Meeting Title: Sales GTM KickOff | Placeholder Date: 2025-04-28 Meeting participants: Mariane Cequina, Luke Daque, Amber Lin, Robert Tseng
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1 00:00:20.220 ⇒ 00:00:23.970 Amber Lin: Bye, we have everyone sorry for the wait.
2 00:00:23.970 ⇒ 00:00:24.590 Luke Daque: 11.
3 00:00:26.320 ⇒ 00:00:29.650 Amber Lin: Here, let me share linear.
4 00:00:30.240 ⇒ 00:00:33.180 Amber Lin: and then we can kick off from there.
5 00:00:33.970 ⇒ 00:00:44.479 Amber Lin: So I know you guys already had a meeting before about this project, and let’s go to Project view.
6 00:00:46.300 ⇒ 00:00:48.599 Amber Lin: So we have 3 main things
7 00:00:50.260 ⇒ 00:00:59.739 Amber Lin: this lead list builder is something that we wanted to immediately. And this is our top priority, and ideally, we want to have something out by
8 00:01:00.290 ⇒ 00:01:04.099 Amber Lin: Friday, so end of this week, and
9 00:01:04.690 ⇒ 00:01:10.760 Amber Lin: I’ll let Robert take over. I don’t know how much you guys already know about this project.
10 00:01:10.970 ⇒ 00:01:12.500 Amber Lin: I’ll just.
11 00:01:12.930 ⇒ 00:01:14.919 Amber Lin: I’ll leave the floor to Robert.
12 00:01:17.990 ⇒ 00:01:22.090 Robert Tseng: Okay, thanks. Amber. So
13 00:01:25.170 ⇒ 00:01:33.180 Robert Tseng: yeah, I mean, I guess we can just talk about the lead List Builder project. So I mean, I think the ask is pretty straightforward. We just we need to, or
14 00:01:34.980 ⇒ 00:01:39.759 Robert Tseng: we have a different ways of targeting
15 00:01:42.780 ⇒ 00:01:48.687 Robert Tseng: prospects. They could be through events. They could be through engagement on social media.
16 00:01:49.600 ⇒ 00:01:56.630 Robert Tseng: you know, they could end up coming through intake. You know, there’s a lot variety of different ways. We can get these
17 00:01:59.230 ⇒ 00:02:03.089 Robert Tseng: prospects. And yeah, I think
18 00:02:03.350 ⇒ 00:02:10.000 Robert Tseng: it’s probably on me to define, like, what are all those methods that we get lead lists? I think I
19 00:02:10.130 ⇒ 00:02:18.350 Robert Tseng: have been just dropping one off things into sales slack, and then they just like vanish like I don’t think I’ve
20 00:02:18.460 ⇒ 00:02:23.481 Robert Tseng: seeing any lists come through there so trying to build a more.
21 00:02:26.460 ⇒ 00:02:34.110 Robert Tseng: yeah, just trying to build like an actual system where we’re actually gonna be able to generate these lead lists. So I can go after them.
22 00:02:36.610 ⇒ 00:02:42.910 Robert Tseng: I think the the stack that we’re using I mean, clay is kind of this.
23 00:02:44.440 ⇒ 00:02:54.090 Robert Tseng: Contacts enrichment database that we could sync to our Crm, which is Hubspot
24 00:02:55.038 ⇒ 00:03:03.600 Robert Tseng: within clay. You can set up all types of automations. To enrich the contact details.
25 00:03:03.980 ⇒ 00:03:06.820 Robert Tseng: Maybe some of you know better than I do.
26 00:03:09.030 ⇒ 00:03:16.270 Robert Tseng: But yeah, I think the ask here is to get that set up, and that you’re able to kind of take in
27 00:03:16.920 ⇒ 00:03:19.780 Robert Tseng: like the requirements that I give for different
28 00:03:20.150 ⇒ 00:03:27.210 Robert Tseng: types of lead lists to build them out and to export them into Hubspot, so that
29 00:03:27.808 ⇒ 00:03:35.030 Robert Tseng: I can then go and send out messaging.
30 00:03:35.860 ⇒ 00:03:43.559 Robert Tseng: for now it’s manual messaging, but that kind of leads into the second project, which is automating at least that 1st touch
31 00:03:44.920 ⇒ 00:03:49.870 Robert Tseng: where we can use tools like Apollo,
32 00:03:52.030 ⇒ 00:03:57.799 Robert Tseng: and a n, possibly to orchestrate like what the interactions will look like
33 00:03:59.730 ⇒ 00:04:05.910 Robert Tseng: for Linkedin we use, hey, reach right now. And that’s been pretty effective, so I could even just
34 00:04:06.810 ⇒ 00:04:08.959 Robert Tseng: take the clay tables.
35 00:04:09.190 ⇒ 00:04:14.200 Robert Tseng: export them via Csv. Into hey reach, or through a direct connection, and be able to
36 00:04:14.560 ⇒ 00:04:24.740 Robert Tseng: do all of my messaging through, hey reach. But that doesn’t apply to email, which is something that hasn’t been active for us that I’d like to turn back on.
37 00:04:25.050 ⇒ 00:04:29.499 Robert Tseng: So that’s at a high level, like what we’re trying to accomplish.
38 00:04:30.020 ⇒ 00:04:35.060 Robert Tseng: I think I’ve been working with amber to break break these up into different milestones. And so.
39 00:04:36.180 ⇒ 00:04:42.450 Robert Tseng: yeah, I think, like the 1st one of defining the Icp and target accounts. I think that’s more on me to
40 00:04:43.170 ⇒ 00:04:47.630 Robert Tseng: kind of consolidate what all those methods are.
41 00:04:48.551 ⇒ 00:04:53.370 Robert Tseng: I think we can parallelize that with the second one, which is, you know, building the
42 00:04:55.750 ⇒ 00:05:02.670 Robert Tseng: the process for getting data and what it should look like in clay. So need this team to
43 00:05:02.830 ⇒ 00:05:11.703 Robert Tseng: get familiar with clay. Set up something for me to be able to test like, yeah, let’s just let’s just run. Let’s just let’s just run a test.
44 00:05:12.760 ⇒ 00:05:15.700 Robert Tseng: I have a lot of different types of
45 00:05:15.800 ⇒ 00:05:17.870 Robert Tseng: list that I would like to send in. And
46 00:05:19.970 ⇒ 00:05:24.650 Robert Tseng: yeah, I think there’s like a lead list architecture diagram that I started to put together.
47 00:05:27.240 ⇒ 00:05:31.290 Robert Tseng: I think this is just really showing like
48 00:05:31.600 ⇒ 00:05:34.930 Robert Tseng: what a funnel would look like.
49 00:05:36.590 ⇒ 00:05:41.569 Robert Tseng: I mean, these images are AI generate. I mean, they’re great. I think I probably would need to
50 00:05:43.270 ⇒ 00:05:47.045 Robert Tseng: either build it myself, or maybe Amber could go in and and
51 00:05:48.190 ⇒ 00:05:51.120 Robert Tseng: build it out more clearly. But
52 00:05:52.198 ⇒ 00:06:00.070 Robert Tseng: it’s meant to just document how the system moves data around pretty much.
53 00:06:06.330 ⇒ 00:06:08.149 Robert Tseng: Yeah. So I kinda
54 00:06:09.050 ⇒ 00:06:34.719 Robert Tseng: I’ve I feel like there’s a lot I’ve kind of presented this idea in a lot of different ways. So just wanna get to a place where there is an actual clay table that I can give a lead list to this team, and it can show up there and then it can be handed off to Hubspot. So, however much we need to simplify this to to get to that. That’s that’s kind of the 1st thing I want to even see so.
55 00:06:34.720 ⇒ 00:06:46.880 Amber Lin: What would one lead table? Then? What is a cause? This will help with learning clay with thinking about it. If we have a specific example. What would be the most representative
56 00:06:47.090 ⇒ 00:06:52.189 Amber Lin: example of a lead list? We’ll just do a small project on that.
57 00:06:53.200 ⇒ 00:07:01.840 Robert Tseng: I probably would just go into slack. And then I’m gonna go and look at need lists, keyword. And I think there have been
58 00:07:02.940 ⇒ 00:07:06.749 Robert Tseng: multiple requests that I’ve made here. So
59 00:07:22.850 ⇒ 00:07:29.590 Robert Tseng: I mean, some of these are like kind of outdated at this point. So I just have to go in and look at the most recent one I’ve asked for.
60 00:07:33.900 ⇒ 00:07:37.819 Amber Lin: Is it more of a event based company based.
61 00:07:41.970 ⇒ 00:07:43.250 Robert Tseng: It should be both.
62 00:07:48.750 ⇒ 00:07:50.940 Luke Daque: And just to be
63 00:07:51.650 ⇒ 00:08:03.139 Luke Daque: clear, the the thing that we want to create and play, which is like the table, is just for testing purposes right? We can do it like we can just use a Csv file for now.
64 00:08:03.913 ⇒ 00:08:07.440 Luke Daque: To make sure that the leads get enriched or something like that
65 00:08:07.950 ⇒ 00:08:11.080 Luke Daque: doesn’t have to be like Web, related already.
66 00:08:15.410 ⇒ 00:08:21.339 Robert Tseng: Yeah, I mean, the web hook is really just to be able to tie it to like a Linkedin
67 00:08:22.749 ⇒ 00:08:33.489 Robert Tseng: post or events or something. So I think that’s the data piece that I think it’d be good for Ryan to be looking at, because
68 00:08:34.390 ⇒ 00:08:38.460 Robert Tseng: I don’t know what we can do with Linkedin data like.
69 00:08:38.760 ⇒ 00:08:40.870 Luke Daque: I would expect that.
70 00:08:42.470 ⇒ 00:09:01.279 Robert Tseng: Yeah, yeah, I think the example would be, I know an event is happening next week. I wanna use the keyword of that event in the search bar, and anybody who’s talking about that event. I want to scrape them all and put them into a lead list and Clay and I would I would I would do a campaign around that.
71 00:09:01.900 ⇒ 00:09:04.069 Robert Tseng: So that that’s 1 example.
72 00:09:05.710 ⇒ 00:09:09.750 Robert Tseng: Yeah. I mean, then there’s our webinar folk, I mean, I I think the
73 00:09:11.820 ⇒ 00:09:18.800 Robert Tseng: like to Ryan’s Point. If we’re just testing a Csv, then I could just give you a random list like it doesn’t really.
74 00:09:19.610 ⇒ 00:09:28.533 Robert Tseng: I don’t think that’s enough for me like I wanna be able to explore like, what? What can we? What can I actually ask for?
75 00:09:29.860 ⇒ 00:09:34.280 Robert Tseng: So there, there has to be an ingestion component to this. That’s not just Csv.
76 00:09:36.780 ⇒ 00:09:37.580 Luke Daque: Makes sense.
77 00:09:37.580 ⇒ 00:09:38.640 Amber Lin: Oh, yeah.
78 00:09:38.640 ⇒ 00:09:41.330 Luke Daque: Like the thing that we noticed in clay.
79 00:09:43.380 ⇒ 00:09:52.039 Luke Daque: at least when we tried testing it last Friday, I believe, was that we needed the higher tier to be able to use the web books
80 00:09:52.380 ⇒ 00:09:53.380 Luke Daque: so.
81 00:09:54.740 ⇒ 00:09:56.968 Luke Daque: But I can’t remember like what
82 00:09:58.020 ⇒ 00:10:00.799 Luke Daque: Ryan mentioned. I think he was like looking into
83 00:10:01.250 ⇒ 00:10:03.910 Luke Daque: using n, 8 n. Instead, or something.
84 00:10:04.330 ⇒ 00:10:09.910 Robert Tseng: No, if we need to pay for it, I will pay for it like I don’t really care. I think we’re well. I’d rather just
85 00:10:10.670 ⇒ 00:10:14.759 Robert Tseng: give this effort like, it’s enough time.
86 00:10:16.480 ⇒ 00:10:17.990 Robert Tseng: Yeah. I mean, if it
87 00:10:18.730 ⇒ 00:10:24.039 Robert Tseng: yeah, like I I will. I will pay for anything that it will take to get it done.
88 00:10:25.030 ⇒ 00:10:25.560 Luke Daque: Okay.
89 00:10:25.560 ⇒ 00:10:26.110 Luke Daque: Sounds good.
90 00:10:26.110 ⇒ 00:10:37.460 Amber Lin: 1st step. Better be to set up the clay table with all the necessary fields. Would that be a good 1st step, and then we can look at the ingestion.
91 00:10:37.830 ⇒ 00:10:38.500 Amber Lin: because I think.
92 00:10:38.500 ⇒ 00:10:39.060 Robert Tseng: Yes.
93 00:10:39.060 ⇒ 00:10:39.900 Amber Lin: Tests.
94 00:10:40.100 ⇒ 00:10:41.770 Robert Tseng: Yeah, I think those are separate things. Yeah.
95 00:10:41.770 ⇒ 00:10:53.100 Amber Lin: Okay, sounds good. I’ll break that. I’ll break up that ticket then and then inc, oh.
96 00:10:58.940 ⇒ 00:10:59.900 Amber Lin: set up
97 00:11:08.971 ⇒ 00:11:16.379 Amber Lin: so that would mean we need to define the fields that we need. Do we already have that.
98 00:11:18.374 ⇒ 00:11:23.680 Robert Tseng: Yeah, I feel like I put some screenshots here and there I feel like they exist.
99 00:11:24.570 ⇒ 00:11:25.910 Amber Lin: Where would that be?
100 00:11:27.021 ⇒ 00:11:31.840 Robert Tseng: Probably all on the the notion, Doc, that’s attached to this page.
101 00:11:32.000 ⇒ 00:11:36.810 Amber Lin: Oh, okay, look at the.
102 00:11:41.200 ⇒ 00:11:43.269 Robert Tseng: Yeah. It’s in the description of this project.
103 00:11:43.750 ⇒ 00:11:44.679 Amber Lin: Sounds good.
104 00:11:45.890 ⇒ 00:11:50.609 Amber Lin: Oh, like that would be a
105 00:11:51.750 ⇒ 00:11:58.419 Amber Lin: something that we wanna do. Now let me see to
106 00:12:04.030 ⇒ 00:12:05.390 Amber Lin: and then
107 00:12:20.280 ⇒ 00:12:26.220 Amber Lin: and then this is sort of numbers.
108 00:12:27.950 ⇒ 00:12:33.580 Amber Lin: and then we want to set up the web hook intake.
109 00:12:34.702 ⇒ 00:12:41.400 Amber Lin: We should run this on a test project. So we would take.
110 00:12:42.090 ⇒ 00:12:46.499 Amber Lin: This is all with Linkedin data. Right? If I understand it correctly.
111 00:12:47.960 ⇒ 00:12:51.379 Robert Tseng: I mean I would I would want to test it via Linkedin.
112 00:12:51.380 ⇒ 00:12:51.830 Amber Lin: Okay.
113 00:12:51.930 ⇒ 00:12:52.890 Robert Tseng: Do you know? Yeah.
114 00:12:53.900 ⇒ 00:12:57.160 Amber Lin: Okay. Do we know how to do this?
115 00:12:57.310 ⇒ 00:12:58.210 Amber Lin: Luke?
116 00:13:01.290 ⇒ 00:13:04.580 Luke Daque: I am not sure yet. I’ll have to like.
117 00:13:04.760 ⇒ 00:13:05.790 Luke Daque: Okay. So.
118 00:13:05.790 ⇒ 00:13:08.320 Amber Lin: Research we need to.
119 00:13:08.730 ⇒ 00:13:11.280 Luke Daque: Spike on, how to.
120 00:13:12.070 ⇒ 00:13:17.040 Amber Lin: Do it we want.
121 00:13:24.653 ⇒ 00:13:27.649 Amber Lin: Let’s just say if we do it for event.
122 00:13:28.230 ⇒ 00:13:34.189 Amber Lin: Robert, what would be a event that you want to do it for like just for a sample project.
123 00:13:37.720 ⇒ 00:13:42.907 Robert Tseng: I don’t know of one off the top of my head, because the ones I posted about all ended,
124 00:13:45.140 ⇒ 00:13:48.490 Robert Tseng: yeah, like I I don’t. I don’t have one off top of my head.
125 00:13:50.642 ⇒ 00:13:58.960 Amber Lin: Since this stone needs to do a spike on how to do it, would you be able, Robert? Would you be able to find one
126 00:13:59.370 ⇒ 00:14:04.750 Amber Lin: and just post either send it to me or just post it in the in a sales channel.
127 00:14:05.060 ⇒ 00:14:08.230 Amber Lin: I’ll probably make a new channel for this.
128 00:14:10.730 ⇒ 00:14:16.350 Robert Tseng: Yeah, hmm!
129 00:14:28.820 ⇒ 00:14:31.259 Robert Tseng: So I just tagged you amber.
130 00:14:31.400 ⇒ 00:14:39.029 Amber Lin: Yeah, just tag me of what event we want to do it on. And we’ll look at this.
131 00:14:39.310 ⇒ 00:14:45.839 Amber Lin: I guess how to do it. What requirements, what kind of like? How much do we need to pay alternative ways.
132 00:14:46.020 ⇒ 00:14:51.640 Amber Lin: just how we can get that done? So I think that’s something to do today.
133 00:14:51.840 ⇒ 00:14:56.264 Robert Tseng: Yeah. So I just forwarded you an event that I had asked for before.
134 00:14:56.990 ⇒ 00:15:03.790 Robert Tseng: yeah. So I mean, I imagine we could probably still try to target the people from that event. But
135 00:15:04.060 ⇒ 00:15:05.670 Robert Tseng: as as an example.
136 00:15:06.690 ⇒ 00:15:13.739 Amber Lin: Sounds good and oh, well, but put it here
137 00:15:23.670 ⇒ 00:15:24.620 Amber Lin: awesome.
138 00:15:25.420 ⇒ 00:15:34.270 Amber Lin: So once we have that sample problem. So hold on.
139 00:15:34.820 ⇒ 00:15:35.540 Amber Lin: Next.
140 00:15:42.960 ⇒ 00:15:47.719 Amber Lin: Luke, does this project make sense to you like, is there anything?
141 00:15:47.830 ⇒ 00:15:52.899 Amber Lin: How do you see this being done like I wanna make sure that we’re on the same page?
142 00:15:56.690 ⇒ 00:15:59.480 Robert Tseng: Yeah, I mean, I think this makes sense to me.
143 00:16:00.028 ⇒ 00:16:01.909 Amber Lin: Luke, does it make sense to you.
144 00:16:03.130 ⇒ 00:16:06.679 Luke Daque: I? I think so. But yeah, I’ll I’ll probably
145 00:16:07.070 ⇒ 00:16:10.769 Luke Daque: out from either Marion or Ryan as well, because they they have
146 00:16:10.990 ⇒ 00:16:13.619 Luke Daque: more context and things like this.
147 00:16:16.160 ⇒ 00:16:24.389 Luke Daque: yeah. But yeah, I think that this makes sense. We can start with the setting up in the table and Csv, and then see what we can do from getting like
148 00:16:24.550 ⇒ 00:16:26.360 Luke Daque: data from Linkedin and stuff like that.
149 00:16:27.100 ⇒ 00:16:27.780 Amber Lin: Okay.
150 00:16:28.160 ⇒ 00:16:35.599 Robert Tseng: Yeah, I mean the deliverable. As long as I have an environment in play that’s like set up for me to go and look at the leads like I,
151 00:16:35.840 ⇒ 00:16:42.659 Robert Tseng: that’s good for this project, I think. Then we will slowly enrich it with more stuff like, but yeah, I think
152 00:16:43.250 ⇒ 00:16:48.569 Robert Tseng: that’s that’s all. That’s I think that’s all we really really need to do.
153 00:16:49.760 ⇒ 00:16:59.220 Amber Lin: Yeah. So I think the original will come after we have a list of it. For the architecture
154 00:16:59.860 ⇒ 00:17:07.949 Amber Lin: diagram, how the system moves data around, okay, so
155 00:17:12.609 ⇒ 00:17:14.869 Robert Tseng: It’s just like the end to end of like
156 00:17:16.129 ⇒ 00:17:22.319 Robert Tseng: data is coming in from where and then, like, where is it gonna live like? How does the intermission process work? It’s
157 00:17:22.489 ⇒ 00:17:29.089 Robert Tseng: and then where we’re gonna route it to, it’s gonna be in Hubspot. So okay, so suspend.
158 00:17:29.330 ⇒ 00:17:31.389 Amber Lin: We just don’t have a diagram for it.
159 00:17:32.140 ⇒ 00:17:35.910 Robert Tseng: Yeah, it’s just we’re we’re talking about it. We just have a diagram for it.
160 00:17:36.753 ⇒ 00:17:40.969 Amber Lin: I know about, you know.
161 00:17:44.120 ⇒ 00:17:45.709 Amber Lin: Okay, sounds good.
162 00:17:47.710 ⇒ 00:17:49.659 Amber Lin: Play to over. Csv.
163 00:17:50.560 ⇒ 00:17:55.440 Amber Lin: Marion, would you have time to do that one? How does.
164 00:17:55.580 ⇒ 00:17:58.580 Amber Lin: How do we want to take these tasks.
165 00:18:01.210 ⇒ 00:18:05.680 Mariane Cequina: For the clay table we actually talked to
166 00:18:05.910 ⇒ 00:18:12.310 Mariane Cequina: with Ryan last time, like last Friday, he actually showed some information. Is that
167 00:18:12.960 ⇒ 00:18:17.529 Mariane Cequina: I I don’t know if if it’s something that we can use.
168 00:18:18.630 ⇒ 00:18:22.300 Amber Lin: What was what was Ryan’s output? What did it look like?
169 00:18:24.130 ⇒ 00:18:31.610 Mariane Cequina: Yeah, I actually showed like a table. Is that correct look like, last Friday he showed something to us. So I’m not quite sure.
170 00:18:32.350 ⇒ 00:18:36.550 Luke Daque: Yeah, I think it should be a clay table. Wait, let me check.
171 00:18:45.340 ⇒ 00:18:48.220 Luke Daque: Yeah, I don’t. I don’t see it in our chat anymore. But
172 00:18:48.530 ⇒ 00:18:52.766 Luke Daque: but yeah, he did share, like some sort of play table that
173 00:18:54.390 ⇒ 00:18:58.300 Luke Daque: We would be potentially using. But yeah, that’s probably
174 00:19:00.280 ⇒ 00:19:08.059 Luke Daque: yeah, we’ll have to. I I guess we can set another call with Ryan on that. So we can have that we can start later on that.
175 00:19:10.210 ⇒ 00:19:11.110 Amber Lin: Okay.
176 00:19:12.330 ⇒ 00:19:13.510 Amber Lin: Finally.
177 00:19:16.940 ⇒ 00:19:21.550 Luke Daque: We need. Do you need Ryan on the call, like in future calls like.
178 00:19:21.801 ⇒ 00:19:25.570 Amber Lin: Good point. I didn’t know he was on this project. I’ll go. I’ll add him.
179 00:19:28.140 ⇒ 00:19:30.239 Luke Daque: I believe he’s like more familiar.
180 00:19:30.510 ⇒ 00:19:31.590 Amber Lin: Let’s play.
181 00:19:32.200 ⇒ 00:19:36.630 Amber Lin: Yeah, totally one for a.
182 00:19:40.310 ⇒ 00:19:46.800 Robert Tseng: So if I can just like share my screen, and then I’m gonna go and jump off.
183 00:19:47.430 ⇒ 00:19:57.339 Robert Tseng: Okay. So Jenna has like, put together, this scraped leads demo thing before. Like to me, this is like our play table. Right? We just come here. We have different workbooks.
184 00:20:00.280 ⇒ 00:20:06.070 Robert Tseng: yeah, we’ve we’ve had some of this stuff before. So you can go in here and just like, click around and look.
185 00:20:09.310 ⇒ 00:20:18.659 Robert Tseng: yeah. And then any of these, you can add enrichment. And like, I know how claim like looks like. So not asking like a complete start from scratch. But I’m
186 00:20:19.260 ⇒ 00:20:24.050 Robert Tseng: like, I’m wanting like a okay. Maybe I’ll just make myself like a
187 00:20:26.930 ⇒ 00:20:36.649 Robert Tseng: we set up. We set up a new workbook that’s just for for this particular workflow. You can reference all these other things to learn like, what does the final state look like?
188 00:20:37.570 ⇒ 00:20:38.230 Luke Daque: Bye.
189 00:20:38.230 ⇒ 00:20:42.037 Robert Tseng: Like if I look at marketing analytics or personal injury firms, I think.
190 00:20:42.840 ⇒ 00:20:48.040 Robert Tseng: here we had set up some, you know, stuff here on like
191 00:20:49.354 ⇒ 00:21:09.655 Robert Tseng: I provided the Csv. Then they went into this custom table, and then we went and we looked up the companies that match those tables. We wrote stuff from these different softwares into it, and then they were added into the Hey Reach campaign. And I I went in. I did that, and they did. So it’s more for you guys to get familiar on how to do this.
192 00:21:11.020 ⇒ 00:21:19.020 Robert Tseng: yeah. So I I don’t think we’re starting from scratch here like, I actually feel like we’re probably further along than what we’re saying on this call.
193 00:21:20.160 ⇒ 00:21:20.810 Amber Lin: Yeah.
194 00:21:20.810 ⇒ 00:21:21.530 Luke Daque: Okay.
195 00:21:21.530 ⇒ 00:21:22.300 Amber Lin: Awesome.
196 00:21:24.140 ⇒ 00:21:28.410 Amber Lin: Marion, how much time do you have? Do you have capacity for this.
197 00:21:30.060 ⇒ 00:21:31.410 Mariane Cequina: For the clay.
198 00:21:31.770 ⇒ 00:21:32.510 Amber Lin: Yes.
199 00:21:33.550 ⇒ 00:21:42.020 Mariane Cequina: I’m actually the the last time that we I I had a conversation with Ryan. We actually have limited information.
200 00:21:42.310 ⇒ 00:21:43.179 Amber Lin: Oh, okay.
201 00:21:43.796 ⇒ 00:21:45.300 Mariane Cequina: But I am. I’m.
202 00:21:46.580 ⇒ 00:21:50.379 Mariane Cequina: I’m actually open to work this this for this project, though.
203 00:21:51.110 ⇒ 00:21:52.850 Amber Lin: I see. Okay.
204 00:21:54.200 ⇒ 00:22:12.939 Amber Lin: Luke Marianne, do you guys, do you guys think who will be the best to take on this clay one? I don’t think it will take a long time. We’ll have a lot of existing clay tables that we can just copy from and then adjust, based on our go to market notion, Doc. Which one do you want to take on this task? And
205 00:22:13.690 ⇒ 00:22:17.449 Amber Lin: because I don’t know how much capacity Ryan has.
206 00:22:23.030 ⇒ 00:22:31.539 Robert Tseng: I would say Marianne should like be doing that the clay stuff Luke should probably, or Luke Ryan should probably
207 00:22:32.110 ⇒ 00:22:34.619 Robert Tseng: figuring out like how to like
208 00:22:35.150 ⇒ 00:22:37.419 Robert Tseng: like what? What like, how do we
209 00:22:38.474 ⇒ 00:22:45.179 Robert Tseng: feel like Luke should understand the ingestion problem like? And then Marianne can build out these things like this is just like.
210 00:22:45.940 ⇒ 00:22:47.179 Amber Lin: Hmm awesome.
211 00:22:47.180 ⇒ 00:22:47.720 Robert Tseng: Yeah.
212 00:22:49.300 ⇒ 00:22:50.190 Amber Lin: Yeah, lovely.
213 00:22:50.190 ⇒ 00:22:51.200 Luke Daque: Okay. Let me check.
214 00:22:51.200 ⇒ 00:22:53.479 Robert Tseng: Seems like Jana has done this before.
215 00:22:53.740 ⇒ 00:23:07.329 Robert Tseng: kind of so I think maybe, she said, running everything by on the Ryan like we can. We can have her do some knowledge transfer here. And then, like, you know, we can review some of these workbooks. Figure out how they were set up.
216 00:23:08.125 ⇒ 00:23:08.740 Robert Tseng: Yeah.
217 00:23:09.610 ⇒ 00:23:10.400 Amber Lin: Awesome.
218 00:23:11.670 ⇒ 00:23:15.559 Amber Lin: That’s great. I think that’s a that’s a good 1st step. We’ll just.
219 00:23:16.153 ⇒ 00:23:18.499 Amber Lin: I know, Robert, you have to jump so.
220 00:23:18.500 ⇒ 00:23:18.880 Robert Tseng: Got a joke.
221 00:23:18.880 ⇒ 00:23:24.469 Amber Lin: Cool, and then Web put intake, mostly just understanding how we want to do it.
222 00:23:24.780 ⇒ 00:23:29.380 Amber Lin: And, Robert, you can jump back and we can figure out the rest.
223 00:23:29.960 ⇒ 00:23:31.699 Amber Lin: Okay, he already jumped.
224 00:23:32.160 ⇒ 00:23:33.840 Amber Lin: That’s that’s okay.
225 00:23:34.680 ⇒ 00:23:35.620 Amber Lin: So.
226 00:23:35.620 ⇒ 00:23:41.699 Luke Daque: Yeah, I just forwarded it to Robert as well. We have a tier list for I mean.
227 00:23:42.570 ⇒ 00:23:50.290 Luke Daque: yeah for Clay, because, like the the we are doing. You’re using the starter pack at the moment, and it’s like limited.
228 00:23:50.430 ⇒ 00:23:53.650 Luke Daque: We can’t use web hooks in the starter pack so.
229 00:23:53.830 ⇒ 00:23:57.240 Luke Daque: But the next tier is like $200.
230 00:23:57.240 ⇒ 00:23:57.560 Amber Lin: Oh!
231 00:23:57.560 ⇒ 00:24:01.330 Luke Daque: It’s quite expensive per,
232 00:24:02.270 ⇒ 00:24:09.479 Luke Daque: yeah. And that’s where we can like either integrate with Api or like, do use web hooks and stuff like that.
233 00:24:09.480 ⇒ 00:24:11.710 Luke Daque: I see. I see, yeah.
234 00:24:11.710 ⇒ 00:24:12.210 Amber Lin: Cool.
235 00:24:12.456 ⇒ 00:24:14.920 Luke Daque: Let me let me loop you into this as well.
236 00:24:24.490 ⇒ 00:24:25.220 Luke Daque: Okay.
237 00:24:28.210 ⇒ 00:24:31.880 Amber Lin: Oh, did you send it?
238 00:24:33.518 ⇒ 00:24:35.490 Luke Daque: Are you in the Sales Channel.
239 00:24:35.490 ⇒ 00:24:37.220 Amber Lin: Yeah. Okay, let me go. Check.
240 00:24:38.450 ⇒ 00:24:40.550 Amber Lin: Oh, sales.
241 00:24:40.550 ⇒ 00:24:46.040 Luke Daque: I sent it in the in the slack sales channel. I looped you into the thread.
242 00:24:46.850 ⇒ 00:24:48.620 Amber Lin: Oh, in the thread I see.
243 00:24:48.620 ⇒ 00:24:49.230 Luke Daque: Yeah.
244 00:24:54.690 ⇒ 00:24:59.730 Amber Lin: okay, I will create a new project.
245 00:25:00.580 ⇒ 00:25:03.830 Amber Lin: We have a new channel based on this.
246 00:25:05.200 ⇒ 00:25:12.200 Amber Lin: Open. And yeah, okay, sounds good.
247 00:25:12.560 ⇒ 00:25:18.150 Amber Lin: So we’ll just explore different ways, like maybe, without having to pay, etc.
248 00:25:19.380 ⇒ 00:25:28.080 Luke Daque: Yeah, I think that’s what Ryan also mentioned, like, maybe we can explore something else.
249 00:25:28.810 ⇒ 00:25:29.200 Amber Lin: Okay.
250 00:25:29.200 ⇒ 00:25:32.660 Luke Daque: Yeah, like, yeah, it’s quite expensive.
251 00:25:32.850 ⇒ 00:25:33.700 Luke Daque: Clay.
252 00:25:34.240 ⇒ 00:25:34.990 Luke Daque: It’s quite exciting.
253 00:25:36.130 ⇒ 00:25:37.159 Amber Lin: I see.
254 00:25:39.419 ⇒ 00:26:04.019 Amber Lin: Yes, we know what we want for today. We want the clay tables. So I’ll schedule a meeting for us tomorrow, and hopefully, we have a clay table set up that we can get feedback on from Robert. Marianne doesn’t have to be perfect. It’s we’ll just have something you can just use AI. It’s just something Robert can look at to say, Okay, I like this, I don’t like this, doesn’t need to be perfect.
255 00:26:04.090 ⇒ 00:26:21.350 Amber Lin: And then for like, if you have some time to investigate. Okay, what are the different options we need to do? We can figure out how to do the ingestion. And like, what kind of information do we need, or what who we need help
256 00:26:21.580 ⇒ 00:26:25.819 Amber Lin: from with, like, maybe it’s Ryan. Maybe it’s Casey.
257 00:26:27.020 ⇒ 00:26:32.049 Amber Lin: maybe it’s Robert himself or me, so we’ll define that for today.
258 00:26:32.290 ⇒ 00:26:35.880 Amber Lin: and then I will. We can meet again tomorrow.
259 00:26:38.480 ⇒ 00:26:39.339 Luke Daque: Makes sense.
260 00:26:39.920 ⇒ 00:26:42.240 Amber Lin: Yeah. Do you guys need
261 00:26:43.900 ⇒ 00:26:49.989 Amber Lin: anything any more questions on the project? Or is there anything that’s not clear.
262 00:26:52.790 ⇒ 00:26:57.009 Mariane Cequina: For me the setting up of the play, should I be invited on it?
263 00:26:58.070 ⇒ 00:27:00.730 Amber Lin: Oh, are you in play now?
264 00:27:01.010 ⇒ 00:27:02.630 Mariane Cequina: No, I think I’m not.
265 00:27:02.630 ⇒ 00:27:06.870 Amber Lin: I see who can give you access to play. Look! Do you know.
266 00:27:07.120 ⇒ 00:27:10.919 Luke Daque: I think it was Utam who sent gave me access, so maybe we can ask him.
267 00:27:11.320 ⇒ 00:27:11.950 Mariane Cequina: Or maybe.
268 00:27:11.950 ⇒ 00:27:12.460 Amber Lin: Hold on!
269 00:27:12.460 ⇒ 00:27:13.830 Luke Daque: Even Robert has.
270 00:27:14.510 ⇒ 00:27:15.200 Amber Lin: Oh, okay.
271 00:27:15.200 ⇒ 00:27:18.699 Luke Daque: Wait, but I can also check if I have admin access.
272 00:27:18.700 ⇒ 00:27:19.240 Amber Lin: Yeah.
273 00:27:19.240 ⇒ 00:27:20.960 Luke Daque: Or something.
274 00:27:21.250 ⇒ 00:27:21.960 Amber Lin: Oops!
275 00:27:27.350 ⇒ 00:27:30.020 Luke Daque: Yeah, I have. So I can just and.
276 00:27:33.770 ⇒ 00:27:38.370 Mariane Cequina: And then do Ryan have, like all the information about this as well.
277 00:27:38.670 ⇒ 00:27:41.630 Amber Lin: Maybe you might have to chat with him about it.
278 00:27:42.430 ⇒ 00:27:46.252 Amber Lin: Chat with Brian if he doesn’t have information.
279 00:27:47.130 ⇒ 00:27:59.610 Amber Lin: What’s his name? Janna maybe has some information and then Robert has information. But I think we have all we need in all the existing play tables and the go to market notion. Talk.
280 00:28:00.960 ⇒ 00:28:03.299 Luke Daque: You can basically just copy anything.
281 00:28:03.300 ⇒ 00:28:06.980 Amber Lin: Yeah, just copy it and make any adjustments needed.
282 00:28:07.450 ⇒ 00:28:08.070 Amber Lin: How do we.
283 00:28:08.070 ⇒ 00:28:08.600 Mariane Cequina: And.
284 00:28:09.270 ⇒ 00:28:12.500 Luke Daque: Oh, I can invite you! Let me let me send that invite.
285 00:28:12.500 ⇒ 00:28:14.050 Amber Lin: Hmm awesome.
286 00:28:18.570 ⇒ 00:28:23.259 Luke Daque: Just sent you an invite. Ryan should receive an email. Yes.
287 00:28:23.260 ⇒ 00:28:25.110 Mariane Cequina: Oh, yeah, yeah, I can see it now.
288 00:28:27.050 ⇒ 00:28:27.890 Luke Daque: Nice.
289 00:28:54.750 ⇒ 00:29:00.140 Mariane Cequina: Okay, I can see it now. So I have another question, what should I be looking in the folder again?
290 00:29:02.160 ⇒ 00:29:02.790 Amber Lin: Hmm.
291 00:29:03.410 ⇒ 00:29:04.740 Mariane Cequina: Here in the clay.
292 00:29:06.930 ⇒ 00:29:07.360 Amber Lin: Oh, yeah.
293 00:29:07.360 ⇒ 00:29:09.070 Luke Daque: Folder that that’s like.
294 00:29:09.070 ⇒ 00:29:10.890 Mariane Cequina: Brainforge seals. Is that correct?
295 00:29:11.810 ⇒ 00:29:14.580 Luke Daque: The brain forge sales is what I created.
296 00:29:15.033 ⇒ 00:29:17.940 Luke Daque: So maybe we can create the tables there. Yeah.
297 00:29:19.270 ⇒ 00:29:23.149 Luke Daque: And then we we just need to copy whatever tables
298 00:29:23.400 ⇒ 00:29:26.699 Luke Daque: are from the other workspaces, or something.
299 00:30:41.230 ⇒ 00:30:44.850 Mariane Cequina: I think it is the Jana test. Right? The scrap leads. Okay, I can see it now
300 00:30:45.150 ⇒ 00:30:46.690 Mariane Cequina: and then. What should I.
301 00:30:46.690 ⇒ 00:30:47.070 Luke Daque: Yeah.
302 00:30:47.070 ⇒ 00:31:04.936 Mariane Cequina: What should I do on this one again? Because a lot of ever when we had a conversation with Ryan, because you can send me a message that we should. We could ask him, but he’s also like he’s not really quite sure as well, like like all of us are actually have limited
303 00:31:05.540 ⇒ 00:31:11.449 Mariane Cequina: information. So I’m not quite sure how I can like, set this up. Yeah, like the context, I’d say, Yeah.
304 00:31:11.760 ⇒ 00:31:13.090 Amber Lin: Huh? What?
305 00:31:13.800 ⇒ 00:31:20.979 Amber Lin: What is the more specific question on the context? I I also just join in. But I think I can answer it a little bit.
306 00:31:22.209 ⇒ 00:31:36.399 Mariane Cequina: so in my case, so I will be, do. I am assigned for the setting up the play table, right? So how can I? What should I do here? Because I can? What I can see right now is the the table, the expo like expo west, so correct.
307 00:31:36.700 ⇒ 00:31:37.240 Amber Lin: Oh!
308 00:31:37.410 ⇒ 00:31:42.490 Mariane Cequina: So what should I like? Exactly? Should I be like like my task here.
309 00:31:44.980 ⇒ 00:31:52.890 Amber Lin: So I think what we want is a new clay table with different columns.
310 00:31:53.270 ⇒ 00:31:54.690 Mariane Cequina: And.
311 00:31:55.230 ⇒ 00:32:05.959 Amber Lin: An extra step would be to give it a few sample data sets. But ultimately the bare. The basic requirements is that we have a new clay table with
312 00:32:06.600 ⇒ 00:32:08.090 Amber Lin: the different columns.
313 00:32:08.920 ⇒ 00:32:19.220 Amber Lin: And how we want to do it is that we can copy and paste previous table columns.
314 00:32:19.470 ⇒ 00:32:22.270 Mariane Cequina: And then modify it.
315 00:32:22.400 ⇒ 00:32:28.390 Amber Lin: Based on the go to market documentation that we have.
316 00:32:28.560 ⇒ 00:32:31.379 Amber Lin: So you have access to the notion, Doc, right?
317 00:32:31.920 ⇒ 00:32:33.199 Mariane Cequina: Oh, yeah. Yeah. Yeah.
318 00:32:33.200 ⇒ 00:32:36.610 Amber Lin: Yeah. I think a good
319 00:32:37.440 ⇒ 00:32:48.170 Amber Lin: process of action would be copy and paste the clay table columns from a few previous tables into Chatgvt.
320 00:32:48.470 ⇒ 00:32:56.499 Amber Lin: and then also paste in the go to market. Notion, Doc. Just copy and paste all the content into the
321 00:32:56.640 ⇒ 00:33:01.809 Amber Lin: prompt as well, and just ask it, hey? I need to create a new play table.
322 00:33:02.020 ⇒ 00:33:07.719 Amber Lin: What should I do? You can just copy and paste the ticket requirements.
323 00:33:10.580 ⇒ 00:33:19.390 Amber Lin: That so ticket number 23 sales 23, and you can just go from there.
324 00:33:20.100 ⇒ 00:33:21.710 Mariane Cequina: Okay, okay, got it.
325 00:33:21.710 ⇒ 00:33:26.279 Amber Lin: Yeah. Trust. Gpt will give you a much more detailed direction.
326 00:33:26.810 ⇒ 00:33:27.929 Mariane Cequina: Okay. Okay.
327 00:33:27.930 ⇒ 00:33:33.430 Amber Lin: Yeah, I will edit the tickets a little bit more.
328 00:33:34.340 ⇒ 00:33:44.839 Amber Lin: And this is also a big like, oh, what is going on? So we’ll figure it out together. I think today we’ll just do these like 2 2 simple tasks that will go from there.
329 00:33:45.410 ⇒ 00:33:46.210 Mariane Cequina: Okay.
330 00:33:46.210 ⇒ 00:33:50.880 Amber Lin: Yeah, is this a good time to meet for you guys?
331 00:33:51.160 ⇒ 00:33:54.110 Amber Lin: Actually, I’ll need to look at Robert’s time. So.
332 00:33:55.210 ⇒ 00:33:57.759 Luke Daque: Yeah, I think Robert’s more like.
333 00:33:57.760 ⇒ 00:33:58.410 Amber Lin: Okay.
334 00:33:59.550 ⇒ 00:34:01.640 Luke Daque: Business. So yeah, you can just check.
335 00:34:02.470 ⇒ 00:34:03.590 Amber Lin: Sounds good.
336 00:34:07.900 ⇒ 00:34:11.900 Amber Lin: Invite Ryan as well.
337 00:34:11.909 ⇒ 00:34:12.639 Luke Daque: Yeah.
338 00:34:13.250 ⇒ 00:34:13.989 Amber Lin: Cool.
339 00:34:14.719 ⇒ 00:34:15.409 Amber Lin: All right.
340 00:34:16.170 ⇒ 00:34:25.420 Amber Lin: I will make it like an hour or 30 min earlier than this awesome.
341 00:34:26.639 ⇒ 00:34:27.639 Luke Daque: Sounds good.
342 00:34:28.290 ⇒ 00:34:31.809 Amber Lin: Okay, thank you for the call.
343 00:34:32.530 ⇒ 00:34:33.520 Luke Daque: Thank you. Guys.
344 00:34:33.710 ⇒ 00:34:35.610 Mariane Cequina: Thank you. Thank you. It’s more clear now.
345 00:34:36.050 ⇒ 00:34:37.480 Luke Daque: Bye, bye.