viral loops

Value Loops, Viral Loops & Network Effects

Anurag Jain

Structure of Talk

• Value Loop• Network Effects• Viral Loops• Designing viral loops

Types of products

• Inherent value or dependent on network effects?

• Primary value => Inherent – even a single user can be a long-term user

• Primary Value => network effects– No community => all users leave

Value loop

• More value + less cost = value loop

• Usually Word of Mouth• Typically takes a while• Concentrate on channels of distribution

• E.g. - mint.com, google.com, early days of facebook

How do we measure value?

• Net Promoter Score– Users rate from 1-10 – 10 = best– Promoters (9-10)– Passives (7-8)– Detractors (1-6)

• NPS = % Promoters - % Detractors• High NPS (>40%) => No need for virality

Network Effects

• 100 users or 10,000 ?

Network Effects

• 100 users or 10,000 ?

• It depends!!

Network Effects

• 100 users or 10,000 ?

• It depends!!

• Imagine 10,000 facebook users with 0 friends each

Network Effects

• 100 users or 10,000 ?

• It depends!!

• Imagine 10,000 facebook users with 0 friends each

Network Effects

• Metcalfe’s law:Value of network = c(P^2)

P – no of connected users

• If n sets of connected users, Value = c(P1^2 + P2^2 + … + Pn^2)

Network Effects

• Metcalfe’s law:Value of network = c(P^2)

P – no of connected users

• If n sets of connected users, Value = c(P1^2 + P2^2 + … + Pn^2)

• E.g. facebook, linkedIn, twitter

Network Effects

• Metcalfe’s law:Value of network = c(P^2)

P – no of connected users

• If n sets of connected users, Value = c(P1^2 + P2^2 + … + Pn^2)

• E.g. facebook, linkedIn, twitter• Cold start problem

Social Layer?

• Facebook -> People/People

• Twitter -> People/News

• Foursquare -> People/Places

Social Layer?

• Facebook -> People/People

• Twitter -> People/News

• Foursquare -> People/Places

• Your product -> People/????

Primary benefit

• Why should I care?

• What’s in it for me?

Primary benefit

• Why should I care?

• What’s in it for me?

• Sharing?

Psychology of sharing

• Facebook -> Socialite• Twitter -> In the know (journalist)• Yelp -> Critic• Quora -> Expert• Instagram -> Photographer• Foursquare -> Person-about-town

Psychology of sharing

• Facebook -> Socialite• Twitter -> In the know (journalist)• Yelp -> Critic• Quora -> Expert• Instagram -> Photographer• Foursquare -> Person-about-town• Your product -> ?????

Friendship graphs

• Symmetric or asymmetric?

• Friend or follower?

• Friend = more private• Follower = public, but higher growth

– More specific to intent-based vertical networks

Building Network Effects

• Critical Mass– community that sustains itself– 150 users in each community

• Alpha Users– High Social Networking Potential (SNP)

• Cold Start problem– If I have only a few friends, where is the value for me?

Building Network Effects

• Social Learning– Watch what others are doing

Building Network Effects

• Social Learning– Watch what others are doing

• Singling Out– Messaging from others

Building Network Effects

• Social Learning– Watch what others are doing

• Singling Out– Messaging from others

• Feedback– How does my network respond to my actions?

Building Network Effects

• Social Learning– Watch what others are doing

• Singling Out– Messaging from others

• Feedback– How does my network respond to my actions?

• Distribution– Extent of reach of my actions. Who all sees it?

Network Effect example

• Credit for user @a all along the chain• More motivation to write funny/interesting tweets

Building Network Effects

• Network Effects– Alpha users will help, but only for a while– Slow growth => death– Need viral growth

What is viral?

• Anything that grows exponentially, like a virus

Why do we want viral growth?

• It’s cheap (and fast)

What is Viral?

• Anything that grows exponentially, like a virus• Word of Mouth propagation can be viral under

certain circumstances

What is Viral?

• Anything that grows exponentially, like a virus• Word of Mouth propagation can be viral under

certain circumstances– But typically slow

• How do we know when something is viral?

Viral Co-efficient

• Let’s say each user invites 5 friends– on avg 22% of invitees register– viral co-eff => 22% * 5 = 1.1

• > 1 = viral

Viral Co-efficient

• Let’s say each user invites 5 friends– on avg 22% of invitees register– viral co-eff => 22% * 5 = 1.1

• > 1 = viral

• If 1 user gets 1 more, can get the entire world

Viral Cycle Time

• If 1 user gets 1 more, can get the entire world• But, how fast?• Until market is exhausted, how fast does it grow?

– Viral Cycle Time– Depends on each product

• Measurement is important!!

Measuring Viral Cycle Time

• Cohort Analysis• Weekly (or daily) cohorts of users

• Track how users behave over period of time, based on when they joined

• Idea: Don’t make decisions for new users based on metrics from more experienced ones

What parts are viral?

• Invitations• Engagement

• Trick is to invite other users as part of the core user experience

• Not to be confused with network effects

What is the viral loop?

• User A takes an action

What is the viral loop?

• User A takes an action• User B is notified as part of that action

What is the viral loop?

• User A takes an action• User B is notified as part of that action• As part of the response, user B takes SIMILAR action

What is the viral loop?

• User A takes an action• User B is notified as part of that action• As part of the response, user B takes SIMILAR action• User B therefore invites User C

What is the viral loop?

• User A takes an action• User B is notified as part of that action• As part of the response, user B takes SIMILAR action• User B therefore invites User C• … and so on

What is the viral loop?

• User A takes an action• User B is notified as part of that action• As part of the response, user B takes SIMILAR action• User B therefore invites User C• … and so on

• Integral part of the product, not a layer

Designing Viral Loops

Designing viral loops

• Single core activity• Single entity for user to interact with• Can have multiple types of users, but with great

difficulty

• Channels for virality

Single activity

• What is the core activity?• Can we add messaging to this activity?• The new user who sees this responds to this activity

by taking the SAME action• … and so on

Single activity

• What is the core activity?• Can we add messaging to this activity?• The new user who sees this responds to this activity

by taking the SAME action• … and so on

• Viral growth

Single type of user

• Multiple sets of users – VERY HARD

• Motivations are very different for different groups• E.g. Seller != Buyer

Single type of user

• Multiple sets of users – VERY HARD

• Motivations are very different for different groups• E.g. Seller != Buyer

• Design loop for each set separately

Channels for being viral

• News Feed• Notifications• Email• Profile• Invites• Non-user pages• Profile Actions

Other Techniques for Viral

• Game Mechanics– Badges, scores, etc.

• Not core value, unless game is the core itself• Rewards• Contests

Steps for viral loop

• Design loop with core activity• Build product• Test on small set• Optimize the loop

Conclusion

• Feature depends on network effects?– Cold start remedies

• Need viral loop• Measure, measure, measure• World dominance