Meeting Title: [Eden] Daily Standup Date: 2025-09-24 Meeting participants: Fireflies.ai Notetaker Tigran, Henry Zhao, Awaish Kumar, Amber Lin, Demilade Agboola, Robert Tseng


WEBVTT

1 00:01:57.320 00:01:58.360 Amber Lin: Hello.

2 00:01:59.190 00:02:00.910 Amber Lin: Okay…

3 00:02:20.350 00:02:25.580 Amber Lin: Alright, let’s see if there’s any view requests.

4 00:02:26.710 00:02:33.650 Amber Lin: Oh, gosh. Okay, let’s get started here.

5 00:02:33.870 00:02:35.890 Amber Lin: Orish, I see that there’s some…

6 00:02:36.000 00:02:40.369 Amber Lin: New tickets added to your plate.

7 00:02:40.790 00:02:41.280 Awaish Kumar: Period.

8 00:02:42.800 00:02:46.440 Amber Lin: What would be the due dates when you complete these?

9 00:02:47.750 00:02:50.550 Awaish Kumar: 932 would be done today.

10 00:02:50.830 00:02:54.390 Awaish Kumar: 933… Oh.

11 00:02:54.540 00:02:58.589 Awaish Kumar: Maybe, maybe… So, is Henry here?

12 00:02:58.950 00:03:01.430 Henry Zhao: Yeah, what is the Spike CIO to PQ?

13 00:03:01.710 00:03:03.809 Awaish Kumar: So, I wanted to know, like.

14 00:03:04.410 00:03:07.739 Awaish Kumar: I, like, this integration with CIU and Victory?

15 00:03:09.830 00:03:12.150 Awaish Kumar: Yeah, I want to spike first, like.

16 00:03:12.440 00:03:24.600 Awaish Kumar: how it would be done, and what will be the risks, or whatever. Like, all the questions from Robert, right? Okay. And we need to answer that first. So, for that, like, I wanted to answer, like.

17 00:03:24.760 00:03:27.800 Awaish Kumar: I wanted to understand, is it a high priority, like…

18 00:03:27.920 00:03:34.269 Awaish Kumar: Should I work on that urgently, or a week… if it is done by end of week, that’s okay.

19 00:03:34.560 00:03:36.240 Henry Zhao: Yeah, end of week is fine. Thank you.

20 00:03:36.570 00:03:39.769 Awaish Kumar: Okay, we can then work on it tomorrow, 9.30.

21 00:03:40.260 00:03:41.470 Henry Zhao: Okay, sounds good.

22 00:03:46.530 00:03:47.190 Amber Lin: Okay.

23 00:03:47.310 00:03:52.280 Amber Lin: And then… For the catalyst spend…

24 00:03:53.770 00:03:54.980 Awaish Kumar: Is this from…

25 00:03:54.980 00:03:55.330 Amber Lin: cutter.

26 00:03:56.790 00:04:07.249 Awaish Kumar: So now, like, few weeks back, we implemented a script, which was untested, because there was no data in Catalyst’s platform.

27 00:04:07.250 00:04:09.760 Amber Lin: So now I see the data is coming in.

28 00:04:09.860 00:04:16.130 Awaish Kumar: So, now I want to rework on that script and see if it is working, and…

29 00:04:16.230 00:04:24.189 Awaish Kumar: Basically, the end goal is to bring in catalyst data, so I will deploy that script, test that script, and verify the data.

30 00:04:24.960 00:04:25.770 Amber Lin: I see.

31 00:04:26.170 00:04:29.679 Amber Lin: Is this related to this ask?

32 00:04:34.370 00:04:40.720 Awaish Kumar: I think that’s something… like, there are two parts of it. Number one is that

33 00:04:41.050 00:04:44.100 Awaish Kumar: He wants it to come in our…

34 00:04:44.210 00:04:52.189 Awaish Kumar: reports, that’s one thing. Second thing is that he wants that correct attribution is done, so…

35 00:04:53.400 00:05:00.130 Awaish Kumar: like, spend is correctly attributed to correct treatment type, and that attribution, I think, is…

36 00:05:00.300 00:05:06.459 Awaish Kumar: is happening in Catalyst Platform itself, that maybe Henry or Zoran can look into it.

37 00:05:08.510 00:05:13.730 Amber Lin: Alright, who would… sorry, would Zora be taking this, or would you be taking this?

38 00:05:14.030 00:05:15.609 Henry Zhao: Can be the two of us.

39 00:05:15.830 00:05:17.180 Henry Zhao: We can work together on it.

40 00:05:17.180 00:05:17.940 Amber Lin: Okay.

41 00:05:18.410 00:05:25.700 Amber Lin: Spent attributed to correct… One time…

42 00:05:26.810 00:05:28.169 Henry Zhao: Yeah, you can assign it to me for now.

43 00:05:31.870 00:05:33.480 Awaish Kumar: Ring, ring, wrong.

44 00:05:34.150 00:05:36.679 Amber Lin: How many points would this be? How many hours?

45 00:05:42.620 00:05:44.040 Henry Zhao: For now, let’s put 2.

46 00:05:45.200 00:05:47.830 Henry Zhao: I can always adjust if it’s different.

47 00:05:49.830 00:05:50.510 Amber Lin: Okay.

48 00:05:55.580 00:06:05.150 Amber Lin: Alright, and then on the bottom… on the bottom here, it says 10 days to reconcile true orders against canceled abandons.

49 00:06:05.890 00:06:11.559 Amber Lin: We’ll need a process for marketing data to verify to marketing to pay out.

50 00:06:12.560 00:06:15.080 Amber Lin: Does that mean we should…

51 00:06:16.000 00:06:19.749 Amber Lin: Establish a process and have them review.

52 00:06:21.220 00:06:22.380 Henry Zhao: Yeah, probably.

53 00:06:22.990 00:06:23.670 Amber Lin: Okay.

54 00:06:28.620 00:06:29.690 Amber Lin: Alright.

55 00:06:33.240 00:06:36.640 Amber Lin: Who would be establishing that process?

56 00:06:40.410 00:06:41.160 Amber Lin: Oh.

57 00:06:42.880 00:06:46.000 Demilade Agboola: What about, like, isn’t it just basically having all…

58 00:06:46.210 00:06:52.819 Demilade Agboola: Catalyst orders in one place, and then being able to see which ones became true orders, and which ones were cast.

59 00:06:52.940 00:06:53.840 Demilade Agboola: I don’t.

60 00:06:55.070 00:06:58.989 Demilade Agboola: But it can always sit about the last 10 days at any point in time.

61 00:07:02.410 00:07:08.780 Demilade Agboola: I think that’s what it basically sounds like, because if we’re thinking about a process, I think a dashboard could handle this.

62 00:07:09.430 00:07:11.260 Demilade Agboola: So they could handle it themselves.

63 00:07:14.450 00:07:21.750 Amber Lin: I guess my question is, does it come to us to verify, and then goes back to them? Do we have to be in the loop?

64 00:07:23.110 00:07:33.250 Demilade Agboola: Yeah, I mean, we need to create a system, that’s why I say we should create a dashboard. If we can create a dashboard, we don’t have to have a constant back and forth. There’s a dashboard they can go to.

65 00:07:33.430 00:07:42.970 Demilade Agboola: verify the true orders, and then they can use that, that, like, dashboard to verify how much to pay out to Catalyst.

66 00:07:45.480 00:07:46.450 Awaish Kumar: Okay.

67 00:07:46.680 00:07:50.980 Awaish Kumar: So, does… does… he wants to know that…

68 00:07:51.470 00:07:56.209 Awaish Kumar: out of all the orders which Catless shows, how many…

69 00:07:57.180 00:08:03.340 Awaish Kumar: like, were actually placed, right? How many of them actually completed?

70 00:08:03.660 00:08:05.830 Awaish Kumar: Is that the question from Qatar?

71 00:08:06.020 00:08:07.680 Amber Lin: I…

72 00:08:08.220 00:08:08.750 Demilade Agboola: Yes.

73 00:08:08.750 00:08:15.570 Amber Lin: So, but do you guys think it’s only about Catalyst? Because we have similar requests about other sources as well.

74 00:08:17.410 00:08:18.850 Demilade Agboola: Yes, it’s only about competitions.

75 00:08:19.840 00:08:23.619 Demilade Agboola: Well, this one is specifically Catalyst, I don’t know about all the other requests.

76 00:08:25.110 00:08:30.679 Amber Lin: I just remember, I think we were also asked to reconcile some other spends here and there.

77 00:08:32.120 00:08:33.240 Awaish Kumar: Okay, thank you.

78 00:08:33.720 00:08:40.040 Awaish Kumar: I think what he… So, he may be asking for catalysts, but we should establish a process

79 00:08:40.270 00:08:46.210 Awaish Kumar: And we should be able to give them a dashboard, where they can verify the…

80 00:08:46.880 00:08:48.670 Awaish Kumar: The actual orders, like…

81 00:08:48.960 00:09:01.349 Awaish Kumar: like, for example, Catalyst says 1,000 orders came from Catalyst platform, and then in our orders, we can verify, like, in September, we got

82 00:09:01.800 00:09:07.970 Awaish Kumar: 1,000 orders from Catless. Out of those, like…

83 00:09:08.370 00:09:18.479 Awaish Kumar: For example, 900 actually converted, 100 were canceled, or things like that, and it’s similar for all other sources as well.

84 00:09:24.010 00:09:24.920 Awaish Kumar: Yeah.

85 00:09:24.920 00:09:30.389 Amber Lin: Okay, so who would do the initial spike, or does this still need clarification?

86 00:09:32.120 00:09:35.779 Demilade Agboola: So I know Oasis bringing in the Catalyst data.

87 00:09:36.100 00:09:40.180 Demilade Agboola: Once data is in, what we need to do next is modeling.

88 00:09:41.060 00:09:42.550 Awaish Kumar: Yeah, that could be fun, right?

89 00:09:42.550 00:09:43.470 Demilade Agboola: Thanks to the dashboard.

90 00:09:44.450 00:09:47.919 Awaish Kumar: So, I will be working in bringing in spend data, right?

91 00:09:48.940 00:09:51.529 Amber Lin: This is more an attribution.

92 00:09:51.990 00:09:59.550 Awaish Kumar: That is… here we are talking about, the data which is, for example.

93 00:10:00.020 00:10:07.350 Awaish Kumar: like, the orders data come… orders coming from Basque, and we have this UTM Feel very, very…

94 00:10:07.460 00:10:11.030 Awaish Kumar: Where we actually get to know, like, where this order came from.

95 00:10:12.150 00:10:16.130 Demilade Agboola: Yes, that’s what I’m saying. So we’re bringing in data about, like, the spend.

96 00:10:16.300 00:10:18.050 Demilade Agboola: But we need to model.

97 00:10:18.380 00:10:24.300 Demilade Agboola: For both the attribution and the spend, so we can see what the orders are.

98 00:10:24.970 00:10:28.270 Demilade Agboola: As well as what the abandoned and canceled ones were.

99 00:10:28.740 00:10:31.129 Demilade Agboola: And we can have that dashboard available.

100 00:10:32.140 00:10:35.140 Demilade Agboola: So they can see what the spend is and the revenue is.

101 00:10:36.250 00:10:43.910 Awaish Kumar: Yeah, yeah, but, like… So, there is one thing about spend data, like, so I’m working on that task.

102 00:10:44.000 00:10:59.830 Awaish Kumar: I will be getting in the spend data. Second task is that the orders coming in, we need to work on that part as well, where we have correct UTMs, right? So if an order came from Catalyst, then it should have UTM source as catalyst.

103 00:11:00.000 00:11:07.899 Awaish Kumar: And that’s, like, where this is a ticket for Henry and Zoran to work on.

104 00:11:08.190 00:11:16.689 Awaish Kumar: And once we have these both, we have expand, and then we have these orders where we have the correct UTM source.

105 00:11:16.810 00:11:23.400 Awaish Kumar: we basically can get the revenue from Catalyst, spend from Catalyst, Cag, can’t get everything.

106 00:11:23.400 00:11:32.289 Henry Zhao: I’m not sure that there will be UTMs, but I can check with Cutter later today. From what I heard from Kevin, Catalyst installs, like, a pixel, and they get the data that way.

107 00:11:34.490 00:11:37.580 Henry Zhao: So, we just gotta make sure that it is by UTMs. If it is by UTMs.

108 00:11:37.580 00:11:42.619 Awaish Kumar: Yeah, but… Like, that’s… that… that’s how it goes to Catalyst.

109 00:11:42.820 00:11:48.990 Awaish Kumar: But, like, that’s what we want to verify, like, Catalyst is already saying, I, I, like.

110 00:11:49.170 00:11:59.940 Awaish Kumar: Ketris is already saying, using my platform, you, earned, like, $30,000, right? If I just get that data from Catless itself, then…

111 00:12:00.040 00:12:10.149 Awaish Kumar: there’s no point, right? I will be getting all the data which Catwis is already providing, right? So we want to verify that with our BASC orders, so that

112 00:12:10.320 00:12:16.479 Awaish Kumar: Are these orders actually from Catalyst, or maybe if some of the orders are missed?

113 00:12:17.000 00:12:22.620 Awaish Kumar: matched by Catalyst, maybe they are from some other platform, from Google Ads.

114 00:12:22.890 00:12:23.990 Awaish Kumar: So, yeah.

115 00:12:24.550 00:12:31.980 Henry Zhao: Honestly, this seems more like an issue with the business deal we make with Catalyst, right? Like, we should be paying based on the order completed transaction, not

116 00:12:32.120 00:12:35.270 Henry Zhao: Based on someone getting to tryEden.com, so…

117 00:12:35.940 00:12:38.050 Awaish Kumar: Yeah, yeah, absolutely. That’s the point, like…

118 00:12:38.050 00:12:38.740 Henry Zhao: Sounds like a bit.

119 00:12:38.740 00:12:46.760 Awaish Kumar: For example, 1,000 orders were completed. Catalyst claims that all of these orders came from its platform.

120 00:12:47.000 00:12:51.529 Awaish Kumar: But what is the… what is the way for us to verify that?

121 00:12:51.610 00:12:54.410 Henry Zhao: Like, we can see that, okay.

122 00:12:54.410 00:13:04.009 Awaish Kumar: all of these thousand orders are completed, and we can say, okay, go ahead. One thing’s that. Other thing is that, maybe in our orders data, we have this

123 00:13:04.340 00:13:14.439 Awaish Kumar: Luteum’s field, where we can actually verify, out of these thousand, all of them came from Catalyst, or maybe out of maybe 100 came from Google Ads or some other platform. So…

124 00:13:14.960 00:13:18.030 Awaish Kumar: Then, what is the way to verify?

125 00:13:18.180 00:13:21.270 Awaish Kumar: Like, what the catalyst is claiming is correct.

126 00:13:22.300 00:13:25.339 Amber Lin: Yeah, question, who is going to spike on this?

127 00:13:25.480 00:13:33.100 Amber Lin: Or to understand what modeling needs we need to do, or what the dashboarding needs are gonna look like.

128 00:13:38.430 00:13:40.029 Demilade Agboola: You can assign that to me.

129 00:13:40.220 00:13:40.900 Amber Lin: Okay.

130 00:13:44.090 00:13:46.920 Amber Lin: And then, how long would the spike take?

131 00:13:49.720 00:13:52.049 Demilade Agboola: Probably, like, 2 plants. Yeah, like, when I need it…

132 00:13:52.050 00:13:59.400 Awaish Kumar: I think I want Henry’s help here, because we are talking about UTMs, so…

133 00:13:59.650 00:14:13.100 Awaish Kumar: like, will we be getting… in the orders data, we have UTM field, so I want to know, like, will we be getting UTM field catalyst or not? Like, like, what is…

134 00:14:14.370 00:14:22.690 Awaish Kumar: like, if Ron will be… will be helping us implement that, or how that is going to be there, so…

135 00:14:23.720 00:14:29.250 Henry Zhao: Yeah, so I will ask that at the… the Eden’s Marketing Sync right after this meeting.

136 00:14:29.250 00:14:29.890 Amber Lin: Okay.

137 00:14:29.890 00:14:30.740 Awaish Kumar: Yes.

138 00:14:30.740 00:14:32.760 Amber Lin: Sounds good.

139 00:14:32.990 00:14:37.419 Awaish Kumar: Yeah, after that, we can work on modeling, and it can be assigned to me or them.

140 00:14:37.420 00:14:38.010 Amber Lin: Okay.

141 00:14:38.230 00:14:44.719 Amber Lin: Sounds good. You said the 933 you were going to do… what day?

142 00:14:46.400 00:14:47.610 Awaish Kumar: Yeah, tomorrow.

143 00:14:47.610 00:14:48.600 Amber Lin: Okay, tomorrow.

144 00:14:50.590 00:14:53.779 Amber Lin: Another looking… looking at these tasks…

145 00:14:57.340 00:15:00.830 Amber Lin: What did you do yesterday, and what do you plan to do today?

146 00:15:02.200 00:15:04.809 Demilade Agboola: So yes, I finished up the paid…

147 00:15:05.120 00:15:07.369 Demilade Agboola: Bus is free. So 8.05 is done.

148 00:15:10.230 00:15:10.920 Amber Lin: Okay.

149 00:15:11.340 00:15:12.220 Amber Lin: Great.

150 00:15:12.220 00:15:19.050 Demilade Agboola: Mmm, I did reach out to Adam, he’s not responded.

151 00:15:19.620 00:15:25.299 Demilade Agboola: So… I let him know… What… what we need to do.

152 00:15:25.790 00:15:30.720 Demilade Agboola: And if there are any discounts he wants to exclude, he’s… he’s not responded.

153 00:15:31.050 00:15:35.070 Demilade Agboola: And then, so today, I’m just gonna finish up 9-18.

154 00:15:36.400 00:15:37.110 Demilade Agboola: Okay.

155 00:15:37.400 00:15:40.130 Demilade Agboola: 745, basically.

156 00:15:40.130 00:15:40.890 Amber Lin: Okay.

157 00:15:41.130 00:15:48.710 Amber Lin: Sounds good. Then, Henry… oh, wow, you did so much stuff yesterday. I was thinking we can move some…

158 00:15:48.970 00:15:53.110 Amber Lin: thing. Maybe we need to move some things… Old…

159 00:15:53.110 00:15:57.599 Henry Zhao: I don’t think so. I think only 753 and 755.

160 00:15:57.600 00:15:58.210 Awaish Kumar: Nope.

161 00:15:58.210 00:16:02.419 Henry Zhao: Might get moved to next week, but it’s… it’s together with 752.

162 00:16:02.570 00:16:03.490 Amber Lin: I see.

163 00:16:03.490 00:16:04.130 Henry Zhao: You know what I mean?

164 00:16:04.510 00:16:15.440 Amber Lin: We have, like, 22 points left, I think it might be manageable, but these will not get done if we don’t move anything out.

165 00:16:16.730 00:16:19.049 Henry Zhao: Those are paused, so…

166 00:16:19.050 00:16:22.640 Amber Lin: The 3 is Oasis helping me with that, 933.

167 00:16:23.040 00:16:26.440 Henry Zhao: Those 3 points are time I’ve already spent, basically.

168 00:16:27.240 00:16:30.159 Henry Zhao: Like, last week, and then actuals dashboard.

169 00:16:30.390 00:16:34.759 Henry Zhao: There’s a lot of stuff missing, but I’ve already spent 2 points on that, just have one point to actually implement.

170 00:16:34.760 00:16:35.659 Awaish Kumar: And I will…

171 00:16:36.100 00:16:40.450 Henry Zhao: There’s some stuff I’m gonna actually need Awash or Demolati’s help, just to confirm some things.

172 00:16:41.020 00:16:46.329 Henry Zhao: And then move BQ queries to dbt. Awash already approved that PR. I’m just gonna want Bobby to give…

173 00:16:46.330 00:16:57.070 Awaish Kumar: I just want to have one thing, like, I approve your… the PR for standardized product names, where you have mainly MECO, like, that we can merge

174 00:16:57.180 00:17:03.110 Awaish Kumar: But the second thing, PR, I don’t see if we are using that macro in there yet.

175 00:17:03.110 00:17:03.649 Henry Zhao: Not yet.

176 00:17:03.650 00:17:07.060 Awaish Kumar: I can just use that, and then we can… I can approve that.

177 00:17:07.069 00:17:10.029 Henry Zhao: Okay, I’m just waiting for Bobby to respond. Remember yesterday? We said.

178 00:17:10.030 00:17:10.640 Awaish Kumar: Good.

179 00:17:10.640 00:17:19.259 Henry Zhao: I’ll be on the consistency issue, but even if he doesn’t respond, I think we are going to merge it, because the change is very easy to reverse if there are

180 00:17:19.960 00:17:22.969 Henry Zhao: inconsistency effects, which I don’t think there will be, like I said.

181 00:17:23.710 00:17:29.180 Awaish Kumar: Yeah, yeah, so I approve your macro, like, I just want you to lose that macro in the other PR.

182 00:17:29.180 00:17:33.359 Henry Zhao: Oh, no, I will. I’m just giving Bobby a chance to respond, in case he has any concerns.

183 00:17:33.360 00:17:35.189 Awaish Kumar: Okay, so no worries.

184 00:17:36.190 00:17:39.160 Amber Lin: Question, you spiked on…

185 00:17:39.280 00:17:46.580 Amber Lin: Brad and Katie’s dashboard, and also Christina’s dashboard, is there modeling tasks we need to do?

186 00:17:46.580 00:17:46.960 Henry Zhao: No.

187 00:17:46.960 00:17:47.430 Amber Lin: Pull that out.

188 00:17:47.430 00:17:58.239 Henry Zhao: But I’m gonna meet with Katie today just to confirm some things, but I don’t think there’s any modeling that’s needed, because I think all of the data we need is already in the order summary table. Demolati, correct me if I’m wrong.

189 00:18:01.550 00:18:02.959 Demilade Agboola: What decides that?

190 00:18:03.480 00:18:06.080 Henry Zhao: So we had a meeting yesterday, remember, with Brad and Katie,

191 00:18:06.220 00:18:12.470 Henry Zhao: So you were there, so it seems like all the data they asked for, we already have in the order summary table.

192 00:18:13.830 00:18:21.440 Demilade Agboola: Yeah, we already have most of the data that they need. It’s just, presenting it in the format that they desire.

193 00:18:21.440 00:18:23.850 Henry Zhao: Exactly. So I don’t think there’s any modeling that’s needed.

194 00:18:24.730 00:18:25.590 Amber Lin: Okay.

195 00:18:26.690 00:18:30.029 Amber Lin: Sounds good. Then I’ll say…

196 00:18:37.010 00:18:37.420 Henry Zhao: Yeah, I didn’.

197 00:18:37.420 00:18:43.299 Amber Lin: Yeah, how long do you think the actual dashboard would take?

198 00:18:44.030 00:18:46.430 Henry Zhao: I already started on some of the changes that are really easy.

199 00:18:47.870 00:18:49.030 Henry Zhao: Probably 2 points.

200 00:18:49.290 00:18:49.950 Amber Lin: Okay.

201 00:19:10.550 00:19:11.400 Amber Lin: Okay.

202 00:19:16.700 00:19:20.900 Henry Zhao: I love that Granola put Qatar’s name as Qatar, the country.

203 00:19:22.570 00:19:23.900 Amber Lin: That’s so funny.

204 00:19:24.330 00:19:27.419 Amber Lin: So we’re meeting with her today…

205 00:19:31.060 00:19:38.649 Amber Lin: 10… Okay, and then we also spiked on Christina’s dashboard. Is there a ticket that came out of that?

206 00:19:38.950 00:19:43.760 Amber Lin: No, so none of the traffic is coming in, so… Oh, okay.

207 00:19:44.250 00:19:49.789 Henry Zhao: Yeah, so basically, we need her to set up UTMs, or maybe work with Zoran to figure out how we can track these.

208 00:19:49.910 00:19:53.050 Henry Zhao: She’s also, like, I don’t want to say bad things, but, like.

209 00:19:53.210 00:19:55.970 Henry Zhao: I just don’t think her stuff was implemented correctly, so…

210 00:19:55.970 00:19:56.970 Amber Lin: Okay.

211 00:19:57.030 00:19:58.999 Henry Zhao: I’ll double check, none of her data’s coming in.

212 00:19:59.160 00:20:05.750 Amber Lin: Yeah, okay, let me just add a… Placeholder… Here…

213 00:20:08.470 00:20:10.090 Henry Zhao: She messaged me, I just haven’t read it yet.

214 00:20:10.340 00:20:11.269 Henry Zhao: I don’t know what she said.

215 00:20:12.500 00:20:14.430 Amber Lin: Implement ETMs.

216 00:20:16.030 00:20:20.219 Henry Zhao: Yeah, this might be as Ron, this might be me. You can assign it to me for now, if it is Zaron, I will just assign it to him.

217 00:20:20.220 00:20:24.290 Amber Lin: Okay, and we’re doing that next week, or are we doing that this week?

218 00:20:25.010 00:20:26.689 Amber Lin: Okay, sounds good.

219 00:20:26.690 00:20:31.910 Henry Zhao: So the effort is very manageable. I might even just not put that many hours on Friday, because I’ve…

220 00:20:32.340 00:20:33.750 Henry Zhao: Had a lot this week already.

221 00:20:35.790 00:20:38.239 Amber Lin: Yeah, in that case, I… I…

222 00:20:38.470 00:20:39.559 Henry Zhao: I think we should be good.

223 00:20:40.290 00:20:45.689 Amber Lin: Okay, what’s the due dates we should put on?

224 00:20:45.900 00:20:48.360 Amber Lin: Dates. There’s missing due dates right now.

225 00:20:49.210 00:20:50.690 Henry Zhao: I think I’ll put for Friday.

226 00:20:54.810 00:20:55.760 Amber Lin: Alright.

227 00:20:56.410 00:21:06.440 Amber Lin: I would also like to clean up some of Soran’s tasks, is there estimates for these?

228 00:21:08.390 00:21:12.240 Henry Zhao: Do you have an update on 909? I think you said you were gonna talk to Matt Schwartz about the login?

229 00:21:13.170 00:21:13.820 Amber Lin: Oh.

230 00:21:13.840 00:21:14.600 Henry Zhao: Yeah.

231 00:21:14.760 00:21:19.170 Amber Lin: Matt, I think they already got the login, let me show you.

232 00:21:19.510 00:21:22.650 Amber Lin: So they got the login here.

233 00:21:23.320 00:21:34.070 Amber Lin: And then he enabled… NordBeam integration with the new account, so I… Think… I think that’s done.

234 00:21:36.960 00:21:39.240 Amber Lin: Okay, so I’ll put that in client review.

235 00:21:40.770 00:21:43.480 Amber Lin: How many points do you think that was?

236 00:21:47.750 00:21:49.019 Henry Zhao: I have no idea, sorry.

237 00:21:49.020 00:21:49.600 Amber Lin: Okay.

238 00:21:50.190 00:21:53.410 Amber Lin: I’ll put… I’ll… I’ll leave it there, and we’ll confirm.

239 00:21:53.750 00:21:54.759 Henry Zhao: Do you think?

240 00:21:55.290 00:21:56.000 Henry Zhao: I don’t…

241 00:21:56.290 00:22:00.939 Amber Lin: Yeah, and then… what’s the North Beam Pixel?

242 00:22:03.080 00:22:04.799 Henry Zhao: No, I didn’t… I didn’t add that one.

243 00:22:05.500 00:22:10.569 Amber Lin: Oh, I see, I remember. This is also for Robert’s documentation.

244 00:22:11.160 00:22:11.910 Henry Zhao: Oh, no.

245 00:22:11.910 00:22:18.990 Amber Lin: Do we want him to do… now we need him to do this. Document wins… so far.

246 00:22:19.100 00:22:21.860 Amber Lin: In 14 pixel.

247 00:22:27.070 00:22:29.429 Robert Tseng: Yeah, I know that. I joined pretty late.

248 00:22:29.430 00:22:30.090 Amber Lin: Hi.

249 00:22:31.190 00:22:45.220 Robert Tseng: I think I just wanted to say… I mean, I think, Amber, you’re on the call as well, but we have, the bi-weekly check-in with DLT at 1PM Eastern today, so I just want to make a couple… I want to just add some stuff to the… have some talking points.

250 00:22:45.510 00:22:52.010 Robert Tseng: That are less like, this is what we did, but more like, you know, two to four weeks from now, like, where are we headed? So it’s more…

251 00:22:52.740 00:22:55.300 Robert Tseng: Yeah, like, it’s… anyway, so,

252 00:22:56.570 00:23:13.159 Robert Tseng: yeah, if there’s anything from this meeting that’s helpful to inform that, I think specifically, like, Zoran’s work, I’d like to talk about where it’s headed in two or four weeks, and then if we have anything else that’s more, like, more future-oriented and less of a recap, I think that’d be helpful for me.

253 00:23:18.770 00:23:22.469 Amber Lin: Henry, what do you think? I know we have a…

254 00:23:22.660 00:23:31.189 Amber Lin: plan for Zoran’s work, and I know you said it’s delayed for a week, so what do you think is the next 2 to 3 weeks? What will that look like?

255 00:23:31.190 00:23:34.490 Henry Zhao: Yeah, I’ll be working on the attribution stitching, so we should be…

256 00:23:36.250 00:23:38.459 Henry Zhao: In a better place with terms of attribution.

257 00:23:38.730 00:23:45.780 Henry Zhao: Maybe not perfect yet, but we should at least be finalizing, you know, testing and making sure we have an attribution plan in place.

258 00:23:45.960 00:23:46.750 Amber Lin: Huh.

259 00:23:46.750 00:23:47.250 Henry Zhao: Yeah.

260 00:23:48.110 00:23:51.289 Amber Lin: Anything else, that Zora will be looking on?

261 00:23:55.510 00:24:07.749 Henry Zhao: I think it’s all related to the tagging and tracking, right? So just making sure that our whole attribution ecosystem is in a healthy spot, where we know what the first touch is, where we know where the last touch is, we know how much money is going to Catalysts.

262 00:24:08.750 00:24:12.630 Henry Zhao: We know… What to rely on in terms of reporting.

263 00:24:13.170 00:24:15.510 Amber Lin: And we don’t send…

264 00:24:15.510 00:24:19.829 Henry Zhao: data basically everywhere, right? Like, we use segment, or we use direct

265 00:24:20.120 00:24:25.529 Henry Zhao: integrations, whether it’s Webhook or Customer I.O, to just say, like, this is our source of truth.

266 00:24:25.860 00:24:27.150 Amber Lin: Okay.

267 00:24:27.380 00:24:31.249 Henry Zhao: I would say it’s, like, much cleaner and more reliable data.

268 00:24:31.540 00:24:32.659 Henry Zhao: for attribution.

269 00:24:33.460 00:24:34.020 Henry Zhao: Is our goal.

270 00:24:34.020 00:24:35.109 Amber Lin: Got it. Okay.

271 00:24:36.090 00:24:39.239 Amber Lin: Is… Robert, is that good, or do you need more?

272 00:24:39.790 00:24:53.850 Robert Tseng: Yeah, that works, so for the attribution stitching, that’s enough notes. I think the other thing I want to talk about, they want, like, they want some point of view on how we’re bringing the mixed panel strategy, so… Henry, we’ve kind of, like, messaged back and forth there, but I’m going to put together some… a slide on that.

273 00:24:54.010 00:24:59.410 Robert Tseng: So, attribution stitching, mixed panel, then… Is there anything on the…

274 00:25:00.210 00:25:07.320 Robert Tseng: data engineering, analyst engineering modeling side. I guess the Remo stuff I can kind of talk about quickly as well with them.

275 00:25:07.830 00:25:11.580 Robert Tseng: But I don’t know how much I have to say, since the TikTok hasn’t really happened.

276 00:25:11.870 00:25:16.330 Robert Tseng: I think just, like, 3 or 4 points is enough, so we have,

277 00:25:16.460 00:25:20.630 Robert Tseng: Is there anything else? Those are the 3 main things that I have on my…

278 00:25:23.440 00:25:30.779 Amber Lin: Let’s see… Oh, we’re also helping the supply chain side.

279 00:25:30.780 00:25:37.579 Robert Tseng: Yeah, maybe give me a sense of the supply chain work that’s coming, like, what, what is, like, what’s the, what’s… what do we see coming?

280 00:25:37.830 00:25:38.500 Amber Lin: So…

281 00:25:38.500 00:25:40.000 Robert Tseng: This is top of mind for Danny.

282 00:25:40.160 00:25:57.090 Amber Lin: Yeah, so we’re already helping them with… we already met with them and scoped out the few helps that they need on the dashboarding side, so we’re improving the existing dashboard that we made for Rebecca. That’s quite urgent for them, and then we are…

283 00:25:57.680 00:25:58.420 Amber Lin: Oh.

284 00:25:58.540 00:26:06.420 Amber Lin: So… and then we’re going to help them make an order flow dashboard, and then move on to forecasting in the next few weeks.

285 00:26:06.860 00:26:07.500 Robert Tseng: Okay.

286 00:26:11.610 00:26:19.479 Robert Tseng: this order flow dashboard, like, what is… isn’t this what we had before? We had SLA dash? Like, how’s this… how’s this different?

287 00:26:23.390 00:26:27.689 Demilade Agboola: So… This is for Brad and Katie.

288 00:26:28.010 00:26:36.939 Demilade Agboola: they want us to present the numbers slightly differently, so this was the call we had that you helped on. Basically, they want the orders that are out of SLA,

289 00:26:37.340 00:26:47.030 Demilade Agboola: But as a percentage of the total orders, over the last 30 days as well, they also want the… just a chart showing the auto SLE by pharmacy.

290 00:26:47.210 00:26:52.340 Demilade Agboola: Then they want a table of out-of-SLE orders that they can easily export, so that they can action

291 00:26:52.980 00:26:54.490 Demilade Agboola: Reconciliation on them.

292 00:26:58.320 00:27:01.880 Henry Zhao: You can call it the SLA dashboard, that’s… yeah, that’s what I’m calling it.

293 00:27:03.260 00:27:07.739 Amber Lin: Right, so that’s for the first one. So the order flow is the same thing.

294 00:27:08.070 00:27:16.209 Amber Lin: I know that he mentioned there was something that he wanted later next week, and there was something that he needed ASAP.

295 00:27:19.690 00:27:20.939 Henry Zhao: I thought it was just one.

296 00:27:21.890 00:27:29.590 Henry Zhao: And then forecasting is… Kind of together with the, the Eden 733, or 71?

297 00:27:29.720 00:27:31.029 Henry Zhao: One of those, yeah.

298 00:27:31.270 00:27:38.009 Henry Zhao: Yeah, so Robert, basically, I’m working on the forecasting dashes, which is… so if you have anything you want to share with the stuff that you’ve built since July.

299 00:27:39.290 00:27:39.979 Henry Zhao: If I could see it.

300 00:27:39.980 00:27:55.480 Robert Tseng: I haven’t built anything since July. But Brad asked a couple questions, so I asked him a few more questions. Basically, I think they just want to do what I… I guess they’re going to take what I did, and they want to just do it for more pharmacies, but which, we saw this coming. I would just, you know, kept pushing it back, because no one was really asking for it.

301 00:27:55.990 00:27:56.590 Henry Zhao: Okay.

302 00:27:57.770 00:27:58.340 Robert Tseng: Yeah.

303 00:27:58.530 00:28:04.460 Robert Tseng: Okay, cool. Do you need me at the next sync? Because if not, I want to probably just take 30 minutes to just knock out these slides.

304 00:28:05.760 00:28:08.209 Amber Lin: Oh, maybe not, but however you make the call.

305 00:28:08.510 00:28:24.730 Amber Lin: Okay, I, team, we have 2 minutes. Can we push out some tickets? Because we’re at 86 right now, that is a lot higher than our goal. I want us to stay within our team’s time allocations.

306 00:28:26.880 00:28:28.230 Henry Zhao: What is our goal, Aiden?

307 00:28:28.640 00:28:36.469 Amber Lin: Our goal is 60… Or… lower, but I know Zoran’s working on some stuff, so probably 60.

308 00:28:37.990 00:28:43.800 Amber Lin: So, thinking we can move these two out, or…

309 00:28:43.960 00:28:44.840 Henry Zhao: I’ll move those throughout.

310 00:28:45.020 00:28:45.690 Amber Lin: Okay.

311 00:28:49.670 00:28:51.050 Amber Lin: Upcoming.

312 00:28:51.050 00:28:54.429 Robert Tseng: Noron comes to stand-ups, like, what, once a week or something, or just kind of.

313 00:28:54.430 00:29:02.189 Amber Lin: No, he haven’t invited him to stand. It’s just because this time, he’s usually not online at this time.

314 00:29:02.310 00:29:10.600 Amber Lin: Yeah, yeah. It’s just harder. Anything on Zoran’s plate, we should move out? I feel like we should give him a priority, though.

315 00:29:10.770 00:29:12.799 Henry Zhao: Improve UTM tracking in North Beam, maybe?

316 00:29:14.890 00:29:16.399 Henry Zhao: That’s, like, the overarching task.

317 00:29:17.300 00:29:21.710 Amber Lin: I see. We said it was gonna get done this week, though.

318 00:29:22.420 00:29:25.030 Henry Zhao: I think this one he said is gonna be delayed one week, because there’s new assets.

319 00:29:25.030 00:29:26.099 Amber Lin: Oh, I see.

320 00:29:31.580 00:29:33.050 Amber Lin: One week…

321 00:29:33.300 00:29:40.179 Henry Zhao: And, like, again, like I said, although it says 78, I think the reality’s probably closer to 60, just because, like, my points I already did last week.

322 00:29:41.020 00:29:43.110 Robert Tseng: Yeah, there’s some carryover I see here, so…

323 00:29:43.940 00:29:47.220 Henry Zhao: I think this is stuff that we’re gonna have to get used to now that we’re doing one-week sprints.

324 00:29:47.800 00:29:51.850 Henry Zhao: Because not everything gets done within a week, so there’s going to be some carryover, some that…

325 00:29:52.020 00:29:55.100 Henry Zhao: is done this week, but gets bled over into next week, you know what I mean?

326 00:29:55.360 00:29:56.690 Robert Tseng: Okay.

327 00:30:00.990 00:30:06.620 Robert Tseng: I mean, I feel like at our 80% completion rate, if we hit 80, we’re fine, because that’ll, you know.

328 00:30:07.370 00:30:19.089 Robert Tseng: But it’s like, if it’s… if we’re… if it says 80, it’s more like we’re doing 65, whatever, and then there’s probably some stuff that goes over. So, I wouldn’t… I wouldn’t be too hard on, like, trying to drive that number down to 60.

329 00:30:19.530 00:30:20.190 Amber Lin: Okay.

330 00:30:21.700 00:30:25.230 Henry Zhao: Yeah, and Robert, I hope it’s okay that I put in more hours this week, just because last week I put in less.

331 00:30:25.670 00:30:26.400 Robert Tseng: Yeah, of course.

332 00:30:26.400 00:30:27.500 Henry Zhao: Things like that, yeah.

333 00:30:28.010 00:30:28.440 Amber Lin: Yeah.

334 00:30:28.440 00:30:29.339 Henry Zhao: Put up on a lot of fun.

335 00:30:30.200 00:30:35.490 Amber Lin: Then this one is in… needs SQL response…

336 00:30:35.720 00:30:42.999 Amber Lin: Barbara, would you be doing the actual dashboard this week, or should I move it to Harry and push this to next week?

337 00:30:43.420 00:30:46.470 Robert Tseng: Yeah, let’s move it. I don’t… I haven’t heard anything from Joanna, sorry.

338 00:30:46.470 00:30:50.289 Amber Lin: Yeah, I have… I also have not heard anything from him.

339 00:30:50.490 00:30:53.430 Henry Zhao: I’m already running some stuff with the actual dashboard, so this probably makes sense.

340 00:30:53.980 00:30:54.620 Amber Lin: Okay.

341 00:30:54.620 00:30:55.310 Robert Tseng: Okay.

342 00:30:55.310 00:30:56.040 Amber Lin: Great.

343 00:30:56.370 00:31:01.390 Henry Zhao: So then if you want to push my other one, the… 7…

344 00:31:01.900 00:31:02.570 Amber Lin: This one?

345 00:31:02.570 00:31:06.570 Henry Zhao: Yeah, 762. Since that’s waiting on stakeholder response, yeah, that…

346 00:31:06.570 00:31:07.250 Amber Lin: Okay.

347 00:31:07.450 00:31:08.240 Amber Lin: Awesome.

348 00:31:08.870 00:31:13.299 Amber Lin: This should be unblocked once… Tomorrow finishes this.

349 00:31:13.490 00:31:20.709 Amber Lin: Today, oh, actually, this one. This one will be unblocked. This…

350 00:31:21.350 00:31:23.489 Amber Lin: Oh, this should be unblocked now.

351 00:31:24.250 00:31:25.100 Henry Zhao: Okay.

352 00:31:25.100 00:31:25.740 Amber Lin: Okay.

353 00:31:25.940 00:31:28.509 Amber Lin: Alright, thanks everyone, let’s hop to the other meeting.

354 00:31:28.510 00:31:33.880 Henry Zhao: Wait, did Awash and Damari, did you guys meet about the… way to…

355 00:31:34.200 00:31:38.749 Henry Zhao: Break down product sales summary by transaction, like, whether we’re doing it by columns or by rows.

356 00:31:39.920 00:31:44.590 Awaish Kumar: Yeah, so far, we are using the same

357 00:31:45.660 00:31:48.109 Awaish Kumar: Using the same schema as we have right now.

358 00:31:48.110 00:31:48.939 Henry Zhao: We’re not gonna do it by…

359 00:31:48.940 00:31:53.060 Awaish Kumar: But we will… but yeah, we are… we are going to meet, right? That’s…

360 00:31:53.540 00:31:58.150 Awaish Kumar: That may be delayed, right? It’s not going to be in this way.

361 00:31:59.240 00:32:01.990 Henry Zhao: Okay, yeah, I just wanted to know for this column coming up next.

362 00:32:02.680 00:32:05.499 Henry Zhao: Okay, but it’s a work in progress. Okay.

363 00:32:05.680 00:32:06.550 Amber Lin: Gotcha.

364 00:32:06.650 00:32:07.679 Amber Lin: Thanks, everyone.

365 00:32:10.100 00:32:10.900 Amber Lin: Right?