Meeting Title: PP2G | Standup Date: 2025-05-02 Meeting participants: Luke Daque, Uttam Kumaran, Amber Lin, Robert Tseng
WEBVTT
1 00:09:32.750 ⇒ 00:09:33.810 Luke Daque: Hi Robert!
2 00:09:35.340 ⇒ 00:09:36.190 Robert Tseng: Hey! Luke!
3 00:09:39.830 ⇒ 00:09:40.790 Luke Daque: How’s everything?
4 00:09:48.860 ⇒ 00:09:49.870 Robert Tseng: Oh! Can you hear me?
5 00:09:50.560 ⇒ 00:09:52.400 Luke Daque: Yeah, I can hear you. Can you hear me?
6 00:09:57.800 ⇒ 00:10:03.299 Robert Tseng: Okay, I had to change my speaker. I think I can. You say something again?
7 00:10:04.250 ⇒ 00:10:05.430 Luke Daque: Hi! Can you hear me now?
8 00:10:06.210 ⇒ 00:10:08.199 Robert Tseng: Yeah, I can hear you better. Okay. Great.
9 00:10:08.200 ⇒ 00:10:09.640 Luke Daque: Nice. Yeah.
10 00:10:12.820 ⇒ 00:10:14.579 Luke Daque: so how’s everything? So far?
11 00:10:16.730 ⇒ 00:10:22.245 Robert Tseng: It’s good. Yeah, this week was
12 00:10:23.710 ⇒ 00:10:32.734 Robert Tseng: We didn’t start off too great. I think I was kind of disappointed with some of the the deals that didn’t go through. I kind of shared a bit about it during the
13 00:10:33.120 ⇒ 00:10:33.940 Robert Tseng: all hands.
14 00:10:35.110 ⇒ 00:10:43.970 Robert Tseng: But yeah, I feel like it was. It was good. I I feel like I know.
15 00:10:45.350 ⇒ 00:10:48.489 Robert Tseng: I mean, it’s always kind of a trade off. Sometimes
16 00:10:49.160 ⇒ 00:10:59.469 Robert Tseng: when you’re trying to grow, you try to do things differently. And I mean, I’m not saying that the advice we got from our advisors or anything was not good, but maybe at some point it
17 00:11:00.600 ⇒ 00:11:05.850 Robert Tseng: like it felt like we were just like trying to be to.
18 00:11:06.250 ⇒ 00:11:09.913 Robert Tseng: I mean to corporate about like this whole sales process.
19 00:11:11.370 ⇒ 00:11:20.439 Robert Tseng: we. We still need to build systems and things, but like as far as like actually closing the deals when we’re on on calls like I,
20 00:11:20.810 ⇒ 00:11:26.039 Robert Tseng: I feel like, maybe I lost a bit of the human element, or like I don’t know some of the.
21 00:11:28.240 ⇒ 00:11:28.730 Luke Daque: Yeah.
22 00:11:28.730 ⇒ 00:11:32.630 Robert Tseng: Yeah, some some of the the secret sauce that I feel like
23 00:11:32.820 ⇒ 00:11:38.529 Robert Tseng: I had when I 1st started this. And like, I don’t know, there’s almost a sense of entitlement that like.
24 00:11:38.940 ⇒ 00:11:46.249 Robert Tseng: Oh, yeah, we get to the stage like it. It should. It should happen it should close. And obviously the expectations have changed. Because.
25 00:11:46.819 ⇒ 00:11:59.020 Robert Tseng: yeah, I mean, we’ve been in business for a couple of years now, and maybe we’ve gotten a good number of clients. And just, you know, really treat each opportunity the same that you did before. So
26 00:11:59.200 ⇒ 00:12:09.109 Robert Tseng: I think it’s it’s been humbling, but it’s it’s good. I think we we need to kind of return to where we were at a little bit, in terms of how we approach conversations
27 00:12:09.250 ⇒ 00:12:14.749 Robert Tseng: not necessarily like like, and that what the work that we did was
28 00:12:15.220 ⇒ 00:12:23.929 Robert Tseng: is not that we still need to scale, but, like sometimes, as you scale you, you lose something along the way, too. So I think that’s all that this
29 00:12:24.350 ⇒ 00:12:28.440 Robert Tseng: this these recent experiences have been have been teaching me.
30 00:12:29.700 ⇒ 00:12:31.299 Luke Daque: Yeah, that now makes sense.
31 00:12:31.820 ⇒ 00:12:42.709 Luke Daque: But yeah, it sucks sucks, like we’re very close like to. I. I can’t even imagine being in your place where where we’re very close to having the
32 00:12:43.520 ⇒ 00:12:45.660 Luke Daque: it gets out. And so, yeah.
33 00:12:45.920 ⇒ 00:12:52.729 Robert Tseng: Yeah, I mean, we we lost 3 deals in the past 2 weeks. So I’ve I’ve been pretty disappointed with myself to be honest, because.
34 00:12:53.230 ⇒ 00:13:04.929 Robert Tseng: yeah, I just feel like we at that point at any. Whenever it gets to that point it. I, I’ve been expecting that we just close it. So, yeah, trying to do things a little bit differently, moving forward.
35 00:13:05.700 ⇒ 00:13:06.430 Robert Tseng: Yeah.
36 00:13:06.430 ⇒ 00:13:07.060 Luke Daque: Cool.
37 00:13:09.620 ⇒ 00:13:10.670 Luke Daque: It works.
38 00:13:11.680 ⇒ 00:13:12.410 Luke Daque: Yeah.
39 00:13:12.410 ⇒ 00:13:18.580 Robert Tseng: That’s just how it is. Kind of like, yeah, it feels like any.
40 00:13:19.090 ⇒ 00:13:21.339 Robert Tseng: Yeah, we’re still small enough that like
41 00:13:21.810 ⇒ 00:13:27.889 Robert Tseng: it feels like at any week. We could just double in size.
42 00:13:28.560 ⇒ 00:13:28.970 Luke Daque: Yeah.
43 00:13:28.970 ⇒ 00:13:33.030 Robert Tseng: Or or nothing or nothing at all. So yeah, that’s I guess.
44 00:13:33.328 ⇒ 00:13:37.810 Robert Tseng: It’s just kind of been nothing in the past past couple of weeks. But yeah.
45 00:13:43.090 ⇒ 00:13:43.700 Luke Daque: Cool.
46 00:13:46.510 ⇒ 00:13:47.169 Robert Tseng: How are you doing.
47 00:13:47.170 ⇒ 00:13:47.760 Luke Daque: Such.
48 00:13:48.090 ⇒ 00:13:54.570 Luke Daque: Yeah, I’m doing doing well then, like, go and do some research on like, mostly the sales stuff
49 00:13:55.325 ⇒ 00:14:00.650 Luke Daque: getting like leads. Still from Linkedin to clay and stuff like that, automating them.
50 00:14:00.650 ⇒ 00:14:01.270 Robert Tseng: Okay.
51 00:14:02.180 ⇒ 00:14:09.239 Robert Tseng: Oh, hey, have you heard of that app called express? I like posted about it in the break.
52 00:14:09.240 ⇒ 00:14:09.580 Luke Daque: I.
53 00:14:09.580 ⇒ 00:14:10.680 Robert Tseng: Team Channel.
54 00:14:10.680 ⇒ 00:14:16.940 Luke Daque: I did check it out. It’s not. It exists here, but it’s not the most used
55 00:14:17.070 ⇒ 00:14:25.459 Luke Daque: way. Means of travel like most people use grab, which is like uber. Still, it’s still the same express. So
56 00:14:25.860 ⇒ 00:14:28.319 Luke Daque: yeah, but yeah, that that could be.
57 00:14:30.130 ⇒ 00:14:33.079 Luke Daque: are they like a potential client or something.
58 00:14:33.800 ⇒ 00:14:40.740 Robert Tseng: Yeah, they’re this. Their CEO reached out to me yesterday. So we were like talking a bit. We’re gonna hop on a call soon. But
59 00:14:41.755 ⇒ 00:14:48.399 Robert Tseng: interesting Philippines based ride sharing app. I don’t know. I’ve never heard of it. But yeah.
60 00:14:49.940 ⇒ 00:14:51.998 Luke Daque: Yeah, is it? Is it
61 00:14:53.010 ⇒ 00:14:56.169 Luke Daque: common in the us to do ride sharing as well, or something.
62 00:14:58.070 ⇒ 00:14:59.080 Robert Tseng: I
63 00:15:00.440 ⇒ 00:15:05.722 Robert Tseng: wait. Is this like, actually, just like, Oh, yeah, it’s like, it’s like uber or grab kind of thing.
64 00:15:06.000 ⇒ 00:15:06.450 Luke Daque: Yeah.
65 00:15:06.450 ⇒ 00:15:09.959 Robert Tseng: Probably not as much, because it’s a much bigger
66 00:15:10.200 ⇒ 00:15:13.090 Robert Tseng: place. So people just have their cars, or whatever.
67 00:15:13.090 ⇒ 00:15:14.339 Luke Daque: Yeah, right, right.
68 00:15:14.340 ⇒ 00:15:19.669 Robert Tseng: Especially like no motorcycle like ride share. I don’t think that exists in the Us.
69 00:15:20.000 ⇒ 00:15:25.180 Luke Daque: Yeah, that’s very common here, because it’s it’s the cheaper to like cars. So yeah.
70 00:15:25.930 ⇒ 00:15:32.329 Robert Tseng: Yeah. And when I was in Vietnam a couple of years ago, like I was just taking the grab everywhere. So you know, I just.
71 00:15:32.330 ⇒ 00:15:32.760 Luke Daque: See you.
72 00:15:32.760 ⇒ 00:15:37.000 Robert Tseng: Just jump on the back of someone’s motorcycle and just go places.
73 00:15:37.895 ⇒ 00:15:38.430 Luke Daque: Yeah.
74 00:15:39.590 ⇒ 00:15:40.190 Robert Tseng: Yeah.
75 00:15:41.170 ⇒ 00:15:41.920 Luke Daque: Nice.
76 00:15:46.140 ⇒ 00:15:47.093 Robert Tseng: Let me
77 00:15:51.410 ⇒ 00:15:54.300 Robert Tseng: I’ll ping amber.
78 00:15:55.460 ⇒ 00:15:59.819 Luke Daque: Yeah. I wonder if Tom’s gonna join as well. He didn’t accept the invite, but.
79 00:16:00.300 ⇒ 00:16:00.640 Robert Tseng: Yeah.
80 00:16:01.500 ⇒ 00:16:07.289 Luke Daque: Oh, it looks like the this was moved to which 10 min from now.
81 00:16:08.250 ⇒ 00:16:09.139 Robert Tseng: Oh! Was it.
82 00:16:10.890 ⇒ 00:16:12.169 Luke Daque: It looks like it.
83 00:16:14.020 ⇒ 00:16:14.410 Robert Tseng: Okay.
84 00:16:14.410 ⇒ 00:16:16.770 Luke Daque: Have other meetings so.
85 00:16:18.120 ⇒ 00:16:20.574 Robert Tseng: No worries. I mean, we can chat for a bit.
86 00:16:21.180 ⇒ 00:16:21.860 Luke Daque: Yeah.
87 00:16:21.860 ⇒ 00:16:33.399 Robert Tseng: Yeah, I mean, I guess, like this, really just trying to be here and talk about like the work that’s been done with pull parts. I think Utam was just wanting me to catch up and see if I can. I can help out.
88 00:16:35.360 ⇒ 00:16:39.410 Robert Tseng: Yeah. So I mean, I’m sure Amber will talk about some things. But
89 00:16:40.218 ⇒ 00:16:47.560 Robert Tseng: I think you have basically been the one consistent person on this client. So I think.
90 00:16:47.560 ⇒ 00:16:47.960 Luke Daque: Yeah.
91 00:16:47.960 ⇒ 00:16:50.709 Robert Tseng: Probably know, have the most context here.
92 00:16:50.970 ⇒ 00:16:51.850 Luke Daque: Yeah.
93 00:16:51.850 ⇒ 00:16:59.370 Luke Daque: this was like Utah’s 1st client, I believe. And this is like the client that I started working on as well. Basically
94 00:16:59.770 ⇒ 00:17:04.000 Luke Daque: what? I’m already started. So yeah.
95 00:17:04.839 ⇒ 00:17:07.867 Robert Tseng: Do you? Wanna just like catch me up on like
96 00:17:09.710 ⇒ 00:17:15.009 Robert Tseng: you don’t have to tell me the whole timeline, but kind of where? Yeah, where? Where we’re at with things now, like what?
97 00:17:15.260 ⇒ 00:17:19.040 Robert Tseng: What reports? Dashboards do we have for them? Like, you know what?
98 00:17:19.339 ⇒ 00:17:26.710 Robert Tseng: Yeah, like, what? What does your roadmap look like kind of. Maybe if you want to give me like a recap of the things that you’ve been working on the past.
99 00:17:27.109 ⇒ 00:17:30.319 Robert Tseng: I don’t know. Let’s just just wind it back like 2 or 3 months, I guess.
100 00:17:30.780 ⇒ 00:17:35.689 Luke Daque: Yeah. So we haven’t actually been getting any tasks that
101 00:17:36.010 ⇒ 00:17:52.240 Luke Daque: like 2 or 3 months ago. I think it just started going back like around April. That was when ben was already like not so happy with the dashboards that we we had something like that. Let me just share my screen real quick.
102 00:17:54.540 ⇒ 00:17:55.330 Robert Tseng: Okay.
103 00:17:56.560 ⇒ 00:18:00.630 Luke Daque: So we already have, like a couple of dashboards here. There’s a lot actually so.
104 00:18:01.280 ⇒ 00:18:02.879 Luke Daque: But this is the most
105 00:18:03.770 ⇒ 00:18:09.539 Luke Daque: use, the one, the Daily Kpis one, and initially we already gave this out to
106 00:18:09.890 ⇒ 00:18:11.760 Luke Daque: to them to to use.
107 00:18:11.900 ⇒ 00:18:18.710 Luke Daque: But I think on April Ben tried to start work at looking into the dashboard, and then, like he was.
108 00:18:18.930 ⇒ 00:18:22.400 Luke Daque: I’m not so happy with it, because, like he wasn’t able to
109 00:18:22.910 ⇒ 00:18:31.479 Luke Daque: drill down all the the sales metrics to each of the selling platform. This wasn’t there before. This is what I added, like
110 00:18:31.710 ⇒ 00:18:33.370 Luke Daque: this one, basically,
111 00:18:34.800 ⇒ 00:18:43.989 Luke Daque: so yeah. So he he wasn’t happy with that. So they added this breakdown for each selling platform. We also wanted supposedly to be able to break it down by product.
112 00:18:44.240 ⇒ 00:18:49.529 Luke Daque: but that would be a that is like much more challenging because, like
113 00:18:51.340 ⇒ 00:19:00.109 Luke Daque: discounts could be order level, not necessarily product level. So that’s like Mark. We can’t like attribute marketing to a specific product
114 00:19:00.730 ⇒ 00:19:03.600 Luke Daque: right? Something like that. So it’s like.
115 00:19:03.600 ⇒ 00:19:07.770 Robert Tseng: Why can’t we? Why can’t we attribute marketing to specific product.
116 00:19:08.660 ⇒ 00:19:13.000 Luke Daque: Because, like, we wouldn’t know like which
117 00:19:14.332 ⇒ 00:19:27.959 Luke Daque: like, yeah, like, how we we wouldn’t know, like we would know that it’s the marketing would be attributed to shopify, for example. But then we wouldn’t know like what specific product that would be coming from a marketing standpoint
118 00:19:28.070 ⇒ 00:19:30.949 Luke Daque: like like from a campaign, for example, marketing campaign.
119 00:19:32.335 ⇒ 00:19:37.279 Luke Daque: So it’s a bit bit more tricky, I guess, to like be able to link
120 00:19:37.620 ⇒ 00:19:42.429 Luke Daque: a specific marketing campaign tool product, something like that.
121 00:19:42.430 ⇒ 00:19:43.180 Robert Tseng: Okay.
122 00:19:44.630 ⇒ 00:19:44.990 Luke Daque: But.
123 00:19:44.990 ⇒ 00:19:52.079 Robert Tseng: I mean? I asked, because like that, this is that was one of the things we solved for Eden. When we started with them.
124 00:19:52.504 ⇒ 00:19:59.390 Robert Tseng: Yeah, like they didn’t. They weren’t able to do product level attribution before. And that was one of the things I pitched them on. I said.
125 00:19:59.590 ⇒ 00:20:12.899 Robert Tseng: yeah, you only get campaign or platform level attribution right now. Like, we’ll be able to get you product level attribution. So I mean, it took some time to get there. But I I think that you know, if that’s something he’s asked for before then we can do it.
126 00:20:13.380 ⇒ 00:20:22.509 Luke Daque: Yeah, then maybe we can like, yeah, we can do whatever you did in Eden. Apply to pull parts to be able to get like product level attribution stuff like that. Right?
127 00:20:23.230 ⇒ 00:20:24.988 Robert Tseng: Okay, yeah, we we did.
128 00:20:25.460 ⇒ 00:20:34.631 Luke Daque: I think primarily, I think, for April at least, the back and forth communication or tasks that I’ve been doing was like mostly
129 00:20:36.150 ⇒ 00:20:44.490 Luke Daque: What do you call this confirming or verifying that the data is accurate, comparing it to like what
130 00:20:46.077 ⇒ 00:20:51.140 Luke Daque: came. So seeing in shopify, for instance, we did see a couple of like.
131 00:20:51.140 ⇒ 00:20:51.820 Robert Tseng: And.
132 00:20:51.950 ⇒ 00:20:52.550 Luke Daque: Inaccuracy.
133 00:20:52.550 ⇒ 00:20:58.099 Robert Tseng: Am I saying this correctly? Their year to date sales is 2.2 5 million.
134 00:20:58.560 ⇒ 00:21:04.740 Luke Daque: Yes, apparently from January, and that’s for, like all or
135 00:21:05.283 ⇒ 00:21:07.250 Luke Daque: sources, Amazon is the highest.
136 00:21:07.250 ⇒ 00:21:08.100 Robert Tseng: I see.
137 00:21:09.080 ⇒ 00:21:12.079 Robert Tseng: Yes, it’s not very good, so.
138 00:21:13.040 ⇒ 00:21:13.620 Luke Daque: Yeah.
139 00:21:14.167 ⇒ 00:21:19.639 Robert Tseng: Huh! With 33% margins. That’s I don’t know.
140 00:21:20.300 ⇒ 00:21:25.860 Robert Tseng: I almost like Utam. Is this guy? Is this company even gonna grow like, is this
141 00:21:26.440 ⇒ 00:21:28.330 Robert Tseng: dude? Yeah, I don’t think like
142 00:21:29.080 ⇒ 00:21:33.670 Robert Tseng: that’s that’s like 33, 30% margins.
143 00:21:34.850 ⇒ 00:21:37.370 Luke Daque: Yeah, like, last year’s also like 30%.
144 00:21:37.370 ⇒ 00:21:44.869 Robert Tseng: Okay, last last year they basically made 3 million in profit. I don’t know how many people are in their operation.
145 00:21:47.810 ⇒ 00:21:51.510 Robert Tseng: Do. Well, I don’t know. Do we have a sense of how big the organization is?
146 00:21:52.790 ⇒ 00:21:55.380 Luke Daque: I’m not sure maybe Tom can answer that.
147 00:21:55.846 ⇒ 00:22:07.190 Luke Daque: But yeah, there’s a lot going on like shipping is pretty high. Marketing cost is pretty high. So normally, if you think about it, 10 million revenue, like 10%, more than 10% is marketing.
148 00:22:07.590 ⇒ 00:22:12.619 Luke Daque: Slot refunds, you know, cost of goods sold.
149 00:22:12.620 ⇒ 00:22:13.240 Robert Tseng: Yeah.
150 00:22:13.420 ⇒ 00:22:14.810 Luke Daque: Highest. It’s like.
151 00:22:18.950 ⇒ 00:22:20.180 Luke Daque: so yeah.
152 00:22:21.330 ⇒ 00:22:26.299 Robert Tseng: So the total marketing costs walk me through that a bit more. What’s what’s in the what’s in that cost?
153 00:22:28.790 ⇒ 00:22:34.550 Luke Daque: There’s like Ads face Facebook ads.
154 00:22:34.730 ⇒ 00:22:40.049 Luke Daque: and show you here what the marketing looks like we’ve got.
155 00:22:53.120 ⇒ 00:22:56.370 Luke Daque: We’ve got app. We have Amazon ads
156 00:22:56.940 ⇒ 00:23:00.880 Luke Daque: for Amazon related orders. We have Facebook ads, we have
157 00:23:01.420 ⇒ 00:23:04.249 Luke Daque: Google analytics or Google ads. I believe.
158 00:23:05.110 ⇒ 00:23:07.229 Robert Tseng: Where? Where do they spend the most money, you know?
159 00:23:09.290 ⇒ 00:23:10.227 Luke Daque: We have a
160 00:23:14.270 ⇒ 00:23:15.299 Luke Daque: it’s the dashboard.
161 00:23:18.270 ⇒ 00:23:21.870 Luke Daque: So Google looks like it’s the highest.
162 00:23:23.410 ⇒ 00:23:26.360 Luke Daque: Let’s the cost.
163 00:23:28.730 ⇒ 00:23:31.599 Luke Daque: See who work in Facebook. Amazon
164 00:23:31.950 ⇒ 00:23:37.800 Luke Daque: SMS direct mail a few weeks rules that it’s so.
165 00:23:51.470 ⇒ 00:23:53.359 Robert Tseng: Okay, mostly in Google.
166 00:23:53.630 ⇒ 00:23:54.210 Luke Daque: Yep.
167 00:23:54.630 ⇒ 00:23:58.389 Robert Tseng: Are they evaluating, like the efficiency of these channels, like.
168 00:23:59.860 ⇒ 00:24:04.300 Luke Daque: That’s a good question. I actually don’t know the answer.
169 00:24:04.410 ⇒ 00:24:09.669 Luke Daque: And maybe that’s also related to what Utah mentioned earlier, right? Because, like, we are like
170 00:24:10.430 ⇒ 00:24:18.109 Luke Daque: not proactive enough in like looking at all the data that they have. And like, we are like reacting to what they want or something.
171 00:24:19.280 ⇒ 00:24:19.910 Robert Tseng: Sure.
172 00:24:20.160 ⇒ 00:24:20.840 Luke Daque: Yeah.
173 00:24:21.980 ⇒ 00:24:24.600 Robert Tseng: But you have access to all of your their ad platforms.
174 00:24:24.770 ⇒ 00:24:28.229 Robert Tseng: I mean, it seems like you. You already modeled all this data and brought it in.
175 00:24:29.710 ⇒ 00:24:36.210 Luke Daque: Yeah, Utam started it. I I just maintained it. Basically, I think when I started, Utam already had all
176 00:24:36.980 ⇒ 00:24:41.290 Luke Daque: the data modeling for the the marketing stuff mostly.
177 00:24:43.110 ⇒ 00:24:44.150 Robert Tseng: Interesting.
178 00:24:45.920 ⇒ 00:24:46.930 Luke Daque: Yeah.
179 00:24:47.760 ⇒ 00:24:58.743 Robert Tseng: Okay? So we bring into the marketing mart. We have it by platform. Yeah, we have all these ads campaigns, asset things. Okay? Sure. And then
180 00:25:00.960 ⇒ 00:25:11.620 Robert Tseng: the conversion rates are what 1.1% 25. I’m just like reading the metrics, because, like, I think, I understand, I’m just trying to see like what anything that sticks out to me.
181 00:25:12.080 ⇒ 00:25:12.455 Luke Daque: Hmm.
182 00:25:13.130 ⇒ 00:25:14.370 Robert Tseng: So.
183 00:25:15.150 ⇒ 00:25:16.239 Luke Daque: Yeah, you’re, you’re.
184 00:25:20.180 ⇒ 00:25:26.720 Robert Tseng: I mean, less than 1% conversion rate is below average. I would say so. I mean, I wonder if you if you took out.
185 00:25:26.860 ⇒ 00:25:31.059 Robert Tseng: But let’s remove. Let’s isolate by platform. Let’s just look at Google.
186 00:25:32.900 ⇒ 00:25:33.660 Luke Daque: Yeah, that’s very.
187 00:25:33.660 ⇒ 00:25:38.370 Robert Tseng: Point 2, yeah point 2. Or it’s like, it’s yeah. I mean, that’s.
188 00:25:38.370 ⇒ 00:25:40.140 Luke Daque: Point 0 2 lah.
189 00:25:40.140 ⇒ 00:25:44.260 Robert Tseng: 1.3%. Okay, I would assume, Facebook is higher. Not Facebook.
190 00:25:45.610 ⇒ 00:25:46.180 Robert Tseng: Yeah, yeah.
191 00:25:46.180 ⇒ 00:25:46.720 Luke Daque: Point 2.
192 00:25:46.720 ⇒ 00:25:49.670 Robert Tseng: Okay, yeah. And then Amazon.
193 00:25:50.610 ⇒ 00:25:52.329 Luke Daque: It’s really high up to me.
194 00:25:52.740 ⇒ 00:25:58.899 Robert Tseng: Why are they spending so much on Google? Google’s terrible? Okay, interesting.
195 00:25:59.110 ⇒ 00:26:06.570 Robert Tseng: And I mean, I guess the rest is just really small, so you can’t measure conversion on SMS and and direct mail.
196 00:26:06.570 ⇒ 00:26:07.170 Luke Daque: Yeah.
197 00:26:07.170 ⇒ 00:26:12.330 Robert Tseng: Or like, how are you doing attribution for these offline channels of SMS direct mail affiliates.
198 00:26:12.726 ⇒ 00:26:15.900 Luke Daque: Frona, from what I understand, they’re all shopify.
199 00:26:16.890 ⇒ 00:26:22.010 Luke Daque: That’s what they said. So you just attribute it directly to shopify.
200 00:26:23.660 ⇒ 00:26:27.599 Robert Tseng: Oh, okay, because it’s like a QR code or something that links to shopify.
201 00:26:28.970 ⇒ 00:26:33.629 Luke Daque: Probably I’m not. I’m not sure as to the like. The details like how they do that.
202 00:26:34.560 ⇒ 00:26:35.210 Robert Tseng: Okay?
203 00:26:35.360 ⇒ 00:26:40.089 Robert Tseng: And then the main people you’re talking to are Ben and Dan. Are those like the co-founders or.
204 00:26:40.570 ⇒ 00:26:45.070 Luke Daque: Actually not. I’m more talking to Kim, who is like the shopify
205 00:26:45.922 ⇒ 00:26:50.340 Luke Daque: person, and then chuck for the shipments. Part.
206 00:26:52.155 ⇒ 00:26:53.110 Luke Daque: Yeah.
207 00:26:53.860 ⇒ 00:26:57.290 Robert Tseng: Okay, are they only on shopify.
208 00:26:58.727 ⇒ 00:27:04.110 Luke Daque: Kim is only on shopify. And then for Amazon, it was Steven that he selected it.
209 00:27:04.110 ⇒ 00:27:06.809 Robert Tseng: Oh, right! They have a shopify Amazon thing, too.
210 00:27:07.690 ⇒ 00:27:10.450 Uttam Kumaran: They also have like, 3 pls.
211 00:27:10.830 ⇒ 00:27:17.449 Uttam Kumaran: yeah, they also have 3 pls, and they have, like a like a wholesale division
212 00:27:19.000 ⇒ 00:27:28.340 Uttam Kumaran: we’re bringing in. We’re bringing in shopify Amazon and the and the 3 pls for shipping. But yeah, everything sales wise is coming from those 2.
213 00:27:29.130 ⇒ 00:27:31.780 Robert Tseng: But most of their business is off of shopify.
214 00:27:32.680 ⇒ 00:27:33.270 Uttam Kumaran: Yes.
215 00:27:34.530 ⇒ 00:27:50.770 Robert Tseng: Okay. I mean, I was just going through some of these reports with Luke, and just better trying to better understand their business. I mean correct. Here’s here’s my take. You’re talking. Let me know if it if you’re ever right now. So if I’m right or not, so I mean, it’s like a it’s kind of like a lead
216 00:27:51.240 ⇒ 00:27:55.100 Robert Tseng: would wait. Do they have inventory? And they store all that somewhere.
217 00:27:55.370 ⇒ 00:28:04.809 Uttam Kumaran: Yes, so they store their. They have their main warehouse in Long Island, and then they also have 3 pls, like scattered across the country
218 00:28:04.910 ⇒ 00:28:07.326 Uttam Kumaran: where they send inventory to
219 00:28:07.960 ⇒ 00:28:10.089 Uttam Kumaran: So then they can increase the shipping time.
220 00:28:11.900 ⇒ 00:28:15.900 Robert Tseng: Okay, but we don’t have their warehouse data.
221 00:28:16.470 ⇒ 00:28:17.280 Uttam Kumaran: We do.
222 00:28:17.280 ⇒ 00:28:19.259 Uttam Kumaran: We just have 3 pl, oh.
223 00:28:19.561 ⇒ 00:28:21.669 Uttam Kumaran: we do. We? We do have both.
224 00:28:23.630 ⇒ 00:28:27.750 Robert Tseng: Okay, is that fact that that’s factored into cogs already?
225 00:28:31.520 ⇒ 00:28:33.289 Luke Daque: Yeah, cogs.
226 00:28:34.500 ⇒ 00:28:35.489 Amber Lin: Is, that.
227 00:28:35.490 ⇒ 00:28:41.390 Luke Daque: Right like unleashed. I’m not sure like what the exact details are coming from unleashed.
228 00:28:41.390 ⇒ 00:28:54.580 Uttam Kumaran: Yeah. So unleash is their inventory management tool. And that’s everything. Basically that has that has all the costs of their active inventory from their New York like their own warehouse.
229 00:28:54.780 ⇒ 00:29:00.660 Uttam Kumaran: And then, yeah, but we haven’t gone that far deeper into like inventory management.
230 00:29:01.267 ⇒ 00:29:04.679 Uttam Kumaran: Our main cogs, cogs. Calculation now is
231 00:29:04.790 ⇒ 00:29:08.730 Uttam Kumaran: revenue minus the cost to sell discounts
232 00:29:09.190 ⇒ 00:29:18.310 Uttam Kumaran: refunds, shipping we’re not doing anything based on like shelf life, or like how long it takes to sit on the shelf stuff like that.
233 00:29:20.120 ⇒ 00:29:20.800 Robert Tseng: Got it.
234 00:29:21.060 ⇒ 00:29:28.529 Robert Tseng: Okay? Well, I mean, if this is their full marketing budget, and that’s their sales. I mean, their bur is like 9 to 10, which is
235 00:29:28.840 ⇒ 00:29:29.400 Robert Tseng: great.
236 00:29:29.400 ⇒ 00:29:29.890 Uttam Kumaran: What is that?
237 00:29:29.890 ⇒ 00:29:31.570 Robert Tseng: I mean, it seems like like they’re.
238 00:29:31.570 ⇒ 00:29:32.019 Uttam Kumaran: How does that make.
239 00:29:32.020 ⇒ 00:29:33.140 Robert Tseng: Efficiency.
240 00:29:33.140 ⇒ 00:29:33.780 Uttam Kumaran: Oh!
241 00:29:33.780 ⇒ 00:29:36.839 Robert Tseng: And so it’s just like, is this revenue over marketing costs.
242 00:29:37.740 ⇒ 00:29:38.490 Uttam Kumaran: Yeah, I mean.
243 00:29:38.490 ⇒ 00:29:39.060 Robert Tseng: That’s
244 00:29:39.180 ⇒ 00:29:53.809 Robert Tseng: that’s even higher than Eden. Eden’s like 6 to 7, but they are a subscription business, so I think then they can. Ltv, and recurring business is more common. I’m assuming this is more like a you know, one time purchase, or I don’t really know how frequent, not really.
245 00:29:53.810 ⇒ 00:30:09.150 Uttam Kumaran: Great question. So yeah, there, it’s a, it’s typically a, it’s typically a 1 time high ticket, because it’s for a pool. So they have a very low recurring business. Very seasonal, very geographically concentrated
246 00:30:09.870 ⇒ 00:30:10.860 Uttam Kumaran: us.
247 00:30:10.860 ⇒ 00:30:11.610 Robert Tseng: Okay.
248 00:30:13.420 ⇒ 00:30:30.610 Robert Tseng: yeah. Well, so there’s like, I mean, it was a few ideas that come top of my feel like on the marketing side. There’s like some stuff that we could do for them. Seems like they don’t have product level, like attribution for them for. And so I don’t know how often they’re adding new skews or experimenting with that. But
249 00:30:31.081 ⇒ 00:30:33.310 Robert Tseng: yeah, you know, if that that’s
250 00:30:33.410 ⇒ 00:30:38.699 Robert Tseng: we can give them like product level visibility, like profitability, like, you know.
251 00:30:38.700 ⇒ 00:30:42.429 Uttam Kumaran: That’s their number. One thing is product level profitability. Right now.
252 00:30:43.571 ⇒ 00:31:01.169 Uttam Kumaran: In particular, they have a business line with Black and Decker. They have one of the exclusive sort of licensing rights for the black and Decker name on a pool pump. It’s their black and decker variable speed pool pump. Their number one goal is to make that more profitable.
253 00:31:02.583 ⇒ 00:31:26.249 Amber Lin: Luke, if we go to a different dashboard I was, I think I was able to pull the profitability per skew from a different dashboard. And then, last time, a week ago, they asked for us to calculate inventory inventory days remaining so they can prepare for the tariffs. So that was something that was pretty interesting and findings that we had. So I do think we have per skew level
254 00:31:26.460 ⇒ 00:31:31.229 Amber Lin: data. I just forgot which dashboard it is.
255 00:31:31.230 ⇒ 00:31:33.059 Luke Daque: Maybe it’s this one, the all order.
256 00:31:33.503 ⇒ 00:31:34.390 Amber Lin: Product. Name.
257 00:31:35.660 ⇒ 00:31:37.200 Amber Lin: Yeah.
258 00:31:37.200 ⇒ 00:31:39.299 Luke Daque: Yeah, we have like, product skews here.
259 00:31:39.820 ⇒ 00:31:40.350 Luke Daque: Yeah.
260 00:31:40.350 ⇒ 00:31:42.449 Robert Tseng: Yeah, but this is just sales and cogs. Right? It doesn’t actually.
261 00:31:42.450 ⇒ 00:31:44.070 Luke Daque: Yeah, factor in costs.
262 00:31:44.070 ⇒ 00:31:46.099 Uttam Kumaran: That does not factor in marketing. Yeah.
263 00:31:46.100 ⇒ 00:31:47.440 Luke Daque: Yeah, that’s what yeah. Me, too.
264 00:31:47.440 ⇒ 00:31:52.020 Luke Daque: don’t have. At the moment we are. We don’t have attribution, marketing, attribution, purse.
265 00:31:52.320 ⇒ 00:31:52.919 Amber Lin: I see.
266 00:31:52.920 ⇒ 00:31:53.700 Luke Daque: Product.
267 00:31:54.580 ⇒ 00:31:57.909 Amber Lin: Attribution just means like a breakdown right?
268 00:31:57.910 ⇒ 00:32:03.069 Uttam Kumaran: Attribution is that they spent money selling. They spent money marketing that product.
269 00:32:03.310 ⇒ 00:32:04.160 Uttam Kumaran: And then you can
270 00:32:04.160 ⇒ 00:32:14.570 Uttam Kumaran: basically take that out of its profitability equation. Okay, we spent a hundred dollars to market the school pumps, so that when we calculate profitability, take the $100 out of that profit out of revenue.
271 00:32:15.690 ⇒ 00:32:16.005 Luke Daque: Yeah.
272 00:32:17.500 ⇒ 00:32:34.779 Robert Tseng: Yeah, right? Yeah. But it’s like a cost to acquire a new customer. And that’s what the that’s what the marketing cost is. Right now. You have, like, you know, the unit economics of it, which is like how much you sold it for minus, how much it costs to manufacture it, but it doesn’t include how much it costs to acquire that customer.
273 00:32:34.780 ⇒ 00:32:36.059 Amber Lin: I see, I see.
274 00:32:37.020 ⇒ 00:32:42.859 Amber Lin: So we should do more of a customer journey, mapping and sort of cost on
275 00:32:42.980 ⇒ 00:32:46.270 Amber Lin: each step of those, because right now. We have
276 00:32:46.868 ⇒ 00:32:51.659 Amber Lin: our dashboard so sort of attacks everything all at once, and it doesn’t.
277 00:32:52.030 ⇒ 00:32:57.150 Uttam Kumaran: But let’s let’s let’s just I. Yeah, I guess let’s just go back. I I before we cause
278 00:32:57.520 ⇒ 00:33:14.990 Uttam Kumaran: to give you guys a sense like before we jump into anything I I’ve like. Of course, I’ve been working on these guys for a while. I think the number one thing they care about on any given day is like, if they’re selling profitably, they don’t really care about like optimizing, marketing spend. They’re on spending a lot of money.
279 00:33:14.990 ⇒ 00:33:28.219 Uttam Kumaran: So they just want to make sure they don’t spend more money. They’re not really adding new skews. We did a shit ton of work for them to basically optimize their shipping costs, which is a huge win. The number. One thing they care about is just understanding.
280 00:33:28.240 ⇒ 00:33:33.930 Uttam Kumaran: If they’re profitable, why or why not on any given day.
281 00:33:34.700 ⇒ 00:33:40.889 Uttam Kumaran: Everything’s also modeled. Very well. So it’s like, purely the problem right now is just analysis, like.
282 00:33:41.750 ⇒ 00:33:44.099 Uttam Kumaran: I don’t think any of our like.
283 00:33:44.630 ⇒ 00:33:53.709 Uttam Kumaran: I think the data quality was actually pretty close. I think, like we have all the marketing spend there. Everything is modeled. It’s a very seasonal business. We have, like 3 years of historical orders.
284 00:33:53.850 ⇒ 00:33:54.600 Uttam Kumaran: so.
285 00:33:57.300 ⇒ 00:34:01.309 Robert Tseng: Okay, but I mean, as far as profitability, you don’t want to show them like
286 00:34:01.590 ⇒ 00:34:04.149 Robert Tseng: with with marketing costs included.
287 00:34:04.340 ⇒ 00:34:06.940 Uttam Kumaran: No, no, definitely, definitely. But I guess like.
288 00:34:06.940 ⇒ 00:34:07.600 Robert Tseng: Okay.
289 00:34:07.600 ⇒ 00:34:10.649 Uttam Kumaran: Doing like a customer funnel, or like stuff like that.
290 00:34:10.650 ⇒ 00:34:14.980 Robert Tseng: No, yeah, I don’t think that’s necessary. It’s it’s not that complicated. They’re just going on to show shopify
291 00:34:14.980 ⇒ 00:34:16.510 Robert Tseng: buying something, or they’re going. Yeah.
292 00:34:16.510 ⇒ 00:34:16.920 Amber Lin: And.
293 00:34:16.929 ⇒ 00:34:18.609 Robert Tseng: So I don’t think that’s really the main thing.
294 00:34:19.550 ⇒ 00:34:27.929 Robert Tseng: Sounds like you did some. So you did some shipping like operational optimization already. You. You you cut, you know you help them optimize their shipping costs.
295 00:34:28.466 ⇒ 00:34:33.849 Robert Tseng: Refund rate doesn’t look that crazy, either, like it’s not like people are refunding a bunch.
296 00:34:34.070 ⇒ 00:34:49.610 Uttam Kumaran: No, they do, really. They do it well on customer service. Their discounts is where there’s a lot of opportunity to give you a sense of why sometimes people refund or request another product, because the product is bad and they issue a hundred percent discount.
297 00:34:49.920 ⇒ 00:34:53.270 Uttam Kumaran: This is not something I’ve been able to get them to change
298 00:34:53.926 ⇒ 00:35:07.609 Uttam Kumaran: just because it’s like a process change. Basically. What they’ll do is they’ll say, Oh, Sally called and said the product wasn’t working. We’re gonna ship her at a new product. So I’ll I’m gonna go in and just I’m gonna ship her out a new product at a hundred percent discount.
299 00:35:08.880 ⇒ 00:35:11.299 Robert Tseng: That’s like 5% of sales. Yeah.
300 00:35:11.550 ⇒ 00:35:14.410 Uttam Kumaran: Yeah, yeah, it’s it’s it’s brutal like this, that stuff.
301 00:35:15.570 ⇒ 00:35:17.110 Uttam Kumaran: Huge topic of conversation.
302 00:35:18.020 ⇒ 00:35:18.790 Robert Tseng: I see.
303 00:35:20.230 ⇒ 00:35:20.830 Robert Tseng: Okay.
304 00:35:20.830 ⇒ 00:35:22.089 Robert Tseng: So I said, they’re dying.
305 00:35:22.090 ⇒ 00:35:25.400 Robert Tseng: They’re not interested in increasing their marketing budget either.
306 00:35:26.800 ⇒ 00:35:27.420 Uttam Kumaran: No
307 00:35:27.830 ⇒ 00:35:47.480 Uttam Kumaran: like I don’t know. I’ve tried. I like I so a couple of things that I I propose on the marketing side I was like one. Why don’t we start to segment? Pool professionals versus full like normal homeowners and like try to do a segmented campaign? I don’t know, and I don’t know, man like Overall, like we’re trying to get out of that game. So I’m kind of like
308 00:35:48.020 ⇒ 00:35:50.890 Uttam Kumaran: these guys like I, where we work closely with
309 00:35:51.130 ⇒ 00:35:55.760 Uttam Kumaran: with Ben, and Ben’s like not trying to increase bad at all.
310 00:35:56.620 ⇒ 00:35:57.300 Robert Tseng: Okay, do you know?
311 00:35:57.300 ⇒ 00:35:58.650 Robert Tseng: So minutes of your time.
312 00:35:59.459 ⇒ 00:36:06.200 Uttam Kumaran: I think they have like 10 or 12 core people like they have.
313 00:36:06.200 ⇒ 00:36:15.720 Robert Tseng: Because I’m also honestly just looking at their their profitability. Right? They’re 10 million last year, 35%, 30% ish like profitability.
314 00:36:15.840 ⇒ 00:36:23.900 Robert Tseng: you know so if they make, they make 3 million a year split across 10 people like it. It’s not, I mean, I’m sure there seems like.
315 00:36:24.830 ⇒ 00:36:30.299 Uttam Kumaran: It’s a good business, and they don’t have much overhead, except the fact that, like the products.
316 00:36:30.410 ⇒ 00:36:33.710 Uttam Kumaran: are expensive. But they’re one of the few independent
317 00:36:34.360 ⇒ 00:36:51.740 Uttam Kumaran: retailers of pool pumps, and they have this exclusive black and Decker license which really differentiates them in the market and has really like, set them apart. There’s a couple of other big players in like online pool, E-com. And these guys have done it with like, very little
318 00:36:51.880 ⇒ 00:36:52.570 Uttam Kumaran: overhead.
319 00:36:54.060 ⇒ 00:36:57.920 Robert Tseng: Yeah, I mean, they’re like making over 300 k per per person, which is.
320 00:36:57.920 ⇒ 00:36:58.240 Uttam Kumaran: Yeah.
321 00:36:58.240 ⇒ 00:36:58.675 Robert Tseng: Then
322 00:36:59.110 ⇒ 00:36:59.590 Uttam Kumaran: Yeah.
323 00:36:59.590 ⇒ 00:37:04.889 Robert Tseng: I mean, I don’t know how much you want to put like this under there, but like I don’t, I don’t know. Is this their full time job?
324 00:37:05.200 ⇒ 00:37:06.289 Uttam Kumaran: Yeah, yeah, yeah.
325 00:37:06.870 ⇒ 00:37:10.610 Robert Tseng: Okay? Well, I mean, yeah, obviously, tariff impact margin goes down over over.
326 00:37:10.610 ⇒ 00:37:11.130 Uttam Kumaran: Yes.
327 00:37:11.130 ⇒ 00:37:32.663 Robert Tseng: Also like if they’re lock. If Black and Decker is their only strategic partnership, what if they move on from like? There’s there is risk to this business that like, it’s kind of like we need to. Maybe we need to phrase it as like, Hey, you need to keep looking for those expansion opportunities. Because I mean, you’re sitting on a nice like pile of cash right now. But you’re not. It’s not gonna stay this way.
328 00:37:33.300 ⇒ 00:37:42.620 Robert Tseng: necessarily. I mean, sure, maybe it’s a bit more, you know, it’s less volatile than other industries. But like I I wonder if that’s part of the conversation we we should be. Ha! We
329 00:37:42.990 ⇒ 00:37:53.329 Robert Tseng: not just we us telling them that. But like we all all like, that’s that’s what we. That’s how we can see ourselves as like we’re we’re we’re we’re like, anyway, that’s that’s like.
330 00:37:53.330 ⇒ 00:37:53.750 Uttam Kumaran: Yeah.
331 00:37:53.750 ⇒ 00:37:55.390 Robert Tseng: One angle that I see. Yeah.
332 00:37:55.710 ⇒ 00:37:59.410 Uttam Kumaran: So I think on the marketing side. Yeah, like, I don’t know.
333 00:37:59.620 ⇒ 00:38:08.249 Uttam Kumaran: like, I’m not sure what they want to invest. I think on the shipping side. We’ve already done a lot of work. But it’s gonna really hit them.
334 00:38:08.380 ⇒ 00:38:22.440 Uttam Kumaran: Basically. Now, as they’re like shipping rates are just gonna start skyrocketing. We haven’t done any. The problem. The other thing is this is a small subset. They have like 3 businesses. Basically, this is one of them.
335 00:38:22.440 ⇒ 00:38:23.140 Robert Tseng: Okay.
336 00:38:23.440 ⇒ 00:38:51.679 Uttam Kumaran: And they wanted us to get involved in the broader conversation. But like it’s with Dan. And so there’s just there’s just some like scoping problems on this account. Where it’s like they have other businesses. They want to get us involved. But like, that’s from the biggest thing that’s happening is they’re going through a potential M and a right now. They’re they’re basically. And this is where I don’t know how. I’ll ask on Monday how it’s going. But there’s so the biggest group. You’re familiar with buyers, groups.
337 00:38:52.530 ⇒ 00:38:53.200 Robert Tseng: Yeah.
338 00:38:53.580 ⇒ 00:39:17.869 Uttam Kumaran: So their biggest buyers groups in pool. And for context for Ryan amber buyer groups are basically like exactly what they’re called, where a company represents a ton of buyers of pool pumps, and then they go negotiate better deals. For example, if we were to go partner with a ton of like 50 other data consultancies, and then go to Snowflake and say, Hey, I want a better deal. So they’re about to get
339 00:39:17.870 ⇒ 00:39:28.560 Uttam Kumaran: well. I don’t know whether it went through or not, actually. But they were basically about to get bought by Uag United Aqua Group. They’re the number One buyer group for, like
340 00:39:28.590 ⇒ 00:39:37.660 Uttam Kumaran: full supplies. And I think Dan was gonna become some big head or something there. So there’s some potential M and a like that was their major like.
341 00:39:37.760 ⇒ 00:39:40.469 Uttam Kumaran: that’s what they’re like kind of gunning for right now.
342 00:39:41.007 ⇒ 00:39:51.479 Uttam Kumaran: But I also do think that they can save a bunch on the discount thing. And then they like they they should try to find ways to to sort of
343 00:39:51.870 ⇒ 00:39:58.350 Uttam Kumaran: improve their pricing strategy. They have their current pricing is, Ben goes, and just change prices like on gut instinct.
344 00:40:00.150 ⇒ 00:40:06.910 Uttam Kumaran: So there’s no really like strategy towards how they price they look at what’s costing to ship.
345 00:40:07.050 ⇒ 00:40:09.540 Uttam Kumaran: and then they sort of like he makes like a gut call.
346 00:40:10.930 ⇒ 00:40:17.320 Robert Tseng: Okay, did did they ask us to help with the due diligence of that transaction of like? After that.
347 00:40:17.320 ⇒ 00:40:17.740 Uttam Kumaran: We yeah.
348 00:40:17.740 ⇒ 00:40:21.710 Robert Tseng: Goes through. Then then their firms that that new firm’s gonna ask for something.
349 00:40:21.710 ⇒ 00:40:27.820 Uttam Kumaran: No, no, we you, we help them with the due diligence, for sure. Yeah, we were doing that. Yeah, it’s just
350 00:40:27.940 ⇒ 00:40:31.639 Uttam Kumaran: we did that. It was maybe like 3 or 3 or 4 months ago.
351 00:40:34.730 ⇒ 00:40:37.300 Robert Tseng: Yeah, was there any feedback on on that, or like.
352 00:40:37.640 ⇒ 00:40:39.159 Robert Tseng: what did what did we send them.
353 00:40:39.800 ⇒ 00:40:49.779 Uttam Kumaran: We just I mean we they took all of our like sales figures, some of our like customer figures that I mean the the feedback has always been like it’s close to the finish line, but you know I don’t
354 00:40:49.990 ⇒ 00:40:55.719 Uttam Kumaran: to where like I didn’t hear that it went through. And
355 00:40:56.070 ⇒ 00:41:01.800 Uttam Kumaran: I mean. This was like as of like. 2 weeks ago. I didn’t hear that it went through so. But then Dan went on, vacation.
356 00:41:01.800 ⇒ 00:41:03.179 Robert Tseng: I was more curious, like.
357 00:41:03.180 ⇒ 00:41:04.650 Uttam Kumaran: I don’t know. Yeah.
358 00:41:04.890 ⇒ 00:41:09.340 Robert Tseng: What I guess if it’s united like did, if the
359 00:41:10.020 ⇒ 00:41:15.630 Robert Tseng: yeah, if the firm gave like feedback on like, all right, we’ll borrow.
360 00:41:15.630 ⇒ 00:41:17.389 Uttam Kumaran: I don’t. I don’t know. This is a good question.
361 00:41:17.390 ⇒ 00:41:32.119 Robert Tseng: High risk, medium risk, low risk. These are. These are the things that they should look out for. Their their revenue is is I mean, like there, it’s it’s risky that they only have this black vendor, I mean, like, you know, stuff like that will definitely
362 00:41:32.420 ⇒ 00:41:34.660 Robert Tseng: drive more urgency for them to
363 00:41:34.800 ⇒ 00:41:38.430 Robert Tseng: make some changes, or look to solve some things with their business. I’m not sure.
364 00:41:38.430 ⇒ 00:41:39.220 Uttam Kumaran: I did not.
365 00:41:39.220 ⇒ 00:41:39.650 Robert Tseng: Any.
366 00:41:39.650 ⇒ 00:41:42.619 Uttam Kumaran: Yeah, I don’t. They didn’t indicate to me like
367 00:41:43.170 ⇒ 00:41:46.080 Uttam Kumaran: like what the feedback on the deal was.
368 00:41:47.910 ⇒ 00:41:59.000 Robert Tseng: Yeah, I mean, like, we just think about it from like an M and a perspective in the day, in the data, in the deal room like, what are the data things they look at? Right? Obviously, P and L margin. They’ll look at like.
369 00:41:59.150 ⇒ 00:42:03.760 Robert Tseng: I mean, I mean, you have all this data here. So I mean, all the other stuff is pretty much
370 00:42:03.890 ⇒ 00:42:06.269 Robert Tseng: there. But I got, I imagine.
371 00:42:06.270 ⇒ 00:42:15.300 Uttam Kumaran: The biggest thing, I think is that there’s only a few people in online and Ecom pool sales that are vertically integrated. That’s why this is strategic.
372 00:42:16.440 ⇒ 00:42:17.010 Robert Tseng: Yeah.
373 00:42:17.010 ⇒ 00:42:17.700 Uttam Kumaran: Like.
374 00:42:17.850 ⇒ 00:42:22.010 Uttam Kumaran: That’s sort of like what it is. But this is where.
375 00:42:22.010 ⇒ 00:42:25.359 Robert Tseng: Integrated, and their margins are still 30%. And that’s is that good.
376 00:42:25.960 ⇒ 00:42:28.359 Uttam Kumaran: They manufacture the pumps.
377 00:42:29.830 ⇒ 00:42:36.620 Robert Tseng: I just imagine that their margin should be higher if they’re if they’re vertically integrated. But I don’t. I guess I don’t have a benchmark in this industry, so.
378 00:42:36.620 ⇒ 00:42:48.889 Uttam Kumaran: Yeah, I guess I don’t really know, either. I I think, like they’ve kept. They keep overhead pretty low, and shipping and cogs are the number one things I mean, they’re able to manufacture pumps like
379 00:42:49.070 ⇒ 00:42:50.510 Uttam Kumaran: pretty effectively.
380 00:42:51.700 ⇒ 00:42:52.140 Robert Tseng: Yeah.
381 00:42:52.140 ⇒ 00:42:57.870 Uttam Kumaran: And mark it up, and they have great, great customer service. But I also don’t know. I don’t know. I feel like 30% is kind of high.
382 00:43:03.020 ⇒ 00:43:05.430 Robert Tseng: Yeah. Well, I mean, I don’t know. Depends.
383 00:43:05.430 ⇒ 00:43:11.450 Uttam Kumaran: Some pumps, some pumps, some pumps they manufacture at some pumps. I don’t know whether they do. I don’t think they manufacture all the products.
384 00:43:13.010 ⇒ 00:43:13.780 Robert Tseng: Yeah.
385 00:43:14.340 ⇒ 00:43:23.060 Robert Tseng: I mean, these are like food margins for manufactured products. I feel like they should be higher, at least in the home and home and goods industry margins are at least 50%. If
386 00:43:23.310 ⇒ 00:43:23.990 Uttam Kumaran: Hmm.
387 00:43:24.840 ⇒ 00:43:38.520 Robert Tseng: Yeah, like ruggable rugs were, it was selling at 60% margin, I mean, around around 70 and then so is I mean, I think Eden has even higher margin, because they’re just drugs or whatever. So.
388 00:43:38.680 ⇒ 00:43:39.400 Uttam Kumaran: Yeah.
389 00:43:39.400 ⇒ 00:44:01.280 Amber Lin: Yeah, I shared the the one that I did for their inventory days remaining by skew, and there’s also a column that’s gross profit percentages. They vary by a lot. Some of them are if their numbers are correct, they’re like mostly hovering around like 50%, even more than 100%. So
390 00:44:01.630 ⇒ 00:44:07.510 Amber Lin: I know a lot of their products are very profitable. There’s probably a few ones that’s really.
391 00:44:07.510 ⇒ 00:44:10.000 Uttam Kumaran: Yeah, like, brushes are not very profitable.
392 00:44:10.190 ⇒ 00:44:10.570 Amber Lin: Yeah.
393 00:44:10.570 ⇒ 00:44:17.609 Uttam Kumaran: Ladders. It’s really the pumps pumps drive. The most like the pumps are like anywhere from a few 100 to a few 1,000.
394 00:44:18.650 ⇒ 00:44:20.760 Robert Tseng: The accessories is not like.
395 00:44:20.960 ⇒ 00:44:21.750 Uttam Kumaran: Yeah.
396 00:44:22.950 ⇒ 00:44:25.950 Robert Tseng: Trying to sort off of total items sold?
397 00:44:26.650 ⇒ 00:44:29.816 Robert Tseng: I don’t know this morning is not really working for me. But
398 00:44:30.360 ⇒ 00:44:35.321 Robert Tseng: yeah, okay, well, it’s like, Okay, they have a low margin prop like skew that’s driving most of their business.
399 00:44:36.150 ⇒ 00:44:36.590 Uttam Kumaran: Yeah.
400 00:44:36.590 ⇒ 00:44:38.219 Robert Tseng: It’s kind of a problem. Yeah.
401 00:44:39.154 ⇒ 00:44:48.279 Robert Tseng: I mean, yeah, okay, I don’t know, can can I doing this wrong? Total items? Is it because we’re all filtering on the same day. I should just do it.
402 00:44:48.280 ⇒ 00:44:51.690 Amber Lin: Yeah, probably probably because there’s stuff we’re all doing.
403 00:44:52.070 ⇒ 00:44:53.139 Robert Tseng: Yeah, that’s it. My bad.
404 00:44:54.926 ⇒ 00:44:56.709 Robert Tseng: Got it. Okay? So
405 00:44:57.960 ⇒ 00:45:04.249 Robert Tseng: okay, this was what over the past. This is a good view. By the way, let’s look at this.
406 00:45:04.420 ⇒ 00:45:10.349 Uttam Kumaran: They do most of their business in right? Like, right about now, did you? Must.
407 00:45:10.350 ⇒ 00:45:13.849 Uttam Kumaran: Yeah. But right about them out. And then, right when pool closes.
408 00:45:14.240 ⇒ 00:45:23.269 Uttam Kumaran: and then, you know, it’s sort of things open up in different sectors like New York opens up a little bit later than like Texas does like Texas will open up right now.
409 00:45:23.870 ⇒ 00:45:24.490 Uttam Kumaran: because it’s.
410 00:45:24.490 ⇒ 00:45:32.100 Robert Tseng: We’re not. We’re not really like connected to their marketing efforts like, I don’t know if they’re gassing their campaigns right now, like.
411 00:45:32.100 ⇒ 00:45:37.080 Uttam Kumaran: No, they they are, they are like, that’s what they, that’s what they do. But again, these are like.
412 00:45:37.080 ⇒ 00:45:37.530 Robert Tseng: Okay.
413 00:45:37.530 ⇒ 00:45:45.829 Uttam Kumaran: They? They do that I don’t. This is where like they, I always tell them like, I want us working on what’s worth a squeeze like. I don’t think that’s worth the squeeze
414 00:45:46.780 ⇒ 00:45:50.149 Uttam Kumaran: like gassing it a little bit more, doing a little less like how much.
415 00:45:50.380 ⇒ 00:45:54.200 Uttam Kumaran: if they’re not willing to spend more which they’re not like. What can you really do?
416 00:45:56.900 ⇒ 00:45:58.879 Uttam Kumaran: It’s a good question. We can bring it up again.
417 00:46:00.030 ⇒ 00:46:02.470 Robert Tseng: Have they said, why, they’re not willing to spend more.
418 00:46:04.010 ⇒ 00:46:05.510 Uttam Kumaran: No, I I.
419 00:46:05.510 ⇒ 00:46:06.250 Robert Tseng: Okay.
420 00:46:06.430 ⇒ 00:46:06.990 Uttam Kumaran: Yeah.
421 00:46:06.990 ⇒ 00:46:26.163 Robert Tseng: Maybe we just need to do like an exercise. This is more of a consulting thing. Amber could understand. You do like an opportunity size, kind of exercise with them. You show them like, Hey, you’ve penetrated the market only 10. So when, if we have to do some like, I mean, if if they’re traditional banker consultant background. So that’s kind of probably what they need.
422 00:46:26.450 ⇒ 00:46:31.719 Uttam Kumaran: So so the guy, the the guy, Dan the guy. Dan used to run a media agency
423 00:46:31.940 ⇒ 00:46:48.139 Uttam Kumaran: so. But he’s like kind of CEO level, but is very familiar with like, basically how to drive traffic and ads. So it’ll be a good question. The guy Ben is more the guy. Ben is kind of a weird background, like he’s used to be like. He also used to run an agency himself. But now it’s sort of operations.
424 00:46:48.572 ⇒ 00:47:03.550 Uttam Kumaran: They have Kim, who runs marketing, but Kim is an external consultant, I believe, and handles all paid marketing, and then they have Chuck, who runs all who runs the warehouse. They have a couple of other people here and there, but it’s worth, I mean, it’s worth, I would say, with anything we do.
425 00:47:04.460 ⇒ 00:47:05.650 Uttam Kumaran: It’s worth.
426 00:47:05.880 ⇒ 00:47:10.190 Uttam Kumaran: Bring some idea to the table 1st to prompt the question versus asking them
427 00:47:10.410 ⇒ 00:47:14.270 Uttam Kumaran: being like, we should if we if we’re like, yeah, we want to go do this
428 00:47:14.440 ⇒ 00:47:20.509 Uttam Kumaran: sort of market sizing. Then we should just do that. And then just like, open up the conversation. Then, right? Cause
429 00:47:21.140 ⇒ 00:47:25.330 Uttam Kumaran: basically what I tried to get to everybody that’s worked on this account is like.
430 00:47:25.720 ⇒ 00:47:29.969 Uttam Kumaran: Don’t ask the don’t ask the 3rd degree question.
431 00:47:30.410 ⇒ 00:47:34.530 Uttam Kumaran: because this has been a pretty stable business for them, and they are very familiar how to run it.
432 00:47:34.650 ⇒ 00:47:39.090 Uttam Kumaran: So we gotta ask like a tough question, or like a question that may not have considered
433 00:47:40.330 ⇒ 00:47:43.230 Uttam Kumaran: which. That’s a good question, like I’ve never asked them that, like
434 00:47:43.970 ⇒ 00:47:49.070 Uttam Kumaran: the only thing I know is they’ve been going for this acquisition because he talked to me about Uag like
435 00:47:49.550 ⇒ 00:47:50.880 Uttam Kumaran: more than a year ago.
436 00:47:55.920 ⇒ 00:48:18.510 Robert Tseng: Yeah, I was gonna say, okay, so maybe what we what would be helpful is like, yeah, I mean, we need to ask kind of these questions like internally, and then, when we present the question to ask them, we need to already have done some of the preliminary work where we size like. Here’s the question that we think it’s important to ask. This is why we think it matters like, you know, you, you start to back into like you do an opportunity sizing exercise where you’re either saying, like.
437 00:48:18.810 ⇒ 00:48:33.699 Robert Tseng: here we have some questions we want to ask about why you’re not like gassing your marketing budget, and it’s like we feel like you’ve only penetrated the market by 10 if given your your mer, your like, your marketing efficiency. And you know this is this is really good, like, if you.
438 00:48:33.700 ⇒ 00:48:34.210 Uttam Kumaran: Keep going.
439 00:48:34.210 ⇒ 00:48:38.420 Robert Tseng: You can. You can pressure test it. Yeah. And you’ll be able to capture. You know you’ll be able to.
440 00:48:38.420 ⇒ 00:48:38.770 Robert Tseng: Great.
441 00:48:38.770 ⇒ 00:48:48.795 Robert Tseng: You’ll double your market share. It’s stuff like that where it’s it’s less yeah like it. Maybe. Yeah, like, it’ll push them to think about it in in those terms.
442 00:48:49.500 ⇒ 00:48:50.280 Robert Tseng: yeah.
443 00:48:50.630 ⇒ 00:48:56.270 Robert Tseng: And so I think that’s maybe one way we can at least tee up some of the marketing conversations again.
444 00:48:56.754 ⇒ 00:49:03.250 Robert Tseng: But then, yeah, I mean, even from like a product perspective and like finding their product mix like I guess
445 00:49:03.900 ⇒ 00:49:09.740 Robert Tseng: I would. I mean, I I think this is a good starting point. Maybe I just need to spend a little time here trying to understand?
446 00:49:12.620 ⇒ 00:49:18.220 Robert Tseng: Yeah, like, what? Yeah, what’s what’s what’s their current product? Mix like.
447 00:49:18.350 ⇒ 00:49:21.700 Robert Tseng: obviously volume looking at volume margin.
448 00:49:22.170 ⇒ 00:49:22.530 Uttam Kumaran: And they.
449 00:49:22.530 ⇒ 00:49:35.000 Robert Tseng: Any bundling and then, yeah, like trying to basically do like a portfolio like
450 00:49:35.160 ⇒ 00:49:44.170 Robert Tseng: exercise categorization exercise for them where I don’t know if they’re what their product development process looks like. But it’s it’s kind of like.
451 00:49:44.820 ⇒ 00:49:49.619 Robert Tseng: here you do. You do brushes and sorry. I’m not all the products I’m just like, kind of spitballing.
452 00:49:49.620 ⇒ 00:49:50.430 Robert Tseng: Yeah, yeah, yeah.
453 00:49:50.430 ⇒ 00:50:01.240 Robert Tseng: Seeing in front of me, you know, brushes, pumps, and and like pipes or something. And but like, hey? Maybe this is like another product line that you should consider as well. Maybe it’s like
454 00:50:01.350 ⇒ 00:50:04.380 Robert Tseng: covers like pool covers or something, and
455 00:50:05.780 ⇒ 00:50:16.430 Uttam Kumaran: One thing I told him was like you should offer subscription chemicals, and I was like one day I had a conversation. Why you guys should start offering some sort of subscription products or something that’s more recurring. Revenue like, that’s perfect. Yeah.
456 00:50:16.430 ⇒ 00:50:16.760 Robert Tseng: Yeah.
457 00:50:16.760 ⇒ 00:50:17.520 Uttam Kumaran: Exactly right.
458 00:50:18.190 ⇒ 00:50:31.239 Robert Tseng: Okay, yeah. So even with the subscription thing. Yeah, then, we have to actually like layer that into like, okay, well, this is, if of your business right now, like 90% of it is single time purchasers, or whatever. In order to like
459 00:50:31.781 ⇒ 00:50:35.308 Robert Tseng: and your your payback period for these single customer
460 00:50:35.870 ⇒ 00:50:55.580 Robert Tseng: is, I don’t know if it’s I’m assuming. In order to answer that question, you need to have the marketing costs, because I’m assuming for some of these single product customers like, maybe they just come in through some random channel, and all they do is buy a brush and even though it looks profitable on the unit economic side, it’s definitely not profitable from a marketing perspective.
461 00:50:55.660 ⇒ 00:51:07.309 Robert Tseng: And so, yeah, like, I think that’s why we need that that full connection of marketing through unit economic profitability. But then you can. You can tell them like, hey? But then
462 00:51:07.430 ⇒ 00:51:14.259 Robert Tseng: for for that, for that customer comes in through the brush like. Then you know they we if we have a
463 00:51:14.410 ⇒ 00:51:22.810 Robert Tseng: if they, if if we can turn that brush buyer into a brush, plus well, they need something to brush onto the thing. They kind of brush your chemicals.
464 00:51:22.810 ⇒ 00:51:23.660 Uttam Kumaran: Yeah, yeah.
465 00:51:23.660 ⇒ 00:51:33.749 Robert Tseng: Brush plus chemicals buyer. Then then you’re able to expand their Ltv. The payback period is this long? And we think we can convert this many pool pool, brush only by.
466 00:51:33.750 ⇒ 00:51:35.480 Uttam Kumaran: Yeah dude. If they hear that, they’ll go watch.
467 00:51:35.480 ⇒ 00:51:36.140 Robert Tseng: Interesting.
468 00:51:36.140 ⇒ 00:51:36.530 Uttam Kumaran: Yeah.
469 00:51:36.530 ⇒ 00:51:37.290 Robert Tseng: Yeah, like.
470 00:51:37.290 ⇒ 00:51:37.700 Uttam Kumaran: Like.
471 00:51:37.700 ⇒ 00:51:42.620 Robert Tseng: That’s that’s the storytelling that we need. I think it sounds like in order to get them to.
472 00:51:42.850 ⇒ 00:51:53.540 Robert Tseng: I don’t. Yeah, I think they’re just default to no right now. And until they can actually get the the dollar impact. But we need to do that exercise for them. Yeah.
473 00:51:53.540 ⇒ 00:52:04.519 Uttam Kumaran: No, I think I think you’re spot on. I mean one I think like this is where it’s out of my depth, like I’ve done that sort of analysis and sort of like a point analysis, manner, but never as like a
474 00:52:04.670 ⇒ 00:52:08.859 Uttam Kumaran: opportunity assessment or in that manner. So that’s where I think.
475 00:52:08.970 ⇒ 00:52:14.850 Uttam Kumaran: and especially everyone we’ve thrown at this project had, like completely missed the mark.
476 00:52:15.425 ⇒ 00:52:28.690 Uttam Kumaran: And so certainly we need to come to the table with that they are super receptive to like our feedback, though, like they will be, they will consider everything we say. They’re just not gonna be open to like if we? Just
477 00:52:29.010 ⇒ 00:52:33.429 Uttam Kumaran: if the next person comes on. It’s like, hey? I noticed that most of your sales are in May. It’s like
478 00:52:33.980 ⇒ 00:52:48.170 Uttam Kumaran: they’re literally looking at me like yo, what the like, what the f like, you know. So it’s like you’re right in that, even in just a short conversation. You’ve gone basically farther than any of the like 8 analysts that have touched this.
479 00:52:48.380 ⇒ 00:52:53.070 Uttam Kumaran: you know, so I totally agree, is like, if we come to the table with that.
480 00:52:53.560 ⇒ 00:52:59.699 Uttam Kumaran: they’re, I think they’re receptive, like they’re not tough to work with. They have high expectations.
481 00:53:01.400 ⇒ 00:53:02.020 Robert Tseng: Yeah.
482 00:53:02.400 ⇒ 00:53:18.210 Robert Tseng: So I mean, I don’t know if they’re willing to necessarily say, I think we kind of have to just put the leg work in upfront to do it. So I would say we could even have a sprint to like. Answer some of these questions and get put something in front of them and assume that whether they pay for it or not is like kind of it’s a wash.
483 00:53:18.620 ⇒ 00:53:24.609 Uttam Kumaran: No, they’ll pay. I mean, they’ll they’re they’re basically they’re gonna pay for like right now. They’re gonna pay for like 10 HA week
484 00:53:24.790 ⇒ 00:53:26.920 Uttam Kumaran: ends up being like 6 KA month.
485 00:53:27.040 ⇒ 00:53:29.199 Uttam Kumaran: They’re gonna pay for that. We’re good on that.
486 00:53:29.715 ⇒ 00:53:38.650 Uttam Kumaran: I think the biggest thing is like we need them to buy in and like, be like cool. We want to put money set before I can ever say cool. It’s gonna start moving up
487 00:53:38.980 ⇒ 00:53:41.780 Uttam Kumaran: to 8 K. Or 10 k, like, you know.
488 00:53:41.780 ⇒ 00:53:42.670 Robert Tseng: Totally. Yeah.
489 00:53:42.670 ⇒ 00:53:45.199 Uttam Kumaran: Otherwise, this is gonna it’s gonna continue to shrink.
490 00:53:46.000 ⇒ 00:54:02.850 Robert Tseng: Yeah, if they already committed to that, then let’s just like over deliver in this next week or this next month. I guess. I think we can. You know we can add we can. We could put some of. We can put a few of these types of analyses in front of them. And I I think that that’ll I think, that could move that could move the needle.
491 00:54:06.580 ⇒ 00:54:11.790 Uttam Kumaran: I’m with it. I mean, this is where, like, I think I’m here is just like a you could just consider me like
492 00:54:12.332 ⇒ 00:54:19.980 Uttam Kumaran: representative of of them, and like, I’ll tell you what I’ve tried. But I I am totally, for, like
493 00:54:20.690 ⇒ 00:54:30.550 Uttam Kumaran: we need some polish like, just like rapid fire thing like, why do you guys do this? We noticed this especially using the heavy metrics. Yeah, I’m totally a fan.
494 00:54:32.050 ⇒ 00:54:48.859 Robert Tseng: Okay, yeah. I mean, I’ll try to just like, come up with some stuff that’s like using what we already have. And then I’ll tee it up in like a few different ways. One is like, I think these are the questions that we could go and answer with data we have today. Maybe others that like low, like less confidence, like, we don’t have the marketing
495 00:54:49.000 ⇒ 00:55:06.670 Robert Tseng: spend by product yet. So maybe we can’t answer this type of question, but it’s kind of like we should put that in front of them. Still, too, it’s like, Hey, we can go. Answer this if you let us go and build. You know the next phase out, or whatever so we kind of need to phase phase this out. But I think, yeah, we just we need to spend some time just
496 00:55:07.270 ⇒ 00:55:14.269 Robert Tseng: building up a backlog of those questions. So I’m happy to do that. I think that’s basically what I did at ruggable like, I
497 00:55:14.500 ⇒ 00:55:16.460 Robert Tseng: build out some stuff. And just
498 00:55:16.610 ⇒ 00:55:36.390 Robert Tseng: I had to basically talk to our Cpo like all the time. And just tell him like, this is what my team’s gonna work on. I think these are the important questions to answer. I think this is how much opportunity there is, and he’d pick the ones that are the bigger opportunities. And he’d be like, Yeah, go answer that question. So I think this is like, totally like up my alley.
499 00:55:36.816 ⇒ 00:55:38.079 Robert Tseng: Yeah, I think again.
500 00:55:38.080 ⇒ 00:55:54.780 Uttam Kumaran: I don’t know what this exercise is called. But yes, and I think we’re lacking this on multiple clients, by the way, so whatever this is which again, it’s not my world we gotta do for like ABC. And we, you know, I don’t know. I just feel like this is a great opportunity.
501 00:55:55.200 ⇒ 00:55:59.629 Uttam Kumaran: But yeah, it’s like totally your in your your. It’s like, right in your field of view.
502 00:56:00.460 ⇒ 00:56:01.420 Amber Lin: Yeah.
503 00:56:01.420 ⇒ 00:56:03.240 Robert Tseng: Yeah, I mean, yeah, go ahead.
504 00:56:03.240 ⇒ 00:56:13.200 Amber Lin: We can start to settle at least a few core questions to ask and make this start some documentation on like a workshop formats.
505 00:56:13.825 ⇒ 00:56:30.900 Amber Lin: I don’t know if, Robert, you have time, you can start it off, and I can flesh it out with my knowledge. My! And with chat Gpt so to sort of have that format, and then we can run experiment with pool parts. Since this, this is the most urgent, and then we should definitely apply this to other clients as well.
506 00:56:32.170 ⇒ 00:56:32.990 Robert Tseng: Okay.
507 00:56:34.790 ⇒ 00:56:47.330 Robert Tseng: yeah, I mean, I kind of doing something similar for Eden already, like, so yeah, I mean, I think I will just do a similar exercise. So I for for here and then, like, yeah, we’ll we can. We can.
508 00:56:47.330 ⇒ 00:56:52.029 Uttam Kumaran: All of our clients. Kind of graduate. Yeah, all of our clients kind of graduate to this point.
509 00:56:53.370 ⇒ 00:56:59.590 Uttam Kumaran: but this is something that is the sexiest part of data that we, I feel like are are always like
510 00:56:59.690 ⇒ 00:57:29.489 Uttam Kumaran: missing. I mean, for me, all of the clients I’ve worked on. They’ve been missing this just because that’s not like this is not my world. And so we haven’t prioritized it. But, for example, urban stems is going to have a hundred of these. And it’s gonna be, it’s a really, really complicated, really great analysis problem. But this is where almost it’s like, once we have the data. And once we have stuff modeled, we should kick off parallel work streams for this type of proactive analysis, not like
511 00:57:29.630 ⇒ 00:57:44.060 Uttam Kumaran: sort of like reactive as they ask us questions, and this is great because these are core outcomes. These are fast like, we can get end to end on some questions and answers within a week, and it goes right to the top.
512 00:57:44.160 ⇒ 00:58:08.370 Uttam Kumaran: and then we can ask for more budget right like it’s hard to say how long a pipeline is going to take. It’s hard to say how long the next model is going to take, but this initiative buys us time to do that, and sort of says, like, Hey, we’re gunning for this goal. We agreed on this goal. We like, let’s go do that. This is my favorite part of data. I just like I was always like, I’m always applying this stuff for this versus, like, yeah, I would love for us to
513 00:58:08.860 ⇒ 00:58:13.730 Uttam Kumaran: to rip these. And yeah, sort of facilitate this process.
514 00:58:15.910 ⇒ 00:58:19.939 Robert Tseng: Okay, are they like deck or brief people, or like, how do they typically, do you just or do.
515 00:58:19.940 ⇒ 00:58:20.780 Uttam Kumaran: I would do that.
516 00:58:20.780 ⇒ 00:58:21.100 Robert Tseng: Maybe it’s.
517 00:58:21.100 ⇒ 00:58:24.199 Uttam Kumaran: They’re not gonna read anything. I would just do the deck. Yeah.
518 00:58:24.200 ⇒ 00:58:24.770 Robert Tseng: Okay.
519 00:58:26.880 ⇒ 00:58:29.840 Uttam Kumaran: I would do Deck. They’re they’re like new. They’re like New Yorkers.
520 00:58:30.150 ⇒ 00:58:34.509 Uttam Kumaran: They’re nice, but they’re just like, you know, they’re like totally to me straight. So.
521 00:58:36.810 ⇒ 00:58:43.590 Robert Tseng: Oh, yeah, give me give me the weekend. I’m gonna I’m gonna start to put something together here.
522 00:58:43.940 ⇒ 00:58:55.489 Robert Tseng: Yeah, I mean, I imagine, like. I mean, we’ll we can review some of the questions and then we’ll bubble it up to them like, I I guess. And you guys, when when you guys talking to them. So I can kind of work backwards from the time.
523 00:58:55.490 ⇒ 00:58:56.950 Uttam Kumaran: Tuesday morning.
524 00:58:56.950 ⇒ 00:58:57.929 Amber Lin: Good morning!
525 00:58:57.930 ⇒ 00:59:01.630 Robert Tseng: Okay, okay, yeah. I’ll definitely have some stuff ready.
526 00:59:01.980 ⇒ 00:59:02.630 Uttam Kumaran: Okay.
527 00:59:02.630 ⇒ 00:59:04.149 Robert Tseng: No, no, I’ll I can do it.
528 00:59:04.550 ⇒ 00:59:09.930 Uttam Kumaran: Do it, and then and then again, that’ll just be the 1st 4 am. I want to take it as a good opportunity to like.
529 00:59:10.100 ⇒ 00:59:14.289 Uttam Kumaran: bring you and amber more into the conversation. And
530 00:59:14.610 ⇒ 00:59:20.960 Uttam Kumaran: yeah, like, these guys are good, they’ll they’ll tell us what they need. They also have this potential need for like AI help.
531 00:59:21.120 ⇒ 00:59:27.750 Uttam Kumaran: So like there’s a couple of things for them to re kick off here. And I just wanna you know, see what we can make happen. So.
532 00:59:30.820 ⇒ 00:59:31.540 Robert Tseng: Nice.
533 00:59:34.380 ⇒ 00:59:45.160 Robert Tseng: Okay, yeah. If there are any other like Comms and stuff that I should catch up on just to like, I feel like I I’ll make sure I have access to the core reports this
534 00:59:46.760 ⇒ 00:59:53.099 Uttam Kumaran: No, these guys are super. These guys are very like, yeah, we can. We can make sure you’re in slack. But these guys.
535 00:59:53.100 ⇒ 01:00:02.545 Robert Tseng: Or I’m just like anything else that I can catch up on resource wise so like this one’s helpful. And then I don’t think I’ve logged into the real for
536 01:00:03.350 ⇒ 01:00:04.090 Robert Tseng: or cold part.
537 01:00:04.090 ⇒ 01:00:08.450 Uttam Kumaran: Yeah, real real is gonna be real is gonna be basically it. And then.
538 01:00:08.450 ⇒ 01:00:08.820 Robert Tseng: Okay.
539 01:00:09.112 ⇒ 01:00:13.800 Uttam Kumaran: May you’re in your you’ll have access. You have access to the repo already, so.
540 01:00:13.800 ⇒ 01:00:14.390 Robert Tseng: Yeah.
541 01:00:16.090 ⇒ 01:00:23.185 Uttam Kumaran: that’s really it. I mean, I can you, my, you can log in with my shopify. It’s on one password.
542 01:00:24.830 ⇒ 01:00:28.479 Uttam Kumaran: yeah. I mean we’ve all the data is sort of there for you. So
543 01:00:28.750 ⇒ 01:00:36.320 Uttam Kumaran: it’s all pretty clean. We haven’t touched a lot of it in a while in a while meaning it’s just pipelines are working. I don’t know, Luke like. Is there anything else.
544 01:00:37.860 ⇒ 01:00:39.200 Luke Daque: I guess just the
545 01:00:39.930 ⇒ 01:00:45.799 Luke Daque: ship station, I mean the split order issue. That’s like different, though. But that’s also like
546 01:00:46.506 ⇒ 01:00:52.700 Luke Daque: concerning because, like, it could potentially result to multiple shipments on their end.
547 01:00:52.980 ⇒ 01:00:55.399 Luke Daque: But yeah, it looks like it’s a ship station.
548 01:00:59.000 ⇒ 01:01:14.550 Luke Daque: like, I like, I already create sent another email to their support because it was like working before. And we didn’t touch anything in terms of like automation rules. And like, split order rules. So yeah, like, it just stopped working. Only like it built for some reason. So.
549 01:01:15.340 ⇒ 01:01:21.279 Uttam Kumaran: Yeah, I know that’s 1 item. But apart from that, I think everything else is fine, like regarding this like analysis, initiative.
550 01:01:22.090 ⇒ 01:01:26.717 Luke Daque: Yeah, okay, I I believe that’s what we really were lacking.
551 01:01:27.070 ⇒ 01:01:27.400 Uttam Kumaran: Okay.
552 01:01:27.400 ⇒ 01:01:30.859 Luke Daque: For couple parts. The analysis part. So, yeah.
553 01:01:32.810 ⇒ 01:01:37.487 Robert Tseng: Okay, I guess, like, once we come up with the questions, we can decide later. But
554 01:01:37.930 ⇒ 01:01:44.110 Robert Tseng: I guess we’re gonna need people to go and actually execute on them. So I
555 01:01:44.790 ⇒ 01:01:46.940 Robert Tseng: I don’t know who’s who’s who we’re.
556 01:01:46.940 ⇒ 01:01:48.440 Uttam Kumaran: I mean, Annie has bandwidth.
557 01:01:49.490 ⇒ 01:01:50.339 Uttam Kumaran: I could also
558 01:01:50.340 ⇒ 01:01:55.789 Uttam Kumaran: go. If it’s digging up. If it’s writing SQL. Queries and doing it like I can totally do that.
559 01:01:56.640 ⇒ 01:01:57.250 Robert Tseng: Okay.
560 01:01:58.020 ⇒ 01:01:58.960 Uttam Kumaran: Like it’ll be, it’ll.
561 01:01:58.960 ⇒ 01:01:59.350 Robert Tseng: Okay, well, we’ll.
562 01:01:59.350 ⇒ 01:01:59.790 Uttam Kumaran: Really, really.
563 01:01:59.790 ⇒ 01:02:03.089 Robert Tseng: We’ll we’ll we’ll plan it out, and then we’ll we’ll still have the work later.
564 01:02:03.390 ⇒ 01:02:09.499 Uttam Kumaran: Yeah. And then also, we’ve done this sort of planning on like questions. These guys.
565 01:02:09.710 ⇒ 01:02:13.249 Uttam Kumaran: amber, where’s the stuff that Pius wrote like? Is that useful at all?
566 01:02:14.250 ⇒ 01:02:32.749 Amber Lin: Those are more so for future products, projects we can take is more about, okay, what kind of forecasting do we want to do? Do we want to pause? These current projects which we are paused? So it doesn’t really relate. Much is about work that we done like work.
567 01:02:32.750 ⇒ 01:02:36.850 Uttam Kumaran: Maybe just send it to maybe just send it in the Channel again to rob.
568 01:02:36.850 ⇒ 01:02:37.390 Amber Lin: We’re just.
569 01:02:37.390 ⇒ 01:02:40.817 Uttam Kumaran: Case, it’s like helps with anything.
570 01:02:41.370 ⇒ 01:02:48.600 Amber Lin: Totally. I can also start something. And then, Robert, you can fill it in.
571 01:02:49.250 ⇒ 01:02:50.410 Amber Lin: Yeah, these.
572 01:02:50.410 ⇒ 01:02:54.380 Uttam Kumaran: Robert for context, these guys are like these guys like like flashy stuff.
573 01:02:54.500 ⇒ 01:02:55.610 Uttam Kumaran: Also.
574 01:02:56.060 ⇒ 01:03:06.859 Uttam Kumaran: So even the stuff you said about marketing efficiency ratio. And that’s the stuff they’re going to really eat up, and they’re more visual. But they run the business on like gut instinct for quite a while.
575 01:03:07.280 ⇒ 01:03:10.869 Uttam Kumaran: So they also have some like truths. They know that like.
576 01:03:11.070 ⇒ 01:03:19.999 Uttam Kumaran: they’re like, Yeah, we can go get all the data to like prove. But like, we know, people buy in May. So like they just have a couple of things like that where you’re like.
577 01:03:20.190 ⇒ 01:03:22.929 Uttam Kumaran: okay, we just need to kind of skip the basics a little bit.
578 01:03:23.060 ⇒ 01:03:24.999 Uttam Kumaran: So that’s that’s really it.
579 01:03:26.000 ⇒ 01:03:26.590 Robert Tseng: Okay.
580 01:03:32.290 ⇒ 01:03:35.849 Amber Lin: Well, I’ll send some stuff in our Ballpark Channel.
581 01:03:37.130 ⇒ 01:03:40.539 Uttam Kumaran: Yeah, I’m really excited. I think if we if we’re able to do this for these guys, then
582 01:03:41.290 ⇒ 01:03:44.410 Uttam Kumaran: this is really like the coolest part of all this is like actually finding these.
583 01:03:44.410 ⇒ 01:03:50.140 Robert Tseng: Yeah, no, I think it’s like the data is in a good place, like, I think we should be able to answer some of these questions. So.
584 01:03:50.140 ⇒ 01:03:56.530 Uttam Kumaran: Yeah, I think I think one good outcome here also is just like, how do we do this across clients like, does this need to be like
585 01:03:56.840 ⇒ 01:04:01.229 Uttam Kumaran: outside of our typical stand up like, how do we make this more of a ritual?
586 01:04:02.240 ⇒ 01:04:23.579 Amber Lin: I was thinking, I was thinking about this as we talked. I feel like we are really able to do the full spiel for consulting because we are building, helping build that data, pipeline infrastructure. And then we’re building dashboards. We’re really there’s opportunity for the last part of analysis and actually doing consulting work.
587 01:04:23.740 ⇒ 01:04:25.860 Amber Lin: Yes, streaming the data. I think this.
588 01:04:25.860 ⇒ 01:04:27.020 Uttam Kumaran: 100%.
589 01:04:27.490 ⇒ 01:04:30.029 Amber Lin: Part of our like whole lives.
590 01:04:30.030 ⇒ 01:04:35.870 Uttam Kumaran: No, it is. It is. That’s the thing like I feel like it is. I feel like we
591 01:04:35.980 ⇒ 01:04:53.130 Uttam Kumaran: we we’re trying to get them to make more money right? And so it’s not. It’s everything in the kitchen sink is like we wanna have, we? Wanna do. We want to do all of it, and that’s what gets us the big scope. And then lucky thing is that we have great engineering meaning like, we engineer these models and like there is maintenance. But.
592 01:04:53.130 ⇒ 01:04:53.470 Amber Lin: So.
593 01:04:53.470 ⇒ 01:05:00.640 Uttam Kumaran: Most of the hours should shift towards this sort of proactive analysis and pool parts is a great version of that where we.
594 01:05:00.640 ⇒ 01:05:01.480 Amber Lin: So.
595 01:05:01.480 ⇒ 01:05:06.210 Uttam Kumaran: We crushed all these really early on, you know, and we’ve sort of been sitting on this data for a while.
596 01:05:08.180 ⇒ 01:05:12.139 Luke Daque: Yeah, we need to document this somewhere. Make it a standard. For across all clients like.
597 01:05:12.140 ⇒ 01:05:15.459 Luke Daque: yeah, Robert, I sent these 2 documents in our.
598 01:05:15.670 ⇒ 01:05:17.399 Uttam Kumaran: Slack channels.
599 01:05:17.980 ⇒ 01:05:18.660 Robert Tseng: Okay.
600 01:05:19.340 ⇒ 01:05:20.130 Amber Lin: And
601 01:05:23.810 ⇒ 01:05:26.059 Amber Lin: let me know if there’s anything I can help with.
602 01:05:27.120 ⇒ 01:05:39.790 Robert Tseng: Yeah, no, I’ll be. Yeah. I’m just gonna be doing client stuff the rest of the afternoon. I have this and something to follow up on meeting. But yeah, I’ll definitely be touching on it over the weekend and get something to you by Monday before your Tuesday call.
603 01:05:43.190 ⇒ 01:05:45.100 Amber Lin: Sounds good. Thanks. Everyone.
604 01:05:45.610 ⇒ 01:05:46.320 Uttam Kumaran: Thank you.
605 01:05:46.320 ⇒ 01:05:46.740 Robert Tseng: Thanks. Everyone.
606 01:05:46.740 ⇒ 01:05:48.010 Luke Daque: Thanks, bye, bye.
607 01:05:48.440 ⇒ 01:05:49.540 Amber Lin: 80. Bye-bye.