Meeting Title: Brainforge x Hydra Project Sync Date: 2026-02-12 Meeting participants: Awaish Kumar, Uttam Kumaran, shriramapte
WEBVTT
1 00:00:54.140 ⇒ 00:00:55.200 Uttam Kumaran: I wish.
2 00:00:57.720 ⇒ 00:00:58.710 Awaish Kumar: Oh, hello.
3 00:01:00.970 ⇒ 00:01:03.159 Awaish Kumar: Just saw your passage of the element.
4 00:01:03.560 ⇒ 00:01:08.659 Uttam Kumaran: Yeah, I think I… I think I’ve messed something up with the monthly view, it’s just duplicating, so…
5 00:01:09.150 ⇒ 00:01:11.129 Awaish Kumar: Okay, I will just take a look.
6 00:01:11.270 ⇒ 00:01:13.860 Uttam Kumaran: Yeah, like, all the… all the segments…
7 00:01:14.350 ⇒ 00:01:18.840 Uttam Kumaran: So, I think it’s just the structure is there, the values are just off.
8 00:01:20.180 ⇒ 00:01:26.260 Uttam Kumaran: And then, yeah, dude, I was also thinking, like, for CTA, Catherine told me that,
9 00:01:26.660 ⇒ 00:01:30.389 Uttam Kumaran: Gee, the Cortex AI thing is working really well.
10 00:01:30.520 ⇒ 00:01:31.880 Uttam Kumaran: So I’m wondering, like.
11 00:01:32.620 ⇒ 00:01:38.239 Awaish Kumar: Maybe just spend 15 minutes, turn… see if it works for Prod Marts and our Snowflake, and, like.
12 00:01:38.380 ⇒ 00:01:40.300 Uttam Kumaran: Just give that to Shivani.
13 00:01:42.270 ⇒ 00:01:45.220 Awaish Kumar: Oh, I could try. I have worked with that already.
14 00:01:45.810 ⇒ 00:01:46.750 Uttam Kumaran: Oh, okay, okay.
15 00:01:46.750 ⇒ 00:01:49.380 Awaish Kumar: We can… I can try out the broad ones.
16 00:01:50.450 ⇒ 00:01:52.430 Uttam Kumaran: Okay, okay, cool. Hey, Sharif.
17 00:01:52.430 ⇒ 00:01:53.220 shriramapte: What’s good?
18 00:01:53.220 ⇒ 00:01:56.629 Uttam Kumaran: I’m just out… I’m just out getting breakfast, so.
19 00:01:57.110 ⇒ 00:01:59.490 shriramapte: Cool, yeah, thank you. Where are you going?
20 00:01:59.870 ⇒ 00:02:02.589 Uttam Kumaran: I’m at this place called Sourduck.
21 00:02:03.010 ⇒ 00:02:06.230 Uttam Kumaran: Me and Jess try to get breakfast, like, once a week.
22 00:02:06.400 ⇒ 00:02:12.159 Uttam Kumaran: But we didn’t do this morning, so I’m like, I’ve just found some time, so… yeah, it’s good.
23 00:02:13.240 ⇒ 00:02:30.030 Uttam Kumaran: Cool, I guess I just wanted to introduce you to Awash. Awish, this is Sri. Sri’s a longtime friend of mine, but, sort of a long career in finance and, like, financial analysis, so I sort of briefed him yesterday on sort of what’s going on at Hydra.
24 00:02:30.180 ⇒ 00:02:38.410 Uttam Kumaran: like, I’m… I basically, kind of gave them a brief of, like, they’re just kind of, like, needs a lot of help digging through, like, core…
25 00:02:39.590 ⇒ 00:02:40.600 Uttam Kumaran: New box.
26 00:02:41.050 ⇒ 00:02:53.809 Uttam Kumaran: And I think that’s probably gonna be the tip of the iceberg. So, like, really the first thing to nail today is, like, just intros, and then probably just dive right into, like, okay, what is the current state of, like, what you’re trying to do, what you’re trying to produce?
27 00:02:54.000 ⇒ 00:03:10.840 Uttam Kumaran: Ultimately, like, our goal is, like, to get her to be able to do that in Hex. If we need to sort of crawl, walk, run with her, then we can do that. So, the current setup is, like, we… Awash worked on a lot of the modeling, based on Stripe data, and that exists in…
28 00:03:11.000 ⇒ 00:03:13.939 Uttam Kumaran: data warehouse, and then that’s coming into HEX.
29 00:03:15.850 ⇒ 00:03:30.469 Uttam Kumaran: we sort of, again, you kind of saw the way we’re modeling, so I think any feedback you have after today, we can pretty easily implement. A couple things, like we talked about yesterday, which is, like, rolling things up to the customer level instead of subscription ID, like, we can do those things.
30 00:03:30.870 ⇒ 00:03:43.250 Uttam Kumaran: But I think probably the goal today is, with our meeting later, is just making sure that we get her reporting requirements, and then almost, like, I think she’s just gonna have questions and scenarios.
31 00:03:43.360 ⇒ 00:03:49.209 Uttam Kumaran: You know? And so I think that’s kind of the biggest thing to go through with her.
32 00:03:50.780 ⇒ 00:03:59.410 Uttam Kumaran: I feel like… I don’t know if there’s, like, really anything else I missed, the waysh, or anything… any other context that we wanna… we wanna give.
33 00:04:00.420 ⇒ 00:04:06.430 Awaish Kumar: Yeah, like… Sandra seems to be very new to doing these kind of analyses.
34 00:04:06.560 ⇒ 00:04:08.650 Awaish Kumar: And she’s more of a…
35 00:04:08.850 ⇒ 00:04:23.559 Awaish Kumar: kind of right now, she’s doing in a… in a way that whenever somebody asks any question, either CEO or someone, then she goes into and does some analysis to answer those questions, instead of being,
36 00:04:23.640 ⇒ 00:04:31.089 Awaish Kumar: other way around, like, okay, we have a dashboard which, basically, where you can see the retention for this month, or ER.
37 00:04:31.230 ⇒ 00:04:38.989 Awaish Kumar: So she don’t have that. So whenever there’s a question, then we have to do that, and while doing that, she…
38 00:04:38.990 ⇒ 00:04:55.590 Awaish Kumar: So that’s why we don’t have exact definitions. What it looks like, we created a model based on some assumptions, and maybe they were not true, or something like that, because nobody actually worked on those definitions from the beginning.
39 00:04:57.460 ⇒ 00:05:02.909 Uttam Kumaran: Yeah, like, we came in, Sri, and she was like, okay, we wanna just… give us the works for Stripe.
40 00:05:03.070 ⇒ 00:05:08.169 Uttam Kumaran: But it’s clear, like, they internally don’t even have definitions for, like, core things.
41 00:05:09.260 ⇒ 00:05:21.040 Uttam Kumaran: So we built… we, like, drove as far as we could, but, like, even she’s, like… it’s… all of her reporting right now is ad hoc, so they need to get to some type of structured reporting with, like, defined metrics, basically. Yeah.
42 00:05:22.530 ⇒ 00:05:23.160 Awaish Kumar: Yeah, so…
43 00:05:23.160 ⇒ 00:05:25.850 shriramapte: Yeah, so this is my, like, rough cut.
44 00:05:26.560 ⇒ 00:05:27.300 Uttam Kumaran: Nope.
45 00:05:28.080 ⇒ 00:05:28.920 shriramapte: Oh, go ahead.
46 00:05:31.840 ⇒ 00:05:36.289 Awaish Kumar: Yeah, I have just filled in a notion talk, if I can share.
47 00:05:36.490 ⇒ 00:05:48.329 Awaish Kumar: It’s just like, I don’t know how we are going to share it, maybe as a Google Doc or something, but it’s more like, whatever work we have done so far for them, it outlines all of that.
48 00:05:49.170 ⇒ 00:05:55.309 Awaish Kumar: And, on… how… how ongoing, like, Engagement looks like, and
49 00:05:55.440 ⇒ 00:05:58.750 Awaish Kumar: Then, also, like, where things live.
50 00:05:58.750 ⇒ 00:06:01.070 Uttam Kumaran: like, move for GitHub and all of that.
51 00:06:03.890 ⇒ 00:06:09.140 Uttam Kumaran: Do you want to just share this away with Sri’s personal email? We’re gonna get him a Brainforge email.
52 00:06:10.800 ⇒ 00:06:12.869 shriramapte: No, I have Brainforge up and running.
53 00:06:13.240 ⇒ 00:06:15.900 Uttam Kumaran: Oh, okay, cool, then… then you should just see…
54 00:06:16.330 ⇒ 00:06:18.369 Uttam Kumaran: You should see his email in there, Awash.
55 00:06:19.260 ⇒ 00:06:20.690 Awaish Kumar: Oh, it’s making a sec.
56 00:06:20.690 ⇒ 00:06:22.900 Uttam Kumaran: Yeah, you can just… you can just share that with them, yeah.
57 00:06:25.350 ⇒ 00:06:27.339 Uttam Kumaran: Okay, cool. I’m sure, yeah, you can go ahead.
58 00:06:28.580 ⇒ 00:06:32.670 shriramapte: Yeah, for this particular problem, like, it isn’t validated.
59 00:06:33.260 ⇒ 00:06:38.749 shriramapte: I put some questions together, like, that we’d want them to answer, so, like.
60 00:06:39.920 ⇒ 00:06:45.079 shriramapte: I don’t know if you guys know this, but can they buy more credits? .
61 00:06:45.080 ⇒ 00:06:49.190 Uttam Kumaran: Yes. Yeah, you can buy… You can buy credit packs.
62 00:06:49.680 ⇒ 00:06:54.530 shriramapte: And if you buy the pack of credits, does it last longer than the current month?
63 00:06:56.390 ⇒ 00:06:58.299 Uttam Kumaran: Not sure.
64 00:06:59.080 ⇒ 00:07:13.879 shriramapte: Okay, so that’s the… that’s the big thing, is, like, if it does, and they can be used outside of the current month, then we have to, like… that adds, like, a level of complexity to the revenue reporting, because it’s like, do you want to…
65 00:07:14.190 ⇒ 00:07:18.540 shriramapte: Recognize those when they’re purchased, or when they’re used.
66 00:07:18.540 ⇒ 00:07:20.050 Uttam Kumaran: When they’re used, yeah, okay.
67 00:07:20.460 ⇒ 00:07:21.580 Uttam Kumaran: Good question.
68 00:07:21.580 ⇒ 00:07:24.310 shriramapte: But if it’s all in the same month, then it doesn’t matter?
69 00:07:24.870 ⇒ 00:07:32.529 shriramapte: And then they kind of have two products, Professional and Teams. Where’s their pricing page?
70 00:07:33.090 ⇒ 00:07:35.470 Uttam Kumaran: And they have an enterprise, right, Awash?
71 00:07:35.720 ⇒ 00:07:36.350 Awaish Kumar: Hey!
72 00:07:36.350 ⇒ 00:07:36.980 Uttam Kumaran: So…
73 00:07:37.730 ⇒ 00:07:38.170 shriramapte: So…
74 00:07:38.170 ⇒ 00:07:39.160 Uttam Kumaran: Tax on that, yeah.
75 00:07:39.160 ⇒ 00:07:43.979 shriramapte: The thing with their professional and teams, though, is that they’re identical products.
76 00:07:44.090 ⇒ 00:08:02.520 shriramapte: like, at least on the bullets. And so, I’m curious, like, are they tracking those? Like, are they identical products, or is it just… is that just, like, lazy copy? And if they are identical products, are they the same SKU, or are they different SKUs on the back end?
77 00:08:06.460 ⇒ 00:08:08.270 Uttam Kumaran: The way she wanna answer that, yeah.
78 00:08:09.570 ⇒ 00:08:15.710 Awaish Kumar: Okay, yeah, so… Can you show me that again, like, the website?
79 00:08:15.710 ⇒ 00:08:18.369 shriramapte: Yeah, so if you go here, right.
80 00:08:18.540 ⇒ 00:08:20.730 shriramapte: These are, I’m assuming, are…
81 00:08:20.730 ⇒ 00:08:30.350 Awaish Kumar: Like, they have different product IDs, so I have a list of different products they sell, where it is… it mentions differently.
82 00:08:31.440 ⇒ 00:08:37.980 Awaish Kumar: Like, the team’s project, and the product as a professional one, and they have a…
83 00:08:39.140 ⇒ 00:08:43.189 Awaish Kumar: Yeah, separate descriptions and all for that in the database, but I don’t know.
84 00:08:43.429 ⇒ 00:08:45.540 Awaish Kumar: I have looked at the website.
85 00:08:45.890 ⇒ 00:08:47.380 shriramapte: I also have big soy.
86 00:08:47.380 ⇒ 00:08:50.970 Uttam Kumaran: Yeah, they also have credit packs, right, Awash? As, like, another product?
87 00:08:51.780 ⇒ 00:08:59.470 Awaish Kumar: Yes, so we have, like, subscriptions, and we have one-off invoices where they… You can buy the credits.
88 00:09:00.020 ⇒ 00:09:04.300 Uttam Kumaran: Okay, okay. And we can, I think, Awash, once Sri has, I think
89 00:09:04.820 ⇒ 00:09:08.289 Uttam Kumaran: Maybe you can also add Sri to Hex, and then…
90 00:09:08.400 ⇒ 00:09:10.280 Uttam Kumaran: I guess the data warehouse as well.
91 00:09:11.270 ⇒ 00:09:12.040 Uttam Kumaran: After this.
92 00:09:12.500 ⇒ 00:09:13.909 Awaish Kumar: Okay, yeah, I can.
93 00:09:14.060 ⇒ 00:09:15.680 Uttam Kumaran: Cool.
94 00:09:15.680 ⇒ 00:09:16.660 Awaish Kumar: What?
95 00:09:18.860 ⇒ 00:09:19.420 shriramapte: Well, because.
96 00:09:19.420 ⇒ 00:09:24.100 Uttam Kumaran: Yeah, that’s a good question. We do have it on the back end, though. Like, each of those are different.
97 00:09:24.410 ⇒ 00:09:25.519 Uttam Kumaran: And we have that.
98 00:09:25.520 ⇒ 00:09:44.349 shriramapte: Got it. Yeah, that’s gonna be… that’s, like… dude, this is coming back to my thing of, like, half of finance problems are process problems, like, they have two SKUs for identical products, like, that could be, like, a recommendation we can empower, what’s her name to make, to, like, simplify those.
99 00:09:47.270 ⇒ 00:09:49.639 Awaish Kumar: Like, they also need, like,
100 00:09:50.370 ⇒ 00:10:08.840 Awaish Kumar: metric definition… definitions in a sense that they use… they are comparing our ER calculation with Shopify’s, and we don’t… I don’t know, like, how Shopify does it, but then we… we never, take into consideration the amount of invoices into ER calculation.
101 00:10:08.840 ⇒ 00:10:11.629 Uttam Kumaran: Dude, they have, like, one-off invoices for random stuff.
102 00:10:12.590 ⇒ 00:10:13.180 Uttam Kumaran: Like…
103 00:10:13.180 ⇒ 00:10:14.050 shriramapte: Interesting.
104 00:10:14.400 ⇒ 00:10:18.240 Uttam Kumaran: Like a… like a… like a grandfathered customer, or like…
105 00:10:18.530 ⇒ 00:10:20.959 Uttam Kumaran: the CEO signs a custom deal.
106 00:10:21.130 ⇒ 00:10:26.789 Uttam Kumaran: So, like, that’s all stuff that, like, will be in the data and sort of just has to get rehashed, but yes.
107 00:10:26.790 ⇒ 00:10:27.340 shriramapte: Nope.
108 00:10:27.580 ⇒ 00:10:31.869 Uttam Kumaran: that is sort of, like, what Sandra has to go back to the team, like, we can’t do this because it’s affecting reporting.
109 00:10:33.070 ⇒ 00:10:43.530 shriramapte: Yeah. Or you can do it, you just have to treat it as an enterprise deal, and then fill in the right fields for it.
110 00:10:44.250 ⇒ 00:10:45.060 Uttam Kumaran: Okay.
111 00:10:45.480 ⇒ 00:10:52.630 shriramapte: But basically, like, this is the output, right? You have an orders table, and the orders table is…
112 00:10:53.240 ⇒ 00:10:57.809 shriramapte: A merge of both the subscriptions and the invoices?
113 00:10:58.400 ⇒ 00:11:01.090 Uttam Kumaran: In a way that makes it…
114 00:11:01.970 ⇒ 00:11:08.890 shriramapte: That, like, we can, like, talk about, like, what the normalized columns should be.
115 00:11:09.120 ⇒ 00:11:15.549 shriramapte: And then there’s a revenue by… monthly, like, revenue by customer table.
116 00:11:16.150 ⇒ 00:11:19.500 shriramapte: And this, you kind of want to make
117 00:11:19.900 ⇒ 00:11:37.889 shriramapte: like, this allows you to make it, like, very filterable, right? So you can filter the customers by different product SKUs, by different start dates, by, like, whatever. But these are… these are kind of the mezy categories you want to have, so…
118 00:11:37.890 ⇒ 00:11:38.589 Uttam Kumaran: What is me see?
119 00:11:39.480 ⇒ 00:11:43.150 shriramapte: Mutually exclusive, collectively exhaustive. So, like.
120 00:11:43.150 ⇒ 00:11:43.810 Uttam Kumaran: Okay.
121 00:11:43.810 ⇒ 00:11:54.640 shriramapte: everything should be represented in one of these categories, and nothing should be in both of these categories, or more than one of these categories.
122 00:11:56.110 ⇒ 00:12:05.099 shriramapte: with the exceptions of deactivations to Enterprise, but, we can talk through how that works in the formulas.
123 00:12:05.100 ⇒ 00:12:07.969 Uttam Kumaran: So, new customers is obvious.
124 00:12:08.040 ⇒ 00:12:12.470 shriramapte: reactivations is obvious. It’s just, like.
125 00:12:14.140 ⇒ 00:12:25.910 shriramapte: were they active… were they not active in the period before? Were they active in any prior period? Are they active in current period? Include in,
126 00:12:26.350 ⇒ 00:12:36.000 shriramapte: reactivation. Monthly tier upgrade is, like, their current month is greater than their prior month.
127 00:12:36.130 ⇒ 00:12:51.059 shriramapte: and they’re on a monthly tier, like, the new order form is, like, a monthly tier, then we want to break that, like, upsell out separately. Similarly, enterprise upgrade, and then we’ll have to figure out, like, marginal credit purchases.
128 00:12:51.620 ⇒ 00:12:57.249 shriramapte: Then there’s, like, downgrading in monthly tiers, which… or, like…
129 00:12:57.440 ⇒ 00:13:04.819 shriramapte: maybe, like, lower credit usage is also a thing we want to track.
130 00:13:05.520 ⇒ 00:13:28.689 shriramapte: And then deactivations, and then… this is gonna be interesting, like, when they view their monthly tier, there will be churn in their monthly… like, when they view their monthly tier standalone, there will be churn that is actually a deactivation, but switching to an enterprise plan, and so we want to make sure that’s broken out separately when viewing it on a…
131 00:13:29.240 ⇒ 00:13:37.749 shriramapte: When viewing the… Monthly business on a standalone basis.
132 00:13:38.920 ⇒ 00:13:53.009 Uttam Kumaran: Okay, this is great. So I think on the call with her, honestly, one good output is if… we have all the columns. We have, like, everything on an invoice, subscription, and customer level, so if you can give us, like, the critical columns.
133 00:13:53.090 ⇒ 00:14:02.859 Uttam Kumaran: for whatever tables you need, and you guys… you and Sandra agree on that, then we’ll just rip it. We can probably have it to you by tomorrow, because most of the stuff is modeled. So…
134 00:14:03.000 ⇒ 00:14:16.890 Uttam Kumaran: that’s sort of all we need. I feel like we’re probably, like, 20% away from just pivoting some tables into these views. But we do need the definitions for some of these. So, especially for the ARR buckets and things like that, we… it’ll just be, like.
135 00:14:17.340 ⇒ 00:14:32.850 Uttam Kumaran: I… usually the way we do it is we, like, we take a month, and we just, like, look for the outliers, and try to be like, okay, in this scenario, this is what happened, things like that, but again, she… she’s… she’s good at QAing, so she’ll be like, hey, there’s this weird… there’s this weird case, like.
136 00:14:33.360 ⇒ 00:14:39.020 Uttam Kumaran: You know, because I don’t… I don’t even… I don’t really know how they’re handling, like, Refund.
137 00:14:39.020 ⇒ 00:14:45.750 shriramapte: For the flow of the call, for the flow of the call today, like, we can introduce me…
138 00:14:46.230 ⇒ 00:14:52.939 shriramapte: I can, like, basically walk her through, like, hey, like, here’s an Excel output that, like, we’ve used.
139 00:14:52.940 ⇒ 00:14:53.730 Uttam Kumaran: Yes.
140 00:14:53.730 ⇒ 00:15:02.729 shriramapte: in the past, to share ARR numbers, like, we could make this a dashboard for you. Here is how we would, like.
141 00:15:02.840 ⇒ 00:15:22.040 shriramapte: configure it to be HEDRA-specific. Do you agree with this configuration? Okay, great. Now let’s ask questions about how you want these different things treated. Like, how do you want credit packs treated? How do you want professional versus teams treated?
142 00:15:22.470 ⇒ 00:15:24.189 shriramapte: How do you want,
143 00:15:24.810 ⇒ 00:15:37.380 shriramapte: to do, like, what else do you want to filter by? Like, do you want to filter by product? Do you want to filter by geo? Do you want to filter by channel? Like, what else do you need to filter by?
144 00:15:37.490 ⇒ 00:15:46.300 shriramapte: and then try to get those requirements captured, and then… I agree with you, we should have everything we need from some of the tables we’ve built already.
145 00:15:47.790 ⇒ 00:16:01.790 Uttam Kumaran: Okay. And then, really, dude, it’s like, if you bust through that, like, in, like, 30, 40 minutes, like, take the rest of the time to sell on net new stuff. Like, they’re not gonna do anything on retention curves, cohorting.
146 00:16:02.140 ⇒ 00:16:04.370 Uttam Kumaran: You know, so, like…
147 00:16:04.620 ⇒ 00:16:09.700 Uttam Kumaran: You can sort of just, like, if you end up with time, you could be like, and here’s, like, where this could possibly go.
148 00:16:10.700 ⇒ 00:16:11.930 Uttam Kumaran: That’s great.
149 00:16:12.140 ⇒ 00:16:16.790 shriramapte: Yeah, actually, I have, I can pull something up.
150 00:16:17.310 ⇒ 00:16:23.979 Uttam Kumaran: Yeah, because, again, they’re not… I don’t think they’re looking significantly at retention curves. They’re not doing any product analytics, which is, like.
151 00:16:24.180 ⇒ 00:16:32.959 Uttam Kumaran: what we basically tried to sell them on, and they were like, oh, I don’t know, we’re, like, too early. And I was like, dude, you’re… you’re wasting money on these customers.
152 00:16:33.470 ⇒ 00:16:37.860 Uttam Kumaran: But something around retention curve, and then honestly.
153 00:16:38.530 ⇒ 00:16:43.430 Uttam Kumaran: You know how it goes, like, Series A, Series B, they’re just sort of getting to the next race.
154 00:16:43.520 ⇒ 00:16:59.770 Uttam Kumaran: So, it’s almost like figuring out, like, when is that, and, like, what do you need for that? And, like, ultimately, also, like, we haven’t had a lot of FaceTime with the CEO, so the breakthrough on this project is, like, how does our work get to him, and how does he, like, holy shit, this team’s nasty? Whatever they need.
155 00:17:00.270 ⇒ 00:17:10.660 Uttam Kumaran: Yeah, yeah, yeah, okay. So that’s, like, that’s the… that’s the… that’s the story arc, broadly. Whatever we could do today to, like, keep nudging, we could do today. Yeah.
156 00:17:10.660 ⇒ 00:17:11.150 shriramapte: Yeah.
157 00:17:11.420 ⇒ 00:17:11.980 Uttam Kumaran: Bill.
158 00:17:11.980 ⇒ 00:17:19.579 shriramapte: So, I have… this… That I can show as an output.
159 00:17:32.030 ⇒ 00:17:32.720 Uttam Kumaran: Bobby.
160 00:17:49.930 ⇒ 00:17:51.780 Awaish Kumar: Yeah, Atham, can you share it?
161 00:17:52.110 ⇒ 00:17:55.010 Awaish Kumar: with Shira, actually, I don’t have permissions.
162 00:17:55.720 ⇒ 00:17:56.890 Awaish Kumar: To share the doc.
163 00:17:57.240 ⇒ 00:17:59.570 Uttam Kumaran: Oh, yeah, okay. Yeah, yeah, I will.
164 00:18:01.170 ⇒ 00:18:02.729 Uttam Kumaran: What is it? What is the doc call?
165 00:18:06.640 ⇒ 00:18:08.780 Awaish Kumar: It is in the Zoom link, the chat.
166 00:18:08.830 ⇒ 00:18:09.529 Uttam Kumaran: Oh, okay.
167 00:18:10.160 ⇒ 00:18:17.500 shriramapte: Check this out. So this is a kind of chart we can… we can show her, and say, hey, this is what we want to produce.
168 00:18:17.500 ⇒ 00:18:17.970 Uttam Kumaran: Yeah.
169 00:18:18.150 ⇒ 00:18:25.479 shriramapte: And, like, these will be your cohorts index, and the red line is your CAC.
170 00:18:25.850 ⇒ 00:18:36.350 shriramapte: And, like, this provides a great engagement point with your CEO to say, hey, like, what are the cohorts that are, like, below our CAC line?
171 00:18:36.410 ⇒ 00:18:49.170 shriramapte: what are the commonalities of those customers, how can we activate those customers? And then, what are the commonalities of the cohorts above the CAC line? How do we.
172 00:18:50.380 ⇒ 00:18:52.130 Uttam Kumaran: How do we, like…
173 00:18:52.230 ⇒ 00:18:55.990 shriramapte: Find more of those customers, and then…
174 00:18:56.210 ⇒ 00:19:04.690 Uttam Kumaran: You know the story for these guys is, like, they sort of want to convert free to paid, and they want to convert paid to enterprise, as, you know, by any means.
175 00:19:05.070 ⇒ 00:19:05.670 shriramapte: Yeah.
176 00:19:08.110 ⇒ 00:19:18.889 shriramapte: And then the real, like, like, thing you could pitch as an engagement, where you’re like, oh, we would need to get a lot deeper to do, is, like, inference adjusts these curves.
177 00:19:20.230 ⇒ 00:19:22.289 Uttam Kumaran: Meaning, me. Okay, okay.
178 00:19:22.570 ⇒ 00:19:23.140 Uttam Kumaran: Yeah.
179 00:19:23.140 ⇒ 00:19:33.910 shriramapte: Like, that could be your hook of, like, oh, you would have to, like, pay for a way bigger engagement to, like, get that, because we’d have to go into your OpenAI data, like, blah blah blah, like, you know.
180 00:19:33.910 ⇒ 00:19:34.860 Uttam Kumaran: Yeah, yeah.
181 00:19:35.030 ⇒ 00:19:35.870 Uttam Kumaran: Yeah.
182 00:19:37.080 ⇒ 00:19:41.160 Uttam Kumaran: Yeah, again, dude, none of the stuff we’re looking at is costs at all.
183 00:19:41.650 ⇒ 00:19:42.510 Uttam Kumaran: So…
184 00:19:42.510 ⇒ 00:19:44.940 shriramapte: Oh, I know, they’re… that’s so funny.
185 00:19:44.940 ⇒ 00:19:52.210 Uttam Kumaran: But see, again, like, you know, dude, there’s, like, a hundred of these types of companies. The pitch we came to them, and I can send it to you, is we basically came to them, we’re like, look, there’s a hundred of you.
186 00:19:52.470 ⇒ 00:19:56.540 Uttam Kumaran: The thing that’s gonna differentiate you, that we can affect, is that you…
187 00:19:56.820 ⇒ 00:20:02.870 Uttam Kumaran: You’ve quickly reduced churn, and you focus on features that are driving expansion.
188 00:20:03.040 ⇒ 00:20:07.190 Uttam Kumaran: They didn’t buy it, because the CEO is, like, really micromanaging.
189 00:20:07.650 ⇒ 00:20:12.180 Uttam Kumaran: he was like, oh, I don’t know if we need amplitude, and we need to see that right now, and I’m like, okay.
190 00:20:12.410 ⇒ 00:20:20.310 Uttam Kumaran: And then I was like, okay, let’s just get… but it’s clear that they still need us, because Sandra’s like, yeah, I’m gonna… she’s probably gonna quit if, like, we don’t keep helping her.
191 00:20:20.660 ⇒ 00:20:28.670 Uttam Kumaran: So, there’s a good chance, like, we just… we’ll just get more at-bats. So, yeah, okay, I think we’re kind of all aligned on this. She’s really easy, by the way, so…
192 00:20:28.840 ⇒ 00:20:34.419 Uttam Kumaran: like, well, I think Awashi, you just… if you can get Sri into Hex, and I just added you, Sri, into our…
193 00:20:34.590 ⇒ 00:20:36.990 Uttam Kumaran: our feedra channel in Slack.
194 00:20:37.430 ⇒ 00:20:43.530 Uttam Kumaran: You can just, like, communicate there. If you could just get Sri into Hex, the Notion doc is in that channel.
195 00:20:44.580 ⇒ 00:20:45.710 Uttam Kumaran: Oh, it should be good.
196 00:20:46.290 ⇒ 00:20:47.390 Awaish Kumar: Okay, yep.
197 00:20:47.750 ⇒ 00:20:49.560 shriramapte: I’m in the Notion doc, yeah.
198 00:20:52.170 ⇒ 00:20:53.550 Uttam Kumaran: I’ll pass. Second?
199 00:20:55.850 ⇒ 00:20:58.949 shriramapte: Sweet, man. Alright, I don’t have the invite for 2.
200 00:20:59.610 ⇒ 00:21:01.979 Uttam Kumaran: Yeah, I’m just gonna send it to you now, Nellie, I’ll be honest.
201 00:21:01.980 ⇒ 00:21:03.009 shriramapte: Alright, perfect.
202 00:21:03.510 ⇒ 00:21:04.050 Uttam Kumaran: Okay.
203 00:21:04.160 ⇒ 00:21:07.149 Uttam Kumaran: Alright, thank you guys, appreciate it. I’ll talk to you then.
204 00:21:07.840 ⇒ 00:21:08.869 Uttam Kumaran: About the crap.