Meeting Title: PP2G | Standup Date: 2025-04-08 Meeting participants: Luke Daque, Amber Lin, Stephen, Kim Todaro
WEBVTT
1 00:05:36.670 ⇒ 00:05:37.200 Luke Daque: Hello!
2 00:05:37.200 ⇒ 00:05:38.420 Stephen: Luke, can you hear me?
3 00:05:39.020 ⇒ 00:05:43.960 Luke Daque: I can hear you now. Hi, Stefan, can you hear me?
4 00:05:45.280 ⇒ 00:05:48.440 Stephen: Getting audio hold on! This is probably my side. One second.
5 00:05:48.630 ⇒ 00:05:49.570 Luke Daque: No problem.
6 00:06:13.400 ⇒ 00:06:14.940 Stephen: Hi, Luke! Can you hear me now?
7 00:06:15.280 ⇒ 00:06:17.190 Luke Daque: Yep, I can hear you. Can you hear me?
8 00:06:17.190 ⇒ 00:06:20.573 Stephen: Awesome. Yes, yes, I can. So sorry about that.
9 00:06:20.950 ⇒ 00:06:21.330 Luke Daque: No problem.
10 00:06:21.330 ⇒ 00:06:22.060 Stephen: How are you?
11 00:06:22.560 ⇒ 00:06:23.910 Luke Daque: I’m doing well. How are you?
12 00:06:24.690 ⇒ 00:06:26.659 Stephen: I’m doing well. I’m doing well.
13 00:06:26.780 ⇒ 00:06:28.020 Stephen: Happy. Tuesday.
14 00:06:28.020 ⇒ 00:06:34.770 Luke Daque: 1st happy Tuesday days are going by so fast these days. For some reason.
15 00:06:35.890 ⇒ 00:06:36.879 Stephen: A surface area.
16 00:06:36.880 ⇒ 00:06:38.010 Stephen: They are. Yes, they are.
17 00:06:38.250 ⇒ 00:06:40.640 Luke Daque: Yeah, 1st time we met, I believe.
18 00:06:41.910 ⇒ 00:06:54.770 Stephen: Yes, yeah, I’ve I’ve heard I’ve heard from from from the rest of the team. I spoke to Kim last week, and I’m I’m excited to to work through and and see what what what we can what we can figure out with this dashboard.
19 00:06:55.140 ⇒ 00:06:56.750 Luke Daque: Cool. Sounds good.
20 00:06:57.330 ⇒ 00:07:02.969 Luke Daque: Yeah, I think. Let’s probably wait for Kim. I I think she’s joining as well right.
21 00:07:04.760 ⇒ 00:07:06.463 Stephen: Yes, you should be
22 00:07:06.990 ⇒ 00:07:13.559 Stephen: Where? Whereabouts are you? Oh, yeah, that’s that. Is not your actual background. The?
23 00:07:13.560 ⇒ 00:07:14.590 Stephen: Oh, yeah. My wife.
24 00:07:14.590 ⇒ 00:07:19.490 Stephen: I was going a little bit in and out. And it’s like, what is happening here. Okay, no. Sweet. Okay.
25 00:07:19.920 ⇒ 00:07:21.959 Stephen: All good whereabouts are you based.
26 00:07:22.690 ⇒ 00:07:25.406 Luke Daque: Yeah, I’m in the I’m based in the Philippines. So like
27 00:07:26.090 ⇒ 00:07:30.480 Stephen: Oh, or elsewhere. Yeah.
28 00:07:30.916 ⇒ 00:07:36.460 Luke Daque: Further in the south, like in Mindanao, like, yeah, okay.
29 00:07:36.746 ⇒ 00:07:47.063 Stephen: My my godmother is from the Philippines, and she’s been trying to get me and my God brothers, out there for ages. So I’m taking this as a sign. I’ve got to get out there.
30 00:07:47.350 ⇒ 00:07:50.120 Luke Daque: Yeah, you haven’t been here yet, like at all.
31 00:07:51.070 ⇒ 00:07:57.980 Stephen: No, I I have not they! They brought the food. I’ve I’ve had that was.
32 00:07:59.020 ⇒ 00:08:00.839 Luke Daque: That’s cool.
33 00:08:01.240 ⇒ 00:08:02.049 Stephen: I don’t.
34 00:08:02.050 ⇒ 00:08:03.720 Luke Daque: Think I would like it more. Now.
35 00:08:04.465 ⇒ 00:08:07.470 Luke Daque: Cool Medea.
36 00:08:07.470 ⇒ 00:08:08.260 Luke Daque: Nice to meet you.
37 00:08:08.260 ⇒ 00:08:08.799 Luke Daque: Thank you.
38 00:08:09.880 ⇒ 00:08:15.456 Amber Lin: Hi! Do I pronounce your name, Stefan? Or is this.
39 00:08:16.470 ⇒ 00:08:19.130 Stephen: It’s even imagine with a V.
40 00:08:19.130 ⇒ 00:08:21.610 Amber Lin: Oh, okay. Okay. Nice to meet you, Steven.
41 00:08:21.610 ⇒ 00:08:22.210 Stephen: Yeah.
42 00:08:22.630 ⇒ 00:08:24.630 Stephen: Great to meet you, too. Amber, hey, Tim?
43 00:08:25.560 ⇒ 00:08:27.070 kim todaro: Hey, guys, how are you.
44 00:08:28.290 ⇒ 00:08:29.759 Stephen: Doing well, doing well. How are you.
45 00:08:29.760 ⇒ 00:08:30.520 Luke Daque: Good.
46 00:08:30.520 ⇒ 00:08:33.471 kim todaro: Good. I’m just gonna get my glasses. I’ll be right back.
47 00:08:33.740 ⇒ 00:08:34.530 Luke Daque: Sure.
48 00:08:56.719 ⇒ 00:09:06.579 Stephen: And as we’re going through this, do we want to use march as like a proxy? Or do we want to use a different date. We’re using March. Awesome.
49 00:09:06.580 ⇒ 00:09:08.260 Luke Daque: Yeah. Let’s let’s do March.
50 00:09:09.180 ⇒ 00:09:10.040 Stephen: Awesome. Okay?
51 00:09:10.040 ⇒ 00:09:10.889 Stephen: Sorry about all that
52 00:09:10.890 ⇒ 00:09:18.120 Stephen: information. Yeah, no. I’m staring at staring at all the raw data. And I’ve got all the sheets up. So we are good to go.
53 00:09:19.020 ⇒ 00:09:21.799 Stephen: Make sure that nothing else is coming through.
54 00:09:22.520 ⇒ 00:09:25.740 Stephen: Nope, yeah.
55 00:09:28.360 ⇒ 00:09:35.330 kim todaro: All right. So did you guys get started with anything or
56 00:09:36.300 ⇒ 00:09:38.629 kim todaro: Did you want me to like? Just kick this off?
57 00:09:39.510 ⇒ 00:09:40.450 kim todaro: I’m happy to.
58 00:09:40.450 ⇒ 00:09:51.010 Stephen: Just some quick intros. But yeah, if you we I think we’re gonna be looking at March. But just to make sure we’re looking at all the same things, if you don’t mind just going back over. Everything will be awesome.
59 00:09:51.320 ⇒ 00:09:58.949 kim todaro: Yes, I think March is a good proxy, I just, you know, like I’ve been telling both of you. Steven knows way more about our Amazon numbers with.
60 00:09:58.950 ⇒ 00:09:59.650 Luke Daque: Hmm.
61 00:09:59.850 ⇒ 00:10:08.829 kim todaro: Mark within marketing sales and everything. So I figured whatever is not correct in real, he can kind of guide us to where we can find the different sources of information.
62 00:10:09.650 ⇒ 00:10:10.430 Luke Daque: Cool
63 00:10:12.090 ⇒ 00:10:17.832 Luke Daque: sounds good. Do you want me to? I can share my screen. We can start looking at the
64 00:10:18.610 ⇒ 00:10:24.140 Luke Daque: real dashboard, and maybe compare it with what numbers you see from your end.
65 00:10:24.610 ⇒ 00:10:26.039 Luke Daque: Can you see my screen.
66 00:10:26.660 ⇒ 00:10:27.800 Stephen: Yes, I can.
67 00:10:27.970 ⇒ 00:10:30.890 Stephen: Alright. Amazon! 1, 74, 6, and that’s.
68 00:10:30.890 ⇒ 00:10:31.480 Luke Daque: So.
69 00:10:31.480 ⇒ 00:10:32.320 Stephen: Billing platform.
70 00:10:32.320 ⇒ 00:10:35.320 Luke Daque: Yeah, this is for March. Let me zoom in a little bit.
71 00:10:35.860 ⇒ 00:10:39.099 Luke Daque: March the whole month of March.
72 00:10:41.400 ⇒ 00:10:48.820 Luke Daque: We have total sales. Here is 734,000. I believe yours was like around 157.
73 00:10:49.050 ⇒ 00:10:50.920 Luke Daque: But I think this is already
74 00:10:51.190 ⇒ 00:10:57.460 Luke Daque: minus refunds and returns. And this is 7 34. Here is like the total I mean the gross.
75 00:10:58.510 ⇒ 00:11:03.839 kim todaro: Oh, you know what I think. I think maybe you’re clicked on Amazon and shopify. But I could be wrong.
76 00:11:03.840 ⇒ 00:11:05.159 kim todaro: Oh, yeah, sorry. Yeah.
77 00:11:05.160 ⇒ 00:11:06.609 Stephen: Let’s just do, okay.
78 00:11:06.610 ⇒ 00:11:07.539 Luke Daque: I did click on.
79 00:11:07.540 ⇒ 00:11:09.010 Stephen: That’s sold as 6.
80 00:11:10.190 ⇒ 00:11:18.940 Stephen: Hmm, okay, I’m seeing a couple discrepancies total shipment cost as well.
81 00:11:19.450 ⇒ 00:11:23.240 Stephen: Hmm, okay, this is interesting. Here.
82 00:11:23.840 ⇒ 00:11:30.371 Stephen: Yeah. Let’s let’s take a full step back. Where do you get this information like,
83 00:11:31.010 ⇒ 00:11:35.019 Stephen: I’m assuming it’s an Api feed, or or is there something else that
84 00:11:35.420 ⇒ 00:11:39.719 Stephen: that you get that number from, because that’s not what we have.
85 00:11:40.310 ⇒ 00:11:58.480 Luke Daque: This is coming from an Api feed. Basically. So we’re we’re connecting Amazon to snowflake through Api, and then these are the total sales that we’re showing here is basically the sum of the item price times the quantity. So basically, whatever the price of the the item is
86 00:11:59.270 ⇒ 00:12:02.110 Luke Daque: times the number of quantities being ordered.
87 00:12:03.990 ⇒ 00:12:09.129 Luke Daque: Yeah, so this would be gross sales. Right? So this, this will still have to be like
88 00:12:09.550 ⇒ 00:12:13.269 Luke Daque: comparing to to this number. It would be like.
89 00:12:13.960 ⇒ 00:12:15.080 Luke Daque: It’s me higher.
90 00:12:17.130 ⇒ 00:12:36.419 Stephen: You were right sorry I was using. I was using the old sheet. Yes, I’m looking at the data 176. That is correct. That sheet does not have that. I’m Kim. I’m comparing what’s in the dashboard to what’s in what’s in the sales dashboard on Amazon to what’s in the dashboard being shown by Luke currently.
91 00:12:36.757 ⇒ 00:12:48.220 Luke Daque: Cool. And just to just to be clear in Amazon, would, you know, like it’s using if it’s using Utc or any kind of time zone, because this report is using est.
92 00:12:48.850 ⇒ 00:12:50.719 Stephen: Pacific. It uses Pacific.
93 00:12:51.890 ⇒ 00:12:52.920 Luke Daque: I see.
94 00:12:54.436 ⇒ 00:12:55.113 Stephen: Pst
95 00:12:55.790 ⇒ 00:13:00.769 Luke Daque: Yeah. So it’s if I do. Utc here, it’s like 176, which should be.
96 00:13:02.140 ⇒ 00:13:03.299 Stephen: Pretty much it. Yeah.
97 00:13:03.630 ⇒ 00:13:09.059 Stephen: And then, if I do cogs off of that, give me one second.
98 00:13:09.580 ⇒ 00:13:11.839 Luke Daque: And where? Where do you get your calls from?
99 00:13:14.050 ⇒ 00:13:25.010 Stephen: So I have actually just got an updated sheet from chuck with regards to the pricing of all products. And then we multiply the units sold by that cost.
100 00:13:26.231 ⇒ 00:13:39.599 Stephen: So it’s not. Unfortunately, it’s not something that we keep in Amazon. And honestly, for good reason, because they will use that against us. The cost reduction is correct or no sorry cogs should be one.
101 00:13:41.140 ⇒ 00:13:42.419 Stephen: No, that’s accurate.
102 00:13:42.420 ⇒ 00:13:43.300 Luke Daque: Unleashed.
103 00:13:43.420 ⇒ 00:13:47.670 Luke Daque: Oh, yeah, cause we’re getting this from unleashed right? Is that the.
104 00:13:47.670 ⇒ 00:13:48.190 kim todaro: Yes.
105 00:13:48.190 ⇒ 00:13:49.590 Luke Daque: Correct with a call.
106 00:13:49.890 ⇒ 00:13:51.020 Stephen: That’s the same thing. Okay.
107 00:13:51.320 ⇒ 00:13:52.289 kim todaro: And those should be updated.
108 00:13:53.010 ⇒ 00:13:55.590 kim todaro: 8 that Stephen has, they should all be the same.
109 00:13:56.160 ⇒ 00:13:56.870 Luke Daque: Yeah.
110 00:13:57.450 ⇒ 00:13:58.060 Stephen: Yeah.
111 00:13:59.180 ⇒ 00:14:04.489 Stephen: no shipment costs. Do you have? Do you have the raw data for the shipment cost? Because that’s gonna be.
112 00:14:04.860 ⇒ 00:14:12.060 Stephen: that’s something I wanna double check on, just because Amazon can get a little bit scriptpy with with the.
113 00:14:12.060 ⇒ 00:14:12.879 Luke Daque: Yeah, I think.
114 00:14:12.880 ⇒ 00:14:15.780 Stephen: Decimal point. Sometimes I can
115 00:14:15.780 ⇒ 00:14:20.710 Stephen: like, is it possible to break that out by product, like what it’s broken out by.
116 00:14:20.970 ⇒ 00:14:23.839 Stephen: like to the to the lowest. Yeah.
117 00:14:24.520 ⇒ 00:14:34.080 Luke Daque: Yeah, I can probably send it to you after the the call, because that I’ll have to do some like querying and stuff like that. But just to give you an overview on shipments, we are getting a lot of
118 00:14:35.015 ⇒ 00:14:42.080 Luke Daque: it sources from shipments we have, like. Ltl Unis, what else did we got? We have here
119 00:14:42.210 ⇒ 00:14:49.900 Luke Daque: ship station Ltl units Primus, and there’s also like some Florida shipping costs that we’re taking into account, too.
120 00:14:50.910 ⇒ 00:14:51.350 Stephen: Okay.
121 00:14:51.350 ⇒ 00:14:58.260 Luke Daque: Not sure if the all of these are just for shopify, though. But I believe it’s it’s also being used for
122 00:14:58.390 ⇒ 00:15:00.520 Luke Daque: both Walmart and Amazon.
123 00:15:00.840 ⇒ 00:15:03.270 Luke Daque: I can. I can double check real quick.
124 00:15:06.420 ⇒ 00:15:07.640 Luke Daque: Oh, no, it’s shipping.
125 00:15:09.260 ⇒ 00:15:11.000 Luke Daque: So for shipments.
126 00:15:15.120 ⇒ 00:15:16.750 Luke Daque: Yeah, we have chip.
127 00:15:16.750 ⇒ 00:15:18.719 Stephen: Station. Yeah. Ltl.
128 00:15:20.720 ⇒ 00:15:21.280 Luke Daque: Premise.
129 00:15:21.280 ⇒ 00:15:22.030 Stephen: And that’s it.
130 00:15:22.240 ⇒ 00:15:23.890 Luke Daque: Yeah, we’re also having premise.
131 00:15:24.140 ⇒ 00:15:32.279 Luke Daque: And yeah, I think that’s about it for Amazon. The other stuff are poor, shopify. The units is shopify
132 00:15:32.860 ⇒ 00:15:36.340 Luke Daque: and shopify also has promise.
133 00:15:36.800 ⇒ 00:15:42.179 Luke Daque: And yeah, we’re we’re we’re using the the heat pumps
134 00:15:42.570 ⇒ 00:15:46.600 Luke Daque: from for Florida as a different like calculation as well.
135 00:15:47.270 ⇒ 00:16:00.550 Luke Daque: So these are all like coming from chuck, I believe, like all the calculation. So yeah, I can send you the more detailed version of this, which is like per order number. Is it like per per product? I guess.
136 00:16:01.430 ⇒ 00:16:13.170 Stephen: If if you can do it by product, that would be much, much by product or by by order number, actually, because both will will correlate. So either one works. No worries there.
137 00:16:13.570 ⇒ 00:16:18.840 Luke Daque: Cool. And is this like very close to what you have or like? It’s different. It’s way different.
138 00:16:19.640 ⇒ 00:16:22.000 Stephen: It’s different, but I can’t calculate it.
139 00:16:22.130 ⇒ 00:16:49.810 Stephen: I’d have to recalculate everything and kind of bubble it up. So I’d rather have your data, and then kind of parse that back to see what is missing, either by units or by cost, because it’s a lot easier to determine across the board like. Oh, this product has the wrong cost in in our system, in that system or somewhere, and we now need to rectify it versus kind of going one by one, and bubbling up and realizing that it’s still not equal. If that’s the case.
140 00:16:50.140 ⇒ 00:16:51.640 Luke Daque: Gotcha sounds good.
141 00:16:52.214 ⇒ 00:16:59.519 Luke Daque: What about for discounts and marketing so like we don’t have numbers here for both discounts and marketing. Maybe this is like something.
142 00:16:59.520 ⇒ 00:17:13.539 Stephen: Discounts will remain. 0 discounts will remain 0. The marketing I want to triple confirm. That is Amazon. Me, that’s Amazon media specifically on Amazon awesome that is, not being captured so.
143 00:17:13.540 ⇒ 00:17:16.790 Luke Daque: So Amazon ads, you mean right. Amazon ads.
144 00:17:16.790 ⇒ 00:17:17.400 Stephen: Yes.
145 00:17:18.140 ⇒ 00:17:26.049 Luke Daque: Gotcha. So if I currently am because I don’t know how to attribute all the marketing stuff, I’m currently.
146 00:17:26.290 ⇒ 00:17:28.300 Stephen: Attributing everything to.
147 00:17:28.530 ⇒ 00:17:35.859 Luke Daque: Shopify, including Amazon ads. But it looks like Kim. You’re not using Amazon ads for shopify right marketing.
148 00:17:35.860 ⇒ 00:17:42.639 kim todaro: Yeah. Even runs Amazon ads. I don’t touch them for shopify. They’re all within Amazon’s ecosystem.
149 00:17:43.180 ⇒ 00:17:43.840 Luke Daque: Cool.
150 00:17:44.668 ⇒ 00:17:51.079 Luke Daque: So so would you know, Steven, like how much you have for the month of March. I can check it here as well.
151 00:17:52.080 ⇒ 00:17:59.549 Stephen: Yes, last month we spent $14,750.
152 00:18:03.930 ⇒ 00:18:05.859 Luke Daque: 14, 7, 50.
153 00:18:07.730 ⇒ 00:18:09.569 Luke Daque: Let me check
154 00:18:21.060 ⇒ 00:18:25.020 Stephen: It might come up as spend, if not cost
155 00:18:26.160 ⇒ 00:18:27.299 Stephen: But we’ll see.
156 00:18:30.560 ⇒ 00:18:33.079 Luke Daque: It’s maybe not by data. That’s something.
157 00:18:33.930 ⇒ 00:18:34.790 Luke Daque: Okay. Thank you.
158 00:18:34.790 ⇒ 00:18:35.280 Stephen: Balance.
159 00:18:35.280 ⇒ 00:18:37.009 Luke Daque: Let me do like the whole one.
160 00:18:37.510 ⇒ 00:18:38.020 kim todaro: Hmm.
161 00:18:38.280 ⇒ 00:18:39.200 Luke Daque: Of March
162 00:18:43.790 ⇒ 00:18:47.699 Luke Daque: looks like I have 11,000. What did you say? It was 16.
163 00:18:48.820 ⇒ 00:18:50.970 Stephen: 14,750.
164 00:18:50.970 ⇒ 00:18:51.520 Luke Daque: Thank you.
165 00:18:51.690 ⇒ 00:18:55.620 Luke Daque: Hmm, yeah, this might be missing some
166 00:18:55.820 ⇒ 00:19:09.080 Luke Daque: stuff, because I only have 11 here from Amazon ads, and that is yeah. Reducing cost.
167 00:19:15.170 ⇒ 00:19:18.179 Stephen: No cost is right. Yeah, that’s that’s that’s in their notes.
168 00:19:20.020 ⇒ 00:19:22.829 Luke Daque: Yeah, and no, that’s essential.
169 00:19:22.830 ⇒ 00:19:24.680 Stephen: March one to March 31.st
170 00:19:25.080 ⇒ 00:19:29.191 Stephen: Everything that’s spent, and it can’t be less
171 00:19:30.630 ⇒ 00:19:36.410 Luke Daque: Okay, I’ll take a look at this. So let me take note of the number you had, like 1614,000.
172 00:19:36.410 ⇒ 00:19:37.250 Stephen: Is it?
173 00:19:37.420 ⇒ 00:19:49.039 Stephen: Is it calculating everything within Amazon media? Or is it specifically looking at certain product types? And I don’t mean like, in terms of a pump or a brush, I mean, in terms of like the ad type itself.
174 00:19:50.680 ⇒ 00:19:57.899 Luke Daque: It. It should be everything like, based on what we have here. It’s just it’s it’s everything. We’re not filtering to any kind of
175 00:19:58.330 ⇒ 00:20:00.319 Luke Daque: product, class or product, type.
176 00:20:01.280 ⇒ 00:20:09.099 Stephen: Yeah. I wonder? I wonder if it’s skipping something hang on one second. I’m gonna try and filter this down targeting. Oh, no type. I think.
177 00:20:10.500 ⇒ 00:20:16.970 Stephen: portfolio type, sponsored products. Let’s see.
178 00:20:18.020 ⇒ 00:20:22.089 Stephen: what was that number that you had? It was 11, 5, 7, oh.
179 00:20:22.860 ⇒ 00:20:27.690 Stephen: 2,005. Okay, so that is only calculating one product.
180 00:20:27.820 ⇒ 00:20:33.409 Stephen: and that would be sponsored products. There’s 1 other ad type that we are incorporating.
181 00:20:33.800 ⇒ 00:20:39.550 Stephen: It’s called sponsored brands and sponsored display.
182 00:20:40.230 ⇒ 00:20:42.620 Luke Daque: So, 2 2 missing here sponsored by.
183 00:20:42.620 ⇒ 00:20:46.880 Stephen: 2 more sorry. 2 more. Yeah. Sorry. Yeah. Sponsored brands and sponsor display.
184 00:20:49.350 ⇒ 00:20:50.140 Luke Daque: Okay.
185 00:20:51.450 ⇒ 00:20:55.819 Stephen: Let me do this. I’m gonna take a screenshot prepared as possible.
186 00:20:56.300 ⇒ 00:20:59.259 Luke Daque: That’s a campaign name, right? You mentioned.
187 00:21:00.580 ⇒ 00:21:01.890 Stephen: That’s the type.
188 00:21:02.590 ⇒ 00:21:07.840 Luke Daque: Campaign, okay.
189 00:21:08.290 ⇒ 00:21:14.680 Stephen: Yeah. Okay, so campaign, id campaign name asset. Id. Well, they all have ids, so can’t be that
190 00:21:16.210 ⇒ 00:21:18.400 Stephen: name. Impression clicks not on.
191 00:21:53.480 ⇒ 00:21:56.979 Luke Daque: Yeah, but just based on what you saw. It’s like missing
192 00:21:57.980 ⇒ 00:22:02.129 Luke Daque: the sponsored brands and sponsored display. It looks like right.
193 00:22:03.190 ⇒ 00:22:13.629 Stephen: Yes. Okay, so yeah, I’m seeing sponsored. S, if it starts with Sp, that’s sponsored, and that’s across the board. If it doesn’t include Sp, it is not that.
194 00:22:14.520 ⇒ 00:22:15.670 Stephen: interesting.
195 00:22:16.630 ⇒ 00:22:17.859 Luke Daque: Okay. I’ll.
196 00:22:17.860 ⇒ 00:22:18.819 Stephen: Just load it.
197 00:22:20.190 ⇒ 00:22:23.129 Luke Daque: Yeah, it’s not. It looks like it’s not showing
198 00:22:24.510 ⇒ 00:22:28.530 Luke Daque: unless it doesn’t have a campaign name or something, because, like I.
199 00:22:28.530 ⇒ 00:22:35.502 Stephen: No, it it does, it does. I’m gonna export. Let me export the names, the campaigns right here.
200 00:22:36.240 ⇒ 00:22:47.250 Stephen: Ms campaigns. Okay, these give me one second. Alright. I’m gonna put these in chat the
201 00:22:50.570 ⇒ 00:22:54.849 Stephen: the 1st 2. I don’t know why it sent double screenshot the 1st 2.
202 00:22:55.020 ⇒ 00:22:56.719 Luke Daque: Are missing.
203 00:22:57.410 ⇒ 00:23:00.270 Luke Daque: Hmm, okay.
204 00:23:00.280 ⇒ 00:23:02.970 Stephen: And to reconfirm.
205 00:23:03.110 ⇒ 00:23:09.100 Luke Daque: S022-20-2424. Those are looks like campaign names. Right? Something.
206 00:23:09.520 ⇒ 00:23:17.559 Stephen: Yes, yeah, those are the campaign names that at both of those campaigns add up together. So 2024 underscore. Q.
207 00:23:19.090 ⇒ 00:23:21.090 Stephen: Some work.
208 00:23:21.520 ⇒ 00:23:29.320 Stephen: March equals 3, 1, 8, 5, 6, 8. We’re looking for that, or at least close to it.
209 00:23:32.430 ⇒ 00:23:37.500 Luke Daque: Okay, okay. I’ll I’ll
210 00:23:38.050 ⇒ 00:23:43.770 Luke Daque: take note of that. We’ll take a look. Why, it’s not showing here. I’m just trying to see.
211 00:23:44.770 ⇒ 00:23:49.180 Luke Daque: I’m trying to unremove the march filter, and it looks like everything is like.
212 00:23:49.510 ⇒ 00:23:54.760 Luke Daque: Still Sp, something so might be missing something here. I’ll have to.
213 00:23:55.140 ⇒ 00:23:59.709 Stephen: Is there? Are you able to? Are you able to select the
214 00:24:01.070 ⇒ 00:24:05.760 Stephen: Are you able to select campaigns based off of the budget that they have.
215 00:24:07.780 ⇒ 00:24:11.960 Luke Daque: I’ll I I’m not sure but this if you can
216 00:24:12.430 ⇒ 00:24:14.960 Luke Daque: provide some details on that, maybe I can take a look.
217 00:24:14.960 ⇒ 00:24:23.399 Stephen: Yeah, yeah, all right. So let’s do what type of status I call it.
218 00:24:25.390 ⇒ 00:24:30.620 Stephen: And then budget equals greater than $2 and one cents.
219 00:24:33.190 ⇒ 00:24:35.389 Stephen: So every active campaign
220 00:24:36.432 ⇒ 00:24:45.380 Stephen: falls under both of those criteria of it’s everything but archive. So it’s either active or not. But it is still in the system.
221 00:24:45.710 ⇒ 00:24:49.650 Stephen: and the budget has to be greater than $2 and one cent.
222 00:24:49.900 ⇒ 00:25:04.879 Stephen: I basically changed all of the budgets. All the daily budgets that we had across all of our old campaigns. Which is primarily what we’re seeing on this screen right now. Yeah, within those campaign names, those sp bar, bt, bar, swim.
223 00:25:05.200 ⇒ 00:25:05.650 Luke Daque: Right.
224 00:25:05.650 ⇒ 00:25:09.830 Stephen: Those are all old campaigns, and I don’t even see the date that they were created.
225 00:25:10.280 ⇒ 00:25:11.740 Luke Daque: There should, there should be a date.
226 00:25:11.740 ⇒ 00:25:19.060 Stephen: Yeah, 2024 there’s some 2025. But yeah.
227 00:25:19.640 ⇒ 00:25:20.700 Luke Daque: Would you know when these were.
228 00:25:20.700 ⇒ 00:25:21.610 Stephen: That is interesting.
229 00:25:21.610 ⇒ 00:25:23.719 Luke Daque: Pretty much q. 4. So it should.
230 00:25:23.720 ⇒ 00:25:37.699 Stephen: Yes, those, the 2024. Q. 4. Ellipses start dates, equals November 7, th one by 4.
231 00:25:45.910 ⇒ 00:25:47.969 Luke Daque: Look at November here.
232 00:25:48.950 ⇒ 00:25:52.330 Luke Daque: Yeah, it looks like we’re not. We’re not getting any November numbers.
233 00:25:54.000 ⇒ 00:25:58.300 Luke Daque: But yeah, I’ll I’ll take a look. I’ll take a look further. Thanks for the details.
234 00:25:59.130 ⇒ 00:26:00.449 Stephen: No, of course, of course.
235 00:26:02.320 ⇒ 00:26:03.660 Stephen: But okay, so.
236 00:26:03.660 ⇒ 00:26:04.290 Luke Daque: Yeah.
237 00:26:04.650 ⇒ 00:26:07.570 Luke Daque: So that would be for the marketing costs.
238 00:26:07.760 ⇒ 00:26:14.539 Stephen: That’d be for marketing. We’ll get the shipment costs sorted. I’ll update the sheet Kim. So so we have all of that.
239 00:26:14.890 ⇒ 00:26:17.599 Stephen: The total refund amount. Okay.
240 00:26:17.600 ⇒ 00:26:18.630 Luke Daque: 3 flights
241 00:26:20.650 ⇒ 00:26:28.159 Luke Daque: refunds. Let me see how we’re doing refunds. I believe we’re using refund date instead of like the order, create date. For this
242 00:26:28.750 ⇒ 00:26:30.520 Luke Daque: I could go wrong. Let me check.
243 00:26:31.180 ⇒ 00:26:37.690 Stephen: Yeah, if you use the order date, it completely messes up financials. Yeah. Because Amazon will hang on to it forever.
244 00:26:38.460 ⇒ 00:26:44.019 Luke Daque: Right do you have not? Do you have the numbers for march for refund.
245 00:26:45.330 ⇒ 00:26:48.029 Stephen: I don’t have it broken out, but actually I
246 00:26:48.450 ⇒ 00:26:55.439 Stephen: I think I can get to it. But if the numbers, if the number that we added up to was incorrect. I’m gonna have to re pull this.
247 00:26:56.390 ⇒ 00:27:01.280 Stephen: anyway, but I can at least get us a little bit close, so give me one second refund.
248 00:27:01.610 ⇒ 00:27:11.089 Stephen: Let me see how far off we are. Okay. Total is 9, 9, 7, 6.
249 00:27:12.040 ⇒ 00:27:23.179 Stephen: And that’s rough. I mean, it’s less so. That’s good because we are looking at less revenue in excel versus here, in in what’s in in the Amazon dashboard.
250 00:27:23.853 ⇒ 00:27:28.576 Stephen: Is that off by the same amount kind of hard to say.
251 00:27:29.440 ⇒ 00:27:42.349 Stephen: let me let me ask you this. Could you send me either the link to this dashboard or a screenshot of all the march data. And when you send over the the the what’s it called the cogs information.
252 00:27:42.680 ⇒ 00:27:53.550 Stephen: I can basically use that to bubble up and figure out what’s either missing or or what’s not working well within either code or or on Amazon side.
253 00:27:53.710 ⇒ 00:27:59.870 Stephen: because even with the profitability, because that profitable, that total profit is still from March.
254 00:28:00.470 ⇒ 00:28:03.459 Stephen: We’re looking at half of that, and that’s.
255 00:28:04.660 ⇒ 00:28:05.130 Luke Daque: Yeah, I think.
256 00:28:05.130 ⇒ 00:28:06.030 Stephen: That’s not close.
257 00:28:06.030 ⇒ 00:28:09.590 Luke Daque: Having like cost on marketing. So if you add marketing oh.
258 00:28:09.590 ⇒ 00:28:16.880 Luke Daque: and also like fees, perhaps because I think we’re only getting the Fba and shipping fees, and I think you
259 00:28:17.440 ⇒ 00:28:24.109 Luke Daque: you mentioned there was like, I don’t like the Fbm.
260 00:28:24.820 ⇒ 00:28:29.059 Luke Daque: I’m not. I don’t think we are using Fbm. And we’re also not
261 00:28:30.750 ⇒ 00:28:35.709 Luke Daque: like. Can you confirm what cost of doing? Business is in storage fees.
262 00:28:37.610 ⇒ 00:28:46.069 Luke Daque: cause I believe we’re only getting storage fees and Fba fees in our dashboard. I’m not sure if we’re getting cost of doing business.
263 00:28:47.350 ⇒ 00:28:51.460 Stephen: Gotcha. Okay? Can you go over to raw data current that tab on the far left.
264 00:28:51.810 ⇒ 00:28:52.550 Luke Daque: Sure.
265 00:28:53.530 ⇒ 00:28:57.170 Stephen: And then column C under type. Hit the filter.
266 00:28:58.500 ⇒ 00:28:59.030 Luke Daque: Hmm.
267 00:28:59.030 ⇒ 00:29:22.430 Stephen: Alright. So this is. This is everything that Amazon gives us. So I no editing from my side. An adjustment, an adjustment would just be like a price. Adjustments. We don’t have to worry about that. The fees are are indicated as such orders would be. Your Ops refund would be counter Ops. The service fee is another fee. The shipping services is another fee, and then transfer is another fee.
268 00:29:22.580 ⇒ 00:29:28.969 Stephen: That is basically how it’s done out. And then the descriptions are in column F
269 00:29:29.160 ⇒ 00:29:45.610 Stephen: for what it is so cost of advertising under service fee for some of them. Fba. Inbound placement, service, fee under service fee. Fba fee is like a carrier, shipment, fee, etc. So the explanations thankfully are are included. In column. F
270 00:29:47.610 ⇒ 00:29:54.219 Luke Daque: Gotcha. So basically, the these are the 4 ones that are considered fees right? Fba service and shipping.
271 00:29:54.410 ⇒ 00:29:56.840 Luke Daque: of course, is there any other.
272 00:29:56.840 ⇒ 00:29:57.370 Stephen: So.
273 00:29:57.370 ⇒ 00:29:57.960 Luke Daque: This! Would.
274 00:29:57.960 ⇒ 00:30:00.859 Stephen: I would include transfer, I would include, transfer.
275 00:30:01.797 ⇒ 00:30:05.340 Stephen: Yeah, it’s small. But like, that’s, that’s everything.
276 00:30:05.340 ⇒ 00:30:05.980 Luke Daque: That’s good.
277 00:30:06.180 ⇒ 00:30:13.109 Luke Daque: This, I believe. Let me just double check hangs on.
278 00:30:13.940 ⇒ 00:30:14.760 Luke Daque: He’s.
279 00:30:14.760 ⇒ 00:30:15.540 Stephen: Over here.
280 00:30:16.750 ⇒ 00:30:18.659 Luke Daque: Yeah, we’re only getting.
281 00:30:19.780 ⇒ 00:30:26.420 Luke Daque: We’re only using FDA and shipping charge back.
282 00:30:27.330 ⇒ 00:30:30.990 Luke Daque: selling fees and FDA fees. So we’re we’re not including the Us.
283 00:30:31.110 ⇒ 00:30:36.049 Luke Daque: Service fee, shipping service and and other stuff.
284 00:30:36.440 ⇒ 00:30:38.949 Luke Daque: So yeah, I can add them in thanks for that.
285 00:30:40.580 ⇒ 00:30:45.249 Stephen: No, thank you. Okay. I just retailed the raw data.
286 00:30:45.820 ⇒ 00:30:46.600 Luke Daque: You today.
287 00:30:46.990 ⇒ 00:30:49.040 Stephen: Let’s see, what are we missing now?
288 00:30:50.080 ⇒ 00:30:51.300 Stephen: I do.
289 00:30:53.040 ⇒ 00:30:54.010 Stephen: I’ll be
290 00:30:59.600 ⇒ 00:31:00.670 Stephen: based on.
291 00:31:05.260 ⇒ 00:31:07.700 Stephen: Alright. Let’s do profitability.
292 00:31:09.170 ⇒ 00:31:12.780 Stephen: The number that you had on the dashboard was 1, 7, 6, correct.
293 00:31:13.530 ⇒ 00:31:15.140 Luke Daque: It was 2, 4, 7.
294 00:31:15.520 ⇒ 00:31:18.380 Stephen: Sorry. Sorry. Sorry. Sorry for for
295 00:31:18.380 ⇒ 00:31:19.749 Stephen: or sales for total sales. Yeah.
296 00:31:19.750 ⇒ 00:31:34.399 Stephen: 1, 76. Okay, perfect. I I see exactly what the issue was, okay. Yeah, that’s what I’m getting. The Fbm fees we’re gonna have or excuse me, the fees. We’re still gonna have to redo a little bit along with the cost, the cogs, just because of the the asp.
297 00:31:37.860 ⇒ 00:31:44.340 Stephen: This is why is this alright?
298 00:31:44.340 ⇒ 00:31:47.870 Luke Daque: It’s like, it’s it’s different here, like the fees.
299 00:31:48.640 ⇒ 00:31:52.319 Luke Daque: names of the fees that you had here like shipping fee service fee.
300 00:31:52.920 ⇒ 00:31:56.479 Luke Daque: Maybe this one would be shipping anything, probably
301 00:31:57.110 ⇒ 00:32:02.840 Luke Daque: name shipping, as the fee type would be shipping fee in the.
302 00:32:02.840 ⇒ 00:32:04.149 Stephen: Yeah, but a lot of them is bubble.
303 00:32:04.150 ⇒ 00:32:08.549 Luke Daque: This digital service fee probably would be the service fee.
304 00:32:12.000 ⇒ 00:32:13.060 Luke Daque: What else.
305 00:32:13.060 ⇒ 00:32:14.810 Stephen: And if it if
306 00:32:14.810 ⇒ 00:32:19.579 Stephen: but if it’s if it says Fee, I think it’s safe for us to just include it all in.
307 00:32:20.180 ⇒ 00:32:29.330 Stephen: I would ask if it’s possible for us to have a way to distinguish what those fees are, either in the dashboard so that we can kind of bubble out.
308 00:32:29.730 ⇒ 00:32:34.079 Stephen: We need to, because at least from a like a digital service fee.
309 00:32:34.540 ⇒ 00:32:42.639 Stephen: I think that’s like, if you’re selling like a like a song or a movie on on Amazon so thankfully. That’s not something that we’d have to deal with, but
310 00:32:43.200 ⇒ 00:32:56.119 Stephen: it would still be helpful in case Amazon decided to charge us like a cent a week, for instance, they wouldn’t do that. But like just putting that out there, it’d be helpful so that we could. We could see what what charges were coming in that should or should not be there.
311 00:32:57.300 ⇒ 00:32:58.620 Luke Daque: Okay, sounds good.
312 00:33:00.590 ⇒ 00:33:09.629 Luke Daque: Yeah. Anything else. I think that’s about it. Right? Like we, we just need to
313 00:33:10.550 ⇒ 00:33:19.399 Luke Daque: get the fees, the marketing, and the shipment. I’ll give you the shipment breakdown. I mean the yeah breakdown.
314 00:33:22.100 ⇒ 00:33:31.149 Stephen: Got it. Okay, thank you. Thank you so much. I’m gonna dig back into this as well, because I just redownloaded the data. And I’m still getting the 1 60 number. So I’m gonna see if there’s something
315 00:33:31.350 ⇒ 00:33:47.020 Stephen: off in the sheet. I don’t think so. But just in case I’m gonna redo it. I’ll get back to you as well. I think I have your. I have everyone’s email on here, so we can obviously stay in contact but any any other questions, or anything else that we didn’t cover. Kim Luke, or or Amber.
316 00:33:48.121 ⇒ 00:33:51.438 kim todaro: No, thank you so much. I feel like we made a lot of progress today.
317 00:33:52.400 ⇒ 00:33:54.780 Luke Daque: Cool, sweet, nice.
318 00:33:54.780 ⇒ 00:33:59.340 Amber Lin: Do you want? Join our slack channel, or do you just wanna
319 00:33:59.450 ⇒ 00:34:04.049 Amber Lin: would it be easier if we communicate on slack? Or do you want to do it through email.
320 00:34:05.292 ⇒ 00:34:16.387 kim todaro: Let’s do it through email for now, just because Steven doesn’t, or unless we want to create like an Amazon specific one, just cause. I don’t wanna bother Steven with all the other stuff, because he doesn’t
321 00:34:16.780 ⇒ 00:34:20.710 kim todaro: need to be involved in shopify stuff, and I want to respect him.
322 00:34:21.210 ⇒ 00:34:22.170 Amber Lin: Sounds good.
323 00:34:22.750 ⇒ 00:34:23.350 Luke Daque: Cool.
324 00:34:25.070 ⇒ 00:34:28.859 Stephen: Thank you so much. All we’ll be in touch. We’ll we’ll get to the bottom of this.
325 00:34:28.860 ⇒ 00:34:29.590 kim todaro: Yes, we will.
326 00:34:29.590 ⇒ 00:34:30.229 Luke Daque: Cool thanks.
327 00:34:30.239 ⇒ 00:34:30.589 kim todaro: Okay.
328 00:34:30.590 ⇒ 00:34:31.290 Luke Daque: Thanks, Stephen.
329 00:34:31.510 ⇒ 00:34:33.469 kim todaro: Awesome. Thanks. Everyone.
330 00:34:34.219 ⇒ 00:34:38.400 Luke Daque: Oh, by the way, Kim, do you wanna stay for the shopify, or you wanna discuss sure
331 00:34:38.409 ⇒ 00:34:39.179 Luke Daque: for shopping for.
332 00:34:39.449 ⇒ 00:34:40.199 kim todaro: Sure.
333 00:34:41.120 ⇒ 00:34:48.560 Luke Daque: Yeah, I did copy, make a copy of your profitability report and compared it to
334 00:34:48.690 ⇒ 00:35:03.839 Luke Daque: so basically that the top portion is the one that you had currently. And then this table is like in real. And this is what I saw. So we are pretty close in terms of sales like just a 1% difference.
335 00:35:04.510 ⇒ 00:35:11.609 Luke Daque: And Google costs were pretty much the same as well in Facebook. Book or Meta cost
336 00:35:11.880 ⇒ 00:35:17.200 Luke Daque: the same what we don’t have from a marketing perspective is
337 00:35:17.460 ⇒ 00:35:20.469 Luke Daque: criteria, or I don’t know how you pronounce this criteria.
338 00:35:20.470 ⇒ 00:35:21.220 kim todaro: Video.
339 00:35:22.624 ⇒ 00:35:28.840 Luke Daque: Cj fees we have. But like, we’re higher. For some reason, I’m not sure why. But we are getting.
340 00:35:28.840 ⇒ 00:35:29.710 Luke Daque: That’s okay.
341 00:35:29.710 ⇒ 00:35:35.340 Luke Daque: Tj post pilot and impact is, I think, where we are missing.
342 00:35:35.670 ⇒ 00:35:36.154 Luke Daque: Okay?
343 00:35:37.280 ⇒ 00:35:40.650 Luke Daque: So if you can, I don’t know like
344 00:35:40.790 ⇒ 00:35:43.350 Luke Daque: where to get this data from at the moment.
345 00:35:44.350 ⇒ 00:35:46.429 Luke Daque: Yeah, especially postparture.
346 00:35:46.930 ⇒ 00:35:55.790 kim todaro: I’m gonna I have. I think Utam has access to everything except maybe Criteo twice.
347 00:35:56.070 ⇒ 00:36:00.010 kim todaro: If he doesn’t, I can get you access. Not a problem.
348 00:36:00.200 ⇒ 00:36:02.369 Luke Daque: Okay, no problem. I’ll I’ll check with.
349 00:36:02.520 ⇒ 00:36:04.039 Luke Daque: We’ll then for this one. Yeah.
350 00:36:04.040 ⇒ 00:36:05.320 kim todaro: Awesome and
351 00:36:05.880 ⇒ 00:36:06.480 Luke Daque: Yes.
352 00:36:06.620 ⇒ 00:36:08.919 kim todaro: Attentive. Looks looks pretty close, too.
353 00:36:09.830 ⇒ 00:36:12.370 Luke Daque: Yeah, yeah.
354 00:36:13.060 ⇒ 00:36:23.269 Luke Daque: The only thing I I have here is like Amazon ads. But like like Stephen mentioned, it’s supposed to be attributed to Amazon instead of shopify. So I’ll have to remove this here.
355 00:36:23.570 ⇒ 00:36:24.330 Luke Daque: Yep.
356 00:36:24.470 ⇒ 00:36:34.119 Luke Daque: yeah. And if we remove that, then marketing should be pretty close like if we remove, like the 5,000 from Amazon. Here it should be almost the same, except it’s missing
357 00:36:34.690 ⇒ 00:36:35.830 Luke Daque: at least 3.
358 00:36:36.150 ⇒ 00:36:41.479 kim todaro: And those fees are not super super high. Well, I guess they do add up, but yeah.
359 00:36:42.120 ⇒ 00:36:42.850 Luke Daque: Yeah.
360 00:36:42.850 ⇒ 00:36:43.839 kim todaro: Google, you know.
361 00:36:45.080 ⇒ 00:36:45.840 Luke Daque: Right.
362 00:36:46.100 ⇒ 00:36:47.360 kim todaro: Okay, so that’s.
363 00:36:47.360 ⇒ 00:36:48.070 Luke Daque: So
364 00:36:48.240 ⇒ 00:37:02.350 Luke Daque: I guess cogs is where it’s a lot different you. You did take note. You did have a note here that’s from shopify. But, like I mentioned in with Stephen, we’re using unleashed for this one, unless it’s it should be different from for shopify.
365 00:37:02.820 ⇒ 00:37:04.820 kim todaro: Okay. So this is great, because I think
366 00:37:05.416 ⇒ 00:37:08.619 kim todaro: the next step for here is to bring Chuck on a call.
367 00:37:08.910 ⇒ 00:37:09.520 Luke Daque: Okay.
368 00:37:09.950 ⇒ 00:37:13.420 kim todaro: He is responsible for unleashed and for shipping.
369 00:37:13.920 ⇒ 00:37:17.330 Luke Daque: Gotcha. Okay, that’d be great.
370 00:37:17.610 ⇒ 00:37:23.519 kim todaro: Yeah. Why don’t we get chuck on a call? Do you guys have a preference between Wednesday, Thursday, or Friday?
371 00:37:24.470 ⇒ 00:37:25.949 Luke Daque: I’m fine either way.
372 00:37:26.280 ⇒ 00:37:29.619 Amber Lin: You know, I mean, plus the sooner the better. So we get this.
373 00:37:29.620 ⇒ 00:37:31.730 Luke Daque: Like tomorrow, if we can do it tomorrow. That’d be great.
374 00:37:31.990 ⇒ 00:37:32.420 kim todaro: Yes.
375 00:37:32.940 ⇒ 00:37:42.380 kim todaro: yeah. And I updated Ben. I said, we’re in a really good spot with, we made a lot of progress with, we’re working on on shopify now. So let me see if Chuck can join tomorrow, and then
376 00:37:42.500 ⇒ 00:37:56.224 kim todaro: we can sort out cogs and shipping costs, and I think that would be a big help. Like, I said. Shipping costs are a little confusing because we have ship station, but we also have Unis, which I think you you kind of have access to. So
377 00:37:57.260 ⇒ 00:37:59.950 kim todaro: I’ll I’ll try to get Chuck on tomorrow, if not Thursday.
378 00:38:00.560 ⇒ 00:38:02.330 Luke Daque: Cool sounds, good.
379 00:38:02.690 ⇒ 00:38:05.600 kim todaro: Alright awesome. Well, thanks, guys, today was a good call.
380 00:38:06.130 ⇒ 00:38:14.279 Amber Lin: Yeah. Do you want me to update Ben? Or does he already know? What happened today? I can send him the meeting notes today as well.
381 00:38:14.650 ⇒ 00:38:17.665 kim todaro: Feel free. Yeah. Sure.
382 00:38:18.975 ⇒ 00:38:23.700 Amber Lin: Yeah, we can keep him happy. Thank you so much, Ken, for joining today.
383 00:38:23.880 ⇒ 00:38:25.669 kim todaro: Yes, I’ll see you guys tomorrow.
384 00:38:26.210 ⇒ 00:38:28.220 kim todaro: Thanks you. Bye-bye.
385 00:38:28.480 ⇒ 00:38:29.050 kim todaro: I.
386 00:38:33.250 ⇒ 00:38:35.770 Amber Lin: Luke. Did she say when we’re meeting tomorrow.
387 00:38:36.980 ⇒ 00:38:38.380 Luke Daque: No, she didn’t. She just said to me.
388 00:38:38.380 ⇒ 00:38:40.039 Amber Lin: Oh, oh, okay. Okay. Okay.
389 00:38:40.040 ⇒ 00:38:40.450 Luke Daque: Ping it.
390 00:38:40.450 ⇒ 00:38:46.179 Amber Lin: Okay, good, thank you. This was so much progress you did so much, for you did so much work.
391 00:38:46.920 ⇒ 00:38:52.189 Luke Daque: Yeah, it’s still still far, though, like but yeah, it’s it’s it’s good progress we got
392 00:38:52.500 ⇒ 00:38:57.779 Amber Lin: Yeah, and we’re gonna get all 3 of them involved. I mean, most of our
393 00:38:57.940 ⇒ 00:39:01.079 Amber Lin: errors was because they were never really involved.
394 00:39:01.280 ⇒ 00:39:01.860 Amber Lin: So.
395 00:39:01.860 ⇒ 00:39:09.429 Luke Daque: Yeah. And it’s been like months since we last talked to them. So we didn’t really know, like, if they were still using the dashboard, or like.
396 00:39:09.430 ⇒ 00:39:11.400 Amber Lin: Yeah, apparently they are.
397 00:39:11.400 ⇒ 00:39:22.250 Luke Daque: So. Yeah, it looks like Ben was always using it, and probably he was like pissed that the numbers are off, and then he never he! Just. It’s just like stacked for months, or something like.
398 00:39:22.670 ⇒ 00:39:23.260 Amber Lin: I got you.
399 00:39:23.260 ⇒ 00:39:25.650 Luke Daque: I’m pissed. So yeah.
400 00:39:26.140 ⇒ 00:39:30.450 Luke Daque: so that yeah, it’s a good thing that we’re we’re doing the these meetings with Ken and.
401 00:39:30.450 ⇒ 00:39:31.660 Amber Lin: Yeah. Awesome.
402 00:39:31.660 ⇒ 00:39:33.650 Luke Daque: Figuring all of these out. So yeah, cool.
403 00:39:34.070 ⇒ 00:39:38.260 Amber Lin: Okay, well, thank you for the call today and on stock list there
404 00:39:38.370 ⇒ 00:39:42.239 Amber Lin: they had a message in their channel, and they’re getting rid of us.
405 00:39:44.320 ⇒ 00:39:53.149 Amber Lin: They’re getting rid of us in 2 weeks, so just do whatever we have some tasks these 2 weeks, but probably after that it’ll be done.
406 00:39:53.530 ⇒ 00:40:00.080 Luke Daque: Okay, no, no problem, no worries, I think. I think. Alejandro, was it? Was like, or what’s his name?
407 00:40:00.648 ⇒ 00:40:02.640 Luke Daque: She’s gonna create a ticket.
408 00:40:02.950 ⇒ 00:40:04.320 Amber Lin: Yeah, yeah, they have.
409 00:40:04.320 ⇒ 00:40:07.480 Luke Daque: Documentation here. I’ll take a look at that.
410 00:40:08.110 ⇒ 00:40:09.120 Amber Lin: Okay.
411 00:40:10.000 ⇒ 00:40:10.990 Amber Lin: Alright. Cool.
412 00:40:10.990 ⇒ 00:40:12.440 Luke Daque: Sounds, good thanks, amber.
413 00:40:12.440 ⇒ 00:40:13.960 Amber Lin: I’ll talk to you tomorrow.
414 00:40:14.090 ⇒ 00:40:15.680 Luke Daque: You, too, have a nice rest of your day.
415 00:40:16.180 ⇒ 00:40:17.440 Luke Daque: Bye, bye.