2025-11-25_brainforge_x_lmnt_firsy_week_planning_2a068e9b

Meeting Title: Brainforge x LMNT: Firsy Week Planning Date: 2025-11-25 Meeting participants: Uttam Kumaran, Shivani Amar, Awaish Kumar

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WEBVTT

1 00:04:34.880 ⇒ 00:04:39.279 Shivani Amar: Hey guys, I’m gonna be camera off for this meeting because I’m a little sick.

2 00:04:40.110 ⇒ 00:04:45.029 Uttam Kumaran: Hey, no problem. I’m just at the library, so I was also gonna be…

3 00:04:45.180 ⇒ 00:04:47.249 Uttam Kumaran: Off, there’s some background movement.

4 00:04:49.900 ⇒ 00:04:51.090 Uttam Kumaran: How’s everything?

5 00:04:52.400 ⇒ 00:04:54.450 Shivani Amar: It’s okay. How are you doing?

6 00:04:55.080 ⇒ 00:04:55.850 Uttam Kumaran: Good!

7 00:04:57.550 ⇒ 00:04:59.149 Uttam Kumaran: Sorry about the sickness.

8 00:05:00.640 ⇒ 00:05:01.450 Shivani Amar: You?

9 00:05:01.750 ⇒ 00:05:04.369 Shivani Amar: Hi, Awish, is that how you’d pronounce the name?

10 00:05:04.890 ⇒ 00:05:06.320 Awaish Kumar: Yup, hello.

11 00:05:07.370 ⇒ 00:05:08.050 Shivani Amar: Cool.

12 00:05:08.240 ⇒ 00:05:09.460 Shivani Amar: Nice to meet you.

13 00:05:12.010 ⇒ 00:05:14.669 Uttam Kumaran: Yeah, so maybe today I just wanted to…

14 00:05:14.910 ⇒ 00:05:22.280 Uttam Kumaran: Talk a little bit about plans for next week, and then, of course, introduce Awash. Wanted to walk through our…

15 00:05:22.410 ⇒ 00:05:29.689 Uttam Kumaran: Gantt chart, and then prepare on, like, who we’re gonna end up, scheduling meetings with next week.

16 00:05:29.690 ⇒ 00:05:30.170 Shivani Amar: That’s on.

17 00:05:31.310 ⇒ 00:05:38.299 Uttam Kumaran: I think we can probably start there, and then… yeah, so maybe I’ll start briefly, introduce Awaish. So Awash is sort of…

18 00:05:38.440 ⇒ 00:05:54.839 Uttam Kumaran: My counterpart on the data side, both of us, you know, have worked in data for a while, but Awasht is really going to be leading a lot of our initial implementations on Snowflake, dbt, and sort of helping me with

19 00:05:54.940 ⇒ 00:06:07.250 Uttam Kumaran: Documentation, and sort of guiding through, you know, the selection of the data warehouse, selection of, you know, any other tooling, and then ultimately, like, implementation of whoever we go with.

20 00:06:07.320 ⇒ 00:06:21.670 Uttam Kumaran: So maybe I wish I’ll let you say hi, and yeah, kind of like the way we work, as I mentioned initially, is sort of like a little bit of a pod model, so we have folks with expertise across each part of the stack. I would say for…

21 00:06:21.670 ⇒ 00:06:29.390 Uttam Kumaran: This initial phase, it’s a lot of, like, architecture, documentation, and, like, discovery. And then as we get into modeling around certain…

22 00:06:29.600 ⇒ 00:06:42.270 Uttam Kumaran: channels and things like that. We’ll bring in, you know, some subject matter experts as we need, but usually I feel like we’ll… it’ll probably be 3 or 4 people, but there may be some other people from the Brainforce team that sort of sub in as

23 00:06:42.400 ⇒ 00:06:45.939 Uttam Kumaran: people go on vacation and stuff like that, but yeah, I’ll wait till you say hi.

24 00:06:48.290 ⇒ 00:06:51.660 Awaish Kumar: Yeah, my name is Avish Kumar, I have been working as a

25 00:06:51.980 ⇒ 00:06:57.590 Awaish Kumar: data engineer for the last 8 years, so I’ve worked with, like,

26 00:06:58.150 ⇒ 00:07:04.240 Awaish Kumar: Help, like, startups and the growth stage companies build their infrastructure from scratch.

27 00:07:04.480 ⇒ 00:07:08.669 Awaish Kumar: And build the, like, end-to-end pipelines for reporting and analytics.

28 00:07:10.980 ⇒ 00:07:13.689 Shivani Amar: Nice, nice to meet you. Where are you based?

29 00:07:14.740 ⇒ 00:07:18.179 Awaish Kumar: I’m from Pakistan, nice to meet you too.

30 00:07:18.560 ⇒ 00:07:19.290 Shivani Amar: Nice.

31 00:07:20.880 ⇒ 00:07:23.179 Uttam Kumaran: Yeah, he’s left… he’s left North America.

32 00:07:23.180 ⇒ 00:07:25.280 Shivani Amar: The wish was in Canada originally.

33 00:07:25.340 ⇒ 00:07:26.639 Uttam Kumaran: Couldn’t keep him here.

34 00:07:26.810 ⇒ 00:07:29.310 Shivani Amar: Gotcha.

35 00:07:30.160 ⇒ 00:07:34.159 Uttam Kumaran: Cool, so… yeah, maybe we can…

36 00:07:34.330 ⇒ 00:07:50.769 Uttam Kumaran: get started, I’m just gonna go ahead and share with you, sort of, our hub for Element that’s in our Notion. Again, I didn’t know, you know, yet where, sort of, Element team does writing, but for us, we’ll make sure, at least on our side.

37 00:07:50.770 ⇒ 00:08:01.520 Uttam Kumaran: all of our notes are structured in this, you know, Notion document… in this Notion, like, hub, and then if we need to move documentation either into the repository or into…

38 00:08:01.620 ⇒ 00:08:05.700 Uttam Kumaran: Another place where, you know, Element docs are could totally do that.

39 00:08:05.700 ⇒ 00:08:08.589 Shivani Amar: Yeah, you got, like, the folder I shared with you, right?

40 00:08:08.750 ⇒ 00:08:09.500 Uttam Kumaran: Yes.

41 00:08:09.500 ⇒ 00:08:15.870 Shivani Amar: Okay, so I would say that that, like, is gonna be the place to make sure we have stuff.

42 00:08:16.300 ⇒ 00:08:16.870 Shivani Amar: Logged.

43 00:08:16.870 ⇒ 00:08:28.240 Uttam Kumaran: Okay, so I guess, would you prefer that we, like, just start creating, like… because Google Docs is sometimes hard to just keep organized, but that’s where we’ll end up, like, we can migrate all of our docs there as we go.

44 00:08:28.240 ⇒ 00:08:34.820 Shivani Amar: Yeah, like, honestly, like, everybody works off Google Drive here, so I think eventually you’re gonna want stuff there.

45 00:08:34.820 ⇒ 00:08:36.030 Uttam Kumaran: Okay. Yeah.

46 00:08:39.919 ⇒ 00:08:44.789 Shivani Amar: yeah, this is like… like, people aren’t really working out of Notion too commonly right now, so…

47 00:08:45.040 ⇒ 00:08:47.750 Shivani Amar: Okay. It would just be, like, a separate thing.

48 00:08:48.100 ⇒ 00:08:48.920 Shivani Amar: Yeah, for…

49 00:08:48.920 ⇒ 00:08:54.869 Uttam Kumaran: For us, we’re gonna be taking a lot of notes on our end, just like, who do we meet and things like that, so it may end up being…

50 00:08:55.210 ⇒ 00:08:59.220 Uttam Kumaran: Redundant, and any sort of net new documentation, we’ll just make sure that no one’s up there.

51 00:08:59.220 ⇒ 00:08:59.960 Shivani Amar: Okay.

52 00:09:00.810 ⇒ 00:09:05.889 Uttam Kumaran: So, today, maybe we can just start. I wanted to…

53 00:09:06.640 ⇒ 00:09:15.730 Uttam Kumaran: one, maybe just continue to frame everything around this Gantt chart and timing, and I’ll just, you know, share my screen.

54 00:09:15.730 ⇒ 00:09:17.310 Shivani Amar: Yeah, please. We could…

55 00:09:17.310 ⇒ 00:09:20.440 Uttam Kumaran: We can talk through…

56 00:09:21.400 ⇒ 00:09:38.689 Uttam Kumaran: both, I want to add, sort of, individual milestones for meetings, but I know last time we talked, we spent some time on who owns each channel, and, like, sort of the ordering of, like, do we want to talk to the head of commercial first, and then sort of work our way down. I sort of thought about it, like, that would be a great

57 00:09:38.690 ⇒ 00:09:46.219 Uttam Kumaran: you know, framing. I know… I think you were going back and forth on, like, the ordering, but my suggestion would be, it would be nice to just say hi.

58 00:09:46.270 ⇒ 00:09:48.970 Uttam Kumaran: Explain a little bit about how we’re going to get his, sort of.

59 00:09:49.480 ⇒ 00:09:56.459 Uttam Kumaran: you know, buy in and just put a face to a name, and then work. Initially, you mentioned there was one person that owned

60 00:09:56.750 ⇒ 00:09:59.939 Uttam Kumaran: You know, Shopify.

61 00:10:00.100 ⇒ 00:10:04.910 Uttam Kumaran: As a whole, and maybe he’s the first person that we can, you know, arrange a time with.

62 00:10:05.050 ⇒ 00:10:07.680 Uttam Kumaran: You know, to ask questions.

63 00:10:07.680 ⇒ 00:10:18.260 Shivani Amar: Alright, so, like, yes, there’s the Gantt chart view, but the thing that was on your plate was to actually put the list of questions together, and so, like, that will help me figure out who to talk to. Have you guys done that?

64 00:10:18.810 ⇒ 00:10:25.969 Uttam Kumaran: We haven’t put a list of questions together, I just need to know, like, like, what channels these people own, and start to put

65 00:10:26.110 ⇒ 00:10:27.070 Uttam Kumaran: But, like…

66 00:10:27.070 ⇒ 00:10:42.329 Shivani Amar: you already know that we’re gonna talk to people who own Shopify and Amazon, right? Like, you already know that. So, like, to me, it’s like, I… I can see, can Jason answer these questions, or do we need Carlos involved? Like, that’s like… like, it’s… it’s like…

67 00:10:42.630 ⇒ 00:10:52.340 Shivani Amar: like, I’m pretty sure that was a next step on your plate, to be like, here’s the set of discovery questions we have so far, and then from there, Jason and I could figure out who you were gonna talk to.

68 00:10:53.070 ⇒ 00:11:00.029 Uttam Kumaran: Yeah, I just… I know that that’s what we discussed, but it’s also, like, it’s… it would just be nice, I think, to just…

69 00:11:00.060 ⇒ 00:11:13.419 Uttam Kumaran: make sure that we just have that meeting booked. I can work on those questions. We’re officially starting off next week, so we’re… we’re sort of getting our stuff aligned on our side, and getting those prepared. It’s a… it’s kind of a lot to go through right

70 00:11:13.680 ⇒ 00:11:27.850 Uttam Kumaran: all those questions on, and we’re… we have some questions already that I would ask them, but I still would like to make sure we get those meetings booked with those people, because before we… because I know that’s, like, when the sprint is starting, so… Totally, totally, but I…

71 00:11:27.850 ⇒ 00:11:43.200 Shivani Amar: Okay, so let me back up. So what I’m saying is, like, once you have a list of high-level questions, I can see if you need time with Jason versus if you need time with Carlos. I’m hesitant to just give time with you and people until we know the set of questions.

72 00:11:43.200 ⇒ 00:12:00.990 Shivani Amar: Like, Will, who is the chief commercial officer, is so busy that if I’m like, man, like, it really would be helpful for him to set the context, then great, I’ll try to set up time with him. But if your questions can be answered by Jason primarily, then I’m gonna, like, I’m gonna, like, let other people have their time.

73 00:12:00.990 ⇒ 00:12:19.280 Shivani Amar: And, like, I get the face-to-a-name piece, but that will happen, so I’m like, it’s more like, once… the first thing might be, like, we talked about the two hours with Jason, but is it two hours? Is it an hour? Like, that’s, like, you guys have done this before with a bunch of clients, and it’s like, what do you typically need to know to be oriented?

74 00:12:19.280 ⇒ 00:12:35.729 Shivani Amar: By a client in terms of what’s going on with Shopify, in terms of what’s going on with Amazon, like, what’s the orientation you need? And then from there, we can say, okay, like, Jason can do the high-level orientation, then maybe the following week, we set up time with you and Carlos, but we, like, let him have next week

75 00:12:35.730 ⇒ 00:12:45.850 Shivani Amar: to just do his own thing, right? Like, I’m trying to be protective a little bit about the element stakeholders, unless you have very clear questions where I’m like, oh yeah, this is definitely, like, you need time with Carlos.

76 00:12:46.710 ⇒ 00:12:50.150 Uttam Kumaran: Yeah, I mean, I just need to walk through… I mean, okay, so we can go ahead and…

77 00:12:50.810 ⇒ 00:12:52.469 Uttam Kumaran: Put that list together today.

78 00:12:52.730 ⇒ 00:13:03.880 Shivani Amar: I think that’s, like, that’s, like, the input, like, that’s, like, really, we’ve stared at the Gantt chart, once you actually have the questions, then we can say, cool, Jason and I believe that the people you need to talk to are A, B, and C.

79 00:13:04.010 ⇒ 00:13:12.529 Shivani Amar: Right? Okay. And I imagine you kind of have, like, a standard set of CPG questions from, like, your discovery with other companies, so hopefully.

80 00:13:12.530 ⇒ 00:13:29.040 Uttam Kumaran: Yeah, I guess, like, I… it’s just, like, I don’t… a lot of the questions are dependent on their answers, so, like, I can write down… I can write down, like, our 20, 30, 40 questions, but these are just, like, discovery conversations. I promise they won’t be a waste of time. I’m not there to chit-chat. It’ll just be…

81 00:13:29.440 ⇒ 00:13:41.979 Uttam Kumaran: like, I have to sort of understand what their… like, how they’ve managed the channel to date. I want to understand, like, what key KPI questions they’re answering, walk… walk through their reporting. So I can structure the agenda of that meeting, but it’s…

82 00:13:42.440 ⇒ 00:13:57.809 Uttam Kumaran: I… part of the goal… part of the reason for the meeting is also just to say, like, hey, I’m here, our team is going to be working on these things with you, and then we can move everything to Slack at that point, if async is better, but part of this is, like, we just need

83 00:13:58.330 ⇒ 00:14:11.020 Uttam Kumaran: brief introductions to people. Like, I get the protection of their time, but I promise you it’s not… we’re… we’re… we just have to… I sort of have to, like, do… run a basic discovery, so I can put together, like, the list of

84 00:14:11.140 ⇒ 00:14:14.129 Uttam Kumaran: Sort of areas, and some sample questions, but…

85 00:14:14.130 ⇒ 00:14:35.300 Shivani Amar: But then the high-level discovery is what I need to prime people with. Like, I need to tell people, these are the high-level questions that Brainforge is gonna want to discuss with you. That’s the way that we work here during Rest and Assess. So it’s like, I’m already pinging Carlos and Laura and people to say, Brainforge is gonna want time with you, stand by while I get, like, a semblance of their questions, so you know what to expect.

86 00:14:35.300 ⇒ 00:14:37.080 Shivani Amar: Like, that’s basically, like…

87 00:14:37.080 ⇒ 00:14:45.509 Shivani Amar: When you think about the rest and assess week, like, the way to do it smoothly is prime people as best as possible for what you need from them, and, like.

88 00:14:45.510 ⇒ 00:14:59.720 Shivani Amar: what kind of questions they should be prepped with, so that everybody’s using their time most efficiently. And so, like, if you look at the folder that I shared with you, I’ve already started sharing some files with you, right? Like, have you taken a look at any of those?

89 00:15:00.200 ⇒ 00:15:09.660 Uttam Kumaran: No, I mean, we’re… like, we’re… we usually don’t start, like, a lot of stuff until, like… like, we… until the contract starts. The contract’s starting next week, so…

90 00:15:09.660 ⇒ 00:15:11.010 Shivani Amar: are starting to kind of get…

91 00:15:11.430 ⇒ 00:15:23.149 Uttam Kumaran: Yeah, I’m starting to, like, get our people together, and so we’re planning to execute, and I’m… I’m just trying to get a sense of, like, who we’re gonna start talking to, but we don’t officially… I can’t dedicate, like, a ton of time.

92 00:15:23.150 ⇒ 00:15:24.190 Shivani Amar: No, that’s…

93 00:15:24.190 ⇒ 00:15:25.010 Uttam Kumaran: We’re on, so…

94 00:15:25.350 ⇒ 00:15:25.960 Shivani Amar: So, like.

95 00:15:25.960 ⇒ 00:15:30.099 Uttam Kumaran: I’m just making sure we have, like, everything set up and ready to go, so we hit the ground running.

96 00:15:30.100 ⇒ 00:15:47.370 Shivani Amar: Perfect. So it’s like, yeah, I… basically what I can assure you is, like, yes, am I pinging all of the stakeholders on the commercial side, saying, we’ve selected Brainforge, Brain… this is their proposal, like, this is a link to the Gantt chart that you can see, like, I’m saying that the milestones for December are…

97 00:15:47.580 ⇒ 00:16:02.189 Shivani Amar: selecting a data warehouse and ingesting Shopify and Amazon data, right? Like, that’s, like, what I’m kind of, like, articulating. And, like, those are the milestones, and then, accordingly, it’s like, like, having the conversations with people who own Shopify wholesale and Amazon, which are

98 00:16:02.190 ⇒ 00:16:08.569 Shivani Amar: Carlos and Laura. That’s basically it. And, like, Blake is, like, this other person that, like, he owns.

99 00:16:08.740 ⇒ 00:16:12.639 Shivani Amar: Partnership data, which, like, look, let me share my screen for a second.

100 00:16:12.640 ⇒ 00:16:13.190 Uttam Kumaran: Yeah.

101 00:16:14.320 ⇒ 00:16:23.890 Shivani Amar: So… Okay, so, like, check this out, okay? So, like, let’s see, is it opening?

102 00:16:28.680 ⇒ 00:16:30.160 Shivani Amar: Okay, you can see that.

103 00:16:30.770 ⇒ 00:16:31.430 Uttam Kumaran: Yes.

104 00:16:31.790 ⇒ 00:16:39.920 Shivani Amar: Okay, so they’re, like, collecting data constantly around, like, the partnerships that we have, and trying to get a feel for…

105 00:16:40.230 ⇒ 00:16:41.790 Shivani Amar: Maybe…

106 00:16:42.340 ⇒ 00:16:52.840 Shivani Amar: I’m like, I made a copy of this spreadsheet, so I’m like, I don’t know, like, whatever. I don’t know if this is broken in theirs, but I made a copy of their spreadsheet, and it’s like, from, you know, our partner.

107 00:16:52.840 ⇒ 00:16:54.110 Uttam Kumaran: These are the wholesale partners.

108 00:16:54.120 ⇒ 00:16:55.549 Shivani Amar: No, no, no, no, no.

109 00:16:55.550 ⇒ 00:16:56.000 Uttam Kumaran: Oh.

110 00:16:56.000 ⇒ 00:17:06.589 Shivani Amar: This is, like, people we advertise with. So this is, like, like, not people who are buying, and selling. This is, like, let’s see…

111 00:17:06.599 ⇒ 00:17:07.849 Uttam Kumaran: Oh, marketing partners, yeah.

112 00:17:07.849 ⇒ 00:17:08.949 Shivani Amar: Veritasium again.

113 00:17:08.950 ⇒ 00:17:10.160 Uttam Kumaran: YouTubers, influencers… okay.

114 00:17:10.160 ⇒ 00:17:16.790 Shivani Amar: I’m like, where’s Huberman? Like, what… like, Andrew Huberman, right? So it’s like, okay, this is…

115 00:17:17.069 ⇒ 00:17:36.059 Shivani Amar: maybe, like, I’m like, is this even the right row? But, like, this is, like, will show you, theoretically, like, okay, how much revenue did we get from Huberman, right? Like, how many sessions went on, like, how many people went on our website? How many people added carts? And then you can kind of, like, look at conversion rates, right? Like…

116 00:17:36.060 ⇒ 00:17:36.510 Uttam Kumaran: Okay.

117 00:17:36.510 ⇒ 00:17:41.849 Shivani Amar: across these partners, and like, for instance, we just started advertising the Skim, you know that newsletter?

118 00:17:42.000 ⇒ 00:17:42.620 Uttam Kumaran: Yes.

119 00:17:42.880 ⇒ 00:17:52.550 Shivani Amar: Okay, so, like, the skim has… is getting us, like, a lot of sessions, as you can see, but it’s, like, a really low conversion to add to cart.

120 00:17:52.930 ⇒ 00:17:53.600 Uttam Kumaran: Yes.

121 00:17:53.600 ⇒ 00:18:04.619 Shivani Amar: Okay, but, like, that’s standard, I think, for newsletters versus, like, trusted health podcasts and stuff like that. So this is kind of interesting, because it’s, like, related to Shopify data, right?

122 00:18:04.620 ⇒ 00:18:05.110 Uttam Kumaran: Yeah.

123 00:18:05.110 ⇒ 00:18:22.639 Shivani Amar: it’s, like, partnership-specific. And so, like, what I’m thinking for you guys is, like, e-commerce, growth dashboard, this is what Carlos owns. Carlos is, like, looking at… now I think it’s for 2026, so it’s kind of, like, you can’t see actuals, but, like, he’s looking at…

124 00:18:22.660 ⇒ 00:18:27.550 Shivani Amar: E-commerce sales, and, like, performance spend, and stuff like that, like.

125 00:18:27.790 ⇒ 00:18:40.779 Shivani Amar: and then Amazon OKRs, right? Shopify OKRs, so it’s like, this is, like, the total for e-com. Then he’s got his Amazon, and then he’s got, like, a little bit for Walmart’s website, basically, for Walmart’s, like.

126 00:18:40.820 ⇒ 00:18:51.759 Shivani Amar: Walmart.com, I guess. So that’s, like, his e-commerce dashboard. So that’s, like, just to give you a sense of, like, this is what Carlos owns, then this is what, like, Blake owns, right? So, like.

127 00:18:51.760 ⇒ 00:19:04.520 Shivani Amar: as you’re prepping discovery with these people, like, part of it is they’ll walk you through this, yes, right? Like, they can definitely walk you through this, but part of it is I wanted to get you the documents so you can make your discovery, like, a little bit more informed.

128 00:19:04.930 ⇒ 00:19:08.479 Uttam Kumaran: Right, and then for these meetings, like, do you think it’s better to prime on, like.

129 00:19:08.940 ⇒ 00:19:21.070 Uttam Kumaran: What, like, what would help improve your reporting? Do you think it’s, like, what questions have you wanted to ask, but you can’t ask? Do you think it’s, like, how much time are you spending to produce this?

130 00:19:22.080 ⇒ 00:19:33.079 Shivani Amar: So, like, for instance, for Carlos, like, the Carlos, the e-commerce one that you’re in right now, like, it’s, like, somebody on his team is, like, going in.

131 00:19:33.540 ⇒ 00:19:36.939 Shivani Amar: And pulling from every system and, like, typing the numbers in.

132 00:19:36.940 ⇒ 00:19:37.540 Uttam Kumaran: Yes, yes.

133 00:19:37.540 ⇒ 00:19:40.159 Shivani Amar: Right? Like, it’s not… it’s not clean.

134 00:19:40.160 ⇒ 00:19:43.700 Uttam Kumaran: It’s a little bit of a leading question, but I guess I’m… I’m sort of like…

135 00:19:43.990 ⇒ 00:20:01.300 Uttam Kumaran: that’s kind of, like, how we… one, I will… I will almost… you… it’s sort of, like, tell me where the pain is, and then try to identify, okay, is this, like… is this, like, annoying, but, like, it’s okay? Or is this, like, we… the business cannot grow?

136 00:20:01.610 ⇒ 00:20:06.220 Uttam Kumaran: Because you can’t get the more numbers, or the numbers fast enough, right?

137 00:20:06.220 ⇒ 00:20:09.219 Shivani Amar: Right, so I don’t think it’s that the business is, like.

138 00:20:09.410 ⇒ 00:20:29.400 Shivani Amar: oh my god, the fact that this reporting is manual is hurting our business, right? Like, that’s not… that’s not… yes, that is a pain point, but it is not THE pain point, right? When you think about, like, you’re like, I’m hungry to add ROI, like, the thing that is gonna be deeply unsexy, I actually, like, wrote this in my…

139 00:20:29.610 ⇒ 00:20:48.720 Shivani Amar: like, rest and assess, like, kind of… I’m just gonna share this very openly, like, I was like, we selected a partner to work with, and the one thing to be, like, really mindful of is, like, that we are doing the deeply unsexy work of, like, where our definitions different? Yeah. Right? And, like, that that’s gonna be, like.

140 00:20:48.890 ⇒ 00:20:53.609 Shivani Amar: like, they’re not even gonna necessarily name that, right? Because if you’re talking to an e-commerce guy.

141 00:20:53.610 ⇒ 00:20:54.170 Uttam Kumaran: Yes.

142 00:20:54.170 ⇒ 00:21:04.449 Shivani Amar: he’s thinking about e-commerce. Then you’re talking to a wholesale person, they’re thinking about wholesale. You’re talking to a retail person, they’re thinking about retail, and then eventually, you, as the triangulator, have to say.

143 00:21:04.450 ⇒ 00:21:08.029 Uttam Kumaran: I’ve heard the word sales, I’ve heard the word income, I’ve heard the word…

144 00:21:08.030 ⇒ 00:21:16.249 Shivani Amar: point of sales, and, like, nobody knows what they’re talking about. Right? And so, like, that’s, like, a piece of triangulation. I would say.

145 00:21:16.500 ⇒ 00:21:29.510 Shivani Amar: Like, one of the examples of things that was on Carlos’ plate this past month that I shared with you previously on e-commerce was the lower conversion rate from sessions to,

146 00:21:29.510 ⇒ 00:21:29.970 Uttam Kumaran: Yes.

147 00:21:30.160 ⇒ 00:21:39.609 Shivani Amar: Right? In our, like, in our Shopify instance. And so, that, like, is that because we’re just driving all these sessions with, like, newsletters?

148 00:21:39.770 ⇒ 00:21:56.570 Shivani Amar: Right? Like, is that, like, we’re just driving a bunch of traffic to our website, and then people are just less likely to convert, and that’s just, like, a natural thing as we broaden our advertising channels, okay? Or, like, what drove… if you think about it that way, it’s like, what drove the increase in the denominator?

149 00:21:57.490 ⇒ 00:22:16.430 Shivani Amar: Right? And then it’s like, okay, that’s going to be… like, you can get the orientation from Carlos around, like, this is his sheet that he looks like, these are all the metrics that he thinks about, and then I think your discovery question is, like, cool, this is probably pretty manual, so, like.

150 00:22:16.430 ⇒ 00:22:16.820 Uttam Kumaran: Yeah, yeah.

151 00:22:16.820 ⇒ 00:22:34.159 Shivani Amar: In time, we can, like, develop a more automated way of doing this, great. But then… and, like, where does all that data sit in Shopify, blah blah blah. If you know it, then great. Then it’s like, what are the pressing questions that you feel like have been hard to answer lately? And, like, if he doesn’t mention conversion rate there, I’ll prompt it. I’ll be like, that was.

152 00:22:34.160 ⇒ 00:22:36.370 Uttam Kumaran: For that, like, for that question.

153 00:22:36.480 ⇒ 00:22:39.020 Uttam Kumaran: Do you think it’s helpful if it’s, like.

154 00:22:39.200 ⇒ 00:22:41.530 Uttam Kumaran: Okay, there is a way, like…

155 00:22:42.000 ⇒ 00:22:48.399 Uttam Kumaran: There is a way for us to answer this short-term, or do you think that’s just something we note down and, like.

156 00:22:49.380 ⇒ 00:22:55.859 Uttam Kumaran: Okay, it’s noted that you’re having a hard time. Like, do you think there will be things that come up where it’s like.

157 00:22:56.190 ⇒ 00:23:02.580 Uttam Kumaran: Hey, actually, maybe go do a little bit of, like, find out the answer to this as a way to, like, win…

158 00:23:02.580 ⇒ 00:23:03.230 Shivani Amar: This is where I think.

159 00:23:03.230 ⇒ 00:23:04.830 Uttam Kumaran: points with Carlos, or…

160 00:23:05.180 ⇒ 00:23:21.699 Shivani Amar: here’s where I think, like, the row sets, like, are, to me, are not clear, okay? So it’s like, let’s say you put, like, a database together, like, everything going on in Shopify and, like, how things are tracked, okay? So then it’s like, here’s, like, what I’m hungry for, just, like, as an example, right? Like, a place where we see

161 00:23:21.950 ⇒ 00:23:25.610 Shivani Amar: Sessions, product… By chance.

162 00:23:25.610 ⇒ 00:23:28.079 Uttam Kumaran: known by, yeah, by Switzpan, yeah.

163 00:23:28.080 ⇒ 00:23:31.539 Shivani Amar: Product page, add to cart… no, I’m talking about the funnel.

164 00:23:31.540 ⇒ 00:23:32.430 Uttam Kumaran: Oh, okay.

165 00:23:32.430 ⇒ 00:23:47.510 Shivani Amar: check out, right? Like, to me, I’ll… you might hear me say this a lot in life, but I’m like, everything’s a funnel, right? So I’m like, okay, everything’s a funnel, so, like, what is the… what are the metrics that we want to look at? Like, and then, right now, it’s like, his dashboard is, like…

166 00:23:47.980 ⇒ 00:23:59.459 Shivani Amar: his dashboard is, like, looking at it at a high level with the conversion rate, okay? He’s like, what was my conversion rate on Amazon? What was my conversion rate on…

167 00:23:59.820 ⇒ 00:24:11.509 Shivani Amar: whatever, like, on Shopify, okay? And, like, what I might want to know is, like, let’s say you have a dashboard eventually that’s, like, sessions, product page, add to cart, checkout, and then it’s, like, by…

168 00:24:12.080 ⇒ 00:24:23.679 Shivani Amar: Month, so you can look at, like, Jan, Feb, March, whatever, but because, like, I’m thinking in Tableau terms, you can also say filters, or date ranges, right, where you can say…

169 00:24:24.260 ⇒ 00:24:33.310 Shivani Amar: Like, weekly versus… monthly, or whatever. Pick the date range that you want, right? Like.

170 00:24:33.650 ⇒ 00:24:50.460 Shivani Amar: 2025, or whatever, I’m just kind of making stuff up right now. And then you could say, like, filters could be Shopify versus Amazon versus total e-commerce kind of thing, right? And it’s like, eventually you want all the metrics to be able to, like.

171 00:24:51.350 ⇒ 00:24:59.789 Shivani Amar: triangulate so you can, like, have dashboards like this. It’s like, whoa, my session spiked, but my checkout was pretty consistent.

172 00:25:00.740 ⇒ 00:25:04.040 Shivani Amar: Does that make sense? That’s, like, my… view of…

173 00:25:04.040 ⇒ 00:25:04.490 Uttam Kumaran: Cool.

174 00:25:04.490 ⇒ 00:25:08.330 Shivani Amar: What good will look like after you have the conversations.

175 00:25:08.630 ⇒ 00:25:09.510 Uttam Kumaran: Cool, okay.

176 00:25:09.720 ⇒ 00:25:12.849 Shivani Amar: Does that resonate with you, Awish?

177 00:25:13.380 ⇒ 00:25:14.409 Awaish Kumar: Yeah, yeah.

178 00:25:14.590 ⇒ 00:25:20.150 Shivani Amar: Yeah, so it’s like, like, you can see, like, he’s, like, manually typing things into this right now.

179 00:25:20.150 ⇒ 00:25:21.850 Uttam Kumaran: Yeah, and doing the deltas, yeah.

180 00:25:21.850 ⇒ 00:25:23.480 Shivani Amar: And he’s, like, doing the deltas.

181 00:25:23.480 ⇒ 00:25:32.040 Uttam Kumaran: This is where we find, I mean, this is where we find everybody, basically. Like, all of our typical things. And I’m like, eventually I want, like, a tool that I can just be like… and, like.

182 00:25:32.140 ⇒ 00:25:49.280 Shivani Amar: My question for you on the discovery side is also that we have… this is a question I have for you, right? You’re like, yeah, I want to talk to… I want to talk to Carlos, I want to talk to people, great, but then, you know how we have, like, we have one part of the business that actually looks at Looker?

183 00:25:49.590 ⇒ 00:25:50.090 Uttam Kumaran: Yes.

184 00:25:50.090 ⇒ 00:25:53.400 Shivani Amar: I think I told you this, right? So, like, they use, like, a coarse medium, and I’m like…

185 00:25:53.400 ⇒ 00:25:53.990 Uttam Kumaran: Yeah, yeah.

186 00:25:53.990 ⇒ 00:26:05.359 Shivani Amar: I’m like, do you need to talk to Source Medium? That’s my question for you. Or, like, do you just need access to this? Or is this, like, irrelevant because you’re gonna pipe the data anyway into…

187 00:26:05.510 ⇒ 00:26:13.150 Shivani Amar: Snowflake or whatever data warehouse, and you don’t actually need to be looking at this. Like, what do you feel about this dashboard that you’re looking at?

188 00:26:13.150 ⇒ 00:26:28.970 Uttam Kumaran: In order to answer that, I need to talk… I need to either get access to this, or talk to them, or talk to whoever the internal element owner is on, like, what was the use case. Because also, again, if there is a duplication of work, then I want to help you make the decision on, like.

189 00:26:29.270 ⇒ 00:26:39.859 Uttam Kumaran: okay, are there actually things here we can reuse, right? But this is where I don’t know what scope source medium has access to, how open that is, and how configurable, so…

190 00:26:40.300 ⇒ 00:26:41.680 Uttam Kumaran: I have to sort of

191 00:26:42.620 ⇒ 00:26:49.819 Uttam Kumaran: Talk to our intern, like, whoever on our side is the source medium sort of person, and get their gauge.

192 00:26:50.090 ⇒ 00:26:55.030 Shivani Amar: I was gonna do a discovery call with stores media, not a discovery call, that’s, like, the wrong word to… I was gonna do.

193 00:26:55.030 ⇒ 00:26:55.540 Uttam Kumaran: What’s in here?

194 00:26:55.540 ⇒ 00:27:01.770 Shivani Amar: people at Source Media myself, so they could orient me. So, like, should I just do that with us together next week?

195 00:27:01.770 ⇒ 00:27:03.629 Uttam Kumaran: Yeah, I’m happy to, and I won’t…

196 00:27:03.630 ⇒ 00:27:04.639 Shivani Amar: I was gonna…

197 00:27:04.640 ⇒ 00:27:12.029 Uttam Kumaran: I’ll play nice with them, like, I’m not trying… for me, more of, like, I’m trying to give you that answer of, like, okay, what’s in here?

198 00:27:12.170 ⇒ 00:27:14.010 Uttam Kumaran: Is this only Shopify?

199 00:27:14.410 ⇒ 00:27:15.790 Uttam Kumaran: Right? And, like…

200 00:27:16.120 ⇒ 00:27:18.939 Shivani Amar: It looks like they also have, like, gorgeous data.

201 00:27:19.500 ⇒ 00:27:33.959 Uttam Kumaran: Yeah, so I feel like what these guys typically do is they’ll pipe your data into, like, a BigQuery, and then they layer on these, like, productized dashboards, which they can just, like, kind of repurpose. What you may find is, like, it’s not very customizable, or…

202 00:27:34.540 ⇒ 00:27:45.760 Uttam Kumaran: yeah, it’s, like, built on Airtable or something, and so there is a… there is a… and then also, for example, you don’t even know if anyone… who in Element is using what part of this.

203 00:27:46.020 ⇒ 00:27:46.480 Shivani Amar: Right.

204 00:27:46.480 ⇒ 00:27:55.379 Uttam Kumaran: for example, typically what we’ll find is, like, the person on Element’s side will be like, yeah, the cohorting is, like, doesn’t include this, so we never use that piece, and you’re like, okay.

205 00:27:55.380 ⇒ 00:28:01.150 Shivani Amar: Yeah, that’s where, like, last week I was like, what is up with this data? I was like, I don’t.

206 00:28:01.150 ⇒ 00:28:14.839 Uttam Kumaran: I mean, it looks great, like, if you… okay, so I would say, like, look, if we have all this and it’s accurate, then we’re kind of far, but I would be surprised if you and Phil didn’t already, like, if someone already didn’t point that out, right? So, like, someone…

207 00:28:14.840 ⇒ 00:28:17.410 Shivani Amar: This is bringing in retail data, for example, right?

208 00:28:17.410 ⇒ 00:28:28.159 Uttam Kumaran: Yeah, so… so my question for Source Medium is, like, okay, is that, like, a you-can’t-do-that-for-us problem? Because then now that comes into the factor of, like, okay, if we can

209 00:28:28.330 ⇒ 00:28:36.669 Uttam Kumaran: if it… and then… but this is, again, like, a conversation to you and Phil, is, like, if you’re able to do in here, what is the benefit of, like, an owned platform?

210 00:28:36.880 ⇒ 00:28:40.830 Uttam Kumaran: Versus relying on a third-party vendor for…

211 00:28:41.020 ⇒ 00:28:42.730 Shivani Amar: these metrics, and I can talk.

212 00:28:42.900 ⇒ 00:28:47.719 Uttam Kumaran: I could give you all the pros and cons. So totally, I think if…

213 00:28:48.200 ⇒ 00:28:57.430 Uttam Kumaran: we can grab time with them, and I can just ask them about the history of what they’ve set up here. And then internally, if you know the core user of this.

214 00:28:57.900 ⇒ 00:29:03.010 Uttam Kumaran: even just asking them to say, like, what’s accurate there. But you already know some of the trade-offs, so…

215 00:29:03.200 ⇒ 00:29:06.930 Uttam Kumaran: we can just put a… on our side, what I want that to come as, like, a…

216 00:29:07.090 ⇒ 00:29:09.940 Uttam Kumaran: Basically, a memo on, like, the source medium.

217 00:29:10.640 ⇒ 00:29:25.139 Shivani Amar: Totally. I’m kind of, like, my stance on the source medium, I’m like, cool, there’s some data, but I’m like, nobody seems to, like… like, this week, when people were like, what happened with our conversion rate? Everybody’s just, like, staring at source medium, right? Like, and like…

218 00:29:25.140 ⇒ 00:29:25.780 Uttam Kumaran: Yeah, yeah.

219 00:29:25.780 ⇒ 00:29:28.410 Shivani Amar: Nobody actually knows, I’m like, these aren’t the…

220 00:29:28.410 ⇒ 00:29:32.759 Uttam Kumaran: That’s also the thing, if you’re not building it, if you never build it, you’re not bought in, and so, like.

221 00:29:32.760 ⇒ 00:29:33.150 Shivani Amar: Yeah.

222 00:29:33.150 ⇒ 00:29:42.559 Uttam Kumaran: Yes, they will give you, like, these, like, really… I mean, it looks… wow, it looks fire, you know? It looks really nice, but that’s, like, usually that’s just, like, vanity stuff, so you don’t even know…

223 00:29:43.140 ⇒ 00:29:48.869 Uttam Kumaran: how this is built, and there’s no buy-in from, like, Carlos is still in a spreadsheet, right? Is Carlos using this? I don’t know.

224 00:29:49.560 ⇒ 00:30:00.100 Shivani Amar: Right, so that’s… I think it, like, some of his data, like, comes from source medium. So I think part of your discovery when you talk to Carlos, like, I… you’re definitely going to talk to Carlos, I’m not, like, gatekeeping any.

225 00:30:00.100 ⇒ 00:30:19.689 Uttam Kumaran: No, no, no, no, I’m not that. It’s also… I’m gonna work… I’ll work on the rough questions. So, for me, it’s like, it is a little bit of, like, both a trust-building exercise, and like, hey, we are gonna start to answer questions, and we may uncover things that sort of show this side of the business, and I want to build, like, a friend out of him, or data out.

226 00:30:19.690 ⇒ 00:30:23.449 Shivani Amar: the entire data ecosystem we’re building.

227 00:30:23.450 ⇒ 00:30:23.770 Uttam Kumaran: Yeah.

228 00:30:23.770 ⇒ 00:30:29.749 Shivani Amar: Carlos is like, if anybody’s the most excited about you getting a data consultant, it’s me, right? Like, he’s, like, so…

229 00:30:30.180 ⇒ 00:30:30.600 Shivani Amar: And then.

230 00:30:30.600 ⇒ 00:30:34.269 Uttam Kumaran: No, and see, I don’t know that also, you know?

231 00:30:34.270 ⇒ 00:30:35.380 Shivani Amar: In your discovery…

232 00:30:35.380 ⇒ 00:30:35.910 Uttam Kumaran: Yeah.

233 00:30:36.060 ⇒ 00:30:39.510 Shivani Amar: in your discovery, I want you to, like, say,

234 00:30:39.820 ⇒ 00:30:45.090 Shivani Amar: like, in your discovery, I want you to say, Like, potentially time to walk

235 00:30:45.170 ⇒ 00:31:03.319 Shivani Amar: Because I’m, like, I didn’t do anything where he was, like, walking me through where he finds the data, but if you go back to, like, his e-commerce dashboard, right? Like, he… what he was gonna do, what he was planning on doing was, like, URLing, or, like, hyperlinking where he’s getting the data from.

236 00:31:03.510 ⇒ 00:31:04.340 Uttam Kumaran: Yes.

237 00:31:04.340 ⇒ 00:31:05.090 Shivani Amar: Throughout this.

238 00:31:05.090 ⇒ 00:31:06.690 Uttam Kumaran: So… Yeah.

239 00:31:07.040 ⇒ 00:31:21.299 Shivani Amar: hold on, sorry. So, what he was planning to do was that, which is fine, and… but I think it’s, like, if you’re, like, if you make your list of questions, and I’m like, hey Carlos, do you want to actually just do, like, an hour and a half block, where you, like, actually walk them through…

240 00:31:21.360 ⇒ 00:31:29.650 Shivani Amar: where you’re getting the data from, and your… your feeling of trust around that data. Like, that…

241 00:31:29.650 ⇒ 00:31:46.760 Shivani Amar: could be interesting, right? So I’m trying to figure out, like, how much time should we be asking him for? Is it 30 minutes just for you to get to know each other, which is not going to be that useful? Is it an hour? Is it, like, let’s just block out, like, a good hour and a half, Carlos, so you can actually also walk them through where you’re, like.

242 00:31:46.760 ⇒ 00:31:51.390 Shivani Amar: Finding things in source medium, and if we don’t end up using an hour and a half, then that’s fine.

243 00:31:52.590 ⇒ 00:32:06.289 Uttam Kumaran: Okay, I’ll send you the questions, and then, yeah, I think it’ll be a good guide. And then on… yeah, and then similarly for… we can take source medium, like, what is going on here as another action item to just…

244 00:32:06.640 ⇒ 00:32:08.290 Uttam Kumaran: Try to wrap a bow around.

245 00:32:08.450 ⇒ 00:32:22.549 Shivani Amar: Totally. So I’m gonna, like, ping this guy, Chase, and just say, he’s at Source Medium, and just say, I’ll look at your calendar, let me do this right now, so I’ll look at your calendar, and actually include,

246 00:32:22.740 ⇒ 00:32:25.249 Shivani Amar: another data consultant.

247 00:32:25.410 ⇒ 00:32:33.010 Shivani Amar: We’ll be working with… On it, so we can get the orientation Together…

248 00:32:33.210 ⇒ 00:32:40.700 Shivani Amar: Element is going to be focusing on building out Our own data stack.

249 00:32:40.850 ⇒ 00:32:48.459 Shivani Amar: for… I’ll just say for context, Element is going to be working on, because I’m, like, I’m still trying to figure out, like, what do they do?

250 00:32:48.770 ⇒ 00:32:50.440 Uttam Kumaran: Well, that’s what I guess my…

251 00:32:50.600 ⇒ 00:32:53.969 Uttam Kumaran: I don’t know if you say that, because I feel like they may…

252 00:32:54.330 ⇒ 00:32:55.260 Shivani Amar: Bristle?

253 00:32:55.560 ⇒ 00:32:56.690 Uttam Kumaran: Yeah.

254 00:32:57.380 ⇒ 00:32:57.770 Shivani Amar: So…

255 00:32:57.770 ⇒ 00:33:00.490 Uttam Kumaran: Like, it may come across as, like, oh, they’re shutting us down.

256 00:33:02.010 ⇒ 00:33:05.820 Uttam Kumaran: tip to… yeah. I may just… Yeah.

257 00:33:06.520 ⇒ 00:33:11.299 Shivani Amar: I’ll look at your calendar and actually include another day, because I’ll be working with on the invite.

258 00:33:13.360 ⇒ 00:33:20.020 Uttam Kumaran: You can just say it’s working on data stuff within the org, because the last thing I want is for them to start to, to, like.

259 00:33:20.290 ⇒ 00:33:37.260 Uttam Kumaran: think we’re… I don’t know, you just never… I just don’t know… I just don’t know, and so it’s better to just be like, hey, we just want to get an overview of the platform, I want to hear about what sources are connected, and… and ultimately, look, I want… I will give… my… our memo is to give you the, hey, what’s…

260 00:33:37.380 ⇒ 00:33:44.329 Uttam Kumaran: being used in here, what’s not, what are the good and what’s the bad, and what… here are, like, the list of decisions and recommendations to make.

261 00:33:44.330 ⇒ 00:33:45.870 Shivani Amar: Yeah. But…

262 00:33:45.870 ⇒ 00:33:49.480 Uttam Kumaran: I think Source Media may be one of those, and so I don’t want to, like.

263 00:33:50.060 ⇒ 00:33:51.560 Uttam Kumaran: The, the way that…

264 00:33:51.970 ⇒ 00:33:59.359 Uttam Kumaran: people typically do this, is where you guide a consultant companies, like, what is all this stuff? Get rid of this. Like, I don’t want to come across that way.

265 00:33:59.360 ⇒ 00:33:59.800 Shivani Amar: Yeah.

266 00:33:59.800 ⇒ 00:34:01.550 Uttam Kumaran: If we can use some of their stuff.

267 00:34:02.020 ⇒ 00:34:04.839 Uttam Kumaran: for certain specific things, and I’d love to, so…

268 00:34:10.250 ⇒ 00:34:24.860 Shivani Amar: Okay, I’ll just say… I said this. I’ll look at your calendar and actually include another data concern we’ll be working with on the invite so we can get the orientation together. Hope that works. Just want an overview of the platform, which sources are connected, and what dashboards the Element team finds most useful today. Thank you. Okay?

269 00:34:24.860 ⇒ 00:34:31.979 Uttam Kumaran: Can you also… if you can mention if he has usage statistics on, like, who’s logging in and what they’re using, versus just, like.

270 00:34:33.040 ⇒ 00:34:36.230 Uttam Kumaran: they like this. If, like, if they can actually tell us, like.

271 00:34:37.150 ⇒ 00:34:38.920 Uttam Kumaran: Who’s logging in how many times?

272 00:34:38.929 ⇒ 00:34:39.559 Shivani Amar: Cool.

273 00:34:41.129 ⇒ 00:34:45.519 Shivani Amar: I’ll send that, and then basically… He’s got…

274 00:34:46.179 ⇒ 00:34:50.459 Shivani Amar: Meetings, let’s see… like, if we were to do…

275 00:34:51.889 ⇒ 00:34:56.459 Shivani Amar: December 1st, and just start off, so this is Pacific time.

276 00:34:56.569 ⇒ 00:34:59.879 Shivani Amar: You want to look at your calendar? And, like, would a way.

277 00:34:59.880 ⇒ 00:35:00.350 Uttam Kumaran: Yeah.

278 00:35:00.350 ⇒ 00:35:02.349 Shivani Amar: Dwayne, or just you, like, what would the flow be?

279 00:35:02.350 ⇒ 00:35:04.069 Uttam Kumaran: Yeah, I would include me in OH.

280 00:35:04.320 ⇒ 00:35:08.230 Shivani Amar: So… Ehh.

281 00:35:12.600 ⇒ 00:35:16.599 Uttam Kumaran: I’m just, like, flipping back and forth. Oh, yeah. You tell me what time.

282 00:35:16.600 ⇒ 00:35:22.210 Shivani Amar: How about noon? Or, like, I’m just…

283 00:35:22.210 ⇒ 00:35:25.030 Uttam Kumaran: Yeah, basically a free afternoon PT.

284 00:35:25.650 ⇒ 00:35:32.340 Shivani Amar: Okay, so let’s do 12.30 PT, and then I’m gonna invite you guys, so your emails…

285 00:35:32.890 ⇒ 00:35:35.850 Shivani Amar: put them at brainforge.ai, right?

286 00:35:36.000 ⇒ 00:35:39.550 Uttam Kumaran: Yeah, and I’ll, I’ll put Alicia’s in the chat.

287 00:35:39.840 ⇒ 00:35:42.919 Shivani Amar: And then… yeah, put a wishes in the chat.

288 00:35:43.600 ⇒ 00:35:45.489 Shivani Amar: Oh, cool. Thank you.

289 00:35:50.210 ⇒ 00:35:53.500 Shivani Amar: Enter a valid email address, a good grade.

290 00:35:55.040 ⇒ 00:35:58.170 Shivani Amar: And then… Perfect.

291 00:35:59.600 ⇒ 00:36:00.370 Shivani Amar: Okay.

292 00:36:01.120 ⇒ 00:36:01.970 Shivani Amar: Great.

293 00:36:02.600 ⇒ 00:36:07.829 Uttam Kumaran: It’s a, you know, it’s… it’s… what’s funny is, like, Athletic Greens had a very similar spreadsheet to this…

294 00:36:08.110 ⇒ 00:36:09.970 Uttam Kumaran: partnerships spreadsheet.

295 00:36:10.580 ⇒ 00:36:11.490 Shivani Amar: Yeah, that makes sense.

296 00:36:11.490 ⇒ 00:36:14.030 Uttam Kumaran: When I was there, like, 3-4 years ago.

297 00:36:14.030 ⇒ 00:36:14.800 Shivani Amar: Yeah.

298 00:36:15.660 ⇒ 00:36:18.389 Uttam Kumaran: This is a little bit better than that. That was pretty brutal.

299 00:36:20.490 ⇒ 00:36:20.869 Uttam Kumaran: And they were.

300 00:36:20.870 ⇒ 00:36:21.300 Shivani Amar: Sure.

301 00:36:21.300 ⇒ 00:36:23.430 Uttam Kumaran: You’re spending, like, an ungodly amount.

302 00:36:23.970 ⇒ 00:36:29.750 Shivani Amar: Like, I think what would be interesting with them is, like, my style versus, like… like, I’m like…

303 00:36:30.050 ⇒ 00:36:32.080 Shivani Amar: this is, like… I wouldn’t have looked.

304 00:36:32.080 ⇒ 00:36:32.500 Uttam Kumaran: Yeah.

305 00:36:32.500 ⇒ 00:36:35.920 Shivani Amar: I’m like, I don’t know how to, you know, like…

306 00:36:35.920 ⇒ 00:36:44.599 Uttam Kumaran: Well, what was your… like, tell me, like, what… how are you feeling about, like, that? Like, do you feel like… I mean, this is where, again, part of me meeting people is, like, this is a…

307 00:36:45.180 ⇒ 00:36:52.590 Uttam Kumaran: it’s like a people, a process, and, like, a tools thing, so, like, I have to get it to build up… be able to give you recommendations on

308 00:36:52.730 ⇒ 00:36:55.369 Uttam Kumaran: Feasibility of certain moves.

309 00:36:55.580 ⇒ 00:37:00.400 Uttam Kumaran: like, on the board, I kind of… I need to… that’s… that’s mostly a lot of, like.

310 00:37:00.980 ⇒ 00:37:10.220 Uttam Kumaran: what I need to meet the people about is understand their receptiveness to certain things, and like, how do I get wins for them along the way to build up the trust

311 00:37:10.380 ⇒ 00:37:15.409 Uttam Kumaran: Because, yes, I think you and Phil both have, like, a good vision on this, but…

312 00:37:15.570 ⇒ 00:37:21.770 Uttam Kumaran: Nothing gets adopted without every character, you know, sort of, like, being on board, and…

313 00:37:22.000 ⇒ 00:37:29.639 Uttam Kumaran: I’ve seen projects like this just die because someone comes in, they’re like, rip all this out, and it’s, like, really horrible, so…

314 00:37:29.980 ⇒ 00:37:37.609 Uttam Kumaran: part of that is… that’s a lot of why, even if… for all… for all what it’s worth on the questions, I think 100%, but…

315 00:37:37.750 ⇒ 00:37:49.330 Uttam Kumaran: it’s… some of these times, it’ll just be nice for folks to hear that there are other people thinking about their problems when it comes to reporting. Totally. And that we are… we are driving towards solutions that

316 00:37:49.520 ⇒ 00:37:54.849 Uttam Kumaran: support them, and their time and their ability to achieve their goals directly, you know? And, like, saying that.

317 00:37:55.010 ⇒ 00:38:01.129 Uttam Kumaran: Sometimes people don’t… don’t… They don’t know that, or they don’t believe it happened, or also identifying, like, okay.

318 00:38:01.250 ⇒ 00:38:11.549 Uttam Kumaran: who do we need to, like, win… spend more time winning over, versus, like, if Carlos is like, I love data, it’s my favorite thing, and we don’t have to, like, worry, you know? .

319 00:38:11.740 ⇒ 00:38:14.340 Shivani Amar: Like, if you think about,

320 00:38:15.590 ⇒ 00:38:23.090 Shivani Amar: I’m just trying to think about what I show you, like, if you think about…

321 00:38:25.750 ⇒ 00:38:28.139 Shivani Amar: Trying to think about how to articulate this.

322 00:38:28.520 ⇒ 00:38:30.919 Uttam Kumaran: It’s also the culture you want to build, too, you know?

323 00:38:30.920 ⇒ 00:38:40.010 Shivani Amar: Yeah, when you paint the picture to any stakeholder, I think… Holding the vision that is of, like.

324 00:38:40.460 ⇒ 00:38:43.450 Shivani Amar: Us having a data stack that, like.

325 00:38:43.590 ⇒ 00:38:52.959 Shivani Amar: can link different parts of the business together, so that eventually we can have better supply-demand planning, so that eventually we can have, like, really clear,

326 00:38:53.070 ⇒ 00:39:02.159 Shivani Amar: So that eventually we can have, like, really clear… Velocity, kind of,

327 00:39:02.530 ⇒ 00:39:11.870 Shivani Amar: statistics across our different channels. Like, the omni-channel piece is, like, the vision I want you to hold, right? And then it’s like…

328 00:39:12.170 ⇒ 00:39:21.130 Shivani Amar: yes, we will also be helping channel by channel by channel, and that’s kind of how we’re starting, but, like, I want you to hold the omni-channel piece.

329 00:39:21.580 ⇒ 00:39:23.399 Uttam Kumaran: Okay. I see, I see what you mean.

330 00:39:23.590 ⇒ 00:39:33.770 Shivani Amar: Because it’s like, that’s where the value comes, really, for the business at large. Everybody’s getting their insights that they kind of need, they’re piecing things together. Sure, it might take them a little bit more.

331 00:39:33.770 ⇒ 00:39:43.599 Uttam Kumaran: Because you’d be surprised at how many people told me that, but then I went and talked to people, and they’re like, dude, I don’t have anything. And it’s like, oh, okay. And that’s why I’m like.

332 00:39:43.850 ⇒ 00:40:01.559 Uttam Kumaran: And I also want to be, like, give you guys the opinion after doing this a bunch of times and say, here’s what I’m seeing on the ground. Totally. But I hear you. Like, I hear you that the omnichannel piece is the… is the highest alpha piece, and it’s clear that people are finding a way to get it done today.

333 00:40:01.890 ⇒ 00:40:04.790 Uttam Kumaran: And so… Yeah, makes sense.

334 00:40:04.790 ⇒ 00:40:09.209 Shivani Amar: Yeah, and so, like, I think, like, examples of…

335 00:40:09.320 ⇒ 00:40:13.960 Shivani Amar: like, I’ve given you now enough examples, right? Which is, like, okay, like.

336 00:40:14.650 ⇒ 00:40:26.810 Shivani Amar: if, you know, is retail cannibalizing, or, like, or not? How would we answer that question, right? Is retail cannibalizing e-com? And then there’s…

337 00:40:26.960 ⇒ 00:40:41.299 Shivani Amar: why did the conversion rate on our website dip? And, like, is that just because of this? Right? These are all examples of things that, like, you could say are… like, the retail cannibalizing is omnichannel, the, like, conversion rate dipping is…

338 00:40:41.300 ⇒ 00:40:54.270 Shivani Amar: partially one channel, just, like, what’s going on across our Shopify itself, but it could be, well, we’re noticing an increase in Amazon, so are people, like, redirecting? Is there even a way for us to track that?

339 00:40:54.800 ⇒ 00:40:58.690 Shivani Amar: Amazon’s so private that maybe there’s no way for us to track it, but, like.

340 00:40:58.870 ⇒ 00:41:03.920 Shivani Amar: where are we seeing spikes in Amazon and dips in Shopify? And, like, what is the story there?

341 00:41:04.030 ⇒ 00:41:14.070 Shivani Amar: Right? Okay. So, like, that’s, like, where it all comes together, in a way, like, I’m gonna short… show you something, one second.

342 00:41:14.350 ⇒ 00:41:20.690 Shivani Amar: So James Murphy, like, our CEO, sends this out, right? Like, and he’s like.

343 00:41:21.020 ⇒ 00:41:26.479 Shivani Amar: it’s a detailed review of the financials and everything. He’s focusing right now just on, like.

344 00:41:27.320 ⇒ 00:41:30.320 Shivani Amar: He’s focusing literally on Shopify in this thing.

345 00:41:30.320 ⇒ 00:41:32.250 Uttam Kumaran: Okay, so he’s like… Yeah, thanks, thanks.

346 00:41:32.250 ⇒ 00:41:36.719 Shivani Amar: He’s like, revenues are up 15% year over year.

347 00:41:39.090 ⇒ 00:41:46.949 Shivani Amar: Net income is reporting up, like, 2X, whatever, from the dip we took last year and this time with the sales decline. Okay, fine.

348 00:41:47.200 ⇒ 00:41:56.449 Shivani Amar: It’s kind of hard… that’s a kind of hard sentence to read, in my opinion. And then he’s, like, doing a month-over-month change specifically in Shopify.

349 00:41:57.660 ⇒ 00:42:00.909 Shivani Amar: Okay? So it’s like, he’s kind of taking this, like.

350 00:42:01.360 ⇒ 00:42:08.460 Shivani Amar: cut… he’s, like, taking a more, like, negative view on things, which is fine, but he’s like, why is this? Right?

351 00:42:08.640 ⇒ 00:42:11.980 Shivani Amar: And, like, what do we need to be monitoring? Is this helpful context?

352 00:42:12.440 ⇒ 00:42:14.109 Uttam Kumaran: This is great, this is perfect.

353 00:42:14.110 ⇒ 00:42:18.620 Shivani Amar: So… so then you can see everybody’s putting their numbers in, right? Like, it’s not like…

354 00:42:18.620 ⇒ 00:42:18.970 Uttam Kumaran: Yes.

355 00:42:18.970 ⇒ 00:42:20.949 Shivani Amar: flying blind, but like…

356 00:42:20.950 ⇒ 00:42:21.640 Uttam Kumaran: Yeah, totally.

357 00:42:22.190 ⇒ 00:42:29.309 Shivani Amar: now that you’ve signed an NDA, I could probably forward you this email, but it’s, like, really detailed. So then you have people being like.

358 00:42:29.710 ⇒ 00:42:41.939 Shivani Amar: retail key accounts, like, what was my actual versus, like, for drinks, what was my sparkling? Okay, so for sparkling, I didn’t hit my target, like, why? Right? Sparkling underperformed target.

359 00:42:41.940 ⇒ 00:42:57.730 Shivani Amar: finishing a million below target, blah blah blah blah. The sharp declines in orders reflect the set order in September, and minimal replenish orders, as they had high inventories at stores coming off end cap with a large set order. And I’m like, okay, does that mean our velocity isn’t good? Does that mean our pricing isn’t good?

360 00:42:59.010 ⇒ 00:42:59.600 Uttam Kumaran: Yeah.

361 00:43:00.340 ⇒ 00:43:02.420 Uttam Kumaran: And, like, does… how does this impact the next month?

362 00:43:04.210 ⇒ 00:43:13.989 Uttam Kumaran: This is great. Okay, see, this is what I kind of… I’m just trying to get a sense of, like… you mentioned the culture. I’m trying to look at, okay, how data-driven is this company today?

363 00:43:14.150 ⇒ 00:43:14.490 Shivani Amar: Yeah.

364 00:43:14.490 ⇒ 00:43:17.490 Uttam Kumaran: And this is helpful to see, that at the top, there is…

365 00:43:17.740 ⇒ 00:43:29.040 Uttam Kumaran: there is an importance set on looking at each core metric. Each person is clearly assigned a metric. There is some level of a… not only put the metric in, but

366 00:43:29.160 ⇒ 00:43:34.540 Uttam Kumaran: But compare it to some goal, and then also give an explainer on why or why not we hit the goal.

367 00:43:35.120 ⇒ 00:43:38.950 Shivani Amar: Exactly. And so it’s like, people are on it, and that’s where it’s more like.

368 00:43:38.950 ⇒ 00:43:39.490 Uttam Kumaran: Great.

369 00:43:39.680 ⇒ 00:43:47.650 Shivani Amar: okay, it’s manual for them to get it, but they’re doing it, and, like, I’ll forward you this email, but, like, but otherwise, it’s kind of like…

370 00:43:48.110 ⇒ 00:43:50.970 Shivani Amar: You know, I think we’re.

371 00:43:50.970 ⇒ 00:43:56.840 Uttam Kumaran: Yeah, I would love to see this email and then use it to sort of… this will give me the sense of, like, what the entire… what the…

372 00:43:57.660 ⇒ 00:44:00.520 Uttam Kumaran: But the company’s looking at from an each-channel perspective.

373 00:44:00.930 ⇒ 00:44:01.630 Shivani Amar: Yeah.

374 00:44:05.330 ⇒ 00:44:07.990 Shivani Amar: And, like, it’s super detailed. And then…

375 00:44:08.100 ⇒ 00:44:10.959 Shivani Amar: Okay, I don’t wanna share…

376 00:44:10.960 ⇒ 00:44:11.990 Uttam Kumaran: You don’t have to… yeah.

377 00:44:12.340 ⇒ 00:44:23.380 Shivani Amar: don’t do that, but, like, at least the email itself is super helpful, and it’s, like, a clipped message, it’s so long, and then you can say, okay, I’m talking to e-commerce people, like.

378 00:44:23.380 ⇒ 00:44:26.320 Uttam Kumaran: How do you feel when you read this? Or when you’ve gone this?

379 00:44:26.320 ⇒ 00:44:27.599 Shivani Amar: Joel, when I read this.

380 00:44:28.100 ⇒ 00:44:32.999 Shivani Amar: I’m like, we’re being thorough to some extent, but I think the, like.

381 00:44:34.240 ⇒ 00:44:39.529 Shivani Amar: The part that, people struggle with is the why.

382 00:44:39.730 ⇒ 00:44:41.529 Shivani Amar: I don’t know if that makes sense, but it’s like…

383 00:44:41.530 ⇒ 00:44:43.669 Uttam Kumaran: No, that’s the only… that’s the only thing that matters, yeah.

384 00:44:43.670 ⇒ 00:44:44.569 Shivani Amar: Yeah, so.

385 00:44:44.570 ⇒ 00:44:45.469 Uttam Kumaran: Of course, yeah.

386 00:44:45.470 ⇒ 00:44:50.950 Shivani Amar: So if you think about, let’s see… Revenue, revenue.

387 00:44:50.950 ⇒ 00:44:55.569 Uttam Kumaran: It’s the why, and, like, can we do something, yes or no? Or, like, what are we doing?

388 00:44:56.450 ⇒ 00:45:06.169 Shivani Amar: So, customer journey… I’m like, hold on, where is the conversion?

389 00:45:06.170 ⇒ 00:45:08.449 Uttam Kumaran: And this is produced during REST and Assess.

390 00:45:08.650 ⇒ 00:45:10.100 Shivani Amar: Y.

391 00:45:10.100 ⇒ 00:45:10.690 Uttam Kumaran: Or, like.

392 00:45:11.560 ⇒ 00:45:20.250 Shivani Amar: Kind of, I think, or it’s, like, maybe… it was produced at the… no, it was produced, the middle of the sprint.

393 00:45:22.040 ⇒ 00:45:25.150 Shivani Amar: Yeah, it… I think it, like, depends on, like.

394 00:45:25.280 ⇒ 00:45:34.260 Shivani Amar: dates, and this is always, like… you see he sent this email, like, November 16th for October, so it takes time for people to, like, close the month and…

395 00:45:34.260 ⇒ 00:45:34.740 Uttam Kumaran: Yeah.

396 00:45:34.740 ⇒ 00:45:37.549 Shivani Amar: Stuff like that. And then,

397 00:45:37.860 ⇒ 00:45:41.400 Shivani Amar: I’m like, where is conversion rate? Okay.

398 00:45:44.390 ⇒ 00:45:45.080 Uttam Kumaran: Yeah, dude.

399 00:45:45.380 ⇒ 00:45:52.179 Shivani Amar: drives, like, customer acquisition costs, higher session volume help maintain spend efficiency.

400 00:45:52.180 ⇒ 00:45:59.119 Uttam Kumaran: Do you feel like it, to some degree, it’s, like, performative responses in that, like, I just gotta put something down that, like.

401 00:46:00.120 ⇒ 00:46:01.689 Uttam Kumaran: Makes sense.

402 00:46:01.950 ⇒ 00:46:19.310 Shivani Amar: No, I don’t think it’s performative, but I think if you’re like, cool, cool, cool, like, why did the conversion rate… it’s like, I’m gonna have to go into, like, these 100 data points to try and figure it out, versus, like, to me, what this… like, my feeling on this is, like, what are our top-level metrics, and then what are our second-order questions?

403 00:46:19.310 ⇒ 00:46:23.429 Uttam Kumaran: This is what I’m gonna use to build, yeah, so this is… I’m gonna basically start the…

404 00:46:23.630 ⇒ 00:46:26.339 Uttam Kumaran: Metrics glossary from this document.

405 00:46:27.330 ⇒ 00:46:28.629 Shivani Amar: And then it’s like…

406 00:46:28.890 ⇒ 00:46:48.489 Shivani Amar: okay, well, where, like, if conversion rate, like, to your point, if conversion rate is a top-level metric, then maybe this is, like, a level 2. I always say level 1, level 2 metrics, but, like, this is level 2. And then it’s, like, this is your double-click into your conversion rate. But then you could easily see, like, what, like, what are the components of my conversion rate, and, like.

407 00:46:48.650 ⇒ 00:46:59.970 Shivani Amar: where is the thing having a spike versus a drop? And, like, where in the funnel is it breaking? And so, like, that’s, like, the next level that I’m kind of, like, looking for.

408 00:47:00.380 ⇒ 00:47:01.010 Uttam Kumaran: Okay.

409 00:47:01.010 ⇒ 00:47:05.879 Shivani Amar: For… and, like, you can ignore right now, like, supply chain stuff, right? You’re like, that doesn’t…

410 00:47:06.180 ⇒ 00:47:11.510 Shivani Amar: That doesn’t, like, that’s not what we’re touching, but anything that’s, like,

411 00:47:12.310 ⇒ 00:47:20.899 Shivani Amar: anything that is, like, BizOps is also whatever, like, anything that is just on the revenue side, I think, is where you’ll be.

412 00:47:21.470 ⇒ 00:47:22.800 Shivani Amar: Curious to…

413 00:47:23.600 ⇒ 00:47:24.130 Uttam Kumaran: Yeah.

414 00:47:24.440 ⇒ 00:47:26.399 Shivani Amar: Understand, like, what’s going on.

415 00:47:28.030 ⇒ 00:47:44.100 Shivani Amar: And, like, look at this. It’s like, right? Wholesale revenue was down in drink mix relative to Target. Now, we see seasonality in the business. We’re still 15% up year over year in terms of revenue. So it’s like, is that a problem? Right? Like, we miss Target.

416 00:47:44.540 ⇒ 00:47:50.440 Shivani Amar: sorry, missed target, not MISS. Did we, like, did we target incorrectly?

417 00:47:51.060 ⇒ 00:47:51.750 Uttam Kumaran: Yes.

418 00:47:52.010 ⇒ 00:47:55.839 Uttam Kumaran: Did we target incorrectly, or is it that, like.

419 00:47:56.060 ⇒ 00:47:58.310 Shivani Amar: the…

420 00:47:59.060 ⇒ 00:48:06.850 Shivani Amar: the miss was, like, really large, and our wholesale partner is, like, sitting there, like, oh my god, why did we miss so hard?

421 00:48:06.850 ⇒ 00:48:07.540 Uttam Kumaran: Yeah, yeah, yeah.

422 00:48:07.540 ⇒ 00:48:13.089 Shivani Amar: But I think we were all just kind of like, seasonality, we’re up year over year, so, like, is this a problem or not?

423 00:48:13.090 ⇒ 00:48:13.430 Uttam Kumaran: Yeah.

424 00:48:13.430 ⇒ 00:48:16.300 Shivani Amar: So even, like, the red, yellow, red, yellow, I’m like.

425 00:48:16.530 ⇒ 00:48:20.550 Shivani Amar: How do we actually… to me, like, the questions are, how do we actually feel

426 00:48:20.790 ⇒ 00:48:27.990 Shivani Amar: which is a weird one, but, like, that’s what I want to know. How do we actually feel about these metrics versus just saying where we are versus not?

427 00:48:28.150 ⇒ 00:48:35.330 Shivani Amar: And then, where do we feel like we need to be, like, having the next level of understanding the why, and we currently don’t…

428 00:48:35.450 ⇒ 00:48:38.099 Shivani Amar: Trust the data, or know the data, or whatever.

429 00:48:38.480 ⇒ 00:48:43.269 Shivani Amar: And do we feel like we’re telling the right overarching story? That’s, like, the very macro question.

430 00:48:43.920 ⇒ 00:48:50.359 Uttam Kumaran: So I guess for you, how interested are you in, from each of these interviews, to ask those people

431 00:48:50.500 ⇒ 00:48:51.920 Uttam Kumaran: that question.

432 00:48:51.920 ⇒ 00:48:56.599 Shivani Amar: Totally, like, when we meet with Laura, I kind of want to be like, I want to ask her, like.

433 00:48:56.800 ⇒ 00:49:00.619 Shivani Amar: how do you feel about how you set targets? How do you feel about the actuals, right?

434 00:49:00.620 ⇒ 00:49:01.070 Uttam Kumaran: Oh, okay.

435 00:49:01.070 ⇒ 00:49:18.209 Shivani Amar: That’s exactly where I’m kind of like, how do you feel about the actuals? How do you feel about the targets? Where are you flying blind? Where do you feel like you need more visibility? And, like, some of it, she kind of told me, she’s right, she’s like, I want to know when people are making their first purchase, third purchase, who are our top wholesalers, like, what we should be doing.

436 00:49:18.210 ⇒ 00:49:26.890 Shivani Amar: differently, blah blah blah, right? Like, this is, like, Laura’s download. So she’s given me a sense of it, but it’s, like, looking at this actual, where do you feel like

437 00:49:26.920 ⇒ 00:49:29.340 Shivani Amar: Where do you feel like you need to be spending your time?

438 00:49:29.920 ⇒ 00:49:30.510 Uttam Kumaran: Yes.

439 00:49:31.030 ⇒ 00:49:32.210 Shivani Amar: Does that help?

440 00:49:32.560 ⇒ 00:49:33.310 Uttam Kumaran: Yes, yes.

441 00:49:33.310 ⇒ 00:49:34.490 Shivani Amar: Cool. Okay.

442 00:49:35.030 ⇒ 00:49:37.690 Uttam Kumaran: Okay, so I kind of have a much better sense of, like.

443 00:49:38.350 ⇒ 00:49:40.000 Awaish Kumar: How things are…

444 00:49:40.500 ⇒ 00:49:41.689 Uttam Kumaran: I mean, this is great.

445 00:49:42.310 ⇒ 00:49:54.990 Shivani Amar: Cool. Okay, great. Well, like, if you… like, I’m like, it’s Thanksgiving, so it’s like, yeah, like, if you’re working on discovery questions on Monday, like, fine, right? Like, I’m like, I don’t know what your structure and flow is.

446 00:49:55.370 ⇒ 00:50:04.679 Uttam Kumaran: No, we’re gonna… I’m gonna… we’ll work on things, we’ll work on things today. Like, I’m gonna work on things right after this, yeah. And I just want, like, I just wanted to share that it’s not purely, like.

447 00:50:05.150 ⇒ 00:50:21.299 Uttam Kumaran: this question, this question, it’s a… it is a little bit of, like, under… like, going down some rabbit holes with some of these people, and… and understanding them walk through how… how do you… how would you answer this question? Like, what is… like, understanding their motivations, but also me learning about

448 00:50:21.500 ⇒ 00:50:24.260 Uttam Kumaran: the culture of, like, Element, right? Because I don’t have the.

449 00:50:24.260 ⇒ 00:50:24.580 Shivani Amar: Yeah.

450 00:50:24.580 ⇒ 00:50:26.459 Uttam Kumaran: I don’t have the insights yet, so…

451 00:50:26.460 ⇒ 00:50:31.189 Shivani Amar: I just messed this up. I wanted this to be an hour. Okay, wait, let me see if I can…

452 00:50:31.650 ⇒ 00:50:36.399 Shivani Amar: Cancel, whatever I just did with Chase. Booked a meeting…

453 00:50:37.430 ⇒ 00:50:42.630 Shivani Amar: I don’t even… I’m like, what is this platform that he’s using for calendaring? .

454 00:50:42.630 ⇒ 00:50:43.630 Uttam Kumaran: The HubSpot?

455 00:50:44.290 ⇒ 00:50:45.749 Shivani Amar: I don’t… what is it?

456 00:50:47.020 ⇒ 00:50:47.640 Shivani Amar: It’s like…

457 00:50:47.640 ⇒ 00:50:52.800 Uttam Kumaran: New Hero. We have another… we have… one of our clients is, like, a big competitor in these class.

458 00:50:52.800 ⇒ 00:51:02.369 Shivani Amar: Yeah, I’m like, this website is… oh, it is HubSpot. Oh, God. Okay. So now I… I’m like, I don’t even know how to cancel it. So, I’m gonna book it for an hour.

459 00:51:02.490 ⇒ 00:51:08.980 Shivani Amar: Let me try that again. Let me just… December 1st.

460 00:51:09.430 ⇒ 00:51:11.540 Shivani Amar: Let’s just say 1 o’clock.

461 00:51:11.680 ⇒ 00:51:15.780 Shivani Amar: And then canceled the other one, so… Both on that.

462 00:51:16.280 ⇒ 00:51:28.510 Shivani Amar: Brainforge.ai… And then… wish dot… Kamar?

463 00:51:29.710 ⇒ 00:51:30.480 Awaish Kumar: Yep.

464 00:51:30.770 ⇒ 00:51:33.020 Shivani Amar: at Brainforge.ai.

465 00:51:33.760 ⇒ 00:51:35.090 Shivani Amar: Let’s try that again.

466 00:51:37.720 ⇒ 00:51:39.220 Shivani Amar: Hopefully that works.

467 00:51:40.580 ⇒ 00:51:47.679 Shivani Amar: Let’s see. Okay, and then… so, let me decline this. Sorry, buddy. Okay.

468 00:51:48.100 ⇒ 00:51:56.489 Shivani Amar: And then, like, let’s look at Jason’s calendar really quickly. So, this is Jason’s flow for next week. I’m like, should we just do…

469 00:51:56.980 ⇒ 00:52:00.040 Shivani Amar: an hour with Jason to start off on either the.

470 00:52:00.040 ⇒ 00:52:04.099 Uttam Kumaran: Yeah, if Jason’s like, yeah, I just need to talk to him about…

471 00:52:04.670 ⇒ 00:52:07.120 Uttam Kumaran: Yeah, I have a bunch of technical questions.

472 00:52:07.300 ⇒ 00:52:09.910 Uttam Kumaran: And to also ask him about his vision for this.

473 00:52:10.110 ⇒ 00:52:11.020 Shivani Amar: You wanna do…

474 00:52:11.020 ⇒ 00:52:12.840 Uttam Kumaran: Security and things like that.

475 00:52:13.880 ⇒ 00:52:15.440 Shivani Amar: Do you want to do 2PM?

476 00:52:15.940 ⇒ 00:52:16.580 Uttam Kumaran: Yeah.

477 00:52:17.040 ⇒ 00:52:17.670 Shivani Amar: Okay.

478 00:52:19.600 ⇒ 00:52:21.840 Shivani Amar: Brain Forge…

479 00:52:27.940 ⇒ 00:52:28.630 Shivani Amar: And then you’ll have.

480 00:52:28.630 ⇒ 00:52:32.680 Uttam Kumaran: And then I… is Jason someone, like, we can have? And he’s already in our Slack, so I assume…

481 00:52:33.000 ⇒ 00:52:37.279 Uttam Kumaran: Both of y’all are, like, good points of contact, like, you won’t worry about getting spammed.

482 00:52:37.390 ⇒ 00:52:41.040 Uttam Kumaran: I’m not spamming, but, like, we’ll be hitting you guys up for stuff.

483 00:52:41.040 ⇒ 00:52:41.710 Shivani Amar: Yeah.

484 00:52:42.060 ⇒ 00:52:42.810 Shivani Amar: So…

485 00:52:42.810 ⇒ 00:52:49.740 Uttam Kumaran: how involved is… so he’s gonna be involved in all, like, vendor decisions. How do you see his involvement on, like, the…

486 00:52:50.240 ⇒ 00:52:54.629 Uttam Kumaran: like, KPI, like, KPI strategy, and, like, or where do you see his purview?

487 00:52:54.630 ⇒ 00:52:56.640 Shivani Amar: API strategy is more me.

488 00:52:56.840 ⇒ 00:52:57.460 Uttam Kumaran: Okay.

489 00:52:57.460 ⇒ 00:53:00.329 Shivani Amar: I think stack is, like, his input.

490 00:53:00.470 ⇒ 00:53:01.560 Uttam Kumaran: Great. And…

491 00:53:01.730 ⇒ 00:53:06.319 Shivani Amar: kPIs is more me and Phil.

492 00:53:06.730 ⇒ 00:53:07.560 Uttam Kumaran: Okay, okay, great.

493 00:53:07.840 ⇒ 00:53:08.460 Shivani Amar: Yeah.

494 00:53:09.320 ⇒ 00:53:12.749 Shivani Amar: So, like, for your discovery with him, it’s more like…

495 00:53:13.960 ⇒ 00:53:19.129 Uttam Kumaran: I just want to know how it’s… what are all the tools, like, how it’s been done, talking about procurement.

496 00:53:19.250 ⇒ 00:53:21.940 Shivani Amar: And, like, hearing about security, and then…

497 00:53:22.310 ⇒ 00:53:32.940 Uttam Kumaran: sort of see, like… yeah, I wanna… and I wanna… I wanna make sure also, like, as we’re… I wanna impart all the… all our… all our knowledge on our, like, sort of selecting stuff, and why.

498 00:53:33.250 ⇒ 00:53:33.900 Shivani Amar: Perfect.

499 00:53:34.320 ⇒ 00:53:34.949 Shivani Amar: Yeah, I love it.

500 00:53:34.950 ⇒ 00:53:37.319 Uttam Kumaran: We’ll make keys, we’ll make keys and everything, so…

501 00:53:37.670 ⇒ 00:53:38.530 Shivani Amar: Exactly.

502 00:53:38.660 ⇒ 00:53:45.060 Shivani Amar: Cool, dude. Okay, so, yeah, look, I… I get the…

503 00:53:45.660 ⇒ 00:53:54.759 Shivani Amar: the… we don’t really start the work until December 1st, but I think, like, the more we can have the discovery questions, and then I can help calendar, like… but just so you know, I’m like.

504 00:53:54.990 ⇒ 00:54:02.560 Shivani Amar: I can put a hold on, like, Carlos’ calendar for next Friday, you know? Like, I can do that now, if you want to do some…

505 00:54:02.720 ⇒ 00:54:08.440 Shivani Amar: Calendaring while we’re on… together, like, I’m looking at his calendar.

506 00:54:08.880 ⇒ 00:54:10.580 Uttam Kumaran: I would like that. That’s…

507 00:54:10.580 ⇒ 00:54:17.099 Shivani Amar: December… Fifth… that… noon Pacific time.

508 00:54:20.790 ⇒ 00:54:23.830 Uttam Kumaran: Can we do… Juan?

509 00:54:24.470 ⇒ 00:54:25.740 Shivani Amar: No, he’s busy then.

510 00:54:26.760 ⇒ 00:54:34.019 Shivani Amar: But we could do… so 2 Pacific time is 5 for me, so that’s not ideal. What about your Thursday?

511 00:54:35.170 ⇒ 00:54:37.150 Uttam Kumaran: There’s, much more open.

512 00:54:37.840 ⇒ 00:54:42.539 Shivani Amar: So, Thursday we could do… 10 a.m. Pacific.

513 00:54:42.650 ⇒ 00:54:44.599 Shivani Amar: for an hour with Carlos.

514 00:54:46.370 ⇒ 00:54:46.980 Uttam Kumaran: Okay.

515 00:54:47.320 ⇒ 00:54:55.250 Shivani Amar: Okay, so, okay, Brain Forge… Data, X, Carlos…

516 00:54:55.770 ⇒ 00:55:00.229 Shivani Amar: Discovery. And I’ll just do it for an hour, and then we can always set up more time.

517 00:55:01.490 ⇒ 00:55:03.149 Shivani Amar: So let me do that.

518 00:55:04.790 ⇒ 00:55:06.330 Shivani Amar: And then…

519 00:55:06.330 ⇒ 00:55:12.710 Uttam Kumaran: And then I’m gonna set… I’ll set a weekly… with you… Mia, Wish.

520 00:55:15.030 ⇒ 00:55:15.820 Uttam Kumaran: Jason?

521 00:55:16.490 ⇒ 00:55:17.050 Shivani Amar: sick.

522 00:55:17.430 ⇒ 00:55:18.270 Shivani Amar: And then…

523 00:55:18.470 ⇒ 00:55:20.429 Uttam Kumaran: on Thursdays, if that’s okay?

524 00:55:21.120 ⇒ 00:55:23.760 Shivani Amar: Yeah, I think we had talked about, like, 2PM, right?

525 00:55:23.760 ⇒ 00:55:24.630 Uttam Kumaran: Yeah, yeah.

526 00:55:24.970 ⇒ 00:55:32.120 Shivani Amar: And then Laura, the wholesale person, like, if you’re like, hey, I’d rather just get, like, back-to-back kind of, like.

527 00:55:33.910 ⇒ 00:55:53.900 Shivani Amar: I’d rather get back-to-back on, like, e-com and wholesale. If you’re like, no, I just want to think about e-commerce first week, like, you tell me what makes sense for you guys. If you’re like, Shopify data is in wholesale, like, sorry, wholesale data is in Shopify anyway, might as well get that download. Then you tell me, like, do you want to talk to Laura next week?

528 00:55:54.900 ⇒ 00:55:56.740 Uttam Kumaran: Let me talk to Carlos.

529 00:55:57.030 ⇒ 00:55:59.629 Uttam Kumaran: I want to talk to Laura before Christmas.

530 00:56:00.780 ⇒ 00:56:04.289 Uttam Kumaran: Totally. For sure. So do you want to do it the week after? Like, do you want to do it.

531 00:56:04.530 ⇒ 00:56:09.529 Shivani Amar: the… I can set up time for us for, like, December 9th or something.

532 00:56:09.750 ⇒ 00:56:10.330 Uttam Kumaran: Yeah.

533 00:56:10.630 ⇒ 00:56:15.570 Shivani Amar: Okay. Because by that point, I’ll be in… I’ll be in Shopify, ideally, by the time I meet Carlos.

534 00:56:16.090 ⇒ 00:56:20.959 Uttam Kumaran: And then… I’ll… Carlos will kind of give me a big lay of the land, and then…

535 00:56:21.460 ⇒ 00:56:24.770 Uttam Kumaran: I’ll… I’ll start to understand, like, SKUs, and…

536 00:56:25.550 ⇒ 00:56:30.340 Uttam Kumaran: generally have a good sense of, like, KPIs, and then I can talk to… about wholesale.

537 00:56:30.830 ⇒ 00:56:38.750 Shivani Amar: What about… do you want to do partnerships before wholesale? Because that’s all about, like, how our partnerships data generates revenue in Shopify?

538 00:56:39.900 ⇒ 00:56:44.659 Uttam Kumaran: I think it’s… they’re… it’s either or. They’re both… they’re both distinct, so…

539 00:56:44.950 ⇒ 00:56:47.940 Shivani Amar: Okay, so let’s do… December 9th.

540 00:56:47.940 ⇒ 00:56:49.879 Uttam Kumaran: One is, like, demand, you know.

541 00:56:50.500 ⇒ 00:56:54.429 Shivani Amar: Yeah, so let’s do December 9th with Blake. How does.

542 00:56:54.900 ⇒ 00:56:59.700 Uttam Kumaran: I’m actually less concerned about the…

543 00:57:00.290 ⇒ 00:57:04.699 Uttam Kumaran: partners’ marketing stuff, because it is marketing sources, like, we’re…

544 00:57:04.990 ⇒ 00:57:08.350 Uttam Kumaran: This is… we’ve seen… we’ve seen this a couple times.

545 00:57:08.500 ⇒ 00:57:10.730 Uttam Kumaran: the Shopify thing will be very unique.

546 00:57:11.690 ⇒ 00:57:13.580 Uttam Kumaran: A little bit more unique.

547 00:57:13.730 ⇒ 00:57:18.010 Uttam Kumaran: So… I would probably put the marketing thing last.

548 00:57:19.200 ⇒ 00:57:24.239 Shivani Amar: Okay, so you… when you say the Shopify thing will be unique, you mean wholesale, or what do you mean?

549 00:57:24.240 ⇒ 00:57:28.479 Uttam Kumaran: Yeah, like, basically how you sell within Shopify and Amazon

550 00:57:28.630 ⇒ 00:57:31.740 Uttam Kumaran: There… there is a lot more opportunity for, like.

551 00:57:32.240 ⇒ 00:57:37.650 Uttam Kumaran: like, there’s a lot more discovery there. I will… I’ll learn a lot by going through the spreadsheet for marketing, and then…

552 00:57:37.750 ⇒ 00:57:38.990 Shivani Amar: Main, like…

553 00:57:38.990 ⇒ 00:57:43.649 Uttam Kumaran: Reconciling this, I just want to do that last, basically.

554 00:57:44.720 ⇒ 00:57:50.749 Uttam Kumaran: But I also want to understand from Carlos and from Jose, like, what… what are they looking at from the demand side?

555 00:57:50.890 ⇒ 00:57:52.839 Uttam Kumaran: And then I can talk about…

556 00:57:53.960 ⇒ 00:58:01.139 Uttam Kumaran: from the… from the ad buying and the marketing buying side, how is… how is she thinking about that when it drives sales?

557 00:58:01.480 ⇒ 00:58:03.989 Shivani Amar: Okay, and then, so, how about…

558 00:58:03.990 ⇒ 00:58:07.160 Uttam Kumaran: First touch, last touch, like… Yeah.

559 00:58:07.370 ⇒ 00:58:10.579 Shivani Amar: 11 a.m. Pacific on Tuesday, December 9th.

560 00:58:12.530 ⇒ 00:58:13.820 Uttam Kumaran: Yeah, perfect.

561 00:58:14.060 ⇒ 00:58:14.920 Shivani Amar: Okay.

562 00:58:15.430 ⇒ 00:58:26.270 Shivani Amar: And then… Let me put Blake on for the week after, then. Okay?

563 00:58:27.860 ⇒ 00:58:29.090 Shivani Amar: Bing.

564 00:58:29.410 ⇒ 00:58:34.320 Shivani Amar: How about… 10 a.m. Pacific on Tuesday the 16th.

565 00:58:39.140 ⇒ 00:58:48.360 Shivani Amar: Okay, partnerships… Then… put, OH… Okay, cool.

566 00:58:48.880 ⇒ 00:58:50.439 Shivani Amar: And, like, once I.

567 00:58:50.440 ⇒ 00:58:51.100 Uttam Kumaran: Know what…

568 00:58:51.330 ⇒ 00:58:51.909 Shivani Amar: Yeah, go ahead.

569 00:58:51.910 ⇒ 00:58:53.360 Uttam Kumaran: Yeah, go ahead. Go ahead, go ahead.

570 00:58:54.190 ⇒ 00:59:14.020 Shivani Amar: Once I see your discovery questions, I’ll figure out if you need time with Will, but his calendar is crazy, and so he basically… I pinged him, and he was like, do you think it would be beneficial for me to meet them? And I was like, let me see what their questions are. That’s what I told him. Okay, cool. Right? So, I’m like, I don’t want to just put time unless… That’s fine. Yeah.

571 00:59:15.290 ⇒ 00:59:16.730 Shivani Amar: Let’s see…

572 00:59:16.730 ⇒ 00:59:25.000 Uttam Kumaran: So, by… and then, I guess, to also talk about, like, timing, by… by, thus before Christmas.

573 00:59:25.390 ⇒ 00:59:26.800 Uttam Kumaran: Like, it would be great.

574 00:59:26.930 ⇒ 00:59:31.829 Uttam Kumaran: To start talking about, like, data ingestion tool.

575 00:59:32.310 ⇒ 00:59:40.460 Uttam Kumaran: So, as part of our weekly meetings, we’ll do a little bit of a download of, like, what we learned from the stakeholders, and

576 00:59:40.740 ⇒ 00:59:44.740 Uttam Kumaran: I wanna also… Basically, spend time on the stack.

577 00:59:44.940 ⇒ 00:59:49.880 Uttam Kumaran: We’re finding that, yeah, it will… it may…

578 00:59:50.290 ⇒ 00:59:54.129 Uttam Kumaran: Depending on the volume, it may take a week or two to sync everything, so…

579 00:59:55.760 ⇒ 01:00:09.309 Shivani Amar: I think that’s perfect. And so I think that Thursday, 2PM with me, you, and Jason is, like, the perfect place to, like, bring that forward. And I, like, commented at Phil and Jason. I was like, Phil.

580 01:00:09.310 ⇒ 01:00:22.110 Shivani Amar: if you have familiarity with Snowflake, do you want to just go with that, or do you feel like you want to do a thorough assessment here? And so I’ll see what he says, but, like, if you’re kind of like, hey, I think we should go with…

581 01:00:22.300 ⇒ 01:00:32.890 Shivani Amar: X and Y, and here’s Y. In e-commerce, I’ve seen it work well, like, just feel free to, like… yes, you have your comparison tables, but try to make it, like, more tailored to element, like, based off of.

582 01:00:32.890 ⇒ 01:00:42.200 Uttam Kumaran: Yeah, yeah, yeah. And no, I’ll give you guys… I’ll… I… we can go as deep. I’ll give you… when we talk about ETL and the different tools, I’ll give you the high level.

583 01:00:42.350 ⇒ 01:00:46.200 Uttam Kumaran: If you have… if we need to go one layer deeper, we’ll keep going.

584 01:00:46.550 ⇒ 01:00:46.940 Shivani Amar: Perfect.

585 01:00:46.940 ⇒ 01:00:55.250 Uttam Kumaran: feel… until we feel comfortable. And we’re not, like… we… the… the thing I want to keep till the end is, like, talk to as least… as…

586 01:00:55.630 ⇒ 01:01:03.479 Uttam Kumaran: It’s basically spend as least time in vendor conversations, like, talking to them and, like, having to deal with them, so it’s, like, the worst.

587 01:01:03.840 ⇒ 01:01:11.439 Shivani Amar: So I want us to talk internally and have a decision, because when we go to them, it’s like a, hey, give me this price at this discount, and here’s what we want.

588 01:01:11.670 ⇒ 01:01:21.620 Uttam Kumaran: And, like, see a… and, like, so we can move past. Otherwise, they’ll just waste a lot of time and ask to get everybody on a call and do demos and crap, so…

589 01:01:24.360 ⇒ 01:01:31.259 Uttam Kumaran: And so, yeah, when I… and this is where also, like, I… I know we were texting about, like, SQL versus Python, so just ask any question

590 01:01:31.390 ⇒ 01:01:39.999 Uttam Kumaran: that comes to mind on any tool on, like, cases, or, you know, how it would handle, I’ll…

591 01:01:40.410 ⇒ 01:01:58.609 Uttam Kumaran: if… yeah, and we’ll totally share… all of our recommendations come from our experiences, like, we’re… we’re not recommending any tools we don’t use all the time, so… Yeah. But there will be trade-offs. This is where, for me, learning from Jason, I’m like, okay, what are budgets? How do you procure? What are security constraints?

592 01:01:58.890 ⇒ 01:02:06.570 Uttam Kumaran: And, like, his understanding, like, where he is at with, like, procurement and setup versus, like, where he wants to be will help me

593 01:02:06.980 ⇒ 01:02:10.290 Uttam Kumaran: That’ll also help me build a criteria for certain tools.

594 01:02:10.290 ⇒ 01:02:15.289 Shivani Amar: That’s perfect. And, like, if you are able to be, like, in Slack, like.

595 01:02:15.750 ⇒ 01:02:18.270 Shivani Amar: like, what I’m picturing is almost like a…

596 01:02:18.900 ⇒ 01:02:22.680 Shivani Amar: I don’t know, Word document or something, like, and it’s just, like.

597 01:02:22.790 ⇒ 01:02:27.220 Shivani Amar: discovery questions, and it’s like, Jason, and then you have a few bullet points for him, for.

598 01:02:27.220 ⇒ 01:02:27.540 Uttam Kumaran: I guess.

599 01:02:27.540 ⇒ 01:02:34.240 Shivani Amar: and one Carlos, and then I can, like, kind of just share that with people, and I’m like, hey, this is what to expect. Then that’s… that’s just like a…

600 01:02:34.420 ⇒ 01:02:37.760 Shivani Amar: Great way for Jason to know what to come in with.

601 01:02:38.360 ⇒ 01:02:40.499 Uttam Kumaran: Great, I’m gonna put that all in the data calls.

602 01:02:40.840 ⇒ 01:02:41.850 Uttam Kumaran: Perfect. Wow.

603 01:02:42.970 ⇒ 01:02:45.330 Shivani Amar: Thanks, dude. Okay, thank you.

604 01:02:45.610 ⇒ 01:02:46.020 Uttam Kumaran: Thank you.

605 01:02:46.020 ⇒ 01:02:48.350 Shivani Amar: You wish, anything else with them?

606 01:02:48.560 ⇒ 01:02:50.380 Uttam Kumaran: No, what’s the Thanksgiving plan?

607 01:02:50.600 ⇒ 01:02:54.379 Shivani Amar: We have, like, 25 people coming over to our parents… my parents’ house.

608 01:02:54.700 ⇒ 01:02:56.290 Shivani Amar: Thursday. Or on Thursday, sorry.

609 01:02:56.290 ⇒ 01:02:57.590 Uttam Kumaran: Oh, that’s wonderful.

610 01:02:57.590 ⇒ 01:03:01.409 Shivani Amar: I need to bounce back, I’m just, like, horizontal all day today.

611 01:03:03.550 ⇒ 01:03:06.080 Uttam Kumaran: making this joke, but you gotta pound some element, dude.

612 01:03:06.080 ⇒ 01:03:10.780 Shivani Amar: Yeah, that’s true. I should have. I haven’t had any today. I’ve just been, like…

613 01:03:10.780 ⇒ 01:03:11.350 Uttam Kumaran: Ugh.

614 01:03:11.350 ⇒ 01:03:12.870 Shivani Amar: been a blog.

615 01:03:12.870 ⇒ 01:03:14.500 Uttam Kumaran: That’s… you need the magnesium.

616 01:03:14.500 ⇒ 01:03:23.539 Shivani Amar: Yeah, I haven’t actually, like… yeah, I’m like, my mom was like, we have emergency, and I was like, oh, I guess I could take that. But yeah, gotta get Element in the mix!

617 01:03:24.780 ⇒ 01:03:25.989 Shivani Amar: My girlfriend’s been sick.

618 01:03:25.990 ⇒ 01:03:40.200 Uttam Kumaran: Yeah, my parents and my sister are visiting, but my sister also has a fever right now, so I’m having her pound. Like, I have a bunch of, like, vitamin elixirs at the house, so I’m like, okay, take this, take this, take this.

619 01:03:40.330 ⇒ 01:03:53.260 Uttam Kumaran: Zycam every 4 hours. And then my girlfriend was sick, one of her… one of her clients was super sick and got her sick, so she’s gotten better too, but we’re all going to my girlfriend’s house for Thanksgiving. There should be also, like.

620 01:03:53.610 ⇒ 01:03:54.950 Uttam Kumaran: 20 people there?

621 01:03:54.950 ⇒ 01:03:55.840 Shivani Amar: Yeah.

622 01:03:56.580 ⇒ 01:03:57.970 Uttam Kumaran: I’m gonna try to make pumpkin pie.

623 01:03:57.970 ⇒ 01:03:58.700 Shivani Amar: reading.

624 01:03:59.490 ⇒ 01:04:03.529 Uttam Kumaran: This is… no, they’ve… they’ve met before. They met last Christmas.

625 01:04:03.840 ⇒ 01:04:05.059 Shivani Amar: Okay, cool.

626 01:04:05.320 ⇒ 01:04:06.000 Uttam Kumaran: Yeah.

627 01:04:06.110 ⇒ 01:04:09.940 Uttam Kumaran: They get along, that’s good, but I’m actually glad, because I don’t want to talk to…

628 01:04:10.060 ⇒ 01:04:12.619 Uttam Kumaran: I don’t want to talk to any of either of them, so…

629 01:04:12.620 ⇒ 01:04:13.230 Shivani Amar: Yeah.

630 01:04:13.430 ⇒ 01:04:18.779 Uttam Kumaran: I’m gonna make pumpkin pie, and drink wine, yeah.

631 01:04:21.630 ⇒ 01:04:23.520 Shivani Amar: For you to go ring shopping.

632 01:04:23.520 ⇒ 01:04:31.330 Uttam Kumaran: Yeah, you should bring that up to her. She’s like, she’s like, yeah, she’s like, yesterday we went to dinner, she’s like.

633 01:04:31.910 ⇒ 01:04:39.730 Uttam Kumaran: is… are you even thinking about it? Like, do you even think about anything but work? And I’m like, dude, why do you, like… we’re in the middle of things, like…

634 01:04:39.730 ⇒ 01:04:42.530 Shivani Amar: No, no, no, no, that’s a very standard question, you gotta, you gotta.

635 01:04:42.530 ⇒ 01:04:49.379 Uttam Kumaran: No, I know, I know. I don’t mind. I don’t mind getting him the questions. I can… I can… I can dodge and dip, you know?

636 01:04:49.830 ⇒ 01:04:50.479 Shivani Amar: You’re like.

637 01:04:50.480 ⇒ 01:04:59.270 Uttam Kumaran: I went and got her a great… I got her some great jewelry from Kendra Scott for her birthday. Yeah. And so that bought me some time. Okay.

638 01:05:01.470 ⇒ 01:05:19.290 Shivani Amar: Alright, well, thanks, guys. I look forward to looking at these discovery questions, and then, yeah, like, we’ll definitely get conversations set up. It was helpful to talk through it, but as you start looking through the emails and stuff, like, feel free to ping me if you’re like, what does this thing mean? And I’m still figuring it out myself, too, but we can figure it out together, okay?

639 01:05:19.290 ⇒ 01:05:21.149 Uttam Kumaran: Okay, okay, perfect. Alright, feel better.

640 01:05:21.150 ⇒ 01:05:22.840 Shivani Amar: Enjoy your Thanksgiving. Bye, guys.

641 01:05:22.840 ⇒ 01:05:24.109 Uttam Kumaran: You too. Bye.