In this video interview with Beet.TV, the MD for solutions at WPP-owned Xaxis says the two different sides of the ad industry need to re-unite.
He says the key is finding ways to put creativity back at the centrality of ad ops, and scaling personal creative to programmatic scale.
“Creative in the programmatic space has always been underutilised, always been a little bit underappreciated,” Lin says.
He blames the separation on creative’s origins in linear media like TV and magazines, which led “creative agencies tend to be separate entities and separate disciplines from the media buying or the media planning entities”.
“In the programmatic industry, that creative activation is an afterthought because most of that creative again comes from the client’s creative agency,” Lin says. “So we’re essentially a lot of times taking or re-purposing what was already created by some agency who really have no connection to the media.”
Lin wants to change that, so that clients to utilise and recognise the power of creative in the programmatic ecosystem.
But that’s going to involve combining distinct requirements from each side.
“What we really want to do as a company is make sure clients have really bespoke creative that speaks to the consumers in this environment, and also connect that to the data and to the media that they’re running with us,” Lin says.
Dynamic creative optimization (DCO) can help the journey – the practice through which individual items within the creative can be customized for different recipients, leading to thousands of different variations.
That is a big increase from what Lin says is currently only “about three to about four creatives per campaign with clients”.
So technology is nevertheless going to be required to mix personal creative at scale.
For Lin, it all adds up to the quest for “responsible media”, which he defines as: “Taking the trends that we have right now, but evolving them to the trends of the future, which means cookieless, which means more cohort-based optimizations and a huge emphasis on creative variations and creative optimization.”
Xaxis is using two tools to make that mix:
Using signals like browser, location, time of day and the weather, “it enables us to create thousands of creative variations on the fly, it introduces thousands more different data inputs to which then our AI Copilot could actually optimise towards the output or the client’s outcome”.
“(It) takes cookieless cohorts of the best performing segments of inventory … like browser, creative, time of day, geo – and essentially optimises towards the best cohorts. So creative will only allow our AI and also other AIs to introduce a tonne of measurable aspects of the creative, like the click, how long someone hover on the ad, if they interacted with a video, how long they played a video.”
This video is part of the Global Forum on Responsible Media produced by Beet.TV, GroupM with the 4A’s. This track on creativity, advanced technology and advertising is sponsored by IBM Watson Advertising. For more videos on this topic, visit this page. For more information on IBM Watson Advertising, please visit this page.
]]>But, increasingly, artificial intelligence algorithms are proving they can restore the primacy of ad creative.
That is what a host of industry executives discussed when they gathered on June 23 for the Global Forum on Responsible Media,
This video is a summary of interviews with executive who spoke in the creativity/technology advertising track presented by IBM Watson Advertising.
The New Majority: MediaCom’s Prabhu Aims To Make Advertising Addressable
Dynamic creative versioning is allowing advertisers to deliver a diverse range of re-mixed ad creatives for consumers. But Anush Prabhu – US Chief Strategy Officer and Global Chief Strategy Officer, Creative Transformation, for MediaCom – says companies need to lean on software for something that is becoming too complex for humans, in two areas:
Robert Redmond thinks he has the answer – if producing a plethora of different ad creatives for a burgeoning range of audience types if complex for humans, call on the machines to help.
Specifically, machine learning like that offered by Redmon’s IBM is increasingly being called on to anticipate and remix the optimum ad creatives for different viewers.
“We teach an algorithm how to predict which individual assets to combine at real time to be most relevant for that consumer,” says Redmond, whose IBM Watson Advertising Accelerator assembles ad campaign creative elements based on audience reactions.
“We’re going to see more and more uses of technology and creativity together in very powerful ways to do this type of work.”
‘Data Artistry’ Unlocks Context & Cohorts: Mindshare’s Clayton’s Post-Cookie Dreams
Creative-focused technology is important because there is a growing sentiment that ad creative, in the programmatic era, has been overlooked in favor of super-targeting alone.
But it also comes as ad buyers look for solutions in the era after third-party cookies and digital identifiers. And that is seeing the re-emergence of contextual targeting.
“Context has always been considered this old-school thing of the past,” says Sean Clayton, executive director, solutions officer at WPP’s Mindshare. “But, really, as you start understanding that people move in waves, they move in larger cohorts, the ability to start executing against those cohorts is actually pretty exciting, especially when you can look within the programmatic ecosystem.”
Machine learning can help advertisers in the new world, despite declining usefulness of traditional identifiers, says Delphine Fabre-Hernoux, Chief Data & Analytics Officer at GropM’s Wavemaker.
“The power of machine learning is really to build this layer of intelligence on top of a more limited amount of signals and translate that into something which is quite meaningful,” she says.
“It may be insight, it can be intelligence that is going to optimise media planning, but it can also be the predictive piece. Everybody’s looking to really know where you need to put your media dollars to maximise the return on investment and contribute more to your bottom line.”
Xiao Lin of Xaxis wants to make sure clients have really bespoke creative that speaks to consumers. But he, too, wants to lean on technology to get there.
The GroupM division uses a tool called Copilot that uses signals like browser, location, time of day and the weather “to create thousands of creative variations on the fly”, Lin says: “It introduces thousands more different data inputs to which then our AI Copilot could actually optimise towards the output or the client’s outcome.”