Meeting Title: Javy-Project-Internal-Review Date: 2024-11-04 Meeting participants: Luke Daque, Nicolas Sucari, Uttam Kumaran, Payas Parab, Robert Tseng


WEBVTT

1 00:05:28.340 00:05:29.190 Luke Daque: Hi Robert!

2 00:05:31.810 00:05:32.560 Robert Tseng: Hey! Luke!

3 00:05:33.130 00:05:35.019 Luke Daque: How’s it going? How was your weekend.

4 00:05:35.920 00:05:37.410 Robert Tseng: Good. How’s yours?

5 00:05:38.090 00:05:39.072 Luke Daque: Yeah, it’s great.

6 00:05:40.120 00:05:40.990 Luke Daque: cool.

7 00:05:41.810 00:05:43.929 Luke Daque: pretty chill, weekend.

8 00:05:45.300 00:05:46.090 Robert Tseng: Nice.

9 00:05:46.250 00:05:47.869 Robert Tseng: Where? Where do you live, Luke?

10 00:05:48.480 00:05:51.150 Luke Daque: I’m currently at the Philippines.

11 00:05:51.150 00:05:52.430 Robert Tseng: Yeah, I like.

12 00:05:52.460 00:05:54.490 Robert Tseng: are you like in Manila or.

13 00:05:54.490 00:05:56.003 Luke Daque: Oh, yeah, I’m in

14 00:05:56.990 00:05:58.919 Luke Daque: south, like Mindanao

15 00:05:59.250 00:06:03.760 Luke Daque: Cagande, or a city. It’s not a very known place, I guess.

16 00:06:03.900 00:06:04.540 Luke Daque: International.

17 00:06:04.540 00:06:05.180 Robert Tseng: Cool.

18 00:06:05.390 00:06:07.280 Luke Daque: I used to live in Cebu.

19 00:06:08.020 00:06:08.390 Robert Tseng: Okay.

20 00:06:08.410 00:06:09.330 Luke Daque: Yeah.

21 00:06:09.330 00:06:10.050 Robert Tseng: Wow!

22 00:06:11.720 00:06:13.409 Robert Tseng: That’s like on a different island.

23 00:06:13.680 00:06:16.610 Luke Daque: Yeah, there’s like thousands of islands here.

24 00:06:16.920 00:06:17.610 Robert Tseng: Yeah.

25 00:06:18.590 00:06:20.630 Luke Daque: Have you ever been to the Philippines?

26 00:06:21.010 00:06:23.909 Robert Tseng: I’ve only been to Manila.

27 00:06:24.720 00:06:25.680 Robert Tseng: Yeah.

28 00:06:25.680 00:06:27.229 Luke Daque: That’s the capital. So.

29 00:06:28.420 00:06:30.670 Robert Tseng: Yeah, but I would like to

30 00:06:31.830 00:06:36.780 Robert Tseng: see more of it, like I know that there’s so many islands.

31 00:06:37.600 00:06:38.210 Luke Daque: Yeah.

32 00:06:38.700 00:06:41.479 Luke Daque: nice beaches, especially on the

33 00:06:42.070 00:06:46.250 Luke Daque: yeah, like, Cebu city. There’s lots of nice beaches there.

34 00:06:46.560 00:06:48.609 Robert Tseng: Yeah, I’ve heard. Huh?

35 00:06:58.320 00:07:00.609 Luke Daque: Let me try to PIN Nicholas.

36 00:07:01.470 00:07:02.800 Robert Tseng: I think they’re all coming on.

37 00:07:04.350 00:07:04.920 Luke Daque: Oh!

38 00:07:05.150 00:07:06.600 Payas Parab: What’s up, guys? Sorry I’m late?

39 00:07:08.020 00:07:09.210 Robert Tseng: No worries.

40 00:07:13.890 00:07:14.750 Nicolas Sucari: Hi, guys.

41 00:07:14.960 00:07:15.890 Nicolas Sucari: how are you.

42 00:07:17.760 00:07:18.789 Robert Tseng: Hey, Nico.

43 00:07:42.730 00:07:44.790 Robert Tseng: I think we have everyone here.

44 00:07:45.520 00:07:46.180 Robert Tseng: Yeah, I mean.

45 00:07:46.180 00:07:47.140 Nicolas Sucari: Everyone is here.

46 00:07:48.340 00:07:50.589 Robert Tseng: Oh, yeah. Alright. Go ahead.

47 00:07:51.920 00:08:01.479 Nicolas Sucari: Cool. So yeah, guys, last week we sent that message with the full update everything would be doing aman didn’t answer that. I don’t know.

48 00:08:01.660 00:08:07.329 Nicolas Sucari: Robert. If you speak to him. You spoke with him last week or anything after that. But if not, I’m gonna

49 00:08:07.800 00:08:11.749 Nicolas Sucari: yeah. Just go through that again tomorrow at the meeting

50 00:08:12.116 00:08:20.869 Nicolas Sucari: today. It’s gonna be good for us if maybe you pay us and show us the refunds return stuff so that we can finally

51 00:08:20.900 00:08:23.799 Nicolas Sucari: match those numbers from what we have.

52 00:08:24.132 00:08:29.870 Nicolas Sucari: So that we can identify those differences. And yeah, I. And I don’t know if we have like

53 00:08:29.930 00:08:43.309 Nicolas Sucari: other stuff. I know, Luke, you were working on adding the product categories, the dashboards. I think I saw that request just a couple of minutes ago. So we should review that merge, and I don’t know if we have, like any other update, for now.

54 00:08:47.330 00:08:55.260 Luke Daque: Yeah, aside from the product categories, product types. Yeah, we’re just like trying to figure out the refunds one or returns.

55 00:09:01.010 00:09:04.636 Payas Parab: And then I think, Luke, one thing I did want to check with you was on the

56 00:09:05.070 00:09:27.719 Payas Parab: basically the kpis that we currently have kind of in Meta base. Right? I think Utam mentioned. You wanted to migrate everything over into like a kpis table, so that, like it’s a partition per day, and you kind of just have like a Kpi table that loads into real to make it more dynamic. That was one thing I wanted to check in with you on, and then we can hash out this refund stuff as well while while we’re here.

57 00:09:27.910 00:09:28.900 Luke Daque: Yeah, sure.

58 00:09:29.110 00:09:31.210 Payas Parab: Those are the main items from my end as well.

59 00:09:31.430 00:09:41.529 Luke Daque: Yeah, we actually already have the Kpi stable. I already added that to the tutorial as well. But we’ll have to verify like, if the numbers look correct on your end.

60 00:09:41.940 00:09:43.299 Luke Daque: Okay, for this one.

61 00:09:44.120 00:09:47.930 Payas Parab: Yep, I can use August to spot check. That’s what we’ve been using, so I’ll use August

62 00:09:48.188 00:09:50.959 Payas Parab: and then I see some of them in there, but I think there’s some

63 00:09:51.640 00:09:56.790 Payas Parab: like other kpis as well. Do. Which which dashboard is it? Daily? Kpis?

64 00:09:56.790 00:09:58.220 Luke Daque: Daily. Kpis yep.

65 00:09:58.220 00:10:00.619 Payas Parab: Got it. Okay? So we may just need.

66 00:10:00.970 00:10:03.160 Payas Parab: I think I see the sales data

67 00:10:03.530 00:10:04.570 Payas Parab: and

68 00:10:05.010 00:10:08.619 Payas Parab: orders data. We might just need some of the other attributes, as well.

69 00:10:08.620 00:10:11.860 Luke Daque: Yeah, just make sure to change the time

70 00:10:12.230 00:10:14.889 Luke Daque: stamp. I mean the the what time zone to P.

71 00:10:16.050 00:10:16.550 Luke Daque: Yeah.

72 00:10:16.550 00:10:17.030 Nicolas Sucari: Yeah.

73 00:10:17.800 00:10:18.330 Payas Parab: Got it.

74 00:10:18.330 00:10:23.209 Luke Daque: Should get you. The should be the correct numbers, unless there’s any other.

75 00:10:23.690 00:10:29.300 Payas Parab: Sounds good. I can. I can review that. That can be an action item for me. To review that. And then we can get everything kind of in there.

76 00:10:29.950 00:10:31.950 Payas Parab: As needed. So okay.

77 00:10:33.050 00:10:33.819 Payas Parab: great

78 00:10:35.670 00:10:36.910 Payas Parab: And then,

79 00:10:37.620 00:10:43.550 Payas Parab: yeah, the refund stuff. You want to hash that out. Now while we’re here. I don’t want to derail if there’s other stuff on Nico and Robert like.

80 00:10:43.650 00:10:49.229 Payas Parab: if it’s just like debugging stuff, me and Luke can take it if there’s anything else that’s like more big group stuff.

81 00:10:49.450 00:10:52.769 Payas Parab: Otherwise you can just get to the the debugging. This refunds thing.

82 00:10:54.400 00:11:10.480 Nicolas Sucari: Don’t think we have, like so many other things. I don’t know, Robert, if we have something your end. But for us, I think we just need to validate that the numbers were showing their unveil are saying that we have in and then it’s just asking Aman what

83 00:11:10.550 00:11:13.310 Nicolas Sucari: would like to see with gorgeous and

84 00:11:13.390 00:11:15.301 Nicolas Sucari: okay. And though we have like

85 00:11:15.965 00:11:26.000 Nicolas Sucari: gorgeous request, I think some questions he sent us. So we’re we. We have that in the dashboard that maybe we can go through and try to answer those ones. But then we can.

86 00:11:26.030 00:11:39.319 Nicolas Sucari: We can start looking into how to match, depend on gorgeous data with the orders, data that we can create like a more complete dashboard with everything. And that’s it, I think. We don’t have like like

87 00:11:39.450 00:11:46.360 Nicolas Sucari: official request or anything detailed. So we we need to just open that and see what we can share.

88 00:11:48.665 00:11:52.295 Robert Tseng: I don’t see recharge on our

89 00:11:53.310 00:12:00.169 Robert Tseng: yeah, I mean, I think I I didn’t hear anybody talk about recharge, but that’s something that they want as well. So

90 00:12:03.340 00:12:03.780 Nicolas Sucari: Right.

91 00:12:03.780 00:12:05.349 Robert Tseng: I mean, I don’t know did.

92 00:12:05.450 00:12:06.900 Robert Tseng: where, where the

93 00:12:07.760 00:12:16.349 Robert Tseng: where the conversation lives, but I’ve been seeing like threads on on recharge since last week, so I think that needs to probably be addressed with the bond tomorrow as well.

94 00:12:17.260 00:12:23.799 Nicolas Sucari: Okay, cool. Yeah, we can ask him on if we if he wants to reach our data ultimately, something we can bring that in. That’s fine.

95 00:12:25.760 00:12:31.439 Payas Parab: There. There was also one other thing. Sorry. I just was reviewing my notes on the the all orders dashboard!

96 00:12:31.770 00:12:47.179 Payas Parab: One thing we also wanted to make. And I I think this change is better handled upstream. Otherwise I would just update it myself and like, make a Pr, but the right. Now we have app, source, display, shopify, and Amazon, and then is Tiktok Shop is sort of like another attribute.

97 00:12:47.250 00:12:53.670 Payas Parab: and is Tiktok Shop is also based on like tags which we found in other cases to be unreliable. So I think we’re gonna do

98 00:12:53.910 00:12:57.979 Payas Parab: like adjust that logic to be if tick tock order. Id is null.

99 00:12:58.260 00:13:00.709 Payas Parab: then the app source equals Tiktok.

100 00:13:00.950 00:13:13.829 Payas Parab: and then to have like shopify and am like shopify. I think, the app source. We should have Tiktok Amazon, and shopify rather than having it be like you. Click, shopify, and then is Tiktok Shop equals? True?

101 00:13:14.129 00:13:19.160 Payas Parab: So I wanted to flag that as well. If we can get that, I I in that all orders dashboard. I still see that.

102 00:13:19.160 00:13:19.860 Luke Daque: Yeah.

103 00:13:19.860 00:13:23.849 Payas Parab: On. This is tick tock. So I think it would make sense to integrate that with

104 00:13:24.486 00:13:31.910 Payas Parab: with that app source. And and they know that, like, you know, that means shopify also. Right, like the order is managed in shopify. But

105 00:13:32.100 00:13:36.410 Payas Parab: like it’ll just be helpful for them to break it out. Tiktok Amazon.

106 00:13:36.410 00:13:38.580 Luke Daque: Breakdown shopify to

107 00:13:39.510 00:13:42.730 Luke Daque: the just tick, tock, and the non tiktok.

108 00:13:42.730 00:13:43.609 Payas Parab: Content. Correct. Yeah.

109 00:13:43.610 00:13:49.409 Luke Daque: Gotcha, and the logic is just. If tick tock order id is null, then it’s Tiktok.

110 00:13:49.410 00:13:50.970 Payas Parab: Yeah, exactly.

111 00:13:51.010 00:13:54.029 Luke Daque: Gotcha. Yeah, we we cannot add that to the.

112 00:13:54.030 00:13:59.819 Payas Parab: Yeah. And I wanna make sure we use that logic instead of the is Tiktok shop because the is shit. Tiktok Shop is a tag.

113 00:14:00.050 00:14:00.600 Luke Daque: Right.

114 00:14:00.600 00:14:03.339 Payas Parab: Having issues with the other tags. So I wanna make sure we use.

115 00:14:03.420 00:14:07.849 Payas Parab: I think if it’s like, if the order Id is there, then we know that it’s like, for sure.

116 00:14:08.590 00:14:09.760 Luke Daque: Right, makes sense.

117 00:14:09.760 00:14:14.329 Payas Parab: Probably pretty close to. I don’t imagine they’re off by a ton, but I think it’s safer that way.

118 00:14:14.570 00:14:19.329 Luke Daque: But this tick tock shop is actually a tag, right? Or something.

119 00:14:19.330 00:14:22.030 Payas Parab: It’s a tag, I believe. Yeah, I believe it’s a tag.

120 00:14:22.270 00:14:22.849 Payas Parab: So yeah.

121 00:14:22.850 00:14:26.500 Luke Daque: If the order has a tag that’s is tick tock shop, and that’s.

122 00:14:26.500 00:14:29.910 Payas Parab: Yeah, but I think we should use the is tiktok order id

123 00:14:30.392 00:14:32.510 Payas Parab: no, as the as the logic and.

124 00:14:32.510 00:14:33.680 Nicolas Sucari: We just

125 00:14:33.810 00:14:57.380 Nicolas Sucari: yeah, we just need to identify the there is a column with Tiktok Id. If that has something in it, and it’s not know. We can identify that as a Tiktok order, and if not, it’s just a shopify, or that should be the only difference. And we can just change the app source field, the Amazon shopify that are the ones we don’t have. Tiktok, id, and then Tiktok, okay.

126 00:14:57.640 00:14:58.940 Luke Daque: I gotcha cool.

127 00:15:00.220 00:15:02.980 Luke Daque: Yeah, I can do that. I’ll let you know once it’s done.

128 00:15:05.540 00:15:06.200 Luke Daque: Yep.

129 00:15:07.950 00:15:12.002 Robert Tseng: Okay, last thing on on my end. For the team is

130 00:15:12.500 00:15:17.969 Robert Tseng: because we kind of pushed the limit on ours. Lat, in October.

131 00:15:18.110 00:15:34.429 Robert Tseng: We’re just like running into whatever I’m still in talks with Joby. We just need to. They want a breakdown of hours in October, and then we need to send weekly hours moving forward. So just for everyone working on it. Just make sure you’re more on top of it. In terms of

132 00:15:34.580 00:15:40.709 Robert Tseng: sending. Yeah, I I need. I need to need to send need to send me out. It’s probably more of a Nico U, Tom, and

133 00:15:41.324 00:15:45.439 Robert Tseng: kind of thing. But yeah, I don’t know how you guys report hours on like.

134 00:15:45.440 00:15:46.540 Uttam Kumaran: Yeah, we have.

135 00:15:47.070 00:15:49.800 Uttam Kumaran: We have hours tracked. I don’t know.

136 00:15:49.810 00:15:53.379 Uttam Kumaran: Yeah, I mean, do you? Do you want a task like a task breakdown, or just

137 00:15:53.460 00:15:55.779 Uttam Kumaran: hours per week, like, what do you think they want?

138 00:15:55.780 00:16:01.750 Robert Tseng: Well, they just they just let me see what Jared just said.

139 00:16:02.990 00:16:05.990 Uttam Kumaran: And what was the like? What’s the vibe? Are they? Are they like.

140 00:16:06.440 00:16:09.360 Uttam Kumaran: where is the hours going? Basically? Or what’s their.

141 00:16:10.620 00:16:12.930 Robert Tseng: Yeah, I mean, I think they.

142 00:16:13.900 00:16:17.640 Robert Tseng: I think we had, like we went back and forth on like

143 00:16:18.850 00:16:30.619 Robert Tseng: cause. I know I know everyone kind of went over a little bit and so there they were, basically like, Why didn’t you just stop once you hit your cap. And I was like, that’s not really how we work like we’re really trying to

144 00:16:31.720 00:16:41.410 Robert Tseng: hit the hit. These deliverables. And I pointed out a couple of situations where because they applied pressure to us. Whether it was Jared’s

145 00:16:41.450 00:16:43.700 Robert Tseng: faster requests or kind of

146 00:16:43.740 00:17:05.459 Robert Tseng: giving, like custom, shovel, shopify, flow automations that Ryan had to go in and model like that definitely added to what we were expecting. So I think they just want weekly hour. Yeah, I think we start with weekly hours and just like what we did each week. Maybe that I’ll send that 1st and see if they are okay with that.

147 00:17:06.050 00:17:10.184 Uttam Kumaran: Okay, yeah, we have that on our end. So we’ll just

148 00:17:11.280 00:17:12.460 Uttam Kumaran: yeah. Go ahead. Nico.

149 00:17:13.220 00:17:24.390 Nicolas Sucari: Oh, no, yeah, we have clock, if we have the hour per the hours per day I can start track mine if you want to, Tom? I don’t know if that’s necessary or not. I mean, we’re just tracking clients.

150 00:17:25.900 00:17:35.979 Robert Tseng: Yeah, well, I think they want something weekly moving forward. So I’m thinking of kind of scheduling an email under the week kind of thing. We have to figure out how we’re gonna coordinate across everyone but

151 00:17:36.520 00:17:42.529 Robert Tseng: yeah. So maybe Nico, Utah, we can, we can slack on this. And then, yeah.

152 00:17:43.197 00:17:47.232 Uttam Kumaran: I’ll show you what we’re doing, and then it may just be easy to slot in there.

153 00:17:47.470 00:17:48.130 Robert Tseng: Okay.

154 00:17:48.670 00:17:49.390 Uttam Kumaran: Cool.

155 00:17:53.720 00:17:54.450 Uttam Kumaran: cool.

156 00:17:54.760 00:18:01.980 Nicolas Sucari: Excellent apart from that. Yeah, I don’t think we have anything else, I think by us, Ryan. Maybe we can

157 00:18:02.060 00:18:04.640 Nicolas Sucari: go through the refunds return stuff.

158 00:18:04.890 00:18:05.949 Nicolas Sucari: If you want.

159 00:18:06.870 00:18:08.390 Luke Daque: Yeah, sure.

160 00:18:08.450 00:18:10.139 Luke Daque: I can share my screen.

161 00:18:11.180 00:18:12.930 Luke Daque: This is more on.

162 00:18:13.950 00:18:14.640 Luke Daque: It’s it

163 00:18:15.100 00:18:17.310 Luke Daque: like, shopify showing

164 00:18:17.840 00:18:19.950 Luke Daque: refunds. Yeah, just.

165 00:18:19.950 00:18:29.460 Nicolas Sucari: Robert, your time. If you want to drop, I think that’s fine, we can handle it. Here we are. Gonna just look into the data and see how we can start identifying the differences.

166 00:18:30.100 00:18:37.450 Robert Tseng: Okay? Wait. I quick question on who has the agenda, Nick, are you? Do you own the agenda for tomorrow’s call?

167 00:18:39.510 00:18:47.360 Nicolas Sucari: Yeah, I think I think we, yeah, I think I can handle. And we we can talk with us. And just, yeah, have the agenda for everyone.

168 00:18:47.360 00:19:00.790 Robert Tseng: Okay. But I’ll just like you a couple of things that I think we needed. Yeah, the the recharge thing we talked about. And then also something something else that I’m on brought up. So I’ll just message you that. Okay, alright. Talk to you soon.

169 00:19:00.790 00:19:01.449 Nicolas Sucari: Thank you.

170 00:19:01.690 00:19:02.240 Luke Daque: Insane.

171 00:19:02.240 00:19:02.940 Nicolas Sucari: Thank you.

172 00:19:05.820 00:19:06.150 Luke Daque: Yeah.

173 00:19:06.850 00:19:11.050 Luke Daque: So yeah, going back to refunds. So we’re actually.

174 00:19:11.400 00:19:20.840 Luke Daque: I don’t see any refunds in like this report, for example, in shopify. But there’s returns. Is this, is this like what we are trying to figure out

175 00:19:21.280 00:19:24.140 Luke Daque: like the numbers? I think you’re on mute.

176 00:19:24.140 00:19:27.209 Payas Parab: I think that’s what’s considered refunds. I had another theory that.

177 00:19:27.210 00:19:28.080 Luke Daque: It was like.

178 00:19:28.680 00:19:31.669 Payas Parab: Refunds as well as canceled orders. Maybe.

179 00:19:32.330 00:19:38.090 Luke Daque: Yeah, yeah, I think they’re. They’re they’re different. Like returns are like already includes

180 00:19:38.690 00:19:44.609 Luke Daque: the refund amount. And maybe, like the shipping cost for the return, because refunds are just

181 00:19:45.120 00:19:47.710 Luke Daque: the exact item, price right being refunded.

182 00:19:48.395 00:19:49.080 Payas Parab: Yep.

183 00:19:49.350 00:19:51.179 Luke Daque: So, yeah, maybe. But

184 00:19:52.480 00:19:59.789 Luke Daque: yeah, I guess that’s why we’re like not matching, because we’re matching refunds and against returns, which is like.

185 00:19:59.790 00:20:00.699 Payas Parab: Yeah, and and it’s.

186 00:20:00.700 00:20:01.100 Luke Daque: The high.

187 00:20:01.100 00:20:03.339 Payas Parab: It’s always lower, right? It’s always yeah, like.

188 00:20:04.000 00:20:08.639 Payas Parab: like some of funds, or like absolute value. Some of refunds is less than some of.

189 00:20:08.640 00:20:09.310 Luke Daque: Right.

190 00:20:09.310 00:20:10.990 Payas Parab: Value of returns. Right almost.

191 00:20:10.990 00:20:13.649 Luke Daque: Right? Yeah, that should.

192 00:20:14.890 00:20:26.069 Payas Parab: Maybe, like, return related shipping costs. I’m wondering if maybe then, if I maybe I’ll pull up Snowflake here in that refunds your returns table. There’s like more columns that we may need.

193 00:20:27.480 00:20:29.605 Luke Daque: Yeah, we have. We only have

194 00:20:30.460 00:20:31.610 Luke Daque: these

195 00:20:33.560 00:20:35.730 Luke Daque: or shopify

196 00:20:40.260 00:20:44.309 Luke Daque: unless there’s a different one called order Refund, or something.

197 00:20:45.640 00:20:46.450 Payas Parab: Hmm.

198 00:20:48.477 00:20:51.399 Luke Daque: I don’t see anything else here.

199 00:20:51.400 00:20:52.949 Payas Parab: Is there like a restock

200 00:20:53.030 00:20:55.340 Payas Parab: folder? Maybe I don’t know. I’m just trying to.

201 00:20:56.710 00:21:00.120 Luke Daque: There’s transaction. Maybe there’s some

202 00:21:01.720 00:21:04.149 Luke Daque: something here refund

203 00:21:05.520 00:21:09.520 Luke Daque: amount. So I guess we can get the refund amount.

204 00:21:09.520 00:21:10.560 Payas Parab: We already have basically.

205 00:21:10.560 00:21:12.850 Luke Daque: Yeah, that’s what we already have that

206 00:21:18.730 00:21:20.812 Luke Daque: we can. We can check the

207 00:21:21.440 00:21:22.400 Luke Daque: I need

208 00:21:23.010 00:21:24.779 Luke Daque: push the Urd.

209 00:21:25.110 00:21:35.749 Nicolas Sucari: Why, why don’t we do it like the other way around? Let’s going to try and see, like, what are the numbers that they are seeing that we want to have, and then see what we have in the tables to try.

210 00:21:35.750 00:21:36.920 Luke Daque: To match those plans.

211 00:21:37.850 00:21:44.840 Luke Daque: Yeah, like for August, we can check. This is already August 2,024 re. Returns

212 00:21:45.240 00:21:49.090 Luke Daque: is 4,000 440,000 right

213 00:21:49.974 00:21:53.789 Luke Daque: in our dashboard if we just go to August.

214 00:21:54.690 00:21:56.469 Luke Daque: Alright, let’s do

215 00:21:57.730 00:21:59.120 Luke Daque: custom.

216 00:22:00.320 00:22:01.790 Luke Daque: August.

217 00:22:02.150 00:22:04.350 Luke Daque: and this would be Pdt.

218 00:22:05.870 00:22:12.140 Luke Daque: We have 322. So it’s a it’s less. That’s it’s like a hundred 1,000 less.

219 00:22:12.860 00:22:16.310 Luke Daque: which makes sense right? Because like returns would

220 00:22:16.320 00:22:18.490 Luke Daque: most probably always be

221 00:22:19.440 00:22:22.040 Luke Daque: larger than the total refund amount.

222 00:22:25.410 00:22:29.049 Payas Parab: Yeah, I’m trying to see if online, they define what it is.

223 00:22:29.490 00:22:33.149 Luke Daque: Yeah, I’m also like trying to look at the Erd here.

224 00:22:33.810 00:22:39.159 Payas Parab: It says a return is different from a refund, because the return deals with the value of the goods.

225 00:22:39.270 00:22:42.170 Payas Parab: but a refund deals with the value of tender that you issue.

226 00:22:42.170 00:22:42.800 Luke Daque: A customer.

227 00:22:42.800 00:22:44.399 Payas Parab: When you process a return.

228 00:22:44.500 00:22:47.419 Luke Daque: Hmm, so we do have a tender

229 00:22:48.880 00:22:50.310 Luke Daque: transaction.

230 00:22:53.110 00:22:56.310 Luke Daque: I wonder if we can use this? We can try. We can try this out.

231 00:23:02.500 00:23:07.710 Payas Parab: So the refund is the amount that like is just given back to the customer. But then the return has to do with.

232 00:23:08.590 00:23:11.399 Luke Daque: Yeah. More than that, cause. It needs like

233 00:23:11.720 00:23:15.349 Luke Daque: they would have to spend for shipping, shipping the item back

234 00:23:15.700 00:23:19.239 Luke Daque: and like whatever packing, whatever else.

235 00:23:19.240 00:23:19.840 Payas Parab: Hmm.

236 00:23:19.990 00:23:20.560 Luke Daque: Right.

237 00:23:20.990 00:23:21.650 Payas Parab: Yeah.

238 00:23:26.390 00:23:31.470 Luke Daque: I can try adding this tender transaction amount and see if that

239 00:23:31.880 00:23:33.600 Luke Daque: sums up with

240 00:23:33.630 00:23:34.900 Luke Daque: the returns.

241 00:23:36.010 00:23:39.249 Luke Daque: They didn’t also like, if we go to shopify

242 00:23:39.760 00:23:43.490 Luke Daque: like total sales, for example, they have like this formula over here.

243 00:23:44.010 00:23:48.350 Luke Daque: but they don’t have anything for returns that that would have been great

244 00:23:48.480 00:23:51.029 Luke Daque: like if they had something over here. But.

245 00:23:51.600 00:23:52.000 Payas Parab: Yeah.

246 00:23:52.000 00:23:52.739 Luke Daque: I think.

247 00:23:53.760 00:23:56.160 Payas Parab: What about net return value does? Oh.

248 00:23:59.750 00:24:01.399 Luke Daque: Yeah, just it’s just that.

249 00:24:02.000 00:24:09.400 Payas Parab: So, but didn’t. Isn’t there also this like thing with like it, might be related to the time period where it’s like the process at date versus the.

250 00:24:09.400 00:24:10.150 Luke Daque: That’s also.

251 00:24:10.150 00:24:11.440 Payas Parab: The original sale.

252 00:24:11.440 00:24:12.920 Luke Daque: That could be

253 00:24:13.160 00:24:15.009 Luke Daque: a thing as well. But

254 00:24:15.030 00:24:19.259 Luke Daque: but still refunds would still be probably different than returns. Right? So

255 00:24:21.140 00:24:23.360 Luke Daque: yeah, I can. I can look into that, I’ll.

256 00:24:23.580 00:24:27.609 Payas Parab: I think I think we had cause. Utam had mentioned that that was an issue before

257 00:24:27.670 00:24:28.920 Payas Parab: with refunds.

258 00:24:30.050 00:24:31.470 Luke Daque: Yeah, like, with.

259 00:24:31.470 00:24:45.179 Payas Parab: So I think he mentioned that like, there’s like a process at date for the refund. And then there’s the date of the created at a date for the order id right, but the refund when it aggregates it’s aggregating, based on like when it was processed.

260 00:24:45.180 00:24:48.040 Luke Daque: Yeah, it was. There’s a process that date. So this might.

261 00:24:48.320 00:24:49.260 Luke Daque: B.

262 00:24:50.350 00:24:53.719 Luke Daque: What shopify is looking at whether it maybe.

263 00:24:53.720 00:24:57.649 Payas Parab: Because my assumption is your other table is built on just joining the order. Id.

264 00:24:57.650 00:24:58.190 Luke Daque: Yeah.

265 00:24:58.190 00:25:01.009 Payas Parab: That it’s tied to that. The refund is tied to.

266 00:25:01.010 00:25:04.559 Luke Daque: Right. So it’s tied to the order created date as opposed.

267 00:25:04.560 00:25:08.280 Payas Parab: That’s what I’m saying. Yeah. So like, I think, I think that’s if you take a stab at

268 00:25:08.858 00:25:28.209 Payas Parab: try and aggregate by month, based on the process that date for refund, and then see how close we get. I think that might explain. That’s that to me, is more likely the explanation than the restocking and logistics fees, because, like I was surprised by this, I didn’t know this, but it seems that a lot of their logistics and fees that way are handled offline.

269 00:25:32.070 00:25:33.082 Payas Parab: so I think.

270 00:25:33.590 00:25:35.189 Payas Parab: I think we just wanna

271 00:25:36.350 00:25:41.660 Payas Parab: I I think my, my guess is, it’s the process that date versus the created at date for the order Id

272 00:25:41.750 00:25:43.120 Payas Parab: is the core issue.

273 00:25:45.590 00:25:50.179 Luke Daque: I can check. I can check this out. I’ll use process at.

274 00:25:50.540 00:25:55.559 Luke Daque: And other thing I can try to is add the refund amount to the

275 00:25:55.810 00:26:00.320 Luke Daque: transact. Tender transaction, like the refund transaction amount versus tender

276 00:26:00.460 00:26:03.650 Luke Daque: transaction, because maybe that could also be

277 00:26:04.020 00:26:05.240 Luke Daque: returned.

278 00:26:06.407 00:26:08.610 Luke Daque: What else can we see here?

279 00:26:08.610 00:26:08.969 Payas Parab: Great.

280 00:26:12.730 00:26:16.359 Luke Daque: order line refund. There’s order line refund here.

281 00:26:17.410 00:26:20.099 Luke Daque: Yeah, this is just the subtotal total.

282 00:26:20.790 00:26:22.320 Luke Daque: There’s tax, though.

283 00:26:26.370 00:26:30.759 Payas Parab: Yeah, I think I think that that to me might be because Utam had mentioned that that’s come up with other clients

284 00:26:30.910 00:26:32.460 Payas Parab: as the core reason.

285 00:26:33.100 00:26:33.820 Luke Daque: Yeah.

286 00:26:34.840 00:26:35.670 Luke Daque: okay.

287 00:26:38.600 00:26:39.589 Payas Parab: Great. Okay.

288 00:26:39.880 00:26:45.440 Payas Parab: Do you want to take a stab at that, and just see if you can aggregate it by that by the process that day, and see how much closer we get.

289 00:26:45.620 00:26:46.519 Luke Daque: For a screenshot.

290 00:26:46.520 00:26:50.089 Payas Parab: Or analytics. And then just let me know, because if it’s not that, then it’s like

291 00:26:50.230 00:26:56.530 Payas Parab: we can figure out a way to frame it and just be like and shopify analytics, does it differently. And this is why, how we’re doing it.

292 00:26:56.530 00:26:57.759 Luke Daque: Yeah, sure. Sounds good.

293 00:26:57.760 00:27:03.429 Payas Parab: Like, but I’d rather, if we can just figure out the my guess is this process. That date might be able to figure it out.

294 00:27:03.430 00:27:06.459 Luke Daque: Okay, yeah, I’ll I’ll do that. I’ll I’ll check it out.

295 00:27:06.980 00:27:11.099 Luke Daque: I’ll I’ll just use August, I guess, because that’s what we’re.

296 00:27:11.100 00:27:13.200 Payas Parab: Yeah, August is like, the good testing, yeah.

297 00:27:13.200 00:27:13.820 Luke Daque: Yeah.

298 00:27:14.160 00:27:14.890 Luke Daque: okay.

299 00:27:14.890 00:27:22.999 Nicolas Sucari: Yeah, let’s have August everything. And yeah, let’s let’s go. Let’s keep tracking and see if we can get with that process that date.

300 00:27:23.180 00:27:24.599 Nicolas Sucari: And then we can just

301 00:27:24.740 00:27:26.690 Nicolas Sucari: keep working on it. I think.

302 00:27:26.840 00:27:34.769 Nicolas Sucari: if not, if that’s not possible. As I said, maybe we can just say, Hey, these are logic. Right for you. Okay, let’s focus on this handle.

303 00:27:35.290 00:27:36.110 Luke Daque: Yeah.

304 00:27:37.490 00:27:43.373 Luke Daque: Sounds good. Yeah. I’ll take a stab at that. I’ll see what what shows. I’ll just slack you

305 00:27:43.720 00:27:45.499 Luke Daque: any difference at all.

306 00:27:45.500 00:27:46.586 Payas Parab: Sure. See?

307 00:27:48.460 00:27:49.460 Payas Parab: Alright guys.

308 00:27:50.000 00:27:50.409 Luke Daque: Yep.

309 00:27:50.930 00:27:51.490 Luke Daque: Cool.

310 00:27:51.490 00:27:52.370 Nicolas Sucari: Guys, bye, bye.

311 00:27:52.370 00:27:52.909 Luke Daque: Sounds good.

312 00:27:52.910 00:27:54.530 Payas Parab: Talk soon. Alright, bye, bye.