Meeting Title: Brainforge Project Management Sync Date: 2025-08-07 Meeting participants: Giselle Agot, Uttam Kumaran, Ryan DeForest, Mustafa Raja, Lev Katreczko, Henry Zhao
WEBVTT
1 00:00:40.086 ⇒ 00:00:41.793 Uttam Kumaran: Hello!
2 00:00:43.500 ⇒ 00:00:47.890 Ryan DeForest: Yo sounds like sounds like you’re in a subway, or something like that.
3 00:00:48.785 ⇒ 00:00:49.629 Uttam Kumaran: Me!
4 00:00:49.630 ⇒ 00:00:50.200 Ryan DeForest: Yeah.
5 00:00:50.200 ⇒ 00:00:53.280 Uttam Kumaran: Cars. It’s just the cars. Hold on! I’ll stay on mute.
6 00:00:53.540 ⇒ 00:00:54.700 Ryan DeForest: Oh, you’re good.
7 00:01:02.320 ⇒ 00:01:04.390 Ryan DeForest: I’m not sure.
8 00:01:04.780 ⇒ 00:01:08.769 Ryan DeForest: Lev said. He’ll be a couple of minutes late, but if we’re waiting for anybody else on your side.
9 00:01:09.940 ⇒ 00:01:36.325 Uttam Kumaran: Yeah, we’ll wait for Mustafa and then, while we’re waiting, Giselle. This is Ryan Ryan. This is Giselle Giselle is joining our project management team. Sort of helping. Just keep some things organized in the background. You think you mentioned amber but we’re sort of growing our own team. So Amber was is juggling like 10 projects. So we’re excited to have Giselle join and take on some, and she’ll be kind of helping keep things organized. So.
10 00:01:36.640 ⇒ 00:01:40.809 Ryan DeForest: Awesome nice to meet you as well.
11 00:01:43.070 ⇒ 00:01:44.120 Uttam Kumaran: Just a moment
12 00:01:45.260 ⇒ 00:01:52.780 Uttam Kumaran: cool, so we can get started, and I think Lev can jump in. So, Mustafa, I would love for you to
13 00:01:52.970 ⇒ 00:02:08.470 Uttam Kumaran: walk through the clay tables and then show where things ended up on the those test accounts in salesforce. So we can run through that. And then we can just have a discussion on whether we want to start executing this for other accounts. And
14 00:02:08.860 ⇒ 00:02:12.989 Uttam Kumaran: yeah, I think I want to spend as much time just getting feedback from Ryan.
15 00:02:12.990 ⇒ 00:02:16.650 Mustafa Raja: Okay, let me share my screen for that.
16 00:03:08.470 ⇒ 00:03:11.539 Mustafa Raja: No, I just want to pull it up later.
17 00:03:13.370 ⇒ 00:03:16.259 Mustafa Raja: So we worked on 2 of the combos.
18 00:03:18.660 ⇒ 00:03:35.140 Mustafa Raja: one one of them is fragmentation without orchestration. And ops hiring. So what we do is we? Firstly, let’s see what that, we created a view. For the accounts.
19 00:03:37.011 ⇒ 00:03:43.388 Mustafa Raja: It’s brain forge. And for any account to be in this view.
20 00:03:44.590 ⇒ 00:03:47.619 Mustafa Raja: it needs to have this check.
21 00:03:47.930 ⇒ 00:04:06.039 Mustafa Raja: this checked, so enrichment, so enrichment ready, must be true for any account to be in this brain forge view that we have here, and once this once we created this view, we were able to pull all of these accounts into the clay.
22 00:04:06.880 ⇒ 00:04:28.739 Mustafa Raja: and then what we do is through their stack. We fetch the tools that these companies are using, and also the jobs that they’ve been posting for a month. This tag did not know about tabs, platform and rainforge these 2 companies on this their stack did not know about. So
23 00:04:29.240 ⇒ 00:04:56.870 Mustafa Raja: so furthermore, what I did is, I added, AI steps for the signals since we, since we now have the tools and technologies that these companies are using. On that data, I added these Gpt steps to analyze their tools and technologies that they are using. So we can then get our responses.
24 00:04:57.937 ⇒ 00:05:05.310 Mustafa Raja: and and then simply update those records. Similarly, for the second
25 00:05:06.221 ⇒ 00:05:10.529 Mustafa Raja: combo, we did. We did a SIM similar things. We didn’t need the
26 00:05:11.545 ⇒ 00:05:16.255 Mustafa Raja: jobs for these companies here.
27 00:05:17.800 ⇒ 00:05:25.150 Mustafa Raja: And we added a and a Gpt step to analyze the data.
28 00:05:25.971 ⇒ 00:05:47.869 Mustafa Raja: And then 2 clay agents. These, what what they did their responsibility was to look into the websites of these companies, and then let us know if they have dual conversion parts, or if they could find form friction this.
29 00:05:48.543 ⇒ 00:05:57.879 Mustafa Raja: This clear agent is is somewhat someone like Gpt, 4 0, so
30 00:05:57.890 ⇒ 00:06:24.239 Mustafa Raja: pretty normal, pretty? Okay. But this one is this one is interesting, this this agent can take browser actions. When it’s looking into a website or web page so this, this was able to find some of the form frictions that we needed. And let’s analyze one response. So we can actually see that the steps it has taken
31 00:06:24.933 ⇒ 00:06:32.789 Mustafa Raja: and we see that it it went in in this website. And perform some of the actions. And
32 00:06:33.100 ⇒ 00:06:39.050 Mustafa Raja: you can see that it clicked the button, and then we can see that
33 00:06:40.922 ⇒ 00:06:56.210 Mustafa Raja: it did click another button. So so these are the actions that it did perform on their website when it when it went there to analyze their forms. Yeah, so this is pretty much it for the for the 2 combos that we worked on
34 00:06:57.661 ⇒ 00:07:07.850 Mustafa Raja: and if you want to see the data that we update, we can just go to any of these accounts. Let’s go to triple lift.
35 00:07:09.580 ⇒ 00:07:26.339 Mustafa Raja: And we have. We did add the the custom properties that we would need for these signals. It starts from this enrichment ready. I already explained that we need this to be checked for an account to be in Brain Forge list.
36 00:07:27.420 ⇒ 00:07:36.300 Mustafa Raja: and then the rest of the properties are going to be filled by these Combos that we have.
37 00:07:39.130 ⇒ 00:07:46.449 Ryan DeForest: Guys. So right now, it’s the category overlap score. And the form friction score is kind of the 2 big things from these Combos is that was you.
38 00:07:46.450 ⇒ 00:07:47.690 Mustafa Raja: Let’s say.
39 00:07:47.920 ⇒ 00:07:55.519 Mustafa Raja: yeah, we can actually see all of the scores that were being edited. Let me pull up the sheet.
40 00:08:01.540 ⇒ 00:08:24.719 Mustafa Raja: So the so all category, overlap, score, high tool, count, orchestration, platform present Ops roles, process, improvement, hiring, dual conversion parts, enrichment, present and form friction. These all these properties would be would have been edited. By our signals over here.
41 00:08:25.660 ⇒ 00:08:26.610 Mustafa Raja: So if I look up.
42 00:08:26.954 ⇒ 00:08:30.399 Ryan DeForest: So on triple lift, and so all those would be.
43 00:08:30.600 ⇒ 00:08:31.340 Mustafa Raja: Yeah, yeah.
44 00:08:31.460 ⇒ 00:08:55.150 Mustafa Raja: all these. Yeah, you see, that high tool count is checked. This is checked by our enrichment. And the category overlap score was also a form friction also, and these one, these these were updated to. These are not checked because these did not match our requirements over here
45 00:08:57.820 ⇒ 00:08:58.760 Mustafa Raja: from Kate.
46 00:08:59.280 ⇒ 00:09:03.150 Ryan DeForest: Oh, from Clay Gotcha, okay? And then
47 00:09:03.340 ⇒ 00:09:07.829 Ryan DeForest: walk me through kind of like the scores. So I assume it’s out of a hundred. So
48 00:09:08.030 ⇒ 00:09:14.880 Ryan DeForest: category overlap just means that there’s a lot of tools that they have that do the same thing, or like we would assume.
49 00:09:15.613 ⇒ 00:09:20.070 Mustafa Raja: Let me open that up over here.
50 00:09:24.870 ⇒ 00:09:38.479 Mustafa Raja: So yeah, category overlap is if they are using tools of the same category. So 2 plus form tools or same tools for gathering and analytics, and so
51 00:09:40.620 ⇒ 00:09:44.970 Mustafa Raja: would be to
52 00:09:45.180 ⇒ 00:09:55.879 Mustafa Raja: category overlap. And then there’s a high tool count. This is for marketing, marketing or sales tax that has 15 or more tools detected.
53 00:09:56.502 ⇒ 00:10:08.329 Mustafa Raja: And then orchestration platform is if if you find J. Piper, revenue hero, lean data calendly, or something like that.
54 00:10:10.736 ⇒ 00:10:22.270 Mustafa Raja: And then form friction. We do. See? If if the forms are, somewhat complicated or not.
55 00:10:23.105 ⇒ 00:10:31.030 Mustafa Raja: And then we see if there’s enrichment tools present within the stack or not.
56 00:10:31.460 ⇒ 00:10:36.490 Uttam Kumaran: We don’t have to do out of a hundred like we can do like
57 00:10:36.660 ⇒ 00:10:41.164 Uttam Kumaran: a smaller version. But yeah, basically, we can label that score. Anyway.
58 00:10:41.920 ⇒ 00:10:46.559 Ryan DeForest: Gotcha. Yeah, yeah. No. Just curious. What like that? That’s out. That’s my thinking was about it.
59 00:10:47.450 ⇒ 00:10:52.300 Uttam Kumaran: So kind of like where we are now, it’s like, if you go back to the accounts and stuff
60 00:10:56.309 ⇒ 00:11:07.730 Uttam Kumaran: just to salesforce accounts. Yeah, so we have enrichments for these ready. And all of these can. Those properties can be now used to create reports?
61 00:11:08.425 ⇒ 00:11:12.879 Uttam Kumaran: So I guess I wanted to kind of get, maybe feedback.
62 00:11:13.020 ⇒ 00:11:34.380 Uttam Kumaran: We can either walk through one of these companies and kind of look at like, okay, do we think that we have enough properties to kind of make some of those signal reports, or would it be better for us, Ryan? We can. Either. Another option is okay. I’m happy with the properties. Let’s go do this for another 100 accounts. Kinda wanna get your sense on like, okay, how can we like.
63 00:11:34.380 ⇒ 00:11:34.820 Ryan DeForest: Sure.
64 00:11:34.820 ⇒ 00:11:41.779 Uttam Kumaran: Get this close to action so that we can get feedback on like, okay, these these are working. The lists are good before we go execute on the other, Combos.
65 00:11:42.140 ⇒ 00:11:50.369 Ryan DeForest: Yeah, let’s, I mean, I I actually like your 1st idea where we just click into one of these and go through it. So let’s do, actually, let’s actually do it for cortex.
66 00:11:55.010 ⇒ 00:12:08.300 Uttam Kumaran: So maybe. Let’s yeah, let’s let’s first, st let’s go through every single enrichment that we found. So okay, we found that they were. Yeah, we can just look at your this screen. So.
67 00:12:08.300 ⇒ 00:12:08.839 Mustafa Raja: Okay. Okay.
68 00:12:09.164 ⇒ 00:12:16.309 Uttam Kumaran: We look we. It looks like they yeah from the top. It looks like they. They’re enrichment ready. There’s some category overlap
69 00:12:16.690 ⇒ 00:12:20.900 Uttam Kumaran: high school account. They don’t have an orchestration. There’s
70 00:12:21.080 ⇒ 00:12:28.870 Uttam Kumaran: roles open for a couple of different things. I think probably my initial
71 00:12:29.020 ⇒ 00:12:42.479 Uttam Kumaran: feedback is like, I think we could probably consolidate some of these signals. I’ll have to think a little bit, but I think it’s also fine. If we want these as granular. It looks like they don’t have a chat, Widget. It looks like there is.
72 00:12:43.151 ⇒ 00:12:51.878 Mustafa Raja: For, for currently we already are only filling a property still form friction
73 00:12:52.550 ⇒ 00:12:53.680 Uttam Kumaran: Okay, okay, so the other ones are.
74 00:12:53.680 ⇒ 00:12:54.710 Mustafa Raja: Yeah, yeah.
75 00:12:55.170 ⇒ 00:13:01.789 Uttam Kumaran: So let’s go to cortex website. And let’s see if we can validate some of these. And also if you can go to their open jobs.
76 00:13:03.250 ⇒ 00:13:13.000 Uttam Kumaran: I guess. Like, if we can do 2 things, one. Can you? Can you find the clay run for cortex so we can have that side by side, and then also let’s go through their site together.
77 00:13:14.012 ⇒ 00:13:17.299 Uttam Kumaran: Let’s go through their form. Let’s take a look at their okay, perfect.
78 00:13:17.620 ⇒ 00:13:21.109 Uttam Kumaran: So just filter to the cortex row in cloud.
79 00:13:23.981 ⇒ 00:13:29.400 Uttam Kumaran: Okay, row 2. Yeah. Let’s just just let’s just have that displayed. So just filter to row 2.
80 00:13:40.620 ⇒ 00:13:44.539 Uttam Kumaran: Okay? So from the left. Okay, great.
81 00:13:45.430 ⇒ 00:13:48.410 Uttam Kumaran: cool. So if you scroll right.
82 00:13:49.060 ⇒ 00:13:58.380 Uttam Kumaran: the 1st thing we’re looking at is category overlap. So can you open that text and let’s look at like what the AI basically said as a reasonable
83 00:13:59.700 ⇒ 00:14:08.520 Uttam Kumaran: bye, okay, so bunch of programming languages, bunch of tools.
84 00:14:10.170 ⇒ 00:14:17.860 Uttam Kumaran: So I think, probably my feedback here, Mustafa is that some of these are not like, go to market tools. They’re more like
85 00:14:18.320 ⇒ 00:14:20.070 Uttam Kumaran: developer tools.
86 00:14:20.250 ⇒ 00:14:22.569 Uttam Kumaran: So like, I think in the
87 00:14:23.330 ⇒ 00:14:27.580 Uttam Kumaran: yeah, like this, this is probably like better.
88 00:14:29.070 ⇒ 00:14:32.190 Uttam Kumaran: But this stuff is like, less relevant.
89 00:14:32.190 ⇒ 00:14:34.470 Uttam Kumaran: Okay, yeah, that makes sense.
90 00:14:34.470 ⇒ 00:14:38.779 Ryan DeForest: Like the testing Qa, and like marketing is more important than like
91 00:14:38.950 ⇒ 00:14:41.699 Ryan DeForest: the multiple languages and stuff like that. For sure.
92 00:14:41.920 ⇒ 00:14:50.449 Mustafa Raja: Okay, I’ll adjust I’ll adjust the agent to look for only these these type of stuff. And then
93 00:14:50.450 ⇒ 00:14:52.669 Mustafa Raja: for sorry. The programming stuff.
94 00:14:53.240 ⇒ 00:14:55.350 Uttam Kumaran: For score like.
95 00:14:55.660 ⇒ 00:15:00.449 Uttam Kumaran: should we? Can we do? Should we just like do like one out of 5, Ryan? Is that like.
96 00:15:00.940 ⇒ 00:15:02.909 Ryan DeForest: Yeah. One out of 10. Something like that would be good.
97 00:15:03.280 ⇒ 00:15:14.300 Uttam Kumaran: Okay, yeah, let’s let’s do them all as 10. And then, Mustafa, one thing that could be helpful for our docs is, let’s try to see whether we can create criteria on like what is a 1.
98 00:15:14.450 ⇒ 00:15:16.370 Mustafa Raja: What is a 5. What is a 10?
99 00:15:16.830 ⇒ 00:15:25.459 Uttam Kumaran: And like, we can take the 1st pass and and send it to Ryan just to approve. But that way there’s some meaning. Otherwise. Yeah, I think it’s just gonna.
100 00:15:25.460 ⇒ 00:15:25.860 Mustafa Raja: Yeah.
101 00:15:25.860 ⇒ 00:15:32.900 Uttam Kumaran: It’s like 78 is random. So I mean, it is overlap and it is high. But that’s probably all it decided. So
102 00:15:33.550 ⇒ 00:15:34.270 Uttam Kumaran: cool.
103 00:15:34.920 ⇒ 00:15:37.568 Uttam Kumaran: Okay, great. Let’s move on to the next.
104 00:15:38.480 ⇒ 00:15:43.199 Uttam Kumaran: So there’s category overlap high tool count is true. Okay, that’s fine.
105 00:15:43.200 ⇒ 00:15:43.850 Ryan DeForest: As.
106 00:15:43.850 ⇒ 00:15:44.180 Uttam Kumaran: We kind.
107 00:15:44.180 ⇒ 00:15:44.720 Ryan DeForest: And so the.
108 00:15:44.720 ⇒ 00:15:45.709 Uttam Kumaran: Happened. The last one.
109 00:15:46.050 ⇒ 00:15:51.259 Ryan DeForest: Yeah, so the high. So the tool count right here is, they’re saying, like the different languages it found, and stuff like that as well.
110 00:15:51.260 ⇒ 00:15:59.929 Mustafa Raja: No, no, so for for the high tool count, it’s only for the marketing and sales tax.
111 00:16:02.285 ⇒ 00:16:02.710 Mustafa Raja: Yeah.
112 00:16:02.710 ⇒ 00:16:03.070 Ryan DeForest: Yeah.
113 00:16:03.070 ⇒ 00:16:11.170 Mustafa Raja: We? I think I did ask it to give me the array with it. Yeah, it’s this.
114 00:16:13.390 ⇒ 00:16:14.050 Ryan DeForest: Betcha.
115 00:16:15.880 ⇒ 00:16:21.340 Uttam Kumaran: Okay, yeah, most of these like these are all, yeah, valid.
116 00:16:22.770 ⇒ 00:16:23.550 Mustafa Raja: Oh, yeah.
117 00:16:26.430 ⇒ 00:16:27.200 Mustafa Raja: Yep.
118 00:16:27.530 ⇒ 00:16:32.060 Uttam Kumaran: And I guess, Ryan, would it be helpful to actually have this list in salesforce.
119 00:16:33.030 ⇒ 00:16:35.052 Ryan DeForest: That’s what I was thinking, too.
120 00:16:35.910 ⇒ 00:16:36.310 Uttam Kumaran: Because I’m trying.
121 00:16:36.310 ⇒ 00:16:36.650 Ryan DeForest: Like as.
122 00:16:36.650 ⇒ 00:16:38.349 Uttam Kumaran: Even as we’re going through it.
123 00:16:38.760 ⇒ 00:16:44.880 Uttam Kumaran: it might be helpful for whoever is going to call them to have this referenceable.
124 00:16:45.460 ⇒ 00:16:48.790 Ryan DeForest: Yeah, it. Just text you. Oh, go ahead.
125 00:16:49.500 ⇒ 00:17:06.983 Lev Katreczko: Yeah, I just wanted to jump in, by the way, sorry off cam just eating here. But I would say that I’ve I’ve used this same integration. And you can select like specific tools that you know you want to to reproduce. And xboxes, or, you know, just filter. Accordingly.
126 00:17:07.540 ⇒ 00:17:12.909 Lev Katreczko: I would say that there are definitely situations of companies that have really massive tech stacks
127 00:17:13.240 ⇒ 00:17:40.540 Lev Katreczko: dealt with, or whatever, but like they have 0 tools that are competing with default in the stock. And then there are also situations of a smaller company that has 10 tools in the stack total, but, like 3 of them are tools that we directly replace. So what I’m getting at, and I think it’s homework on our side is, it would probably be highest leverage to distill, like the 5 or 10 most key tools that indicate like a buying opportunity.
128 00:17:41.210 ⇒ 00:17:44.549 Lev Katreczko: and then use those as like the sole list that will
129 00:17:44.790 ⇒ 00:17:50.559 Lev Katreczko: that will inform whether or not we actually consider the stack to be large, because
130 00:17:50.710 ⇒ 00:17:56.169 Lev Katreczko: this is an interesting example. There’s a lot of stuff on here, things like Linkedin ads.
131 00:17:56.550 ⇒ 00:18:07.059 Lev Katreczko: Google ads, sales navigator showing up like that’s adding some bloat. But like 0% overlap with like, what default caters to. So just like some food for thought, there.
132 00:18:09.280 ⇒ 00:18:15.590 Uttam Kumaran: Yeah, this that’s actually would be really helpful in our signals. Doc. We have kind of both what you described. We have
133 00:18:15.840 ⇒ 00:18:20.480 Uttam Kumaran: direct competitors as a signal and just high tools in general. But
134 00:18:20.650 ⇒ 00:18:24.840 Uttam Kumaran: you’re right. I think high tools in general could be like a false flag
135 00:18:25.030 ⇒ 00:18:42.890 Uttam Kumaran: kind of the way to defend against that is, you sort of have both, but, like, you know, to put my math hat on. If competitors is always going to be a subset of that. You might as we just can use the competitors flag like if we’re only going to use them together, and one is always going to be
136 00:18:44.500 ⇒ 00:18:48.899 Uttam Kumaran: like true when the other is true, then it might as well only use that. But if you go into that.
137 00:18:48.900 ⇒ 00:18:52.949 Uttam Kumaran: yeah, you can literally just just put a comment there on on which ones, and we can.
138 00:18:54.680 ⇒ 00:19:01.430 Lev Katreczko: Yeah, yeah, I can help there. I would imagine that the in general, the 2 are correlated. Where.
139 00:19:01.720 ⇒ 00:19:05.630 Lev Katreczko: if default oh, awesome.
140 00:19:07.090 ⇒ 00:19:08.263 Lev Katreczko: Anyway, I
141 00:19:08.980 ⇒ 00:19:15.349 Lev Katreczko: yeah, Ryan, I’m just thinking like, especially if we’re piping this stuff into salesforce. Maybe it’s better to be picky about
142 00:19:15.600 ⇒ 00:19:22.150 Lev Katreczko: little names that show up. Yeah. So you don’t have to have like, you know, Zendesk, showing up as a tech stack.
143 00:19:24.160 ⇒ 00:19:26.669 Ryan DeForest: Yeah, agreed, although I don’t know. Is that relevant?
144 00:19:27.700 ⇒ 00:19:29.470 Ryan DeForest: I mean, it could be both. I mean
145 00:19:29.620 ⇒ 00:19:34.539 Ryan DeForest: to be fair, like the fact that they have a lot. A shit ton of tools like this
146 00:19:34.780 ⇒ 00:19:38.830 Ryan DeForest: could be just showing that they are open to like more.
147 00:19:38.830 ⇒ 00:19:42.859 Lev Katreczko: Yeah, yeah. So so we could do both. You know what I mean?
148 00:19:43.360 ⇒ 00:19:44.730 Lev Katreczko: Not like, I would future safe.
149 00:19:44.730 ⇒ 00:19:47.529 Uttam Kumaran: To have both. You know, it’s it’s a
150 00:19:48.390 ⇒ 00:19:57.360 Uttam Kumaran: it’s just like, I think one thing I want to do over time is like we may, we have, like probably 50 to 100 signals like, we want to get that down over time. So it’s
151 00:19:57.490 ⇒ 00:20:04.299 Uttam Kumaran: we could even try it for a bit. And then, if you’re like, we’ve never used this or it didn’t come up. We can remove it, you know.
152 00:20:04.470 ⇒ 00:20:09.840 Uttam Kumaran: It’s just cost and decision fatigue like the actual cost to get it is a lot was pretty low.
153 00:20:10.630 ⇒ 00:20:12.160 Lev Katreczko: Right same page.
154 00:20:15.630 ⇒ 00:20:16.300 Uttam Kumaran: Okay.
155 00:20:19.760 ⇒ 00:20:20.340 Mustafa Raja: Yeah, let me know.
156 00:20:20.340 ⇒ 00:20:26.139 Uttam Kumaran: So tool count. And then, yeah, let’s go to the next one. So the orchestration platform one.
157 00:20:26.540 ⇒ 00:20:30.400 Uttam Kumaran: can we see the okay? It didn’t find anything.
158 00:20:30.710 ⇒ 00:20:31.340 Mustafa Raja: Yep.
159 00:20:32.610 ⇒ 00:20:47.640 Uttam Kumaran: And then, what is okay, that’s fine. And then Ops role. So yeah, so let’s maybe let’s now that we’re gonna go into the job stuff. Let’s take a look at their site, and maybe we can walk through it together if you can open it up, and then also just go through their
160 00:20:48.130 ⇒ 00:20:52.429 Uttam Kumaran: their form. We can kind of see like what it is, and then compare it to what the
161 00:20:52.620 ⇒ 00:20:54.060 Uttam Kumaran: result in boundary.
162 00:20:54.510 ⇒ 00:20:58.379 Uttam Kumaran: So I don’t know. I think probably book a live demo is gonna be that form
163 00:20:59.540 ⇒ 00:21:04.600 Uttam Kumaran: we can come. We can look at what Clay used.
164 00:21:05.470 ⇒ 00:21:07.909 Mustafa Raja: Okay, do you want to see that side by side.
165 00:21:08.630 ⇒ 00:21:09.970 Uttam Kumaran: Oh, yeah, that’d be great.
166 00:21:11.110 ⇒ 00:21:12.580 Mustafa Raja: Let me filter it.
167 00:21:25.240 ⇒ 00:21:26.150 Uttam Kumaran: Nice.
168 00:21:27.710 ⇒ 00:21:28.470 Uttam Kumaran: Okay.
169 00:21:35.570 ⇒ 00:21:39.610 Uttam Kumaran: okay, it click book. A live demo. So yeah, let’s go through book a live demo ourselves.
170 00:21:42.080 ⇒ 00:21:44.599 Mustafa Raja: Yeah, so this field is required.
171 00:21:44.600 ⇒ 00:21:48.840 Uttam Kumaran: I guess I’m curious from Lev and Ryan. Tell me, like, when you guys see this.
172 00:21:48.960 ⇒ 00:21:50.970 Uttam Kumaran: what’s in what comes to your mind.
173 00:21:53.420 ⇒ 00:22:12.069 Ryan DeForest: So right away, like, 1st thing that we would do is like inspect it in general, and then it pops up in the form, inspect date. And the only reason why this company is top of mind is because, like, we’re in a active deal cycle with them right now. And so like. I know, I know instantly that this is a marketo form.
174 00:22:13.100 ⇒ 00:22:14.290 Uttam Kumaran: Oh, okay.
175 00:22:14.290 ⇒ 00:22:23.280 Ryan DeForest: So I so I know instantly when I inspect this. And I look at the the code, I actually know that this is a marketo form, which means that there’s no, there’s no like
176 00:22:24.038 ⇒ 00:22:38.519 Ryan DeForest: intense routing happening in the background. Nothing like that. I bet you once you once you actually fill in your 1st name, last. Name all that stuff it’s gonna say, like, we’ll reach out to you appropriately, because they’re doing all the filtering and all the routing and qualification after you submit the form.
177 00:22:40.570 ⇒ 00:22:44.370 Uttam Kumaran: So, Ryan? I mean, Mustafa, can you fill in the form with your stuff
178 00:22:44.950 ⇒ 00:22:47.475 Uttam Kumaran: and just see what happens?
179 00:22:50.220 ⇒ 00:22:54.907 Uttam Kumaran: You don’t have to actually take a sales call, you can just cancel it later.
180 00:23:05.190 ⇒ 00:23:08.079 Lev Katreczko: Hey, Ryan, were you looped in on the calls with these guys.
181 00:23:08.440 ⇒ 00:23:10.739 Ryan DeForest: Yeah, I know, Matt. I’m pretty close with Matt.
182 00:23:11.380 ⇒ 00:23:13.749 Lev Katreczko: So you know their process through and through.
183 00:23:14.220 ⇒ 00:23:14.870 Ryan DeForest: Yeah.
184 00:23:15.310 ⇒ 00:23:26.439 Lev Katreczko: I was. I was just gonna ask if you had a look at the tools that were pulled up in the clay table, and if it was covering everything as far as like what you know about what they’re using, what would be relevant.
185 00:23:27.470 ⇒ 00:23:33.690 Ryan DeForest: Yeah, I don’t know specifically, but I do know that they have a shitload of tools that are like all over the place. So I’m not shocked that
186 00:23:34.240 ⇒ 00:23:36.410 Ryan DeForest: that’s coming up as like a high score for that.
187 00:23:37.520 ⇒ 00:23:38.609 Mustafa Raja: Yeah, let me know if I.
188 00:23:38.790 ⇒ 00:23:40.269 Uttam Kumaran: Mustafa go ahead. Yeah.
189 00:23:43.560 ⇒ 00:23:45.629 Mustafa Raja: Let me use my brain for zoom!
190 00:23:45.630 ⇒ 00:23:46.670 Uttam Kumaran: Pray for us. Yeah.
191 00:24:05.330 ⇒ 00:24:13.879 Ryan DeForest: And like, then, what is this? This is? Count. This is no Chili piper. Yeah.
192 00:24:14.020 ⇒ 00:24:19.690 Ryan DeForest: yeah. So that form, yeah. So they’re using right now, so that form on the front end was Marketo, and then once you
193 00:24:20.250 ⇒ 00:24:22.079 Ryan DeForest: it pop! It pops up Chili Piper.
194 00:24:22.740 ⇒ 00:24:27.710 Uttam Kumaran: Can you? Can you inspect Mustafa? And and see
195 00:24:28.030 ⇒ 00:24:31.060 Uttam Kumaran: where you can find either the Js. Snippet, or whatever for this.
196 00:24:31.060 ⇒ 00:24:33.560 Ryan DeForest: Yeah, see? So it says, Chili, pipe right there, right above.
197 00:24:33.740 ⇒ 00:24:34.590 Uttam Kumaran: Oh, go back!
198 00:24:35.800 ⇒ 00:24:36.290 Ryan DeForest: Yep.
199 00:24:36.580 ⇒ 00:24:40.590 Ryan DeForest: So scroll go up like 2 rows, 3 rows, 2 divs, basically.
200 00:24:40.590 ⇒ 00:24:44.600 Uttam Kumaran: Oh, yeah, yeah, right above where your cursor was. Yeah, right there, Chili Piper.
201 00:24:44.820 ⇒ 00:24:50.690 Uttam Kumaran: Frank, yeah, quite slowly. Scroll your cursor up. It’s it’s at the top. Yeah, it’s right there. Yeah.
202 00:24:51.240 ⇒ 00:24:53.430 Lev Katreczko: I’m curious. Did it come through in the clay table.
203 00:24:53.860 ⇒ 00:24:56.460 Ryan DeForest: So so that did not come through in the clay table. Yeah.
204 00:24:56.900 ⇒ 00:25:04.539 Uttam Kumaran: Yeah. So one thing with Staff is we should. It’s not, I don’t think is gonna be able to infer it from
205 00:25:04.940 ⇒ 00:25:15.190 Uttam Kumaran: the visual front end. You should probably we should probably export the entire HTML. After rendering.
206 00:25:15.570 ⇒ 00:25:16.180 Mustafa Raja: And.
207 00:25:17.930 ⇒ 00:25:21.329 Ryan DeForest: I mean, if you could even have the agent like sign up for a demo and see what happens after that.
208 00:25:21.330 ⇒ 00:25:22.890 Uttam Kumaran: Immediately to be able to spot it.
209 00:25:24.340 ⇒ 00:25:32.860 Ryan DeForest: Like. If if an agent can actually like sign up for a demo, too, they could find this like the fact that, like, we wouldn’t know that they have a marketo form on the front end, and then you sign up.
210 00:25:32.860 ⇒ 00:25:35.050 Uttam Kumaran: No, that’s exactly. That’s exactly it. Yeah.
211 00:25:35.050 ⇒ 00:25:45.090 Ryan DeForest: Yeah, and that it’s a market form, and once you fill it out it pops up Chili Piper. Then that’s like a big like red flag. That means that there’s there’s 2 disconnected tools right there that don’t. That don’t even work nicely together.
212 00:25:45.610 ⇒ 00:25:47.050 Mustafa Raja: Okay. Noted.
213 00:25:47.890 ⇒ 00:25:50.084 Lev Katreczko: Yeah, and another quick call out,
214 00:25:50.580 ⇒ 00:25:53.099 Lev Katreczko: I mentioned this like on our 1st call. But
215 00:25:53.170 ⇒ 00:26:14.630 Lev Katreczko: there, this is a situation where the Chili Piper code is searchable and HTML, like the second you hit the landing page. So this is ideally like a layout. This is what you want to see. There are situations where they have a Chili piper scheduler on the website, but it’s not visible until we go through this flow. It actually pops up like hidden in some other page.
216 00:26:14.959 ⇒ 00:26:26.010 Lev Katreczko: I think that’s the biggest challenge. But we should definitely be able to knock this one out pretty easy, I think. Usually when I’m running like built with or like their stack searches, these types of examples do yield like positives.
217 00:26:27.730 ⇒ 00:26:45.819 Uttam Kumaran: Okay, okay, cool. Yeah. I’m glad we’re going through like a live example. So Mustafa, probably 2 things for us to talk about is like immediately on page land, we should get the tools, and then second at each step of the form fill. We should see how we can get a console or or an export of HTML, and then.
218 00:26:46.290 ⇒ 00:26:51.479 Uttam Kumaran: like, basically try to see what we can spot. But this is great. Okay, okay, perfect.
219 00:26:53.850 ⇒ 00:26:58.239 Uttam Kumaran: So then let’s go back, and then let’s also. Can you go to the careers, page or.
220 00:26:58.240 ⇒ 00:26:58.660 Mustafa Raja: Oh!
221 00:26:58.660 ⇒ 00:27:04.340 Uttam Kumaran: The Careers Page or the Linkedin, whatever the Linkedin jobs pages for them. Whatever the clay is gonna be using.
222 00:27:04.820 ⇒ 00:27:07.880 Uttam Kumaran: I guess it doesn’t matter anything we can just oh, shit.
223 00:27:08.720 ⇒ 00:27:11.171 Mustafa Raja: So to get the jobs
224 00:27:11.580 ⇒ 00:27:13.549 Uttam Kumaran: Going through their careers. Here, let’s see.
225 00:27:26.170 ⇒ 00:27:34.819 Mustafa Raja: Hmm, we have these jobs open. And for the jobs over here, we can look into this.
226 00:27:40.050 ⇒ 00:27:47.039 Mustafa Raja: And these are all these jobs are the job postings for the past 30 days.
227 00:27:49.100 ⇒ 00:27:56.410 Uttam Kumaran: Okay. And then what was the the outcome of this category was just a Boolean or.
228 00:27:56.410 ⇒ 00:27:57.195 Mustafa Raja: Then,
229 00:27:59.314 ⇒ 00:28:09.180 Mustafa Raja: we used this data over here to find if they have Ops role opens and it could find these 2 roles
230 00:28:11.310 ⇒ 00:28:12.269 Mustafa Raja: these are in.
231 00:28:12.270 ⇒ 00:28:14.230 Uttam Kumaran: And do you see that on their careers page.
232 00:28:20.247 ⇒ 00:28:21.799 Mustafa Raja: Let’s translate it.
233 00:28:40.250 ⇒ 00:28:43.140 Mustafa Raja: Internship sales intelligence, intelligence.
234 00:28:45.040 ⇒ 00:28:49.099 Uttam Kumaran: I guess. Do you see this on their careers, page here, or do you see it on Linkedin.
235 00:28:52.512 ⇒ 00:28:55.790 Mustafa Raja: It’s not a marketing.
236 00:28:56.770 ⇒ 00:28:57.690 Mustafa Raja: Send
237 00:29:01.625 ⇒ 00:29:02.749 Mustafa Raja: let me go to the.
238 00:29:02.750 ⇒ 00:29:05.089 Uttam Kumaran: Yes, see if they have something different on their Linkedin.
239 00:29:05.090 ⇒ 00:29:05.989 Mustafa Raja: We didn’t do.
240 00:29:48.970 ⇒ 00:29:49.860 Uttam Kumaran: Okay?
241 00:29:50.470 ⇒ 00:29:56.269 Uttam Kumaran: So I feel like, probably we have to check. I think it doesn’t look like they have clear Ops roles, but they do have sales, roles.
242 00:29:56.270 ⇒ 00:29:59.180 Mustafa Raja: Boom, yeah.
243 00:29:59.710 ⇒ 00:30:01.620 Uttam Kumaran: So let’s debug, yeah.
244 00:30:01.620 ⇒ 00:30:06.500 Mustafa Raja: This actually is pulling jobs for past 30 days.
245 00:30:06.950 ⇒ 00:30:08.130 Mustafa Raja: Oh, okay.
246 00:30:11.470 ⇒ 00:30:17.359 Uttam Kumaran: So can we confirm, like, so open up the role type. Let’s just go through the description and just confirm that it was accurate. Then.
247 00:30:18.396 ⇒ 00:30:19.680 Mustafa Raja: Which way do you want.
248 00:30:19.680 ⇒ 00:30:22.760 Uttam Kumaran: For the for the Ops jobs that it did pull.
249 00:30:23.580 ⇒ 00:30:27.730 Ryan DeForest: I do. I do have to hop off, though I have a hard stop right now.
250 00:30:28.440 ⇒ 00:30:29.929 Mustafa Raja: Okay. Yeah. Both. Too.
251 00:30:30.762 ⇒ 00:30:43.799 Ryan DeForest: But either way, this is good. I mean, it’s a good 1st step. I think we’re on the same page. Kind of like using. This example gave us a good kind of next steps as well. So let me know you know where to find me, and we’ll we’ll get to keep the ball rolling.
252 00:30:44.010 ⇒ 00:30:45.210 Uttam Kumaran: Okay, okay, perfect.
253 00:30:45.740 ⇒ 00:30:46.220 Ryan DeForest: Thanks team.
254 00:30:46.870 ⇒ 00:30:47.330 Uttam Kumaran: Thank you.
255 00:30:47.330 ⇒ 00:30:48.040 Mustafa Raja: Thank you.
256 00:30:48.420 ⇒ 00:30:54.770 Mustafa Raja: Do you want to see if we have any success? Ops, job in the.
257 00:30:56.060 ⇒ 00:30:59.539 Uttam Kumaran: Yeah, I would just check to see if if there are Ops.
258 00:31:00.540 ⇒ 00:31:01.350 Mustafa Raja: Like.
259 00:31:01.600 ⇒ 00:31:06.630 Uttam Kumaran: Like, for example, like, what is the what is the job description like? Can you just confirm that it was.
260 00:31:06.630 ⇒ 00:31:15.524 Mustafa Raja: Oh, yeah, let’s just if you want the job description we can look into the raw data over here, find the job. And
261 00:31:18.120 ⇒ 00:31:19.839 Mustafa Raja: Okay, it didn’t give us the URL.
262 00:31:19.840 ⇒ 00:31:21.619 Uttam Kumaran: Yeah, like, that’s what I’m interested.
263 00:31:23.240 ⇒ 00:31:23.940 Mustafa Raja: Oh, yeah.
264 00:31:25.060 ⇒ 00:31:26.070 Mustafa Raja: Hmm.
265 00:31:26.880 ⇒ 00:31:28.699 Uttam Kumaran: Let’s see, this is core of.
266 00:31:31.470 ⇒ 00:31:32.629 Mustafa Raja: Do we have some.
267 00:31:33.500 ⇒ 00:31:35.790 Uttam Kumaran: But like is this for the same company.
268 00:31:36.880 ⇒ 00:31:38.159 Mustafa Raja: Contact zone.
269 00:31:38.570 ⇒ 00:31:40.289 Mustafa Raja: Yeah, see, this is, I think, a different company.
270 00:31:40.290 ⇒ 00:31:41.120 Mustafa Raja: It couldn’t be.
271 00:31:43.710 ⇒ 00:31:50.089 Mustafa Raja: Hmm, because, the context we are looking into would be, for.
272 00:31:50.970 ⇒ 00:31:53.109 Mustafa Raja: Oh, it’s United States right!
273 00:31:53.600 ⇒ 00:31:54.599 Mustafa Raja: I will do.
274 00:32:01.890 ⇒ 00:32:08.811 Uttam Kumaran: Yeah, we have to make them some more dynamic. But I think one ticket is that just how do we make this job search.
275 00:32:17.200 ⇒ 00:32:18.989 Uttam Kumaran: They’re the job.
276 00:32:22.960 ⇒ 00:32:24.140 Mustafa Raja: Sorry you’re cutting off.
277 00:32:25.760 ⇒ 00:32:30.099 Uttam Kumaran: And stuff we did.
278 00:32:30.370 ⇒ 00:32:31.690 Uttam Kumaran: It’s false.
279 00:32:36.820 ⇒ 00:32:42.019 Mustafa Raja: Hmm, yeah, we. I think we need a better source for the jobs, because
280 00:32:43.390 ⇒ 00:32:47.720 Mustafa Raja: for cortex it gave gave us job from another company.
281 00:32:57.930 ⇒ 00:33:01.219 Uttam Kumaran: Is there anything after this, or those? All the Sigmas.
282 00:33:02.953 ⇒ 00:33:08.599 Mustafa Raja: Yeah. So we have 2 combos that we worked on
283 00:33:09.895 ⇒ 00:33:18.079 Mustafa Raja: after Ops. We see this process improvement that that’s also based on the roles.
284 00:33:19.538 ⇒ 00:33:26.730 Mustafa Raja: and we see that the jobs aren’t accurate for the accurate company. So I feel this would be
285 00:33:27.775 ⇒ 00:33:29.470 Mustafa Raja: incorrect for now
286 00:33:33.560 ⇒ 00:33:34.999 Mustafa Raja: and for the other.
287 00:33:35.000 ⇒ 00:33:36.499 Uttam Kumaran: That’s all the signals I.
288 00:33:37.387 ⇒ 00:33:43.459 Mustafa Raja: For this combo for the 1st combo. Yes, and for the second combo we have, these agents.
289 00:33:47.870 ⇒ 00:33:49.870 Mustafa Raja: The phone go through.
290 00:33:50.323 ⇒ 00:33:51.230 Mustafa Raja: Conversion path.
291 00:33:52.858 ⇒ 00:33:56.890 Uttam Kumaran: Can we go through the form example as well.
292 00:33:58.034 ⇒ 00:34:08.619 Mustafa Raja: Yeah, let’s look into the response. So it took to so let’s see the reasoning. We can look into the reasoning. First, st let me know if you want to look into the reasoning, and then look into the steps.
293 00:34:11.969 ⇒ 00:34:13.259 Uttam Kumaran: Yeah, reasoning is, first.st
294 00:34:13.760 ⇒ 00:34:17.499 Mustafa Raja: Yeah. The recapture from has 6 fields.
295 00:34:18.254 ⇒ 00:34:20.470 Mustafa Raja: Low fee income school.
296 00:34:21.630 ⇒ 00:34:25.330 Mustafa Raja: There’s nothing. So using the optional
297 00:34:31.550 ⇒ 00:34:33.310 Mustafa Raja: she’s on.
298 00:34:36.590 ⇒ 00:34:44.110 Mustafa Raja: Yeah. It was able to grab a lot of it, but did not grab that once we book a live demo, it takes us to the
299 00:34:47.503 ⇒ 00:34:48.729 Mustafa Raja: Calendar thing.
300 00:34:50.699 ⇒ 00:34:51.269 Uttam Kumaran: Okay.
301 00:34:52.639 ⇒ 00:34:53.429 Uttam Kumaran: Okay.
302 00:34:53.880 ⇒ 00:34:54.440 Mustafa Raja: Yeah.
303 00:34:56.330 ⇒ 00:35:02.193 Uttam Kumaran: So I think a couple of things, maybe, as we wrap up today. So one, I think, Giselle, there’s a lot of
304 00:35:02.610 ⇒ 00:35:08.868 Uttam Kumaran: sort of the follow ups and tickets that we discussed. If we can get those created.
305 00:35:09.730 ⇒ 00:35:22.429 Uttam Kumaran: a. Again, if you if you chat with the Pm. Team, they’ll show you how you can. You know, review the transcript to get those created. That would be wonderful. And then, if you once you create them, if you can send a note into the channel
306 00:35:22.550 ⇒ 00:35:27.817 Uttam Kumaran: like, Hey, these are graded, would love a review. The stuff and I can both go review them.
307 00:35:28.410 ⇒ 00:35:32.019 Uttam Kumaran: and then we can start to get them scheduled, and an estimated.
308 00:35:34.130 ⇒ 00:35:38.500 Henry Zhao: And I’m gonna create some tickets, too, regarding what I meant sent in slack as well.
309 00:35:39.660 ⇒ 00:35:41.170 Henry Zhao: I’ll get those over today.
310 00:35:41.170 ⇒ 00:35:41.800 Uttam Kumaran: Okay.
311 00:35:48.100 ⇒ 00:35:51.266 Uttam Kumaran: yeah, on the on the product analytics piece. I mean for me, it’s
312 00:35:51.690 ⇒ 00:35:54.570 Uttam Kumaran: I just need to know, like what we can share.
313 00:35:54.710 ⇒ 00:35:59.100 Uttam Kumaran: And like when I mean, we haven’t been, we’re not. Gonna we haven’t been able to share anything today.
314 00:35:59.559 ⇒ 00:36:04.910 Uttam Kumaran: So if there’s something that I can send over tomorrow or Monday. Like, I’m yeah.
315 00:36:04.910 ⇒ 00:36:07.570 Uttam Kumaran: Just would like to know, like what that is and what the deliverable is.
316 00:36:07.570 ⇒ 00:36:14.790 Henry Zhao: Let me send something. Yeah, let me send something over to you in a few hours, just for you to take a look at and approve and then, if it’s good, we can share it tomorrow.
317 00:36:15.540 ⇒ 00:36:24.500 Uttam Kumaran: Yeah, we can. Yeah, we can send it. Send it all in the Channel. And then I would love to take a look, and then I can ask anyone else in the team to give a review as well. So it’s not blocked by me.
318 00:36:25.088 ⇒ 00:36:26.852 Henry Zhao: Okay. Sounds good.
319 00:36:32.030 ⇒ 00:36:33.839 Uttam Kumaran: Okay. Any other questions.
320 00:36:39.710 ⇒ 00:36:41.640 Giselle Agot: No, I think we’re all.
321 00:36:42.270 ⇒ 00:36:43.459 Uttam Kumaran: Okay. Okay, perfect.
322 00:36:43.570 ⇒ 00:36:45.000 Uttam Kumaran: Alright. Thank you. Everyone.
323 00:36:45.170 ⇒ 00:36:45.770 Giselle Agot: Thank you.
324 00:36:45.770 ⇒ 00:36:46.240 Mustafa Raja: Thank you.
325 00:36:46.240 ⇒ 00:36:46.950 Henry Zhao: You guys.
326 00:36:50.910 ⇒ 00:36:51.559 Mustafa Raja: Thank you.