AI images in marketing: Save costs, increase effectiveness and unlock new creative opportunities
AI images in marketing: Save costs, increase effectiveness and unlock new creative opportunities
Key points
- Opportunities
Generative AI unlocks vast potential in marketing by creating photorealistic images or illustrations without expensive photo shoots or stock images. Reduce reliance on creative agencies, save time in communication, explore new creative possibilities, and gain greater control over brand conformity.
- Challenges
(a.) Image and video generation is currently only mature for a fraction of marketing tasks. (b.) Whether it’s Midjourney, Stable Diffusion, Adobe Firefly, DALL-E, etc., only a few of these AI tools currently provide tangible benefits for professional applications. (c.) Businesses must effectively integrate and ensure long-term scalability of this technology in their processes. - Our Solution
Using a tried-and-tested approach, we identify individual use cases, AI tools, and methods for image and video in marketing tailored to each company. Our practical consulting and assistance combines over 15 years of strategic and operational experience as a marketing agency with tested AI tech from customer projects.
Key Points
- Opportunities
Generative AI unlocks vast potential in marketing by creating photorealistic images or illustrations without expensive photo shoots or stock images. Reduce reliance on creative agencies, save time in communication, explore new creative possibilities, and gain greater control over brand conformity. - Challenges
(a.) Image and video generation is currently only mature for a fraction of marketing tasks. (b.) Whether it’s Midjourney, Stable Diffusion, Adobe Firefly, DALL-E, etc., only a few of these AI tools currently provide tangible benefits for professional applications. (c.) Businesses must effectively integrate and ensure long-term scalability of this technology in their processes.
- Our Solution
Using a tried-and-tested approach, we identify individual use cases, AI tools, and methods for image and video in marketing tailored to each company. Our practical consulting and assistance combines over 15 years of strategic and operational experience as a marketing agency with tested AI tech from customer projects.
Opportunities of AI Image Generation
Generative AI creates images indistinguishable from real photos, unlocking entirely new marketing possibilities for businesses and teams. Below is a selection from our client projects:
Scale Creativity
AI image generation makes the conception and implementation of creative ideas scalable. This opens up nearly limitless new possibilities for customer engagement.
More Control
AI generation enables the creation and adaptation of imagery that adheres to the specifications of Corporate Identity (CI) and Corporate Design (CD), ensuring brand conformity.
Reduce Costs
Previously, creating images required expensive photo shoots, purchasing stock images, or working with creative agencies. Now, you can generate large volumes of images for a fraction of the cost.
Efficient Communication
AI-generated concept designs greatly reduce time-consuming communication loops with external creative agencies or in-house teams.
Challenges of AI image creation
For companies, the rapidly evolving technology landscape quickly leads to wasted time and significant costs, often without yielding better results. Our client projects highlight three major challenges:
This is where we help
With our structured and tested approach, we help companies identify, prioritize, integrate, and scale AI for the right marketing use cases with the most suitable tools aligned with business goals and processes. At FraMar, we combine over 15 years of expertise as a marketing agency with our experience and numerous tests with generative AI for image and video.
Advanced: Train individual Stable Diffusion AI models
For more specific requirements and long-term scalable use, it’s advisable to train custom AI image models specifically on company assets and brand visual language. A trained Stable Diffusion model offers finer control over the generated imagery and facilitates a better alignment with the unique specifications of Corporate Identity and Brand Design.
Current Use Cases of AI-Generated Images
1. Mood and Branding Images
AI generation works particularly well for photorealistic mood, branding, or lifestyle images showing people, landscapes, and backgrounds without a product focus. These images can be used in a variety of ways, especially for websites, social media or newsletters.
More information below.
2. Product Image Creation
AI has the potential to seamlessly integrate products into (generated) backgrounds without relying on expensive product photography. For now it still struggles with more complex and intricate products.
More information below.
3. Creatives
AI enables the (semi-)automated creation and optimization of creatives for ads, organic social media posts, emails, and newsletters. Particularly for scaling A/B testing AI generated creatives show significant potential.
More information below.
4. Model Images - Try On
This AI generation method allows for the creation of images featuring real products naturally worn by AI-generated models. The AI still faces challenges with intricate and overly complex products and often changes them.
More information below
5. Model Modification Images
Model Modification images offer another way to cost-effectively showcase products worn or presented by AI-generated individuals. Key difference to Try Ons being that a real person is needed for the initial image.
More information below.
6. Brand Ambassadors
Paying real people as brand ambassadors is costly, generative AI can create images of models with consistent appearances for use across websites, social media, and brand influencer campaigns.
More information below.
7. Video
Generative AI is already able to create short animated videos from images, working decently well as the basis for advertising videos. However, the technology still has a long way to go as complex or longer animations continue to look unrealistic.
More information below.
Detailed Explanation of AI Image Use Cases
Artificial intelligence offers incredible potential for multiple image use cases in marketing. Depending on the image type, different software delivers the best results. Next to current market leaders like Midjourney, Stable Diffusion, DALL-E, or Adobe Firefly, there’s a multitude of specialized software. Depending on the individual use case each software has advantages and disadvantages.
1. Mood, Branding and Lifestyle Images
AI-generated images showing people, landscapes, and other motifs are a crucial basis for all kinds of visual media. Artificial intelligence impresses with stunning photorealism and beautiful illustrations. From website and symbolic images to visual content for social media and email newsletters, extending to print media, these images convey emotions, product value propositions, as well as company and brand values. Additionally, they serve as base material for creating product visualizations, advertising material, and AI-generated videos.
2. Product Image Creation with AI
Currently, AI is particularly suited for generating photorealistic backgrounds in product images, where the product can be presented naturally or symbolically. The more complex the product, the more likely the AI is to produce „hallucinations“ and alter it. Complex product photography can rarely be completely replaced by AI at this time. However, generated product imagery works well for concept designs during creative development or for better communication of ideas. Additionally, AI already helps in efficiently editing and optimizing product images.
3. Creatives
Although AI still struggles with generating text in images, it can already add significant value by creating base images for ads or social media posts. Particularly when a large number of creatives are needed, artificial intelligence offers substantial cost and time savings. Additionally, AI works well with optimizing the composition of creative elements (text, logos, products, etc.) based on performance criteria. For a fully automated process generative AI makes too many errors which is something we expect to change in the near future.
4. Model Images – Try On
AI-created models wearing products is a use case that’s particularly interesting for fashion and clothing brands, as it allows them to showcase products in various worn poses with greater output control at lower cost. The poses of the generated model often still appear somewhat unrealistic and artificial intelligence still tends to alter the product when it comes to special patterns or intricate details. Future development in 2D to 3D imaging should provide significant improvements, enabling clothing to look more natural when worn by an AI-generated model.
5. Model Modification Images
In contrast to try-on technology, this method allows products to be presented more naturally by individuals. The major advantage here is that all that’s required is a simple snapshot of a real person with the product using a basic smartphone camera. There’s no need for elaborate and expensive camera and lighting setups or a professional photo studio. Based on this photo, artificial intelligence can generate a model wearing or holding the product in the same pose against a customized background. This offers great flexibility in AI-assisted product photography. Even selfies work, and the method shows surprisingly good results with small products, such as earrings or delicate jewelry.
6. Brand Ambassadors and AI Influencers
In addition to creating different individuals, AI can now also generate images of the same or similar-looking people in a variety of scenes and poses. This capability is specifically interesting for corporate influencers a company wants to maintain full control over. Here, generative AI still struggles with significant changes in angle or lighting, often altering the created brand ambassador too much. The same AI model can be generated wearing similar clothing, although the result is often still inconsistent when it comes to detailed patterns. This method shows great potential but also highlights that further refinement is needed.
7. Videos
AI also offers incredible opportunities for generating videos, but it must be clearly stated that the technology for videos is still very much in its early experimental stage. Particularly with longer videos or fast animations, the generated results appear highly unrealistic and are currently not suitable for marketing. As demonstrated by our two examples, AI can already animate short zoom-ins on products or individual elements of an otherwise static image relatively well. Currently, this works well for short videos lasting a maximum of 4-5 seconds. Also, AI is suitable for creating concept shots for planning and discussing campaign ideas with creative agencies or in-house teams. AI can also accelerate certain tasks in video editing already like removing static objects in a moving environment or replacing backgrounds.
Our structured Approach
Our 4-step process provides structure with maximum flexibility for tailored solutions.
Our Services
Individual consultation
- Tailored AI solutions for marketing and advertising by experienced experts.
- Actionable recommendations: Translating AI jargon into clear steb by step measures.
- Successful Growth: To accelerate growth, we systematically deploy the most suitable AI technologies.
Practical Implementation
- Creation of hands-on documentation with examples.
- Visualization of processes for a better understanding.
- Development of Proof of Concepts for pioneering AI development.
- Regular training of team based on practical use cases and visualized examples.
Channel Management
- Operational management of marketing channels.
- Enhanced productivity, effectiveness and scaling through targeted use of AI.
- Combining 15+ years of marketing experience with proven AI expertise.
- Continuous development of AI-supported channel processes.
FraMar x AnalyticaA
We believe that Artificial Intelligence fundamentally changes digital marketing, presenting immense opportunities but also significant challenges. With our four-step approach, combining AnalyticaA’s experience with FraMar’s innovation, we help shape this future.
1. The (End) Customer at the Center
Despite all the innovation in AI, marketing still revolves around the customer as a human being. Due to the heavy technologization, many companies and marketing strategies lose this focus. We continue to put the customer at the center when utilizing AI.
2. Collaboration without Boundaries
We democratize the use of AI for businesses of all types, teams, and professionals. Promoting an active exchange on new AI tech, tools and methods without restrictions as part of a global community.
3. Performance & Creativity
Having to choose between a creative or a performance oriented strategy is outdated. By leveraging AI and our experience in performance marketing, we combine and scale creative work with data-driven, measurable success.
4. Innovation and Expertise
Due to its rapid development, finding AI tools and methods that have a measurable impact has never been as challenging as it is now. We use our marketing expertise and AI experience to identify which software is practical and currently helpful.
Interested in fully utilizing AI’s potential?