Not sure when (or if) to run a sale? Not sure what IAP items to offer? In this session, Playtika EVP Salim Mitha and Amazon show you what works. We share best practices and analytics data that we've aggregated from the top 50 in-app purchase (IAP) grossing games in the Amazon Appstore. We cover user retention and engagement data comparisons and examine several purchasing UI layouts to learn how to manage and present IAP item selection. We also cover how to manage IAP price points and how and when to tailor price variety, sales, and offers for customers. You get actionable data and suggestions that you can use on your current as well as future projects to help maximize IAP revenue.

1. November 12, 2014 | Las Vegas, NV
AFF201What the Top 50 Apps Do with IAP That the Rest of Us Don’tAnd How Playtika Uses This Knowledge to Maximize Revenue
Mike Hines, Developer Evangelist, Amazon
Salim Mitha, EVP Product + Monetization, Playtika (Caesars Interactive)

2. •How the top 50 did vs. the rest of us
•What the top 50 did differently
•How Playtika uses Top 50 strategy

3. 3
The Amazon Appstore reaches millions of customers in 236 countries and territories worldwideAndroidFire phoneKindle FireFire TV and Fire TV StickBB 10

5. Group A: Top-50 Grossing
Source: Amazon Appstore, March 2014
Group B: Rest of Freemium

6. Group A: Top-50 Grossing
iiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiii
Source: Amazon Appstore, March 2014
Group B: Rest of Freemium
iiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiii
100
100
installed

7. Group A: Top-50 Grossing
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiii
Source: Amazon Appstore, March 2014
Group B: Rest of Freemium
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
Iiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiii
41
42
In active
59
58
active

8. Group A: Top-50 Grossing
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiii
Source: Amazon Appstore, March 2014
Group B: Rest of Freemium
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
Iiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiii
13
18
uninstalled
59
58
active

9. GroupA:Top-50 Grossing
iii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiii
Source: Amazon Appstore, March 2014
Group B: Rest of Freemium
iii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiii
13
18
uninstalled
59
58
active
3
3
paying

10. 2.6
2.9
Source: Amazon Appstore, March 2014
Group A: Top-50 Grossing
iii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiii
Group B: Rest of Freemium
iii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiii
13
18
uninstalled
59
58
active
3
3
paying
# of sessions / active
session length / active
(minutes)
×
=
avg. session length
(minutes)
6.9
7.4
18
22

11. 6.9
7.4
2.6
2.9
Group A: Top-50 Grossing
iii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiii
Source: Amazon Appstore, March 2014
Group B: Rest of Freemium
iii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiii
=
×
# of items / paying
100%
112%
avg. selling price
100%
136%
100%
154%
ARPPU
13
18
uninstalled
59
58
active
3
3
paying
# of sessions / active
session length / active
(minutes)
×
=
avg. session length
(minutes)
18
22

12. Source: Amazon Appstore, March 2014
Group A: Top-50 Grossing
ii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiii
Group B: Rest of Freemium
ii
Iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiii
# of sessions / active
session length / active
(minutes)
×
avg. session length
(minutes)
17
25
uninstalled
34
37
active
1
1
paying
=
×
# of items / paying
100%
106%
avg. selling price
100%
107%
100%
114%
ARPPU
6.7
7.7
3.2
3.5
21
27
=
# of sessions / active

13. Group A: Top-50 Grossing
iiiiiiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiiiii
Source: Amazon Appstore, March 2014
Group B: Rest of Freemium
iiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiii
# of sessions / active
session length / active
(minutes)
×
avg. session length
(minutes)
19
28
uninstalled
19
23
active
=
×
# of items / paying
100%
107%
avg. selling price
100%
122%
100%
131%
ARPPU
2.6
3.2
15
25
=
# of sessions / active

14. Group A: Top-50 Grossing
iiiiiiiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
Source: Amazon Appstore, March 2014
Group B: Rest of Freemium
iiiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiii
# of sessions / active
session length / active
(minutes)
×
avg. session length
(minutes)
20
32
uninstalled
14
18
active
=
×
# of items / paying
100%
102%
avg. selling price
100%
121%
100%
124%
ARPPU
5.7
7.4
2.6
3.2
15
24
=
# of sessions / active

15. Group A: Top-50 Grossing
iiiiiiiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
Source: Amazon Appstore, March 2014
Group B: Rest of Freemium
iiiiiiiiiii
iiiiiiiiiiiiiiiiiiiii
# of sessions / active
session length / active
(minutes)
×
avg. session length
(minutes)
21
34
uninstalled
10
14
active
=
×
# of items / paying
100%
111%
avg. selling price
100%
108%
100%
120%
ARPPU
5.7
7.3
2.5
3.1
14
22
=
# of sessions / active

16. Group A: Top-50 Grossing
iiiiiiii
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
Source: Amazon Appstore, March 2014
Group B: Rest of Freemium
iiii
iiiiiiiiiiiiiiiiiiiiiiii
# of sessions / active
session length / active
(minutes)
×
=
avg. session length
(minutes)
22
36
uninstalled
4
8
active
=
×
# of items / paying
100%
103%
avg. selling price
100%
128%
100%
131%
ARPPU
5.9
7.3
2.4
3.1
14
23
# of sessions / active

17. Hours Since App Download
Source: Amazon Appstore, March 2014
0
24
48
72
96
120
144
168
192
216
240
264
288

18. Days User Owned App
80%
90%
100%
110%
120%
130%
140%
150%
160%
170%
1
4
7
10
13
16
19
22
25
28
Source: Amazon Appstore, March 2014
+60%
average
selling price

20. What the top 50 do differentlyREVENUE

21. ?
GIVE THEM A REASON TO COME BACK
MAKE IT EASY TO COME BACK
ENGAGE CUSTOMER EARLY
Source: Amazon Appstore, March 2014

22. Apps with tutorials that introduce IAP items
HAVE A 2.5xHIGHER CONVERSION RATE

23. Apps that show users how to “consume”
GET MORE REPEAT ORDERS
Games that provide a post-purchasing tutorial generated 65%more repeat orders than the market average.
Source: Amazon Appstore, March 2014

24. 69%
100%
145%
1-5 Items
6-10Items
11-15Items
Games with bigger selection
RECEIVE MORE ORDERS PER CUSTOMER
Developers that add new items regularly are able to re-engage their paying customers, and developers who differentiate offers for long-time customers sell more items at higher prices.
Source: Amazon Appstore, March 2014

25. 147%
101%
52%
0%
50%
100%
150%
200%
1-5PricePoints
6-10PricePoints
11-15PricePoints
Don’t confuse your customerOFFER VARIETY, BUT NOT TOO MUCH
Source: Amazon Appstore, March 2014

26. To sell more IAP items,
BE CLEAR ABOUT VALUE
Make it obvious what the benefit is for buying different price items. Confused customers don’t buy anything.
Source: Amazon Appstore, March 2014

27. To sell more IAP items,
BE CLEAR ABOUT VALUE
Make it obvious what the benefit is for buying different price items. Confused customers don’t buy anything.
Source: Amazon Appstore, March 2014

28. Total Marketplace: Assortment by Price Point
Source: Amazon Appstore, March 2014
31%
29%
7%
12%
11%
5%
3%
1%
14%
11%
6%
3%
16%
16%
11%
9%
0%
10%
20%
30%
40%
0.99
1.99
2.99
4.99
9.99
19.99
49.99
99.99
% of Assortment
% of Sales
Most of us have too muchCONCENTRATION ON LOW PRICES

29. Source: Amazon Appstore, March 2014
Top 50 Apps: Assortment by Price Point
28%
15%
10%
13%
11%
9%
9%
5%
32%
19%
7%
4%
10%
12%
5%
4%
0%
10%
20%
30%
40%
0.99
1.99
2.99
4.99
9.99
19.99
49.99
99.99
% of Assortment
% of Sales
We find that theTOP GAMES ARE MORE BALANCED

30. Games with bigger selection
RECEIVE MORE ORDERS
Tutorials that teach buying and using
HAVE HIGHER CONVERSION AND REPEAT ORDERS
Highlighting customer value
MAKES IT EASY TO SHOP
Cater to your best and longest customers
DIFFERENTIATE YOUR IAP CATALOG

33. Tuning Game Difficulty
WILL ENCOURAGE LONGER SESSIONS
Too hard, and users will abandon. Too easy, and they can get bored. Just right, and it becomes addictive!

34. Adopting Social
CAN CREATE BUZZ AND KEEP USERS ENGAGED
This will result in more friend-to-friend marketing as players share their achievements and ranks. Players will also compete with friends and leaders and stay engaged.

35. Leaderboards and Achievements are
THE MINIMUM BAR FOR SOCIAL ENGAGEMENT

36. Design IAP into the fabric of your game
MAKE IT EASY TO BUY
Offering ways to buy your IAP items when they are needed will increase conversion.

37. Design IAP into the fabric of your game
MAKE IT EASY TO BUY
Offering ways to buy your IAP items when they are needed will increase conversion.

38. Design IAP into the fabric of your game
MAKE IT EASY TO BUY
Offering ways to buy your IAP items when they are needed will increase conversion.
Apps that made it easy to shop
INCREASED REVENUE 75% (ARPPU)
Source: Amazon Appstore, March 2014

39. Increase time and count of sessions
TWEAK GAME DIFFICULTY & ADD SOCIAL
Increase engagement with IAP
INTEGRATE IAP INTO APP DESIGN
Know. Don’t guess
IMPLEMENT A|B TESTING

43. How PlaytikaImplements Top 50 Strategy

44. Two big
MARKETING QUESTIONS
How much can we pay for traffic? What is our “Payback period”?
What is going on with Daily Active Users? How can we grow it?

45. Assumptions about
PAYBACKPERIOD
First 7–14 days is critical (for monetization & payback)
Game follows a typical arc

46. Reality about
PAYBACKPERIOD
Month 2 is super critical
Our LTV is spread out over many months
“Evergreen” game & “evergreen” content

47. Assumptions about
DAILY ACTIVE USERS (DAU)
Black magic
Most of the DAUs are from recent acquisition activity so we need to keep topping up the funnel

48. Reality about
DAILY ACTIVE USERS
Over 33% of our players have
played 2+ years!
60% of our DAU comes from
players over tenure > 1 year
Retention & reactivation
matters
DAU Composition by Install Cohort

49. Tying back DAU & Buyers – How “potent” is our DAU?
Very Cool Metric: Percentage % of DAU that are Payers
17%
18%
19%
20%
21%
22%
23%
Percentage of of DAU that Payers

50. To make a game profitable
RETENTION MATTERS
With good retention and reactivation
YOUR PAYBACK PERIOD IS LONGER THAN YOU THINK
Understand your Daily Active Users
KNOW % OF DAU THAT ARE PAYING CUSTOMERS

51. Two big
MONETIZATION QUESTIONS
Who are our buyers? Are they gonnago away?
Should I run a sale? Or am I training users? Will I get a Revenue Hangover?

52. 52
20% of Buyers represent 90% of Revenue
6%
14%
81%
65%
24%
11%
Buyers %
Revenue %
Med
Low
High
Importance of our VIP Payers
WHO ARE OUR BUYERS?
REVENUE PARETO PRINCIPLE

53. +93% YoY growth +59% YoY growth
0
10,000
20,000
30,000
40,000
50,000
60,000
High Spenders Cohort Population
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
Medium Spenders Cohort Population
The problem with revenue/user concentration:
ARE THEY GONNA GO AWAY?
Metric: Buyer Cohort Size Growth

54. 83%
55%
87%
65%
90%
74%
0%
20%
40%
60%
80%
100%
PLAY
PAY
High Spender Play & Pay % over the last 30 / 60 / 90 Days
Play - 30 Days
Play - 60 Days
Play - 90 Days
65%
29%
71%
38%
76%
47%
0%
20%
40%
60%
80%
100%
PLAY
PAY
Medium Spender Play & Pay % over the last 30 / 60 / 90 Days
Play - 30 Days
Play - 60 Days
Play - 90 Days
Fostering good growth
HOW ACTIVE ARE OUR BUYERS?
Metrics: 1) Play % over the last 30/60/90 days2) Pay % over the last 30/60/90 days

55. Monitor and create offers for new buyers
Daily New Buyers
+25%in
FTB
Let’s not ignore our non payers…
FOCUS ON FIRST TIME BUYERS (FTB)

56. Is it a good idea?
SHOULD I RUN A SALE?
We looked at:
% of revenue coming from Normal Payment Page vs. Sale Page
Staggered sale dates for unpredictability

57. Metric: Average Currency Balance of Payers
•When balances are low, the timing is right
•Content cadence is critical here
When is
THE RIGHT TIME TO RUN A SALE?

58. Metric: Absorption and Velocity of Paid Sale Currency
74.6%
49.0%
11.4%
27.1%
4.9%
19.5%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Normal Day
Sale
Money supply can
IMPACT FUTURE REVENUE

59. Jan-13
Feb-13
Mar-13
Apr-13
May-13
Jun-13
Jul-13
Aug-13
Sep-13
Oct-13
Nov-13
Dec-13
Jan-14
Feb-14
Mar-14
Apr-14
May-14
Jun-14
Revenue Trend(Daily Max, Min and Average)
Max
Min
Average
Sale Timing + Content CadenceHANGOVER MANAGEMENT
Look at the Min & Max
Steadily increase Min

60. Understand what your users are doing
USE ANALYTICS
Does 90% of revenue come from 20% of your buyers?
MITIGATE CONCENTRATION RISK
Optimal sale timing is…
WHEN HARD CURRENCY BALANCES LOW
To prevent sale hangovers
PAIR SALES WITH NEW CONTENT

61. Metrics: Conversion, Monthly Buyers & ARPPU
Monthly ARPPU
Follow the best practices of the top 50
Bottom Line
BRINGING IT ALL TOGETHER

62. Most of your revenue will come from long-term users
DIFFERENTIATE YOUR OFFERS
Encourage longer sessions, long-term use, greater conversion, more reorders
USE A|B TESTING TO TUNE APP YOUR APP
Reduce revenue concentration, increase long-term payers
MAKE OFFERS JUST FOR LONG-TERM NON-PAYERS
Keep users engaged and encourage conversion
COMBINE SALES AND CONTENT UPDATES

63. TO LEARN MORE…
…about the Amazon Appstore and APIs that can help you monetize, visit the Amazon DevPortal:
http://developer.amazon.com/API

64. NextSessions:
Wed2:15 in Delfino4105
AFF302: ResponsiveGame Design
Thur11:00 in Murano3304
AFF202: Everything You Need to Know about Building Apps for the Fire Phone
Thur4:30 in Murano3304
AFF301: Fire Phone: The Dynamic Perspective API, Under the Hood

65. https://developer.amazon.com/welcome
https://developer.amazon.com/blogAndroidFire phoneKindle FireFire TV and Fire TV StickBB 10

66. http://bit.ly/awsevals