Meeting Title: ABC Standup Date: 2025-08-15 Meeting participants: Casie Aviles, Amber Lin, Mustafa Raja


WEBVTT

1 00:00:12.830 00:00:13.980 Amber Lin: Hello.

2 00:00:16.379 00:00:17.019 Casie Aviles: A.

3 00:00:17.990 00:00:22.600 Amber Lin: Let’s talk about the insomnia cookies slide.

4 00:00:23.820 00:00:28.210 Amber Lin: Hmm… That’s neat.

5 00:00:33.500 00:00:34.510 Amber Lin: Okay.

6 00:00:46.470 00:00:53.850 Casie Aviles: Oh, … Yeah, for this client, yeah, I was able to…

7 00:00:54.550 00:00:58.189 Casie Aviles: put this into DON, I deployed it on Dogster, so….

8 00:00:58.400 00:00:58.860 Amber Lin: Hmm.

9 00:00:58.860 00:01:04.079 Casie Aviles: Every… yeah, every 9 a.m. Eastern Time, I believe.

10 00:01:04.300 00:01:06.260 Casie Aviles: Yeah, it’s going to get embrace stuff.

11 00:01:06.260 00:01:08.460 Amber Lin: updated this morning.

12 00:01:09.460 00:01:10.670 Casie Aviles: Yeah, actually, I used.

13 00:01:10.670 00:01:14.349 Amber Lin: Oh, yay! It took me so much fun, sir.

14 00:01:14.790 00:01:23.469 Casie Aviles: Definitely, it cut the time, although I still have some manual stuff to work on, but it did make it easier, because I don’t have to go through each campaign.

15 00:01:23.470 00:01:25.860 Amber Lin: Yeah, that’s awesome.

16 00:01:26.210 00:01:27.400 Amber Lin: …

17 00:01:27.610 00:01:40.110 Amber Lin: Okay, let’s talk about Google. Are we going with the API, or are we going to… you know, we have… they have a lookup report that already has the data. What are we gonna do?

18 00:01:41.170 00:01:46.799 Casie Aviles: Oh, there’s a looker? I don’t… I haven’t checked the Looker, I’m just checking the snowflake one right now.

19 00:01:49.930 00:01:52.019 Casie Aviles: Yeah, I think there are some…

20 00:01:52.780 00:01:59.910 Casie Aviles: data here that we could definitely use, like, conversion value and cost. Yeah, we could use these.

21 00:02:01.120 00:02:04.070 Casie Aviles: Because this is what I’m manually looking for.

22 00:02:04.270 00:02:05.430 Casie Aviles: But….

23 00:02:05.430 00:02:06.250 Amber Lin: Hmm.

24 00:02:09.699 00:02:12.199 Casie Aviles: Yeah, yeah, we could use these.

25 00:02:13.360 00:02:15.909 Amber Lin: I think that’s…

26 00:02:20.360 00:02:24.769 Amber Lin: Yeah, that one, that… It asked….

27 00:02:27.510 00:02:29.480 Casie Aviles: Oh, this one, this one I haven’t checked.

28 00:02:30.590 00:02:45.570 Amber Lin: Yeah, there’s a… it’s possible to do it from that Looker report, but we don’t have access yet. So, do you think the Snowflake one makes more sense, or would we go with…

29 00:02:46.160 00:02:47.779 Amber Lin: The local report.

30 00:02:50.760 00:02:55.580 Casie Aviles: … I’ll have to check what the Looker one looks like.

31 00:02:57.070 00:02:59.289 Casie Aviles: Sorry, let me just see.

32 00:03:00.390 00:03:08.430 Amber Lin: Okay, let me… Click on Google as a very important.

33 00:03:09.200 00:03:14.290 Amber Lin: Paste it here. We might not have access, I think is what they… what Robert is saying.

34 00:03:14.520 00:03:19.800 Amber Lin: So we… because we’re short on time, we might have to go with… …

35 00:03:22.680 00:03:28.350 Amber Lin: It’s essentially… all the report is, is… Two rows.

36 00:03:28.600 00:03:33.989 Amber Lin: Which is so funny. That’s it for each day.

37 00:03:34.330 00:03:36.260 Casie Aviles: Oh, it’s just two rows.

38 00:03:36.260 00:03:38.700 Amber Lin: Yeah, it’s just like this.

39 00:03:38.810 00:03:43.739 Amber Lin: That’s it. So if you can have it from Snowflake, I think that’s something that we can do.

40 00:03:44.950 00:03:49.329 Casie Aviles: I think my consideration would be if…

41 00:03:49.960 00:03:55.390 Casie Aviles: we could… because I… we still have to look at this, right? But if we’re able to pull it.

42 00:03:57.330 00:04:01.380 Casie Aviles: And then place it anywhere we want, and that should be good.

43 00:04:02.280 00:04:05.699 Casie Aviles: Because if I understand correctly, this local report is just…

44 00:04:06.030 00:04:09.380 Casie Aviles: a view, right? Or is it something we can…

45 00:04:12.520 00:04:15.959 Casie Aviles: I don’t know, like, move around, like, we could download, or we could…

46 00:04:16.850 00:04:18.890 Casie Aviles: Because it looks like it’s just a view.

47 00:04:20.019 00:04:21.029 Amber Lin: Yeah, it could be.

48 00:04:22.019 00:04:23.679 Mustafa Raja: Hey, sorry for joining late.

49 00:04:23.680 00:04:35.340 Amber Lin: Hi! No worries. … So, we’re talking about, the Google Ads side. So, right now.

50 00:04:35.740 00:04:39.080 Amber Lin: we can… I think we can either get it from the…

51 00:04:39.280 00:04:44.120 Amber Lin: from Snowflake, or we can have it

52 00:04:44.240 00:04:58.210 Amber Lin: Robert asked if we can also do it… if there’s another option if we can do it from this Looker report. However, we don’t have access to this Looker report yet, I assume, and…

53 00:04:58.460 00:05:01.649 Amber Lin: So we’re just talking about how we’re gonna do the Google Ads.

54 00:05:04.060 00:05:04.810 Mustafa Raja: Yep.

55 00:05:05.440 00:05:09.370 Mustafa Raja: So how are we getting it from Snowflake, though?

56 00:05:10.080 00:05:11.419 Casie Aviles: We’re using Volatom.

57 00:05:11.620 00:05:12.490 Casie Aviles: For that.

58 00:05:12.630 00:05:13.570 Mustafa Raja: Yeah.

59 00:05:16.120 00:05:17.730 Casie Aviles: I’m just taking a look at the…

60 00:05:18.620 00:05:25.780 Casie Aviles: data, because the benefit of having it in Snowflake would be… we’ll be able to move this around, like, this data.

61 00:05:25.890 00:05:31.330 Casie Aviles: So we’re not You know, we’re not just gonna look at another view or another dashboard.

62 00:05:32.000 00:05:35.990 Casie Aviles: We can actually move it around, like what we are doing with Braze right now.

63 00:05:36.620 00:05:36.970 Amber Lin: Yeah.

64 00:05:36.970 00:05:37.460 Mustafa Raja: Yep.

65 00:05:38.580 00:05:41.749 Amber Lin: Okay. Is it in Snowflake already?

66 00:05:42.750 00:05:47.450 Casie Aviles: I can see that there’s… there are tables, but I’m checking the contents.

67 00:05:53.880 00:06:00.550 Amber Lin: If we have the data we need in Snowflake, how long would it take for us to bring that into a spreadsheet?

68 00:06:01.840 00:06:09.900 Casie Aviles: I think we’ll just use… maybe we could even use N8N, or if not, then….

69 00:06:10.270 00:06:12.539 Amber Lin: We’ll do another dogster.

70 00:06:12.840 00:06:14.050 Casie Aviles: job.

71 00:06:14.510 00:06:22.340 Casie Aviles: So that… that could be… I would say around 2 points, probably, or… yeah.

72 00:06:23.080 00:06:27.529 Amber Lin: Okay. Do you think this is something we can get done by today?

73 00:06:28.480 00:06:29.679 Casie Aviles: For Google.

74 00:06:29.910 00:06:30.530 Amber Lin: Yeah.

75 00:06:32.700 00:06:34.840 Casie Aviles: Yeah, let me check if, …

76 00:06:35.400 00:06:39.340 Casie Aviles: Yeah, I haven’t really… I’m checking right now, like, the contents of the table.

77 00:06:44.810 00:06:47.320 Mustafa Raja: Abish also linked the spreadsheet.

78 00:06:47.820 00:06:49.320 Casie Aviles: Oh, there’s a spreadsheet.

79 00:06:49.480 00:06:53.870 Mustafa Raja: Yeah, … do you want me to pull it over here in the….

80 00:06:53.870 00:06:55.489 Casie Aviles: Yeah, yeah, sure, sure, sure, sure.

81 00:06:55.830 00:06:57.429 Mustafa Raja: Yeah, let me just go through the link.

82 00:07:03.310 00:07:09.179 Mustafa Raja: Yeah, but, but the, spreadsheet doesn’t have any, what’s it called?

83 00:07:09.970 00:07:10.640 Mustafa Raja: ….

84 00:07:10.640 00:07:11.040 Casie Aviles: there’s.

85 00:07:11.040 00:07:11.520 Mustafa Raja: Headers?

86 00:07:12.070 00:07:12.840 Casie Aviles: Go ahead, Eric.

87 00:07:12.840 00:07:18.489 Mustafa Raja: There isn’t any headers, so it’s really, … do you have to guess what it is?

88 00:07:19.270 00:07:20.799 Amber Lin: Interesting.

89 00:07:21.340 00:07:23.480 Amber Lin: Where did you send the….

90 00:07:23.480 00:07:24.690 Mustafa Raja: In the Zoom chat.

91 00:07:25.620 00:07:27.989 Amber Lin: Oh, oh, there we go.

92 00:07:28.640 00:07:29.620 Amber Lin: I see it now.

93 00:07:29.620 00:07:32.060 Mustafa Raja: Avish worked on this.

94 00:07:33.170 00:07:35.820 Mustafa Raja: What is this? Yeah.

95 00:07:37.880 00:07:43.319 Amber Lin: I think he… I think he did a test poll. I remember, I think he tried.

96 00:07:43.320 00:07:44.070 Mustafa Raja: Yeah, too.

97 00:07:44.070 00:07:45.239 Amber Lin: It is Tez from Politics.

98 00:07:45.240 00:07:59.429 Mustafa Raja: So what he said, was that we can pull data from Google Ads, to the Sheets. Now, he wanted to… he wanted, us to see which

99 00:07:59.430 00:08:05.970 Mustafa Raja: Which sort of data, do we want to pull, and if we can pull it through, polyatomic.

100 00:08:10.590 00:08:11.270 Casie Aviles: Yeah.

101 00:08:12.900 00:08:16.059 Amber Lin: What sort of data do we have right now?

102 00:08:17.730 00:08:24.880 Mustafa Raja: I don’t have access to Pultome, or I don’t think it’s snowflake.

103 00:08:26.700 00:08:32.839 Casie Aviles: Yeah, yeah, I’m checking. I can share my screen right now, so you guys can see as well.

104 00:08:33.320 00:08:33.970 Amber Lin: Okay.

105 00:08:34.490 00:08:36.180 Amber Lin: Let me stop sharing.

106 00:08:42.480 00:08:44.919 Casie Aviles: Yeah, it’s just this table.

107 00:08:47.520 00:08:54.759 Mustafa Raja: We just need… we just need cost, … For all campaigns.

108 00:08:56.770 00:08:58.580 Casie Aviles: Oh, all campaigns….

109 00:08:58.580 00:09:02.050 Mustafa Raja: Yeah, all costs for all campaigns.

110 00:09:07.110 00:09:09.440 Mustafa Raja: For the previous things.

111 00:09:11.590 00:09:12.630 Mustafa Raja: complicated.

112 00:09:12.840 00:09:14.980 Mustafa Raja: That’s what the SOPs say.

113 00:09:15.600 00:09:17.559 Casie Aviles: Yeah, it looks like we have…

114 00:09:17.680 00:09:20.250 Casie Aviles: We don’t have a lot of data, there’s a lot of….

115 00:09:20.250 00:09:22.539 Mustafa Raja: Can we… can we search for cost?

116 00:09:23.810 00:09:25.150 Casie Aviles: Yeah, yeah, of course.

117 00:09:25.580 00:09:34.410 Amber Lin: Let me also pull up the SOP to see what data we need to fill in for Google. I think for paid media.

118 00:09:34.530 00:09:37.090 Amber Lin: All we need, really, is the…

119 00:09:37.260 00:09:41.729 Amber Lin: Current year cost and revenue, and previous year cost and revenue.

120 00:09:43.890 00:09:47.369 Amber Lin: There you go. As long as we have those two, I think we’ll be good.

121 00:09:48.330 00:09:49.599 Casie Aviles: Getting the costs.

122 00:09:50.080 00:09:56.920 Mustafa Raja: You see, would this be everything that we are getting from, … polyatomic.

123 00:09:59.390 00:10:03.330 Casie Aviles: Ye… yeah, I think this is, …

124 00:10:04.420 00:10:08.689 Casie Aviles: I haven’t really configured this. I think that’s what Always was asking us.

125 00:10:09.280 00:10:13.380 Casie Aviles: To configure… check the configurations, if it’s… Correct.

126 00:10:13.380 00:10:13.890 Mustafa Raja: Yep.

127 00:10:13.890 00:10:16.010 Casie Aviles: I mean, as far as he knows.

128 00:10:16.460 00:10:20.450 Casie Aviles: We’re able to pull data. Yeah, I haven’t really checked these.

129 00:10:27.220 00:10:31.569 Mustafa Raja: Yeah, looks like there’s a lot, and we can… we should be able to get…

130 00:10:31.830 00:10:33.429 Mustafa Raja: The data we need, right?

131 00:10:36.210 00:10:37.809 Mustafa Raja: Amazingly to look into it.

132 00:10:42.380 00:10:50.109 Amber Lin: Let’s see… There’s a few things that says cost, and a few things that says revenue.

133 00:10:50.600 00:10:51.640 Amber Lin: ….

134 00:10:57.670 00:11:01.979 Casie Aviles: Yeah, I think for revenue, we’re looking at the conversions, then…

135 00:11:02.990 00:11:09.280 Casie Aviles: Yeah, because we’re looking at this conversion val- or purchase sales, but they’re the same value, so….

136 00:11:10.730 00:11:14.309 Casie Aviles: And then we have costs. So this is what we… these are what we want.

137 00:11:23.440 00:11:25.410 Casie Aviles: Metrics, average costs.

138 00:11:34.820 00:11:35.410 Amber Lin: Hmm.

139 00:11:38.630 00:11:39.480 Amber Lin: Hmm.

140 00:11:47.650 00:11:48.840 Amber Lin: -Oh.

141 00:11:59.800 00:12:03.450 Amber Lin: Micro, measurable cost microbes?

142 00:12:04.170 00:12:04.810 Amber Lin: Huh.

143 00:12:04.810 00:12:06.649 Casie Aviles: Yeah, this doesn’t tell us much.

144 00:12:07.430 00:12:08.490 Amber Lin: Yeah.

145 00:12:08.490 00:12:10.760 Casie Aviles: This is the metrics average cost.

146 00:12:11.230 00:12:15.219 Amber Lin: Okay, that’s great. Maybe there’s another…

147 00:12:15.710 00:12:21.940 Amber Lin: Like, conversion value that will come… Up.

148 00:12:25.000 00:12:27.790 Casie Aviles: It should be this, but it’s all zeros.

149 00:12:28.140 00:12:30.000 Casie Aviles: Is this for….

150 00:12:31.800 00:12:33.249 Amber Lin: What day is this?

151 00:12:37.110 00:12:37.940 Casie Aviles: D.

152 00:12:41.030 00:12:43.140 Casie Aviles: We just have a bunch of IDs.

153 00:12:46.240 00:12:48.620 Casie Aviles: Let’s say the date… let’s see the….

154 00:12:49.390 00:12:55.179 Mustafa Raja: Maybe pull date, in configuration if it’s not there.

155 00:12:57.650 00:13:03.360 Casie Aviles: And we have… Where is this segment state? Not sure if this is it, but….

156 00:13:05.660 00:13:06.400 Amber Lin: Hmm.

157 00:13:07.650 00:13:07.970 Casie Aviles: This is true.

158 00:13:08.040 00:13:11.880 Amber Lin: Maybe it is because it’s too early.

159 00:13:12.420 00:13:16.220 Casie Aviles: Yeah, okay, so I think we have to fix the configuration, then.

160 00:13:16.220 00:13:17.050 Mustafa Raja: Yay.

161 00:13:17.050 00:13:18.200 Amber Lin: Yeah, okay.

162 00:13:22.370 00:13:24.779 Casie Aviles: I’m not sure how to set that, though.

163 00:13:26.020 00:13:27.250 Amber Lin: …

164 00:13:29.460 00:13:37.269 Amber Lin: In Snowflake, did we say select all? Then, if that’s the case, did it only show the top 5 report?

165 00:13:37.540 00:13:42.869 Amber Lin: If this is all, then I don’t think we pulled in the data yet.

166 00:13:44.040 00:13:50.590 Casie Aviles: This is just all, I mean, this is not all of it, yeah, this is just a test pool, I pro- I believe.

167 00:13:50.730 00:13:51.640 Amber Lin: Hmm.

168 00:13:51.640 00:13:54.810 Casie Aviles: But, yeah, we’re selecting everything because of this.

169 00:13:55.220 00:13:56.580 Amber Lin: Wow, I see.

170 00:13:56.840 00:14:01.009 Amber Lin: I was thinking if we can select for the most recent, say, August.

171 00:14:01.280 00:14:08.860 Amber Lin: Reports, and then maybe the… it won’t be zero, because I think for 2021, they just got started.

172 00:14:09.000 00:14:12.340 Amber Lin: So they probably wouldn’t have anything.

173 00:14:14.520 00:14:17.430 Casie Aviles: Yeah, oh, we have a lookup period.

174 00:14:30.160 00:14:31.950 Casie Aviles: Yeah, this was just a test.

175 00:14:32.240 00:14:34.530 Amber Lin: And records.

176 00:14:34.860 00:14:35.930 Amber Lin: I see.

177 00:14:37.990 00:14:39.609 Casie Aviles: I’ll save this for now.

178 00:14:39.810 00:14:40.500 Casie Aviles: Damn.

179 00:14:42.660 00:14:46.580 Casie Aviles: Because I think, everything we’ll need is in the campaign performance.

180 00:14:46.730 00:14:51.799 Casie Aviles: And then… I think we can do… this is just a test sync, so I can do…

181 00:14:52.910 00:14:55.979 Casie Aviles: I think we could do a bulk sync.

182 00:14:59.740 00:15:02.590 Casie Aviles: Okay, so we’ll have to wait for this.

183 00:15:02.920 00:15:04.739 Casie Aviles: It’s running a sync, I believe.

184 00:15:06.070 00:15:06.560 Amber Lin: Okay.

185 00:15:06.560 00:15:09.630 Casie Aviles: So I’ll come back to… let’s just come back to this thing.

186 00:15:09.800 00:15:11.270 Amber Lin: Alright, I hear you.

187 00:15:11.650 00:15:21.110 Amber Lin: Okay, … Let’s check on… …

188 00:15:33.210 00:15:40.509 Amber Lin: Yeah, on the ABC side, did you get… did you guys have time to work on that client yesterday?

189 00:15:41.740 00:15:42.569 Mustafa Raja: I was out.

190 00:15:43.090 00:15:47.509 Casie Aviles: I was just triaging… A couple of tickets, ….

191 00:15:48.690 00:15:50.950 Casie Aviles: And did some minor fixes, but….

192 00:15:50.950 00:15:51.380 Amber Lin: Oh!

193 00:15:51.380 00:15:53.880 Casie Aviles: Right now, I’m… Okay, cool.

194 00:15:53.880 00:15:56.279 Mustafa Raja: Yeah, there’s a… yeah, go on.

195 00:15:56.670 00:15:58.840 Casie Aviles: Yeah, right now, I want to work on…

196 00:15:59.340 00:16:03.869 Casie Aviles: the exact wording issue, so I put it in progress.

197 00:16:04.420 00:16:06.839 Amber Lin: Okay. Yeah, I think that’s good.

198 00:16:06.840 00:16:12.529 Mustafa Raja: Yeah, there’s a… there’s a triage, for Patricia’s, feedback.

199 00:16:12.780 00:16:14.429 Mustafa Raja: That I want to talk about.

200 00:16:15.430 00:16:16.400 Amber Lin: Yeah, sure.

201 00:16:17.110 00:16:20.979 Mustafa Raja: … Let me see what ticket it was.

202 00:16:21.480 00:16:23.070 Amber Lin: 659?

203 00:16:23.610 00:16:31.609 Mustafa Raja: Yeah, so, she’s also in… so what’s… what’s happening is, she… she’s mentioned twice in this sheet.

204 00:16:31.870 00:16:37.050 Amber Lin: Oh, you’re right. We have duplicates in the sheet. How can we remove those?

205 00:16:37.490 00:16:50.649 Mustafa Raja: I can just check them manually, and just merge everything, remove the duplicates and convert them to one row. But let me know if this is the correct one, right?

206 00:16:52.650 00:16:57.230 Amber Lin: Yeah, yeah, she’s a trainer, so I would say just give her access to all.

207 00:16:58.500 00:17:09.419 Amber Lin: Okay. I added… I added a column that has a checkbox. I think I’ll check all the ones that are trainers, and then we can just give all access to them.

208 00:17:09.609 00:17:18.540 Amber Lin: I don’t think it covers everybody, but I’ll… I’ll keep adding as I… as people get feedback, say, hey, I don’t have access to this, and we’ll change it.

209 00:17:19.099 00:17:19.899 Mustafa Raja: Monkey.

210 00:17:20.510 00:17:21.119 Amber Lin: Yeah.

211 00:17:22.310 00:17:26.220 Mustafa Raja: Yeah, it’s, that… yeah, it’s only that one. ….

212 00:17:30.220 00:17:37.640 Amber Lin: … Oh, did we manage to normalize the…

213 00:17:38.570 00:17:52.260 Amber Lin: tab in the spreadsheet, I still heard a few… remember we changed something about the age column and the skills and zips? I think we’re still hearing Janiece’s feedback on, oh, one of this is not…

214 00:17:54.570 00:17:58.990 Amber Lin: One of this is not showing, let me try and grab…

215 00:17:59.350 00:18:04.080 Amber Lin: Oh, I have one minute. I’ll grab… their feedback.

216 00:18:04.960 00:18:06.350 Amber Lin: …

217 00:18:20.350 00:18:22.109 Amber Lin: Oh, let me share a screen.

218 00:18:22.450 00:18:26.360 Amber Lin: Here… remember when we did…

219 00:18:26.790 00:18:32.840 Amber Lin: Termite Tech, it’s updated. We updated it for them, and I… And, like…

220 00:18:33.270 00:18:36.569 Amber Lin: I’m not seeing who can do inspections and maintenance visits.

221 00:18:37.110 00:18:38.390 Amber Lin: And then…

222 00:18:43.480 00:18:46.819 Amber Lin: Do you guys know what she’s talk- what they’re talking about?

223 00:18:47.670 00:18:51.540 Mustafa Raja: I can take a look at sheet and see if it makes sense.

224 00:18:51.770 00:18:56.600 Amber Lin: Yeah, I think they’re talking about this special termite licensing, which…

225 00:18:56.710 00:19:09.790 Amber Lin: it’s a tech, but they do inspections, but they’re not an inspector, so inspectors are people who do estimates and sales. I think the service itself is an inspection, and that’s…

226 00:19:09.980 00:19:11.709 Amber Lin: the skills and zips.

227 00:19:12.820 00:19:21.900 Amber Lin: … Don’t… I don’t know. Austin… Column… 8.

228 00:19:28.370 00:19:37.399 Mustafa Raja: If it says Termite Maintenance Service, the, the AI is getting, it has termite maintenance.

229 00:19:37.640 00:19:38.700 Mustafa Raja: ….

230 00:19:40.220 00:19:43.610 Amber Lin: Yeah, I think she needs to… name….

231 00:19:43.610 00:19:47.009 Mustafa Raja: Yeah, yeah. Okay, but is it gonna be reflected? No.

232 00:19:47.010 00:19:48.020 Amber Lin: Okay.

233 00:19:48.020 00:19:51.920 Mustafa Raja: We’ll have to… for now, we’ll have to manually update.

234 00:19:53.320 00:19:54.350 Amber Lin: I see.

235 00:20:06.380 00:20:17.419 Amber Lin: Alright, I’ll go let them know, and if they update it, I’ll message you guys, and then we can change it, but I want them to confirm first, so let’s hold off on that for now.

236 00:20:18.030 00:20:18.860 Amber Lin: Alright.

237 00:20:20.690 00:20:22.530 Amber Lin: Thanks, that’s… that’s all.

238 00:20:23.120 00:20:23.659 Mustafa Raja: Thank you.

239 00:20:23.660 00:20:25.120 Amber Lin: develop, right? Okay.

240 00:20:25.120 00:20:25.970 Casie Aviles: Thank you.

241 00:20:25.970 00:20:26.680 Mustafa Raja: Bye.