Meeting Title: Sales-Automation-Weekly Date: 2024-09-03 Meeting participants: Uttam Kumaran, Patrick Trainer, Abigail Zhao
WEBVTT
1 00:00:46.210 ⇒ 00:00:46.940 Patrick Trainer: A.
2 00:00:47.480 ⇒ 00:00:48.380 Abigail Zhao: Hi.
3 00:00:48.980 ⇒ 00:00:49.750 Patrick Trainer: What’s going on.
4 00:00:51.391 ⇒ 00:00:53.399 Abigail Zhao: Not much. I’m doing okay.
5 00:00:53.410 ⇒ 00:00:54.450 Abigail Zhao: Up with you.
6 00:00:55.630 ⇒ 00:00:56.830 Patrick Trainer: Same same
7 00:00:58.230 ⇒ 00:01:00.119 Patrick Trainer: Yup yup doing that.
8 00:01:01.780 ⇒ 00:01:02.780 Uttam Kumaran: How’s cool?
9 00:01:03.550 ⇒ 00:01:05.500 Abigail Zhao: It’s going okay. So far.
10 00:01:05.630 ⇒ 00:01:10.130 Abigail Zhao: I mean, it was only like the 1st week, so like, not nothing too much yet. But
11 00:01:10.240 ⇒ 00:01:12.759 Abigail Zhao: I feel like. I can anticipate this
12 00:01:12.950 ⇒ 00:01:14.490 Abigail Zhao: semester being
13 00:01:15.110 ⇒ 00:01:16.220 Abigail Zhao: a bit
14 00:01:16.350 ⇒ 00:01:18.150 Abigail Zhao: crazy already, but it’s.
15 00:01:18.150 ⇒ 00:01:18.960 Uttam Kumaran: Oh, yeah.
16 00:01:18.960 ⇒ 00:01:19.950 Abigail Zhao: Yeah.
17 00:01:21.640 ⇒ 00:01:23.670 Patrick Trainer: This is your what Junior Year.
18 00:01:23.670 ⇒ 00:01:24.330 Abigail Zhao: Yeah.
19 00:01:25.090 ⇒ 00:01:26.410 Patrick Trainer: I think that was
20 00:01:27.310 ⇒ 00:01:29.920 Patrick Trainer: honestly like the most like taxing year.
21 00:01:30.110 ⇒ 00:01:30.780 Abigail Zhao: Yeah.
22 00:01:30.890 ⇒ 00:01:32.560 Abigail Zhao: Great. Looking forward.
23 00:01:32.560 ⇒ 00:01:34.360 Patrick Trainer: Yeah, I think, because, like
24 00:01:34.930 ⇒ 00:01:36.490 Patrick Trainer: freshman and sophomore.
25 00:01:36.930 ⇒ 00:01:44.320 Patrick Trainer: you’re mostly getting away like the the core classes, right? And then some of your like Prereqs, and then
26 00:01:45.111 ⇒ 00:01:50.299 Patrick Trainer: Junior year you get into like the actual meat of everything.
27 00:01:50.390 ⇒ 00:01:55.090 Patrick Trainer: and then senior is just like Capstone, and you should know everything by then.
28 00:01:56.040 ⇒ 00:01:56.470 Abigail Zhao: Yeah.
29 00:01:58.720 ⇒ 00:01:59.270 Patrick Trainer: The
30 00:02:01.180 ⇒ 00:02:02.270 Patrick Trainer: that’ll be fun.
31 00:02:05.150 ⇒ 00:02:10.110 Uttam Kumaran: Cool. Today, we want to walk through some stuff in Apollo, Abigail. Maybe you can walk
32 00:02:10.880 ⇒ 00:02:13.839 Uttam Kumaran: through stuff. And then we could talk about Hubspot.
33 00:02:14.190 ⇒ 00:02:14.860 Uttam Kumaran: Sure.
34 00:02:16.243 ⇒ 00:02:17.710 Abigail Zhao: Yeah, okay.
35 00:02:25.220 ⇒ 00:02:25.880 Abigail Zhao: But
36 00:02:35.690 ⇒ 00:02:36.550 Abigail Zhao: okay.
37 00:02:43.420 ⇒ 00:02:44.350 Abigail Zhao: okay.
38 00:02:44.580 ⇒ 00:02:46.459 Abigail Zhao: can you all see this or no?
39 00:02:46.820 ⇒ 00:02:47.540 Patrick Trainer: Yeah.
40 00:02:47.540 ⇒ 00:02:54.411 Abigail Zhao: Okay? So yeah, I just have it saved under here. If any of you guys also want to take a look at it.
41 00:02:55.090 ⇒ 00:02:59.700 Abigail Zhao: it’s pretty straightforward. I just like, put in a few
42 00:02:59.960 ⇒ 00:03:05.400 Abigail Zhao: of these filters and signals that we discussed. I mainly focused on
43 00:03:05.460 ⇒ 00:03:14.329 Abigail Zhao: these 2 industries cause I found that when I added, like related ones, it did not change it at all, so I just kind of left it
44 00:03:14.825 ⇒ 00:03:20.670 Abigail Zhao: as did these main 2, which I think were the higher level industries that we discussed.
45 00:03:22.230 ⇒ 00:03:27.981 Abigail Zhao: but yeah, like, I said, pretty straightforward. I kept the location to the United States as well,
46 00:03:28.700 ⇒ 00:03:32.449 Abigail Zhao: yeah, just cause I feel like that just made sense. But
47 00:03:33.180 ⇒ 00:03:37.480 Abigail Zhao: yeah. So job titles, I put the higher level up
48 00:03:37.895 ⇒ 00:03:42.520 Abigail Zhao: positions as well with. I included manager, just because I think that
49 00:03:43.230 ⇒ 00:03:45.679 Abigail Zhao: opened up more
50 00:03:47.149 ⇒ 00:03:56.969 Abigail Zhao: like people in terms of like different companies and stuff, because a lot of them, I found, didn’t have someone like directly with this.
51 00:03:56.980 ⇒ 00:04:07.740 Abigail Zhao: with these like higher positions. So I just included manager as well. But we can remove that if we need to. And then revenue was the like key
52 00:04:08.290 ⇒ 00:04:12.010 Abigail Zhao: range of the higher point system.
53 00:04:12.060 ⇒ 00:04:16.530 Abigail Zhao: And then funding, we discussed like series C, and above, I think so.
54 00:04:16.740 ⇒ 00:04:26.520 Abigail Zhao: I just checked off all those. And then signals were the 2 that we discussed as well. And then it generated a list of 930 emails cool.
55 00:04:27.460 ⇒ 00:04:28.390 Uttam Kumaran: So
56 00:04:28.610 ⇒ 00:04:31.510 Uttam Kumaran: we had recent funding, rapid growth.
57 00:04:33.250 ⇒ 00:04:34.329 Uttam Kumaran: So let’s
58 00:04:34.370 ⇒ 00:04:36.879 Uttam Kumaran: so do. Do you have a sense of like, what
59 00:04:36.970 ⇒ 00:04:40.350 Uttam Kumaran: like is there any overall theme in the
60 00:04:40.360 ⇒ 00:04:44.420 Uttam Kumaran: types of companies? Or they’re all just like a little bit all over the place.
61 00:04:45.340 ⇒ 00:04:47.790 Abigail Zhao: It is kind of like
62 00:04:47.860 ⇒ 00:04:51.369 Abigail Zhao: a little bit all over the place, in my opinion.
63 00:04:52.170 ⇒ 00:04:57.070 Abigail Zhao: yeah, obviously, I wasn’t. I didn’t like look into, like every single company that came up, but
64 00:04:57.160 ⇒ 00:04:59.430 Abigail Zhao: from what I gauged it
65 00:04:59.490 ⇒ 00:05:02.800 Abigail Zhao: did seem like a little bit random.
66 00:05:02.990 ⇒ 00:05:06.900 Uttam Kumaran: Okay? Cause? Yeah, some of these look like these are like.
67 00:05:06.970 ⇒ 00:05:10.670 Uttam Kumaran: probably, like, yeah, series C or Csd startups like, Harvey.
68 00:05:10.730 ⇒ 00:05:14.429 Uttam Kumaran: just raise series. B, superhuman is like, probably like, series. T,
69 00:05:15.179 ⇒ 00:05:16.769 Uttam Kumaran: yeah, okay, cool.
70 00:05:17.380 ⇒ 00:05:24.264 Uttam Kumaran: So the thing is is like, Will, will you get stuff outside this funding range or no
71 00:05:25.320 ⇒ 00:05:26.460 Uttam Kumaran: meaning like.
72 00:05:28.800 ⇒ 00:05:29.890 Abigail Zhao: I
73 00:05:31.490 ⇒ 00:05:33.139 Abigail Zhao: like, outside of this funding.
74 00:05:33.140 ⇒ 00:05:43.470 Uttam Kumaran: For example, like the folks that are raising like. For example, let’s talk about a company that’s like, let’s say they’re just a big private company like Stella, who is one of our clients.
75 00:05:43.470 ⇒ 00:05:43.790 Abigail Zhao: Yeah.
76 00:05:43.790 ⇒ 00:05:52.120 Uttam Kumaran: Like, what would I want to know what they would fall under like? I assume they fall under like other private equity, right like I I guess I just don’t want to rule those.
77 00:05:52.860 ⇒ 00:05:54.070 Uttam Kumaran: Folks out.
78 00:05:55.880 ⇒ 00:05:56.630 Patrick Trainer: Make that like.
79 00:05:56.630 ⇒ 00:05:57.680 Uttam Kumaran: Separate.
80 00:05:57.850 ⇒ 00:06:02.410 Patrick Trainer: I would probably make that like a separate filter in and of itself, just because, like.
81 00:06:03.320 ⇒ 00:06:07.479 Patrick Trainer: like, if you think of these as like a sequel. Query right like
82 00:06:07.550 ⇒ 00:06:12.640 Patrick Trainer: this is like a series, CDEF is like in A, where clause
83 00:06:14.880 ⇒ 00:06:16.080 Patrick Trainer: and then.
84 00:06:16.410 ⇒ 00:06:21.799 Patrick Trainer: if you have another one like if we want to make a list for like private equity.
85 00:06:21.800 ⇒ 00:06:22.940 Uttam Kumaran: Oh, I see!
86 00:06:22.940 ⇒ 00:06:26.524 Patrick Trainer: Then, yeah, then, just like, create a campaign for private equity
87 00:06:26.880 ⇒ 00:06:29.510 Patrick Trainer: that could honestly probably be
88 00:06:29.730 ⇒ 00:06:32.990 Patrick Trainer: said the same, for, like CDE, and F
89 00:06:33.486 ⇒ 00:06:38.079 Patrick Trainer: I mean, if we even want to, or if we want to go that route.
90 00:06:40.330 ⇒ 00:06:41.240 Patrick Trainer: so you’re saying.
91 00:06:41.622 ⇒ 00:06:43.150 Uttam Kumaran: One list for like.
92 00:06:43.850 ⇒ 00:06:48.499 Uttam Kumaran: I guess what I’m trying to say. If you want to do one, you want to do like a list to campaign
93 00:06:48.690 ⇒ 00:06:50.999 Uttam Kumaran: like, how is the mapping gonna work.
94 00:06:52.620 ⇒ 00:06:55.131 Patrick Trainer: Or I guess, like what I’m saying is like
95 00:06:55.700 ⇒ 00:06:58.690 Patrick Trainer: to get the most signal like. So we there’s
96 00:06:59.380 ⇒ 00:07:11.870 Patrick Trainer: 800 private equity. And then there’s like, I think, another 800 series. C, so like, that’s gonna create like a lot of noise to that signal, right? So
97 00:07:12.450 ⇒ 00:07:15.870 Patrick Trainer: if we want to keep it narrowed down.
98 00:07:18.330 ⇒ 00:07:19.690 Patrick Trainer: We should
99 00:07:20.230 ⇒ 00:07:21.380 Patrick Trainer: probably like.
100 00:07:21.800 ⇒ 00:07:26.829 Patrick Trainer: I mean, like, this is, this is like, I don’t think there’s like a best
101 00:07:26.920 ⇒ 00:07:30.780 Patrick Trainer: way to do this, but that may just be able to
102 00:07:32.650 ⇒ 00:07:37.980 Patrick Trainer: like. We have our base filter right, which is like on revenue. And then
103 00:07:39.426 ⇒ 00:07:43.590 Patrick Trainer: job title. So like, that’s the common thing between everything.
104 00:07:43.680 ⇒ 00:07:50.920 Patrick Trainer: And then, like as we want to filter farther down. Maybe that’s when we create these different lists.
105 00:07:53.510 ⇒ 00:07:57.369 Uttam Kumaran: Yeah, I mean, I think it would be good to have a theme. I I would say we start with
106 00:07:57.660 ⇒ 00:07:59.240 Uttam Kumaran: the campaign
107 00:08:00.050 ⇒ 00:08:06.259 Uttam Kumaran: theme and then fill it with the right people. And that way there’s some link, for example, these 1,000.
108 00:08:06.270 ⇒ 00:08:12.449 Uttam Kumaran: So like, let’s walk through. Let’s walk through just for this pat like, if you, if we take this list, send to Hubspot.
109 00:08:12.940 ⇒ 00:08:15.769 Uttam Kumaran: We then get a ranking basically of like.
110 00:08:15.770 ⇒ 00:08:16.410 Patrick Trainer: Yeah, that’s true.
111 00:08:16.410 ⇒ 00:08:22.500 Uttam Kumaran: Out of the 1,000. Here’s like. So then, what we what ideally like, what’s the next step after that, where we
112 00:08:22.730 ⇒ 00:08:24.750 Uttam Kumaran: we take like the top
113 00:08:24.970 ⇒ 00:08:33.060 Uttam Kumaran: 200, and then we add them to the campaign, like, I guess, is that is that the action cause? Then what I’ll what we’ll think about is like.
114 00:08:33.289 ⇒ 00:08:34.179 Uttam Kumaran: there’s
115 00:08:34.880 ⇒ 00:08:37.560 Uttam Kumaran: there is a we start with the campaign idea.
116 00:08:37.870 ⇒ 00:08:41.560 Uttam Kumaran: right? We form like we wanna do a campaign around these targets.
117 00:08:41.650 ⇒ 00:08:49.070 Uttam Kumaran: We use Apollo to get the widest swath. We use Hubspot to filter that even lower, and then those get set.
118 00:08:49.070 ⇒ 00:08:52.480 Patrick Trainer: Right? Right? Right? Right? Right? Right? Because.
119 00:08:52.600 ⇒ 00:08:56.780 Patrick Trainer: yeah, because, like once, they’re in Hubspot, that’s when we start scoring them.
120 00:08:57.040 ⇒ 00:08:59.680 Patrick Trainer: And like you said, yeah, we’ll rank them.
121 00:09:00.080 ⇒ 00:09:07.430 Patrick Trainer: And then and then, essentially, it’s once they’re in the campaign. That campaign’s all going to map to different types of marketing.
122 00:09:07.750 ⇒ 00:09:10.320 Patrick Trainer: Yeah, whatever. And then.
123 00:09:10.620 ⇒ 00:09:17.699 Patrick Trainer: like of those that’s like, that’s where that outreach or like contact between brain forge and whatever
124 00:09:17.900 ⇒ 00:09:22.569 Patrick Trainer: company is ranked or like in rank from this list.
125 00:09:22.850 ⇒ 00:09:25.409 Patrick Trainer: Those are the people that we are contacting.
126 00:09:25.800 ⇒ 00:09:26.370 Uttam Kumaran: Okay.
127 00:09:27.000 ⇒ 00:09:29.919 Patrick Trainer: Or interacting with, or targeting.
128 00:09:30.520 ⇒ 00:09:33.629 Uttam Kumaran: So let’s just consider the theme of this like.
129 00:09:34.130 ⇒ 00:09:35.900 Uttam Kumaran: let’s just consider these
130 00:09:35.940 ⇒ 00:09:37.400 Uttam Kumaran: like startups.
131 00:09:37.950 ⇒ 00:09:39.229 Patrick Trainer: Late, stage, startup.
132 00:09:39.230 ⇒ 00:09:40.780 Uttam Kumaran: Late stage startups.
133 00:09:41.010 ⇒ 00:09:47.530 Uttam Kumaran: So can we walk through the filters again, Abigail. So we have. We have these filters on funding.
134 00:09:49.720 ⇒ 00:10:04.680 Uttam Kumaran: Job titles. Okay, that makes sense. Those are people filters. Location makes sense. So industries, I guess what we’re gonna what let’s, we’re just gonna do no industry, I guess what? Yeah, let I do not. I think, meaning, these are just
135 00:10:04.810 ⇒ 00:10:06.689 Uttam Kumaran: finance. And it.
136 00:10:09.390 ⇒ 00:10:10.289 Uttam Kumaran: yeah, there’s also.
137 00:10:10.290 ⇒ 00:10:20.540 Abigail Zhao: I like. They only have, like a set like number of industries I could have chosen from because my input in my own thing it does not like register as anything.
138 00:10:20.540 ⇒ 00:10:22.400 Uttam Kumaran: Yeah, yeah, so I.
139 00:10:22.400 ⇒ 00:10:27.440 Patrick Trainer: I think that’s actually going to be beneficial, because, like in Hubspot, when we’re
140 00:10:28.110 ⇒ 00:10:37.989 Patrick Trainer: like parsing for like job title, for example, like, I imagine it’s like a finite set of of job titles, right? There’s like manager.
141 00:10:38.280 ⇒ 00:10:41.120 Patrick Trainer: intern engineer. But there’s not like
142 00:10:42.050 ⇒ 00:10:43.669 Patrick Trainer: data, analytics.
143 00:10:44.160 ⇒ 00:10:46.200 Patrick Trainer: professional or something like some.
144 00:10:46.200 ⇒ 00:10:46.629 Uttam Kumaran: It! Up!
145 00:10:46.630 ⇒ 00:10:50.789 Patrick Trainer: That’s not going to be there. So in in Hubspot, when it’s parsing that
146 00:10:50.850 ⇒ 00:10:51.860 Patrick Trainer: it’s like
147 00:10:52.120 ⇒ 00:10:58.710 Patrick Trainer: it’s also free text like. So it’s we’ll need it to like match up like, if
148 00:10:58.820 ⇒ 00:11:03.809 Patrick Trainer: like, if we search for like one of the criteria that we were looking for was like
149 00:11:04.050 ⇒ 00:11:08.030 Patrick Trainer: data director. But if it’s just director.
150 00:11:08.300 ⇒ 00:11:12.790 Patrick Trainer: then, like data director’s not gonna hit. And like, I don’t think you can
151 00:11:13.030 ⇒ 00:11:18.399 Patrick Trainer: use like Regex or anything like that to to match on that. So I think.
152 00:11:18.420 ⇒ 00:11:26.289 Patrick Trainer: having this like finite set from Apollo, will actually be kind of like beneficial. We’ll just have to keep those filters in sync.
153 00:11:29.300 ⇒ 00:11:29.930 Uttam Kumaran: Okay.
154 00:11:30.700 ⇒ 00:11:31.410 Uttam Kumaran: Do you sell them?
155 00:11:31.410 ⇒ 00:11:31.980 Patrick Trainer: Saying, like.
156 00:11:31.980 ⇒ 00:11:32.409 Uttam Kumaran: You know.
157 00:11:32.410 ⇒ 00:11:33.010 Patrick Trainer: Sense.
158 00:11:33.010 ⇒ 00:11:35.480 Uttam Kumaran: Yeah, I see what you’re saying. I guess
159 00:11:35.810 ⇒ 00:11:36.530 Uttam Kumaran: I think it helps.
160 00:11:36.530 ⇒ 00:11:38.799 Patrick Trainer: There may be another way to do it, but like
161 00:11:38.850 ⇒ 00:11:43.900 Patrick Trainer: that was something that I noticed when I was setting it up
162 00:11:44.510 ⇒ 00:11:46.959 Patrick Trainer: was just like the
163 00:11:49.080 ⇒ 00:11:50.080 Patrick Trainer: like. The
164 00:11:50.720 ⇒ 00:11:52.800 Patrick Trainer: the titles have to like match.
165 00:11:53.610 ⇒ 00:12:00.959 Uttam Kumaran: Yeah, this will be more like a. This will be like a string match, and then yours, I think, will be super fixed, basically.
166 00:12:01.310 ⇒ 00:12:02.160 Uttam Kumaran: like.
167 00:12:02.160 ⇒ 00:12:02.620 Patrick Trainer: Yeah.
168 00:12:02.620 ⇒ 00:12:07.920 Uttam Kumaran: Cause cause. If you click on advanced here, Abigail, I think you can click. You can do like
169 00:12:08.960 ⇒ 00:12:11.930 Uttam Kumaran: or company keywords. What does that have.
170 00:12:12.550 ⇒ 00:12:15.839 Uttam Kumaran: Okay, yeah, maybe this is where you can type in like
171 00:12:16.150 ⇒ 00:12:17.970 Uttam Kumaran: something specific. But.
172 00:12:21.300 ⇒ 00:12:21.950 Patrick Trainer: Right
173 00:12:22.970 ⇒ 00:12:28.460 Patrick Trainer: from what it seems like. Like, all of these are like whatever the fields
174 00:12:28.540 ⇒ 00:12:30.379 Patrick Trainer: are going to be from Linkedin.
175 00:12:30.660 ⇒ 00:12:37.930 Patrick Trainer: and like you know how, when you created, like the brain forged Linkedin Company profile, it’s like
176 00:12:38.010 ⇒ 00:12:39.310 Patrick Trainer: consulting
177 00:12:41.070 ⇒ 00:12:44.170 Patrick Trainer: analytics like that sort of stuff.
178 00:12:46.030 ⇒ 00:12:54.109 Uttam Kumaran: So let’s let me. Let’s take this. I want to take an example of a company that I was talking to earlier this year. And let’s see, kind of like where they fit in so
179 00:12:54.577 ⇒ 00:12:57.969 Uttam Kumaran: can you save this search that way? We can.
180 00:12:57.970 ⇒ 00:12:58.870 Abigail Zhao: Same searches.
181 00:12:58.870 ⇒ 00:13:02.409 Uttam Kumaran: Okay, okay, cool. So then, can we? Can you try to find
182 00:13:02.530 ⇒ 00:13:04.496 Uttam Kumaran: I’m gonna send it in?
183 00:13:05.360 ⇒ 00:13:08.639 Uttam Kumaran: I’ll send it in slack. But can you see if you can find
184 00:13:09.560 ⇒ 00:13:13.229 Uttam Kumaran: what criteria it takes for us to find this company?
185 00:13:19.080 ⇒ 00:13:25.924 Uttam Kumaran: This should I want to go out so like, I I think ideally. Oh, actually, actually, no, I I have the
186 00:13:26.980 ⇒ 00:13:28.860 Uttam Kumaran: okay, cool. It’s got a little bit about.
187 00:13:30.130 ⇒ 00:13:33.629 Uttam Kumaran: I install the Apollo Linkedin extension, and it works kind of well.
188 00:13:33.720 ⇒ 00:13:37.249 Uttam Kumaran: but basically, it looks like it’s under logistics.
189 00:13:38.100 ⇒ 00:13:42.289 Uttam Kumaran: They’re like a logistics series. B, they have 9 million in revenue.
190 00:13:42.790 ⇒ 00:13:45.390 Uttam Kumaran: So what our what our filter
191 00:13:45.410 ⇒ 00:13:47.829 Uttam Kumaran: like hit them at the moment.
192 00:13:48.140 ⇒ 00:13:49.440 Patrick Trainer: I don’t think so, because, like.
193 00:13:49.440 ⇒ 00:13:55.579 Uttam Kumaran: I want to structure. I want to structure a campaign around manufacturing and logistics. So let’s just start with
194 00:13:55.660 ⇒ 00:13:59.480 Uttam Kumaran: shipping and logistics as one, and see if we can
195 00:13:59.670 ⇒ 00:14:04.990 Uttam Kumaran: do create another list that just tackles that I think you could probably just duplicate this list.
196 00:14:06.339 ⇒ 00:14:08.919 Uttam Kumaran: So let’s see if we can.
197 00:14:09.480 ⇒ 00:14:18.609 Uttam Kumaran: If we can duplicate the search, just go after. And again the search. The search name I want to match with the campaign. So the campaign we’re going after now is
198 00:14:19.010 ⇒ 00:14:20.330 Uttam Kumaran: start up
199 00:14:21.632 ⇒ 00:14:23.479 Uttam Kumaran: like high growth, startup
200 00:14:25.390 ⇒ 00:14:26.670 Uttam Kumaran: logistics.
201 00:14:27.420 ⇒ 00:14:28.850 Uttam Kumaran: And let’s just start there.
202 00:14:31.410 ⇒ 00:14:32.930 Abigail Zhao: Wait. Sorry. Say that one more time.
203 00:14:32.930 ⇒ 00:14:34.929 Uttam Kumaran: You do high growth startup.
204 00:14:36.900 ⇒ 00:14:38.640 Uttam Kumaran: and then logistics.
205 00:14:44.410 ⇒ 00:14:45.210 Abigail Zhao: Cool.
206 00:14:45.800 ⇒ 00:14:46.560 Abigail Zhao: but
207 00:14:47.750 ⇒ 00:14:48.560 Abigail Zhao: did that.
208 00:14:50.030 ⇒ 00:14:50.730 Abigail Zhao: but
209 00:14:53.190 ⇒ 00:14:54.859 Uttam Kumaran: Maybe just try to refresh.
210 00:14:59.690 ⇒ 00:15:01.530 Uttam Kumaran: or you may have to rename it again.
211 00:15:14.990 ⇒ 00:15:15.819 Abigail Zhao: No.
212 00:15:16.650 ⇒ 00:15:19.429 Patrick Trainer: Seems like like an Apollo bug. That’s weird.
213 00:15:19.430 ⇒ 00:15:22.319 Abigail Zhao: Right. I can go back in later and try it again.
214 00:15:22.320 ⇒ 00:15:25.899 Uttam Kumaran: Okay, so let’s just see if we can. If you can filter
215 00:15:26.060 ⇒ 00:15:28.570 Uttam Kumaran: the keywords to
216 00:15:29.224 ⇒ 00:15:34.859 Uttam Kumaran: actually, actually, I want to see if you could maybe do this on your end. So do you. Have you have your Linkedin right.
217 00:15:36.210 ⇒ 00:15:39.225 Uttam Kumaran: If you did, you can. You install the Apollo
218 00:15:40.560 ⇒ 00:15:44.110 Uttam Kumaran: like extension? I think if you go into Apollo
219 00:15:45.530 ⇒ 00:15:48.799 Uttam Kumaran: there’s like an Apollo Linkedin extension.
220 00:15:52.010 ⇒ 00:15:58.499 Uttam Kumaran: because ideally, it’s like the best way to do. I think this is gonna work is like we find a couple of companies. And we’re like.
221 00:15:58.680 ⇒ 00:16:09.230 Uttam Kumaran: for example I want to. If I want to say I want to tackle everybody that looks like that’s like Stella. We find the keywords that Stella matches with, then expand that to basically the list right
222 00:16:09.580 ⇒ 00:16:13.260 Uttam Kumaran: that way. That’s the campaign we’re going after.
223 00:16:15.540 ⇒ 00:16:18.330 Uttam Kumaran: So if you search for Apollo
224 00:16:19.410 ⇒ 00:16:21.160 Uttam Kumaran: chrome extension, I think
225 00:16:22.000 ⇒ 00:16:23.839 Uttam Kumaran: you should be able to install that.
226 00:16:26.490 ⇒ 00:16:28.229 Abigail Zhao: Oh, yeah, I got it. Okay.
227 00:16:28.230 ⇒ 00:16:33.779 Uttam Kumaran: But it it might actually, I don’t know. It may like fuck with your Google calendar and stuff.
228 00:16:36.224 ⇒ 00:16:36.909 Uttam Kumaran: But
229 00:16:37.110 ⇒ 00:16:38.790 Uttam Kumaran: it may be annoying. I don’t know.
230 00:16:48.075 ⇒ 00:16:48.770 Abigail Zhao: Okay.
231 00:16:54.800 ⇒ 00:16:56.009 Uttam Kumaran: Is it frozen?
232 00:16:57.750 ⇒ 00:16:58.240 Uttam Kumaran: Oh.
233 00:16:58.240 ⇒ 00:17:00.360 Abigail Zhao: Oh, wait! Sorry! I think I might be doing this in a different way.
234 00:17:00.360 ⇒ 00:17:03.570 Uttam Kumaran: Oh, no, you’re good. Okay, you’re good. Okay.
235 00:17:06.810 ⇒ 00:17:10.489 Abigail Zhao: My God, I’m sorry. There’s like construction happening right next to.
236 00:17:11.369 ⇒ 00:17:12.739 Uttam Kumaran: You’re fine. We can’t hear you at all.
237 00:17:12.740 ⇒ 00:17:13.530 Patrick Trainer: Can’t hear it.
238 00:17:26.270 ⇒ 00:17:27.060 Abigail Zhao: Good
239 00:17:28.920 ⇒ 00:17:30.040 Abigail Zhao: alright.
240 00:17:30.750 ⇒ 00:17:32.750 Abigail Zhao: Then.
241 00:17:34.430 ⇒ 00:17:37.180 Abigail Zhao: wait! I think it should be installed. Now let me try.
242 00:17:38.230 ⇒ 00:17:39.060 Abigail Zhao: Yeah.
243 00:17:39.570 ⇒ 00:17:44.239 Uttam Kumaran: Okay, if you go to Linkedin now, you just type in hurry. CURI.
244 00:17:44.540 ⇒ 00:17:45.350 Abigail Zhao: Okay.
245 00:17:47.530 ⇒ 00:17:49.039 Uttam Kumaran: CURR i.
246 00:17:49.040 ⇒ 00:17:50.270 Abigail Zhao: Oh, see you, my bad.
247 00:17:54.390 ⇒ 00:17:57.380 Uttam Kumaran: And just try to go to the company profile
248 00:18:00.730 ⇒ 00:18:02.650 Uttam Kumaran: and that little thing on the right.
249 00:18:03.920 ⇒ 00:18:07.380 Uttam Kumaran: the Apollo thing. Just click on that. Yeah, okay, cool.
250 00:18:07.560 ⇒ 00:18:10.249 Uttam Kumaran: So this is basically like the filter.
251 00:18:10.710 ⇒ 00:18:11.449 Abigail Zhao: Oh, okay.
252 00:18:11.450 ⇒ 00:18:12.549 Uttam Kumaran: Can you write?
253 00:18:13.680 ⇒ 00:18:16.700 Uttam Kumaran: So let’s see if we can match
254 00:18:17.770 ⇒ 00:18:23.209 Uttam Kumaran: that save search to basically hit these. So like, let’s type in transportation logistics
255 00:18:23.900 ⇒ 00:18:31.149 Uttam Kumaran: and like logistics platform, basically just copy over those filters into here. And then we’ll we’ll do a camp. We’ll we’ll test the campaign around
256 00:18:31.550 ⇒ 00:18:33.450 Uttam Kumaran: logistic startups basically.
257 00:18:33.680 ⇒ 00:18:34.330 Abigail Zhao: Okay.
258 00:18:37.840 ⇒ 00:18:40.669 Uttam Kumaran: And then I think some of these you probably have to
259 00:18:41.460 ⇒ 00:18:43.319 Uttam Kumaran: a local commerce.
260 00:18:43.900 ⇒ 00:18:45.570 Uttam Kumaran: So these are keywords.
261 00:18:45.570 ⇒ 00:18:46.780 Abigail Zhao: Oh, okay.
262 00:18:46.920 ⇒ 00:18:47.800 Abigail Zhao: got it.
263 00:18:48.110 ⇒ 00:18:50.130 Uttam Kumaran: Well, you could do both, I think.
264 00:18:50.600 ⇒ 00:18:53.050 Abigail Zhao: I don’t. Oh, okay.
265 00:18:54.490 ⇒ 00:18:58.000 Abigail Zhao: yeah, it’s like different. Because, like, technology doesn’t.
266 00:18:58.870 ⇒ 00:18:59.650 Uttam Kumaran: Well, so there’s 2.
267 00:19:00.530 ⇒ 00:19:01.410 Abigail Zhao: Yeah.
268 00:19:01.410 ⇒ 00:19:04.110 Uttam Kumaran: You have. You have industry, and you have the queue.
269 00:19:04.110 ⇒ 00:19:04.940 Abigail Zhao: Yeah.
270 00:19:04.940 ⇒ 00:19:07.750 Uttam Kumaran: So if you do both, it’ll be like a or Yeah.
271 00:19:33.253 ⇒ 00:19:35.709 Patrick Trainer: You can’t do space. Oh, wait! Oh, never mind.
272 00:19:37.460 ⇒ 00:19:37.925 Abigail Zhao: Oh.
273 00:19:54.460 ⇒ 00:19:55.880 Abigail Zhao: 3. Speed.
274 00:20:02.095 ⇒ 00:20:02.980 Patrick Trainer: There they are!
275 00:20:03.170 ⇒ 00:20:04.210 Uttam Kumaran: So they showed up.
276 00:20:04.620 ⇒ 00:20:06.820 Abigail Zhao: Yeah. Oh, that’s like, all of.
277 00:20:08.490 ⇒ 00:20:12.200 Uttam Kumaran: So let’s keep series CDE, and F.
278 00:20:12.660 ⇒ 00:20:16.409 Abigail Zhao: I don’t think there’s anything for them, cause there’s like a 0 right next to all of them.
279 00:20:16.450 ⇒ 00:20:27.120 Uttam Kumaran: That’s fine, but like, so we only we’re only at 88. So this. So I guess one thing is like on the filter side. What are the other filters that we have? That’s like limiting this
280 00:20:27.220 ⇒ 00:20:32.940 Uttam Kumaran: so recent funding rapid growth. But so these need to have happened.
281 00:20:33.210 ⇒ 00:20:33.650 Patrick Trainer: Sure. Yeah.
282 00:20:33.650 ⇒ 00:20:34.130 Uttam Kumaran: I guess I.
283 00:20:34.130 ⇒ 00:20:34.970 Patrick Trainer: Those out.
284 00:20:35.250 ⇒ 00:20:36.040 Uttam Kumaran: Yeah.
285 00:20:36.040 ⇒ 00:20:40.370 Patrick Trainer: Just I mean, like we can experiment with this to see. There we go under 57.
286 00:20:41.590 ⇒ 00:20:44.210 Patrick Trainer: Who? What other companies we got.
287 00:20:45.680 ⇒ 00:20:48.779 Uttam Kumaran: These are all 31.st So so this is, the other thing is like.
288 00:20:48.900 ⇒ 00:20:49.919 Uttam Kumaran: there’s a lot.
289 00:20:49.920 ⇒ 00:20:50.870 Patrick Trainer: Carrier is great.
290 00:20:50.870 ⇒ 00:20:51.660 Uttam Kumaran: Company
291 00:20:54.690 ⇒ 00:20:57.999 Uttam Kumaran: see? Like we would be hitting like 30 people per company.
292 00:20:59.180 ⇒ 00:21:03.010 Uttam Kumaran: That’s the thing that’s not gonna work about. This is why
293 00:21:03.710 ⇒ 00:21:10.969 Uttam Kumaran: we only want we don’t want to have this many contacts per company, because we’re basically going after we’re going to spam their whole company. We’re going to get blocked.
294 00:21:11.310 ⇒ 00:21:15.340 Patrick Trainer: Well, remember, we’re gonna be scoring these in Hubspot, too.
295 00:21:15.340 ⇒ 00:21:17.099 Uttam Kumaran: Oh, okay. Okay.
296 00:21:17.100 ⇒ 00:21:20.379 Patrick Trainer: Head of customer experience is not going to be.
297 00:21:20.570 ⇒ 00:21:22.520 Patrick Trainer: or 3 pl.
298 00:21:22.890 ⇒ 00:21:23.680 Patrick Trainer: Warehouse.
299 00:21:23.680 ⇒ 00:21:24.150 Uttam Kumaran: What’s leaving.
300 00:21:24.150 ⇒ 00:21:25.310 Patrick Trainer: Success. Yeah.
301 00:21:27.410 ⇒ 00:21:32.139 Uttam Kumaran: So on the left. So we have. We remove what are the other filters? You have
302 00:21:32.650 ⇒ 00:21:35.219 Uttam Kumaran: revenue technologies, territories.
303 00:21:36.490 ⇒ 00:21:38.189 Abigail Zhao: Job titles. And that’s.
304 00:21:38.700 ⇒ 00:21:41.860 Uttam Kumaran: So for revenue. What are the what’s the revenue? We have.
305 00:21:42.740 ⇒ 00:21:43.320 Abigail Zhao: Look like.
306 00:21:43.320 ⇒ 00:21:45.000 Patrick Trainer: Between 8 and 12.
307 00:21:45.180 ⇒ 00:21:46.340 Patrick Trainer: Yeah.
308 00:21:48.762 ⇒ 00:21:51.419 Uttam Kumaran: What was the reason for this?
309 00:21:52.180 ⇒ 00:21:53.390 Uttam Kumaran: I just forgot.
310 00:21:54.560 ⇒ 00:21:56.870 Patrick Trainer: we were wanting to target like
311 00:21:56.990 ⇒ 00:21:59.689 Patrick Trainer: around 10 million in arr.
312 00:22:00.260 ⇒ 00:22:01.690 Uttam Kumaran: Oh, okay, okay.
313 00:22:09.510 ⇒ 00:22:19.089 Uttam Kumaran: Should we expand this? I guess I’m trying to think, like, I’m trying to think, when do we know that this is a isn’t enough for a campaign, or enough to at least send to you
314 00:22:20.060 ⇒ 00:22:21.330 Uttam Kumaran: in Hubspot.
315 00:22:25.070 ⇒ 00:22:25.490 Patrick Trainer: I
316 00:22:26.030 ⇒ 00:22:31.519 Patrick Trainer: I mean, I guess we can like take this off, because, like the Hubspot’s going to score
317 00:22:31.860 ⇒ 00:22:33.580 Patrick Trainer: like, remember, we had.
318 00:22:33.740 ⇒ 00:22:37.010 Patrick Trainer: if it’s if they’re above like 50 million
319 00:22:37.130 ⇒ 00:22:39.850 Patrick Trainer: like that’s a a lower score.
320 00:22:40.440 ⇒ 00:22:43.320 Patrick Trainer: So I would probably just like put it as like, yes, no.
321 00:22:43.320 ⇒ 00:22:46.010 Uttam Kumaran: I would put a Yeah, let’s do is known.
322 00:22:47.650 ⇒ 00:22:49.469 Patrick Trainer: Yeah, and then take out the
323 00:22:49.580 ⇒ 00:22:51.700 Patrick Trainer: that. And okay.
324 00:22:51.700 ⇒ 00:22:52.390 Abigail Zhao: Oh!
325 00:22:53.370 ⇒ 00:22:56.229 Uttam Kumaran: Okay, cool. So now we have 2,000. Okay, so that’s great
326 00:23:01.030 ⇒ 00:23:02.380 Uttam Kumaran: is known.
327 00:23:04.260 ⇒ 00:23:11.130 Uttam Kumaran: I wonder if that you think the technologies will work or not, or do, or do you like 2,000 again? This is where I’m trying to think of, like
328 00:23:11.380 ⇒ 00:23:14.499 Uttam Kumaran: how aggressive we want to be on these lists.
329 00:23:16.100 ⇒ 00:23:21.510 Patrick Trainer: I mean, if you think about it like lists are like, it’s just a list of people. And then
330 00:23:23.210 ⇒ 00:23:29.529 Patrick Trainer: it’s like potentials. It’s like top of funnel, but curated by us in a way.
331 00:23:31.480 ⇒ 00:23:35.820 Patrick Trainer: But it’s also it’s like, part of this is just like experimentation, too.
332 00:23:36.530 ⇒ 00:23:39.689 Patrick Trainer: I mean, that’s what all marketing is. It’s all kind of like.
333 00:23:40.500 ⇒ 00:23:41.060 Uttam Kumaran: Is it? Yeah.
334 00:23:41.060 ⇒ 00:23:41.660 Patrick Trainer: Bullshit.
335 00:23:41.660 ⇒ 00:23:49.199 Uttam Kumaran: I’m just trying to get a sense because we only have a certain amount of credit. So I just wanna we only have 24,000 credits, so we can’t.
336 00:23:49.890 ⇒ 00:23:53.889 Patrick Trainer: Okay, okay, just yeah. Burn them all at once.
337 00:23:53.930 ⇒ 00:23:56.140 Uttam Kumaran: I mean, we can always.
338 00:23:56.340 ⇒ 00:23:58.427 Patrick Trainer: We can try and
339 00:23:59.240 ⇒ 00:24:05.250 Patrick Trainer: whittle it down by, I would say by title, I think, is going to be like the most signal, like
340 00:24:05.320 ⇒ 00:24:15.140 Patrick Trainer: account manager like we don’t need account manager, and it seems like in the title series, or like in the the title filter here.
341 00:24:16.430 ⇒ 00:24:20.240 Patrick Trainer: it looks like it’s like Fuzzy matching everything like
342 00:24:20.910 ⇒ 00:24:27.200 Patrick Trainer: like one of the filters was head right. And then I’m seeing head of central operations.
343 00:24:27.290 ⇒ 00:24:30.139 Patrick Trainer: So it’s like it’s not necessarily
344 00:24:30.710 ⇒ 00:24:31.720 Patrick Trainer: like
345 00:24:31.800 ⇒ 00:24:34.480 Patrick Trainer: try try filtering for.
346 00:24:34.870 ⇒ 00:24:36.759 Uttam Kumaran: Or what should we do by department just.
347 00:24:36.760 ⇒ 00:24:40.169 Patrick Trainer: Just do like head of central operations to see if it’s like.
348 00:24:40.630 ⇒ 00:24:43.769 Patrick Trainer: if we can get like exact matches.
349 00:24:45.155 ⇒ 00:24:45.620 Abigail Zhao: And.
350 00:24:45.620 ⇒ 00:24:47.010 Patrick Trainer: Oh, I see!
351 00:24:47.010 ⇒ 00:24:48.089 Abigail Zhao: I see can.
352 00:24:48.090 ⇒ 00:24:49.589 Patrick Trainer: You. You can’t type them
353 00:24:50.250 ⇒ 00:24:51.530 Patrick Trainer: indirectly.
354 00:24:51.530 ⇒ 00:24:52.480 Uttam Kumaran: Let’s see, this is where I was.
355 00:24:52.480 ⇒ 00:24:54.590 Patrick Trainer: Oh, I see. Departments. Departments. Yeah.
356 00:24:54.590 ⇒ 00:24:56.420 Abigail Zhao: Yeah, you can go by department.
357 00:24:57.060 ⇒ 00:25:04.029 Patrick Trainer: Okay, so maybe go, yeah, maybe add in like operations. And then engineering, technical.
358 00:25:04.030 ⇒ 00:25:06.379 Uttam Kumaran: Yeah, I would just do operations.
359 00:25:06.800 ⇒ 00:25:08.300 Uttam Kumaran: And then engineering.
360 00:25:08.650 ⇒ 00:25:09.250 Patrick Trainer: Yeah.
361 00:25:09.890 ⇒ 00:25:11.379 Uttam Kumaran: Into the entire category.
362 00:25:11.580 ⇒ 00:25:12.360 Abigail Zhao: Okay.
363 00:25:12.790 ⇒ 00:25:18.570 Patrick Trainer: You think so? Cause then we’re getting customer support. And oh, okay, that actually, would that actually whittled it down like.
364 00:25:18.570 ⇒ 00:25:19.899 Uttam Kumaran: And then do it.
365 00:25:24.470 ⇒ 00:25:25.170 Uttam Kumaran: Okay.
366 00:25:27.890 ⇒ 00:25:30.200 Patrick Trainer: Okay, yeah. And then we look like, okay, yeah.
367 00:25:30.200 ⇒ 00:25:31.050 Uttam Kumaran: Can you? Can. You just.
368 00:25:31.050 ⇒ 00:25:32.010 Patrick Trainer: Of engineering.
369 00:25:32.010 ⇒ 00:25:34.829 Uttam Kumaran: Yeah, can you just scroll through some of these? So.
370 00:25:38.720 ⇒ 00:25:39.550 Uttam Kumaran: okay.
371 00:25:44.580 ⇒ 00:25:45.210 Patrick Trainer: Okay.
372 00:25:47.610 ⇒ 00:25:49.784 Patrick Trainer: software engineering manager.
373 00:25:50.510 ⇒ 00:25:56.190 Uttam Kumaran: So pat. For let’s take. Let’s let’s even so, let’s save this search, Abigail. And then
374 00:25:56.350 ⇒ 00:26:00.600 Uttam Kumaran: in this meeting today, I want to just take one of these companies.
375 00:26:00.670 ⇒ 00:26:09.120 Uttam Kumaran: because again, I don’t. Wanna I we can’t. If we burn all these credits, it’s gonna be like a shit. So I want to just take one of these companies
376 00:26:09.500 ⇒ 00:26:12.379 Uttam Kumaran: get. So let’s just pick one of these.
377 00:26:13.860 ⇒ 00:26:15.293 Uttam Kumaran: I mean, I don’t know
378 00:26:15.910 ⇒ 00:26:18.390 Patrick Trainer: Go with pickup that 1st one.
379 00:26:19.970 ⇒ 00:26:23.700 Patrick Trainer: Oh, escalation manager of luxury! What.
380 00:26:24.270 ⇒ 00:26:24.970 Uttam Kumaran: Account.
381 00:26:26.290 ⇒ 00:26:29.019 Uttam Kumaran: Okay, I mean, this looks fine.
382 00:26:29.020 ⇒ 00:26:30.939 Patrick Trainer: Yeah, like, yeah, it’ll it literally.
383 00:26:30.940 ⇒ 00:26:33.250 Uttam Kumaran: So how many matches do we have on this one.
384 00:26:34.810 ⇒ 00:26:36.699 Patrick Trainer: I think there was like 600, something
385 00:26:36.810 ⇒ 00:26:38.810 Patrick Trainer: 7, yes, 7, 80,
386 00:26:39.730 ⇒ 00:26:40.880 Patrick Trainer: 7, 70.
387 00:26:44.470 ⇒ 00:26:46.010 Uttam Kumaran: So we just called Pickup.
388 00:26:46.260 ⇒ 00:26:48.530 Uttam Kumaran: So can you just filter to that company.
389 00:26:49.200 ⇒ 00:26:51.180 Abigail Zhao: Yeah, I was trying to find. Oh.
390 00:26:51.420 ⇒ 00:26:57.140 Uttam Kumaran: On the on the if you just on the left. I think you can just filter that company somehow.
391 00:26:57.340 ⇒ 00:26:57.910 Patrick Trainer: Tenant.
392 00:26:59.280 ⇒ 00:26:59.960 Abigail Zhao: Yeah.
393 00:27:03.280 ⇒ 00:27:05.230 Uttam Kumaran: Yeah, you can just type in pick up. Yeah
394 00:27:07.760 ⇒ 00:27:08.860 Uttam Kumaran: of now.
395 00:27:13.750 ⇒ 00:27:16.240 Uttam Kumaran: Okay, I mean, see, now, these guys.
396 00:27:18.190 ⇒ 00:27:18.850 Abigail Zhao: Whoops.
397 00:27:19.590 ⇒ 00:27:24.669 Uttam Kumaran: But see, this is where I like. It’s not. I want to make sure our filters get the right people.
398 00:27:24.750 ⇒ 00:27:28.840 Uttam Kumaran: cause I we can’t hit fuel quality managers right? Like
399 00:27:35.703 ⇒ 00:27:39.540 Uttam Kumaran: like, what’s 1 of these people’s name? Jeff brandy Decker?
400 00:27:48.360 ⇒ 00:27:49.360 Uttam Kumaran: Okay?
401 00:27:55.860 ⇒ 00:27:58.949 Uttam Kumaran: So I do see senior product managers.
402 00:27:59.510 ⇒ 00:28:04.359 Uttam Kumaran: I see, senior directors. So that’s where I’m like, why aren’t those people showing up
403 00:28:19.630 ⇒ 00:28:22.409 Uttam Kumaran: so master engineering technical?
404 00:28:26.960 ⇒ 00:28:33.280 Uttam Kumaran: Okay? So I have, let’s, I’m gonna send you a person and let’s find out why he’s not showing up in this list.
405 00:28:39.710 ⇒ 00:28:44.579 Uttam Kumaran: okay, take a look, this guy said on Linkedin. So you should. The Apollo thing will work again.
406 00:28:46.850 ⇒ 00:28:48.290 Uttam Kumaran: so
407 00:28:52.430 ⇒ 00:28:54.540 Uttam Kumaran: this guy’s a senior. Pm.
408 00:28:55.500 ⇒ 00:28:57.430 Uttam Kumaran: this is a guy that we should have.
409 00:29:00.710 ⇒ 00:29:04.349 Uttam Kumaran: So what I want to know is like, how what are what’s the
410 00:29:04.580 ⇒ 00:29:08.560 Uttam Kumaran: filters on the title side for us to be able to hit this guy?
411 00:29:16.270 ⇒ 00:29:24.920 Uttam Kumaran: So if you go back into Apollo, where we? What are the? So we have manager the departments. If you click on the departments again.
412 00:29:27.950 ⇒ 00:29:31.030 Uttam Kumaran: if you type in product, click on product.
413 00:29:31.710 ⇒ 00:29:33.880 Uttam Kumaran: well, you just just click on the whole thing.
414 00:29:34.090 ⇒ 00:29:36.789 Uttam Kumaran: Well, we want click on product and click on c-suite.
415 00:29:38.790 ⇒ 00:29:39.989 Uttam Kumaran: like a whole thing.
416 00:29:41.760 ⇒ 00:29:43.510 Uttam Kumaran: Does this guy show up? Now?
417 00:29:48.620 ⇒ 00:29:49.310 Uttam Kumaran: It
418 00:29:49.570 ⇒ 00:29:50.690 Uttam Kumaran: yeah, exactly.
419 00:29:51.040 ⇒ 00:29:51.699 Abigail Zhao: He’s like.
420 00:29:53.190 ⇒ 00:29:55.779 Uttam Kumaran: So I don’t want field quality managers.
421 00:29:56.420 ⇒ 00:29:57.330 Abigail Zhao: Okay.
422 00:29:57.330 ⇒ 00:30:01.420 Uttam Kumaran: So like. How? What? Why, do we need to filter out to get rid of those folks
423 00:30:04.790 ⇒ 00:30:06.640 Uttam Kumaran: like? Is there an exclude.
424 00:30:11.250 ⇒ 00:30:13.200 Abigail Zhao: I think, is not any oath.
425 00:30:14.270 ⇒ 00:30:16.980 Abigail Zhao: but that might be a bit more like tedious.
426 00:30:17.550 ⇒ 00:30:21.069 Uttam Kumaran: Oh, okay. So with type in is not any of and see what happens?
427 00:30:21.680 ⇒ 00:30:25.330 Uttam Kumaran: Oh, okay. So scroll down. See? What are the options?
428 00:30:32.420 ⇒ 00:30:34.210 Uttam Kumaran: Type in just field.
429 00:30:34.760 ⇒ 00:30:38.589 Uttam Kumaran: So so this is where like, okay, this is actually good. Because I think
430 00:30:38.750 ⇒ 00:30:44.109 Uttam Kumaran: for every campaign and every industry, there’s going to be these specific things.
431 00:30:44.800 ⇒ 00:30:46.030 Uttam Kumaran: Right? So
432 00:30:46.630 ⇒ 00:30:57.959 Uttam Kumaran: what what we’re gonna do is like, try to think about for every campaign we want to have a Max and a minimum amount of leads that we send the Hubspot to process from Apollo.
433 00:30:58.140 ⇒ 00:30:59.030 Uttam Kumaran: Right?
434 00:30:59.170 ⇒ 00:31:14.829 Uttam Kumaran: So basically, how we’re gonna do that is is think through this. For example, in the manufacturing industry with the filters we are default to. We’re gonna get people that are like field engineers. The plant people like in engineers will be like
435 00:31:14.960 ⇒ 00:31:26.040 Uttam Kumaran: technician engineer. But they’re like welders, right? Like, those are people that don’t have email so like, we can’t hit them that. So there’s gonna be a couple of these nuances to every single list.
436 00:31:26.120 ⇒ 00:31:27.629 Uttam Kumaran: But I believe
437 00:31:28.560 ⇒ 00:31:31.630 Uttam Kumaran: in Apollo, we’re gonna have to continue to filter down.
438 00:31:32.690 ⇒ 00:31:36.070 Uttam Kumaran: I think this is a pretty good list, though I don’t know. What do you think, Pat?
439 00:31:36.980 ⇒ 00:31:38.740 Patrick Trainer: Yeah, I think it’s a pretty solid list.
440 00:31:41.240 ⇒ 00:31:48.460 Uttam Kumaran: So we just filtered to pick up. And these are the people in pickup that we want to hit. Let me look. Is there anyone else like
441 00:31:51.410 ⇒ 00:31:57.279 Uttam Kumaran: there are like, we’re not getting any of the directors or or senior people there, though
442 00:32:07.460 ⇒ 00:32:08.539 Uttam Kumaran: you know what I mean.
443 00:32:08.990 ⇒ 00:32:09.660 Patrick Trainer: Yeah.
444 00:32:19.710 ⇒ 00:32:20.450 Patrick Trainer: it
445 00:32:20.770 ⇒ 00:32:23.410 Patrick Trainer: could be.
446 00:32:23.830 ⇒ 00:32:27.829 Patrick Trainer: Oh, go into like the scroll up a bit.
447 00:32:28.850 ⇒ 00:32:30.570 Patrick Trainer: Alright. The
448 00:32:30.790 ⇒ 00:32:33.100 Patrick Trainer: not the industry, but the
449 00:32:33.600 ⇒ 00:32:35.080 Patrick Trainer: it was like the job.
450 00:32:35.470 ⇒ 00:32:38.680 Patrick Trainer: Oh, yeah, yeah. Okay. C-suite’s already there
451 00:32:39.196 ⇒ 00:32:42.459 Patrick Trainer: or management level. Oh, they’re all zeros.
452 00:32:42.460 ⇒ 00:32:43.300 Abigail Zhao: Yeah.
453 00:32:51.120 ⇒ 00:32:54.589 Patrick Trainer: Maybe this is something specific to this company or something.
454 00:32:54.590 ⇒ 00:32:56.959 Uttam Kumaran: Yeah, I’m I’m only seeing one other.
455 00:32:58.020 ⇒ 00:33:01.719 Uttam Kumaran: I mean, you’re right, like, there’s actually not a data person.
456 00:33:03.360 ⇒ 00:33:08.899 Patrick Trainer: Yeah, we can try choosing a different company like, maybe this would be something that would be filtered out in Hubspot just.
457 00:33:08.900 ⇒ 00:33:13.860 Uttam Kumaran: I think this is. I think this is fine. Let’s just try to run with this. Let’s just try to run with these 3 people
458 00:33:14.800 ⇒ 00:33:19.910 Uttam Kumaran: right? So now that we so I would go, we can save this search.
459 00:33:20.340 ⇒ 00:33:21.980 Uttam Kumaran: Let’s say, this is
460 00:33:22.930 ⇒ 00:33:25.750 Uttam Kumaran: like a test like high growth
461 00:33:26.350 ⇒ 00:33:28.650 Uttam Kumaran: bunch of high growth logistics
462 00:33:29.770 ⇒ 00:33:32.929 Uttam Kumaran: like single company tests or something like that.
463 00:33:33.240 ⇒ 00:33:34.340 Uttam Kumaran: And then.
464 00:33:35.100 ⇒ 00:33:42.600 Uttam Kumaran: Pat, I’ll kind of hand it to you. So now, what like? What’s the process? Let’s export these and like, how do we do this to get these folks in Hubspot?
465 00:33:43.560 ⇒ 00:33:43.960 Abigail Zhao: Cool
466 00:33:45.120 ⇒ 00:33:46.420 Patrick Trainer: Yeah, so
467 00:33:54.170 ⇒ 00:33:56.069 Patrick Trainer: so they.
468 00:33:56.070 ⇒ 00:34:02.067 Uttam Kumaran: And you wanna make these public like searches that? Oh, I guess everybody’s logged into my account. So it doesn’t matter.
469 00:34:03.990 ⇒ 00:34:04.600 Uttam Kumaran: Okay.
470 00:34:15.940 ⇒ 00:34:18.964 Patrick Trainer: How did you udum? How did you get the
471 00:34:20.800 ⇒ 00:34:22.269 Patrick Trainer: like? There’s a bunch of
472 00:34:22.639 ⇒ 00:34:25.110 Patrick Trainer: people already in here are.
473 00:34:25.110 ⇒ 00:34:28.690 Uttam Kumaran: Oh, those those are all people from like my Google contacts.
474 00:34:28.699 ⇒ 00:34:33.959 Patrick Trainer: Okay, okay. Let’s see, content actions.
475 00:34:35.139 ⇒ 00:34:37.909 Patrick Trainer: Okay, I see there’s an import.
476 00:34:39.389 ⇒ 00:34:40.848 Uttam Kumaran: Do you want to share
477 00:34:47.579 ⇒ 00:34:48.529 Uttam Kumaran: alright?
478 00:34:49.010 ⇒ 00:34:51.667 Patrick Trainer: So 1st I’ll show I’ll show you what
479 00:34:57.350 ⇒ 00:35:00.590 Patrick Trainer: The hubspot like lead scores even look like.
480 00:35:01.310 ⇒ 00:35:06.719 Patrick Trainer: So if we come into what like what you do. You go up to this little gear thing.
481 00:35:07.010 ⇒ 00:35:07.850 Patrick Trainer: and
482 00:35:07.960 ⇒ 00:35:12.399 Patrick Trainer: you come into properties like in data management.
483 00:35:13.030 ⇒ 00:35:17.170 Patrick Trainer: and then the field is called the Hubspot score.
484 00:35:18.170 ⇒ 00:35:19.160 Patrick Trainer: And it’s
485 00:35:19.500 ⇒ 00:35:21.700 Patrick Trainer: okay. Here it had, like a little
486 00:35:22.310 ⇒ 00:35:28.459 Patrick Trainer: like the numbers shows qualifications for sales readiness. It’s like lead scoring.
487 00:35:29.020 ⇒ 00:35:31.780 Patrick Trainer: And so this thing comes up.
488 00:35:32.450 ⇒ 00:35:33.810 Patrick Trainer: And you’re
489 00:35:34.200 ⇒ 00:35:35.760 Patrick Trainer: basically what you’re doing.
490 00:35:35.820 ⇒ 00:35:40.260 Patrick Trainer: You’re applying these filters that then apply a score.
491 00:35:40.560 ⇒ 00:35:41.400 Patrick Trainer: So
492 00:35:41.630 ⇒ 00:35:49.659 Patrick Trainer: like, for example, like I was just testing with, like, my like, we we have, like job title is like sea level
493 00:35:50.330 ⇒ 00:35:56.749 Patrick Trainer: top Vp of analytics, director data lead like, that’s everything that was coming from
494 00:35:57.490 ⇒ 00:36:03.800 Patrick Trainer: here. Right? And then we also have just put it as like known.
495 00:36:04.050 ⇒ 00:36:06.469 Patrick Trainer: So that’s kind of like the other.
496 00:36:07.020 ⇒ 00:36:08.420 Patrick Trainer: And then
497 00:36:08.570 ⇒ 00:36:10.719 Patrick Trainer: we go into like revenue.
498 00:36:11.100 ⇒ 00:36:12.779 Patrick Trainer: like we have
499 00:36:13.530 ⇒ 00:36:15.290 Patrick Trainer: between 8 and 12.
500 00:36:15.660 ⇒ 00:36:18.039 Patrick Trainer: We’re looking at like 25,
501 00:36:18.930 ⇒ 00:36:21.190 Patrick Trainer: 5, and 8, 20,
502 00:36:21.720 ⇒ 00:36:24.520 Patrick Trainer: 12 and 15 was also 20,
503 00:36:24.810 ⇒ 00:36:27.659 Patrick Trainer: and that all corresponds to
504 00:36:27.700 ⇒ 00:36:29.050 Patrick Trainer: to this right?
505 00:36:29.400 ⇒ 00:36:30.850 Patrick Trainer: And so
506 00:36:31.500 ⇒ 00:36:34.519 Patrick Trainer: what’s nice is like, you can like, test this.
507 00:36:34.620 ⇒ 00:36:41.279 Patrick Trainer: And so I’m gonna actually go over here 1st and like open up contacts.
508 00:36:41.790 ⇒ 00:36:45.319 Patrick Trainer: So I’ve been testing it with.
509 00:36:46.850 ⇒ 00:36:47.510 Patrick Trainer: Me!
510 00:36:47.970 ⇒ 00:36:49.210 Patrick Trainer: And so
511 00:36:50.970 ⇒ 00:36:53.580 Patrick Trainer: you can see my
512 00:36:53.920 ⇒ 00:36:55.649 Patrick Trainer: profile here.
513 00:36:56.140 ⇒ 00:36:57.080 Patrick Trainer: and
514 00:36:58.130 ⇒ 00:36:59.519 Patrick Trainer: I made myself.
515 00:37:00.370 ⇒ 00:37:01.100 Uttam Kumaran: Nice.
516 00:37:01.460 ⇒ 00:37:03.030 Patrick Trainer: An engineer right?
517 00:37:03.180 ⇒ 00:37:05.879 Patrick Trainer: And so if we go back over
518 00:37:05.930 ⇒ 00:37:08.229 Patrick Trainer: into the Hubspot score.
519 00:37:08.660 ⇒ 00:37:09.530 Patrick Trainer: if
520 00:37:09.770 ⇒ 00:37:12.080 Patrick Trainer: well, so we don’t have
521 00:37:13.100 ⇒ 00:37:14.409 Patrick Trainer: this or that, and
522 00:37:15.440 ⇒ 00:37:18.550 Patrick Trainer: just the job. Title is filled out. So job title is known.
523 00:37:18.630 ⇒ 00:37:22.719 Patrick Trainer: and so you can test the score criteria with like a name.
524 00:37:23.090 ⇒ 00:37:23.770 Uttam Kumaran: Cool.
525 00:37:24.416 ⇒ 00:37:27.170 Patrick Trainer: And you can test and look at that. I’ve.
526 00:37:27.170 ⇒ 00:37:28.319 Uttam Kumaran: 10 points.
527 00:37:29.316 ⇒ 00:37:33.839 Patrick Trainer: But if we let’s come over here.
528 00:37:35.260 ⇒ 00:37:36.280 Patrick Trainer: any.
529 00:37:36.720 ⇒ 00:37:38.440 Patrick Trainer: Okay? Yeah. And it shows like
530 00:37:39.060 ⇒ 00:37:40.610 Patrick Trainer: what it matches.
531 00:37:40.740 ⇒ 00:37:43.200 Patrick Trainer: So like, if we come in here
532 00:37:43.340 ⇒ 00:37:44.140 Patrick Trainer: and
533 00:37:44.300 ⇒ 00:37:44.980 Patrick Trainer: oops
534 00:37:51.660 ⇒ 00:37:55.119 Patrick Trainer: come here and we edit my contact.
535 00:37:56.450 ⇒ 00:37:57.130 Patrick Trainer: Nope.
536 00:38:01.980 ⇒ 00:38:05.450 Patrick Trainer: let’s say, director of analytics.
537 00:38:10.020 ⇒ 00:38:11.910 Patrick Trainer: and we come back over here.
538 00:38:12.120 ⇒ 00:38:13.269 Patrick Trainer: Oh, where’d it go?
539 00:38:13.380 ⇒ 00:38:14.840 Patrick Trainer: Okay, come here.
540 00:38:15.030 ⇒ 00:38:17.630 Patrick Trainer: We’re going to test that score criteria.
541 00:38:18.080 ⇒ 00:38:19.620 Patrick Trainer: Find my name again.
542 00:38:19.830 ⇒ 00:38:22.989 Patrick Trainer: Test it. Look at that. Oh, yeah. 35 points.
543 00:38:23.270 ⇒ 00:38:23.820 Uttam Kumaran: Thanks.
544 00:38:25.509 ⇒ 00:38:27.809 Patrick Trainer: And so if we
545 00:38:29.190 ⇒ 00:38:31.470 Patrick Trainer: continue doing this like we
546 00:38:31.490 ⇒ 00:38:34.070 Patrick Trainer: like, let’s go over to
547 00:38:34.820 ⇒ 00:38:37.450 Patrick Trainer: like brain forges.
548 00:38:38.620 ⇒ 00:38:39.460 Patrick Trainer: How do we?
549 00:38:42.150 ⇒ 00:38:44.020 Patrick Trainer: Brian Forge’s
550 00:38:46.380 ⇒ 00:38:48.359 Patrick Trainer: whatever? So we have
551 00:38:48.990 ⇒ 00:38:50.460 Patrick Trainer: the.
552 00:38:51.680 ⇒ 00:38:53.663 Patrick Trainer: I don’t think that’s right.
553 00:38:54.890 ⇒ 00:38:57.959 Patrick Trainer: I’m still like figuring out how to navigate all this shit.
554 00:38:59.138 ⇒ 00:39:02.009 Patrick Trainer: And so the company
555 00:39:02.730 ⇒ 00:39:05.770 Patrick Trainer: view all properties, I think.
556 00:39:09.610 ⇒ 00:39:15.829 Patrick Trainer: Okay, cool. So the company information we should have like revenue
557 00:39:16.760 ⇒ 00:39:19.799 Patrick Trainer: annual revenue. Like, let’s say, we make
558 00:39:20.360 ⇒ 00:39:21.340 Patrick Trainer: 9
559 00:39:22.780 ⇒ 00:39:24.900 Patrick Trainer: 1 billion dollars. Is that 9,
560 00:39:25.050 ⇒ 00:39:27.320 Patrick Trainer: you know, 9 million dollars
561 00:39:28.100 ⇒ 00:39:29.877 Patrick Trainer: in annual revenue.
562 00:39:33.760 ⇒ 00:39:34.440 Patrick Trainer: back.
563 00:39:36.370 ⇒ 00:39:37.850 Patrick Trainer: So this company
564 00:39:41.760 ⇒ 00:39:44.370 Patrick Trainer: and I think I can edit, yeah, edit this.
565 00:39:46.470 ⇒ 00:39:49.459 Patrick Trainer: Well, that’s not actually important.
566 00:39:49.750 ⇒ 00:39:50.430 Patrick Trainer: Yeah.
567 00:39:52.951 ⇒ 00:39:57.480 Patrick Trainer: and so this is on the company, and that we have.
568 00:39:57.990 ⇒ 00:39:59.839 Patrick Trainer: Look at that. Who’s Ian?
569 00:40:01.260 ⇒ 00:40:05.260 Uttam Kumaran: Ian. Oh, that’s a guy who’s doing our insurance.
570 00:40:06.120 ⇒ 00:40:10.330 Patrick Trainer: Nice and so we’ll come back over here
571 00:40:10.750 ⇒ 00:40:13.049 Patrick Trainer: and let’s test that
572 00:40:13.280 ⇒ 00:40:17.927 Patrick Trainer: on me again. And so, because remember, we have that like
573 00:40:19.430 ⇒ 00:40:20.510 Patrick Trainer: revenue
574 00:40:20.850 ⇒ 00:40:23.130 Patrick Trainer: filter on the Hubspot score.
575 00:40:23.310 ⇒ 00:40:25.890 Patrick Trainer: We should expect this to like update.
576 00:40:30.780 ⇒ 00:40:31.430 Uttam Kumaran: Nice.
577 00:40:32.277 ⇒ 00:40:34.989 Patrick Trainer: Well, no, it it didn’t update. So.
578 00:40:37.820 ⇒ 00:40:39.730 Uttam Kumaran: Well, test contact didn’t match.
579 00:40:42.980 ⇒ 00:40:45.150 Patrick Trainer: let, why didn’t it match that?
580 00:40:47.190 ⇒ 00:40:48.550 Patrick Trainer: Wait? Is this
581 00:40:49.410 ⇒ 00:40:51.690 Patrick Trainer: Primary Associated company?
582 00:40:52.740 ⇒ 00:40:54.150 Patrick Trainer: Is this the
583 00:41:14.900 ⇒ 00:41:16.430 Patrick Trainer: maybe I didn’t save it?
584 00:41:28.060 ⇒ 00:41:29.909 Patrick Trainer: Okay, I guess I didn’t save it.
585 00:41:36.020 ⇒ 00:41:38.460 Patrick Trainer: Okay, that’s oh, yeah, I didn’t save.
586 00:41:39.370 ⇒ 00:41:40.259 Patrick Trainer: There we go.
587 00:41:40.850 ⇒ 00:41:45.120 Patrick Trainer: Okay. And so let’s actually test this again.
588 00:41:48.380 ⇒ 00:41:50.040 Patrick Trainer: Boom 60.
589 00:41:50.040 ⇒ 00:41:50.990 Uttam Kumaran: Nice. Okay.
590 00:41:51.411 ⇒ 00:41:53.940 Patrick Trainer: Better lead? Because, yeah. Yeah.
591 00:41:54.240 ⇒ 00:41:56.960 Uttam Kumaran: Because the company you’re associated with yeah.
592 00:41:56.960 ⇒ 00:41:59.660 Patrick Trainer: And and the company that I’m associated with.
593 00:41:59.660 ⇒ 00:42:00.710 Uttam Kumaran: Pizza bell.
594 00:42:00.710 ⇒ 00:42:02.840 Patrick Trainer: Fits. Yeah, fits the bill there.
595 00:42:03.020 ⇒ 00:42:06.179 Patrick Trainer: And so, like all of these other filters like fail.
596 00:42:06.560 ⇒ 00:42:08.968 Uttam Kumaran: And then where? So where? Where are these?
597 00:42:10.990 ⇒ 00:42:19.290 Uttam Kumaran: this hubspot? So all the hubspots for building actually happens right here. Oh, 10 out of 100. So you’re just you’re gonna walk through and just make sure everything’s in here. Basically.
598 00:42:19.480 ⇒ 00:42:21.990 Patrick Trainer: Yeah, yeah, this is what I was saying. It’s like.
599 00:42:22.200 ⇒ 00:42:23.320 Uttam Kumaran: Get pain in the ass.
600 00:42:23.320 ⇒ 00:42:27.639 Patrick Trainer: To to have to go in here. Add criteria like
601 00:42:28.690 ⇒ 00:42:31.109 Patrick Trainer: type. All this shit in there.
602 00:42:31.280 ⇒ 00:42:33.600 Patrick Trainer: but it’s like there’s all sorts of like different
603 00:42:33.660 ⇒ 00:42:35.680 Patrick Trainer: things. It’s like we can
604 00:42:36.130 ⇒ 00:42:38.340 Patrick Trainer: look at like touches or
605 00:42:38.370 ⇒ 00:42:41.790 Patrick Trainer: but like, here’s like the contact properties. If, like, we wanna
606 00:42:42.060 ⇒ 00:42:44.500 Patrick Trainer: give attributes on the contact itself.
607 00:42:44.510 ⇒ 00:42:47.840 Patrick Trainer: or give attributes on the
608 00:42:48.090 ⇒ 00:42:49.050 Patrick Trainer: company
609 00:42:49.290 ⇒ 00:42:52.640 Patrick Trainer: itself, like they have all of these different things.
610 00:42:54.650 ⇒ 00:42:56.179 Patrick Trainer: Or there’s even
611 00:42:56.630 ⇒ 00:42:57.700 Patrick Trainer: like, I don’t.
612 00:42:58.650 ⇒ 00:43:00.710 Patrick Trainer: I don’t think we’ve done any of these.
613 00:43:01.082 ⇒ 00:43:02.530 Patrick Trainer: But so I think
614 00:43:03.130 ⇒ 00:43:06.839 Patrick Trainer: company and contact are really what we’re going to be paying attention to now.
615 00:43:06.860 ⇒ 00:43:09.869 Patrick Trainer: But we can come up to contact. And then, like.
616 00:43:12.070 ⇒ 00:43:13.090 Patrick Trainer: there’s like.
617 00:43:15.150 ⇒ 00:43:17.109 Patrick Trainer: I don’t know, like all the other stuff.
618 00:43:17.480 ⇒ 00:43:20.170 Patrick Trainer: maybe like company, like, let’s
619 00:43:28.640 ⇒ 00:43:30.060 Patrick Trainer: company information.
620 00:43:30.550 ⇒ 00:43:31.730 Patrick Trainer: Yeah. So
621 00:43:32.450 ⇒ 00:43:38.309 Patrick Trainer: we can do this. And we can add all of these filters, or add all the filters that we’ve done here.
622 00:43:39.345 ⇒ 00:43:40.240 Patrick Trainer: And
623 00:43:41.020 ⇒ 00:43:43.549 Patrick Trainer: that’s going to affect the score.
624 00:43:43.990 ⇒ 00:43:46.490 Patrick Trainer: And so let’s actually see
625 00:43:49.840 ⇒ 00:43:50.950 Patrick Trainer: what
626 00:44:01.260 ⇒ 00:44:02.800 Patrick Trainer: wonder where.
627 00:44:06.200 ⇒ 00:44:09.900 Patrick Trainer: if we can see where my
628 00:44:14.450 ⇒ 00:44:16.019 Patrick Trainer: score is?
629 00:44:25.250 ⇒ 00:44:26.809 Patrick Trainer: You can’t see the score
630 00:44:27.010 ⇒ 00:44:27.899 Patrick Trainer: in this
631 00:44:28.720 ⇒ 00:44:29.780 Patrick Trainer: this contact.
632 00:44:47.420 ⇒ 00:44:49.160 Patrick Trainer: I’m sure there’s a way to
633 00:44:49.570 ⇒ 00:44:51.740 Patrick Trainer: display like what the score is.
634 00:44:52.140 ⇒ 00:44:56.809 Patrick Trainer: And then and then I’m thinking, so we there’s like automations.
635 00:44:58.930 ⇒ 00:45:00.900 Patrick Trainer: or let’s actually go to
636 00:45:09.850 ⇒ 00:45:12.590 Patrick Trainer: okay. And so we can create like a list.
637 00:45:17.860 ⇒ 00:45:19.180 Patrick Trainer: and it’s gonna be
638 00:45:19.680 ⇒ 00:45:20.680 Patrick Trainer: based
639 00:45:23.810 ⇒ 00:45:24.980 Patrick Trainer: that filter
640 00:45:29.370 ⇒ 00:45:30.460 Patrick Trainer: pain in the ass.
641 00:45:32.950 ⇒ 00:45:36.170 Patrick Trainer: Well, so I’m not. I’m not sure how to do this yet.
642 00:45:37.093 ⇒ 00:45:37.676 Patrick Trainer: But
643 00:45:41.380 ⇒ 00:45:42.860 Patrick Trainer: let’s get contacts.
644 00:45:48.190 ⇒ 00:45:49.839 Patrick Trainer: Let’s see if we can.
645 00:45:54.430 ⇒ 00:45:55.519 Patrick Trainer: How’s hospital score
646 00:46:00.520 ⇒ 00:46:01.370 Patrick Trainer: then?
647 00:46:16.350 ⇒ 00:46:19.619 Patrick Trainer: So you actually already have some scores in there.
648 00:46:19.860 ⇒ 00:46:20.850 Uttam Kumaran: For everybody.
649 00:46:21.110 ⇒ 00:46:23.059 Patrick Trainer: Yeah, because they’re in there.
650 00:46:23.540 ⇒ 00:46:25.040 Uttam Kumaran: Is there anyone who drink high.
651 00:46:27.750 ⇒ 00:46:28.960 Patrick Trainer: Well, you think I oh.
652 00:46:29.660 ⇒ 00:46:30.430 Patrick Trainer: Patrick.
653 00:46:35.660 ⇒ 00:46:36.350 Patrick Trainer: Leonard.
654 00:46:36.350 ⇒ 00:46:38.820 Uttam Kumaran: You just remember you just had a but oh, wait, you.
655 00:46:38.820 ⇒ 00:46:42.970 Patrick Trainer: Oh, yeah, these are all they just have their. They just have their watchma call it
656 00:46:45.010 ⇒ 00:46:47.179 Patrick Trainer: like, if we go into here. I bet.
657 00:46:55.090 ⇒ 00:46:55.929 Patrick Trainer: Yeah, like this.
658 00:46:55.930 ⇒ 00:46:58.229 Uttam Kumaran: This guy’s associated with property vista.
659 00:46:59.390 ⇒ 00:47:01.089 Patrick Trainer: Do we have like the revenue?
660 00:47:01.280 ⇒ 00:47:03.860 Patrick Trainer: But so, oh, yeah, okay. Annual revenue.
661 00:47:04.160 ⇒ 00:47:05.349 Patrick Trainer: 10 million. So.
662 00:47:05.350 ⇒ 00:47:06.150 Uttam Kumaran: Okay.
663 00:47:06.150 ⇒ 00:47:07.430 Patrick Trainer: They got some.
664 00:47:08.110 ⇒ 00:47:10.329 Patrick Trainer: He got some points because of that.
665 00:47:11.500 ⇒ 00:47:15.060 Uttam Kumaran: So right now. Probably the Max you can get is like 65, or whatever.
666 00:47:18.520 ⇒ 00:47:19.919 Patrick Trainer: I I guess like.
667 00:47:20.630 ⇒ 00:47:22.010 Patrick Trainer: currently.
668 00:47:22.490 ⇒ 00:47:24.260 Patrick Trainer: because of.
669 00:47:24.590 ⇒ 00:47:27.840 Patrick Trainer: let’s see. So we got 1525,
670 00:47:28.330 ⇒ 00:47:28.920 Patrick Trainer: 20.
671 00:47:28.920 ⇒ 00:47:32.080 Uttam Kumaran: Yeah, okay, 2550. Okay, t, 10.
672 00:47:33.510 ⇒ 00:47:34.000 Patrick Trainer: Yeah.
673 00:47:34.000 ⇒ 00:47:35.885 Uttam Kumaran: Oh, but some of these are
674 00:47:37.020 ⇒ 00:47:38.490 Uttam Kumaran: Oh, okay.
675 00:47:38.550 ⇒ 00:47:42.619 Uttam Kumaran: so you you have 4 fill. You have 4 per property.
676 00:47:43.330 ⇒ 00:47:45.769 Uttam Kumaran: almost 4 filters per property.
677 00:47:47.460 ⇒ 00:47:48.500 Uttam Kumaran: Is that right?
678 00:47:48.830 ⇒ 00:47:49.470 Patrick Trainer: Around.
679 00:47:49.620 ⇒ 00:47:50.110 Patrick Trainer: my.
680 00:47:50.110 ⇒ 00:47:54.980 Uttam Kumaran: Meaning like if you go back to the spreadsheet like we have 4
681 00:47:55.610 ⇒ 00:47:58.049 Uttam Kumaran: per subcategory. So it’s actually the number of.
682 00:47:58.050 ⇒ 00:47:58.830 Patrick Trainer: Value, yeah.
683 00:47:58.830 ⇒ 00:48:00.530 Uttam Kumaran: Values map to filters.
684 00:48:00.900 ⇒ 00:48:02.230 Patrick Trainer: Right? Yes.
685 00:48:02.230 ⇒ 00:48:04.610 Uttam Kumaran: Maybe change that to filter
686 00:48:04.760 ⇒ 00:48:09.170 Uttam Kumaran: that way. We have the same nomenclature, or, like you could say Hubspot, filter, or whatever.
687 00:48:10.910 ⇒ 00:48:14.569 Patrick Trainer: Okay, let’s let’s actually do like hub, spot.
688 00:48:15.930 ⇒ 00:48:16.800 Patrick Trainer: score
689 00:48:17.510 ⇒ 00:48:18.390 Patrick Trainer: filter.
690 00:48:18.669 ⇒ 00:48:21.459 Uttam Kumaran: Yeah, that way. That’s super clear. So that if we
691 00:48:21.650 ⇒ 00:48:22.340 Uttam Kumaran: change these.
692 00:48:22.340 ⇒ 00:48:22.970 Patrick Trainer: Maybe.
693 00:48:22.970 ⇒ 00:48:23.700 Uttam Kumaran: Where to go.
694 00:48:23.700 ⇒ 00:48:24.829 Patrick Trainer: We just like.
695 00:48:26.110 ⇒ 00:48:26.650 Patrick Trainer: let’s see.
696 00:48:26.650 ⇒ 00:48:27.210 Uttam Kumaran: Yeah.
697 00:48:27.210 ⇒ 00:48:27.590 Patrick Trainer: Scored.
698 00:48:27.590 ⇒ 00:48:31.690 Uttam Kumaran: And then subcategory. What’s up? What is subcategory is that the property.
699 00:48:31.960 ⇒ 00:48:34.209 Patrick Trainer: Yeah, so that’s gonna be.
700 00:48:34.210 ⇒ 00:48:35.400 Uttam Kumaran: Company, property.
701 00:48:36.140 ⇒ 00:48:39.489 Patrick Trainer: Yes, the company property. But then there’s also
702 00:48:39.590 ⇒ 00:48:40.210 Patrick Trainer: like.
703 00:48:40.210 ⇒ 00:48:42.369 Uttam Kumaran: Oh, like, okay. Decision. Maker.
704 00:48:42.370 ⇒ 00:48:49.920 Patrick Trainer: Like that’s going to be like on the contact. So there’s a property, and just like it, think about it as like
705 00:48:50.580 ⇒ 00:48:52.280 Patrick Trainer: different SQL tables. Right? There’s.
706 00:48:52.280 ⇒ 00:48:52.680 Uttam Kumaran: Yeah.
707 00:48:52.680 ⇒ 00:48:53.710 Patrick Trainer: Property table
708 00:48:54.148 ⇒ 00:49:00.510 Patrick Trainer: and then there’s like a contact table. And then there’s a company table, and it’s like we’re attributing those properties
709 00:49:00.820 ⇒ 00:49:02.080 Patrick Trainer: on those tables.
710 00:49:05.350 ⇒ 00:49:06.520 Uttam Kumaran: Okay, don’t.
711 00:49:07.460 ⇒ 00:49:10.650 Patrick Trainer: Yeah, it’s like, and then, like, there’s
712 00:49:10.990 ⇒ 00:49:12.989 Patrick Trainer: away in here
713 00:49:13.270 ⇒ 00:49:14.680 Patrick Trainer: to see.
714 00:49:17.280 ⇒ 00:49:20.079 Patrick Trainer: I think it’s this, okay, yeah, these are like, all.
715 00:49:20.080 ⇒ 00:49:22.000 Uttam Kumaran: Oh, okay. Great. Great.
716 00:49:22.000 ⇒ 00:49:24.669 Patrick Trainer: Yeah, you can see, like all of the odd shit
717 00:49:26.240 ⇒ 00:49:28.450 Patrick Trainer: you have to click everything.
718 00:49:31.270 ⇒ 00:49:34.720 Patrick Trainer: But there’s like a way, oh, okay.
719 00:49:35.450 ⇒ 00:49:38.740 Patrick Trainer: you can see the entire data model, right?
720 00:49:38.740 ⇒ 00:49:39.749 Uttam Kumaran: Oh, nice. Okay.
721 00:49:39.750 ⇒ 00:49:41.020 Patrick Trainer: You have a company.
722 00:49:41.260 ⇒ 00:49:44.119 Patrick Trainer: A company has a contact, contact.
723 00:49:44.660 ⇒ 00:49:45.389 Patrick Trainer: has a
724 00:49:45.560 ⇒ 00:49:46.729 Patrick Trainer: has a ticket.
725 00:49:49.320 ⇒ 00:49:52.200 Patrick Trainer: Dang! You can zoom in, zoom out, but you can’t
726 00:49:52.720 ⇒ 00:49:53.470 Patrick Trainer: like
727 00:49:53.640 ⇒ 00:49:56.500 Patrick Trainer: through scrolling, but you can’t scroll left or right.
728 00:49:58.180 ⇒ 00:50:00.340 Patrick Trainer: Okay? And then you have sales, objects.
729 00:50:00.690 ⇒ 00:50:03.409 Uttam Kumaran: I think if you probably hold shift in zoom, it’ll work. Try that.
730 00:50:04.110 ⇒ 00:50:06.269 Uttam Kumaran: Nope. Oh, never mind. Okay.
731 00:50:07.300 ⇒ 00:50:07.990 Uttam Kumaran: okay.
732 00:50:08.650 ⇒ 00:50:09.840 Patrick Trainer: Is marketers.
733 00:50:10.050 ⇒ 00:50:14.419 Patrick Trainer: And then you have activities. So like activities.
734 00:50:18.590 ⇒ 00:50:20.169 Patrick Trainer: fuck is going on here.
735 00:50:22.400 ⇒ 00:50:24.200 Patrick Trainer: Okay, like quotes.
736 00:50:24.390 ⇒ 00:50:26.109 Patrick Trainer: all this stuff
737 00:50:26.670 ⇒ 00:50:27.890 Patrick Trainer: can’t move those
738 00:50:29.440 ⇒ 00:50:30.880 Patrick Trainer: was analysis.
739 00:50:34.430 ⇒ 00:50:35.879 Patrick Trainer: I think this is just.
740 00:50:37.550 ⇒ 00:50:38.800 Patrick Trainer: oh, okay.
741 00:50:39.480 ⇒ 00:50:40.529 Patrick Trainer: see what you’re saying.
742 00:50:44.490 ⇒ 00:50:47.140 Patrick Trainer: yeah. But we have all of these different
743 00:50:47.200 ⇒ 00:50:49.999 Patrick Trainer: objects, right? Which are just
744 00:50:50.070 ⇒ 00:50:51.890 Patrick Trainer: going to different
745 00:50:53.560 ⇒ 00:50:56.089 Patrick Trainer: the tables. So we’ve got like.
746 00:50:56.220 ⇒ 00:50:57.780 Patrick Trainer: here’s our company table.
747 00:50:57.920 ⇒ 00:50:58.770 Patrick Trainer: You’ve got
748 00:50:59.200 ⇒ 00:51:01.760 Patrick Trainer: hope hydration. You got
749 00:51:01.940 ⇒ 00:51:03.130 Patrick Trainer: beehive
750 00:51:04.350 ⇒ 00:51:05.290 Patrick Trainer: gone.
751 00:51:06.540 ⇒ 00:51:08.089 Patrick Trainer: That’s a terrible name.
752 00:51:11.522 ⇒ 00:51:12.819 Patrick Trainer: It’s yeah like.
753 00:51:14.380 ⇒ 00:51:15.859 Patrick Trainer: never mind
754 00:51:17.390 ⇒ 00:51:18.560 Patrick Trainer: And then we got.
755 00:51:18.650 ⇒ 00:51:19.220 Uttam Kumaran: Cool.
756 00:51:19.220 ⇒ 00:51:19.960 Patrick Trainer: Excuse me
757 00:51:20.540 ⇒ 00:51:21.570 Patrick Trainer: by Forge.
758 00:51:21.810 ⇒ 00:51:25.220 Patrick Trainer: and we come back to companies, and we can
759 00:51:27.410 ⇒ 00:51:29.369 Patrick Trainer: look at these
760 00:51:30.690 ⇒ 00:51:34.139 Patrick Trainer: objects. We don’t have anything else except for contacts.
761 00:51:34.960 ⇒ 00:51:37.590 Patrick Trainer: But here’s like all the contacts and
762 00:51:41.120 ⇒ 00:51:42.529 Patrick Trainer: looks like it updated.
763 00:51:43.140 ⇒ 00:51:44.080 Patrick Trainer: So
764 00:51:44.470 ⇒ 00:51:46.019 Patrick Trainer: you should call me
765 00:51:46.860 ⇒ 00:51:48.100 Patrick Trainer: and see
766 00:51:48.250 ⇒ 00:51:50.029 Patrick Trainer: see if I want to buy Brain Forge
767 00:51:52.380 ⇒ 00:51:55.120 Patrick Trainer: and then we could also probably create like a
768 00:51:55.650 ⇒ 00:51:57.250 Patrick Trainer: a filter and a score.
769 00:51:58.210 ⇒ 00:52:00.920 Uttam Kumaran: And there’s no cost to running the scores again and again.
770 00:52:01.300 ⇒ 00:52:02.000 Uttam Kumaran: Correct.
771 00:52:02.300 ⇒ 00:52:07.680 Uttam Kumaran: Okay, cool. So I guess before let’s can we? Can you check how to get the Apollo stuff in there. Now.
772 00:52:07.680 ⇒ 00:52:09.399 Patrick Trainer: Yeah, so they’re.
773 00:52:09.400 ⇒ 00:52:15.379 Uttam Kumaran: Let’s try that, and then that, and then that way. The last thing I think will just be continuing to beef up the filter.
774 00:52:15.380 ⇒ 00:52:17.970 Patrick Trainer: I think this will. This will be nice. So there’s
775 00:52:18.070 ⇒ 00:52:19.970 Patrick Trainer: integrations
776 00:52:20.760 ⇒ 00:52:21.540 Patrick Trainer: right?
777 00:52:22.200 ⇒ 00:52:24.720 Patrick Trainer: Apollo integration, literally the 1st one.
778 00:52:25.170 ⇒ 00:52:26.950 Patrick Trainer: And so.
779 00:52:27.250 ⇒ 00:52:28.559 Uttam Kumaran: I think there’s something.
780 00:52:28.560 ⇒ 00:52:28.970 Patrick Trainer: Already.
781 00:52:28.970 ⇒ 00:52:30.149 Uttam Kumaran: You you were in the.
782 00:52:30.150 ⇒ 00:52:31.410 Patrick Trainer: Says it’s installed.
783 00:52:31.410 ⇒ 00:52:33.140 Uttam Kumaran: Yeah, I installed as much as
784 00:52:33.570 ⇒ 00:52:40.320 Uttam Kumaran: I basically tried to connect to everything we were doing. But I don’t know where you go to actually do the oh, go to import export data management.
785 00:52:45.640 ⇒ 00:52:48.590 Uttam Kumaran: I don’t know why you were on it somewhere.
786 00:52:49.870 ⇒ 00:52:51.360 Patrick Trainer: Yeah, I was.
787 00:52:51.690 ⇒ 00:52:53.100 Uttam Kumaran: Maybe if you go to
788 00:52:53.190 ⇒ 00:52:54.380 Uttam Kumaran: contacts.
789 00:52:54.380 ⇒ 00:52:57.690 Patrick Trainer: I think I remember it was
790 00:52:58.190 ⇒ 00:53:01.749 Patrick Trainer: here. Oh, yeah, that’s where it was. It was in contacts.
791 00:53:02.150 ⇒ 00:53:03.750 Patrick Trainer: Then we import
792 00:53:04.830 ⇒ 00:53:07.669 Patrick Trainer: sync data between, set up a sync.
793 00:53:09.240 ⇒ 00:53:11.720 Patrick Trainer: What is it called Apollo?
794 00:53:12.580 ⇒ 00:53:13.240 Patrick Trainer: What.
795 00:53:14.310 ⇒ 00:53:15.999 Uttam Kumaran: Maybe there’s something else you have to do.
796 00:53:19.380 ⇒ 00:53:20.720 Uttam Kumaran: List
797 00:53:21.400 ⇒ 00:53:22.540 Uttam Kumaran: how’s call it?
798 00:53:34.000 ⇒ 00:53:35.810 Patrick Trainer: What’s the what was the shit that.
799 00:53:35.810 ⇒ 00:53:39.570 Uttam Kumaran: Oh, you have to do it in. You have to do it in in Apollo.
800 00:53:40.110 ⇒ 00:53:40.760 Patrick Trainer: Yeah.
801 00:53:40.980 ⇒ 00:53:42.349 Uttam Kumaran: It’s a push.
802 00:53:42.520 ⇒ 00:53:44.559 Patrick Trainer: Invalid access credentials.
803 00:53:45.730 ⇒ 00:53:48.330 Patrick Trainer: Apollo. Request access?
804 00:53:48.450 ⇒ 00:53:49.370 Patrick Trainer: Why?
805 00:53:53.020 ⇒ 00:53:54.470 Patrick Trainer: Oh, it’s like hitting.
806 00:53:57.630 ⇒ 00:54:00.413 Uttam Kumaran: So in Apollo, go to
807 00:54:01.740 ⇒ 00:54:03.119 Patrick Trainer: Oh, I’m not signed in.
808 00:54:05.000 ⇒ 00:54:07.029 Patrick Trainer: Oh, wait! No, I gotta use you.
809 00:54:07.030 ⇒ 00:54:08.419 Uttam Kumaran: Yeah, it’s under me.
810 00:54:09.150 ⇒ 00:54:11.309 Uttam Kumaran: I can try to do it, too, while I’m in here.
811 00:54:11.310 ⇒ 00:54:12.609 Patrick Trainer: Here I got it.
812 00:54:15.060 ⇒ 00:54:18.490 Uttam Kumaran: Cool, it says, go to setting integrations. Hubspot.
813 00:54:19.810 ⇒ 00:54:22.509 Patrick Trainer: Oh, are you doing it right now, or you want me to do it?
814 00:54:22.792 ⇒ 00:54:25.049 Uttam Kumaran: I can do it. I’m just poking around.
815 00:54:25.900 ⇒ 00:54:27.360 Patrick Trainer: Bi-directional sync.
816 00:54:34.450 ⇒ 00:54:35.830 Uttam Kumaran: So.
817 00:54:35.830 ⇒ 00:54:38.280 Patrick Trainer: Okay, push all new contacts.
818 00:54:39.370 ⇒ 00:54:40.040 Uttam Kumaran: Well.
819 00:54:40.040 ⇒ 00:54:41.859 Patrick Trainer: Or all her father.
820 00:54:42.250 ⇒ 00:54:43.850 Patrick Trainer: Okay, automatically, pull.
821 00:54:43.850 ⇒ 00:54:44.779 Uttam Kumaran: Check, push, content.
822 00:54:44.780 ⇒ 00:54:45.230 Patrick Trainer: Yeah, that’s.
823 00:54:45.230 ⇒ 00:54:50.939 Uttam Kumaran: Push any newly created or updated contacts. When you push a new contact, Apollo pushes the account.
824 00:54:51.430 ⇒ 00:54:55.340 Uttam Kumaran: After enabling push all Apollo to push all your contacts.
825 00:54:56.950 ⇒ 00:54:58.580 Uttam Kumaran: push details
826 00:55:02.670 ⇒ 00:55:05.470 Uttam Kumaran: or you can push them based on certain stages.
827 00:55:11.700 ⇒ 00:55:13.000 Uttam Kumaran: Okay, cool.
828 00:55:15.340 ⇒ 00:55:17.639 Uttam Kumaran: And you could also push individual ones.
829 00:55:19.220 ⇒ 00:55:19.950 Patrick Trainer: Okay.
830 00:55:20.060 ⇒ 00:55:21.130 Patrick Trainer: so let’s
831 00:55:26.630 ⇒ 00:55:28.269 Patrick Trainer: the hell. Are contacts.
832 00:55:31.440 ⇒ 00:55:33.980 Uttam Kumaran: Oh, contact status! I don’t know what.
833 00:55:51.740 ⇒ 00:55:52.590 Patrick Trainer: Okay.
834 00:56:01.100 ⇒ 00:56:03.049 Patrick Trainer: Oh, look! No! This already.
835 00:56:03.170 ⇒ 00:56:04.510 Patrick Trainer: this already synced.
836 00:56:07.140 ⇒ 00:56:08.080 Uttam Kumaran: I think back.
837 00:56:11.060 ⇒ 00:56:11.980 Patrick Trainer: Yeah.
838 00:56:17.030 ⇒ 00:56:19.239 Patrick Trainer: okay, alright. So we
839 00:56:19.460 ⇒ 00:56:20.790 Patrick Trainer: change this
840 00:56:21.090 ⇒ 00:56:23.920 Patrick Trainer: in Hubspot sync back to this.
841 00:56:26.260 ⇒ 00:56:29.459 Uttam Kumaran: I guess you just wanna make sure that you have all the fields you need.
842 00:56:31.130 ⇒ 00:56:31.830 Patrick Trainer: Okay.
843 00:56:32.030 ⇒ 00:56:34.869 Patrick Trainer: okay? And then it can bring me to this.
844 00:56:38.710 ⇒ 00:56:39.880 Uttam Kumaran: Contacts.
845 00:56:39.880 ⇒ 00:56:41.260 Patrick Trainer: How the hell do you think.
846 00:56:44.420 ⇒ 00:56:48.549 Uttam Kumaran: Well here. This I mean, there’s if you go to Sync, there’s a thing there’s a button that says.
847 00:56:48.620 ⇒ 00:56:50.090 Uttam Kumaran: push all contacts.
848 00:56:53.140 ⇒ 00:56:54.459 Patrick Trainer: The hell is sync.
849 00:56:55.780 ⇒ 00:56:58.919 Uttam Kumaran: You have to go to. You have to go to Hubspot in the settings
850 00:57:00.580 ⇒ 00:57:01.610 Uttam Kumaran: and integration.
851 00:57:01.610 ⇒ 00:57:04.890 Patrick Trainer: But like no, what about like pushing the Apollo
852 00:57:05.330 ⇒ 00:57:07.020 Patrick Trainer: contacts to Hubspot.
853 00:57:12.240 ⇒ 00:57:16.810 Uttam Kumaran: There is a hubspot! Action called push to Hubspot!
854 00:57:18.590 ⇒ 00:57:22.130 Uttam Kumaran: Launch, Apollo! Click, search, click! Saved.
855 00:57:22.680 ⇒ 00:57:26.709 Uttam Kumaran: then click! Hubspot action beside the contact account.
856 00:57:27.690 ⇒ 00:57:29.519 Patrick Trainer: Oh, is it the save lists.
857 00:57:30.420 ⇒ 00:57:33.629 Uttam Kumaran: Yeah, like, just go to the go to the list
858 00:57:34.340 ⇒ 00:57:36.830 Uttam Kumaran: and see there should be Hubspot actions.
859 00:57:37.080 ⇒ 00:57:39.710 Uttam Kumaran: No, no! Within the individual record.
860 00:57:40.770 ⇒ 00:57:43.040 Uttam Kumaran: There’s a little hubspot icon on the top.
861 00:57:44.070 ⇒ 00:57:47.389 Uttam Kumaran: the little hubspot thing in the in the nav bar.
862 00:57:47.960 ⇒ 00:57:48.560 Patrick Trainer: This.
863 00:57:48.750 ⇒ 00:57:50.179 Uttam Kumaran: No, it’s kind of like a
864 00:57:51.260 ⇒ 00:57:53.120 Uttam Kumaran: see it, says Hubspot. Next to enrich.
865 00:57:53.120 ⇒ 00:57:54.680 Patrick Trainer: Oh, oh, okay.
866 00:57:58.090 ⇒ 00:58:00.799 Patrick Trainer: I hate this. Ui.
867 00:58:02.880 ⇒ 00:58:06.360 Patrick Trainer: Okay, okay, I see. Push to Hubspot.
868 00:58:06.420 ⇒ 00:58:08.350 Patrick Trainer: Alright. So let’s actually go
869 00:58:08.410 ⇒ 00:58:10.189 Patrick Trainer: and push someone
870 00:58:11.640 ⇒ 00:58:12.490 Patrick Trainer: else.
871 00:58:14.210 ⇒ 00:58:19.250 Uttam Kumaran: Well, try the people, try the people that we were doing with like, go to the go to the list that we were just doing.
872 00:58:20.740 ⇒ 00:58:22.440 Patrick Trainer: Have we added them to a list.
873 00:58:24.720 ⇒ 00:58:27.270 Uttam Kumaran: They’re they’re all in a safe search.
874 00:58:28.660 ⇒ 00:58:29.590 Patrick Trainer: Okay.
875 00:58:29.930 ⇒ 00:58:30.500 Abigail Zhao: Well.
876 00:58:32.700 ⇒ 00:58:35.290 Abigail Zhao: It’s blocking the yeah, right there.
877 00:58:35.290 ⇒ 00:58:38.699 Patrick Trainer: Okay, save search, high growth logistics.
878 00:58:45.540 ⇒ 00:58:46.859 Patrick Trainer: Alright, it’s these 3.
879 00:58:47.110 ⇒ 00:58:47.790 Uttam Kumaran: Yeah.
880 00:58:50.890 ⇒ 00:58:51.640 Uttam Kumaran: like.
881 00:58:52.310 ⇒ 00:58:54.320 Patrick Trainer: This is so dumb. Come on!
882 00:58:54.750 ⇒ 00:58:57.309 Patrick Trainer: Why do I have to click this and then click another button.
883 00:58:58.905 ⇒ 00:58:59.510 Patrick Trainer: Alright!
884 00:59:00.220 ⇒ 00:59:01.349 Patrick Trainer: Push the Hubspot.
885 00:59:06.090 ⇒ 00:59:07.740 Uttam Kumaran: So save them to a list
886 00:59:10.280 ⇒ 00:59:12.520 Uttam Kumaran: like save hit, save.
887 00:59:13.610 ⇒ 00:59:14.810 Patrick Trainer: Add to list.
888 00:59:15.000 ⇒ 00:59:15.810 Uttam Kumaran: Yeah.
889 00:59:16.040 ⇒ 00:59:16.740 Uttam Kumaran: okay.
890 00:59:16.740 ⇒ 00:59:17.160 Patrick Trainer: Well.
891 00:59:17.160 ⇒ 00:59:19.009 Uttam Kumaran: Create a new list with the same name.
892 00:59:19.790 ⇒ 00:59:23.359 Uttam Kumaran: It’s like high growth, single test, or something like that.
893 00:59:23.970 ⇒ 00:59:25.609 Patrick Trainer: Yeah, we’ll just do test
894 00:59:25.780 ⇒ 00:59:26.590 Patrick Trainer: hi
895 00:59:28.590 ⇒ 00:59:29.370 Patrick Trainer: growth
896 00:59:30.440 ⇒ 00:59:31.620 Patrick Trainer: logistics.
897 00:59:35.420 ⇒ 00:59:36.210 Patrick Trainer: Safe.
898 00:59:39.990 ⇒ 00:59:40.920 Patrick Trainer: Okay?
899 00:59:42.580 ⇒ 00:59:44.469 Uttam Kumaran: And go to save lists at the top.
900 00:59:46.470 ⇒ 00:59:47.190 Patrick Trainer: Lists.
901 00:59:48.359 ⇒ 00:59:51.239 Patrick Trainer: Test, high growth logistics.
902 00:59:55.320 ⇒ 00:59:56.360 Patrick Trainer: Dom
903 00:59:57.640 ⇒ 01:00:00.339 Patrick Trainer: Hubspot. We’re gonna push them.
904 01:00:02.770 ⇒ 01:00:04.790 Patrick Trainer: Okay, brandy.
905 01:00:05.390 ⇒ 01:00:09.000 Uttam Kumaran: Oh, so you’re it! Said one of them was missing an email. There was an error.
906 01:00:10.230 ⇒ 01:00:10.900 Uttam Kumaran: But
907 01:00:11.450 ⇒ 01:00:13.180 Uttam Kumaran: one scroll to the right.
908 01:00:13.180 ⇒ 01:00:15.229 Patrick Trainer: Oh, yeah, it’s I. I think it’s this one.
909 01:00:15.380 ⇒ 01:00:16.290 Uttam Kumaran: Oh, okay.
910 01:00:16.930 ⇒ 01:00:18.050 Uttam Kumaran: Okay. Cool.
911 01:00:19.170 ⇒ 01:00:21.260 Uttam Kumaran: But let’s see if they got scores. Then.
912 01:00:23.410 ⇒ 01:00:24.940 Patrick Trainer: Brandi Decker.
913 01:00:41.600 ⇒ 01:00:44.520 Patrick Trainer: We couldn’t like see it from there.
914 01:00:44.520 ⇒ 01:00:47.076 Uttam Kumaran: I think maybe you have to add the property to like the.
915 01:00:47.290 ⇒ 01:00:51.270 Patrick Trainer: Yeah. Yeah. Oh, well, here’s Christopher Tune. He was.
916 01:00:51.380 ⇒ 01:00:53.390 Patrick Trainer: Oh, and here’s both of them actually.
917 01:00:57.360 ⇒ 01:01:02.140 Uttam Kumaran: So now you can run the test with the other one. Right with the you can run the filter test.
918 01:01:03.630 ⇒ 01:01:04.970 Patrick Trainer: Yeah, I don’t know why
919 01:01:05.270 ⇒ 01:01:07.600 Patrick Trainer: this didn’t update the.
920 01:01:09.910 ⇒ 01:01:11.120 Patrick Trainer: You would think it would.
921 01:01:12.870 ⇒ 01:01:15.879 Uttam Kumaran: I guess it should be 0 if it didn’t hit anything.
922 01:01:16.420 ⇒ 01:01:19.959 Uttam Kumaran: Try to bring them. Try to bring them into the thing you process you were doing before.
923 01:01:20.410 ⇒ 01:01:21.100 Patrick Trainer: And a
924 01:01:32.580 ⇒ 01:01:35.309 Patrick Trainer: okay, it should have 10. Maybe it just hasn’t.
925 01:01:36.720 ⇒ 01:01:39.030 Uttam Kumaran: Yeah. Maybe it’s takes some time.
926 01:01:39.030 ⇒ 01:01:39.940 Patrick Trainer: Yeah, maybe it
927 01:01:40.560 ⇒ 01:01:42.139 Patrick Trainer: on some sort of crown.
928 01:01:43.850 ⇒ 01:01:44.930 Patrick Trainer: Let’s see
929 01:01:45.270 ⇒ 01:01:47.850 Patrick Trainer: if this has updated them.
930 01:01:52.850 ⇒ 01:01:53.510 Patrick Trainer: Share it.
931 01:01:53.850 ⇒ 01:01:54.540 Patrick Trainer: tax
932 01:02:00.590 ⇒ 01:02:01.440 Patrick Trainer: the hell.
933 01:02:05.940 ⇒ 01:02:08.000 Uttam Kumaran: Yeah, I don’t know how long it takes.
934 01:02:12.580 ⇒ 01:02:17.230 Uttam Kumaran: Oh, if you take up again for it, I think it can take some time.
935 01:02:18.370 ⇒ 01:02:19.080 Patrick Trainer: Really.
936 01:02:19.240 ⇒ 01:02:19.990 Uttam Kumaran: Yeah.
937 01:02:26.470 ⇒ 01:02:27.709 Patrick Trainer: Let’s just learn more.
938 01:02:30.650 ⇒ 01:02:34.430 Uttam Kumaran: Most most score property should update within a few minutes.
939 01:02:36.170 ⇒ 01:02:40.790 Uttam Kumaran: but it can take up to 2 h, and the database is large. So let’s monitor.
940 01:02:40.820 ⇒ 01:02:45.790 Uttam Kumaran: Let’s monitor throughout the next meeting. But okay, just like to close this out
941 01:02:45.820 ⇒ 01:02:55.079 Uttam Kumaran: one, if can you filter? Can you finish up the filters? Because then I’m I think now, it’s actually really clear how we do the links. Basically what I’m gonna look at.
942 01:02:55.080 ⇒ 01:02:56.560 Patrick Trainer: Randy Decker, 10.
943 01:02:57.100 ⇒ 01:03:03.309 Uttam Kumaran: Okay, cool. So his net, I think his will come at some point. So can we filter? Can we finish up the filters?
944 01:03:03.810 ⇒ 01:03:04.510 Uttam Kumaran: Yeah.
945 01:03:05.309 ⇒ 01:03:15.530 Uttam Kumaran: Let’s if you can do that, then I’m going to start to create. I think the campaign list looks fine in Apollo. So I’m going to start to basically come up with
946 01:03:15.580 ⇒ 01:03:17.460 Uttam Kumaran: 3 to 5 campaigns.
947 01:03:17.630 ⇒ 01:03:19.460 Uttam Kumaran: and then we’ll then create
948 01:03:19.600 ⇒ 01:03:21.439 Uttam Kumaran: the lead list for them.
949 01:03:21.650 ⇒ 01:03:24.109 Uttam Kumaran: And it looks like in order to do
950 01:03:24.860 ⇒ 01:03:28.930 Uttam Kumaran: what what we’ll do is like, I’ll I’ll look about how we can.
951 01:03:29.010 ⇒ 01:03:33.380 Uttam Kumaran: I think, for now what we’ll do once a week we’ll just basically push stuff into Hubspot
952 01:03:33.940 ⇒ 01:03:38.960 Uttam Kumaran: for those. And then the next thing I want to work on is, how do we get the Hubspot stuff into instantly?
953 01:03:39.540 ⇒ 01:03:42.979 Uttam Kumaran: Alright. So we’ll try to do another meeting this week on, how do we
954 01:03:43.080 ⇒ 01:03:44.600 Uttam Kumaran: take these guys
955 01:03:44.750 ⇒ 01:03:47.029 Uttam Kumaran: get them into instantly with the right
956 01:03:47.070 ⇒ 01:03:48.600 Uttam Kumaran: emails? Basically.
957 01:03:49.370 ⇒ 01:03:51.170 Uttam Kumaran: right? But this is great.
958 01:03:52.040 ⇒ 01:03:54.260 Patrick Trainer: Yeah, this this is solid. I’m glad to.
959 01:03:54.260 ⇒ 01:03:59.120 Uttam Kumaran: So will the Hubspot. You’re if you add filters. The new score runs on everybody.
960 01:04:00.490 ⇒ 01:04:01.160 Patrick Trainer: Yes.
961 01:04:01.410 ⇒ 01:04:02.659 Uttam Kumaran: Okay. Okay. Cool.
962 01:04:03.050 ⇒ 01:04:04.519 Patrick Trainer: Yeah, cause remember.
963 01:04:05.130 ⇒ 01:04:06.510 Patrick Trainer: added the
964 01:04:07.740 ⇒ 01:04:09.010 Patrick Trainer: Whatchamacall, it
965 01:04:09.370 ⇒ 01:04:10.240 Patrick Trainer: to me.
966 01:04:19.210 ⇒ 01:04:19.820 Patrick Trainer: Okay, cool.
967 01:04:19.820 ⇒ 01:04:23.489 Uttam Kumaran: Let’s hop on. Let’s hop to the team meeting. But chat. Let’s chat in slack.
968 01:04:24.820 ⇒ 01:04:25.660 Uttam Kumaran: sweet
969 01:04:26.160 ⇒ 01:04:27.040 Uttam Kumaran: thanks, guys.