Meeting Title: Brainforge Dashboard Progress Check-in Date: 2026-04-09 Meeting participants: Greg Stoutenburg, Nandika Jhunjhunwala, Demilade Agboola
WEBVTT
1 00:00:21.270 ⇒ 00:00:22.400 Greg Stoutenburg: Hey, Nautica.
2 00:00:23.080 ⇒ 00:00:24.620 Nandika Jhunjhunwala: Hi, how’s it going?
3 00:00:24.780 ⇒ 00:00:26.130 Greg Stoutenburg: Doing alright. How’s your week?
4 00:00:26.570 ⇒ 00:00:29.059 Nandika Jhunjhunwala: Good! Drinking coffee?
5 00:00:30.300 ⇒ 00:00:31.969 Greg Stoutenburg: Yeah, I think this is,
6 00:00:32.870 ⇒ 00:00:34.630 Greg Stoutenburg: My sixth cup of the day?
7 00:00:34.810 ⇒ 00:00:35.759 Nandika Jhunjhunwala: Oh, wow.
8 00:00:35.760 ⇒ 00:00:36.489 Greg Stoutenburg: Yeah, yeah, yeah.
9 00:00:36.490 ⇒ 00:00:38.900 Nandika Jhunjhunwala: Wow, are you okay?
10 00:00:38.900 ⇒ 00:00:39.250 Greg Stoutenburg: No.
11 00:00:40.140 ⇒ 00:00:45.189 Greg Stoutenburg: No, people shouldn’t do this. Yeah, I,
12 00:00:45.310 ⇒ 00:00:48.480 Greg Stoutenburg: I don’t know, I’m just a really big coffee drinker, just like…
13 00:00:49.050 ⇒ 00:00:55.190 Greg Stoutenburg: Yeah, and I think also there’s just… when there’s not a lot of, like, break time to do things like
14 00:00:55.880 ⇒ 00:00:57.760 Greg Stoutenburg: Just a quick exercise to, like, eat something.
15 00:00:57.760 ⇒ 00:00:58.200 Nandika Jhunjhunwala: Yeah.
16 00:00:58.200 ⇒ 00:01:06.049 Greg Stoutenburg: Besides the old taco that I found a minute ago in my, in my fridge, then just coffee just keeps the machine running, you know?
17 00:01:06.050 ⇒ 00:01:11.099 Nandika Jhunjhunwala: No, I get that. I’m just super caffeine sensitive, so if I have, like, 2 cups.
18 00:01:11.230 ⇒ 00:01:15.270 Nandika Jhunjhunwala: I’m, like, a little too… jittery?
19 00:01:15.270 ⇒ 00:01:17.919 Greg Stoutenburg: Yeah, yeah, yeah, I understand that.
20 00:01:17.920 ⇒ 00:01:24.459 Nandika Jhunjhunwala: For me, 6 cups is… 6 cups are, like, unfathomable, like, I would die. I would be in the ER.
21 00:01:24.460 ⇒ 00:01:29.060 Greg Stoutenburg: Yeah, yeah, I had a… let’s see. Well, you know, tolerance grows over time, so I had a…
22 00:01:29.450 ⇒ 00:01:31.600 Greg Stoutenburg: Let’s see, I had a… I had a 12-ounce cup.
23 00:01:31.980 ⇒ 00:01:37.930 Greg Stoutenburg: And then, I had a… large Dunkin’ Donuts cold brew.
24 00:01:37.930 ⇒ 00:01:38.620 Nandika Jhunjhunwala: Whoa.
25 00:01:38.620 ⇒ 00:01:40.709 Greg Stoutenburg: back, and I had another 12-ounce cup.
26 00:01:41.130 ⇒ 00:01:45.280 Greg Stoutenburg: And then… and then 2 more. Yeah, I’m at 6, including the cold brew.
27 00:01:45.280 ⇒ 00:01:46.600 Nandika Jhunjhunwala: Oh my god.
28 00:01:46.600 ⇒ 00:01:47.330 Greg Stoutenburg: Yeah.
29 00:01:47.770 ⇒ 00:01:49.970 Nandika Jhunjhunwala: Have you tried going a day without coffee?
30 00:01:50.150 ⇒ 00:01:50.800 Greg Stoutenburg: Oh yeah, I can do it.
31 00:01:50.800 ⇒ 00:01:51.810 Nandika Jhunjhunwala: an experiment.
32 00:01:51.810 ⇒ 00:01:53.170 Greg Stoutenburg: It’s just a terrible day.
33 00:01:53.680 ⇒ 00:01:56.529 Nandika Jhunjhunwala: Oh my god, I’m so sorry!
34 00:01:56.530 ⇒ 00:02:02.480 Greg Stoutenburg: Yeah, I mean, like, the headache kicks in right away. I…
35 00:02:02.610 ⇒ 00:02:10.280 Greg Stoutenburg: I use it… well, I used to just do that, like, every… every few months or so. Just go, like, alright, I’m gonna remove my caffeine addiction. I’m just not gonna have…
36 00:02:10.479 ⇒ 00:02:10.879 Nandika Jhunjhunwala: many calls.
37 00:02:10.880 ⇒ 00:02:20.819 Greg Stoutenburg: for, like, you know, for a week. I think it takes most people something like… it’s not that long, like, five days, and you’ll pick your habit. The problem is that that… is that at, like.
38 00:02:21.260 ⇒ 00:02:28.169 Greg Stoutenburg: At, like, 30 hours after you’ve had your last cup of coffee, it hits you, and that’s when, like, the withdrawal really starts happening.
39 00:02:29.100 ⇒ 00:02:31.160 Greg Stoutenburg: And I remember reading that that’s…
40 00:02:31.530 ⇒ 00:02:35.379 Greg Stoutenburg: Believed to be one of the reasons why people become daily coffee drinkers, is because, like.
41 00:02:35.380 ⇒ 00:02:36.180 Nandika Jhunjhunwala: Mmm.
42 00:02:36.180 ⇒ 00:02:42.569 Greg Stoutenburg: I don’t know, half-life of caffeine in the brain, or however that works exactly, is… it really is around 24 hours or so.
43 00:02:42.780 ⇒ 00:02:43.290 Nandika Jhunjhunwala: Damn.
44 00:02:43.290 ⇒ 00:02:46.190 Greg Stoutenburg: So then you have it every morning, so you continue to live.
45 00:02:51.380 ⇒ 00:02:55.369 Greg Stoutenburg: Alright, where’s everybody at? I know that Lev is not coming.
46 00:02:56.210 ⇒ 00:02:59.309 Nandika Jhunjhunwala: Oh, neither is Caitlin. She’s traveling right now.
47 00:02:59.310 ⇒ 00:02:59.950 Greg Stoutenburg: Oh, okay.
48 00:02:59.950 ⇒ 00:03:02.789 Nandika Jhunjhunwala: Coming to the office, actually, so we can get started.
49 00:03:02.790 ⇒ 00:03:03.569 Greg Stoutenburg: Cool, let’s do it.
50 00:03:03.570 ⇒ 00:03:04.620 Nandika Jhunjhunwala: from default.
51 00:03:04.950 ⇒ 00:03:06.380 Greg Stoutenburg: Oh, okay, okay, cool.
52 00:03:06.550 ⇒ 00:03:13.509 Greg Stoutenburg: Well, let’s just jump right into it, then. So, I will share the deck, and…
53 00:03:13.860 ⇒ 00:03:20.620 Greg Stoutenburg: We’ll go kind of quickly through the deck, and then I’d like to just pull up Omni and kind of chat about where we are there. So,
54 00:03:21.030 ⇒ 00:03:25.349 Greg Stoutenburg: That’s our… that’s our overview, table of contents.
55 00:03:25.780 ⇒ 00:03:38.369 Greg Stoutenburg: we’ve got… for all the dashboard spec that we’re aligned on a few months ago that Demolade has been sort of, you know, plowing away on with the modeling and the dashboard creation, we’re to the point where we’re…
56 00:03:38.370 ⇒ 00:03:54.540 Greg Stoutenburg: We’ve only got a few left, and, it’s pretty exciting to see how much work has been done, and so quickly, and been reviewed and QA’d. So, I spoke with Laura yesterday morning, and got feedback on the, on the Customer Success Dashboard.
57 00:03:54.710 ⇒ 00:04:04.950 Greg Stoutenburg: she… her… her insight was, this was actually really helpful to just, like, have this one-on-one with her. So, she shared that, like, the goal of all of this dashboarding
58 00:04:05.260 ⇒ 00:04:21.680 Greg Stoutenburg: from her perspective is to help manage all of these different teams, because there isn’t currently much of a finger on the pulse of how these different parts of the organization are doing, and so this is going to provide, like, a level of executive and management oversight on how different parts of the business are performing. So.
59 00:04:21.800 ⇒ 00:04:29.379 Greg Stoutenburg: getting that context, I think, was very helpful for being clear on where we can improve, on
60 00:04:29.380 ⇒ 00:04:44.219 Greg Stoutenburg: on… when we have our reporting done, where we can look to see, you know, where there are gaps where we think that there are solutions or ways to help default win and help the teams grow. So, that was very helpful. She had some feedback that I’ve ticketed out and that we’ll… we’ll work on.
61 00:04:44.220 ⇒ 00:04:58.179 Greg Stoutenburg: Mostly what amount to things like tweaks, but also some additional charts, like, like, by customer success rep, what are the… what’s the average deal size that renews in a given month? Like, things like that.
62 00:04:58.640 ⇒ 00:05:16.420 Greg Stoutenburg: As well, Demi is, Demi and Ryan and I talked about the ARR dashboard this morning. Ryan had some more questions around figures that are being reported as included in ARR or not included in ARR, and so we’re gonna, part of the solution is gonna be just
63 00:05:16.420 ⇒ 00:05:26.590 Greg Stoutenburg: getting some additional documentation right on the dashboard, which is something that we’ve talked about before. We want to continue to do so that it takes us further in the direction of self-service.
64 00:05:26.630 ⇒ 00:05:34.679 Greg Stoutenburg: And then, finally actioning the customer reporting and enablement feedback that we received. You know, recently.
65 00:05:34.960 ⇒ 00:05:37.439 Greg Stoutenburg: On the product analytics side, you know, as we know.
66 00:05:37.570 ⇒ 00:05:57.500 Greg Stoutenburg: We’re still just continuing to work on the progress toward getting all the dashboards done that were in our initial SOW. Advait, on our team, I think he was invited, looks like he’s not on this call right now, but I gave him the document that we reviewed that… that show, like, the gap between
67 00:05:57.500 ⇒ 00:06:05.839 Greg Stoutenburg: Charts that we have currently that were largely built by you, and the charts that we need to have to have sort of rounded-out reporting on these various dashboards.
68 00:06:05.840 ⇒ 00:06:12.379 Greg Stoutenburg: And, and have given him some of those to continue, you know, building those charts and organizing the dashboards.
69 00:06:13.600 ⇒ 00:06:20.310 Greg Stoutenburg: I just said a lot of this. So I think the two that I didn’t say are lines
70 00:06:20.590 ⇒ 00:06:37.910 Greg Stoutenburg: 2 and 3 here. Modeling for the BDR dashboard is in progress, and so that’s a matter of getting business logic to, the live Salesforce data. And as well, this is a place where Laura’s, Laura’s context yesterday was so helpful, right? Like, the goal is
71 00:06:37.920 ⇒ 00:06:48.589 Greg Stoutenburg: to help the BDR team be effective. So as we continue to build this thing, we’ll keep that view in mind, and it’ll, you know, it’ll inform what we decide to put on the dash and not…
72 00:06:48.590 ⇒ 00:06:49.800 Nandika Jhunjhunwala: Totally.
73 00:06:50.010 ⇒ 00:06:50.590 Greg Stoutenburg: Yeah.
74 00:06:50.590 ⇒ 00:06:58.020 Nandika Jhunjhunwala: On the BDR modeling, I have a ton of context on what’s needed as well, so…
75 00:06:58.020 ⇒ 00:06:58.750 Greg Stoutenburg: Yeah, please.
76 00:06:58.750 ⇒ 00:07:05.299 Nandika Jhunjhunwala: either me or Lev, if you need to, like, brainstorm or, like, talk through metrics, live.
77 00:07:05.720 ⇒ 00:07:10.320 Nandika Jhunjhunwala: I can identify on the table for them, on the table for you as well.
78 00:07:10.490 ⇒ 00:07:21.830 Nandika Jhunjhunwala: So, would love to get this moved along, like, as soon as possible. So, this is, like, one year that I can totally, like, I have all the context, like, equals, I don’t really dabble in, but…
79 00:07:21.830 ⇒ 00:07:22.180 Greg Stoutenburg: Yeah.
80 00:07:22.180 ⇒ 00:07:22.970 Nandika Jhunjhunwala: Seta.
81 00:07:23.140 ⇒ 00:07:26.689 Nandika Jhunjhunwala: I have a decent handle on, so let me know if I can be helpful there.
82 00:07:26.870 ⇒ 00:07:34.410 Greg Stoutenburg: Yeah, I appreciate that, yeah, and I think, I haven’t… I also just haven’t had a call with Lev, so I think he’s someone that I need to talk to.
83 00:07:34.410 ⇒ 00:07:34.790 Nandika Jhunjhunwala: Yeah.
84 00:07:35.750 ⇒ 00:07:36.450 Nandika Jhunjhunwala: Yeah, for sure.
85 00:07:36.450 ⇒ 00:07:37.259 Greg Stoutenburg: But, you know…
86 00:07:37.260 ⇒ 00:07:41.819 Nandika Jhunjhunwala: Love to be looped in there as well, and we can all talk about the data, yeah.
87 00:07:41.820 ⇒ 00:08:00.909 Greg Stoutenburg: Yeah, yep, talk about the data, and really, you know, for me, what’s very helpful to help everyone most effectively is just understanding what the concerns are, right? Like, what is it you want to try to do? And then we move backward from that, right? We understand the goal, and then we move back a step to what do we need to do to get there. So yeah, that sounds good. We’ll make that a follow-up.
88 00:08:01.080 ⇒ 00:08:01.510 Nandika Jhunjhunwala: Oh.
89 00:08:02.750 ⇒ 00:08:04.850 Nandika Jhunjhunwala: to shoot… yeah, sorry, Ego Brew.
90 00:08:04.850 ⇒ 00:08:20.069 Demilade Agboola: In terms of, like, the BDR stuff, like, modeling is in flight. We’re currently using… if you see the old dashboard metrics file, so we’re currently trying to build out the metrics to build out what we need right now.
91 00:08:20.170 ⇒ 00:08:22.509 Demilade Agboola: And so the…
92 00:08:23.450 ⇒ 00:08:39.279 Demilade Agboola: there will be some questions around certain things, and maybe certain definitions of certain things, but right now, yeah, we have started the modeling. The idea is by next week, we can start to show what’s been done, and then you can also use that to help fill out some certain contacts.
93 00:08:39.320 ⇒ 00:08:48.469 Demilade Agboola: And use that to be able to enrich, like, what we have so far. So right now, just think of it, like, building foundations and everything around that right now.
94 00:08:49.120 ⇒ 00:08:52.100 Nandika Jhunjhunwala: Yeah, with the modeling aspect too, I think
95 00:08:52.720 ⇒ 00:08:56.040 Nandika Jhunjhunwala: Especially because Salesforce data is so tricky, and so, like…
96 00:08:56.550 ⇒ 00:09:04.320 Nandika Jhunjhunwala: nuanced, maybe we connect pre… you finishing modeling as well, just because it would
97 00:09:04.800 ⇒ 00:09:14.509 Nandika Jhunjhunwala: it would just be, like, duplicative work to, like, go back in there and, like, fix stuff, because I know, like, CRMs are so tricky, you know, like, we have, like, 10 queues that say the same thing,
98 00:09:15.320 ⇒ 00:09:20.639 Nandika Jhunjhunwala: Just to give you additional context there, and I guess for the BDR dashboard in general.
99 00:09:20.940 ⇒ 00:09:34.130 Nandika Jhunjhunwala: the view is, like, the idea is to, like, have, like, an overview of BDR activity, how they’re performing at, like, baseline, like, we have, like, 3DRs right now, but I think the team is going to continue to grow.
100 00:09:34.210 ⇒ 00:09:46.750 Nandika Jhunjhunwala: to, like, see how many, like, how much, you know, activity they’re doing in terms of, like, outreach and, like, the outcomes of that, and tracking that over, like, a time period, and, like, analyzing trends is, like, the goal of the BER dashboards.
101 00:09:47.510 ⇒ 00:09:51.459 Nandika Jhunjhunwala: It’s very granular sales activity data that we were trying to see.
102 00:09:51.780 ⇒ 00:09:59.879 Nandika Jhunjhunwala: to make informed decisions, for the sales team in general. And I think Laura has oversight on that as well.
103 00:10:00.050 ⇒ 00:10:04.260 Nandika Jhunjhunwala: So she is very interested in the dashboard, from, like, an executive perspective.
104 00:10:04.380 ⇒ 00:10:04.910 Greg Stoutenburg: Yeah.
105 00:10:04.910 ⇒ 00:10:07.120 Nandika Jhunjhunwala: For some additional context there.
106 00:10:09.060 ⇒ 00:10:11.720 Greg Stoutenburg: Yeah, that’s helpful. I think,
107 00:10:12.090 ⇒ 00:10:14.630 Greg Stoutenburg: Demi, we’ll chat about the specs for the dash.
108 00:10:14.970 ⇒ 00:10:17.340 Greg Stoutenburg: Something that, as, you know.
109 00:10:17.920 ⇒ 00:10:32.099 Greg Stoutenburg: thinking about this as we’re talking about it right now, maybe understanding what the BDR’s goals are is something that would be really helpful, right? Like, if it’s… if it’s something that the BDRs need to see, or the management needs to see, having some documentation, like, here’s what we’re…
110 00:10:32.100 ⇒ 00:10:47.230 Greg Stoutenburg: here’s what a good month for a BDR looks like, or here’s what a good quarter for BDR looks like, and so we can have that right on the dash, and we can also make sure that we’ve got… if we don’t already have it built in, then we can have charts that sort of, like, very directly align with
111 00:10:47.230 ⇒ 00:10:50.780 Greg Stoutenburg: With hitting those targets and showing progress toward those targets.
112 00:10:53.430 ⇒ 00:10:54.240 Greg Stoutenburg: Yep.
113 00:10:55.830 ⇒ 00:10:57.390 Greg Stoutenburg: Right,
114 00:10:57.770 ⇒ 00:11:10.360 Greg Stoutenburg: This is the ARR dash, Laura signed off, and this is the one that we managed to catch up with Ryan on a moment ago. Demi, do you want to give just, like, a quick overview of what… oh, yeah, look at that, major celebration over there.
115 00:11:10.700 ⇒ 00:11:16.240 Greg Stoutenburg: A quick overview of what Ryan was looking at that we’re, chipping away at right now.
116 00:11:17.070 ⇒ 00:11:24.870 Demilade Agboola: Yeah, so what we’re just trying to chip away right now is just, like, the final reconciliation, and get the dashboard to the…
117 00:11:25.010 ⇒ 00:11:37.270 Demilade Agboola: exactly how, like, Ryan envisions it. So he’s just said we could use the Salesforce numbers. My hesitation with that initially was how the Salesforce numbers came to be.
118 00:11:37.530 ⇒ 00:11:46.660 Demilade Agboola: And he just explained that there’s some scheduled, agents in the background that ensure that we get those numbers. So that at least has some
119 00:11:47.020 ⇒ 00:11:57.080 Demilade Agboola: That has put some confidence in trusting those numbers a bit more, and so the plan will be to tighten up certain things in overviewing the numbers, and just, like, switch
120 00:11:58.140 ⇒ 00:12:04.689 Demilade Agboola: the numbers that we’re looking at to the numbers that Ryan is getting through his agents, and use that in our dashboard.
121 00:12:04.830 ⇒ 00:12:07.790 Demilade Agboola: For a lot of other analysis that we’re currently doing.
122 00:12:11.020 ⇒ 00:12:11.620 Greg Stoutenburg: Yup.
123 00:12:12.440 ⇒ 00:12:15.590 Greg Stoutenburg: Okay, yep, so a few more dashboard changes coming.
124 00:12:16.120 ⇒ 00:12:25.669 Greg Stoutenburg: The customer success and revenue performance metrics… I should put a new screenshot on there. Old dark mode, I’m just not a dark mode person. I think I’m too old to like dark mode.
125 00:12:25.670 ⇒ 00:12:27.539 Nandika Jhunjhunwala: Neither am I, honestly.
126 00:12:27.950 ⇒ 00:12:32.350 Demilade Agboola: I’m dark mode forever. I am the dark mode warrior.
127 00:12:33.790 ⇒ 00:12:40.409 Greg Stoutenburg: This morning, just this morning, I woke up, and for whatever reason, several of the widgets on my phone were using dark mode, and I was like, I can’t even use this!
128 00:12:40.670 ⇒ 00:12:42.350 Nandika Jhunjhunwala: Yeah, no, I feel that.
129 00:12:43.560 ⇒ 00:12:46.320 Demilade Agboola: I think… I think because I work… I work in darkness a lot.
130 00:12:46.590 ⇒ 00:12:50.479 Demilade Agboola: The contrast of, like, a white screen, and really hurt my eye.
131 00:12:50.590 ⇒ 00:12:53.250 Demilade Agboola: So I… I need the dark… I need the dark mode.
132 00:12:54.300 ⇒ 00:12:57.510 Greg Stoutenburg: I do understand why people say they like it.
133 00:12:58.400 ⇒ 00:13:00.309 Greg Stoutenburg: I do get it, like, you know, less material.
134 00:13:00.720 ⇒ 00:13:03.980 Greg Stoutenburg: Supposedly. I just also can’t see it, so…
135 00:13:03.980 ⇒ 00:13:05.389 Demilade Agboola: Anyway.
136 00:13:05.890 ⇒ 00:13:22.219 Greg Stoutenburg: Laura was in favor, we’re making some changes now to align it with, you know, now that she’s had a chance to review, it’s like, okay, here’s some additional charts I’d like to see. So, working on that. Already provided this update, right? I mean, the update is everything’s going fine, we’re still moving toward the target.
137 00:13:22.600 ⇒ 00:13:34.889 Greg Stoutenburg: really looking forward to, really looking forward to when we have these stood up and Phoenix actually launches, to get that initial data and… and see what we see, and actually jam on some hypotheses.
138 00:13:34.890 ⇒ 00:13:35.400 Nandika Jhunjhunwala: Yeah.
139 00:13:35.400 ⇒ 00:13:37.789 Greg Stoutenburg: how to tighten up the product.
140 00:13:37.890 ⇒ 00:13:43.280 Greg Stoutenburg: Yeah, do you have any… is there any update about timeline for Phoenix? I mean, I think last.
141 00:13:43.280 ⇒ 00:13:43.970 Nandika Jhunjhunwala: Yeah.
142 00:13:43.970 ⇒ 00:13:46.669 Greg Stoutenburg: you know, sometime early May.
143 00:13:47.420 ⇒ 00:13:55.030 Nandika Jhunjhunwala: I think the timeline is still pretty much the same, but it’s so hard to tell. That’s the black box right now for us.
144 00:13:55.990 ⇒ 00:14:02.959 Nandika Jhunjhunwala: I’m also, like, still waiting on instrumentation, because I know they’re making a few changes, but…
145 00:14:03.090 ⇒ 00:14:06.580 Nandika Jhunjhunwala: Possibly next week is when I do some more instrumentation.
146 00:14:06.810 ⇒ 00:14:15.419 Nandika Jhunjhunwala: And get back on that post hoc brain, for stuff that we need to make headway on. So mostly, like, waiting on the engineering team.
147 00:14:15.520 ⇒ 00:14:22.210 Nandika Jhunjhunwala: To, like analyze the different parts of the product, SKUs that we need.
148 00:14:22.680 ⇒ 00:14:25.629 Nandika Jhunjhunwala: But I think the timeline is still early, man. Yeah.
149 00:14:25.630 ⇒ 00:14:26.190 Greg Stoutenburg: Okay.
150 00:14:26.190 ⇒ 00:14:26.570 Nandika Jhunjhunwala: Okay.
151 00:14:26.570 ⇒ 00:14:26.960 Greg Stoutenburg: Perfect.
152 00:14:26.960 ⇒ 00:14:32.509 Nandika Jhunjhunwala: I mean, I think ideally, realistically, like, it should definitely be live, like, end of May, for sure, so…
153 00:14:32.510 ⇒ 00:14:40.930 Greg Stoutenburg: Okay, okay, yeah, alright, sounds good. Well, we’ll just keep doing what we’re doing then, and and look forward to that data coming in.
154 00:14:41.730 ⇒ 00:14:46.789 Greg Stoutenburg: Some things that are still in progress. Now, some of these, we’ve really just mentioned all of these.
155 00:14:47.040 ⇒ 00:15:01.189 Greg Stoutenburg: everything that’s in progress right now, so the BizEv dashboard, that’s the one that’s, you know, currently being modeled, and that, that Demi’s working on. And then the rest of these are, you know, touch-ups to things that have already had their, their version 1, so they’re in QA.
156 00:15:01.900 ⇒ 00:15:04.280 Greg Stoutenburg: So, pretty happy about the progress there.
157 00:15:05.220 ⇒ 00:15:06.140 Greg Stoutenburg: Okay.
158 00:15:06.140 ⇒ 00:15:07.719 Nandika Jhunjhunwala: Yeah, thank you.
159 00:15:07.720 ⇒ 00:15:14.780 Greg Stoutenburg: So, that’s it for that part, and wanted to just kind of, like, show off where we are on some of these things.
160 00:15:15.210 ⇒ 00:15:23.010 Greg Stoutenburg: Customer success and performance, that’s what we just… well, I’ll actually open this up, because I just talked to Laura about this.
161 00:15:23.010 ⇒ 00:15:25.430 Nandika Jhunjhunwala: Do I have access to this in Omni?
162 00:15:25.690 ⇒ 00:15:27.110 Greg Stoutenburg: Yeah, yeah, this is all in Omni.
163 00:15:27.110 ⇒ 00:15:27.630 Nandika Jhunjhunwala: Check.
164 00:15:27.830 ⇒ 00:15:29.919 Greg Stoutenburg: Yeah, and…
165 00:15:30.100 ⇒ 00:15:44.660 Greg Stoutenburg: So, this is an Omni. We’ve got the definitions up top, right? One of the things that we talked about the last time we reviewed a dashboard altogether is just, again, having more documentation up at the top. And this, I mean, like, Demi could confirm this, even just from our conversation with Ryan.
166 00:15:44.660 ⇒ 00:15:53.920 Greg Stoutenburg: very often we’ll hear something like, oh, you know, this doesn’t quite line up with what I’m expecting, and the solution is just like, yeah, here’s how this is defined, right? Like, here’s the definition.
167 00:15:54.480 ⇒ 00:15:56.559 Greg Stoutenburg: Here’s time frame, and so…
168 00:15:56.810 ⇒ 00:16:03.950 Greg Stoutenburg: As we’re building these out, we’ll continue to provide these kinds of overviews, you know, to provide clarity and confidence in the data.
169 00:16:04.490 ⇒ 00:16:06.660 Greg Stoutenburg: But, like, looking at the specifics.
170 00:16:06.760 ⇒ 00:16:10.550 Greg Stoutenburg: What this is trying to capture is just what… what…
171 00:16:11.130 ⇒ 00:16:16.959 Greg Stoutenburg: what these financial metrics look like for the CSM team.
172 00:16:17.130 ⇒ 00:16:22.710 Greg Stoutenburg: And so, we’re looking, for example, at, like, new and expansion ARR,
173 00:16:22.940 ⇒ 00:16:42.090 Greg Stoutenburg: Oh, sorry, backing up. One of the definitions we’ll want to include, like, here we’ve got 100.9% NRR, which sounds amazing, right? Like, we did more than everything. And that’s because NRR includes, you know, it includes expansion, whereas GRR doesn’t, right? So,
174 00:16:42.090 ⇒ 00:16:44.030 Greg Stoutenburg: So that kind of clarity is helpful.
175 00:16:44.930 ⇒ 00:17:04.829 Greg Stoutenburg: We’re gonna move away from product tier, because product tier is pretty messy. It looks like it’s just, like, per SKU, and that’s not very informative. So we’re gonna move this, actually, to MRR by enterprise versus mid-market, and hopefully, you know, get some data that’s a little bit more, useful. Same here as well.
176 00:17:04.839 ⇒ 00:17:05.209 Nandika Jhunjhunwala: Good.
177 00:17:05.210 ⇒ 00:17:05.810 Greg Stoutenburg: Product type.
178 00:17:05.810 ⇒ 00:17:08.560 Nandika Jhunjhunwala: I think here you can use support tier. We have three…
179 00:17:08.800 ⇒ 00:17:17.770 Nandika Jhunjhunwala: types of customers, like Enterprise Growth and Standard, so that might be an interesting one. It’s the support tier field in Salesforce.
180 00:17:17.770 ⇒ 00:17:21.189 Greg Stoutenburg: Okay, support tier. Okay, that’s helpful.
181 00:17:21.190 ⇒ 00:17:25.059 Nandika Jhunjhunwala: You can write it out, too. But I think it’s just called support, too, yeah.
182 00:17:25.060 ⇒ 00:17:29.150 Greg Stoutenburg: Yeah, or yeah, maybe even just, like, put it in the… if you put Like, you know, suggestions.
183 00:17:29.150 ⇒ 00:17:29.710 Demilade Agboola: Yay.
184 00:17:29.710 ⇒ 00:17:30.500 Greg Stoutenburg: this one.
185 00:17:31.700 ⇒ 00:17:41.839 Demilade Agboola: Yeah, so also, like, everyone just, like… I also asked, like, Ryan about it, so if you can also help me with stuff around the columns where we would see, like, mid-market and enterprise.
186 00:17:41.840 ⇒ 00:17:42.400 Nandika Jhunjhunwala: Yeah.
187 00:17:42.960 ⇒ 00:17:44.590 Demilade Agboola: Classifications as well.
188 00:17:44.590 ⇒ 00:17:48.260 Nandika Jhunjhunwala: Totally. So that’s the… that’s the… that’s the column. It’s called support tier.
189 00:17:48.570 ⇒ 00:17:51.219 Greg Stoutenburg: Support tier. Okay, great. Great.
190 00:17:51.590 ⇒ 00:18:05.339 Nandika Jhunjhunwala: Yeah, anything Salesforce data, I can help you out on, Jenny, so please feel free to, like, ping me if Ryan’s not available, because I know Ryan has, like, a lot on his plate as well, so it might be quicker to respond than he is, yeah.
191 00:18:07.270 ⇒ 00:18:07.839 Demilade Agboola: Sounds good.
192 00:18:07.840 ⇒ 00:18:08.400 Greg Stoutenburg: Nice.
193 00:18:08.650 ⇒ 00:18:13.240 Greg Stoutenburg: Yeah. Yeah, okay, so those were some of the bigger ones,
194 00:18:13.730 ⇒ 00:18:25.910 Greg Stoutenburg: And then, again, products here, we’ll change that to, you know, looking at enterprise and mid-market. And I think those are some of the main changes. Like I said, I’ve got it all ticketed out, but,
195 00:18:25.910 ⇒ 00:18:40.599 Greg Stoutenburg: The goal will be, basically, to just get clearer on how effective the customer success team is being, and make… just make sure that anywhere there’s an opportunity to, drive growth for the team, that… that we’ve… we’re taking it, so…
196 00:18:41.580 ⇒ 00:18:45.119 Nandika Jhunjhunwala: Yeah, thank you so much, this looks great. Really appreciate it.
197 00:18:45.120 ⇒ 00:18:46.050 Greg Stoutenburg: No.
198 00:18:46.410 ⇒ 00:18:56.919 Greg Stoutenburg: And then here, customer reporting and enablement. This one… oh yeah, this is the one we reviewed with Deanna. We’ll be talking to her next week as well.
199 00:18:57.130 ⇒ 00:19:04.270 Greg Stoutenburg: And, we’re gonna add… Some metrics around…
200 00:19:04.640 ⇒ 00:19:07.889 Greg Stoutenburg: Yeah, we’re gonna add some information about support tickets.
201 00:19:08.010 ⇒ 00:19:21.829 Greg Stoutenburg: Right, so just some more information about support tickets that are, like, a little bit more specific. And similarly with, with customer churn, we’re gonna break that out into churn reason as well, because currently, we’ve sort of left off whether someone left because they were, like.
202 00:19:21.830 ⇒ 00:19:22.200 Nandika Jhunjhunwala: Yep.
203 00:19:22.200 ⇒ 00:19:28.980 Greg Stoutenburg: satisfied, or even just, like, you know, the contract just expired and then they made a new one. Those are different things to try to understand.
204 00:19:29.180 ⇒ 00:19:32.489 Greg Stoutenburg: So, we’ll be, including that as well.
205 00:19:33.920 ⇒ 00:19:34.770 Greg Stoutenburg: Yeah.
206 00:19:36.310 ⇒ 00:19:43.920 Demilade Agboola: Since we’re in Omni, can we, like, take a look at, like, the Omni usage, and just, like, potential thoughts we can…
207 00:19:44.960 ⇒ 00:19:46.630 Demilade Agboola: Yeah, and drive adoption.
208 00:19:47.610 ⇒ 00:19:48.980 Greg Stoutenburg: Wrong button.
209 00:19:49.350 ⇒ 00:19:53.560 Nandika Jhunjhunwala: Yeah, I think usage will also spike, like, once the product is live, for sure.
210 00:19:54.320 ⇒ 00:19:56.030 Nandika Jhunjhunwala: The new product.
211 00:19:56.230 ⇒ 00:20:00.610 Nandika Jhunjhunwala: I think currently everybody’s just in sort of flux, yeah.
212 00:20:02.630 ⇒ 00:20:03.430 Greg Stoutenburg: So…
213 00:20:03.430 ⇒ 00:20:04.520 Nandika Jhunjhunwala: Oh, wow.
214 00:20:05.040 ⇒ 00:20:06.630 Greg Stoutenburg: Yeah, we still have to get Lev in here.
215 00:20:07.020 ⇒ 00:20:07.340 Nandika Jhunjhunwala: No.
216 00:20:08.640 ⇒ 00:20:12.479 Nandika Jhunjhunwala: Honestly, I haven’t opened on me in a second as well, yeah.
217 00:20:12.900 ⇒ 00:20:14.760 Greg Stoutenburg: We’re gonna send an alert just for you, then.
218 00:20:16.460 ⇒ 00:20:17.869 Greg Stoutenburg: Yeah, hang on one second.
219 00:20:17.870 ⇒ 00:20:19.439 Nandika Jhunjhunwala: Top AI users.
220 00:20:20.520 ⇒ 00:20:21.200 Nandika Jhunjhunwala: Hmm.
221 00:20:23.890 ⇒ 00:20:31.220 Nandika Jhunjhunwala: Let’s see… Caitlin… Oh, it looks like it hasn’t moved much.
222 00:20:37.770 ⇒ 00:20:48.159 Demilade Agboola: Okay, it does seem like the goal this week will just be, like, showing people some of the dashboards, especially, like, the Salesforce-based dashboards, Salesforce pipeline.
223 00:20:48.270 ⇒ 00:20:50.169 Demilade Agboola: pylon dashboards. They’re live.
224 00:20:50.170 ⇒ 00:20:50.680 Nandika Jhunjhunwala: For shorter.
225 00:20:50.680 ⇒ 00:20:53.679 Demilade Agboola: That’s a lot of data, and they’re updating consistently.
226 00:20:53.790 ⇒ 00:20:54.690 Demilade Agboola: product.
227 00:20:54.690 ⇒ 00:20:55.100 Nandika Jhunjhunwala: Yeah.
228 00:20:55.100 ⇒ 00:20:55.960 Demilade Agboola: currently.
229 00:20:55.960 ⇒ 00:20:56.450 Nandika Jhunjhunwala: Totally.
230 00:20:56.450 ⇒ 00:20:57.760 Demilade Agboola: sports? Yeah.
231 00:20:57.760 ⇒ 00:20:58.310 Nandika Jhunjhunwala: I, I wish…
232 00:20:58.310 ⇒ 00:20:58.839 Demilade Agboola: Checking with.
233 00:20:58.840 ⇒ 00:21:08.159 Nandika Jhunjhunwala: the customer success team and tell them about the dashboard. I think only Diana’s looked at it, and we can share it with the entire team. They might think it’s useful.
234 00:21:08.880 ⇒ 00:21:27.299 Demilade Agboola: Yeah, yeah, and even just, like, the… yeah, the customer success dashboard will be an amazing dashboard. It’s still, like, we’re making, like, final tweaks based off of feedback with Laura, but, like, we can start to see stuff about the cohort, we can do filters, we can use filters around, like, the CS… by CSM, we can do filters by,
235 00:21:27.900 ⇒ 00:21:38.930 Demilade Agboola: just, like, there are multiple filters in there, and we can kind of get more information about the different segments, so you can get an idea of what’s happening. People can use the dashboard for what will drive them on a day-to-day basis.
236 00:21:39.240 ⇒ 00:21:41.770 Demilade Agboola: And so I think it’s pretty useful right now.
237 00:21:42.770 ⇒ 00:21:48.729 Nandika Jhunjhunwala: And is it final, or was there any specific feedback from Deanna that you’re working on?
238 00:21:50.630 ⇒ 00:21:50.949 Greg Stoutenburg: from DM.
239 00:21:52.790 ⇒ 00:22:04.059 Demilade Agboola: Yeah. Yeah, so from Deanna, a couple things on her side. She… major theme is obviously the Postgres. She wants, like, live data, so it is fully reactive and responsive.
240 00:22:04.160 ⇒ 00:22:13.169 Demilade Agboola: Other feedback would be about, like, switching from plane to pylon for, like, the current Correct. Tickets. Infrastructure.
241 00:22:13.330 ⇒ 00:22:24.889 Demilade Agboola: And then there are other things about adding some, like, more context in terms of, like, the notes on top, like how we have for the other dashboard that we’ve done, as well as some small tweaks to some settings that’s here and there.
242 00:22:25.460 ⇒ 00:22:26.599 Nandika Jhunjhunwala: Yeah, I think then…
243 00:22:26.600 ⇒ 00:22:27.339 Demilade Agboola: You’re in a good spot.
244 00:22:28.010 ⇒ 00:22:34.729 Nandika Jhunjhunwala: The reason for her not sharing it is probably that she wants it to be live data and a complete source of data.
245 00:22:34.910 ⇒ 00:22:38.869 Nandika Jhunjhunwala: Greg, I know you, like, chatted with Kieran about
246 00:22:39.380 ⇒ 00:22:54.569 Nandika Jhunjhunwala: adding pylon as a source, and, the extra work that’s gonna take. Just wondering, like, where you are in that process. I know that pushes our timelines back a bit, which is totally understandable, because we threw this on last minute.
247 00:22:54.710 ⇒ 00:22:59.419 Nandika Jhunjhunwala: Our customer success team, like, switched from, like, one provider to the other, so…
248 00:22:59.550 ⇒ 00:23:03.179 Nandika Jhunjhunwala: Hopefully the data is similar, or there are, like, parallels there.
249 00:23:03.180 ⇒ 00:23:04.889 Greg Stoutenburg: Yeah. But… Yeah.
250 00:23:05.400 ⇒ 00:23:08.549 Nandika Jhunjhunwala: Would love to know, like, when we can see that data, and, like.
251 00:23:09.510 ⇒ 00:23:18.019 Greg Stoutenburg: Demi’s working his magic. Yeah, Demi’s got it connected, and he’s working his magic to get the fields to sync up. As far as timeline, Demi…
252 00:23:18.100 ⇒ 00:23:31.230 Greg Stoutenburg: It previously said, you know, somewhere between 5 and 10 hours total, but that, you know, as, you know, at 10 hours a week sort of pushes back timeline on some things a few days. Demi, can you say a little more to round it out?
253 00:23:31.850 ⇒ 00:23:51.579 Demilade Agboola: Yeah, I mean, we’re currently working on it. I think right now, it’s… it’s in flight. It’s all about, like, prioritization, because, like, right now, I’m getting feedback from the different dashboards, from different people, so I’m making, like, the small tweaks. But definitely by, like, early next week, it should be completely done, and we should have a, like, fully modeled into, like.
254 00:23:52.050 ⇒ 00:23:58.149 Demilade Agboola: Or we have non-existing infrastructure. But yeah, right now, the focus is just trying to
255 00:23:58.550 ⇒ 00:24:01.950 Demilade Agboola: Kill off the dashboards that… or build off the dashboards that we have existing.
256 00:24:01.950 ⇒ 00:24:02.280 Nandika Jhunjhunwala: Like.
257 00:24:02.280 ⇒ 00:24:03.149 Demilade Agboola: you have already.
258 00:24:03.150 ⇒ 00:24:03.480 Nandika Jhunjhunwala: Yeah.
259 00:24:03.480 ⇒ 00:24:11.310 Demilade Agboola: get the ER out, and, you know, handle any issues for, like, the customer success modeling that we need some tweaks for, like, you know.
260 00:24:11.430 ⇒ 00:24:22.110 Demilade Agboola: changing from product tier to, you know, support tier, and that would allow us to have that sort of visibility. And then, from tomorrow and maybe early Monday, we can just ideal.
261 00:24:23.010 ⇒ 00:24:23.860 Demilade Agboola: Play line.
262 00:24:23.860 ⇒ 00:24:24.290 Nandika Jhunjhunwala: That’s true.
263 00:24:24.290 ⇒ 00:24:26.899 Demilade Agboola: the coins. Customer number one dashboard.
264 00:24:27.010 ⇒ 00:24:33.739 Nandika Jhunjhunwala: Yeah, the other thing I wanted to ask you, how are you dedupeing between pylon and plane tickets? Because…
265 00:24:34.040 ⇒ 00:24:36.670 Nandika Jhunjhunwala: Whatever data is in Pylon is also in plane.
266 00:24:37.630 ⇒ 00:24:47.239 Demilade Agboola: Yeah, so I haven’t fully gotten that working yet, but the idea is to keep looking at differentiators.
267 00:24:47.740 ⇒ 00:24:51.159 Demilade Agboola: And should we be clear, like, if we can’t get the…
268 00:24:51.380 ⇒ 00:25:08.739 Demilade Agboola: primary key that automatically helps us dedupe. We might have to create, like, a surrogate key, which will be a combination of multiple different columns, that we can then use as a source of truth to be able to say, hey, this is… this combination of columns equates to the same
269 00:25:08.960 ⇒ 00:25:13.809 Demilade Agboola: Or we can use a hash. Basically, we’re just gonna have to create a… duplicate, like.
270 00:25:14.000 ⇒ 00:25:21.739 Demilade Agboola: priority, or an official primary, and use that as a source of truth, also to duplicate between pylon and things.
271 00:25:24.160 ⇒ 00:25:29.109 Nandika Jhunjhunwala: But you haven’t identified the differentiators yet. Is that…
272 00:25:29.110 ⇒ 00:25:33.700 Demilade Agboola: Yeah, not for you. But that will be the plan of attack.
273 00:25:35.150 ⇒ 00:25:37.300 Nandika Jhunjhunwala: Got it, okay, please keep me updated.
274 00:25:38.120 ⇒ 00:25:38.870 Demilade Agboola: Yeah, older.
275 00:25:39.080 ⇒ 00:25:39.640 Nandika Jhunjhunwala: Yep.
276 00:25:41.560 ⇒ 00:25:47.999 Greg Stoutenburg: Yeah, and just understanding, sort of, like, level of priority and urgency, and what you’ll do with this data, Nandika.
277 00:25:48.000 ⇒ 00:25:48.530 Nandika Jhunjhunwala: Yeah.
278 00:25:48.530 ⇒ 00:25:50.030 Greg Stoutenburg: Sort of speak to that a little bit.
279 00:25:50.330 ⇒ 00:26:00.480 Greg Stoutenburg: the team… and I guess I’m saying because, right, just sort of interpreting what people are thinking, in the chat, it seemed like the team is like, no, we, like, we really do want this now. So yeah, if you can speak to that, that’s helpful for us as well.
280 00:26:00.480 ⇒ 00:26:08.670 Nandika Jhunjhunwala: Totally, yeah, I’m sorry for, like, the back and forth, if that’s caused confusion. I think…
281 00:26:09.310 ⇒ 00:26:20.539 Nandika Jhunjhunwala: I think in my head, and I’ll confirm with Caitlin on this, she’s traveling right now, but priorities are, like, whatever dashboards that we have currently in progress are, like, close to…
282 00:26:21.000 ⇒ 00:26:22.600 Nandika Jhunjhunwala: Being finalized, we, like.
283 00:26:22.600 ⇒ 00:26:22.920 Greg Stoutenburg: Yeah.
284 00:26:22.920 ⇒ 00:26:29.099 Nandika Jhunjhunwala: refine them before moving on to the next dashboard, so the urgency on the pylon is because it…
285 00:26:29.260 ⇒ 00:26:36.729 Nandika Jhunjhunwala: Goes into the customer retention dashboard directly for, like, customer success, data.
286 00:26:36.730 ⇒ 00:26:37.170 Greg Stoutenburg: Yeah.
287 00:26:37.170 ⇒ 00:26:40.180 Nandika Jhunjhunwala: That we sort of prioritize that.
288 00:26:40.180 ⇒ 00:26:40.630 Greg Stoutenburg: Yeah.
289 00:26:40.630 ⇒ 00:26:43.210 Nandika Jhunjhunwala: Just because, like, I think that’s gonna be, like, the first…
290 00:26:43.660 ⇒ 00:26:53.799 Nandika Jhunjhunwala: sort of, like, leverage that Omni would create, because I think customer success managers are going to directly start using that before anybody else will. Got it. Once that data is live and complete.
291 00:26:54.410 ⇒ 00:26:55.639 Nandika Jhunjhunwala: If that makes sense.
292 00:26:55.640 ⇒ 00:26:59.249 Greg Stoutenburg: Yeah, so it’s maybe the most directly actionable board.
293 00:26:59.450 ⇒ 00:27:00.520 Nandika Jhunjhunwala: Right. Yes.
294 00:27:00.520 ⇒ 00:27:01.700 Greg Stoutenburg: Okay, yeah, that’s good.
295 00:27:01.700 ⇒ 00:27:09.380 Nandika Jhunjhunwala: I think after the ARR one that Laura signed off on, so we’re good there. So the next order of business would be the CS one, for sure.
296 00:27:09.580 ⇒ 00:27:13.330 Greg Stoutenburg: Yep, great. Okay, cool. Yeah, that’s helpful context for us.
297 00:27:13.610 ⇒ 00:27:21.390 Greg Stoutenburg: Yeah, okay, looking at this, it looks like, Brainforge is beginning to take the lead.
298 00:27:21.510 ⇒ 00:27:24.040 Greg Stoutenburg: We gotta, we gotta, we gotta do something.
299 00:27:24.040 ⇒ 00:27:27.929 Nandika Jhunjhunwala: Yeah, no, hard to compete with that. 56 sessions.
300 00:27:27.930 ⇒ 00:27:28.610 Greg Stoutenburg: Well, I mean, this is.
301 00:27:28.610 ⇒ 00:27:29.090 Nandika Jhunjhunwala: Yeah.
302 00:27:29.090 ⇒ 00:27:31.149 Greg Stoutenburg: He’s… he’s cheating. I mean, I think, you know.
303 00:27:32.040 ⇒ 00:27:42.550 Greg Stoutenburg: Yeah, you know, he sort of tipped the scales by building too much stuff too quickly. So, yeah, I mean, I think… I guess one thought I have is, like, what…
304 00:27:42.750 ⇒ 00:27:46.079 Greg Stoutenburg: Monica, what do you… what do you think we can do to sort of encourage
305 00:27:46.360 ⇒ 00:27:50.840 Greg Stoutenburg: more usage from the folks who’ve been let in so far, like…
306 00:27:51.180 ⇒ 00:27:54.630 Greg Stoutenburg: like, why is… why is Nico at zero? Like, is he… is he…
307 00:27:54.630 ⇒ 00:27:55.340 Nandika Jhunjhunwala: Yeah.
308 00:27:55.340 ⇒ 00:27:57.159 Greg Stoutenburg: It’s hearing from other people, or doesn’t think.
309 00:27:57.160 ⇒ 00:27:59.290 Nandika Jhunjhunwala: It’s valuable, yeah.
310 00:27:59.290 ⇒ 00:28:05.539 Greg Stoutenburg: Doesn’t know about, you know, the ability to ask questions, directly, rather than waiting for dashboards.
311 00:28:05.960 ⇒ 00:28:10.699 Nandika Jhunjhunwala: Totally. I think usage will spike once,
312 00:28:11.440 ⇒ 00:28:15.159 Nandika Jhunjhunwala: Data is more… like, we have more of the pipelines finalized, and.
313 00:28:15.160 ⇒ 00:28:15.760 Greg Stoutenburg: Yeah.
314 00:28:15.760 ⇒ 00:28:23.329 Nandika Jhunjhunwala: I think currently we’re in a state where everybody’s just, like, at capacity with whatever they’re doing with the new product, but I think once…
315 00:28:23.330 ⇒ 00:28:24.380 Greg Stoutenburg: lobby during this.
316 00:28:24.380 ⇒ 00:28:25.190 Nandika Jhunjhunwala: Yeah.
317 00:28:25.190 ⇒ 00:28:25.790 Greg Stoutenburg: in the Saturday.
318 00:28:25.790 ⇒ 00:28:34.809 Nandika Jhunjhunwala: I think once we’re over that hill, though, definitely we should see more usage out of everybody. I think, like, Karen and I can also do a better job of, like.
319 00:28:35.190 ⇒ 00:28:39.130 Nandika Jhunjhunwala: propagating for Omni. She does that, she, like, talks about it every week.
320 00:28:39.460 ⇒ 00:28:43.219 Nandika Jhunjhunwala: Yeah. Like, the all-hands ball, so hopefully we get more users here, yeah.
321 00:28:43.220 ⇒ 00:29:02.299 Greg Stoutenburg: Yeah, yeah. Well, yeah, and I’ll, I’ll reach out to, I’ll reach out to her about it, or, you know, maybe you and her about it, or just raise it in the channel. Like, maybe something that we should adopt as a policy is when we… when we finish a dash, and we go, alright, you know, here it is, come and take a look at this,
322 00:29:02.460 ⇒ 00:29:08.270 Greg Stoutenburg: one of the things that’s implied in that is now you can ask questions to Blobby about this topic, right?
323 00:29:08.270 ⇒ 00:29:08.620 Nandika Jhunjhunwala: Yeah.
324 00:29:08.620 ⇒ 00:29:12.690 Greg Stoutenburg: particular piece of subject matter. So, you know, customer success dashboard is done.
325 00:29:12.690 ⇒ 00:29:13.170 Nandika Jhunjhunwala: Yeah.
326 00:29:13.170 ⇒ 00:29:20.039 Greg Stoutenburg: step, besides, here’s our dashboard, is, hey, you can also just go straight here and ask the AI questions about, like, you know.
327 00:29:20.040 ⇒ 00:29:20.529 Nandika Jhunjhunwala: For sure.
328 00:29:20.650 ⇒ 00:29:27.080 Greg Stoutenburg: which, which CSM you know, had the most renewals in the last.
329 00:29:27.080 ⇒ 00:29:27.600 Nandika Jhunjhunwala: Yeah.
330 00:29:27.600 ⇒ 00:29:28.240 Greg Stoutenburg: months.
331 00:29:28.240 ⇒ 00:29:32.919 Nandika Jhunjhunwala: I think that’s, like, also, like, a data freshness question that we, yeah, yeah.
332 00:29:33.120 ⇒ 00:29:49.699 Nandika Jhunjhunwala: once that… when the data is fresh enough, I think people will start using it more, I think. Yeah. Because currently, like, we don’t have, like, ETL set up everywhere, that that becomes a blocker. Yeah. And I’ll follow up with Victor on the product data access. We’re still blocked on that, right?
333 00:29:50.970 ⇒ 00:29:51.620 Greg Stoutenburg: Demi?
334 00:29:54.280 ⇒ 00:30:00.219 Demilade Agboola: Yeah, access is still an issue. I know we… Utam gave some feedback on… I know.
335 00:30:00.860 ⇒ 00:30:11.370 Demilade Agboola: that was seen, but I’m not sure that has necessarily led to any action, or, like, any plan of action right now. I think I’ll just follow up on that, and just ensure that we’re all in sync on that.
336 00:30:12.050 ⇒ 00:30:13.040 Nandika Jhunjhunwala: Sounds good.
337 00:30:13.230 ⇒ 00:30:20.450 Nandika Jhunjhunwala: Yeah. Cool. That makes sense. I’ll follow up again. I asked Victor last week, and he said you should…
338 00:30:20.690 ⇒ 00:30:28.530 Nandika Jhunjhunwala: be giving you guys access soon, I think of ES3 or some other GitHub actions or something, so… yeah, I’ll ask him again, sorry about that.
339 00:30:28.660 ⇒ 00:30:34.220 Greg Stoutenburg: Okay. Yeah, any, any thoughts on why, I mean, do you think maybe you just sort of forgot or overlooked it?
340 00:30:34.400 ⇒ 00:30:36.450 Greg Stoutenburg: Or was there, like, a change?
341 00:30:37.590 ⇒ 00:30:38.630 Nandika Jhunjhunwala: Yeah.
342 00:30:38.630 ⇒ 00:30:39.550 Greg Stoutenburg: rates or anything?
343 00:30:40.080 ⇒ 00:30:44.829 Nandika Jhunjhunwala: No, I think Victor’s just in the development mode.
344 00:30:44.830 ⇒ 00:30:45.350 Greg Stoutenburg: Yeah.
345 00:30:45.350 ⇒ 00:30:56.229 Nandika Jhunjhunwala: And I keep following up with him, but I don’t wanna, bother him again and again, so whenever I see him, and he has a moment, I do, like, you know, push for it, so…
346 00:30:56.230 ⇒ 00:30:57.049 Greg Stoutenburg: Yeah, no.
347 00:30:57.050 ⇒ 00:31:00.539 Nandika Jhunjhunwala: Trying my best to get you guys active as soon as I can.
348 00:31:00.540 ⇒ 00:31:02.690 Greg Stoutenburg: Yeah, I’m reminded of my…
349 00:31:03.180 ⇒ 00:31:21.150 Greg Stoutenburg: the first time that I professionally sort of learned firsthand about, not nagging someone too much is, I was working in the Human Resources Department at this law firm in Chicago, and my job was to collect this signature on this form that acknowledged everyone had, like, read some policy.
350 00:31:21.150 ⇒ 00:31:25.359 Greg Stoutenburg: And, the firm was called, Neil Gerber & Eisenberg.
351 00:31:25.360 ⇒ 00:31:25.700 Nandika Jhunjhunwala: Yeah.
352 00:31:25.720 ⇒ 00:31:41.930 Greg Stoutenburg: one of the names I didn’t have a signature from ended in Eisenberg, and it was like a 500-person firm. And I remember just, like, he hadn’t signed the thing, and so I just walked into his office. I was like, you need to sign this thing. And then my boss got a follow-up the next day, and then I heard about it.
353 00:31:41.930 ⇒ 00:31:42.760 Nandika Jhunjhunwala: Oh my god.
354 00:31:42.760 ⇒ 00:31:45.169 Greg Stoutenburg: Not supposed to do that. So there’s… there’s a right amount of.
355 00:31:45.170 ⇒ 00:31:45.930 Nandika Jhunjhunwala: Yeah.
356 00:31:45.930 ⇒ 00:31:46.510 Greg Stoutenburg: I, I,
357 00:31:46.510 ⇒ 00:31:50.569 Nandika Jhunjhunwala: Yeah, no, there’s no such thing like that at a startup, for sure, but…
358 00:31:51.450 ⇒ 00:31:53.880 Nandika Jhunjhunwala: It’s more like, oh, I don’t wanna…
359 00:31:54.130 ⇒ 00:31:54.600 Greg Stoutenburg: Yeah.
360 00:31:54.600 ⇒ 00:31:57.119 Nandika Jhunjhunwala: annoy my CTO.
361 00:31:57.120 ⇒ 00:31:57.720 Greg Stoutenburg: Yeah.
362 00:31:57.890 ⇒ 00:32:00.350 Nandika Jhunjhunwala: Yeah, yeah, that’s what I’m assuming happened.
363 00:32:00.830 ⇒ 00:32:01.769 Nandika Jhunjhunwala: Okay. That’s good.
364 00:32:01.850 ⇒ 00:32:04.899 Greg Stoutenburg: All right, sounds good. Alright, thanks for your time, everybody. We’ll follow up on those things.
365 00:32:04.900 ⇒ 00:32:05.380 Nandika Jhunjhunwala: Thank you.
366 00:32:05.380 ⇒ 00:32:07.929 Greg Stoutenburg: And yeah, talk soon. Alright.
367 00:32:07.930 ⇒ 00:32:09.049 Nandika Jhunjhunwala: See you. Bye.