Meeting Title: Brainforge x Eden Project Check-in Date: 2026-01-15 Meeting participants: Greg Stoutenburg, Robert Tseng, Rico Rejoso, Amber Lin, Uttam Kumaran
WEBVTT
1 00:00:39.760 ⇒ 00:00:40.460 Robert Tseng: Hey, Greg.
2 00:00:40.800 ⇒ 00:00:41.560 Greg Stoutenburg: Morning.
3 00:00:43.260 ⇒ 00:00:44.120 Robert Tseng: How’s it going?
4 00:00:44.740 ⇒ 00:00:46.099 Greg Stoutenburg: Doing okay, how are you?
5 00:00:47.520 ⇒ 00:00:50.299 Robert Tseng: It went okay as well, yeah. This is,
6 00:00:50.640 ⇒ 00:00:54.579 Robert Tseng: Been a pretty wild week, but we’re getting through it.
7 00:00:54.810 ⇒ 00:00:55.460 Greg Stoutenburg: Yeah.
8 00:01:16.820 ⇒ 00:01:26.689 Robert Tseng: we need more analysts. That is my… that is my, biggest… Dilemma right now.
9 00:01:27.110 ⇒ 00:01:27.700 Greg Stoutenburg: Yeah.
10 00:01:27.910 ⇒ 00:01:28.460 Robert Tseng: Yeah.
11 00:01:28.860 ⇒ 00:01:29.560 Greg Stoutenburg: Yeah.
12 00:01:30.360 ⇒ 00:01:38.640 Greg Stoutenburg: Yeah, obviously I’m not in all the conversations, but it does seem like a lot of new stuff is coming in, and quickly. Yeah. Which is great, great problem to have.
13 00:01:39.430 ⇒ 00:01:40.680 Robert Tseng: Yeah, yeah.
14 00:01:47.060 ⇒ 00:01:57.009 Robert Tseng: Well, I know you did the dry run with the folks yesterday. I don’t really know how it went, but is there anything else that you feel like you need to prep for the heat recall?
15 00:01:57.630 ⇒ 00:02:20.070 Greg Stoutenburg: So today will be, yeah, today’s Hydra, I need to get default on the calendar somewhere. But honestly, no, I think Hedra’s gonna be great. So, what I’m going to be… I mean, this… my update for the day is what I’ll be doing is, today’s gonna be focused on doing that audit for Eden, feeling in a good place about that. I’ve had some time to review a bunch of stuff.
16 00:02:20.070 ⇒ 00:02:24.709 Greg Stoutenburg: And ready to dig in. And I’ll just spend some time
17 00:02:24.950 ⇒ 00:02:43.609 Greg Stoutenburg: I’ll spend some time in default, so I feel like when I get there, I know them. And that’s… that’ll just help me overcome the issue of, I’ve never even met these people before, so this is not… this is a totally brand new thing for me, just based on client notes, transcripts, things like that. So, you know, I want to go in feeling like I know them, even though we’ve never met, and…
18 00:02:43.610 ⇒ 00:02:44.090 Robert Tseng: Yeah.
19 00:02:44.090 ⇒ 00:02:51.699 Greg Stoutenburg: speak confidently to the product. But yeah, the dry run went well. I think the conversation will go great. Looking forward to pitching them a big number, and…
20 00:02:52.840 ⇒ 00:02:53.960 Greg Stoutenburg: Getting more business.
21 00:02:54.350 ⇒ 00:03:03.140 Robert Tseng: Yeah, okay, sounds good. I mean, I guess Amber’s on this call too, but, both you and Amber are gonna basically be pulled back into Eden.
22 00:03:03.260 ⇒ 00:03:11.230 Robert Tseng: Yeah, I mean, I probably won’t make the announcement until next week, I’ll just give you both a chance to kind of get back into, you know, you’re both working on different things, so…
23 00:03:11.410 ⇒ 00:03:19.819 Robert Tseng: Yeah, if I could support on, like, answering any questions, like, I’m available for… for that. I was able to just kind of
24 00:03:20.240 ⇒ 00:03:24.840 Robert Tseng: I do a bi-weekly, check-in with their C-suite, so I did it yesterday,
25 00:03:25.010 ⇒ 00:03:34.019 Robert Tseng: went as well as it could have gone. Like, I… I feel like I just, like, scrambled and, like, did whatever I could. So, yeah. Yeah, I mean, still…
26 00:03:34.520 ⇒ 00:03:51.349 Robert Tseng: I mean, at this point, we… like, there’s trust, you know, I’ve mentioned to you, being like, okay, we’re gonna have Greg be running this, so I think there… it’s not… it was like, we didn’t have that much to show, yesterday, which is not great, but, I think, you know, they understand that.
27 00:03:51.490 ⇒ 00:04:07.510 Robert Tseng: there, we’re different… moving people around, trying to, like, staff our team so that we can, yeah, go after the objectives for this quarter. So, I think overall, like, you know, they were still optimistic about it, so, feel like I was able to manage that well.
28 00:04:07.810 ⇒ 00:04:08.520 Greg Stoutenburg: Okay.
29 00:04:08.800 ⇒ 00:04:09.839 Greg Stoutenburg: Sounds good.
30 00:04:10.190 ⇒ 00:04:24.689 Robert Tseng: But yeah, I mean, I think the audit kind of piece on your side, it’s all written on the outline. If you have any other questions, let me know. I think it’s not just… I mean, obviously, getting into mixed panel, looking at… just trying to establish some sort of internal benchmarking, right? They… they…
31 00:04:24.690 ⇒ 00:04:31.630 Robert Tseng: Like, nobody really understands the state of affairs, and so kind of your first pass as a new person looking in the business from that angle.
32 00:04:31.630 ⇒ 00:04:32.910 Robert Tseng: Especially looking at
33 00:04:32.910 ⇒ 00:04:49.230 Robert Tseng: kind of conversion rates, and, like, what their current experimentation motion is. You know, BWO and Nick’s panel are kind of the two sources to go and investigate that. I think, yeah, that’s where you would start. But once you need to talk to other people, probably next week I’ll get you on a call.
34 00:04:49.370 ⇒ 00:04:56.550 Robert Tseng: The other product analytics agency is a Mixpanel guy, pretty much, that, they are working with.
35 00:04:56.760 ⇒ 00:05:05.139 Robert Tseng: I mean, he’s been… he’s been poking around in the business for 2 weeks now, so, I think it’d be a good time for us to all get on a call with him early next week.
36 00:05:05.150 ⇒ 00:05:07.940 Greg Stoutenburg: Yeah. So I will try to arrange that.
37 00:05:07.940 ⇒ 00:05:18.450 Robert Tseng: Great. Hopefully your Brainforge calendar is updated, and I’ll just try to find something that time… sometime that works with him. And I think that’ll be a way to kind of throw you into the fray.
38 00:05:18.690 ⇒ 00:05:23.010 Greg Stoutenburg: Yeah, cool, that sounds good. Yeah, I think I’m pretty clear on what to do for now,
39 00:05:23.190 ⇒ 00:05:43.139 Greg Stoutenburg: You know, I… most of my work, it’s been in SaaS, so feel free to, you know, if there’s a direction, like, hey, you know, provide feedback freely, please. Yeah. As far as a deliverable for… for this audit, I mean, should I just revise the slides that were shared with me, or should I.
40 00:05:43.140 ⇒ 00:05:52.760 Robert Tseng: No, no need for slides, yeah. I think, yeah, we can just, whatever, if you want to just keep it in a long-form doc, or… Okay. Yeah, that’s totally fine.
41 00:05:52.760 ⇒ 00:05:53.899 Greg Stoutenburg: That’ll speed it up.
42 00:05:54.020 ⇒ 00:06:11.709 Robert Tseng: Yeah, I do know that, I mean, with your SaaS background, I mean, this… the scope of this is very narrow, it’s just… it’s really just first… first purchase. They want to… it’s like a conversion rate optimization exercise. So, I do think it’s simpler than, like, product analytics work. I mean, I came from SaaS as well, so, like, I wasn’t really in CPG before, and I learned that, like.
43 00:06:11.740 ⇒ 00:06:21.040 Robert Tseng: CPG product analytics is just, like, landing page optimization and, like, figuring out, like, what are the levers they can do to basically get more first-time purchasers, so… Sweet.
44 00:06:21.040 ⇒ 00:06:21.630 Greg Stoutenburg: Okay.
45 00:06:21.890 ⇒ 00:06:32.349 Robert Tseng: Yeah, the one nuance with this CPG company is this whole thing of intakes. They have this, like, if you… I would just recommend just going through and trying to buy a product, and, like, you’ll… you’ll see, like.
46 00:06:32.350 ⇒ 00:06:41.930 Robert Tseng: there’s more steps than just going on and buying coffee from, like, a direct-to-consumer coffee brand, right? So, you have to get approval from a pharmacist and all that, yeah.
47 00:06:41.930 ⇒ 00:06:43.099 Greg Stoutenburg: Yeah, yeah. Okay.
48 00:06:43.100 ⇒ 00:06:43.510 Robert Tseng: Yeah.
49 00:06:43.630 ⇒ 00:06:59.160 Robert Tseng: once you understand that flow, then, you know, I think that’s pretty much all you’ll need. I think, like, looking ahead, assuming this goes well and in the scope, what I was really kind of honing in with them is where I think their business is unique is that they’re trying to be, like.
50 00:06:59.370 ⇒ 00:07:06.999 Robert Tseng: the one-stop shop for, like, a personalized help journey. So, contrary to other D2C, help brands, they…
51 00:07:07.010 ⇒ 00:07:19.360 Robert Tseng: you know, they have their own health club. They have two health clubs, one in Denver and one in Detroit. So, like, they sell services as well. This is just their telehealth business. They’re, like, doing… and they’re trying to, like.
52 00:07:19.360 ⇒ 00:07:34.870 Robert Tseng: Trying to figure out, well, is there actually a competitive advantage when they, like, vertically own everything from the pharmacy that compounds the drugs that they’re producing, to the direct-to-consumer drugs that they sell, to also the services that go along with it?
53 00:07:34.870 ⇒ 00:07:35.230 Greg Stoutenburg: Huh.
54 00:07:35.230 ⇒ 00:07:46.910 Robert Tseng: And so, I think, like, being able… I think that makes it a more interesting kind of, like, omni-channel, like, unified kind of experience that maybe your product analytics kind of, you know.
55 00:07:46.910 ⇒ 00:07:47.250 Greg Stoutenburg: Yeah.
56 00:07:47.250 ⇒ 00:07:50.750 Robert Tseng: would be able to help, help with. How do we actually
57 00:07:50.750 ⇒ 00:08:00.360 Robert Tseng: And we could start very narrow. It’s just like Denver and Detroit. I mean, if we just picked one market, we would just look at Denver. Like, can we really have a through line, to…
58 00:08:00.360 ⇒ 00:08:15.809 Robert Tseng: for somebody who learns of Eden on Facebook, that goes to the Eden Health Club, gets some services there, ends up signing up for a prescription, and then, like, you know, like, what’s their outcome? Is their outcome, you know, better than.
59 00:08:15.810 ⇒ 00:08:23.660 Greg Stoutenburg: you know, somebody who just purchases some from Hims and purse, or whatever. So, I think, you know, that’s, like, the bigger meta question on, like, whether or not…
60 00:08:23.660 ⇒ 00:08:41.710 Robert Tseng: either will exist in a year or two years, or if they’re just gonna get bought out in this, like, massive consolidation kind of, like, sprint, where all these, like, you know, similar companies are all gonna, I feel like in the next two years, they’re all gonna basically merge. So, I think that’s, like, the biggest thesis that they’re trying to prove out this year. Yeah.
61 00:08:41.710 ⇒ 00:08:42.360 Greg Stoutenburg: Cool.
62 00:08:42.480 ⇒ 00:08:49.010 Greg Stoutenburg: Cool, yeah, and maybe when I’m home in Detroit, I’ll be like, hey, you guys want to send me to your club, and I’ll tell you what I think.
63 00:08:49.180 ⇒ 00:09:01.529 Robert Tseng: Yeah, no, I mean, if you’re in Detroit, I mean, yeah, like, I… I can get both of us out to an onsite there, like, you know, I think it’s a… that to me is like a… towards the end of Q1, like, like, thing that I’m looking ahead for.
64 00:09:01.530 ⇒ 00:09:09.340 Greg Stoutenburg: I’m already gonna go in March with my, with my girlfriend and kids, and see… say hi to mom, stay with mom, go to a Red Wings game Friday night. It’s already…
65 00:09:09.670 ⇒ 00:09:14.330 Greg Stoutenburg: By the way, there’s some PTO I have planned coming up. Well, I don’t like PTO, but TO.
66 00:09:14.330 ⇒ 00:09:15.030 Robert Tseng: Thank you.
67 00:09:15.030 ⇒ 00:09:26.230 Greg Stoutenburg: Cool. Okay, yeah, thanks for that additional context as well. Okay, I can keep working on the doc, understanding that we’re really looking at that first purchase as the first.
68 00:09:26.230 ⇒ 00:09:32.000 Robert Tseng: for this part, but, like, I’m just trying to give you a picture of where this… why I brought you on this project and where I see this going.
69 00:09:32.000 ⇒ 00:09:36.120 Greg Stoutenburg: I, are they… they’re not using VWO?
70 00:09:36.570 ⇒ 00:09:50.620 Robert Tseng: They are. They are currently. We should have creds all in the OnePass. If you don’t have it yet, you can ask Ricoh to share things with you, so you should be able to poke around in there. It’s very limited. I’ve gone in there. I haven’t gone in there in a couple months, but it’s not much going on in there.
71 00:09:50.620 ⇒ 00:10:05.150 Greg Stoutenburg: Okay, sounds good. Yeah. Rest of my updates, read me, we know, we just corresponded about this. Default pitching today, Hedra, just need the call set up, the SOW’s ready to go. I think I had pinged you on…
72 00:10:05.340 ⇒ 00:10:07.869 Greg Stoutenburg: The default dock.
73 00:10:07.870 ⇒ 00:10:11.879 Robert Tseng: Right, I have not looked at that yet. Okay, sure.
74 00:10:11.880 ⇒ 00:10:13.449 Greg Stoutenburg: I think.
75 00:10:14.460 ⇒ 00:10:31.229 Robert Tseng: I think we’re probably just gonna go off hours, because we already have, like, an hourly rate with them. I think it’s just easier. Caitlin doesn’t really seem to be that diligent with her reviews, to be honest. She’s just kind of like, alright, we’ll just give you more hours. So I think it’ll be… it’ll be different from each, yeah.
76 00:10:31.230 ⇒ 00:10:35.589 Greg Stoutenburg: Yeah, that’s fine. And so then, I guess, just… I don’t know what that rate is, so if you want to just put it on there.
77 00:10:35.590 ⇒ 00:10:36.980 Robert Tseng: Yeah, yeah, yeah, I’ll put it on there.
78 00:10:36.980 ⇒ 00:10:37.440 Greg Stoutenburg: Okay, cool.
79 00:10:37.440 ⇒ 00:10:37.970 Robert Tseng: Okay.
80 00:10:37.970 ⇒ 00:10:38.980 Greg Stoutenburg: Those are my updates.
81 00:10:39.340 ⇒ 00:10:39.810 Robert Tseng: Okay.
82 00:10:39.810 ⇒ 00:10:40.579 Greg Stoutenburg: Cool.
83 00:10:40.580 ⇒ 00:10:41.260 Robert Tseng: Thanks!
84 00:10:41.660 ⇒ 00:10:42.470 Greg Stoutenburg: I’ll drop.
85 00:10:42.470 ⇒ 00:10:43.950 Robert Tseng: Alright, see you guys. Thanks.
86 00:10:45.310 ⇒ 00:10:49.760 Robert Tseng: Amber, I don’t know, you… do you want to review the ABC stuff?
87 00:10:49.760 ⇒ 00:10:51.389 Amber Lin: Oh, yeah, sure.
88 00:10:51.390 ⇒ 00:10:52.010 Robert Tseng: Okay.
89 00:10:52.160 ⇒ 00:10:55.260 Robert Tseng: Great, let’s just do that, since I haven’t gotten a chance to look at it.
90 00:10:58.160 ⇒ 00:11:00.980 Amber Lin: I can share screen, or…
91 00:11:01.660 ⇒ 00:11:04.209 Robert Tseng: Yeah, you wanna share a screen and just walk you through it, what you would…
92 00:11:07.330 ⇒ 00:11:11.240 Amber Lin: Let me pull up my… Computer.
93 00:11:19.050 ⇒ 00:11:20.210 Amber Lin: Hmm…
94 00:11:20.540 ⇒ 00:11:22.879 Robert Tseng: Oh, Amber, I need to hire, like.
95 00:11:23.700 ⇒ 00:11:27.160 Robert Tseng: more of you… Yeah.
96 00:11:28.140 ⇒ 00:11:29.640 Robert Tseng: I don’t know what to do.
97 00:11:30.230 ⇒ 00:11:34.940 Amber Lin: I mean, I think we’re looking for analysts, I think you need consultants.
98 00:11:36.160 ⇒ 00:11:41.670 Robert Tseng: Yeah, no, I don’t like the people that were being put on my calendar.
99 00:11:41.670 ⇒ 00:11:42.540 Amber Lin: Yeah.
100 00:11:42.540 ⇒ 00:11:48.610 Robert Tseng: I don’t think we need… I’m… anybody that has product analysts in their name, like, I don’t want to talk to them anymore, I just feel.
101 00:11:48.610 ⇒ 00:11:49.879 Amber Lin: Why is that?
102 00:11:50.210 ⇒ 00:11:54.420 Robert Tseng: I think their, their, their skill set is actually quite narrow.
103 00:11:57.390 ⇒ 00:12:08.829 Robert Tseng: Yeah, I know, I know, Rico. I don’t really want to talk to her, but I guess I will, I will talk to her. Utam seems optimistic about her, but I’m like, I’m not confident in product analyst people anymore, like…
104 00:12:08.930 ⇒ 00:12:18.339 Robert Tseng: There have been 3 people that have come by that have been product analysts that I’ve not… not really enjoyed. But it’s okay, I’ll keep an open mind, I’ll talk to her.
105 00:12:18.340 ⇒ 00:12:18.700 Amber Lin: Okay.
106 00:12:18.700 ⇒ 00:12:24.029 Robert Tseng: But yeah, I mean, private property analysts, they’re just… it’s just very, very narrow. They’re just,
107 00:12:25.010 ⇒ 00:12:32.169 Robert Tseng: They may just know what MixedPanel or Amplitude and just do some experimentation. I think Greg’s background is a bit more interesting, because.
108 00:12:33.680 ⇒ 00:12:34.960 Robert Tseng: is a PM.
109 00:12:35.160 ⇒ 00:12:45.140 Robert Tseng: And he also was not a product analyst, like, analytic… analyst right out of college. Like, he… he did, like, he taught English, and, like, did other… he, like, he knows how to think.
110 00:12:45.140 ⇒ 00:12:45.540 Amber Lin: Yeah.
111 00:12:45.540 ⇒ 00:12:47.569 Robert Tseng: So, I mean, I don’t know, maybe you’ve…
112 00:12:47.710 ⇒ 00:12:55.170 Robert Tseng: Well, yeah. So, anyway, like, the people… other people that have come by that are running analyst, I’ve… I don’t really think, like, know how to think.
113 00:12:55.450 ⇒ 00:12:55.950 Robert Tseng: Yeah.
114 00:12:55.950 ⇒ 00:12:56.870 Amber Lin: I see.
115 00:12:57.990 ⇒ 00:13:00.210 Amber Lin: We can go, like, the…
116 00:13:00.350 ⇒ 00:13:07.810 Amber Lin: Like, the bigger companies, they go for other measures, so maybe we should go… for the…
117 00:13:08.060 ⇒ 00:13:10.580 Amber Lin: Like, the liberal arts majors, maybe.
118 00:13:10.580 ⇒ 00:13:12.359 Robert Tseng: Oh, yeah, yeah. Totally.
119 00:13:12.500 ⇒ 00:13:18.030 Robert Tseng: I guess… I don’t want to get too sidetracked, but I’m curious, like, what you thought of, like,
120 00:13:18.560 ⇒ 00:13:20.240 Robert Tseng: Sezim’s background.
121 00:13:22.500 ⇒ 00:13:34.920 Amber Lin: I think when I worked with her, I think she was really good with the Excel stuff. I don’t necessarily know how she would do on exploratory analysis, but I think if you have
122 00:13:36.120 ⇒ 00:13:47.239 Amber Lin: I think she’s really good with Excel. I haven’t seen her do much else, but if it’s, like, something we want to optimize, I think if there’s something existing, like, I think she’s really good with that.
123 00:13:47.630 ⇒ 00:13:55.149 Amber Lin: So… I haven’t read her background, though. Is there anything specific about her background?
124 00:13:55.150 ⇒ 00:14:04.000 Robert Tseng: I don’t know, I mean, I don’t really think it matters on paper. You worked with her, so you kind of know, like, what she has… what she can and can’t do. Yeah, I did feel like…
125 00:14:04.330 ⇒ 00:14:06.139 Robert Tseng: even her Excel is, like.
126 00:14:06.370 ⇒ 00:14:12.599 Robert Tseng: mediocre, in my opinion. She, like, doesn’t… the polish isn’t there, it’s her first job out of college, but, like, I’m like.
127 00:14:13.550 ⇒ 00:14:17.870 Robert Tseng: So I feel like she needed some hand-holding to do it, but… and then…
128 00:14:18.660 ⇒ 00:14:27.380 Robert Tseng: But, I mean, I do think that finance-based people, like, kind of understand it better. Like, I like the fact that she’s not…
129 00:14:27.580 ⇒ 00:14:28.480 Robert Tseng: that…
130 00:14:29.110 ⇒ 00:14:35.800 Robert Tseng: like, you get somebody who’s been at a big company for a while, they’re like, oh, I need data coming to me in this way, because this is…
131 00:14:36.200 ⇒ 00:14:40.010 Robert Tseng: I saw it at Google or Amazon, whatever. Yeah. And then, like.
132 00:14:40.700 ⇒ 00:14:44.700 Robert Tseng: Yeah, where she’s just like, I just need CSVs, and I can do something, and, like.
133 00:14:45.160 ⇒ 00:14:54.059 Robert Tseng: that… I think you… we… a lot of the time, we just need to start there. I don’t care. But yeah, so, yeah, anyway, so I think that was…
134 00:14:54.460 ⇒ 00:15:02.269 Robert Tseng: interesting experiment. I mean, I… see what, anyway, so, I’m… I’m just bringing in stuff I’m thinking about outside of these movies.
135 00:15:02.270 ⇒ 00:15:04.370 Amber Lin: Yeah, it is, it is interesting.
136 00:15:04.990 ⇒ 00:15:05.600 Robert Tseng: Yeah.
137 00:15:05.600 ⇒ 00:15:15.559 Amber Lin: Okay, sorry, let’s talk about this. Oh, good. I need to polish the slide, so I want to run through the narrative. I changed it up a little bit, so I’m mainly gonna talk about
138 00:15:16.160 ⇒ 00:15:31.030 Amber Lin: like, which service deserves investment, and that kind of ties into, like, cost to serve, ties into ROI, and the market research that Clarence has done. After that, this section is less developed, but it’s more of, okay, which branch
139 00:15:31.060 ⇒ 00:15:36.740 Amber Lin: are you gonna invest in? And that’s more straightforward than services, I think.
140 00:15:37.380 ⇒ 00:15:48.440 Amber Lin: So, this is still the same, but after this, I put in the slide that Kellaris had, and the main thing I’m pointing out is, like, hey, I don’t think you know that
141 00:15:48.570 ⇒ 00:15:58.800 Amber Lin: say HVAC services are much bigger than your residential passes. In fact, others, like landscaping and plumbing, is even bigger than residential paths. I think this is…
142 00:15:59.030 ⇒ 00:16:05.639 Amber Lin: like, good points for discussion. That’s… that’s essentially my goal here, is like, can this…
143 00:16:06.020 ⇒ 00:16:16.989 Amber Lin: Can this spark some discussion? Can this spark some thinking about, oh, like, maybe we should change our investment direction, or change how they’re allocating the current budget?
144 00:16:17.470 ⇒ 00:16:19.109 Robert Tseng: This is from, parents?
145 00:16:19.340 ⇒ 00:16:21.330 Amber Lin: Yeah, this is from Clarice’s research.
146 00:16:21.860 ⇒ 00:16:22.900 Robert Tseng: Okay.
147 00:16:26.470 ⇒ 00:16:36.760 Amber Lin: I should ask him for the source, because I don’t know if this is from, say, Claude, or Perplexity, or from his, like, EY paper-ish.
148 00:16:36.950 ⇒ 00:16:39.650 Robert Tseng: Yeah, yeah, I think throwing a source on there would be helpful.
149 00:16:39.650 ⇒ 00:16:40.250 Amber Lin: Yeah.
150 00:16:40.660 ⇒ 00:16:47.160 Amber Lin: Okay, cool. And then next one, I… I decided to add this growth rate per top 5 services.
151 00:16:47.160 ⇒ 00:16:47.680 Robert Tseng: Great.
152 00:16:47.680 ⇒ 00:17:03.739 Amber Lin: And so we have… we see HVAC trending up in the past years, and reaching almost about residential pests. And then on the right side is growth rates. So we see, HVAC plumbing, has really good growth rates during, like, during COVID, and it…
153 00:17:03.740 ⇒ 00:17:17.710 Amber Lin: it dropped after COVID, and the more traditional services, like, to ABC, so they’re more core… the services they’re more familiar with has seen, like, a rebound, so, like, Pest and rodent has rebounded in growth.
154 00:17:17.980 ⇒ 00:17:23.630 Robert Tseng: Yeah. So I want to discuss that with them. I was like, why do you think that is? Is it because you didn’t invest much?
155 00:17:23.630 ⇒ 00:17:27.750 Amber Lin: In marketing, and, did it grow here because, like.
156 00:17:28.150 ⇒ 00:17:34.889 Amber Lin: Just because macro factors, or did you do anything there? So, wanted to see what they have done.
157 00:17:35.340 ⇒ 00:17:44.850 Amber Lin: And then… then we’ll lead into, okay, so, for every dollar you invest in marketing, what would be the return?
158 00:17:45.460 ⇒ 00:17:59.460 Amber Lin: So, this first column is calculated, revenue per job, but then I have assumptions just based on how complex these jobs are, because, say, lawn mowing is going to be a lot.
159 00:17:59.600 ⇒ 00:18:13.729 Amber Lin: Oh, sorry. This is so… there’s CAC acquisition, and then there’s multipliers. I just did a 12-month period. I can’t extend this to, like, 5 years in the future, but I haven’t talked with them enough about
160 00:18:13.800 ⇒ 00:18:18.779 Amber Lin: If customers, how customers churn, or…
161 00:18:18.820 ⇒ 00:18:34.039 Amber Lin: if they still remember ABC over a 12-month period, so I just did… I just did one year for now, and this is my assumption that, okay, like, how many times are they going to repeat? So, for example, pests, because they have a… they need… they need pest control to pass
162 00:18:34.090 ⇒ 00:18:45.809 Amber Lin: to pass tests, so they might need them more frequently. But these are up for discussion so that we can talk about, like, okay, what do you think about these? And I also asked Steven for his
163 00:18:45.930 ⇒ 00:18:50.200 Amber Lin: cost report, so hopefully I’ll get some more data there.
164 00:18:50.350 ⇒ 00:18:58.470 Amber Lin: But overall, I also assumed the margins are okay, based on your materials, your labor, etc.
165 00:18:58.470 ⇒ 00:19:01.629 Robert Tseng: Wait, tell me how you got the repeat multiplier again? Sorry, did I miss that?
166 00:19:01.630 ⇒ 00:19:08.900 Amber Lin: Oh, that’s just an assumption of, okay, per customer, how many times are they going to get a service in a 12-month period?
167 00:19:09.400 ⇒ 00:19:11.999 Robert Tseng: And you think commercial pest control would do 8?
168 00:19:12.550 ⇒ 00:19:20.150 Amber Lin: I was thinking, like, if for one account, usually commercial properties will have
169 00:19:20.170 ⇒ 00:19:35.360 Amber Lin: like, multiple properties, and they probably need to pass tests. I’m not sure if they’re on an annual basis that they need to pass it, or more on, like, a quarterly basis. So I just… that might be a higher multiplier, but I think still…
170 00:19:35.360 ⇒ 00:19:39.110 Robert Tseng: I’m just curious, like, if you got these assumptions, you just made them up, I guess.
171 00:19:39.110 ⇒ 00:19:46.060 Amber Lin: I… I made them up based on, because I have their services, and sometimes they have…
172 00:19:46.470 ⇒ 00:19:49.420 Amber Lin: I’ll just flash this through real quick.
173 00:19:49.980 ⇒ 00:19:55.959 Amber Lin: So, they have, like, annual, bi-monthly, bi-weekly, and I can see.
174 00:19:56.230 ⇒ 00:19:57.200 Robert Tseng: Oh, great.
175 00:19:57.200 ⇒ 00:19:59.110 Amber Lin: Volume here, monthly, is the greatest.
176 00:19:59.110 ⇒ 00:19:59.910 Robert Tseng: Yeah, yeah.
177 00:19:59.910 ⇒ 00:20:10.029 Amber Lin: And bi-monthly is also very high, so I know that I made a more conservative assumption. I said, okay, half of them is gonna be not, like, monthly, they’re gonna be annual, so…
178 00:20:10.250 ⇒ 00:20:11.010 Robert Tseng: Sure.
179 00:20:11.010 ⇒ 00:20:11.600 Amber Lin: Yeah.
180 00:20:12.370 ⇒ 00:20:13.630 Robert Tseng: Okay.
181 00:20:13.690 ⇒ 00:20:30.709 Amber Lin: Based on that, I think I… this is still a model, like, a lot of them is floating-in-the-air assumptions, so I want to talk with them about, okay, does this look familiar to you? Have you thought about things in this way? And we’re just… I’m just going to point out, okay, commercial pests.
182 00:20:30.760 ⇒ 00:20:34.329 Amber Lin: Residential pest, landscaping.
183 00:20:34.330 ⇒ 00:20:36.549 Robert Tseng: Landscape’s spelled wrong, by the way, but anyway.
184 00:20:36.730 ⇒ 00:20:38.210 Amber Lin: Oh, I see.
185 00:20:38.440 ⇒ 00:20:40.330 Amber Lin: Good point.
186 00:20:40.330 ⇒ 00:20:42.149 Robert Tseng: It’s okay, I’m just following it, yeah, let’s it.
187 00:20:42.150 ⇒ 00:20:45.260 Amber Lin: Yeah, so these things would have…
188 00:20:46.080 ⇒ 00:20:52.690 Amber Lin: like, higher returns based on the current assumptions. And I also put, like, a small screenshot of the
189 00:20:53.540 ⇒ 00:20:59.100 Amber Lin: of the… existing CAC on GA?
190 00:20:59.650 ⇒ 00:21:01.350 Amber Lin: So… Yeah.
191 00:21:01.830 ⇒ 00:21:08.059 Amber Lin: This is sort of, like, the basis of my assumption of, okay, so for, your cross-network.
192 00:21:08.100 ⇒ 00:21:24.940 Amber Lin: You usually spend about $55, per gen… I believe per generated lead, so for the actual booking of phone calls, it might be more. And then this is for display ads, this is just for paid search, so that’s kind of the basis for my assumption there.
193 00:21:25.410 ⇒ 00:21:33.450 Amber Lin: So, I want to discuss with… discuss with them, and then I’ll flesh this out once Sorum has more, more data on that.
194 00:21:34.470 ⇒ 00:21:44.570 Amber Lin: Yeah. Lastly, I wanted to wrap it up so it’s not just poking evidence in the air, so this is still, like, a…
195 00:21:45.150 ⇒ 00:22:00.600 Amber Lin: high-level summary, I just want to use this to discuss, okay, based on what we’ve seen so far, what are we going to recommend you to invest in, and what should be the strategy for these different things? I took into…
196 00:22:01.000 ⇒ 00:22:03.290 Amber Lin: Factors of these things, of… so…
197 00:22:04.920 ⇒ 00:22:23.559 Amber Lin: these are still, like, these are my ratings out of 5, so these are not based on actual numbers. Like, I did factor in the market size, I factored in, their growth rates, their current market share, but overall, this is still, like, my ratings out of 5 assumption, so…
198 00:22:23.680 ⇒ 00:22:33.130 Amber Lin: I would like to improve this with better data, but overall, like, I want to tell them, okay, on your investment effectiveness, what is going to be,
199 00:22:34.310 ⇒ 00:22:42.310 Amber Lin: What’s the rating there? And, okay, if you do invest, what is the incremental,
200 00:22:42.860 ⇒ 00:22:45.700 Amber Lin: profit potential, so, like, they’re…
201 00:22:45.700 ⇒ 00:22:51.829 Robert Tseng: Yeah, so I think on this note, so, yeah, I mean, models like this, these scoring… these scoring models, they’re…
202 00:22:52.650 ⇒ 00:23:02.919 Robert Tseng: It’s a good… it’s a good way to try to, like, take a bunch of different variables and try to normalize in one score. I think interpretability is always the biggest thing. People look at it and they’re like.
203 00:23:03.050 ⇒ 00:23:10.269 Robert Tseng: I don’t know if I trust these. I mean, maybe intuitively it will make sense, so I think I just want to just… I would probably… I just want to…
204 00:23:10.690 ⇒ 00:23:19.939 Robert Tseng: test, test this a bit. So, service revenue per job, yeah, I mean, that’s basically your, like, your.
205 00:23:21.060 ⇒ 00:23:24.589 Amber Lin: Like, the actuals for 2024.
206 00:23:24.870 ⇒ 00:23:34.520 Robert Tseng: Yeah, it’s like your… it’s like your profitability standard, whatever. And then, investment effectiveness, I think even that’s a little bit unclear, like, what that is still. So…
207 00:23:34.730 ⇒ 00:23:38.300 Robert Tseng: I don’t know if there’s a way for you to kind of more clearly define.
208 00:23:38.300 ⇒ 00:23:44.349 Amber Lin: Yeah, I want to rename it. They look… they sound… now that I’ve read it out to you, they sound like they’re the same thing.
209 00:23:44.870 ⇒ 00:23:52.429 Robert Tseng: Yeah, so, like, I would… maybe I can share a slide with you, but I would do a slide before this, kind of explaining, like, okay, well.
210 00:23:53.900 ⇒ 00:24:08.489 Robert Tseng: you know, we… like, this is how I’m, you know, this is our approach to, like, being able to, like, build this, like, score or whatever. And then you could flash this table. Like, I think there’s just too many things that, like, are uncertain about this that people will, like, not know what to think of it.
211 00:24:08.490 ⇒ 00:24:09.950 Amber Lin: That makes sense, okay.
212 00:24:10.380 ⇒ 00:24:25.019 Amber Lin: Cool. So, like, I think that’s… that’s, like, the end of narratives for the services, so I’ll add in the other side there. This market part is a bit less developed. I don’t have enough market research or
213 00:24:25.020 ⇒ 00:24:33.550 Amber Lin: I think this is where competitive analysis comes in handy, or we’ll need the, like, the localized marketing data from Zoran, or…
214 00:24:33.570 ⇒ 00:24:38.920 Amber Lin: how that works, but, essentially, I’m gonna flash them this distribution.
215 00:24:38.950 ⇒ 00:24:47.479 Amber Lin: You can see San Antonio’s a lot lower, but then I’m gonna flash this market sizing to say, hey, it’s, it’s actually the same size, it might be a little bigger.
216 00:24:47.800 ⇒ 00:25:03.849 Amber Lin: And this is, like, I don’t know the source of this, like, Clarence flashed me this, probably, just as an AI demo, but if they have actual data backing this, like, I want to be able to say, hey, your Waco, market size is
217 00:25:03.980 ⇒ 00:25:13.539 Amber Lin: tiny, whereas the actual market might be a lot bigger, because their Waco is, is… is this compared to their Austin. So…
218 00:25:14.000 ⇒ 00:25:32.709 Amber Lin: it, like, my argument is more so, hey, you have a lot of potential in markets that you maybe have not looked at. Let’s discuss, is it better to invest in a mature market, or should we, put some effort into, say, the emerging or less mature markets? So that’s the discussion I won’t have there.
219 00:25:34.420 ⇒ 00:25:35.060 Robert Tseng: Yeah.
220 00:25:37.670 ⇒ 00:25:40.090 Amber Lin: Oh, and this is the current marketing budget.
221 00:25:40.520 ⇒ 00:25:47.189 Amber Lin: Like, I think it’s just mostly an exact replica of their current, service sizes, or sales sizes.
222 00:25:58.890 ⇒ 00:26:06.330 Robert Tseng: I’m about to show you some slides. Example of how I… Built out.
223 00:26:06.630 ⇒ 00:26:07.580 Robert Tseng: Error.
224 00:26:09.860 ⇒ 00:26:12.410 Robert Tseng: explained a…
225 00:26:13.540 ⇒ 00:26:15.790 Amber Lin: methodology, I was…
226 00:26:17.150 ⇒ 00:26:25.140 Robert Tseng: how I introduced a methodology… For market sizing.
227 00:26:25.610 ⇒ 00:26:30.689 Robert Tseng: That wasn’t going to be intuitive.
228 00:26:33.560 ⇒ 00:26:34.310 Robert Tseng: Okay.
229 00:26:34.610 ⇒ 00:26:37.560 Robert Tseng: You’ve probably seen these slides before, but…
230 00:26:39.090 ⇒ 00:26:46.100 Robert Tseng: I guess, like, what I would call out there… oh, this is not in the right order. Okay, well, yeah, it’s not in the right order. I think, like, the page numbers will show you.
231 00:26:46.100 ⇒ 00:26:47.970 Amber Lin: Oh, there’s page numbers. Yeah. It’s all good.
232 00:26:48.300 ⇒ 00:26:55.900 Robert Tseng: Yeah. So… I mean, you don’t have to make it as complicated as I did. I think I spent a lot more time on it than you did.
233 00:26:56.250 ⇒ 00:26:58.809 Robert Tseng: But, yeah, I mean…
234 00:26:59.160 ⇒ 00:27:18.139 Robert Tseng: hopefully you can see, like, the first one is just, like, methodology with no numbers, just really explaining, kind of, what the equation is. Then the second one, I plugged some numbers in to basically, like, kind of walk them through, like, how I did it for one, and then maybe after, like… I mean, you don’t have to… if you don’t want to do three slides, because it’s too much, it’s fine, you can just do two, but…
235 00:27:18.140 ⇒ 00:27:23.200 Robert Tseng: Yeah, just to kind of help make the leap a lot, like, not much.
236 00:27:23.200 ⇒ 00:27:24.910 Amber Lin: Yeah, yeah, that makes sense.
237 00:27:24.910 ⇒ 00:27:33.850 Robert Tseng: Yeah. Otherwise, if I just threw up, like, slide 5, I guess, like, that would have been a lot for them to take in, and yeah, so, like, I…
238 00:27:34.170 ⇒ 00:27:36.169 Robert Tseng: felt like I needed to, like.
239 00:27:36.410 ⇒ 00:27:40.549 Robert Tseng: introduce it in a… I walk them through it when I clear it.
240 00:27:40.550 ⇒ 00:27:50.609 Amber Lin: That makes sense. My downside right here, like, is that my numbers are not completely backed by, like, actual
241 00:27:51.820 ⇒ 00:28:05.100 Amber Lin: numbers of, say, market size or penetration rate. It’s based on it, but, like, it’s a rating, so I… I might just need two slides, because if I go in too deep, it will make this model seem very weak.
242 00:28:05.520 ⇒ 00:28:08.799 Robert Tseng: Yeah, I mean, you can see in my slide 5, like.
243 00:28:08.970 ⇒ 00:28:14.510 Robert Tseng: two of my inputs are… three of my inputs are assumptions. Three out of four, so, like, it’s…
244 00:28:14.510 ⇒ 00:28:14.860 Amber Lin: Mmm.
245 00:28:14.860 ⇒ 00:28:20.890 Robert Tseng: I don’t really think it’s that far off from what I… what I did. But, you know, you can…
246 00:28:21.280 ⇒ 00:28:27.879 Robert Tseng: It’s okay if you have… assumptions are not, like, raw. I think as long as you can explain, like, where you got them from, it’s fine.
247 00:28:27.880 ⇒ 00:28:34.330 Amber Lin: Mmm, okay, okay, sounds good. I’ll try to use the market data to plug in some assumptions there.
248 00:28:34.780 ⇒ 00:28:35.580 Robert Tseng: Yeah.
249 00:28:36.950 ⇒ 00:28:42.319 Robert Tseng: Yeah, I mean, I would, you know, you could look at slide 5 to see how I, like, how I use subjects, but anyway, so…
250 00:28:42.320 ⇒ 00:28:43.670 Amber Lin: Yeah, cool. Okay.
251 00:28:43.970 ⇒ 00:29:00.020 Amber Lin: Yeah, and I think, so far, the next steps I can think of is, one, to refine the, the ROI model, and I think the next thing I want to do is do a scenario analysis of, okay, we did calculate
252 00:29:00.170 ⇒ 00:29:05.690 Amber Lin: like, ROI. So, if you were to change your marketing budget, what would that look like?
253 00:29:05.760 ⇒ 00:29:21.389 Amber Lin: Yeah. If you were to invest more in San Antonio, does it really give you a lot of return? Should you invest more in HVAC? Wouldn’t it make that service grow a lot, a lot higher? So that’s what I want to do. I don’t know what data I would need to do that there.
254 00:29:21.860 ⇒ 00:29:26.210 Amber Lin: But I think that’s a pretty logical progression after this.
255 00:29:26.800 ⇒ 00:29:27.440 Robert Tseng: Okay.
256 00:29:27.660 ⇒ 00:29:31.739 Robert Tseng: Great, yeah, no, I mean, definitely looks… looks better than the last one, so…
257 00:29:31.740 ⇒ 00:29:35.569 Amber Lin: Yeah, I mean, it tells a story better, so thank you for pointing it out.
258 00:29:36.940 ⇒ 00:29:41.099 Amber Lin: Okay. Cool. We’re at time, we’ll see you on the Eden call.
259 00:29:41.100 ⇒ 00:29:41.990 Robert Tseng: Yep, yeah.
260 00:29:41.990 ⇒ 00:29:42.970 Amber Lin: Alright, thanks.