Meeting Title: GigRadar Deep Dive Date: 2025-09-12 Meeting participants: Hannah Wang, Ryan Brosas
WEBVTT
1 00:04:31.350 ⇒ 00:04:32.060 Ryan Brosas: Yay.
2 00:04:33.430 ⇒ 00:04:34.280 Hannah Wang: Bye.
3 00:04:36.060 ⇒ 00:04:37.153 Ryan Brosas: Yes,
4 00:04:38.110 ⇒ 00:04:46.240 Hannah Wang: Yeah, sorry, I feel like your mic is a little quiet again. It’s like the same problem we had last time.
5 00:04:48.180 ⇒ 00:04:50.210 Ryan Brosas: Is it okay now?
6 00:04:50.360 ⇒ 00:04:52.109 Hannah Wang: Yes, that’s better.
7 00:04:54.130 ⇒ 00:05:04.630 Hannah Wang: Okay, so I don’t really know how to use GigRadar, so if you share your screen and log in, maybe we can just
8 00:05:04.880 ⇒ 00:05:10.949 Hannah Wang: implement some of the changes that Victor mentioned. I…
9 00:05:11.170 ⇒ 00:05:18.759 Hannah Wang: took some notes, so we can just kind of go over… go over it.
10 00:05:21.850 ⇒ 00:05:22.730 Hannah Wang: But yeah.
11 00:05:28.930 ⇒ 00:05:30.040 Ryan Brosas: apart.
12 00:05:39.930 ⇒ 00:05:41.640 Ryan Brosas: Thank you, please bear.
13 00:05:42.860 ⇒ 00:05:45.110 Ryan Brosas: Nothing, it has to log in.
14 00:06:05.430 ⇒ 00:06:10.889 Ryan Brosas: Just a second. Thank you, God.
15 00:06:20.140 ⇒ 00:06:22.150 Ryan Brosas: Okay, downloading…
16 00:06:27.030 ⇒ 00:06:27.730 Ryan Brosas: Here.
17 00:06:28.650 ⇒ 00:06:29.380 Ryan Brosas: Huh.
18 00:07:30.820 ⇒ 00:07:33.190 Ryan Brosas: So, dashboard…
19 00:07:33.750 ⇒ 00:07:40.640 Hannah Wang: Okay, nice. So, can you help me understand how it works? So, with each scanner.
20 00:07:40.950 ⇒ 00:07:47.890 Hannah Wang: Like, does it apply to all the jobs that… populate that.
21 00:07:48.200 ⇒ 00:07:52.140 Hannah Wang: Are the results of the scanner, or how does it work?
22 00:07:53.290 ⇒ 00:08:02.000 Ryan Brosas: So, if… If they have, like, a specific keyword, am I…
23 00:08:03.140 ⇒ 00:08:09.419 Ryan Brosas: Okay, okay, so if there’s, like, specific keywords, for example, data analytics.
24 00:08:09.420 ⇒ 00:08:09.960 Hannah Wang: Yeah.
25 00:08:09.960 ⇒ 00:08:13.649 Ryan Brosas: It… We’ll potentially, like.
26 00:08:14.050 ⇒ 00:08:23.120 Ryan Brosas: submit a… what do you call these? Proposals? For example, you can see most of it on the sales…
27 00:08:23.400 ⇒ 00:08:25.320 Ryan Brosas: Notification…
28 00:08:26.090 ⇒ 00:08:29.849 Ryan Brosas: For example, here, data scientist, competitive.
29 00:08:30.090 ⇒ 00:08:34.250 Ryan Brosas: This is the scanner,
30 00:08:41.360 ⇒ 00:08:42.629 Ryan Brosas: Yeah, it’s sucked.
31 00:08:42.919 ⇒ 00:08:50.830 Ryan Brosas: So, it’s not… Pushing on that. So, yeah, for example, the last, here is the last one.
32 00:08:50.940 ⇒ 00:08:57.490 Ryan Brosas: That, we submitted via… with, with, with Robert’s account.
33 00:08:57.960 ⇒ 00:09:09.150 Ryan Brosas: So, so, as we include a data set… data analytics, so I think the…
34 00:09:10.390 ⇒ 00:09:17.270 Ryan Brosas: Yeah, data anal… data mining analysis, so I think… it…
35 00:09:18.640 ⇒ 00:09:23.720 Ryan Brosas: Proceeded to submit a, what do you call this, proposal.
36 00:09:24.370 ⇒ 00:09:29.340 Ryan Brosas: Or, so, the proposal has been sent.
37 00:09:29.590 ⇒ 00:09:37.849 Ryan Brosas: And, yeah, I think that’s pretty much it. If it’s, like, on our scanner’s keyword, if it’s fit.
38 00:09:38.210 ⇒ 00:09:51.540 Ryan Brosas: They will automatically, submit a proposal that is specifically on what we… what… where is that?
39 00:09:52.970 ⇒ 00:09:59.620 Ryan Brosas: Yeah, we’ve set, like, for example, like, for these…
40 00:09:59.770 ⇒ 00:10:06.449 Ryan Brosas: And if you want to set, like, a specific budget, or… A specific rating.
41 00:10:06.640 ⇒ 00:10:08.859 Ryan Brosas: It will only follow that.
42 00:10:08.990 ⇒ 00:10:13.680 Ryan Brosas: But here, it’s pretty much more on… Keywords.
43 00:10:15.090 ⇒ 00:10:17.260 Hannah Wang: So it applies to every job.
44 00:10:17.450 ⇒ 00:10:21.579 Hannah Wang: That appears here, like, in the results? Yes. Okay.
45 00:10:22.140 ⇒ 00:10:23.510 Hannah Wang: Yes. For example, this system.
46 00:10:23.510 ⇒ 00:10:24.919 Ryan Brosas: data analytics.
47 00:10:24.920 ⇒ 00:10:25.410 Hannah Wang: Yeah.
48 00:10:25.410 ⇒ 00:10:32.870 Ryan Brosas: then, it will also, like, expand to amplitude, mixed panel, pulseHub.
49 00:10:33.620 ⇒ 00:10:53.309 Ryan Brosas: And I think, the… what do you call this? The degrader team, or the guy that hopped on the call with us, did an amazing job of, like, setting up, so there’s, like, a lot… a less of, like, other stuff here, like marketing.
50 00:10:53.530 ⇒ 00:11:07.049 Ryan Brosas: Because, if, like, from previous, there’s, like, writer and other positions that is not aligned to what we’re trying to, we’re trying to target, so…
51 00:11:07.250 ⇒ 00:11:12.650 Ryan Brosas: I think that’s really good. And, for example, like this, this is something that…
52 00:11:14.070 ⇒ 00:11:21.580 Ryan Brosas: is not aligned, I guess, on our… Yeah. I’m not sure what is this, but, like.
53 00:11:22.420 ⇒ 00:11:25.099 Ryan Brosas: This is something that will be, like.
54 00:11:25.910 ⇒ 00:11:31.750 Ryan Brosas: a normal occurrence, I guess, on their scanner, because we are targeting amplitude.
55 00:11:31.920 ⇒ 00:11:37.130 Hannah Wang: I think we need to get rid of these keywords, probably. Like, electrical engineering.
56 00:11:37.830 ⇒ 00:11:43.180 Ryan Brosas: Yeah, I think, yes, for that particular part. Like, engineering…
57 00:11:43.710 ⇒ 00:11:44.320 Hannah Wang: I think…
58 00:11:44.320 ⇒ 00:11:50.840 Ryan Brosas: That’s, that’s, that’s… Hitting that also. So…
59 00:11:50.840 ⇒ 00:11:55.850 Hannah Wang: Can you get rid of, yeah, the keyword, electrical, or something?
60 00:11:56.480 ⇒ 00:11:57.820 Ryan Brosas: All that funny.
61 00:11:58.200 ⇒ 00:12:01.590 Hannah Wang: Or,
62 00:12:12.800 ⇒ 00:12:17.960 Hannah Wang: Yeah… so is that going to… oh, okay, cool. It’s redoing it.
63 00:12:18.320 ⇒ 00:12:19.075 Hannah Wang: Oh…
64 00:12:20.660 ⇒ 00:12:27.270 Ryan Brosas: Okay, so it removes… I hope that, it also includes on the tag, because, yeah, it’s not…
65 00:12:27.270 ⇒ 00:12:28.270 Hannah Wang: Oh, okay.
66 00:12:28.270 ⇒ 00:12:38.130 Ryan Brosas: It’s not, doing the type. But yeah, I think we can request, like, a specific job category for engineering, because it’s…
67 00:12:38.970 ⇒ 00:12:42.219 Ryan Brosas: It’s kind of like…
68 00:12:43.370 ⇒ 00:12:44.010 Hannah Wang: Hardware.
69 00:12:44.010 ⇒ 00:12:54.300 Ryan Brosas: Pulling, pulling all, including the hardware and the other, like, Spectrum of, like, engineering that On the other lecture.
70 00:12:55.400 ⇒ 00:12:57.470 Ryan Brosas: Yeah, so…
71 00:12:57.470 ⇒ 00:13:04.530 Hannah Wang: Do we wanna, like… Ask Victor to help us filter stuff even more.
72 00:13:04.650 ⇒ 00:13:06.580 Hannah Wang: Like, I remember he said if we…
73 00:13:07.300 ⇒ 00:13:15.120 Hannah Wang: Like, with a scanner, send him, like, the jobs that it’s populating, and then tell him, like, oh, we don’t want this, like, maybe he can help us.
74 00:13:16.440 ⇒ 00:13:21.809 Ryan Brosas: Yeah, I think… Can be our,
75 00:13:21.910 ⇒ 00:13:24.150 Ryan Brosas: That… we can do that also.
76 00:13:24.650 ⇒ 00:13:31.500 Ryan Brosas: Yeah, so… Okay, so…
77 00:13:31.500 ⇒ 00:13:35.559 Hannah Wang: Yeah, let me make a notion, Doc, of…
78 00:13:36.450 ⇒ 00:13:39.849 Hannah Wang: Stuff that we want to ask.
79 00:13:40.720 ⇒ 00:13:44.240 Hannah Wang: help for. So gig radar…
80 00:13:44.870 ⇒ 00:13:50.989 Hannah Wang: I’m just gonna… so, in the U.S.-only amplitude…
81 00:13:52.300 ⇒ 00:13:56.050 Hannah Wang: Scanner… or I guess we can get rid of electronics.
82 00:13:56.890 ⇒ 00:13:57.910 Hannah Wang: Yeah.
83 00:13:59.350 ⇒ 00:14:00.340 Hannah Wang: Okay.
84 00:14:04.390 ⇒ 00:14:05.890 Ryan Brosas: 2 to 6…
85 00:14:12.360 ⇒ 00:14:14.790 Hannah Wang: Okay, that worked, I think.
86 00:14:15.590 ⇒ 00:14:26.299 Ryan Brosas: Yeah, I did this manually before, so I spent, like, a whole day just putting keywords, but yeah, there will always be, like, something like this.
87 00:14:26.300 ⇒ 00:14:27.120 Hannah Wang: Okay.
88 00:14:28.280 ⇒ 00:14:31.690 Hannah Wang: Is… do you know if this is case sensitive?
89 00:14:33.500 ⇒ 00:14:36.659 Ryan Brosas: It’s not, okay, it’s not. I don’t think so.
90 00:14:36.660 ⇒ 00:14:37.660 Hannah Wang: Yeah, it’s not.
91 00:14:38.000 ⇒ 00:14:38.730 Hannah Wang: Oops.
92 00:14:40.350 ⇒ 00:14:42.970 Hannah Wang: Yeah, it’s not case sensitive.
93 00:14:43.420 ⇒ 00:14:53.430 Hannah Wang: Okay, I feel like this scanner’s fine, and then I know he created, like, a no…
94 00:14:54.340 ⇒ 00:14:56.719 Hannah Wang: Divorce analyst, interesting.
95 00:15:13.750 ⇒ 00:15:16.770 Hannah Wang: Do you need to put it in quotes?
96 00:15:17.730 ⇒ 00:15:25.920 Ryan Brosas: Yeah, so, I, for, for, for this, you just need to add comma.
97 00:15:27.320 ⇒ 00:15:30.000 Hannah Wang: Or, like, if it’s two words…
98 00:15:30.480 ⇒ 00:15:32.450 Hannah Wang: Do we need to put it in quotes?
99 00:15:37.190 ⇒ 00:15:44.480 Ryan Brosas: I’m not sure, but… I just put this as… As it is.
100 00:15:47.440 ⇒ 00:15:50.410 Ryan Brosas: But you can just add that.
101 00:15:50.960 ⇒ 00:15:51.640 Ryan Brosas: calm.
102 00:16:04.270 ⇒ 00:16:06.449 Hannah Wang: Oh, you’re missing one right here. Oh.
103 00:16:06.780 ⇒ 00:16:07.800 Hannah Wang: Right here.
104 00:16:11.150 ⇒ 00:16:11.890 Hannah Wang: Oops.
105 00:16:27.110 ⇒ 00:16:28.310 Ryan Brosas: Oh…
106 00:16:49.150 ⇒ 00:16:58.920 Ryan Brosas: And, yeah, yes… 137… Boom.
107 00:17:02.430 ⇒ 00:17:05.079 Ryan Brosas: Can add a writer for that.
108 00:17:05.540 ⇒ 00:17:10.470 Ryan Brosas: Yeah, I think this is, like, a continuous reiteration, so.
109 00:17:11.900 ⇒ 00:17:16.350 Hannah Wang: That’s fine. I feel like maybe we can add, like, the no,
110 00:17:17.060 ⇒ 00:17:24.799 Hannah Wang: Like, I know he created the second filter here on the left about no budget. Like, do you think that’s worth putting into?
111 00:17:26.780 ⇒ 00:17:29.160 Hannah Wang: Like, turning it on, basically.
112 00:17:30.540 ⇒ 00:17:31.320 Ryan Brosas: Hmm.
113 00:17:31.320 ⇒ 00:17:34.100 Hannah Wang: Filtering clients, yeah.
114 00:17:36.330 ⇒ 00:17:39.999 Ryan Brosas: Yeah, I think we can, we can add that.
115 00:17:42.680 ⇒ 00:17:45.510 Hannah Wang: But I don’t really know what our rate is.
116 00:17:47.890 ⇒ 00:17:58.399 Ryan Brosas: Yeah, so… I’m not sure. So, we can base that on our previous trade…
117 00:18:00.330 ⇒ 00:18:02.100 Hannah Wang: Oh, yeah, good idea.
118 00:18:03.550 ⇒ 00:18:04.869 Ryan Brosas: Is it quite soon.
119 00:18:07.560 ⇒ 00:18:14.489 Ryan Brosas: Or… It doesn’t have… Let me look at Robert’s account.
120 00:18:31.080 ⇒ 00:18:35.360 Hannah Wang: Robert has 120 an hour.
121 00:18:36.390 ⇒ 00:18:37.710 Ryan Brosas: One, thank you.
122 00:18:45.760 ⇒ 00:18:51.339 Hannah Wang: Or one of them is 120, one of them is 150, so I don’t… I don’t know.
123 00:18:59.920 ⇒ 00:19:02.360 Ryan Brosas: 12315…
124 00:19:06.670 ⇒ 00:19:11.650 Hannah Wang: Or I feel like Max is okay. We don’t need to have a max.
125 00:19:12.560 ⇒ 00:19:13.980 Ryan Brosas: Oh, we don’t have… okay.
126 00:19:14.590 ⇒ 00:19:17.270 Hannah Wang: I don’t… I don’t think we have a max. It’s fine.
127 00:19:20.370 ⇒ 00:19:21.980 Ryan Brosas: I’m sorry, that’s not good.
128 00:19:22.750 ⇒ 00:19:23.400 Hannah Wang: Or…
129 00:19:26.880 ⇒ 00:19:29.930 Hannah Wang: You can just have a minimum of 120, that’s fine.
130 00:19:32.600 ⇒ 00:19:40.710 Ryan Brosas: Yep. We got, like, 0 to 1 for no budget.
131 00:19:43.040 ⇒ 00:19:49.499 Ryan Brosas: 7 months ago… 5 months ago, 2 months ago, 16 months ago.
132 00:19:49.500 ⇒ 00:19:51.040 Hannah Wang: 15 days ago.
133 00:19:54.580 ⇒ 00:20:00.359 Hannah Wang: So, like, if we turn this on, is it going to apply to all of these, or is it…
134 00:20:01.750 ⇒ 00:20:04.689 Hannah Wang: The new one comes in, it’ll apply to the new one.
135 00:20:05.160 ⇒ 00:20:07.879 Ryan Brosas: Yes, I think that would be… the…
136 00:20:08.550 ⇒ 00:20:16.720 Ryan Brosas: it would be doing, so the new one, a new, what do you call this? Job pools, I guess, would be…
137 00:20:16.720 ⇒ 00:20:17.660 Hannah Wang: Okay.
138 00:20:18.790 ⇒ 00:20:24.720 Ryan Brosas: Let’s check here… So…
139 00:20:24.900 ⇒ 00:20:31.089 Ryan Brosas: This is for Robert, so it has, like, a fiscal start.
140 00:20:34.410 ⇒ 00:20:38.090 Hannah Wang: I changed the cover letter. It’s too long.
141 00:20:38.310 ⇒ 00:20:39.060 Ryan Brosas: Hmm.
142 00:20:39.740 ⇒ 00:20:44.390 Ryan Brosas: We can… Get, like, one instead?
143 00:20:44.390 ⇒ 00:20:49.800 Hannah Wang: Yeah, just include, backplits.
144 00:20:52.470 ⇒ 00:20:55.270 Hannah Wang: And then sample win instead of wins.
145 00:20:58.870 ⇒ 00:21:03.680 Hannah Wang: And then…
146 00:21:08.950 ⇒ 00:21:10.630 Ryan Brosas: Should we…
147 00:21:10.630 ⇒ 00:21:13.470 Hannah Wang: You can remove that, it’s fine. Remove it.
148 00:21:13.890 ⇒ 00:21:19.410 Hannah Wang: And then… I think the recommendation is fine.
149 00:21:24.290 ⇒ 00:21:26.540 Hannah Wang: Identify the…
150 00:21:31.340 ⇒ 00:21:34.649 Hannah Wang: Is there any specific phrase up there to include?
151 00:21:49.930 ⇒ 00:21:53.660 Hannah Wang: My job depends on it. That’s funny.
152 00:21:53.790 ⇒ 00:21:57.079 Hannah Wang: Right here.
153 00:21:57.810 ⇒ 00:21:59.089 Ryan Brosas: It’s.
154 00:21:59.090 ⇒ 00:22:00.329 Hannah Wang: It’s a prompt, yeah.
155 00:22:00.330 ⇒ 00:22:01.230 Ryan Brosas: Yeah.
156 00:22:01.230 ⇒ 00:22:08.509 Hannah Wang: How about we make it one sentence?
157 00:22:09.090 ⇒ 00:22:10.360 Hannah Wang: Instead of 2?
158 00:22:11.120 ⇒ 00:22:12.709 Ryan Brosas: One sentence long…
159 00:22:18.380 ⇒ 00:22:22.710 Hannah Wang: I think that’s… Fine.
160 00:22:24.710 ⇒ 00:22:27.070 Hannah Wang: Let me see the example he gave.
161 00:22:28.180 ⇒ 00:22:32.220 Ryan Brosas: Should we, we already mentioned…
162 00:22:32.450 ⇒ 00:22:33.520 Hannah Wang: That’s true.
163 00:22:33.770 ⇒ 00:22:39.680 Ryan Brosas: then… We mentioned this top here.
164 00:22:39.870 ⇒ 00:22:49.470 Ryan Brosas: But… I’m not sure, but this is already, like, obvious that we have… we are implementing this stuff.
165 00:22:49.470 ⇒ 00:22:49.870 Hannah Wang: Right.
166 00:22:49.870 ⇒ 00:22:54.970 Ryan Brosas: So, should we… Mentioned this on a cover letter.
167 00:22:58.420 ⇒ 00:23:00.929 Hannah Wang: I think you can delete it, yeah.
168 00:23:08.200 ⇒ 00:23:14.160 Ryan Brosas: I think it’s just to start working down on how… Oh…
169 00:23:23.750 ⇒ 00:23:28.310 Ryan Brosas: And you’ll already, like, mention here, I don’t know, ticks function.
170 00:23:28.470 ⇒ 00:23:30.059 Ryan Brosas: So yeah, I think that’s fine.
171 00:23:31.920 ⇒ 00:23:43.309 Hannah Wang: Okay, we’ll just see how, like, for our future one that it applies to, let’s just see how long it is, and then if it’s still too long, we can shorten it more, but I think this is good for now.
172 00:23:43.980 ⇒ 00:23:44.650 Ryan Brosas: Nothing.
173 00:23:44.650 ⇒ 00:23:47.210 Hannah Wang: So, I feel like you’re gonna need a copy-paste
174 00:23:47.990 ⇒ 00:23:50.809 Hannah Wang: it into the other scanners, or, like.
175 00:23:51.390 ⇒ 00:23:54.230 Hannah Wang: Yeah, we have to modify the other scanners, too.
176 00:23:55.350 ⇒ 00:23:56.339 Ryan Brosas: Yeah, -oh.
177 00:24:04.560 ⇒ 00:24:07.060 Ryan Brosas: So… 18…
178 00:24:19.660 ⇒ 00:24:22.420 Ryan Brosas: I should… Yeah, I think that’s fine.
179 00:24:22.880 ⇒ 00:24:30.020 Ryan Brosas: She said something about… Profiles of, Robert…
180 00:24:30.020 ⇒ 00:24:33.449 Hannah Wang: This one? This section? Are you talking about that?
181 00:24:33.450 ⇒ 00:24:44.410 Ryan Brosas: Yeah, the other, the other profile that he has, like, the data visuals, visualization, like, adding, like, tool…
182 00:24:44.830 ⇒ 00:24:47.589 Ryan Brosas: I, I mean, the tools on the…
183 00:24:47.970 ⇒ 00:24:56.029 Ryan Brosas: what do you call this? Cover, or… On his profile.
184 00:24:56.460 ⇒ 00:25:02.050 Hannah Wang: I have, I have Robert’s profile pulled up, so I can share my screen and we can look at it.
185 00:25:02.180 ⇒ 00:25:05.400 Hannah Wang: Because that’s, boutons. So I will…
186 00:25:06.130 ⇒ 00:25:06.760 Ryan Brosas: Okay.
187 00:25:06.980 ⇒ 00:25:08.880 Hannah Wang: I will share my screen.
188 00:25:09.750 ⇒ 00:25:12.460 Hannah Wang: I think we can both share at the same time, it’s okay.
189 00:25:13.170 ⇒ 00:25:16.790 Hannah Wang: Okay, do you see my screen?
190 00:25:18.560 ⇒ 00:25:19.450 Ryan Brosas: Yeah.
191 00:25:19.950 ⇒ 00:25:22.879 Hannah Wang: Okay, so I know he mentioned…
192 00:25:23.850 ⇒ 00:25:30.989 Hannah Wang: So he talked about, like, the job stuff, and then, like, within each profile, adding
193 00:25:31.230 ⇒ 00:25:36.650 Hannah Wang: the job, so I already did that, like, because before this was 13 or something. This was, like.
194 00:25:37.270 ⇒ 00:25:47.239 Hannah Wang: funny, so I just, like, selected all the projects in the profile to show up so that we get more
195 00:25:47.370 ⇒ 00:25:54.750 Hannah Wang: jobs. Like, each profile has the same number of jobs as the total number of jobs, so I already did that.
196 00:25:54.940 ⇒ 00:25:58.090 Hannah Wang: And then…
197 00:25:59.890 ⇒ 00:26:03.940 Ryan Brosas: Yeah, I think, that’s good enough.
198 00:26:03.940 ⇒ 00:26:09.935 Hannah Wang: Yeah, and then I remember he said something about…
199 00:26:14.890 ⇒ 00:26:23.800 Hannah Wang: Forgot, like, in the… if you go back to your screen, like, the match, the percentage match thing, and adding, like, keywords.
200 00:26:24.310 ⇒ 00:26:25.020 Hannah Wang: Even if it’.
201 00:26:25.020 ⇒ 00:26:25.730 Ryan Brosas: Yeah.
202 00:26:25.730 ⇒ 00:26:26.790 Hannah Wang: Relevant.
203 00:26:28.050 ⇒ 00:26:37.760 Ryan Brosas: for example, for Tom, we need to add, like, a… like, I’m… Adobe Illustrator? Something?
204 00:26:37.760 ⇒ 00:26:38.370 Hannah Wang: Oh, yeah.
205 00:26:39.020 ⇒ 00:26:47.640 Hannah Wang: I don’t really know about… I don’t really know if we should do that, but maybe, like, yeah, adding machine learning, or to… yeah, so let’s do that right now.
206 00:26:48.950 ⇒ 00:27:00.549 Hannah Wang: because I think Utam kind of gave up on his profile, and so we’re using Robert’s mostly. But we need to add a bunch of AI stuff to Utam’s stuff, so…
207 00:27:04.100 ⇒ 00:27:04.600 Ryan Brosas: Yeah.
208 00:27:04.600 ⇒ 00:27:07.390 Hannah Wang: I don’t know where we do that, but…
209 00:27:09.220 ⇒ 00:27:11.880 Ryan Brosas: Your AI integration…
210 00:27:22.940 ⇒ 00:27:30.470 Hannah Wang: Yeah, a lot of these are, for data, but I think right now, UTAM is AI, and Robert is data, so…
211 00:27:56.930 ⇒ 00:27:59.669 Hannah Wang: Okay, so machine learning…
212 00:28:52.010 ⇒ 00:28:53.419 Ryan Brosas: Oh, is that correct?
213 00:28:54.760 ⇒ 00:28:56.200 Hannah Wang: With an A, yeah.
214 00:28:59.980 ⇒ 00:29:00.889 Ryan Brosas: Yes, please.
215 00:29:19.580 ⇒ 00:29:21.649 Ryan Brosas: Just, this, just compliance.
216 00:29:38.710 ⇒ 00:29:39.930 Hannah Wang: Okay, cool.
217 00:29:41.110 ⇒ 00:29:43.320 Hannah Wang: Did you want to uncheck Python?
218 00:29:46.470 ⇒ 00:29:47.559 Ryan Brosas: Hi, it’s here.
219 00:29:47.560 ⇒ 00:29:48.940 Hannah Wang: Oh, it’s there, okay.
220 00:29:54.380 ⇒ 00:29:58.150 Ryan Brosas: It’s this, real time… And it was not brutal fun.
221 00:30:02.270 ⇒ 00:30:03.820 Ryan Brosas: Oh, thanks.
222 00:30:03.820 ⇒ 00:30:09.029 Hannah Wang: Is that for, Robert’s account, though? The GigRadar percentage?
223 00:30:09.550 ⇒ 00:30:12.730 Hannah Wang: Or how do we… Oh, Tom, okay.
224 00:30:12.730 ⇒ 00:30:13.520 Ryan Brosas: restaurants.
225 00:30:18.380 ⇒ 00:30:19.540 Ryan Brosas: Hmm, yeah.
226 00:30:20.230 ⇒ 00:30:27.240 Hannah Wang: It’s probably not real time, or it’ll take a while. Yeah. The last sync was 10 hours ago, it says.
227 00:30:28.400 ⇒ 00:30:31.250 Ryan Brosas: Okay, so… Yeah.
228 00:30:32.510 ⇒ 00:30:38.390 Ryan Brosas: So, I think that’s… for Bhutam’s account.
229 00:30:38.570 ⇒ 00:30:49.810 Ryan Brosas: Then we can, apply the same stuff on… The scanner here… Oh, the cover letter?
230 00:30:50.170 ⇒ 00:30:50.770 Ryan Brosas: Yeah.
231 00:30:51.080 ⇒ 00:30:54.470 Hannah Wang: Yeah, how about you keep ABC?
232 00:30:56.390 ⇒ 00:30:58.560 Hannah Wang: And then change to sample VIN.
233 00:30:58.700 ⇒ 00:30:59.970 Hannah Wang: Level wins.
234 00:31:04.930 ⇒ 00:31:06.570 Hannah Wang: One sentence…
235 00:31:33.880 ⇒ 00:31:40.669 Hannah Wang: How about, for companies in legal, healthcare, e-com, and real estate, I’ve saved teams.
236 00:31:41.190 ⇒ 00:31:46.219 Hannah Wang: So you can get rid of all the co… like, that’s obvious that we’re gonna do that.
237 00:31:51.920 ⇒ 00:31:56.360 Hannah Wang: And then, can you add a D after save? Saved? I have saved.
238 00:31:57.650 ⇒ 00:31:58.440 Hannah Wang: Yeah.
239 00:31:59.240 ⇒ 00:32:02.160 Hannah Wang: An unlocked. Past tense, unlocked.
240 00:32:09.200 ⇒ 00:32:10.600 Hannah Wang: Whoa.
241 00:32:11.120 ⇒ 00:32:12.949 Hannah Wang: Write a personal greeting.
242 00:32:18.930 ⇒ 00:32:21.000 Hannah Wang: I think that’s fine to keep.
243 00:32:32.450 ⇒ 00:32:36.020 Hannah Wang: Okay, I think that’s okay. What do you think?
244 00:32:37.560 ⇒ 00:32:43.890 Ryan Brosas: Yeah, I think that’s fine. We chopped down, a lot of, like,
245 00:32:44.280 ⇒ 00:32:58.239 Ryan Brosas: sentences here, so it’s not… so it’s, I think it will be much more better when, when, what’s called this employer, or when they see our proposal.
246 00:32:58.490 ⇒ 00:33:01.109 Ryan Brosas: It will much be better, because we…
247 00:33:02.770 ⇒ 00:33:04.100 Hannah Wang: Jump down the load.
248 00:33:07.480 ⇒ 00:33:09.390 Hannah Wang: Okay, oops.
249 00:33:19.250 ⇒ 00:33:20.710 Ryan Brosas: Okay, so…
250 00:33:21.250 ⇒ 00:33:26.449 Hannah Wang: I know, utom changed the verification.
251 00:33:26.830 ⇒ 00:33:36.110 Hannah Wang: Cause that… I don’t know if you looked at the email thread, but… It was saying… That…
252 00:33:41.980 ⇒ 00:33:44.860 Ryan Brosas: I think he’s… he already verified…
253 00:33:44.860 ⇒ 00:33:46.910 Hannah Wang: Yeah, his account. Yeah.
254 00:33:47.700 ⇒ 00:33:56.590 Hannah Wang: So, he verified it on the 9th, so we haven’t applied to a job since then, so we don’t know if it’s working or not.
255 00:33:58.590 ⇒ 00:34:05.230 Ryan Brosas: Yeah, let me check here… I can start this…
256 00:34:07.720 ⇒ 00:34:10.310 Ryan Brosas: I’ll… well, it’s already start.
257 00:34:10.670 ⇒ 00:34:14.559 Ryan Brosas: So, I’m not sure why it’s not…
258 00:34:15.719 ⇒ 00:34:18.700 Hannah Wang: Can you check the results? Yeah.
259 00:34:19.150 ⇒ 00:34:19.830 Hannah Wang: Four days.
260 00:34:19.830 ⇒ 00:34:20.580 Ryan Brosas: to collect it.
261 00:34:20.580 ⇒ 00:34:21.520 Hannah Wang: ago.
262 00:34:22.090 ⇒ 00:34:25.649 Ryan Brosas: We have, like, 111 sold here.
263 00:34:25.659 ⇒ 00:34:30.959 Hannah Wang: I feel like we already applied… we applied to it 4 days ago, right? Can you check?
264 00:34:40.860 ⇒ 00:34:44.370 Ryan Brosas: It’s all… Robert.
265 00:34:48.949 ⇒ 00:34:54.969 Hannah Wang: Oh, but, like, the screen that you showed me before, where we were seeing all the error messages, I think…
266 00:34:54.969 ⇒ 00:34:55.289 Ryan Brosas: EM.
267 00:34:55.290 ⇒ 00:34:55.800 Hannah Wang: Yes.
268 00:34:56.250 ⇒ 00:35:01.359 Hannah Wang: So go back to that to see if we applied to the latest job, and…
269 00:35:01.820 ⇒ 00:35:09.060 Hannah Wang: Because that was 4 days ago, that was before he verified his account. So, we just didn’t have a job coming.
270 00:35:09.470 ⇒ 00:35:11.760 Hannah Wang: Yeah, we applied to that one, I think.
271 00:35:13.600 ⇒ 00:35:18.300 Hannah Wang: Yeah, right. AI Engineer Insert Media Platform. That was the…
272 00:35:18.860 ⇒ 00:35:21.979 Hannah Wang: First one on the list of results.
273 00:36:04.500 ⇒ 00:36:13.120 Hannah Wang: Is there any way we can increase the number of results by adding more keywords, or do you think we should just leave it for now?
274 00:36:14.650 ⇒ 00:36:15.930 Ryan Brosas: Or, Otam.
275 00:36:15.930 ⇒ 00:36:16.440 Hannah Wang: Yeah.
276 00:36:16.440 ⇒ 00:36:25.059 Ryan Brosas: So… Yeah, that’s AI ChatGPT…
277 00:36:27.180 ⇒ 00:36:27.780 Hannah Wang: like…
278 00:36:28.110 ⇒ 00:36:36.910 Hannah Wang: I forget… do we have to add, like, the asterisk? I’m forgetting what the terminology is, but I know asterisk does, like, a match…
279 00:36:37.390 ⇒ 00:36:42.410 Hannah Wang: like, it’s, oh, I forgot. It’s like a coding thing.
280 00:36:43.450 ⇒ 00:36:46.190 Ryan Brosas: Here, at the… for example, here.
281 00:36:46.920 ⇒ 00:36:54.650 Hannah Wang: Yeah, I’m forgetting what that does, though. Like, I know it’s a string… something.
282 00:36:59.240 ⇒ 00:37:03.969 Ryan Brosas: You can add other, framework, like N8N.
283 00:37:04.670 ⇒ 00:37:07.190 Hannah Wang: Oh, okay, yeah. Rag.
284 00:37:08.530 ⇒ 00:37:10.680 Ryan Brosas: I think that’s…
285 00:37:13.710 ⇒ 00:37:19.610 Ryan Brosas: Then… Nothing else?
286 00:37:20.140 ⇒ 00:37:22.479 Ryan Brosas: Yeah, Brad, that is good.
287 00:37:23.950 ⇒ 00:37:25.150 Ryan Brosas: Yes.
288 00:37:34.160 ⇒ 00:37:35.520 Ryan Brosas: And…
289 00:37:41.120 ⇒ 00:37:42.540 Ryan Brosas: Oh, I think…
290 00:37:48.990 ⇒ 00:37:50.780 Ryan Brosas: What else?
291 00:37:53.110 ⇒ 00:37:57.240 Ryan Brosas: What did you say on his…
292 00:38:00.470 ⇒ 00:38:01.740 Ryan Brosas: Fangqing.
293 00:38:02.410 ⇒ 00:38:03.880 Hannah Wang: Oh yeah, land chain.
294 00:38:27.880 ⇒ 00:38:29.300 Ryan Brosas: Yeah, it’s not increasing.
295 00:38:29.510 ⇒ 00:38:32.050 Hannah Wang: Okay, that’s fine.
296 00:38:40.680 ⇒ 00:38:42.390 Ryan Brosas: Okay…
297 00:38:51.510 ⇒ 00:38:54.420 Hannah Wang: Do you… can you go to the end of that search?
298 00:38:56.330 ⇒ 00:39:00.070 Hannah Wang: Do we need to add a parentheses? Like, a closing parentheses?
299 00:39:07.720 ⇒ 00:39:13.820 Hannah Wang: Like, get rid of the… That character, and just… yeah.
300 00:39:16.140 ⇒ 00:39:21.890 Hannah Wang: I mean, I don’t know if that’ll change anything, but it’s just because it begins with a parentheses, so…
301 00:39:23.890 ⇒ 00:39:25.260 Hannah Wang: You wanna close it.
302 00:39:28.000 ⇒ 00:39:29.750 Ryan Brosas: Didn’t add anything.
303 00:39:30.370 ⇒ 00:39:33.640 Ryan Brosas: I guess we can just put, like…
304 00:39:35.510 ⇒ 00:39:42.500 Ryan Brosas: another, scanner that is focusing on this tree framework.
305 00:39:42.690 ⇒ 00:39:46.880 Ryan Brosas: That we are, or, well, just, like, this too.
306 00:39:47.360 ⇒ 00:39:52.489 Ryan Brosas: And check what else framework they’re currently using, if it’s, like.
307 00:39:52.680 ⇒ 00:40:02.110 Ryan Brosas: pedantic or other AI frameworks that they are currently using on product… in production, so I will be asking
308 00:40:02.290 ⇒ 00:40:05.140 Ryan Brosas: Key supports, and.
309 00:40:05.360 ⇒ 00:40:10.489 Hannah Wang: Okay. I mean, I kind of know the tools they use already, because I make the case studies.
310 00:40:10.660 ⇒ 00:40:21.290 Hannah Wang: So, it’s like… NAN, Brain Trust, claude.
311 00:40:21.570 ⇒ 00:40:26.789 Hannah Wang: But yeah, maybe ask Casey what other tools they use, because I don’t know everything.
312 00:40:27.310 ⇒ 00:40:32.160 Hannah Wang: Yeah, I think that’s a good idea.
313 00:40:43.060 ⇒ 00:40:52.280 Ryan Brosas: Yeah, yeah, we can, we can, do another scanner, or I can experiment over the weekend, I think I can, like.
314 00:40:52.590 ⇒ 00:40:58.300 Ryan Brosas: Devote an hour, so… I can present this, on Monday.
315 00:40:59.080 ⇒ 00:41:01.190 Hannah Wang: Okay. Over the meeting.
316 00:41:02.280 ⇒ 00:41:13.700 Hannah Wang: Okay, do you wanna make a… No budget scanner for… this, too.
317 00:41:13.700 ⇒ 00:41:14.200 Ryan Brosas: mute.
318 00:41:14.850 ⇒ 00:41:21.890 Ryan Brosas: Like, sure, let’s… let’s… Make one… purpose.
319 00:41:40.160 ⇒ 00:41:40.729 Ryan Brosas: Oh, what?
320 00:41:40.730 ⇒ 00:41:42.030 Hannah Wang: We do 120?
321 00:41:44.400 ⇒ 00:41:46.180 Ryan Brosas: Hmm, no budget.
322 00:41:48.070 ⇒ 00:41:49.700 Hannah Wang: 120… yeah.
323 00:41:49.870 ⇒ 00:41:50.900 Hannah Wang: Oh, wait.
324 00:41:52.050 ⇒ 00:42:01.010 Ryan Brosas: Just, it’s… Hey, wait, Where is the no budgets here, so I can… Anticipate.
325 00:42:02.690 ⇒ 00:42:03.080 Hannah Wang: Oh, it’.
326 00:42:03.080 ⇒ 00:42:04.250 Ryan Brosas: The client.
327 00:42:04.250 ⇒ 00:42:04.860 Hannah Wang: Great.
328 00:42:07.030 ⇒ 00:42:14.170 Hannah Wang: Oh, but we added the budget, right? So maybe we should take it out, because… I wasn’t thinking.
329 00:42:20.140 ⇒ 00:42:20.740 Ryan Brosas: Excuse me.
330 00:42:27.780 ⇒ 00:42:30.039 Ryan Brosas: Project, payment verified.
331 00:42:31.960 ⇒ 00:42:32.790 Ryan Brosas: Amen.
332 00:42:35.080 ⇒ 00:42:37.130 Ryan Brosas: Yeah, you are peace at this.
333 00:42:37.850 ⇒ 00:42:41.360 Ryan Brosas: And, finds… and…
334 00:42:44.720 ⇒ 00:42:46.190 Ryan Brosas: That’s awesome.
335 00:42:48.780 ⇒ 00:42:54.309 Hannah Wang: They unchecked include clients with no feedback. Does that make sense?
336 00:42:54.520 ⇒ 00:42:56.110 Hannah Wang: So it’s including…
337 00:42:57.250 ⇒ 00:42:57.860 Ryan Brosas: God.
338 00:42:57.860 ⇒ 00:42:59.120 Hannah Wang: with feedback.
339 00:43:00.610 ⇒ 00:43:02.270 Hannah Wang: Okay, sure.
340 00:43:02.270 ⇒ 00:43:10.650 Ryan Brosas: So, so, for the include clients with no feedback, it’s a, like, a new…
341 00:43:10.800 ⇒ 00:43:15.069 Ryan Brosas: Like, it’s a new, like, it’s a new user on Upwork?
342 00:43:15.490 ⇒ 00:43:20.520 Hannah Wang: Yeah, okay. But we don’t want that. We want clients with feedback, or…
343 00:43:25.900 ⇒ 00:43:26.710 Ryan Brosas: So…
344 00:43:44.630 ⇒ 00:43:47.579 Ryan Brosas: I’m not sure where there’s, like, an AI here.
345 00:43:57.000 ⇒ 00:43:57.750 Ryan Brosas: Oh.
346 00:44:00.310 ⇒ 00:44:06.790 Ryan Brosas: Thin this to this… Yeah, that’s not… He’s death.
347 00:44:08.930 ⇒ 00:44:21.290 Ryan Brosas: Yeah, 129… 44… About 16…
348 00:44:23.760 ⇒ 00:44:27.380 Hannah Wang: I think 16 is… Too low?
349 00:44:27.380 ⇒ 00:44:29.010 Ryan Brosas: Yes, it’s pretty remote.
350 00:44:29.480 ⇒ 00:44:35.339 Hannah Wang: So should we add a minimum? Oh, but it’s a no-budget one. Okay, ugh.
351 00:44:38.380 ⇒ 00:44:40.470 Hannah Wang: Wait, if this is no budget…
352 00:44:40.760 ⇒ 00:44:45.180 Hannah Wang: Oh, it’s including those with budget and no budget. Is that what’s happening?
353 00:44:47.240 ⇒ 00:44:58.509 Ryan Brosas: It’s no budget, so… So it’s always, like, including… also, that has a budget, or…
354 00:44:58.920 ⇒ 00:45:06.659 Ryan Brosas: what do you call this? There’s specific spend? Because we are targeting spend on here, so…
355 00:45:06.950 ⇒ 00:45:12.549 Ryan Brosas: Instead of, like, getting a low, for example, here.
356 00:45:13.090 ⇒ 00:45:14.769 Ryan Brosas: We are basing on total spend.
357 00:45:14.770 ⇒ 00:45:16.400 Hannah Wang: Oh, I see, okay.
358 00:45:22.950 ⇒ 00:45:25.640 Ryan Brosas: But yeah, I think it’s a keyword.
359 00:45:25.870 ⇒ 00:45:27.020 Ryan Brosas: Problem?
360 00:45:27.280 ⇒ 00:45:31.209 Ryan Brosas: And, I will be,
361 00:45:31.610 ⇒ 00:45:34.379 Ryan Brosas: Doing an experiment for… with this.
362 00:45:35.700 ⇒ 00:45:42.389 Hannah Wang: Okay, let me look at my notes and see what other stuff… Victor mentioned.
363 00:45:57.610 ⇒ 00:46:02.650 Hannah Wang: Well, yeah, I think for the no-budget one, we want to remove new clients.
364 00:46:03.160 ⇒ 00:46:07.050 Hannah Wang: Like, we want… clients.
365 00:46:08.020 ⇒ 00:46:10.300 Hannah Wang: We want to uncheck.
366 00:46:10.930 ⇒ 00:46:17.249 Hannah Wang: So we don’t want to include clients with no feedback, because if they have no budget and they don’t have feedback.
367 00:46:17.370 ⇒ 00:46:21.830 Hannah Wang: Then it’s probably scammy, so… Yeah, uncheck that.
368 00:46:22.210 ⇒ 00:46:23.160 Hannah Wang: I think.
369 00:46:25.680 ⇒ 00:46:29.250 Hannah Wang: Okay, we fixed the cover letter.
370 00:46:49.780 ⇒ 00:46:55.740 Ryan Brosas: Yeah, nathan… You can see…
371 00:47:13.050 ⇒ 00:47:13.970 Ryan Brosas: Hmm…
372 00:47:17.970 ⇒ 00:47:26.530 Ryan Brosas: Oh, I think… Yeah, I added a lot of stuff here.
373 00:47:27.260 ⇒ 00:47:28.030 Hannah Wang: Okay.
374 00:47:29.260 ⇒ 00:47:32.670 Ryan Brosas: Shit.
375 00:47:34.940 ⇒ 00:47:36.640 Ryan Brosas: Should I remove this?
376 00:47:37.310 ⇒ 00:47:43.280 Ryan Brosas: Or… Should just remove it for our… a second.
377 00:47:48.170 ⇒ 00:47:50.169 Ryan Brosas: Then get the…
378 00:47:56.900 ⇒ 00:47:59.170 Ryan Brosas: There’s the one…
379 00:48:05.780 ⇒ 00:48:07.079 Ryan Brosas: This is the original.
380 00:48:08.470 ⇒ 00:48:09.085 Ryan Brosas: Oh…
381 00:48:15.550 ⇒ 00:48:20.559 Ryan Brosas: Then we have 1,800. Wow, that’s a lot.
382 00:48:21.390 ⇒ 00:48:29.780 Ryan Brosas: But, as he’s mentioned, that it will include marketing, so we want to be specific on our
383 00:48:30.020 ⇒ 00:48:36.730 Ryan Brosas: Job category, AI Ops… Where is also AI?
384 00:48:38.240 ⇒ 00:48:39.650 Ryan Brosas: Maybe a linear.
385 00:48:40.950 ⇒ 00:48:42.970 Ryan Brosas: Oops, integration.
386 00:48:46.630 ⇒ 00:48:47.879 Ryan Brosas: Then we got…
387 00:48:47.880 ⇒ 00:48:50.099 Hannah Wang: Oh, okay, that’s better.
388 00:48:50.660 ⇒ 00:48:51.819 Hannah Wang: I think.
389 00:48:53.790 ⇒ 00:48:56.679 Ryan Brosas: Yeah, I think it’s much better, because,
390 00:48:56.790 ⇒ 00:49:07.680 Ryan Brosas: From my excluded stuff, it is a lot, so… That’s not step one.
391 00:49:12.690 ⇒ 00:49:14.729 Ryan Brosas: And everything, so…
392 00:49:15.080 ⇒ 00:49:19.010 Hannah Wang: Wow, you added a lot of keywords to filter out.
393 00:49:19.010 ⇒ 00:49:29.540 Ryan Brosas: Yeah… So, I think that… Finally, like, the keyword system. This is because we have this specific stuff.
394 00:49:29.880 ⇒ 00:49:30.280 Hannah Wang: Yeah.
395 00:49:30.280 ⇒ 00:49:33.019 Ryan Brosas: Focusing on our target.
396 00:49:33.370 ⇒ 00:49:37.090 Ryan Brosas: category. I think this is much better.
397 00:49:37.330 ⇒ 00:49:38.120 Hannah Wang: Yeah.
398 00:49:38.910 ⇒ 00:49:41.260 Ryan Brosas: This is much on, like…
399 00:49:41.980 ⇒ 00:49:45.870 Ryan Brosas: 12, but we can…
400 00:49:46.780 ⇒ 00:49:51.550 Ryan Brosas: Apply this to, to this also, if…
401 00:49:51.550 ⇒ 00:49:52.350 Hannah Wang: Yeah.
402 00:49:54.060 ⇒ 00:49:54.810 Hannah Wang: Let’s try it.
403 00:49:58.940 ⇒ 00:50:04.180 Ryan Brosas: Just saving that one, and… Okay, so…
404 00:50:15.230 ⇒ 00:50:16.519 Ryan Brosas: We hung up…
405 00:50:27.000 ⇒ 00:50:27.690 Ryan Brosas: Yep.
406 00:50:27.880 ⇒ 00:50:32.060 Ryan Brosas: So, we increased our scanner here.
407 00:50:33.320 ⇒ 00:50:36.390 Ryan Brosas: Oh, or is it the same? Is this still the same?
408 00:50:45.560 ⇒ 00:50:47.539 Hannah Wang: I forgot what it was before.
409 00:50:51.660 ⇒ 00:50:52.730 Ryan Brosas: Yes.
410 00:50:54.490 ⇒ 00:51:02.320 Ryan Brosas: 261… Yeah, I think it’s… it’s much… more from before, I guess.
411 00:51:03.390 ⇒ 00:51:06.309 Ryan Brosas: I think it’s, like, 100 plus or something.
412 00:51:06.310 ⇒ 00:51:07.080 Hannah Wang: Okay.
413 00:51:07.300 ⇒ 00:51:15.300 Hannah Wang: Sorry, scroll back up a little bit. I saw a bunch of, like, keywords that we can maybe use. Keep going up…
414 00:51:16.420 ⇒ 00:51:19.389 Hannah Wang: More. Just keep going.
415 00:51:20.280 ⇒ 00:51:26.110 Hannah Wang: More, more… oh, right there? Is that Gemini? We can include Gemini, too.
416 00:51:35.890 ⇒ 00:51:42.320 Ryan Brosas: Turn around… Hmm… Llama.
417 00:51:43.590 ⇒ 00:51:44.310 Hannah Wang: Yeah.
418 00:52:07.650 ⇒ 00:52:09.150 Ryan Brosas: I think this is pretty much…
419 00:52:10.590 ⇒ 00:52:19.699 Ryan Brosas: Oh, but this has now, like, the average speed, 60… No client feedback.
420 00:52:24.040 ⇒ 00:52:33.459 Ryan Brosas: And… Okay, so Tam has, like, like, some past work on, on, Upwork.
421 00:52:37.470 ⇒ 00:52:39.490 Hannah Wang: What… sorry, what was that? Does he have.
422 00:52:39.490 ⇒ 00:52:45.660 Ryan Brosas: Does he have, like, past experience on Upwork?
423 00:52:45.920 ⇒ 00:52:47.089 Ryan Brosas: This is great.
424 00:52:47.090 ⇒ 00:52:49.410 Hannah Wang: tests work? I don’t think so.
425 00:52:49.410 ⇒ 00:52:50.610 Ryan Brosas: Budget, yeah.
426 00:52:51.390 ⇒ 00:52:54.599 Hannah Wang: Most of it has been Robert’s account.
427 00:52:54.840 ⇒ 00:52:55.810 Hannah Wang: Mountain.
428 00:52:56.280 ⇒ 00:52:59.520 Hannah Wang: So, yeah, I think that… But that’s mostly data. Yeah.
429 00:52:59.520 ⇒ 00:53:07.739 Ryan Brosas: This will be, like, pretty, hard for Otam’s account, because he doesn’t have, like, any feedback on here.
430 00:53:07.740 ⇒ 00:53:10.880 Hannah Wang: I think adding a testimonial.
431 00:53:10.930 ⇒ 00:53:17.269 Ryan Brosas: I think, that he can request something on our current client.
432 00:53:17.800 ⇒ 00:53:22.810 Ryan Brosas: So they can provide, like, a testimonial, That’s one…
433 00:53:22.810 ⇒ 00:53:23.230 Hannah Wang: one thing.
434 00:53:24.130 ⇒ 00:53:24.690 Hannah Wang: Nice.
435 00:53:24.690 ⇒ 00:53:25.060 Ryan Brosas: Because…
436 00:53:25.060 ⇒ 00:53:33.869 Hannah Wang: So, like, for ABC, do you think, for example, we can ask them for a testimonial? I don’t even know if they have an Upwork account, though.
437 00:53:34.650 ⇒ 00:53:40.659 Ryan Brosas: Yeah, I think that’s fine if they don’t have an Upwork account, as I already also, like.
438 00:53:40.940 ⇒ 00:53:42.730 Ryan Brosas: Right? It.
439 00:53:42.730 ⇒ 00:53:44.490 Hannah Wang: Oh, yeah, right.
440 00:53:44.660 ⇒ 00:53:50.050 Hannah Wang: Yeah, I remember that. Okay, let me…
441 00:53:53.630 ⇒ 00:53:57.700 Ryan Brosas: Also, we can, work history also here.
442 00:53:59.750 ⇒ 00:54:05.960 Ryan Brosas: Yeah, I think… I’ll just add a little bit of here, later.
443 00:54:06.460 ⇒ 00:54:09.620 Ryan Brosas: when I have… Time here.
444 00:54:10.550 ⇒ 00:54:13.630 Hannah Wang: So, for the testimony, Neil, can you, like.
445 00:54:13.630 ⇒ 00:54:14.320 Ryan Brosas: here.
446 00:54:14.500 ⇒ 00:54:15.700 Hannah Wang: Click on it.
447 00:54:17.130 ⇒ 00:54:17.530 Ryan Brosas: Yes.
448 00:54:17.530 ⇒ 00:54:20.659 Hannah Wang: Oh… I see.
449 00:54:24.260 ⇒ 00:54:36.899 Hannah Wang: Well, like, technically, we do have a testimonial from Yvette. She is from ABC, and I put it in our case study, but I don’t…
450 00:54:37.250 ⇒ 00:54:43.880 Hannah Wang: want to add it without her permission, yeah, that’s fine.
451 00:54:45.070 ⇒ 00:54:46.160 Hannah Wang: So…
452 00:54:46.670 ⇒ 00:54:54.299 Hannah Wang: Maybe… because I know Jake is trying to get something from Yvette, so maybe I’ll ask Jake if he can also ask
453 00:54:54.520 ⇒ 00:54:55.600 Hannah Wang: You bet.
454 00:54:55.740 ⇒ 00:54:59.540 Hannah Wang: If we can include it in our Upwork account.
455 00:54:59.720 ⇒ 00:55:03.619 Hannah Wang: Let me take a note of that, and then I’ll ask him.
456 00:55:05.890 ⇒ 00:55:07.949 Ryan Brosas: Yeah, I think that’s fine.
457 00:55:08.440 ⇒ 00:55:16.179 Ryan Brosas: Yeah, I think, that one also, because, I know, Upwork is really hard when
458 00:55:16.610 ⇒ 00:55:21.540 Ryan Brosas: We don’t, the… if the travel doesn’t have, like, Fast project?
459 00:55:21.540 ⇒ 00:55:22.500 Hannah Wang: Yeah, I agree.
460 00:55:22.500 ⇒ 00:55:29.310 Ryan Brosas: I think that’s also one of the variables that it’s not converting on OTAM’s side.
461 00:55:29.710 ⇒ 00:55:32.629 Ryan Brosas: So… Yeah, I’ll let…
462 00:55:32.740 ⇒ 00:55:42.130 Ryan Brosas: we can start off, like, getting some testimonial, and I hope, hopefully, that… that can solve our…
463 00:55:42.370 ⇒ 00:55:44.370 Ryan Brosas: Fixed the conversion rate.
464 00:55:44.720 ⇒ 00:55:46.579 Ryan Brosas: Yeah, can you click on…
465 00:55:46.580 ⇒ 00:55:50.269 Hannah Wang: Manage projects? Like, what… what goes in there?
466 00:55:51.470 ⇒ 00:55:53.130 Ryan Brosas: Manage Budgets…
467 00:55:53.130 ⇒ 00:55:54.490 Hannah Wang: Yeah, go up.
468 00:55:54.640 ⇒ 00:55:55.360 Hannah Wang: Up.
469 00:55:56.240 ⇒ 00:56:00.540 Hannah Wang: Oh, down, oh, you’re scrolling so fast, go down, right here.
470 00:56:00.600 ⇒ 00:56:01.550 Ryan Brosas: Sorry.
471 00:56:01.620 ⇒ 00:56:02.580 Hannah Wang: It’s okay.
472 00:56:03.750 ⇒ 00:56:06.500 Hannah Wang: Can we just create a project?
473 00:56:08.170 ⇒ 00:56:08.860 Ryan Brosas: this…
474 00:56:14.480 ⇒ 00:56:19.140 Hannah Wang: Oh, I thought I did this. Did I not… did I do it for Robert?
475 00:56:19.680 ⇒ 00:56:20.760 Hannah Wang: Oh.
476 00:56:21.600 ⇒ 00:56:22.530 Hannah Wang: I see.
477 00:56:23.760 ⇒ 00:56:26.080 Hannah Wang: Okay.
478 00:56:37.230 ⇒ 00:56:41.289 Hannah Wang: Maybe we can bring it up in our meeting on Monday.
479 00:56:42.790 ⇒ 00:56:48.800 Hannah Wang: Because I don’t really know what projects… we offer…
480 00:56:49.760 ⇒ 00:56:52.070 Hannah Wang: Or maybe we can ask the AI team.
481 00:57:12.230 ⇒ 00:57:18.259 Hannah Wang: Okay, I’ll just ask the AI team for ideas, so I can do the project stuff, too.
482 00:57:30.310 ⇒ 00:57:31.330 Hannah Wang: Okay.
483 00:57:33.010 ⇒ 00:57:38.610 Hannah Wang: So should we turn on the no-budget filters? Or scanners? Sorry.
484 00:57:39.550 ⇒ 00:57:43.959 Ryan Brosas: Yeah, I think we can turn on for,
485 00:57:48.230 ⇒ 00:57:49.270 Ryan Brosas: For Robert?
486 00:57:52.630 ⇒ 00:57:55.559 Hannah Wang: Do you think it’s not worth it to turn it on for UTAM?
487 00:57:57.050 ⇒ 00:58:04.359 Ryan Brosas: For Utom, let’s see… Okay, let’s see…
488 00:58:08.100 ⇒ 00:58:08.920 Ryan Brosas: Okay.
489 00:58:15.410 ⇒ 00:58:16.340 Hannah Wang: Right here.
490 00:58:16.460 ⇒ 00:58:17.590 Hannah Wang: No budget.
491 00:58:19.380 ⇒ 00:58:20.970 Ryan Brosas: Okay, thank you.
492 00:58:22.710 ⇒ 00:58:33.179 Ryan Brosas: Yeah, yeah, we can try on… well, it’s… they have, like, a 31, an hour, 45.
493 00:58:33.510 ⇒ 00:58:41.260 Ryan Brosas: Video consultant, made for a light project, so… That’s something…
494 00:58:44.460 ⇒ 00:58:45.519 Ryan Brosas: Me too.
495 00:58:47.610 ⇒ 00:58:48.720 Ryan Brosas: I’ll see what’s fine.
496 00:58:57.910 ⇒ 00:59:02.539 Ryan Brosas: Yeah, I’m saying, yeah, I… Did you try…
497 00:59:02.960 ⇒ 00:59:05.849 Ryan Brosas: Yeah, this is pretty low. Yeah, I think we can.
498 00:59:05.850 ⇒ 00:59:06.310 Hannah Wang: Okay.
499 00:59:06.310 ⇒ 00:59:07.420 Ryan Brosas: try this.
500 00:59:08.690 ⇒ 00:59:11.000 Hannah Wang: I think it’s too low, I don’t know.
501 00:59:11.780 ⇒ 00:59:13.600 Ryan Brosas: Yeah, this is too low.
502 00:59:14.030 ⇒ 00:59:27.240 Ryan Brosas: Well… 13… This is… I’m not sure if they’re going to agree, agree with this rate, but… Yeah.
503 00:59:29.520 ⇒ 00:59:34.289 Hannah Wang: Sorry, can you go back to the one that Victor set up for us, over here?
504 00:59:38.430 ⇒ 00:59:43.409 Hannah Wang: And then… Go to jobs…
505 00:59:49.470 ⇒ 00:59:54.680 Hannah Wang: So I think no budget means
506 00:59:55.140 ⇒ 00:59:58.539 Hannah Wang: checking this, but I think we can still have an hourly rate.
507 00:59:58.680 ⇒ 01:00:01.690 Hannah Wang: I think that’s fine to do, so we should just add that.
508 01:00:09.030 ⇒ 01:00:12.500 Hannah Wang: Yeah, so check that, and then add a rate.
509 01:00:14.040 ⇒ 01:00:20.740 Hannah Wang: Yeah, I think that should be better. There’s gonna be less results, but it’ll be… Better, maybe?
510 01:00:21.290 ⇒ 01:00:23.210 Ryan Brosas: Yeah, I think, this is good.
511 01:00:25.670 ⇒ 01:00:27.609 Hannah Wang: Why is it still 13, though?
512 01:00:30.670 ⇒ 01:00:31.150 Hannah Wang: Boyd.
513 01:00:32.860 ⇒ 01:00:35.979 Hannah Wang: Oh, it’s okay, but at least the hourly is there.
514 01:00:37.140 ⇒ 01:00:41.660 Ryan Brosas: the hourly, yeah. There is no hourly care.
515 01:00:42.170 ⇒ 01:00:46.359 Ryan Brosas: this state’s good enough.
516 01:00:49.030 ⇒ 01:00:52.919 Ryan Brosas: Yeah, I think, this is good.
517 01:00:53.560 ⇒ 01:01:01.560 Ryan Brosas: 50, 60 to 120… 69…
518 01:01:02.530 ⇒ 01:01:09.400 Ryan Brosas: 300K… they have a budget, so I guess… Hi, AI clown.
519 01:01:15.370 ⇒ 01:01:16.810 Ryan Brosas: calculator.
520 01:01:24.370 ⇒ 01:01:24.955 Ryan Brosas: Oh…
521 01:01:29.690 ⇒ 01:01:32.090 Ryan Brosas: Yeah, we can turn this on.
522 01:01:32.570 ⇒ 01:01:34.139 Ryan Brosas: And let’s see…
523 01:01:35.200 ⇒ 01:01:40.359 Hannah Wang: You probably want to copy the keyword filter to the other one, too.
524 01:01:56.590 ⇒ 01:01:57.430 Hannah Wang: Yeah.
525 01:02:05.360 ⇒ 01:02:09.820 Hannah Wang: Okay, yeah, let’s turn the no-budget ones on, see.
526 01:02:10.640 ⇒ 01:02:11.970 Hannah Wang: What happens?
527 01:02:14.290 ⇒ 01:02:19.890 Hannah Wang: And then, on Monday, we can check back on the… Match. Profile match.
528 01:02:32.510 ⇒ 01:02:35.200 Ryan Brosas: Already, this is already turned on.
529 01:02:35.470 ⇒ 01:02:36.990 Hannah Wang: Okay, cool.
530 01:02:37.180 ⇒ 01:02:40.349 Hannah Wang: And then, do we want to turn on this one, too?
531 01:02:41.490 ⇒ 01:02:43.340 Ryan Brosas: Okay, sure, nope.
532 01:02:45.810 ⇒ 01:02:50.460 Ryan Brosas: So… Okay… Okay.
533 01:03:06.130 ⇒ 01:03:07.029 Hannah Wang: Okay. Yep.
534 01:03:09.430 ⇒ 01:03:12.559 Ryan Brosas: So, we turned on no budget.
535 01:03:13.920 ⇒ 01:03:18.390 Ryan Brosas: And… Yes.
536 01:03:18.690 ⇒ 01:03:22.270 Ryan Brosas: Do we want to turn this on also? That product?
537 01:03:22.510 ⇒ 01:03:24.240 Ryan Brosas: Product analytics…
538 01:03:25.860 ⇒ 01:03:28.909 Hannah Wang: How is that different than the first one?
539 01:03:30.290 ⇒ 01:03:38.800 Ryan Brosas: I think he added this for this one? No… This one, I guess?
540 01:03:42.160 ⇒ 01:03:44.040 Ryan Brosas: But, yeah, I’m not sure, so…
541 01:03:55.640 ⇒ 01:03:59.590 Ryan Brosas: Yeah, this has a lot of… like, updated.
542 01:04:01.730 ⇒ 01:04:03.210 Ryan Brosas: Oh, interesting.
543 01:04:03.210 ⇒ 01:04:06.969 Hannah Wang: I don’t… oh, is it out of… Oh, it’s…
544 01:04:07.340 ⇒ 01:04:08.370 Ryan Brosas: No budget.
545 01:04:08.370 ⇒ 01:04:10.779 Hannah Wang: No budget, and also other countries.
546 01:04:12.920 ⇒ 01:04:15.110 Ryan Brosas: Oh, yeah, all the volunteers.
547 01:04:16.010 ⇒ 01:04:18.300 Ryan Brosas: So do we work with other countries?
548 01:04:18.300 ⇒ 01:04:21.079 Hannah Wang: I don’t… I don’t know. I don’t…
549 01:04:22.940 ⇒ 01:04:23.335 Ryan Brosas: Hmm…
550 01:04:23.730 ⇒ 01:04:25.410 Hannah Wang: I don’t think so.
551 01:04:27.010 ⇒ 01:04:27.910 Ryan Brosas: Yeah, we…
552 01:04:28.120 ⇒ 01:04:29.970 Hannah Wang: I think we just do U.S.
553 01:04:32.110 ⇒ 01:04:33.690 Ryan Brosas: Yeah, - so…
554 01:04:34.220 ⇒ 01:04:35.830 Hannah Wang: Okay, just leave it off.
555 01:04:38.480 ⇒ 01:04:39.090 Ryan Brosas: Thank you.
556 01:04:42.010 ⇒ 01:04:43.410 Hannah Wang: Okay, we can…
557 01:04:43.410 ⇒ 01:04:43.830 Ryan Brosas: Yeah.
558 01:04:43.830 ⇒ 01:04:49.309 Hannah Wang: Monitor this, and then see how our cover letters do, as well.
559 01:04:50.080 ⇒ 01:04:52.719 Hannah Wang: Because we changed it.
560 01:04:53.330 ⇒ 01:04:56.920 Hannah Wang: Today, the cover letters, so we can…
561 01:04:58.160 ⇒ 01:05:01.110 Hannah Wang: See how short… how much shorter it is later.
562 01:05:01.970 ⇒ 01:05:04.619 Ryan Brosas: Yeah, so, I forgot.
563 01:05:05.760 ⇒ 01:05:07.550 Ryan Brosas: I think, I think…
564 01:05:12.740 ⇒ 01:05:14.360 Hannah Wang: Oh, right.
565 01:05:21.330 ⇒ 01:05:22.689 Ryan Brosas: I don’t see the same.
566 01:05:26.950 ⇒ 01:05:31.550 Ryan Brosas: Mmm… Oh, it’s already set up, I guess.
567 01:05:31.770 ⇒ 01:05:32.490 Hannah Wang: Okay.
568 01:05:36.030 ⇒ 01:05:39.600 Ryan Brosas: But… since…
569 01:05:51.050 ⇒ 01:05:52.460 Ryan Brosas: Nope, nope.
570 01:05:54.260 ⇒ 01:05:55.270 Ryan Brosas: So long.
571 01:06:21.500 ⇒ 01:06:22.240 Ryan Brosas: Yeah?
572 01:06:22.920 ⇒ 01:06:24.500 Hannah Wang: Okay, sounds good.
573 01:06:27.080 ⇒ 01:06:28.020 Ryan Brosas: Thank you.
574 01:06:28.210 ⇒ 01:06:29.610 Hannah Wang: Yeah, we’ll see how this goes.
575 01:06:29.790 ⇒ 01:06:40.900 Hannah Wang: We can… I… I know that… I understand it better now, and I’ll check the sales notification channel, more frequently. But yeah.
576 01:06:41.020 ⇒ 01:06:43.589 Hannah Wang: Thank you, Ryan, for making all those changes.
577 01:06:44.110 ⇒ 01:06:45.110 Ryan Brosas: Thank you.
578 01:06:45.110 ⇒ 01:06:47.379 Hannah Wang: Alright, bye-bye, have a good weekend.