Meeting Title: Phoenix Project Dry Run Date: 2026-01-29 Meeting participants: Uttam Kumaran, Mustafa Raja, Greg Stoutenburg, Demilade Agboola
WEBVTT
1 00:00:29.860 ⇒ 00:00:30.460 Mustafa Raja: Right.
2 00:00:32.159 ⇒ 00:00:33.049 Uttam Kumaran: Hello.
3 00:00:34.640 ⇒ 00:00:35.320 Greg Stoutenburg: Hey, guys.
4 00:00:35.910 ⇒ 00:00:36.690 Uttam Kumaran: A…
5 00:00:58.620 ⇒ 00:01:02.340 Uttam Kumaran: Yeah, I was thinking we just do a dry run of stuff.
6 00:01:06.160 ⇒ 00:01:07.199 Greg Stoutenburg: Yeah, sounds good.
7 00:01:08.080 ⇒ 00:01:08.850 Uttam Kumaran: Okay.
8 00:01:12.560 ⇒ 00:01:14.859 Greg Stoutenburg: Looks like we’re just waiting for Demi since I’ll have most of the slides.
9 00:01:15.300 ⇒ 00:01:16.070 Uttam Kumaran: Yes.
10 00:01:50.100 ⇒ 00:01:50.970 Mustafa Raja: Hey, Demi.
11 00:01:56.710 ⇒ 00:01:58.060 Demilade Agboola: Hello, how’s everyone doing?
12 00:01:58.350 ⇒ 00:01:58.879 Uttam Kumaran: There you go.
13 00:01:59.600 ⇒ 00:02:00.629 Greg Stoutenburg: Hey, doing well, Drew?
14 00:02:06.410 ⇒ 00:02:08.570 Greg Stoutenburg: And it’s important to be out for us.
15 00:02:12.990 ⇒ 00:02:15.560 Greg Stoutenburg: Alright, Debbie, you want to kick it off, since you have most of the slides?
16 00:02:17.020 ⇒ 00:02:17.900 Demilade Agboola: Hmm, sure.
17 00:02:19.800 ⇒ 00:02:23.550 Greg Stoutenburg: So, Tom, you just want us to just… just start, like, we’re going?
18 00:02:23.550 ⇒ 00:02:37.930 Uttam Kumaran: Yeah, I think just before we start, I think I called Caitlin, yesterday. I think overall feedback is good. I think the biggest thing just to remember is, like, they’re very early, so… I think, like, we just really have to, like…
19 00:02:38.460 ⇒ 00:02:45.280 Uttam Kumaran: dumb everything down, and maybe dumb down is not, like, you know, the best term here, but, like, really…
20 00:02:45.570 ⇒ 00:03:01.659 Uttam Kumaran: spend time to make sure they’re, like, understanding, because they’ve never done anything in, like, data this significant before. So that’s probably the only call-out, I would say, especially to both y’all, Demi and Greg, is just really maintain and make sure that they’re coming along with us, like.
21 00:03:01.800 ⇒ 00:03:11.210 Uttam Kumaran: even explanations of, like, why we’re using tools, and, like, things that may seem small to us, I think I just want to really make sure we’re patient with them.
22 00:03:12.780 ⇒ 00:03:18.339 Uttam Kumaran: So yeah, that would be my… my primary feedback. But yeah, let’s go through it, and I can call out if we’re…
23 00:03:18.480 ⇒ 00:03:22.200 Uttam Kumaran: If we’re… we need to slow down anywhere, or… yeah, happy to.
24 00:03:23.670 ⇒ 00:03:24.380 Greg Stoutenburg: Got it.
25 00:03:26.650 ⇒ 00:03:32.820 Demilade Agboola: Alright, got it, so I’ll keep that in mind while… Talking today.
26 00:03:35.430 ⇒ 00:03:47.969 Demilade Agboola: So, high level… so I’m going to be faster than I will in the actual call, because we don’t have as much time. So high level, we’re just going to go over what we did this week. So product analytics workstream.
27 00:03:48.680 ⇒ 00:03:53.759 Demilade Agboola: we were able to align on how we want to instrument, amplitude for Phoenix.
28 00:03:54.140 ⇒ 00:04:00.499 Demilade Agboola: And as well as make some other progress in terms of, like, building out the designs and updating the Gantt chart.
29 00:04:00.860 ⇒ 00:04:05.000 Uttam Kumaran: On the data platform and analytics stream, we’re able to…
30 00:04:05.000 ⇒ 00:04:08.199 Demilade Agboola: you know, start work on the dbt setup on Mother Doc.
31 00:04:08.630 ⇒ 00:04:13.159 Demilade Agboola: As well as, like, the Salesforce and Polyatomic integration.
32 00:04:13.510 ⇒ 00:04:16.910 Demilade Agboola: And we’ve also done some ad hoc Work.
33 00:04:17.100 ⇒ 00:04:20.090 Demilade Agboola: For, the default team.
34 00:04:21.760 ⇒ 00:04:29.789 Demilade Agboola: So again, this kind of goes deeper into details, so I will just kind of reinforce and go into, deeper details into what we did this week.
35 00:04:30.750 ⇒ 00:04:35.159 Demilade Agboola: So, for dbt setup, we’re just starting up, a dbt…
36 00:04:35.520 ⇒ 00:04:41.189 Demilade Agboola: core setup, where we will have, like, our local instance of dbt connecting to…
37 00:04:41.410 ⇒ 00:04:47.069 Demilade Agboola: Mother dock, and use that to be able to start Creating standard modeling flows.
38 00:04:47.810 ⇒ 00:05:00.649 Demilade Agboola: We’ve also been able to do a performance table within our metrics dashboard, where we’re able to show the inbound performance for different companies, based off of
39 00:05:00.880 ⇒ 00:05:06.010 Demilade Agboola: Their web… their website traffic, as well as conversion, in terms of submission.
40 00:05:06.910 ⇒ 00:05:15.050 Demilade Agboola: And then we’re also able to do, vendor analysis, where we’re able to use the new data from our refined
41 00:05:15.250 ⇒ 00:05:21.660 Demilade Agboola: Company data sets to… We run our previously done vendor analysis.
42 00:05:23.430 ⇒ 00:05:27.599 Demilade Agboola: So the inbound dashboard that was mentioned before, this is what it looks like.
43 00:05:27.760 ⇒ 00:05:31.169 Demilade Agboola: We’ve been able to show, you know, total visits in the last month.
44 00:05:31.470 ⇒ 00:05:41.220 Demilade Agboola: The name of the company, as well as the… or name of the domain, as well as the submissions of the form over that time period.
45 00:05:41.450 ⇒ 00:05:45.740 Demilade Agboola: So we can use that to show the conversion rates, and the link to the dashboard is here.
46 00:05:46.340 ⇒ 00:05:49.509 Demilade Agboola: And I think this will all be handed over to Greg.
47 00:05:50.620 ⇒ 00:05:59.410 Greg Stoutenburg: Yeah, thanks for the workshop we did last week, where you’re able to explain what you’re doing with Phoenix, and what the rollout timeline looks like for that.
48 00:05:59.410 ⇒ 00:06:24.299 Greg Stoutenburg: I think we made good progress in just understanding, better, at least for me, what, what Phoenix is going to do, and how this is going to be a change for default. And I got to spend some time with Nandika this week, understanding what the new flows will look like. And she gave me access to a Notion page that I’ve got here that shows your PLG pricing and packaging that you’re going to be rolling out with Phoenix, as well as all the Figma designs.
49 00:06:24.300 ⇒ 00:06:45.299 Greg Stoutenburg: for what the user experience is going to look like. So, with that, Mustafa and I were able to rearrange the timeline so that we can make sure that we’re tracking the things that you want to have tracked in order to answer valuable questions with the Phoenix launch, but also to do this in an iterative way, so that as Phoenix is being rolled out.
50 00:06:45.300 ⇒ 00:07:04.650 Greg Stoutenburg: the implementation of the analytics that we’ll be tracking is going along with it. We don’t want to wait until everything is done, because then we’ll have a rush to try to get everything stood up after Phoenix is launched. So, we’ve got this plan that we’ll walk through in a moment here to show that we’ve got a plan in place that’ll allow us to do that.
51 00:07:06.350 ⇒ 00:07:06.930 Uttam Kumaran: Cool.
52 00:07:08.630 ⇒ 00:07:10.089 Greg Stoutenburg: How was that, right? Level of depth?
53 00:07:10.880 ⇒ 00:07:17.319 Uttam Kumaran: I think that was good. Yeah, I think maybe I would just pause there to just make sure that, like, Caitlin’s with you, and that she agrees.
54 00:07:18.500 ⇒ 00:07:19.290 Greg Stoutenburg: Cool.
55 00:07:20.890 ⇒ 00:07:22.810 Greg Stoutenburg: Mustafa, you wanna talk through this part?
56 00:07:22.810 ⇒ 00:07:23.400 Mustafa Raja: Yeah.
57 00:07:23.880 ⇒ 00:07:25.419 Mustafa Raja: Let me share my screen.
58 00:07:27.270 ⇒ 00:07:29.130 Mustafa Raja: Can I share my screen? Namely?
59 00:07:33.550 ⇒ 00:07:35.200 Mustafa Raja: Okay…
60 00:07:35.560 ⇒ 00:07:52.579 Mustafa Raja: Okay, so, we had the, stakeholder kickoff workshops. Now, next week, yes, we would start, documenting, events and user properties based on, the Figma, or, or what else we can get about Figma, about Phoenix.
61 00:07:52.580 ⇒ 00:08:02.180 Mustafa Raja: And then, we will, have a master event tracking template, and, funnel, funnel definitions.
62 00:08:02.700 ⇒ 00:08:05.979 Mustafa Raja: And then, mid-Feb is,
63 00:08:06.040 ⇒ 00:08:18.080 Mustafa Raja: where we are expecting a Phoenix to roll out, and so, by then we will start, implementing the new organization setup,
64 00:08:18.080 ⇒ 00:08:30.019 Mustafa Raja: And then we will start instrumentation of amplitude within Phoenix. And then, two weeks into that, we’ll start, building up dashboards.
65 00:08:30.980 ⇒ 00:08:39.949 Mustafa Raja: And then, after the dashboard, we’ll have some training, and handoffs, and then we’ll plan, next steps.
66 00:08:40.280 ⇒ 00:08:42.399 Mustafa Raja: Let me know if that sounds good.
67 00:08:45.240 ⇒ 00:08:45.790 Uttam Kumaran: Cool.
68 00:08:46.180 ⇒ 00:08:58.690 Greg Stoutenburg: And you, Tom, just for you, what Mustafa and I did, basically, to revise this Gantt chart, is we pushed back and stretched out a little bit the initial period. The reason being that I’ve got to work off of Figma designs instead of a product, and so…
69 00:08:58.690 ⇒ 00:08:59.140 Uttam Kumaran: Yeah.
70 00:08:59.140 ⇒ 00:09:15.199 Greg Stoutenburg: the hope is, alright, get a lot of this stuff documented, and then, you know, if mid-February, because Caitlin kept saying things like, you know, it’ll be into February before we start rolling out Phoenix, then what we can say is, suppose, for example, that it’s just the sign-up flow for Phoenix that’s able to go live in…
71 00:09:15.230 ⇒ 00:09:28.779 Greg Stoutenburg: whatever, third week of February, then that will be the week that we’re working with, you know, whoever’s going to be doing the engineering portion of it. That’ll be the week, then, that they’re putting that code in, so that that data starts coming into Amplitude.
72 00:09:28.940 ⇒ 00:09:33.539 Uttam Kumaran: Okay. And so on for all of the successive stages of Phoenix being rolled out.
73 00:09:34.600 ⇒ 00:09:35.190 Uttam Kumaran: Okay.
74 00:09:37.760 ⇒ 00:09:43.259 Uttam Kumaran: So I think that’s probably the biggest thing on the PA side, is just to be like, look, we’re gonna parallel path alongside you.
75 00:09:43.270 ⇒ 00:09:46.709 Greg Stoutenburg: Yeah. So that as soon as the feature launches, we’re able to show data.
76 00:09:47.100 ⇒ 00:09:47.650 Greg Stoutenburg: Yeah.
77 00:09:49.530 ⇒ 00:09:52.739 Uttam Kumaran: I guess my only point… yeah, sorry, go ahead, Demi.
78 00:09:53.340 ⇒ 00:09:57.080 Demilade Agboola: I was just gonna say, okay, I was going to ask if you had any feedback on the presentation so far.
79 00:09:57.550 ⇒ 00:10:00.689 Uttam Kumaran: Yeah, I was just gonna say, like, on the modeling side, I think…
80 00:10:00.980 ⇒ 00:10:18.449 Uttam Kumaran: I want to just talk as much as we can, like, I think I want to move us past talking about a couple of keywords that, like, make me throw up for this project are S3, Polyatomic, dbt, like, let’s see how we can push to talk about Omni and the reporting, like, within Omni.
81 00:10:18.850 ⇒ 00:10:24.710 Uttam Kumaran: Because otherwise, we’re just gonna continue to get stuck in, like, them having questions about infrastructure.
82 00:10:25.020 ⇒ 00:10:35.439 Uttam Kumaran: Like, so how much can we… can we spend any time today, actually, like, in Omni? Do we know if they’re using any of the stuff we’ve already put out? Like, that’s sort of the questions I have.
83 00:10:39.440 ⇒ 00:10:52.250 Demilade Agboola: I don’t necessarily know how much they are actively using stuff. I know, like, there are ad hoc things that they might make requests for, and stuff has been handling that, and I’m pushing that into Omni, so an example would be the…
84 00:10:53.110 ⇒ 00:10:58.930 Demilade Agboola: inbound, performance, basically, by the different domains.
85 00:10:59.210 ⇒ 00:11:03.390 Demilade Agboola: So obviously that’s an ad hoc request, we’re able to meet it.
86 00:11:03.460 ⇒ 00:11:22.160 Demilade Agboola: And we’ve also been able to do some other stuff, over the past couple of weeks for Beth and some other people on the team. So there is some, like, analysis that we’re doing, but it hasn’t yet matured to the point where it can stand on itself, because obviously the data flow isn’t necessarily as ideal as it needs to be.
87 00:11:22.270 ⇒ 00:11:23.200 Demilade Agboola: For that.
88 00:11:23.390 ⇒ 00:11:30.810 Demilade Agboola: So yeah, I mean, yeah, we could definitely show that, like, you know, Omni has the… some of the data that we are using.
89 00:11:31.190 ⇒ 00:11:34.160 Demilade Agboola: for the analysis, and maybe I can hop on the…
90 00:11:34.280 ⇒ 00:11:47.879 Demilade Agboola: inbound, performance. I also know Caitlin asked for some more, like, she talked about range being interesting, so I could just use this opportunity to ask her what she meant about that, and get some perspective.
91 00:11:48.210 ⇒ 00:11:52.659 Demilade Agboola: As to how much you would like to dive into the inbound
92 00:11:53.180 ⇒ 00:11:55.889 Demilade Agboola: charts out. Let me show you the inbound charts.
93 00:11:56.100 ⇒ 00:11:58.129 Demilade Agboola: The inbound chart that we created for them.
94 00:11:59.230 ⇒ 00:12:04.000 Demilade Agboola: And, like, what other ways they’ll like to slice and dice this, potentially.
95 00:12:04.240 ⇒ 00:12:09.669 Demilade Agboola: So yeah, we could maybe harp a bit on, like, what we can do with what we have, versus…
96 00:12:09.850 ⇒ 00:12:12.939 Demilade Agboola: Just like, hey, we’re still stuck.
97 00:12:13.070 ⇒ 00:12:18.240 Demilade Agboola: Even though we do… we still do have it as a… brisk, because…
98 00:12:18.880 ⇒ 00:12:26.600 Demilade Agboola: ultimately, we do need to be able to, like, say, hey, what’s the progress on the S3 bucket that Nautica is creating?
99 00:12:27.010 ⇒ 00:12:27.860 Demilade Agboola: Boss.
100 00:12:27.860 ⇒ 00:12:28.560 Uttam Kumaran: Okay.
101 00:12:28.750 ⇒ 00:12:30.410 Uttam Kumaran: So, can you go back to 7?
102 00:12:34.920 ⇒ 00:12:37.759 Uttam Kumaran: Yeah, I wonder if, like, is this already in Omni?
103 00:12:38.860 ⇒ 00:12:39.620 Demilade Agboola: Yes, it is.
104 00:12:39.660 ⇒ 00:12:40.160 Mustafa Raja: Yeah.
105 00:12:40.160 ⇒ 00:12:47.260 Uttam Kumaran: So this, I guess, like, I think this would be a good time, let’s just pull that up. Yeah, okay, okay, sorry. Yeah. Let’s pull this up, and then…
106 00:12:47.490 ⇒ 00:12:49.620 Uttam Kumaran: I mean, I also think, like.
107 00:12:49.940 ⇒ 00:12:54.840 Uttam Kumaran: one thing that I just wanted… want to do for a few clients as we’re pushing out BI is just, like.
108 00:12:55.010 ⇒ 00:13:05.140 Uttam Kumaran: if you end up with free time in the meeting, like, I want to pull this up, because I’m worried that they’re not… they’re, like, thinking we’re still waiting for stuff, where there’s already a lot of information here.
109 00:13:05.370 ⇒ 00:13:08.819 Uttam Kumaran: That they can start using for understanding their business.
110 00:13:09.060 ⇒ 00:13:14.240 Uttam Kumaran: Like, for example, like, can you pull up the AI associated with this dashboard?
111 00:13:15.090 ⇒ 00:13:18.910 Uttam Kumaran: Like, can you pull up the blobby thing? Will it show up on the side?
112 00:13:19.780 ⇒ 00:13:20.990 Demilade Agboola: I’m trying to see…
113 00:13:27.970 ⇒ 00:13:29.609 Demilade Agboola: Is it enabled for this dashboard?
114 00:13:30.900 ⇒ 00:13:35.449 Uttam Kumaran: Yeah, I don’t think you have to re-enable it, but maybe it’s in the workbook view.
115 00:13:38.750 ⇒ 00:13:40.439 Demilade Agboola: So this is the workbook view.
116 00:13:41.470 ⇒ 00:13:44.439 Uttam Kumaran: Yeah, so go to the… go to the… Oh, I don’t know.
117 00:13:44.440 ⇒ 00:13:48.749 Demilade Agboola: I’m trying to see… Yeah, I’m just trying to see if, like, from the dashboard itself, I could…
118 00:13:50.730 ⇒ 00:13:51.400 Demilade Agboola: What the hell?
119 00:13:57.450 ⇒ 00:14:00.090 Uttam Kumaran: Usually, it’s just on the side, right? Oh yeah, click on that?
120 00:14:01.020 ⇒ 00:14:02.380 Uttam Kumaran: The AI assistant?
121 00:14:03.060 ⇒ 00:14:03.790 Uttam Kumaran: Oh.
122 00:14:04.990 ⇒ 00:14:11.000 Uttam Kumaran: Just see… just type in some… say, like, tell me about who are my more… most, valuable customers.
123 00:14:46.050 ⇒ 00:14:48.070 Uttam Kumaran: Nice, so this is in the Salesforce data.
124 00:14:51.840 ⇒ 00:15:03.320 Uttam Kumaran: So then, I think my question here is, like, this is coming from Salesforce, I think we also have this data from Hyperline already loaded here. So this, I guess, my more point, we can jump to the meeting, is…
125 00:15:03.470 ⇒ 00:15:17.070 Uttam Kumaran: if, like, we’re gonna run through, I think, the slides pretty quick. My suggestion is to, like, spend time with her in Omni, being like, hey, are you aware you can go use the AI already to ask questions? I really feel like they’re not using it that much.
126 00:15:18.150 ⇒ 00:15:18.810 Demilade Agboola: Okay.
127 00:15:19.000 ⇒ 00:15:19.520 Uttam Kumaran: Okay.
128 00:15:19.790 ⇒ 00:15:24.849 Demilade Agboola: Yeah, I guess part of it is that they kind of… some of them seem to be waiting for, like, the, like, live data.
129 00:15:25.010 ⇒ 00:15:26.540 Demilade Agboola: Versus,
130 00:15:27.990 ⇒ 00:15:32.449 Demilade Agboola: what exists right now, but we’ll see. We’ll just push them to see if they can start utilizing it.
131 00:15:32.820 ⇒ 00:15:33.400 Uttam Kumaran: Yeah, yeah.
132 00:15:33.400 ⇒ 00:15:33.980 Mustafa Raja: Yep.
133 00:15:34.730 ⇒ 00:15:36.359 Uttam Kumaran: Okay, perfect. Alright, let’s hop there.
134 00:15:36.610 ⇒ 00:15:37.459 Mustafa Raja: See you guys.
135 00:15:37.600 ⇒ 00:15:38.170 Uttam Kumaran: Okay, thanks.
136 00:15:38.170 ⇒ 00:15:38.680 Demilade Agboola: She goes.
137 00:15:38.680 ⇒ 00:15:39.250 Mustafa Raja: Bye.