Preparing content for the future of self-service

Structured authoring provides a lot of advantages in terms of positioning your product/software documentation to meet the needs of next-generation end-users. The current market trends are

• End-users do not have time to read the documentation articles, understand the information and then be able to accomplish a task using that documentation
• End-users wish to use any digital device, any time and anywhere to seek the answers they need to accomplish a task
• End-users prefer to ask digital voice-assistant and want accurate answers

Information architecture will play a key role in meeting end-users evolving needs. Artificial Intelligence capabilities are required to scan the vast amount of product documentation using the Natural Language Understanding (NLU) engine. The NLU engine will rely on the rich DITA metadata to understand taxonomy. Ontology will play a huge role in mapping relationships among entities and their semantics. Technical writers will be adding rich metadata to augment the product documentation thus future-proofing their documentation for self-service.

Key takeaways

• The way the end-users are consuming online product/software documentation is shifting as end-users want documentation delivered at any device, anytime and anywhere through the means they prefer
• To scale the support and reduce cost, Artificial Intelligence capabilities are required to provide personalized and contextualized self-service
• Product, services, and documentation should be treated as part of the same system to provide highly personalized self-service
• Technical writers need to enhance their capabilities in Information Architecture to help with taxonomy and ontology by utilizing DITA rich metadata
• Natural Language Understanding (NLU) based chatbot will play a vital role in building knowledge graphs based on product documentation to deliver personalized self-service support