“AI can’t be as creative as humans.”
“Only humans can understand how to ideate and conceptualize ads. AI can’t understand the nuances of human nature.”
Advertising, a primarily creative field, has not been too welcoming of the advances of artificial intelligence but that hasn’t stopped AdTech companies from exploring the endless possibilities that come along with AI.
This technology is far from a threat to the creative field as its functionalities are actually complementary and can be used to automate various manual processes making more time for creative activities and tasks. One such possible application is in creative testing as AI can help with quantitative findings that can complement the findings from qualitative research and customer discussion.
Because even though it is raining data, it is not always easy to pick a creative variable and pin the success of an entire campaign on it. There needs to be a method to this madness of understanding what actually makes a creative work.
Michelle Greenwald, Marketing Professor & CEO of Marketing Visualized, in one of the articles on the most important change in the advertising industry shares, ‘Developing ad campaigns was always hit or miss. We were never sure if it was optimized, had little idea which micro-targets it resonated with most, and it could take as long as 6 months to a year in test markets to determine the sales impact. By that time, market dynamics could have changed.’
With so many creative variables in play and the constantly changing dynamics of the industry, it becomes harder to define what actually makes a creative work. Most marketers would say that the secret to the success of their ads is creativity, but it can only take us so far.
Testing is the Ultimate Way to Creating Better Ads
There are two stages at which testing is conducted – first at concept stage to test and finalize concept for the ad and then at creative stage to test and pick the best performing ad for the campaign. Testing is an optimization process carried out before launching any ad campaign which allows you to zero in on the aspects that are performing well with your target audience at the brand level as well as at an individual campaign/creative level.
The current testing methods help marketers and insight teams understand if the creative will resonate with their target audience; based on which they make changes if necessary to improve the performance of creatives.
Unrecognized Limitations of Current Testing Methods
But it is not as straightforward as it seems. Even with all the tools and technologies available for creative testing, there are certain limitations to their usage. The current methods of creative testing are time-consuming, and tedious which again run a risk of not being able to cope with the changing market dynamics, making the results obsolete sometimes.
On the other hand, the increasing dependency on advertising platforms and their limited ad performance data is proving to be not enough to realize the true potential of ad creatives. While Meta allows you to conduct split and lift testing on its various social media platforms, the insights rarely pinpoint the creative variables contributing to the performance of the campaign. Since there are limited actionable insights, it becomes necessary to have a certain level of guesswork in the process.
Another major drawback of the current testing methods is their unscalable nature that limits marketers from testing the impact of multiple creative variables at once for different sets of target audience. Hence most times marketers only test important campaigns, leaving a large part of the social campaigns untested.
The scalability and robustness required for solving such complex problems and evaluating every creative variable to measure creative effectiveness can only be achieved by infusing advanced technologies like artificial intelligence in creative testing.
What is AI-Powered Creative Testing?
AI has been eliminating the tediousness, manual efforts, and scalability issues from various industries and it is also being explored in the ad testing space by various AdTech companies.
AI-powered creative testing allows you to test your creatives against campaign goals for a particular target audience in a matter of minutes.
The majority of AI-powered creative testing tools use different datasets to predict the effectiveness of creatives for various creative parameters. The parameters differ from one tool to another, but the general idea is to leverage the next generation of technologies to gather empirical data to build a fundamental understanding of what makes an ad work and to shorten the testing process. Thereby, shortening the launch cycles of ad campaigns, making the entire process more reliable and data-driven, and maximizing the return on ad spend.
How AI-Powered Creative Testing Tools Work
AI-powered creative testing tools evaluate the effectiveness of different creatives on variables like recall, attention, copies, music, emotions, and more which then can be compared and analyzed to pick the best performing creative.
Apart from ad testing, you can also measure
- Impact of promotional creatives on customers’ purchase intent
- The resonance of packaging with the target audience
- Performance of ad creatives based on channel-specific insights
AI-driven creative testing tools come equipped with custom creative analytics and reporting that are packed with actionable insights and improvement suggestions based on industry standards and current trends. They also alert you in case your target audience is experiencing ad fatigue with the current ad sets so you can replace ads and retarget to maximize the return on ad spend.
The standout advantage of this technology is its ability to suggest prescriptive measures to improve ad performance before the campaigns are made live rather than relying on the results from A/B or split testing.
Why AI-powered Creative Testing is the Next Big Disruptor in Advertising
As and how the use of technology grows in the advertising industry, the acceptance and usage of such tools will be more pervasive. Because not only does AI-based creative testing eliminate guesswork out of creative decision-making, but it also overcomes most challenges and limitations of current creative testing practices.
Both display and video ads can be optimized and launched at scale targeting different customer segments. This also enables you to add more context to ads by optimizing them for micro-segments defined by demographics, psychographics, journey stage, purchase behavior, and more.
Way around cookies
With Apple’s recent update of eliminating ID for Advertising and Google’s plan for phasing out 3rd party cookies, AI-powered creative testing can be the way around cookies as it provides insights that can help you better maximize return on your ad spend while respecting the privacy of the viewers and consumers.
To perform effectively, AI-powered tools need data, lots of data which means marketing teams and agencies will be pushed to broaden their horizons of thinking and test a wider range of messaging and customer segment hypotheses and creative assets.
Given the unpredictable nature of ads and the fast-paced dynamics of the entire industry, AI-driven creative testing can help marketers drive desired results and brand growth in a sustainable and creative manner.
Start Your Trial with AI-powered Creative Testing
At Incivus, we are building a creative intelligence platform powered by perception and various machine learning technologies.
Our Creative Intelligence Platform provides an interactive, easy-to-understand, and actionable evaluation of branding, characters, emotions, copies, visuals, and other creative variables to help you make attention-grabbing and engaging ads. Our platform also evaluates ad performance against campaign goals, past data, category and industry data to help you pick the right ads even before they go live and save time and cost of A/B testing, so you can launch successful campaigns at scale, which is the need of the hour.
To start your trial with us, write to us at firstname.lastname@example.org.