Meeting Title: [Eden] Daily Standup Date: 2025-04-15 Meeting participants: Aakash Tandel, Annie Yu, Demilade Agboola, Josh, Rob, Awaish Kumar


WEBVTT

1 00:03:38.770 00:03:40.009 Aakash Tandel: Hey, Josh! How’s it going.

2 00:03:44.060 00:03:45.339 Josh : Hey? How’s it going.

3 00:03:46.680 00:03:47.560 Aakash Tandel: Dude

4 00:04:02.640 00:04:03.560 Aakash Tandel: here. I’m.

5 00:04:05.330 00:04:06.280 rob: Hey, guys.

6 00:04:07.090 00:04:08.080 Aakash Tandel: How you doing.

7 00:04:09.030 00:04:10.530 rob: Good. How are you guys.

8 00:04:10.990 00:04:12.370 Aakash Tandel: Not too bad.

9 00:04:16.890 00:04:24.800 Aakash Tandel: good folks. A minute or 2. Robert is at a conference for the next 2 days, so he will not be joining us.

10 00:04:30.930 00:04:31.830 Josh : Okay.

11 00:04:32.890 00:04:44.029 Josh : I just wanna know how we’re looking on our graphs. Hey? You know, Rob, do you want to pull up that? You know liquor dashboard that we use all we used to use all the time

12 00:04:44.500 00:04:47.040 Josh : it has. Like the bar chart.

13 00:04:47.540 00:04:51.250 Josh : It shows like, I don’t like.

14 00:04:51.590 00:04:55.159 Josh : Basically it’s 1 Adam uses all the time. You know what I’m talking about.

15 00:04:55.890 00:05:02.689 rob: Let me share and tell me if this is it, let’s see.

16 00:05:03.730 00:05:10.629 rob: it’s either gonna be this performance dashboard, or it’s probably this one that Zack made.

17 00:05:17.180 00:05:18.600 rob: Does this look right.

18 00:05:21.240 00:05:22.149 Josh : Okay? And then it’s.

19 00:05:22.150 00:05:35.190 rob: Right the sandbox which we use for like just testing new reports.

20 00:05:35.190 00:05:39.109 Josh : Had the stacked chart or the stack bars on it.

21 00:05:39.810 00:05:40.510 rob: Yeah, I think.

22 00:05:40.510 00:05:43.860 Josh : There’s revenues per month.

23 00:05:50.130 00:05:51.749 rob: Yeah, it might be this one.

24 00:05:51.750 00:05:57.870 Josh : That that one, that one, this is the one that I want to see done this week at cash.

25 00:05:58.040 00:06:00.190 Josh : This, this, the exact thing.

26 00:06:02.010 00:06:07.470 Aakash Tandel: Cool. Rob, can you take a screenshot of like? Maybe the top.

27 00:06:07.470 00:06:08.130 rob: Was it?

28 00:06:08.430 00:06:10.639 rob: I’ll send you a link to it, I mean, unless you.

29 00:06:10.640 00:06:10.980 Josh : Row.

30 00:06:10.980 00:06:13.830 rob: Screenshot. Then you could see the formulas and stuff.

31 00:06:14.150 00:06:16.869 Aakash Tandel: Okay, yeah, that’d be great.

32 00:06:17.090 00:06:19.619 Aakash Tandel: I think this was Annie. Has this been? I know.

33 00:06:19.620 00:06:21.790 Josh : The one Annie’s working on. Yeah.

34 00:06:22.130 00:06:27.369 Aakash Tandel: Okay, let me look at this thing.

35 00:06:34.810 00:06:36.399 Aakash Tandel: Where do you guys go.

36 00:06:39.290 00:06:41.229 rob: I sent you that link on slack.

37 00:06:44.960 00:06:46.090 Aakash Tandel: Cool? Any.

38 00:06:46.090 00:06:48.350 rob: Let me make you an editor on that.

39 00:06:49.230 00:06:50.100 rob: Gosh!

40 00:06:52.990 00:06:56.400 rob: Oh, sorry, I guess, May. You’re not on here yet.

41 00:06:56.920 00:06:58.189 Aakash Tandel: Yeah, your email.

42 00:06:58.390 00:07:01.389 Aakash Tandel: I don’t have a try Eden email. So I don’t know if that’ll.

43 00:07:01.720 00:07:04.569 rob: I can share it outside. Is it Akash?

44 00:07:04.570 00:07:09.070 Aakash Tandel: You’ve got tandell TAND EL.

45 00:07:09.070 00:07:11.050 rob: rainforge.ai.

46 00:07:11.050 00:07:12.330 Aakash Tandel: Yep, that’s right.

47 00:07:14.600 00:07:17.740 rob: I don’t know if it’ll let me make you an editor. But let’s try.

48 00:07:22.010 00:07:23.299 rob: Yeah, there we go.

49 00:07:23.300 00:07:25.119 Aakash Tandel: Cool. Okay. Awesome. Yeah.

50 00:07:25.120 00:07:33.169 rob: Yeah, there’s a lot of just random stuff in here. You can ignore, because it it is just the sandbox like, we don’t use this for live reporting anymore. But.

51 00:07:34.920 00:07:40.935 Aakash Tandel: okay, cool. Yeah, we’ll make sure. All the components of this are good to go, i know,

52 00:07:41.830 00:07:50.219 Aakash Tandel: i think, demo Lade, or no. I know, Annie, you were able to make the stack bar chart without the model change. So

53 00:07:51.600 00:07:56.939 Aakash Tandel: do you trying to pull the ticket that you talked about that in

54 00:08:01.970 00:08:16.589 Annie Yu: Yeah. So obviously, I will have to take more time to look into that. But while I have everyone here, I think I wanna ask, is that more like a version? 2 of our current retention dashboard, or is a separate one separate one with different metrics.

55 00:08:18.340 00:08:40.991 Aakash Tandel: Yeah. So I think that’s the one that they’ve been working off of from their bigquery export. And the idea was for us to build that with our snowflake data. In tableau. So that was kind of the the transition over to the other tool. So I see that you have 1st order and repeat order. Revenue. Here, taken as a screenshot

56 00:08:41.890 00:08:50.290 Aakash Tandel: I’ll you and I can sync up to make sure that this aligns with kind of the thing that Rob’s seeing in his set of things, just to make sure all those numbers align.

57 00:08:50.290 00:09:05.489 Annie Yu: Oh, yeah, these screenshot. These screenshots are not the right one, but I was able to use the table for the same one for executive dashboard, so the number should be aligned with that.

58 00:09:06.700 00:09:13.330 Aakash Tandel: Okay, okay, that sounds good. Yeah. Which one is this regards to this is the.

59 00:09:15.800 00:09:18.979 Aakash Tandel: oh, this is the order revenue. Okay, yeah, that’s fine.

60 00:09:21.960 00:09:40.029 Aakash Tandel: cool. Yeah. So overall. Annie, how how close is the dashboard that we have to the one that Rob just showed? Is it fairly close, I I know. Like not. Maybe not. Numbers wise to validate. We’ll check that. But like visualization wise. Is that fairly close?

61 00:09:41.460 00:09:49.050 Annie Yu: I think so. From what James has done, but also I think he was doing that

62 00:09:52.000 00:10:10.129 Annie Yu: using another retention on big on, not big crib on Looker studio. So that’s why I asked. I was not sure which one to follow. Are they supposed to be separate dashboards, or it’s really just the same thing. But now we are looking at another looker.

63 00:10:10.580 00:10:12.649 Josh : I don’t know what your question is, and

64 00:10:12.830 00:10:16.239 Josh : we just need this business intelligence to be.

65 00:10:16.350 00:10:19.320 Josh : Provide it like I don’t. I don’t understand.

66 00:10:20.040 00:10:28.180 Josh : like, we just need this dashboard in in tableau. Why is this like feels like this is like rocket science right now. It’s like dude. Just recreate it.

67 00:10:28.997 00:10:36.500 Annie Yu: No. I was saying that James was recreating the dash, using this looker studio, so I’m not sure what’s the difference.

68 00:10:37.130 00:10:39.249 Aakash Tandel: There shouldn’t be. It should be the same.

69 00:10:40.290 00:10:41.070 Annie Yu: Okay.

70 00:10:41.070 00:10:49.380 Aakash Tandel: Yeah, that’s that’s the goal. Yep. So the thing Rob shared is what we want in tableau, just like a basically the same thing.

71 00:10:53.220 00:10:53.820 Annie Yu: Okay.

72 00:10:54.860 00:10:58.113 Aakash Tandel: Cool all right.

73 00:10:58.740 00:11:05.579 Josh : Is there any other questions? And they’re positive, because, like this, I’m hoping is done. We’ve been talking about this for 2 weeks now.

74 00:11:05.820 00:11:08.469 Josh : and this I need. This thing done.

75 00:11:13.010 00:11:25.289 Demilade Agboola: James. I think James had left the number. I think the only thing we really wanted to add was the like. 1st time orders repeat orders. That bar. I believe that was the missing piece. Is there any other than missing.

76 00:11:35.860 00:11:42.359 Josh : I mean, the chart is just broken, so I I don’t know. I mean when someone has it ready for review. Tell me.

77 00:11:43.980 00:11:47.320 Aakash Tandel: Okay, yeah, we’ll sync up and then get that

78 00:11:47.670 00:11:53.839 Aakash Tandel: over to you. Definitely by the end of this week. But hopefully, by like tomorrow. If that’s possible.

79 00:11:55.430 00:11:55.990 Josh : Crap.

80 00:11:56.840 00:12:03.490 Josh : And then there should be a whole marketing dashboard updates that need to be provided today.

81 00:12:04.330 00:12:11.320 Aakash Tandel: Yes, let’s see where these I know. Did Mattesh give us is he’s not on this call, is he?

82 00:12:11.430 00:12:15.240 Aakash Tandel: Neither is Sahana or Robert.

83 00:12:17.680 00:12:23.199 Aakash Tandel: Yeah, I will. I’ll slack Mattesh and see what he

84 00:12:23.640 00:12:31.480 Aakash Tandel: needs now. Because I I don’t know if this is still waiting on him, or

85 00:12:31.800 00:12:33.600 Aakash Tandel: this is ready to go.

86 00:12:34.910 00:12:39.980 Aakash Tandel: He’s the last update is me writing Mattesh to review 4 days ago. But I feel like that’s not

87 00:12:40.270 00:12:41.950 Aakash Tandel: probably the most recent thing.

88 00:12:42.583 00:12:48.080 Aakash Tandel: So I will ask those people. I’ll ask Sahana, and I’ll ask Mintesh what’s left on that

89 00:12:55.600 00:12:56.270 Aakash Tandel: perfect.

90 00:13:04.276 00:13:11.720 Awaish Kumar: are we talking about getting the offline channel spent into our bigquery?

91 00:13:11.920 00:13:12.590 Aakash Tandel: Yep.

92 00:13:13.369 00:13:19.540 Awaish Kumar: If that is it like it is done. Now we have the table in our warehouse.

93 00:13:20.408 00:13:24.039 Awaish Kumar: It’s called Offline Channel Marketing Channel. Spend.

94 00:13:24.240 00:13:31.009 Awaish Kumar: and it includes the all, all the offline channels date, and these and.

95 00:13:32.540 00:13:36.849 Aakash Tandel: Okay, that makes sense. And that was going to be used in the mer calculation. Is that correct?

96 00:13:39.858 00:13:41.731 Awaish Kumar: Yes, that can be

97 00:13:42.330 00:13:52.499 Awaish Kumar: choose for that. But like we have the the data which was in the sheet. And now we have that in warehouse, but like I don’t have the further

98 00:13:53.138 00:14:00.320 Awaish Kumar: requirements like, if we have to model it, some somehow like, or it will directly be chosen. The dashboard.

99 00:14:01.660 00:14:05.930 Aakash Tandel: Okay, yeah. Let me ask Sahana where

100 00:14:06.598 00:14:19.010 Aakash Tandel: they’re doing that calculation because it could just be happening in the dashboard side of things and not like aggregate on dashboard side of things. But I will need to see what’s remaining on on that with her.

101 00:14:22.620 00:14:29.260 Aakash Tandel: Real quickly. Let’s just go through oasis at the main is that this guy no.

102 00:14:29.630 00:14:48.780 Awaish Kumar: No like so this was marketing spend by channel modeling. So we have data coming from North Beam where we have the information of channel and the spend and the other ticket, which is right now it is in progress. But it is like this one like

103 00:14:49.070 00:14:51.080 Awaish Kumar: we bring offline 2 to 4.

104 00:14:51.864 00:14:58.970 Awaish Kumar: This one is done. So yeah, we can mark it as done. And data is in the warehouse.

105 00:14:59.657 00:15:07.979 Aakash Tandel: And I know this was already in the dashboard, did this need to be was this like cleaned up or like, how did this change the data.

106 00:15:10.440 00:15:15.030 Awaish Kumar: Yeah, it was already in the dashboard. I I just I it was already in the warehouse. I just

107 00:15:15.140 00:15:20.560 Awaish Kumar: informed that we have this data coming from northwest right now.

108 00:15:21.306 00:15:23.870 Awaish Kumar: We’re like, we have a table which

109 00:15:24.709 00:15:28.809 Awaish Kumar: which we can use to see the spread by channels.

110 00:15:29.610 00:15:38.140 Aakash Tandel: Okay, so this is also gonna be using that calculation. Then, okay, that makes sense. So is this item is still in testing, or is it done.

111 00:15:39.190 00:15:44.739 Awaish Kumar: Yeah, it is done. So. But the final, my final question is like, we have data

112 00:15:45.162 00:15:52.650 Awaish Kumar: coming from North Main, we have data coming from this sheet now is, if is, there is any modeling requirement on top of it?

113 00:15:53.190 00:15:58.762 Awaish Kumar: Yeah, right now, I don’t know. But if there is like, we can just

114 00:15:59.510 00:16:00.909 Awaish Kumar: create a ticket for that.

115 00:16:01.220 00:16:26.259 Aakash Tandel: Yep, I am going to assume that we are going to use that. I’m gonna ask Sahana if that’s true. But basically, I’m fairly sure that that’s how mattesh wants to see that information all in aggregate because he’s looking for the total marketing spend on that type of thing. So for the mer calculation, he’ll need it in in aggregate, so I will ask them both in slack, and then

116 00:16:26.765 00:16:32.670 Aakash Tandel: let us know. I’ll write a ticket for you, or yeah, probably you for for getting that through the pipeline.

117 00:16:34.740 00:16:40.209 Aakash Tandel: Okay? And I know this is also this is a naughty thing. Robert was gonna use corral.

118 00:16:40.210 00:16:46.809 Awaish Kumar: Yeah, Robert, Robert was is is still, he said. He needs some time to work on work on this.

119 00:16:47.610 00:16:53.770 Aakash Tandel: Okay? Yeah. Cause I know we’re gonna use corral as opposed to the other, the Api, because the Api didn’t have anything. Okay.

120 00:16:58.210 00:17:03.200 Aakash Tandel: these anything else on on your end? Wish? I know these are.

121 00:17:03.876 00:17:05.339 Awaish Kumar: Not not right now.

122 00:17:05.930 00:17:16.986 Aakash Tandel: Okay, cool. The other thing I had put on your plate away, and a bunch of other people’s plates is to do that documentation. So we know where all the data pipeline is going. So I have this

123 00:17:17.270 00:17:41.700 Aakash Tandel: spreadsheet in the data platform documentation. If you have time, can you? I flagged 2 columns for you specifically, data source and pipeline. So if you can include that information here, it’ll help just to have this documented so that if you know some like a product owner or like me, is looking at this, I can quickly find the information. Instead of having to go into Snowflake.

124 00:17:44.012 00:17:48.219 Awaish Kumar: Okay, so what we need to fill in data pipeline like.

125 00:17:48.988 00:17:56.680 Aakash Tandel: So I was hoping to have it like mid this week just to I’m I’m hoping this is an easy task for you, and it’s not a like. It doesn’t.

126 00:17:56.680 00:18:02.279 Awaish Kumar: I I’m just. I was just saying that, like, for example, revenue data is coming from

127 00:18:02.865 00:18:07.850 Awaish Kumar: some source like a Basque like but what is the

128 00:18:08.130 00:18:14.720 Awaish Kumar: what do we need to fill in the pipeline, the table names, or the Dbt models, or like, what’s that.

129 00:18:14.920 00:18:31.280 Aakash Tandel: Yeah, yeah. So I was seeing table names like initial table names. And then, yeah, the the Dvc models are fine as well, but I was thinking like the raw, to like raw to intermediary whatever the intermediary

130 00:18:32.225 00:18:34.245 Aakash Tandel: table is to the

131 00:18:34.750 00:18:35.680 Awaish Kumar: That type of thing.

132 00:18:35.850 00:18:42.140 Aakash Tandel: And then and then this would be the final place where we’re building the report off of. So if someone needed to go into snowflake, and found like

133 00:18:42.470 00:18:45.010 Aakash Tandel: if the table is called revenue, or whatever.

134 00:18:45.010 00:18:46.019 Awaish Kumar: So big curry.

135 00:18:46.690 00:18:47.250 Aakash Tandel: Yeah.

136 00:18:47.910 00:18:50.110 Awaish Kumar: It goes. Yeah, yeah, it should be big. Kelly.

137 00:18:50.110 00:18:51.340 Aakash Tandel: Oh, yeah, okay.

138 00:18:56.100 00:18:56.840 Aakash Tandel: yep.

139 00:18:57.050 00:18:59.400 Aakash Tandel: And then yep, down the line like that.

140 00:19:00.170 00:19:04.560 Aakash Tandel: But mostly just these 2 columns, 3 columns.

141 00:19:04.560 00:19:06.459 Awaish Kumar: Okay. Okay. Thank you.

142 00:19:06.460 00:19:07.580 Aakash Tandel: Okay, thanks.

143 00:19:07.970 00:19:12.379 Aakash Tandel: Let me switch over to oh, Demo Lade

144 00:19:13.670 00:19:18.870 Aakash Tandel: Demo, a day looks like you’re waiting for feedback on this one.

145 00:19:19.390 00:19:25.500 Demilade Agboola: Yeah, so that’s done. It’s it’s emergency part. So any changes.

146 00:19:25.770 00:19:30.900 Demilade Agboola: it will spark. If we learn our test and we’ll be alerted.

147 00:19:31.200 00:19:43.790 Demilade Agboola: If there’s a sharp change in the Ltv values or values based off of Pr, so that will allow us to be able to look deeper into it, and see that if that’s what it’s supposed to do, and then merge it.

148 00:19:45.730 00:19:50.000 Aakash Tandel: Okay, that sounds good. This sub issue

149 00:19:50.170 00:19:55.500 Aakash Tandel: push all tests across all. Cordova. I’m assuming this is also done. We’re wrapped into that.

150 00:19:56.327 00:20:05.829 Demilade Agboola: No, it’s not yet done. But I will. So that is so. That is more general. It’s not just, for, like Lcv. And Calc, this is just across

151 00:20:05.970 00:20:10.080 Demilade Agboola: the different models, yeah, and ensuring that, like, the tests

152 00:20:10.870 00:20:22.029 Demilade Agboola: are set up in such a way that we know what’s happening across the different models. And if things are changing, or even just things like data freshness, if data isn’t coming in as it should, we will be ahead of the curve.

153 00:20:22.620 00:20:28.005 Aakash Tandel: Okay. Yep, that makes sense. Okay, cool. I pulled that part into progress. Then.

154 00:20:28.875 00:20:39.990 Aakash Tandel: Demo, I have the same thing. I don’t know if you and the way have, like a split on like what you have more information on like. If you, for example, if you had more information on like

155 00:20:40.540 00:20:54.470 Aakash Tandel: the agent performance dashboard. And you knew where these things came from. I have this ticket for you as well, just for documentation purposes just again. So someone who’s not an engineer can go in and kind of figure out what’s happening with the data.

156 00:20:55.400 00:21:12.329 Demilade Agboola: Yeah, I’ll I’ll think with our wish on that for some things we’ve worked on the same things like at different points in times for some, for some things, you know, he’s worked on alone like the agent performance. He’s worked on that exclusively, so we can just kind of split it amongst ourselves, and then we’ll handle the rest.

157 00:21:12.910 00:21:28.486 Aakash Tandel: Perfect. Okay, and these things are ready for development. Review new Basque order details and bring in other models. Looks like Robert created that one and this one a while back. And this one a while. Yeah, these are kind of old.

158 00:21:29.370 00:21:39.959 Aakash Tandel: I will sync up with Robert to see, like the freshness or the the necessity of these to see if they’re still ready to be picked up. But yeah, it sounds like these are moving for you.

159 00:21:41.640 00:21:42.775 Demilade Agboola: Yeah,

160 00:21:44.140 00:21:50.040 Demilade Agboola: that that’s that’s good. I also. Another thing is, I don’t know if Rob has heard anything or any feedback

161 00:21:50.340 00:21:53.999 Demilade Agboola: above the orders like the missing orders, cause that’s still.

162 00:21:54.000 00:21:54.790 rob: Oh, yeah.

163 00:21:54.790 00:21:55.880 Demilade Agboola: Kind of just a.

164 00:21:56.862 00:22:14.170 rob: Oh, I don’t. This doesn’t explain all of those payment intents with missing orders, but in the audit of a full bask export they have actually increased the number of orders that they’re dropping. That we’re never getting web hook from.

165 00:22:14.290 00:22:39.859 rob: It’s still pretty low. It’s point 2%. But it used to be like point 0 2%. And so I think there are 42 orders out of 22,000 that we just never got a web hook, for I wanted to mention that to Robert to see if he thought, you know, we’re tracking them down over it. There’s just not that much they could do other than giving us an Api, because if they’re

166 00:22:40.440 00:22:52.728 rob: if their web hooks not firing, you know, it’s not firing, for whatever reason I’ll make Zach aware of it, but it doesn’t explain those missing payment intents, so I can’t find any orders.

167 00:22:53.570 00:22:55.230 rob: That would account for those.

168 00:22:56.650 00:22:59.790 Demilade Agboola: Yeah, so

169 00:23:00.100 00:23:07.140 Demilade Agboola: yeah, so we still need to get kind of get to the bottom of that. And just kind of figure out like where those missing orders exist where they leave.

170 00:23:07.671 00:23:13.860 Demilade Agboola: It would really be helpful if Zack could give us, you know, an orders list like just a list of those orders.

171 00:23:14.200 00:23:18.110 Demilade Agboola: That’s only with those transactions it will be very helpful.

172 00:23:21.870 00:23:22.810 Demilade Agboola: Okay, I don’t know.

173 00:23:22.810 00:23:28.499 Demilade Agboola: I don’t. I don’t know if it’s something Josh could push that would like. I said it would be very helpful if we could. Just, you know, get that list.

174 00:23:28.500 00:23:31.409 Josh : Exactly. What do you need? He already gave that. I thought.

175 00:23:32.910 00:23:35.470 Demilade Agboola: Oh, no! He just mentioned, I believe he just mentioned.

176 00:23:35.470 00:23:35.940 Josh : No, no!

177 00:23:36.390 00:23:38.769 Josh : That one. You sent one to Robert.

178 00:23:44.000 00:23:47.230 Josh : You sent like a whole list in a side channel to Robert.

179 00:23:48.060 00:23:50.889 Demilade Agboola: Oh, I guess I I didn’t see that.

180 00:23:51.340 00:23:55.629 Aakash Tandel: Emily, are you in this? Let me see if you’re you’re in the

181 00:23:57.320 00:24:06.400 Aakash Tandel: this thread. I’ll send you the thread. And Robert responded yesterday, I guess. Yeah. So I’m not sure what.

182 00:24:08.010 00:24:08.850 Demilade Agboola: Gotcha.

183 00:24:17.410 00:24:19.970 Aakash Tandel: So we still, yeah. So we don’t know why those

184 00:24:20.570 00:24:24.421 Aakash Tandel: orders are being dropped. But both, thanks. Okay,

185 00:24:26.450 00:24:29.600 rob: Well, we don’t even know for sure if they’re real orders right?

186 00:24:31.080 00:24:38.090 rob: They could be the replacement order theory he was talking about. But we do need to confirm that.

187 00:24:41.950 00:24:46.609 Aakash Tandel: demolati, can you review that ticket? Or that’s the one.

188 00:24:47.220 00:24:51.409 Demilade Agboola: Yeah. So I thought, all he says is at his earliest convenience. He will send that.

189 00:24:52.520 00:25:02.230 Demilade Agboola: And then Robert replies, we’d appreciate your support as we resolve. This did not tend to make sweep and accusations and all that, but like there isn’t any like Csv. Or like list of

190 00:25:02.620 00:25:06.870 Demilade Agboola: quarters that we can look at.

191 00:25:12.070 00:25:13.619 Demilade Agboola: or am I missing something?

192 00:25:19.450 00:25:21.979 Aakash Tandel: I don’t know. I’ll have to review this thread again.

193 00:25:21.980 00:25:22.650 Demilade Agboola: Yeah.

194 00:25:24.140 00:25:25.010 Aakash Tandel: I don’t know if something.

195 00:25:25.010 00:25:31.590 Josh : There’s like a Zack have. Have Robert send it to you. Robert should have gotten all the orders taken

196 00:25:32.620 00:25:36.199 Josh : from Zack last week when you guys 1st asked for it?

197 00:25:41.040 00:25:45.210 Demilade Agboola: He? He didn’t. He didn’t send. All he just said is that we see this

198 00:25:47.692 00:25:54.390 Demilade Agboola: and to which we responded, Hey, can we get a list of those orders.

199 00:25:57.850 00:26:03.130 Aakash Tandel: Okay, yeah, we’ll sync up with Robert and try to figure out what’s happening. If if he got that list, or if

200 00:26:03.570 00:26:08.789 Aakash Tandel: yeah, where Zack might have put that list. Okay, yeah.

201 00:26:08.790 00:26:09.450 Demilade Agboola: There!

202 00:26:09.450 00:26:13.589 Aakash Tandel: Alright Demo a can you sync up with Robert to

203 00:26:14.240 00:26:22.619 Aakash Tandel: find the try to get the at least do start the kind of Qa. Process, and and where those are being dropped.

204 00:26:23.730 00:26:24.950 Demilade Agboola: Stuff, sounds, good.

205 00:26:25.090 00:26:27.250 Aakash Tandel: Okay, cool.

206 00:26:28.560 00:26:29.170 Aakash Tandel: Okay.

207 00:26:30.300 00:26:33.320 Aakash Tandel: Let me host on the call.

208 00:26:33.820 00:26:36.938 Aakash Tandel: Annie. I think we already talked about your stuff. But

209 00:26:40.950 00:26:57.189 Aakash Tandel: data, retention dashboards, the main thing. Okay, yeah. And these are all kind of in progress. Okay, yeah. So the main people I need to sync up with our Sahana because she has those marketing service dashboard, and also the stuff that Rebecca wanted. So I will sync up with her.

210 00:26:58.800 00:27:01.250 Aakash Tandel: To get those filled out.

211 00:27:03.300 00:27:07.450 Aakash Tandel: Is there anyone else? Yeah, I think that’s it. And then let me check on Roberts.

212 00:27:11.000 00:27:11.650 Aakash Tandel: Okay.

213 00:27:15.400 00:27:18.129 Aakash Tandel: this, I think, okay, so this is the one

214 00:27:25.420 00:27:28.320 Aakash Tandel: is this one that’s no. This is something different.

215 00:27:29.160 00:27:34.500 Aakash Tandel: Okay, alright, does anyone have anything else they’re working on? And they’re blocked on.

216 00:27:41.250 00:27:42.020 Aakash Tandel: Okay.

217 00:27:43.500 00:27:51.151 Aakash Tandel: cool. Annie, you and I can sync up to get the retention check on that dashboard to see if that’s ready to go.

218 00:27:51.620 00:27:57.050 Aakash Tandel: I can put time on your calendar to do that, and then we can get that out the door as soon as ready.

219 00:27:57.760 00:27:59.839 Annie Yu: Yeah, that’s super helpful. Thanks.

220 00:27:59.840 00:28:01.180 Aakash Tandel: Okay, awesome.

221 00:28:01.400 00:28:05.050 Aakash Tandel: Alright. Y’all have a good rest of your day. Talk to you soon.

222 00:28:05.050 00:28:05.687 rob: See you guys.