The K-factor is based on the following assumptions which limit, according to Data Community DC its reliability to measure viral growth:
1.) The market is infinite:
Since viral growth can be so explosive, the market for a product can become saturated very quickly. As the market becomes saturated, fewer potential customers will respond to invitations, effectively reducing the “viral coefficient”. Since market saturation could occur in a matter of days or weeks, the effect of a finite market size cannot be ignored.
2.) Once a customer, always a customer.
The rate of customers which stop using the product is ignored. Leaving this very real effect out of the equations is not justified.
3.) Customers only send one invite and then never again.
The assumption that each new customer sends invitations shortly after trying the product and then never again is not accurate. While this may be true for some products, it’s likely that the pattern of sharing depends on the nature of the product and often occurs long after the user has had a chance to try the product and grow to love it.