VerbAItim Research

Viewer Research as a Real Conversation. At scale.

We use AI that's been specially built to understand and analyze viewer conversation about news and news anchors. Because we've trained our computers to talk TV, we don’t have to put words in viewers’ mouths or limit them to talking about things that we think should matter.

We let viewers speak for themselves.

“We’ve been measuring how much viewers think like us instead of letting them teach us how to think like them. No wonder they’re losing interest.”
– Barry Nash

John Doe

More About VerbAItim Research

We have tools to listen like never before.

Traditional news research models are either quantitative with limited qualitative data or qualitative at a scale so small that the data is quantitatively unreliable. VerbAItim Research is built to overcome and transcend those limitations by delivering qualitative data at quantitative scale.

We don’t talk to just a couple of dozen viewers. We talk to hundreds – and sometimes more.

Because we’re able to ask open-ended questions at will, we’re able to get qualitative feedback at quantitative scale. That means it’s qualitative data you can trust like never before.

Our analyses go way beyond word clouds.

Word clouds are the most primitive form of linguistic analysis – telling you what words viewers use most but nothing about how they use those words or whether they use them negatively or positively. And sometimes the things viewers talk about most aren’t the things with potential to have the most impact. We use AI-driven technologies to discover the “whys” as well as the “what.”

There are no limits on what – or on how much – viewers can say.

Traditionally, quantitative news research literally puts words in viewers’ mouths, limiting them to evaluating news and news talent on our terms. With VerbAItim’s analysis technologies, we can invite viewers to say whatever they want and to say as much as they want. To be honest, is there any other way to know what they’re really thinking?

We take the bias out of verbatim analysis.

No matter how experienced or well-intentioned, it’s impossible for any one person to accurately absorb and analyze thousands of impressions submitted by hundreds of viewers. With AI, there’s no fatigue and no inherent bias. Every word gets equal attention and consideration. There’s no better way to ensure that you’re hearing what you need to hear, as opposed to just hearing what you want to hear.

We learn what to coach and we learn what to market.

Because we learn what truly matters most to viewers, we learn where coaching will have power to make a real difference. And because we’re getting everything in viewers’ own words, we literally learn what marketing conversations – language and images – will have power to make a real difference.

We sacrifice nothing quantitatively.

We’re easily able to capture all the quantitative data you’re used to seeing. Viewer demos, station preferences, performance relative to others in the market, and so on. In other words, just to put it in sophisticated research terms, that means you’re having your cake and eating it, too.

What is Possible with VerbAItim

Viewers tell us what they value most — and how your brand and your people measure up to that.

Traditional research limits viewers to rating talent on based on a list of predetermined attributes. We let viewers speak for themselves by simply asking them to tell us what matters most to them. The things they tell us are eye-opening and often nothing like those lists we’ve been using. And since it’s the viewers’ words and not ours, what we learn is as valuable and important to news marketers as it is to the journalists themselves.

What works and what doesn’t has never been clearer.

We learn what’s positive, what’s negative and what’s in-between. The result is a strikingly detailed report on where there is potential for improvement and, more importantly, where improvement will make a real difference.

We can map possibility.

When difficult decisions have to be made, is anything more valuable than knowing who has both the appeal and the potential to grow your base?

We get to the “why.”

Traditional quantitative methodologies stop at the “what.” Traditional focus group methodologies aspire to go deeper, but are compromised by small sample sizes, group dynamics and the limitations and biases inherent in unaided observation. AI-assisted analysis overcomes all of that, so that we achieve real qualitative insight at quantitative scale. We learn what’s going on, and we learn what we can do about it.

We see which problems matter most.

Because we can measure how strongly viewers feel about things, we can see clearly where coaching is likely to have the most impact. After all, if you’re going to invest in getting better, shouldn’t you know where you’ll get the biggest bang for your buck?

Want to know more?

If you’re counting on history and habit to secure your future, chances are good you won’t have one. Surviving and then thriving will depend on whether you can provide something so valuable and compelling that viewers will make an effort to keep you in their lives. We’d love to talk about how VerbAItim Research can help you figure that something out – and stake your claim to it -- before the other guys do.