Categories
Storytelling

Why your brand may need more than one voice

Conventional wisdom says that brands need to speak with one voice.  I think that advice is incomplete, and can be sometimes counterproductive.

Content strategists often talk about the importance of the voice and tone of content.  The words a writer uses convey more than literal meaning.  Perhaps as you read these words you are wondering who wrote them.  You may be asking yourself who the author is, and whether you should pay attention.

Voice and tone are about the broader meaning of words.  Voice is the implied persona of the author. Tone is “the attitude of the speaker to what he is speaking about,”  said I.A. Richards,  the moral philosopher and literary critic who first developed the concept in 1929.  I like to think about tone as the emotional intelligence the author reveals.

Voice is how you speak in general, and tone is how you talk in specific situations.  Voice is your general attitude, while tone is your attitude in specific circumstances.  For example, someone talks with the detached casualness of a hipster (voice), and reacts with irony to discussions about politics (tone).  The attitude you infer shapes how much you like the author.

There are two aspects to likeability: the extent we self-identify with the category of person we perceive someone as being, and the extent to which we judge their behavior as compatible with our own standards.  Voice addresses the self-identification aspect, while tone addresses the moral judgment aspect.

The concept of literary voice has been co-opted by the commercial world for some time now.  First, companies seeking to shore up their corporate identity adopted the idea of a “brand voice,” which applied to short form content used in advertising.  More recently, companies have started embracing the notion of a “content voice” to cover all their content.  But as the notion of voice has stretched to serve new purposes, its assumptions may need revisiting.

His_Master's_Voice
His Master’s Voice. Image of Nipper from wikipedia

The corporate takeover of voice as a concept has been motivated by a desire to inject personality into organizations.  By having a distinct voice, brands hope to be seen as people, not as faceless corporations.  They reason: “People don’t want to read some corporate blah-blah talk.  We need a distinct voice that differentiates us from everyone else.”

Personifying organizations is tricky. When a prominent American politician argued that “corporations are people,” he was mocked.  People rarely expect corporations to be their personal friends, even if they don’t want the organizations they deal with to be robotic.   Corporations aren’t people, except when people decide to act like corporations, as in the case of celebrities. One can run into trouble buying into the myth that brands are just like your next-door neighbor, or your favorite novelist.  Brands in many respects are more complex than individuals, and equating a brand persona with a human creates confusion.

Consistency advice

One widely offered bit of advice concerns the need for a consistent voice.  Nearly everyone who addresses the topic of brand voice or content voice repeats the recommendation to keep one’s voice consistent.  The recommendation rests on two assumptions: 1. that consumers expect brands to have a consistent voice, else they will be confused, and 2. that brands are more impactful when they use a consistent voice.

The advice for content strategists is well captured by the folks at MailChimp, who have been at the forefront of promoting voice and tone guidelines for content.  “You have the same voice all the time, but your tone changes.”

There is indeed value in having a consistent voice for an audience, but that does not imply brands should have the same voice for everyone.  And while brands should have a unifying purpose, it doesn’t follow brand should have a single voice to express that purpose.

Even when drive by a common purpose, brands can have diverse missions, and as a result, different groups notice and relate to a brand’s purpose in different ways.  Brands should not come across as being one-dimensional by having a voice that’s too narrow.

Individuals have a single, recognizable personality largely because the attitudes we express unconsciously reflect both our personal history and our organic make up.  We have limited capacity to be all things to all people; our attention can’t be spread everywhere.  Even so, people aren’t one-dimensional; we can have many sides to our personality, sometimes even contradictory. Our cohesion comes naturally, without seeming robotic.

Voice and identity

Organizations are artificial entities, and need to be purposeful in how they coordinate their activities and communicate them.  Without coordination, they seem chaotic; with too much coordination, they can appear robotic or artificial.

A voice helps us answer who the speaker is: their intent and their perspective.   A voice is not simply what is signaled, but how it is perceived.  Often, brands spend too much effort worrying about what they are signaling at the expense of considering how it is perceived.  For perception is a matter of individual interpretation.  Perceptions, by definition, will vary.

To date, advice about content voice has largely assumed that people will perceive the voice in the same way.  The assumption is: the more consistent you are in your voice, the more likely people will see you as you want to be seen.  Tone should be dynamic, modulating according to different circumstances, but voice should be the same always.

This preoccupation with consistency of voice can risk freezing out audiences a brand may wish to reach.

Dynamic branding

The proscriptive character of voice guidelines can resemble the corporate identity guidelines used by big brands in the past.  Branding teams became known as “logo police” because of their preoccupation with the sanctity of the logo.  The logo was the symbol of the unity of the corporation, and minor inconsistencies and deviations were thought to harm the brand.

Visual and service branding has since evolved beyond assuming that consistency is the highest priority.  Many corporations are developing “dynamic brands” that morph to adapt to different contexts and audiences.  Even the logos change.  The goal is to present an impression on customers that seems living, not rigid.

Many brands still maintain tight controls and lay down explicit guidance.  But growing numbers of brands rely on implicit guidance based on example rather than rules, and allow a looser and more dynamic interpretation by operating units for how to express the brand.

If voice is meant to reflect the brand, but it’s no longer axiomatic that the brand must be rigidly fixed, then perhaps content voice should be flexible as well.

The limits of fixed voices

Ideally, the goal of a content voice should be for audiences to know who you are, and what you stand for.  Voice tells audiences what they can assume about you based on the way you communicate.

The goal of consistency can result in bland advice.  Voice guidelines may tell writers to sound “smart but not elitist.”  Such guidelines may be sound and be applicable to all audiences, but not provide the patina of personality desired.

The alternative is to develop voice guidelines with a strong personality.  MailChimp is recognized as a well-developed example of a content voice with a strong personality. With its lighthearted voice and cartoon avatar, MailChimp embodies a voice personality the Japanese would describe as kawaii — teeming with cuteness.  It embodies the firm’s culture, informal and friendly.  It’s different from most IT voices; it’s quirky and has its fans.

MailChimp voice and tone guidelines. screenshot from voiceandtone.com
MailChimp voice and tone guidelines. Screenshot from voiceandtone.com

The danger with an approach like MailChimp’s is to offer too much personality.  Sounding different and appearing unique may be a goal of the brand, but is not necessarily a goal of consumers.  Consumers are primarily seeking the actual product, not the content supporting the product.  The benefits of voice differentiation are limited: the more successful a brand is at attracting certain audiences, the more likely it is to alienate other audiences.

MailChimp is apparently successful with how its content is perceived by customers in its target markets.  But no matter how good their service, some potential customers may be put off by their voice, and by Freddie-the-Chimp’s jokes.  Fun and informal doesn’t necessarily convey gravitas, or imply serious standards compliance or fault-free reliability of delivery performance to a dour corporate IT procurement officer.  The tone of their contractual information may be more serious, but the general impression given through their voice overall is one of fun.  As long as their voice is both fixed and iconic, they are defined by what audience segment is willing to self-identify with their voice.

Brands don’t need to act monolithically

Brands don’t necessarily mean the same thing to all people, even when the brand is driven by a common business strategy and purpose.  When brands mean different things to different people, they shouldn’t try to act the same to everyone.

Let’s consider some common situations.  Many organizations have divergent stakeholders who are attracted to a common offering but expect different things from it.  Health organizations deal with patients, doctors, and researchers.  All are interested in health, but in different ways.  Countless businesses sell similar or even identical products to both businesses and consumers.  How the B2B customer uses and evaluates products can be very different from a B2C customer.  Finally, nonprofits focus on an issue or service but have widely different stakeholders.  The concerns of large foundations that are donors will be different from small organizations or individuals that are recipients of grants or services offered by the nonprofit.

When brands serve very different constituencies, they need to talk to them with different voices.  It is not enough to simply change the tone according to different situations.  Different constituencies will need to perceive the brand as reliable according to the values that most matter to them.  The brand’s voice needs to reflect that.

An example of a brand that serves different constituencies with different voices is Oxfam.  The charity has a mission of being a “practical visionary.”  According to Wolff Olins, Oxfam’s branding agency, the charity uses two voices:  simple direct language to talk about practical topics such as emergencies, and a rich language to talk about visions for solving problems.  These different languages correspond to the different constituencies: practical support is sought by people and groups in need, while visions are developed to attract interest by funders and large donors.

When to use one voice, when to use two

A single consistent voice is appropriate in some cases, but not others.  To illustrate, we can divide brands into two types.

The first type of brand is confident they have one audience that all wants the same thing from them.  The brand may offer many products or address many topics, but does so in a consistent way. The brand’s advantage is about its process: how they do things is special, rather than what they address.  Whatever it does or sells, it delivers it in a consistent way, emphasizing some particular brand value such as efficiency, convenience, selection, price, or value.  Walmart, Amazon and Gilt will all have different voices even though all sell a range of products.  But each brand will use a consistent voice regardless of product it is selling.

The second type of brand is more defined by the specialty they address than their process.   What they chose to address is notable, and they are experts about that specialty.  They attract interest from a range of people who have different concerns and levels of understanding.   Each different constituency has particular needs.  They need to be addressed in different ways, according to their interests and level of understanding.  The voice needs to speak to what’s at stake for the constituency.  We can imagine such a brand having two distinct voices.  Perhaps one is a caring voice, aimed at non-specialists who rely on the services of the brand.  These people already are sold on the brand’s expertise: they just want to be assured they can take advantage of it easily.  Another voice might be an expert voice, competent and efficient, aimed at proving to other experts they really are the best at what they do.  Such a constituency of peers might include investors, hiring candidates, business partners, or the trade press.

Conclusions

Voice and tone guidelines are helpful tools — without them content effectiveness is hampered.  But the guidelines need to reflect not only the brand’s goals for how they wish to be seen, but also consider how audiences need to hear things. Voice and tone guidelines for content have evolved from the practice of branding guidelines, and accordingly often have a brand-centric orientation, rather than a truly audience centric one.  There rarely is there much audience input into the development of voice and tone guidelines.

Rather than rush to implement guidelines for staff to follow, brands should first test content with likely users to see how it is perceived, and learn the expectations of users.  I like how MailChimp has done a lot of work with tone to make sure that it adapts to different user situations.  The tone is emotionally intelligent, taking into consideration the user’s likely frame of mind in a given situation.  Other brands should considered user needs for tone the way that MailChimp has.

User needs are important not just for tone, but for voice as well.  Users can’t define your voice, but your voice needs to work for them.  Voice can help brands relate more effectively to their audiences, but it’s important brands don’t come across as  a tribe that some feel excluded from.

— Michael Andrews

Categories
Intelligent Content

Making linked data more author friendly

Linked data — the ability to share and access related information within and between websites — is an emerging technology that’s already showing great promise. Current CMS capabilities are holding back adoption of linked data. Better tools could let content authors harness the power of linked data.

The value of linked data

Linked data is about the relationships between people, items, locations, and dates. Facebook uses linked data in its graph search, which lets Facebook users ask such questions as find “restaurants nearby that my friends like.” Linked data allows authors to join together related items, and encourage more audience interaction with content. Authors can incorporate useful, up-to-date info from other sources within content they create. Digital content that uses linked data lets audiences discover relevant content more easily, showing them the relationship between different items of content.

BBC sports uses linked data to knit together different content assets for audiences.  Screenshot source: BBC Internet blog
BBC sports uses linked data to knit together different content assets for audiences. Screenshot source: BBC Internet blog

An outstanding example of what is possible with linked data is how the BBC covered the 2012 London Olympics. They modeled the relationships between different sports, teams, athletes, and nations, and were able to update news and stats about games across numerous articles that were available through various BBC media. With linked data, the BBC could update information more quickly and provide richer content. Audiences benefited by seeing all relevant information, and being able to drill down into topics that most interested them.

What’s holding back linked data?

Not many authors are familiar with linked data. Linked data has been discussed in technical circles for over a decade (it’s also called the semantic web — another geeky sounding term). Progress has been made to build linked data sets, and many enterprises used linked data to exchange information. But comparatively little progress has been made to popularize linked data with ordinary creators of content. The most ubiquitous application of linked data is Google’s knowledge graph, which previews snippets of information in search results, retrieving marked up information using a linked data format known as RDFa.

There are multiple reasons why linked data hasn’t yet taken off. There are competing implementation standards, and some developers are skeptical about its necessity. Linked data is also unfortunately named, suggesting that it concerns only data-fields, and not narrative content such as found on Wikipedia. This misperception has no doubt held back interest. A cause and symptom of these issues is that linked data is too difficult for ordinary content creators to use. Linked data looks like this:

Example of linked data code in RDF.  screenshot source: LinkedDataTools.com
Example of linked data code in RDF. Screenshot source: LinkedDataTools.com

According to Dave Amerland in Google Semantic Search, the difficulty of authoring content with linked data markup presents a problem for Google. “At the moment …no Content Management System (CMS) allows for semantic markup. It has to be input manually, which means unless you are able to work with the code…you will have to ask your developer to assist.”

It is not just the syntactical peculiarities of linked data that are the problem. Authors face other challenges:

  • knowing what entities there are that have related information
  • defining relationships between items when these have not already been defined

Improving the author experience is key to seeing wider adoption of linked data. In the words of Karen McGrane, the CMS is “the enterprise software that UX forgot.”  The current state of linked data in the CMS is evidence of that.

Approaches to markup

Authors need tools to support two kinds of tasks. First, they need to mark up their content to show what different parts are about, so these can be linked to other content elsewhere that is related. Second, they may want to access other related content that’s elsewhere, and incorporate it within their own content.

For marking up text, there are three basic approaches to automating the process, so that authors don’t have to do mark up manually.

The first approach looks at what terms are included in the content that relate to other items elsewhere. This approach is known as entity recognition. A computer script will scan the text to identify terms that look like “entities”: normally proper nouns, which in English are generally capitalized. One example of this approach is a plug-in for WordPress called WordLift. WordLift flags probable entities for which there is linked data, and the author needs to confirm that the flagged terms have been identified correctly. Once this is done, the terms are marked up and connected to content about the topic. If the program doesn’t identify a term that the author wants marked up, the author can enter it himself.

WordLift plugin identifies linked data entities.  It also allows authors to create new linked data entities.
WordLift plugin identifies linked data entities. It also allows authors to create new linked data entities.

A second approach to linked data markup is using highlighting, which is essentially manually tagging parts of text with a label. Google has promoted this approach through its Data Highlighter, an alternative to coding semantic information (a related Google product, the Structured Data Markup Helper, is similar but a bit more complex). A richer example of semantic highlighting is offered by the Pundit. This program doesn’t markup the source code directly, and is not a CMS tool —it is meant to annotate websites. The Pundit relates the data on different sites to each other using a shared linked data vocabulary. It allows authors to choose very specific text segments or parts of images to tag with linked data. The program is interesting from a UI perspective because it allows users to define linked data relationships using drag and drop, and auto-suggestions.

Pundit lets users highlight parts of content and tag it with linked data relationships (subject-predicate-object)
Pundit lets users highlight parts of content and tag it with linked data relationships (subject-predicate-object)

The third approach involves pre-structuring content before it is created. This approach can work well when authors routinely need to write descriptive content about key facets of a topic or domain. The CMS presents the author with a series of related fields to fill in, which together represent the facets of a topic that audiences are interested in. As Silver Oliver notes, a domain model for a topic can suggest what related content might be desired by audiences. A predefined structure can reveal what content facets are needed, and guide authors to fill in these facets.  Pre-structuring content before it is created builds consistency, and frees the author from having to define the relationships between content facets. Structured modules allow authors to reuse descriptive narratives or multi-line information chunks in different contexts.

Limitations: use of data from outside sources

While authors may get better tools to structure content they create, they still don’t have many options to utilize linked data created by others. It is possible for an author to include a simple RSS-type feed with their content (such as most recent items from a source, or mentioning a topic). But it is difficult for authors to dynamically incorporate related content from outside sources. Even a conceptually straightforward task, such as embedding a Google map of locations mentioned in a post, is hard for authors to do currently.  Authors don’t yet have the ability to mashup their content with content from other sources.

There may be restrictions using external content, either due to copyright, or the terms of service to access the content. However, a significant body of content is available from open sources, such as Wikipedia, geolocation data, and government data. In addition, commercial content is available for license, especially in the areas of health and business. APIs exist for both open source and licensed content.
Authors face three challenges relating to linked data:

  1. how to identify content elements related to their content
  2. how to specify to the system what specific aspects of content they want to use
  3. how to embed this external content

What content can authors use?

Authors need a way to find internal and external content they can use. The CMS should provide them with a list of content available, which will be based on the APIs the CMS is linked to. While I’m not aware of any system that let’s author’s specify external linked data, we can get some ideas of how a CMS might approach the task by looking at examples of user interfaces for data feeds.

The first UI model would be one where authors specify “content extraction” through filtering. Yahoo Pipes uses this approach, where a person can specify the source, and what elements and values they want from that source. Depending on the selection, Yahoo Pipes can be simple or complex. Yahoo Pipes is not set up for linked data specifically, and many of its features are daunting to novices. But using drag and drop functionality to specify content elements could be an appealing model.

Yahoo Pipes interface uses drag and drop to connect elements and filters.  This example is for a data feed for stock prices; it is not a linked data example.
Yahoo Pipes interface uses drag and drop to connect elements and filters. This example is for a data feed for stock prices; it is not a linked data example.

Another Yahoo content extraction project (now open source) called Dapper allows users to view the full original source content, then highlight elements they would like to include in their feed. This approach could also be adapted for authors to specify linked data. Authors could view linked data within its original context, and select elements and attributes they want to use in their own content (these could be identified on the page in the viewer). This approach would use a highlighter to fetch content, rather than to markup one’s own content for the benefit of others.

Finally, the CMS could simplify the range of the linked data available, which would simplify the user interface even more. An experimental project a few years ago called SPARQLZ created a simple query interface for linked data using a “Mad Lib” style. Users could ask “find me job info about _______ in (city) _______. “ The ability to type in free-text, natural language requests is appealing. The information entered still needs to be validated and formally linked to the authoritative vocabulary source. But using a Mad Lib approach might be effective for some authors, and for certain content domains.

Moving forward

According to one view, most of the innovation in content management has happened, now that different CMSs largely offer similar features. I don’t subscribe to that view. As the business value of linked data in content increases, we should expect a renewed focus on intelligent features and the author experience. CMSs will need to support the framing of more complex content relationships. This need presents an opportunity for open source CMS projects in particular, with their distributed development structure, to innovate and develop a new paradigm for content authoring.

—Michael Andrews