A Content Strategy Conversation — Cruce Saunders
This is part two of the content conversations series. Our guest today is Cruce Saunders.
Founder and principal at [A] and author of Content Engineering for a Multi-Channel World, Cruce brings more than 20 years of experience focused on content delivery technology. His team has delivered more than 300 successful digital, content syndication, and intelligent content engagements. Cruce regularly speaks on multichannel marketing, content engineering, content asset valuation, intelligent content, personalization, chatbots, artificial intelligence (AI), customer experience platforms, and digital maturity. [A] operates in the US, Mexico, and Latin America and serves large corporations, governments, associations, NGOs and other complex institutions.
What delights you the most about the work that you have done so far?
[CS]: As a content engineer, I love the process of uncovering the inherent structure that is built into large content sets, and discovering underutilized value within content assets inside of organizations.
So, I find most delight in structure and value.
On the structure side, for example, we once worked for a large governmental organization involved with aerospace. They were making a number of government assets available for use by private industry, and needed to build a customer experience that exposed all of the numerous physical assets, industrial capabilities, and hard sciences involved in their domain. This engagement involved working closely with content strategy and user experience stakeholders. We focused on engineering content structure, including creating a detailed taxonomy, schemas, standardized vocabulary, and a CMS implementation topology that enabled their in-house developers to implement the resulting content engineering deliverables in it into a Sitecore implementation.
On the value side, I’m continually amazed by the amount of content riches we discover inside of organizations. Most of our clients at [A] are at least 20 years old, but many of them are 40, 50, and even over 100 years old. Many of the smartest people inside of these organizations have been working on the subject matter for decades. Therefore, a lot of the knowledge inside the organization has been codified into a number of unstructured documents, often in the form of PDFs. Sometimes we are able to offer a tremendous amount of value by simply identifying and structuring the content hidden inside of these static blobs, so it may be freed for reuse within different parts of the organization and published to the outside world across multiple channels. Freeing locked-up content feels remarkably good — it allows the knowledge to impact and improve the lives of more people, which advances [A]’s mission of making the world a smarter place.
What is your dream content strategy project that you want to get involved in? It can be for any group or organization, for any goals, anywhere in the world.
[CS]: Our team likes to work on big, hairy interconnected content challenges. The bigger and hairier, the better. We’ve worked with a lot of national organizations that have a number of affiliates and subsidiaries, so in other words, organizational structures that are inherently hub-and-spoke with multiple parent-child relationships.
We would like to work on more federal government, large national association, and publisher content sets. We have not yet worked with a large transnational organization like the United Nations or NATO. I think that would be fun.
What is the most important need or pain point that content strategists have not been able to address as effectively as they would have loved to? It can be for standards, or defining expectations from CS as a discipline, a tool, or for anything else.
[CS]: Possibly the most important tool that a content engineer works with on a daily basis is the content model. Content models are the backbone of any cross-functional, multi-channel publishing initiative. And yet, content models at [A], by and large within the industry as a whole, are expressed as spreadsheets.
Often we translate the spreadsheet into boxes and arrows for the purposes of communicating and collaborating with business stakeholders, but ultimately in order to encapsulate everything they need to hold, the final models need to be translated back into a spreadsheet. This creates a cumbersome back and forth that is currently very manual. Because of the importance of content models, and their impact on everything from user experience, to database design, to CMS configuration, to integration, to content reuse planning, and almost everything else related to large-scale multi-channel initiatives, I believe it will be important for the tools space to evolve significantly from where we are today.
I imagine a content modeling suite that can allow content engineers to work with models in a data or grid view, but then also see them represented as an entity relationship diagram as a dimensional knowledge graph, and to permit arranging content elements within different views or renderings.
Ideally, this modeling suite would further give plug into existing data sources, allowing schemas to be imported from third-party sources and normalize against a company-wide model.
For now, we will continue to work with more pedestrian spreadsheet and prototyping tools. But as a content engineer, it’s hard to imagine the amount of cutting and pasting and rework that we are currently required to do when modeling complex systems will last forever. I’m looking forward to tools innovations in our space.
On one hand, we have AI and automation for predictive intelligence and recommendation engines. At the same time, we talk about human centered design, and a personalized experience. How do you see a balance where you can use your awareness and experience to take certain decisions, while allowing technology to automate certain things?
[CS]: Artificial intelligence and machine learning amplify and extend what human editors and customer experience orchestrators can imagine. So, we see basic personalization happening today with content targeting that is tied to a visitors demonstrated interests by working with the session data in real-time. This form of personalization is fairly easy to accomplish with a base of content that’s been associated with a segment-oriented taxonomy configured in a customer experience management platform.
The next generation shift will see that same content targeting facilitated by predictive analytics and machine learning, wherein what content appears within which interface varies, based on the track record of performance of certain content targeted at audience segments. So, our customer experience platforms will start to design the most efficient and effective customer experiences out of the millions of possible combinations.
However, regardless of how effective our platforms are in testing, targeting, and optimizing, there will always need to be the purposeful human storyteller that weaves the overall customer journey and is at the heart of each customer’s experience.
So, AI will only enhance the effectiveness, reach, and personalization of its stories, but never replace the need for a storyteller.
We talk about future friendly content that should make sense for all known devices and channels. Also, this content should be so planned that the architecture can support even unknown devices and unexpected contexts for the way audience may need it in future (as far as possible). How do you prepare yourself to address this massive challenge?
[CS]: Any organization publishing to more than one channel, beyond the organization’s website, needs to be thinking in terms of a “content as a service” approach. We need to be building towards content APIs.
Of course, building a content API requires structured content, which requires engineering content with model, metadata, microdata, schema, taxonomy, and topology. All disciplines at [A] that we refer to as content engineering.
So, in order to be ready for the future, I would prescribe two main strategic directions:
- Build a content engineering practice, along with all of its disciplines.
- Build everything towards content APIs.
Can you name any companies or brands that you admire for their content strategy? And why do you admire them?
[CS]: Besides Dow Jones, no. Everyone is evolving, and it’s early days for all of us. Dow Jones is further along because they have seen content as a service for many years, and have put resources where their strategy is in the form of their new Data, News and Analytics (DNA) Platform.
We should all be creating these kinds of intelligent content APIs, even for internal use.
If you get a chance to have lunch with a content strategist in your favorite restaurant in the city of your choice, whom will you pick, and why?
[CS]: I’d love to take Joe Gollner out for coffee and a walk on a clear day in Ottawa.
Who are the 3 individuals in CS whom you follow for their talks, writings, or for their social presence? Why them?
[CS]: There are many, many content engineers and strategists I follow, and whose work I admire. It would be impossible to list everyone, especially given that I would not want to accidentally exclude any of the very capable colleagues and partners that [A] works with around the world, however, I would be remiss if I did not mention the person that I consider to be the father of content engineering: Joe Gollner. His seminal thinking on the import and discipline surrounding structured content have very much influenced my own thinking and personal direction.
If you could weave a magic wand to seek one wish, what will you wish as a content strategist?
[CS]: I would wish that every digital team on the planet earth included a content engineer or had all of the disciplines of a content engineering practice represented. Too many digital projects are failing or not reaching their potential audience. Adding a few ingredients changes the whole recipe: model, metadata, microdata, schema, taxonomy, and topology. None of these disciplines are terribly hard. They just require focus and resources. Everyone that publishes anything multichannel needs to build content engineering knowledge and expertise. [A] helps smart organizations get smarter by adopting practices surrounding intelligent content.