How businesses can take advantage of text-to-image AI

Images are the most frequently used form of visual content in marketing campaigns [1], with 32% of marketers spending 2 to 5 hours a week creating visual content [2]. The advent of text-to-image AI tools like Dall-E 2 has made the process even easier, allowing businesses to reap long-lasting benefits in increased conversion, sales, and leads, without over-exerting their marketing teams.

Read on as we evaluate how businesses can leverage text-to-image AI technologies. But first, let’s look at text-to-image generation and how it works.

Text-to-image AI in marketing

Marketing is frequently based on graphic design. However, sometimes it’s difficult to find a relevant stock photo or to organize a photo shoot. In such a situation, AI comes to the rescue with the solution known as text-to-image. How can it improve the lives of marketers?

Text-to-image AI allows you to generate images from scratch based on a text description. Essentially, you only need to input text describing an image you’re thinking of, and the AI will generate a surprisingly accurate picture matching your description.

This technology has been around for years, but recent developments in AI have allowed researchers to develop strong machine-learning models that can use large datasets to create high-quality models.

Typically, text-to-image generation tools like Dall-E 2[3] work by inputting natural language processing (NLP)[4] with text descriptions of an image. The AI tools then use machine-learning algorithms to convert the descriptions into images.

Leveraging text-to-image generators in business

Businesses are rapidly adopting AI-powered text-to-image tools for their ability to create custom assets on the fly. With tools like Dall-E 2, your marketing team can create flashy and attractive visuals to attract customers and show off your products. Here are a few ways in which businesses can leverage text-to-image tools to boost customer engagement and conversion.

Managing creative content

Experts predict that by 2030, 99% of online content will be AI-generated [5]. Organic content remains one of the best long-term strategies for growing your customer base on social media. Creating and posting content organically enables businesses to gain long-lasting benefits in leads, increased traffic, and sales.

On the downside, creating and maintaining your social media presence with visuals takes a lot of work. Businesses need a dedicated team of marketers and content creators working together with other departments to create content that resonates with the company’s customer base.

However, by using AI-powered text-to-image generators, businesses can significantly reduce the human resources needed to create and run an effective social media campaign. Text-to-image generators can also help you create high-quality content quickly and consistently. The result is a more effective campaign and cost-saving benefits.

Read more about AI in Digital Marketing

Creating graphics seamlessly

The popularity of text-to-image generators doesn’t come from their ability to mirror the world accurately but from their ability to create wonderfully styled images. Most companies rely on stock images to boost content engagement. While this strategy may be effective to some degree, it lacks originality, and in most cases, it doesn’t fully convey the message in relation to the brand’s uniqueness.

Text-to-image generators, on the other hand, open up new opportunities for creativity with unique, playful, and well-structured images. This doesn’t mean that technology will replace human designers. On the contrary, AI image generators will pave the way for hybrid roles by incorporating designers’ creativity with AI capabilities.

The result is a seamless graphics creation process that cuts design time by half and creates opportunities for unique images that resonate with the target audience.

Generating social media content

Visual content performs up to 4.4 times better than text-based content in any social media campaign [6]. Text-to-image generators allow marketers to create visually appealing images and graphics in just a few clicks.

Additionally, businesses don’t run the risk of running into any copyright issues since all content is generated by a third party who owns the right to the software and all its processes.

One of the biggest trends in social media marketing today is memes. Memes offer a great way to engage with your customers on social media. Relatable memes help increase brand awareness, which, in turn, boosts engagement and conversion.

Text-to-image generators have numerous advantages over traditional methods of creating memes and other graphics. You can make more complex memes and other graphics with an AI-powered image generator without contracting a professional. And, since the process is automatic, you can create a lot more images than you would manually.

It might be interesting for you: How Artificial Intelligence Is Transforming Influencer Marketing Industry

Issues with using text-to-image AI generators

Despite having the potential to revolutionize image generation in marketing, AI image generator tools face a few drawbacks, especially in the first months of implementation. Here are two of the most common challenges facing the implementation of the technology:

Shallow data pool

Image generator models need vast amounts of image data to turn basic text into an image. Essentially, these models rely on training data to learn how to process requests. Since most companies don’t have their own data sets, they rely on the web – and that’s where the problem lies.

Sourcing training data from the web is quite problematic since some images aren’t always appropriate and require a tighter filtration process to curate relevant, comprehensive data sets.

Bias in output

Image generation tools offer remarkably creative and innovative design opportunities. Unfortunately, these models often replicate prevailing stereotypes and social biases.

For instance, Google recently acknowledged Imagen’s tendency to portray various professions to reflect Western gender stereotypes and an overall bias towards producing images of people with lighter skin tones [7].

The output is, therefore, sexist, racist, and toxic in a way. These unwanted results can be traced back to incomplete data sets that are not comprehensive and representative, resulting in bias. On the bright side, the company is currently trying to resolve the issue.

The bottom line

Text-to-image generation is the future of graphic design, particularly in marketing. By using vast amounts of training data, these models can create unique images for company logos, marketing campaigns, and other purposes.

Companies can then use these models to cut their marketing budget and produce images that resonate better with their target audience. There, however, is the issue of bias in output images resulting from poor training data. But ultimately, AI-powered image-generating models will pave the way for further AI-human collaboration in the workplace, particularly in marketing. See more about AI consulting services.

References

[1] Socialmediaexaminer.com. Social Media Marketing Industry Report. URL: https://www.socialmediaexaminer.com/social-media-marketing-industry-report-2022/. Accessed December 6, 2022
[2] Venngage.com. Visual Content Marketing Statistics. URL: https://venngage.com/blog/visual-content-marketing-statistics/. Accessed December 6, 2022
[3]Openai.com. Dall-E-2. URL: https://openai.com/dall-e-2/. Accessed December 6, 2022
[4] Ibm.com. Natural Language Processing. URL: https://www.ibm.com/cloud/learn/natural-language-processing.  Accessed December 6, 2022
[5] Futurism.com. Internet generation. URL: https://futurism.com/the-byte/ai-internet-generation. Accessed December 6, 2022
[6] Tapsnap.net. 5 Stats Explaining the Importance of Visual Content. URL: https://blog.tapsnap.net/5-stats-explaining-the-importance-of-visual-content-on-social-media. Accessed December 6, 2022
[7] Imagen.research. URL:  https://imagen.research.google. Accessed December 6, 2022