How content is fed and influenced by attribution modeling

The standard configuration of most content generating organizations has authors on one side and marketers on the other. This division of labor facilitates the creation and distribution of content, yet fundamentally both sides serve the same ends: to create compelling content for a particular audience.

Attribution modeling – the process of determining the most effective pathways that deliver desired results – feeds content creation and influences authors in several distinct ways. While ostensibly a marketing diagnostic and analytic process, understanding how content drives valuable operational metrics like conversion, retention and sales leads can help authors and reviewers better tailor content for audiences.

Single-touch attribution
There are several varieties of attribution models that marketers focus on, each with its features and ways to reflect on content. Nevertheless, there are two major categories within attribution modeling—single-touch and multi-touch.

Single-touch attribution refers to when a customer is converted after a single interaction with content. Typically, single-touch attribution models are broken into first-touch or last-touch attribution, referring to what the analyst determines to have been the most meaningful interaction that eventually drove conversion. First-touch emphasizes the importance of the moment the customer enters the marketing funnel, essentially attributing the conversion to this single moment. Last-touch takes on the perspective that the final step in the marketing process was the one that prompted the customer to make the leap.

“The virtue of single-touch attribution is it’s simplicity.”

The virtue of single-touch attribution is its simplicity: It can be implemented with ease and marketers and analysts can point to a singular moment in the marketing process, thereby zeroing in more effectively on these stages in content strategy recommendations. Within single-touch content strategy, it’s easy to emphasize the importance of customer “hooks” that prompt conversion. CTAs, sign-up forms and customer personas all feature heavily into this attribution model and the conversion process is seen as linear, which in turn allows content authors to focus in on these features.

However, one of the pitfalls of single-touch attribution is that, due to its simplicity, there is a significant risk of errors and improper attribution. As Jordan Con of bizible points out, technological limitations – combined with marketing speculation – often lead to conclusions that may not accurately reflect the customer pathway.

“The issue here is that if you are using conversion tracking (e.g. Google Analytics) in a B2B setting, the time between first touch and the conversion can be longer than the common 30- to 90-day expiration on the tracking cookie,” Con wrote. “So often times, this model is really attributing credit to the first touch that’s within the cookie expiration window, and not the true first touch.”

Multi-touch attribution
Recognizing the shortcomings of single-touch attribution models, multi-touch is a more nuanced approach to measuring the efficacy of content. Multi-touch attribution presupposes that there is rarely a single piece of content that drives conversion. Instead, a sustained and multi-step process of encountering content is what will eventually result in conversion. Data from MarketingSherpa suggests that multi-touch attribution models may increase ROI by 22 percent year over year.

The nuance of this approach lends itself to both a variety of different models within the umbrella of multi-touch attribution as well as its likelihood of filtering into a greater content strategy. Rather than presuming that single exposure will be enough to hook a potential customer, multi-touch attribution allows content to be crafted in more subtle ways. Content authors may be better served focusing on branding, thought leadership and the creation of a conversion-encouraging environment instead of leading with a strong CTA or forms.

While neither single-touch or multi-touch models are perfect, they both can inform a content development and management strategy in distinct ways. The close relationship between marketing and authorship means that focusing on determining the most operationally helpful modeling for what is key.

Make a Quantum Shift in Structured Authoring

Eric Kuhnen and Michael Rosinski join Ed Marsh to talk about their presentation at LavaCon, Making a Quantum Shift in Structured Authoring.

According to Eric, one of the key changes in the content industry has become the inability for multiple groups within a department to share content while using a common set of tools. The technical documentation team works with structured content, and the content repository is often not available to those outside the team. Astoria Software now provides integration with Witty Parrot to enable “rich sharing” and ensure that XML-based content is available to non-XML content creators.

Julie Newcome of Ultimate Software, an Astoria Software customer, immediately saw the appeal of the integration:

When we first saw the demo with Witty Parrot, it really excited us. One of the things we have had to overcome is the challenge of sharing content between departments. The benefit for us is that [Astoria with WittyParrot] allows other departments to use vetted content, content that is accurate for a customer-facing audience without having the technical skills to author in DITA, and that’s huge for us.

Ultimate Software is scheduled to go live with their integration of Witty Parrot soon after the LavaCon Conference. You can see a demonstration of their implementation at the Astoria booth; the demonstration includes:

  • Pulling technical content, such as a task or FAQ, from the content repository and sharing it with a customer
  • Generating instructor slides for a training class directly from the source DITA and creating an updated course manual, which is a faster, more efficient, and better managed process

On this Podcast

  • Michael Rosinski: President and CEO of Astoria Software, Inc.
  • Julie Newcome: Content Management Analyst at Ultimate Software.
  • Eric Kuhnen: an expert in product research, development and management.
  • Ed Marsh: Creator and host of the Content Content podcast.


Castaways: Dealing with orphaned content

Even the most robust, expertly maintained content management system will inevitably face the challenge of orphaned content. Regardless of how small or seemingly insignificant the content block may be, when an important piece of your written intellectual property loses its link to its original author, that piece of IP loses its chain of provenance that gave rise to the content in the first place.  The effect is a disrupted chain of linkages, rendering many related content blocks essentially useless and degrading the value of the IP itself.

It takes careful and regular monitoring to avoid orphaned content and the subsequent increase in resources needed to rectify the condition.  Let’s take a look at a few issues surrounding orphaned content, starting with its genesis.

What makes content ‘orphaned’?
Content is orphaned when it loses its link to authorship and, therefore, its link to an authoritative source. This can occur if a CMS user/author account is deleted or updated without the content itself being updated. The content subsequently can become a “problem resource” – disconnected from clear authorship permissions and only able to be updated or deleted by a system administrator.

“You can’t verify the veracity of orphaned content.”

When content is orphaned, it can send ripples through the entire CMS. Every piece of linked content that refers back to data owned by the orphaned content is affected by its change in status, rendering them either broken or unable to be edited since the original author no longer exists in the CMS. This can be a serious problem, particularly if a CMS has significant user turnover or the system purges its authors regularly.


The impact of orphaned content
The challenge that heavily linked orphaned content creates is a considerable one. In addition to the manifold software errors it can prompt, the lack of author roles can undermine the authority of the content. Without author accountability, it becomes impossible to verify the veracity of data underpinning the piece of content – or even whose job it is keep the content updated. Deleting it may only make the matter worse – doing so can further break links in related files and folders.

“As content wranglers accustomed to dealing with orphaned content, we know from firsthand experience that it is unrealistic to rely upon the availability of original authors as the backbone of our quality system,” Robert Norris wrote in The Content Wrangler. “Far too often we’ve been left wondering who is going to fix the problem…and how…and when.”

Repairing orphaned content
To avoid the operational hassle of orphaned content, Norris urges CMS designers to build a mechanism that acts a “self-examination” for a system, combing through content and flagging issues of quality and authorship, and funneling these issues into a repair feed.

“[It] makes sense to assign topical content ownership at the upper-management level to establish accountability with a role that has authority,” Norris said. “Since every resource we publish incurs a burden of maintenance, this principle places that burden on the shoulders of someone with the resources needed to prioritize and execute the task.”

What this means is that orphaned content ideally needs to be repaired rather than purged. As previously stated, regular author turnover means that the task of repairing orphaned content defaults to a system administrator. The best practice, though,  is for the self-examination algorithm to assign ownership to widely accessible dummy account whereby qualified authors can claim ownership and reestablish the chain the provenance.

By taking a tactical, strategic approach and flagging content as problems arise – rather than only discovering a buildup of orphaned content after an audit – CMS managers can ensure their systems are clean and efficient.

How artificial intelligence will help you deliver exceptional customer experiences with content

Artificial intelligence (AI) is at work right now, even if you don’t notice it. While you’re busy creating new marketing campaigns or documenting new products and services, AI systems are busy augmenting your capabilities.

Behind the scenes, AI is working to help you understand the bigger picture by providing an always-on alert system designed to ensure recognition of patterns, trends, threats, and opportunities hidden deep in the data. Content management systems depend on this data to help improve the way content is created, managed, translated, and delivered; that is, the right content to the right people, when, where, and how they need it.

And yet, most content management systems have yet to incorporate AI-powered functionality into their products. But, that’s about to change.

Once you recognize that content is a business asset, you will see the importance of leveraging every ounce of value from each dollar that is spent developing it. But, recognizing a need—and tackling it—are two very different things.

When ready to take action, you’ll likely find yourself in need of a digital transformation; a profound evolution of business activities, (including all things related to producing content) designed to help meet the fast-changing, technology-fueled needs of today, while simultaneously preparing your organization for changes coming tomorrow. AI is certainly going to be part of the mix.

Today, AI is in use in content production departments around the globe. It helps financial service companies automatically generate content that adheres to U.S. government regulations. AI helps news organizations (like the Associated Press) make corporate earnings reports on demand, and at scale, much faster—and more consistently—than its business reporters can. And it helps small businesses compete with much larger competitors by helping them develop capabilities previously limited to Fortune 500 companies.

AI also plays a significant role in content distribution and delivery. Today, with a few commands from the keyboard, intelligent agents can be put to work on your behalf. Intelligent agents can be instructed to generate a website, publish content simultaneously—and at the right time and to the right people—to multiple social media outlets, and provide predictive analytics designed to create relevant content of value to prospects and customers.

As AI matures, expect it to expand into other areas of the content lifecycle. For instance, your content management system can be fed insights generated from predictive analytics that can help guide conversations with customers. AI will serve up content designed to steer your prospects toward relevant content, product, and service offerings.

One of the promises AI will deliver is improvements to content management over time. As machines learn, they adapt and become smarter. AI will enforce the rules set in place to govern the creation, management, translation, and delivery of content. AI-enabled content management systems will identify threats (like incongruent content, bad links, security concerns) and help prevent violations of conventions, rules, regulations, and laws. Properly tuned, AI-augmented content management systems will help spot opportunities to produce new content and assist in determining whether the content created delivers the value expected. Education, business, and government will all benefit from AI-powered content personalization.

The future of artificial intelligence is uncertain in many ways, but one forecast remains clear—all worldwide industries, governments, employees, and retail consumers will be affected.

There exist doomsayers, such as Elon Musk of Tesla, who says he believes that artificial intelligence poses an “existential threat to human civilization”. Some technology leaders are more optimistic, like Facebook’s Mark Zuckerberg, who says artificial intelligence applications will help businesses “build things” that make the world “better.” Zuckerberg says AI promises—over the next 5 to 10 years—to help us develop new operational models.

While I understand the need to be aware of the dangers, I believe harnessing the power of AI cooperatively through partnerships with Fortune 500 companies is our best strategy. An example would be the recent deal announced by AT&T and Oracle that combines AI technology and data analytics to improve AT&T’s field service technician’s workflow—problem discovery, solution efficiency, and overall customer experience. When scheduling an appointment with a telephone installation technician, imagine being given a firm appointment time, rather than a 4-hour appointment time window. This same strategy could be deployed in the content world to build an AI-enabled Component Content Management System with content creation, quality, translation, and distribution interacting in real time.

My advice: Learn everything you can about AI. Seek out opportunities to become involved in projects, both at work and in your free time. In a world in which machine-ready content will play a critical role in your remaining relevant, it’s best to stay ahead of the AI curve.

Michael Rosinski, Astoria Software’s President & CEO, Discusses Augmented Reality: Will It Live Up To The Hype?

There’s a lot of hype about augmented reality (AR) and its impact on content. Lately, it’s getting difficult to avoid. From analyst firms to magazines—and from newspapers to corporate websites and blogs—everyone seems to be writing about how AR will transform the way we live, work, and play.

Virtual reality versus augmented reality

To understand the potential impact that AR may have in the future, it helps to start with a clear understanding of the difference between augmented and virtual reality (VR). AR and VR are related. AR is a distant cousin to VR. The primary difference between the two is rooted in reality.

  • Virtual reality aims to create convincing—yet artificial—computer-generated experiences that feel real. VR experiences are designed to be stimulating, immersive simulations that are made possible with the help of a headset like Facebook’s Oculs Rift.
  • Augmented reality, on the other hand, aims to complement reality by adding a layer of complementary information—something useful or entertaining—on top of reality. It’s live and in real-time. AR makes it possible for us to produce content that can be super-imposed over an image of physical world with the help of a camera-equipped mobile device or specialized headgear. If you’ve watched live television broadcasts of sporting events, chances are you’ve seen AR in action. But, AR’s true value is in the capability it provides users. AR can help consumers make simple repairs to an automobile, learn to cook, and more.

    How Augmented Reality Works

While opportunities to apply AR to business are almost unlimited, opinions about its value vary.

The Future of Computing? Perhaps.

Some exclaim AR is “the future of computing!”. They cite examples of AR’s ability to radically transform education, healthcare, food safety, manufacturing, fashion, retail, and entertainment. A recent report from Forrester says AR’s “immersive digital overlays represent an opportunity to improve customer engagement.”

Gartner predicts that “through 2021, businesses will see a rapid evolution of immersive content and applications that will range from consumer entertainment experiences to optimizing complex work processes.”

Gartner also predicts that by 2020, 10 million consumers will use augmented reality while shopping online. “Immersive technologies such as augmented reality increase user engagement with a product or service by enabling a consumer to fully explore features and conveying additional information that can aid in a buying decision,” Gartner says. “This will drive immersive interfaces, including both augmented and virtual reality, to become the standard customer experience paradigm for scenarios requiring human-to-machine interactions.”

Others are not so easily impressed. The nay-sayers complain that adoption of AR technology is slow; and the bar to entry, too high. Others say what started as a revolutionary technology with amazing promise has been co-opted—and dramatically watered-down—by the tech players like Facebook.

Facebook CEO Mark Zuckerberg, predicts augmented reality will dramatically change the types of content we produce. At its annual F8 developer’s conference in San Jose, CA recently, Zuckerberg laid out his vision for incorporating AR into Facebook. Zuckerberg says he believes the future of augmented reality won’t involve headsets or televisions. Instead, widespread adoption will be driven by smartphones and other mobile devices with cameras.

 Not Everyone Agrees

“The problem is that the acceptable bar for what can, or should, be considered augmented reality is dropping quickly,” reports market researcher, Bob O’Donnell in USA Today. O’Donnell (and others like him) believe the original promise of AR has been diluted and can’t be delivered through a smartphone camera.  (NOTE: see also: Camera Effects Platform)

The question of which technology company will be the big winner in the advancement of augmented reality to a wide audience is not clear yet. Some speculate that Apple (a late entry into the AR space) could easily find itself on top. “If Apple put augmented reality in the iPhone 8’s cameras,” writes Caitlin McGarry in Macworld, “the company would own the full stack: hardware powerful enough to put AR experiences in the palm of your hand without burning through your battery and the software support to entice developers into creating those experiences.”

A Big Market With A Big Opportunity

With support from industry heavyweights like Google, Apple, Microsoft, and Facebook, analysts predict the AR market in the US could reach $50 billion USD (see chart below) in annual sales by 2021. Global growth is expected to reach 90 billion USD annually by the same time. With such a big opportunity for revenue generation, it’s no wonder that nearly every tech brand is looking for a way to grab their share of this promising market.

The question for content producing companies is not should they create AR content, but how will they manage the complex relationships between content assets in a world of layers. Add localization and translation to the mix, and the need for powerful, enterprise-wide content management becomes clear.


Artificial Intelligence and Work: Preparing for the Fourth Industrial Revolution

The Fourth Industrial Revolution

We’re at the beginning of what some analysts call The Fourth Industrial Revolution—sometimes referred to as Industry 4.0—the marriage of advanced manufacturing techniques with artificial intelligence (AI) and the Internet of Things (IoT). The goal is to produce a hyper-efficient, automated, interconnected system capable of communicating, analyzing, and using information to drive progress.

There’s a lot of talk about the impact of Industry 4.0 on jobs and the future of work. It’s a newsworthy topic that has made its way into the daily media cycle, particularly as some investors predict more automation and fewer jobs in the future.

What is AI?

According to the Google dictionary, “Artificial intelligence is the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”

AI is not a discrete technology. It’s a constellation of technologies that mimic behaviors and cognitive abilities associated with humans, such as rationalizing, reasoning, problem-solving and learning. Being able to sense, comprehend, and automatically act upon what is learned—without being explicitly programmed to do so—is what makes AI more powerful than traditional computing technologies.

Some of the most popular AI technologies are:

  • Speech Recognition — transforms human speech to text and other machine-readable formats
  • Natural Language Processing and Text Analytics — makes it possible for computers to understand sentence structure, intent, meaning, and sentiment
  • Machine Learning Systems — algorithms that learn and make predictions based on patterns in data
  • Decision Management — automated decision-making engines
  • Virtual Agents — chat bots and more advanced personal assistants like Amazon’s Alexa and Apple’s Siri

AI is with you already. There’s no escape.

No, robots will not organize a digital insurrection and take over the planet—at least, not any time soon. But, AI will usher in dramatic and significant changes to the way we live, work, and play.

Today, no matter where you look, AI is likely to be making a debut appearance. While previously limited to the fictional world of motion pictures, AI is making its way into almost every product, service, and technology imaginable. In fact, if you’re like many people, AI has been part of your life for a few years now:

And, if you own a smartphone, chances are, you have a helpful personal assistant powered by AI at your beck and call. Perhaps the most widely-known personal assistant, Siri, is now available across much of the Apple product line. Siri’s power increases by connecting it to Apple HomeKit, allowing you to communicate with—and control—connected smarthome devices from afar with your voice.

The impact of AI

AI evangelists often tout the potential benefits AI may have on business, education, and humanity as a whole, but some experts worry that it may also introduce significant negative repercussions if allowed to develop unabated. Just imagine the arms race that might occur with the introduction of autonomous weapons.

Fear of mass destruction—or a hostile robot takeover—aside, currently AI is being employed to solve some of the world’s toughest challenges:

In 2016, Gartner ranked AI as its number one strategic technology (for the second year in a row). Google, IBM, Salesforce, Amazon, and Apple have invested significantly in the development, purchase, and acquisition of AI technologies. And, the AI race is on inside global brands. According to research from Narrative Science, 38% of enterprises today report using AI. By 2018, that number is expected to grow to 62%.

With Fortune 1000 companies embracing AI in a major way, it is no surprise that AI will continue to be a growing influence on the technology front impacting jobs, automation, and productivity—all with touchpoints to the political landscape.

Is a Document Management System a half measure?

While the direction of this blog is forward-looking, it is instructive at times to consider the history of technologies and techniques.  One such is document management, and its predecessor, electronic document imaging, both of which are precursors to modern content management.  This is not to say that document management is dead as a technology or a solution; in fact, in some operational circles document management is very much alive and useful.

The earliest document management systems addressed the problem of paper proliferation.  "Electronic document imaging systems" combined document scanning with database-driven storage, indexing, and retrieval to form libraries of what were once reams of paper files. "Document management" became a solution in its own right as vendors added support for digital file formats generated by word processors, spreadsheets, and other office-productivity products. The descendants of those earlier systems are the document-based enterprise content management systems of today, such as Microsoft SharePoint, OpenText Documentum, and Hyland OnBase.

When is DMS useful?
One question to consider: is a document management system (DMS) relevant in the modern world of digital content management? At its core, a DMS knows nothing about the information within a document; that is, users don't link to content within a document managed in a DMS. Instead, users tag whole documents and link one whole document to another whole document; the DMS simply maintains the inter-document links.  Hence, in the context of digitized content, a DMS is something of a half-measure because each document under management exists as a static element.

"DMS is closer to DAM rather than CMS."

This may be sufficient for some organizations and in some applications. If the document itself is significant – either supplementary to or alongside the data it contains – then a DMS represents what could be a supremely useful permutation of content management. For instance, it's one thing to have a database containing the collected works of William Shakespeare intricately tagged and linked via hypertext. It's an entirely different concern, though, to digitize a specific document written in Shakespeare's own hand.

In a way, a DMS is closer in function to that of a digital asset management system rather than that of a content management system, especially in its ability to protect and preserve the original form of a document. A DMS can also be a very low-cost solution given the dozens of open-source document management solutions available today. Enterprises looking to achieve organization and clarity when dealing with large physical archives of documents may choose from a wide variety of free and fee-based DMS solutions. Using existing hardware and software like cloud computing, scanners and simple image editing and management software, an enterprise can digitize its documents without having to build or acquire a more complicated CMS.

The limits of DMS
However, by leaning on a DMS, enterprises may find themselves running up against the lack of sophistication innate to the software. Since the tagged data is essentially referential to the document itself, it is easy to miss valuable insight contained within the document. Documents cannot easily be interrelated with similar content or data recombined into something new.

Enterprises have found value in linking digital asset management with content management, so it's likely that a DMS working in conjunction with CMS is the ideal solution. If the physical document itself – or at least the visual representation of it – is of value, the ability to tag and separate the data within the document while still preserving it in a static form will lead to a more agile, comprehensive information.

The importance of simplicity in content languages

Everyone agrees: When designing a content or markup language, simple is better. Yet as intuitive as this may seem, the development arc of technology runs counter to this imperative – always evolving in terms of complexity. If we are looking to get more done with content, why do we want a relatively unsophisticated language to assist us?

Building blocks of complexity
First, it helps to understand the rationale for the evolving complexity. As technological capabilities expand – combined with users coming of age with expanded capabilities – innovation naturally pushes the boundaries of current content languages, particularly as we find ourselves needing to express and support more complex and dynamic content. The companies at the fore of innovation have subsequently made developing new programing languages to support expanding infrastructure an imperative. This has led to a boom in different programming languages of varying levels of complexity, particular according to Viral Shah, one of the creators of the programming language Julia

"Lightweight languages have endured for years."

"Big tech companies tend to have their own programming languages — Go at Google, Hack at Facebook, Swift at Apple, Java at Oracle [sic; Sun developed Java for different reasons], C# at Microsoft, or Rust at Mozilla," Shah told VentureBeat. "If you think about it, this makes sense: Software is the core competency of traditional tech companies — they can afford to have their legions of professional programmers use 'hard' languages like C++ and Java, which are great for performance and deployment, but less good for exploration and prototyping."

What Shah is pointing out is one of the key principles that makes lightweight markup languages crucial: While these companies have the capabilities to design their own languages that suit development needs, at the core of each are less sophisticated languages. In this respect Java and C++ are the building blocks supporting increased complexity.

The lasting power of markup
Similarly, when it comes to content – including tagging and metadata – lightweight languages have endured for years alongside more complex, proprietary solutions. Something like Markdown has been a favorite of bloggers, web writers and editors, developers, academics, technical writers and scientists looking for simple ways to translate simple text into HTML and XML, acting essentially as shorthand.

"Years ago, I started coding websites with HTML and then structuring documentation with XML, but Markdown allows me to use plain text for similar purposes," Carlos Evia, Ph.D., director of professional and technical writing and associate professor of technical communication in the Department of English and Center for Human-Computer Interaction at Virginia Tech told The Content Wrangler. "My Markdown files can become HTML and XML deliverables with one or two lines of commands or a few keystrokes."

Lightweight markup languages like Markdown thrive on their simplicity, bringing with them built-in constraints. As such, they area rarely the be-all, end-all for content creators and instead act as a vital component in a more sophisticated authoring tool chain. But this is the key to its staying power: With no end in sight for innovation and development of new languages, being able to author content in a simple language allows that content to be more portable a future iteration. Rather than having to parse artifacts of an outmoded language when transferring in older content, with simpler languages, the content remains relatively "pure" and thus more easily repurposed.

"The constraints of markup languages are one of their virtues."

Constrained, yet free
Mark Baker, writing for Every Page Is Page One, points out that the constraints of markup languages are one of their primary virtues. He points out these constraints essentially translate into a style guide, limiting the possibility for errors or deviations from house style. He also points out that simpler languages can interface with software and algorithms more easily, supporting automation and creating more naturalistic content.

"Every markup language has at least one program to process it and turn it into output (at a minimum, HTML)," Baker writes. "Those programs work because they know the constraints of the language. They know all the structures that are allowed to exist in the content, and all the combinations they are allowed to exist in, and they know how to format each of them."

He goes on to outline how this can extend well beyond formatting into API documentation, allowing for more sophisticated source tracking, combining sources into a single reference entry, error checks and validating the written content to make sure it conforms with the actual function definitions in the code.

Which brings us back to the main point: a relatively unsophisticated language with known constraints leaves authors free to create more compelling and dynamic content.  It is informal proof of the mantra that "simple is better."

Who ‘owns’ content design features?

Content is ever-changing. This is both its greatest virtue and the most significant challenge for designers. In the pursuit of even more intelligent and efficient user interfaces, CMS vendors are tasked with constantly redesigning their software to accommodate innovations in content format and design.

In the pursuit of a CMS that will successfully manage new forms of optimized content, there is one major obstacle that stands in the way of innovation: the provenance of content throughout its lifecycle.  With the rise of cross-platform giants like Amazon and Google, content is now being repurposed, reinterpreted or filtered through any number of proprietary formats, any one of which allows a company to stake an ownership claim. But where is the the line between content that can exist safely and comfortably within an multi-platform ecosystem and content that can be designated "property"?

The changing definition of content
The challenge of defining what counts as "proprietary" content lies in defining content in our modern data economy. If you are a user investigating a certain product on an ecommerce platform like Amazon, you will encounter a product description possibly submitted by the manufacturer or drafted by an author at Amazon itself. It is nearly impossible to trace authorship and ownership of the content since it will have been repurposed many times across a variety of platforms whenever you search for the product. This content may also be repurposed to appear in different formats: Written word turns into spoken audio which can in turn be captured on film. If all this different content is connected to the product and is the same copy, can it truly be considered different – or the same – content?

"Experts suggest that the definition of content should be expanded."

This has led to experts within the content and CMS design community to suggest we move away from the traditional definition of content as "copy produced by a single author," embracing instead a broader definition outside of where it occurs and its format.

"We need to shift our definition of content to be what the user needs right now," says Jared Spool, founder of User Interface Engineering. "It has nothing to do with how it's produced or where it lives on the server. If the user needs it, it's content."

Can you 'own' a need?
In this regard, Spool identifies content as the solution to an operational problem. Creating it comes down to identifying a need and producing something that satiates the need. This, however, becomes complicated once you introduce the idea of commercial platforms producing and managing content to meet the demands of their customers.

"If we want content seen as a business solution to a problem, we need to change expectations around what it is and what it is supposed to do," wrote AHA Media Group's Ahava Leibtag. Leibtag points to the obligations that organizations have, not only to produce and disseminate content, but to protect branding and control what it considers "proprietary."

Companies cannot patent an identified consumer "need", and the infrastructure relating to the pursuit of original content authorship privileges above all else simply doesn't exist in a robust form. Yet what organizations can do is develop proprietary design features. These features essentially act as a lens for content to be viewed: The basic content would exist outside the reach of patent, but the design features that can be woven into the overall platform interface could be copyrighted. Much like the way Microsoft and Apple of a generation ago sought to protect the look-n-feel of their respective products, modern companies can use formatting and user behavior as a mechanism for protect their proprietary interests over data that they did not create.

Most frequently used content creation and editing tools

In the world of content creation and editing, tracking the tools used across the entire industry can be tricky. For example, tools at one enterprise that facilitate collaboration while preserving authorship may be less valuable to another enterprise that needs integrated formatting and the ability to embed rich media.

In its exploration of content creation and management trends in 2016, the Center for Information-Development Management issued a survey to 328 individuals across the entire content creation spectrum. Writers, managers, information architects, content strategists, editors and a small contingent of IT support, customer services and publishers were represented – with the overwhelming majority of respondents representing computer software companies.

The survey sought to answer a few basic questions: What tools do you use to create and manage content? What kind of content do you most frequently develop? How will this content be published in years to come?

Tools of the trade 
As one might imagine, DITA played a significant role in content creation across all respondents. Roughly 74 percent of those surveyed reported using some kind of DITA-capable XML Editor as their primary content creation tool, far exceeding other tools. Following that, 66 percent reportedly used Madcap Flare, 53 percent Unstructured Adobe FrameMaker, 43 percent Adobe InDesign and finally, at 38 percent, Microsoft Word.

Microsoft Word's fall from preeminence for content creators is somewhat predictable. Content experts across the industry have been predicting the end of generic simple document creators, with many saying that basic text-to-HTML conversion tools like Markdown will render Word virtually obsolete among professional content creators.

One of the more fascinating insights in this data is the role native HTML authorship plays in content creation: While few survey respondents (25 percent) claimed an HTML editor as a primary tool, it was overwhelmingly the favorite secondary tool across all categories – coming in at a total of 52 percent. From this, we can extrapolate that content creators:

  • Are shifting away from creating HTML first/only content.
  • Still require HTML editing tools to fully leverage content production and publishing.

Where is content being published?
This seems to follow data insights related to falling use of HTML-based delivery: While still the preferred means of publishing for almost 75 percent of survey respondents, mobile is coming up rapidly – albeit with content creators seemingly confused as to how to fully leverage it.

"We were interested to learn how organizations are approaching publishing to mobile devices, since we advocate designing content differently for mobile devices," the authors of the CIDM survey stated. "Fully 38 percent report that their content is the same on all devices. Some publish more content on mobile devices (only 4 percent); more publishing less content (24 percent)."

The one not mentioned: Localization
This points to the fact that mobile content creation tools are still not being considered separately to traditional content creation. One facet not mentioned in the CIDM survey is localization. Yet this seems to ignore one of the fundamental tenants of the mobile experience: that localized UX is a crucial element for consumer engagement and must be taken into account in the creation of specific content. Tech.Co emphasizes that, for mobile experiences related to e-commerce, localization tools beyond simply translation are key as well.

"If you're doing this, be sure to use widely accepted localization packages or hire an expert to work on the content for you as there will be nuances across languages that even Google Translate doesn't quite get yet," wrote Tech.Co's Joe Liebkind. While mainstream content creators may be focused on issues related to format conversions, the greater topic of authoring content for diverse audiences seems to be underrepresented.