Meeting Title: Omni Analytics x Brainforge Partnership Sync Date: 2026-02-10 Meeting participants: Luke Scorziell, Omni Analytics
WEBVTT
1 00:00:19.770 ⇒ 00:00:21.220 Omni Analytics: Hello?
2 00:00:21.220 ⇒ 00:00:22.739 Luke Scorziell: Hey, how are you?
3 00:00:22.740 ⇒ 00:00:24.810 Omni Analytics: Hi, I’m doing okay, how are you?
4 00:00:25.130 ⇒ 00:00:27.820 Luke Scorziell: Go ahead. Correct.
5 00:00:28.390 ⇒ 00:00:32.380 Luke Scorziell: Oh, good day. I had to get my passport and…
6 00:00:32.380 ⇒ 00:00:34.410 Omni Analytics: Real ID stuff. Oh.
7 00:00:34.410 ⇒ 00:00:38.980 Luke Scorziell: Earning that out, so it was, like, my… Today was the day.
8 00:00:38.980 ⇒ 00:00:50.960 Omni Analytics: Yeah… I got all of that… I got all of that, like, a month before COVID hit, because I was supposed to do, like, a ton of travel that year, and I paid for, like, Rush on the passport.
9 00:00:50.960 ⇒ 00:00:51.810 Luke Scorziell: Yeah.
10 00:00:51.810 ⇒ 00:00:58.399 Omni Analytics: And then, for several years, it went uneased. Dang, yeah, that’s tough. Yeah, I like…
11 00:00:58.730 ⇒ 00:01:03.560 Luke Scorziell: I’ve been getting shamed every time I go to the airport, and they give me this, like, slip that’s like.
12 00:01:04.310 ⇒ 00:01:05.509 Omni Analytics: Gotta do this, yeah.
13 00:01:05.510 ⇒ 00:01:11.979 Luke Scorziell: You need to do the… yeah, and then I’m like, at some point, I feel like they’re gonna be like, you just can’t fly. Yeah. I don’t really want to get,
14 00:01:12.250 ⇒ 00:01:15.300 Luke Scorziell: Be in line at security and get that message, so…
15 00:01:15.300 ⇒ 00:01:16.420 Omni Analytics: Yeah, that’s fair.
16 00:01:17.260 ⇒ 00:01:18.010 Omni Analytics: But…
17 00:01:18.200 ⇒ 00:01:21.499 Luke Scorziell: Yeah, thanks so much for making time to meet, and I…
18 00:01:21.780 ⇒ 00:01:25.930 Luke Scorziell: Busy, busy schedule. How did the conference go last week?
19 00:01:25.930 ⇒ 00:01:33.090 Omni Analytics: It was good! So it was our entire team, it was our company off-site, so it was, like, two, almost, we’re just… just shy of 200 people.
20 00:01:33.760 ⇒ 00:01:36.039 Luke Scorziell: Oh, wow. And you said you planned the whole…
21 00:01:36.290 ⇒ 00:01:44.800 Omni Analytics: All, like, all the, like, all content is my team, so that’s everything from the website and blogs to…
22 00:01:45.180 ⇒ 00:01:52.659 Omni Analytics: presentations and thought leadership decks to, like, internal content and, like, sales decks and trainings and all that stuff.
23 00:01:53.210 ⇒ 00:01:54.450 Omni Analytics: So, I’m…
24 00:01:54.780 ⇒ 00:02:12.840 Omni Analytics: very… I’m happy with how it went, I’m relieved to have it done, and now I’m worried about all the things that I was avoiding for that. So reality is hitting me a little bit this week. It was good. It was really good to get the team together, and just, like, wild to see how much we’ve grown. We were,
25 00:02:12.860 ⇒ 00:02:14.949 Omni Analytics: It was, like, 18 people when I joined.
26 00:02:15.540 ⇒ 00:02:17.970 Luke Scorziell: Oh, wow. Which was, like, 3? 3 of them.
27 00:02:19.050 ⇒ 00:02:21.079 Luke Scorziell: Yeah, like 3 years.
28 00:02:21.320 ⇒ 00:02:23.280 Luke Scorziell: Dang. And how,
29 00:02:23.560 ⇒ 00:02:28.570 Luke Scorziell: So I was curious, too, just to pick your brain on, like, your career of how you ended up where you are,
30 00:02:28.740 ⇒ 00:02:32.230 Luke Scorziell: Does it seem… you’ve been, obviously, in, like, the data and analytics space for…
31 00:02:32.390 ⇒ 00:02:35.919 Luke Scorziell: a while. This is my first foray, really, into it, so…
32 00:02:35.920 ⇒ 00:02:38.499 Omni Analytics: Oh, welcome, it’s wild.
33 00:02:38.750 ⇒ 00:02:56.660 Omni Analytics: I mean, I never… I never really planned on it, so actually 10 years ago today marks the start of my career in data. I started as a BDR, like, doing sales development at Looker. And the reason was, like, at the time we moved to Santa Cruz, my husband was getting his PhD,
34 00:02:56.660 ⇒ 00:03:01.499 Omni Analytics: And I was working in tech, and I was like, I didn’t want to commute, and so I was looking for a job in Santa Cruz.
35 00:03:01.560 ⇒ 00:03:11.709 Omni Analytics: And long story short, I ended up at Looker, which was just kind of starting to… to take off at the time, and I wanted to be in marketing, but
36 00:03:12.680 ⇒ 00:03:17.689 Omni Analytics: didn’t have any marketing jobs, and I had no marketing experience, so I just kind of worked my way up.
37 00:03:18.560 ⇒ 00:03:28.770 Omni Analytics: And just never, never left data. And then at Google, did not enjoy the big company thing. I really enjoyed working with Colin and Jamie, two of our co-founders here.
38 00:03:28.900 ⇒ 00:03:29.370 Luke Scorziell: Huh.
39 00:03:29.370 ⇒ 00:03:33.779 Omni Analytics: And so when they announced Omni, I just kind of reached out and was like.
40 00:03:34.330 ⇒ 00:03:38.010 Omni Analytics: When you want marketing, like… If you want me, I’m in.
41 00:03:38.130 ⇒ 00:03:43.099 Omni Analytics: And just kind of bugged them until they… until they let me in.
42 00:03:43.100 ⇒ 00:03:45.280 Luke Scorziell: Yeah, wow, that’s exciting, that’s cool.
43 00:03:45.280 ⇒ 00:03:47.890 Omni Analytics: Not intentional at all.
44 00:03:47.890 ⇒ 00:03:54.659 Luke Scorziell: Yeah, but I mean, now it’s been 10 years, so it’s… you’re, like, an expert, I guess, in…
45 00:03:54.660 ⇒ 00:03:55.620 Omni Analytics: Oh my god, no.
46 00:03:56.730 ⇒ 00:03:59.039 Omni Analytics: But I’ve survived this long, so that’s great.
47 00:03:59.430 ⇒ 00:04:07.229 Luke Scorziell: Yeah, I mean, I feel like a lot has changed, too, I’m sure, since when you, like, would have started… I mean, it’s just even in the last, like, 2 years, I feel like.
48 00:04:07.840 ⇒ 00:04:09.890 Luke Scorziell: It’s been, like… insane.
49 00:04:10.180 ⇒ 00:04:15.950 Omni Analytics: I mean, the last year especially, I think, is, like, the single biggest year that I’ve seen.
50 00:04:16.149 ⇒ 00:04:18.150 Omni Analytics: Ep change.
51 00:04:18.500 ⇒ 00:04:31.149 Omni Analytics: just because AI is changing… it sounds, like, really cheesy, but AI is changing, like, how we work, and it’s just changing the product so much. Like, our engineers are building new things that, like, weren’t even possible, like.
52 00:04:31.540 ⇒ 00:04:46.249 Omni Analytics: I do not know when people first started talking about MCP servers, but that was definitely not on our roadmap, because it wasn’t really a thing. And then this summer, one of our engineers was just kind of like, oh, here’s a new thing, I thought it was cool, so I built it.
53 00:04:48.190 ⇒ 00:04:48.800 Luke Scorziell: Huh.
54 00:04:48.800 ⇒ 00:04:50.830 Omni Analytics: And it’s just been wild.
55 00:04:51.410 ⇒ 00:04:55.960 Luke Scorziell: Versus before, where it would have been, you have to, like, really… Plan out, and…
56 00:04:56.250 ⇒ 00:04:57.220 Omni Analytics: It’s funny.
57 00:04:57.220 ⇒ 00:04:59.159 Luke Scorziell: Sources to build, or what was the…
58 00:04:59.770 ⇒ 00:05:00.520 Luke Scorziell: Is that, like, different?
59 00:05:00.770 ⇒ 00:05:10.200 Omni Analytics: I mean, I think just because, like, AI is changing so fast, and what’s possible with AI is changing so fast, and also what’s expected, like, people who…
60 00:05:10.470 ⇒ 00:05:19.439 Omni Analytics: are adopting, are really adopting it, and, like, MCP servers, all of a sudden, it was like, everyone had a chat for everything, and so…
61 00:05:19.570 ⇒ 00:05:27.090 Omni Analytics: It created a new need, which was, like, to streamline these chats and bring them all, you know, kind of into one user experience.
62 00:05:27.360 ⇒ 00:05:31.810 Omni Analytics: And that… Wasn’t.
63 00:05:32.240 ⇒ 00:05:38.269 Omni Analytics: you know, it wasn’t really a mainstream thing or something that you really needed to think about before.
64 00:05:38.710 ⇒ 00:05:46.550 Omni Analytics: and Omni, especially just kind of coming from a, like, a BI tool with a built-in semantic layer, like, we were very much kind of focused on…
65 00:05:47.020 ⇒ 00:05:55.429 Omni Analytics: precision and governance, and before, very much felt that, like, AI was not the best way to do that, because it is…
66 00:05:55.760 ⇒ 00:06:05.700 Omni Analytics: by nature, not precise. But then just kind of, like, the way that things have changed in the last year, and changes that we’ve made to our product to try to, like.
67 00:06:05.970 ⇒ 00:06:10.600 Omni Analytics: help keep AI on its guardrails a lot more, like, suddenly just opened up.
68 00:06:10.930 ⇒ 00:06:12.420 Omni Analytics: A ton of new things.
69 00:06:13.350 ⇒ 00:06:13.820 Luke Scorziell: Yeah.
70 00:06:15.050 ⇒ 00:06:18.319 Omni Analytics: So, it’s been a very wild year.
71 00:06:19.000 ⇒ 00:06:21.309 Luke Scorziell: Yeah, no, that’s… that’s funny, I’ve…
72 00:06:21.540 ⇒ 00:06:29.870 Luke Scorziell: there was an article in Fortune that I sent to Robert and Tom, and was like, can I get your reactions to this? Because it was basically talking about how so many enterprise
73 00:06:30.520 ⇒ 00:06:32.670 Luke Scorziell: Companies, like, now are just, like.
74 00:06:33.950 ⇒ 00:06:37.429 Luke Scorziell: what is the ROI on any of the AI stuff that we’ve done?
75 00:06:37.430 ⇒ 00:06:37.900 Omni Analytics: when you’re.
76 00:06:37.900 ⇒ 00:06:40.149 Luke Scorziell: at what they’ve implemented, it’s mostly, like.
77 00:06:40.660 ⇒ 00:06:45.019 Luke Scorziell: Giving people subscriptions to, like, some kind of co-pilot thing.
78 00:06:45.020 ⇒ 00:06:45.829 Omni Analytics: Oh, yeah.
79 00:06:45.830 ⇒ 00:06:58.920 Luke Scorziell: like, so generic, and so it’s like, yeah, they’re probably wasting time on stuff that’s not streamlined, and, like, we’re finding that AI works best when it’s, like, a specific workflow that you give it, and, like.
80 00:06:59.050 ⇒ 00:07:05.039 Luke Scorziell: say, you can only use this… this information, you need to do this, and these are the steps, so…
81 00:07:05.040 ⇒ 00:07:05.650 Omni Analytics: Yeah.
82 00:07:05.780 ⇒ 00:07:08.410 Luke Scorziell: Yeah, I don’t know, it’s really interesting. It’s, like, cool to be…
83 00:07:08.750 ⇒ 00:07:12.130 Luke Scorziell: I guess at the beginning of my career, as all of this stuff is…
84 00:07:12.240 ⇒ 00:07:14.189 Luke Scorziell: It’s cool and a little scary.
85 00:07:14.190 ⇒ 00:07:15.670 Omni Analytics: Yeah, I mean, I’ve…
86 00:07:16.520 ⇒ 00:07:23.790 Omni Analytics: I’ve been in it for 10 years, and I still find it a little scary. And there’s so much stuff that I don’t know, and I don’t spend all of my time…
87 00:07:24.120 ⇒ 00:07:26.360 Omni Analytics: Like, reading the latest art, like.
88 00:07:26.770 ⇒ 00:07:32.130 Omni Analytics: I feel like you need to kind of live in it to keep up with it, and I certainly don’t.
89 00:07:32.580 ⇒ 00:07:48.609 Omni Analytics: So there’s just, like, so much going on. But yeah, I agree. I think a lot of people, especially with AI, kind of… we’re in a weird moment where some people haven’t done anything with it, but also people have been talking about it for so long that it does feel very overhyped, and everyone’s kind of like, oh, well…
90 00:07:48.730 ⇒ 00:08:01.110 Omni Analytics: kind of what about it? And I think a lot of people have just, like, these really big, lofty, undefined goals that they’re like, AI is going to change the way we work, but then you kind of dig in, and you’re like, how? What are you using it for? Like…
91 00:08:01.860 ⇒ 00:08:04.590 Omni Analytics: what are the workflows? And it’s, you know…
92 00:08:05.870 ⇒ 00:08:09.729 Omni Analytics: Gotta have, like, clear structure and goals, and it can’t just be…
93 00:08:10.400 ⇒ 00:08:14.909 Omni Analytics: oh, we’ve got an AI initiative, and now our entire organization’s gonna be more effective.
94 00:08:15.570 ⇒ 00:08:21.009 Luke Scorziell: Yeah, it seems like it’s not really how things are shaping out at all. Yeah.
95 00:08:21.370 ⇒ 00:08:26.450 Luke Scorziell: So… But yeah, I guess, I mean, I kind of mentioned, too, like.
96 00:08:26.680 ⇒ 00:08:31.940 Luke Scorziell: Curious to learn from you, but then… and also, like, how, you know, Brainforged can be.
97 00:08:32.070 ⇒ 00:08:32.840 Omni Analytics: Yeah.
98 00:08:32.840 ⇒ 00:08:35.210 Luke Scorziell: a really good partner. Like, I think we’re kind of, like.
99 00:08:35.470 ⇒ 00:08:39.029 Luke Scorziell: We’re excited about partnerships, and you guys are super excited about partnerships.
100 00:08:39.039 ⇒ 00:08:39.609 Omni Analytics: Totally.
101 00:08:39.610 ⇒ 00:08:43.120 Luke Scorziell: One of the only companies in our partner network that’s, like.
102 00:08:43.350 ⇒ 00:08:46.980 Luke Scorziell: Taking it super seriously, and has been like, we’ll even put, like, paid…
103 00:08:46.980 ⇒ 00:08:47.550 Omni Analytics: Oh, yeah.
104 00:08:47.550 ⇒ 00:08:51.040 Luke Scorziell: Like, dollars behind it and stuff, so yeah, I guess just, like.
105 00:08:51.430 ⇒ 00:09:05.480 Luke Scorziell: I’m kind of curious just how we can be supportive to, like, Omni, because I think, like, I was on a call with a videographer earlier today, talking about having, like, doing demos, where Utam, like, walks through stuff, and…
106 00:09:06.010 ⇒ 00:09:13.890 Luke Scorziell: Like, I’d like to do, like, at some point, a customer testimonial video. Yeah. Like, and would love to, like, see if that’s something we could collaborate on.
107 00:09:14.330 ⇒ 00:09:17.980 Luke Scorziell: Yeah, I’m just like, like, I want to open up the conversations here.
108 00:09:17.980 ⇒ 00:09:18.500 Omni Analytics: Yeah.
109 00:09:18.500 ⇒ 00:09:23.899 Luke Scorziell: You know, how can BrainForge You know, be a really key partner for you guys.
110 00:09:23.900 ⇒ 00:09:40.289 Omni Analytics: Awesome. I mean, I think, definitely, I’m kind of thinking back to the program that Kira shared. I know, like, I think you guys were the first ones, actually, to… because we’ve, like, shared that with a few folks to write a post, so that was awesome to see, and just kind of, like, loving experimenting with that.
111 00:09:40.410 ⇒ 00:09:54.609 Omni Analytics: I know, like, some of the very specific things from that, I think, would still be super helpful, so, like, a listicle article or something like that, if that’s an opportunity, I know that would be, like, still very much of interest to the team.
112 00:09:54.610 ⇒ 00:10:01.660 Omni Analytics: And just helpful. A couple things, actually, let me pull up something. So you said that you’re thinking about videos.
113 00:10:02.120 ⇒ 00:10:04.679 Luke Scorziell: Yeah, I like love, love videos.
114 00:10:04.840 ⇒ 00:10:23.540 Omni Analytics: Okay, awesome. I’m gonna send you this on Slack so that it doesn’t go away, but this is a, so I… this is something that I’ve had. It’s, like, $300 for 3 seats. I mean, this is… this is… this solves a different need than the videographer, so I don’t wanna… Yeah. This is a different thing.
115 00:10:23.670 ⇒ 00:10:34.890 Omni Analytics: But this is something that, like, my team does a lot of our, like, social media demos, and we use this for demos on the website and demos in our blogs and stuff.
116 00:10:34.890 ⇒ 00:10:43.679 Omni Analytics: And I have just, like, bought a few different seats to it, so it’s, like, $300, and you can get, like, a pack of 3 seats or something, so…
117 00:10:43.680 ⇒ 00:10:50.510 Omni Analytics: I give those away, and then I just buy a new pack when I need them. But we use this for…
118 00:10:51.010 ⇒ 00:11:09.149 Omni Analytics: a lot of our demo videos, like, on blogs and the websites, and the cool thing about it is it allows you to zoom in, so if someone is doing a video and they’re like, oh, hey, like, let me show you this code, or like, I’m gonna click in on this button, it’s nice. Like, it takes a little bit of getting used to,
119 00:11:09.280 ⇒ 00:11:16.290 Omni Analytics: But you can, like, customize the zooming in and stuff. We also use some of this, like, in our technical documentation.
120 00:11:17.420 ⇒ 00:11:27.259 Omni Analytics: And then you can customize, like, the background and stuff, so it’s, like, your brand colors, or it’s, like, general, or, you know, you can kind of do little things like that. And this has been…
121 00:11:29.420 ⇒ 00:11:32.710 Omni Analytics: So cheap and so helpful.
122 00:11:32.970 ⇒ 00:11:35.510 Omni Analytics: So if you guys are thinking about…
123 00:11:36.130 ⇒ 00:11:50.909 Omni Analytics: content, even for your own stuff, like, not even just, like, stuff on Omni, or, like, videos or things you can send customers, or, like, engaging things, for, like, LinkedIn and social media, and then you can export things as either, like, GIFs or MP4s.
124 00:11:53.160 ⇒ 00:11:56.229 Omni Analytics: And, like, the… I think I bought…
125 00:11:56.930 ⇒ 00:12:00.940 Omni Analytics: I think my… I mean, I think we’ve, like, my team, I’ve been using this for…
126 00:12:01.190 ⇒ 00:12:02.780 Omni Analytics: Over 2 years here.
127 00:12:03.110 ⇒ 00:12:04.799 Luke Scorziell: Oh, cool, okay.
128 00:12:04.800 ⇒ 00:12:05.260 Omni Analytics: Thank you.
129 00:12:05.260 ⇒ 00:12:08.219 Luke Scorziell: Literally today, we had someone do a demo, and…
130 00:12:08.690 ⇒ 00:12:16.570 Luke Scorziell: they were like, I don’t think it’d be that exciting to follow the mouse around the screen, and I don’t know if this does, like, that kind of zooming, but that.
131 00:12:16.570 ⇒ 00:12:17.180 Omni Analytics: Yeah.
132 00:12:17.180 ⇒ 00:12:21.270 Luke Scorziell: I was like, it would be interesting to, like, zoom in and actually see what you’re looking at versus just.
133 00:12:21.500 ⇒ 00:12:29.740 Omni Analytics: Oh yeah, let me find… let me just see, I’ve got… let me just pull up, I’m sure… I mean, we use this on our blog all the time, but let me…
134 00:12:31.660 ⇒ 00:12:35.110 Luke Scorziell: cool, like, presentation software, too, because I saw some of the…
135 00:12:35.500 ⇒ 00:12:39.179 Luke Scorziell: Like, the thing that has all, like, the clapping, and everyone’s, like, in a stadium.
136 00:12:39.230 ⇒ 00:12:57.289 Omni Analytics: Oh, yeah, that’s, I can send you what that is. Here, I’ll screen share with you really quick, just so you can see. This is, like, far easier than what I’m describing. So, like, here’s just, like, a demo embedded on our blog, so here’s just, like, normal… but then when someone types, they, like, zoom in, and it’s like, how’s our pipeline looking?
137 00:12:57.320 ⇒ 00:13:00.810 Omni Analytics: And then you can zoom out and look at the whole thing.
138 00:13:01.760 ⇒ 00:13:08.820 Omni Analytics: And you… and it just, like, allows you to do all of that kind of stuff. You can, like, zoom in and be like, here’s the task list that AI is going through.
139 00:13:08.970 ⇒ 00:13:11.819 Omni Analytics: And we find that especially for…
140 00:13:12.270 ⇒ 00:13:20.629 Omni Analytics: demos, like, you know, if we’re kind of showing the whole product, but there’s a specific spot on the screen where we want folks to focus.
141 00:13:21.250 ⇒ 00:13:23.649 Omni Analytics: We use this for things, like, all the time.
142 00:13:24.400 ⇒ 00:13:30.689 Omni Analytics: Oh, cool. And just, like, a nice, helpful, like, zoom in. But yeah, you mean on the demos, that… actually, let me just send you that really quick.
143 00:13:37.270 ⇒ 00:13:40.159 Omni Analytics: Yeah, this is what we use internally.
144 00:13:42.420 ⇒ 00:13:49.219 Omni Analytics: I’ll send it to you. I’ll stop my screen share. It’s like our virtual office space. How big is your team?
145 00:13:49.910 ⇒ 00:13:52.600 Luke Scorziell: We’re, like, 20 to 30.
146 00:13:52.600 ⇒ 00:13:55.109 Omni Analytics: Okay, awesome. Yeah, I mean…
147 00:13:55.320 ⇒ 00:14:12.620 Omni Analytics: we’ve been using Roam since we were that size, and it’s like a virtual office space, and so when we turn on our computers, we’re there. You can, like, knock on someone’s office, you can go into a meeting room, and then we do our Friday demos.
148 00:14:13.240 ⇒ 00:14:20.300 Omni Analytics: on it, and so we don’t use, like, Zoom or anything like that internally, we just… it’s like, it’s very weird. It takes…
149 00:14:20.510 ⇒ 00:14:21.129 Omni Analytics: it’s like.
150 00:14:21.130 ⇒ 00:14:21.570 Luke Scorziell: None.
151 00:14:21.570 ⇒ 00:14:36.590 Omni Analytics: it takes a little bit to get used to, but I kinda like it, and it’s nice. You can, like, see people and go knock on someone’s office, and… yeah. I don’t know. We’ve been using it for, like, 3 years. It definitely takes a little while to get used to, but, like, we really like it.
152 00:14:36.590 ⇒ 00:14:38.399 Luke Scorziell: Yeah, I can float it. Bye.
153 00:14:38.400 ⇒ 00:14:38.810 Omni Analytics: Yeah.
154 00:14:39.390 ⇒ 00:14:43.649 Luke Scorziell: pretty asynchronous a lot of the time, and then just, like, hop on Zoom and…
155 00:14:43.650 ⇒ 00:14:44.250 Omni Analytics: Yeah.
156 00:14:44.250 ⇒ 00:14:47.670 Luke Scorziell: But we’re, like, yeah, I think we’re figuring out all of our internal…
157 00:14:48.120 ⇒ 00:14:48.830 Omni Analytics: Totally.
158 00:14:48.830 ⇒ 00:14:53.610 Luke Scorziell: tooling and stuff. I guess I’d be curious, too, like, when… When you…
159 00:14:54.280 ⇒ 00:14:58.780 Luke Scorziell: I’m assuming you’ve done other videos, too, over the course of your career, but, like, as you’re thinking about, like.
160 00:14:59.500 ⇒ 00:15:05.480 Luke Scorziell: There’s, like, demos that you just screen record, right? And that’s, like, obviously very low production value, like, not…
161 00:15:06.930 ⇒ 00:15:12.569 Luke Scorziell: Not a high lift, and then there’s, like, bringing in a producer, and, like, doing, like, a literal, like, okay, we’re, like.
162 00:15:12.800 ⇒ 00:15:19.379 Luke Scorziell: of someone walking through, and then there’s, like, maybe the high level of, like, we’re gonna do, like, a commercial-type video that shows you, like.
163 00:15:19.610 ⇒ 00:15:28.100 Luke Scorziell: a customer on-site, and we walk through and do interviews. Have you, like, do you have experience with the different, like, levels of…
164 00:15:28.100 ⇒ 00:15:46.000 Omni Analytics: Yeah, a little bit. I mean, so we did, I mean, at Omni, we, as you might have gathered, are very casual crew. So, I mean, like, Roam is our internal virtual software, and, like, we… actually, it’s Colin, our CEO, just, like, takes
165 00:15:46.000 ⇒ 00:15:48.359 Omni Analytics: We record that meeting every week.
166 00:15:48.550 ⇒ 00:15:52.430 Omni Analytics: Over the weekend, Colin cuts it up and puts it on YouTube.
167 00:15:52.430 ⇒ 00:15:53.330 Luke Scorziell: Oh, really?
168 00:15:53.330 ⇒ 00:15:55.470 Omni Analytics: Yeah, like, it’s… it’s his…
169 00:15:55.470 ⇒ 00:15:56.669 Luke Scorziell: startup desk.
170 00:15:56.670 ⇒ 00:15:59.849 Omni Analytics: is his project. Like, he…
171 00:16:00.040 ⇒ 00:16:14.359 Omni Analytics: he loves doing it. We should probably make someone else do it, but also call in, like, last week we were at our off-site, and I had the video, because I… like, we did it… we did demos in person, but I was the one who had, like, set up the recording, and…
172 00:16:14.530 ⇒ 00:16:19.329 Omni Analytics: like, Colin wanted the video the next day. Like, he loves going through and watching them again.
173 00:16:20.580 ⇒ 00:16:27.299 Omni Analytics: So… that is to say, like, we are very comfortable with low production value.
174 00:16:27.640 ⇒ 00:16:38.890 Omni Analytics: And, like, on our… on our blogs and stuff, we usually use, like, Screen Studio, or, like, Loom, or kind of just different things, and are like, hey, like, as a technical product, it’s kind of…
175 00:16:39.180 ⇒ 00:17:02.320 Omni Analytics: expected and super helpful to have videos, and people would rather have something like that than expecting something super fancy. That being said, like, in the past, like, when I was at Looker and Google, obviously, like, we would do really nice customer videos. It’s not something that we’ve done yet, but actually I have a meeting later this week to kind of talk about it, because we’re going to be doing some customer stuff, and we might do our first customer
176 00:17:03.280 ⇒ 00:17:06.640 Omni Analytics: Testimonial than interviews.
177 00:17:06.849 ⇒ 00:17:07.519 Luke Scorziell: Huh.
178 00:17:07.520 ⇒ 00:17:10.020 Omni Analytics: So I haven’t done them in a long time.
179 00:17:11.640 ⇒ 00:17:12.849 Omni Analytics: Like… Yeah.
180 00:17:13.130 ⇒ 00:17:19.529 Omni Analytics: But at Looker, we used to bring in, like, a video team, and they would go and get, like, B-roll, and we’d get…
181 00:17:19.980 ⇒ 00:17:29.540 Omni Analytics: you know, a wonderful, a wonderful shot of the customer talking and kind of do that. So we’re gonna start exploring that a little bit more at Omni.
182 00:17:31.390 ⇒ 00:17:34.630 Omni Analytics: I think it’s helpful… for, like.
183 00:17:34.940 ⇒ 00:17:41.329 Omni Analytics: advertising and stuff, I think, like, our growth team would probably use it, and we’d probably embed it into blogs,
184 00:17:43.420 ⇒ 00:17:59.799 Omni Analytics: yeah, I just haven’t… I haven’t done, like, a nice one in a while, and we’re just about to start doing it. But also, there was another software that I was looking into a couple years ago that… before I got Screen Studio, called, like, Vouch, and it’s a video software where you can send, like, a customer questions, and they can answer things, but…
185 00:18:00.220 ⇒ 00:18:03.269 Omni Analytics: And it kind of does a little basic editing for them.
186 00:18:03.560 ⇒ 00:18:16.980 Omni Analytics: I might potentially explore that again, but I don’t know. With customers, I’m fine being super scrappy on internal things, but then with customers, I like it to feel, like, very white glove, and so I’ve actually been a little hesitant, like, we’ve had…
187 00:18:17.340 ⇒ 00:18:25.340 Omni Analytics: other video services and stuff, like, reach out to us and say, like, oh, we’ll go to your customer’s office and send us the questions, and we’ll ask them, and I’m like.
188 00:18:25.800 ⇒ 00:18:30.630 Omni Analytics: I’m extremely protective of our customers, I, like, don’t really let other people talk to them.
189 00:18:30.630 ⇒ 00:18:32.050 Luke Scorziell: Yeah, yeah.
190 00:18:32.240 ⇒ 00:18:35.590 Omni Analytics: Wanted to be a transactional bad experience.
191 00:18:35.940 ⇒ 00:18:43.350 Luke Scorziell: Yeah, no, let me send you… this is just what’s been percolating in my head, this is a company that I, like… because I… I was…
192 00:18:44.310 ⇒ 00:18:47.050 Luke Scorziell: Running my own, like, marketing.
193 00:18:47.050 ⇒ 00:18:47.700 Omni Analytics: Yeah.
194 00:18:47.700 ⇒ 00:18:54.439 Luke Scorziell: before, joining Brain Forge and doing, like, projects mainly with small businesses, but this was a friend that
195 00:18:54.580 ⇒ 00:19:00.190 Luke Scorziell: I… we did a documentary together that ended up on,
196 00:19:01.490 ⇒ 00:19:03.660 Luke Scorziell: Oh my gosh, man. Oh, Tubi.
197 00:19:04.130 ⇒ 00:19:09.859 Luke Scorziell: And so, I got to come in and, like, help with the whole, like, marketing campaign. Yeah. But he did these two videos…
198 00:19:09.980 ⇒ 00:19:15.259 Luke Scorziell: One, the first one I think I put is… is, like, pretty high production value, I think.
199 00:19:15.670 ⇒ 00:19:20.460 Luke Scorziell: Like, they brought in different actors and, like, created a whole, like.
200 00:19:21.080 ⇒ 00:19:32.020 Luke Scorziell: kind of, like, you know, like, a lot of the people that watched the video who were part of the company cried, because they felt like it, like, really represented them very well. Yeah. And then the second one is more of, like, the documentary style, like.
201 00:19:32.470 ⇒ 00:19:34.169 Luke Scorziell: Who are we as a company?
202 00:19:34.550 ⇒ 00:19:37.660 Luke Scorziell: owners and people. But, yeah, that’s like…
203 00:19:37.880 ⇒ 00:19:43.810 Luke Scorziell: like, as I’ve… I’ve been thinking about our partnerships, and then just from, like, a content perspective, is, like.
204 00:19:44.140 ⇒ 00:19:49.719 Luke Scorziell: Wanting to give people, like, customers and partners a video that they can, like, have that feels like.
205 00:19:50.220 ⇒ 00:19:50.610 Omni Analytics: Yeah.
206 00:19:50.610 ⇒ 00:19:53.880 Luke Scorziell: Super proud of it, and they want to just be able to share it with.
207 00:19:54.680 ⇒ 00:19:55.200 Omni Analytics: Hmm.
208 00:19:56.120 ⇒ 00:19:58.270 Luke Scorziell: Yeah, with, like, their family and friends.
209 00:19:58.610 ⇒ 00:20:05.289 Luke Scorziell: like, oh, this really speaks to who we are, and I know, like, we have ABC Homes, which is, like, a commercial
210 00:20:05.550 ⇒ 00:20:09.810 Luke Scorziell: It’s like a home and commercial services client, and they’re like.
211 00:20:10.140 ⇒ 00:20:14.450 Luke Scorziell: An interesting one that I think, like, I think would feel very, like.
212 00:20:14.850 ⇒ 00:20:16.830 Luke Scorziell: You could draw a lot of emotion from just.
213 00:20:16.830 ⇒ 00:20:17.360 Omni Analytics: Yeah.
214 00:20:17.360 ⇒ 00:20:26.819 Luke Scorziell: that they have with the company. But yeah, so that’s, like, I think something I’m… it’s just more of, like, a budget, and then, like, does this make sense with where we’re at strategically?
215 00:20:26.820 ⇒ 00:20:27.770 Omni Analytics: Yeah, I’m…
216 00:20:27.770 ⇒ 00:20:28.920 Luke Scorziell: Like… Yeah.
217 00:20:29.000 ⇒ 00:20:33.330 Omni Analytics: I’m not familiar with that customer, I need to look into it. You said ABC Homes is a joint customer?
218 00:20:33.610 ⇒ 00:20:36.959 Omni Analytics: Oh, I don’t think they’re a joint customer. Okay, I was like, huh.
219 00:20:37.720 ⇒ 00:20:38.390 Omni Analytics: I was like, that was…
220 00:20:38.390 ⇒ 00:20:44.349 Luke Scorziell: So, I’m working with Upta. I don’t know if you have a list of giant customers, otherwise it’s something I need to get from…
221 00:20:44.630 ⇒ 00:20:58.390 Omni Analytics: I can check with… with John and team to see. I mean, I think, yeah, videos, I… like, obviously, like, people always love good content, and, like, customer stuff. I am really…
222 00:20:59.280 ⇒ 00:21:03.859 Omni Analytics: Yeah, I think, yeah, with videos, it’s just hard, and not something that I’ve really…
223 00:21:04.040 ⇒ 00:21:09.659 Omni Analytics: obviously, like, prioritized putting time into yet, and kind of like, okay, technical, we love.
224 00:21:09.660 ⇒ 00:21:10.050 Luke Scorziell: Yeah.
225 00:21:10.050 ⇒ 00:21:18.750 Omni Analytics: people, the details, and then now, as we’re starting to grow up, it’s like, okay, I can think more a little bit about brand moments, where at the beginning, it’s just kind of been, like.
226 00:21:19.540 ⇒ 00:21:25.449 Omni Analytics: Proof, proof, proof, proof, like, details, like… Kind of focusing on that.
227 00:21:25.780 ⇒ 00:21:28.989 Omni Analytics: And then, so, for customers, like, I love doing…
228 00:21:29.450 ⇒ 00:21:35.010 Omni Analytics: all of our, like, customer case studies and kind of deep dive interviews and stuff and pulling from that, but I think
229 00:21:36.390 ⇒ 00:21:44.059 Omni Analytics: like, I like having the full story that someone can learn from, but then I think it’s super valuable to have
230 00:21:44.410 ⇒ 00:21:51.490 Omni Analytics: Like, an accompanied video that’s, like, some of those wonderful quotes, and some of those highlights, and something, and something that someone’s, like.
231 00:21:51.700 ⇒ 00:21:54.759 Omni Analytics: More likely to engage with and remember, and then…
232 00:21:55.360 ⇒ 00:21:58.719 Omni Analytics: Maybe it earns you the right for them to read the full story.
233 00:21:59.150 ⇒ 00:22:05.110 Luke Scorziell: Yeah, yeah. Well, if you watch those videos and at all are interested in getting connected with that company, I’m happy.
234 00:22:05.110 ⇒ 00:22:05.500 Omni Analytics: Awesome.
235 00:22:05.500 ⇒ 00:22:06.070 Luke Scorziell: realm.
236 00:22:06.570 ⇒ 00:22:12.860 Luke Scorziell: To… yeah, because I, like, I don’t know, it was really cool, they… that company, BusRite, they’re like a…
237 00:22:13.380 ⇒ 00:22:22.590 Luke Scorziell: school bus transportation management software. Yeah. And, like, their one thing is that, like, the school admin and the parents can see the location of students at the same time.
238 00:22:22.900 ⇒ 00:22:24.570 Luke Scorziell: And, I guess, like.
239 00:22:25.020 ⇒ 00:22:29.799 Luke Scorziell: Yeah, so the software itself, like, doesn’t sound like the most exciting thing to me.
240 00:22:29.800 ⇒ 00:22:30.430 Omni Analytics: I mean…
241 00:22:30.870 ⇒ 00:22:31.500 Luke Scorziell: But…
242 00:22:31.500 ⇒ 00:22:33.539 Omni Analytics: I’m a mom, so I’m immediately… yeah.
243 00:22:33.810 ⇒ 00:22:43.700 Luke Scorziell: But the… the story that they told, and was… yeah, it was pretty huge, and then helped them secure, like, more invest… investor money, stuff like that, so…
244 00:22:43.700 ⇒ 00:22:47.699 Omni Analytics: No, I know, I’m just like, ugh. I have a toddler, so…
245 00:22:49.420 ⇒ 00:22:49.860 Luke Scorziell: Absolutely.
246 00:22:49.860 ⇒ 00:22:51.990 Omni Analytics: worried about everything.
247 00:22:52.520 ⇒ 00:22:53.219 Luke Scorziell: How old?
248 00:22:53.220 ⇒ 00:22:55.059 Omni Analytics: He’s 18 months.
249 00:22:55.440 ⇒ 00:22:57.150 Luke Scorziell: Oh, okay, wow, so pretty new.
250 00:22:57.150 ⇒ 00:23:00.359 Omni Analytics: Yeah, and he, like, tries to kill himself all the time, so…
251 00:23:00.360 ⇒ 00:23:01.260 Luke Scorziell: Oh, really.
252 00:23:01.490 ⇒ 00:23:02.340 Omni Analytics: Yeah.
253 00:23:02.690 ⇒ 00:23:09.289 Omni Analytics: big into climbing things right now, and all these things he shouldn’t do, so… yeah, sorry, you were saying something?
254 00:23:09.290 ⇒ 00:23:14.350 Luke Scorziell: No, no, well, I think I was gonna say, there’s two families at my church that both have
255 00:23:14.680 ⇒ 00:23:17.630 Luke Scorziell: They both just had their kids’ second birthdays.
256 00:23:17.630 ⇒ 00:23:18.080 Omni Analytics: Yeah.
257 00:23:18.080 ⇒ 00:23:24.580 Luke Scorziell: And it’s just been fun to watch them grow up, a little bit. Like, this is the first time I’m seeing
258 00:23:25.140 ⇒ 00:23:27.799 Luke Scorziell: a human that didn’t… I mean, not the first time, but, like.
259 00:23:27.800 ⇒ 00:23:28.580 Omni Analytics: Yeah.
260 00:23:28.580 ⇒ 00:23:29.990 Luke Scorziell: Like, didn’t exist.
261 00:23:30.780 ⇒ 00:23:31.600 Luke Scorziell: And then…
262 00:23:31.800 ⇒ 00:23:40.389 Luke Scorziell: now has, like, come into existence and is, like, a functioning human that’s now, like, walking and talking and has a personality. It’s just… it’s, like, so…
263 00:23:41.500 ⇒ 00:23:49.440 Omni Analytics: Oh my gosh, no, it’s so wild. I’m constantly, like… How? Yeah, it’s amazing.
264 00:23:49.770 ⇒ 00:23:51.990 Omni Analytics: Lots of fun fears come with it, though, too.
265 00:23:52.350 ⇒ 00:23:53.949 Luke Scorziell: Yeah, I’m sure.
266 00:23:54.220 ⇒ 00:24:05.479 Omni Analytics: No, yeah, these videos are cool. I’ll take a look. I know some folks on our team are thinking a little bit about videos and stuff, so I’ll send them and just see if they’re, like, look, if this might fit what they’re looking into.
267 00:24:05.830 ⇒ 00:24:12.619 Luke Scorziell: Yeah, cool. And then I guess, like, with the… so some, like, logistical questions, too, I had, it was just…
268 00:24:13.570 ⇒ 00:24:18.130 Luke Scorziell: like, we’re down to post a lot about Omnia. Is there, like…
269 00:24:18.400 ⇒ 00:24:21.940 Luke Scorziell: a cap that you guys were thinking? I mean, obviously we’re not, like, every day.
270 00:24:21.940 ⇒ 00:24:22.480 Omni Analytics: Yeah.
271 00:24:22.480 ⇒ 00:24:29.329 Luke Scorziell: like, spend 500 bucks on, but is it, like, once a week that you’re thinking, or, like, once a month? I was just curious.
272 00:24:29.330 ⇒ 00:24:39.190 Omni Analytics: Let me… yeah, so I am content… I own product marketing, but Kira on the growth team is the one who actually, like, built the program and owns the budget.
273 00:24:39.190 ⇒ 00:24:43.210 Luke Scorziell: Okay. Let me just send her a message really quick and see if I can get anything for you live.
274 00:24:44.060 ⇒ 00:24:45.070 Luke Scorziell: Okay, cool.
275 00:24:50.340 ⇒ 00:24:57.740 Omni Analytics: Because that is a really good question that we should know.
276 00:25:00.960 ⇒ 00:25:05.520 Luke Scorziell: Yeah, and I mean, if there’s, like, stuff that we can do, joint, like…
277 00:25:06.460 ⇒ 00:25:10.379 Luke Scorziell: Too, then, like… You know, there might be better ways to spend budget than.
278 00:25:10.760 ⇒ 00:25:11.480 Omni Analytics: Yeah.
279 00:25:11.560 ⇒ 00:25:12.760 Luke Scorziell: $500.
280 00:25:12.760 ⇒ 00:25:29.110 Omni Analytics: Yeah, no. Of course, yeah, I just shouted to Kira, so she leads growth and is kind of thinking about, like, all the budget and campaigns and everything like that. And then I lead product marketing, so kind of thinking more about, like, the content, the messaging,
281 00:25:29.520 ⇒ 00:25:36.650 Omni Analytics: And, like, and what we’re writing, and then her team is, like, pushing it out and kind of sharing it all over. I mean, I think…
282 00:25:36.750 ⇒ 00:25:53.909 Omni Analytics: I’m trying to remember from our call, and I remember, like, Utam’s post was very, like, AI-forward, and kind of talking about, like, the semantic layer, and dbt and everything, and, like, I think that is something that is really key for us, and something that we’re trying to write about a lot, because, like.
283 00:25:54.620 ⇒ 00:26:03.469 Omni Analytics: We’ve had a semantic layer built into Omni since day one, and that’s always just been, like, core to our belief of what was important for analytics.
284 00:26:03.730 ⇒ 00:26:12.570 Omni Analytics: like, long… or not long, but, like, well before AI really started being, like, a key… a key part of the picture,
285 00:26:12.730 ⇒ 00:26:21.120 Omni Analytics: But we actually, like, very strongly believe that the semantic layer is what makes us, like, uniquely fit to do reliable AI.
286 00:26:21.740 ⇒ 00:26:25.409 Omni Analytics: And so, just kind of, like, talking about that.
287 00:26:25.660 ⇒ 00:26:46.469 Omni Analytics: often, and kind of, like, what sets ours apart, and also, I mean, I think especially for your team, like, the impact on joint customers, and what that means for people. I mean, like, we started the call at the beginning with you saying, everyone’s talking about AI, but people are like, what’s the value? Like, what is it actually doing for us? And so talking about that, and just kind of
288 00:26:47.430 ⇒ 00:26:55.259 Omni Analytics: the reality of that, because I think a lot of people, and probably myself included, and a lot of us included, it’s just, like, it’s been…
289 00:26:55.510 ⇒ 00:27:02.439 Omni Analytics: a lot of noise for a long time, so it’s like, okay, we’ve been talking about AI for a while, what’s it actually doing?
290 00:27:02.920 ⇒ 00:27:13.009 Omni Analytics: And so, like, good use cases or, like, joint customer stories showing, like, how it’s helping the data team, you know, either, like, you know, reducing… there’s just…
291 00:27:14.280 ⇒ 00:27:26.800 Omni Analytics: small, like, non-impactful work, and just, like, repeat asks and tickets, and actually, like, having them work on more strategic things, and how it’s helping business users, like, not just be…
292 00:27:27.420 ⇒ 00:27:35.650 Omni Analytics: waiting weeks for a ticket, or, like, a new dashboard, or, like, a new poll or something, and just kind of get some of those answers and everything on their own.
293 00:27:39.540 ⇒ 00:27:45.659 Omni Analytics: So… Yeah, I think… That is just kind of something that is really…
294 00:27:46.020 ⇒ 00:27:48.640 Omni Analytics: I think as a team, we just need…
295 00:27:48.850 ⇒ 00:27:54.389 Omni Analytics: We want to be getting out a lot on there, because, like, we’ve had this since day one.
296 00:27:55.040 ⇒ 00:27:55.410 Luke Scorziell: Yeah.
297 00:27:55.410 ⇒ 00:28:01.440 Omni Analytics: building for it, and it also, like, we think uniquely positions us to do like, better with AI.
298 00:28:05.440 ⇒ 00:28:12.610 Luke Scorziell: And when you’re measuring, like, the, I guess, return or, like, success on some of these, like, what is that?
299 00:28:12.940 ⇒ 00:28:16.989 Luke Scorziell: look like to you? Is it just, like, people are engaging, or you’re getting leads?
300 00:28:17.470 ⇒ 00:28:19.480 Luke Scorziell: The content itself, or…
301 00:28:19.900 ⇒ 00:28:27.609 Omni Analytics: So that would be more of a Kira question, because her team is, like, more running the programs, but I think, like, the thing that we kind of think about, and even just, like.
302 00:28:28.120 ⇒ 00:28:37.720 Omni Analytics: when we… when I first started, because I run all of our organic LinkedIn, and we just started paying on LinkedIn, so I can… I can speak more to, like, the organic and, like.
303 00:28:37.920 ⇒ 00:28:38.630 Omni Analytics: We just…
304 00:28:38.630 ⇒ 00:28:39.300 Luke Scorziell: It’s not that.
305 00:28:39.300 ⇒ 00:28:44.750 Omni Analytics: We just started putting… putting kind of money behind this, but it was, like, the way that we did it early on was just, like.
306 00:28:46.080 ⇒ 00:28:52.670 Omni Analytics: It, you know, it wasn’t even that scientific, because, like, obviously we’re an analytics software, but… everything…
307 00:28:53.000 ⇒ 00:29:08.499 Omni Analytics: you gotta, like, prioritize everything. And so, it wasn’t like, oh, we did our first LinkedIn post, and then it was like, oh, let’s go get, like, really advanced LinkedIn reporting and stuff, and, like, start tracking everything. Like, a lot of it was just kind of like, is it directionally helping?
308 00:29:08.680 ⇒ 00:29:21.950 Omni Analytics: And so, I put together, like, a content calendar and a social media calendar and everything for, like, when we’re posting a thing, and would look at, like, website traffic, and would look at our demo requests, and this was, like, 3 years ago before we even had…
309 00:29:21.950 ⇒ 00:29:29.569 Omni Analytics: like, on our demo form now, it’s like, how did you find out about us? And, like, LinkedIn, and, like, ChatGTP, and there’s all these different options that didn’t exist.
310 00:29:29.570 ⇒ 00:29:33.700 Omni Analytics: But even before then, we would notice like…
311 00:29:34.130 ⇒ 00:29:47.560 Omni Analytics: very clear lifts in, like, when we would talk about, like, certain topics and have, like, a founder or opinionated post on LinkedIn that was talking about something that, like, clearly
312 00:29:48.360 ⇒ 00:29:56.810 Omni Analytics: was an area where we have credibility, but also was an area where we have an opinion. Like, I think the opinion especially really matters.
313 00:29:57.250 ⇒ 00:30:00.879 Omni Analytics: Because a lot of people will just kind of, you know, post, like.
314 00:30:02.400 ⇒ 00:30:20.580 Omni Analytics: you know, surprise, it’s good for you to drink water every day, like, we all know that, you know, it’s like, yes, thank you. We… we found that it really helps to talk about things where, like, we’ve got credibility to talk about, so we’re not just, like, out there talking about, like, Bitcoin or whatever.
315 00:30:20.790 ⇒ 00:30:25.109 Omni Analytics: But also to have an opinion on it, and something that people…
316 00:30:25.370 ⇒ 00:30:29.640 Omni Analytics: Like, we’re not afraid for people to potentially argue with something.
317 00:30:29.920 ⇒ 00:30:36.210 Omni Analytics: Because I think if you don’t have an opinion on something, then it’s just kind of like, okay, yeah, we all know we should drink more water.
318 00:30:37.010 ⇒ 00:30:50.600 Omni Analytics: But we then would see lifts in, like, website traffic and demo forms and everything, and, like, we knew that it was… it was working, and so we’ve just kind of been, like, very lucky from some of that… those, like, early…
319 00:30:50.710 ⇒ 00:30:58.139 Omni Analytics: Noticeable winds to just… know to continue doing it more, and to continue investing in it, and now…
320 00:30:58.710 ⇒ 00:31:15.840 Omni Analytics: like, we’ve layered in, and now we post much more often, and we have, you know, our founders post more often, and now we’re, you know, also layering in paid as well as organic, and, like, starting to work with partners and stuff, but I think it’s also just kind of a… we know LinkedIn is where our core audience is.
321 00:31:16.080 ⇒ 00:31:16.859 Luke Scorziell: Huh.
322 00:31:17.080 ⇒ 00:31:24.479 Omni Analytics: Versus, you know, like, Meta. I think Kira’s team is gonna start growing… is gonna start testing some things on Meta,
323 00:31:25.150 ⇒ 00:31:39.060 Omni Analytics: I am in no rush to start managing an omni Facebook page. But it’s kind of like a… why not? But, like, LinkedIn definitely is where our people are.
324 00:31:39.410 ⇒ 00:31:45.400 Luke Scorziell: Yeah, it’d be interesting about, like, X, or Twitter, or whatever, too, because we’ve found that there’s a lot of people
325 00:31:47.310 ⇒ 00:31:54.470 Luke Scorziell: I know, like, you’re Thomoused on people through Twitter. Yeah. And, like, a… I know it’s… I don’t know, it’s a little on the…
326 00:31:54.690 ⇒ 00:31:57.450 Luke Scorziell: Seems like it’s on my town, but…
327 00:31:58.970 ⇒ 00:32:10.759 Omni Analytics: Yeah, that’s probably on me. I used to… we used to be pretty active on Twitter, and then it just kind of felt like it was falling apart, and everyone was leaving, and so I just kind of stopped posting on Twitter, but it also feels…
328 00:32:12.120 ⇒ 00:32:13.000 Luke Scorziell: Yeah.
329 00:32:13.000 ⇒ 00:32:14.709 Omni Analytics: are back again?
330 00:32:15.110 ⇒ 00:32:19.440 Omni Analytics: And I probably just need to start posting more on Twitter.
331 00:32:20.080 ⇒ 00:32:22.059 Luke Scorziell: Yeah, cause we’ll def- yeah.
332 00:32:22.350 ⇒ 00:32:26.600 Luke Scorziell: I don’t know, it’s an experiment slash bet that I’m thinking about.
333 00:32:26.800 ⇒ 00:32:27.330 Omni Analytics: Yeah.
334 00:32:27.330 ⇒ 00:32:30.340 Luke Scorziell: Can we just repurpose some of our LinkedIn?
335 00:32:30.440 ⇒ 00:32:31.360 Luke Scorziell: Content.
336 00:32:31.560 ⇒ 00:32:32.080 Omni Analytics: Yeah.
337 00:32:32.080 ⇒ 00:32:32.899 Luke Scorziell: put on there.
338 00:32:32.900 ⇒ 00:32:47.689 Omni Analytics: Yeah, I used to do it almost, like, kind of an exactly one-for-one, like, usually a shorter, like, version and slightly change, because just, like, Twitter, obviously, you’re gonna have different character counts and limitations and things. I used to do that, like.
339 00:32:47.910 ⇒ 00:32:49.410 Omni Analytics: And this is…
340 00:32:49.530 ⇒ 00:32:56.349 Omni Analytics: years ago, and never really saw a ton with it, but I do think, like, there are some…
341 00:32:57.110 ⇒ 00:32:57.830 Omni Analytics: like…
342 00:32:58.770 ⇒ 00:33:04.800 Omni Analytics: I feel like to do Twitter well, you probably need to treat it a little bit like a different platform, and like…
343 00:33:05.560 ⇒ 00:33:08.800 Omni Analytics: have a different personality on there, but also, I think…
344 00:33:09.800 ⇒ 00:33:17.360 Omni Analytics: something that is really important for social media strategy that, like, was not at all a thing when I was first doing it at Looker.
345 00:33:18.300 ⇒ 00:33:27.230 Omni Analytics: is using the executives and, like, thought leaders. Like, it used to… I feel like it used to be about the brand and, like, very corporate, and there’s just, like, things that a brand…
346 00:33:27.490 ⇒ 00:33:30.200 Omni Analytics: Shouldn’t do, or, like, don’t work from a brand.
347 00:33:30.950 ⇒ 00:33:35.589 Omni Analytics: Like, if I was to post kind of an opinionated
348 00:33:36.980 ⇒ 00:33:42.819 Omni Analytics: like, we call them micro-posts, like what Utam did. Like, if I was to post something like that from Omni, people…
349 00:33:43.070 ⇒ 00:33:52.730 Omni Analytics: I don’t think it would do very well, because it’s like, well, who… who is this? Obviously, like, it’s not… it’s a corporate account, it’s not as fun to engage with.
350 00:33:52.970 ⇒ 00:34:06.639 Omni Analytics: Whereas I think things like that from a founder or, like, leader person, where you want to comment, you want to talk back to the person and say, like, oh, I love this idea, or wow, I completely disagree with you, this is why,
351 00:34:08.159 ⇒ 00:34:10.559 Omni Analytics: I think that works really well, and, like, I think…
352 00:34:10.980 ⇒ 00:34:13.800 Omni Analytics: Twitter is probably also a really good spot for that.
353 00:34:13.940 ⇒ 00:34:21.170 Luke Scorziell: Yeah, we’re… also, I think we were scheduled for 45 minutes, but if you have to… I know it’s been 30 minutes, so if you have to hop on…
354 00:34:21.170 ⇒ 00:34:27.769 Omni Analytics: Awesome, yeah, I’ve got a ton of stuff, but I can kind of chat a little bit more. I know I was rambling, and then I’ll… I’ll need to…
355 00:34:27.770 ⇒ 00:34:30.149 Luke Scorziell: No, no, yeah, I just wanted to make sure of your time.
356 00:34:30.159 ⇒ 00:34:31.069 Omni Analytics: Wow.
357 00:34:32.060 ⇒ 00:34:33.039 Luke Scorziell: Yeah, let me know.
358 00:34:34.650 ⇒ 00:34:39.899 Omni Analytics: Awesome, and let me see, if I heard back from Kira… So she said on…
359 00:34:41.989 ⇒ 00:34:56.389 Omni Analytics: She said, like, I mean, I think we’re, like, still flexible and kind of figuring it out, but she said, you know, potentially up to, like, one a week, or, like, a budget of, you know, up to, like, $2,000 in a month. That would be, like, one a week is something that would be down to experiment with.
360 00:34:56.690 ⇒ 00:35:08.170 Luke Scorziell: Okay. Yeah, I mean, I think it sounds like… On…
361 00:35:11.290 ⇒ 00:35:16.720 Luke Scorziell: Yeah, so our current strategy, I mean, things are kind of shifting, like, week by week, so… Whatever.
362 00:35:16.720 ⇒ 00:35:18.679 Omni Analytics: Always. Feedback on is, like…
363 00:35:18.680 ⇒ 00:35:19.200 Luke Scorziell: Where?
364 00:35:19.200 ⇒ 00:35:19.650 Omni Analytics: Always.
365 00:35:19.650 ⇒ 00:35:21.460 Luke Scorziell: ago.
366 00:35:21.620 ⇒ 00:35:30.270 Luke Scorziell: But we’re… like, we ramped it up to, like, two posts from… or one post from Robert’s count, one post from Tom’s count a day.
367 00:35:31.140 ⇒ 00:35:32.060 Omni Analytics: Oh, that’s awesome.
368 00:35:32.060 ⇒ 00:35:35.890 Luke Scorziell: Timing for, like, 10 a week, and so within that, we’re doing…
369 00:35:36.610 ⇒ 00:35:43.140 Luke Scorziell: like, I’m kind of trying to test service-specific, like, service and ICP-specific posts, so, like.
370 00:35:43.480 ⇒ 00:35:49.869 Luke Scorziell: We launched a campaign with a different partner that we built, like, a solution,
371 00:35:50.730 ⇒ 00:35:54.590 Luke Scorziell: For insurance and legal companies to help with their, like, documentation.
372 00:35:54.870 ⇒ 00:36:02.929 Luke Scorziell: or, like, pulling forms and automating it with AI. And so that’s something we launched, then I launched, like, a DBT audit.
373 00:36:03.630 ⇒ 00:36:05.880 Luke Scorziell: series of content, so I’m kind of saying, like.
374 00:36:06.170 ⇒ 00:36:10.599 Luke Scorziell: What’s doing well, and then we have an attribution series going out on,
375 00:36:10.910 ⇒ 00:36:16.990 Luke Scorziell: Robert’s account, so my hunch there, I guess, is that the ones that get more engagement, I can kind of…
376 00:36:17.410 ⇒ 00:36:23.019 Luke Scorziell: Start to, like, hone… And see if we can, like, get more, but then another, like.
377 00:36:23.890 ⇒ 00:36:30.430 Luke Scorziell: vertical. I mean, it’s easy to throw in partners if we do it, right? I think there’s, like, if it’s just, like, a…
378 00:36:30.700 ⇒ 00:36:31.590 Omni Analytics: Rah rah.
379 00:36:31.590 ⇒ 00:36:36.350 Luke Scorziell: Yeah, Omni’s the best, like, it’s, like, probably, like, one or two of those, like… Yeah.
380 00:36:36.350 ⇒ 00:36:36.770 Omni Analytics: Oh, no.
381 00:36:36.770 ⇒ 00:36:38.860 Luke Scorziell: It’s fine, but
382 00:36:39.030 ⇒ 00:36:44.580 Luke Scorziell: the ones that I… my gut says will do really well are kind of what you said, like.
383 00:36:44.740 ⇒ 00:36:47.739 Luke Scorziell: Joint customer testimonials of, like.
384 00:36:48.090 ⇒ 00:36:57.590 Luke Scorziell: here’s a client we worked with, and they had this problem, this problem, this problem. We implemented Omni because of, like… and then we can speak to, like, your value proposition.
385 00:36:57.590 ⇒ 00:36:58.120 Omni Analytics: Yeah.
386 00:36:58.940 ⇒ 00:37:06.830 Luke Scorziell: So that’s kind of one category that I’m thinking about, and then the other category would be, like, more of, yeah, the demos,
387 00:37:07.330 ⇒ 00:37:13.559 Luke Scorziell: and just kind of, like, showing features. I don’t know if there’s… yeah, if you would add…
388 00:37:14.260 ⇒ 00:37:16.380 Omni Analytics: Yeah, I think, like, on…
389 00:37:17.270 ⇒ 00:37:34.850 Omni Analytics: on the demos, like, something that we’re kind of thinking about is starting to build out more of our, like, use case-specific content, and so we do kind of, like, a lot of, like, product tips and demos and stuff, but if there’s… and forgive me, I do not know enough about your clients, but if there’s, like, very specific
390 00:37:35.200 ⇒ 00:37:53.410 Omni Analytics: industries or, like, line of businesses that you focus on, like, those use case-specific demos are super helpful, so if you’re like, oh, you know, we, like, just because I, like, the bus ride video is still up on my other screen, if you’re like, oh, like, we’re really big in the transportation space, and, like, have unique expertise there,
391 00:37:54.040 ⇒ 00:37:59.949 Omni Analytics: Like, demos and kind of use cases on that that kind of just, like, flex and show, hey, you know, like, here’s…
392 00:38:00.110 ⇒ 00:38:06.910 Omni Analytics: You know, we help a lot of customers in this space, like, here’s kind of common metrics, like, common challenges and things that they’re trying to tackle, like.
393 00:38:07.160 ⇒ 00:38:20.770 Omni Analytics: let me show you, you know, kind of, like, something that we built out that, like, helps them do this. And then it’s, like, a way to layer in the features, and the semantic layer, and, like, AI, but that’s very focused on, like, solving someone’s problem.
394 00:38:21.760 ⇒ 00:38:32.480 Omni Analytics: I think that is, like, really helpful, and something, like, my team is starting to kind of, like, build out our first industry pages and work a little bit more on, like, line of business blogs, because it’s just not…
395 00:38:32.640 ⇒ 00:38:37.819 Omni Analytics: something we’ve gone to… we’ve been able to focus on yet, and it’s hard because Omni can be…
396 00:38:38.090 ⇒ 00:38:43.420 Omni Analytics: like, every company’s got… I mean, yeah, like, every company’s got data, and so we have customers
397 00:38:43.560 ⇒ 00:38:47.739 Omni Analytics: You know, that have… 10 employees, and we have customers that have
398 00:38:48.140 ⇒ 00:38:57.160 Omni Analytics: Thousands and thousands of employees across you know, 200 countries. And so…
399 00:38:58.370 ⇒ 00:39:11.850 Omni Analytics: it’s nice to be like, yes, if you’ve got data, we can help you, but also it’s, like, very hard for people, especially as we’re, like, moving upmarket into the enterprise, to get that vision of, well, can you help retailers who look like me? Have you helped someone who’s…
400 00:39:11.970 ⇒ 00:39:14.539 Luke Scorziell: Been dealing with this type of data, so…
401 00:39:14.540 ⇒ 00:39:18.879 Omni Analytics: Now we’re starting to build out some of those, like, specifics a little bit more.
402 00:39:19.450 ⇒ 00:39:24.920 Luke Scorziell: Yeah, and are there verticals that you’re, like, mostly focused on? I know you said tech, retail, maybe.
403 00:39:24.920 ⇒ 00:39:26.660 Omni Analytics: Yeah. Services. Yeah.
404 00:39:27.630 ⇒ 00:39:31.540 Omni Analytics: Like, tech, retail, financial services,
405 00:39:31.880 ⇒ 00:39:37.659 Omni Analytics: are probably, like, 3 of the big ones that we’re focusing on early on, and then also media.
406 00:39:38.660 ⇒ 00:39:41.059 Omni Analytics: I mean, we work across, like, a lot of other
407 00:39:41.610 ⇒ 00:39:45.860 Omni Analytics: Verticals as well, like, we’ve got healthcare customers, and, like, tech is so weird.
408 00:39:46.020 ⇒ 00:39:46.600 Luke Scorziell: Yeah.
409 00:39:46.600 ⇒ 00:39:48.649 Omni Analytics: Because there’s, like, everyone is in tech.
410 00:39:51.280 ⇒ 00:39:56.999 Omni Analytics: But those are… those are, like, the first ones that we’re starting to… to think about and focus on a little bit more.
411 00:39:57.330 ⇒ 00:40:02.540 Luke Scorziell: And what is media to you guys? Is that, like, agency? Or what, like…
412 00:40:02.540 ⇒ 00:40:11.040 Omni Analytics: I use it as a very broad term. So for example, like, Conde Nast and BuzzFeed are customers.
413 00:40:11.580 ⇒ 00:40:30.870 Omni Analytics: And so I’m making my team build a media page because I love, like, naming both of those customers, as often as possible. But also, like, I would say, like, we do work with agencies, also for now, just because we don’t have the bandwidth to build out a specific page, but I would say, like, gaming analytics is huge.
414 00:40:30.870 ⇒ 00:40:31.350 Luke Scorziell: So.
415 00:40:31.350 ⇒ 00:40:37.220 Omni Analytics: We’ll probably highlight gaming on that page as well, just, like, as a way to…
416 00:40:37.500 ⇒ 00:40:47.770 Omni Analytics: showcase it until, like, my team, frankly, just has the bandwidth to build, like, a specific gaming page. We have a couple gaming blogs,
417 00:40:48.240 ⇒ 00:40:52.420 Omni Analytics: But, like, gaming. So, but for now, just for the sake of…
418 00:40:53.660 ⇒ 00:41:02.379 Omni Analytics: starting to… to get some of that focused at things… stuff out. I’m probably gonna put gaming on the media page. So, like, entertainment, broadly. Okay.
419 00:41:02.380 ⇒ 00:41:06.130 Luke Scorziell: No, that’s ins… I actually have a call with, someone who’s kind of…
420 00:41:06.390 ⇒ 00:41:10.940 Luke Scorziell: That’s heard me a little bit, from… I don’t know if you’re familiar with Eisenberg?
421 00:41:10.940 ⇒ 00:41:12.640 Omni Analytics: But there are, like.
422 00:41:12.640 ⇒ 00:41:19.379 Luke Scorziell: Brand agency that they specifically focus on media, or on video games.
423 00:41:19.380 ⇒ 00:41:20.220 Omni Analytics: Oh, yeah.
424 00:41:20.220 ⇒ 00:41:22.830 Luke Scorziell: And so, she’s, like, the director of…
425 00:41:23.500 ⇒ 00:41:31.490 Luke Scorziell: insights and data, I think, so I don’t know, she might be… that could be interesting. Because I, like, yeah, I think we’re… probably overlap is in…
426 00:41:31.610 ⇒ 00:41:34.210 Luke Scorziell: And do you guys do CPG stuff?
427 00:41:34.210 ⇒ 00:41:37.370 Omni Analytics: Yeah, I just put them, like, again, like.
428 00:41:37.780 ⇒ 00:41:44.960 Omni Analytics: just because focus is such an issue that I’m generally telling my team, let’s start building out, like, a retail page.
429 00:41:45.340 ⇒ 00:41:47.590 Omni Analytics: But on that, it’s like, you’re gonna have folks…
430 00:41:48.730 ⇒ 00:41:57.130 Omni Analytics: like, across the whole spectrum. Like, from Guitar Center to direct-to-consumer, e-commerce only…
431 00:41:58.020 ⇒ 00:42:13.330 Luke Scorziell: Yeah. Well, we can start… so maybe, like, actionable takeaways for me, then, for this call is, like, highlighting the semantic layer and the AI. I don’t like the… yeah, that’s, like, the key value proposition.
432 00:42:13.610 ⇒ 00:42:15.880 Luke Scorziell: And then, through…
433 00:42:16.980 ⇒ 00:42:21.589 Luke Scorziell: I’m still gaining familiarity with our clients, but we’ve had a lot of success with, like, econ.
434 00:42:21.590 ⇒ 00:42:22.200 Omni Analytics: No.
435 00:42:22.340 ⇒ 00:42:23.050 Omni Analytics: Awesome.
436 00:42:23.050 ⇒ 00:42:25.640 Luke Scorziell: and CPG-type clients, so, like.
437 00:42:25.640 ⇒ 00:42:26.080 Omni Analytics: Mmm.
438 00:42:26.080 ⇒ 00:42:27.460 Luke Scorziell: Amazon-type shop.
439 00:42:27.460 ⇒ 00:42:27.970 Omni Analytics: Yeah.
440 00:42:29.210 ⇒ 00:42:37.009 Luke Scorziell: people, and then we’ve also done agencies in terms of, like, we were working with… but that’s more on the AI, I guess, side.
441 00:42:37.410 ⇒ 00:42:39.599 Luke Scorziell: But they still need data analytics, especially.
442 00:42:39.600 ⇒ 00:42:43.089 Omni Analytics: Oh my god, we have a lot of AI companies, so, like, Perplexity is a customer.
443 00:42:43.930 ⇒ 00:42:45.640 Omni Analytics: Okay.
444 00:42:46.170 ⇒ 00:42:53.239 Omni Analytics: And I would just kind of, like, again, for now, for, like, the hell of focusing, I, like, group them into tech.
445 00:42:53.530 ⇒ 00:42:54.290 Luke Scorziell: Yeah.
446 00:42:54.780 ⇒ 00:43:04.569 Omni Analytics: But… Yeah, so, like, Perplexity’s a customer, like, Writer’s a customer, Synthesia, Photo Room,
447 00:43:05.370 ⇒ 00:43:07.090 Omni Analytics: We… a lot of…
448 00:43:07.420 ⇒ 00:43:12.059 Omni Analytics: like, we’ve been really lucky to get to work with a lot of cool AI companies.
449 00:43:12.060 ⇒ 00:43:14.480 Luke Scorziell: Yeah, that’s super cool.
450 00:43:14.590 ⇒ 00:43:21.910 Luke Scorziell: Cool, okay. Well, I’ll try to get the… or I guess if you get a list, but I’ll try to get a list from my side of overlapping customers.
451 00:43:21.910 ⇒ 00:43:32.220 Omni Analytics: Awesome. Yeah, I’ll ping John, and just see if there, if there’s anyone who is. But yeah, if you hear of anything, or like, if there’s an opportunity to collaborate on a case study, definitely let me know. Yeah.
452 00:43:32.560 ⇒ 00:43:49.580 Omni Analytics: I, like, lead all of our case studies, but I’m happy to, like, work together and kind of figure out, like, what works best, for you. Obviously, like, I would imagine you’re probably quite comfortable, like, interviewing people and doing that kind of stuff. Yeah. So that’s awesome. Yeah, and then on the post…
453 00:43:49.610 ⇒ 00:43:55.799 Omni Analytics: yeah, I think from, you know, Kira, potentially up to 4 a month is something that we’re, like, down to test and stuff,
454 00:43:56.020 ⇒ 00:44:01.620 Omni Analytics: like, yeah, I think talking about, kind of, the uniqueness of our semantic layer and, like, why that
455 00:44:02.320 ⇒ 00:44:12.099 Omni Analytics: like, really contributes to more reliable AI is really helpful, and then just, like, some of those use cases, I think the very specific use cases and stuff are… are super,
456 00:44:12.210 ⇒ 00:44:15.069 Omni Analytics: Nice, and something my team’s starting to think about a little more.
457 00:44:15.540 ⇒ 00:44:17.559 Luke Scorziell: Yeah, okay.
458 00:44:18.410 ⇒ 00:44:30.050 Luke Scorziell: I mean, we’re super down to experiment, so… and I was a journalism major in college, and then I had a podcast, in high school, so… and it was all, like, interview-based, so I love doing interviews, and like…
459 00:44:30.240 ⇒ 00:44:30.630 Omni Analytics: Yeah.
460 00:44:30.630 ⇒ 00:44:33.729 Luke Scorziell: Learning people’s stories and, and whatnot, so…
461 00:44:33.730 ⇒ 00:44:34.260 Omni Analytics: Awesome.
462 00:44:34.650 ⇒ 00:44:39.149 Luke Scorziell: Yeah, and if there’s any way that I can be of help to you at all, like, feel free to…
463 00:44:39.340 ⇒ 00:44:48.529 Luke Scorziell: reach out, like, whatever, if you have, like, random ideas that pop up, like, here’s what, you know, you could market, or if, if, again, if you’re, like, interested in that video.
464 00:44:48.630 ⇒ 00:44:50.390 Omni Analytics: Production company, yeah.
465 00:44:50.390 ⇒ 00:44:53.180 Luke Scorziell: Very happy to be a resource in whatever way I can, so…
466 00:44:53.180 ⇒ 00:44:55.679 Omni Analytics: Awesome, thank you. Yeah, I’ve gotta…
467 00:44:56.350 ⇒ 00:45:00.180 Omni Analytics: I’ve got to get my feet under me a little bit more after last week. I need to…
468 00:45:00.180 ⇒ 00:45:00.870 Luke Scorziell: Yeah, like…
469 00:45:01.040 ⇒ 00:45:11.990 Omni Analytics: I’m behind on my OKRs for this quarter, I need to plan those a little bit, and… and get some, like, event presentation decks up, but I’m like, I know that there’s a lot of big things that I need to be thinking about that I’m kind of like, oh, yes.
470 00:45:13.130 ⇒ 00:45:16.739 Omni Analytics: I’ve got a… I’ve gotta schedule time to think about that.
471 00:45:16.930 ⇒ 00:45:25.479 Luke Scorziell: Yeah, well, anything, I mean, even if we can help with, like, the case studies, or… I don’t know, like, what specific OKRs you have, but…
472 00:45:25.800 ⇒ 00:45:31.739 Luke Scorziell: like… Like, yeah, I just want to be able to support you in however we can, so…
473 00:45:31.740 ⇒ 00:45:39.820 Omni Analytics: Awesome, thank you. And if there’s anything, like, on the content side, if you’re like, hey, we’re thinking about this, like, would love to share, like, if you have any feedback or anything like that,
474 00:45:40.120 ⇒ 00:45:46.919 Omni Analytics: Like, happy to take a look at things, or just kind of, like, share feedback based on, like, what we’ve seen.
475 00:45:47.410 ⇒ 00:45:56.070 Luke Scorziell: Yeah, okay, that sounds good. I’m, like… I’m past the point, I think, of, like, does this even make sense? Which is kind of where I first was, but…
476 00:45:56.070 ⇒ 00:45:59.360 Omni Analytics: I mean, I still ask myself that all the time, I’m like, does this…
477 00:45:59.690 ⇒ 00:46:05.519 Omni Analytics: Does this make sense? Because it makes sense in my head, but did I, like, reason over that? Yeah.
478 00:46:05.720 ⇒ 00:46:10.560 Luke Scorziell: Well, there was a time where I was, like… I was just, like, I felt like I needed Robert, I knew Tom to, like.
479 00:46:10.760 ⇒ 00:46:15.869 Luke Scorziell: check every single detail, and now I’m like… If I get it wrong.
480 00:46:16.070 ⇒ 00:46:22.710 Luke Scorziell: Hopefully it’s not, like, so wrong, but, but yeah, it’s been… it’s been fun. It’s like learning a whole new…
481 00:46:23.150 ⇒ 00:46:24.020 Omni Analytics: Wow.
482 00:46:24.120 ⇒ 00:46:25.519 Luke Scorziell: Language, I don’t know.
483 00:46:26.150 ⇒ 00:46:28.730 Omni Analytics: Yeah, it’s wild. I used to make Colin…
484 00:46:28.780 ⇒ 00:46:32.149 Luke Scorziell: read every blog post that I was in.
485 00:46:32.150 ⇒ 00:46:40.460 Omni Analytics: And it was, like, when we were small, I was like, okay, like, I wanted Colin to look at everything, even though I had been in data for a while, it was still, like.
486 00:46:40.890 ⇒ 00:46:46.229 Omni Analytics: you know, at that size, it’s like, you’re building a company, you’re building a voice, you’re building an opinion, like…
487 00:46:46.480 ⇒ 00:46:53.389 Omni Analytics: Even if you know enough to something… to know if something is technically correct, you’re like, does this align with who we are?
488 00:46:53.720 ⇒ 00:46:54.230 Luke Scorziell: Yeah.
489 00:46:54.230 ⇒ 00:47:00.800 Omni Analytics: And, like, our opinion of the world, because, like, there’s being correct, but then there’s also having a point of view, and it’s…
490 00:47:01.550 ⇒ 00:47:02.810 Omni Analytics: Very hard.
491 00:47:03.340 ⇒ 00:47:03.800 Luke Scorziell: Yeah.
492 00:47:03.800 ⇒ 00:47:14.489 Omni Analytics: And, like, now, over, like, the last few years, obviously, like, as we’ve been, like, building the business and stuff, and, like, understand all that a little bit more, it’s easier, but I used to make Colin look at everything, be like, do you agree with this?
493 00:47:17.390 ⇒ 00:47:29.860 Luke Scorziell: Yeah, that was funny, so… Totally happens. We’re definitely at early, yeah, early stage of, like… we had a post go out last week or two weeks ago, I think, I don’t know, and then your Tom read it and was like, we have to take this down.
494 00:47:29.860 ⇒ 00:47:31.039 Omni Analytics: Oh yeah, I’ve been there.
495 00:47:32.290 ⇒ 00:47:35.929 Luke Scorziell: So, it’s just like, okay, learning experience.
496 00:47:35.930 ⇒ 00:47:42.499 Omni Analytics: I remember one very specific… actually, it was a tweet at Looker on a blog, and I…
497 00:47:42.770 ⇒ 00:47:55.860 Omni Analytics: had posted it on LinkedIn, and the LinkedIn copy was great, but then I had had to cut it for Twitter. This is, like, 8 years ago. I had to cut the copy for Twitter to make it fit. It was, like, back when Twitter’s… I don’t even know what the Twitter character count is now.
498 00:47:56.020 ⇒ 00:47:58.610 Omni Analytics: But it was, like, quite small, and I cut it.
499 00:47:59.410 ⇒ 00:48:07.500 Omni Analytics: And I was, you know, was like a baby, and I had no idea what I was doing. I remember getting multiple messages, and people were like.
500 00:48:07.640 ⇒ 00:48:08.960 Omni Analytics: That doesn’t work.
501 00:48:10.060 ⇒ 00:48:12.880 Omni Analytics: It no longer makes the point that you want it to make.
502 00:48:13.750 ⇒ 00:48:14.680 Luke Scorziell: Oh, gosh.
503 00:48:16.480 ⇒ 00:48:18.280 Omni Analytics: So… I have been there.
504 00:48:18.550 ⇒ 00:48:19.290 Luke Scorziell: Yeah.
505 00:48:19.710 ⇒ 00:48:21.570 Luke Scorziell: Good to know. Yeah.
506 00:48:22.050 ⇒ 00:48:23.990 Luke Scorziell: Yeah, I’m like, so.
507 00:48:23.990 ⇒ 00:48:27.780 Omni Analytics: I mean, it’s hard, like, not everyone has everyone, like, their job so public.
508 00:48:28.820 ⇒ 00:48:32.579 Luke Scorziell: Yeah, yeah, yeah, that’s true. And it’s, yeah.
509 00:48:33.700 ⇒ 00:48:34.140 Omni Analytics: Yeah.
510 00:48:34.140 ⇒ 00:48:43.650 Luke Scorziell: Yeah, it’s fun, though. I don’t know, it’s fun. I’m, like, I think early… earlier in my career, so… and I don’t know, maybe it was just something that you struggle with throughout your whole career, but it’s just, like,
511 00:48:44.770 ⇒ 00:48:45.979 Luke Scorziell: Yeah, I think…
512 00:48:46.540 ⇒ 00:48:51.879 Luke Scorziell: Some… maybe the way my generation grew up was, like, very, like, anti-mistake, like, don’t make any money.
513 00:48:52.260 ⇒ 00:48:55.359 Luke Scorziell: So I feel like it can be… there’s, like, the perfectionistic, like…
514 00:48:55.830 ⇒ 00:48:57.930 Luke Scorziell: Tendencies. Maybe that’s everyone, I don’t know.
515 00:48:57.930 ⇒ 00:49:01.449 Omni Analytics: I mean, that was 8 years ago, and I can tell you exactly what the tweet was, so…
516 00:49:01.450 ⇒ 00:49:03.660 Luke Scorziell: Oh, okay.
517 00:49:03.660 ⇒ 00:49:11.419 Omni Analytics: I’m… and, like, but I’ve run corporate socials for, like, 10 years, or it’s been on my team for 10 years, and I still hate posting on LinkedIn.
518 00:49:12.440 ⇒ 00:49:14.160 Omni Analytics: And never… and, like, I…
519 00:49:15.160 ⇒ 00:49:21.569 Omni Analytics: I don’t want any, like, yeah, I don’t want to give it up, because I would have an opinion about it, but I also… it’s terrifying, so…
520 00:49:21.570 ⇒ 00:49:22.130 Luke Scorziell: Yeah.
521 00:49:22.130 ⇒ 00:49:22.869 Omni Analytics: I get it.
522 00:49:23.410 ⇒ 00:49:25.250 Luke Scorziell: We’re just entering the world, so…
523 00:49:25.390 ⇒ 00:49:26.230 Omni Analytics: They’re like.
524 00:49:26.230 ⇒ 00:49:27.020 Luke Scorziell: I’m not, yeah.
525 00:49:27.020 ⇒ 00:49:40.479 Omni Analytics: No, but that sounds good. If, yeah, if there’s anything that you’re like, hey, here’s, here’s, like, a few topics we were thinking of, like, what do you, like, which one do you think is the most interesting? Or, like, here’s kind of a draft, like, would love opinions on that. Feel free to send that over.
526 00:49:40.480 ⇒ 00:49:47.249 Omni Analytics: Yeah, on the LinkedIn post, if you’re thinking about something, like, let us know, and we can kind of plan and boost some stuff, or take a look.
527 00:49:47.390 ⇒ 00:49:59.640 Omni Analytics: And then, yeah, I think, like, use case stuff would be really interesting, and then if you guys, like, have a listicle or anything like that, I know that that’s something that, like, Kira is really interested in, and would love to see.
528 00:49:59.890 ⇒ 00:50:08.370 Luke Scorziell: Okay, and with the listicle and the use cases, are those… would those just be, like, certain… like, are there any features that you would want us to highlight? I mean, obviously, Blobby…
529 00:50:09.340 ⇒ 00:50:18.840 Omni Analytics: I mean, I think the listicle, and I need to look back kind of more things from her, I think that was kind of more, like, comparing different tools and stuff like that.
530 00:50:18.980 ⇒ 00:50:19.610 Luke Scorziell: Yeah.
531 00:50:21.210 ⇒ 00:50:27.339 Omni Analytics: But then… so that would kind of be, like, more broad, like, not necessarily Omni-specific.
532 00:50:27.740 ⇒ 00:50:35.549 Omni Analytics: Thing, that would be, like, kind of the listicle posts that she shared, but then, yeah, for use cases, I think, like, depending on the use case, but, like.
533 00:50:36.070 ⇒ 00:50:43.100 Omni Analytics: Definitely… highlighting Blobby, and just kind of depending on the use case, so…
534 00:50:43.100 ⇒ 00:50:58.889 Omni Analytics: and, like, what the blog is about, so if you’d want to kind of, like, highlight different ways, like, to bring in context, like context from DBT, like, building with AI, using Blobby, like, dashboard summaries, like, a big wow thing for me whenever I talk to customers, like.
535 00:50:59.120 ⇒ 00:51:18.059 Omni Analytics: they’re always just like, oh my god, my stakeholders love, like, we have an AI summary viz, which is a visual that you can put on a dashboard, and rather than it having to be, like, a bar chart, it can, like, summarize and give you key takeaways from the dashboard, which is really nice, because if you think about it, like, a lot of people have dashboards, but then they… a very common
536 00:51:18.080 ⇒ 00:51:24.740 Omni Analytics: next step is to go back to the data team and be like, what does this mean? What do I do with it? What matters? Is this… I see, like.
537 00:51:24.740 ⇒ 00:51:38.959 Omni Analytics: it says this is 500. Is 500 good? Is 500 bad? So, like, a lot of our customers will use the AI summary visualization, and, like, they’ll code in kind of the context and say, like, hey, like, the person looking at this dashboard is a sales leader.
538 00:51:38.960 ⇒ 00:51:50.209 Omni Analytics: This is what they care about. Here’s context on this. Like, here’s what their goal is. So, like, give them summaries on, like, how they’re pacing to goal. Like, you can really customize it.
539 00:51:51.470 ⇒ 00:52:00.440 Omni Analytics: And so, I think, like, the AI summary visual is something… that… it’s not…
540 00:52:00.710 ⇒ 00:52:06.800 Omni Analytics: it may not, like, totally catch your eyes if you’re, like, looking through docs, but it’s something that I talk to customers all the time, and they’re like.
541 00:52:07.450 ⇒ 00:52:10.459 Omni Analytics: The data teams love it, and their stakeholders love it.
542 00:52:10.930 ⇒ 00:52:15.009 Luke Scorziell: Yeah, okay. I mean, we can definitely dive into that.
543 00:52:15.010 ⇒ 00:52:15.810 Omni Analytics: Yeah.
544 00:52:16.760 ⇒ 00:52:24.170 Luke Scorziell: And then, I guess, is there anyone else that you think would be helpful for me to chat with? Who’s… I don’t know, like… maybe it sounds like Kira might be…
545 00:52:24.520 ⇒ 00:52:31.070 Omni Analytics: Yeah, I mean, I think… I think potentially, like, if we… if you have…
546 00:52:31.260 ⇒ 00:52:49.519 Omni Analytics: Like, from kind of our first call and stuff, if you have, like, a list goal or anything like that that you want us to, like, react to, like, and you want to, like, share it, we can take a look at it, and then, like, see if it would, like, make sense to hop on a call or, like, different things and stuff like that. Like, if there’s, like, specific questions, yeah, we can definitely help with that.
547 00:52:49.970 ⇒ 00:52:54.460 Luke Scorziell: Cool, okay. Awesome. Sweet, we’ll get that to work. I mean, we’re down a deal once a week, so…
548 00:52:54.460 ⇒ 00:52:56.120 Omni Analytics: Okay. Awesome.
549 00:52:56.120 ⇒ 00:52:57.730 Luke Scorziell: And see how it goes.
550 00:52:57.730 ⇒ 00:52:59.540 Omni Analytics: Awesome, yeah, I mean, that’s…
551 00:53:00.020 ⇒ 00:53:06.269 Omni Analytics: yeah, we just kind of test a lot of things, and we’re like, was that good? Was it bad? Do we know why? Let’s try it again.
552 00:53:06.270 ⇒ 00:53:07.420 Luke Scorziell: Yeah.
553 00:53:07.910 ⇒ 00:53:09.150 Omni Analytics: There’s a lot of that.
554 00:53:09.350 ⇒ 00:53:12.650 Luke Scorziell: Okay, cool. Well, yeah, and I’ll look at Screen Studio,
555 00:53:12.650 ⇒ 00:53:13.380 Omni Analytics: Yeah!
556 00:53:13.380 ⇒ 00:53:17.090 Luke Scorziell: We can use that as, like, a… I can have UTOM hop on that or something, and…
557 00:53:17.460 ⇒ 00:53:22.389 Luke Scorziell: we can just record some demos, or I guess I can start getting on the platforms, too.
558 00:53:22.390 ⇒ 00:53:28.269 Omni Analytics: Yeah, no, Screen Studio’s been great. We use it for, like, little GIFs, for videos, it’s just been…
559 00:53:28.660 ⇒ 00:53:33.279 Omni Analytics: Like, yeah, so cheap, and so… it’s paid for itself so many times.
560 00:53:33.550 ⇒ 00:53:35.450 Luke Scorziell: Oh, great, okay, good to know.
561 00:53:35.450 ⇒ 00:53:40.410 Omni Analytics: Yeah, I think it’s, like, $300, to get, like, 3 seats.
562 00:53:40.540 ⇒ 00:53:45.150 Omni Analytics: And that’s, like, a lifetime seat, so it’s just, like, a key for your computer. It’s not a subscription.
563 00:53:45.150 ⇒ 00:53:46.340 Luke Scorziell: Oh, oh, oh, that’s…
564 00:53:46.340 ⇒ 00:53:47.979 Omni Analytics: Like, it’s very cheap.
565 00:53:48.170 ⇒ 00:53:51.630 Luke Scorziell: Okay, yeah, I wasn’t sure if it was $300 a month for, like, their.
566 00:53:51.630 ⇒ 00:53:52.500 Omni Analytics: Oh, no.
567 00:53:52.780 ⇒ 00:53:53.410 Luke Scorziell: Okay.
568 00:53:53.410 ⇒ 00:54:00.299 Omni Analytics: No, I think I’ve spent $600 on it total in, like, 3 years, and I’ve bought, like, 6 different people licenses.
569 00:54:00.940 ⇒ 00:54:02.050 Luke Scorziell: Wow, okay.
570 00:54:02.540 ⇒ 00:54:04.679 Omni Analytics: So, definitely…
571 00:54:04.990 ⇒ 00:54:13.410 Omni Analytics: I mean, I don’t… yeah, for us, it’s been, like, super worth it, and I share it with people all the time, and I’m like… for other, like, product marketers that I talk to, I’m like, this is great.
572 00:54:13.900 ⇒ 00:54:14.470 Luke Scorziell: Yeah.
573 00:54:14.670 ⇒ 00:54:19.280 Luke Scorziell: Okay, yeah, I mean, we’re just… we’re using, like, Loom and Zoom.
574 00:54:21.180 ⇒ 00:54:23.349 Luke Scorziell: I think this’ll be… could be better.
575 00:54:23.350 ⇒ 00:54:24.430 Omni Analytics: Awesome.
576 00:54:24.730 ⇒ 00:54:25.150 Luke Scorziell: Cool.
577 00:54:25.150 ⇒ 00:54:33.459 Omni Analytics: Okay, well, great chatting. Yeah, let me know if there’s, like, questions or specific things, feel free just to, like, send it over, like, Slack, and then we can see who’s the right person and kind of see.
578 00:54:33.720 ⇒ 00:54:34.959 Luke Scorziell: Yeah, that sounds good.
579 00:54:34.960 ⇒ 00:54:35.470 Omni Analytics: Awesome.
580 00:54:35.470 ⇒ 00:54:39.339 Luke Scorziell: Well, thanks so much again for making time, I appreciate it. Of course. Good luck catching up on everything.
581 00:54:39.340 ⇒ 00:54:40.160 Omni Analytics: Thanks.
582 00:54:40.160 ⇒ 00:54:40.720 Luke Scorziell: Alright.