Meeting Title: Brainforge Weekly Project Sync Date: 2025-07-17 Meeting participants: Awaish Kumar, Fireflies.ai Notetaker Tigran, Robert Tseng, Amber Lin, Henry Zhao, Annie Yu, Demilade Agboola
WEBVTT
1 00:03:53.770 ⇒ 00:03:55.770 Robert Tseng: Hello! Everyone.
2 00:03:56.250 ⇒ 00:03:57.600 Amber Lin: Hello!
3 00:04:03.940 ⇒ 00:04:07.519 Robert Tseng: Okay, yeah, I’m gonna go camera off.
4 00:04:18.589 ⇒ 00:04:20.390 Robert Tseng: I’m gonna wait like 1 min.
5 00:04:20.940 ⇒ 00:04:24.029 Robert Tseng: Just I’m just like, quickly scanning all the tickets.
6 00:04:25.360 ⇒ 00:04:29.999 Robert Tseng: I guess a lot of this is from grooming so as far as progress.
7 00:04:31.190 ⇒ 00:04:33.430 Robert Tseng: So they want to ship something.
8 00:04:36.490 ⇒ 00:04:42.460 Robert Tseng: Okay, cool. I’m gonna jump into it.
9 00:04:46.460 ⇒ 00:04:49.917 Robert Tseng: Yeah. So maybe I’ll just start this side.
10 00:04:52.380 ⇒ 00:04:58.029 Robert Tseng: yeah, Dame Lotto. I saw that you marked like that slack Channel thing like report done.
11 00:04:58.520 ⇒ 00:05:04.519 Robert Tseng: I wasn’t added to a new slack channel. So I’m not really sure like.
12 00:05:04.760 ⇒ 00:05:09.189 Robert Tseng: if that’s if you could just just clarify that for me, cause I didn’t see any comments.
13 00:05:10.730 ⇒ 00:05:13.520 Demilade Agboola: Oh, so actually, I’ve built out the model.
14 00:05:14.110 ⇒ 00:05:19.380 Demilade Agboola: I oh, I actually haven’t gotten the slack channel as well. My bad I should have
15 00:05:20.860 ⇒ 00:05:24.330 Demilade Agboola: the done was the model, not necessarily the forwarding to the channel.
16 00:05:24.810 ⇒ 00:05:29.840 Robert Tseng: Oh, I see. Okay. Well, I mean, if you could just kind of reopen that up and then like, let
17 00:05:30.942 ⇒ 00:05:44.040 Robert Tseng: this, let the stakeholder know? Like, okay, this is ready. Do we like, we’re gonna create XYX channel like. And then just make sure that she’s okay with it. I think that’d be. We could just give her like a 1 time. Look of it.
18 00:05:45.140 ⇒ 00:05:46.240 Demilade Agboola: Okay. Sounds good.
19 00:05:46.400 ⇒ 00:05:46.990 Robert Tseng: Yeah.
20 00:05:47.370 ⇒ 00:05:49.060 Demilade Agboola: That would be Katie right.
21 00:05:50.810 ⇒ 00:05:53.799 Robert Tseng: I’m assuming, so I don’t call off top of my head.
22 00:05:53.800 ⇒ 00:05:54.680 Demilade Agboola: Upper.
23 00:05:55.670 ⇒ 00:05:56.210 Robert Tseng: Yeah.
24 00:05:56.210 ⇒ 00:05:56.810 Demilade Agboola: I think.
25 00:05:56.930 ⇒ 00:06:00.620 Demilade Agboola: cause I have a call with her today, so that would I could just kill 2 birds with one stone.
26 00:06:00.850 ⇒ 00:06:01.710 Robert Tseng: Great
27 00:06:02.320 ⇒ 00:06:20.530 Robert Tseng: love to hear that. Okay, cool. And then I think we gave Mattash clarification already on like the but did I don’t know, did we? I feel like he came in, asked a question about why ncac was moving. We were gonna check on it. Can we? Yeah, did we did we look into that.
28 00:06:24.758 ⇒ 00:06:31.189 Demilade Agboola: Yes, I started looking on it. I haven’t been able to figure out why, but I’m still like keeping an eye out on that.
29 00:06:32.470 ⇒ 00:06:37.139 Robert Tseng: Okay, let’s just kinda quickly create a ticket or feel like we already have one.
30 00:06:39.280 ⇒ 00:06:40.530 Demilade Agboola: I don’t think so.
31 00:06:42.190 ⇒ 00:06:42.940 Robert Tseng: Okay.
32 00:06:47.570 ⇒ 00:06:49.989 Robert Tseng: Y and cats over there.
33 00:06:51.540 ⇒ 00:06:57.190 Robert Tseng: And let’s just I would consider that urgent just to
34 00:06:59.240 ⇒ 00:07:02.510 Robert Tseng: give him peace of mind over what he’s looking at.
35 00:07:04.340 ⇒ 00:07:05.070 Robert Tseng: Yeah.
36 00:07:07.720 ⇒ 00:07:12.330 Robert Tseng: Still paid growth one.
37 00:07:18.080 ⇒ 00:07:18.950 Robert Tseng: It’s good
38 00:07:23.520 ⇒ 00:07:25.119 Robert Tseng: toss this in here.
39 00:07:31.120 ⇒ 00:07:35.749 Robert Tseng: my screen being shared, by the way, because I can’t see, like the yellow box around it that normally has.
40 00:07:37.320 ⇒ 00:07:39.130 Demilade Agboola: Yeah, I can see your linear.
41 00:07:39.310 ⇒ 00:07:40.320 Robert Tseng: Okay, cool.
42 00:07:45.390 ⇒ 00:07:47.621 Robert Tseng: Okay, so that’s that.
43 00:07:48.320 ⇒ 00:07:51.919 Robert Tseng: Gonna see? Great. You and Katie are gonna meet.
44 00:07:57.470 ⇒ 00:08:02.130 Robert Tseng: Yeah. Any booth win stuff?
45 00:08:02.510 ⇒ 00:08:09.339 Robert Tseng: Where are we with this? Okay, send a note. She didn’t look at it yet, or like, What’s what’s the next step here.
46 00:08:13.278 ⇒ 00:08:16.779 Annie Yu: Correct me if I’m wrong, Tim Laude. But to my knowledge.
47 00:08:16.950 ⇒ 00:08:21.760 Annie Yu: right now, with the Cox work that Demoda is working on.
48 00:08:21.880 ⇒ 00:08:29.520 Annie Yu: we will be able to estimate, to get like the numbers of dispense dollar amounts
49 00:08:29.920 ⇒ 00:08:32.579 Annie Yu: like in terms of what should have been.
50 00:08:34.179 ⇒ 00:08:41.630 Annie Yu: and then compare that with actual amount that boost when charged.
51 00:08:42.780 ⇒ 00:08:44.879 Demilade Agboola: Yeah, I think.
52 00:08:46.499 ⇒ 00:08:57.939 Robert Tseng: She just asked for vial size. She can do the like the pricing estimation exercise. Because, yeah, like for us, it’s like manually stitching like cogs, whatever like she, I don’t think she yeah, like
53 00:08:58.589 ⇒ 00:09:03.229 Robert Tseng: the minimum viable product. Here is just the vial size. So.
54 00:09:03.230 ⇒ 00:09:07.170 Annie Yu: Yeah. And the limitation is, now we have lots of nulls
55 00:09:07.430 ⇒ 00:09:09.430 Annie Yu: from from the data we have.
56 00:09:09.910 ⇒ 00:09:22.420 Robert Tseng: Yeah, I still don’t see us quantifying like, what percentage of orders or whatever have have nulls or products have nulls? But yeah, sure. I guess it’s like, okay, we’re we’re gonna bring this up with bask
57 00:09:23.241 ⇒ 00:09:28.580 Robert Tseng: I’m gonna plug this sheet again. I recorded video, sent it to the team.
58 00:09:28.780 ⇒ 00:09:33.769 Robert Tseng: I really just asked Damalade, and a wish to wash it. Watch it. But
59 00:09:33.920 ⇒ 00:09:40.930 Robert Tseng: I think, yeah, this is Basque data quality, deep dive. Everyone here should be able to have access to it.
60 00:09:41.100 ⇒ 00:09:53.390 Robert Tseng: Don’t worry about the structure. I’ll clean it up over the weekend, but like, I think if we could just at least focus on Section 2, listing all all the things that we think are wrong, or we need to call out. I’ve already started to
61 00:09:53.730 ⇒ 00:10:04.685 Robert Tseng: throw some ideas on here. Yeah, like, we just need, like, I want, like a full agenda where I can just go and call out everything to to bask and hand this off to them.
62 00:10:05.420 ⇒ 00:10:10.119 Robert Tseng: Once again. It’s like not guaranteed that everything will be solved.
63 00:10:10.220 ⇒ 00:10:14.159 Robert Tseng: resolved. I mean, I’m going to stack rank everything so that I can
64 00:10:14.400 ⇒ 00:10:18.720 Robert Tseng: identify what are the highest priority things that if I
65 00:10:18.780 ⇒ 00:10:45.340 Robert Tseng: picked like basking you to fix 3 things by end of next week, like I’ll I’ll determine what those are. But yeah, if we could. Just, you know, as anytime, the answer has something to do with bask data sucks like, let’s throw it in here. So I I have something to. I’m literally. I’m going to their office on Tuesday like Bask’s office. And I’m gonna like talk to them. So I think, that’s that’s why that’s why this is here.
66 00:10:47.960 ⇒ 00:10:55.909 Robert Tseng: Okay, cool. So I’m just gonna throw a quick note here. Any details to
67 00:11:00.650 ⇒ 00:11:01.520 Robert Tseng: Great.
68 00:11:04.160 ⇒ 00:11:09.732 Robert Tseng: Okay? Yeah. Other than that. Mattesh doesn’t respond to other stuff.
69 00:11:10.670 ⇒ 00:11:13.919 Robert Tseng: share of patients with sla pharmacy. So
70 00:11:14.810 ⇒ 00:11:28.409 Robert Tseng: quick question on this would be Annie. Like we, we read, we updated the order journey, dash! We sent it out. I know you did like some kind of follow up video on like what you added the new tables and stuff. Did we get any other feedback on that.
71 00:11:29.460 ⇒ 00:11:31.500 Annie Yu: No, not to my knowledge.
72 00:11:31.850 ⇒ 00:11:37.900 Robert Tseng: Okay, and we shared it in farm Ops. I believe.
73 00:11:38.340 ⇒ 00:11:38.690 Annie Yu: Yes.
74 00:11:38.690 ⇒ 00:11:51.315 Robert Tseng: So I will just double tap and be like, Okay, Sarah and Rebecca. Any any
75 00:11:55.840 ⇒ 00:11:57.809 Robert Tseng: Any questions about this?
76 00:11:58.570 ⇒ 00:12:02.030 Robert Tseng: Was it helpful? How is it being used?
77 00:12:02.210 ⇒ 00:12:03.130 Robert Tseng: Okay?
78 00:12:03.420 ⇒ 00:12:04.220 Robert Tseng: Great.
79 00:12:05.280 ⇒ 00:12:10.340 Robert Tseng: Just sent that. Yeah.
80 00:12:10.510 ⇒ 00:12:18.319 Robert Tseng: And then I think this is also on the same view or same dashboard. So no questions there
81 00:12:19.030 ⇒ 00:12:24.882 Robert Tseng: roadmap for Emr project. Thank you. Awaish for sending that message.
82 00:12:26.390 ⇒ 00:12:30.199 Robert Tseng: yeah, it’s also kind of like we’re chasing them. Now, it’s like, okay. Well.
83 00:12:31.620 ⇒ 00:12:57.080 Amber Lin: Yeah for the roadmap. Once you guys have a have more in the audit. I know you just shared a notion dollar. I assume it’s for the same thing. Once we have more of that, I can help make the roadmap and present to the Eden team to talk about. Hey? This is what we found. This is what you we envision of current state and future state. And this is what needs to get done. So I need the audit to do that.
84 00:12:58.170 ⇒ 00:13:00.069 Awaish Kumar: Yeah, like, the more like
85 00:13:00.630 ⇒ 00:13:09.129 Awaish Kumar: I’m I’m not sure how to visualize it, because mostly it is like the data which is coming from bus is a is a just a list of tables
86 00:13:09.760 ⇒ 00:13:11.059 Awaish Kumar: and the fields.
87 00:13:11.250 ⇒ 00:13:19.570 Awaish Kumar: And then, yeah, we have few tables which can be modified like order. We want
88 00:13:19.690 ⇒ 00:13:22.149 Awaish Kumar: orders and order. Item thing.
89 00:13:22.260 ⇒ 00:13:27.620 Awaish Kumar: but that’s just like one or 2 tables which can, which is which are going to be split
90 00:13:28.628 ⇒ 00:13:35.810 Awaish Kumar: into 2. But a lot of different other tables which are already there are going to stay the same.
91 00:13:37.540 ⇒ 00:13:44.730 Awaish Kumar: So like, even if I create a kind of a diagram or something. It’s it will be just the names of the keyboards.
92 00:13:46.730 ⇒ 00:13:50.009 Awaish Kumar: because they are not really a kind of database design
93 00:13:51.270 ⇒ 00:13:59.110 Awaish Kumar: with with some relationships. So it’s just a list of table, the list of tables which are getting the events from segment.
94 00:13:59.530 ⇒ 00:14:23.413 Amber Lin: Yeah, I see is I mean, it’ll be great if you can document that somewhere. I know I’ve seen the tables that you shared I’ve read a little bit about the current audit that we’re doing. I just the more that we document, the easier the roadmaps gonna be and then, like I put it together. But I feel like it’s lacking some
95 00:14:24.430 ⇒ 00:14:34.590 Amber Lin: It didn’t document the real consequences that they’re facing now. So let me know when that’s in a better state, and then I can go back and revise the roadmap.
96 00:14:38.000 ⇒ 00:14:46.769 Robert Tseng: Yeah. So just let’s let’s try to be a bit clear on this. So I guess, yeah, we’ve referencing a couple of docs. This is a wish
97 00:14:46.880 ⇒ 00:14:53.010 Robert Tseng: great. This is like line by line, every table that we currently have for bask everything that needs to be preserved.
98 00:14:53.351 ⇒ 00:15:01.460 Robert Tseng: Which is great. I think this answers the what is the current state? What do we have? I think anyone can click into this and like kind of figure that out. Understand the schema?
99 00:15:01.940 ⇒ 00:15:06.490 Robert Tseng: Oh, weird that it didn’t auto open in notion.
100 00:15:06.840 ⇒ 00:15:11.210 Robert Tseng: So yeah, I think that works. And then, yeah, I think, like amber saying, we’re trying to figure out.
101 00:15:11.370 ⇒ 00:15:24.249 Robert Tseng: yeah, this is like the audit of everything currently. But like, what’s yeah, like, where where do we need to be? It doesn’t have to be like some fancy visualization like architecture, diagram, or whatever. I think.
102 00:15:24.470 ⇒ 00:15:27.483 Robert Tseng: I think this is a good one for
103 00:15:28.450 ⇒ 00:15:46.830 Robert Tseng: amber to kind of jump in on because we have no relationship with the Emr team. Currently. So this is net. New stakeholder should be good, like good way to kind of like, dip your toes into this work because it’s not urgent yet. It’s important. But yeah, we’re just trying to get some alignment here. So the Emr team.
104 00:15:47.276 ⇒ 00:15:51.560 Robert Tseng: Yeah, we should. Yeah, just kind of think through some objectives, you know, between
105 00:15:51.740 ⇒ 00:15:53.649 Robert Tseng: oats and amber. I’m hoping.
106 00:15:53.650 ⇒ 00:15:59.321 Awaish Kumar: Yeah, I, yeah, I was like, like in in these tables and also in these
107 00:15:59.990 ⇒ 00:16:05.470 Awaish Kumar: even for individual field, I have a column which is like if it is used by brain force.
108 00:16:05.670 ⇒ 00:16:12.070 Awaish Kumar: So what I’m planning to do is like the second exercise for me is to go in.
109 00:16:12.210 ⇒ 00:16:16.010 Awaish Kumar: figure out all the tables which are we are using in some modeling or
110 00:16:16.190 ⇒ 00:16:18.649 Awaish Kumar: anywhere in our work, and then
111 00:16:18.750 ⇒ 00:16:24.729 Awaish Kumar: also find out which of which fields are being used, so we can define the objectives based on that like.
112 00:16:24.940 ⇒ 00:16:27.749 Awaish Kumar: this is milestone one like that’s the field.
113 00:16:27.860 ⇒ 00:16:31.820 Awaish Kumar: The tables and fields are between, which is which are being used in downstream modeling
114 00:16:32.409 ⇒ 00:16:45.579 Awaish Kumar: which are like directly, or like, responsible for our tableau dashboards, for example, they are like we can split them in then milestones. This is milestone one like we need these tables.
115 00:16:45.920 ⇒ 00:16:51.850 Awaish Kumar: This is, too, and then all of other are like, yes, you can add it right, you know.
116 00:16:52.220 ⇒ 00:16:53.589 Awaish Kumar: later milestones.
117 00:16:54.420 ⇒ 00:17:02.550 Amber Lin: Okay. Sounds good. I wish I will. I’ll go ask you. I’ll take what you said, and I’ll ask you for feedback and for the milestones.
118 00:17:02.730 ⇒ 00:17:04.859 Amber Lin: When we, when I make the format.
119 00:17:06.040 ⇒ 00:17:15.610 Robert Tseng: Cool. So yeah, that’s part of the information we need to share with them. The other side is like, I have no idea what they’re doing so like, I kinda need to know their timeline. I need to like, yeah, like we.
120 00:17:15.780 ⇒ 00:17:34.899 Robert Tseng: you know, if I’m meeting with Elt tomorrow, you know, Josh Adam are gonna ask me, you know, what’s the 3 month? Kind of like timeline here? Yeah, I can talk about all the immediate stuff we’re doing. But I want to be able to place the Emr work appropriately. Maybe I won’t get that answer by tomorrow, which is fine. I can just, you know I can.
121 00:17:35.480 ⇒ 00:17:52.839 Robert Tseng: I can make something up. It’s fine. But yeah, I think this is definitely something I would want to know. Is this coming in the next month, like everyone’s been saying, it’s coming in July. I don’t believe it is. I think September is probably more likely. But I don’t really know, because I haven’t talked to them. So
122 00:17:52.960 ⇒ 00:17:56.430 Robert Tseng: I’m hoping that we’re gonna get some information from them as well.
123 00:18:00.250 ⇒ 00:18:01.920 Robert Tseng: Yep, okay. So I’ll just.
124 00:18:01.920 ⇒ 00:18:09.600 Awaish Kumar: I’ve also sent a message to Ayush like he’s 1 from intact team on the Mr. Side.
125 00:18:09.890 ⇒ 00:18:10.300 Robert Tseng: Yeah.
126 00:18:10.480 ⇒ 00:18:13.609 Awaish Kumar: Like he can. Few few like.
127 00:18:14.030 ⇒ 00:18:20.669 Awaish Kumar: Some time ago he, he this year, like they are working on this. And I just sent a message to to see the
128 00:18:20.840 ⇒ 00:18:22.860 Awaish Kumar: like where they are, with the interaction.
129 00:18:23.640 ⇒ 00:18:45.319 Robert Tseng: Okay, yeah, I would say, don’t DM, ayush, like everything. Should you know Adam’s a CEO. So like, you know, if if you chat in these groups like he’s gonna see that they’re ignoring and whatever like, I don’t know if you’re if you just being responsive. But yeah, you could see that these guys will respond if Adam’s there. So just like, yeah, I mean as much as you can just use these channels like, I think, probably better.
130 00:18:49.100 ⇒ 00:18:52.930 Robert Tseng: Okay, cool. Let’s quickly hand off.
131 00:18:53.640 ⇒ 00:19:01.130 Robert Tseng: Not urgent. So I mean, this will. This will happen when it happens? You’re gathering all the g sheets hopefully, we don’t have a due date on this.
132 00:19:01.470 ⇒ 00:19:02.540 Robert Tseng: I think
133 00:19:02.810 ⇒ 00:19:09.300 Robert Tseng: if we can still get this out by tomorrow, because this doesn’t involve us pushing any code, I think that’d be great.
134 00:19:10.500 ⇒ 00:19:15.390 Robert Tseng: Yeah, maybe a quick cogs update. I know I saw some. Prs pushed
135 00:19:15.820 ⇒ 00:19:21.729 Robert Tseng: the past 12 h. So curious kind of impact any of these? Do we need to click into anything here.
136 00:19:23.195 ⇒ 00:19:27.944 Demilade Agboola: No, there’s not click into anything here. The Prs are for the
137 00:19:29.100 ⇒ 00:19:35.070 Demilade Agboola: The reports here for the monthly refunds as well as the daily
138 00:19:35.290 ⇒ 00:19:39.319 Demilade Agboola: in transit, and deliver delivered orders.
139 00:19:41.230 ⇒ 00:19:41.940 Robert Tseng: Okay.
140 00:19:43.630 ⇒ 00:19:44.340 Demilade Agboola: For Co.
141 00:19:44.790 ⇒ 00:19:46.510 Demilade Agboola: In terms of cops, though.
142 00:19:47.089 ⇒ 00:20:11.669 Demilade Agboola: I’m still trying to get Rebecca to be able to figure out how we will rebuild that in terms of like the historical data. But obviously, it’s part of things we said. We want to talk about with Bask. I have my internal list like I’m compiling. I have about 5 items, but I I think that they’ll definitely more than 5 things we need to bring up like that. I have noticed with Bask, and I would add them to the notion. Doc.
143 00:20:12.200 ⇒ 00:20:29.270 Robert Tseng: Yeah, is there? If you have a hard time getting a hold of Rebecca, is this something that you can get from Christiana because Christiana is the operator. Rebecca doesn’t go into any of this stuff. So she’s a bit kind of zoomed out kind of maybe like me on the data side. So yeah, I wonder like if there’s a better escalation path for you.
144 00:20:30.380 ⇒ 00:20:40.830 Demilade Agboola: I mean I I literally started with Christiana and Christiana escalated to Rebecca. So I don’t know if cause Christiana was like, you know Rebecca because she talked Rebecca. And all of this.
145 00:20:42.260 ⇒ 00:20:45.940 Robert Tseng: Okay, got it.
146 00:20:46.260 ⇒ 00:20:52.948 Robert Tseng: Alright. So you’re kind of blocked from feedback on Rebecca. I I hear that I under understand. Okay?
147 00:20:55.230 ⇒ 00:21:01.479 Robert Tseng: yeah, I’ll probably just try to find time between between you and Rebecca, and I’ll just grab time on her calendar and throw something on there.
148 00:21:03.550 ⇒ 00:21:04.240 Robert Tseng: Does that help?
149 00:21:04.240 ⇒ 00:21:06.079 Robert Tseng: Yes, I do have 30 min with her.
150 00:21:06.750 ⇒ 00:21:08.110 Demilade Agboola: Yeah, that sounds good. That sounds good.
151 00:21:08.680 ⇒ 00:21:10.260 Robert Tseng: Alright, you bet.
152 00:21:10.845 ⇒ 00:21:23.610 Robert Tseng: Cool. So you’re gonna do the Ncac. Investigation if I can get that and obviously respond on in the slack thread in the general analytics channel that Mattesh commented. That’d be great meeting with Katie. Great good.
153 00:21:24.275 ⇒ 00:21:41.469 Robert Tseng: Yeah, web hook missing data. I answered this yesterday. So I’m just gonna reassign it to myself. And this was covered in my loom. Video, I think just as like a quick tldr, I mean, I don’t know, maybe worth watching for, Henry as well.
154 00:21:41.870 ⇒ 00:21:55.420 Robert Tseng: But oh, I can’t open the other tab, because it probably timed out. Basically, the conclusion was.
155 00:21:57.880 ⇒ 00:21:58.690 Robert Tseng: yeah.
156 00:21:58.880 ⇒ 00:22:08.949 Robert Tseng: you know, we already knew this to some extent, but order statuses via the vast webhook are nonsense. They don’t really reflect true order. Behavior took a 6 month monthly average of
157 00:22:09.420 ⇒ 00:22:32.381 Robert Tseng: orders by status that were actually shipped to the pharmacy, and you can see that no matter what status most of them do get shipped to the pharmacy. So that tells me that these are not reliable, obviously sent to pharmacy makes sense that it would be, you know. That’s what you would expect to be sent to pharmacy errored orders. I would expect this number to be 0. So
158 00:22:32.710 ⇒ 00:22:41.739 Robert Tseng: I think, yeah, on the on what I’ve been doing on the tagging and tracking side with the specific filters that we were being asked for.
159 00:22:41.800 ⇒ 00:22:47.649 Robert Tseng: This is something that I’ll eventually come to a wish I might need your help on this, or I will need your help on this today.
160 00:22:48.632 ⇒ 00:23:06.769 Robert Tseng: I tried to fire the order completed. Web hook itself, or like the data coming in from there the payload into Meta ads. I was able to filter by 1st time orders, but I’m not able to filter by ship to pharmacy like is shipped to pharmacy. Yes, no.
161 00:23:07.271 ⇒ 00:23:17.239 Robert Tseng: I’m assuming that we get that that is shipped to pharmacy off of order shipped, which is kind of the same. At least that was the web hook I was looking at.
162 00:23:17.460 ⇒ 00:23:21.750 Robert Tseng: I’ll just pop. Does that make sense? Is that? Where is that? Where is shed to pharmacy came from?
163 00:23:24.660 ⇒ 00:23:26.379 Robert Tseng: Does anyone know off the top of your head?
164 00:23:27.970 ⇒ 00:23:28.530 Awaish Kumar: No.
165 00:23:29.400 ⇒ 00:23:29.990 Robert Tseng: Yes.
166 00:23:30.730 ⇒ 00:23:33.420 Awaish Kumar: I don’t remember right now. I can check.
167 00:23:33.420 ⇒ 00:23:43.440 Robert Tseng: Okay, yeah. So if you could, just, you know, run this query, just just kind of check me on this like, this is my understanding of like how we validate an order that has actually been shipped to pharmacy.
168 00:23:43.640 ⇒ 00:24:03.900 Robert Tseng: I’m using that as a proxy, for whether or not a patient actually got, approved, Rx approved. I guess because we don’t really have an event that’s like, Oh, doctor says, Okay, we’ll give you drugs kind of thing. So I kind of just use the the next event that I could think of, which seems to be sent to pharmacy.
169 00:24:04.351 ⇒ 00:24:24.228 Robert Tseng: But because they come from 2 different web hooks I need to. I needed like a custom function, and segment won’t let me do that. We have to send it from the warehouse, and so I need a model, or I don’t think order summary will do it. But basically I need a model. That kind of combines like order completed and order shipped
170 00:24:24.530 ⇒ 00:24:42.410 Robert Tseng: or just like maybe order. Summary kind of gets us somewhere there. I need to just double check. But I think I could pair if I could pair with with you, or something, just to make sure I’m using the right model to get this event to to Meta. That would be helpful.
171 00:24:43.450 ⇒ 00:24:47.479 Awaish Kumar: Okay. So ownership is great. Like center. Pharmacy is coming from there.
172 00:24:47.870 ⇒ 00:25:08.739 Robert Tseng: Yeah, exactly so, tldr, my, the meta thing hasn’t finished yet, because I can’t fire it from a single web hook I need to use like something from the warehouse. So I just need to pick the right model. We need to build one really quick, like we can. We can do it. But I generally it’s it’s it should be the way that I’ve constructed this
173 00:25:09.231 ⇒ 00:25:28.308 Robert Tseng: and then, as far as reliability, I looked at just the distribution of orders that were sent to pharmacy. I think, yeah, basically, you can see that it’s should be reliable. It’s like 90 something percent, that of orders. Over 90% of orders get sent within 7 days.
174 00:25:29.270 ⇒ 00:25:30.710 Robert Tseng: yeah. So
175 00:25:32.490 ⇒ 00:25:42.535 Robert Tseng: oh, I guess this is only for order status sent to pharmacy. Maybe I have to rerun this for all statuses, but I would still assume it’s probably above 90%. So I think it’s fine to use
176 00:25:43.280 ⇒ 00:25:57.229 Robert Tseng: 92 to 97%. Right? Okay? So 92 to 97% of orders are shipped within Meta’s attribution window. So I don’t think we have an issue with using this approach.
177 00:25:57.720 ⇒ 00:26:07.413 Robert Tseng: So that is what I kind of was trying to get working yesterday. I think it’s clear, and I’m ready to try to push it to production today.
178 00:26:08.790 ⇒ 00:26:22.749 Robert Tseng: yeah, I guess that’s not really a ticket, because I didn’t create tickets for myself. But that’s just to kind of catch you guys up on what I’m doing there. So relevance to Henry, I know that I asked you to kind of in parallel. Look at the Google ad side
179 00:26:22.750 ⇒ 00:26:44.539 Robert Tseng: basically need to fire the same event. So whatever model I end up coming up with a wish, I think you should be able to use that to fire the conversion event into Google ads. I think the conversion window or the attribution window is different. It’s probably less than 7 days. So we may have to adjust our assumptions here, but I think
180 00:26:44.710 ⇒ 00:26:49.780 Robert Tseng: it probably won’t be like 90%. It might be like 80% of orders will be within the window.
181 00:26:49.930 ⇒ 00:27:01.149 Robert Tseng: But either way, it’s all better than what currently there is, which is, you know, 200% plus over counting. So I think whatever we’re gonna do is gonna get us closer.
182 00:27:01.970 ⇒ 00:27:06.959 Henry Zhao: Are we able to adjust the attribution window? I had always thought that that was something customizable.
183 00:27:08.020 ⇒ 00:27:27.765 Robert Tseng: Yeah, I mean, frankly, I’ve never adjusted. I just always assume that marketers will do it. But like this, yeah, I mean, if you feel confident that that’s possible, and we can adjust the Google, you know window. Then I think I don’t. I don’t think Meta’s window goes higher. I think that’s that’s that’s pretty. That’s pretty set
184 00:27:28.100 ⇒ 00:27:30.319 Henry Zhao: I’ll see if I can do 7 for Google. Yeah.
185 00:27:30.830 ⇒ 00:27:36.310 Robert Tseng: Okay, sweet, do you have access to Google ads and everything that you need to see on on that side or.
186 00:27:36.520 ⇒ 00:27:39.330 Henry Zhao: Let me take a look. Let me see if it’s in one pass.
187 00:27:40.210 ⇒ 00:27:47.431 Robert Tseng: Yeah, it might not, because I’ve never gone in there. So I yeah, if not, you can just let me know
188 00:27:48.290 ⇒ 00:27:49.070 Robert Tseng: cool
189 00:27:49.750 ⇒ 00:27:54.960 Robert Tseng: alright. So I think that gets through everything. I’m just gonna not talk about the stuff that’s blocked.
190 00:27:55.690 ⇒ 00:28:22.580 Robert Tseng: yeah, amber. If you could kind of help me like just review things in cycle. Anything that needs to be pulled in, I think at least, what I think would be helpful is like cause we pre we? We talk through a lot in these meetings. Anything that needs to be added. I think if we could, just if you could pull it in like Async. And then, just like tag someone in the slack channel. I think that’s a good way to kick it off so that they’re aware that. That’s something that we need to follow up on.
191 00:28:23.970 ⇒ 00:28:24.530 Robert Tseng: Okay.
192 00:28:25.570 ⇒ 00:28:43.879 Robert Tseng: yeah. So like, I’ll just use this as an example price negotiation. You know, Henry and I were working on this segment came back with a much better price than I thought. I think they’re wrong on their assumption. So there’s yeah like I. If Henry, if you could. Just, you know, sanity check me on that, I think.
193 00:28:44.530 ⇒ 00:28:49.899 Henry Zhao: Yeah, why did they? Why did they quote 4 million events? If we asked for 15 to 20 million.
194 00:28:50.170 ⇒ 00:28:58.460 Robert Tseng: Yeah, I I think they just wanted to. I don’t know some kind of weird play here. So I very clearly said 15 to 20, but like, I think.
195 00:28:58.460 ⇒ 00:29:04.269 Henry Zhao: And why and why is functions in hours? Did you see the chart? It said, functions 60 h.
196 00:29:05.277 ⇒ 00:29:18.859 Robert Tseng: I think it’s not in hours. I think it’s in like number of functions, because I was capped at 20 or 25. And then I asked them to double the functions or something, and then they just
197 00:29:19.450 ⇒ 00:29:21.899 Robert Tseng: I don’t know. They they increased it to 60.
198 00:29:22.640 ⇒ 00:29:25.230 Henry Zhao: Okay, let me just reach out and just clarify on these points.
199 00:29:25.540 ⇒ 00:29:26.880 Robert Tseng: Okay, cool.
200 00:29:27.926 ⇒ 00:29:36.079 Robert Tseng: Yeah. Anything else? I guess, Henry, on your side that we haven’t checked. I talked about all the customer. I/OI guess on Eden 50.
201 00:29:36.210 ⇒ 00:29:39.499 Robert Tseng: We just met with Bobby. You review the transcript there.
202 00:29:39.956 ⇒ 00:29:52.689 Robert Tseng: Yeah, I guess I just didn’t really synthesize. Like, okay, I wanna be able to come back with that model if we could kind of get that today of like, okay, we walked him through the customer enriched model.
203 00:29:52.850 ⇒ 00:29:59.140 Robert Tseng: He kind of just gave us an audible on what else he uses in in customer I/O,
204 00:29:59.400 ⇒ 00:30:09.850 Robert Tseng: and I just want to take that schema of the table and send it to Cutter, who’s the head of growth and be like, okay, here it is like, this is what we’re gonna build and push into Customer I/O,
205 00:30:10.280 ⇒ 00:30:13.420 Robert Tseng: other than that. We’re kind of blocked on like
206 00:30:13.950 ⇒ 00:30:20.099 Robert Tseng: the actual testing. Because, you know, he’s putting together that data glossary.
207 00:30:20.340 ⇒ 00:30:28.879 Robert Tseng: I think the biggest challenge we’re gonna run into is just getting all the data in the same format. That customer I/O kind of has, you know, like
208 00:30:29.020 ⇒ 00:30:33.340 Robert Tseng: it’s so we do need that information from him. I think.
209 00:30:34.570 ⇒ 00:30:35.230 Henry Zhao: Okay.
210 00:30:36.080 ⇒ 00:30:36.730 Robert Tseng: Yeah.
211 00:30:38.360 ⇒ 00:30:43.349 Henry Zhao: So should I. Just look through customer and rich profiles, and if it looks good, just we can send it to Cutter already.
212 00:30:44.310 ⇒ 00:30:55.730 Robert Tseng: Yeah, I think. I mean, I know you have the granola notes. If there was anything else that was in there that was missing that we don’t have. Then I think we just need to add that. And then I think we’re ready to go.
213 00:30:55.730 ⇒ 00:31:00.249 Henry Zhao: Yeah. All he said was the treatment data needed cleaning up. But I think that’s a separate project, right?
214 00:31:00.560 ⇒ 00:31:01.440 Robert Tseng: Yeah.
215 00:31:02.900 ⇒ 00:31:13.570 Robert Tseng: the treatment summary. Yeah. And that’s we’re not gonna go and turn that off like his whole like treatment objects and Customer island. That’s not something we can do immediately, so we don’t have to.
216 00:31:13.570 ⇒ 00:31:18.889 Henry Zhao: But eventually, yeah. But eventually, I want to work on cleaning up the treatment table. Maybe make a like a different.
217 00:31:18.890 ⇒ 00:31:24.719 Robert Tseng: We don’t even have one in the warehouse. So yeah, we you’re gonna build, or we’re gonna build that from scratch pretty much.
218 00:31:25.100 ⇒ 00:31:25.660 Henry Zhao: Yeah.
219 00:31:26.050 ⇒ 00:31:32.284 Robert Tseng: Yeah, okay, cool. I think we’re doing. We’re on track on that.
220 00:31:34.940 ⇒ 00:31:41.319 Robert Tseng: yeah, I think we kind of ran through everything. I guess
221 00:31:41.760 ⇒ 00:31:49.419 Robert Tseng: with the remaining time we can kind of just pull in a couple things. So emr findings, I guess.
222 00:31:50.140 ⇒ 00:31:56.360 Robert Tseng: Oh, these are the same ticket, these 2, I guess. So apologies for that. But I guess
223 00:31:57.430 ⇒ 00:32:05.560 Robert Tseng: you guys can consolidate when you’re in event, volume tracker.
224 00:32:05.790 ⇒ 00:32:11.060 Robert Tseng: Yeah, I mean, this was, yeah. Wish. If this is not
225 00:32:11.750 ⇒ 00:32:26.950 Robert Tseng: fat, like too slow. I I just wanna like I don’t always trust like what I see in tools. So I just wanna make sure that number of events that we’re actually streaming into bigquery. From segment. I think we should be able to just kind of take a look at this
226 00:32:28.440 ⇒ 00:32:32.850 Robert Tseng: if it’s just running a query. Yeah. Anyway, if if it’s
227 00:32:32.970 ⇒ 00:32:37.037 Robert Tseng: if you think you can do it like just I think that would be helpful.
228 00:32:37.580 ⇒ 00:32:43.590 Awaish Kumar: Do you need like coming from Baskel any from anywhere like from any.
229 00:32:43.590 ⇒ 00:32:49.600 Robert Tseng: Yeah, any anything coming from segment? Yeah. So including the basketball hooks and all that, like, I kind of just wanted.
230 00:32:49.800 ⇒ 00:32:55.479 Robert Tseng: make sure that it makes sense to like what segments reporting to us.
231 00:32:56.250 ⇒ 00:32:56.990 Awaish Kumar: Okay.
232 00:32:57.680 ⇒ 00:32:58.310 Robert Tseng: Yeah.
233 00:32:58.890 ⇒ 00:33:05.240 Robert Tseng: Cause if they’re telling us, like, Oh, 15 million. And then it’s actually like 10 million events like, I want to be able to
234 00:33:05.570 ⇒ 00:33:14.600 Robert Tseng: like, I don’t know. I just I don’t. I want to verify what they’re saying. So, okay, cool.
235 00:33:14.700 ⇒ 00:33:15.890 Robert Tseng: And then.
236 00:33:17.960 ⇒ 00:33:27.777 Robert Tseng: yeah, I feel like amber, and Annie’s pretty light, so like if there’s anything that you want to pull that pull in. And then I think, ad hoc stuff that’s coming her way like I think,
237 00:33:28.450 ⇒ 00:33:32.290 Robert Tseng: we we yeah, we we feel like we need to figure out how to add
238 00:33:32.410 ⇒ 00:33:34.020 Robert Tseng: kind of add to her plate. So.
239 00:33:37.350 ⇒ 00:33:43.820 Amber Lin: Yeah, alright. I will go look over that once I’m done with another meeting.
240 00:33:45.280 ⇒ 00:33:45.960 Robert Tseng: Okay.
241 00:33:46.750 ⇒ 00:33:47.070 Amber Lin: Yeah.
242 00:33:47.070 ⇒ 00:33:53.839 Robert Tseng: Yeah, I mean at least everything in cycle she can be. She can. She can pull then probably. I mean, some of it won’t happen immediately. But
243 00:33:54.050 ⇒ 00:33:58.049 Robert Tseng: yeah, I think other stuff will come from other outside projects.
244 00:33:59.770 ⇒ 00:34:03.209 Amber Lin: Okay, cool. Alright, thanks. Everyone.
245 00:34:04.130 ⇒ 00:34:05.416 Amber Lin: Thanks. Bye.
246 00:34:06.530 ⇒ 00:34:07.050 Henry Zhao: Bye, guys.