3.28B (E) +60% Whole gaming: +13% +116% ...like really fast. More than 3.2B downloads in 2018 is expected Source: AppAnnie. Note: only apps, published by Playgendary, Voodoo, Ketchapp Studio, Playdots, Easybrain, Miniclip, Tap Tap Games, SuperTapx, Kwalee, TabTale, BitMango, BoomBit, FuturePlay, Green Panda, Homa 3.28B (E)
Casual/New Economical Enthusiasts Sporadic Spenders Whales Value Scale Having the right user segment mix is key for the success of the game The right user segment mix is function of • Studio strategy • Monetisation model • Game maturity
Scale Engagement Revenue What are the associated KPIs? - Max scale below tCPI - Max scale for a specific budget Understanding your app’s strategy and goals
Scale Engagement Revenue What are the associated KPIs? - Max scale below tCPI - Max scale for a specific budget - Short term retention (D1, D3) - Med term retention (D7,14) Understanding your app’s strategy and goals
Scale Engagement Revenue What are the associated KPIs? - Max scale below tCPI - Max scale for a specific budget - Short term retention (D1, D3) - Med term retention (D7,14) - Short term ROAS (D3, D7) - Med term ROAS (D14, D30) - Cost per purchaser - Cost per purchase at x days Understanding your app’s strategy and goals
Scale Engagement Revenue What are the associated KPIs? - Max scale below tCPI - Max scale for a specific budget - Short term retention (D1, D3) - Med term retention (D7,14) - Short term ROAS (D3, D7) - Med term ROAS (D14, D30) - Cost per purchaser - Cost per purchase at x days Events to track Understanding your app’s strategy and goals
Scale Engagement Revenue What are the associated KPIs? - Max scale below tCPI - Max scale for a specific budget - Short term retention (D1, D3) - Med term retention (D7,14) - Short term ROAS (D3, D7) - Med term ROAS (D14, D30) - Cost per purchaser - Cost per purchase at x days Events to track - Install /1st open Understanding your app’s strategy and goals
Scale Engagement Revenue What are the associated KPIs? - Max scale below tCPI - Max scale for a specific budget - Short term retention (D1, D3) - Med term retention (D7,14) - Short term ROAS (D3, D7) - Med term ROAS (D14, D30) - Cost per purchaser - Cost per purchase at x days Events to track - Install /1st open - App open at Dx - Level X achieved - X sessions played - Tutorial completion Understanding your app’s strategy and goals
Scale Engagement Revenue What are the associated KPIs? - Max scale below tCPI - Max scale for a specific budget - Short term retention (D1, D3) - Med term retention (D7,14) - Short term ROAS (D3, D7) - Med term ROAS (D14, D30) - Cost per purchaser - Cost per purchase at x days Events to track - Install /1st open - App open at Dx - Level X achieved - X sessions played - Tutorial completion - Purchases with value - 1st time purchase - Virtual currency spent - iAP shop visited Understanding your app’s strategy and goals
Scale Engagement Revenue What are the associated KPIs? - Max scale below tCPI - Max scale for a specific budget - Short term retention (D1, D3) - Med term retention (D7,14) - Short term ROAS (D3, D7) - Med term ROAS (D14, D30) - Cost per purchaser - Cost per purchase at x days Events to track - 1st open - App open at Dx - Level X achieved - X sessions played - Tutorial completion - Purchases with value - 1st time purchase - Virtual currency spent - iAP shop visited Preferred UAC Mix UAC Installs UAC Installs Advanced Understanding your app’s strategy and goals
Scale Engagement Revenue What are the associated KPIs? - Max scale below tCPI - Max scale for a specific budget - Short term retention (D1, D3) - Med term retention (D7,14) - Short term ROAS (D3, D7) - Med term ROAS (D14, D30) - Cost per purchaser - Cost per purchase at x days Events to track - 1st open - App open at Dx - Level X achieved - X sessions played - Tutorial completion - Purchases with value - 1st time purchase - Virtual currency spent - iAP shop visited Preferred UAC Mix UAC Installs UAC Installs Advanced UAC Actions (retention event) Understanding your app’s strategy and goals
Scale Engagement Revenue What are the associated KPIs? - Max scale below tCPI - Max scale for a specific budget - Short term retention (D1, D3) - Med term retention (D7,14) - Short term ROAS (D3, D7) - Med term ROAS (D14, D30) - Cost per purchaser - Cost per purchase at x days Events to track - 1st open - App open at Dx - Level X achieved - X sessions played - Tutorial completion - Purchases with value - 1st time purchase - Virtual currency spent - iAP shop visited Preferred UAC Mix UAC Installs UAC Installs Advanced UAC Actions (retention event) UAC Actions (revenue event) UAC Value* Understanding your app’s strategy and goals
is rendered on (e.g. Interstitial AdMob or YouTube TrueView). Ad Formats are auto generated from different assets Asset An ad component such a text, image or a video. Can either be manual assets provided by advertisers or automatic assets pulled by UAC from either App / Play store. Definitions
Serve via ad formats depending on network and inventory across all Google properties AdMob Interstitial AdMob Square AdMob Banner YouTube Native Mobile Web AdMob (all sizes) AdMob GIF YouTube TrueView AdMob Rewarded AdMob Native AdMob Portrait AdMob Square AdMob Landscape Mobile Web Text Input (Asset) Output (Ad Format) Play Homepage Play Browse Play Search Search Ads YouTube Native Gmail App Install AdMob (all sizes) Video Image HTML5
asset mix 4 text ideas Text lines in different order can appear as a separate ad, or they can combine with videos. As for images, the text lines can be matched only with landscape image (1200x628). Write standalone sentences in text lines because the system will automatically combine these to create the best text ad.
asset mix 20 html5 Recommended sizes (your assets will appear as full screen ads on the majority of devices): 320x480 (portrait) 480x320 (landscape) Mobile only (no Tablets) No audio / video media support Having a persistent “install now” button throughout is mandatory.
asset mix 20 videos We recommend to upload different versions of multiple assets across the top 3 recommended ratios. I.e. 10 landscape videos, 5 portrait and 5 square videos with different messages. YouTube is optimized for all video types. 70% of AdMob impressions are portrait.
to tap into value based optimization and to acquire new users who are likely to have a set return within their selected conversion window, either based on: • Dynamic transactions • Or user centric dynamic pLTV via s2s
to tap into value based optimization and to acquire new users who are likely to have a set return within their selected conversion window, either based on: Similar Audience Device IDs as hints. ‘Feed’ UAC with additional ‘user’ information it currently does not have, but advertisers can provide. • Dynamic transactions • Or user centric dynamic pLTV via s2s
to tap into value based optimization and to acquire new users who are likely to have a set return within their selected conversion window, either based on: Similar Audience Device IDs as hints. ‘Feed’ UAC with additional ‘user’ information it currently does not have, but advertisers can provide. UACe UAC for Engagement is a dedicated, automated, cross-channel (Search, Play, Display, YouTube) campaign driving users back into the app to complete a specific action/conversion. • Dynamic transactions • Or user centric dynamic pLTV via s2s
IDFA / Web_id of install / login_id as GA dimension age Number of days since install the data below is gathered for Numeric (0,1,2..) sessions Number of sessions by a certain day player_level in-game level reached (0+) battles Total In-game battles played messages Total in-app messages sent ... ... Binary (0 or 1) facebook_login Did the player use their facebook account for the app login? promo_used Did the player use any promo codes ... ... Categorical (A,B,C.) device User's device model, i.e. “Xiaomi” country User's location, i.e. “UK” ... ...
Start with simple (e.g. linear regression) • Collect features as much as you could. 10-20? 200-400-1000! ◦ Firebase, BigQuery, ClickHouse - some solutions to use
Start with simple (e.g. linear regression) • Collect features as much as you could. 10-20? 200-400-1000! ◦ Firebase, BigQuery, ClickHouse - some solutions to use • Save historical data (no re-writings)
Start with simple (e.g. linear regression) • Collect features as much as you could. 10-20? 200-400-1000! ◦ Firebase, BigQuery, ClickHouse - some solutions to use • Save historical data (no re-writings) • Define model quality metrics ◦ Precision / Recall ratio ◦ F1 score, Accuracy
Start with simple (e.g. linear regression) • Collect features as much as you could. 10-20? 200-400-1000! ◦ Firebase, BigQuery, ClickHouse - some solutions to use • Save historical data (no re-writings) • Define model quality metrics ◦ Precision / Recall ratio ◦ F1 score, Accuracy • Revise your model regularly