Meeting Title: Planning: Strategy-Analytics Date: 2025-12-22 Meeting participants: Robert Tseng, Sezim Zhenishbekova, Henry Zhao, Rico Rejoso, Uttam Kumaran, Zoran Selinger, Elizah Joy
WEBVTT
1 00:00:17.460 ⇒ 00:00:18.630 Sezim Zhenishbekova: Hi, Robert.
2 00:00:19.620 ⇒ 00:00:20.730 Robert Tseng: Hey, morning.
3 00:00:21.160 ⇒ 00:00:22.090 Sezim Zhenishbekova: Morning.
4 00:01:17.310 ⇒ 00:01:28.059 Robert Tseng: Alright, hopefully this link doesn’t… I think all the links should have been updated for the… moving forward. I think the Monday one was just a separate, separate, like, thing, so…
5 00:01:28.220 ⇒ 00:01:30.599 Robert Tseng: Apologies for not noticing that earlier.
6 00:02:07.740 ⇒ 00:02:08.509 Robert Tseng: Eddie.
7 00:02:08.680 ⇒ 00:02:09.350 Robert Tseng: Nope.
8 00:02:09.870 ⇒ 00:02:11.610 Robert Tseng: Just gonna get started.
9 00:02:12.770 ⇒ 00:02:13.800 Robert Tseng: Man.
10 00:02:22.010 ⇒ 00:02:26.609 Robert Tseng: Alright, I mean, this week will be relatively a quieter week,
11 00:02:27.560 ⇒ 00:02:39.169 Robert Tseng: Yeah, I mean, with this group, I’m not… there’s not really that much to say. Honey, singer read me something? I don’t need to talk about any of those with you. Really only Eden.
12 00:02:40.490 ⇒ 00:02:53.649 Robert Tseng: with Eden, I mean, I just need to spend some time, like, going through Josh’s feedback. I know, Henry, you looked through it, so… I mean, I think we should just spend this time planning Eden. I think that’s what I think it should be.
13 00:02:54.310 ⇒ 00:02:54.969 Henry Zhao: Sounds good.
14 00:02:56.470 ⇒ 00:03:00.710 Robert Tseng: So… Pull up.
15 00:03:00.710 ⇒ 00:03:04.950 Henry Zhao: Is… is the EOS platform just the… basically the… a bask replacement?
16 00:03:05.920 ⇒ 00:03:06.590 Robert Tseng: Yeah.
17 00:03:06.730 ⇒ 00:03:07.310 Henry Zhao: Okay.
18 00:03:50.580 ⇒ 00:03:51.530 Robert Tseng: Okay.
19 00:03:54.280 ⇒ 00:04:01.610 Robert Tseng: Yeah, well, I wanna, like, move this… I mean, you guys, you could move into Gantt, we can just go through these things, so… we have…
20 00:04:01.850 ⇒ 00:04:06.959 Robert Tseng: In about… In an hour and a half, we’re gonna… I’m gonna…
21 00:04:07.040 ⇒ 00:04:26.100 Robert Tseng: have a call with Mitesh and Josh, so I will be kind of going through this line by line with them. So, this is really just for us to make any other adjustments that we can internally before we go and put in front of them. So, I guess he gave his initial feedback on, like, something we’re missing here,
22 00:04:26.240 ⇒ 00:04:31.919 Robert Tseng: And, yeah, I guess he didn’t really leave any feedback on other things, so…
23 00:04:37.150 ⇒ 00:04:43.140 Robert Tseng: I think, just to kind of size this down, let’s see…
24 00:04:44.230 ⇒ 00:04:52.720 Robert Tseng: Filter by… only gonna look at things that are high prive. So,
25 00:05:01.710 ⇒ 00:05:04.280 Robert Tseng: Okay, where did you get this number from?
26 00:05:05.570 ⇒ 00:05:07.159 Henry Zhao: This is, from Rebecca.
27 00:05:07.620 ⇒ 00:05:09.559 Henry Zhao: That’s their goal, you know.
28 00:05:10.770 ⇒ 00:05:16.749 Robert Tseng: Alright, I want this to be fleshed out more, so let’s see. What exactly are we doing to help them drive this?
29 00:05:19.570 ⇒ 00:05:28.939 Henry Zhao: I think if they just need to basically be prepared to handle that volume, then Brad and Ryan can direct that volume, that much volume, to them.
30 00:05:29.850 ⇒ 00:05:32.710 Robert Tseng: How much volume? What is the scale-up right now?
31 00:05:35.880 ⇒ 00:05:38.500 Henry Zhao: Can you clarify the question on what you mean by what is that?
32 00:05:38.500 ⇒ 00:05:44.780 Robert Tseng: Like, if they’re shipping 10 orders, and they need to get to 100 orders, like, what, like, how…
33 00:05:45.530 ⇒ 00:05:51.210 Robert Tseng: Yeah, like, what is… how does this translate to $700,000 a month?
34 00:05:52.770 ⇒ 00:05:57.249 Henry Zhao: They need to get new… yeah, they need to have enough staffing and supply chain.
35 00:05:58.170 ⇒ 00:06:00.870 Henry Zhao: To be able to handle that volume, you know.
36 00:06:03.320 ⇒ 00:06:11.960 Robert Tseng: So, is the ask that you’re planning their headcount? Like, you’re doing some workforce planning exercise, or what?
37 00:06:12.270 ⇒ 00:06:14.140 Henry Zhao: Yeah, we definitely, that definitely should be part of it.
38 00:06:18.850 ⇒ 00:06:22.690 Henry Zhao: Yeah, I need to talk more to Rebecca on, like, how we can get that to happen.
39 00:06:24.630 ⇒ 00:06:26.250 Henry Zhao: Maybe I’ll schedule a call with her.
40 00:06:32.410 ⇒ 00:06:33.120 Robert Tseng: Okay.
41 00:06:41.170 ⇒ 00:06:44.809 Robert Tseng: I don’t know if I should just leave comments here, but it’s like.
42 00:06:45.550 ⇒ 00:06:47.079 Henry Zhao: Yeah, just, like, flesh it out more.
43 00:06:47.490 ⇒ 00:06:51.289 Henry Zhao: Like, understand what’s in our power to get that number up.
44 00:07:05.690 ⇒ 00:07:09.880 Uttam Kumaran: I mean, you can also add, Robert, like, a status column, which could be, like.
45 00:07:10.490 ⇒ 00:07:11.020 Henry Zhao: Okay.
46 00:07:11.020 ⇒ 00:07:13.410 Uttam Kumaran: Posed, like, confirmed, or, like.
47 00:07:14.230 ⇒ 00:07:22.509 Uttam Kumaran: confidence or something, because there’s some… there’s some on here that I think we’re… it’s very well defined, and some on here that are like this, where it’s, like, not well-defined.
48 00:07:22.510 ⇒ 00:07:23.120 Robert Tseng: Yeah.
49 00:07:23.120 ⇒ 00:07:23.700 Henry Zhao: Yeah.
50 00:07:24.350 ⇒ 00:07:28.520 Uttam Kumaran: That way, you can still have your conversation with them today, even on the ones that are…
51 00:07:29.850 ⇒ 00:07:34.339 Uttam Kumaran: Not as clear. And then, can I get a… can I get a link in the chat to this, Doc?
52 00:07:34.700 ⇒ 00:07:35.670 Henry Zhao: Yeah, I’ll send it.
53 00:07:35.670 ⇒ 00:07:36.540 Uttam Kumaran: Okay, thanks.
54 00:07:39.490 ⇒ 00:07:41.439 Robert Tseng: Okay, and then for this one…
55 00:07:42.180 ⇒ 00:07:44.390 Robert Tseng: Yeah, like, talk me through this one.
56 00:07:45.760 ⇒ 00:07:57.279 Henry Zhao: So this one I just met with Brad. Basically all we need to do to improve SLA, is to have the accurate forecasting numbers, so that’s why I’ve created a Tableau dash that has that now, so he can break it down.
57 00:07:57.310 ⇒ 00:08:07.410 Henry Zhao: By pharmacy, by drug, and so he knows how to kind of divide up that volume, and how to ramp up pharmacies that aren’t ready to handle
58 00:08:07.480 ⇒ 00:08:08.809 Henry Zhao: Whatever volumes.
59 00:08:08.810 ⇒ 00:08:11.869 Robert Tseng: What’s the current situation? What’s the expected lift?
60 00:08:13.860 ⇒ 00:08:17.509 Henry Zhao: So the current situation is we have this dashboard now, the way he likes it.
61 00:08:17.510 ⇒ 00:08:22.039 Robert Tseng: I’m talking about operationally, like, where is he failing? Like, is this actually a big deal?
62 00:08:22.920 ⇒ 00:08:25.809 Henry Zhao: Yeah, he’s just failing just because there’s not enough, like.
63 00:08:26.690 ⇒ 00:08:41.690 Henry Zhao: infrastructure, I guess, to handle the increased volumes, so he needs to know exactly how much forecast we’re going to have in 2026, based on SEZM’s work for Jonah, so he can ask for what he needs in terms of
64 00:08:41.809 ⇒ 00:08:45.579 Henry Zhao: Pharmacy resources and staffing to handle that volume.
65 00:08:45.720 ⇒ 00:08:48.229 Henry Zhao: And obviously, it needs to be accurate so we don’t overdo it.
66 00:08:53.990 ⇒ 00:09:02.740 Robert Tseng: Okay, I’m still, like, unclear on, like, where the… where is the needle right now, and, like, what are we… and you’ve shown me what we’re moving it to, but what are we right now?
67 00:09:03.930 ⇒ 00:09:12.730 Henry Zhao: Right now, it’s not great, right? Right now, we have about 2% of pending orders over 10 days, and…
68 00:09:13.040 ⇒ 00:09:19.080 Henry Zhao: let me see what the exact number was for SLA over 3 days, but it’s pretty high right now.
69 00:09:24.150 ⇒ 00:09:27.690 Henry Zhao: So he knows there’s a lot of work to be done, but he just needs that accurate forecast.
70 00:09:28.010 ⇒ 00:09:29.730 Henry Zhao: To be able to plan for it.
71 00:09:31.470 ⇒ 00:09:32.270 Robert Tseng: Huh.
72 00:09:32.970 ⇒ 00:09:33.480 Henry Zhao: Yo.
73 00:09:42.510 ⇒ 00:09:45.799 Henry Zhao: Yeah, so it’s like, there’s, like, 20% missing SLA right now.
74 00:09:47.140 ⇒ 00:09:48.910 Henry Zhao: It’s kind of just all over the place each month.
75 00:09:51.000 ⇒ 00:09:57.649 Robert Tseng: How… but that doesn’t check out. You said 2% of orders shipped greater than 3 business days. What is that? Oh, no, that’s, pending orders over 10 days.
76 00:09:59.260 ⇒ 00:10:09.270 Henry Zhao: So there’s two metrics here. It’s how many orders are pending for over 10 days. So those are the ones that are, like, stuck in pending, and then how many got shipped after 3 business days since sent to pharmacy.
77 00:10:10.080 ⇒ 00:10:18.299 Robert Tseng: I mean, do you see what I’m trying to do? I’m trying to spell out, this is what it is currently, and then this is what we’re moving… what we need to move it towards.
78 00:10:18.720 ⇒ 00:10:19.639 Robert Tseng: Shut up still.
79 00:10:19.930 ⇒ 00:10:23.369 Henry Zhao: Yeah, 22% of orders… Better missed SLA.
80 00:10:25.300 ⇒ 00:10:26.789 Robert Tseng: And what is SLA?
81 00:10:27.180 ⇒ 00:10:29.200 Henry Zhao: 3 business days since the pharmacy.
82 00:10:32.480 ⇒ 00:10:37.160 Robert Tseng: So And then the target…
83 00:10:37.960 ⇒ 00:10:38.869 Henry Zhao: is 10%.
84 00:10:38.870 ⇒ 00:10:41.090 Robert Tseng: is under 10%.
85 00:10:45.700 ⇒ 00:10:55.860 Robert Tseng: Okay, yeah, I mean, I think this is what… basically, this is basically what we need for every… every one of these, so, like, it makes it easier to talk about, like, the magnitude of what we’re doing.
86 00:10:56.900 ⇒ 00:10:57.580 Robert Tseng: Okay.
87 00:10:58.130 ⇒ 00:11:00.870 Robert Tseng: Yeah, okay, same thing here.
88 00:11:11.620 ⇒ 00:11:13.519 Robert Tseng: Yeah, can we do the same thing here?
89 00:11:13.520 ⇒ 00:11:18.600 Henry Zhao: Yeah, this one I have less data on just because we don’t have accurate cogs, because we don’t have vial size from BASC.
90 00:11:19.310 ⇒ 00:11:22.010 Henry Zhao: So I don’t know how we want to do this one.
91 00:11:24.560 ⇒ 00:11:27.850 Henry Zhao: Yeah, according to Demolida, the COGS number we have right now is completely inaccurate.
92 00:11:32.420 ⇒ 00:11:36.020 Robert Tseng: Okay, I don’t really understand, like, Then…
93 00:11:36.020 ⇒ 00:11:45.060 Henry Zhao: We’ve been following up with Basque… I’ve been following up with Basque every week on where we are at with file size, and I haven’t gotten a response. But I have asked Brad to follow up with Gal.
94 00:11:52.190 ⇒ 00:12:00.799 Robert Tseng: Okay, so let’s just take that one, for example. Like, you were saying COGS is wildly inaccurately… is it wildly inaccurate right now? Like, how do we know that?
95 00:12:02.650 ⇒ 00:12:13.370 Henry Zhao: Because right now it’s just, like, a guess based on the invoices that we have, and also, I’m breaking down, like, the orders by COGS we have, and a lot of orders just have no COGS data, so…
96 00:12:14.650 ⇒ 00:12:17.599 Robert Tseng: then why don’t the order… why don’t… why don’t they have COGS data?
97 00:12:18.110 ⇒ 00:12:29.230 Henry Zhao: I think just because we don’t have the correct mapping, so we don’t… so there’s invoices where this is, like, how much we’ve spent, but we don’t know which orders those are attributed to, so they’re kind of just, like, floating
98 00:12:29.750 ⇒ 00:12:31.480 Henry Zhao: these floating COGS numbers.
99 00:12:31.670 ⇒ 00:12:34.129 Robert Tseng: And what percentage of orders is that?
100 00:12:34.820 ⇒ 00:12:43.400 Henry Zhao: I have it here, I can… I can calculate it really quickly, but… One second.
101 00:12:43.850 ⇒ 00:12:45.230 Henry Zhao: Just a filtering.
102 00:12:45.570 ⇒ 00:12:57.959 Robert Tseng: Okay, well, yeah, so, like, what I’m driving at is, like, okay, we… sure, like, this number may be unknown, but, like, is it unknown for all orders, or is it unknown for 20% of orders? Like…
103 00:12:59.700 ⇒ 00:13:02.389 Henry Zhao: Yeah, so it totals for $25,000.
104 00:13:09.080 ⇒ 00:13:11.390 Henry Zhao: Like, 25% we don’t know.
105 00:13:12.650 ⇒ 00:13:20.280 Robert Tseng: Okay, so… 25% of orders, we don’t know COGS.
106 00:13:20.740 ⇒ 00:13:22.810 Robert Tseng: And… why?
107 00:13:23.830 ⇒ 00:13:32.450 Henry Zhao: Because we don’t have the vial size, so we don’t know, like, when we have an order, how much of it that was actually contributing to COGS. So we know the total COGS, we don’t know the breakdown.
108 00:13:34.340 ⇒ 00:13:43.540 Henry Zhao: So we know it’s building 400,000 orders, and we know the total COGS, but we don’t know what it is by pharmacy, by order, because the vial size determines the actual COGS.
109 00:13:44.290 ⇒ 00:13:47.149 Robert Tseng: Okay, so, to me, that’s basically saying, like.
110 00:13:48.380 ⇒ 00:13:50.390 Robert Tseng: Well, I mean, like, maybe on…
111 00:13:50.590 ⇒ 00:14:04.240 Robert Tseng: average order is, like, 4 vials, possibly? Like, I don’t know, like, because how, like… you have the… you have the COGS for orders, but you don’t have the vial size, so if you’re saying 25% orders, we don’t know COGS.
112 00:14:04.780 ⇒ 00:14:07.710 Robert Tseng: Does that mean those are all multi-vial odors?
113 00:14:08.760 ⇒ 00:14:11.300 Henry Zhao: Probably. I’d have to check, but…
114 00:14:11.370 ⇒ 00:14:12.600 Robert Tseng: Okay. Cool.
115 00:14:12.870 ⇒ 00:14:15.639 Robert Tseng: No file size breakdown.
116 00:14:16.710 ⇒ 00:14:24.120 Henry Zhao: Yeah, if we had demo a lot of here, he would know for sure, because he… I think he did the modeling DBT logic for how we calculate COGS right now.
117 00:14:24.360 ⇒ 00:14:24.870 Robert Tseng: Okay.
118 00:14:25.440 ⇒ 00:14:28.329 Robert Tseng: Still waiting on the bass.
119 00:14:29.970 ⇒ 00:14:33.260 Robert Tseng: Do add vial size orders.
120 00:14:33.260 ⇒ 00:14:36.300 Henry Zhao: Yeah, I honestly don’t know why this is so hard for them to add.
121 00:14:37.210 ⇒ 00:14:41.720 Uttam Kumaran: Yeah, I feel like this is, something that I’ve heard about for at least, like, 2 months now.
122 00:14:41.720 ⇒ 00:14:42.330 Henry Zhao: Yeah.
123 00:14:42.730 ⇒ 00:14:45.629 Uttam Kumaran: Inter… and we’ve… all we’ve done is ask again and again.
124 00:14:46.080 ⇒ 00:14:46.780 Robert Tseng: Yeah.
125 00:14:47.770 ⇒ 00:14:52.500 Robert Tseng: Like, so… it’s…
126 00:14:53.150 ⇒ 00:14:58.459 Robert Tseng: And then, what… have we considered, like, proxies? Like, what… what can we do to work around it?
127 00:14:58.750 ⇒ 00:15:08.139 Robert Tseng: Like, we know what orders have multiple vials, we know what the mapping is, we can just, like, kind of project it out. It may not be accurate, but it’s better than nothing.
128 00:15:08.840 ⇒ 00:15:28.650 Henry Zhao: what I would do… so this is what you said, Robert, last week, it’s like, you don’t need accurate data to make insights, like, I think we don’t need to know the exact amount of COGS by pharmacy and by order, we just need to know how can we decrease COGS, and that’s the analysis we talked about last week, of looking at why credit card fees are so high, seeing how we can shift orders to pharmacies that have lower COGS.
129 00:15:28.650 ⇒ 00:15:34.279 Henry Zhao: Like, I don’t need to know COGS to know that moving an order to a lower COGS pharmacy is gonna decrease COGS.
130 00:15:34.650 ⇒ 00:15:35.210 Robert Tseng: Yeah.
131 00:15:36.370 ⇒ 00:15:44.759 Henry Zhao: So this goes back to the role above, which is getting those lower COGS pharmacies ready to handle increased volume, and then just shifting volume over. Like, it doesn’t need to be more complicated than that.
132 00:15:46.630 ⇒ 00:15:47.310 Robert Tseng: Okay.
133 00:15:47.480 ⇒ 00:15:52.679 Robert Tseng: So, and that… I mean, to me, this is not high priority. It’s like, you don’t really need this to move the needle.
134 00:15:52.980 ⇒ 00:15:53.610 Henry Zhao: Okay.
135 00:15:56.820 ⇒ 00:15:57.860 Robert Tseng: Okay.
136 00:16:00.460 ⇒ 00:16:01.690 Robert Tseng: Let’s,
137 00:16:06.790 ⇒ 00:16:08.699 Robert Tseng: And, okay, the C…
138 00:16:08.700 ⇒ 00:16:14.219 Henry Zhao: Yeah, and if it’s not high priority and we’re not getting it from BASC, I would move that timeline also to February, so I’ll make that change later.
139 00:16:14.220 ⇒ 00:16:17.259 Robert Tseng: Okay, yeah, and then what about… what about this one?
140 00:16:17.770 ⇒ 00:16:37.009 Henry Zhao: Yeah, so this one I think is really important. I don’t know if we do any of this right now, but I think it’s important that we implement, some sort of CSAT or MPS surveys, because right now we’re kind of very blind in terms of how customers feel about their Eden trials. We don’t know if they’re feeling side effects, if there’s things that we can improve, if FSLA even really matters that much to them, so…
141 00:16:37.280 ⇒ 00:16:42.440 Henry Zhao: I’d love to implement this and get some data there and start to do analysis on customer sentiment.
142 00:16:43.080 ⇒ 00:16:47.709 Henry Zhao: That’ll help us prioritize, and also help us find areas of improvement, which will drive revenue.
143 00:16:48.120 ⇒ 00:16:48.810 Robert Tseng: Okay.
144 00:16:49.830 ⇒ 00:16:53.810 Robert Tseng: Yeah, I mean, that seems like an easy one to do, like, I don’t… Yeah. Yeah. Okay.
145 00:16:56.580 ⇒ 00:16:58.840 Robert Tseng: Okay, I mean, that one’s fine.
146 00:16:59.600 ⇒ 00:17:05.520 Robert Tseng: there’s no… there is no current KPI, like, that’s, like, nothing right now, so, sure. Yeah. Okay.
147 00:17:06.250 ⇒ 00:17:07.859 Robert Tseng: What about this one?
148 00:17:08.220 ⇒ 00:17:14.269 Henry Zhao: Alright, so this one I’m gonna work with Sezum today, on to, you know, continue to make progress on the forecasting model for Jonah.
149 00:17:14.270 ⇒ 00:17:32.019 Henry Zhao: So as we know, V1, we just want to use marketing spend and CAC to forecast the, like, future monthly volume. This will help us prepare from a finance perspective, but also on the pharmacy distribution, so that we can improve SLA and COGS.
150 00:17:32.020 ⇒ 00:17:42.270 Henry Zhao: So eventually, this product… this end product is going to be a dashboard where you can input how much ad spend you’re planning on doing by drug, and it’ll forecast the volume based on the CAC.
151 00:17:43.820 ⇒ 00:17:50.679 Henry Zhao: That way, we can say, if we plan on spending $10,000, just as an example, can we handle that from a pharmacy’s perspective?
152 00:17:51.760 ⇒ 00:17:58.579 Henry Zhao: And if we can’t, what do we need to increase in terms of staffing or resourcing to be able to handle that increased volume?
153 00:18:02.500 ⇒ 00:18:17.760 Robert Tseng: Okay, so this is really, like, a… Supply elasticity… Forecast…
154 00:18:24.600 ⇒ 00:18:35.399 Robert Tseng: Yeah, it’s like, you’re modeling… if you adjust these marketing inputs, like, you’re expecting, you know, this, you know, a certain volume increase, and, like, how do we, like,
155 00:18:35.820 ⇒ 00:18:41.759 Robert Tseng: Oh yeah, and then you’re feeding it to operations, and being like, you should be able to handle this type of volume.
156 00:18:42.180 ⇒ 00:18:42.820 Henry Zhao: Yeah.
157 00:18:42.820 ⇒ 00:18:43.460 Robert Tseng: Okay.
158 00:18:43.920 ⇒ 00:18:49.680 Henry Zhao: But I think it’s also for Jonah to see, like, should I spend an extra X dollars if… if that’s gonna be the return?
159 00:18:51.210 ⇒ 00:18:52.250 Henry Zhao: Okay. So V1 minus…
160 00:18:52.250 ⇒ 00:18:56.730 Robert Tseng: What’s his input on this? I mean, I don’t think… I doubt he’s doing something like this right now.
161 00:18:57.360 ⇒ 00:19:06.400 Henry Zhao: he’s doing something basic like this in Excel, so we’re gonna put it in Tableau so that it can handle more, like, more calculations and more breakdowns and more…
162 00:19:06.540 ⇒ 00:19:12.099 Henry Zhao: just basically be more flexible. Right now, all he’s doing is in Excel, and all he’s doing is retention curves.
163 00:19:12.710 ⇒ 00:19:19.250 Henry Zhao: So all he’s saying is we’re retaining this many customers, and if we bring in this many new… new customers, this is gonna be the total. That’s all he’s doing.
164 00:19:22.090 ⇒ 00:19:27.550 Henry Zhao: Eventually, we want to add other things too, like market trends, like decreasing…
165 00:19:27.820 ⇒ 00:19:35.309 Henry Zhao: order, like, decreasing return as you spend more and more, things like that. So we want to continue to fine-tune this so that it becomes as accurate as possible.
166 00:19:35.480 ⇒ 00:19:39.070 Henry Zhao: And as… As flexible as possible.
167 00:19:39.580 ⇒ 00:19:40.280 Robert Tseng: Okay.
168 00:19:46.350 ⇒ 00:19:51.270 Robert Tseng: Okay, great. Actually, Josh is gonna join in 5 minutes, so we’ll finish running through this, and then I’m gonna…
169 00:19:51.730 ⇒ 00:19:55.900 Robert Tseng: Well, this should be good. He can’t make the call later.
170 00:19:57.010 ⇒ 00:20:02.560 Robert Tseng: Let me… grab the… length…
171 00:20:08.720 ⇒ 00:20:16.079 Uttam Kumaran: Yeah, and also, if you need, Robert, I just messaged Rico in the chat to help with the Gantt chart. He could work on that while this is going.
172 00:20:16.700 ⇒ 00:20:17.360 Robert Tseng: Okay.
173 00:20:19.770 ⇒ 00:20:20.950 Uttam Kumaran: Do you need that?
174 00:20:20.950 ⇒ 00:20:28.010 Robert Tseng: I don’t think I need to… I think this is fine for discussion purposes, like, yeah, so…
175 00:20:29.030 ⇒ 00:20:34.700 Robert Tseng: All right, so let’s just kind of keep going through as much as we can. I’m expecting him to join in, like, 5 minutes, so…
176 00:20:35.680 ⇒ 00:20:51.729 Robert Tseng: Yeah, it might be a little bit redundant with, like, Mitesh’s call later, but it’s fine, like, I just… we just need to get a couple… we just need to get this approved, no matter what it takes, I guess. So, sorry, we were… we left off here, right? So, win back… okay, yeah.
177 00:20:52.450 ⇒ 00:20:55.959 Henry Zhao: So next, these are the things I guess I talked to Zoran about, so…
178 00:20:56.020 ⇒ 00:21:15.159 Henry Zhao: these next two are things that I think Judd already knows that he needs to focus on. So, two of his main focuses are win-back campaigns and abandoned cart campaigns. So, right now, obviously, we’re not partnering with Judd that much yet, so we want to work with him to see how effective are win-back campaigns at increasing retention, what is the additional revenue associated.
179 00:21:15.190 ⇒ 00:21:23.850 Henry Zhao: And we want to know this, because we want to know how much he should be focusing on win-back versus abandoned cart campaigns, because obviously there is a limited amount of…
180 00:21:24.420 ⇒ 00:21:39.869 Henry Zhao: emails that we can send out, right? We can’t just send out infinite emails, so where should we focus on this? And then, can we do some A-B testing to improve the timing of win-back campaigns, or the content, anything to make it more effective, if we think that there’s room for opportunity there?
181 00:21:42.510 ⇒ 00:21:45.520 Robert Tseng: Okay, and what’s the baseline? What is it currently?
182 00:21:47.480 ⇒ 00:21:51.589 Henry Zhao: I actually don’t know, I haven’t looked at this. Zoran, have you looked at this yet?
183 00:21:52.020 ⇒ 00:21:53.570 Zoran Selinger: No. No.
184 00:21:53.700 ⇒ 00:21:56.480 Zoran Selinger: I don’t know exactly what the breakdown means.
185 00:21:57.490 ⇒ 00:22:06.330 Henry Zhao: Yeah, I don’t know if we have enough data yet, because Judd has been here only a few months, and when back, I guess you need some time to see it, but Zaran, you can look at the retention dashboard that I sent you.
186 00:22:07.160 ⇒ 00:22:09.849 Henry Zhao: I filter it by the win-back campaigns, and we should have a…
187 00:22:10.580 ⇒ 00:22:12.989 Henry Zhao: not… I don’t know if it’s a trustworthy number, but…
188 00:22:14.830 ⇒ 00:22:22.710 Zoran Selinger: Yeah, I know… I know the report you’re talking about, and I’ll look into all of that tomorrow. I just… I was… I was waiting for.
189 00:22:22.710 ⇒ 00:22:23.220 Henry Zhao: Got it.
190 00:22:23.220 ⇒ 00:22:32.800 Zoran Selinger: for this call with Mitesh that we have after this, and then I’m gonna consolidate everything, and I’m gonna work on… on this, and I’m gonna work on the deck as well.
191 00:22:35.630 ⇒ 00:22:36.230 Henry Zhao: Yeah.
192 00:22:36.380 ⇒ 00:22:43.740 Henry Zhao: Actually, this number should probably just be that bottom part of the chart, which shows how many orders came from win-back campaigns, and just compare it to…
193 00:22:43.740 ⇒ 00:22:44.360 Zoran Selinger: Yeah.
194 00:22:44.500 ⇒ 00:22:45.389 Henry Zhao: Yeah, the people that didn’t get.
195 00:22:45.390 ⇒ 00:22:51.479 Zoran Selinger: Yeah, that part’s clear. I was… I was talking to Giotto over the last week or so.
196 00:22:51.560 ⇒ 00:23:05.980 Zoran Selinger: his understanding is very basic. He doesn’t have many metrics in his head. It’s very, very kind of loose, so we’ll, like… he doesn’t even know if…
197 00:23:06.020 ⇒ 00:23:15.019 Zoran Selinger: For example, his campaigns are more effective when they… when he lands people on… on the… directly into the intake versus on the product page.
198 00:23:15.790 ⇒ 00:23:31.499 Henry Zhao: Yeah, so that’s what we want to help him with. Robert, we didn’t have numbers on this earlier because he wasn’t trusting the numbers in the dash. We wanted to add the edge layer stuff so that he can be more confident in those numbers. So, Zoran, once you add the edge layer data, then you can analyze this, and we’ll probably feel better about that number.
199 00:23:32.310 ⇒ 00:23:43.629 Zoran Selinger: I was looking into that last week, and yeah, we do have a big discrepancy in clicks versus sessions in the Edge.
200 00:23:43.810 ⇒ 00:23:53.750 Zoran Selinger: which is basically the way, the way, for example, Google, handles sessions, and we handle sessions is very, very different.
201 00:23:54.300 ⇒ 00:23:59.319 Zoran Selinger: So I’ll figure… figure out exactly what that means for us.
202 00:23:59.480 ⇒ 00:24:05.980 Zoran Selinger: Yeah, but, edge… edge numbers are… are accurate.
203 00:24:06.500 ⇒ 00:24:10.390 Henry Zhao: I would, I would trust age numbers, because it simply,
204 00:24:10.390 ⇒ 00:24:15.700 Zoran Selinger: It’s simply number of requests that we’re getting from particular traffic source.
205 00:24:15.940 ⇒ 00:24:29.899 Zoran Selinger: So, I see there are a lot of people revisiting from emails within the same session and all of that, so that happens a lot, which is inflating the numbers both of clicks and, for example, sessions that we see in Google Ads… Google Analytics.
206 00:24:29.900 ⇒ 00:24:46.780 Zoran Selinger: Because Google Analytics will start a new session every time a link with a UTM visit. So even if you do it every 5 seconds, it will always start a new session, which is not how our edge works. Our Edge won’t start a new session if you do that.
207 00:24:47.080 ⇒ 00:24:51.319 Zoran Selinger: Yeah, so… Real, real treat.
208 00:24:51.320 ⇒ 00:24:56.520 Henry Zhao: So the current API is part of the analysis. Yeah, that’s part of the analysis we want to do, and then we’ll make recommendations based off of that.
209 00:24:58.090 ⇒ 00:25:10.870 Robert Tseng: Okay, and we… do we have on the roadmap… I mean, this is… I don’t want to get into linear right now, but, like, like, how long will it take to put the edge data in MixedPanel? Or, like, or, sorry, in Customer I.O, or whatever… whatever… like, why… I don’t understand why we haven’t…
210 00:25:11.030 ⇒ 00:25:12.199 Robert Tseng: Why we don’t have that yet.
211 00:25:13.970 ⇒ 00:25:28.779 Zoran Selinger: Oh, I mean, mixed panel… I mean, it’s simply because other things were priority, mainly. We’re dealing with Catalyst right now, and that’s what I was, preparing, both for Mitesh’s meeting and Catalyst. Today, Ryan and myself are talking to
212 00:25:28.780 ⇒ 00:25:44.079 Zoran Selinger: to Catalyst, and we… it’s an important one. We might get, you know, grilled a little bit about particular orders, so we’re just doing our best to understand every single order, and why it wasn’t approved, or it was approved, and it’s…
213 00:25:44.440 ⇒ 00:25:52.419 Zoran Selinger: But Ryan feels like we’re in a really good place, and we’ll… we’ll be in a good relationship with them.
214 00:25:52.550 ⇒ 00:26:03.629 Zoran Selinger: Going forward. Our updates work well, so that was the focus, let’s finish that today, and then we can finally focus on other things a little bit more.
215 00:26:03.630 ⇒ 00:26:05.359 Robert Tseng: Okay, okay, got it.
216 00:26:05.810 ⇒ 00:26:10.009 Robert Tseng: Yeah, I’m assuming this kind of covers the abandoned cart stuff as well.
217 00:26:13.260 ⇒ 00:26:25.790 Zoran Selinger: Yeah, the only part of the, of the analysis, obviously, for abandoned cart. I don’t think if he understands, the phases of cart abandonment, so this is a segmentation we absolutely must do.
218 00:26:26.200 ⇒ 00:26:34.070 Zoran Selinger: If it’s not in place, I don’t know if it is. I just asked him today, and I’m waiting for his, and he logs in a little bit later, I don’t know, I think…
219 00:26:34.320 ⇒ 00:26:35.899 Zoran Selinger: I think he’s in the West Coast.
220 00:26:37.710 ⇒ 00:26:47.529 Zoran Selinger: I have no idea what kind of segmentation he has available on his side at the moment, so I’m trying to figure out what we need to do to support him there.
221 00:26:47.760 ⇒ 00:26:49.050 Zoran Selinger: Yeah.
222 00:26:49.740 ⇒ 00:26:50.150 Robert Tseng: Okay.
223 00:26:50.370 ⇒ 00:26:51.320 Zoran Selinger: I…
224 00:26:51.600 ⇒ 00:27:02.590 Zoran Selinger: getting information from him, it’s… that’s just very sparse. I don’t know if that’s because he doesn’t have it, doesn’t understand it, or I don’t know, I’m not sure why.
225 00:27:02.750 ⇒ 00:27:13.030 Zoran Selinger: But I will… I’ll get to that point where I understand. Okay, he just simply doesn’t have the, you know, the answers to my question. So we’ll see, yeah.
226 00:27:13.560 ⇒ 00:27:19.139 Zoran Selinger: It’s very… it’s very basic. I don’t… I don’t… I’m not sure, what’s happening there exactly.
227 00:27:19.530 ⇒ 00:27:28.670 Robert Tseng: Okay. I feel like Bobby knew more than he did, and like, I don’t know, he’s been here for 3 months, like, I don’t understand why he can’t give you any of these answers. It’s kind of strange.
228 00:27:30.160 ⇒ 00:27:47.619 Zoran Selinger: I’ll press him a little bit more. We’ll do our… we’ll do our goals, and we’re gonna… I’m gonna press, press him on every single thing that we write here. And we plan, and I wanna get those answers, with him as well.
229 00:27:48.620 ⇒ 00:27:50.490 Zoran Selinger: I want us to be on the same page.
230 00:27:52.530 ⇒ 00:27:53.140 Robert Tseng: Okay.
231 00:27:54.180 ⇒ 00:27:57.350 Henry Zhao: Yeah, I think this gives us an opportunity to go in and make noise and make impact.
232 00:27:58.180 ⇒ 00:28:05.789 Robert Tseng: I do feel like this is the lowest hanging fruit for us, for, like, the ed… like, for the work that we’ve done. Like, this is, like.
233 00:28:05.900 ⇒ 00:28:06.690 Robert Tseng: you know.
234 00:28:07.400 ⇒ 00:28:08.090 Robert Tseng: Pop.
235 00:28:08.160 ⇒ 00:28:21.080 Robert Tseng: customer identity stitching and, like, you know, more accurate tracking, like, that… it should… the results should show up in this type of work. So, yeah, I mean, if it means, like.
236 00:28:21.080 ⇒ 00:28:41.820 Robert Tseng: going to the new year, and… I mean, I want to just put on display. Even if he doesn’t measure these things, like, we can measure it, like, we can just go… we should know what the baseline is. He may not be giving it to us, but I don’t think that’s an excuse for us to not know it. We should just go and figure it out. And then, yeah, then we can… we can drive it. Like, this is kind of like what we were doing on Insomnia, like…
237 00:28:42.420 ⇒ 00:28:45.989 Robert Tseng: Yeah, it’s really not that hard, like, I think with, you know.
238 00:28:46.560 ⇒ 00:29:01.699 Robert Tseng: we measured the baseline there, and then Amber kind of made a couple recommendations. They implemented, like, a couple campaigns, and we outperformed what every other campaign that they ran. So, like, I think it’s… it is pretty… I feel like this is very easy for us to make an impact on.
239 00:29:02.090 ⇒ 00:29:02.920 Henry Zhao: Yeah, agreed.
240 00:29:03.170 ⇒ 00:29:07.399 Robert Tseng: Okay. But alright, fine, we can, we can skip that, and then…
241 00:29:07.660 ⇒ 00:29:26.769 Henry Zhao: And then next, yeah, next time I’m already working with Ryan on a plan for intake form improvements. Obviously, now that we have Mixpanel, we want to use the heatmaps, session replays, as well as the funnels to look at areas of improvement for the intake forms and see where people are abandoning, and then come up with two to three big bets on design changes to
242 00:29:26.870 ⇒ 00:29:29.050 Henry Zhao: Kind of improve the conversion rates there.
243 00:29:29.520 ⇒ 00:29:34.829 Henry Zhao: So here we can also do A-B testing, and I think Mixpanel even allows us to do A-B testing within that tool.
244 00:29:35.920 ⇒ 00:29:36.850 Henry Zhao: So, yeah.
245 00:29:38.510 ⇒ 00:29:39.240 Robert Tseng: Okay.
246 00:29:42.290 ⇒ 00:29:44.240 Robert Tseng: Yeah, let’s talk about A-B testing.
247 00:29:44.240 ⇒ 00:29:49.240 Henry Zhao: The current KPI is intake forms are 6-12% CTR.
248 00:29:49.240 ⇒ 00:29:49.640 Robert Tseng: Okay.
249 00:29:49.640 ⇒ 00:29:53.970 Henry Zhao: Our first goal is to improve them all to 12%. So there should be no, like…
250 00:29:54.290 ⇒ 00:29:58.210 Henry Zhao: Discrepancy or inconsistency with the conversion rate, and then we drive it up.
251 00:30:04.550 ⇒ 00:30:05.300 Robert Tseng: Perf.
252 00:30:08.690 ⇒ 00:30:12.459 Robert Tseng: Okay, this was the most… this is the biggest one that’s, like.
253 00:30:12.580 ⇒ 00:30:18.399 Robert Tseng: This is, like, about setting up an A-B testing, like, process. Like, they don’t have…
254 00:30:18.400 ⇒ 00:30:41.820 Robert Tseng: they’re not running… we have to look broadly. This is not tool-specific, right? They have VWO, they have their HRO experiments. It’s just, like, this is a… this is a change management project, like, kind of scope, which is, I think, it’s not going to look the same as these other ones. I mean, I want to talk about it, because I think this is what Adam’s asking for the most. He’s like, how do we… like, why is our team not running more experiments? Like, how do we actually do that?
255 00:30:41.910 ⇒ 00:30:54.780 Robert Tseng: you know, they’re shopping around, ask… trying to look for other experts. I mean, it’s… they’re all gonna run into the same thing. It’s like, well, we just have to… we have to, like, get… we have to coach them to run… run more experiments.
256 00:30:55.110 ⇒ 00:30:56.199 Robert Tseng: That’s kind of the thought here.
257 00:30:56.200 ⇒ 00:31:04.509 Henry Zhao: VWO’s a mess right now, right? Like, we don’t know who’s running those VWO tests, there’s no organization, so we probably just want to take this over, set up a plan.
258 00:31:04.510 ⇒ 00:31:16.889 Henry Zhao: I want to have a spreadsheet just on A-B testing, where people put in ideas, and we’ll propose our ideas also, and then we do a prioritization and say, these are tests we want to do, these are the ways where we’re going to set it up, this is the sample size that we expect.
259 00:31:16.890 ⇒ 00:31:26.229 Henry Zhao: this is the timeline, and this is what the metric of success would be, right? So, if we run an A-B test, like, we’re gonna cut down all intake forms by half.
260 00:31:26.480 ⇒ 00:31:34.860 Henry Zhao: Is our measure of success either increased conversion rates, or is it better customers coming in?
261 00:31:35.240 ⇒ 00:31:38.439 Henry Zhao: Because one thing I’ve seen from A-B tests of, for example, like.
262 00:31:38.810 ⇒ 00:31:56.370 Henry Zhao: reducing the number of steps to an intake form is you get more people terminating it, but you get the quality drops. So you get more people that are allergic to medicine, maybe, you get more people that are not serious and churn. So, this needs to be very well defined in terms of what are we testing, what is our measure of success, and what are our risks.
263 00:31:58.240 ⇒ 00:31:58.920 Robert Tseng: Okay.
264 00:31:59.060 ⇒ 00:32:05.860 Henry Zhao: Yeah, so I want to establish the tracking, I want to understand what we’re trying to drive, and then run those tests.
265 00:32:06.230 ⇒ 00:32:13.120 Henry Zhao: And I want to make sure, also, VWO is the best tool, or do we need something like Optimizely or… or something… something else?
266 00:32:13.450 ⇒ 00:32:30.009 Henry Zhao: And I put 6 tests because the way I see it, I think of, like, 2 tests for lifecycle marketing, so either timing or content of the email messaging, or more targeted messaging, 2 for, like, intake and conversions, and then 2 for, like, operations.
267 00:32:31.420 ⇒ 00:32:32.760 Henry Zhao: Cause I think those are the…
268 00:32:33.210 ⇒ 00:32:37.540 Henry Zhao: the big pillars, and I want to make sure that we’re testing in all areas of the business.
269 00:32:38.080 ⇒ 00:32:38.730 Robert Tseng: Okay.
270 00:32:42.480 ⇒ 00:32:52.129 Robert Tseng: All right, well then, I think, like, when… when we do talk to, Josh Mitesh, I guess if he’s not coming on now, maybe he’ll join later. I don’t know why he’s not on.
271 00:32:52.540 ⇒ 00:33:11.690 Robert Tseng: I’m gonna lead with this one. Like, I think this is the… this is the most… this is the biggest one. Like, all this… all these other things are, like, good to have, but, like, also not fully in our control. Like, this is, like, more… like, we still need to rely on whatever, like, to get our data, and… and,
272 00:33:12.520 ⇒ 00:33:14.790 Robert Tseng: Oh, we moved it… okay, we moved it up, yeah, so…
273 00:33:14.790 ⇒ 00:33:15.779 Henry Zhao: On the top, okay.
274 00:33:16.630 ⇒ 00:33:19.660 Henry Zhao: And I guess I’ll move EOS also, since Josh said that’s a big piece.
275 00:33:20.160 ⇒ 00:33:22.400 Robert Tseng: Yeah, yeah, and EOS,
276 00:33:22.860 ⇒ 00:33:27.939 Robert Tseng: I mean, we’re, we’re just… we’re not, we’re not there yet. Like, I, I, like, I,
277 00:33:28.670 ⇒ 00:33:40.079 Robert Tseng: I’m on the EdenOS project, so, like, I know what progress we’ve made there. We’re not ready to do anything with data structuring for another, like, 2 weeks, probably. So, like, he just wanted that on the sheet, but I don’t need to talk.
278 00:33:40.080 ⇒ 00:33:45.349 Henry Zhao: But I think it’s fine, because this sheet has all the way until… Like, end of 2026, basically.
279 00:33:45.350 ⇒ 00:33:45.930 Robert Tseng: Yeah.
280 00:33:46.460 ⇒ 00:34:06.250 Robert Tseng: Okay, cool. So I think these are the… these are the things that I want to get their sign-off on for… for Q1. Like, I… I think there’s, you know, timeline stuff we can adjust. Honestly, I think this… there’s a lot of moving pieces to this. This is… we’re creating a whole new work stream here, and this is very cross-function. Like, I… in terms of, like, how we’re staffed to do this.
281 00:34:06.510 ⇒ 00:34:23.249 Robert Tseng: like, realistically, Henry, there’s no way you’re gonna be able to do all of these different ones, like, I think this is probably the biggest priority, you’re gonna, you know, you probably end up doing this. Anything around, like, Brad, Rebecca, these types of things, like, we might end up just moving it to Seism. Like, I think…
282 00:34:23.250 ⇒ 00:34:31.950 Robert Tseng: these are all kind of related together, I mean, I’m sure you could support her on it, but, like, you don’t need to be the one chasing them, gathering requirements, whatever, like, I think,
283 00:34:32.420 ⇒ 00:34:51.759 Robert Tseng: Yeah, I think we’re more passive here, because, like, I don’t know, like… I mean, we’re creating forecasts, sure, we can gather the inputs that we want, but, like, actually pushing them to make operational changes is, like… I think that’s less… that’s gonna be less in our ability to influence than this one, so…
284 00:34:51.760 ⇒ 00:34:58.609 Henry Zhao: We can actually hold them accountable, we can have the dash and just look at it weekly, and say, hey, why has this needle not been driven yet, and when do you plan to…
285 00:34:59.060 ⇒ 00:35:02.719 Henry Zhao: kind of drive the needle by how much. And just hold them accountable.
286 00:35:03.250 ⇒ 00:35:06.289 Henry Zhao: Yeah. Otherwise, the same issue of, like, it’s been 3 months and nothing has moved.
287 00:35:06.420 ⇒ 00:35:09.030 Henry Zhao: I mean, we’re gonna get… Also.
288 00:35:09.240 ⇒ 00:35:19.490 Henry Zhao: you know, like, why haven’t we helped them move it, right? So, if we can at least hold them accountable. I think it’ll be good, Seism, when I schedule a call with Rebecca, to have the three of us on it, so that I can make the rest… the…
289 00:35:21.250 ⇒ 00:35:27.040 Henry Zhao: introduction of you with Rebecca, and just say, like, Seism will be helping us out on this, and…
290 00:35:27.250 ⇒ 00:35:30.299 Henry Zhao: Ask her those questions also, of, like, what is she doing operationally?
291 00:35:30.700 ⇒ 00:35:32.779 Sezim Zhenishbekova: Yep, that’ll be perfect.
292 00:35:33.690 ⇒ 00:35:34.310 Robert Tseng: Okay.
293 00:35:35.580 ⇒ 00:35:54.140 Robert Tseng: Cool. Yeah, I like… I like this. I mean, I know we’re not gonna talk through the other priorities, but, anything else that’s not listed on here? I… yeah, once again, this is not, like… we’re still expecting ad hoc requests, right? They’re gonna make us adjust things, like catalyst, whatever, and, like, this is more of, like, if we…
294 00:35:54.140 ⇒ 00:35:56.710 Robert Tseng: Have… yeah, if we’re deciding our roadmap.
295 00:35:56.730 ⇒ 00:36:20.599 Robert Tseng: And, like, yeah, this gives us, you know, these are the… these are the important things. We align with them, saying, like, okay, this is what they want. We’re aligned, this is what they want to get done, too. This allows me to push back on stuff that comes in, right? Like, if we get random requests to do other things, like, you know, this is what they’d be replacing. So, this is, like, our kind of opportunity to kind of carve out, like, a more proactive
296 00:36:20.600 ⇒ 00:36:22.110 Robert Tseng: Part of, the roadmap.
297 00:36:22.860 ⇒ 00:36:23.739 Henry Zhao: No, makes sense.
298 00:36:23.740 ⇒ 00:36:24.430 Robert Tseng: Okay.
299 00:36:24.840 ⇒ 00:36:25.650 Robert Tseng: Cool.
300 00:36:25.830 ⇒ 00:36:35.180 Robert Tseng: Alright, well, yeah, I mean, I feel… I feel good for this… for this discussion. I think this’ll be… I mean, I’m gonna really try to get the approval on it this week,
301 00:36:37.170 ⇒ 00:36:41.500 Robert Tseng: Yeah. I think other than that,
302 00:36:42.320 ⇒ 00:36:53.589 Robert Tseng: Yeah, I think… I think that’s it. So, I mean, as far as, like, tickets and grooming, we have a delivery meeting later today, so I’ll probably have it groomed by then, but I don’t really think we need to spend more time on it now.
303 00:36:55.380 ⇒ 00:36:56.050 Henry Zhao: Okay.
304 00:36:56.050 ⇒ 00:36:59.789 Robert Tseng: Okay, cool. Thanks, everyone. It was good.