Social apps stages - measure & management methods

Over the past few months I've spent a lot of time researching social apps and their lifecycle. I wanted to share some of what I've learnt in terms of how to manage and measure a social application. A lot of this data comes from tons of blogs that I've read and my own interpretation and learnings. Special thanks to FrameThink blog which has done a great summary of the customer acquisition metrics.

I created this table to put things in context, it lists the key items to track during a lifecycle of a social app, the levers to pull for improvement, metrics to track, and examples. This is assuming that we’ve a social app ready to go and that it’ll live for perpetuity (no end of life). In summary, the lifecycle stages of interest to us - product folks:

1. Customer acqusition. Get users and more users. And ideally with zero customer acquisition costs (CAC=0). So, how do we do this ? Viral growth.
2. Engagement. Now, that you’ve users, keep them engaged and coming back for more.
3. Revenue generation. Make some money while you’re at it.

Social app stages-->	Customer acquisition	Engagement	Revenue generation
Mechanism / methods	Viral growth	Applications and widgets	Virtual goods Real goods Lead generation Revenue share (storefronts)
Levers to pull	Increase 1. Active users making contact with non-users 2. Contact rate - avg. num of contacts per time period 3. Duration of active users 4. User conversion - prob. that non-user get converted to users.	1. Understand user type. The apps should have the following features: 2. Organic: encourage user to take action that has a side effect of causing other customers to re-engage 2. Promotions 3. Positioning: make it a must-have for your user.	1. Features such as collecting/decorating, frienship/love, gambling. 2. Scarcity of goods 3. Differentiated and targeted offers 4. Virtual goods lifecycle - goods wear out, so should virtual goods.
Metrics	DAU and MAU DAU/MAU ratio is a very imp. ratio: of your monthly users how many are coming back on a daily basis.  Ideally 0.2 to 0.3. Farmville is at 0.28. K-factor (viral coefficient) = Distribution X Prob of conversion Ideal value between 1.4 and 2 (super viral growth) Distribution: how many non-active users will an active user contact. Prob. of conversion: probability of converting a non-active user. . CAC (customer acquisition cost) LTV (lifetime value of customer) = Total sales & marketing costs / customers LTV > CAC. A factor of 3 is ideal.	Engagement ratio: Reactivation of dormant customers exceeds the rate of customer fatigue.	Revenue / DAU or Revenue / 1,000 DAU. Should be around $150-$200. $300 is great! Transactions/DAU Repeat customers Velocity of money. Keep it high.
Examples	Message user’s friends on activation of the app - i.e when the app goes live, send message to all fans. Active users with non-actives: Contact rate: invite 10 friends to get additional coupon Duration of active users: insert collaborative filtering - ratings, rankings and comments; these tend to increase time spent. User conversion: use image or videos to convert non-users in user to user messaging.	What is your user’s usage profile - is she killing time, socializing, browsing... Organic: linked-in sending email listing status changes. Oolium sending notification about a user taking part in a social app. Promotions: sweepstakes, video contest, polls, in the app. Positioning: if the customer’s goal is to “kill time” make your product the goto product for killing time. i.e. associate the thought of killing time with your product. So when the user sees the icon in iPAD she instinctively clicks on it when bored.	In an ideal scenario, scarce virtual goods should be sold in a player to player secondary market. Target sale of goods to women 25-35.