Meeting Title: Brainforge Product Report Stand-Up Date: 2025-06-26 Meeting participants: Awaish Kumar, Annie Yu, Bobby Caruso, Cutter, Mitesh Patel, Josh, Demilade Agboola
WEBVTT
1 00:00:59.950 ⇒ 00:01:00.880 Demilade Agboola: Hi kota.
2 00:01:03.080 ⇒ 00:01:10.279 Cutter: Ow, hey? Maybe you guys can hang with this before everybody gets in here.
3 00:01:11.720 ⇒ 00:01:12.609 Demilade Agboola: What’s happening.
4 00:01:13.620 ⇒ 00:01:17.050 Cutter: Can you tell me why my report looks like this now?
5 00:01:20.080 ⇒ 00:01:23.780 Cutter: Did somebody ask it to be set up this way?
6 00:01:24.760 ⇒ 00:01:26.979 Demilade Agboola: Oh, what report? What reports is that.
7 00:01:27.393 ⇒ 00:01:30.289 Cutter: This is the new product row, as.
8 00:01:31.730 ⇒ 00:01:32.330 Demilade Agboola: Sure.
9 00:01:33.190 ⇒ 00:01:36.059 Demilade Agboola: Oh, I mean IA quick fix.
10 00:01:36.240 ⇒ 00:01:37.970 Demilade Agboola: It’s probably a
11 00:01:42.760 ⇒ 00:01:49.020 Demilade Agboola: Someone like it’s probably published after being clicked, and it like tableau does where things like that?
12 00:01:49.250 ⇒ 00:01:51.640 Demilade Agboola: Oh, okay, of course. Yeah.
13 00:02:00.260 ⇒ 00:02:03.120 Demilade Agboola: New product for us.
14 00:02:18.380 ⇒ 00:02:19.780 Demilade Agboola: Can you refresh it? Now?
15 00:02:20.660 ⇒ 00:02:24.200 Cutter: Yeah. And then just one more thing like, when I’m trying to see the
16 00:02:24.780 ⇒ 00:02:28.710 Cutter: new product revenue report when I click the button
17 00:02:30.546 ⇒ 00:02:33.030 Cutter: it just takes me to
18 00:02:37.780 ⇒ 00:02:39.349 Cutter: it. Takes me to this screen.
19 00:02:39.620 ⇒ 00:02:41.539 Cutter: Wants me to sign into Brainforge.
20 00:02:45.440 ⇒ 00:02:52.990 Cutter: This is from slack like before Josh report. When I click it. It pushes me here. I don’t know if I did something wrong, or what.
21 00:02:55.220 ⇒ 00:02:55.760 Mitesh Patel: Cutter Irish.
22 00:02:55.760 ⇒ 00:02:56.719 Mitesh Patel: That’s that’s it.
23 00:02:56.720 ⇒ 00:03:00.020 Mitesh Patel: Just click on the Pdf versus going to the report.
24 00:03:00.020 ⇒ 00:03:01.580 Demilade Agboola: Isn’t like, yeah.
25 00:03:01.770 ⇒ 00:03:05.029 Cutter: No, I’m clicking on the Pdf. And it pushes me there.
26 00:03:05.030 ⇒ 00:03:06.130 Mitesh Patel: Oh, really.
27 00:03:06.130 ⇒ 00:03:06.940 Cutter: Yeah.
28 00:03:06.940 ⇒ 00:03:13.370 Mitesh Patel: Now I was doing that I got the same error. And then I was like, Oh, wait! I just need to open the Pdf. And then I was clicking on something wrong.
29 00:03:14.250 ⇒ 00:03:19.529 Demilade Agboola: Can you? Can you? Can. I see you like try the process right now on screen, so I can just see if there’s anything.
30 00:03:21.040 ⇒ 00:03:21.630 Cutter: Yeah.
31 00:03:24.460 ⇒ 00:03:26.880 Cutter: So I’m like clicking the link.
32 00:03:27.790 ⇒ 00:03:29.260 Cutter: And for Josh.
33 00:03:30.300 ⇒ 00:03:32.460 Mitesh Patel: Hold on, not seeing we’re not seeing that that page.
34 00:03:32.460 ⇒ 00:03:35.850 Demilade Agboola: Yeah, we’re not seeing the slack like you’re clicking in slack.
35 00:03:37.010 ⇒ 00:03:37.700 Cutter: Oh.
36 00:03:42.300 ⇒ 00:03:44.220 Cutter: this is the button that I’m clicking.
37 00:03:46.530 ⇒ 00:03:47.620 Mitesh Patel: Seems right.
38 00:03:48.140 ⇒ 00:03:48.970 Demilade Agboola: Yeah.
39 00:03:50.510 ⇒ 00:03:53.419 Cutter: And it just tells me to sign into Brainforge.
40 00:03:54.160 ⇒ 00:03:55.290 Mitesh Patel: Really strange.
41 00:03:55.290 ⇒ 00:03:57.659 Demilade Agboola: Are you signed in through?
42 00:04:00.190 ⇒ 00:04:00.910 Demilade Agboola: Alright.
43 00:04:02.100 ⇒ 00:04:05.750 Demilade Agboola: I’m trying to figure out why that is.
44 00:04:07.510 ⇒ 00:04:11.190 Cutter: I don’t think that I’m a workspace owner, but I can try.
45 00:04:11.650 ⇒ 00:04:18.489 Demilade Agboola: No, no, like, yeah. But you don’t have to be a workplace. And I use like, is that emails your work email signed in on that browser.
46 00:04:19.459 ⇒ 00:04:19.919 Cutter: Yeah.
47 00:04:20.519 ⇒ 00:04:24.379 Demilade Agboola: So can you try like signing in through Google and seeing what happens.
48 00:04:28.020 ⇒ 00:04:28.730 Cutter: Cancel.
49 00:04:31.500 ⇒ 00:04:32.480 Cutter: Oh, yeah.
50 00:04:37.020 ⇒ 00:04:38.010 Cutter: same thing.
51 00:04:39.170 ⇒ 00:04:39.950 Demilade Agboola: Same thing.
52 00:04:40.170 ⇒ 00:04:40.870 Cutter: Yeah.
53 00:04:41.670 ⇒ 00:04:42.720 Demilade Agboola: And.
54 00:04:46.740 ⇒ 00:04:48.289 Mitesh Patel: Check your downloads, folder.
55 00:04:49.990 ⇒ 00:04:50.800 Cutter: Okay
56 00:04:59.950 ⇒ 00:05:08.510 Cutter: downloads. And I also got a new computer. That’s why. So now I’m on a Mac. And after I switched to Mac, now, it’s doing this.
57 00:05:10.690 ⇒ 00:05:16.090 Demilade Agboola: But yeah, I believe I believe it should be fine. I think it’s 1 of those things where
58 00:05:16.514 ⇒ 00:05:20.469 Demilade Agboola: you might need to sign in to slack on your browser as well.
59 00:05:20.910 ⇒ 00:05:21.530 Cutter: Alright, cool.
60 00:05:21.530 ⇒ 00:05:32.969 Demilade Agboola: I think it’s like an authentication thing. It just wants to know that you have the right access to be able to, because, you know it’s potentially sensitive information, right? But they just want to know you have the right access to be able to view that
61 00:05:33.180 ⇒ 00:05:41.390 Demilade Agboola: if you sign into like slack on your browser. I think that would allow them to know that. Yes, you are also in the channel that receives that email.
62 00:05:41.900 ⇒ 00:05:44.209 Demilade Agboola: and therefore you can download the Pdf.
63 00:05:45.120 ⇒ 00:05:46.630 Cutter: Awesome. Thanks. Buddy.
64 00:05:52.890 ⇒ 00:05:58.180 Demilade Agboola: Okay, before we hop into stand up. Does anyone have any like issues or anything to say?
65 00:05:59.416 ⇒ 00:06:08.760 Josh: We do have some. We we probably need to carve out some time with the the Ehc team to start getting some data
66 00:06:08.890 ⇒ 00:06:11.949 Josh: from from that group integrated in.
67 00:06:12.520 ⇒ 00:06:18.979 Josh: So I just want to make sure that that’s on for this part, at least over the next week week and a half for the sprint.
68 00:06:20.680 ⇒ 00:06:21.750 Demilade Agboola: Okay.
69 00:06:25.090 ⇒ 00:06:28.389 Demilade Agboola: Let me add, as a ticket, and assign to Robert.
70 00:06:29.520 ⇒ 00:06:31.650 Josh: Yeah, I can work with Robert directly on it.
71 00:06:33.150 ⇒ 00:06:33.890 Demilade Agboola: Sure
72 00:06:49.140 ⇒ 00:06:50.230 Demilade Agboola: about share my screen.
73 00:06:50.840 ⇒ 00:06:51.710 Demilade Agboola: That’s our kind.
74 00:06:59.880 ⇒ 00:07:00.570 Cutter: Oh, yeah.
75 00:07:03.550 ⇒ 00:07:05.580 Demilade Agboola: Okay, I can do.
76 00:07:06.330 ⇒ 00:07:06.990 Cutter: Okay!
77 00:07:06.990 ⇒ 00:07:08.580 Cutter: Oh, oh.
78 00:07:19.970 ⇒ 00:07:20.720 Mitesh Patel: So
79 00:07:22.140 ⇒ 00:07:35.160 Mitesh Patel: I think the 1st step in this, Ehc, you know, whatever dashboard is going to be. What what I mentioned to Robert yesterday is. There’s already a request in from Vanessa, and he was going to
80 00:07:35.300 ⇒ 00:07:39.320 Mitesh Patel: figure out the work effort required, so we can prioritize it.
81 00:07:43.820 ⇒ 00:07:44.480 Cutter: Bye.
82 00:07:52.050 ⇒ 00:07:53.980 Demilade Agboola: Okay, so
83 00:07:54.830 ⇒ 00:08:01.060 Demilade Agboola: at least this is trackable, and if he needs to change things to modify things, add more details. He’ll be able to do that.
84 00:08:01.250 ⇒ 00:08:01.940 Mitesh Patel: Yep.
85 00:08:05.060 ⇒ 00:08:06.220 Demilade Agboola: Okay,
86 00:08:11.430 ⇒ 00:08:13.360 Demilade Agboola: so I think we could start with
87 00:08:15.450 ⇒ 00:08:22.789 Demilade Agboola: Annie. I know she has a couple of things, I mean.
88 00:08:25.810 ⇒ 00:08:28.800 Demilade Agboola: alright. So we have some things in client review.
89 00:08:29.400 ⇒ 00:08:31.290 Demilade Agboola: And then Internet review.
90 00:08:32.730 ⇒ 00:08:34.800 Demilade Agboola: So I think we just stop there.
91 00:08:37.164 ⇒ 00:08:46.259 Annie Yu: Yeah, we shipped the product road on dash updates yesterday. And looking to hear some feedback
92 00:08:46.580 ⇒ 00:08:54.360 Annie Yu: and then the skill level reporting, I think we can close that out. We shared this couple of days ago.
93 00:08:55.974 ⇒ 00:08:59.520 Annie Yu: And Kyle did reply. He said, it looks good.
94 00:09:03.280 ⇒ 00:09:09.040 Mitesh Patel: The when you say the product drill down. Report is that the cross sell, report. The new version of it.
95 00:09:09.260 ⇒ 00:09:12.549 Annie Yu: Yeah, that’s 1 of it.
96 00:09:18.780 ⇒ 00:09:22.620 Mitesh Patel: Josh, did you have a chance to look at the new product? Journey? Dashboard!
97 00:09:23.889 ⇒ 00:09:27.079 Josh: I saw that it was sent. I have not looked yet.
98 00:09:27.300 ⇒ 00:09:28.130 Mitesh Patel: Okay.
99 00:09:28.130 ⇒ 00:09:31.720 Josh: Where it, where? What channel was it in? Was it in the analytics Channel?
100 00:09:32.230 ⇒ 00:09:33.670 Demilade Agboola: Yes, the analytics Channel.
101 00:09:35.980 ⇒ 00:09:37.120 Josh: Slack.
102 00:09:38.360 ⇒ 00:09:41.040 Demilade Agboola: So there’s a loom as well on how to use it
103 00:09:41.500 ⇒ 00:09:44.840 Demilade Agboola: on, on the thought processes behind it.
104 00:09:47.140 ⇒ 00:09:49.070 Josh: She’s popping it open right now.
105 00:09:50.080 ⇒ 00:09:50.640 Demilade Agboola: Okay.
106 00:09:59.870 ⇒ 00:10:02.479 Demilade Agboola: what about channel data sources and.
107 00:10:03.000 ⇒ 00:10:06.960 Annie Yu: Yeah, this one. We’re waiting for Mattesh’s feedback.
108 00:10:06.960 ⇒ 00:10:10.309 Mitesh Patel: Yep, so I have some now.
109 00:10:12.190 ⇒ 00:10:12.849 Demilade Agboola: I’m sorry.
110 00:10:14.000 ⇒ 00:10:20.080 Mitesh Patel: For the for the marketing dashboard. Right? So let me share my screen if I can. Oh, I can’t.
111 00:10:22.940 ⇒ 00:10:24.330 Demilade Agboola: Can you share now, or.
112 00:10:24.858 ⇒ 00:10:26.600 Mitesh Patel: Yeah, looks like I can
113 00:10:30.120 ⇒ 00:10:36.987 Mitesh Patel: alright. So this marketing the marketing efficiency ratio that you added.
114 00:10:39.390 ⇒ 00:10:46.929 Mitesh Patel: can we just make it weekly, the same as the rest of these reports here, or dashes charts here.
115 00:10:49.320 ⇒ 00:10:51.410 Annie Yu: The right hand side is the weekly.
116 00:10:53.490 ⇒ 00:10:54.860 Mitesh Patel: Oh.
117 00:10:55.280 ⇒ 00:11:02.603 Mitesh Patel: okay, I I don’t know why. I just saw this. Well, yeah, never mind. Yeah, it’s right there.
118 00:11:03.010 ⇒ 00:11:05.440 Annie Yu: 3rd week, or keep it.
119 00:11:06.130 ⇒ 00:11:14.999 Mitesh Patel: No, no, keep it. I that’s fine. Keep it, I think. Mostly I’m gonna use the weekly. It’s right there. I didn’t even. I just got zeroed in on this didn’t even look here.
120 00:11:17.070 ⇒ 00:11:20.829 Mitesh Patel: And then, as far as the channels go, the ones that you’ve
121 00:11:23.230 ⇒ 00:11:29.670 Mitesh Patel: the ones that you’re calling paid channels and the free channels.
122 00:11:30.191 ⇒ 00:11:40.599 Mitesh Patel: I think we need to maybe just align on those, because I mean again, this is all coming from north beam right? So in north Beam there are.
123 00:11:42.820 ⇒ 00:11:46.590 Mitesh Patel: you know, like 33 channels right?
124 00:11:47.225 ⇒ 00:12:00.360 Mitesh Patel: The ones that are free, and I’ll show you a different view of this are the ones that I’m looking at as free are. And we can talk through this email, Facebook, organic Instagram, organic
125 00:12:00.810 ⇒ 00:12:06.539 Mitesh Patel: metashops organic. Although there’s an organic organic search. Now, I have other
126 00:12:06.960 ⇒ 00:12:12.020 Mitesh Patel: unattributed and non-set, also as free
127 00:12:14.750 ⇒ 00:12:19.640 Mitesh Patel: because non-set or unattributed, would be direct.
128 00:12:21.180 ⇒ 00:12:26.170 Mitesh Patel: which is free because they don’t. They don’t actually call out direct traffic.
129 00:12:29.920 ⇒ 00:12:34.000 Mitesh Patel: And then so that’s 10. The other 23
130 00:12:34.530 ⇒ 00:12:37.709 Mitesh Patel: that are currently here would be paid.
131 00:12:42.520 ⇒ 00:12:44.670 Demilade Agboola: So we’re miscategorizing.
132 00:12:44.860 ⇒ 00:12:53.739 Mitesh Patel: Yeah, it’s just that. Yeah, I don’t. I don’t want to really call it miscategorization. But it’s more. Let’s just be consistent on the categorization.
133 00:12:56.580 ⇒ 00:13:03.209 Demilade Agboola: Okay, can we get cut like the list like for both? So we could just like apply it and just ensure that.
134 00:13:03.770 ⇒ 00:13:04.430 Mitesh Patel: Yeah, I’ll get.
135 00:13:04.430 ⇒ 00:13:05.420 Mitesh Patel: Didn’t see that.
136 00:13:05.420 ⇒ 00:13:11.570 Mitesh Patel: Yeah, I’ll add it to the that marketing analytics channel the this list versus the others. Yeah.
137 00:13:12.470 ⇒ 00:13:13.620 Demilade Agboola: Okay. Sounds good.
138 00:13:14.670 ⇒ 00:13:16.770 Mitesh Patel: Alright, that was.
139 00:13:16.900 ⇒ 00:13:23.455 Mitesh Patel: I think that was it. And the request for weekly. But that’s already there. You know it’s
140 00:13:24.180 ⇒ 00:13:29.600 Mitesh Patel: and it’s a north beam issue, I know, but there’s just so much of it that is unattributed
141 00:13:30.060 ⇒ 00:13:38.767 Mitesh Patel: huge, you know. Most of it is, which is, makes things, you know, there’s almost nothing in other non set also has some, but
142 00:13:39.550 ⇒ 00:13:56.119 Mitesh Patel: most of it is unattributed. What I need to do is to see if I can figure out kind of the the details behind. You know who what the actual referral link is, whether it’s source or medium behind the unattributed. And then we can split that out, too.
143 00:13:56.540 ⇒ 00:14:02.650 Mitesh Patel: That’s what we typically do in Ga 4, which is, you know, make sure if if new
144 00:14:02.940 ⇒ 00:14:10.659 Mitesh Patel: traffic and sales are unattributed. Then we try to assign it to the right, a channel.
145 00:14:13.130 ⇒ 00:14:17.310 Awaish Kumar: Okay, like that’s revenue, which is unattributed. Right?
146 00:14:17.480 ⇒ 00:14:19.889 Mitesh Patel: Yeah, yeah, revenue. Yeah.
147 00:14:20.120 ⇒ 00:14:28.530 Awaish Kumar: Okay, yeah, like, we are getting a lot of orders with Utm source with some some like
148 00:14:29.210 ⇒ 00:14:34.329 Awaish Kumar: strings which which we are not able to like attribute to
149 00:14:34.710 ⇒ 00:14:37.810 Awaish Kumar: not able to attribute it to any source.
150 00:14:37.980 ⇒ 00:14:41.119 Awaish Kumar: So it’s like, some like in the ticket. I have
151 00:14:41.320 ⇒ 00:14:47.400 Awaish Kumar: mention some of these strings. It’s like just things like that.
152 00:14:47.400 ⇒ 00:14:55.780 Mitesh Patel: Can you share that list? Because that’s the level of detail I’d have to look at to see if we can attribute, you know, or categorize some of that.
153 00:14:57.130 ⇒ 00:15:00.030 Awaish Kumar: Like, can we show linear demo.
154 00:15:05.400 ⇒ 00:15:06.460 Mitesh Patel: What was that?
155 00:15:07.590 ⇒ 00:15:12.950 Awaish Kumar: Or I don’t, I’ll just pull it. And then let me.
156 00:15:16.900 ⇒ 00:15:22.270 Awaish Kumar: You know these. These are the basically.
157 00:15:25.560 ⇒ 00:15:31.839 Awaish Kumar: So I have replied in this zoom chat. Basically, this is what I’m getting where I’m saying. It is unattributive.
158 00:15:33.414 ⇒ 00:15:37.690 Awaish Kumar: It’s under the ticket 3, 7, 2.
159 00:15:38.330 ⇒ 00:15:39.080 Demilade Agboola: Okay.
160 00:15:40.180 ⇒ 00:15:47.150 Awaish Kumar: Yeah? And then, so the data which is coming from bask, like bus quarters data.
161 00:15:47.290 ⇒ 00:15:50.820 Awaish Kumar: can we go in in the Utm source and identify the source.
162 00:15:51.350 ⇒ 00:15:55.340 Awaish Kumar: and then there, I’m getting this. So we might need to.
163 00:15:55.980 ⇒ 00:15:57.730 Mitesh Patel: Dns error.
164 00:15:58.590 ⇒ 00:16:02.229 Mitesh Patel: I mean that, may I? Yeah, I have no idea what to do with that.
165 00:16:02.990 ⇒ 00:16:05.499 Mitesh Patel: Dns error assist from Att.
166 00:16:09.800 ⇒ 00:16:13.470 Awaish Kumar: So like the place where we are trying to get these
167 00:16:13.650 ⇒ 00:16:16.370 Awaish Kumar: freedom sources for our orders like, it’s
168 00:16:16.720 ⇒ 00:16:18.970 Awaish Kumar: it’s in the boss, or it’s in the
169 00:16:19.140 ⇒ 00:16:27.670 Awaish Kumar: Gf, 4 the like. Google tag manager. It’s there needs to be some work to fix this.
170 00:16:29.150 ⇒ 00:16:30.080 Mitesh Patel: Okay.
171 00:16:36.007 ⇒ 00:16:40.890 Demilade Agboola: I I don’t know. Is this something that we we need to face with Fix with bask?
172 00:16:40.990 ⇒ 00:16:47.839 Demilade Agboola: Or do we like? How do we get at least some context on this.
173 00:16:47.840 ⇒ 00:17:02.120 Mitesh Patel: It seems to be a bask issue. But let me let me. I’ll talk to Sebastian to say what might be creating this right, what might be causing the the. You know where where the source is identified as Dns error.
174 00:17:04.210 ⇒ 00:17:14.830 Mitesh Patel: and if it’s a bask issue, I think we’ll just maybe leave it alone, for now, because it might be more, you know, more effort to chase it down than the value we’re going to get out of it in the next couple of months.
175 00:17:15.227 ⇒ 00:17:16.779 Demilade Agboola: Fair enough, fair enough.
176 00:17:17.463 ⇒ 00:17:28.799 Mitesh Patel: But I’ll find out. But yeah, okay, otherwise any. This. This part of it is looking good as soon as we’re consistent on categorizing the free and paid channels. Thank you. This is good.
177 00:17:30.150 ⇒ 00:17:30.750 Annie Yu: Mattesh.
178 00:17:31.240 ⇒ 00:17:34.750 Annie Yu: The the update that I shared yesterday was
179 00:17:35.080 ⇒ 00:17:38.679 Annie Yu: also about the marketing Kpi dashboard.
180 00:17:39.140 ⇒ 00:17:40.040 Mitesh Patel: Yep.
181 00:17:40.520 ⇒ 00:17:42.959 Annie Yu: So, yeah, just just so you aware.
182 00:17:42.960 ⇒ 00:17:49.580 Mitesh Patel: Yeah, yeah, no, I know it was both. So the marketing Kpi dashboard is here.
183 00:17:51.600 ⇒ 00:17:56.470 Mitesh Patel: Yep. And then that was the offline. Spend also.
184 00:17:57.180 ⇒ 00:17:58.760 Annie Yu: Yeah. The bottom section.
185 00:17:58.760 ⇒ 00:17:59.400 Mitesh Patel: Yeah.
186 00:18:02.840 ⇒ 00:18:07.339 Mitesh Patel: and we’re not yet. And you noted that we are not breaking it down by
187 00:18:07.748 ⇒ 00:18:15.540 Mitesh Patel: product group just yet. But I’d like to be able to break it down. But you know how we have the 3 tables and the growth Kpis
188 00:18:15.740 ⇒ 00:18:21.331 Mitesh Patel: for new products for non Glp products and then glp products.
189 00:18:22.090 ⇒ 00:18:26.780 Mitesh Patel: I’d love to do that. I’d like I you know, I need this total right the way you have it.
190 00:18:27.776 ⇒ 00:18:29.409 Mitesh Patel: Up here.
191 00:18:29.890 ⇒ 00:18:38.129 Mitesh Patel: Well, I don’t know if we can break it down. The offline spends because I don’t think we give you. Never mind, we don’t give. We don’t track
192 00:18:38.320 ⇒ 00:18:42.709 Mitesh Patel: products in the offline spends. Yet we need to add that first.st
193 00:18:44.510 ⇒ 00:18:45.350 Annie Yu: Okay.
194 00:18:45.350 ⇒ 00:18:45.780 Mitesh Patel: Yeah.
195 00:18:45.780 ⇒ 00:18:49.160 Annie Yu: So let’s just keep it as is.
196 00:18:49.160 ⇒ 00:18:54.540 Mitesh Patel: As is, yeah, okay.
197 00:18:57.580 ⇒ 00:19:04.000 Mitesh Patel: this is a cumulative row, as including the offline spend. This is just ad spend.
198 00:19:06.670 ⇒ 00:19:11.860 Annie Yu: Yeah. The the top one is just yeah, that’s been at the bottom has both.
199 00:19:11.860 ⇒ 00:19:13.469 Mitesh Patel: Okay, alright good.
200 00:19:14.990 ⇒ 00:19:20.110 Mitesh Patel: And the way I read all of these is point 6 6 to 1.6 2 to one. Right?
201 00:19:22.730 ⇒ 00:19:27.040 Mitesh Patel: Yeah. Okay, looks.
202 00:19:27.040 ⇒ 00:19:32.099 Annie Yu: Let me let me know if you have any like feedback or anything you want to adjust down the line.
203 00:19:32.290 ⇒ 00:19:33.920 Mitesh Patel: No looks good, thank you.
204 00:19:34.150 ⇒ 00:19:34.670 Annie Yu: Yeah.
205 00:19:35.430 ⇒ 00:19:38.249 Mitesh Patel: Alright! I think that was it for me.
206 00:19:38.420 ⇒ 00:19:40.939 Cutter: Cool. I got Bobby in here. If we can
207 00:19:41.150 ⇒ 00:19:43.899 Cutter: kind of go through this email reporting
208 00:19:44.110 ⇒ 00:19:49.129 Cutter: schema. I got a giant Csv, not sure what to do with it.
209 00:19:49.350 ⇒ 00:19:51.400 Cutter: Maybe we can go over that and
210 00:19:51.720 ⇒ 00:19:54.520 Cutter: see what we’re supposed to be trying to figure out in there.
211 00:19:58.618 ⇒ 00:20:00.470 Demilade Agboola: What? What’s the issue with it?
212 00:20:02.670 ⇒ 00:20:04.980 Cutter: What do you want me to do with the giant Csv
213 00:20:08.730 ⇒ 00:20:09.490 Cutter: like? Am I supposed?
214 00:20:09.490 ⇒ 00:20:11.340 Cutter: I’m not sure to something.
215 00:20:14.710 ⇒ 00:20:17.370 Demilade Agboola: Can you share your screen? I have no idea what you’re talking about.
216 00:20:17.730 ⇒ 00:20:20.700 Cutter: It’s in the analytics channel. I think.
217 00:20:22.490 ⇒ 00:20:24.750 Cutter: Bobby, do you got it? Can you share it?
218 00:20:27.260 ⇒ 00:20:28.339 Mitesh Patel: You’re on mute.
219 00:20:30.576 ⇒ 00:20:41.120 Bobby Caruso: Yeah, there’s 2 of them, this one and best one.
220 00:20:43.300 ⇒ 00:20:47.520 Bobby Caruso: And then I think there was also a 3rd that was referenced in the slack, but only 2 were attached.
221 00:21:00.400 ⇒ 00:21:02.560 Demilade Agboola: Alicia. I think you worked on this.
222 00:21:03.270 ⇒ 00:21:04.260 Demilade Agboola: I’m.
223 00:21:05.753 ⇒ 00:21:06.999 Awaish Kumar: Yeah. Sorry.
224 00:21:07.550 ⇒ 00:21:08.870 Awaish Kumar: Where’s the question?
225 00:21:10.930 ⇒ 00:21:15.010 Demilade Agboola: I think that they’re not exactly sure how to utilize this, or like what’s going on here.
226 00:21:15.010 ⇒ 00:21:20.300 Awaish Kumar: Yeah, I have. I have shared the full summary of each column in the slack channel.
227 00:21:22.070 ⇒ 00:21:22.665 Bobby Caruso: Okay.
228 00:21:23.260 ⇒ 00:21:24.489 Awaish Kumar: But each column is.
229 00:21:25.410 ⇒ 00:21:28.999 Bobby Caruso: Where is this gonna like live? Or is it just like.
230 00:21:29.700 ⇒ 00:21:35.570 Awaish Kumar: It’s a table I have shared the excel for everybody to see, but it’s in the big query
231 00:21:36.060 ⇒ 00:21:41.659 Awaish Kumar: cool the like. The title of the sheet is is the table name in the bigquery.
232 00:21:42.920 ⇒ 00:21:44.060 Bobby Caruso: On that.
233 00:21:45.100 ⇒ 00:21:54.170 Bobby Caruso: I don’t know like Cutter Mattesh, Josh, like, is this what you guys need? As far as reporting, it’s all a little gobbled to me.
234 00:21:54.170 ⇒ 00:21:57.580 Cutter: Yeah, can you like, put it in a table or something? So we can look at it like.
235 00:21:57.870 ⇒ 00:22:01.950 Awaish Kumar: Yeah, it’s certain it’s already in bigquery. That’s what I’m saying.
236 00:22:02.470 ⇒ 00:22:06.540 Demilade Agboola: Okay, okay, can. Can I be tagged in? My, I’m I’m just kind of. I’m kind of out of.
237 00:22:06.540 ⇒ 00:22:07.340 Awaish Kumar: I have shared.
238 00:22:07.340 ⇒ 00:22:07.960 Demilade Agboola: If.
239 00:22:09.100 ⇒ 00:22:18.980 Awaish Kumar: Yeah, in my slack message to you in the thread. I’ve shared the names of the tables and the description for each field of this table.
240 00:22:20.810 ⇒ 00:22:26.649 Demilade Agboola: Yes, but I you know I don’t think they necessarily know how to use this in this form.
241 00:22:27.268 ⇒ 00:22:34.590 Demilade Agboola: We might need to maybe aggregate it in a way that it’s easier for them to see, compare and just make decisions of.
242 00:22:34.690 ⇒ 00:22:41.100 Demilade Agboola: Maybe we need to turn into like a chart, or we need to turn into like a line graph, or something.
243 00:22:41.320 ⇒ 00:22:42.740 Demilade Agboola: where they can compare.
244 00:22:42.990 ⇒ 00:22:47.330 Mitesh Patel: Yeah, what was the request we made where this was the output, because.
245 00:22:49.040 ⇒ 00:22:49.440 Awaish Kumar: Okay.
246 00:22:49.440 ⇒ 00:22:50.709 Mitesh Patel: I think that’s what we need.
247 00:22:50.710 ⇒ 00:22:56.900 Awaish Kumar: I I got a request through, like again, to create this table
248 00:22:57.240 ⇒ 00:23:01.170 Awaish Kumar: which I have created. And it it was exactly in the same aggregation.
249 00:23:01.460 ⇒ 00:23:08.439 Awaish Kumar: So now, if you need a dashboard, we need to make an another request for any to build a dashboard out of it.
250 00:23:08.680 ⇒ 00:23:10.329 Awaish Kumar: The table is there.
251 00:23:10.550 ⇒ 00:23:18.499 Cutter: The request, Mattesh was, can we see email success rate in tableau? And then we had 2 columns that were important.
252 00:23:18.660 ⇒ 00:23:21.619 Cutter: open to convert and click to convert.
253 00:23:22.090 ⇒ 00:23:23.070 Cutter: That’s it.
254 00:23:25.080 ⇒ 00:23:27.730 Mitesh Patel: And to be able to see that by campaign.
255 00:23:27.730 ⇒ 00:23:30.410 Cutter: By campaign, by email, etcetera.
256 00:23:31.590 ⇒ 00:23:37.030 Bobby Caruso: We started like Mvp. It was just for broadcast, not broadcast.
257 00:23:37.030 ⇒ 00:23:38.030 Mitesh Patel: Okay.
258 00:23:38.250 ⇒ 00:23:46.320 Cutter: But then we’ll be able to get in there and say, for this workflow data for this workflow data.
259 00:23:48.280 ⇒ 00:23:54.279 Bobby Caruso: Yeah. And the original request that we like scoped out. I think it was me I was either me Cutter and Josh or me, Natasha and Josh.
260 00:23:54.570 ⇒ 00:23:55.750 Mitesh Patel: I wasn’t there.
261 00:23:55.950 ⇒ 00:24:06.290 Bobby Caruso: Yeah, the idea was for it to look like this with like these columns that it it seems like we have all the columns. It’s just. I don’t think we have a good view of it right now.
262 00:24:07.000 ⇒ 00:24:07.460 Mitesh Patel: Yeah, so.
263 00:24:07.460 ⇒ 00:24:17.710 Demilade Agboola: Right now. It’s it’s about like the granularity of it. So it’s split out more than you know. You probably want it to be split out. But it just needs to be rolled up into a form that, like.
264 00:24:18.230 ⇒ 00:24:24.650 Demilade Agboola: like all the data, is there, it just needs to be rolled up in a form that you can look at, and just get your answers like right off the bat.
265 00:24:24.930 ⇒ 00:24:27.290 Demilade Agboola: So that’s the final step.
266 00:24:28.620 ⇒ 00:24:39.539 Demilade Agboola: like. I’m out of loop of this request, so I am not exactly sure what the initial request was, and all of that. But I will reach out to Tigran, understand what the request was.
267 00:24:39.900 ⇒ 00:24:42.290 Demilade Agboola: and then just try and see how we can like
268 00:24:42.460 ⇒ 00:24:46.339 Demilade Agboola: moderate that in this sprint, but also let Robert know as well.
269 00:24:46.340 ⇒ 00:24:50.333 Mitesh Patel: Let let me let me. I want to bounce this off a cutter and Bobby
270 00:24:50.800 ⇒ 00:24:57.089 Mitesh Patel: I think what we would like, what we need. What would be very helpful is for each
271 00:24:57.930 ⇒ 00:25:00.770 Mitesh Patel: broadcast series, right?
272 00:25:01.030 ⇒ 00:25:13.130 Mitesh Patel: Have the metrics the number sent open rate open to convert, total convert, and then be able to expand
273 00:25:14.700 ⇒ 00:25:19.019 Mitesh Patel: that into the emails within the the series.
274 00:25:19.020 ⇒ 00:25:19.690 Bobby Caruso: So.
275 00:25:19.690 ⇒ 00:25:20.750 Mitesh Patel: Same data.
276 00:25:21.850 ⇒ 00:25:34.910 Bobby Caruso: Like, yes, and we had started an Mvp. Just like broadcast for 1st campaigns. And the campaigns are the ones with like workflows with multiple emails within them. Each broadcast is standalone, and only has
277 00:25:35.090 ⇒ 00:25:48.766 Bobby Caruso: one email inside of it. So it’s like we might do 50 emails as part of like a, you know, series, but for broadcast, for all intents and purposes, their standalone they have a unique newsletter id, which is how we can parse them out.
278 00:25:49.750 ⇒ 00:25:58.583 Bobby Caruso: So we were gonna after that was done worry about the campaigns, because we were just spending so much time on broadcast right now, with like a hundred broadcast this last month.
279 00:25:59.130 ⇒ 00:26:03.460 Bobby Caruso: so. But overall like the things to look at, absolutely like
280 00:26:03.720 ⇒ 00:26:14.210 Bobby Caruso: cutter wanted us to see both conversion over open rate, which is how it’s defined in customer I/O, but then conversion after click, and then revenue is a big one, because, you know.
281 00:26:14.210 ⇒ 00:26:15.210 Mitesh Patel: Revenue. Yeah.
282 00:26:15.210 ⇒ 00:26:24.180 Bobby Caruso: Because right now, if I want to find out how much revenue got from email, I have to open up every conversion and the user like, it takes 2 h to figure out how much revenue we got from an email.
283 00:26:24.470 ⇒ 00:26:26.303 Mitesh Patel: Yeah. Okay.
284 00:26:27.920 ⇒ 00:26:29.840 Josh: There’s great.
285 00:26:29.840 ⇒ 00:26:34.730 Josh: I mean, there’s gotta be a better way. I mean, we just this has to get figured out like, if
286 00:26:34.840 ⇒ 00:26:37.819 Josh: otherwise it’s like. I have no idea what the point of the email.
287 00:26:38.310 ⇒ 00:26:39.330 Cutter: That’s right.
288 00:26:39.330 ⇒ 00:26:47.599 Cutter: that dash that board that they have that giant Csv. That will tell us revenue literally in a glance.
289 00:26:47.980 ⇒ 00:26:54.790 Cutter: But the further development of this is like some Moreland Odt Activation series.
290 00:26:54.890 ⇒ 00:26:59.879 Cutter: How? What do we put together in there to to judge successful or unsuccessful?
291 00:27:00.360 ⇒ 00:27:07.799 Cutter: You know, nad nasal spray same all the way across. Then we can have workflows, maybe broadcast as its own standalone board.
292 00:27:07.910 ⇒ 00:27:12.150 Cutter: like up at the top, and then we have workflow performance down at the bottom.
293 00:27:12.410 ⇒ 00:27:19.609 Bobby Caruso: Yeah, yeah, cause the workflows will be more in the weeds because it’s like, for example, our welcome series
294 00:27:19.760 ⇒ 00:27:26.550 Bobby Caruso: has like 70 emails in it. So it’s like that. We’ll probably have to architect completely, separately. And that wasn’t
295 00:27:26.800 ⇒ 00:27:31.887 Bobby Caruso: part of this initial scope. I mean, we have to work on that, too. So we’ll submit a request. But, like
296 00:27:32.810 ⇒ 00:27:36.250 Bobby Caruso: that will have its own kind of data. Intricacies, too.
297 00:27:36.600 ⇒ 00:27:43.569 Cutter: So if the data team can get that Csv into a dashboard, theoretically, we’ll be able to click it and look at revenue.
298 00:27:43.960 ⇒ 00:27:44.500 Cutter: We’ll have.
299 00:27:44.500 ⇒ 00:27:49.590 Bobby Caruso: Like, I want to know, like the churned email we sent out Monday morning.
300 00:27:49.992 ⇒ 00:27:58.230 Bobby Caruso: What was the revenue from it? So I don’t have to keep calculating like it was 40 k. The last time I checked. But it’s like we should be able to pretty clearly see
301 00:27:59.220 ⇒ 00:27:59.986 Bobby Caruso: the revenue.
302 00:28:00.950 ⇒ 00:28:04.929 Cutter: Is it? Take a long time to turn that table into.
303 00:28:07.060 ⇒ 00:28:07.800 Demilade Agboola: Hello!
304 00:28:08.900 ⇒ 00:28:21.830 Demilade Agboola: It shouldn’t but it also depends on how much time like Annie has on her plate and all of that. But we’ll we’ll definitely look at the in house. It does appear that there there was some miscommunication in terms of scoping.
305 00:28:22.502 ⇒ 00:28:29.619 Demilade Agboola: So it’s just converting, just like the raw data into like what we need for the dashboards.
306 00:28:29.965 ⇒ 00:28:33.124 Demilade Agboola: So we’ll look in house and just try and get that out to you.
307 00:28:33.550 ⇒ 00:28:37.800 Demilade Agboola: But, like Robert. I’ll definitely let Robert know, and he would handle a lot of the scoping.
308 00:28:38.500 ⇒ 00:28:39.150 Cutter: Cool man.
309 00:28:39.460 ⇒ 00:28:42.970 Bobby Caruso: I think the short answer. Everything in the Csv.
310 00:28:43.410 ⇒ 00:28:52.277 Bobby Caruso: Can be in the dashboard, like, I think the columns, like we hammered out after, like the 1st iteration. Any issues
311 00:28:53.030 ⇒ 00:28:58.989 Bobby Caruso: like now should be fine, I believe. And we have, like the multiple versions of
312 00:28:59.230 ⇒ 00:29:03.420 Bobby Caruso: multiple definitions of conversions, revenue appears to be in here so
313 00:29:04.020 ⇒ 00:29:07.570 Bobby Caruso: kind of exactly as is but in an interactive format.
314 00:29:12.990 ⇒ 00:29:19.899 Demilade Agboola: Okay, sounds sounds good. Yeah, I’ll definitely let Robert know, and we’ll we’ll get back to you on that.
315 00:29:20.740 ⇒ 00:29:22.130 Cutter: Alright, thanks, Buddy.
316 00:29:22.843 ⇒ 00:29:23.409 Demilade Agboola: Right, then.
317 00:29:26.320 ⇒ 00:29:28.010 Mitesh Patel: I need to drop as well.
318 00:29:28.710 ⇒ 00:29:32.320 Demilade Agboola: Okay, me, too. So I guess.
319 00:29:33.620 ⇒ 00:29:34.310 Cutter: Good talk.
320 00:29:34.310 ⇒ 00:29:39.969 Demilade Agboola: We can. Yeah, we can update our tickets Async, so that Robert also has an idea of what happened during stand up.
321 00:29:40.600 ⇒ 00:29:42.080 Cutter: Cool man. All right. We got.
322 00:29:42.080 ⇒ 00:29:42.760 Demilade Agboola: All right. Back.
323 00:29:43.230 ⇒ 00:29:43.650 Cutter: Yeah.
324 00:29:43.940 ⇒ 00:29:47.730 Josh: You said most important things for me are
325 00:29:48.240 ⇒ 00:29:53.969 Josh: getting that ehc data starting to sculpt in. So just please make sure Robert gets back to me today.
326 00:29:55.440 ⇒ 00:29:59.889 Demilade Agboola: Okay. I will message him right now.
327 00:30:00.480 ⇒ 00:30:01.830 Josh: Cool, Later.
328 00:30:02.500 ⇒ 00:30:04.510 Demilade Agboola: Alright, take care, bye.
329 00:30:09.240 ⇒ 00:30:13.809 Demilade Agboola: Okay? So I guess we can just update our tickets, Async, because we’re out of time.
330 00:30:16.330 ⇒ 00:30:19.080 Demilade Agboola: And yeah.
331 00:30:20.150 ⇒ 00:30:24.600 Awaish Kumar: Okay, yeah, just for that, like, we don’t.
332 00:30:25.080 ⇒ 00:30:37.669 Awaish Kumar: Yeah. It was like a request to create a table initially and like that, Sigma Sigma. She he showed like it exactly mentions that we need to build a table for
333 00:30:37.920 ⇒ 00:30:39.750 Awaish Kumar: and newsletter
334 00:30:39.910 ⇒ 00:30:51.479 Awaish Kumar: like for the for the newsletters, and that’s the model shows and the exact granularity they needed. But like, it’s just that they need in a in a tableau. That’s the new requirement.
335 00:30:52.770 ⇒ 00:30:54.420 Awaish Kumar: Yeah, yeah.
336 00:30:56.690 ⇒ 00:31:22.420 Demilade Agboola: Yeah, I I forgot they need a dashboard. But I didn’t want to put any on the table, because I just didn’t want I don’t know what you’re like, how much is on your plate right now. So I didn’t want to put you like, oh, and you’ll get it to you today or tomorrow, because, honestly, I don’t know how much I I didn’t want to put any on the spot. I didn’t say, Oh, and you’ll get it back to them today or tomorrow. Build a dashboard today or tomorrow, because I don’t know how much workload Annie has. So I was just
337 00:31:22.420 ⇒ 00:31:22.890 Demilade Agboola: it’s like
338 00:31:22.890 ⇒ 00:31:28.169 Demilade Agboola: deflect and say, like, Hey, we have the numbers, but we’ll get. We’ll look at it and get back to you.
339 00:31:29.170 ⇒ 00:31:29.770 Awaish Kumar: Okay. Yeah.
340 00:31:29.770 ⇒ 00:31:30.350 Demilade Agboola: Oh, yeah.
341 00:31:31.610 ⇒ 00:31:39.419 Demilade Agboola: yeah, I guess we can create a ticket for that. So that you know, I’m assigning to Annie. And we can see what, Roberts like! How high that ranks
342 00:31:40.290 ⇒ 00:31:40.870 Demilade Agboola: follow up.
343 00:31:40.870 ⇒ 00:31:41.880 Awaish Kumar: Okay. Sure.
344 00:31:45.920 ⇒ 00:31:53.780 Demilade Agboola: Okay, yeah, I guess we just update our ticket Async, because, like, we’re out of time. And I also have another meeting right now. So.
345 00:31:56.050 ⇒ 00:31:57.540 Annie Yu: Okay, thank you so much.
346 00:31:58.820 ⇒ 00:32:00.729 Demilade Agboola: Okay. Thank you. Bye.
347 00:32:00.890 ⇒ 00:32:01.510 Annie Yu: Hey!