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Viral marketing by the numbers

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360iDev Conference Slides - We describe how Voxilate marketed HeyTell to 1M users using viral techniques, and how to measure and predict the viral growth in your own apps.

360iDev Conference Slides - We describe how Voxilate marketed HeyTell to 1M users using viral techniques, and how to measure and predict the viral growth in your own apps.

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Transcript

  • 1. Viral Marketing By The Numbers Steven Hugg Voxilate Inc.
  • 2. Who We Are Voxilate founded in July 2009 Voice messaging app HeyTell hit 1M downloads in October 2010 Reached #2 in Social Networking Free apps category (so far!)
  • 3. New Users by Month 700000 525000 350000 175000 0 Feb Mar Apr May Jun Jul Aug Sep Oct
  • 4. What We’re Going To Talk About Some observations Our experiences How to measure and estimate viral growth Math WARNING: Not science or even good quality snake oil, YMMV
  • 5. History and Observations
  • 6. Old-School Viral Model Wanna Buy A Panda Hat?
  • 7. Viral Marketing is Nothing New Amway, Mary Kay Charles Ponzi Some religions
  • 8. Viral Brand-Building Model Awesome Funny Video
  • 9. Viral Brand-Building Blair Witch Project (1999) BMW Films (2002) Burger King Chicken (2004) Will It Blend? (2006) Old Spice (2010)
  • 10. Viral Product-Sharing Model Check it Out Dude!
  • 11. Viral Product-Sharing Successes Grateful Dead (late 60’s) MST3K tapes (early 90’s) DOOM (1993) ICQ (1996) Gmail (2004) Minecraft (2010)
  • 12. Why Do People Share Products Online? It’s cool/funny/important to them They might get something in return Sharing is inherent in the product To meet people Vanity (looks + smarts)
  • 13. When Do People NOT Share a Product? When they think it’s lame (make it good) When they don’t trust it (stop being creepy) When sharing is too difficult (get feedback) When they’re no longer using the product (make something with longevity!)
  • 14. Successful Viral App Sharing Needs: A good app (duh!) Easy way to find friends Easy way to invite or share with friends Easy way to get the product after being invited
  • 15. Our Sharing Process App Make Store Friend
  • 16. What We’re After
  • 17. Predicting and Measuring Growth (and some strained analogies)
  • 18. Types of Measurements Quantitative (numbers) Qualitative (emotions) ROI ($$$)
  • 19. Quantifying Viral Propagation “Going viral” is not magic, it’s math Getting your app into the right state where it CAN go viral requires a combination of skill and luck Prediction lets you know if you have a chance, measuring lets you know how you’re doing
  • 20. The Drake Equation # of E.T.s in our galaxy N = N * fp n e f l f i f c fL N* represents the number of new stars/year in the Milky Way Galaxy fp is the fraction of stars that have planets around them ne is the number of planets per star that are capable of sustaining life fl is the fraction of planets in ne where life evolves fi is the fraction of fl where intelligent life evolves fc is the fraction of fi that communicate fL is average lifetime of the communicating civilizations (in years)
  • 21. The Vlake Equation Daily Viral Conversions N = N * n f fi fu fa fL 1000 N* represents the number of new users/day 100 nf is the average number of friends per user 5% fi is the fraction of friends that users will invite daily 50% fu is the fraction of fi that can download the app 50% fa is the fraction of fu that will download the app 2 days fL is the average lifetime of the app during which users invite each other N ~ 2,500 conversions/day
  • 22. Maximizing nf the average number of friends per user Address Book Email and SMS Twitter Facebook Game networks
  • 23. Invitation Vectors Direct SMS Facebook Server SMS Email 6% 13% 0% 81%
  • 24. Maximizing fi fraction of friends that users will invite User Interface - Make it easy (and even fun) to find and invite friends! Lead users through the process, don’t make them guess what to do next Indirectly invite via a link in shared content on Facebook/Twitter
  • 25. % of Users With This Many Accepted Friends 40% 30% 20% 10% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
  • 26. Maximizing fu fraction of fi that can download the app Does your app have specific capability requirements? (camera, microphone) Does your app have OS requirements? (e.g. 4.x+) Is your app cross-platform? Do you state explicitly what platforms you support? Is your app international?
  • 27. Maximizing fa fraction of fu that will download the app Make your invite message non-spammy Feature the inviter’s name prominently in message Link directly to App Store (JavaScript can be used to check if app already exists) Lots of buzz on social networks = good, overloading with email/SMS = bad
  • 28. Invitation Accept Rates By Method SMS Email (est.) Facebook 0% 25% 50% 75% 100%
  • 29. Maximizing fL average lifetime of the app during which users invite each other Friend-initiated notifications send users back to the app Frequent updates to generate interest Peer pressure - Users may reinstall the app if they see their friends are using it
  • 30. % of Invitations Sent N Days After Install 70% 53% 35% 18% 0% 1 2 3 4 5 6 7
  • 31. “Going Viral”
  • 32. “Going Viral” The Biological Metaphor K = avg. invites per user * conversion rate k<1 no growth steady k=1 state k>1 growth
  • 33. “Going Viral” Computing K-factor N = n f f i fu f a fL N* represents the number of new users/day 100 nf is the average number of friends per user 5% fi is the fraction of friends that users will invite per day 50% fu is the fraction of fi that can download the app 50% fa is the fraction of fu that will download the app 2 days fL is the average lifetime of the app during which users invite each other k = 2.5
  • 34. “Going Viral” The Nuclear Metaphor
  • 35. “Going Viral” The Nuclear Metaphor Fast Invite - “Oh boy a new app! I’ll invite all my friends right NOW!” Slow Invite - “You don’t have this app yet? We’ve been on it for WEEKS! Hold on, I’ll invite you...”
  • 36. “Going Viral” The Nuclear Metaphor K = avg. invites per user * conversion rate β = percentage of “slow” invites You get explosive growth if your K-factor is above: 1/(1-β)
  • 37. “Going Viral” The Nuclear Metaphor K = avg. invites per user * conversion rate β = percentage of “slow” invites No Growth K-Value Steady Explosive! 0 1 2 3 4 1/(1-β) (for β = 66%)
  • 38. “Going Viral” Example Numbers infection rate = 4 conversion rate = 38% K = 1.5 66% of users delayed invite β = 0.66 No Growth K-Value Steady Explosive! 0 1 2 3 4 Result: Steady Growth
  • 39. The Danger of Explosive Growth? Is your server ready? Is your app ready? Is your revenue model ready? Is support ready? How about your customers? (Usually, it’s a good thing)
  • 40. What Else Contributes To Explosive Growth? App Store ranking General “buzz” on social networks Big In Japan Oprah, Bieber Popularity begets popularity
  • 41. How To Measure Analytics packages Your own server Run links through your web site to use Google Analytics Use your beta as a sample Watch for anomalies (could mean bugs!) A/B test
  • 42. What To Measure User invitations User invite acceptances Time spent in app Failed sharing attempts Failed invitation accepts
  • 43. Remember the Humans Your customers are not robots Users may act predictably for awhile, but your user community can turn on a dime - watch where the wind is blowing Perception affects growth Goodwill creates advocates
  • 44. Thanks! @sehugg Additional Links: http://www.delicious.com/sehugg/viral Attributions to: xkcd.com http://www.flickr.com/photos/tohoscope/ http://www.flickr.com/photos/7969902@N07/ Abi Paramaguru