Meeting Title: Brainforge Messaging and Branding Discussion Date: 2026-01-12 Meeting participants: Robert Tseng, Luke Scorziell, Luke’s Notetaker
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1 00:00:43.940 ⇒ 00:00:44.819 Luke Scorziell: Hey, Robert.
2 00:00:46.140 ⇒ 00:00:46.750 Robert Tseng: Hey, Luke.
3 00:00:48.650 ⇒ 00:00:50.249 Luke Scorziell: How you doing?
4 00:00:51.010 ⇒ 00:00:52.049 Robert Tseng: Good, how are you?
5 00:00:52.700 ⇒ 00:00:53.410 Luke Scorziell: Good.
6 00:00:53.850 ⇒ 00:00:57.130 Luke Scorziell: Gotta start week two.
7 00:00:58.220 ⇒ 00:00:58.920 Robert Tseng: Nice.
8 00:00:59.250 ⇒ 00:01:01.240 Luke Scorziell: Oh, jumping in full force.
9 00:01:01.610 ⇒ 00:01:02.290 Robert Tseng: Yeah.
10 00:01:02.810 ⇒ 00:01:05.630 Robert Tseng: Do you get my messages about my LA trip?
11 00:01:06.300 ⇒ 00:01:07.270 Luke Scorziell: Yeah, yeah, yeah.
12 00:01:07.600 ⇒ 00:01:08.110 Robert Tseng: Cool.
13 00:01:08.110 ⇒ 00:01:08.549 Luke Scorziell: That’s why I’.
14 00:01:08.550 ⇒ 00:01:09.730 Robert Tseng: Yeah, make sure you saw it.
15 00:01:10.050 ⇒ 00:01:14.500 Robert Tseng: Are you gonna be available then? Like, are you gonna be out of town? Because that would be a bummer, but it’ll be…
16 00:01:15.560 ⇒ 00:01:20.370 Luke Scorziell: No, I should be… I should be in town Thursday and Friday, for sure.
17 00:01:20.380 ⇒ 00:01:22.409 Robert Tseng: Okay. Hannah has.
18 00:01:24.010 ⇒ 00:01:26.730 Luke Scorziell: It’s like a conference for,
19 00:01:27.820 ⇒ 00:01:31.459 Luke Scorziell: it’s called January Jumpstart, and they do, like, manuscript study.
20 00:01:31.670 ⇒ 00:01:33.100 Luke Scorziell: To start off the year.
21 00:01:33.980 ⇒ 00:01:38.209 Luke Scorziell: So her parents are coming down on Saturday and Sunday, and they want me to…
22 00:01:38.400 ⇒ 00:01:41.089 Luke Scorziell: Potentially help with the cooking team, so…
23 00:01:41.090 ⇒ 00:01:41.820 Robert Tseng: Yeah.
24 00:01:43.130 ⇒ 00:01:48.330 Luke Scorziell: So we’ll see, but I should be definitely around Thursday, Friday, and if you want to grab dinner or something.
25 00:01:50.000 ⇒ 00:01:59.040 Robert Tseng: Yeah, yeah, well, I mean, we’ll think… we’re thinking we’re gonna do some co-working, Thursday, Friday. Yeah, weekends and stuff is off, you know, whatever, so again, I’m not… no… no worries on that.
26 00:01:59.580 ⇒ 00:02:01.969 Luke Scorziell: I mean, yeah, it should be. I should.
27 00:02:02.200 ⇒ 00:02:06.849 Robert Tseng: I’ll be there, like, Thursday noon to, like, Monday evening, is basically what I’ve…
28 00:02:07.140 ⇒ 00:02:13.489 Robert Tseng: mapped out. I wanna, yeah, I think by that point, it’ll be your one month full-time check-in. So, definitely want to spend some time with you.
29 00:02:13.850 ⇒ 00:02:14.880 Robert Tseng: Got it.
30 00:02:15.220 ⇒ 00:02:26.619 Robert Tseng: And, you know, basically anything else we can kind of get through in person would probably be helpful, rather than just having these, like, chunks of 30 minutes, you know, every now and then, so… Yeah.
31 00:02:26.910 ⇒ 00:02:27.710 Robert Tseng: Yeah.
32 00:02:28.450 ⇒ 00:02:31.060 Luke Scorziell: Wait, are you just coming out for,
33 00:02:31.320 ⇒ 00:02:34.800 Luke Scorziell: Just because, or did you… what’s… anything happening out here?
34 00:02:35.030 ⇒ 00:02:48.429 Robert Tseng: No. I mean, mostly work, yeah. I feel like, just timing it with your month, plus Amber and Hannah’s almost one year. Amber’s one year, Hannah’s a little less. And then, since we’re interviewing.
35 00:02:48.760 ⇒ 00:02:58.569 Robert Tseng: a couple other people, that are in LA that are pretty close to, like, the finish line, like, I also want to see if we’re gonna… if we can close them there, so…
36 00:02:58.700 ⇒ 00:03:03.440 Robert Tseng: Yeah, I usually try to come to LA at least once a quarter, so…
37 00:03:03.630 ⇒ 00:03:11.199 Robert Tseng: Yeah, I’d like to do another happy hour, just kind of continue to keep connections warm and meet new people, and then…
38 00:03:11.330 ⇒ 00:03:17.430 Robert Tseng: yeah, I guess that’s… weekend stuff, like, I’ll… I’ll probably see my friends, but, that’s… that’s,
39 00:03:17.730 ⇒ 00:03:19.149 Robert Tseng: Yeah, that’s it.
40 00:03:19.150 ⇒ 00:03:22.010 Luke Scorziell: Yeah, nice. So… Yeah.
41 00:03:22.290 ⇒ 00:03:24.950 Luke Scorziell: Yeah, well, that’ll be exciting. So…
42 00:03:25.400 ⇒ 00:03:27.330 Luke Scorziell: Yeah, I don’t know, I’m still, like, I’m…
43 00:03:27.710 ⇒ 00:03:30.960 Luke Scorziell: Still just hyped, like, I was on the call with you, Tom, and it was fun.
44 00:03:31.090 ⇒ 00:03:33.540 Robert Tseng: Yeah, the contextual call? Nice.
45 00:03:33.540 ⇒ 00:03:35.089 Luke Scorziell: Yeah, and then I spent, like.
46 00:03:35.650 ⇒ 00:03:42.439 Luke Scorziell: I don’t know, I just kind of lost myself in that, like, stuff on Friday. I was just going down the rabbit hole.
47 00:03:42.440 ⇒ 00:03:55.970 Robert Tseng: Yeah, yeah, no, I mean, I haven’t even fully sat through and read everything you put out, but yeah, I mean, you know, reorient me, like, what do you… what do you need my attention on, kind of today? How can I be helpful for today?
48 00:03:56.140 ⇒ 00:04:00.889 Luke Scorziell: Yeah, yeah, well, one, too, I was thinking, like, I don’t know if you’d want to make
49 00:04:01.460 ⇒ 00:04:04.920 Luke Scorziell: Prayer, like, or even just, like, praying to open.
50 00:04:05.320 ⇒ 00:04:07.040 Luke Scorziell: Yeah.
51 00:04:07.040 ⇒ 00:04:08.189 Robert Tseng: Yeah, let’s do that.
52 00:04:09.430 ⇒ 00:04:13.619 Luke Scorziell: Yeah, it doesn’t have to be crazy. And then, yeah, I was just thinking about that, and then I have some ideas.
53 00:04:13.750 ⇒ 00:04:15.220 Robert Tseng: Okay, cool.
54 00:04:15.590 ⇒ 00:04:18.089 Luke Scorziell: But, yeah, I can… I can start. Yep.
55 00:04:23.210 ⇒ 00:04:35.280 Luke Scorziell: Yeah, my father, just, thank you so much, just for a new week, a new day to get to, yeah, serve you and see just how you’re moving, in Robert’s life and my life, Lord, and just through Brainforge, and…
56 00:04:36.680 ⇒ 00:04:43.799 Luke Scorziell: Yeah, God, would you just, guide us to the topics and areas that, yeah, would be most productive for us to discuss, Lord, and…
57 00:04:44.120 ⇒ 00:04:50.490 Luke Scorziell: Most honoring to you, and yeah, just pray for your favor and blessing just as we enter into this,
58 00:04:51.400 ⇒ 00:04:55.929 Luke Scorziell: Yeah, just new season, on the go-to-market team, Lord, and
59 00:04:56.140 ⇒ 00:04:59.989 Luke Scorziell: yeah, just pray for your guidance, and your blessing, Lord. So, thank you, and…
60 00:05:00.220 ⇒ 00:05:03.270 Luke Scorziell: Yeah, just lift those things up to you in Jesus’ name. Amen.
61 00:05:06.820 ⇒ 00:05:11.810 Robert Tseng: The Holy Father, Lord, just thank you for, yeah, start your new week.
62 00:05:11.930 ⇒ 00:05:18.470 Robert Tseng: yeah, I’ve started a lot of new things. For me, it’s my first day back in school, in the new semester, and…
63 00:05:18.630 ⇒ 00:05:25.160 Robert Tseng: Yeah, it just feels like a lot of things are kind of coming back on after… after the holidays. Spray over the…
64 00:05:25.540 ⇒ 00:05:40.810 Robert Tseng: all the circle back messages, just trying to get people’s attention after the holidays, old clients, old… old leads, friends, whoever it is, Laura, it feels like this is a pretty open season right now. People are eager to…
65 00:05:40.870 ⇒ 00:05:51.989 Robert Tseng: Are more open to meet people and be interrupted as people are starting to figure out what their routines will look like. And so, just pray for
66 00:05:52.170 ⇒ 00:05:59.870 Robert Tseng: Yeah, just your, just the spirit of openness, as we get to…
67 00:06:00.150 ⇒ 00:06:14.899 Robert Tseng: yeah, just jump on a lot of… a lot of calls and meet new people at… whether this event that I… that’s just kind of down the street from me, or, different calls that you have booked for us, later… later this week. Yeah, would we…
68 00:06:14.900 ⇒ 00:06:20.200 Robert Tseng: Yeah, really just have an eye for just how we can help and serve,
69 00:06:21.280 ⇒ 00:06:32.220 Robert Tseng: the people that we talk to, and a way to just inspire the team and help them to articulate, just the… what they do. So, yeah, Lord, we just thank you and pray this in Jesus’ name. Amen.
70 00:06:32.990 ⇒ 00:06:33.760 Luke Scorziell: Amen.
71 00:06:35.310 ⇒ 00:06:37.290 Luke Scorziell: Sweet,
72 00:06:37.880 ⇒ 00:06:43.110 Luke Scorziell: So, Elsa, you mentioned your… you guys are thinking of moving to Asia in a couple years? Is that, like, missions related?
73 00:06:43.380 ⇒ 00:06:54.989 Robert Tseng: Yeah, I think, I mean, missions, also, just Rachel wants to be closer to family when she has kids, so, but yeah, I mean, I…
74 00:06:55.800 ⇒ 00:07:08.579 Robert Tseng: I would… I’m open to being in Asia. I never really thought I would stay in the States my entire life, so… I may not be a long-term thing, but, at least for medium-term, I could see us moving there for a few years.
75 00:07:08.900 ⇒ 00:07:09.830 Luke Scorziell: Yeah, nice.
76 00:07:09.830 ⇒ 00:07:10.480 Robert Tseng: Yeah.
77 00:07:10.480 ⇒ 00:07:11.519 Luke Scorziell: Recording for that.
78 00:07:11.800 ⇒ 00:07:12.800 Luke Scorziell: Yeah.
79 00:07:13.780 ⇒ 00:07:20.920 Luke Scorziell: So… Yeah, well, so I guess…
80 00:07:21.420 ⇒ 00:07:24.819 Luke Scorziell: Friday, got to kind of go deep on some of the work that I’ve been, like.
81 00:07:25.680 ⇒ 00:07:31.150 Luke Scorziell: wanting to do, it’s just, I guess, just, like, simplifying… down the…
82 00:07:31.280 ⇒ 00:07:40.509 Luke Scorziell: like, messaging, and I still think it’s, like, I’m probably missing some gaps and stuff, but I think just what I saw looking through the story brand framework that you guys did in the…
83 00:07:40.990 ⇒ 00:07:45.779 Luke Scorziell: Last quarter, it’s just, like, kind of an overall theme. I can kind of show you.
84 00:07:46.080 ⇒ 00:07:55.610 Luke Scorziell: Just that, like, that ad seems to make people feel kind of, like, out of their element, a little confused, like, probably, like, they’re not really…
85 00:07:56.560 ⇒ 00:07:59.169 Luke Scorziell: Able to lead in the way that they know that they can.
86 00:08:00.790 ⇒ 00:08:03.949 Luke Scorziell: And… so, yeah, let me just…
87 00:08:07.130 ⇒ 00:08:14.360 Luke Scorziell: Like, this is kind of what I… This outlined, like, a…
88 00:08:15.310 ⇒ 00:08:16.949 Luke Scorziell: Just like a lot of these, like.
89 00:08:17.390 ⇒ 00:08:25.289 Luke Scorziell: That is slow, there’s no answers, no confidence, unhelpful. So just, like, a lot of emotions, like frustration, people feel confused.
90 00:08:25.880 ⇒ 00:08:27.810 Luke Scorziell: There’s, like, no mobility…
91 00:08:27.950 ⇒ 00:08:33.260 Luke Scorziell: Try to build systems, but they’re janky, which to me is, like, complexity and probably makes people feel incompetent.
92 00:08:33.650 ⇒ 00:08:34.630 Luke Scorziell: Yeah.
93 00:08:35.020 ⇒ 00:08:41.829 Luke Scorziell: And so I just, like, yeah, these, like, feelings of, like, powerlessness, confusion, frustration, overwhelm.
94 00:08:42.309 ⇒ 00:08:47.100 Luke Scorziell: I feel embarrassed about how inefficient our systems are. Like, I’m wasting time and money.
95 00:08:47.370 ⇒ 00:08:48.490 Luke Scorziell: And so…
96 00:08:48.490 ⇒ 00:08:50.119 Robert Tseng: Yeah, that’s a big one, yeah.
97 00:08:50.780 ⇒ 00:08:51.840 Luke Scorziell: Yeah, so, like.
98 00:08:51.840 ⇒ 00:08:52.380 Robert Tseng: Yeah.
99 00:08:52.710 ⇒ 00:09:00.100 Luke Scorziell: just as I was, yeah, kind of going through each of these, it’s like, a few, like, key emotions that stood out as just, like.
100 00:09:00.670 ⇒ 00:09:08.310 Luke Scorziell: Kind of this, like, you know, Sentence, if you’re… Let’s just say you’re like, Brian Forge, Brian.
101 00:09:08.490 ⇒ 00:09:15.830 Luke Scorziell: Like, I’m the boss, I’m smart, my systems are making me feel dumb, I want to feel empowered to make good decisions, because I know I was brought in the organization to make them.
102 00:09:16.050 ⇒ 00:09:23.070 Robert Tseng: Yeah. I feel like I’m wasting hours of a week doing things that I should be giving to an intern. It’s embarrassing, especially when I’m in a high-caliber role at this company.
103 00:09:23.150 ⇒ 00:09:30.699 Luke Scorziell: It’s a waste of my time and the company’s time. I should feel confident, smart, and our team should function smoothly, and I should be able to emanate, like, confidence.
104 00:09:31.040 ⇒ 00:09:35.050 Luke Scorziell: I like peace. Peace, calm, and confidence. So it’s kind of like… you’re like…
105 00:09:36.640 ⇒ 00:09:42.550 Luke Scorziell: Like, smart and capable, but you’re in a role where the data systems are making you feel like.
106 00:09:43.140 ⇒ 00:09:48.750 Luke Scorziell: Dumb, and, like, not, like, you know, potentially, like, your job is on the line.
107 00:09:49.290 ⇒ 00:09:49.920 Robert Tseng: Yeah.
108 00:09:51.210 ⇒ 00:10:00.889 Luke Scorziell: So then what I was thinking is, like, if we position Brainforge as, you know, we’re here to empower you with confidence, you can be the leader that you know you were made to be.
109 00:10:01.250 ⇒ 00:10:07.000 Luke Scorziell: You know, stop letting your system sabotage you. We’re here to put you back in the driver’s seat.
110 00:10:07.330 ⇒ 00:10:13.350 Luke Scorziell: You know, and then I kind of came on this idea of intelligence, which is just, like.
111 00:10:13.480 ⇒ 00:10:17.450 Luke Scorziell: And I think I’d like to test this more with the data, but, like, is…
112 00:10:18.470 ⇒ 00:10:22.620 Luke Scorziell: Is data a word that makes people feel kind of like…
113 00:10:23.470 ⇒ 00:10:28.510 Luke Scorziell: Oh, that’s, like, not for me, or, like, a little bit hesitant, versus, like, intelligence is a word that…
114 00:10:28.640 ⇒ 00:10:32.500 Luke Scorziell: I mean, obviously, it’s kind of a buzzword right now with artificial intelligence, but.
115 00:10:32.500 ⇒ 00:10:33.080 Robert Tseng: Yeah.
116 00:10:34.160 ⇒ 00:10:40.150 Luke Scorziell: Yeah, just that, like, you know, playing around with some of these lines. I really like this one, like.
117 00:10:41.530 ⇒ 00:10:47.959 Luke Scorziell: We… Empowering intelligence, or, like, empowering intelligent leaders.
118 00:10:49.540 ⇒ 00:10:52.699 Luke Scorziell: you know, just kinda… and I don’t know, like, we can…
119 00:10:53.110 ⇒ 00:10:59.520 Luke Scorziell: kind of go back and forth on that, too, but just… I think, in my mind, as I’m thinking about the messaging and
120 00:10:59.750 ⇒ 00:11:02.279 Luke Scorziell: Especially if they’re turning on, like, LinkedIn content.
121 00:11:03.580 ⇒ 00:11:05.480 Luke Scorziell: I kind of was like, is there…
122 00:11:06.100 ⇒ 00:11:10.590 Luke Scorziell: Like, what is the one thing that Brainforge can, like, be about?
123 00:11:11.450 ⇒ 00:11:13.899 Luke Scorziell: In terms of, like, helping its customers.
124 00:11:14.100 ⇒ 00:11:18.470 Luke Scorziell: And helping people in, and so… This is…
125 00:11:18.610 ⇒ 00:11:20.180 Luke Scorziell: Yeah, I think kind of, like.
126 00:11:20.300 ⇒ 00:11:24.149 Luke Scorziell: Maybe the beginnings to me of thinking about, like, what is the overall brand?
127 00:11:24.320 ⇒ 00:11:28.860 Luke Scorziell: Or that we want to build. So…
128 00:11:30.020 ⇒ 00:11:32.110 Robert Tseng: Yeah,
129 00:11:34.070 ⇒ 00:11:39.680 Robert Tseng: I’m just gonna Slack you something, and I can send you the full link, you can take a look.
130 00:11:39.930 ⇒ 00:11:42.870 Robert Tseng: I was sharing this with someone the other day.
131 00:11:44.240 ⇒ 00:12:01.459 Robert Tseng: Yeah, as far as, like, intelligence, so yeah, data still feels too, like… it just doesn’t feel like it’s… it’s not personal, it just feels like this abstract concept. Intelligence, I think, gets a little bit closer. On our… on our website, I don’t know if it shows it anymore, but, like, data people often talk about, like,
132 00:12:01.840 ⇒ 00:12:06.090 Robert Tseng: Yeah, we accelerate giving you actionable insights.
133 00:12:06.200 ⇒ 00:12:09.589 Robert Tseng: And that’s, like, that’s… that’s a… that’s become, like, a…
134 00:12:11.120 ⇒ 00:12:25.729 Robert Tseng: I mean, it’s used in, like, every pitch that we make. Oh, it’s like, oh, you don’t just want… because if you just have a bunch of data, it’s just noise, you don’t really know what to do with it. Intelligence is, like, yeah, business intelligence kind of gets, like, a bad rep, because, like.
135 00:12:26.030 ⇒ 00:12:33.189 Robert Tseng: Yeah, it’s like, the intelligence there is not necessarily, like, kind of what you brought out on this point,
136 00:12:33.600 ⇒ 00:12:51.990 Robert Tseng: it… it may contradict, like, your intuitions, like, it just kind of feels like you’re… it’s like this outsource… you’re, like, personifying this, like, artificial brain. It’s, like, artificial intelligence, data intelligence, business intelligence, whatever, and it’s, like, it doesn’t… doesn’t really feel like you’re the owner. And I think,
137 00:12:52.210 ⇒ 00:13:03.460 Robert Tseng: Yeah, people, like, you can see it across the industry. The word BI analyst or business intelligence analyst is no longer, like, being used in job descriptions. People aren’t really calling it intelligence anymore.
138 00:13:03.530 ⇒ 00:13:16.740 Robert Tseng: So yeah, I think that’s why Actionable Insights has kind of been, like, the default, but I’ve been, like, trying to think about, like, well, even that doesn’t seem like it’s enough, and I saw… I read this article that I thought was pretty good, that kind of just talks about
139 00:13:17.340 ⇒ 00:13:26.410 Robert Tseng: yeah, insights, suggestions, assertions. I think it’s more in talking about, like, how humans influence each other, but, like.
140 00:13:26.530 ⇒ 00:13:31.720 Robert Tseng: I mean, I would like to… I kind of feel like what we’re giving people is…
141 00:13:31.860 ⇒ 00:13:49.920 Robert Tseng: I like the… what the… their definition of assertion. Like, a bias towards action, giving a point of view, a personal conviction, and then, like, enabling some sort of ownership to, like, do… take responsibility for the idea. Like, that’s really what we’re trying to, like, put in the hands of people. So…
142 00:13:49.920 ⇒ 00:13:53.769 Robert Tseng: I think, like, insight has kind of been watered down to just be, like.
143 00:13:53.790 ⇒ 00:14:00.819 Robert Tseng: okay, here’s a dashboard, the inside is, like, this metric moved up or down, and that’s… that’s, like, what it is. And I…
144 00:14:01.420 ⇒ 00:14:19.409 Robert Tseng: then there needs to be some suggestions, like, what do we do about it? If something goes down, like, what do we… what do we need to, like, what are the levers? Like, what can this person who’s reading these reports actually do about it? The assertion is more kind of, like, to me, a more informed, like, kind of point of view on,
145 00:14:20.660 ⇒ 00:14:22.170 Robert Tseng: Yeah, like…
146 00:14:22.200 ⇒ 00:14:37.140 Robert Tseng: given all these facts, we’re triangulating, kind of, different pieces of data, the hypothesis that I have is that we need to be taking this… we need to be moving in this direction, and I believe that because X, Y, and Z things. Like, there’s just something that seems to be more…
147 00:14:37.140 ⇒ 00:14:43.229 Robert Tseng: kind of closings in the loop. So, I don’t know if we actually want to use that word in the,
148 00:14:43.850 ⇒ 00:14:46.340 Robert Tseng: In the branding, but, like.
149 00:14:46.470 ⇒ 00:14:55.050 Robert Tseng: I’m just trying to articulate, what we’ve seen in terms of, like, different stages of data-drivenness,
150 00:14:55.710 ⇒ 00:15:11.649 Robert Tseng: yeah, like, I think it’s… when it’s really watered down, it’s just what people are typically seeing, which is just a bunch of numbers… too many login portals, so all these tools spitting you out charts and data that you don’t really understand.
151 00:15:11.650 ⇒ 00:15:23.729 Robert Tseng: Everything’s a black box, you don’t fully get to… you don’t really know how things are calculated, you’re just assuming that things kind of speak. But they are, and in the marketing world, this is, like, a big problem, because every
152 00:15:23.730 ⇒ 00:15:42.100 Robert Tseng: every report, like, Facebook ads will tell you that if you log into Facebook, it’ll always show you that your ads are performing better than if you were to actually calculate it yourself, because they want you to spend more money. So everybody has, like, their own biased, like, spin on presenting you data. You don’t really know what the source of truth is. And so,
153 00:15:42.150 ⇒ 00:15:58.720 Robert Tseng: Yeah, I think, like, the distrust between, like, what people see and what their intuition, like, I think we’ve not… like, that’s… that’s the biggest… that’s the biggest gap, and oftentimes the biggest hurdle for us to overcome when we step into a messy situation where people don’t trust the data.
154 00:15:58.730 ⇒ 00:16:11.399 Robert Tseng: just getting it all in one place doesn’t necessarily, like, build that trust with them, but there’s also some educational piece, too, where we have to help them kind of correct their assumptions and, like, to learn how to see the data with a clearer
155 00:16:11.400 ⇒ 00:16:11.990 Robert Tseng: Wait.
156 00:16:11.990 ⇒ 00:16:32.169 Robert Tseng: Yeah, with less than their own bias, and that’s, like, part of the hard work of, like, what we have to do. It just requires a lot of reps, setting up regular reviews, that’s why we do so many client calls and reviews, because a lot of what we’re saying is kind of disrupting the narrative that, like, people are typically used to seeing internally from their own intuitions.
157 00:16:32.510 ⇒ 00:16:46.799 Robert Tseng: And yeah, like, we have… it kind of feels like we have to move mountains, and of, like, getting people to be open to letting the data speak to them before they actually will rely on it to make, to make decisions.
158 00:16:46.880 ⇒ 00:17:00.160 Robert Tseng: I’ll just pause there. I think that just felt like I needed to clarify, kind of, that’s… that to me is, like, kind of the different stages of, like, how… when we partner with an organization, we move from just chaos
159 00:17:00.370 ⇒ 00:17:07.419 Robert Tseng: We were talking about… we used to say, chaos to clarity. I think that’s another kind of spectrum to, like, kind of articulate as well.
160 00:17:07.560 ⇒ 00:17:08.920 Robert Tseng: Yeah.
161 00:17:09.550 ⇒ 00:17:10.160 Luke Scorziell: Huh.
162 00:17:11.369 ⇒ 00:17:12.500 Luke Scorziell: So…
163 00:17:15.030 ⇒ 00:17:21.589 Luke Scorziell: Yeah, it’s interesting. So then the… there’s the… what you’re saying is there’s a lack of trust that the data that they’re getting even
164 00:17:21.990 ⇒ 00:17:28.760 Luke Scorziell: at a baseline is accurate, because they don’t necessarily trust the sources of the data, whether that be Meta, Google.
165 00:17:29.170 ⇒ 00:17:33.840 Luke Scorziell: Or, I guess, like, And that’s particularly in, like, the marketing?
166 00:17:34.190 ⇒ 00:17:35.190 Luke Scorziell: Yeah, in the marketing world.
167 00:17:35.190 ⇒ 00:17:51.380 Robert Tseng: on finance or ops people, it’s like, okay, they trust QuickBooks. QuickBooks is, like, their accounting software. They know when money comes in or out, in terms of, like, when payments are made, but that’s not the full picture of, like, how an organization’s measures of revenue, right?
168 00:17:51.490 ⇒ 00:18:01.610 Robert Tseng: we… when we report on monthly recurring revenue in Brainforge, it’s not based off of, like, when the, invoice hits, like, because…
169 00:18:01.610 ⇒ 00:18:19.839 Robert Tseng: we have net 14 to 30, sometimes 60 payment terms with clients. There could be, like, you know, a two-week to 2-month delay before the payment hits. But we still have to, like, make decisions, like… so, like, the accounting perspective is always lagging behind, like, what the business is actually doing.
170 00:18:19.960 ⇒ 00:18:29.129 Robert Tseng: And if you… you can’t run a business off of just looking at accounting reports, because you’ll always be 2 months behind. You won’t really… you won’t really know what’s actually coming in.
171 00:18:29.130 ⇒ 00:18:44.419 Robert Tseng: But then if you look too far ahead, and you’re looking at the checkout, if you’re a consumer band company, and you’re just, like, counting revenue when a customer checks out, well, statistically, the industry knows that 10-15% of those transactions will not actually go through.
172 00:18:44.420 ⇒ 00:19:02.969 Robert Tseng: credit card failures, people will change their order, like, things will get refunded or whatever. So you’re over-reporting your revenue in the beginning, and it’s not… and… and it’s too closely tied to, maybe, promotions that you’re… that you’re… that you’re making. So, like, there’s… you can fudge the numbers by just, like, kind of doing some things to make your, like, the first
173 00:19:02.970 ⇒ 00:19:06.020 Robert Tseng: The first, the first checkout look… look good.
174 00:19:06.120 ⇒ 00:19:12.900 Robert Tseng: So really, like, the truth is somewhere in the middle, and, like, people… oftentimes, like, we walk into situations where
175 00:19:13.050 ⇒ 00:19:28.669 Robert Tseng: you know, they’re… they… they don’t have that intermediary. It’s just, like, they have the back half of the equation, which is the 2-month delayed report, and then they also have, like, the checkout from their marketplace, or whatever they’re… whatever, you know, payment portal they’re using.
176 00:19:28.670 ⇒ 00:19:35.910 Robert Tseng: But that’s not really how, they should be measuring their business, and they don’t really know how they’re actually doing at this point in time.
177 00:19:36.580 ⇒ 00:19:54.590 Robert Tseng: So that’s… yeah, so, like, there’s, like, more examples of this for every department, where, you know, we know… we know the tools that they rely on, they’re operating in, but they all tell an incomplete picture. And so, like, to find…
178 00:19:54.810 ⇒ 00:20:11.480 Robert Tseng: like, to be able to have, yeah, once again, this single source of truth in a way that everyone across all teams can agree on, like, this is what the definition should be, this is when we’re talking about sales, this is what sales should be, this is what cost really means, like, you know, there’s some of these very basic
179 00:20:11.480 ⇒ 00:20:22.890 Robert Tseng: Definition… that you would think are basic definitions in an organization are, you know, just get very… kind of get blown out of proportion, depending on who you talk to and on a team.
180 00:20:24.160 ⇒ 00:20:26.640 Luke Scorziell: Yeah, huh, okay. Yeah.
181 00:20:34.260 ⇒ 00:20:36.420 Luke Scorziell: And so then is, like, the main issue that…
182 00:20:37.420 ⇒ 00:20:40.560 Luke Scorziell: Brainforge is, like, I mean, on an emotional level.
183 00:20:40.910 ⇒ 00:20:46.059 Luke Scorziell: like, how does Brainforge then go about solving that, like, trust issue, and helping them…
184 00:20:46.600 ⇒ 00:20:52.689 Luke Scorziell: Helping customers to, I guess, trust Brainforge more. Or, not trust Brainforge, but trust the data.
185 00:20:52.880 ⇒ 00:20:56.259 Luke Scorziell: It’s like… Guiding them through…
186 00:20:56.750 ⇒ 00:21:02.000 Luke Scorziell: Like, here’s how we’re… we’re doing something different, or, like, what… what changes when you guys work with them?
187 00:21:02.530 ⇒ 00:21:12.429 Robert Tseng: Yeah, I think it’s a few things, like, one is, like, like, we know how to reconcile differences, technically, across all of these systems, like.
188 00:21:12.430 ⇒ 00:21:13.140 Luke Scorziell: Hmm.
189 00:21:13.150 ⇒ 00:21:20.140 Robert Tseng: If you’re a company running on Shopify, I could tell you exactly what Shopify’s account reporting is doing wrong.
190 00:21:20.880 ⇒ 00:21:32.449 Robert Tseng: in terms of, like, what you shouldn’t trust about it, where the limitations are, or whatever. So, like, I could… I could do that. So there’s, like, a technical, like, level of expertise there. But then also, we’ve been… we’ve been, you know, we’ve been, like.
191 00:21:32.680 ⇒ 00:21:46.410 Robert Tseng: operators, we’ve led data teams within various organizations, and we know how to navigate these conversations. You know, I think, like, a typical leader, frustrated leader, would just kind of give up. They’d just be like, well.
192 00:21:46.500 ⇒ 00:21:59.900 Robert Tseng: you and I don’t disagree, I’m just gonna stick by my definition, you stick with yours, and they continue to operate in the silo. So, like, we… we get brought in when, like, the silos need to be broken down, and, like.
193 00:22:00.210 ⇒ 00:22:12.689 Robert Tseng: you know, there is kind of like a, you know, you’re kind of delaying the inevitable by not kind of resolving this, you know, at a certain point. Like, you’ll… you will need that type of clarity.
194 00:22:12.950 ⇒ 00:22:17.639 Robert Tseng: For different milestones in a business. If you’re trying to raise around.
195 00:22:17.660 ⇒ 00:22:22.320 Robert Tseng: At your venture-backed startup, you need to have… it needs to be at some…
196 00:22:22.320 ⇒ 00:22:41.970 Robert Tseng: like, level of, understanding that’s, of an industry standard to what VCs and whatever would care about. But that’s not necessarily the same standard as a publicly traded company at an enterprise level. Like, they have a different set of standards. But, like, we just understand the standards for, like, what they’ll need at different stages.
197 00:22:41.970 ⇒ 00:22:44.590 Robert Tseng: Of their, of their business lifecycle.
198 00:22:44.620 ⇒ 00:22:49.450 Robert Tseng: And we can kind of help them kind of get, get through that.
199 00:22:49.750 ⇒ 00:22:52.649 Robert Tseng: we’re not, like… so it’s, like, kind of… yeah, like, I…
200 00:22:52.760 ⇒ 00:22:55.979 Robert Tseng: I’ve used to… on pitches, I would say, you know, like.
201 00:22:56.810 ⇒ 00:23:00.299 Robert Tseng: You know, contrary to a lot of other, you know, just…
202 00:23:00.520 ⇒ 00:23:16.060 Robert Tseng: technical sweatshops, like, overseas sweatshops that are, you know, India, Indonesia-based, like, engineering teams that will just, like, go and do the thing. You need people who actually know how to meet you, like, in your stage, understand your context, and be able to, like.
203 00:23:16.070 ⇒ 00:23:31.090 Robert Tseng: flex the expertise of, like, what you do when you’re starting from zero to all the way up to, like, something that’s enterprise trustworthy, like a Fortune 500, like, level, like, quality type of stack. And we, and we have the,
204 00:23:31.240 ⇒ 00:23:42.000 Robert Tseng: And, yeah, because we’ve, like, seen the whole spectrum, we know how to, like, kind of meet the organization where they’re at to give them what they need with no kind of, like, additional fluff.
205 00:23:42.920 ⇒ 00:23:43.610 Luke Scorziell: Yeah.
206 00:23:43.840 ⇒ 00:23:44.520 Luke Scorziell: Okay.
207 00:23:50.620 ⇒ 00:23:59.719 Luke Scorziell: So it’s the technical expertise that you offer in terms of, like, just knowing. It’s the operator… having worked as operators and knowing just that there’s…
208 00:24:00.120 ⇒ 00:24:03.939 Luke Scorziell: There can be silos and, like, Lacks of, of,
209 00:24:04.050 ⇒ 00:24:07.850 Luke Scorziell: shared definitions, or just a universal stage of truth, and then you know…
210 00:24:08.020 ⇒ 00:24:11.899 Luke Scorziell: I guess the standards that… that they each need.
211 00:24:12.240 ⇒ 00:24:18.149 Luke Scorziell: Okay. Yeah, it’s funny, every time I feel like I’m, like, I get… I get to a layer of, like, okay, I understand this.
212 00:24:18.420 ⇒ 00:24:22.150 Luke Scorziell: Then there’s another layer of, of… of…
213 00:24:22.150 ⇒ 00:24:32.629 Robert Tseng: like, a steeper, yeah, well, I mean, there’s just, like, stuff from… I mean, I mean, I wanna… I could… I could share a lot more about this. I mean, even this call could probably get returned to content.
214 00:24:32.960 ⇒ 00:24:43.739 Robert Tseng: to kind of describe, like, what does a data leader need to be in an organization? You know, what’s our perspective on that? Like, I think, like, this transcript could end up becoming that content.
215 00:24:44.180 ⇒ 00:24:59.969 Robert Tseng: Yeah, so I mean, I’m trying to just give you that type of insight, that you won’t be able to get from just listening to the pain of, like, the people that are… that are talking about what they… what they think the problem is. People don’t know how to diagnose their own problems, they just know how to describe how they’re feeling.
216 00:25:00.970 ⇒ 00:25:07.029 Luke Scorziell: Yeah, and the, so… I mean, from your perspective, then, what is… what does a good data leader do?
217 00:25:08.090 ⇒ 00:25:13.209 Robert Tseng: Yeah, I mean, kind of a lot of those things that I described, but, like, I think…
218 00:25:14.190 ⇒ 00:25:21.580 Robert Tseng: The data leader, I mean, I guess there’s a few… I’ll take… go from a different perspective, but, like, you…
219 00:25:21.920 ⇒ 00:25:27.910 Robert Tseng: They need to be able to, like, see…
220 00:25:28.200 ⇒ 00:25:36.649 Robert Tseng: they need to be able to understand everyone’s perspective. I think that’s, like, a really important one. Because you’re a bridge builder. You need to be able to bring people to
221 00:25:36.800 ⇒ 00:25:42.809 Robert Tseng: to the… to the table to discuss things. But you also need to be opinionated about, like.
222 00:25:42.960 ⇒ 00:25:59.039 Robert Tseng: you know, when people are just kind of talking over each other, like, what is… is there, like, a universal kind of standard? Like, what are, like, the best practices that can kind of help ground people, in navigating, like, difficult conversations where there… where there’s, like, big… big disagreement?
223 00:25:59.200 ⇒ 00:26:07.390 Robert Tseng: The data team always gets blamed for when something is… seems off, and so, yeah, you kind of need to be able to kind of take
224 00:26:07.750 ⇒ 00:26:13.209 Robert Tseng: Take blame all the time, but, like, be able to, like.
225 00:26:13.480 ⇒ 00:26:24.880 Robert Tseng: kind of compartmentalize a bit to just root cause the problem really quickly. Understand that, like, the blame is not, like, something… you can’t be so defensive about it. It’s not really…
226 00:26:24.880 ⇒ 00:26:34.659 Robert Tseng: It’s not necessarily something you can do anything about it, but the faster we can get answers and diagnose, like, what’s going on, that helps to build the trust, because ultimately, like.
227 00:26:34.810 ⇒ 00:26:40.440 Robert Tseng: If… if marketing spend is down by, like, 20% month over month.
228 00:26:40.580 ⇒ 00:26:50.799 Robert Tseng: it’s not the data team’s fault. Like, we’re not the ones that are spending money inefficiently, whatever. We could say, like, what’s wrong? And we can… we can go and, like, kind of…
229 00:26:50.800 ⇒ 00:27:00.980 Robert Tseng: Provide the answer, but we need to be able to do it in a way where we’re partnering with the marketing leader to be able to help them spot what the most inefficient channel is.
230 00:27:00.980 ⇒ 00:27:05.620 Robert Tseng: That’s leading to this… to this de… to this drop, and, like, where…
231 00:27:05.620 ⇒ 00:27:18.580 Robert Tseng: where… and maybe even recommend, like, where they should reinvest in as well. So, I think those are some of the qualities of, like, a data leader that… that, like, that need… that you need to have, yeah.
232 00:27:19.500 ⇒ 00:27:21.220 Luke Scorziell: Yeah,
233 00:27:25.580 ⇒ 00:27:28.030 Luke Scorziell: And when you say understood, yeah, yeah, yeah.
234 00:27:28.030 ⇒ 00:27:29.980 Robert Tseng: I was gonna say, like,
235 00:27:30.350 ⇒ 00:27:44.949 Robert Tseng: a lot of this is, like, kind of the same cloth as the AI side, because AI, engineering, like, I don’t know what you saw in the contextual, but something I’m, like, continually, like, learning now is the problem isn’t necessarily, like.
236 00:27:45.240 ⇒ 00:27:59.099 Robert Tseng: designing workflows. I think people… the operators themselves can think about the workflows that they want, they’re the best, and now with AI, they can… you can prototype, like, a new workflow very quickly.
237 00:27:59.100 ⇒ 00:28:07.069 Robert Tseng: Or at least put out… put out… build diagrams, like, kind of change the way that, like, how people actually complete their tasks.
238 00:28:07.150 ⇒ 00:28:18.160 Robert Tseng: But it is ultimate… before it to be adopted by an organization, it’s still a data problem. You have to trust that, like, the workflow is pulling from the right source of truth.
239 00:28:18.160 ⇒ 00:28:28.489 Robert Tseng: That the documents that you’re trying to mix together, they’re all in a standardized format, where, like, you could actually trust the LLM to extract data out of this or that.
240 00:28:29.000 ⇒ 00:28:39.999 Robert Tseng: And those are all data problems, in terms of, like, data… the data team exists to make sure that disparate sources of data and whatever presentation
241 00:28:40.000 ⇒ 00:28:52.359 Robert Tseng: can all be kind of, like, presented in a single interpretable plane, where you can actually do apples-to-apples comparisons. That is not something that operators can figure out on their own.
242 00:28:52.600 ⇒ 00:29:06.670 Robert Tseng: So many people are always like, oh, I just want to throw ChatGPT on top of my… on top of my data and chat with it instead of, dashboards. But if you’re asking ChatGPT, okay, what’s your, like.
243 00:29:06.930 ⇒ 00:29:18.229 Robert Tseng: Yeah, what, what does, yeah, what’s, what’s the gross margin on your, on your product over the past month? It’s going to get that question wrong, unless you have
244 00:29:18.460 ⇒ 00:29:33.699 Robert Tseng: properly traded on. These are the specific things that we exclude from gross margin. We do some unique discounts, we actually, like, throw in free products, stuff like that that’s, like, not typical of other CPG brands. Like, the LLM definition.
245 00:29:33.700 ⇒ 00:29:43.039 Robert Tseng: will always go to the average. It’s just like a statistical model, where it will guess at what’s the most probable
246 00:29:43.140 ⇒ 00:29:52.180 Robert Tseng: Kind of next… Like, word or group of words to complete the phrase. And in a business.
247 00:29:52.350 ⇒ 00:30:08.400 Robert Tseng: like, you’re always going to have nuances that are unique to your business, and you can’t rely on an LLM to be able to go and fish those out for you, unless you know what they are already, and you can train it to spot those things. So, I think, like.
248 00:30:08.400 ⇒ 00:30:23.840 Robert Tseng: that’s… I think that’s the problem that people are running up against, and why a lot of this, like, chat with your data stuff, like, is it actually being used, at an organizational level? Like, people use it, like, as a hobby. But yeah, it’s really hard to go from
249 00:30:23.910 ⇒ 00:30:31.690 Robert Tseng: prototype of just, like, here’s showing some functionality to, like, I actually trust the stuff that it’s spitting out for me.
250 00:30:33.410 ⇒ 00:30:36.519 Luke Scorziell: Yeah, well, because it seems like underneath it all is just…
251 00:30:36.640 ⇒ 00:30:42.929 Luke Scorziell: how probably 99% of people use ChatGPT is just out of the box with whatever.
252 00:30:43.260 ⇒ 00:30:43.830 Robert Tseng: Yeah.
253 00:30:44.190 ⇒ 00:30:49.729 Luke Scorziell: like… Whatever it’s going off of, based on all the conversations that it’s had and been trained on.
254 00:30:49.990 ⇒ 00:30:55.050 Luke Scorziell: Versus at an organizational level, you need, like, an AI that’s specifically trained
255 00:30:55.480 ⇒ 00:31:02.870 Luke Scorziell: with, like, very specific rules and subsets and data and all that stuff to make sure that it’s actually going on. Okay.
256 00:31:09.170 ⇒ 00:31:16.119 Luke Scorziell: Okay, yeah, that makes sense. I mean, I guess, do you think I’m going in, like, the right direction in terms of, like, the branding and messaging? Also, did you have a meeting at…
257 00:31:16.120 ⇒ 00:31:20.850 Robert Tseng: Yeah, I do. I have to have an interview with a guy, but I can take another minute.
258 00:31:21.110 ⇒ 00:31:26.870 Robert Tseng: Yeah, I think, like, you know, I think it’s, like I said, it’s headed in the right direction. I think,
259 00:31:27.760 ⇒ 00:31:36.930 Robert Tseng: Yeah, hopefully I’ve described some… I feel like what you’re… what seems to be missing is,
260 00:31:37.260 ⇒ 00:31:56.170 Robert Tseng: Yeah, I think, like, maybe… and maybe we’re just too much of a data per data people. Like, everything is so nuanced. I view everything on a spectrum. Like, I know that whatever I say, there’s gonna be somebody who thinks something differently, and, like, my role in an organization is always to try to, like, find how people should meet in the middle.
261 00:31:56.170 ⇒ 00:32:06.100 Robert Tseng: There are some… actually, it’s always in the middle. Sometimes, like, organizations are just doing something blatantly wrong, and I will just… because I’ve seen it enough times, like, I’ll be able to tell them, like.
262 00:32:06.100 ⇒ 00:32:24.099 Robert Tseng: this is actually just not how you… this is actually not how you… you should calculate it. You just need to do it… do it differently. But, I think people rely on… on us to be able to help them, like, build, like, that source of truth. Like, I think that’s… that’s always been the elusive, like, like.
263 00:32:24.970 ⇒ 00:32:44.039 Robert Tseng: thing in the data world. Like, we’ve been selling this vision of a source of truth for… for decades, but, like, it’s… I think it’s getting easier to do so, and a lot of the tools that we use help us do that. Things like the dbt audit, and, yeah, just, like, the way that we approach data engineering, like.
264 00:32:44.100 ⇒ 00:32:55.729 Robert Tseng: it’s never been easier to, like, take different data sources and to bring them all in one place. Like, that will only get… become more of a commodity and make it… and it’ll be cheaper and faster to run those things.
265 00:32:55.730 ⇒ 00:33:11.460 Robert Tseng: And so, what differentiates us after the, kind of, often the engineering piece is… is really that we can… we can help organizations, like, navigate those… those difficult… those… those hard… those hard conversations, and to help them design, like.
266 00:33:11.460 ⇒ 00:33:14.039 Robert Tseng: how their system should be structured. So…
267 00:33:14.050 ⇒ 00:33:24.390 Robert Tseng: So that it can… it can really be… you can really hook up, like, like an LLM to it, so that you can get… get what you want out of it. I think that’s…
268 00:33:24.840 ⇒ 00:33:33.289 Robert Tseng: Yeah, I mean, I feel like we gotta, like, workshop that pitch more, but, like, I think that’s at the heart of it, like, what we do.
269 00:33:33.750 ⇒ 00:33:34.550 Luke Scorziell: Yeah.
270 00:33:34.580 ⇒ 00:33:35.570 Robert Tseng: Edge.
271 00:33:35.670 ⇒ 00:33:36.410 Robert Tseng: Yeah.
272 00:33:37.260 ⇒ 00:33:40.260 Luke Scorziell: Okay. Yeah, I can work… I can run with that a little bit. Okay.
273 00:33:40.260 ⇒ 00:33:40.800 Robert Tseng: Cool.
274 00:33:41.030 ⇒ 00:33:42.720 Luke Scorziell: Okay, sweet. Alright, I got it.
275 00:33:43.000 ⇒ 00:33:45.300 Robert Tseng: But, yeah. Cool. Talk to you later.
276 00:33:45.650 ⇒ 00:33:46.420 Luke Scorziell: Yep.