Meeting Title: Polytomic x BF Kickoff Meeting Date: 2025-05-02 Meeting participants: Pranab Sachithanandan, Uttam Kumaran, Hannah Wang
WEBVTT
1 00:00:14.800 ⇒ 00:00:15.670 Pranab Sachithanandan: Hey!
2 00:00:16.300 ⇒ 00:00:17.220 Uttam Kumaran: Hey!
3 00:00:17.760 ⇒ 00:00:18.480 Pranab Sachithanandan: See ya.
4 00:00:18.860 ⇒ 00:00:20.030 Uttam Kumaran: Good to see ya.
5 00:00:20.030 ⇒ 00:00:20.960 Pranab Sachithanandan: Good to meet you, Hannah.
6 00:00:23.110 ⇒ 00:00:25.070 Hannah Wang: Hi! Nice meeting you.
7 00:00:25.070 ⇒ 00:00:28.270 Pranab Sachithanandan: Yeah, nice. How’s the week?
8 00:00:30.845 ⇒ 00:00:31.944 Uttam Kumaran: You go first, st Hannah.
9 00:00:32.619 ⇒ 00:00:34.799 Hannah Wang: Oh, it’s
10 00:00:36.189 ⇒ 00:00:41.999 Hannah Wang: it’s been alright. I don’t know why my brain is like all over the place, but this week
11 00:00:42.289 ⇒ 00:00:58.389 Hannah Wang: I just feel like mush. And also it’s not sunny at all. So I feel like I’m deficient in vitamin D, so maybe that’s also why and my in-laws are in town. So I think that also kind of like messes with the rhythm that I have. So I just feel like, mush. Yeah.
12 00:00:58.570 ⇒ 00:01:05.860 Pranab Sachithanandan: Yeah, no, this this week my sleep’s been a little off, so I’m just also similar. But it’s on the up and up. Got some good sleep last night. We’re
13 00:01:06.550 ⇒ 00:01:08.480 Pranab Sachithanandan: we’re moving. We’re just moving along.
14 00:01:08.680 ⇒ 00:01:13.019 Hannah Wang: Yeah, I like your green walls. It’s a nice pop of color.
15 00:01:13.380 ⇒ 00:01:16.010 Pranab Sachithanandan: Yeah, it feels it feels like, I’m in a
16 00:01:16.160 ⇒ 00:01:18.270 Pranab Sachithanandan: it’s a cactus or something, you know.
17 00:01:18.671 ⇒ 00:01:21.480 Uttam Kumaran: Cactus. I’ve never heard that before, but
18 00:01:21.480 ⇒ 00:01:24.059 Uttam Kumaran: it is like cactus, or it’s like almost like a
19 00:01:24.390 ⇒ 00:01:27.730 Uttam Kumaran: it’s almost like a like matcha, or like some sort.
20 00:01:27.730 ⇒ 00:01:30.599 Pranab Sachithanandan: Yeah, matcha is more enticing than cactus.
21 00:01:30.600 ⇒ 00:01:31.400 Hannah Wang: Yeah.
22 00:01:31.810 ⇒ 00:01:35.229 Uttam Kumaran: Or like ginseng, you know, that’s like that ginseng color.
23 00:01:35.880 ⇒ 00:01:36.640 Pranab Sachithanandan: Yeah.
24 00:01:37.040 ⇒ 00:01:38.500 Hannah Wang: Like Wasabi. I don’t know.
25 00:01:38.500 ⇒ 00:01:46.758 Uttam Kumaran: It is kind of like a lot cheap. Wasabi, like like grocery store. Wasabi.
26 00:01:48.420 ⇒ 00:01:52.089 Pranab Sachithanandan: 100% nice cool. Let’s get into it.
27 00:01:55.290 ⇒ 00:02:02.310 Pranab Sachithanandan: Alright. I I got the doc pulled up. Thanks for making this. Yeah, this all makes sense.
28 00:02:02.450 ⇒ 00:02:05.922 Pranab Sachithanandan: All makes. Yeah, maybe maybe we can. Maybe we can.
29 00:02:07.470 ⇒ 00:02:16.508 Pranab Sachithanandan: yeah, let’s go through. Let’s go through some of this together. And yeah, I know it’s just we can get in sync and then figure out like the next few times, we gotta check in
30 00:02:16.880 ⇒ 00:02:17.575 Pranab Sachithanandan: and
31 00:02:18.530 ⇒ 00:02:25.979 Pranab Sachithanandan: and yeah. And then with them. I I caught up with Clay, the the guy who runs data to kettle on fire. So I had a good yeah. Yeah. And I can tell you more about that.
32 00:02:26.780 ⇒ 00:02:27.440 Pranab Sachithanandan: Pardon.
33 00:02:27.780 ⇒ 00:02:29.220 Uttam Kumaran: I saw your notes. They’re good.
34 00:02:29.220 ⇒ 00:02:54.029 Pranab Sachithanandan: Yeah, yeah, thanks. And then he also talked to go live. And then the talk with gollip. I listened to that recording. And it was. Basically, it was good. It was basically like the takeaway was. They don’t actually use a ton of data. It’s mostly kind of like even a hundred 1,000 or like up to a million, would be like a lot for them in a single sync. So they’re kind of like they’re pro from polytomic point of view. Probably not the best fit, I think, from your guys point of view, there’s something there when it comes to
35 00:02:54.430 ⇒ 00:03:05.950 Pranab Sachithanandan: forgot the name of the tool, but like the one he mentioned that you were, gonna do a demo with, like the kind of harmonizing like whole foods. Heb, plus spins data. That’s that they they do.
36 00:03:05.950 ⇒ 00:03:07.690 Uttam Kumaran: What do they use for sales data.
37 00:03:09.903 ⇒ 00:03:26.220 Pranab Sachithanandan: That, it’s that stuff, because basically like, so so for re, so for only 10% of their business is E-com, now, 90% is retail. So so it used to be that they could like sales. Data was just what was it run online and Amazon, which is easy to check in on. So it’s easy to kind of like attribute
38 00:03:26.310 ⇒ 00:03:41.080 Pranab Sachithanandan: effects of like promotions and all that kind of stuff. But then, now that it’s retail, it’s really just probabilistic. So they don’t really know what the revenue is per store. They just know how much money they’re making in general, but they can’t actually like do targeted stuff as much. It’s just like
39 00:03:41.280 ⇒ 00:03:42.790 Pranab Sachithanandan: different kinds of modeling.
40 00:03:44.000 ⇒ 00:03:49.300 Uttam Kumaran: I mean, what do you think like, do you want to do something more like Sas focus? Then
41 00:03:49.410 ⇒ 00:03:51.800 Uttam Kumaran: we’re like, how do you think about yeah.
42 00:03:51.800 ⇒ 00:04:01.769 Pranab Sachithanandan: Yeah, yeah, great. Yeah. So I I think that’s the big question. I I talked to gall about this. Honestly, he’s his priority is really just like, let’s just practice getting a dinner in. He doesn’t.
43 00:04:01.770 ⇒ 00:04:02.150 Uttam Kumaran: Okay.
44 00:04:02.150 ⇒ 00:04:29.588 Pranab Sachithanandan: Care as much if it’s not the best fit. I mean, I would like it to be a better fit, because then there’s a better chance we’ll get customers. That’s for 1, 2. We have a couple of people in Austin that are customers that could come by, and they’re all like sas people. So we have someone who’s at Retool. And Vercell, who both live here. So so that’s a point towards pivoting it to more sas type thing. I just, I think. And then I think,
45 00:04:30.320 ⇒ 00:04:30.800 Pranab Sachithanandan: even.
46 00:04:30.800 ⇒ 00:04:35.579 Uttam Kumaran: The other thing we should do is you should just invite everyone who’s on who’s on 5. Tran.
47 00:04:36.170 ⇒ 00:04:36.740 Pranab Sachithanandan: Yeah.
48 00:04:36.740 ⇒ 00:04:38.040 Uttam Kumaran: And scrape there.
49 00:04:38.760 ⇒ 00:04:45.960 Uttam Kumaran: I mean, there’s a couple of ways, but I can probably find find a way to get you all the 5 Chan, folks that are that have offices here or like.
50 00:04:46.180 ⇒ 00:04:48.080 Uttam Kumaran: and then you can just invite those people to be like
51 00:04:48.290 ⇒ 00:04:52.759 Uttam Kumaran: we’re another Etl tool like you may want to try this. We also do reverse blah blah.
52 00:04:52.760 ⇒ 00:04:59.899 Pranab Sachithanandan: Yeah, yeah, if you’re that, would, I think that would be yeah. So I actually do. I just found a tool today called Stumble. Have you heard of this.
53 00:05:03.630 ⇒ 00:05:05.970 Uttam Kumaran: Stumble or stumble? Oh, no.
54 00:05:06.240 ⇒ 00:05:13.419 Pranab Sachithanandan: So basically, you know how people do the play of finding a tech stack based on job job postings.
55 00:05:13.420 ⇒ 00:05:15.590 Uttam Kumaran: Yes, I there’s another company that does that.
56 00:05:15.820 ⇒ 00:05:16.530 Pranab Sachithanandan: Nice.
57 00:05:17.100 ⇒ 00:05:29.090 Pranab Sachithanandan: I’ve only ever seen that from like vendors, or like from like service providers who are like oh, you know, we’ll send you the leads. But we’ll do this. But this is actually just like a free database like they’re trying to be an Apollo competitor. So
58 00:05:29.360 ⇒ 00:05:32.990 Pranab Sachithanandan: so I think, yeah, I I just found out about it today.
59 00:05:34.340 ⇒ 00:05:36.539 Uttam Kumaran: Did you search polyatomic like? Was it accurate.
60 00:05:37.634 ⇒ 00:05:39.289 Pranab Sachithanandan: Good point. I don’t.
61 00:05:41.580 ⇒ 00:05:46.889 Pranab Sachithanandan: Well, oh, interesting air garage. We’re still. Yeah. Yeah. Yeah.
62 00:05:47.660 ⇒ 00:05:54.770 Pranab Sachithanandan: Dude. The cool thing about this is this guy that showed me they actually have. They almost have like interpretability where you can click
63 00:05:55.090 ⇒ 00:06:06.509 Pranab Sachithanandan: on. Why, unlike the actual job posting they scraped for like, why, they came up with the suggestion. So this is the actual job posting. So you can actually can like poke in and see if the signal makes any sense manually.
64 00:06:06.620 ⇒ 00:06:07.820 Pranab Sachithanandan: which is really helpful.
65 00:06:08.430 ⇒ 00:06:10.792 Uttam Kumaran: One company. Yeah, there’s a company that’s
66 00:06:14.670 ⇒ 00:06:18.889 Uttam Kumaran: a bill with. It’s like it’s an alternative to Bill with. It’s like.
67 00:06:18.890 ⇒ 00:06:20.449 Pranab Sachithanandan: Oh, to build alternative. I see.
68 00:06:20.930 ⇒ 00:06:22.900 Uttam Kumaran: But you, you know, like built with.
69 00:06:22.900 ⇒ 00:06:23.750 Pranab Sachithanandan: Yeah, yeah.
70 00:06:23.750 ⇒ 00:06:27.040 Uttam Kumaran: Yeah, it’s it’s something. But they did it based on job.
71 00:06:27.860 ⇒ 00:06:29.949 Pranab Sachithanandan: Oh, interesting!
72 00:06:30.130 ⇒ 00:06:32.640 Uttam Kumaran: Oh, it’s called their stack.
73 00:06:34.000 ⇒ 00:06:36.390 Uttam Kumaran: I always keep forgetting. He says there’s that yeah.
74 00:06:36.390 ⇒ 00:06:38.360 Pranab Sachithanandan: Interesting, interesting.
75 00:06:39.200 ⇒ 00:06:41.699 Uttam Kumaran: I mean, let me search it. I’m gonna search you all in here.
76 00:06:43.480 ⇒ 00:06:45.939 Uttam Kumaran: Nothing by train.
77 00:06:47.350 ⇒ 00:06:48.749 Uttam Kumaran: 4 K companies.
78 00:06:49.410 ⇒ 00:06:52.889 Pranab Sachithanandan: So some of them might be better. But I mean these are both great right? So.
79 00:06:53.050 ⇒ 00:06:57.839 Uttam Kumaran: Yeah, I mean, like, I haven’t. We haven’t done anything with this purely
80 00:06:58.070 ⇒ 00:07:01.279 Uttam Kumaran: just because we’re busy. But like, yeah.
81 00:07:01.280 ⇒ 00:07:02.080 Pranab Sachithanandan: Present
82 00:07:02.240 ⇒ 00:07:08.330 Pranab Sachithanandan: nice cool dude. So okay, in that case, if you’re if you’re open to pivoting, I’m open to it as well. I think.
83 00:07:08.330 ⇒ 00:07:09.350 Uttam Kumaran: That’s fine!
84 00:07:09.670 ⇒ 00:07:11.429 Pranab Sachithanandan: Sweet. Yeah, it was. It was really just like
85 00:07:11.808 ⇒ 00:07:22.050 Pranab Sachithanandan: if there’s momentum, then let’s keep it going. But honestly, even after talking to the kettle and Fire people that he’s not going to come to Austin. He said he could connect us to his director of finance. But it’s like, maybe not.
86 00:07:22.230 ⇒ 00:07:27.899 Pranab Sachithanandan: you know. So probably not as relevant but yeah, I’m I’m pretty game to just kind of do like
87 00:07:28.190 ⇒ 00:07:31.849 Pranab Sachithanandan: a general one, and they’re gonna hit up, hit up people manually, and kind of do that kind of thing.
88 00:07:33.490 ⇒ 00:07:35.280 Uttam Kumaran: Okay, I’m fine with that.
89 00:07:35.680 ⇒ 00:07:40.910 Uttam Kumaran: I mean, so, okay, I’m I’m fine with generally doing that. I mean, do we want to have like any theme.
90 00:07:41.550 ⇒ 00:07:49.142 Pranab Sachithanandan: For sure, for sure. Yeah, yeah. So let’s let’s talk through that. So like for. So so I think I think I think, still, if that’s the new scope, I think the
91 00:07:50.160 ⇒ 00:07:54.078 Pranab Sachithanandan: I think, yeah, I I still want it to be valuable to you guys. And
92 00:07:54.460 ⇒ 00:07:57.370 Pranab Sachithanandan: yeah, what kind of pitch is usually helpful for someone who like.
93 00:07:57.760 ⇒ 00:08:04.389 Pranab Sachithanandan: yeah, so we can, we can narrow it down to 2 things like people who use 5 tran, or you send. So use 5 tran or census
94 00:08:05.810 ⇒ 00:08:07.310 Pranab Sachithanandan: or bigger picture.
95 00:08:07.440 ⇒ 00:08:11.290 Pranab Sachithanandan: We could go after data teams like data people. Or you can go after robots. People
96 00:08:11.480 ⇒ 00:08:28.000 Pranab Sachithanandan: that’s like one kind of bifurcation. For the robots people, the angle is, hey, learn how to use your data. You probably don’t have a reverse etl tool. Learn how to use. Ctl, and then like, this is how we help sales. Customer success product ops all this kind of stuff.
97 00:08:28.110 ⇒ 00:08:48.190 Pranab Sachithanandan: Right? The data people. That’s a bit more of a technical thing. And then we can and like, but I’m and I think the people make a lot of sense because I feel like, that’s where you guys come in because you guys are the data people that help props people. So that probably makes the most sense on the data side. There they already are. Data literate. I don’t know if they’d actually work with you guys. But like, let me know if that’s not true.
98 00:08:48.190 ⇒ 00:08:51.449 Uttam Kumaran: No, no, no, I mean we we’ve sort of sold into both.
99 00:08:51.450 ⇒ 00:08:52.070 Pranab Sachithanandan: Like.
100 00:08:52.880 ⇒ 00:09:09.829 Uttam Kumaran: I think if you have data people and you’re like doing really well, then, it’s sort of like you don’t really need us, I think. For the most part we found that if we sell higher we don’t talk much about like, technically, we help with like more procurement and things like that I think we could go either way. I mean, like.
101 00:09:10.550 ⇒ 00:09:11.649 Uttam Kumaran: I think you can
102 00:09:12.100 ⇒ 00:09:20.170 Uttam Kumaran: like, there are the problem with the non data people is, you may get people with no ability to like make decisions.
103 00:09:20.340 ⇒ 00:09:26.669 Uttam Kumaran: So you’ll have to like, we basically have to filter for that where we get people that that are more in the like
104 00:09:27.660 ⇒ 00:09:32.860 Uttam Kumaran: that are more on the decision making side like data and managers or stuff like that.
105 00:09:33.240 ⇒ 00:09:33.740 Pranab Sachithanandan: Yep.
106 00:09:33.740 ⇒ 00:09:36.050 Uttam Kumaran: I’m finding. I wanna say, don’t mind.
107 00:09:36.530 ⇒ 00:09:55.679 Uttam Kumaran: either way, I will say in Austin, there’s actually not a lot for data people. There is a lot for people that want data. And that attracts a lot of like kind of people. There’s actually like I and I, because I go to all the data stuff. Here I go to the Snowflake user group. I go to the stuff.
108 00:09:56.060 ⇒ 00:09:56.650 Pranab Sachithanandan: You’ve been to this one.
109 00:09:57.375 ⇒ 00:09:58.020 Uttam Kumaran: Stuff.
110 00:09:58.360 ⇒ 00:10:03.490 Uttam Kumaran: I I’ve been to the this one. This one is like, really like this is where, like nothing happens with this one.
111 00:10:03.830 ⇒ 00:10:04.490 Pranab Sachithanandan: Yep.
112 00:10:04.490 ⇒ 00:10:06.899 Uttam Kumaran: This is like just random, just like, Meet up.
113 00:10:07.273 ⇒ 00:10:15.759 Uttam Kumaran: So I think there, you’ll get a good. But that one there’s Random, who are like senior people. But like, there’s no organization, it’s sort of just like it’s like a
114 00:10:16.070 ⇒ 00:10:19.910 Uttam Kumaran: like a amorphous thing that just like recurring, you know.
115 00:10:20.160 ⇒ 00:10:31.889 Uttam Kumaran: So yeah, I think like having something that’s that’s there is good. And then we can get yeah, I think so. I think you should do it. Maybe from talking myself into saying you should do it for just for data people.
116 00:10:32.180 ⇒ 00:10:32.900 Pranab Sachithanandan: Sweet.
117 00:10:33.130 ⇒ 00:10:36.289 Uttam Kumaran: And then it’s really for you guys to really highlight the features.
118 00:10:37.170 ⇒ 00:10:49.460 Uttam Kumaran: you know. And you guys have a ton of features right? You could talk about new connectors. You could talk about the way you do pricing you could talk about, hey? The way we work is we do. We don’t price like 5, 10. We do these proof of concepts. We’re able to do all these things like.
119 00:10:49.700 ⇒ 00:10:57.049 Uttam Kumaran: I think you could super slam that, and you will most likely find that everybody hates their Etl provider.
120 00:10:57.780 ⇒ 00:11:02.329 Uttam Kumaran: So it’s like, Yeah, I guess. Now, I’m just like, yeah, I think that’s probably the best route.
121 00:11:02.580 ⇒ 00:11:19.905 Pranab Sachithanandan: Sweet. That sounds great to me. Yeah. And I think I could get I would. I would invite all the people like I basically, any of our customers in Austin would be a good fit for this, because it’s like not, you know, we already have customers in this way. So I think that’d be useful. And we could entice. Yeah, there’s a few people there.
122 00:11:21.550 ⇒ 00:11:26.290 Pranab Sachithanandan: yeah, sweet cool. That sounds good. Yeah. And then on your side, I guess.
123 00:11:26.480 ⇒ 00:11:39.827 Pranab Sachithanandan: Yeah. And then in that case we can just kind of make it more chill where it’s more, maybe not more chill. But maybe it doesn’t have to be as formal for presentation. We can kind of just do like we maybe we would do a fireside chat, or maybe, like I can think of some way to kind of structure it so that it’s more
124 00:11:40.190 ⇒ 00:11:41.230 Pranab Sachithanandan: more.
125 00:11:41.230 ⇒ 00:11:46.529 Uttam Kumaran: Yeah, like we did this, but I don’t know. The fireside chat is kinda nice. We just pick a topic.
126 00:11:47.500 ⇒ 00:11:51.150 Uttam Kumaran: I’ll literally talk as long as you want. But whatever you want.
127 00:11:51.280 ⇒ 00:11:51.650 Pranab Sachithanandan: Nice.
128 00:11:52.980 ⇒ 00:11:56.980 Uttam Kumaran: We can call on people, we can make it more interactive.
129 00:11:57.330 ⇒ 00:11:57.950 Pranab Sachithanandan: Yeah.
130 00:11:58.900 ⇒ 00:12:01.719 Uttam Kumaran: Yeah, I mean, and and I, yeah, I’m.
131 00:12:02.930 ⇒ 00:12:05.709 Pranab Sachithanandan: Sweet olive can do that, too, for sure.
132 00:12:05.710 ⇒ 00:12:06.270 Uttam Kumaran: Yeah.
133 00:12:07.595 ⇒ 00:12:14.710 Pranab Sachithanandan: Cool, nice nice, and then I guess one decision. So, and then
134 00:12:15.570 ⇒ 00:12:19.049 Pranab Sachithanandan: do you have a preference? Or do you think any any between, like a house
135 00:12:19.180 ⇒ 00:12:31.780 Pranab Sachithanandan: that has like a like, basically like, I know a place that’s you can just rent it. And it’s like a 2 story house that can be used for events, like cater food from like honest Mary’s, or some other kind of healthy food or something, and that feels pretty good. I think
136 00:12:31.960 ⇒ 00:12:34.849 Pranab Sachithanandan: we could target like 20 or 30 people doing that.
137 00:12:34.850 ⇒ 00:12:36.869 Uttam Kumaran: Kind of like, yeah, I guess I kind of like that.
138 00:12:37.160 ⇒ 00:12:44.040 Pranab Sachithanandan: Did you survive? And there’s like a presentation space, and it’s more like mingling and chill versus like, I think, at a sit down restaurant. No one can. Really. You can’t really talk to other people.
139 00:12:44.040 ⇒ 00:12:49.889 Uttam Kumaran: And it’s like, and if I guess if it’s more technical people at a like a restaurant setting, it’s gonna be like awkward.
140 00:12:49.890 ⇒ 00:12:50.500 Pranab Sachithanandan: How awkward.
141 00:12:50.900 ⇒ 00:12:51.699 Uttam Kumaran: The engineers.
142 00:12:51.700 ⇒ 00:12:52.790 Pranab Sachithanandan: Yeah, yeah, yeah, yeah.
143 00:12:52.790 ⇒ 00:12:58.319 Uttam Kumaran: Yeah, I mean, I just know that for a fact, because I go. I go to like all these. I’ve been going to these for a long time.
144 00:12:58.450 ⇒ 00:12:58.940 Pranab Sachithanandan: Nice.
145 00:12:58.940 ⇒ 00:13:05.279 Uttam Kumaran: And it’s awkward if it’s all engineers, because they’re all like it’s kind of like they’re not like. It’s no, it’s like, not like a lot of sales people. So.
146 00:13:05.280 ⇒ 00:13:07.629 Pranab Sachithanandan: Yeah, when the salespeople are there, it’s like chiller.
147 00:13:07.630 ⇒ 00:13:12.690 Uttam Kumaran: It’s electric. Yeah, it’s electric. But then there’s like, no substance. It’s all like.
148 00:13:12.810 ⇒ 00:13:15.161 Pranab Sachithanandan: Yeah, nice. And then
149 00:13:15.750 ⇒ 00:13:21.001 Uttam Kumaran: I think house is good. It’s our sort of fits with the Austin theme. Yeah, you can get honest Mary’s or whatever
150 00:13:21.540 ⇒ 00:13:22.400 Uttam Kumaran: and my.
151 00:13:22.920 ⇒ 00:13:31.010 Uttam Kumaran: I think the biggest thing is to think about yeah, what to present on. But also, even if we just go talk to people like, I think it’d be good. You could have polytomic
152 00:13:31.150 ⇒ 00:13:32.999 Uttam Kumaran: like stuff out. Or
153 00:13:33.260 ⇒ 00:13:37.540 Uttam Kumaran: again, at least, you get a good email list of people. I mean, basically, I think
154 00:13:38.130 ⇒ 00:13:52.300 Uttam Kumaran: a couple, I mean. I don’t know what said, but like it is true that I think, for the most part people, if they’re on 5 train, or if they’re on stitch, hevo, they should be using. You guys, you guys are cheaper, faster, better customer service. So you could kind of like.
155 00:13:52.420 ⇒ 00:13:56.000 Uttam Kumaran: this is where I think I having a great product helps because you should just basically like.
156 00:13:56.250 ⇒ 00:14:08.359 Uttam Kumaran: ask like you, as your you just ask like, with basic leading questions. That could be even good as part of a discussion to be like, has your Etl ever failed? Or have you ever like had like a basically like
157 00:14:09.330 ⇒ 00:14:16.680 Uttam Kumaran: like a pricing scare, where, like something just ramped up in pricing that you never like expected common things like that.
158 00:14:18.152 ⇒ 00:14:23.120 Uttam Kumaran: You can have people explain like. Why, they’re frustrated with their etl or or data movement, or.
159 00:14:23.670 ⇒ 00:14:26.505 Uttam Kumaran: you know, just like sort of gauge that and
160 00:14:26.820 ⇒ 00:14:27.430 Pranab Sachithanandan: Yeah.
161 00:14:27.710 ⇒ 00:14:34.500 Pranab Sachithanandan: I think the Fomo aspect of it is also important of, like, you know, featuring data leaders at Vercel retool.
162 00:14:34.500 ⇒ 00:14:34.960 Uttam Kumaran: Yes.
163 00:14:34.970 ⇒ 00:14:36.109 Pranab Sachithanandan: Big names.
164 00:14:37.960 ⇒ 00:14:46.080 Uttam Kumaran: You should definitely yeah, and you should definitely make it make the luma or whatever invite only or like. You have to basically admit people.
165 00:14:46.080 ⇒ 00:14:46.620 Pranab Sachithanandan: Yup!
166 00:14:50.130 ⇒ 00:14:57.289 Uttam Kumaran: And then I can get like, yeah, I mean, I can get Vc people, or whatever you want to like, how we wanna like, we want to include more logos.
167 00:14:57.760 ⇒ 00:14:58.140 Pranab Sachithanandan: Yep.
168 00:14:59.450 ⇒ 00:15:01.130 Pranab Sachithanandan: Yeah, even if like, yeah.
169 00:15:01.130 ⇒ 00:15:05.369 Uttam Kumaran: Sure I can get someone. I I know some people at Snowflake that are here. I can ask them
170 00:15:08.670 ⇒ 00:15:12.991 Pranab Sachithanandan: That’d be cool. And even if it’s like we think they’ll come, you know, that’s.
171 00:15:13.500 ⇒ 00:15:16.240 Uttam Kumaran: That’s just marketing. That’s just marketing. Yeah.
172 00:15:16.860 ⇒ 00:15:18.850 Pranab Sachithanandan: Oh, for sure, for sure!
173 00:15:19.390 ⇒ 00:15:20.570 Pranab Sachithanandan: Makes sense.
174 00:15:20.940 ⇒ 00:15:23.560 Uttam Kumaran: Who’s where’s his house? Where like? How is that? What is that?
175 00:15:23.730 ⇒ 00:15:31.010 Pranab Sachithanandan: Yeah, yeah, there’s this event called one salon. So one salon.
176 00:15:31.010 ⇒ 00:15:32.950 Uttam Kumaran: Oh, yeah, I haven’t heard of one salon.
177 00:15:32.950 ⇒ 00:15:39.447 Pranab Sachithanandan: Yeah, yeah, I know the people running this. They’re good people so I went to this one in July, and they basically rent from the same place.
178 00:15:41.470 ⇒ 00:15:51.479 Pranab Sachithanandan: yeah. 1 1. 0, 9, Angelina. So it’s an East Side. And yeah, I gotta. I gotta just text. 1st name is Dale. She actually did did data at Google. So maybe she’d be open to join this, too.
179 00:15:51.480 ⇒ 00:15:52.160 Hannah Wang: Oh!
180 00:15:52.530 ⇒ 00:15:55.490 Pranab Sachithanandan: But yeah, it’s just this random house, decent.
181 00:15:55.490 ⇒ 00:15:55.830 Hannah Wang: Wow!
182 00:15:55.830 ⇒ 00:15:57.040 Pranab Sachithanandan: And it’s.
183 00:15:57.040 ⇒ 00:15:58.670 Hannah Wang: Literally a random house.
184 00:15:58.670 ⇒ 00:16:03.680 Pranab Sachithanandan: Yeah, no, literally, it’s just a house and they just I think they just open it up for events and stuff.
185 00:16:05.160 ⇒ 00:16:07.519 Pranab Sachithanandan: Yeah, yeah. But it’s like.
186 00:16:07.880 ⇒ 00:16:08.370 Uttam Kumaran: Oh, yeah.
187 00:16:08.370 ⇒ 00:16:09.310 Uttam Kumaran: Nice.
188 00:16:09.310 ⇒ 00:16:10.070 Pranab Sachithanandan: Good spot.
189 00:16:10.310 ⇒ 00:16:11.849 Uttam Kumaran: I used to live down the street dude.
190 00:16:12.200 ⇒ 00:16:14.150 Pranab Sachithanandan: Oh, nice! Can you say it?
191 00:16:14.520 ⇒ 00:16:19.690 Uttam Kumaran: Yeah, I live. I live like, literally like 2 min away. I just drove by this house yesterday.
192 00:16:19.690 ⇒ 00:16:20.790 Pranab Sachithanandan: Amazing. That’s crazy.
193 00:16:20.790 ⇒ 00:16:22.359 Uttam Kumaran: I didn’t even know that. Okay.
194 00:16:22.670 ⇒ 00:16:23.280 Pranab Sachithanandan: Money.
195 00:16:23.520 ⇒ 00:16:24.400 Uttam Kumaran: Nice.
196 00:16:25.120 ⇒ 00:16:30.789 Pranab Sachithanandan: Yeah, yeah, yeah, sweet. So that sounds good. And then I think, like, honest, Mary’s is like, tasty, healthy. Got awesome food.
197 00:16:30.790 ⇒ 00:16:32.050 Uttam Kumaran: Okay. Yeah.
198 00:16:33.130 ⇒ 00:16:37.410 Pranab Sachithanandan: Yeah, cool. Cool. Yeah. I’ll organize the yeah, the event side. And then.
199 00:16:38.130 ⇒ 00:16:40.238 Uttam Kumaran: So let’s talk about maybe like
200 00:16:41.140 ⇒ 00:16:52.370 Pranab Sachithanandan: Yes, I think for the Graphic like, we’ll basically just need a theme or a title for this event. So I think that’s when we if we nail that today, then I think we’re good. And then I can create the Luma, and I can create the graphic and.
201 00:16:52.370 ⇒ 00:16:55.460 Uttam Kumaran: Kind of make it centered around like data movement.
202 00:16:57.680 ⇒ 00:16:58.120 Pranab Sachithanandan: That’s correct.
203 00:16:58.120 ⇒ 00:17:06.609 Uttam Kumaran: Data movement, or like that way, it stays really heavily on, just like moving stuff around.
204 00:17:07.750 ⇒ 00:17:09.750 Pranab Sachithanandan: Yeah, that’s where I’m like,
205 00:17:12.339 ⇒ 00:17:17.619 Pranab Sachithanandan: I I think yes and no. Yes, or I don’t want it to feel boring. I wanted to still have a some kind of like.
206 00:17:17.890 ⇒ 00:17:19.630 Pranab Sachithanandan: you know, like some kind of like
207 00:17:19.750 ⇒ 00:17:25.435 Pranab Sachithanandan: like, why should people join, you know, like, why should? It’s gotta be something kind of interesting
208 00:17:29.570 ⇒ 00:17:34.189 Pranab Sachithanandan: some vibe of like exclusive invite. Only kind of thing is helpful.
209 00:17:37.140 ⇒ 00:17:37.810 Pranab Sachithanandan: Because I think.
210 00:17:37.810 ⇒ 00:17:43.010 Uttam Kumaran: Oh, you’re so you’re just thinking about making it just like any topic and date like, sort of like.
211 00:17:45.070 ⇒ 00:17:53.279 Uttam Kumaran: I mean, you could just do Austin, data leaders, just because not none of the stuff. You can just make it up. Because, like, there’s no Austin, you can just say, like
212 00:17:54.070 ⇒ 00:17:57.850 Uttam Kumaran: and data. Awesome data leaders meet up or like,
213 00:18:01.550 ⇒ 00:18:04.760 Uttam Kumaran: yeah, something flat, like flattering like that.
214 00:18:05.190 ⇒ 00:18:06.320 Pranab Sachithanandan: Yeah, yeah, yeah, yeah.
215 00:18:06.600 ⇒ 00:18:10.540 Pranab Sachithanandan: yeah, let’s use that. Let’s just use that provisionally. And then we can change it. Like, just to have something.
216 00:18:10.540 ⇒ 00:18:11.420 Uttam Kumaran: Cheerleaders.
217 00:18:11.420 ⇒ 00:18:18.129 Pranab Sachithanandan: Change the title, and then the sub header would just be like an evening of talking about data
218 00:18:18.830 ⇒ 00:18:20.020 Pranab Sachithanandan: with other
219 00:18:21.070 ⇒ 00:18:29.315 Pranab Sachithanandan: flagship. I don’t know. Yeah, I need a blank, something, meet other data people and then sponsored by polytomic and brain forge.
220 00:18:29.690 ⇒ 00:18:32.019 Uttam Kumaran: I’m just gonna write this note here. So it’s like.
221 00:18:32.020 ⇒ 00:18:35.159 Pranab Sachithanandan: Yeah. What do you? What do you? What do you? What do you think I feel like? I feel like this is not.
222 00:18:35.420 ⇒ 00:18:36.460 Uttam Kumaran: What do you think?
223 00:18:36.460 ⇒ 00:18:37.280 Pranab Sachithanandan: Yeah.
224 00:18:39.190 ⇒ 00:18:48.179 Hannah Wang: I mean, I learned I don’t come from a marketing background, but I feel like a lot of marketing. You just kind of make it up and make it more inflated than it sounds. So I do feel like
225 00:18:48.560 ⇒ 00:18:52.360 Hannah Wang: something kind of flattering around those lines makes sense.
226 00:18:52.360 ⇒ 00:18:57.979 Pranab Sachithanandan: Let’s start here, and then we can take this whole thing and put it into oh, 3.
227 00:18:58.760 ⇒ 00:19:03.090 Pranab Sachithanandan: Yeah. And I would say, I would also say for for
228 00:19:03.530 ⇒ 00:19:08.719 Pranab Sachithanandan: I think I think having a nice vibe for the, for the cover makes a big difference.
229 00:19:08.720 ⇒ 00:19:13.490 Uttam Kumaran: Oh, yeah, yeah, that’s where that’s where the team comes in.
230 00:19:13.490 ⇒ 00:19:23.640 Pranab Sachithanandan: 100. Yeah, I think, like, this is like nothing. We shouldn’t copy this. But like this kind of thing is really nice where it’s just like it looks professional. Yeah, join us for an evening of learning drinks and discussion.
231 00:19:26.020 ⇒ 00:19:27.440 Pranab Sachithanandan: Or, yeah, we could say, like.
232 00:19:30.080 ⇒ 00:19:36.360 Pranab Sachithanandan: yeah, like having having having having an enticing type, the future of data that’s kind of like, you know.
233 00:19:38.080 ⇒ 00:19:41.060 Uttam Kumaran: You can just say future data leaders, or like,
234 00:19:43.830 ⇒ 00:19:45.290 Pranab Sachithanandan: Where is data going?
235 00:19:46.830 ⇒ 00:19:49.760 Uttam Kumaran: Yeah, this is where I’m not. I’m like, so out of death, like.
236 00:19:49.760 ⇒ 00:19:50.779 Pranab Sachithanandan: Yeah, yeah, yeah.
237 00:19:51.100 ⇒ 00:19:55.120 Pranab Sachithanandan: so what is what is what is fascinating about data. You know what I mean, what is.
238 00:19:55.600 ⇒ 00:19:57.259 Hannah Wang: Yeah? Ask? AI.
239 00:19:57.410 ⇒ 00:19:59.450 Pranab Sachithanandan: Ask chat, gpt.
240 00:19:59.450 ⇒ 00:20:04.740 Uttam Kumaran: You’re asking like I’m the I’m the data engineer on the call. I I don’t know. I don’t know. It’s not very fast.
241 00:20:04.740 ⇒ 00:20:07.749 Pranab Sachithanandan: What’s what’s on your mind these days? What do you.
242 00:20:07.880 ⇒ 00:20:10.560 Uttam Kumaran: My mind is growing the company.
243 00:20:11.983 ⇒ 00:20:18.879 Uttam Kumaran: No, I mean, I think, Austin, data leaders stuff like that is flattering. Especially get invited to it.
244 00:20:19.850 ⇒ 00:20:30.499 Uttam Kumaran: I just realized you sort of lead with flattery. And so something around that. But again, I I think maybe that’s just good nugget nugget to start with, and maybe we should iterate with Gpt or something.
245 00:20:30.500 ⇒ 00:20:32.199 Pranab Sachithanandan: Yeah, yeah, yeah, I think.
246 00:20:33.280 ⇒ 00:20:54.880 Pranab Sachithanandan: yeah. And I think, having it, I’ll I’ll do it on Luma, the invite only kind of thing, or like an approval. So you have to get approved for it. And that way it kind of like keeps it, you know. Hide the invite list and stuff like that? Yeah, I think I think an event cover. That is this design that we can maybe swap some of the stuff out for makes sense, but like cool picture cool colors, we’ll keep the same. Join us for an evening, and then, like
247 00:20:55.530 ⇒ 00:21:02.980 Pranab Sachithanandan: polytomic and brainforge presents, and then for the title, we’ll do you know the title? And then in parentheses presented by polytomic and brainforge.
248 00:21:02.980 ⇒ 00:21:03.620 Uttam Kumaran: Cool.
249 00:21:03.910 ⇒ 00:21:09.629 Uttam Kumaran: Did we get your like media, like our Logos and stuff.
250 00:21:09.630 ⇒ 00:21:11.299 Pranab Sachithanandan: I can send those to you.
251 00:21:11.300 ⇒ 00:21:12.516 Uttam Kumaran: Okay, that’d be great.
252 00:21:15.250 ⇒ 00:21:24.419 Hannah Wang: So, for, like all the designs and stuff, I feel like with previous promotions, that we did have, like a brain forge theme design, and like the
253 00:21:25.030 ⇒ 00:21:31.040 Hannah Wang: the other company’s theme design is that. And we also like post on Linkedin and stuff. So I guess, like.
254 00:21:31.370 ⇒ 00:21:32.819 Hannah Wang: yeah, what are do you wanna make.
255 00:21:32.820 ⇒ 00:21:37.900 Uttam Kumaran: You should try to merge, I mean, I think. Well, I thought Polycom was also kind of green right.
256 00:21:37.900 ⇒ 00:21:46.130 Pranab Sachithanandan: Yeah, I’m not really have much of a design. If you can just slap our logo on top of it, we’re good to go. So I think, yeah, do what you want with Brainforge stuff. And.
257 00:21:46.387 ⇒ 00:21:55.650 Uttam Kumaran: Think maybe like white, because you guys is like, kind of like, just at least we could do white. And then our green, or maybe something like with a mix. I mean, the logo is great.
258 00:21:57.570 ⇒ 00:21:59.890 Pranab Sachithanandan: Yeah, yeah, this is our.
259 00:21:59.890 ⇒ 00:22:01.460 Hannah Wang: Okay.
260 00:22:02.480 ⇒ 00:22:02.850 Pranab Sachithanandan: Awesome.
261 00:22:02.850 ⇒ 00:22:09.003 Hannah Wang: I’ve seen that logo a lot. I’ve used that logo everywhere in all our assets, so I’m quite familiar with your colors and stuff.
262 00:22:10.890 ⇒ 00:22:11.900 Pranab Sachithanandan: Sounds good.
263 00:22:12.340 ⇒ 00:22:14.180 Uttam Kumaran: Yeah, even your case is just light.
264 00:22:14.450 ⇒ 00:22:18.470 Uttam Kumaran: I mean, it’s kind of clean. So yeah, maybe it’s white. It’s just white in our green. Hannah.
265 00:22:18.960 ⇒ 00:22:19.380 Hannah Wang: Okay.
266 00:22:19.380 ⇒ 00:22:21.999 Uttam Kumaran: I don’t think their white is particularly
267 00:22:22.610 ⇒ 00:22:25.340 Uttam Kumaran: like any sort of distinct way. But
268 00:22:26.340 ⇒ 00:22:29.369 Uttam Kumaran: there’s also this kind of like blue. Yeah, I don’t know.
269 00:22:30.010 ⇒ 00:22:34.509 Pranab Sachithanandan: Oh, and let me know if we can get on your website. Your little scroll bar, cool scroll, bar.
270 00:22:35.540 ⇒ 00:22:41.139 Uttam Kumaran: Oh, yeah, you’re the 1st person to ask. Oh, we should totally. I mean, we just haven’t updated in a sec. But.
271 00:22:41.410 ⇒ 00:22:41.800 Hannah Wang: Yeah.
272 00:22:41.800 ⇒ 00:22:45.940 Uttam Kumaran: We’re gonna we’re gonna we need actually update with so many more Logos.
273 00:22:46.240 ⇒ 00:22:50.420 Uttam Kumaran: Yes, we should. We should. We should replace 5 train, or at least bump them back.
274 00:22:50.990 ⇒ 00:22:52.590 Pranab Sachithanandan: What do you think of the acquisition news.
275 00:22:53.736 ⇒ 00:22:59.089 Uttam Kumaran: I don’t know. I was talking to someone about it today. I was mainly like
276 00:22:59.766 ⇒ 00:23:06.290 Uttam Kumaran: I don’t know company. Some like I saw that census guy just like stop posting on Linkedin for a while.
277 00:23:06.530 ⇒ 00:23:24.490 Uttam Kumaran: and I was talking to I was talking to the head of sales at real Sid. He was like he was like, we’re noticing the same thing with evidence with another bi tool. And I was kind of like, yeah, I wonder if these guys just sort of silently fail. And then they like, get bought. And he’s like, it’s definitely like a aqua hire. But
278 00:23:26.290 ⇒ 00:23:32.159 Uttam Kumaran: yeah, I don’t know I’m talking to someone very senior at 5 trend next week, a friend of mine.
279 00:23:32.300 ⇒ 00:23:38.149 Uttam Kumaran: So that I’ll ask. That’s my 1st question. Yeah, find out.
280 00:23:38.150 ⇒ 00:23:42.519 Pranab Sachithanandan: That was gollip steak he was like. They didn’t announce how much they were requiring for.
281 00:23:42.520 ⇒ 00:23:47.579 Uttam Kumaran: Yeah, you never. Yeah. It’s dude. This industry is so sham like
282 00:23:48.080 ⇒ 00:23:54.759 Uttam Kumaran: such a sham. And even 5, 10 raise a ton of money. So I think they’re just looking to deploy capital and
283 00:23:55.050 ⇒ 00:24:04.290 Uttam Kumaran: your post about it was good, though your post was really good. I actually need to repost it. I was, gonna wait. Yeah, I’ll repost and say something. Cause that was really, really, that’s actually, really, really like.
284 00:24:04.860 ⇒ 00:24:06.520 Uttam Kumaran: yeah, it’s like super accurate.
285 00:24:06.690 ⇒ 00:24:30.910 Pranab Sachithanandan: Yeah, I appreciate that. No, my take was like, Oh, this is actually really good for us, because their millions of dollars of marketing is now going to be pushing the message that is helpful for us, which is like, you know. And it’s funny, because both on the census side and the 5 5. Their marketing materials had like strategic frames that were basically like, pro polytomic. It’s like, Yes, we’re trying to get across. Yes, you know.
286 00:24:31.690 ⇒ 00:24:32.030 Uttam Kumaran: That’s all.
287 00:24:32.030 ⇒ 00:24:32.370 Pranab Sachithanandan: It’s like.
288 00:24:32.370 ⇒ 00:24:33.390 Uttam Kumaran: That’ll be great.
289 00:24:33.390 ⇒ 00:24:37.410 Pranab Sachithanandan: Like bidirectional. Etl is kind of a new category like it’s not. It’s not really a thing yet.
290 00:24:38.060 ⇒ 00:24:41.249 Pranab Sachithanandan: So it’s kind of like framing it as that, and people.
291 00:24:41.250 ⇒ 00:24:45.759 Uttam Kumaran: Yeah. But do 5, 10. These guys are slow and like that company is very bloated like.
292 00:24:46.170 ⇒ 00:24:48.469 Uttam Kumaran: either they’re gonna make it to Ipo or like
293 00:24:48.870 ⇒ 00:24:52.079 Uttam Kumaran: something’s gonna happen, because they’re very, very bloated company.
294 00:24:52.370 ⇒ 00:24:59.219 Pranab Sachithanandan: Yeah, yeah, yeah, I think census like, yeah, their valuation they’re at like 2 50 million or something or something crazy. And I don’t think they got bought for that much. So.
295 00:24:59.220 ⇒ 00:25:01.629 Uttam Kumaran: Well, isn’t but high touch pivoted right.
296 00:25:01.630 ⇒ 00:25:04.299 Pranab Sachithanandan: Yeah, yeah, yeah, towards audiences. And.
297 00:25:04.520 ⇒ 00:25:05.660 Uttam Kumaran: Yeah, yeah.
298 00:25:05.660 ⇒ 00:25:06.860 Pranab Sachithanandan: Personalization, side.
299 00:25:06.860 ⇒ 00:25:12.389 Uttam Kumaran: Yeah, the census guys. I mean, that guy was like, really, for like a like 2 years there, like
300 00:25:13.380 ⇒ 00:25:18.980 Uttam Kumaran: all I could see is like high touch or census related stuff. And like.
301 00:25:19.460 ⇒ 00:25:21.540 Uttam Kumaran: yeah, I don’t know. It sort of just dropped off.
302 00:25:21.890 ⇒ 00:25:22.530 Pranab Sachithanandan: Yeah.
303 00:25:22.530 ⇒ 00:25:23.110 Uttam Kumaran: Yeah.
304 00:25:25.540 ⇒ 00:25:31.920 Pranab Sachithanandan: Nice, cool, alright. Well, this is this, feels this feels good. I I’m I’m yeah. I’ll get you guys. Monday. Yeah.
305 00:25:31.980 ⇒ 00:25:35.790 Uttam Kumaran: Hannah. Anything else we need like. We probably need headshots.
306 00:25:37.300 ⇒ 00:25:38.130 Hannah Wang: Yeah.
307 00:25:38.960 ⇒ 00:25:39.630 Pranab Sachithanandan: Lip.
308 00:25:41.290 ⇒ 00:25:43.730 Uttam Kumaran: I’ll just from Linkedin. So I’ll just send that to you, okay.
309 00:25:43.730 ⇒ 00:25:46.555 Hannah Wang: Shop and headshot, and bio
310 00:25:47.120 ⇒ 00:25:49.140 Pranab Sachithanandan: Cool. I’ll get that. Yeah, I’ll get both those to you.
311 00:25:49.370 ⇒ 00:25:49.990 Uttam Kumaran: Yeah.
312 00:25:49.990 ⇒ 00:25:50.340 Hannah Wang: And then.
313 00:25:50.340 ⇒ 00:25:52.280 Uttam Kumaran: Any way, you can get the original image.
314 00:25:53.590 ⇒ 00:25:54.230 Uttam Kumaran: So, yeah.
315 00:25:54.230 ⇒ 00:25:55.454 Hannah Wang: So it’s not as grainy.
316 00:25:56.590 ⇒ 00:25:57.700 Pranab Sachithanandan: Doing something. Yeah.
317 00:25:58.560 ⇒ 00:26:09.099 Hannah Wang: So is there anything that you need from our side? I’m assuming, like we can take on all the design stuff? But is there anything that you guys need? I know the Luma?
318 00:26:09.280 ⇒ 00:26:10.259 Hannah Wang: Yeah, I can.
319 00:26:10.260 ⇒ 00:26:16.470 Uttam Kumaran: Rob. Once once you get the Luma, can you just share with us? What like?
320 00:26:16.600 ⇒ 00:26:24.246 Uttam Kumaran: I don’t know what images, sizes we need to do like we. I have actually have a couple of other ones that we can look at. But
321 00:26:25.660 ⇒ 00:26:27.780 Uttam Kumaran: yeah, I think that’s the only thing.
322 00:26:27.940 ⇒ 00:26:33.280 Pranab Sachithanandan: I think, 16 9 should be good.
323 00:26:34.580 ⇒ 00:26:35.900 Hannah Wang: For Luma. Okay.
324 00:26:38.510 ⇒ 00:26:43.100 Pranab Sachithanandan: Yeah, let me let me actually let me just open it up right now, just to confirm.
325 00:26:43.280 ⇒ 00:26:47.930 Uttam Kumaran: And then we’ll also do. We’ll also generate a bunch of the copy
326 00:26:48.941 ⇒ 00:26:51.680 Uttam Kumaran: for like content that you can use.
327 00:26:51.900 ⇒ 00:26:53.060 Pranab Sachithanandan: My sorry. Say it again.
328 00:26:53.060 ⇒ 00:26:57.470 Uttam Kumaran: We’ll generate like copy for like content like.
329 00:26:57.660 ⇒ 00:27:03.870 Uttam Kumaran: And then do we want to put out any like materials together
330 00:27:06.970 ⇒ 00:27:09.140 Uttam Kumaran: that we can send to everyone as like.
331 00:27:10.860 ⇒ 00:27:12.450 Hannah Wang: Basically after.
332 00:27:16.260 ⇒ 00:27:18.350 Pranab Sachithanandan: Yeah, like, what’s the next call to action after this.
333 00:27:18.760 ⇒ 00:27:35.650 Uttam Kumaran: Yeah, I mean, you know what we did for one of the events is we put out like a white paper with our, with our the guy. We were doing it with their company about using AI and consulting it was pretty good, actually. And and we sent it out to a bunch of people, and then we actually just now have it behind the landing page.
334 00:27:37.140 ⇒ 00:27:41.099 Uttam Kumaran: So I don’t know whether it’s like we could do a joint like.
335 00:27:42.600 ⇒ 00:27:44.790 Uttam Kumaran: Maybe I’ll think about it, and we could do something.
336 00:27:45.240 ⇒ 00:27:47.770 Uttam Kumaran: either a joint customer story or like
337 00:27:48.070 ⇒ 00:27:56.429 Uttam Kumaran: how we work together. And we could just put something up, because also, then, I’m gonna I’ll just leave that up as a landing page, and we’ll have that collateral. And then.
338 00:27:57.470 ⇒ 00:27:58.369 Pranab Sachithanandan: Yeah, I would say.
339 00:27:58.370 ⇒ 00:28:10.950 Uttam Kumaran: For me the reason why I I want to have that, because now, when anyone asks about us, I’ll say like, Oh, check out! Go check out this landing page to see like how we work with them. And we’re starting to generate that for every like of our core vendors.
340 00:28:10.950 ⇒ 00:28:12.550 Pranab Sachithanandan: Yeah, yeah.
341 00:28:12.660 ⇒ 00:28:25.218 Pranab Sachithanandan: yeah, I’m happy to. If you have like a template for that, I’m happy to fill in. And we could just have one page like hosted on words that has some stuff on polytomic. And I think on your side, if there’s yeah like for the ideal, let’s say, like
342 00:28:26.190 ⇒ 00:28:45.799 Pranab Sachithanandan: If the target is like heads of data data, engineers, heads of data, heads of engineering, heads of data, analytics. However, you guys would work with that kind of person and the kind of projects that you would help in on you. Can. That can be some of the stuff that’s featured. When we leave, and some of those talking points during the intros.
343 00:28:46.380 ⇒ 00:28:47.000 Uttam Kumaran: Okay.
344 00:28:47.150 ⇒ 00:28:53.469 Uttam Kumaran: The only sort of random advice I got from somebody recently was
345 00:28:54.149 ⇒ 00:28:56.629 Uttam Kumaran: cause I was talking about SEO. He’s like
346 00:28:56.830 ⇒ 00:29:00.359 Uttam Kumaran: he’s like dude. You should just you should start hammering press releases.
347 00:29:00.500 ⇒ 00:29:04.419 Uttam Kumaran: so maybe we could do like a pr newswire
348 00:29:04.660 ⇒ 00:29:08.219 Uttam Kumaran: and like some sort of joint partnership copy.
349 00:29:08.690 ⇒ 00:29:15.980 Uttam Kumaran: He was like, it gets you back linked somewhere with high Dr. And then it gets picked up by other publications.
350 00:29:16.130 ⇒ 00:29:18.040 Uttam Kumaran: And I’m like, Okay, I’ll ask. I’ll ask.
351 00:29:18.280 ⇒ 00:29:24.159 Pranab Sachithanandan: I’ve I’ve worked with Pr news like a bunch of the previous companies. I I don’t ever think it’s really that worth it.
352 00:29:24.160 ⇒ 00:29:31.810 Uttam Kumaran: Oh, right? Okay. I mean, I don’t care. He was just like you should consider it, because it’ll get you higher domain rating for like SEO.
353 00:29:31.810 ⇒ 00:29:32.679 Pranab Sachithanandan: I see it’s.
354 00:29:32.680 ⇒ 00:29:34.730 Uttam Kumaran: I don’t think it’s not about like.
355 00:29:35.190 ⇒ 00:29:40.269 Uttam Kumaran: yeah, I mean, not dude. It’s not on dry. I like, yeah. People put stuff out there all the time. I think it’s
356 00:29:40.530 ⇒ 00:29:41.960 Uttam Kumaran: primarily just for that.
357 00:29:42.260 ⇒ 00:29:46.797 Pranab Sachithanandan: Yeah, yeah, I I for Dr, I think there’s a lot of better ways to get high. Dr.
358 00:29:47.330 ⇒ 00:29:48.060 Pranab Sachithanandan: yeah, yeah.
359 00:29:48.060 ⇒ 00:29:52.249 Uttam Kumaran: Really okay. Then I then I then I direct to you, because I’m just talking out of my ass. Now.
360 00:29:52.250 ⇒ 00:30:04.640 Pranab Sachithanandan: No, no, you’re no, it makes sense. I think I think I’ve I’ve like at the last few startups I’ve been at. We like thought about it, paid for it and see no effect. So I’m just like, yeah, especially at the Dr. You guys are at, which is, let me just check real quick.
361 00:30:05.200 ⇒ 00:30:06.420 Uttam Kumaran: We’re okay.
362 00:30:06.930 ⇒ 00:30:15.420 Pranab Sachithanandan: Yeah, yeah. A h ref tr checker, you guys are.
363 00:30:17.100 ⇒ 00:30:20.199 Pranab Sachithanandan: oh, you’re pretty low, actually, only 9. Yeah. So I think
364 00:30:20.460 ⇒ 00:30:27.875 Pranab Sachithanandan: so. I think once you get to like 1520, yeah, I would. I would. I would say, there’s better way. There’s better ways to do it. But
365 00:30:29.740 ⇒ 00:30:33.569 Pranab Sachithanandan: yeah, you could actually have a bit of a better domain rating. That’s interesting.
366 00:30:34.720 ⇒ 00:30:39.829 Uttam Kumaran: If you have ideas, you should totally talk to Ryan. He’s out of office today. But he would have loved to ask you like a bunch of questions.
367 00:30:39.830 ⇒ 00:30:41.010 Pranab Sachithanandan: Is he a growth guy.
368 00:30:41.010 ⇒ 00:30:47.635 Uttam Kumaran: Yeah, yeah, he’s doing it. Well, he’s sort of doing everything like copywriting, but it does all of our SEO and all of our like,
369 00:30:48.230 ⇒ 00:30:53.088 Uttam Kumaran: blog. And like, yeah, everything SEO and sort of growth on.
370 00:30:53.530 ⇒ 00:31:13.621 Pranab Sachithanandan: I feel like for you guys, I mean, since you’re like a service provider, there are a ton of service provider listing directories. So if you get listed in all of those those usually are like good high authority backlinks with with it’s called, do follow. A lot of these listing directories are no follow. So even though you get listed, they don’t give you any SEO juice, but I feel like most of these will be pretty good for you.
371 00:31:14.950 ⇒ 00:31:18.479 Uttam Kumaran: I just look up like, for example, like Cloud tango is like.
372 00:31:20.140 ⇒ 00:31:26.940 Uttam Kumaran: it’s like this, basically, yeah, it looks like just some service provider listing. I mean, I have us listed on like some of the common ones.
373 00:31:28.030 ⇒ 00:31:32.609 Pranab Sachithanandan: Another one is like, if you, if you do this like, who’s a competitor of yours?
374 00:31:33.280 ⇒ 00:31:34.750 Uttam Kumaran: Ph data.
375 00:31:38.250 ⇒ 00:31:45.669 Pranab Sachithanandan: So if you check their authority, so they oh, wow! There’s a.
376 00:31:46.860 ⇒ 00:31:48.600 Uttam Kumaran: They’re a big company. They’re not like
377 00:31:48.880 ⇒ 00:31:52.939 Uttam Kumaran: competitor of ours. I don’t know. I mean, I think they’re we compete. But.
378 00:31:52.940 ⇒ 00:31:58.319 Pranab Sachithanandan: So I would say, like, if you have, if you guys have a tool like this, you can scrape all of the backlink profile.
379 00:31:58.320 ⇒ 00:32:00.520 Uttam Kumaran: Oh, and just try to get listed there.
380 00:32:00.520 ⇒ 00:32:01.490 Pranab Sachithanandan: Yeah, yeah, you’ll get.
381 00:32:01.490 ⇒ 00:32:03.189 Uttam Kumaran: You’re a genius.
382 00:32:03.190 ⇒ 00:32:05.670 Pranab Sachithanandan: This is the usual. Yeah, exactly. This is like a really.
383 00:32:05.670 ⇒ 00:32:07.280 Uttam Kumaran: So smart. Heck!
384 00:32:08.860 ⇒ 00:32:19.619 Pranab Sachithanandan: For sure. Yeah, this is. This is one of the best ways to do that, and then half them. Like most of them, you can just kind of send an email and you’re on there. Maybe some. You have to pitch them, but you can ignore those. But yeah, this is, I would just do this. This is like the best.
385 00:32:20.153 ⇒ 00:32:21.219 Uttam Kumaran: All right.
386 00:32:21.220 ⇒ 00:32:22.960 Pranab Sachithanandan: Yeah, yeah.
387 00:32:22.960 ⇒ 00:32:26.160 Uttam Kumaran: Okay, well, I gotta jump to another client thing.
388 00:32:26.160 ⇒ 00:32:28.639 Pranab Sachithanandan: Yeah, yeah, cool, sweet. Good to meet you guys. Good to meet you guys.
389 00:32:28.860 ⇒ 00:32:32.229 Hannah Wang: Yeah, we can talk on slack and just communicate there.
390 00:32:32.470 ⇒ 00:32:33.010 Uttam Kumaran: Cool.
391 00:32:33.310 ⇒ 00:32:33.980 Pranab Sachithanandan: Cool.
392 00:32:33.980 ⇒ 00:32:34.889 Hannah Wang: How are y’all.
393 00:32:34.890 ⇒ 00:32:35.250 Uttam Kumaran: Happy Friday.
394 00:32:35.820 ⇒ 00:32:36.960 Uttam Kumaran: Happy Friday. Bye.