Meeting Title: Brainforge Interview with Demilade (Jasmin Multani) Date: 2025-12-16 Meeting participants: Demilade Agboola, Jasmin Multani
WEBVTT
1 00:02:13.920 ⇒ 00:02:16.249 Jasmin Multani: Hi there! Sorry for the delay!
2 00:02:16.250 ⇒ 00:02:23.510 Demilade Agboola: Hi, Jasmine. Oh, it’s all my fault, actually. I forgot to insert it, but then I just inserted it, and then also sent the link.
3 00:02:24.130 ⇒ 00:02:36.780 Jasmin Multani: Okay, no worries, no worries. Yeah, I was just, like, going through Zoom, I’m like, was it Google Meets? Was it Zoom? Oh, but I’m glad, we, we got time. And it looks like we have until 9.45 to… to catch up and everything.
4 00:02:36.780 ⇒ 00:02:40.040 Demilade Agboola: Yeah. You know, what time zone are you in? Like, where are you based?
5 00:02:40.290 ⇒ 00:02:42.050 Jasmin Multani: I’m based out of LA.
6 00:02:42.050 ⇒ 00:02:42.900 Demilade Agboola: So…
7 00:02:43.130 ⇒ 00:02:50.539 Jasmin Multani: I’m actually pretty close to Amber, we both realized yesterday, and I think Hannah’s also, around Culver area, so…
8 00:02:51.010 ⇒ 00:02:57.869 Demilade Agboola: Yeah, yeah, that’s pretty cool. That means the LA team potentially could be growing quite big.
9 00:02:58.020 ⇒ 00:02:59.060 Jasmin Multani: Yeah, that…
10 00:02:59.060 ⇒ 00:03:00.039 Demilade Agboola: We’re all around.
11 00:03:00.220 ⇒ 00:03:13.069 Demilade Agboola: So Utam’s in Dallas, Roberts in New York, I’m in Malta, we have people in the Philippines, we have someone in… we have someone in Pakistan, someone in India, so we’re around.
12 00:03:13.360 ⇒ 00:03:18.379 Jasmin Multani: We’re around, yeah. So, first off, like, how do I pronounce your name?
13 00:03:18.380 ⇒ 00:03:20.590 Demilade Agboola: Oh, okay. My name is Demilade.
14 00:03:21.020 ⇒ 00:03:22.250 Jasmin Multani: Demilade.
15 00:03:22.430 ⇒ 00:03:26.900 Demilade Agboola: Team Lady, yes, so… Okay. So I’m Nigerian, that’s…
16 00:03:28.050 ⇒ 00:03:31.299 Demilade Agboola: from the Uruga tribe, and that’s where my name comes from.
17 00:03:31.850 ⇒ 00:03:35.520 Demilade Agboola: Fun fact, that’s the shorter version, it’s actually a bit longer.
18 00:03:35.520 ⇒ 00:03:39.020 Jasmin Multani: Oh, man. Okay, what’s the longer version, then?
19 00:03:39.020 ⇒ 00:03:45.770 Demilade Agboola: Oh, so the longer version is Uluwa Dimladeh. It translates into God Has Crowned Me, if you ever were curious.
20 00:03:45.770 ⇒ 00:03:49.749 Jasmin Multani: Yeah, yeah, sounds very melodic, too.
21 00:03:49.750 ⇒ 00:03:53.709 Demilade Agboola: Oh, but Tim Light is fine.
22 00:03:54.120 ⇒ 00:03:59.940 Demilade Agboola: So, yeah, I work in Brainforge, as an analytics engineer.
23 00:04:00.070 ⇒ 00:04:04.460 Demilade Agboola: I have been there, like, I’ve been in Brainforge for the past…
24 00:04:04.790 ⇒ 00:04:07.310 Demilade Agboola: 8 months, thereabout. I joined in March.
25 00:04:07.570 ⇒ 00:04:22.840 Demilade Agboola: And so far, it’s been pretty cool, it’s been pretty nice. I work with a bunch of clients, and this isn’t actually my first rodeo in consulting, but, you know, it’s nice to be able to, you know, hop back on that and be able to do
26 00:04:23.460 ⇒ 00:04:23.990 Demilade Agboola: Yeah.
27 00:04:24.420 ⇒ 00:04:30.409 Demilade Agboola: work with dbt and just help people solve their data problems, which a lot of people have a lot of data problems.
28 00:04:30.410 ⇒ 00:04:37.140 Jasmin Multani: Yeah, especially when startups are scaling. I feel like there’s gonna be a… there’s already a huge boom with all these, like,
29 00:04:37.750 ⇒ 00:04:51.900 Jasmin Multani: Code Vibe apps, so… but I feel like not a lot of people know how to grow their actual apps and glean insights from there, so there’s gonna be a lot of work for us.
30 00:04:51.960 ⇒ 00:04:53.100 Demilade Agboola: Yeah, fabulous.
31 00:04:53.100 ⇒ 00:04:58.029 Jasmin Multani: Maybe we can spend the next just 40 minutes just asking each other questions?
32 00:04:58.030 ⇒ 00:04:58.680 Demilade Agboola: Yeah, sure.
33 00:04:58.680 ⇒ 00:05:01.629 Jasmin Multani: Yeah, I had asked at them just to…
34 00:05:02.020 ⇒ 00:05:09.990 Jasmin Multani: get a sense of how the team is, what your pain points are, before I understand, you know, how can I actually be a good…
35 00:05:10.120 ⇒ 00:05:13.120 Jasmin Multani: Good contribution for the team.
36 00:05:13.150 ⇒ 00:05:14.600 Demilade Agboola: So…
37 00:05:14.600 ⇒ 00:05:15.300 Jasmin Multani: Yeah.
38 00:05:15.470 ⇒ 00:05:24.130 Demilade Agboola: That’s fair. I did have a bunch of questions I wanted to ask, but, like, that I think it’s more, like, within the flow of the conversation.
39 00:05:26.230 ⇒ 00:05:26.610 Jasmin Multani: Yeah.
40 00:05:26.610 ⇒ 00:05:33.490 Demilade Agboola: you know, obviously, I think the first part would just be, like, it would be nice to, like, care about yourself and your history, and, like, what tools you’re proficient in.
41 00:05:34.490 ⇒ 00:05:42.749 Jasmin Multani: Okay, yeah, yeah, yeah. So, starting off, I actually did my undergrad BS in neuroscience, and I worked in research for a couple of years.
42 00:05:42.750 ⇒ 00:05:57.319 Jasmin Multani: From there, I was able to get my feet wet with MATLAB, and in MATLAB, what’s interesting is that, yeah, you can do data analysis in the programming world, but, MATLAB also is able to coordinate with hardware.
43 00:05:57.330 ⇒ 00:06:02.909 Jasmin Multani: So, what ends up happening is, like, for animal research, let’s say we want to understand…
44 00:06:03.190 ⇒ 00:06:13.900 Jasmin Multani: auditory tones, like perception of certain frequencies, for the animals, you can actually program in MATLAB, different…
45 00:06:13.930 ⇒ 00:06:31.609 Jasmin Multani: You know, auditory herds, and the train, and build different, sound trains, and have that coordinated so that it’s working with the hardware, and it’s being, triggered by the hardware, and it’s being played out by the speakers, in a well-coordinated way.
46 00:06:31.670 ⇒ 00:06:37.529 Jasmin Multani: And from there, I realized, I don’t want to do research, I want to do something more,
47 00:06:37.590 ⇒ 00:06:53.529 Jasmin Multani: with a closer feedback loop, instead of, you know, spending 20 years funneling into one, niche, I’d rather, you know, build a skill set that lets me have exposure to different types of projects and ideas.
48 00:06:53.740 ⇒ 00:07:07.610 Jasmin Multani: And I think that’s why I am still looking, for the next best thing. From there, I was able to, level, level, teach myself SQL and Python online.
49 00:07:07.610 ⇒ 00:07:17.370 Jasmin Multani: Reached out to people on LinkedIn so that they could review my GitHub, which is now completely dead at this point. And got my foot through the door in DoorDash.
50 00:07:17.760 ⇒ 00:07:34.570 Jasmin Multani: From there, I was working on strategy and ops. At that point, restaurant side was doing really well, and I was… I had joined in the middle of the pandemic when the company was growing its grocery and new vertical, verticals.
51 00:07:34.830 ⇒ 00:07:43.539 Jasmin Multani: So, we started off with grocery and convenience, and then, as time went on, I watched,
52 00:07:43.790 ⇒ 00:07:57.529 Jasmin Multani: the company make stronger brand deals with alcohol, flowers, retail was a big, big one before I left as well. So, just understanding how we can adapt the products,
53 00:07:57.660 ⇒ 00:07:59.229 Jasmin Multani: As we scaled out.
54 00:07:59.680 ⇒ 00:08:17.789 Jasmin Multani: And from there, I did a small stint with Robert, when we… he was over at Pungo Insights, and then I transitioned to TikTok, where I’m at right now. At… yeah, yeah, TikTok, I’m in trust and safety, so a lot of it is…
55 00:08:17.980 ⇒ 00:08:35.119 Jasmin Multani: detection anomalies and working with data engineers to make sure that the pipelines are flowing accurately to the respective moderator queues. That’s one part of it. The other part of it is making sure, you know, my detections are
56 00:08:35.320 ⇒ 00:08:41.399 Jasmin Multani: tracking what they’re supposed to be tracking, right? So, I’m in charge of…
57 00:08:42.490 ⇒ 00:09:00.819 Jasmin Multani: Tracking for people who are selling drugs, or people who are selling guns, on the platform, and whatever works for US side, I hand it over to Global. And obviously, TikTok’s a big company, so we already have LLMs and MLs that, track for these things.
58 00:09:00.870 ⇒ 00:09:02.859 Jasmin Multani: At the…
59 00:09:03.210 ⇒ 00:09:12.069 Jasmin Multani: platform level, but where my team acts is we act as a stopgap to, track leakage that the models aren’t,
60 00:09:12.930 ⇒ 00:09:21.309 Jasmin Multani: aren’t able to catch. And if we see a high enough volume from a certain user case, the idea is to,
61 00:09:21.450 ⇒ 00:09:27.610 Jasmin Multani: Grab that training data and send it over to the larger algorithm team so that they can just train.
62 00:09:27.610 ⇒ 00:09:28.310 Demilade Agboola: spring.
63 00:09:28.310 ⇒ 00:09:29.540 Jasmin Multani: Yeah, that’s pretty cool.
64 00:09:29.970 ⇒ 00:09:30.489 Demilade Agboola: That’s pretty cool.
65 00:09:30.490 ⇒ 00:09:38.600 Jasmin Multani: It’s cool in theory, but I think given the amount of reorgs that have happened, and the amount of churn, especially with…
66 00:09:38.990 ⇒ 00:09:46.239 Jasmin Multani: all the many Congress cases TikTok is facing in the US.
67 00:09:46.240 ⇒ 00:09:47.270 Demilade Agboola: Things have…
68 00:09:47.270 ⇒ 00:09:54.100 Jasmin Multani: Much slower than even seasoned employees have anticipated, so…
69 00:09:54.220 ⇒ 00:09:59.060 Jasmin Multani: there’s that. But now that I’m here, you know.
70 00:09:59.330 ⇒ 00:10:11.680 Jasmin Multani: I was talking to Hannah, we were just hanging out, at a pottery class, and she was like, hey, do you want to come back to Brainforge? And I’m like, hmm, I wonder what that would look like. So, this is me exploring, what that.
71 00:10:11.680 ⇒ 00:10:12.280 Demilade Agboola: Take one.
72 00:10:12.280 ⇒ 00:10:18.190 Jasmin Multani: like, where I would lean in. It sounds like the role is gonna be very, self-driven.
73 00:10:18.910 ⇒ 00:10:23.160 Demilade Agboola: Yeah, it’s definitely, like, in Brainforge,
74 00:10:23.920 ⇒ 00:10:30.060 Demilade Agboola: We definitely have… we have clients across board, and the basic idea is we…
75 00:10:30.770 ⇒ 00:10:43.110 Demilade Agboola: we try to roadmap the idea, like, the client. So we say, hey, it’s a 3-month project, this is what that roadmap looks like, or in some cases, 6 months, and the idea is we need to be…
76 00:10:44.360 ⇒ 00:10:52.629 Demilade Agboola: responsible for ourselves, in the sense of, like, we will figure out, like, what the roadmap looks like. And then, obviously, with the team.
77 00:10:54.160 ⇒ 00:10:57.610 Demilade Agboola: We’re able to then, and a lot of the
78 00:10:58.010 ⇒ 00:10:59.900 Demilade Agboola: Broad mapping tends to come from
79 00:11:00.180 ⇒ 00:11:12.429 Demilade Agboola: project management, as well as the analysts, so we’re able to scope everything together and say, hey, this is a realistic timeline for this. Project manager is able to go, hey, this is what we expect to get out of this project by the close of it.
80 00:11:12.440 ⇒ 00:11:26.230 Demilade Agboola: And that allows us to be able to create the roadmap. So we can say, hey, we need metrics on this, which means the A team and D team need to be responsible for getting the data out by this time, and then the analysts can take over and build out the dashboards by this time.
81 00:11:26.360 ⇒ 00:11:33.280 Demilade Agboola: So, in a way, there’s, you know, a lot of constant communication across multiple like, roles.
82 00:11:33.480 ⇒ 00:11:41.740 Demilade Agboola: And also, there is that ability to communicate issues when they arise, as well as, just being able to
83 00:11:41.990 ⇒ 00:11:47.550 Demilade Agboola: Be responsible, quote-unquote, for, like, The outcomes of your role, if that makes any sense.
84 00:11:47.810 ⇒ 00:11:49.360 Jasmin Multani: Yes. Yeah, sure. Okay.
85 00:11:50.830 ⇒ 00:11:54.069 Demilade Agboola: I am curious still, like, what tools would you say you’re, like.
86 00:11:54.370 ⇒ 00:11:55.250 Jasmin Multani: Oh, yeah.
87 00:11:55.850 ⇒ 00:12:13.539 Jasmin Multani: I’d say most comfortable in SQL. I think in terms of dashboarding, dashboarding, I’ve had so much exposure to different softwares that I’m like, okay, I’m not married to one thing. I think the reality is…
88 00:12:16.620 ⇒ 00:12:18.840 Jasmin Multani: There are only so many ways…
89 00:12:18.960 ⇒ 00:12:28.400 Jasmin Multani: a C-suite wants to track retention, and wants to understand, metric degradation week over week, and,
90 00:12:28.660 ⇒ 00:12:45.610 Jasmin Multani: I’ve worked with Snowflake, TikTok, I’ve worked… yeah, I’ve worked with Snowflake, worked with Chartio, worked with Tableau. I don’t really like Tableau, but maybe that’s because of the license I had, for at DoorDash. And then, at TikTok, we actually have… all of our tools are in-house.
91 00:12:45.700 ⇒ 00:12:53.570 Jasmin Multani: So, it’s all internally built by ByteDance, but… so, like.
92 00:12:54.590 ⇒ 00:13:04.319 Jasmin Multani: if companies are using Salesforce, we have our own version of Salesforce. So, that’s the tricky part. I think the tools that I’ve built…
93 00:13:04.440 ⇒ 00:13:12.320 Jasmin Multani: the tool exposure I’ve built is very niche, but I’ve also been exposed to enough software over the years where I’m like, okay.
94 00:13:12.520 ⇒ 00:13:32.299 Jasmin Multani: If I use Mixpanel all over again, I’m gonna have to start from ground zero. If I use amplitude again, I’m gonna have to start from ground zero, familiarize myself. But the large idea is the same. It’s like, people want to understand week-over-week degradation. There are folks who, surprisingly, even at TikTok.
95 00:13:32.480 ⇒ 00:13:40.990 Jasmin Multani: they are just tracking metrics, but they’re not making decisions out of those metrics, and that’s very frustrating. Or they’ll say, hey, yeah, so…
96 00:13:40.990 ⇒ 00:13:57.029 Jasmin Multani: this, video violation rate, it’s been trending pretty plateaued, but then back in October, there was a huge spike, and that kicked us off with our RCA, and I’m like, that’s it? Like, you guys don’t have any thresholds, you guys don’t have any, like.
97 00:13:57.690 ⇒ 00:14:02.639 Jasmin Multani: goals, week-over-week goals, so I think that’s been the frustration at TikTok, because,
98 00:14:03.160 ⇒ 00:14:10.780 Jasmin Multani: there is no cost spent, right? Because every… all the tools are internally built,
99 00:14:11.100 ⇒ 00:14:18.670 Jasmin Multani: moderators mostly aren’t in-house and salaried. There are BPO counterparts, but,
100 00:14:19.210 ⇒ 00:14:33.489 Jasmin Multani: that’s, like, the only dollar sign that I see. Whereas over at DoorDash, it was very clear, you know, to make these strategies and say, hey, customers are inbounding about this one prop… order problem.
101 00:14:33.490 ⇒ 00:14:43.899 Jasmin Multani: and it’s driving an X percent or X dollar, amount in, Salesforce, venture, and we can…
102 00:14:44.000 ⇒ 00:14:57.069 Jasmin Multani: we can justifiably say, hey, every inbound costs us $1.50. And that’s a really easy… that’s a really easy, argument to make, to get people aligned and get resources aligned.
103 00:14:57.140 ⇒ 00:15:08.340 Jasmin Multani: But I’d say over at TikTok, it’s very vision-based, very creative-based, and saying, hey, if I were… if I were a user, what would I want, to make my life better?
104 00:15:08.560 ⇒ 00:15:10.349 Jasmin Multani: So I think that’s the interesting part.
105 00:15:10.510 ⇒ 00:15:13.749 Jasmin Multani: Yeah, I’m sure that answered your questions, but…
106 00:15:14.440 ⇒ 00:15:30.890 Demilade Agboola: No, no, no, I do have, like, two follow-ups to that. First being, have you ever, like, used any, like, semantic layer tools, BI tools, so, like, Looker or Omni, where you kind of have to create those, your semantic layer within the tool as well, before you can build the dashboards?
107 00:15:32.030 ⇒ 00:15:34.980 Jasmin Multani: Yeah, like the drag and drop graphs?
108 00:15:35.210 ⇒ 00:15:42.930 Demilade Agboola: No, so, like, you know how, like, Looker has, like, LookML, where you kind of have to define a view, and then define, like.
109 00:15:43.690 ⇒ 00:15:55.160 Demilade Agboola: Each column within the view, and then do your joins across views, and say, hey, this is a many-to-one left join, or a one-to-one, you know, inner join, and all that stuff.
110 00:15:55.180 ⇒ 00:16:03.979 Demilade Agboola: So you kind of create, like, the kind of modeling that would happen in, say, dbt. You’re also kind of doing parts of that as well within Looker before you then start to visualize.
111 00:16:04.020 ⇒ 00:16:08.350 Demilade Agboola: stuff, so I’m just wondering if you’ve ever had to use tools like that.
112 00:16:09.080 ⇒ 00:16:15.609 Jasmin Multani: Yeah, I’d say the drag… there’s, like, a drag-and-drop version that’s UX-friendly. Okay.
113 00:16:15.730 ⇒ 00:16:21.650 Jasmin Multani: So I use that. I largely prefer building things out through SQL.
114 00:16:22.540 ⇒ 00:16:32.220 Jasmin Multani: left joins, the week-over-week degradations, or the formulas in SQL, and getting an understanding there, just because I, like, look at the raw data.
115 00:16:32.220 ⇒ 00:16:43.069 Jasmin Multani: And validating CTE by CTE, hey, is this funnel working the way I want it to work? And from there, I’ll start building out, the visuals.
116 00:16:45.580 ⇒ 00:16:46.500 Demilade Agboola: Yep.
117 00:16:46.500 ⇒ 00:16:52.419 Jasmin Multani: yeah, in terms of, like, visual tables, or visual, like, graphs, or things, but I have a huge…
118 00:16:53.600 ⇒ 00:16:56.070 Jasmin Multani: Preference for…
119 00:16:56.390 ⇒ 00:17:04.820 Jasmin Multani: making raw calculations in SQL, just so I can root cause things better. And I just get frustrated with the UX design.
120 00:17:05.089 ⇒ 00:17:06.059 Demilade Agboola: Fair enough, fair enough.
121 00:17:06.939 ⇒ 00:17:08.909 Demilade Agboola: I think…
122 00:17:09.449 ⇒ 00:17:18.439 Demilade Agboola: out of curiosity, I was just like… because it does appear you really like data to be used, like, productively, right? Like, you want them to be able to go towards a goal.
123 00:17:18.489 ⇒ 00:17:35.989 Demilade Agboola: And I actually like that. That’s a great thing, because, like, sometimes one of our biggest frustrations as well is people just want dashboards, and, you know, dashboards as a concept sounds nice, but, like, you need to be able to use it for something. If not, you just didn’t drive value, and you would find yourself churning, quote-unquote, from the dashboard.
124 00:17:36.059 ⇒ 00:17:42.049 Demilade Agboola: So I’m just curious as to, like, how would you… Number one…
125 00:17:43.189 ⇒ 00:17:53.479 Demilade Agboola: drive, like, if you were on a project, how would you come up with, like, a roadmap? Like, oh, this is what I want the client’s numbers to look like, and how would you be…
126 00:17:53.749 ⇒ 00:18:03.789 Demilade Agboola: how would you ensure that those numbers are useful to those clients, basically? How would you ensure that, like, you’re not just giving them… you had… this was your revenue last week, or last month?
127 00:18:04.520 ⇒ 00:18:18.789 Jasmin Multani: Yeah, sure thing. First off, I’d ask a series of questions, just to try to understand what the dashboard is intended to do. First things first, what kind of company is this? Is this e-commerce? Is this marketing?
128 00:18:19.960 ⇒ 00:18:33.620 Jasmin Multani: is this, like, a decision-making, platform, so on and so forth. From there, I would then ask, what is their most pressing, quarter goal? Are they focused on growth? Are they focused on,
129 00:18:34.020 ⇒ 00:18:40.600 Jasmin Multani: Staying lean and mean with their few markets, and driving deeper, dependency for their customers.
130 00:18:40.760 ⇒ 00:18:48.120 Jasmin Multani: And another thing I’d ask is how do these metrics talk to each other end-to-end across different,
131 00:18:48.540 ⇒ 00:18:53.540 Jasmin Multani: user segments, right? For something like e-commerce, you have a…
132 00:18:54.480 ⇒ 00:18:59.969 Jasmin Multani: let’s say, for some reason, Facebook Marketplace comes to us, right? And,
133 00:19:00.170 ⇒ 00:19:05.290 Jasmin Multani: It’s gonna be a double-sided, marketplace where we have to monitor both.
134 00:19:05.950 ⇒ 00:19:20.290 Jasmin Multani: the seller and the buyer’s habits for the overall metric to understand, hey, are we doing well in growth? And growth can be in terms of, like, net new customers who are paying, or net new customers who are buying.
135 00:19:20.790 ⇒ 00:19:28.940 Jasmin Multani: So, I’d want to ask, does the client care about one over the other, or do they want an end-to-end experience?
136 00:19:29.150 ⇒ 00:19:37.860 Jasmin Multani: From all those things gathered, I would then ask, okay, what is the customer currently tracking for? What are they experienced in?
137 00:19:37.860 ⇒ 00:19:50.150 Jasmin Multani: Do they understand retention? Do they understand, the value? Do they have a strategy for creating net new customers? Or do they have a strategy for
138 00:19:50.150 ⇒ 00:19:54.239 Jasmin Multani: Work with the existing customers and deepening their,
139 00:19:54.250 ⇒ 00:20:11.609 Jasmin Multani: wallet share. So just getting a baseline understanding of what, the customer’s doing today. And from there, have some sort of benchmarks ready to go, right? either industry-wide or company-wide with what’s, existing.
140 00:20:11.650 ⇒ 00:20:21.689 Jasmin Multani: There are some obvious industry-wide, metrics we just talked about, like, retention, CSAT,
141 00:20:22.450 ⇒ 00:20:41.289 Jasmin Multani: proactive detection rates, so on and so forth, and those… they have the same general themes, but I’d want to push back and ask the client, how are you guys calculating the numerator and denominator? Just to get a sense of where we are as a team, and making sure we’re speaking the same language.
142 00:20:41.370 ⇒ 00:20:46.800 Jasmin Multani: That’s some frustration I’ve had in the past, where people will talk about retention, and I’m like.
143 00:20:46.890 ⇒ 00:20:52.959 Jasmin Multani: we’re calculating this differently. So, just making it very obvious from there.
144 00:20:53.290 ⇒ 00:20:56.499 Jasmin Multani: Once those series of questions are asked,
145 00:20:56.790 ⇒ 00:21:02.339 Jasmin Multani: as a first stab, I would pick one or two, high-level metrics that C-suite cares about.
146 00:21:02.620 ⇒ 00:21:05.210 Jasmin Multani: And…
147 00:21:05.590 ⇒ 00:21:21.450 Jasmin Multani: have some supplemental metrics involved, right? So, if C-suite cares about order rate, day over day, like, orders made per day, that’s great, but if we have 500 orders made per day, but
148 00:21:21.650 ⇒ 00:21:38.540 Jasmin Multani: cancellation rate is sitting at, like, 50%, well, then we need to add those extra, supplemental values to get a sense of how we are working directionally, right? So I’d say those supplemental values are gonna be,
149 00:21:39.250 ⇒ 00:21:50.079 Jasmin Multani: contrast to the main metrics. So have your supplemental contrasting values, but also have your benchmarked metrics as well. So, for example.
150 00:21:50.360 ⇒ 00:21:57.950 Jasmin Multani: as New Verticals was building out, we saw that, CSAT was sitting at around 30%.
151 00:21:58.400 ⇒ 00:22:02.100 Jasmin Multani: Because restaurant side at that point was,
152 00:22:02.450 ⇒ 00:22:19.600 Jasmin Multani: sitting at around 80%, we had a clear benchmark value to say, hey, there’s an obvious gap, and there’s an obvious strategy that we can build, right? How do we get this 30% over to the 80% to be at par with our company-wide status?
153 00:22:19.790 ⇒ 00:22:26.220 Jasmin Multani: So that’s another really good way to draw strategy and draw a roadmap to say, hey.
154 00:22:26.600 ⇒ 00:22:30.190 Jasmin Multani: there is a gap, why… where is this gap coming in from?
155 00:22:30.500 ⇒ 00:22:39.870 Jasmin Multani: strategically. Is it coming in from a certain customer segment, a market, geographical market, or is it,
156 00:22:40.280 ⇒ 00:23:00.089 Jasmin Multani: being driven by a certain complaint. So in CSAT, we have certain inbounds, like missing and incorrect, my order was late, why did you cancel my order without telling me? And in practice, there are, like, there could be a hundred different inbound reasons, but in practice, what I’ve seen is…
157 00:23:00.310 ⇒ 00:23:08.989 Jasmin Multani: That there could be… out of those 100, there are only, like, 10 inbounds that contribute to 80% of…
158 00:23:09.080 ⇒ 00:23:22.800 Jasmin Multani: the fire. So, further, you know, separating those metrics out, that main metric, let’s say it’s CSAT for this, or order volume,
159 00:23:22.800 ⇒ 00:23:34.030 Jasmin Multani: Adding more qualitative information to show, hey, qualitatively, this is what’s contributing to this huge metric degradation, to build a story.
160 00:23:34.150 ⇒ 00:23:48.160 Jasmin Multani: And from there, we just do the obvious, right? Week-over-week trends to make sure, you know, where we start… if we started off at 30%, at the start of the month, have we begun closing the gap steadily towards, like, 40%, 50%.
161 00:23:48.160 ⇒ 00:23:57.139 Jasmin Multani: I’d say we should start off with an aggressive cut and say, we started off at 30% this month, I want to push us to 60%.
162 00:23:57.170 ⇒ 00:24:00.590 Jasmin Multani: What’s the one tool product,
163 00:24:01.440 ⇒ 00:24:04.890 Jasmin Multani: Product advice we can offer that can,
164 00:24:05.470 ⇒ 00:24:10.010 Jasmin Multani: That can be a lowest hanging fruit that saves a lot of money for our clients.
165 00:24:10.800 ⇒ 00:24:13.430 Demilade Agboola: That’s fair, that’s great, that’s all, like, that’s really great stuff.
166 00:24:13.540 ⇒ 00:24:19.389 Demilade Agboola: Honestly, I do find that sometimes, like, with clients and, again.
167 00:24:19.710 ⇒ 00:24:27.459 Demilade Agboola: because I do more AE work, so I’m handling a lot of transformations, but I do, like, sometimes I’m still in the meetings around, like,
168 00:24:27.920 ⇒ 00:24:38.459 Demilade Agboola: data strategy and data analysis, and I mean, technically, because of my experience, I’ve done stuff… I’ve been the first data hire for a startup before, so I basically did everything.
169 00:24:38.460 ⇒ 00:24:48.399 Demilade Agboola: And sometimes it can be really frustrating when everyone’s just all about the, oh, I have a dashboard, because a lot of people’s idea of data ends in the actual dashboard.
170 00:24:49.500 ⇒ 00:24:52.450 Demilade Agboola: And I think sometimes, out of just, like.
171 00:24:52.960 ⇒ 00:25:06.350 Demilade Agboola: And I also see sometimes when we… when we are… so this is, like, an internal pain point, sometimes we are pushing out dashboards because they are requested, and it just kind of feels like the meetings… instead of them being, like, data strategy meetings.
172 00:25:06.350 ⇒ 00:25:19.180 Demilade Agboola: They’re more of, like, status updates meetings, where it’s like, oh, we got this dashboard done, or we got that dashboard done, or we got that dashboard done, or we’ve updated this metric, which in and of itself is not bad, but it’s not the idea of
173 00:25:19.350 ⇒ 00:25:22.650 Demilade Agboola: an engagement, right? We want to be able to
174 00:25:23.300 ⇒ 00:25:29.030 Demilade Agboola: Ensure that we are proactive, and we are able to put our best foot forward and say, hey.
175 00:25:29.330 ⇒ 00:25:31.650 Demilade Agboola: Like, you asked for this dashboard.
176 00:25:32.030 ⇒ 00:25:42.810 Demilade Agboola: But not only are we giving you this dashboard, but then we are also giving you an analysis on this, right? Able to, like, show you the direction in which you should be thinking of, right? And so I think…
177 00:25:43.080 ⇒ 00:25:54.450 Demilade Agboola: Part, like, part of what you’ve said is just… we’ll take a meeting from just, like, hey, we’re just, you know, giving you feedback or updating you to, hey, you should consider this strategy.
178 00:25:55.220 ⇒ 00:26:08.459 Demilade Agboola: that strategy, and I feel like that’s very important, because a lot of times, it just… it just gets lost in this sauce, right? Everyone’s just focused on the numbers, or, like, a one-time analysis that we don’t necessarily go beyond that, right?
179 00:26:08.820 ⇒ 00:26:13.070 Jasmin Multani: Yeah, and the truth is, like, really good product builds could take
180 00:26:13.670 ⇒ 00:26:27.510 Jasmin Multani: two to three quarters to build. But if you want to get that first version, I’m sure you can get that in two months, but after that, it’s just, like, making sure it’s working end-to-end, which requires a lot of fine-tuning, a lot of, like.
181 00:26:27.680 ⇒ 00:26:36.299 Jasmin Multani: Because every time you build a new product, you’re also creating net new problems, and capturing those problems. And, yeah, I’m really curious to see how you guys
182 00:26:36.700 ⇒ 00:26:47.509 Jasmin Multani: Are able to extend your billing schedule, when you’re trying to honestly give good recommendations to the clients without making them feel like
183 00:26:47.970 ⇒ 00:26:50.000 Jasmin Multani: We’re just nickel and diming them.
184 00:26:50.400 ⇒ 00:26:54.459 Demilade Agboola: Yeah, so part of it is we are…
185 00:26:55.910 ⇒ 00:27:01.880 Demilade Agboola: we… like, again, that’s part of the roadmap, right? And so I think part of that would also come back to, like.
186 00:27:01.990 ⇒ 00:27:06.990 Demilade Agboola: the analyst on the team, and being able to, like, not just say, hey, I’m good at, like.
187 00:27:07.170 ⇒ 00:27:19.109 Demilade Agboola: potentially, you know, Tableau or whatever tool, but I’m also, like, strategic in how I think about it. So yeah, we might have an SOW when the project started, where we’re like, oh.
188 00:27:19.580 ⇒ 00:27:23.510 Demilade Agboola: you know, our data warehouse is a mess. We have no idea what our
189 00:27:23.730 ⇒ 00:27:35.980 Demilade Agboola: retention values or revenue values really are, which some people really have no idea what their revenue is. Like, they have an idea, but they don’t have, like, a nailed-on number. Their warehouses or their data is such a mess.
190 00:27:36.070 ⇒ 00:27:52.859 Demilade Agboola: So we come in and we say, okay, gotcha, we’ve cleaned your warehouse, now the cadence is every 12 hours, you get fresh data, we’ve built out your dashboards, and now, you know, you have dashboards showing your revenue, which… that’s cool.
191 00:27:53.230 ⇒ 00:27:57.079 Demilade Agboola: I think the question would be, how would you then, like.
192 00:27:57.260 ⇒ 00:28:07.080 Demilade Agboola: convert that from just that 3-month project to, say, like, another 3 months. So, usually, what we in-house will do would rely on strategy, and being able to say, hey.
193 00:28:07.540 ⇒ 00:28:11.509 Demilade Agboola: We have done this for you, but in the process of doing this.
194 00:28:11.660 ⇒ 00:28:14.260 Demilade Agboola: We can also still do more of this.
195 00:28:14.530 ⇒ 00:28:15.730 Jasmin Multani: Right.
196 00:28:16.080 ⇒ 00:28:25.819 Demilade Agboola: Being able to show them that roadmap and say, hey, if we’ve done this in 3 months, just imagine what we could do in 6 or 7, like, 9 months, right?
197 00:28:26.160 ⇒ 00:28:28.310 Demilade Agboola: And I guess that’s the…
198 00:28:30.340 ⇒ 00:28:34.120 Demilade Agboola: That’s kind of, like, my question to you in the sense of, like,
199 00:28:34.670 ⇒ 00:28:39.910 Demilade Agboola: How would you, like, take wins, and just be able to think of it in, like.
200 00:28:41.390 ⇒ 00:28:57.260 Demilade Agboola: an expansion, you know? I know you talked about it in a bit, like, with the whole, like, oh, putting supplementary metrics and all of that, but, like, in terms of, like, being able to show from a business, and so not just, like, for instance, you might be working on revenue.
201 00:28:57.650 ⇒ 00:29:12.399 Demilade Agboola: But, like, being able to tie things together, being able to say, hey, I’m working revenue, but here’s how marketing ties into that, or here’s how, like, just a business, full business feeling, being able to say, hey, this is what, like, the roadmap looks like.
202 00:29:12.400 ⇒ 00:29:25.900 Demilade Agboola: We might have started from revenue, but we’re looking at retention next, and we’re looking at, marketing and ads next, and what other strategies can we look at? And maybe we should try this, and we should try that, and then, you know, see how that works out for the business.
203 00:29:26.990 ⇒ 00:29:29.290 Jasmin Multani: Yeah, so, I’d say…
204 00:29:29.510 ⇒ 00:29:37.339 Jasmin Multani: So, good question. You’re asking, basically, how do I convert a 3-month plan into a 6-month plan, right?
205 00:29:37.510 ⇒ 00:29:42.849 Demilade Agboola: Yeah, or potentially even longer, but, like, how would, like, what does that look like in terms of,
206 00:29:43.190 ⇒ 00:29:52.759 Demilade Agboola: an analysis roadmap, if that makes any sense. Like, how would you take a startup, let’s just say a startup, that is just starting in their data journey.
207 00:29:53.000 ⇒ 00:29:54.559 Demilade Agboola: And what would you…
208 00:29:54.710 ⇒ 00:30:12.699 Demilade Agboola: want to show them that they could potentially do. So let’s take an e-com, for instance. So they’re just starting up, they’re getting some data. We’ve built out… we’ve built out the initial dashboards in the, say, 3-month period. So, you know, the basics, daily active users,
209 00:30:12.770 ⇒ 00:30:28.300 Demilade Agboola: order volume, things like that. How would we then go from, like, that to saying, hey, we should keep… like, we would like to, you know, build on that in the next, like, 6 months, and what ideas would you have? How would you like to slice and splice the data, basically?
210 00:30:29.730 ⇒ 00:30:39.170 Jasmin Multani: I feel like if it’s a startup, then my gut tells me is that they are under-resourced in people, and
211 00:30:40.050 ⇒ 00:30:48.430 Jasmin Multani: they have to be very cutthroat about their priority list, right? There are only so many people, and they need to build fast, especially in those early days.
212 00:30:48.610 ⇒ 00:30:57.710 Jasmin Multani: So, where I would advise we come in is build a roadmap that, cuts their metrics by…
213 00:30:58.510 ⇒ 00:31:00.340 Jasmin Multani: background operations.
214 00:31:00.600 ⇒ 00:31:01.600 Jasmin Multani: Right?
215 00:31:02.030 ⇒ 00:31:20.279 Jasmin Multani: you want to have a sticky relationship between the customer and, let’s say, the app or the product, from the get-go, from the first, first, like, 2 or 3 experiences. So my argument would be, how do we make that a reliable relationship between the app and the customer first?
216 00:31:20.510 ⇒ 00:31:28.610 Jasmin Multani: I would… Stress test the app first, and get some sort of,
217 00:31:28.730 ⇒ 00:31:43.200 Jasmin Multani: storytelling going, and saying, hey, when I experience the app, this is what I’m experiencing, this is what I’m experiencing as a user, this is my misconception. I’d write that down. I’d then go forward and do some, customer…
218 00:31:44.030 ⇒ 00:31:52.550 Jasmin Multani: customer interviews to see if they’re also having the same experiences, or if they’re having net new experiences that I didn’t catch.
219 00:31:52.720 ⇒ 00:31:53.800 Jasmin Multani: From there.
220 00:31:54.030 ⇒ 00:32:04.979 Jasmin Multani: I would marry the nitty-gritty ground operations with the metrics involved itself, right? So, let’s say that I have a bad experience with,
221 00:32:05.760 ⇒ 00:32:13.720 Jasmin Multani: Getting to the next page, or being able to explore, the webpage to, add to… easily add to cart.
222 00:32:13.870 ⇒ 00:32:33.050 Jasmin Multani: Let’s say that’s, that’s my experience, then I would say, and that’s been validated by, like, a few other customers, I would say, hey, this is your biggest priority that’s, preventing, revenue. From there, I would take that as a hunch and marry it with the actual metrics that are involved.
223 00:32:33.380 ⇒ 00:32:40.399 Jasmin Multani: So I would then create some sort of user funnel and say, hey, users are playing around with a lot of,
224 00:32:40.690 ⇒ 00:32:48.650 Jasmin Multani: items that they click through, but they’re… this… there’s an obvious drop to add to cart rate. And that’s not because they’re not a…
225 00:32:49.510 ⇒ 00:32:55.080 Jasmin Multani: attracted to the product. From there, we start hypothesis building.
226 00:32:55.720 ⇒ 00:33:00.430 Jasmin Multani: to drive the gap, right? We start understanding, like, hey, is this because…
227 00:33:00.820 ⇒ 00:33:08.529 Jasmin Multani: The customer doesn’t like the product, or is it because they just can’t find a reasonable spot for them to actually add to cart?
228 00:33:08.650 ⇒ 00:33:14.990 Jasmin Multani: Or maybe there’s, like, a weird bug that’s preventing them from adding to cart. So from there, I would…
229 00:33:15.610 ⇒ 00:33:20.739 Jasmin Multani: Get the ground research, marry it with the metrics, and start ranking the hypothesis.
230 00:33:21.130 ⇒ 00:33:35.710 Jasmin Multani: hypotheses based off of, like, what’s most realistic in terms of building, within a week, two months, or six months, and have that priority list in terms of build, but also have a projection, and forecasting
231 00:33:35.860 ⇒ 00:33:42.990 Jasmin Multani: rank of, hey, if you solve this, this is how much money you’ll actually be able to save and generate.
232 00:33:43.230 ⇒ 00:33:44.460 Jasmin Multani: From there.
233 00:33:45.720 ⇒ 00:34:01.270 Jasmin Multani: start off with the easier builds, and say, hey, because we were able to build this thing out, and solve this hypothesis, we were A able to build it within the rational, time period that we promised, and hey.
234 00:34:01.330 ⇒ 00:34:19.370 Jasmin Multani: given, our forecast, did we fall above or below, our forecasting? And I think that’s where we have to be a bit more honest, and not try to upsell. We do want to have honesty with our clients and say… and admit when we’re,
235 00:34:19.570 ⇒ 00:34:35.960 Jasmin Multani: underperforming or overperforming in our forecasting. That’s also a really good litmus test as to, like, does the client trust us to, walk back on certain decisions? Or say, hey, you know, interestingly enough, we actually…
236 00:34:36.380 ⇒ 00:34:39.600 Jasmin Multani: Initially thought we were gonna get more money out of this, but we…
237 00:34:39.860 ⇒ 00:34:50.479 Jasmin Multani: Ended up getting less money out of this, but this led to these other insights, that, if built, will keep us back on track.
238 00:34:51.659 ⇒ 00:34:58.280 Jasmin Multani: So, I’d say, yeah, roadmap depends on hypothesis building and resource allocation.
239 00:34:59.500 ⇒ 00:35:05.610 Demilade Agboola: I agree, like, that makes a lot of sense, and I totally agree, like, The… the heart of being…
240 00:35:06.020 ⇒ 00:35:13.369 Demilade Agboola: sometimes I do talk to people who are starting in the field, and I’m like, at the heart of data is hypothesis building, and, like.
241 00:35:13.500 ⇒ 00:35:21.960 Demilade Agboola: If you could be great with all the tools in the world, but if you can’t consist anything of, you know, hypothesis and how to, like,
242 00:35:23.550 ⇒ 00:35:39.349 Demilade Agboola: think of, like, think of the effect of things on things. Like, you’re just going to constantly end up just being a dashboard builder, which is still a good thing, but you will… you will… the higher echelon is people who can do that, plus also think of, like.
243 00:35:39.470 ⇒ 00:35:42.210 Demilade Agboola: The hypothesis that backs up whatever they’re doing.
244 00:35:44.140 ⇒ 00:35:53.969 Demilade Agboola: I do have a question about, like, how you interact with a stakeholder. So, say, for instance, you want to build out a dashboard for something, and, like, you know.
245 00:35:55.240 ⇒ 00:36:07.670 Demilade Agboola: say me, for instance, I’m the engineer on duty, and I haven’t been able to fully build out the pipeline, but they kind of wanted, how do you manage, like, stakeholder expectations where, like, yo, this hasn’t been built yet.
246 00:36:09.220 ⇒ 00:36:15.720 Demilade Agboola: I know you want it, you’re really asking for it, but, like, I don’t… I don’t yet have the data, like, how do you, like…
247 00:36:15.940 ⇒ 00:36:20.569 Demilade Agboola: Merge all of that in terms of relating with the internal team that you need it from.
248 00:36:20.680 ⇒ 00:36:25.960 Demilade Agboola: As well as also relating with the stakeholder that you’re trying to meet the, you know, deadline for.
249 00:36:26.880 ⇒ 00:36:40.679 Jasmin Multani: Yeah, so first things first is, ahead of those meetings, I would want to sync with the internal stakeholder, the internal data engineer directly, and just get our ducks in order, and have our storyline aligned.
250 00:36:40.700 ⇒ 00:36:52.849 Jasmin Multani: So I first asked, like, hey, is this data pipeline ready to go? What are the limits? What are… what are the issues that are unfolding? And realistically.
251 00:36:53.130 ⇒ 00:37:02.500 Jasmin Multani: I feel like data can be, like, pulling a string out of the gutter. The more you pull it, the more you realize, oh, this is really bad. There’s all these other extra fixes we have to make.
252 00:37:02.790 ⇒ 00:37:04.050 Jasmin Multani: So…
253 00:37:04.470 ⇒ 00:37:17.709 Jasmin Multani: I would level set my expectations there, and be highly in sync with the data engineer, maybe with, like, a daily sync, to see what’s going on in terms of progress, and from there, try to understand
254 00:37:18.100 ⇒ 00:37:20.560 Jasmin Multani: At what point are we off track?
255 00:37:20.900 ⇒ 00:37:22.289 Jasmin Multani: On our roadmap.
256 00:37:22.410 ⇒ 00:37:37.500 Jasmin Multani: If we are off track on our roadmap, do we have a clear answer why? And is it something that’s realistically going to be built, in-house, or is this going to require more resources, like buying a new software, or…
257 00:37:38.360 ⇒ 00:37:48.479 Jasmin Multani: Having more, having a specific API built with the client themselves to get direct data from them.
258 00:37:49.040 ⇒ 00:37:58.749 Jasmin Multani: From there, if I understand the resources, now, for every no or pushback on the roadmap timeline, I’m gonna have to go to the client with an alternative plan.
259 00:37:59.020 ⇒ 00:38:08.700 Jasmin Multani: So I would collaborate with the data engineer and ask, hey, because this isn’t built, what… how can the client,
260 00:38:09.790 ⇒ 00:38:15.590 Jasmin Multani: Use data today until we get this entire pipeline ready to go.
261 00:38:17.350 ⇒ 00:38:37.040 Jasmin Multani: I understand that, like, things happen, but in order to retain trust with the client, we still have to make sure that they’re not flying blind for all these other months. So, can we work with partial data? Is there some sort of data cleaning that we can do, in the interim while the pipelines get, fully set up?
262 00:38:39.120 ⇒ 00:38:55.779 Jasmin Multani: And from there, also caveat, hey, in this interim period, this data’s not perfect, but we… it is good enough for us to make certain decisions based off of XYZ things, and relay that information over to the client. So,
263 00:38:56.200 ⇒ 00:39:04.379 Jasmin Multani: In terms of, like, internal stakeholder relationships, we have to be in sync, like, Maybe an hour-by-hour, basis.
264 00:39:04.430 ⇒ 00:39:23.199 Jasmin Multani: like, top of day and end of day, and then have an understanding, not to be, like, micromanaging, but to make sure that our, expectations… we’re telling the same story. And from there, I don’t know how often… I’d say maybe we’re meeting with the clients,
265 00:39:23.610 ⇒ 00:39:24.870 Jasmin Multani: Once a week.
266 00:39:25.290 ⇒ 00:39:30.919 Jasmin Multani: And, having a dock ready for us to go internally to say, hey.
267 00:39:31.370 ⇒ 00:39:40.509 Jasmin Multani: This is how the picture is being painted. These are the subsequent queries that the client could use, as we automate this pipeline out.
268 00:39:41.470 ⇒ 00:39:42.340 Demilade Agboola: Okay.
269 00:39:42.500 ⇒ 00:39:44.030 Demilade Agboola: That’s great, like,
270 00:39:44.330 ⇒ 00:39:50.149 Demilade Agboola: I feel like that’s very important, and yeah, you’re right, like, theater is really like pulling a string from a gutter sometimes.
271 00:39:50.270 ⇒ 00:40:05.689 Demilade Agboola: it’s… it’s easy, but sometimes the string just keeps going on and on and on and on, and it definitely goes over. Just out of curiosity, do you have any questions about any pain points, that we have, or anything about the internal flow of things?
272 00:40:06.410 ⇒ 00:40:08.650 Jasmin Multani: Yeah, so I’d want to ask,
273 00:40:09.360 ⇒ 00:40:13.339 Jasmin Multani: A couple questions, like, first, how did you get introduced to Brainforge?
274 00:40:14.160 ⇒ 00:40:25.080 Demilade Agboola: So personally, I used to work in a former data consulting that I mentioned, was called Data Culture, or it is called Data Culture, and I had a manager there,
275 00:40:25.360 ⇒ 00:40:38.279 Demilade Agboola: And basically, he introduced me to Otam sometime earlier this year, and he’s just like… because Otam was looking out for engineers, and he’s like, oh, I have an engineer I’ve worked with that is pretty good. And so, that was kind of the…
276 00:40:38.480 ⇒ 00:40:42.409 Demilade Agboola: meet, started talking to Otam, had an interview with the team.
277 00:40:42.840 ⇒ 00:40:49.559 Demilade Agboola: And they were like, yeah, this seems like a pretty good fit, and so I joined in March of this year, and I’ve been here, you know, since then.
278 00:40:49.560 ⇒ 00:41:03.729 Jasmin Multani: Nice. Nice, nice, nice. Yeah, I really appreciate how them and Robert are very relationship-focused when they’re supporting their team. I think reputation goes a long way, so I appreciate they also feel the same way.
279 00:41:04.080 ⇒ 00:41:12.709 Jasmin Multani: Follow-up question, so, what do you know about the possible role that I’d be entering, and how do you expect the both of us to be working?
280 00:41:13.670 ⇒ 00:41:20.880 Demilade Agboola: So the possible role, it would be as an analyst on the team, but in a way.
281 00:41:20.970 ⇒ 00:41:39.819 Demilade Agboola: I would say, like, a senior perspective of things, so it’s not like a, hey, we just need a dashboard sort of thing, here’s a dashboard, can we get it out by next week? It’s more of a strategic thinking. It’s more of, like, hey, I’m gonna be sending, you know, bi-weekly
282 00:41:40.000 ⇒ 00:41:42.319 Demilade Agboola: C-suite updates, where it’s like.
283 00:41:42.460 ⇒ 00:41:55.649 Demilade Agboola: this is the pro… and again, since we don’t really care about, oh, I built out the dashboard, per se, you know, I built out these… these are the num… these are the dashboards and links to dashboards. No, it’s more of a, hey, this is… this is what we did.
284 00:41:55.650 ⇒ 00:42:06.660 Demilade Agboola: This is the business impact, and this is potentially what the roadmap looks like for the next 2 weeks, or the next 3 months… 3 weeks, or 4 weeks, whatever timeframe you believe that to be.
285 00:42:06.670 ⇒ 00:42:15.800 Demilade Agboola: So I guess that’s the mindset that that role will entail. So it’s kind of… it’s not just, like, the tools. Tools are cool, but, like.
286 00:42:15.950 ⇒ 00:42:19.270 Demilade Agboola: The strategic thinking is also a very huge part of that.
287 00:42:19.990 ⇒ 00:42:24.769 Demilade Agboola: And in terms of how we would work, it would, again, kind of, like, the roadmap.
288 00:42:24.950 ⇒ 00:42:35.829 Demilade Agboola: will tie into, like, my modeling goals. So it’s like, oh, I need to build out these models, I need to get that source data source to you, and then model it, so you can then have a dashboard off of that.
289 00:42:36.030 ⇒ 00:42:39.370 Demilade Agboola: Into, like, what they need for their strategy.
290 00:42:39.930 ⇒ 00:42:40.540 Jasmin Multani: Okay.
291 00:42:40.680 ⇒ 00:42:52.450 Jasmin Multani: Interesting. Just to, like, dig deeper into the modeling, so what’s an example of, like, a model that you created for a client at Brainforge that got you really excited?
292 00:42:54.350 ⇒ 00:43:00.110 Demilade Agboola: I mean, they all get me excited, that’s why I do what they do. But, like, just generally speaking, I…
293 00:43:00.660 ⇒ 00:43:06.109 Demilade Agboola: I do build models for, like, different things, so, like, in some cases, it’s…
294 00:43:06.310 ⇒ 00:43:12.290 Demilade Agboola: Revenue, in some cases, it’s attribution, in some cases, it’s,
295 00:43:13.490 ⇒ 00:43:29.320 Demilade Agboola: it’s, like, the customer profile, and I guess for me, it’s just… there’s just a lot of things that I have done. I will say stuff around, like, customer segmentation, and being able to classify customers into, like, what they do, like, how they spend money, like, so an RFM analysis, or just, like.
296 00:43:29.320 ⇒ 00:43:29.860 Jasmin Multani: Yep.
297 00:43:29.860 ⇒ 00:43:39.400 Demilade Agboola: those kind of things would be stuff I enjoy, or, like, I find exciting, because, like, in the way in which you’re building out the model, you can kind of see
298 00:43:39.920 ⇒ 00:43:47.530 Demilade Agboola: the utility of it. Sometimes it… what you model requires the analysts to come together and piece things together.
299 00:43:47.530 ⇒ 00:43:47.890 Jasmin Multani: That’s right, yeah.
300 00:43:47.890 ⇒ 00:43:55.170 Demilade Agboola: I have everything, like, you know, aggregated daily revenue by whatever customer, whatever, you know.
301 00:43:55.310 ⇒ 00:43:57.490 Demilade Agboola: Dashboards you might be powering.
302 00:43:57.640 ⇒ 00:44:02.599 Demilade Agboola: But, like, when you are doing some of the, like, heavy business logic, it’s also pretty cool, so…
303 00:44:02.600 ⇒ 00:44:06.750 Jasmin Multani: Okay, so a lot of, like, user segmentation, and…
304 00:44:07.090 ⇒ 00:44:11.909 Jasmin Multani: I’m trying to… that comes down to the client and what they want their segmentation to look like.
305 00:44:12.080 ⇒ 00:44:22.589 Demilade Agboola: Exactly, and some people have different, like, focuses, so we have, like, a pharmaceutical company that we consult for. They really care about ops and SLAs, so they…
306 00:44:23.060 ⇒ 00:44:31.570 Demilade Agboola: very… they care about, like, things being shipped within two to three business days. They care, like… so, for them, those are, like… they literally… they literally have deals with
307 00:44:31.740 ⇒ 00:44:39.459 Demilade Agboola: Partners that they cannot breach, or, like, you know, that they’re trying to hold up. And so, being able to, like, let them know
308 00:44:39.760 ⇒ 00:44:45.380 Demilade Agboola: that, yeah, it’s been over 3 business days, and this order hasn’t shipped. Those kind of things are really important to them.
309 00:44:45.600 ⇒ 00:44:52.840 Demilade Agboola: So yeah, different clients would have different needs, and the idea is always being flexible to meet them at their point of need.
310 00:44:53.730 ⇒ 00:44:54.870 Jasmin Multani: Okay, okay.
311 00:44:55.110 ⇒ 00:45:00.639 Jasmin Multani: Alright, sounds good. Thank you so much for chatting, I know we’re at time, and I don’t…
312 00:45:00.870 ⇒ 00:45:13.169 Jasmin Multani: I mean to, like, end this abruptly, but I do have a… I think we both have a hard stop. I think next steps for me will be, chatting with Robert to try to figure out, like, what expectations are.
313 00:45:13.290 ⇒ 00:45:15.300 Jasmin Multani: And what role fit would look like.
314 00:45:15.620 ⇒ 00:45:16.250 Demilade Agboola: Yeah.
315 00:45:16.490 ⇒ 00:45:21.470 Demilade Agboola: Yeah, definitely. I will also talk to the team internally and just, you know, convey my…
316 00:45:21.710 ⇒ 00:45:27.370 Demilade Agboola: So I think you’re a great fit, and it will be nice to see what the team
317 00:45:27.660 ⇒ 00:45:30.759 Demilade Agboola: Also feels, like, internally, as we discussed this as well.
318 00:45:31.660 ⇒ 00:45:37.160 Jasmin Multani: Yeah, because I know Robert as well over the years, and now Hannah as well, like.
319 00:45:37.480 ⇒ 00:45:46.289 Jasmin Multani: I just really prioritize relationships over everything, so I just want to make sure I am a strong fit, and then I’m not wasting anyone’s time or resources.
320 00:45:46.950 ⇒ 00:45:54.239 Demilade Agboola: Definitely, definitely. But yeah, it was great talking, it was great talking to you, Jasmine. Hopefully, soon sometime.
321 00:45:54.740 ⇒ 00:45:56.080 Jasmin Multani: Of course, yeah.
322 00:45:56.320 ⇒ 00:45:58.060 Demilade Agboola: Alright then, take care of yourself.
323 00:45:58.060 ⇒ 00:45:59.890 Jasmin Multani: Take care! Bye!
324 00:45:59.890 ⇒ 00:46:00.540 Demilade Agboola: Bye.