Can AI Streamline Marketing for Speed, Efficiency and Cost?
Recent months have seen the remarkable rise of artificial intelligence (AI) and groundbreaking technologies, introducing new platforms and advancements that directly address the recurring question burdening marketers: How can we enhance our marketing efforts to achieve better results in less time and at lower costs? This enduring quest for improvement has finally found an answer to this question.
From the perspective of CEOs, CFOs, CMOs and other key stakeholders responsible for marketing their brand, a recurring question has always nagged at them: How can we enhance our marketing efforts, achieving better results in less time and at lower costs? Recent months have witnessed the rise of AI and groundbreaking technologies, introducing new platforms and advancements that address these very challenges. With these transformative advancements, it should come as no surprise that the advertising industry is feeling a sense of unease.
“Recent months have witnessed the rise of AI and groundbreaking technologies, introducing new platforms and advancements that address these very challenges.”
One such platform embracing AI is Omneky, which uses it to seamlessly integrate a marketer’s messaging strategy, brand assets and compelling imagery to generate hundreds or even thousands of iterations, each meticulously tailored to engage specific target audiences.
Source: Omneky
As explained here by TechCrunch, “After connecting Omneky with your accounts on Facebook, Google, LinkedIn and Snapchat, the platform pulls performance data from your past advertising campaigns. From this analytics dashboard, you can see how much you’re spending, how many clicks you’re getting, the average cost per click and more. But it gets even more interesting once you start diving a bit deeper. Omneky lists the top-performing and worst-performing images and text used in your ads. Customers can click on individual ads to see more details. Omneky automatically adds tags to each ad using computer vision and text analysis. The result is a dashboard with useful insights, such as the dominant color you should use, the optimal number of people in the ad and some keywords that work well in the tagline.”
The company is looking to expand deeper into the marketing technology and lead-gen marketing space by applying the same technology to landing pages. In addition to Omneky, similar AI tools to generate digital ad creative include Ad Creative, Creatopy, Luna, and Smartly.io. An overview about all of these platforms can be read here.
How Are Ad Agencies Responding?
This past week, global ad agency holding company WPP announced here that it is partnering with NVIDIA to develop a content engine that will leverage the ‘NVIDIA Omniverse™’ and AI to enable creative teams to produce high-quality commercial content faster, more efficiently and at scale while staying fully aligned with a client’s brand.” The press release expanded on this by describing how, “The new engine connects an ecosystem of 3D design, manufacturing and creative supply chain tools, including those from Adobe and Getty Images, letting WPP’s artists and designers integrate 3D content creation with generative AI. This enables their clients to reach consumers in highly personalized and engaging ways, while preserving the quality, accuracy and fidelity of their company’s brand identity, products and logos.”
“The new engine connects an ecosystem of 3D design, manufacturing and creative supply chain tools, including those from Adobe and Getty Images, letting WPP’s artists and designers integrate 3D content creation with generative AI.”
One aspect of this release that particularly caught my attention was the statement, “In addition to speed and efficiency, the new engine surpasses current methods, which require creatives to manually generate a vast number of content pieces using disconnected tools and systems.”
As someone who has worked for holding companies such as WPP and Omnicom, where billable hours were prioritized, I can’t help but question the implications for the creative teams responsible for executing the AI-generated work. To what degree will this technology ultimately commoditize the industry? And how will the holding companies justify billing a similar amount for an hour or so of AI-generated work versus days or even weeks of work performed by creative teams?
Furthermore, what would prevent brands of all sizes from licensing similar AI ad creative platforms and completely bypassing ad agencies altogether? These platforms are accessible to and designed for everyone, regardless of company size. Should this become the central question for marketers to consider—i.e., What are the true benefits of AI and how can they retain their share of the $700 billion digital advertising industry?
AI Ads vs. the Creative Team’s Ads: Is There a Difference?
Recently, the organization BrXnd.ai held its first conference in New York City to discuss the landscape of generative AI companies powering marketing and advertising.
One of the events at the conference was called the “Ad Turing Test.” As explained here, the Turing Test is a game introduced by computing pioneer Alan Turing to assess a machine’s intelligence. Turing wondered if it was possible to create a computer that could deceive a person into perceiving it as human. The ad Turing Test set out to follow a similar methodology by having humans follow an ad brief and then create an ad the way you would normally create one. The AI teams had to follow more rigid guidelines and rules:
• Use AI to generate all ad components and assemble the layout without relying on external technologies or manual crafting.
• Implement an end-to-end generation process that requires only the provided assets as inputs, aiming for a seamless “push a button, and an ad comes out” experience.
• Utilize specified technologies (e.g., LLM, Stable Diffusion) to synthetically generate all other assets used in the ad, avoiding the use of curated or copied media from external sources.
• Prohibit any post-processing of the ads, including text addition, logo placement or rearrangement, font selection, cropping, color grading, filtering, or other modifications after generation.
• Avoid generating components separately and stitching them together using tools like ImageMagick or similar methods.
As you can see below, some of the AI-generated ads were so convincing, I was only able to correctly identify half of them. You can take the same test here.
Source: BrXnd.ai
There’s no doubt that AI can, and will, streamline marketing processes, creating efficiency and accelerating speed. The ability to iterate and tailor digital marketing to various audiences and platforms presents a significant advantage for brands. In terms of cost, AI has the potential to save marketers money, especially if they invest in an AI platform and bring marketing responsibilities in-house.
This shift may lead to increased profitability, but could also result in a reduction in headcount. The final question revolves around the quality of work and level of creativity. While AI platforms excel at language crafting and summarizing vast amounts of content, as well as creating visually stunning outputs, human input is still essential to strategically define what the AI should generate in terms of relevance.
Questions? Feel free to email me here. As always, thank you for reading.
Photo by Google DeepMind on Unsplash
