Meeting Title: Zoom-Meeting Date: 2024-06-25 Meeting participants: Ryan Luke Daque, Nicolas Sucari, Jakob Kagel
WEBVTT
1 00:00:29.630 ⇒ 00:00:30.730 Hey! Jacob.
2 00:00:36.340 ⇒ 00:00:42.949 Nicolas Sucari: Kind of tricky that information right? I don’t know why. It’s like a number on one side and a different one. Real.
3 00:00:42.950 ⇒ 00:00:48.589 Jakob Kagel: Yeah, I mean, exactly. I’m a little concerned. Because, yeah, I mean, I I can’t
4 00:00:48.610 ⇒ 00:00:50.629 Jakob Kagel: say like, exactly
5 00:00:50.950 ⇒ 00:00:59.309 Jakob Kagel: like I can’t remember every number like off the top of my head. But I mean, 1st of all, it’s like they shouldn’t. Yeah, they should match like the 15.
6 00:00:59.310 ⇒ 00:00:59.820 Nicolas Sucari: Exactly.
7 00:01:00.455 ⇒ 00:01:01.090 Jakob Kagel: Real.
8 00:01:01.440 ⇒ 00:01:04.639 Jakob Kagel: It should not be 800. Something in the table.
9 00:01:06.430 ⇒ 00:01:07.410 Jakob Kagel: so.
10 00:01:07.410 ⇒ 00:01:09.900 Nicolas Sucari: If we like, if we split
11 00:01:10.030 ⇒ 00:01:14.260 Nicolas Sucari: like. Our logic now includes, like 3 different variables. Right?
12 00:01:14.730 ⇒ 00:01:19.029 Nicolas Sucari: 1st of all is the self identify flag that we have from the checkout.
13 00:01:19.400 ⇒ 00:01:22.480 Nicolas Sucari: So that was kind of 16 K. Right
14 00:01:22.620 ⇒ 00:01:23.220 Nicolas Sucari: customer.
15 00:01:23.220 ⇒ 00:01:30.390 Jakob Kagel: Right. That’s that’s what I’m I mean, that’s what I’m like confused about. And that’s also like, what’s like concerning it’s like.
16 00:01:30.540 ⇒ 00:01:31.680 Jakob Kagel: Okay.
17 00:01:31.720 ⇒ 00:01:37.820 Jakob Kagel: like, we shouldn’t like we shouldn’t have overwritten like, and I talked to Tom about this yesterday, but like.
18 00:01:38.110 ⇒ 00:01:38.790 Nicolas Sucari: China.
19 00:01:38.790 ⇒ 00:01:46.690 Jakob Kagel: Like we shouldn’t. If we’re gonna create our own like pool pro like flag, we should not name. It is pool pro.
20 00:01:47.090 ⇒ 00:01:49.379 Nicolas Sucari: No, because that’s the checkout flag.
21 00:01:49.650 ⇒ 00:01:54.949 Jakob Kagel: Right. And that’s the checkout flag, right? And then that’s very confusing.
22 00:01:57.120 ⇒ 00:02:06.069 Jakob Kagel: like. So that’s the part that yeah, I’m confused about. Cause I’m like, okay. And but then even then, it’s like, okay, if our logic right?
23 00:02:06.210 ⇒ 00:02:08.460 Jakob Kagel: Say, we’re taking email
24 00:02:08.509 ⇒ 00:02:17.019 Jakob Kagel: is pool pro true and like the multiple orders, then our total should still be higher than.
25 00:02:17.020 ⇒ 00:02:17.550 Nicolas Sucari: Exactly.
26 00:02:17.550 ⇒ 00:02:24.570 Jakob Kagel: Overall pool pro number like or like the self identified pool pro number. Like, if cause we’re combining shouldn’t be. It shouldn’t be.
27 00:02:24.570 ⇒ 00:02:26.669 Nicolas Sucari: We’re adding them, yeah, exactly.
28 00:02:27.000 ⇒ 00:02:29.030 Jakob Kagel: They, they should be combined. Yeah.
29 00:02:29.030 ⇒ 00:02:32.948 Nicolas Sucari: We are adding them, and we are. We are not like seeing which
30 00:02:33.680 ⇒ 00:02:59.419 Nicolas Sucari: which clients like have the 3 variables to name it through right. It should be like an aggregate number of all these self identified all the ones that we have. The emails that we are guessing. And the the clients that order more than 2 pumps, probably, or something like that right? That number should be higher on each, like individual number that we have for each of the 3 variables.
31 00:03:00.380 ⇒ 00:03:01.320 Jakob Kagel: Yeah.
32 00:03:06.220 ⇒ 00:03:08.729 Jakob Kagel: I’m just he’s writing the mess image today. Can you join.
33 00:03:08.730 ⇒ 00:03:09.590 Nicolas Sucari: Yeah, yeah.
34 00:03:09.800 ⇒ 00:03:10.115 Jakob Kagel: Yeah.
35 00:03:41.750 ⇒ 00:03:44.579 Nicolas Sucari: I send the link on that thread? Yeah, probably.
36 00:04:19.040 ⇒ 00:04:20.770 Nicolas Sucari: Yeah, I I think
37 00:04:22.780 ⇒ 00:04:26.029 Nicolas Sucari: And with you that that number shouldn’t be like
38 00:04:26.570 ⇒ 00:04:30.260 Nicolas Sucari: lower than what we are identifying as the self.
39 00:04:30.860 ⇒ 00:04:41.610 Jakob Kagel: Right, because even then, like, even if it’s whatever 700 is still lower than like 800 self identified, or whatever I mean. Anyway, hey, Ryan.
40 00:04:42.284 ⇒ 00:04:42.740 Ryan Luke Daque: Guys.
41 00:04:43.230 ⇒ 00:04:43.630 Nicolas Sucari: Iran.
42 00:04:44.690 ⇒ 00:04:55.160 Jakob Kagel: okay, cool. Yeah. Thanks for joining the call. I think it’d just be easier right if we just talk through this like instead of like going back and forth on text. Right? So
43 00:04:55.780 ⇒ 00:05:03.020 Jakob Kagel: the 14 k. 15 k. That we see in real. And then the 8 27 that is in the table
44 00:05:03.180 ⇒ 00:05:06.569 Jakob Kagel: can. Do you understand? Like, what is there.
45 00:05:07.080 ⇒ 00:05:12.810 Ryan Luke Daque: Yeah, let me maybe share my screen. That should be probably easier to understand.
46 00:05:13.873 ⇒ 00:05:15.737 Ryan Luke Daque: Can you see my screen? By the way.
47 00:05:15.970 ⇒ 00:05:16.450 Jakob Kagel: This is.
48 00:05:16.450 ⇒ 00:05:17.230 Nicolas Sucari: Yeah.
49 00:05:17.680 ⇒ 00:05:20.369 Ryan Luke Daque: Yeah. So there’s actually like 9
50 00:05:20.830 ⇒ 00:05:23.500 Ryan Luke Daque: different is pool. Pro.
51 00:05:23.670 ⇒ 00:05:25.859 Ryan Luke Daque: Wait, let me zoom in
52 00:05:28.060 ⇒ 00:05:30.340 Ryan Luke Daque: right? So there’s like, there’s
53 00:05:30.690 ⇒ 00:05:33.710 Ryan Luke Daque: the 1st one is the is pool pro derived.
54 00:05:33.770 ⇒ 00:05:39.909 Ryan Luke Daque: which is the 675 that you were like talking about. And this is basically
55 00:05:41.480 ⇒ 00:05:43.319 Ryan Luke Daque: like, based on the
56 00:05:43.750 ⇒ 00:05:45.749 Ryan Luke Daque: from what I understand here.
57 00:05:46.070 ⇒ 00:05:46.895 Ryan Luke Daque: there’s
58 00:05:48.350 ⇒ 00:05:49.850 Ryan Luke Daque: yeah, it’s this one.
59 00:05:50.590 ⇒ 00:05:53.439 Ryan Luke Daque: the 1st one which is coming from.
60 00:05:58.280 ⇒ 00:06:00.009 Ryan Luke Daque: where was that?
61 00:06:02.470 ⇒ 00:06:05.219 Ryan Luke Daque: Yeah, basically, the one that’s that’s
62 00:06:05.410 ⇒ 00:06:07.000 Ryan Luke Daque: anytime that
63 00:06:07.370 ⇒ 00:06:10.100 Ryan Luke Daque: customer is has this.
64 00:06:10.770 ⇒ 00:06:13.669 Ryan Luke Daque: are you a pool industry, professional? Basically.
65 00:06:13.670 ⇒ 00:06:18.269 Jakob Kagel: That’s that’s that. Shouldn’t be right, though. Then like, sorry you’re saying this.
66 00:06:18.270 ⇒ 00:06:18.990 Ryan Luke Daque: Yeah, for.
67 00:06:18.990 ⇒ 00:06:19.640 Jakob Kagel: I’veed.
68 00:06:20.190 ⇒ 00:06:21.930 Ryan Luke Daque: Yes, this is for derive.
69 00:06:21.930 ⇒ 00:06:29.270 Jakob Kagel: I mean. Utom had a conversation about this last night, and I was like saying that derived would be our
70 00:06:29.530 ⇒ 00:06:36.430 Jakob Kagel: like. That would be the like our naming convention, for, like our is pool pro like definition.
71 00:06:36.790 ⇒ 00:06:38.129 Ryan Luke Daque: And what is that? Again.
72 00:06:38.130 ⇒ 00:06:41.269 Jakob Kagel: About that. I mean, I’m not saying that you’re wrong, but like.
73 00:06:41.270 ⇒ 00:06:41.659 Ryan Luke Daque: Yeah.
74 00:06:43.210 ⇒ 00:06:46.549 Ryan Luke Daque: what’s our definition then? For the is pool pro.
75 00:06:46.550 ⇒ 00:06:52.890 Jakob Kagel: It would be like the combination of like the self identified the email and like the 2 plus orders.
76 00:06:53.230 ⇒ 00:07:01.169 Jakob Kagel: So I mean, so the 14 K. Here, let’s maybe start with like the 1415 K, that’s in real right.
77 00:07:01.630 ⇒ 00:07:03.089 Ryan Luke Daque: It’s like the blue process.
78 00:07:03.090 ⇒ 00:07:04.430 Jakob Kagel: Self identified.
79 00:07:04.490 ⇒ 00:07:09.380 Jakob Kagel: So that should be coming from the what you just pointed out.
80 00:07:10.530 ⇒ 00:07:13.799 Jakob Kagel: like the the line item, or whatever
81 00:07:13.910 ⇒ 00:07:18.540 Jakob Kagel: like that should that number is like closer to what we had previously.
82 00:07:19.170 ⇒ 00:07:27.277 Ryan Luke Daque: Maybe this is cause this is the one the the self identified, based on what? The, what time created here. It’s the
83 00:07:28.737 ⇒ 00:07:30.350 Ryan Luke Daque: Where was that?
84 00:07:32.900 ⇒ 00:07:35.269 Nicolas Sucari: It’s it’s the raw information. Yeah.
85 00:07:35.270 ⇒ 00:07:36.139 Ryan Luke Daque: Yes, it’s the right.
86 00:07:36.140 ⇒ 00:07:39.530 Nicolas Sucari: Are we doing? Okay? So that’s that’s correct. Okay.
87 00:07:39.530 ⇒ 00:07:40.010 Ryan Luke Daque: The role.
88 00:07:40.010 ⇒ 00:07:49.400 Nicolas Sucari: That. Okay, that’s like our 1st variable. And that’s like our base number. To start with the full provided identification of customers. Okay.
89 00:07:49.400 ⇒ 00:07:59.149 Ryan Luke Daque: But you mentioned that the the I so sorry about that, Nicholas. But Jacob mentioned that the our definition for is pool pro is whether it’s
90 00:07:59.180 ⇒ 00:08:00.919 Ryan Luke Daque: from email, right?
91 00:08:01.300 ⇒ 00:08:04.470 Nicolas Sucari: Yeah, it, but they should. They should be aggregate.
92 00:08:04.470 ⇒ 00:08:05.250 Jakob Kagel: Yeah, it should be.
93 00:08:05.610 ⇒ 00:08:05.970 Ryan Luke Daque: Age!
94 00:08:05.970 ⇒ 00:08:13.319 Jakob Kagel: Becky. It should. Yeah, it shouldn’t be like the derived number should be higher than the 14 K.
95 00:08:15.190 ⇒ 00:08:20.230 Jakob Kagel: Like, because it should be, it should be the 14 k plus.
96 00:08:20.814 ⇒ 00:08:38.405 Jakob Kagel: And then also, another thing is like when we have it in the table like we don’t have in the table right now is pool pro derived? Or is pool pro self identified? So we need to split those out. We need to keep this self identified one as a column.
97 00:08:38.750 ⇒ 00:08:42.052 Ryan Luke Daque: Yeah, I think it’s there. It’s just named differently.
98 00:08:42.429 ⇒ 00:08:43.099 Jakob Kagel: Okay.
99 00:08:43.620 ⇒ 00:08:47.449 Ryan Luke Daque: And yeah, based on what I see here
100 00:08:47.830 ⇒ 00:08:50.310 Ryan Luke Daque: for customers.
101 00:08:52.330 ⇒ 00:08:54.489 Ryan Luke Daque: So that is derived.
102 00:08:55.250 ⇒ 00:08:56.080 Ryan Luke Daque: Wait
103 00:08:57.540 ⇒ 00:09:02.540 Ryan Luke Daque: is is the is pool pro in the table, basically.
104 00:09:02.870 ⇒ 00:09:06.560 Ryan Luke Daque: And then the self identified is called
105 00:09:06.900 ⇒ 00:09:10.609 Ryan Luke Daque: is pool pro checkout flag. In the in the table.
106 00:09:10.960 ⇒ 00:09:31.249 Jakob Kagel: Is pool pro checkout flag. Okay? So that is, wait. See, this is like, yeah, th, this is like, we need to communicate this like internally, I guess I don’t know or what like, you know. But okay. So now I’m running is pool pro checkout flag. And now I’m getting the 16 K, okay.
107 00:09:31.250 ⇒ 00:09:31.990 Ryan Luke Daque: Right.
108 00:09:32.373 ⇒ 00:09:34.290 Jakob Kagel: Okay, so this makes sense.
109 00:09:34.320 ⇒ 00:09:36.260 Jakob Kagel: So, but
110 00:09:36.560 ⇒ 00:09:44.530 Jakob Kagel: yeah, I don’t. I don’t like that. We have the naming in the dashboard is like derived and self-identified, and then the naming in the table.
111 00:09:45.079 ⇒ 00:09:45.629 Ryan Luke Daque: Yeah.
112 00:09:45.630 ⇒ 00:09:50.740 Jakob Kagel: And is pool pro checkout flag. That’s that’s not like, yeah.
113 00:09:50.740 ⇒ 00:09:55.289 Ryan Luke Daque: Yeah, it’s not. It’s inconsistent. And and and yeah, I I get you. It’s like it.
114 00:09:55.290 ⇒ 00:09:56.459 Jakob Kagel: Right? So that’s.
115 00:09:56.460 ⇒ 00:09:57.400 Ryan Luke Daque: Using right.
116 00:09:57.400 ⇒ 00:09:59.429 Jakob Kagel: Right. And that’s where yeah.
117 00:09:59.470 ⇒ 00:10:13.850 Jakob Kagel: and and and that’s what I’m trying to to to understand exactly. And then even then, it’s like, Okay, if we have is pool pro checkout flag. 16 K. Why are we only getting like 14 K. In the dashboard.
118 00:10:14.140 ⇒ 00:10:18.069 Jakob Kagel: like all time? Period right?
119 00:10:18.470 ⇒ 00:10:19.170 Ryan Luke Daque: Right.
120 00:10:19.170 ⇒ 00:10:21.249 Jakob Kagel: Missing like 2,000,
121 00:10:22.560 ⇒ 00:10:23.389 Jakob Kagel: like even.
122 00:10:23.390 ⇒ 00:10:24.209 Ryan Luke Daque: Yeah, no doubt.
123 00:10:24.210 ⇒ 00:10:26.730 Jakob Kagel: But if we’re using the self identified one.
124 00:10:28.170 ⇒ 00:10:29.319 Ryan Luke Daque: Yeah, I think.
125 00:10:29.720 ⇒ 00:10:30.430 Jakob Kagel: You what I’m saying.
126 00:10:30.430 ⇒ 00:10:31.560 Ryan Luke Daque: Let’s see. Right?
127 00:10:33.400 ⇒ 00:10:41.019 Ryan Luke Daque: Yeah. So the 14,000 or the 16,000 that you’re seeing for the all time is basically the the raw
128 00:10:41.100 ⇒ 00:10:43.569 Ryan Luke Daque: like, Nicola said, that’s coming from
129 00:10:44.494 ⇒ 00:10:45.910 Ryan Luke Daque: April that was coming.
130 00:10:45.910 ⇒ 00:10:48.949 Jakob Kagel: Screenshot. I can put this screenshot here like
131 00:10:50.194 ⇒ 00:10:51.220 Jakob Kagel: so.
132 00:10:51.220 ⇒ 00:11:00.420 Nicolas Sucari: Can you like? My question is, do we have, like the 3 different variables, like split apart, so that we understand the 3 numbers.
133 00:11:00.420 ⇒ 00:11:01.490 Ryan Luke Daque: Yeah, so Joe.
134 00:11:01.670 ⇒ 00:11:12.090 Nicolas Sucari: Each. Each is getting to us like we have the 16 K from the self identified. That’s okay. Do we have the number from the email domain. Like, how many?
135 00:11:12.220 ⇒ 00:11:13.410 Nicolas Sucari: Yeah, we do have.
136 00:11:13.410 ⇒ 00:11:14.509 Ryan Luke Daque: 100 and 91.
137 00:11:14.510 ⇒ 00:11:17.993 Jakob Kagel: And that that I don’t think that’s the issue. Like, yeah.
138 00:11:18.310 ⇒ 00:11:21.519 Nicolas Sucari: Kind of fine. What I’m trying to understand is we have the 3
139 00:11:21.670 ⇒ 00:11:46.859 Nicolas Sucari: different things split apart. We need to aggregate that, obviously removing the duplicates that should be between them, and that should be like our baseline number of pull pros right? And then we can start using that number to split it into different dimensions and understand what is like in inside them. Right
140 00:11:46.910 ⇒ 00:11:56.660 Nicolas Sucari: like, if we want to understand which or if we wanna then split that number into amount of orders or amount of order items or amount of
141 00:11:56.750 ⇒ 00:12:04.649 Nicolas Sucari: pop pumps that they bought in a 365 day period. We can do it. But the baseline should be that aggregate number right.
142 00:12:04.920 ⇒ 00:12:16.999 Jakob Kagel: That’s exactly right. I mean, that is, that’s the like. The most important thing like when doing like this kind of like analysis and stuff is that we can always like tie the splits out to the total, and that we.
143 00:12:17.000 ⇒ 00:12:18.020 Nicolas Sucari: Yeah, exactly.
144 00:12:18.020 ⇒ 00:12:45.160 Jakob Kagel: But the total number should be. You know what I’m saying like. If we don’t know what the total number should be or like, we can’t align on that North Star. It it can get buried like messy very quickly, because you take numbers that, like you’ll assume. Are, you know, valid? But you’re not validating them, you know. There’s no validation. So that’s I mean A, and I’ve learned this lesson, you know, many times kind of in my in my career. So
145 00:12:45.160 ⇒ 00:12:57.829 Jakob Kagel: that that’s exactly what I’m trying to do here is say, like, Okay, the 16 k, like that should be the total right. And then all of our splits should sum to the total. And that’s how we’re gonna validate it like.
146 00:12:58.191 ⇒ 00:13:04.489 Jakob Kagel: so yeah, that’s what we need to do here is, and I don’t know. We may have to push the meeting back a day, because.
147 00:13:04.510 ⇒ 00:13:14.430 Jakob Kagel: like we, I I think, like it should be 16 k. In real, too, right now. We only have 14.6. So we’re missing like 2,000,
148 00:13:14.580 ⇒ 00:13:15.299 Jakob Kagel: you know. It’s that.
149 00:13:15.300 ⇒ 00:13:20.380 Ryan Luke Daque: That’s because we’re like filtering here from January one.
150 00:13:20.760 ⇒ 00:13:24.029 Jakob Kagel: But that’s all time. That’s all time. So I it’s not.
151 00:13:24.030 ⇒ 00:13:24.690 Ryan Luke Daque: So excuse me.
152 00:13:24.690 ⇒ 00:13:27.500 Jakob Kagel: Thing right? Like, I mean, that’s the all time date range.
153 00:13:28.030 ⇒ 00:13:28.889 Ryan Luke Daque: Maybe I can.
154 00:13:28.890 ⇒ 00:13:33.909 Jakob Kagel: Select the same date range in the query, but it it should be the same, because that’s all time.
155 00:13:34.080 ⇒ 00:13:34.830 Ryan Luke Daque: Yeah, I think.
156 00:13:34.830 ⇒ 00:13:37.420 Jakob Kagel: Real quick. What is the date range? It’s like.
157 00:13:37.420 ⇒ 00:13:43.770 Ryan Luke Daque: Yeah, I think maybe would have made a filter over here. Let’s see.
158 00:13:46.160 ⇒ 00:13:51.329 Ryan Luke Daque: Yeah, we’ll have to check on that like, what what filtering is going on.
159 00:13:51.330 ⇒ 00:14:00.249 Jakob Kagel: Part that we need to. Yeah, that we need to check on, and that we need like to figure out. Because, yeah, I think it’s important to say, like, Yeah, this is like our total number of pool.
160 00:14:00.250 ⇒ 00:14:01.480 Nicolas Sucari: Exactly. Yeah.
161 00:14:02.180 ⇒ 00:14:17.449 Jakob Kagel: Cause. This is the whole issue I had with him yesterday, or like the discussion that we had yesterday, too, is like, Okay, like the sales numbers are like not tying out. And then it’s like the namings are confusing to like, you know, like, I don’t think.
162 00:14:17.970 ⇒ 00:14:18.820 Jakob Kagel: yeah.
163 00:14:19.180 ⇒ 00:14:20.510 Jakob Kagel: I yeah.
164 00:14:20.700 ⇒ 00:14:31.299 Jakob Kagel: I don’t. Yeah, exactly. So I I just think exactly like, yeah, we just need to first, st just align on this total number and see, like, okay, is that number going to match like in the dashboard from the table.
165 00:14:31.370 ⇒ 00:14:37.509 Jakob Kagel: like, you know. And if it doesn’t, yeah, why is it only 14 K. And why is it? Not? 16? K, you know.
166 00:14:38.270 ⇒ 00:14:39.180 Jakob Kagel: Yeah.
167 00:14:39.180 ⇒ 00:14:43.062 Ryan Luke Daque: I’m trying to see if, like this matches. If we add all these like
168 00:14:43.340 ⇒ 00:14:44.220 Nicolas Sucari: Yeah, but it will.
169 00:14:44.220 ⇒ 00:14:45.290 Ryan Luke Daque: We, we.
170 00:14:45.600 ⇒ 00:15:00.340 Nicolas Sucari: Yeah, but we don’t need to add like the exact number, because if we are like considering each they mentioned separately, probably there are duplicates between them. Right? Probably one of the emails is considered as self identified too. So what we need to do is to have.
171 00:15:00.500 ⇒ 00:15:00.660 Ryan Luke Daque: Yeah.
172 00:15:00.660 ⇒ 00:15:03.549 Nicolas Sucari: 3 numbers are split apart and then
173 00:15:03.610 ⇒ 00:15:09.570 Nicolas Sucari: look between them to remove duplicate. Okay, once we have that number, we can start doing like
174 00:15:09.914 ⇒ 00:15:27.819 Nicolas Sucari: Ryan just left. Okay. But once we have that that number, we just start to split with different flags and understand how to segment that like big number. I think that’s the best way, and that’s the only way that each of the segmentation that we are gonna do afterwards will sum up the total number right.
175 00:15:28.630 ⇒ 00:15:46.643 Jakob Kagel: I agree. I I guess he dropped from the call. I don’t know. But yeah, I agree with you. And yeah, I don’t know. I don’t think that like I don’t think we should be too much in a rush. I mean, I know we wanna like, like, you know, present the stuff like to them. But we I mean, I think it’s more important that we like align on the.
176 00:15:46.890 ⇒ 00:15:47.770 Nicolas Sucari: Studies, yeah.
177 00:15:48.030 ⇒ 00:15:48.420 Jakob Kagel: Exactly.
178 00:15:48.420 ⇒ 00:15:50.049 Nicolas Sucari: We need to be accurate. Yeah.
179 00:15:50.050 ⇒ 00:15:59.880 Jakob Kagel: Back a day or whatever. Then we should do that, because, yeah, I don’t want to go in there and say, like, these are the numbers. And then we have to come back a week later. And we’re not confident. Basically.
180 00:15:59.880 ⇒ 00:16:07.458 Nicolas Sucari: No, no, me, me, neither. Me neither. So yeah, let’s let’s hope yeah, that Brian can work on it, or I don’t know. I’m gonna ask.
181 00:16:08.040 ⇒ 00:16:28.688 Jakob Kagel: I mean, I can jump on later this afternoon, too, like and yeah, so I mean, yeah, just let me know. But yeah, I think we. We’re on the same page. So we just need to communicate with him sort of like what the issue is and like what the concern is, and and why, like exactly, we want like these numbers like need to tie out. So
182 00:16:29.400 ⇒ 00:16:52.139 Nicolas Sucari: You know what we can do? You wanna write like what should be the names of the actual variables that we need to like like what what you’re hoping to understand from the variables. Just write that names and what to include like a brief description. And we can share that with put them and see if if that works so that we can all understand like the same thing.
183 00:16:52.910 ⇒ 00:16:56.224 Jakob Kagel: You mean like for each of the flags or whatnot like, yeah, like.
184 00:16:56.480 ⇒ 00:17:09.369 Nicolas Sucari: We? We have. Yeah, we have 3 different variables, right? That make out that that aggregate, all of aggregating them will do our baseline number so like what should be like the name of that variable
185 00:17:09.850 ⇒ 00:17:18.510 Nicolas Sucari: that each variable that we need, and what will be like the name of the aggregate variable like will be our baseline pull pro segment right?
186 00:17:18.940 ⇒ 00:17:20.537 Jakob Kagel: Yeah, I mean,
187 00:17:21.560 ⇒ 00:17:26.509 Nicolas Sucari: So that we can, so that we can agree in the best naming like convention
188 00:17:26.520 ⇒ 00:17:31.749 Nicolas Sucari: from all of us, and everyone understand, like what we need to do with the same information.
189 00:17:32.970 ⇒ 00:17:35.339 Nicolas Sucari: I can do it, if not. But yeah.
190 00:17:35.920 ⇒ 00:17:36.360 Jakob Kagel: Right.
191 00:17:36.360 ⇒ 00:17:37.450 Nicolas Sucari: Like, I’m like.
192 00:17:37.590 ⇒ 00:17:41.274 Jakob Kagel: Yeah, no, it’s fine. I mean, yeah, I’m I’m happy to help, too. I think.
193 00:17:41.610 ⇒ 00:17:45.380 Jakob Kagel: I think the 1st thing like in terms of the order of operations is like.
194 00:17:45.490 ⇒ 00:18:03.610 Jakob Kagel: let’s 1st like, figure out, why does the self identified flag number not match like in real? That’s the 1st one, right, so like. Why is it 14 k. Instead of 16 k. Then the next one is like, why is our derived pool pro flag less than the the self identified. One
195 00:18:03.760 ⇒ 00:18:17.710 Jakob Kagel: like that doesn’t make any sense either. Right? Like, why is it 675? It should be over 15 k. Or over 16 k. Whatever, like, you know, because we’re not like they, they shouldn’t be mutually exclusive. We’re like trying to combine them.
196 00:18:17.930 ⇒ 00:18:18.670 Jakob Kagel: Yeah. And.
197 00:18:18.670 ⇒ 00:18:19.260 Nicolas Sucari: Exactly.
198 00:18:19.610 ⇒ 00:18:39.804 Jakob Kagel: And then once we do that like we, and we finalize the derived logic, right? And say, like, Okay, it’s like 2 plus orders or 2 plus pump orders. Right? Then, we need to align on. Okay, this is the overall derived number, right? Like this is like the number that we’re gonna say is like the total number of pool pros.
199 00:18:40.940 ⇒ 00:18:58.220 Jakob Kagel: and yeah, because even the 675, or whatever doesn’t match either like what is in this the shopify orders or shopify customers. Table for the derived flag like is pool pro, because that number’s like 800 something. So there’s still one’s missing there, too. Yeah.
200 00:18:59.890 ⇒ 00:19:10.760 Jakob Kagel: But yeah, I think we should. Yeah, I think we should just jump on a call with him like later today. If he’s free. And I’m pretty free this afternoon, so
201 00:19:11.660 ⇒ 00:19:12.950 Jakob Kagel: just let me know.
202 00:19:16.330 ⇒ 00:19:16.760 Ryan Luke Daque: Cool.
203 00:19:17.125 ⇒ 00:19:17.490 Nicolas Sucari: Great.
204 00:19:17.860 ⇒ 00:19:19.568 Jakob Kagel: Cool. I gotta jump. Yeah.
205 00:19:19.910 ⇒ 00:19:28.669 Nicolas Sucari: Okay, I’m gonna I’m gonna send like, what are the numbers that we are expecting? I think. What do we need to do with the aggregate and see if everyone is like.
206 00:19:29.025 ⇒ 00:19:53.120 Nicolas Sucari: If everyone agrees on that that number, okay? And then we can start looking into why, the table is saying a number on real saying a different number, and we can try to fix that just to clarify. We got the self identified flag from Checkout. The amount of pros identified by email address. And we have the clients that order 2 or more pumps in a 3, 65 day period. Right? Like those are the 3
207 00:19:53.120 ⇒ 00:20:01.629 Nicolas Sucari: variables, or the last one needs to change. How was the what we agreed on the amount of orders or pumps? I know I don’t remember.
208 00:20:01.630 ⇒ 00:20:11.599 Jakob Kagel: I’m i i’m fine. I mean, I’m I’m I’m indifferent kind of on that, I think he, you know, decided I can’t remember exactly what we said, but
209 00:20:11.920 ⇒ 00:20:13.560 Jakob Kagel: I also don’t think like
210 00:20:13.670 ⇒ 00:20:28.069 Jakob Kagel: I also don’t think like for this next meeting that we necessarily need to have, like our own derived definition. Yet I mean, I I now I think the conversation that we’re gonna have in the meeting is gonna be like, Hey, this is the split for one. Order this for 2 orders.
211 00:20:28.070 ⇒ 00:20:42.200 Nicolas Sucari: Okay, exactly. So I’m not. I’m not. Gonna consider that variable in the base number. I’m gonna leave it for the segmentation later so that we can split that base number into one order to orders more than 2 orders and different stuff. Okay.
212 00:20:42.200 ⇒ 00:20:54.139 Jakob Kagel: Right? Right? Exactly. I mean, so yeah, so I think that exactly for the meeting, exactly. It’s like, we wanna say, like, Okay, these are the splits. And like, Yeah, do you wanna do 2 orders? You wanna do 2 plus like greater than.
213 00:20:54.140 ⇒ 00:20:54.930 Nicolas Sucari: Exactly.
214 00:20:54.930 ⇒ 00:21:15.920 Jakob Kagel: They’re gonna like they can pick the logic or whatever. So that’s why it’s not even the derived part is not even that important. I think we maybe got ahead of ourselves a little bit here. But the what’s really important is like, Okay, why is it? 14.6 K and not 16 in real, you know. And then, yeah, what is like the total number. And how do we get that, like, you know, to tie out? So yeah.
215 00:21:17.280 ⇒ 00:21:22.960 Jakob Kagel: Anyway, I got to bounce real quick. But yeah, just let me know if we need to jump on later.
216 00:21:24.850 ⇒ 00:21:26.230 Jakob Kagel: Okay, so that’s good.
217 00:21:26.870 ⇒ 00:21:27.810 Ryan Luke Daque: That’s good.
218 00:21:29.890 ⇒ 00:21:31.780 Nicolas Sucari: segmentation.
219 00:21:31.830 ⇒ 00:21:39.389 Nicolas Sucari: Or how do you say, after, okay, perfect. Okay, don’t worry. I’m I’ll send this message. And yeah.
220 00:21:39.390 ⇒ 00:21:41.850 Jakob Kagel: Let me, I’ll I’ll be free. Sounds good. See? It.
221 00:21:42.590 ⇒ 00:21:43.170 Nicolas Sucari: Thank you.
222 00:21:43.570 ⇒ 00:21:44.770 Ryan Luke Daque: Thanks thanks guys.
223 00:21:45.880 ⇒ 00:21:46.680 Nicolas Sucari: Thank you.