Meeting Title: Refund sync Date: 2025-07-17 Meeting participants: Demilade Agboola, Katie Sullivan


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1 00:01:53.360 00:01:54.410 Katie Sullivan: Hello!

2 00:01:56.880 00:01:58.070 Demilade Agboola: Hi, Katie, how are you?

3 00:01:58.740 00:02:00.230 Katie Sullivan: Hey? I’m doing well. How are you?

4 00:02:00.900 00:02:01.830 Demilade Agboola: Firewall.

5 00:02:02.420 00:02:03.130 Katie Sullivan: Good.

6 00:02:04.460 00:02:10.479 Demilade Agboola: Let me just quickly sync with. I know the refunds have been a bit of an issue about the past couple of weeks.

7 00:02:10.985 00:02:14.839 Demilade Agboola: I just wanted to let you have an idea of what was going on.

8 00:02:15.356 00:02:24.080 Demilade Agboola: The high level summary is that we’re being handicapped by the data available from past or data that we get from past

9 00:02:24.763 00:02:30.410 Demilade Agboola: and I just want to give you some like examples of how that unfolds.

10 00:02:30.830 00:02:31.330 Katie Sullivan: Got it.

11 00:02:32.840 00:02:37.659 Demilade Agboola: So let me share my.

12 00:02:44.350 00:02:45.450 Demilade Agboola: is it my screen?

13 00:02:48.390 00:02:49.490 Katie Sullivan: Yes.

14 00:02:52.430 00:02:53.050 Demilade Agboola: Chest.

15 00:02:53.450 00:03:09.219 Demilade Agboola: So I attracted data from a certain timeframe. And then I decided to just filter by. These are the ones with refunds. So there’s a filter down to refunds only. So this is a raw bask extract.

16 00:03:09.610 00:03:10.180 Katie Sullivan: Yep.

17 00:03:10.540 00:03:18.670 Demilade Agboola: And then we can see that on this, in this timeframe we have 20 like rows where there are refund values.

18 00:03:20.694 00:03:28.710 Demilade Agboola: If we go to our web hook. So how we get data is bask sends us data through something called a web hook.

19 00:03:28.830 00:03:38.449 Demilade Agboola: So the data then leaves in our bigquery instance, and that’s like a data warehouse. And we query it, and just see what Pasca sent to us when we.

20 00:03:38.450 00:03:38.780 Katie Sullivan: Right.

21 00:03:38.780 00:03:40.749 Demilade Agboola: Try and query by the exact

22 00:03:40.990 00:03:46.820 Demilade Agboola: order numbers that we can see. So all 28. We only get 24

23 00:03:47.060 00:03:50.329 Demilade Agboola: that have a refund amount better than 0.

24 00:03:51.140 00:03:54.609 Demilade Agboola: So that means there are some that exist in this timeframe.

25 00:03:54.840 00:03:56.370 Katie Sullivan: But also.

26 00:03:56.580 00:04:00.240 Demilade Agboola: They don’t have like. It doesn’t represent. It’s not registered here as

27 00:04:00.400 00:04:11.480 Demilade Agboola: refunds, basically. And then in some cases we have also seen scenarios where we would have

28 00:04:12.880 00:04:16.159 Demilade Agboola: if, despite the fact that we only have

29 00:04:21.320 00:04:24.650 Demilade Agboola: right. Now take a second.

30 00:04:27.340 00:04:32.750 Demilade Agboola: And so this, if you look at this, this, is there are 2.

31 00:04:32.980 00:04:36.360 Demilade Agboola: There were 2 refunds for this order, right?

32 00:04:37.550 00:04:43.720 Demilade Agboola: And then the refund was 2,200

33 00:04:43.890 00:04:48.490 Demilade Agboola: 2,200 basically. And you know 2,000 blah blah.

34 00:04:48.700 00:04:50.690 Katie Sullivan: If we come here.

35 00:04:51.350 00:04:56.129 Demilade Agboola: And we search by that like that. Id

36 00:04:56.450 00:04:58.459 Demilade Agboola: alone on that order, not by loan.

37 00:04:58.930 00:05:05.940 Demilade Agboola: We would see that there’s only one scenario in which that refund occurred. It doesn’t appear twice, just appears once.

38 00:05:06.570 00:05:15.860 Demilade Agboola: Not only not only do we have situations where some don’t appear, and that’s the 2,000, so there was only one refund, the other refund of $2,064

39 00:05:16.510 00:05:24.249 Demilade Agboola: doesn’t rep it. It shows in our web hook, but it doesn’t show in the Royal Pass data, you know. Potentially we we.

40 00:05:24.840 00:05:32.260 Demilade Agboola: It’s a thing of maybe it did happen. It was processed, it canceled. And then it was already sent to us. We will need to like sync with bask on this.

41 00:05:32.930 00:05:33.290 Katie Sullivan: Okay.

42 00:05:33.290 00:05:37.920 Demilade Agboola: Because obviously, these these things put our numbers in like a bad spot.

43 00:05:38.450 00:05:52.510 Demilade Agboola: We don’t want you, for instance, in this case, reimbursing someone over 2,200. Yeah. So just being able to like, know what’s going on

44 00:05:52.660 00:05:57.850 Demilade Agboola: and give you that full clarity. So we have a meeting in Basque early next week. I believe it’s Tuesday.

45 00:05:58.311 00:06:07.979 Demilade Agboola: But we will present all these findings not just about refunds, but like the bask interface, because we also have issues with the data quality coming from bask. And we’re obviously.

46 00:06:07.980 00:06:08.339 Katie Sullivan: Got it.

47 00:06:08.340 00:06:11.469 Demilade Agboola: You know, limited to whatever you know we can do with bask.

48 00:06:12.920 00:06:16.603 Katie Sullivan: Understood. Thank you. I appreciate the explanation.

49 00:06:18.240 00:06:24.130 Katie Sullivan: I think so. What I have to do basically on my end is, go through these manually and see

50 00:06:24.945 00:06:32.170 Katie Sullivan: why we we refunded, and whether it like a true cancellation, or maybe

51 00:06:32.410 00:06:36.584 Katie Sullivan: you know, the customer accidentally triggered a charge by clicking on something.

52 00:06:37.580 00:06:44.330 Katie Sullivan: So even though it’s not 100% accurate, yet would it be possible to pull all the data from.

53 00:06:44.720 00:06:53.480 Katie Sullivan: say June and the 1st half of July, because it’s gonna take me like a really really long time

54 00:06:53.700 00:06:54.200 Katie Sullivan: of.

55 00:06:54.200 00:07:00.359 Demilade Agboola: Oh, no, if if you want it for June and 1st half of July, I can get that to you within the hour. If you.

56 00:07:00.360 00:07:13.335 Katie Sullivan: Oh, awesome! That would be great. I can at least then get started. On going through it, and have more like a rough estimate to present to Adam of like you know what our actual refund rate is.

57 00:07:14.110 00:07:21.830 Katie Sullivan: And then, when we get it resolved with Basque, we can just do a like, I can just do a better job of it. Moving forward. Basically.

58 00:07:22.130 00:07:22.990 Demilade Agboola: Okay.

59 00:07:23.110 00:07:24.070 Demilade Agboola: And then.

60 00:07:24.070 00:07:24.920 Katie Sullivan: Sure!

61 00:07:25.120 00:07:26.220 Katie Sullivan: Oh, sorry!

62 00:07:26.490 00:07:31.989 Demilade Agboola: I was just gonna ask, do you do you want this to be like an order list? Or do you want like us? A rolled up aggregate.

63 00:07:34.093 00:07:37.539 Katie Sullivan: No, it has to be by order, like line by line.

64 00:07:38.020 00:07:39.009 Demilade Agboola: Okay, that’s fine.

65 00:07:39.777 00:07:48.919 Katie Sullivan: And then like future when it’s resolved with Basque, if we could. Kind of I I know you had put together a dashboard which seems to be working, and then it kind of

66 00:07:49.160 00:08:03.530 Katie Sullivan: stopped working. If we could have a like dashboard that gets updated every day for the previous day’s refund. So so then we can kind of track it on a day by day basis and not spend like a week going through the entire month.

67 00:08:05.000 00:08:09.220 Demilade Agboola: Yeah, that’s fine. It does. It does work. Yes, definitely.

68 00:08:09.640 00:08:15.079 Katie Sullivan: Like it’s like, it’s not. I like, I’m doing more refunds than it’s showing. So I know it’s way awesome.

69 00:08:15.950 00:08:18.049 Demilade Agboola: No, I understand.

70 00:08:18.050 00:08:29.129 Katie Sullivan: I know, like, yeah, like it works. But yeah, there’s just I know it’s way more than that. And I’m nervous that people are looking at it like, Oh, we’re doing a really good job on refunds, and we’re not.

71 00:08:30.430 00:08:33.200 Demilade Agboola: Well, that’s fair. That’s fair. I will.

72 00:08:34.010 00:08:37.359 Demilade Agboola: Again. It all comes back to like this web hook thing.

73 00:08:37.360 00:08:38.470 Demilade Agboola: Yeah, I know

74 00:08:38.470 00:08:51.860 Demilade Agboola: issue. And I also some of these things, because I know, like right now, ensuring that we’ve seen 24 refunds. I know when I looked at it last week, because I did this investigation last week. I only saw about 17 refunds.

75 00:08:52.000 00:09:00.399 Demilade Agboola: and that was even with the duplicates. So that means some of them actually came in over the past like week or so. So it’s it’s a bit tricky, which is.

76 00:09:00.690 00:09:08.520 Katie Sullivan: Is it when like it would be triggered, based on, when we refund not, when the refund processes right.

77 00:09:10.833 00:09:11.480 Demilade Agboola: I think.

78 00:09:11.480 00:09:11.840 Katie Sullivan: You know.

79 00:09:11.840 00:09:13.350 Demilade Agboola: I think it’ll be.

80 00:09:13.470 00:09:19.949 Demilade Agboola: I would need to sync with Bath to be fair if I can give you a full response, but I do believe it will be

81 00:09:20.510 00:09:21.750 Demilade Agboola: based off.

82 00:09:24.660 00:09:26.299 Katie Sullivan: Like when we click that button.

83 00:09:26.690 00:09:31.160 Demilade Agboola: Yeah, I think it would be best off when you click the button. I’ll just need to be.

84 00:09:31.290 00:09:32.600 Katie Sullivan: Okay, yeah, it should be sure.

85 00:09:32.600 00:09:39.479 Katie Sullivan: If it’s not, then we’ll have to like run historical report like, we will have to like, wait a week, you know.

86 00:09:39.820 00:09:41.590 Katie Sullivan: Yeah, if they yeah, not change.

87 00:09:42.320 00:09:49.650 Demilade Agboola: Yeah, the thing is a bit frustrating when like numbers are not available, like, right? When they happen.

88 00:09:49.870 00:09:52.270 Demilade Agboola: Yeah, no, I think Bask has a lot of a.

89 00:09:52.500 00:09:54.869 Katie Sullivan: Has a lot of issues there. So.

90 00:09:55.100 00:10:03.680 Demilade Agboola: Yeah, that’s part of why, I just said, like, let me reach out to you. So we can just have a quick sync, and we can just be on the same page. So you don’t keep wondering what’s going on.

91 00:10:03.680 00:10:06.328 Katie Sullivan: Okay, cool. Yeah, no. I appreciate that. And

92 00:10:07.270 00:10:17.329 Katie Sullivan: and yeah, so I think short term, you know, if if I can just get like that summary. It’s gonna be a really long list. But that’ll be fine, for now and then, hopefully, we can get bask.

93 00:10:17.790 00:10:24.390 Demilade Agboola: Alright fine is, are there any things you want to see in particular in the list? Is it just the orders and the other total, like the other number and the other total.

94 00:10:24.390 00:10:24.730 Demilade Agboola: Yeah, I just.

95 00:10:25.330 00:10:31.580 Katie Sullivan: Order order number order total is fine. I’m just gonna search it. And that’s it.

96 00:10:31.710 00:10:35.440 Demilade Agboola: Gotcha, and I’ll also add the refund amount just for good measure.

97 00:10:35.440 00:10:37.909 Katie Sullivan: Yes. Yes. Refund. Amount. Yeah. Perfect.

98 00:10:39.080 00:10:44.559 Demilade Agboola: I’ll send this to you like probably just right now, to be honest, since I’m on it.

99 00:10:45.160 00:10:46.950 Katie Sullivan: Okay, awesome. I appreciate that.

100 00:10:47.390 00:10:48.230 Demilade Agboola: You’re welcome.

101 00:10:48.380 00:10:50.829 Demilade Agboola: Alright. Then it was great talking to you.

102 00:10:51.320 00:10:54.633 Demilade Agboola: Yeah, likewise, and good luck with Basque next week. I hope they fix it.

103 00:10:56.620 00:10:58.310 Demilade Agboola: Thank you very much. We’ll need all the luck.

104 00:10:58.310 00:10:59.880 Katie Sullivan: Later, bye.

105 00:10:59.880 00:11:00.540 Demilade Agboola: Bye.