Viral and Retention Excel Model

A model to explain: how come and when do apps “jump the shark?” (i.e: when they fall from successful to failure)

activation ratesgrowthmarketingretention ratessaturationstartupsuser retentionuserbaseviral acquisitionviral marketing

Description
When your application increases its usage and starts to become saturated, low retention rates can lead your app to complete failure. Why? This simplified model will enable you to simulate exactly what happens.

- Andrew Chen, www.andrewchen.co

Distributed for free under GNU Free Documentation License - http://www.gnu.org/copyleft/fdl.html

This business tool includes
1 Excel Model, 1 pdf Supporting Article

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Further information

The gist of this computation, when looking at the statistics is:

o At an early stage, the shape of your growth curve is fuelled by the invitations
o Although, as time flies by your number of invitations progressivelys start to slumber at the same time of hitting your "network saturation"
o The retention coefficient has an impact on your system as it creates a “lagging indicator” on your acquisition of new customers – if you have high retention rates, you won't actually notice it as much, even if your invites slow down.
o When your retention coefficient is at rock bottom, be vigilant. Indeed, your new invites can't keep your growth at a steady level and you will finish with a bad looking "shark fin".

Your performance can look great at a first glance, but if you don't have the capacities to retain users on the long-run, then your business is an illusion.

- Andrew Chen, www.andrewchen.co

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