Meeting Title: [Eden] Standup and Weekly Sprint Retro-Planning Date: 2025-04-11 Meeting participants: Aakash Tandel, Annie Yu, Demilade Agboola, Robert Tseng, Sahana Asokan, Awaish Kumar


WEBVTT

1 00:04:03.960 00:04:05.420 Robert Tseng: Hey, Annie! Hey! Akash!

2 00:04:06.640 00:04:07.610 Annie Yu: Hello guys.

3 00:04:08.910 00:04:09.719 Aakash Tandel: Hey? How’s it going.

4 00:05:12.670 00:05:15.359 Aakash Tandel: Annie? Is this ticket still blocked.

5 00:05:16.030 00:05:16.750 Annie Yu: I.

6 00:05:16.990 00:05:31.399 Annie Yu: So yesterday I got the new table. For some reason for that one I was having trouble to turn it into a bar chart. But I was playing around with the original data source, and I was able to turn that into a bar chart using the original one.

7 00:05:31.650 00:05:33.400 Annie Yu: So I published it.

8 00:05:33.750 00:05:35.169 Aakash Tandel: Oh, okay, this is done.

9 00:05:36.220 00:05:36.830 Annie Yu: Yeah.

10 00:05:40.290 00:05:43.230 Aakash Tandel: Awesome sounds good.

11 00:05:47.870 00:05:48.910 Aakash Tandel: Alright!

12 00:05:50.750 00:05:56.549 Aakash Tandel: Do we want to start off with the marketing? Dash stuff.

13 00:05:57.110 00:06:02.519 Sahana Asokan: Yeah, I published that. So that should be on tablet online with all the updates.

14 00:06:02.700 00:06:03.340 Aakash Tandel: Okay.

15 00:06:03.340 00:06:07.249 Sahana Asokan: The Ltv. That’s like that. That was the only other thing we needed to add.

16 00:06:08.410 00:06:12.269 Aakash Tandel: Cool and has had Mattesh had a chance to review that yet or no, probably not.

17 00:06:12.650 00:06:18.960 Sahana Asokan: I don’t think so, cause I was not on stand up yesterday, and I didn’t hear it from any of you, so I don’t think so.

18 00:06:19.430 00:06:21.580 Aakash Tandel: Yeah, Robert, I’m assuming that’s right.

19 00:06:21.580 00:06:23.800 Robert Tseng: Yeah, I don’t think Natasha’s responded.

20 00:06:23.940 00:06:34.304 Aakash Tandel: Okay? So we can waiting on Letish to review. It’s in client and the client feedbacks. That sounds good.

21 00:06:35.280 00:06:40.509 Aakash Tandel: guess we can ping update him on slack. Just let him know that this is available.

22 00:06:40.510 00:06:46.329 Robert Tseng: Yeah. But wasn’t. Weren’t we trying to edit some of the Channel specific stuff, too? Like, it wasn’t just adding a new thing.

23 00:06:48.940 00:06:55.030 Robert Tseng: So like, yeah, we’re gonna ask him for review. And we’re we’re gonna be like, hey, Mattesh? We added. Ltv.

24 00:06:55.710 00:07:00.770 Robert Tseng: and then he’s gonna look at it. And he’s be like. Well, what about the other stuff that I asked to edit right.

25 00:07:01.600 00:07:02.999 Aakash Tandel: What were those other edits.

26 00:07:04.010 00:07:04.730 Robert Tseng: Oh!

27 00:07:04.910 00:07:05.670 Aakash Tandel: At the end.

28 00:07:05.670 00:07:12.499 Robert Tseng: Channel specific performance. Metrics were still kind of a a wash like it, like it was just like not ready right.

29 00:07:13.340 00:07:15.130 Sahana Asokan: No, that’s all in there.

30 00:07:15.890 00:07:17.940 Robert Tseng: Yeah. But is it accurate?

31 00:07:17.940 00:07:31.530 Sahana Asokan: Oh, I asked, if you guys could use, I think I posted the screenshots of the some of those metrics not being accurate for the trailing 7 days. I don’t know. I didn’t hear back from anyone about the update on that.

32 00:07:35.180 00:07:43.830 Sahana Asokan: This was the north main comparison. I had included the screenshots of the the data that I was seeing versus Robert’s excel sheet.

33 00:07:44.740 00:07:45.480 Aakash Tandel: This guy.

34 00:07:46.940 00:07:49.660 Sahana Asokan: No, I posted it in, I believe. Slack.

35 00:07:54.270 00:07:55.110 Awaish Kumar: So like.

36 00:07:56.350 00:08:06.000 Awaish Kumar: in the north beam data like factored performance table which you are looking. It is coming directly from north beam. And it should have correct spam by channel.

37 00:08:06.240 00:08:11.519 Awaish Kumar: and, as I mentioned, like, we don’t have a revenue by channel, and I don’t know.

38 00:08:11.650 00:08:15.130 Awaish Kumar: See any way to link the

39 00:08:15.961 00:08:18.850 Awaish Kumar: spend to the orders directly, like

40 00:08:19.410 00:08:22.960 Awaish Kumar: I can merge. I can connect with the specific

41 00:08:24.121 00:08:30.400 Awaish Kumar: product. But yeah, we cannot connect to orders with channel.

42 00:08:34.100 00:08:36.989 Aakash Tandel: Yeah, that attribution is, gonna be hard.

43 00:08:37.340 00:08:42.180 Aakash Tandel: Robert. What was the idea? With what did they have recommendations on how to do this?

44 00:08:43.409 00:08:46.343 Robert Tseng: Well, we discussed this and stand up yesterday.

45 00:08:48.799 00:08:51.069 Robert Tseng: They don’t. I mean, they don’t have.

46 00:08:52.159 00:08:56.509 Robert Tseng: They. They don’t have recommendations. It’s we we have to kind of figure that out.

47 00:08:59.060 00:08:59.730 Aakash Tandel: Okay?

48 00:09:03.930 00:09:12.800 Aakash Tandel: Yeah. Cause we’re gonna need it. Some sort of, yeah, this, okay.

49 00:09:13.570 00:09:15.799 Sahana Asokan: Robert, I just tagged you in that thread.

50 00:09:21.990 00:09:30.433 Aakash Tandel: Okay. Okay. Well, let’s alright. Yeah, I’m not. I honestly don’t know how to do that.

51 00:09:32.780 00:09:33.980 Aakash Tandel: sounds like a way she don’t.

52 00:09:33.980 00:09:39.699 Robert Tseng: Talked about this yesterday. I wish I honestly don’t remember what I told you. So. It’s just yeah. This has been too many.

53 00:09:39.700 00:09:48.660 Awaish Kumar: Yeah, we we just discussed that we cannot directly connect the orders. But what we can do is that maybe in the north span data. We have a

54 00:09:48.990 00:09:52.180 Awaish Kumar: like product name. We have a channel name. We have a spam

55 00:09:53.201 00:09:58.910 Awaish Kumar: we can connect the data revenue on the product level.

56 00:09:59.999 00:10:03.950 Awaish Kumar: But we we cannot go further down there to the channel level.

57 00:10:06.270 00:10:12.460 Awaish Kumar: yeah. So like, that’s that’s what like. That’s the only thing we we discussed like we didn’t add any solution yet.

58 00:10:12.830 00:10:23.230 Robert Tseng: Yeah. So Cac is just spend over a number of orders. So spend by channel we have that we just can’t associate orders to channel. That’s the problem. Right?

59 00:10:24.380 00:10:28.502 Robert Tseng: Okay? So orders by channel.

60 00:10:30.140 00:10:35.680 Robert Tseng: we can’t use. I mean, U Utms, is typically.

61 00:10:35.680 00:10:36.120 Awaish Kumar: Oh!

62 00:10:36.120 00:10:42.429 Robert Tseng: That’s that’s brought in. I don’t think the Utms are that reliable, but especially historically.

63 00:10:42.750 00:10:52.110 Robert Tseng: but, like, I don’t know, we just have to think about what’s what’s the proxy here like, how how can we like do or order to channel association is that that’s that’s basically what we’re trying to figure out.

64 00:10:53.720 00:10:55.210 Robert Tseng: And like, yeah.

65 00:10:55.210 00:10:58.931 Demilade Agboola: What’s the issue with the what’s the issue with the Utms?

66 00:11:01.110 00:11:03.460 Demilade Agboola: Is it that the one not tracked, or is it that.

67 00:11:03.460 00:11:13.697 Robert Tseng: Yeah, it was like there was a good chunk that wasn’t tracked before. The way that they were labeling like Channel was inconsistent. This was an issue. That kind of like was flagged last week.

68 00:11:14.030 00:11:36.430 Robert Tseng: remember when for semaglutide gummies there was ad spend showing up there. Yes, it was partially because we’re spreading ad spend across all orders. So even though there are no new gummy customers there are still existing gummy customers. And so some of the ad spend gets brought there.

69 00:11:36.766 00:11:53.909 Robert Tseng: So that’s that was part of it. But the other part was just in when when a wish gave a kind of ran a query, and sent this like spreadsheet. There were some other like campaigns that weren’t actually gummy, that were being wrongly associated. And that’s just from the

70 00:11:54.220 00:12:02.380 Robert Tseng: well, we we’ve changed it now to look for product name at different levels. But it was. It was, yeah, I think it just. It’s just

71 00:12:02.510 00:12:12.440 Robert Tseng: this is Pre, or they just were not following the naming conventions that we had sent them. And so that was kind of an issue with the Utm tracking.

72 00:12:13.740 00:12:28.209 Robert Tseng: But I mean you’re right. I think we should assume that Utms should be dialed in like. It’s pretty straightforward. We’ve already given the naming conventions, whether they followed or not is a different story. But yeah, like I, I don’t see why we wouldn’t be able to use that.

73 00:12:29.730 00:12:30.530 Awaish Kumar: Okay.

74 00:12:31.360 00:12:36.910 Awaish Kumar: So like from Utm, we can get the You are saying we can get the Channel information from Utm.

75 00:12:36.910 00:12:39.381 Robert Tseng: I mean, every order should have a Utm

76 00:12:40.030 00:12:44.089 Robert Tseng: attached to like multiple Utms, and we just use the Utm by channel, right.

77 00:12:44.840 00:12:45.560 Demilade Agboola: Yeah, also.

78 00:12:45.560 00:12:46.750 Awaish Kumar: Okay. Fine.

79 00:12:47.170 00:13:05.369 Demilade Agboola: The the thing we add is also like, you know, there should be a window of aggregation. So because people don’t usually converse immediately. So how do we type the ad. So first, st if an ad was done today, do we do like over the past over the next 7 days, all Utms from this source can be tied to this ad

80 00:13:07.140 00:13:13.600 Demilade Agboola: because there also has to be a date factor in how we’re aggregating, aggregating these ads to conversions.

81 00:13:13.920 00:13:23.049 Robert Tseng: Okay? So I think what we need here is a sub issue, to define, like, the yeah, like.

82 00:13:23.260 00:13:32.130 Robert Tseng: which utm the window. Yeah, like, I guess I don’t know what we want to call this ticket. But it’s just defining the

83 00:13:33.010 00:13:38.690 Robert Tseng: yeah, the order to channel like association. And how we model that

84 00:13:39.580 00:13:47.309 Robert Tseng: I’m like, yeah, Sahana, you’ve mentioned this on Tuesday, but like, I don’t know like it’s, I think there was Oasius

85 00:13:48.510 00:14:11.959 Robert Tseng: question like there isn’t really. There’s not really something for me to take action on, like I actually have to like, discuss, and like, think through this like I I think if you run into an issue like this, you should give your for your point of view on this is what I think we should do to associate these orders like, I, I mean, otherwise, I’m just basically going to be doing it like, on, like through through a stand up like this, or just doing it on my own.

86 00:14:33.440 00:14:37.869 Robert Tseng: But yeah, I guess, Akash, once you create that, you can assign that to me, I’ll I’ll

87 00:14:41.320 00:14:42.510 Robert Tseng: I can define it.

88 00:14:47.860 00:14:56.719 Aakash Tandel: That’s good. I don’t know if that falls into some of the

89 00:14:59.090 00:15:22.099 Aakash Tandel: stuff that Mattesh was trying to get with like cutter, and those folks on like attribution like timelines, because I know that they had, like an unknown timeline on their attribution for off the offer? We’ll need to factor that into here. And also, yeah, actually, one thing I want to add is that, are we just talking first? st

90 00:15:22.610 00:15:30.449 Aakash Tandel: 1st touch attribution versus other attribution

91 00:15:31.850 00:15:35.689 Aakash Tandel: models. Because that’s gonna impact what that looks like.

92 00:15:36.910 00:15:41.790 Robert Tseng: Yeah, I kind of. I’ve I’ve I mean, I

93 00:15:42.880 00:15:59.870 Robert Tseng: once again, like, I think this is like a couple hours investigation, or me for to do it from scratch, but like I need, I don’t. I don’t believe that Northweam doesn’t do this already, like they have. They must do it by channel like that. That’s like, and we should be able to like. Figure out what their logic is. And

94 00:16:00.780 00:16:07.329 Robert Tseng: it’s probably not that complicated. They probably just use like they probably just use last touch is my guess.

95 00:16:07.330 00:16:09.459 Sahana Asokan: Yeah, I agree, I actually feel like

96 00:16:09.700 00:16:14.700 Sahana Asokan: we should just go down that path. And just look at how they’re defining it. And if we can just change it.

97 00:16:17.720 00:16:20.940 Aakash Tandel: Yeah, this is not.

98 00:16:26.120 00:16:27.000 Aakash Tandel: Okay.

99 00:16:27.100 00:16:28.610 Aakash Tandel: Yeah, maybe.

100 00:16:30.230 00:16:34.940 Robert Tseng: Is probably in the north beam settings. You would have to just go into the platform and figure that out.

101 00:16:50.090 00:16:54.670 Aakash Tandel: So this is like, sounds like it needs some investigation. So that’s

102 00:16:56.180 00:17:00.989 Aakash Tandel: I guess it’s fine. I yeah assigned that sub issue to Robert.

103 00:17:01.940 00:17:08.420 Aakash Tandel: Aside from that, is there anything else remaining on the dashboard that

104 00:17:10.500 00:17:13.080 Aakash Tandel: mutesh is looking for that we don’t have currently on there.

105 00:17:13.280 00:17:15.359 Sahana Asokan: No, I think all of this is there.

106 00:17:15.750 00:17:16.310 Aakash Tandel: Okay.

107 00:17:16.819 00:17:18.369 Sahana Asokan: And a Qc. The

108 00:17:18.799 00:17:26.689 Sahana Asokan: Ltv. And Calc. As well as the Mer. I know we we’re not like. I think I don’t think we’re finalized on that number right, but

109 00:17:26.819 00:17:28.509 Sahana Asokan: I think it looks better than before.

110 00:17:29.930 00:17:33.440 Aakash Tandel: Okay, yeah. And mer, we’re just pulling from.

111 00:17:34.650 00:17:39.780 Robert Tseng: We can’t do mer. We haven’t even done the full marketing budget. So it’s not even. It’s not a true mer.

112 00:17:39.980 00:17:44.689 Sahana Asokan: Yeah, it’s just it’s just kind of like a placeholder. We have to, I think, clean it up later.

113 00:17:44.690 00:17:49.449 Aakash Tandel: Not just using north beam data as their number. For from, yeah, okay.

114 00:17:49.450 00:17:49.790 Robert Tseng: Yeah.

115 00:17:49.790 00:17:50.440 Aakash Tandel: Our hands.

116 00:17:50.550 00:17:54.150 Aakash Tandel: I can’t take it out. Okay, alright.

117 00:17:57.390 00:18:00.699 Aakash Tandel: What else is this? Still, I know this is still.

118 00:18:00.700 00:18:06.319 Sahana Asokan: Still waiting. I mean, I think it wasn’t a priority for this week, right? That’s kind of why we

119 00:18:06.570 00:18:08.820 Sahana Asokan: like. We never talked about it.

120 00:18:09.840 00:18:12.700 Aakash Tandel: It was not. I’m trying to

121 00:18:13.360 00:18:20.039 Aakash Tandel: get an overview of what everything looks like. Let’s just go through, I guess what everyone’s working on and

122 00:18:20.700 00:18:29.280 Aakash Tandel: stand up. But just just so we can get pulsive check of everything. So it’s on your. This is still pending client feedback. This is kind of paused.

123 00:18:30.620 00:18:32.770 Sahana Asokan: Yes, I would say

124 00:18:33.300 00:18:45.569 Sahana Asokan: I would actually just group this with the customer journey dashboard, because the customer journey dashboard is one of 3 dashboards. That’s part of this initiative like I would look almost look at that as like a higher level ticket.

125 00:18:46.340 00:18:48.450 Aakash Tandel: Yeah, that makes sense to me.

126 00:18:48.760 00:18:58.319 Aakash Tandel: I can put these blocks there. We’re gonna restart those later. These reviews already happened right?

127 00:18:59.990 00:19:03.419 Aakash Tandel: That was, that was with the call, with Rebecca.

128 00:19:03.420 00:19:06.350 Sahana Asokan: Yeah, that’s what our call with her last week, I believe.

129 00:19:07.400 00:19:08.900 Aakash Tandel: And then

130 00:19:12.320 00:19:20.769 Aakash Tandel: oh, I don’t know exactly what this is, but I may cancel this one product. Owner seems random.

131 00:19:21.610 00:19:25.570 Aakash Tandel: Not a lot of contacts here, I’m gonna say, cancel.

132 00:19:28.710 00:19:33.370 Aakash Tandel: okay, okay. Anything else you’re working on, son.

133 00:19:33.650 00:19:36.180 Sahana Asokan: No, those are kind of the 3 main areas.

134 00:19:38.270 00:19:41.480 Aakash Tandel: Alright. Let’s go to Demo A.

135 00:19:42.150 00:19:47.489 Aakash Tandel: What are you working on, Demo today? I know there’s some. This is is this Pr, still out there?

136 00:19:49.315 00:20:03.500 Demilade Agboola: Yes. Spr is still out there. Trying to close it. So the issue is not necessarily in the pr, but it’s just investigating the beta of the Pr is testing because the Pr

137 00:20:03.780 00:20:20.179 Demilade Agboola: basically the Pr is not changing anything. But then it’s showing that we have more than 10% change in the staging and the prod environment. So it’s kind of looking into where that change coming from. And if we need to rerun both environments so that they’re the same

138 00:20:20.900 00:20:22.420 Demilade Agboola: because there should be no error.

139 00:20:24.890 00:20:27.440 Demilade Agboola: So that’s kind of what’s going on in that regard.

140 00:20:27.910 00:20:41.221 Demilade Agboola: Then I think, like the exact dashboard, the updating models. I have done that. But then, effectively,

141 00:20:42.440 00:20:51.749 Demilade Agboola: it wasn’t necessarily useful to Annie, so I don’t necessarily think because any could could do it without this. So it’s done. But

142 00:20:51.910 00:20:58.109 Demilade Agboola: I I think for the second one, I think if any could do without it for this, you potentially could do it.

143 00:20:58.270 00:21:02.129 Demilade Agboola: So you could also build out the second bar chart without needing another model.

144 00:21:02.570 00:21:05.140 Robert Tseng: Alright. Anyone was able to do it without any model change.

145 00:21:06.120 00:21:07.529 Demilade Agboola: Yeah, she used the original.

146 00:21:08.610 00:21:09.310 Robert Tseng: Amazing.

147 00:21:09.310 00:21:16.509 Annie Yu: I actually had problems using the updated model. But I was able to turn that into bar charts with using the original.

148 00:21:16.660 00:21:19.520 Robert Tseng: Hmm, interesting.

149 00:21:19.850 00:21:24.029 Aakash Tandel: Yeah, that sounds good. I guess we can just say that we won’t do.

150 00:21:24.210 00:21:25.529 Aakash Tandel: I mean, we don’t need to push

151 00:21:26.390 00:21:29.093 Aakash Tandel: if we don’t need to do it

152 00:21:33.690 00:21:39.100 Demilade Agboola: So so technically that one is done. It’s the second one we’re canceling, but it’s still still the same thing.

153 00:21:39.770 00:21:42.240 Aakash Tandel: Yeah, this is the same thing. Yeah. Okay. Awesome.

154 00:21:42.993 00:21:46.650 Aakash Tandel: Yeah. I would say, if you don’t need to make change, don’t make a change.

155 00:21:47.581 00:21:52.390 Aakash Tandel: Okay, anything on this guy also apologies.

156 00:21:53.930 00:21:56.909 Demilade Agboola: Yes, this is the one that was blocked right based on.

157 00:21:57.180 00:22:07.963 Robert Tseng: This is more my investigation, I mean, that’s where I’ve been spending a good chunk of my time, because I’m basically trying to help them recover 50 orders a week. So that’s

158 00:22:08.700 00:22:09.440 Robert Tseng: That’s

159 00:22:10.240 00:22:19.269 Robert Tseng: I think my investigation is pretty much done done at this point, but I’ve already shared everything with the client and basically for context, like

160 00:22:19.420 00:22:21.269 Robert Tseng: the rest of the team

161 00:22:22.180 00:22:32.933 Robert Tseng: with the new payment statuses web, the new web hooks that they showed. We’re seeing successful payments go through, and then orders not being created. There’s a little there’s there are some patterns.

162 00:22:33.550 00:22:42.109 Robert Tseng: I mean, I think 50 is pretty generous, but like there we we, I think we’re. I’m still trying to like PIN the magnitude of like

163 00:22:43.110 00:22:47.849 Robert Tseng: which customers are seeing how how many customers are seeing this. But the impact.

164 00:22:48.190 00:22:55.440 Robert Tseng: you know, somewhere between 5 to 15% of transactions are are being impacted by this. By this issue on bask and

165 00:22:56.410 00:23:02.715 Robert Tseng: yeah, I mean, there’s all this context in the tickets that I’ve created. Like as sub issues of the of this thing. So

166 00:23:03.330 00:23:05.509 Robert Tseng: yeah, I mean, I think that’s

167 00:23:06.010 00:23:11.550 Robert Tseng: that’s that’s been an ongoing investigation that I’ve been

168 00:23:11.800 00:23:14.169 Robert Tseng: spending my time on the past couple of days.

169 00:23:15.470 00:23:16.160 Aakash Tandel: Okay,

170 00:23:18.410 00:23:26.250 Aakash Tandel: cool. I just pulled that ticket off of demo audio. Then I think it makes sense. I put it to you on ending client feedback.

171 00:23:28.700 00:23:34.849 Robert Tseng: Yeah, I mean, Dick and I discussed that like, he’s not really blocked on that anymore. Right? It’s just like.

172 00:23:35.220 00:23:41.399 Robert Tseng: yeah, I mean, we’ll. I’ll resolve these edge cases, but then, like I should still be assigned to him, because.

173 00:23:41.910 00:23:45.270 Demilade Agboola: Same water. We we talked about you needing to work back absolutely.

174 00:23:45.270 00:24:05.040 Robert Tseng: From what is that final model that we need from the initial transaction all the way to when the order is like delivered? We need to have that full customer journey, transaction order, journey, whatever you want to call it. You were supposed to design that solution, and so kind of bring that to me. Right? That’s kind of what the description is. Here.

175 00:24:06.100 00:24:09.030 Demilade Agboola: Yeah, at this point, that is the task.

176 00:24:12.390 00:24:14.650 Demilade Agboola: Yeah, that’s been. That’s the task. Basically.

177 00:24:15.210 00:24:15.770 Aakash Tandel: Okay.

178 00:24:15.910 00:24:17.739 Aakash Tandel: Cool. Yeah.

179 00:24:17.740 00:24:29.069 Robert Tseng: So this should. Yeah, this should not be assigned to me. All the sub tickets are assigned to me. But he there is. We updated the subscription yesterday. And I mean, I think this is, we’re just rehashing what we talked about yesterday.

180 00:24:29.961 00:24:34.750 Aakash Tandel: Just to do yesterday. Can I put due today? Is that possible today or no demo audit.

181 00:24:36.800 00:24:41.279 Demilade Agboola: It will be tight squeeze, the more more realistic expectation will be Monday.

182 00:24:45.340 00:24:45.890 Aakash Tandel: Okay?

183 00:24:46.000 00:24:47.890 Aakash Tandel: Sounds good.

184 00:24:48.326 00:24:52.620 Aakash Tandel: Okay, anything else you’re working on? It sounds like that’s gonna be the main thing you’re working on. But.

185 00:24:53.520 00:24:56.463 Demilade Agboola: Yeah, those are the main things I’m working on.

186 00:25:01.650 00:25:07.209 Aakash Tandel: Cool. Okay, sounds good. I guess I can switch over to Robert because we were just talking about your stuff.

187 00:25:11.270 00:25:16.729 Aakash Tandel: any. I mean, it sounds like you’re working on a lot of things, anything you need to specifically highlight to here.

188 00:25:16.730 00:25:36.999 Robert Tseng: No, yeah. I mean, I think for me coming these standups. I was telling the team like, I think, coming out of these meetings. I don’t need to know, like all these moving tickets or whatever like, I think all these updates need to be happening. Async, like, I need to get out of this meeting what are like the 2 or 3 most important things that I can do to support the team? For for the day. I think

189 00:25:37.220 00:25:38.240 Robert Tseng: that whole

190 00:25:38.500 00:26:01.268 Robert Tseng: order journey investigation came out of a stand up a couple of days ago and day malady was kind of sharing where he was blocked and some issues. He he flagged so that I think that was a great example of like where I knew where I needed to jump in. As I was working through it. Team turned out to be a bigger issue than we thought, and then I was able to go and get the right people involved to continue that

191 00:26:01.610 00:26:29.979 Robert Tseng: But yeah, I think it was because he he was able to tell me specifically what error he was thinking, what what error he was seeing like what like he thinks like could have happened like I I don’t know. Just like it helped me reduce like cognitive load, so I could actually like, figure out like how he was thinking about the problem. So that’s that’s I mean, I feel like, that’s where my, that’s how like my tickets kind of assign. I kind of just pick up wherever we’re we got stuck. And yeah, like I

192 00:26:30.150 00:26:31.570 Robert Tseng: I that’s

193 00:26:31.680 00:26:45.449 Robert Tseng: like, that’s how I feel like I would prefer to spend this time on stand up like figuring out what are. How do I need to arrange these priorities so that I know what are like the 2 or 3 things that I can knock out for the for the team.

194 00:26:45.870 00:26:47.110 Aakash Tandel: Yeah, no. That makes sense.

195 00:26:47.660 00:27:02.639 Robert Tseng: For the offer and vibe, and whatever like. I’m not doing that this week. It’s just not that important. We are trying to get them a demo for like direct integrations. So that’s like the other thing that I want to get done today.

196 00:27:03.021 00:27:23.900 Robert Tseng: Have the initial platform set up already, like, I’ve connected Zanodi data. And then I just need to get all these other random ad like Google, Facebook, Tiktok, Snapchat, whatever, all all connected. So I’m just gonna be like knocking on the doors and trying to get people to give me like access so I can go and make set up those connectors.

197 00:27:24.180 00:27:26.370 Aakash Tandel: Okay. And those are going direct to.

198 00:27:26.613 00:27:30.070 Robert Tseng: Think this is a corral demo. So yeah.

199 00:27:31.160 00:27:35.650 Aakash Tandel: That sounds good. Okay. Cool. Is there a ticket here for that? Do you want me to make a ticket for that?

200 00:27:37.330 00:27:40.670 Aakash Tandel: Yeah, I thought there was a ticket already.

201 00:27:41.290 00:27:43.189 Aakash Tandel: Maybe it’s not assigned to you.

202 00:27:44.270 00:27:48.448 Robert Tseng: Yeah, if not, I’ll if not, I’ll make the ticket myself. It’s fine.

203 00:27:49.410 00:27:50.960 Aakash Tandel: Okay, cool.

204 00:27:52.940 00:28:04.219 Aakash Tandel: Let’s go to. Oh, okay. Zendesk data to raw.

205 00:28:05.810 00:28:07.410 Aakash Tandel: Oh, yeah. Has this

206 00:28:10.000 00:28:12.190 Aakash Tandel: Has anyone run this by the client.

207 00:28:12.670 00:28:14.820 Aakash Tandel: if they go for a polytomic, refresh.

208 00:28:14.820 00:28:26.040 Robert Tseng: No, we’re we’re blocked on this. Knows. I think I I’m not gonna tell the client we’re gonna charge them more on connectors unless we’re able to cut cost cut costs elsewhere. Josh won’t approve it.

209 00:28:26.770 00:28:31.740 Aakash Tandel: Okay, that makes sense. I will.

210 00:28:32.050 00:28:40.530 Aakash Tandel: That’s blocked. Okay, marketing. Spend. Okay, we talked about that one Zenati. This is gonna be crow.

211 00:28:41.620 00:28:43.100 Aakash Tandel: By offline.

212 00:28:45.770 00:28:48.919 Aakash Tandel: Is this the same thing as no, this is also crow.

213 00:28:49.716 00:28:51.234 Robert Tseng: No, this is

214 00:28:52.020 00:29:04.729 Robert Tseng: yeah. This is like the offer. Mountain vibe influencer. These are like offline channels. Corral will not have these integrations. I’ve set up a spreadsheet that’s in the description. Mattesh.

215 00:29:05.340 00:29:11.060 Robert Tseng: this team has already filled it out. So I guess the action item for a waste here is like to

216 00:29:11.670 00:29:22.483 Robert Tseng: basically look at the spreadsheet and think about like how we’re gonna ingest this into our marketing models so that we can include these data sources as channels.

217 00:29:23.550 00:29:24.320 Robert Tseng: this will be.

218 00:29:24.320 00:29:24.850 Awaish Kumar: Oh, yeah.

219 00:29:24.850 00:29:39.650 Robert Tseng: We need to get these in so that we have the full mer calculate like, so we can do the full mer- mer calculation. This is the other stuff in their marketing budget that isn’t currently being tracked. That Sahana will need in her model to finish the mer.

220 00:29:40.890 00:29:48.309 Awaish Kumar: So I have a I. I read the spreadsheet. So we want to ingest that data

221 00:29:48.620 00:29:59.119 Awaish Kumar: in our warehouse. And then we want to have a table where we have spend, which is by channel, which is coming from north beam, and plus this also right.

222 00:29:59.120 00:30:01.609 Robert Tseng: We’re gonna move off north beam. But yeah, so.

223 00:30:01.610 00:30:01.930 Awaish Kumar: Okay.

224 00:30:01.930 00:30:03.130 Robert Tseng: That source needs to be.

225 00:30:03.130 00:30:04.010 Awaish Kumar: For right now.

226 00:30:04.010 00:30:06.860 Robert Tseng: The model is gonna be the same I’m assuming. But yeah.

227 00:30:06.980 00:30:07.820 Awaish Kumar: Yep.

228 00:30:07.990 00:30:32.229 Awaish Kumar: okay. So. And my question was that you also you mentioned had this sheet and also mentioned an Api for Mntn source. So, and I can also see that there are some rows in that spreadsheet which which is, which are showing that spend for Mntn source as well. So I do. I want to like, do we want to also connect that

229 00:30:32.510 00:30:35.950 Awaish Kumar: through that Api, or just use this spreadsheet? Only.

230 00:30:36.100 00:30:38.395 Robert Tseng: Yeah. So I kind of wrote it as like,

231 00:30:40.230 00:31:00.390 Robert Tseng: If they give us Apis, we should use the Api. If not, then we should just use a spreadsheet. But honestly, we should just we should just use the spreadsheet first.st I feel like that’s easier to spin up so we can just show it to them. They have somebody who’s manually keying in these daily, anyway, so I don’t. I don’t think we need to figure out the the Mnt and Api stuff like I feel like that’s just gonna.

232 00:31:00.690 00:31:01.770 Awaish Kumar: Like, yeah.

233 00:31:01.770 00:31:03.300 Robert Tseng: I think that’s like rendered.

234 00:31:03.940 00:31:04.780 Awaish Kumar: Okay.

235 00:31:04.780 00:31:05.340 Robert Tseng: Yeah.

236 00:31:06.150 00:31:08.109 Awaish Kumar: Yeah, I will bring that in.

237 00:31:08.740 00:31:18.069 Robert Tseng: Okay, yeah. I mean, if you if you’re missing anything else in the in that spreadsheet, just like, let me know. I think it should be enough. It’s just just day

238 00:31:18.270 00:31:27.660 Robert Tseng: like channel and spend right? It’s like daily ad spend per channel like, I think that should be enough to do it. But just let me know if there, if we need more.

239 00:31:30.495 00:31:36.590 Awaish Kumar: Yeah, sure, I will bring that in. We I have a date channel and spend. We can have a table for that, and.

240 00:31:36.790 00:31:37.380 Robert Tseng: Okay.

241 00:31:37.380 00:31:40.349 Awaish Kumar: And and there is a separate table for Northwean, and I think

242 00:31:40.660 00:31:45.189 Awaish Kumar: both can be joined together if we need to have all the channels at one place.

243 00:31:45.190 00:31:48.000 Robert Tseng: Yeah, okay.

244 00:31:49.740 00:31:50.360 Aakash Tandel: Awesome.

245 00:31:50.840 00:31:55.110 Aakash Tandel: That sounds good, anything else for you for wish. There’s some stuff that’s

246 00:31:55.380 00:31:58.719 Aakash Tandel: ready for development if you get

247 00:31:59.380 00:32:03.259 Aakash Tandel: time. But it sounds like that. Ingestion is probably the main thing for today.

248 00:32:05.240 00:32:14.699 Awaish Kumar: Yeah, I will work on that, but ready for development. I think that these 2 I don’t know about the top one, but the second one is just about Zendesk data.

249 00:32:15.510 00:32:16.020 Aakash Tandel: Yeah, so.

250 00:32:16.020 00:32:20.919 Awaish Kumar: It’s blocked, so I don’t think I have anything on this to work right now.

251 00:32:21.900 00:32:27.060 Aakash Tandel: Yeah. Okay. Oh, yeah, that’s a sub issue. Okay? I wish you would clearly identify that. That’s fine. Okay, cool.

252 00:32:27.240 00:32:31.170 Aakash Tandel: That sounds good. Alright, anyone else.

253 00:32:35.220 00:32:41.099 Aakash Tandel: If not, I think I have some stuff, but I’ll be

254 00:32:41.687 00:32:47.220 Aakash Tandel: the main thing. I I can show you guys still work in progress. But oh, wait

255 00:32:47.610 00:32:49.510 Aakash Tandel: now, where is it? I?

256 00:32:51.800 00:32:55.229 Aakash Tandel: Oh, man, where’s that ticket?

257 00:32:57.880 00:32:58.730 Aakash Tandel: Hold on!

258 00:33:01.980 00:33:04.429 Aakash Tandel: I’ll just pull it up this way.

259 00:33:12.370 00:33:17.734 Aakash Tandel: Documentation. Okay, so this is a piece of documentation, and I’ll keep this very quick promise.

260 00:33:18.580 00:33:30.633 Aakash Tandel: This piece of documentation we have for Brand Forge. Sorry for Eden. And it has some of the pieces of information like our source documentation. Well, it’s not filled out. But

261 00:33:31.010 00:33:49.640 Aakash Tandel: I was trying to get a full comprehensive list of the things that Josh and their team is considering like their core data sources. So I’m gonna do some sort of inventory. And I’ve started to do that here. And I’ve also flagged that things are like requested by, you know, parts of the client base. So

262 00:33:49.860 00:34:17.599 Aakash Tandel: as I start filling this out, I’m probably gonna start pinging people in comments. If it’s easy for you to answer the comment, that’ll be great. And if we need to do like a call. I might pull this up on one of our stand ups next week just to fill this thing out. So we all are working off the same page. We’re all working off like the same understanding. And that type of thing cause. I think that’s been kind of lacking across the board and then I think the client would really appreciate having this type of organization.

263 00:34:20.020 00:34:45.090 Robert Tseng: Yeah, this is great. I think, like, Josh is always talking about. Oh, do we have the core data right ready? But it’s like a moving target. I don’t really feel he he really knows what that means, either. So being able to spell it out and like our team, their team all knows, like what quote unquote core data is like, and the metrics that go along with that. I think this is this will help us organize like what.

264 00:34:45.190 00:34:59.039 Robert Tseng: or at least talk about like what we like, what what we’re measuring. And then maybe this will even be helpful when we do the eventually we push into the next like weekly business review. Whatever kind of like project like, it’ll just be like weekly reviews of these metrics. So.

265 00:35:00.690 00:35:16.330 Aakash Tandel: Awesome. Alright also, when you’re working on this, if you have any feedback on like we should add this column, we should pull this thing off. Let me know. This is not a is a living document, not a thing interested in stone, so alright. Y’all appreciate the time.

266 00:35:16.450 00:35:21.849 Aakash Tandel: Feel free to slack, huddle email, do whatever to to get things going.

267 00:35:22.090 00:35:23.650 Aakash Tandel: Otherwise I’ll talk to you all soon.

268 00:35:24.150 00:35:25.699 Robert Tseng: Alright, thanks, all.

269 00:35:25.700 00:35:26.889 Aakash Tandel: So have a good weekend bye.

270 00:35:26.890 00:35:27.420 Robert Tseng: Bye.