November 18, 2020
Content is king. However, some types of content are more royal than others.
That's the case with visual content. And this is nothing strange.
It's one of the most natural characteristics of the human brain. In fact, 90% of the information transmitted to the human brain is visual.
Visuals can help brands connect with customers on a higher, more emotional level.
When organizations produce visual content, they have to handle their assets and processes professionally.
How are resources stored and arranged? How are teams communicating, validating, and updating their work?
Furthermore, success is measured not only by the way an enterprise organizes its digital assets.
It's also crucial to use the visuals in an accurate and optimized way.
They have to be consistent and quality, loading fast regardless of the device and eventually providing a better experience.
This is a challenge that organizations can solve by incorporating a digital asset management (DAM) solution into their processes.
A digital asset management (DAM) system represents a collection of instruments and market practices used to capture, coordinate, optimize, and distribute digital assets.
Initially, DAM systems used to leverage basic metadata from content that was used to create interactive advertisements.
They contained simple information about the files, like name, date, etc.
This means that you had to know some of this information to find the file you were searching for, with no context included.
However, things have evolved. Now, DAM systems can collect presentations, GIFs, vectors, and more file types.
What is even more important, they work with more advanced information, allowing companies to combine content into catalogs, manage it, and distribute it.
More recently, the implementation of artificial intelligence (AI) has resulted in impressive quality and performance improvements and has made DAM a must-have for enterprises looking to increase their digital marketing potential.
As the DAM market is expected to reach $5.66 billion by 2022, the rising demand will also increase the use of technologies that make DAM systems smart.
Modern DAMs enable advertisers to dynamically convert content to any shape, design, or dimension, apart from standardized workflows and simpler processing.
Boosted by AI and machine learning algorithms, DAMs can go beyond basic data and become smart, dynamic, and automated.
AI makes DAMs faster, enabling them to process data in real-time, making media personalized and tailored to specific customer needs.
It also automates many manual processes, saving e-commerce operators a lot of time they can use to focus on essential business decisions instead.
As AI learns from data, it gives DAM systems the ability to scan, validate, and arrange content, which traditional e-commerce platforms are unable to do.
With as little human intervention as possible, Ai algorithms' purpose is to take control of activities that generally require the action of the human brain.
The abilities and the level of autonomy are different for each system that leverages AI.
However, their basic functionality should be to collect and process information.
Moreover, they leverage machine learning algorithms to mimic the human brain's activities, requiring time to learn from data and thus become smarter.
The perfect AI-based system should collect information, understand its context, analyze it, maybe even add a bit of creativity, and bring conclusions based on the processed data.
Here are some of the most popular AI-based technologies that can be incorporated into DAMs to make them more efficient:
Digital content pieces contain tags as keywords that describe their context.
Usually, the number of tags allowed is limitless, allowing you to leverage them as metadata that helps you search and sort your assets.
Traditionally, you have to add tags manually, which takes up a lot of valuable time.
But, not with automatic tagging. AI-powered automatic tagging replaces the exhausting process of manual tagging, recognizing the context of images and adding tags according to their features.
This powerful technology has the ability to reduce catalog processing time by 90%.
The AI algorithms scan the pictures, recognize the objects in them, and then tag the image using relevant keywords.
This is also useful to optimize the delivery of a large number of assets through various distribution channels.
Suggested read: The Complete Guide for Automatic Product Tagging in E-Commerce
AI-based DAM applications use object recognition, image recognition, and face recognition to detect different objects on the images they are scanning.
The AI analyzes the content piece and monitors patterns to recognize artifacts and human characteristics within it.
When combined, these three computer vision elements can help e-commerce managers organize their content more efficiently.
To scan audio, AI technologies use speech recognition based on natural language processing (NLP).
Combined with deep learning neural networks, NLP can recognize words and sounds within the audio file. It can detect patterns in the text and offer a textual description of them.
Thanks to this ability, you can take out searchable text from multimedia files and use it to optimize your search results.
DAM systems powered by AI provide a more in-depth insight into digital content.
They have the power to remove hours of manual tagging, arranging, transferring, and formatting digital content.
What is more, developments like computer vision can make AI-based tools even more efficient, automating even more digital asset management processes.
With AI in their DAM systems, e-commerce operators can benefit from smart features without having any software development knowledge.
AI can help them maximize the value of their visual content, providing seamless user experience.