Meeting Title: Robert Tseng’s Personal Meeting Room Date: 2025-05-13 Meeting participants: Robert Tseng, Awaish Kumar, Annie Yu
WEBVTT
1 00:00:58.970 ⇒ 00:00:59.870 Robert Tseng: Hey, everyone.
2 00:01:03.180 ⇒ 00:01:04.230 Annie Yu: Hi! Everyone.
3 00:01:04.780 ⇒ 00:01:05.640 Awaish Kumar: Hello!
4 00:01:12.320 ⇒ 00:01:20.640 Robert Tseng: Yeah. So I guess, Annie. And then Lotta, if you don’t have anything you need to talk about is drop off early. I just wanna
5 00:01:20.820 ⇒ 00:01:22.580 Robert Tseng: move things along with the wish
6 00:01:22.710 ⇒ 00:01:27.964 Robert Tseng: I didn’t end up getting to as much as I wanted to yesterday. So
7 00:01:28.750 ⇒ 00:01:32.370 Robert Tseng: yeah, I think I think we just gotta we gotta finish
8 00:01:33.320 ⇒ 00:01:35.910 Robert Tseng: from stuff that we were talking about yesterday.
9 00:01:43.350 ⇒ 00:01:49.350 Robert Tseng: Okay? So I mean, I wish. And then I’m assuming any like, you guys don’t really need
10 00:01:49.640 ⇒ 00:01:53.279 Robert Tseng: like, you’re kind of working on stuff. And
11 00:01:54.090 ⇒ 00:01:57.980 Robert Tseng: yeah, I mean, like, every I feel like, everything in progress is just
12 00:01:58.230 ⇒ 00:02:04.378 Robert Tseng: that needs to move along is really just blocked by me to wait. So I I guess that’s
13 00:02:05.110 ⇒ 00:02:11.370 Robert Tseng: yeah. Well, I’m I’m I’m not. I’m not gonna be going into the the board unless you have any specific questions.
14 00:02:12.700 ⇒ 00:02:14.860 Annie Yu: I do have one quick question. If that’s okay.
15 00:02:15.280 ⇒ 00:02:15.810 Robert Tseng: Yeah.
16 00:02:15.810 ⇒ 00:02:28.160 Annie Yu: Oh, and this is for a wish. I did see the channel sales, summary and channel. Spend summary in the stage. So would that get moved to Mars today? Is that the plan.
17 00:02:28.600 ⇒ 00:02:29.480 Awaish Kumar: Yes! Yes!
18 00:02:29.480 ⇒ 00:02:33.269 Annie Yu: Okay, and one more follow up is so one
19 00:02:33.680 ⇒ 00:02:43.910 Annie Yu: covers spend data by channel, and one covers revenue. So is the plan to if I want to get more, do I join them by on Channel.
20 00:02:43.910 ⇒ 00:02:50.070 Awaish Kumar: Channel sales summary is kind of combining both suspendance.
21 00:02:51.290 ⇒ 00:02:52.523 Annie Yu: So there’s.
22 00:02:53.140 ⇒ 00:03:01.739 Awaish Kumar: So in the summary, you have basically the date Channel order account, like, I just need.
23 00:03:03.380 ⇒ 00:03:04.080 Annie Yu: Yeah, yeah.
24 00:03:04.080 ⇒ 00:03:08.480 Awaish Kumar: Probably as order number, which is a 3. Order, count order total, and spend.
25 00:03:09.620 ⇒ 00:03:10.450 Annie Yu: Okay. Okay.
26 00:03:10.450 ⇒ 00:03:13.459 Awaish Kumar: These are things you can get from this channel system.
27 00:03:14.100 ⇒ 00:03:16.169 Annie Yu: Okay, thank you so much.
28 00:03:17.980 ⇒ 00:03:18.880 Annie Yu: Cool.
29 00:03:19.540 ⇒ 00:03:20.210 Robert Tseng: Okay.
30 00:03:22.150 ⇒ 00:03:22.890 Robert Tseng: Alright.
31 00:03:24.270 ⇒ 00:03:36.649 Robert Tseng: ohish! Let’s just kind of talk through what needs to like, how how we need to move things along. So mentioned leaving comments in the whimsical. I’m just gonna share my screen. We’re just gonna go in, actually just do some stuff. So
32 00:03:37.340 ⇒ 00:03:40.700 Robert Tseng: I don’t see comments here. But I mean whimsical.
33 00:03:40.700 ⇒ 00:03:41.070 Awaish Kumar: I don’t know.
34 00:03:41.070 ⇒ 00:03:42.409 Robert Tseng: Have to. Yeah.
35 00:03:43.280 ⇒ 00:03:52.850 Awaish Kumar: Okay. I actually logged in, joined the team and added some tickets on the side. I I don’t know. Why do we need to save it?
36 00:03:54.649 ⇒ 00:04:05.689 Robert Tseng: Mean, I don’t pay for whimsical. So like, I don’t think you can actually collaborate like that. We really shouldn’t be doing this with, but like I just never moved it over so.
37 00:04:06.860 ⇒ 00:04:12.709 Awaish Kumar: Yeah, it showed me as free as well, but it also like I was able to edit it.
38 00:04:13.242 ⇒ 00:04:15.899 Awaish Kumar: If you can. Can you open this one.
39 00:04:21.029 ⇒ 00:04:28.460 Awaish Kumar: In this in this zoom, but then I otherwise I can share my if it doesn’t show.
40 00:04:32.500 ⇒ 00:04:34.430 Robert Tseng: Is it talking about?
41 00:04:38.360 ⇒ 00:04:39.559 Robert Tseng: I opened it.
42 00:04:40.810 ⇒ 00:04:41.380 Awaish Kumar: Yeah.
43 00:04:41.380 ⇒ 00:04:47.420 Awaish Kumar: I’m the okay, the music.
44 00:04:47.910 ⇒ 00:04:50.780 Robert Tseng: This is the one or.
45 00:04:50.780 ⇒ 00:04:51.159 Awaish Kumar: Oh.
46 00:04:54.990 ⇒ 00:04:57.190 Awaish Kumar: okay, if I don’t mind.
47 00:04:59.740 ⇒ 00:05:04.469 Awaish Kumar: Okay, you are on this. It says you are on this same link right.
48 00:05:05.780 ⇒ 00:05:08.119 Robert Tseng: Yeah, I mean, I got it from the chat.
49 00:05:09.170 ⇒ 00:05:14.100 Awaish Kumar: Yeah, in the whimsical. You actually can see if I am on the same page, because I can see.
50 00:05:15.721 ⇒ 00:05:21.820 Awaish Kumar: On the top right. I actually see that you are on this page like it says Robert, is 0.
51 00:05:22.690 ⇒ 00:05:23.840 Awaish Kumar: It’s too weird.
52 00:05:24.820 ⇒ 00:05:27.349 Robert Tseng: Oh, yeah, I didn’t know that you could
53 00:05:27.350 ⇒ 00:05:29.369 Robert Tseng: do that, so I don’t see anything.
54 00:05:30.340 ⇒ 00:05:32.519 Awaish Kumar: Okay, can I then share?
55 00:05:32.870 ⇒ 00:05:33.869 Awaish Kumar: Yeah, go ahead.
56 00:05:41.375 ⇒ 00:05:42.240 Awaish Kumar: Basically
57 00:05:46.110 ⇒ 00:05:48.070 Awaish Kumar: Europe. Yeah, this one.
58 00:05:53.320 ⇒ 00:05:58.570 Awaish Kumar: This is on the in the right side of
59 00:05:59.270 ⇒ 00:06:03.839 Awaish Kumar: of all these tickets, you have added, and it’s on the top. Maybe. Then.
60 00:06:05.304 ⇒ 00:06:11.449 Robert Tseng: Yeah, that’s not actually the right model. That’s Sahana’s model. I I completely redid her model.
61 00:06:12.340 ⇒ 00:06:13.289 Awaish Kumar: I’ll be here.
62 00:06:15.720 ⇒ 00:06:16.930 Awaish Kumar: Okay, I’m.
63 00:06:20.460 ⇒ 00:06:21.939 Robert Tseng: But I mean it probably.
64 00:06:21.940 ⇒ 00:06:22.410 Awaish Kumar: Yeah, that’s.
65 00:06:22.890 ⇒ 00:06:23.370 Robert Tseng: Yeah.
66 00:06:24.260 ⇒ 00:06:31.409 Awaish Kumar: We can go ahead with what I have added here, because it’s not like contradicting with with your model. It’s just
67 00:06:31.910 ⇒ 00:06:39.560 Awaish Kumar: what I found in the segment and the in the G, 4 data.
68 00:06:39.950 ⇒ 00:06:40.380 Robert Tseng: Yep.
69 00:06:41.650 ⇒ 00:06:47.850 Awaish Kumar: So we like, these are the event names which are being captured. So in the segment, basically, there’s a 4.
70 00:06:47.850 ⇒ 00:06:49.150 Robert Tseng: I’ve seen everything there.
71 00:06:49.600 ⇒ 00:07:00.300 Awaish Kumar: Functions and in the functions we receive an event name as new patient. And then there’s data regarding that is being sent over in the bask signed up table. Right?
72 00:07:01.270 ⇒ 00:07:05.520 Awaish Kumar: I can’t see the similar kind of event claims
73 00:07:05.630 ⇒ 00:07:07.770 Awaish Kumar: in the like. Gf, 4 data.
74 00:07:08.570 ⇒ 00:07:13.140 Awaish Kumar: These are the event names in the large per ticket.
75 00:07:15.070 ⇒ 00:07:21.170 Awaish Kumar: This is all the event names which we get from this year for data.
76 00:07:21.510 ⇒ 00:07:22.130 Robert Tseng: Yep.
77 00:07:23.210 ⇒ 00:07:28.349 Awaish Kumar: And it’s like so like how we are going to map it like the new
78 00:07:29.110 ⇒ 00:07:33.326 Awaish Kumar: new patient it says, signed up. We don’t have anything for signed up. But we have
79 00:07:33.710 ⇒ 00:07:35.380 Awaish Kumar: for 1st visit.
80 00:07:36.680 ⇒ 00:07:37.800 Awaish Kumar: Maybe not.
81 00:07:38.400 ⇒ 00:07:39.370 Awaish Kumar: So.
82 00:07:39.780 ⇒ 00:07:47.900 Awaish Kumar: Did you have any anything here or like I need? I should take down like more into this.
83 00:07:49.180 ⇒ 00:07:54.579 Robert Tseng: Okay, so let’s let’s kind of like back up a bit here. So yeah, I think, like.
84 00:07:55.120 ⇒ 00:08:20.739 Robert Tseng: yeah, I did a design. I asked. Like the web flow team, which I mean, whatever the develop their developer team to go. And basically they said, they don’t hard code any events. Everything is straight up in Google, tag, manager or segment. And so we need to go and look in these 2 environments like, I understand which events come through segment. It’s much clearer. These are server side events.
85 00:08:21.530 ⇒ 00:08:36.800 Robert Tseng: yeah. Each source is basically a web hook, a separate individual web hook. It gets passed in through like the segment tracking snippet. And then it goes into big word right? And that’s like how we get. Like all of the order events that we have there.
86 00:08:37.020 ⇒ 00:08:38.759 Robert Tseng: We don’t really do
87 00:08:38.890 ⇒ 00:09:01.704 Robert Tseng: so. I mean, I you know I know you listed out everything here. I don’t think every basketball event is actually active. I think. Some of those are not actually active, and then what you have on the right is, you have all of the events that you think that you saw on Google Tag, manager. I don’t know if you went and you looked at the tags and just down like kind of exported from there, or if you actually went and did like
88 00:09:02.363 ⇒ 00:09:11.850 Robert Tseng: preview, and like, actually tried to go through the flow. And those are the events that were firing, because I would say that there’s a few events in there that I don’t think they’re live either.
89 00:09:12.534 ⇒ 00:09:27.460 Robert Tseng: So yeah, I think we kind of just have to figure out what events are actually live. What’s the sequence? And then, if we need to add any intermediary things based on the plan that I had put out, and we need to go and like add those. So I think that’s what that’s what we need to do here.
90 00:09:28.690 ⇒ 00:09:38.569 Awaish Kumar: Yeah. So like, what I’m saying is that so we have a Google tag manager. And then we have Ga, 4. So some of
91 00:09:38.830 ⇒ 00:09:45.900 Awaish Kumar: data is going into Gf, 4 from Google Tag manager. And then it is by using streaming. I think
92 00:09:46.030 ⇒ 00:09:51.999 Awaish Kumar: I think you have. You have enabled the stream into bigquery as well. So I can see this data, the big carry.
93 00:09:53.760 ⇒ 00:10:02.730 Awaish Kumar: So that’s where I got it. And then, I in the in the Geo. Google Tag manager. I can see some other triggers as well, which are for
94 00:10:03.312 ⇒ 00:10:14.630 Awaish Kumar: segment, which is in segment this and that. But I I can’t really understand by just seeing the trigger, how it’s like the flow is working, or what really the trigger is going like.
95 00:10:14.880 ⇒ 00:10:21.249 Awaish Kumar: how is is pushing the data to segment. So if, like, you can connect me with someone in the team like
96 00:10:22.350 ⇒ 00:10:26.199 Awaish Kumar: anything which can overview me, that things.
97 00:10:28.320 ⇒ 00:10:48.260 Robert Tseng: Yeah, I I frankly don’t think anybody understands how Google Tag manager like fires events into segment like I. I’ve asked Ryan. I’ve asked Nick. I’ve asked Danny, like we brought them into multiple stand up. And I would rather just figure that out ourselves and not have to ask. But
98 00:10:48.410 ⇒ 00:10:49.130 Robert Tseng: bye.
99 00:10:50.280 ⇒ 00:10:50.680 Awaish Kumar: Okay.
100 00:10:50.680 ⇒ 00:11:07.109 Robert Tseng: Yeah, like, I just, I just don’t think that they’re gonna give us an answer like, I feel like I brought him onto the call last week, and he just he sat here, and he was just like, I don’t know how any of this works, and I was like Dude. Are you the lead engineer on the website. And he was like, Yeah, but I don’t. I don’t touch this.
101 00:11:08.410 ⇒ 00:11:17.764 Awaish Kumar: Okay. Okay. Then I can spend some more time into this and maybe collaborate with other team members. And then,
102 00:11:18.894 ⇒ 00:11:27.929 Awaish Kumar: like like you spend one more day and figure out what kind, what? What I can understand from here, how they are going to the segment, and
103 00:11:28.200 ⇒ 00:11:30.430 Awaish Kumar: then we can move forward like.
104 00:11:33.630 ⇒ 00:11:38.719 Robert Tseng: Okay, yeah, I mean, like, here, if you look at like the Google Tag manager. So I mean, he’s.
105 00:11:38.880 ⇒ 00:11:41.660 Awaish Kumar: I’m I’m assuming you understand? Like.
106 00:11:42.320 ⇒ 00:11:47.490 Robert Tseng: Okay, you haven’t. You know you? I’m sure you understand tags and triggers. Yeah.
107 00:11:48.740 ⇒ 00:11:49.310 Awaish Kumar: Yeah.
108 00:11:49.780 ⇒ 00:11:50.433 Awaish Kumar: So I
109 00:11:51.020 ⇒ 00:11:59.140 Awaish Kumar: I see that there are some triggers which actually trigger a tag from where the data goes. I it does say some
110 00:12:00.430 ⇒ 00:12:05.940 Awaish Kumar: something related to segment as well, Tom.
111 00:12:08.170 ⇒ 00:12:10.829 Awaish Kumar: But then, like, we also have to
112 00:12:12.090 ⇒ 00:12:16.689 Awaish Kumar: push them to Gf 4, so that we can move with them to victory.
113 00:12:16.830 ⇒ 00:12:21.120 Awaish Kumar: So yeah, I have to understand that flow that.
114 00:12:25.570 ⇒ 00:12:29.040 Robert Tseng: Yeah. So I mean, yeah, you’re
115 00:12:29.550 ⇒ 00:12:37.329 Robert Tseng: it will. I believe. It has to go through ga, 4 in order to get into bigquery.
116 00:12:39.880 ⇒ 00:12:40.770 Awaish Kumar: Sorry.
117 00:12:41.460 ⇒ 00:12:43.869 Robert Tseng: I believe that like the tag,
118 00:12:47.860 ⇒ 00:12:56.840 Robert Tseng: yeah, the tags that fire in G in Google tag manager, they have to be logged as the Event stream. Google analytics before you push that into bigquery.
119 00:12:57.310 ⇒ 00:13:06.809 Awaish Kumar: Yes, yes, but that’s what I’m saying. Not all of them are not. Not. All of them are in G 4. That’s why we are not getting them into our victory.
120 00:13:06.980 ⇒ 00:13:32.950 Awaish Kumar: So I have analyzed the data which we have in bigquery. And Gfr. Is pushing all the events right? We don’t have any filter. It’s just pushing all the events which it gets gets and it they get loaded into bigquery. And I have analyzed these real, the streaming data. And this is what I listed here as well. Like these are the events currently which are coming in into bigquery. So we might have to add more
121 00:13:34.020 ⇒ 00:13:41.780 Awaish Kumar: oops flow so that it goes from tag manager to pick Gf. 4. Then it goes to pick curry.
122 00:13:42.350 ⇒ 00:13:53.919 Robert Tseng: Yeah. And so that’ll only be like the web flow like events, right? Like the the bask events they get. They come through the web hook in segment. So we don’t need
123 00:13:54.170 ⇒ 00:13:59.599 Robert Tseng: like we don’t necessarily need to recreate the same things like here, right like the
124 00:13:59.700 ⇒ 00:14:11.220 Robert Tseng: isn’t that the whole point of the web, the web, hook and segment like it. It goes direct from because a vast server event that gets logged in, or that gets sent as an event into bigquery. So like, we don’t
125 00:14:11.480 ⇒ 00:14:17.900 Robert Tseng: have to do everything through this Google tag manager, Google analytics to bigquery like, Wow.
126 00:14:19.280 ⇒ 00:14:28.709 Awaish Kumar: But but they are using actually Google Tag manager on their website to basically collect that information for the
127 00:14:29.030 ⇒ 00:14:30.080 Awaish Kumar: for a drive.
128 00:14:30.460 ⇒ 00:14:31.940 Robert Tseng: Even for the web hook.
129 00:14:37.610 ⇒ 00:14:45.510 Awaish Kumar: Okay, I I like in the Google Tag man tags. If we open this like we, I see segment
130 00:14:45.840 ⇒ 00:14:53.719 Awaish Kumar: related tags. And they are like coming from
131 00:14:56.300 ⇒ 00:15:04.140 Awaish Kumar: like from from the the flow on the website. Right? We are not like directly getting something using Apis from bask.
132 00:15:04.360 ⇒ 00:15:05.990 Robert Tseng: Yeah. No. Apis, yeah.
133 00:15:07.000 ⇒ 00:15:14.309 Awaish Kumar: So this is like this, Gtm is being used to basically track the flow on the website.
134 00:15:15.210 ⇒ 00:15:25.840 Awaish Kumar: So if it pushes a button or it clicks something. Then we have the tag which could gets triggered and and it loads the data to G 4 or
135 00:15:26.580 ⇒ 00:15:28.989 Awaish Kumar: orange trigger segment, or whatever.
136 00:15:32.130 ⇒ 00:15:32.883 Robert Tseng: I see.
137 00:15:34.040 ⇒ 00:15:43.509 Robert Tseng: Okay? Well, I mean, like, I need to update my understanding. I I did not know that the web hooks were also instrumented through this way. I thought the whole purpose of like
138 00:15:43.810 ⇒ 00:16:00.509 Robert Tseng: asking Bask to, hey? We’re not. We’re missing certain data. Can you include it in the web hook. They’ll update something in the web hook. It’s like a data layer event that they fire. But then we use segment to basically go in and fish that out. And I I thought we were just, you know
139 00:16:00.710 ⇒ 00:16:06.120 Robert Tseng: that. Yeah, it’s it was purely set up in segment, and it didn’t go through. Gtm. At all.
140 00:16:06.890 ⇒ 00:16:10.219 Awaish Kumar: Yeah, like, if you if we keep going to segment, how
141 00:16:13.230 ⇒ 00:16:19.293 Awaish Kumar: what happens here is basically it just
142 00:16:21.160 ⇒ 00:16:26.920 Awaish Kumar: And it provides a link right it. It provides a URL so you can hit this
143 00:16:27.380 ⇒ 00:16:33.149 Awaish Kumar: URL. So so there is someone who is triggering this URL. So that is
144 00:16:33.330 ⇒ 00:16:52.330 Awaish Kumar: the Gtm right? So that makes a trigger. And in that trigger we are maybe triggering this web hook, and why we are providing the data in its body. So segment is listening on this URL basically. And then it. This is the function which basically then
145 00:16:52.510 ⇒ 00:16:57.769 Awaish Kumar: loads it into the source of the segment.
146 00:16:58.060 ⇒ 00:17:03.410 Awaish Kumar: So it is basically this kind of an Api endpoint which is just there
147 00:17:03.580 ⇒ 00:17:15.267 Awaish Kumar: and any, the any trigger which gets triggered on. Gtm, then that trigger basically calls this Api with the data which provides in the body. And
148 00:17:16.040 ⇒ 00:17:22.239 Awaish Kumar: then this endpoint in the back end runs this function to load it into the source.
149 00:17:23.599 ⇒ 00:17:24.489 Robert Tseng: Oh, okay.
150 00:17:24.969 ⇒ 00:17:31.139 Robert Tseng: yeah. I mean, I like, I’ve never set up a web book before. So I didn’t know that that’s how it works. I
151 00:17:31.629 ⇒ 00:17:35.659 Robert Tseng: I guess I’m not. I don’t want to derail this too much. I just
152 00:17:36.273 ⇒ 00:17:53.589 Robert Tseng: you know, we’re missing some data from web hooks. So let’s say, I wanted to like, get an order updated event we’re talking about like doctor errors in the pharmacy. Does that mean that we just go in and edit the source code on one of these existing web hooks. And we just add, like some more
153 00:17:53.939 ⇒ 00:17:56.049 Robert Tseng: traits that we want to pull in. Yeah.
154 00:17:56.050 ⇒ 00:18:13.250 Awaish Kumar: Yeah, we have to do 3 things. Number one, we we have to figure out. If there is a tag already. If not, we add a tag, and then we maybe add a trigger, and then we add this web hook in the segment. So after these 3 things we can like, add more events into our data.
155 00:18:14.360 ⇒ 00:18:15.020 Robert Tseng: Huh?
156 00:18:16.270 ⇒ 00:18:22.830 Robert Tseng: Okay. I also did not know we had to create a new tag for every web hook event.
157 00:18:24.620 ⇒ 00:18:26.979 Robert Tseng: I assume that the same
158 00:18:27.140 ⇒ 00:18:33.410 Robert Tseng: tag could be used multiple times, or like I I didn’t know it was a 1 to one like kind of
159 00:18:34.200 ⇒ 00:18:35.200 Robert Tseng: relationship here.
160 00:18:37.060 ⇒ 00:18:45.590 Awaish Kumar: I actually saw something. Yeah, this like, you can see here, segment order completed. Tag segment. Sign up tab.
161 00:18:48.530 ⇒ 00:18:55.779 Robert Tseng: Yeah, I mean. So I’ve clicked into these. I’ve looked at the triggers. I I’ve looked at the script, too. So I know, like what I guess
162 00:18:56.150 ⇒ 00:18:59.420 Robert Tseng: traits. They’re like trying to track with it
163 00:18:59.600 ⇒ 00:19:05.149 Robert Tseng: like for product added, or add to cart. For example, there’s like a events that’s like
164 00:19:05.330 ⇒ 00:19:08.739 Robert Tseng: product product added, we get the products.
165 00:19:09.496 ⇒ 00:19:10.800 Robert Tseng: I mean, I’m assuming.
166 00:19:11.430 ⇒ 00:19:18.679 Robert Tseng: I mean I and then the user id for that. So like it, kind of references like other, what is deal? The items?
167 00:19:19.880 ⇒ 00:19:20.460 Robert Tseng: Yeah.
168 00:19:20.460 ⇒ 00:19:26.380 Awaish Kumar: And also in the segment we, we have this thing called. So. This is, they are filtering here. If even if
169 00:19:26.824 ⇒ 00:19:30.279 Awaish Kumar: there is some other event which is going to trigger this.
170 00:19:30.450 ⇒ 00:19:49.830 Awaish Kumar: This is not going to perform anything because we are checking. If it’s order shipped to event. Only, then we process the data and it go goes to the order ship table. If there’s any other event which could triggers this one, then, like we don’t do anything. Basically. So it’s like, particularly for each event. We have seen
171 00:19:50.010 ⇒ 00:19:56.960 Awaish Kumar: separate web hook and the function and which separate separate trigger for every level.
172 00:19:57.680 ⇒ 00:19:58.560 Robert Tseng: I see.
173 00:19:59.820 ⇒ 00:20:00.610 Robert Tseng: Huh?
174 00:20:01.170 ⇒ 00:20:07.769 Robert Tseng: Okay. Well, I know, like, thank you for the explaining this. I think I kind of had to. I mean, I
175 00:20:08.720 ⇒ 00:20:13.000 Robert Tseng: guess I’m I’m wrong. So
176 00:20:14.250 ⇒ 00:20:16.580 Robert Tseng: I’m gonna try to. Okay. I see.
177 00:20:19.600 ⇒ 00:20:22.509 Robert Tseng: Oh, man, I can’t edit this view. Only,
178 00:20:27.040 ⇒ 00:20:31.590 Robert Tseng: okay. So if I can just take the screen over again.
179 00:20:33.560 ⇒ 00:20:37.740 Robert Tseng: This, okay, so this is what you’ve audited. I guess
180 00:20:38.370 ⇒ 00:20:42.610 Robert Tseng: this is what the ideal state is, from what I’ve seen
181 00:20:42.770 ⇒ 00:20:44.749 Robert Tseng: or for what I’ve I’ve created.
182 00:20:46.110 ⇒ 00:20:52.400 Robert Tseng: I think that there are some edits that we need to make here like we don’t have these events
183 00:20:53.025 ⇒ 00:21:06.020 Robert Tseng: like, I know we don’t have intake flow started like we don’t really have like a clear question answered. You know, as you know, we there’s a lot of stuff going on here. But we only really need to get this pre purchase stuff up and running like asap.
184 00:21:06.932 ⇒ 00:21:14.289 Robert Tseng: So yeah, I think if we could just get some clarity around. What or is it?
185 00:21:19.060 ⇒ 00:21:22.459 Robert Tseng: I thought I saw your stuff here earlier.
186 00:21:22.810 ⇒ 00:21:25.219 Awaish Kumar: Yeah, I also saw that hang on.
187 00:21:25.780 ⇒ 00:21:26.970 Awaish Kumar: Well, Aunt.
188 00:21:28.870 ⇒ 00:21:29.909 Robert Tseng: Actually work.
189 00:21:32.110 ⇒ 00:21:36.841 Robert Tseng: Well, I was just displaying that I don’t even know what where it was. Okay? Well, anyway, I think
190 00:21:38.100 ⇒ 00:21:44.819 Robert Tseng: yeah. So if I were to just kind of not just forward here, like if we could try to get these
191 00:21:45.110 ⇒ 00:21:49.589 Robert Tseng: up and running like just just the intake flow, I think that would be
192 00:21:50.310 ⇒ 00:21:53.039 Robert Tseng: that would be a good win like
193 00:21:53.250 ⇒ 00:21:55.169 Robert Tseng: as soon as possible, and then
194 00:21:55.370 ⇒ 00:22:04.780 Robert Tseng: we have to eventually get to these other ones. But like, yeah, I I, if we can just make this a smaller scope like we just want to get these events up.
195 00:22:06.380 ⇒ 00:22:12.682 Awaish Kumar: Okay, yeah, just to that, to do that, we have to understand like someone
196 00:22:13.950 ⇒ 00:22:23.610 Awaish Kumar: like, how their website is basically the tag manager is collaborating with website. And how the
197 00:22:23.810 ⇒ 00:22:29.800 Awaish Kumar: these triggers? Basically like, obviously, they are on some buttons. Right? So
198 00:22:29.920 ⇒ 00:22:33.770 Awaish Kumar: if there is some button gets clicked on the website in the back end.
199 00:22:33.980 ⇒ 00:22:40.459 Awaish Kumar: Tag manager reacts to that right? There is something, some development there as well.
200 00:22:40.590 ⇒ 00:22:49.130 Awaish Kumar: So we have to involve web development team or someone like that, because.
201 00:22:49.900 ⇒ 00:23:00.599 Awaish Kumar: like from tag manager, we cannot just directly say this was, it has to be behind some button or some click or something like something which triggers this flow, or whatever.
202 00:23:01.900 ⇒ 00:23:08.169 Robert Tseng: Okay, I will tag the right people and like, just
203 00:23:08.350 ⇒ 00:23:12.004 Robert Tseng: try to see if you can work with them directly.
204 00:23:14.420 ⇒ 00:23:18.310 Robert Tseng: so I’m not entirely sure what the right question to answer is.
205 00:23:23.950 ⇒ 00:23:30.870 Awaish Kumar: Yeah, it’s okay. Like, if I get to some like tech engineering person, I can talk with him. Maybe he can
206 00:23:30.990 ⇒ 00:23:35.299 Awaish Kumar: answer something with basically without those answer, maybe I can.
207 00:23:35.730 ⇒ 00:23:41.460 Robert Tseng: How? How should I phrase the question like, What what am I asking? I’m not. I don’t fully get it. So.
208 00:23:42.580 ⇒ 00:23:47.019 Awaish Kumar: Okay. So like, you can say we are trying to add some more
209 00:23:48.070 ⇒ 00:23:58.599 Awaish Kumar: events we are trying to. As what to say. Listen. More events regarding intact flow on the website. And we want to implement the tags and triggers.
210 00:23:58.920 ⇒ 00:24:04.000 Awaish Kumar: Hi on the Gtm and segment. So
211 00:24:04.530 ⇒ 00:24:08.559 Awaish Kumar: who would you love to meet someone from the Web Development team on.
212 00:24:08.560 ⇒ 00:24:09.480 Robert Tseng: Yeah, okay.
213 00:24:10.060 ⇒ 00:24:11.219 Awaish Kumar: Those tags!
214 00:24:30.080 ⇒ 00:24:31.750 Robert Tseng: Okay, I,
215 00:24:44.650 ⇒ 00:24:54.149 Robert Tseng: okay. So I think that’s clear. I don’t know. It seems like the lead engineer is on vacation this week, and then I don’t even know the other day. It is just like.
216 00:24:55.810 ⇒ 00:25:01.370 Robert Tseng: I don’t really know what he’s up to. But okay, so
217 00:25:01.720 ⇒ 00:25:07.840 Robert Tseng: that’s 1 piece of it. I know we have a few minutes left, and I just want to try to unblock as much as possible. So
218 00:25:09.163 ⇒ 00:25:15.850 Robert Tseng: that’ll kind of address 3 0 1 like that’s kind of addressing what we’re talking about here.
219 00:25:21.680 ⇒ 00:25:30.100 Robert Tseng: Yeah, I mean that kind of blocks this as well. I guess I’ll throw all these block
220 00:25:31.390 ⇒ 00:25:36.449 Robert Tseng: send desk. I’m just gonna cancel this.
221 00:25:42.240 ⇒ 00:25:43.889 Robert Tseng: What was the thing here?
222 00:25:49.910 ⇒ 00:26:01.209 Robert Tseng: Yeah, I feel like we’re just stuck. We’re waiting on bask to send more stuff. Rebecca hasn’t updated the sheet like, we’re just like stuck on data modeling today, which is kind of frustrating.
223 00:26:02.770 ⇒ 00:26:05.400 Robert Tseng: Hopefully, we can move forward in other areas.
224 00:26:07.280 ⇒ 00:26:14.810 Robert Tseng: Yeah, I mean, I’ve blocked off 2 h in my calendar like later this afternoon to try to like, just push on everything here. So
225 00:26:14.990 ⇒ 00:26:20.009 Robert Tseng: I’ll probably come back to this. But you know, assuming that you’re not able to
226 00:26:20.580 ⇒ 00:26:23.939 Robert Tseng: hook up with the right person, we might be stuck there.
227 00:26:26.670 ⇒ 00:26:33.670 Robert Tseng: In the meanwhile, other segment stuff like I’ve been studying like their customer, I/O
228 00:26:34.080 ⇒ 00:26:39.549 Robert Tseng: segments. So these are all of the custom segment. There’s a lot of stuff I have to like, go in and look at every single one.
229 00:26:40.950 ⇒ 00:26:43.800 Robert Tseng: I’m trying to make a decision, or like
230 00:26:44.310 ⇒ 00:26:53.889 Robert Tseng: figure out what should be what should stay in customer. I/O, what can we actually push further upstream? We either create those segments in the warehouse ourself?
231 00:26:54.571 ⇒ 00:27:02.929 Robert Tseng: Or we or we manage them through segment. So I think that’s like one part of like what the time I’ve set aside to do
232 00:27:03.210 ⇒ 00:27:13.459 Robert Tseng: I anything else wish I’m missing on like what we can do in the meanwhile, or or do you? Do you feel like you’re? I mean, I feel like, you understand, like the ask, like, we just really want to get these events going.
233 00:27:13.770 ⇒ 00:27:15.560 Robert Tseng: but we’re kind of stuck right.
234 00:27:16.640 ⇒ 00:27:25.170 Awaish Kumar: Yeah, like, these events are not there. So we have to implement the events first, st then we get the data and then work on modeling. So that’s like
235 00:27:27.310 ⇒ 00:27:28.520 Awaish Kumar: the greetings.
236 00:27:29.600 ⇒ 00:27:30.110 Robert Tseng: Okay.
237 00:27:31.710 ⇒ 00:27:33.429 Awaish Kumar: Good God! Yep.
238 00:27:38.840 ⇒ 00:27:45.410 Robert Tseng: Alright. I guess they’re the CTO. Is stepping in as like the tag manager Guy, and I know he’s around so.
239 00:27:46.075 ⇒ 00:27:49.029 Robert Tseng: I think maybe it’ll you’ll have to meet with him.
240 00:27:50.030 ⇒ 00:27:50.740 Awaish Kumar: Okay.
241 00:27:50.920 ⇒ 00:27:52.140 Awaish Kumar: Yeah. Sure.
242 00:28:02.330 ⇒ 00:28:05.799 Robert Tseng: Yeah, he’s nice. He’s nice. He understands me. I guess
243 00:28:06.460 ⇒ 00:28:13.449 Robert Tseng: I I feel like he doesn’t understand how segment works. To be honest, like, I’ve been talking right away. We’ll we’ll just get in a call. We’ll figure it out.
244 00:28:15.530 ⇒ 00:28:17.300 Robert Tseng: Okay, so
245 00:28:17.650 ⇒ 00:28:27.000 Robert Tseng: yeah, thank you. I think I know what we need to do. Yeah, sorry. I mean, I guess any of them letters are on. But yeah, if you need anything else to kind of keep pushing
246 00:28:27.210 ⇒ 00:28:32.959 Robert Tseng: your tickets along, especially on the reporting side, like these. Just like
247 00:28:33.300 ⇒ 00:28:36.770 Robert Tseng: message in slack. And we’ll we’ll keep. We’ll keep going from there.
248 00:28:41.270 ⇒ 00:28:48.530 Robert Tseng: Okay? Well, yeah, that’s it. Thanks. Everyone. Appreciate your time. Wish. Thank you for the explanation. There.
249 00:28:49.330 ⇒ 00:28:51.980 Robert Tseng: Yeah, hopefully, we’ll we’ll get the right person on the call.
250 00:28:53.660 ⇒ 00:28:54.570 Awaish Kumar: Okay. Thank you.
251 00:28:54.710 ⇒ 00:28:55.520 Robert Tseng: See you, Ron.