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The power of social media continues to transform how brands engage their target audiences. It's also placed a burden on them to be "always on." And brands, for the most part, are responding to customer demand. Some 42% of customer service responses made through Facebook, for instance, are answered in the first 60 minutes.

But that's just one element of customer engagement. Marketers are still looking for solutions that allow them to create, test, and choose the most effective social media ads—and AI is making it possible. AI and machine-learning can achieve two goals: help marketers make better ads, faster; and make those ads more engaging through creative.

The power of creative is underrated. But an assist from AI can do more than just reveal information about top-performing creative—it can also give marketers more freedom to be creative in how they engage with customers through advertising on social media.

By testing various creative treatments, prioritizing the role creative plays in ads, and choosing the right tools for ad creation, marketers can do more of what they do best: offer creative solutions to their customers and prospects.

The Utility of Creativity

A picture might be worth a thousand words, but the right images in social ads can convert prospects to customers.

It's already been proven that social ads with visuals are more impactful than text alone: On Twitter, tweets with images receive 18% more clicks than tweets without images. And video can be even more powerful: Four times as many consumers would rather watch a video about a product than read about it.

Creative, therefore, is the most important element of social ads. Accordingly, creative is also the element that should be tested most.

Building social ads with several creative treatments is just one step of many. The first step should be looking at past ads to see what performed best among target audiences. That data, paired with research on creative trends for various social channels, is a great start toward crafting effective and engaging ads.

But how can AI accelerate the creative process? By making data analysis faster and more accurate.

Analyzing data from earlier ads, trends from current ads across channels, and feedback from target audiences can help marketers explore and expand creative limits without wasting time or resources. Tracking ad performance, performance benchmarks, and real-time feedback can be easy if you use the right solutions. Of course, the results from experimentation aren't instant, but they do offer a clear roadmap toward consistent social ad success.

The Certainty of Testing

For years, marketers have relied on A/B testing to determine which types of content to display to customers. But in today's fast-changing social ad landscape, how can a marketer make such important decisions with only two choices? What happens when both A and B are wrong?

That's where multivariate testing comes in. Building a variety of ads—testing creative or video, copy, and headline options—can give marketers a better idea of what performs best for their target audiences. It can also reveal how to engage more than one target audience at a time. For example, 94% of B2B marketers use LinkedIn to distribute content. With that knowledge, B2B marketers can prioritize LinkedIn and use multivariate testing to discover which ads perform best on the platform.

Multivariate testing requires marketers to track each aspect of their ads, remove spend from low-performing ads, increase spend on effective ads, and use that data to create new ads. Creating several ads to test can be time-consuming, but finding the right formula is worth the cost—and the right AI-powered solutions can make creation and variation much faster and more effective.

Devote time and resources to multivariate testing, and evaluate your process regularly to ensure it's consistently effective.

Building the Right Tech Stack

Most marketers expect a tradeoff in relation to experimentation: Saving time means spending money. And that's to be expected, because very few effective social ad tools are completely free. But for paid social, investing in an effective solution can make the difference between a positive return on ad spend (ROAS) and a dent in the bottom line.

Going back to the importance of creative and testing: think about your current social ad tech stack. Are you using tools that make finding, making, and choosing creative faster? Are your solutions designed to report on the most- and least-effective ads on a regular basis? Does your tech automate both ad creation and improvement? Can your tech stack reveal benchmarks for ad performance across channels?

You can get out of your tech stack only what you put into it. Few solutions on the market meet all those criteria, but building a tech stack that fills the gaps is essential. Choose tools that allow you to automate ad creation and monitor ad performance. Search for solutions that highlight your successful ads and coach you on how to improve low-performing ads. Finally, evaluate your entire tech stack regularly to ensure you're still receiving a positive ROAS.

Each of those elements can help you deliver visually arresting ads in a relatively short amount of time.

Creating social ads that win and engage customers isn't something that can be done overnight. And the most effective tools to maximize time and resources are rarely one-size-fits-all. But for social media marketers, investing the time and money in tools that prioritize creativity are the best way to ensure more wins and better customer relationships.

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Effective Social Media Ads: How to Leverage AI-Assisted Creativity

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Quantifi is the leading R&D platform for digital ads. To learn more, visit quantifi.ai.