The Top Types of AI-Generated Content in Marketing for 2024 [New Data, Examples & Tips]

The robots are here, and they‘re ready to write your marketing copy. By 2024, AI-generated content will be everywhere, automating and enhancing every stage of the content creation process.

In a recent survey of 1,350+ marketers, we uncovered the top use cases for AI in content marketing today, along with emerging applications that will reshape the industry in the years ahead. Let‘s dive in.

1. Social Media Posts (Used by 58% of AI Marketers)

Social media marketing has reached a breaking point. The average brand now maintains 7.7 different social channels, each requiring a constant stream of fresh, engaging content. No human team can keep up.

That‘s why 58% of marketers using AI leverage it to generate social media content at scale. For example:

  • Mailchimp uses AI to automatically create variations of social ads and posts, then A/B test them to identify top performers.

  • Chase Bank leverages natural language generation (NLG) to create highly personalized social content that speaks to each customer segment.

AI-powered social media tools can assist with:

  • Content Ideation: Analyzing top-performing posts to suggest high-engagement topics, hashtags and creative angles. 35% of marketers rely on AI primarily for content inspiration.

  • Copywriting: Generating the full text of posts, including product descriptions, CTAs and links.

  • Personalization: Dynamically tailoring post creative and copy to individual users based on their demographics, interests and behaviors.

  • Scheduling & Resizing: Identifying optimal send times for each platform and automatically reformatting content for each channel.

Social Media AI Tools & Tips

To get started with AI for social media content, check out tools like Sprout Social, Cortex and Socialbakers. A few best practices to keep in mind:

  1. Focus on AI for content inspiration and optimization vs. fully automated publishing. You still need a human in the loop for quality control and brand voice.

  2. Use AI to personalize and test creative elements at scale, but keep copies short and conversion-focused.

  3. Feed your AI tool a large volume of your top-performing human-created posts so it can learn your winning content patterns.

2. Product Descriptions (50%)

Half of AI marketers now use machine learning to generate and optimize ecommerce product descriptions. This use case is a no-brainer – with catalogs often containing thousands of SKUs, writing unique, compelling copy for each product page is incredibly time-consuming.

AI product description generators and SEO tools can create engaging, keyword-optimized copy at scale:

  • Stitch Fix algorithmically generates personalized descriptions for each recommended clothing item based on the shopper‘s style profile.

  • L‘Oreal uses AI to create localized product copy in 30+ languages, while ensuring consistent brand messaging.

AI-powered product descriptions offer several key benefits:

  • Efficiency: Automating description writing for large catalogs and marketplaces.

  • SEO: Ensuring each product page is uniquely optimized for relevant search terms.

  • Personalization: Tailoring descriptions and value propositions to each shopper segment.

Tips for AI Product Descriptions

To make the most of this use case, I recommend:

  1. Choose an AI tool that connects with your ecommerce platform and can pull in product details automatically, like Eunimart‘s AI Product Description Generator.

  2. Start by using AI to complement human-written descriptions vs. fully replacing them. Have your team focus on top-selling or high-margin products while using AI to fill in the rest.

  3. Feed your AI writing tool a few examples of your best-performing descriptions so it learns your brand voice and style.

3. Email Copy (43%)

Email remains one the most widely used and successful marketing channels, with an average ROI of 36:1. It‘s also one of the most promising applications for AI-generated content.

According to our survey, 43% of marketers using AI leverage it to optimize their email campaigns, from generating subject lines to personalizing full message copy. For example:

  • JetBlue uses NLG to create highly tailored emails at the individual level, resulting in open rates over 2x higher than the industry average.

  • Sephora leverages machine learning to identify high-performing email copy, predict likely clickthroughs and dynamically adjust email content.

Key use cases for AI in email marketing include:

  • Subject Line Optimization: Generating and testing high-converting subject lines informed by past performance data.

  • Copy Generation: Automatically writing email body copy, including personalized product recommendations and dynamic CTAs.

  • Send Time Optimization: Identifying the best send times and cadences for each audience segment based on engagement data.

Email Marketing AI Tools & Tips

Popular AI-powered email tools include Phrasee, Seventh Sense and Ortto.

To get the most out this use case:

  1. Use AI to power ultra-personalized emails triggered by individual user behaviors rather than blasting generic promos to your full list.

  2. Test a wide variety of AI-generated subject lines but let only the strongest ones go to your main list. Subject lines are too high-impact to fully automate.

  3. Visually designate AI-generated copy in your email platform so it‘s not mistaken for human-approved messaging.

4. Images & Graphics (36%)

While AI-generated visual content hasn‘t received as much attention as its text-based counterpart, it‘s one of the fastest-growing use cases in marketing.

36% of marketers using AI rely on it to generate images and designs, particularly for social media ads, blog illustrations, and product shots.

For example:

  • Heinz used Dall-E to generate images for a recent ad campaign featuring ketchup bottles in unusual contexts. The surreal visuals went viral.

  • MidJourney has been used by major brands like Coke and Mcdonalds to generate stylized product shots and ad concepts.

Top benefits of AI image generation:

  • Speed & Cost: Creating on-brand visuals in seconds vs. days and for a fraction of the cost of traditional design or photography.

  • Testing & Personalization: Rapidly generating visual variations for A/B testing and audience-specific personalization.

  • Fueling Creativity: Enabling marketers to quickly visualize ad concepts and content ideas to kickstart brainstorms and inspire designers.

Tips for AI-Generated Visuals

A few key considerations when using AI to generate marketing visuals:

  1. Use AI image tools primarily for initial concepts and inspiration vs. publishing the raw outputs directly. Results still need human refinement.

  2. Provide the AI detailed text instructions, specifying key brand elements like logo, colors, dimensions etc. The more context, the better.

  3. Be mindful of potential usage rights issues, as the legal landscape around AI-generated images is still murky. Confirm ownership before publishing.

5. Blog Content (35%)

Today, 35% of content marketers are using AI to assist with researching, writing and optimizing blog posts. AI‘s biggest value-add is in accelerating the content production process so brands can publish more frequently without sacrificing quality.

For example:

  • Levi‘s used Persado to generate blog title variations, resulting in a 75%+ increase in click-through rates.

  • JPMorgan Chase leverages Contently‘s AI-powered content platform to predict content performance and recommend high-engagement topics for their thought leadership blogs.

Common applications for AI in blog content include:

  • Topic Ideation: Analyzing competitor content, search trends and user data to identify high-performing post topics and angles.

  • SEO Optimization: Incorporating relevant keywords and metadata to improve search rankings.

  • Writing & Editing: Assisting with research, outlines, drafts and editing suggestions to speed up content production.

Tips for Using AI Writing Tools

When leveraging AI to create blog content, I suggest:

  1. Use AI writing primarily for first drafts and research vs. publishing unedited, fully machine-written posts. AI content still requires a human touch.

  2. Build your own knowledge base of top-performing posts for the AI to learn from and imitate, vs. relying solely on public web data.

  3. Fact-check any AI-generated claims or statistics, as language models can sometimes present misinformation as fact.

6. Landing Page Copy & Design (19%)

Creating high-converting landing pages is both an art and a science. While human expertise is still essential, AI is an increasingly valuable tool for optimizing the post-click experience.

19% of marketers we surveyed are using AI to generate and test landing page copy and designs at scale. For example:

  • Epson leveraged Unbounce‘s Smart Copy tool to generate hundreds of landing page copy variants targeted to different search terms, resulting in a 25% lift in conversion rates.

  • Vodafone used AI to dynamically adjust its mobile landing pages based on each visitor‘s device, browser, and other behavioral attributes.

AI-powered landing page optimization typically focuses on:

  • Copy Generation: Writing targeted headlines, subheads, and body copy for different audience segments and campaigns.

  • Design & UX Optimization: Identifying high-converting page layouts, element placements, and design styles based on behavioral data.

  • Dynamic Content: Personalizing page content in real-time based on referral source, user demographics, in-session behavior and other data points.

Landing Page Optimization Tools & Tips

Some popular AI tools for landing pages include Google Optimize, Unbounce, and Instapage.

A few landing page best practices to consider:

  1. Align your landing page copy and design with the specific ad, email or post that‘s driving traffic. AI can help tailor page content to different campaigns.

  2. Use AI to dynamically hide or show form fields based on a lead‘s likelihood to convert. More fields for top-funnel visitors, fewer for those likely to buy.

  3. Don‘t just blindly implement AI recommendations. Use them as a starting point for hypothesis development and further testing.

The Future of Marketing: Human + Machine

By 2024, AI will be deeply embedded into content creation in nearly every marketing department. However, fully automated, hands-off content generation is not the goal, nor will it be feasible anytime soon.

Instead, the future of content is a close collaboration between human creativity and artificial intelligence. AI will increasingly handle the grunt work – research, optimization, testing, production at scale – freeing up marketers to focus on higher-level strategy, storytelling, and brand building.

To stay ahead of the curve, marketers must develop a keen understanding of AI‘s capabilities and limitations in the content space, and learn to wield AI as a tool to enhance, rather than replace, human ingenuity.

By thoughtfully integrating AI into their content workflows today, marketers can build the skills and best practices needed to thrive in an AI-powered future.

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