What is Content Engineering?
Content Engineering helps address content challenges that organizations face. For example, some metadata and taxonomy is in use, but there are no standards – one version is used by marketing and another is used by other divisions. Although some content structure is employed, much of the content is still authored in unstructured “blobs” with MS Word. The content remains “unfindable” for internal use and is not optimized to match customer journeys. Despite their best efforts, teams are not achieving their Search Engine Optimization goals.
This scenario may seem overwhelming, but the solution is not. As described below, Content Engineering puts in place practices for organizing content at time of creation, and optimizing it for a variety of applications. In this article we explore just what Content Engineering is and how it can help you achieve better results with intelligent content.
1. Common issues enterprises face that can be solved with Content Engineering
Most organizations continue to work with content in very siloed ways, with many internal obstacles, inefficient operational processes and organizational structures and outdated technology.
These inefficiencies lead to:
Some of the most common Content related problems that can be resolved though Content Engineering are:
To make this level of personalized, multi-channel delivery and reuse of content possible, operations, people and technology need to be aligned. For these elements to work together efficiently, successful enterprises share a common foundation, Content Engineering.
2. What Is Content Engineering?
Content engineering is the practice of organizing the shape and structure of content by deploying content models, in authoring and publishing processes in a manner that meets the requirements of an organization’s Content Strategy, and its implementation through the use of technology such as CMS, XML, Schema, AI, APIs and others.
Content Engineering consists of several primary disciplines: model, metadata, markup, schema, taxonomy, and graphs.
Model – Content modeling creates a representation of types of content, their elements, attributes, and their interdependent relationships.
Metadata – Metadata is content that provides useful, but generally not visible information about other content. Metadata helps applications, authors, and robots use and relate the content in smart ways.
Markup – Broadly speaking, markup is everything wrapping content that’s not the content itself. Markup describes and presents content and can include XML and content transformations.
Schema – Schema is a form of metadata that provides meaning and relationships to content. Schema often involves published standard vocabularies, such as schema.org, for describing concepts with standardized terms. Schema enables robots to understand and relate ideas.
Taxonomy – A map of related concepts that are applied to content, often as tags. Taxonomy shows content relationships by enabling dynamic collections of content items. It enables and supports features like related content reuse, search, navigation, and personalization.
Graph – Graph architecture and design competencies help to connect various parts of an enterprise content ecosystem and customer data platform. Graphs form node-based relationships between customer states and the modular content needed to deliver fluid, personalized experiences.
3. Benefits of Content Engineering for your organization
Most enterprises can benefit from integrating a Content Engineering practice. Real short and long term operational, commercial and financial benefits range from:
3.1 Content Engineering for Customer Experience Management
Content engineering fuels customer experience management. It enables content to shape itself in discrete, structured formats for adaptive use across desktop, tablet, mobile experiences, voice, and print products. Content must transform for implicit and explicit content personalization.
Multi-Channel content supported across devices, contexts, and platforms requires thoughtful architecture and planning. Customer journeys take place on owned media, but also in search, social, native mobile applications, and syndicated views of the publisher’s content. The content must be properly engineered to facilitate that reach.
Leaders in customer experience management outperform their marketing peers. A content engineering practice is not optional for organizations intending to effectively orchestrate digital customer experiences.
3.2 Content Engineering for Multi-Channel Content
Content assets become more valuable the more they are discovered by humans and used as part of customer journeys. Content engineering is the practice most accountable for an organization’s ability to design multi-channel content that can be elegantly reused in multiple digital properties, applications, and workflows at low cost.
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3.3 Content Engineering for Machine Learning, Artificial Intelligence, and Cognitive Computing
Robots need structured content to effectively provide answers and value to humans. Google, Siri, Cortana, Alexa, Watson, and others function on the basis of understanding relationships between semantic concepts. In order for organizations to develop presence and authority, content engineering must be employed to create meaningful machine-consumable content and interactions between robots and humans.
As intelligent agents become a bigger part of the way organizations understand themselves, their vendors, customers, and the world around them, structured content increasingly becomes an essential pathway to relevance in a cognitive era.
3.4 Content Engineering for SEO (Search Engine Optimization)
Search engines and Google in particular are promoting the use of structured content, Schema.org markup and metadata.
Schema markup, also known as Schema, is a semantic vocabulary of standardized tags that are added to the page’s HTML. These tags help search engines understand the content and context of your webpage and better represent it in search results. Content Engineering facilitates the use of Schema by incorporating it in the Core Content Model®, in the authoring process and by automating the transfer of that metadata from CMS to Google.
Schema provides an important standard for metadata and provides a basis to communicate semantics about unstructured and structured data.
Benefits of Schema markup for SEO (Search Engine Optimization)
What is the value of Schema markup for your business
4. A successful Content Engineering Practice starts with teamwork
Creating and delivering engaging content experiences to customers across multiple channels challenges even the largest organizations. Add on personalization, interaction, and a myriad of device types, and it’s no wonder marketing technologists have trouble keeping up!
Content engineering bridges the gaps between content strategy and development. Working with content strategy, content engineering transforms static content into a form that’s modular, intelligent, structured, and standardized. Sophisticated content that is designed for reuse – multi-channel content – requires thoughtful architecture and planning. It takes engineering and teamwork.
If the team is managed in a way that encourages continuous learning and an open dialog about the team’s constraints and limitations, the content engineer(s) will be the key to identifying what needs your organization has in terms of other content support. They will know if programmers need to automate content processes, they’ll recognize when taxonomy requirements have become so complex they’re in way over their head, and they’ll identify areas where machine learning expertise will provide significant lift.
In this way, content engineering principles are at the center of the organization, but the team may grow to include members from other disciplines. Think about building and growing a content engineering organization as a wheel with spokes. At the center is the content engineer role.
Further Reading:
The Role of the Content Engineer
Based on the requirements defined by the content strategist, a content engineer focuses on defining the technical requirements of content and defining and maintaining the Core Content Model® for the organization.
A Core Content Model® plays a crucial role in implementing Content Engineering and developing modular content for multi-channel reuse.
The Content Services Organization
At the core of customer engagement and customer relationship management is relevant, timely, context-specific content. Creating personalized and relevant content at scale is easier said than done in our constantly evolving digital landscape.
Download this Free Guide which explains how Content Engineering works with Content Strategy and Content Services to ensure consistent messaging and search results.
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Marketing and Technical Publishing Professional seeks new opportunities. Mensa.
2yI found this article very informative. Among other things, content engineering "enables content to shape itself in discrete, structured formats for adaptive use across desktop, tablet, mobile experiences, voice, and print products. Content must transform for implicit and explicit content personalization." 💡