Generative AI is empowering people to express themselves and interact with the world in ways that were not possible even just a few months ago. It is a technology exploding with possibility. At Kantar, we’ve discussed what Large Language Models (LLMs) could mean for market research, now we consider the potential for multimedia, such as images and video. We explore what Generative AI could mean for visual creative and concept development - the potential to help companies craft ads or new concepts that more deeply resonate with people by tapping into their needs in new ways.

One of the most common questions raised about AI is, can technology really replace what is usually considered to be the uniquely human ability to be creative? We would say the answer is partly yes and partly no:

• Yes, in the sense that Generative AI has advanced to the point where anyone can, with a few simple prompts, generate what looks like amazing art, using tools such as Midjourney, DALL-E, Canva text-to-image, Fliki, Synthesia and Peech AI (to name just a few).
• But also no, as Generative AI is built on a vast human database containing the work of real artists and their styles. This enables the technology to do what it does, but human artistry has not been replaced. Strategically, prompting and moderating the outputs of AI systems will become a prominent role in the months and years to come.

But asking if technology can ‘replace’ a person may be the wrong question. We argue that humans and technology, when combined optimally, result in a better product.

AI in the creative development process

AI has a long history in the creative process - it’s not new. At Kantar, we help companies with solutions like Link AI to test creative variations in bulk and make rapid, confident decisions about which ads to run, and NeedScope AI to analyse a brand’s imagery and video to understand the degree to which they are in alignment with the brand’s targeted emotive positioning across touchpoints. We are also in the process of enhancing our Concept eValuate product to use AI to automatically identify and optimise innovation concepts with the most top-line growth. These products are informed by high-quality training data – Link AI is built on a database of over 250,000 campaigns and 35 million human interactions.

Using image and video AI in creative and concept testing

1. Concept evaluation

Imagine spending a lot of effort creating an ad or product concept that is likely to underperform. With Generative AI you could make near-instant changes to the original copy and re-test those changes to see if they outperform the original. The text in the concept could be used as a Generative AI prompt to create a more compelling image that captures the essence of the concept. This could be an iterative process where both the text and image(s) are refined together with oversight from a human analyst.

We tested this approach on a real product concept for a ready-made ingredients box delivery service. First, we used GPT-4 to optimise the text, which gave us a higher predicted performance than the original. We then used DALL-E to optimise the concept imagery and found the combination of optimised text and imagery, reviewed by a human achieved the highest performance.

2. Video summary

Our Link survey asks respondents to summarise an ad in their own words. This is valuable to media agencies who want to know if the ad conveys the intended message. If ads can be accurately summarised at scale, without asking respondents for input, they can be catalogued and subject to a meta-analysis on best practice from the most successful ads (or themes that are common to underperforming ads). Generative AI, when combined with Optical Character Recognition (OCR) - the process of recognising text from images - can help achieve high-quality video summarisation faster with fewer human inputs. This is again something we are actively pursuing at Kantar.

3. Creative shaping

While Generative AI tools are built for images, you can split a video into multiple images, pass them through image AI tools to edit them appropriately and stitch the results back together. Such edits could range from relatively simple (changing the overall colour palette of the ad) to very sophisticated (replacing an actor with a celebrity). This would drastically scale up the number of combinations that could be produced, tested, and re-tested in less time, with less effort. Human creativity supercharged by Generative AI technology. This is an ambitious idea with the current state of Generative AI technology, but it is something we are already testing and are excited about.

So, we can get rid of humans, right?

Definitely not. For a start, machines cannot understand the nuance of a brand’s identity and personality, which is a crucial component of creating content that fits a brand’s commercial and community objectives. The art of storytelling, of stitching together a compelling and authentic narrative, remains a distinctly human one. As is the art of using emotion appropriately to elicit the desired responses. A machine cannot make the right cultural decisions, consider principles of diversity and inclusivity, interrogate a brand’s purpose, etc.

And of course, things can just go wrong. Brands like Mint Mobile have humorously played with this concept: in January 2023 the company released an ad ‘testing’ ChatGPT’s ability to write advertising scripts. The technology’s limitations are played on, such as taking instructions literally, or not understanding the nuance of humour. The point is well made that humans need to craft the story. Coca-Cola understood this when creating their recent ad, which integrates AI smartly with live action and other digital effects, with stunning results.

Coca-Cola Masterpiece