Meeting Title: Zoom Meeting Date: 2025-02-19 Meeting participants: Nicolas Sucari, Uttam Kumaran, Payas Parab, Bo Yoon
WEBVTT
1 00:00:35.450 ⇒ 00:00:36.480 Nicolas Sucari: Hey! Bayas!
2 00:00:36.710 ⇒ 00:00:38.039 Payas Parab: Hey, Nico! How are you?
3 00:00:40.650 ⇒ 00:00:42.179 Nicolas Sucari: All good. How are you.
4 00:00:43.100 ⇒ 00:00:44.010 Payas Parab: Good.
5 00:00:55.650 ⇒ 00:00:56.410 Uttam Kumaran: Hey, guys.
6 00:00:57.530 ⇒ 00:00:58.870 Payas Parab: Hey, Tom, how are you.
7 00:00:58.870 ⇒ 00:00:59.640 Uttam Kumaran: Hey! Good!
8 00:01:04.720 ⇒ 00:01:06.090 Payas Parab: What’s your dog’s name? Again?
9 00:01:07.060 ⇒ 00:01:08.310 Uttam Kumaran: His name is Finn.
10 00:01:08.480 ⇒ 00:01:09.769 Payas Parab: Finn. That’s right.
11 00:01:10.000 ⇒ 00:01:12.520 Payas Parab: Yo, Finn, big dog.
12 00:01:14.030 ⇒ 00:01:16.840 Uttam Kumaran: He ran around outside for a while. He’s tired now.
13 00:01:17.090 ⇒ 00:01:24.409 Payas Parab: Bang awesome. Well, we wanted to say, get through
14 00:01:24.550 ⇒ 00:01:34.897 Payas Parab: essentially, just like all the types of analysis you guys have done with them before we sort of made that document where we’re like, okay, here’s all the data sets that we have access to. Here’s you know what type of
15 00:01:35.310 ⇒ 00:01:40.542 Payas Parab: if you would be just really helpful if like. And I’m gonna pull up that, doc and just take notes there, just like, what
16 00:01:41.310 ⇒ 00:01:47.540 Payas Parab: What have we done in the past, or actually, I’ll make a different one, because I think we shared that with them already, or was linked somewhere.
17 00:01:49.750 ⇒ 00:01:55.554 Uttam Kumaran: Yeah, if you can. If you can guide me by like, domain by domain, I can sort of just
18 00:01:56.130 ⇒ 00:01:57.930 Payas Parab: Yeah, it was done.
19 00:01:59.287 ⇒ 00:02:00.222 Payas Parab: Let me
20 00:02:01.760 ⇒ 00:02:02.950 Payas Parab: Let’s pull up that.
21 00:02:13.480 ⇒ 00:02:26.089 Payas Parab: Yeah. So I can go through. I think the best way to kind of look through. It is just like, sort of what data we have available. Right? Like, I’m I basically looked through like, here’s all the production marks that we have so I guess the 1st thing would be affiliates.
22 00:02:27.250 ⇒ 00:02:34.820 Uttam Kumaran: Yeah. So on the marketing side for affiliates, we are getting our marketing data from this company called Cj.
23 00:02:34.820 ⇒ 00:02:35.460 Payas Parab: Okay.
24 00:02:35.990 ⇒ 00:02:43.510 Uttam Kumaran: We haven’t done anything except for ad reporting on like, basically just reporting.
25 00:02:43.510 ⇒ 00:02:43.830 Payas Parab: Okay.
26 00:02:43.830 ⇒ 00:02:44.690 Uttam Kumaran: Performance.
27 00:02:49.190 ⇒ 00:02:54.880 Payas Parab: Got it. Got it? So basically, cj, are, they like they’re like in a
28 00:02:56.280 ⇒ 00:03:05.190 Payas Parab: affiliate network, or like a service provider that then like has their own little network of like affiliates that they’re like launching campaigns with and things like that, and just reporting back at aggregate to them.
29 00:03:05.430 ⇒ 00:03:06.200 Uttam Kumaran: Correct.
30 00:03:06.590 ⇒ 00:03:07.070 Payas Parab: Got it.
31 00:03:07.070 ⇒ 00:03:07.880 Payas Parab: Okay.
32 00:03:09.770 ⇒ 00:03:12.129 Uttam Kumaran: So broadly on the Ad. Side.
33 00:03:12.130 ⇒ 00:03:12.629 Payas Parab: Like we have.
34 00:03:13.480 ⇒ 00:03:13.830 Payas Parab: Yeah.
35 00:03:18.520 ⇒ 00:03:19.630 Payas Parab: On the ad side.
36 00:03:19.820 ⇒ 00:03:21.861 Uttam Kumaran: Yeah on the ad side.
37 00:03:22.850 ⇒ 00:03:28.139 Uttam Kumaran: they’re spending across all major ad platforms.
38 00:03:28.677 ⇒ 00:03:50.040 Uttam Kumaran: They are also doing things with affiliates. They’re also doing things with post pilot. They have tested out doing sort of one off like ugc, things like that. The only thing we are giving to them on the marketing side. Is sort of overall ad performance
39 00:03:50.220 ⇒ 00:03:59.720 Uttam Kumaran: related to measurements with the site they’re using. Ga on the website. We haven’t gone anywhere beyond just measuring on total performance. There.
40 00:03:59.830 ⇒ 00:04:00.780 Payas Parab: Okay.
41 00:04:02.080 ⇒ 00:04:10.219 Uttam Kumaran: Yeah, we haven’t gone. We haven’t gone deep on marketing at all. The other thing is, we haven’t done. We haven’t really done any sort of serious work on
42 00:04:10.924 ⇒ 00:04:13.950 Uttam Kumaran: the event analytics for their site.
43 00:04:16.180 ⇒ 00:04:22.523 Uttam Kumaran: We’re just bringing in raw page views and stuff and then sort of doing sums, you know.
44 00:04:22.850 ⇒ 00:04:25.820 Payas Parab: Got it. And where is that? Let me check. Is that housed in
45 00:04:27.040 ⇒ 00:04:29.909 Payas Parab: Snowflake, or is there? Is there a 3rd party tool? There.
46 00:04:30.711 ⇒ 00:04:34.790 Uttam Kumaran: No, that’s all. It’s all in Snowflake. If in the if you go into.
47 00:04:35.340 ⇒ 00:04:40.450 Uttam Kumaran: there’s like a combined marketing table that has everything.
48 00:04:44.040 ⇒ 00:04:48.650 Nicolas Sucari: Yeah, I think it’s called combined marketing performance that we have there in Snowflake.
49 00:04:50.540 ⇒ 00:04:56.710 Payas Parab: Got it. So you said, we haven’t done any analytics on like so like page views. And we have like events from the website, right and like what actually.
50 00:04:56.710 ⇒ 00:05:03.130 Uttam Kumaran: Yeah, we’re just exactly like we have. We didn’t go through an audit sort of what their conversion points are.
51 00:05:03.610 ⇒ 00:05:05.580 Uttam Kumaran: We didn’t do anything around.
52 00:05:07.020 ⇒ 00:05:10.469 Uttam Kumaran: Yeah, like what people, what events are firing? Nothing like that.
53 00:05:10.960 ⇒ 00:05:11.680 Payas Parab: Got it.
54 00:05:13.070 ⇒ 00:05:29.800 Payas Parab: Okay, that’s a great starting point. So for marketing, what I’m reading is basically, yeah, we have like event tracking on the website is like, sort of like a big thing that like we haven’t really explored yet. Even the campaign level performance beyond just aggregating it is like nothing that we’ve touched yet on the marketing side.
55 00:05:30.140 ⇒ 00:05:31.479 Uttam Kumaran: That’s correct. Yeah.
56 00:05:31.480 ⇒ 00:05:32.726 Payas Parab: Excellent. Okay.
57 00:05:33.350 ⇒ 00:05:35.900 Uttam Kumaran: To give you the overall. Yeah.
58 00:05:36.461 ⇒ 00:05:52.519 Uttam Kumaran: to give you the overall. So Kim is sort of running all marketing. She’s mainly in the ui, and she does some stuff in spreadsheets. Ben is concerned with lowering, marketing spend, or Aka like making it more efficient.
59 00:05:52.680 ⇒ 00:06:15.800 Uttam Kumaran: Dan is probably more on the side of like keep spending I don’t think they have a good idea about what has what has worked in the past. They have. This business has been running very anecdotally so they have feelings about sort of how things are going. And they’ve they’ve it’s they’ve continued to double down on those when they see any list, but nothing like
60 00:06:16.320 ⇒ 00:06:20.120 Uttam Kumaran: nothing’s like really clear for them on like whether what’s working or not.
61 00:06:20.480 ⇒ 00:06:34.399 Payas Parab: On the marketing side, like, let’s if we think about the marketing you kind of mentioned like Kim, you have Dan Ben right like, and especially like I am not familiar. And like, I’m sure Bo definitely isn’t right. What are the dynamics between these types of people? Could we even get like just a little bit about their like personality.
62 00:06:34.400 ⇒ 00:06:34.800 Uttam Kumaran: That’s right.
63 00:06:34.800 ⇒ 00:06:41.079 Payas Parab: You mentioned, like great feedback around like, you don’t know these guys. But they don’t like emails like this, right? But we’re like, we’re just trying to do our job. Right?
64 00:06:41.080 ⇒ 00:06:41.740 Payas Parab: Yeah, yeah.
65 00:06:41.740 ⇒ 00:06:53.599 Payas Parab: like, if you could just kind of walk through those 3 people and let’s even step away from marketing. Just like, are these people? How do they operate that type of thing? Just we have like a sense of like the stakeholders. Yeah.
66 00:06:54.300 ⇒ 00:06:57.629 Uttam Kumaran: So Dan is a CEO Dan previously ran
67 00:06:58.298 ⇒ 00:07:01.712 Uttam Kumaran: like a really massive marketing agency.
68 00:07:03.770 ⇒ 00:07:10.430 Uttam Kumaran: This company actually was not founded by Dan pool parts. Was
69 00:07:10.660 ⇒ 00:07:17.960 Uttam Kumaran: Dan’s wife’s dad’s company. Originally they were just selling pool parts in
70 00:07:18.140 ⇒ 00:07:21.709 Uttam Kumaran: like 2 retail stores in Long Island
71 00:07:22.275 ⇒ 00:07:27.398 Uttam Kumaran: came in and basically turned this into like a massive business.
72 00:07:28.750 ⇒ 00:07:47.610 Uttam Kumaran: basically switching to start doing ecom. They’re also doing wholesale. They got this very exclusive license with black and decker, which no other sort of manufacturer has. They now have multiple parts of business. They sell retail, they have the Ecom, which we have only really touched. Ecom. You guys are now being a bit about
73 00:07:47.730 ⇒ 00:07:59.943 Uttam Kumaran: the broader like. You know strategy across the other businesses. So far I’ve I’ve only been working on the com side. Dan is like,
74 00:08:01.376 ⇒ 00:08:10.049 Uttam Kumaran: dan has a lot of familiarity about the data world and sort of what we can do. And he’s actually the main reason we’re here.
75 00:08:11.030 ⇒ 00:08:25.050 Uttam Kumaran: He knows that in order to make this like a data driven business, and to make sure, we have data available for when they want to get investment. They want to try new things. They need data. He’s always pushed us to do things like
76 00:08:25.400 ⇒ 00:08:30.310 Uttam Kumaran: think like, very far ahead. And things like the weather analysis.
77 00:08:30.480 ⇒ 00:08:38.430 Uttam Kumaran: Probably they want some reverse, Etls. They want us to do everything. They were our 1st client, though, so to give you. So I I got them
78 00:08:38.760 ⇒ 00:08:42.749 Uttam Kumaran: from another friend of a friend who was about to drop them as a client, because.
79 00:08:43.120 ⇒ 00:08:45.520 Uttam Kumaran: he said, like they were really tough to work with.
80 00:08:45.960 ⇒ 00:08:46.340 Payas Parab: Good.
81 00:08:46.360 ⇒ 00:08:48.530 Uttam Kumaran: Time terms, I said.
82 00:08:48.960 ⇒ 00:09:02.139 Uttam Kumaran: Those are like my people like I don’t. I don’t, really. I don’t worry too much about that, and it’s tough. They are both very much interested in data, but because they’ve ran this, they’ve run this business sort of on touch.
83 00:09:03.600 ⇒ 00:09:16.629 Uttam Kumaran: If the data doesn’t necessarily line up with what they think. They ask the next question next question. So everything we show we have to be ready to go. 2, 3, 4, 5 layers deep. But Dan is really like
84 00:09:17.160 ⇒ 00:09:40.810 Uttam Kumaran: there have been weeks where we haven’t done anything, and he’s we’re still. He’s still pushing us to sort of try to get stuff done and really is is forward on data. Ben, we built a really great relationship from, I think we’ve accomplished some really big wins with him. That sort of turned his head on our our usefulness. I think before that I think he probably would have been like, you’re just consultants like you’re just taking
85 00:09:41.140 ⇒ 00:09:43.620 Uttam Kumaran: and like not doing anything. We.
86 00:09:43.620 ⇒ 00:09:46.679 Payas Parab: What were some of those wins? What were some of those wins? Sorry to interrupt.
87 00:09:46.680 ⇒ 00:09:53.709 Uttam Kumaran: Yeah, the biggest thing is one we sort of were able to finally give them a view of shopify and Amazon. In one place
88 00:09:54.640 ⇒ 00:10:02.300 Uttam Kumaran: we also ha gave them. We also were able to enable them to do A huge renegotiation of their ups contract.
89 00:10:02.300 ⇒ 00:10:02.830 Payas Parab: Okay.
90 00:10:02.830 ⇒ 00:10:15.919 Uttam Kumaran: Like hundreds of thousands of dollars there, we basically were able to look at all their past shipments, get the rate card from Fedex, rep that into sequel, and then able to forecast in the future what their.
91 00:10:15.920 ⇒ 00:10:16.350 Payas Parab: It’s good.
92 00:10:16.350 ⇒ 00:10:30.479 Uttam Kumaran: Shipping costs were. And then basically able to say, this is what you’re gonna pay. Let’s take that Fedex and and ups and renegotiate. And so we actually handled the renegotiation, and we save them like a ton of money. Got it.
93 00:10:30.670 ⇒ 00:10:49.579 Uttam Kumaran: We also worked a lot on like their ship station to Amazon and shopify sort of integration in terms of how did they automatically tag different shipments and report on those tags? So we help them with. With a bunch of that we did some custom python work for them.
94 00:10:49.980 ⇒ 00:11:13.249 Uttam Kumaran: And so those are like a lot of the wins. So we really touched executive reporting that went to help on everything related to shipping and fulfillment with chuck. Chuck is like their head of like warehousing, and then we then also started helping a lot of stuff with Kim. I think they are not. I don’t believe they’re using any dashboards like we. We built them, but I don’t think they’re using them.
95 00:11:13.667 ⇒ 00:11:18.109 Uttam Kumaran: I think this is probably a client where we probably will need to run
96 00:11:18.430 ⇒ 00:11:25.230 Uttam Kumaran: like monthly or like Qbrs. If we’re really gonna want them to affect some change.
97 00:11:25.230 ⇒ 00:11:25.750 Payas Parab: Yeah.
98 00:11:25.750 ⇒ 00:11:32.300 Uttam Kumaran: Reason we haven’t done it is time. You know, the data. Mart is pretty good.
99 00:11:33.180 ⇒ 00:11:36.319 Uttam Kumaran: like, it’s stuff that we’ve been working on for over a year. So.
100 00:11:36.550 ⇒ 00:11:37.020 Payas Parab: Yeah.
101 00:11:37.020 ⇒ 00:11:38.370 Uttam Kumaran: You have a lot of stuff in there.
102 00:11:38.885 ⇒ 00:11:44.250 Uttam Kumaran: So they give you the dynamic on Ben. Yeah, Ben is more like skeptical about everything.
103 00:11:44.380 ⇒ 00:11:45.210 Payas Parab: Hello!
104 00:11:45.700 ⇒ 00:11:50.810 Uttam Kumaran: Definitely not like a hop on a meeting. I mean, none of them are really like hop on a meeting type people.
105 00:11:51.590 ⇒ 00:11:55.690 Uttam Kumaran: If he if Ben will, Ben will text him like, Call me like he’s like, I don’t even wanna like
106 00:11:56.110 ⇒ 00:12:03.959 Uttam Kumaran: slack or email about it. So someone who really wants to like, be communicated like what is actually the point, and like, what? What do you need from me?
107 00:12:04.760 ⇒ 00:12:09.240 Uttam Kumaran: However, we we did a lot of big wins with him, and so he loved it. Ben is
108 00:12:10.570 ⇒ 00:12:15.959 Uttam Kumaran: I don’t know if Dan’s Republican Ben is probably more republican, but Ben is sort of like a quick crypto, Guy.
109 00:12:16.110 ⇒ 00:12:19.870 Uttam Kumaran: So if you talk to him and you bring up Crypto like we’ll get some brownie points.
110 00:12:20.572 ⇒ 00:12:22.189 Payas Parab: Ben is a big sorry. Dan’s a guy.
111 00:12:22.190 ⇒ 00:12:25.759 Uttam Kumaran: Ben is a big crypto guy ben like day trades all these like meme coins.
112 00:12:26.840 ⇒ 00:12:29.040 Uttam Kumaran: So if you talk to him and bring that up
113 00:12:30.170 ⇒ 00:12:32.570 Payas Parab: Yeah, I have a script I could give him if he wants.
114 00:12:32.770 ⇒ 00:12:34.499 Uttam Kumaran: Yeah. Yeah. You should talk to him about.
115 00:12:34.500 ⇒ 00:12:38.820 Payas Parab: Volume volume, Weighted Etf. Of all the shit coins I made. I could.
116 00:12:38.820 ⇒ 00:12:42.580 Uttam Kumaran: Yeah, dude you will. Yeah, no, if you next time you talk to him.
117 00:12:42.690 ⇒ 00:12:49.669 Uttam Kumaran: if I’m if I’m there, I’ll sort of like tee it up. But you should talk to him about it, because, yeah, he’s trading like he’s trading like all these
118 00:12:49.800 ⇒ 00:12:53.749 Uttam Kumaran: shit coins and meme coin projects. But he’s making money. But like.
119 00:12:53.750 ⇒ 00:12:55.519 Payas Parab: How old is? How old is Ben?
120 00:12:56.431 ⇒ 00:12:58.000 Uttam Kumaran: They’re probably both in their forties.
121 00:12:58.000 ⇒ 00:12:58.849 Payas Parab: In their forties. Okay.
122 00:12:58.850 ⇒ 00:13:00.766 Uttam Kumaran: Yeah, they both have kids.
123 00:13:01.920 ⇒ 00:13:08.090 Payas Parab: Got it. Okay? So Ben is a little bit more skeptical. Dan’s kind of more of like our internal champion that we should think about like.
124 00:13:08.090 ⇒ 00:13:17.859 Uttam Kumaran: But then has more time availability than Dan. So that’s the sort of difficult part we comment. But again, I’ve been working with them since July of 2023.
125 00:13:19.320 ⇒ 00:13:23.479 Uttam Kumaran: Me really really well won them over because
126 00:13:23.630 ⇒ 00:13:46.410 Uttam Kumaran: of just like how we do things. But like they don’t care at all about Snowflake don’t care all about dbt care. They barely care about real questions that are like, we’re going to a meeting. We need like blah blah, and they know me, because they know I’ve worked in that sort of scenario, and I can pull anything together. The other thing is, they need this sort of stuff where we’re coming to them with
127 00:13:47.180 ⇒ 00:13:50.979 Uttam Kumaran: thesis hypothesis, like with the scientific method on like.
128 00:13:51.180 ⇒ 00:13:51.940 Payas Parab: Yeah, yeah.
129 00:13:52.720 ⇒ 00:14:00.190 Uttam Kumaran: Which is fun, because we have an entire business with all really rich data. Very seasonal business, very. Geo. Business.
130 00:14:00.410 ⇒ 00:14:10.449 Uttam Kumaran: very low. Competition business. Not very complicated, a little bit complicated on the shipment side, but apart from that, like pretty, straightforward Ecom.
131 00:14:11.040 ⇒ 00:14:11.980 Payas Parab: Got it. Okay.
132 00:14:11.980 ⇒ 00:14:12.849 Uttam Kumaran: Awesome, no.
133 00:14:13.439 ⇒ 00:14:38.590 Payas Parab: I think, got a good sense of stakeholders. Bo. Also feel free to jump in at any time like you’re you’re gonna be like, just as involved in all of this as I am so feel free like getting context here. Feel free to jump in at any point. I’m just gonna keep going through like kind of like categories. So we talked about marketing. I think maybe we’ll jump to kind of the next. The the other main categories of business, right? So we talked. You mentioned a bunch about shipping right? Like shipping is sort of
134 00:14:38.590 ⇒ 00:14:47.989 Payas Parab: where we got a big win. There’s chuck we have like, we kind of work with a lot that like, what are, what are some of the problems? What are some of the things you’ve done there. So I saw on ups
135 00:14:48.976 ⇒ 00:14:57.630 Payas Parab: ship station, and like the Amazon integration, is there anything else that like sort of sticks out in like the world of shipping any like open questions that you know are top of mind for them. That type of thing.
136 00:14:57.890 ⇒ 00:15:03.779 Uttam Kumaran: Yeah. So it’s like a huge area. In fact, the shipping sort of folder in March.
137 00:15:03.780 ⇒ 00:15:04.200 Payas Parab: Hmm.
138 00:15:04.200 ⇒ 00:15:06.670 Uttam Kumaran: Especially the shipments file is probably like
139 00:15:07.180 ⇒ 00:15:23.380 Uttam Kumaran: you’ll. It’s like pretty complicated couple of things. One they sh. And this is something that we can. We can definitely scale to other clients, too. So I’m like very interested in like nailing this. They use ship station ship station is what’s used to create all their labels.
140 00:15:24.260 ⇒ 00:15:30.159 Uttam Kumaran: They also ship stuff on freight. Some of these pumps are hundreds and hundreds of pounds. So they use
141 00:15:30.590 ⇒ 00:15:40.990 Uttam Kumaran: this thing called Ltl freight. They switched over to New Provider. One common theme across. It is shipment data from the vendors really sucks. So we need to do a lot of cleanup.
142 00:15:41.525 ⇒ 00:15:53.250 Uttam Kumaran: In order to make sure that we can map shipments to customers, map shipments to the right. Geos. Things like that. Second is a shipment. One order can have multiple shipments. So
143 00:15:53.650 ⇒ 00:15:58.930 Uttam Kumaran: we went through a whole exercise of like, Oh, shit like we can’t. Just look at.
144 00:15:59.130 ⇒ 00:16:09.299 Uttam Kumaran: We can’t do that straight join. So we need to create a separate shipment. So we have order lines, orders, and shipments. Shipments have length, white length with height. They have weight.
145 00:16:10.060 ⇒ 00:16:12.693 Uttam Kumaran: and that is sort of what dictates
146 00:16:13.220 ⇒ 00:16:36.990 Uttam Kumaran: the price to ship. So we do 2 things, one we don’t. There’s. There’s a lag on when we’re billed for the shipment. So we we do an estimated shipping cost, because at any moment they want to know, in order to calculate gross profit, how much it costs to ship that item which means I needed to go into. I need to get from our shipment providers literally like the rate card like, how do you guys calculate.
147 00:16:36.990 ⇒ 00:16:37.450 Payas Parab: Oh!
148 00:16:37.450 ⇒ 00:16:39.289 Uttam Kumaran: What it costs to ship this
149 00:16:39.977 ⇒ 00:16:44.892 Uttam Kumaran: and we actually like built that out. So there’s a couple of factors. One is
150 00:16:45.460 ⇒ 00:16:53.700 Uttam Kumaran: what zone. It is so there’s a concept in shipping called like shipping zones, which means it’s like circular.
151 00:16:54.610 ⇒ 00:17:02.619 Uttam Kumaran: like things from a from a given point. So there’s 1 zone that’s within like 10 miles 50 miles 100 miles. Right? So those aren’t like
152 00:17:03.060 ⇒ 00:17:09.819 Uttam Kumaran: States. Those are like distance from where where the facility is to where it’s getting shipped to. So you have.
153 00:17:09.980 ⇒ 00:17:14.810 Uttam Kumaran: You have, like you have a couple of things, you have carriers you have, and you have zones, and you have the weights
154 00:17:15.020 ⇒ 00:17:28.130 Uttam Kumaran: so depending on the carrier depending on how far it’s getting shipped and how much it weighs. Those are the factors. There’s also factors on like volume discounts and other stuff. But those are like the the main things I will make sure that you have.
155 00:17:28.470 ⇒ 00:17:34.589 Uttam Kumaran: I’ll I’ll just send this literally right now the Google sheet that we use to sort of manage some of this.
156 00:17:34.840 ⇒ 00:17:39.020 Uttam Kumaran: Oh.
157 00:17:52.300 ⇒ 00:17:58.239 Uttam Kumaran: okay, I’ll find this and get it to you, because it’s been a little bit. But basically, yeah, there’s a bunch of factors for
158 00:17:58.789 ⇒ 00:18:12.639 Uttam Kumaran: shipments. So we have to calculate for every order how much it’s gonna cost a ship. There’s probably still Alpha there, and like getting that right, there’s probably still some alpha and going back and just renegotiating with Ups and Fedex like.
159 00:18:12.640 ⇒ 00:18:13.380 Payas Parab: Yep.
160 00:18:13.380 ⇒ 00:18:25.069 Uttam Kumaran: Every fucking 6 months. The negotiation was not that hard, and they gave us like 90% off and we’re and we were probably the only they literally said, we’re the only client that’s ever had like this much data.
161 00:18:25.596 ⇒ 00:18:34.020 Uttam Kumaran: Because it’s like a complete pain to like. Do what we did, which is rate card is like dude ray card was like a spreadsheet.
162 00:18:34.220 ⇒ 00:18:36.610 Payas Parab: Was like a was like a Pdf of a table
163 00:18:36.800 ⇒ 00:18:40.129 Payas Parab: spreadsheet. So we we mapped all of that.
164 00:18:41.003 ⇒ 00:18:53.049 Uttam Kumaran: And the other thing is we have. We also did the way we did. The proposal is when I looked at all of our pass rates. I got 2 proposals from Ups and Fedex, and then I put those in so we can see
165 00:18:53.180 ⇒ 00:18:57.900 Uttam Kumaran: proposed rates and actual rates, and then scale those to project it.
166 00:18:58.326 ⇒ 00:19:12.709 Uttam Kumaran: So there’s a big thing through Fedex and Ups. They do freight shipping. There’s a big whole world there of like how much it costs to ship freight. That’s a huge cost center for them. Again, these are big products. The last thing is to ship some stuff like brushes through ups.
167 00:19:13.560 ⇒ 00:19:14.140 Payas Parab: Sure.
168 00:19:14.140 ⇒ 00:19:15.699 Uttam Kumaran: There’s through the mail. So
169 00:19:15.950 ⇒ 00:19:21.920 Uttam Kumaran: there’s a lot of things on shipping in terms of the the high level goals, reducing shipping costs.
170 00:19:21.920 ⇒ 00:19:22.290 Payas Parab: Yep.
171 00:19:22.520 ⇒ 00:19:24.790 Uttam Kumaran: So that’s the number one directive we had.
172 00:19:25.040 ⇒ 00:19:25.760 Payas Parab: We.
173 00:19:25.760 ⇒ 00:19:30.226 Uttam Kumaran: We accomplish that in a big way. There’s probably still places to go.
174 00:19:30.730 ⇒ 00:19:36.330 Uttam Kumaran: Chuck is a key stakeholder there. Chuck manages all the warehouse chuck is like the nicest guy
175 00:19:36.570 ⇒ 00:19:40.970 Uttam Kumaran: works in their Long Island warehouse, basically are like.
176 00:19:41.350 ⇒ 00:19:45.539 Uttam Kumaran: knows everything about how they ship every every single thing, and how that whole machine works.
177 00:19:46.860 ⇒ 00:19:52.060 Payas Parab: Cool, excellent, so shipping good there, and then we talked about marketing. We talked about.
178 00:19:52.060 ⇒ 00:19:53.757 Uttam Kumaran: Oh, the last thing on shipping.
179 00:19:54.320 ⇒ 00:19:58.610 Uttam Kumaran: So they also decided to switch to using 3 pls.
180 00:19:59.090 ⇒ 00:19:59.490 Payas Parab: For sure.
181 00:19:59.490 ⇒ 00:20:07.030 Uttam Kumaran: All volume because they were like, we want to open a 3 pl. In Texas. We want to open a 3 Pl. Somewhere else. We help them?
182 00:20:07.250 ⇒ 00:20:13.829 Uttam Kumaran: We help tell them where they should open those 3 pls based on where the con previously they were shipping everything from Long Island.
183 00:20:13.990 ⇒ 00:20:14.670 Payas Parab: Got it.
184 00:20:14.670 ⇒ 00:20:24.430 Uttam Kumaran: So they were like, we can get closer to the customer. Of course they pay the 3 pl fees, but then they benefit from basically, the way the 3 pls work is they just pass on the cost plus
185 00:20:24.600 ⇒ 00:20:25.660 Uttam Kumaran: a kicker.
186 00:20:25.850 ⇒ 00:20:32.698 Uttam Kumaran: So it’s a 3 pls closer by, like, 50% of the kicker is 10%. Then you save 40. Right? So
187 00:20:33.370 ⇒ 00:20:41.279 Uttam Kumaran: I don’t think there’s, I think, one. They lost a lot of time because the 3 pl companies sucked, and 2. I still don’t think we’ve proven that that even worked.
188 00:20:41.880 ⇒ 00:20:46.569 Uttam Kumaran: I don’t. This company is not good at like being like. Let’s go prove that it worked.
189 00:20:48.330 ⇒ 00:20:52.450 Uttam Kumaran: It may cause more drama than anything, but
190 00:20:53.740 ⇒ 00:20:56.779 Uttam Kumaran: I don’t know. That’s just like another thing on shipping side.
191 00:20:57.540 ⇒ 00:20:58.680 Payas Parab: Got it. Okay.
192 00:20:58.900 ⇒ 00:21:12.310 Payas Parab: got it. So I think, like, my read so far is that like marketing is relatively untapped like. But shipping is something that’s been historically like. There’s been a lot of wins there, but it’s also like one of the most prominent parts of their business.
193 00:21:12.310 ⇒ 00:21:23.369 Uttam Kumaran: Yeah, so exactly so. The core metric to keep in your mind is gross profit. So revenue discounts, refunds, warranties, shipping
194 00:21:23.760 ⇒ 00:21:25.699 Uttam Kumaran: right, and the marketing costs.
195 00:21:25.990 ⇒ 00:21:26.660 Payas Parab: Yep.
196 00:21:27.530 ⇒ 00:21:30.180 Uttam Kumaran: The when I came to this company they didn’t.
197 00:21:30.300 ⇒ 00:21:31.560 Uttam Kumaran: I was like.
198 00:21:31.690 ⇒ 00:21:42.510 Uttam Kumaran: We are going to look, go one by one in this equation and find a way to affect that right on the revenue side. Okay, maybe we can maybe test price testing. We try a little bit of that.
199 00:21:42.830 ⇒ 00:21:44.099 Uttam Kumaran: They didn’t really like it.
200 00:21:44.260 ⇒ 00:21:50.890 Uttam Kumaran: They’re like a little bit nervous. We then went after shipment costs really kill that one. That was that crush.
201 00:21:50.890 ⇒ 00:21:51.440 Payas Parab: You know.
202 00:21:51.580 ⇒ 00:22:04.779 Uttam Kumaran: We haven’t done much on discounts where it’s like, what are you discounting? What is the lift? Things like that? We haven’t done anything there refunds and Zendesk, and sort of looking at like what people are refunding. We haven’t done anything there. The data is there.
203 00:22:04.780 ⇒ 00:22:05.440 Payas Parab: Got it.
204 00:22:05.720 ⇒ 00:22:07.939 Uttam Kumaran: We started and we stopped
205 00:22:08.140 ⇒ 00:22:13.759 Uttam Kumaran: again. Mostly my fault warranties. We have, we should. We definitely haven’t done anything there.
206 00:22:13.760 ⇒ 00:22:15.370 Payas Parab: Clarify what warranties are in this case.
207 00:22:15.370 ⇒ 00:22:18.990 Uttam Kumaran: So they offer. They offer manufacturer warranties on their products.
208 00:22:18.990 ⇒ 00:22:19.680 Payas Parab: Yep.
209 00:22:19.680 ⇒ 00:22:26.080 Uttam Kumaran: And when client can just literally be like this is broken, and they have to ship another one. But they have no data on, like.
210 00:22:26.270 ⇒ 00:22:33.619 Uttam Kumaran: for example. And and we probably have the meeting where I talked to Dan about their entire warranty program. Basically they
211 00:22:33.930 ⇒ 00:22:39.669 Uttam Kumaran: they want to know if a product is getting hit by warranties. They should go to the manufacturer and be like this product is fucked.
212 00:22:39.870 ⇒ 00:22:40.409 Payas Parab: Yeah, yeah.
213 00:22:40.410 ⇒ 00:22:42.290 Uttam Kumaran: No feedback loop for that.
214 00:22:42.290 ⇒ 00:22:42.890 Payas Parab: Yep.
215 00:22:42.890 ⇒ 00:22:45.440 Uttam Kumaran: They just issue the warranty and like, it’s sort of like the.
216 00:22:45.440 ⇒ 00:22:46.259 Payas Parab: Got it.
217 00:22:46.260 ⇒ 00:22:50.579 Uttam Kumaran: But it is a big portion of their of that calculation right.
218 00:22:50.580 ⇒ 00:23:00.680 Payas Parab: Got it. We’re like warranties track. Would that be something that like it’s like a Zen. It starts in Zendesk where the customer starts something. Then ultimately it gets resolved. And it’s like, Okay, cool warranty.
219 00:23:00.680 ⇒ 00:23:07.467 Uttam Kumaran: So this is also a really good piece. So right now, one of the things that we went and told them, and this is
220 00:23:08.360 ⇒ 00:23:18.610 Uttam Kumaran: I’ll have to find this information on how we did this. But the way they’re dictating what is a warranty is, they go back, create a new order and shopify and tag and tag tag it as a hundred percent discount.
221 00:23:19.300 ⇒ 00:23:19.800 Uttam Kumaran: Sorry.
222 00:23:19.800 ⇒ 00:23:20.370 Payas Parab: See.
223 00:23:20.370 ⇒ 00:23:39.409 Uttam Kumaran: So to follow up on the next problem is that discounts is really probably inflated with other bullshit, like refunds, returns, and and warranties, meaning for a while. I wasn’t filtering it out of discounts, but like those are not discounts. Those are warranty purchases where
224 00:23:39.620 ⇒ 00:23:47.759 Uttam Kumaran: they’re just $0. And so I was like, why, the fuck are we giving product away? And they were like, I was like, Oh, these are warranty reorders.
225 00:23:48.120 ⇒ 00:23:51.430 Uttam Kumaran: but they just throw that in. They just give them a hundred percent discount.
226 00:23:52.110 ⇒ 00:23:53.320 Payas Parab: I see. Okay.
227 00:23:53.650 ⇒ 00:24:01.270 Uttam Kumaran: Right? So then, so one, we have 2 options, one, we can continue there. 2. We can give them a better process that would involve working with.
228 00:24:01.660 ⇒ 00:24:03.330 Uttam Kumaran: That involves working with their
229 00:24:03.820 ⇒ 00:24:20.019 Uttam Kumaran: customer care team, which is just like 2 people, and then being like in order to process a re a warranty, we should do it X way, right? They still want to understand that product left. But having it come in, because then it comes in as a hundred percent discount sale so that it comes into the order. Count.
230 00:24:20.946 ⇒ 00:24:21.380 Payas Parab: Well, I.
231 00:24:21.380 ⇒ 00:24:26.720 Uttam Kumaran: There’s nothing in the revenue so like it’s bonds like.
232 00:24:27.150 ⇒ 00:24:32.529 Payas Parab: Yeah, basically, knows it out instead of like capturing like, this is what it could have been. But you lost this much right?
233 00:24:32.530 ⇒ 00:24:37.360 Uttam Kumaran: Yeah. But then your, if you do have within your average order values kind of messed up, your
234 00:24:37.590 ⇒ 00:24:46.289 Uttam Kumaran: your gross profit is messed up because we look at the we look at the revenue, and then we we subtract the discounts, so the gross would be 100, and then we we do minus 100.
235 00:24:47.610 ⇒ 00:24:52.080 Uttam Kumaran: So then it looks like you’re giving way. Too many discounts when, in fact, these are warranty claims.
236 00:24:52.080 ⇒ 00:25:00.309 Payas Parab: Like filter warranty claims 100 refund. Is that is that accurate always? Or is it like like? If we see that like discounts, equals revenue.
237 00:25:00.690 ⇒ 00:25:04.980 Payas Parab: Is that safe? To assume that that’s a warranty is that like a rule, we could use or no.
238 00:25:04.980 ⇒ 00:25:09.990 Uttam Kumaran: Yeah, but it’s probably best like right now they do a discount code.
239 00:25:11.150 ⇒ 00:25:15.710 Uttam Kumaran: That’s like warranty. And that’s how I kind of identify it.
240 00:25:16.050 ⇒ 00:25:21.309 Uttam Kumaran: I think it’s probably best to filter those out and and then go case by case and see like, what are these 100% discounts?
241 00:25:21.450 ⇒ 00:25:22.240 Uttam Kumaran: I see.
242 00:25:22.240 ⇒ 00:25:22.680 Payas Parab: Okay.
243 00:25:22.680 ⇒ 00:25:26.899 Uttam Kumaran: But that was like, Do you guys give 100% discounts or like, no. And I’m like, Well, don’t like what’s going on here.
244 00:25:27.240 ⇒ 00:25:32.659 Payas Parab: And and do you say for refunds they do the same thing? Or is refunds captured? The more traditional way that it’s done in shopify.
245 00:25:33.484 ⇒ 00:25:35.259 Uttam Kumaran: Let’s take a look
246 00:25:49.420 ⇒ 00:25:53.029 Uttam Kumaran: yeah, it’s it’s captured. The normal way through shopify, refund.
247 00:25:55.630 ⇒ 00:25:57.580 Payas Parab: Capture the normal way through. Shopify. Okay.
248 00:26:00.510 ⇒ 00:26:12.559 Payas Parab: okay, this is super helpful. Bo. I’ll let you go. Sorry. I’ve kind of like owned this Bo. Any any other things that like top of mind, anything that like, you know, on anything we’ve discussed. You want to double tap into.
249 00:26:13.310 ⇒ 00:26:21.639 Bo Yoon: So which one do you think we should focus on 1st like, besides, the Asia.
250 00:26:21.810 ⇒ 00:26:22.730 Payas Parab: Yeah Asia.
251 00:26:22.730 ⇒ 00:26:26.320 Bo Yoon: Connection thing that we’re doing, that we’ll be talking next week.
252 00:26:26.320 ⇒ 00:26:32.960 Uttam Kumaran: Yeah, I think the agent connection definitely keep going. So there’s 2 other areas. One is inventory.
253 00:26:33.110 ⇒ 00:26:38.340 Uttam Kumaran: We haven’t done anything on inventory and supply chain. What is inventory supply chain?
254 00:26:38.740 ⇒ 00:26:43.800 Uttam Kumaran: They have to place orders to the manufacturer months ahead of it, getting sold.
255 00:26:44.380 ⇒ 00:26:48.280 Uttam Kumaran: And they currently don’t have a good idea about
256 00:26:48.490 ⇒ 00:26:55.390 Uttam Kumaran: like how long that takes. How do we set up a great inventory purchasing plan through data.
257 00:26:55.510 ⇒ 00:26:57.819 Uttam Kumaran: and then actually like, what is the
258 00:26:58.120 ⇒ 00:27:01.390 Uttam Kumaran: what is the stock throughput from their facility.
259 00:27:01.840 ⇒ 00:27:03.950 Uttam Kumaran: I proposed a bunch of work on that.
260 00:27:04.570 ⇒ 00:27:07.889 Uttam Kumaran: and was like, there’s no juice there. Don’t worry about that.
261 00:27:08.270 ⇒ 00:27:08.800 Payas Parab: Yup!
262 00:27:08.800 ⇒ 00:27:09.380 Uttam Kumaran: You know.
263 00:27:09.500 ⇒ 00:27:11.274 Uttam Kumaran: So I was like, Okay, but
264 00:27:12.030 ⇒ 00:27:16.529 Uttam Kumaran: that’s sort of the the story there. There’s definitely probably something we can do to
265 00:27:17.213 ⇒ 00:27:23.669 Uttam Kumaran: improve the time it takes to get product in, get it stocked on the shelf, and use data for that whole process.
266 00:27:25.770 ⇒ 00:27:32.670 Uttam Kumaran: They’re also, they’re also using klaviyo they’re using attent. They’re using attentive for SMS.
267 00:27:33.190 ⇒ 00:27:35.830 Uttam Kumaran: So there’s definitely like a whole area of like marketing where.
268 00:27:36.170 ⇒ 00:27:36.670 Payas Parab: Yeah.
269 00:27:36.670 ⇒ 00:27:38.830 Uttam Kumaran: Probably just wrap and think about how to
270 00:27:39.650 ⇒ 00:27:47.459 Uttam Kumaran: the problem with marketing is, it’s not good enough just to show the data we would have to actually probably own like helping them run a campaign and testing it.
271 00:27:49.570 ⇒ 00:27:57.473 Uttam Kumaran: The last thing is, yeah, I’m customer service. We really haven’t done anything on customer service. So customer service marketing and
272 00:27:59.497 ⇒ 00:28:01.109 Uttam Kumaran: supply chain inventory.
273 00:28:01.940 ⇒ 00:28:05.470 Uttam Kumaran: The last thing is warranties and discounts.
274 00:28:05.590 ⇒ 00:28:18.499 Uttam Kumaran: They have a they are. They’re very disorganized on how they give out discounts the discount code, naming conventions, how those coming through the system? So that’s all sort of around customer care.
275 00:28:19.590 ⇒ 00:28:20.360 Uttam Kumaran: Right.
276 00:28:20.360 ⇒ 00:28:37.470 Payas Parab: So warranties and discounts. Seems like it would have a higher impact on the like. If you’re thinking about that gross profit equation right? Like, I think it would have a higher impact. So I’m curious. Why, like, if you were just list, if they were ordered, I’m curious like, why, marketing is like about they weren’t ordered.
277 00:28:37.470 ⇒ 00:28:44.880 Uttam Kumaran: These are in order, but they do spend a shit ton of marketing. And they did spend a shit ton on shipping. The next area is gonna be returns, refunds, and discounts.
278 00:28:45.770 ⇒ 00:28:51.429 Payas Parab: Got it. Customer service, because, like, my head is like, what? What are the unexplored areas right? And then like
279 00:28:52.250 ⇒ 00:29:02.049 Payas Parab: doesn’t have enough impact on their business right? So customer service, I think, is unexplored. But I don’t think it has probably as much impact as like warranties and discounts does right overall.
280 00:29:02.240 ⇒ 00:29:04.245 Uttam Kumaran: That’s correct. Yeah, I mean, I
281 00:29:06.290 ⇒ 00:29:08.256 Uttam Kumaran: I’m not 100% sure.
282 00:29:09.020 ⇒ 00:29:09.660 Payas Parab: Yeah.
283 00:29:10.220 ⇒ 00:29:23.549 Uttam Kumaran: It’s just the tail end of the purchasing process. So it’s sort of been like, just go figure it out, but they don’t. They like that affects the money you make, because they’re really a revenue in cost out like on a day to day, week to week.
284 00:29:24.030 ⇒ 00:29:24.460 Payas Parab: Yeah.
285 00:29:24.460 ⇒ 00:29:27.710 Uttam Kumaran: They’re not looking like overall at like
286 00:29:29.090 ⇒ 00:29:42.319 Uttam Kumaran: overall equation. We got them to trust that we’re bringing in the right data every single piece, though, but it was. It took us a year to just get through the 1st getting all the sales done, and then getting the shipping done.
287 00:29:43.610 ⇒ 00:29:44.220 Uttam Kumaran: Right.
288 00:29:44.220 ⇒ 00:29:49.560 Payas Parab: Yeah, yep, awesome. Alright. I think
289 00:29:50.040 ⇒ 00:30:01.870 Payas Parab: this, I think, Bo, what we can do like. Now, Tom, thank you for this brain dump. I’m gonna just get all these notes from my dot txt file into chat, gpt, and then notion and then we will
290 00:30:02.223 ⇒ 00:30:16.400 Payas Parab: organize these. I think Bo, you, me and Nico. We’ll just have a strategy session. And then what I want to do is like, just get some organization around like, here’s the top 3 buckets, and like, maybe we’ll do like each of us. Take a stab at some preliminary analysis. So then we can like
291 00:30:16.480 ⇒ 00:30:32.820 Payas Parab: meaningfully, like pitch right like we can be like, Hey, like cool. We started looking at this and like, here’s all the data. And Zendesk. And here’s what we could do there, that type of thing, and like sort of think as if we’re like pitching it again. Like, maybe next week, when we also connect on the Asia connection? Does that sound good.
292 00:30:34.010 ⇒ 00:30:35.250 Bo Yoon: Yeah, yeah, sure.
293 00:30:35.710 ⇒ 00:30:43.405 Uttam Kumaran: Yeah, I’m gonna ping. I’m gonna ping Nico and Luke to sort of send any past. We. So we’ve done a bunch of like point analysis for them.
294 00:30:44.170 ⇒ 00:30:48.212 Uttam Kumaran: And I’ll just try to get all that brain dumped here.
295 00:30:48.790 ⇒ 00:30:51.189 Uttam Kumaran: The data model is like, not that bad.
296 00:30:52.383 ⇒ 00:30:52.890 Payas Parab: It? Yeah.
297 00:30:52.890 ⇒ 00:30:54.829 Uttam Kumaran: Shipping is the hardest part.
298 00:30:55.200 ⇒ 00:31:04.239 Uttam Kumaran: but outside of that which I feel like that’s like on a good track. Right now. The marketing standard marketing stuff. Send this up standards and this stuff, shopify shop standard shopify stuff.
299 00:31:04.450 ⇒ 00:31:05.920 Uttam Kumaran: Got it? Yeah.
300 00:31:06.720 ⇒ 00:31:07.880 Payas Parab: Awesome. Okay?
301 00:31:08.000 ⇒ 00:31:09.440 Payas Parab: Alright, thank you, Tom.
302 00:31:09.440 ⇒ 00:31:18.880 Uttam Kumaran: And then the last thing I’ll say is, they do have a lot of bandwidth to think about like doing fun, analysis, fun, meaning like things that are a little bit outside the box.
303 00:31:18.880 ⇒ 00:31:19.460 Payas Parab: Yep.
304 00:31:19.460 ⇒ 00:31:24.609 Uttam Kumaran: That may engage their attention, while we also try to help them on shit. That’s like very basic.
305 00:31:24.610 ⇒ 00:31:25.260 Payas Parab: Yeah, yeah.
306 00:31:25.260 ⇒ 00:31:32.420 Uttam Kumaran: Cool, and it helps us actually work on shit. That’s like interesting. There may be something you could do that where it’s like
307 00:31:32.670 ⇒ 00:31:40.250 Uttam Kumaran: cause they? They also they don’t they? We could do stuff on the competitive analysis side. We could do stuff on the cost of goods, sold the manufacturing side like.
308 00:31:41.010 ⇒ 00:31:47.770 Uttam Kumaran: It’s sort of all open to us. And now that we have access to quickbooks, we sort of have everything like we have all their stuff, you know, so.
309 00:31:47.770 ⇒ 00:31:54.779 Payas Parab: Yeah, yeah, the quickbooks element. So that like. And we, we finally got like our heads around like
310 00:31:54.890 ⇒ 00:32:06.260 Payas Parab: Asia connection, we’re like, sort of thinking about Asia connection almost as like a second client as like in addition to pool parts to go right like there’s sort of this like pool parts like Ecom wholesale business that they’ve built out.
311 00:32:06.690 ⇒ 00:32:08.980 Payas Parab: Connection, which is just like our read is that.
312 00:32:09.254 ⇒ 00:32:14.459 Uttam Kumaran: Think the Asia connection those is that just like accounting company like that’s just this guy’s accounting agency right?
313 00:32:14.460 ⇒ 00:32:21.149 Payas Parab: No, no, Asia connection is like the like. It looks like they’re like the logistics providers from China
314 00:32:21.740 ⇒ 00:32:23.570 Payas Parab: bring in cool parts.
315 00:32:23.760 ⇒ 00:32:24.520 Uttam Kumaran: Oh, okay.
316 00:32:24.520 ⇒ 00:32:30.839 Payas Parab: Like they’re the middle man. They’re like the importer. Essentially. I guess that would be the best description of them. They’re like an importer, and it seems that they like
317 00:32:30.970 ⇒ 00:32:36.080 Payas Parab: do importing for more than just pool parts. That’s like what we’re or like. Island rec, like right beau.
318 00:32:36.615 ⇒ 00:32:37.150 Uttam Kumaran: Okay.
319 00:32:37.150 ⇒ 00:32:38.160 Payas Parab: So there’s like like when.
320 00:32:38.160 ⇒ 00:32:38.920 Bo Yoon: They have a lot of.
321 00:32:38.920 ⇒ 00:32:41.810 Payas Parab: It has, like customers other than pool parts, and I.
322 00:32:41.810 ⇒ 00:32:42.800 Uttam Kumaran: Oh!
323 00:32:42.800 ⇒ 00:32:50.299 Payas Parab: Why the fuck are these in here, right? Like our. And then he’s like, Yeah, the company is owned by Dan’s father-in-law.
324 00:32:50.510 ⇒ 00:33:08.149 Payas Parab: and it sounds like he just wants him to get. He’s like he’s like my father-in-law has been like raw dogging, like what the prices should be and like how much the costs are, and he like doesn’t know how much it costs to actually like land these things here. He’s just sort of like using gut checks. So it’s almost like
325 00:33:08.310 ⇒ 00:33:12.050 Payas Parab: it’s almost like a second client is that makes sense.
326 00:33:12.050 ⇒ 00:33:12.640 Uttam Kumaran: Okay.
327 00:33:13.150 ⇒ 00:33:19.659 Payas Parab: Like he he like. He wants us to analyze Asia connection, and it’s like sort of like Dan wants us to consult so he can like.
328 00:33:19.860 ⇒ 00:33:20.520 Uttam Kumaran: Yeah.
329 00:33:20.520 ⇒ 00:33:22.230 Payas Parab: To his father-in-law like.
330 00:33:22.639 ⇒ 00:33:23.049 Uttam Kumaran: Okay.
331 00:33:23.303 ⇒ 00:33:26.090 Payas Parab: Maybe some succession shit going on down there that we’re like.
332 00:33:26.510 ⇒ 00:33:29.930 Uttam Kumaran: There’s a lot of drama between Dan and his father in law like that.
333 00:33:29.930 ⇒ 00:33:30.880 Payas Parab: Really, okay.
334 00:33:30.880 ⇒ 00:33:31.490 Uttam Kumaran: Yeah.
335 00:33:32.590 ⇒ 00:33:33.130 Uttam Kumaran: Oh.
336 00:33:33.670 ⇒ 00:33:35.930 Payas Parab: Is that that? Yeah, maybe we’re like.
337 00:33:35.930 ⇒ 00:33:44.930 Uttam Kumaran: I just, it’s interesting. These are interesting guys like, I don’t know they’re making a lot of money in this business, though, like a shit ton of money.
338 00:33:46.990 ⇒ 00:33:50.010 Payas Parab: Cool. All right, man. Any last thoughts. Bo uta.
339 00:33:51.290 ⇒ 00:33:52.050 Bo Yoon: I’m good.
340 00:33:52.480 ⇒ 00:33:59.630 Payas Parab: Awesome. Alright. But we’ll have a sync, and we can do a team strategy session unique of like. Let’s let’s figure out how to run from this, maybe later this week.
341 00:33:59.630 ⇒ 00:34:00.030 Payas Parab: Yeah.
342 00:34:00.150 ⇒ 00:34:13.020 Payas Parab: you can just be ready to get all that in front of Dan on the phone. And then, yeah on the email comes like Bo, too, like utam kind of laid, I know. If you saw the reply that Utam had, I like I didn’t understand what was wrong. Like, I was like, Okay, but like, yeah, these guys are like.
343 00:34:13.020 ⇒ 00:34:18.080 Uttam Kumaran: But see, Nico does. That’s why like Nico knows. That’s why that’s why I was like dude.
344 00:34:18.550 ⇒ 00:34:30.269 Uttam Kumaran: these guys are gonna they? They’re just like they’re gonna get. They’re just gonna get overwhelmed. If we have 10 people on email, if the email is bigger than something they can read on their phone. They’re gonna be like, I’m not reading that.
345 00:34:30.270 ⇒ 00:34:30.880 Payas Parab: Yeah, yeah.
346 00:34:30.889 ⇒ 00:34:40.119 Uttam Kumaran: Just think, think like, if you were just like running a company. You’re gonna be like, like, I sit on my laptop all day, but like, these guys are running a pool parts business, they’re like moving around. So.
347 00:34:40.120 ⇒ 00:34:40.730 Payas Parab: Yeah, yeah.
348 00:34:40.730 ⇒ 00:34:47.930 Payas Parab: everything. We should try to get them on the phone and everything. Just keep it like super crisp couple lines.
349 00:34:48.070 ⇒ 00:34:49.419 Uttam Kumaran: Because I like.
350 00:34:49.429 ⇒ 00:34:51.619 Payas Parab: Those detailed questions, right? Cause? It’s like without.
351 00:34:51.620 ⇒ 00:34:58.100 Uttam Kumaran: No, no, those are good questions. But like I meaning be like, we have questions. Can we hop on.
352 00:34:58.610 ⇒ 00:35:03.430 Payas Parab: Yeah, like, let let’s just take that up. We’ll have like, sort of like, internal facing external facing way. I didn’t.
353 00:35:03.580 ⇒ 00:35:04.820 Payas Parab: I don’t know. Like I’m always.
354 00:35:04.820 ⇒ 00:35:05.700 Uttam Kumaran: I mean Governor, I mean.
355 00:35:05.700 ⇒ 00:35:10.490 Payas Parab: I wanna know what you want to talk to me about like in detail, so I can like prep review.
356 00:35:10.490 ⇒ 00:35:11.190 Uttam Kumaran: Yeah, like.
357 00:35:11.370 ⇒ 00:35:11.890 Payas Parab: Yeah.
358 00:35:11.890 ⇒ 00:35:13.339 Uttam Kumaran: This, those aren’t these guys.
359 00:35:13.630 ⇒ 00:35:15.330 Payas Parab: It’s a turkey status.
360 00:35:15.330 ⇒ 00:35:21.770 Uttam Kumaran: These aren’t these guys. And Nico knows. So that’s why I was like dude. We can’t be sending like we weren’t working. I’ve been working with them since
361 00:35:22.040 ⇒ 00:35:37.500 Uttam Kumaran: 2 Julys ago. Right? I know how to communicate. I made this mistake in that July where they’re like yo, we’re not reading this, and also we’ve had this client. Multiple analysts come and work on this client. We’ve made this mistake every time. So that’s why I was like
362 00:35:37.610 ⇒ 00:35:44.370 Uttam Kumaran: I was like I was like, Nico, why, the fuck are you doing this like? But like.
363 00:35:44.950 ⇒ 00:36:00.310 Uttam Kumaran: it’s okay. So it’s it’s all. It’s all learning process. You’ll get that. They’re actually wanna help us. Their communication style is unique, but it’s also great because we don’t have to talk about the nitty gritty that’s for us to figure out they care about the outcome.
364 00:36:00.650 ⇒ 00:36:07.220 Uttam Kumaran: It’s pretty in a lot of ways, but also we can’t like some. We can’t pat stat pad with, like
365 00:36:08.260 ⇒ 00:36:11.539 Uttam Kumaran: the the infra work. They don’t care about that.
366 00:36:11.820 ⇒ 00:36:12.490 Payas Parab: Yep.
367 00:36:12.900 ⇒ 00:36:14.120 Uttam Kumaran: So, okay.
368 00:36:16.450 ⇒ 00:36:18.029 Payas Parab: Got it. Okay. Awesome.
369 00:36:18.690 ⇒ 00:36:25.989 Bo Yoon: Alright. Then then should it be just only one person who’s who’s sending the emails for workers to go.
370 00:36:27.710 ⇒ 00:36:29.199 Uttam Kumaran: I’ll let you guys decide. I mean.
371 00:36:29.200 ⇒ 00:36:57.739 Payas Parab: I I think I think, like even Uton, like one of the things I want to like sort of organize, even like it sounds like silly, but like these big consulting firms do it right is like just like a page where it’s like, here is the engagement team who we are like, why, who is this bow guy like, you know what I mean, like a little like, here’s what we’re doing like we have this new process for, like each analysis sprint and like, who the fuck are these guys? And like, why are they involved? I think, like, even like, I just remember, like, there’s like the team slide right? And I know we don’t like Powerpoints for these guys. So that’s not their vibe.
372 00:36:57.740 ⇒ 00:37:02.140 Uttam Kumaran: I know we can, but, like I I’m down to do that. They just won’t care.
373 00:37:02.140 ⇒ 00:37:03.419 Payas Parab: They just won’t care. Yeah.
374 00:37:03.640 ⇒ 00:37:10.120 Uttam Kumaran: Like, and it’s it’s it pains me to say that because I’ve tried this dude, I’m working like
375 00:37:10.260 ⇒ 00:37:16.190 Uttam Kumaran: they don’t give a shit. They know I’m on there, and they know whatever I say is the way to go. They’re gonna be like cool.
376 00:37:16.190 ⇒ 00:37:16.660 Payas Parab: Yeah.
377 00:37:16.800 ⇒ 00:37:34.260 Uttam Kumaran: I kind of keep them updated on like, hey? Cause they were. The problem is, this is a client that’s churned out more analysts than any client we’ve had, because people do not understand what it takes to work with a company that fundamentally does not give a shit about how we get there. They care about getting there.
378 00:37:34.400 ⇒ 00:37:34.980 Payas Parab: Yeah.
379 00:37:34.980 ⇒ 00:37:42.100 Uttam Kumaran: So anything we do with them focus on what the outcome is. They don’t care about anything, which is.
380 00:37:42.310 ⇒ 00:37:48.350 Uttam Kumaran: It’s a lot. It’s a lot different than what. Not only when you’re working, you try to show your work, and, like
381 00:37:48.570 ⇒ 00:37:50.289 Uttam Kumaran: other clients, need that.
382 00:37:50.410 ⇒ 00:37:54.990 Uttam Kumaran: These guys are like, not that right? They don’t. They just want
383 00:37:55.190 ⇒ 00:37:57.692 Uttam Kumaran: to save money or make more money.
384 00:37:58.590 ⇒ 00:38:02.139 Uttam Kumaran: So I but I think for internal communication.
385 00:38:02.290 ⇒ 00:38:07.770 Uttam Kumaran: We we’re still kind of sucking right? So it’s either, I think I wanna.
386 00:38:08.050 ⇒ 00:38:15.189 Uttam Kumaran: I want to make a decision whether it’s either you pies or you or Nico to sort of just handle those emails.
387 00:38:15.430 ⇒ 00:38:18.189 Uttam Kumaran: They will respond to any email. However.
388 00:38:18.820 ⇒ 00:38:23.030 Uttam Kumaran: you may get caught in a jam, if like they say something, and it’s something else. So
389 00:38:23.160 ⇒ 00:38:27.400 Uttam Kumaran: I would say, either it should be pies, or nico, like.
390 00:38:28.510 ⇒ 00:38:30.290 Payas Parab: Yeah, I don’t know. I’ve I don’t.
391 00:38:30.290 ⇒ 00:38:33.689 Payas Parab: Yeah, I think we’ll get some organization around this. And like, now we have these.
392 00:38:33.690 ⇒ 00:38:41.867 Uttam Kumaran: Introduce yourself when you go talk to them on the call. But like otherwise, they’re just not. They’re not gonna like they’re not gonna go to notion.
393 00:38:42.160 ⇒ 00:38:49.660 Payas Parab: Oh, yeah, I wasn’t planning any notion, like, I mean, the thing is like, I’m a boomer at heart. So I kind of like, understand what these guys like. I’m just like
394 00:38:50.500 ⇒ 00:38:53.099 Payas Parab: I’m trying to put in my boomer shoes right is like, if I see like.
395 00:38:53.100 ⇒ 00:38:57.219 Uttam Kumaran: You will win trust by delivering and by being like a cool.
396 00:38:57.330 ⇒ 00:38:59.620 Uttam Kumaran: like understanding person on the call.
397 00:38:59.620 ⇒ 00:39:00.340 Payas Parab: Yeah.
398 00:39:00.760 ⇒ 00:39:06.849 Uttam Kumaran: That’ll that’ll get you there, and they know me. So they know if it’s associated with me. You already get like a big head start.
399 00:39:06.850 ⇒ 00:39:08.140 Payas Parab: Sure. Okay.
400 00:39:08.720 ⇒ 00:39:09.580 Payas Parab: Cool. Alright.
401 00:39:09.580 ⇒ 00:39:11.170 Uttam Kumaran: If it gets if it gets tense.
402 00:39:11.620 ⇒ 00:39:13.590 Uttam Kumaran: just blew me in. But like
403 00:39:13.920 ⇒ 00:39:19.149 Uttam Kumaran: otherwise, I don’t want us to like I really, this is why I don’t like. We keep doing this with pool parts
404 00:39:19.470 ⇒ 00:39:26.909 Uttam Kumaran: and like I don’t know what needs to change here, because we’ve done this over and over again is we go back to treating them like a normal client.
405 00:39:27.100 ⇒ 00:39:44.689 Uttam Kumaran: like on some level on the data side. Sure, most data companies, the same problem. But the way we communicate has to be unique, right? And I don’t know. And Nico should have known this, that, like we’re sending them a page is not going to go anywhere with them. In fact, we’re just gonna ghost it
406 00:39:44.920 ⇒ 00:39:46.840 Uttam Kumaran: right like
407 00:39:47.020 ⇒ 00:39:55.089 Uttam Kumaran: other people may say they’re a bad client. I’m like, we’ve we need to be better, right? And so I think that keep it short.
408 00:39:55.420 ⇒ 00:39:59.999 Uttam Kumaran: Translate exactly what we need for them. Win Brownie points on the call.
409 00:40:00.000 ⇒ 00:40:04.819 Payas Parab: Now, what can I can I ask like a question there? Right? So, like some of these things, there is like an element
410 00:40:05.050 ⇒ 00:40:13.229 Payas Parab: of like iterative things that need to happen right where it’s like, we’re sort of doing this proactive like, I. I do imagine that historically, we’ve hit a wall where it’s like.
411 00:40:13.670 ⇒ 00:40:26.109 Payas Parab: well, one is like we need to validate that. The thing we want to go explore and do a bunch of data shit like we don’t need to tell them how the sausage is made. But like we need to know, we’re making the right sausage right like that. That aspect does need some level of buy in what would be.
412 00:40:26.110 ⇒ 00:40:26.780 Uttam Kumaran: Yes.
413 00:40:26.780 ⇒ 00:40:51.719 Payas Parab: The way to win that right like, is it like? Would they respond? What would they respond to? Where it’s like? Hey, cool! I’m understanding what you’re saying and what you’re planning to do and like I can confirm. This is an important thing to me before we go. Do like 3 h of work and build them for a bunch of like before I send like on a wild goose chase of like me and Beau going through Zendesk trying to come up with like a bunch of like insights right like we we.
414 00:40:51.720 ⇒ 00:41:01.499 Uttam Kumaran: These ideas you should think about like what an elevator pitch for each of these ideas are for the next projects. You should run them by Ben and Slack, which we can do.
415 00:41:02.074 ⇒ 00:41:06.739 Uttam Kumaran: Dan is gonna be the most supportive, but it’s gonna be hardest to get on the phone.
416 00:41:07.110 ⇒ 00:41:25.810 Uttam Kumaran: Otherwise dude we used to have day. I used to meet with this guy every day, like they used to be a huge client. They used to be our only like our major clients. So I was meeting with Chuck Kim Ben every single day for a long time. We’ve like lost the steam here, which is like. That’s sort of what we’re trying to pick back up. The ultimate thing is to find out who in the organization it affects
417 00:41:26.110 ⇒ 00:41:37.630 Uttam Kumaran: right for marketing stuff. It affects Kim’s day to day. Ultimately Ben may say something, but, like Kim, runs the marketing budget right? This Asia stuff is hard because it’s Dan and Dan is like
418 00:41:37.830 ⇒ 00:41:40.339 Uttam Kumaran: the there’s no, there’s no one else
419 00:41:40.480 ⇒ 00:41:43.860 Uttam Kumaran: doing any of that stuff like he’s the only one yeah.
420 00:41:44.260 ⇒ 00:41:52.099 Uttam Kumaran: Anything on shipping is chuck anything else. Sort of like operations. Wise has been. Those are the. And then there’s 1 person on Zendesk, basically.
421 00:41:52.420 ⇒ 00:41:53.140 Payas Parab: Yep.
422 00:41:53.140 ⇒ 00:41:53.990 Uttam Kumaran: So
423 00:41:55.520 ⇒ 00:42:06.970 Uttam Kumaran: I think I think, like work on the clear elevator pitch for the ideas and then email them or slack for feedback. And don’t worrying about. Don’t worry about keeping and keep emailing them, I think. Just make it like
424 00:42:07.230 ⇒ 00:42:08.330 Uttam Kumaran: concise
425 00:42:08.520 ⇒ 00:42:14.090 Uttam Kumaran: and get to the you know what the actual, you know, goal goal is like breaking it down right? For it’s like
426 00:42:14.210 ⇒ 00:42:22.050 Uttam Kumaran: we’re we looked at the gross margin equation. These are, gonna go after these pieces. Here are the like one or 2 things we’re gonna try. What do you think?
427 00:42:22.620 ⇒ 00:42:35.630 Uttam Kumaran: Yeah, that’s a that’s a great summary, right? I wish you could do that for every other client. But like every other client, it’s like a discussion there’s buy. And these guys are bought in. They know they trust us. They just don’t have the I the idea
428 00:42:35.800 ⇒ 00:42:42.160 Uttam Kumaran: on other clients. They come with bad ideas, and then we sort of have to execute those. Show them why it’s bad, and then do the right thing.
429 00:42:42.360 ⇒ 00:42:42.970 Payas Parab: Yeah, yeah.
430 00:42:43.150 ⇒ 00:42:43.920 Uttam Kumaran: Yeah.
431 00:42:46.930 ⇒ 00:42:54.330 Uttam Kumaran: it’s tough. This isn’t. It’s not an easy one. And again, like we’ve had probably 10 different people work on this client.
432 00:42:55.450 ⇒ 00:42:56.110 Payas Parab: Yeah.
433 00:42:58.050 ⇒ 00:43:03.730 Uttam Kumaran: So, but I mean I did it. So it’s it’s possible.
434 00:43:03.930 ⇒ 00:43:04.590 Payas Parab: Yeah.
435 00:43:05.280 ⇒ 00:43:06.090 Payas Parab: Okay.
436 00:43:06.320 ⇒ 00:43:08.379 Payas Parab: Awesome. Alright. Thank you, Tom.
437 00:43:08.740 ⇒ 00:43:09.580 Uttam Kumaran: Thank you.
438 00:43:09.900 ⇒ 00:43:11.679 Bo Yoon: Bye, guys, alright, thank you. Guys.