These are not the only signals that help a video ascend to the trending charts for the day, however. YouTube collects additional engagement data for videos including like and dislike counts, comments, and – most importantly – how long users watch the video. They specifically state that, “…the video with the highest view count on a given day may not be #1 on Trending, and videos with more views may be shown below videos with fewer views.”
Speaking of selling stuff online, that's another mostly passive way to generate income. You could generate an income stream for a while by clearing out your basement or attic and selling items on eBay or elsewhere. This can be especially effective with collections. If you have lots of games or jigsaw puzzles that are taking up space and not being used, they can be great sources of income. You might reap a lot by selling new and used clothing you don't need.
To model Viral Cycle Time’s effect on growth, I searched the web, high and low, looking for a pre-defined formula. To my great surprise, there was no formula that I could find that correctly calculated customer growth, and showed the impact of Viral Cycle Time. What was also surprising, was that I did find several blogs showing formulae for viral growth, but in every case, they appeared to make the same mistake, which was assuming that the entire customer base would continue sending out invitations for every cycle. So I collaborated with my partner, Stan Reiss, who turns out to be a whole lot smarter than I am, and he helped me develop the fomulae that are used in the more sophisticated model for viral growth below:
My favorite type of semi-passive income was rental property because it was a tangible asset that provided reliable income. As I grew older, my interest in rental property waned because I no longer had the patience and time to deal with maintenance issues and tenants. Online real estate became more attractive, along with tax-free municipal-bond income once rates started to rise.
Now that we have the model built, we can play with the variables to see what effect they have. In the spreadsheet above, go to cell B11, and change the Conversion rate for invites (conv%) to 5%. This will make the Viral Coefficient less than 1. Now look at what that did to your population growth. Instead of continuing to grow, it grows to 20 people, and then stops.
Exploits common motivations and behaviors. Clever viral marketing plans take advantage of common human motivations. What proliferated “Netscape Now” buttons in the early days of the web? The desire to be cool. Greed drives people. So does the hunger to be popular, loved, and understood. The resulting urge to communicate produces millions of websites and billions of email messages. Design a marketing strategy that builds on common motivations and behaviors for its transmission, and you have a winner.
The ultimate goal of marketers interested in creating successful viral marketing programs is to create viral messages that appeal to individuals with high social networking potential (SNP) and that have a high probability of being presented and spread by these individuals and their competitors in their communications with others in a short period of time.