Marketers of Technology
00:08:07 · Andres Figuera, Elizabeth Arnold
[00:08:07] S1: Okay. And that was about what, three to four years ago since the ChatGPT and all that AI boom started? Or how long has ViralMoment been in the market? [00:08:16] S0: Yeah. ViralMoment has been in the market, I believe we're at about five years now, just around five years. So it all started around the AI boom. It took about a year to try and get in front of the right people. Would say you have to get the right traction, the right reports, and then all of sudden the Gartner analyst like, oh. [00:08:33] S1: No. And I imagine it would be a bit of a longer process to get the market to really understand that you're a category creator. As you mentioned, that was a bit of a difficulty you had. But after that obstacle has been surpassed, now let's come to the present. And how is marketing looking like for you guys nowadays? Since I believe you've already then situated yourself as a leader in this category and are pretty much the authority in AI understanding and analysis of this type of content, then do you feel a lot of competition has been created within the category after you guys? Or how is that looking?
00:09:06 · Elizabeth Arnold
[00:09:06] S0: Yes. So there is definitely more competition in the category. Now that AI is more widespread, it's easier to access. Models are opening up. Training models is becoming a little less cost heavy, little more efficient. People understand how to do this now. So more AI engineers are out there able to build something like this. So there's definitely been a lot of competition which has come through, which is great. It's validating, right? You're like, Hey, it's a thing, which is fun. Also a little scary. So there's like two worlds you kind of live in as like an executive leading that space. But there is a lot of competition coming in. I think what we're doing now is actually a little bit ironic is I'm breaking down that category. And I'm saying it was a category. And now I'm like, great, we did this. We made it a category. We told you this is a thing. But at the same time, we're not just this sidebar thing that you've only spent like you got a $100,000 on. Like this is data and it is important data that layers into your other data. If 82% of all the content on the internet is video and you're not looking at any of that, then you're missing all of the content that's important to you. Like your people are gonna be on TikTok, on YouTube, on Instagram reels, whether or not you're there. So what are they saying? And how are you gonna figure out what that is? And so that is just another data layer that doesn't necessarily have to live separately from your current intelligence layers. So although it is a new category, the data layer itself really should be an integrated data layer on top of the rest of the social listening that you have.
00:10:31 · Andres Figuera
[00:10:31] S1: And differentiating yourselves, Elizabeth, that's another question I always like to ask with these AI companies or anybody who is heavily using AI to provide a service, and that is, how are you being able to get customers to know all these values that you provide and that it's not just another AI company? Because I know you guys are situated as a leader and the authority right now, but do you feel that you have to educate still in order to not be confused with other companies that might be arising or that might be within the market right now?
00:11:00 · Elizabeth Arnold, Andres Figuera
[00:11:00] S0: Yeah, absolutely. Some of it comes down to basic things where over the next eighteen months, I just see not really being quite big differentiators. But right now it's things like data access. We've been around for a long time. We have a lot of different ways that we can access tons of data. So we have a lot of it, which is the most validating that you need. You're like, well, I need to see everything on dog, everything on YouTube. I need to see as much as I can. So having that a massive amount of data is very helpful. I think we're getting to a point in technology in the world where just having all the data isn't gonna be such a differentiator anymore. I think with the way that AI is going and access to these tools, that's all gonna collapse. So a lot of what we do is actually more multimodal now. So it's not only creating our own AI models on top of what we're running to make sure that we're grabbing the best taxonomies, the best sentiment emotion layers, best different layers to tell you what's happening with logo recognitions and visual recognitions. So what can we put inside of these videos to make the data richer and deeper? But then on top of it, it's layering that data and telling one cohesive story. So if you have your Reddit and your Twitter, sorry, axe data of the world, I really can't get over that whole Twitter fax thing. Like, still, it's been years now. [00:12:04] S1: I missed the little bird, honestly. I missed the blue logo, everything.
00:12:04 · Andres Figuera, Elizabeth Arnold
[00:12:04] S1: I missed the little bird, honestly. I missed the blue logo, everything. [00:12:09] S0: We need some more, yeah, blue logos back in our life. This black and white stuff's gotta go. So anyways, if you have all of that regular text based data, then you can layer in that video data on top of it and tell a really cohesive story about where people are, how they move from platform to platform. How does that sentiment trail from Reddit into TikTok and vice versa? Where are the trends really starting? How are they starting? Who's leading this conversation and what location and kind of demographic specificities you wanna go into. So the more multimodal that this data becomes, the better that you're gonna have more richer visual, deeper insights you can act on and move faster on. And that's a bigger thing nowadays is all these teams aren't necessarily cutting down the forty hour work week. Right? They're just saying, hey. Now you can do more. [00:12:51] S1: Exactly. [00:12:51] S0: So do more faster.
00:12:51 · Elizabeth Arnold, Andres Figuera
[00:12:51] S0: So do more faster. [00:12:53] S1: That's what I've seen that beginning to happen. Like the shift and the perspective of what a regular work day used to look like is completely different now because it's not a forty hour work week, just doing manual labor or just doing the tedious tasks that we used to do, but it's rather focusing on what matters most and allowing AI to create more time for us in order to curate and provide the human taste and whatever it outputs or whatever we're asking it to do. But Elizabeth, in terms of analysis and everything that you're learning with the data you guys have, what are the channels via which you're making sure that people see you guys and see everything you're mentioning that you're doing?