The Importance of Artificial Intelligence for Marketing Campaigns

Artificial intelligence (AI) will have an impact on  marketing since it will increase the efficiency of strategies, segment audiences and manage advertising campaigns. Both AI  and machine learning are the most significant data initiatives in the coming years.

It’s an important time for brands because the potential of AI is increasingly relevant and for brands, it becomes a great help to understand the strengths of advertising. A Kantar study tells us that 49 percent of global marketers plan to spend more on AI creative testing next year.

The success of AI tools is in the fact that they promise quick responses and lower costs than traditional surveys. The potential to test more content faster has an appeal that makes a significant difference. This brings us to the following questions: Where should AI solutions sit alongside survey-based testing? What are the strengths and advantages of each? And most importantly, when to use one or the other? But above all, brands seek to obtain the best return on investment.

But you don't just have to have AI tools available; creative quality is vital to the success of ad campaigns. Kantar data shows that creative quality is the second-most important factor in profitable advertising, whereas marketers think it’s the fourth-most important. We also know that great creatives drive both brand equity and sales. So the right creative approach, coupled with getting the executional details right, add up to memorable elements that form the basis of winning campaigns.

These successful executions would not be possible without the new platforms that are emerging all the time as well as new digital formats. For example, in the last year, we have heard about the potential of the metaverse, with some brands leading the way to find a role they can play in these virtual worlds. This is something we hope more brands will explore in 2023 and beyond.

Furthermore, even traditionally offline channels are moving online with the unstoppable rise of VOD viewing, programmatic audio, and innovation within digital out-of-home (DOOH). At DOOH, we're seeing brands get really creative, using dynamic creative approaches that change based on weather conditions, time of day, traffic levels or location, as well as advanced display technologies to deliver truly engaging experiences. All of which require insights at every stage to understand where the creativity is being delivered or where it could be further improved.

From establishing your strategy and kicking off ideation, through to executing your campaign and optimizing in-flight, getting creative right is a journey, with testing and learning involved at every stage. This process can take months or days depending on whether it’s a new landmark campaign being devised or changing assets in a digital campaign. But the fundamental process remains the same.

Ai Allows Test and Learn

Brands need to constantly test and learn, but they need to have a backup of the results they are obtaining. One part is understanding the correct testing approach for each stage of a campaign. At Kantar, we see the role of AI-powered creative testing as a predictive tool. It can give you a go/no-go result with a creative approach and having lower costs opens up the possibility of testing competitor advertising, which has been largely prohibitive in terms of investment until now. But crucial to the output of any AI tool is the data that feeds it and is used to generate those quick indicative results.

Advances in AI simply reinforce why and when brands should use survey-based tests. Foundational data is crucial because an AI tool is only as good as the data behind it. This is where scale and quality matter. For example: the data that powers Kantar's AI tools comes from a database of 230,000 real-world ad tests.

When launching a new campaign, whether on TV or digital, granular insights are important because the details matter. It's a good idea to test a TV run three times, whether it's for a new product, a new campaign, a new creative theme, or even a downsize: first at an early stage, then again after a few key edits, with adjustments based on the findings, and finally in the near final stage, to refine. This means you are maximizing your chances of success and you can only get this granular, second-by-second understanding and optimization from previous survey-based testing as well as insights on key topics.

The future we see is not one where AI replaces survey-based tests but where it is a complement. For specific cases, both can coexist and work together, and offer excellent results. This hybrid approach will enable suitable pre-testing frameworks for any client who wants to maximize the return on their creativity.

Currently, we live in a world where immediacy rules and real time governs all business processes. In this context – and this is valid for professionals in any business area – you have to know how to take risks, as well as seek and experiment with solutions, even if they don't sound so viable at first and the environment seems to be against putting them into practice. The way to make the research and data we provide more relevant is to constantly reinvent ourselves and dare to do things differently. With the help of AI ,it is possible.