High quality metadata plays an outsized role in improving enterprise search results. But convincing people to consistently apply quality metadata has been an uphill battle for most companies. One solution that has been around for a long time now is to automate metadata's creation, using rules-based content auto-classification products. Back in 2004, I ran a large, greenfield enterprise content management program for a big UK university. I was lucky to work with information management experts in the university library and a member of the W3C metadata group on the project.
Digital business platform provider Magnolia formed a partnership with IBM in 2015 to integrate with its IBM Marketing Cloud. With the integration, Magnolia users could incorporate the email marketing, lead management and mobile engagement solutions the platform provided into their daily workflows. When Armonk, NY-based IBM folded its Marketing Cloud under the broader umbrella of Watson Marketing in March, the capabilities expanded, which meant good news for Magnolia users. By installing the Magnolia Silverpop Module, Magnolia customers with a Watson Marketing account can plug their Magnolia instances into IBM Watson, bringing further capabilities for personalized content delivery based on scoring models derived from visitor behavior. IBM Watson can, "analyze and interpret all of your data, including unstructured text, images, audio and video [with the aim of] providing personalized recommendations by understanding a user's personality, tone and emotion."
Machine learning applications in editing and post-production projects are coming to the fore, and the BBC recently made use of the technology in its first experimental BBC 4 documentary, 'Made by Machine - When AI Met the Archive'. Vast archives of footage, images, marketing materials and post production work can be used for machine learning applications, and in turn drive creative automation. The technology also offers solutions to internal organisational problems. With the cloud and machine learning algorithms, businesses can begin to structure and automate processes for all of their content, saving hours of manual review and data entry. Video intelligence can identify key speech and individual faces.
Artificial intelligence and machine learning have emerged in the marketing industry as a pathway to competitive advantage. The best marketers are identifying, evaluating and testing AI-driven applications to make better sense of their data, create personalized customer experiences and accelerate revenue growth. In fact, 84% of marketing organizations either implemented or expanded AI and machine learning experiments and implementations in 2018. While it's no doubt that artificial intelligence has helped marketing teams improve their productivity, with most brands spending between 25 and 43% of their marketing budget on content, it's important to understand how AI can impact this specific department. The truth is, artificial intelligence has actually had an active presence in the content marketing industry for years.