Meeting Title: Robert Tseng’s Personal Meeting Room Date: 2025-06-13 Meeting participants: Robert Tseng, Demilade Agboola, Awaish Kumar, Fireflies.ai Notetaker Joshua, Annie Yu, Josh, cutter
WEBVTT
1 00:02:50.050 ⇒ 00:02:51.110 Demilade Agboola: However, it’s.
2 00:02:52.550 ⇒ 00:02:53.459 Robert Tseng: He didn’t want it.
3 00:02:55.660 ⇒ 00:02:56.799 Robert Tseng: How’s it going.
4 00:02:57.440 ⇒ 00:02:58.910 Demilade Agboola: I’m doing very well. How are you?
5 00:03:00.060 ⇒ 00:03:00.760 Robert Tseng: Heads.
6 00:03:01.390 ⇒ 00:03:03.329 Robert Tseng: Are you in a new place now.
7 00:03:04.780 ⇒ 00:03:08.140 Demilade Agboola: Like. I’m still in multiple, like I have a new house here
8 00:03:08.420 ⇒ 00:03:13.470 Robert Tseng: Yeah, like you. You moved like shortly after you got back to Malta right.
9 00:03:13.960 ⇒ 00:03:28.009 Demilade Agboola: Yes, been chaotic like 2 weeks. I barely had a breather so like personal movement, and having to renew my residence permit here. It’s just a lot of moving parts everywhere. But yeah.
10 00:03:28.410 ⇒ 00:03:32.730 Demilade Agboola: we keep pushing and guessing gets into our skills. I guess.
11 00:03:33.180 ⇒ 00:03:38.650 Robert Tseng: Okay. Well, I hope. Hope it doesn’t have as many roadblocks moving forward.
12 00:03:39.497 ⇒ 00:03:46.720 Demilade Agboola: Yeah, yeah, it’s fine. I think I think right now. Because I have to get a new place because my restaurant wanted to sell the house.
13 00:03:47.280 ⇒ 00:03:47.745 Robert Tseng: So.
14 00:03:48.210 ⇒ 00:03:48.750 Demilade Agboola: Yeah.
15 00:03:48.750 ⇒ 00:03:50.569 Robert Tseng: You weren’t really planning to move. Yeah.
16 00:03:50.940 ⇒ 00:03:52.230 Demilade Agboola: Exactly so. It was just a little.
17 00:03:52.230 ⇒ 00:03:56.900 Robert Tseng: Yeah, cause you’re like moving to the States in December. So then, yeah, you weren’t really looking.
18 00:03:57.310 ⇒ 00:04:05.490 Demilade Agboola: Yeah, so like ideally, I’m trying to get everything in place. It might not be as early as December, but maybe February or March.
19 00:04:05.490 ⇒ 00:04:05.900 Robert Tseng: That’s.
20 00:04:06.930 ⇒ 00:04:18.069 Demilade Agboola: That’s the plan. So I’m trying to like work on that as well. So that’s also another like work stream that’s going on in the background. So yeah, there’s just like multiple things happening.
21 00:04:18.570 ⇒ 00:04:22.440 Robert Tseng: Yeah, I get it. There’s a lot of ambient stress from things going on.
22 00:04:22.440 ⇒ 00:04:28.090 Demilade Agboola: Yeah, yeah, but it’s fine. It’s all good, that is all good.
23 00:04:29.690 ⇒ 00:04:35.850 Robert Tseng: Yeah. Well, I know you wanted to spend some time talking about the cutter thing, so we have a few minutes before the others jump on. I think.
24 00:04:36.490 ⇒ 00:04:38.849 Demilade Agboola: Yeah, sure, I I just wasn’t sure.
25 00:04:39.160 ⇒ 00:04:43.729 Demilade Agboola: I fully understood what what we’re trying to say about like the task.
26 00:04:44.100 ⇒ 00:04:44.650 Demilade Agboola: Oh, it’s.
27 00:04:44.650 ⇒ 00:04:45.130 Robert Tseng: Nothing, about.
28 00:04:45.130 ⇒ 00:04:45.690 Demilade Agboola: Like
29 00:04:48.070 ⇒ 00:04:59.209 Demilade Agboola: cause, like he’s talking to me about like the new order count, and your custom account. So yep, I was trying to understand that. And then you hit me up with the return on ad spend. And I’m just like, Okay, what’s going on here.
30 00:05:00.360 ⇒ 00:05:04.460 Robert Tseng: Oh, yeah, I
31 00:05:04.590 ⇒ 00:05:08.740 Robert Tseng: okay. Well, I mean the 2 dashboards that he’s talking about. I mean, we’ll just pull them up. So
32 00:05:09.990 ⇒ 00:05:13.919 Robert Tseng: maybe I misspoke. I thought I reviewed everything in my notes. But
33 00:05:19.710 ⇒ 00:05:24.500 Robert Tseng: it will start telling me, I’m really
34 00:05:33.240 ⇒ 00:05:34.190 Robert Tseng: okay.
35 00:05:37.910 ⇒ 00:05:57.010 Robert Tseng: Okay. So he’s saying, like, Yeah, I mean, these customer accounts like, Look, look off right. So he was talking to you about the customer accounts. Yeah, the Ross is like a byproduct of whatever we get here. So if the customer accounts change and the Ross changes. So I think that might have been the commute, confusing part of my message. But basically what he’s saying. Here is.
36 00:05:57.422 ⇒ 00:06:11.279 Robert Tseng: yeah. The way that new customers should be counted on this dashboard and the growth Kpis dashboard. It’s new customers of that product. Which is why the product sequence model, I thought, was going to be the best way for team for that.
37 00:06:11.410 ⇒ 00:06:17.079 Robert Tseng: because we’re not looking. He’s not looking at net new customers entirely here, like he’s looking at
38 00:06:17.240 ⇒ 00:06:23.887 Robert Tseng: even existing customers. That switch to a new product like that should be considered part of like new looking at new product.
39 00:06:24.550 ⇒ 00:06:25.490 Robert Tseng: I,
40 00:06:26.630 ⇒ 00:06:34.429 Robert Tseng: or really the main metric he’s looking at is Roas. So he wants that to be considered in in the in this dashboard and the growth kpis dashboard. Does that make sense.
41 00:06:35.530 ⇒ 00:06:38.185 Demilade Agboola: Okay, Gotcha, so effectively.
42 00:06:39.460 ⇒ 00:06:47.749 Demilade Agboola: the concept of new customer in this concept is not is no longer about like new to Eden. It’s just new to this product.
43 00:06:48.170 ⇒ 00:07:11.350 Robert Tseng: Yeah. And I know he didn’t communicate that very well. So I think that’s what was, that’s what we weren’t aligned on. So he’s saying that like, yeah, this dashboard he looks at for the 120 days of like launching new products. Then afterwards they’re considered a mature product, or they’ll shut off the product entirely, and then the rest of the business kind of looks at like true new customers.
44 00:07:11.460 ⇒ 00:07:17.959 Robert Tseng: So this isn’t really new customers. It’s like new customers on that power. I mean, I don’t know where to think about how we phrase it, but it’s like
45 00:07:18.490 ⇒ 00:07:25.670 Robert Tseng: 1st time customers of that product. That’s really what this is. So yeah.
46 00:07:27.530 ⇒ 00:07:30.330 Demilade Agboola: Okay. Alright, gotcha. That should be
47 00:07:31.260 ⇒ 00:07:34.430 Demilade Agboola: hard to figure out. It’s just basically
48 00:07:36.500 ⇒ 00:07:39.450 Demilade Agboola: yeah. It shouldn’t hurt to like, come up with that.
49 00:07:41.200 ⇒ 00:07:45.129 Demilade Agboola: It’ll just be worth rolling up. Yeah, just rolling up the count
50 00:07:46.140 ⇒ 00:07:51.409 Demilade Agboola: of every customer that has made an order within that product. But
51 00:07:52.540 ⇒ 00:07:55.110 Demilade Agboola: have we made that order previously?
52 00:07:57.060 ⇒ 00:08:03.259 Robert Tseng: Yeah, I mean, I saw your like product sequence model that looked good. I think there’s you know. You look at
53 00:08:08.060 ⇒ 00:08:10.619 Robert Tseng: most of you have your first.st The 1st product.
54 00:08:11.071 ⇒ 00:08:19.850 Robert Tseng: Makes sense like that’s that’s easier like that column, like 1st product timestamp you can use obviously for the 1st product, the second product.
55 00:08:20.530 ⇒ 00:08:47.200 Robert Tseng: I think. Yeah, if their second product falls into one of these new products. You know, that should be when they’re considered a new customer there, right? And same thing with my 3rd product. If their 3rd product is, you know, let’s say, a summer customer their second product they get some more than odt, then they should be counted there and then let’s let’s say they get another 3rd product again. Like. If they go and purchase a med kit, they should also be counted in the med kit. So
56 00:08:47.802 ⇒ 00:08:53.437 Robert Tseng: I I kind of just saw it as like, because we now have this
57 00:08:54.510 ⇒ 00:09:03.149 Robert Tseng: ledger of, like the different types of products that customers have purchased, and the 1st purchase timestamp
58 00:09:03.570 ⇒ 00:09:07.310 Robert Tseng: like, I think, that should be able to get you
59 00:09:07.540 ⇒ 00:09:10.470 Robert Tseng: like help help you with this aggregation right.
60 00:09:10.890 ⇒ 00:09:13.547 Demilade Agboola: Oh, fair enough, fair enough, fair enough. Yeah.
61 00:09:15.100 ⇒ 00:09:18.830 Demilade Agboola: yeah. So we know the day which they count as new customers, basically.
62 00:09:19.800 ⇒ 00:09:25.880 Demilade Agboola: And fair enough. I see what you’re. I see what you’re trying to do that. Yeah, I could just do that. I could do that, roll up
63 00:09:26.985 ⇒ 00:09:29.310 Demilade Agboola: and make it available to any
64 00:09:31.030 ⇒ 00:09:35.919 Demilade Agboola: Also, I know I were talking about it. I she said she might do overthinking it, and
65 00:09:36.610 ⇒ 00:09:49.500 Demilade Agboola: I think potentially she is. But like she’s she was asking about situations where people have like multiple orders across multiple, like so like, sorry, someone has 2 treatments. Say, San Marlene and
66 00:09:50.361 ⇒ 00:10:04.610 Demilade Agboola: what’s it called anyone like thermally, or maybe some other side right? And then they have one order another, order one order of one another, order of one. So a b ab ap ab just doing in terms of like sequence model.
67 00:10:05.248 ⇒ 00:10:07.090 Demilade Agboola: She’s asking like switch like.
68 00:10:07.310 ⇒ 00:10:09.310 Demilade Agboola: where does do we only count?
69 00:10:09.310 ⇒ 00:10:10.750 Demilade Agboola: Oh, stops.
70 00:10:11.250 ⇒ 00:10:11.740 Robert Tseng: Yeah, yeah.
71 00:10:11.740 ⇒ 00:10:12.520 Demilade Agboola: To be.
72 00:10:12.990 ⇒ 00:10:23.850 Demilade Agboola: And I’m like that might be like, quite tricky, because, like literally, what I’m just doing right now is this is where the 1st time A appears, and then the next, like the 1st time B appears.
73 00:10:23.850 ⇒ 00:10:24.580 Demilade Agboola: Yeah, I’m sure
74 00:10:24.580 ⇒ 00:10:29.499 Demilade Agboola: that counts as as a okay. So this was the 1st product. This is the second product.
75 00:10:29.670 ⇒ 00:10:30.620 Demilade Agboola: But, like.
76 00:10:31.140 ⇒ 00:10:39.320 Demilade Agboola: if I’m going to have to do that, I will need to find out where a ends for everybody. So some people that’s currently ongoing. I’m not necessarily sure if we always know
77 00:10:39.450 ⇒ 00:10:46.500 Demilade Agboola: what the order should be like, where we can say this treatment has ended, and then they switch to another treatment.
78 00:10:46.990 ⇒ 00:10:55.160 Robert Tseng: Yeah, I mean, I would imagine there aren’t many customers that are starting new treatments while they’re on other treatments. But yeah, I mean, I think you’re
79 00:10:55.300 ⇒ 00:11:02.390 Robert Tseng: so. Yeah, I think this will. This will evolve. But for now the sequence is really just the 1st time they purchase a 1st time they purchase. B.
80 00:11:02.530 ⇒ 00:11:28.850 Robert Tseng: I mean, I don’t think that people will be switching back and forth so often. So even if they’re on 2 treatments, and they’re running them in parallel like. That’s fine as far as like a sequence perspective. We just care like when they when they purchased A, and then when they also started. B, the complication is, let’s say somebody is on A, then they start B, they stop A, and they stay on B, and then they restart a again, like then we’ll have to like. Have
81 00:11:29.400 ⇒ 00:11:33.390 Robert Tseng: you know, we’ll we’ll probably need to flag like when they.
82 00:11:33.590 ⇒ 00:11:41.141 Robert Tseng: you know, paused or didn’t complete certain treatments, and when they restarted them again, and that might just be a different model entirely.
83 00:11:41.470 ⇒ 00:11:41.870 Demilade Agboola: Yeah, bye.
84 00:11:42.130 ⇒ 00:11:47.530 Robert Tseng: Yeah, I think that I don’t think anybody’s asking for that yet, so I don’t think we have to account for that now.
85 00:11:47.530 ⇒ 00:11:50.820 Demilade Agboola: Okay, fair enough, fair enough. So yeah, yeah.
86 00:11:50.820 ⇒ 00:11:57.829 Demilade Agboola: So yeah, I think that’s fine. Then so we can like neatly tie this up.
87 00:11:58.320 ⇒ 00:12:17.030 Robert Tseng: Okay, yeah. I mean cutters, this kind of urgent for him. So if if you could try to get that out today, I know we don’t really try to make these changes on Fridays. But he’s trying to basically pull the plug on some stuff. So like starting next week, he might shut off one of these products. So I think he really wants that by today.
88 00:12:17.578 ⇒ 00:12:21.762 Robert Tseng: I think it’s kind of obvious like which ones he’d probably consider sh shutting off
89 00:12:22.320 ⇒ 00:12:22.840 Demilade Agboola: Okay? Bye.
90 00:12:22.930 ⇒ 00:12:31.100 Robert Tseng: But yeah, so I think, yeah, once we update that model, if we could refresh the report or just like export and send it to him again. I think that’s basically what he wants.
91 00:12:31.910 ⇒ 00:12:32.570 Demilade Agboola: Okay.
92 00:12:34.040 ⇒ 00:12:39.660 Robert Tseng: Cool all right, hey? Wish
93 00:12:41.600 ⇒ 00:12:42.490 Awaish Kumar: Hello!
94 00:12:44.870 ⇒ 00:12:53.209 Robert Tseng: Yeah, I think, like, I want to just make sure that we’ve closed out anything else that we can ship out today from things that we’re working, that we’ve worked on.
95 00:12:53.705 ⇒ 00:13:00.760 Robert Tseng: Yeah, I wish anything on your side that we that we want, that we feel like is ready to ship out.
96 00:13:02.840 ⇒ 00:13:04.310 Awaish Kumar: I know you kind of helped.
97 00:13:04.310 ⇒ 00:13:05.370 Awaish Kumar: It knows the time for the day.
98 00:13:05.370 ⇒ 00:13:07.744 Robert Tseng: It’s really there’s no issue there.
99 00:13:09.540 ⇒ 00:13:12.710 Awaish Kumar: Yeah. And also, like I, I didn’t understand
100 00:13:13.010 ⇒ 00:13:16.749 Awaish Kumar: this new ticket like about the CIO stuff.
101 00:13:18.620 ⇒ 00:13:19.529 Awaish Kumar: So make this.
102 00:13:19.960 ⇒ 00:13:23.600 Awaish Kumar: Like you. You mentioned some comments from
103 00:13:23.830 ⇒ 00:13:32.220 Awaish Kumar: that someone from Eden. Yeah. And no, not this like.
104 00:13:32.560 ⇒ 00:13:34.000 Robert Tseng: Oh, not this one. Okay.
105 00:13:34.220 ⇒ 00:13:39.630 Awaish Kumar: Yeah, there was another like slack message from, I think, yeah.
106 00:13:39.850 ⇒ 00:13:51.190 Awaish Kumar: But like, we have the dashboard. And they wanted to have see email conversion, using 2 different methods like with the open emails and the
107 00:13:51.330 ⇒ 00:13:57.029 Awaish Kumar: link clicked emails. And that was all right. And it is already modeled out.
108 00:13:58.670 ⇒ 00:14:02.850 Robert Tseng: Oh, we just didn’t! We just didn’t turn it into a dashboard. Is that what it was.
109 00:14:02.850 ⇒ 00:14:04.040 Awaish Kumar: Oh, okay.
110 00:14:11.410 ⇒ 00:14:19.729 Robert Tseng: Sorry. Can I just look at the query like, can I just query it? I just want to see can we just send him like. I don’t even know if there’s a dash for me, I’ll just send him that.
111 00:14:20.780 ⇒ 00:14:23.980 Robert Tseng: What about you, oops?
112 00:14:24.750 ⇒ 00:14:28.419 Robert Tseng: What do we call it like? Oh, oops. This is the wrong balance.
113 00:14:28.420 ⇒ 00:14:35.150 Awaish Kumar: Call like, you know, we engagement model.
114 00:14:37.870 ⇒ 00:14:38.540 Robert Tseng: Okay.
115 00:14:43.170 ⇒ 00:14:45.980 Robert Tseng: engagement, model.
116 00:14:47.790 ⇒ 00:14:56.030 Awaish Kumar: We’re not like, yeah, email, newsletter, at least participant engagement. And.
117 00:15:02.430 ⇒ 00:15:04.000 Robert Tseng: So.
118 00:15:09.060 ⇒ 00:15:15.540 Robert Tseng: and then I mean, this was kind of you got this from his Paul, I guess.
119 00:15:15.540 ⇒ 00:15:17.489 Awaish Kumar: And then there’s another one.
120 00:15:18.560 ⇒ 00:15:20.700 Awaish Kumar: yeah, there’s another one also, like
121 00:15:28.500 ⇒ 00:15:49.210 Awaish Kumar: this is based on CIO data in this model. I’m combining CIO data with our orders, data to to get the conversion and the revenue. I’ve added the latest comment from Qatar that he wanted to see conversion by both ways, like having different columns like
122 00:15:49.470 ⇒ 00:16:07.590 Awaish Kumar: conversion based on email emails opened and conversion based on email link clicked. So I’ve added both of them. And then and there is another model which basically is aggregates this model, which is called like something like email newsletter performance.
123 00:16:08.190 ⇒ 00:16:09.020 Awaish Kumar: Alright.
124 00:16:15.474 ⇒ 00:16:17.390 Robert Tseng: Yeah, I’m just.
125 00:16:17.520 ⇒ 00:16:19.710 Robert Tseng: This is, I think I’m not spelling this correctly.
126 00:16:19.710 ⇒ 00:16:23.599 Awaish Kumar: Okay, yeah, this one.
127 00:16:23.910 ⇒ 00:16:27.500 Awaish Kumar: So this is basically kind of aggregations on top of this one.
128 00:16:35.900 ⇒ 00:16:36.610 Robert Tseng: Okay.
129 00:16:49.920 ⇒ 00:16:50.579 Robert Tseng: Okay.
130 00:16:51.240 ⇒ 00:16:51.990 Awaish Kumar: So, yeah.
131 00:16:54.660 ⇒ 00:17:03.880 Robert Tseng: Yeah, I mean, I feel like it was. I don’t think he really. I mean, he keeps calling it a dashboard, but there’s no dashboard. This is just like a table. So like, I don’t really understand what he said.
132 00:17:07.119 ⇒ 00:17:10.339 Robert Tseng: Yeah, I mean May. If you could, just
133 00:17:12.300 ⇒ 00:17:24.919 Robert Tseng: I I would just export these and then just send it to him via Csv, and then just tell him like, well, yeah, like this, this is the data is data sphere kind of thing like
134 00:17:25.190 ⇒ 00:17:27.500 Robert Tseng: I don’t think they asked for a dashboard, so.
135 00:17:30.680 ⇒ 00:17:31.350 Awaish Kumar: Okay.
136 00:17:32.850 ⇒ 00:17:36.480 Robert Tseng: Yeah, like they call it a dashboard. But this is not a dashboard.
137 00:17:37.810 ⇒ 00:17:39.000 Robert Tseng: yeah, if you could just do that
138 00:17:39.360 ⇒ 00:17:44.809 Robert Tseng: close that out. Yeah, that would be great. So that can be something that we ship today.
139 00:17:48.100 ⇒ 00:17:49.970 Robert Tseng: Yeah. And then I don’t.
140 00:17:49.970 ⇒ 00:17:50.480 Awaish Kumar: Spent, too much.
141 00:17:50.480 ⇒ 00:17:58.399 Robert Tseng: I’m going through tickets. But anything else that we’re trying to ship out today. I know Dave Mulatte has something away from something, Annie, on your end.
142 00:18:00.000 ⇒ 00:18:08.679 Annie Yu: I do have some clarifying question. One is for the order to delivered. So I’m not sure what’s the next step now? Looks like
143 00:18:08.910 ⇒ 00:18:11.420 Annie Yu: Eden’s site also doesn’t.
144 00:18:12.480 ⇒ 00:18:13.980 Annie Yu: No.
145 00:18:14.270 ⇒ 00:18:17.740 Robert Tseng: You didn’t. I don’t know I did. Did you speak with Christiana on this.
146 00:18:17.740 ⇒ 00:18:27.920 Annie Yu: No, but Rebecca said. They also don’t know, and it’s bad. It’s best that our team talks to bask. I think that’s what she said.
147 00:18:29.760 ⇒ 00:18:32.879 Robert Tseng: Nobody takes responsibility for these things.
148 00:18:34.190 ⇒ 00:18:35.650 Robert Tseng: What was that sorry.
149 00:18:36.522 ⇒ 00:18:44.759 Demilade Agboola: I was going to like walk into yesterday, but the bigquery outage thing like messed up my thought process. But basically
150 00:18:45.230 ⇒ 00:18:51.010 Demilade Agboola: I do know that there are some delay. There’s some delivery information within past.
151 00:18:51.719 ⇒ 00:18:56.030 Demilade Agboola: But obviously we use shippel because they have more.
152 00:18:57.180 ⇒ 00:19:04.180 Demilade Agboola: they just have more information. So that’s obviously where like a disparity can come, because sources are different.
153 00:19:04.580 ⇒ 00:19:10.570 Demilade Agboola: But I did want to say that I was going to actually. Now look at the disparity between the Basque
154 00:19:10.680 ⇒ 00:19:27.229 Demilade Agboola: and the ship, or data in terms of like the average time it takes to deliver, or like the time that they say it, they delivered, and see if there’s a disparity. So maybe I can see on average bask on the estimates delivery by, say, 20% or whatever
155 00:19:27.652 ⇒ 00:19:33.639 Demilade Agboola: but that that’s something in my to do. I may have done that, but that was what I was thinking of doing.
156 00:19:34.510 ⇒ 00:19:41.200 Robert Tseng: Okay, yeah. If you could also just give me that like, kind of, I mean, if you yeah, if you could
157 00:19:41.510 ⇒ 00:19:52.369 Robert Tseng: give me a full check on that. Let me let me. I mean, I’ll if there’s a discrepancy, then I can bring it to. I’ll bring it up with bask. Bask is basically just gonna be like whatever this is what we do.
158 00:19:52.480 ⇒ 00:19:58.080 Robert Tseng: And I I mean, I would I would. We just have to decide. Are we? Do we trust fast or ship out more? And I think
159 00:19:58.520 ⇒ 00:20:04.830 Robert Tseng: I mean I think this kind of it’s baseless. But I I would say we’ve trusting Chippo more because they’re the actual
160 00:20:06.710 ⇒ 00:20:07.760 Robert Tseng: fulfillment.
161 00:20:08.200 ⇒ 00:20:18.070 Robert Tseng: They generate those fulfillment labels so they should be the primary like source for that data and bask like, I don’t really know how they actually calculate it. So.
162 00:20:18.290 ⇒ 00:20:21.000 Robert Tseng: But but yeah, if we could get that
163 00:20:21.350 ⇒ 00:20:23.659 Robert Tseng: comparison, I think that would. That would help.
164 00:20:25.210 ⇒ 00:20:26.470 Demilade Agboola: Okay. Sounds good.
165 00:20:26.610 ⇒ 00:20:26.929 Robert Tseng: Okay.
166 00:20:27.530 ⇒ 00:20:33.230 Demilade Agboola: I I can’t promise I’ll do that today. It might be either over the weekend or early Monday, but.
167 00:20:33.570 ⇒ 00:20:42.770 Robert Tseng: Okay. It’s yeah. I that’s fine. I mean.
168 00:20:43.590 ⇒ 00:20:49.350 Robert Tseng: I think she’s just it doesn’t say immersion. It’s just like something that they’re asking about for anything. I’ll just.
169 00:20:50.220 ⇒ 00:21:03.040 Robert Tseng: We can stall by just explaining like, it’s because we’re looking at 2 different sources, and we have to decide like, do we trust bask or ship. Oh, on delivery data, and we think, ship. Oh, but we will talk to bask about it.
170 00:21:04.538 ⇒ 00:21:08.370 Robert Tseng: I can manage the comms around that. There’s no problem there.
171 00:21:09.020 ⇒ 00:21:10.150 Demilade Agboola: Alright, sounds good.
172 00:21:10.600 ⇒ 00:21:14.220 Robert Tseng: Okay, cool and anything else that you’re trying to ship out today.
173 00:21:14.220 ⇒ 00:21:33.065 Annie Yu: Yeah, I do have a few other items that I have to get to today. Once, the type form I do see, there are more requirements now, so I haven’t really looked into that. But I’ll work on that. And then the marketing kpis from a test.
174 00:21:34.560 ⇒ 00:21:41.120 Annie Yu: the yeah. Oish was helping aligning the numbers, and I think they are
175 00:21:41.220 ⇒ 00:21:49.470 Annie Yu: almost ready. So once that’s ready, I can get that free to pay Channel revenue ratio for Natasha.
176 00:21:49.470 ⇒ 00:21:49.990 Robert Tseng: Okay.
177 00:21:50.465 ⇒ 00:21:57.119 Annie Yu: And then the product drill down the product sequence model is also almost ready.
178 00:21:57.120 ⇒ 00:21:58.569 Robert Tseng: Yeah, we talked about that.
179 00:21:58.860 ⇒ 00:22:00.050 Annie Yu: And then.
180 00:22:00.520 ⇒ 00:22:06.330 Robert Tseng: I wanna spend like like just a few seconds on the testing. So I know there’s like multiple requests that he had
181 00:22:06.771 ⇒ 00:22:17.990 Robert Tseng: I mean, even though I’ve like taken them out. You may do better just by kind of like going back to the recording and re re-watching the segment where he’s talking through it, if if you’re
182 00:22:18.150 ⇒ 00:22:21.869 Robert Tseng: cause I know he’s like move channels from paid on, I mean.
183 00:22:23.190 ⇒ 00:22:25.460 Robert Tseng: if I were you, I would approach it by like.
184 00:22:25.760 ⇒ 00:22:31.830 Robert Tseng: I mean, I don’t know how much progress is made on that already, but just structuring, like, okay? Well.
185 00:22:32.030 ⇒ 00:22:37.679 Robert Tseng: kind of break down, like all the different channels like, what are the categories? Right? The unpaid paid?
186 00:22:38.080 ⇒ 00:22:49.029 Robert Tseng: What’s moving to what? And then for the uncategorized like, how like we’re basically have to. We have to us. I mean, it’s mostly customer. I right? So. I think that’s
187 00:22:49.190 ⇒ 00:22:59.010 Robert Tseng: I think he’s the way that he sees the the channels are just different than the way that we’ve we’ve had it modeled so far. So I just
188 00:22:59.340 ⇒ 00:23:09.459 Robert Tseng: rather than you kind of like doing it channel by channel, like if I don’t know if you if you’re clear on what what that kind of overall picture looks like. Now.
189 00:23:09.970 ⇒ 00:23:16.769 Annie Yu: And right now just exclude everything customer. I/O because, according to him, he doesn’t want that to be included in any channel right.
190 00:23:16.770 ⇒ 00:23:19.939 Robert Tseng: Correct. Yeah, he doesn’t want that to be in those 2 charts. Yeah.
191 00:23:19.940 ⇒ 00:23:23.709 Annie Yu: Yeah. And I moved the the offer to paid. So I think
192 00:23:23.820 ⇒ 00:23:29.020 Annie Yu: we are all set now. On like what’s paid. What’s free.
193 00:23:30.830 ⇒ 00:23:41.774 Robert Tseng: Yeah, okay. But did you get the revenue and cost piece, too? Because if it’s if it’s now paid, then we need to recognize both the cost and the revenue. So I think, before we were excluding
194 00:23:43.990 ⇒ 00:23:49.799 Robert Tseng: revenue from from the offer, because we weren’t considering at the primary like paid channel.
195 00:23:52.980 ⇒ 00:24:02.819 Annie Yu: Oh, yeah, that I don’t know. I think a wish will have more context around that.
196 00:24:02.820 ⇒ 00:24:09.700 Awaish Kumar: For the the offer. I think we just get got a 1 message from Rob that
197 00:24:09.920 ⇒ 00:24:12.689 Awaish Kumar: we need to filter out the
198 00:24:13.750 ⇒ 00:24:18.599 Awaish Kumar: the customers which are coming from channel the offer.
199 00:24:18.800 ⇒ 00:24:22.820 Awaish Kumar: and, like we, we should not count them in new customer count, and then.
200 00:24:22.820 ⇒ 00:24:23.320 Robert Tseng: Yeah, well, that.
201 00:24:23.320 ⇒ 00:24:24.220 Awaish Kumar: That’s not.
202 00:24:24.220 ⇒ 00:24:29.909 Robert Tseng: The case anymore, because we’re moving into paid. So okay, I I think you guys, yeah, we we need to.
203 00:24:31.300 ⇒ 00:24:37.610 Robert Tseng: Yeah, can, can you? Can you? Can you meet again? And we we need we need to get this right like he he told us earlier this week. So
204 00:24:39.280 ⇒ 00:24:45.250 Robert Tseng: yeah, like, I’ll link you the the transcript, the the recording like, just watch the segment
205 00:24:45.590 ⇒ 00:24:51.120 Robert Tseng: that. And I mean I I just. I don’t think we’re clear on this. So I think this this is this is important.
206 00:24:53.040 ⇒ 00:24:53.720 Awaish Kumar: Okay.
207 00:24:54.310 ⇒ 00:25:02.214 Robert Tseng: Okay, yeah. So if you can meet any like right after this call like, and I mean you add me, add me to it. I will. I will stay on and we can. We can.
208 00:25:02.910 ⇒ 00:25:05.132 Robert Tseng: we can go through in more detail. But
209 00:25:05.650 ⇒ 00:25:08.300 Robert Tseng: because I mean, I don’t. I don’t. Wanna we?
210 00:25:08.480 ⇒ 00:25:10.369 Robert Tseng: I don’t want to derail it right now.
211 00:25:13.060 ⇒ 00:25:16.159 Robert Tseng: Okay, anything else, Danny.
212 00:25:16.845 ⇒ 00:25:21.800 Annie Yu: One thing I also wanna discuss is the profit refresh.
213 00:25:22.580 ⇒ 00:25:31.330 Annie Yu: So I added, the comments based on Jonah’s feedback, what needs to be considered for profit.
214 00:25:31.790 ⇒ 00:25:38.980 Annie Yu: and there are some fields that we have, and there are some things that we already
215 00:25:39.770 ⇒ 00:25:46.600 Annie Yu: have considered. But, there are just some things that we would need in the key model.
216 00:25:50.180 ⇒ 00:25:57.480 Annie Yu: So net revenue he wants to exclude returns, chargebacks and discounts.
217 00:25:59.185 ⇒ 00:26:02.949 Annie Yu: Which I don’t think we currently
218 00:26:06.860 ⇒ 00:26:21.120 Annie Yu: consider, and I found refund. I know that we have refund amount. We also have order, discount, just not in the model that we’re using, and I didn’t find anything charge back, related.
219 00:26:21.120 ⇒ 00:26:30.870 Robert Tseng: Yeah, there’s no charge back, I mean, did did he do? I mean, he’s just using an assumption. He’s just like putting in a you know, like a percentage, or whatever it’s like. Did he tell you what his sources for these things.
220 00:26:31.460 ⇒ 00:26:32.470 Annie Yu: Nope.
221 00:26:33.040 ⇒ 00:26:33.620 Robert Tseng: Okay?
222 00:26:36.210 ⇒ 00:26:52.710 Robert Tseng: Oh, yeah, I mean, we can’t just like conjure up chargebacks and supply them here. I I mean, I think he’s just on an excel sheet just like calling it 2.9% or something. I don’t. I don’t really think there’s like that much to it. I don’t think he’s pulling it from a source we don’t have. I think he’s just making up these assumptions, but I mean they’re probably right. But he’s.
223 00:26:53.040 ⇒ 00:27:02.340 Annie Yu: So my question is, we use this net revenue, and if that’s the case, we need to account for refund amount and order, discount.
224 00:27:02.830 ⇒ 00:27:10.901 Robert Tseng: No, I I think for the purposes of what we have and the other reporting like we don’t we? We don’t need to include everything that he does.
225 00:27:11.940 ⇒ 00:27:13.013 Robert Tseng: I think.
226 00:27:20.170 ⇒ 00:27:23.659 Robert Tseng: on the cog side we should, but on the revenue side, like
227 00:27:23.850 ⇒ 00:27:30.465 Robert Tseng: including chargebacks in the current in our current reporting like it’s I don’t think it’s necessary like that should just be.
228 00:27:34.300 ⇒ 00:27:50.679 Robert Tseng: I mean, I don’t really want to give him another dashboard like he can just include chargebacks himself like this is something that nobody else in the company really will look at like. It’s it’s something that’s just kind of calculated towards the end of end of month. It’s it’s not. It’s not true. Rep. I mean, it is revenue, but it’s
229 00:27:51.380 ⇒ 00:27:58.130 Robert Tseng: it’s it’s not related to product sales or anything. So I don’t really want to include that awesome.
230 00:27:59.600 ⇒ 00:28:01.009 Annie Yu: So we should just keep.
231 00:28:01.250 ⇒ 00:28:03.810 Annie Yu: Keep it as it is, at least for the rest.
232 00:28:03.810 ⇒ 00:28:07.510 Robert Tseng: Yeah, I mean, I don’t think he’s asking us to update it
233 00:28:07.650 ⇒ 00:28:13.839 Robert Tseng: like on that. I mean on the cog side. I I hear. I think that makes sense like this should impact the way that we view costs.
234 00:28:14.220 ⇒ 00:28:15.429 Annie Yu: Yeah. But I’m gonna charge back.
235 00:28:15.430 ⇒ 00:28:16.050 Robert Tseng: Side. We don’t have to.
236 00:28:16.050 ⇒ 00:28:23.569 Annie Yu: We are pretty close. I see. I just went into Github and see the code, and I think
237 00:28:23.750 ⇒ 00:28:28.339 Annie Yu: with our current cogs we include all those, for, like doctor visits.
238 00:28:28.340 ⇒ 00:28:28.870 Robert Tseng: Yeah, yeah.
239 00:28:29.852 ⇒ 00:28:35.749 Annie Yu: And we don’t have merchant fees, or like material, or supply fees.
240 00:28:36.050 ⇒ 00:28:48.020 Robert Tseng: Yeah, I mean, this is a platform fee. I don’t know what the what, the what the what the percentages. And then I don’t what we don’t. We’ve never gotten supplier material costs from from from the others teams before.
241 00:28:48.020 ⇒ 00:28:52.079 Annie Yu: Does that mean? We are but good as of now?
242 00:28:56.240 ⇒ 00:29:06.019 Robert Tseng: Well, I mean there’s nothing you can do. You can’t make. You can’t make make these up, I think, if anything now we know, like where the difference would be between like how we calculate it versus how Jonah would want to calculate it.
243 00:29:07.720 ⇒ 00:29:13.540 Robert Tseng: I I mean, we have to go and figure out like where he’s getting these these numbers from. I think that’s the next step.
244 00:29:16.320 ⇒ 00:29:26.620 Annie Yu: Yeah, I, yeah, at least from his message. I I’m not sure if he’s using this logic now, I feel like that’s more like a discussion like it would be great to.
245 00:29:27.340 ⇒ 00:29:29.029 Robert Tseng: Oh, I see. Yeah, I mean, it’s
246 00:29:29.920 ⇒ 00:29:34.030 Robert Tseng: yeah. You’re saying it might be more aspirational. He may not actually even have these things yet.
247 00:29:34.030 ⇒ 00:29:36.800 Annie Yu: Yeah, that’s that’s what I thought, at least
248 00:29:37.919 ⇒ 00:29:41.309 Annie Yu: but I also remember you said, if anything, we can
249 00:29:41.690 ⇒ 00:29:44.800 Annie Yu: manually calculate the merchant fee that.
250 00:29:45.760 ⇒ 00:29:53.869 Robert Tseng: Yeah, I mean, this is just a percentage. And I mean, this is probably variable. But and this is like, not something we can calculate right now.
251 00:29:57.720 ⇒ 00:30:07.779 Robert Tseng: yeah, like, okay. Anyway, I, I think this is, this is good for the spike. I think we’re yeah. There’s probably no action to be taken here. We’ve already split out the profit bars here.
252 00:30:07.890 ⇒ 00:30:10.419 Robert Tseng: Yeah, if anything, we need to go and try to.
253 00:30:10.600 ⇒ 00:30:14.719 Robert Tseng: I mean, I think there’s an order of like which ones we can add. But like we’re not gonna add it in now.
254 00:30:15.440 ⇒ 00:30:16.190 Annie Yu: Okay.
255 00:30:16.540 ⇒ 00:30:20.400 Robert Tseng: Yeah, I’ll reassign it to myself.
256 00:30:22.820 ⇒ 00:30:24.470 Robert Tseng: Okay, thanks.
257 00:30:26.540 ⇒ 00:30:41.049 Robert Tseng: Well, I mean, I wanted to do retro, because kind of we’re at the end of a sprint now. But we don’t really have that much time left. So I mean, I think, rather than doing the whole exercise of like writing down stickies and everything like let’s
258 00:30:41.970 ⇒ 00:30:50.209 Robert Tseng: see if we can just like discuss a bit more like talk kind of. We’ll just reference things that we’ve already put together before.
259 00:30:56.070 ⇒ 00:31:12.999 Robert Tseng: yeah, I mean, this was 2 weeks ago. We kind of ran this. We kind of made some adjustments. And I just wanna make sure that we’re still kind of trending in the right direction. Or if some of these issues continue to exist, or if there’s anything new here, so I’ll kind of just like, talk quickly about it. And then I want to get feedback on it.
260 00:31:13.140 ⇒ 00:31:14.170 Robert Tseng: So
261 00:31:14.741 ⇒ 00:31:23.189 Robert Tseng: I’m gonna skip the while, I’m just gonna talk about the problems. So on the ticket scrubbing side, I think. Yeah, I think my opinion is, I think people
262 00:31:23.620 ⇒ 00:31:31.691 Robert Tseng: still need to be keeping up with updating your tickets like. Don’t kind of expect me to be scrubbing it kind of on all the calls every day.
263 00:31:32.170 ⇒ 00:31:33.090 Robert Tseng: I think
264 00:31:34.170 ⇒ 00:31:49.210 Robert Tseng: we do have a better process now generating the tickets out of out of meetings. And I know you guys are kind of going off and making calls with with different stakeholders as well. So I think a lot of maybe some of that gets like falls through the cracks. And
265 00:31:49.910 ⇒ 00:31:53.640 Robert Tseng: I think I think that’s still something that we
266 00:31:53.920 ⇒ 00:31:56.036 Robert Tseng: are are getting tighter on
267 00:31:57.990 ⇒ 00:32:03.259 Robert Tseng: But I don’t know, I guess, from from your guys, perspective like, what? What do we like? Any?
268 00:32:03.600 ⇒ 00:32:05.380 Robert Tseng: Any thoughts on this.
269 00:32:14.191 ⇒ 00:32:20.059 Demilade Agboola: Yeah, I think we are guessing that being able to. Get through tickets.
270 00:32:22.330 ⇒ 00:32:39.899 Demilade Agboola: I will say that like, I know one thing that has helped in terms of like things falling through the cracks is because of like my zoom account, like, I now have access to like transcripts and recordings. So that makes it easier. I know even things like the call I had with Rebecca some weeks back.
271 00:32:40.220 ⇒ 00:32:46.446 Demilade Agboola: where she explained the vow thing, and I had to like, basically create a new
272 00:32:47.410 ⇒ 00:32:54.170 Demilade Agboola: like, I had to create a room to explain that like, if there was a transcript that would have been much easier to like, have that accessible to us?
273 00:32:55.129 ⇒ 00:33:00.199 Demilade Agboola: And also potentially, yeah, do you want to say something.
274 00:33:00.443 ⇒ 00:33:27.950 Robert Tseng: Yeah. 1 1 thing on that. Yeah. So I think I know that maybe not. All of you are kind of transcribing all your all your rooms, but as far as zooms, but as far as like stand up goes every stand up. Transcript goes into here. We have it kind of broken out. You can just take the transcript we have like kind of in the Prompts library, like, you know. Ask ask the it if you need help there. But yeah, if you guys need to reference anything, and it’s just like you don’t. You can’t recall something, because, like some, I got left something out on the tickets like.
275 00:33:28.340 ⇒ 00:33:38.820 Robert Tseng: I don’t think you should wait on me to kind of go and answer that question. You can just go in and pull pull in one of the questions from the meeting itself. So we just pick like
276 00:33:39.540 ⇒ 00:33:40.900 Robert Tseng: I don’t know, like
277 00:33:41.080 ⇒ 00:33:48.969 Robert Tseng: I guess most of them are named my personal meeting room, because that’s just like what it’s think here. But I think you can go.
278 00:33:49.500 ⇒ 00:34:12.019 Robert Tseng: I mean, there aren’t that many you can just kind of figure out which which one which one it is, and just grab. Grab the transcript there. Like. That’s what I do, too. When you guys are asking me questions. I just throw in a Gpt and have it kind of recall, like whatever nuance we discussed. So yeah, I think that would save me like some of the turnaround time on like getting you guys unblocked on just like small details that like
279 00:34:12.159 ⇒ 00:34:22.419 Robert Tseng: I maybe just like missed on a ticket or just wanted some clarification so would appreciate if you could do at least that 1st before you kind of like hit me with the question.
280 00:34:26.170 ⇒ 00:34:41.309 Robert Tseng: But regarding looms, and if we need to be, do a better job of like, also getting looms in a single place, and being able to like, turn those into transcripts and everything as well, so that everyone knows like what looms we’re sharing like. What are I mean? These are like evergreen
281 00:34:41.570 ⇒ 00:35:03.830 Robert Tseng: training things so like you don’t have to meet 2 separate people on the same. Like to do tableau Walkthroughs with like 3 separate people like, if we’ve done one before, just share just you can just share it. So I want to like, minimize the number of like duplicative meetings that we have. Because people are just like it’s just like the the tea ground situation today. Right?
282 00:35:03.930 ⇒ 00:35:16.930 Robert Tseng: Calls out like requirements not done like. Obviously, I didn’t look at it any like I just you know you’re in what I built it. So I just flagged. You turns out just user error just to know how to use the filters. So like stuff like that like, I mean.
283 00:35:17.120 ⇒ 00:35:20.829 Robert Tseng: great good thing. We didn’t jump on a call with him. But like also,
284 00:35:22.290 ⇒ 00:35:45.920 Robert Tseng: yeah, that’s what I’m saying. Like, I would. I expect, like 50% of the messages we get shouted out in to not actually be real issues. I think people don’t understand what’s going on. There’s user error, or whatever whatever it is, so more of a bank that we can draw from our bank of like different resources that we’ve already put together, and share kind of we do a better job of sharing that. So
285 00:35:46.210 ⇒ 00:35:55.634 Robert Tseng: and maybe that’s an action item for me to better like, enable this team anytime we have a loom that shared. I’ll create a spot, a place where we can drop it in there, and I’ll make sure that it’s
286 00:35:56.080 ⇒ 00:36:00.460 Robert Tseng: It’s it’s more visible. So we can reuse like the things that we’re sharing with with people.
287 00:36:02.270 ⇒ 00:36:05.200 Robert Tseng: Yeah, do. Do you think that would be more helpful.
288 00:36:16.210 ⇒ 00:36:22.630 Demilade Agboola: Yeah, I could see that being more helpful. So that would be reduce the number of he’s error
289 00:36:22.950 ⇒ 00:36:24.980 Demilade Agboola: responses that we can.
290 00:36:25.770 ⇒ 00:36:30.539 Robert Tseng: Okay, yeah, I mean, I I mean, I don’t really know if we’re gonna yeah. Well.
291 00:36:31.080 ⇒ 00:36:37.349 Robert Tseng: it’ll just speed up our the way we triage user error responses. I think, yeah. So
292 00:36:37.480 ⇒ 00:36:41.700 Robert Tseng: that’s I think that’s the point. I don’t think we’re gonna reduce the volume. Necessarily. Like.
293 00:36:42.430 ⇒ 00:36:49.530 Robert Tseng: yeah, there’s just like new people, kind of just like adding, me or you guys like all the time. So I mean this, it’s just
294 00:36:49.830 ⇒ 00:36:51.950 Robert Tseng: that’s just part of what we have to deal with.
295 00:36:53.420 ⇒ 00:37:12.990 Robert Tseng: then the other thing that I think we are doing better here on escalations. I think. Great. You guys know who your who your people are. You’re reaching out to them, hopping on calls with them. It’s totally fine. If you don’t know who it is or somebody is not responsive. You just like, let me know. And I’m I’m kind of escalating for you. So you can keep leveraging me for that.
296 00:37:13.321 ⇒ 00:37:28.239 Robert Tseng: I know on like the product categories. Thing like that seems like nobody is taking ownership there. So that’s kind of like, yeah, I pointed you to the 2 people that I knew, but if neither of them want to own it, then like, then we have to like make a decision there. Right? So.
297 00:37:28.883 ⇒ 00:37:32.910 Robert Tseng: I think we probably let too much time go go by for that.
298 00:37:32.910 ⇒ 00:37:33.559 Demilade Agboola: I wouldn’t.
299 00:37:33.760 ⇒ 00:37:36.590 Demilade Agboola: What do you mean? The product categories? Thing.
300 00:37:38.110 ⇒ 00:37:47.840 Robert Tseng: right? Like the whole from category subcategory to variance to vial size. Right? Like that whole. I mean to me, that’s that’s just like, yeah.
301 00:37:48.030 ⇒ 00:37:49.170 Demilade Agboola: That’s been done.
302 00:37:49.570 ⇒ 00:37:52.890 Demilade Agboola: I don’t know if I know, sir, but that’s been done like.
303 00:37:52.890 ⇒ 00:37:53.340 Robert Tseng: Oh, yeah.
304 00:37:53.340 ⇒ 00:37:53.919 Demilade Agboola: I don’t know.
305 00:37:53.920 ⇒ 00:38:00.020 Robert Tseng: In it a couple like a day or 2. I I think I saw the Pr. Yesterday right.
306 00:38:00.570 ⇒ 00:38:01.210 Demilade Agboola: Yeah.
307 00:38:01.540 ⇒ 00:38:07.000 Robert Tseng: Yeah. So I I know that I know that one’s done now. But I’m just like in re, in retrospect, like
308 00:38:07.230 ⇒ 00:38:12.450 Robert Tseng: we kind of took like a while just to get the answers we needed on there.
309 00:38:14.210 ⇒ 00:38:15.490 Demilade Agboola: That’s fair. Yeah.
310 00:38:15.490 ⇒ 00:38:20.986 Robert Tseng: Yeah, yeah, I think like, just to reiterate, I think,
311 00:38:21.940 ⇒ 00:38:33.189 Robert Tseng: we will. We’ll see things more end to end than most of the people. That we’re talking to, because they only care about their like narrow slice of the view. So I think, like, when we kind of
312 00:38:33.290 ⇒ 00:38:53.839 Robert Tseng: yeah, like to me. I consider the categories conversation the same conversation, even though we’re talking with Rebecca about kind of like all the different nuances around like treatment, order, vial size, and different treatment steps and and all that, and then all the way to, you know, up to Cutter when Cutter is talking about like how the different categories should be
313 00:38:53.840 ⇒ 00:39:16.329 Robert Tseng: to me. That’s all product categorization, right? And they may not care about like Rebecca may not care about the product categories and cover doesn’t care about the file size, but for us, like we we kind of, we see it as like the same the same thing. So I know it’s a bit kind of confusing when we have separate tickets and like different people to go after. But, like the acceptance criteria for that whole piece of work
314 00:39:16.560 ⇒ 00:39:26.769 Robert Tseng: is like it needs to kind of. I mean, we were. We started from variant, and maybe like one level above that. And we were expanding like, I guess vertically, in both directions. And so.
315 00:39:27.440 ⇒ 00:39:28.870 Robert Tseng: yeah, I mean, I think
316 00:39:31.370 ⇒ 00:39:37.749 Robert Tseng: in that situation, I think, Dave, a lot of you were assigned to kind of like working with both of them separately, but being able to take that
317 00:39:38.607 ⇒ 00:39:53.029 Robert Tseng: position of like, hey, this is actually part of like one single scope of of work if we need to get them both together, I mean, like, you know, just and kind of treating it as such. Rather than kind of like piece mailing it, you know you know what I mean. There.
318 00:39:54.960 ⇒ 00:40:02.580 Demilade Agboola: Yeah, I could see like, how we could have made it a faster process, or just been able to make it a more holistic process.
319 00:40:03.340 ⇒ 00:40:04.030 Robert Tseng: Yeah.
320 00:40:04.764 ⇒ 00:40:13.010 Robert Tseng: I think, yeah. So I think that’s that’s that’s just a domain thing that we have to. You know. I think it’s just part of territory that we cover.
321 00:40:13.520 ⇒ 00:40:14.510 Robert Tseng: And
322 00:40:15.890 ⇒ 00:40:25.559 Robert Tseng: yeah, I think that’s why, when I’m kind of discussing things in our stand ups or when we’re meeting, like, I’m not really. I’m not zeroing in on the tickets, because
323 00:40:25.680 ⇒ 00:40:28.279 Robert Tseng: I know that the tickets are yeah. They’re
324 00:40:28.460 ⇒ 00:40:33.109 Robert Tseng: they’re they’re time box to like a particular like task that needs to be done. But like.
325 00:40:33.650 ⇒ 00:40:47.139 Robert Tseng: maybe it is just about kind of grouping the tickets better, too. But I’m not gonna spend all this time like doing ticket management. So I I you know, I I think we all should be trying to think from 1st principles a bit more. And that like.
326 00:40:47.220 ⇒ 00:41:12.029 Robert Tseng: yeah, if you’re assigned to multiple things. And I’m not, I’m not just picking on you anymore. But just like whenever we’re assigned to multiple things serving one client whether it’s like Mattesh and Mattesh has multiple requests on the the Cmo dashboard and the growth Kpis dashboard. He may be asking the same question. He’s just like trying to understand. Like, okay, well, like the Ltv thing, we we that we worked on this past past couple of weeks.
327 00:41:12.200 ⇒ 00:41:17.762 Robert Tseng: He was not too preoccupied with. He wasn’t like responsive on the cohort.
328 00:41:18.340 ⇒ 00:41:30.600 Robert Tseng: Ltv update that we gave him, and it turns out like he just didn’t know how to use it right? And it’s like, Okay, well, that’s helpful in a context where he’s tracking users over time. But he’s caring more about
329 00:41:30.710 ⇒ 00:41:42.130 Robert Tseng: yeah, like that single view that we had in the original product from Ros, Ltv. Dashboard. And so I mean it was great that I mean. I wish I wish I got him into the call earlier, because I feel like
330 00:41:42.510 ⇒ 00:41:52.470 Robert Tseng: he just was kind of mia for a few days. But yeah, it’s just stuff like that where, like, I feel like, I don’t have to be the one to detect that like.
331 00:41:52.930 ⇒ 00:42:16.299 Robert Tseng: okay, if someone’s being unresponsive, it’s not just about like pinging them. Or it’s not just about like getting this ticket out or whatever like. Maybe they’re just not understanding, like what we’re delivering them and needing to like, think about. Okay, what? How do we? How do we see it? How do they see it? And trying to trying to close that gap? So I know that that’s mostly my kind of like role in kind of helping us get the
332 00:42:16.470 ⇒ 00:42:22.870 Robert Tseng: visibility impact that we need to have with our work. But I think that whatever you’re working on like we should
333 00:42:23.540 ⇒ 00:42:32.439 Robert Tseng: if I can’t scale that to you guys, then we’re always going to be constrained by the amount of of like headspace that I have to think about about these things.
334 00:42:35.290 ⇒ 00:42:47.040 Robert Tseng: okay, I mean, I know we’re kind of at time with this one. If you can go a couple of minutes over, and I know I want a waste and need to kind of stay on to meet over in the test situation.
335 00:42:47.380 ⇒ 00:42:53.589 Robert Tseng: Yeah, and anything else that’s like not covered here that we think that didn’t work well in this past sprint.
336 00:42:54.180 ⇒ 00:43:09.489 Robert Tseng: that wanted to flag. I mean, I’ll just toss something there, but we don’t have to talk about it. I think too many. I let too many tickets come in like in the middle of the sprint. So we ended up kind of fanning out, and that’s why we were slammed on kind of delivering stuff towards the end of this week.
337 00:43:09.919 ⇒ 00:43:28.389 Robert Tseng: And so I’m still nailing down that cadence because we do our sprint planning and our cycles, but like the requests that we get from stakeholders come in any time. And so I think I need to better understand, like what we can add to cycle and what we should push off so that’s that’s something I’ll be thinking about before we start next week.
338 00:43:28.820 ⇒ 00:43:38.550 Robert Tseng: But yeah, anything else on your guys minds that we could have yeah learnings, learnings that we did better, or things that we that you think really didn’t go well, that we need to do better.
339 00:43:52.457 ⇒ 00:43:57.672 Demilade Agboola: From my end. I mean, not much beyond what you just said, I think.
340 00:43:58.280 ⇒ 00:44:08.460 Demilade Agboola: Oh, man, the only like, yeah, just largely being able to get information quicker, being able to
341 00:44:08.940 ⇒ 00:44:09.990 Demilade Agboola: be the like
342 00:44:10.210 ⇒ 00:44:24.030 Demilade Agboola: processing things just like, oh, people not responding. How do we get the responses? We need faster processing things. And also, yeah, like you mentioned, like, too many like tickets came in during the spring. So we had to keep like
343 00:44:25.150 ⇒ 00:44:30.140 Demilade Agboola: prioritizing over the course of the days, and some things obviously fall into the backlog
344 00:44:30.550 ⇒ 00:44:41.290 Demilade Agboola: as a result of that. But I think all in all, it’s been a successful sprint. We’re able to get most things out. And I think the things we’re getting now have, like good business impact, too. So.
345 00:44:42.230 ⇒ 00:44:43.000 Robert Tseng: Yeah.
346 00:44:44.450 ⇒ 00:45:04.789 Robert Tseng: yeah. I mean, once we get the couple of things out today, I think we should be good, like, I don’t feel like we’re behind. I will say that, like the things that got stale that I was like pushing hard on the past couple of days. Those were things that we had in sprint planning that I know got pushed out because other tickets came to play. And you guys work on it. So I’m not blaming anyone, for, like, necessarily, those being late, I I mean.
347 00:45:05.380 ⇒ 00:45:08.969 Robert Tseng: I wish we could have done the faster. It’s just just didn’t really happen.
348 00:45:09.412 ⇒ 00:45:27.540 Robert Tseng: So yeah, I think hopefully. Better management of that on on my side of like will help help make sure that you know the 1 2 week long things that you guys are working on don’t get derailed. Otherwise, we’re just like stuck in this reactive, like ad hoc, like nonsense, like all the time. So
349 00:45:29.650 ⇒ 00:45:39.839 Robert Tseng: okay, I mean it was Annie. I know they’ll be pretty quiet. Anything else you want to mention before we kind of we can. We could move on as well. I’m sorry we’ll do a more.
350 00:45:40.020 ⇒ 00:45:42.699 Robert Tseng: I’ll try to protect this time more every every week, so.
351 00:45:42.700 ⇒ 00:45:43.830 Josh: Alright cool. How’s going on
352 00:45:44.260 ⇒ 00:45:48.539 Josh: before everyone else jumps in speaking of ad hoc nonsense! I do have like one
353 00:45:48.700 ⇒ 00:45:52.839 Josh: one thing from Qatar, but all good.
354 00:45:53.590 ⇒ 00:45:56.000 Robert Tseng: The cutter thing we are. Yeah, we’re on it. Yeah.
355 00:45:56.000 ⇒ 00:45:56.650 Josh: Okay.
356 00:45:57.150 ⇒ 00:45:57.700 Robert Tseng: Yeah.
357 00:45:58.630 ⇒ 00:46:00.629 Josh: He’s. I think he’s gonna jump in.
358 00:46:04.300 ⇒ 00:46:07.300 Josh: They said they’re doing it. They said, Yeah, that they’re.
359 00:46:07.300 ⇒ 00:46:10.500 cutter: Demo Lotte just text me, he said. He’s gonna get.
360 00:46:10.500 ⇒ 00:46:14.989 Robert Tseng: Yeah, it’ll it’ll be out today like hopefully, in a couple of hours.
361 00:46:15.500 ⇒ 00:46:19.870 cutter: Cool man. Can you rerun yesterday’s once it’s back so I can do my kpis and shit.
362 00:46:20.220 ⇒ 00:46:21.380 Robert Tseng: Yes, yes.
363 00:46:21.740 ⇒ 00:46:23.510 cutter: Yeah, we’ll do. Thank you.
364 00:46:23.880 ⇒ 00:46:24.580 cutter: Thanks, boys.
365 00:46:24.580 ⇒ 00:46:25.150 Josh: Cool.
366 00:46:25.150 ⇒ 00:46:25.470 Robert Tseng: Yeah.
367 00:46:25.470 ⇒ 00:46:32.219 Josh: I don’t know what his, what his request was, but like mine, like I was looking at that snapshot after we made those changes, Robert.
368 00:46:32.690 ⇒ 00:46:37.239 Josh: and it’s like messed up a little bit.
369 00:46:37.360 ⇒ 00:46:38.989 Josh: We can talk about it later.
370 00:46:40.100 ⇒ 00:46:40.990 Robert Tseng: Oh, yeah.
371 00:46:40.990 ⇒ 00:46:41.630 Josh: Yeah.
372 00:46:43.940 ⇒ 00:46:46.680 Robert Tseng: Okay. Well, yeah, I will. Okay.
373 00:46:46.780 ⇒ 00:46:49.899 Robert Tseng: not not good news. But we’ll. Yeah. We’ll. We’ll talk.
374 00:46:50.690 ⇒ 00:46:51.340 Josh: Alright!
375 00:46:51.760 ⇒ 00:46:52.780 Robert Tseng: Okay, thank you.
376 00:46:53.240 ⇒ 00:46:55.280 Robert Tseng: Aisha. Any anything else.
377 00:46:58.797 ⇒ 00:46:59.959 Awaish Kumar: Know? Like, why.
378 00:47:00.290 ⇒ 00:47:03.543 Annie Yu: Is more like a sorry. Aisha, you’re talking.
379 00:47:05.890 ⇒ 00:47:06.779 Awaish Kumar: Yeah. Go ahead.
380 00:47:07.870 ⇒ 00:47:10.710 Annie Yu: No, I I just have one thing that I like
381 00:47:11.460 ⇒ 00:47:17.280 Annie Yu: would love to have a standard. So sometimes in my tickets even though it’s assigned to me, but then
382 00:47:17.840 ⇒ 00:47:21.270 Annie Yu: turns out I need like them all day and always just help.
383 00:47:21.810 ⇒ 00:47:31.759 Annie Yu: are on like modeling side of things. But then I don’t have a like great place to follow up or so. And things are just like in slack sometimes.
384 00:47:32.040 ⇒ 00:47:39.086 Robert Tseng: Yeah, I I had a feeling you were, gonna say that I don’t. Yeah, I think that’s that’s come up a couple of times.
385 00:47:39.580 ⇒ 00:47:44.590 Robert Tseng: because we did need to build a a few new models these past couple of weeks for you to action it.
386 00:47:44.810 ⇒ 00:48:01.890 Robert Tseng: And I mean, with some of the work coming up. Now, there’s going to be more net new, the net new source, the circle stuff coming in. I mean, we’re not doing stripe yet. But so yeah, I’m assuming we’re gonna need more of that. I will. Yeah, I will get back to you on how we can do that better. Annie. Sorry that’s definitely a bad.
387 00:48:03.170 ⇒ 00:48:13.769 Robert Tseng: So figure out how to loop in internal ticket is assigned to.
388 00:48:14.560 ⇒ 00:48:16.850 Robert Tseng: Let’s see it’s support.
389 00:48:17.620 ⇒ 00:48:22.622 Robert Tseng: Yeah, I’ll work with. I’ll work with you top to figure out how to do that. Better. Okay,
390 00:48:22.900 ⇒ 00:48:35.050 Annie Yu: It’s a huge deal, but sometimes it’s it’s small that I like. Feel like, not sure like, should I just create a ticket for them or like. Sometimes it’s not like a huge thing, so.
391 00:48:35.310 ⇒ 00:48:44.909 Robert Tseng: Yeah, no, I I’m trying to. I don’t want you. I know you guys were like creating tickets while I was out. I don’t want you guys creating tickets. Like, I think I’m also trying to, you know.
392 00:48:45.440 ⇒ 00:48:52.690 Robert Tseng: Yeah, I I think we only need 1 1 person doing that at this point, because otherwise we’re gonna lead to the situation where
393 00:48:52.870 ⇒ 00:49:10.109 Robert Tseng: too many tickets then, like things get pushed out, or whatever. So yeah, I’m I’m trying not to you. You can, if you ever need to create a ticket, just assign it to me like I think, whatever is assigned to me like I don’t really consider as part of cycle like I just do it and don’t really keep track of it.
394 00:49:10.665 ⇒ 00:49:20.440 Robert Tseng: So yeah, I think that’s that’s still fine. It’s like your your your way out, if you if you if you need to. But yeah, I trying not to
395 00:49:20.580 ⇒ 00:49:22.480 Robert Tseng: have you guys assign stuff to each other.
396 00:49:22.830 ⇒ 00:49:23.830 Annie Yu: That’s good.
397 00:49:23.830 ⇒ 00:49:26.238 Annie Yu: I don’t. I don’t wanna create tickets too.
398 00:49:26.540 ⇒ 00:49:28.790 Robert Tseng: Yeah. A wish. What were you gonna say?
399 00:49:29.560 ⇒ 00:49:33.769 Awaish Kumar: No, no, I was just saying like like I had the same things like to
400 00:49:34.750 ⇒ 00:49:38.880 Awaish Kumar: as you, and damn already discussed, so like nothing new for me.
401 00:49:40.950 ⇒ 00:49:41.600 Robert Tseng: Okay.
402 00:49:42.640 ⇒ 00:49:56.110 Robert Tseng: okay, yeah, no, I will. Yeah. Let me. Let me let me figure out how we can do this better for the next next cycle. Yeah, I’ll thank you for feedback. I’ll I’ll I’ll probably have something by end of end of week, or you know, over the weekend. I’ll send something.
403 00:49:56.950 ⇒ 00:50:11.950 Robert Tseng: Okay. Well, that’s it, for now I do gotta jump so yeah a wish. And, Annie, if you could stay on, I’ll link you some stuff. Alright. You don’t have to stay in this zoom, but please get on a call to figure out like Natasha’s request to make sure we understand what we’re doing there.
404 00:50:16.980 ⇒ 00:50:18.130 Robert Tseng: Cool, alright.
405 00:50:18.130 ⇒ 00:50:20.859 Demilade Agboola: Alright everyone. Thank you. See, you guys, next week.