Ooh!Media to use machine learning in new automated marketplace

By AdNews | 7 July 2018
 
Ooh!Media boss Brendon Cook unveils his machine learning plans at the recent A World of Unmissable event in Sydney.

Ooh!Media is launching an automated private marketplace that uses machine learning to help marketers find the best inventory to use and when to reach and engage with a target audience across its network of assets.

The online planning, buying and placement platform, announced at Ooh!’s A World of Unmissable event, will go to market next April.

It combines Ooh!Media’s network of more than 20,000 assets across roadside, retail, office towers, airports, cafes, universities fitness venues and elsewhere with audience data sets, such as Quantium, and machine learning models to work out contextually relevant media planning.

The marketplace is part of Ooh!Media’s $15 million investment in revolutionising out of home advertising to help it gain a larger share of the media investment pie. Ooh!Media recently sealed a $570 million deal to acquire street furniture giant Adshel, which is before the ACCC – another sign the outdoor company is investing heavily to grow its proposition.

“Serving ads is the easy part, but to operate a major out of home platform we had to rebuild the entire way we function as a business – from finance to operations to data and of course on how we deliver the right message at the right time in the right place to meet our client’s objectives and deliver results,” Ooh!Media CEO Brendon Cook said.

“We have worked alongside multiple partners in multiple industries to understand how, in this real time and connected world, Out Of Home needs to scale, be brand safe and deliver advertisers with a solution to book an optimised, flexible, contextually relevant creative and location-based campaign that will make their brand unmissable.”

'Tech company structure'

To build the machine learning infrastructure in-house, Ooh!Media has developed a ‘tech company structure’, including a team of data architects, data scientists, mathematicians and product people.

Today, the team is training the machine using clients’ briefs and audience behaviours so that it will be ready to go to market by next April.

When it is available, clients will be required to submit responses to a series of questions including typical information of a current media brief, such as period, budget, requirements for proposal and locations, plus specific information around audiences and media considerations.

“This will enable our clients, no matter what time of day and night – let’s say at midnight – buy, plan and place campaigns across our digital and classic inventory,” Cook added.

“It is a complete ecosystem that includes DSP (demand side platforms), SSP (supply side platforms), DMP (data management platforms) and other out of home specific platforms.”

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