Meeting Title: PP2G Marketing x Brainforge Date: 2025-04-03 Meeting participants: Kim Todaro, Luke Daque, Amber Lin


WEBVTT

1 00:00:17.050 00:00:17.880 Amber Lin: Hi Luke.

2 00:00:17.880 00:00:18.510 Luke Daque: Never mind.

3 00:00:20.210 00:00:21.540 Luke Daque: Hi, how’s it going

4 00:00:22.960 00:00:24.260 Amber Lin: For this meeting

5 00:00:26.042 00:00:27.130 Luke Daque: What is that?

6 00:00:28.161 00:00:30.340 Amber Lin: Do you feel prepared for this meeting

7 00:00:31.710 00:00:33.860 Luke Daque: I don’t know. Maybe like

8 00:00:34.020 00:00:40.300 Luke Daque: 60% or something. Not that much. But we should be fine. I guess we, I guess.

9 00:00:41.670 00:00:45.910 Luke Daque: yeah, we can ask questions from Kim as to like

10 00:00:47.320 00:00:54.960 Luke Daque: what actual requirement other requirements she she needs from the dashboard, and I believe she has, like a couple of questions for for us

11 00:00:56.400 00:01:05.259 Amber Lin: I see. So I know Uta also texting that channel will get the requirements from them, because what Ben has is a little bit unclear

12 00:01:05.720 00:01:06.590 Luke Daque: Yeah.

13 00:01:07.050 00:01:13.520 Amber Lin: But other than that, I guess also getting a few more tasks for us to do.

14 00:01:13.780 00:01:19.570 Amber Lin: because we right now don’t really have much except for this emerging. And we have the tech depths. And we have this

15 00:01:20.380 00:01:22.300 Luke Daque: Yeah, exactly. Yeah.

16 00:01:26.150 00:01:28.269 Amber Lin: Okay. We’ll wait for her.

17 00:01:36.730 00:01:43.010 Luke Daque: We can also, like, show her the updates that we had last the other day. I believe

18 00:01:44.230 00:01:48.360 Luke Daque: the selling platform fulfillment channel in the product class

19 00:01:48.500 00:01:51.650 Luke Daque: as like dimensions to the kpis

20 00:01:52.390 00:01:53.030 Amber Lin: Sounds good

21 00:01:53.030 00:01:54.229 Luke Daque: And yeah.

22 00:01:54.230 00:02:08.270 Amber Lin: I’ll let you talk with her a bit, and then I’ll ask what other tasks she has, because I I am a little bit lost on all of this dashboard stuff and Ben’s request, and I think I have an idea

23 00:02:08.430 00:02:12.749 Luke Daque: But probably you will have to lead this conversation correct?

24 00:02:12.750 00:02:13.610 Luke Daque: Yeah, sure.

25 00:02:17.310 00:02:18.380 Amber Lin: Hi kim

26 00:02:19.050 00:02:20.560 kim todaro: Hello! How are you?

27 00:02:20.970 00:02:25.690 Amber Lin: Hi! I’m good, nice to meet you.

28 00:02:26.230 00:02:28.779 kim todaro: Nice to meet you, too. Where are you out of

29 00:02:29.460 00:02:31.710 Amber Lin: I’m in la right now. What about you

30 00:02:31.710 00:02:34.772 kim todaro: Oh, nice! I am in New Jersey.

31 00:02:35.430 00:02:40.680 Amber Lin: New Jersey is in, where which state is that in

32 00:02:40.900 00:02:42.909 kim todaro: No, it’s it is a state. It’s near New York.

33 00:02:42.910 00:02:45.679 Amber Lin: Oh, oh, okay. Cool.

34 00:02:45.820 00:02:46.690 kim todaro: Yep.

35 00:02:48.090 00:02:48.720 Amber Lin: And

36 00:02:50.010 00:02:52.260 Amber Lin: Luke, have you met Luke before

37 00:02:52.460 00:02:53.639 kim todaro: Yes, I’ve met Luke

38 00:02:53.870 00:02:55.030 Amber Lin: Okay. It’s been a while

39 00:02:55.300 00:02:58.070 kim todaro: Nice to meet you, also, known as Ryan

40 00:02:58.490 00:03:01.020 Luke Daque: Yeah, yeah.

41 00:03:01.020 00:03:06.415 Amber Lin: Yeah, we had another Ryan join the team. And so it was like, Okay, you can take my name

42 00:03:07.590 00:03:10.006 kim todaro: Yeah, I heard

43 00:03:10.630 00:03:12.039 Luke Daque: It’s pretty common name.

44 00:03:12.160 00:03:17.290 Luke Daque: Looks like not like Utam, like. I don’t know any other person named Utam

45 00:03:18.400 00:03:19.170 kim todaro: Aim.

46 00:03:21.630 00:03:24.149 kim todaro: Okay. So I think

47 00:03:24.580 00:03:31.180 kim todaro: the point of this call is just to go over how we can get more up to date and accurate profitability, reporting

48 00:03:32.860 00:03:44.190 Amber Lin: Yeah, and any other to just flesh out the requirements. So we know what exactly you want. And if you have any other work suggestions. We’re very open to work on that as well

49 00:03:44.190 00:03:49.860 kim todaro: Yeah, I think the biggest issue is that like a lot of these reports weren’t created with me. And I like

50 00:03:51.000 00:03:59.930 kim todaro: maybe you created with Ben, and I actually use the report a lot. Up until 2 weeks ago, when Ben told me everything was incorrect because

51 00:03:59.930 00:04:00.440 Amber Lin: Hmm.

52 00:04:00.440 00:04:09.229 kim todaro: He it? March looked like a good month to me in terms of profit, profitability, and he told me that it was wrong. And so I’m just trying to figure out

53 00:04:09.780 00:04:12.480 kim todaro: what’s wrong and how we can fix it.

54 00:04:12.873 00:04:17.019 kim todaro: So that we can like kind of look at things in the morning and be like, okay.

55 00:04:17.480 00:04:28.290 kim todaro: these. This wasn’t profitable. As a whole. And then also, just from like a product standpoint, too, like for marketing purposes. And just so, you know, Amber, I I should give an intro of myself. I

56 00:04:28.670 00:04:31.790 kim todaro: kind of do everything at pool parts to go a lot of things, but

57 00:04:31.790 00:04:32.200 Amber Lin: So.

58 00:04:32.200 00:04:50.440 kim todaro: Mostly focused on marketing me and my counterpart, Mike, Mike, does Google. And I do everything else like affiliates. Email text Meta, a bunch like even like Post Pilot, which is a direct mail service. So yeah, I think that’s just like

59 00:04:50.580 00:04:55.999 kim todaro: the the big thing here. And I know Ben messaged. You guys this morning, too, about like.

60 00:04:56.810 00:05:01.131 kim todaro: I don’t even know. Okay, I see just kind of echoing what I just said

61 00:05:01.420 00:05:02.370 Amber Lin: Okay.

62 00:05:05.240 00:05:12.979 Amber Lin: yeah, I think for this meeting. I’ll let Luke right walk you through what we have. And then, based on that, have a better conversation

63 00:05:13.240 00:05:15.479 kim todaro: Okay? And I’m opening up the report right now.

64 00:05:15.740 00:05:16.300 Amber Lin: Good.

65 00:05:16.590 00:05:16.990 Luke Daque: Sure.

66 00:05:17.261 00:05:18.889 Amber Lin: Do you want to share screen

67 00:05:20.750 00:05:21.939 kim todaro: Me, or Luke

68 00:05:22.380 00:05:22.820 Amber Lin: Luke!

69 00:05:23.050 00:05:23.980 kim todaro: Okay. Cool.

70 00:05:23.980 00:05:24.610 Luke Daque: Sure.

71 00:05:27.270 00:05:32.469 Luke Daque: Okay, can you see my screen?

72 00:05:32.930 00:05:33.500 Amber Lin: Yep.

73 00:05:36.120 00:05:39.689 Luke Daque: Yeah, so I’m just wondering, though, like with.

74 00:05:39.800 00:05:45.239 Luke Daque: we already have, like a couple of reports in here. Would you know what? Which report

75 00:05:46.100 00:05:47.709 kim todaro: Yeah. Daily, Kpis.

76 00:05:47.980 00:05:48.840 Luke Daque: Dotson

77 00:05:49.180 00:05:53.740 kim todaro: Yeah, that’s that’s like my profitability report that I like. Look at

78 00:05:54.230 00:06:02.640 Luke Daque: Right, gotcha. And yeah, I actually just recently added a couple of dimensions here, because, like, that was

79 00:06:02.780 00:06:06.539 Luke Daque: what Ben was asking for last Monday or Tuesday.

80 00:06:07.125 00:06:11.679 Luke Daque: because it was only showing the aggregated data for all

81 00:06:11.880 00:06:14.760 Luke Daque: selling platforms and like product classes, and

82 00:06:14.880 00:06:20.440 Luke Daque: like, I believe, Ben wanted to see be able to drill down. Like how much

83 00:06:20.570 00:06:26.700 Luke Daque: sales we have for each platform or like which product class, like keep pumps for example

84 00:06:28.300 00:06:30.960 Luke Daque: have and stuff like that. So I just added these

85 00:06:31.070 00:06:34.810 Luke Daque: that way, we can like drill drill down to these.

86 00:06:36.100 00:06:37.750 Luke Daque: Yeah, yeah.

87 00:06:38.270 00:06:44.020 kim todaro: I know. I think that’s a good idea, because it helps us also like, understand what products to push

88 00:06:44.600 00:06:45.370 Luke Daque: Right.

89 00:06:46.200 00:06:50.645 Luke Daque: So in terms of like accuracy of the the numbers,

90 00:06:51.270 00:06:57.109 Luke Daque: it’ll be great if we we have like something to compare to, because I I wouldn’t know which one which part is like.

91 00:06:57.250 00:07:00.200 Luke Daque: inaccurate or like stuff like that. So

92 00:07:00.200 00:07:00.950 kim todaro: Same.

93 00:07:02.410 00:07:07.660 Luke Daque: That would be like if we look at. Do you have any idea, for, like March, for instance.

94 00:07:08.100 00:07:10.130 Luke Daque: what this look like

95 00:07:10.630 00:07:13.860 kim todaro: Yeah, before you updated it. It seemed like

96 00:07:15.040 00:07:21.520 kim todaro: it seemed to me like it was on the right track. But, like now, you could see, like total profit is like 1.5 million.

97 00:07:23.180 00:07:24.620 kim todaro: It’s like, really out there

98 00:07:25.110 00:07:26.590 Luke Daque: Hmm, yeah. Yeah.

99 00:07:26.850 00:07:30.341 kim todaro: Seems like there’s like a little bit of an issue with that month now.

100 00:07:32.160 00:07:33.749 kim todaro: but I think a lot of it

101 00:07:33.970 00:07:38.159 kim todaro: has to do with the the shipment fees. That aren’t correct.

102 00:07:39.480 00:07:40.270 Luke Daque: Hey?

103 00:07:41.480 00:07:45.499 Luke Daque: Like this total shipment cost might be too high.

104 00:07:46.000 00:07:46.829 Luke Daque: You think

105 00:07:47.920 00:07:53.929 kim todaro: I think it might be. I think the issue was before you updated it, which is obviously like very off right now.

106 00:07:56.120 00:07:58.950 kim todaro: It seemed like the shipment cost was too low.

107 00:07:59.890 00:08:27.130 kim todaro: cause I I thought we were in a good position, and then Ben was like, No, like we’re not profitable at all this month, and I was like, oh, really like it, said 80 at the time I looked at the report. It said we were like 80 K in prop like in profit and he was like, No, me. And I was just like, Okay, like, it’s hard because I don’t have anything to cross reference, either. But maybe if you guys give me the inputs of all this, I can talk to the different stakeholders within the company and get access to all those things so we can double check it

108 00:08:28.370 00:08:30.120 Luke Daque: Okay, that makes sense

109 00:08:30.120 00:08:30.720 kim todaro: Yeah.

110 00:08:31.090 00:08:37.169 Luke Daque: Yeah, maybe the calculation is incorrect here for total profit. It’s like very wild.

111 00:08:37.590 00:08:40.300 Luke Daque: It looks like the marketing cost is very high.

112 00:08:40.780 00:08:44.980 kim todaro: Yeah, I think I think that is actually the problem

113 00:08:45.590 00:08:52.765 Luke Daque: Yeah, because I believe total profit is just basically sales minus all the

114 00:08:54.860 00:08:55.700 kim todaro: The costs.

115 00:08:55.950 00:08:57.260 Luke Daque: All the costs. Yeah.

116 00:08:57.260 00:08:57.820 kim todaro: Yes.

117 00:08:59.570 00:09:01.560 Luke Daque: So, which amounts to this number

118 00:09:02.070 00:09:08.069 kim todaro: And I also like it would be helpful to see what you guys consider total fees, cause that’s a little ambiguous

119 00:09:08.830 00:09:11.649 Luke Daque: Hmm, okay, yeah. I believe this is

120 00:09:12.920 00:09:17.150 Luke Daque: only Amazon related like Amazon fees, Fba fees and stuff.

121 00:09:18.068 00:09:25.160 Luke Daque: It’s only Amazon. So like Fba and whatever fee Amazon

122 00:09:25.720 00:09:30.319 Luke Daque: pass when when we use when we use them to fulfill the order.

123 00:09:31.130 00:09:32.230 Luke Daque: Yeah, yeah.

124 00:09:32.831 00:09:37.780 Luke Daque: For sure. I’ll take a look at the marketing cost. This this, for sure, is pretty high.

125 00:09:39.400 00:09:42.489 Luke Daque: But for the others like discounts business.

126 00:09:42.800 00:09:45.929 Luke Daque: this seems low. But do you think this is correct?

127 00:09:46.830 00:09:49.259 kim todaro: Are you on Amazon, or are you on all channels

128 00:09:50.930 00:09:52.759 Luke Daque: This is all channels. Yeah.

129 00:09:53.310 00:09:55.520 kim todaro: Total discounts is definitely not right.

130 00:09:56.910 00:09:57.720 Luke Daque: Gotcha

131 00:09:58.540 00:10:02.369 Luke Daque: Should be like higher. Do you think it’s it’s a lot higher than this

132 00:10:02.660 00:10:05.490 kim todaro: Yeah, on shopify alone. It’s like 10,000. Maybe

133 00:10:07.340 00:10:09.930 kim todaro: I’m just cross-referencing it with with that

134 00:10:13.580 00:10:15.580 Luke Daque: So it should be around 10,000.

135 00:10:17.036 00:10:17.970 Luke Daque: No! Actually

136 00:10:18.100 00:10:24.160 kim todaro: In March. It’s around 30. It’s $35,721, 89 cents

137 00:10:26.880 00:10:28.369 Luke Daque: And that’s shopify alone

138 00:10:30.480 00:10:31.280 Luke Daque: Gotcha

139 00:10:32.540 00:10:35.310 kim todaro: Amazon and Walmart. There shouldn’t be too many discounts

140 00:10:35.820 00:10:36.540 Luke Daque: Okay

141 00:10:38.520 00:10:45.580 Luke Daque: and marketing. I’ll have to look into that but do you have any idea like what where that could be for March

142 00:10:46.170 00:10:50.113 kim todaro: For March. I can definitely we can definitely get there.

143 00:10:51.400 00:10:58.639 kim todaro: do you know what costs are included in that calculation? Like what sources like, I know.

144 00:10:58.880 00:11:04.090 kim todaro: I’m just looking at Meta. I know Meta, Google. Obviously, I’m trying to think where else it pulls

145 00:11:05.220 00:11:07.980 Luke Daque: Yeah, let me let me check real quick

146 00:11:32.900 00:11:39.280 Luke Daque: marketing cost is combined marketing performance.

147 00:12:10.000 00:12:14.790 Luke Daque: So this looks like it’s well, it’s from.

148 00:12:15.440 00:12:19.379 Luke Daque: It’s it’s combined marketing performance. Basically

149 00:12:20.010 00:12:20.850 kim todaro: Hmm.

150 00:12:33.910 00:12:38.669 kim todaro: yeah, it’s way off, like I’m just pulling numbers like, I don’t think it should be more than like

151 00:12:39.240 00:12:44.000 kim todaro: a hundred grand, but I’m just double checking some of the the bigger platforms, at least

152 00:12:44.880 00:12:46.259 kim todaro: for the month of March.

153 00:12:47.960 00:12:48.780 kim todaro: Okay.

154 00:12:49.190 00:12:50.969 Luke Daque: Okay, yeah. I’ll take a look at that.

155 00:12:51.930 00:13:00.049 kim todaro: But essentially another thing that Ben shared with me. When he we hopped on a call yesterday to to kind of talk about this is

156 00:13:00.670 00:13:03.410 kim todaro: he likes the way that

157 00:13:06.460 00:13:07.530 kim todaro: helps us.

158 00:13:09.655 00:13:11.579 kim todaro: He likes the way that

159 00:13:11.890 00:13:15.359 kim todaro: this report, which I’ll share in a second is structured.

160 00:13:15.980 00:13:18.379 kim todaro: I think the Amazon team does it for him.

161 00:13:20.560 00:13:23.273 kim todaro: and I think we could do it in real. I just

162 00:13:25.490 00:13:26.450 kim todaro: I think

163 00:13:26.700 00:13:36.249 kim todaro: if you guys have like any documentation about this report about where everything is getting pulled from. I can find the actual sources and make sure that I can cross reference

164 00:13:36.550 00:13:41.150 kim todaro: everything up that would be super helpful and

165 00:13:46.510 00:13:48.749 Luke Daque: Sure I can. I can create, like a

166 00:13:49.450 00:13:56.389 Luke Daque: documentation on that one like where where sources are coming from, especially for all the measures we have here at discounts called

167 00:13:56.390 00:13:56.750 kim todaro: Yeah.

168 00:13:56.750 00:14:01.879 Luke Daque: Calls and stuff like that. And then, yeah, we can cross reference like you mentioned

169 00:14:02.790 00:14:10.100 kim todaro: And like, I said, I think that the biggest issue was like the biggest discrepancy when we didn’t have all these errors that we have today

170 00:14:10.280 00:14:10.780 Luke Daque: Hmm.

171 00:14:10.780 00:14:11.590 kim todaro: Was

172 00:14:13.120 00:14:32.749 kim todaro: was actually the shipping. And so I can work with Chuck. I can talk to Chuck, and I know I know that the shipping costs weren’t gonna be perfect for some reason, but we were trying to estimate something, and so I think those were still off. So I can bring Chuck into these calls, too, so we can like make sure we get as close to the real number as we can.

173 00:14:33.270 00:14:34.140 kim todaro: Gotcha

174 00:14:34.140 00:14:34.790 Luke Daque: Okay.

175 00:14:35.291 00:14:41.708 kim todaro: This is basically the sheet pen was referring to, and he was like, he may wanted me to show you guys it.

176 00:14:42.650 00:14:44.070 Luke Daque: Let me stop sharing

177 00:14:45.050 00:14:45.970 kim todaro: Okay.

178 00:14:50.670 00:14:51.590 kim todaro: Cute.

179 00:14:54.040 00:14:55.070 kim todaro: Can you see it?

180 00:14:57.330 00:14:57.880 Luke Daque: Yep.

181 00:14:58.600 00:14:59.110 kim todaro: Okay. Cool.

182 00:14:59.110 00:15:03.940 Luke Daque: Sales a Amazon fees, I guess. Amz fees.

183 00:15:04.210 00:15:05.760 Luke Daque: Yeah, percentage

184 00:15:09.530 00:15:11.069 Luke Daque: cost of production

185 00:15:12.710 00:15:18.480 kim todaro: Cost. Fbm. I don’t know where where we would be able to get those, though, like the cost of production cost

186 00:15:18.930 00:15:20.050 Luke Daque: Fbm.

187 00:15:20.620 00:15:23.129 kim todaro: I think cost of production is cogs.

188 00:15:24.165 00:15:24.849 Luke Daque: Okay.

189 00:15:25.100 00:15:26.160 kim todaro: Yep, and

190 00:15:27.190 00:15:33.179 kim todaro: If so, the I think this is Amazon fees, and then this is Fbm fees.

191 00:15:33.390 00:15:34.260 Luke Daque: Hmm.

192 00:15:34.260 00:15:38.320 kim todaro: I guess they’re 2 different fees. I’m not 100% sure on that.

193 00:15:39.090 00:15:46.823 kim todaro: But I can. The guy who manages this. I can have a call with him, and try to better understand that as well

194 00:15:47.510 00:15:48.510 Luke Daque: Yeah, okay.

195 00:15:51.187 00:15:53.762 kim todaro: Just for Amazon as a channel. But

196 00:15:56.980 00:16:03.439 Luke Daque: This is the month of February, right? We can like cross check what we have in real at the moment

197 00:16:03.840 00:16:06.530 kim todaro: Yeah, this is March, and then this is February.

198 00:16:07.870 00:16:16.459 kim todaro: and then this. This is 2,024. So we don’t have to worry about that right now. But this is definitely the format Ben likes. But we can cross reference February, if you want

199 00:16:17.060 00:16:18.139 kim todaro: for Amazon.

200 00:16:19.370 00:16:20.480 kim todaro: It’s a good idea

201 00:16:21.500 00:16:31.029 Luke Daque: Yeah, it’s it’s still like, Co, total orders. Sales you have is 85,000 in real. It’s a hundred 1,000 for Amazon. So that’s still off.

202 00:16:31.780 00:16:34.499 Luke Daque: like really showing higher numbers.

203 00:16:34.710 00:16:41.119 Luke Daque: Amazon fees. It shows you have 68,000 there here, this.

204 00:16:43.840 00:16:49.139 Luke Daque: Yeah, it’s only $200, not not really

205 00:16:49.540 00:16:54.939 kim todaro: Oh, you know what it is. It’s the total minus Amazon fees, which

206 00:16:55.180 00:16:57.837 kim todaro: for some reason are not here

207 00:17:00.920 00:17:02.060 Luke Daque: You see

208 00:17:02.690 00:17:04.619 kim todaro: These are hard numbers. These aren’t even

209 00:17:05.680 00:17:06.349 Luke Daque: Yeah.

210 00:17:06.579 00:17:08.969 kim todaro: These aren’t even formulas

211 00:17:10.349 00:17:10.669 Luke Daque: Yeah.

212 00:17:10.670 00:17:14.220 kim todaro: It’s all pulling from different things. So this is essentially

213 00:17:14.930 00:17:19.359 kim todaro: total minus Amazon fees, which I would have to look up, probably in another

214 00:17:21.960 00:17:28.620 Luke Daque: Gotcha. So Amazon fees would be like 85,000, minus 68, whatever that was for February

215 00:17:30.080 00:17:31.120 kim todaro: Yeah.

216 00:17:33.230 00:17:34.010 kim todaro: Let’s just see

217 00:17:34.010 00:17:34.870 Luke Daque: No worries.

218 00:17:37.460 00:17:38.080 Luke Daque: Yeah.

219 00:17:38.080 00:17:40.190 kim todaro: So that’s probably what the number looks like.

220 00:17:40.820 00:17:45.580 Luke Daque: The cost of production does look correct, though 35,000

221 00:17:46.158 00:17:50.740 Luke Daque: to real and Fbm, which is what’s what’s Fbm. Again.

222 00:17:51.550 00:17:54.199 kim todaro: Fulfillment. I thought it was fulfillment by

223 00:17:54.910 00:17:57.854 kim todaro: I don’t know what the M. Stands for, but I can ask

224 00:17:58.220 00:18:00.440 Luke Daque: So there’s like an actual and related

225 00:18:00.880 00:18:02.050 kim todaro: I believe. So. Yeah.

226 00:18:02.250 00:18:02.980 Luke Daque: Okay.

227 00:18:03.210 00:18:05.979 kim todaro: Shipping cost of Fbm. Shipped orders.

228 00:18:07.110 00:18:11.800 kim todaro: so that might be. Some orders, I think, are maybe shipped by merchant, so maybe fulfillment by merchant

229 00:18:11.800 00:18:13.400 Luke Daque: I see.

230 00:18:13.990 00:18:14.530 Luke Daque: Okay.

231 00:18:14.530 00:18:23.350 kim todaro: So this might include Amazon’s shipping fee, or whatever that $17,000. And then this might be extra from from some orders that we fulfill

232 00:18:23.860 00:18:24.530 Luke Daque: Okay.

233 00:18:25.150 00:18:26.049 Luke Daque: Sounds good.

234 00:18:27.410 00:18:40.429 kim todaro: So I’m gonna I’m gonna for at least for the channel of Amazon. I’m gonna ask Steven, the guy that runs this hop on a call, and I’m gonna get more information and I’ll cross reference it with role, too, and we can meet back up. But I think

235 00:18:41.830 00:18:50.059 kim todaro: for the time being. If you could just fix the real dashboard how it is now and then. I can also try to identify what’s not correct. There

236 00:18:50.530 00:19:03.850 Luke Daque: Sure. Yeah, maybe I’ll for now I can revert it back to what it was previously, but just include the platform so we can filter Amazon with. So I I maybe maybe the heat pumps thing or like the product class.

237 00:19:03.950 00:19:06.520 Luke Daque: it’s like messing the numbers up or something. But yeah.

238 00:19:07.090 00:19:07.440 kim todaro: Okay.

239 00:19:07.440 00:19:08.529 Luke Daque: I’ll do that

240 00:19:10.410 00:19:14.740 kim todaro: That sounds good and then shopify

241 00:19:17.080 00:19:18.910 kim todaro: like, I said, if you guys can just like

242 00:19:19.400 00:19:23.090 kim todaro: the market like, give me what the definitions of some of like the big big

243 00:19:24.527 00:19:27.512 kim todaro: Parameters are like the marketing costs.

244 00:19:30.010 00:19:39.359 kim todaro: like, what are these definitions like total cogs? I think I is pretty self. Explanatory. Total discounts, I think, is too. But what makes up the total marketing cost the shipment cost

245 00:19:39.800 00:19:40.460 Luke Daque: Right.

246 00:19:41.080 00:19:44.319 kim todaro: Total fees like that type of thing that would be helpful, too.

247 00:19:44.670 00:19:45.340 Luke Daque: Sure.

248 00:19:45.450 00:19:49.339 Luke Daque: Yeah, I’ll I’ll I’ll make a documentation on that one, so

249 00:19:49.550 00:19:51.110 Luke Daque: we’ll be on the same page.

250 00:19:52.270 00:19:58.140 kim todaro: Cool. But I think that’s I think that’s it. For now, do you guys have any more questions

251 00:20:00.100 00:20:03.045 Luke Daque: Yeah, I think that’s that. That was very helpful.

252 00:20:03.600 00:20:04.300 kim todaro: Okay.

253 00:20:04.770 00:20:05.330 Luke Daque: Yeah.

254 00:20:06.700 00:20:07.885 kim todaro: Alright cool. I

255 00:20:08.680 00:20:13.650 kim todaro: I’ll schedule a call with the Amazon guy, so I can understand those fees better

256 00:20:14.080 00:20:14.640 Luke Daque: Cool.

257 00:20:15.590 00:20:20.089 kim todaro: But yeah, let me know when when the initial report is fixed, too.

258 00:20:20.640 00:20:21.300 Luke Daque: Sure.

259 00:20:21.690 00:20:24.059 kim todaro: Alright cool. Thank you. Guys for your time.

260 00:20:24.520 00:20:26.360 Luke Daque: Thank you. Do you think you as well

261 00:20:27.206 00:20:32.689 Amber Lin: Ben’s concerns, cause I I think he was pretty frustrated by this

262 00:20:32.690 00:20:36.699 kim todaro: He’s very frustrated. And sometimes

263 00:20:37.140 00:20:44.759 kim todaro: he just wants he wants things done and doesn’t know how like, and just wants you to figure out how to do them. So that’s why I’m trying to step in and kind of help

264 00:20:45.373 00:20:50.330 kim todaro: and I’m gonna try to help him as best I can understand.

265 00:20:50.790 00:20:56.395 kim todaro: Get the report working and understand what’s what needs to be fixed right now, because I don’t even know if he knows

266 00:20:56.830 00:20:57.730 kim todaro: So

267 00:20:58.350 00:21:04.819 kim todaro: I think he’s frustrated. But I I think if we could just get this like figured out in the next week, he’ll be very happy. This is like

268 00:21:05.670 00:21:07.620 kim todaro: the the most important. Report. Right? Now.

269 00:21:08.250 00:21:08.940 Amber Lin: -

270 00:21:09.861 00:21:19.080 Amber Lin: sounds good, and when he says, I know when he said, I need to see this in one click. Do you know what he’s referring to?

271 00:21:19.330 00:21:21.509 kim todaro: He just wants to make sure that report is

272 00:21:22.305 00:21:27.054 kim todaro: available. And it’s correct. That’s that’s just just his translation of that

273 00:21:27.450 00:21:28.940 Amber Lin: That’s good. Okay, that’s very helpful.

274 00:21:29.310 00:21:35.779 kim todaro: Yeah, even me. I told him I was like, you know, what can I cross reference? And he

275 00:21:35.990 00:21:37.810 kim todaro: kind of like figure it out so

276 00:21:38.370 00:21:38.900 Amber Lin: I mean

277 00:21:39.420 00:21:49.730 kim todaro: We’ll get there. But let’s just like, keep in in touch and I’ll try to find out more information about from you guys where these costs are defined, and then also from Amazon, too, like

278 00:21:50.690 00:21:53.329 kim todaro: to replicate that that report that was made

279 00:21:54.590 00:21:55.360 Luke Daque: Gotcha

280 00:21:55.650 00:21:56.570 Amber Lin: Sounds good

281 00:21:57.130 00:21:58.060 kim todaro: Alrighty!

282 00:21:58.460 00:21:59.880 Amber Lin: Okay. Thank you. Kim.

283 00:21:59.880 00:22:01.830 kim todaro: Okay. Thanks. Kim, thanks. Guys.

284 00:22:01.830 00:22:02.990 Luke Daque: I stress really.

285 00:22:03.320 00:22:04.660 kim todaro: Yes, you too. Thank you.