Evolving the New Content Order—Cruce Saunders on Content Engineering

We’re evolving a new order of content that is different than the one we experienced 10 years ago—humans are no longer the only consumers of content, and the robots using our content are increasingly important brokers of customer experience.

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Radka UhlirovaPublished on Dec 12, 2017

Cruce Saunders, Founder, Principal, and Content Engineer at [A], and author of Content Engineering for a Multi-Channel World, delivered an outstanding presentation on the rapidly changing multichannel, multimodal content landscape at Kentico Roadshow in Chicago. Those in attendance came away inspired to think hard about the future of content.

What is the future order of multichannel content going to look like? And how do we adapt our content repositories as well as business and development processes in order to accommodate the content that needs to be more and do more than ever before?

Content Moves

As Cruce says, “content is everything that a company is, knows, and does.” Content is not just what marketers use to get leads, but also something that customer service teams use to create relationships with customers. It’s the materials that chatbots use to answer questions and introduce clients to what we do.

Content has got a tremendous value and we can’t leave it in one channel and place. In Cruce’s words, the Web as we know it is transforming in front of our eyes—it’s no longer web content alone, it’s an interactive form of that content that needs to exist.”

Because robots are searching our content, they need to understand the content in order to bring the answers back. When we’re engineering our content, we’re engineering it not only for multichannel distribution, customer experiences, and great websites, but also for robot consumption.

As recently reported in Forbes, half of all searches will be voice searches by 2020. And according to Gartner, chatbots will power 85% of all customer service interactions by the year 2020.

Engineering for the New Content Stack

The content landscape has quickly evolved, and now our watches and cars want to talk to us. To be able to manage this new kind of content, we need to bake engineering for the new content stack into our processes.

Let’s take a look at the Published, Interactive and Automated modes of content that are all different ways that our content interacts with the world. As Cruce says, “the CMS is the beating central heart of the new content stack and it’s more than just a place to publish web pages.”

In the past, we used to have just the web presentation layer. But when the robots came along, we needed to give them information about what was in our web presentation layer. Therefore, we need a Content API to push our content from the CMS database and the application layer and get it out to the world.

Published Mode

As chatbots also need to consume our content, we have to unify the content from the Content API to a chatbot platform—rather than having these platforms live in their own silos. Because when they live in their own silos, we’re recreating some of our valued question-and-answer-based content outside of the core CMS.

Interactive Mode

Last but not least, we need an automated marketing system that we can tie together with customer experience information. Signals about how our customers interact with our content are essential for emails campaigns, personalization, and delivering fluid experiences.

Automated Mode

Content is evolving quickly—from static to dynamic, and from one channel to many channels. If we don’t have a content intelligence system, then we have an environment where we author, manage, and publish content across lots and lots of silos.

Moving towards Content Intelligence

For most companies, content is unstructured and siloed at best, and completely inaccessible at worst—we need to move towards content intelligence.

To increase content flow across authoring, managing, and publishing, we need to start asking questions about content structure:

  • How does content transit from CMS to our mobile app, chatbot, and other channels?
  • How does the content model flex to accommodate all the targeting and reuse cases?
  • How do we tie related content together with taxonomy and metadata?
  • How do we structure content for search impact and discoverability?
  • How can we minimize content copy and pasting, but maximize distribution and reuse?

The practice of content engineering will help us get the full context of individual content items and start with a unified content model. With the built-in structure and metadata, we can shape the personalization scenarios as well as the understanding of robots of what content is and why it matters.

With a content intelligence system, we have a new order for content: Model – Authoring – Management – Publishing. Using the model-first approach, we can create great customer experiences.

Building the Master Content Model

Content modeling opens the doors to using content in multiple modes and makes content personalization easier. When you build the master content model first, the authoring schemas will follow the master. Some of the benefits of the master content model include uniting silos, greater efficiency, flexibility, agility, and improved quality. 

The master content model defines how all content assets will be structured throughout the entire content lifecycle.

Each content model is unique, reflects the needs of the organization, and can be quite simple. With Kentico Cloud headless CMS, which has a native content modeling functionality, you can easily build your own content models to suit your needs.

As chatbots are made of entities, responses, and utterances that express users’ intents, you can build all of those things directly into content types in a CMS like Kentico Cloud.

The Power of Structure

According to Cruce, structure supports efficiency, and therefore, we need to move to content engineered with structure, schema, metadata, microdata, and taxonomy. We need to craft our processes around creating intelligent content for ourselves and our clients.

Structure also supports AI, because structured content is the beating heart of cognition. Machine learning applied to content creates impressive impacts that artificial intelligence amplifies through inputs, understanding, and interactions with humans. Machine learning uses many nodes of content to generate smart outputs.

Furthermore, structure supports chatbots. Since we already have a lot of content in our CMS that answers many users’ questions, we need to expose it through structure to unlock the chatbot inside our CMS.

Wrap up

Artificial Intelligence is becoming the new user interface. We’ll talk with a lot of our content, as the content discovery will start with mobile and voice-based, AI-mediated questions.

AI is also becoming the new Information Architecture. Our content will evolve based on interactions with users. The way a user gets around our digital properties will be optimized in real-time by artificial intelligence.

We’ll expect content to be smart, available in multiple forms, and personalized for our needs. Dumb, single-channel content will receive less and less mindshare from anyone or any-bot.

And most importantly, we have to start with a model-first mindset. The model exists independently of technology and is not something that fits inside of one silo. The evolution towards intelligent content depends on orchestrating authoring, management, and publishing with a Master Content Model.

If you want to learn more about the evolving content order, watch a recording of Cruce’s presentation below, or see the slides on SlideShare.

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Cruce Saunders on Evolving the New Content Order
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Written by

Radka Uhlirova