Tag Archives: adaptive content

Landscape of Content Variation

Publishers understandably want to leverage what they’ve already produced when creating new content.  They need to decide how to best manage and deliver new content that’s related to — but different from — existing content. To create different versions of content, they have three options, which I will refer to as the template-based, compositional, and elastic approaches.

To understand how the three approaches differ, it is useful to consider a critical distinction: how content is expressed, as distinct from the details the content addresses.

When creating new content, publishers face a choice of what existing material to use again, and what to change.  Should they change the expression of existing content, or the details of that content?  The answer will depend on whether they are seeking to amplify an existing core message, or to extend the message to cover additional material.  That core message straddles between expression (how something is said) and details (specifics), which is one reason both these aspects, the style and the substance, get lumped together into a generic idea of “content”.  Telling an author to simply “change the content” does not indicate whether to change the connotation or denotation of the content.  They need more clarity on the goal of the change.

Content variation results from the interaction of the two dimensions:

  1. The content expression (the approach of written prose or other manifestations such as video)
  2. The details (facts and concrete information).

Both expression and details can vary.  Publishers can change both the expression and the details of content, or they can focus on just one of the dimensions.

The interplay of content expression and details can explain a broad range of content variation.  Content management professionals commonly explain content variation by referring to a more limited concept: content structure —  the inclusion and arrangement of chunk-size components or sections.  Content structure does influence content variation in many cases, but not in all cases. Expressive variation can result when content is made up of different structural components.  Variation in detail can take place within a common structural component.   But rearranging content structure is not the only, or even necessarily the preferred, way to manage content variation.  Much content lacks formal structure, even though the content follows distinguishable variations that are planned and managed.

The expression of content (for example, the wording used) can be either fixed (static, consistent or definitive) or fluid (changeable or adaptable).  A fixed expression is present when all content sounds alike, even if the particulars of the content are different.  As an example, a “form” email is a fixed expression, where the only variation is whether the email is addressed to Jack or to Jill.  When the expression of content is fluid,  in contrast, the same basic content can exist in many forms.  For example, an anecdote could be expressed as a written short story, as a dramatized video clip, or as a comic book.

Details in content can also be either fixed, or they can vary.  Some details are fixed, such as when all webpages include the same contact details.  Other content is entirely about the variation of the details.  For example, tables often look similar (their expression is fixed), though their details vary considerably.

Diagram showing how both expression and details in content can vary (revised).  NB: elastic content can also fluidly address a diverse range of details, but its unique power comes from its ability to express the same fixed details different ways.

Now let’s look at three approaches for varying content.  Only one relies on leveraging structures within content, while the other two exist without using structure.

Template-based content has a fixed expression.  Think of a form letter, where details are merged into a fixed body of text.  With template-based content, the details vary, and are frequently what’s most significant about the content.   Template-based content resembles a “mad libs” style of writing, where the basic sentence structure is already in place, and only certain blanks get filled in with information.  Much of the automated writing referred to as robo-journalism relies on templates.  The Associated Press will, for example, feed variables into a template to generate thousands of canned sports and financial earnings reports.  Needless to say, the rigid, fixed expression of template-based writing rates low on the creativity scale.  On the other hand, fixed expression is valuable when even subtle changes in wording might cause problems, such as in legal disclaimers.

Compositional content relies on structural components.  It is composed of different components that are fixed, relying on a process known as transclusion.  These components may include informational variables, but most often do not.  The expression of the content will vary according to which components are selected and included in the delivered content.  Compositional content allows some degree of customization, to reflect variations in interests and detail desired.  Content composed from different components can offer both expressive variation and consistency in content to some degree, though there is ultimately a intrinsic tradeoff in those goals.  Generally the biggest limitation of compositional content is that its range of variation is limited.  Compositional variation increases complexity, which tends to prioritize creating consistency in content instead of variation.  Compositional content can’t generate novel variation, since it must rely on existing structures to create new variants.

Elastic content is content that can be expressed in a multitude of ways.  With elastic content, the core informational details stay constant, but how these details are expressed will change. None of the content is fixed, except for the details.  In fact, so much variation in expression is possible that publishers may not notice how they can reuse existing informational details in new contexts.  Elastic content can even morph in form, by changing media.

Authors tend to repeat facts in content they create.  They may want to keep mentioning the performance characteristic of a product, or an award that it has won. Such proof points may appeal to the rational mind, but don’t by themselves stimulate  much interest.  To engage the reader’s imagination, the author creates various stories and narratives that can illustrate or reinforce facts they want to convey.  Each narrative is a different expression, but the core facts stay constant.  Authors rely on this tactic frequently, but sometimes unconsciously.  They don’t track how many separate narratives draw on the same facts. They can’t tell if a story failed to engage audiences because its expression was dull, or because the factual premise accompanying the narrative had become tired, and needs changing.  When authors track these informational details with metadata, they can monitor which stories mention which facts, and are in a better position to understand the relationships between content details and expression.

Machines can generate elastic content as well.   When information details are defined by metadata, machines can use the metadata to express the details in various ways.  Consider content indicating the location of a store or an event.  The same information, captured as a geo-coordinate value in metadata, can be expressed multiple ways.  It can be expressed as a text address, or as a map.  The information can also be augmented, by showing a photo of the location, or with a list of related venues that are close by.  The metadata allows the content to become versatile.

As real time information becomes more important in the workplace, individuals are discovering they want that information in different ways.  Some people want spreadsheet-like tools they can use to process and refine the raw alphanumeric values.  Others want data summarized in graphic dashboards.  And a growing number want the numbers and facts translated into narrative reports that highlight, in sentences, what is significant about the information.  Companies are now offering software that assesses information, contextualizes it, and writes narratives discussing the information.  In contrast to the fill-in-the-blank feeding of values in a template, this content is not fixed.  The content relies on metadata (rather than a blind feed as used in templates); the description changes according to the information involved.  The details of the information influence how the software creates the narrative.   By capturing key information as metadata, publishers have the ability to amplify how they express that information in content.  Readers can get a choice of what medium to access the information.

The next frontier in elastic content will be conversational interfaces, where natural language generation software will use informational details described with metadata, to generate a range of expressive statements on topics.  The success of conversational interfaces will depend on the ability of machines to break free from robotic, canned, template-based speech, and toward more spontaneous and natural sounding language that adapts to the context.

Weighing Options

How can publishers leverage existing content, so they don’t have to start from scratch?  They need to understand what dimensions of their content that might change.  They also need to be realistic about what future needs can be anticipated and planned for.  Sometimes publishers over-estimate how much of their content will stay consistent, because they don’t anticipate the circumstantial need for variation.

Information details that don’t change often, or may be needed in the future, should be characterized with metadata.  In contrast, frequently changing and ephemeral details could be handled by a feed.

Standardized communications lend themselves to templates, while communications that require customization lend themselves to compositional approaches using different structural components.  Any approach that relies on a fixed expression of content can be rendered ineffective when the essence of the communication needs to change.

The most flexible and responsive content, with the greatest creative possibilities, is elastic content that draws on a well- described body of facts.  Publishers will want to consider how they can reuse information and facts to compose new content that will engage audiences.

— Michael Andrews

Adaptive Content: Three Approaches

Adaptive content may be the most exciting, and most fuzzy, concept in content strategy at the moment.  Shapeshifting seems to define the concept: it promises great things — to make content adapt to user needs — but it can be vague on how that’s done. Adaptive content seems elusive because it isn’t a single coherent concept. Three different approaches can be involved with content adaptation, each with distinctive benefits and limitations.

The Phantom of Adaptive Content

The term adaptive content is open to various interpretations. Numerous content professionals are attracted to the possibility of creating content variations that match the needs of individuals, but have different expectations about how that happens and what specifically is accomplished. The topic has been muddled and watered-down by a familiar marketing ploy that emphasizes benefits instead of talking about features. Without knowing the features of the product, we are unclear what precisely the product can do.

People may talk about adaptive content in different ways: for example, as having something to do with mobile devices, or as some form of artificial intelligence. I prefer to consider adaptive content as a spectrum that involves different approaches, each of which delivers different kinds of results.  Broadly speaking, there are three approaches to adaptive content, which vary in terms of how specific and how immediately they can deliver adaptation.

Commentators may emphasize adaptive content as being:

  • Contextualized (where someone is),
  • Personalized (who someone is),
  • Device-specific (what device they are using).

All these factors are important to delivering customized content experiences tailored to the needs of an individual that reflect their circumstances.  Each, however, tends to emphasize a different point in the content delivery pipeline.

Delivery Pipelines

There are three distinct windows where content variants are configured or assembled:

  1. During the production of the content
  2. At the launch of a session delivering the content
  3. After the delivery of the content

Each window provides a different range of adaptation to user needs.   Identifying which window is delivering the adaptation also answers a key question: Who is in charge of the adaption?  Is it the creator of the content, the definer of business rules, or the user themself?  In the first case the content adapts according to a plan.  In the second case the content adapts according to a mix of priorities, determined algorithmically.  In the final case, the content adapts to the user’s changing priorities.

Content variations can occur at different stages
Content variations can occur at different stages

Content Variation Possibilities

Content designers must make decisions what content to include or exclude in different content variations.  Those decisions depend on how confident they are about what variations are needed:

  • Variants planned around known needs, such as different target segments
  • Variants triggered by anticipated needs reflecting situational factors
  • Variants generated by user actions such as queries that can’t be determined in advance

On one end of the spectrum, users expect customized content that reflects who they are based on long-established preferences, such as being a certain type of customer or the owner of an appliance. On the other end of the spectrum, users want content that immediately adapts to their shifting preferences as they interact with the content.

Situational factors may invoke contextual variation according to date or time of day, location, or proximity to a radio transmitter device. Location-based content services are the most common form of contextualized content.  Content variations can be linked to a session, where at the initiation of the session, specific content adapts to who is accessing it, and where they are — physically, or in terms of a time or stage.

Variations differ according to whether they focus on the structure of the content (such as including or excluding sections), or on the details (such as variables that can be modified readily).

Different point of content adaptation
Different forms of variation in content adaptation

Customization, Granularity and Agility

While many discussions of adaptive content consciously avoid talking about how content is adapted, it’s hard to hide from the topic altogether. There is plenty of discussion about approaches to create content variations, however.  On one side are XML-based approaches like DITA that focus on configuring sections of content, while on the other side are JSON-based approaches involving JavaScript that focus on manipulating individual variables in real-time.

Contrary to the wishes of those who want only to talk about the high concepts, the enabling technologies are not mere implementation details. They are fundamental to what can be achieved.

Adaptive content is realized through intelligence. The intelligence that enables content to adapt is distributed in several places:

  • The content structure (indicating how content is expected to be used),
  • Customer profile (the relationship history, providing known needs or preferences)
  • Situational information from current or past sessions (the reliability of which involves varying degrees of confidence).

What approach is used impacts how the content delivery system defines a “chunk” of content — the colloquial name for a content component or variable. This has significant implications for the detail that is presented, and the agility with which content can match specific needs.

Different approaches to delivering content variations are solving different problems.

The two main issues at play in adaptive content are:

  1. How significant is the content variation that is expected?
  2. How much lead time is needed to deliver that variation?

The more significant the variant in content that is required, the longer the lead time needed to provide it.  If we consider adaptive content in terms of scope and speed, this implies narrow adaptation offers fast adaptation, and that broad adaptation entails slow adaptation.  While it makes sense intuitively that global changes aren’t possible instantly, it’s worth understanding why that is in the context of today’s approaches to content variation.

First, consider the case of structural variation in content. Structure involves large chunks of content.  Adaptive content can change the structure of the content, making choices about what chunks of content to display.  This type of adaptation involves the configuration of content.  Let’s refer to large chunks of content as sections.  Configuration involves selecting sections to include in different scenarios, and which variant of a section to use.  Sections may have dependencies: if including  one section, related detailed sections will be included as well.  Sectional content can entail a lot of nesting.

Structural variation is often used to provide customized content to known segments.  XML is often used to describe the structure of content involving complex variations.  XML is quite capable when describing content sections, but it is hard to manipulate, due to the deeply nested structure involved.  XSLT is used to transform the structure into variations, but it is slow as molasses.  Many developers are impatient with XSLT, and few users would tolerate the latency involved with getting an adaptation on demand.  Structural adaptation tends to be used for planned variations that have a long lead time.

Next, consider the assembly of content when it is requested by the user — on the loading of a web page. This stage offers a different range of adaptive possibilities linked to the context associated with the session.    Session-based content adaptation can be based on IP, browser or cookie information.  Some of the variation may be global (language or region displayed) while other variations involve swapping out the content for a section (returning visitors see this message).    Some pseudo personalization is possible within content sections by providing targeted messages within larger chunks of static content.

Finally, adaptive content can happen in real-time.  The lead time has shrunk to zero, and the range of adaptation is more limited as well.  The motivation is to have content continuously refresh to reflect the desires of users.  Adaptation is fast, but narrow. Instead of changing the structure of content, real-time adaptation changes variables while keeping the structure fixed.

It is easier to swap out small chunks of text such as variables or finely structured data in real-time than it is to do quick iterative adaptations of large chunks such as sections.  JSON and Javascript are designed to manipulate discrete, easily identified objects quickly.  Large chunks of content may not parse easily in JavaScript, and can seem to jump around on the screen. Single page applications can avoid page refreshes because the content structure is stable: only the details change. They deliver a changing “payload” to a defined content region.  Data tables change easily in real time.  Single page applications can swap out elements that can be easily and quickly identified — without extensive computation.


Content adaptation can be a three stage process, involving different sets of technologies, and different levels of content.

The longer the lead time, the more elaborate the customization possible. When discussing adaptive content, it’s important to distinguish adaptation in terms of scope, and immediacy.

A longer-term challenge will be how to integrate different approaches to provide the customization and flexibility users seek in content.

— Michael Andrews

When is Adaptive Content Appropriate?

Publishers want their content to be appropriate for their audiences.  They need to know when it is appropriate to adapt their content to specific situations.

Until recently, publishers presumed audiences would adapt to their content.  They supplied the same content to everyone, and people were expected to find what interested them in that content.  In some circumstances, they created different versions of the same content targeted for different segments of readers, perhaps people in different countries.  But audiences still needed to find what was relevant to them in that version.

What happens if we reverse the equation, so that the content adapts to the individual, rather than the individual adapting to the content? On an intuitive level it sounds great, but how is it done in practice?  Does it now mean everyone is not getting the same content?

Discussion of adaptive content has increased noticeably in the past year. The motivation behind adaptive content is to give people precisely what they want, when they want it, how they want it. Marketers imagine if their brand that can satisfy the egocentric needs of their customers, they will cement their relationship with them.

Now a buzzy topic: Sample headlines of recent posts about adaptive content.
Now a buzzy topic: Sample headlines of recent posts about adaptive content.

Adaptive content is attractive as an ideal.  But much recent discussion of the approach is short on specifics.  Karen McGrane, who introduced the concept several years ago to the wider content strategy community, recently wrote: “I am really, really annoyed with hearing adaptive solutions presented as some kind of magical panacea.”  We need less discussion about adaptive content as an abstract concept, and more focus on how it is implemented.  The critical question is not, “Why adaptive content?” but “How?”  Until we understand more of the how, its value can’t be judged.

What Adaptive Content Means

Adaptive content is difficult to define precisely.  It has various properties, a number of which are also associated with other content concepts, such as personalization, dynamic content, and intelligent content. Those who discuss adaptive content may emphasize different aspects of it.  Perhaps the biggest difference is between those who emphasize the production side of adaptive content (What do producers need to do to deliver content adaptively?) and those who talk about the consumption side (Why do consumers care and what do they notice that’s different?)

Adaptive content is a topic of growing interest in large part due to the smartphone.  The significance of the smartphone goes beyond the difference between a smaller touchscreen and a larger screen with a keyboard.  Smartphones are used in diverse situations and offer many capabilities.  They have cameras, microphones, GPS, a unique ID tied to an individual, and sensors such as gyroscopes.  These features can capture different information to support interaction with content and influence what content is provided to the user.  They’ve changed our assumptions about when and where users might need information.  We can no longer assume users will be making a simple explicit request, and getting content matching that request.

The adjective adaptive implies the user can somehow direct the content.  An adaptive approach involves various possibilities.  It’s an approach in the early stage of its adoption.  Its benefits and limitations at this point aren’t yet well understood.

I’ll pass here on trying to define precisely what adaptive content is.  Others such as Karen McGrane, Joe Goliner and Noz Urbina have valuable things to say on this topic.  I want to focus on what is genuinely useful in the approach. Understanding in more detail what adaptive content could represent helps us assess both its application, and the effort involved.

For me, the core idea of adaptive content is that content variations are available to provide a better, more relevant experience for users.  The key phrases are content variations (production side) and experiences (consumption side).

Many discussions of adaptive content look at the numerous variables relating to people, devices, locations, and so forth.  The number of permutations can seem enormous, and would imply a need for omniscient engineering.

It may be more valuable to focus on variations, which links the content to scenarios of use, and to whom is responsible for it.

Two key questions of adaptive content are:

  1. How much variation is necessary?
  2. How much variation is possible?

The first question speaks to what audiences need, and the second to what businesses can realistically do to meet those needs.

One point needs clarifying.  Adaptive content is not about mind-reading.  There is a big push in the world of big data around predictive analytics.  While predictive analytics might occasionally play a role in determining what content variation to show, it generally will not.  In most cases the intent and needs of the individual user will be clear, and conjecture isn’t necessary.

Examples of Adaptive Content

The best way to illustrate content variation is through examples, looking at use cases where individuals receive different variations of content depending on their situation.  These examples may not be relevant to all organizations, but they offer alternative perspectives on the value of content adaption.  We might even consider these as adaptive archetypes.

One popular archetype is context aware content.  The best known example is the card UI provided by Google.  A Google card might combine information relating to time, location, and the user’s calendar with status information from elsewhere.  The context is often event-focused.  Different people receive different variations of structured information.  People know the structure of the information they will receive, but not the precise information they will be getting.

A related archetype is situationally aware content.  Here, the context is not predefined, but is fluid. The situation is defined by preferences set by the user relating to variables in their environment.  Wearable devices may offer situationally aware content.  You may be a work and can’t watch a football match, but perhaps your wrist will buzz when your team scores a goal.  The focus is less on the structure of the information, and more on what specific content to receive, and how to receive it.  In the future, wearables may have sensors that trigger health advice, possibly on a different platform.  So we have a possibility of trans-device content.

Another kind of adaptive content is omnichannel content, a favorite of the retail sector.  Macy’s, the U.S. department store chain, needs to adapt content to various shopping scenarios.  Some people will go to the store to browse, but others want to know what’s available before going to the store.  A shopper may be looking for a sweater that’s been advertised in a specific color and size, and wants to know if it is in stock at her local store.  The content needs to display the stock availability of the item according to location.  There will be countless variations of content about the sweater depending on the size, color and store location.

A different sort of adaptive content is possible in e-learning.  Pearson, a large educational publisher, provides students with materials that adapt to their understanding of subject matter.  It compares what learning outcomes they need to achieve for different proficiencies with the student’s mastery of these topics, and provides an individualized learning path based on their knowledge of concepts.  Each student will see a different sequence of content, and different students may see different content items.  This is an example of outcome driven content variation based on inference.

In some of these examples, users imagine they are getting unique content.  But we are discussing content for an audience of many people, not personal information such as your fitness tracker information.  Individuals may just be seeing a variation tailored to them, and others matching their circumstances will see similar variations.

Back to the Future: Adaptive Content’s Origins

Adaptive content may seem like a new approach, but much of the thinking around it has been years in the making. The W3C defined core aspects of adaptive content over ten years ago, in 2004.  The proliferation of internet-connected devices with different characteristics and purposes has been evident for a long while, and with that, questions about how to provide content to increasingly diverse users.

The W3C uses the phrase “content adaptation” rather than “adaptive content,” but the two terms refer to the same general topic.  Here’s the W3C definition:

“Content Adaptation is a process that based on factors such as the capabilities of the displaying device or network, or the user’s preferences, adapts the content that has been requested to provide an optimized user experience. This adaptation can occur in a number of places in the content delivery chain: the author may make choices when writing the content, or intermediary automated content transformation proxies could adapt the content based on heuristics and knowledge of the user, or the adaptation could occur within the browser itself.”

This definition is slightly different from how adaptive content is commonly discussed.  Yet it highlights some important issues.   First, there are technical considerations (hardware and network) but also human considerations (preferences).  The goal is to deliver a good user experience, not conversions or network optimization. And there are multiple ways to accomplish this: through content planning, technical transformation of content based according to specific user needs, and using browser technology.

Delivery Context

Over a decade ago a W3C working group documented issues relating to device independent-content: How to provide different versions of the same core content, irrespective of platform.  They looked at the relationship between what is created and what is presented, and also the different dimensions of how content is received and manipulated by users.  A major focus is what they call the delivery context.

Schematic of W3C terms relating to device independence and content adaptation.
Schematic of W3C terms relating to device independence and content adaptation.

The W3C working group believed that users will often need to interact with units of content that are different from the units created by authors.  Authors may create larger content units that are broken down when presented to users (the perceivable unit).   The decomposition approach contrasts with the infinite scrolling people commonly experience these days, regardless of device.  The notion of decomposition also contrasts with some newer ideas of writing small atomic units of content, although the W3C also considered the possibility of aggregating units of content.

The most significant idea was the possibility of variations in content created.  Users weren’t just seeing different presentational views of a single version of content, they were seeing different variants.

The W3C considered how the delivery context shapes the user’s focus of attention: what users notice, and how they need to interact.  They noted interaction might not only be visual, but also gestural or based on speech.  They considered adaptation preferences — how the user indicates they want to experience the content, such as alert preferences.  And they reviewed the impacts of application personalization — things likes settings for video playback, or whether sound or location tracking is on. These variables are already important considerations for content on smartphones.

The delivery context is often overlooked. Some recent adaptive content discussions have focused on predicting implicit user desires and delivering variations based on those predictions. But the other, less explored aspect of adaptive content is making sure users can get content that matches their explicit preferences — especially when they don’t want to use a feature. Many applications assume users will use certain features: to take a selfie, use beacons, talk to a virtual assistant, or something else that designers think would be fun.  A growing number of applications assume people will use their smartphones to do things, including producing content such as bar code IDs or  social media check-ins, for use by the brand.  Except it might not be fun for everyone.   Content needs to adapt to when people opt-out of such experiences.

Adaptive Content Delivery

Before the rise of today’s popular techniques like AJAX, responsive web design and APIs, the W3C identified different techniques that can enable content adaptation. They identified different processes to support content adaption, and listed various client and server side processors to deliver the content. While the specific recommendation details are dated, the range of approaches remains interesting because they are not limited by current conceptions about how content is delivered.

Adaption Processes refer to how to change the content itself.  Examples the working group identified included:

  • Select/Remove
    • Selection via URL redirect
    • In-document Decision Tags (conditional or switch selection)
    • Layout decisions
    • Style conditions
    • Relevancy
  • Navigation
  • Adaptation via Substitution
  • Adaptation via Transformation

Many of these techniques involved markup and other instructions embedded in the content.  A tremendous amount of variation is possible using these techniques in combination.

Adaptation Processors, in the W3C working group’s terminology, refer to the technical means for enabling content adaptation — from the server side, client side, or some combination.  The working group identified:

  • Server-side Adaptation
    • Variant Selection
    • Structural Transformation
    • Media Adaptation
    • Using Meta-information
    • Decomposition
  • Client-side Adaptation
    • Image Resizing
    • Font Substitution
    • Transcoding
    • Contextual Selection

While most of the client-side adaptation techniques focused on alternative renderings of content, the server side techniques focused more on generating substantive variations in the content.  For example, one possibility mentioned for structural transformation is providing auto-summarization of content.

Today’s web environment places a strong emphasis on the client side. Responsive web design provides many of the client-side capabilities identified by the working group.  The extensive use of JavaScript libraries emphasizes user-screen interaction.  Conditional loading helps to manage when content appears on screen.

Much of the substantive variation in content needs to come from the server side.  Server-side data repositories are becoming more flexible delivering mixed types of content from different sources.  The lagginess of server-provided content should improve with true 4G network speeds.  The other major server-side factor, which was not mentioned at all by the working group, is the use of analytics data to shape the content adaptation. Using data to guide the display of content has been a significant transformation in the past five years.  Tracking user behavior over time can provide useful information for providing the right content variant, as the Pearson example shows.

The tools available to adapt content vary in what they accomplish and the effort they entail.  Server side approaches will generally be more complex to do, though they can potentially offer the most value if they provide content that would otherwise be unavailable or not accessed.   We can see this with Macy’s approach.  Having specific inventory information could be a decisive factor for a person making a purchase.  It is an example where the content variation is both high value to the user, and high value to the brand.

Design Parameters for Adaptive Content

What should publishers focus on, given that there are many approaches to adapting content?  Adaptive content can be challenging to implement, given the many factors that influence its success.

The success of adaptive content depends on the alignment of three factors:

  • The profile of the individual user
  • The opportunity that a variation offers the user and the brand
  • The constraints on the ability to execute the variation in a manner that offers value to both parties

The individual user profile is a mix of their current and past behavior (typically clicks, perhaps purchases), together with any preferences they have provided (opt-ins, default settings, etc.)   Brands with loyalty programs may have a range of indicators about a user.  A person who is a frequent patron of a hotel would expect content more adapted to their needs than someone who doesn’t use the hotel often.  This suggests that the opportunity to implement adaptive content is strongest in cases where a relationship already exists.  Adaptive content may be more effective at keeping a customer than it is at creating one.

The opportunities for content variations will often relate to timing and location: when and where users most need specific content.  It may be based on the need variations of different segments. Location and segmentation could even be related in the case of regional segments.

Constraints can be technical or human:

  • Technical constraints: device capabilities, network connection, ability to offer desired content
  • Human constraints: motivation to engage, attention and distraction

Sometimes constraints interact.  Many retailers show an option to pick up merchandise at the nearest store, but not everyone lives near a store.  That information, while useful to those near stores, may seem punishing to those far away.  Ideally, the adaptation needs to account for the possibility that not everyone can take advantage of the variant content, so that the content can “gracefully degrade” to a state where the variant is not in the foreground.

A critical implementation dimension involves timing: how anticipatory the adaptation is.  Some adaptations are real-time, responding to uncertain user interactions.  Other are event-triggered, where the event is already known and being monitored. Still others involve scripts based on knowable interaction pathways.  Here adaptive content overlaps with dynamic content (user-initiated requests) and some forms of personalization (remembering information across sessions.)

Content adapts to what is known within different time horizons:

  • Path-based adaptation, which serves different variations according either to prior actions from past sessions, or the immediate preceding actions of the current session
  • Forecast-based adaptation, which serves variations based on known variables such as calendar information or stages of a lifecycle
  • Real-time adaptation, which provides variations based on matching current behaviors with user profiles or task outcome goals.

Real-time adaptation is a data and algorithmically intensive approach.   It requires fast decisions using multiple variables, some of which may lack data.  The more inputs into the decision, and the more outputs of the decision (different content variations), the more challenging it is. A widely encountered example of real time adaptation are ad exchanges, where display ads are shown according to user profile characteristics and advertiser bids.  An impressive amount of computing power is marshaled to deliver display ads, a cost justified by the big stakes involved.

When is adaptation appropriate?

If done properly adaptive content can benefit audiences.  So should brands implement adaptive content?   The answer depends on many factors.   Brands need to evaluate how important content variants are to the audience, and to the brand.  Brands need to understand how much complexity is involved: the inputs needed to decide on the variant, and the number of variants needed to deliver the expected experience.

Adaptive content will often have the strongest business case when supporting transactions, such as sales.  The stronger the business rationale, the larger the potential investment and sophistication.

Adaptive content encompasses a range of approaches.  Not all require state-of-the-art back-end systems.  Some implementations may be small enhancements that improve the experience of using content without involving complex implementations.

What’s appropriate depends on user needs analysis, an assessment of available technical capabilities, and a development of a business case.

— Michael Andrews