Meeting Title: Zoom-Meeting Date: 2024-10-29 Meeting participants: Luke Daque, Nicolas Sucari


WEBVTT

1 00:00:46.740 00:00:47.620 Nicolas Sucari: Hey, Ryan.

2 00:00:48.840 00:00:51.489 Luke Daque: Yeah. Hi, Nico, how’s it? How’s it going.

3 00:00:52.680 00:00:54.259 Nicolas Sucari: Doing good about you.

4 00:00:55.700 00:00:57.420 Luke Daque: Yeah, doing? Well, so far.

5 00:01:01.510 00:01:06.039 Luke Daque: Yeah, that’s probably I can share my screen. So we can

6 00:01:06.660 00:01:07.260 Luke Daque: see.

7 00:01:07.260 00:01:07.740 Nicolas Sucari: Okay.

8 00:01:07.740 00:01:08.300 Luke Daque: Been

9 00:01:09.380 00:01:11.699 Luke Daque: what we are up to.

10 00:01:11.700 00:01:15.189 Nicolas Sucari: Yeah, I think Payas is a little bit like kind of

11 00:01:15.500 00:01:18.100 Nicolas Sucari: disorganized, and we can help him

12 00:01:18.820 00:01:19.449 Nicolas Sucari: get details.

13 00:01:19.450 00:01:20.180 Luke Daque: Yeah.

14 00:01:20.180 00:01:21.070 Nicolas Sucari: Where we?

15 00:01:21.510 00:01:26.129 Nicolas Sucari: Yeah, but because we, I think we have everything clear. But he’s kind of a little bit

16 00:01:26.440 00:01:32.020 Nicolas Sucari: disorganized and getting some stuff from tables we shouldn’t be using. Maybe.

17 00:01:32.870 00:01:34.829 Luke Daque: Yeah, that’s also one thing.

18 00:01:36.022 00:01:39.399 Luke Daque: Yeah, he’s like looking into the Dev tables

19 00:01:40.400 00:01:42.459 Luke Daque: and stuff like that. So

20 00:01:43.290 00:01:45.870 Luke Daque: yeah, we can, we can talk about that.

21 00:01:47.090 00:01:56.578 Luke Daque: So yeah, basically, just quick updates on my end. For yesterday I was like working mostly on the real dashboard that I showed you, which was,

22 00:01:57.580 00:01:59.229 Luke Daque: yeah, this one, like

23 00:01:59.580 00:02:01.070 Luke Daque: I tried to.

24 00:02:02.880 00:02:04.959 Luke Daque: I tried to replicate

25 00:02:05.689 00:02:10.640 Luke Daque: what we had in pool parts to go for the Kpi aggregates, but this time I

26 00:02:10.710 00:02:13.963 Luke Daque: use the logic that he has on his

27 00:02:15.330 00:02:16.730 Luke Daque: What do you call that?

28 00:02:17.460 00:02:18.320 Luke Daque: And I mean.

29 00:02:18.780 00:02:19.700 Nicolas Sucari: Yeah, okay.

30 00:02:19.700 00:02:24.090 Luke Daque: Yeah, the the query. So basically, it already has the new sub sales

31 00:02:24.290 00:02:28.040 Luke Daque: and stuff like that. That he has new non sub

32 00:02:28.220 00:02:28.930 Luke Daque: new order.

33 00:02:28.930 00:02:35.589 Nicolas Sucari: But you’re taking. You’re taking. All of those metrics are in the pro table impact orders.

34 00:02:36.030 00:02:38.786 Luke Daque: Yes, that’s correct. So it’s coming from.

35 00:02:40.778 00:02:43.120 Luke Daque: Where’s my Vs code here?

36 00:02:43.380 00:02:44.870 Luke Daque: So this one.

37 00:02:45.440 00:02:50.860 Luke Daque: these are all coming from fact orders, which is yeah the one that Brian created.

38 00:02:51.080 00:02:54.334 Luke Daque: And I just had like a few updates here, because,

39 00:02:54.720 00:02:58.029 Luke Daque: there was initially no customer type. So I added this

40 00:02:59.528 00:03:05.110 Luke Daque: field, so we can filter it out. But anyway, aside from that.

41 00:03:06.280 00:03:10.549 Luke Daque: yeah, that was it. And so far it looks to be

42 00:03:11.830 00:03:13.540 Luke Daque: matching, I believe, like

43 00:03:14.930 00:03:16.489 Luke Daque: Where was the video?

44 00:03:17.990 00:03:20.280 Luke Daque: Wait, let me let me open that

45 00:03:22.930 00:03:24.280 Luke Daque: video.

46 00:03:25.910 00:03:27.380 Luke Daque: I think it was

47 00:03:27.860 00:03:29.880 Luke Daque: yeah, this this I haven’t

48 00:03:29.960 00:03:32.190 Luke Daque: checked yet, like for from Robert. But

49 00:03:34.560 00:03:35.220 Nicolas Sucari: Okay.

50 00:03:37.180 00:03:38.380 Luke Daque: Where? Where was that

51 00:03:42.760 00:03:43.680 Luke Daque: this one?

52 00:03:54.810 00:03:57.060 Luke Daque: So basically, he was looking at

53 00:03:58.240 00:04:00.680 Luke Daque: this for the month of September.

54 00:04:00.840 00:04:03.220 Luke Daque: Right? So total

55 00:04:04.528 00:04:08.580 Luke Daque: orders would be 117,933,

56 00:04:08.690 00:04:12.610 Luke Daque: which I checked in the one that I created.

57 00:04:13.660 00:04:14.640 Luke Daque: It’s

58 00:04:16.440 00:04:21.059 Luke Daque: yes, 117,933. So we should be

59 00:04:21.620 00:04:22.910 Luke Daque: good with that.

60 00:04:23.750 00:04:25.849 Luke Daque: Yeah, not this one.

61 00:04:26.520 00:04:32.289 Luke Daque: This one isn’t exactly matching, though this is, we have 39, 4, 7, 8,

62 00:04:32.720 00:04:34.129 Luke Daque: where he has

63 00:04:38.520 00:04:44.290 Luke Daque: 39, 4, 1 0. So we’re like off by a bit.

64 00:04:44.640 00:04:47.439 Luke Daque: But but this is like where I’m

65 00:04:48.190 00:04:50.839 Luke Daque: probably don’t know like what

66 00:04:50.880 00:04:52.540 Luke Daque: exactly.

67 00:04:54.060 00:04:54.500 Nicolas Sucari: Or one.

68 00:04:54.500 00:04:58.510 Luke Daque: On like, maybe there’s like existing logic for

69 00:04:59.331 00:05:04.419 Luke Daque: that’s not matching between pay us and us like from the fact orders.

70 00:05:04.500 00:05:07.520 Luke Daque: because in Payas query.

71 00:05:08.110 00:05:10.729 Luke Daque: which was the long one? Where was that?

72 00:05:26.860 00:05:28.490 Luke Daque: or is it this one?

73 00:05:42.110 00:05:46.030 Luke Daque: Where is the where is the database? I wonder if I can still

74 00:05:47.080 00:05:49.290 Luke Daque: still have the metabase query.

75 00:05:49.570 00:05:50.749 Luke Daque: oh, yeah. Here.

76 00:05:54.390 00:05:58.280 Luke Daque: So yeah, like one of the things that I didn’t know like he did this

77 00:05:59.280 00:06:02.020 Luke Daque: conversion time zone conversion to

78 00:06:03.360 00:06:08.490 Luke Daque: Timestamp Ntz, so this is. This was also like one of the reasons why we weren’t matching.

79 00:06:08.730 00:06:10.660 Luke Daque: And then like this one.

80 00:06:16.500 00:06:20.199 Luke Daque: And this is just to determine whether it’s new or not.

81 00:06:21.060 00:06:21.730 Nicolas Sucari: Yeah.

82 00:06:24.440 00:06:29.190 Luke Daque: But here in the is subscription order. I don’t really know like what.

83 00:06:31.160 00:06:37.839 Luke Daque: how he got this like, what is his description, or like logic to get his subscription order.

84 00:06:38.974 00:06:41.199 Luke Daque: But we do have that.

85 00:06:42.660 00:06:43.510 Luke Daque: It

86 00:06:46.310 00:06:48.400 Luke Daque: is subscription order

87 00:06:49.570 00:06:52.050 Luke Daque: in the fact they also in.

88 00:06:55.800 00:06:57.739 Luke Daque: But I don’t really know, like.

89 00:06:57.780 00:07:00.480 Luke Daque: if this is the same logic that

90 00:07:01.590 00:07:02.980 Luke Daque: that he’s using.

91 00:07:03.700 00:07:04.410 Nicolas Sucari: Okay.

92 00:07:05.080 00:07:07.590 Luke Daque: So maybe this is like one of the reasons

93 00:07:07.820 00:07:12.969 Luke Daque: why, if there’s like a discrepancy in our logic, this could probably be

94 00:07:13.320 00:07:15.130 Luke Daque: one of the reasons why

95 00:07:15.410 00:07:17.751 Luke Daque: we’re not exactly matching because

96 00:07:18.300 00:07:20.539 Luke Daque: because of this. So I’m not sure.

97 00:07:21.330 00:07:24.540 Luke Daque: And like this tick, tock shop is false.

98 00:07:25.280 00:07:26.630 Luke Daque: It’s probably

99 00:07:26.720 00:07:27.950 Luke Daque: also like.

100 00:07:28.330 00:07:30.039 Luke Daque: just one of the tags.

101 00:07:31.430 00:07:33.100 Luke Daque: But yeah, there’s there’s yeah.

102 00:07:33.630 00:07:34.259 Luke Daque: It’s a couple.

103 00:07:34.260 00:07:34.630 Nicolas Sucari: Okay.

104 00:07:34.630 00:07:36.450 Luke Daque: Discrepancies for force

105 00:07:36.540 00:07:37.859 Luke Daque: for this

106 00:07:39.100 00:07:40.420 Luke Daque: the measures here.

107 00:07:40.530 00:07:41.510 Luke Daque: But except for that.

108 00:07:41.510 00:07:41.850 Nicolas Sucari: Thank you.

109 00:07:41.850 00:07:42.959 Luke Daque: Orders, which is exactly.

110 00:07:42.960 00:07:43.480 Nicolas Sucari: You know.

111 00:07:43.480 00:07:44.370 Luke Daque: Name, now.

112 00:07:44.820 00:07:47.149 Nicolas Sucari: You’re you’re comparing September

113 00:07:47.390 00:07:47.970 Nicolas Sucari: to August.

114 00:07:47.970 00:07:48.400 Luke Daque: Yes.

115 00:07:48.830 00:07:51.709 Nicolas Sucari: Think his. His metrics are in August right like.

116 00:07:52.980 00:07:57.160 Luke Daque: I think it’s September like in based on this one.

117 00:07:58.330 00:07:58.780 Nicolas Sucari: Okay.

118 00:07:59.630 00:08:00.740 Luke Daque: He’s also like

119 00:08:02.010 00:08:04.550 Luke Daque: previous. Yeah, it’s it’s also September.

120 00:08:05.280 00:08:06.510 Luke Daque: Comparing to.

121 00:08:06.510 00:08:09.509 Nicolas Sucari: Oh, yeah, yeah, it’s September. Don’t worry. Yeah, it’s it’s September.

122 00:08:11.430 00:08:12.090 Nicolas Sucari: cool.

123 00:08:12.280 00:08:20.150 Luke Daque: But anyway, that’s that for this one at least we’re pretty close, I think. We just need to clarify a bit of some of the logic to get

124 00:08:20.290 00:08:22.000 Luke Daque: the other measures. But

125 00:08:22.270 00:08:27.600 Luke Daque: this should be good for comparing like month on month, or like even week on week right? They can also do.

126 00:08:27.600 00:08:33.759 Nicolas Sucari: Yeah, yeah, and that’s fine. I I think. He’s. Can you go to his query on metase again?

127 00:08:36.409 00:08:41.600 Nicolas Sucari: Where is he? He’s taking all of the data from where.

128 00:08:42.720 00:08:44.400 Nicolas Sucari: from the debt table, right?

129 00:08:44.670 00:08:47.400 Nicolas Sucari: But from which of the.

130 00:08:48.150 00:08:52.420 Luke Daque: I think, just from Meta Base itself from the

131 00:08:53.480 00:08:55.610 Luke Daque: raw. I believe so like.

132 00:08:56.160 00:08:59.989 Nicolas Sucari: Yeah, but the raw one. That’s what I’m trying to say. The raw one, I think

133 00:09:02.060 00:09:08.000 Nicolas Sucari: I think that’s the dev one where you see like that’s not getting updated. If we don’t run the query.

134 00:09:10.930 00:09:11.850 Nicolas Sucari: I don’t know.

135 00:09:12.160 00:09:13.270 Nicolas Sucari: I’m not sure

136 00:09:13.650 00:09:14.780 Nicolas Sucari: about that one.

137 00:09:17.992 00:09:19.600 Luke Daque: Fix the fact! Order.

138 00:09:20.120 00:09:21.409 Nicolas Sucari: Yeah, you see.

139 00:09:22.640 00:09:23.460 Nicolas Sucari: because.

140 00:09:23.460 00:09:24.120 Luke Daque: Yeah.

141 00:09:24.340 00:09:29.569 Nicolas Sucari: Because he’s doing all of the analysis for shopify and our pro tables has both has both

142 00:09:29.620 00:09:36.299 Nicolas Sucari: shopify and Amazon. That’s why he’s using the dev. Maybe we should create the prod one only for shopify right?

143 00:09:38.970 00:09:40.349 Luke Daque: Yeah, we can do that.

144 00:09:41.030 00:09:41.760 Nicolas Sucari: That’s.

145 00:09:41.760 00:09:44.819 Luke Daque: Unless you can just filter it out. It’s easy to just.

146 00:09:45.400 00:09:45.890 Nicolas Sucari: Yeah, yeah.

147 00:09:45.890 00:09:47.670 Luke Daque: The Amazon, one.

148 00:09:48.110 00:09:52.390 Nicolas Sucari: He should filter out Amazon. It’s using the app source. I think

149 00:09:52.620 00:09:53.310 Nicolas Sucari: it’s the field.

150 00:09:53.310 00:09:53.850 Luke Daque: Right.

151 00:09:53.850 00:09:54.440 Nicolas Sucari: Right.

152 00:09:55.070 00:09:55.670 Luke Daque: Yeah.

153 00:09:57.000 00:10:01.840 Nicolas Sucari: We should let him know that, so maybe he can fix that and see if the numbers are

154 00:10:02.100 00:10:02.720 Nicolas Sucari: correct.

155 00:10:02.720 00:10:03.629 Luke Daque: The same.

156 00:10:04.090 00:10:08.189 Nicolas Sucari: Yeah, so that we both got the data from the same place right?

157 00:10:10.620 00:10:12.760 Luke Daque: Yeah, let’s see if we can.

158 00:10:14.040 00:10:16.110 Luke Daque: Let’s try to do that here.

159 00:10:20.310 00:10:22.619 Luke Daque: because I have access to.

160 00:10:24.910 00:10:30.199 Nicolas Sucari: Yeah, but but we don’t have. We don’t have shop. The the table is not called shopify order.

161 00:10:30.240 00:10:31.640 Nicolas Sucari: It’s called.

162 00:10:31.640 00:10:32.340 Luke Daque: Right.

163 00:10:32.340 00:10:33.340 Nicolas Sucari: Orders.

164 00:10:33.700 00:10:34.360 Luke Daque: Right.

165 00:10:34.970 00:10:36.910 Luke Daque: So this has to change as well.

166 00:10:37.670 00:10:38.930 Nicolas Sucari: Yeah, exactly.

167 00:10:40.830 00:10:42.999 Nicolas Sucari: I think it’s fact. Orders.

168 00:10:43.930 00:10:47.547 Luke Daque: And then this will have to filter also.

169 00:10:49.960 00:10:52.270 Nicolas Sucari: Yeah, I’m sorry. It’s called Shopify.

170 00:10:54.540 00:10:56.199 Luke Daque: Let’s see if this will

171 00:10:56.620 00:10:58.340 Luke Daque: have the same output.

172 00:11:01.200 00:11:01.800 Luke Daque: Oh.

173 00:11:01.800 00:11:02.580 Nicolas Sucari: Hmm.

174 00:11:05.860 00:11:10.839 Nicolas Sucari: but yeah, the thing is, if you go to the database, we don’t have the table here. That’s why.

175 00:11:11.185 00:11:13.260 Luke Daque: Yeah. So he didn’t put the

176 00:11:13.520 00:11:14.230 Luke Daque: fact

177 00:11:14.330 00:11:16.649 Luke Daque: orders here yet. Yes.

178 00:11:16.650 00:11:17.420 Nicolas Sucari: We need to.

179 00:11:17.420 00:11:18.030 Luke Daque: Orders, so.

180 00:11:18.030 00:11:21.520 Nicolas Sucari: Yeah, exactly. But these facts shopify orders. This is them.

181 00:11:22.420 00:11:24.220 Luke Daque: Right? Yeah.

182 00:11:24.540 00:11:27.380 Luke Daque: that’s yeah. That’s that’s kind of a problem.

183 00:11:28.460 00:11:30.279 Luke Daque: Well, we can try this in

184 00:11:31.100 00:11:32.120 Luke Daque: Snowflake.

185 00:11:32.630 00:11:33.700 Nicolas Sucari: Yeah, exactly.

186 00:11:34.470 00:11:36.270 Luke Daque: Let’s let me just create.

187 00:11:46.690 00:11:49.110 Nicolas Sucari: You have to select warehouse top. Right?

188 00:12:07.700 00:12:12.909 Nicolas Sucari: You see, I think we have the same that we yeah, it’s the same that we are getting in real.

189 00:12:15.720 00:12:18.520 Nicolas Sucari: I remember the 39.4, I think.

190 00:12:20.490 00:12:24.639 Luke Daque: And he had. What this? What did we have here?

191 00:12:34.820 00:12:37.329 Luke Daque: He had 39, 4, 10.

192 00:12:37.960 00:12:38.800 Luke Daque: We have.

193 00:12:39.860 00:12:40.580 Nicolas Sucari: That’s fine!

194 00:12:40.610 00:12:42.349 Luke Daque: 8, 9, 4, 10,

195 00:12:43.040 00:12:44.390 Luke Daque: and in real

196 00:12:46.100 00:12:47.129 Luke Daque: nice to meet you.

197 00:12:51.570 00:12:52.160 Luke Daque: Don’t go.

198 00:12:52.160 00:12:52.850 Nicolas Sucari: To me.

199 00:12:55.810 00:12:58.940 Luke Daque: Yeah. Here, it’s 39, 4, 7, 8.

200 00:13:02.070 00:13:07.039 Nicolas Sucari: Maybe because of the time zone, different time zones or something like that.

201 00:13:07.500 00:13:08.980 Nicolas Sucari: But it’s close enough.

202 00:13:09.130 00:13:12.549 Nicolas Sucari: Total orders 1 17. And let’s go.

203 00:13:20.530 00:13:20.990 Luke Daque: Use.

204 00:13:20.990 00:13:22.040 Nicolas Sucari: Qtc.

205 00:13:22.970 00:13:25.459 Nicolas Sucari: What is he using in metabase? Do you know.

206 00:13:34.700 00:13:37.520 Luke Daque: He’s converting it from Utc to.

207 00:13:42.240 00:13:44.140 Nicolas Sucari: That’s pacific, right?

208 00:13:44.140 00:13:45.170 Luke Daque: Yeah.

209 00:13:45.170 00:13:45.960 Nicolas Sucari: That’s pacific.

210 00:13:45.960 00:13:46.920 Luke Daque: And then.

211 00:13:48.270 00:13:49.350 Luke Daque: yeah.

212 00:13:51.810 00:13:54.050 Nicolas Sucari: And what if you leave, can you?

213 00:13:54.160 00:13:55.100 Nicolas Sucari: Hmm.

214 00:13:55.810 00:13:57.640 Nicolas Sucari: I don’t wanna change the output.

215 00:13:58.720 00:14:02.980 Nicolas Sucari: Okay, let’s see. Let’s ask him. But we are really close on this one. Don’t worry.

216 00:14:03.750 00:14:04.089 Luke Daque: Yeah.

217 00:14:05.190 00:14:06.909 Luke Daque: the next.

218 00:14:07.150 00:14:13.409 Luke Daque: Yeah. So yeah, we can. We can check with him on this. But this would be a great way to like the drill down I mean the.

219 00:14:13.410 00:14:13.850 Nicolas Sucari: Yeah.

220 00:14:13.850 00:14:15.779 Luke Daque: Do a monthly of more.

221 00:14:16.250 00:14:17.300 Luke Daque: be sure.

222 00:14:17.770 00:14:19.016 Luke Daque: But anyway,

223 00:14:20.440 00:14:29.449 Luke Daque: The other thing that I was doing is trying to figure out like what he has, for, like the returns, refunds returns.

224 00:14:29.690 00:14:31.250 Luke Daque: which is pretty

225 00:14:31.530 00:14:32.770 Luke Daque: confusing.

226 00:14:32.930 00:14:34.410 Luke Daque: because if we look at

227 00:14:35.400 00:14:42.543 Luke Daque: refunds, I mean it’s called refunds. We don’t have a return stable even in the raw.

228 00:14:43.290 00:14:49.550 Luke Daque: So if you look at the raw table, we don’t have anything re related to returns, but we have refund right.

229 00:14:50.354 00:14:55.179 Luke Daque: and if I just sum up the refunds, it’s never. It’s not even close

230 00:14:56.350 00:14:58.600 Luke Daque: like to this value, like

231 00:14:58.680 00:15:00.070 Luke Daque: 300 and

232 00:15:00.440 00:15:02.519 Luke Daque: and 60. This is for August, though.

233 00:15:03.300 00:15:04.310 Luke Daque: Okay.

234 00:15:04.530 00:15:07.300 Luke Daque: So refunds would just be very close, like

235 00:15:07.490 00:15:10.190 Luke Daque: a hundred, 90,000 compared to

236 00:15:10.710 00:15:11.410 Luke Daque: 3.

237 00:15:11.410 00:15:11.810 Nicolas Sucari: Yeah.

238 00:15:13.140 00:15:16.180 Nicolas Sucari: And I think, yeah, we need to check the

239 00:15:16.240 00:15:21.869 Nicolas Sucari: the one that Robert sent right the shopify logic message. That’s been.

240 00:15:21.870 00:15:22.300 Luke Daque: Yeah.

241 00:15:22.300 00:15:22.950 Nicolas Sucari: Black.

242 00:15:23.590 00:15:24.280 Luke Daque: Right.

243 00:15:25.110 00:15:25.780 Luke Daque: But

244 00:15:26.050 00:15:28.060 Luke Daque: the other thing is, I think

245 00:15:29.860 00:15:35.880 Luke Daque: I think re Refund returns is different for refunds, and it’s also, it already adds, like

246 00:15:36.180 00:15:38.940 Luke Daque: the tax, and and whatever what else

247 00:15:39.190 00:15:43.070 Luke Daque: it needs to be added, like refund tax, for example, and.

248 00:15:43.070 00:15:43.580 Nicolas Sucari: Okay.

249 00:15:43.580 00:15:44.450 Luke Daque: Their stuff.

250 00:15:44.910 00:15:50.209 Luke Daque: Because if we just compare, like gross sales, for example, in this.

251 00:15:50.210 00:15:50.810 Nicolas Sucari: Yeah.

252 00:15:50.810 00:15:51.939 Luke Daque: Point we have.

253 00:15:52.760 00:15:57.919 Luke Daque: we have the same 600 6.2 million to 5.8 million

254 00:15:59.240 00:16:02.470 Luke Daque: 6.2,000,005.8 million. It’s the same

255 00:16:02.910 00:16:04.959 Luke Daque: even the orders there’s like

256 00:16:05.340 00:16:08.480 Luke Daque: different. But maybe it’s another time. Zone thing

257 00:16:08.550 00:16:12.890 Luke Daque: 82,900 versus 82,008, 9, 8, and 46.

258 00:16:12.890 00:16:13.520 Nicolas Sucari: Yeah, that’s why.

259 00:16:13.520 00:16:14.420 Luke Daque: 1st time.

260 00:16:14.840 00:16:16.510 Luke Daque: Right? It’s very close.

261 00:16:17.104 00:16:26.401 Luke Daque: and then but and if we look at net sales, which is actually in this, it’s just gross sales minus returns minus discounts.

262 00:16:27.380 00:16:31.450 Luke Daque: it’s 2.6,000,005 point 5 million.

263 00:16:31.580 00:16:33.680 Luke Daque: which is actually already.

264 00:16:34.720 00:16:39.100 Luke Daque: Yeah, it’s also not close, like 5.6 million instead of

265 00:16:40.900 00:16:41.670 Luke Daque: 5.

266 00:16:41.670 00:16:42.320 Nicolas Sucari: Okay.

267 00:16:42.620 00:16:43.410 Luke Daque: Yeah, there’s this.

268 00:16:43.410 00:16:44.380 Nicolas Sucari: Something, so.

269 00:16:44.380 00:16:45.020 Luke Daque: Going on.

270 00:16:45.020 00:16:52.460 Nicolas Sucari: Orders. So I think orders and gross sales is kind of we are accurate there. So this something happening in between.

271 00:16:53.070 00:16:53.530 Luke Daque: Yeah.

272 00:16:53.530 00:16:55.559 Nicolas Sucari: Sales. Yeah, because we need to figure out.

273 00:16:56.650 00:16:57.570 Luke Daque: Yeah.

274 00:16:57.900 00:16:59.659 Nicolas Sucari: So what? There should be another.

275 00:17:00.340 00:17:00.980 Nicolas Sucari: Have you?

276 00:17:01.340 00:17:02.160 Nicolas Sucari: Yeah.

277 00:17:02.160 00:17:05.039 Luke Daque: Yeah, I can check this this out.

278 00:17:05.270 00:17:09.330 Luke Daque: But this is for cogs, though like a cost over goods sold. So

279 00:17:09.660 00:17:10.329 Luke Daque: I wasn’t.

280 00:17:10.339 00:17:10.719 Nicolas Sucari: No, no.

281 00:17:11.680 00:17:14.829 Nicolas Sucari: this is everything. Now this is everything else

282 00:17:15.522 00:17:21.850 Nicolas Sucari: up minus cogs. So cogs is not here. This is all of the other costs that are

283 00:17:22.020 00:17:22.509 Nicolas Sucari: in between.

284 00:17:22.510 00:17:23.910 Luke Daque: Oh, okay.

285 00:17:24.180 00:17:30.809 Nicolas Sucari: Cogs is natively the one we have in shopify. So we should find cogs in a table there in the product table, I think.

286 00:17:33.880 00:17:34.859 Nicolas Sucari: from shopify.

287 00:17:34.860 00:17:35.260 Luke Daque: Be fine.

288 00:17:35.260 00:17:39.090 Nicolas Sucari: This is, yeah, this is all extra. Yeah.

289 00:17:40.670 00:17:42.340 Luke Daque: Okay. Sounds good.

290 00:17:44.220 00:17:45.970 Nicolas Sucari: So, yeah, we should check this one.

291 00:17:48.320 00:17:52.759 Luke Daque: Okay, I’ll look into this. Maybe I can see something related to

292 00:17:53.220 00:17:56.169 Luke Daque: refunds or something else. Yeah.

293 00:17:56.950 00:18:02.440 Nicolas Sucari: Okay, cool, excellent. You continue with that until have that meeting with Payas. I’m.

294 00:18:02.440 00:18:02.960 Luke Daque: Okay.

295 00:18:02.960 00:18:04.310 Nicolas Sucari: Trying to.

296 00:18:04.480 00:18:05.560 Nicolas Sucari: Yeah.

297 00:18:06.240 00:18:11.219 Nicolas Sucari: let me go to main switch branch. So I’m gonna fetch origin.

298 00:18:13.900 00:18:14.720 Nicolas Sucari: Okay?

299 00:18:15.469 00:18:19.319 Nicolas Sucari: There was a pull request or something that you merged right.

300 00:18:21.245 00:18:22.280 Luke Daque: Yeah, that was

301 00:18:22.310 00:18:27.079 Luke Daque: pay us. Pr. Wait, this is my keyboard.

302 00:18:30.450 00:18:31.150 Luke Daque: Okay?

303 00:18:32.140 00:18:33.020 Luke Daque: But anyway.

304 00:18:33.456 00:18:40.010 Nicolas Sucari: And if if let me, and trying to check okay, we have all order dashboards.

305 00:18:40.040 00:18:48.489 Nicolas Sucari: daily, Kpi dashboards, and then we have 2 dev ones. We need to replace that that once we brought one. So maybe I can create a model

306 00:18:49.449 00:18:55.749 Nicolas Sucari: for the shopify order one so that we can have all of the shopify metrics in one dashboard.

307 00:18:56.140 00:18:58.359 Nicolas Sucari: Okay, apart coming from

308 00:18:59.360 00:19:02.690 Nicolas Sucari: broad and not there. Okay, I can check that.

309 00:19:03.770 00:19:04.580 Luke Daque: Okay.

310 00:19:04.870 00:19:05.790 Luke Daque: Sounds good.

311 00:19:06.810 00:19:07.580 Luke Daque: Okay.

312 00:19:08.100 00:19:09.520 Nicolas Sucari: Okay, yeah, that’s

313 00:19:09.750 00:19:16.689 Nicolas Sucari: keep keep trying to understand that refunds. And we can just join the meeting with pay us in like 15 min. Okay.

314 00:19:16.940 00:19:19.440 Luke Daque: Sounds good. Thanks. See you bye, bye.

315 00:19:19.440 00:19:20.860 Nicolas Sucari: Thanks, Ryan. Bye-bye.