Regular map (graph theory): Difference between revisions

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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 23:27, 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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Template:Marketing-stub

  1. ↑ Radoff, Jon (2010), Social Game/Application Growth Model Spreadsheet, http://radoff.com/blog/2010/06/11/social-applicationgame-growth-model-spreadsheet/
  2. ↑ http://www.forentrepreneurs.com/lessons-learnt-viral-marketing/
  3. ↑ Template:Cite web
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