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SOCIAL: Viral Loop Methodology

Remember the days when viral meant "send to a friend"?, well now its becoming a full blown tactic that may be the key to your success.

Some of the most successful viral apps have spent as much time on their viral formula as on developing the app itself. While this is more a facebook phenomena today - it will soon be key across the entire web network as opensocial and widgets get more established. Here is the beginings of a methodology for measuring virality and what it means for an app to “go viral.”

K-factor and R-zero

Terms like “K-factor” (contagion) and “R-zero” (reproduction rate) are often used to describe the growth rate of viral apps. These terms come from the fields of medicine and biology — they’re originally intended to describe the spread of of viral diseases, but they’re nice analogies for how web/SN apps grow. Some would even describe widgets and apps as “diseases” that have “corrupted” popular social networks like MySpace and Facebook! If you are interested in viral apps, read on!

Whether we’re talking about apps or diseases, the key factors in determining virality are the same:

1. Distribution: how many people, on average, will an “infected” host make contact with while the host is still “infectious”?
2. Infection: how likely is a person, on average, to also become “infected” after contact with a viral host?

If you multiply these factors together, that’s your viral growth rate (or “K” or “R-zero” or “viral coefficient”). The product of these factors answers an important question:

How many people will be infected by a single viral host while the host remains infected?

With real-world viruses, the infectious period has very dramatic outcomes. E.g., a host remains infectious until either the virus kills the host or until the host’s immune system fights off the virus. If K=1, then the host basically passes the virus on to one new person before either the host dies or the virus is expelled. Either way, if K=1, then the host exactly replaces him or herself in the population of infected people before becoming non-infectious.

Hopefully, the growth of social apps will never involve physical death or illness! Instead, we would consider a host to be “no longer infectious” if they either uninstall the app or stop actively using the app. Using that definition, an app with a K-factor of 1 will have a userbase in steady-state - no growth, no decline, just flatline; where every current user replaces themselves before leaving the userbase. "K>1" means an app is growing its userbase virally (exponentially). And, conversely, if K is less then 1 then the userbase is decaying exponentially.

Assuming that you've got a reliable way of collecting metrics, here’s a list of four key levers for achieving viral app objectives. You can design, measure and optimize these key success metrics as part of your overall viral plan.


4 Viral App Control Levers

1. Increase the percentage of “active hosts” who actively make contact with uninfected people
2. Increase the contact rate for each active host (average number of contacts per time period)
3. Increase the duration of each active host’s infectious time period
4. Increase the likelihood that contacts turn into infections (i.e., infection conversion)

Some example methods for optimizing virality:

1. Active Hosts

• Require users to invite more people to join the app before they can view/use the app. Typically paired with premium or high value content. (eg: “Invite 10 friends in order to unlock this pr0n video in high-definition” or “Invite 15 friends to see how who has a crush on you”). Some users complain about this tactic, but you may be surprised at how many users will effective.
  
• Opportunism — you can’t always predict how people will utilize an application, so give your users multiple ways to share your app. Ideally, every app pageview should contain one or more ways for a user to share the app (and thereby become an active viral host).

2. Contact Rate

• Create incentives for inviting more people. E.g., “invite 10 more friends to level up and become a Black Belt Ninja”
• Specific requests tend to work better than vague encouragements. E.g., don’t just ask users to “please invite friends”, specifically ask for a number, “invite 10 friends”
  
• Simplify, simplify, simplify. If your #1 goal is to go viral, then that should be the #1 action-request that “pops” out to a user. Make it easy to invite more people. Utilize address book importers. Auto-select large(r) distribution lists for invitations. Basically, minimize the amount of hunting-and-clicking it takes to get a user through your invitation process. Ideally, it should just be 1 click.

3. Activity Duration

• User-to-user messaging is a great way to keep users coming back to an app. If pokes, walls, comments or private messaging fit into the context of your app, you should seriously consider building those in.
• User generated content and media — in general, apps that have some form of UGC/media built into them (music, photos, videos, drawings, etc.) do a better job at drawing repeat visits. I’d also group collaborative filtering functionality in this bucket — e.g., ratings, rankings, top playlists, “most viewed” lists, etc.

4. Infection Conversion

• Social context — when you’re writing the content/copy for your app invitations, be sure to keep in mind the fact that all your app invitations are occurring in the context of a social relationship between two friends. Use that knowledge as you phrase every call-to-action and craft each sentence to reinforce the social relationship and play on influence mechanisms between these two friends.
• Images and buttons — beyond writing the actual content/copy, app authors should also experiment with design and layout of their invitations. Some top tips include: use buttons instead of plain text links; and use images of people to draw the eye.

Of course, the list above is not exhaustive, it’s just a sampling of top-of-mind viral engineering techniques.

Sidenote on app metrics

Note that this also implies that in order to affect any of these, you, as an app developer, need to be able measure each of these stats for your userbase. You can’t tell if you’re driving any of these numbers up (or down) until you know how many contacts/invitations each of your users sends out per day/week/month that they have the app installed; how many days/weeks/months each of your users tends to keep the app installed; and what the conversion rate from a contact/invite into a new infected user is.

Collection and analysis of metrics for social apps is a meaty topic in and of itself, so we’ll leave that for another day. But for now, it should suffice to say that it’s really important to have an effective way to collect statistics on what your users are doing with your app!

Summary

So good luck to all you app developers out there seeking app virality! As you can see, none of this stuff is not “secret sauce” or anything — you can readily view all of these techniques in action on Facebook, MySpace and other social network sites today. If you have other top tips for tweaking virality, please post a comment below.

TECH: Monetizing and Marketing Thru Widgets

Lots of continuing discussion everywhere, about Widgets. Widgets are the new cool. Everyone agrees they are a big phenomenon that’s here to stay. That said let's revisit this trend.

In their current form, widgets are the next step in the trend towards disaggregation of content at the production end and aggregation of content by the consumer. This is why they are here to stay. They will also go mobile, partly because the form factor is a fit for small screens. Most in the mobile space, from Nokia (Widsets) to Opera (Opera Widgets) are exploring the concept. There is even a W3C TR for Widgets 1.0. Widgetbox’s directory has about 7,000 widgets. And, yes, there is volume. RockYou is pushing 100M/day.

So, in all of this, where is the money?

Let’s first consider some of the models for monetizing widgets:

• Several widgets can be packaged with an ad unit next to them.
• Widgets can embed advertising in their content.
• They can show promotional campaigns, competitions or other pay-for-placement content.
• Widgets can tie into affiliate networks, e.g., buy this product on Amazon.
• They can collect valuable data, e.g., MyBlogLog.

To analyze how monetization might work we have to look at the content value chain. There are widget builders. There are the page owners (think bloggers and folks who own a profile on a soc networking site). There are the publishers (site owners). There may or may not be a widget distribution/syndication network in the middle.

Widgets are content and widgets builders can extract value based on whether that content is unique, valuable and relevant. Nothing new here but the form factor. Content owners can let widgets spread in order to drive traffic back to their sites or they can decide to monetize valuable content. What’s new with widgets is the need/opportunity to syndicate at the level of the Net as opposed to through a small set of pre-negotiated relationships. This poses some distribution and measurement challenges.

For most page owners, widgets are bling. Direct monetization doesn’t make sense. The average casual blogger gets 150-250 hits/month. The average “pro” blogger gets 800-1000 hits/month. The average social network profile gets less than 100 hits/month. There is no meaningful eCPM that makes direct monetization relevant for the average page owner.

The opportunity for widget distribution / syndication / management platforms is to help address the above mentioned problems that arise when you try to match X widget builders with Y site owners and their Z millions of users, namely:

• Discovery of widgets (content) that is relevant for people with specific interests. This is not trivial as it involves not just search but also recommendation. How else can you help widget developers “move” new widgets onto pages? As the number of widgets on the Net grows, the value of these services will increase.
• Easy distribution of the widgets, from putting them on pages to enabling actions (say, working around MySpace’s Flash linking restrictions) to making sure that content is served fast. As widgets become commonplace and some standards (formal or de facto) emerge, the value-add here will decrease.
• Measurement, measurement, measurement. And analytics, which are not easy to do in a broad syndication environment. There is a lot of value in this for two reasons. First, from the standpoint of traffic rating agencies, widgets count as page views. That won’t last. Eventually, someone will realize that serving 4 square inches of content is not the same as serving 100 square inches. Second, widgets will penetrate real estate that’s not monetizable. For example, I don’t want to make money from my blog but I may put some widgets on it. From a behavioral targeting standpoint, widget distribution networks may get better data than even some of the very large ad networks.
• Monetization enablement + audit. No rocket science here but someone needs to make money move through the content value chain.
• Widget marketing services, from SEO to SEM to viral distribution enablement. A widget syndication network may have the best data to optimize these. Some type of fee or pay-for-placement structure has to be put in place amongst widget developers to address prioritization conflicts.

From the markers perspective, I have spoken with several of my clients who are very marketing savvy and they continue to be skeptical about any significant marketing spending in this space. There is a measurement, ROI, and accountability issue that still remains to be solved. There is a vibrant spirit to tinker and experiment to see what works.

The widgetized future is just beginning!

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