How AI-Fueled Metadata Is Changing Content Marketing
Metadata has evolved into a crucial asset for marketers that can build a more relevant and stronger connection between a brand and its consumers, and provide much-needed, relatable content that generates real-time conversions and loyalty.
When you consider the wealth of information that consumers possess to indulge in digital purchasing, it becomes clear just how much pressure marketers are under to effectively communicate the right content to their target audience to drive sales. From lead generation to brand awareness, customer satisfaction to conversions, marketing teams are under constant duress to produce better, faster and more relevant results, especially in digital markets already crowded and growing with new offerings.
With marketers spending 38 percent of their budget on developing content and content marketing, it is more imperative than ever to deliver returns on investment. Metadata is helping to bridge that gap.
What is AI-fueled Metadata?
Metadata is simply data that delivers information that describes content. It organizes content via tags and definitions to help marketers (or in the case of SEO) audiences to find relevant material.
One of the earliest forms of metadata can be allegedly traced back to 280 BC, where librarians and historians attached tags to scrolls in the Great Library of Alexandria containing the title, subject and author, enabling users with relevant information without opening the scrolls. In 1994, Adobe began to embed metadata into digital file images. In 2007, Google made a huge break in how metadata was consumed with its search platform that included news, images, and video and changed the face of SEO forever.
The application of artificial intelligence to content analysis has accelerated the production of high-quality metadata that can both classify and improve searchability. Consider a news channel that has access to an almost infinite amount of metadata, and the time and effort that will be invested into sorting through it to produce highlights or news. Through AI, metadata is now accessible, scannable and editable in seconds meaning marketers can package bite-sized content in real-time and can reach audiences on the right platform seamlessly.
AI-Fueled Tagging for SEO
When it comes to SEO, Google has already established just how well metadata can work in securing the most amount of visibility. Today, AI-fueled metadata can be used to discern data such as objects, image and/or facial recognition, emotion, player performance, location, keywords, archival content – such extensive detailing permits marketers and companies to monetize their content be in the form of ad placements, news broadcasts, SEO, and so on.
The Human Connection
AI is only as smart as its user makes it.
AI-fueled Metadata tagging still requires human innovation and expertise to deliver the expected output. The volumes of metadata now available to marketers thanks to AI don’t just create the problem of choice, they add to the issue of processing the right content at its productive best. Bad metadata management that is inaccurate can kill viewers and businesses. A simple example: If the same piece of content is available under different metadata, it can cause confusion. Further, multiple metadata files received from multiple content providers can cause chaos.
Consumers want a rich buying experience without feeling like they have been stalked or that their security and privacy are at stake. Metadata can help zero down on the right balance to ensure that content and data is used according to preferences and master personalization at scale.
Metadata’s future propelled by AI lies in its ability to finetune and deliver the right content for marketers to forecast and subsequently make informed decisions that are all backed by data. With the explosion of video and, in particular, short-form video as one of the most popular mediums of content, it is crucial that marketers understand the asset and deliver results to the right consumers by developing faster and higher precision metadata. Faster data that is produced without manual inaccuracies and errors means shorter turn-around time, fewer resources, better coverage, and ultimately cash flow. It will also help draw lines between usable information and redundant material.
The future of metadata still lies based on the content that is availed. If content is king, then metadata is its successor and AI, its crown.
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