Below are the celebrities for whom I’ve been able to analyze at least 100 links shortened through the bit.ly service. I define “clickthrough rate” as the average number of clicks on the links they Tweeted divided by the number of followers the accounts had.

Got a favorite celebrity? Want to Tweet about their clickthrough rate?

• @KhloeKardashian gets a 1.56% clickthrough rate   Tweet This
• @stephenfry gets a 1.12% clickthrough rate   Tweet This
• @KimKardashian gets a 1.09% clickthrough rate   Tweet This
• @alyssa_milano gets a 0.98% clickthrough rate   Tweet This
• @selenagomez gets a 0.91% clickthrough rate   Tweet This
• @shakira gets a 0.73% clickthrough rate   Tweet This
• @feliciaday gets a 0.69% clickthrough rate   Tweet This
• @alyankovic gets a 0.66% clickthrough rate   Tweet This
• @lancearmstrong gets a 0.64% clickthrough rate   Tweet This
• @PerezHilton gets a 0.6% clickthrough rate   Tweet This
• @rainnwilson gets a 0.48% clickthrough rate   Tweet This
• @wilw gets a 0.44% clickthrough rate   Tweet This
• @tonyrobbins gets a 0.43% clickthrough rate   Tweet This
• @biz gets a 0.4% clickthrough rate   Tweet This
• @mrskutcher gets a 0.36% clickthrough rate   Tweet This
• @jtimberlake gets a 0.32% clickthrough rate   Tweet This
• @RyanSeacrest gets a 0.29% clickthrough rate   Tweet This
• @aplusk gets a 0.28% clickthrough rate   Tweet This
• @SnoopDogg gets a 0.26% clickthrough rate   Tweet This
• @chelseahandler gets a 0.25% clickthrough rate   Tweet This
• @jimmyfallon gets a 0.24% clickthrough rate   Tweet This
• @ParisHilton gets a 0.22% clickthrough rate   Tweet This
• @MarthaStewart gets a 0.21% clickthrough rate   Tweet This
• @mashable gets a 0.19% clickthrough rate   Tweet This
• @algore gets a 0.18% clickthrough rate   Tweet This
• @50cent gets a 0.12% clickthrough rate   Tweet This
• @brookeburke gets a 0.11% clickthrough rate   Tweet This
• @johnlegend gets a 0.1% clickthrough rate   Tweet This

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Taking an idea from hip hop culture, I’m organizing a new kind of Tweetup: Social Media Battles.

Each battle will be composed of 2 people representing opposing viewpoints on a social media topic. They’ll each be given 2 minutes to make their case, and 1 minute rebuttals to their opponents, then the audience will decide the winner. Fast, simple and honest. We’ll do a bunch of these depending on how many people want to step up to the plate and battle.

The first one is going to be during FutureM week here in Boston on the evening of October 7th at the HubSpot offices in Cambridge, mark it on your calendars.

If you’ve got ideas for topics to debate, please leave them in the comments. And if you’re feeling brave and want to battle, email me.

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This tool will show you the 20 most ReTweetable words about any given topic. Simply enter a keyword (like “marketing”) and click analyze. The tool will return a list of words that were found to be related to that word and highly ReTweetable. It will also display the number of Tweets and ReTweets analyzed to generate the list.

Each word is recalculated after 24 hours, and the tool analyzes up to 1500 Tweets and 1500 ReTweets per word. Therefore the most ReTweetable words displayed represent the most contagious topics recently.

The tool works by comparing words found in ReTweets against how commonly they appeared in non-ReTweet Tweets, and identifies those words that appear in ReTweets more than they do in non-ReTweets.

It does take a few moments to analyze a new word for the first time, so please be patient. And this tool is very beta, so expect some (read: plenty) bugs. There are some known issues with multiple word searches.

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In the first two experiments, I split tested ReTweet buttons with different ReTweet counts shown on blog posts. First I compared “0 Tweets” with “776 Tweets.” The results were exactly the opposite of what I expected. After 36 hours, the button showing no Tweets had been clicked more than double the times the other button had. The sample size and variation performance are statistically significant, and the results show a 96% confidence level.

While discussing these results with Alison, she suggested that they may have been due to a “first post” effect, where people want to be the first to share a piece of content. So I tested a button showing “15 Tweets” against one showing “776 Tweets.”

While the post I used for this test was more popular, the results of the experiment showed a far less significant difference between the two buttons. The “15 Tweets” button performed marginally better, but the low confidence value means there is probably no meaningful difference between the two buttons.

The results of the first two tests had me questioning whether or not social proof has the effect online I thought it did. My next step was to test the Feedburner subscriber count RSS button, which I believed was perhaps more likely to exhibit traditional social conformity effects.

I began by testing a button displaying “12 Subscribers” against one that displayed “62172 Subscribers.” The higher variation was clicked on a slight .13% more, and again this experiment’s confidence interval is too low to really be significant.

Finally, I decided to test the “first post” effect on the RSS button, by comparing a “0 Subscribers” button against the “62172 Subscribers” button. Again, the 62172 version did a little better, but failed to reach a statistically significant level.

In spite of the insignificant results I found in 3 of 4 tests, I believe my findings are interesting for a few reasons. First and perhaps most importantly, they represent a first step towards “contagiousness testing” which would allow marketers to apply split and multivariate testing methods to content virality.

An elongated test may reveal that higher showing a higher subscriber count on an RSS button, does lead to a small, but significant click-through increase.

These 4 experiments also suggest that there may be a powerful “first post” effect that marketers can leverage in certain situations. I plan to do more research into this in the future.

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1. Suggestibility

Suggestibility is a measure of how inclined a person is to act on the suggestions of other people. Research has shown that there is a correlation between how suggestible a person is and how hypnotizeable a person is.
Stage hypnotists spend a lot of effort on identifying the most suggestible people in their audience to bring up on stage. They’ve developed a wide range of quick tests to highlight those people who will demonstrate their abilities to the rest of the crowd, making them more suggestible as well. Clinical practitioners also have tests and scales of suggestibility and hypnotizeability.
In social media it is somewhat difficult to administer traditional stage or clinical tests, but once we understand that people who comply with initial, small requests are likely to engage in later, larger requests we can begin to identify the most suggestible of our audience. Simply asking people to joining mailing lists, ReTweet links, or supply comments are rudimentary forms of suggestibility tests.

2. Social Requests

Experiments conducted on highly suggestible people in 1998 showed that subjects who were given non-hypnotic social requests to send a series of postcards to the experimenters did so more often than those who were given hypnotic suggestions. While the social request subjects said their actions felt more “planned and effort-ful” and less “compulsive,” this seems to indicate that simple social requests can be just as powerful with subjective people as full-on hypnosis.
As marketers we should remember this research when we are constructing our calls-to-action. We can achieve the same levels of compliance as professional hypnotists with well formed social requests, especially when accompanied by the other lessons in this post.

3. Expectancy Manipulation

Clinical studies, including ones done by University of Connecticut researcher Irving Kirsch have shown that by creating the expectations of suggestibility, subjects can be made more suggestible than they’d otherwise be. Experiments were done in which subjects were given baseline suggestibility tests, then shown “evidence” that they were highly suggestible. When the subjects retook the tests, they registered as far more suggestible than they were before. Expectancy manipulations like this have also been show to work for pain, blood pressure and nausea reduction as well as increasing the effect of placebo medications.
One of the most common motivations for sharing content on social media is that people want to increase their personal reputations. As marketers we can take advantage of this, by increasing the expectation that sharing our content will do wonders for our audience’s reputation. One example would be retelling stories of how other people who’ve shared your content got more followers or Facebook friends.

4. Authority

Stage hypnotists work hard to establish an image of authority or “prestige and faith.” They rely on their audience’s belief (and expectations) that they are gifted hypnotists who always get results. They are also very quick to eliminate non-responsive subjects who would erode their effective image.
Memetics researcher Francis Heylighen has pointed out that for an idea to spread it has to come from a source that is authoritative in some regard, so did WWII rumor-weapons experts.
In social media we should work to always appear authoritative, without saying so much our self often. Subtle indications of social proof like high subscriber or follower counts can help.

5. Psychological Barriers

Stage and clinical hypnotists engage typically have a speech they give to their subjects prior to hypnosis called a “preinduction talk.” The idea of the talk is to establish rapport, remove the fears, about hypnosis, and establish favorable expectations.
Developing rapport with your audience as a marketer is generally a long-term strategy, but the more you can align your own interests and motivations with your audience the better. To make your audience identify with you, you need to make it clear that you understand their problems and desires. It is also useful to ingratiate yourself with your audience by remaining humble and frequently commenting on their intelligence. Remarks like “you guys are smarter than I am, so I need your help,” satisfy both the identification and the ingratiation demands.
Our readers understand that every piece of content they share in social media will be viewable by their friends. If you’re asking them share something they might be embarrassed by, do your best to anticipate their social fears and assuage them before you ask them to share.

6. Direct Suggestions

In their 1956 book on hypnosis, Charles Edward Cooke and A.E. Van Vogt discuss how to structure therapeutic suggestions. They give three “rules” that can be applied to social media calls-to-action: “Be Positive,” “Be Specific,” and “Be Detailed.”
In explaining how to alleviate phobias through hypnosis, they explain that by saying “you are not afraid” you are creating a large mental image of “fear” with a small label “not.” Negation requires higher level mental processing to understand, so avoid calls-to-action like “don’t hesitate to ReTweet,” state everything in the positive form.
They also direct the hypnosis operator to be as specific and detailed as possible. For social media calls-to-action this means that we should say things like “ReTweet this article by clicking on this link.” Avoid vague calls to “share” content, describe the action you want your reader to take as specifically as possible.

7. Repetition

Most hypnotic subjects reach deeper levels of trance each time they are inducted by a practitioner and the suggestions they are given likewise increase in power through repetition.
As marketers, not only can we enhance the power of our calls-to-action by repeating them more than once in a single piece of content, but we can also build on their effectiveness across touches with our audience. Each time a person interacts with you, the effectiveness of the above techniques will increase.

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In 2007, researchers at the Hewlett-Packard’ s Information Dynamics Laboratory in Palo Alto studied social news site Digg and found that “novelty within groups decays with a stretched-exponential law, suggesting the existence of a natural time scale over which attention fades.”

And Free University of Brussels research professor Francis Heylighen lists “novelty” as a criteria for a successful meme, saying “New, unusual or unexpected ideas or perceptions tend to attract the attention, and thus arouse the cognitive energy which will facilitate their assimilation.”

In our everyday lives we are exposed to many more stimuli than we could ever hope to consciously digest, so our minds have evolved to include a sophisticated filtering mechanism by which our attention is drawn only to the important bits. This selective attention can be triggered by things like hearing our name over the noise of a loud party, or by a change in something familiar.

We’ve all had the experience of noticing something different about someone or something we see every day. Perhaps a co-worker got a hair cut, or construction on our daily commute changes it. Were it not for the difference, we would have never actively focused our attention on these things since they’re so common place.

I follow several thousand people on Twitter, I’m subscribed to a few hundred blogs and I get a hundred or so emails a day. I (like nearly every one else on the web) am exposed to lots of ideas every day, in fact, many more than I could ever become consciously aware of and ponder. Before I ever have a chance to spread one of these ideas, I have to be come aware of it. Remember my Hierarchy of Contagiousness?

If someone wants to get my attention as an individual, they’d do best to personalize the message to me, and use my name to trigger my selective attention. But, if they (like most marketers) want to get the attention of many individuals they need to rely on novelty.

Many of the other characteristics of contagiousness I’ve come across, such as social proof or scarcity, contain fairly obvious ways for marketers to use them to our advantage. But novelty isn’t quite so easy, we don’t always have an endless supply of breaking news at our disposal.

As an individual, I’ll consider an idea novel if I’ve never heard of it. It doesn’t have to something no one has ever heard before, just new to me. This opens up an entirely new set of possibilities for being novel without being breaking news.

In a 2002 study on attention and memory in advertising in the Management Science journal, researchers found that: “advertisements that were both original and familiar attracted the largest amount of attention to the advertised brand.” This means that we should use a tactic I like to call “new/old” to design novel content that is also intuitive for readers.

“New/old” is a structure where either new content is put into a old structure, or old content is put into a new structure. An example of the former is steam punk, where sci-fi gadgets are constructed from steam-age technology, and an example of the former the Newest Romeo and Juliet movie, where an old play was set in the modern day.

So if you have existing content or ideas, try fashioning them into a new structure, as the authors of Tough Love, a business book written as a screenplay have done. Conversely if you have an entirely new idea you’re trying to communicate, reach for a familiar structure.

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Write with nouns and verbs, not with adjectives and adverbs. The adjective hasn’t been built that can pull a weak or inaccurate noun out of a tight place… it is nouns and verbs, not their assistants, that give good writing its toughness and color.
The Elements of Style

And now we have the data to prove that they were right all along.

By analyzing my Facebook data set to study the relationship between parts-of-speech and Facebook sharing, I found that adjectives and adverbs don’t perform as well as regular, plain old nouns and verbs.

So re-read your Strunk & White and remember that when you’re writing for Facebook, use nouns and verbs.

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If you want to know more about my dataset and methods, read this.

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I analyzed the words that occurred most often in titles in my dataset and their effect on Facebook sharing and found a set of “highly shareable” words.

What I found was that list-based superlatives like “best” and “most” work pretty well on Facebook and that contain that explains something “why” and “how” also does.

If you want to know more about my dataset and methods, read this.

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This time, I applied the two linguistic algorithms (RID and LIWC) that power TweetPsych to my Facebook sharing data set and found an interesting, if not entirely surprising phenomenon.

Articles in my dataset that include sexual references in their titles, are shared on Facebook far more than the average story. Additionally, positivity is more shared than negativity. If you want to your blog post or article shared on Facebook, it’s a trying writing (positively) about sex.

If you’re curious about my methodology and dataset, read this page.

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What I found was that as the reading grade level required to understand the title of an article increased, the number of times it was shared on Facebook decreased. The takeaway? Use simple language if you want to get shared on Facebook.

If you’re curious about my methodology, start by reading this page.

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The first-of-its-kind committee will be chaired by Harvard Economist Edward Glaeser, and will meet four times in 2010 to discuss how Boston can attract and retain the skilled labor workforce that will enable our city to compete in the 21st century.

I want to tap your brains, what ideas do you have? We have a wealth of smart, tech-savvy people (like you guys) in Boston and it’s time to start putting our money where our mouth is to make Boston a seriously leading-edge place. How can Boston become a more innovative city?

The Hashtag for the committee will be #FutureBOS, so if you want to tweet your ideas, use that.

The list of committee members reads like a who’s-who of Boston innovators:

• Klare Allen Environmental Activist and Boston Housing Authority Resident
• George “Chip” Greenidge Executive Director of National Black College Alliance & The GREATEST MINDS
• Pat Johnson President, College Democrats of Massachusetts Chairman of Governor Patrick’s Statewide Youth Council
• Bryan Koop Senior Vice President, Boston Properties
• Ted Landsmark President and CEO, Boston Architectural College
• Barbara Lynch Restaurant Owner
• Jill Medvedow Director, Institute of Contemporary Art
• Diane Paulus Artistic Director, American Repertory Theater
• Rocio Saenz President, SEIU Local 615
• Kairos Shen, Ex Officio Director of Planning, Boston Redevelopment Authority
• Greg Bialecki, Ex Officio Secretary, MA Housing and Economic Development

The first meeting will be held April 7th, from 4 to 6pm at the Skywalk Observatory at the top of the Prudential Building, so if you have any interest in how the city can leverage web and social media technologies to make Boston a more innovative place, be sure to attend if you can.

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I first began to formulate this framework as a model for understanding how ReTweets work (If you’re interested in my Science of ReTweets study, check out my live webinar Friday). But I think the concept extends far beond just Twitter in fact, it is a framework for understanding criteria required for an individual to share any kind of content. Each of these criteria has a corresponding action we as marketers can take to increase the contagiousness of our content and ideas.

As you can see there are three criteria and together they form a funnel of decreasing volumes, like a sales conversion rate funnel.

1. A person must be exposed to your content to ever have a chance of spreading it. This means they have to be following you on Twitter, fans of your page on Facebook, on your email list etc.
2. The person must become aware of your specific piece of content before they can spread it. They have to read your Tweet or open your email.
3. That person must be motivated by something (generally in the content itself) to want to share it with their contacts.

Every piece of content, social network and campaign has vastly different conversion rates at each step of this process but, to understand the scales involved, it helps to visualize a hypothetical set of percentages. The gray boxes on the left of the graphic above represent assumed numbers: if you email 900 people and 20% of them notice and open the email and then 10% of those readers are forward it to a friend, your email was shared 18 times.

At each step we can change the numbers in our favor:

1. Increase the number of people exposed to your content by building your reach. Get more email subscribers or Twitter followers.
2. Create attention grabbing content. Do lots of testing on your subject lines to increase open rates.
3. Include powerful viral calls to action.

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The next Facebook sharing data point I analyzed is the presence of numbers (in digit form, 1 through 9) in titles. In a wide range of marketing arenas digits have been shown to perform very well. They tend to help conversion rates in the form of prices and on social news sites like Digg “Top 10″ style posts have always done well.

The difference isn’t huge but according to my data, articles with digits in their titles tend to be shared more on Facebook than stories without digits. I found that most articles in my data set didn’t use numbers in their titles, and you can see the scale of difference in volumes in the gray bars at the bottom of the chart.

For details on my methodology start with this post, then read

• Tweet This!
• Share this on Facebook
• Share this on del.icio.us
• Share this on LinkedIn
• Share this on Reddit
• Sphinn this on Sphinn
• Stumble upon something good? Share it on StumbleUpon
• Share this on FriendFeed

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While I found less articles posted on the weekends (notice the gray bars at the bottom of the graph which indicate volume of URLs analyzed for each day), those stories that were published on the weekends tended to be shared on Facebook more, on average, than stories that were published during the week. The reasons for this probably include the fact that more than half of companies in the US block Facebook, so people can only use the social network at home, on the weekends. Additionally, the mainstream Facebook audience does not use Facebook for work.

The takeaway? If you want your article to be shared on Facebook by your readers, try posting it over the weekend.

For information on my methodology, start with this page. For this data point I’m using over 5000 stories and “average” is the interquartile mean which is less sensitive to outliers. The 0% line indicates the average number of “shares” stories from each site in my study get, when the line is above 0% it means that stories on that day are shared more than the average, and when it is below, they’re shared less. If you’re curious why it appears most of the stories in the data set are above average, this is because of the difference in the volume of published stories on various days.

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It turns out that those stories that indicated they contained videos were shared more than the average story on Facebook, while they were actually shared less than the average story on Twitter. This is likely because the Facebook platform makes it easy to embed multimedia content into updates while Twitter does not.

The takeaway here? Facebook may be a better platform for your videos to go viral than Twitter.

And again, if you have any other datapoints you’d like to see, please let me know. I’m really excited about my new Facebook analysis capabilities and I’ve got a ton more stuff planned for you.

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I’ve begun by capturing links posted to social media sites from 10 extremely popular news outlets. Some of the top blogs, both mainstream and geeky, as well as a handful of the most web-enabled newspapers of record. Then I’m counting the number of times those links are shared on Facebook (in three different ways) and on Twitter (through good old ReTweets). I then find the average number of “shares” for links posted to each site and compare the individual stories to the average in percent form and then combine those numbers to get a percent “effect” as a positive or negative number away from the average.

At this point I’ve got well over a thousand links and counting with full information stored. I’m also getting better at retrieving the data I want faster and more reliably.

I’ve already got a bunch awesome of things to show you, so keep your eyes out for more, but first lets talk about “meta mentions.” A meta mention is when someone on a given site, say Facebook talks about Facebook, or when someone Tweets about Twitter. Typically with ReTweet data I’ve seen that talking about Twitter gets you a lot of ReTweets, and this is to be expected since most people on Twitter are into talking about Twitter. Of course with older technologies like email, people aren’t really “into” email so much as they just use it to get stuff done.

So far my data shows that while articles that use the word “Facebook” in their title get shared more often than the average story on both Facebook and Twitter, stories that mention “Twitter” actually get shared less on Facebook. My assumption here is that Facebook is less of the early adopter crowd that wants to sit around all day and talk about Twitter, while Twitter users are more likely to be social media geeks.

The key takeaway is to know your audience. If you want to go viral on Facebook, don’t talk about Twitter.

And since I’m just starting to get into Facebook data like this, what kind of stuff would you guys like to see?

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I like to call this kind of stuff “unicorns and rainbows.” Sure, it sounds good and makes you feel all warm and fuzzy, but it’s not actually based on anything other than “truthiness” and guesswork.

It’s the modern day equivalent of the witchdoctor or snake oil salesman. A couple of time-honored adages repeated ad nauseum, coupled with the unquestioning awe of an unaware audience, and pretty soon you’ve got an entire industry made of easy-to-agree with smoke and mirrors.

Problem is, bleeding with leeches and magical tonics don’t actually work. In fact, a lot of the time they do more harm than good.

And then along comes real science–real medicine and real data about what works and what doesn’t. Curing disease moved out of the dark ages and started making progress; now it’s time for social media to move past the unicorns and rainbows.

The great thing about the web is that nearly every interaction can be measured and observed in aggregates of tens and hundreds of millions. We can gather more qualitative and quantitative data about human behavior than at any other time in history. Yet the future of marketing, the very industry that is trying to push communications, business and public relations forward, is built on advice that comes from nothing more meaningful than soft-focus fantasies.

To the snake-oil salespeople, social media success isn’t something repeatable. It’s not the outcome of a process; it is black magic, guessing and praying.

Those of us who are a part of this social media thing now will be the forefathers of the next generation of marketing. We’re going to be the ones who decide how it plays out. Of course, there aren’t any formal degrees in this yet, and most of us don’t wear labs coats. But we need to decide if we are going to leave the future of social media to magical tonics, or if we are going to use science and data to discover what really works to motivate people.

To the scientists, social media success is something you can iterate on, plan for and learn from. Things that work can be analyzed to produce repeatable, dependable results.

The next time you see or read or hear someone giving superstitious, feel-good social media advice, question them. Ask what data it is based on, what science? Ask them to prove what they’re saying.

Most importantly ask yourself: are you a snake-oil salesman or are you a scientist?

And if you look around hard enough, I’m sure you’ll see that social media science is catching on. Its encouraging to see that there are at least 7 people on Twitter with “social media scientist” in their bios, lets blow that number up.

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In a 1983 article titled “On Viral Sentences and Self-Replicating Structures” the author, Douglas R. Hofstadter recounts a letter he was sent in response to a previous peice. This letter describes self replicating (viral) sentences, beginning with the rudimentary:

It is your duty to convince others that this is true.

The letter writer notes the obvious: unless the listener believes the statement above, it won’t spread. (Tweet this and see what happens.) He then moves on to a more sophisticated structure where the above sentance occurs at the end of a set of beliefs:

If the listener accepts statements S1 through S99 they will act on S100.This is how many religions work, the belief system is the bait and attached to it is an evangelism hook.

The letter then explores a more subtle variation based on a simple structure:

The villain is wronging the victim.

If the listener believes this statement, and believes that the victim deserves to be saved and if the villain is bigger or more powerful than them they will realize that the only way to effectively challenge the villain is to recruit more people to help. The evangelism hook is implicit, subtle and powerful.

When I looked at urban legends I found a similar phenomenon that occurs with striking regularity online called the Goliath effect. Simply put, people love to communicate about abuses of power against the underdog. Microsoft and the RIAA are favorite Goliaths of the web.

If we want to design a viral idea based on this structure, we have 3 blanks to fill: “villain,” “victim,” and “wronging.” For example let’s look at the title of one of my most popular blog posts ever:

“Twitter plans to Mangle ReTweets.”

The easiest way to make someone believe that he victim is worth saving is to make them identify with the victim, in this case anyone who ReTweets. ReTweeters were the target of this sentence, and given their contagious behavior, they make a wonderful audience.

The villain of this sentence is, of course, Twitter. They may not be a huge company, but they’re larger and more powerful in this area than any individual user. The only way someone could hope to #saveretweets would be to recruit all of their followers in the fight.

In the post I spent considerable time asserting and proving the “wronging” part. I explained why the proposed changes were going bad and needed to be stopped or at least challenged, this is the “bait” part in the figure above.

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Subtly

People like to think that everything they do comes from some logical, un-manipulateable part of their own brain. Doing what you’re told doesn’t feel as good as doing what you want to do, and nobody really wants to believe that what they “want to do” can be easily directed. This is especially true when it comes to sharing ideas and content with friends. Who would share something just because they’ve been told to by some marketer they don’t know?

The point here is that if you want to persuade your readers to spread your content, its not a great idea to whack them over the head with painfully obvious commands (although it will work in special instances, like when you’ve giving something away). You shouldn’t tell them what to do, you should make them want to do it in such a way that it feels like the idea was their own.

Motivation

There are a number of reasons why people spread ideas and content, and when you’re constructing your viral call to action, you should be leveraging one or more of these specifically.

If you get a group of marketers in a room together and ask them how to “make something go viral” one of the first things someone suggests is to give something away for free. And it works. People love free stuff and they’re often willing to do something for a chance to win. A pretty easy, if unimaginative and elementary way to get people to spread an idea or piece of content is to offer them a prize for doing so. This is perhaps the most surefire way to “go viral” and if you’re in a hurry to come up with a contagious idea, this is often your best bet. You’re essentially paying them to spread your content for you. The only concern with this tactic is that high-reach individuals will probably see right through it, and you’re unlikely to bribe someone with a size able audience this way.

When you directly ask people why they share things with their friends, the most common response is “relevance.” Things like “it seemed right up my friend’s alley” or “it made me think of so-and-so.” One fairly obvious CTA that exploits this motivation would be “send this link to your friends who’d be interested in it” or something to that effect. Its simple and obvious, but it might just work to a point.

My favorite, way to encourage this response, is the more subtle “combined relevance” technique that allows you to create content that seems personalized for a lot of people. Of course if you sent every one of your friends links to every piece of content that was relevant to them, that would be all you did. You’re going to need to hit on more powerful motivators than just relevance.

A 1983 article titled “On Viral Sentences and Self-Replicating Structures” the author, Douglas R. Hofstadter recounts a letter he was sent in response to a previous piece. This letter describes viral sentences beginning with the rudimentary: “It is your duty to convince others that this is true.”

The letter then explores a more subtle variation of that technique based on a simple structure: “The villain is wronging the victim.” If the listener believes this statement, and believes that the victim deserves to be saved and if the villain is bigger or more powerful than them they will realize that the only way to effectively challenge the villain is to recruit more people to help. Thus the motivation is powerful and the call-to-action itself is subtle.

For example let’s look at the title of one of my most popular blog posts ever:

“Twitter plans to Mangle ReTweets.”

The easiest way to make someone believe that he victim is worth saving is to make them identify with the victim, in this case anyone who ReTweets. ReTweeters were the target of this sentence, and given their contagious behavior, they make a wonderful audience. The villain of this sentence is, of course, Twitter. They may not be a huge company, but they’re larger and more powerful in this area than any individual user. The only way someone could hope to #saveretweets would be to recruit all of their followers in the fight.

I’ve written and talked about a bunch of different motivations and rather than detail each one of them here, I’ll list some of the best and link to more indepth studies of them.

• Social Proof and Cascades
• The Goliath Effect
• Combined Relevance
• Information Scarcity
• Social Exchange
• Warnings
• They-Might-Miss-It

Friction Reduction

As with any good call to action, you should have a very clear idea of the specific action you want your readers to take. Is it to share the blog post on Facebook? Is it to ReTweet you? Is it to email your YouTube video to all their friends? The most effective calls will likewise have a very specific aim.

Since you know precisely what you’re trying to persuade people to do, you should also be ale to understand how much time and effort it will take for them to do it. This time and effort is friction and the more friction presented to your potential spreaders, the less likely they’re going to be to share your content.

You can overcome a high friction action with a lot of motivation. If you want people to compose customized 500 word emails to 20 of their best friends with your link at the bottom, you’d better be offering them a very good reason for wanting to do so.

The other side of this problem is to reduce the amount of friction present. Asking people to click a single link to ReTweet or Digg something is asking very little of them. Creating a one-click sharing action is the holy grail of frictionless viral calls to action. But if you want them to do something that requires a bit more effort, like sending lots of emails, consider offering them some cut-and-paste text to use.

Timing & Placement

Consider for a moment, the tiresome marketing/dating analogy: if you go out on a first date, you wouldn’t propose marriage, so you shouldn’t ask someone to do something for you before you’ve provided them any value or built a relationship with them.

When we’re talking about viral calls to action there are two issues at play. One is that you want your calls above the fold in as prominent a location as possible, and the other is that you want to present your readers with the call to action exactly when they’re most likely to want to use it and share your content (which is typically after they’ve read it). The easiest solution is to put your buttons, links, whatever form your CTAs take in both places, that is at the beginning of your content and at the end.

In the case of a button, like the ReTweet or Digg buttons, the mere site of them becomes a form of social proof motivation. If a visitor sees that hundreds of people have already liked this content, they’re much more likely to percieve it as more valuable as well. With these types of calls to action you should place them where a visitor will see them upon first viewing your content.

There is also much to be said about the colors and look and feel of the CTA, especially if it is a button. I’ve written about that in more depth elsewhere, so I won’t go into it in this post.

Self-Replication

In many forms of social media, the element of a piece of content that is actually being shared by users is the title. On Twitter, ReTweets of an article typically contain its title, the same with social news sites, social networks and often email and IM. This means that when an individual spreads your content for you, they’re likely to be using the headline as if it were their own words, anything you say in the title borrows the authority of the sharer.

When we construct content we wish to spread, if we can bake in the viral call to action in such a way that it is contained in the title itself, we can make the act of sharing it self-replicating. A simple example is the blog post with the title “ReTweet this to win.” Again, while giveaways and less subtle calls-to-action like this can be effective there are drawbacks. A more sophisticated example would be the “the villian is wronging the victim” model from above.

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