Meeting Title: Default | Weekly Product Analytics Sync Date: 2025-09-03 Meeting participants: read.ai meeting notes, Scratchpad Notetaker, Rico Rejoso, Henry Zhao, Uttam Kumaran, vishalag, Caitlyn Vaughn
WEBVTT
1 00:02:13.560 ⇒ 00:02:14.560 vishalag: Hey, guys.
2 00:02:19.660 ⇒ 00:02:20.640 Henry Zhao: Hey, Michelle, how’s it going?
3 00:02:22.400 ⇒ 00:02:24.739 vishalag: Going pretty good. How’s going on your end?
4 00:02:26.090 ⇒ 00:02:26.950 Henry Zhao: What’s that?
5 00:02:28.100 ⇒ 00:02:29.830 vishalag: Lusain, how is it going on your end?
6 00:02:31.140 ⇒ 00:02:31.770 Henry Zhao: Good.
7 00:02:33.150 ⇒ 00:02:33.790 vishalag: Awesome.
8 00:02:33.790 ⇒ 00:02:37.009 Henry Zhao: I’m gonna give everyone an update today on the stuff that we’ve been doing.
9 00:02:37.900 ⇒ 00:02:47.729 vishalag: Yeah, I mean, for you also, like, you asked me for 3 events, right? Work for Published, meeting scheduled, and
10 00:02:48.210 ⇒ 00:02:49.819 vishalag: I think there was another one.
11 00:02:50.920 ⇒ 00:03:08.430 vishalag: workflow… workflow run with how many… what’s the status, how many errors or something, so that’s also in the pipe. That will be over with you, I think, as soon as possible. I mean, like, I’ve raised it… I’ve raised a ticket for that, and my development has been completed.
12 00:03:08.720 ⇒ 00:03:13.349 vishalag: Okay. It’s just that the review team once completes it, that will be with you.
13 00:03:16.400 ⇒ 00:03:18.709 Henry Zhao: Okay, let me share my screen.
14 00:03:21.940 ⇒ 00:03:26.069 Henry Zhao: A few things, Vishal,
15 00:03:26.630 ⇒ 00:03:29.830 Henry Zhao: We’ll start with the stuff with Lutam first.
16 00:03:30.250 ⇒ 00:03:34.229 Henry Zhao: What am I quickly?
17 00:03:41.080 ⇒ 00:03:42.160 Henry Zhao: Jesus said?
18 00:03:46.310 ⇒ 00:03:48.570 Henry Zhao: You need it.
19 00:03:49.280 ⇒ 00:03:51.910 Henry Zhao: So I’m trying to sign in FrameForge at default.com.
20 00:03:53.590 ⇒ 00:03:54.290 vishalag: Hmm.
21 00:03:54.500 ⇒ 00:03:57.840 Henry Zhao: I think it takes me to… Yep, you can just.
22 00:03:57.840 ⇒ 00:04:01.530 Uttam Kumaran: You could just… you could just let me know what the code is, because it’s my number, so…
23 00:04:02.640 ⇒ 00:04:04.460 Henry Zhao: Yours, 3273?
24 00:04:04.970 ⇒ 00:04:09.460 Uttam Kumaran: Yes, so… You can just ping me whenever if you need the code.
25 00:04:09.740 ⇒ 00:04:11.850 Henry Zhao: Okay, what’s the signature code right now?
26 00:04:12.490 ⇒ 00:04:16.720 Uttam Kumaran: It’s 854… 535.
27 00:04:17.700 ⇒ 00:04:18.360 Henry Zhao: Okay.
28 00:04:23.470 ⇒ 00:04:27.620 Henry Zhao: So, yeah, Vishal, it looks like we still don’t have access to the… oh, maybe we do.
29 00:04:27.620 ⇒ 00:04:31.510 Uttam Kumaran: Yeah, we have all the access, so yeah, thank you, Karen.
30 00:04:34.760 ⇒ 00:04:35.600 Henry Zhao: Okay, cool.
31 00:04:38.390 ⇒ 00:04:42.090 Henry Zhao: Yeah, I’m trying to figure out why things are being sent twice.
32 00:04:46.170 ⇒ 00:04:51.039 vishalag: And I don’t know why, like, it was… this was established, like, 2 years back.
33 00:04:51.370 ⇒ 00:04:52.579 Henry Zhao: And then…
34 00:04:52.900 ⇒ 00:05:02.519 Henry Zhao: So I’ll have to look into it, but I’m looking at, like, for example, engagement events, and, like, people are only doing things 2 times, four times, 6 times, so clearly things are being sent in twice.
35 00:05:02.790 ⇒ 00:05:05.040 Henry Zhao: Otherwise, it’s the biggest coincidence ever.
36 00:05:05.940 ⇒ 00:05:06.530 vishalag: Yeah.
37 00:05:07.630 ⇒ 00:05:10.100 Henry Zhao: Do we want to wait for Caitlin, or do we want to get started?
38 00:05:11.700 ⇒ 00:05:15.640 vishalag: I think let’s give her some few minutes more. Yeah.
39 00:05:15.640 ⇒ 00:05:17.520 Henry Zhao: I think we’re already pretty much aligned, so…
40 00:05:17.840 ⇒ 00:05:21.449 Henry Zhao: I think the… what we want to do is get everyone in here.
41 00:05:22.280 ⇒ 00:05:23.480 vishalag: Yeah, exactly.
42 00:05:23.870 ⇒ 00:05:25.860 Henry Zhao: But as in the meantime, I’ll talk to Utam,
43 00:05:26.350 ⇒ 00:05:39.300 Henry Zhao: with Vishal watching. So I have here the list of all the things that Caitlin asked for, Utem, and basically, I literally just copied and pasted, and for each one, I’m just saying, what do we need for a V1, or a Lite version, and what is the status?
44 00:05:39.520 ⇒ 00:05:50.420 Henry Zhao: So, the ones that I’ve marked in red are probably things that we need to work together as a team to figure out. So, when they ask, like, personas are who our current customer base is, what kind of companies are using defaults.
45 00:05:50.470 ⇒ 00:06:00.230 Henry Zhao: Are there trends in demograph… in firmographics or usage? We’re going to need to implement… complement that with probably some third-party user or firm data, because right now we don’t have any of that in Amplitude.
46 00:06:00.690 ⇒ 00:06:03.510 Henry Zhao: Not even, like, country, like, abs… like, nothing.
47 00:06:03.830 ⇒ 00:06:04.450 Uttam Kumaran: Okay, cool.
48 00:06:05.430 ⇒ 00:06:16.700 Henry Zhao: So I don’t know if that comes from, like, the signal work we’ve been doing, or do we need to use, like, DNB, or Clay, or whatever to get some of this information that Caitlin might need? But we’ll ask her when she gets here, like, what kind of…
49 00:06:16.850 ⇒ 00:06:23.289 Henry Zhao: things that she wants to care about? Like, does she care about the industry? Does she care about company size? Like, what are the…
50 00:06:23.670 ⇒ 00:06:27.580 Henry Zhao: things that we probably want to look at here. And then we’ll figure out as a team where to get that from.
51 00:06:31.040 ⇒ 00:06:36.140 Uttam Kumaran: Okay, I’m fine with this. So, can we sort this by status and see, like, what are the ones that we do have?
52 00:06:38.020 ⇒ 00:06:42.250 Henry Zhao: Yeah, we can sort it, but it’s already pretty much… In a row.
53 00:06:42.710 ⇒ 00:06:44.709 Henry Zhao: The greens are available.
54 00:06:45.690 ⇒ 00:06:52.639 Henry Zhao: So we’re just… we just have the very basics, but then this week, maybe we can start talking about adding the tab events, so…
55 00:07:09.980 ⇒ 00:07:17.320 Henry Zhao: So any of these other tabs, like clicking on companies, Adding a record… Meetings we’ve worked on already.
56 00:07:19.830 ⇒ 00:07:22.860 Henry Zhao: Forms? I’m still not sure, Michelle, so…
57 00:07:23.260 ⇒ 00:07:30.910 Henry Zhao: You said workflow creation completed has 3 amplitude events, right? We have form creation,
58 00:07:32.410 ⇒ 00:07:37.470 Henry Zhao: Which, it’s… I don’t think it’s this one, because this one we’ve made live last week, Vishal, but nothing is coming in.
59 00:07:38.340 ⇒ 00:07:39.230 Henry Zhao: For form creation.
60 00:07:39.230 ⇒ 00:07:39.620 vishalag: By me.
61 00:07:39.620 ⇒ 00:07:40.800 Henry Zhao: I’m a different name.
62 00:07:41.690 ⇒ 00:07:51.090 vishalag: No, I mean, if anything is, like, form underscore creation, that’s… that’s not from segment, or, like, I mean, I don’t know where it’s coming from. It should be, like.
63 00:07:51.670 ⇒ 00:07:55.189 vishalag: Properly written form creation or something.
64 00:07:55.460 ⇒ 00:07:57.250 vishalag: new form created, I guess.
65 00:07:57.830 ⇒ 00:07:59.369 Henry Zhao: This one also, there’s nothing coming in, though.
66 00:07:59.630 ⇒ 00:08:02.850 Henry Zhao: This looks better because it has the by-default analytics, but still nothing’s coming in.
67 00:08:04.770 ⇒ 00:08:07.890 vishalag: I can check for it if Wyatt’s not coming in.
68 00:08:08.290 ⇒ 00:08:13.599 vishalag: Might be some… Something on our end.
69 00:08:14.100 ⇒ 00:08:20.150 Henry Zhao: Okay, form duplicated, I do see that, that is…
70 00:08:20.800 ⇒ 00:08:24.340 Henry Zhao: Here, form duplicated is live, and you see the events in here.
71 00:08:25.280 ⇒ 00:08:31.539 Henry Zhao: And then imported form creation is another thing where I don’t know which one that is. Imported form creation.
72 00:08:34.450 ⇒ 00:08:35.100 vishalag: Hmm.
73 00:08:35.320 ⇒ 00:08:38.750 Henry Zhao: Anything for imported form creation, except for this new imported form created.
74 00:08:39.270 ⇒ 00:08:40.340 Henry Zhao: Which, if we can…
75 00:08:40.340 ⇒ 00:08:44.150 vishalag: It should just say new imported form. It should just say new imported form.
76 00:08:44.290 ⇒ 00:08:48.279 vishalag: New imported form created, this one also, but I think it’s not coming in, right?
77 00:08:48.550 ⇒ 00:08:50.309 Henry Zhao: Yeah. How data is coming in.
78 00:08:50.480 ⇒ 00:08:51.310 vishalag: Yeah.
79 00:08:52.160 ⇒ 00:08:54.220 Henry Zhao: Okay, so let me add that to this.
80 00:08:55.210 ⇒ 00:08:56.020 vishalag: Yep.
81 00:08:59.960 ⇒ 00:09:01.349 Henry Zhao: And you imported form.
82 00:09:08.450 ⇒ 00:09:09.830 Henry Zhao: to indicate…
83 00:09:18.650 ⇒ 00:09:21.979 Henry Zhao: But then if we have the workflow created event, then I will just use that.
84 00:09:25.960 ⇒ 00:09:30.309 vishalag: Yeah, I mean, I told you, right, like, workflow creation event is…
85 00:09:30.500 ⇒ 00:09:33.850 vishalag: Anything related to form creation is workflow creation.
86 00:09:34.240 ⇒ 00:09:37.850 Henry Zhao: So yeah, I can use those 3, if you have those 3, and then… if not, I can do…
87 00:09:44.910 ⇒ 00:09:47.370 Uttam Kumaran: That’s just Caitlin, she said she’s gonna be on in a minute.
88 00:09:48.290 ⇒ 00:09:54.170 Uttam Kumaran: So, in terms of, Henry, for those updated, if you go back to, like, the to-do list.
89 00:09:54.310 ⇒ 00:10:00.350 Uttam Kumaran: So, are we gonna plan on giving Caitlin, like, views here in Amplitude for answering these questions?
90 00:10:00.350 ⇒ 00:10:06.279 Henry Zhao: So my question to you is… my question to you is, are we paying for an amplitude? Because right now, if I try to save a chart.
91 00:10:06.540 ⇒ 00:10:11.209 Henry Zhao: It asked us to upgrade, because on the starter plan, you only get 10 saved charts.
92 00:10:11.550 ⇒ 00:10:24.110 Henry Zhao: But right now, since it’s a live version, it’s not that hard to create a chart, it’s literally clicking two buttons. So, for now, I don’t think we should create views and save them just and pay money, unless I’m not using the paid account or something like that.
93 00:10:25.350 ⇒ 00:10:36.749 Uttam Kumaran: Yeah, I mean, it’s a good question for Caitlin. I don’t think A would be too… it’d be too much to ask for this, but, like, so previously, you said, like, we would just create these views and save the links to them?
94 00:10:37.730 ⇒ 00:10:38.869 Uttam Kumaran: Or, like.
95 00:10:38.940 ⇒ 00:10:44.080 Henry Zhao: So also, Amplitude has, like, a default view tab, where it’s, like.
96 00:10:44.250 ⇒ 00:10:48.910 Henry Zhao: If you click on the product analytics default view, they… not default as in the company, but default, like.
97 00:10:48.910 ⇒ 00:10:49.560 Uttam Kumaran: Yeah.
98 00:10:49.560 ⇒ 00:10:54.610 Henry Zhao: It gives you these charts that, like, most product analytics teams care about.
99 00:10:55.260 ⇒ 00:10:57.310 Henry Zhao: So…
100 00:10:57.410 ⇒ 00:11:03.450 Henry Zhao: These are already saved for free, and you can click in and select the event that you care about.
101 00:11:03.880 ⇒ 00:11:09.140 Henry Zhao: So I think that’s already good enough, at least right now when we’re doing this Lite version, and when we don’t have PLG yet.
102 00:11:10.360 ⇒ 00:11:16.739 Henry Zhao: And then maybe after we have PLG, and they want to have an easier way to look at the charts, we can upgrade to the…
103 00:11:17.870 ⇒ 00:11:19.420 Henry Zhao: Plus plan, and have more charts.
104 00:11:19.420 ⇒ 00:11:23.090 Uttam Kumaran: Like, can we… can we keep adding stuff to the main dashboard?
105 00:11:23.420 ⇒ 00:11:25.719 Uttam Kumaran: Like to answer the additional questions.
106 00:11:25.860 ⇒ 00:11:29.880 Henry Zhao: We can, but anytime you add something that’s not in the default view, you have to pay to save it.
107 00:11:29.880 ⇒ 00:11:32.749 Uttam Kumaran: But then how are we gonna… how are we gonna answer those questions?
108 00:11:35.750 ⇒ 00:11:38.259 Henry Zhao: I can give instructions on, like, how to set up this chart.
109 00:11:38.970 ⇒ 00:11:40.699 Henry Zhao: Or would have to pay to have it saved.
110 00:11:41.920 ⇒ 00:11:47.719 Uttam Kumaran: Well, that’s what I’m saying, like, the outcome for Kalen is, like, the… a view of this on the dashboard, right?
111 00:11:47.940 ⇒ 00:11:48.910 Uttam Kumaran: So…
112 00:11:49.270 ⇒ 00:11:53.459 Uttam Kumaran: is the only… I just want to know, like, the only route is, like, we have to pay so we can get more.
113 00:11:53.890 ⇒ 00:11:55.169 Uttam Kumaran: Thanks, that’s final.
114 00:11:56.820 ⇒ 00:11:57.450 Henry Zhao: Yeah.
115 00:11:58.100 ⇒ 00:12:10.210 Uttam Kumaran: Because I don’t… she’s… she’s gonna be too busy to go build this herself. I want to just build it. So if we go, like, if you go back to the spreadsheet, basically, I want to give her a view of, like, you can go to a dashboard or a couple dashboards to answer all of these questions.
116 00:12:11.440 ⇒ 00:12:12.020 Henry Zhao: Yeah.
117 00:12:12.570 ⇒ 00:12:16.409 Henry Zhao: So right now, we… yeah, we have… this is already how often do they visit?
118 00:12:16.510 ⇒ 00:12:20.210 Henry Zhao: This one is in Salesforce, so they’re already not gonna be in the same place.
119 00:12:20.460 ⇒ 00:12:26.460 Henry Zhao: maybe we can discuss as a team if we want to use Segment to put all these somewhere else, like in Tableau or something.
120 00:12:27.320 ⇒ 00:12:34.670 Uttam Kumaran: Yeah, let’s just… that’s gonna take way too long, like, I want to just get her as many of these as possible in amplitude as fast as we can.
121 00:12:35.110 ⇒ 00:12:36.689 Henry Zhao: Like, that’s the priority.
122 00:12:37.690 ⇒ 00:12:38.140 Henry Zhao: Okay.
123 00:12:38.140 ⇒ 00:12:42.199 Uttam Kumaran: So, we can get her approval today just to do this, and then this gets her…
124 00:12:42.580 ⇒ 00:12:47.319 Uttam Kumaran: We just get, like… we just get a bunch more dashboard capabilities, right?
125 00:12:47.750 ⇒ 00:12:48.520 Henry Zhao: Yeah, yeah.
126 00:12:48.760 ⇒ 00:12:51.440 Uttam Kumaran: Okay, cool. Yeah, I would like to have this…
127 00:12:52.600 ⇒ 00:12:56.849 Uttam Kumaran: here in amplitude mode. I don’t want to do it in time mode, except for…
128 00:12:57.250 ⇒ 00:13:04.989 Henry Zhao: Yeah, it looks like with $42 a month, it’s, like, unlimited save charts, so we’ll be able to have the dashboard capability if we just do the plus plan.
129 00:13:05.890 ⇒ 00:13:09.870 Uttam Kumaran: Yeah, what’s an… like, I don’t want to sign up for annual, though, let’s just do monthly.
130 00:13:13.110 ⇒ 00:13:14.000 Henry Zhao: Thanks, dude.
131 00:13:14.800 ⇒ 00:13:16.879 Uttam Kumaran: I’ll ask her about this. I don’t know what…
132 00:13:17.260 ⇒ 00:13:19.130 Uttam Kumaran: Do you know what MTUs they’re at?
133 00:13:24.880 ⇒ 00:13:25.689 Henry Zhao: Let’s find out.
134 00:13:30.940 ⇒ 00:13:36.270 Henry Zhao: All users… How do I…
135 00:13:48.400 ⇒ 00:13:50.529 Henry Zhao: I hate that it’ll make this easier.
136 00:13:52.190 ⇒ 00:13:56.899 Uttam Kumaran: Maybe you can go into settings and see, like, what the current MPU amount is, and…
137 00:13:58.390 ⇒ 00:13:59.450 Henry Zhao: Yeah, I think so, hold on
138 00:14:00.280 ⇒ 00:14:02.669 Henry Zhao: I think amplitude is kind of hard to find out on this.
139 00:14:06.050 ⇒ 00:14:08.020 Henry Zhao: Please go away.
140 00:14:22.600 ⇒ 00:14:27.200 Uttam Kumaran: We’ll just go back to data, and let’s just… If you can use it.
141 00:14:31.210 ⇒ 00:14:33.080 Uttam Kumaran: Let’s just go back to data.
142 00:14:35.330 ⇒ 00:14:37.530 Uttam Kumaran: We just got a little slower, and it’s just hungry up.
143 00:14:38.200 ⇒ 00:14:40.050 Uttam Kumaran: It’s somewhere here in London.
144 00:14:42.530 ⇒ 00:14:44.389 Uttam Kumaran: And we can keep scrolling through…
145 00:14:53.230 ⇒ 00:14:54.650 Henry Zhao: Oh, see, hold on a second.
146 00:15:01.330 ⇒ 00:15:03.929 Henry Zhao: Settings, General, Plans, and Billing section.
147 00:15:17.920 ⇒ 00:15:23.690 Henry Zhao: Well, right now we’re at 196, but when Vishal adds in more events, I think we’re gonna have more than this.
148 00:15:24.540 ⇒ 00:15:26.389 Henry Zhao: Although not really, because…
149 00:15:26.610 ⇒ 00:15:34.060 Henry Zhao: If he implements… we’ve already implemented user login, so everyone technically should log in before they have any other sort of activity. Hi, Caitlin!
150 00:15:34.320 ⇒ 00:15:35.860 Caitlyn Vaughn: Hey! Sorry!
151 00:15:35.860 ⇒ 00:15:39.270 Uttam Kumaran: you’re good.
152 00:15:39.270 ⇒ 00:15:39.630 Henry Zhao: Bum.
153 00:15:39.630 ⇒ 00:15:48.229 Uttam Kumaran: Okay, then I’m fine with that, Henry. So kind of, maybe, Henry, do you want to walk through the spreadsheet, and then we can talk through making the decision on entities?
154 00:15:49.040 ⇒ 00:16:01.670 Henry Zhao: Yeah, absolutely. So, Caitlin, I was just giving everyone an update on, kind of, the way that we’ve been attacking this. So, out of the message that you sent us in that group, I basically just copied and pasted into the spreadsheet of all the things that you care about.
155 00:16:02.020 ⇒ 00:16:12.550 Henry Zhao: And the things that we can act on, I put in this column B on, like, what we would need to have a V1, or a light version of the analytics, and then the third column is kind of the status of where we’re at.
156 00:16:12.940 ⇒ 00:16:18.720 Henry Zhao: This first group of things, like personas of who our current customer base is, what kinds of companies are using default.
157 00:16:19.020 ⇒ 00:16:25.870 Henry Zhao: and trends and firmographics, I think we’re gonna need to complement that data with some third-party data to figure out
158 00:16:26.000 ⇒ 00:16:35.689 Henry Zhao: the answer to this question, but we wanted to hear from you, kind of, what things you care about in terms of personas and kinds of companies. Like, do you care about company size, industry.
159 00:16:36.190 ⇒ 00:16:40.219 Henry Zhao: Location, like, what are these things that you think would be interesting?
160 00:16:40.600 ⇒ 00:16:41.860 Henry Zhao: And could be accidental.
161 00:16:42.230 ⇒ 00:16:57.609 Caitlyn Vaughn: Yeah, so, I mean, the truth is we have, like, very little information in general right now, right? What I have been working on, like, very recently is the, like, plan for rolling out PLG, and one of the things that
162 00:16:57.860 ⇒ 00:17:10.919 Caitlyn Vaughn: like, one of our advisors said to me that I thought was so funny, she was like, just imagine that the way, like, the people and the way people are using default right now is gonna stay the same regardless of if you roll out PLG or not, right?
163 00:17:10.920 ⇒ 00:17:20.019 Caitlyn Vaughn: And she’s like, so who’s using it now? Like, how are they using it? And I was just like, well, we have, like… I can tell you how I think people are using it, but…
164 00:17:20.240 ⇒ 00:17:21.190 Caitlyn Vaughn: like…
165 00:17:22.250 ⇒ 00:17:33.069 Caitlyn Vaughn: I mean, generally, we’ve been trying to, like, segment customer bases into, like, different areas of, like, support, plus company size, plus, you know.
166 00:17:33.420 ⇒ 00:17:46.350 Caitlyn Vaughn: like, those types of things, so I would say anything around, like, who our actual companies are, where are they located, how many employees do they have, who, like, who is actually inside of default, how many sales reps do they have, like…
167 00:17:46.630 ⇒ 00:18:01.770 Caitlyn Vaughn: what people are looking at what screens would be helpful. Like, when someone logs into default for the first time, what is the first thing that they do? Where are people, like, heatmap spending their time in the, in the app? And then…
168 00:18:02.240 ⇒ 00:18:03.670 Caitlyn Vaughn: Yeah, yeah, I feel…
169 00:18:03.670 ⇒ 00:18:05.909 Uttam Kumaran: Any of that on… on sign-up, by the way?
170 00:18:06.160 ⇒ 00:18:07.139 Caitlyn Vaughn: What’d you say, Tom?
171 00:18:07.140 ⇒ 00:18:09.250 Uttam Kumaran: Are you collecting any of that on sign-up?
172 00:18:10.770 ⇒ 00:18:19.849 Caitlyn Vaughn: We are collecting some of that. We do have, like, an onboarding flow. I need to look back through it and see. I think it’s, like.
173 00:18:20.470 ⇒ 00:18:25.809 Caitlyn Vaughn: What is your persona kind of a thing, but it’s… it’s extremely limited if we are catching anything.
174 00:18:26.180 ⇒ 00:18:33.749 Uttam Kumaran: And then my next question is, is the, like, enrichment thing that you’re working on for the product ready? Because we’ll just use that to get this data.
175 00:18:34.020 ⇒ 00:18:35.160 Caitlyn Vaughn: Or…
176 00:18:35.160 ⇒ 00:18:38.599 Uttam Kumaran: Should we just go get it manually and make sure it’s available?
177 00:18:39.240 ⇒ 00:18:44.879 Caitlyn Vaughn: No, so we had to, like, close a couple of these vendor contracts,
178 00:18:45.840 ⇒ 00:18:58.679 Caitlyn Vaughn: Already, so that would be super helpful. I can send you a list of, like, who we already purchased and who have keys for, but yeah. I mean, literally, if you could use a million credits for those and, like, actually leverage our contracts, that would be great.
179 00:18:59.260 ⇒ 00:19:09.839 Uttam Kumaran: Okay, so we’ll… I just want to reuse that instead of us going and figuring this out, so if you could… I don’t know who it was, but yeah. If you can send me whatever details, then Henry, we’ll use… we’ll use those.
180 00:19:10.050 ⇒ 00:19:15.890 Uttam Kumaran: It’s like D&B alternatives, like, similar. We’ll go get this type of data from them.
181 00:19:16.010 ⇒ 00:19:34.729 Uttam Kumaran: So kind of, like, our hope, really, if you kind of scroll to the left, Henry, like, these are all the questions, and basically we’re going through with Michelle, making sure we have events to address these. Once the events come in, we’re de-duping, making sure that they’re all firing effectively, and then we’re going to produce charts in amplitude.
182 00:19:34.800 ⇒ 00:19:51.539 Uttam Kumaran: I think we’re gonna avoid Caitlin’s short-term, like, doing anything in, like, another BI tool or moving data around. I think we’re gonna just try to accomplish as many of this stuff as fast as possible in amplitude. And then, like, if we want to marry this data with, like.
183 00:19:51.620 ⇒ 00:19:58.270 Uttam Kumaran: more product data that isn’t in Amplitude, we can talk about that later, but I think a good amount of these, we…
184 00:19:58.680 ⇒ 00:20:01.799 Uttam Kumaran: we can accomplish straight in amplitude. The only…
185 00:20:01.900 ⇒ 00:20:11.689 Uttam Kumaran: thing we need is approval to upgrade our amplitude plan. We’re currently on the free plan, we just need to upgrade to, like, $60 a month to get charts.
186 00:20:11.840 ⇒ 00:20:12.500 Caitlyn Vaughn: Yep.
187 00:20:12.780 ⇒ 00:20:14.829 Uttam Kumaran: Okay. Am I… is this the one that I’m in?
188 00:20:15.490 ⇒ 00:20:16.420 Uttam Kumaran: Yes.
189 00:20:16.420 ⇒ 00:20:17.689 Caitlyn Vaughn: Okay, here, let me just…
190 00:20:17.690 ⇒ 00:20:21.649 Uttam Kumaran: Yeah, this is, this is the… Yeah, it’s even default.
191 00:20:23.420 ⇒ 00:20:23.970 Caitlyn Vaughn: Amplitude.
192 00:20:23.970 ⇒ 00:20:35.449 Uttam Kumaran: And so we’ll build out… we’re basically gonna use that spreadsheet and just build out charts. Probably, Henri, I don’t know up to you, but if you wanna… you can logically break down, or you just throw everything into the main chart.
193 00:20:35.790 ⇒ 00:20:40.910 Uttam Kumaran: Maybe we’d do that for now. Unless it gets too crowded, then you can think about a couple of dashboards.
194 00:20:42.030 ⇒ 00:20:42.830 Uttam Kumaran: Corona?
195 00:20:42.830 ⇒ 00:20:47.050 Henry Zhao: like, this default view, which is kind of just comes out of the box with amplitude.
196 00:20:48.210 ⇒ 00:20:57.789 Henry Zhao: it’s kind of like what the final product is going to look like anyway, but basically you’ll get your, like, daily active users. We could probably put on top, like, how many are monthly active users.
197 00:20:58.760 ⇒ 00:21:02.900 Henry Zhao: And then once, Michelle, you’re able to add in the additional
198 00:21:03.060 ⇒ 00:21:06.189 Henry Zhao: events within the app, right? So…
199 00:21:06.920 ⇒ 00:21:17.919 Henry Zhao: like, any of the other behaviors here, like clicking on dashboards, contacts, adding records to answer Caitlin’s question of where… what are they doing, like, where are they spending their time, what is the funnel?
200 00:21:18.070 ⇒ 00:21:26.900 Henry Zhao: Then there’s a lot of good charts of, like, after step one, they went to step two, and there’s, like, the waterfall charts of this is the most common path that people go down.
201 00:21:27.860 ⇒ 00:21:38.210 Henry Zhao: And I would say with default, it won’t be too messy. I know some companies, they have, like, 100 different paths you can take. Those are not as useful, but I think for default, those will be pretty useful, as long as we keep them pretty big picture.
202 00:21:39.230 ⇒ 00:21:46.259 Henry Zhao: And then you have here, like, engagement, how often are users performing your event? So you can see things like how often are people logging in.
203 00:21:47.060 ⇒ 00:21:48.300 Henry Zhao: So that’s…
204 00:21:50.350 ⇒ 00:21:57.120 Henry Zhao: So right now, it would look something like this, but right now, I think there’s duplication going in, so that’s why you see everything is 2, 4, 6, 8, 10.
205 00:21:57.660 ⇒ 00:22:04.290 Henry Zhao: Vishal, do you think just by looking at segment, I can figure out why duplication is happening here?
206 00:22:06.240 ⇒ 00:22:10.289 vishalag: Yeah, I mean, because if you go to the events, it says from segment, like…
207 00:22:10.500 ⇒ 00:22:13.830 vishalag: It’s not from, like, our gold-based end.
208 00:22:14.050 ⇒ 00:22:15.929 vishalag: So it’s definitely from segment.
209 00:22:17.030 ⇒ 00:22:17.700 Henry Zhao: Okay.
210 00:22:18.710 ⇒ 00:22:23.440 vishalag: Or you can just disregard those completely, whichever has a suffix.
211 00:22:23.690 ⇒ 00:22:26.759 vishalag: Of by default analytics. I just completed that.
212 00:22:26.760 ⇒ 00:22:28.740 Uttam Kumaran: They’re at all the segment ones, yeah.
213 00:22:29.400 ⇒ 00:22:37.619 Henry Zhao: Okay, so right now, Vishal is adding meeting booked, which is gonna be pretty high pri. That’ll help us answer…
214 00:22:38.600 ⇒ 00:22:46.129 Henry Zhao: where is it? How many inbound leads are coming in daily or monthly, right? When you say how many inbound leads, you’re talking about leads coming in because they booked a meeting.
215 00:22:46.880 ⇒ 00:22:48.150 Caitlyn Vaughn: Yes.
216 00:22:49.030 ⇒ 00:22:53.859 Caitlyn Vaughn: Yes, I mean, probably form submits plus, like, meetings booked.
217 00:22:54.500 ⇒ 00:22:55.740 Henry Zhao: Okay, meeting booked.
218 00:22:56.340 ⇒ 00:22:58.530 Henry Zhao: And add form submits.
219 00:22:59.470 ⇒ 00:23:02.920 Henry Zhao: Okay, so then… Form submits for us to know how many…
220 00:23:03.400 ⇒ 00:23:16.850 vishalag: Yeah, I mean, just a second, like, meeting books will be lesser, or… will be lesser than form submits, right, Caitlin? Like, not everyone will definitely have a form submission and will have a meeting booking thing, right?
221 00:23:17.080 ⇒ 00:23:19.099 vishalag: So it should be just fine.
222 00:23:19.780 ⇒ 00:23:28.339 Caitlyn Vaughn: Yes, I mean, I’m curious, like, how many form submits we have across the platform, and also, like, per person, and then also, like, you know
223 00:23:28.670 ⇒ 00:23:32.510 Caitlyn Vaughn: Across the platform, plus per account, right?
224 00:23:32.960 ⇒ 00:23:37.579 Caitlyn Vaughn: Like, those are both data points I would be curious to see, and then…
225 00:23:37.680 ⇒ 00:23:52.180 Caitlyn Vaughn: I feel like this is probably too complicated at the moment, but further down the line, figuring out, like, meeting booked, or sorry, forms submitted to, like, meeting booked to, like, meeting attended, and being able to track for customers, those kinds of things.
226 00:23:52.630 ⇒ 00:23:54.090 Henry Zhao: Got the meeting attendant.
227 00:23:54.310 ⇒ 00:23:55.450 Henry Zhao: Is that right, Michelle?
228 00:23:55.750 ⇒ 00:23:56.810 Henry Zhao: Because we don’t know if they’ve actually…
229 00:23:57.680 ⇒ 00:24:02.290 Henry Zhao: We don’t know if they did the meeting attended or not, right? But I think there was, like, a proxy we could have done.
230 00:24:03.780 ⇒ 00:24:10.939 vishalag: Yeah, I mean, like, if the meeting is not canceled, or it’s not marked as no-show, and the time has passed, we assume that it’s attended.
231 00:24:11.320 ⇒ 00:24:12.060 Henry Zhao: You bet.
232 00:24:12.270 ⇒ 00:24:14.109 Caitlyn Vaughn: Yeah, I mean…
233 00:24:15.800 ⇒ 00:24:32.309 Caitlyn Vaughn: obviously, if there was a way for us to, like, be more explicit with the definition of, like, meetings attended, like, at least one person that was invited to the meeting who is not the host shows up, that would probably be, like, a good definition, but I don’t know if it’s even possible for us to pull that data, if it’s through, like.
234 00:24:32.560 ⇒ 00:24:35.409 Caitlyn Vaughn: you know, Google or Outlook or whatever.
235 00:24:35.410 ⇒ 00:24:43.790 Uttam Kumaran: Yeah, like, I think the biggest thing you could probably do is either have a post-meeting form, or some mechanism in the product to mark, like, that this didn’t happen.
236 00:24:43.910 ⇒ 00:24:53.480 Uttam Kumaran: And it goes and affects that. But even more importantly is, like, you could… you want to be able to do things, like, in the product. Hey, if you add a meeting booking, your odds of you getting,
237 00:24:53.690 ⇒ 00:25:03.679 Uttam Kumaran: some people converting our X amount, right? Those are the things that you want to start to share, so you can have people continue to use more of the product areas.
238 00:25:07.280 ⇒ 00:25:09.730 Caitlyn Vaughn: Yeah, you kind of cut out for a second, but yes.
239 00:25:13.320 ⇒ 00:25:23.330 Caitlyn Vaughn: Okay, and then… also… I can share really quickly… Hmm, okay.
240 00:25:23.890 ⇒ 00:25:31.979 Caitlyn Vaughn: So I’m on… Amplitude… Is it this one that you want?
241 00:25:32.490 ⇒ 00:25:35.160 Uttam Kumaran: Yes, don’t do… don’t do annual, though.
242 00:25:35.430 ⇒ 00:25:37.429 Uttam Kumaran: And just do whatever the lowest is.
243 00:25:38.010 ⇒ 00:25:39.660 Uttam Kumaran: this, and then upgrade that. Yeah.
244 00:25:39.990 ⇒ 00:25:40.530 Uttam Kumaran: Yes.
245 00:25:40.670 ⇒ 00:25:41.769 Caitlyn Vaughn: Okay, will do.
246 00:25:42.310 ⇒ 00:25:42.840 Uttam Kumaran: Okay.
247 00:25:43.430 ⇒ 00:25:43.910 vishalag: I am.
248 00:25:43.910 ⇒ 00:25:44.280 Uttam Kumaran: I didn’.
249 00:25:44.740 ⇒ 00:25:48.850 vishalag: Caitlin, like, we have all the data in Superbase, right?
250 00:25:49.420 ⇒ 00:26:01.350 vishalag: why don’t we just push the data… like, we just make a pipeline from Superbase over to the Amplitude, rather than us making all these events. We have all the data in Superbase, you can, like, literally make analysis out of it, right?
251 00:26:02.090 ⇒ 00:26:03.829 Caitlyn Vaughn: I mean, can you?
252 00:26:04.240 ⇒ 00:26:09.019 Uttam Kumaran: What data is in Superbase? Because that’s, I guess, the first time I heard about Superbase data.
253 00:26:09.550 ⇒ 00:26:10.070 Caitlyn Vaughn: Yeah.
254 00:26:10.070 ⇒ 00:26:14.260 vishalag: We have all the submission data, we have all the meetings status data.
255 00:26:14.260 ⇒ 00:26:26.720 Uttam Kumaran: So I already have… I have the exports of that, but this is more, we want to look at the event flows, right? So, like, currently… and we’re gonna start to use this for the next…
256 00:26:28.440 ⇒ 00:26:46.690 Uttam Kumaran: We’re gonna start to use this for the next PLG product, which is, like, starting to have different front-end events for various parts. We have some of the product data already, meetings, teams, users, but what we want is actually, like, to look at the event structures, and, like, kind of, like, what buttons are getting, like, the more specific events.
257 00:26:49.080 ⇒ 00:26:58.949 vishalag: Yeah, I mean, like, events like what you just showed, like, how many leads got into the inbound funnels, that you can do with SuperViz itself. I get your point, like, if there’s, let’s say, which
258 00:26:58.950 ⇒ 00:27:09.739 vishalag: which particular modules have been clicked the most. For that, Superbase won’t help. But, like, these things can be, I think, analyzed pretty simply, rather than us pushing more events over to amplitude and all of that.
259 00:27:12.030 ⇒ 00:27:15.550 Caitlyn Vaughn: You don’t think we should push from Supabase into Amplitude?
260 00:27:16.570 ⇒ 00:27:19.489 vishalag: Yeah, I think we should push for those kind of events.
261 00:27:20.090 ⇒ 00:27:22.000 Uttam Kumaran: I don’t know if you’re gonna be able to push
262 00:27:22.110 ⇒ 00:27:31.189 Uttam Kumaran: like, fire… we’re gonna be able to backfill events that way. Like, it has… it’s gonna be through this, like, amplitude event collector, basically, where you’re firing events at the amplitude.
263 00:27:31.310 ⇒ 00:27:50.130 Uttam Kumaran: I mean, it’s a good debate, like, kind of like, there’s two things that typically happen. One, you have, like, your product usage data that typically lives there, which is, like, the meetings, the teams. Those have event timestamps, and yes, we can start to build some type of, like, event structure, but there’s gonna be a lot of other events, and things about page load.
264 00:27:50.160 ⇒ 00:28:00.759 Uttam Kumaran: And like, I don’t know, Henry, if you have the… if you want to pull up our original spreadsheet of, like, all of the different questions you’re going to answer, I think some of those are going to be beyond scope of what we can get.
265 00:28:00.970 ⇒ 00:28:06.939 Uttam Kumaran: directly in… Super Bates. Like, can you go to the product events?
266 00:28:07.990 ⇒ 00:28:08.650 Henry Zhao: Yeah.
267 00:28:09.130 ⇒ 00:28:14.730 Uttam Kumaran: Or the… remember we had that other spreadsheet with, the different, like, yeah…
268 00:28:17.860 ⇒ 00:28:18.709 Henry Zhao: This one, right?
269 00:28:19.040 ⇒ 00:28:19.970 Uttam Kumaran: Yes.
270 00:28:20.750 ⇒ 00:28:22.849 Uttam Kumaran: So if you show some of these…
271 00:28:23.090 ⇒ 00:28:41.069 Uttam Kumaran: we’re trying to look at, like, various different flows within multiple parts of the product. So on onboarding, on creating projects, purchase events, so I think a lot of those flows are… we’re not gonna have the specifics all within the product usage. We may have, like, bots.
272 00:28:41.160 ⇒ 00:28:46.119 Uttam Kumaran: Right? But we’re not gonna be able to see the pre-flows. Also, post-purchase.
273 00:28:46.320 ⇒ 00:28:47.260 Uttam Kumaran: That’s weird.
274 00:28:48.230 ⇒ 00:28:54.989 Uttam Kumaran: So it’s just gonna get a lot beefier than this, but there are, I guess, Rashaun, to your point, there are existing questions that we can’t answer there.
275 00:28:55.180 ⇒ 00:28:57.920 Uttam Kumaran: We’ll… we’ll… there will be some duplication for now.
276 00:28:58.090 ⇒ 00:29:02.710 Uttam Kumaran: And we already have that data, and we’re using it for a couple other questions.
277 00:29:02.840 ⇒ 00:29:05.299 Uttam Kumaran: But I think the amplitude piece is gonna get a lot bigger.
278 00:29:06.340 ⇒ 00:29:10.119 Caitlyn Vaughn: Yeah, I think we should aggregate everything into a single place so that we can, like.
279 00:29:10.490 ⇒ 00:29:17.629 Caitlyn Vaughn: you know, do queries inside of it, pull different data, filter for different things, like, I’m interested in having it.
280 00:29:18.170 ⇒ 00:29:18.770 Uttam Kumaran: Yes.
281 00:29:18.770 ⇒ 00:29:36.000 Caitlyn Vaughn: to the same place, because I don’t really want to, like, chase it down. Like, I know we can go find number of forms submitted each month, like, I did pull that data last month, but to get that specific data point was, like, a massive pain, right? So I don’t want to have to, like, do that every time.
282 00:29:36.360 ⇒ 00:29:52.330 Uttam Kumaran: So to answer that question, the long tail of this is everything will land into a data warehouse. So amplitude data will end up there, the product data will end up there, that’s sort of the stuff we bring to Vic, and I forget who else on the team, which we’re doing in Mother Duck.
283 00:29:52.330 ⇒ 00:30:04.049 Uttam Kumaran: which is basically centralizing the product data, so Supabase will be one source of that, Amplitude will be one source of that. We’ll then marry the event data to the actual, like, object data.
284 00:30:04.200 ⇒ 00:30:21.669 Uttam Kumaran: So you’ll be able to see, like, what events were associated with the user, and, like, start to do deeper analysis. The only reason we’re centralizing in Amplitude now is just as it’s something we can get to, like, really, really quickly. Centralizing everything in the warehouse, implementing dbt and a BI tool is kind of, like.
285 00:30:22.320 ⇒ 00:30:25.150 Uttam Kumaran: It’s gonna take longer. Yeah.
286 00:30:25.900 ⇒ 00:30:44.690 Caitlyn Vaughn: Another thing that I’m thinking of is, at the moment, like, one of our current issues is that you can actually, like, add seats in the platform without, like, actually going through sales, right? Like, we’ll sell you a certain number of seats or a certain number of credits for enrichment, and you can just use as many as you want. It’s not really actually rate-limited on the back end, and we don’t have a way of, like.
287 00:30:44.700 ⇒ 00:30:50.479 Caitlyn Vaughn: figuring out or seeing who has crossed the threshold and, like, following up with them, even. So…
288 00:30:50.480 ⇒ 00:30:51.140 Uttam Kumaran: Okay.
289 00:30:51.140 ⇒ 00:31:03.119 Caitlyn Vaughn: Yeah, I mean, there’s obviously things that are, like, current issues, and then as we launch PLG, we’ll have, like, credit base, so we need to be able to track, like, number of workflows run, or enrichment credits used, and all of that, and have, like, hard limits built in.
290 00:31:03.520 ⇒ 00:31:09.719 Uttam Kumaran: Yes. So that’s, like, all product stuff that will end up coming in through, like, Superbase or whatever the product backend is.
291 00:31:09.720 ⇒ 00:31:11.320 Caitlyn Vaughn: And then impacting…
292 00:31:11.320 ⇒ 00:31:19.590 Uttam Kumaran: the state of the front end. So the product team will do that on the fly, dynamically, but on the reporting side, and how you guys look at it, we’ll need to have that all
293 00:31:19.660 ⇒ 00:31:33.060 Uttam Kumaran: centralized. For example, you wanna… if you want to answer a question, like, what are, our enterprise organizations, like, most used product features, that is a mix of both of those sources, right? Like, Amplitude, we may…
294 00:31:33.060 ⇒ 00:31:44.170 Uttam Kumaran: or may not be able to do that. Consumer base, certainly, we’re not gonna have all those events, so we’re gonna wanna marry that. That’s all gonna happen in a data warehouse. It’s gonna take another, probably, month to, like, figure that out.
295 00:31:44.330 ⇒ 00:31:58.829 Uttam Kumaran: getting this stuff in Amplitude, I think we’ll probably need another week, or less. That’s kind of, like, why we’re prioritizing that, so we can answer these questions. You’re gonna immediately have follow-up questions, and I want to answer all of those through these events in Amplitude, and making sure that those are prior.
296 00:31:59.350 ⇒ 00:32:07.150 Caitlyn Vaughn: Okay, cool. Awesome. Okay, other than the upgrading amplitude, is there anything else that you need from me to, like, unblock you?
297 00:32:07.750 ⇒ 00:32:14.029 Henry Zhao: I just have a quick follow-up question, as, form submit is not the same as, Vishal, when you said form create for workflows, right?
298 00:32:14.430 ⇒ 00:32:17.250 Henry Zhao: Like, there’s form submit and form create, they’re different things, right?
299 00:32:17.580 ⇒ 00:32:20.220 vishalag: Yeah, form submission is, like, different.
300 00:32:20.770 ⇒ 00:32:26.350 Henry Zhao: Form submit is, like, a lead form, and then form create is, like, creating a form inside the product for a workflow, right?
301 00:32:27.390 ⇒ 00:32:27.710 vishalag: Yes.
302 00:32:27.710 ⇒ 00:32:34.849 Caitlyn Vaughn: Yeah, also, form create… actually, Vishal brought this up to me last week or this week, that was a good point, which is…
303 00:32:35.450 ⇒ 00:32:46.049 Caitlyn Vaughn: Like, workflow created and probably form created are metrics that doesn’t make sense for us to track inside the platform, purely because, like.
304 00:32:47.410 ⇒ 00:32:51.540 Caitlyn Vaughn: I don’t know, I guess it could be, like, creating a new one versus publishing, but…
305 00:32:51.770 ⇒ 00:32:57.200 Caitlyn Vaughn: It probably matters more to track, like, the published form, or, like, publish a workflow.
306 00:32:57.470 ⇒ 00:33:04.329 Uttam Kumaran: I mean, you probably want to see all of them, right? You’ll see, you should expect there to be a ton of workflows created, less published.
307 00:33:04.700 ⇒ 00:33:05.300 Caitlyn Vaughn: Yeah.
308 00:33:05.300 ⇒ 00:33:11.539 Uttam Kumaran: Again, you wanna… you wanna know what that poor publishing cadence is, like, where are people dropping off?
309 00:33:11.540 ⇒ 00:33:11.920 Caitlyn Vaughn: Yeah.
310 00:33:11.920 ⇒ 00:33:14.939 Uttam Kumaran: But yeah, you should expect these different, like, workflow states.
311 00:33:14.940 ⇒ 00:33:15.299 Caitlyn Vaughn: Thank you.
312 00:33:15.300 ⇒ 00:33:33.630 Uttam Kumaran: track. But see, in the… if we were to do that on the product data, we would probably just only have the latest state of the form. We wouldn’t be able to see the, like, how many… how many are locked into each, at what point, and how often they get moved, who’s publishing the most, who’s editing the most. Those are the things that we want to start to look at.
313 00:33:33.820 ⇒ 00:33:39.860 Caitlyn Vaughn: I think we do have in-product, like, versioning, at least a little bit. Yeah.
314 00:33:40.220 ⇒ 00:33:49.679 Caitlyn Vaughn: on workflows, for sure, where you can roll… not roll back, but you can see past versions, in performs. I don’t know, Vishal, can you see past form versions, or no?
315 00:33:50.660 ⇒ 00:33:52.060 vishalag: Yeah, I mean, you can…
316 00:33:52.350 ⇒ 00:33:59.759 vishalag: Form versions, you can go back, yeah. I mean, you just have to change the UI and check it out. But we don’t have it in the, I think, UI to do it directly.
317 00:33:59.760 ⇒ 00:34:00.630 Caitlyn Vaughn: Yeah.
318 00:34:01.090 ⇒ 00:34:01.950 Caitlyn Vaughn: Yeah.
319 00:34:03.130 ⇒ 00:34:06.199 Uttam Kumaran: You are saving the different states, as you guys are alliterating.
320 00:34:06.570 ⇒ 00:34:10.109 Caitlyn Vaughn: Yeah, we are on the back end, but I don’t think on the front end for forms.
321 00:34:10.870 ⇒ 00:34:11.310 vishalag: Yeah.
322 00:34:11.310 ⇒ 00:34:11.870 Uttam Kumaran: Okay.
323 00:34:14.060 ⇒ 00:34:15.300 Uttam Kumaran: Cool. Okay, cool.
324 00:34:15.300 ⇒ 00:34:32.939 Caitlyn Vaughn: I also dropped in the chat here, these are the 3, 4, 5, 6… I think these are the data providers that I have had to purchase over the last couple months. There’s, like, another dozen that we’re holding off on until we actually roll out Phoenix, but…
325 00:34:33.370 ⇒ 00:34:40.980 Caitlyn Vaughn: this is what I got for you now. So if any of these, like, tickle you, or you think you can leverage these for what you guys need, that would be great, actually.
326 00:34:40.989 ⇒ 00:34:57.389 Uttam Kumaran: I’ll look into the Oler, Weeza, I mean, Clearbit and Apollo would be, like, two that stand out as probably easiest for us to do, but let me… let me get back to you and see, Henry, how we can… whether we do this directly in Amplitude, or whether we need to do, like, post-enrichments or not. Okay, fine.
327 00:34:57.870 ⇒ 00:35:13.650 Caitlyn Vaughn: Owler is also, like, awesome, and our most expensive vendor, so if you want to leverage that, we can do full enrich, and then they also do, like, any kind of, like, signal changes, like, new job changes, or competitor news coming out, or, like, they have a bunch of really
328 00:35:13.990 ⇒ 00:35:17.050 Caitlyn Vaughn: Maybe for, like, Lev and Ryan as well. But…
329 00:35:17.050 ⇒ 00:35:20.350 Uttam Kumaran: Okay, cool. Yeah, we’re using,
330 00:35:21.940 ⇒ 00:35:31.549 Uttam Kumaran: I don’t know if we’re using Apollo, or… but I should swap out whatever we’re using for this, or what we’re doing for 11 Ryan, because I don’t know who we’re using, but yeah.
331 00:35:31.920 ⇒ 00:35:33.360 Caitlyn Vaughn: Cool. Apollo sucks.
332 00:35:33.710 ⇒ 00:35:42.059 Uttam Kumaran: Yeah, Apollo sucks. But if you guys have the… if these are the premium versions, then yeah, I would love to use that, because I’m stuck using Apollo and Clearbit.
333 00:35:42.090 ⇒ 00:35:47.260 Caitlyn Vaughn: Yeah. We paid, like, 50K contract for Owler, so… and it’s not…
334 00:35:47.260 ⇒ 00:35:47.719 Uttam Kumaran: Great, okay.
335 00:35:47.720 ⇒ 00:35:48.750 Caitlyn Vaughn: format.
336 00:35:48.750 ⇒ 00:35:57.390 Uttam Kumaran: Okay, okay, so we’ll, yeah, we’ll use some, we’ll use some of that. I mean, I want to use it for 11, Ryan, because we’re using some bad sources, but yeah, I’d rather swap these.
337 00:35:57.620 ⇒ 00:35:58.300 Caitlyn Vaughn: Cool.
338 00:35:59.350 ⇒ 00:35:59.930 Uttam Kumaran: Okay.
339 00:36:00.260 ⇒ 00:36:00.990 Uttam Kumaran: Nope.
340 00:36:02.910 ⇒ 00:36:04.139 Caitlyn Vaughn: Awesome, anything else?
341 00:36:04.630 ⇒ 00:36:08.500 Henry Zhao: Michelle, let’s do another 30 minutes talk tomorrow, just to talk about the next round of events.
342 00:36:09.790 ⇒ 00:36:10.900 vishalag: Does that work for you?
343 00:36:11.740 ⇒ 00:36:12.500 vishalag: Let me know.
344 00:36:12.920 ⇒ 00:36:14.080 Henry Zhao: Okay, that’s it then.
345 00:36:14.320 ⇒ 00:36:15.830 Henry Zhao: Thank you, Caitlin. Thanks, everyone.
346 00:36:15.830 ⇒ 00:36:18.399 Caitlyn Vaughn: Nope. Thanks to you guys. Bye.