What is the "key" to breakthrough in the ReGenerative AI era?

According to CNBC, here's how to take advantage of the next quantum "leap" in digital advertising (Re)Generative AI.

The world of digital advertising is on the verge of dramatic change. According to experts, the past 10 years have been the period of the "decade of data".

In 2014, digital advertising accounted for only about 25% of total advertising spending. Today, that number is nearly two-thirds, or $667 billion, in annual global spending. The emergence of data has driven a “wave” of innovation, changing the way we define audiences, targets, and apply measurement and attribution to determine campaign success.

Illustration photo.

Illustration photo.

As the "decade of data" cedes control to the "decade of innovation," here's what you should know:

Data pressure.  With increasing restrictions on data collection and use, companies are having to spend more on data and application targeting.

Research on the power of creativity . Research continues to show that ad content is responsible for up to 70% of ad performance.

Focus on audiences across channels . Over-reliance on channels like Google (search) and Meta (social) has forced advertising providers to shape their thinking and shape their organizations around these channels. However, consumers are increasingly omnichannel.

Limitations of Generative AI:

Generative AI can struggle to maintain brand consistency and value due to its inability to capture the subtleties of a brand's voice and identity.

The opaque nature of Generative AI's content creation process raises concerns about copyright infringement and the potential for misleading or deceptive content.

Generative AI's reliance on diverse quality data can lead to biases and inaccuracies in content, requiring human oversight to ensure alignment with brand standards.

Focus on (Re)Generative AI

(Re)Generative AI is a lesser known term than Generative AI but there is still a big difference. Understanding this difference will transform AI from a vague concept with applications in the distant future into a series of clear steps that advertising platforms, publishers, agencies and investors can take advantage of. use now.

Comparison between (Re)Generative AI and Generative AI.

Comparison between (Re)Generative AI and Generative AI.

(Re)Generative AI will enable:

Enhance creativity . (Re)generative AI can analyze existing creative content and create new, innovative versions that push the boundaries of original content and design.

Increase efficiency . By automating and repurposing content across multiple platforms and formats, (Re)Generative AI dramatically reduces the time and resources required for creative production.

Scalability across platforms . ((Re)Generative AI enables brands to quickly scale creative efforts across different platforms (technical requirements) or user preferences, including display, video, CTV, etc. ..

How to apply (Re)Generative AI:

Leverage success on social networks : Using (Re)Generative AI helps expand the reach of content across channels and screens, enhancing creative performance.

Innovation in TV Advertising : Transform engaging social media videos into TV ads through (Re)Generative AI, optimize budget allocation for media spend and increase audience engagement viewers.

Apply Omni-Channel Strategy : Break down platform barriers by using (Re)Generative AI to create seamless, adaptable ads for different platforms that meet viewing habits diverse user content.

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