Meeting Title: Data-Review-1-26-24 Date: 2024-01-26 Meeting participants: Devon Drew, Uttam Kumaran
WEBVTT
1 00:00:07.080 ⇒ 00:00:13.600 Devon Drew: Like massive glass double doors we could get. stood. Frame me around the outside.
2 00:00:27.520 ⇒ 00:00:28.719 Uttam Kumaran: Hey? Good morning!
3 00:00:29.130 ⇒ 00:00:32.850 Uttam Kumaran: Hey? Good! How’s it going?
4 00:00:34.550 ⇒ 00:00:36.360 Oh, good brother, how about yourself?
5 00:00:36.600 ⇒ 00:00:41.339 Uttam Kumaran: Oh, well, I’m excited to kind of share a couple of things today
6 00:00:44.310 ⇒ 00:00:46.000 Devon Drew: is sarf joining us.
7 00:00:46.950 ⇒ 00:00:53.719 Uttam Kumaran: I think so. Let me send him a text, but we can probably get started.
8 00:00:54.220 ⇒ 00:01:05.480 Uttam Kumaran: I guess the main thing is, I wanted to see whether you can drive and log into light dash.
9 00:01:05.730 ⇒ 00:01:11.140 Uttam Kumaran: which is the tool that I wanted to demo to kind of do some basic reporting.
10 00:01:13.310 ⇒ 00:01:19.140 Uttam Kumaran: You should have received an email to log in. If not, let me know I can send another one.
11 00:01:20.810 ⇒ 00:01:22.740 Devon Drew: Let me
12 00:01:22.900 ⇒ 00:01:24.859 Uttam Kumaran: remember seeing email.
13 00:02:41.200 ⇒ 00:02:43.490 Uttam Kumaran: yeah, looks like you’re activated on there.
14 00:03:00.640 ⇒ 00:03:05.380 Devon Drew: Yeah, I’m just waiting for a a code to be sent to my email.
15 00:03:05.500 ⇒ 00:03:06.450 Uttam Kumaran: Okay.
16 00:03:07.050 ⇒ 00:03:09.409 Devon Drew: see if we maybe ended up on spam or something.
17 00:03:44.060 ⇒ 00:03:45.160 Devon Drew: Nothing. Yet
18 00:03:46.160 ⇒ 00:03:52.099 Uttam Kumaran: it says that you accepted the invite. So we did you? Were you able to just log in straight?
19 00:03:54.010 ⇒ 00:03:57.210 Devon Drew: Yeah, accepted the invite and
20 00:03:58.970 ⇒ 00:04:03.819 Devon Drew: just said to verify, check my check, my email inbox.
21 00:04:04.460 ⇒ 00:04:08.110 Uttam Kumaran: okay, okay, maybe let me let me just send you another one.
22 00:04:09.500 ⇒ 00:04:10.730 Uttam Kumaran: See if it works.
23 00:04:21.720 ⇒ 00:04:23.220 Surfield Thomas, Jr.: 18.
24 00:04:24.530 ⇒ 00:04:25.500 Uttam Kumaran: Hey?
25 00:04:29.600 ⇒ 00:04:33.160 Uttam Kumaran: Alright! I sent. Send an invite in the
26 00:04:33.320 ⇒ 00:04:34.650 Uttam Kumaran: zoom!
27 00:04:35.670 ⇒ 00:04:44.239 Surfield Thomas, Jr.: That’s for my dash. Yeah, that’s for Devon’s account, I think. So if you should have one in your email.
28 00:04:44.830 ⇒ 00:04:53.860 Devon Drew: yeah, it’s like the same thing that’s happening with with with our, with our email, with our system. So check your email. And then I don’t get an email.
29 00:04:54.210 ⇒ 00:05:14.529 Surfield Thomas, Jr.: Devon has me in a blender. All you finance grows. Email, me. Luton. I literally stole the Login flow from Prequel, and we never have login issues. And I’ve never had as many login issues as I’ve had in my life login and email issues in my life. I’m just like what’s happening.
30 00:05:14.550 ⇒ 00:05:33.680 Surfield Thomas, Jr.: I don’t know.
31 00:05:34.140 ⇒ 00:05:37.010 Surfield Thomas, Jr.: Yeah. Oh, yeah, we never had. We’d never had to deal with firewalls
32 00:05:37.490 ⇒ 00:05:50.939 Surfield Thomas, Jr.: because everybody was assass customer at a normal tech startup stuff like that. So yeah, no firewall stuff, no Internet stuff never had to do with that time. I clicked on it says, no link, no invite link found.
33 00:05:51.400 ⇒ 00:05:53.840 Uttam Kumaran: But
34 00:05:53.850 ⇒ 00:05:59.900 Devon Drew: is it saying, check your inbox still, and nothing resend it again.
35 00:06:00.160 ⇒ 00:06:05.519 Devon Drew: and then and then I try to resend it said, oh, and then it says we couldn’t send a verification
36 00:06:05.910 ⇒ 00:06:07.810 Devon Drew: email to your inbox.
37 00:06:09.600 ⇒ 00:06:11.110 Uttam Kumaran: But
38 00:06:11.470 ⇒ 00:06:14.959 Uttam Kumaran: okay.
39 00:06:16.660 ⇒ 00:06:19.680 Uttam Kumaran: well, I can drive
40 00:06:21.300 ⇒ 00:06:29.979 Uttam Kumaran: in case it’s not working right now. I have no clue. I wasn’t expecting this to be the problem.
41 00:06:32.590 ⇒ 00:06:39.330 Surfield Thomas, Jr.: Yeah, drive Devon gets here. I think next week I’m gonna take a look at his laptop to see what’s going on.
42 00:06:40.320 ⇒ 00:06:45.810 Uttam Kumaran: Okay, maybe let’s it doesn’t work. It’s okay. Just came in. Oh, it just came in. Okay.
43 00:06:47.210 ⇒ 00:06:48.610 Uttam Kumaran: okay, cool
44 00:07:05.620 ⇒ 00:07:06.320 up.
45 00:07:14.880 ⇒ 00:07:16.449 Uttam Kumaran: It’s working or no.
46 00:07:19.270 ⇒ 00:07:20.869 Devon Drew: not at this time.
47 00:07:21.010 ⇒ 00:07:25.740 Uttam Kumaran: Okay, I’m refreshing the page. See what happens.
48 00:07:25.860 ⇒ 00:07:26.810 Uttam Kumaran: Alright.
49 00:07:39.630 ⇒ 00:07:41.100 Devon Drew: let me try. Safari.
50 00:08:14.480 ⇒ 00:08:16.280 Devon Drew: Yeah, I don’t know, man, it’s a strange.
51 00:08:20.070 ⇒ 00:08:35.059 Uttam Kumaran: Let me let me just drive, and I can. We can figure it out after But basically. this is the tool that
52 00:08:35.559 ⇒ 00:08:37.869 Uttam Kumaran: I’m sharing. It’s this tool called
53 00:08:39.360 ⇒ 00:08:40.510 Uttam Kumaran: like dash.
54 00:08:43.010 ⇒ 00:08:50.709 Uttam Kumaran: So to give you a little bit of context on bi tools. So bi tools you may be familiar with like power bi tabloker.
55 00:08:50.760 ⇒ 00:08:53.040 Uttam Kumaran: All of those guys charge
56 00:08:53.090 ⇒ 00:09:02.530 Uttam Kumaran: on a per seat basis. And they charge like you have to sign like a minimum, like 15 K contract
57 00:09:02.650 ⇒ 00:09:10.030 Uttam Kumaran: to even get onto there. It’s like ridiculous. This industry is like really like in a choke hold by a couple of people.
58 00:09:10.050 ⇒ 00:09:26.430 Uttam Kumaran: The the thing I love about this product is that it’s actually has a lot of the same features, and pretty much this part, which is just like I can work at really, really fast and get data into charts for you without having to
59 00:09:26.690 ⇒ 00:09:31.369 Uttam Kumaran: deal with a lot of the headache of like looker and tableau. Actually, so, it’s like really lightweight
60 00:09:31.690 ⇒ 00:09:46.880 Uttam Kumaran: and I’ve been using this for about a year or so. And I, it’s really similar to some other products I use. So I kinda recommend, we try this basically again, if if you’ve used a Vi tool like this, maybe
61 00:09:47.020 ⇒ 00:10:13.960 Uttam Kumaran: new. But I’ll kind of walk through. So you kinda have a home page here. Typically what we’re kind of digesting is these assets. That may be charts or dashboards. Right now, we don’t have much created. It’s kind of what I wanted to chat about today. But basically, you can come on here and see data that we produce. You can also come on here and create charts from tables
62 00:10:13.970 ⇒ 00:10:23.280 Uttam Kumaran: cleaned up tables that have metrics and dimensions similar to how you would create a pivot table in excel, except it’s like pivot table on steroids.
63 00:10:23.580 ⇒ 00:10:34.269 Surfield Thomas, Jr.: Is it any data from my database or any data from Snowflake. It’s right now, any data from Snowflake.
64 00:10:35.180 ⇒ 00:10:47.229 Uttam Kumaran: So I don’t. So I can. I can connect it to postpress. And I’m thinking about doing that. I need to double check. I would. I would prefer to have everything in Snowflake.
65 00:10:47.410 ⇒ 00:10:48.600 Uttam Kumaran: model it.
66 00:10:49.230 ⇒ 00:10:53.300 Uttam Kumaran: join things, clean it up, and then make it available.
67 00:10:53.850 ⇒ 00:11:01.750 Uttam Kumaran: And we can talk about how to get some of that other. how how I can move some of the other data to S 3, or move it directly into Snowflake
68 00:11:01.810 ⇒ 00:11:02.950 Surfield Thomas, Jr.: 4, 3.
69 00:11:03.280 ⇒ 00:11:26.569 Surfield Thomas, Jr.: Yeah, II feel like there should be some way to integrate our data in our back end. You just have everything, and then you can do your stuff cause I think that will also help when when Devon’s asking, like, what are the things that we can potentially like, send off as new letters and stuff like that. And I think this would be the first step.
70 00:11:27.080 ⇒ 00:11:35.669 Surfield Thomas, Jr.: so that we understand the capabilities first, and that we have the data. Then it’s how do you summarize it and then send it to prospective clients?
71 00:11:36.010 ⇒ 00:11:43.909 Uttam Kumaran: You’re totally right. So that’s exactly what I think we’ll try to do either this weekend or next week.
72 00:11:44.140 ⇒ 00:11:57.199 Uttam Kumaran: so the the main thing I wanted to share is you can come here and click new, and then you could hit query from tables, and we have 3 tables that are available right now. The first 2 are actually the affinity score tables that I’m sending to serve.
73 00:11:57.260 ⇒ 00:12:05.320 Uttam Kumaran: So they don’t have mo a ton of information. It’s really just the asset manager name and the wealth manager name, and then the affinity score.
74 00:12:05.370 ⇒ 00:12:07.689 For example, if I were to say.
75 00:12:08.300 ⇒ 00:12:13.540 Uttam Kumaran: Let’s look at asset manager, name, wealth, manager, name.
76 00:12:13.570 ⇒ 00:12:16.980 Uttam Kumaran: and the affinity score, and
77 00:12:17.170 ⇒ 00:12:19.030 Uttam Kumaran: we can hit run.
78 00:12:21.970 ⇒ 00:12:36.959 Uttam Kumaran: You’ll see here in one, in, in one screen that quickly. You cannot see all that data. So, for example, you can go in here and and create like filter. This to say, I only want to look at affinity scores
79 00:12:37.040 ⇒ 00:12:52.549 Uttam Kumaran: that are less than let’s say 50 right? And then we can bring that in here. And then, for example, okay, these are all the ones less than 50. Let’s also bring in the match reasoning so why they were a match.
80 00:12:53.280 ⇒ 00:12:59.110 Uttam Kumaran: and then you can go in here and kind of look at this data. So this data doesn’t have much right. There’s one of these couple columns
81 00:12:59.190 ⇒ 00:13:04.100 Uttam Kumaran: where it gets interesting. Is when we kind of bring in
82 00:13:04.260 ⇒ 00:13:09.450 Uttam Kumaran: all of the data. So what I have here is a table set up to bring in all of the data
83 00:13:09.700 ⇒ 00:13:22.460 Uttam Kumaran: we have from the asset manager profiles. So they give you a sense of how much that is. We have all these core user fields. So when they’re created at we have all their demographic data, all the firm info data.
84 00:13:22.570 ⇒ 00:13:25.470 Uttam Kumaran: all the investment preferences, preferences.
85 00:13:25.610 ⇒ 00:13:30.540 Uttam Kumaran: location stuff they filled out, and the
86 00:13:30.630 ⇒ 00:13:32.600 Uttam Kumaran: professional information that they filled out.
87 00:13:33.710 ⇒ 00:13:44.119 Uttam Kumaran: So we can now create metrics on any of these. So these are all dimensions that you can bring in. For example, if I were to say, I want to look at all
88 00:13:44.230 ⇒ 00:13:50.439 Uttam Kumaran: first name, last name Id. Faith, Company, City
89 00:13:50.540 ⇒ 00:13:53.749 Uttam Kumaran: and Company state and hit run.
90 00:13:55.670 ⇒ 00:14:11.279 Uttam Kumaran: You’re not gonna see all of that data populate here. Now, again, this is where it’s gonna become even more apparent that, like we want people to kind of fill out a lot of data, because you can see there’s a lot of company city company state that isn’t filled out.
91 00:14:11.410 ⇒ 00:14:22.160 Uttam Kumaran: But some things like average account side as a class. I just wanna show a couple of things that I did see are filled out.
92 00:14:24.970 ⇒ 00:14:32.199 Uttam Kumaran: And so right in this data, you can now see all the aum information, all the preferred aum information
93 00:14:32.680 ⇒ 00:14:35.590 Uttam Kumaran: and then the nice thing you can do is
94 00:14:35.610 ⇒ 00:14:38.150 Uttam Kumaran: if we just to get rid of some of these
95 00:14:41.090 ⇒ 00:14:46.149 Uttam Kumaran: what I can show you is if we hit run.
96 00:14:46.820 ⇒ 00:14:53.320 Uttam Kumaran: we can actually see this on a chart in terms of like, who has. Sorry this isn’t a good chart.
97 00:14:53.920 ⇒ 00:14:55.890 What I’m gonna do is
98 00:14:56.290 ⇒ 00:14:57.800 Uttam Kumaran: just get rid of
99 00:14:58.620 ⇒ 00:14:59.820 these.
100 00:15:00.570 ⇒ 00:15:05.760 Uttam Kumaran: and then I’m gonna bring in a metric. That’s gonna be the number of asset managers.
101 00:15:06.290 ⇒ 00:15:11.870 Uttam Kumaran: and I will just bring that in here.
102 00:15:12.120 ⇒ 00:15:15.169 Uttam Kumaran: So at the bottom here there’s a number of distinct users.
103 00:15:15.630 ⇒ 00:15:20.619 Uttam Kumaran: and so we’ll bring that in, and then we’ll be able to look at distinct users
104 00:15:20.640 ⇒ 00:15:31.449 Uttam Kumaran: by preferred a ur. And so this is where I think we can really get into. And one thing you could do here is you could edit charts. So
105 00:15:31.510 ⇒ 00:15:38.339 Uttam Kumaran: to change names, add more columns. The one thing I want to do here is I want to add
106 00:15:38.450 ⇒ 00:15:41.579 Uttam Kumaran: the value label on top.
107 00:15:41.900 ⇒ 00:15:44.749 Uttam Kumaran: so we can see that. And so now you can see.
108 00:15:45.100 ⇒ 00:15:47.470 Uttam Kumaran: Okay, bye.
109 00:15:47.670 ⇒ 00:15:52.090 Uttam Kumaran: a lot. Some of them are null, but a lot of them are
110 00:15:52.480 ⇒ 00:15:54.590 Uttam Kumaran: are filled out like
111 00:15:54.890 ⇒ 00:16:06.489 Uttam Kumaran: you could see. And now here, there’s 19 people, 0 to 100 million and things like that. So that’s up. So that’s that 34 users. Where do they fall?
112 00:16:06.800 ⇒ 00:16:14.809 Uttam Kumaran: So that’s that’s a great question. So let’s say, if we were to say, who are these folks? If I were to say, I want to just filter by
113 00:16:15.030 ⇒ 00:16:24.809 Uttam Kumaran: everyone who has a who has a like an empty. Let’s say this is just an empty array.
114 00:16:30.270 ⇒ 00:16:43.850 Uttam Kumaran: I may need to make some changes because it’s a weird data type. But that’s exactly what what like a follow up question would be is like, I wanna go look at. Okay, where are all these? Who are these asset managers that have nothing in
115 00:16:43.940 ⇒ 00:16:49.770 Uttam Kumaran: their id. And so if we were to go back and say, Okay, Alice, go back and add first name.
116 00:16:49.830 ⇒ 00:16:52.609 Uttam Kumaran: last name Id.
117 00:16:52.760 ⇒ 00:16:54.789 Uttam Kumaran: and like company info.
118 00:16:54.860 ⇒ 00:16:59.269 Uttam Kumaran: And then we want to sort by
119 00:16:59.340 ⇒ 00:17:00.920 Uttam Kumaran: preferred a
120 00:17:02.070 ⇒ 00:17:06.599 Uttam Kumaran: We can go and look at all the people that have nothing in their preferred aom.
121 00:17:11.839 ⇒ 00:17:15.460 Uttam Kumaran: And so you can see there are people who have filled have filled out
122 00:17:16.079 ⇒ 00:17:16.950 Uttam Kumaran: and
123 00:17:17.079 ⇒ 00:17:20.270 Uttam Kumaran: but there’s quite a bit of people that don’t have anything there.
124 00:17:20.510 ⇒ 00:17:28.300 Uttam Kumaran: And so that’s exactly what I think we would do is one we can go through and say, Okay, now, we can really vividly see
125 00:17:28.390 ⇒ 00:17:42.859 Uttam Kumaran: how. Now it’s really hard for us to get that data. And we need these people to go fill it out so can we. Is there any engagement or activation we could do there? The second thing is all the data we do have. We can now begin building, not only internal reporting at
126 00:17:42.960 ⇒ 00:17:56.450 Uttam Kumaran: are people adding more information? What is like? How do we segment our users? But then, also you mentioned you. We needed data for marketing efforts. So, for example, you could say, like, we have
127 00:17:56.690 ⇒ 00:18:05.449 Uttam Kumaran: X amount of people seeking X amount of ao a aum, or seeking X amount of investment. Or you know, we can really quickly run those queries and get that information.
128 00:18:07.620 ⇒ 00:18:17.249 Devon Drew: Yeah, I mean, I’m, you know, obviously going into a right. All this, all this Bi is is very important to be able to put on a pitch deck.
129 00:18:17.300 ⇒ 00:18:20.669 Devon Drew: and then, from a marketing perspective,
130 00:18:21.060 ⇒ 00:18:22.799 Devon Drew: know, being able to
131 00:18:23.130 ⇒ 00:18:30.010 Devon Drew: go back to our existing pipeline of, you know, 3, 400 managers and say, Hey.
132 00:18:30.140 ⇒ 00:18:44.830 Devon Drew: you know, turn these report, turn, turn this. turn this into offense. Right? So you wanna say. you know, hey? you know, we currently have 30% of searches are now going to
133 00:18:44.980 ⇒ 00:18:49.859 Devon Drew: large cap value. If you have a large cap strategy, large cap value strategy.
134 00:18:50.040 ⇒ 00:19:00.309 Devon Drew: That’s large cap etf you should, you know you should come to ask and link so I’m thinking of it as a revenue driver.
135 00:19:00.520 ⇒ 00:19:08.669 Devon Drew: As well as you know, we’re gonna need this. Yo, we’re going to need all this break down when it UN when we’re goin to due diligence.
136 00:19:09.990 ⇒ 00:19:19.749 Uttam Kumaran: Totally. III totally agree. And the couple. The last thing I wanted to show before I kind of just have a bunch of questions to ask is what
137 00:19:20.130 ⇒ 00:19:31.130 Uttam Kumaran: the what you can do is you can take those graphs, and you can make them into charts. And so the only the chart that I made here is just new users over time, so you could see we’re adding about one to 3
138 00:19:31.260 ⇒ 00:19:34.229 Uttam Kumaran: new users per day pretty consistently.
139 00:19:34.740 ⇒ 00:19:47.779 Uttam Kumaran: And if you look at the results. You can kind of see that in here. And then, additionally, you can actually click in and view underlying data. And you can actually see who joined.
140 00:19:47.980 ⇒ 00:19:54.580 Uttam Kumaran: So you can see, is this person Id, and these people join on the twenty-fourth.
141 00:19:55.780 ⇒ 00:19:57.610 Uttam Kumaran: So again, the speed at which we can
142 00:19:58.250 ⇒ 00:20:06.350 Uttam Kumaran: ask and answer these questions is, you know, like 10 x but the kind of where I wanted to lead into now is like
143 00:20:06.810 ⇒ 00:20:10.310 Uttam Kumaran: for for you, Devon, and then also for surf.
144 00:20:10.410 ⇒ 00:20:11.680 Uttam Kumaran: What
145 00:20:11.850 ⇒ 00:20:19.600 Uttam Kumaran: are the most important charts and data points that we need now, and though I’ll give you a kind of sense of how to
146 00:20:19.990 ⇒ 00:20:24.960 Uttam Kumaran: II get after just being involved in a lot of analytics organizations. There’s
147 00:20:25.080 ⇒ 00:20:35.599 Uttam Kumaran: a couple of different ways of looking at data on, like a both on a weekly basis and on like an ad hoc basis. So one, there’s things where you just want to understand. The health of the platform
148 00:20:35.630 ⇒ 00:20:38.919 Uttam Kumaran: are people joining? Are there? Are all the features working?
149 00:20:38.990 ⇒ 00:20:53.469 Uttam Kumaran: Things like that. The second thing is, you want to understand your core. Kpis. So this is where you want to establish. Okay, our company Kpis, that we want to drive our new user sign ups. People with 90% of their profile filled out.
150 00:20:53.720 ⇒ 00:21:04.589 Uttam Kumaran: XYZ. Right? So we have like 5 to 7 of those. Those are the metrics that we can look at on a daily, weekly and monthly basis, and also forecast that growth.
151 00:21:04.650 ⇒ 00:21:27.160 Uttam Kumaran: The the the tough part with in a lot of places I’ve worked at is they like 50 metrics. And then you get you know you get. And there’s issues where you’re tracking too many things. So the one thing maybe we can do is think about. What are those key internal company, Kvis? This doesn’t have to be stuff that gets shared. This is, how do what are the things we need to affect to grow the business
152 00:21:27.160 ⇒ 00:21:38.049 Uttam Kumaran: and again, very simply that we can start with just like new users, people with filled up profiles, things like that. The second thing that I would suggest is a cadence at which we look at the data
153 00:21:38.350 ⇒ 00:21:51.540 Uttam Kumaran: so pretty commonly. I think people at least look at the stuff like this on a weekly and a monthly basis. II think it’s healthy to look at it on a daily basis. You’re just gonna get a lot more stressed out.
154 00:21:51.790 ⇒ 00:22:00.260 Uttam Kumaran: but at the same time we have the data on a daily basis. So I’m I’m happy. And so how does this differ from
155 00:22:00.750 ⇒ 00:22:03.729 Devon Drew: the things that pop the populate from Hubspot.
156 00:22:04.810 ⇒ 00:22:10.159 Uttam Kumaran: Yeah. So Hubspot will just have the information about your marketing efforts.
157 00:22:10.210 ⇒ 00:22:13.039 Uttam Kumaran: So they’re not gonna have information about
158 00:22:13.290 ⇒ 00:22:25.410 Uttam Kumaran: new user sign ups the profiles that get filled out the values in those profiles. And then, of course, any any information, any other information that we begin to bring in about
159 00:22:25.520 ⇒ 00:22:32.330 Devon Drew: asset link. Yeah. So they so I get like new user sign ups every day from Hubspot.
160 00:22:32.400 ⇒ 00:22:38.879 Devon Drew: Well, when are you know? When are the users. And and then they have, like forecasting tools.
161 00:22:39.170 ⇒ 00:22:45.870 Devon Drew: based off of like your average contract value, and and what you have them set for.
162 00:22:46.600 ⇒ 00:22:51.829 Devon Drew: And so. and there’s I guess there’s no way to integrate
163 00:22:51.870 ⇒ 00:22:57.969 Devon Drew: everything. So you know. So when you print off ports, or when we go to
164 00:22:58.470 ⇒ 00:23:00.190 Devon Drew: put these decks together.
165 00:23:01.450 ⇒ 00:23:03.760 Devon Drew: II guess we’ve had to go to 2 different places.
166 00:23:04.280 ⇒ 00:23:15.759 Uttam Kumaran: So we can actually Bru, we I. My suggestion is to actually bring in that hubspot data to snowflake. So anything around Hubspot contacts, hubspot opportunities we will bring in, we just
167 00:23:15.870 ⇒ 00:23:27.490 Uttam Kumaran: again. That’s a great point. I think, that we can add. We should add that to the list of to do that you should not have to go to multiple places to get that. The thing I will say is, Hubspot again is focused on Crm.
168 00:23:27.660 ⇒ 00:23:41.439 Uttam Kumaran: so we don’t wanna rebuild like a Crm system. We just wanna provide reporting on top of it. So the way a tool like this is helpful is when you wanna join that Hubspot contact data to the actual platform data
169 00:23:41.640 ⇒ 00:23:46.269 Uttam Kumaran: that you know, I kind of showed off where you have all the profile information. The other thing is.
170 00:23:46.430 ⇒ 00:23:53.150 Uttam Kumaran: surf sent me a flat file all the messages. So the one thing I wanna work on is
171 00:23:53.210 ⇒ 00:24:16.219 Uttam Kumaran: identifying all the messages sent on platform. What are people sending? How are they getting open all that info as well as I want to get the email info that we’re using to send emails out. So all that we we gotta centralize and join. And and again, this is primarily just so we can ask those questions and get to the answer really quickly in one area, how spot is gonna be the king of
172 00:24:16.460 ⇒ 00:24:18.879 Uttam Kumaran: anything you want to do on the Crm side.
173 00:24:18.950 ⇒ 00:24:23.530 Uttam Kumaran: But bringing everything in one place is is fairly.
174 00:24:23.540 ⇒ 00:24:31.579 Uttam Kumaran: and they do have a snowflake integration. That’s correct. Yeah. So II think you may have to talk to sales
175 00:24:31.850 ⇒ 00:24:37.939 Devon Drew: last time, so I could call. You need to upgrade your.
176 00:24:37.970 ⇒ 00:24:45.740 Uttam Kumaran: They’re gonna they’re they’ll try to rinse us. But I will. I have a couple of like alternatives. I’ll propose about how we could do that.
177 00:24:46.460 ⇒ 00:24:49.189 Uttam Kumaran: Again. This is about just what we need today
178 00:24:49.330 ⇒ 00:25:02.390 Uttam Kumaran: and what you we need for a what we need to understand the health of the business daily, Weekly, monthly. And then can we forecast right? And that will, I think, put us in a really good place to be able to decide
179 00:25:02.430 ⇒ 00:25:10.320 Uttam Kumaran: what are the 5 key kpis? Do. We have granular reporting on all them. And can we look at that on a daily, weekly, monthly basis?
180 00:25:15.030 ⇒ 00:25:22.149 Uttam Kumaran: So again, I guess, Devon, like looking at this stuff like, what are what are data points that you think would be
181 00:25:22.300 ⇒ 00:25:31.040 Uttam Kumaran: important to look at. Or I can even give you some time to play around in here once hopefully, you could get access.
182 00:25:31.380 ⇒ 00:25:38.350 Uttam Kumaran: but I definitely want to bring in all the web dwell manager, profile information, and all the messages. There’s anything else
183 00:25:38.360 ⇒ 00:25:40.280 Uttam Kumaran: or other charts
184 00:25:40.720 ⇒ 00:25:42.920 Uttam Kumaran: that you think are important to look at.
185 00:25:43.210 ⇒ 00:25:45.749 Uttam Kumaran: Let me know we can with them whip them up.
186 00:25:46.430 ⇒ 00:25:49.720 Devon Drew: Yeah, I mean. I it’s
187 00:25:50.140 ⇒ 00:25:55.489 Devon Drew: there’s the marketing, the sales and marketing hat. And then there’s like the business help hat.
188 00:25:55.740 ⇒ 00:26:07.290 Devon Drew: So from a marketing. Yeah, I got tons of ideas around around that cause. We need to turn these. We need to turn this business intelligence into revenue.
189 00:26:07.570 ⇒ 00:26:10.669 Devon Drew: And we need a seamless flow.
190 00:26:10.950 ⇒ 00:26:25.709 Devon Drew: To be able to to be able to do that right. Maybe it’s taking it from here. Going over to Tj. He creates a like one of those type of deals where, like he, you know cause we this is going to be like like knowing
191 00:26:27.030 ⇒ 00:26:33.460 Devon Drew: preferences, investing preferences is so important. right? And then
192 00:26:33.550 ⇒ 00:26:40.540 Devon Drew: being able to turn those preferences into into revenue is really important.
193 00:26:41.840 ⇒ 00:26:42.810 Devon Drew: I
194 00:26:43.330 ⇒ 00:26:47.910 Devon Drew: I would like to say, demographic data is important, but it’s probably not
195 00:26:48.990 ⇒ 00:26:51.550 Devon Drew: but it’s, you know, it’s good to know. So I know.
196 00:26:51.790 ⇒ 00:26:54.010 Devon Drew: Let’s see
197 00:26:54.670 ⇒ 00:26:56.939 Devon Drew: how many people were touching a month.
198 00:26:57.130 ⇒ 00:27:02.969 Devon Drew: yeah, I don’t know if that’s a month, or a day, or
199 00:27:03.380 ⇒ 00:27:10.799 Devon Drew: or or what. But you know definitely, people that are, they’re actively using investment preferences.
200 00:27:11.520 ⇒ 00:27:16.119 Devon Drew: engagement. Whether that is. you know, whether that is
201 00:27:16.130 ⇒ 00:27:28.529 Devon Drew: sending out messages, or if we’re able to track meetings even better cause that’s something tangible. Everybody everybody understand. If we just say, Hey, there’s a you know, there’s a thousand meeting requests sent out. And okay, well, what happens?
202 00:27:28.910 ⇒ 00:27:32.740 Devon Drew: So I think something quantifiable like.
203 00:27:33.090 ⇒ 00:27:39.190 Devon Drew: you know, having having engagement be quantifiable. isn’t is important.
204 00:27:39.480 ⇒ 00:27:50.359 Devon Drew: Right? Cause that shows that the platform works, and I think we’ve seen a lot of activity. But I don’t know. I don’t know how many meetings have been generated from that.
205 00:27:50.780 ⇒ 00:27:51.580 Uttam Kumaran: Yeah.
206 00:27:54.120 ⇒ 00:28:07.010 Uttam Kumaran: So one, let’s have a process by which maybe maybe we do a meeting on Monday or something. And we can decide. Here’s some great market. Here’s some great intelligence finds that we have.
207 00:28:07.180 ⇒ 00:28:08.569 Uttam Kumaran: How do we package that up?
208 00:28:08.830 ⇒ 00:28:29.210 Surfield Thomas, Jr.: I get surf. I’ll kind of leave it to you like, do you think is something Tj, can do. Well, I can. I can go in and find alright. Yeah, let me let me dig in here. So I actually have written a sheet that I wanted this to talk about. Right? Like we have high level aggregations, which is a lot of what I’m showing here. And then, like really, really deep level aggregations. Right?
209 00:28:29.250 ⇒ 00:28:38.359 Surfield Thomas, Jr.: So I guess I’ll give you the example again. There is like total aum on platform. Then there’s total aum in New York right?
210 00:28:38.680 ⇒ 00:28:46.139 Surfield Thomas, Jr.: When we’re talking about people that we’ve created profiles for trying to get them to convert and come on, I think
211 00:28:46.260 ⇒ 00:28:55.480 Surfield Thomas, Jr.: total aum on platform in a newsletter to the people who didn’t verify cause like, I can actually tell the difference between like real users and fake users.
212 00:28:55.920 ⇒ 00:29:14.740 Surfield Thomas, Jr.: Right? That kind of makes sense. Then when we’re talking about somebody like like an open Vc or people who are actually using the platform right, we can slice the same data at the lower level be like total aum in New York. Is this number right? Cause, like, we know that you’re located there? Right? So I think.
213 00:29:14.860 ⇒ 00:29:32.429 Surfield Thomas, Jr.: There’s 2 things right. We have a lot of this data uttam showing some of it. Now, we still need some of the context, which is what I was talking to you about, Devon, which is like going through the profiles, talking about all of the different fields, and like, give us the context there so that we can then send all of that to Tj to be like.
214 00:29:32.430 ⇒ 00:29:48.319 Surfield Thomas, Jr.: we’re gonna send that a newsletter. And it’s gonna have. This is, gonna say a UN. It’s gonna say, total amount of asset managers is gonna show you your top 10 is gonna show you. This is gonna show you that right like summarized in some way. And then we need to figure out like what the sequences cause like. When I first looked at it, I was like, we can send people emails
215 00:29:48.320 ⇒ 00:29:56.110 Surfield Thomas, Jr.: every single day of the week with the data that we have. So we need to figure out like how to put it together so that we’re not like going crazy like that.
216 00:29:56.230 ⇒ 00:30:03.199 Surfield Thomas, Jr.: What are the different targeting strategies, those sorts of things? So yes, this data is super useful. The question is, we need to figure out how to use it?
217 00:30:05.900 ⇒ 00:30:07.920 Devon Drew: Yeah, I think from a
218 00:30:08.600 ⇒ 00:30:10.919 Devon Drew: you know, there’s there’s the.
219 00:30:11.790 ⇒ 00:30:15.060 Devon Drew: There’s the what is important to
220 00:30:15.390 ⇒ 00:30:25.580 Devon Drew: people that’s gonna cut us a check for. And then there’s like, what what’s gonna drive that revenue when I think about like, what’s gonna drive the revenue from the day we have.
221 00:30:25.760 ⇒ 00:30:32.639 Devon Drew: I think, about asset classes interested in. I think, about total a one platform
222 00:30:33.690 ⇒ 00:30:50.720 Surfield Thomas, Jr.: I think about you know, I think about asset classes interested in. So so last is the not to cut you off right? But like that context is exactly what I want, right? Cause I could send that a newslet to every asset manager who hasn’t verified meaning. We created their profile
223 00:30:50.760 ⇒ 00:30:53.970 Surfield Thomas, Jr.: right? And there’s a bunch of interesting ways that I’m doing verification now.
224 00:30:54.100 ⇒ 00:30:57.040 Surfield Thomas, Jr.: where we could say.
225 00:30:57.550 ⇒ 00:30:58.460 Surfield Thomas, Jr.: there’s a
226 00:30:58.580 ⇒ 00:31:10.159 Surfield Thomas, Jr.: 10 billion dollars of aum on our platform, 450 advisers. And here are the top 10 asset classes they’re interested in. Come and join. That’s that’s that’s
227 00:31:11.030 ⇒ 00:31:18.940 Surfield Thomas, Jr.: alright. But that’s what I’m saying. III just came up with that because you just told me that was what’s important. So that’s what I need. I need the contacts
228 00:31:19.110 ⇒ 00:31:26.369 Devon Drew: for me when I’m look, when I’m looking at, when I’m looking at a profile. I’m like, Oh, this is nice. They’re filling this out. But like me and Utah really don’t have the content.
229 00:31:26.510 ⇒ 00:31:29.259 Uttam Kumaran: Yeah, that’s what you just said.
230 00:31:29.800 ⇒ 00:31:38.270 Devon Drew: like that drives revenue that drives that drives more important to revenue. That drives Fomo
231 00:31:38.370 ⇒ 00:31:50.850 Devon Drew: right? I mean, we have 15 million dollars in in in recurring revenue sitting in our pipeline right now. and they none of them have been nurtured. Right? You start sending out those those type
232 00:31:51.100 ⇒ 00:31:53.849 Devon Drew: emails on. On a regular cadence.
233 00:31:54.010 ⇒ 00:31:55.310 Devon Drew: They’re going to convert
234 00:31:55.710 ⇒ 00:32:03.830 Surfield Thomas, Jr.: Yup, and that’s what I’m saying. I got you there. So I what I’ll do is I’ll just have Tj. Work on what we just talked about right there. So we have one email.
235 00:32:03.840 ⇒ 00:32:08.720 Surfield Thomas, Jr.: But then what I want you to do is again go through each profile type
236 00:32:08.880 ⇒ 00:32:14.830 Surfield Thomas, Jr.: right? And just talk about each field. I sent them all over to you.
237 00:32:15.260 ⇒ 00:32:20.530 Surfield Thomas, Jr.: When did you send that over? Oh, as soon as the the day of Bro. I did not see that.
238 00:32:20.670 ⇒ 00:32:28.880 Surfield Thomas, Jr.: Remember, you could always call me and text me if you don’t hear me about forwarded forward. It’s a zoom cloud recording
239 00:32:30.080 ⇒ 00:32:31.989 Surfield Thomas, Jr.: zone cloud
240 00:32:33.820 ⇒ 00:32:41.110 Surfield Thomas, Jr.: you sent it on Tuesday, right? I see 3 of them. I bet I got it. I’ll take that over from here.
241 00:32:41.130 ⇒ 00:32:44.139 Surfield Thomas, Jr.: I want to get him working on that because I told him about it yesterday.
242 00:32:44.220 ⇒ 00:32:52.230 Surfield Thomas, Jr.: I was like, I got some. I didn’t see those emails.
243 00:32:52.530 ⇒ 00:33:16.409 Devon Drew: You know, you always gotta contact me with this email stuff I gotta get to. I gotta get you on upgrading to the New World. We gotta get the von all slack. That’s the problem I love. I love slack, and I have a whole bunch of them as well.
244 00:33:16.660 ⇒ 00:33:32.210 Surfield Thomas, Jr.: But II got it. I’m gonna take a look at them today. And I’m gonna start having doing some breakdowns. And I have some stuff for today. So yeah, maybe let’s look at a first version. And then we can. I can pull all the data we need, sir, really easily. And then I can even have him come in here and pull the data.
245 00:33:32.220 ⇒ 00:33:44.739 Surfield Thomas, Jr.: Yeah, well, that. So that’s the thing. I think we want to have the data so that we cause like the graph that utam showing right now, the is probably the highest level data that we’re going to use to get investment.
246 00:33:45.070 ⇒ 00:34:01.489 Surfield Thomas, Jr.: But then, like that, data is a semi like is like the highest level form of what we then need to do for 2 different things. Right? Get users on platform, which is the large level aggregations, and then nurture users using platforms so that they keep up with their engagement
247 00:34:01.660 ⇒ 00:34:02.450 Devon Drew: right
248 00:34:03.180 ⇒ 00:34:03.880 Surfield Thomas, Jr.: sweet.
249 00:34:05.400 ⇒ 00:34:18.210 Uttam Kumaran: So the second thing Devon is like, let’s talk about the business side that you mentioned like, what do you think is good to measure business health? And if you could just think about a couple of kpis, I’ll put something together that we can look at.
250 00:34:19.020 ⇒ 00:34:24.380 Uttam Kumaran: and I’ll send it either today or this weekend that would probably be
251 00:34:26.330 ⇒ 00:34:27.870 Devon Drew: is lament on this call.
252 00:34:28.060 ⇒ 00:34:29.109 Surfield Thomas, Jr.: Not he’s not.
253 00:34:30.090 ⇒ 00:34:34.560 Surfield Thomas, Jr.: We didn’t we? Didn’t. We never invited them. Not like we weren’t trying to, but we just
254 00:34:34.750 ⇒ 00:34:37.500 Surfield Thomas, Jr.: just moving. That would probably, I mean, like.
255 00:34:38.310 ⇒ 00:34:40.310 Devon Drew: I don’t know, you know, like
256 00:34:40.889 ⇒ 00:34:50.889 Devon Drew: I don’t know what like a Vc or strategic. I mean, I assume they want to know. People use the platform. People are actually, you know, people are using it, and and
257 00:34:50.900 ⇒ 00:34:53.530 Uttam Kumaran: like what else it could lead to?
258 00:34:53.620 ⇒ 00:35:03.920 Devon Drew: So II you know, II assume, using a platform I love like, you know, surf was like, Hey, this person who is talking shit as like.
259 00:35:05.100 ⇒ 00:35:08.379 I don’t have much time you spent on platform. But
260 00:35:08.390 ⇒ 00:35:10.010 Surfield Thomas, Jr.: being able to say.
261 00:35:10.280 ⇒ 00:35:11.610 Devon Drew: William.
262 00:35:11.760 ⇒ 00:35:21.860 Surfield Thomas, Jr.: oh, yeah. Snape was wild enough. so that’s the data that I know Utam. I showed you guys that we could get from
263 00:35:24.370 ⇒ 00:35:43.329 Surfield Thomas, Jr.: log rocket, but we have to pay. They’re not. They’re not. They’re not trying to just get up off that data. But they have all of the actual events like the like. The click events, the typing events, everything. So we had 2 users do, Williams. They had, like 963 events in one session. And there was other user that I sent you the
264 00:35:43.340 ⇒ 00:35:58.170 Surfield Thomas, Jr.: I don’t know who that person was, but you probably know who is. He had like 736 events. So like, they’re really clicking on stuff looking at stuff, looking at profiles kinda going crazy. That’d be like a power user like, Hey, we have this many users, but our power users.
265 00:35:58.740 ⇒ 00:36:03.090 Devon Drew: you know, like, I mean having being able to.
266 00:36:04.520 ⇒ 00:36:06.569 Devon Drew: you know, being able to chart out.
267 00:36:06.780 ⇒ 00:36:20.930 Devon Drew: I think, is, I think it’s very important to say, people actually using it right is one thing to talk about. Hey, we got data. We got this. But there’s another thing like people are using this as their business as their go to business development tool.
268 00:36:21.120 ⇒ 00:36:24.600 Uttam Kumaran: So I want to get in. I want to get in the messages.
269 00:36:25.510 ⇒ 00:36:31.100 Uttam Kumaran: And I think that’s a really good question. So I just, I’ve been involved in a bunch of like
270 00:36:31.170 ⇒ 00:36:39.490 Uttam Kumaran: seat in Series A and series B raises where I put the data together, and you’re you’re pretty spot on. They want to look at one. They want to look at
271 00:36:39.520 ⇒ 00:36:40.570 Uttam Kumaran: the money.
272 00:36:40.640 ⇒ 00:36:52.329 Uttam Kumaran: So if and when that exists, we can display that, the on platform metrics they’re gonna wanna look at are the number of users, the new user growth.
273 00:36:53.120 ⇒ 00:36:58.120 Uttam Kumaran: They’re gonna wanna. they’re gonna want us to have a notion of like active users
274 00:36:58.410 ⇒ 00:37:02.430 Uttam Kumaran: like, and we can decide what that is. This is where people kind of
275 00:37:02.540 ⇒ 00:37:04.820 Uttam Kumaran: finagle and and
276 00:37:04.870 ⇒ 00:37:06.690 Uttam Kumaran: kind of like just juice.
277 00:37:06.730 ⇒ 00:37:12.929 Uttam Kumaran: Pretty much so we can decide what active users are. They wanna look at. We wanna look at messages on platform.
278 00:37:12.980 ⇒ 00:37:14.689 Uttam Kumaran: We want to look at logins.
279 00:37:14.740 ⇒ 00:37:18.619 Uttam Kumaran: And then we also want to look at penetration into companies by email.
280 00:37:18.690 ⇒ 00:37:22.190 Uttam Kumaran: So what we’re gonna do is take all the email domains.
281 00:37:22.550 ⇒ 00:37:38.989 Uttam Kumaran: And then those are those companies are now technically users. Right? So we’ll do an analysis of email domains and get a sense of like things like fortune, 1,000 penetration, fortune, 500 penetration top banks, things like that. So you can have a nice logo sheet of
282 00:37:39.870 ⇒ 00:37:42.050 Uttam Kumaran: people at companies that are using it.
283 00:37:42.440 ⇒ 00:37:47.819 Uttam Kumaran: So all the information we have. I think, sir, if I may need login data.
284 00:37:47.930 ⇒ 00:38:04.060 Surfield Thomas, Jr.: or I know you mentioned you wanted to get. That’s like an activity feed. Yup, I’m gonna do an activity feed with login that shows login data, messaging data, and profile view data.
285 00:38:04.680 ⇒ 00:38:10.850 Surfield Thomas, Jr.: Yeah. So as like a person is clicking around on profiles, we’ll be able to see who’s looking at whose profiles.
286 00:38:12.110 ⇒ 00:38:22.039 Surfield Thomas, Jr.: So login data view data, I mean, you have the messages themselves. But I wanna just like be able to do a quick summary because it’s gonna just be one activity table. So it’s gonna be
287 00:38:22.360 ⇒ 00:38:23.540 Surfield Thomas, Jr.: user
288 00:38:23.860 ⇒ 00:38:24.810 action.
289 00:38:24.920 ⇒ 00:38:31.449 Surfield Thomas, Jr.: And then metadata and the metadata will just in most times it will be blank. But I’ll then also tell you the direction
290 00:38:31.710 ⇒ 00:38:38.589 Surfield Thomas, Jr.: view like like it’d be like user me viewed profile, and then it’ll say, like
291 00:38:39.190 ⇒ 00:38:54.519 Surfield Thomas, Jr.: profile. Devon, like like Devon’s Id, or something like that.
292 00:38:54.790 ⇒ 00:38:58.609 Devon Drew: with the when I was talking about a dashboard like a trends dashboard.
293 00:39:00.060 ⇒ 00:39:02.720 Devon Drew: So like if we have a lot of stuff I mean, like
294 00:39:03.040 ⇒ 00:39:08.990 Devon Drew: logging on and seeing, you know, like people seeing like the analytics behind
295 00:39:09.250 ⇒ 00:39:13.650 Devon Drew: things. I mean. I know I was probably, gonna you know.
296 00:39:14.450 ⇒ 00:39:21.239 Surfield Thomas, Jr.: I guess it could be somewhere on a roadmap. But that’s kind of what I’m talking about, just like, Hey.
297 00:39:21.280 ⇒ 00:39:24.390 Surfield Thomas, Jr.: I’m not filling out the idea of a dashboard.
298 00:39:24.790 ⇒ 00:39:40.100 Surfield Thomas, Jr.: but to create any sort of dashboard, even like the dashboard Utop showed us right now we need data. And I wanna understand what all our data means. Because then, once we yeah, once we solve that, I can give it to you as an email, we can give it to you as a dashboard. We could do whatever.
299 00:39:40.140 ⇒ 00:39:54.589 Surfield Thomas, Jr.: But it’s like we, we need to intrinsically understand what is the data we need to capture. And how do we like clean it? Kind of like this like repackage it? And then, after that, yeah, we could smack people over the face with, however, we want.
300 00:39:57.190 ⇒ 00:40:14.159 Uttam Kumaran: Yeah. And actually, this is a what, what I just showed doing it in my world is a lot easier than doing it on the platform. So this, what we crack on this initial dashboard will be like the guinea pig for, like, okay, can we turn this into something that’s on platform. What are the steps needed? It’s it’s
301 00:40:14.500 ⇒ 00:40:23.129 Uttam Kumaran: that’s the best way of doing this, because it’s lot easier for me to write these queries and get there internally, and then we could say, Okay, let’s turn this around and display this to users.
302 00:40:25.070 ⇒ 00:40:36.110 Uttam Kumaran: I guess my other question was, okay. So this is, I would say, this is pretty typical. I think what would also be helpful is to display some of those finance specific data.
303 00:40:36.280 ⇒ 00:40:38.240 Uttam Kumaran: right? Which is like. I think
304 00:40:38.340 ⇒ 00:40:42.839 Uttam Kumaran: I don’t know, Devon. What would you think is like about the profiles
305 00:40:43.250 ⇒ 00:40:47.300 Uttam Kumaran: or about what people are adding to their profiles would be helpful to look at
306 00:40:47.750 ⇒ 00:40:57.209 Uttam Kumaran: on like as a kpi cause. This is all. This is all pretty standard platform. But this is where it’s actually unique to your business.
307 00:41:00.610 ⇒ 00:41:01.980 Devon Drew: Yeah, so
308 00:41:05.020 ⇒ 00:41:22.390 Uttam Kumaran: find a specific or investment experience. Yeah, it’s almost like asset link specific meaning like, you can go to any software product and measure users or logins. But now it’s like, what’s what is the how do you measure the success of your product? Is it that, like
309 00:41:22.460 ⇒ 00:41:32.110 Devon Drew: we have 90% full profiles. Is it like we have this much. People want to go somewhere where they can get meetings.
310 00:41:33.570 ⇒ 00:41:52.779 Surfield Thomas, Jr.: I can’t check meetings, booked, or meetings attended
311 00:41:52.920 ⇒ 00:41:53.880 Surfield Thomas, Jr.: right now.
312 00:41:54.080 ⇒ 00:42:09.510 Surfield Thomas, Jr.: but I can check like meetings tried, and when I say tried, like, they actually have to click a button on our platform to schedule the meeting that takes them to the calendar link. I can see that data. Well, I can’t see it now, but I can add something in to see that data.
313 00:42:10.430 ⇒ 00:42:23.950 Surfield Thomas, Jr.: so we’ll we’ll have like meeting attempts we could call it. I mean, we can jazz it and call it whatever I was. But again, it’s like this is also helpful. For, like, okay, let’s now have a roadmap to drive towards how we can actually measure
314 00:42:24.070 ⇒ 00:42:32.219 Uttam Kumaran: whether the meeting happened right. And then this is the first step is like, did they click that button? Okay? Now, with the evolution of that kind of product.
315 00:42:32.460 ⇒ 00:42:41.719 Devon Drew: people will. So I’m in Miami right now, and I’m at a conference called, or I connections and surf. I’ve showed you the app before.
316 00:42:41.750 ⇒ 00:43:00.580 Devon Drew: would they? Tout all day long? Right? And I’ve been to Singapore with them. I’ve been next month into Dubai with them, and the reason people pay and and and granted I got a I got a pretty friendly deal, but you got people paying them a hundred 1,000 per conference, because they’re saying we will get you
317 00:43:01.690 ⇒ 00:43:02.920 Devon Drew: 50 meetings
318 00:43:04.290 ⇒ 00:43:14.820 Devon Drew: right. But we will get you a certain amount of meetings. Now. I don’t know if it’s all gonna happen like, for for last year I had 38 meetings for this conference. This one I have 12.
319 00:43:15.230 ⇒ 00:43:16.790 Devon Drew: Right? So it’s
320 00:43:17.930 ⇒ 00:43:20.520 Devon Drew: so I have to. I’ll have to look at the spend
321 00:43:20.550 ⇒ 00:43:26.910 Devon Drew: to see if it was worth it. But you give me 20 at bats, and I feel pretty damn good, and I’m gonna close them damn business.
322 00:43:26.950 ⇒ 00:43:29.359 Devon Drew: Same thing with Asylink, right? So
323 00:43:29.410 ⇒ 00:43:40.920 Devon Drew: we would. Probably we could probably jazz it up like, Hey, this meeting we had. If we say, Hey, we have 10,000 meeting requests. The next question is going to be like, Well, how many meetings are booked.
324 00:43:41.200 ⇒ 00:44:02.939 Uttam Kumaran: But but again, that’s what that’s what on the technology side and surf, we’ll be like, okay, let’s let’s find a way to capture that or or we can just say it as engagement. Right? So we don’t exactly intentions or engagements. Right? I agree with you guys. Let’s jazz up the word, because the problem is, we’re sending them to other people so like we don’t get to see that.
325 00:44:02.940 ⇒ 00:44:24.380 Uttam Kumaran: No, no, I. But what I what I’m saying is like, it’s helpful to define and to hear that as the Kpi, because driving that that kpi is is what determines the roadmap right? And so we can say now we need them. Now we need a way to either embed accountly or embed a zoom and be able to get closer to that meeting happening.
326 00:44:24.710 ⇒ 00:44:48.630 Uttam Kumaran: And like, that’s that’s, I think that’s great cause. Then we can say, like, actually, we have this many meetings that are happening on platform right? And then we can have external meetings. We we have all the message data. So people message about a meeting. We can consider that right. There’s all these ways of us getting closer to that. But I think that’s great. I didn’t. I think this conversation has helped me really being like, okay, it’s the interactions that’s actually the most important.
327 00:44:48.680 ⇒ 00:44:53.030 Uttam Kumaran: not not just the growth of the platform, but the fact that people are
328 00:44:53.170 ⇒ 00:44:58.089 Uttam Kumaran: booking meetings is like great. And then that we drive towards. How do we capture that?
329 00:44:59.020 ⇒ 00:45:03.889 Surfield Thomas, Jr.: And and look, calendar does have a Api
330 00:45:03.960 ⇒ 00:45:08.850 Surfield Thomas, Jr.: integration. So we could potentially actually do the directed booking.
331 00:45:09.670 ⇒ 00:45:15.879 Uttam Kumaran: It’s almost like. I wonder if like to pay in tope is an advisor.
332 00:45:16.810 ⇒ 00:45:21.170 Surfield Thomas, Jr.: the CEO dude. Yeah, he’s he’s on our advisory committee.
333 00:45:21.180 ⇒ 00:45:24.030 Surfield Thomas, Jr.: Oh, fire. So yeah, we listen, you can chop it over him.
334 00:45:24.710 ⇒ 00:45:36.650 Uttam Kumaran: Yeah, ask him. And you know also know how like some of these. You know how gl or like some of these pre, like professional network companies they like connect you. There’s probably ways for us to capture this data
335 00:45:36.670 ⇒ 00:45:42.240 Uttam Kumaran: again. Now that we have it, I’ll kind of think about what other ways we can find indications that a meeting is booked.
336 00:45:42.940 ⇒ 00:45:50.220 Uttam Kumaran: or it’s like something like, confirm, confirm. After your meeting. Did it go? Well, things like that?
337 00:45:51.330 ⇒ 00:45:54.160 Surfield Thomas, Jr.: Yeah. yeah. We could do follow up emails.
338 00:45:54.310 ⇒ 00:46:01.260 Uttam Kumaran: for example, if you if you book a meeting with somebody, then you need to indicate with us whether the meeting happened or whether it was good.
339 00:46:02.840 ⇒ 00:46:06.089 Surfield Thomas, Jr.: I would say, Yeah, but here’s the problem with that utam.
340 00:46:06.330 ⇒ 00:46:14.809 Surfield Thomas, Jr.: the types of users that we have. They just want it to be automated. They don’t want to do any extra steps.
341 00:46:14.930 ⇒ 00:46:19.430 Devon Drew: If I know eventually we’ll practice, get granted. But like, here’s what I’m also thinking.
342 00:46:19.580 ⇒ 00:46:41.009 Devon Drew: And engagement could just be so like these people want to know, they’re not gonna get it. So like other platforms like a fentrix, or whatever the feedback is like. Hey? I got the data I sent. Nobody ever responds. So I would actually make the argument. We could just say, Hey, as long as someone even like clicks on your damn email or opens your email like that’s considered engagement.
343 00:46:41.200 ⇒ 00:46:42.290 Uttam Kumaran: Yep, yes.
344 00:46:42.870 ⇒ 00:46:54.569 Devon Drew: So I would say, like we could make the at least the Kpi about engagement is is like, you know. one person sends something out. Another person has has an action on it.
345 00:46:55.080 ⇒ 00:47:08.320 Surfield Thomas, Jr.: That’s another interesting one, right? Cause like we have the ability to get. But we don’t have the open data yet. But we can pull it from Sendgrid, so it would have to.
346 00:47:08.500 ⇒ 00:47:13.709 Surfield Thomas, Jr.: And it sees everybody. It’s from like info at asset link or booking an asset link.
347 00:47:14.220 ⇒ 00:47:17.379 Uttam Kumaran: and it sends them light, then
348 00:47:18.040 ⇒ 00:47:19.469 Uttam Kumaran: that’s even closer.
349 00:47:19.490 ⇒ 00:47:23.790 Surfield Thomas, Jr.: Well, alright. So there’s 2 things. Let’s back up. So right now, we send emails
350 00:47:23.860 ⇒ 00:47:44.579 Surfield Thomas, Jr.: and we send them on the behalf of people we can actually see on our side the open race. But that data is in send grid. So we can build it out to actually pull in that data as well. So that we have, like the email opens. And I’ll summarize that into some sort of activity thing. So that can be done. Now, when we’re talking about
351 00:47:45.140 ⇒ 00:47:50.040 messaging, it’s actually a button on a platform that just opens out to their calendar.
352 00:47:50.610 ⇒ 00:47:53.980 Surfield Thomas, Jr.: So it’s not an email that goes out. I see
353 00:47:54.260 ⇒ 00:48:15.859 Surfield Thomas, Jr.: exactly. But what we could do is the same thing that Google does, which is like when you click on that. First you would like the Google tracker link, and then it like redirects you to where you want to go. Track that the event happened, not what happens after the fact, but even doing it like Google, when you go and Google Calendar. And you book a meeting with somebody, it cut. The email comes from Google Calendar.
354 00:48:18.310 ⇒ 00:48:24.910 Surfield Thomas, Jr.: Yeah. But we’re not. Yeah, yeah, yeah. But like, I, I’ll give you the perfect example, like, Devon didn’t even use
355 00:48:24.920 ⇒ 00:48:33.309 Surfield Thomas, Jr.: Google before, like, ask something he was using Microsoft as email provider. So it’s like, it’s not like we can like.
356 00:48:33.480 ⇒ 00:48:56.960 Surfield Thomas, Jr.: do the calendar thing and connect to Google Calendar cause. They all have Gmail. They all use all sorts of weird, different, like Msn crazy email providers. So it’s not. It’s it’s not 6 to sync, which is why we just take them on their word of like where their meeting schedule thing is cause like for right now we’re using Hubspot for for email, for Devon instead of calendar.
357 00:48:57.270 ⇒ 00:49:03.829 Surfield Thomas, Jr.: So they all use like a different meeting providers, different types of emails. It’s it’s
358 00:49:04.970 ⇒ 00:49:15.250 Devon Drew: connections, does. So so here’s what I connections does. And I’ll give you. And I’ll give you my login, if you want to look at it. So you request a meeting
359 00:49:15.340 ⇒ 00:49:28.230 Devon Drew: and it auto it. It auto generates your it auto generates a time to meet right?
360 00:49:28.480 ⇒ 00:49:31.900 Surfield Thomas, Jr.: Oh, yeah, stop sharing, and then I’ll share.
361 00:49:37.700 ⇒ 00:49:42.280 Surfield Thomas, Jr.: Yeah, go ahead to send me this recording, too. Sixth.
362 00:49:42.650 ⇒ 00:49:48.710 Devon Drew: So this is eye connections. So it has your chat. It has your meetings?
363 00:49:53.970 ⇒ 00:49:56.029 Devon Drew: Come on, okay, come on.
364 00:49:58.630 ⇒ 00:50:00.480 Devon Drew: So I have
365 00:50:02.070 ⇒ 00:50:03.990 Devon Drew: 12 confirmed meetings.
366 00:50:04.370 ⇒ 00:50:14.559 Devon Drew: 50 declined. Right? So I’m going into this. I’m saying, Oh, okay, III know for future that my benchmark is a 20 acceptance rate.
367 00:50:15.160 ⇒ 00:50:19.149 Devon Drew: and then I have 73 meetings sent that haven’t been answered. Yet
368 00:50:19.270 ⇒ 00:50:22.340 Devon Drew: right? The conference and the conference starts this week.
369 00:50:23.430 ⇒ 00:50:33.340 Devon Drew: Now what happens? So I go to upcoming events might be close now.
370 00:50:33.450 ⇒ 00:50:36.940 Devon Drew: so I have the event here.
371 00:50:38.090 ⇒ 00:50:45.330 Devon Drew: Global. Alt cool. I’m registered here to download the app. Let’s say you go to attendees
372 00:50:48.550 ⇒ 00:50:52.779 Devon Drew: and you go here and you say, meet you send a message.
373 00:51:00.500 ⇒ 00:51:18.969 Devon Drew: So say, meeting subject. Let receiver know why you wanna meet, hey? Well, this is what we’re doing. Well, we have this right cause. We have 20. We have. Oh, damn! I damn! I got 27 left. I need to start sending the shits up. Damn okay. I need to pull this shit up?
374 00:51:19.850 ⇒ 00:51:26.629 Devon Drew: I just made my day was I? Gonna say, you put it here right, hey? I wanna meet because of Xyz.
375 00:51:27.590 ⇒ 00:51:38.819 Devon Drew: You say, send request. If they accept it it automatically. goes from your calendar to their calendar and optimize the time to meet and just puts it on your calendar.
376 00:51:40.020 ⇒ 00:51:42.379 Surfield Thomas, Jr.: That’s the part. I don’t understand how that works.
377 00:51:43.910 ⇒ 00:51:44.930 Surfield Thomas, Jr.: Cause like
378 00:51:45.280 ⇒ 00:51:57.749 Surfield Thomas, Jr.: wait, hold on, hold on! Hold on! I was about to say this Devon is the calendar in this app. It’s everything’s in this app. That’s why. So they have their own calendar.
379 00:52:00.490 ⇒ 00:52:12.649 Surfield Thomas, Jr.: No. So here let me. Most people have to be using. I connections? Right? So it doesn’t. It doesn’t care about my other calendars, my other, it just says.
380 00:52:13.110 ⇒ 00:52:25.930 Devon Drew: and you here, where? Where can you go? Here? confirm meetings. That’s kind of cool. So everything is here. and it goes directly to your your email. And then you go.
381 00:52:28.260 ⇒ 00:52:30.639 Devon Drew: You go to availability and schedule.
382 00:52:31.340 ⇒ 00:52:38.819 Devon Drew: and it has the days where it has the remind you like, these conferences are only a couple of days. Right? So so, Wednesday.
383 00:52:39.420 ⇒ 00:52:41.510 Devon Drew: These are my meetings on Wednesday, so
384 00:52:41.580 ⇒ 00:52:48.049 Devon Drew: based off. And I could check when I’m available when I’m not available. So I’ll say, Hey, this time I’m not available.
385 00:52:48.130 ⇒ 00:52:53.870 Devon Drew: and whatever time I have available, they’ll just put it, and when you both have it open they just put it on your calendar.
386 00:52:55.710 ⇒ 00:53:06.110 Surfield Thomas, Jr.: So here’s the issue that we have, right we can build. We can build all of this out again over time. The main issue that we have is the same one. Why, I had to rewrite chat right
387 00:53:06.360 ⇒ 00:53:09.320 Surfield Thomas, Jr.: like it only works. If you have both sides of the network.
388 00:53:10.050 ⇒ 00:53:21.419 Uttam Kumaran: we even like a halfway solution to this, is like, if we can just understand that we that a calendly link, if we could just get the event data from the calendar
389 00:53:21.600 ⇒ 00:53:30.149 Uttam Kumaran: that, like the meeting, was confirmed, that that event happened. That’s it. Then we’d just assumed that happened
390 00:53:30.240 ⇒ 00:53:39.409 Surfield Thomas, Jr.: like, yes, we can do Calendar. But then, now we have to integrate across the board right cause, like I just told you Devon is using Hubspot for his.
391 00:53:39.440 ⇒ 00:53:42.430 Surfield Thomas, Jr.: How do we get that date? My Hubspot’s attached to Calendar?
392 00:53:43.660 ⇒ 00:53:45.290 Surfield Thomas, Jr.: Oh, I didn’t know that.
393 00:53:45.390 ⇒ 00:54:12.120 Surfield Thomas, Jr.: I understand that I’m seeing is the link that you put in. It’s not like we create it right? We are taking it for the end user. So if I work at Morgan Stanley. It doesn’t have to be calendly. Morgan Stanley.
394 00:54:12.210 ⇒ 00:54:31.030 Surfield Thomas, Jr.: Yeah, we’re taking. We’re we’re saying, do you want? If I if I do, you want people to to book meetings with you. If the answer to that is, yes, give us a link. We are indiscriminate on the link. We would. We would probably have to create our own link, and everybody gets their
395 00:54:31.050 ⇒ 00:54:49.080 Surfield Thomas, Jr.: exactly. Now, if we were to do that, then we actually need some sort of functionality like calendar, and what we could do is again link with their Apis and auto generate those sorts of things. The question is twofold right, one.
396 00:54:49.130 ⇒ 00:55:05.010 Surfield Thomas, Jr.: if we do it on their behalf? Will it just syncs up to their calendars? And I that might not even be important? Or do we build just an interface like I connections where everything is happening in the platform. Now, if we go, if we go, hold on, if we go the latter right.
397 00:55:06.110 ⇒ 00:55:17.580 Surfield Thomas, Jr.: that will work, but it will work for all of the people on platform. because, remember, a double sided network only works with double sides of the network, which is the issue that we have with chat.
398 00:55:17.710 ⇒ 00:55:28.759 Surfield Thomas, Jr.: We had chat. People were sending messages, but no one was responding because the other person wasn’t actually on the platform, which is why we went to Inbox, which is like every time you send the chat we send an email.
399 00:55:28.910 ⇒ 00:55:46.269 Devon Drew: And now they’re seeing the emails which is getting them to butt back to the app. So it’s connections works because everybody is going. It’s flying. And everyone right? So everyone is flying in and like they’re all gonna like they’re all gonna be here. But with that said, even though it’s on platform.
400 00:55:46.410 ⇒ 00:55:50.460 Devon Drew: this goes directly to my personal calendar. So as well.
401 00:55:51.750 ⇒ 00:55:59.169 Surfield Thomas, Jr.: Exactly. So now we got it. So so I when you say your personal calendar, you’re talking about, what calendar are you using? So whatever email that I have here.
402 00:55:59.420 ⇒ 00:56:07.390 Devon Drew: it goes to that calendar. So I. So when I pull up my iphone, or when I pull up my phone and I go to that day.
403 00:56:07.600 ⇒ 00:56:14.889 Uttam Kumaran: can you look at who that invite came from? Devon? Yeah, that that’s the part that we need to figure out. Cause I think I’m from.
404 00:56:15.410 ⇒ 00:56:18.029 Surfield Thomas, Jr.: I guess it could work.
405 00:56:18.230 ⇒ 00:56:32.079 Uttam Kumaran: So the way the way the way I think it’s working is they you? When you go book, they have both of your emails. They have the time they create an event. They’re the host of the event they invite both of you.
406 00:56:32.280 ⇒ 00:57:01.520 Surfield Thomas, Jr.: Yeah, III actually think that’s what’s yeah. I think you’re right. I think it’s not actually using calendar, you know, when you like it get, add exactly. So that’s what I need to figure out. What is the format cause. Remember it. They’re all different formats. So when you, when you create one of those in, when you get one of those invites to something, it’s like are using ical Google this, this, that the third right? Sometimes it comes with 9 different buttons, and you gotta click on the one for what you use
407 00:57:01.520 ⇒ 00:57:19.789 Uttam Kumaran: to then integrate? No, no, I actually think if it’s an if it’s an yeah, I think so. The the but I think this goes back to your previous point. Is you mentioned that like, okay, these guys just want it to be dead simple. What’s what’s more dead simple than having asset Link. Send you the invite with you guys there
408 00:57:19.940 ⇒ 00:57:28.739 Uttam Kumaran: and add your meet. Add like a zoom, or it comes pre loaded with Google Meets. That seems that seems even more simple than what we’re doing now.
409 00:57:28.960 ⇒ 00:57:35.090 Uttam Kumaran: Right? I think it’s like we need to figure out how to get that either integrated with calendly or it’s like
410 00:57:35.210 ⇒ 00:57:41.110 Uttam Kumaran: you can make your availability like. And the nice thing about here is Devon set his availability
411 00:57:41.120 ⇒ 00:57:43.320 Surfield Thomas, Jr.: within here.
412 00:57:43.780 ⇒ 00:57:46.519 Uttam Kumaran: And that’s how like, somehow, we need to get
413 00:57:47.010 ⇒ 00:58:12.840 Surfield Thomas, Jr.: in involved with calendar and find out whether we can hook up to calendar and have everybody use that or something. But yeah, like that idea which is like now, it’s not even that we send you an email with a calendar link that you’ve both been invited to. So you you could just join the link from the email right? But it’ll also be on your calendar. But it’s like it’s no longer like your calendly. It’s like, Are
414 00:58:12.980 ⇒ 00:58:27.910 Uttam Kumaran: Carolyn Lee, that you’re real like, really be like power into innovation. Yeah. And it’s it’s also like again, we don’t. We can. We can try to get around like, oh, can you book availability? But all we they could reschedule. All we need to know is that the meeting got booked?
415 00:58:28.210 ⇒ 00:58:46.079 Surfield Thomas, Jr.: Yeah, right? That’s all we need to know if they move it around, or if it’s like, Oh, that time didn’t work, whatever ideally from our perspective, if we can, if we actually own the meaning itself. Right? So we own the meeting. We do something with talent. Leave where we generate it. Then we get all the data
416 00:58:46.110 ⇒ 00:58:47.599 Surfield Thomas, Jr.: right. We get to see
417 00:58:47.640 ⇒ 00:58:54.520 Surfield Thomas, Jr.: you showed up. And that’s where you create a profile. You get your own link.
418 00:58:56.650 ⇒ 00:59:10.130 Surfield Thomas, Jr.: Yeah, this is interesting. There’s there’s a lot of different like, I mean, like, this is basically 2 integrations that we need here. We need something, something, something calendly, and then something something something like zoom
419 00:59:11.520 ⇒ 00:59:19.759 Surfield Thomas, Jr.: cause. Then we have all of the data. We can create, the, the, the, the link with. Well, we can send out the email
420 00:59:19.820 ⇒ 00:59:23.929 Surfield Thomas, Jr.: with the calendar, invite and have
421 00:59:24.180 ⇒ 00:59:27.339 Surfield Thomas, Jr.: Like to host the meeting itself.
422 00:59:27.550 ⇒ 00:59:28.750 Surfield Thomas, Jr.: Then we know everything.
423 00:59:33.980 ⇒ 00:59:45.500 Surfield Thomas, Jr.: The zoom will be ours inside of the meeting link and all of the data around the emails and acceptance will be provided by our integration with calendar or something like that.
424 00:59:45.880 ⇒ 00:59:55.869 Devon Drew: And then we need to figure out. So like, we’re gonna have to build this cost into our a when we talk about what a funds used for. So I’d also be curious of
425 00:59:55.920 ⇒ 00:59:58.760 Devon Drew: how much this would cost to build out.
426 00:59:58.880 ⇒ 01:00:13.859 Devon Drew: So then we said, we’re raising 10 million bucks, a million and a half scented patent. Another 500 go into the meeting integration. We can say, here’s what we know today.
427 01:00:13.900 ⇒ 01:00:31.340 Uttam Kumaran: This is where, in order for us to get even closer to the conversion event and own the conversion event and the details of it where the actual value exchange is happening. Right? The dream, again, that you guys mentioned is like having the platform own the exchange of the
428 01:00:31.480 ⇒ 01:00:38.189 Uttam Kumaran: actual cash. And so how do we get closer to that right? And this is the first step, I think, being close to these meetings.
429 01:00:40.930 ⇒ 01:00:43.080 Uttam Kumaran: So I think I think that’s
430 01:00:43.110 ⇒ 01:00:55.400 Uttam Kumaran: great, so I’ll let me let me put together a little dashboard with that stuff, I think, while if we have still have a couple of minutes. I wanted to just quickly talk about the
431 01:00:55.770 ⇒ 01:00:57.190 Uttam Kumaran: catalyze data.
432 01:00:57.820 ⇒ 01:01:00.509 Surfield Thomas, Jr.: Okay, I just stopped sharing.
433 01:01:01.900 ⇒ 01:01:11.130 Uttam Kumaran: So yeah, I guess I was like, because they just took so long to get back to us. I didn’t. I guess I didn’t really like
434 01:01:11.750 ⇒ 01:01:21.010 Devon Drew: get what what even their their email is about, but I guess this is what we this is what I sent to them with users, and they enriched it.
435 01:01:22.570 ⇒ 01:01:26.590 Uttam Kumaran: So I sent them a little random sample of
436 01:01:26.710 ⇒ 01:01:32.560 Uttam Kumaran: stuff. But don’t. But knowing. But knowing an advisor’s income means nothing to me.
437 01:01:35.280 ⇒ 01:01:43.070 Surfield Thomas, Jr.: Oh, okay, what? So you say, okay, let me let me what I initially sent.
438 01:01:43.490 ⇒ 01:01:46.459 Surfield Thomas, Jr.: yeah, yeah, I got it. I got it. This makes sense to me. Now.
439 01:01:48.540 ⇒ 01:01:59.400 Surfield Thomas, Jr.: yeah, I wanna even pull up what I initially sent. So if you if you send somebody you time. If you send somebody a subset of our data, it’s gonna be mixed. It’s gonna have
440 01:01:59.500 ⇒ 01:02:06.040 Surfield Thomas, Jr.: wealth managers, accredited investors and asset managers.
441 01:02:06.130 ⇒ 01:02:23.519 Surfield Thomas, Jr.: ideally, it should be split depending on who we’re sending it to. But it’s also interesting. Now that we’ve learned that catalyzed does. Yeah, they can enrich it, cause maybe they might be our data partner for everything.
442 01:02:23.840 ⇒ 01:02:35.110 Surfield Thomas, Jr.: It just depends on the well, like, well, like again, like what you just now, said an advisor, is, income means nothing to you. So it’s like, what are the fields we would want. So if we could actually get a parity of
443 01:02:35.370 ⇒ 01:02:46.710 Surfield Thomas, Jr.: advisor pros data like what they have. If catalyze could do it, we could just go to catalyze. But I wouldn’t imagine that catalyzed has 13 F data. So this, so this is what I sent to them.
444 01:02:47.720 ⇒ 01:02:49.480 Surfield Thomas, Jr.: And this is from us from us.
445 01:02:50.440 ⇒ 01:02:53.280 Devon Drew: I, yeah, I don’t know what that even means.
446 01:02:53.340 ⇒ 01:02:57.720 Surfield Thomas, Jr.: yeah. So d th, this is a mix. This is a mix of our user base. That’s why
447 01:02:58.910 ⇒ 01:03:05.180 Uttam Kumaran: it’s just a random subset from us. And then they sent us that they can enrich all those people with all this information.
448 01:03:05.390 ⇒ 01:03:08.949 Uttam Kumaran: which is kind of great
449 01:03:09.230 ⇒ 01:03:10.840 Devon Drew: company
450 01:03:12.830 ⇒ 01:03:14.110 Devon Drew: work email.
451 01:03:14.770 ⇒ 01:03:16.710 Uttam Kumaran: It’s really like this.
452 01:03:17.110 ⇒ 01:03:22.450 Uttam Kumaran: this, this I mean, I just send them. I just send a random stuff. So that’s why most of them are
453 01:03:22.960 ⇒ 01:03:29.769 Surfield Thomas, Jr.: investment folks cause. That’s so. I would. I would actually try this with, no, this is interesting.
454 01:03:30.600 ⇒ 01:03:40.320 Surfield Thomas, Jr.: This makes me very happy. Actually, I didn’t expect it. Not that I understand what’s going on. So I mean, so we should reach back out and try to set up another call.
455 01:03:40.660 ⇒ 01:03:44.589 Surfield Thomas, Jr.: Yeah. So let me let me see what we last sent. So
456 01:03:45.420 ⇒ 01:03:49.430 they so they have 2 things they want this enrichment. The second thing they have is
457 01:03:50.070 ⇒ 01:03:53.850 Uttam Kumaran: people going through the life events.
458 01:03:55.300 ⇒ 01:03:58.399 Uttam Kumaran: So we originally were discussing about
459 01:03:59.130 ⇒ 01:04:04.940 Uttam Kumaran: that. But then I was like, okay, they said, they have enrichment. Let me just send you some stuff
460 01:04:05.220 ⇒ 01:04:21.549 Surfield Thomas, Jr.: separated of data.
461 01:04:21.820 ⇒ 01:04:28.019 Surfield Thomas, Jr.: So Utam, you need to filter on if accredited investor or not.
462 01:04:28.030 ⇒ 01:04:32.379 Surfield Thomas, Jr.: all of the nots is one seat, all of the accredited investors in another seat.
463 01:04:32.390 ⇒ 01:04:36.929 Surfield Thomas, Jr.: because only for the accredited investors do we care about the life of it.
464 01:04:37.260 ⇒ 01:04:41.459 Surfield Thomas, Jr.: because those are the people that the non-credited investors want to target.
465 01:04:43.510 ⇒ 01:04:50.819 Surfield Thomas, Jr.: So we want the life events of the accredited investors right? And then we want whatever day they can give us on
466 01:04:50.850 ⇒ 01:04:55.579 Surfield Thomas, Jr.: the wealth manager, asset manager folks.
467 01:04:55.690 ⇒ 01:04:59.610 Surfield Thomas, Jr.: So with those 2 subsets, then we can fill out all of the profiles.
468 01:05:00.100 ⇒ 01:05:04.990 Uttam Kumaran: So let me send them a subset of our accredited investors and say.
469 01:05:05.030 ⇒ 01:05:09.609 Uttam Kumaran: Here’s 10. Can you tell me if you have any data on the
470 01:05:09.670 ⇒ 01:05:28.750 Uttam Kumaran: yeah.
471 01:05:28.830 ⇒ 01:05:41.669 Surfield Thomas, Jr.: yeah, this, yeah, that. But but but again, I think we, Tom, should follow with the email on just the accredited investors information. So maybe even before that call, we could just get one more piece of data to see what it looks like.
472 01:05:41.790 ⇒ 01:05:48.849 Surfield Thomas, Jr.: Cause if we could get the money in motion, plus this level of detail for the accredited investors. Now it is looking real crazy.
473 01:05:49.510 ⇒ 01:06:01.899 Surfield Thomas, Jr.: because if you can tell me where all these people live and all of that stuff. Then, again, now, I can summarize that into a message to the wealth managers like, look, there’s 400 people in New York.
474 01:06:02.410 ⇒ 01:06:05.470 Surfield Thomas, Jr.: 50 million dollars is gonna move in the next 6 months.
475 01:06:07.380 ⇒ 01:06:12.940 Surfield Thomas, Jr.: Come, find! Here are the PE here the top 10 people with the most money
476 01:06:14.150 ⇒ 01:06:23.210 Surfield Thomas, Jr.: right? Go after them. That’s just game over that. So exactly. So, yeah, we will. Yeah, this actually catalyzed might be to play.
477 01:06:44.170 ⇒ 01:07:02.299 Surfield Thomas, Jr.: Now, here’s my question. They only will enrich our data. They won’t give us extra data. No, they will give us net new data for the money in motion blanket. So that’s why I think advisor pros different.
478 01:07:03.570 ⇒ 01:07:20.499 Surfield Thomas, Jr.: Yeah. But utam, we already have all of the wealth managers and asset managers on hubspot. So we could just give them. Yeah, exactly. Yeah, now this, this. Now, now I’m happy.
479 01:07:20.580 ⇒ 01:07:27.869 Surfield Thomas, Jr.: This is very interesting. This is very, very interesting. I like this a lot.
480 01:07:28.320 ⇒ 01:07:33.769 Devon Drew: This is good. Yeah, so this is just so, and that’s what discovery said, hey, we’ll
481 01:07:34.220 ⇒ 01:07:40.189 Devon Drew: discovery said. We’ll enrich your data for 20 grand plus access to our platform.
482 01:07:41.280 ⇒ 01:07:46.159 Surfield Thomas, Jr.: Alright so. But but but but, bo but Devon, let’s back up, I think.
483 01:07:46.270 ⇒ 01:07:53.730 Surfield Thomas, Jr.: talking right. I don’t. I don’t know.
484 01:07:54.530 ⇒ 01:08:03.650 Devon Drew: I was confused, cause I thought they just. I thought they just had a credit. I thought they just had money motion data. I didn’t know anything about the advisor data.
485 01:08:03.870 ⇒ 01:08:07.050 Devon Drew: so I think I’m still kind of confused on.
486 01:08:07.170 ⇒ 01:08:09.920 Surfield Thomas, Jr.: And but I think there’s a thing they have both.
487 01:08:10.070 ⇒ 01:08:15.679 Uttam Kumaran: They have both. So this is a dollar product level level data.
488 01:08:16.050 ⇒ 01:08:20.040 Surfield Thomas, Jr.: Yeah, they won’t have the product level data.
489 01:08:20.270 ⇒ 01:08:27.490 Uttam Kumaran: advisor pro will have all. That’s why Advisor Pro has all, all the flight crd, stuff like that.
490 01:08:27.920 ⇒ 01:08:32.879 Surfield Thomas, Jr.: You guys are just like life, and they’re just enriching like about you.
491 01:08:33.029 ⇒ 01:08:37.989 Devon Drew: But shit we but like we might need to spend 30 grand to like
492 01:08:38.020 ⇒ 01:08:41.789 Devon Drew: Turbo charge 400,000 profiles.
493 01:08:42.660 ⇒ 01:08:46.289 Uttam Kumaran: So last thing we got to call and say, like, what’s the
494 01:08:46.390 ⇒ 01:08:48.050 Uttam Kumaran: kind of like, what’s the deal?
495 01:08:48.109 ⇒ 01:08:57.120 Surfield Thomas, Jr.: Yeah, we need to get a, we need to get a base bucket rate, right? Because if they’re talking a dollar per lead, 20,000 leads is $20,000, then we might as well go with the summer right? Like.
496 01:08:58.160 ⇒ 01:09:02.149 Surfield Thomas, Jr.: So it’s like that. I think that’s the one thing we need to. Now massage the pricing
497 01:09:03.380 ⇒ 01:09:07.430 Surfield Thomas, Jr.: like, what can we get for X number, right. It can’t be an option.
498 01:09:07.670 ⇒ 01:09:15.079 Devon Drew: But but we but let’s say we start with 5,000 money in motion to credit. Investor leads right. That’s
499 01:09:15.279 ⇒ 01:09:19.069 Devon Drew: now we’re at 6,000 on platform, right?
500 01:09:19.220 ⇒ 01:09:21.769 Surfield Thomas, Jr.: 7,000 on platform.
501 01:09:22.470 ⇒ 01:09:25.099 Surfield Thomas, Jr.: I mean you. Yeah. You tell me.
502 01:09:25.240 ⇒ 01:09:27.439 Devon Drew: no, I’m yeah. I’m
503 01:09:28.090 ⇒ 01:09:32.760 Devon Drew: that fills out the that fills out the profiles
504 01:09:32.920 ⇒ 01:09:44.870 Devon Drew: and then and then catalyze. Never told us. Have, you know, like Advisor pro, their data comes to stipulations right? They don’t want us to auto generate, even though it’s like the data is a data Bro relax
505 01:09:45.410 ⇒ 01:09:52.609 Devon Drew: same with discovery. They don’t want to see. But like catalyzed ago, here it is a dollar a dollar pro here, a dollar per. Here here it is.
506 01:09:53.020 ⇒ 01:10:03.259 Surfield Thomas, Jr.: And again it’s like all we’re trying to do. Why, so let’s back up on a lot on this idea. All we’re trying to do right now is have profiles filled out.
507 01:10:03.460 ⇒ 01:10:08.319 Surfield Thomas, Jr.: and enough of a space that when people are using the platform right?
508 01:10:08.890 ⇒ 01:10:22.000 Surfield Thomas, Jr.: It’s worthwhile all of the other data attributes that all these companies are getting. We can do ourselves. We just need more time right? Because if Advisor Pro can do it, we can do it. We can.
509 01:10:22.030 ⇒ 01:10:25.080 Surfield Thomas, Jr.: interpolated 13 F. We just need the time to build it.
510 01:10:25.890 ⇒ 01:10:32.090 Surfield Thomas, Jr.: They’re not doing anything like special or rocket sizes, just like we have so many like pleats spinning.
511 01:10:32.180 ⇒ 01:10:40.449 Surfield Thomas, Jr.: We need to get the platform to a state where, like people are using it. And people are like, Oh, this is awesome. And then we can go and build the rest of this enrichment.
512 01:10:42.050 ⇒ 01:10:46.400 Uttam Kumaran: Yeah. here’s here’s the advisor pro data again.
513 01:10:51.890 ⇒ 01:10:53.340 Devon Drew: And I got 3 min.
514 01:10:57.490 ⇒ 01:11:05.059 Devon Drew: Hold on. Was it a designation phone Linkedin? Years of experience
515 01:11:05.910 ⇒ 01:11:12.320 Devon Drew: team Id. I don’t know what that is. firm.
516 01:11:13.950 ⇒ 01:11:16.730 Devon Drew: So they’re gonna give. So we we get the role.
517 01:11:18.300 ⇒ 01:11:33.669 Uttam Kumaran: invest net.
518 01:11:33.950 ⇒ 01:11:35.250 Surfield Thomas, Jr.: catalyst.
519 01:11:37.250 ⇒ 01:11:40.540 Devon Drew: firm type, independent. Raa, that’s important.
520 01:11:42.140 ⇒ 01:11:44.989 Devon Drew: We don’t have that broken down in ours.
521 01:11:46.290 ⇒ 01:11:49.929 Uttam Kumaran: And then you can go. You can go contact all their people at their firm right?
522 01:11:56.570 ⇒ 01:12:05.619 Uttam Kumaran: So the the one thing with catalyzed is, if you do a bulk, they’ll cut a discount. So we should talk to them about like can we get? Can we do 25 cents per lead? What does what does that look like.
523 01:12:07.850 ⇒ 01:12:13.489 Uttam Kumaran: But again, it’s maybe if we request less data, we could get something else. But
524 01:12:17.100 ⇒ 01:12:22.059 Surfield Thomas, Jr.: I think the catalyzed data gets us really close.
525 01:12:22.170 ⇒ 01:12:24.460 Uttam Kumaran: This is what they sent us about.
526 01:12:25.910 ⇒ 01:12:28.270 Uttam Kumaran: Oh, this is where I grew up.
527 01:12:28.780 ⇒ 01:12:33.240 Uttam Kumaran: This is what they send us about. the firms.
528 01:12:34.410 ⇒ 01:12:39.640 Uttam Kumaran: but some of these all. Look, I don’t know. Not really sure.
529 01:12:47.540 ⇒ 01:12:51.890 Surfield Thomas, Jr.: There’s a lot. There’s a lot here which again is cool. But
530 01:12:53.740 ⇒ 01:12:57.519 Uttam Kumaran: this is about the firms, though this is really the ones about the people that
531 01:13:01.200 ⇒ 01:13:02.350 Uttam Kumaran: so like
532 01:13:03.740 ⇒ 01:13:15.760 Surfield Thomas, Jr.: licenses, Zip, State City City. But they again, these guys don’t want us to fill out profiles. But what? Yeah, but they don’t know what we don’t have already.
533 01:13:16.210 ⇒ 01:13:23.420 Uttam Kumaran: That’s true. There’s no there’s really no verification. II sent an email back to them. I was like yo kill me
534 01:13:27.520 ⇒ 01:13:35.830 Surfield Thomas, Jr.: cool. I think the name of the game is pricing on all of this from all the different parties. And then what’s the best bang for. But
535 01:13:36.110 ⇒ 01:13:45.909 Uttam Kumaran: when we talk to catalyze, let’s tell them that we’re we’re about to go with Advisor Pro, and we need the like, we need the price to come down.
536 01:13:46.480 ⇒ 01:13:48.160 Surfield Thomas, Jr.: Yeah, I think that’s fair.
537 01:13:48.890 ⇒ 01:13:54.630 Surfield Thomas, Jr.: I want yeah. Cause a dollar lead just is just, I don’t know. That’s crazy. I gotta hop.
538 01:13:54.690 ⇒ 01:14:05.599 Surfield Thomas, Jr.: Yeah, I’ll keep working.
539 01:14:05.710 ⇒ 01:14:08.880 Uttam Kumaran: Okay. Alright, please, Steve.