Finding Potential for Monetization in Social Casino | Michal Witkowski
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Transcript of Finding Potential for Monetization in Social Casino | Michal Witkowski
![Page 1: Finding Potential for Monetization in Social Casino | Michal Witkowski](https://reader034.fdocuments.net/reader034/viewer/2022051404/586f89fd1a28ab54768b622b/html5/thumbnails/1.jpg)
Finding Potential for Monetization in Social Casino
Michał Witkowski
GameDesire Ltd.
Head of Product Analytics
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About company
• GameDesire Ltd. – est. 2004 (previously known as Ganymede)
• The leading social casino games developer in Poland
• Key products:• Snooker Live Pro
• Pool Live Pro
• Poker Live Pro
• GameDesire.com
• Key markets:• Poland
• Brasil
• USA
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About me
• Game data analyst by profession• Head of Product Analytics at GameDesire Limited
• Psychologist and researcher by education• Jagiellonian University in Krakow
• LangUsta Lab for Psychology of Language
• Gamer by passion• PC games (rouglikes, RPG, turn-based strategy)
• Narrative RPGs (World of Darkness, Neuroshima)
• Modern board games
• Chess
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Introduction
• Main goal:• Social casino vs other casual games – similarities and differences
• Deriving possible strategies from data
• Presentation plan:1. Information about analysed games and data scope
2. Engagement metrics
3. Basic financial metrics
4. Lifetime value analysis
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Social casino games
In-house data from the following games:
• Poker Texas Hold’em („Poker Texas”)
• Golden Reels Casino Slots („Slots”)
• Bingo
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Non-casino casual games
In-house data from the following games:
• Pool Live Pro
• Snooker Live Pro
• Mahjong
• Last Temple
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Design of the analysis
• Players group: Web (non-mobile) players and their paymentsonly. Extra focus on FB
• Data sources:• In-house analytical system
• Engagement and monetisation: representative time period from 2015,allowing for comparison across the products
• Lifetime value analysis: 2014-2015 payments data
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Traffic metrics
0.0% 100.0%
Slots
Poker Texas
Non-casino
Bingo
Traffic metricsFB / all partners comparison
Reactivations New registrations
Commentary:
• Observation: Newly registered players overflow in Slots and Poker
• Possible action: Take 1st session funnel to perfection
• Observation : Little new registrations on Bingo
• Possible action : Work on reactivations and loyalty of your Bingo
players
New regsitrations / MAU
Reactivations / MAU
New regsitrations / MAU
Reactivations / MAU
FB
All
Traffic metricsBenchmarked against non-casino games
Poker Texas Slots Non-casino Bingo
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Cohort retention
D7 / D1 retention ratio
D28 / D1 retention ratio
D7 / D1 retention ratio
D28 / D1 retention ratio
FB
All
D1 / 7 / 28 cohort retention comparisonSplit per game and affiliate
Slots Poker Texas Bingo Non-casino
• Cohort vs rolling retention
• 100/50/25 rule
• Is the rule present in social
casino?• Repeatability
• Many similar games on the
market
• Competitive market
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Cohort retention
D1 retention
D7 retention
D28 retention
D1 retention
D7 retention
D28 retention
FB
All
D1 / 7 / 28 cohort retentionBenchmarked against non-casino games
Non-casino Slots Poker Texas Bingo
Commentary:
• Observation: low long-term retention
• Possible action: long-term retention mechanism
• Observation: low FB retention
• Possible action: dedicated websites? Notification
mastery?
0.0% 100.0%
Non-casino
Poker Texas
Bingo
Slots
Players' retentionFB / all partners comparison
D1 retention D7 retention D28 retention
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Game sessions metrics
Session time
Sessions played daily per user
Session time
Sessions played daily per user
FB
All
Game sessions metricsBenchmarked against non-casino games
Poker Texas Slots Bingo Non-casino
0.0% 100.0%
Non-casino
Bingo
Poker Texas
Slots
Game session metricsFB / all partners comparison
Sessions played daily per user Session time
Commentary:
• Observation: Short Slots and Bingo sessions
• Possible action: Show as much as possible, as quickly
as possible (Tradeoff: information overflow / content
hype)
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Basic financial metrics
Conversion rate
ARPPU
ARPU
All
Basic financial metricsBenchmarked against non-casino games (all partners)
Non-casino Slots Poker Texas Bingo
Conversion rate
ARPPU
ARPU
FB
Basic financial metricsBenchmarked against non-casino games (FB only)
Non-casino Slots Poker Texas Bingo
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Basic financial metrics
0.0% 100.0%
Conversion rate
ARPPU
ARPU
Basic financial metricsFB / all partners comparison
Non-casino Slots Poker Texas Bingo
• Observation: Social casino relatively
less profitable on FB
• Possible action: Use dedicated
gaming websites / platforms
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Lifetime value analysis
Probability of first payment per lifetime dayBenchmark against non-casino games
Bingo Non-casino games Poker Texas Slots
Bingo
Non-casino games
Slots
Poker Texas
Days to first payment (median)
Commentary:
• Observation: payers in social casino are moreimpulsive
• Possible action: Unethical and short-term, butpossiblyprofitable high early monetisation pressure
• Observation: Most Poker payers emerge by D2• Possible action: Early VIP offers for your payers
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Lifetime value analysis
DAY 0 DAY 30 DAY 60 DAY 90 DAY 120 DAY 150 DAY 180
LTV realisation curve
Bingo Slots Poker Texas Non-casino games
• Observation: Poker players tend to
realise their LTV much earlier than
other games
• Possible actions: Experiment with
1st session monetisation mechanisms; create attractive early
payments offers
• Observation: Bingo and Slots
payers realise their LTV like casual payers
• Possible action: create offers that
would be attractive for mid- and
long-term players
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Lifetime value analysis
Probability of becoming a multiple-paying user per day of first transaction made
Bingo Non-casino games Poker Texas Slots
Average amount of payments per first payment date
Benchmarked against non-casino games
Bingo Non-casino games Poker Texas Slots
Commentary:
• Observation: The most valuable players in Bingo deposit first after 6-9
months of playing
• Possible action: treat your acquired traffic as a long-term investment,
work on players’ loyalty and long-term retention
• Observation: Tradeoff in payments - pay early or pay frequently
• Possible actions: choose which one works best for you
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Lifetime value analysis
DAY 1+ DAY 11+ DAY 31+
Percentage of a multiply-paying users yet to make their first payment
Non-casino games Bingo Slots Poker Texas
Commentary:
• Observation: Multiple Poker
payers emerge very early on
• Possible actions: VIP clubs and
special offers; quick contact with
paying users
• Observation: Multiple Bingo
payers emerge relatively late
• Possible action: Focus on loyalty
rather than quick monetisation
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Summary - Bingo
• Traffic characteristics:• Loyal and conservative users
• The most casual of the three social casino games
• Engagement strategy: • Think and plan in a very long term
• Work towards loyalty and reactivations
• Monetisation strategy:• Don’t pressure monetisation too early, focus on retention
• After the critical mass is reached, the game will produce steady income
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Summary – Poker Texas
• Traffic characteristics:• Impulsive, highly-monetising users• Unstable, leaving often and usually early
• Engagement strategy:• Working on short-term retention will ensure the quickest and highest profit of all
analysed games• Working on long-term retention might be very difficult (competition), but will help in
keeping long-term payers satisfied and faithful
• Monetisation strategy:• Important tradeoff: quick payments vs multiple payments• D0 is critical in Poker Texas in generating LTV• BUT most of the early-paying users don’t deposit again, as opposed to D1+ first-time
payers• Rely on VIP clubs and / or special offers to keep your paying users engaged• Consider using a dedicated website for Poker
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Summary - Slots
• Traffic characteristics:• Moderately impulsive payers• Play for short preiods of time
• Engagement strategy:• Design your game to show off the important content as early and as
concisely as possible• Focus on mid-term retention
• Monetisation startegy:• Using monetisation pressure after a few sessions will be most
profitable
• Use mid-term retention mechanisms to get your players there
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The end!
Thank you for attention!
Do you have any questions?