FROM  M ATCH M AKER   TO  S QUEEZE M E Brian Berseth Evan Rosenfeld Clay Whitehead
M ATCH M AKER A WESOME ,   right? C REATE I NVITE V OTE E NGAGE
FAILED Broken Feedback Loops M ATCH M AKER
A N EW  A PPROACH… A simple 1-to-1 action model
T HE  N EW  L INE  U P
S QUEEZE M E  T AKES  O FF !
S QUEEZE M E  Demographics Geography: 33% UK 20.1% Canada 8% US 6% Australia Average Age: ~30-50 ~1% of users are in university!
G ROWTH  T RENDS Server Crash
G ROWTH  T RENDS Server Crash
A Mathematical Model? Number of new users is directly proportional to number of squeezes sent on the  same day ! (r 2  = .968) App users receive and respond to invitations the day they are sent!
Concluding Thoughts 40,000 in four weeks with SqueezeMe Doubled in the last week Talk to us: Questions about our methods Want to target SqueezeMe’s demographic Further insights

MATCH MAKER - Stanford Facebook Class

  • 1.
    FROM MATCH M AKER TO S QUEEZE M E Brian Berseth Evan Rosenfeld Clay Whitehead
  • 2.
    M ATCH MAKER A WESOME , right? C REATE I NVITE V OTE E NGAGE
  • 3.
    FAILED Broken FeedbackLoops M ATCH M AKER
  • 4.
    A N EW A PPROACH… A simple 1-to-1 action model
  • 5.
    T HE N EW L INE U P
  • 6.
    S QUEEZE ME T AKES O FF !
  • 7.
    S QUEEZE ME Demographics Geography: 33% UK 20.1% Canada 8% US 6% Australia Average Age: ~30-50 ~1% of users are in university!
  • 8.
    G ROWTH T RENDS Server Crash
  • 9.
    G ROWTH T RENDS Server Crash
  • 10.
    A Mathematical Model?Number of new users is directly proportional to number of squeezes sent on the same day ! (r 2 = .968) App users receive and respond to invitations the day they are sent!
  • 11.
    Concluding Thoughts 40,000in four weeks with SqueezeMe Doubled in the last week Talk to us: Questions about our methods Want to target SqueezeMe’s demographic Further insights