Meeting Title: ABC | Data Catch up Date: 2025-04-30 Meeting participants: Annie Yu, Amber Lin
WEBVTT
1 00:00:40.900 ⇒ 00:00:42.290 Annie Yu: Hi amber.
2 00:00:42.290 ⇒ 00:00:45.119 Amber Lin: Hi! Oh, I didn’t know you were there. I just texted you.
3 00:00:45.953 ⇒ 00:00:46.786 Annie Yu: Nice.
4 00:00:48.580 ⇒ 00:00:55.749 Annie Yu: Okay, okay, we are. Gonna go through. I guess my tickets.
5 00:00:57.240 ⇒ 00:01:06.979 Amber Lin: Yeah, we’ll flesh them out together. Essentially, one is our daily, like weekly stuff of getting stuff from Brian.
6 00:01:07.120 ⇒ 00:01:07.950 Annie Yu: Hmm.
7 00:01:07.950 ⇒ 00:01:11.679 Amber Lin: Which let’s ping him now, cause he.
8 00:01:11.680 ⇒ 00:01:13.320 Annie Yu: I just said I just.
9 00:01:13.320 ⇒ 00:01:14.040 Amber Lin: Okay. Then.
10 00:01:14.040 ⇒ 00:01:15.720 Annie Yu: A second ago.
11 00:01:16.280 ⇒ 00:01:21.919 Amber Lin: Yeah, that cause I had, like my brain has just been caught in other meetings. Nonstop. So.
12 00:01:21.920 ⇒ 00:01:39.329 Annie Yu: No, that makes sense. I I think also, just because I don’t really know. I know that obviously before until we get everything integrated. We. We will need his support to get those data manually. But I think also, like, just because we.
13 00:01:39.330 ⇒ 00:01:40.120 Amber Lin: Cut off.
14 00:01:40.120 ⇒ 00:01:41.900 Annie Yu: Oh, can you hear me? Okay. Now.
15 00:01:41.900 ⇒ 00:01:43.200 Amber Lin: Yeah, I can hear you now.
16 00:01:43.200 ⇒ 00:02:12.720 Annie Yu: So we, yeah, I, I was also thinking, like, which is the best day to ask for that. Just because if we are showing data. If we are showing dashboard on a Thursday or Friday, I think initially, I thought, okay, I want to get the data as early as possible. But now, I think, okay, if we’re showing a dashboard on a Thursday or Friday, it would make sense to get, I guess. Wait a couple more days, so we get more days of data. So.
17 00:02:13.060 ⇒ 00:02:18.420 Amber Lin: I mean that hopefully this manual process only lasts for
18 00:02:20.560 ⇒ 00:02:22.279 Annie Yu: This week. Is that too.
19 00:02:22.280 ⇒ 00:02:31.469 Amber Lin: Yeah, hopefully, this manual process only lasts for, like at least a week or 2. I really want him to send the Api key. But there is nothing we can do.
20 00:02:31.470 ⇒ 00:02:31.950 Annie Yu: What’s.
21 00:02:31.950 ⇒ 00:02:33.140 Amber Lin: Have the key.
22 00:02:33.370 ⇒ 00:02:41.440 Annie Yu: Yeah, I what’s the process now? I don’t really know. What would the flow look like? And what’s the the status now.
23 00:02:41.714 ⇒ 00:02:42.810 Amber Lin: What do you mean?
24 00:02:42.970 ⇒ 00:02:48.070 Annie Yu: The from from like to move the data
25 00:02:48.190 ⇒ 00:02:54.439 Annie Yu: into our system. And where are are we switching a different K Api.
26 00:02:55.422 ⇒ 00:02:57.300 Amber Lin: Right now, we don’t have any.
27 00:02:57.480 ⇒ 00:03:01.399 Amber Lin: We had. Okay. So you know how Apis work. Right?
28 00:03:02.140 ⇒ 00:03:08.350 Amber Lin: Briefly, Casey was able to get one of them working. So we know that it will work.
29 00:03:08.720 ⇒ 00:03:09.120 Annie Yu: Yeah.
30 00:03:09.120 ⇒ 00:03:12.429 Amber Lin: The Api key that he got has limited information.
31 00:03:13.300 ⇒ 00:03:13.870 Annie Yu: So.
32 00:03:13.870 ⇒ 00:03:20.999 Amber Lin: You’re asking Tim to, hey? Can you give us the key to this one that apparently has a lot more information to your system?
33 00:03:21.300 ⇒ 00:03:24.029 Amber Lin: So we’re gonna try and get that.
34 00:03:24.490 ⇒ 00:03:35.799 Amber Lin: And ultimately, the Api should should the say, acceptance criteria for that is that it should give you all the information you need to create a good dashboard.
35 00:03:37.770 ⇒ 00:03:38.170 Amber Lin: Oh!
36 00:03:38.170 ⇒ 00:03:47.209 Annie Yu: That could mean more, we would. We would possibly get more data fields than the Brian than the one Brian provided.
37 00:03:47.210 ⇒ 00:03:51.889 Amber Lin: Yeah, cause that one he he like manually chooses what columns.
38 00:03:51.890 ⇒ 00:03:52.539 Annie Yu: I know.
39 00:03:52.990 ⇒ 00:03:58.679 Amber Lin: The Api will give you more options, and then you can pick and choose to see like what works and what doesn’t.
40 00:03:58.850 ⇒ 00:03:59.960 Annie Yu: Yeah, yeah.
41 00:03:59.960 ⇒ 00:04:06.860 Amber Lin: Yeah, so that would be the process. I just don’t know when Tim is. Gonna give you that one tomorrow. Let’s ask Yvette
42 00:04:06.970 ⇒ 00:04:08.080 Amber Lin: on.
43 00:04:08.230 ⇒ 00:04:15.159 Amber Lin: hey? Can you nudge Tim cause we would love to do it, but we’re stuck on your end. So.
44 00:04:15.644 ⇒ 00:04:16.130 Annie Yu: Yeah.
45 00:04:16.130 ⇒ 00:04:22.760 Amber Lin: That’s the event tomorrow. So that’s that’s where the Api stuff before that comes we’ll just have to do things manually.
46 00:04:24.850 ⇒ 00:04:26.650 Amber Lin: Is there?
47 00:04:27.470 ⇒ 00:04:30.200 Amber Lin: How do you want to structure tomorrow’s review
48 00:04:32.650 ⇒ 00:04:40.680 Amber Lin: the dashboard. And we can look at the different areas we have and kind of what you want to talk about for tomorrow.
49 00:04:41.600 ⇒ 00:04:46.469 Annie Yu: So is this review more so for our
50 00:04:47.130 ⇒ 00:04:52.459 Annie Yu: so like to see the impact of using our bot versus not.
51 00:04:52.860 ⇒ 00:05:02.029 Amber Lin: Kind of like, also a good, because I don’t think they have a dashboard yet, like even internally, I think they only have an excel sheet.
52 00:05:02.300 ⇒ 00:05:04.180 Annie Yu: That’s my assumption.
53 00:05:04.350 ⇒ 00:05:26.410 Amber Lin: So we’ll see how much like what state event is that for their internal reporting? I don’t think they have a dashboard. So even just to walk through the basic kpis of, okay, how was maybe, how was this month, or how is this week? And ideally, we can also show them what our, what the impact of our bot is. What do you think.
54 00:05:28.870 ⇒ 00:05:36.252 Annie Yu: I do think that’s doable and makes sense. I do notice one thing, though.
55 00:05:37.390 ⇒ 00:05:42.217 Annie Yu: so right now we don’t have a lot of metrics to compare
56 00:05:43.110 ⇒ 00:05:47.729 Annie Yu: bot assisted calls versus not right. But we do have
57 00:05:47.850 ⇒ 00:05:53.649 Annie Yu: that average handling time. But that average handling time is actually
58 00:05:54.270 ⇒ 00:06:01.940 Annie Yu: much longer for bot assisted calls compared to the total.
59 00:06:03.160 ⇒ 00:06:04.240 Amber Lin: See? Oh.
60 00:06:05.030 ⇒ 00:06:19.289 Amber Lin: that one. Yeah. I wanted to. I wanted to have a note on that one. I kind of know why it’s longer, because we, the total one, has all divisions. If you look at pest, the average handling time is a lot longer.
61 00:06:19.990 ⇒ 00:06:24.480 Amber Lin: because the total one average is also a lot of reception calls
62 00:06:24.690 ⇒ 00:06:32.009 Amber Lin: where it gets routed really quickly, so they will take very short period of time because they’re not actually answering the calls.
63 00:06:32.440 ⇒ 00:06:40.539 Amber Lin: So. Do you know, if we can filter those like all of those calls by just pest and compare them.
64 00:06:41.830 ⇒ 00:06:43.844 Annie Yu: Let me. Let me let me.
65 00:06:44.690 ⇒ 00:06:48.430 Annie Yu: Can I steal the screen and we can see if we can.
66 00:06:48.430 ⇒ 00:06:50.600 Amber Lin: Yeah, can you share your screen?
67 00:06:50.820 ⇒ 00:06:51.540 Annie Yu: Yeah.
68 00:06:51.840 ⇒ 00:06:52.350 Amber Lin: Yeah.
69 00:06:53.350 ⇒ 00:06:53.930 Annie Yu: Okay.
70 00:06:54.330 ⇒ 00:07:00.160 Annie Yu: So so these are cute name, right? And then I’m I’m setting.
71 00:07:00.290 ⇒ 00:07:02.870 Annie Yu: I think we only got data till this day.
72 00:07:03.110 ⇒ 00:07:04.120 Annie Yu: So far.
73 00:07:04.120 ⇒ 00:07:04.600 Amber Lin: That’s okay.
74 00:07:04.600 ⇒ 00:07:08.489 Annie Yu: Okay? And then so we’ll see queue name.
75 00:07:10.018 ⇒ 00:07:18.670 Amber Lin: Down there, count. It’s like count by queue. I tried to filter last time, but I wasn’t able to hence why I sent you the sent you the message.
76 00:07:19.000 ⇒ 00:07:21.049 Amber Lin: Say, if we select.
77 00:07:21.530 ⇒ 00:07:23.630 Annie Yu: Residential pest.
78 00:07:23.630 ⇒ 00:07:25.220 Amber Lin: Yeah, residential. Pest.
79 00:07:25.660 ⇒ 00:07:29.750 Annie Yu: Okay, what’s this past? Cp, do you know.
80 00:07:29.750 ⇒ 00:07:36.820 Amber Lin: Maybe maybe that’s let’s just see pass. And we’ll figure out the other parts later.
81 00:07:38.135 ⇒ 00:07:44.210 Amber Lin: So average way, average handling is 4.5 min.
82 00:07:44.330 ⇒ 00:07:47.909 Amber Lin: What is it for our bot handling time.
83 00:07:48.080 ⇒ 00:07:49.540 Annie Yu: 8.2.
84 00:07:52.970 ⇒ 00:07:54.300 Amber Lin: That’s so funny.
85 00:07:54.300 ⇒ 00:08:05.420 Annie Yu: And I think that’s also why I wanted to ask for not average handling time, but average holding time.
86 00:08:06.460 ⇒ 00:08:14.029 Annie Yu: you know, like handling. Time means when I’m a customer. If I just happen to have more questions and.
87 00:08:14.030 ⇒ 00:08:14.830 Amber Lin: Yeah.
88 00:08:14.830 ⇒ 00:08:17.050 Annie Yu: Your handling time will always increase, but
89 00:08:18.930 ⇒ 00:08:21.160 Annie Yu: when they are searching for it, and.
90 00:08:21.160 ⇒ 00:08:33.070 Amber Lin: So yeah, let’s let’s write that down. That’s a great point to raise the event, because we can say, Hey, it might take longer, because we’re having a better relationship. We’re like doing more sales. And we don’t know
91 00:08:33.340 ⇒ 00:08:53.640 Amber Lin: even we don’t even know what type of call it is. It could be more of like. It’s taking longer, because it’s more junior people using the bot, or it’s taking longer, because it’s like very senior people using the bot with Janice, and she’s handling very, very tough situations. So I guess we can
92 00:08:54.890 ⇒ 00:09:06.970 Amber Lin: like a point of get average holding time and also divide by call type.
93 00:09:07.710 ⇒ 00:09:08.510 Amber Lin: Yeah.
94 00:09:14.250 ⇒ 00:09:23.760 Annie Yu: I think also I might have to ask, do we have any analytics engineer on the team now, or just.
95 00:09:23.760 ⇒ 00:09:27.500 Amber Lin: No, but we can add, we can add them. Who do you want like? What do we need.
96 00:09:28.492 ⇒ 00:09:32.569 Annie Yu: One thing I can show you real quick. I
97 00:09:33.000 ⇒ 00:09:40.049 Annie Yu: I haven’t done this for a while, but one thing I do want, someone’s kind of verification was
98 00:09:40.170 ⇒ 00:09:42.410 Annie Yu: I had to do like a
99 00:09:43.940 ⇒ 00:09:54.840 Annie Yu: how do I explain this? So so remember, like, we were having different records. Okay, let’s say, if 1 1 phone call and this person used
100 00:09:55.460 ⇒ 00:10:08.159 Annie Yu: that had 3 box botch exchanges right? So there’s back and forth, back and forth, back and forth, and our spreadsheet, or in our table, that
101 00:10:09.430 ⇒ 00:10:12.579 Annie Yu: That handling time will get duplicated
102 00:10:12.740 ⇒ 00:10:15.870 Annie Yu: across those roles. So if they sell it.
103 00:10:16.650 ⇒ 00:10:25.870 Annie Yu: So I did write a code. So we only get the 1st average handling time of each conversation.
104 00:10:26.660 ⇒ 00:10:34.109 Annie Yu: Of each phone call. And I did write that, and then Utop approved. But I I think I am.
105 00:10:34.390 ⇒ 00:10:44.440 Annie Yu: I think that’s that’s something I like don’t normally deal with a lot. So I think I might ask to just to double check again. That’s
106 00:10:45.010 ⇒ 00:10:51.410 Annie Yu: something we are doing right. Just so we are. We are making sure. Okay, we are not duplicating the time here.
107 00:10:51.410 ⇒ 00:11:00.629 Amber Lin: Sure. Yeah, yeah, totally. And especially once, I think the Ae will be really helpful, especially once we have the Api data.
108 00:11:01.120 ⇒ 00:11:14.019 Amber Lin: So let’s raise that, Tom, and get him like an idea of who we want to put on here. And once we get that data, I’ll the Ae. We’ll get the Ae. Started
109 00:11:14.250 ⇒ 00:11:16.139 Amber Lin: on helping with that.
110 00:11:17.230 ⇒ 00:11:22.630 Annie Yu: Oh, okay, so wait. So are you saying that we are planning to get an A or.
111 00:11:22.630 ⇒ 00:11:27.959 Amber Lin: I think so. I heard some of it mentioned before, and like I mean, why not?
112 00:11:29.250 ⇒ 00:11:36.849 Amber Lin: If that’s your expertise, and this is, say something will take them an hour versus for 4 h, like, why wouldn’t we put a on here.
113 00:11:36.850 ⇒ 00:11:40.679 Annie Yu: That’s true, that’s true. They don’t have to dedicate like a 10 h, 20 h.
114 00:11:40.680 ⇒ 00:11:43.910 Amber Lin: Exactly. So this is, and it’s pretty pretty straightforward.
115 00:11:44.080 ⇒ 00:11:47.959 Amber Lin: and we have a pretty good bot that will explain anything that they need.
116 00:11:48.080 ⇒ 00:11:50.529 Amber Lin: So I don’t see a problem with that.
117 00:11:51.460 ⇒ 00:11:52.840 Annie Yu: Okay, okay. But.
118 00:11:52.840 ⇒ 00:11:54.599 Amber Lin: I mean sorry. Go ahead.
119 00:11:54.600 ⇒ 00:12:02.740 Annie Yu: No, no, I’m I think I I will find like a call with more than one record as an example, and then
120 00:12:03.060 ⇒ 00:12:11.380 Annie Yu: probably screenshot my code, and then I will, Tom, to make sure that I’m doing it right, he approved. But I he might not know.
121 00:12:11.380 ⇒ 00:12:13.829 Amber Lin: I haven’t looked at it closely.
122 00:12:14.870 ⇒ 00:12:20.350 Amber Lin: Great! How do you want to structure the walkthrough tomorrow? I want.
123 00:12:21.090 ⇒ 00:12:21.690 Amber Lin: Thank you.
124 00:12:26.700 ⇒ 00:12:35.519 Amber Lin: I know they will also have a lot of questions, I guess, like a 1st thing we could just walk through like explain to them what each of these do.
125 00:12:35.520 ⇒ 00:12:40.419 Annie Yu: We do have yeah, we we have 3 sections, even though
126 00:12:41.080 ⇒ 00:12:53.480 Annie Yu: I think this dashboard is way too long. It’s way too big. But we are just squeezing everything in now. I think obviously, we’ll start with this one. This is like total cost.
127 00:12:53.480 ⇒ 00:12:54.150 Amber Lin: Yeah.
128 00:12:54.150 ⇒ 00:12:57.410 Annie Yu: Including bot used or not.
129 00:12:58.049 ⇒ 00:13:03.799 Annie Yu: And yeah, I don’t think we have to explain these kpis a lot, because I feel like they.
130 00:13:03.800 ⇒ 00:13:04.950 Amber Lin: Yeah, very very helpful.
131 00:13:04.950 ⇒ 00:13:05.860 Amber Lin: Hilary.
132 00:13:11.880 ⇒ 00:13:20.289 Amber Lin: Yeah, I guess the main thing we need to teach them is to like filter by queue name, residential pest, or else they’ll just get really confused.
133 00:13:20.716 ⇒ 00:13:25.830 Annie Yu: Okay, yeah, we can touch on how to get like, add filters.
134 00:13:27.730 ⇒ 00:13:31.399 Annie Yu: And this like this is where I like.
135 00:13:33.040 ⇒ 00:13:33.820 Annie Yu: Still.
136 00:13:33.820 ⇒ 00:13:34.290 Amber Lin: At all.
137 00:13:34.290 ⇒ 00:13:41.229 Annie Yu: So like real, but because I feel like when when you filter, you should just keep dimensions, but not the
138 00:13:41.620 ⇒ 00:13:47.130 Annie Yu: measures. I guess we yeah, no. I think this makes sense.
139 00:13:48.070 ⇒ 00:13:48.780 Amber Lin: Okay.
140 00:13:49.650 ⇒ 00:13:50.200 Annie Yu: Okay.
141 00:13:51.100 ⇒ 00:13:51.920 Annie Yu: Oh.
142 00:13:52.270 ⇒ 00:13:58.930 Amber Lin: Okay, I mean, tomorrow will just be an establishment of, and then oh, a goal for tomorrow. I think
143 00:13:59.270 ⇒ 00:14:11.010 Amber Lin: we should also get some feedback from Yvette of what she wants to use this dashboard for, and then I think you would be a great person to answer her questions as to like what’s possible.
144 00:14:14.250 ⇒ 00:14:14.760 Amber Lin: Oh!
145 00:14:14.760 ⇒ 00:14:15.490 Annie Yu: Okay.
146 00:14:15.750 ⇒ 00:14:21.790 Amber Lin: Yeah, I don’t know. What do you want to just come up with a few questions to prompt her to start
147 00:14:21.980 ⇒ 00:14:22.510 Amber Lin: like.
148 00:14:23.190 ⇒ 00:14:29.660 Amber Lin: because maybe you already have ideas of. Okay, this would be a good thing to show like, what do you think.
149 00:14:30.031 ⇒ 00:14:42.288 Annie Yu: Think I would think. Given what we have now, I initially thought I would want to compare the average handling time, but in this case. I don’t know if we should.
150 00:14:42.860 ⇒ 00:14:43.430 Amber Lin: Hmm.
151 00:14:44.533 ⇒ 00:14:54.859 Amber Lin: we can like we can compare and just raise to her. Hey, this is the this is what we see. This is why we want average holding time, because we want an accurate measure.
152 00:14:55.488 ⇒ 00:15:03.129 Amber Lin: And then we go. We’ll also ask her, like, what are other measures you you want to compare between, like bot versus non bot.
153 00:15:06.100 ⇒ 00:15:07.000 Annie Yu: Yeah.
154 00:15:07.000 ⇒ 00:15:08.389 Amber Lin: Yeah, okay,
155 00:15:11.040 ⇒ 00:15:16.061 Annie Yu: I’ll I’ll I’ll set some time today and then go through this.
156 00:15:20.610 ⇒ 00:15:27.269 Annie Yu: yeah, I’ll try to come up with 1, 1 or 2 questions that we can try to answer. Using this one.
157 00:15:27.670 ⇒ 00:15:30.319 Amber Lin: Yeah, awesome. I think that’s all we need.
158 00:15:30.610 ⇒ 00:15:38.879 Amber Lin: Tomorrow is just gonna be an intro. It’s only 30 min. And now I also have some other questions like, not related to the dashboard. I want to ask her. So
159 00:15:39.060 ⇒ 00:15:40.210 Amber Lin: it’s okay.
160 00:15:40.550 ⇒ 00:15:41.649 Amber Lin: Okay. Yeah.
161 00:15:41.890 ⇒ 00:15:44.539 Amber Lin: That’s all. How are you? Recently.
162 00:15:44.880 ⇒ 00:15:52.227 Annie Yu: Not too bad. I having a pause on Javi Helps.
163 00:15:53.580 ⇒ 00:15:56.319 Annie Yu: I feel like I can only do like
164 00:15:56.550 ⇒ 00:16:00.730 Annie Yu: 2 to 3 projects, Max. A day.
165 00:16:00.730 ⇒ 00:16:01.560 Amber Lin: What are you off.
166 00:16:04.460 ⇒ 00:16:12.750 Annie Yu: I am on Eden, Eden, and then joby matter more in this one.
167 00:16:14.920 ⇒ 00:16:23.520 Annie Yu: But I feel like the bees, the busiest for me are Eden or Javi.
168 00:16:24.080 ⇒ 00:16:28.999 Annie Yu: So it’s kinda nice to have. Joby paused so I can.
169 00:16:29.000 ⇒ 00:16:29.330 Amber Lin: Up.
170 00:16:29.330 ⇒ 00:16:31.430 Annie Yu: Do more like, eat them, work.
171 00:16:31.780 ⇒ 00:16:32.810 Amber Lin: Totally.
172 00:16:32.990 ⇒ 00:16:38.310 Amber Lin: I’m just getting more and more crowded every single day.
173 00:16:38.930 ⇒ 00:16:42.940 Amber Lin: Yeah. Well, you do have a lot of meetings right?
174 00:16:42.940 ⇒ 00:16:51.950 Amber Lin: I have. ABC, I have internal AI team. I have matter more. I have the sales go to market project
175 00:16:52.220 ⇒ 00:16:59.320 Amber Lin: and think, yeah, I think that’s mostly it.
176 00:16:59.540 ⇒ 00:17:03.169 Amber Lin: like here and there urban stems, but not really.
177 00:17:04.250 ⇒ 00:17:09.540 Annie Yu: Who are on those projects. I feel like I never really heard who’s on.
178 00:17:11.540 ⇒ 00:17:31.700 Amber Lin: Is our, you know. For urban stamps. It’s mostly damalade. And but now we’re planning for the next phase. So the next phase is going to get out of it and put Luke in and also go into Pm, that’s urban stamps for
179 00:17:32.240 ⇒ 00:17:38.550 Amber Lin: internal AI team. It’s Casey Miguel, and then a wish to help with the data stuff.
180 00:17:38.550 ⇒ 00:17:41.099 Annie Yu: We wish it’s on ait too.
181 00:17:41.438 ⇒ 00:17:49.560 Amber Lin: He’s helping with data, because we have a lot of, we’re ingesting all of our internal data sources. So there’s like linear slack Github.
182 00:17:50.120 ⇒ 00:17:58.439 Amber Lin: Meetings, and AI. The engineers don’t know much about data. They were stuck for 4 whole weeks on it, so we got a wait on.
183 00:17:58.710 ⇒ 00:18:01.745 Amber Lin: Oh, that’s cool or
184 00:18:02.700 ⇒ 00:18:09.110 Amber Lin: full parts. Oh, yeah, I forgot to mention full parts is just mostly just me and Luke, for now.
185 00:18:09.480 ⇒ 00:18:10.280 Annie Yu: Oh!
186 00:18:10.280 ⇒ 00:18:12.960 Amber Lin: Yeah. And then for sales
187 00:18:13.200 ⇒ 00:18:22.740 Amber Lin: that we have a like, go to market project, which we get. So the flow is like, we get a list of people
188 00:18:22.980 ⇒ 00:18:39.570 Amber Lin: from like related to events, or interact with our posts, or just related to a company, and then we enrich, make a lead list out of it, enrich the lead list, and then eventually want to like automate sending messages. So that project we’re doing.
189 00:18:40.330 ⇒ 00:18:45.020 Amber Lin: That’s me, Luke, Marianne and Ryan.
190 00:18:45.170 ⇒ 00:18:46.030 Amber Lin: So.
191 00:18:46.570 ⇒ 00:18:50.260 Annie Yu: Got it. Wait right. Wait! Who’s Ryan?
192 00:18:50.260 ⇒ 00:18:53.169 Annie Yu: Brian is the content person on the marketing?
193 00:18:53.170 ⇒ 00:18:58.400 Annie Yu: Oh, oh, yeah, yeah, that’s Ryan. I I feel like I keep seeing wait. But Luke’s middle name is Ryan.
194 00:18:58.480 ⇒ 00:19:08.349 Amber Lin: Luke is his. Luke is 1st name is Ryan, but because we have content Ryan. So okay, just use my middle name.
195 00:19:08.510 ⇒ 00:19:14.799 Annie Yu: Wait. Oh, okay, but is, does he prefer to be called Luke or Ryan?
196 00:19:15.210 ⇒ 00:19:21.999 Annie Yu: I? He said. He doesn’t care, so I would say, Luke, cause I can’t afford to be so confused.
197 00:19:22.822 ⇒ 00:19:26.937 Annie Yu: Got it? That’s why. Okay.
198 00:19:27.760 ⇒ 00:19:39.909 Amber Lin: Yeah, I know sometimes his like Zoom is still Ryan. So I get really confused. And so older people who folks who were here earlier still. Call him Ryan, so I get lost.
199 00:19:40.360 ⇒ 00:19:58.337 Annie Yu: Oh, okay, yeah. I think I think I remember seeing him in a meeting, and then I remember he was Ryan. But then I went to another meeting, and people look, and I was like, Wait, are they 2 different people? Or I just remember, like wrong.
200 00:20:00.360 ⇒ 00:20:07.190 Amber Lin: Yeah, that’s that. Okay, I think I have another meeting. Let me go. Check.
201 00:20:10.780 ⇒ 00:20:14.079 Amber Lin: Okay, I don’t have meetings for now, Chris.
202 00:20:14.240 ⇒ 00:20:19.170 Amber Lin: Great talking to you. I’m gonna go eat some, eat breakfast.
203 00:20:19.520 ⇒ 00:20:24.159 Annie Yu: Yeah, and I’ll I’ll I’ll I’ll do that
204 00:20:25.050 ⇒ 00:20:28.659 Annie Yu: thing to to make Utam review again.
205 00:20:28.660 ⇒ 00:20:29.210 Amber Lin: Okay.
206 00:20:29.210 ⇒ 00:20:30.889 Annie Yu: Double check. Okay.
207 00:20:31.640 ⇒ 00:20:40.030 Amber Lin: Sounds good. I’ll also send, like agenda for tomorrow in our channel, and just add add your questions or comments to it.
208 00:20:40.570 ⇒ 00:20:46.059 Annie Yu: Okay. Alright, thank you so much, amber bye, for now.