Around the marketing world, everyone is talking about the rise of direct-to-consumer (D2C) brands – those that don’t rely on anyone else’s retail channels and which exert great control over their advertising capabilities.

But, whilst not every brand is a Casper, Allbirds or Soylent, many other traditional companies which are reliant on marketing partners could be doing more to look like D2C.

That is according to one ad-tech exec whose company aims to capture data which infers the intent of consumers – and then execute on that in TV environments.

Former CNBC SVP and general manager Kevin Krim is CEO of EDO (Entertainment Data Oracle), a data science company that uses machine learning to crunch data sets like consumer search and browsing behaviour, turning it in to marketing data.

“What we saw in our research is that, this trend around direct-to-consumer brands that are doing such smart and interesting things with TV advertising… that’s not a phenomenon that’s unique in the consumers mind to direct-to-consumer brands,” says Krim in this video interview with Beet.TV.

“They don’t sit there and think, ‘Oh, well Dollar Shave Club is a direct-to-consumer therefore I will respond instantaneously to their ads on TV, and buy what they’re selling, but, oh, Toyota is a different kind of brand, so therefore I won’t do something when I see an ad for Toyota’.

“The reality is, consumers react in the exact same way to these ads. They grab whatever connected device they have near them if they’re stimulated … they’re going to go search for it.”

That is why search is one of the key signals that EDO uses in its machine learning analysis for customers.

Those customers are marketers, TV networks and movie studios.

For them, EDO has a database of real-time ad airings and measurement for how well national TV airings drive consumers in to purchase funnels.

Backers include the venture capitalist Jim Breyer, the co-founders of Moat and the actor/filmmaker Edward Norton.