Viral loops
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Transcript of 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