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In [[viral marketing]], the '''K-factor''' can be used to describe the growth rate of websites or [[Mobile app|apps]].<ref>Radoff, Jon (2010), Social Game/Application Growth Model Spreadsheet, http://radoff.com/blog/2010/06/11/social-applicationgame-growth-model-spreadsheet/</ref> The formula is roughly as follows: | |||
:<math>i=\text{number of invites sent by each customer } </math> (e.g. if each new customer invites five friends, ''i'' = 5) | |||
:<math>c=\text{percent conversion of each invite } </math> (e.g. if one in five invitees convert to new users, ''c'' = .2) | |||
:<math>k = i * c</math><ref>http://www.forentrepreneurs.com/lessons-learnt-viral-marketing/</ref> | |||
This usage is borrowed from the medical field of [[epidemiology]] in which a virus having a k-factor of 1 is in a "steady" state of neither growth nor decline, while a k-factor greater than 1 indicates exponential growth and a k-factor less than 1 indicates exponential decline. The k-factor in this context is itself a product of the rates of distribution and infection for an app (or virus). "Distribution" measures how many people, on average, a host will make contact with while still infectious and "infection" measures how likely a person is, on average, to also become infected after contact with a viral host.<ref name="viral">{{cite web | |||
|url=http://framethink.wordpress.com/2008/01/15/the-four-viral-app-objectives-aka-social-network-application-virality-101/ | |||
|title=The Four Viral App Objectives | |||
|accessdate=16 December 2008 | |||
|work= | |||
|publisher= | |||
|date= | |||
}}</ref> | |||
==References== | |||
{{reflist}} | |||
[[Category:Viral marketing]] | |||
[[Category:Definition]] | |||
{{marketing-stub}} |
Revision as of 22:27, 27 December 2013
In viral marketing, the K-factor can be used to describe the growth rate of websites or apps.[1] The formula is roughly as follows:
- (e.g. if each new customer invites five friends, i = 5)
- (e.g. if one in five invitees convert to new users, c = .2)
- [2]
This usage is borrowed from the medical field of epidemiology in which a virus having a k-factor of 1 is in a "steady" state of neither growth nor decline, while a k-factor greater than 1 indicates exponential growth and a k-factor less than 1 indicates exponential decline. The k-factor in this context is itself a product of the rates of distribution and infection for an app (or virus). "Distribution" measures how many people, on average, a host will make contact with while still infectious and "infection" measures how likely a person is, on average, to also become infected after contact with a viral host.[3]
References
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- ↑ Radoff, Jon (2010), Social Game/Application Growth Model Spreadsheet, http://radoff.com/blog/2010/06/11/social-applicationgame-growth-model-spreadsheet/
- ↑ http://www.forentrepreneurs.com/lessons-learnt-viral-marketing/