Meeting Title: Eden Upfluence Sync Date: 2026-02-23 Meeting participants: Demilade Agboola, Ashwini Sharma, Zoran Selinger
WEBVTT
1 00:00:29.750 ⇒ 00:00:30.830 Zoran Selinger: Bye, guys.
2 00:00:32.119 ⇒ 00:00:32.999 Ashwini Sharma: Hello.
3 00:00:34.219 ⇒ 00:00:35.139 Ashwini Sharma: Hello.
4 00:00:36.389 ⇒ 00:00:39.619 Zoran Selinger: Hey, let me share my screen now.
5 00:00:48.859 ⇒ 00:00:58.789 Ashwini Sharma: Right, okay, so basically this is the sheet that… that’s being produced by Eden Team, right?
6 00:00:59.159 ⇒ 00:01:04.259 Ashwini Sharma: And they have at least, like, there are two components that are essential for us, right?
7 00:01:04.379 ⇒ 00:01:05.889 Ashwini Sharma: One is a monthly rate.
8 00:01:06.199 ⇒ 00:01:22.089 Ashwini Sharma: And not too common, but three components. One is a monthly rate, the other is the commission, and the last is, basically, the commission earned, which is nothing but the commission into the number of orders that have been processed by this particular influencer, right? So I’m able to get this one.
9 00:01:22.459 ⇒ 00:01:27.099 Ashwini Sharma: to a very close extent. Like, for example, there are certain records where
10 00:01:27.239 ⇒ 00:01:33.329 Ashwini Sharma: this does not match, right? For example, like, for Ashley Beta, it’s 16, so this is…
11 00:01:33.619 ⇒ 00:01:36.749 Ashwini Sharma: this matches, but for something like Gracefully Stuff.
12 00:01:37.159 ⇒ 00:01:42.649 Ashwini Sharma: It says 8 on affluence, here it says 7, so I don’t know where that mismatch is coming from.
13 00:01:42.949 ⇒ 00:01:47.129 Ashwini Sharma: So at least this part is good.
14 00:01:47.539 ⇒ 00:01:50.879 Ashwini Sharma: What I’m not able to get is this part from the affluence data.
15 00:01:51.869 ⇒ 00:01:55.829 Ashwini Sharma: And I have looked into multiple this thing, right?
16 00:01:56.299 ⇒ 00:02:06.229 Ashwini Sharma: Like, this is one way that I can get it, but then when I get this one, I also get, like, a bunch of other data, which is irrelevant, right? And there is no way to filter that out.
17 00:02:08.589 ⇒ 00:02:16.439 Ashwini Sharma: So, for example, over here, if you see, right, Ashley Pita is at 3250, so that… that kind of matches with this thing.
18 00:02:16.690 ⇒ 00:02:17.220 Zoran Selinger: Yeah.
19 00:02:17.220 ⇒ 00:02:27.940 Ashwini Sharma: 8250, right? Sabrina is at 1000, but in the data, if you see, Sabrina is at 750, right?
20 00:02:28.150 ⇒ 00:02:30.190 Ashwini Sharma: be… Sabrina.
21 00:02:30.830 ⇒ 00:02:34.920 Ashwini Sharma: Sabrina is a 750, right? I don’t know where that 1000 comes from in the sheet.
22 00:02:35.090 ⇒ 00:02:38.779 Demilade Agboola: Can you pull influencer price? So, can you do call my influencer price, please?
23 00:02:40.060 ⇒ 00:02:42.120 Ashwini Sharma: You want me to pull which one? Influencer Price.
24 00:02:42.120 ⇒ 00:02:42.970 Demilade Agboola: Yes, please.
25 00:02:43.130 ⇒ 00:02:45.070 Ashwini Sharma: Okay, one second.
26 00:02:45.690 ⇒ 00:02:48.010 Demilade Agboola: I’m pulling water.
27 00:02:48.010 ⇒ 00:02:49.120 Ashwini Sharma: Yeah, it’s both.
28 00:02:49.120 ⇒ 00:02:50.459 Demilade Agboola: Just so I know, just so I know.
29 00:02:51.420 ⇒ 00:02:53.539 Ashwini Sharma: Don’t let me separate it, no, that’s okay.
30 00:03:04.180 ⇒ 00:03:07.150 Ashwini Sharma: Yeah, so let’s do someone else.
31 00:03:14.150 ⇒ 00:03:17.270 Demilade Agboola: Also, are you sure this is her slug? That would be the next thing.
32 00:03:17.670 ⇒ 00:03:25.240 Ashwini Sharma: Yeah, yeah, I’m quite sure about that. Because, see, I did this one also, right? This is basically,
33 00:03:26.530 ⇒ 00:03:28.980 Ashwini Sharma: Yeah, and this is the number of orders.
34 00:03:29.100 ⇒ 00:03:37.140 Ashwini Sharma: based on influencer ID, right? And that kind of matches very closely with what we see in the data. For example, the Ashley Peta16
35 00:03:37.400 ⇒ 00:03:47.840 Ashwini Sharma: orders 800, this one, right? Severin and I, on the other hand, it says 4 orders, whereas over there, I see… okay, Severin and I is correct. I think, gracefully, Steph was wrong.
36 00:03:48.380 ⇒ 00:03:54.020 Ashwini Sharma: Sabrina is… is 4 orders, right? So, we have $200, that matches.
37 00:03:54.150 ⇒ 00:03:59.300 Ashwini Sharma: For example, this one, right? Gracefully Steph. Steph is… it says, 7 orders over here.
38 00:03:59.750 ⇒ 00:04:06.279 Ashwini Sharma: Right? In this one, you can see step is at 8 orders, 1600, right?
39 00:04:06.440 ⇒ 00:04:08.400 Ashwini Sharma: And if you go to this one.
40 00:04:09.200 ⇒ 00:04:14.260 Ashwini Sharma: stuff is again at… for February 1 to 23, at 8 orders.
41 00:04:14.420 ⇒ 00:04:23.079 Ashwini Sharma: This one, right? So that’s, again, 12345678. So, basically, it should have been 8 into 21600.
42 00:04:24.020 ⇒ 00:04:26.710 Ashwini Sharma: Whereas here, it is reported as 7 only.
43 00:04:27.080 ⇒ 00:04:30.240 Demilade Agboola: Alright, so can you… there are two things you can do with that. One is…
44 00:04:30.360 ⇒ 00:04:37.320 Demilade Agboola: You can take the list of transactions, because transactions are there.
45 00:04:37.480 ⇒ 00:04:39.349 Ashwini Sharma: Transactions are not there.
46 00:04:39.520 ⇒ 00:04:49.160 Demilade Agboola: No, like, the… if you go to other contributions, you can see the, like, orders, contribution orders, you can see the transactions, like, the order ID or something.
47 00:04:49.690 ⇒ 00:04:51.329 Ashwini Sharma: Yeah, order ID is there, yeah.
48 00:04:51.330 ⇒ 00:04:57.600 Demilade Agboola: Yes, so that, that number, that PI, blah blah blah, is equals to a transaction
49 00:04:58.270 ⇒ 00:05:01.080 Demilade Agboola: ID in our orders table.
50 00:05:02.470 ⇒ 00:05:03.300 Ashwini Sharma: Okay.
51 00:05:03.740 ⇒ 00:05:09.939 Demilade Agboola: So the idea now is, let’s… like, that one order that is missing, let’s figure out why that is. Maybe it is a function…
52 00:05:10.060 ⇒ 00:05:13.269 Demilade Agboola: Of, like, it’s a very recent order.
53 00:05:13.560 ⇒ 00:05:22.760 Demilade Agboola: Or, like, maybe it was initially for her, it has been reversed against, like, was it canceled out? Like, just, like, get an idea of what the order is, basically.
54 00:05:24.430 ⇒ 00:05:24.900 Demilade Agboola: Hold on.
55 00:05:24.900 ⇒ 00:05:27.739 Ashwini Sharma: Yeah, in the campaign orders, all 8 orders are present.
56 00:05:28.380 ⇒ 00:05:33.450 Demilade Agboola: That’s… Fine. So, is it associated with her in all of them?
57 00:05:34.230 ⇒ 00:05:41.159 Ashwini Sharma: Yes, in campaign orders, it is associated with her. All those 8 orders are associated with her, and I can see 8 orders in the uplens also.
58 00:05:41.350 ⇒ 00:05:45.990 Demilade Agboola: Okay, so why is it not… when you aggregate it, why is it 7 instead of 8, then?
59 00:05:46.480 ⇒ 00:05:51.500 Ashwini Sharma: So, because they are reporting here, they are under-reporting it. They are saying it’s only 7.
60 00:05:51.850 ⇒ 00:05:57.470 Demilade Agboola: Yes, that’s what I’m… oh, who is… oh, like, you’re saying the… the dashboard is underreported, and it’s not…
61 00:05:58.390 ⇒ 00:06:01.250 Ashwini Sharma: This… this sheet is underreporting it. This sheet is…
62 00:06:01.250 ⇒ 00:06:03.380 Demilade Agboola: Annually created. Gotcha, gotcha.
63 00:06:03.380 ⇒ 00:06:05.130 Ashwini Sharma: This is manually created sheet, yeah.
64 00:06:05.130 ⇒ 00:06:08.799 Demilade Agboola: Okay, and how often is it updated? So that’s the issue, that will probably be the issue.
65 00:06:08.800 ⇒ 00:06:16.659 Ashwini Sharma: It’s updated very regularly, right? I’ve seen, like, Monday itself, it has been… today itself, it has been updated 2-3 times.
66 00:06:16.810 ⇒ 00:06:19.930 Ashwini Sharma: So this is a very regular, update sheet.
67 00:06:20.240 ⇒ 00:06:26.870 Demilade Agboola: Okay. I think we should… I think, personally, like, then we… our API will give us more accurate numbers.
68 00:06:27.060 ⇒ 00:06:35.839 Demilade Agboola: And we can just let them know that, hey, this is an example of, like, gracefully 7, but we… we can see 8, it’s 8 in the dashboard, it’s 8 in the API.
69 00:06:36.040 ⇒ 00:06:44.679 Demilade Agboola: And we can ask them if we just want to confirm, is there any reason why it’s 7 here? Maybe there’s a… there’s something that isn’t to remove, not… to remove conversions? Maybe.
70 00:06:44.680 ⇒ 00:06:52.680 Ashwini Sharma: The other thing I want to know is, how do they get this list? Because the list that I am getting is about 90 records over here.
71 00:06:52.960 ⇒ 00:06:55.850 Ashwini Sharma: If I look at all the campaign contributions, right?
72 00:06:56.050 ⇒ 00:06:58.480 Ashwini Sharma: And… Right over here.
73 00:06:59.640 ⇒ 00:07:01.320 Ashwini Sharma: with each influencer.
74 00:07:05.140 ⇒ 00:07:07.409 Ashwini Sharma: Yeah, I get about 98 records.
75 00:07:08.470 ⇒ 00:07:12.380 Ashwini Sharma: So, question is, how do I filter it down to… You know…
76 00:07:13.050 ⇒ 00:07:16.569 Ashwini Sharma: 54, or 53, whatever it is there in the sheet.
77 00:07:17.040 ⇒ 00:07:18.550 Ashwini Sharma: 57 reports.
78 00:07:18.960 ⇒ 00:07:21.180 Ashwini Sharma: What’s the criteria over here?
79 00:07:24.050 ⇒ 00:07:31.830 Demilade Agboola: I have no idea. Is it based on active… is it based on campaigns, though? Like, if you’re looking at that campaigns, or active campaigns, maybe that could be why it is?
80 00:07:32.530 ⇒ 00:07:36.540 Ashwini Sharma: Active campaigns. What do you mean by that?
81 00:07:36.850 ⇒ 00:07:40.589 Demilade Agboola: Like, Are you looking at the same campaign they’re looking at?
82 00:07:40.800 ⇒ 00:07:41.350 Demilade Agboola: Sweet.
83 00:07:41.350 ⇒ 00:07:43.949 Ashwini Sharma: I’m looking at GLP-1 campaigns.
84 00:07:43.950 ⇒ 00:07:45.120 Demilade Agboola: Oh, okay.
85 00:07:45.120 ⇒ 00:07:45.540 Ashwini Sharma: So…
86 00:07:45.540 ⇒ 00:07:57.589 Demilade Agboola: Another reason, another question you can ask them. So, we have a chat with them, I can add you to it, so you can ask these questions, like, okay, hey, we have a list of 90-something, but you have a list of 57, is there any reason why, like…
87 00:07:57.770 ⇒ 00:08:01.360 Demilade Agboola: there’s some… There’s some disparities.
88 00:08:02.050 ⇒ 00:08:06.220 Ashwini Sharma: Yeah, yeah, we can ask about this, like, for example, 7, right, for Grace Philly stuff.
89 00:08:06.300 ⇒ 00:08:09.779 Demilade Agboola: Yeah. The sheet reports 7, but affluence was 8.
90 00:08:10.090 ⇒ 00:08:12.340 Demilade Agboola: What’s the, you know, discrepancy here?
91 00:08:12.540 ⇒ 00:08:23.179 Demilade Agboola: Yeah, sure. I think the hard… the really hard part, or the really tricky part, would be… is there any way we can automate, like… because influencers… the ID is… there’s an influencer ID, but is there an email?
92 00:08:24.170 ⇒ 00:08:35.600 Ashwini Sharma: No, it’s, it’s… email is not used, like, not everywhere it is available. So, basically, what is happening over here is that, this has an influencer ID, right? Campaign order has an influencer ID.
93 00:08:35.809 ⇒ 00:08:45.409 Ashwini Sharma: And you can use that influencer ID, right? And somehow you can… like, in the campaign contributions, right, there is a contribution ID,
94 00:08:45.520 ⇒ 00:08:58.250 Ashwini Sharma: Which, basically maps exactly to one slug, one influencer, per campaign, right? One influencer campaign. That is how it maps. So you can do the join, and then kind of, you know, figure out the influencer ID.
95 00:08:59.680 ⇒ 00:09:05.470 Demilade Agboola: Oh, okay. Yeah, it doesn’t necessarily sound automatic, that’s the problem, that’s what I’m trying to think about,
96 00:09:06.320 ⇒ 00:09:15.040 Demilade Agboola: maybe something we can also push to upload and see if we can get, like, even if it’s just emails, for instance, or something, we… at least, like, can identify and, like.
97 00:09:17.340 ⇒ 00:09:20.519 Demilade Agboola: Something to identify who, like, the…
98 00:09:20.800 ⇒ 00:09:23.640 Demilade Agboola: what good influencer ID is, basically.
99 00:09:24.230 ⇒ 00:09:28.090 Ashwini Sharma: So influencer ID is not there in this one, right? It’s only there in campaign orders.
100 00:09:28.260 ⇒ 00:09:32.629 Demilade Agboola: Yeah, I know what you’re trying… I know what you’re saying, I’m just saying that, like, it’s… right now, things aren’t…
101 00:09:32.770 ⇒ 00:09:41.630 Demilade Agboola: to get everything back to the influencer, like, that made the… that made the sale, it’s not the easiest, is what I’m trying to say.
102 00:09:43.140 ⇒ 00:09:47.640 Ashwini Sharma: Yeah, yeah, that way, yeah, there is no direct mapping, right? There is no direct mapping.
103 00:09:47.640 ⇒ 00:09:49.080 Demilade Agboola: Like, there’s no direct money.
104 00:09:51.090 ⇒ 00:09:57.259 Demilade Agboola: Alright, so if we need to get… so, okay, a couple things. I think plan of action would be… one is,
105 00:09:58.430 ⇒ 00:10:17.939 Demilade Agboola: We’ll need to update the team, and let them know that, hey, the numbers we’re getting are very close, they don’t match, but we seem to be able to, like, match with the dashboard. So, for instance, give the example of Gracefully Steph, and say, hey, it’s 7, dashboard says 8, API says 8, is there any reason why it’s 7 versus 8?
106 00:10:18.070 ⇒ 00:10:23.490 Demilade Agboola: maybe they might have a reason, so that’s number one. Number two, you also are talking about.
107 00:10:24.020 ⇒ 00:10:25.000 Ashwini Sharma: this list.
108 00:10:25.540 ⇒ 00:10:33.849 Demilade Agboola: Yes, the length of the list. We have, like, 90-something people. Maybe you can also filter out people that are zero, maybe if…
109 00:10:33.960 ⇒ 00:10:47.139 Demilade Agboola: zero might be a marker that they’re not getting any money, that might be what we need to look at. But ultimately, yes, we can just say, hey, this is a list of 90-something influencers. Right now, you have 57, but we have, like, 90-something or 56, we have, like.
110 00:10:48.770 ⇒ 00:11:01.329 Demilade Agboola: 90-something. Is there a reason why they’re, like, we are missing 40, influencers? That’s 2. And then 3 on the upfront’s end, I think we should just send them an email where we talk about being able to easily map
111 00:11:01.890 ⇒ 00:11:03.879 Demilade Agboola: The influencers…
112 00:11:04.020 ⇒ 00:11:11.580 Demilade Agboola: Back to, like, whether it’s an email or whatever it is, but just being easily able to map it back.
113 00:11:11.910 ⇒ 00:11:14.799 Demilade Agboola: 2… The campaigns and what they’ve done.
114 00:11:15.980 ⇒ 00:11:19.779 Ashwini Sharma: What is the third? Third was a retainer amount also, mismatch in retainer amount, right?
115 00:11:21.560 ⇒ 00:11:30.630 Demilade Agboola: Mismatch in… yes, so yeah, so let’s look at that, too. Like, I’ve not looked enough into that. So, the mismatch appears to be what, exactly, in the return?
116 00:11:30.630 ⇒ 00:11:38.829 Ashwini Sharma: For example, like, for Sabrina, right, Affluence says that it’s 700, whereas, this one, she says it is 1000.
117 00:11:38.830 ⇒ 00:11:41.760 Demilade Agboola: Okay, can we look at the data, please?
118 00:11:41.760 ⇒ 00:11:42.400 Ashwini Sharma: Yeah.
119 00:11:45.150 ⇒ 00:11:47.140 Ashwini Sharma: So… yeah.
120 00:11:55.370 ⇒ 00:11:57.519 Ashwini Sharma: Let’s look at Sabrina.
121 00:12:02.850 ⇒ 00:12:07.659 Demilade Agboola: Also, in that sheet, this influencer name, is that you that put it there, or is it what they put themselves?
122 00:12:08.980 ⇒ 00:12:15.110 Ashwini Sharma: Which one? That sheet, I don’t know that sheet, like, I’m just trying to closely match with things, right, over here.
123 00:12:15.150 ⇒ 00:12:16.090 Demilade Agboola: That’s what?
124 00:12:16.090 ⇒ 00:12:23.440 Ashwini Sharma: Because I could see influencer name in that shit, and I was wondering if it’s the same. Yeah, sometimes… it does not match all the time. Only sometimes it matches, yeah.
125 00:12:23.680 ⇒ 00:12:24.270 Demilade Agboola: Alright.
126 00:12:24.270 ⇒ 00:12:30.760 Ashwini Sharma: For example, like, you can take a look at this one, right? Like, this step, right? Step.
127 00:12:31.240 ⇒ 00:12:37.000 Ashwini Sharma: So the email is modestmama92, gracefully, Steph, that’s the only thing that I have over here.
128 00:12:37.330 ⇒ 00:12:42.459 Ashwini Sharma: But, the influencer name over there in the slug is only step.
129 00:12:42.900 ⇒ 00:12:47.669 Demilade Agboola: Oh, okay. Yeah, I can… yeah, that’s hard. So yeah, we need something that helps us map.
130 00:12:47.990 ⇒ 00:12:48.390 Ashwini Sharma: Yeah.
131 00:12:48.750 ⇒ 00:12:51.350 Demilade Agboola: To the influencers in an easy way.
132 00:12:51.590 ⇒ 00:12:52.110 Demilade Agboola: Alright.
133 00:12:52.110 ⇒ 00:12:55.750 Ashwini Sharma: For example, 600 over here, this 600 matches, I think.
134 00:12:57.060 ⇒ 00:12:58.070 Ashwini Sharma: 600 degrees.
135 00:12:58.070 ⇒ 00:13:00.069 Demilade Agboola: That’s cool stuff.
136 00:13:00.070 ⇒ 00:13:04.659 Ashwini Sharma: It’s only 300, it’s not even 600, right? So this is also a mismatch, right, you see?
137 00:13:04.790 ⇒ 00:13:05.670 Ashwini Sharma: Yeah.
138 00:13:05.670 ⇒ 00:13:11.909 Demilade Agboola: Okay, so two things. One is, well, can you try exporting from Upfluence and see if there’s influencer ID as well?
139 00:13:11.910 ⇒ 00:13:19.839 Ashwini Sharma: No, that is not working, right? So, uploads export is not working. It goes into an email, at least, that is what Zoran is saying, right?
140 00:13:20.190 ⇒ 00:13:24.840 Ashwini Sharma: And, export as CSV. Let’s do this.
141 00:13:25.200 ⇒ 00:13:28.510 Zoran Selinger: I think that’s the case, yeah, if we have all the report.
142 00:13:29.230 ⇒ 00:13:31.440 Zoran Selinger: What does it say? Yeah, internal…
143 00:13:31.440 ⇒ 00:13:32.700 Ashwini Sharma: into this email ID.
144 00:13:32.700 ⇒ 00:13:36.300 Demilade Agboola: Yeah, we have access, we have access to that emailer. Check one pass, it’s one pass.
145 00:14:13.200 ⇒ 00:14:14.600 Ashwini Sharma: What happened? Okay.
146 00:14:33.110 ⇒ 00:14:34.240 Ashwini Sharma: This is the one?
147 00:14:37.990 ⇒ 00:14:39.669 Ashwini Sharma: No, this is just uploads, right?
148 00:14:39.670 ⇒ 00:14:43.210 Demilade Agboola: Yeah, I thought… I thought we did, let me check.
149 00:14:55.960 ⇒ 00:14:58.420 Ashwini Sharma: This is Google.
150 00:15:02.840 ⇒ 00:15:03.500 Demilade Agboola: Okay, yeah.
151 00:15:03.500 ⇒ 00:15:04.799 Ashwini Sharma: dirt, right? And…
152 00:15:04.960 ⇒ 00:15:07.269 Demilade Agboola: We don’t, we don’t have it. Interesting.
153 00:15:07.270 ⇒ 00:15:08.689 Ashwini Sharma: No, we don’t have it.
154 00:15:08.690 ⇒ 00:15:13.429 Demilade Agboola: Alright, so sure, in that case, that would make it hard for us to do anything.
155 00:15:13.720 ⇒ 00:15:16.280 Demilade Agboola: Okay, yeah, so…
156 00:15:16.480 ⇒ 00:15:22.720 Demilade Agboola: We don’t know if there’s user, influencer ID, so I think we can just, ask offline instead.
157 00:15:22.910 ⇒ 00:15:26.959 Demilade Agboola: hey, there’s that. And also, yes.
158 00:15:31.250 ⇒ 00:15:40.509 Demilade Agboola: What’s the retainer for… can we see the retainer for Steph in… or is it Steph or Sabrina in… in the dashboard, like, the appliance dashboard?
159 00:15:41.020 ⇒ 00:15:46.740 Ashwini Sharma: uplift dashboard does not show a retainer amount, right? It just shows the sales value.
160 00:15:46.880 ⇒ 00:15:48.950 Demilade Agboola: So if you click on her name, you can’t see anything.
161 00:15:49.610 ⇒ 00:15:52.580 Ashwini Sharma: Hmm… No.
162 00:15:52.870 ⇒ 00:15:53.530 Demilade Agboola: Oh, okay.
163 00:15:53.530 ⇒ 00:15:58.099 Ashwini Sharma: Maybe you can look at the payments that have been made, right? So, basically…
164 00:15:59.150 ⇒ 00:16:04.760 Ashwini Sharma: If you look at the payments, and… What was that, Sabrina?
165 00:16:04.760 ⇒ 00:16:05.890 Demilade Agboola: Sabrina, yeah.
166 00:16:16.880 ⇒ 00:16:20.969 Ashwini Sharma: Where is that payment history? There was somewhere payment history we had seen, right?
167 00:16:21.330 ⇒ 00:16:23.470 Demilade Agboola: Can you go to Campaigns, probably?
168 00:16:26.930 ⇒ 00:16:28.080 Ashwini Sharma: Aiden…
169 00:16:42.750 ⇒ 00:16:46.149 Demilade Agboola: Yeah, so it’s $7.50. I don’t know why their shit is 1,000, so…
170 00:16:47.250 ⇒ 00:16:49.679 Ashwini Sharma: Yeah, this is 750, right? .
171 00:16:49.680 ⇒ 00:16:53.589 Demilade Agboola: Yeah, so… again, it’s another thing we just confirmed with them, like, hey.
172 00:16:53.940 ⇒ 00:17:03.470 Demilade Agboola: written as a non-match, and it says, like, Sabrina is 1,000 year sheets by 750 in, you know, the dashboard, as well as the data, so why exactly is that?
173 00:17:04.050 ⇒ 00:17:06.200 Ashwini Sharma: Yeah, here they have paid $1,000, though.
174 00:17:06.200 ⇒ 00:17:06.730 Demilade Agboola: Yeah, yeah, yeah.
175 00:17:06.730 ⇒ 00:17:09.209 Ashwini Sharma: I don’t know where this comes from.
176 00:17:09.210 ⇒ 00:17:17.809 Demilade Agboola: That’s fine, but that’s why we need to clarify, because the data is telling us 750. You have 1,000 as the retainer. Why is there a disparity?
177 00:17:17.900 ⇒ 00:17:21.009 Ashwini Sharma: That’s all. Like, just, we just need to confirm from the Eden team.
178 00:17:22.010 ⇒ 00:17:22.609 Ashwini Sharma: Yeah.
179 00:17:23.260 ⇒ 00:17:26.999 Ashwini Sharma: And we don’t have this payment history extracted from Polyatomics, right?
180 00:17:27.720 ⇒ 00:17:34.089 Demilade Agboola: No, that’s what we’re trying to build with the snapshots, so we can kind of have an idea of when amounts were paid.
181 00:17:34.610 ⇒ 00:17:37.309 Ashwini Sharma: No, because that payment history is not there at all with us.
182 00:17:37.550 ⇒ 00:17:42.569 Demilade Agboola: Yeah, I know, I know. That’s the problem. That’s what we told UpFluence, and they said they’re going to build.
183 00:17:43.180 ⇒ 00:17:45.370 Demilade Agboola: They’re going to integrate that into their roadmap.
184 00:17:45.580 ⇒ 00:17:51.329 Demilade Agboola: But for now, since we don’t have that, that’s why we’re using Snapshots, so we can say, hey, this is the amount that was paid out.
185 00:17:51.450 ⇒ 00:17:58.519 Demilade Agboola: maybe 1,200 has been paid, therefore $200 was paid out within that day.
186 00:17:58.770 ⇒ 00:18:01.760 Demilade Agboola: And we can just use that to build our own roadmap by ourselves.
187 00:18:02.090 ⇒ 00:18:04.050 Demilade Agboola: Or payments history ourselves here.
188 00:18:04.270 ⇒ 00:18:08.259 Ashwini Sharma: But even if I look into the snapshot, right, I want,
189 00:18:10.170 ⇒ 00:18:12.850 Ashwini Sharma: Yeah, maybe we can get this information, but…
190 00:18:12.850 ⇒ 00:18:14.900 Demilade Agboola: But it was on January 30th, right?
191 00:18:14.900 ⇒ 00:18:17.459 Ashwini Sharma: We won’t be able to, yeah, capture that.
192 00:18:18.260 ⇒ 00:18:22.059 Demilade Agboola: All I’m saying is about the retainer, let’s ask about the retainer. It’s insane.
193 00:18:22.060 ⇒ 00:18:22.520 Ashwini Sharma: Yeah.
194 00:18:22.520 ⇒ 00:18:27.160 Demilade Agboola: in dashboards… dashboard and API, but in the re… I mean, the…
195 00:18:27.940 ⇒ 00:18:36.749 Demilade Agboola: sheet to send me 1,000. Same thing for the orders. Let’s just get clarification for the Eden team. Are we undercounting, over-counting? Yeah, let’s just get that, let’s get that clear.
196 00:18:39.290 ⇒ 00:18:42.919 Ashwini Sharma: Alright, is there an email thread that I can reply to, or .
197 00:18:43.530 ⇒ 00:18:45.360 Demilade Agboola: For our plans, or for Ian?
198 00:18:46.070 ⇒ 00:18:47.070 Ashwini Sharma: How are you done, yeah?
199 00:18:47.520 ⇒ 00:18:52.010 Demilade Agboola: No, no, I didn’t need a Slack… Slack channel. I’ll add you to that right now.
200 00:18:52.780 ⇒ 00:18:53.400 Ashwini Sharma: Okay.
201 00:18:53.630 ⇒ 00:18:57.840 Demilade Agboola: So the people, your managers are Allison and… .
202 00:18:57.960 ⇒ 00:18:58.820 Zoran Selinger: Vanessa.
203 00:18:58.820 ⇒ 00:19:02.599 Demilade Agboola: Vanessa, yeah, so you will just ask them these questions, please.
204 00:19:03.180 ⇒ 00:19:03.800 Ashwini Sharma: Okay.
205 00:19:06.940 ⇒ 00:19:07.780 Ashwini Sharma: Alright.
206 00:19:08.420 ⇒ 00:19:12.100 Demilade Agboola: Alright, so I just added you, so you can ask them the questions, please.
207 00:19:12.580 ⇒ 00:19:13.580 Ashwini Sharma: Okay, sure.
208 00:19:13.750 ⇒ 00:19:14.809 Demilade Agboola: Alright, thank you.
209 00:19:15.390 ⇒ 00:19:16.030 Zoran Selinger: you guys?