Meeting Title: Zoom Meeting Date: 2025-06-09 Meeting participants: Robert Tseng, Annie Yu
WEBVTT
1 00:00:15.770 ⇒ 00:00:16.870 Annie Yu: Hello, Robert!
2 00:00:17.430 ⇒ 00:00:19.410 Annie Yu: You back in the States.
3 00:00:19.580 ⇒ 00:00:20.890 Annie Yu: I am back.
4 00:00:20.890 ⇒ 00:00:22.322 Annie Yu: We’ll come back.
5 00:00:23.470 ⇒ 00:00:26.159 Robert Tseng: Yes, it feels feels good to be back.
6 00:00:26.450 ⇒ 00:00:27.360 Annie Yu: Okay.
7 00:00:27.360 ⇒ 00:00:28.540 Robert Tseng: How was your weekend.
8 00:00:31.310 ⇒ 00:00:36.510 Annie Yu: Not too bad. Had to like trim some plants around the house.
9 00:00:37.370 ⇒ 00:00:42.412 Annie Yu: That’s pretty much it like it took so much time that I expected.
10 00:00:42.800 ⇒ 00:00:46.300 Robert Tseng: Oh, wow! You do your own gardening, I guess.
11 00:00:46.300 ⇒ 00:00:52.369 Annie Yu: Well, not not really. We have like a great vines on like a pergola
12 00:00:52.710 ⇒ 00:01:01.349 Annie Yu: trellis kind of thing like like, just like bushes between, like our house and neighbor’s house.
13 00:01:03.430 ⇒ 00:01:06.680 Robert Tseng: Very cool. Well, you’re growing. You’re you’re growing grapes.
14 00:01:07.260 ⇒ 00:01:25.224 Annie Yu: Yeah, that’s from the previous owner. And we just kind of took it over. And it’s out of control. It’s it’s actually insane. It’s so much. But I I think it’s also like kind of pretty, too, and I imagine all the birds will just come eat those grapes, so we’ll see.
15 00:01:25.570 ⇒ 00:01:27.159 Robert Tseng: Have you ever harvested them?
16 00:01:27.440 ⇒ 00:01:35.200 Annie Yu: No, I think I saw some of them like in the like. They are still growing, and I haven’t seen anything
17 00:01:35.850 ⇒ 00:01:36.910 Annie Yu: that’s like.
18 00:01:37.290 ⇒ 00:01:40.160 Annie Yu: I don’t think I’ve seen any graves yet, but.
19 00:01:40.516 ⇒ 00:01:41.230 Robert Tseng: It’s okay.
20 00:01:41.230 ⇒ 00:01:44.569 Annie Yu: Device there are, like all.
21 00:01:44.850 ⇒ 00:01:45.600 Robert Tseng: Huh!
22 00:01:45.840 ⇒ 00:01:51.360 Robert Tseng: That’s cool. That reminds me of a childhood memory. I have like a
23 00:01:52.190 ⇒ 00:01:56.100 Robert Tseng: childhood friend whose family would grow grapes in their yard
24 00:01:56.852 ⇒ 00:02:04.199 Robert Tseng: and we every year would go and help them like harvest, and they would press it into, and they would make their own wine and stuff so.
25 00:02:04.200 ⇒ 00:02:05.999 Annie Yu: That’s so cool.
26 00:02:06.770 ⇒ 00:02:18.059 Robert Tseng: It was yeah. Good good memories, because it’s just, you know, hot hot sun just pulling a bunch of graves, and they would get like close to a thousand pounds every year, or something like that, as well.
27 00:02:18.060 ⇒ 00:02:19.840 Annie Yu: Wow, that’s amazing.
28 00:02:19.840 ⇒ 00:02:21.100 Robert Tseng: Yeah, so
29 00:02:21.400 ⇒ 00:02:26.940 Robert Tseng: don’t know how I do it myself. But there was I. I can do it. If you need someone to harvest your grapes. I can help.
30 00:02:27.933 ⇒ 00:02:28.736 Annie Yu: Noted.
31 00:02:30.640 ⇒ 00:02:31.740 Robert Tseng: Yeah.
32 00:02:31.990 ⇒ 00:02:40.840 Robert Tseng: cool. Well, I I guess it’s just gonna be me. And it’s just gonna be us 2. Today, I think the wage is still out today and then off so I just thought
33 00:02:43.410 ⇒ 00:03:02.119 Robert Tseng: Well, I’d like to share. I just like walk through the deck with you. And then, since this zoom is being recorded hopefully, I’ll just have a wish it as well. And then yeah, with remaining time, we can talk about like the like things that you’re working on in flight. Does that sound? Okay?
34 00:03:02.500 ⇒ 00:03:03.340 Annie Yu: Yeah, yeah.
35 00:03:03.340 ⇒ 00:03:09.129 Robert Tseng: Okay, cool. This won’t take too long. I think I’ll my- my segment. Only be like 10 min. And it was kind of
36 00:03:11.380 ⇒ 00:03:18.959 Robert Tseng: last minute, is it? Last minute? Yeah, kind of I mean, I would. I was gonna work on it over the weekend, but I didn’t. So I was doing it all this morning?
37 00:03:19.461 ⇒ 00:03:33.429 Robert Tseng: So yeah, I mean, this is like a data deck. I’ve been doing this. I was doing it this with Eden every 2 weeks when I 1st started. So it hasn’t been like updated with all the brain force, designs and stuff. I might have to have
38 00:03:33.990 ⇒ 00:03:35.729 Robert Tseng: Hannah or Ann kind of.
39 00:03:36.340 ⇒ 00:03:36.790 Annie Yu: Oh!
40 00:03:36.790 ⇒ 00:03:38.439 Robert Tseng: Them? Later. Oh, yeah.
41 00:03:38.440 ⇒ 00:03:42.039 Annie Yu: When was your client back at jungle.
42 00:03:42.680 ⇒ 00:03:44.190 Robert Tseng: Yeah. Eden was my client. Yeah.
43 00:03:44.210 ⇒ 00:03:45.320 Annie Yu: Oh, well, cool!
44 00:03:45.470 ⇒ 00:03:46.080 Robert Tseng: Yeah.
45 00:03:47.960 ⇒ 00:03:50.750 Robert Tseng: Yeah, I’ve been. I’ve been working with them since
46 00:03:51.530 ⇒ 00:03:54.610 Robert Tseng: no November or December of last year. I forget
47 00:03:55.570 ⇒ 00:04:06.149 Robert Tseng: but yeah, it probably took like a month or 2 months before, like built up enough work to like, sell into, like the brain force team and bring people on and stuff so.
48 00:04:06.310 ⇒ 00:04:06.880 Annie Yu: Yeah.
49 00:04:07.150 ⇒ 00:04:07.800 Robert Tseng: Yeah,
50 00:04:09.450 ⇒ 00:04:26.349 Robert Tseng: yeah. And so, like, you know, I haven’t really touched this in a couple of months, because it just seemed like, once, Josh kind of came in. We changed the sprint planning like this felt like we. We weren’t really doing as much strategic stuff and doing more like just execution. It seems like we’re kind of back at a place where we want to bring it up again.
51 00:04:27.430 ⇒ 00:04:42.300 Robert Tseng: I think it just gives us more leverage just to have our own okayrs or objectives that we’re that we’re kind of recommending or pushing for alongside kind of obviously the daily needs of, you know, people requesting things or whatever.
52 00:04:42.590 ⇒ 00:04:52.279 Robert Tseng: And so you know, looking a bit into the future, like, I think, for where they’re at right now, like, I’ve kind of Consolidated. 2 objectives like one is.
53 00:04:53.290 ⇒ 00:05:05.870 Robert Tseng: you know, we’ve kind of. We’ve introduced new data tools. We’ve also seen kind of other things not be used. And so there’s kind of like a consolidation effort here. As we talk about, like Eden’s data platform.
54 00:05:06.670 ⇒ 00:05:10.220 Robert Tseng: and especially kind of like with the with
55 00:05:10.410 ⇒ 00:05:22.750 Robert Tseng: the big transition off fast looming, like, you know. Supposedly in a month or a month or 2 they’re gonna move off to a different new system that they’ve been building out. So it’s kind of
56 00:05:22.850 ⇒ 00:05:25.959 Robert Tseng: timely that we kind of get ahead of that conversation.
57 00:05:27.070 ⇒ 00:05:31.519 Robert Tseng: Yeah, anyway. So I’m not gonna read through the text on the page you could kind of consume at your own time.
58 00:05:31.650 ⇒ 00:05:39.003 Robert Tseng: But yeah, I would say, just like the 2 objectives that I kind of like drilled into like one that I’ve heard commonly is.
59 00:05:39.850 ⇒ 00:05:42.290 Robert Tseng: yeah, we did a lot of work on
60 00:05:43.430 ⇒ 00:05:51.979 Robert Tseng: transact kind of transactional data and building out these core data models, as Josh calls them. Of all the different.
61 00:05:52.500 ⇒ 00:06:15.669 Robert Tseng: you know, from a transaction to an order, and then, like kind of the full order journey, and then being able to tie that to some customer like service requests like through Zendesk and Whatnot. That’s those are the tickets and the patient journey to some extent, but it’s still pretty limited view. Right? And so we’ve we’ve seen that we have certain holes in this full funnel
62 00:06:17.160 ⇒ 00:06:44.840 Robert Tseng: like on the Presale side. I think we’re fine. We had attribution there, but after the sale, being able to know, like what happens to the order, you know, when they get to the pharmacist. If you have to get to the pharmacy, how it’s processed before it gets shipped out, you know. There, we don’t really have anything there. I think that will be fixed with the Emr, because we’re going to be able to capture more data. But then, also, just being able to look at customer behavior beyond the 1st transaction. So
63 00:06:44.980 ⇒ 00:07:03.579 Robert Tseng: you know, when they’re repeating orders, when they’re opening emails and trying. And they’re launching and they’re being targeted with re retargeting campaigns like, what are all the different levers that we have to communicate with? You know the customers or patients, you know, even after they’ve made that 1st sale known to us. Right?
64 00:07:05.270 ⇒ 00:07:10.559 Robert Tseng: and so we you know, I know you’re doing some of this kind of having some of these conversations with.
65 00:07:11.810 ⇒ 00:07:30.879 Robert Tseng: Well, actually, I would say, maybe on the product launch side, Joanna and Cutter still really only care about that 1st sale, or you know, the 1st couple of purchases because they’re expected to launch products that through their campaigns will be able to be profitable within the 1st or 2. 1, st one or 2 kind of like transactions.
66 00:07:31.382 ⇒ 00:07:39.499 Robert Tseng: But yeah, I think, like the the organization more broadly, wants to understand the patient more, or like the customer journey right? So
67 00:07:39.861 ⇒ 00:07:51.440 Robert Tseng: mixed panel as a tool for that. We haven’t talked too much about it. Maybe you’ve heard me bring it up here and there, or like maybe other people have asked you about it, but I do think that that’s like an initiative that I want to push for again.
68 00:07:53.260 ⇒ 00:07:57.589 Robert Tseng: I think it’ll just save us from a lot of
69 00:07:58.250 ⇒ 00:08:05.330 Robert Tseng: a lot of random things that I’m not really bringing to the team. But I know that people are are want are wanting to know.
70 00:08:06.900 ⇒ 00:08:09.650 Robert Tseng: Yeah, I think we just don’t really have, like a very
71 00:08:10.900 ⇒ 00:08:14.049 Robert Tseng: well supported way to let kind of
72 00:08:14.270 ⇒ 00:08:17.153 Robert Tseng: users be able to explore
73 00:08:20.130 ⇒ 00:08:37.810 Robert Tseng: like different segments with different ways of cutting up the customers like we. We’re kind of the ones that do all the determination there, which is not great, because that means we’re the bottleneck for how much exploration they can do, and we want to be able to empower like the other stakeholders, to go and do that more effectively.
74 00:08:39.413 ⇒ 00:09:04.389 Robert Tseng: So I think that’s 1 piece of it. It’s like figuring out what we’re gonna do to activate mix panel and kind of the steps to get there, and then the other piece is really with the emr migration, like what other steps? What steps do we need to take to make sure we’re ready for that. So I kind of flushed out both of these more in more detail in these 2 slides, so you can feel free to look at that in your own time.
75 00:09:06.060 ⇒ 00:09:14.220 Robert Tseng: Yeah, we all just pause there. See if you have any questions. This is kind of like framing of like kind of where they’re at and where we’re headed kind of makes sense to you.
76 00:09:15.537 ⇒ 00:09:21.659 Annie Yu: One question I do have is for the mix panel. Does that mean?
77 00:09:22.910 ⇒ 00:09:27.320 Annie Yu: So what would we kind of keep or use on? There.
78 00:09:28.230 ⇒ 00:09:33.270 Robert Tseng: Yeah. So I guess maybe a good have you? Have you clicked around in it much.
79 00:09:33.460 ⇒ 00:09:35.919 Annie Yu: No, I don’t think I have access.
80 00:09:36.320 ⇒ 00:09:40.890 Robert Tseng: Okay, I can. I can add you, but
81 00:09:43.990 ⇒ 00:09:47.610 Annie Yu: So the Eden and Brand Forge doesn’t also doesn’t have access.
82 00:09:48.200 ⇒ 00:09:49.550 Robert Tseng: Yeah, maybe not.
83 00:09:50.300 ⇒ 00:09:58.849 Robert Tseng: So there’s a few boards that I’ve put out. So I mean for ads, basic
84 00:09:59.120 ⇒ 00:10:05.950 Robert Tseng: basic use case like for the creative brand team. I’ve kind of just built them some a dashboard here to help them
85 00:10:06.580 ⇒ 00:10:30.459 Robert Tseng: monitor traffic to the main website which I’m calling the marketing site. So you can kind of consume this. But you know, it’s like it’s a drag and drop interface. You can go. And it’s it uses events. And so based on your track events, you can go and like, build different funnels. You can build flows. You can look at retention. So you know, I I know that you’ve been working on retention reporting and heat maps and stuff. And
86 00:10:31.160 ⇒ 00:10:32.570 Robert Tseng: like.
87 00:10:32.680 ⇒ 00:10:38.830 Robert Tseng: yeah, I mean, mixed panel is a good tool for that. Why, we haven’t really pushed this too much is
88 00:10:39.460 ⇒ 00:10:48.110 Robert Tseng: really just that. I think the data that’s going into mixed panel isn’t super clean. I I would say, it’s like 80 90% of the way there.
89 00:10:49.330 ⇒ 00:10:56.049 Robert Tseng: like, it’s really just a lot of bask data that goes in there and then web flow data. So
90 00:10:56.220 ⇒ 00:11:08.210 Robert Tseng: you know everything that a customer does on the website and on the in the shopping or in the in the, in the shopping cart. Most of those events are already kind of firing to this.
91 00:11:09.340 ⇒ 00:11:22.720 Robert Tseng: But when people are talking about like revenue and trying to assign dollar value to things, then things start to get like messed up and don’t really line up with what we see in bigquery. And so that’s why I’ve kind of just like shut it down entirely right. So
92 00:11:23.131 ⇒ 00:11:28.360 Robert Tseng: or like, I didn’t shut it down. It’s obviously still live. But like I’ve directed people away from it until
93 00:11:28.900 ⇒ 00:11:33.339 Robert Tseng: you know, we’ve really had an opportunity to go and and make it usable.
94 00:11:34.760 ⇒ 00:11:36.420 Robert Tseng: So yeah, I think there’s
95 00:11:38.280 ⇒ 00:11:51.570 Robert Tseng: like, frankly speaking, there’s not that much like a customer can do on a even site like they can log into their portal, change their subscription, make more purchases. That’s it. I would say. This is more traditionally a tool that’s usable for software companies.
96 00:11:52.045 ⇒ 00:12:11.219 Robert Tseng: So yeah, like, you’ve maybe you haven’t seen. But for some of our other clients like, I’ve been starting like 2 of the new clients from the past 2 weeks, like, I’ve started them. Mostly, I’ve started both in next panel. So they’re both software companies with more complex user journeys or whatever. So this made sense to start from here more than it did
97 00:12:11.846 ⇒ 00:12:19.189 Robert Tseng: to like. Just go and do all the revenue and order reporting, because that’s not how that business works.
98 00:12:21.230 ⇒ 00:12:27.490 Annie Yu: Yeah, is this more like, like, a Google analytics kind of equivalent.
99 00:12:27.790 ⇒ 00:12:42.669 Robert Tseng: Yeah, I would say, like, Google, analytics is really just like the beginning, like it, it does use event based data. But it only focuses on like conversions, just like the 1st part of the customer journey, right where they’re coming from, and when they make their 1st transaction.
100 00:12:43.120 ⇒ 00:13:10.924 Robert Tseng: But it doesn’t really stitch together. Well, what the user does afterwards. The underlying data model is very simple. You just need an event stream. It’s just like date, you know the event name, and then maybe some properties. And then, ideally, you can just put that all into a single take like model. That’s, you know, just a time, just time based. And so that’s why you’re able to do time based reporting very easily any trends, any funnels stuff like that becomes easier to do
101 00:13:11.450 ⇒ 00:13:18.690 Robert Tseng: And yeah, so that’s that’s why like this type of tools is useful. But yeah, it doesn’t replace tableau, I think.
102 00:13:19.020 ⇒ 00:13:26.790 Robert Tseng: But I do think it’s a good way to model and view behavior data like what users can do.
103 00:13:28.180 ⇒ 00:13:33.530 Robert Tseng: Yeah. Cause we don’t really need to like, turn every event into like a.
104 00:13:33.800 ⇒ 00:13:38.330 Robert Tseng: you know, like a fixed like
105 00:13:38.470 ⇒ 00:14:04.170 Robert Tseng: we don’t. Yeah, we don’t need to. If you create individuals like models for all the different events. Then, you know, you just the fan out is pretty wide, like you can have, you know, virtually infinite events. So it makes more sense to keep it in a single model, and then, just, you know, use a tool like this to be able to get the different views that you want without having to have so much maintenance on like the data.
106 00:14:05.440 ⇒ 00:14:06.060 Robert Tseng: Yeah.
107 00:14:07.530 ⇒ 00:14:12.749 Robert Tseng: So that’s where I feel like is an untapped opportunity that we haven’t really dug into. Because.
108 00:14:12.990 ⇒ 00:14:29.339 Robert Tseng: yeah, I don’t want oation them a lot of, you know, spending their time modeling event data and like creative way, like, you don’t really need to. You just need it all in one place, but we just even getting it all into one place and making sure it’s deduplicated and normalized, and everything
109 00:14:29.670 ⇒ 00:14:47.070 Robert Tseng: we kind of have that set up in segment like, but it’s yeah, like, I think I would prefer it to just be in the data warehouse. And then we push it into mixed panel from there. So that’s really the engineering work that I think needs to happen for me to feel confident that the mix panel is ready, is ready to go.
110 00:14:47.640 ⇒ 00:14:48.850 Annie Yu: Okay. Okay.
111 00:14:49.930 ⇒ 00:14:50.510 Robert Tseng: Yeah.
112 00:14:51.824 ⇒ 00:15:10.419 Robert Tseng: Yeah. The other part with emr migration. I really just think so. I think there’s more of a case for me to. So I’ve been evaluating some tools along the way of like whether or not we should stay in segment or or move off segment. So I think that’s where most of the conversation I’m going to be having with them goes today. I mean, I’m just trying to push them away from segment
113 00:15:11.292 ⇒ 00:15:16.130 Robert Tseng: to a tool called Rudder Stack. So it’s another customer data platform. But
114 00:15:16.380 ⇒ 00:15:21.209 Robert Tseng: it’s it’s it’s built on top of your warehouse. And so all the data sits there.
115 00:15:21.810 ⇒ 00:15:29.119 Robert Tseng: And yeah, like, it’s, I think, because of the way that our
116 00:15:29.280 ⇒ 00:15:33.230 Robert Tseng: data platform already works. We run everything off of the warehouse.
117 00:15:33.440 ⇒ 00:15:46.660 Robert Tseng: It makes sense to me to be able to shift even the way that we, we track process and model event data into the warehouse rather than leaving it in segment, which is, it’s just whole other Saas platform. So
118 00:15:47.221 ⇒ 00:15:50.359 Robert Tseng: that’s really like the biggest point that I’m gonna be making towards them.
119 00:15:50.828 ⇒ 00:16:02.279 Robert Tseng: And then on the mixed panel side. I’m gonna have to clean up the slides, but outdated here. But yeah. So I’m I think I’m just gonna remind them of like, kind of where what steps we need to take in order to get mixed panel activated.
120 00:16:02.940 ⇒ 00:16:15.219 Robert Tseng: I think this was the architecture diagram that wish had put together. This is what it currently looks like. But if we were, we’re gonna be moving a few things away. So I think this needs to be updated as well, so having him own that.
121 00:16:16.205 ⇒ 00:16:29.374 Robert Tseng: The roadmap you’ve seen this doc before. Kind of this is still from like when we’re thinking about tickets and taking on require like requests from from clients like, how do we actually think about
122 00:16:30.100 ⇒ 00:16:39.739 Robert Tseng: tying like the request that we’re getting to like the most important initiatives in the company. I think this is still like a good framework, for, like making sure that everything we do
123 00:16:39.880 ⇒ 00:16:53.239 Robert Tseng: ties back to, you know, product, profitability or understanding the patient lifecycle, optimizing payback periods like doing stuff like this. So I mean, this is still, this is probably more relevant to you, just making sure that when you’re thinking through like
124 00:16:53.260 ⇒ 00:17:16.159 Robert Tseng: reporting requests like, sure, you’re building dashboards and like helping people answer questions here and there, but like the the deeper insight is like, how do we push any of these initiatives? Because if we make an impact here, then that that you know that directly ties to the company’s performance. And that gives us more. You know, Leverage, when we’re talking about the impact that our team has had on the business.
125 00:17:18.640 ⇒ 00:17:28.359 Robert Tseng: Yeah, event, data design and specs. Like, I built this out, you can feel free to click into it. If you’re curious, like, how does event data design work like this is a very core work to.
126 00:17:28.520 ⇒ 00:17:49.570 Robert Tseng: Yeah. When I was running Pongo, I started every client like this way, like product analytics was like my main thing, pretty much so. I helped set up kind of what events people needed. Every every business needed to track. You can have a bunch of ones here. Examples here I can share if you’re curious. And then, like helping them set up kind of their initial dashboards around.
127 00:17:49.890 ⇒ 00:18:08.789 Robert Tseng: Who are their customers, you know. Where are they coming in from? That’s the Google analytics kind of domain. But then, also, more importantly, like, what are they doing in your product? Especially if it’s like a free software product that has a paywall later on. What are all the different things that they do like? How do you get your user to convert to a paid user?
128 00:18:08.860 ⇒ 00:18:30.008 Robert Tseng: Or if it’s more of an E-com company like Eden, it’s like, Okay, where are where are our customers dropping off in their purchase cycle like, how do we optimize intake forms, or like a shopping cart to make it more to to reduce friction, and and stuff and those those types of questions. So
129 00:18:30.380 ⇒ 00:18:45.259 Robert Tseng: we’re this has never been like a core priority for Eden. Up to this point. I’ve done a lot of thinking around it, and already did a lot of the design work. We just never implemented it. So I think that’s kind of where I think these 2 kind of come into play.
130 00:18:45.450 ⇒ 00:18:48.330 Annie Yu: Yeah, I’m I’m just curious for the events.
131 00:18:48.440 ⇒ 00:18:51.390 Annie Yu: And this is just like educating myself. Is.
132 00:18:51.390 ⇒ 00:18:52.120 Robert Tseng: Yeah, yeah.
133 00:18:52.350 ⇒ 00:18:57.599 Annie Yu: Do we like? How do we differentiate like
134 00:18:57.910 ⇒ 00:19:03.719 Annie Yu: activities on like app on mobile or website? Is that something that.
135 00:19:04.510 ⇒ 00:19:16.830 Robert Tseng: Yeah. So I mean, they don’t have an app. So that’s that helps. But yeah, you’re right. Mobile app implementation is different from web app. So, although I would say, for, like an E-com company like Eden, it doesn’t make sense to have a mobile app.
136 00:19:17.190 ⇒ 00:19:32.359 Robert Tseng: I mean, they probably use like a, I know they use a react Js based framework. And so that’s just a web and a web development framework that, you know, is optimized for both mobile and desktop. So
137 00:19:32.660 ⇒ 00:19:40.959 Robert Tseng: yeah, even though you’re, you know, going into a domain on on a browser, it’ll be optimized for a mobile experience. Most of their customers do come in on mobile.
138 00:19:42.280 ⇒ 00:19:58.079 Robert Tseng: But yeah, if that’s the case, it’s the same underlying framework. And so the tracking is the same. It’s just through. It’s just used Javascript, whereas, like the mobile app, the tracking is slightly different. It requires, like another set of instrumentation as well.
139 00:19:59.680 ⇒ 00:20:20.210 Robert Tseng: Yeah, the. And then, yeah, the the events themselves like this one for Eden. I can just share a few things I focus on just breaking it up into like, what are all the different? What are? What are the important milestones that a customer would go through on the Eden product? So one is like pre purchase. They get onto the website or on a landing page.
140 00:20:20.210 ⇒ 00:20:33.210 Robert Tseng: No matter who you are, you have to go through an intake because that questionnaire qualifies you to be a patient and also helps recommend, like the right product, to choose. So that’s always been an important piece to the user journey.
141 00:20:33.879 ⇒ 00:20:40.529 Robert Tseng: And then I think the purchase event is pretty straightforward. It’s what you would expect from any checkout process.
142 00:20:40.939 ⇒ 00:20:51.040 Robert Tseng: And then the post purchase is like, maybe this is a bit more unique to Eden. It’s like as a patient. You can log into your patient portal, and there’s a few different things that you can do there.
143 00:20:51.591 ⇒ 00:21:01.228 Robert Tseng: But that’s that’s pretty much it like there aren’t that many, you know, activities that a user can do compared to like some of the other software companies that I’ve modeled. So
144 00:21:01.730 ⇒ 00:21:13.539 Robert Tseng: they weren’t modeling it this way before. If you look at segment or mixed panels quite messy. They have, like, you know, 100 plus events, when I think that it really can be consolidated down to less than 20
145 00:21:14.473 ⇒ 00:21:18.380 Robert Tseng: and so yeah, I think that would be like
146 00:21:18.630 ⇒ 00:21:21.760 Robert Tseng: this is part of like the mixed panel activation work.
147 00:21:22.210 ⇒ 00:21:36.939 Robert Tseng: I would want these events to be kind of like consolidated and streamlined into something that’s more manageable because nobody wants to maintain a hundred plus events. And anyway. So that’s that’s that’s how
148 00:21:37.060 ⇒ 00:21:39.369 Robert Tseng: that work kind of gets kicked off there.
149 00:21:41.640 ⇒ 00:21:54.989 Robert Tseng: I think I would probably still be doing the design tracking. And you know, once we get to the reporting side and building dashboards. I would probably loop you in, and you can go in, and you can learn how to build reports. In this in this way as well.
150 00:21:56.220 ⇒ 00:21:56.740 Annie Yu: Okay.
151 00:21:57.080 ⇒ 00:21:57.660 Robert Tseng: Yeah.
152 00:21:58.337 ⇒ 00:22:12.729 Robert Tseng: I’ll wrap up. I’ll wrap up now. So data platform documentation, that’s Dave. A lot of used to own. You’ve kind of seen this, Doc. I don’t feel like we’ve been doing a great job of keeping it updated and thorough. But anyway, I think that’s something he’ll keep owning
153 00:22:13.291 ⇒ 00:22:24.530 Robert Tseng: this was something specific that you didn’t ask for. I wanted a waste to finish it, but he didn’t finish it yet, so I might end up just moving the slide. But I think the
154 00:22:24.760 ⇒ 00:22:39.089 Robert Tseng: yeah, leadership wants to just understand, like, what do we? How are we actually tracking a user? And what data we’re collecting for them, how we’re using it to retarget them. That’s kind of just a general question of. They want to understand how that works. So.
155 00:22:39.090 ⇒ 00:22:39.440 Annie Yu: Yeah.
156 00:22:39.440 ⇒ 00:22:42.859 Robert Tseng: I just threw up a couple well, high level
157 00:22:43.120 ⇒ 00:22:47.230 Robert Tseng: pictures, but I would want an actual technical diagram from this.
158 00:22:49.250 ⇒ 00:22:55.340 Robert Tseng: I’ve tagged you in a couple of things. So I know there’s a lot of slides here, and I think, eventually.
159 00:22:55.370 ⇒ 00:23:24.679 Robert Tseng: you know, you’re working on some strategic stuff like we haven’t talked about, predicted Ltv. In some time. But you know, hopefully, like, you’re gonna have capacity to work on more stuff like this, where you’re basically changing the way that they think about a metric, or, you know, introducing something that’s more. Ml, or you know, oriented. And yeah, I would love to be able to kind of bring your work into into these check ins that I do with them as well. So
160 00:23:25.800 ⇒ 00:23:39.780 Robert Tseng: Obviously, there’s nothing for you to put out. Now, I think this is something that’s outstanding for us to kind of work on in this cycle or the next couple of weeks. But anyway, so I think that’s the only one I tag you in. Everything else is more architecture or
161 00:23:40.576 ⇒ 00:23:45.079 Robert Tseng: platform related stuff. So I’ve kind of left that to wish. And Camelotte?
162 00:23:46.770 ⇒ 00:23:56.470 Robert Tseng: yeah, if you have any other questions you can. You want to read about everything we’ve done with Eden. You can kind of look through this 50 slide deck like, I’ve put together everything here. So
163 00:23:57.040 ⇒ 00:24:03.540 Robert Tseng: yeah, could give you some context about how I think about helpings. And
164 00:24:04.270 ⇒ 00:24:10.900 Robert Tseng: well, anyway. So I think this is, this is like the I’ll be talking to them in like 2 h. This is kind of
165 00:24:11.370 ⇒ 00:24:14.477 Robert Tseng: I, yeah, this is this is what I’m gonna be sharing with them. So.
166 00:24:15.150 ⇒ 00:24:15.720 Annie Yu: Okay.
167 00:24:17.360 ⇒ 00:24:23.340 Robert Tseng: Cool. Let’s kinda just jump quickly into like linear stuff. Now.
168 00:24:24.220 ⇒ 00:24:31.969 Robert Tseng: Yeah, anything that you want to call out. I know I haven’t roomed the tickets today, so apologize, and things kind of haven’t carried over.
169 00:24:32.080 ⇒ 00:24:32.690 Robert Tseng: But yeah.
170 00:24:32.690 ⇒ 00:24:49.969 Annie Yu: Yeah, I do have some items. One is, the one is the daily refund, and I know we talked about this last Friday. But I think right now it’s kind of pending demoday’s work, but I don’t believe he has a ticket. So I I’m just thinking it might be
171 00:24:52.670 ⇒ 00:24:54.230 Annie Yu: forgotten.
172 00:24:57.500 ⇒ 00:25:00.520 Annie Yu: Yeah, it’s in that. More details is
173 00:25:01.030 ⇒ 00:25:04.829 Annie Yu: more details are in this thread that I
174 00:25:05.620 ⇒ 00:25:08.830 Annie Yu: I remember tagging you and him.
175 00:25:09.610 ⇒ 00:25:10.480 Annie Yu: But
176 00:25:11.766 ⇒ 00:25:14.534 Robert Tseng: Yeah. I mean, you’re probably right. I think.
177 00:25:21.740 ⇒ 00:25:22.830 Annie Yu: Share.
178 00:25:25.850 ⇒ 00:25:27.754 Robert Tseng: Yeah, I see it.
179 00:25:29.140 ⇒ 00:25:32.220 Robert Tseng: Fund model thing. Yeah, you have a, you need.
180 00:25:33.460 ⇒ 00:25:35.929 Annie Yu: Oh, wait not the wait! Watch this one.
181 00:25:36.770 ⇒ 00:25:40.679 Robert Tseng: This is daily refunds like this is what you’re talking about.
182 00:25:40.680 ⇒ 00:25:42.200 Annie Yu: Oh, yeah. Yeah. Yeah.
183 00:25:43.820 ⇒ 00:25:45.840 Robert Tseng: Yeah, okay, let me, just.
184 00:25:54.380 ⇒ 00:26:04.669 Annie Yu: yeah. So as of now, the yesterday, I guess the daily refund from yesterday is accurate, but not the monthly summary. Just because of that.
185 00:26:04.670 ⇒ 00:26:05.340 Robert Tseng: Okay.
186 00:26:12.410 ⇒ 00:26:16.229 Robert Tseng: okay, I just follow up on the thread. Anything else.
187 00:26:18.156 ⇒ 00:26:23.740 Annie Yu: Yes, the Colorado Zip code.
188 00:26:25.570 ⇒ 00:26:34.549 Annie Yu: So for that part, I saw a Pr. The mother created and kind of tested using the staging, which
189 00:26:34.890 ⇒ 00:26:43.870 Annie Yu: I haven’t like compared that against like Rob’s list. But at least the real numbers look a lot closer to what he had.
190 00:26:44.502 ⇒ 00:26:51.690 Annie Yu: So I guess my follow up question is, then do I give an updated list to Jonah?
191 00:26:53.080 ⇒ 00:26:57.039 Robert Tseng: I mean, do we feel like it’s close, or like ready
192 00:26:59.150 ⇒ 00:27:16.839 Annie Yu: I now have. I also have a question. So the last time I just did all the qualified latest order of each person. So I got like, based on the latest order of each person. If they are in those zip codes, I I grab them.
193 00:27:17.320 ⇒ 00:27:17.660 Robert Tseng: Yep.
194 00:27:17.660 ⇒ 00:27:19.820 Annie Yu: Now, I’m thinking, like, do we do?
195 00:27:21.380 ⇒ 00:27:31.149 Annie Yu: What is there like a better proxy, or something that Rob has always done like the last
196 00:27:31.520 ⇒ 00:27:34.980 Annie Yu: 6 months, or last 12 months, or.
197 00:27:34.980 ⇒ 00:27:37.310 Robert Tseng: Using their you’re using their last order. Is that what you’re saying.
198 00:27:37.310 ⇒ 00:27:38.980 Annie Yu: Just the last order.
199 00:27:41.080 ⇒ 00:27:47.489 Robert Tseng: yeah, I think that’s fine. We’ll just call it out. Just tell Jonah like we confirm this. This is like what it is.
200 00:27:47.969 ⇒ 00:27:54.440 Robert Tseng: Where this is based off of like their last order. I think as long as we tell them that I think that’s fine.
201 00:27:54.930 ⇒ 00:27:58.007 Annie Yu: Okay, yeah, that with the updated.
202 00:27:59.040 ⇒ 00:28:04.650 Annie Yu: yeah, I’m just testing and staging so far. But I, if I’m
203 00:28:05.370 ⇒ 00:28:11.600 Annie Yu: remember right, I remember seeing at least like 6, 600, or even 700.
204 00:28:12.320 ⇒ 00:28:13.040 Robert Tseng: Okay.
205 00:28:16.870 ⇒ 00:28:34.949 Robert Tseng: yeah. Well, I would just say, like, if it’s a huge variance from what Rob’s list has, then I think we should just make sure that we have an explanation for why? Even if you don’t know how to match it up exactly. But even just qualifying like this is because we’re using last quarter. But like to me, I would be like, does it make sense that we’re off by like?
206 00:28:35.090 ⇒ 00:28:45.310 Robert Tseng: I’m not saying we are. But if we are off by like 500 patients, I wouldn’t believe that it’s because that we’re using the last order. And Rob is using like.
207 00:28:45.310 ⇒ 00:28:54.480 Annie Yu: Oh, yeah, yeah. So so last week we were off by around 300 and push that. Pr, I think it fixed something. So now we have.
208 00:28:54.640 ⇒ 00:28:57.810 Annie Yu: I think it’s like very close to what Rob had.
209 00:28:58.020 ⇒ 00:29:05.060 Robert Tseng: Okay, yeah. I mean, if it’s really close, you know, plus minus, like, you know, less than 5% difference. Like, I don’t really think I care that much.
210 00:29:05.782 ⇒ 00:29:08.190 Robert Tseng: But yeah, I think
211 00:29:08.790 ⇒ 00:29:27.520 Robert Tseng: that’s that’s generally what I would. I would say if if somebody comes back to you being like, I don’t know. If I trust your data, it’s more than 5% off from what my understanding is, then I think we do owe them an explanation generally anything less than that like I don’t know. It could just be something really small for like why, the difference is what it is.
212 00:29:27.520 ⇒ 00:29:29.040 Annie Yu: Yeah.
213 00:29:32.850 ⇒ 00:29:40.690 Annie Yu: and oh, and one more thing I wanna talk about is the profit bars for exact dash.
214 00:29:41.310 ⇒ 00:29:41.820 Robert Tseng: Yep.
215 00:29:42.233 ⇒ 00:30:08.710 Annie Yu: If you can click into that ticket. I did ask some comments. I haven’t published the the chart, but that’s what I like. Came came up with. So just like a small caveat was that for revenue and orders we were having, like new customers versus returning customers. But then, for profit, we only have total versus new. So not like returning and new.
216 00:30:10.100 ⇒ 00:30:15.480 Robert Tseng: I would say, just look at total. We don’t need to show new. We already do the new.
217 00:30:15.480 ⇒ 00:30:18.919 Annie Yu: They’ll need like a stack bar. So really, just the total.
218 00:30:18.920 ⇒ 00:30:27.109 Robert Tseng: Yeah, yeah, I think just like a simple profit would be fine, because we already do the new versus returning kind of view in a different in like revenue. Right? So.
219 00:30:27.110 ⇒ 00:30:28.330 Annie Yu: Yeah. And
220 00:30:29.120 ⇒ 00:30:37.259 Annie Yu: and if you can just double check on the formula for me, if that would be great, I I think I’m just
221 00:30:37.850 ⇒ 00:30:41.870 Annie Yu: I just wanna double check on the if you scroll up a little bit.
222 00:30:42.080 ⇒ 00:30:46.989 Annie Yu: That’s what I got from the existing dashboard.
223 00:30:48.450 ⇒ 00:30:50.790 Annie Yu: So is this how I think about profit.
224 00:30:52.070 ⇒ 00:31:01.300 Robert Tseng: Revenue minus ad spend minus cogs. Yeah, I would say, that’s correct. I mean ad spend and cogs
225 00:31:02.520 ⇒ 00:31:08.320 Robert Tseng: we don’t have like a full customer
226 00:31:11.400 ⇒ 00:31:12.909 Robert Tseng: like, I mean our hogs definition.
227 00:31:12.910 ⇒ 00:31:13.309 Robert Tseng: That’s pretty much.
228 00:31:13.310 ⇒ 00:31:21.290 Robert Tseng: Jonah knows this. He’s working on this as well. He has a sense of what profitability is. So I would say, just like, Let him know.
229 00:31:23.310 ⇒ 00:31:25.219 Robert Tseng: yeah, I mean, I.
230 00:31:27.320 ⇒ 00:31:31.320 Annie Yu: I mean, I could always like write this kind of formula under the.
231 00:31:33.290 ⇒ 00:31:41.334 Robert Tseng: Yeah, I would. I would spell it out and like, maybe just have Jonah review it 1st before we we share it with
232 00:31:41.980 ⇒ 00:31:46.219 Robert Tseng: the the broader company, or like, yeah, the the entire analytics show.
233 00:31:46.440 ⇒ 00:31:49.749 Annie Yu: So does that mean? He might have a different.
234 00:31:49.970 ⇒ 00:31:55.770 Robert Tseng: I I he, I think he does have a different number. But I will.
235 00:31:59.510 ⇒ 00:32:07.874 Robert Tseng: Yeah, actually, yeah. Once, once you once you get into the right place, or like, you know, you change it up a bit. Just let me know. I’ll I’ll talk it out with him.
236 00:32:08.120 ⇒ 00:32:08.740 Annie Yu: Correct.
237 00:32:13.960 ⇒ 00:32:19.059 Robert Tseng: I was like seeing something that he he shared like last week, and I think his numbers are different.
238 00:32:20.270 ⇒ 00:32:28.589 Annie Yu: Okay? So oh, okay, I guess if that’s updated, we then next steps have to update all the
239 00:32:29.140 ⇒ 00:32:32.350 Annie Yu: profit related metrics in other.
240 00:32:32.350 ⇒ 00:32:38.249 Robert Tseng: Yeah, that’s okay. I think we just we just put up what we have to him. And then we’ll we can. We can figure out how we need to.
241 00:32:38.770 ⇒ 00:32:39.400 Annie Yu: Okay. Yeah.
242 00:32:39.400 ⇒ 00:32:41.570 Robert Tseng: Probably will need to update it. But yeah.
243 00:32:41.570 ⇒ 00:32:42.590 Annie Yu: Okay. Cool.
244 00:32:47.040 ⇒ 00:32:47.800 Robert Tseng: Okay.
245 00:32:48.701 ⇒ 00:32:53.120 Annie Yu: An order last week. Rebecca asked about the order
246 00:32:53.220 ⇒ 00:32:59.770 Annie Yu: to deliver date. I also just saw that the model they had the Pr for that.
247 00:33:00.170 ⇒ 00:33:06.190 Annie Yu: So I’ll update last section using the the new field.
248 00:33:07.040 ⇒ 00:33:07.810 Robert Tseng: Okay.
249 00:33:14.400 ⇒ 00:33:25.150 Robert Tseng: yeah. Thanks for taking the the Friday like random. What did? What did? What did Joan even ask you to do? And actually, I mean, I haven’t. I haven’t reviewed finished reading all the messages. I can go and look it up. And
250 00:33:26.460 ⇒ 00:33:27.389 Robert Tseng: yeah, I know.
251 00:33:27.390 ⇒ 00:33:31.269 Annie Yu: He, he DM’d me he asked for something
252 00:33:31.890 ⇒ 00:33:40.250 Annie Yu: I don’t even remember now, but it’s just some fields from from older summary, I think like order details.
253 00:33:42.366 ⇒ 00:33:45.399 Annie Yu: Current status order. Total. Cox.
254 00:33:47.370 ⇒ 00:33:54.419 Annie Yu: Yeah, I didn’t really know what the use case was. I just like confront with him
255 00:33:54.620 ⇒ 00:33:58.529 Annie Yu: the kind of the granularities and the fields.
256 00:33:58.960 ⇒ 00:33:59.600 Robert Tseng: Okay.
257 00:34:03.420 ⇒ 00:34:08.949 Robert Tseng: yeah. If you could. If you could forward that message that you got from him into the
258 00:34:09.139 ⇒ 00:34:15.238 Robert Tseng: like in into the one of our shared channels. Like, I think that might be helpful.
259 00:34:16.300 ⇒ 00:34:22.625 Robert Tseng: yeah, because basically, what I’m hearing is like, he just asked you like to about a particular field and a data model like
260 00:34:22.900 ⇒ 00:34:24.459 Annie Yu: Yeah, yeah, we’re working.
261 00:34:24.469 ⇒ 00:34:27.529 Robert Tseng: On some automation here, so that, like.
262 00:34:28.569 ⇒ 00:34:38.699 Robert Tseng: if there are any questions about the data model like we should have it. We should have, like a an agent that just like responds and and tells tells it to them without us having to agree.
263 00:34:39.360 ⇒ 00:34:43.040 Annie Yu: Okay, is there a way I can add you to this.
264 00:34:43.750 ⇒ 00:34:49.058 Robert Tseng: I think if you forward it, you forward his his DM. And you forward it into
265 00:34:49.757 ⇒ 00:34:53.230 Robert Tseng: one of the other Eden channels. I think you should be able to do that. But
266 00:34:54.120 ⇒ 00:34:55.600 Robert Tseng: that’s why that’s what I usually do.
267 00:34:56.110 ⇒ 00:34:57.970 Annie Yu: Okay, copy link.
268 00:34:58.610 ⇒ 00:34:59.260 Annie Yu: I didn’t.
269 00:34:59.260 ⇒ 00:35:07.340 Robert Tseng: I would say, not copy Link. It’s forward. I don’t know if you have it. Forward message. When you go hover around. Reply to thread.
270 00:35:07.530 ⇒ 00:35:15.400 Annie Yu: Oh, yeah, but okay, but our like chats were like pretty scattered that that would mean like multiple shares.
271 00:35:15.400 ⇒ 00:35:19.150 Robert Tseng: Oh, it wasn’t like a full thread then just screenshot it and send it. I think it’s fine.
272 00:35:19.300 ⇒ 00:35:19.790 Annie Yu: Like.
273 00:35:19.790 ⇒ 00:35:20.870 Robert Tseng: Do not too.
274 00:35:23.250 ⇒ 00:35:24.170 Robert Tseng: Okay.
275 00:35:26.010 ⇒ 00:35:27.330 Robert Tseng: Cool.
276 00:35:27.330 ⇒ 00:35:35.230 Annie Yu: Type form, but I think I I did take a look, but I will probably have more questions for a wish on that.
277 00:35:35.230 ⇒ 00:35:39.420 Robert Tseng: Okay, yeah, no problem. I think oasis kind of out today. But yeah.
278 00:35:39.420 ⇒ 00:35:41.089 Annie Yu: I think it’s on holiday.
279 00:35:41.530 ⇒ 00:35:42.290 Robert Tseng: Okay.
280 00:35:44.370 ⇒ 00:35:44.980 Robert Tseng: Cool.
281 00:35:46.120 ⇒ 00:35:47.359 Annie Yu: Okay. Alright. Thank you.
282 00:35:47.360 ⇒ 00:35:48.860 Annie Yu: Thanks, Manny. Bye.