Publish 12 Jan 2022
Publish 12 Jan 2022

The Advertising Model is Broken... But AI can fix it

Digital gurus will tell you that these are the golden years of advertising.

Long gone are the days of the spray and pray approach, where brands deployed extraordinary campaign budgets without being able to determine which channel or campaign generated sales or met their objectives.

The same data enthusiasts will tell you we’ve come a long way, and it's true. Thanks to sophisticated attribution modelling platforms, high volume multi-variant creative software and leaps in Artificial Intelligence, launching campaigns and optimising them towards the highest ROI has never been simpler.

AI adoption has saved trillions of advertising dollars and altered the media buying landscape forever. By focusing on ROI and maximising budgets’ yield, performance marketing has transformed the ad landscape.

But the reality is that only the media side of the industry has radically changed. When it comes to creative development, AI is currently plugged into the process after campaigns are launched.

Is this because we believe that human behaviour is too hard to decode? Expecting a machine to provide us with critical insights capable of shaping the ideal creative brief still belongs to a sci-fi novel.

Or maybe not.

The Current Model is Broken

Through its ability to process large amounts of data in a very short amount of time, AI finds the best possible interests, keywords, custom affinities, and targeting segments to create the perfect targeting plans and deliver better advertising to the right customer. It lowers ad costs by eliminating wasted ad spend on under-targeted consumers and provides real-time feedback, which can be turned into actionable campaign adjustments.

In other words, AI helps advertisers understand how to re-mix all campaign elements once the campaign is in the market.

But can marketers be sure they have the best advertising recipe to begin with? Could they be missing some key ingredients?

Today, creative campaigns are still conceived the same way they were 20 years ago: marketers and creative agencies blend their intuitions and experience with observations from market research.

The gestation involves multiple concepts, long presentations, heated debates, countless revisions, and last-minute approvals.

The result is a series of ads gone through the ‘brand filter’ which can only be the best guess of what appeals to a global audience.

That happens because cognitive bias affects creative people, like any other human on the planet.

Despite their brilliance in coming up with concepts that inspire and drive people into action, they cannot consider several points of view at the same time. Therefore, the message they develop works for some, but not others.

The core issue is that, under the current model, creative campaigns stem from limited assumptions. And that’s when machine learning comes into play.

In a world first, one company is using AI to analyse trillions of impressions and unlock the secrets of successful ad creative even before the first impression is served.

Zooming in on specific audience segments and target markets, they analyse ad campaigns and provide marketing managers with the answers they need when it matters the most: at the start of the creative development.

Thanks to data, they can now predict the highest-performing creative elements to use in their ads: the words that will elicit a response, the imagery, colours and shapes that will appeal to the audience, the gender and ethnicity of the talents to feature in photography, the call to actions to use and more.

Once given the ingredients, creative teams decide how to mix them, the recipes to follow and the rules to break, according to their experience and creative instinct.

In other words, creatives are provided with the audience’s favourite ingredients, but they use their talent to bake the tastiest cake for them.

The best part is that following this process increases the likelihood of their cake to be eaten (and thoroughly enjoyed).

There’s a New Model in Town

By combining machine learning capabilities with human intuition, a brand new model is born:

  • The intel provided by AI augments marketers’ knowledge and experience
  • Creative teams can focus on what they do best: injecting emotion and humanity into their ads
  • The old ‘Creative vs Data’ debate morphs into the ‘Creative informed by Data’ consensus
  • Brands shift from reactive to proactive
  • Optimal creative is developed first, and A/B split testing, tweaking and media optimisation come second
  • More personalised, creatively impactful campaigns that generate better results are produced.
Old Model New Model
Creative vs Data Creative informed by Data
Reactive approach Proactive approach
Media focus Integration of creative and media
Low segmentation High personalisation
Tweaks & retweets, A/B split tests Creative optimisation first
Small, incremental progress with many wasteful iterations Huge time and cost savings

This model has been pioneered by QuantPlus, the first company in the world to use real data to provide an affordable, accessible and scalable solution to inform future advertising creative.

QuantPlus – The Evolutionary Leap in AI Creative

QuantPlus CEO, Brad Pickett, has held leadership roles in digital advertising for over fifteen years. 

Throughout his career, he has observed that “traditional optimisation techniques can only result in incremental improvements after launching a campaign.”

Along with Salvador Klein and William Bakos, Pickett founded QuantPlus to allow clients to benefit from the new model:

“Informing ad creative with real data before ads are developed has proven a 300% increase in ROI.”

QuantPlus uses next generation technology powered by Google AI to analyse trillions of impressions across thousands of ads and match them to performance metrics.

The technology assesses every creative element of an ad:

  • Colour palette
  • Design and layout
  • Type of Imagery:
  • ~People (complexion, ethnicity, gender, activity)
  • ~Context (natural or built environment)
  • ~Objects (technology or miscellaneous objects)
  • Wording:
  • ~Primary text
  • ~Secondary text
  • ~CTA

All attributes are tagged and ranked based on their potential to drive higher engagement, lower media costs, and increase ad spend ROI.

They capture the analysis in their Creative Insights Report, which informs brands’ future creatives.

Unlike other AI ad creative platforms, QuantPlus allows marketers and creative teams to reimagine their campaigns before they launch.

The reports can inform better briefs, better conversations, better outcomes. This means no more guesswork for marketers, and no more tedious meetings spent justifying their decisions for creative teams.

Newcastle University and TAFE Queensland are amongst the first clients in the beta round, but more organisations have shown interest in testing QuantPlus technology.

Bottom Line

Companies whose decisions are informed by QuantPlus AI’s technology experience some fundamental, tangible benefits:

  • Faster and more efficient creative development
  • Better creative and higher engagement
  • Personalised advertising via multi-variant ad campaigns
  • Lower media costs and increased ROI

This gives them a real competitive advantage in the market, as shown in ‘Deloitte's State of AI in the Enterprise’.

According to the research, companies adopting AI believe smart technologies have helped them establish a significant lead over their competitors.

With AI adoption fast increasing, the time to act is now. Secure your competitive advantage with QuantPlus.

Book a call.