The TV ad-buying landscape remains a highly analog business – but, no sooner have digital platforms begun making in-roads to the process, already the newfangled technology of blockchain is staking its claim.
After a year or two of talk and theory, now several vendors are out there, promising to enhance media-buying transparency with blockchain, a distributed technology which creates a tamper-proof ledger of actions and transactions within a given system.
Those vendors think that core principle can sit well in media buying, which has been hit by concerns over excess and often invisible fees charged along the supply chain.
One is MadHive. More than that, MadHive is involved in two initiatives:
- MAD Network: a set of standards with which MadHive hopes other blockchain products will interoperate.
- Adledger: an R&D consortium along with Tegna, IBM and a host of members aimed at technical standards and solutions for the digital media and blockchain industries.
“It’s very early days,” says Adam Helfgott, MadHive CEO, in this video interview with Beet.TV.
“Our goal is to create a transparent ecosystem, where basically math and physics proves what happened, rather than having attestation from third parties.
“And with that, we can return digital to a linear-like ecosystem, where … the way that advertiser wants to advertise, and the seller creates a contract, and you have measurement that proved it aired.”
Whilst the explosion of transparency and fraud worries, a couple of years ago, spooked the internet advertising world, analog media like TV seemed to remain largely untouched.
But, now that more TVs are getting connected to the net, could the risk spread?
Helfgott says he is aware of fraudsters editing certain bid streams to change desktop inventory in to video connected TV inventory, because it commands higher prices.
TV bosses may yet resist a migration to the digital ecosystem. But Helfgott hopes they can see the opportunity, in new technology, to trade in a linear-like way that is nevertheless powered by software and data.