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

A WESOME ,

right?

FAILED Broken Feedback Loops M ATCH M AKER

Broken Feedback Loops

A N EW A PPROACH… A simple 1-to-1 action model

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!

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!

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

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