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Finding Potential for Monetization in Social Casino | Michal Witkowski

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Delivered at Casual Connect Europe 2016

Social casino players' behavior differs from that of other casual gamers. The presentation aims at showing these differences in terms of the most important monetization and engagement KPIs, with an extra focus on Facebook players. The data from the analysis is then used to infer about potential business strategies that can help in getting more loyal and higher-paying players in social casino games.

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Finding Potential for Monetization in Social Casino | Michal Witkowski

  1. 1. Finding Potential for Monetization in Social Casino Michał Witkowski GameDesire Ltd. Head of Product Analytics
  2. 2. 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
  3. 3. 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
  4. 4. 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
  5. 5. Social casino games In-house data from the following games: • Poker Texas Hold’em („Poker Texas”) • Golden Reels Casino Slots („Slots”) • Bingo
  6. 6. Non-casino casual games In-house data from the following games: • Pool Live Pro • Snooker Live Pro • Mahjong • Last Temple
  7. 7. Design of the analysis • Players group: Web (non-mobile) players and their payments only. 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
  8. 8. Traffic metrics 0.0% 100.0% Slots Poker Texas Non-casino Bingo Traffic metrics FB / 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 FBAll Traffic metrics Benchmarked against non-casino games Poker Texas Slots Non-casino Bingo
  9. 9. Cohort retention D7 / D1 retention ratio D28 / D1 retention ratio D7 / D1 retention ratio D28 / D1 retention ratio FBAll D1 / 7 / 28 cohort retention comparison Split 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
  10. 10. Cohort retention D1 retention D7 retention D28 retention D1 retention D7 retention D28 retention FBAll D1 / 7 / 28 cohort retention Benchmarked 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' retention FB / all partners comparison D1 retention D7 retention D28 retention
  11. 11. Game sessions metrics Session time Sessions played daily per user Session time Sessions played daily per user FBAll Game sessions metrics Benchmarked against non-casino games Poker Texas Slots Bingo Non-casino 0.0% 100.0% Non-casino Bingo Poker Texas Slots Game sessionmetrics FB / 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)
  12. 12. Basic financial metrics Conversion rate ARPPU ARPU All Basic financial metrics Benchmarked against non-casino games (all partners) Non-casino Slots Poker Texas Bingo Conversion rate ARPPU ARPU FB Basic financial metrics Benchmarked against non-casino games (FB only) Non-casino Slots Poker Texas Bingo
  13. 13. Basic financial metrics 0.0% 100.0% Conversion rate ARPPU ARPU Basic financial metrics FB / all partners comparison Non-casino Slots Poker Texas Bingo • Observation: Social casino relatively less profitable on FB • Possible action: Use dedicated gaming websites / platforms
  14. 14. Lifetime value analysis Probability of first payment per lifetime day Benchmark 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 more impulsive • Possible action: Unethical and short-term, but possiblyprofitable high early monetisation pressure • Observation:Most Poker payers emerge by D2 • Possible action:Early VIP offers foryour payers
  15. 15. 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
  16. 16. 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
  17. 17. 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
  18. 18. 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
  19. 19. Summary – Poker Texas • Traffic characteristics: • Impulsive, highly-monetising users • Unstable, leaving often and usually early • Engagement strategy: • Workingon short-term retention will ensure the quickest and highest profit of all analysed games • Workingon 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
  20. 20. 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
  21. 21. The end! Thank you for attention! Do you have any questions?

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