Even though you might not know the term “visual marketing”, you likely have already used it in your business. It is the use of videos, images, and other types of multimedia content in a business’s marketing efforts. Visual marketing is one of the best ways to strengthen a brand and its messaging and communicate effectively with a target audience.
At its core and as a strategy, it helps businesses showcase concepts and subjects that would otherwise be difficult to explain in textual formats. Underlying this type of marketing is the content businesses use. They have to create this content, a process that can be expensive, tedious, and time-consuming.
For this reason, businesses are always looking for tools to help with creating the content they need for their visual content marketing. A crucial tool that has emerged is machine learning.
In this article, we will look at how you can leverage machine learning development services in your visual content marketing efforts.
Using Machine Learning for Image and Video Generation
By now, almost every business with access to an AI model or option has created at least one image for its marketing efforts. Generative Adversarial Networks (GANs) are an excellent tool for this, pitting two neural networks against each other to generate authentic data; in this case, images and videos, from training data.
Businesses are already using this tool to generate images and videos for various uses. The most obvious is media for product visualization. Photoshoots are expensive, especially for smaller businesses that do not have the money to spare. Machine learning and related tools can help them create realistic product images in different settings without expensive photoshoots.
They can also use these tools to generate unique, brand-consistent visuals at scale. Think of creating visual content for social media, then for advertising, then for a website, and so on. Creating everything you need one at a time would take a long time, but a Generative Adversarial Network can do it in seconds.
They can work with cloud service providers to access servers using the latest Nvidia H100 GPU, a GPU that is excellent at machine learning tasks. These GPUs are also content creation powerhouses, and they can create the creatives and variations they need quickly.
Businesses are also using these tools for customized ad creatives. When doing this, they create multiple ad variations tailored towards different audience segments. This also helps them with better targeting, which is one of the best ways to get a better return on their marketing spend.
Visual Content Optimization
Testing and iteration are crucial in getting the most out of marketing campaigns. Marketers use data like click-through rates, time spent, conversions, and so on to gauge the success and return of their marketing campaigns. They might test different visuals and tweak them to ensure the best return.
This is another area where machine learning can help.
Businesses are already collecting the data they need to use with their machine learning solutions. The only thing remaining is feeding it into machine learning algorithms for analysis. Once they do this, they can use the output to optimize their visual content for better marketing efforts and returns.
Marketers can also leverage machine learning in A/B testing. This methodology compares two versions of a web page or other marketing material to determine which performs better. By making small changes to a single element, such as the headline, image, or call to action, marketers can gather data on user behavior and optimize their content for maximum effectiveness.
Instead of doing all this manually, they can leverage machine learning to do it for them. They can then keep the high-performing content while tweaking the rest.
Lastly, businesses can leverage machine learning to analyze videos. They can analyze its quality depending on factors like length, topic, and thumbnail image. As with A/B testing, they can tweak different aspects of the video to ensure it performs best.
With access to video editing servers and machine learning algorithms, making these changes is much easier than it was a few years ago.
Enabling Visual Searches
Anyone who has been using the internet for long enough knows they can search any image and find the same image or similar images online. Businesses are already implementing this on their websites using machine learning.
Now, customers can find similar products at a retailer using an image they found somewhere. Also, they can find inspiration for things like fashion items and home decor based on a single image.
These functionalities can help a business increase sales and become the go-to provider for products in specific segments. This is why so many businesses are implementing such solutions.
Enabling visual searches has also opened up a new world of image-based product recommendations. All shoppers have seen a recommended section on an ecommerce website or received an email with such information.
In the past, doing this was based on user behavior, purchase history, demographics, and similar data. Now, businesses can suggest complementary products based on a user’s shopping cart. Amazon is the perfect example of this, but their API is proprietary. However, companies like Clarifai have developed tools businesses can access and use in similar ways.
Using Machine Learning to Analyze User-generated Content
User-generated content (UGC) has emerged as a strong marketing option in recent years. This is where users post about their favorite products and services on social media. Businesses know that if many social media posts show their products, their marketing campaigns are working and people are buying.
But, how can they know this when the internet is so vast? By using machine learning.
Numerous solutions help with identifying branded products in user-generated content through social media monitoring. Such identification can also help businesses determine which creatives or influencers to work with because social media platforms post metrics about posts such as likes, views, and shares.
Machine learning has so many applications in different industries that many people have never thought about before. Marketers now have access to tools that help them enhance their visual content marketing efforts, ultimately leading to better content, ads, and returns on their marketing investments.
