How to Measure Marketing Creative Effectiveness with Artificial Intelligence (AI)
By Rasheeqa Jacquesson, Marketing Science Partner for MEA at Meta
The 'creative impact' of an ad used to be too subjective to measure. But innovative AI solutions are now enabling brands’ creatives to be analyzed effectively. Rasheeqa Jacquesson, Marketing Science Partner for MEA, from Meta explores how AI tools can help marketers develop more successful advertising strategies through leveraging creative effectiveness insights.
Did you know that the creative quality of an ad accounts for 70% of its success? Or that it’s more important than execution elements like scheduling or platform choice? Yet, despite being the most important campaign element, creative effectiveness is often overlooked. Around 40% of advertisers don’t even measure it. That’s because it’s subjective and therefore tricky to quantify. Right? Wrong.
Traditionally, feedback on creative has been measured using post-campaign focus groups or surveys, making the data somewhat undependable. However, today’s AI (Artificial Intelligence) solutions can analyze an ad’s creative impact far more effectively, and they’re becoming increasingly accessible to marketers.
Tools from Meta and others are optimizing campaigns’ creative prowess and advancing AI-enabled creative workflows – resulting in more sales. They’re helping marketers measure campaign performance and brand recognition, and removing the guesswork from future ad strategies. Moreover, automating routine creative tasks using AI enables marketers to focus on the campaign's long-term health and ensure ad budgets go further.
Creative AI: Where art and (data) science meet
Pioneering marketers are already using AI to maximize their advertising’s potential by simplifying the creative process, by helping to produce new creative assets, and by adjusting existing ones, at scale.
Automated software can translate content across languages, crop images to frame subjects better, and generate image descriptions to make visual assets more accessible. This allows marketers to uncover new artistic heights and reimagine how to convey messages across mediums.
But that’s not all. It’s now possible for AI to take an even larger role within the advertising lifecycle and assist marketing teams with planning and optimizing content like never before. AI tools can help marketers to develop more effective advertising strategies based on audience interaction data. This continuous approach to ad optimization is the future of marketing, and will help brands lead with content that audiences love.
How can AI measure creative effectiveness?
Performance prediction: Measuring creative effectiveness begins with Illumination, which provides both initial insights on a campaign’s creative effectiveness and builds a model to predict future performance. The results can help a brand uncover its next breakthrough campaign idea and guide the later stages of the creative process.
So how does it work? Illumination’s algorithms analyze anonymized and aggregated historical data on consumer behavior and identify which creative elements are most common in a brand’s highest-performing ads.
The result is a framework that helps marketers compare different advertising approaches and pinpoint the most effective one before the campaign begins. In turn, marketers can generate new creative assets with more confidence and surpass audience expectations more effectively.
Continuous optimization: AI can also help direct the creative strategy after a campaign kicks off. Recent changes to the digital ecosystem have meant that advertisers need to adopt a new playbook. By employing a test-and-learn process that continuously optimizes the creative, marketers can focus on what audiences like rather than who they are – and avoid privacy-related concerns from targeted advertising.
Performance evaluation, using machine learning, can highlight the potential of each creative element within an existing suite of assets. Automated testing can also enable brands to experiment more efficiently with dynamic business outcomes. This means that creative teams can continue to iterate and formulate more effective strategic approaches while campaigns are live.
Brand governance: It can be challenging for marketers in global businesses to balance variations in brand guidelines across territories, but it’s necessary if one wants to connect with local audiences effectively: consistent color palettes and tones of voice help brands feel unified and cultivate a consistent public image.
AI tools can help with this, too. They measure how creative assets and copy fit within existing brand guidelines, both between and within sub-brands, and identify areas for improvement, ensuring customer-facing communications are curated and consistent.
How have brands benefitted from Creative AI?
Domino’s Pizza is one of the world’s most recognized pizza brands, offering what seems like an infinite number of combinations of toppings and crust fillings.
When the company wanted to improve its video creativity using technology and AI, it enlisted Spirable’s creative intelligence suite. The two partnered together to create three unique ad variants to test on Facebook and Instagram, across a four-week period.
The result? Spirable found that while motion helped the effectiveness of the ads, moving the pizza out of the frame didn’t. By using these new insights in future ads, Dominoes increased its return on ad spend by 20%, click-through rate by 6%, and reduced cost per result by 9%.
