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The Science behind Viral Marketing is a look at the key factors that drive growth in viral marketing. (Hint, the most important factor is not the one everyone expects.) It also looks at what is needed to get virality to work, and how to create and optimize viral marketing campaigns or viral products. One part of the presntation shows the key formulae behind viral marketing. Suitable for marketers or for product designers.
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The Science behindViral Marketing
Lessons Learned
Explosive growth!
YouTube Facebook Zynga Groupon Twitter Gilt Groupe
All have set records for growth rates
The key is Virality
The Power of Viral Marketing
When it works it is Free!! Far more effective than paid promotions and
advertising campaigns If done well can be self-sustaining + growth Unfortunately rarely achieved!
The Best Business Model
Monetization(LTV)
Cost ofCustomer
Acquisition(CoCA)
Virally acquired customers are free
Topics
The Science behind Viral Marketing How to do Viral Marketing Optimizing for Virality Making this work for your business Examples
Where my experiences come from
Tabblo Photosharing site Founded by Antonio Rodriguez, 2005 Acquired by HP within 18 months Great investment return
All credit is owed to Antonio Rodriguez
The Viral Loop
Customer first sees your app
Tries it
Decides they like it enough to invite their
friends
Creates an invitation, looks up
addresses, and sends
Friend receives
invitation
Friend decides to take a look
The Math behind Virality
Key variables: Custs(0) The initial set of customers i The number of invites sent out conv% The percentage of invites that
convert into customers
The Viral Coefficient
K The Viral Coefficient
K = no of invites x The conversion % (i x conv%)
Turns out to be a very important variable. It equals the number of new customers that each customer is able to successfully invite.
An Example
Custs(0) = 5 i = 10 conv% = 20% K = 2
Cycles 0 1 2 3 4 5
New custs added this cycle 10
20
40
80
160
Total Customers: C(c) 5
15
35
75
155
315
The Formula
New custs added in this cycle = New custs added in the previous cycle x K
Assumes that customers only send out invites once, and not continuously in every later cycle
To calculate the number of customers at any particular cycle (c):
Custs(c) = Custs(c-1) + NewCusts(c)
Sensitivity to K
See Spreadsheet model
Sensitivity to K
Viral Coeffi cient K 0.5 Cycles 0 1 2 3 4 5 6 7 8 9 10 11 12New custs added this cycle 3 1 1 0 0 0 0 0 0 0 0 0 Total Customers: C(c) 5 8 9 9 10 10 10 10 10 10 10 10 10
Viral Coeffi cient K 0.9 Cycles 0 1 2 3 4 5 6 7 8 9 10 11 12New custs added this cycle 5 4 4 3 3 3 2 2 2 2 2 1 Total Customers: C(c) 5 10 14 17 20 23 26 28 31 33 34 36 37
Viral Coeffi cient K 1.0 Cycles 0 1 2 3 4 5 6 7 8 9 10 11 12New custs added this cycle 5 5 5 5 5 5 5 5 5 5 5 5 Total Customers: C(c) 5 10 15 20 25 30 35 40 45 50 55 60 65
Viral Coeffi cient K 2.0 Cycles 0 1 2 3 4 5 6 7 8 9 10 11 12New custs added this cycle 10 20 40 80 160 320 640 1,280 2,560 5,120 10,240 20,480 Total Customers: C(c) 5 15 35 75 155 315 635 1,275 2,555 5,115 10,235 20,475 40,955
What we learned
Viral Coefficient must be > 1 to have viral growth
Viral Growth is a compounding phenomenon
Increasing the Viral Coefficient has a big impact on the rate of growth
YouTube versus Tabblo
Both started around the same time YouTube’s growth massively outstripped Tabblo
What was happening here?
Tabblo’s Viral Loop
User discovered Tabblo Wait till they take some photos Upload Share (i.e. invite others) Some portion of those think, this is great, I want to use
this myself Wait till they take some photos Upload Etc.
YouTube’s Viral Loop
User discovers YouTube Sees some hilariously funny content Decides to share that with friends Friends see hilariously funny content Decide to share that with their friends
The time to infect is far shorter!
A More Sophisticated Formula
t = timect = cycle time
Thanks to Stan Reissfor help with the forumula
What this tells us
Multiplier
Raised to the Power of …
Shortening the cycle time has a far bigger effect than changing Viral coefficient!
Some experiments
See Spreadsheet model
Some Experiments
No wonder YouTube was explosive!
Viral Coeffi cient K 1.50
Custs(t) 161 0 10 20 30 40 50 60 70 80 90 100 110 120Viral Loop Time (lt) 1 5 855 49,870 2,876,336 165,866,278 9,564,781,592 551,559,020,225 31,805,990,505,278 1,834,112,025,928,330 105,765,199,266,334,000 6,099,015,336,964,180,000 351,703,474,664,229,000,000 20,281,197,415,788,400,000,000
2 5 104 855 6,558 49,870 378,766 2,876,336 21,842,355 165,866,278 1,259,553,409 9,564,781,592 72,632,923,440 551,559,020,225 5 5 24 66 161 374 855 1,936 4,369 9,843 22,159 49,870 112,220 252,507
10 5 13 24 41 66 104 161 246 374 567 855 1,287 1,936 20 5 8 13 18 24 31 41 52 66 83 104 130 161 50 5 6 8 9 11 13 14 16 19 21 24 27 30
Time tTime - t
Lesson Learned
Reducing Viral Loop cycle time has by far and away the greatest effect on viral growth
How to do Viral Marketing
The Basics
Figure out the Viral Hook What makes people want to share content?
Content or Product/Service Initial Seeding Use communications networks to spread
Email, Twitter, Facebook, Google+, etc.
Refresh & Re-seed
Figure out the Viral Hook
Something very compelling that the user wants to share
Viral Hook - What works:
Something of Value: Applications Educational content Data Things of monetary value (Discounts and coupons)
Something entertaining Humor Games
News Inherently Viral Services
Email, Skype, etc.
Other?
Why do people share?
A paper on that here: http://marketing.wharton.upenn.edu/documents/research/Virality.pdf http://www.nytimes.com/2010/02/09/science/09tier.html (summary)
Virality driven by physiological arousal High arousal, Postive (awe) – most likely to be shared High arousal, Negative (anger or anxiety) – less likely Low arousal, de-activating (sadness) – unlikely
Content Types
Blogs Videos eBooks Applications and Services Etc.
Using engineering for marketing
Inherently Viral Applications
The most viral apps are those that are require sharing to work properly: HotMail Skype YouTube FaceBook Etc.
Initial Seeding
The bigger your initial seeding the better Identify Influencers
Reach / Influence Klout, SocMetrics and other services emerging to help
Develop the right relationship Listen, Strategize, Engage, Measure
Paid Seeding Paid search, Virool.com, etc.
Spread through Communications Networks
Early days this was email Social Networks have turbo-charged sharing
What you want: Low effort for the user doing the sharing
Refreshing and Re-Seeding
Google Search (paid and organic) Creates new seeding
New Blog posts Cause your existing readers to re-invite
Farmville, etc. Continue to invite by regular posts to your wall
Lessons Learned Optimizing for Virality
Lessons Learned
Apply my “Unblock your Sales Funnel” principles to the viral loop steps
Customer first sees your app
Tries it
Decides they like it enough to invite their
friends
Creates an invitation, looks up
addresses, and sends
Friend receives
invitation
Friend decides to take a look
CONCERNS- Hate being sold to- Find it offensive to give
name and email- Don’t want to get spam
sales emails- Worried that email
address will be given to other marketers
GET INSIDE YOUR CUSTOMER’S HEAD
UNDERSTAND WHAT MOTIVATES THEM
- Want to solve my problem- Recommendation from a friend- Education- Data/ information reports- Entertainment- Free stuff- Meeting other people like me that
have insights to share
CONCERNS
MOTIVATIONS
CREATE A SOLUTION THAT ENTICES THEM AND ADDRESS THEIR CONCERNS
- Customer testimonials address vendor risk
- Free trials address product viability and fit concerns
- Lowest price guarantees
CONCERNS
ENTICE & ADDRESS CONCERNS
Example: Groupon
Example: Living Social
Another strategy
Offer a reward both to the user and to their friend Overcomes the feeling of being sleazy Can lead to much higher success rates
Lessons Learned
Maximize the number of invites they send out Leverage tools that provide easy reach to their friends:
Twitter Facebook: post to their News Stream LinkedIn
Automate access to their address book Works well for GMail, and other on-line address
books Etc.
Lessons Learned
Look for ways to automate the whole invitation process No thinking required No work required
Don’t just invite once
Look for ways to keep repeating invites E.g. Facebook games like Farmville that post to your
News Stream
Lessons Learned
Look for other ways to get your customers to tell their friends about you
Example: ConstantContact’s email signature
Reduce the Cycle Time
Customer first sees your app
Tries it
Decides they like it enough to invite their
friends
Creates an invitation, looks up
addresses, and sends
Friend receives
invitation
Friend decides to take a look
Lessons Learned
Hybrid Viral Even if you can’t get a viral coefficient > 1
you can still enhance customer acquisitionwith some virality
Lessons Learned
The Viral Loop is an important Funnel Design each step carefully
Simplify and eliminate manual steps Test for adequate motivations and incentives
Address concerns A/B test each step
Metrics to evaluate and improve
Make it work for your Business
Creepy Effective
What can go wrong? - Branchout
Social networks are for hanging out with friends Not promoting your business
Branchout (recruiting app on Facebook) Spammed users walls with way too many entries
The Result:
Thanks to paulamarttila.posterous.com
Some Fun Examples
For a full set, visit:http://www.ignitesocialmedia.com/social-media-examples/viral-marketing-examples/
