two methods for modeling ltv with a spreadsheet
DESCRIPTION
NB! The bitly link in the deck is hard to read, please use this one: http://bit.ly/2LTVXLS This is the presentation I gave at Slush 2013 in Helsinki, Finland. It describes two methods for modeling Lifetime Customer Value (LTV) in Excel. Linked within the presentation is a spreadsheet exemplifying both methods against 100k rows of fake user data that I generated with a Python script to "look" real (although they probably don't).TRANSCRIPT
TWO METHODS FOR MODELING LTV WITH A SPREADSHEET
Eric Benjamin SeufertSlush 2013
WHO AM I?
WHO AM I?Head of Marketing at Wooga
WHO AM I?Head of Marketing at Wooga
MobileDevMemo.com
WHO AM I?Head of Marketing at Wooga
MobileDevMemo.com
Freemium Economics
DOWNLOAD THE SPREADSHEET100k rows of fake data
DOWNLOAD THE SPREADSHEET100k rows of fake data
• Probably doesn’t look like real data!
DOWNLOAD THE SPREADSHEET100k rows of fake data
• Probably doesn’t look like real data!
http://bit.ly/183lFwp
WHAT IS LTV?
FUNDAMENTALLY A PROJECTION
PRIMARILY USEFUL FOR MARKETING
DIFFICULT TO CALCULATE FOR FREEMIUM GAMES
USUALLY CALCULATED PROGRAMMATICALLY
GOOD REASONS TO CALCULATE LTV IN A SPREADSHEET
Prototyping using comparable data
GOOD REASONS TO CALCULATE LTV IN A SPREADSHEET
Prototyping using comparable dataProject investment decisions
GOOD REASONS TO CALCULATE LTV IN A SPREADSHEET
Prototyping using comparable dataProject investment decisionsSprint prioritizations
GOOD REASONS TO CALCULATE LTV IN A SPREADSHEET
Prototyping using comparable dataProject investment decisionsSprint prioritizations
General strategic decision making
GOOD REASONS TO CALCULATE LTV IN A SPREADSHEET
WHAT ARE THE INPUTS TO LTV?
WHAT ARE THE INPUTS TO LTV?Monetization (Value)
WHAT ARE THE INPUTS TO LTV?Monetization (Value)Retention (Lifetime)
WHICH DIMENSIONS?
WHICH DIMENSIONS?
WHICH DIMENSIONS?
LTV TIMELINE180 days or 365 days?Spreadsheet shows both
RETENTION APPROACH
RETENTION APPROACH
Real Retention Rates
ESTIMATING LIFETIME
Power function
ESTIMATING LIFETIMEPower Function: y = a * x ^ b
a -> =EXP(INDEX( LINEST( LN(Known Ys), LN(Known Xs)), 2))
b -> =INDEX(LINEST(LN(Known Ys), LN(Known Xs)), 1)
ESTIMATING LIFETIMEArea under the curve
ESTIMATING LIFETIMECalculating lifetime:
• Retention curve essentially a survival function
More info: http://data.princeton.edu/wws509/notes/c7.pdf
Source: Survival Analysis, a Self-Learning Text (Klein 2005)http://books.google.de/books?id=GNhzxRkFnJ0C&lpg=PA262&ots=Z3foUkFg-4
Example survival curves for two groups ofpatients given different Leukemia treatments
ESTIMATING LIFETIMECalculating lifetime:
• Retention curve essential a survival function • Mean is value of integral
More info: http://data.princeton.edu/wws509/notes/c7.pdf
CALCULATING LTVBuild retention function:
CALCULATING LTVBuild retention function:
Retention curve power function model( y = a x ^ b )
CALCULATING LIFETIMEBuild retention function: Lifetime (180):
Integral (1 -> 180):Y = 0.61x ^ -0.37
= 25.3 Days
Lifetime (365): Integral (1 - > 365):y = 0.61x ^ -0.37
= 40.1 Days
CALCULATING LTVFor the trailing 7 days of data…
CALCULATING LTVFor the trailing 7 days of data……for users in the UK…
CALCULATING LTVFor the trailing 7 days of data……for users in the UK……that downloaded the game organically…
CALCULATING LTV
LTV(180):25.3 * $0.13 = $3.30
LTV(365):40.1 * $0.13 = $5.21
HONING THE MODEL
More real data
HONING THE MODEL
More real data
MONETIZATION APPROACH
MONETIZATION APPROACH
© 2014 Freemium Economics
MONETIZATION-BASED APPROACH
Real Average Daily Cumulative Spend Data
MONETIZATION-BASED APPROACH
Logarithmic Function
PROJECTING THE CURVELogarithmic Function: y = (c * LN( x )) + b
c -> =INDEX(LINEST(Known Ys, LN(Known Xs)), 1)
b -> =INDEX(LINEST(Known Ys, LN(Known Xs)), 1,2)
MONETIZATION-BASED APPROACH
LTV
CALCULATING LTVBuild monetization function:
CALCULATING LTVBuild monetization function:
Monetization curve logarithmic model( y = ( c * ln( x )) + b)
CALCULATING LTV
CALCULATING LTVUsing trailing 3 days of retention data…
CALCULATING LTVUsing trailing 3 days of retention data……for users in the US…
CALCULATING LTVUsing trailing 3 days of retention data……for users in the US……acquired through Flurry Video Ads…
CALCULATING LTVUsing trailing 3 days of retention data……for users in the US……acquired through Flurry Video Ads…
y(180) = ( .45 * ln (180)) + .41 = $2.75y(365) = ( .45 * ln( 365 )) + .41 = $3.06
HONING THE MODEL
HONING THE MODEL
