Summary:

Different traffic sources imply different reasons for why visitors
might immediately leave your site. Design to keep deep-link followers
engaged through additional pageviews.

A huge increase in “deep dips” was one of the big findings in our new user research for this year’s Fundamental Guidelines for Web Usability seminar. That is, ever-more users are arriving deep within websites rather than entering them through the homepage.

The homepage is still important, and you should continue to ensure homepage usability for two main reasons:

• The homepage is typically the single most-visited page, because the deep entry points are scattered across a vast number of interior pages.
• The homepage is the orienteering point for visitors who arrive through deep links and then decide to explore the site further.

For many sites, the deep-dip increase has an unfortunate consequence: much bigger bounce rates.

The bounce rate is defined as the percentage of
visitors who turn around at the entry page and immediately leave the
site. Such visitors “bounce” out and never see additional pages.

“Unique Visitors” Must Die

Given growing bounce rates, we must stop using “unique visitors” as a metric for site success. Site tourists who leave a site immediately ratchet up the unique visitor count, but don’t contribute long-term value.

On the contrary, bouncers should be considered a negative statistic: the site failed to engage them enough to entice even a second pageview.

To measure site success, you should count only loyal users
who return repeatedly. Or, if your site is such that most people will
visit only once, at least require that they exhibit a minimum amount of
engagement before you count them as a positive statistic.

Chasing higher unique-visitor counts will undermine your
long-term positioning because you’ll design gimmicks rather than build
features that bring people back and turn them into devotees and
customers.

Analyzing Bounce Rates by Entry Source

As with all quantitative methods,
Web analytics is a dangerous game. If you measure the wrong thing, your
metrics won’t just be weak — they’ll be directly misleading and might cause you to pursue an erroneous strategy that reduces your design’s business value.

In this case, it’s important to realize that there’s no such thing as a
single bounce rate; you must analyze bounce rates separately for the 4 sources of visitors (ordered by their level of commitment to your site):

1. Low-value referrers,
   such as Digg. People arriving through these sources are notoriously
   fickle and are probably not in your target audience. You should expect
   most of them to leave immediately, once they’ve satisfied their idle
   curiosity. Consider any value derived from Digg and its like as pure
   gravy; don’t worry if this traffic source has a sky-high bounce rate.
2. Direct links from other websites. These links are the equivalent of a vague recommendation: “You might want to check out this site.”
   People who click such links haven’t expressed a direct intent to engage
   with your topic to the same degree as someone who actively enters a
   search engine query. These visitors do have some degree of interest,
   however, so a high bounce rate is a symptom of a user experience
   problem.
3. Search engine traffic,
   whether from organic SEO or paid links. By clicking your link, these
   users have actively indicated an acute interest in the topic and should
   engage intensely with your content. If they leave immediately, it’s a
   sign that something is seriously wrong with your landing pages.
   • Note: for some search keywords, you’ll rank highly
     even though you don’t serve the user intent that the keywords express.
     Obviously, people who come looking for something you don’t have will
     leave. Because they’re not your customers, you shouldn’t worry about a
     high bounce rate from these visitors.
4. Loyal users who
   return repeatedly to your site. On the one hand, you’d expect the
   highest engagement from your biggest fans. On the other hand, this
   engagement might not show up on every visit if they visit often. As
   long as people keep coming back, there’s nothing wrong with having them
   sometimes leave after a page view or two.
   • As an example, when I send out my email newsletter announcing a new
     Alertbox column, there’s a flood of visits from my subscribers to that
     page. Of these visitors, only 10% click on to additional pages. I
     expect that, however, because long-term subscribers have already read
     most of the earlier articles I link to. Also, it usually takes about 3
     years before new subscribers can convince their bosses to send them to
     my conference, so I don’t expect them to repeatedly click through to
     in-depth course descriptions of the topics I briefly cover in a column.

The following chart shows a rough visualization of the
expected bounce rates from the four user-interest levels. The rates
resemble an inverted checkmark:

Intranet Bounces

Even though bouncing users may seem most common on websites, they are
also found on intranets. Here, employees are predisposed to accept the
validity of a page or section, since it’s the official company
intranet, after all. Thus, intranet bounces are usually symptoms of
poor navigation or poor use of related links, as well as poor section
landing pages. (For more on all these topics, see the report on Intranet Information Architecture [IA].)

Getting One More Pageview

Depending on the source of visitors, your bounce rates might be high or
low. But, except for low-value visitors, you should certainly strive
for fewer bounces.

In one of our case studies on the Return on Investment (ROI) from usability,
a website reduced its bounce rate from 30% to a minuscule 2.5% through
a simple redesign. Even if you can’t always cut your bounce rates to
one-tenth their previous levels, simple changes can often lead to
substantial improvements.

First and foremost, test your site with
representative users. You’ll almost always find striking ways in which
you repel visitors through low-credibility design, fluffy content, or
confusing navigation.

Second, expose some next steps for people to take if they’re interested in the current page. There are two good approaches here:

• A linear information path offering a single link
  to either follow-up information or a deeper treatment of the topic.
  Place this link at the bottom of the page, where people are (hopefully)
  motivated to learn more. (But don’t use the lame follow-up link employed by the New York Times, which refers people to “more articles” without listing a specific, relevant article.)
• Contextual see-also links can provide
  multiple pointers to key places of interest to people who liked the
  current page. Specific links are vastly superior to generic navigation
  menus for this purpose.

Third, if you have a product or service that alleviates the
pain point that motivated visitors to seek out the deep link, you
should say so explicitly (and link directly to it), instead of hoping that people will find the right page by perusing your product catalog.

http://www.useit.com/alertbox/bounce-rates.html

At its simplest form, it means that if you take a bunch of people
and ask them (as individuals) to answer a question, the average of each
of those individual answers will likely be better than if the group works together to come up with a single answer. And he has a ton of real examples (but you’ll just have to read the book for them ; )

[Also] diversity increases the quality of the aggregated wisdom of the group.
If you have too many people who are alike, then no matter how smart
they all are, they may not come up with the same quality of answer than
if you have less smart folks who have a very different point of view. Diversity brings new information. And that new information is valuable.

In order for the crowd to have wisdom, the crowd has to be made up of individuals who argue! Or as he puts it in the book,

“Diversity
and independence are important because the best collective decisions
are the product of disagreement and contest, not consensus or
compromise. An intelligent group, especially when confronted with
cognition problems, does not ask its members to modify their positions
in order to let the group reach a decision everyone can be happy with.
Instead, it figures out how to use mechanisms–like market prices, or
intelligent voting systems–to aggregate and produce collective
judgements that represent now what any one person in the group thinks
but rather, in some sense, what they all think.”

And my favorite line that sums it up:

“Paradoxically, the best way for a group to be smart is for each person in it to think and act as independently as possible.”

http://headrush.typepad.com/creating_passionate_users/2005/03/one_of_us_iisi_.html

After you launch campaigns, continue to test them for conversion
metrics and adjust your top bid accordingly. Many marketers think that
if the clickthrough rate is higher, the keyword should be more
expensive. But you should determine the value of a keyword based on
conversion rate, not clickthrough rate, because you only pay by the
click.

Heads or tails?
Head keywords are generic terms
that people search while browsing or doing product research, such as
“mp3 player.” Head keywords often benefit from being in first position,
because they capture a lot of “browsers” who just click on the first
link and may be exposed to your site for the first time. These people
may not buy now, but they’ll connect with your brand.

Tail keywords are often best in third or fourth position. These
keywords are specific and appeal to committed buyers, such as “black
ipod nano 8gb.” People searching for these keywords are usually more
ready to buy, so they’ll look at — and even click through
– several ads to find the best deal, even if that deal appears in
a link halfway down the page.

The upshot? Head terms get much more volume and are often more
expensive to boot, so to justify your investment you may need to
measure carefully which visitors return to your website.

Set a top position
This is a tool on Google you
can use to hold your keywords down in the rankings, even if you are
bidding enough to be #1. It’s always better to figure out first how
much your keywords are worth to your bottom line, and then find out
where that places you. But this tool can be useful if you find that
position #1 gets a lot of poor quality traffic that never converts.

Focus on the dirty dozen
Most marketers spend the majority of their budgets on a few top keywords, usually about a dozen, which are high volume and
have a strong conversion rate. Focus on fixing the position of these
keywords first, because correctly placing these top keywords will have
the biggest impact on total revenues. Let the others fall where they
will according to their conversion rates as described above.

Turn off Google Search and Content Networks
If
you don’t opt out of Google’s search partners, like AOL and Ask.com,
your position numbers will reflect a blend of your positions across all
of those properties. To get an accurate picture of where your keywords
are positioned on Google itself, turn off the additional distributions.
You can always turn them back on after you finish your measurement.

Turn off Google Content Network. Ditto as above
To
figure out what your keywords’ true positions are, focus on Google
itself, not your position across all its content partners, such as New
York Times, MySpace and About.com.

Work weekends
Some keywords perform stronger on
the weekend, such as “gardening” or “beach wear,” for example. Set up
automatic bid increases for these terms to boost your position solely
on the weekends. (Google supports this at the campaign level; MSN
supports this at the Ad Group level; and Yahoo doesn’t support it right
now.) Remember: These boosts should be based on changes in conversion
rates, not click volume. Look for the pattern before you set the boosts.

Pony up for brand and “executive” keywords
If
you’re Coca-Cola, you just have to pay whatever it costs to have
“Coca-Cola” be in the top position — that’s crucial for your brand.
Plus you can use your company name in those brand-term ads, and other
advertisers cannot (call the support team at the search engine if you
see any violations of this). Likewise, if your CMO tells you the
company needs to be in top position for certain keywords, like “digital
camera” or “PC” to build your brand in those categories, then just pay
what it costs to be in the top spot (and pull the cost from the
branding budget!).

Chris Lien
http://www.imediaconnection.com/content/19624.asp

Summary:

Linear vs. non-linear. Author-driven vs. reader-driven. Storytelling
vs. ruthless pursuit of actionable content. Anecdotal examples vs.
comprehensive data. Sentences vs. fragments.

I’ve spent many columns explicating the differences between the Web and television, which can be summarized as lean-forward vs. lean-back:

• On the Web, users are engaged and want to go places and get things done. The Web is an active medium.
• While watching TV, viewers want to be entertained. They are in relaxation mode and vegging out; they don’t want to make choices. TV is a passive medium.

This doesn’t mean that you can’t have entertaining websites or
informative TV shows. But it does mean that the two media’s contrasting
styles require different approaches to entertainment and education.

The differences between print and the Web may not seem as strong,
but to achieve optimal results, each requires a distinct content style.

Example: Tall Travelers

I recently read an article in The New York Times about tall people’s travails on the road: “Coping With the Tall Traveler’s Curse.” The headline itself is actually an example of the differences between print and online content style:

• In print, a phrase like “tall traveler’s curse” is a bit enticing
  and might draw readers in. Because the article featured a photo of a
  tall guy crunched in the back of a taxi, the article’s content was
  clear to anybody glancing at that page in the newspaper.
• In contrast, putting the same headline online would fail several guidelines for writing for the Web:
  • The first 3 words have no information-carrying content. On the Web, you must start with words like “tall traveler” because users often scan down the left part of a list of items. They never see the last words in a link unless the first few words attract their attention.
  • The headline lacks keywords — such as
    “airline seat” and “hotel bed” — that are important for search
    engine optimization (SEO). No one will search “curse” when trying to
    find out which hotel chains offer extra-long beds or which airline
    seats are the least unpleasant for long-legged travelers.
  • The words “tall traveler’s curse” are insufficiently specific
    to tell users what the story is about. Because headlines are often
    presented as plain links removed from the article itself, the photo of
    the poor guy in the cab won’t be there to explain the story’s content.
    Online, the headline alone must provide enough information scent to let users predict what they’ll get if they follow the link.

Even though I’m not particularly tall myself, I read the entire article
in the printed newspaper. Why? Because it was well written and
contained several interesting anecdotes about tall business travelers,
ending with the story of a tall woman executive having to bend down to
use a hotel room makeup mirror.

I would never have read that same article on nytimes.com, because
the story lacks both immediacy and utility. Even though the article
surely attracted some pageviews online, it’s style is not optimal for
presenting information on the Web.

The Web rewards comprehensive coverage that’s more specific
than print content. On the Web, content for tall travelers should
feature ratings of airline seats and hotel beds for all the major
airlines and hotel chains, respectively. Even better would be to
differentiate coverage for tall men vs. tall women and for somewhat
tall vs. gigantically tall people.

This more detailed approach works online because the content is
searchable and you can sort and present it in personalized views for
each user. Say, for example, you’re 6-foot-8 (2.03 m) like the guy in
the article photo, and you’re flying United Airlines from San Francisco
to Chicago. A good site will tell you which departing plane has the
best seat configuration for you, and which seat you should book.

Narrative vs. Actionable Content

Print publications
— from newspaper articles to marketing brochures — contain
linear content that’s often consumed in a more relaxed setting and
manner than the solution-hunting behavior that characterizes most
high-value Web use.

In print, you can spice up linear narrative with anecdotes and individual examples that support a storytelling
approach to exposition. On the Web, such content often feels like
filler; it slows down users and stands in the way of their getting to
the point.

For example, in print, discussing the tall-friendly rooms in
the Palms Casino Resort in Las Vegas feels somewhat interesting. That’s
not the case online when a user is looking for tall-friendly rooms in
Chicago (or wherever he or she is going next week).

Web content must be brief
and get to the point quickly, because users are likely to be on a
specific mission. In many cases, they’ve pulled up the page through
search. Web users want actionable content; they don’t
want to fritter away their time on (otherwise enjoyable) stories that
are tangential to their current goals.

Instead of a predefined narrative, websites must support the user’s personal story
by condensing and combining vast stores of information into something
that specifically meets the user’s immediate needs. Thus, instead of an
author-driven narrative, Web content becomes a user-driven narrative.

Print’s narrative exposition calls for well-crafted, complete sentences. Online, less so. Fragments often let you pull information-carrying keywords to the front, while also reducing froufrou word count. Because Web users read only 18% of added verbiage, cutting words is well worth the accusing squiggles that MS Word will throw at your sentence fragments.

E-Learning: An Oxymoron?

I continue to believe in the linear, author-driven narrative
for educational purposes. I just don’t believe the Web is optimal for
delivering this experience. Instead, let’s praise old narrative forms
like books and sitting around a flickering campfire — or its
modern day counterpart, the PowerPoint projector — which have
been around for 500 and 32,000 years, respectively.

I continue to write books, and I continue to develop training seminars, because I believe these media are best for deep learning of new concepts.

We should accept that the Web is too fast-paced for big-picture learning. No problem; we have other media, and each has its strengths. At the same time, the Web is perfect for narrow, just-in-time learning
of information nuggets — so long as the learner already has the
conceptual framework in place to make sense of the facts.

For example, I dated “learning around the campfire” to 32,000 years ago
to coincide with the emergence of high culture and the Cro-Magnons. Not
that the Neanderthals didn’t have campfires — they simply didn’t
have the cultural depth of modern humans, so I don’t think their
storytelling was equal to my seminars. So, did I actually remember that
Cro-Magnon culture started 32,000 years ago with the Lascaux cave
paintings? No, I looked that little fact up online.

Writing for Selfish Readers

In linear media — such as print and TV — people expect you to construct their experience for them. Readers are willing to follow the author’s lead.

In non-linear hypertext, the rules reverse. Users want to construct their own experience
by piecing together content from multiple sources, emphasizing their
desires in the current moment. People arrive at a website with a goal
in mind, and they are ruthless in pursuing their own interest and in rejecting whatever the site is trying to push. Banner blindness is only the most extreme manifestation of this selfishness.

Particularly on commercial sites — whether they’re B2C e-commerce or specialized B-to-B
sites — users cherry-pick the information and concentrate
narrowly on what they want. If you’re smart, you’ll write accordingly:
make your content actionable and focused on user needs.

http://www.useit.com/alertbox/print-vs-online-content.html

Clicking on Sport gets you to a left column navigation beginning
with: Football, Cricket, Rugby Union, etc. (Notice it is not
alphabetical; it begins with the most popular, Football.)

Clicking on Football removes all the other Sport options and
shows you just Football ones. What if someone is interested in
Cricket? If I was interested in Cricket I’d have clicked on
cricket.

You keep clicking until you select, say, Manchester United. In
the left navigation you now see links such as Squad Selector,
Results, Fixtures, etc. The worst navigation systems would
continue to offer you Cricket in the left navigation. Of course,
that would result in a huge list of links in the left navigation
that would cause great confusion.

Gerry McGovern
mailto:gerry@gerrymcgovern.com
http://www.gerrymcgovern.com/nt/2008/nt-2008-06-02-navigation.htm

In 2007, podcasts served 18.5 million users in the US — a figure projected to rise to 65 million by 2012 (eMarketer).

These tips for launching an engaging podcast will help you build a loyal and responsive brand audience.

1. Plan your podcast schedule. An engaging podcast is more than a “one-off” episode. Plan each in advance, and launch them on a consistent day and time.

If you broadcast weekly, publish a monthly schedule so listeners get a sense of what to expect. Stick to your schedule — inconsistency encourages even devotees to look elsewhere.

2. Make it RSS-accessible. A downloadable mp3 file
is only one component of a podcast. Enable people to subscribe via RSS
so they can retrieve updates automatically.

3. Keep it short. It’s not a one-hour radio show.
Brevity encourages relevance. Unless you have a strong feature, don’t
press listeners’ patience.

A typical episode of The Wall Street Journal’s “Your Money Matters” podcast lasts a little over five minutes.

4. Don’t waste time hard-selling. Don’t discuss
your product or service all the time. When you do, invite a client or
user to speak frankly about it on air. It’s okay to promote a website
if the site contains content relevant to the episode.

5. Segment your podcasts. Think “Client Talk,” “Tip
of the Day,” “Your Questions Answered,” that kind of thing. Content
segments give listeners bearings and yield a sense of familiarity with
your podcast’s ebbs and flows. This is key to the success of any series.

6. Simplify podcast management. Keep your recording process and RSS feed management simple, so you can focus on developing content (the tough part).

Garageband, Gcast.com, ClickCaster.com and Audacity are the most
popular programs for recording podcasts. FeedforAll helps with editing,
and its simple GUI eases management of RSS feeds.

7. Submit your podcast to popular directories. iTunes lets users submit podcasts from within its program; here are some podcasting resources from Apple.

Pinging services like Autopinger and Pingoat will submit podcast
updates to major blogs and search engines. Burn your podcast with
Feedburner, which allows you to notify listeners about new episodes
through email updates.

8. Build a compelling podcast website. Any ad
campaign or product launch should have its own web destination, loaded
with up-to-date and relevant information. Your podcast is no different.
Keep the site updated with your podcast schedule, and website-only
tidbits, to build listener loyalty.

Bonus features on the website will go a long way. Coffee Break
Spanish uses its site to sell written transcripts of its free audio
lessons. The website is also the place for visibly advocating your
product or brand.

9. Let website visitors commune with one another. Provide listeners with a newsgroup so they can interact. You can also start a Facebook group or invite them to follow you on Twitter.

10. Measure and analyze. None of this does much good if you’re not keeping metrics on your progress. Some handy tools:

• Google Analytics helps track users and audio file downloads
• Feedburner lets you measure the number of unique subscribers per episode
• Podtrac and Volomedia help you gain deeper insight in behavioral and demographic data

Happy podcasting.

This MarketingVOX How-To was written by Arun Krishnan, VP of Marketing at Pontiflex. His podcast, “Learn Hindi from Bollywood Movies,” has been running since 2006.

• Size DOES matter: Bigger donate buttons helped convert more donors
• Color can matter too: A vividly colored donation button can strongly boost donation page conversion…but seasonality and color choice influenced whether it did
• Less is more: Removing unnecessary fields from the personal information form significantly increased conversion to donate
• Remind people (nicely) why they want to donate: Polite header copy (“Please make a tax-deductible gift…”) followed by short appeal copy yielded better conversion than a more forceful call-to-action (“Donate Now! Help us…”) without appeal copy􀀁
• No need to be demanding: Using firmer language on the donation button (“Donate Now” instead of “Submit”) did not produce statistically higher conversions

1. Information on copyright releases can be found here.
2. As to the conflict-of-interest issue, the thing to do is first to
   request that some impartial third party create an article, a thing done
   here.
3. If an editor agrees that the organization passes muster under WP:GROUP, and an article is
   created, then COI persons would make suggestions on the talk page of
   the article, and other editors would take up the suggestions they found
   most useful.
4. (I’d advise you to clarify the relationship between OPA,
   the WWF, etc., because I was having trouble figuring it out from the
   pages.)

Summary:
On the average Web page, users have time to read at most 28% of the words during an average visit; 20% is more likely.

We’ve known since our first studies of how users read on the Web that they typically don’t read very much. Scanning text is an extremely common behavior for higher-literacy users; our recent eyetracking studies further validate this finding.

The only thing we’ve been missing is a mathematical formula to quantify exactly how much (or how little) people read online. Now, thanks to new data, we have this as well.

The Research Study

For full details, see the following academic paper:

Harald Weinreich, Hartmut Obendorf, Eelco Herder, and Matthias Mayer: “Not Quite the Average: An Empirical Study of Web Use,” in the ACM Transactions on the Web, vol. 2, no. 1 (February 2008), article #5.

In the study, the authors instrumented 25 users’ browsers and recorded extended information about everything they did as they went about their normal Web activities. What’s important about this study is that it was completely naturalistic: the users didn’t have to do anything special.

One downside of the study is that the users had above-average intelligence, with several being university employees. This might not be a problem in the long run, however. If, for example, we compare data we collected in 2008 for our Fundamental Guidelines for Web Usability seminar with a similar study we ran in 2004, we find that 2008’s average behavior is close to that of 2004’s higher-end users. Thus, even though Weinreich et al.’s data represents high-end users, it’s likely to be fairly representative of broader user behavior in the future. In fact, the authors collected their data in 2005, so the recorded behaviors might already be fairly common.

In any case, the research yielded several interesting findings, and the full paper is well worth reading.

Among other things, the authors found that the Back button is now only the 3rd most-used feature on the Web. Clicking hypertext links remains the most-used feature, but clicking buttons (on the page) has now overtaken Back to become the second-most used feature. The reason for this change is the increased prevalence of applications and feature-rich Web pages that require users to click page buttons to access their functionality.

Of course, Back is still the user’s lifeline and is so frequently used that supporting it remains a strong usability guideline.

Real-Life Reading Behavior

Harald Weinreich graciously provided me with the dataset detailing 59,573 page views.

From this data, I removed the following records:

• 10,163 page views (17%) that lasted less than 4 seconds. In such brief “visits,” users clearly bounced right out without truly “using” the page.
• 2,615 page views (4%) that lasted more than 10 minutes. In these cases, users almost certainly left the browser open while doing something else.
• 1,558 page views (3%) with fewer than 20 words on them. Such pages are probably server errors or disrupted downloads.

After cleaning the dataset, I was left with 45,237 page views for my analysis.

I was able to fit very nice formulas to describe users’ reading behavior for pages containing between 30 and 1,250 words. For longer pages, reading became quite erratic. Pages with a huge word count are probably not “real” pages anyway — they’re more likely to be either academic papers or “terms & conditions” pages, which people don’t give the time of day. (In research for the book Prioritizing Web Usability, we found that people read only about 10% of the text that they supposedly “agreed” to.)

The following chart shows the average time users spend on pages with different word counts:

Obviously, users tend to spend more time on pages with more information. However, the best-fit formula tells us that they spend only 4.4 seconds more for each additional 100 words.

Usually, I assume a reading speed of 200 words per minute (WPM), but because the users in this study are highly literate, I’ll go with 250 WPM. At that reading speed, users can read 18 words in 4.4 seconds. Thus, when you add verbiage to a page, you can assume that customers will read 18% of it.

Percentage of Text Read

This wasn’t an eyetracking study, so we don’t know precisely how users allocated their time on the Web pages. The formula in the chart above indicates that there is a fixed time of about 25 seconds, plus an additional 4.4 seconds per 100 words. (Of course, the numbers are not “fixed” in the sense that they’re always the same — these are averages.)

The formula seems to indicate that people spend some of their time understanding the page layout and navigation features, as well as looking at the images. Clearly, people don’t read during every single second of a page visit.

However, the total time spent on a page is definitely the upper limit of possible reading time. Thus, we can calculate the hypothetical maximum number of words users would be able to read, if they allocated their entire page-visit to reading.

The following chart shows the maximum amount of text users could read during an average visit to pages with different word counts:

This is a very rapidly declining curve. On an average visit, users read half the information only on those pages with 111 words or less.

In the full dataset, the average page view contained 593 words. So, on average, users will have time to read 28% of the words if they devote all of their time to reading. More realistically, users will read about 20% of the text on the average page.

As an example of word count on various pages, here’s the total for some popular Alertbox columns:

Clearly, the average visitor won’t make it too far through most of my articles. But I’ve consciously targeted a small, elite readership with a firm commitment to usability. If you target a broader audience or have sales cycles that are shorter than 5 years, you’d be wise to put your word count on a strict diet.