how.
135 00:14:54.540 ⇒ 00:14:58.329 Robert Tseng: I don’t think this project is like done done, but like we’ve
136 00:14:58.530 ⇒ 00:15:02.099 Robert Tseng: done, we’ve done what we set out to do in these past 2 weeks.
137 00:15:05.890 ⇒ 00:15:13.830 Amber Lin: Yeah, so currently, we have sorry we have.
138 00:15:15.320 ⇒ 00:15:18.469 Amber Lin: can you give me like, one sentence on the current state.
139 00:15:20.920 ⇒ 00:15:33.020 Robert Tseng: Yeah, we’ve we’ve moved customer data or customer profiles from segment into bigquery. We’ve enriched it with our
140 00:15:33.320 ⇒ 00:15:37.589 Robert Tseng: like with other data in the warehouse. And
141 00:15:38.310 ⇒ 00:15:52.290 Robert Tseng: we’ve consol, yeah, like, we’re we’ve Consolidated. Yeah, we will. We’ve Consolidated customer data modeling into the single model that lives in the warehouse. And it’s ready to push into Customer I/O and mix panel. We need to showcase those capabilities.
142 00:15:53.920 ⇒ 00:15:56.679 Robert Tseng: I think that’s what we should push out this week.
143 00:15:58.180 ⇒ 00:16:05.440 Robert Tseng: It’s just keeping the conversation going and letting them know that we have this capability. Now it it’s
144 00:16:05.440 ⇒ 00:16:05.860 Robert Tseng: it’s hard
145 00:16:05.860 ⇒ 00:16:14.150 Robert Tseng: for non technical stakeholders to really understand what we did so like. It’s this is just a way to to show the progress that we’ve made
146 00:16:14.732 ⇒ 00:16:29.849 Robert Tseng: but we need their use cases which we already have a couple in order to make this come to life. So I mean, as far as like Josh and Elt is concerned, none of this really matters to them because they haven’t seen anything like. So we
147 00:16:30.010 ⇒ 00:16:37.540 Robert Tseng: like the milestones are just there for us to keep pushing
148 00:16:37.880 ⇒ 00:16:44.649 Robert Tseng: the value of what we did and looking searching for the use cases so that we can actually apply what we’ve built.
149 00:16:48.140 ⇒ 00:16:49.200 Amber Lin: Sounds good.
150 00:16:49.811 ⇒ 00:16:53.829 Amber Lin: We’ll try. Then we’ll try to do this one by
151 00:16:55.710 ⇒ 00:17:06.780 Amber Lin: Maybe by end of this week, Henry, before you guys head out after you guys have the meeting. I think we can work on this loom video so that the people can get informed.
152 00:17:08.670 ⇒ 00:17:09.920 Henry Zhao: Okay. Sounds good.
153 00:17:10.130 ⇒ 00:17:23.949 Amber Lin: Yeah, awesome. So next we have tagging and tracking. I just made. I just made these tickets. I think last week, is this a project we’re currently taking on. Or should I move this to backlog.
154 00:17:24.430 ⇒ 00:17:29.260 Robert Tseng: It is, it is active, although I feel like I’m the bottleneck here because I’m the one that’s kind of
155 00:17:29.510 ⇒ 00:17:31.743 Robert Tseng: working a lot of these.
156 00:17:33.450 ⇒ 00:17:40.950 Robert Tseng: So I see this backlog, we’re implementing key conversion instead using Cdp pipelines like.
157 00:17:41.550 ⇒ 00:17:46.181 Robert Tseng: I’m just gonna start assigning stuff. But this a lot of this was me. So
158 00:17:47.520 ⇒ 00:18:02.629 Robert Tseng: we did this Gtm container they were bringing. I’m I’m bringing in a guy, Andrew who’s gonna start today or tomorrow. Hopefully. He’ll catch Henry before he leaves, and then he’ll work with me.
159 00:18:02.810 ⇒ 00:18:05.779 Robert Tseng: But yeah, he’s gonna end up owning some of the stuff
160 00:18:06.000 ⇒ 00:18:15.309 Robert Tseng: so like Gtm. Cleanup will be his outdated tags. You’ll also do that. And he’s gonna he’s gonna take over Google tag manager.
161 00:18:25.160 ⇒ 00:18:31.250 Robert Tseng: checked status status game cycle.
162 00:18:32.980 ⇒ 00:18:39.540 Robert Tseng: It’s Facebook conversion events misfiring. This is in progress. It’s not fully done yet.
163 00:18:42.910 ⇒ 00:18:57.300 Robert Tseng: Tabloid dashboards. We don’t need training Ryan backlog consolidating historical data sources. I mean, I guess that’s
164 00:18:57.590 ⇒ 00:18:58.800 Robert Tseng: I don’t really know.
165 00:18:59.250 ⇒ 00:19:02.189 Robert Tseng: I don’t really think that’s 1. So let me take that out
166 00:19:02.800 ⇒ 00:19:16.649 Robert Tseng: assessing Facebook, 7 day window. I already did that and backs up. Brian with Henry
167 00:19:18.120 ⇒ 00:19:21.109 Robert Tseng: verify. Meta receives approve orders.
168 00:19:22.517 ⇒ 00:19:26.260 Robert Tseng: Yeah. We verified that that I did that
169 00:19:31.150 ⇒ 00:19:32.030 Robert Tseng: oops
170 00:19:35.290 ⇒ 00:19:41.630 Robert Tseng: test for event accuracy, lag impact on real time reporting, I would say, that’s still in testing.
171 00:19:43.072 ⇒ 00:19:51.260 Robert Tseng: Yeah, I mean, like, we have a lot of tickets here. But generally I think my feedback on this project, was I.
172 00:19:52.860 ⇒ 00:19:58.592 Robert Tseng: I tried to write the specs and like have a wish, and Henry kinda execute on it.
173 00:19:59.210 ⇒ 00:20:03.470 Robert Tseng: I think we got stuck earlier in the week. So I jumped in and I
174 00:20:04.110 ⇒ 00:20:13.270 Robert Tseng: built the bottle and pushed it in, testing. So it works in the Meta Pixel. But now we have to go and switch it to production. But like, basically.
175 00:20:13.560 ⇒ 00:20:38.459 Robert Tseng: I might ended up, it ended up back being in my hands, which I was hoping to not be that way. So it’s fine, like, I think there’s a time crunch, and that’s why I urgently like am hiring someone to kind of help keep this going, because we have to cover north beam, reddit pinterest, or whatever. But yeah, like, I, I kind of feel like I became the the owner of this project again. This, my is basically what happened.
176 00:20:41.930 ⇒ 00:20:43.280 Amber Lin: Moving forward.
177 00:20:44.300 ⇒ 00:20:45.129 Awaish Kumar: Name is Project
178 00:20:45.130 ⇒ 00:20:55.890 Awaish Kumar: yeah, on this, like, I just have feedback, like like, when, while connecting the segment to Meta, I, and without like seeing
179 00:20:56.040 ⇒ 00:21:03.349 Awaish Kumar: the destination it was really hard for me, like I can see the errors and segment and fix those. I’m not sure what
180 00:21:03.815 ⇒ 00:21:17.180 Awaish Kumar: is going to Meta. How do I see the Meta platform itself? It was really hard to like, guess anything. And I I it was successful in segment. I thought, it’s going to Meta the way I’m sending. So yeah.
181 00:21:19.750 ⇒ 00:21:26.230 Robert Tseng: Yeah, that’s true. I think a waste did send some test events. We did see something show up in Meta, it.
182 00:21:26.500 ⇒ 00:21:28.259 Robert Tseng: But yeah, I think that just
183 00:21:28.410 ⇒ 00:21:36.449 Robert Tseng: yeah, you didn’t have the same level of access to Meta, which is kind of frustrating.
184 00:21:38.750 ⇒ 00:21:41.080 Robert Tseng: yeah, I don’t. I don’t honestly don’t know
185 00:21:41.880 ⇒ 00:21:54.070 Robert Tseng: how to make that smoother like we did get Meta access pretty late, I think even Henry has a different level of access than I do like. He sees more than I do on and you’d need a Facebook account in order to
186 00:21:54.200 ⇒ 00:22:06.319 Robert Tseng: like, get on ads. Manager. It. It’s kind of messy like I’m not even using. I’m using my wife’s Facebook to to like access their ads manager because my ads, my Facebook account has been banned for like years.
187 00:22:06.780 ⇒ 00:22:09.080 Robert Tseng: so it’s just like.
188 00:22:09.220 ⇒ 00:22:18.329 Robert Tseng: I don’t know we couldn’t. We couldn’t give the same level of access to everyone, just because I’m not. I’m not the one who controls that and they, they just.
189 00:22:18.770 ⇒ 00:22:26.690 Robert Tseng: It’s they’ve given our team inconsistent access on this front. So yeah, I
190 00:22:28.150 ⇒ 00:22:32.649 Robert Tseng: I don’t know what could have made it go smoother. I think it just. That’s just the
191 00:22:33.240 ⇒ 00:22:40.179 Robert Tseng: that’s the trouble of like. Why, I wanted to stay away from this tag management work like for the longest time. But
192 00:22:40.610 ⇒ 00:22:46.360 Robert Tseng: yeah, I mean, it’s it’s here now. It’s on our plate. So I don’t know like I’m just trying to find a way.
193 00:22:55.440 ⇒ 00:22:56.110 Amber Lin: Okay.
194 00:22:56.704 ⇒ 00:23:05.570 Amber Lin: do you think we can hand off tickets, at least for other people to do so? It’s not just you doing and executing these tickets.
195 00:23:06.960 ⇒ 00:23:26.170 Robert Tseng: I feel like we’re kind of late. So like, honestly, the rest of this day, I’m gonna try to catch up more on this. So I’m gonna do everything else that’s in cycle pretty much. And I don’t know I’m just once Andrew gets in here. I’m just gonna finish it with him. But yeah, because I’m because this is on my plate. I can’t really do anything else like I. This is all I have the time for.
196 00:23:26.170 ⇒ 00:23:27.239 Amber Lin: I see.
197 00:23:27.240 ⇒ 00:23:27.770 Robert Tseng: Yeah.
198 00:23:28.450 ⇒ 00:23:30.250 Amber Lin: I see it’s valid.
199 00:23:32.000 ⇒ 00:23:41.830 Amber Lin: all right. We have 5 around 5 min left, and then me and a way just gonna hop over to the Emr meeting. I guess I just watch. I want to take this time to confirm what the
200 00:23:42.640 ⇒ 00:23:46.409 Amber Lin: the goals are for the meeting, so I know we want to
201 00:23:46.570 ⇒ 00:23:51.849 Amber Lin: get the current state or the timeline for the Emr for the Emr team.
202 00:23:55.580 ⇒ 00:23:56.340 Amber Lin: Yeah.
203 00:23:56.990 ⇒ 00:23:58.290 Robert Tseng: Yeah, I think.
204 00:23:58.570 ⇒ 00:23:59.280 Amber Lin: Absurd.
205 00:24:00.010 ⇒ 00:24:17.589 Robert Tseng: I don’t know the Emr development timeline. I I hear different things from different people. So just like kind of knowing when are they going live. And then how do we align? What we’re asking with asking them for to their development cycle, like, I know, they’re touching post hog work now, which
206 00:24:17.770 ⇒ 00:24:19.550 Robert Tseng: it’s just like, kind of
207 00:24:20.540 ⇒ 00:24:26.509 Robert Tseng: whatever people are making like tech decisions that don’t fully make sense to me, because
208 00:24:27.060 ⇒ 00:24:32.449 Robert Tseng: we already have mixed panel. I don’t know why we’re also doing post hog just. And
209 00:24:32.630 ⇒ 00:24:46.850 Robert Tseng: yeah, I I don’t. I don’t. I don’t. I just I don’t really understand like what they’re doing and where they’re considering like our needs from a data perspective. And I want to make sure that we come out of that meeting just with some more clarity around, like
210 00:24:50.380 ⇒ 00:24:55.370 Robert Tseng: how their development is kind of
211 00:24:55.970 ⇒ 00:25:02.580 Robert Tseng: taking in taking into consideration, like our needs for what the data needs to look like. But but but.
212 00:25:03.500 ⇒ 00:25:05.410 Awaish Kumar: Like they are they using
213 00:25:05.810 ⇒ 00:25:12.330 Awaish Kumar: post work. But like I, I heard from a user that we they are moving to Gtm for
214 00:25:13.318 ⇒ 00:25:16.110 Awaish Kumar: event tracking for the
215 00:25:16.340 ⇒ 00:25:23.180 Awaish Kumar: in tax. So I’m not sure for other product analytics. They will use post hoc, or Gtm itself.
216 00:25:24.520 ⇒ 00:25:27.650 Robert Tseng: Yeah, so I guess, like
217 00:25:28.020 ⇒ 00:25:43.080 Robert Tseng: I I don’t. I don’t. I guess I don’t. I don’t know. It seems like you heard something different than I did away. So hopefully, you guys can can get that. I think I will say that like, I don’t know if Sebastian is going to be on that call. But Sebastian has a big influence on like what
218 00:25:43.320 ⇒ 00:25:46.410 Robert Tseng: tech, by what tools they’re prioritizing.
219 00:25:46.540 ⇒ 00:25:53.099 Robert Tseng: I don’t agree with all the decision he’s making, like he is a Google tag manager guy through like through and through. And it.
220 00:25:53.900 ⇒ 00:26:09.770 Robert Tseng: I don’t really think that that’s necessarily the best best approach like I. I’m I just I don’t know what I don’t know. I don’t know what what they, what their directive is. And I I just I don’t wanna give my bias on like where things should be headed. Because I I just
221 00:26:10.390 ⇒ 00:26:20.929 Robert Tseng: yeah, like I, I’ve never once again. I just I just feel like I don’t really understand what they’re what the marketing is doing. They’ve been working on this for 5 months, and I have no idea like what they’re developing.
222 00:26:23.060 ⇒ 00:26:23.680 Amber Lin: Hmm!
223 00:26:24.200 ⇒ 00:26:24.790 Amber Lin: I see.
224 00:26:24.790 ⇒ 00:26:39.080 Awaish Kumar: Like. But but yeah, I have a question here, like, how like are we looking to impact their Emr decisions like we are, they are building. Emr is kind of a like a platform
225 00:26:39.230 ⇒ 00:26:50.059 Awaish Kumar: for handling their the regular sales. We we are concerned about the data side of it. How like are we
226 00:26:50.290 ⇒ 00:26:55.320 Awaish Kumar: like, what different kind of tools and technologies they are using?
227 00:26:55.640 ⇒ 00:26:56.839 Awaish Kumar: Are we like
228 00:26:57.500 ⇒ 00:27:04.110 Awaish Kumar: somehow want to make some suggestions on that as well? Or it’s just like we want to be in the, in, the.
229 00:27:04.720 ⇒ 00:27:08.050 Awaish Kumar: in the scope of data, analytics.
230 00:27:08.050 ⇒ 00:27:17.100 Robert Tseng: I think, for this call we should not make any suggestions. I think we should just try to learn as much as we can, and then we can kind of come back to and kind of see if we need to
231 00:27:17.410 ⇒ 00:27:24.850 Robert Tseng: impact what they’re doing in any way. Yeah, I.
232 00:27:25.830 ⇒ 00:27:26.540 Amber Lin: Okay.
233 00:27:26.840 ⇒ 00:27:27.869 Robert Tseng: Yeah. Hopefully, that answers.
234 00:27:28.159 ⇒ 00:27:34.539 Amber Lin: Sorry. What was this one? What was this one for? Figure out tables every is using, and others that aren’t being used.
235 00:27:35.400 ⇒ 00:27:58.609 Awaish Kumar: So like these are our internal like discussion that we what we are doing on our side, like we are setting it. We are like defining current state of what tables and which are coming from bask. And this is something we need to share with them. But like.
236 00:27:59.500 ⇒ 00:28:04.580 Awaish Kumar: we just need to understand what they are developing and how
237 00:28:04.994 ⇒ 00:28:10.969 Awaish Kumar: they can set up the different web books for us to get the data we are getting from bask.
238 00:28:12.140 ⇒ 00:28:19.359 Robert Tseng: Yeah. Or if they’re gonna do an Api like I I think I would, I think obviously that would be better for us in the long term. So like I.
239 00:28:19.590 ⇒ 00:28:28.269 Awaish Kumar: Yeah, Api is not real time. I don’t know. Like, if what is the need here like, is it? We are looking looking for more real time
240 00:28:30.240 ⇒ 00:28:39.130 Awaish Kumar: data coming in. Or we are okay with batchy load loading like Api. Loading is kind of good for batch loading, not for event streaming.
241 00:28:40.170 ⇒ 00:28:49.309 Robert Tseng: Do you think web hook for event streaming is? I mean, if that’s your decision, then I I mean I I trust your judgment, but like, I, I think those are the types of questions I’m curious. And like.
242 00:28:49.600 ⇒ 00:29:02.460 Robert Tseng: how is the data gonna be accessible to us like, how frequently is it gonna be there like, what what are they including? Are they gonna be able to satisfy everything that we need? Like? I? Those are like, those are the questions that I would be interested in asking.
243 00:29:02.460 ⇒ 00:29:18.267 Awaish Kumar: For that, like for real time, we need even the streaming. There are multiple ways to handle. Like number one is the the current one we are using like web books with segment. But there are other ways like the. For example, default is handling it a differently
244 00:29:18.820 ⇒ 00:29:24.889 Awaish Kumar: using. Yeah, red Panda so they send events from their
245 00:29:25.761 ⇒ 00:29:33.569 Awaish Kumar: app to the red panda, and then it goes to the warehouse. So things like that, and that’s more, much more
246 00:29:33.910 ⇒ 00:29:52.310 Awaish Kumar: faster than the segment. So, yeah, there could be multiple tools here. But yeah, that’s that’s for real time streaming. And we we are looking for that. Right? They need to develop some web books. But yeah, how they support that. What is the architecture behind those is is up to them.
247 00:29:52.750 ⇒ 00:29:58.459 Awaish Kumar: Oh, yeah, how they can make it more reliable than the bus ones.
248 00:29:58.890 ⇒ 00:30:02.929 Robert Tseng: Yeah, okay, yeah. I’m with you. Yep.
249 00:30:03.399 ⇒ 00:30:09.879 Amber Lin: Go into the call now, Robert, do you want the optional, or are you from.
250 00:30:09.880 ⇒ 00:30:10.230 Robert Tseng: Emi.
251 00:30:10.230 ⇒ 00:30:11.310 Amber Lin: Yeah, all of this.
252 00:30:11.310 ⇒ 00:30:16.140 Amber Lin: I’m I’m not gonna join. Yeah, yeah, no, okay, that’s all good.
253 00:30:16.340 ⇒ 00:30:18.420 Robert Tseng: Recording so you can watch it.
254 00:30:18.610 ⇒ 00:30:19.410 Amber Lin: Alright!
255 00:30:19.410 ⇒ 00:30:20.090 Robert Tseng: Thanks.
256 00:30:21.080 ⇒ 00:30:22.270 Amber Lin: Thanks. Everyone.
257 00:30:22.770 ⇒ 00:30:23.690 Henry Zhao: You guys.
258 00:30:23.870 ⇒ 00:30:24.860 Amber Lin: Bye.