Meeting Title: DE-AE-AI Standup Date: 2025-11-18 Meeting participants: Gabriel Lam, Mustafa Raja, Awaish Kumar, Casie Aviles, Rico Rejoso, Samuel Roberts, Uttam Kumaran, Robert Tseng, Henry Zhao, Zoran Selinger, Amber Lin
WEBVTT
1 00:00:42.460 ⇒ 00:00:43.560 Mustafa Raja: Hey…
2 00:00:45.370 ⇒ 00:00:46.440 Gabriel Lam: Hello?
3 00:00:47.590 ⇒ 00:00:48.380 Mustafa Raja: How are you?
4 00:00:48.540 ⇒ 00:00:57.290 Gabriel Lam: I’m good, how are you? I wonder if people are still on the… Apparently there’s a call.
5 00:00:58.150 ⇒ 00:01:00.999 Gabriel Lam: At 9.30 for salmon.
6 00:01:01.640 ⇒ 00:01:02.590 Gabriel Lam: Utahan.
7 00:01:10.390 ⇒ 00:01:13.059 Mustafa Raja: Oh, so they would join or not, yeah?
8 00:01:15.720 ⇒ 00:01:19.150 Gabriel Lam: I think they’re just a little… they’re running… Over time.
9 00:14:33.290 ⇒ 00:14:40.069 Gabriel Lam: Okay, seems like they’re… they have a call, and it’s running really late. Mustafa and Casey, I…
10 00:14:41.090 ⇒ 00:14:47.640 Gabriel Lam: Wrote out a PRD, I put it in the chat. I have some questions about it, we can go over now.
11 00:14:47.910 ⇒ 00:14:51.370 Gabriel Lam: But, otherwise, you can also wait till later. Let me know what you guys think.
12 00:14:56.720 ⇒ 00:14:57.959 Mustafa Raja: I’m looking at it.
13 00:15:07.020 ⇒ 00:15:13.819 Gabriel Lam: I guess my main question is, on the… on the Forge, on the platform, I see, like, there’s a linear tickets agent.
14 00:15:14.910 ⇒ 00:15:18.560 Gabriel Lam: But it doesn’t really work, and then in the…
15 00:15:20.080 ⇒ 00:15:22.880 Gabriel Lam: Dashboard, or when we go to, like, client videos.
16 00:15:23.030 ⇒ 00:15:27.009 Gabriel Lam: Or, the Zoom… Calls that are saved.
17 00:15:27.260 ⇒ 00:15:31.670 Gabriel Lam: And then there’s a Create Linear Tickets tab. That also doesn’t work, so I just want to know…
18 00:15:34.370 ⇒ 00:15:35.090 Gabriel Lam: like.
19 00:15:35.870 ⇒ 00:15:39.819 Gabriel Lam: If you guys have any idea of what the existing system is for those.
20 00:15:40.620 ⇒ 00:15:45.609 Mustafa Raja: Yeah, so… So what happened with the one that was in the meetings?
21 00:15:49.280 ⇒ 00:15:54.849 Mustafa Raja: So I’m guessing you ran it, and it threw an error or something?
22 00:15:55.460 ⇒ 00:16:05.929 Gabriel Lam: Well, I ran it, and nothing happens, or I don’t see any tickets being made, maybe because… Yeah. Yeah.
23 00:16:05.930 ⇒ 00:16:08.500 Mustafa Raja: Which is…
24 00:16:08.500 ⇒ 00:16:11.839 Gabriel Lam: I don’t, I don’t know if there’s a… Sorry, Casey, what was that?
25 00:16:12.350 ⇒ 00:16:15.850 Casie Aviles: This is for the linear tickets generation, right?
26 00:16:16.550 ⇒ 00:16:18.030 Mustafa Raja: Yeah, the, the…
27 00:16:18.030 ⇒ 00:16:18.600 Casie Aviles: Okay.
28 00:16:18.930 ⇒ 00:16:22.340 Mustafa Raja: Create limit… create linear ticket stab 1.
29 00:16:23.840 ⇒ 00:16:32.710 Gabriel Lam: And then there’s also the AI tools linear tickets agent, which I tested, and I’m getting HTTP error, so I don’t know if…
30 00:16:33.560 ⇒ 00:16:37.859 Gabriel Lam: There’s a… there’s a bug, I don’t know if it’s worked for you guys before, but it’s not working for me.
31 00:16:38.800 ⇒ 00:16:39.460 Mustafa Raja: Yeah.
32 00:16:39.460 ⇒ 00:16:40.199 Gabriel Lam: I’m also just curious.
33 00:16:40.200 ⇒ 00:16:41.089 Mustafa Raja: Come on.
34 00:16:41.090 ⇒ 00:16:41.740 Gabriel Lam: Okay.
35 00:16:42.510 ⇒ 00:16:45.270 Mustafa Raja: Yeah, I just ran it, and…
36 00:16:51.600 ⇒ 00:16:57.319 Gabriel Lam: I mean, if you guys built this, then I’m just curious to know, you know, what it’s taking at the moment, and…
37 00:16:57.810 ⇒ 00:16:59.400 Mustafa Raja: Oh, so…
38 00:16:59.800 ⇒ 00:17:11.490 Mustafa Raja: Right now, it just takes, how our linear teams are structured. So, what are the teams and, what are the members in the teams?
39 00:17:11.540 ⇒ 00:17:25.839 Mustafa Raja: And then it takes in the transcript, and then tries to infer which team does this meeting belong to, right? Yeah. And then, creates tickets. So let me share my screen, actually.
40 00:17:25.849 ⇒ 00:17:27.369 Gabriel Lam: I appreciate that. Thank you.
41 00:17:30.460 ⇒ 00:17:31.100 Mustafa Raja: Right.
42 00:17:36.750 ⇒ 00:17:37.600 Mustafa Raja: Okay.
43 00:17:37.800 ⇒ 00:17:41.109 Mustafa Raja: Okay, so this, this is what it would look like.
44 00:17:41.320 ⇒ 00:17:44.110 Mustafa Raja: Okay. If it ran successfully.
45 00:17:44.110 ⇒ 00:17:44.700 Gabriel Lam: Okay.
46 00:17:44.700 ⇒ 00:17:45.840 Mustafa Raja: So I just ran it.
47 00:17:46.640 ⇒ 00:17:47.470 Gabriel Lam: Okay.
48 00:17:50.830 ⇒ 00:17:55.210 Mustafa Raja: And then here, we can push the ticket to linear, but…
49 00:17:55.850 ⇒ 00:17:58.559 Mustafa Raja: what it does is it.
50 00:18:10.950 ⇒ 00:18:12.450 Gabriel Lam: Sorry, not sure if you cut off.
51 00:18:13.490 ⇒ 00:18:14.430 Casie Aviles: Yeah, yeah.
52 00:18:15.490 ⇒ 00:18:16.010 Casie Aviles: huh?
53 00:18:20.520 ⇒ 00:18:22.810 Casie Aviles: Do you reckon? There you go.
54 00:18:25.170 ⇒ 00:18:26.160 Mustafa Raja: Sorry.
55 00:18:26.160 ⇒ 00:18:27.240 Gabriel Lam: No worries.
56 00:18:28.340 ⇒ 00:18:36.820 Mustafa Raja: I was talking, and then I… and then I forget that no one’s answering, so… Yeah.
57 00:18:37.600 ⇒ 00:18:44.129 Mustafa Raja: Let me share again. Okay, okay, so this is, this is how the interface would look like if it ran successfully for you.
58 00:18:44.130 ⇒ 00:18:44.790 Gabriel Lam: Yep.
59 00:18:44.790 ⇒ 00:18:50.290 Mustafa Raja: So here we can accept, and push the tickets to… to linear, and we see that…
60 00:18:50.470 ⇒ 00:19:02.220 Mustafa Raja: This is a meeting with Lilo, so, I believe this would be the right team to assign it to, for now, since we don’t have, specifically Lilo team, right?
61 00:19:02.450 ⇒ 00:19:03.000 Gabriel Lam: Yep.
62 00:19:03.780 ⇒ 00:19:11.449 Mustafa Raja: Anyways, what it takes in is the linear teams, and then it knows which members belong to which team.
63 00:19:11.600 ⇒ 00:19:29.230 Mustafa Raja: And then it also takes in the transcript for the meeting, and then it infers, okay, which, which ticket it needs to create, and for each ticket, which team and which member of the team should the ticket belong to.
64 00:19:29.770 ⇒ 00:19:30.430 Gabriel Lam: Gotcha.
65 00:19:30.430 ⇒ 00:19:35.299 Mustafa Raja: That’s pretty much the gist of what we have right now, and it’s in here.
66 00:19:36.420 ⇒ 00:19:40.460 Mustafa Raja: Let me also tag that, so you can take a look at the workflow.
67 00:19:40.460 ⇒ 00:19:41.529 Gabriel Lam: Oh, yeah.
68 00:19:44.190 ⇒ 00:19:44.889 Gabriel Lam: And so right now.
69 00:19:44.890 ⇒ 00:19:45.540 Casie Aviles: It’s just…
70 00:19:46.180 ⇒ 00:19:47.400 Gabriel Lam: Sorry, go Casey.
71 00:19:47.810 ⇒ 00:19:54.150 Casie Aviles: Oh, yeah, the one under AI Tools is the one that’s causing… that’s showing the error, right? Yeah.
72 00:19:55.950 ⇒ 00:20:01.779 Gabriel Lam: Okay. Yeah, when I try to press… go to the Create Linear Tickets tab under a video.
73 00:20:02.160 ⇒ 00:20:04.379 Gabriel Lam: Like, nothing shows up, so I’m not sure.
74 00:20:04.840 ⇒ 00:20:07.689 Gabriel Lam: Why that’s the case, or if it’s just not running for me.
75 00:20:08.240 ⇒ 00:20:11.209 Gabriel Lam: But it seems like it’s working from Mustafa, so… that’s great.
76 00:20:11.210 ⇒ 00:20:20.489 Mustafa Raja: This is the one for, that is with the, meeting. I haven’t tested this yet.
77 00:20:20.490 ⇒ 00:20:22.200 Casie Aviles: Yeah, that’s not working, that one.
78 00:20:23.240 ⇒ 00:20:24.869 Mustafa Raja: Okay, we can, we can negotiate on that.
79 00:20:24.870 ⇒ 00:20:25.450 Gabriel Lam: Yeah.
80 00:20:25.590 ⇒ 00:20:29.200 Gabriel Lam: The one with the meeting isn’t working for me either, so I don’t know if it’s…
81 00:20:29.480 ⇒ 00:20:31.539 Gabriel Lam: Yeah, of course, some meetings, I don’t know if it’s…
82 00:20:31.540 ⇒ 00:20:34.720 Mustafa Raja: Yeah, for some meetings, it might do that.
83 00:20:35.030 ⇒ 00:20:41.459 Mustafa Raja: We can actually take a look at executions and see what happened.
84 00:20:42.470 ⇒ 00:20:45.389 Mustafa Raja: Oh, let’s just see where it is.
85 00:20:46.060 ⇒ 00:20:46.820 Casie Aviles: One of the tools.
86 00:20:47.520 ⇒ 00:20:50.540 Mustafa Raja: This is the… Oh.
87 00:20:51.220 ⇒ 00:20:55.299 Mustafa Raja: So this is the workflow, let me tag that in here.
88 00:21:12.510 ⇒ 00:21:19.339 Mustafa Raja: Okay… yeah, this is the workflow, and essentially.
89 00:21:20.590 ⇒ 00:21:21.790 Gabriel Lam: Okay.
90 00:21:22.330 ⇒ 00:21:30.719 Mustafa Raja: One of these, one of these, sources is for this one, and the other one is for this one.
91 00:21:30.720 ⇒ 00:21:31.410 Gabriel Lam: Got it.
92 00:21:31.990 ⇒ 00:21:34.120 Mustafa Raja: And then,
93 00:21:34.380 ⇒ 00:21:46.679 Mustafa Raja: the only extra part is this. If it identifies that this ticket is for a client team, it will go ahead and look into the, client hub.
94 00:21:46.840 ⇒ 00:21:57.040 Mustafa Raja: To sort of find some extra context on the ticket. Because, right now you can see that the descriptions are pretty small.
95 00:21:57.270 ⇒ 00:21:57.590 Gabriel Lam: Yeah.
96 00:21:57.590 ⇒ 00:22:07.340 Mustafa Raja: And this is something that we did receive feedback about from PM Team, that they would want the descriptions to be in a certain format.
97 00:22:07.800 ⇒ 00:22:08.350 Gabriel Lam: Yep.
98 00:22:08.350 ⇒ 00:22:10.700 Mustafa Raja: I think it should be in AIPM.
99 00:22:44.930 ⇒ 00:22:46.489 Mustafa Raja: Yeah, I guess so.
100 00:22:58.120 ⇒ 00:23:03.889 Mustafa Raja: Yeah, I guess… I guess we can take a look, at where the review is.
101 00:23:04.620 ⇒ 00:23:07.749 Mustafa Raja: But it was a format that the PM team wants.
102 00:23:07.750 ⇒ 00:23:08.520 Gabriel Lam: That they wanted.
103 00:23:08.520 ⇒ 00:23:10.450 Mustafa Raja: This description, and yeah.
104 00:23:10.960 ⇒ 00:23:11.810 Mustafa Raja: Yeah.
105 00:23:12.960 ⇒ 00:23:18.080 Gabriel Lam: And this is just making new tickets, it doesn’t edit any existing tickets?
106 00:23:18.080 ⇒ 00:23:22.790 Mustafa Raja: Yeah, yeah, currently it doesn’t… it doesn’t know about what exists.
107 00:23:22.900 ⇒ 00:23:29.900 Mustafa Raja: already in the board. It just goes ahead and… this isn’t actually creating one, this is suggesting.
108 00:23:30.340 ⇒ 00:23:31.030 Gabriel Lam: Hmm.
109 00:23:31.450 ⇒ 00:23:39.719 Mustafa Raja: So only if you press approve. Then it goes. If I press this one, these tickets will go ahead, in the linear board.
110 00:23:39.980 ⇒ 00:23:40.750 Gabriel Lam: I see.
111 00:23:51.190 ⇒ 00:23:53.450 Mustafa Raja: When did you try this out?
112 00:23:53.820 ⇒ 00:23:56.100 Gabriel Lam: I… I tried it just now.
113 00:23:56.100 ⇒ 00:23:56.660 Mustafa Raja: pumped.
114 00:23:57.050 ⇒ 00:23:58.780 Mustafa Raja: I think it bugs for the.
115 00:23:58.780 ⇒ 00:24:02.540 Gabriel Lam: Stand-up meetings, when there’s many… clients being.
116 00:24:02.540 ⇒ 00:24:03.750 Mustafa Raja: Yeah.
117 00:24:05.610 ⇒ 00:24:08.689 Mustafa Raja: Okay, so it’s 25 right now…
118 00:24:11.510 ⇒ 00:24:12.469 Gabriel Lam: Oh, hey, Sam.
119 00:24:13.200 ⇒ 00:24:19.360 Samuel Roberts: Hey, yeah, sorry, that was the whole… they were getting access to a whole bunch of stuff, so there was a bunch of people on the call, and…
120 00:24:19.590 ⇒ 00:24:27.079 Samuel Roberts: they’re using Okta, so it’s… they have to jump through a whole bunch of hoops and stuff, so… once we finally got everything sorted, we were able to get off.
121 00:24:27.350 ⇒ 00:24:30.250 Gabriel Lam: Yep. I was just going over,
122 00:24:30.430 ⇒ 00:24:42.479 Gabriel Lam: like, a brief PRD that I wrote yesterday, I think I can do massive changes, because it… things were bugged for me yesterday, and I was like, oh, things aren’t working, but then Mustaf is showing me what the workflow is now, and…
123 00:24:42.640 ⇒ 00:24:47.799 Samuel Roberts: I think we’re a lot further along than I thought, so… Got it, yeah. I’ll make some changes.
124 00:24:47.930 ⇒ 00:24:52.180 Gabriel Lam: And then… Depending on your guys’ capacity, I can…
125 00:24:52.720 ⇒ 00:24:55.000 Gabriel Lam: I can send out a bunch of things that we could do.
126 00:24:56.390 ⇒ 00:24:57.359 Gabriel Lam: But I know.
127 00:24:57.360 ⇒ 00:25:03.749 Mustafa Raja: Yeah, I guess also we can… we can, we can, further take a look why… why it broke for you.
128 00:25:03.750 ⇒ 00:25:04.170 Gabriel Lam: Yeah.
129 00:25:05.340 ⇒ 00:25:10.060 Mustafa Raja: Yeah, but now this is saying, yeah, all of them ran good, so…
130 00:25:10.330 ⇒ 00:25:10.960 Gabriel Lam: Got it.
131 00:25:11.820 ⇒ 00:25:12.440 Mustafa Raja: Yeah.
132 00:25:12.680 ⇒ 00:25:16.009 Samuel Roberts: How complex is that… is that flow? Is it…
133 00:25:16.830 ⇒ 00:25:22.090 Mustafa Raja: Not, no, not… It isn’t much complex, I believe.
134 00:25:22.090 ⇒ 00:25:22.660 Samuel Roberts: Okay.
135 00:25:22.960 ⇒ 00:25:23.500 Samuel Roberts: Okay.
136 00:25:23.500 ⇒ 00:25:24.619 Mustafa Raja: Yeah, pretty simple.
137 00:25:25.300 ⇒ 00:25:27.920 Samuel Roberts: Is it worth moving to Amazra as part of this PRD, if we’re.
138 00:25:27.920 ⇒ 00:25:28.239 Mustafa Raja: Oh, yeah.
139 00:25:28.240 ⇒ 00:25:29.959 Samuel Roberts: Or is that too much? Okay.
140 00:25:30.590 ⇒ 00:25:32.110 Mustafa Raja: Yes, I want to do that.
141 00:25:32.520 ⇒ 00:25:33.009 Samuel Roberts: Okay, great.
142 00:25:33.010 ⇒ 00:25:33.740 Mustafa Raja: I believe.
143 00:25:33.740 ⇒ 00:25:36.779 Samuel Roberts: I just wasn’t sure if it was, like, a this week thing or not.
144 00:25:37.060 ⇒ 00:25:38.410 Samuel Roberts: Yeah, okay.
145 00:25:38.410 ⇒ 00:25:42.180 Gabriel Lam: And for Utam, Awish was here earlier,
146 00:25:43.040 ⇒ 00:25:49.179 Gabriel Lam: I think he dropped off just because we were kind of waiting for a bit, but just letting you know that he was here earlier.
147 00:25:49.180 ⇒ 00:25:56.359 Uttam Kumaran: Okay, perfect. Yeah, maybe I just take a couple minutes. So, yeah, I think kind of a couple of folks are gonna be,
148 00:25:57.090 ⇒ 00:26:01.369 Uttam Kumaran: moving to the next meeting, but just while I have you guys,
149 00:26:01.620 ⇒ 00:26:08.159 Uttam Kumaran: I guess I could ask, Mustafa, so for default stuff, you’re moving that along, like, no problem there, right?
150 00:26:08.790 ⇒ 00:26:19.820 Mustafa Raja: Yeah, I’ll have the people analysis ready today, and, for Hani Stinger, I, I looked into it, and,
151 00:26:19.980 ⇒ 00:26:28.739 Mustafa Raja: DBT and 5Fran have some sort of partnership, and what they do is, for their connectors, they build…
152 00:26:28.740 ⇒ 00:26:31.330 Uttam Kumaran: What is… what is the, like, what’s the… what’s the ask?
153 00:26:32.360 ⇒ 00:26:34.300 Mustafa Raja: The staging models.
154 00:26:36.850 ⇒ 00:26:38.330 Uttam Kumaran: Oh, who asked for that?
155 00:26:39.530 ⇒ 00:26:42.229 Mustafa Raja: Oh, there’s a ticket for that, assigned to me.
156 00:26:43.470 ⇒ 00:26:44.710 Uttam Kumaran: From Robert?
157 00:26:46.050 ⇒ 00:26:49.040 Mustafa Raja: I believe it is from you…
158 00:26:50.710 ⇒ 00:26:54.499 Uttam Kumaran: Yeah, don’t, no, don’t work on that, no worries.
159 00:26:56.050 ⇒ 00:26:56.790 Mustafa Raja: Okay, okay.
160 00:26:56.790 ⇒ 00:27:00.769 Uttam Kumaran: Hold on, let me see, yeah, because I don’t know… I feel like for hunters…
161 00:27:00.770 ⇒ 00:27:01.380 Mustafa Raja: There’s much…
162 00:27:01.380 ⇒ 00:27:04.599 Uttam Kumaran: Whatever Robert… whatever Robert needs, don’t work on anything else.
163 00:27:06.150 ⇒ 00:27:11.849 Mustafa Raja: Oh, I discussed it with Robert, and he said that, yeah, go ahead and work on it, so…
164 00:27:15.380 ⇒ 00:27:17.259 Mustafa Raja: Yeah, let me know if I should, or…
165 00:27:17.260 ⇒ 00:27:23.280 Uttam Kumaran: Yeah, I wouldn’t say these are staging models, though. I would say build intermediate models.
166 00:27:25.370 ⇒ 00:27:30.630 Uttam Kumaran: And not int, so I would…
167 00:27:31.000 ⇒ 00:27:39.240 Uttam Kumaran: So one is I would follow, are we doing tea?
168 00:27:40.030 ⇒ 00:27:41.200 Uttam Kumaran: Hold on.
169 00:27:45.990 ⇒ 00:27:47.990 Uttam Kumaran: So follow,
170 00:27:54.900 ⇒ 00:27:56.510 Uttam Kumaran: Like, this doc.
171 00:27:57.800 ⇒ 00:27:59.899 Uttam Kumaran: This is how we model dbt.
172 00:28:00.420 ⇒ 00:28:08.439 Uttam Kumaran: And then… I… I… just ask, ask questions, so don’t use the Fivetran DBT stuff.
173 00:28:09.840 ⇒ 00:28:10.830 Mustafa Raja: Oh, okay.
174 00:28:10.830 ⇒ 00:28:18.899 Uttam Kumaran: Yeah, I would ask Awayish how to set up dbt, but you can just go ahead and, like, initialize
175 00:28:19.110 ⇒ 00:28:25.140 Uttam Kumaran: within the repo. I guess, like, the ask is just to, like, set up so models are running.
176 00:28:25.890 ⇒ 00:28:27.059 Uttam Kumaran: In Mother Duck?
177 00:28:29.880 ⇒ 00:28:30.760 Mustafa Raja: Yeah.
178 00:28:32.580 ⇒ 00:28:37.250 Uttam Kumaran: Yeah, I mean, I would…
179 00:28:37.680 ⇒ 00:28:51.080 Uttam Kumaran: we probably need to, honestly, create, like, a doc on, like, how to set it up, but we… we already have, like, boilerplate dbt code that you should just start to leverage, so if you go into,
180 00:28:51.180 ⇒ 00:28:52.280 Uttam Kumaran: GitHub.
181 00:28:52.540 ⇒ 00:28:59.990 Uttam Kumaran: there is a template repo that you can start to use. Call, new client.
182 00:29:02.740 ⇒ 00:29:09.780 Uttam Kumaran: Yeah, and just… I would just say anything on data, just ask before going down, because we do this 100 times a week.
183 00:29:10.450 ⇒ 00:29:11.590 Uttam Kumaran: But…
184 00:29:11.590 ⇒ 00:29:12.110 Mustafa Raja: Okay.
185 00:29:12.110 ⇒ 00:29:18.009 Uttam Kumaran: Definitely, I know it’s new for you, but yeah, don’t use the Fivetran thing. It’s… it’s not… it’s, yeah, not worth it.
186 00:29:19.320 ⇒ 00:29:20.120 Mustafa Raja: Oh, okay.
187 00:29:20.980 ⇒ 00:29:29.939 Uttam Kumaran: And then ask questions. This, this repo has, like, all of the structure for dbt, so I would just suggest starting here.
188 00:29:31.070 ⇒ 00:29:36.179 Uttam Kumaran: And then… If we want, me, you, and Awash can hop on, or… yeah.
189 00:29:38.440 ⇒ 00:29:43.529 Uttam Kumaran: Cool, I guess… I know you guys have to hop to the next thing, I guess,
190 00:29:44.000 ⇒ 00:29:47.369 Uttam Kumaran: Casey, any… anything that we could… I can be helpful with?
191 00:29:49.060 ⇒ 00:29:57.260 Casie Aviles: Hmm… No, I’m just working on yesterday, the Eden stuff. I already asked Henry for some feedback, and…
192 00:29:57.450 ⇒ 00:29:59.130 Casie Aviles: He gave me so-and-so.
193 00:29:59.390 ⇒ 00:30:02.740 Casie Aviles: I’m just going to look into that next.
194 00:30:03.360 ⇒ 00:30:07.269 Casie Aviles: And then, yeah, for the spike, I’m still working on that.
195 00:30:07.530 ⇒ 00:30:13.529 Casie Aviles: Colonel, I managed… I’m also asking contextual if I could…
196 00:30:13.670 ⇒ 00:30:19.170 Casie Aviles: That’s what they have, although I think it’s still gonna… Their beta phase, so…
197 00:30:19.630 ⇒ 00:30:21.430 Uttam Kumaran: Okay. We’ll see, and…
198 00:30:21.640 ⇒ 00:30:28.340 Casie Aviles: Yeah, I’ll just, look into more tools, and hopefully get something to test today.
199 00:30:29.480 ⇒ 00:30:30.130 Uttam Kumaran: Okay.
200 00:30:30.450 ⇒ 00:30:31.980 Robert Tseng: Am I in the wrong meeting room?
201 00:30:32.600 ⇒ 00:30:36.259 Uttam Kumaran: No. Why? It’s probably the same link in both.
202 00:30:36.260 ⇒ 00:30:37.429 Samuel Roberts: It’s the same link, yeah.
203 00:30:37.430 ⇒ 00:30:38.100 Uttam Kumaran: Yeah.
204 00:30:40.350 ⇒ 00:30:43.240 Uttam Kumaran: Why was your question?
205 00:30:45.820 ⇒ 00:30:46.740 Uttam Kumaran: Like, my…
206 00:30:46.740 ⇒ 00:30:49.140 Robert Tseng: Might be, I don’t know, I’m… hello, can anyone hear me?
207 00:30:49.140 ⇒ 00:30:52.129 Uttam Kumaran: Yeah, yeah, yeah, the meeting’s the same link for both meetings.
208 00:30:52.130 ⇒ 00:30:53.410 Robert Tseng: testing, testing, testing.
209 00:30:53.410 ⇒ 00:30:55.030 Uttam Kumaran: Your…
210 00:30:55.470 ⇒ 00:30:57.509 Robert Tseng: No one can hear me.
211 00:30:58.580 ⇒ 00:30:59.999 Samuel Roberts: We can all hear you, can you hear us?
212 00:31:00.000 ⇒ 00:31:06.569 Uttam Kumaran: I can’t hear Well, we can hear… I can hear you, but you… I… You can’t hear us.
213 00:31:07.050 ⇒ 00:31:07.880 Robert Tseng: Huh.
214 00:31:13.630 ⇒ 00:31:18.189 Uttam Kumaran: Maybe, Sam, we can jump and plan out CTA, and I could…
215 00:31:18.190 ⇒ 00:31:18.810 Samuel Roberts: Sounds good.
216 00:31:18.810 ⇒ 00:31:23.300 Uttam Kumaran: Okay, and I’ll… I guess my… maybe the last question…
217 00:31:23.610 ⇒ 00:31:27.990 Uttam Kumaran: Awash, Neet, do you need anything from me, for Vidra?
218 00:31:29.310 ⇒ 00:31:30.830 Awaish Kumar: Yeah, GitHub Access.
219 00:31:31.730 ⇒ 00:31:33.350 Uttam Kumaran: Okay, yeah, I asked them.
220 00:31:33.820 ⇒ 00:31:40.800 Awaish Kumar: And then what, like, what is after the… Job is set up.
221 00:31:41.330 ⇒ 00:31:43.440 Awaish Kumar: Is there anything you want me to work on?
222 00:31:43.710 ⇒ 00:31:49.310 Uttam Kumaran: Yes, yes.
223 00:31:49.450 ⇒ 00:31:51.290 Uttam Kumaran: Long story short,
224 00:31:51.670 ⇒ 00:31:58.459 Uttam Kumaran: So, I guess, if me use… I guess me, Sam, and Awash, if we want to hop off, I guess, Robert, do you need Awash on this next part?
225 00:31:58.760 ⇒ 00:32:04.859 Robert Tseng: I mean, I, I, I, I don’t… Next off, so yeah.
226 00:32:05.160 ⇒ 00:32:09.270 Uttam Kumaran: Okay, cool. Then, Sam, me and Awash can hop off, and then I’ll give it to me.
227 00:32:09.760 ⇒ 00:32:14.389 Henry Zhao: Eventually, I needed some ways to ask for some Eden help, so… I don’t know how we want to do that.
228 00:32:15.840 ⇒ 00:32:20.540 Robert Tseng: Well then, yeah, you should keep them on the call. I mean, for me, I just assume that I don’t need to talk to them, but…
229 00:32:20.860 ⇒ 00:32:33.569 Uttam Kumaran: I mean, but if it’s not, like, part… if you… if you can just do that with a wish and call a wish on your own time. Okay, cool. Better. Alright, okay, thanks. Robert, I’m just gonna make you the host of this.
230 00:32:33.570 ⇒ 00:32:36.450 Robert Tseng: Okay, so this is, like, the right meeting room. Okay.
231 00:32:36.450 ⇒ 00:32:39.180 Samuel Roberts: It’s the same link, yeah, it was just… it going to each other.
232 00:32:39.180 ⇒ 00:32:44.829 Uttam Kumaran: Oh, cool. Rico, Rico, you’re the host, so I’ll leave you in here, and whatever. Okay. Alright.
233 00:32:44.980 ⇒ 00:32:46.270 Robert Tseng: Excellent. See ya!
234 00:32:48.450 ⇒ 00:32:53.350 Robert Tseng: Okay, cool. Let’s… do this.
235 00:32:53.780 ⇒ 00:32:57.810 Robert Tseng: Is Amber still out Anyone know?
236 00:33:00.050 ⇒ 00:33:02.819 Robert Tseng: I was hoping she’d be on this call. Maybe I’ll ping her.
237 00:33:08.070 ⇒ 00:33:21.180 Robert Tseng: Okay, well, yeah, let’s just kind of go into Eden. Thanks for kind of adding some tickets. I think we’re at, like, 66. It seems off. There’s, like, some stuff that’s stale, so we’re just gonna kind of go through more line by line.
238 00:33:21.260 ⇒ 00:33:29.020 Robert Tseng: away from the lottery tickets, I’m not gonna cover. Casey, I know you were mentioning that spike. Did you already take over this?
239 00:33:29.780 ⇒ 00:33:32.019 Casie Aviles: Yeah, they should be in progress.
240 00:33:32.390 ⇒ 00:33:34.089 Robert Tseng: Okay, so this should be in progress.
241 00:33:34.090 ⇒ 00:33:36.130 Casie Aviles: And still, same due date?
242 00:33:36.960 ⇒ 00:33:37.610 Casie Aviles: Yes.
243 00:33:37.780 ⇒ 00:33:41.200 Robert Tseng: Alright, I didn’t see any comments. What’s, like, what’s kind of the update here?
244 00:33:43.480 ⇒ 00:33:52.120 Casie Aviles: I just… Included this spread document, and I’m just talking to several… Then there’s, like, contextual…
245 00:33:52.250 ⇒ 00:33:54.450 Casie Aviles: And I’ll have, like, a demo with Bond.
246 00:33:54.850 ⇒ 00:33:58.550 Casie Aviles: attested, but around Thursday, I believe, yeah.
247 00:33:58.550 ⇒ 00:33:59.660 Robert Tseng: Okay, cool.
248 00:34:00.570 ⇒ 00:34:05.339 Robert Tseng: Alright, we’ll move on. So, Henry, yes, you got a lot of stuff here, so I want to make sure that we’re…
249 00:34:05.480 ⇒ 00:34:17.619 Robert Tseng: I think, kind of, what I’m thinking is, I guess when Rico and Amber are on, for, like, the stuff that’s blocked, I mean, I feel like a lot of the time it’s just blocked on the same things, and it requires us, kind of.
250 00:34:18.320 ⇒ 00:34:21.389 Robert Tseng: talking to somebody, so… I mean, I think…
251 00:34:21.880 ⇒ 00:34:40.779 Robert Tseng: the owner of the ticket should know what the blocker is, but maybe, like, we will need, kind of, PMs to set up, like, the, set up a meeting, or try to just make sure that these are the things that need to be followed up on until they’re no longer blocked. So, maybe slightly different from the way that,
252 00:34:40.780 ⇒ 00:34:46.200 Robert Tseng: who John runs this, like, I know he’s been asking you guys to, like, kind of share, like, the whole summaries, but…
253 00:34:46.239 ⇒ 00:34:54.159 Robert Tseng: really, I don’t think I need a daily update on every ticket, I just care about, like, whether or not we’re getting the things that are blocked unblocked, so…
254 00:34:54.350 ⇒ 00:35:00.050 Robert Tseng: Yeah, so we’ll just kind of go through this just to get a feel for it. So, like, with this one,
255 00:35:00.920 ⇒ 00:35:03.109 Robert Tseng: Yeah, what’s the blocker here on this, Henry?
256 00:35:03.360 ⇒ 00:35:04.390 Henry Zhao: Yeah, so this is the vial…
257 00:35:04.390 ⇒ 00:35:09.380 Robert Tseng: Same, same one, yeah. So, did we, like, have any, any progress on this?
258 00:35:09.520 ⇒ 00:35:12.559 Henry Zhao: Brad is, asking to set up a call with Zach from Bass.
259 00:35:13.340 ⇒ 00:35:15.020 Robert Tseng: Okay,
260 00:35:15.940 ⇒ 00:35:22.820 Robert Tseng: Well, so what I’m gonna do is I’m literally just gonna go into Bask Channel, and I’m going to…
261 00:35:23.510 ⇒ 00:35:27.130 Robert Tseng: Say… Oops.
262 00:35:28.950 ⇒ 00:35:33.570 Robert Tseng: Sack… Brad and Henry.
263 00:35:34.960 ⇒ 00:35:41.060 Robert Tseng: Third, we’re trying to… I guess, no, it’s not everyone’s seeing my full screen.
264 00:35:46.800 ⇒ 00:35:49.850 Robert Tseng: Let me set up a call. Whoa!
265 00:35:52.140 ⇒ 00:36:01.680 Robert Tseng: To discuss our progress on… File size… Orders, mapping…
266 00:36:02.580 ⇒ 00:36:04.759 Robert Tseng: Okay, then you guys kind of take it from there.
267 00:36:04.870 ⇒ 00:36:08.970 Robert Tseng: Yeah, so, ping’s back, back door.
268 00:36:09.150 ⇒ 00:36:14.339 Robert Tseng: Great. Alright, so that kind of just saves, like… I mean, Rico, you don’t have to… and Amber doesn’t have to do that then.
269 00:36:14.460 ⇒ 00:36:18.540 Henry Zhao: be fine. Sometimes, like, I just… I need to be the one to send it, so I’m okay with that.
270 00:36:18.620 ⇒ 00:36:21.480 Robert Tseng: Alright, what about this one? What’s the blocker here?
271 00:36:21.480 ⇒ 00:36:24.430 Henry Zhao: We need orders sent to pharmacy, but not yet shipped from Basque.
272 00:36:25.640 ⇒ 00:36:29.139 Robert Tseng: RFC, but not been able to ship from Basque, so…
273 00:36:29.140 ⇒ 00:36:32.709 Henry Zhao: Yeah, I give a list of all the things we need from Basque to Brad, and there’s, like, 4 things.
274 00:36:33.720 ⇒ 00:36:40.519 Robert Tseng: Okay, is this documented? Like, kind of, you met with Brad last week, so what was, like, kind of the takeaway there? I didn’t watch the recording.
275 00:36:41.510 ⇒ 00:36:49.019 Henry Zhao: Just that we need vial size and all this other stuff to unblock all of the… a lot of the pharmacy analysis we want to do.
276 00:36:50.390 ⇒ 00:36:51.280 Robert Tseng: Okay, so…
277 00:36:51.530 ⇒ 00:37:07.209 Robert Tseng: I mean, with Zach Bask, like, you send him a list of things, he’s not gonna action any of them. You have to be able to tie it to impact, and it has to be kind of in a calling-out way. You can run it by me before, but… I guess Dave Milani’s not on this call, but in the past, like, when I wanted him to add…
278 00:37:07.430 ⇒ 00:37:13.390 Robert Tseng: like, transaction ID to orders, because that wasn’t there before. I…
279 00:37:13.470 ⇒ 00:37:31.330 Robert Tseng: kind of shared how there were all these delinquent transactions that were not mapped to orders. It had, like, X dollar amount revenue, so, you know, I kind of flagged it, like, we’re mis… we risk risk reporting on whatever. He didn’t like that, because it makes it sound like… but it makes… it makes him, like.
280 00:37:31.490 ⇒ 00:37:49.659 Robert Tseng: itchy, like, because ELT will see that, and they’ll be like, what? This is the magnitude of not having this? And it forced him to kind of prioritize it. So, yeah, I feel like, you know, we can’t just keep coming up with a longer and longer list, like, we have to give him a sense of the urgency by doing the…
281 00:37:49.840 ⇒ 00:37:52.260 Robert Tseng: estimations ourselves, so…
282 00:37:52.660 ⇒ 00:37:53.470 Henry Zhao: So what if, so what if.
283 00:37:53.470 ⇒ 00:37:53.870 Robert Tseng: Yeah.
284 00:37:53.870 ⇒ 00:38:03.109 Henry Zhao: So I need your feedback. One of the things we need is if a prescription gets transferred to a different pharmacy. To me, that’s not that big of a deal, because it’s not happening that often.
285 00:38:03.110 ⇒ 00:38:15.640 Henry Zhao: But, I believe that the stakeholders that are looking at our dashboards by delivery state are not going to trust our data if they see, like, California for Eden Pharmacy, and we know that Eden Pharmacy doesn’t do California.
286 00:38:15.680 ⇒ 00:38:20.249 Robert Tseng: Yeah. So they told me, like, unless you fix this little issue, like, I’m not gonna trust your dashboard.
287 00:38:20.280 ⇒ 00:38:23.669 Henry Zhao: So, what do I rank that in terms of priority?
288 00:38:23.900 ⇒ 00:38:25.440 Robert Tseng: Why is it misreporting?
289 00:38:25.820 ⇒ 00:38:28.950 Robert Tseng: Just because the prescription didn’t, like, move, like, we didn’t…
290 00:38:28.950 ⇒ 00:38:36.719 Henry Zhao: Yeah, because it was initially sent to a pharmacy… it was initially sent to Eden Pharmacy, but then they couldn’t fill it, so they sent it to a different pharmacy that does do California.
291 00:38:37.270 ⇒ 00:38:39.939 Robert Tseng: Why can we not do that ourselves?
292 00:38:40.390 ⇒ 00:38:43.260 Henry Zhao: Because we don’t have that data from BASC, if it transfers pharmacy.
293 00:38:43.260 ⇒ 00:38:45.989 Robert Tseng: We don’t know if it transfers.
294 00:38:48.040 ⇒ 00:38:51.010 Robert Tseng: Okay, I mean, I wonder if there’s a…
295 00:38:52.350 ⇒ 00:39:03.079 Robert Tseng: in the order updated, we can’t see that it comes from a different pharmacy. Like, there must be some identifier and webhook. It may not be a new pharmacy ID, like, I’m saying, like, is there, like, another, like.
296 00:39:03.600 ⇒ 00:39:13.100 Robert Tseng: field that we get from some webhook that allows us to label it as, like, this is a transferred order. Like, we don’t… we can’t even tell whether an order has been transferred.
297 00:39:13.730 ⇒ 00:39:16.030 Henry Zhao: I think I looked and ordered up there, I don’t think I found anything like that.
298 00:39:17.840 ⇒ 00:39:19.319 Henry Zhao: But I can, I can check again. Okay.
299 00:39:20.900 ⇒ 00:39:32.970 Robert Tseng: Okay, well, then that to me is like, well, that needs to come in the order updated. Like, otherwise, how else are we gonna know if orders are going… are being transferred? Like, that’s… that’s important, like, obviously that impacts pharmacy SLAs, like.
300 00:39:33.180 ⇒ 00:39:46.770 Robert Tseng: if we’re… yeah, like, that’s… I think that’s… that is, like, that’s a valid perspective for them to take. Like, we should… we definitely… that, to me, is really high priority. I don’t know how… I don’t know how many orders, but, like, here’s how you… you quantify it. It’s like,
301 00:39:47.390 ⇒ 00:40:05.960 Robert Tseng: 20% of orders are being transferred every month, and we’re not moving, and we’re not transferring them. And so, anything that we report on SLA, on pharmacy-based SLA, you know, runs the risk of being off by, you know, that… it’s not… it’s not going to be a one-to-one, it’s not going to be 20% off. It could be more.
302 00:40:06.140 ⇒ 00:40:20.810 Robert Tseng: for pharmacies doing lower volume, that could be… that swing could be very wide. It could be greater than 20%. And obviously, for lower… for larger pharmacies, that volume may not impact it as much, but yeah, that’s… that’s kind of how you build the case.
303 00:40:21.250 ⇒ 00:40:22.569 Henry Zhao: Okay, got it. Cool.
304 00:40:23.050 ⇒ 00:40:31.140 Robert Tseng: Okay, so then, yeah, I think that’s kind of on you to put together put together… their doc…
305 00:40:31.270 ⇒ 00:40:32.120 Henry Zhao: Oof.
306 00:40:32.930 ⇒ 00:40:35.070 Robert Tseng: What? Of missing…
307 00:40:35.640 ⇒ 00:40:43.549 Robert Tseng: Deals, priorities, impact. Like, you just gotta… you have to opportunity size this. So, I’m gonna just kinda say this is probably higher.
308 00:40:43.880 ⇒ 00:40:58.030 Robert Tseng: even if BAS doesn’t do it, like, this is the diligence that we need, because it is going to end up kind of flowing into, like, what we… the capabilities that we have on the… on the Remo side. You know, it’s like, I don’t think this is wasted effort, either way, is kind of my point.
309 00:40:58.140 ⇒ 00:41:00.350 Robert Tseng: Yeah.
310 00:41:00.470 ⇒ 00:41:07.950 Robert Tseng: Okay, so that’s that. Yeah, anything else here? Like, what… you’re doing… you’re doing all of these things? I’m not gonna click into every single one.
311 00:41:09.170 ⇒ 00:41:15.610 Henry Zhao: Yeah, and some of these, points might be overestimated, but I’ll… I adjust them if they take… end up taking less.
312 00:41:16.410 ⇒ 00:41:20.790 Robert Tseng: Okay, so, I mean, I see some stuff sitting in here since September. What does that mean? Lights.
313 00:41:27.020 ⇒ 00:41:37.649 Henry Zhao: Yeah, so this is what we talked about yesterday, where it’s like, we were waiting for BASC to send us data, but we don’t have these columns, so we’re just gonna see if we can do it with the columns that we do have and get a close enough number.
314 00:41:38.060 ⇒ 00:41:50.330 Robert Tseng: Okay, so it seems like a lot of these are blocked by Bass things. I don’t think it’s very clear. It looks to me that you’re, like, executing, like, 10 tickets, but really, like, most of them are blocked from the same Bass doesn’t have things. So, like, I think there’s…
315 00:41:50.330 ⇒ 00:41:51.259 Henry Zhao: Yeah, but I’m gonna close it out.
316 00:41:51.260 ⇒ 00:41:52.069 Robert Tseng: this view.
317 00:41:52.370 ⇒ 00:42:00.200 Henry Zhao: But I’m gonna close it out if I… if I pull the numbers with the columns we do have and it’s not close. I’m just gonna close it out and say, when Basque figures it out, we’ll revisit this.
318 00:42:00.570 ⇒ 00:42:05.030 Robert Tseng: Okay, so we gotta update the due date, so what is this due date? Like, when is this gonna be done?
319 00:42:05.030 ⇒ 00:42:05.770 Henry Zhao: Or tomorrow?
320 00:42:06.280 ⇒ 00:42:13.229 Robert Tseng: Okay, so… Alright, and then… what about this one?
321 00:42:15.600 ⇒ 00:42:18.489 Henry Zhao: Isn’t this the same thing? This is what we.
322 00:42:18.490 ⇒ 00:42:19.769 Robert Tseng: Wait, did I just clicked the same one?
323 00:42:19.920 ⇒ 00:42:20.460 Henry Zhao: Yeah.
324 00:42:21.540 ⇒ 00:42:22.680 Henry Zhao: We’re looking for a P1.
325 00:42:29.290 ⇒ 00:42:48.669 Henry Zhao: Yeah, so I got some more details from Brad on what this is. This is, like, very related to the forecasting stuff I’m doing for him, which is just breaking down the volume by… by day, month, state, pharmacy, product, vial size. We don’t have vial size, but I made this do the parts we can. So, like, the stuff without vial size, and then we add it when Bass gives us his vial size.
326 00:42:51.130 ⇒ 00:42:59.880 Robert Tseng: Okay, I don’t know what that means. So, can you, like… like, what’s the, what’s, like, what’s the finding, and, like, what, what are we doing about it?
327 00:42:59.880 ⇒ 00:43:05.769 Henry Zhao: Just building a Tableau dash, but it was blocked because we didn’t have all the columns we needed, but right now, just build it with the columns we do have.
328 00:43:05.900 ⇒ 00:43:06.570 Henry Zhao: Essentially.
329 00:43:06.570 ⇒ 00:43:11.439 Robert Tseng: Okay, so… no, blocked. And due… when?
330 00:43:11.440 ⇒ 00:43:12.180 Henry Zhao: Tomorrow.
331 00:43:12.340 ⇒ 00:43:15.499 Robert Tseng: I’m all Thursday and Fridays, everything has to be done tomorrow, by tomorrow.
332 00:43:16.090 ⇒ 00:43:21.229 Henry Zhao: The whole organic social layer is already done. There’s only one order, sadly.
333 00:43:21.940 ⇒ 00:43:25.690 Henry Zhao: So I’m just getting a sanity check from Trinity, like, if that sounds right to her.
334 00:43:26.110 ⇒ 00:43:40.710 Robert Tseng: Okay, yeah, I’m not gonna go and add due dates for everything else, but you can see, like, I think everything needs to have some sort of due date, because I don’t know what to push you on if something’s not done, like, these are just kind of sitting here. So, also, like, mixed panel funnel, like, whatever that is.
335 00:43:41.490 ⇒ 00:43:45.490 Robert Tseng: Yeah.
336 00:43:46.740 ⇒ 00:43:47.780 Robert Tseng: Okay, so…
337 00:43:47.780 ⇒ 00:43:51.309 Henry Zhao: My channel funnel is done, actually, also. I did that yesterday, and I sent a loom to Casey.
338 00:43:51.560 ⇒ 00:43:55.219 Henry Zhao: So, Casey, you can watch that loom, just to see how I analyzed it.
339 00:43:58.090 ⇒ 00:44:00.119 Robert Tseng: Okay, anything else to cover here?
340 00:44:03.300 ⇒ 00:44:05.889 Henry Zhao: No, I’m gonna move some of these to the next cycle, so I think we should be good.
341 00:44:06.490 ⇒ 00:44:07.639 Henry Zhao: After you’re thinking.
342 00:44:08.020 ⇒ 00:44:08.810 Henry Zhao: Yeah.
343 00:44:09.080 ⇒ 00:44:20.919 Robert Tseng: Yeah, so due dates on everything, and then adjust what’s in… what’s actually in cycle. Okay. We have some stuff I’ll skip. Zoran, yeah, I guess, kind of, what’s… what’s going on here?
344 00:44:24.260 ⇒ 00:44:28.940 Robert Tseng: This is edge layer, comment task update, okay.
345 00:44:28.940 ⇒ 00:44:34.330 Zoran Selinger: Yeah, so you, you saw that, BAS has an update with,
346 00:44:34.510 ⇒ 00:44:45.340 Zoran Selinger: with the, what, session ID? So I have to read the document, understand it, and see how we can… they said that’s going to improve the accuracy on the transaction ID that we have.
347 00:44:45.780 ⇒ 00:44:51.019 Zoran Selinger: So I need to understand that and see exactly what this means.
348 00:44:51.510 ⇒ 00:45:00.350 Zoran Selinger: I’ll do that, by tomorrow, when you… when you guys get online. I’m gonna understand what exactly that means.
349 00:45:02.100 ⇒ 00:45:08.880 Zoran Selinger: Okay. So we’ll see. I can do… I can do updates on… on the, on the Edge and GTM.
350 00:45:09.090 ⇒ 00:45:14.799 Zoran Selinger: If we need to, but we’ll have to figure out what that means exactly for our… our stitching.
351 00:45:15.500 ⇒ 00:45:18.549 Zoran Selinger: Yes, so that’s… that’s that.
352 00:45:19.030 ⇒ 00:45:19.980 Zoran Selinger: Right. Right.
353 00:45:22.060 ⇒ 00:45:22.860 Zoran Selinger: Yeah, so…
354 00:45:22.860 ⇒ 00:45:23.250 Robert Tseng: Amen.
355 00:45:23.250 ⇒ 00:45:26.859 Zoran Selinger: so I think we’ll… so I,
356 00:45:27.130 ⇒ 00:45:32.719 Zoran Selinger: gave a ticket to… to Ovation for our Facebook copy setup.
357 00:45:32.960 ⇒ 00:45:35.840 Zoran Selinger: To figure out the crediting.
358 00:45:36.150 ⇒ 00:45:41.570 Zoran Selinger: So we can have Facebook, ready by the end of the month.
359 00:45:42.080 ⇒ 00:45:46.509 Zoran Selinger: But we… we have another one that just popped up, and that’s…
360 00:45:46.990 ⇒ 00:45:51.149 Zoran Selinger: They are going back to the old Catalis.
361 00:45:51.400 ⇒ 00:45:54.190 Zoran Selinger: Crediting. So we are changing the model again.
362 00:45:55.380 ⇒ 00:45:56.090 Robert Tseng: Oh.
363 00:45:56.600 ⇒ 00:46:01.050 Zoran Selinger: So I think that’s gonna take precedence over… over Facebook.
364 00:46:01.570 ⇒ 00:46:07.389 Zoran Selinger: Okay. Yeah. So, we are going back to any touchpoint in the last 14 days.
365 00:46:07.610 ⇒ 00:46:09.880 Robert Tseng: Wait, what? Why… why?
366 00:46:10.690 ⇒ 00:46:16.460 Zoran Selinger: Seems like they… they are now using the word unfair towards catalysts.
367 00:46:16.760 ⇒ 00:46:20.810 Zoran Selinger: So, they feel like, even Mitesh.
368 00:46:21.760 ⇒ 00:46:23.389 Zoran Selinger: is VR.
369 00:46:24.840 ⇒ 00:46:34.759 Zoran Selinger: too restrictive in crediting them. It’s not fair to them, we need to give them credits for touchpoints as well, not just people going through their dedicated funnels.
370 00:46:35.620 ⇒ 00:46:36.430 Robert Tseng: Okay.
371 00:46:36.430 ⇒ 00:46:36.750 Zoran Selinger: Yeah.
372 00:46:36.750 ⇒ 00:46:45.159 Robert Tseng: Alright, well, I mean, I didn’t hear that, so I’m… I’m assuming that you’re… you’re good with them. You meet with Cutter daily, or you kind of, like… I mean, it seems like you’re…
373 00:46:45.160 ⇒ 00:46:55.379 Zoran Selinger: We are meeting daily, now we just canceled, because those meetings last for a minute or two, so we don’t need to meet. Okay.
374 00:46:55.840 ⇒ 00:46:56.600 Zoran Selinger: That’s.
375 00:46:56.600 ⇒ 00:46:57.569 Robert Tseng: So, another thing…
376 00:46:57.570 ⇒ 00:47:03.190 Zoran Selinger: Ryan will, Ryan will write a message during the day about this.
377 00:47:03.650 ⇒ 00:47:08.219 Robert Tseng: Yeah. Do these guys actually show up to this weekly data sync?
378 00:47:08.980 ⇒ 00:47:10.360 Zoran Selinger: Mmm, everyone.
379 00:47:10.360 ⇒ 00:47:12.270 Henry Zhao: Cutter does, but not Mitesh.
380 00:47:12.270 ⇒ 00:47:16.060 Zoran Selinger: Carter definitely does. Mitesh was in one of them a couple of weeks.
381 00:47:16.060 ⇒ 00:47:16.379 Henry Zhao: That’s the goal.
382 00:47:16.380 ⇒ 00:47:20.379 Zoran Selinger: Tigran, I don’t remember seeing.
383 00:47:20.780 ⇒ 00:47:23.349 Robert Tseng: Okay, is this still helpful? Do we… do you want to keep this?
384 00:47:24.650 ⇒ 00:47:32.110 Zoran Selinger: Yeah, I think, I think Qatar just canceled our daily, so we are going to rely on that one still, yes.
385 00:47:32.320 ⇒ 00:47:34.650 Robert Tseng: I mean, this is really just… oh, dear.
386 00:47:34.940 ⇒ 00:47:52.559 Robert Tseng: Okay, well, yeah, I mean, can you, update the title, Henry, if you’re the organizer? Actually, you should transfer it to Zoran, because Zoran is the one who owns the relationship with Cutter and Mitesh now, so… Okay, alright. Yeah, you can transfer it to Zoron. Zoran, if you could name it, like, this is your weekly marketing analytics sync, like, yeah, I think that’s… I don’t think…
387 00:47:52.560 ⇒ 00:47:59.139 Robert Tseng: we can remove some people… I mean, obviously, yeah, anyway. Actually, it’s fine, you can just keep the same one. People just won’t show up.
388 00:47:59.420 ⇒ 00:48:02.010 Robert Tseng: Okay, so maybe we’ll just… do that.
389 00:48:02.200 ⇒ 00:48:03.620 Robert Tseng: Yeah. Okay, and then I…
390 00:48:03.620 ⇒ 00:48:04.669 Zoran Selinger: One ticket for you.
391 00:48:04.670 ⇒ 00:48:07.399 Robert Tseng: Noron. Just some more context here.
392 00:48:07.510 ⇒ 00:48:08.850 Zoran Selinger: Yes.
393 00:48:08.850 ⇒ 00:48:19.619 Robert Tseng: Yeah, I mean, it’s just remote, they’re trying to work on the data layer now, or at least put together a plan for, like, how their new system’s gonna do it, so they want to know, like, what we’re actually sending, what we’re…
394 00:48:19.650 ⇒ 00:48:31.189 Robert Tseng: you know, what we… examples of what we use in the… in the GTM data layer, and then kind of, like, examples of payloads to these, to… to Facebook. I would… I would edit this, so…
395 00:48:31.190 ⇒ 00:48:39.900 Robert Tseng: metacapi, I mean, you know what the sources are, so I would… I would say this is a very misinformed way of writing the requirement.
396 00:48:39.900 ⇒ 00:48:44.150 Robert Tseng: if you need help kind of clarifying it, I can help answer questions, but…
397 00:48:44.180 ⇒ 00:48:55.560 Robert Tseng: I don’t think this is… we can just edit this now. Most popular charts using the mix panel, I mean, I would just ignore that, that doesn’t matter. I would say, yeah, so…
398 00:48:56.130 ⇒ 00:49:03.269 Robert Tseng: most common… or, like, most important GTM data layer, payloads.
399 00:49:04.040 ⇒ 00:49:08.949 Robert Tseng: yeah, names of most-use analytics does make any sense.
400 00:49:09.560 ⇒ 00:49:12.020 Robert Tseng: Okay, you know what? Let’s just keep it simple.
401 00:49:12.870 ⇒ 00:49:22.830 Robert Tseng: Keep streamlined here, cappy, segment. So, like, I guess the goal really is, like, you know.
402 00:49:22.940 ⇒ 00:49:29.900 Robert Tseng: They’re designing a in-house solution of a mixed you know.
403 00:49:30.940 ⇒ 00:49:37.400 Robert Tseng: combining, like, with a mix of webhooks, API,
404 00:49:38.300 ⇒ 00:49:42.080 Robert Tseng: I mean, I don’t really know how to describe this,
405 00:49:42.620 ⇒ 00:49:50.249 Robert Tseng: We just need to share with, them, like… How the data…
406 00:49:50.720 ⇒ 00:49:56.229 Robert Tseng: should look like. So yeah, I think I would kind of… it’s like…
407 00:49:56.620 ⇒ 00:50:01.340 Robert Tseng: This might be a multifaceted thing, so…
408 00:50:02.330 ⇒ 00:50:09.749 Robert Tseng: I might actually say, I think the marketing stuff is the most important, because that impacts intake, but then there’s also, like.
409 00:50:10.120 ⇒ 00:50:17.500 Robert Tseng: Well, yeah, this is gonna be between Henry and Zoran. Like, every webhook, you know, anything in the data layer that we access right now, we pull into
410 00:50:19.570 ⇒ 00:50:35.350 Robert Tseng: into our warehouse. We don’t have to share, like, our modeling with him, we just need to know, like, what the payloads look like, but we adjust, right? So that’s basically the ask here. We can start with the marketing stuff and send it over to them, and then Henry can add on to it later on, with, you know, all the
411 00:50:35.420 ⇒ 00:50:42.129 Robert Tseng: we’re not sending exactly what Basque is sending them, we’re sending what we want, them to show. So, like, it should be, like, a…
412 00:50:42.330 ⇒ 00:50:50.890 Robert Tseng: You know, this should be, sequential to, like, the basket stuff that, you know, we asked you to do on the other, block ticket.
413 00:50:52.160 ⇒ 00:50:52.920 Zoran Selinger: Sure, he’s very…
414 00:50:52.920 ⇒ 00:50:53.389 Robert Tseng: Does that make sense?
415 00:50:53.390 ⇒ 00:50:57.509 Zoran Selinger: Is there anything in our notion that I can read about this?
416 00:50:58.650 ⇒ 00:51:01.060 Robert Tseng: Yeah, I mean, I would say…
417 00:51:03.640 ⇒ 00:51:09.770 Robert Tseng: Yeah, there might be some Notion stuff. Okay, you know what, I’ll send you what I can. Okay, Robert sends…
418 00:51:10.070 ⇒ 00:51:11.650 Robert Tseng: They’re on.
419 00:51:11.650 ⇒ 00:51:14.760 Amber Lin: It also has context, if that would be more helpful.
420 00:51:15.270 ⇒ 00:51:15.960 Robert Tseng: Yeah.
421 00:51:16.430 ⇒ 00:51:20.089 Robert Tseng: docs, then also reach out to Awash.
422 00:51:20.310 ⇒ 00:51:21.120 Robert Tseng: Okay.
423 00:51:21.320 ⇒ 00:51:28.450 Robert Tseng: And then it’s gonna be Henry will… Cool. We’ll do marketing first.
424 00:51:29.080 ⇒ 00:51:30.060 Robert Tseng: other…
425 00:51:34.710 ⇒ 00:51:40.050 Robert Tseng: Other data… bigger. Okay, cool. Anything else on Eden?
426 00:51:42.800 ⇒ 00:51:46.260 Henry Zhao: Not on my end, I’ll just meet with Awish later to ask him for the stuff we need.
427 00:51:47.020 ⇒ 00:51:47.810 Robert Tseng: Okay, so…
428 00:51:47.810 ⇒ 00:52:06.349 Zoran Selinger: Yeah, we have… we have a few… few other tweaks for… for Edge. Ryan wants to add, unanimous IDs, anonymous IDs, and all of those things to the… to our Edge data table, so we can… we can stitch it a little bit more.
429 00:52:06.350 ⇒ 00:52:09.710 Zoran Selinger: with other things, we’re also probably gonna enable
430 00:52:09.710 ⇒ 00:52:14.730 Zoran Selinger: direct input, to BigQuery from GA4.
431 00:52:15.020 ⇒ 00:52:16.699 Zoran Selinger: So we have all that data.
432 00:52:16.980 ⇒ 00:52:29.500 Zoran Selinger: In there, and it’ll be ready, kind of, to stitch all of those, all those things together, if we need in the future. So, but that’s, that, that’s not a priority. Now we have to deal with Catalysts again.
433 00:52:31.650 ⇒ 00:52:31.980 Robert Tseng: Okay.
434 00:52:31.980 ⇒ 00:52:35.789 Zoran Selinger: So, yeah, but there are tickets for all of that already.
435 00:52:35.790 ⇒ 00:52:36.380 Robert Tseng: Okay.
436 00:52:36.890 ⇒ 00:52:39.119 Amber Lin: Any analysis that’s needed?
437 00:52:39.570 ⇒ 00:52:52.939 Robert Tseng: Yeah, so, I mean, that’s, like, the thing here. I… analysis is not clear on, like, what we’re actually delivering. So, all I’ve seen is, like, Casey’s doing a spike on Texas SQL, and then we… Henry shared something around Mixpanel.
438 00:52:53.140 ⇒ 00:52:58.630 Robert Tseng: I mean, we should be churning out some analysis as well. I mean, we don’t have to…
439 00:52:58.920 ⇒ 00:53:05.640 Robert Tseng: I guess I have two questions. One is, like, Amber, is this… is this the right… I forgot pacing, like, what are we expecting for Eden?
440 00:53:07.240 ⇒ 00:53:13.959 Amber Lin: Yeah, we’re trying to do probably around… 50 points per cycle.
441 00:53:14.870 ⇒ 00:53:16.550 Robert Tseng: Even with the budget increase.
442 00:53:16.550 ⇒ 00:53:20.210 Amber Lin: No, with the budget increase, I have not calculated it yet.
443 00:53:20.810 ⇒ 00:53:23.599 Robert Tseng: Okay, I’m just gonna assume it’s around 60, so…
444 00:53:24.190 ⇒ 00:53:40.020 Robert Tseng: To me, these are just, like, random, like, Tableau tweaks that, like, Henry’s working on, and then some documentation. So it feels like we’re light. I mean, on the engineering side, like, I understand we’re doing some things on the Catalyst stuff, but yeah, I feel like we need to be kind of building out an analysis motion here. So…
445 00:53:40.180 ⇒ 00:53:45.989 Robert Tseng: I mean, I can take this as, like, a… go back and figure it out, but…
446 00:53:46.410 ⇒ 00:53:50.359 Robert Tseng: As far as analysis time, I mean…
447 00:53:51.370 ⇒ 00:53:58.809 Henry Zhao: I think we’re setting ourselves up for analysis, right? So the Mixpanel stuff, once we fix the intakes, instead of session replays, there’s gonna be data to be analyzed there.
448 00:53:59.490 ⇒ 00:54:04.100 Henry Zhao: On, like, intake drop-off, connecting that to the UTMs, and seeing, like, where are the opportunities.
449 00:54:04.790 ⇒ 00:54:08.049 Robert Tseng: Okay, so, like, when… when… when is… when can we start that, though?
450 00:54:08.950 ⇒ 00:54:15.019 Henry Zhao: Probably starting tomorrow, so tomorrow I’m giving them Mixpanel training, and then I need to work with Ryan to fix the…
451 00:54:15.390 ⇒ 00:54:16.990 Henry Zhao: the intake tracking.
452 00:54:17.470 ⇒ 00:54:29.080 Henry Zhao: because right now they’re doing intake tracking by, like, putting the title of each page of the intake, but the titles change. So all that stuff is broken. So we just need to fix that, then we can start looking at intake forms and, like, where’s the drop-off?
453 00:54:29.200 ⇒ 00:54:33.769 Henry Zhao: Do people from certain UTMs have a better completion rate? Things like that.
454 00:54:35.360 ⇒ 00:54:42.120 Robert Tseng: Okay, yeah, I think I expect to see more of that stuff on your roadmap moving forward, rather than these, like, random, like, tweets.
455 00:54:42.120 ⇒ 00:54:43.710 Henry Zhao: We can’t do that until we fix this stuff.
456 00:54:44.080 ⇒ 00:54:45.120 Robert Tseng: Okay, that’s fine.
457 00:54:45.120 ⇒ 00:54:51.749 Henry Zhao: And then pharmacy, same thing, right? Pharmacy, I’m calling Michelle today on Pharmedica to get the data, then we’ll be doing analysis on pharmacy operations.
458 00:54:52.170 ⇒ 00:54:52.880 Robert Tseng: Okay.
459 00:54:52.880 ⇒ 00:54:55.170 Henry Zhao: We need the data, yeah, so… yeah.
460 00:54:57.480 ⇒ 00:55:10.060 Robert Tseng: All right, let’s, yeah, we’ll move on. Insomnia. So, Amber, I know you’ve been out. I sent you a message, so I think, if you could watch that, that would be helpful.
461 00:55:10.770 ⇒ 00:55:16.619 Robert Tseng: Yeah, I had shared out your slides. I think there’s some cleanup work,
462 00:55:17.090 ⇒ 00:55:24.689 Robert Tseng: Just in terms of, like, insomnia… oh dear. This is not gonna go well.
463 00:55:25.040 ⇒ 00:55:28.759 Robert Tseng: it’s this one…
464 00:55:33.190 ⇒ 00:55:48.379 Robert Tseng: Yeah, so, I mean, I left some comments, but things like product, like, type one point, like, this is, like, you know, people have to be able to… it’s… it’s just not, it’s not very clear, so clean up the legend, like, and Rita wants to share this with, like, C-level people, so…
465 00:55:48.380 ⇒ 00:55:48.839 Amber Lin: Oh, I see.
466 00:55:48.840 ⇒ 00:55:58.519 Robert Tseng: Yeah, like, you should watch the video, kind of understand the adjustments that we’re gonna make. These recommendations are good. Obviously, we don’t… this is too much, so it needs to be top 10, so just…
467 00:55:58.520 ⇒ 00:56:18.599 Robert Tseng: you know, we… we’re obviously trying to rush, like, the analysis out. The insights were good, I think just, like, the… the crispness of the… of it is not there yet. So, the fact that, like, we have to present, and then they’re asking us to go and change some things, I mean, we’ll get there, I’m not concerned. Generally, the… like, the quality of the insight is there, it’s just the presentation is a little bit…
468 00:56:18.600 ⇒ 00:56:19.140 Amber Lin: Hmm.
469 00:56:19.490 ⇒ 00:56:28.069 Robert Tseng: like, yeah, we just need a little bit more attention to detail there. But overall, this was good. I think there are peer follow-ups, and we need to set up those follow-ups there.
470 00:56:28.070 ⇒ 00:56:30.419 Amber Lin: That’s exciting. Okay, I’ll go edit the slides.
471 00:56:31.040 ⇒ 00:56:42.469 Robert Tseng: Yeah. So, yeah, and I think, like, the goal isn’t to do a net new one of these every week. I think, yeah, like, there’s a lot of good nuggets here, so you can take this time and, like.
472 00:56:42.470 ⇒ 00:56:59.750 Robert Tseng: you know, based off of the notes, you can watch the video, follow up. Like, they… they really were like, okay, this way of segmentation actually makes a lot more sense. RFM is all relative, you can’t actually do the… by order number, you can’t do it by price or whatever, it’s all… it’s just a relative, like,
473 00:56:59.920 ⇒ 00:57:16.510 Robert Tseng: segmentation. So, I think overall, like, this… this is making sense. Like, it’s… there’s… there’s… there’s good, there’s good nuggets in here. We, like, I think there’s more to do there. So, yeah, I think there are some outdated tickets here that I want to just kind of clean out.
474 00:57:16.510 ⇒ 00:57:29.879 Robert Tseng: I… I know it’s, like, kind of weird straddling, like, the docs that you do for the analysis outlines versus the tickets. I think, to me, the tickets on the analysis side is just to kind of, like, articulate, like, what are you, like, investigating? I think.
475 00:57:30.230 ⇒ 00:57:37.700 Robert Tseng: If you want to do one ticket per analysis, that’s fine, if that’s helpful, but I do feel like we were kind of, like, there’s not enough detail on a lot of the stuff.
476 00:57:37.700 ⇒ 00:57:44.769 Amber Lin: I haven’t been ticketing, so I’ve only been working in Drock, so, it makes sense that the tickets doesn’t seem very…
477 00:57:44.980 ⇒ 00:57:46.130 Amber Lin: Descriptive.
478 00:57:46.480 ⇒ 00:58:00.930 Robert Tseng: Yeah, I want to do a feedback on this. I know, like, I wasn’t managing the reviews before, so I apologize for not giving this detail earlier, Casey, but, yeah, I kind of just gave you some feedback. It took me a while to figure out the takeaways from your analysis.
479 00:58:00.930 ⇒ 00:58:12.830 Robert Tseng: I mean, I believe that what you did is fine, like, I’m not, like, questioning it. I think there is, like, you know, there’s some feedback here. Like, I don’t know what to share with the client from this. I think the takeaway is just, like.
480 00:58:13.520 ⇒ 00:58:25.880 Robert Tseng: what revenue is driven by conversions. I mean, we kind of knew that, so I don’t really… I think we kind of strayed away from the business question within your actual doc, which was, whatever it was.
481 00:58:26.230 ⇒ 00:58:34.239 Robert Tseng: Anyway, so I left some feedback there, like, I reviewed it, but, like, I don’t have a next step, because I just… I don’t really know what to share with them. So, just kind of…
482 00:58:34.240 ⇒ 00:58:40.840 Amber Lin: me to pair with Casey, and we can look at it together, or we can brainstorm some stuff, because I have more context now.
483 00:58:41.770 ⇒ 00:59:01.699 Robert Tseng: Yeah… I mean, like, I think it’s more urgent to kind of just… or not… well, yeah, I think we don’t have to do too many different things right now. I… yeah, I think the kind of doing the follow-ups here makes more sense. Like, I think we’ll just… like, I don’t… I don’t really know what to do with this for now, so…
484 00:59:01.700 ⇒ 00:59:02.640 Amber Lin: Yeah, I see.
485 00:59:02.640 ⇒ 00:59:04.809 Robert Tseng: I’m just gonna put it to,
486 00:59:05.230 ⇒ 00:59:07.759 Robert Tseng: these revisions, like, I don’t… I don’t have…
487 00:59:07.940 ⇒ 00:59:09.629 Robert Tseng: I don’t have anything to say there.
488 00:59:09.630 ⇒ 00:59:13.399 Amber Lin: Can I get a time cap of how much time I should spend this week?
489 00:59:14.170 ⇒ 00:59:33.100 Robert Tseng: Well, yeah, so, like, I guess I’m not really sure in terms of, like, hours-wise. Data engineering work is pretty much null on this. Like, all we have is updating the daily tracker. Like, I still think updating the tracker to have, like, a more efficient version is… is, like, what I’ve been asking for that we haven’t done.
490 00:59:33.430 ⇒ 00:59:40.959 Robert Tseng: I mean, maybe I just need to go and redesign the tracker myself, and then we can kind of backfill it that way.
491 00:59:41.270 ⇒ 00:59:42.110 Robert Tseng: But…
492 00:59:42.290 ⇒ 00:59:57.670 Robert Tseng: I mean, other… if there’s no data engineering work, and Casey is just spending 30 minutes a day, then we’re only spending, like, two and a half hours a week on this client, plus, like, some scattered meetings. So, I mean… I mean, Amber, I feel like you should be spending at least 10 hours on this client, because it’s kind of basically what.
493 00:59:57.670 ⇒ 00:59:59.849 Amber Lin: I’ve been doing that, so I just want to make sure.
494 01:00:00.890 ⇒ 01:00:05.040 Robert Tseng: Yeah. Yeah, I think somewhere between 10 to 15 hours is, like, makes sense to me.
495 01:00:06.730 ⇒ 01:00:07.779 Amber Lin: Okay. Sounds good.
496 01:00:08.680 ⇒ 01:00:23.669 Robert Tseng: Yeah. Okay, so, I would appreciate if we could just kind of clean some of this up. I’ll start, like, adding the projects and stuff to this again, because I feel like this… this board is a little bit messy. But okay, that’s… that’s it for Insomnia.
497 01:00:23.670 ⇒ 01:00:26.650 Amber Lin: Yeah, send me the projects, I can… I can help put them in.
498 01:00:27.890 ⇒ 01:00:33.530 Robert Tseng: I have written the projects before. They’re just… yeah, we’re just not using them.
499 01:00:33.530 ⇒ 01:00:34.320 Amber Lin: Okay, okay.
500 01:00:34.530 ⇒ 01:00:38.630 Robert Tseng: Yeah, I think these are the active ones,
501 01:00:38.860 ⇒ 01:00:40.820 Robert Tseng: Yeah, we just haven’t been using them.
502 01:00:42.860 ⇒ 01:00:50.920 Robert Tseng: Okay, so we’ll move on to Honey Stinger. I saw Henry added a few things here. Yeah, walk me through, like, kind of where we’re at.
503 01:00:51.380 ⇒ 01:01:01.510 Henry Zhao: Yeah, so last night, I was able to take a look at the Amazon data, and for the most part, it makes sense. I was able to find all the data that we need on the traffic.
504 01:01:02.070 ⇒ 01:01:21.699 Henry Zhao: views, sales, inventory… I was able to figure out where to get highly available inventory stuff, but we don’t have FC’s data and geographical data, so I’ve asked Mustafa if he can figure that out for me in his, modeling work, but I was also able to figure out SKU to ASIN mapping on my own, I think, so…
505 01:01:22.320 ⇒ 01:01:23.770 Robert Tseng: Great. Yeah.
506 01:01:26.070 ⇒ 01:01:27.910 Henry Zhao: Yeah, so today I’m gonna work on…
507 01:01:28.120 ⇒ 01:01:32.770 Henry Zhao: Getting at least the first few analyses that you’ve listed in your analytics overhaul done.
508 01:01:33.240 ⇒ 01:01:37.260 Henry Zhao: And also, I think it would be interesting to look at, kind of, the search terms that are bringing in sales.
509 01:01:37.550 ⇒ 01:01:39.890 Henry Zhao: Yeah.
510 01:01:41.440 ⇒ 01:01:52.260 Henry Zhao: I just want to confirm if you know how to know if it’s a pallet versus a one-off shipment. Is it based on the cases versus each’s unit size, or is it a certain number of order size?
511 01:01:52.620 ⇒ 01:01:57.980 Henry Zhao: Like, if somebody orders 720 eaches of Honey Stinger, is that a pallet, or is that a one-off shipment?
512 01:01:58.930 ⇒ 01:02:01.290 Henry Zhao: I couldn’t find Horizons Canada data.
513 01:02:01.690 ⇒ 01:02:13.749 Robert Tseng: Yeah, so… I think, like, each’s versus pallets, I believe each is the base unit pallet. There’s, like, many eachs on a pallet, forgot how many eachs are per pallet, so…
514 01:02:13.860 ⇒ 01:02:15.120 Robert Tseng: I mean, if you just, like…
515 01:02:15.120 ⇒ 01:02:16.250 Henry Zhao: 120 things.
516 01:02:16.490 ⇒ 01:02:17.959 Henry Zhao: As a one-off shipment, you know?
517 01:02:20.750 ⇒ 01:02:27.369 Robert Tseng: I think, like, we… I don’t… I don’t think Byron knows… like, the way that things are being fulfilled right now.
518 01:02:29.260 ⇒ 01:02:43.800 Robert Tseng: because they’re completely Amazon, dependent, they don’t do any of their own fulfillment, Amazon will place purchase orders. And if you look at that one table that has, like, like, their purchase orders or whatever, if you just bought, like, a general
519 01:02:43.800 ⇒ 01:02:58.329 Robert Tseng: like, graph, like, you’ll see, like, these random spikes, like, why is… why are they ordering, like, 2,000 each on one week, and then, like, you know, 50 on another? Or, like, on a particular pallet, they have, you know, 12, 20 different ASINs, like, I mean, like, it’s just…
520 01:02:58.730 ⇒ 01:03:04.480 Robert Tseng: I think we just have to… we have to identify, like, what…
521 01:03:05.420 ⇒ 01:03:28.330 Robert Tseng: what’s consistently being ordered, what’s not being consistently ordered? Like, if there are certain ASINs that are being ordered, like, in bulk once every, like, 3 months or whatever, like, I would consider that a one-off shipment. But then there’s also going to be certain ASINs that are… sorry, SKU and ASIN I use interchangeably. It should be just SKUs. Asin is just, like, an Amazon version of a SKU. Then it, you know.
522 01:03:28.330 ⇒ 01:03:43.030 Robert Tseng: Like, I… I don’t think it’s… the point is, like, it’s… it’s not… like, he doesn’t know, he just feels like they’re one-off shipments, like, he… he knows on, like, their inventory side, they’re struggling to keep up, because they don’t know how to forecast for Amazon’s purchases. Like.
523 01:03:43.100 ⇒ 01:03:59.789 Robert Tseng: sometimes Amazon will just, like, make a large purchase, and they’re scrambling to, like, fulfill the purchase order, because, like, they don’t really know… it’s so erratic. So, I think, like, it’s more about telling them, these are your one-off shipments on these SKUs, these are the ones that are consistent.
524 01:03:59.790 ⇒ 01:04:11.610 Robert Tseng: You see these volume spikes, they’re spiking… I don’t know if we can say… we can say why yet, but, like, I think we’re just… we’re trying to help them to understand what are the patterns behind Amazon’s purchasing behavior.
525 01:04:12.120 ⇒ 01:04:21.160 Henry Zhao: Okay, and I’m gonna see… Amazon has forecasting data, because obviously they need that for HAI, but I’m gonna see if that, like, kind of aligns with the actual purchase behavior we’re seeing.
526 01:04:21.340 ⇒ 01:04:22.160 Robert Tseng: This is so gorgeous.
527 01:04:22.160 ⇒ 01:04:23.240 Henry Zhao: Rely on that, yeah.
528 01:04:23.830 ⇒ 01:04:32.579 Robert Tseng: Yeah, and then for Horizon’s vendor account, what I… if you watched the meeting that we had with them, I was asking, like, why are there all these, like, random search terms?
529 01:04:32.640 ⇒ 01:04:48.000 Robert Tseng: I don’t know if you can filter by Canada, but anything that’s just, like, I don’t know, there was, like, girls’ dresses, or, like, random, like, products that were… had nothing to do with Honey Stinger, those are all horizon search terms, so, like, I would just exclude those for your analysis as you’re doing this.
530 01:04:48.000 ⇒ 01:04:52.620 Henry Zhao: I think one of the… some of the tables have general Amazon data, not just Honey Stinger related.
531 01:04:54.480 ⇒ 01:04:58.789 Robert Tseng: Yes, but, like, it’s general, like, it’s Horizon data. It’s not…
532 01:04:59.260 ⇒ 01:05:01.529 Robert Tseng: it’s not Amazon data, right? It’s…
533 01:05:01.930 ⇒ 01:05:06.580 Robert Tseng: Like, it’s because they’re on Horizon’s account that they’re able to see Horizon’s data.
534 01:05:07.850 ⇒ 01:05:08.220 Henry Zhao: And so…
535 01:05:08.220 ⇒ 01:05:09.600 Robert Tseng: So, we just need to, like.
536 01:05:10.040 ⇒ 01:05:16.049 Robert Tseng: basically filter those out. Like, obviously, like, rent… the other products that have nothing to do with
537 01:05:16.320 ⇒ 01:05:18.040 Robert Tseng: their product, like.
538 01:05:18.510 ⇒ 01:05:18.899 Henry Zhao: Oh, yeah.
539 01:05:18.900 ⇒ 01:05:20.830 Robert Tseng: an example off the top of my head, but, like.
540 01:05:20.830 ⇒ 01:05:28.200 Henry Zhao: I assumed that… I assumed that we were getting all Amazon search data, even if it’s not related to Honey Stinger, so that we could look at the rankings.
541 01:05:28.660 ⇒ 01:05:30.799 Henry Zhao: That was my turn when I looked at the data.
542 01:05:31.480 ⇒ 01:05:37.080 Robert Tseng: But I don’t think we actually are getting their search data. I think that’s just, like, the search terms that are tied to Horizon’s account.
543 01:05:37.310 ⇒ 01:05:37.710 Henry Zhao: Okay.
544 01:05:37.710 ⇒ 01:05:40.719 Robert Tseng: I mean, still a good benchmark, because we can say.
545 01:05:40.730 ⇒ 01:05:50.419 Robert Tseng: hey, look, like, we see all Horizon’s data, we know that, like, we’re their biggest customer, and we drive the most traffic from them. That’s also good leverage for them to go back and be like.
546 01:05:50.420 ⇒ 01:06:02.920 Robert Tseng: hey, like, we know that we’re your… we’re your biggest customer, like, you know, whatever, like, we drive most of the search volume for you, we do blah, blah, blah, blah. Or we can… we can just help… yeah, like, I… I think it’d still be good to give them
547 01:06:03.270 ⇒ 01:06:22.830 Robert Tseng: I don’t think Horizon is a good proxy for, like, overall Amazon search terms, but it is something. So, like, I… I would, you know, I would exclude it from when you’re doing the search terms analysis, but also just try to understand, like, from a positioning perspective, within Horizon’s portfolio, how is, like, Honey Stinger actually performing?
548 01:06:23.090 ⇒ 01:06:23.620 Henry Zhao: Okay.
549 01:06:23.620 ⇒ 01:06:24.310 Robert Tseng: Does that make sense?
550 01:06:24.360 ⇒ 01:06:34.629 Henry Zhao: But for search term analysis, there’s a table that connects it to the ASIN, so I’m just gonna filter only the ASINs that are Honey Stinger to figure out what are the actual search terms that brought people to Honey Stinger. So then I was just thinking about everything else.
551 01:06:35.270 ⇒ 01:06:44.759 Robert Tseng: Okay, cool. Yeah, so I would say, if you’re gonna update this ticket, like, I mean, really to me, like, as I kind of build this out, I mean.
552 01:06:45.110 ⇒ 01:07:00.470 Robert Tseng: I try to think about, like, what actions are we taking? Like, what questions are we answering? It’s usually some triangulation of all, so I can’t always say that you just pull this into there, but, like, obviously, like, this is a very large initiative, this shouldn’t really be a ticket, I just kind of put it there.
553 01:07:00.470 ⇒ 01:07:19.430 Robert Tseng: Whatever you ended up picking off and you feel like you could do it, I’d like if you could at least make, like, the ticket related to the question that you’re trying to answer, and then, like, maybe your, like, the description is, like, kind of what you’re actually approaching. I think that would maybe be more helpful for me to, like, see a thread of, like, how you’re thinking about it.
554 01:07:20.070 ⇒ 01:07:20.470 Henry Zhao: Okay.
555 01:07:20.470 ⇒ 01:07:21.299 Robert Tseng: Does that make sense?
556 01:07:21.650 ⇒ 01:07:29.479 Henry Zhao: Yeah, and then in the meantime, Mustafa, if you can help me get data on FCs and geography, as well as, like, any of the Buy With Prime stuff.
557 01:07:29.770 ⇒ 01:07:31.569 Henry Zhao: then we can, I think, close this one out.
558 01:07:32.640 ⇒ 01:07:33.000 Robert Tseng: Yeah.
559 01:07:33.000 ⇒ 01:07:33.770 Mustafa Raja: Yeah.
560 01:07:33.770 ⇒ 01:07:42.240 Robert Tseng: Because, like, there’s no way that this is, like, one ticket. This is just, like, this is the end state, but this is, like, not a ticket. Yeah. Okay, sorry, Mustafa, go ahead.
561 01:07:43.190 ⇒ 01:07:48.380 Mustafa Raja: Yeah, so, the ticket, for modeling that was assigned to me, so, it was about…
562 01:07:48.600 ⇒ 01:07:56.109 Mustafa Raja: staging models, but, Utam said we don’t need that. We would need intermediate models, and then…
563 01:07:56.300 ⇒ 01:08:06.520 Mustafa Raja: He provided me a Notion doc on how BrainForge does it, so, I’ll just get my… get myself up to speed with that.
564 01:08:06.810 ⇒ 01:08:12.299 Mustafa Raja: work on the modeling stuff. It’s, HON21.
565 01:08:13.270 ⇒ 01:08:15.409 Robert Tseng: Yeah, I’m… I’m on it. Yeah.
566 01:08:16.510 ⇒ 01:08:23.559 Henry Zhao: Yep, and then I didn’t have a chance to look at Shopify or SMS data, so if you want to dole those out to other team members.
567 01:08:23.569 ⇒ 01:08:31.979 Robert Tseng: Yeah, I would say you don’t need to cover Shopify, just do the Amazon stuff this week. Yeah, I think we’ll eventually get to Shopify.
568 01:08:32.279 ⇒ 01:08:34.909 Henry Zhao: Okay. Yeah, I’ll do Amazon by today.
569 01:08:36.430 ⇒ 01:08:37.050 Robert Tseng: Okay.
570 01:08:37.160 ⇒ 01:08:55.139 Robert Tseng: Cool, because, like, I know you’re gonna be out end of week, but it’s been 3 weeks, we haven’t set any analysis to, Honey Stinger. We’ve only been relying on, like, me just, like, talking with Byron and getting him excited for what’s coming, so this is very, like, high priority for me, like, we need to have something to deliver him on by Friday, so…
571 01:08:55.420 ⇒ 01:09:00.920 Robert Tseng: I’m, like, watching this very closely, and I mean, I’m not trying to be annoying about it, but, like.
572 01:09:00.920 ⇒ 01:09:01.289 Henry Zhao: I get it.
573 01:09:01.290 ⇒ 01:09:04.530 Robert Tseng: I do, I do need something to go to him this week.
574 01:09:04.760 ⇒ 01:09:07.769 Henry Zhao: But I want to do it today because I would like your feedback, so that if…
575 01:09:07.910 ⇒ 01:09:13.709 Henry Zhao: it’s not what you were expecting, we have tomorrow to kind of fix it. And then, worst case, Thursday and Friday, I can be available.
576 01:09:14.479 ⇒ 01:09:15.069 Robert Tseng: Okay.
577 01:09:15.069 ⇒ 01:09:15.929 Henry Zhao: I won’t be off the ground.
578 01:09:16.420 ⇒ 01:09:25.999 Robert Tseng: All right, yeah, so just, yeah, make sure that you… I mean, I still don’t know which ones you’re picking, so, like, just kind of update that here so I know what questions you’re actually gonna go after. Okay.
579 01:09:26.000 ⇒ 01:09:32.480 Mustafa Raja: For the… for the modeling… for the modeling ticket, I would want, the due date to be end of week.
580 01:09:33.640 ⇒ 01:09:34.649 Robert Tseng: Okay.
581 01:09:35.649 ⇒ 01:09:36.359 Mustafa Raja: Got it.
582 01:09:38.960 ⇒ 01:09:44.519 Henry Zhao: Okay, Robert, let’s go over just, like, what are the questions that I was able to answer, and you can let me know if that’s good enough. If not, we have.
583 01:09:44.520 ⇒ 01:09:54.359 Robert Tseng: Yeah, we have one-on-one later today, so we can kind of discuss things. I basically have stacked Mustafa, Amber, and you back-to-back, to kind of talk through different analysis things.
584 01:09:54.530 ⇒ 01:09:55.590 Henry Zhao: Okay.
585 01:09:55.610 ⇒ 01:10:13.239 Robert Tseng: Okay, README, yeah, Mustafa, this one, I will… I will get this done before we meet, and then we can talk about analysis on README. So, I don’t have anything new to share here. But yeah, I just needed to give you an intro to the client. I feel like that’s how we’ll spend our 101 today.
586 01:10:14.350 ⇒ 01:10:14.980 Mustafa Raja: Okay.
587 01:10:15.270 ⇒ 01:10:22.080 Robert Tseng: Okay. And then Ellie, like, I know, Zoran, if you’re still there, you’re kind of just working through some things.
588 01:10:22.210 ⇒ 01:10:41.500 Robert Tseng: they feel like they’re, like, stuck on this. They’re, like, not willing to sign the contract because they feel like things kind of didn’t work here. I know it’s not our fault. I don’t know, like… I followed the email thread, but I’m not really sure how much… like, is this a lot of work for you to finish, or, like, what have we… like, I don’t really know why… like, why they’re so stuck on this.
589 01:10:42.190 ⇒ 01:10:47.170 Zoran Selinger: I mean, there’s… currently, there’s no proof that there’s anything wrong.
590 01:10:47.550 ⇒ 01:10:47.890 Robert Tseng: Okay.
591 01:10:47.890 ⇒ 01:10:52.489 Zoran Selinger: So, I just want to have another check. I asked in the last email, I asked for…
592 01:10:53.350 ⇒ 01:10:56.999 Zoran Selinger: for, and can I amplitude contact?
593 01:10:57.330 ⇒ 01:11:05.329 Zoran Selinger: So they can just check if our… our destination settings are okay. I see nothing wrong in there.
594 01:11:05.480 ⇒ 01:11:15.740 Zoran Selinger: We simply… we received no… no David Grant events in the last… since… October 7th… see, November 7th.
595 01:11:17.320 ⇒ 01:11:26.919 Zoran Selinger: Yeah. So yeah, I just need someone to check there, because in… on our side, everything seems… seems fine.
596 01:11:27.830 ⇒ 01:11:28.430 Robert Tseng: Okay.
597 01:11:29.580 ⇒ 01:11:30.120 Zoran Selinger: Yeah.
598 01:11:30.120 ⇒ 01:11:32.370 Robert Tseng: Don’t… yeah, so…
599 01:11:32.370 ⇒ 01:11:40.829 Zoran Selinger: That’s where I can point at the moment. I just don’t see anything wrong on there, unless something’s on the amplitude side is wrong.
600 01:11:41.820 ⇒ 01:11:42.470 Robert Tseng: Okay.
601 01:11:43.140 ⇒ 01:11:45.840 Zoran Selinger: So I’d like with amplitude.
602 01:11:46.090 ⇒ 01:11:51.990 Robert Tseng: Yeah, okay. It’s alright.
603 01:11:53.440 ⇒ 01:11:54.480 Robert Tseng: Zero.
604 01:11:54.720 ⇒ 01:11:55.550 Robert Tseng: Okay.
605 01:11:55.910 ⇒ 01:12:00.360 Robert Tseng: Alright, so that’s that.
606 01:12:00.590 ⇒ 01:12:08.530 Robert Tseng: Yeah, okay, I think that’s pretty much it. I guess…
607 01:12:09.390 ⇒ 01:12:19.239 Robert Tseng: people who have specific questions, I’ll stay on, just to kind of, like, we can work through some of these things now. Otherwise, I guess, if nothing else, then feel free to drop.
608 01:12:26.210 ⇒ 01:12:27.510 Zoran Selinger: Alright, thank you.
609 01:12:27.930 ⇒ 01:12:28.510 Robert Tseng: Okay.
610 01:12:40.530 ⇒ 01:12:41.370 Robert Tseng: Okay.