Meeting Title: Omni vs Tableau Data Alignment Sync Date: 2026-02-17 Meeting participants: Mustafa Raja, Greg Stoutenburg, Uttam Kumaran, Demilade Agboola
WEBVTT
1 00:03:07.710 ⇒ 00:03:08.670 Greg Stoutenburg: Hey!
2 00:03:14.950 ⇒ 00:03:15.940 Mustafa Raja: Hey, how are you?
3 00:03:16.600 ⇒ 00:03:17.779 Greg Stoutenburg: Hey, good, how are you?
4 00:03:18.670 ⇒ 00:03:23.080 Mustafa Raja: Yeah, doing good. So… Okay.
5 00:03:27.700 ⇒ 00:03:33.819 Mustafa Raja: Okay, so, this graph I divided into 3, alright? You can see it here.
6 00:03:34.100 ⇒ 00:03:44.730 Mustafa Raja: This is now divided into 3 different charts. The values are, pretty good for all of these, except this one, and I think it’s because, when we drain it down
7 00:03:44.990 ⇒ 00:03:51.579 Mustafa Raja: to weeks, what happens is there’s a difference in time zones, and we have seen it before between me and Deni.
8 00:03:51.710 ⇒ 00:04:11.440 Mustafa Raja: So, if you would pull it up, I believe these values are going to be a little different, right? But this is still closer to, what’s it called, the tableau. And let’s look at the difference in time. So you’d see… you’d see this is grained down to September 29th week, right?
9 00:04:12.340 ⇒ 00:04:12.950 Greg Stoutenburg: Yep.
10 00:04:13.970 ⇒ 00:04:14.800 Greg Stoutenburg: Yep.
11 00:04:15.180 ⇒ 00:04:20.379 Mustafa Raja: Okay, now let’s look at… then let’s look at the dates in here.
12 00:04:20.860 ⇒ 00:04:23.570 Mustafa Raja: So… This is September 28th.
13 00:04:24.210 ⇒ 00:04:26.909 Mustafa Raja: And this is Omni doing it in the back, right?
14 00:04:27.170 ⇒ 00:04:36.989 Mustafa Raja: We don’t have much control on that, but this is because of the time zones. Can you open this chart… this… this up, this dashboard, and see what…
15 00:04:36.990 ⇒ 00:04:37.750 Greg Stoutenburg: You just shoot me the link?
16 00:04:37.750 ⇒ 00:04:39.020 Mustafa Raja: on your side?
17 00:04:40.010 ⇒ 00:04:41.150 Greg Stoutenburg: Yeah, can you shoot me the link?
18 00:04:41.150 ⇒ 00:04:41.600 Mustafa Raja: Oh, yeah.
19 00:04:41.600 ⇒ 00:04:41.920 Greg Stoutenburg: Okay.
20 00:04:41.920 ⇒ 00:04:42.570 Mustafa Raja: Sorry.
21 00:04:43.320 ⇒ 00:04:44.170 Greg Stoutenburg: Yep, terrific.
22 00:04:47.170 ⇒ 00:04:48.040 Mustafa Raja: this.
23 00:04:49.000 ⇒ 00:04:52.170 Mustafa Raja: Yeah, so, just want to verify on your…
24 00:04:52.640 ⇒ 00:04:54.330 Mustafa Raja: It’s going to be 29th or 28th.
25 00:04:56.020 ⇒ 00:05:01.390 Mustafa Raja: If it’s Twin Night, I could… I could… Alright, weekly…
26 00:05:01.520 ⇒ 00:05:03.360 Mustafa Raja: Let me see what it…
27 00:05:03.360 ⇒ 00:05:05.539 Greg Stoutenburg: Weekly total revenue versus revenue growth rate.
28 00:05:05.540 ⇒ 00:05:06.520 Mustafa Raja: Weekly total meetings.
29 00:05:06.520 ⇒ 00:05:08.409 Greg Stoutenburg: to September 29th?
30 00:05:09.310 ⇒ 00:05:11.880 Greg Stoutenburg: Yep, and I’ve got one point…
31 00:05:12.820 ⇒ 00:05:13.720 Mustafa Raja: That’s a big one.
32 00:05:14.810 ⇒ 00:05:19.540 Greg Stoutenburg: Yep, I’ve got $1.49 million in revenue, growth rate 22.6%.
33 00:05:20.430 ⇒ 00:05:23.800 Mustafa Raja: And, okay, so it’s the same for both of us then, right?
34 00:05:23.800 ⇒ 00:05:25.949 Greg Stoutenburg: I say the same thing for you as you. Yep.
35 00:05:31.180 ⇒ 00:05:32.399 Greg Stoutenburg: And that gives…
36 00:05:32.400 ⇒ 00:05:33.100 Mustafa Raja: 10%.
37 00:05:33.100 ⇒ 00:05:34.070 Greg Stoutenburg: that higher.
38 00:05:35.740 ⇒ 00:05:39.859 Mustafa Raja: No, no, no, it’s 3% lower than that, you know?
39 00:05:40.330 ⇒ 00:05:42.289 Mustafa Raja: Wait. No, no, no, twin.
40 00:05:42.290 ⇒ 00:05:45.330 Greg Stoutenburg: Sorry, sorry, Tableau was 10%.
41 00:05:45.330 ⇒ 00:05:45.940 Mustafa Raja: percentage point.
42 00:05:45.940 ⇒ 00:05:46.790 Greg Stoutenburg: it’s higher.
43 00:05:47.800 ⇒ 00:05:52.579 Greg Stoutenburg: See, that says 32%. This says 22.6%.
44 00:05:58.190 ⇒ 00:05:59.980 Mustafa Raja: 1.49 revenue…
45 00:06:03.120 ⇒ 00:06:03.880 Mustafa Raja: Hmm.
46 00:06:04.850 ⇒ 00:06:05.800 Mustafa Raja: Okay…
47 00:06:15.490 ⇒ 00:06:19.659 Mustafa Raja: Okay, Always, I’ll… I’ll get with Demi, take a look at this.
48 00:06:19.880 ⇒ 00:06:21.799 Mustafa Raja: But the rest is there.
49 00:06:22.530 ⇒ 00:06:24.270 Mustafa Raja: And the values are pretty good.
50 00:06:25.250 ⇒ 00:06:28.179 Mustafa Raja: Okay. I just need to do something about these projection masks.
51 00:06:28.320 ⇒ 00:06:30.000 Greg Stoutenburg: Oh… Okay.
52 00:06:30.000 ⇒ 00:06:36.479 Mustafa Raja: I can’t… I… I couldn’t find any good way to put that… put these masks in…
53 00:06:36.720 ⇒ 00:06:41.299 Mustafa Raja: In Omni, but I’ll take a deeper look, I haven’t taken…
54 00:06:41.300 ⇒ 00:06:44.530 Greg Stoutenburg: Well… Why don’t we… can we ask Bobby this question?
55 00:06:44.680 ⇒ 00:06:47.870 Greg Stoutenburg: Can we ask Blobby the question about the misalignment with Tableau?
56 00:06:48.670 ⇒ 00:06:50.340 Greg Stoutenburg: And see if it’ll just fix it.
57 00:06:51.680 ⇒ 00:06:52.590 Mustafa Raja: This one, yeah.
58 00:06:53.170 ⇒ 00:06:54.630 Mustafa Raja: Yeah.
59 00:06:54.760 ⇒ 00:06:56.109 Mustafa Raja: I didn’t want to look…
60 00:07:10.580 ⇒ 00:07:15.389 Mustafa Raja: I don’t think Blobby has, direct contacts on… what’s it called?
61 00:07:15.500 ⇒ 00:07:16.700 Mustafa Raja: Tableau.
62 00:07:16.930 ⇒ 00:07:28.640 Mustafa Raja: Him not be… There… Actually, I am migrating this… Let me just chime.
63 00:07:29.870 ⇒ 00:07:30.980 Mustafa Raja: Oh my god.
64 00:07:39.980 ⇒ 00:07:48.920 Mustafa Raja: Oh, no… Dear… Is…
65 00:07:53.310 ⇒ 00:07:54.340 Mustafa Raja: Indeed.
66 00:07:55.130 ⇒ 00:07:57.199 Mustafa Raja: In the selection, actually.
67 00:07:57.490 ⇒ 00:07:59.300 Mustafa Raja: Weeks in action…
68 00:08:02.510 ⇒ 00:08:04.130 Mustafa Raja: How many,
69 00:08:09.300 ⇒ 00:08:14.100 Mustafa Raja: I have no… In June.
70 00:08:15.590 ⇒ 00:08:16.164 Mustafa Raja: Mmm…
71 00:08:23.620 ⇒ 00:08:29.290 Mustafa Raja: from… I mean, you know… Okay.
72 00:08:32.080 ⇒ 00:08:32.789 Mustafa Raja: Yes.
73 00:08:40.460 ⇒ 00:08:41.140 Mustafa Raja: not.
74 00:09:23.920 ⇒ 00:09:24.800 Mustafa Raja: Monday…
75 00:09:27.810 ⇒ 00:09:29.600 Mustafa Raja: New tweak, yes.
76 00:09:33.000 ⇒ 00:09:35.369 Mustafa Raja: I’m just a regrouping in the query.
77 00:09:37.620 ⇒ 00:09:40.470 Mustafa Raja: Different time frames and… Moop.
78 00:09:42.300 ⇒ 00:09:44.629 Mustafa Raja: Custom calculation.
79 00:09:51.800 ⇒ 00:09:53.050 Mustafa Raja: Option A.
80 00:09:55.020 ⇒ 00:09:59.670 Mustafa Raja: And then… Oh, Lord.
81 00:10:08.300 ⇒ 00:10:11.470 Mustafa Raja: I like option 8, and then…
82 00:10:11.860 ⇒ 00:10:18.179 Mustafa Raja: For the time frame, I guess just let… let’s move one day back, since…
83 00:10:18.820 ⇒ 00:10:24.119 Mustafa Raja: Since that’s the whole difference between Tableau and Omni, right? So let’s just do it.
84 00:10:24.940 ⇒ 00:10:25.570 Greg Stoutenburg: Yeah.
85 00:10:25.880 ⇒ 00:10:27.730 Greg Stoutenburg: We’re just talking about moving back a day.
86 00:10:29.680 ⇒ 00:10:34.969 Mustafa Raja: Yeah, yeah, I’m, I’m using the… what’s it called? Whisperflow, right?
87 00:10:35.900 ⇒ 00:10:36.580 Greg Stoutenburg: Yep.
88 00:10:36.860 ⇒ 00:10:39.389 Mustafa Raja: So I talk, and it lights.
89 00:10:39.630 ⇒ 00:10:40.570 Greg Stoutenburg: Yeah, yep.
90 00:10:40.980 ⇒ 00:10:41.790 Mustafa Raja: It helps.
91 00:10:42.910 ⇒ 00:10:45.270 Mustafa Raja: Okay, let’s see if it does it.
92 00:10:51.420 ⇒ 00:11:01.079 Mustafa Raja: You can see… Hmm… Okay, something is happening.
93 00:11:03.020 ⇒ 00:11:04.510 Mustafa Raja: Something big happened.
94 00:11:12.750 ⇒ 00:11:16.569 Mustafa Raja: I see the pre-emissioner, but I…
95 00:11:17.110 ⇒ 00:11:20.589 Mustafa Raja: Even the day shift didn’t actually work as intended.
96 00:11:22.430 ⇒ 00:11:24.300 Mustafa Raja: We’ll fix the weak boundaries.
97 00:11:25.990 ⇒ 00:11:27.460 Mustafa Raja: What does it do?
98 00:11:30.650 ⇒ 00:11:32.210 Mustafa Raja: So… Drainland.
99 00:11:32.710 ⇒ 00:11:33.869 Mustafa Raja: September 9th.
100 00:11:42.060 ⇒ 00:11:42.460 Greg Stoutenburg: Okay.
101 00:11:42.460 ⇒ 00:11:42.960 Mustafa Raja: Hmm.
102 00:11:42.960 ⇒ 00:11:46.740 Greg Stoutenburg: So, let me see what calendar day September 29th is.
103 00:11:52.830 ⇒ 00:11:59.219 Greg Stoutenburg: That would be a Monday. The 28th would be a Sunday. So Tableau is showing Monday.
104 00:12:00.180 ⇒ 00:12:00.740 Greg Stoutenburg: Tableau.
105 00:12:00.740 ⇒ 00:12:02.260 Mustafa Raja: No, no, that was on Sunday.
106 00:12:02.630 ⇒ 00:12:15.829 Mustafa Raja: Yeah, definitely selecting Sunday, and normally selecting one day. And this discrepancy comes when we are converting between weeks. This doesn’t happen when we are converting between months.
107 00:12:15.940 ⇒ 00:12:20.710 Mustafa Raja: So… so if you’re talking month… month to month, it’s going to be, you know…
108 00:12:21.310 ⇒ 00:12:24.719 Mustafa Raja: The same, but different for week to week.
109 00:12:25.270 ⇒ 00:12:25.980 Greg Stoutenburg: Okay.
110 00:12:27.450 ⇒ 00:12:31.089 Mustafa Raja: Yeah, I guess this is something we need to debate or something, yeah.
111 00:12:31.310 ⇒ 00:12:41.860 Greg Stoutenburg: Yeah, I’m making a note, let’s… we don’t need to let this… yeah, we don’t need to let this slow us down. If… if Demi knows a quick fix to… to apply globally, like, to all.
112 00:12:41.860 ⇒ 00:12:45.349 Mustafa Raja: of our charts, then let’s do it.
113 00:12:45.350 ⇒ 00:12:49.330 Greg Stoutenburg: But this doesn’t need to slow us down. Especially because we know that it’s.
114 00:12:49.330 ⇒ 00:12:49.740 Mustafa Raja: Okay.
115 00:12:49.740 ⇒ 00:12:50.910 Greg Stoutenburg: level. Yeah.
116 00:12:51.590 ⇒ 00:12:57.069 Mustafa Raja: Yeah, okay, so the context… Context is there now, you know, the AI context.
117 00:12:57.540 ⇒ 00:12:58.030 Greg Stoutenburg: Awesome.
118 00:12:58.030 ⇒ 00:13:02.539 Mustafa Raja: We have the topics tool, so if you have any questions…
119 00:13:04.070 ⇒ 00:13:09.390 Mustafa Raja: Okay. We could test them out. And I also got rid of, what’s it called? Cabbage.
120 00:13:09.800 ⇒ 00:13:13.149 Greg Stoutenburg: Caveats are gone. Okay, cool. Alright.
121 00:13:13.550 ⇒ 00:13:23.139 Greg Stoutenburg: So, all of the topics are filled in here with all this context, that’s great. So, does that cover the semantic layer for everything we’re gonna move over, or just the P0 stuff?
122 00:13:24.020 ⇒ 00:13:35.470 Mustafa Raja: This is only P… these topics are P01s. But I believe, this P0 is also, going to have a lot of stuff for other dashboards too, you know?
123 00:13:35.650 ⇒ 00:13:45.830 Mustafa Raja: Because, you know, all of these tables, all of these topics are just based on these three schemas, March, season, intermediate. So.
124 00:13:46.020 ⇒ 00:14:02.330 Mustafa Raja: Even with this, I can get rid of this transaction, what’s it called, topic, because it’s, it’s using facts only, this facts table only, and… which is a base view, over here.
125 00:14:04.450 ⇒ 00:14:05.250 Greg Stoutenburg: Okay.
126 00:14:05.860 ⇒ 00:14:13.489 Mustafa Raja: So, I could just get rid of it, and then I’ll just see if, you know, if we should still have it or not.
127 00:14:13.870 ⇒ 00:14:20.300 Mustafa Raja: So, you see fag transactions, and it’s still, and it’s over here, all alone, so it doesn’t make sense.
128 00:14:20.490 ⇒ 00:14:28.970 Mustafa Raja: But I’ll see. And it’s not being used right now, so if we grow, and this is still there, not being used, I’ll just get rid of this.
129 00:14:29.770 ⇒ 00:14:32.249 Greg Stoutenburg: Yeah, okay, got it. Alright.
130 00:14:32.630 ⇒ 00:14:34.209 Greg Stoutenburg: Or… let’s see…
131 00:14:34.570 ⇒ 00:14:49.109 Greg Stoutenburg: Home page is currently empty. I’m trying to imagine the user’s view now, because the next thing will be… I’ll do a version 1 of a training for Eden stakeholders, and so just want to make sure that the right stuff is in for that. I’m just gonna do a dry run tomorrow with people here.
132 00:14:49.270 ⇒ 00:14:51.520 Greg Stoutenburg: internally.
133 00:14:51.520 ⇒ 00:14:52.360 Mustafa Raja: Okay.
134 00:14:52.360 ⇒ 00:14:59.310 Greg Stoutenburg: So let’s see, if I go to Hub… yeah, that’s where we’ve got Executive Financial Overview, and that is…
135 00:15:00.310 ⇒ 00:15:02.230 Greg Stoutenburg: one of the Tableau…
136 00:15:02.960 ⇒ 00:15:04.569 Mustafa Raja: Yeah, this is the first B0.
137 00:15:04.570 ⇒ 00:15:08.310 Greg Stoutenburg: Dashboards, yep, yeah, I just gave it a… I just gave it a star.
138 00:15:08.650 ⇒ 00:15:10.629 Greg Stoutenburg: So that it shows up under my favorites.
139 00:15:10.630 ⇒ 00:15:11.280 Mustafa Raja: Oh.
140 00:15:12.930 ⇒ 00:15:15.900 Greg Stoutenburg: Yep, cool, that looks good.
141 00:15:19.700 ⇒ 00:15:25.940 Mustafa Raja: Yeah, and I saw Demi’s comment on mobile view. I opened it in mobile view, and it doesn’t look good.
142 00:15:27.310 ⇒ 00:15:36.080 Greg Stoutenburg: Doesn’t look good? No, that’s okay. So, what I’ll do for that is, I’ll look through, since he specifically mentioned that it’s Danny who likes to do it.
143 00:15:36.190 ⇒ 00:15:44.469 Greg Stoutenburg: I’ll just look at what Danny seems to visit most often, and prioritize those, and then anything else, if they… if they want to ask, they can just ask, you know?
144 00:15:44.630 ⇒ 00:15:45.270 Greg Stoutenburg: Oh, John.
145 00:15:45.680 ⇒ 00:15:46.570 Greg Stoutenburg: It’s Josh.
146 00:15:49.850 ⇒ 00:15:50.610 Mustafa Raja: Yeah.
147 00:15:50.610 ⇒ 00:15:51.300 Greg Stoutenburg: Okay.
148 00:15:52.840 ⇒ 00:15:54.750 Mustafa Raja: Okay. Yeah.
149 00:15:57.730 ⇒ 00:16:02.810 Greg Stoutenburg: Okay, oh, it’s not letting me sign into Tableau.
150 00:16:02.810 ⇒ 00:16:06.429 Mustafa Raja: Yeah, do we want… There’s a,
151 00:16:12.770 ⇒ 00:16:13.400 Mustafa Raja: But it’s…
152 00:16:13.400 ⇒ 00:16:14.020 Greg Stoutenburg: Sorry, you…
153 00:16:14.020 ⇒ 00:16:14.700 Mustafa Raja: Corona.
154 00:16:14.700 ⇒ 00:16:17.779 Greg Stoutenburg: You’re breaking up. I think one of us has a bad signal, you’re breaking up a bit.
155 00:16:19.500 ⇒ 00:16:20.529 Greg Stoutenburg: Can you hear me?
156 00:16:26.090 ⇒ 00:16:27.180 Greg Stoutenburg: Mustafa?
157 00:16:49.190 ⇒ 00:16:50.190 Greg Stoutenburg: Mustafa?
158 00:16:50.370 ⇒ 00:16:51.370 Greg Stoutenburg: Check, check.
159 00:16:52.760 ⇒ 00:16:53.980 Greg Stoutenburg: Here, I’ll drop in…
160 00:17:08.540 ⇒ 00:17:09.770 Greg Stoutenburg: Hey, can you hear me?
161 00:17:11.750 ⇒ 00:17:12.899 Greg Stoutenburg: Check, check. Oh, yes.
162 00:17:12.900 ⇒ 00:17:16.250 Mustafa Raja: Yes, sorry, sorry, my connection dropped for a moment.
163 00:17:16.250 ⇒ 00:17:22.539 Greg Stoutenburg: Oh, okay, alright, yeah, alright. I lost your audio, so… Yeah, so I was saying… Yeah, I was saying, yeah, yeah, yeah.
164 00:17:22.540 ⇒ 00:17:37.140 Mustafa Raja: It was just my own connection. So, what I was saying is, I need to add some headings and stuff, headings and description, because right now it’s just charts, right? So, I’ll just copy that over from…
165 00:17:38.270 ⇒ 00:17:42.710 Mustafa Raja: what’s it called? The… the dashboard itself? And then…
166 00:17:45.720 ⇒ 00:17:46.650 Mustafa Raja: Alright.
167 00:18:25.920 ⇒ 00:18:31.829 Mustafa Raja: So, yeah, so I was saying, do you want to test, what’s it called? The AI thing?
168 00:18:32.400 ⇒ 00:18:34.390 Greg Stoutenburg: Yeah, let’s do it. Let’s just do it together.
169 00:18:34.850 ⇒ 00:18:35.730 Mustafa Raja: Beautiful.
170 00:18:36.780 ⇒ 00:18:37.690 Mustafa Raja: Thank you.
171 00:18:38.890 ⇒ 00:18:47.540 Mustafa Raja: So… I mean, let’s just, let me… Hmm… It was…
172 00:18:48.340 ⇒ 00:18:50.570 Mustafa Raja: Oh, do you want to.
173 00:18:50.570 ⇒ 00:18:53.630 Greg Stoutenburg: I see you, Tom’s comment. Want to just invite him?
174 00:18:54.370 ⇒ 00:18:55.819 Greg Stoutenburg: If he’s asking right now.
175 00:18:55.820 ⇒ 00:18:56.610 Mustafa Raja: Oh, yeah.
176 00:18:58.700 ⇒ 00:18:59.960 Mustafa Raja: How do we…
177 00:19:00.980 ⇒ 00:19:04.779 Greg Stoutenburg: Probably just give them the same link. Is this just your private room?
178 00:19:05.450 ⇒ 00:19:07.890 Mustafa Raja: Yeah, let me grab that.
179 00:19:26.770 ⇒ 00:19:31.740 Mustafa Raja: Okay, so Utam suggested… What we should do is…
180 00:19:33.460 ⇒ 00:19:38.980 Mustafa Raja: Where is the channel? This one. Okay, here… Okay.
181 00:19:41.530 ⇒ 00:19:43.390 Mustafa Raja: Effectiveness or status.
182 00:19:43.960 ⇒ 00:19:48.869 Mustafa Raja: Questions, easy meeting, use transcript to… In context of builders.
183 00:19:50.020 ⇒ 00:19:50.560 Greg Stoutenburg: You did that.
184 00:19:50.560 ⇒ 00:19:57.480 Mustafa Raja: me questions. Okay. Yeah, I’m just going to ask it. Based on these transcripts, this…
185 00:19:58.140 ⇒ 00:20:01.359 Mustafa Raja: create me some questions that I can test the AI with.
186 00:20:01.760 ⇒ 00:20:02.620 Mustafa Raja: Yep, great.
187 00:20:05.570 ⇒ 00:20:09.140 Greg Stoutenburg: And do, at 3 different levels of complexity.
188 00:20:10.660 ⇒ 00:20:15.940 Greg Stoutenburg: Like, simple, medium difficulty, and… complex analysis.
189 00:20:17.770 ⇒ 00:20:18.680 Greg Stoutenburg: Yep.
190 00:20:23.320 ⇒ 00:20:24.010 Mustafa Raja: Alright.
191 00:20:34.830 ⇒ 00:20:53.759 Mustafa Raja: Hey, can you please, generate me a few questions in three different dimensions? Easy, medium, and then hard? Use the transcripts, and, you know which, topics we have just, worked on. So, keep this all in context and generate me a few questions in three different dynamics. Thank you.
192 00:20:56.820 ⇒ 00:20:59.210 Mustafa Raja: Thank you, work sometimes.
193 00:20:59.210 ⇒ 00:21:03.050 Greg Stoutenburg: That speeds it up, wants to put in a little more effort for you.
194 00:21:03.530 ⇒ 00:21:04.290 Mustafa Raja: Yeah.
195 00:21:07.740 ⇒ 00:21:09.389 Mustafa Raja: And do you use WhisperFlow?
196 00:21:11.610 ⇒ 00:21:15.950 Greg Stoutenburg: I haven’t used text-to-speech, no.
197 00:21:16.430 ⇒ 00:21:25.760 Mustafa Raja: Oh, this is super cool, you need to… I mean, there are a few text-to-speech, but this is just next level.
198 00:21:26.420 ⇒ 00:21:31.429 Mustafa Raja: You can… even cursor… cursor, text-to-speech isn’t good at all, you know?
199 00:21:31.710 ⇒ 00:21:33.400 Mustafa Raja: Is this out of each one? What are you using?
200 00:21:34.070 ⇒ 00:21:38.260 Mustafa Raja: Wait, let me open the show you the whisper flow.
201 00:21:39.200 ⇒ 00:21:39.760 Greg Stoutenburg: Whisper.
202 00:21:39.760 ⇒ 00:21:45.480 Mustafa Raja: this, this whisper flow. We, let me… Type that also.
203 00:21:46.470 ⇒ 00:21:46.990 Greg Stoutenburg: Yeah, cool.
204 00:21:47.380 ⇒ 00:21:49.229 Mustafa Raja: So, blue, yeah.
205 00:21:49.870 ⇒ 00:21:50.850 Mustafa Raja: Super good.
206 00:21:51.040 ⇒ 00:21:51.940 Mustafa Raja: Try that.
207 00:21:52.500 ⇒ 00:21:53.200 Greg Stoutenburg: Yeah, I will.
208 00:21:53.200 ⇒ 00:22:05.140 Mustafa Raja: Okay… Hmm… Well, let’s see… And… is it difficult? Easy questions. Let’s do hard ones first.
209 00:22:09.720 ⇒ 00:22:10.940 Mustafa Raja: Let’s do this.
210 00:22:11.920 ⇒ 00:22:14.850 Mustafa Raja: Let’s see what it comes up with. Hopefully something.
211 00:22:14.850 ⇒ 00:22:16.050 Greg Stoutenburg: There we go.
212 00:22:16.510 ⇒ 00:22:17.040 Mustafa Raja: Yeah.
213 00:22:18.770 ⇒ 00:22:19.650 Mustafa Raja: Bro.
214 00:22:21.120 ⇒ 00:22:21.760 Greg Stoutenburg: Nope.
215 00:22:22.310 ⇒ 00:22:25.979 Greg Stoutenburg: That’s not what we wanted to see. Not a good start.
216 00:22:29.120 ⇒ 00:22:30.000 Mustafa Raja: Okay.
217 00:22:31.520 ⇒ 00:22:32.460 Mustafa Raja: Sweet.
218 00:22:36.740 ⇒ 00:22:41.140 Mustafa Raja: I want to see if the dashboard is over, right? Yeah. Okay.
219 00:22:41.280 ⇒ 00:22:43.560 Mustafa Raja: Let’s go back. Could be just my internet.
220 00:22:45.780 ⇒ 00:22:46.920 Mustafa Raja: Okay.
221 00:22:50.090 ⇒ 00:22:51.900 Mustafa Raja: Do some justice now.
222 00:22:52.890 ⇒ 00:22:54.100 Greg Stoutenburg: Alright, yeah, let’s see.
223 00:22:54.580 ⇒ 00:22:58.329 Greg Stoutenburg: Yeah, you told him a second ago he broke it with the first question.
224 00:22:58.540 ⇒ 00:23:00.170 Uttam Kumaran: No worries.
225 00:23:07.610 ⇒ 00:23:09.890 Uttam Kumaran: This is a crazy question.
226 00:23:11.440 ⇒ 00:23:15.150 Mustafa Raja: Yeah, it’s the, it’s the… it’s one of the hard ones, so I just started with those.
227 00:23:15.150 ⇒ 00:23:16.290 Uttam Kumaran: Oh, nice.
228 00:23:16.290 ⇒ 00:23:16.670 Mustafa Raja: Yeah.
229 00:23:16.670 ⇒ 00:23:18.340 Uttam Kumaran: It’s a brutal question.
230 00:23:19.150 ⇒ 00:23:20.400 Greg Stoutenburg: It is.
231 00:23:28.330 ⇒ 00:23:29.370 Mustafa Raja: How’s your day going?
232 00:23:30.160 ⇒ 00:23:37.580 Uttam Kumaran: Oh, my day is… My day’s actually fairly, like, light on meetings. I think it’s… it’s been positive, like…
233 00:23:37.770 ⇒ 00:23:41.969 Uttam Kumaran: This Magic Spoon stuff is going well, and I’m switching to work on Hedra stuff.
234 00:23:42.530 ⇒ 00:23:43.200 Uttam Kumaran: Yeah, it’s good.
235 00:23:45.680 ⇒ 00:23:48.600 Mustafa Raja: Here is the, AI video generator thing, right?
236 00:23:49.030 ⇒ 00:23:49.720 Uttam Kumaran: Yes.
237 00:23:50.040 ⇒ 00:23:50.720 Mustafa Raja: Yeah.
238 00:23:55.130 ⇒ 00:24:02.809 Uttam Kumaran: I don’t know if we need it… if we need it for anything, but we can get free credits if you… if we need it for stuff, but I don’t think we’re… we’re using… doing a lot of…
239 00:24:03.270 ⇒ 00:24:04.690 Mustafa Raja: Yeah, everything, yeah.
240 00:24:06.260 ⇒ 00:24:11.380 Mustafa Raja: LinkedIn marketing or LinkedIn thing… LinkedIn people would want to use that?
241 00:24:12.310 ⇒ 00:24:12.639 Uttam Kumaran: You know.
242 00:24:12.640 ⇒ 00:24:13.510 Mustafa Raja: Aldi?
243 00:24:14.840 ⇒ 00:24:17.359 Mustafa Raja: They’re… I think they’re using a bunch of free ones.
244 00:24:17.970 ⇒ 00:24:18.800 Mustafa Raja: Okay, okay.
245 00:24:20.320 ⇒ 00:24:22.320 Mustafa Raja: What do you feel… how do you feel about this one, though?
246 00:24:23.460 ⇒ 00:24:23.940 Mustafa Raja: I’m just trying.
247 00:24:23.940 ⇒ 00:24:25.540 Uttam Kumaran: Wait, let me read it, hold on.
248 00:24:25.890 ⇒ 00:24:26.610 Mustafa Raja: Yeah.
249 00:24:27.180 ⇒ 00:24:28.340 Mustafa Raja: This is the summary.
250 00:24:34.080 ⇒ 00:24:40.049 Uttam Kumaran: Can you, export or send these screenshots to the…
251 00:24:40.650 ⇒ 00:24:43.220 Uttam Kumaran: Data Team channel, and just ask, like.
252 00:24:43.920 ⇒ 00:24:48.239 Uttam Kumaran: just ask, like, Amber, Jasmine, Robert, like, yo, what do you think?
253 00:24:48.370 ⇒ 00:24:49.930 Greg Stoutenburg: Yeah, can you verify this?
254 00:24:51.130 ⇒ 00:25:02.889 Uttam Kumaran: Yeah, or just be like, what do you think about an answer like this? I mean, really, this is a crazy question, like, I don’t know if we’ll ever get to this point. Like, what are some of the… what are some of the medium questions?
255 00:25:04.860 ⇒ 00:25:06.959 Greg Stoutenburg: A medium question would be something like.
256 00:25:07.360 ⇒ 00:25:10.679 Uttam Kumaran: Oh, yeah, so some of these are, like… these are, these are good ones.
257 00:25:11.600 ⇒ 00:25:14.639 Mustafa Raja: Oh, yeah, yeah, let me just, let me just ask the data team, and then…
258 00:25:14.640 ⇒ 00:25:18.410 Uttam Kumaran: Yeah, yeah. Meaning, like, I think it’s good for us to have the hard ones.
259 00:25:18.410 ⇒ 00:25:19.240 Mustafa Raja: Yeah.
260 00:25:20.140 ⇒ 00:25:24.410 Uttam Kumaran: I feel like the medium E’s are gonna be more, like, Realistic.
261 00:25:24.410 ⇒ 00:25:28.680 Greg Stoutenburg: Well, yeah. We also just found out what Omni thinks is a hard question.
262 00:25:29.020 ⇒ 00:25:32.030 Greg Stoutenburg: It’s a pretty hard question.
263 00:25:41.740 ⇒ 00:25:44.559 Mustafa Raja: So I should tag Amber, and… whom else?
264 00:25:45.710 ⇒ 00:25:48.659 Uttam Kumaran: Tag Amber, Jasmine, and Robert.
265 00:25:49.580 ⇒ 00:25:50.280 Mustafa Raja: Boom.
266 00:25:50.860 ⇒ 00:25:51.840 Uttam Kumaran: Anna Waysh.
267 00:25:53.470 ⇒ 00:25:54.610 Mustafa Raja: Okay.
268 00:25:54.610 ⇒ 00:25:56.340 Uttam Kumaran: And Demi.
269 00:25:56.670 ⇒ 00:25:57.380 Mustafa Raja: But…
270 00:25:57.380 ⇒ 00:26:03.410 Uttam Kumaran: Just see what they think. Say, like, hey, here’s an example of, like, a super hard question we asked, and, like, in the reply.
271 00:26:03.900 ⇒ 00:26:06.230 Uttam Kumaran: Wondering, like, get your gut reaction.
272 00:26:06.740 ⇒ 00:26:07.510 Mustafa Raja: Mmm.
273 00:26:09.240 ⇒ 00:26:13.400 Uttam Kumaran: I mean, ideally, like, I think it would be great to send them, like, the Omni chat link.
274 00:26:14.680 ⇒ 00:26:16.480 Uttam Kumaran: You can all… you can add them whenever, but…
275 00:26:16.630 ⇒ 00:26:24.250 Mustafa Raja: Yeah, and this stores history also, so they can just come over here… Oh, nice, nice, okay. …look at the history, the question is going to be here.
276 00:26:45.040 ⇒ 00:26:45.990 Mustafa Raja: Okay.
277 00:26:50.030 ⇒ 00:26:53.989 Mustafa Raja: Okay. Okay, let’s do a medium one. How do you feel about this?
278 00:27:00.120 ⇒ 00:27:02.160 Uttam Kumaran: Ask the number 8 question.
279 00:27:04.210 ⇒ 00:27:04.920 Uttam Kumaran: Yeah.
280 00:27:08.990 ⇒ 00:27:11.260 Uttam Kumaran: And then after this, ask it.
281 00:27:11.540 ⇒ 00:27:13.690 Uttam Kumaran: what are some ways I can improve?
282 00:27:14.480 ⇒ 00:27:15.160 Mustafa Raja: Hmm.
283 00:27:20.960 ⇒ 00:27:23.159 Uttam Kumaran: I wonder how many tokens are burning.
284 00:27:23.370 ⇒ 00:27:25.700 Uttam Kumaran: I mean, I guess we’re not technically paying for it, right?
285 00:27:25.700 ⇒ 00:27:26.390 Mustafa Raja: Yeah.
286 00:27:26.880 ⇒ 00:27:29.780 Uttam Kumaran: Or we are, but like… sort of covered.
287 00:27:30.770 ⇒ 00:27:31.600 Mustafa Raja: Yeah.
288 00:27:31.830 ⇒ 00:27:33.570 Uttam Kumaran: I guess the AI seats are another.
289 00:27:33.570 ⇒ 00:27:33.920 Mustafa Raja: additional.
290 00:27:33.920 ⇒ 00:27:34.940 Uttam Kumaran: price, right?
291 00:27:35.240 ⇒ 00:27:35.940 Mustafa Raja: Yeah, yeah, yeah.
292 00:27:35.940 ⇒ 00:27:37.950 Greg Stoutenburg: It’s a higher price, and they’re capped.
293 00:27:38.660 ⇒ 00:27:39.490 Uttam Kumaran: What’s capped?
294 00:27:40.060 ⇒ 00:27:51.739 Greg Stoutenburg: So you can… the AI seats are a higher price, and per the… whatever the packages are, there’s some number, and then above that number of AI seats, you start paying for additional.
295 00:27:51.740 ⇒ 00:27:52.970 Uttam Kumaran: But it’s seat-based, not like…
296 00:27:52.970 ⇒ 00:27:53.440 Greg Stoutenburg: Really?
297 00:27:53.440 ⇒ 00:27:55.570 Uttam Kumaran: Not token-based, like, they’re not, like…
298 00:27:57.230 ⇒ 00:28:02.280 Greg Stoutenburg: I don’t think it’s seats and then tokens, I think it’s, like… Let me just…
299 00:28:03.360 ⇒ 00:28:05.819 Greg Stoutenburg: Just… let me just verify what it is.
300 00:28:06.880 ⇒ 00:28:09.570 Greg Stoutenburg: It wasn’t that complicated.
301 00:28:23.490 ⇒ 00:28:24.320 Mustafa Raja: Hey, Demi.
302 00:28:26.320 ⇒ 00:28:27.710 Demilade Agboola: Hey, Mustafa, hey everyone.
303 00:28:28.360 ⇒ 00:28:29.140 Uttam Kumaran: A…
304 00:28:37.070 ⇒ 00:28:37.999 Mustafa Raja: Is this good?
305 00:28:40.550 ⇒ 00:28:41.290 Greg Stoutenburg: Hey, Demi.
306 00:28:42.030 ⇒ 00:28:48.340 Demilade Agboola: Hello, let me see what it looks like in… Tableau.
307 00:28:48.880 ⇒ 00:28:57.530 Uttam Kumaran: Yeah, this seems good, Mustafa. Maybe ask it… ask it, like, hey, give me some ways to improve based on the data you have. I just want to see what it says.
308 00:29:21.660 ⇒ 00:29:24.469 Greg Stoutenburg: Correction, you, Tom. The…
309 00:29:25.000 ⇒ 00:29:33.350 Greg Stoutenburg: Pricing includes, yeah, there’s per-seat pricing, and then the platform includes 50 million Omni tokens per month.
310 00:29:33.350 ⇒ 00:29:34.140 Mustafa Raja: Whoa.
311 00:29:34.960 ⇒ 00:29:36.369 Greg Stoutenburg: And they don’t roll over.
312 00:29:37.150 ⇒ 00:29:38.100 Uttam Kumaran: Okay, okay.
313 00:29:38.470 ⇒ 00:29:39.599 Mustafa Raja: I mean, like…
314 00:29:39.600 ⇒ 00:29:40.140 Uttam Kumaran: there’s…
315 00:29:40.540 ⇒ 00:29:44.509 Uttam Kumaran: I don’t know if we’ll end up hitting that, but if we do, we can… there’s other ways for us to get around.
316 00:29:44.510 ⇒ 00:29:45.850 Greg Stoutenburg: We’ll figure it out, yeah.
317 00:30:31.740 ⇒ 00:30:33.640 Mustafa Raja: So these are some recommendations.
318 00:30:41.490 ⇒ 00:30:48.469 Greg Stoutenburg: That’s pretty cool. At the end of this, let’s ask Blobby to…
319 00:30:48.840 ⇒ 00:30:51.559 Greg Stoutenburg: Create a new chart to help us measure
320 00:30:56.010 ⇒ 00:31:00.570 Greg Stoutenburg: I don’t know, I’m looking for an easy one. I just want to go from query.
321 00:31:00.730 ⇒ 00:31:02.599 Mustafa Raja: Did you want to take a look at the easy questions, then?
322 00:31:02.600 ⇒ 00:31:04.670 Greg Stoutenburg: Recommendation, new chart.
323 00:31:05.910 ⇒ 00:31:08.000 Greg Stoutenburg: And… and close the loop that way.
324 00:31:08.370 ⇒ 00:31:11.579 Greg Stoutenburg: No, I just… actually, I mean, like, based off of the…
325 00:31:11.910 ⇒ 00:31:17.540 Greg Stoutenburg: recommendations that it just gave us. Let’s go from here and say,
326 00:31:17.850 ⇒ 00:31:28.449 Greg Stoutenburg: maybe, like, okay, so the first recommendation at the bottom is about inefficient campaigns. Wait, pause, I’m from a audit channel mix. Say, create a new chart.
327 00:31:29.010 ⇒ 00:31:30.470 Greg Stoutenburg: to show…
328 00:31:33.900 ⇒ 00:31:38.810 Greg Stoutenburg: lowest performing… Channel.
329 00:31:39.740 ⇒ 00:31:42.340 Greg Stoutenburg: by NetCAC.
330 00:31:43.510 ⇒ 00:31:44.700 Greg Stoutenburg: Yeah, how about that? I don’t know.
331 00:31:47.700 ⇒ 00:31:49.300 Greg Stoutenburg: I’m just trying to imagine what…
332 00:31:49.420 ⇒ 00:31:51.739 Greg Stoutenburg: What would someone want to do from here?
333 00:31:52.270 ⇒ 00:31:56.240 Greg Stoutenburg: To get started on the work. And how will Omni do that?
334 00:32:14.770 ⇒ 00:32:16.100 Greg Stoutenburg: That’s pretty cool.
335 00:32:20.560 ⇒ 00:32:27.830 Greg Stoutenburg: So, we see that it’s just switched topics. It was in the topic cohort, LTV and ROAS, now it’s gonna look at revenue summary.
336 00:32:35.950 ⇒ 00:32:36.770 Uttam Kumaran: Nice.
337 00:32:38.070 ⇒ 00:32:39.250 Greg Stoutenburg: That’s pretty slick.
338 00:32:46.090 ⇒ 00:32:48.909 Greg Stoutenburg: Then at the end, let’s see if we can figure out how many tokens this took.
339 00:32:49.840 ⇒ 00:32:50.839 Mustafa Raja: Oh, can we?
340 00:32:51.590 ⇒ 00:32:53.300 Greg Stoutenburg: Have you ever done before that?
341 00:32:53.540 ⇒ 00:32:54.730 Greg Stoutenburg: Let’s ask Blubby.
342 00:32:55.680 ⇒ 00:32:56.990 Mustafa Raja: Yeah.
343 00:32:59.790 ⇒ 00:33:05.349 Greg Stoutenburg: We could probably find out in the conversation, right? How many tokens did this particular conversation take?
344 00:33:08.040 ⇒ 00:33:09.330 Mustafa Raja: Meow.
345 00:33:31.300 ⇒ 00:33:34.129 Mustafa Raja: Hmm, I, I think what it’s struggling with is…
346 00:33:35.860 ⇒ 00:33:36.709 Greg Stoutenburg: There we go.
347 00:33:39.140 ⇒ 00:33:39.860 Greg Stoutenburg: Go.
348 00:33:39.860 ⇒ 00:33:44.000 Mustafa Raja: So, it wants to take a look at, the channels.
349 00:33:44.570 ⇒ 00:33:52.650 Mustafa Raja: And then, how channels are affecting this product, and I think… That topic might…
350 00:33:53.670 ⇒ 00:33:55.350 Mustafa Raja: Let me visualize the town.
351 00:33:55.560 ⇒ 00:33:57.070 Mustafa Raja: Oh, nice.
352 00:33:59.470 ⇒ 00:34:06.129 Demilade Agboola: Mustafa, can you take a screenshot of the terzapicide NCAC and send it to me? I just want to confirm that, like.
353 00:34:06.130 ⇒ 00:34:06.590 Mustafa Raja: Which one?
354 00:34:06.590 ⇒ 00:34:07.980 Demilade Agboola: watch… The first question.
355 00:34:07.980 ⇒ 00:34:08.400 Mustafa Raja: This one.
356 00:34:09.770 ⇒ 00:34:11.030 Mustafa Raja: What it turns out.
357 00:34:11.030 ⇒ 00:34:12.699 Demilade Agboola: beside NCOC.
358 00:34:13.889 ⇒ 00:34:15.610 Mustafa Raja: Like, the month-on-month, yes. This one.
359 00:34:15.610 ⇒ 00:34:16.710 Demilade Agboola: This one, here.
360 00:34:17.270 ⇒ 00:34:19.470 Mustafa Raja: Let me… Share that.
361 00:34:37.020 ⇒ 00:34:38.929 Mustafa Raja: Okay, how do you feel about this?
362 00:34:43.239 ⇒ 00:34:44.969 Mustafa Raja: Oh, this is good, good.
363 00:34:45.889 ⇒ 00:34:47.909 Mustafa Raja: I was able to do that. Nice.
364 00:34:48.380 ⇒ 00:34:49.250 Greg Stoutenburg: That is cool.
365 00:34:55.120 ⇒ 00:34:57.370 Mustafa Raja: Yeah. So, so what next now?
366 00:34:59.160 ⇒ 00:35:00.529 Mustafa Raja: Do we have anything else?
367 00:35:02.780 ⇒ 00:35:16.240 Greg Stoutenburg: I mean, I think we can keep asking it questions. I think this demonstrates that we’re able to get its answer, medium-level questions, create some recommendations, do some analysis that’ll help someone get started executing those recommendations.
368 00:35:16.370 ⇒ 00:35:18.500 Greg Stoutenburg: So I think… I think this is pretty good.
369 00:35:19.700 ⇒ 00:35:20.910 Mustafa Raja: Hmm, yeah.
370 00:35:20.910 ⇒ 00:35:22.690 Greg Stoutenburg: Ask an easy question.
371 00:35:28.140 ⇒ 00:35:28.530 Mustafa Raja: This…
372 00:35:28.530 ⇒ 00:35:30.509 Greg Stoutenburg: Because I’m curious to see how long it takes.
373 00:35:37.990 ⇒ 00:35:39.930 Mustafa Raja: Yeah. Let’s do this.
374 00:35:41.870 ⇒ 00:35:42.480 Greg Stoutenburg: Cool.
375 00:35:42.480 ⇒ 00:35:46.889 Mustafa Raja: We haven’t asked anything about cumulative repurchase rate. Let’s do that then.
376 00:35:48.290 ⇒ 00:35:50.290 Mustafa Raja: Oh, this isn’t an image, Bill.
377 00:35:51.840 ⇒ 00:35:54.199 Mustafa Raja: This one.
378 00:35:58.580 ⇒ 00:35:59.950 Mustafa Raja: That’s Etsy.
379 00:36:06.430 ⇒ 00:36:10.170 Mustafa Raja: Also, Demi, I might need, your help on some of the charts.
380 00:36:10.530 ⇒ 00:36:11.500 Mustafa Raja: Aww.
381 00:36:11.670 ⇒ 00:36:16.910 Mustafa Raja: We, we, we’re mostly there, but… We have some… some discrepancy.
382 00:36:17.490 ⇒ 00:36:20.709 Mustafa Raja: on how Omni and Tableau select their week starts.
383 00:36:20.970 ⇒ 00:36:25.289 Mustafa Raja: Tableau, Tableau week starts from Sunday and normally does it from Monday.
384 00:36:25.450 ⇒ 00:36:29.030 Mustafa Raja: So we have, on weekly green, some difference in data.
385 00:36:30.020 ⇒ 00:36:32.900 Uttam Kumaran: Did Eden ever do that, beside Demi?
386 00:36:34.140 ⇒ 00:36:36.159 Demilade Agboola: Sorry, I didn’t, I didn’t get questions.
387 00:36:36.850 ⇒ 00:36:37.920 Uttam Kumaran: Week start.
388 00:36:39.060 ⇒ 00:36:43.939 Demilade Agboola: When we do a weak start, they just usually had, like, dynamic,
389 00:36:44.290 ⇒ 00:36:47.809 Demilade Agboola: Filters to be able to look at whatever they need to look at.
390 00:36:50.430 ⇒ 00:36:50.970 Uttam Kumaran: So they were able.
391 00:36:50.970 ⇒ 00:36:55.589 Demilade Agboola: Yeah, they were able to just change the date filters to look at what they wanted to look at.
392 00:36:55.750 ⇒ 00:37:00.760 Demilade Agboola: Alternatively, they sometimes just needed the previous day, like, values.
393 00:37:00.990 ⇒ 00:37:03.799 Demilade Agboola: So those are usually what they used to look at,
394 00:37:06.240 ⇒ 00:37:12.249 Demilade Agboola: So they usually use the date filters to be able to go back and do, like, months or date, and just kind of get an idea of what’s going on.
395 00:37:12.720 ⇒ 00:37:14.879 Demilade Agboola: Or, like, previous month compared to last month.
396 00:37:19.240 ⇒ 00:37:20.899 Mustafa Raja: Okay, how do you feel about this?
397 00:37:26.920 ⇒ 00:37:30.459 Greg Stoutenburg: I’m trying to see where Omni has any such filters.
398 00:37:31.400 ⇒ 00:37:32.489 Greg Stoutenburg: I mean, that’s a great answer.
399 00:37:32.490 ⇒ 00:37:33.579 Mustafa Raja: Oh, yeah, yeah.
400 00:37:33.580 ⇒ 00:37:34.340 Greg Stoutenburg: Great answer to the question.
401 00:37:34.340 ⇒ 00:37:38.319 Mustafa Raja: Yeah, we could have dashboard-wide filters, but…
402 00:37:38.880 ⇒ 00:37:40.869 Mustafa Raja: We can have diamond wire filters.
403 00:37:41.340 ⇒ 00:37:46.579 Mustafa Raja: And then I think we could also have jar twice filters also.
404 00:37:47.980 ⇒ 00:37:52.489 Mustafa Raja: I’m not sure about chart-wise, but I’ve seen, dashboard-wide filters.
405 00:37:52.860 ⇒ 00:37:56.940 Mustafa Raja: That apply to all of the charts, or selected charts that we seem to select.
406 00:37:58.030 ⇒ 00:38:05.400 Greg Stoutenburg: Yeah, I’m looking at it right now, yeah. You just go, you go, File, And explore, and…
407 00:38:07.040 ⇒ 00:38:09.440 Greg Stoutenburg: Click around to your heart’s content. Yep.
408 00:38:09.580 ⇒ 00:38:16.530 Demilade Agboola: Also, like, Mustafa, does this data use… have you created, like, the new data sets for these topics, or is it using, like, the summary tables?
409 00:38:17.600 ⇒ 00:38:31.470 Mustafa Raja: It’s using summary tables, because it’s auto-selecting that, but, the details table… the details are also in there, so the joins are there if it wants to take a look. But it’s choosing summary by its choice.
410 00:38:32.010 ⇒ 00:38:33.229 Demilade Agboola: Okay, gotcha.
411 00:38:36.320 ⇒ 00:38:43.360 Demilade Agboola: Alright, so I looked at, like, the tzapatide. It’s directionally, like, similar, but the numbers don’t match.
412 00:38:43.470 ⇒ 00:38:44.940 Demilade Agboola: It’s slightly off.
413 00:38:47.660 ⇒ 00:38:50.450 Mustafa Raja: Yeah, I think… mmm… hmm…
414 00:38:54.010 ⇒ 00:38:54.930 Mustafa Raja: Okay.
415 00:38:57.980 ⇒ 00:38:59.619 Greg Stoutenburg: There’s a particular value where it looks like it’s off?
416 00:39:00.860 ⇒ 00:39:09.529 Demilade Agboola: So for instance, it says… Give me one sec… Unless I’m using a different…
417 00:39:09.860 ⇒ 00:39:13.019 Demilade Agboola: So I’m looking at the Products for us LTV dashboard.
418 00:39:13.850 ⇒ 00:39:18.619 Demilade Agboola: And so for the month of February till date.
419 00:39:18.980 ⇒ 00:39:24.450 Demilade Agboola: it seemed the NCOC is 287, 90.
420 00:39:25.390 ⇒ 00:39:28.310 Demilade Agboola: Right? 20… like, $287.90.
421 00:39:29.480 ⇒ 00:39:36.170 Demilade Agboola: But when I’m looking at the NCAC in… The dashboard I’m seeing 343.
422 00:39:39.720 ⇒ 00:39:41.450 Greg Stoutenburg: What’s the name of the chart in the dashboard?
423 00:39:43.470 ⇒ 00:39:47.569 Demilade Agboola: Products for us LTV dashboard in… that’s in Tableau.
424 00:39:50.590 ⇒ 00:39:53.160 Greg Stoutenburg: Okay. So let’s hold that number.
425 00:39:53.420 ⇒ 00:39:57.070 Greg Stoutenburg: Producto SLTV dashboard, yep. The one that says Draft.
426 00:39:57.230 ⇒ 00:39:58.610 Greg Stoutenburg: Oh, no, sorry.
427 00:39:59.100 ⇒ 00:40:01.860 Demilade Agboola: I can show you the slang. Yeah, yeah, slang.
428 00:40:01.860 ⇒ 00:40:02.370 Greg Stoutenburg: Yeah, yeah, yeah.
429 00:40:02.370 ⇒ 00:40:02.829 Mustafa Raja: She’s the same.
430 00:40:02.830 ⇒ 00:40:05.639 Greg Stoutenburg: No, I just want to make sure we’re looking at exactly the same thing.
431 00:40:06.160 ⇒ 00:40:12.789 Greg Stoutenburg: And I’m seeing the date filter Specifically on December 1st, 2025.
432 00:40:15.240 ⇒ 00:40:17.889 Demilade Agboola: Yes, yeah, so I moved it to the 1st of…
433 00:40:19.100 ⇒ 00:40:22.969 Mustafa Raja: We can take a look at the query itself if we want, you know. Sure.
434 00:40:23.440 ⇒ 00:40:25.270 Mustafa Raja: Hey, Gustava, can we…
435 00:40:25.270 ⇒ 00:40:27.330 Greg Stoutenburg: Mustafa, can we start by just asking Blobby?
436 00:40:27.780 ⇒ 00:40:28.600 Demilade Agboola: Yeah.
437 00:40:29.190 ⇒ 00:40:39.119 Greg Stoutenburg: Let’s start by just asking Bobby, and try to test this out as the user first. So let’s… let’s ask, well, I don’t know, how would you phrase the question, Demi?
438 00:40:39.720 ⇒ 00:40:41.579 Greg Stoutenburg: About this particular data point.
439 00:40:42.390 ⇒ 00:40:46.360 Demilade Agboola: So, can I look at the query again? So I understand what it’s trying to do?
440 00:40:47.230 ⇒ 00:40:53.610 Demilade Agboola: So it’s basically saying, for every… where the first order month is this, Gotcha.
441 00:40:55.650 ⇒ 00:40:59.180 Demilade Agboola: So it’s looking at the cohort revenue retention summary.
442 00:40:59.810 ⇒ 00:41:04.970 Demilade Agboola: Okay, so what I’m looking at is slightly different. I’m just looking at the… the dashboard.
443 00:41:05.330 ⇒ 00:41:11.050 Demilade Agboola: for… each product, and the NCAC for the products in the month.
444 00:41:11.640 ⇒ 00:41:18.030 Demilade Agboola: it’s not viewing it by any cohort, it’s just, like, in the entire month, what was the NCAC for trisepatide?
445 00:41:18.590 ⇒ 00:41:27.239 Demilade Agboola: for the new users, basically. How much did it cost to acquire each of these new users for today’s website? That’s the last word that I’m looking at.
446 00:41:32.080 ⇒ 00:41:36.550 Mustafa Raja: I mean, this data is coming from… even if you not look at the query.
447 00:41:39.980 ⇒ 00:41:46.320 Mustafa Raja: I think if we… if we remove this one, this filter, do we have this filter over there also?
448 00:41:46.810 ⇒ 00:41:51.120 Demilade Agboola: No, no, so I’m just going month by month and looking at the numbers and trying to compare it with this.
449 00:41:52.540 ⇒ 00:41:55.710 Mustafa Raja: Okay. Yeah, I’m just wondering if this first-order month filter is there.
450 00:41:57.570 ⇒ 00:42:00.379 Demilade Agboola: Give me one second, let me also try and look at something else.
451 00:42:08.900 ⇒ 00:42:10.810 Demilade Agboola: The quant revenue retention.
452 00:43:11.330 ⇒ 00:43:20.470 Demilade Agboola: Because I’m wondering if the reason why there’s a slight disparity is because it’s looking at it from a cohort perspective, it’s also looking at follow-up orders that the cohorts made.
453 00:43:20.890 ⇒ 00:43:22.599 Demilade Agboola: So that would lower the NCAC.
454 00:43:29.750 ⇒ 00:43:36.079 Mustafa Raja: Yeah, month since first order is set to minus 1, which indicates the current month, right?
455 00:43:42.440 ⇒ 00:43:43.890 Mustafa Raja: Or, like, whenever they joined.
456 00:43:44.650 ⇒ 00:43:45.920 Mustafa Raja: Elementary.
457 00:44:41.180 ⇒ 00:44:47.520 Mustafa Raja: Hmm… So even if I don’t have any filters for February 2026, this summary
458 00:44:47.680 ⇒ 00:44:50.799 Mustafa Raja: Table is just giving out these figures, you know?
459 00:44:52.800 ⇒ 00:44:55.829 Demilade Agboola: So, I think… Where do I put it?
460 00:45:01.370 ⇒ 00:45:03.189 Mustafa Raja: And, and I don’t have any, any…
461 00:45:03.190 ⇒ 00:45:03.570 Demilade Agboola: The number?
462 00:45:03.570 ⇒ 00:45:04.000 Mustafa Raja: on this.
463 00:45:04.000 ⇒ 00:45:08.570 Demilade Agboola: So the numbers actually match the numbers if you were to… can I quickly share my dash? Can I quickly share my screen?
464 00:45:08.570 ⇒ 00:45:09.869 Mustafa Raja: It’s what happens on that.
465 00:45:10.970 ⇒ 00:45:18.579 Demilade Agboola: Alright, so, high level… The numbers do match what you will see in…
466 00:45:21.740 ⇒ 00:45:23.120 Demilade Agboola: 6 months?
467 00:45:23.580 ⇒ 00:45:28.899 Demilade Agboola: In the marketing dashboard. So, you’ll see, like, it’s 184 point something, so it’s 185 here.
468 00:45:29.650 ⇒ 00:45:32.939 Demilade Agboola: So you can kind of see that the numbers are matching.
469 00:45:34.210 ⇒ 00:45:38.640 Demilade Agboola: However, when I look in here…
470 00:45:40.050 ⇒ 00:45:42.999 Demilade Agboola: that’s where I’m like, so, based off the products.
471 00:45:44.820 ⇒ 00:45:48.079 Demilade Agboola: it… the NCACs appear to be different.
472 00:45:49.540 ⇒ 00:45:53.029 Demilade Agboola: So, my guess is I would have to look into it.
473 00:45:53.270 ⇒ 00:46:00.699 Demilade Agboola: It’s either this… Is you looking at less data, like, less, ad spend numbers than…
474 00:46:00.970 ⇒ 00:46:05.219 Demilade Agboola: That other dashboard, so that’s why this has, like, slightly.
475 00:46:05.220 ⇒ 00:46:07.010 Mustafa Raja: Yeah, yeah, that makes sense.
476 00:46:07.010 ⇒ 00:46:07.650 Demilade Agboola: war.
477 00:46:08.980 ⇒ 00:46:10.490 Demilade Agboola: because, like.
478 00:46:13.730 ⇒ 00:46:20.679 Demilade Agboola: Or, because this is about, like, the first order product, It’s looking at…
479 00:46:22.960 ⇒ 00:46:26.440 Demilade Agboola: It’s looking at more… it’s looking at more orders.
480 00:46:26.550 ⇒ 00:46:32.680 Demilade Agboola: how do I put it? I think the other dashboard is looking at the first order as a general principle.
481 00:46:33.620 ⇒ 00:46:51.999 Demilade Agboola: Right? So, like, this is their first order ever placed, and this is the NCAC to acquire those customers. Whereas this is looking at the first time they ordered this product. So they may have ordered something before, but now they’re ordering tri-septide for the first time, and now that’s… that might count them in.
482 00:46:52.430 ⇒ 00:46:54.810 Demilade Agboola: And that’s why you might have slightly different numbers.
483 00:46:55.410 ⇒ 00:46:56.180 Mustafa Raja: Okay.
484 00:46:56.850 ⇒ 00:47:07.419 Greg Stoutenburg: Yeah, it’s right there. LTV reflects cumulative revenue of all future purchases, regardless of product. So it’s, yeah, if they have just ordered Tezepatide for the first time in February.
485 00:47:07.840 ⇒ 00:47:17.190 Greg Stoutenburg: What’s their LTV to CAC ratio for any future purchase at all, whether Tizepatide or something else?
486 00:47:18.310 ⇒ 00:47:18.970 Mustafa Raja: Yeah.
487 00:47:19.760 ⇒ 00:47:20.120 Greg Stoutenburg: Yep.
488 00:47:20.120 ⇒ 00:47:25.069 Demilade Agboola: So the same call type is $683 for this, and for here.
489 00:47:25.460 ⇒ 00:47:27.239 Demilade Agboola: Okay, it’s also saying 683.
490 00:47:28.450 ⇒ 00:47:29.100 Greg Stoutenburg: Cool.
491 00:47:31.510 ⇒ 00:47:35.080 Demilade Agboola: I’m gonna see if the quad sizes are the same… One second…
492 00:47:36.530 ⇒ 00:47:41.249 Demilade Agboola: Then, my guess is, let’s say in 1620.
493 00:47:44.290 ⇒ 00:47:48.610 Demilade Agboola: And here is also, I mean, 11 offices, not that significant.
494 00:47:49.010 ⇒ 00:47:54.080 Demilade Agboola: So my guess is, yeah, the value we’re looking at in terms of the ad spend?
495 00:47:55.660 ⇒ 00:48:05.180 Demilade Agboola: is what’s much lower here than the other dataset. So, I don’t think the query did anything wrong. I don’t think the, like, Blobby did anything wrong, I just think it’s…
496 00:48:05.630 ⇒ 00:48:11.559 Demilade Agboola: A difference in how… The dataset itself is calculated.
497 00:48:13.380 ⇒ 00:48:16.119 Demilade Agboola: So I’ll just look into that, and I’ll let you know.
498 00:48:23.890 ⇒ 00:48:36.699 Greg Stoutenburg: Okay, yep, that sounds good. So since it looks like we know that we’re getting the right data in and put in front of the user, I think this will just be, like, an education point, so we can tell users, hey, just so you know, if you run the same
499 00:48:36.700 ⇒ 00:48:45.890 Greg Stoutenburg: query that, you would have expected to see a dashboard for. You know, here’s what to look out for to make sure that you’re looking at the number that means what you think it means.
500 00:48:47.810 ⇒ 00:48:48.570 Mustafa Raja: Yeah.
501 00:48:49.810 ⇒ 00:48:50.880 Mustafa Raja: Okay.
502 00:48:52.030 ⇒ 00:48:53.849 Mustafa Raja: Okay, what’s the next steps here, though?
503 00:48:55.610 ⇒ 00:48:59.440 Mustafa Raja: We have some more P0s to move, right?
504 00:49:00.540 ⇒ 00:49:18.320 Greg Stoutenburg: yeah, let’s get all the P0s in, and I’ll do a training dry run tomorrow during the CSO meeting, and the goal will be to get everything moved over, everything that’s in Tableau as a dashboard, to have that in Omni by the end of the week, and, I mean, you know, always the sooner the better.
505 00:49:18.340 ⇒ 00:49:24.429 Greg Stoutenburg: And start training Omni, sorry, Eden folks, on Omni at the beginning of next week.
506 00:49:25.630 ⇒ 00:49:38.850 Mustafa Raja: Okay, so, for this dashboard, this P0 dashboard that I have built, Demilada, there are some, missing things here, and I’ll link with you, either tomorrow before our stand-ups.
507 00:49:38.850 ⇒ 00:49:55.550 Mustafa Raja: to sort of discuss about those and how we can mitigate that. I’ll be working on other PG rules. And I have a work session in 5 minutes, so after that, I’ll link this Omni instance to our GitHub, so we can work with MCP also.
508 00:49:57.370 ⇒ 00:50:00.990 Demilade Agboola: Sounds good. And what can you.
509 00:50:01.100 ⇒ 00:50:08.919 Greg Stoutenburg: Is it possible to start getting the context for all of the topics, for all of the dashboards we’re gonna put in, just running in the background?
510 00:50:08.920 ⇒ 00:50:21.250 Mustafa Raja: Yeah, it’s just… it’s just, we don’t know how, how many more topics we are going to, you know, create in. Now, on my local machine, I have that, I have that all set up, right?
511 00:50:22.520 ⇒ 00:50:38.049 Mustafa Raja: So I should… should I work on getting the rest of the topics in? I mean, we haven’t discussed that, right? We haven’t discussed on how the topics, are going to look like for dashboards other than P0.
512 00:50:38.820 ⇒ 00:50:57.190 Greg Stoutenburg: Here, I have… everything that you’ve seen, so company performance dashboards, product performance daily snapshots, marketing attribution, and Pharmacy ops, and finance, those can be… that’s gonna… that covers all of the dashboards that are gonna go in. Let me grab the… see you, Tom.
513 00:51:00.310 ⇒ 00:51:04.870 Greg Stoutenburg: I just sent you this in… Slack.
514 00:51:04.870 ⇒ 00:51:07.180 Mustafa Raja: Let me share my screen, actually.
515 00:51:07.180 ⇒ 00:51:07.500 Greg Stoutenburg: Okay.
516 00:51:07.500 ⇒ 00:51:09.480 Mustafa Raja: Discusses, you have 5 minutes.
517 00:51:09.690 ⇒ 00:51:16.700 Mustafa Raja: Okay. Okay, so till this dashboard, we have the topics that we need, right?
518 00:51:17.070 ⇒ 00:51:21.029 Mustafa Raja: Moving from… moving on from here… We need to see…
519 00:51:21.210 ⇒ 00:51:23.949 Mustafa Raja: If our topics can entertain these dashboards.
520 00:51:24.560 ⇒ 00:51:25.210 Greg Stoutenburg: Yeah.
521 00:51:25.750 ⇒ 00:51:29.159 Mustafa Raja: Right, so I guess I could take a look tomorrow.
522 00:51:29.310 ⇒ 00:51:37.010 Mustafa Raja: And then maybe, write a doc on what topics we need in there. Maybe I could work on that.
523 00:51:37.360 ⇒ 00:51:41.460 Mustafa Raja: Okay. Yeah, I guess this… this we could discuss tomorrow, then.
524 00:51:42.500 ⇒ 00:51:43.820 Greg Stoutenburg: Okay, sounds good.
525 00:51:44.430 ⇒ 00:51:45.040 Mustafa Raja: Yeah.
526 00:51:46.620 ⇒ 00:51:47.720 Mustafa Raja: Okay.
527 00:51:49.090 ⇒ 00:51:50.200 Greg Stoutenburg: Cool. Thanks.
528 00:51:50.200 ⇒ 00:51:50.790 Mustafa Raja: Thanks, all.
529 00:51:50.790 ⇒ 00:51:52.910 Greg Stoutenburg: Alright, thanks guys. See ya.
530 00:51:53.430 ⇒ 00:51:54.589 Mustafa Raja: Have a good day. Bye.
531 00:51:54.780 ⇒ 00:51:55.490 Greg Stoutenburg: You too.