Meeting Title: AE-Planning-Session Date: 2024-08-26 Meeting participants: Ryan Luke Daque, Nicolas Sucari, Suraj
WEBVTT
1 00:00:30.770 ⇒ 00:00:31.580 Nicolas Sucari: Hi guys.
2 00:00:33.420 ⇒ 00:00:35.050 suraj: Ken Nicholas. He ran.
3 00:00:38.210 ⇒ 00:00:38.990 Nicolas Sucari: User, ash.
4 00:00:39.810 ⇒ 00:00:40.729 suraj: Good, good.
5 00:00:42.470 ⇒ 00:00:43.160 Ryan Luke Daque: Hello!
6 00:00:43.330 ⇒ 00:00:44.196 Ryan Luke Daque: Hi guys.
7 00:00:44.880 ⇒ 00:00:45.680 suraj: Iran.
8 00:00:46.120 ⇒ 00:00:46.620 Ryan Luke Daque: As you’re.
9 00:00:46.620 ⇒ 00:00:47.000 Nicolas Sucari: Yeah.
10 00:00:47.900 ⇒ 00:00:50.619 suraj: Good! How how about you? How are you feeling now?
11 00:00:51.240 ⇒ 00:00:55.180 Ryan Luke Daque: Yeah, I’m feeling a lot better than last Friday. So yeah, thanks.
12 00:00:56.040 ⇒ 00:00:56.970 Nicolas Sucari: Awesome.
13 00:00:57.540 ⇒ 00:00:58.109 suraj: It’s a good thing.
14 00:00:58.110 ⇒ 00:01:00.610 Nicolas Sucari: It was a tough week for you. Yeah.
15 00:01:00.610 ⇒ 00:01:01.220 Ryan Luke Daque: Yeah.
16 00:01:01.810 ⇒ 00:01:05.609 Ryan Luke Daque: like, the the past 2 weeks were pretty tough because of like.
17 00:01:06.150 ⇒ 00:01:07.130 Ryan Luke Daque: I don’t know you’ll.
18 00:01:07.130 ⇒ 00:01:07.540 Nicolas Sucari: Necessary.
19 00:01:07.540 ⇒ 00:01:08.780 Ryan Luke Daque: Yeah, I don’t know.
20 00:01:10.730 ⇒ 00:01:14.379 Nicolas Sucari: Is your your audition? Will you be covered.
21 00:01:16.786 ⇒ 00:01:17.880 Ryan Luke Daque: Not really.
22 00:01:17.880 ⇒ 00:01:19.090 Nicolas Sucari: Here, well now.
23 00:01:19.090 ⇒ 00:01:20.179 Ryan Luke Daque: Still not really.
24 00:01:20.420 ⇒ 00:01:26.210 Ryan Luke Daque: Yeah. I I just went to the doctor last Friday, and like they and she gave me, like
25 00:01:26.840 ⇒ 00:01:28.631 Ryan Luke Daque: some other set of
26 00:01:29.530 ⇒ 00:01:35.349 Ryan Luke Daque: medicines to take. So I’ll be like, I need to go back after an another week.
27 00:01:35.560 ⇒ 00:01:37.250 Ryan Luke Daque: you know, for another check up. So yeah.
28 00:01:38.200 ⇒ 00:01:41.159 Ryan Luke Daque: But it’s it’s a lot better now, actually, so, yeah.
29 00:01:42.570 ⇒ 00:01:43.310 Nicolas Sucari: Nice.
30 00:01:44.790 ⇒ 00:01:47.819 Nicolas Sucari: or were you able to relax the weekend.
31 00:01:48.200 ⇒ 00:01:49.560 Ryan Luke Daque: Yeah, I think I slept
32 00:01:49.890 ⇒ 00:01:53.001 Ryan Luke Daque: 12 h straight on Sunday. So yeah.
33 00:01:56.670 ⇒ 00:01:59.479 Nicolas Sucari: Sometimes you need that that amount of sleep. Yeah.
34 00:01:59.480 ⇒ 00:02:00.240 Ryan Luke Daque: Yeah.
35 00:02:02.400 ⇒ 00:02:09.160 Nicolas Sucari: Excellent. Okay, guys, I don’t think Uta is gonna join. Today. He was working on some sales stuff.
36 00:02:09.720 ⇒ 00:02:16.050 Nicolas Sucari: And yeah, we we can start. I have some stuff I want to run by you guys.
37 00:02:17.710 ⇒ 00:02:33.489 Nicolas Sucari: I think, Ryan, you were working last week on those reports, those dashboards on real to add the customer lifetime value and revenue loss for some of the paid marketing performance. Dashboard right.
38 00:02:33.490 ⇒ 00:02:34.580 Ryan Luke Daque: Right, yeah.
39 00:02:35.850 ⇒ 00:02:37.859 Nicolas Sucari: Okay, perfect. I think.
40 00:02:37.860 ⇒ 00:02:39.754 Ryan Luke Daque: Stuff that I have to be.
41 00:02:40.470 ⇒ 00:02:43.060 Ryan Luke Daque: yeah, I think there’s still a like a ticket
42 00:02:43.120 ⇒ 00:02:44.889 Ryan Luke Daque: open that I need to do
43 00:02:45.050 ⇒ 00:02:46.875 Ryan Luke Daque: for a dashboard, I guess.
44 00:02:47.480 ⇒ 00:02:47.960 Ryan Luke Daque: and look.
45 00:02:47.960 ⇒ 00:02:52.029 Nicolas Sucari: Yeah. The the one that is missing is, yeah. The Daily Kpis, one.
46 00:02:52.030 ⇒ 00:02:52.830 Ryan Luke Daque: Yeah.
47 00:02:52.830 ⇒ 00:02:53.810 Nicolas Sucari: Dimensions.
48 00:02:53.810 ⇒ 00:02:54.460 Ryan Luke Daque: Yeah.
49 00:02:54.460 ⇒ 00:02:56.019 Nicolas Sucari: That’s okay. I wanna
50 00:02:56.800 ⇒ 00:03:04.250 Nicolas Sucari: When I go through the the issue that we are having with the post pilot conversion list.
51 00:03:04.694 ⇒ 00:03:11.625 Nicolas Sucari: Maybe something I I know. So, Raj, that you can’t work on real yet because your computer is not
52 00:03:12.320 ⇒ 00:03:20.209 Nicolas Sucari: yeah, you you can’t install real on your computer yet, but probably something we can look into in in Snowflake.
53 00:03:21.870 ⇒ 00:03:33.750 Nicolas Sucari: I I’m like, I’m trying to understand what is the difference between the 2 conversions lists that we are having from post pilots. Or probably guys, I can show you, because we have 2 lists that we are importing from the emails.
54 00:03:33.830 ⇒ 00:03:40.430 Nicolas Sucari: Right, Brian. We have one that is called Conversions List, and the other one is like the overview report.
55 00:03:40.710 ⇒ 00:03:42.310 Ryan Luke Daque: Right, right.
56 00:03:43.440 ⇒ 00:03:50.479 Nicolas Sucari: So what I’m trying to understand is if we are using the conversion list anyway, or we are just using the
57 00:03:51.395 ⇒ 00:03:53.450 Nicolas Sucari: the overview report.
58 00:03:53.900 ⇒ 00:03:56.289 Nicolas Sucari: because I don’t think we are using
59 00:03:56.550 ⇒ 00:03:59.740 Nicolas Sucari: the conversions list anywhere, anywhere.
60 00:04:00.180 ⇒ 00:04:02.320 Ryan Luke Daque: Yeah, let me check.
61 00:04:03.510 ⇒ 00:04:07.380 Nicolas Sucari: I can. I can open up Snowflake if you want
62 00:04:08.196 ⇒ 00:04:09.450 Nicolas Sucari: yeah share.
63 00:04:09.630 ⇒ 00:04:11.989 Nicolas Sucari: so that we can all see that.
64 00:04:12.390 ⇒ 00:04:13.760 Nicolas Sucari: Sure. I mean, I’ll.
65 00:04:14.470 ⇒ 00:04:16.640 Ryan Luke Daque: Also open up
66 00:04:18.970 ⇒ 00:04:20.929 Ryan Luke Daque: the repo and see if we can.
67 00:04:21.089 ⇒ 00:04:23.349 Ryan Luke Daque: If I can find anything that’s
68 00:04:25.210 ⇒ 00:04:27.960 Ryan Luke Daque: that shows that we’re using it, or something.
69 00:04:30.970 ⇒ 00:04:31.600 Nicolas Sucari: Okay.
70 00:04:32.860 ⇒ 00:04:38.909 Nicolas Sucari: I need, I will share so that you suresh can start looking into this, too.
71 00:04:40.820 ⇒ 00:04:43.430 Nicolas Sucari: 2 factorial education.
72 00:04:45.440 ⇒ 00:04:46.110 Nicolas Sucari: Okay?
73 00:04:52.270 ⇒ 00:04:55.119 Nicolas Sucari: Okay. Yeah.
74 00:04:55.230 ⇒ 00:04:57.920 Nicolas Sucari: Let me let me know if you are seeing the screen.
75 00:04:58.050 ⇒ 00:04:58.630 Nicolas Sucari: Yeah.
76 00:05:01.250 ⇒ 00:05:02.930 Nicolas Sucari: okay. So we have, like.
77 00:05:04.610 ⇒ 00:05:06.480 Nicolas Sucari: you have 2 lists. Right?
78 00:05:07.182 ⇒ 00:05:13.520 Nicolas Sucari: Post pilot. Rush. Just for you to know is like an email service is for direct emails
79 00:05:13.864 ⇒ 00:05:20.260 Nicolas Sucari: the cool parts is using. So we have conversions like this is the tool. Probably I can show you here.
80 00:05:21.440 ⇒ 00:05:22.130 Nicolas Sucari: Yeah.
81 00:05:23.092 ⇒ 00:05:29.589 Nicolas Sucari: So we have some campaigns set up here. And yeah, we are just like tracking conversions
82 00:05:29.660 ⇒ 00:05:31.549 Nicolas Sucari: and returns on ad spend.
83 00:05:31.600 ⇒ 00:05:35.430 Nicolas Sucari: So we have like this report here that’s called Conversions Lists.
84 00:05:35.590 ⇒ 00:05:36.660 Nicolas Sucari: Okay?
85 00:05:37.150 ⇒ 00:05:46.319 Nicolas Sucari: Which, where? Where we can like, see all of the conversions by conversion, date, and which was the campaign and that kind of stuff and the total price.
86 00:05:47.610 ⇒ 00:05:55.330 Nicolas Sucari: we are receiving, like a report, a daily report of these through email, and 1 1 other report that is not here.
87 00:05:55.540 ⇒ 00:06:17.470 Nicolas Sucari: and there is a difference on the conversions, because this one that says Conversions list is looking by like it’s filtering the conversions by conversions date. So I think that’s fine, like we can see all of the conversions by conversion state. But the other one that we received. It’s called overview. It’s like it’s using the postcard date.
88 00:06:17.530 ⇒ 00:06:19.590 Nicolas Sucari: And that’s something that I’m like
89 00:06:19.700 ⇒ 00:06:32.909 Nicolas Sucari: trying to understand, because I don’t get why we’re using like the postcard date and not the conversion date, I mean. I think it’s because we need to relate or try trying to match the conversion on
90 00:06:33.813 ⇒ 00:06:36.230 Nicolas Sucari: when that postcard was sent.
91 00:06:36.240 ⇒ 00:06:41.409 Nicolas Sucari: so that we can like understand the performance of each of the campaigns.
92 00:06:41.850 ⇒ 00:06:49.109 Nicolas Sucari: But yeah, I mean, we are receiving 2 different things, 2 different things. So in Snowflake I was trying to understand that and try to see.
93 00:06:49.200 ⇒ 00:06:50.630 Nicolas Sucari: For example, these
94 00:06:50.700 ⇒ 00:06:56.140 Nicolas Sucari: is the Conversions list that we were just seeing that report. And I was trying to see if this one is like.
95 00:06:57.690 ⇒ 00:07:03.610 Nicolas Sucari: this is what we we saw there. And I think we are still okay. I’m not gonna limit it.
96 00:07:06.490 ⇒ 00:07:07.190 Nicolas Sucari: Okay?
97 00:07:07.886 ⇒ 00:07:23.029 Nicolas Sucari: I I think we are receiving, like all of the different conversions I need to check like the table. But yeah, I think all of these conversions we are. We are receiving them. But if we go to the other one, that in
98 00:07:23.670 ⇒ 00:07:26.120 Nicolas Sucari: whose pilot I think it’s
99 00:07:27.110 ⇒ 00:07:28.480 Nicolas Sucari: and marked.
100 00:07:28.680 ⇒ 00:07:30.329 Nicolas Sucari: Let me see if it was here.
101 00:07:32.090 ⇒ 00:07:33.950 Nicolas Sucari: No, it was in 5. Grand sorry.
102 00:07:38.250 ⇒ 00:07:41.579 Nicolas Sucari: Yeah. This one is the other one, the post pilot overview. Report
103 00:07:42.920 ⇒ 00:07:44.540 Nicolas Sucari: me go like
104 00:07:50.810 ⇒ 00:07:57.629 Nicolas Sucari: here we are not like we’re. We’re not getting all of the conversions. This is like the issue that I’m trying to understand
105 00:07:57.670 ⇒ 00:08:00.640 Nicolas Sucari: and see, how can we like
106 00:08:00.660 ⇒ 00:08:06.139 Nicolas Sucari: get the correct conversions? Because I think, Ryan, we are using this table
107 00:08:06.240 ⇒ 00:08:09.949 Nicolas Sucari: to populate our dashboard in real right.
108 00:08:11.460 ⇒ 00:08:13.730 Ryan Luke Daque: Yeah, so it looks like.
109 00:08:14.400 ⇒ 00:08:18.589 Ryan Luke Daque: yeah, I’m looking at the code base at the moment. So it looks like
110 00:08:18.610 ⇒ 00:08:21.310 Ryan Luke Daque: the conversions list was.
111 00:08:22.120 ⇒ 00:08:26.670 Ryan Luke Daque: So originally, we were using the post pilot overview report. So
112 00:08:27.040 ⇒ 00:08:27.685 Ryan Luke Daque: yeah,
113 00:08:28.830 ⇒ 00:08:33.620 Ryan Luke Daque: I’ll maybe maybe it would be better if I can share my screen. So maybe.
114 00:08:33.620 ⇒ 00:08:34.730 Nicolas Sucari: Yeah, of course.
115 00:08:35.500 ⇒ 00:08:38.210 Ryan Luke Daque: You can explain it.
116 00:08:39.289 ⇒ 00:08:40.370 Ryan Luke Daque: anyway.
117 00:08:41.929 ⇒ 00:08:43.539 Ryan Luke Daque: Yep. Can you see my screen.
118 00:08:43.900 ⇒ 00:08:44.660 suraj: Yeah.
119 00:08:44.660 ⇒ 00:08:45.240 Nicolas Sucari: Yep.
120 00:08:45.850 ⇒ 00:08:46.579 Ryan Luke Daque: So
121 00:08:49.060 ⇒ 00:08:52.010 Ryan Luke Daque: before we move that to
122 00:08:52.880 ⇒ 00:08:54.279 Ryan Luke Daque: what do you call this
123 00:08:55.220 ⇒ 00:09:01.699 Ryan Luke Daque: before we move that to 5 grand it was we were doing it manually right. And we were adding it into this
124 00:09:01.720 ⇒ 00:09:02.839 Ryan Luke Daque: Google sheet.
125 00:09:02.920 ⇒ 00:09:05.359 Ryan Luke Daque: the Ppt. 2 G. Google sheets.
126 00:09:05.360 ⇒ 00:09:06.090 Nicolas Sucari: Yeah.
127 00:09:06.250 ⇒ 00:09:10.349 Ryan Luke Daque: So originally it was only this one direct mail.
128 00:09:10.630 ⇒ 00:09:15.700 Ryan Luke Daque: this tab, direct mail, and this is the same as the
129 00:09:17.060 ⇒ 00:09:17.950 Nicolas Sucari: Overview.
130 00:09:18.550 ⇒ 00:09:20.740 Ryan Luke Daque: The overview report. That’s correct. Yeah.
131 00:09:20.930 ⇒ 00:09:21.840 Ryan Luke Daque: And
132 00:09:22.860 ⇒ 00:09:24.340 Ryan Luke Daque: based on
133 00:09:25.430 ⇒ 00:09:30.810 Ryan Luke Daque: what we have here. It’s being used by this specific model at the direct mail staging model.
134 00:09:30.960 ⇒ 00:09:36.250 Ryan Luke Daque: and it is also used. And in this specific staging model.
135 00:09:39.220 ⇒ 00:09:40.720 Ryan Luke Daque: wait looks like.
136 00:09:41.570 ⇒ 00:09:43.689 Ryan Luke Daque: let me reopen that
137 00:09:47.380 ⇒ 00:09:51.959 Ryan Luke Daque: the staging model is being used by the team’s weekly report
138 00:09:53.630 ⇒ 00:09:54.470 Ryan Luke Daque: and
139 00:09:54.650 ⇒ 00:09:58.289 Ryan Luke Daque: combined marketing performance report. So
140 00:09:59.540 ⇒ 00:10:01.420 Ryan Luke Daque: it’s still loading.
141 00:10:03.860 ⇒ 00:10:06.879 Nicolas Sucari: Yeah. So if it is being used by the combined marketing.
142 00:10:06.880 ⇒ 00:10:07.210 Ryan Luke Daque: Yeah.
143 00:10:07.537 ⇒ 00:10:13.099 Nicolas Sucari: Model. It’s it’s the one that we are using unreal. We’re not using the conversions list right.
144 00:10:13.100 ⇒ 00:10:17.200 Ryan Luke Daque: Well, that’s the the thing is, I think Utam created this
145 00:10:17.240 ⇒ 00:10:21.309 Ryan Luke Daque: direct mail conversions. Model! Which is
146 00:10:21.410 ⇒ 00:10:23.510 Ryan Luke Daque: being used by one of the
147 00:10:23.940 ⇒ 00:10:24.950 Ryan Luke Daque: real
148 00:10:25.757 ⇒ 00:10:29.879 Ryan Luke Daque: tables as well, or like a dashboards as well.
149 00:10:30.120 ⇒ 00:10:31.480 Ryan Luke Daque: So if we look at
150 00:10:31.760 ⇒ 00:10:33.940 Ryan Luke Daque: direct mail conversions.
151 00:10:36.300 ⇒ 00:10:37.810 Ryan Luke Daque: I think it’s this one.
152 00:10:38.600 ⇒ 00:10:39.260 Ryan Luke Daque: Nope.
153 00:10:44.830 ⇒ 00:10:49.020 Nicolas Sucari: Yeah, I was trying to look for this one, and I couldn’t find it last week.
154 00:10:50.381 ⇒ 00:10:53.120 Ryan Luke Daque: This one direct mail by order. Item.
155 00:10:53.510 ⇒ 00:10:56.220 Ryan Luke Daque: So it’s using direct mail conversions
156 00:10:57.100 ⇒ 00:10:59.780 Ryan Luke Daque: also this direct mail by order.
157 00:11:00.870 ⇒ 00:11:02.660 Ryan Luke Daque: So this, too.
158 00:11:03.000 ⇒ 00:11:06.479 Ryan Luke Daque: are using this one, the direct mail conversions.
159 00:11:07.840 ⇒ 00:11:08.450 Ryan Luke Daque: and I think.
160 00:11:08.450 ⇒ 00:11:08.850 Nicolas Sucari: Hmm.
161 00:11:08.850 ⇒ 00:11:09.890 Ryan Luke Daque: Reference?
162 00:11:09.950 ⇒ 00:11:10.849 Ryan Luke Daque: Right? Because
163 00:11:11.390 ⇒ 00:11:15.480 Ryan Luke Daque: the the the old one, the direct mail, which is the
164 00:11:16.120 ⇒ 00:11:22.050 Ryan Luke Daque: oh, what was that? The list or the conversion? Yeah, the list doesn’t have conversions.
165 00:11:22.750 ⇒ 00:11:32.479 Ryan Luke Daque: it only has, like the revenue, the cost, robust orders, but no conversions, whereas the other one has the conversions right? The total price. I guess
166 00:11:32.720 ⇒ 00:11:37.927 Ryan Luke Daque: it’s different. And it also has coupon code. So it’s it’s a totally different
167 00:11:39.390 ⇒ 00:11:42.900 Ryan Luke Daque: different data cause. It’s by campaign. Id.
168 00:11:46.220 ⇒ 00:11:47.030 Nicolas Sucari: Okay.
169 00:11:47.730 ⇒ 00:12:06.199 Nicolas Sucari: But what? What does it mean? Because we have, like 3 different reports on on real. We have direct mail conversions for order items. We have direct mail conversions just for orders, and then we have one that says direct mail, and then we have paid marketing performance, and we have, like revenue there.
170 00:12:06.330 ⇒ 00:12:12.459 Nicolas Sucari: and all of the metrics, and like it doesn’t seem right. I think.
171 00:12:13.220 ⇒ 00:12:14.479 Ryan Luke Daque: Yeah, that’s a
172 00:12:15.490 ⇒ 00:12:17.319 Ryan Luke Daque: that’s a good question. I
173 00:12:18.080 ⇒ 00:12:26.879 Ryan Luke Daque: I’m also not quite sure, because I I didn’t create this direct mail by order. I I haven’t really like taken a look into like what this does.
174 00:12:27.700 ⇒ 00:12:32.416 Ryan Luke Daque: but it looks like it’s it’s the direct mails joined by the
175 00:12:33.250 ⇒ 00:12:39.220 Ryan Luke Daque: shopify order items or in in the orders case, it’s just shopify orders.
176 00:12:39.600 ⇒ 00:12:40.640 Ryan Luke Daque: So I think
177 00:12:41.560 ⇒ 00:12:43.000 Ryan Luke Daque: I think this is
178 00:12:45.080 ⇒ 00:12:48.499 Ryan Luke Daque: This is how autumn is trying to
179 00:12:48.780 ⇒ 00:12:49.690 Ryan Luke Daque: link
180 00:12:50.150 ⇒ 00:12:51.699 Ryan Luke Daque: the orders to
181 00:12:52.480 ⇒ 00:12:53.769 Ryan Luke Daque: the direct mail
182 00:12:55.280 ⇒ 00:12:55.910 Ryan Luke Daque: data
183 00:12:56.260 ⇒ 00:12:58.599 Ryan Luke Daque: and based based on the email
184 00:13:00.120 ⇒ 00:13:01.860 Ryan Luke Daque: and conversion date.
185 00:13:03.730 ⇒ 00:13:04.330 Nicolas Sucari: Okay.
186 00:13:04.330 ⇒ 00:13:05.430 Ryan Luke Daque: I shouldn’t name.
187 00:13:07.420 ⇒ 00:13:08.400 Ryan Luke Daque: Yeah.
188 00:13:10.780 ⇒ 00:13:11.724 Nicolas Sucari: Okay.
189 00:13:13.440 ⇒ 00:13:18.150 Ryan Luke Daque: Whereas the others, like direct Mail doesn’t have any customer related
190 00:13:18.710 ⇒ 00:13:20.180 Ryan Luke Daque: data. It’s just
191 00:13:20.260 ⇒ 00:13:22.350 Ryan Luke Daque: it’s just whatever we have here.
192 00:13:22.840 ⇒ 00:13:23.510 Ryan Luke Daque: Yeah.
193 00:13:23.510 ⇒ 00:13:24.390 Nicolas Sucari: Exactly.
194 00:13:28.610 ⇒ 00:13:29.550 Nicolas Sucari: Okay.
195 00:13:30.250 ⇒ 00:13:32.079 Nicolas Sucari: I’m just trying to
196 00:13:32.670 ⇒ 00:13:34.460 Nicolas Sucari: understand. If we
197 00:13:35.630 ⇒ 00:13:44.760 Nicolas Sucari: okay, how can we like what? Because what I’m trying to do, I I mean, Kim is. I think, like she’s using the paid marketing performance dashboard.
198 00:13:45.040 ⇒ 00:13:45.630 Ryan Luke Daque: Okay.
199 00:13:45.630 ⇒ 00:13:49.060 Nicolas Sucari: Real the other 3. That
200 00:13:49.340 ⇒ 00:13:53.500 Nicolas Sucari: yeah, which is the the one that’s coming from combined marketing performance. Right?
201 00:13:53.500 ⇒ 00:13:54.190 Ryan Luke Daque: Right.
202 00:13:55.080 ⇒ 00:13:56.880 Ryan Luke Daque: which is just using
203 00:13:56.890 ⇒ 00:13:59.760 Ryan Luke Daque: the list, not the conversions. Yeah.
204 00:14:01.730 ⇒ 00:14:07.240 Nicolas Sucari: Yeah, exactly. It’s using the one that says overview that we that don’t have the conversions.
205 00:14:07.240 ⇒ 00:14:07.840 Ryan Luke Daque: Right.
206 00:14:08.140 ⇒ 00:14:11.070 Nicolas Sucari: The one that filters by postcard date.
207 00:14:12.000 ⇒ 00:14:21.960 Nicolas Sucari: Yeah, okay, I think we need to. Yeah, I don’t know. We need to check a little bit more about that new metrics that we added there, Brian, because.
208 00:14:22.520 ⇒ 00:14:26.119 Nicolas Sucari: like I don’t think all of them make sense.
209 00:14:29.620 ⇒ 00:14:30.489 Ryan Luke Daque: You mean like the.
210 00:14:30.490 ⇒ 00:14:31.050 Nicolas Sucari: Yeah.
211 00:14:32.060 ⇒ 00:14:34.560 Ryan Luke Daque: Conversions cost per acquisition.
212 00:14:36.840 ⇒ 00:14:39.359 Ryan Luke Daque: robust and revenue. I think we saw the 4.
213 00:14:39.360 ⇒ 00:14:40.430 Nicolas Sucari: Yeah, because I,
214 00:14:41.470 ⇒ 00:14:47.660 Nicolas Sucari: yeah, because, like, if in that report we are using like all platforms. But then we are, we don’t have the.
215 00:14:48.110 ⇒ 00:14:50.349 Nicolas Sucari: I don’t know. We don’t have, like Cpa.
216 00:14:50.390 ⇒ 00:15:07.620 Nicolas Sucari: that it was cost per conversion for direct mail, because we don’t have the conversions, and we don’t have the revenue for Facebook and Google, so that, like all of those measures, are kind of weird in the when you don’t filter it down by platform right.
217 00:15:10.460 ⇒ 00:15:11.739 Ryan Luke Daque: Can you say that again.
218 00:15:12.790 ⇒ 00:15:14.609 Nicolas Sucari: Yeah. Let me let me share again.
219 00:15:14.740 ⇒ 00:15:15.460 Ryan Luke Daque: Yeah, sure.
220 00:15:20.740 ⇒ 00:15:21.560 Nicolas Sucari: Okay.
221 00:15:24.800 ⇒ 00:15:30.010 Nicolas Sucari: so I’m looking to in this one. That’s the paid marketing performance. And
222 00:15:30.820 ⇒ 00:15:39.140 Nicolas Sucari: we don’t have, like Facebook, Google and Amazon re like the revenue. So when we look at like all of these.
223 00:15:40.010 ⇒ 00:15:51.510 Nicolas Sucari: like these metrics, or the return on Adsense like these 2, these 2 metrics are not like the real value because we are not adding Facebook, Google and Amazon revenues right?
224 00:15:53.330 ⇒ 00:16:01.550 Nicolas Sucari: Filter, just on Facebook, like, we don’t have data. But we are adding, like the costs and all of that. So these measures are also kind of
225 00:16:01.740 ⇒ 00:16:02.589 Nicolas Sucari: I don’t know.
226 00:16:04.710 ⇒ 00:16:07.330 Nicolas Sucari: It’s kind of I don’t know.
227 00:16:07.370 ⇒ 00:16:09.080 Nicolas Sucari: It’s it’s weird.
228 00:16:10.340 ⇒ 00:16:10.980 Ryan Luke Daque: It’s missing.
229 00:16:10.980 ⇒ 00:16:22.700 Nicolas Sucari: See. And we don’t have yeah. And and if we and when we go with for conversions, it’s missing the conversions for the direct mail because we’re we’re using the report and not the list. So we don’t get the conversions. So it’s kind of
230 00:16:22.860 ⇒ 00:16:29.780 Nicolas Sucari: those metrics are like we we have the information for part of the platforms, but not the entire platforms
231 00:16:30.171 ⇒ 00:16:36.479 Nicolas Sucari: so like the aggregate measure when we when you don’t filter by platform, is kind of
232 00:16:37.110 ⇒ 00:16:38.400 Nicolas Sucari: I don’t know, fucked up.
233 00:16:38.740 ⇒ 00:16:39.400 Ryan Luke Daque: Yeah.
234 00:16:39.920 ⇒ 00:16:42.209 Ryan Luke Daque: so it’s not complete. Basically.
235 00:16:42.210 ⇒ 00:16:49.980 Nicolas Sucari: Yeah, exactly. It’s not complete. And it’s kind of difficult to understand where, like, if, if I’m seeing the Cpa
236 00:16:50.030 ⇒ 00:16:51.430 Nicolas Sucari: like it’s kind of.
237 00:16:51.520 ⇒ 00:16:52.699 Nicolas Sucari: I don’t always
238 00:16:52.880 ⇒ 00:16:55.110 Nicolas Sucari: like this is real or not right.
239 00:16:56.380 ⇒ 00:16:57.670 Nicolas Sucari: because we don’t have the.
240 00:16:57.670 ⇒ 00:16:58.220 Ryan Luke Daque: Prison, spike.
241 00:16:58.220 ⇒ 00:16:59.020 Nicolas Sucari: Email.
242 00:16:59.610 ⇒ 00:17:00.470 Nicolas Sucari: you see.
243 00:17:01.820 ⇒ 00:17:02.360 Ryan Luke Daque: Yeah.
244 00:17:02.360 ⇒ 00:17:05.880 Nicolas Sucari: But we have the costs, but if I go to cost, we have the cost
245 00:17:07.599 ⇒ 00:17:08.380 Nicolas Sucari: right.
246 00:17:08.680 ⇒ 00:17:09.135 Ryan Luke Daque: Right.
247 00:17:13.310 ⇒ 00:17:15.840 Nicolas Sucari: So I don’t know if we need to like
248 00:17:18.290 ⇒ 00:17:19.840 Nicolas Sucari: remove these
249 00:17:20.440 ⇒ 00:17:24.069 Nicolas Sucari: values, or how can we like give the
250 00:17:24.777 ⇒ 00:17:26.449 Nicolas Sucari: give like clear
251 00:17:26.569 ⇒ 00:17:35.810 Nicolas Sucari: visibility on these metrics per platform, like, we need to create one report per each, because we we have this one direct mail
252 00:17:36.322 ⇒ 00:17:42.960 Nicolas Sucari: this just has, like the detail campaign name, and these measures, probably we can add.
253 00:17:43.270 ⇒ 00:17:55.150 Nicolas Sucari: we can add the measures for Cpa, Cpc Cpm. Revenue and all of those ones here. But that’s this should be just for direct mail. Right?
254 00:17:56.500 ⇒ 00:18:01.269 Nicolas Sucari: But how can we like work on that? To have like an aggregate
255 00:18:02.187 ⇒ 00:18:07.909 Nicolas Sucari: like like this should be like the mar, the aggregate report with everything. How can we?
256 00:18:08.020 ⇒ 00:18:14.689 Nicolas Sucari: I get these values like correctly working? Maybe it’s rash. You can help on this one, but I’m I’m not sure.
257 00:18:17.860 ⇒ 00:18:22.160 suraj: Yeah, I’m I’m looking. I’m thinking about it. So
258 00:18:26.020 ⇒ 00:18:33.230 suraj: so we don’t have the revenue or all the stuff in the in the database for this Google, Facebook or this.
259 00:18:33.370 ⇒ 00:18:34.800 suraj: All these platforms.
260 00:18:36.290 ⇒ 00:18:39.519 Nicolas Sucari: Yeah, we just have the revenue for
261 00:18:39.580 ⇒ 00:18:51.899 Nicolas Sucari: affiliates SMS and some direct mail. We don’t have Facebook, Google and Amazon. We need to try to see how to add these ones. I think, Ryan, you were like digging into this one, but I I don’t think we
262 00:18:52.110 ⇒ 00:18:58.460 Nicolas Sucari: like. I don’t know if we have, like a way on understanding the revenue of these ones.
263 00:18:59.030 ⇒ 00:19:04.931 Ryan Luke Daque: Yeah for Facebook and Google, I’ll have to do some further investigation. So we can
264 00:19:06.200 ⇒ 00:19:08.350 Ryan Luke Daque: we can split it by
265 00:19:09.200 ⇒ 00:19:11.019 Ryan Luke Daque: Id and Ad group.
266 00:19:11.470 ⇒ 00:19:16.759 Ryan Luke Daque: because currently, the conversions that we have for Facebook and Google are just on a campaign level.
267 00:19:20.140 ⇒ 00:19:20.810 Ryan Luke Daque: But they.
268 00:19:20.810 ⇒ 00:19:21.589 Nicolas Sucari: Even though.
269 00:19:21.590 ⇒ 00:19:22.740 Ryan Luke Daque: Down. Yeah.
270 00:19:23.200 ⇒ 00:19:25.390 Nicolas Sucari: What I’m what I’m seeing is that the ad
271 00:19:26.465 ⇒ 00:19:32.700 Nicolas Sucari: like the revenue is not being split by added set id, and add id.
272 00:19:32.920 ⇒ 00:19:40.769 Nicolas Sucari: I mean, they are just like normal values. So probably that’s not important. But we need to add, like the amount of revenues
273 00:19:41.500 ⇒ 00:19:42.290 Nicolas Sucari: right
274 00:19:44.020 ⇒ 00:19:46.099 Nicolas Sucari: by campaign Id only. Maybe.
275 00:19:46.950 ⇒ 00:19:49.270 Ryan Luke Daque: Yeah, but the that’s the that’s the.
276 00:19:49.870 ⇒ 00:19:56.049 Ryan Luke Daque: So if we wanted to show just campaign, then we can remove, add, and add set here.
277 00:19:56.390 ⇒ 00:19:57.870 Ryan Luke Daque: because if we
278 00:19:59.530 ⇒ 00:20:03.769 Ryan Luke Daque: if we include the data from the campaign, it would be like duplicating.
279 00:20:04.020 ⇒ 00:20:08.850 Ryan Luke Daque: Or if if there’s a specific, if there’s a campaign that has multiple ads, for example.
280 00:20:08.980 ⇒ 00:20:13.779 Ryan Luke Daque: like, if there are 10 ads, then the campaign for Facebook, I mean the the
281 00:20:13.990 ⇒ 00:20:17.489 Ryan Luke Daque: revenue for Facebook, for that specific campaign would be like
282 00:20:17.630 ⇒ 00:20:20.860 Ryan Luke Daque: duplicated 10 times one for each ad.
283 00:20:22.220 ⇒ 00:20:29.159 Ryan Luke Daque: So it would. Ideally, we should have, like the most granular level of revenue data.
284 00:20:29.530 ⇒ 00:20:30.830 Nicolas Sucari: Yeah, yeah, probably.
285 00:20:30.830 ⇒ 00:20:31.530 Ryan Luke Daque: Yeah.
286 00:20:34.590 ⇒ 00:20:41.379 Nicolas Sucari: Yeah, what I’m saying is like, we have everything. But I think it’s the only one that we don’t have is Romania.
287 00:20:41.850 ⇒ 00:20:42.510 Nicolas Sucari: Yep.
288 00:20:43.030 ⇒ 00:20:47.099 Nicolas Sucari: cause. We have impressions. We have everything. Conversion rate clicks.
289 00:20:47.470 ⇒ 00:20:51.339 Nicolas Sucari: See, we have everything. But we don’t have revenue on those.
290 00:20:53.930 ⇒ 00:20:54.780 Nicolas Sucari: Okay.
291 00:20:56.280 ⇒ 00:21:07.529 Nicolas Sucari: maybe. Sure as you can help looking into this with Ryan. I don’t know guys. If you want to work it together like, try to what we need to do to understand. If if this report
292 00:21:07.620 ⇒ 00:21:10.739 Nicolas Sucari: gives like a clear and accurate
293 00:21:12.270 ⇒ 00:21:16.700 Nicolas Sucari: way of of showing all of these measures to to Kim?
294 00:21:17.156 ⇒ 00:21:18.779 Nicolas Sucari: Because for now, like
295 00:21:19.283 ⇒ 00:21:24.889 Nicolas Sucari: she thinks like these measures are not accurate, and some of them are kind of
296 00:21:25.030 ⇒ 00:21:25.909 Nicolas Sucari: I don’t know.
297 00:21:26.230 ⇒ 00:21:29.279 Nicolas Sucari: not reflecting the real values.
298 00:21:30.660 ⇒ 00:21:34.710 Nicolas Sucari: I think Thorash is something that you can start looking into
299 00:21:35.093 ⇒ 00:21:49.859 Nicolas Sucari: by using snowflake and not real. Now, I mean, you can use real for exploration on what we already have. But if you need like any change on real, first, st we need to understand if we can do it through Snowflake. And if that’s if we get to the correct data, then
300 00:21:49.950 ⇒ 00:21:52.829 Nicolas Sucari: moving it into real. It should be something easy.
301 00:21:53.570 ⇒ 00:21:54.820 suraj: Yeah, yeah, true.
302 00:21:55.420 ⇒ 00:22:00.024 suraj: Yeah, of course. we are not showing the revenue, and we are showing the cost. It’s
303 00:22:00.320 ⇒ 00:22:02.359 suraj: it’s affecting the Cpa, right?
304 00:22:04.520 ⇒ 00:22:07.730 Nicolas Sucari: Yeah, I’m not a marketing expert, but
305 00:22:08.020 ⇒ 00:22:13.009 Nicolas Sucari: I don’t know if you have more experience on these kind of measures, and.
306 00:22:13.690 ⇒ 00:22:15.540 suraj: Yeah, yeah, yeah, so.
307 00:22:15.540 ⇒ 00:22:19.960 Nicolas Sucari: I hope? Yes. But yeah, I think we need to like review
308 00:22:20.150 ⇒ 00:22:26.599 Nicolas Sucari: these calculations and see like which data, how do we have for each of the platforms and see what we can do. There.
309 00:22:29.870 ⇒ 00:22:40.639 suraj: Yeah, yeah, I’ll I’ll I think I’ll I’ll get the laptop, probably by end of today. So in the meanwhile, also, I’ll look into the snowflake data and see what’s going on.
310 00:22:42.120 ⇒ 00:22:56.280 Nicolas Sucari: Perfect. Okay? I mean, I think it’s something you can track using the code. This code like, Ryan was just showing where we have. I think that models is in staging. I think Ryan right.
311 00:22:58.070 ⇒ 00:22:58.640 Ryan Luke Daque: Yep.
312 00:22:58.640 ⇒ 00:23:02.809 Nicolas Sucari: Limiting mode staging. I think there is where we have
313 00:23:02.880 ⇒ 00:23:03.900 Nicolas Sucari: the
314 00:23:03.940 ⇒ 00:23:10.659 Nicolas Sucari: actual code of how we are using. We’re creating those models. And then we are just using those models and sources from Rio. So
315 00:23:11.320 ⇒ 00:23:14.240 Nicolas Sucari: we should be able to look at that. Yeah.
316 00:23:14.980 ⇒ 00:23:15.860 Nicolas Sucari: okay.
317 00:23:17.770 ⇒ 00:23:32.680 Nicolas Sucari: yeah, I think we need to like work on on that stuff this week. So probably you guys, yeah, you can start taking a look suresh. And Ryan, yeah, you, too, maybe. And if you guys want to work it together, I think that’s fine.
318 00:23:33.151 ⇒ 00:23:42.619 Nicolas Sucari: And then the only task that we are just missing for the real stuff is adding some measures into the Daily Kpis dashboard
319 00:23:42.990 ⇒ 00:23:45.600 Nicolas Sucari: this one, let me go back to Real.
320 00:23:47.360 ⇒ 00:23:55.090 Nicolas Sucari: at least this one. I think we need to understand where the data is coming from, and how to add the dimensions. But it shouldn’t be so difficult. Right.
321 00:23:57.310 ⇒ 00:23:57.870 Ryan Luke Daque: Yeah.
322 00:24:00.110 ⇒ 00:24:00.800 Nicolas Sucari: Okay.
323 00:24:03.680 ⇒ 00:24:04.580 Nicolas Sucari: perfect.
324 00:24:05.950 ⇒ 00:24:15.520 Nicolas Sucari: I don’t know if we have anything else. Guys. yeah. Ryan, just one more. Uton mentioned that there were some workflows. Failing
325 00:24:15.740 ⇒ 00:24:18.149 Nicolas Sucari: that, you were going to look at.
326 00:24:19.630 ⇒ 00:24:20.859 Ryan Luke Daque: Are they like.
327 00:24:20.860 ⇒ 00:24:26.520 Nicolas Sucari: Or if you can, if you can look at them. Because yeah, I would have said there were some workflows failing.
328 00:24:26.650 ⇒ 00:24:28.660 Ryan Luke Daque: Okay, let me let me check real quick.
329 00:24:32.220 ⇒ 00:24:34.220 Ryan Luke Daque: Oh, hmm.
330 00:24:35.590 ⇒ 00:24:37.550 Ryan Luke Daque: yeah, it looks like it.
331 00:24:40.750 ⇒ 00:24:42.560 Ryan Luke Daque: Yeah, I’ll look into this.
332 00:24:42.980 ⇒ 00:24:44.200 Ryan Luke Daque: It’s a
333 00:24:44.530 ⇒ 00:24:46.810 Ryan Luke Daque: looks like it’s a volume, anomaly.
334 00:24:47.500 ⇒ 00:24:48.460 Ryan Luke Daque: failure.
335 00:24:48.460 ⇒ 00:24:49.190 Nicolas Sucari: Okay.
336 00:24:49.190 ⇒ 00:24:51.009 Ryan Luke Daque: So, yeah, I’ll look into this.
337 00:24:53.500 ⇒ 00:24:59.819 Nicolas Sucari: Perfect. Okay? Well, thanks, guys. Yeah, I think for now, like, that’s like our main.
338 00:25:00.670 ⇒ 00:25:10.630 Nicolas Sucari: I mean stuff to work on. And yes, Raj, once you get the new computer and we can start real, we can start taking a look on
339 00:25:10.710 ⇒ 00:25:16.020 Nicolas Sucari: modifying the dashboards. But for now I think we can just focus on Snowflake and
340 00:25:16.040 ⇒ 00:25:19.840 Nicolas Sucari: the data and see how we can like, understand a little bit that
341 00:25:20.060 ⇒ 00:25:23.239 Nicolas Sucari: to see what changes we need to make afterwards. Okay.
342 00:25:23.450 ⇒ 00:25:24.850 suraj: Yeah, sure. Nicholas.
343 00:25:26.220 ⇒ 00:25:36.130 Nicolas Sucari: Perfect. Well, thanks, guys. Let me know if you have something else. Or if you wanna okay, or you need anything. I’m available today to chat at any time. Okay.
344 00:25:36.480 ⇒ 00:25:37.220 Nicolas Sucari: yeah.
345 00:25:38.490 ⇒ 00:25:39.210 suraj: Alright!
346 00:25:41.860 ⇒ 00:25:43.170 Ryan Luke Daque: Sounds. Good. Perfect.
347 00:25:43.500 ⇒ 00:25:44.130 Ryan Luke Daque: Yeah.
348 00:25:44.130 ⇒ 00:25:44.909 Nicolas Sucari: You guys.
349 00:25:45.140 ⇒ 00:25:46.179 Ryan Luke Daque: Thanks, thanks and.
350 00:25:46.180 ⇒ 00:25:46.820 Nicolas Sucari: Bye, bye.
351 00:25:47.060 ⇒ 00:25:48.400 Ryan Luke Daque: Thanks, everyone. Bye, bye.