Meeting Title: Phoenix Product Analytics Dashboard Review Date: 2026-03-23 Meeting participants: Greg Stoutenburg, Nandika Jhunjhunwala


WEBVTT

1 00:01:24.150 00:01:25.330 Nandika Jhunjhunwala: Hello!

2 00:01:26.430 00:01:27.530 Greg Stoutenburg: Happy Monday!

3 00:01:27.530 00:01:30.790 Nandika Jhunjhunwala: Happy Monday, sorry, maybe I was in the wrong room, I don’t know.

4 00:01:31.320 00:01:35.389 Greg Stoutenburg: Well, I clicked the button, and I was like, okay, sometimes it takes a minute.

5 00:01:35.740 00:01:37.570 Greg Stoutenburg: They’re like, nope, it’s been mapped.

6 00:01:38.260 00:01:39.760 Greg Stoutenburg: So, okay.

7 00:01:40.520 00:01:54.340 Greg Stoutenburg: Cool. Alright, well, I hope to just take a minute, I mean, let me know if anything’s top of mind for you, but just to keep the product analytics work moving forward, I wanted to just take a minute and just sort of, like, high-level overview the dashboard that you put together, and then,

8 00:01:54.470 00:02:11.429 Greg Stoutenburg: see if there’s anything that we… we identify as, like, alright, you know, here’s, like, this could be a template for some other feature that we’ll analyze, or some other core metric, like time to value on, on usage of key features, so… and just sort of, like, take it from there, and then afterwards, you know, I can… I can take this

9 00:02:11.500 00:02:16.319 Greg Stoutenburg: take the notes from this and, you know, look forward to that next iteration, if that sounds good.

10 00:02:16.470 00:02:25.590 Nandika Jhunjhunwala: Definitely, yeah, I think I just threw on a bunch of insights on the dashboard, and it’s not organized according to, like, how they would be used, or, like, what’s most useful, so…

11 00:02:25.590 00:02:26.150 Greg Stoutenburg: Perfect.

12 00:02:26.150 00:02:28.519 Nandika Jhunjhunwala: Definitely need, like, help with that area, for sure.

13 00:02:28.520 00:02:36.179 Greg Stoutenburg: Yeah, yeah, perfect. And then what we can do is, we’ll just curate as we go. So, and we have the time for that.

14 00:02:37.320 00:02:42.390 Greg Stoutenburg: Has there been anything else that has shipped to staging since the last time that we did this kind of session?

15 00:02:42.630 00:02:43.479 Greg Stoutenburg: It seemed like it had been.

16 00:02:44.820 00:03:02.650 Nandika Jhunjhunwala: Maybe? I don’t think it’s been, like… I’m waiting till the end of the week to do more instrumentation, because I just have, like, growth and, like, support on my plate, so I haven’t instrumented anything else. Like, the last time I checked was last week, Thursday, and I pushed some updates on, like, the routing app.

17 00:03:02.720 00:03:06.430 Nandika Jhunjhunwala: But besides that, I think there hasn’t been much of a change.

18 00:03:06.430 00:03:07.090 Greg Stoutenburg: Okay.

19 00:03:07.090 00:03:08.240 Nandika Jhunjhunwala: So, yeah.

20 00:03:08.240 00:03:10.620 Greg Stoutenburg: Okay, cool. Let’s jump in, then.

21 00:03:12.130 00:03:12.480 Nandika Jhunjhunwala: Yeah.

22 00:03:12.770 00:03:13.740 Greg Stoutenburg: Yep.

23 00:03:13.910 00:03:14.890 Greg Stoutenburg: Alright, cool.

24 00:03:14.890 00:03:18.099 Nandika Jhunjhunwala: Can you talk through, like, some of the insights, great.

25 00:03:18.120 00:03:33.929 Nandika Jhunjhunwala: So, this is the one you made. I thought this was great, but there were, like, other tables feature engagement, and maybe you were thinking of it from, like, a higher level, like, clicking on the table icon, like, creating a view, requesting an enrichment, saving it as a new view.

26 00:03:33.930 00:03:40.820 Nandika Jhunjhunwala: Yep. I made, like, another one that’s, like, similar to this, so I’ll just flag it for you. Okay.

27 00:03:40.820 00:03:42.210 Greg Stoutenburg: Should I scroll to find it?

28 00:03:43.080 00:03:45.489 Nandika Jhunjhunwala: Yeah, this one.

29 00:03:45.490 00:03:45.899 Greg Stoutenburg: This one?

30 00:03:45.900 00:04:05.130 Nandika Jhunjhunwala: Yeah, again, a lot of this here is not significant activity, like, toggling the sidebar is not significant, or, like, syncing changes, that might be a significant one that we could add here. Syncing changes means you’re syncing the data back to, like, the data model.

31 00:04:05.490 00:04:08.159 Greg Stoutenburg: Okay, these were all the view menu action buttons.

32 00:04:09.200 00:04:12.579 Nandika Jhunjhunwala: No, not all of them.

33 00:04:13.310 00:04:13.670 Greg Stoutenburg: Sorry.

34 00:04:13.670 00:04:15.640 Nandika Jhunjhunwala: I’ll show you my piece.

35 00:04:15.640 00:04:17.269 Greg Stoutenburg: I may be in the wrong chart.

36 00:04:18.190 00:04:28.619 Nandika Jhunjhunwala: Sorry. Let me… I’ll share, at least visually would help, too.

37 00:04:28.620 00:04:29.449 Greg Stoutenburg: Yeah, go ahead.

38 00:04:29.770 00:04:31.889 Nandika Jhunjhunwala: That tripped me up as well, so…

39 00:04:32.460 00:04:36.449 Nandika Jhunjhunwala: Okay, let me open the project.

40 00:04:36.820 00:04:37.630 Greg Stoutenburg: Sure.

41 00:04:39.390 00:04:42.660 Nandika Jhunjhunwala: Do you see my versatile screen, or do you see the post hoc still?

42 00:04:42.660 00:04:44.780 Greg Stoutenburg: I don’t see anything from yours.

43 00:04:44.780 00:04:46.129 Nandika Jhunjhunwala: Oh, okay, I’m sorry.

44 00:04:46.130 00:04:48.080 Greg Stoutenburg: That’s alright.

45 00:04:49.410 00:04:50.940 Nandika Jhunjhunwala: Oh, weird. Okay.

46 00:04:55.130 00:04:56.580 Nandika Jhunjhunwala: Do you see this now?

47 00:04:57.180 00:05:01.130 Greg Stoutenburg: Looks like it’s loading. Okay, cool. Alright, tables, all event activity. Okay, great.

48 00:05:01.130 00:05:14.740 Nandika Jhunjhunwala: Yes. So, the sidebar toggle is not super relevant, so this can definitely be, like, hidden. Sure. But the other stuff, like sync changes, I think that’s, like, a significant activity, and we can add that here as well.

49 00:05:14.960 00:05:25.070 Nandika Jhunjhunwala: Because you’re syncing whatever activity you did back to the data model. Yep. And then again, column toggle not super significant, filtering not super significant.

50 00:05:25.310 00:05:29.340 Nandika Jhunjhunwala: But, like, approving the same changes could also be significant.

51 00:05:29.530 00:05:44.930 Nandika Jhunjhunwala: you, you have the create view as well, and then, yeah, like, update view and all of that. So there’s, like, some granularity here, but I think, like, this captures most of it, and we can, like, combine them, and create one insight and, like.

52 00:05:45.070 00:05:49.710 Nandika Jhunjhunwala: Remove the redundancy from here, in terms of, like, sorry.

53 00:05:50.040 00:05:55.850 Nandika Jhunjhunwala: Removing redundancy here in terms of, like, some actions that don’t really signify much.

54 00:05:56.070 00:05:58.459 Nandika Jhunjhunwala: From, like, a user behavior perspective.

55 00:05:58.460 00:06:01.010 Greg Stoutenburg: Yeah, yeah, simple things like navigation.

56 00:06:01.010 00:06:01.630 Nandika Jhunjhunwala: Yeah.

57 00:06:01.630 00:06:03.840 Greg Stoutenburg: We don’t need to have recorded.

58 00:06:03.840 00:06:04.960 Nandika Jhunjhunwala: For sure.

59 00:06:04.960 00:06:18.539 Greg Stoutenburg: I mean, unless it is also, and it… sometimes this is the case, right? Unless that piece of navigation is by itself some significant product usage, then we can take it off to just understand, like, how users are using the feature.

60 00:06:18.960 00:06:24.290 Greg Stoutenburg: So, yeah, so some can come down, but yeah, mostly Put these charts together.

61 00:06:24.850 00:06:25.860 Nandika Jhunjhunwala: For sure.

62 00:06:25.860 00:06:26.540 Greg Stoutenburg: Nope.

63 00:06:26.670 00:06:36.080 Nandika Jhunjhunwala: And then there’s this one, this is, again, dialogue cancellation drop-off, so basically, whenever someone opens the dialogue, it doesn’t follow through and just, like, drops off.

64 00:06:36.650 00:06:43.799 Nandika Jhunjhunwala: That is, like, one. So, like, if someone opens the waterfall dialogue and doesn’t really, like, request enrichment, and just, like.

65 00:06:43.990 00:06:49.429 Nandika Jhunjhunwala: navigates out of it. This is what this is tracking, like, when the users bail.

66 00:06:49.610 00:06:54.729 Nandika Jhunjhunwala: So I have it, like, a stacked bar chart, so, like, it’s divided by, like…

67 00:06:54.940 00:07:03.170 Nandika Jhunjhunwala: where that dialog box is appearing, like… Okay. Force field, cube, pixel, waterfall,

68 00:07:03.490 00:07:07.499 Nandika Jhunjhunwala: Again, this data can be, funny.

69 00:07:09.140 00:07:12.019 Nandika Jhunjhunwala: But… yeah.

70 00:07:12.820 00:07:25.079 Nandika Jhunjhunwala: I don’t know if this was, like, significant, or… this is, like, something I was thinking we could do, like, a Slack notification off of. Yeah. Maybe? If it’s, like, a CRM dialogue box that people drop off of when they’re, like, onboarding. Right.

71 00:07:25.080 00:07:34.650 Nandika Jhunjhunwala: That could be, like, significant data in terms of, like, oh, okay, they were trying to connect the CRM, but they didn’t, and this could be, like, a good outreach point for us to be like, hey, you know.

72 00:07:34.970 00:07:42.560 Nandika Jhunjhunwala: let me… let us know if we can help you connect the CRM, or, like, give them, like, a document, like, while the CRM connector.

73 00:07:42.560 00:07:55.179 Greg Stoutenburg: I like that. So I guess a way to think about what this chart is doing is that this kind of cuts across several funnels. So, if we had a funnel for, you know, for finishing the queue, for finishing the pixel.

74 00:07:55.180 00:07:55.730 Nandika Jhunjhunwala: so much heat.

75 00:07:55.730 00:08:10.889 Greg Stoutenburg: for finishing Salesforce setup, then we’d see those drop-offs there, but what this can help us do is go, alright, so like, you know, imagine you did a pivot on the funnel drop-off stage. That’s kind of what this is, right?

76 00:08:10.890 00:08:12.140 Nandika Jhunjhunwala: Yeah.

77 00:08:12.140 00:08:12.770 Greg Stoutenburg: Yeah.

78 00:08:12.770 00:08:18.640 Nandika Jhunjhunwala: Yeah, and then I have the pixel funnel, specifically, so,

79 00:08:19.230 00:08:26.570 Nandika Jhunjhunwala: if they, like, click on add a domain, and then they, like, copy that code, and then that test kind of loads, yeah.

80 00:08:27.190 00:08:29.559 Nandika Jhunjhunwala: Yeah, I’ll just, like, show you the…

81 00:08:29.730 00:08:37.680 Nandika Jhunjhunwala: the funnel it’s tracking exactly. I think that… that would help me, like, create the, funnel as well. Yep.

82 00:08:37.970 00:08:39.309 Nandika Jhunjhunwala: Okay.

83 00:08:39.929 00:08:44.470 Nandika Jhunjhunwala: So… Sharing my second screen,

84 00:08:45.140 00:08:52.600 Nandika Jhunjhunwala: So if we go on configuration, pixel, can I do, like… Rain Forge.

85 00:08:53.040 00:08:53.920 Nandika Jhunjhunwala: -

86 00:08:54.640 00:08:57.569 Nandika Jhunjhunwala: And click Add Domain, so that’s the first step.

87 00:08:57.570 00:08:58.500 Greg Stoutenburg: Yep.

88 00:08:59.110 00:09:07.550 Nandika Jhunjhunwala: And then once you copy and click continue, that’s, like, the second step. And this is, like, the third step where it’s, like, testing.

89 00:09:07.870 00:09:13.300 Nandika Jhunjhunwala: Now set up, then continue. So that is the entire flow.

90 00:09:13.540 00:09:16.680 Nandika Jhunjhunwala: That I’m tracking here?

91 00:09:17.230 00:09:30.579 Greg Stoutenburg: Let’s make one thought real quick, since I saw what that final dialogue looked like. Let’s make sure that when the it’s now complete, message appears, that clicking cancel won’t register as a funnel drop-off.

92 00:09:31.860 00:09:32.759 Greg Stoutenburg: And the reason.

93 00:09:32.760 00:09:33.129 Nandika Jhunjhunwala: I’m saying.

94 00:09:33.130 00:09:45.569 Greg Stoutenburg: That is, if hitting the cancel button makes that drop-off event fire, then it’ll be misleading because, cancel appeared even though the setup was successful.

95 00:09:46.380 00:09:53.860 Nandika Jhunjhunwala: Hmm. I think that… Might be, like, a… bug, this…

96 00:09:54.250 00:09:56.349 Greg Stoutenburg: Yeah, so if you hit copy there…

97 00:09:57.050 00:10:04.880 Greg Stoutenburg: Watch what it… watch what it says at the end. Just wait for these all to run. So, it says now set up, but you can still hit the X or the cancel button.

98 00:10:06.840 00:10:13.649 Nandika Jhunjhunwala: Yeah, this is, like, a tricky one, because if they click cancel mid-process of it being tested.

99 00:10:13.650 00:10:14.300 Greg Stoutenburg: Yeah.

100 00:10:14.300 00:10:24.819 Nandika Jhunjhunwala: I’m assuming it would still, like… I’m not sure if it would still be set up. I guess for this one, we would know more once it’s, like, live in production as to, like.

101 00:10:24.820 00:10:25.680 Greg Stoutenburg: Yeah, yeah.

102 00:10:25.680 00:10:33.160 Nandika Jhunjhunwala: how Pixel would work, and I can ask the engineers as well, and this is, like, a great point out, because I didn’t gloss over that little.

103 00:10:33.160 00:10:55.240 Greg Stoutenburg: Yeah, no, yeah, sure, yeah, no, no problem. No, and this is just one of those ones where it’s like, depending on how the instrumentation is set up, that’s what would make it happen or not, right? If hitting cancel, if the event drop-off button just is hitting the cancel button, then actually you could drop off, right, the event fires, even though you actually set it up successfully.

104 00:10:55.240 00:10:56.069 Nandika Jhunjhunwala: Yeah, so…

105 00:10:56.070 00:10:58.300 Greg Stoutenburg: No, that’s just a follow-up for us to look at, yeah, it doesn’t have.

106 00:10:58.300 00:11:02.190 Nandika Jhunjhunwala: No, definitely. So, pixel setup, completed. Cool.

107 00:11:02.190 00:11:02.770 Greg Stoutenburg: Yeah.

108 00:11:02.770 00:11:03.530 Nandika Jhunjhunwala: Yeah.

109 00:11:03.530 00:11:11.950 Greg Stoutenburg: Yeah, so on this, right, on this funnel, it wouldn’t affect it, but on the overview chart that’s showing all of the cancellations, then that’s where

110 00:11:12.260 00:11:14.099 Greg Stoutenburg: That’s where we could get some noise.

111 00:11:14.300 00:11:15.850 Nandika Jhunjhunwala: Definitely, yeah.

112 00:11:15.850 00:11:16.490 Greg Stoutenburg: Yeah.

113 00:11:16.820 00:11:25.520 Nandika Jhunjhunwala: And then I have, like, this kind of fun one, which is just, like, navigation patterns, like, what are people clicking on, like, from the dock?

114 00:11:25.520 00:11:26.050 Greg Stoutenburg: Yep, good.

115 00:11:26.720 00:11:27.340 Greg Stoutenburg: Yep.

116 00:11:27.580 00:11:28.720 Nandika Jhunjhunwala: And it’s good.

117 00:11:28.890 00:11:33.960 Nandika Jhunjhunwala: It’s just, like, overall data. I couldn’t find, like, a good visualization for it, so I just kept it, like.

118 00:11:34.210 00:11:34.770 Greg Stoutenburg: Yeah.

119 00:11:35.630 00:11:41.290 Greg Stoutenburg: Well, one kind of visualization is the, oh, I’m gonna blank, what do they call it?

120 00:11:41.480 00:11:56.330 Greg Stoutenburg: like, journey, they might call it Journey. So it’ll show, like, if, you know, this many users clicked on this, and then, you know, there’s, like, an arrow, and then this percent went to app, this percent went to settings, this percent went to Routing.

121 00:11:57.420 00:12:00.199 Nandika Jhunjhunwala: Oh, is it, like, somewhere here, or…

122 00:12:00.290 00:12:02.149 Greg Stoutenburg: I don’t think it’s one of those.

123 00:12:02.150 00:12:02.855 Nandika Jhunjhunwala: Ugh.

124 00:12:05.780 00:12:07.899 Nandika Jhunjhunwala: Yeah,

125 00:12:11.830 00:12:15.180 Nandika Jhunjhunwala: Do I have to, like, query this differently, or…

126 00:12:15.180 00:12:18.069 Greg Stoutenburg: No, no, you don’t have to change anything like that.

127 00:12:20.440 00:12:26.290 Greg Stoutenburg: I feel like I’m in the area. Surveys Toolbar… No, those are all apps.

128 00:12:26.640 00:12:27.580 Nandika Jhunjhunwala: Hmm…

129 00:12:27.580 00:12:30.069 Greg Stoutenburg: I just want product analytics, new…

130 00:12:33.560 00:12:36.519 Greg Stoutenburg: User paths. That’s what I’m trying to find. Okay.

131 00:12:39.510 00:12:42.679 Nandika Jhunjhunwala: Oh, so maybe it’s not an insight and it’s a user path? Is it…

132 00:12:42.680 00:12:49.680 Greg Stoutenburg: Oh, wait, go back, go back one page, and maybe it was there. No, just, just go, just hit the back button.

133 00:12:50.040 00:12:50.980 Nandika Jhunjhunwala: Oh.

134 00:12:51.210 00:12:53.190 Nandika Jhunjhunwala: Oops.

135 00:12:53.190 00:12:54.490 Greg Stoutenburg: And… nope.

136 00:12:55.150 00:12:56.070 Nandika Jhunjhunwala: O.

137 00:12:59.200 00:13:06.199 Greg Stoutenburg: Okay. Now… Edit this, just like you were before, when you were looking at all those different options.

138 00:13:06.600 00:13:07.730 Nandika Jhunjhunwala: Like, here.

139 00:13:07.980 00:13:15.900 Greg Stoutenburg: Yeah, now, I saw… okay, that says results visualization. Oh, shoot. So, here’s what I’m looking at.

140 00:13:17.680 00:13:18.750 Greg Stoutenburg: And then…

141 00:13:19.060 00:13:23.899 Greg Stoutenburg: maybe you don’t have to stop your share, and I can just do mine. So, I just opened a new Product Analytics Insight.

142 00:13:24.400 00:13:27.309 Greg Stoutenburg: And of these options here, when I click User Paths.

143 00:13:27.480 00:13:29.760 Greg Stoutenburg: You get this kind of visualization.

144 00:13:29.960 00:13:30.760 Nandika Jhunjhunwala: Oh…

145 00:13:30.760 00:13:34.189 Greg Stoutenburg: This is what I was talking about. So this seems like a natural way to visualize what you were showing there.

146 00:13:34.190 00:13:34.749 Nandika Jhunjhunwala: Which is just.

147 00:13:34.750 00:13:39.579 Greg Stoutenburg: like, well, paths, right? The users land here, and then they go app, they go, you know.

148 00:13:39.580 00:13:39.960 Nandika Jhunjhunwala: Yes.

149 00:13:39.960 00:13:41.120 Greg Stoutenburg: vault, or whatever.

150 00:13:43.020 00:13:45.789 Nandika Jhunjhunwala: So I’ll make a note of that, and I’ll send it later.

151 00:13:45.790 00:13:48.479 Greg Stoutenburg: Yeah, we can follow up on that, yeah. Cool.

152 00:13:49.200 00:13:50.210 Greg Stoutenburg: Okay.

153 00:13:50.380 00:13:51.769 Greg Stoutenburg: Very good, very good.

154 00:13:53.050 00:13:53.569 Nandika Jhunjhunwala: Let’s keep…

155 00:13:53.570 00:13:54.320 Greg Stoutenburg: going.

156 00:13:54.830 00:13:57.360 Nandika Jhunjhunwala: Sounds good.

157 00:14:00.710 00:14:13.490 Nandika Jhunjhunwala: This was, again, like, a table feature usage. It was not a plan, but… Yeah. I think this is not super significant, because this is, like, when I go to tables, they’re…

158 00:14:13.900 00:14:16.750 Nandika Jhunjhunwala: And I click on… Oh.

159 00:14:22.290 00:14:25.500 Nandika Jhunjhunwala: And then I, like, it’s these four options here.

160 00:14:25.500 00:14:26.140 Greg Stoutenburg: Okay.

161 00:14:26.140 00:14:29.559 Nandika Jhunjhunwala: So… and that’s what this is? Yeah.

162 00:14:29.560 00:14:30.890 Greg Stoutenburg: Some interactions, yeah.

163 00:14:30.890 00:14:36.919 Nandika Jhunjhunwala: Yeah, so I don’t… this is not useful, right? So I can just, remove this from the dashboard.

164 00:14:36.920 00:14:39.410 Greg Stoutenburg: Yeah, yeah, we don’t have to delete it or anything like that, we might decide.

165 00:14:39.410 00:14:39.940 Nandika Jhunjhunwala: later on.

166 00:14:39.940 00:14:41.330 Greg Stoutenburg: There’s a reason for it.

167 00:14:41.560 00:14:47.890 Nandika Jhunjhunwala: Yeah, but this was… that was, like, not… and here, this is, like, the integration funnel, like.

168 00:14:47.890 00:14:48.480 Greg Stoutenburg: Yeah.

169 00:14:48.480 00:14:49.320 Nandika Jhunjhunwala: ends?

170 00:14:49.520 00:15:01.819 Nandika Jhunjhunwala: The only issue I’m seeing is, like, I’m seeing Google and Google Meet separately for some weird reason, so I will check into that. Maybe they are separate things?

171 00:15:01.820 00:15:02.360 Greg Stoutenburg: Yeah.

172 00:15:02.360 00:15:07.530 Nandika Jhunjhunwala: I go to Integrations… There’s Google Meet.

173 00:15:07.530 00:15:08.220 Greg Stoutenburg: meet.

174 00:15:08.540 00:15:22.549 Nandika Jhunjhunwala: Oh, maybe Google Calendar and Google Meet are showing differently. So it could just be an instrumentation error, and I should label them properly. So I will, I will check into that. Okay.

175 00:15:22.990 00:15:24.040 Nandika Jhunjhunwala: Yeah.

176 00:15:24.200 00:15:28.769 Nandika Jhunjhunwala: And then funnel creation. This is the one you made, right? The funnel creation?

177 00:15:29.280 00:15:32.849 Greg Stoutenburg: That sounds… that looks like my kind of chart.

178 00:15:32.970 00:15:36.700 Nandika Jhunjhunwala: So I put it here, but I guess we don’t have a lot of activity on there.

179 00:15:39.280 00:15:41.150 Greg Stoutenburg: Yeah, it’s okay, we’re just testing, so…

180 00:15:41.150 00:15:46.999 Nandika Jhunjhunwala: Yeah, is this… Oh, you have, like, yeah, window limit, 14 days, so…

181 00:15:47.000 00:15:47.670 Greg Stoutenburg: Yeah.

182 00:15:47.990 00:15:48.710 Nandika Jhunjhunwala: Yeah.

183 00:15:50.110 00:15:50.700 Greg Stoutenburg: Okay.

184 00:15:54.200 00:16:04.550 Nandika Jhunjhunwala: This is, like, view… this is also, like, not super useful. There’s, like, a different way of visualizing the one that I deleted, like, update, view, delete view, save view.

185 00:16:04.550 00:16:05.680 Greg Stoutenburg: Yep. Okay.

186 00:16:05.830 00:16:22.260 Nandika Jhunjhunwala: And I can remove this as well, because I’m pretty sure that’s not super helpful. This is an interesting one, like, this is very niche, I guess, like, or switching frequency. So, like, if someone’s part of two organizations, like, switching, so if I go here, like…

187 00:16:22.730 00:16:23.280 Greg Stoutenburg: Yep.

188 00:16:23.280 00:16:27.019 Nandika Jhunjhunwala: organization, and how frequently do I do that?

189 00:16:27.020 00:16:27.650 Greg Stoutenburg: Yep.

190 00:16:28.130 00:16:30.410 Nandika Jhunjhunwala: That’s, like, what this is.

191 00:16:30.690 00:16:37.739 Nandika Jhunjhunwala: Or how many people do that? Very niche insight, I guess, wouldn’t be super relevant until, like, half later.

192 00:16:37.740 00:16:45.450 Greg Stoutenburg: Yeah, I mean, I was… I will be curious to see how many individuals are active in more than one organization.

193 00:16:46.240 00:16:51.950 Greg Stoutenburg: Especially if they’re not only a member of another organization, but use them, both.

194 00:16:52.190 00:17:04.599 Greg Stoutenburg: To any significant degree. I think that’ll be interesting for understanding something about power users. Maybe it’ll turn out power users are, you know, one of the rules is that they have more than one organization, or maybe not.

195 00:17:04.609 00:17:16.109 Nandika Jhunjhunwala: Definitely. I think for, like, our partnerships motion, this could be interesting as well, where our partners, like, recommend default to, like, multiple clients, and, like, set up for different people.

196 00:17:16.109 00:17:16.589 Greg Stoutenburg: Yep.

197 00:17:16.589 00:17:23.339 Nandika Jhunjhunwala: And I’m sure there’s, like, a better way of visualizing it as well than, like, this line chart, probably. Yeah.

198 00:17:23.619 00:17:24.349 Greg Stoutenburg: Yeah.

199 00:17:25.889 00:17:26.799 Greg Stoutenburg: Okay.

200 00:17:27.619 00:17:32.999 Nandika Jhunjhunwala: And then this one should have more data later on, but this is, like, most popular waterfall providers.

201 00:17:33.209 00:17:39.369 Nandika Jhunjhunwala: Okay. So if I go here, and… Configure waterfall.

202 00:17:39.859 00:17:43.559 Nandika Jhunjhunwala: And, like… or if I look at an existing one…

203 00:17:43.949 00:17:47.739 Nandika Jhunjhunwala: Like, which one do people, like, use the most?

204 00:17:47.949 00:17:53.079 Nandika Jhunjhunwala: Sort of data, provider added.

205 00:17:53.179 00:17:58.949 Nandika Jhunjhunwala: So which provider has been added to, like, the most amount of waterfalls total?

206 00:17:59.449 00:18:01.649 Nandika Jhunjhunwala: Yeah, that’s…

207 00:18:01.939 00:18:07.599 Nandika Jhunjhunwala: I don’t know why there’s only people data labs here. I don’t think we have, like, data on War currently, but…

208 00:18:08.330 00:18:13.440 Nandika Jhunjhunwala: Yeah, we’ll know more on this, I guess, once people use… use it more.

209 00:18:13.440 00:18:16.679 Greg Stoutenburg: Yep. Yeah, and right now, really, we’re just sort of looking at

210 00:18:16.830 00:18:29.990 Greg Stoutenburg: chart types that we need. Like, some of this… like, the things that we find useful for the… for analyzing tables, we’ll just sort of take that same structure and use it for the other features as well, and then what we’ll end up with is a feature engagement dashboard.

211 00:18:30.060 00:18:38.289 Greg Stoutenburg: You know what I mean? So, like, that’ll be one output. And then we look at things like, admin behaviors, and that’s things like.

212 00:18:38.290 00:18:38.760 Nandika Jhunjhunwala: Yeah.

213 00:18:38.760 00:18:41.029 Greg Stoutenburg: Team management and invites sent.

214 00:18:41.100 00:18:59.300 Greg Stoutenburg: switching orgs, you know, that’ll then naturally constitute another sort of dashboard, and all of this will roll up to higher-level things like, you know, engagement and conversion to certain types of add-ons and plan changes and contacting sales and things like that.

215 00:18:59.300 00:19:00.430 Nandika Jhunjhunwala: Yeah, definitely.

216 00:19:01.150 00:19:04.640 Nandika Jhunjhunwala: This was a fun one, like…

217 00:19:05.210 00:19:20.990 Nandika Jhunjhunwala: team management, so if you’ve sent an email invite to someone, if a user’s role has changed, and this could be, like, a good, like, signal here, like, if a user’s role has changed to admin, like, outreach signal or, like.

218 00:19:21.380 00:19:29.160 Nandika Jhunjhunwala: a specific funnel or, like, a specific insight to specifically track just that could be interesting.

219 00:19:30.060 00:19:49.630 Nandika Jhunjhunwala: Yeah, because if someone’s been converted to an admin, like, we currently, like, enable them to use default better, like, we set up a call with them, and I’m assuming, like, if it’s a good… good customer, or, like, a high priority customer, we would do the same, or if it’s a PRG motion, we would, like, send them.

220 00:19:49.630 00:19:50.160 Greg Stoutenburg: Yeah.

221 00:19:50.160 00:19:51.770 Nandika Jhunjhunwala: I’ll read. Yeah.

222 00:19:52.170 00:20:01.609 Greg Stoutenburg: Something else for us to add here, and maybe we’ll have to think about the right way to add it, but, is users who join because they were sent an invitation link.

223 00:20:01.820 00:20:02.470 Nandika Jhunjhunwala: Yeah.

224 00:20:02.510 00:20:07.539 Greg Stoutenburg: And so then we could add a row for, like, you know, user joined via invite.

225 00:20:08.960 00:20:09.660 Nandika Jhunjhunwala: Yep.

226 00:20:09.950 00:20:14.860 Greg Stoutenburg: And then that would help us get a ratio of invites sent to invites received.

227 00:20:16.120 00:20:17.100 Nandika Jhunjhunwala: Yeah.

228 00:20:17.380 00:20:19.150 Nandika Jhunjhunwala: That would be… that would be cool.

229 00:20:20.030 00:20:20.670 Greg Stoutenburg: Yep.

230 00:20:21.760 00:20:22.700 Greg Stoutenburg: Okay.

231 00:20:22.860 00:20:30.639 Greg Stoutenburg: Any other… I will have a hard stop at 2.30, so maybe we could… Yeah. …review, see if there’s anything else that’s big down here.

232 00:20:30.640 00:20:33.299 Nandika Jhunjhunwala: Yeah. Like, logging out, like…

233 00:20:33.670 00:20:52.399 Nandika Jhunjhunwala: login activity. It’s, like, calendar connection, same as, like, Google… I’ve seen Google and Google Meet separately, so I’ll look into that. Yeah. This is, like, field mapping changes. Again, I don’t think this is super relevant, and I can remove this for now. I think it’s just gonna cause confusion.

234 00:20:52.670 00:20:55.140 Nandika Jhunjhunwala: And then field mapping by source, like…

235 00:20:55.670 00:21:04.229 Nandika Jhunjhunwala: what sources they’re prioritizing the most, like, form data, pixel data, enrichment data, stuff like that. Yeah.

236 00:21:04.470 00:21:05.920 Greg Stoutenburg: Yeah, that’s good.

237 00:21:05.920 00:21:16.060 Nandika Jhunjhunwala: Yeah. And then I have, like, custom field creation funnel, like, if someone’s creating, like, a custom field, so, to give you context.

238 00:21:16.480 00:21:16.800 Greg Stoutenburg: Yeah.

239 00:21:16.800 00:21:20.310 Nandika Jhunjhunwala: Like, configuration objects.

240 00:21:20.690 00:21:27.250 Nandika Jhunjhunwala: company, and I have all these fields under company, but someone creates, like, a specific field that doesn’t…

241 00:21:27.540 00:21:31.299 Nandika Jhunjhunwala: show up here, that would be a custom field.

242 00:21:31.300 00:21:31.850 Greg Stoutenburg: Yeah.

243 00:21:32.760 00:21:40.060 Nandika Jhunjhunwala: And then I just had this, like, one that has, like, all activities ever in the objects.

244 00:21:40.280 00:21:46.419 Nandika Jhunjhunwala: So, like, here, because so much of Phoenix hinges on the core data model,

245 00:21:46.420 00:21:47.030 Greg Stoutenburg: Yeah.

246 00:21:47.210 00:21:57.599 Nandika Jhunjhunwala: this is all, like, activities related to, like, people configuring the core data model. A lot of it could be, like, redundant, and we can identify that and remove it from the chart.

247 00:21:57.730 00:22:03.730 Nandika Jhunjhunwala: I don’t know if, like, object priority, like, reordering is interesting, or if they, like.

248 00:22:04.220 00:22:09.909 Nandika Jhunjhunwala: do something like that, that would be interesting. But I have it here just as, like.

249 00:22:09.910 00:22:13.559 Greg Stoutenburg: Yeah. Yeah, I think that’ll be something to dive in on specifically.

250 00:22:13.560 00:22:13.920 Nandika Jhunjhunwala: And we’ll.

251 00:22:13.920 00:22:22.529 Greg Stoutenburg: end up making a few different charts for that, and just need to have a view toward where do we think users are going to find value there, and then we can take that understanding and work backward.

252 00:22:22.640 00:22:24.330 Greg Stoutenburg: To map out the right things.

253 00:22:25.780 00:22:40.929 Nandika Jhunjhunwala: Yeah. But yeah, just to give you a quick overview, and yeah, let me know if I can expand on something further that doesn’t look self-explanatory. Yeah. And yeah, if you have any more, like, insights on, like, what I can do further, I’ll…

254 00:22:40.930 00:22:49.459 Greg Stoutenburg: Yeah, I like it. Yeah, no, this is… this is great. So, great start here. And I’ll come back with, you know, notes and things, and think about where we can expand.

255 00:22:49.640 00:23:01.279 Greg Stoutenburg: I think something that we’ll want to include that isn’t here is time to value, especially since we’re going in the PLG direction, like, time to value from first sign-up to some of these actions, right?

256 00:23:01.790 00:23:15.099 Greg Stoutenburg: first calendar connected to first queue created. Some of those are going to be important for us, because it’s always the case in PLG

257 00:23:15.150 00:23:27.810 Greg Stoutenburg: Especially, you know, on the self-service side, that users are able to quickly and efficiently get from signing up to doing those first things in order that you’re able to retain them and hopefully get them to, you know, use a lot and convert.

258 00:23:30.570 00:23:31.720 Nandika Jhunjhunwala: Sounds good.

259 00:23:31.720 00:23:32.530 Greg Stoutenburg: Cool.

260 00:23:32.860 00:23:39.019 Greg Stoutenburg: All right, well, we’ll do that, I’ll have a follow-up on that, and we can talk about it soon.

261 00:23:39.240 00:23:40.640 Nandika Jhunjhunwala: Yeah, thank you.

262 00:23:40.640 00:23:41.440 Greg Stoutenburg: Thanks for work.

263 00:23:41.780 00:23:42.290 Greg Stoutenburg: See you not again.

264 00:23:42.290 00:23:43.710 Nandika Jhunjhunwala: Bye. Thanks, bye.