Meeting Title: Eden Retention Dashboard Finish Date: 2025-04-15 Meeting participants: Aakash Tandel, Annie Yu
WEBVTT
1 00:00:35.240 ⇒ 00:00:36.100 Aakash Tandel: Hey!
2 00:00:36.320 ⇒ 00:00:37.420 Annie Yu: Hello! Akash!
3 00:00:37.820 ⇒ 00:00:39.080 Aakash Tandel: How’s it going.
4 00:00:39.430 ⇒ 00:00:51.200 Annie Yu: Good. Good. I I’m still trying to I’m gonna need to record that one to you and Kyle. But also I feel like I have to rethink through it every time before I can even explain.
5 00:00:51.510 ⇒ 00:00:55.278 Aakash Tandel: Okay, no worries. Yeah. That sounds good.
6 00:00:55.970 ⇒ 00:01:07.189 Aakash Tandel: I can. Here, let me share my screen, and we can. Do you want to pull up the tablet dashboard on your end just to make sure we’re looking at it.
7 00:01:07.200 ⇒ 00:01:21.000 Annie Yu: Sure, and I think my question was cause in the ticket. There was one also Lucas studio retention dashboard, and I’m pretty sure James built his views based on that. So this is a different
8 00:01:21.260 ⇒ 00:01:27.190 Annie Yu: dashboard. It looks like. But I so I think I was confused.
9 00:01:28.200 ⇒ 00:01:33.049 Annie Yu: I’m like, why are there 2 versions, so are we trying to build a separate one? Or
10 00:01:33.230 ⇒ 00:01:36.180 Annie Yu: was that 1st lucre studio was
11 00:01:37.400 ⇒ 00:01:40.689 Annie Yu: was like not the one we should be looking at.
12 00:01:40.910 ⇒ 00:01:42.649 Aakash Tandel: Can you slack me the link to that tableau.
13 00:01:42.650 ⇒ 00:01:43.290 Annie Yu: Yeah.
14 00:01:43.290 ⇒ 00:01:44.559 Aakash Tandel: We’ll open that, too.
15 00:01:44.560 ⇒ 00:01:45.170 Annie Yu: Okay.
16 00:01:45.170 ⇒ 00:01:45.730 Aakash Tandel: Oh, okay.
17 00:01:45.730 ⇒ 00:01:48.360 Annie Yu: And I found this throughout the tickets.
18 00:01:49.400 ⇒ 00:01:55.610 Annie Yu: the one assigned to me, but also the ones assigned to James before.
19 00:02:00.590 ⇒ 00:02:07.130 Aakash Tandel: Give me one sec. I’m gonna login to
20 00:02:27.010 ⇒ 00:02:28.250 Aakash Tandel: blue.
21 00:02:52.190 ⇒ 00:02:52.740 Aakash Tandel: Okay?
22 00:03:10.060 ⇒ 00:03:14.226 Annie Yu: I think I’m using one that’s called Eden.
23 00:03:15.060 ⇒ 00:03:17.279 Annie Yu: Eden, is that bird forge.
24 00:03:19.500 ⇒ 00:03:23.680 Aakash Tandel: So many things trying to.
25 00:03:24.920 ⇒ 00:03:25.480 Aakash Tandel: That’s fine.
26 00:03:25.778 ⇒ 00:03:26.970 Annie Yu: Try to find it.
27 00:03:38.080 ⇒ 00:03:38.790 Aakash Tandel: Okay.
28 00:03:39.850 ⇒ 00:03:40.680 Aakash Tandel: Alright.
29 00:03:41.630 ⇒ 00:03:46.240 Aakash Tandel: Okay. So these are definitely, yes. Are these the same?
30 00:03:46.920 ⇒ 00:03:49.160 Aakash Tandel: Think, let me pull these okay
31 00:03:49.590 ⇒ 00:03:52.390 Aakash Tandel: and pull this to one side
32 00:03:53.150 ⇒ 00:03:57.519 Aakash Tandel: and then pull this to the side over here.
33 00:03:58.170 ⇒ 00:03:59.320 Aakash Tandel: And
34 00:04:00.970 ⇒ 00:04:09.359 Aakash Tandel: okay. So this is 2024. I’m just trying to see if even the same data. So we’re at 10,027 orders.
35 00:04:09.640 ⇒ 00:04:14.510 Aakash Tandel: 10,027 orders. Okay, so this is the same data.
36 00:04:17.660 ⇒ 00:04:23.539 Aakash Tandel: and 5, 3, 3, 5, 3, 8, 8, 3.
37 00:04:24.230 ⇒ 00:04:31.710 Aakash Tandel: Okay, so that’s the same table. This is, is this the same table? Let me see, I’m wondering if they just sent us.
38 00:04:32.100 ⇒ 00:04:35.009 Aakash Tandel: or they just rearrange this. Okay? So this is
39 00:04:35.650 ⇒ 00:04:40.019 Aakash Tandel: 24 is a 3,000,071,
40 00:04:41.200 ⇒ 00:04:47.189 Aakash Tandel: 3,000,007, one. Yep. Okay, cool alright, and then revenue.
41 00:04:49.360 ⇒ 00:04:50.080 Aakash Tandel: Okay.
42 00:04:54.090 ⇒ 00:04:59.240 Aakash Tandel: okay, cool. Alright, so the top ones are the same, which is good, that’s helpful.
43 00:05:01.380 ⇒ 00:05:04.279 Aakash Tandel: And then what is this? And get cohort engagement.
44 00:05:06.660 ⇒ 00:05:07.140 Annie Yu: Oh!
45 00:05:07.140 ⇒ 00:05:08.230 Aakash Tandel: These.
46 00:05:09.890 ⇒ 00:05:11.700 Aakash Tandel: And is this the same?
47 00:05:12.750 ⇒ 00:05:20.190 Aakash Tandel: You’re looking at 80 April size? Okay? So this looks different
48 00:05:20.640 ⇒ 00:05:24.620 Aakash Tandel: orders after first.st But that’s the same.
49 00:05:25.440 ⇒ 00:05:28.529 Aakash Tandel: One orders after first.st
50 00:05:29.220 ⇒ 00:05:33.770 Aakash Tandel: Okay, months after. First, st
51 00:05:34.270 ⇒ 00:05:50.200 Aakash Tandel: let me just see, I’m just looking at the most recent days. So 1, 9, 9, 3, okay, so that’s actually, and 3, 4, 7. Okay, so these do kind of line up. Okay, that’s good month after first.st And this is month after 1st 2, 3. Okay.
52 00:05:50.920 ⇒ 00:05:54.190 Aakash Tandel: okay? So that lines up, I think.
53 00:05:56.940 ⇒ 00:06:05.430 Aakash Tandel: And then this is the month after 1st 3, 4, 6. Okay.
54 00:06:06.400 ⇒ 00:06:14.685 Aakash Tandel: so this thing they shared is the same as this guy, which is good except it doesn’t have this. Ltv. One.
55 00:06:15.080 ⇒ 00:06:15.750 Annie Yu: Yeah.
56 00:06:15.750 ⇒ 00:06:17.160 Aakash Tandel: So that’s fine.
57 00:06:17.605 ⇒ 00:06:25.849 Aakash Tandel: Oh, I wasn’t sharing my whole screen. So you didn’t see? Sorry. That was my bad, basically was just. I was just comparing numbers in these things.
58 00:06:26.588 ⇒ 00:06:36.700 Aakash Tandel: It looks like all the things here are the same as here. The thing that Rob showed today that only missing component is the L 2.
59 00:06:36.700 ⇒ 00:06:38.560 Annie Yu: Right. The Ltv.
60 00:06:38.720 ⇒ 00:06:42.959 Aakash Tandel: Yeah, so do you want to? Okay, actually,
61 00:06:43.750 ⇒ 00:06:47.970 Aakash Tandel: let me find the, is it in the recents? Probably.
62 00:06:49.100 ⇒ 00:06:52.619 Annie Yu: There should be one that’s published.
63 00:06:56.640 ⇒ 00:06:58.570 Aakash Tandel: Is it called? Just the retention dashboard.
64 00:06:58.780 ⇒ 00:07:00.200 Annie Yu: Yeah, this one.
65 00:07:00.510 ⇒ 00:07:01.080 Aakash Tandel: Okay.
66 00:07:03.030 ⇒ 00:07:03.820 Aakash Tandel: Okay.
67 00:07:04.000 ⇒ 00:07:08.750 Annie Yu: And I think these are pretty messy and I.
68 00:07:09.280 ⇒ 00:07:12.980 Annie Yu: So what I did yesterday with the bar charts, I
69 00:07:14.456 ⇒ 00:07:16.439 Annie Yu: let me look through it.
70 00:07:17.340 ⇒ 00:07:23.260 Annie Yu: Yeah, I think this one, we it’s better to look by like tab, by tab worksheet, by worksheet.
71 00:07:24.340 ⇒ 00:07:29.798 Aakash Tandel: Oops to do this and share this whole thing.
72 00:07:32.080 ⇒ 00:07:35.189 Aakash Tandel: and by worksheet you mean, like the like, the individual.
73 00:07:35.680 ⇒ 00:07:39.519 Annie Yu: Yeah, I think everything was published.
74 00:07:40.510 ⇒ 00:07:41.110 Aakash Tandel: Okay.
75 00:07:43.510 ⇒ 00:07:49.159 Annie Yu: So, and for the bar charts
76 00:07:50.980 ⇒ 00:08:05.709 Annie Yu: from my understanding standing of yesterday’s session, we just use the same table that we use for executive dashboard for the bar charts. So the 1st align with the executive dashboard, but not the not this one.
77 00:08:06.320 ⇒ 00:08:10.920 Aakash Tandel: Not this one but the executive dashboard. Okay, let me.
78 00:08:11.250 ⇒ 00:08:13.970 Aakash Tandel: I just wanna see what the numbers like generally look like.
79 00:08:17.400 ⇒ 00:08:22.719 Aakash Tandel: Repeat 1st revenue order. Okay, yeah, these look very
80 00:08:22.920 ⇒ 00:08:29.270 Aakash Tandel: okay. Oh, no. That 1.3 and 1.8. Actually. Now, let’s look very close.
81 00:08:32.049 ⇒ 00:08:33.920 Aakash Tandel: Okay, these are just rounded.
82 00:08:34.346 ⇒ 00:08:39.990 Aakash Tandel: I just wanted to get like a general sense of like, make sure these are close ish, and this is what is.
83 00:08:40.220 ⇒ 00:08:46.290 Aakash Tandel: This is close to what? 1.7 and 2.4
84 00:08:46.560 ⇒ 00:08:49.980 Aakash Tandel: cool. Okay, so that looks good.
85 00:08:52.390 ⇒ 00:08:56.850 Aakash Tandel: and this is the order version. So this is gonna be close to.
86 00:08:57.080 ⇒ 00:08:58.509 Aakash Tandel: Actually, I can go after this one.
87 00:08:59.030 ⇒ 00:09:12.720 Aakash Tandel: 24. So 4.1 and 5.9. Yep, okay.
88 00:09:12.900 ⇒ 00:09:19.939 Aakash Tandel: 5.1 and 7.6. Okay, cool. These look right, too. Okay, sweet. So that works
89 00:09:20.920 ⇒ 00:09:22.790 Aakash Tandel: orders. After first, st
90 00:09:29.520 ⇒ 00:09:33.299 Aakash Tandel: this is just an inverted version of this.
91 00:09:33.750 ⇒ 00:09:40.539 Aakash Tandel: I’m seeing slightly different quarters after 1st quarter.
92 00:09:41.060 ⇒ 00:09:45.405 Aakash Tandel: I’m seeing slightly different numbers here, and
93 00:09:47.240 ⇒ 00:09:53.080 Aakash Tandel: I see here that they also have the cohort sizes. Is there a way to pull in cohort size here.
94 00:09:56.283 ⇒ 00:09:59.850 Annie Yu: I’m not 100% sure.
95 00:10:09.150 ⇒ 00:10:10.580 Aakash Tandel: Few of these numbers.
96 00:10:17.350 ⇒ 00:10:18.550 Aakash Tandel: Orders.
97 00:10:19.760 ⇒ 00:10:20.540 Aakash Tandel: 5.
98 00:10:22.610 ⇒ 00:10:27.970 Aakash Tandel: Yeah, this is where the Ltv by cohort
99 00:10:29.690 ⇒ 00:10:33.250 Aakash Tandel: orders. Numbers don’t match this thing.
100 00:10:33.580 ⇒ 00:10:36.630 Aakash Tandel: Okay, so
101 00:10:40.840 ⇒ 00:10:48.240 Aakash Tandel: these these look good. This looks good. We should. Is there a way to expand this? So it’s like visually better.
102 00:10:49.680 ⇒ 00:10:52.649 Annie Yu: Oh, yeah, yeah, sure. Cause I, yeah.
103 00:10:52.880 ⇒ 00:11:11.349 Annie Yu: I think everything was published, because, to my knowledge, usually we publish the dashboard only without other tabs. But for this one i i saw that everything, every worksheet was published, and then the 1st one was all compiled together, and I’m not sure if that’s something I should touch or not.
104 00:11:12.124 ⇒ 00:11:15.490 Annie Yu: But I can do. I can definitely expand that.
105 00:11:16.250 ⇒ 00:11:41.689 Aakash Tandel: Okay, yeah, let’s expand these. Those look, those tape, those charts look exactly the same. And I think those numbers line up with exactly what we’re looking at. So that’s that’s good and also, I think you can totally modify anything here. I don’t think just because it’s published doesn’t mean anyone’s working off this data because I, James, is the only one that worked on it. And I know that this wasn’t really widely shared with the the
106 00:11:42.356 ⇒ 00:11:46.363 Aakash Tandel: Eden team. So that’s fine.
107 00:11:49.000 ⇒ 00:11:56.410 Aakash Tandel: And the other thing. Okay? Oh, wait. So
108 00:11:56.960 ⇒ 00:11:58.919 Aakash Tandel: 5.3 5.3.
109 00:11:59.130 ⇒ 00:11:59.930 Aakash Tandel: Okay,
110 00:12:03.407 ⇒ 00:12:12.160 Aakash Tandel: let me. Let me just make a note of the things we need to do. So expand bar charts for visual impact.
111 00:12:13.512 ⇒ 00:12:17.370 Aakash Tandel: The other thing is, is it possible to
112 00:12:17.905 ⇒ 00:12:23.769 Aakash Tandel: hover over and get the non rounded number on returning revenue. You see that like 5.3.
113 00:12:25.180 ⇒ 00:12:25.875 Annie Yu: Yeah,
114 00:12:26.990 ⇒ 00:12:37.319 Annie Yu: I will. I’ll look into that. I think usually we can with, like the normal bar charts. But for this one I’m using just measure values. So
115 00:12:37.430 ⇒ 00:12:41.670 Annie Yu: I my guess is just.
116 00:12:41.850 ⇒ 00:12:56.300 Annie Yu: but that I could be wrong. But my guess is they, the format has to be universal. So if we want to see the All. The the labels on the bar chart would also be the phone numbers. But I could be wrong. So I.
117 00:12:56.300 ⇒ 00:13:01.390 Aakash Tandel: Oh, I see what you’re saying. So like this. The this number matches the tooltip number.
118 00:13:01.390 ⇒ 00:13:09.269 Annie Yu: Yeah, I. Usually we can separate that. But the way I’m like configurating this one, because how the data was structured.
119 00:13:09.270 ⇒ 00:13:12.569 Annie Yu: Yeah, okay, you will have to stay the same.
120 00:13:12.570 ⇒ 00:13:27.125 Aakash Tandel: Okay, that’s fine. If if it has to get more, get unrounded and tooltip, if not, yes.
121 00:13:27.920 ⇒ 00:13:34.120 Aakash Tandel: if not, let’s get 2 decimal places.
122 00:13:35.630 ⇒ 00:13:41.570 Annie Yu: Okay. So even on the bar charts, right? So if they have to be the same across, okay.
123 00:13:52.760 ⇒ 00:13:56.600 Aakash Tandel: Okay, so that that fixes those 2
124 00:13:57.630 ⇒ 00:14:03.470 Aakash Tandel: like, see if we can get cohort size on the 3.
125 00:14:04.340 ⇒ 00:14:05.920 Aakash Tandel: These 3 charts
126 00:14:09.840 ⇒ 00:14:16.290 Aakash Tandel: billboard size number 3.
127 00:14:16.930 ⇒ 00:14:18.449 Aakash Tandel: I’m just calling them tables
128 00:14:21.810 ⇒ 00:14:28.120 Aakash Tandel: And then one thing I feel like they’re gonna bring up is
129 00:14:31.190 ⇒ 00:14:39.900 Aakash Tandel: actually is it? Can we invert this table. So it looks identical to this and the
130 00:14:40.180 ⇒ 00:14:43.430 Aakash Tandel: I guess you order differently by the month. Oh, wait.
131 00:14:45.511 ⇒ 00:14:50.149 Aakash Tandel: Okay, cool. Can we set that as a default?
132 00:14:50.960 ⇒ 00:14:52.030 Annie Yu: Yeah, okay.
133 00:14:52.350 ⇒ 00:15:09.560 Aakash Tandel: Cool, alright default sort on 3 tables to oldest month top and current month.
134 00:15:09.840 ⇒ 00:15:10.780 Aakash Tandel: Awesome.
135 00:15:11.130 ⇒ 00:15:23.785 Aakash Tandel: Okay. I’m literally trying to get this like, like as identical as the other one, so that they like, don’t complain about this. It’s silly little things that they might be like, why is this different. It’s like, okay, dude. Just relax.
136 00:15:26.300 ⇒ 00:15:34.130 Aakash Tandel: okay? And then, I’m seeing here. The numbers are slightly off.
137 00:15:35.310 ⇒ 00:15:41.020 Annie Yu: I think I noticed in the past months. There are.
138 00:15:42.070 ⇒ 00:15:58.179 Annie Yu: Some of them are aligned, but then, in the more more recent months, they aren’t. But I also am not sure if they are supposed to align or not, because I think my knowledge we’re using a different table like the one the team had
139 00:15:58.300 ⇒ 00:15:59.359 Annie Yu: to build.
140 00:15:59.640 ⇒ 00:16:02.090 Aakash Tandel: Or though that is a different one than this right.
141 00:16:02.180 ⇒ 00:16:06.090 Annie Yu: I’m that that I don’t have the precise answer.
142 00:16:06.330 ⇒ 00:16:11.311 Aakash Tandel: Yeah, I don’t either. But I think that makes sense.
143 00:16:13.250 ⇒ 00:16:16.050 Aakash Tandel: So this one is, yeah, this one’s off
144 00:16:16.310 ⇒ 00:16:18.610 Aakash Tandel: trying to see if there’s any that are like identical.
145 00:16:20.850 ⇒ 00:16:25.329 Aakash Tandel: August, in April 2024.
146 00:16:25.570 ⇒ 00:16:28.260 Aakash Tandel: Yeah. So they’re all close.
147 00:16:28.430 ⇒ 00:16:38.550 Aakash Tandel: They’re just different by a little bit. Okay, let me try the other ones month months
148 00:16:39.180 ⇒ 00:16:44.160 Aakash Tandel: after 1st order. That’s this one. Right? Yeah, okay.
149 00:16:45.500 ⇒ 00:16:51.309 Annie Yu: Oh, and I I think we aren’t supposed to have that 0 because 0 would
150 00:16:51.610 ⇒ 00:16:58.519 Annie Yu: most likely be inaccurate, which I don’t think they have in their original charts either.
151 00:16:59.740 ⇒ 00:17:00.850 Aakash Tandel: Yes, you’re right.
152 00:17:02.190 ⇒ 00:17:02.890 Annie Yu: Okay.
153 00:17:03.270 ⇒ 00:17:12.980 Aakash Tandel: So let me add the note, so remove, move 0 month, or these are days right.
154 00:17:13.976 ⇒ 00:17:15.229 Annie Yu: Months after.
155 00:17:15.559 ⇒ 00:17:16.139 Annie Yu: Then? Yeah.
156 00:17:16.140 ⇒ 00:17:20.770 Aakash Tandel: Months, yeah, 0 months 0 month, and
157 00:17:21.150 ⇒ 00:17:28.030 Aakash Tandel: start at one month after for all 3 tables.
158 00:17:28.290 ⇒ 00:17:28.980 Annie Yu: Yeah.
159 00:17:30.100 ⇒ 00:17:36.950 Aakash Tandel: That makes sense. And then let me just get a numbers basis of so
160 00:17:38.630 ⇒ 00:17:43.740 Aakash Tandel: oh, by churn, I’m looking at the wrong chart. Okay, me scroll here.
161 00:17:44.450 ⇒ 00:17:50.669 Aakash Tandel: So 75. And that’s 73. This is 32, that’s 31,
162 00:17:51.160 ⇒ 00:18:02.710 Aakash Tandel: 73. Okay, yeah. So these are again similar, but slightly off. So that’s a question. And then let me look at the last one.
163 00:18:04.480 ⇒ 00:18:09.159 Aakash Tandel: this 1. 0, wait! I should have been going after this one, because this is the one they currently asked us.
164 00:18:10.070 ⇒ 00:18:10.409 Annie Yu: Hmm.
165 00:18:10.750 ⇒ 00:18:16.710 Aakash Tandel: Let me let me just do that real quick. Alright, months after it’s this one, right? Months after 1st
166 00:18:16.930 ⇒ 00:18:31.240 Aakash Tandel: 2426, 67, 2763, 52, 20, okay, so yeah, that yep, okay.
167 00:18:31.240 ⇒ 00:18:33.399 Annie Yu: It’s slightly different, but.
168 00:18:33.980 ⇒ 00:18:38.450 Aakash Tandel: Months after 70.
169 00:18:38.840 ⇒ 00:18:43.730 Aakash Tandel: 3. Okay, yes, also slightly different.
170 00:18:43.870 ⇒ 00:19:00.760 Aakash Tandel: And oops this one, and that’s 1, 34, 31, 1. 0, 1.
171 00:19:01.857 ⇒ 00:19:05.699 Aakash Tandel: Okay, alright. So those are also slightly different. Alright.
172 00:19:06.110 ⇒ 00:19:11.949 Aakash Tandel: that is good to know. So basically, once we expand this.
173 00:19:13.550 ⇒ 00:19:16.119 Annie Yu: Can you actually refresh it?
174 00:19:16.290 ⇒ 00:19:16.870 Aakash Tandel: Yep.
175 00:19:16.870 ⇒ 00:19:20.920 Annie Yu: Profile. Yeah, just did. Or if that went through or not.
176 00:19:22.060 ⇒ 00:19:22.700 Aakash Tandel: Cool.
177 00:19:23.170 ⇒ 00:19:26.960 Annie Yu: Or we could expand it even more if we want.
178 00:19:27.330 ⇒ 00:19:33.170 Aakash Tandel: I think that’s good. Yeah. So let me, just I’ll just cross this item off.
179 00:19:36.020 ⇒ 00:19:39.019 Aakash Tandel: Okay, so that looks does look good to me now.
180 00:19:44.740 ⇒ 00:19:49.790 Annie Yu: And one thing to note here. So you see that marketing product name is
181 00:19:49.940 ⇒ 00:19:55.330 Annie Yu: that’s the filter for the bar charts, because we are using different tables, and
182 00:19:55.870 ⇒ 00:20:02.509 Annie Yu: this one product filter would be the one for those retention.
183 00:20:02.670 ⇒ 00:20:11.250 Annie Yu: these ones. I I can make them align a bit more. But that’s just some nuances, because they have different product names.
184 00:20:11.250 ⇒ 00:20:17.549 Aakash Tandel: That makes sense. Yeah, can. Yeah, if you can visually, is there a way to like box them together?
185 00:20:17.860 ⇒ 00:20:27.880 Annie Yu: I? I actually have like a you see that empty, that’s actually an empty box. So I can expand that so that product filter will align at retention, charts.
186 00:20:27.880 ⇒ 00:20:28.739 Aakash Tandel: Okay. Cool.
187 00:20:28.740 ⇒ 00:20:30.760 Annie Yu: If that’s good enough.
188 00:20:30.760 ⇒ 00:20:38.819 Aakash Tandel: Yeah, I think, yeah, as long as we’re it’s like, clear that, hey? This goes to these 2. And then this can be pulled down to where, like these start.
189 00:20:39.210 ⇒ 00:20:39.820 Annie Yu: Okay.
190 00:20:41.095 ⇒ 00:20:47.229 Aakash Tandel: Cool. And then, okay. And these are whatever they are, they’re different. But
191 00:20:47.950 ⇒ 00:20:55.199 Aakash Tandel: yeah, we’ll get rid of the 0 there. I think we’re already getting rid of the 0 on this one, so just get rid of it. On the next 2.
192 00:20:55.440 ⇒ 00:20:55.950 Annie Yu: Okay.
193 00:20:56.328 ⇒ 00:20:58.360 Aakash Tandel: And I wrote that down right?
194 00:20:59.230 ⇒ 00:21:06.889 Aakash Tandel: Cool. Okay, add cohort size. Do you know, if cohort size is in the data.
195 00:21:06.890 ⇒ 00:21:14.240 Annie Yu: Yes, it is. I’m just not sure if we can put it next to that month column.
196 00:21:15.450 ⇒ 00:21:16.190 Aakash Tandel: Okay.
197 00:21:16.190 ⇒ 00:21:17.749 Annie Yu: Like right next to it.
198 00:21:17.750 ⇒ 00:21:18.660 Aakash Tandel: Yeah.
199 00:21:20.260 ⇒ 00:21:23.210 Aakash Tandel: Okay.
200 00:21:26.680 ⇒ 00:21:34.639 Aakash Tandel: yeah. I guess I’ll let you play around with that afterwards. Let me look at the what they have here, cause. That’s not in their current one they want. But
201 00:21:36.620 ⇒ 00:21:38.449 Aakash Tandel: I wish this would.
202 00:21:40.750 ⇒ 00:21:48.230 Aakash Tandel: Okay. So this is customer orders orders per customer. So customer orders.
203 00:21:49.050 ⇒ 00:21:54.700 Aakash Tandel: Oh, and then this one they’ve sorted okay orders, customer
204 00:21:58.920 ⇒ 00:22:07.479 Aakash Tandel: orders per customer revenue revenue per users. Okay? One thing, if we can swap these 2, if we can put this one here and this one there.
205 00:22:07.760 ⇒ 00:22:11.360 Annie Yu: Okay, so revenue and orders per customer.
206 00:22:11.530 ⇒ 00:22:13.189 Aakash Tandel: Yep, swap those.
207 00:22:29.110 ⇒ 00:22:33.610 Aakash Tandel: And then are these numbers lining? Let me see okay.
208 00:22:35.750 ⇒ 00:22:53.130 Aakash Tandel: 5, 3, actually, let’s go to 52, 8 orders are okay, these numbers are or off than
209 00:22:54.510 ⇒ 00:22:57.260 Aakash Tandel: do you know where this data is coming from?
210 00:22:59.470 ⇒ 00:23:02.940 Annie Yu: From a data source named User Summary v, 2.
211 00:23:03.300 ⇒ 00:23:09.010 Annie Yu: And that’s a published data source on Pablo.
212 00:23:12.580 ⇒ 00:23:14.639 Aakash Tandel: Okay, let me just make a note of that.
213 00:23:16.520 ⇒ 00:23:27.679 Aakash Tandel: Be the in Ltv. By cohort. Looks different from big Booker studio version.
214 00:23:28.040 ⇒ 00:23:28.730 Aakash Tandel: Okay?
215 00:23:32.580 ⇒ 00:23:35.090 Aakash Tandel: Ask Robert and Robert.
216 00:23:35.520 ⇒ 00:23:36.440 Aakash Tandel: Funny enough.
217 00:23:38.750 ⇒ 00:23:42.369 Annie Yu: Yeah, if I’m not wrong, I think Robert
218 00:23:42.480 ⇒ 00:23:50.660 Annie Yu: already went through kind of the data validation with James. That at least what I thought
219 00:23:51.220 ⇒ 00:23:59.390 Annie Yu: was done. But so it probably would be a good idea to include him, and he probably has more context around that.
220 00:23:59.700 ⇒ 00:24:04.917 Aakash Tandel: Cool. Okay, that sounds good. Okay, so I’m gonna put these like, more.
221 00:24:06.819 ⇒ 00:24:13.249 Aakash Tandel: like tactical changes here, and then I will kick off a message to Robert.
222 00:24:15.040 ⇒ 00:24:21.069 Aakash Tandel: And Rob seems pretty like relaxed and chill. I feel like I might just ask him directly.
223 00:24:21.070 ⇒ 00:24:26.444 Annie Yu: Rob’s role. I I know he’s always there, but I’m not sure like who’s who and.
224 00:24:26.780 ⇒ 00:24:37.589 Aakash Tandel: Yeah, that’s a good question. So I didn’t realize this until kind of recently. Rob’s actually not even a client. He is another contractor. For Eden, so he’s not even.
225 00:24:37.590 ⇒ 00:24:39.080 Annie Yu: Like their Pm.
226 00:24:39.350 ⇒ 00:24:41.200 Aakash Tandel: No, he’s supposed to be their data person.
227 00:24:41.200 ⇒ 00:24:42.520 Annie Yu: Oh, okay. Okay.
228 00:24:42.520 ⇒ 00:24:48.990 Aakash Tandel: Yeah. Yeah. So he’s he’s kind of like similar to us. But he’s more in enmeshed in their day to day stuff.
229 00:24:49.360 ⇒ 00:24:50.060 Annie Yu: Yeah.
230 00:24:50.710 ⇒ 00:24:51.280 Aakash Tandel: Yep.
231 00:24:52.533 ⇒ 00:24:54.950 Aakash Tandel: Okay, cool. So I will.
232 00:24:56.870 ⇒ 00:25:12.880 Aakash Tandel: I, yeah, I will write you a ticket for the these modifications. I’ll pop. Put these in a ticket, and then I will get these things. The conversation started off on these guys to get the ball rolling on, the data being close to each other.
233 00:25:13.580 ⇒ 00:25:20.750 Annie Yu: Okay. So for the I think for the calculations of each metric, I’m just gonna leave it as it is now.
234 00:25:20.750 ⇒ 00:25:21.220 Aakash Tandel: Yeah.
235 00:25:21.220 ⇒ 00:25:26.870 Annie Yu: I’m just changing, really kind of the layout. And yep, okay.
236 00:25:27.000 ⇒ 00:25:29.109 Aakash Tandel: Yeah. Exactly. Awesome. Okay.
237 00:25:29.470 ⇒ 00:25:40.140 Annie Yu: I’m looking at my ticket. I am seeing there is a retention dashboard, v. 2, created by Robert that
238 00:25:40.400 ⇒ 00:25:44.299 Annie Yu: I’m assuming. That’s something.
239 00:25:47.350 ⇒ 00:25:50.149 Annie Yu: It’s a good continuous work for this one.
240 00:25:51.076 ⇒ 00:25:52.819 Aakash Tandel: Let me find this
241 00:26:03.290 ⇒ 00:26:04.710 Aakash Tandel: retention. Dashboard.
242 00:26:05.130 ⇒ 00:26:06.760 Aakash Tandel: First, st that retention.
243 00:26:07.560 ⇒ 00:26:18.699 Aakash Tandel: Dashboard. Oh, I see this okay, add all date groupings, apply product filters, stack bar charts. Okay?
244 00:26:20.540 ⇒ 00:26:32.770 Aakash Tandel: those, I think, are other pieces of feedback we got to modify. But let’s not worry about the all those yet, because we don’t have it exactly like the josh wants in the current format. So does that work.
245 00:26:32.770 ⇒ 00:26:37.189 Annie Yu: Yeah, yeah, for sure. So I’ll just look at the the new ticket.
246 00:26:38.377 ⇒ 00:26:45.749 Aakash Tandel: Actually, I’m just gonna edit to actually retention dashboards. New versus. Yes, this is this is done. I’m gonna put this as done.
247 00:26:46.670 ⇒ 00:26:48.329 Aakash Tandel: And then I’m gonna put.
248 00:26:49.550 ⇒ 00:26:55.400 Aakash Tandel: And this is already in progress. So I’m just gonna set it to in progress. Okay? So tension
249 00:27:00.640 ⇒ 00:27:06.721 Aakash Tandel: 2, and I can put it as version 1.2, because we already kind of have it.
250 00:27:08.960 ⇒ 00:27:17.940 Aakash Tandel: changes code in progress.
251 00:27:18.930 ⇒ 00:27:23.820 Aakash Tandel: 39 age retention.
252 00:27:37.390 ⇒ 00:27:38.870 Aakash Tandel: What’s this thing?
253 00:27:40.480 ⇒ 00:27:41.299 Aakash Tandel: All right?
254 00:27:44.710 ⇒ 00:27:47.269 Aakash Tandel: I just used that ticket.
255 00:27:55.160 ⇒ 00:27:59.910 Annie Yu: And I do have one more question. It’s probably easier to
256 00:28:00.170 ⇒ 00:28:07.979 Annie Yu: screen share on my end. And I’m just thinking what you said like, we want to make it as identical as they have.
257 00:28:07.980 ⇒ 00:28:08.350 Aakash Tandel: Yeah.
258 00:28:08.756 ⇒ 00:28:14.039 Annie Yu: So I’m I’m not sure which one’s easier to read, though. So for
259 00:28:16.290 ⇒ 00:28:20.440 Annie Yu: you see, like this one, we have that kind of colors in the background.
260 00:28:20.570 ⇒ 00:28:32.709 Annie Yu: And then this one. We have the colors on the text color, and I can make it like similar to that. I’m not sure if this is like easier to read at all, because they have that like white and black.
261 00:28:34.174 ⇒ 00:28:37.679 Aakash Tandel: Yeah, I mean, yeah, we can do that. Yeah, that sounds good. If you want to change colors.
262 00:28:38.300 ⇒ 00:28:43.940 Annie Yu: Oh, no, I’m I’m not sure like which one will be more.
263 00:28:45.020 ⇒ 00:28:47.600 Aakash Tandel: Yeah, honestly.
264 00:28:47.600 ⇒ 00:28:55.190 Annie Yu: They have all the font color as black, but here I think it automatically changed.
265 00:28:55.670 ⇒ 00:29:03.120 Aakash Tandel: I think it’s fine, but I kind of do like this where it’s like. The blocks are kind of bold blocks. You know what I’m saying.
266 00:29:03.830 ⇒ 00:29:05.529 Aakash Tandel: But I think, yeah, I think that’s a good change to make.
267 00:29:05.870 ⇒ 00:29:09.269 Annie Yu: Okay. Alright, I’ll I’ll add that, too.
268 00:29:09.270 ⇒ 00:29:14.189 Aakash Tandel: Awesome. Okay. So I just added that ticket. And I’m gonna link to those
269 00:29:14.770 ⇒ 00:29:18.059 Aakash Tandel: dashboards so that we have
270 00:29:26.620 ⇒ 00:29:27.520 Aakash Tandel: this stuff.
271 00:29:27.910 ⇒ 00:29:31.179 Aakash Tandel: Oh, wait, no, this is the current and the other ones.
272 00:29:35.040 ⇒ 00:29:35.800 Aakash Tandel: Okay.
273 00:29:38.110 ⇒ 00:29:39.819 Aakash Tandel: Awesome. Okay. Sweet.
274 00:29:40.090 ⇒ 00:29:44.050 Aakash Tandel: That looks good. Yeah. Anything? Other questions, Olica.
275 00:29:44.410 ⇒ 00:29:46.250 Annie Yu: I believe that’s everything.
276 00:29:46.250 ⇒ 00:29:47.500 Aakash Tandel: Okay. Cool.
277 00:29:47.500 ⇒ 00:29:48.280 Annie Yu: Oh, my! Gosh!
278 00:29:48.280 ⇒ 00:29:55.730 Aakash Tandel: Yeah, no, I appreciate your help, too. On this. I will kick off those messages, and hopefully we can get this wrapped up.
279 00:29:55.880 ⇒ 00:29:57.410 Annie Yu: Alright, sounds good.
280 00:29:57.410 ⇒ 00:29:58.440 Aakash Tandel: See you have a good one. Bye.
281 00:29:58.440 ⇒ 00:29:59.040 Annie Yu: Bye.