Presentation given to Yetizen on LTV: the importance of it, what to measure and how to affect it, and the predictive nature of LTV. Similar to previous presentation at Groundworks Lab with an added section on Uncertainty.

1. H O W L I F E T I M E V A L U E D E T E R M I N E S Y O U R
S U C C E S S A N D H O W T O I M P A C T I T
Lifetime Value

2. Presentation Overview
Relevant background
Why Lifetime Value
Importance beyond social media
Virality
Retention
Monetization
The Cost Side
LTV varies among customers
Uncertainty of LTV

3. F R O M S T A R T - U P T O B I G C O
Relevant Background

4. • Grew to top-5 casual game company
• Initiated and negotiated sale to Playdom, which was then rolled into $570 million Disney
acquisition
Co-founded Merscom CCO, led all marketing/sales/distribution
• Responsible for Europe, Latin America, Russia and India
• Grew it from scratch to 25 percent of Playdom’s revenue
GM of Playdom’s International Publishing team
• Joint venture of EW Scripps and Capitol Broadcasting
• Launched Facebook and mobile games
CEO of FiveOneNine Games
• Lead UA, analytics, monetization and community
• Social Casino space
Currently Chief Growth Officer at Spooky Cool Labs and Chairman of
Globalization Committee at NC Central’s School of Business
Been there, done that

5. T H E T H R E E M O S T I M P O R T A N T L E T T E R S F O R
Y O U R B U S I N E S S : L T V
Why Lifetime Value

6. Based on three performance metrics
Monetization
Virality
Retention

7. Interdepence

8. Relationship between LTV and CPA
• Success
LTV > CPA
• Failure
LTV < CPA

9. Think of LTV starting day 1
Green-light
Design and
develop
focused on
LTV
Beta and
other testing
to optimize
LTV
Post launch
to focus on
improving
LTV

10. C R U C I A L T O A N Y B U S I N E S S
Importance beyond social media

11. Online offerings
 Netflix
 Ebates
 Farmville

12. B2B
Square
Rackspace
Bronto

13. SaaS
 Salesforce
 HootSuite
 Basecamp

14. Retail
Restaurants
Department
stores
Car dealers

15. W O R D O F M O U T H ’ S E X P O N E N T I A L E F F E C T
Virality

16. Definition of virality
 K-score
 K=i*conv% (conversion percentage), where “i” is the
number of invites sent out by each new customer and
“conv%” is the percentage of invites that convert into
costumers

17. An advanced look

18. Importance of virality
Lowers cost of
customer
acquisition
Exponential
growth

19. Improving Virality
K=i*conv%
Increasing I
• Generate virality quickly
• Cater to Connectors
Increasing conv%
• Quality of communication
• Provide value for virality

20. C R U C I A L A N D H A R D T O F I X
Retention

21. Definition of retention
Customer
lifetime
N-day retention
Churn rate

22. Importance of retention
If they do not come
back, monetization
improvements are
virtually useless

23. Improving retention
 Product quality
 Get in their heads
 Make it social
 Make it global
 Use email and
advertising for re-
engagement

24. S H O W M E T H E M O N E Y
Monetization

25. Definition of monetization
ARPU (Average
revenue per user)
ARPDAU
(Average
revenuer per
daily active user)
Percentage of
customers who
monetize
Average
transaction
Average number
of monetization
events per
customer

26. Importance of monetization

27. Improving monetization
Product
quality
Value
More
selection
Balancing
Shopping
experience
Promotions
and sales

28. D O N O T F O R G E T V A R I A B L E C O S T S
The Cost Side

29. Cost Drivers
• Hosting
• Support
Running Costs
• Platform fees
• Payment processors
Payment Processing
• Engine, such as Epic’s UDK
• Analytics
Software Royalties
• Properties
• Talent
IP Licensing

30. T H E R E I S N O S I N G L E L T V
LTV varies among customers

31. Cohorts
Time of year
Stage of product lifecycle
Holidays

32. Segments
Age
Sex
Income
Interests

33. Sources
Incentived
ads
Targeted
search ads
Television
Virality Press
Cross
promotion

34. I T I S A P R E D I C T I O N
Uncertainty of LTV

35. Uncertainty Principle
Quantum Mechanics
• The universe is random
• Perfect predictions are impossible if the universe is random
Not a function that creates a value
You are predicting a future event
Create a range, not a number
• Albert Pujols is likely to hit 30-40 home runs is more accurate than Pujols is
likey to hit 36 home runs
Models are simplifications of the world

36. Risk vs Uncertainty
Risk
Something you can put a
price on
Uncertainty
Risk that is hard to
measure
Do not
confuse
uncertainty
for risk
Correlation of past data
does not create certainty

37. The major difference between a thing that might go wrong and a thing that cannot possibly go wrong is
that when a thing that cannot possibly go wrong goes wrong it usually turns out to be impossible to get at
or repair,” wrote Douglas Adams in The Hitchhiker’s Guide to the Galaxy series.
Wrong assumptions can have profound effects
• Independence of variables
• Mortgage industry
Chaos Theory
• Not a synonym for the game industry
• A small change in initial conditions can produce a large
and unexpected divergence in outcomes
• Major risk when modeling against past performance

38. Do not discount qualitative information
More data is better than less
This includes non-quantitive measures
Billy Beane has dramatically increased scouting
The Smell Test

39. Avoid Overfitting
Mistaking noise for signal
Fitting a statistical model to
match past observations
Test how much of the
variability of the data is
accounted for by your model

40. Solutions
• Think probabilistically
• Distribution shows honest uncertainty
Create LTV range
• Can validate assumptions
A/B Test
• Regularly (weekly or monthly) compare data with predictions
• “When the facts change, I change my mind”, John Maynard Keynes
Surveillance
Avoid Overfitting
Include qualitative data

41. L L O Y D @ V E R U S E N T E R T A I N M E N T G R O U P . C O M
W W W . L L O Y D M E L N I C K . C O M
@ L L O Y D M E L N I C K
Thank you