Meeting Title: Brainforge Attribution and Product Analytics Overview Date: 2026-01-13 Meeting participants: Luke Scorziell, Zoran Selinger
WEBVTT
1 00:01:09.530 ⇒ 00:01:11.099 Luke Scorziell: What is our own sky.
2 00:01:12.150 ⇒ 00:01:16.019 Zoran Selinger: for my connection problems, I don’t know… I don’t know what happened, and it’s been stable.
3 00:01:16.290 ⇒ 00:01:17.530 Luke Scorziell: No, no, it was…
4 00:01:17.530 ⇒ 00:01:19.640 Zoran Selinger: Last time I dropped out, I don’t know.
5 00:01:20.240 ⇒ 00:01:25.419 Zoran Selinger: I have this internet provider because of how stable they are.
6 00:01:25.650 ⇒ 00:01:29.430 Luke Scorziell: I mean, it happens to us all.
7 00:01:29.430 ⇒ 00:01:37.500 Zoran Selinger: everyone else is pretty bad in Croatia. This one was always stable for me. I mean, I’ve been with them since I was 12.
8 00:01:37.940 ⇒ 00:01:38.550 Luke Scorziell: Oh, really?
9 00:01:38.550 ⇒ 00:01:39.050 Zoran Selinger: Cool.
10 00:01:39.370 ⇒ 00:01:47.619 Zoran Selinger: pretty long time, really, but they are stable, usually. I don’t know, I’m hoping this won’t happen.
11 00:01:48.810 ⇒ 00:01:56.020 Zoran Selinger: Again, we’ll see. We’ll see. In any case, yeah, yeah.
12 00:01:56.990 ⇒ 00:01:59.019 Luke Scorziell: I’ll just put this link in the chat.
13 00:01:59.020 ⇒ 00:02:06.680 Zoran Selinger: So, initially, my idea, my thought was that potentially this is just, like, a
14 00:02:06.790 ⇒ 00:02:10.580 Zoran Selinger: A guy that, wants to… Huh.
15 00:02:10.759 ⇒ 00:02:18.129 Zoran Selinger: Wants to suss out what our, you know, technical solution is, to maybe replicate it, or whatever, right?
16 00:02:19.200 ⇒ 00:02:27.749 Zoran Selinger: And then I saw… then I saw, like, the website, which doesn’t seem like he’s a tech guy at all.
17 00:02:28.020 ⇒ 00:02:28.930 Luke Scorziell: Oh, interesting.
18 00:02:28.930 ⇒ 00:02:34.110 Zoran Selinger: But then the question, he was mostly interested in… In the technical side.
19 00:02:34.780 ⇒ 00:02:40.069 Luke Scorziell: So do you think that maybe, like, he was trying to learn what we’re doing?
20 00:02:40.540 ⇒ 00:02:42.570 Zoran Selinger: Maybe, maybe, because…
21 00:02:42.710 ⇒ 00:02:48.900 Zoran Selinger: He seems to be pretty, pretty knowledgeable about, you know, just the modern stack that is typical.
22 00:02:49.050 ⇒ 00:02:55.920 Zoran Selinger: So he has triple whale in place, he’s aware of server-side tagging,
23 00:02:56.060 ⇒ 00:03:01.079 Zoran Selinger: They… he has people already working on that, so he’s aware of
24 00:03:01.800 ⇒ 00:03:11.550 Zoran Selinger: Basically, everything that people have been doing for the last couple of years to battle these inaccuracies introduced by
25 00:03:12.560 ⇒ 00:03:19.720 Zoran Selinger: By, tracking prevention. That’s already in place. So, I don’t know, I don’t know, I’m not, I’m not sure.
26 00:03:19.940 ⇒ 00:03:21.060 Zoran Selinger: I’m not sure.
27 00:03:21.790 ⇒ 00:03:29.280 Zoran Selinger: Yeah. I’m still glad that I didn’t get into… More… into more technical details.
28 00:03:32.260 ⇒ 00:03:32.800 Zoran Selinger: Because…
29 00:03:32.800 ⇒ 00:03:33.410 Luke Scorziell: Oh, yeah.
30 00:03:34.330 ⇒ 00:03:37.340 Zoran Selinger: I could talk about that, but I understand that
31 00:03:37.630 ⇒ 00:03:41.260 Zoran Selinger: It’s what we sell right now, so we shouldn’t.
32 00:03:41.670 ⇒ 00:03:42.440 Luke Scorziell: Yeah, yeah.
33 00:03:42.440 ⇒ 00:03:50.959 Zoran Selinger: Yeah, we should, and I understand that, and I don’t have a lot of experience in these, these types of, meeting, meetings.
34 00:03:52.600 ⇒ 00:03:53.270 Luke Scorziell: Nope.
35 00:03:53.860 ⇒ 00:04:00.380 Luke Scorziell: It’s… that’s… that’s alright. Yeah, I think that’s probably a good call then to, there’s.
36 00:04:00.500 ⇒ 00:04:01.820 Zoran Selinger: Yeah, yeah.
37 00:04:01.940 ⇒ 00:04:06.029 Zoran Selinger: I think, yeah, it’s, you know, pretty low risk.
38 00:04:06.750 ⇒ 00:04:12.010 Zoran Selinger: Hearing that call, his questions were… Fine.
39 00:04:12.660 ⇒ 00:04:17.360 Luke Scorziell: Yeah, they seem pretty… this is my first time being on a call like that.
40 00:04:18.630 ⇒ 00:04:22.250 Luke Scorziell: Oh, I’m still, yeah, I was like…
41 00:04:22.390 ⇒ 00:04:24.960 Luke Scorziell: Learning and whatnot, but where was it pretty…
42 00:04:25.080 ⇒ 00:04:31.369 Luke Scorziell: like, basic questions? What… I don’t know, what was your overall take? I guess, I’m just trying to learn.
43 00:04:32.000 ⇒ 00:04:33.089 Luke Scorziell: There’s nothing like that.
44 00:04:33.270 ⇒ 00:04:43.760 Zoran Selinger: No, I mean, you, you’ve done… Robert told me your, your, basically your goal on the call was to, to figure out this… the ICP scoring, right?
45 00:04:44.120 ⇒ 00:04:51.259 Zoran Selinger: So, I mean, you know, you know if you’ve done that or not. I think it was,
46 00:04:52.900 ⇒ 00:05:00.510 Zoran Selinger: It was clear that it’s kind of a smaller size for us, it’s not… we’re not a perfect fit.
47 00:05:01.980 ⇒ 00:05:08.930 Zoran Selinger: For him, and he’s just not, not spending, not spending enough for this to be, you know, super impactful.
48 00:05:10.520 ⇒ 00:05:11.879 Zoran Selinger: So we can, you know.
49 00:05:12.560 ⇒ 00:05:12.950 Luke Scorziell: Yeah.
50 00:05:12.950 ⇒ 00:05:20.170 Zoran Selinger: really create a huge story, but, maybe, maybe, I would maybe…
51 00:05:21.250 ⇒ 00:05:24.169 Zoran Selinger: Maybe the easiest thing to do for…
52 00:05:25.040 ⇒ 00:05:29.150 Zoran Selinger: is maybe not Edge, but I, let’s say…
53 00:05:29.700 ⇒ 00:05:33.609 Zoran Selinger: Technical implementation audit, for example.
54 00:05:34.020 ⇒ 00:05:34.829 Luke Scorziell: Huh.
55 00:05:35.090 ⇒ 00:05:50.589 Zoran Selinger: Where we… when we go in, and I actually look at their tracking setup… setup that they have, and see if there are any holes in there, or not, right? And especially if he’s… if he’s working with,
56 00:05:51.330 ⇒ 00:05:59.189 Zoran Selinger: you know, people from Upwork, and who knows? Who knows what kind of hourly rates he’s paying.
57 00:05:59.190 ⇒ 00:05:59.620 Luke Scorziell: Yeah.
58 00:06:01.180 ⇒ 00:06:04.100 Zoran Selinger: That could be a huge mess.
59 00:06:04.100 ⇒ 00:06:05.790 Luke Scorziell: Yeah.
60 00:06:05.790 ⇒ 00:06:06.480 Zoran Selinger: Yeah.
61 00:06:06.480 ⇒ 00:06:07.080 Luke Scorziell: And…
62 00:06:07.950 ⇒ 00:06:13.660 Zoran Selinger: There’s a lot of different levels of service that you can get there.
63 00:06:15.330 ⇒ 00:06:19.369 Luke Scorziell: Yeah, and it’s all kind of the luck of the drama beyond who you… who you end up hiring.
64 00:06:19.940 ⇒ 00:06:20.350 Zoran Selinger: Yeah.
65 00:06:20.350 ⇒ 00:06:25.879 Luke Scorziell: So, yeah, and then, like, I don’t know, I’ve been kind of wondering…
66 00:06:26.280 ⇒ 00:06:30.079 Luke Scorziell: Can you just, like, do you have stuff you can, like, screen share with me, just to show?
67 00:06:30.430 ⇒ 00:06:35.400 Luke Scorziell: like, an example of what this looks like on, like, your end, just so I can kind of see.
68 00:06:36.090 ⇒ 00:06:38.209 Zoran Selinger: I mean, sure, sure.
69 00:06:38.430 ⇒ 00:06:42.440 Zoran Selinger: Well, yeah, well, because I’d be curious, too, like, with… he’s tracking, obviously, like.
70 00:06:43.190 ⇒ 00:06:44.660 Luke Scorziell: Ad spend and wanting…
71 00:06:45.100 ⇒ 00:06:53.169 Luke Scorziell: ROAS, and I keep, you know, I’m hearing all these… the different platforms and everything, and I think, you know, on some level, it’s like… I’d just be curious to see, like.
72 00:06:53.660 ⇒ 00:06:56.130 Luke Scorziell: What does the warehouse actually look like?
73 00:06:57.860 ⇒ 00:07:00.710 Zoran Selinger: Okay, let me share these,
74 00:07:08.200 ⇒ 00:07:09.700 Zoran Selinger: battery, here.
75 00:07:10.570 ⇒ 00:07:12.460 Zoran Selinger: So, this green…
76 00:07:14.220 ⇒ 00:07:22.479 Zoran Selinger: So let me start… where do I wanna start? I want to start… okay, let me show you the… the warehouse.
77 00:07:22.950 ⇒ 00:07:27.070 Zoran Selinger: The data warehouse, and this is our data warehouse.
78 00:07:27.220 ⇒ 00:07:33.809 Zoran Selinger: So there are all these, so, here, under here, so you have…
79 00:07:34.120 ⇒ 00:07:40.099 Zoran Selinger: So, these are all groups of… these are all groups of tables that we have available.
80 00:07:40.570 ⇒ 00:07:40.910 Luke Scorziell: Yeah.
81 00:07:40.910 ⇒ 00:07:47.209 Zoran Selinger: So… in, let’s say here, I have a fax, transaction table.
82 00:07:48.430 ⇒ 00:07:52.719 Zoran Selinger: If you go into the preview, you’ll see some rows from it, okay?
83 00:07:53.050 ⇒ 00:07:53.820 Luke Scorziell: Puh.
84 00:07:54.050 ⇒ 00:08:01.480 Zoran Selinger: So this is what Eden, for example, their actual conversions are in here. So we know
85 00:08:01.850 ⇒ 00:08:07.289 Zoran Selinger: exhaustion, and I’m going to try to find all the different sessions that this person had.
86 00:08:09.160 ⇒ 00:08:09.790 Luke Scorziell: Yeah.
87 00:08:11.130 ⇒ 00:08:18.619 Zoran Selinger: And I’m just gonna find a good example of someone that visited multiple times. Oh, this is someone that visited 2 times.
88 00:08:19.680 ⇒ 00:08:25.340 Zoran Selinger: And Bo, yeah, so you see, first time, they visited via Google.
89 00:08:26.430 ⇒ 00:08:30.190 Zoran Selinger: campaign, particular campaign. Let me just, check…
90 00:08:31.540 ⇒ 00:08:37.850 Zoran Selinger: Yes, so they visited at 9pm, I mean, European time.
91 00:08:39.360 ⇒ 00:08:41.699 Zoran Selinger: via Google, okay?
92 00:08:41.900 ⇒ 00:08:43.919 Luke Scorziell: And then they returned.
93 00:08:44.360 ⇒ 00:08:48.059 Zoran Selinger: an hour and a half later, via Catalis.
94 00:08:48.410 ⇒ 00:08:59.069 Zoran Selinger: Basically, from a… from a… affiliate, right, from, let’s say, Forbes.
95 00:08:59.340 ⇒ 00:09:00.640 Luke Scorziell: There’s a catalog.
96 00:09:00.640 ⇒ 00:09:07.469 Zoran Selinger: from an affiliate, so that means they clicked a display ad, a visual ad.
97 00:09:09.410 ⇒ 00:09:11.820 Zoran Selinger: And they actually transacted at that time.
98 00:09:14.520 ⇒ 00:09:16.709 Luke Scorziell: so now I can attribute.
99 00:09:16.710 ⇒ 00:09:18.179 Zoran Selinger: First time they visited?
100 00:09:18.180 ⇒ 00:09:18.920 Luke Scorziell: Yeah.
101 00:09:19.170 ⇒ 00:09:30.389 Zoran Selinger: You see, first time they visited, they did not yet have anonymous IDs from Google Analytics, Mixpanel, and all of that, because they haven’t loaded the page yet.
102 00:09:30.530 ⇒ 00:09:42.259 Zoran Selinger: So they were not set up. But then, hour and a half when they visited, they have all these identifiers with them, meaning the new cookies were set up when they visited the first time here.
103 00:09:43.420 ⇒ 00:09:44.380 Zoran Selinger: Okay?
104 00:09:44.890 ⇒ 00:09:51.259 Zoran Selinger: So you can imagine now, some people visit 10 times before they purchase, and we can now say, okay.
105 00:09:51.460 ⇒ 00:09:54.140 Zoran Selinger: Let’s do… you know what? So, this is…
106 00:09:54.690 ⇒ 00:10:02.550 Zoran Selinger: the definition of attribution, okay? So, we know that this transaction is worth $500.
107 00:10:03.920 ⇒ 00:10:09.890 Zoran Selinger: So, who do we want to give this $500 to? Google or Catalyst?
108 00:10:12.140 ⇒ 00:10:15.660 Zoran Selinger: This is what we’re talking about when we’re talking about attribution.
109 00:10:15.980 ⇒ 00:10:21.510 Luke Scorziell: But then we could… so then you could argue that, well, if they hadn’t seen the Google ad first.
110 00:10:21.920 ⇒ 00:10:26.029 Luke Scorziell: then maybe they wouldn’t have been as inclined to click into the catalyst.
111 00:10:26.770 ⇒ 00:10:32.610 Zoran Selinger: But yeah, but maybe if they… if they never click on Catalyst, maybe they would never convert.
112 00:10:34.660 ⇒ 00:10:35.170 Zoran Selinger: forever.
113 00:10:35.950 ⇒ 00:10:47.580 Luke Scorziell: So then when he was asking about weighting, and, like, how you wait which campaigns, so that’s… that’s what he was asking here, is, like, should I spend more on Catalysts, or should I spend more on Google?
114 00:10:49.180 ⇒ 00:10:51.590 Zoran Selinger: That’s it. This is what attribution is.
115 00:10:52.170 ⇒ 00:10:54.740 Luke Scorziell: It’s not that… yeah, okay.
116 00:10:55.250 ⇒ 00:10:57.610 Zoran Selinger: So… Technically.
117 00:10:57.880 ⇒ 00:11:05.470 Zoran Selinger: we are… with Edge, we are very close to solving it… solving it technically, but it always comes down to
118 00:11:06.720 ⇒ 00:11:10.199 Zoran Selinger: Our own rules on how we want to credit this.
119 00:11:10.610 ⇒ 00:11:11.520 Zoran Selinger: Okay.
120 00:11:13.510 ⇒ 00:11:22.789 Luke Scorziell: Seriously, like, the definitions kind of guide that we have of how we define things?
121 00:11:23.890 ⇒ 00:11:31.760 Zoran Selinger: Yeah, I mean, that’s gonna be… some companies will have a good idea of how they want to credit certain things.
122 00:11:32.020 ⇒ 00:11:43.390 Zoran Selinger: Some companies will rely on a tool like… like NordBeam or Triple Whale that will, you know, use algorithmic stuff to, you know, give them
123 00:11:43.930 ⇒ 00:11:46.919 Zoran Selinger: Whatever. It’s completely arbitrary.
124 00:11:47.470 ⇒ 00:11:48.400 Zoran Selinger: Okay?
125 00:11:50.270 ⇒ 00:11:52.299 Zoran Selinger: It is completely arbitrary.
126 00:11:53.550 ⇒ 00:11:55.680 Zoran Selinger: Before, we had algorithmic.
127 00:11:56.180 ⇒ 00:11:57.490 Zoran Selinger: attribution.
128 00:11:57.880 ⇒ 00:12:03.070 Zoran Selinger: But we still… we were… so, initially, everything was credited to…
129 00:12:03.220 ⇒ 00:12:06.050 Zoran Selinger: The first or the last interaction.
130 00:12:07.270 ⇒ 00:12:15.670 Zoran Selinger: Okay? And then we decided, okay, we want to have we wanna, we want to attribute
131 00:12:16.120 ⇒ 00:12:18.390 Zoran Selinger: To every single touchpoint.
132 00:12:19.190 ⇒ 00:12:22.310 Zoran Selinger: And then you had either linear, where you would
133 00:12:24.560 ⇒ 00:12:28.030 Zoran Selinger: Give equally to every single interaction.
134 00:12:28.650 ⇒ 00:12:30.880 Zoran Selinger: In the, in the flow.
135 00:12:31.150 ⇒ 00:12:39.590 Zoran Selinger: So, in this case, it would be 2 times 250, right? They would be credited equally.
136 00:12:40.210 ⇒ 00:12:49.449 Zoran Selinger: Then, the most popular, and the one I was mostly applying to the campaigns that I was managing, was the so-called U-shaped
137 00:12:51.160 ⇒ 00:13:00.600 Zoran Selinger: Also, there is a time decay as well. So time decay would give, give the first one the most, and then would slowly drop.
138 00:13:00.850 ⇒ 00:13:03.930 Zoran Selinger: Towards the… towards the end of the transaction.
139 00:13:04.310 ⇒ 00:13:05.320 Zoran Selinger: Okay?
140 00:13:05.600 ⇒ 00:13:12.399 Zoran Selinger: I preferred U-shaped. U-shaped is, let’s say we have, we have 10 interactions.
141 00:13:12.620 ⇒ 00:13:17.059 Zoran Selinger: I would give 40% of value to the first one.
142 00:13:17.910 ⇒ 00:13:20.220 Luke Scorziell: And 40% to the last one.
143 00:13:21.450 ⇒ 00:13:26.120 Zoran Selinger: So, the rest, 20%, I will split equally to the middle interactions.
144 00:13:28.710 ⇒ 00:13:31.869 Zoran Selinger: So the middle interactions would get really small percentage.
145 00:13:32.070 ⇒ 00:13:36.030 Zoran Selinger: But the first and the last would get 40% of the value.
146 00:13:36.140 ⇒ 00:13:36.950 Zoran Selinger: Both.
147 00:13:37.410 ⇒ 00:13:43.589 Zoran Selinger: 40% first, 40% last, and then the middle would be split equally.
148 00:13:43.730 ⇒ 00:13:44.690 Zoran Selinger: This is…
149 00:13:44.910 ⇒ 00:13:53.679 Zoran Selinger: Like, that’s… this is still valid to do today. This is very valid if we decide to do that, right?
150 00:13:54.440 ⇒ 00:13:54.880 Luke Scorziell: Yeah.
151 00:13:54.880 ⇒ 00:13:59.839 Zoran Selinger: We have ability to apply this model, these models to the data that we have.
152 00:14:00.090 ⇒ 00:14:04.470 Zoran Selinger: But we are doing it… we just use a tool called NordBeam.
153 00:14:04.940 ⇒ 00:14:09.899 Zoran Selinger: They collect this data, and they… Do whatever they do, right?
154 00:14:10.200 ⇒ 00:14:11.540 Luke Scorziell: Can you show me NordBeam?
155 00:14:11.970 ⇒ 00:14:12.520 Zoran Selinger: Yeah.
156 00:14:16.780 ⇒ 00:14:23.400 Zoran Selinger: So, it’s… It’s actually very basic. NordBeam does exactly this.
157 00:14:26.430 ⇒ 00:14:32.539 Zoran Selinger: it’s not on the edge, so they lose a lot of the data that we have, right? It’s not…
158 00:14:32.540 ⇒ 00:14:35.310 Luke Scorziell: to do clients. Like, this is all tracking requests.
159 00:14:35.460 ⇒ 00:14:36.409 Luke Scorziell: That you’re showing the.
160 00:14:36.410 ⇒ 00:14:41.939 Zoran Selinger: Yes, so these are requests, but normally will sit in Google Tag Manager, basically.
161 00:14:42.160 ⇒ 00:14:45.559 Luke Scorziell: So, it suffers from the client… client layer problems.
162 00:14:45.560 ⇒ 00:14:53.160 Zoran Selinger: Right? But let’s say they have everything, So, what they do.
163 00:14:54.090 ⇒ 00:14:56.820 Zoran Selinger: They have your traffic sources here.
164 00:14:57.470 ⇒ 00:15:05.209 Zoran Selinger: they would plug into your Google Ads, Facebook ads, and they will pull how much you’ve spent on those channels.
165 00:15:05.550 ⇒ 00:15:22.759 Zoran Selinger: And they just show you a comparison, basically. You generated this, you spent this, and then they try to, you know, do algorithmic stuff where they will tell you, oh, you should put more into Instagram, maybe less into email, right?
166 00:15:24.420 ⇒ 00:15:31.549 Zoran Selinger: So you have your, like, touch points one day, you have forecasted ROIs and stuff like that.
167 00:15:31.580 ⇒ 00:15:51.459 Zoran Selinger: So, campaign managers would come here, especially marketing managers, would come in here and look at… look at the recommendations here, and say, okay, we need to give more budget to… more budget to Pinterest, and maybe decrease the Facebook budget… budget by, you know, 15%.
168 00:15:52.800 ⇒ 00:15:55.000 Luke Scorziell: That’s…
169 00:15:55.000 ⇒ 00:16:04.150 Zoran Selinger: the whole idea of attribution, right? But if we are super, if we are super, Like…
170 00:16:04.680 ⇒ 00:16:05.970 Zoran Selinger: smart…
171 00:16:06.100 ⇒ 00:16:20.030 Zoran Selinger: we can do it ourselves. We can… a company can be… a company can have their own rules, and we can have our own analysis. We don’t need Nordbin. It just takes a lot of weight off us.
172 00:16:20.330 ⇒ 00:16:21.500 Zoran Selinger: In terms of…
173 00:16:21.850 ⇒ 00:16:29.390 Zoran Selinger: In terms of attribution, I’m not against it at all, just because those rules are pretty arbitrary.
174 00:16:29.860 ⇒ 00:16:30.680 Zoran Selinger: Okay?
175 00:16:31.500 ⇒ 00:16:39.240 Zoran Selinger: It’s really hard to say that, like, time decay model that gives to the first one and then kind of drops down.
176 00:16:39.640 ⇒ 00:16:43.340 Zoran Selinger: or U-shaped, or linear, is…
177 00:16:43.880 ⇒ 00:16:45.190 Luke Scorziell: Well, cause, like, an example.
178 00:16:45.190 ⇒ 00:16:49.770 Zoran Selinger: But one is better than the other. It’s… it’s almost impossible to say.
179 00:16:50.040 ⇒ 00:16:50.370 Luke Scorziell: Yeah.
180 00:16:50.370 ⇒ 00:16:53.540 Zoran Selinger: pretty arbitrary of what we do. The…
181 00:16:54.270 ⇒ 00:16:57.539 Luke Scorziell: As soon as you start looking at, at, at,
182 00:16:57.540 ⇒ 00:17:09.390 Zoran Selinger: attribution in multi-touch. Basically, if you start crediting multiple Multiple sessions, interactions with credit.
183 00:17:09.650 ⇒ 00:17:17.410 Zoran Selinger: you just won. You’ve done… you’ve done your job, right? As long as you don’t just credit one interaction.
184 00:17:17.619 ⇒ 00:17:18.380 Zoran Selinger: I…
185 00:17:19.089 ⇒ 00:17:22.409 Luke Scorziell: Yeah, because, like, in theory, if you’re doing…
186 00:17:25.419 ⇒ 00:17:28.109 Luke Scorziell: Like, if someone sees you on Pinterest.
187 00:17:28.209 ⇒ 00:17:30.229 Luke Scorziell: And this is the first time they’ve seen you.
188 00:17:30.339 ⇒ 00:17:32.049 Luke Scorziell: And then they Google you.
189 00:17:32.519 ⇒ 00:17:39.769 Luke Scorziell: And then… so then they find you through organic search, and then they maybe see you again on Pinterest, or see you on Meta.
190 00:17:40.169 ⇒ 00:17:43.829 Luke Scorziell: Like, You would get less…
191 00:17:44.999 ⇒ 00:17:54.559 Luke Scorziell: like, maybe the Google search would get less attribution under the U-shaped model than, like, the original Pinterest ad, even though, like, I don’t know, maybe…
192 00:17:55.369 ⇒ 00:18:00.329 Luke Scorziell: Like… I don’t know, like, I guess if they directly searched you, then…
193 00:18:00.330 ⇒ 00:18:03.149 Zoran Selinger: You just started guessing what’s in people’s heads.
194 00:18:03.540 ⇒ 00:18:04.300 Zoran Selinger: Right?
195 00:18:04.500 ⇒ 00:18:05.260 Luke Scorziell: Huh, haha.
196 00:18:05.260 ⇒ 00:18:10.250 Zoran Selinger: Who’s to say that the first interaction impacted me the most?
197 00:18:11.460 ⇒ 00:18:14.579 Luke Scorziell: Maybe you just scrolled past it and didn’t even notice it.
198 00:18:15.400 ⇒ 00:18:23.569 Zoran Selinger: I noticed it, it’s fine. But then, your organic listing on Google really impresses me.
199 00:18:23.870 ⇒ 00:18:28.430 Zoran Selinger: And it gave me… Just the right text.
200 00:18:28.550 ⇒ 00:18:30.320 Zoran Selinger: that I wanted to see.
201 00:18:31.820 ⇒ 00:18:37.620 Zoran Selinger: And that’s… that’s when… that… that made the most impact in my… in my journey.
202 00:18:38.080 ⇒ 00:18:42.279 Zoran Selinger: To the transaction. It’s… this is what I’m saying, this is…
203 00:18:42.990 ⇒ 00:18:47.910 Zoran Selinger: no one solved this yet. We’ve been at it for over a decade now.
204 00:18:48.880 ⇒ 00:18:50.790 Zoran Selinger: No one solved it yet.
205 00:18:50.790 ⇒ 00:18:51.250 Luke Scorziell: Okay.
206 00:18:52.530 ⇒ 00:19:00.669 Zoran Selinger: Because it’s very, very arbitrary. So as long as… like I said, for me, as long as you start creating multi-touch.
207 00:19:01.260 ⇒ 00:19:01.590 Luke Scorziell: Yeah.
208 00:19:01.590 ⇒ 00:19:08.450 Zoran Selinger: So, as long as you give credit to multiple interactions in the, let’s call it, conversion path.
209 00:19:08.870 ⇒ 00:19:10.120 Zoran Selinger: I’m fine with it.
210 00:19:10.810 ⇒ 00:19:13.119 Luke Scorziell: Cause, cause the alternative could be, like.
211 00:19:13.720 ⇒ 00:19:21.279 Luke Scorziell: like, you see the Pinterest ad, you see the Google, ad, you see the Meta ad, but then, like.
212 00:19:22.580 ⇒ 00:19:29.109 Luke Scorziell: Most people who see the… who interact with the TikTok ad only interact with that one and then drop off.
213 00:19:29.560 ⇒ 00:19:32.809 Luke Scorziell: And then they don’t buy anything, so then maybe you could say…
214 00:19:33.010 ⇒ 00:19:40.320 Luke Scorziell: oh, it looks like TikTok is… is… there’s some… it might not be TikTok as a platform as bad, but maybe the ad that we’re running on TikTok
215 00:19:40.710 ⇒ 00:19:42.160 Luke Scorziell: is not great.
216 00:19:42.620 ⇒ 00:19:45.580 Zoran Selinger: Yeah, and… Exactly, exactly.
217 00:19:45.580 ⇒ 00:19:47.280 Luke Scorziell: It’s not resonating in the way that, like.
218 00:19:47.480 ⇒ 00:19:51.040 Luke Scorziell: the Pinterest ad… I’m just making this up, obviously, but the Pinterest ad is…
219 00:19:51.160 ⇒ 00:19:56.140 Luke Scorziell: Because typically, after people see the Pinterest tab, then they go and do these few.
220 00:19:56.790 ⇒ 00:19:59.749 Luke Scorziell: interactions, or, you know, something kind of like that, I guess?
221 00:20:00.300 ⇒ 00:20:03.900 Zoran Selinger: Yeah, yeah, but like, like I said, this is…
222 00:20:05.010 ⇒ 00:20:10.319 Zoran Selinger: It’s very susceptible to how you interpret it.
223 00:20:11.770 ⇒ 00:20:12.830 Luke Scorziell: Yeah, which.
224 00:20:12.830 ⇒ 00:20:20.200 Zoran Selinger: And then it’s what the… a lot of guesswork. It’s just so much, so much guesswork in it.
225 00:20:20.340 ⇒ 00:20:28.219 Zoran Selinger: But… It is a central problem that we absolutely need, to deal with.
226 00:20:28.740 ⇒ 00:20:30.619 Zoran Selinger: It is… it is the key.
227 00:20:32.080 ⇒ 00:20:32.720 Luke Scorziell: Huh.
228 00:20:32.720 ⇒ 00:20:39.079 Zoran Selinger: And I, like… like I said, I don’t think,
229 00:20:39.520 ⇒ 00:20:47.520 Zoran Selinger: You will not make many mistakes, in my experience, if you are crediting
230 00:20:48.040 ⇒ 00:20:51.349 Zoran Selinger: Multiple touches, you will mostly be fined.
231 00:20:51.950 ⇒ 00:20:59.500 Zoran Selinger: If you’re in that mindset, you will likely credit, at least linear.
232 00:20:59.930 ⇒ 00:21:01.320 Zoran Selinger: Which is fine.
233 00:21:01.960 ⇒ 00:21:17.009 Zoran Selinger: Your… if you’re crediting, like, a linear, the same value for all the touchpoints, a lot of your best channels will… will convert from the first session. So your best channels will still get credited with more.
234 00:21:17.500 ⇒ 00:21:24.849 Zoran Selinger: Right? So you will still see them winning, and that’s how you will split your budget.
235 00:21:25.510 ⇒ 00:21:25.930 Luke Scorziell: Because then…
236 00:21:26.780 ⇒ 00:21:32.939 Luke Scorziell: Yeah, then if you’re putting equal spend, or equal attribution to each platform, but then you start to see
237 00:21:33.110 ⇒ 00:21:40.370 Luke Scorziell: Well, everyone sees our Instagram campaign and then purchases, so… Or, like…
238 00:21:40.880 ⇒ 00:21:42.600 Luke Scorziell: Maybe I’m getting that a little off.
239 00:21:42.780 ⇒ 00:21:50.439 Luke Scorziell: Then you could see maybe the return on ad spend from Instagram is higher.
240 00:21:50.910 ⇒ 00:21:55.910 Luke Scorziell: So then let’s just… we can assume let’s put more into Instagram than,
241 00:21:55.910 ⇒ 00:21:59.979 Zoran Selinger: Yeah, obviously, everything’s about that return on that spend.
242 00:21:59.980 ⇒ 00:22:02.560 Luke Scorziell: Everything’s above that, so… Okay.
243 00:22:03.120 ⇒ 00:22:06.839 Luke Scorziell: Okay, this is… yeah, this is really helpful. Thanks for… for walking through this.
244 00:22:06.840 ⇒ 00:22:09.830 Zoran Selinger: It’s a complicated topic that is…
245 00:22:09.960 ⇒ 00:22:22.099 Zoran Selinger: We can talk about it for hours, and we will not be smarter for it. That’s… that’s one of those things, because there’s so much arbitrary decisions that we could make there, that you cannot…
246 00:22:22.360 ⇒ 00:22:25.780 Zoran Selinger: Really prove that they’re right or wrong at all.
247 00:22:27.500 ⇒ 00:22:35.420 Zoran Selinger: what I usually pushed for is, let’s have… let’s agree on the attribution model, and let’s just do it.
248 00:22:36.280 ⇒ 00:22:38.900 Zoran Selinger: Let us do it. It has to be multi-touch.
249 00:22:39.660 ⇒ 00:22:42.129 Zoran Selinger: Right? It has to be multi-touch.
250 00:22:43.690 ⇒ 00:22:47.369 Zoran Selinger: And I just implement it, and that’s where we go off, and…
251 00:22:50.960 ⇒ 00:22:59.900 Zoran Selinger: And that will work. That will work. You only make huge, huge mistakes in… In…
252 00:23:00.350 ⇒ 00:23:03.549 Zoran Selinger: In attribution, when you only create first or the last.
253 00:23:03.960 ⇒ 00:23:11.609 Luke Scorziell: And is this one of the more profitable areas of the Brain Forge overall? Or I don’t know if you know that, but, like, is… because obviously.
254 00:23:11.610 ⇒ 00:23:12.050 Zoran Selinger: Yeah, so let’s.
255 00:23:12.050 ⇒ 00:23:14.580 Luke Scorziell: This is one of a variety of services that we offer.
256 00:23:14.850 ⇒ 00:23:28.470 Zoran Selinger: everything will come down to, to the attribution, yes. Everything will basically come down to the attribution. When we talk about marketing, of course. So, ops will be, you know, different.
257 00:23:28.470 ⇒ 00:23:38.229 Zoran Selinger: That won’t have anything to do with traffic sources and campaigns. So when… but when we talk about marketing, everything will come down to this.
258 00:23:38.780 ⇒ 00:23:39.780 Zoran Selinger: Everything.
259 00:23:42.830 ⇒ 00:23:43.540 Zoran Selinger: Yeah.
260 00:23:45.440 ⇒ 00:23:50.569 Luke Scorziell: And then, real quick, if you have a sec, can you just open up Mixpanel, just so I can see?
261 00:23:51.250 ⇒ 00:23:52.390 Luke Scorziell: Like, what is it?
262 00:23:52.390 ⇒ 00:23:57.980 Zoran Selinger: I can. I’m not a… I’m not very familiar with Mixpanel, by the way.
263 00:23:58.340 ⇒ 00:23:59.090 Luke Scorziell: Okay.
264 00:24:00.910 ⇒ 00:24:02.990 Zoran Selinger: That’s the tool I’ve used the least.
265 00:24:03.910 ⇒ 00:24:08.039 Luke Scorziell: But it… It’s, like, a visualer, or a visualizer of…
266 00:24:08.040 ⇒ 00:24:13.069 Zoran Selinger: Very similar to… to… It’s mostly similar to amplitude.
267 00:24:13.950 ⇒ 00:24:28.890 Zoran Selinger: Because MixedPanel is your, kind of, product analytics. We can treat websites as products, right? Sometimes, some people like using, using, product, analytics on websites.
268 00:24:29.700 ⇒ 00:24:45.270 Zoran Selinger: the goal… do you know, kind of, general difference between… between product and… and, kind of, Google Analytics? What’s the… the difference? The product is mostly made… product analytics is made to see how people follow through your website.
269 00:24:45.430 ⇒ 00:24:47.369 Zoran Selinger: So, where they actually click.
270 00:24:47.650 ⇒ 00:24:48.000 Luke Scorziell: Yeah.
271 00:24:48.000 ⇒ 00:24:58.990 Zoran Selinger: But it’s not necessarily made to answer where people came from, what the campaigns are. They’re not here to solve the attribution problem for you.
272 00:24:59.090 ⇒ 00:25:12.110 Zoran Selinger: Okay? Whereas Google Analytics and NordBeam Triple Whale are mostly attribution tools. They are not necessarily there to tell you where people clicked on your website.
273 00:25:12.770 ⇒ 00:25:16.689 Zoran Selinger: But where they came from, Where they converted?
274 00:25:16.910 ⇒ 00:25:20.019 Zoran Selinger: And whether that traffic is profitable for you or not.
275 00:25:21.300 ⇒ 00:25:24.789 Zoran Selinger: So there are those two types. Most companies that
276 00:25:25.200 ⇒ 00:25:27.399 Zoran Selinger: that care about this stuff will have
277 00:25:27.670 ⇒ 00:25:33.650 Zoran Selinger: both, right, in place. They will have, you know, your mix panel or amplitude, and they will have
278 00:25:33.790 ⇒ 00:25:37.159 Zoran Selinger: still NordBeam, Triple Whale, Google Analytics, whatever.
279 00:25:39.050 ⇒ 00:25:44.999 Luke Scorziell: So the product analytics side is more like, if I want to see which products are most profitable.
280 00:25:45.380 ⇒ 00:25:46.779 Luke Scorziell: And who’s purchasing what?
281 00:25:46.780 ⇒ 00:25:55.410 Zoran Selinger: It goes… it goes further than that. They… they literally go down to the button level, like, there’s a…
282 00:25:55.410 ⇒ 00:25:55.790 Luke Scorziell: Oh.
283 00:25:55.790 ⇒ 00:26:00.280 Zoran Selinger: You know, add to cart button on this particular product.
284 00:26:00.840 ⇒ 00:26:16.960 Zoran Selinger: how many times someone clicked on that button in the last 30 days, and what they’ve done after they clicked that button? Did they go… proceed straight to the checkout, or did they browse more products, edit more products before they proceeded to the checkout, right?
285 00:26:16.960 ⇒ 00:26:22.670 Luke Scorziell: The product analytics is tracking what’s happening on the website, and that’s maybe more, like, more, like, user interface, user experience.
286 00:26:22.670 ⇒ 00:26:23.450 Zoran Selinger: Exactly.
287 00:26:23.450 ⇒ 00:26:27.890 Luke Scorziell: Optimization comes in, or, like, Optimizely, I don’t know if you’ve heard of them.
288 00:26:27.890 ⇒ 00:26:42.520 Zoran Selinger: Yes, yes, Optimizely is for A-B testing, right? Yeah. So, you would likely get hypotheses for A-B testing from a product analytics tool. So you will dig in around, you see, okay, there…
289 00:26:43.050 ⇒ 00:26:57.779 Zoran Selinger: there might be a friction here, and they want to test it. You create device a test in Optimizely or VWO, and then, yeah, you use Optimizely for that kind of stuff. So, it’s…
290 00:26:59.080 ⇒ 00:27:04.080 Zoran Selinger: It’s a very important part of the modern stack, is the A-B testing part.
291 00:27:04.270 ⇒ 00:27:05.909 Zoran Selinger: And Eden does a lot.
292 00:27:06.980 ⇒ 00:27:09.330 Luke Scorziell: And Amplitude is one of our partners, right?
293 00:27:10.040 ⇒ 00:27:15.590 Zoran Selinger: Yes, yes, amplitude, I know more about amplitude, in particular.
294 00:27:16.510 ⇒ 00:27:19.350 Zoran Selinger: Especially how bad their customer service is.
295 00:27:23.100 ⇒ 00:27:24.769 Zoran Selinger: Very, very similar.
296 00:27:29.600 ⇒ 00:27:32.939 Luke Scorziell: And their attribution, or more product analytics?
297 00:27:32.940 ⇒ 00:27:34.780 Zoran Selinger: This is Product Analytics.
298 00:27:35.180 ⇒ 00:27:36.030 Luke Scorziell: Okay.
299 00:27:42.700 ⇒ 00:27:53.739 Zoran Selinger: Yeah, so this is a client that… it’s not actually ours. I coded a custom solution for them, and we kind of sold it to them, and trying to get them
300 00:27:54.020 ⇒ 00:27:57.610 Zoran Selinger: To… to do more… more work with us,
301 00:27:57.890 ⇒ 00:28:10.950 Zoran Selinger: So, yeah, very similar. You have your live events, where people click, this and that, you define, you see, people click here, click there, you might have your heat map, session replays, stuff like that.
302 00:28:13.950 ⇒ 00:28:14.530 Luke Scorziell: Huh.
303 00:28:18.020 ⇒ 00:28:23.290 Zoran Selinger: So that’s Amplitude. Amplitude is… is more for… for techy people.
304 00:28:25.810 ⇒ 00:28:31.240 Zoran Selinger: But MixedPanel is a little bit more, kind of, beginner-friendly than Amplitude.
305 00:28:32.360 ⇒ 00:28:37.259 Zoran Selinger: So it’s usually one or the other when it comes to product analytics.
306 00:28:38.790 ⇒ 00:28:39.440 Luke Scorziell: Yeah.
307 00:28:42.050 ⇒ 00:28:45.070 Luke Scorziell: So the attribution is getting them to the website.
308 00:28:45.820 ⇒ 00:28:50.599 Luke Scorziell: Product analytics is… Finding the optimal way for them to navigate the website.
309 00:28:51.460 ⇒ 00:29:00.670 Luke Scorziell: And then… which… and on some level, we’re hypothesizing across everything, because… We don’t know if…
310 00:29:01.000 ⇒ 00:29:08.050 Luke Scorziell: All of our campaigns are doing great, but there’s some issue with the website that’s causing people to not click into purchase.
311 00:29:08.260 ⇒ 00:29:12.620 Luke Scorziell: and so then we would need this, you know, okay.
312 00:29:15.090 ⇒ 00:29:20.340 Zoran Selinger: Yeah, there’s a lot. There’s a lot. There’s a lot of moving pieces there.
313 00:29:20.780 ⇒ 00:29:27.019 Zoran Selinger: But when it comes to, kind of, the groups of tools, you really have…
314 00:29:27.130 ⇒ 00:29:34.140 Zoran Selinger: You, you really have those few groups of tools that everyone uses, and now we kind of…
315 00:29:34.800 ⇒ 00:29:39.069 Zoran Selinger: We are layered under… the edge layer is under them.
316 00:29:39.250 ⇒ 00:29:41.239 Zoran Selinger: And kind of benefits.
317 00:29:41.800 ⇒ 00:29:42.859 Zoran Selinger: All of it.
318 00:29:43.180 ⇒ 00:29:51.910 Zoran Selinger: But you have to have good data modelers, data engineers, to turn, you know, your…
319 00:29:52.020 ⇒ 00:29:55.540 Zoran Selinger: warehouse into some really good Tableau reports.
320 00:29:56.760 ⇒ 00:30:03.690 Luke Scorziell: Yeah, yeah, because it all starts on the data level, so if you have disorganized… a disorganized warehouse.
321 00:30:03.690 ⇒ 00:30:05.020 Zoran Selinger: Absolutely.
322 00:30:05.020 ⇒ 00:30:09.230 Luke Scorziell: More definitions, then the rest of the stuff’s gonna be screwy.
323 00:30:10.000 ⇒ 00:30:14.340 Zoran Selinger: Let me see if I have a link for you… I don’t… Oh, yeah, I do.
324 00:30:14.760 ⇒ 00:30:19.820 Zoran Selinger: So, if you go… Putting it in…
325 00:30:24.340 ⇒ 00:30:29.880 Zoran Selinger: in Slack for you. So you’ll see a link to a LinkedIn post.
326 00:30:30.010 ⇒ 00:30:32.650 Zoran Selinger: It’s a Martech report.
327 00:30:32.830 ⇒ 00:30:34.779 Zoran Selinger: for 2026.
328 00:30:35.470 ⇒ 00:30:36.930 Luke Scorziell: Oh, how are you?
329 00:30:37.490 ⇒ 00:30:46.670 Zoran Selinger: And it’s all about AI, and how AI is used in marketing, but… the number one.
330 00:30:47.210 ⇒ 00:30:51.730 Zoran Selinger: friction, number one problem with AI, adoption.
331 00:30:51.910 ⇒ 00:30:56.919 Zoran Selinger: in marketing, is… The lack of quality data.
332 00:30:57.090 ⇒ 00:31:00.070 Zoran Selinger: And that’s exactly what Edge Layer solves.
333 00:31:02.560 ⇒ 00:31:12.619 Zoran Selinger: So, it’s a huge report. It’s a huge report of 120 pages, and on one page, you’ll see, kind of, the biggest frictions.
334 00:31:13.340 ⇒ 00:31:20.580 Zoran Selinger: That they… that companies deal with. And really, the biggest problem is the lack of good quality data.
335 00:31:26.130 ⇒ 00:31:27.000 Luke Scorziell: Okay.
336 00:31:27.250 ⇒ 00:31:29.070 Zoran Selinger: And that’s what we solve with Edge.
337 00:31:29.350 ⇒ 00:31:34.809 Zoran Selinger: Not just with Edge, but everything that we do, because guys are great, if you give them…
338 00:31:35.050 ⇒ 00:31:41.500 Zoran Selinger: any data, they will… they will turn it into insights. They’re really good at it.
339 00:31:42.320 ⇒ 00:31:44.170 Luke Scorziell: Okay.
340 00:31:44.340 ⇒ 00:31:51.240 Luke Scorziell: Cool. Well, this is… this is great. Thank you, Zoran. You should be our Chief Educational Officer.
341 00:31:51.650 ⇒ 00:32:11.610 Zoran Selinger: I’m not sure, not sure about that. I mean, I’ve done a lot in my… I’ve done a lot of training sessions, and I’ve spoke at conferences, and so I am somehow used to it. It’s just been a while. It’s been a while, though.
342 00:32:11.610 ⇒ 00:32:12.240 Luke Scorziell: Yeah, yeah.
343 00:32:12.240 ⇒ 00:32:16.140 Zoran Selinger: a lot while I was… when I was living in Dublin, Ireland.
344 00:32:16.800 ⇒ 00:32:17.510 Luke Scorziell: Oh, cool.
345 00:32:17.510 ⇒ 00:32:21.200 Zoran Selinger: But that was, you know, 8 years ago now.
346 00:32:21.200 ⇒ 00:32:21.880 Luke Scorziell: Yeah.
347 00:32:21.980 ⇒ 00:32:22.930 Zoran Selinger: Like…
348 00:32:23.400 ⇒ 00:32:28.029 Luke Scorziell: That’s… yeah, and did you grow up in Croatia, or…
349 00:32:28.030 ⇒ 00:32:33.099 Zoran Selinger: Yeah, yeah, yeah, yeah. I have been my whole life here, just had a
350 00:32:33.560 ⇒ 00:32:37.479 Zoran Selinger: kind of three and a half years in Dublin.
351 00:32:37.800 ⇒ 00:32:43.140 Zoran Selinger: I started freelancing immediately, like, in college, doing marketing stuff.
352 00:32:43.740 ⇒ 00:32:52.910 Zoran Selinger: So I… and then I realized, okay, I should really… learn from… the best.
353 00:32:53.110 ⇒ 00:32:53.540 Luke Scorziell: Yeah.
354 00:32:53.550 ⇒ 00:33:02.300 Zoran Selinger: decided that okay, how far am I okay with going? And I decided Ireland is the place to go.
355 00:33:03.290 ⇒ 00:33:06.630 Zoran Selinger: And, I mean… Oh, shit.
356 00:33:06.870 ⇒ 00:33:14.290 Zoran Selinger: Yeah, I applied to a company that is the best in Europe, and They even won Worlds.
357 00:33:15.050 ⇒ 00:33:17.990 Zoran Selinger: Because you have industry awards for marketing.
358 00:33:19.550 ⇒ 00:33:32.180 Zoran Selinger: actually, the campaigns and, campaign that I worked for, worked on, won, literally, the world championship in Search Engine Land Awards.
359 00:33:32.780 ⇒ 00:33:33.220 Luke Scorziell: Oh, wow.
360 00:33:33.220 ⇒ 00:33:38.449 Zoran Selinger: one year. So we beat, Super Bowl campaigns.
361 00:33:38.450 ⇒ 00:33:38.970 Luke Scorziell: Nope.
362 00:33:38.970 ⇒ 00:33:41.349 Zoran Selinger: With, with what we’ve done.
363 00:33:42.920 ⇒ 00:33:49.849 Zoran Selinger: For us. So, I’ve done really good work there, and… and people in Wolverine Digital are super smart.
364 00:33:49.900 ⇒ 00:34:03.030 Zoran Selinger: They… they don’t hire… they… they basically only hire on intelligence. They don’t care about what you… what school, or whatever you finished. They have, like, electrical engineers in there.
365 00:34:04.700 ⇒ 00:34:10.089 Zoran Selinger: They don’t care, like, if you’re smart enough, you can be here, we’ll train you, and…
366 00:34:10.630 ⇒ 00:34:12.880 Zoran Selinger: You’ll do phenomenal campaigns.
367 00:34:13.560 ⇒ 00:34:15.729 Luke Scorziell: And I was there, kind of.
368 00:34:16.280 ⇒ 00:34:29.369 Zoran Selinger: I’ve run campaigns, I’ve ran campaigns, but I was mostly interested in doing cool technical stuff for campaigns, and yeah, I’ve done stuff like bidding based on weather, for example, and…
369 00:34:30.579 ⇒ 00:34:32.679 Luke Scorziell: So you weren’t joking about the…
370 00:34:33.300 ⇒ 00:34:34.949 Zoran Selinger: No, no, no, that’s…
371 00:34:35.199 ⇒ 00:34:44.980 Zoran Selinger: I’ve done that. I’ve also done, like, based on, like, currency conversion rates, really, really interesting stuff based on that, and…
372 00:34:46.320 ⇒ 00:35:02.520 Zoran Selinger: Wow. But I still manage millions every year in ad budget myself, even though it’s not really my thing, it just I kind of landed into that role, and I just accepted, okay, I’m gonna run campaigns myself.
373 00:35:02.760 ⇒ 00:35:09.280 Zoran Selinger: I’ve done good there as well, but I was most… mostly interested in Martech, you know?
374 00:35:09.780 ⇒ 00:35:10.760 Luke Scorziell: Yeah.
375 00:35:10.820 ⇒ 00:35:11.980 Zoran Selinger: Yeah, yeah.
376 00:35:12.240 ⇒ 00:35:17.469 Luke Scorziell: Okay, well, yeah, I’ll read that report, and then maybe I’ll, ping you with some questions, and…
377 00:35:18.100 ⇒ 00:35:22.029 Luke Scorziell: And whatnot. Dude, I’m looking at pictures of Croatia, it’s beautiful.
378 00:35:23.190 ⇒ 00:35:26.020 Zoran Selinger: Yes, yes, it is, it is.
379 00:35:26.600 ⇒ 00:35:28.429 Luke Scorziell: Or, I mean, the coast, yeah, so…
380 00:35:28.430 ⇒ 00:35:36.509 Zoran Selinger: People do visit a lot. I’ve heard a lot of my clients, people that I’ve worked with over the years.
381 00:35:36.880 ⇒ 00:35:39.439 Zoran Selinger: People do fly a lot here.
382 00:35:40.190 ⇒ 00:35:40.780 Luke Scorziell: Huh.
383 00:35:41.570 ⇒ 00:35:42.150 Zoran Selinger: Yeah.
384 00:35:43.240 ⇒ 00:35:48.500 Luke Scorziell: Sweet, well, I’ll let you, I’ll let you off. Thanks so much for the time. Super helpful.
385 00:35:48.670 ⇒ 00:36:04.780 Zoran Selinger: No worries, I… I mean, we’ll… I’m… I’m guessing we’ll… we’ll work more, together. It’s important that we… that, you understand, and I… I also… that I understand exactly what your roles, roles are, you know,
386 00:36:04.960 ⇒ 00:36:09.649 Zoran Selinger: I think we’ll… We can do some good work if we achieve that.
387 00:36:10.010 ⇒ 00:36:12.059 Luke Scorziell: Yeah, yeah, yeah. I’ll keep you in the…
388 00:36:12.060 ⇒ 00:36:21.870 Zoran Selinger: But it’s clear to me now, from this first meeting, that, you scoping kind of the ICP and all that, it’s super important.
389 00:36:22.610 ⇒ 00:36:23.360 Zoran Selinger: role.
390 00:36:23.780 ⇒ 00:36:35.619 Zoran Selinger: I thought initially that you might be the one that’s going to present everything, and I’m just there for technical questions. I have no idea exactly what’s gonna happen.
391 00:36:35.620 ⇒ 00:36:38.599 Luke Scorziell: I think it’s, Learned by… Learned by Fire.
392 00:36:38.600 ⇒ 00:36:41.980 Zoran Selinger: Yeah, no, that’s fine, I’ve done that a lot in my career.
393 00:36:42.190 ⇒ 00:36:46.199 Luke Scorziell: Yeah, no, I think, I mean, we’re getting the ICP
394 00:36:46.730 ⇒ 00:36:59.189 Luke Scorziell: toned out, and then I guess, like, I’m… I’m still learning how Robert works, and kind of how he thinks, and so I think, as… as well as obviously trying to absorb the technical side of the platform.
395 00:36:59.430 ⇒ 00:37:03.649 Luke Scorziell: Trying to also absorb how we think about who to work with, and…
396 00:37:03.770 ⇒ 00:37:07.360 Luke Scorziell: And whatnot, but I think it all works together, right? Because if I don’t understand…
397 00:37:07.640 ⇒ 00:37:12.479 Luke Scorziell: The very base… the building blocks of what you just showed me, then it’s gonna be hard to…
398 00:37:12.660 ⇒ 00:37:14.220 Luke Scorziell: To gauge.
399 00:37:14.220 ⇒ 00:37:28.770 Zoran Selinger: Absolutely, absolutely. I’m here for any of your questions, just let me know. We can do asynchronous stuff, like with Loom, we can do just typing, if I’m not here, so…
400 00:37:29.630 ⇒ 00:37:42.460 Zoran Selinger: Yeah, if you ping me, like, you can ping me any time, day or night. If I’m not here, I’m gonna reply to you when I can, and that should be… that should be fine, right?
401 00:37:42.690 ⇒ 00:37:47.829 Zoran Selinger: So just, yeah, don’t hesitate. Whenever you have a question, ping me.
402 00:37:48.520 ⇒ 00:37:50.429 Zoran Selinger: Do a loom, if you want.
403 00:37:50.620 ⇒ 00:37:59.480 Zoran Selinger: send a link to me, I’ll have a look, and I’ll reply when I can, and we’ll get there, you’ll be comfortable with this, don’t worry about it.
404 00:37:59.720 ⇒ 00:38:02.780 Luke Scorziell: Sweet. Sweet. No, thank you, I appreciate that.
405 00:38:02.780 ⇒ 00:38:03.290 Zoran Selinger: Thank you.
406 00:38:03.500 ⇒ 00:38:04.790 Luke Scorziell: Alright, Zora.
407 00:38:04.790 ⇒ 00:38:05.510 Zoran Selinger: Yep.
408 00:38:05.520 ⇒ 00:38:06.480 Luke Scorziell: Goodbye.