Meeting Title: KPI work session Date: 2026-01-29 Meeting participants: Zoran Selinger, Ryon


WEBVTT

1 00:01:23.890 00:01:24.930 Zoran Selinger: Hadron.

2 00:01:25.860 00:01:27.379 Ryon: Morning, Zoran, how are you doing?

3 00:01:27.700 00:01:31.390 Zoran Selinger: Yeah, yeah, good, good, come on.

4 00:01:34.390 00:01:37.229 Zoran Selinger: One sec. Simply, world needs something.

5 00:01:38.800 00:01:55.700 Ryon: All at once. Alright, real quick, for this call, can you just, for my sake, walk me through our attribution capabilities right now, either what you’ve been building, or, what you are… what we’ve worked on, or what… what already exists? Because I just need to take a step back and kind of look at this

6 00:01:55.840 00:01:56.369 Ryon: From a high…

7 00:01:56.370 00:02:02.699 Zoran Selinger: Okay, let me… let me go from the… from the start. So, I’m discovering this, as well.

8 00:02:02.700 00:02:03.310 Ryon: Okay.

9 00:02:05.430 00:02:09.919 Zoran Selinger: Let me show you what we have in… in the cloud… in GCP.

10 00:02:10.840 00:02:13.719 Zoran Selinger: We have two tables in GCP.

11 00:02:14.200 00:02:17.309 Ryon: I don’t know about them. GCP, what does that stand for?

12 00:02:17.470 00:02:19.700 Zoran Selinger: Google Hub Platform, GCP.

13 00:02:21.540 00:02:23.090 Zoran Selinger: On BigQuery, basically.

14 00:02:23.670 00:02:33.020 Ryon: So we have two tables. One is… so this is automatically being pulled already. The guys were using it for other reports.

15 00:02:34.740 00:02:37.150 Zoran Selinger: You guys were using it for other reports.

16 00:02:39.630 00:02:43.249 Zoran Selinger: Oh, it switched to… to dark.

17 00:02:44.230 00:02:45.530 Zoran Selinger: Yesterday.

18 00:02:45.730 00:02:52.349 Zoran Selinger: So in, production DBT marts, you will find…

19 00:02:52.710 00:03:01.359 Zoran Selinger: you will find NordBeam. We have ad spend, and we have clean table. You see here? Those two?

20 00:03:01.470 00:03:03.290 Zoran Selinger: In the display name.

21 00:03:03.620 00:03:05.169 Zoran Selinger: I don’t… do you see my…

22 00:03:05.170 00:03:05.780 Ryon: Okay.

23 00:03:05.910 00:03:13.330 Zoran Selinger: Yeah, so I’m using the clean table in our KPI dash,

24 00:03:13.710 00:03:20.779 Zoran Selinger: I’m still not convinced this is… this data is absolutely correct. I still have to do the checks for it.

25 00:03:20.960 00:03:27.130 Zoran Selinger: In particular, like, this first-time ROAS revenue, things like that.

26 00:03:27.290 00:03:30.129 Zoran Selinger: I need to figure that out.

27 00:03:32.230 00:03:38.860 Zoran Selinger: So that’s… that’s basically… that’s the idea, there. So this is coming directly from,

28 00:03:39.530 00:03:41.670 Zoran Selinger: from Norbim, I believe the.

29 00:03:41.670 00:03:46.400 Ryon: This is coming from North Beam? This is coming from… this is coming FROM North Beam.

30 00:03:46.400 00:03:57.110 Zoran Selinger: from NordBeam, yes. This is coming from NordBeam. This is NordBeam data, so I think this ad spend data is actually raw, raw NordBeam, data.

31 00:03:57.940 00:04:10.649 Zoran Selinger: That we have. And then the guys are doing something to… to get a clean table, whatever that means. I still have to have that discussion with them. So that’s where we are.

32 00:04:11.080 00:04:15.679 Zoran Selinger: At the moment, Let me just log into my…

33 00:04:19.269 00:04:26.419 Zoran Selinger: I just used, that table to import some data.

34 00:04:26.800 00:04:33.320 Zoran Selinger: So if we go to our attribution dash, it’s literally a query from the… from the…

35 00:04:33.680 00:04:35.410 Zoran Selinger: From the clean table.

36 00:04:35.630 00:04:46.360 Zoran Selinger: You can expand this to a particular day and look at the data. Obviously, a lot of formatting will go into that. I’m probably not going to be the person to do it. I think Amber…

37 00:04:46.620 00:04:53.710 Zoran Selinger: is going to do, formatting for us. But I still have to, like, check this data, a little bit.

38 00:04:53.710 00:05:02.200 Ryon: Hold on, this BFKPI PACE dashboard here. Okay, can you real quick, send this link to me, because I need to look through this.

39 00:05:03.170 00:05:05.289 Zoran Selinger: Yeah, but you, you were there.

40 00:05:05.660 00:05:12.359 Ryon: Yeah, yeah, I know, it’s… I didn’t know this is where it is. Actually, no, never mind, never mind. Okay, go back to that real quick here, the attribution dash, real quick.

41 00:05:13.760 00:05:14.710 Ryon: the…

42 00:05:14.710 00:05:15.840 Zoran Selinger: Yeah.

43 00:05:17.980 00:05:18.650 Ryon: Okay.

44 00:05:19.050 00:05:20.040 Zoran Selinger: So we’ll come back.

45 00:05:20.720 00:05:37.189 Zoran Selinger: not our priority. We will come back to that portion after we finish the number 2, like, the channel bit. I was just using time while I was waiting for your and Mitesh’s feedback, I was just using it to at least do something while I wait.

46 00:05:38.670 00:05:39.510 Zoran Selinger: Mmm.

47 00:05:39.510 00:05:58.060 Ryon: Okay, so help me understand something. Northbeam, this is… I’m sort of, like, figuring out what our attribution stack is, to a degree, so please understand, I’m a bit confused here, and also I don’t trust it. Northbeam basically is… is attribut… attributing the traffic for us, and this is… it’s sending data to this table.

48 00:05:58.150 00:05:59.669 Ryon: In BigQuery, yes?

49 00:06:00.110 00:06:00.990 Zoran Selinger: Yes.

50 00:06:01.720 00:06:04.449 Ryon: It itself reports on this data.

51 00:06:05.570 00:06:07.369 Zoran Selinger: Yes, I mean, the…

52 00:06:08.240 00:06:27.509 Zoran Selinger: the whole point of NordBeam is, it is the attribution tool that we use, right? We don’t need to build anything additional. Obviously, we have multiple options in NordVim. For example, you see what’s happening here. So, the attribution model, we…

53 00:06:28.090 00:06:35.830 Zoran Selinger: We, we look at here is we look at clicks only, and attribution window is lifetime.

54 00:06:36.040 00:06:43.469 Zoran Selinger: We can probably… pull data based on multiple attribution models from the… from Norbing.

55 00:06:44.130 00:06:49.980 Zoran Selinger: But I’d have to talk to the guys. And, you haven’t looked much into Norbing, right?

56 00:06:50.340 00:06:56.279 Ryon: I have, I don’t like it, that’s why I’m asking, but it’s my… it’s my opinion. We’re using it, I don’t care.

57 00:06:56.280 00:07:03.020 Zoran Selinger: I mean, they are… all the attribution tools are pretty much the same. NordBeam is…

58 00:07:03.370 00:07:10.269 Zoran Selinger: an industry standard at the moment for… for kind of more serious companies. And,

59 00:07:10.700 00:07:15.400 Zoran Selinger: I mean, bigger companies than ours, you use them.

60 00:07:15.490 00:07:16.810 Ryon: I, I’m sure, I’m sure…

61 00:07:16.810 00:07:19.109 Zoran Selinger: As good as we can get.

62 00:07:19.380 00:07:19.730 Ryon: Yeah.

63 00:07:19.730 00:07:21.529 Zoran Selinger: From, like.

64 00:07:21.970 00:07:30.360 Zoran Selinger: if you’re using a tool that’s out there already. That’s it. That’s simply it. And yeah, we have some, obviously.

65 00:07:30.400 00:07:42.780 Zoran Selinger: the whole point is attribution, so we have a bunch of attribution models and things that we can tweak inside NordBeam, and that probably means, I’m saying probably, but almost certainly means we can get this data here.

66 00:07:42.950 00:07:45.299 Zoran Selinger: And do whatever reports we want.

67 00:07:45.580 00:07:49.600 Zoran Selinger: So that, that is what we have at the moment.

68 00:07:52.050 00:07:54.539 Zoran Selinger: For the attribution, and we should… we should…

69 00:07:55.360 00:08:02.530 Zoran Selinger: make that as perfect as possible. Norvium will look better as well soon, because we are…

70 00:08:02.680 00:08:06.100 Zoran Selinger: Activating more channels, so we’ll have

71 00:08:08.700 00:08:11.539 Zoran Selinger: More channels to look at in there.

72 00:08:11.860 00:08:12.790 Zoran Selinger: Okay.

73 00:08:13.130 00:08:20.220 Ryon: Give me two seconds, I need to take a quick phone call, and then I want to talk to you about Northbeam itself. Give me 2 seconds.

74 00:10:34.220 00:10:34.950 Ryon: Alright.

75 00:10:35.120 00:10:36.359 Ryon: Sorry about that.

76 00:10:39.520 00:10:43.029 Ryon: I don’t know why, but it, like, seems everybody needs everything all at once.

77 00:10:43.760 00:10:46.030 Ryon: So, Northbeam here, I…

78 00:10:56.020 00:10:59.849 Ryon: Are you at all concerned about it favoring one channel over the other a little much?

79 00:11:02.460 00:11:15.760 Zoran Selinger: We can’t really say… I mean, we can’t really know that, since one channel is so overpowering still in our promotional mix, so it’s… it’s really hard,

80 00:11:16.460 00:11:30.129 Zoran Selinger: to conclude that, right? But you can play with the attribution models. You can come… come here, and you can change your… your model, your windows, and try to play with that.

81 00:11:32.600 00:11:44.169 Zoran Selinger: Right? And then we can always… listen, and you know that yourself. Attribution model, as long as they’re… as long as they’re multi-touch, none of them are wrong.

82 00:11:44.310 00:11:46.079 Zoran Selinger: Really, right?

83 00:11:46.080 00:11:47.280 Ryon: No, they’re not, it’s just…

84 00:11:47.280 00:11:51.210 Zoran Selinger: It’s almost super arbitrary, so whatever we agree on.

85 00:11:52.040 00:11:59.829 Zoran Selinger: It’s… it’s fine. As long as it’s… as long as it’s multi-touch, because any single touch is absolutely wrong.

86 00:12:00.220 00:12:03.950 Zoran Selinger: and multi-touch you know,

87 00:12:04.900 00:12:23.110 Zoran Selinger: it’s really hard to make an argument that one is right over the other. For example, like, U-shaped, or linear, or time decay, whatever. It’s really hard to make arguments that stand for each one of them in particular.

88 00:12:24.060 00:12:31.759 Zoran Selinger: Right? That’s my opinion generally. I’ve never seen anyone, solve attribution fully,

89 00:12:32.100 00:12:42.300 Zoran Selinger: like, okay, this is… this is the model. And obviously today, none of… so none of these that you see in… in these tools, none of these are,

90 00:12:43.290 00:12:50.189 Zoran Selinger: models, like linear, U-shaped, or time decay, they’re all, like, data-driven models, so it’s…

91 00:12:50.680 00:12:54.680 Zoran Selinger: And obviously, those things are going to be black boxes for us.

92 00:12:57.150 00:13:02.900 Zoran Selinger: Because we are using, you know, a proprietary tool. So, they’re gonna be playboxes for us.

93 00:13:04.460 00:13:13.759 Zoran Selinger: I don’t know… How to solve this, apart from playing with the attribution settings, and see

94 00:13:16.480 00:13:18.470 Zoran Selinger: What looks good to us, right?

95 00:13:20.380 00:13:39.649 Zoran Selinger: And we are… we are always gonna go by vibes, right? If we’re talking about the attribution models. If… when you look at… okay, let’s say we’re gonna choose an attribution model, it’s one of those, we’re gonna play the attribution window, and all that, and then you’re gonna see a split.

96 00:13:39.880 00:13:48.019 Zoran Selinger: Across a little bit of difference split across channels. And to… to you, that’s gonna look…

97 00:13:48.180 00:13:49.570 Zoran Selinger: better, right?

98 00:13:50.790 00:13:55.499 Zoran Selinger: How would you defend that it looks better to you in that particular case?

99 00:13:57.250 00:14:02.469 Ryon: Okay. From a formatting perspective, here’s what I’m wondering if we can do,

100 00:14:09.550 00:14:14.510 Ryon: sort of looking at this and trying to see if I can get some notes for you on what would be an action item.

101 00:14:17.500 00:14:20.870 Ryon: you know, at least we have attribution, I guess that’s a start.

102 00:14:23.660 00:14:37.639 Ryon: I guess I just don’t understand some things about it. Let me share my screen and see if I can go through it, because I’m not trying to be, like, a problem here, I’m just trying to basically, like… I know what Mitesh is gonna ask Zoran, so I know what he’s gonna get at. Like, as an example…

103 00:14:37.640 00:14:46.189 Zoran Selinger: don’t hesitate, let’s… let’s look into this. So, the reason why I didn’t fully report on this is because those numbers

104 00:14:46.640 00:14:48.009 Zoran Selinger: Seem off to me.

105 00:14:48.160 00:14:49.880 Zoran Selinger: Sound of those numbers.

106 00:14:50.350 00:14:50.870 Ryon: I mean…

107 00:14:50.870 00:14:57.300 Zoran Selinger: what the model is exactly, and I want to talk to the guys next week about that particular model, and…

108 00:14:59.330 00:15:00.989 Zoran Selinger: See what I can see, right?

109 00:15:01.810 00:15:04.389 Ryon: Okay. Is this looking at all time here?

110 00:15:04.950 00:15:07.399 Zoran Selinger: No, this is just the last 30 days.

111 00:15:08.210 00:15:08.640 Ryon: This is like…

112 00:15:08.640 00:15:12.119 Zoran Selinger: If you go, open the hidden sheets.

113 00:15:13.480 00:15:19.109 Zoran Selinger: Look at the list of sheets, the, the three dashes, yeah.

114 00:15:19.500 00:15:23.030 Zoran Selinger: and just, take a NordBeam roll.

115 00:15:23.760 00:15:28.970 Zoran Selinger: Yeah, the one that’s grayed out, yeah. So, and look at the,

116 00:15:29.140 00:15:34.539 Zoran Selinger: Click on the connection settings on the top right.

117 00:15:35.560 00:15:41.080 Zoran Selinger: So that’s basically the… the query.

118 00:15:41.760 00:15:43.390 Zoran Selinger: That’s grabbing the data.

119 00:15:43.390 00:15:45.549 Ryon: From, from Bigger. Okay.

120 00:15:45.550 00:15:51.419 Zoran Selinger: Yeah, so… I did… I did miss one calculated field, which is…

121 00:15:52.060 00:15:55.599 Zoran Selinger: Which is not, like, full Ross.

122 00:15:55.620 00:16:12.259 Zoran Selinger: total ROS, not just first time only. I’m missing that field in the model. I also don’t like something, Ryan, and I… I believe it’s potentially… that’s the problem here. You see that we have, like, calculated columns.

123 00:16:12.260 00:16:19.350 Zoran Selinger: Here. But I want to calculate whole columns only after I create a pivot table.

124 00:16:20.390 00:16:26.460 Zoran Selinger: Right? Not before. I don’t want an average of ROS or NCAC.

125 00:16:27.780 00:16:30.439 Zoran Selinger: I want to calculate it after pivoting.

126 00:16:30.600 00:16:38.629 Zoran Selinger: This is not, like, I could do it manually on the side here, right? I can do it manually.

127 00:16:38.730 00:16:40.500 Zoran Selinger: And I might do that.

128 00:16:40.900 00:16:55.190 Zoran Selinger: I can do it manually. In Excel, in Microsoft Excel, you have that option of actually creating calculated field after. So any relative metric, you should really only calculate it after.

129 00:16:55.450 00:16:58.659 Zoran Selinger: U, or UPOT, right?

130 00:17:02.040 00:17:03.900 Ryon: Okay.

131 00:17:06.990 00:17:13.109 Zoran Selinger: So that’s why I just need a deeper dive into this, and the data will at least look

132 00:17:13.670 00:17:24.850 Zoran Selinger: how it should look in… in here, like, calculation-wise. I can fix that, no problem. This was just a quick start for me.

133 00:17:25.050 00:17:27.419 Zoran Selinger: Influencer total is wrong.

134 00:17:27.619 00:17:34.050 Zoran Selinger: I just pinged guys, so we have 2 days of importing influencer spend, and now…

135 00:17:34.260 00:17:39.820 Zoran Selinger: They’re not importing again, and we should have… we should essentially have daily numbers here.

136 00:17:40.000 00:17:44.079 Zoran Selinger: Right? So that’s a problem for me as well.

137 00:17:47.470 00:17:48.770 Zoran Selinger: Unfortunately, yeah.

138 00:17:48.770 00:17:56.470 Ryon: I don’t… I don’t know… I don’t know how much I trust these numbers, Arun, I’m just gonna be honest with you, flat out, like, this… this is suspicious. All of this is suspicious.

139 00:17:56.470 00:17:58.270 Zoran Selinger: What’s suspicious do you…

140 00:17:58.510 00:18:00.979 Zoran Selinger: So, Microsoft Ads…

141 00:18:00.980 00:18:03.599 Ryon: We don’t run Microsoft ads right now.

142 00:18:03.720 00:18:18.109 Ryon: as far as I know. So, 43 conversions coming from Microsoft, that’s weird. We have not run Snapchat Reddit ads for almost as long as I’ve been here, so over a year, yet it’s being attributed

143 00:18:18.170 00:18:28.670 Ryon: sales, so that doesn’t make sense. We’re not running on Twitter at all. Again, sort of weird. Here’s what I’m…

144 00:18:29.130 00:18:30.940 Zoran Selinger: Speculating.

145 00:18:30.940 00:18:34.350 Ryon: This is what I’m sort of speculating here.

146 00:18:35.410 00:18:45.330 Ryon: Only recently, as you recall, I had Caesar pause those… tags inside of… GTM.

147 00:18:46.530 00:18:52.399 Ryon: I wonder… Does the fact that the tag itself fires?

148 00:18:52.940 00:18:56.949 Ryon: Give the channel credit when it has technically none?

149 00:18:59.170 00:19:11.460 Ryon: Like, as an example here, the offer, we definitely did not drive 350 conversions within the past 3 days, and I can tell you this for fact, because of the simple fact that, like.

150 00:19:13.150 00:19:17.670 Ryon: They basically are frauds. They took money from us and drove nothing, so…

151 00:19:17.930 00:19:20.770 Ryon: How on earth we got conversions from them.

152 00:19:21.210 00:19:25.460 Ryon: is weird to me. Like, this does not make sense at all.

153 00:19:26.280 00:19:33.870 Ryon: I need to understand that a little better. In terms of catalysts, That’s right, that makes sense.

154 00:19:34.580 00:19:39.040 Ryon: Influencers… this seems a little low, but that makes sense.

155 00:19:39.040 00:19:41.140 Zoran Selinger: YouTube is not running…

156 00:19:41.140 00:19:42.200 Ryon: at all.

157 00:19:42.960 00:19:43.489 Ryon: Yeah, good.

158 00:19:43.490 00:19:53.259 Zoran Selinger: I just want to tell you, when you’re looking at Catalyst in NordBeam in the interface, so I renamed it here, okay, but it’s gonna be under Other, okay?

159 00:19:53.500 00:19:54.290 Ryon: Other?

160 00:19:54.290 00:19:56.340 Zoran Selinger: In the interface, yes. In order…

161 00:19:56.340 00:19:58.760 Ryon: So it’s this bucket right here, right here.

162 00:19:59.040 00:20:00.910 Zoran Selinger: Yes, that’s Catalyst, yes.

163 00:20:00.910 00:20:02.610 Ryon: Can we rename it in here?

164 00:20:06.670 00:20:18.010 Zoran Selinger: I don’t think we… I mean, I guess if we send the platform name We might be able to.

165 00:20:20.100 00:20:21.660 Zoran Selinger: We might be able to.

166 00:20:25.770 00:20:29.379 Zoran Selinger: I wonder if… if this will invalidate

167 00:20:29.530 00:20:38.930 Zoran Selinger: invalidate, what we’re sending from… from our backend, or not, in terms of the spend? Oh, yeah, yeah, okay, okay, okay.

168 00:20:40.820 00:20:42.740 Zoran Selinger: I think we can’t.

169 00:20:44.570 00:20:49.310 Zoran Selinger: I think we can’t change that, so it’s just for the reporting that I changed this.

170 00:20:49.310 00:20:56.929 Ryon: Okay, so, just so I… we’re on the same page here, because, again, a lot of this I’m sort of picking up and learning. I appreciate your patience with me.

171 00:20:57.500 00:21:12.630 Ryon: Northbeam is taking in data. It’s telling us, based on its modeling, what the attribution of that data is. Data’s going to BigQuery, BigQuery Clean Table. Cleant table is what you’re pulling in here, and of course, in this case, you’ve just pivoted it out so we can see what a pivot looks like, right?

172 00:21:12.630 00:21:13.180 Zoran Selinger: Yup.

173 00:21:13.300 00:21:20.040 Ryon: I have doubts around the data. My suspicion is that, if I go back here to,

174 00:21:20.270 00:21:25.330 Ryon: Let’s go just to sales attribution, and then we’ll go down here to…

175 00:21:27.730 00:21:30.109 Ryon: I bet you it’s set to infinite here.

176 00:21:30.800 00:21:31.640 Ryon: Right?

177 00:21:31.920 00:21:38.889 Zoran Selinger: Oh, yes, for sure. Yes, yes, exactly. And you see that from the table, look, look at the table here. Attribution window lifetime.

178 00:21:43.910 00:21:53.250 Zoran Selinger: This is why… this is why we can get 6 conversions from someone that interacted with a campaign that was last paused, you know, 10 months ago.

179 00:21:54.060 00:22:03.260 Ryon: That’s what I’m basically seeing here. So, what we’re observing is not that we are actually driving conversions, it is that we are,

180 00:22:09.220 00:22:19.699 Ryon: We are observing that Northbeam believes these channels, which have long been off, to be contributing to conversions that happen today, because that person was a touchpoint for that channel way back when.

181 00:22:20.030 00:22:20.590 Zoran Selinger: Yeah.

182 00:22:21.720 00:22:28.770 Zoran Selinger: Essentially, we need to agree on what is our attribution window, our

183 00:22:31.270 00:22:39.430 Zoran Selinger: what do… yeah, what’s our attribution window? This is…

184 00:22:40.910 00:22:44.449 Zoran Selinger: What we need to decide as a… basically, as a company.

185 00:22:46.770 00:22:47.370 Ryon: Okay.

186 00:22:47.600 00:22:50.299 Ryon: Minus 30 days.

187 00:22:50.720 00:22:51.820 Ryon: So…

188 00:22:52.170 00:22:53.760 Zoran Selinger: What? Say again?

189 00:22:54.010 00:23:01.730 Ryon: Mine is 30 days. The attribution window for me is 30 days. In other words, I’m looking at that 30-day period, and I want to know in a 30-day period, what are people doing? Now.

190 00:23:01.920 00:23:06.430 Ryon: That said, with… if I’m answering that question.

191 00:23:07.040 00:23:22.029 Ryon: correctly, the right answer that I should give is, well, what is the best attribution window for us to have for the segment or the traffic that we’re getting? As an example here, these guys right here, 350 conversions.

192 00:23:22.280 00:23:26.530 Ryon: them happening Way back when.

193 00:23:27.010 00:23:41.549 Ryon: tells me that there’s an audience of people that are still engaging with this channel over here, and they are converting, so I should be cognizant of that fact, and if I have a 30-day cutoff for my attribution window.

194 00:23:41.550 00:23:56.750 Ryon: I’m missing that data. I’m missing that information when it comes to understanding the nature of the audience or the segment that I’m looking at. So that’s what I’m saying, like, I think we sort of have to be careful with that as a whole.

195 00:23:58.220 00:24:02.790 Zoran Selinger: So you… so you understand that this 350 means this is…

196 00:24:03.540 00:24:21.280 Zoran Selinger: this is not obviously coming from campaigns that are active now, or from the link clicks that someone saved with the OTMs that are active now, but it could be for any time in the future, since we have the lifetime attribution window. So it’s the same person, same people that did

197 00:24:21.280 00:24:26.639 Zoran Selinger: interact with the offer campaigns, and you can see that from the end transactions.

198 00:24:26.670 00:24:30.170 Zoran Selinger: Where we have only new… 5 new customers from

199 00:24:31.030 00:24:35.420 Zoran Selinger: from this segment. We do have 5 new customers. So, meaning…

200 00:24:35.420 00:24:37.830 Ryon: So is this… is this new customers here?

201 00:24:37.830 00:24:41.789 Zoran Selinger: Yeah, N, and everything that has N, that’s new customers.

202 00:24:49.070 00:24:52.610 Ryon: Still, what I take away from this is…

203 00:24:59.170 00:25:02.259 Zoran Selinger: I think we should limit attribution window, for sure.

204 00:25:02.500 00:25:09.639 Zoran Selinger: And we should discuss what that is. I’ve never seen lifetime attribution window. That is not…

205 00:25:11.260 00:25:28.989 Ryon: I’m not saying… I’m not saying… sorry, maybe my comment didn’t… didn’t say lifetime. I just don’t want to get too aggressive with the attribution window and miss out on people who are a longer conversion, right? This product, this treatment, I mean, you’re buying something to stick yourself with a needle. Like, that takes a lot of thinking.

206 00:25:28.990 00:25:38.029 Ryon: You’re not gonna walk into a local retail store and buy a pen, or like, you know, a charger. You know, that’s a very simple decision. So…

207 00:25:38.160 00:25:43.849 Ryon: My thinking is, most people convert within a 30-day window. That’s what I would assume.

208 00:25:43.950 00:25:48.290 Ryon: I would ask, maybe you could tell me, like…

209 00:25:48.290 00:26:07.690 Ryon: X percentage of people convert within 30 days, therefore this is probably a good cutoff. Or maybe we need to increase it to 60 days. That way we can see, okay, we started a campaign back here, it was churning for a while, but its conversions didn’t show up until the latter 60 days, or the last 30 of the 60 days, and they came through these channels, something like that. That’s what I’m wondering if you can kind of tell me.

210 00:26:07.690 00:26:10.640 Ryon: Yeah.

211 00:26:11.010 00:26:18.739 Ryon: Yeah, yeah, yeah. Okay. Alright, so, from a visual perspective, here’s what I’m gonna do today.

212 00:26:19.210 00:26:28.359 Ryon: I’m gonna go through this, I’m gonna provide you with, like, a visual look of how things need to be. If it’s north… so… part of me is like, you know.

213 00:26:30.960 00:26:34.679 Ryon: part of me is, like, you and I…

214 00:26:35.090 00:26:36.780 Ryon: Are the only ones who know this crap.

215 00:26:37.120 00:26:41.259 Ryon: We need to go through and just, like, audit it, and at least, like.

216 00:26:42.490 00:26:57.770 Ryon: turn over every rock, and make sure there’s nothing that’s happening that we don’t know about, because I feel like there’s a lot of people that have come in here, and there’s a chance that, like, there’s something happening we don’t know about, or what they’re doing, so that’s kind of the first step. So if I give you feedback, and it’s more just kind of meant as sort of like an audit, or kind of like a…

217 00:26:57.770 00:27:06.719 Ryon: a test of what’s going on, please understand, I don’t intentionally mean it to be something of, like, I doubt you, I just want to make sure that, like, we all understand what’s working and what’s doing well.

218 00:27:06.720 00:27:15.390 Ryon: Second, from a formatting perspective, I want to figure out how we… configure…

219 00:27:15.920 00:27:28.139 Ryon: this so that it looks the way that Mitesh and others want it to. So, I’m gonna spend some time looking at a format and setting things up the way that they need to be formatted. My question to you is…

220 00:27:29.190 00:27:31.129 Ryon: I have two questions. One.

221 00:27:31.760 00:27:41.270 Ryon: is this data sufficient for us to produce the weekly projections report? Like, does it have all the metrics that you think you need? And…

222 00:27:41.780 00:27:45.179 Ryon: with that, I sent you a metrics document yesterday.

223 00:27:45.320 00:27:59.349 Ryon: With all of the metrics for each and every one of the, the channels, and what we need to be tracking and what we need to see here. Can the North Beam data at least support this, enough for us to understand

224 00:27:59.400 00:28:07.480 Ryon: what’s going on here and how things are working. Can it support all these metrics, or at least most of them, all the critical ones?

225 00:28:09.030 00:28:12.599 Zoran Selinger: So, I wasn’t sure about the projections,

226 00:28:13.250 00:28:19.750 Zoran Selinger: Isn’t this something that, campaign managers do for their own channels every week?

227 00:28:20.250 00:28:27.650 Ryon: It is… here’s what I’m gonna… here’s what I’m gonna say. You and I are taking that over. We are gonna be the ones who say, like, we think you.

228 00:28:27.650 00:28:30.370 Zoran Selinger: projections, and… Like.

229 00:28:30.370 00:28:30.770 Ryon: Yeah.

230 00:28:30.770 00:28:31.490 Zoran Selinger: the actual…

231 00:28:31.490 00:28:46.830 Ryon: I want to… Mitesh wants you and me, me specifically, to be the one who says, like, hey, we think you should be here, right? Now, I’m not suggesting that that’s what everyone’s going to adopt, but I want us both to be like.

232 00:28:47.300 00:28:56.340 Ryon: we think that they can hit this, or we think that we can hit this, that kind of thing. So, yeah, we need to have that known for ourselves. And then,

233 00:28:58.660 00:29:02.610 Ryon: the formatting of this needs to change.

234 00:29:02.740 00:29:07.070 Zoran Selinger: Yeah, I mean, we can break, like, in pivots, you can break…

235 00:29:07.180 00:29:15.640 Zoran Selinger: Yeah, let’s figure out what we need in terms of dimension, because now I’m… I’m thinking this table, Norring Clean.

236 00:29:15.850 00:29:19.750 Zoran Selinger: table is not gonna be enough. We need more dimensions in there.

237 00:29:21.160 00:29:26.529 Ryon: We need more dimensions. Take a look at the file I sent you. This is more of an exhaustive list here.

238 00:29:26.770 00:29:41.079 Ryon: of what each one of the channels needs to include. Some of these things are very… I don’t want to call them vanity metrics, but they’re kind of like, they don’t really matter all that much, like, impressions, reach, like, who cares? You know what I mean? Like, if we don’t have this, I’m not gonna freak out.

239 00:29:41.140 00:29:51.430 Ryon: Right, it does not matter. It’s a vanity metric to a point. The ones that are gonna really matter are things like the number of clicks, the conversion rate, the sales, the ROAS, and then the cost band, those types of things, right? The business metrics.

240 00:29:51.430 00:30:12.420 Ryon: Right, and then, for this thing here, I need to… maybe I should set up time with you and Amber, and we can go through a format. The format that Mitesh is really looking for is something very similar to what I’ve produced with my forecast, where it’s by channel, here it is, by month, and then by week, that kind of thing. So, if we can do that, that’s excellent. Now, my last question for you is going to be…

241 00:30:31.950 00:30:35.850 Ryon: Is Northbeam data the best way to do forecasting?

242 00:30:37.870 00:30:40.090 Ryon: Or is there a better way for us to do it?

243 00:30:42.340 00:30:44.800 Zoran Selinger: Well, when it comes to forecasting.

244 00:30:44.960 00:30:47.350 Zoran Selinger: I mean, we should do it

245 00:30:47.770 00:30:55.450 Zoran Selinger: We should do it in a… In a channel… in a…

246 00:30:55.780 00:30:58.100 Zoran Selinger: Place where we have most historical data.

247 00:30:59.410 00:31:00.759 Zoran Selinger: That’s where you should do it.

248 00:31:01.000 00:31:06.749 Zoran Selinger: So if that’s our backend, that’s our backend. It’s our… it’s our… if it’s our warehouse, it’s our warehouse.

249 00:31:06.930 00:31:14.280 Zoran Selinger: BigQuery ML, And we can do probably a lot with that.

250 00:31:14.770 00:31:26.930 Zoran Selinger: the idea is, so, Ryan, I wanna… I want us to, to understand this also. Like, the attribution dash that you were just looking at, this is not…

251 00:31:27.150 00:31:29.569 Zoran Selinger: 0.2. This is not the second

252 00:31:29.870 00:31:34.439 Zoran Selinger: thing that we listed. We listed 5 things, you remember? If you go to the plan.

253 00:31:35.350 00:31:55.000 Zoran Selinger: So that’s not the number 2, that’s number 3. And really, this is… the number 3 is essentially just to decide where to allocate budget. That’s why it needs to answer. So we… we shouldn’t… we shouldn’t use it for more than we need to, essentially.

254 00:31:55.320 00:31:56.130 Zoran Selinger: Okay?

255 00:31:56.850 00:32:01.449 Zoran Selinger: So I wouldn’t rely on Norbin for… for things that are not for Norbin.

256 00:32:02.710 00:32:08.929 Ryon: Okay. If I ever showed you this report here, I showed this to Henry a while back. Let’s see if I can show this here to you.

257 00:32:11.900 00:32:12.660 Zoran Selinger: Okay.

258 00:32:12.970 00:32:20.140 Zoran Selinger: Essentially, the number 2, the channel report, I want us to create it from other things, right?

259 00:32:20.720 00:32:21.919 Ryon: Yeah, yeah. I agree.

260 00:32:21.920 00:32:22.560 Zoran Selinger: From my phone.

261 00:32:22.560 00:32:27.350 Ryon: You answered my question. This report here, This report here.

262 00:32:27.700 00:32:32.849 Ryon: I don’t think this should use Northbeam data. I just wanted to make sure that you agreed with me that it should not.

263 00:32:32.850 00:32:35.080 Zoran Selinger: Yes, I agree, I agree with you.

264 00:32:35.550 00:32:37.680 Ryon: Second, this right here.

265 00:32:37.840 00:32:44.140 Ryon: This was built a long time ago. I’ll send you this. I think it’s long been,

266 00:32:47.180 00:32:49.280 Ryon: It’s long been.

267 00:32:50.880 00:32:52.909 Zoran Selinger: not maintained, I understand.

268 00:32:58.450 00:33:00.569 Ryon: That’s what abandoned carts does, Danny.

269 00:33:10.780 00:33:13.259 Ryon: Okay, so,

270 00:33:17.850 00:33:35.019 Ryon: This report here was built by Zach Casey a while ago. It has long since been broken, and in fact, it was also built by Rob, who had this in Looker Studio, right? It doesn’t need to be in Looker, it can be in Tableau, it doesn’t need to be in anything. But this is basically, I think, where the leadership

271 00:33:35.130 00:33:46.179 Ryon: wants to see things, right? They want to go to a dashboard like this, and just, in a single place, be able to measure performance across all channels, and see everything

272 00:33:46.350 00:33:50.350 Ryon: Through a certain lens, this kind of thing, right?

273 00:33:50.440 00:34:08.320 Ryon: So, I’m gonna… I don’t know if you have access to that, but, like, go ahead and take a look at this report. This is basically what they want to see, at a high level, right? You can look at total orders, you can look at first-time orders, this kind of thing, right? Like, all of this at a high level. Now, they layered in things like COGS,

274 00:34:11.960 00:34:27.739 Ryon: other metrics on users, right? Like, what the BMI scores were, what the health data was, so we could kind of see, like, hey, who’s bringing everybody else in, that kind of thing. We just need to start with this. A dashboard like this, where they can take the data.

275 00:34:27.800 00:34:32.720 Ryon: that you’re pulling from North Beam like this, and just kind of distill it down into visual…

276 00:34:32.719 00:34:35.709 Zoran Selinger: presentations. That’s it. Okay?

277 00:34:35.710 00:34:42.419 Ryon: So, now, this process here, channel attribution incrementality, yes,

278 00:34:42.820 00:34:48.379 Ryon: Mitesh basically wants to see a dashboard, he wants us to build a process to understand

279 00:34:48.679 00:34:51.440 Ryon: Which channels are driving the most incrementality.

280 00:34:51.560 00:34:56.329 Ryon: I think that’s gonna be, like, a metric, we’re gonna have to measure that. And then,

281 00:34:56.850 00:35:03.470 Ryon: process for pulling, you know, data from Northbeam into a spreadsheet and then build a channel attribution dashboard. This, this fourth one here.

282 00:35:04.240 00:35:06.779 Ryon: That’s what this is, basically. That’s what he’s referring to.

283 00:35:06.780 00:35:12.359 Zoran Selinger: Yeah, that’s exactly what my… the attribution dash… this is just a table now, obviously.

284 00:35:13.300 00:35:17.960 Zoran Selinger: It’s not the idea, that this is the final… that that’s the final project.

285 00:35:18.210 00:35:18.739 Ryon: Yeah, yeah, I know.

286 00:35:18.740 00:35:19.319 Zoran Selinger: I just want to make.

287 00:35:19.320 00:35:29.189 Ryon: Yeah, we’re clear on that. Yeah, yeah. Okay. And then, weekly report, this one, look at the sheet I sent you, and tell me what you think, and then campaign tagging dashboard.

288 00:35:29.540 00:35:34.279 Zoran Selinger: I already done that, you see the UTM checker. So, we have two hidden fields.

289 00:35:34.410 00:35:41.180 Zoran Selinger: between F and I, if you look at those hidden fields, these are kind of the valid

290 00:35:41.430 00:35:43.780 Zoran Selinger: Sources and mediums that we have.

291 00:35:44.470 00:36:02.209 Zoran Selinger: And anything outside of that, I’m just highlighting in red. It’s nothing, nothing crazy. Obviously, we can do something more. I simply did not do any formatting, apart from this conditional formatting, right?

292 00:36:03.500 00:36:06.720 Zoran Selinger: So, this is basically pulling the last 7 days of data.

293 00:36:07.190 00:36:09.370 Zoran Selinger: Okay. That UTM checker, yeah.

294 00:36:09.960 00:36:12.280 Ryon: This one here, Intake Funnel Dashboard.

295 00:36:12.720 00:36:14.289 Ryon: Let’s talk about this.

296 00:36:14.530 00:36:15.940 Ryon: Are you off tomorrow?

297 00:36:16.390 00:36:17.449 Zoran Selinger: I am, I am.

298 00:36:17.450 00:36:22.710 Ryon: Okay. I’ll send you a video on this. I can tell you what I think he’s looking for here, and we can…

299 00:36:22.710 00:36:42.469 Zoran Selinger: Honestly, that scares me the most, because that’s the thing I understand the least about this business. Especially, so a really important thing that I wanted to bring up, and I’m going to bring it up in my update today, I’m going to send you the weekly slides that I have for today, and

300 00:36:42.710 00:36:47.830 Zoran Selinger: There’s gonna be a slide about risks, and… Ike.

301 00:36:48.180 00:37:02.720 Zoran Selinger: we are really uncomfortable with moving now away from Basque. I’m not sure if we’re ready for it. So, Ryan, we also need to, to talk about,

302 00:37:03.130 00:37:07.999 Zoran Selinger: what can break in tagging when that happens. This is very important.

303 00:37:08.000 00:37:15.850 Ryon: But I’m already ready for that. The only thing I would say is I’ve already been ready for that for a while. In fact, let’s talk about that for a second.

304 00:37:16.510 00:37:19.769 Ryon: Okay, this is what I want to do.

305 00:37:19.900 00:37:22.969 Ryon: inside of GTM.

306 00:37:27.890 00:37:31.869 Ryon: We’re gonna create… A new container.

307 00:37:31.870 00:37:32.710 Zoran Selinger: Okay.

308 00:37:32.910 00:37:34.909 Ryon: Alright, underneath here.

309 00:37:35.140 00:37:36.020 Zoran Selinger: Okay.

310 00:37:36.020 00:37:42.399 Ryon: The reason for this is twofold. A, I want to have a space where we set things fresh and clean.

311 00:37:42.540 00:38:00.939 Ryon: Okay? Okay. We start fresh and clean. B, I want to make sure that if anyone out there is snooping on our container to see edits, which it seems like the answer to that question is yes, they don’t see that we’re making edits and updates to new URLs, or to new changes or things like that, and, you know, pick up on things, okay?

312 00:38:01.830 00:38:14.899 Ryon: Also, it sets the container up in a way where you and I are the ones who know everything, and we don’t have to worry about trying to answer this or that from whoever built whatever back when. We know what was built from start to finish, because we built it.

313 00:38:14.930 00:38:26.279 Ryon: Okay. Okay? So, set up a new container here. Now, that said, I remain confident in the team that we’ll get off of BASC pretty soon. My only thing is…

314 00:38:28.910 00:38:35.019 Ryon: I’m very concerned. They don’t understand how much work there still is to be done to get us to MVP.

315 00:38:35.180 00:38:38.040 Ryon: But… Fine, right?

316 00:38:38.330 00:38:40.179 Zoran Selinger: That’s not going to happen soon, then.

317 00:38:40.870 00:38:55.339 Ryon: I’m… I’m… I don’t know. I don’t have an answer for you. I’m holding out hope, but preparing for a world where it’s not going to be immediate. That’s all I’m saying. Now, from your perspective, what I would say is, you and I just need to be foolproof.

318 00:38:55.460 00:39:01.909 Ryon: So, what I would propose is create a new container, and then I can earmark

319 00:39:02.030 00:39:07.000 Ryon: What we’re pulling… what we need to pull over, and what needs to stay, and we can just…

320 00:39:07.290 00:39:21.810 Ryon: start fresh, okay? Now, what’s gonna break? I can tell you the triggers that are gonna break, because I know the triggers that are gonna break, I can tell you the stuff that’s gonna break, so I can tell you what’s gonna break. And I can start a… why don’t we start a project for that as quick as possible?

321 00:39:22.120 00:39:22.480 Zoran Selinger: Okay.

322 00:39:22.480 00:39:24.970 Ryon: But… Okay,

323 00:39:25.630 00:39:34.749 Ryon: as far as this is concerned, just give me an idea, how are we doing on the attribution stuff? Like, how long do you think you have until you have the dashboard or everything ready? I’m just trying to get a sense.

324 00:39:35.180 00:39:40.619 Zoran Selinger: Are we talking about the… A particular number here.

325 00:39:40.840 00:39:41.630 Zoran Selinger: Or the fall.

326 00:39:41.630 00:39:43.140 Ryon: Number 3, yes, number three.

327 00:39:43.140 00:39:46.939 Zoran Selinger: Oh, yeah, yeah. 2 weeks, because…

328 00:39:47.280 00:39:56.199 Zoran Selinger: I think it can happen next week as well. It’s just about, how soon I get,

329 00:39:57.820 00:40:07.789 Zoran Selinger: I get the data guys to give me a model. It’s just about that, and then Amber to kind of format it a little bit.

330 00:40:08.250 00:40:17.360 Zoran Selinger: So, it can happen next week, maybe. But we need to figure out what to do in terms of, in terms of…

331 00:40:19.780 00:40:21.810 Zoran Selinger: the attribution model.

332 00:40:23.580 00:40:26.430 Zoran Selinger: We need to decide on something, right?

333 00:40:26.430 00:40:30.469 Ryon: I’ll call it social on what criteria he wants, and we’ll just figure that out.

334 00:40:30.470 00:40:31.010 Zoran Selinger: Yeah.

335 00:40:31.180 00:40:36.239 Zoran Selinger: If you can get that answer, so look at the… look at the Norbit.

336 00:40:36.240 00:40:43.729 Ryon: Give me a list of questions you need answered, like attribution window, preferred model, like, whatever you want, and I’ll make sure I get that answer for you.

337 00:40:43.730 00:40:49.160 Zoran Selinger: Okay, okay. So, would you be happy with having that portion done next week?

338 00:40:49.430 00:41:01.340 Ryon: Yes. We absolutely need it done next week. This has been long overdue, but we absolutely need it done next week. Okay. Now, as for, the… this one, number 2 here.

339 00:41:01.610 00:41:03.220 Ryon: Take a look at this.

340 00:41:03.470 00:41:17.480 Ryon: and just start earmarking all the metrics that you know, where we can find them, and we’ll start building this out. I sort of see this as just like you did here, like a large query. You’re gonna pull all the data in, or maybe you aggregate it from a lot of different…

341 00:41:17.620 00:41:29.289 Zoran Selinger: We’ll probably have to use polyatomic and aggregate it in a single table. There’s gonna be modeling, I’m already preparing the guys for it, so they’re aware that this work is coming.

342 00:41:29.560 00:41:36.290 Ryon: Right, put it into a stage like this, and then just a weekly projection, formatted similar to what I have here.

343 00:41:36.670 00:41:40.540 Ryon: And we can then… Start working on phasing things out.

344 00:41:40.710 00:41:41.410 Zoran Selinger: Okay.

345 00:41:41.440 00:41:46.189 Ryon: Okay? Those would be the two main things. What am I looking at? I’m not looking at the right thing.

346 00:41:46.400 00:41:50.370 Ryon: This you’ve already kind of done.

347 00:41:51.270 00:41:54.419 Ryon: Which is good. We need to go over this a bit more.

348 00:41:57.760 00:42:10.379 Zoran Selinger: we have some standard things that are not on the list, that have been here for a while. So, the list that I have, is essentially from when Henry had the…

349 00:42:10.380 00:42:21.280 Zoran Selinger: UTM tagging session with you guys, so I have those standards. And people are pretty good at adhering to the standards.

350 00:42:22.270 00:42:29.320 Zoran Selinger: Obviously, anything capitalized is just the… those are just the handles of… influencers.

351 00:42:29.500 00:42:35.149 Zoran Selinger: And those are all fine, actually. So, anything capitalized is actually fine.

352 00:42:35.150 00:42:37.070 Ryon: These are just influencer names. The team…

353 00:42:37.070 00:42:47.289 Zoran Selinger: influencer name, those are actually fine. But the idea is for every single campaign manager to come in and just have a quick look

354 00:42:47.430 00:42:48.840 Zoran Selinger: regularly.

355 00:42:50.170 00:42:57.650 Zoran Selinger: And just see if anything pertaining to them is read, and just, you know, fix it.

356 00:42:58.970 00:43:01.250 Zoran Selinger: I don’t know if you want to enforce that.

357 00:43:01.610 00:43:10.370 Ryon: I am gonna enforce that. In fact, I’m gonna make an announcement in the channel, so much so that, what I’m gonna do here is,

358 00:43:11.690 00:43:13.499 Ryon: This is auto-updating, right?

359 00:43:13.890 00:43:20.389 Zoran Selinger: Yes, if you go to, to the hidden sheet, Distinct UTMs.

360 00:43:20.590 00:43:24.130 Zoran Selinger: And go to the connection settings.

361 00:43:24.130 00:43:27.850 Ryon: Not the connection settings, but the refresh options.

362 00:43:28.400 00:43:34.860 Zoran Selinger: You will see that we are doing a refresh, every…

363 00:43:39.030 00:43:40.100 Zoran Selinger: Every day.

364 00:43:40.480 00:43:50.450 Ryon: Okay, so here’s what I want you to do for this. Take those two components and make them their own file, and we’ll call it UTM Auditor.

365 00:43:50.670 00:43:51.729 Ryon: Or something?

366 00:43:51.820 00:43:54.600 Zoran Selinger: Sorry, which two components, sorry.

367 00:43:54.600 00:44:03.010 Ryon: Take the distinct UTMs, this connection here, hide it, so they can’t see it, and then UTM Checker, make these two things their own file.

368 00:44:03.010 00:44:03.420 Zoran Selinger: Okay.

369 00:44:03.420 00:44:05.519 Ryon: And we’ll call it UTM Auditor.

370 00:44:05.850 00:44:22.600 Ryon: or daily UTM auditor, and then I’ll share that out with the group and say, hey everybody, Zarin has been working to make sure that we monitor our UTMs on a regular basis. This is now an automated tool, which allows you to see which UTMs are being hit, you know, the number of touchpoints within the last few days.

371 00:44:22.720 00:44:26.670 Ryon: Please take a look at ones marked in red. These are things that…

372 00:44:27.100 00:44:31.040 Ryon: are outliers we don’t understand and are causing problems. Something like that.

373 00:44:31.360 00:44:31.770 Zoran Selinger: Yeah.

374 00:44:31.770 00:44:32.420 Ryon: Mmm.

375 00:44:33.430 00:44:34.150 Ryon: Yep.

376 00:44:34.510 00:44:35.350 Ryon: Okay.

377 00:44:35.780 00:44:41.509 Zoran Selinger: And if they, yeah, if anything new becomes standard, we just add it to the hidden columns, and…

378 00:44:41.820 00:44:43.299 Ryon: It should be fine. Yep.

379 00:44:43.750 00:44:46.010 Zoran Selinger: Okay, I’ll do that today.

380 00:44:46.280 00:44:50.409 Ryon: That’s perfect. I’ll send it out tomorrow. Now, outside of that.

381 00:44:50.880 00:45:01.920 Ryon: This stuff here, this is where I’m representing these tickets for you, in the Sprint, just so you’re aware. I’m representing, I think it’s 1 to 3, or sorry, 2 to 3, so 2…

382 00:45:02.770 00:45:07.269 Ryon: Yeah, so… This one here, I’ll call this one in review.

383 00:45:07.660 00:45:08.530 Zoran Selinger: God.

384 00:45:08.750 00:45:09.850 Ryon: Ceremonials.

385 00:45:10.030 00:45:17.400 Ryon: Okay, cool. Alright, I’ll make an announcement once that one’s done, and then, yep.

386 00:45:20.740 00:45:23.620 Zoran Selinger: Okay, let me, let me do that, and .

387 00:45:24.630 00:45:25.899 Ryon: I think it’s a good start.

388 00:45:25.900 00:45:28.020 Zoran Selinger: At some point… Talk on Monday if we…

389 00:45:28.020 00:45:31.229 Ryon: I’m gonna set up a ticket for GTM migration.

390 00:45:38.370 00:45:43.420 Ryon: I’m gonna set up a ticket for GTM migration, and then add some notes in there for you and I.

391 00:45:43.710 00:45:53.130 Ryon: To discuss, because I don’t think it’s gonna be as big as we make it out to be. Since everything’s gonna be split out onto a URL, I think it’s gonna make sense for us to just…

392 00:45:53.360 00:45:57.159 Ryon: Yeah. I don’t think it’s gonna be as complicated as we make it out to be, but we’ll see.

393 00:45:57.240 00:45:59.920 Zoran Selinger: We’ll see. Okay. Alright? Cool, cool.

394 00:45:59.920 00:46:02.479 Ryon: Thanks, Aaron. Appreciate it. Hey, enjoy your day off. Talk soon.

395 00:46:02.480 00:46:03.809 Zoran Selinger: Yeah, thanks, bye.