2025-11-05_eden_honeystinger_insomnia_project_plann_98fda3ab

Meeting Title: Eden, Honeystinger, Insomnia Project Planning Date: 2025-11-05 Meeting participants: Awaish Kumar, Uttam Kumaran, Henry Zhao, Robert Tseng, Henry Zhao

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WEBVTT

1 00:01:12.750 ⇒ 00:01:13.820 Uttam Kumaran: Hey, Wish.

2 00:01:17.400 ⇒ 00:01:18.210 Awaish Kumar: Hello?

3 00:04:11.760 ⇒ 00:04:13.880 Robert Tseng: Hello?

4 00:04:15.370 ⇒ 00:04:18.149 Uttam Kumaran: Dude, I just gave a sick demo.

5 00:04:18.769 ⇒ 00:04:19.549 Robert Tseng: You did?

6 00:04:19.849 ⇒ 00:04:20.489 Robert Tseng: 2…

7 00:04:21.579 ⇒ 00:04:31.929 Uttam Kumaran: That, like, yeah, it was probably, like, 60… Ecom, CPG… Like, seniors, seniors, senior people.

8 00:04:32.109 ⇒ 00:04:36.859 Uttam Kumaran: And I basically did a 15-minute end-to-end N8N

9 00:04:37.009 ⇒ 00:04:41.469 Uttam Kumaran: develop, make your own N8N email draft writer workflow.

10 00:04:42.159 ⇒ 00:04:45.149 Uttam Kumaran: and… it was.

11 00:04:45.150 ⇒ 00:04:46.699 Robert Tseng: Are you teaching any it now?

12 00:04:47.380 ⇒ 00:04:51.609 Uttam Kumaran: Dude, give me a break. Hey, Dad?

13 00:04:51.610 ⇒ 00:04:52.260 Robert Tseng: coach?

14 00:04:52.260 ⇒ 00:04:55.779 Uttam Kumaran: I knew NAN when I was 3.

15 00:04:57.100 ⇒ 00:05:09.020 Uttam Kumaran: No, Craig called me last week, he was like, yo, we’re… he does sort of, like, midweek things with this group, and he’s like, we’re teaching AI stuff, do you want to do a demo on it at the end?

16 00:05:09.250 ⇒ 00:05:19.699 Uttam Kumaran: And so Casey helped me put together a little demo, and then, yeah, it went really, really well. He’s also, like, I’ll give you everybody’s emails, he’s like, just send them, like, something relevant, but, like.

17 00:05:20.920 ⇒ 00:05:23.380 Uttam Kumaran: kind of like, like the CEO of Ridge.

18 00:05:23.630 ⇒ 00:05:26.780 Uttam Kumaran: people from Fabletics, like, all types of, like.

19 00:05:27.710 ⇒ 00:05:30.030 Uttam Kumaran: very nice people that I got to just…

20 00:05:30.490 ⇒ 00:05:33.679 Uttam Kumaran: sort of show that we’re… we know what we’re talking about with AI, so let’s see…

21 00:05:33.680 ⇒ 00:05:35.339 Robert Tseng: CEO of Ridge was on that call.

22 00:05:35.940 ⇒ 00:05:40.650 Uttam Kumaran: CEO Ridge, like, yeah, I mean, I don’t even know who… there was just, like.

23 00:05:40.890 ⇒ 00:05:45.839 Uttam Kumaran: I’ll get you the email list, yoke. You’re gonna cry, but…

24 00:05:45.840 ⇒ 00:05:47.110 Robert Tseng: They’re amazing.

25 00:05:47.580 ⇒ 00:05:52.199 Uttam Kumaran: It was, like… Ridge, Fabletics, HexClad, like.

26 00:05:52.200 ⇒ 00:05:55.559 Robert Tseng: Oh, the hexclad, I’ve got to get back in on Hexclad, yeah.

27 00:05:55.740 ⇒ 00:06:01.589 Uttam Kumaran: Yeah, so I’m… I’m probably, like, a quarter of these we probably, like, already made inroads into.

28 00:06:01.800 ⇒ 00:06:02.220 Robert Tseng: Yeah.

29 00:06:02.660 ⇒ 00:06:12.229 Uttam Kumaran: like, almost 30 minutes uninter… well, slightly interrupted to just present about us and, like, a simple AI thing, so…

30 00:06:13.830 ⇒ 00:06:14.870 Uttam Kumaran: I feel good.

31 00:06:15.870 ⇒ 00:06:16.690 Robert Tseng: Nice.

32 00:06:17.190 ⇒ 00:06:18.570 Uttam Kumaran: But I’m just like…

33 00:06:18.820 ⇒ 00:06:23.870 Uttam Kumaran: spazzed out right now. Okay, so let’s talk about, let’s… can we start by talking about Eden?

34 00:06:24.040 ⇒ 00:06:33.469 Uttam Kumaran: I kind of just want a conversation, and I’ll let you, Robert, maybe… Give, like, your vision?

35 00:06:35.000 ⇒ 00:06:45.159 Uttam Kumaran: I kind of, like… again, if I could set the stage here, there are things that when we started with Eden, we wanted to do, there are things that we got done.

36 00:06:45.550 ⇒ 00:06:49.359 Uttam Kumaran: There are things that, out of getting those things done, came up.

37 00:06:49.530 ⇒ 00:06:51.079 Uttam Kumaran: And then there’s sort of, like.

38 00:06:51.690 ⇒ 00:07:01.939 Uttam Kumaran: what our roadmap is right now. And so what I really want to focus on is driving the ship in two ways. One, continuing to just band-aid due to plumbing.

39 00:07:02.070 ⇒ 00:07:09.819 Uttam Kumaran: Second is really sexy, like, analysis, or, like, showing that our work is driving outcomes.

40 00:07:10.030 ⇒ 00:07:16.019 Uttam Kumaran: And so, yeah, maybe I can just host a discussion on that. I don’t know if you want to, like.

41 00:07:16.200 ⇒ 00:07:20.100 Uttam Kumaran: Just share your… Sort of some feedback there.

42 00:07:21.000 ⇒ 00:07:23.520 Robert Tseng: Yeah

43 00:07:25.060 ⇒ 00:07:31.279 Robert Tseng: I… well, what I was hoping to have before this call was I was, like, reaching out to all the folks and telling to…

44 00:07:31.730 ⇒ 00:07:46.149 Robert Tseng: like, the other teams to resend me their OKRs, just so I could try to, like, realign on it. Like, I feel like I could spend just, like, 2 hours just, like, trying to build out a roadmap for every function, but even without those details, I think…

45 00:07:46.350 ⇒ 00:07:50.259 Robert Tseng: Yeah, there’s… there’s some element of, like,

46 00:07:51.100 ⇒ 00:08:05.420 Robert Tseng: Well, yeah, I think our data engineering roadmap, I think, needs to be clear. That’s probably where I would lean on this team to, like, what are the things that are kind of, like, band-aid solutions right now? Like, what further improvements could we make? Like.

47 00:08:05.530 ⇒ 00:08:09.410 Robert Tseng: I… I think the biggest thing to me is that

48 00:08:09.430 ⇒ 00:08:23.009 Robert Tseng: their pace of experimentation is just, like, too slow for a company of this size. That’s, like, the biggest, like, unlock for them. And so, I’m just, like, thinking about, like, how do we help them to

49 00:08:23.010 ⇒ 00:08:31.229 Robert Tseng: run better experiments. A part of it is standing up Mixpanel, training the team, having them use it so that they could actually, like.

50 00:08:31.430 ⇒ 00:08:35.130 Robert Tseng: Start to analyze their own, kind of.

51 00:08:35.960 ⇒ 00:08:53.889 Robert Tseng: like, web analytics, like, conversion funnel changes, and, like, to… for the… for their team to, like, go in there and build their own segmentation or cohorts. Like, we have to, like, democratize, like, this, this, like, low-level analysis to them, and get them bought into it.

52 00:08:53.890 ⇒ 00:08:57.449 Robert Tseng: So, I think that, to me, from, like, a…

53 00:08:58.450 ⇒ 00:09:08.550 Robert Tseng: tooling perspective is a big priority. Obviously there’s, like, some operational reporting that’s, like, gonna eat up a lot of the modeling work.

54 00:09:10.180 ⇒ 00:09:25.710 Robert Tseng: So, I mean, I don’t know the status of, like, when Henry’s gonna be doing their quote-unquote on-site with them, but if we don’t do it soon, like, I think I would just… I would push to do it soon. So, I think that’s, that’s another…

55 00:09:25.840 ⇒ 00:09:30.050 Robert Tseng: Part that needs to… that’s gonna end up kind of eating up a lot of our time.

56 00:09:30.220 ⇒ 00:09:31.050 Robert Tseng: like…

57 00:09:31.770 ⇒ 00:09:37.530 Robert Tseng: Yeah, so I think those are kind of the two big buckets of work that I see kind of coming.

58 00:09:39.530 ⇒ 00:09:46.549 Henry Zhao: Yeah, and that’s kind of what I said to Utam yesterday, also, for our big, big rocks, and the virtual visit is supposed to happen tomorrow.

59 00:09:46.700 ⇒ 00:09:48.160 Henry Zhao: If Rebecca responds.

60 00:09:48.720 ⇒ 00:09:49.110 Robert Tseng: Okay.

61 00:09:49.110 ⇒ 00:09:52.129 Henry Zhao: The HIPAA training’s done, so I’m all good on my end.

62 00:09:52.560 ⇒ 00:09:53.270 Robert Tseng: Okay.

63 00:09:55.890 ⇒ 00:09:56.510 Uttam Kumaran: Okay.

64 00:09:58.090 ⇒ 00:09:59.480 Uttam Kumaran: What do you think, Awash?

65 00:10:00.520 ⇒ 00:10:03.989 Awaish Kumar: Like, what I’m thinking of is,

66 00:10:04.400 ⇒ 00:10:12.439 Awaish Kumar: One is, like, the immediate things which aren’t going to come, like, decision on North Beam, and…

67 00:10:12.650 ⇒ 00:10:18.159 Awaish Kumar: If we are moving on to another tool, we will… get some…

68 00:10:18.440 ⇒ 00:10:20.639 Awaish Kumar: A few weeks of work to migrate.

69 00:10:20.980 ⇒ 00:10:22.790 Awaish Kumar: Everything there.

70 00:10:23.050 ⇒ 00:10:26.630 Awaish Kumar: And then underlying modeling work, maybe?

71 00:10:28.520 ⇒ 00:10:29.230 Uttam Kumaran: Okay.

72 00:10:29.230 ⇒ 00:10:30.720 Awaish Kumar: And then…

73 00:10:35.020 ⇒ 00:10:36.060 Awaish Kumar: We…

74 00:10:37.030 ⇒ 00:10:38.300 Uttam Kumaran: We are…

75 00:10:39.000 ⇒ 00:10:43.020 Awaish Kumar: we have this COGS thing, which has been being, like, pushed out.

76 00:10:43.620 ⇒ 00:10:45.770 Awaish Kumar: Of our sprints.

77 00:10:45.880 ⇒ 00:10:51.240 Awaish Kumar: For a few weeks, like, so, like, working on,

78 00:10:53.050 ⇒ 00:11:03.170 Awaish Kumar: optimizing how COGS are updated for each product. We have been pushing it because we thought we might be moving on to

79 00:11:03.370 ⇒ 00:11:06.119 Awaish Kumar: Like, remote pretty soon?

80 00:11:06.250 ⇒ 00:11:09.010 Awaish Kumar: But I don’t think that’s happening.

81 00:11:09.740 ⇒ 00:11:10.500 Awaish Kumar: Hold on.

82 00:11:11.670 ⇒ 00:11:15.140 Awaish Kumar: And then, yeah, we can think of, like,

83 00:11:15.350 ⇒ 00:11:18.499 Awaish Kumar: We have also had a task for self-service.

84 00:11:19.190 ⇒ 00:11:21.380 Awaish Kumar: Things like, we have been…

85 00:11:21.660 ⇒ 00:11:28.090 Awaish Kumar: We’re working a lot on ad hoc requests, so we can… we… I created a… plan…

86 00:11:28.300 ⇒ 00:11:34.069 Awaish Kumar: To standardize those requests and convert them into some kind of dashboards.

87 00:11:35.090 ⇒ 00:11:35.770 Uttam Kumaran: Okay.

88 00:11:36.640 ⇒ 00:11:37.800 Awaish Kumar: Yeah, these are…

89 00:11:41.970 ⇒ 00:11:54.409 Robert Tseng: Yeah, so I kind of, like, am trying to bucket this into, like, 3 work streams. There’s, like, on the marketing side, like, marketing to me is, like, MarTech. Like, all the stuff from Cutter, I mean, obviously it’s GPT-generated, but it’s, like.

90 00:11:54.460 ⇒ 00:12:12.839 Robert Tseng: conversion sources, like, tagging, identity matching, like, that… Zoran is the lead on this. Like, this is Zoran, like, Zoran’s responsible for the outcomes here. So, as far as, like, prioritizing, like, which outcomes are important to go after, like, I kind of want him to own this, like, all these… all these OKRs.

91 00:12:12.940 ⇒ 00:12:25.839 Robert Tseng: They… he… he is now meeting with them regularly enough. He has, like, you know, 15 hours a week with just this team, like, that’s already budgeted for him. He needs to, like, really own this roadmap,

92 00:12:26.370 ⇒ 00:12:33.599 Robert Tseng: So I think that’s one piece of it. Then there’s, like, operational OKRs, which is, like, I guess…

93 00:12:33.600 ⇒ 00:12:34.160 Awaish Kumar: Oh, yeah.

94 00:12:35.020 ⇒ 00:12:37.339 Awaish Kumar: I have a question on the first part, like.

95 00:12:37.530 ⇒ 00:12:37.980 Robert Tseng: Yes.

96 00:12:37.980 ⇒ 00:12:43.660 Awaish Kumar: that it’s, like, marketing okay as the responsibility of Zoran. Does that mean he’s…

97 00:12:44.360 ⇒ 00:12:51.930 Awaish Kumar: He will be entirely working on this, or it’s just, like, he will be leading the development, and then, obviously, team can help him?

98 00:12:52.200 ⇒ 00:13:02.509 Robert Tseng: Yeah, the team’s gotta help, but Zoran works on literally nothing else. Like, he’s only in Marketing Man. Like, he should not be touching anything else. Like, we don’t… he doesn’t really have the time for that, nor do I really… I mean…

99 00:13:02.690 ⇒ 00:13:09.419 Robert Tseng: At this point in time, anyway, like, we don’t really see a need to pull them into the other… to the other work, so…

100 00:13:09.950 ⇒ 00:13:16.949 Awaish Kumar: No, I mean, like, like, I’ve been involved, like, on the server-side things, or API development, or…

101 00:13:17.650 ⇒ 00:13:19.729 Awaish Kumar: For adjustment and segment, or things like that.

102 00:13:19.730 ⇒ 00:13:23.750 Uttam Kumaran: No, no, you’re totally, like, I… but it’s gonna be up to him to drive the roadmap.

103 00:13:23.750 ⇒ 00:13:24.150 Awaish Kumar: Okay.

104 00:13:24.150 ⇒ 00:13:43.070 Uttam Kumaran: I don’t care who works on it, it’s not relevant to me, but to give you a sense of ways, I need you on, like, other clients, so he… what I’m saying here is he’s gonna say to us what capacity is needed, and whether that exceeds his time or not, and we’ll make a joint decision on who’s gonna work on it.

105 00:13:43.150 ⇒ 00:13:44.650 Awaish Kumar: Bye. Okay.

106 00:13:45.030 ⇒ 00:13:45.630 Uttam Kumaran: Sure.

107 00:13:47.820 ⇒ 00:13:55.110 Robert Tseng: Yeah, I mean, yeah, obviously the team is involved in, like, kind of executing any of these things. At this point, Zoran’s familiar with

108 00:13:55.180 ⇒ 00:14:10.070 Robert Tseng: kind of our internal capabilities when we need to, like, do data modeling, how that works, and we’re able to get him whatever format he needs in order to make these different tools connect to each other. But that’s… that’s really what he’s owning.

109 00:14:12.770 ⇒ 00:14:27.079 Robert Tseng: Yeah. I don’t personally consider Mixpanel, like, part of this work. Like, I understand everything… everything is marketing, like, we’re not really doing, like, product development or whatever with them, so even when I talk about product, to me, this is, like.

110 00:14:27.280 ⇒ 00:14:34.709 Robert Tseng: What product is, like, their site experience, the intake forms, like, everything else kind of falls within, like, the digital product, like, that’s, that’s what.

111 00:14:34.710 ⇒ 00:14:37.670 Uttam Kumaran: Would you consider awareness versus conversion?

112 00:14:40.370 ⇒ 00:14:48.369 Uttam Kumaran: awareness-related, like… Basically, like, awareness and… and, like, paid… and paid marketing.

113 00:14:51.480 ⇒ 00:14:54.039 Robert Tseng: Yeah… yeah, I guess so.

114 00:14:55.570 ⇒ 00:14:56.150 Uttam Kumaran: Okay.

115 00:14:56.150 ⇒ 00:14:57.320 Robert Tseng: Yeah, yeah.

116 00:15:00.040 ⇒ 00:15:07.010 Henry Zhao: Yeah, that’s what I was thinking for Mixpanel, because Mixpanel is, like, the UTMs for awareness, and then where do they drop off,

117 00:15:07.620 ⇒ 00:15:09.750 Henry Zhao: Like, what does the intake process look like?

118 00:15:09.930 ⇒ 00:15:12.059 Henry Zhao: It’s like, getting rid of the ID, how does that…

119 00:15:12.060 ⇒ 00:15:19.509 Uttam Kumaran: You’re not gonna be using Mixpanel as, like, attribution. Like, that’s what I’m saying. Like, Mixpanel’s not doing the attribution.

120 00:15:19.690 ⇒ 00:15:20.360 Uttam Kumaran: But it’s…

121 00:15:20.360 ⇒ 00:15:21.930 Henry Zhao: But it’s connecting, right? It’s like…

122 00:15:22.140 ⇒ 00:15:26.730 Henry Zhao: It’s reporting on, based on attribution, what are the actions being taken.

123 00:15:27.040 ⇒ 00:15:32.570 Henry Zhao: Exactly, but it’s connected, right? So it’s like, are Facebook people dropping off more? Are our email bringing them back?

124 00:15:32.570 ⇒ 00:15:39.330 Uttam Kumaran: But, like, I guess what I’m saying is, like, if this is solved, then the mixed panel data will be high…

125 00:15:39.760 ⇒ 00:15:44.770 Uttam Kumaran: will be accuracy, right? You can rely on the mixed channel segmentation accurately.

126 00:15:44.770 ⇒ 00:15:45.770 Henry Zhao: Yeah. That’s…

127 00:15:45.770 ⇒ 00:15:47.280 Uttam Kumaran: Yeah. Okay.

128 00:15:49.960 ⇒ 00:15:55.979 Uttam Kumaran: So, I mean, I would… I… in my mind, and again, we can polish it, but I would say that’s all around the

129 00:15:56.990 ⇒ 00:15:58.500 Uttam Kumaran: kind of conversion…

130 00:15:59.040 ⇒ 00:16:13.419 Uttam Kumaran: basically, like, conversion funnel and experience, because you can’t really, like, we don’t have measurements on when they’re injecting themselves, right? So the only experience that we do have is when they’re signing up.

131 00:16:13.550 ⇒ 00:16:16.420 Uttam Kumaran: And then, like, when they’re back on the platform, right?

132 00:16:17.150 ⇒ 00:16:24.890 Awaish Kumar: We do have the identities of those which visited, basically, with their new age layer system.

133 00:16:25.190 ⇒ 00:16:29.639 Awaish Kumar: We can basically identify the people visiting…

134 00:16:29.640 ⇒ 00:16:41.529 Robert Tseng: Yeah, that’s all the top level, that’s, like, awareness, yeah. No, but I mean, they do have some self-reported… they have to do, like, weight check-ins, and, like, there’s some, like, medical outcome things that they… that patients are self-reported.

135 00:16:41.530 ⇒ 00:16:42.329 Uttam Kumaran: That’d be possible.

136 00:16:43.230 ⇒ 00:16:56.059 Robert Tseng: Yeah, there’s no true diagnostic that’s happening. Everything is just, like, self-reported, like, check-ins that they have to go and fill out in order to renew their subscription and whatever. Like, there’s, like, that… that’s… there’s at least one check-in point

137 00:16:56.060 ⇒ 00:17:04.889 Robert Tseng: That’s why… that’s… we have, like, a dashboard somewhere about, like, weight loss and, like, outcomes and stuff that’s in Tableau that Annie had built out early on.

138 00:17:05.819 ⇒ 00:17:17.159 Uttam Kumaran: Yeah, I remember that. So, I would say under here, this is, like, conversion and… so you can split up, right? Conversion, and then you can split up the customer journey, but I feel like these are all under here, basically.

139 00:17:18.359 ⇒ 00:17:19.029 Robert Tseng: Yeah.

140 00:17:20.200 ⇒ 00:17:22.649 Uttam Kumaran: And would you put, like, discounts?

141 00:17:23.250 ⇒ 00:17:26.090 Uttam Kumaran: Bundling, like, pricing strategy all under here.

142 00:17:28.130 ⇒ 00:17:32.540 Robert Tseng: Yeah, well, so, like, I think this is kind of where we need to, like, separate, like.

143 00:17:40.700 ⇒ 00:17:59.520 Robert Tseng: like, I think calling it customer journey was, like, not enough. Like, we did that before, and, like, nobody owns the customer journey end-to-end. Instead, like, there are different levers. There’s, like, the people who are just spending more money, which is, like, the paid ads, like, conversion, like, traditional CRO stuff, which is…

144 00:17:59.600 ⇒ 00:18:10.609 Robert Tseng: like, landing pages, like, web analytics, like, whatever, just, like, intake experiment, like, yeah, all that. Pricing experimentation, new product offerings, like.

145 00:18:10.610 ⇒ 00:18:26.680 Robert Tseng: and… and, like, retention, like, that’s all, like, product-driven, in my opinion. That’s not really… then they don’t really… they don’t have a product team, but, like, for our purposes, like, to separate one happens later on in the customer journey, or, like.

146 00:18:26.770 ⇒ 00:18:45.970 Robert Tseng: what… and, like, what happens, like, obviously before they convert to customers. So, like, I… I… like, Tutter is not running pricing experiments, and, like, he just is trying to throw money in different channels. Like, he’s… that’s… that’s all he will, like, keep…

147 00:18:46.080 ⇒ 00:19:05.920 Robert Tseng: like, kind of grilling, like, Zoran on, and Zoran is just… is just there to kind of help with the paid kind of team’s efforts. Where our real nuggets are coming from are from pricing experiments, from, bundling, like, insights, like, stuff like that, that… that, like, happens

148 00:19:05.950 ⇒ 00:19:20.899 Robert Tseng: like, nobody’s doing that analysis right now. That’s all, like, white space for us. I consider that to be, like, product insights. Like, that’s… at least that’s the way that it was structured in previous teams for me, and, like, I… I kind of… that’s how… that’s where I draw the line.

149 00:19:29.350 ⇒ 00:19:30.090 Uttam Kumaran: Okay.

150 00:19:52.280 ⇒ 00:20:02.519 Uttam Kumaran: Okay. I mean, it seems clear that there is something on, like, sort of the sign-up journey, retention journey. There is, like, sort of a…

151 00:20:02.630 ⇒ 00:20:06.920 Uttam Kumaran: customer experience, with, like, pharmacy SLAs.

152 00:20:07.240 ⇒ 00:20:14.909 Uttam Kumaran: And then… do we have any understanding of, like, retention, like LTV to date?

153 00:20:17.610 ⇒ 00:20:20.230 Robert Tseng: Sorry, I’m, like, rearranging these things, because, like…

154 00:20:21.730 ⇒ 00:20:25.320 Robert Tseng: Yeah, like, CRO is… is, like.

155 00:20:29.990 ⇒ 00:20:46.190 Robert Tseng: Like, yeah, I’m just gonna… Like, landing… a landing page, like, design… experiments, intake, expe… like…

156 00:20:46.600 ⇒ 00:20:58.840 Robert Tseng: intake experiments, like, it makes panel, like, like, funnel reporting. I don’t even think this is part of that, like, I consider retention part of this.

157 00:20:59.090 ⇒ 00:21:00.000 Robert Tseng: like…

158 00:21:00.760 ⇒ 00:21:07.359 Robert Tseng: We need to get… I’m just gonna be writing things… we need to get Judd and Ryan need to be in…

159 00:21:08.030 ⇒ 00:21:13.060 Robert Tseng: in… in Mixpanel, running their, like, running reports.

160 00:21:13.060 ⇒ 00:21:14.250 Awaish Kumar: building…

161 00:21:14.280 ⇒ 00:21:23.370 Robert Tseng: building segments, Building behavioral segments that will guide, like, the…

162 00:21:23.480 ⇒ 00:21:29.649 Robert Tseng: types of experiments they run against, like, guide their experimentation.

163 00:21:30.790 ⇒ 00:21:37.010 Robert Tseng: On the ops side, yeah, pharmacy SLA, it’s really just, like, what goes into

164 00:21:37.310 ⇒ 00:21:42.570 Robert Tseng: What happens when an order gets to the pharmacy?

165 00:21:42.710 ⇒ 00:21:47.850 Robert Tseng: To, like, when… When it leaves the pharmacy.

166 00:21:47.950 ⇒ 00:21:51.300 Robert Tseng: Like, that’s… that’s… that’s what’s missing.

167 00:21:52.010 ⇒ 00:21:55.630 Robert Tseng: Then there’s gonna be, like, you know.

168 00:21:55.900 ⇒ 00:22:05.859 Robert Tseng: like, last mile, like, logistics optimizations as well. There’s gonna be re… returns and refunds, like.

169 00:22:06.030 ⇒ 00:22:12.159 Robert Tseng: I mean, I don’t think there’s refunds. I don’t really even know if there’s returns, but kind of just, like, reverse logistics, which is called that.

170 00:22:21.700 ⇒ 00:22:30.649 Robert Tseng: like, that’s pretty much it. Like, there might be, like, something around, like, network, like, pharmacy,

171 00:22:34.430 ⇒ 00:22:35.870 Robert Tseng: like…

172 00:22:37.160 ⇒ 00:22:54.979 Robert Tseng: customer success, like, escalations, like, which we already do, this is, like, the whole, like, Zendesk reporting and all that. So I think that’s already more or less taken care of. And then for products, yeah, discounts, bundling, like, how do you… how do you package, like…

173 00:22:55.060 ⇒ 00:23:08.570 Robert Tseng: How do you, like, launch and package products to maximize Profitability, like… Who are, like, the…

174 00:23:10.250 ⇒ 00:23:16.589 Robert Tseng: Yeah, like, this is kind of… Voice… voice of the customer…

175 00:23:20.160 ⇒ 00:23:29.520 Robert Tseng: Like, looking at, like, oh.

176 00:23:30.170 ⇒ 00:23:42.990 Robert Tseng: This is kind of just, like, ongoing. This is, like, LTV, LTV, CAC, by segments, like… And…

177 00:23:43.590 ⇒ 00:23:56.529 Robert Tseng: Yeah, just, like, trying to help identify, like, what… which segments are underperforming, like, cut them out, like, which ones are the higher performing ones, keep them, trying to get people to become more like that. Like, this will, like…

178 00:23:56.530 ⇒ 00:24:07.340 Robert Tseng: Yeah, anyway, so, like, that’ll always kind of be there. So, I know I just, like, kind of brain-dumped a lot of things, but, like, I view these as, like, separate… I mean, this is how I would separate it.

179 00:24:11.800 ⇒ 00:24:14.660 Uttam Kumaran: Yeah, I’m just gonna move these up, and so we can see everything.

180 00:24:16.560 ⇒ 00:24:17.589 Uttam Kumaran: Actually, I’m just thinking…

181 00:24:17.590 ⇒ 00:24:18.320 Awaish Kumar: Hmm.

182 00:24:18.320 ⇒ 00:24:22.140 Robert Tseng: So, like, this one, I think, like, Brainforge needs to do this.

183 00:24:22.520 ⇒ 00:24:24.339 Robert Tseng: This is, like.

184 00:24:27.540 ⇒ 00:24:36.489 Robert Tseng: high leverage… hard work. This is, like… low leverage.

185 00:24:39.370 ⇒ 00:24:45.979 Robert Tseng: like, relatively low, like, or like, I don’t know, kind of… like, kind of…

186 00:24:46.800 ⇒ 00:24:54.570 Robert Tseng: hard… it’s… it’s… it’s hard work as well, to be honest. And then this one is, like, high leverage, low effort, like.

187 00:24:54.750 ⇒ 00:24:58.450 Robert Tseng: like… not hard work. Like…

188 00:25:00.030 ⇒ 00:25:09.389 Robert Tseng: Because we just have to build, like, the… the system for them to go and… it’s, like, about getting… we keep saying mixed panel is, like, not ready, it’s… it’s…

189 00:25:09.710 ⇒ 00:25:19.639 Robert Tseng: it’s ready. Like, I feel like if I just spent, like, one or two weeks in it, I would put it in their hands, I’d be forcing people to be using it. Like, I… it’s just a function of us, like, not really, like.

190 00:25:19.640 ⇒ 00:25:20.130 Henry Zhao: Yeah, I agree.

191 00:25:20.130 ⇒ 00:25:25.750 Robert Tseng: really, like, doing that. So… And then they will need to just…

192 00:25:25.840 ⇒ 00:25:44.730 Robert Tseng: they need to feed… they need to learn how to feed themselves. Like, the… the fact that, like, nobody on their team really pulls any data for themselves other than the finance is just, like, is… is not great. So, like, I think this is… this is the easiest thing to do. Like, lowest effort from us, and, like, it’s just about…

193 00:25:45.130 ⇒ 00:25:53.690 Robert Tseng: kind of coaching… coaching their team, getting the people right in there, like, finding… like, yeah, like, I think this is, like, the eas… this is… this is probably the easiest thing that we should be doing.

194 00:25:53.700 ⇒ 00:26:07.000 Robert Tseng: this is, like, good to do as well, because I think we can actually do… this is what they’ll… they want us to do, but they’re not really, like, looking at these two other areas. So, anyway, like, that’s kind of how I see it.

195 00:26:07.450 ⇒ 00:26:14.839 Uttam Kumaran: So, yeah, in my mind, like, there’s… of course, there’s a lot of different frameworks. For me, it’s, like, importance.

196 00:26:15.090 ⇒ 00:26:16.810 Uttam Kumaran: and effort.

197 00:26:17.180 ⇒ 00:26:27.990 Uttam Kumaran: and, like, urgency, right? So urgency kind of can trump a lot of things, but if we are, like, hey, every… all of this is technically urgent, then…

198 00:26:28.250 ⇒ 00:26:34.219 Uttam Kumaran: I’m interested in this as, like, the tasks for our analysis team.

199 00:26:34.580 ⇒ 00:26:37.479 Uttam Kumaran: And then, this is purely…

200 00:26:37.850 ⇒ 00:26:43.410 Uttam Kumaran: like, Henry to own and drive. But what I guess I would say is, like.

201 00:26:43.630 ⇒ 00:26:52.799 Uttam Kumaran: I… I have not seen, like, a clear plan around mixed panel implementation, adoption, training, and, like, measurement of

202 00:26:53.090 ⇒ 00:26:56.419 Uttam Kumaran: adoption. So, simply implementing.

203 00:26:56.420 ⇒ 00:26:57.760 Henry Zhao: I can work on a plane for that.

204 00:26:58.430 ⇒ 00:26:59.190 Uttam Kumaran: Diet?

205 00:26:59.670 ⇒ 00:27:01.940 Henry Zhao: I can work on a plan for that, by Friday.

206 00:27:02.830 ⇒ 00:27:16.319 Uttam Kumaran: Yeah, no, but I guess even before that, what I want to do here is, like, I need, like, I want to just agree that, okay, like, we’re good with these two. And so, for me, the optics, Robert, is, like, these are things that

207 00:27:16.640 ⇒ 00:27:24.270 Uttam Kumaran: We can produce insights on a weekly basis that you can deliver on the… ELT calls.

208 00:27:24.400 ⇒ 00:27:27.590 Uttam Kumaran: This is stuff that, like, also may…

209 00:27:27.690 ⇒ 00:27:37.189 Uttam Kumaran: enhance some of these analyses, but more importantly, enables just people to Start doing things themselves, right?

210 00:27:39.730 ⇒ 00:27:47.000 Uttam Kumaran: Like, would you be making some… would you be presenting some of this work to… ELT? Okay, yeah.

211 00:27:51.380 ⇒ 00:27:58.119 Robert Tseng: like, I don’t know, I guess, like, the CRO stuff, like, ultimately, we don’t own the outcomes here. We just need to…

212 00:27:58.360 ⇒ 00:28:03.000 Robert Tseng: yeah, like, I… they… they will present it in their own check-in, like, it’s…

213 00:28:03.080 ⇒ 00:28:22.099 Robert Tseng: like, I want them to be using, like, what we get, what we’ve built for them to make their insights, like, I think that would be enough credit for us. But, like, ultimately, we’re not a CRO company, we’re not running experiments, it’s just not… it’s just not, like, it’s not our thing. So, it’s more of an enablement. Yeah, this one is, like, they expect us to own this one. Like, it’s…

214 00:28:22.100 ⇒ 00:28:41.969 Robert Tseng: this is, like, where all the, you know, all the requests we’ve been kicking down the road, they’re all gonna come and get us now, like, the… we need to do some of this, like, operational reporting work, especially as they’re moving different systems, like, new pharmacy provider, like, whatever, like, all that stuff, like, this is just, like, we need to do this.

215 00:28:43.500 ⇒ 00:28:55.069 Robert Tseng: Or, I meant the ops work. And then the product stuff is, like, no one’s asking for this, but I… this is, like, what I want to, on a bi-weekly basis, be able to put nuggets in front of them so that

216 00:28:55.070 ⇒ 00:29:05.269 Robert Tseng: they will be like, hey, like, do more of that. Like, I think we… we have the least buy-in around this, and if we have no margin in our roadmap planning, we never do miss work.

217 00:29:05.270 ⇒ 00:29:13.069 Robert Tseng: But this, to me, it could be slower, and we should just put stuff out, like, on a bi-weekly cadence, doesn’t have to be every week. But, like, I think…

218 00:29:13.070 ⇒ 00:29:30.409 Robert Tseng: Yeah, to do something really high quality, I think it would probably take two weeks to get there. I think this, like, that’s… that would be a good goal, to put, you know, to put, like, an analysis out, you know, for ELT, like, once every two weeks kind of thing.

219 00:29:33.240 ⇒ 00:29:42.790 Uttam Kumaran: Yeah, for all of our clients that we are doing both… the DE work and the modeling work is just not worth putting in front of

220 00:29:42.970 ⇒ 00:29:58.240 Uttam Kumaran: like, the high-level stakeholders. We have to always try to drive towards these, even if we just, like, have something half-baked, but we’re probably the only people that have thought about this. And so, okay, I feel like this is pretty fair. I think what… what I’ll need

221 00:29:58.460 ⇒ 00:30:05.360 Uttam Kumaran: what we’ll need to start with, you know, Henry, is, like, we do have project.

222 00:30:05.470 ⇒ 00:30:20.549 Uttam Kumaran: templates, so don’t go… don’t write something new. There are project… like, project templates on how to structure, like, a project around this, but for me, I… in order for me to give feedback, that document has to have, like.

223 00:30:20.840 ⇒ 00:30:24.619 Uttam Kumaran: what exists to date? Like, who is…

224 00:30:24.790 ⇒ 00:30:39.860 Uttam Kumaran: like, who are the people involved? And then, certainly here, we need to have some plan around training, and then also a clear plan on reporting to ELT on how many people are using Mixpanel. So these are, like.

225 00:30:39.860 ⇒ 00:30:40.180 Henry Zhao: Go ahead.

226 00:30:40.180 ⇒ 00:30:51.199 Uttam Kumaran: you can… you can look in Mixpanel to see logins and see, like, what they’re doing. That is the data for us to prove, okay, people, once a week, people are now using

227 00:30:51.520 ⇒ 00:30:52.530 Uttam Kumaran: Mixed panel.

228 00:30:52.700 ⇒ 00:30:57.570 Uttam Kumaran: You know, like, that’s… that’s what would really be success for me.

229 00:30:57.960 ⇒ 00:30:59.039 Henry Zhao: Okay, sounds good.

230 00:31:03.730 ⇒ 00:31:09.540 Uttam Kumaran: And then for this, Robert, like, this is just gonna be… squarely in Amber’s court.

231 00:31:10.180 ⇒ 00:31:10.840 Robert Tseng: Yeah.

232 00:31:11.550 ⇒ 00:31:18.189 Uttam Kumaran: We can also, you know, see, like, Demolari’s appetite to take on some of this.

233 00:31:18.640 ⇒ 00:31:22.289 Uttam Kumaran: but I would like to move…

234 00:31:23.040 ⇒ 00:31:27.720 Uttam Kumaran: One of them towards this area, and out of… the rest.

235 00:31:28.200 ⇒ 00:31:28.810 Robert Tseng: Yeah.

236 00:31:31.660 ⇒ 00:31:32.260 Uttam Kumaran: Okay.

237 00:31:34.800 ⇒ 00:31:39.320 Robert Tseng: I think the ops work is gonna be, like, yeah,

238 00:31:40.000 ⇒ 00:31:47.640 Robert Tseng: Henry’s gonna go and get the lay of the land, but I think this is purely data engineering work. Like, it’s really just about

239 00:31:47.830 ⇒ 00:31:58.370 Robert Tseng: making sure that we’re tracking the right milestones, like, being able to, like, build in this capability to reporting. So, if I were to assign owners, like, the ops stuff should be…

240 00:31:59.430 ⇒ 00:32:02.429 Robert Tseng: should be, whatever, a Demolade…

241 00:32:02.540 ⇒ 00:32:10.859 Robert Tseng: I’m just… yeah, I think a lot of product is, I guess, could be me, and then, like, the CRO stuff is really, like, Henry.

242 00:32:11.210 ⇒ 00:32:19.379 Robert Tseng: Yeah, like, I… I don’t know, something… some mix of that, and Awash is not really the owner or anything, because he’s kind of just able to float wherever.

243 00:32:22.480 ⇒ 00:32:27.170 Uttam Kumaran: Okay, so my… what… where… how this is gonna get leveraged…

244 00:32:27.190 ⇒ 00:32:44.929 Uttam Kumaran: this is where, like, in the past, when we’ve done these things, they never made it more than a week into, like, what the fuck we’re actually working on in a sprint. So, I am going to be very crisp on evaluating work that we get that aligns to each of these OKRs.

245 00:32:45.070 ⇒ 00:32:58.339 Uttam Kumaran: And the other piece I’m gonna do is, like, the senior folks, like Henry, Zoran, Awash, like, I’m gonna really push on you to defend, like, why, like, the plan around achieving these.

246 00:32:58.510 ⇒ 00:33:01.640 Uttam Kumaran: This is something that it has to move from

247 00:33:01.680 ⇒ 00:33:12.179 Uttam Kumaran: Robert and I’s responsibility down, and we have the structure in place for y’all to accomplish that. It will take a little bit more strategic thinking and planning here.

248 00:33:12.180 ⇒ 00:33:30.199 Uttam Kumaran: But I want to move you guys to a level that’s not just like, what tickets do I have on my plate? I will get you more people that will go do that, and those people will be more junior than you. And what… and I want to move you guys, with your experience, to a point where you’re able to define your own roadmap.

249 00:33:30.530 ⇒ 00:33:48.160 Uttam Kumaran: And so, for me, the biggest thing here is when we talk in our Eden meetings, I’ll be looking to see how the work we’re taking on aligns for these OKRs, and in our delivery meetings weekly, I want to be seeing our progress towards these OKRs for Eden.

250 00:33:48.190 ⇒ 00:33:52.839 Uttam Kumaran: Right? That will be… that will be something that… I’ll ask about.

251 00:33:53.620 ⇒ 00:33:58.320 Henry Zhao: We already have people that can help us on these, like, ad hoc tickets that, like, as they come in, we can maybe, like.

252 00:33:58.610 ⇒ 00:34:01.409 Henry Zhao: Start delegating those already, so we can make progress on these?

253 00:34:01.760 ⇒ 00:34:03.930 Henry Zhao: Because these ad hoc tickets come in all the time.

254 00:34:04.350 ⇒ 00:34:06.439 Uttam Kumaran: You have to tell me what ad hoc tickets.

255 00:34:07.170 ⇒ 00:34:12.339 Uttam Kumaran: Because it’s not clear to me what ad hoc tickets can’t be done with the, like.

256 00:34:12.570 ⇒ 00:34:26.029 Uttam Kumaran: for example, like, what are those tickets? And if they’re not… if they don’t fit into this, like, can we push back on them? So, all that has to happen, again, like, what I’m gonna push back on is, like, oh, there’s add-on tickets, can I get more people?

257 00:34:26.190 ⇒ 00:34:34.350 Uttam Kumaran: what we need to… what you need to tell me is, like, what are those ad hoc tickets? Do they fit under any of these OKRs? And if not, okay, then we can make a decision on who takes them.

258 00:34:34.469 ⇒ 00:34:47.449 Uttam Kumaran: there’s always going to be ad hoc stuff that comes on, so it’s not like 100% of our time can go to this, but it certainly can’t be now, where 20% of our time, I feel like, is going to really accomplishing some of these.

259 00:34:48.370 ⇒ 00:34:49.689 Henry Zhao: Okay, yeah, makes sense.

260 00:34:50.110 ⇒ 00:34:54.679 Uttam Kumaran: So we’ll push… we will… we have many mechanisms to push back on the ad hoc work.

261 00:34:56.760 ⇒ 00:35:01.519 Uttam Kumaran: So that’s… that’s… that’s what I… I would just need to know, and we can do that all in planning.

262 00:35:02.600 ⇒ 00:35:20.099 Henry Zhao: Yeah, and I would say also, just keep in mind that these ad hoc requests, sometimes, like, they evolve, so sometimes they start out looking like they… they service some of these, but then as we work on them, they’re like, actually, those are not actually that helpful, or sometimes they… it looks like it’ll take an hour, but actually, like, takes a lot longer, so we need to also have a plan to, like.

263 00:35:20.360 ⇒ 00:35:25.320 Uttam Kumaran: Yeah, so the biggest thing there is don’t say yes to new work until you understand what you’re signing up for.

264 00:35:25.520 ⇒ 00:35:26.650 Henry Zhao: Yeah.

265 00:35:26.780 ⇒ 00:35:33.750 Uttam Kumaran: you shouldn’t take… number one, don’t say yes to new… to new work. That seems like not what it seems like.

266 00:35:33.950 ⇒ 00:35:38.089 Uttam Kumaran: do some light discovery, then come to stand-up and be like, I got this task.

267 00:35:38.260 ⇒ 00:35:40.059 Uttam Kumaran: Should we do it this week or not?

268 00:35:40.650 ⇒ 00:35:41.619 Henry Zhao: Yeah, yeah, that works.

269 00:35:41.620 ⇒ 00:35:45.480 Uttam Kumaran: You have to protect your time, certainly, and…

270 00:35:45.770 ⇒ 00:36:00.460 Uttam Kumaran: we’re the data team for this company that’s growing, this is, like, the peril. So you just have to be really, really clear on, like, okay, what is… what am I gonna take? And in the situation where you get asked, say, hey, this is super urgent, can I get back to you tomorrow?

271 00:36:01.260 ⇒ 00:36:01.810 Henry Zhao: Ram.

272 00:36:02.320 ⇒ 00:36:02.730 Uttam Kumaran: Yeah.

273 00:36:02.730 ⇒ 00:36:03.260 Henry Zhao: Yep.

274 00:36:05.610 ⇒ 00:36:07.620 Henry Zhao: I think we all need to be better on that, so…

275 00:36:08.210 ⇒ 00:36:23.189 Uttam Kumaran: to give you a sense, like, I don’t even know, like, the reason we’re doing tickets is because we’ve… we sort of never are talking at this level. Most of our meetings about Eden should start at this point, and then move to, like, okay, are we ticketing everything out?

276 00:36:23.190 ⇒ 00:36:32.700 Uttam Kumaran: ultimately, like, if we’re… if we don’t have active work that hits the two core priorities, that’s, like, that’s our… our failure, right? So…

277 00:36:33.550 ⇒ 00:36:40.010 Uttam Kumaran: I don’t know whether we’ll talk about this daily, but at least on a weekly basis, we want to make sure how we’re making progress towards these two.

278 00:36:43.050 ⇒ 00:36:43.710 Awaish Kumar: Okay.

279 00:36:44.340 ⇒ 00:36:45.030 Uttam Kumaran: Cool.

280 00:36:45.580 ⇒ 00:36:50.409 Uttam Kumaran: Can we talk through insomnia?

281 00:36:51.970 ⇒ 00:36:52.660 Robert Tseng: Yeah.

282 00:36:54.050 ⇒ 00:36:55.350 Uttam Kumaran: What will happen?

283 00:36:55.940 ⇒ 00:36:59.679 Robert Tseng: No, no, I just, like, energy level is low.

284 00:36:59.680 ⇒ 00:37:05.750 Uttam Kumaran: So this is… no, this is overwhelming, and it’s like, this is… this is the alignment, like, I need…

285 00:37:06.090 ⇒ 00:37:10.390 Uttam Kumaran: this alignment. This is truly, like, again, we talked about in the services meeting, like.

286 00:37:10.770 ⇒ 00:37:14.210 Uttam Kumaran: I want there to be no doubt that we, like.

287 00:37:14.370 ⇒ 00:37:19.649 Uttam Kumaran: are pushing our way towards, is whether we achieve it or not, it could be a hundred reasons. But…

288 00:37:20.180 ⇒ 00:37:23.780 Uttam Kumaran: this is what I think makes or breaks, like, the best, like.

289 00:37:23.990 ⇒ 00:37:26.660 Uttam Kumaran: true consultancies, you know? So, like…

290 00:37:26.660 ⇒ 00:37:27.310 Robert Tseng: Yeah.

291 00:37:27.520 ⇒ 00:37:34.330 Uttam Kumaran: I’ve never hired a consultancy that has broken down our business in this way and thought about it like this, right? So, like.

292 00:37:35.050 ⇒ 00:37:49.639 Uttam Kumaran: It’s impressive. We don’t hire consultants even for our business that ever do this. Most of them are like, what can I do today? Right? Instead of being like, let me actually, like, think holistically about who these guys are and what they need. We’re already, like, doing a good job.

293 00:37:49.790 ⇒ 00:37:55.910 Uttam Kumaran: We just need… we just have to… to… to… to constantly align ourselves, you know, so…

294 00:37:56.120 ⇒ 00:37:59.880 Robert Tseng: Yeah, can I… can I just get, like, a… a message?

295 00:38:00.160 ⇒ 00:38:04.350 Robert Tseng: or slide on these, just so I can share it with ELT.

296 00:38:05.070 ⇒ 00:38:05.570 Uttam Kumaran: Yeah.

297 00:38:05.570 ⇒ 00:38:22.469 Robert Tseng: be like, hey, we discussed, we planned, like, yeah, we’re not gonna… not… this is not a project-level kind of view, but this is, like, kind of what we… what we see coming, and, like, kind of how we… how we expect our time to kind of be split, you know, with the recent… with the changes. So, I think that would be… that would be helpful for them.

298 00:38:26.520 ⇒ 00:38:27.280 Uttam Kumaran: Yes.

299 00:38:27.480 ⇒ 00:38:34.180 Robert Tseng: Yeah, I mean, just because you’re already gonna, you know, rework these to get to… I mean, yeah, so if I can just get that.

300 00:38:36.530 ⇒ 00:38:39.879 Uttam Kumaran: And this is, this is kind of like Q4 and Q1.

301 00:38:40.050 ⇒ 00:38:41.180 Robert Tseng: Yeah, yeah, yeah.

302 00:38:51.680 ⇒ 00:38:52.350 Uttam Kumaran: Okay.

303 00:38:59.550 ⇒ 00:39:00.290 Uttam Kumaran: Okay.

304 00:39:07.650 ⇒ 00:39:09.519 Uttam Kumaran: Let’s talk about insomnia.

305 00:39:10.260 ⇒ 00:39:11.000 Robert Tseng: Sure.

306 00:39:26.590 ⇒ 00:39:28.849 Uttam Kumaran: So, I’m gonna go into…

307 00:39:56.800 ⇒ 00:39:59.599 Robert Tseng: Yeah, I don’t know which link it is, but it should be this one.

308 00:40:05.110 ⇒ 00:40:05.700 Uttam Kumaran: Great.

309 00:40:07.100 ⇒ 00:40:19.630 Robert Tseng: Yeah, I mean, I still think these are the main objectives. So, I mean, obviously, we’re, like, hyper-focused on just one. I mean, the budget is lower, so I’m not expecting us to work on four different things at once. I still think it’s just, like, it’s just the first objective.

310 00:40:19.990 ⇒ 00:40:32.070 Robert Tseng: although, like, kind of what we’re running into now is, like, we’re running into the limits of just using BRA’s data. Like, there’s other stuff which… I had a good conversation with… with Amber, she’s, like, asking good questions, she’s like.

311 00:40:32.440 ⇒ 00:40:46.120 Robert Tseng: okay, well, if we’re not… if we’re trying to expand, like, segmentation, like, and if we’re not only just using RFM, like, what other data do we have? Like, what data… what… what… what behavioral points actually, like, communicate intent?

312 00:40:46.350 ⇒ 00:40:49.840 Robert Tseng: Well, I… there’s Punch, which is their loyalty program.

313 00:40:50.020 ⇒ 00:40:57.939 Robert Tseng: You can look at all the offers and, like, kind of activity for rewards members. That gives you a sense of intent and, like, what kind of,

314 00:40:58.060 ⇒ 00:41:18.020 Robert Tseng: like, behaviors we can influence there, but that’s the only seg… that’s the only… yeah, other than that, all you have is transactional data that’s just, like, POS data from the retail locations that they’re purchasing at, or, you know, whatever… whatever sale is coming in from a different… like, whatever channel they’re com… whatever a channel

315 00:41:18.530 ⇒ 00:41:27.319 Robert Tseng: whichever channel a sale is coming in from, whether it’s a food delivery app, whether it’s a retail store, POS,

316 00:41:27.480 ⇒ 00:41:37.439 Robert Tseng: Or, you’re buying directly from the app or website, which is usually not most, most of the, most of the orders. So…

317 00:41:37.550 ⇒ 00:41:46.350 Robert Tseng: Yeah, there’s kind of, like, a need to expand, like, that’s what’s going to, like, push us to expand, like, the data we use.

318 00:41:46.420 ⇒ 00:41:57.420 Robert Tseng: Like, we’re both simultaneously maximizing the data that we have that we’re starting with, which is just brace, and also making the case to be like.

319 00:41:57.420 ⇒ 00:42:05.569 Robert Tseng: We need the time and resourcing to go and expand, like, our view to pull in more data from other places.

320 00:42:05.570 ⇒ 00:42:19.090 Robert Tseng: we’ve lightly touched on what’s in holistics. There’s nothing that we’ve touched on around loyalty and… and… and, I mean, yeah, there’s, like, whatever other… whatever… whatever other sources. Like, yeah, that’s…

321 00:42:19.110 ⇒ 00:42:26.959 Robert Tseng: We’re extrapolating as much as we can out of, like, what we have, and we also need to be continuously

322 00:42:27.070 ⇒ 00:42:36.830 Robert Tseng: like, telling them why we need to expand into… into… into more. So, we don’t have as free…

323 00:42:37.150 ⇒ 00:42:54.300 Robert Tseng: We’re not as freely able to roam like we do in other clients, which is the biggest risk, is just that we are set up to fail because we’re pigeonholed too much, and to just one system, and you just can’t answer that many questions from one system.

324 00:42:56.750 ⇒ 00:42:58.389 Uttam Kumaran: Yeah, okay, I agree.

325 00:42:58.390 ⇒ 00:42:59.070 Robert Tseng: Yeah.

326 00:43:01.750 ⇒ 00:43:20.379 Robert Tseng: So, I mean, I’m not worried about our pace or whatever, like, I think it’s clear, like, what needs to be done. Like, I’ve already, like, outlined all the stuff, like, I don’t need to rehash it, like, I… I… it’s just that, okay, we did push out… we are pushing out weekly insights, now we have to follow through, not just, like, letting it be, okay, leave some feedback.

327 00:43:20.380 ⇒ 00:43:26.719 Robert Tseng: But really pressing our stakeholders well, what are you doing about it? And, like, making sure that we’re

328 00:43:26.770 ⇒ 00:43:42.679 Robert Tseng: kind of seeing through, like, that our work is being operationalized, or if it’s being rejected, that we know why, so that we can go and follow up and, like, kind of produce something that’s a bit more… that’s more actionable. So, I think that’s… that’s kind of the… the dance that we’re playing with them right now.

329 00:43:45.250 ⇒ 00:43:50.510 Robert Tseng: The only engineering request that they have is It’s just like…

330 00:43:50.790 ⇒ 00:43:53.119 Robert Tseng: Hey, we have this weekly business review.

331 00:43:53.420 ⇒ 00:44:12.659 Robert Tseng: everyone’s on this call, this is what the format looked like when we arrived. We have the opportunity to reinvent it, and we… I mean, obviously, we’re not there yet, but that’s… that is the only engineering task that we should really be, like, that… that they… that they are… that they are actually, that’s actually top of mind for them.

332 00:44:14.760 ⇒ 00:44:18.799 Uttam Kumaran: But I guess my point will be, with the budget we have with them.

333 00:44:19.660 ⇒ 00:44:26.709 Uttam Kumaran: it’s gonna be hard to do anything but support the reporting needed for the analysis. And, like.

334 00:44:27.550 ⇒ 00:44:34.030 Uttam Kumaran: continue to support that. Like, we need at least a little bit more budget to move on a V2 of…

335 00:44:34.230 ⇒ 00:44:38.269 Uttam Kumaran: reporting, And to, like, actually have some, like, DE support.

336 00:44:38.970 ⇒ 00:44:45.360 Uttam Kumaran: Which I think… I think you can push for in, like, the next… version, like, we have enough

337 00:44:45.610 ⇒ 00:44:52.549 Uttam Kumaran: There, and we ate some budget on our side just to, like, Prove that that opportunity exists.

338 00:44:53.050 ⇒ 00:44:53.929 Robert Tseng: Yeah, I…

339 00:44:54.010 ⇒ 00:45:03.660 Uttam Kumaran: The other piece here is, I think I kind of now understand the scope, and I’m able to support from the technical side. I think the next biggest

340 00:45:03.800 ⇒ 00:45:08.939 Uttam Kumaran: Thing here is to start to get… you know, Amber more involved.

341 00:45:10.140 ⇒ 00:45:15.610 Uttam Kumaran: So, we’re starting to get a couple more people that are, like, a little bit deeper,

342 00:45:16.840 ⇒ 00:45:19.970 Uttam Kumaran: And then, yeah, I mean, I agree with you, is that, like, the…

343 00:45:20.350 ⇒ 00:45:27.800 Uttam Kumaran: I don’t know that she can sort of go in and drive the decision-making, though. Like, it will still be me and you having to meet with

344 00:45:29.050 ⇒ 00:45:32.319 Uttam Kumaran: Birdie or whoever to just be, like, driving this.

345 00:45:32.570 ⇒ 00:45:33.620 Uttam Kumaran: Yeah.

346 00:45:34.430 ⇒ 00:45:41.509 Uttam Kumaran: Right? And so, I certainly don’t mind meeting with Birdie and the technical people, I think you’re still probably…

347 00:45:41.720 ⇒ 00:45:43.549 Uttam Kumaran: I think you’re more equipped.

348 00:45:43.700 ⇒ 00:45:46.509 Uttam Kumaran: To do the higher level reviews.

349 00:45:46.680 ⇒ 00:45:51.899 Uttam Kumaran: I think it’s still similar, it’s all… but we wanted to get to, like, an Eden-type situation, right?

350 00:45:52.540 ⇒ 00:45:54.790 Robert Tseng: Yeah, we want… we wanted to get there, yeah.

351 00:45:58.030 ⇒ 00:46:03.499 Uttam Kumaran: So, if you were to say, like, at this current state.

352 00:46:04.560 ⇒ 00:46:12.299 Uttam Kumaran: Do you feel, on a week-to-week basis, Like, you’re equipped To walk into that…

353 00:46:12.690 ⇒ 00:46:17.180 Uttam Kumaran: Business review, or walk into, like, a weekly meeting with them, and, like, push.

354 00:46:17.780 ⇒ 00:46:23.959 Uttam Kumaran: And if not, like… what are the changes that we should make? Because…

355 00:46:24.100 ⇒ 00:46:26.950 Uttam Kumaran: I agree with you, I think we’re at, like, a good pace.

356 00:46:27.220 ⇒ 00:46:31.389 Uttam Kumaran: But… one, I know that you’re jammed.

357 00:46:31.620 ⇒ 00:46:38.720 Uttam Kumaran: to drive, so I’m now involved, continuing to push, at least taking over, like, a lot of the technical BS.

358 00:46:38.990 ⇒ 00:46:39.690 Robert Tseng: Yeah.

359 00:46:39.690 ⇒ 00:46:44.119 Uttam Kumaran: Amber is also now conducting analyses and tossing them to you for review.

360 00:46:44.450 ⇒ 00:46:45.090 Robert Tseng: Yeah.

361 00:46:45.450 ⇒ 00:46:51.120 Uttam Kumaran: what else… Like, can we do… Yeah, what else?

362 00:46:53.210 ⇒ 00:47:10.840 Robert Tseng: Yeah, I mean, I think… I think my time really just needs to just go into the… have more meetings then. I think… I don’t really know what else I can do. Like, there’s not that many levers that we have. I don’t need us to work faster, it doesn’t really matter. Like, I think we’re working… we’re working good enough for, like, the budget that we have.

363 00:47:12.830 ⇒ 00:47:18.269 Robert Tseng: Yeah, I mean, I think that they’re just shaping up to not be a very engaging fight. Like, it’s just like…

364 00:47:18.360 ⇒ 00:47:27.749 Robert Tseng: it… it kind of reminds me of Javi a bit, where… but it’s… it’s different. It’s a different stakeholder, obviously. With Eden, when I look back to the first couple months, like.

365 00:47:27.750 ⇒ 00:47:38.819 Robert Tseng: yeah, it made a lot of noise, and I picked one project, kind of really focused on that, and yeah, once we did a good job there, they continued to give us more access to more things.

366 00:47:38.960 ⇒ 00:47:55.869 Robert Tseng: Whereas, like, I don’t know, the way that things are set up here, it’s like, okay, we approved your budget for 3 months, it’s just gonna stay fixed, and it’s like, well, if… if the budget doesn’t… this doesn’t have the flexibility, if the scope doesn’t have the flexibility, then we’re, you know, this is just all we can, you know.

367 00:47:55.960 ⇒ 00:48:00.550 Robert Tseng: You’re just… it just forcibly slows us down, because we’re not really able to push

368 00:48:00.670 ⇒ 00:48:08.440 Robert Tseng: push more into other areas. So, that’s how I feel about it right now, and I… I don’t know what else we can do.

369 00:48:08.590 ⇒ 00:48:14.700 Robert Tseng: on the reporting side, I think it’s clear there is a… there is a braze

370 00:48:14.780 ⇒ 00:48:33.699 Robert Tseng: Braze currents is the fix, and, like, some mix of backfilling and also connecting to this product will repair, like, the brokenness of the Braze reporting. But that’s only one system. There’s all these other systems that we’re not in charge of, that we…

371 00:48:33.740 ⇒ 00:48:38.539 Robert Tseng: That we’re not… we don’t have the green light to go and own either, and it’s just, you know…

372 00:48:38.680 ⇒ 00:48:46.159 Robert Tseng: if we’re just, like, the guardians of Braze, then, like, I don’t really see… this is… this is, like, not really gonna end up going well, like, after December.

373 00:48:46.950 ⇒ 00:48:56.499 Uttam Kumaran: Yeah, so I think you need to both… you just need to do kind of what we did with you, just continue to say, like, dangle the fact that, like, hey, there are these infrastructure changes.

374 00:48:56.740 ⇒ 00:49:00.109 Uttam Kumaran: That we should make, based on our experience.

375 00:49:00.350 ⇒ 00:49:18.349 Uttam Kumaran: And here’s what that unlocks. And every time you meet with them, just keep bringing that up. And that’s something that we’ll put… I’ll put everything I’ve learned about Braze and the solution forward that I’ve sent… I just… I sent them an email about, in a Slack, in a Slack to Robert Cantor about. So we’ll summarize that in a slide, and that’ll just be there.

376 00:49:18.420 ⇒ 00:49:32.620 Uttam Kumaran: Second piece, and so that way you can have that conversation and really be like, I just want to make sure we’re all on the same page, that we’re not doing anything about this. Like, there’s literally email threads with all these passive people that are, like.

377 00:49:32.680 ⇒ 00:49:51.579 Uttam Kumaran: oh, don’t we need this? Blah blah blah. Like, I want us to address the fact that we could say, okay, we’re all okay on this call with not doing anything. That’s the decision. So that’s one thing, at least on the infra side. The second piece is, I think we’re going to continue to elevate Amber into a point where she can run the analysis.

378 00:49:51.650 ⇒ 00:49:57.900 Uttam Kumaran: Get our first draft at 60%, get a review, get the second draft at 90%, hand it to you.

379 00:49:58.060 ⇒ 00:50:00.320 Uttam Kumaran: And, like, that is, like, I think…

380 00:50:00.920 ⇒ 00:50:15.029 Uttam Kumaran: a great manufacturing pipeline of those insights. If she starts to nail it, then I can train one or two more people to start doing that as well, and basically start feeding you those things to drive those meetings. But I don’t know…

381 00:50:15.420 ⇒ 00:50:20.709 Uttam Kumaran: At this point, if… It can only be me and you in those calls, pushing.

382 00:50:20.820 ⇒ 00:50:23.009 Uttam Kumaran: But I think we wanna almost, like…

383 00:50:23.270 ⇒ 00:50:26.460 Uttam Kumaran: I think we… what we do… what we do with Javi is…

384 00:50:26.670 ⇒ 00:50:31.239 Uttam Kumaran: did too much infra and talked too much about infra, and… Yeah.

385 00:50:31.610 ⇒ 00:50:40.860 Uttam Kumaran: I think here, your job is to dangle the infra thing as more of, like, these are the foundations for us to run these analyses and run them

386 00:50:41.110 ⇒ 00:50:52.779 Uttam Kumaran: accurately and with all the data are hampered throughout these. This is not the star of the show, though. The analysis is the star of the show. So we’re going to continue to push these questions and ask these questions.

387 00:50:52.910 ⇒ 00:51:01.520 Uttam Kumaran: And I can hop on with Bertie, and Amber can, too, and then we’re just gonna try to give you, like, 3 or 4 pieces to drive those meetings.

388 00:51:02.020 ⇒ 00:51:12.309 Uttam Kumaran: like, if I was to say, like, how this… how we do this differently than Javi, then that’s the thing. That’s where we messed up, like, none of the junior folks on Javi

389 00:51:12.810 ⇒ 00:51:19.120 Uttam Kumaran: could have gone into those meetings and do it. Instead, our stakeholder kind of, like, didn’t know anything.

390 00:51:19.340 ⇒ 00:51:27.740 Uttam Kumaran: And, like, nothing kind of got done, we just said, like, we’re gonna wait. Instead, it’s like, we’re gonna just keep… we keep trying with what we have.

391 00:51:29.400 ⇒ 00:51:31.079 Uttam Kumaran: And at least that’s just a different…

392 00:51:31.750 ⇒ 00:51:34.260 Uttam Kumaran: We just… it’s just a different thing, you know?

393 00:51:34.980 ⇒ 00:51:40.740 Awaish Kumar: I think, like, we… Holistics does have some, like, revenue data in there.

394 00:51:41.920 ⇒ 00:51:43.569 Awaish Kumar: Maybe we can use…

395 00:51:43.570 ⇒ 00:51:47.049 Uttam Kumaran: Yeah, I asked… I asked them where… I asked them where’s the…

396 00:51:47.460 ⇒ 00:51:50.119 Uttam Kumaran: Where’s the data coming from? Blah blah blah, so…

397 00:51:50.120 ⇒ 00:51:56.190 Awaish Kumar: No, but, like, in Holistic itself, we have access to it. We have access to views and models.

398 00:51:56.860 ⇒ 00:51:57.970 Uttam Kumaran: No, I know, but what are you gonna do?

399 00:51:57.970 ⇒ 00:52:04.560 Robert Tseng: through every table in Holistics, I’ve mapped out everything in there, I’ve dumped it in a couple Notion docs, I know what’s in there.

400 00:52:04.710 ⇒ 00:52:16.680 Robert Tseng: Like, it’s all tr… it’s all aggregated transactions data. Yes, there’s revenue by all this stuff, but the problem is that there is no… like, we don’t need another product sales summary model. We need, like, a…

401 00:52:16.740 ⇒ 00:52:29.359 Robert Tseng: here’s a customer, how much they spent, their first purchase, like, it’s that, like, it’s that wide, flat customer table that doesn’t exist. There’s, like, nothing around that, and so we can’t do the segmentation that we want.

402 00:52:30.670 ⇒ 00:52:38.369 Robert Tseng: Yeah, I mean, it’s obviously easier said than done, but, like, you know, dim customers is what we’re missing. Like, that’s… that’s ultimately what we’re missing, yeah.

403 00:52:50.780 ⇒ 00:52:56.330 Uttam Kumaran: So, I mean, I’m pushing to ask him where’s… what is Holistic sitting on, and give us that, and so I’m just gonna keep pushing.

404 00:52:57.450 ⇒ 00:52:58.970 Uttam Kumaran: So, I’ll get there.

405 00:53:03.140 ⇒ 00:53:13.909 Uttam Kumaran: But again, this is where, like, I’m gonna… what we also want to dangle is anytime we’re blocked, I want to put that in an opportunity slide that says what we’re blocked on.

406 00:53:14.270 ⇒ 00:53:26.639 Uttam Kumaran: And then you just hammer that, and at least we die that way, you know? Yeah. I don’t want to die where we never push them to the point of saying, we are not doing anything about this.

407 00:53:26.860 ⇒ 00:53:43.930 Uttam Kumaran: like, I’m getting ghosted, blah… I want them to admit that that’s happening, and then candidly be like, okay, we’re hap- we’re okay with that happening. What I don’t want to do is that we sit in silence here and wait. So, we will continue to rack up all the things we can’t do, and just that’s…

408 00:53:44.500 ⇒ 00:53:52.689 Uttam Kumaran: Yeah, at least it’s a new way of trying this. These are just… it’s just bureaucratic people passive in this big-ass company that don’t care, and like…

409 00:53:53.270 ⇒ 00:53:58.260 Uttam Kumaran: Hopefully, the person that we’re working for cares, and has some clout, you know?

410 00:53:59.370 ⇒ 00:54:11.079 Robert Tseng: Yeah, I mean, things just kind of… the CMO getting fired was, like, that was not a great… that didn’t bode well for us, because she was kind of a big advocate of, like, what we were doing. So, now they’re kind of… whatever, it’s just…

411 00:54:11.770 ⇒ 00:54:27.019 Robert Tseng: well, I mean, it’s not… it’s not over, it’s not too late, or whatever. But yes, we’re… we’re kind of… this is what’s happening, we… yeah, we just have to keep hammering, like, we are blocked, we are blocked, we’re blocked, this is why it’s important, and just keep… just being… I mean, that… that’s… that’s all, you know…

412 00:54:27.140 ⇒ 00:54:35.110 Robert Tseng: We don’t need to do more on the engineering, like, it’s not, like, do more work on other sides, we just need to… we just need to keep telling them what, like, what we need, so…

413 00:54:37.460 ⇒ 00:54:38.160 Uttam Kumaran: Okay.

414 00:54:39.500 ⇒ 00:54:40.110 Robert Tseng: Okay.

415 00:54:40.110 ⇒ 00:54:50.340 Uttam Kumaran: I also want to give you, Robert, like, a demo of, like, okay, what is Mother Duck, blah blah blah, like, why a data warehouse, so we’ll… we’ll make sure all that is in the slide, easily accessible.

416 00:54:51.010 ⇒ 00:54:58.369 Robert Tseng: Yeah, I mean, I kind of want to even pull up my old Eden slides, like, just kind of, like, I don’t know, they might have been reworked over and over again, but, like…

417 00:54:59.350 ⇒ 00:55:06.529 Robert Tseng: I… yeah, we, like, before we did anything, we had it in a slide, and they were just looked at it, and they were like, alright, go for it. Like, it’s just like…

418 00:55:10.950 ⇒ 00:55:17.320 Robert Tseng: Strategy…

419 00:55:21.720 ⇒ 00:55:26.150 Robert Tseng: Like, if I might just… Hijack this, like…

420 00:55:27.470 ⇒ 00:55:41.789 Robert Tseng: Yeah, I mean, this was some of my early slides. Like, this was early on. They had no idea what the hell segment was, like, they had it. We were like… I was explaining to them, this is what your current segment situation looks like. Da-da-da-da-da-da-da, right? Like, this was a helpful slide.

421 00:55:41.980 ⇒ 00:55:59.630 Robert Tseng: you know, this was when we were evaluating whether or not they moved to Rudderstack or not. I mean, I guess this is already some ways in, when they were like, okay, well, what is the architecture? Like, we used to do this kind of stuff, oh yeah, like, early data tracking when I first got into Mixpanel, because that was the first project that I was doing on them. I redesigned their data design.

422 00:56:01.140 ⇒ 00:56:02.510 Robert Tseng: Sure.

423 00:56:08.320 ⇒ 00:56:13.440 Robert Tseng: I don’t know how to…

424 00:56:14.200 ⇒ 00:56:19.220 Robert Tseng: Go back to the chat from here, so… Team, try it.

425 00:56:19.220 ⇒ 00:56:19.890 Uttam Kumaran: I don’t know.

426 00:56:27.900 ⇒ 00:56:28.460 Robert Tseng: O.

427 00:56:33.140 ⇒ 00:56:46.630 Robert Tseng: like, this was early on when we did data platform documentation, like, we would, you know, we would do a little bit of work, and then show them, like, what was coming, and these were all talking points that I was able to go through. I, like, wrote out their objections, like, you know, just, like.

428 00:56:46.740 ⇒ 00:56:48.479 Robert Tseng: Yeah, like, I don’t know, this is…

429 00:56:49.470 ⇒ 00:56:56.070 Robert Tseng: there’s a whole history of, like, how we even push anything forward here, like, yeah, so…

430 00:56:56.370 ⇒ 00:57:03.519 Robert Tseng: This isn’t even the earliest one, I just picked, like, some random copy, like, I’m sure there were earlier ones, I just can’t find them right off the top of my head.

431 00:57:10.440 ⇒ 00:57:11.920 Robert Tseng: January.

432 00:57:13.530 ⇒ 00:57:17.099 Robert Tseng: Oh, yeah, this is, like, one of the early ones.

433 00:57:18.520 ⇒ 00:57:28.369 Robert Tseng: OKRs, segment overview, data modeling, yeah, we were telling them real versus MixedPanel, Mixed panel data strategy, answering questions about MixedPanel at the time.

434 00:57:28.580 ⇒ 00:57:44.799 Robert Tseng: Wesh did this early, like, designing, before we even built out any of the models. Actually, this was just, like, a copy from Javi. Yeah, we didn’t even build them a sample, we just showed them, like, these are the data marts that we’re gonna build, and we had a conversation about that.

435 00:57:45.010 ⇒ 00:57:54.910 Robert Tseng: Yeah, like, this was from… this is from January of this year. So, yeah, like, I… you know, the pattern here is, like.

436 00:57:55.060 ⇒ 00:58:10.549 Robert Tseng: I don’t feel like we’re… yeah, I mean, we’re not doing enough of this on the Insomnia side, where, yes, we have the questions of, like, opportunities, we have an opportunity slide, but each one of those opportunities should be its own slide with, like, a one sentence, like, this is what you’re gonna get.

437 00:58:10.550 ⇒ 00:58:15.080 Robert Tseng: Here’s, like, a random demo or some screenshot of, like, what this looks like.

438 00:58:15.080 ⇒ 00:58:21.979 Robert Tseng: And then, like, some benefits, and, like, that kind of is a talking point for when I’m jumping on more calls with them, so…

439 00:58:23.100 ⇒ 00:58:39.150 Robert Tseng: Yeah. I will say that just, like, they’re less available than Eden was. I think, like, Amrita is kind of annoying, she just only schedules, like, one or two days in advance, and now my schedule looks very different from January, so I can’t just, like, drop everything and answer calls, but .

440 00:58:39.150 ⇒ 00:58:46.309 Uttam Kumaran: No, but even if you can do a loom and send it to her, like, whatever we can get you, like, I don’t see a reason why we can’t have a running deck.

441 00:58:46.890 ⇒ 00:58:47.240 Robert Tseng: Yeah.

442 00:58:47.240 ⇒ 00:58:53.989 Uttam Kumaran: all the time that we keep updated. Yeah, yeah. I see no gap between that, so that’s what I’m gonna do here.

443 00:58:54.600 ⇒ 00:59:00.650 Robert Tseng: Yeah. Yeah, you’re right, the looms should be there. We should just be sending them a loom every week, at least, so…

444 00:59:04.250 ⇒ 00:59:04.830 Uttam Kumaran: Okay.

445 00:59:06.170 ⇒ 00:59:07.729 Robert Tseng: Okay, cool.

446 00:59:08.030 ⇒ 00:59:10.059 Robert Tseng: Yeah, this was, this was better.

447 00:59:10.060 ⇒ 00:59:14.509 Uttam Kumaran: I’m not as nervous there, because we are at least good… we have at least things we can try differently.

448 00:59:14.820 ⇒ 00:59:26.420 Uttam Kumaran: I’m now involved, so, like, it’s at least the engineering side, I’m just gonna make… you could just kind of, like… I’m gonna drive us towards some decisions or a non-decision, and then…

449 00:59:26.830 ⇒ 00:59:29.529 Uttam Kumaran: Yeah. Okay, so then let’s,

450 00:59:29.770 ⇒ 00:59:33.040 Uttam Kumaran: Let’s pivot slightly to talk about, Honeysinger.

451 00:59:33.770 ⇒ 00:59:34.390 Robert Tseng: Yeah.

452 00:59:35.530 ⇒ 00:59:42.909 Robert Tseng: I haven’t looked at anything from Byron, like, I don’t know if you want to kind of just catch me up on, like, where… what access we have, and then we can start to.

453 00:59:42.910 ⇒ 00:59:46.580 Uttam Kumaran: Sure, yeah, I have access to all of their core sources now.

454 00:59:46.890 ⇒ 00:59:50.680 Uttam Kumaran: And I’m just gonna kind of create a note. I’m gonna open up our…

455 00:59:52.080 ⇒ 00:59:56.609 Uttam Kumaran: Heidenstanger thing, and… I don’t know why there’s two of these…

456 00:59:59.380 ⇒ 01:00:03.899 Uttam Kumaran: Let’s just say honey stinger… Beautiful work.

457 01:00:09.970 ⇒ 01:00:23.139 Uttam Kumaran: So, I have access to, amazon, Walmart, Shopify, Fuck, mother stuff…

458 01:00:26.380 ⇒ 01:00:28.349 Uttam Kumaran: Klaviyo…

459 01:00:32.520 ⇒ 01:00:37.409 Uttam Kumaran: But we have everything. I think my questions for today is, one.

460 01:00:37.520 ⇒ 01:00:40.280 Uttam Kumaran: I actually also got,

461 01:00:42.470 ⇒ 01:00:44.440 Uttam Kumaran: I don’t know if I got… we don’t need it.

462 01:00:44.840 ⇒ 01:00:49.460 Uttam Kumaran: Did we… we’re not… we’re not doing anything on the ad side, right? Like, I don’t need to ask them about that?

463 01:00:51.130 ⇒ 01:00:52.230 Robert Tseng: Yeah, no ads.

464 01:00:52.950 ⇒ 01:00:55.380 Uttam Kumaran: Okay, so I have all the access.

465 01:00:55.610 ⇒ 01:01:01.960 Uttam Kumaran: I think another thing that… so, one is, like, we just need to land this somewhere.

466 01:01:02.420 ⇒ 01:01:06.479 Uttam Kumaran: So… In that sense, my first question is, like.

467 01:01:06.800 ⇒ 01:01:09.010 Uttam Kumaran: Are you okay with me just, like.

468 01:01:09.990 ⇒ 01:01:15.610 Uttam Kumaran: Setting up Polyatomic, driving all this data somewhere so it could be queried.

469 01:01:16.810 ⇒ 01:01:18.310 Robert Tseng: Yeah, I think that, that works.

470 01:01:19.230 ⇒ 01:01:24.550 Uttam Kumaran: Okay, can we land data somewhere so it can be queried?

471 01:01:28.830 ⇒ 01:01:30.360 Uttam Kumaran: Answer is yes.

472 01:01:30.580 ⇒ 01:01:35.129 Uttam Kumaran: Next question is… I don’t think…

473 01:01:35.970 ⇒ 01:01:41.760 Uttam Kumaran: I guess, does that… Henry, do you have any experience in, like, Klaviyo?

474 01:01:42.760 ⇒ 01:01:44.840 Henry Zhao: Yeah, I do, I’ve worked with Klaviyo before.

475 01:01:45.300 ⇒ 01:01:45.980 Henry Zhao: Many years.

476 01:01:47.470 ⇒ 01:01:52.170 Uttam Kumaran: Like, in this situation, like, kind of, like, what we’re trying to…

477 01:01:52.450 ⇒ 01:01:55.289 Uttam Kumaran: What we’re basically trying to do is help them…

478 01:01:56.050 ⇒ 01:02:08.390 Uttam Kumaran: build, like, better Klaviyo segments. Like, we want to stitch together… so there’s a… the data challenge here is, like, we need to stitch together customers across these sources.

479 01:02:08.560 ⇒ 01:02:14.120 Uttam Kumaran: And help build better segments in… in Klaviyo.

480 01:02:15.780 ⇒ 01:02:21.950 Uttam Kumaran: So, to kind of start from the beginning, the first part is, like, I need to land customer and transaction lists

481 01:02:22.060 ⇒ 01:02:27.940 Uttam Kumaran: into a simple warehouse. So I’ll go ahead and shove that into,

482 01:02:28.120 ⇒ 01:02:32.879 Uttam Kumaran: Mother Duck, and I’ll get Polycomic to spin us up a free

483 01:02:33.170 ⇒ 01:02:36.269 Uttam Kumaran: I’ll get Polyatomic to give us a trial.

484 01:02:36.390 ⇒ 01:02:40.909 Uttam Kumaran: The second piece is we’re gonna… I guess, can you talk to me about, like.

485 01:02:41.590 ⇒ 01:02:47.970 Uttam Kumaran: how this works in the next step, which is… if you look on the right, if I could just, like, highlight this, one is…

486 01:02:49.010 ⇒ 01:02:53.400 Uttam Kumaran: they just have very disparate customer lists.

487 01:02:54.180 ⇒ 01:02:59.869 Uttam Kumaran: Second, we need to have some model of, like, a clear, dim customers with, like.

488 01:03:00.040 ⇒ 01:03:06.900 Uttam Kumaran: all the different IDs from the other platforms that we can then send to into Klaviyo.

489 01:03:10.040 ⇒ 01:03:25.119 Uttam Kumaran: And then, again, once we have that, there’s a couple of different areas we can go to, like, do more insights, discover things about buying patterns and things like that. But talk to me about, like, the work you’ve done in Klaviyo before, and, like, kind of, like, hearing that, like, what this kind of sounds like.

490 01:03:26.060 ⇒ 01:03:37.170 Henry Zhao: Yeah, I’ve never done, like, any setting up segments in Klaviyo before, I’ve only helped email marketers do that, but, like, I’ve helped analyze the data in Klaviyo, like, A-B testing and kind of how email campaigns are performing.

491 01:03:37.800 ⇒ 01:03:47.380 Henry Zhao: I’m sure we could figure that out with, like, the Klaviyo API, like, we could send data in and out, we can analyze the segments, and we can help them build the correct workflows.

492 01:03:47.380 ⇒ 01:03:48.040 Robert Tseng: Okay.

493 01:03:48.290 ⇒ 01:03:51.140 Robert Tseng: Yeah, so I want to align on a couple things here. So…

494 01:03:51.140 ⇒ 01:03:51.510 Uttam Kumaran: Sure.

495 01:03:51.510 ⇒ 01:04:04.089 Robert Tseng: through BFCM, like, we’re not doing foundational playvale setup. We will not… we do not have to set up any segments. They have someone who’s basically building out their flows, basic segments, basic deliverability.

496 01:04:04.110 ⇒ 01:04:20.899 Robert Tseng: But I think the reporting side will be helpful. So we have access to read-only Klaviyo, we have the data access, and so to not step on their toes, we just kind of have the… we just built some benchmark reporting on Klaviyo performance, right? So, that’s all we need to do in Klaviyo.

497 01:04:20.980 ⇒ 01:04:35.719 Robert Tseng: Then, from now through December, what we need to do that’s more urgent is the cross-channel data pipeline. So, landing all the data, the Amazon OneP stuff, the Walmart, Shopify, into a warehouse, and then doing some identity

498 01:04:35.720 ⇒ 01:04:52.130 Robert Tseng: starting to do, like, do some light identity stitching. So, like, being able to have, like, a model that’s like, this is the same customer who came to Amazon, who then went to Shopify, or whatever. Like, if you could just match on emails and let them know.

499 01:04:52.130 ⇒ 01:05:06.789 Robert Tseng: 20% of your email, of your customer base, has, like, been in multiple marketplaces or whatever. Like, that’s, like, a level one omni-channel analysis, just to get… communicate the overlap in their customers across channels.

500 01:05:06.790 ⇒ 01:05:18.329 Robert Tseng: Because right now, they can log into each of those tools, and then count up the number of customers, and that’s how many customers they think they have. Obviously, there must be some overlap, and so they don’t even really know what that looks like yet.

501 01:05:18.330 ⇒ 01:05:26.819 Robert Tseng: But that’s… that’s kind of the scope that we’re really trying to tackle. Like, what is… what is, like, yeah, doing some omnichannel analysis there.

502 01:05:27.370 ⇒ 01:05:46.059 Robert Tseng: from there, we’ll be able to see, like, I think you’ll be able to… we’ll be able to have… make some… we’ll be able to outline, okay, these are, from a data perspective, these are the different strategies to grow in these different marketplaces. With Shopify, you know, it’s like a different set than

503 01:05:46.060 ⇒ 01:06:02.929 Robert Tseng: that Amazon, for Amazon, you could just turn on subscribe and save. From other clients we’ve worked up with, when you do subscribe and save, you know, 10% of your customers go into that, the price per or… the order value drops, but then they’re able… their LTV increases by whatever percent. Like, that would be a, like, a nugget that you would share with them.

504 01:06:02.930 ⇒ 01:06:08.630 Robert Tseng: With Shopify, it’s like, well, you have to… you have to… you have to beat them on price. You know, Amazon.

505 01:06:08.660 ⇒ 01:06:20.220 Robert Tseng: whatever, like, the whole customer experience in Amazon is a lot more pleasant, and so customers will only really buy from Shopify if you’re trying to drive more sales that way, if you’re able to beat Amazon on price.

506 01:06:20.220 ⇒ 01:06:28.730 Robert Tseng: But, you know, yeah, so I’m just… I’m just, like, articulating, like, these are kind of some of the different directions that we… that we start to go in to be able to

507 01:06:28.730 ⇒ 01:06:35.500 Robert Tseng: Have, like, some, like, the recommendations that we’re having on what they can do with each of these channels.

508 01:06:36.730 ⇒ 01:06:47.159 Robert Tseng: And then, like, the next phase after that is, like, okay, well, then, like, now we take action. Like, we actually want to drive people from one marketplace to another.

509 01:06:47.200 ⇒ 01:06:53.170 Robert Tseng: And that’s where you will need to be able to… to have email enrichment, and be like.

510 01:06:53.180 ⇒ 01:07:08.750 Robert Tseng: okay, like, I’m gonna email this Amazon customer and, you know, tell them to go into… go purchase from Shopify, or whatever. Like, the… and that’s kind of where you’re going to maybe even to ideate on some of those initial, like, cross… cross-platform, like, segments.

511 01:07:08.750 ⇒ 01:07:15.660 Robert Tseng: Everything else after that is, like, you know, January onwards, which we can kind of strategize, like, on the fly.

512 01:07:15.660 ⇒ 01:07:25.270 Robert Tseng: But there’s nothing about attribution that we need to worry about. It’s purely just understanding, customer data within each of these… within each of these marketplaces.

513 01:07:25.270 ⇒ 01:07:37.090 Robert Tseng: doing some light initial modeling on, like, any, like, cross-marketplace, like, stitching that we can do, which we know can be done. We’ve done a project stitching Shopify and Amazon.

514 01:07:37.100 ⇒ 01:07:38.720 Robert Tseng: That was, you know.

515 01:07:38.720 ⇒ 01:07:40.350 Henry Zhao: by email? Do we just touch by email?

516 01:07:41.080 ⇒ 01:07:44.879 Robert Tseng: Not… it wasn’t just purely by email, like, I think whatever…

517 01:07:44.900 ⇒ 01:07:49.160 Uttam Kumaran: Yeah, Pius’s old Python script. There was, like, some…

518 01:07:49.160 ⇒ 01:07:51.870 Robert Tseng: Probabilistic, kind of, like, matching off of.

519 01:07:51.970 ⇒ 01:07:53.420 Henry Zhao: Cool. Yeah.

520 01:07:53.420 ⇒ 01:08:12.350 Robert Tseng: even if you don’t have, email, you have IP address, and you have zip, and then, like, they purchased the same item one month apart from each other, so you can assume that this was the same… this was the same customer. Or, like, you know, there’s, like, some… there were some, like, assumptive, like, leaps like that, but, yeah.

521 01:08:13.740 ⇒ 01:08:19.420 Henry Zhao: What are the different marketplaces, besides the website, obviously, and Walmart and Amazon?

522 01:08:20.399 ⇒ 01:08:23.579 Robert Tseng: It’s Walmart and Amazon and their website, that’s it. Yeah.

523 01:08:23.580 ⇒ 01:08:24.450 Henry Zhao: Okay, and Walmart is the.

524 01:08:24.450 ⇒ 01:08:30.560 Robert Tseng: I don’t know if… I don’t know if they gave us access to their other B2B stuff, but I’m assuming it’s just those three.

525 01:08:31.700 ⇒ 01:08:34.859 Henry Zhao: Walmart, are you talking about, like, Walmart.com or Walmart, like, physical stores?

526 01:08:35.290 ⇒ 01:08:36.330 Robert Tseng: Both.

527 01:08:36.979 ⇒ 01:08:41.199 Henry Zhao: Because I wouldn’t know how to stitch, like, real life stores. I’ve never done any of that before. I don’t know if that’s…

528 01:08:41.200 ⇒ 01:08:45.060 Uttam Kumaran: Yeah. No, no, this is not all on you, by the way. We’re just talking. We haven’t done a

529 01:08:45.759 ⇒ 01:08:46.239 Uttam Kumaran: Man.

530 01:08:46.240 ⇒ 01:08:48.059 Henry Zhao: I’m also just, like, spitballing, yeah.

531 01:08:48.620 ⇒ 01:08:52.160 Robert Tseng: Yeah, yeah, I… Amazon is their baby.

532 01:08:52.160 ⇒ 01:08:52.909 Uttam Kumaran: That’s mine, so I think.

533 01:08:52.920 ⇒ 01:08:53.600 Robert Tseng: Yeah.

534 01:08:53.609 ⇒ 01:08:56.469 Uttam Kumaran: You should rewatch my meeting with Byron.

535 01:08:56.629 ⇒ 01:09:01.369 Uttam Kumaran: has a lot of stuff we talked about initially on, like, sources. He gave me a bunch of things.

536 01:09:01.439 ⇒ 01:09:20.069 Uttam Kumaran: But we’ll start. As soon as we start producing something, he’ll be like, oh, you guys have this? No, okay, I’ll give you access, so… Okay, so this makes sense. I think we have… there’s some obvious things to do on channel-by-channel analysis and doing the omni-channel. I guess, Henry, tell me about, like, what are the Klaviyo-type analyses that we could

537 01:09:20.179 ⇒ 01:09:25.409 Uttam Kumaran: do, like… I guess, frame it from, like, a question perspective, like, if we were gonna…

538 01:09:25.939 ⇒ 01:09:33.759 Uttam Kumaran: Propose to answer some questions about… email, Like, what would we…

539 01:09:33.760 ⇒ 01:09:40.439 Henry Zhao: I mean, there’s not a lot, there’s really just A-B testing, and there’s, like, opens, unsubscribes, clicks.

540 01:09:40.810 ⇒ 01:09:43.589 Henry Zhao: It’s pretty… pretty limited. Pretty straightforward.

541 01:09:43.890 ⇒ 01:09:48.770 Uttam Kumaran: Yeah, but, like, you can do testing on, like, what subject lines perform, what.

542 01:09:48.779 ⇒ 01:09:50.509 Henry Zhao: Yeah. Like, what subject lines?

543 01:09:51.039 ⇒ 01:09:51.829 Henry Zhao: Yeah, like…

544 01:09:51.830 ⇒ 01:09:54.620 Uttam Kumaran: Tell me what those are, yeah, I guess that’s… or…

545 01:09:54.620 ⇒ 01:10:00.710 Henry Zhao: Yeah, so, like, A-B testing, you could test, like, subject lines, you could test, like, do you have a lot of content, or do you have a lot more images?

546 01:10:01.160 ⇒ 01:10:03.420 Henry Zhao: You could test,

547 01:10:03.720 ⇒ 01:10:07.310 Henry Zhao: I mean, I don’t believe in the stuff of, like, what color button do you press, but, like.

548 01:10:07.450 ⇒ 01:10:09.190 Henry Zhao: We’ve done testing of, like.

549 01:10:10.200 ⇒ 01:10:17.980 Henry Zhao: very, like, informative emails versus, like, more edgy emails, right? Like, don’t click here if you don’t want a discount, stuff like that.

550 01:10:19.130 ⇒ 01:10:22.929 Henry Zhao: But yeah, it’s almost all along those lines. Subject, content.

551 01:10:23.640 ⇒ 01:10:28.579 Uttam Kumaran: Part of this is, like, we want to do a back… we want to do a back analysis.

552 01:10:28.800 ⇒ 01:10:32.349 Uttam Kumaran: We will have all their Klaviyo data, and we just need to be like.

553 01:10:32.710 ⇒ 01:10:34.750 Uttam Kumaran: Here are, like, things that we found.

554 01:10:35.050 ⇒ 01:10:41.469 Uttam Kumaran: So, I think these are the factors that I have, right? So, like, kind of, like, subject line.

555 01:10:41.590 ⇒ 01:10:44.399 Henry Zhao: Images, images, I would say, like, rich…

556 01:10:44.630 ⇒ 01:10:47.400 Uttam Kumaran: Whatever, rich content, body…

557 01:10:47.400 ⇒ 01:10:47.870 Henry Zhao: body.

558 01:10:47.870 ⇒ 01:10:52.460 Uttam Kumaran: Offers, colors, time, geo… Yeah, frequency.

559 01:10:52.460 ⇒ 01:10:58.560 Henry Zhao: I would say frequency. I would say frequency, like, do we want to email them once a week, or is, like, 3 times a day too much?

560 01:10:58.680 ⇒ 01:11:04.699 Henry Zhao: And then also, I would say, call to action, right? So, is it, like, an informative email, or is it, like, buy now?

561 01:11:05.210 ⇒ 01:11:08.790 Henry Zhao: Yeah, those… I think those are pretty much it.

562 01:11:09.840 ⇒ 01:11:10.390 Uttam Kumaran: Okay.

563 01:11:11.790 ⇒ 01:11:13.400 Uttam Kumaran: So, there’s partly, like.

564 01:11:14.140 ⇒ 01:11:20.149 Uttam Kumaran: And I guess what I want to press on here is that we don’t just share, oh, your open rate is this, because he can get that from the UI.

565 01:11:20.730 ⇒ 01:11:21.110 Henry Zhao: Right, yeah.

566 01:11:21.110 ⇒ 01:11:36.450 Uttam Kumaran: So, a couple of ways that we could do this that I feel like… I used to do a bunch of email analysis, too. One thing that is new, given we have AI, is you can actually have AI take an email and give you structured outputs.

567 01:11:36.590 ⇒ 01:11:37.420 Uttam Kumaran: like…

568 01:11:37.980 ⇒ 01:11:47.579 Uttam Kumaran: so you can, instead of saying, like, did an email contain a word, you can say, hey, I want AI to go through every email and map it to, like.

569 01:11:47.780 ⇒ 01:11:54.139 Uttam Kumaran: urgent, non-urgent, right? You can think about descriptive factors about the email, right? Yeah.

570 01:11:54.770 ⇒ 01:12:07.939 Henry Zhao: Yeah, and it’d be cool, like, if every campaign they run, like, they send to, like, a Brainforge at AI email that, like, AI would then categorize each campaign into the things that we want to analyze, right? So, like, this campaign is this type of subject line, this type of content, this type of.

571 01:12:07.940 ⇒ 01:12:19.059 Uttam Kumaran: I guess, like, yeah, this is exactly something that we can do, given, like, AI exists, is we’ll use, like, a mini model, and this is where, like, what… when you design this analysis.

572 01:12:19.310 ⇒ 01:12:25.760 Uttam Kumaran: what I’ll be expecting is, yes, you define all these factors, and you define what structured outputs you need from AI.

573 01:12:25.920 ⇒ 01:12:26.960 Henry Zhao: Like… Okay.

574 01:12:26.960 ⇒ 01:12:39.020 Uttam Kumaran: if you want to do, for example, you want to do an analysis on subject line, right? Let’s take subject line, for example. And, like, let’s… let’s even, like, I mean, my, my, my personal email is probably a better sense of, like.

575 01:12:39.660 ⇒ 01:12:43.569 Uttam Kumaran: Random, let’s go to, like, like, shopping.

576 01:12:44.360 ⇒ 01:12:47.309 Uttam Kumaran: Right? Let’s look at, like, all of these.

577 01:12:47.890 ⇒ 01:12:55.240 Uttam Kumaran: Alright, so let’s… let’s take an example, like, if you were looking at some of these, what are some, like, subject line

578 01:12:55.720 ⇒ 01:13:05.359 Uttam Kumaran: what AI is doing is taking this and then giving you a structured output, whether that’s, like, short, long, urgent, non-urgent, you know, like, so…

579 01:13:06.320 ⇒ 01:13:23.820 Uttam Kumaran: Well, that’s kind of, like, what I’m trying to get at, is, like, we need to give AI some specific structure outputs to map… to map towards, to take long-form text, short-form text, and for example, say, like, this is a… this is a certain type, or this is another type. That’s what I would suggest doing.

580 01:13:24.450 ⇒ 01:13:38.050 Henry Zhao: And speaking outside of, I think this is also something that we could develop as a case study and sell to other clients. I think a lot of people just look at marketing performance by, like, campaign and spend, but they don’t realize that they need to, like, analyze their creative a little bit deeper, or, like.

581 01:13:38.350 ⇒ 01:13:40.969 Henry Zhao: Dig deeper into, like, what emails they’re actually sending.

582 01:13:41.240 ⇒ 01:13:41.799 Henry Zhao: Because that’s what

583 01:13:42.140 ⇒ 01:13:57.569 Henry Zhao: Because, like, I get a lot of emails that are like, these are well-timed, but the content’s just not interesting to me, and some marketers, they’re, like, just thinking about, like, not even, like, what they’re writing, but just, like, these other things that they’re analyzing in terms of their data, and they just need to take it one step further, and I think our AI could do things like that.

584 01:13:59.150 ⇒ 01:14:08.909 Robert Tseng: Yeah, I mean, this is… this would be helpful for Insomnia, too. Yeah, I mean, the fact… Get in, too. We should… we should set up, like, a… like a Brainforge email that’s, like.

585 01:14:09.100 ⇒ 01:14:16.880 Robert Tseng: that’s just getting emails from all of the competitors from our existing clients. That’d be a great way to, like, benchmark

586 01:14:17.110 ⇒ 01:14:32.809 Robert Tseng: that’s not using, like, random aggregations that were… that are from Klaviyo or Braze, but we’re actually just, like, analyzing their competitors’ emails and using that to, like, kind of guide, like, the… the insights that we’re giving them, too. That’s… that’s a great idea.

587 01:14:32.810 ⇒ 01:14:41.330 Henry Zhao: And this is how we set ourselves apart from the competition, because all the competition, like you said, Utam, is just looking at open rates, unsubscribe rates, and that’s as far as they’re taking it, I feel like.

588 01:14:41.330 ⇒ 01:14:48.570 Uttam Kumaran: Yeah, and like, even frequency and, long versus short, like, those are things you can do with structured data.

589 01:14:49.120 ⇒ 01:14:55.230 Uttam Kumaran: Does this contain an email or not? Image or not? Is there a link or not?

590 01:14:55.400 ⇒ 01:15:03.449 Uttam Kumaran: But what is really not possible, except until now, is to actually pass in the entire email

591 01:15:04.460 ⇒ 01:15:15.920 Uttam Kumaran: Like, and basically get a deeper, like, more nuanced understanding of the email, including the time it was sent, the subject, the body, who it was sent to, right?

592 01:15:16.120 ⇒ 01:15:21.679 Uttam Kumaran: And so it’s all stuff that we should consider. So, like, kind of my expectation here

593 01:15:22.110 ⇒ 01:15:27.069 Uttam Kumaran: And, you know, if I was you, like, how I would structure this is, one, I would…

594 01:15:27.430 ⇒ 01:15:38.870 Uttam Kumaran: I would create an outline, start it on, like, without any AI, we should at least analyze these things. The second thing you could totally do is you take this transcript segment of this conversation we just had.

595 01:15:39.030 ⇒ 01:15:53.940 Uttam Kumaran: you put that into AI, you put that into, like, our solution architect AI, you put in this notion as well, and you say, I’m thinking about structuring an analysis that takes advantage of the fact that we have AI to implement a great, like.

596 01:15:54.060 ⇒ 01:15:56.299 Uttam Kumaran: analysis of Klaviyo information.

597 01:15:56.520 ⇒ 01:16:14.860 Uttam Kumaran: In our transcript, we’re talking about using mini-LLMs to achieve a more nuanced understanding of the email, to implement some more back analysis. What are certain things, if you had access to a model and you could pipe in the email into, would you look to test? It’ll give you the answers.

598 01:16:14.960 ⇒ 01:16:17.730 Uttam Kumaran: Okay. That’s what I would do first.

599 01:16:18.330 ⇒ 01:16:22.100 Uttam Kumaran: Then add yours… add your brain to it.

600 01:16:22.580 ⇒ 01:16:23.230 Henry Zhao: Okay.

601 01:16:23.790 ⇒ 01:16:24.840 Henry Zhao: That makes sense.

602 01:16:26.020 ⇒ 01:16:32.789 Uttam Kumaran: Okay, so I think we at least… we have a couple of ideas here. I think…

603 01:16:32.890 ⇒ 01:16:35.230 Uttam Kumaran: This, I’m very comfortable with.

604 01:16:35.550 ⇒ 01:16:36.320 Uttam Kumaran: What?

605 01:16:37.000 ⇒ 01:16:51.210 Robert Tseng: No, no, I love it, I love it, this is great. This is… we sold Honey Stinger on a AI, powered lifecycle sprint, and we’re, like, inventing it as we’re, like, meeting, which is fantastic, yeah.

606 01:16:51.210 ⇒ 01:16:57.080 Uttam Kumaran: This is just part of… this is part of discovery. But also, like, I’m telling you, nobody is…

607 01:16:57.260 ⇒ 01:17:10.740 Uttam Kumaran: I did… I did email analysis, like, my whole career, like, nope, I never… you’re never able to test beyond factors that are structured data, except until now, and what this… this we would… yeah, we could do in an afternoon, so…

608 01:17:10.930 ⇒ 01:17:28.900 Uttam Kumaran: I think the biggest thing is, like, we have a bunch of stuff around Klaviyo, which we should just bang out. This will show that we’re much better than whatever the other guy’s doing, anyways. Second is, we have our standard channel-by-channel analysis. This is something that we can decide who on the team

609 01:17:29.250 ⇒ 01:17:30.830 Uttam Kumaran: Wants to take this.

610 01:17:32.520 ⇒ 01:17:41.609 Uttam Kumaran: And then, yeah, again, very similarly, we have a Friday… we have Fridays booked with Byron, where I want to sort of just, like.

611 01:17:42.830 ⇒ 01:17:46.220 Uttam Kumaran: We have an ongoing deck that we sort of show what we’re doing.

612 01:17:46.410 ⇒ 01:17:51.259 Uttam Kumaran: So this… so this Friday, when I meet with him, I’m basically gonna show him landed data.

613 01:17:51.620 ⇒ 01:18:01.589 Uttam Kumaran: and sort of, like, a couple of… I want to at least show him an outline of an Klaviyo analysis that we’re going for that is going to be a little bit AI-driven.

614 01:18:01.740 ⇒ 01:18:08.510 Uttam Kumaran: And so, Henry, I think that will be the task for this week, is if you can work on… you can use our analysis outline.

615 01:18:08.900 ⇒ 01:18:17.770 Uttam Kumaran: and just write there what we talked about around these Klaviyo analyses that we want to do, I can present to him and get into

616 01:18:18.040 ⇒ 01:18:22.499 Uttam Kumaran: Both get excited about him, and give me a sense of what he already knows.

617 01:18:22.730 ⇒ 01:18:23.750 Uttam Kumaran: Okay.

618 01:18:23.860 ⇒ 01:18:28.850 Uttam Kumaran: So that next week, we’ll basically run towards a couple of these.

619 01:18:29.480 ⇒ 01:18:30.190 Henry Zhao: Okay.

620 01:18:31.680 ⇒ 01:18:37.360 Uttam Kumaran: Okay, I feel like otherwise this is, like, a pretty chill client. I messaged Polyatomic about getting us

621 01:18:38.250 ⇒ 01:18:45.939 Uttam Kumaran: whatever for these guys, so it should be fine. Yeah, what else? That’s it?

622 01:18:49.130 ⇒ 01:18:50.030 Robert Tseng: Woohoo!

623 01:18:51.040 ⇒ 01:18:51.900 Uttam Kumaran: Not bad.

624 01:18:51.900 ⇒ 01:18:52.570 Awaish Kumar: Yeah.

625 01:18:54.430 ⇒ 01:19:03.499 Robert Tseng: This is good. I, I, I enjoyed, I enjoyed this conversation. I, I, yeah, this is a great, great idea on the email stuff. This is, this is, this is good.

626 01:19:03.630 ⇒ 01:19:18.569 Robert Tseng: Yeah, this is what I want to do. I want to talk about, like, we’re gonna dump out everything that we know about analysis, and then we just kind of pick apart our own ideas and figure out how we can use AI to, like, kind of make it better, and I mean, this is… this is the stuff. Like, this is what… this is… this is why this is…

627 01:19:18.570 ⇒ 01:19:25.500 Uttam Kumaran: Yeah, like, this is what I would prefer to even use our stand-up. The only reason I’m using stand-ups is because things are falling through the cracks, so…

628 01:19:25.700 ⇒ 01:19:39.589 Uttam Kumaran: Like, I am… I will throw out everything if we just have these right processes, so I feel like this week we did a good job on, like, at least getting in line on these three clients. Next week, I would like for us to think about urban stems.

629 01:19:41.750 ⇒ 01:19:51.079 Uttam Kumaran: like, who else do we work for? I would like us to think about Urban Stems, I would like us to think about README, I would like us to think about Ellie.

630 01:19:51.350 ⇒ 01:20:02.389 Uttam Kumaran: Yeah. And at least… and if we can’t use this time, we will continue to build out roadmaps, or kind of use it similarly in our services-type discussion about

631 01:20:02.660 ⇒ 01:20:07.999 Uttam Kumaran: okay, like, just wrapping up this work. So I think if we’re okay with, like, having kind of this standing time.

632 01:20:08.550 ⇒ 01:20:12.519 Uttam Kumaran: This is a great… Thing that we should just do each week.

633 01:20:13.030 ⇒ 01:20:22.140 Uttam Kumaran: it at least buys us two… my goal is to buy us two weeks of work, you know, and a North Star that we can present on, so we’ve got that today for all three of these.

634 01:20:25.730 ⇒ 01:20:26.400 Uttam Kumaran: Okay.

635 01:20:26.740 ⇒ 01:20:27.940 Robert Tseng: Okay.

636 01:20:29.690 ⇒ 01:20:35.760 Uttam Kumaran: Great, alright, I’ll send some updates to Slack, and then I’ll… I’ll sort of just, like, we can start moving on.

637 01:20:35.890 ⇒ 01:20:41.529 Uttam Kumaran: Honey Stinger, Insomnia, some stuff on Amber’s side, and Eden we’ll talk about in the morning.

638 01:20:42.660 ⇒ 01:20:47.790 Uttam Kumaran: When do you present a… when are you meeting with any of these folks, Robert? I guess Eden and,

639 01:20:48.060 ⇒ 01:20:49.160 Uttam Kumaran: Insomnia.

640 01:20:49.790 ⇒ 01:20:52.470 Robert Tseng: Insomnia will be Friday, and you should…

641 01:20:53.560 ⇒ 01:20:53.970 Uttam Kumaran: They’re off.

642 01:20:53.970 ⇒ 01:20:55.120 Robert Tseng: Book time with me.

643 01:20:55.860 ⇒ 01:21:03.390 Robert Tseng: Yeah, well, Amrita’s not off on Fridays, or it’s a good time to book them, because some people still work. Yeah.

644 01:21:05.360 ⇒ 01:21:06.320 Uttam Kumaran: Okay, then I’m just gonna.

645 01:21:06.320 ⇒ 01:21:07.320 Robert Tseng: I’m just gonna say.

646 01:21:07.920 ⇒ 01:21:14.839 Uttam Kumaran: I’m gonna put a placeholder on my calendar that is, like, insomnia meeting. And then, when are you meeting with Eden? On next Wednesday?

647 01:21:15.420 ⇒ 01:21:17.030 Robert Tseng: Yeah, next Wednesday.

648 01:21:30.150 ⇒ 01:21:36.199 Henry Zhao: Yeah, so Wish, if you could fill in that Notion doc for the polyatomic stuff that you worked on, I think those could feed the slides for Friday.

649 01:21:38.430 ⇒ 01:21:42.140 Uttam Kumaran: If you want to just add the part that you did with, Zaron’s new solution.

650 01:21:43.220 ⇒ 01:21:43.950 Awaish Kumar: Yeah.

651 01:21:44.270 ⇒ 01:21:47.189 Awaish Kumar: Yeah, that’s not point of it, but yeah, I will add.

652 01:21:47.610 ⇒ 01:21:49.400 Henry Zhao: Okay, let me know if you need the link.

653 01:21:50.070 ⇒ 01:21:53.100 Uttam Kumaran: Yeah, so on Friday, we can at least do a first pass of a deck.

654 01:21:53.730 ⇒ 01:21:57.440 Uttam Kumaran: And then, that way, it’ll get somewhere polished by Wednesday.

655 01:21:57.780 ⇒ 01:22:00.780 Henry Zhao: Yeah, you can give your final update, Robert, on, Catalyst stuff.

656 01:22:01.140 ⇒ 01:22:03.059 Henry Zhao: Oh, sorry, I said polytopic, but I meant catalyst.

657 01:22:03.060 ⇒ 01:22:09.470 Uttam Kumaran: Don’t… don’t say that too many times. It’s not gonna happen.

658 01:22:09.610 ⇒ 01:22:12.530 Uttam Kumaran: Okay, alright, great. Thank you.

659 01:22:12.530 ⇒ 01:22:17.929 Henry Zhao: And I guess the other thing, Robert, would be to present on, like, our Northbeam slash wicked slash attribution.app analysis, right?

660 01:22:18.540 ⇒ 01:22:25.510 Robert Tseng: Yeah, I didn’t… I didn’t show up to the North Beam one, so I haven’t connected with, with Zoran, but I’ll talk to him tomorrow morning, we’ll send it out.

661 01:22:25.860 ⇒ 01:22:28.630 Henry Zhao: Okay, and then by Friday, we should also be able to discuss, yeah.

662 01:22:29.000 ⇒ 01:22:36.160 Uttam Kumaran: I’m gonna create an outline for the deck, even if it’s just, like, throw-in slides of what you want to do, that’ll be a great place for us to start.

663 01:22:37.540 ⇒ 01:22:41.769 Uttam Kumaran: And you could just put in ideas of, like, slides we should make and have ready.

664 01:22:42.900 ⇒ 01:22:43.540 Robert Tseng: Okay.

665 01:22:44.480 ⇒ 01:22:53.839 Henry Zhao: And Robert, before our one-on-one tomorrow, I’ll have the Mixed panel project plan ready also, so we can discuss that if you want to present that to leadership. Because I think it really is just about training and getting people to use it.

666 01:22:54.300 ⇒ 01:22:54.890 Robert Tseng: Yeah.

667 01:22:56.300 ⇒ 01:23:02.360 Henry Zhao: And then if anything’s missing, they can just ticket it, right? Like, and then we can do the prioritization we talked about on whether we want to do it or not.

668 01:23:04.330 ⇒ 01:23:04.920 Robert Tseng: Yep.

669 01:23:06.430 ⇒ 01:23:07.330 Robert Tseng: Alright.

670 01:23:07.570 ⇒ 01:23:08.230 Robert Tseng: Thanks, guys.

671 01:23:08.950 ⇒ 01:23:09.720 Uttam Kumaran: Thank you.

672 01:23:10.320 ⇒ 01:23:11.420 Henry Zhao: Alright, bye guys.