Meeting Title: ABC Discovery Sync Date: 2026-01-06 Meeting participants: Uttam Kumaran, Amber Lin, Clarence Stone
WEBVTT
1 00:00:08.660 ⇒ 00:00:10.000 Amber Lin: Hello.
2 00:00:15.970 ⇒ 00:00:16.990 Uttam Kumaran: Hello.
3 00:00:17.570 ⇒ 00:00:19.780 Uttam Kumaran: Alright, this meeting keeps getting pushed and pushed.
4 00:00:19.970 ⇒ 00:00:29.600 Amber Lin: I know, I talked to Robert today just to get some direction on where to go based on the sales data we have. Yeah.
5 00:00:30.220 ⇒ 00:00:32.739 Amber Lin: So I’m thinking we can do a…
6 00:00:33.060 ⇒ 00:00:37.889 Amber Lin: Compare the branches and compare their services to see if…
7 00:00:38.010 ⇒ 00:00:45.190 Amber Lin: A particular service is doing very well in a given market, so we can make some recommendations there.
8 00:00:45.310 ⇒ 00:01:00.199 Amber Lin: Another thing Robert says, like, we can see if there’s any data to support Zoran’s work with the GA. I don’t think there’s any channel marketing spend-related data in… in… from Julie, so…
9 00:01:00.310 ⇒ 00:01:05.069 Amber Lin: If there’s any more data that comes in, I can do that.
10 00:01:05.510 ⇒ 00:01:14.259 Amber Lin: And lastly, another option is to look at the P&L of the different services, but I’m still trying to find the cost.
11 00:01:14.590 ⇒ 00:01:21.970 Amber Lin: of the services, I’m only able to find budget, but I’ll need to compare that and find the equivalent.
12 00:01:21.970 ⇒ 00:01:25.589 Uttam Kumaran: I think I got… I think we got the cost data from…
13 00:01:25.790 ⇒ 00:01:28.860 Uttam Kumaran: From them. Did you see that in a spreadsheet somewhere?
14 00:01:29.380 ⇒ 00:01:34.569 Amber Lin: It’s not called cost, it could have been the budget.
15 00:01:34.570 ⇒ 00:01:37.230 Uttam Kumaran: Like, do you see residential pricing guidelines? I thought that.
16 00:01:37.230 ⇒ 00:01:40.539 Amber Lin: Oh, that one? Okay, let me, let me check.
17 00:01:41.160 ⇒ 00:01:43.100 Uttam Kumaran: This is all pricing.
18 00:01:44.180 ⇒ 00:01:51.950 Amber Lin: Yeah, pricing’s not necessarily… The cost of,
19 00:01:52.890 ⇒ 00:01:56.770 Amber Lin: Because the pricing is just probably… We’ll sell.
20 00:01:57.040 ⇒ 00:01:59.580 Amber Lin: So that’s just the sales price.
21 00:02:00.910 ⇒ 00:02:04.560 Uttam Kumaran: And then I also… oh, well, I did get the 2025 budget.
22 00:02:05.150 ⇒ 00:02:05.640 Amber Lin: Mmm.
23 00:02:05.640 ⇒ 00:02:07.580 Uttam Kumaran: I can… I can give that to you.
24 00:02:08.580 ⇒ 00:02:09.350 Amber Lin: Yeah, I’m.
25 00:02:09.350 ⇒ 00:02:10.799 Uttam Kumaran: Let me put that in the drive.
26 00:02:10.800 ⇒ 00:02:27.410 Amber Lin: Sure, sounds good, because I’m looking at their previous year’s budgets. That budget is mostly per service line, it’s not really, say, marketing budget. I don’t know what’s included. The line items are very…
27 00:02:27.610 ⇒ 00:02:34.540 Amber Lin: high level. So, for example, This is the… This is the 2023 budget.
28 00:02:35.260 ⇒ 00:02:36.830 Amber Lin: And it does have…
29 00:02:37.080 ⇒ 00:02:46.639 Amber Lin: the actuals for previous years, and then 2023, but there’s… I wasn’t able to find any, say, marketing-related, channel-specific.
30 00:02:46.640 ⇒ 00:02:50.370 Uttam Kumaran: So I do… so I do have the… I do have a marketing budget.
31 00:02:50.490 ⇒ 00:02:56.480 Amber Lin: Okay, cool. For you that I’ll… I’m gonna… I’m gonna move into the, sounds good, okay.
32 00:02:56.480 ⇒ 00:02:57.599 Uttam Kumaran: Can I just do it.
33 00:02:57.600 ⇒ 00:02:58.320 Amber Lin: more.
34 00:02:59.000 ⇒ 00:03:01.609 Uttam Kumaran: Yeah, let me move that now, so you have that.
35 00:03:03.600 ⇒ 00:03:06.840 Amber Lin: Do you know if the budget is their spend?
36 00:03:07.420 ⇒ 00:03:09.740 Uttam Kumaran: Yes. Okay, cool.
37 00:03:09.880 ⇒ 00:03:13.289 Uttam Kumaran: But they don’t… they’re not… they’re not doing ROI associated with it.
38 00:03:13.860 ⇒ 00:03:14.790 Amber Lin: Yeah.
39 00:03:15.000 ⇒ 00:03:18.689 Amber Lin: I’ll… I’ll go find the sales numbers.
40 00:03:18.850 ⇒ 00:03:26.589 Amber Lin: So, that will… that will give some interesting insight. It just is separated by year, and, like, I would like to put that together.
41 00:03:27.900 ⇒ 00:03:32.640 Uttam Kumaran: Okay, so I threw… I threw those into the… into the Discovery Workstream folder, so…
42 00:03:32.640 ⇒ 00:03:33.190 Amber Lin: Cool.
43 00:03:33.190 ⇒ 00:03:39.320 Uttam Kumaran: Residential pricing guidelines, master marketing budget, and the 2025 budget, which is there.
44 00:03:39.550 ⇒ 00:03:44.819 Uttam Kumaran: like, FP&A budget. So that’s, like, what Matt… this is, like, Matt’s budget.
45 00:03:45.260 ⇒ 00:03:46.659 Amber Lin: I see.
46 00:03:46.660 ⇒ 00:03:48.490 Uttam Kumaran: So it has revenue in here.
47 00:03:48.700 ⇒ 00:03:50.700 Uttam Kumaran: Oh, okay.
48 00:04:01.640 ⇒ 00:04:03.890 Uttam Kumaran: Wait, requested access to which one?
49 00:04:04.160 ⇒ 00:04:08.550 Amber Lin: The master must… Master marketing budget.
50 00:04:09.060 ⇒ 00:04:11.080 Uttam Kumaran: Okay, let me jump out to you.
51 00:04:17.300 ⇒ 00:04:19.380 Uttam Kumaran: Okay, actually, it’ll go to… well…
52 00:04:20.190 ⇒ 00:04:21.390 Amber Lin: I can use the ABC.
53 00:04:21.399 ⇒ 00:04:22.809 Uttam Kumaran: I’m just gonna download it as an… I’m.
54 00:04:22.810 ⇒ 00:04:23.250 Amber Lin: Okay.
55 00:04:23.250 ⇒ 00:04:24.419 Uttam Kumaran: as an Excel.
56 00:04:24.970 ⇒ 00:04:25.940 Amber Lin: Sounds good.
57 00:04:33.020 ⇒ 00:04:34.860 Uttam Kumaran: Okay, I threw that into the folder, too.
58 00:04:35.270 ⇒ 00:04:35.910 Amber Lin: Cool.
59 00:04:36.280 ⇒ 00:04:40.969 Amber Lin: Were we able to get the GA data? Is Zorin already looking at it?
60 00:04:41.300 ⇒ 00:04:47.800 Uttam Kumaran: Yes, so… Let me… my pings are on, if you can join.
61 00:04:48.250 ⇒ 00:04:49.990 Uttam Kumaran: We do have the GA data.
62 00:04:50.300 ⇒ 00:04:53.080 Amber Lin: Were you able to log in and see that?
63 00:04:53.490 ⇒ 00:04:57.040 Amber Lin: Oh, no, I haven’t tried. I was going through all the different Excels.
64 00:04:57.040 ⇒ 00:04:59.139 Uttam Kumaran: Maybe give… maybe just give it a shot?
65 00:04:59.140 ⇒ 00:04:59.860 Amber Lin: Okay.
66 00:05:02.670 ⇒ 00:05:05.740 Amber Lin: Yeah, I can help him with analysis if he needs.
67 00:05:05.880 ⇒ 00:05:06.370 Amber Lin: Cool.
68 00:05:06.370 ⇒ 00:05:07.160 Uttam Kumaran: Yeah.
69 00:05:07.340 ⇒ 00:05:07.749 Amber Lin: to the one.
70 00:05:07.750 ⇒ 00:05:10.510 Uttam Kumaran: Yeah, see if you can log in using the brain forges.
71 00:05:47.640 ⇒ 00:05:48.200 Amber Lin: Mmm…
72 00:05:49.290 ⇒ 00:05:52.179 Uttam Kumaran: Oh, so maybe I only have… do I only have it?
73 00:05:52.990 ⇒ 00:05:55.709 Amber Lin: Is it? I don’t see a no one pass yet.
74 00:05:55.710 ⇒ 00:05:57.359 Uttam Kumaran: Okay, hold on, let me see.
75 00:05:57.360 ⇒ 00:06:01.110 Amber Lin: I see Dream and Evolve. I don’t see G.
76 00:06:09.440 ⇒ 00:06:15.670 Uttam Kumaran: Okay, well, I have it under my account, well…
77 00:06:15.890 ⇒ 00:06:19.459 Uttam Kumaran: Tell me, I can run whatever exports you need, I guess.
78 00:06:19.460 ⇒ 00:06:34.150 Amber Lin: I have not been in GA, I wouldn’t be able to tell you. You can also just export what you see, and I can get started, and then I’ll have extra questions, and then I can sync with Zoran. How’s he gonna work in there if it’s on your account?
79 00:06:34.150 ⇒ 00:06:38.910 Uttam Kumaran: Well, that’s what I mean, like, I’ve… I’m a… I’m…
80 00:06:39.030 ⇒ 00:06:47.310 Uttam Kumaran: I tried to ask him that… he should have… someone should have told me that they had… I mean, I pinged Zoran 3 weeks ago, being like, checks DA, he said okay, but.
81 00:06:47.310 ⇒ 00:06:48.610 Amber Lin: Mmm, I see.
82 00:06:48.610 ⇒ 00:06:49.729 Uttam Kumaran: Yeah. I don’t know.
83 00:06:49.860 ⇒ 00:06:55.099 Uttam Kumaran: I basically need him to do something here, so I can tell what I can give him some guidance.
84 00:06:57.500 ⇒ 00:07:03.690 Uttam Kumaran: That’s why even I threw everything at you, because it’ll… I just need you to see what we have, and then we can start forming, like, the directions we need to go.
85 00:07:03.690 ⇒ 00:07:04.470 Amber Lin: Yeah.
86 00:07:05.700 ⇒ 00:07:08.760 Uttam Kumaran: Let me, yeah.
87 00:07:18.420 ⇒ 00:07:21.080 Clarence Stone: Hey, Tom, I’m on now. Hey.
88 00:07:21.330 ⇒ 00:07:34.429 Clarence Stone: I, I told Zoran about the things that, you know, we covered in the meeting that we might be interested in looking into in GA. He said he was gonna start working on it tomorrow, didn’t even mention that he didn’t have access.
89 00:07:35.420 ⇒ 00:07:40.880 Uttam Kumaran: Yeah, he hasn’t touched shit, and also, like, that’s certainly not enough. Like, I want to talk to him.
90 00:07:40.900 ⇒ 00:07:42.010 Clarence Stone: Does that have, like…
91 00:07:42.870 ⇒ 00:07:44.920 Uttam Kumaran: Tom’s got, like.
92 00:07:44.920 ⇒ 00:07:48.239 Clarence Stone: I know things, yeah, I was just like, here’s a starting point.
93 00:07:48.240 ⇒ 00:07:55.140 Uttam Kumaran: Yeah, let me, yeah, let me… let me message him to see if he’s still free.
94 00:08:14.200 ⇒ 00:08:15.050 Uttam Kumaran: And then…
95 00:08:15.050 ⇒ 00:08:16.999 Amber Lin: The sizing you did was really cool.
96 00:08:18.070 ⇒ 00:08:18.840 Clarence Stone: What’s that?
97 00:08:18.840 ⇒ 00:08:21.050 Amber Lin: The marker sizing you did was really cool.
98 00:08:21.050 ⇒ 00:08:21.930 Clarence Stone: Oh, thank you!
99 00:08:21.930 ⇒ 00:08:23.569 Amber Lin: Listen to the presentation.
100 00:08:23.980 ⇒ 00:08:31.520 Clarence Stone: No, yeah, I’m glad you liked it. If you ever have to make one of those, just let me know. I can, you know, talk you through how I put those together.
101 00:08:31.740 ⇒ 00:08:32.539 Amber Lin: Awesome.
102 00:08:33.480 ⇒ 00:08:35.140 Amber Lin: Utam, you were saying…
103 00:08:35.840 ⇒ 00:08:42.890 Uttam Kumaran: Yeah, are we… did we start a Notion or anything for this yet? I don’t think I did, I don’t know if you started writing anything anymore, but…
104 00:08:43.799 ⇒ 00:08:45.070 Uttam Kumaran: You have not. I’m going to.
105 00:08:45.410 ⇒ 00:08:47.460 Clarence Stone: Nope, we can start one now.
106 00:08:47.750 ⇒ 00:08:51.229 Uttam Kumaran: So let me, I’m just gonna go ahead and create,
107 00:08:52.700 ⇒ 00:09:00.169 Uttam Kumaran: I’m just gonna create a blanket one for, like, they say, this whole discovery work stream. Well, actually, there is a discovery project plan.
108 00:09:00.860 ⇒ 00:09:01.430 Amber Lin: Yeah.
109 00:09:01.430 ⇒ 00:09:04.299 Uttam Kumaran: Will you have a discovery analysis outline one?
110 00:09:04.300 ⇒ 00:09:14.359 Amber Lin: I do, but that was based on assuming that I would get all the data. I don’t know the data would look like this, so… Okay, okay. Might as well work from what we have.
111 00:09:15.510 ⇒ 00:09:17.750 Uttam Kumaran: Okay, so I’m gonna move your…
112 00:09:19.760 ⇒ 00:09:24.430 Uttam Kumaran: Yeah, I’m gonna move your doc on… under the bottom of this.
113 00:09:24.930 ⇒ 00:09:25.560 Amber Lin: Cool.
114 00:09:26.700 ⇒ 00:09:31.119 Uttam Kumaran: And then… Basically, I’m still just… I’m still kind of thinking about, like.
115 00:09:31.300 ⇒ 00:09:33.959 Uttam Kumaran: as a CSO, how I’m taking notes on
116 00:09:34.130 ⇒ 00:09:40.270 Uttam Kumaran: all clients, like, what I’m probably gonna end up doing is, like, keep a running Doc.
117 00:09:40.780 ⇒ 00:09:43.970 Uttam Kumaran: Like, a running, like, internal meeting doc.
118 00:09:44.400 ⇒ 00:09:49.849 Uttam Kumaran: And just kind of keep notes for each, like, work stream I’m managing, but for now, this is okay. So what I’m gonna do is…
119 00:09:50.040 ⇒ 00:09:59.129 Uttam Kumaran: I’m gonna move this discovery plan… Tune in here… Mox cannot be moved, though.
120 00:10:07.540 ⇒ 00:10:08.290 Uttam Kumaran: Oh.
121 00:10:08.780 ⇒ 00:10:10.690 Uttam Kumaran: So, I’m aware of this.
122 00:10:17.780 ⇒ 00:10:27.930 Uttam Kumaran: And… oops And 6, 265… The discovery analysis outline is here.
123 00:10:28.570 ⇒ 00:10:34.259 Uttam Kumaran: So, you guys wanna check… this out.
124 00:10:34.710 ⇒ 00:10:37.260 Uttam Kumaran: I’m gonna send this in the Slack.
125 00:10:50.670 ⇒ 00:10:52.440 Uttam Kumaran: Okay, so I sent in Slack.
126 00:10:54.510 ⇒ 00:11:00.609 Uttam Kumaran: So I’m just gonna… let’s just brain dump a couple directions, and then… I mean, I just mainly need…
127 00:11:00.780 ⇒ 00:11:02.920 Uttam Kumaran: Amber, you and Zoran to start.
128 00:11:03.160 ⇒ 00:11:07.979 Uttam Kumaran: just think about it a little bit, and then we’ll start to craft, because I’ve been thinking about it for a week, so…
129 00:11:08.230 ⇒ 00:11:12.999 Uttam Kumaran: Yeah, we could just put a bunch of stuff here. So I’m gonna put, like,
130 00:11:14.690 ⇒ 00:11:18.849 Uttam Kumaran: Like, sort of logistics items, so… requested…
131 00:11:19.270 ⇒ 00:11:25.600 Uttam Kumaran: GA access to Brainforge at GoAntEater.com.
132 00:11:26.080 ⇒ 00:11:29.239 Uttam Kumaran: For now, if you need exports.
133 00:11:53.580 ⇒ 00:11:58.360 Uttam Kumaran: Yeah, I don’t… I don’t know how much COGS analysis we need to do, necessarily.
134 00:11:58.720 ⇒ 00:12:00.339 Uttam Kumaran: Most of what they’re…
135 00:12:00.500 ⇒ 00:12:06.889 Uttam Kumaran: gonna be focused on, like… so, to kind of give you the high level, I don’t think there’s gonna be much optimism…
136 00:12:07.160 ⇒ 00:12:14.870 Uttam Kumaran: 2… One earpod just died. I’m gonna give you, I don’t think there’s gonna be…
137 00:12:15.550 ⇒ 00:12:22.320 Uttam Kumaran: For us to do, like, on profit, and on COGS. Instead, it’s really gonna be about…
138 00:12:22.870 ⇒ 00:12:24.670 Uttam Kumaran: Capturing missed revenue.
139 00:12:24.910 ⇒ 00:12:25.580 Uttam Kumaran: So…
140 00:12:26.030 ⇒ 00:12:31.729 Uttam Kumaran: I would honestly, at this point, say, like, don’t worry about getting the cost of the service data, because…
141 00:12:32.040 ⇒ 00:12:36.589 Uttam Kumaran: I don’t think it’s gonna be as relevant as, like, where can we grow the revenue.
142 00:12:36.860 ⇒ 00:12:37.910 Amber Lin: So…
143 00:12:38.070 ⇒ 00:12:43.559 Uttam Kumaran: Mainly, what we’re trying to understand is, like, growth trends across services, growth trends across…
144 00:12:44.000 ⇒ 00:12:46.049 Uttam Kumaran: So, like, the couple of, like, main…
145 00:12:46.520 ⇒ 00:12:52.060 Uttam Kumaran: Yeah, like, they have a couple main dimensions, right? So if I was to say dimensions, they have, like… oops.
146 00:12:53.470 ⇒ 00:12:55.980 Amber Lin: market services…
147 00:12:56.190 ⇒ 00:13:02.350 Uttam Kumaran: Yeah, like, so Dimensions is… Basically, like, what they call branches, which is markets.
148 00:13:02.960 ⇒ 00:13:04.230 Uttam Kumaran: services.
149 00:13:05.660 ⇒ 00:13:13.960 Uttam Kumaran: The other dimension is, like, source, like, customer, source, Customer demo.
150 00:13:16.370 ⇒ 00:13:20.600 Uttam Kumaran: Right? So, like, this is, like, where they came from.
151 00:13:22.240 ⇒ 00:13:29.380 Uttam Kumaran: This also can… they also basically have, like, the, yeah, services or combo of services.
152 00:13:33.780 ⇒ 00:13:35.560 Uttam Kumaran: What else?
153 00:13:40.110 ⇒ 00:13:50.840 Amber Lin: Mmm… my customer lifetime? Because I… there’s… There’s always the… Cancellations, or…
154 00:13:51.150 ⇒ 00:13:52.709 Uttam Kumaran: Yeah, yeah, yeah, it’s like, yeah.
155 00:13:52.710 ⇒ 00:13:54.880 Amber Lin: Like, lifetime value, maybe.
156 00:13:55.100 ⇒ 00:13:57.879 Uttam Kumaran: Yeah, so, like, we also have definitely their,
157 00:13:59.920 ⇒ 00:14:10.230 Uttam Kumaran: So I was thinking, yeah, like, cancellation… Info… survey info… reward data…
158 00:14:19.300 ⇒ 00:14:22.890 Uttam Kumaran: Yeah, I think this is, like, probably a good amount of it, you know?
159 00:14:23.070 ⇒ 00:14:27.480 Uttam Kumaran: So, like, if I was to think about, like, high-level…
160 00:14:28.290 ⇒ 00:14:35.650 Uttam Kumaran: Like, on the analytics side, basically, we have awareness, to conversion.
161 00:14:36.160 ⇒ 00:14:37.860 Uttam Kumaran: site or phone.
162 00:14:39.020 ⇒ 00:14:42.300 Uttam Kumaran: to service… delivered.
163 00:14:43.440 ⇒ 00:14:50.930 Uttam Kumaran: to… expansion, retention… churn, right?
164 00:14:51.590 ⇒ 00:14:57.340 Uttam Kumaran: Our focus is, we don’t care… we’re not gonna care much about the service delivery piece for this phase.
165 00:14:58.720 ⇒ 00:15:04.009 Uttam Kumaran: So we care about… Where… how are they… how are people finding out about ABC?
166 00:15:04.160 ⇒ 00:15:06.060 Uttam Kumaran: Where are they coming from?
167 00:15:06.330 ⇒ 00:15:10.000 Uttam Kumaran: How are they converting? How or how are they not converting?
168 00:15:10.780 ⇒ 00:15:13.559 Uttam Kumaran: And then, how are we expanding or keeping them?
169 00:15:15.580 ⇒ 00:15:19.840 Uttam Kumaran: So my hope is that Zoran kind of can figure out the…
170 00:15:20.320 ⇒ 00:15:23.320 Uttam Kumaran: The piece of the awareness to convert, like.
171 00:15:23.920 ⇒ 00:15:26.949 Uttam Kumaran: Basically, like, Zoran has to figure out this.
172 00:15:29.620 ⇒ 00:15:34.590 Uttam Kumaran: You’re figuring out, like, this.
173 00:15:34.940 ⇒ 00:15:40.710 Uttam Kumaran: And… this, right?
174 00:15:42.660 ⇒ 00:15:43.780 Amber Lin: Cool.
175 00:15:44.110 ⇒ 00:15:52.799 Amber Lin: For the conversions, do you have their events data, how they go through that funnel, and where people drop off? Are we able to see that at all?
176 00:15:52.800 ⇒ 00:15:54.390 Uttam Kumaran: All the GA stuff, yeah, all GA stuff.
177 00:15:54.390 ⇒ 00:15:56.340 Amber Lin: Oh, okay.
178 00:15:57.910 ⇒ 00:15:59.040 Uttam Kumaran: Oh, yeah, yeah.
179 00:15:59.560 ⇒ 00:16:02.499 Amber Lin: Cool. Okay, let me write the goodness for a second.
180 00:16:27.260 ⇒ 00:16:35.149 Amber Lin: Okay. Are we able to access their, say, customer profiles of how long they’ve been with the company, or how they.
181 00:16:35.150 ⇒ 00:16:35.690 Uttam Kumaran: Yes.
182 00:16:35.690 ⇒ 00:16:36.150 Amber Lin: Overall.
183 00:16:36.150 ⇒ 00:16:39.719 Uttam Kumaran: We… so… so we will have all of that data coming from Evolve.
184 00:16:40.010 ⇒ 00:16:41.310 Amber Lin: Okay, okay.
185 00:16:41.510 ⇒ 00:16:46.589 Amber Lin: So that’ll include when the customer started, where they came from, what they bought.
186 00:16:46.590 ⇒ 00:16:52.569 Uttam Kumaran: where they live, what their name is, whatever, how much they spend. Yeah, everything.
187 00:16:53.280 ⇒ 00:16:54.160 Amber Lin: Okay.
188 00:16:56.550 ⇒ 00:17:02.680 Amber Lin: Alright, I think this is at, like, a customer level. Are we helping them look at more of a…
189 00:17:02.940 ⇒ 00:17:18.940 Amber Lin: at a higher level of services, Marcus, so where is… where is it growing? Is anything overlooked? Are we helping them look at that, or is that already done internally? Like, service growth rates, market growth rates?
190 00:17:21.020 ⇒ 00:17:22.469 Uttam Kumaran: One more time?
191 00:17:23.730 ⇒ 00:17:35.300 Amber Lin: like, this funnel, you wrote down, awareness to churn or retention, it’s at the customer level, right? I was thinking, are we going to do anything at the market or service line level of.
192 00:17:35.300 ⇒ 00:17:35.740 Uttam Kumaran: Yes.
193 00:17:35.740 ⇒ 00:17:36.360 Amber Lin: So that’s a great question.
194 00:17:36.360 ⇒ 00:17:36.870 Uttam Kumaran: Question.
195 00:17:36.870 ⇒ 00:17:37.780 Amber Lin: Okay.
196 00:17:38.180 ⇒ 00:17:47.600 Uttam Kumaran: Yeah, so we will need to also look at service churn and, like, market churn. The thing to consider about market churn is people move.
197 00:17:49.220 ⇒ 00:17:51.950 Uttam Kumaran: You may see churn within a market, but no net churn.
198 00:17:52.520 ⇒ 00:17:52.940 Amber Lin: Hmm…
199 00:17:52.940 ⇒ 00:17:59.919 Uttam Kumaran: Similarly, people may churn One service, but still remain a customer.
200 00:18:01.310 ⇒ 00:18:03.840 Uttam Kumaran: These are all things that they’re not looking at.
201 00:18:03.920 ⇒ 00:18:07.870 Amber Lin: So, to give you a sense of… I’m also gonna add something, like, what are we missing?
202 00:18:07.870 ⇒ 00:18:11.649 Uttam Kumaran: Like, what is the current… State of reporting.
203 00:18:12.970 ⇒ 00:18:16.719 Uttam Kumaran: One, they have a weekly exec meeting.
204 00:18:18.060 ⇒ 00:18:25.279 Uttam Kumaran: Julie… prints out one of her sales reports.
205 00:18:25.620 ⇒ 00:18:32.360 Uttam Kumaran: They are looking at, all they’re looking at is, market.
206 00:18:32.950 ⇒ 00:18:36.050 Uttam Kumaran: Level, inflow, and outflow.
207 00:18:36.600 ⇒ 00:18:42.079 Uttam Kumaran: service level, Level, inflow, and outflow.
208 00:18:42.490 ⇒ 00:18:45.819 Uttam Kumaran: outflow, cancellation reason.
209 00:18:46.810 ⇒ 00:18:49.480 Uttam Kumaran: That’s all they’re looking at. They don’t look at anything else.
210 00:18:51.050 ⇒ 00:18:52.250 Amber Lin: Gotcha, okay.
211 00:18:52.250 ⇒ 00:18:58.860 Uttam Kumaran: So they’re not looking at, bundling, they’re not looking at acceleration, they’re not looking at,
212 00:18:59.470 ⇒ 00:19:02.069 Uttam Kumaran: like, marketing, like.
213 00:19:02.190 ⇒ 00:19:09.129 Uttam Kumaran: where… where are people coming from? Like, they’re not looking at ROI, like, marketing ROAS, anything. So that’s… this is all they’re doing.
214 00:19:09.800 ⇒ 00:19:16.700 Uttam Kumaran: And then, annually, they… They set marketing budgets.
215 00:19:18.440 ⇒ 00:19:21.760 Uttam Kumaran: they set… FP&A targets?
216 00:19:22.760 ⇒ 00:19:27.220 Uttam Kumaran: Marketing budgets, Are basically 6% of revenue.
217 00:19:27.330 ⇒ 00:19:35.120 Uttam Kumaran: spread by CMO. FP&A targets, they just… you’ll find out, but I think they just set fixed growth targets.
218 00:19:35.250 ⇒ 00:19:36.889 Uttam Kumaran: Like, they don’t… there’s no nuance.
219 00:19:43.220 ⇒ 00:19:44.450 Amber Lin: I see.
220 00:19:49.310 ⇒ 00:19:53.179 Amber Lin: Okay, I think the market level, since they already look at it.
221 00:19:53.590 ⇒ 00:19:58.719 Amber Lin: Generally, we can do it after we do the customer level one, because I…
222 00:19:58.930 ⇒ 00:20:06.420 Amber Lin: it’s been a while, I do want to wow them with some analysis. So, I would say we start with the customer journey.
223 00:20:06.600 ⇒ 00:20:08.480 Uttam Kumaran: There, and then…
224 00:20:08.540 ⇒ 00:20:22.859 Amber Lin: Because looking at bundling, looking at customers moving across service lines might require more complex data, and maybe some modeling, because I don’t know how their data is integrated. It’s a lot of Excel sheets that’s not linked at all, so…
225 00:20:22.980 ⇒ 00:20:23.520 Uttam Kumaran: Yes.
226 00:20:23.520 ⇒ 00:20:25.350 Amber Lin: That will be harder to do.
227 00:20:35.530 ⇒ 00:20:37.690 Amber Lin: Mmm… okay.
228 00:20:50.590 ⇒ 00:20:51.460 Amber Lin: Okay.
229 00:21:03.930 ⇒ 00:21:08.560 Amber Lin: What is, can you talk more about the goals by end of January?
230 00:21:10.140 ⇒ 00:21:16.209 Uttam Kumaran: Yes, I would… I think we just have to try to present as many,
231 00:21:17.860 ⇒ 00:21:25.380 Uttam Kumaran: As many of these, like, As many of these decks as possible.
232 00:21:26.480 ⇒ 00:21:29.280 Uttam Kumaran: So, I don’t know, like, Clarence, what do you think, like.
233 00:21:29.760 ⇒ 00:21:32.159 Uttam Kumaran: Yeah, I’m kind of curious, like, how you think.
234 00:21:33.040 ⇒ 00:21:36.619 Clarence Stone: So we’re asking about, like, what the end state.
235 00:21:36.960 ⇒ 00:21:39.210 Uttam Kumaran: Deliverable after 4 weeks is?
236 00:21:39.580 ⇒ 00:21:40.350 Uttam Kumaran: Yes.
237 00:21:41.090 ⇒ 00:21:47.189 Uttam Kumaran: Well, I guess, like, yeah, even, like, incrementally, if we can start to do some of the presentations that we did, I think would be great.
238 00:21:47.540 ⇒ 00:21:59.260 Clarence Stone: Yeah. So let’s work backwards. In my mind, you, Tom, like, I think for this, we definitely need to go into this with recommendations for work that you can absolutely do.
239 00:21:59.480 ⇒ 00:22:00.670 Clarence Stone: Right, so…
240 00:22:00.780 ⇒ 00:22:14.359 Clarence Stone: Like, if we back into what we kind of look into data with that, you know, understanding of what we can sell, it would help us figure out, you know, what we can deliver in the intermediary.
241 00:22:15.940 ⇒ 00:22:34.720 Clarence Stone: How do I explain this? Well, for example, like, one of the things they definitely need is a better platform to manage everything that’s happening, from scheduling to assignments to the people in the field, right? We’re not gonna create a new CMS for them, so, like, that’s not gonna be something that we can look into, that we should spend time looking into.
242 00:22:35.580 ⇒ 00:22:45.749 Clarence Stone: Yeah. Makes sense. Like, right? Like, so, like, I think coming up with a list of all the services and products that we can sell to them and actually deliver on.
243 00:22:46.130 ⇒ 00:22:52.369 Clarence Stone: And then saying, okay, do they actually need any of these things based on analytics and research that we do?
244 00:22:58.950 ⇒ 00:22:59.780 Clarence Stone: Because I, I mean…
245 00:23:00.380 ⇒ 00:23:05.710 Clarence Stone: Basically, they need a whole entire frickin’ data team, but, like, we don’t have 7 people to give them.
246 00:23:05.710 ⇒ 00:23:15.939 Uttam Kumaran: I almost wonder if, like, I should… if I should start working backwards, and… and Amber and Zoran work forwards. Yep, exactly. Meaning, I’m gonna work on the final deck.
247 00:23:17.190 ⇒ 00:23:18.870 Uttam Kumaran: like, now?
248 00:23:19.130 ⇒ 00:23:27.209 Uttam Kumaran: and build towards that, while Amber and Zoran help me flesh out the details, because I already know some proposals that I want to put in front of them.
249 00:23:29.160 ⇒ 00:23:45.499 Clarence Stone: Yeah, and that’s why the data recon at this point, like, can be pretty general, right? We definitely need to understand ClickFunnels. We definitely need to understand demographics. We also need to understand, like, service distribution and, ROI of each of those services. Like, for example, like.
250 00:23:45.650 ⇒ 00:24:01.800 Clarence Stone: I don’t… I wouldn’t just look into how many people are buying into certain services, because maybe, like, pool cleaning actually makes a lot more money than, you know, something else, right? So, it’s not like we should have equal distribution of people in each of these services as well.
251 00:24:01.800 ⇒ 00:24:19.150 Uttam Kumaran: Well, this is the other thing, they just don’t, like… no one in that… so, I have the first meeting recorded, nobody in that meeting could answer me basic questions, and so I’m gonna list… let’s just go ahead and list some of these questions, because I want to make it… I don’t… I almost want to make it painfully obvious, like.
252 00:24:19.260 ⇒ 00:24:25.980 Uttam Kumaran: Like, what kind of questions can they not answer that…
253 00:24:27.000 ⇒ 00:24:34.900 Uttam Kumaran: Right? What is the dist of revenue across services? What is the dist
254 00:24:35.290 ⇒ 00:24:41.690 Uttam Kumaran: of customers across services, right? Where are customers coming from?
255 00:24:42.260 ⇒ 00:24:48.180 Uttam Kumaran: How long does a customer spend with ABC? How much
256 00:24:48.320 ⇒ 00:24:50.629 Uttam Kumaran: does a customer spend with ABC?
257 00:24:50.770 ⇒ 00:24:54.520 Uttam Kumaran: like, where is ABC Growth?
258 00:24:54.520 ⇒ 00:24:57.340 Clarence Stone: What’s the average LTV? What’s ROAS?
259 00:24:57.340 ⇒ 00:25:01.440 Uttam Kumaran: Yeah. Like, where is ABC shrinkage coming from?
260 00:25:02.640 ⇒ 00:25:04.350 Uttam Kumaran: Where? What?
261 00:25:04.750 ⇒ 00:25:09.660 Uttam Kumaran: marketing channels have the highest ROAS.
262 00:25:09.950 ⇒ 00:25:16.070 Uttam Kumaran: Right? What organic channels drive the most Traffic.
263 00:25:17.530 ⇒ 00:25:26.329 Clarence Stone: I mean, you, Tom, to me, I think that those are great starting baseline questions that we have to answer regardless of whatever services we recommend, so, like, it’s perfect for.
264 00:25:26.330 ⇒ 00:25:26.990 Uttam Kumaran: Exactly.
265 00:25:26.990 ⇒ 00:25:36.890 Clarence Stone: And Zoran to start with. And then on the flip side, we should talk about, like, what are we going to be able to sell? Because I have some concepts of that, too, because I want you to be able to lock in this client for, like, 2 years.
266 00:25:37.190 ⇒ 00:25:44.399 Uttam Kumaran: Yeah, exactly. So me and you will work on that. Yeah. Those we… we… those I already have, probably, we already have 50%.
267 00:25:44.900 ⇒ 00:25:49.550 Uttam Kumaran: Probably by the time Amber and Zorong get to 50% of their analysis, we’ll be able to finish our end.
268 00:25:49.950 ⇒ 00:26:09.600 Clarence Stone: Yeah, exactly. And you know what my gut instinct is? Like, the actual ROI of a service is a floating number because of, like, whether or not somebody’s gonna go overtime, how soon it was, scheduled, or route distances that occur, like, that changed the profitability of a service.
269 00:26:09.600 ⇒ 00:26:16.869 Clarence Stone: Right? Like, but we can’t even look into those levels of complexities until we get that baseline information.
270 00:26:19.270 ⇒ 00:26:22.760 Clarence Stone: There’s so much money they have left sitting on the table that they don’t even know about.
271 00:26:35.090 ⇒ 00:26:37.619 Uttam Kumaran: That’s super helpful, actually, to think about it that way.
272 00:26:40.370 ⇒ 00:26:45.219 Clarence Stone: Right, so I think, you know, from our side, we go, okay, number one, like.
273 00:26:46.080 ⇒ 00:26:51.810 Clarence Stone: Baseline, you know, digital analytics data package that gives you all of these insights that are actually, like.
274 00:26:52.130 ⇒ 00:27:04.600 Clarence Stone: pretty industry standard at this point. Like, it’s… that’s gonna be a no-shit, absolute buy, right? But then we say, like, now that we have that baseline, look at all of these other things that we can do for you. And that’s what we gotta figure out.
275 00:27:05.450 ⇒ 00:27:10.740 Uttam Kumaran: Yeah, so at the bottom of this, maybe that’s what we start filling out, is, like, menu options, which is, like.
276 00:27:11.800 ⇒ 00:27:17.340 Uttam Kumaran: Yeah, it’s basically, like, digital analytics reporting suite, right?
277 00:27:17.810 ⇒ 00:27:18.260 Clarence Stone: Yeah.
278 00:27:18.260 ⇒ 00:27:25.110 Uttam Kumaran: it’s sales, and Customer Analytics Reporting Suite.
279 00:27:25.280 ⇒ 00:27:40.559 Uttam Kumaran: It’s… the, like… Monthly… and quarterly… business reviews, it’s… ad hoc analysis.
280 00:27:40.880 ⇒ 00:27:48.230 Uttam Kumaran: Right, so we’ll continue to fill that out. Yeah. But I think, Amber, these are the types of things they can’t do at the moment. They can’t even answer some of these things.
281 00:27:51.980 ⇒ 00:27:59.020 Uttam Kumaran: So ultimately, like, I… like, ultimately, I think we will most likely get to the end of January and not…
282 00:27:59.150 ⇒ 00:28:07.300 Uttam Kumaran: and not do… not end up… have done all the analysis we want to do, but it will be enough for me and Clarence to go sell the follow-on work.
283 00:28:10.500 ⇒ 00:28:11.250 Uttam Kumaran: Yeah.
284 00:28:12.210 ⇒ 00:28:24.589 Uttam Kumaran: But fundamentally, like, what… we need to… we need to end up with a better understanding of their sales, their customer, their purchasing journey, retention, and churn than they are, and we’ll…
285 00:28:24.840 ⇒ 00:28:27.030 Uttam Kumaran: That’s it, and it’ll be great.
286 00:28:31.550 ⇒ 00:28:42.720 Amber Lin: Sounds good. I think the ones we have here that I cannot answer are quite high level, and should I… based on the data I’ve seen, it should be able to answer most of the… most… most of them.
287 00:28:42.870 ⇒ 00:28:50.060 Amber Lin: On the customer journey part is where it will need more… data wrangling.
288 00:28:50.560 ⇒ 00:28:54.830 Uttam Kumaran: Because I can’t just use one sheet, I have to combine their…
289 00:28:55.250 ⇒ 00:29:00.959 Amber Lin: we’re going to evolve, so I’ll probably have a better answer once we see the Evolve data.
290 00:29:11.130 ⇒ 00:29:15.400 Uttam Kumaran: So… I’ve just… I’m emailing back and forth.
291 00:29:15.870 ⇒ 00:29:17.920 Uttam Kumaran: with, Monkey Boy.
292 00:29:31.660 ⇒ 00:29:39.120 Clarence Stone: And you, Tom, before I forget, I think one of the things we should pitch selling is, AI layers on top of all the data analytics, like.
293 00:29:39.680 ⇒ 00:29:44.389 Clarence Stone: a version of Andy that does, like, analytics chats.
294 00:29:44.920 ⇒ 00:29:45.590 Uttam Kumaran: Yeah.
295 00:29:52.250 ⇒ 00:29:52.940 Uttam Kumaran: Okay.
296 00:30:55.320 ⇒ 00:30:57.729 Uttam Kumaran: Okay, I’m just writing one more email.
297 00:31:50.740 ⇒ 00:31:51.260 Uttam Kumaran: Okay.
298 00:31:55.930 ⇒ 00:31:58.150 Uttam Kumaran: So… yeah, I mean…
299 00:31:58.580 ⇒ 00:32:07.969 Uttam Kumaran: I think, basically, Amber, if, like, by Thursday we don’t end up getting, like, SQL access, I’m just gonna see if Mustafa can help you load any of that.
300 00:32:08.260 ⇒ 00:32:10.530 Uttam Kumaran: data.
301 00:32:11.500 ⇒ 00:32:13.680 Uttam Kumaran: into BigQuery directly.
302 00:32:13.810 ⇒ 00:32:24.570 Amber Lin: Okay. Most of it follows a certain pattern, but it is separated out by.
303 00:32:24.570 ⇒ 00:32:28.259 Uttam Kumaran: Even if I can get… you can get a year of data in the same pattern, you know?
304 00:32:28.260 ⇒ 00:32:29.070 Amber Lin: Yeah, okay.
305 00:32:29.070 ⇒ 00:32:34.750 Uttam Kumaran: But ultimately, like, I think you can probably start by looking at some of that FP&A data, or…
306 00:32:35.270 ⇒ 00:32:37.030 Uttam Kumaran: The marketing budget data.
307 00:32:37.630 ⇒ 00:32:38.250 Amber Lin: Yo, bro.
308 00:32:38.250 ⇒ 00:32:41.159 Uttam Kumaran: Seeing if, like, you can load that into BigQuery, or I don’t know.
309 00:32:41.770 ⇒ 00:32:50.620 Amber Lin: Yeah, I’ll see. I can also try it just in cursor to do some of the smaller stuff manually, but…
310 00:32:51.480 ⇒ 00:32:54.080 Amber Lin: do we have BigQuery access loaded in?
311 00:32:54.080 ⇒ 00:32:54.810 Uttam Kumaran: Yeah, we do.
312 00:32:54.810 ⇒ 00:32:56.170 Amber Lin: Your own, okay.
313 00:32:56.400 ⇒ 00:32:59.689 Uttam Kumaran: But what you can do, what you can do locally.
314 00:33:00.580 ⇒ 00:33:03.489 Uttam Kumaran: is you can suggest, and I’ll put this in the.
315 00:33:03.640 ⇒ 00:33:06.200 Amber Lin: And the discovery work stream is…
316 00:33:06.330 ⇒ 00:33:12.720 Uttam Kumaran: tell Cursor to use DuckDB and the Excel connector.
317 00:33:12.930 ⇒ 00:33:16.140 Uttam Kumaran: To load in the data?
318 00:33:16.390 ⇒ 00:33:22.010 Uttam Kumaran: And then… you’ll be able to use SQL
319 00:33:22.370 ⇒ 00:33:24.450 Uttam Kumaran: in the CLI to query again.
320 00:33:24.450 ⇒ 00:33:27.439 Amber Lin: Awesome. Because I was trying to figure out how to…
321 00:33:27.440 ⇒ 00:33:27.960 Uttam Kumaran: Yeah.
322 00:33:27.960 ⇒ 00:33:28.630 Amber Lin: together.
323 00:33:28.630 ⇒ 00:33:37.129 Uttam Kumaran: So tell it, tell it this, basically, just say, use DuckDB and the Excel connector. What it’s gonna do is it’s gonna load the Excel file into a local database.
324 00:33:37.130 ⇒ 00:33:39.320 Amber Lin: And then it will be able to query that.
325 00:33:39.490 ⇒ 00:33:46.690 Uttam Kumaran: You won’t even need BigQuery. The only reason for… the only reason I wanted to do BigQuery is we’ll end up needing to do this.
326 00:33:46.960 ⇒ 00:33:47.790 Uttam Kumaran: Eventually.
327 00:33:47.790 ⇒ 00:33:48.750 Amber Lin: Yes, yeah.
328 00:33:49.070 ⇒ 00:33:54.340 Uttam Kumaran: But this… you’ll be able to replicate the exact same SQL functionality, Locally.
329 00:33:55.350 ⇒ 00:33:55.920 Amber Lin: Cool.
330 00:33:56.540 ⇒ 00:33:57.120 Uttam Kumaran: Yeah.
331 00:33:58.300 ⇒ 00:34:02.510 Amber Lin: Sounds good. Yeah, that’s very helpful. I’ll let you know if it works for me.
332 00:34:02.510 ⇒ 00:34:05.140 Uttam Kumaran: Tell me what cursor says, yeah, if it messes up,
333 00:34:05.510 ⇒ 00:34:10.300 Uttam Kumaran: everybody on the data team, or at least everybody on the DE team, like Awash, Mustafa.
334 00:34:10.800 ⇒ 00:34:12.630 Uttam Kumaran: No, no, DuckDB had it.
335 00:34:13.070 ⇒ 00:34:16.209 Amber Lin: Oh, cool, okay, so I can, I can ask them.
336 00:34:16.590 ⇒ 00:34:17.340 Uttam Kumaran: Yeah.
337 00:34:19.150 ⇒ 00:34:19.840 Amber Lin: Alright.
338 00:34:21.130 ⇒ 00:34:24.580 Uttam Kumaran: So, like, I think, basically, I wanna…
339 00:34:24.690 ⇒ 00:34:31.600 Uttam Kumaran: just to reiterate, like, I’m… maybe, Clarence, I’m gonna start working on the master deck, and then as…
340 00:34:31.840 ⇒ 00:34:40.899 Uttam Kumaran: as you work your magic, Amber, you can start forming decks. I basically listed some of the topics that I think could be good, which is, like.
341 00:34:42.000 ⇒ 00:34:44.600 Uttam Kumaran: Market analysis, which we did…
342 00:34:44.989 ⇒ 00:34:49.639 Uttam Kumaran: Well, we’ll market it… we kind of did industry analysis already, right? So, industry analysis.
343 00:34:51.469 ⇒ 00:34:53.499 Uttam Kumaran: And then we have some follow-ups.
344 00:34:54.040 ⇒ 00:34:54.630 Clarence Stone: Yeah, there’s…
345 00:34:54.639 ⇒ 00:34:57.029 Uttam Kumaran: I have a market analysis? Yeah.
346 00:34:57.609 ⇒ 00:35:05.979 Uttam Kumaran: Market analysis, services analysis services, awareness, site conversion, customer… demographics.
347 00:35:06.089 ⇒ 00:35:10.679 Uttam Kumaran: And then we also have, like, Basically, a churn and retention.
348 00:35:10.829 ⇒ 00:35:15.949 Uttam Kumaran: stuff, right? So… Let’s see if we can basically…
349 00:35:16.109 ⇒ 00:35:27.019 Uttam Kumaran: I think we want to get all of these to the state, kind of like that Clarence had is. We may not get it all right, but at least there’ll be enough for us to present. Think about, like, an hour-long presentation.
350 00:35:28.060 ⇒ 00:35:32.849 Uttam Kumaran: And then each of these, as we sort of round these out, will present over the next 4 weeks.
351 00:35:33.160 ⇒ 00:35:44.169 Uttam Kumaran: And naturally, I’ll meet us in the middle, wherever we get to, with the final menu of options. We’re also trying to show them our capabilities in this whole thing, you know?
352 00:35:44.290 ⇒ 00:35:47.570 Uttam Kumaran: More than get to the final answer within the 4 weeks.
353 00:35:48.340 ⇒ 00:35:53.880 Uttam Kumaran: But I think the data here is actually gonna be… like, Honey Stinger and Insomnia.
354 00:35:54.250 ⇒ 00:36:02.830 Uttam Kumaran: it was complicated because they already had a lot of stuff, right? So we’re going one step deeper. These guys don’t have anything, you know? Even the basics.
355 00:36:03.120 ⇒ 00:36:13.669 Amber Lin: Mmm, I see. I think I’m still in that previous mindset. I was like, how am I even gonna give them anything that I don’t know, that they don’t know, but I guess they just don’t know.
356 00:36:16.790 ⇒ 00:36:34.950 Clarence Stone: Yeah, and Amber, as you’re getting those insights, I’m… I, like, I promised them that I was gonna get them sector-based, market, data, so, like, I can try to see if I can match up to what you’re seeing, that way there’s a comparison to the market as a whole, and what you’re able to find in their data.
357 00:36:35.600 ⇒ 00:36:41.819 Amber Lin: When you say sector-based market data, do you mean based on, say, this demographic?
358 00:36:42.290 ⇒ 00:36:48.929 Clarence Stone: It’s more of, like, Pest Control in Austin.
359 00:36:48.930 ⇒ 00:36:49.860 Amber Lin: Oh, okay, got it.
360 00:36:49.860 ⇒ 00:36:53.910 Clarence Stone: Right. Or, like, pool cleaning, yeah, all that stuff. Like, I want to be able…
361 00:36:53.910 ⇒ 00:36:55.310 Amber Lin: I’ll be able to grab that.
362 00:36:55.540 ⇒ 00:37:05.829 Clarence Stone: Yeah, and then you… yeah, and then take your data and then match it up and say, like, hey, this is the average, you know, numbers that we see across your market, this is what you have, right?
363 00:37:05.830 ⇒ 00:37:13.779 Amber Lin: Awesome, okay. So I think that will take up another, like, 10-20 minutes in the presentation. We’ll do, like, an industry benchmark.
364 00:37:13.780 ⇒ 00:37:14.750 Clarence Stone: Yeah.
365 00:37:14.750 ⇒ 00:37:24.799 Amber Lin: Anything else in the market… I’ll start there, because that’s what Julie’s data lets me do. Anything else in the market analysis deck we want?
366 00:37:29.160 ⇒ 00:37:32.719 Clarence Stone: Nothing from me. You, Tom, you got anything?
367 00:37:33.130 ⇒ 00:37:34.320 Uttam Kumaran: Yeah, nothing for me.
368 00:37:34.320 ⇒ 00:37:35.960 Amber Lin: Okay, I’ll see what I find.
369 00:37:36.150 ⇒ 00:37:53.979 Clarence Stone: And Amber, I can also put, like, I also owe them a slide on additional competitors that they wanted me to look into. So, I mean, if it makes sense to put it into your slide deck for your presentation or a future one, you tell me. I don’t think there’s a rush on that information, but I do need to look into that and create a deck for it as well.
370 00:37:54.790 ⇒ 00:38:02.510 Amber Lin: We can put it in the services deck, do you think that works? Because it’s more of a pool service competitor than this competitor’s.
371 00:38:02.650 ⇒ 00:38:11.149 Clarence Stone: Yeah, that works too. Yeah, yeah. I think, just for your planning purposes, like, I’m super flexible, you can put it anywhere in that, you know, timeline.
372 00:38:11.580 ⇒ 00:38:12.929 Amber Lin: Cool. Sounds good.
373 00:38:18.230 ⇒ 00:38:19.060 Uttam Kumaran: Okay.
374 00:38:20.570 ⇒ 00:38:35.890 Uttam Kumaran: Nice. Okay, cool. Let’s see where we end up at the end of this week. What I’m gonna… I’m gonna… I’m gonna work to break this out a little bit into a… into a Gantt, just to show stuff, but I think we keep this kind of Notion doc running. It’s gonna be scrappy.
375 00:38:37.460 ⇒ 00:38:46.209 Uttam Kumaran: But again, like, any… any… there… let’s… let me work as hard as I can to try to get you as much structured data as possible, Amber, so that’s what I’ll need to.
376 00:38:47.400 ⇒ 00:38:55.270 Amber Lin: Cool, sounds good. And if anyone’s working on that, I can… I can tell them what I’ve seen so far on the data… data that…
377 00:38:55.270 ⇒ 00:38:59.269 Uttam Kumaran: Yeah, I CC’d you, I think, with Evolve yesterday.
378 00:39:00.590 ⇒ 00:39:04.320 Uttam Kumaran: And… They told me they’re working on it.
379 00:39:04.570 ⇒ 00:39:05.380 Amber Lin: Okay.
380 00:39:06.880 ⇒ 00:39:17.750 Uttam Kumaran: They told me, though, they’re gonna tell me updates later today, which it is later today, or tomorrow morning, so… Oh, actually, I didn’t CC, I CC’d Awish and Mustafa, but I will,
381 00:39:19.480 ⇒ 00:39:23.100 Uttam Kumaran: I’ll just forward this to you so you kind of, like, have some visibility.
382 00:39:30.250 ⇒ 00:39:31.040 Uttam Kumaran: Great.
383 00:39:31.860 ⇒ 00:39:32.990 Uttam Kumaran: Okay, awesome.
384 00:39:33.380 ⇒ 00:39:34.350 Uttam Kumaran: Nice.
385 00:39:37.120 ⇒ 00:39:39.650 Uttam Kumaran: All right, perfect. Thank you both. I’ll talk to you.
386 00:39:39.650 ⇒ 00:39:40.640 Clarence Stone: Thanks, guys.
387 00:39:40.640 ⇒ 00:39:41.530 Amber Lin: Anytime.
388 00:39:41.530 ⇒ 00:39:42.500 Clarence Stone: Yep, right.