AI Ad Creative on the Open Web: A Performance Advertiser’s Guide

Performance marketing teams are using open web advertising to discover massive new audiences and cost-effective inventory, as they move beyond oversaturated search and social channels. The open web offers massive scale, but it also brings fragmented ad formats and volume requirements that can quickly stymie a small team.

Without the help of artificial intelligence (AI) resources, performance advertising teams can easily fall behind. Incorporating AI ad creative can save time, as well as helping break through creative fatigue and testing effective copy and creative in a fraction of the time, versus strictly manual work.

What Is AI Ad Creative?

AI ad creative refers to the use of artificial intelligence tools to generate, optimize, and score advertising assets. These might include images, video, copy, and any other assets included in a performance marketing AI strategy. Done well, AI ad creative can take an advertising team from using slow, manual design processes to data-driven workflows built for high conversion output. It allows teams to scale in a way that isn’t possible otherwise.

AI ad creative tools include AI ad generators that provide all-in-one ad creation, along with video generation, image creation and editing, performance analysis and prediction, copywriting, and more.

As heavily used social and search channels show diminishing returns, advertisers are exploring broader options, and AI tools can help performance marketers meet the open web opportunity.

The open web — sites beyond the walled gardens of Google, Meta, and others — includes independent websites, news outlets, and other channels with massive reach. AI’s capabilities make it easy for marketers to scale ad creative quickly, which wasn’t previously possible for small, human-only teams. AI can support creating thousands of different ad sizes for these varied placements.

Gauging the Core Capabilities of AI Ad Creative Generators

When deciding on an AI ad creative generator for your particular needs, it’s essential to look at how a particular tool can ingest brand guidelines, then produce ready-to-launch campaigns, with the format types needed. Keep these capabilities in mind when evaluating AI ad creative generators:

1. Rapid Visual and Video Production

AI features can transform product photos into studio-quality static ads or create dynamic ad variations, such as AI video ads, to ensure synergy across channels and formats. Brands can use these features to produce high-end content without long production cycles or expensive photo shoots. These features can also be useful in creating or editing imagery to fit holiday or event campaigns, or to target a particular audience.

2. Data-Driven Copywriting and Hooks

High-converting ad copy is a top performance marketing goal across industries, and AI models can be particularly helpful here. AI ad generators can create headlines and CTAs based on high-converting frameworks, then use data to refine and test variations. AI tools analyze the psychological tone of the associated visual, taking into account brand guidelines, then create a cohesive, persuasive message.

3. Predictive Creative Scoring

Predictive creative scoring helps marketers get to the ideal creative to reach audiences, but it can also save significant budget and time. With predictive creative scoring, AI and ML can evaluate newly generated creative work against historic performance metrics like CTR, brand recall, and others. The AI analyzes the potential impact of the ad. With that data, teams can make sure to only allocate budget to those assets with the best statistical probability of success.

Beating Creative Fatigue With Infinite Variations

Modern digital audiences often look past ads they’ve seen before. This creative fatigue can be a real barrier to success for performance advertisers. AI tools can go beyond the creativity and available time of advertising teams to instantly produce brand-new, data-backed variations of successful ads and campaigns. These quickly created ads can extend campaign lifespans without requiring a lot of extra resources.

Adapting Ads for Diverse Open Web Placements

The open web requires multiple creative formats and sizes, which can easily consume a marketing team’s time. AI is able to automatically resize and reformat work so that the visual in a standard display banner can become a native content widget in seconds. This allows advertisers to adapt quickly and test campaign variations in hours, instead of months.

Using AI for Competitor Analysis

Beyond creating images, video, and copy for ads, AI platforms offer features that can identify and then reverse-engineer top-performing ads across particular industries. These can save a ton of time in competitor research and building a strategy. Consider exploring these capabilities depending on your business and marketing goals:

Social Media and Sentiment Analysis

AI tools can monitor the engagement rates, hashtags, and overall user sentiment of competitors to show what’s resonating.

Automated Monitoring and Alerts

Set up AI agents to continually track competitor websites for changes, then alert at certain thresholds or updates.

SEO and Content Strategy Analysis

AI tools can analyze keyword rankings, content gaps, and traffic sources of competitors to help you make regular updates.

Exploring A/B Testing Strategies for AI-Generated Assets

Using an AI ad generator brings a lot of power to your performance marketing team, particularly when it comes to ad creative testing. It also brings a new surge in the sheer volume of ad variations you can test. It’s easy to get overwhelmed by the possibilities, so make sure you bring a systematic approach to this multivariate testing, following these steps:

1. Define the goal of which metric you’re optimizing for and a hypothesis of which variant will perform better.
2. Use a tool like the GenAI Ad Maker to create multiple high-contrast variations of different ad elements, like headlines, images, and CTAs. Or, start with broad visual concepts if you don’t already have a sense of what’s generally successful with your audience.
3. Run the ads you want to test simultaneously to two equal audiences against a high-performing control version from your advertising platform. As with any A/B testing, focus on just one variable at a time, like the style of the image or the tone of the headline or CTA copy.
4. Once you have a statistically significant sample size, see what your ad platform or other AI-powered tools can tell you about the winning variant.
5. Use the AI tool to make smaller optimizations, like color tweaks.
6. Allocate budget accordingly to the winning ad.

Integrating AI Into Your Performance Marketing Workflow

The possibilities of using AI in performance marketing are nearly endless, and the number of product options on the market can support teams’ goals whatever their size, budget, or industry. Keep these tips in mind when adopting AI and integrating it into your performance marketing workflow:

• Prioritize high-quality, organized, and compliant data from the start to ensure on-brand outputs and accurate insights.
• Automate repetitive tasks first with AI (e.g., campaign monitoring) to learn quickly and continue automating workflows.
• Use a “human in the loop” model: set guidelines for AI usage and review all AI output for brand safety and consistency.

Measuring the ROI of AI Ad Creatives

Many AI ad generation platforms will assist with measuring ad creative ROI, but make sure you’re tracking your preferred key performance indicators (KPIs) when you’re paying to use AI-generated ad creative tools. Some foundational metrics include click-through rate (CTR), cost per acquisition (CPA), and return on ad spend (ROAS). When using AI ad creatives, remember that a core value metric is the reduction in creative production turnaround times.

Key Takeaways

AI capabilities have matured so quickly that performance marketers can now choose from a variety of platforms, depending on their needs. This maturity curve aligns nicely with the potential of open web advertising, which offers scale and incremental growth beyond the walled gardens of search and social. Modern performance marketers have to include AI automation in their strategy to overcome creative fatigue, save time and money, and successfully scale on the open web.

Frequently Asked Questions (FAQs)

How does AI improve ad creative performance?

Beyond simply making different types of ad creative, AI ad generators are able to analyze vast amounts of historical performance data to predict which visual and textual elements will drive the highest engagement. With this information, ad generators can then create optimized variations for specific audiences. Ideally, you’ll then see increased CTR and lowered CAC.

Can AI generate video ads as well as static images?

Yes, AI ad generators can produce video ads as well as static images to provide consistency across formats. AI-generated videos can be very realistic, with AI avatars, voiceovers, product interactions, and more, all without the overhead expenses of a studio. AI can also write effective copy.

Does using AI ad creative mean replacing human designers entirely?

No, it doesn’t. AI is an efficiency tool for performance advertising teams. It can cut out repetitive and time-consuming tasks like resizing, versioning, reformatting, repurposing, and ideating for testing and campaign expansion. Human designers and strategists can use AI as a tool to support their work of managing and using brand voice, building campaigns and setting goals, and developing creative guardrails for AI tools to follow.

Why is AI crucial for campaigns beyond search and social?

Search and social have served performance marketing teams well for many years, but their oversaturation and cost have become prohibitive. The open web offers less expensive opportunities, but the thousands of featured display and native ad placements require specific asset dimensions and guidelines. Work that would take humans many hours can be done in minutes or less with AI, which scales and adapts one core concept into every specific asset requirement. This makes multi-channel expansion an option for even very small teams.