2024-06-25_uttam-kumarans-personal-meeting-room_32479308

Meeting Title: Uttam-Kumaran’s-Personal-Meeting-Room Date: 2024-06-25 Meeting participants: Uttam Kumaran, Nicolas Sucari, Jakob Kagel

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WEBVTT

1 00:01:31.660 ⇒ 00:01:32.819 Jakob Kagel: Hey? How’s it going.

2 00:01:33.540 ⇒ 00:01:34.260 Uttam Kumaran: Yo.

3 00:01:35.650 ⇒ 00:01:36.450 Nicolas Sucari: Hi guys.

4 00:01:40.597 ⇒ 00:01:43.459 Uttam Kumaran: Cool. Let’s just jump right in.

5 00:01:43.460 ⇒ 00:01:43.910 Jakob Kagel: Yeah.

6 00:01:43.910 ⇒ 00:01:44.490 Uttam Kumaran: Us.

7 00:01:44.900 ⇒ 00:01:57.290 Jakob Kagel: So, yeah, exactly. So I just wanna say, real quick, yeah, I don’t. I don’t wanna change like I’m not trying to change any of the logic. What’s confusing and like what me and Nicholas were talking about, or like what we’re trying to do

8 00:01:57.320 ⇒ 00:02:06.450 Jakob Kagel: right? It’s like to always have like these big like numbers, like total sales, and like total pro customers, right? That we can tie out to.

9 00:02:06.840 ⇒ 00:02:25.679 Jakob Kagel: That’s how we validate, like, you know. That’s how you can always tell right? Like, if the thing is like working correctly, like, if it’s aggregating correctly or whatnot, it’s just if everything ties out now where that’s been confusing for me is just like on the names like that we’re using on some of these labels,

10 00:02:26.010 ⇒ 00:02:47.170 Jakob Kagel: and like, in this shopify like orders, table or customers table. Now, it’s like we have like 4 different names. Right? We have like is pool pro in the table. Then we have like is pool pro like question or whatever in the table. And then we have, like derived and self identified in real. So we have, like 4 different names, like for all the same things. And that’s like

11 00:02:47.240 ⇒ 00:02:53.089 Jakob Kagel: where it’s just like getting a little confusing. But I don’t think that there’s any issue like with our logic.

12 00:02:53.472 ⇒ 00:02:59.690 Jakob Kagel: And I’m actually like i i i feel pretty good about like the numbers that we have in real. The only thing

13 00:02:59.870 ⇒ 00:03:01.902 Jakob Kagel: that I would say

14 00:03:02.450 ⇒ 00:03:23.429 Jakob Kagel: we should check on, or that we should figure out first.st Here is like we have, like 14.6, like from K, like from the self identified question. And I know it’s over 16 k. Like in the Shopify Orders table. Now, where we’re probably losing some of these is like, if we’re joining to all orders. Because, like, we said that we have some

15 00:03:23.430 ⇒ 00:03:41.590 Jakob Kagel: like self identified pool pros that like don’t complete the checkout process right? But they, their data is like, stored, basically, right? So we’re losing some probably like that way. But I think we should just be able to say like, why we have 14.6 and not like the full amount, basically.

16 00:03:42.390 ⇒ 00:03:44.749 Uttam Kumaran: Okay, cool. So let’s just note down

17 00:03:44.920 ⇒ 00:03:48.587 Uttam Kumaran: the things we wanna go through. And then let’s just run through stuff.

18 00:03:49.800 ⇒ 00:03:53.589 Nicolas Sucari: It’s inside. Paul. Yeah. Inside birds.

19 00:03:54.180 ⇒ 00:03:54.910 Nicolas Sucari: There.

20 00:03:58.315 ⇒ 00:04:01.364 Uttam Kumaran: Okay, cool. So I’m just gonna have

21 00:04:04.560 ⇒ 00:04:06.440 Uttam Kumaran: just gonna have some notes from

22 00:04:06.930 ⇒ 00:04:07.760 Uttam Kumaran: our fading.

23 00:04:16.380 ⇒ 00:04:19.080 Uttam Kumaran: So the 1st thing is,

24 00:04:19.620 ⇒ 00:04:30.809 Jakob Kagel: I would just say, like naming conventions is like the 1st thing. It’s just like, make sure we have them like consistent between, like the table. And like what we’re using in real.

25 00:04:31.240 ⇒ 00:04:32.090 Jakob Kagel: Yeah.

26 00:04:32.500 ⇒ 00:04:36.630 Jakob Kagel: it just helps a lot. Cause this is like not confusing. You know.

27 00:04:37.530 ⇒ 00:04:38.230 Uttam Kumaran: Totally

28 00:04:38.810 ⇒ 00:04:42.099 Uttam Kumaran: the naming conventions. Let’s also do tie out

29 00:04:42.920 ⇒ 00:04:46.180 Uttam Kumaran: and let’s have a

30 00:04:48.070 ⇒ 00:04:49.590 Uttam Kumaran: tab, a

31 00:04:55.010 ⇒ 00:04:56.578 Uttam Kumaran: okay, cool. So let’s

32 00:04:57.520 ⇒ 00:05:03.180 Uttam Kumaran: I’m gonna walk you through the flow. And actually, let’s

33 00:05:03.780 ⇒ 00:05:07.459 Uttam Kumaran: even try to use elementary for this, because.

34 00:05:07.460 ⇒ 00:05:08.330 Jakob Kagel: Sure I mean.

35 00:05:09.020 ⇒ 00:05:10.920 Uttam Kumaran: It’ll be pretty easy for me to just.

36 00:05:10.920 ⇒ 00:05:12.460 Jakob Kagel: Right? Exactly.

37 00:05:12.520 ⇒ 00:05:22.229 Jakob Kagel: Yeah. Let’s just go through the flow. I mean, the thing is right. That I’m just saying is like, once we show them like 14.6 or something. Then it’s like we can’t go back on that right.

38 00:05:22.230 ⇒ 00:05:26.390 Uttam Kumaran: No, you’re totally right. You’re totally right, and it’s like again, I don’t mind going through this.

39 00:05:26.780 ⇒ 00:05:29.640 Uttam Kumaran: I can go. I can go. There’s over and over. I don’t mind.

40 00:05:29.640 ⇒ 00:05:31.500 Jakob Kagel: I got. I’m not. Yeah.

41 00:05:31.500 ⇒ 00:05:32.640 Uttam Kumaran: It’s gonna be like, and.

42 00:05:32.640 ⇒ 00:05:38.300 Jakob Kagel: Validation, or like stall us out here, or anything like that. I’m just like thinking, like, you know, before we go.

43 00:05:38.300 ⇒ 00:05:41.449 Uttam Kumaran: For me. It’s actually like everybody should be confident. So if, like.

44 00:05:41.450 ⇒ 00:05:41.830 Jakob Kagel: But.

45 00:05:41.830 ⇒ 00:05:46.200 Uttam Kumaran: One of us is like, I’m nervous. Then we shouldn’t go past.

46 00:05:46.410 ⇒ 00:05:49.059 Uttam Kumaran: you know. Let’s so let’s go. We’ll just let’s roll time either way.

47 00:05:49.060 ⇒ 00:05:55.610 Jakob Kagel: I still think, like, yeah, like, the numbers are, are all basically good. But yeah, let’s just go through the the flow real quick.

48 00:05:55.610 ⇒ 00:05:56.250 Uttam Kumaran: Yeah.

49 00:06:27.050 ⇒ 00:06:28.290 Uttam Kumaran: okay, cool.

50 00:06:32.570 ⇒ 00:06:33.700 Uttam Kumaran: So

51 00:06:33.930 ⇒ 00:06:43.550 Uttam Kumaran: to give you guys a little sense of what I’m even doing here. So when I came to lineage, search for the top of my customers table. This will actually give you like, basically.

52 00:06:44.330 ⇒ 00:06:47.760 Uttam Kumaran: I don’t know, Jacob. I don’t know what the word the stats word is for like

53 00:06:48.440 ⇒ 00:06:51.950 Uttam Kumaran: the nodes or whatever basically, you can go to

54 00:06:52.760 ⇒ 00:06:55.390 Uttam Kumaran: like 2 levels deep on each side.

55 00:06:55.510 ⇒ 00:06:59.750 Uttam Kumaran: this side basically stops but 2 dot 2 levels deep this way.

56 00:06:59.870 ⇒ 00:07:02.539 Uttam Kumaran: So if we look at that, basically.

57 00:07:03.970 ⇒ 00:07:05.280 Uttam Kumaran: actually, we’ll just

58 00:07:06.510 ⇒ 00:07:11.239 Uttam Kumaran: basically what happens is shops like customers pulls from like a whole host of things.

59 00:07:11.360 ⇒ 00:07:17.610 Uttam Kumaran: some of which is actually still not perfect, some of which is in a good spot. Basically.

60 00:07:17.680 ⇒ 00:07:24.030 Uttam Kumaran: basically, we’re using a pre aggregated shop by customer stable from 5 train that this that has a lot of helpful stuff like

61 00:07:24.120 ⇒ 00:07:28.579 Uttam Kumaran: it provides like average Ltv. Like all those deals that are in shopify customers that are like.

62 00:07:28.780 ⇒ 00:07:30.729 Uttam Kumaran: Oh, maybe this would be nice to have.

63 00:07:30.730 ⇒ 00:07:31.140 Jakob Kagel: Right.

64 00:07:31.140 ⇒ 00:07:35.600 Uttam Kumaran: There. In addition, we’re pulling stuff from the pool pro emails.

65 00:07:35.750 ⇒ 00:07:39.160 Uttam Kumaran: We’re pulling stuff, and that is pulling from the orders.

66 00:07:40.205 ⇒ 00:07:41.130 Uttam Kumaran: Basically.

67 00:07:41.130 ⇒ 00:07:43.259 Jakob Kagel: That’s for a shopify customer’s table, right?

68 00:07:43.260 ⇒ 00:07:44.576 Uttam Kumaran: Suggest for the shopify customer.

69 00:07:44.840 ⇒ 00:07:47.209 Jakob Kagel: I’m less concerned with the table

70 00:07:47.330 ⇒ 00:08:00.160 Jakob Kagel: now that we got like. Did we figured out like the naming convention there. What? I’m like a little bit more concerned about is like in real. Basically, if we look at like our total, like unique customers by like, is like

71 00:08:00.300 ⇒ 00:08:06.539 Jakob Kagel: self-identified pool. Pro true is only like 14.6 and.

72 00:08:06.540 ⇒ 00:08:07.889 Uttam Kumaran: For the 2 years.

73 00:08:07.890 ⇒ 00:08:15.179 Jakob Kagel: Right, for that would no, for the whole time period like I mean, I think it’s probably the same. I mean 2 years. It’s probably about the same. But

74 00:08:15.510 ⇒ 00:08:20.099 Jakob Kagel: if you do it like, if you go to the pivot, right? Or you can see it probably in here. Yeah.

75 00:08:21.010 ⇒ 00:08:23.600 Jakob Kagel: yeah, like 14.6. Right? There. Yeah.

76 00:08:23.600 ⇒ 00:08:24.880 Uttam Kumaran: Yes. Okay.

77 00:08:25.110 ⇒ 00:08:35.819 Jakob Kagel: So. But if we have like in the table, right like in the in the Shopify Customers table, we have like over 16 k. So it’s not like, I mean, it’s it’s not a huge, huge discrepancy.

78 00:08:35.820 ⇒ 00:08:39.619 Uttam Kumaran: Wait! Wait! Can you say that? Can you? Can you say that one more time? And what is the 16 cat.

79 00:08:39.780 ⇒ 00:08:41.960 Jakob Kagel: That’s like is pool pro true.

80 00:08:42.669 ⇒ 00:08:45.489 Jakob Kagel: and like out of like customer id.

81 00:08:45.660 ⇒ 00:08:47.239 Uttam Kumaran: And that’s from yours.

82 00:08:47.500 ⇒ 00:08:49.689 Jakob Kagel: That’s from the shopify table.

83 00:08:49.930 ⇒ 00:08:51.220 Uttam Kumaran: Shopify.

84 00:08:51.894 ⇒ 00:08:54.589 Jakob Kagel: Shopify Customers, Shopify Customers.

85 00:08:54.590 ⇒ 00:08:56.560 Uttam Kumaran: Okay. So let’s let’s look at which

86 00:08:56.980 ⇒ 00:09:00.610 Uttam Kumaran: let’s look at where this maps into realm. Let’s walk through that.

87 00:09:00.610 ⇒ 00:09:01.629 Jakob Kagel: Yeah, okay. And I don’t.

88 00:09:01.939 ⇒ 00:09:02.559 Uttam Kumaran: Saying it.

89 00:09:02.560 ⇒ 00:09:05.870 Jakob Kagel: Like wrong or like, it’s an issue. I just want us to be able to say, like.

90 00:09:05.870 ⇒ 00:09:08.370 Uttam Kumaran: No, totally. Totally. Yeah.

91 00:09:08.370 ⇒ 00:09:21.604 Jakob Kagel: Like, I said. We have orders that haven’t like completed the checkout pro like they don’t have purchases, or whatever we have. Customer ids that don’t have purchases, basically. And if that’s it, then that’s fine, and we can say that. But

92 00:09:22.230 ⇒ 00:09:22.860 Jakob Kagel: it’s just good.

93 00:09:22.860 ⇒ 00:09:23.710 Uttam Kumaran: And one.

94 00:09:23.710 ⇒ 00:09:25.230 Jakob Kagel: Understanding, too.

95 00:09:25.500 ⇒ 00:09:32.969 Uttam Kumaran: The one thing why shopify customers is is is like exist. Why shopify orders exist in all these is basically

96 00:09:33.010 ⇒ 00:09:37.709 Uttam Kumaran: I don’t wanna look at customers that haven’t made a purchase. I don’t consider those a customer.

97 00:09:37.710 ⇒ 00:09:38.959 Jakob Kagel: That’s fine. I.

98 00:09:38.960 ⇒ 00:09:43.489 Uttam Kumaran: So so one, I think that’s 1 thing. That’s a good thing. Maybe we’ll just note that down, because

99 00:09:44.050 ⇒ 00:09:48.969 Uttam Kumaran: then you’ll we actually have customer ids for people that like have just like

100 00:09:49.330 ⇒ 00:09:52.469 Uttam Kumaran: basically made the checkout or created an account, you know. So.

101 00:09:52.470 ⇒ 00:09:53.240 Jakob Kagel: Right.

102 00:09:53.720 ⇒ 00:10:02.879 Uttam Kumaran: So one is like we’re we’re considering. And it’s probably not that important for them to know that. But again, we’re gonna see customer ids that have numbers.

103 00:10:02.880 ⇒ 00:10:11.050 Jakob Kagel: And that makes perfect sense to me, because it’s like, if I join the shopify customers table on all orders, like, yeah, we get down to basically like 15 k.

104 00:10:11.230 ⇒ 00:10:11.780 Uttam Kumaran: Yeah.

105 00:10:11.780 ⇒ 00:10:17.380 Jakob Kagel: It’s close, I mean. Now, we’re only talking about a difference of like 400, you know, which is fine, too, I mean, like so.

106 00:10:17.380 ⇒ 00:10:19.099 Uttam Kumaran: No, let’s find out where it is.

107 00:10:19.100 ⇒ 00:10:28.489 Jakob Kagel: But it’s like we have. Yeah, I mean, some of the stuff. It’s like, we can say, Okay, this is like, reasonably close enough or whatnot. But it would just be good, I think, yeah, like for us to like, you know.

108 00:10:28.910 ⇒ 00:10:44.509 Jakob Kagel: have the understanding, because, like once, we trust that number, it’s like, Okay, now, we can like, trust all the splits. And we can say, like, Yeah, this is shopify self, identify pool pro that has made a purchase, you know, like, and and we just have that like sort of like foundation.

109 00:10:45.890 ⇒ 00:10:47.136 Uttam Kumaran: and then

110 00:10:53.070 ⇒ 00:11:00.139 Uttam Kumaran: so we have. Is pool pro here. What I’m gonna do is, and I’m gonna go to the real folder on the left.

111 00:11:00.470 ⇒ 00:11:04.100 Uttam Kumaran: I’m going to open up the shopify

112 00:11:04.760 ⇒ 00:11:06.550 Uttam Kumaran: customers

113 00:11:07.600 ⇒ 00:11:08.900 Uttam Kumaran: dashboard.

114 00:11:09.100 ⇒ 00:11:16.609 Uttam Kumaran: What we’re gonna see here is these are all the fields that we’re bringing in right. This is like, basically where we’re focused on. So this is gonna be

115 00:11:29.800 ⇒ 00:11:33.490 Uttam Kumaran: the ordering matters in this file because kind of how it

116 00:11:33.610 ⇒ 00:11:38.080 Uttam Kumaran: populates in the brill. But I’m just gonna I’ll kind of separate it out here.

117 00:11:38.400 ⇒ 00:11:43.410 Uttam Kumaran: So is pool pro derived pulls from cs.is full pro

118 00:11:43.810 ⇒ 00:11:47.029 Uttam Kumaran: right. cs.is pool pro.

119 00:11:47.110 ⇒ 00:11:50.049 Uttam Kumaran: It’s pulling from customer segments.

120 00:11:50.640 ⇒ 00:11:53.299 Uttam Kumaran: Customer segment is here.

121 00:11:53.440 ⇒ 00:11:55.500 Uttam Kumaran: which is basically looking at

122 00:11:56.000 ⇒ 00:11:56.840 Uttam Kumaran: which

123 00:11:56.970 ⇒ 00:12:03.010 Uttam Kumaran: which customer ids from the shopify customers, table shopify customers table is

124 00:12:06.110 ⇒ 00:12:08.850 Uttam Kumaran: it’s this from shopify customers. Basically.

125 00:12:09.640 ⇒ 00:12:13.026 Uttam Kumaran: It’s looking at which customers from here.

126 00:12:13.940 ⇒ 00:12:15.240 Uttam Kumaran: RN,

127 00:12:16.108 ⇒ 00:12:21.029 Uttam Kumaran: like, which customers basically have a joint. This all pool pool pro cte

128 00:12:21.250 ⇒ 00:12:26.079 Uttam Kumaran: apple pros cte is a union between

129 00:12:26.940 ⇒ 00:12:29.560 Uttam Kumaran: people that have multiple orders.

130 00:12:30.510 ⇒ 00:12:34.749 Uttam Kumaran: people that have people have that multiple orders where they have more than 2 pump orders.

131 00:12:35.850 ⇒ 00:12:44.199 Uttam Kumaran: This is also union between everybody that has a pool pro email and a union between where they have checkup. It’s not a union. All because

132 00:12:44.616 ⇒ 00:12:55.273 Uttam Kumaran: if they’re in one of these, then it doesn’t really matter. And we’re basically looking at the checkout flag. Where is pool? Pro is is true. So let’s go through each of these. So.

133 00:12:55.570 ⇒ 00:12:59.949 Jakob Kagel: Sorry. This is one more thing that so that we have to talk about now, because, like.

134 00:12:59.950 ⇒ 00:13:00.560 Nicolas Sucari: Yeah.

135 00:13:00.720 ⇒ 00:13:06.330 Jakob Kagel: The is pool pro equals true here, that’s like supposed to be the self identified flag right?

136 00:13:06.330 ⇒ 00:13:07.180 Uttam Kumaran: Yes.

137 00:13:07.180 ⇒ 00:13:12.290 Jakob Kagel: Right. So the count right? The count of derived pool pro.

138 00:13:12.370 ⇒ 00:13:20.589 Jakob Kagel: which is our calculation. Right? We’re adding these like email and these like multiple orders, it should be higher than 14.6 right.

139 00:13:20.610 ⇒ 00:13:21.449 Uttam Kumaran: Where was he?

140 00:13:22.300 ⇒ 00:13:23.220 Uttam Kumaran: Because we’re.

141 00:13:23.220 ⇒ 00:13:25.280 Jakob Kagel: Additional ones in right.

142 00:13:25.930 ⇒ 00:13:30.770 Uttam Kumaran: Ours should be okay. Well, let’s okay. So let’s let’s look at it now. So

143 00:13:30.820 ⇒ 00:13:32.460 Uttam Kumaran: shopify customers.

144 00:13:32.710 ⇒ 00:13:34.760 Uttam Kumaran: We have our derived.

145 00:13:34.760 ⇒ 00:13:36.519 Jakob Kagel: It’s like, 600. Yeah.

146 00:13:36.520 ⇒ 00:13:38.250 Uttam Kumaran: Oh, yeah, so.

147 00:13:38.250 ⇒ 00:13:54.249 Jakob Kagel: That’s what I was like tripping on a little bit earlier, too. Because and I think it’s fine. If we have arrived as just email and like multiple orders for now. But I was like, that’s not what we were trying to do. I thought, Yeah.

148 00:13:54.940 ⇒ 00:13:55.530 Uttam Kumaran: Yeah, right.

149 00:13:55.530 ⇒ 00:13:56.319 Nicolas Sucari: No, I’m

150 00:13:56.770 ⇒ 00:14:10.729 Nicolas Sucari: yeah. i i i think we need to change that. And also what in? In what we talked before. Jacob, I think we? We need to get rid of the 1st part of that Union right, the the part of the the amount of orders.

151 00:14:11.120 ⇒ 00:14:12.330 Uttam Kumaran: In circles.

152 00:14:12.600 ⇒ 00:14:13.410 Jakob Kagel: I mean, that’s.

153 00:14:13.410 ⇒ 00:14:14.690 Uttam Kumaran: That’s fine!

154 00:14:14.690 ⇒ 00:14:16.000 Jakob Kagel: Fine. I mean, like.

155 00:14:16.740 ⇒ 00:14:27.809 Jakob Kagel: I don’t think we should really show any splits with the, because the whole point of the meeting right is like, we’re gonna show them like these, 1, 2 and 3 splits like the 6 splits, basically like multiple orders. And then multiple.

156 00:14:27.810 ⇒ 00:14:31.020 Uttam Kumaran: Yeah, you’ll bring them. You’ll bring them in while you need it.

157 00:14:31.020 ⇒ 00:14:32.299 Jakob Kagel: Right and then.

158 00:14:32.490 ⇒ 00:14:40.180 Jakob Kagel: and that’s the thing. But the derived is like they can decide, basically based on what we show them like, do they want to do 2 orders, or like 2 plus.

159 00:14:40.180 ⇒ 00:14:41.370 Nicolas Sucari: Exactly. Yeah.

160 00:14:42.000 ⇒ 00:14:44.199 Jakob Kagel: But I think like.

161 00:14:44.580 ⇒ 00:14:46.830 Uttam Kumaran: So I wonder if we should have it derived at all.

162 00:14:46.830 ⇒ 00:15:01.730 Jakob Kagel: Right. Exactly. No, I’m I’m totally the exactly. We don’t even need it. To be honest, I think what’s important. And yeah, what I’ve been trying to get at. And that’s like how I was like when we had the conversation yesterday, too, is like what we wanna show, I think, is like the coverage of like the.

163 00:15:01.730 ⇒ 00:15:02.530 Uttam Kumaran: Yeah.

164 00:15:02.530 ⇒ 00:15:30.399 Jakob Kagel: Pro flag by all of these splits. Because that’s like, kind of the meet on the phone is like, Okay, like your 3 plus orders or 2 plus orders, or whatever they have, like 90% coverage with self identified pros. Now you can say, this is like high confidence, you know, but the derived like doesn’t really matter, because that’s like, what can come out of the meeting is they can stay based on that like, okay, we feel good about, you know, using this combination, I think.

165 00:15:30.450 ⇒ 00:15:31.050 Uttam Kumaran: So that’s.

166 00:15:31.050 ⇒ 00:15:36.360 Jakob Kagel: We already have all of that, too. So that’s great, like we already have it. It was just confusing.

167 00:15:36.640 ⇒ 00:15:42.319 Uttam Kumaran: No, you’re no, you’re right. No, I think that’s the right plan. So let’s walk through. So I just want to go through.

168 00:15:42.530 ⇒ 00:15:45.129 Uttam Kumaran: Let’s go through what? What it’s gonna look like. Then.

169 00:15:45.401 ⇒ 00:15:48.936 Jakob Kagel: Let’s talk about the meeting and kind of work backwards a little bit.

170 00:15:49.480 ⇒ 00:15:52.549 Uttam Kumaran: Yeah, so let me pull up. Let me pull up real with what we have.

171 00:15:52.610 ⇒ 00:15:54.899 Uttam Kumaran: Now, which is, I just commented out.

172 00:15:55.850 ⇒ 00:15:57.450 Jakob Kagel: Right? Yeah.

173 00:15:58.420 ⇒ 00:16:02.853 Jakob Kagel: But either way, like we, I mean, yeah, there definitely is like a flaw.

174 00:16:03.170 ⇒ 00:16:04.930 Uttam Kumaran: There’s something fucked up.

175 00:16:04.930 ⇒ 00:16:05.180 Jakob Kagel: Yes,

176 00:16:05.430 ⇒ 00:16:07.990 Uttam Kumaran: That’s okay. That’s fine. That’s fine.

177 00:16:07.990 ⇒ 00:16:11.480 Jakob Kagel: Yeah, like, when we do implement that or whatever. Then? Yeah.

178 00:16:11.650 ⇒ 00:16:14.224 Jakob Kagel: you know, we have to check that or whatnot.

179 00:16:14.690 ⇒ 00:16:15.360 Uttam Kumaran: Yeah.

180 00:16:16.700 ⇒ 00:16:17.680 Uttam Kumaran: I, like.

181 00:16:19.920 ⇒ 00:16:33.620 Jakob Kagel: And yeah, I mean, we know, like, basically, too, with like the total, like with the self identified pool. Pro, like with the all orders. That’s basically like the biggest. The big chunk you know of people that are not in

182 00:16:34.100 ⇒ 00:16:48.649 Jakob Kagel: like that are not counted in real is because they haven’t made order. I mean, there’s like 400, and we can definitely like, I don’t know we should look into that, probably, but I feel like 14.6 and 1,500. I don’t feel so bad about that like extra 400. There.

183 00:16:50.040 ⇒ 00:16:51.360 Uttam Kumaran: Yeah, no, I agree.

184 00:16:51.360 ⇒ 00:16:57.239 Jakob Kagel: Oh, I mean, it would be good to know, like, you know, but we know, like the majority is like.

185 00:16:57.240 ⇒ 00:16:58.640 Uttam Kumaran: Because it’s still right.

186 00:16:58.640 ⇒ 00:16:59.380 Jakob Kagel: Yeah.

187 00:17:00.990 ⇒ 00:17:01.710 Uttam Kumaran: Awesome.

188 00:17:02.241 ⇒ 00:17:04.349 Uttam Kumaran: Let me just start these

189 00:17:06.760 ⇒ 00:17:07.790 Uttam Kumaran: everything.

190 00:17:10.710 ⇒ 00:17:11.450 Uttam Kumaran: Okay.

191 00:17:12.069 ⇒ 00:17:12.790 Uttam Kumaran: Scott.

192 00:17:16.890 ⇒ 00:17:17.980 Uttam Kumaran: thank you. Thank you.

193 00:17:19.650 ⇒ 00:17:20.699 Uttam Kumaran: All that breath.

194 00:17:21.730 ⇒ 00:17:22.719 Uttam Kumaran: Take over and.

195 00:17:23.930 ⇒ 00:17:28.310 Jakob Kagel: See what else I think would be useful. Sorry, I’m just not trying to go on a tangent.

196 00:17:28.319 ⇒ 00:17:30.259 Uttam Kumaran: No, no, no! Keep going. Keep going. I’m listening.

197 00:17:30.400 ⇒ 00:17:34.999 Jakob Kagel: Yeah. But I think what else would be useful to is maybe like another split is like.

198 00:17:35.060 ⇒ 00:17:39.670 Jakob Kagel: if we actually split the pool pro question into the 2 answers.

199 00:17:39.670 ⇒ 00:17:41.560 Uttam Kumaran: They do really good job. Oh.

200 00:17:41.560 ⇒ 00:17:54.899 Jakob Kagel: If it doesn’t really matter, you know, because we’re counting them both as like is pool pro. But like I don’t know, there might be some things to be said there, where it’s like more likely, you know, and that’s the whole thing we’re trying to get to is like.

201 00:17:54.900 ⇒ 00:17:55.880 Uttam Kumaran: Oh!

202 00:17:56.050 ⇒ 00:18:04.639 Jakob Kagel: And say, like, okay, the people that said Pool Service professional are kinda like they actually spend more than the people that said Pool owners.

203 00:18:04.640 ⇒ 00:18:08.200 Uttam Kumaran: You know I don’t know what I mean.

204 00:18:08.200 ⇒ 00:18:09.630 Nicolas Sucari: We can do that in real with you.

205 00:18:09.700 ⇒ 00:18:10.740 Uttam Kumaran: Run home.

206 00:18:11.000 ⇒ 00:18:16.929 Nicolas Sucari: Why, why we can’t, why, we can’t do that in real right now. With that that like, with that field.

207 00:18:16.930 ⇒ 00:18:26.600 Uttam Kumaran: I combine that answer right right now. It’s like a are you this? Are you? This I combine into. Are you the top? Yes or no, I’m not giving you what they select.

208 00:18:26.600 ⇒ 00:18:28.190 Nicolas Sucari: I think I’m also good, awesome.

209 00:18:28.430 ⇒ 00:18:32.670 Uttam Kumaran: Jacob. Sometimes they put they put in null, so I can bring in just the values.

210 00:18:32.860 ⇒ 00:18:33.920 Uttam Kumaran: And now you can have it.

211 00:18:33.920 ⇒ 00:18:39.280 Jakob Kagel: Yeah, I don’t know if it’s like super high priority. And like also, I don’t know if we need it necessarily for this meeting, you know.

212 00:18:39.280 ⇒ 00:18:49.809 Uttam Kumaran: The one thing is dude they’re gonna get. If they’re gonna if we’re confused about this, they’re gonna be like, I don’t know. I want to be like a little bit.

213 00:18:49.810 ⇒ 00:18:50.690 Jakob Kagel: Exactly here.

214 00:18:50.690 ⇒ 00:18:55.440 Uttam Kumaran: There’s also the thing. If we get too far down this rabbit hole, they’re gonna say, make a decision.

215 00:18:55.470 ⇒ 00:19:03.019 Uttam Kumaran: I know, like I know, that that’s good. They’re gonna say, you figure it out. So I wanna make sure we just like know what we want for them.

216 00:19:03.020 ⇒ 00:19:03.410 Jakob Kagel: Yeah.

217 00:19:03.410 ⇒ 00:19:05.020 Uttam Kumaran: And we like give them more.

218 00:19:05.170 ⇒ 00:19:06.610 Uttam Kumaran: you know. So.

219 00:19:08.030 ⇒ 00:19:10.820 Nicolas Sucari: So if if right now, the logic is that if you

220 00:19:11.261 ⇒ 00:19:21.540 Nicolas Sucari: yeah, if if you select the default ones on that field like you’re not taking into account the ones that says, let’s say I’m a pool owner, not a pull pro owner, but.

221 00:19:21.540 ⇒ 00:19:22.559 Uttam Kumaran: You’re including. Yeah.

222 00:19:22.560 ⇒ 00:19:25.410 Nicolas Sucari: I’m the nose, too, because it’s not mandatory.

223 00:19:25.410 ⇒ 00:19:27.139 Uttam Kumaran: Right, yeah, yeah.

224 00:19:27.140 ⇒ 00:19:27.780 Nicolas Sucari: Oh, man!

225 00:19:28.180 ⇒ 00:19:29.326 Nicolas Sucari: Get it!

226 00:19:29.900 ⇒ 00:19:33.045 Uttam Kumaran: And any answer apart from the top one, you’re considered.

227 00:19:35.070 ⇒ 00:19:38.379 Nicolas Sucari: But I mean that’s not totally wrong either way.

228 00:19:38.790 ⇒ 00:19:39.640 Uttam Kumaran: Yeah, it’s

229 00:19:40.250 ⇒ 00:19:41.619 Uttam Kumaran: okay. So here we go. So.

230 00:19:41.620 ⇒ 00:19:48.030 Jakob Kagel: I don’t think it’s wrong at all. It’s more just like that. It’s like like. It might be interesting to see.

231 00:19:48.030 ⇒ 00:19:48.520 Uttam Kumaran: Yeah.

232 00:19:48.720 ⇒ 00:19:50.740 Jakob Kagel: Nothing’s wrong with how we’re doing. I think that’s.

233 00:19:50.740 ⇒ 00:19:51.480 Uttam Kumaran: Like us.

234 00:19:51.630 ⇒ 00:19:52.910 Jakob Kagel: Told us to do it. They.

235 00:19:52.910 ⇒ 00:19:55.260 Uttam Kumaran: Yeah, let’s keep. Let’s keep that for us.

236 00:19:55.260 ⇒ 00:19:55.970 Jakob Kagel: Sure.

237 00:19:56.540 ⇒ 00:19:57.830 Uttam Kumaran: And then we’ll

238 00:19:58.250 ⇒ 00:20:06.460 Uttam Kumaran: we’ll make a call. The other thing I’m gonna do is, I’m gonna add a previous 24 months as an option here because it’s been really annoying.

239 00:20:07.470 ⇒ 00:20:07.790 Jakob Kagel: Yeah.

240 00:20:08.545 ⇒ 00:20:09.300 Uttam Kumaran: Okay?

241 00:20:09.510 ⇒ 00:20:10.490 Uttam Kumaran: Greats.

242 00:20:11.240 ⇒ 00:20:12.370 Uttam Kumaran: So

243 00:20:13.110 ⇒ 00:20:16.359 Uttam Kumaran: we should see that here last 24 months.

244 00:20:19.160 ⇒ 00:20:21.430 Uttam Kumaran: And so self-identified.

245 00:20:24.810 ⇒ 00:20:26.929 Uttam Kumaran: this is total customers.

246 00:20:32.540 ⇒ 00:20:33.230 Jakob Kagel: Yeah.

247 00:20:33.880 ⇒ 00:20:37.169 Uttam Kumaran: That seems right. Right. So is poor pro self identified.

248 00:20:37.170 ⇒ 00:20:39.969 Jakob Kagel: Right? I I don’t think that’s wrong. Yeah. I mean

249 00:20:40.220 ⇒ 00:20:46.829 Jakob Kagel: this 2 years. I mean, we had what 14 6 overall in the last 2 years we have 13. I don’t think that’s unreasonable.

250 00:20:46.830 ⇒ 00:20:48.630 Uttam Kumaran: Yeah. And let me. Let’s just walk through this.

251 00:20:48.630 ⇒ 00:20:52.109 Jakob Kagel: Like some people are shopping in multiple years. I don’t know

252 00:20:54.170 ⇒ 00:20:55.400 Jakob Kagel: But yeah.

253 00:20:57.250 ⇒ 00:20:59.520 Uttam Kumaran: Basically, what I’m doing is I look at.

254 00:21:00.070 ⇒ 00:21:03.539 Uttam Kumaran: If you’re a pool industry professional, you’re considered a pro.

255 00:21:04.360 ⇒ 00:21:06.220 Uttam Kumaran: your full owner.

256 00:21:06.670 ⇒ 00:21:07.880 Uttam Kumaran: It’s this

257 00:21:09.470 ⇒ 00:21:10.140 Uttam Kumaran: step.

258 00:21:11.660 ⇒ 00:21:13.379 Uttam Kumaran: Oh, I’m sure there’s so much.

259 00:21:13.710 ⇒ 00:21:14.199 Jakob Kagel: The yellow

260 00:21:15.100 ⇒ 00:21:19.850 Jakob Kagel: talk about like in the meeting, like what we wanna show them real quick, and that will like

261 00:21:19.880 ⇒ 00:21:23.319 Jakob Kagel: we can align on that at least, too, I think that would be good right.

262 00:21:23.650 ⇒ 00:21:23.980 Uttam Kumaran: All.

263 00:21:23.980 ⇒ 00:21:40.709 Jakob Kagel: Like, I said. I think we should show them right like 1, 2, and 2 plus order groups and 1, 2, 2 plus like order groups, but that have pool, pump purchases, or whatever, like the multiple pool pump purchases, and then we should show the coverage, like the is pro coverage

264 00:21:40.710 ⇒ 00:22:02.030 Jakob Kagel: for all of those. And then we can. We’ll basically, I think it will show, say, like, Okay, these are the high confidence ones, or, like, you know, at this order level, you’re basically gonna say, like, this is 70 confidence, 80% confidence, 90% confidence based on the coverage of the self identified question. Now, is there anything else like that we really like want to show.

265 00:22:02.030 ⇒ 00:22:02.620 Uttam Kumaran: Maybe.

266 00:22:02.884 ⇒ 00:22:08.179 Jakob Kagel: Cause the emails like we said, right, the emails are self explanatory. I don’t think we really have to like.

267 00:22:08.790 ⇒ 00:22:16.377 Jakob Kagel: we don’t have to show too much for the emails. I mean, we can show it, too, because we have the flag for it. So we can show email and.

268 00:22:16.630 ⇒ 00:22:22.150 Uttam Kumaran: The thing is that’s only gonna get better. That’s never gonna be worse. We’re only gonna get smarter there.

269 00:22:22.270 ⇒ 00:22:25.239 Uttam Kumaran: and that one works like if they have pool in their thing.

270 00:22:25.290 ⇒ 00:22:28.999 Uttam Kumaran: It’s not Joe. It’s not like Joe Pool. It’s like it’s a pool company.

271 00:22:29.000 ⇒ 00:22:44.075 Jakob Kagel: Exactly. So. I mean, yeah, that one makes sense like, you know, I don’t think we have to show that one but I think the I mean sort of to like the risk, or like what they’re gonna still maybe come back with is that like the pro account is too high?

272 00:22:44.360 ⇒ 00:22:46.250 Uttam Kumaran: From the from the self, identify.

273 00:22:46.250 ⇒ 00:22:49.295 Jakob Kagel: From the self identified. I mean, they’ve mentioned that in the last meeting.

274 00:22:49.530 ⇒ 00:22:50.310 Uttam Kumaran: High school.

275 00:22:50.310 ⇒ 00:22:56.660 Jakob Kagel: And that’s why I kind of think it would be good to have the split like on the question, because then you can also say, like.

276 00:22:56.980 ⇒ 00:23:02.130 Jakob Kagel: you know, this percentage of people answer this. I don’t know.

277 00:23:02.130 ⇒ 00:23:02.920 Uttam Kumaran: I mean I don’t.

278 00:23:03.149 ⇒ 00:23:05.210 Jakob Kagel: Go down that rabbit hole exactly, but it’s just.

279 00:23:05.210 ⇒ 00:23:12.459 Uttam Kumaran: I think it should be a mix of this and the pump cause that. Look if we do, if we do true here, and we do more than 2,

280 00:23:13.160 ⇒ 00:23:14.229 Uttam Kumaran: I mean, like

281 00:23:15.160 ⇒ 00:23:18.080 Uttam Kumaran: more than 2 orders, is already so small. Dude.

282 00:23:18.480 ⇒ 00:23:21.540 Jakob Kagel: Yeah, for sure. But that’s just cause you. The number is like smaller.

283 00:23:21.540 ⇒ 00:23:26.559 Uttam Kumaran: Oh, so we would do like, so yeah, more than 2 orders, only 365.

284 00:23:26.560 ⇒ 00:23:27.040 Jakob Kagel: Yeah.

285 00:23:27.040 ⇒ 00:23:28.659 Uttam Kumaran: But that’s good, which means like, look.

286 00:23:28.990 ⇒ 00:23:31.299 Uttam Kumaran: that’s like a 3, rd 2 thirds of it.

287 00:23:32.020 ⇒ 00:23:35.389 Uttam Kumaran: 2 thirds of more than 2 orders, self identified, which is great.

288 00:23:36.330 ⇒ 00:23:36.790 Jakob Kagel: Okay.

289 00:23:36.790 ⇒ 00:23:43.289 Uttam Kumaran: You know what I mean? So 200 6,269 out of 365 self identified is true.

290 00:23:43.980 ⇒ 00:23:57.959 Jakob Kagel: Right exactly. I mean, you can even take the 2 orders like, you know, and the 2 orders, plus or whatever like. I don’t think that you know that would be like 2,000 or something that would be a good segment. I’m not saying what we should do. I’m just saying like, you know, if they.

291 00:23:57.960 ⇒ 00:23:58.909 Uttam Kumaran: Like a less.

292 00:23:59.410 ⇒ 00:24:00.100 Jakob Kagel: Right?

293 00:24:00.290 ⇒ 00:24:04.909 Jakob Kagel: And they wanted to say, like, Okay, these people are, you know.

294 00:24:05.100 ⇒ 00:24:06.550 Jakob Kagel: more high value.

295 00:24:06.560 ⇒ 00:24:15.533 Jakob Kagel: But this is good. And this is exactly like what I’m talking about, because it’s like if we look at all like the 2 ordered, like the 2 orders, more than 2 orders, and then

296 00:24:15.790 ⇒ 00:24:16.440 Uttam Kumaran: But bring.

297 00:24:17.020 ⇒ 00:24:20.449 Jakob Kagel: The one order. It’s like all that ties out to like 13 K.

298 00:24:20.693 ⇒ 00:24:21.180 Uttam Kumaran: She did.

299 00:24:21.180 ⇒ 00:24:22.750 Jakob Kagel: So it’s like it. It’s.

300 00:24:23.145 ⇒ 00:24:23.540 Uttam Kumaran: Trial!

301 00:24:23.540 ⇒ 00:24:24.830 Jakob Kagel: The overall number. Yeah.

302 00:24:24.830 ⇒ 00:24:29.810 Uttam Kumaran: So so I think probably where we’ll end up is like we definitely do the

303 00:24:30.990 ⇒ 00:24:33.530 Uttam Kumaran: well, the email domain flagged

304 00:24:34.440 ⇒ 00:24:35.160 Uttam Kumaran: now.

305 00:24:35.750 ⇒ 00:24:38.059 Uttam Kumaran: So it’s it’s always gonna be an or.

306 00:24:39.190 ⇒ 00:24:41.649 Nicolas Sucari: So you you need to. Yeah, yes.

307 00:24:43.960 ⇒ 00:24:52.349 Nicolas Sucari: if if you are self identified or you are true on that email domain flag, you need to be like you need to aggregate that number to see like.

308 00:24:52.350 ⇒ 00:24:52.990 Uttam Kumaran: How’s that?

309 00:24:52.990 ⇒ 00:24:54.249 Nicolas Sucari: He’s pulled for a true.

310 00:24:54.527 ⇒ 00:24:58.410 Uttam Kumaran: Here’s here’s the best example, like for people that had more than 2 pumps.

311 00:24:59.240 ⇒ 00:25:00.720 Uttam Kumaran: It’s really

312 00:25:01.120 ⇒ 00:25:05.530 Uttam Kumaran: talent, right? But for people that have like one pump order.

313 00:25:05.760 ⇒ 00:25:07.350 Uttam Kumaran: It’s not really that telling.

314 00:25:07.350 ⇒ 00:25:10.360 Jakob Kagel: No, definitely, not exactly. The one orders is that.

315 00:25:10.360 ⇒ 00:25:12.420 Uttam Kumaran: 2. It’s getting better.

316 00:25:12.679 ⇒ 00:25:21.400 Uttam Kumaran: We look at 2 orders. It’s getting better if we look at if we, that’s more than 2. If we look at just 2. It’s still pretty good, so I think 2 orders, maybe.

317 00:25:22.530 ⇒ 00:25:32.410 Jakob Kagel: I think 2 orders makes the most sense. But I’m not gonna tell them what to do. Basically, I think we should just show them, you know. I don’t know. We could hide them in that direction for sure. I think it’s fine. Yeah.

318 00:25:33.063 ⇒ 00:25:34.010 Jakob Kagel: I’m here.

319 00:25:34.010 ⇒ 00:25:41.409 Nicolas Sucari: So if if we want to like kind of storytelling stuff like to see okay in the past 2 years we had.

320 00:25:41.460 ⇒ 00:25:44.140 Nicolas Sucari: how many like total orders.

321 00:25:44.410 ⇒ 00:25:49.820 Nicolas Sucari: and then from that total orders, how many have been self identified as pool pros?

322 00:25:49.830 ⇒ 00:25:52.409 Nicolas Sucari: How we? How could we do that?

323 00:25:53.530 ⇒ 00:25:57.550 Uttam Kumaran: So what if I, if I bring it in here, does it end up working out like what

324 00:25:58.340 ⇒ 00:25:59.319 Uttam Kumaran: they do here?

325 00:25:59.550 ⇒ 00:26:00.110 Jakob Kagel: Yeah, I mean.

326 00:26:00.110 ⇒ 00:26:00.810 Uttam Kumaran: Bring it.

327 00:26:01.940 ⇒ 00:26:03.690 Uttam Kumaran: Is it kind of hard to see.

328 00:26:06.510 ⇒ 00:26:08.589 Nicolas Sucari: Not, as you can see.

329 00:26:08.590 ⇒ 00:26:11.749 Jakob Kagel: The the the visuals are kind of better, but.

330 00:26:11.750 ⇒ 00:26:12.500 Uttam Kumaran: In color.

331 00:26:12.500 ⇒ 00:26:15.517 Jakob Kagel: I don’t know. I don’t mind the table view, either. To be honest.

332 00:26:15.750 ⇒ 00:26:16.540 Nicolas Sucari: Yeah.

333 00:26:19.840 ⇒ 00:26:20.590 Uttam Kumaran: Oh, she’s

334 00:26:20.710 ⇒ 00:26:21.520 Uttam Kumaran: time!

335 00:26:21.690 ⇒ 00:26:30.560 Jakob Kagel: What’s good, too, is like a lot of times like with like these type of things. I don’t know how easy this is to do in real. But like, I mean, I’m assuming it’s not done.

336 00:26:30.570 ⇒ 00:26:34.270 Jakob Kagel: It’s just to change some of these to like percent values, too.

337 00:26:35.700 ⇒ 00:26:37.919 Jakob Kagel: A lot of business people like

338 00:26:38.190 ⇒ 00:26:58.170 Jakob Kagel: they also kind of like to. I I think we should definitely care about like, you know, the total number and like, make sure that ties out and everything. But like a lot of them, they care about like, yeah, the percent, you know. And it’s sort of easier to to see. Like, okay, 13 and 19. It’s like, okay, or 13 and 9. It’s like, I have to do that math in my head. I’m like, Okay, that’s like, I don’t know.

339 00:26:58.170 ⇒ 00:26:59.600 Nicolas Sucari: Yeah, but you cannot. Yeah.

340 00:26:59.907 ⇒ 00:27:02.210 Nicolas Sucari: But here we can see the percentage. Yeah.

341 00:27:03.050 ⇒ 00:27:06.610 Jakob Kagel: So I think that’s a good like thing to have for sure in here.

342 00:27:06.610 ⇒ 00:27:09.579 Uttam Kumaran: So I’m gonna save this as like a report.

343 00:27:09.600 ⇒ 00:27:11.210 Uttam Kumaran: Basically, this is perfect.

344 00:27:11.210 ⇒ 00:27:16.539 Jakob Kagel: Right here, and we can build the whole notion page like, just off of this. Right here is great, I think.

345 00:27:17.830 ⇒ 00:27:18.520 Jakob Kagel: Cat.

346 00:27:22.140 ⇒ 00:27:23.440 Jakob Kagel: So yeah, let’s say.

347 00:27:24.700 ⇒ 00:27:25.360 Uttam Kumaran: That ball.

348 00:27:25.770 ⇒ 00:27:28.559 Uttam Kumaran: So so again, the thing that, yeah, go ahead.

349 00:27:28.560 ⇒ 00:27:30.880 Nicolas Sucari: Okay, go no. No. Go ahead. Go ahead. Sorry.

350 00:27:30.880 ⇒ 00:27:33.963 Uttam Kumaran: Yeah, the big thing is just like, I wanna make sure that

351 00:27:34.590 ⇒ 00:27:39.780 Uttam Kumaran: So the couple of things that are gonna that are gonna come up again is like, why, for example.

352 00:27:39.870 ⇒ 00:27:42.849 Uttam Kumaran: when I, when we do true, for like

353 00:27:43.560 ⇒ 00:27:47.279 Uttam Kumaran: 2 orders, there’s still people that have one order, it’s because of

354 00:27:47.390 ⇒ 00:27:48.400 Uttam Kumaran: dialect

355 00:27:48.610 ⇒ 00:27:52.769 Uttam Kumaran: rolling thing. You see what I mean. Like, someone could have one order.

356 00:27:53.210 ⇒ 00:27:55.360 Uttam Kumaran: and like a 3, 65 day.

357 00:27:55.570 ⇒ 00:28:02.010 Uttam Kumaran: some somewhere could have 2 orders in 365 day, and then have one order in another 365 day, so they could account for both.

358 00:28:02.240 ⇒ 00:28:03.389 Uttam Kumaran: Do you see what I mean?

359 00:28:04.350 ⇒ 00:28:06.760 Uttam Kumaran: That’s the discussion we were having like these aren’t.

360 00:28:06.760 ⇒ 00:28:07.190 Nicolas Sucari: Yeah, but.

361 00:28:07.190 ⇒ 00:28:08.679 Uttam Kumaran: Segments. These are overlapping.

362 00:28:08.890 ⇒ 00:28:10.480 Jakob Kagel: Hmm, okay.

363 00:28:10.860 ⇒ 00:28:13.390 Nicolas Sucari: Why, we can’t just make them distinct.

364 00:28:13.390 ⇒ 00:28:14.360 Jakob Kagel: Yeah, because.

365 00:28:14.360 ⇒ 00:28:15.040 Uttam Kumaran: Does.

366 00:28:15.300 ⇒ 00:28:16.369 Jakob Kagel: So I go ahead.

367 00:28:16.370 ⇒ 00:28:18.790 Uttam Kumaran: The definition is a rolling windows.

368 00:28:20.400 ⇒ 00:28:21.000 Nicolas Sucari: That.

369 00:28:21.000 ⇒ 00:28:24.929 Jakob Kagel: Still have the logic as equal to one. That’s the thing.

370 00:28:25.020 ⇒ 00:28:32.420 Jakob Kagel: So I’m like, I don’t know. I have to check it right like, but I’m not so convinced that they’re overlapping.

371 00:28:32.740 ⇒ 00:28:37.159 Uttam Kumaran: But it’s it’s it’s calculates for every start and end date difference. But the thing.

372 00:28:37.160 ⇒ 00:28:37.610 Nicolas Sucari: Yeah. No.

373 00:28:37.610 ⇒ 00:28:39.450 Uttam Kumaran: Join is on the start and end date.

374 00:28:39.520 ⇒ 00:28:42.540 Uttam Kumaran: So it it you will land in both.

375 00:28:45.980 ⇒ 00:28:55.656 Jakob Kagel: Okay, cause like, in a 2 year period, like, what’s like, how could you have like an overlap of 2 years where they don’t overlap like, you know.

376 00:28:55.990 ⇒ 00:28:57.279 Uttam Kumaran: Yeah, yeah, in our show, actually.

377 00:28:57.280 ⇒ 00:29:06.909 Jakob Kagel: They would literally have to be on the 1st day of like the New Year, because any other way that you slice it, they’re going to be overlapping somehow.

378 00:29:10.370 ⇒ 00:29:12.549 Uttam Kumaran: So let’s say you have one order on like.

379 00:29:13.230 ⇒ 00:29:16.039 Uttam Kumaran: let’s do. 6, 1,

380 00:29:17.560 ⇒ 00:29:19.070 Uttam Kumaran: 23.

381 00:29:19.130 ⇒ 00:29:21.339 Uttam Kumaran: Put me on order on like 6,

382 00:29:21.510 ⇒ 00:29:22.490 Uttam Kumaran: one.

383 00:29:22.870 ⇒ 00:29:23.830 Uttam Kumaran: 24,

384 00:29:24.530 ⇒ 00:29:27.759 Uttam Kumaran: right? So in a 2 year.

385 00:29:28.170 ⇒ 00:29:34.550 Uttam Kumaran: Okay, actually, this is the best way of doing this. But like, okay, let’s say, let’s say we have, like a

386 00:29:34.560 ⇒ 00:29:36.520 Uttam Kumaran: our flag for 2,

387 00:29:36.660 ⇒ 00:29:41.399 Uttam Kumaran: 2 orders in 365. It’s gonna be true, right?

388 00:29:42.746 ⇒ 00:29:46.560 Uttam Kumaran: Because, let’s say, let’s say the example is

389 00:29:47.040 ⇒ 00:29:49.439 Uttam Kumaran: like June to June.

390 00:29:50.580 ⇒ 00:29:53.020 Uttam Kumaran: Now, what about one order in 3, 65?

391 00:29:55.000 ⇒ 00:29:56.479 Uttam Kumaran: It’s also true, because.

392 00:29:56.480 ⇒ 00:29:57.770 Jakob Kagel: No, it’s not.

393 00:29:58.040 ⇒ 00:29:59.419 Uttam Kumaran: Yeah, because you could, you could have.

394 00:29:59.715 ⇒ 00:30:02.370 Jakob Kagel: June 1st to June 1st is 3, 65

395 00:30:02.670 ⇒ 00:30:04.960 Jakob Kagel: like that’s not 66.

396 00:30:05.080 ⇒ 00:30:07.407 Uttam Kumaran: But you could have. You could have

397 00:30:09.346 ⇒ 00:30:15.069 Jakob Kagel: 366 like it’s it’s it’s not 2 orders, but it’s 365.

398 00:30:15.950 ⇒ 00:30:26.349 Nicolas Sucari: i i i i know what you’re saying. Good. I’m probably it’s gonna be true if you look for one year period. But we should exclude that customers, or that clients that already are

399 00:30:26.510 ⇒ 00:30:28.529 Nicolas Sucari: like contained in the 2 year.

400 00:30:29.180 ⇒ 00:30:30.480 Nicolas Sucari: In the 2 year period.

401 00:30:30.480 ⇒ 00:30:35.730 Jakob Kagel: 7, 1, yeah, 7, 1 to 7, 1 is 365. It’s not. It’s not like.

402 00:30:36.070 ⇒ 00:30:39.039 Jakob Kagel: So it’s going to be 2 orders in 3, 65.

403 00:30:39.310 ⇒ 00:30:39.940 Jakob Kagel: But it’s not.

404 00:30:39.940 ⇒ 00:30:41.530 Uttam Kumaran: Looking at any.

405 00:30:44.000 ⇒ 00:30:47.200 Uttam Kumaran: No, but you do. You do qualify for both.

406 00:30:47.900 ⇒ 00:30:49.269 Nicolas Sucari: Yeah, but can can we know?

407 00:30:49.270 ⇒ 00:30:49.670 Jakob Kagel: The of the.

408 00:30:49.670 ⇒ 00:30:50.610 Nicolas Sucari: And wouldn’t. Yeah.

409 00:30:50.610 ⇒ 00:30:58.750 Jakob Kagel: Equal to one like you. It’s equal like it’s case when the count of orders like like you, you’re counting. The 1st thing you gotta do. Here is what is the count of orders?

410 00:30:58.750 ⇒ 00:30:59.400 Uttam Kumaran: Kind of.

411 00:30:59.400 ⇒ 00:31:00.539 Jakob Kagel: Orders is 2.

412 00:31:00.840 ⇒ 00:31:01.210 Uttam Kumaran: Rangers.

413 00:31:01.210 ⇒ 00:31:01.790 Jakob Kagel: It’s equally.

414 00:31:01.790 ⇒ 00:31:02.550 Uttam Kumaran: Then sure

415 00:31:02.650 ⇒ 00:31:06.510 Uttam Kumaran: the join is on. The join is on this.

416 00:31:06.820 ⇒ 00:31:11.839 Uttam Kumaran: which means for every we calculate for every customer, for every end, date.

417 00:31:12.230 ⇒ 00:31:12.800 Jakob Kagel: Right. I will.

418 00:31:12.800 ⇒ 00:31:13.990 Uttam Kumaran: End up in boss.

419 00:31:14.160 ⇒ 00:31:18.600 Jakob Kagel: But in a 2 year period no end date can fall out of both

420 00:31:18.730 ⇒ 00:31:27.910 Jakob Kagel: like there’s not an example like, think about it like, okay, whatever. May 23, rd 2,023. It’s like

421 00:31:27.970 ⇒ 00:31:35.880 Jakob Kagel: from May 23rd to May 23rd the next year, and then anything outside of that is not 365, unless you slice it down.

422 00:31:36.210 ⇒ 00:31:40.162 Uttam Kumaran: So let’s look at. Let’s let’s let’s pick an example of someone that that’s in both.

423 00:31:40.410 ⇒ 00:31:49.889 Jakob Kagel: Pick like one actual example and show me like, show me in the table what’s the table is is shopify customers right? Let’s do it. We can just query it right now, cause we can.

424 00:31:49.890 ⇒ 00:31:51.280 Uttam Kumaran: Exciting.

425 00:31:51.280 ⇒ 00:31:52.170 Jakob Kagel: Wouldn’t want.

426 00:31:52.930 ⇒ 00:31:54.986 Uttam Kumaran: So we’re looking for folks that are

427 00:31:55.840 ⇒ 00:31:56.550 Uttam Kumaran: Nigel.

428 00:31:58.280 ⇒ 00:32:02.640 Uttam Kumaran: Where this is true and the one order is true, right? So both these are true.

429 00:32:02.640 ⇒ 00:32:05.080 Jakob Kagel: Can just query it real quick. Hold on

430 00:32:05.930 ⇒ 00:32:08.310 Jakob Kagel: so where

431 00:32:09.060 ⇒ 00:32:17.040 Jakob Kagel: and it’s what’s what’s the field called? It’s called is pool pro one general order, right.

432 00:32:17.040 ⇒ 00:32:17.890 Uttam Kumaran: Yeah.

433 00:32:17.890 ⇒ 00:32:20.269 Jakob Kagel: For the one, and then

434 00:32:21.250 ⇒ 00:32:25.739 Jakob Kagel: is pool pro 2 orders equal to one right.

435 00:32:26.750 ⇒ 00:32:27.340 Uttam Kumaran: let’s see.

436 00:32:27.340 ⇒ 00:32:27.940 Jakob Kagel: He

437 00:32:31.570 ⇒ 00:32:33.600 Jakob Kagel: is pool pro.

438 00:32:33.600 ⇒ 00:32:34.130 Uttam Kumaran: Break in.

439 00:32:34.130 ⇒ 00:32:36.842 Jakob Kagel: Do general orders. Okay? What a 1.

440 00:32:37.230 ⇒ 00:32:38.500 Uttam Kumaran: It wasn’t like super.

441 00:32:38.680 ⇒ 00:32:39.320 Jakob Kagel: See.

442 00:32:39.320 ⇒ 00:32:40.332 Uttam Kumaran: Do it like.

443 00:32:40.670 ⇒ 00:32:44.519 Jakob Kagel: I’m doing count distinct customer. Id. Let’s see. Alright.

444 00:32:46.760 ⇒ 00:32:53.270 Jakob Kagel: Okay, there’s 66 customers, whereas but that’s only the ones that can then fall on that one day

445 00:32:53.500 ⇒ 00:32:56.469 Jakob Kagel: like, so that’s yeah. I mean, there’s 66.

446 00:32:56.470 ⇒ 00:32:57.650 Uttam Kumaran: What about this example?

447 00:32:57.650 ⇒ 00:32:59.429 Jakob Kagel: My customers table.

448 00:33:00.210 ⇒ 00:33:01.090 Jakob Kagel: Yeah.

449 00:33:03.910 ⇒ 00:33:15.750 Jakob Kagel: So I’m not that concerned about that. I mean, that’s yeah. That’s like, maybe an edge case, because it’s like, yeah, that one day, like, I guess, maybe technically like June first, st or something is a new 3, 65 degree period.

450 00:33:15.920 ⇒ 00:33:22.359 Uttam Kumaran: So here. But here’s an example. This is one order, and the 2 order flow. If we go to shopify, this person fits in that

451 00:33:22.370 ⇒ 00:33:24.580 Uttam Kumaran: category. So what’s going on here.

452 00:33:26.180 ⇒ 00:33:29.060 Jakob Kagel: Well, this one says, what 2 items!

453 00:33:30.400 ⇒ 00:33:31.810 Jakob Kagel: And they’re in both.

454 00:33:32.130 ⇒ 00:33:32.730 Uttam Kumaran: Yeah.

455 00:33:34.000 ⇒ 00:33:38.654 Jakob Kagel: Well, I guess maybe they’re one of the 66. But yeah, I don’t know. April 7, th and then.

456 00:33:38.900 ⇒ 00:33:40.030 Uttam Kumaran: What’s up?

457 00:33:40.030 ⇒ 00:33:42.990 Jakob Kagel: Other one June 18, th but it doesn’t say what year.

458 00:33:43.920 ⇒ 00:33:45.040 Uttam Kumaran: It’s coming this year.

459 00:33:45.250 ⇒ 00:33:46.309 Jakob Kagel: This year, okay.

460 00:33:46.310 ⇒ 00:33:50.120 Uttam Kumaran: This is this year. This is April 7, 23. This is Jan. 1123.

461 00:33:50.900 ⇒ 00:33:52.039 Uttam Kumaran: So why, it’s.

462 00:33:52.040 ⇒ 00:33:58.730 Jakob Kagel: June. Okay, so June should be yet to June 23, and then April 23

463 00:33:58.840 ⇒ 00:34:00.270 Jakob Kagel: to April.

464 00:34:00.400 ⇒ 00:34:01.980 Jakob Kagel: Tony, you know.

465 00:34:02.770 ⇒ 00:34:06.989 Jakob Kagel: But that’s 22 is like outside of the 2 year period. Then.

466 00:34:06.990 ⇒ 00:34:09.870 Nicolas Sucari: No, no, I think it’s June June 24.th

467 00:34:09.870 ⇒ 00:34:10.489 Uttam Kumaran: Why is.

468 00:34:10.940 ⇒ 00:34:23.740 Jakob Kagel: But then it would be yeah. It would be April to April. So that would that should overlap. Then, yeah, because the period start date April 23, end date April 24. Start, date June

469 00:34:24.000 ⇒ 00:34:30.979 Jakob Kagel: 24, to the current, or like to June 23, so they would overlap in that 365.

470 00:34:31.389 ⇒ 00:34:32.089 Jakob Kagel: Your peers.

471 00:34:32.090 ⇒ 00:34:33.590 Uttam Kumaran: So let me grab, let me grab.

472 00:34:33.590 ⇒ 00:34:35.100 Jakob Kagel: Counted in one order.

473 00:34:35.969 ⇒ 00:34:38.164 Uttam Kumaran: Let me grab the sequel for

474 00:34:39.679 ⇒ 00:34:41.679 Uttam Kumaran: for this, and

475 00:34:41.829 ⇒ 00:34:45.749 Uttam Kumaran: we’ll run it with that customer, Id, and see what the see. See where the logic fails.

476 00:34:45.750 ⇒ 00:34:52.189 Jakob Kagel: I mean, where it fails is probably because you’re counting forward from June into like the I guess, like.

477 00:34:53.520 ⇒ 00:34:54.260 Uttam Kumaran: Gossip.

478 00:34:54.260 ⇒ 00:34:56.479 Jakob Kagel: Oh, be! That’s the only way it could fail. But.

479 00:34:56.489 ⇒ 00:34:57.249 Uttam Kumaran: Basically it’s like.

480 00:34:57.250 ⇒ 00:34:59.880 Jakob Kagel: You’re saying from June 23.rd

481 00:34:59.880 ⇒ 00:35:00.550 Uttam Kumaran: Chat.

482 00:35:00.550 ⇒ 00:35:07.460 Jakob Kagel: Like June 24 to June 23 is not in April, but if you’re counting April as the start date

483 00:35:07.750 ⇒ 00:35:08.820 Jakob Kagel: like.

484 00:35:09.950 ⇒ 00:35:12.909 Jakob Kagel: and June is the end date, because it’s like

485 00:35:13.260 ⇒ 00:35:16.939 Jakob Kagel: technically, that 300. Well, no.

486 00:35:17.180 ⇒ 00:35:18.220 Jakob Kagel: no, I don’t know.

487 00:35:18.220 ⇒ 00:35:20.145 Uttam Kumaran: Let me try. Let me try something.

488 00:35:20.420 ⇒ 00:35:21.340 Jakob Kagel: Brian. Me

489 00:35:22.230 ⇒ 00:35:23.230 Jakob Kagel: good luck.

490 00:35:24.453 ⇒ 00:35:25.100 Nicolas Sucari: Let me.

491 00:35:25.280 ⇒ 00:35:38.489 Nicolas Sucari: What I think is this case is happening. Is he bought something in June 24. So if if we take that date as like the start, the the end date, if you want, and we go back to June 23, it should.

492 00:35:38.490 ⇒ 00:35:39.170 Jakob Kagel: But that’s yeah.

493 00:35:39.170 ⇒ 00:35:40.139 Nicolas Sucari: One order.

494 00:35:40.470 ⇒ 00:35:42.080 Jakob Kagel: This is one order. Yeah.

495 00:35:42.080 ⇒ 00:35:51.559 Nicolas Sucari: Yeah, it’s just one order. And then when you go to the 2 year period, it goes to the second order. So that’s why it’s in both, because it takes the end date as the.

496 00:35:51.830 ⇒ 00:35:52.620 Uttam Kumaran: Are all married.

497 00:35:52.620 ⇒ 00:35:54.559 Nicolas Sucari: Starting from, and then go back.

498 00:35:54.710 ⇒ 00:36:15.919 Jakob Kagel: But now I’m like that actually like that shouldn’t be 2 orders like that should only be one order, because the is the start date, like the order date, and the end date is like 365 days from the order, or is it the other way? Where it’s like the end date is the order date, and you’re taking 365 days back as the start date.

499 00:36:15.920 ⇒ 00:36:19.619 Uttam Kumaran: I’m taking that. That’s the second one. It’s just it’s a rolling window. Yeah.

500 00:36:19.620 ⇒ 00:36:35.340 Jakob Kagel: Right. So then, if it’s 365 days back, then you have one order. In the June period, from June 24, one order in the April period, which is April 23 to April 22, which don’t overlap.

501 00:36:35.590 ⇒ 00:36:38.840 Jakob Kagel: so that should not be 2 orders. Then.

502 00:36:39.170 ⇒ 00:36:40.440 Uttam Kumaran: But these 2 overlap.

503 00:36:40.710 ⇒ 00:36:42.840 Jakob Kagel: Okay. So they have 3 orders. Okay?

504 00:36:43.120 ⇒ 00:36:44.160 Uttam Kumaran: These do overlap.

505 00:36:44.160 ⇒ 00:36:45.899 Jakob Kagel: Okay, so that’s why. Yeah.

506 00:36:46.330 ⇒ 00:36:55.900 Jakob Kagel: But then, okay, so now we’re introducing January. So now, if we say in January through, if we’re saying the order. Count is 3 now, and we’re saying it’s in January. Then.

507 00:36:56.390 ⇒ 00:36:57.030 Jakob Kagel: one way.

508 00:36:57.802 ⇒ 00:37:10.070 Nicolas Sucari: No, it. It’s it’s 1 order in the last 30 in the, in a period of 3, 65 year. Yeah. One order in the period of 2 years of one year and 2 orders in the period of the the other year before that.

509 00:37:10.462 ⇒ 00:37:23.030 Jakob Kagel: January. Now, January is before April, so if you take a 365 day P. There’s no period now with January in there, where they have only made one order.

510 00:37:23.030 ⇒ 00:37:26.940 Nicolas Sucari: Yeah, yeah, because, yeah, I know. No, it’s 2 orders. There. Yeah, exactly.

511 00:37:26.940 ⇒ 00:37:32.019 Jakob Kagel: Right? So there’s No. 365 day period in there that only has one order. So it has.

512 00:37:32.020 ⇒ 00:37:39.419 Nicolas Sucari: Yeah, yeah, yeah, no, no. It has one order. Ja, June 24, to June 23. It’s just one order.

513 00:37:39.580 ⇒ 00:37:40.150 Uttam Kumaran: Yeah.

514 00:37:40.950 ⇒ 00:37:56.369 Nicolas Sucari: Exactly. That’s why you yeah, that’s why it is in both. It has 2 orders in the period between April 23 and April 22 and one order between June and June 24 and 23. That’s why it’s it’s it’s on both. But what we, what we need to do, I think is.

515 00:37:56.370 ⇒ 00:37:57.290 Uttam Kumaran: Yeah, just.

516 00:37:57.290 ⇒ 00:38:06.039 Nicolas Sucari: Take the the last order as as end date, and keep that end date, and look for that. The amount of orders

517 00:38:06.130 ⇒ 00:38:11.549 Nicolas Sucari: like back from that end date for 365 or 2 years.

518 00:38:11.550 ⇒ 00:38:18.399 Jakob Kagel: Okay, you’re right. You’re right. No, that makes sense. Okay, so it can be both. But it’s still a very, very small amount that are.

519 00:38:18.400 ⇒ 00:38:20.479 Uttam Kumaran: But I guess, like, what should we

520 00:38:21.810 ⇒ 00:38:22.890 Uttam Kumaran: like?

521 00:38:23.330 ⇒ 00:38:28.760 Uttam Kumaran: Even the even the thing that we decided, which is like in one year in the last 2 years is arbitrary.

522 00:38:29.120 ⇒ 00:38:36.269 Jakob Kagel: Right. I mean I I am. I I gotta say in general I’m not a huge, even though we have like a super small overlap right now.

523 00:38:36.350 ⇒ 00:38:40.539 Jakob Kagel: I’m not a huge fan of like having these groups overlap

524 00:38:40.620 ⇒ 00:38:42.180 Jakob Kagel: kind of, because.

525 00:38:42.180 ⇒ 00:38:42.900 Uttam Kumaran: Back, to.

526 00:38:42.900 ⇒ 00:38:43.880 Jakob Kagel: I don’t know.

527 00:38:44.290 ⇒ 00:38:50.760 Uttam Kumaran: Why don’t we just do? Why don’t we just do? And and why don’t we just do in the 2 year period? 1, 2, 2, plus.

528 00:38:53.660 ⇒ 00:39:02.189 Jakob Kagel: I think it’s fine. Let’s leave it with the 365 in any cause that’s more comprehensive, and I think the overlap is small and I don’t think it’s like.

529 00:39:02.190 ⇒ 00:39:03.030 Uttam Kumaran: Unlucky.

530 00:39:03.030 ⇒ 00:39:12.919 Jakob Kagel: As long as we know that they overlap. I don’t think it’s like as much of an issue. It’s more like, just for our awareness that like, yeah, you can be in both. But it’s unlike. It’s still unlikely.

531 00:39:12.990 ⇒ 00:39:17.729 Jakob Kagel: like there’s only 66 people that are have one order and 2 that have.

532 00:39:18.129 ⇒ 00:39:26.509 Uttam Kumaran: I think that I think I think a year is important as a window, because of this seasonality in the business.

533 00:39:26.760 ⇒ 00:39:27.809 Jakob Kagel: I agree.

534 00:39:29.330 ⇒ 00:39:29.880 Uttam Kumaran: But

535 00:39:31.420 ⇒ 00:39:32.880 Uttam Kumaran: I also.

536 00:39:39.320 ⇒ 00:39:45.781 Jakob Kagel: I mean, that’s why I did everything on a year likes. I’d always do every like trailing 12 months or more like the most like.

537 00:39:46.040 ⇒ 00:39:49.610 Uttam Kumaran: I wonder, I wonder if like, for so in so in this case.

538 00:39:49.650 ⇒ 00:39:52.330 Uttam Kumaran: let’s take this example, because there’s actually what

539 00:39:53.110 ⇒ 00:39:57.300 Uttam Kumaran: this is, what the home is telling us to do is is basically saying.

540 00:39:57.460 ⇒ 00:40:00.939 Uttam Kumaran: See how there is 2 and 1, 3, 6, 5. Just call this a 2.

541 00:40:02.510 ⇒ 00:40:05.710 Jakob Kagel: That’s what I’m saying, like, you know, because.

542 00:40:06.060 ⇒ 00:40:07.489 Uttam Kumaran: Like don’t don’t call it a lot.

543 00:40:07.490 ⇒ 00:40:10.290 Jakob Kagel: I mean this one, too. It’s like, think about it. It’s like

544 00:40:10.570 ⇒ 00:40:22.609 Jakob Kagel: you. Okay, you have 1, 3, 65, where you have one, and you have 1, 3, 65, where you have 2. You’re a 2 like you had 2 orders in a 365 year period in the last 2 years.

545 00:40:22.610 ⇒ 00:40:23.170 Uttam Kumaran: Okay.

546 00:40:23.480 ⇒ 00:40:30.980 Jakob Kagel: We also had one order in a separate 365. But right like you’re a 2 right? Like we, we would say, don’t you all agree.

547 00:40:31.180 ⇒ 00:40:31.650 Uttam Kumaran: Yes.

548 00:40:31.650 ⇒ 00:40:32.480 Jakob Kagel: Yeah.

549 00:40:32.480 ⇒ 00:40:33.060 Uttam Kumaran: Yeah.

550 00:40:33.210 ⇒ 00:40:35.519 Uttam Kumaran: I think like I think we should.

551 00:40:35.780 ⇒ 00:40:38.680 Uttam Kumaran: But the the I think we should, if you like.

552 00:40:38.870 ⇒ 00:40:42.350 Uttam Kumaran: The reason the business case for why is that

553 00:40:42.820 ⇒ 00:40:44.849 Uttam Kumaran: at at some point you had

554 00:40:45.100 ⇒ 00:40:46.300 Uttam Kumaran: a recurring order

555 00:40:46.888 ⇒ 00:40:51.030 Uttam Kumaran: on a in a yearly cadence. And so, maybe, even though you missed, maybe you missed

556 00:40:51.260 ⇒ 00:40:54.310 Uttam Kumaran: another year. It’s fine. We’re just gonna count you.

557 00:40:54.310 ⇒ 00:40:56.449 Jakob Kagel: Yeah, we’re we’re just gonna count you

558 00:40:56.510 ⇒ 00:41:04.780 Jakob Kagel: like, I, I I do agree with that. I have to say, like, Yeah, I think it’s better like to count them as a 2, and like, have them be sort of like

559 00:41:04.810 ⇒ 00:41:06.100 Jakob Kagel: distinct groups.

560 00:41:06.640 ⇒ 00:41:07.345 Uttam Kumaran: So

561 00:41:08.930 ⇒ 00:41:20.229 Jakob Kagel: Because it’s like, if you do this like you have to think about this like I don’t know in the future to I mean, this is a little bit in the future or whatnot, but like, if we expanded this to 3 years and said, 365, we might have a lot of overlap, you know.

562 00:41:20.230 ⇒ 00:41:20.880 Uttam Kumaran: Yeah, yeah, yeah.

563 00:41:20.880 ⇒ 00:41:30.640 Jakob Kagel: Talking about like a lot bigger time period, like when it’s only 2 years like, you know, this is very. There’s like a really sort of like small window, basically that this can happen.

564 00:41:32.510 ⇒ 00:41:34.550 Uttam Kumaran: So let’s see if it can help me write this, because I’m

565 00:41:34.981 ⇒ 00:41:38.109 Uttam Kumaran: not thinking about how we can do this.

566 00:41:47.130 ⇒ 00:41:48.110 Uttam Kumaran: counts.

567 00:41:49.690 ⇒ 00:41:51.249 Uttam Kumaran: I’ve been one day

568 00:41:51.270 ⇒ 00:41:52.980 Uttam Kumaran: 2 categories.

569 00:41:53.390 ⇒ 00:41:54.910 Uttam Kumaran: It’s built. For example.

570 00:41:58.070 ⇒ 00:42:00.539 Uttam Kumaran: I’m trying to even word this like

571 00:42:00.730 ⇒ 00:42:04.480 Uttam Kumaran: I guess I don’t cause I don’t know exactly what I would change here like cause

572 00:42:10.880 ⇒ 00:42:12.790 Jakob Kagel: I think you just have to like you.

573 00:42:12.790 ⇒ 00:42:13.990 Uttam Kumaran: Movies, Maxes.

574 00:42:13.990 ⇒ 00:42:22.899 Jakob Kagel: But the way I would do it is like, do once you have all the flags like in a table, right in a Ct. Or whatever

575 00:42:23.110 ⇒ 00:42:24.700 Jakob Kagel: you just say, like.

576 00:42:24.790 ⇒ 00:42:33.370 Jakob Kagel: when you have the the 2 order flag and the one order flag, you just create a new column, or whatever, as like the final version of the 2 order.

577 00:42:33.370 ⇒ 00:42:34.100 Uttam Kumaran: Least.

578 00:42:34.100 ⇒ 00:42:44.251 Jakob Kagel: Hey, this one like case when this is one, and this is one you’re you know you’re this. But if it’s 0, and this is one like you’re still that.

579 00:42:44.590 ⇒ 00:42:50.550 Uttam Kumaran: I think I know what to do. Let me just say it to this guy, and then I think I know exactly. I can do the logic?

580 00:42:50.730 ⇒ 00:42:52.399 Uttam Kumaran: No, like, basically, it’s like.

581 00:42:52.400 ⇒ 00:42:55.599 Jakob Kagel: I know we’ve been kind of like. This meeting’s been like all over the place, like.

582 00:42:55.600 ⇒ 00:42:57.310 Uttam Kumaran: No, no, no, dude, I think this is like.

583 00:42:57.310 ⇒ 00:42:59.619 Jakob Kagel: Like, we are actually being productive here.

584 00:42:59.620 ⇒ 00:43:01.340 Uttam Kumaran: Yeah, yeah, yeah, no. I’m fine.

585 00:43:01.340 ⇒ 00:43:07.709 Jakob Kagel: Okay, yeah, I know. Good, like, sometimes, like a little chaotic. But I feel like, yeah, we’re on the wrong.

586 00:43:07.710 ⇒ 00:43:17.289 Uttam Kumaran: No, no, yeah. I think I think we ended up like where we need to be. I mean again, like, yeah. So one of my favorites says someone’s 2 orders and has one order. They get counted as 2

587 00:43:17.310 ⇒ 00:43:20.189 Uttam Kumaran: basically go for the

588 00:43:21.050 ⇒ 00:43:24.100 Uttam Kumaran: iron logs. It’s not bad.

589 00:43:24.380 ⇒ 00:43:28.600 Jakob Kagel: Right. And and the logic would be like if you have 3 or like 2 plus.

590 00:43:28.870 ⇒ 00:43:37.059 Jakob Kagel: and you have to like, if that’s somehow possible which it technically could be possible. Right? I mean, probably not like you’re probably 0 in that. But

591 00:43:37.150 ⇒ 00:43:42.009 Jakob Kagel: I would just say like, then you take 2 plus likes has to supersede that, like, you know.

592 00:43:42.010 ⇒ 00:43:43.090 Uttam Kumaran: Yeah, yeah.

593 00:43:44.640 ⇒ 00:43:46.310 Uttam Kumaran: I think this is gonna do it.

594 00:43:46.670 ⇒ 00:43:47.420 Jakob Kagel: Sure

595 00:43:54.520 ⇒ 00:43:56.360 Jakob Kagel: the good old Gpt.

596 00:43:56.700 ⇒ 00:43:57.910 Jakob Kagel: It’s amazing.

597 00:43:58.340 ⇒ 00:44:02.630 Uttam Kumaran: Dude. It just helps me think through some of these things where I’m like dude. I would have sat really 4 h.

598 00:44:03.190 ⇒ 00:44:03.820 Uttam Kumaran: and it’s got it.

599 00:44:03.820 ⇒ 00:44:05.550 Jakob Kagel: And college. Could you imagine.

600 00:44:05.550 ⇒ 00:44:07.670 Uttam Kumaran: No, I would not be.

601 00:44:07.810 ⇒ 00:44:12.689 Uttam Kumaran: I would not have been. I would not have been here dude like I would have cheated on every fuck thing.

602 00:44:12.690 ⇒ 00:44:15.569 Jakob Kagel: Oh, we would have. Yeah, we would have crushed like, for sure.

603 00:44:15.570 ⇒ 00:44:18.600 Uttam Kumaran: I would have crushed, but then I would have been stupid like. I wouldn’t have been good.

604 00:44:18.600 ⇒ 00:44:22.939 Jakob Kagel: I don’t know like it doesn’t make you stupid or like, you know, I don’t know.

605 00:44:23.300 ⇒ 00:44:26.899 Jakob Kagel: I mean, there’s some stuff like think about. I don’t know. I wouldn’t go on a whole tangent, but.

606 00:44:26.900 ⇒ 00:44:30.669 Uttam Kumaran: No, no, no, I agree. I mean you know me. I’m pushing all of us to.

607 00:44:30.860 ⇒ 00:44:31.426 Jakob Kagel: Yeah. Autumn.

608 00:44:31.710 ⇒ 00:44:36.269 Uttam Kumaran: This guy cause dude, it’s gonna we’re gonna spend less time making more money

609 00:44:36.310 ⇒ 00:44:37.870 Uttam Kumaran: sound. That’s a.

610 00:44:38.270 ⇒ 00:44:45.380 Jakob Kagel: We can automate stuff. No, I’m with you for sure. I mean, it’s tricky, because it still can’t like, you know, it’s a lot of stuff that it can’t do. That’s kind of like specific to.

611 00:44:45.380 ⇒ 00:44:54.272 Uttam Kumaran: Let’s see also dude like I couldn’t I? If I didn’t know sequel, I can’t ask this question. I wouldn’t have been able to articulate this conversation so.

612 00:44:54.590 ⇒ 00:44:57.300 Jakob Kagel: Prompt, prompt engineering, component, or whatever.

613 00:44:57.300 ⇒ 00:45:02.246 Uttam Kumaran: It’s almost like it’s like you have to know everything. But then be like, I want to do this in 30 min instead of like 4 h.

614 00:45:02.430 ⇒ 00:45:04.799 Jakob Kagel: Yeah, yeah, for sure, basically, yeah.

615 00:45:04.800 ⇒ 00:45:10.829 Uttam Kumaran: I think we’re actually in a perfect spot like, because I think we learned everything. And now it’s like, Okay, cool. It’s just easy.

616 00:45:11.000 ⇒ 00:45:12.810 Uttam Kumaran: right. Imagine not learning it.

617 00:45:13.770 ⇒ 00:45:17.656 Jakob Kagel: Yeah, right? Cause? Yeah, it’s it’s different. Yeah, for sure.

618 00:45:18.010 ⇒ 00:45:22.259 Uttam Kumaran: Maybe there’s maybe maybe it’ll get to a point where, like you don’t have to know sequel, anyways. But

619 00:45:22.310 ⇒ 00:45:24.520 Uttam Kumaran: I get even to articulate the questions.

620 00:45:24.520 ⇒ 00:45:24.870 Jakob Kagel: But yeah.

621 00:45:24.870 ⇒ 00:45:25.200 Uttam Kumaran: Wish, in the.

622 00:45:25.200 ⇒ 00:45:40.640 Jakob Kagel: Yeah, you. Still, you may not have to know sequel, but you have to understand like the like conceptually like would like join tables and like unions, and like you know what I’m saying like, let me certain like language at least, that you’ll have to know it like to, you know.

623 00:45:40.930 ⇒ 00:45:41.430 Uttam Kumaran: Yeah.

624 00:45:41.430 ⇒ 00:45:42.210 Nicolas Sucari: And back.

625 00:45:42.400 ⇒ 00:45:43.940 Jakob Kagel: Denver. But anyway.

626 00:45:45.200 ⇒ 00:45:51.139 Jakob Kagel: yeah, I don’t know. Let’s maybe just talk about like the plan for the meeting tomorrow to here, like at the end.

627 00:45:51.140 ⇒ 00:46:00.365 Uttam Kumaran: So yeah, let me just yeah, keep going. If you do, you want to pull up a notion you could write in there. I’m just gonna run this. So we have, we can just take a look at it while it’s

628 00:46:01.100 ⇒ 00:46:01.740 Jakob Kagel: Okay.

629 00:46:02.380 ⇒ 00:46:03.400 Uttam Kumaran: Sure the numbers are right.

630 00:46:03.400 ⇒ 00:46:10.240 Jakob Kagel: Notion. Now do I? Should I do like add property? Or should I just add a comment? Or should I just type in the page.

631 00:46:10.590 ⇒ 00:46:12.065 Uttam Kumaran: Just type in the page.

632 00:46:12.360 ⇒ 00:46:13.670 Jakob Kagel: Sure, so.

633 00:46:15.550 ⇒ 00:46:20.250 Nicolas Sucari: Let me know if you, if you can type in the page, if not, I can give you some permissions.

634 00:46:20.250 ⇒ 00:46:21.636 Jakob Kagel: Working fine.

635 00:46:22.580 ⇒ 00:46:28.370 Jakob Kagel: okay? So basically, yes. So what we aligned on right is like, we want to show

636 00:46:28.780 ⇒ 00:46:30.610 Jakob Kagel: the 3 splits

637 00:46:31.150 ⇒ 00:46:32.830 Jakob Kagel: of orders

638 00:46:33.370 ⇒ 00:46:34.250 Jakob Kagel: plus

639 00:46:35.720 ⇒ 00:46:37.860 Jakob Kagel: self-identified coverage.

640 00:46:42.118 ⇒ 00:46:45.609 Jakob Kagel: And then we wanna do the same thing for

641 00:46:45.630 ⇒ 00:46:49.850 Jakob Kagel: the 3 orders or the 3 splits of orders with pumps.

642 00:46:52.340 ⇒ 00:46:53.790 Jakob Kagel: right? Okay.

643 00:46:55.610 ⇒ 00:46:57.589 Jakob Kagel: cool. And then.

644 00:46:58.540 ⇒ 00:47:06.942 Jakob Kagel: right, let’s just talk about, is there anything else like, do we just wanna like, take the conversation like, do we just wanna let it go where it’s gonna go. Kind of from there.

645 00:47:07.190 ⇒ 00:47:08.769 Uttam Kumaran: Like in terms of like.

646 00:47:08.770 ⇒ 00:47:20.639 Jakob Kagel: Anything like like, how much to? I mean, this is the question is like, how much do we care? Sort of about like our outstanding like issues. I mean, I’m not saying we have big like issues or whatnot. But

647 00:47:20.670 ⇒ 00:47:25.350 Jakob Kagel: you know, we just have some small ones, right? We have, like a small number of

648 00:47:25.360 ⇒ 00:47:50.170 Jakob Kagel: you know, self identified. That’s not in real, maybe like 400 that we can’t explain. And then we have the logic here that we need to make sure works like for the overlap. I mean at the same time. Right? It’s like the overlap is very small, like, at least for this one cut. I mean that we looked at one and 2. It’s like 66. So it’s like, Are we just gonna go ahead and show them the numbers like before we fix this or like.

649 00:47:50.580 ⇒ 00:47:51.620 Jakob Kagel: you know.

650 00:47:52.380 ⇒ 00:48:14.810 Jakob Kagel: I’m not so like I. I don’t wanna be like, I’m so so stiff on the numbers that, like we can’t like. We have to not show them something, because, like, you know, we can’t explain. Like 55. You know people what they did, or something, you know, like I wanna get in the way of like us making progress or anything like that. I just, I just wanna sort of say, like, you know this is what we have like

651 00:48:14.990 ⇒ 00:48:19.310 Jakob Kagel: right now, and like, we just have to be good with that, you know.

652 00:48:19.510 ⇒ 00:48:20.920 Uttam Kumaran: Yeah. So if we look at.

653 00:48:21.140 ⇒ 00:48:24.270 Uttam Kumaran: why is it still happening? So this is true.

654 00:48:27.440 ⇒ 00:48:30.440 Uttam Kumaran: So now it’s basically concentric rings.

655 00:48:32.900 ⇒ 00:48:35.559 Jakob Kagel: Is this the logic like you just made the logic change.

656 00:48:35.560 ⇒ 00:48:36.330 Uttam Kumaran: Yeah.

657 00:48:36.330 ⇒ 00:48:37.080 Jakob Kagel: Right

658 00:48:37.980 ⇒ 00:48:38.620 Jakob Kagel: so now.

659 00:48:38.904 ⇒ 00:48:39.189 Uttam Kumaran: Shed.

660 00:48:39.190 ⇒ 00:48:42.789 Jakob Kagel: It’s it’s counting like them. Yeah, okay.

661 00:48:43.800 ⇒ 00:48:45.429 Uttam Kumaran: Okay, so actually, this is wrong.

662 00:48:45.680 ⇒ 00:48:49.399 Jakob Kagel: But you need to get you cause it. It can’t all be one right.

663 00:48:52.520 ⇒ 00:48:53.420 Uttam Kumaran: Yeah. So

664 00:48:54.470 ⇒ 00:48:55.720 Uttam Kumaran: see, I fucked it up.

665 00:48:56.170 ⇒ 00:49:02.199 Jakob Kagel: Well, because yeah, they can’t all be one like you need it to be 2 like for the ones that you’re trying to split

666 00:49:02.430 ⇒ 00:49:05.034 Jakob Kagel: cause. Otherwise, if you say equal to one.

667 00:49:05.360 ⇒ 00:49:07.640 Uttam Kumaran: So this will. This will be right. It’s 1, 2, greater than 2.

668 00:49:07.640 ⇒ 00:49:09.950 Jakob Kagel: They’re not summing. Yeah, exactly.

669 00:49:10.100 ⇒ 00:49:11.950 Jakob Kagel: Well, that’s what we had before.

670 00:49:12.190 ⇒ 00:49:14.850 Uttam Kumaran: Hmm! No, we didn’t have. Well, no, no.

671 00:49:14.850 ⇒ 00:49:15.170 Jakob Kagel: No.

672 00:49:15.170 ⇒ 00:49:16.130 Uttam Kumaran: Oaks.

673 00:49:17.850 ⇒ 00:49:19.236 Uttam Kumaran: No, because

674 00:49:20.310 ⇒ 00:49:21.790 Uttam Kumaran: we had, Max.

675 00:49:21.890 ⇒ 00:49:24.530 Uttam Kumaran: but it was a different thing, cause we were looking at like

676 00:49:25.000 ⇒ 00:49:36.539 Uttam Kumaran: cause. We we joined on the end date. So it was like, if you were at any point 1, 2, or more than 2, it put you in those categories, which means you could have been in multiple. Now there’s no shot.

677 00:49:38.170 ⇒ 00:49:39.020 Jakob Kagel: Okay.

678 00:49:39.980 ⇒ 00:49:43.065 Uttam Kumaran: Watch. Okay, I’ll show you. Here.

679 00:49:43.580 ⇒ 00:49:46.560 Jakob Kagel: Yeah, I mean, we can check it real quick, just about it.

680 00:49:48.000 ⇒ 00:49:48.770 Jakob Kagel: Yeah.

681 00:49:59.070 ⇒ 00:50:06.239 Uttam Kumaran: Dude. The thing that would be killer tomorrow, though, is, if you can give a little bit of your perspective from home depot. And, Mike.

682 00:50:06.310 ⇒ 00:50:09.553 Uttam Kumaran: what you think we should do, cause that’s a conversation I wanna get to, too.

683 00:50:09.920 ⇒ 00:50:13.160 Jakob Kagel: I mean, I had this conversation with them already. Basically.

684 00:50:13.160 ⇒ 00:50:14.529 Uttam Kumaran: Then then it’s okay. Yeah.

685 00:50:14.530 ⇒ 00:50:20.320 Jakob Kagel: While ago, I mean no, I mean the I’ll talk about it there. And I mean, I’m gonna tell you what I told them, basically, too, which is like

686 00:50:20.630 ⇒ 00:50:22.340 Jakob Kagel: home Depot is just like

687 00:50:22.940 ⇒ 00:50:36.889 Jakob Kagel: we have all these transactions. So it’s like, and we have all these different products. You know, we’d like they don’t even have like a complex product. Mix. They sell like 13 things or something like, you know, whatever I don’t know. I mean, it’s more than that, you know, but it’s not like.

688 00:50:37.030 ⇒ 00:50:46.750 Jakob Kagel: you know, they they have like 8 key product classes, right? Like, it’s not like we at Home depot. It’s like, you know, we have hundreds, probably like thousands. So

689 00:50:46.780 ⇒ 00:50:51.660 Jakob Kagel: it’s like we can do customer segmentation cause with like a machine learning model, because we have.

690 00:50:51.660 ⇒ 00:50:58.050 Uttam Kumaran: No, no, no, no, no, I’m not. I’m not asking you to to look in the past. I’m asking you to think about what they should do in the business.

691 00:50:58.050 ⇒ 00:51:03.600 Jakob Kagel: Right right? And but that’s what I’m saying is like, you can’t compare like they wanna they basically. But what they were saying in the conversation, where.

692 00:51:03.600 ⇒ 00:51:04.410 Uttam Kumaran: Wow!

693 00:51:04.410 ⇒ 00:51:15.390 Jakob Kagel: Say, like, what did you do at home depot like? Do that for us? Basically. But I’m like we can’t do exactly what we did there. So that’s where I’m getting at is like, yeah, I mean, we definitely have to be forward looking. And we have to think about like things that.

694 00:51:15.390 ⇒ 00:51:20.369 Uttam Kumaran: No, but your solution would be, you guys should have more products. You guys should have like, that’s that’s what I.

695 00:51:20.370 ⇒ 00:51:21.980 Jakob Kagel: I know. That’s yeah.

696 00:51:21.980 ⇒ 00:51:23.900 Uttam Kumaran: No, but that’s actually what I’m saying.

697 00:51:23.900 ⇒ 00:51:26.129 Jakob Kagel: I didn’t say it to them like that, either. Like.

698 00:51:26.130 ⇒ 00:51:27.729 Uttam Kumaran: Should you should? They don’t like.

699 00:51:27.730 ⇒ 00:51:28.689 Jakob Kagel: Yeah, I mean, I’ve

700 00:51:28.870 ⇒ 00:51:36.800 Jakob Kagel: yeah, I’m not trying to like, come back to them and say, like, Hey, like your data sucks, we can’t do anything with it that’s not going to get us anywhere. Like, yeah, I get that.

701 00:51:36.800 ⇒ 00:51:37.599 Uttam Kumaran: And but our.

702 00:51:37.600 ⇒ 00:51:42.020 Jakob Kagel: But there is some. There’s some truth in that, or like it’s at least is not as robust.

703 00:51:42.320 ⇒ 00:51:48.760 Uttam Kumaran: No, the fun part about this client is that they actually want our feedback on what to do on the business side.

704 00:51:48.760 ⇒ 00:51:49.550 Jakob Kagel: Right.

705 00:51:49.800 ⇒ 00:51:54.370 Uttam Kumaran: Because we are now just as acquainted with their metrics as they’ve ever been.

706 00:51:54.854 ⇒ 00:52:06.929 Uttam Kumaran: which is. But this is this is like, which is, it’s like, imagine this was home depot before they had a crazy built out pro segment. What would you do so if our answers are like, Hey, here are some options. Either we go.

707 00:52:06.930 ⇒ 00:52:30.150 Jakob Kagel: What the the next best thing that they can do is or and we talked about this, I think before, too, is like, Okay, we once we finalize like these are like the high confidence pros. Right, like whatever we said is 2 2 plus, you know, combined with self identified, combined with email, whatever the logic we end up on, we then just go into, like our email marketing and see like which one of these one like emails, have we targeted, and which ones have we not.

708 00:52:30.150 ⇒ 00:52:31.239 Uttam Kumaran: That’s it. Yeah, I agree.

709 00:52:31.240 ⇒ 00:52:32.000 Jakob Kagel: That’s it. I mean, I.

710 00:52:32.000 ⇒ 00:52:33.569 Uttam Kumaran: I think that’s the lowest hanging fruit as well.

711 00:52:33.570 ⇒ 00:52:35.329 Jakob Kagel: The lowest hanging fruit. Right there.

712 00:52:35.330 ⇒ 00:52:43.069 Uttam Kumaran: Kim Kim should start to segment these guys and talk to them differently. The second thing we need to get we need to get more net new of those guys.

713 00:52:43.300 ⇒ 00:52:49.869 Uttam Kumaran: because because the the base, the other thing I want to do is basically be like, what’s our penetration? The thing I’m gonna do is dude there like

714 00:52:49.980 ⇒ 00:52:54.343 Uttam Kumaran: I’m gonna pay like fucking $100. These guys like.

715 00:52:54.780 ⇒ 00:52:55.990 Jakob Kagel: 3rd party.

716 00:52:55.990 ⇒ 00:52:58.039 Uttam Kumaran: It’s it scrapes Google Maps.

717 00:52:58.040 ⇒ 00:52:58.390 Jakob Kagel: Yeah.

718 00:52:58.390 ⇒ 00:53:08.899 Uttam Kumaran: And I already ran this for them. And I told them how much is gonna cost. It’s gonna be like, really cheap for us to basically get every Pool Service related company on Google Maps.

719 00:53:09.130 ⇒ 00:53:09.860 Jakob Kagel: Right.

720 00:53:10.190 ⇒ 00:53:11.100 Uttam Kumaran: So the thing.

721 00:53:11.100 ⇒ 00:53:14.980 Jakob Kagel: I’m I’m I’m totally with you on that. I think that’s a great idea. I think we talked about this before.

722 00:53:14.980 ⇒ 00:53:20.680 Uttam Kumaran: This is actually like what they want from us. Because, again, this is why they like the work we we do is because

723 00:53:21.030 ⇒ 00:53:26.969 Uttam Kumaran: what what do usual data teams do? They do like what our inclinations be like? Y’all figure it out on this side. They’re like, Yo.

724 00:53:27.240 ⇒ 00:53:32.290 Uttam Kumaran: is this the best route. And so this is the best route. I think we should work with Kim basically to say, Hey.

725 00:53:32.330 ⇒ 00:53:39.749 Uttam Kumaran: I think we’re gonna go. Let’s go. We’re gonna think about 2 things, one, the existing pros we have. How do we get them to come back and buy? Second thing is, how do we get more pros.

726 00:53:39.790 ⇒ 00:53:41.059 Uttam Kumaran: Those are the 2 works.

727 00:53:41.060 ⇒ 00:53:54.369 Jakob Kagel: That’s sort of the 2 that’s sort of the 2 pronged approach to. And that’s where we have to have the discussion with them. Tomorrow, too, is like, I. I think we’re both aligned like on, we need to like, do the email marketing. But it’s like, Do you want to target the people like that. You already have repeat purchases.

728 00:53:54.370 ⇒ 00:53:55.700 Uttam Kumaran: They’re gonna say, both.

729 00:53:55.700 ⇒ 00:54:02.790 Jakob Kagel: Or both, exactly like, do you want to target the people that haven’t bought because it’s like the people that haven’t repeat bought? It’s a way.

730 00:54:02.790 ⇒ 00:54:03.490 Uttam Kumaran: I don’t.

731 00:54:03.690 ⇒ 00:54:21.689 Jakob Kagel: And like, it’s also like that’s kind of the goal is like to get the returning customers like if they’re already buying multiple from you. There is opportunity, of course, like depending on the nature of their business, or whatever assuming it’s a business like that. They would have like demand for more product. But like I don’t know.

732 00:54:21.690 ⇒ 00:54:34.269 Uttam Kumaran: I think what they’re gonna say is that the consumers, you know, are like dead. Wait, it’s like one and done type shit, which means their turn is super high, I think what what the likely solution is gonna be is for us to go get

733 00:54:34.320 ⇒ 00:54:35.890 Uttam Kumaran: more people

734 00:54:36.330 ⇒ 00:54:45.860 Uttam Kumaran: and spend the marketing dollars there, cause right now they’re spending all their marketing dollars on the consumers, which are again all one and done in and out. No Lcv.

735 00:54:45.860 ⇒ 00:54:46.200 Jakob Kagel: Sure.

736 00:54:46.200 ⇒ 00:54:49.439 Uttam Kumaran: So I think the goal is probably gonna be, we cover scrape.

737 00:54:49.560 ⇒ 00:54:54.009 Uttam Kumaran: We kind of she’s gonna think about a content strategy. And we basically let it go market to these guys.

738 00:54:54.120 ⇒ 00:55:03.919 Uttam Kumaran: The nice thing about having the data is we’re gonna start to see from June onwards, the segment started growing. And then basically, next year, we’ll be able to see like, holy shit. These guys are coming back.

739 00:55:04.180 ⇒ 00:55:06.380 Uttam Kumaran: I think this is the kickoff for them to really

740 00:55:06.440 ⇒ 00:55:07.969 Uttam Kumaran: boost that shit. Basically.

741 00:55:07.970 ⇒ 00:55:10.369 Jakob Kagel: Okay, I mean, I’m with that. I mean, yeah, for sure.

742 00:55:10.370 ⇒ 00:55:16.030 Uttam Kumaran: That’s gonna be my like, take for them is like, you guys need to grow the segment from net new people.

743 00:55:16.200 ⇒ 00:55:23.030 Uttam Kumaran: You have some people that already exist in the database, that we should retarget. And I think there’s going to be some percentage conversion there.

744 00:55:23.090 ⇒ 00:55:29.570 Uttam Kumaran: But there’s a whole shitload of people that are not using you, who could be buying from you on a recurring basis.

745 00:55:29.570 ⇒ 00:55:35.409 Jakob Kagel: Right. I mean, you can do like, I mean, obviously, like, the strategies are kind of different, as far as like acquiring.

746 00:55:35.410 ⇒ 00:55:36.110 Uttam Kumaran: Yeah.

747 00:55:36.350 ⇒ 00:55:36.750 Jakob Kagel: Like the.

748 00:55:36.750 ⇒ 00:55:39.069 Uttam Kumaran: Nice thing is Kim can do both Kim can handle both.

749 00:55:39.360 ⇒ 00:55:57.110 Jakob Kagel: Is like, Yeah, you can do. I feel like it. You take a smaller segment. You do a little bit more kind of like care in the message. You know what I’m saying. Like to try to, you know. Like, when you’re just running whatever Instagram ads or so I’m getting like all the pool pro to go. Instagram ads nuts.

750 00:55:57.110 ⇒ 00:55:58.870 Uttam Kumaran: Yeah, yeah, yeah, yeah.

751 00:55:59.180 ⇒ 00:56:09.749 Jakob Kagel: Yeah, like, when you’re just running Instagram ads or whatever I mean, you’re just sending it to a million people and like, whoever clicks on. It clicks on it. But you know, it’s like this opportunity, like, okay, here’s 10% offer.

752 00:56:09.750 ⇒ 00:56:27.060 Uttam Kumaran: No, it’s. It’s exactly the problem that we have in this business. It’s exactly the problem that everybody has is like you need to segment. Your customers. Because customers come through different channels, they spend way differently right now. They’re thinking everybody’s a fucking same, and they’re losing because they have customers. They don’t stick around so they’re burning cash.

753 00:56:27.150 ⇒ 00:56:34.020 Uttam Kumaran: They’re absolutely throwing cash into the wind. It gets spent. They get one buy out of it, and then nothing happens

754 00:56:34.040 ⇒ 00:56:36.229 Uttam Kumaran: so that the ratio’s so bad.

755 00:56:36.230 ⇒ 00:56:40.800 Jakob Kagel: The the the scraping like the pools like.

756 00:56:41.220 ⇒ 00:56:44.739 Jakob Kagel: that’s like, yeah, that’s got to be like the next thing we do. I feel like.

757 00:56:44.740 ⇒ 00:56:48.509 Uttam Kumaran: Yeah. But see, that’s for me the fun that’s like, okay, cool. I wanna.

758 00:56:48.510 ⇒ 00:56:56.099 Jakob Kagel: That’s like, that’s like the thing that it’s like they definitely can’t do that themselves, like they’re gonna think we’re like wizards for doing that. Basically.

759 00:56:56.100 ⇒ 00:56:58.446 Uttam Kumaran: Oh, I already. Yeah. Dude. I sent them.

760 00:56:58.740 ⇒ 00:57:04.719 Jakob Kagel: Tell them. Yeah, don’t tell them that it’s easy, or whatever pay these people 100 bucks like milk them.

761 00:57:04.720 ⇒ 00:57:10.519 Uttam Kumaran: No, no, no, no, I mean, I just want to show you what I sent them. Basically because, like.

762 00:57:10.770 ⇒ 00:57:12.709 Uttam Kumaran: I sent through 2 things. Basically, I was like.

763 00:57:12.810 ⇒ 00:57:19.869 Uttam Kumaran: this was in April 17, th when we kind of kicked this stuff up. I was like, I can get you every Pool Service Company

764 00:57:20.200 ⇒ 00:57:21.290 Uttam Kumaran: for.

765 00:57:22.390 ⇒ 00:57:27.430 Uttam Kumaran: like a 3rd of a set of a cent per listing.

766 00:57:27.430 ⇒ 00:57:28.120 Jakob Kagel: Right.

767 00:57:29.060 ⇒ 00:57:31.169 Uttam Kumaran: So 10,000 for 60 bucks.

768 00:57:31.940 ⇒ 00:57:38.409 Jakob Kagel: Yeah, and that will make your marketing just like so much more efficient like, if you can even like the mail like just mail them all shit like.

769 00:57:38.410 ⇒ 00:57:46.890 Uttam Kumaran: Let’s see, this is a really key thing where it’s like a numbers don’t lie. Type situation, because the thing we did on shipments dude for them.

770 00:57:48.610 ⇒ 00:57:52.690 Uttam Kumaran: basically, if you looked at if you look at like our average shipping costs.

771 00:57:52.710 ⇒ 00:57:54.849 Uttam Kumaran: this was like right when I came in.

772 00:57:54.930 ⇒ 00:57:57.929 Uttam Kumaran: And this is our new busy season. We’re in the middle of it.

773 00:57:58.230 ⇒ 00:58:01.049 Jakob Kagel: Right? And it’s like, really low. Yeah.

774 00:58:01.050 ⇒ 00:58:03.930 Uttam Kumaran: This is when we put the new contract in place.

775 00:58:04.380 ⇒ 00:58:04.780 Jakob Kagel: Yeah.

776 00:58:04.780 ⇒ 00:58:07.559 Uttam Kumaran: Yeah, I saved them like half a million dollars.

777 00:58:07.560 ⇒ 00:58:08.110 Jakob Kagel: Right.

778 00:58:08.110 ⇒ 00:58:08.940 Uttam Kumaran: Easily.

779 00:58:09.760 ⇒ 00:58:14.109 Uttam Kumaran: And we’re and this is the. This is where I like, because we have them. This is like what

780 00:58:14.280 ⇒ 00:58:22.329 Uttam Kumaran: ultimately it’s the toughest part. And you know, like this never happens in data where you actually make a recommendation. They do it. You see the benefits, because

781 00:58:22.550 ⇒ 00:58:27.689 Uttam Kumaran: just probably leave the company by then, or shit happens, or you don’t know. You don’t know what the fuck happens to any of our analysis.

782 00:58:27.690 ⇒ 00:58:28.190 Jakob Kagel: Yeah.

783 00:58:28.190 ⇒ 00:58:33.119 Uttam Kumaran: The thing I like about these guys is that dude? They will do the thing, and then we’ll see the fucking line change.

784 00:58:33.120 ⇒ 00:58:33.640 Jakob Kagel: Right.

785 00:58:33.640 ⇒ 00:58:34.959 Uttam Kumaran: You know

786 00:58:35.620 ⇒ 00:58:52.209 Jakob Kagel: Good. I mean, yeah. So I think that’s like, I mean, that’s the other part. Exactly that I was trying to get into me is like, Okay, we’ll show them, like, you know, basically the low medium, high confidence splits right? And then we’ll say, but then it’s like, I think it’s good exactly like you said, because they’ll actually do shit like.

787 00:58:52.210 ⇒ 00:58:52.760 Uttam Kumaran: They will.

788 00:58:52.760 ⇒ 00:58:58.859 Jakob Kagel: They should have like a recommendation like Hey, like you should do this like you should take the high confidence ones, and.

789 00:58:58.860 ⇒ 00:58:59.700 Uttam Kumaran: Yes.

790 00:58:59.700 ⇒ 00:59:02.700 Jakob Kagel: Email, these people, or whatever like, you know. So I think.

791 00:59:02.700 ⇒ 00:59:06.240 Uttam Kumaran: The even better part is like they may have had this idea.

792 00:59:06.250 ⇒ 00:59:08.699 Uttam Kumaran: but they wouldn’t have been able to say it worked.

793 00:59:08.870 ⇒ 00:59:10.389 Uttam Kumaran: and by how much did it work.

794 00:59:10.390 ⇒ 00:59:13.299 Jakob Kagel: Right exactly. And now we can quantify it. That’s great.

795 00:59:13.980 ⇒ 00:59:17.679 Uttam Kumaran: And then that buys us another fucking. Yeah, right? So that’s the thing is like.

796 00:59:18.180 ⇒ 00:59:27.429 Uttam Kumaran: And I have a feeling that although we made a shit ton of strides on the cost side of shipments. That’s like a race to bottom, right? We can only reduce that

797 00:59:27.780 ⇒ 00:59:29.710 Uttam Kumaran: to like. Sum them out.

798 00:59:29.710 ⇒ 00:59:30.420 Jakob Kagel: Facts.

799 00:59:30.420 ⇒ 00:59:32.669 Uttam Kumaran: On the revenue side, though there’s like.

800 00:59:32.910 ⇒ 00:59:33.490 Jakob Kagel: Yeah.

801 00:59:33.490 ⇒ 00:59:35.960 Uttam Kumaran: A lot of opportunity to keep growing.

802 00:59:37.335 ⇒ 00:59:43.469 Uttam Kumaran: And the nice thing is like, I think this is something that they haven’t done, which is like so obvious. Like, I’m 2 targetings

803 00:59:43.510 ⇒ 00:59:45.479 Uttam Kumaran: like target people differently. And.

804 00:59:45.710 ⇒ 00:59:46.290 Jakob Kagel: Right.

805 00:59:46.290 ⇒ 00:59:51.299 Uttam Kumaran: I’ll get your more expensive luxury. Customers like what dance? And he’s like those people should be getting a fucking phone calls like.

806 00:59:51.330 ⇒ 00:59:54.519 Uttam Kumaran: Yeah, dude they should. Someone should be calling those people.

807 00:59:54.520 ⇒ 00:59:56.770 Jakob Kagel: Twice as much. We already established that the like.

808 00:59:56.770 ⇒ 00:59:57.670 Uttam Kumaran: Yeah, like, it.

809 00:59:57.670 ⇒ 01:00:04.649 Jakob Kagel: But even if you say it’s like whatever you know is bullshit, it’s like the the numbers don’t lie. The people they.

810 01:00:04.650 ⇒ 01:00:05.700 Uttam Kumaran: No. Yeah.

811 01:00:05.700 ⇒ 01:00:08.859 Jakob Kagel: Spend twice as much. So that’s like

812 01:00:08.890 ⇒ 01:00:15.710 Jakob Kagel: already, like, you know, I don’t know just using that 1,600, or whatever like 16 K. Is like.

813 01:00:16.230 ⇒ 01:00:25.480 Jakob Kagel: you know, I don’t know. That’s even better than what they’re doing before. You know, they can say whatever the business is like, consumer this or consumer that. And I mean, like.

814 01:00:25.500 ⇒ 01:00:28.669 Jakob Kagel: that’s why I think it’s good. We’ll just show them the split like the competency.

815 01:00:28.670 ⇒ 01:00:29.540 Uttam Kumaran: Yeah, let’s.

816 01:00:29.540 ⇒ 01:00:34.429 Jakob Kagel: Sort of like, say, like, okay, it’s self identified. Plus, we added, like this confidence, there.

817 01:00:34.880 ⇒ 01:00:37.084 Uttam Kumaran: So this is working now. So like, for example.

818 01:00:37.330 ⇒ 01:00:54.605 Jakob Kagel: Sorry. I know this meeting’s going on long, but size couple of last things I want to talk about real real quick. So in the meeting. Are we just gonna like you want to have the notion page, which is basically just going to be like a written out summary of what we’re looking at in real right? It’s gonna be like, this is like the percentages like this is the, you know, whatever the splits like.

819 01:00:54.830 ⇒ 01:00:57.189 Uttam Kumaran: We should, I think we should pull up real.

820 01:00:57.550 ⇒ 01:00:58.690 Jakob Kagel: Just walk them through it.

821 01:00:58.690 ⇒ 01:01:02.581 Uttam Kumaran: Have the notion as like the script, because the thing that’s gonna happen.

822 01:01:02.860 ⇒ 01:01:03.870 Jakob Kagel: Us, then.

823 01:01:04.130 ⇒ 01:01:09.300 Uttam Kumaran: But the notion is a notion is for everybody, as basically like, this is mean meaning like

824 01:01:09.530 ⇒ 01:01:15.569 Uttam Kumaran: dude. We’re gonna forget this whole conversation. And like the next 40 apps, I wanna make sure that like what we talked about.

825 01:01:15.950 ⇒ 01:01:18.230 Jakob Kagel: Like less, is less than 20.

826 01:01:18.230 ⇒ 01:01:33.829 Uttam Kumaran: No, no, but it’s it’s it’s the script for us to basically be like when they ask about a specific thing like a nuance here, we know. But also they’re gonna want. I want to show them this because it’s super clear. And our goal basically confidently get them past. Get him one to make a decision on

827 01:01:33.870 ⇒ 01:01:36.789 Uttam Kumaran: the flag, and second, to talk about how we execute.

828 01:01:37.350 ⇒ 01:01:39.540 Jakob Kagel: Okay. So yeah, I’m in.

829 01:01:39.540 ⇒ 01:01:42.560 Uttam Kumaran: Whether it takes this, whether it takes notion, whatever it takes

830 01:01:43.360 ⇒ 01:01:44.479 Uttam Kumaran: like we do it.

831 01:01:44.480 ⇒ 01:01:51.130 Jakob Kagel: I think I got the gist of what you want in the notion page. So I’ll just yeah. I’ll type that up. And like, yeah, I’m not gonna make it like crazy long.

832 01:01:51.130 ⇒ 01:01:52.460 Uttam Kumaran: No, no, no, no, no, no.

833 01:01:52.460 ⇒ 01:01:52.850 Jakob Kagel: Like.

834 01:01:52.850 ⇒ 01:01:54.820 Uttam Kumaran: Whatever we need and whatever. Yeah.

835 01:01:54.820 ⇒ 01:01:58.220 Jakob Kagel: The key points that we discussed. Like, you know, everything from

836 01:01:58.570 ⇒ 01:02:15.069 Jakob Kagel: like I said, we’re not bringing in customers that haven’t ordered, like all that like, you know, just sort of nuanced stuff. And then like the meat on the bone, like we talked about, which is like the confidence basically that we can show them now. And like the email targeting like opportunity for them, based on.

837 01:02:15.070 ⇒ 01:02:18.030 Uttam Kumaran: Yeah. And this this slog is, this is all working. Now.

838 01:02:18.390 ⇒ 01:02:20.600 Jakob Kagel: Yeah, that’s great. Okay, cool.

839 01:02:20.920 ⇒ 01:02:21.430 Jakob Kagel: like.

840 01:02:21.430 ⇒ 01:02:22.360 Uttam Kumaran: These are all individuals.

841 01:02:22.360 ⇒ 01:02:23.479 Jakob Kagel: Dude man. I’m sorry.

842 01:02:23.480 ⇒ 01:02:25.020 Uttam Kumaran: Aye, aye, aye.

843 01:02:25.020 ⇒ 01:02:28.469 Jakob Kagel: Yeah, sounds great. I appreciate you jumping on. I know it’s a lot of time, and.

844 01:02:28.470 ⇒ 01:02:35.260 Uttam Kumaran: No, no, no, this is good. I again, this is like the type of analysis that we did on shipping. We’re gonna do here. It’s getting faster and faster.

845 01:02:35.260 ⇒ 01:02:36.229 Jakob Kagel: Yeah. Why don’t we.

846 01:02:36.230 ⇒ 01:02:36.900 Uttam Kumaran: Like as much.

847 01:02:36.900 ⇒ 01:02:48.040 Jakob Kagel: We have some. We have some good learnings, you know. We learned a lot, and I think, like the name conventions and stuff like that is like, you know, we now, we know basically not to do that in the future. So I’m gonna.

848 01:02:48.040 ⇒ 01:02:52.935 Uttam Kumaran: Push this real stuff, and then I’m gonna go home. So.

849 01:02:53.380 ⇒ 01:02:54.980 Jakob Kagel: I’ll see you in the fun. See it? Bye.