Information Architecture Assignment

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CHAPTER 7

Labeling Systems

Now the LORD God had formed out of the ground all the wild animals and all the birds in the sky. He brought them

to the man to see what he would name them; and whatever the man called each living creature, that was its name.

—Genesis 2:19

In this chapter, we’ll cover:

• What labeling is and why it’s important • Common types of labels • Guidelines for developing labels • Sources of inspiration for your labeling system

Labeling is a form of representation. Just as we use spoken words to represent concepts and thoughts, we use labels to represent larger chunks of information in our information environments. For exam‐ ple, “Contact Us” is a label that represents a chunk of content, often including a contact name, an address, and telephone, fax, and email information. You cannot present all this information quickly and effectively on an already crowded web page without overwhelming impatient people who might not actually need that information. Instead, a label like “Contact Us” works as a shortcut that triggers the right association in someone’s mind without presenting all that stuff prominently. The person can then decide whether to click through or read on to get more contact information. So, the goal of a label is to communicate information efficiently—that is, to convey

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Rosenfeld, Louis, et al. Information Architecture : For the Web and Beyond, O'Reilly Media, Incorporated, 2015. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/unt/detail.action?docID=4333758. Created from unt on 2023-02-19 06:00:35.

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meaning without taking up too much of a page’s physical space or the user’s cognitive space.

Unlike the weather, hardly anyone ever talks about labeling (aside from a few deranged librarians, linguists, journalists, and informa‐ tion architects), but everyone can do something about it. In fact, we are doing something about it, albeit unconsciously: anyone develop‐ ing content or an architecture for a website or app is creating labels without even realizing it. And our label creation goes far beyond our information products; ever since Adam named the animals, labeling has been one of the things that make us human. Spoken language is essentially a labeling system for concepts and things. Perhaps because we constantly label, we take the act of labeling for granted. That’s why labeling can often be confusing, and users suffer the con‐ sequences. This chapter provides some advice on how to think through an information environment’s labeling before diving into implementation.

How does labeling fit with the other systems we’ve discussed? Well, labels are often the most obvious way to clearly show the user your organization and navigation schemes across multiple systems and contexts. For example, a single screen layout might contain different groups of labels, with each group representing a different organiza‐ tion or navigation system. Examples include labels that match the environment’s organization system (e.g., Home/Home Office, Small Business, Medium & Large Business, Government, Health Care), a global navigation system (e.g., Main, Search, Feedback), a subsite navigation system (e.g., Add to Cart, Enter Billing Information, Confirm Purchase), and systems specific to other channels such as interactive voice response (IVR) phone services and printed catalogs.

Why You Should Care About Labeling Prerecorded or canned communications, including print, the Web, scripted radio, and TV, are very different from interactive real-time communications. When we talk with another person, we rely on constant user feedback to help us hone the way we get our message across. We subconsciously notice our conversation partner zoning out, getting ready to make her own point, or beginning to clench her fingers into an angry fist, and we react by shifting our own style of

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1 A popular game that goes by different names around the world. Players pass a message in secret from one person to another. When it reaches the last player, they compare the (often unrecognizable) final message to the one they started with.

2 Thanks to information architect Andrew Hinton, who brought this example to our attention. You can read more about Andrew’s take on Starbucks’s labels in his book Understanding Context (Sebastopol, CA: O’Reilly, 2014).

communication, perhaps by raising our speaking volume, increasing our use of body language, changing a rhetorical tack, or fleeing.

Unfortunately, when we “converse” with users through the systems we design, the feedback isn’t quite so immediate, if it exists at all. There are certainly exceptions—social media such as Twitter, for example—but in most cases an information environment serves as an intermediary that slowly translates messages from the system’s owners and authors to users, and back again. This “telephone game”1 muddies the message. So in such a disintermediated medium with few visual cues, communicating is harder, and labeling is there‐ fore more important.

To minimize this disconnect, we must try our best to design labels that speak the same language as our environment’s users while reflecting its content. And, just as in a dialogue, when there is a question or confusion over a label, there should be clarification and explanation. Labels should educate people about new concepts and help them quickly identify familiar ones.

The conversation between a user and the environment’s owner often begins on a website’s main page. To get a sense of how successful this conversation might be, look at a site’s main page, do your best to ignore the other aspects of its design, and ask yourself a few ques‐ tions: Do the prominent labels on this page stand out to you? If they do, why? (Often, successful labels are invisible; they don’t get in your way.) If a label is new, unanticipated, or confusing, is there an explanation? Or are you required to click through to learn more? Although unscientific, this label testing exercise will help you get a sense of how the conversation might go with actual users.

Let’s try it with an average corporate information environment: Star‐ bucks’s public website, which is shown in Figure 7-1.2

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Figure 7-1. How do you respond to these labels?

Starbucks’s labels don’t seem terribly out of the ordinary. However, mediocrity isn’t an indicator of value or success; in fact, trouble spots arise from an informal cruise through the site’s labels. Let’s have a look:

My Bag | Find a Store | Sign In | Search this site So far so good: these are fairly standard labels on websites for companies that sell goods in physical and online stores. The location pin icon next to the “Find a Store” link implies that this will lead to the geographic locations of Starbucks’s stores, and the “My Bag” label, while not as common, is accompanied by a fairly standard bag icon that implies “shopping cart.”

Coffee Again, not bad—Starbucks sells coffee, so we’d expect some‐ thing like this here. It’s also good that it’s the first label next to the Starbucks logo, because it reinforces the association of the company logo with its primary product.

Menu This is where we start spotting trouble. What do we mean by “Menu” in the context of a website? Does this refer to the navi‐ gation menu of the site? A list of coffee drinks? Or is it a menu in the sense of a restaurant? (It turns out to be the latter.) While

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this label doesn’t seem to be that ambiguous in a desktop browser—after all, the rest of the site menu items are laid out next to it—it becomes more problematic when rendered in a mobile browser, because the label “Menu” is more often experi‐ enced in those browsers as a way of accessing the system’s main navigation menu (Figure 7-2).

Figure 7-2. When accessed in a mobile browser, the labels used on the Starbucks website are experienced in a different context, which can change their meaning

It’s worth noting here that while clicking the global menu links in the desktop version of the Starbucks website reveals mega- menus for each label, mobile users can’t derive additional con‐ textual clues; all they have to go by are the labels of the global navigation menu.

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Coffeehouse You’ve probably seen this word before. What does it mean to you? According to the OS X dictionary, it means “a cafe or other place where coffee is served, sometimes also offering informal entertainment”—in other words, a physical place where you can buy coffee. So you’d think that this is where you will find a list of Starbucks’s stores, and you’d be partly right... But there is much more there! For example, this is also where you find informa‐ tion about Starbucks’s iOS and Android apps and the company’s “Online Community” (Figure 7-3). It gives the impression that “Coffeehouse” has a particular meaning within the Starbucks Corporation, and one that is not immediately evident from examining the content it represents. It’s also worth noting that because “Coffeehouse” begins with the word “Coffee” (and sits close to it in the navigation menu), this label may cause users to do a double-take when looking for coffee.

Figure 7-3. The word “Coffeehouse” seems to have a particular meaning in the context of Starbucks

Responsibility Again, we don’t have too many issues with this label; it’s fairly common for large corporations to have social responsibility programs, and we’d expect to find that type of information here.

Card “Card” seems like a very broad term. Does it refer to your Star‐ bucks Card, the Starbucks eGift Card you received for your

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birthday, or the credit card that is registered as a valid payment method in your Starbucks account?

Shop “Shop” can be a verb or a noun. Here it is meant as a verb: it’s where you shop online in the “Starbucks Store” (which is not the same type of physical Starbucks “store” referred to in the “Find a Store” link). This is the only verb in the global naviga‐ tion, a potential source of confusion for users who may read it as leading to information about a physical “shop.”

The results of this quick exercise can be summarized by these categories:

The labels aren’t representative and don’t differentiate Many of Starbucks’s labels don’t represent the content they link to or precede. Other than clicking through, users have no way to learn what “Menu” means, or what the difference is between “Coffeehouse,” “Coffee,” and “Shop.” Groupings of dissimilar items (e.g., “Wi-Fi,” “Starbucks Mobile Apps,” and “Online Community”) don’t provide any context for what those items’ labels really represent. There is too much potential for confu‐ sion to consider these labels effective.

Some labels are jargony, not user-centric Labels like “Coffeehouse” and “Starbucks Store” can expose an organization that, despite its best intentions, does not consider the importance of its customers’ needs as important as its own goals, politics, and culture. This is often the case when websites use organizational jargon for their labels. You’ve probably seen such sites; their labels are crystal clear, obvious, and enlighten‐ ing, as long as you’re one of the .01% of users who actually work for the sponsoring organization. A sure way to lose a sale is to label your site’s product-ordering system as an “Order Process‐ ing and Fulfillment Facility.”

The labels waste money There are too many chances for a user to step into one of the many confusing cognitive traps presented by Starbucks’s labels. And any time an architecture intrudes on a user’s experience and forces him to pause and say “huh?” there is a reasonable chance that he will give up on a site and go somewhere else, especially given the competitive nature of this medium. In other

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words, confusing labels can negate the investment made to design and build a useful site and to market that site to intended audiences.

The labels don’t make a good impression The way you communicate or represent information on your site says a lot about you, your organization, and its brand. If you’ve ever read an airline magazine, you’re familiar with those ads for some educational series that develops your vocabulary. “The words you use can make or break your business deals,” or something like that. The same is true with an information envi‐ ronment’s labeling—poor labeling can destroy a user’s confi‐ dence in an organization. While it may have spent heavily on traditional branding, Starbucks doesn’t seem to have given much thought to the labels on the most important piece of its virtual real estate—its main page.

Like writing or any other form of professional communication, labels do matter. It’s fair to say that they’re as integral to an effective web presence as any other aspect of your website, be it brand, visual design, functionality, content, or navigability.

Varieties of Labels In information environments, we regularly encounter labels in two formats: textual and iconic. In this chapter, we’ll spend most of our time addressing textual labels (as they remain the most common, despite the Web’s highly visual nature), including:

Contextual links Hyperlinks to chunks of information on other pages or to other locations on the same page

Headings Labels that simply describe the content that follows them, just as print headings do

Navigation system choices Labels representing the options in navigation systems

Index terms Keywords, tags, and subject headings that represent content for searching or browsing

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These categories are by no means perfect or mutually exclusive. A single label can do double duty; for example, the contextual link “Naked Bungee Jumping” could lead to a page that uses the heading label “Naked Bungee Jumping” and has been indexed as being about (you guessed it) naked bungee jumping. And some of these labels could be iconic rather than textual, although we’d rather not imagine a visual representation of naked bungee jumping!

In the following section, we’ll explore the varieties of labels in greater detail and provide you with some examples.

Labels as Contextual Links Labels describe the hypertext links within the body of a document or chunk of information, and naturally occur within the descriptive context of their surrounding text. Contextual links are easy to create and are the basis for the exciting interconnectedness that drives much of the Web’s success.

However, just because contextual links are relatively easy to create doesn’t mean they necessarily work well. In fact, ease of creation introduces problems. Contextual links are generally not developed systematically; instead, they are developed in an ad hoc manner when the author makes a connection between her text and some‐ thing else, and encodes that association in her document. These hypertext connections are therefore more heterogeneous and per‐ sonal than, say, the connections between items in a hierarchy, where links are understood to be connecting parent items and child items. The result is that contextual link labels mean different things to dif‐ ferent people. You see the link “Shakespeare” and, upon clicking it, expect to be taken to the Bard’s biography. I, on the other hand, expect to be taken to his Wikipedia entry. In fact, the link actually takes us to a page for the village of Shakespeare, New Mexico. Go figure...

To be more representational of the content they connect to, contex‐ tual links rely instead upon, naturally, context. If the content’s author succeeds at establishing that context in his writing, then the label draws meaning from its surrounding text. If he doesn’t, the label loses its representational value, and users are more likely to experience occasionally rude surprises.

Because GOV.UK (Figure 7-4) is a site dedicated to providing infor‐ mation to the entire population of the UK, contextual links need to

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be straightforward and meaningful. GOV.UK’s contextual link labels, such as “Benefits,” “Money and tax,” and “Disabled people,” are representational, and draw on surrounding text and headings to make it clear what type of help you’ll receive if you click through. These highly representational labels are made even clearer by their context: explanatory text, clear headings, and a site that itself has a few straightforward uses.

Figure 7-4. The contextual links on the GOV.UK home page are straightforward and meaningful

On the other hand, contextual links on a blog aren’t necessarily so clear. The author is among friends and can assume that her regular readers possess a certain level of background (or, really, contextual) knowledge. Or she knows that keeping her link labels less represen‐ tational creates some mystery around what they’ll lead to. So the author may choose to design contextual link labels that aren’t so representational.

In Figure 7-5, the author expects us to know who “Dr. Drang” is— perhaps s/he’s been mentioned in this blog before. Or the author knows that we’ll recognize the label “Dr. Drang” as a person, and provides some mysterious context—“Your favorite snowman and mine”—to entice the user to click through. “Brent Simmons’ obser‐ vation” is equally obscure; we have no idea what this label repre‐ sents, but the blog author summarizes it by stating that “software

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engineers don’t really have a code of ethics.” Nonrepresentational labels have their place; as it’s likely that we already trust the author’s opinion, we’ll probably want to click through and learn more. In a case like the blog illustrated here, they can even convey the feeling that you are dropping in on a discussion among friends. But without that degree of trust already in place, nonrepresentational links could be damaging.

Figure 7-5. These contextual links aren’t very representational, but that’s acceptable when there is a high degree of trust in the author

As we’ll see, other varieties of labels derive context, and therefore meaning, from being part of larger sets of labels or labeling systems. But systematic consistency isn’t quite so possible with link labels. These labels are glued together by the copy and context rather than membership in a peer group. However, consistency among these labels and the chunks of information to which they link remains an issue to keep in mind.

We can ensure that contextual link labels are representational by asking, “What kind of information will the person expect to be taken to?” before creating and labeling a contextual link. Contextual links are created in such an ad hoc manner that simply asking this question will improve the quality of representation. (An easy way to study people’s interpretations of labels is to provide a printout of a

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page with the labels clearly identified, and have participants jot down what they’d expect each to link to.)

On the other hand, it’s important to acknowledge that contextual links are often not within our control. Usually, content authors are responsible for contextual links. They are the ones who know the meaning of their content and how to best link it to other content. So while you may want to enforce rules for contextual link labels (such as what an employee’s name should always link to), you may be bet‐ ter off suggesting guidelines to content authors (such as suggesting that employees’ names link to corresponding directory listings when possible).

Labels as Headings Labels are often used as headings that describe the chunks of infor‐ mation that follow. Headings, as shown in Figure 7-6, are often used to establish a hierarchy within content. Just as in a book, where headings help us distinguish chapters from sections, they also help us determine a site’s subsites, or differentiate categories from subcategories.

Figure 7-6. Layout, typographic treatment, and whitespace help the reader distinguish labels and hierarchy in the Windows Store

The hierarchical relationships between headings—whether parent, child, or sibling—are usually established visually through consistent use of numbering, font sizes, colors and styles, whitespace and indentation, or combinations thereof. A visually clear hierarchy,

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often the work of information or graphic designers, can take some pressure off information architects by reducing the need to create labels that convey that hierarchy. So, a set of labels that don’t mean much can suddenly take on meaning when presented in a hierarchy. For example, this set of inconsistent headings may be quite confusing:

Our Furniture Selection Office Chairs Our buyer’s picks Chairs from Steelcase Hon products Herman Miller Aerons Lateral Files

However, they are much more meaningful when presented in a hierarchy:

Our Furniture Selection Office Chairs Our buyer’s picks Chairs from Steelcase Hon products Herman Miller Aerons Lateral Files

It’s also important not to be too rigidly bound to showcasing hier‐ archical relationships. In Figure 7-7, heading labels such as “Lead‐ ers” and “Southeastern Standings” represent the content that follows them. Yet the game schedule closer to the top of the page doesn’t merit the same treatment, because most readers could visually dis‐ tinguish these without actually reading them. In other words, insert‐ ing the heading “Game Schedule” before the table and applying to it the same typographic style as that used for “Leaders” and “South‐ eastern Standings” wouldn’t greatly benefit users, who would likely recognize the schedule already.

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Figure 7-7. This hierarchy of heading labels is inconsistent, but that’s OK

It is interesting to note, however, that it’d be impossible to correctly read the schedule if each column in the table didn’t have its own heading label.

We can be a bit more flexible when designing hierarchical headings, but it’s especially important to maintain consistency when labeling steps in a process. To successfully navigate a process, it’s typically necessary for users to complete each step along the way, so heading labels have to be obvious and must also convey sequence. Using numbers is an obvious way to communicate progression, and

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consistently framing the labels as actions—utilizing verbs—also helps tie together the sequence of steps. In effect, the labels should tell users where to start, where to go next, and what action will be involved in each step along the way. Figure 7-8 shows a page in the process to sign up to become a Google Play Developer, which clearly describes the actions required in each step.

Figure 7-8. Clear sequential labeling in the Google Play Developer signup process

Heading labels, whether hierarchical or sequenced, come in multi‐ ples, and should be more systematically designed than contextual link labels.

Labels Within Navigation Systems Because navigation systems typically have a small number of options, their labels demand consistent application more than any other type of label. A single inconsistent option can introduce an “apples and oranges” effect more quickly in a navigation system, which usually has fewer than 10 choices, than in a set of index terms, which might have thousands. Additionally, a navigation sys‐ tem is typically experienced repeatedly throughout the environment, so navigation labeling problems are magnified through repeated exposure.

Users rely on a navigation system to behave “rationally” through a consistent location and look; labels should be no different.

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Effectively applied labels are integral to building a sense of familiar‐ ity, so they’d better not change from page to page. Using the label “Main” on one page, “Main Page” on another, and “Home” else‐ where could destroy the familiarity that the user needs when navi‐ gating a site. In Figure 7-9, the horizontal navigation system’s four labels—“The Janus Advantage,” “Our Funds,” “Planning,” and “My Account”—are applied consistently throughout the website, and would be even more effective if their colors and locations were also consistent.

There are no standards, but some common variants exist for many navigation system labels. You should consider selecting one from each of these categories and applying it consistently, as these labels are already familiar to most web users. Here is a nonexhaustive list:

• Main, Main Page, Home • Search, Find, Browse, Search/Browse • Site Map, Contents, Table of Contents, Index • Contact, Contact Us • Help, FAQ, Frequently Asked Questions • News, News & Events, News & Announcements, Announce‐

ments • About, About Us, About <company name>, Who We Are

Of course, the same label can often represent different kinds of information. For example, in one system, “News” may link to an area that includes announcements of new additions to the website. In another site, “News” may link to an area of news stories describ‐ ing national and world events. Obviously, if you use the same labels in different ways within your own system, your users will be very confused. One alternative in such cases is to include brief descrip‐ tions under navigational labels, with the obvious trade-off being that these descriptions consume valuable screen real estate.

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Figure 7-9. Janus’s navigation system labels remain consistent through‐ out the website

Labels as Index Terms Often referred to as keywords, tags, descriptive metadata, taxono‐ mies, controlled vocabularies, and thesauri, sets of index term labels can be used to describe any type of content: sites, subsites, pages, content chunks, and so on. By representing the meaning of a piece

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of content, index terms support more precise searching than simply searching the full text—someone has assessed the content’s meaning and described it using index terms, and searching those terms ought to be more effective than having a search engine match a query against the content’s full text.

Index terms are also used to make browsing easier: the metadata from a collection of documents can serve as the source of browsable lists or menus. This can be highly beneficial to users, as index terms provide an alternative to a primary organization system, such as an information architecture organized by business unit. Index terms in the form of indexes and other lists provide a valuable alternative view by “cutting across the grain” of organizational silos.

The index of the SFGate website shown in Figure 7-10 is generated from index term labels, which in turn are used to identify content from many different sections of the site. Much of the content already accessible through the site’s primary organization system is also accessible by browsing these index terms (i.e., keywords).

Figure 7-10. The SFGate site index

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Frequently, index terms are completely invisible to users. The records we use to represent documents in content management sys‐ tems and other databases typically include fields for index terms, which are often heard but not seen: they come into play only when you search. Similarly, index terms may be hidden as embedded met‐ adata in an HTML document’s <meta> or <title> tags. For example, a furniture manufacturer’s website might list the following index terms in the <meta> tags of records for its upholstered items:

A search on “sofa” would then retrieve the page with these index terms even if the term “sofa” doesn’t appear anywhere in the page’s text. Figure 7-11 shows a similar, more delectable example from the Bon Appétit website. A search for “snack” retrieves this recipe, though there is no mention of the term in the recipe itself. “Snack” is likely stored separately as an index term in a database record for this recipe.

Figure 7-11. A search for “snack” retrieves this recipe, even though the term doesn’t appear within the text

Web search engines such as Google have become the primary way in which people find and access websites. Using index terms to describe a main page is an effective way for getting that page, and

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3 Search Engine Watch is the most useful resource for learning how web-wide search engines and directories work, and how you can index your site’s main and other major pages so they “rise to the top” of retrieval results.

the site as a whole, indexed and “known” so that users who search the Web are more likely to find it.3

Getting your pages to stand out from one another is a different and much more daunting challenge. That’s where a more systematic approach to labeling—using index terms from controlled vocabula‐ ries or thesauri—has more value. These sets of labels are designed to describe delineated domains—such as products and services, or oncology—and to do so in a consistent, predictable manner. We’ll describe these vocabularies in great detail in Chapter 10.

Iconic Labels It’s true that a picture is worth a thousand words. But which thousand?

Icons can represent information in much the same way as text can. We see them most frequently used as navigation system labels, espe‐ cially in mobile apps where screen space is constrained. Addition‐ ally, icons occasionally serve as heading labels and have even been known to show up as link labels, although this is rare.

The problem with iconic labels is that they constitute a much more limited language than text. That’s why they’re more typically used for navigation system or small organization system labels, where the list of options is small, than for larger sets of labels such as index terms, where iconic “vocabularies” are quickly outstripped. They also can work well for less text-oriented audiences, such as children.

Even so, iconic labels are still a risky proposition in terms of whether or not they can represent meaning. Figure 7-12 shows navi‐ gation tiles on the Microsoft Band fitness tracker. What do the icons mean to you?

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http://www.searchenginewatch.com

Figure 7-12. Icons from the Microsoft Band’s navigation system (image: https://www.microsoft.com/microsoft-band/en-us)

(They are, respectively: Mail, Run, Calendar, Exercise, Sleep, Mes‐ saging, and Finance.)

Even given the fairly specific context of a fitness band, most users probably won’t understand this language immediately, although they might correctly guess the meaning of one or two of these labels.

Iconic labels like these add aesthetic appeal to an information envi‐ ronment, and as long as they don’t compromise the system’s usabil‐ ity, there’s no reason not to use them. In fact, the iconic “language” might get established in your users’ minds through repeated expo‐ sure. In such situations, icons are especially useful shorthand, both representational and easy to visually recognize—a double bonus. Unless your system has a patient, loyal audience of users who are willing to learn your visual language, however, we suggest using iconic labels only for environments with a limited set of options, being careful not to place form ahead of function.

Designing Labels Designing effective labels is perhaps the most difficult aspect of information architecture. Language is simply too ambiguous for you to ever feel confident that you’ve perfected a label. There are always synonyms and homonyms to worry about, and different contexts influence our understanding of what a particular term means. And of course, the challenge is much more complicated if your system deals with more than one language. But even labeling conventions are questionable: you absolutely cannot assume that the label “main page” will be correctly interpreted by 100% of your system’s users. Your labels will never be perfect, and you can only hope that your efforts make a difference, as measuring label effectiveness is an extremely difficult undertaking.

If it sounds to you like labeling is an art rather than a science, you’re absolutely correct. And, as in all such cases, you can forget about

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https://www.microsoft.com/microsoft-band/en-us

finding incontrovertible rules, and hope for guidelines instead. Fol‐ lowing are some guidelines and related issues that will help you as you delve into the mysterious art of label design.

General Guidelines Remember that content, users, and context affect all aspects of an information architecture, and this is particularly true with labels. Any of the variables attached to users, content, and context can drag a label into the land of ambiguity.

Let’s revisit the term “pitch.” From baseball (what’s thrown) to foot‐ ball (the field where it’s played in the United Kingdom), from busi‐ ness (what’s sometimes made while riding in an elevator) to sailing (the angle of the boat in the water), there are at least 15 different def‐ initions, and it’s hard to make sure that your site’s users, content, and context will converge upon the same definition. This ambiguity makes it difficult to assign labels to describe content, and difficult for users to rely on their assumptions about what specific labels actually mean.

So what can we do to make sure our labels are less ambiguous and more representational? The following two guidelines may help.

Narrow the scope whenever possible If we focus our information environments on a more defined audi‐ ence, we reduce the number of possible perspectives on what a label means. Sticking to fewer subject domains achieves more obvious and effective representation. A narrower business context means clearer goals for the system, its architecture, and therefore its labels.

Labeling is easier if your content, users, and context are kept simple and focused. Too many environments have tried to take on too much, achieving broad mediocrity rather than nailing a few choice tasks. Accordingly, labeling systems often cover too much ground to truly be effective. If you are planning any aspect of your environ‐ ment’s scope—who will use it, what content it will contain, and how, when, and why it should be used—erring toward simplicity will make your labels more effective.

If your environment must be a jack of all trades, avoid using labels that address the entire system’s content. The obvious exceptions are the labels for global navigation systems, which do cover the entire

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system. But in the other areas of labeling, modularizing and simpli‐ fying content into subsections that meet the needs of specific audi‐ ences will enable you to design more modular, simpler collections of labels to address those specific areas.

This modular approach may result in separate labeling systems for different areas of your environment. For example, records in your staff directory might benefit from a specialized labeling system that wouldn’t make sense for other parts of the site, while your site-wide navigation system’s labels wouldn’t really apply to entries in the staff directory.

Develop consistent labeling systems, not labels It’s also important to remember that labels, like organization and navigation systems, are systems in their own right. Some are planned systems; some aren’t. A successful system is designed with one or more characteristics that unify its members. In successful labeling systems, one characteristic is typically consistency.

Why is consistency important? Because consistency means predicta‐ bility, and systems that are predictable are simply easier to learn. You see one or two labels, and then you know what to expect from the rest—if the system is consistent. This is especially important for first-time users, but consistency benefits all users by making labeling easy to learn, easy to use, and therefore invisible.

Consistency is affected by many issues:

Style Haphazard usage of punctuation and case is a common problem within labeling systems, and can be addressed, if not eliminated, by using style guides. Consider hiring a proofreader and pur‐ chasing a copy of Strunk & White.

Presentation Similarly, consistent application of fonts, font sizes, colors, whitespace, and grouping can help visually reinforce the sys‐ tematic nature of a group of labels.

Syntax It’s not uncommon to find verb-based labels (e.g., “Grooming Your Dog”), noun-based labels (e.g., “Diets for Dogs”), and question-based labels (e.g., “How Do You Paper Train Your Dog?”) all mixed together. Within a specific labeling system,

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consider choosing a single syntactical approach and sticking with it.

Granularity Within a labeling system, it can be helpful to present labels that are roughly equal in their specificity. Exceptions (such as site indexes) aside, it’s confusing to encounter a set of labels that cover differing levels of granularity—for example, “Chinese res‐ taurants,” “Restaurants,” “Taquerias,” “Fast Food Franchises,” “Burger Kings.”

Comprehensiveness People can be tripped up by noticeable gaps in a labeling sys‐ tem. For example, if a clothing retailer’s website lists “trousers,” “ties,” and “shoes,” while somehow omitting “shirts,” we may feel like something’s wrong. Do they really not carry shirts? Or did they make a mistake? Aside from improving consistency, a comprehensive scope also helps people do a better job of quickly scanning and inferring the environment’s content.

Audience Mixing terms like “lymphoma” and “tummy ache” in a single labeling system can also throw people off, even if only tem‐ porarily. Consider the languages of your environment’s major audiences. If each audience uses a very different terminology, you may have to develop a separate labeling system for each audience, even if these systems are describing exactly the same content.

There are other potential roadblocks to consistency. None is particu‐ larly difficult to address, but you can certainly save a lot of labor and heartache if you consider these issues before you dive into creating labeling systems.

Sources of Labeling Systems Now that you’re ready to design your labeling systems, where do you start? Believe it or not, this is the easy part. Unless you’re dealing with ideas, concepts, and topics that until now were unknown to humanity, you’ll probably have something to start with. And already having a few labels generally beats starting from scratch, which can be prohibitively expensive, especially with large vocabularies.

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4 Like many information environments, Budget.com is evolving. Prior to going to press, the site implemented changes to its design and labeling that fixed many of the issues presented here.

Existing labeling systems might include the labels currently on your website, or comparable or competitors’ sites. Ask yourself who might have taken this on before. Study, learn, and “borrow” from what you find in other environments. And keep in mind that a major benefit of examining existing labeling systems is that they’re systems—they’re more than groups of odd, miscellaneous labels that don’t necessarily fit together.

As you look for existing labeling systems to draw upon, consider what works and what doesn’t. Which systems can you learn from, and, perhaps more importantly, which of those labels can you keep? There are a variety of sources for labels that you should examine.

Your current information environment Your current website or app probably already has labeling systems by default. At least some reasonable decisions had to have been made during the course of its creation, so you probably won’t want to throw all those labels out completely. Instead, use them as a start‐ ing point for developing a complete labeling system, taking into consideration the decisions made while creating the original system.

A useful approach is to capture the existing labels in a single docu‐ ment. To do so, walk through the entire system, either manually or automatically, and gather the labels. You might consider assembling them in a simple table containing a list or outline of each label and the documents it represents. Creating a labeling table is often a natu‐ ral extension of the content inventory process. It’s a valuable exer‐ cise, though we don’t recommend it for indexing term vocabularies, which are simply too large to table-ize unless you focus on small, focused segments of those vocabularies.

Table 7-1 provides a breakdown of the navigation system labels on Budget Rent A Car’s main page.4

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Table 7-1. Budget Rent A Car’s navigation labels

Label Destination’s heading label

Destination’s <TITLE> label

Top-of-page navigation system labels

car rental - Automobile Rental from Budget

specials Daily, Weekly, Weekend Day & Monthly Specials

Budget coupons and car rental deals U.S. | Budget.com

car types Rental car, SUV, and truck fleet

Rental Car, SUV & Truck Fleet

locations find your location in USA United States Car Rentals and car rental deals at Budget.com

services Smart Car Rental Services Smart Car Rental Services - Perks & Products - Budget.com

customer care Customer Care contact us | customer care | Budget

car sales - Great Prices on Used Rental Cars - Budget Car Sales

country / language Renting outside of the U.S.? -

Reserve with customer ID

- rent your car today | Budget

Create customer ID Frequent Renter Account Services

Car Rental Deals

Body navigation system labels

Rent a car in 60 seconds

- rent your car today | Budget

Make a Car Reservation

- rent your car today | Budget

Already Have a Reservation?

View, Change or Cancel an Existing Reservation

rent your car today | Budget

Common Questions Just the FAQs Common Questions - Car Rental FAQs - Budget.com

Find a Location find your location in USA United States Car Rentals and car rental deals at Budget.com

Bottom-of-page navigation system labels

About Budget About Us About Us - Car Rentals - Budget.com

Privacy U.S. Privacy US Privacy Policy - Customer Care - Budget.com

Site map Budget.com car rental site map

Site Map - Car Rental, Reservations & Discounts - Budget.com

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Label Destination’s heading label

Destination’s <TITLE> label

Employment avis budget group Avis Budget Group

Car Rental Locations find your location in USA United States Car Rentals and car rental deals at Budget.com

Budget Worldwide Budget Rental Car Locations: Worldwide

Budget Car Rentals Locations Worldwide - Budget

US & Canada Budget Rental Car Locations: World

Budget Car Rentals Locations - Budget

Major Airports Popular Airport Car Rental Locations

Airport Car Rental Locations from Budget.com

Orlando Car Rental Orlando Car Rental Orlando Car Rental - Rent a Car in Orlando, Florida at Budget.com

Featured Rentals Popular Available Car Types Available Car Types from Budget.com

Van Rentals Van Car Rental Van Rental - Passenger Van rental from Budget

Car Rental Deals Budget Coupons at Budget.com

Budget Rental Car Coupons - Save On a Budget Car Rental

One Way Car Rental One Way Car Rental One Way Car Rental - Budget offers special deals on one way car rentals

Monthly Car Rental Long Term Car Rental Monthly Car Rental - Save more with long term car rental

Featured Products Smart Car Rental Services Smart Car Rental Services - Perks & Products - Budget.com

Small Business Rentals

Budget Business Program company account | frequent renters | Budget

Car in the shop? Reservations Budget Reservations - Vehicle Replacement

Budget Mobile Apps The Budget Mobile App Budget Rent A Car - Budget Mobile

Go Green - Rent Clean Go Greener. Drive Cleaner. Green Car Rental - Rent an Eco-Friendly Vehicle - Budget.com

Business accounts U.S. Budget Business Program®

Budget Business Car Rental Program - Budget.com

Partners Partners Partners, Affiliates, Travel Agents - Budget.com

Affiliates Travel Affiliate Program affiliates | partners | about us | Budget

Travel agents Car Rental Services for Travel Agents

Rent A Car at Budget - Travel Agents

Car sales Love it. Buy it. Car Sales - Buy Used Cars from Budget

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Label Destination’s heading label

Destination’s <TITLE> label

Budget is your earth friendly alternative

Go Greener. Drive Cleaner. Green Car Rental - Rent an Eco-Friendly Vehicle - Budget.com

Arranging labels in a table provides a more condensed, complete, and accurate view of navigation labels as a system. Inconsistencies are easier to catch; in Budget’s case, we encounter three variants of the company’s name: “Budget,” “Budget Rent A Car,” and “Budget.com.” We find inconsistencies for a single page’s labels: the contact page is labeled “Contact Us” and “Customer Care.” Some pages don’t have main headings. We encounter various other style and capitalization inconsistencies that may confuse users. We may decide that, personally, we just don’t like certain labels. We may also decide that some of the problems aren’t worth changing. In any case, we now have a sense of the site’s current labeling system and how it could be improved.

Comparable and competitive environments If you don’t have a website or app in place or are looking for new ideas, look elsewhere for labeling systems. The open nature of the Web allows us to learn from one another. So, just as you might view the source of a wonderfully designed page, you can learn from another site’s great labeling system.

Determine beforehand what your audiences’ needs are most likely to be, and then surf your competitors’ sites, borrowing what works and noting what doesn’t (you might consider creating a label table for this specific purpose). If you don’t have competitors, visit compara‐ ble sites or sites that seem to be best in class.

As we mentioned in Chapter 4, the Web is already old enough to have produced various industry-specific typologies. If you explore multiple competitive or comparative environments, you may find that labeling patterns emerge. These patterns may not yet be indus‐ try standards, but they at least can inform your choice of labels. For example, in a competitive analysis of eight financial services sites “personal finance” was found to be more or less the de facto label choice, compared to its synonyms. Such data may discourage you from using a different label.

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Figure 7-13 shows labeling systems from United, Delta, Virgin America, and American Airlines, all competing in the airline busi‐ ness. Do you notice trends and differences here? Just a glance shows how much variation there is in terms of the number of labels (from five to as many as nine). Some use the “My...” approach, and some use brand-specific labels (e.g., “AAdvantage”). Task-based labels (e.g., “Book a trip”) are less common than one would expect, as is the use of a “Home” or “Main” option.

Figure 7-13. Labeling systems from United, Delta, Virgin America, and American Airlines

Controlled vocabularies and thesauri Another great source for labels is existing controlled vocabularies and thesauri (a topic we’ll cover in depth in Chapter 10). These especially useful resources are created by professionals with library or subject-specific backgrounds, who have already done much of the work of ensuring accurate representation and consistency. These vocabularies are often publicly available and have been designed for broad usage. You’ll find these to be most useful for populating label‐ ing systems used for indexing content.

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Seek out narrowly focused vocabularies that help specific audiences to access specific types of content. For example, if your system’s users are computer scientists, a computer science thesau‐ rus “thinks” and represents concepts in a way your users are likely to understand, more so than a general scheme like the Library of Con‐ gress subject headings would.

A good example of a specific controlled vocabulary is the Educa‐ tional Resources Information Center (ERIC) Thesaurus. This the‐ saurus was designed, as you’d guess, to describe the domain of education. An entry in the ERIC Thesaurus for “scholarship” is shown in Figure 7-14.

Figure 7-14. Controlled vocabularies and thesauri are rich sources of labels

If your environment has to do with education or if your audience is comprised of educators, you might start with ERIC as the source for your system’s labels. You can use a thesaurus like ERIC to help you with specific labeling challenges, like determining a better variant for a particularly knotty label. You might go as far as to license the entire vocabulary and use it as your system’s labeling system.

Unfortunately, there aren’t controlled vocabularies and thesauri for every domain. Sometimes you may find a matching vocabulary that

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emphasizes the needs of a different audience. Still, it’s always worth seeing if a potentially useful controlled vocabulary or thesaurus exists before creating labeling systems from scratch. Try these excel‐ lent resources as you hunt for sources of labels:

• Taxonomy Warehouse • American Online Thesauri and Authority Files (American Soci‐

ety for Indexing)

Creating New Labeling Systems When there are no existing labeling systems that meet your needs, or when you need to do more customizing than you’d expected, you face the tougher challenge of creating labeling systems from scratch. Your most important sources are your content (and potentially its authors), and the people who will be using your environment.

Content analysis Labels can come directly from your content. You might read a repre‐ sentative sample of your environment’s content and jot down a few descriptive keywords for each document along the way. It’s a slow and painful process, and it obviously won’t work with a huge set of documents. If you go this route, look for ways to speed up the pro‐ cess by focusing on any existing content representations like titles, summaries, and abstracts. Analyzing content for candidate labels is certainly another area where art dominates science.

There are software tools available that can perform auto-extraction of meaningful terms from content. These tools—typically referred to as “entity extraction” applications—can save you quite a bit of time if you face a huge body of content; like many software-based solutions, auto-extraction tools may get you 80% of the way to the finish line. You’ll be able to take the terms that are output by the software and use them as candidates for a controlled vocabulary, but you’ll still need to do a bit of manual labor to make sure the output actually makes sense. (And it’s worth noting that auto-extraction tools—and the training and tuning required to make them work well—can be quite expensive.)

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http://taxonomywarehouse.com/

http://bit.ly/online_thesauri

Content authors Another manual approach is to ask content authors to suggest labels for their own content. This might be useful if you have access to authors; for example, you could talk to your company’s researchers who create technical reports and white papers, or to the PR people who write press releases.

However, even when authors select terms from a controlled vocabu‐ lary to label their content, they don’t necessarily do it with the reali‐ zation that their documents are only one of many in a broader collection. So, they might not use sufficiently specific labels. Also, few authors happen to be professional indexers.

So take their labels with a grain of salt, and don’t rely upon them for accuracy. As with other sources, labels from authors should be con‐ sidered useful candidates for labels, not final versions.

User advocates and subject matter experts Another approach is to find advanced users or user advocates who can speak on the users’ behalf. Such people may include librarians, switchboard operators, or subject matter experts (SMEs) who are familiar with the users’ information needs in a larger context. Some of these people—reference librarians, for example—keep logs of what people want; all will have a good innate sense of people’s needs by dint of constant interaction.

We found that talking to user advocates was quite helpful when working with a major healthcare system. Working with its library’s staff and SMEs, we set out to create two labeling systems: one with medical terms to help medical professionals browse the services offered by the healthcare system, the other for the lay audience to access the same content. It wasn’t difficult to come up with the med‐ ical terms because there are many thesauri and controlled vocabula‐ ries geared toward labeling medical content. It was much more difficult to come up with a scheme for the layperson’s list of terms. There didn’t seem to be an ideal controlled vocabulary, and we couldn’t draw labels from the site’s content because it hadn’t been created yet. So we were truly starting from scratch.

We solved this dilemma by using a top-down approach: we worked with the librarians to determine what they thought users wanted out of the system. We considered their general needs, and came up with a few major ones:

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• They need information about a problem, illness, or condition. • The problem is with a particular organ or part of the body. • They want to know about the diagnostics or tests that the

healthcare professionals will perform to learn more about the problem.

• They need information on the treatment, drug, or solution that will be provided by the healthcare system.

• They want to know how they can pay for the service. • They want to know how they can maintain their health.

We then came up with basic terms to cover the majority of these six categories, taking care to use terms appropriate to this audience of laypersons. Table 7-2 shows some examples.

Table 7-2. Sample laypersons’ labels for identified categories

Category Sample labels

Problem/illness/condition HIV, fracture, arthritis, depression

Organ/body part Heart, joints, brain

Diagnostics/tests Blood pressure, X-ray

Treatment/drug/solution Hospice, bifocals, joint replacement

Payment Administrative services, health maintenance organization, medical records

Health maintenance Exercise, vaccination

By starting with a few groupings, we were able to generate labels to support indexing. We knew a bit about the audience (laypersons), and so were able to generate the right kinds of terms to support their needs (e.g., leg instead of femur). The secret was working with peo‐ ple (in this case, staff librarians) who were knowledgeable about the kind of information people want.

Users (directly) The actual users of a system may be able to tell you what the labels should be. This isn’t the easiest information to get your hands on, but if you can, it’s the best source of labeling there is.

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5 Donna Spencer’s book Card Sorting: Designing Usable Categories (Brooklyn, NY: Rose‐ nfeld Media, 2011) is quite helpful here.

Card sorting. Card sort exercises are one of the best ways to learn how your users would use information.5 (Card sorting methodolo‐ gies are covered more extensively in Chapter 11.) There are two basic varieties of card sorts: open and closed. Open card sorts allow participants to cluster labels for existing content into their own cate‐ gories and then label those categories (and clearly, card sorting is useful when designing organization systems as well as labeling sys‐ tems). Closed card sorts provide participants with existing categories and ask them to sort content into those categories. At the start of a closed card sort, you can ask users to explain what they think each category label represents and compare these definitions to your own. Both approaches are useful ways to determine labels, although they’re more appropriate for smaller sets of labels such as those used for navigation systems.

In the following example, we asked participants to categorize cards from the owner’s section of a website for a large automotive com‐ pany (let’s call it “Tucker”). After we combined the data from this open card sort, we found that participants labeled the combined cat‐ egories in different ways. “Maintenance,” “maintain,” and “owner’s” were often used in labels for the first cluster, indicating that these were good candidates for labels (see Table 7-3).

Table 7-3. Cluster 1

Participant Identified categories

Participant 1 Ideas & maintenance

Participant 2 Owner’s guide

Participant 3 Items to maintain car

Participant 4 Owner’s manual

Participant 5 Personal information from dealer

Participant 6 [No response]

Participant 7 Maintenance upkeep & ideas

Participant 8 Owner’s tip AND owner’s guide and maintenance

But in other cases, no strong patterns emerged (see Table 7-4).

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Table 7-4. Cluster 2

Participant Identified categories

Participant 1 Tucker features

Participant 2 [No response]

Participant 3 Shortcut for info on car

Participant 4 Auto info

Participant 5 Associate with dealer

Participant 6 Tucker website info

Participant 7 Manuals specific to each car

Participant 8 [No response]

In a corresponding closed card sort, we asked participants to describe each category label before they grouped content under each category. In effect, we were asking participants to define each of these labels, and we compared their answers to see if they were simi‐ lar or not. The more similar the answers, the stronger the label.

Some labels, such as “Service & Maintenance,” were commonly understood, and were in line with the content that you’d actually find listed under that category (see Table 7-5).

Table 7-5. Service & Maintenance

Participant Identified content

Participant 1 When to change the fluids, rotate tires; a place to keep track when I had my vehicle in for service (sic)

Participant 2 How to maintain vehicle: proper maintenance, features of car, where to find fuse box, etc., owner’s manual

Participant 3 Find service that might be open on Sunday sometimes

Participant 4 When I will need service and where to go to get it

Participant 5 Reminders on when services is recommended (sic)

Participant 6 Timeline for service and maintenance

Participant 7 Maintenance schedule and tips to get best performance out of car and longevity of car

Participant 8 Maintenance tips, best place to go to fix car problem, estimated price

Other category labels were more problematic. Some participants understood “Tucker Features & Events” in the way that was intended, representing announcements about automobile shows, discounts, and so on. Others interpreted this label to mean a

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6 The best summary of this method is Rashmi Sinha’s short but highly useful article, “Beyond Cardsorting: Free-Listing Methods to Explore User Categorizations,” Boxes & Arrows, February 2003 (http://bit.ly/beyond_cardsorting).

vehicle’s actual features, such as whether or not it had a CD player (see Table 7-6).

Table 7-6. Tucker Features & Events

Participant Identified content

Participant 1 New items for my vehicle; upcoming new styles—new makes & models; financial news—like 0% financing

Participant 2 Local & national sponsorship; how to obtain Tucker sponsorship; community involvement

Participant 3 Mileage, CD or cassette, leg room, passengers, heat/AC control dull or not, removable seats, automatic door openers

Participant 4 All information regarding the Tucker automobile I’m looking for and any sale events going on regarding this auto

Participant 5 Looking for special pricing events

Participant 6 Site for outlining vehicles and options available. What automobile shows are available and where.

Participant 7 About Tucker, sales, discounts, special events

Participant 8 No interested (sic)

Card sort exercises are very informative, but it’s important to recog‐ nize that they don’t present labels in the context of an actual prod‐ uct. Without this natural context, the labels’ ability to represent meaning is diminished. So, like all other techniques, card sorts have value but shouldn’t be seen as the only method of investigating label quality.

Free-listing. While card sorting isn’t necessarily an expensive and time-consuming method, free-listing is an even lower-cost way to get users to suggest labels.6 Free-listing is quite simple: select an item and have participants brainstorm terms to describe it. You can do this in person (capturing data with pencil and paper will be fine) or remotely, using a free or low-cost online survey tool like Survey‐ Monkey, Zoomerang, or Google Forms. That’s really all there is to it.

Well, not quite: you’ll want to consider your participants: who (ide‐ ally representative of your overall audience) and how many (three to

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http://bit.ly/beyond_cardsorting

five may not yield scientifically significant results, but it is certainly better than nothing and may yield some interesting results). You might also consider asking participants to rank the terms they’ve suggested as a way to determine which are the most appropriate.

You’ll also need to choose which items to brainstorm terms for. Obviously you can only do this with a subset of your content. You could choose some representative content, such as a handful of your company’s products. But even then, it’ll be tricky—do you choose the most popular products or the more esoteric ones? It’s important to get the labeling right for your big sellers, but conventions for their labels are already fairly established. The esoteric items? Well, they’re more challenging, but fewer people care about them. So you may end up with a balance among the few items you select for a free-listing exercise. This is one of those cases where the art of infor‐ mation architecture is at least as important as the science.

What do you do with the results? Look for patterns and frequency of usage; for example, perhaps most of your participants use the term “cell phone” while surprisingly few prefer “mobile phone.” Patterns like these not only can provide you with a sense of how to label an individual item, but may also demonstrate the tone of users’ lan‐ guage overall. You might note that they use jargon quite a bit, or the reverse; perhaps you find a surprising amount of acronyms in their labels, or some other pattern emerges from free listing. The result won’t be a full-fledged labeling system, but it will give you a better sense of what tone and style you should take when developing a labeling system.

Users (indirectly) Most organizations—especially those whose information environ‐ ments include search engines—are sitting on top of reams of user data that describe users’ needs. Analyzing those search queries can be a hugely valuable way to tune labeling systems, not to mention to diagnose a variety of other problems with your system. Additionally, the popularization of free-form tagging in social networks has cre‐ ated a valuable, if indirect, source of data on users’ needs that can help in the creation of labeling systems.

Search log analysis. Search log analysis (also known as search analyt‐ ics) is one of the least intrusive sources of data on the labels your

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7 For more on search analytics, an excellent resource is Lou’s book Search Analytics for Your Site: Conversations with Your Customers (Brooklyn, NY: Rosenfeld Media, 2011).

site’s audiences actually use. Analyzing search queries7 is a great way to understand the types of labels your site’s visitors typically use (see Table 7-7). After all, these are the labels that users utilize to describe their own information needs in their own language. You may notice the use of acronyms (or lack thereof), product names, and other jar‐ gon, which could impact your own willingness to use jargony labels. You might notice that users’ queries use single or multiple terms, which could affect your own choice of short or long labels. And you might find that people simply aren’t using the terms you thought they would for certain concepts. You may decide to change your labels accordingly, or use a thesaurus-style lookup to connect a user- supplied term (e.g., “pooch”) to the preferred term (e.g., “dog”).

Table 7-7. 40 common queries from Michigan State University’s site; each query tells us something about what the majority of users seek most often and how they label their information needs

Rank Count Cumulative Percent of total Query

1 1184 1184 1.5330 capa

2 1030 2214 2.8665 lon+capa

3 840 3054 3.9541 study+abroad

4 823 3877 5.0197 angel

5 664 4541 5.8794 lon-capa

6 656 5197 6.7287 library

7 584 5781 7.4849 olin

8 543 6324 8.1879 campus+map

9 530 6854 8.8741 spartantrak

10 506 7360 9.5292 cata

11 477 7837 10.1468 housing

12 467 8304 10.7515 map

13 462 8766 11.3496 im+west

14 409 9175 11.8792 computer+store

15 399 9574 12.3958 state+news

16 395 9969 12.9072 wharton+center

17 382 10351 13.4018 chemistry

18 346 10697 13.8498 payroll

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Rank Count Cumulative Percent of total Query

19 340 11037 14.2900 breslin+center

20 339 11376 14.7289 honors+college

21 339 11715 15.1678 calendar

22 334 12049 15.6002 human+resources

23 328 12377 16.0249 registrar

24 327 12704 16.4483 dpps

25 310 13014 16.8497 breslin

26 307 13321 17.2471 tuition

27 291 13612 17.6239 spartan+trak

28 289 13901 17.9981 menus

29 273 14174 18.3515 uab

30 267 14441 18.6972 academic+calendar

31 265 14706 19.0403 im+east

32 262 14968 19.3796 rha

33 262 15230 19.7188 basketball

34 255 15485 20.0489 spartan+cash

35 246 15731 20.3674 loncapa

36 239 15970 20.6769 sparty+cash

37 239 16209 20.9863 transcripts

38 224 16433 21.2763 psychology

39 214 16647 21.5534 olin+health+center

40 206 16853 21.8201 cse+101

Another—perhaps less obvious—way to obtain search terms is by using Google AdWords to see what terms people are searching for. These terms can then inform the labeling of your information environment.

Tuning and Tweaking Your list of labels might be raw, coming straight from your content, another system, your environment’s users, or your own ideas of what should work best. Or, it may come straight from a polished controlled vocabulary. In any case, it’ll need some work to become an effective labeling system.

First, sort the list of terms alphabetically. If it’s a long list (e.g., from a search log), you’ll likely encounter some duplicates; remove these.

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Then review the list for consistency of usage, punctuation, letter case, and so forth, considering some of the consistency issues dis‐ cussed earlier in this chapter. This is a good time to resolve these inconsistencies and to establish conventions for punctuation and style.

Decisions about which terms to include in a labeling system need to be made in the context of how broad and how large a system is required. First, determine if the labeling system has obvious gaps. Does it encompass all the possibilities that your environment may eventually need to include?

If, for example, your online store currently allows users to search only a portion of your product database, ask yourself if eventually it might provide access to all products. If you’re not certain, assume it will, and devise appropriate labels for the additional products.

If the environment’s labeling system is topical, try to anticipate the topics not yet covered. You might be surprised to see that the addi‐ tion of these “phantom” labels has a large impact on your labeling system, perhaps even requiring you to change its conventions. If you fail to perform this predictive exercise, you might learn the hard way that future content doesn’t fit into your system because you’re not sure how to label it, or it ends up in cop-out categories such as “Mis‐ cellaneous,” “Other Info,” and the classic “Stuff.” Plan ahead so that labels you might add in the future don’t throw off the current label‐ ing system.

Of course, this planning should be balanced with an understanding of what your labeling system is there to accomplish today. If you try to create a labeling system that encompasses the whole of human knowledge (instead of the current and anticipated content of your website), don’t plan on doing anything else for the rest of your life. Keep your scope narrow and focused enough so that it can clearly address the requirements of your environment’s unique content, the special needs of its audiences, and the business objective at hand, but be comprehensive within that well-defined scope. This is a diffi‐ cult pursuit, to be sure—all balancing acts are.

Finally, remember that the labeling system you launch will need to be tweaked and improved shortly thereafter. That’s because labels represent a relationship between two things—people and content— that is constantly changing. Stuck between two moving targets, your labeling system will also have to change. So be prepared to perform

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usability tests, analyze search logs on a regular basis, and adjust your labeling system as necessary.

Recap OK, let’s recap what we learned in this chapter:

• We label things all the time. • Labeling is the most obvious way to show our organization

schemes across multiple systems and contexts. • We must try to design labels that speak the same language as

our environment’s users, while also reflecting its content. • Textual labels are the most common type we encounter in our

work; they include contextual links, headings, navigation system options, and index terms.

• Iconic labels are less common, but the widespread adoption of devices with less screen real estate means that they are an important component of many information environments.

• Designing labels is one of the most difficult aspects of informa‐ tion architecture.

• That said, there are various sources of inspiration—such as your existing information environment and search log analysis—that can help inform your labeling choices.

Let’s now move on to Chapter 8, where we’ll dig into one of the mainstays of effective information architectures: navigation systems.

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