Content monetization involves learning new ways to package, distribute and market your digital assets (data, information and knowledge) to generate revenue. In the age of Artificial Intelligence (AI) and Big Data (i.e., Unstructured, Semi-structured, and Structured data) more organizations are looking for ways that their content can be packaged and distributed to take advantage of this new revenue opportunity. However, to take advantage of AI and your Big Data assets you must curate your content to prepare your content to take advantage of AI tools and the increase opportunities for monetization (see AI’s Secret Ingredient – Information Architecture and The Road to AI leads through Information Architecture).
The improvement of data curation tools and methods directly provides greater efficiency of the knowledge discovery process and these tools will help in preparing your content for the varied monetization efforts you will be considering.
AI plays an important part in delivering specific content to your customers and increasing the opportunity to package your content for successful monetization efforts. AI is used to scale the volume and effectiveness of content distribution. AI will enable your organization to:
- Predict trending content areas/topics that your customers need
- Identify which targeted content will resonate with audiences based on real-time engagement and content consumption
- Auto-curate and personalize content based on individual preferences
- Improve content decisions by determining precise distribution schedules, paired with machine learning around what content will resonate best with certain audiences
- Different algorithms and models can be applied to specific content domains and content sources various kinds of media organizations
- AI will make search and its search products more relevant, precise and efficient.
- AI through intents will be able to better know what content your customer needs. Intents will provide a better understanding of what the customer is looking for by better understanding each customer intended use of the content.
In order to derive the maximum benefit from Big Data, organizations must be able to handle the rapid rate of delivery and extraction of huge volumes of data, with varying data types. This can then be integrated with the organization’s enterprise data and analyzed. Your Big Data assets specifically unstructured data, must be organized, labeled, associated in the right way and described (through metadata) so that the benefits of using AI and Big Data for your content monetization can be realized (see Information Architecture and Big Data Analytics).
The following are a few Content Monetization efforts to consider:
- Repackage content for course offerings:
- Capture knowledge of the experts in your organization as a pre-cursor to developing course material to provide the “best-in-class” course offerings both internally and externally
- Create a subscription based service to deliver specialized content to your customers
- Repacking data to be sold to specific markets (i.e., your industry related data, marketing insights, customer trends, pricing, Business Intelligence). This will facilitate providing Data-as-a-Service (DaaS) solutions that will enable your organization to monetize many of its data resources
- Through AI create tools that will extract knowledge from your Big Data resources and repackage this by providing Knowledge-as-a-Service (KaaS) to your customers, suppliers and partners
To provide monetization opportunities for your organization’s content, access to an effective, consistent and reliable source(s) of content is needed. However, some challenges to monetization exist. These challenges include (but not limited to) security and privacy concerns, investing in acquiring new capabilities that often lack sufficient returns, setting up a suitable and scalable data processing architecture as well as creating business processes to support content monetization.