Meeting Title: ABC Discovery Timeline Gantt Date: 2026-01-14 Meeting participants: Zoran Selinger, Amber Lin
WEBVTT
1 00:01:07.220 ⇒ 00:01:10.170 Amber Lin: Hi, someone, let me check if Utam’s coming.
2 00:01:14.100 ⇒ 00:01:14.750 Zoran Selinger: Bye.
3 00:01:15.180 ⇒ 00:01:16.640 Zoran Selinger: Sure, sure.
4 00:03:27.280 ⇒ 00:03:29.909 Zoran Selinger: What’s the purpose of this meeting, exactly?
5 00:03:31.870 ⇒ 00:03:45.800 Amber Lin: It’s mostly to look at the Gantt chart for the discovery workflow. I think we want to add the timelines to the tasks available. I don’t think…
6 00:03:46.040 ⇒ 00:03:53.439 Amber Lin: I asked Utam if he wants you to be here, so I think we should wait another 5 minutes. If not, I think feel free to hop off.
7 00:03:55.380 ⇒ 00:03:56.770 Zoran Selinger: Yeah, okay, cool.
8 00:03:56.920 ⇒ 00:04:01.779 Amber Lin: Yeah, we can get started on it if we want.
9 00:04:02.500 ⇒ 00:04:07.520 Amber Lin: Let’s see… Here is… Hmm.
10 00:04:12.940 ⇒ 00:04:22.670 Amber Lin: Here’s the Gantt chart. Anything you see here that we need to add, for example, like, access, I remember you said you want GTM.
11 00:04:22.830 ⇒ 00:04:24.130 Amber Lin: Access…
12 00:04:24.320 ⇒ 00:04:25.869 Zoran Selinger: Actually, we got it.
13 00:04:26.200 ⇒ 00:04:26.700 Amber Lin: Oh, okay.
14 00:04:26.700 ⇒ 00:04:27.640 Zoran Selinger: caught it.
15 00:04:28.140 ⇒ 00:04:30.700 Zoran Selinger: I’ll confirm that with you.
16 00:04:35.940 ⇒ 00:04:45.009 Amber Lin: And then… For example, for acquisition, or for conversion, or anything, other tasks you want to add here?
17 00:04:47.860 ⇒ 00:04:51.209 Zoran Selinger: So, invitations from ABC.
18 00:04:51.470 ⇒ 00:04:53.680 Zoran Selinger: For GTM. We got it.
19 00:04:54.030 ⇒ 00:04:54.680 Amber Lin: Okay.
20 00:05:08.140 ⇒ 00:05:14.989 Amber Lin: Would GTM analysis fall under acquisition, or would it be, like, a separate marketing…
21 00:05:14.990 ⇒ 00:05:19.220 Zoran Selinger: It’s… it’s more… so I would call that.
22 00:05:20.190 ⇒ 00:05:23.150 Zoran Selinger: A technical tracking implementation.
23 00:05:27.590 ⇒ 00:05:36.620 Zoran Selinger: So, under that, we would have, we would have, basically, GA4, or it…
24 00:05:38.670 ⇒ 00:05:41.699 Zoran Selinger: We would have Google Time Manager on it.
25 00:05:43.440 ⇒ 00:05:49.550 Zoran Selinger: we would have a GA4 e-commerce tracking implementation.
26 00:05:52.700 ⇒ 00:05:54.339 Amber Lin: I see. I don’t know…
27 00:05:54.340 ⇒ 00:05:58.370 Zoran Selinger: So those are the items I know that we could do, we should.
28 00:05:58.370 ⇒ 00:05:59.810 Amber Lin: Cool. Okay.
29 00:06:00.120 ⇒ 00:06:14.739 Amber Lin: Any other, like, non-implementation stuff we can do? Because I don’t think we’re doing the actual work yet, we’re just looking at stuff and telling them, hey, these are possible stuff you can do.
30 00:06:16.040 ⇒ 00:06:22.120 Zoran Selinger: I mean, everything that’s in that document Is what we’ve done.
31 00:06:22.960 ⇒ 00:06:26.940 Zoran Selinger: Actually, wait, I do have… did I have one thing?
32 00:06:27.350 ⇒ 00:06:33.370 Zoran Selinger: Pull channel comparisons over a longer period of time. Yeah, so I’ve done that today.
33 00:06:33.470 ⇒ 00:06:37.749 Zoran Selinger: So if you look at the link that I sent in the channel.
34 00:06:38.100 ⇒ 00:06:44.039 Amber Lin: Yeah, I saw that, I saw that one. Actually, the link is to the previous doc, so I don’t know if you made it.
35 00:06:44.040 ⇒ 00:06:51.529 Zoran Selinger: Yes, but to a particular, particular, section that is new to the document.
36 00:06:51.530 ⇒ 00:06:52.470 Amber Lin: Okay.
37 00:06:52.630 ⇒ 00:06:54.349 Amber Lin: Cool, foam.
38 00:06:54.350 ⇒ 00:06:58.279 Zoran Selinger: The chart that you saw for organic, there’s more there.
39 00:06:58.970 ⇒ 00:07:07.030 Amber Lin: I see. Awesome. Yeah. Let me put this… we are working on this… This is weak.
40 00:07:08.540 ⇒ 00:07:09.340 Amber Lin: Cool.
41 00:07:11.520 ⇒ 00:07:20.569 Amber Lin: Are we gonna do anything related to attribution, or… like, I don’t really understand what… what that would include, so wanted to ask you about that.
42 00:07:20.570 ⇒ 00:07:27.219 Zoran Selinger: So the attribution that we have is in Google Analytics. I’m not aware of anything else. So basically, the work…
43 00:07:27.570 ⇒ 00:07:30.710 Zoran Selinger: That’s already in there.
44 00:07:31.010 ⇒ 00:07:33.090 Zoran Selinger: is the attribution.
45 00:07:33.630 ⇒ 00:07:34.340 Amber Lin: I see.
46 00:07:35.640 ⇒ 00:07:47.010 Amber Lin: would we be able to do attribution of other channels? Because they have, like, TV, they have Yellow Book, and they have, like, all these other channels. Would we be able to…
47 00:07:47.160 ⇒ 00:07:50.259 Amber Lin: Are we able to do attribution of those by any chance?
48 00:07:50.260 ⇒ 00:07:54.910 Zoran Selinger: I don’t see that in GA. So unless we have another…
49 00:07:55.210 ⇒ 00:08:00.549 Zoran Selinger: system that tracks those, yeah, we don’t, we don’t have the data. I see, okay.
50 00:08:01.950 ⇒ 00:08:02.590 Amber Lin: Okay.
51 00:08:02.590 ⇒ 00:08:10.310 Zoran Selinger: I don’t know what you… you guys were looking into other systems apart from GA, so what are those?
52 00:08:11.380 ⇒ 00:08:13.540 Amber Lin: Let me show you…
53 00:08:14.270 ⇒ 00:08:22.340 Amber Lin: Yeah, we have the… I just got the marketing spend, but I don’t think we have the…
54 00:08:22.670 ⇒ 00:08:27.309 Amber Lin: like, the actual conversions from those things, I would say it’s probably, like.
55 00:08:27.810 ⇒ 00:08:35.240 Amber Lin: other sources on GA, like, maybe it’s just categorized as other. I’m not 100% sure. Let me…
56 00:08:35.690 ⇒ 00:08:39.360 Amber Lin: Find, so in here, marketing.
57 00:08:40.730 ⇒ 00:08:42.130 Zoran Selinger: Yeah, so…
58 00:08:42.130 ⇒ 00:08:45.420 Amber Lin: They have, like, radio, television, direct mail.
59 00:08:45.730 ⇒ 00:08:51.550 Amber Lin: on the internet, which this is probably what is showing on GA.
60 00:08:52.100 ⇒ 00:08:54.769 Amber Lin: But this is, like, this is what they have.
61 00:08:56.010 ⇒ 00:09:06.889 Zoran Selinger: Yeah, so basically, for… obviously, for offline, we typically need… we have, like, offline-specific phone numbers, offline-specific.
62 00:09:06.890 ⇒ 00:09:09.239 Amber Lin: I see, I see.
63 00:09:09.240 ⇒ 00:09:25.160 Zoran Selinger: So we would need to understand what those are, and then we can actually make some, you know, informed inferences about, okay, this is offline traffic, and it performs this way. But we would need to know that.
64 00:09:26.050 ⇒ 00:09:27.729 Amber Lin: Gotcha, okay, I’ll put it there.
65 00:09:27.730 ⇒ 00:09:35.779 Zoran Selinger: I don’t know, it’s… Not everyone, just so you know, not many companies go to that length.
66 00:09:35.920 ⇒ 00:09:48.540 Zoran Selinger: To actually identify offline traffic. They literally just launch campaigns, and they expect to see the lift somewhere in financials, right?
67 00:09:48.540 ⇒ 00:09:49.420 Amber Lin: I see, I see.
68 00:09:49.420 ⇒ 00:09:52.639 Zoran Selinger: That’s typically the extent it goes.
69 00:09:52.640 ⇒ 00:09:53.180 Amber Lin: Fuck.
70 00:09:53.360 ⇒ 00:09:57.860 Zoran Selinger: Might not be the case here, maybe they are more sophisticated.
71 00:09:59.820 ⇒ 00:10:05.010 Amber Lin: I don’t know, I don’t think they know what’s going on in their marketing. Okay.
72 00:10:05.180 ⇒ 00:10:06.470 Zoran Selinger: Yeah, so…
73 00:10:06.960 ⇒ 00:10:07.370 Amber Lin: Yeah.
74 00:10:07.370 ⇒ 00:10:11.089 Zoran Selinger: I don’t know, we can ask, maybe they surprise us.
75 00:10:11.090 ⇒ 00:10:11.450 Amber Lin: Yep.
76 00:10:11.450 ⇒ 00:10:13.199 Zoran Selinger: I, I don’t think it’s like…
77 00:10:13.200 ⇒ 00:10:22.769 Amber Lin: Yeah, we’ll ask. You mentioned to look at Facebook or Meta will have better demographics. Is that still something we’re gonna look into?
78 00:10:24.810 ⇒ 00:10:26.679 Zoran Selinger: I mean, if they…
79 00:10:29.260 ⇒ 00:10:36.699 Zoran Selinger: I… yeah, we would need the access to their… to their ad accounts to actually look at some stats on…
80 00:10:36.930 ⇒ 00:10:37.890 Zoran Selinger: on those.
81 00:10:38.530 ⇒ 00:10:39.749 Amber Lin: I see. Cool.
82 00:10:43.170 ⇒ 00:10:46.880 Zoran Selinger: It’s simply, they’re way, way, way better than…
83 00:10:48.100 ⇒ 00:11:00.330 Zoran Selinger: the demographic data we see in GA, especially pertaining to the, like, user attributes, apart from geography and technology they use, is very sparse.
84 00:11:00.880 ⇒ 00:11:01.670 Amber Lin: I’ll see.
85 00:11:01.670 ⇒ 00:11:08.370 Zoran Selinger: And it goes so far that it kind of borderlines, unusable.
86 00:11:09.490 ⇒ 00:11:14.300 Zoran Selinger: Yeah, because basically 90% of of…
87 00:11:14.820 ⇒ 00:11:21.519 Zoran Selinger: interactions in Google Analytics will be marked as unknown for both age and gender.
88 00:11:22.060 ⇒ 00:11:23.110 Amber Lin: I see.
89 00:11:23.110 ⇒ 00:11:23.740 Zoran Selinger: Yeah.
90 00:11:25.120 ⇒ 00:11:32.249 Zoran Selinger: So it’s just not… not very usable. But on Facebook, you, you have actual data.
91 00:11:32.250 ⇒ 00:11:32.800 Amber Lin: Hmm.
92 00:11:35.830 ⇒ 00:11:47.100 Amber Lin: Cool, okay. I think that’s it for now. There’s not much else we can add. I’ll try to grab Utam’s time to meet again, but I think we’re… we’re done for this meeting for now.
93 00:11:47.100 ⇒ 00:11:48.100 Zoran Selinger: Okay, okay.
94 00:11:48.100 ⇒ 00:11:51.250 Amber Lin: Okay, yeah, thank you for having me on. Yeah, bye.
95 00:11:51.250 ⇒ 00:11:51.900 Zoran Selinger: Bye-bye.