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User Acquisition focused on LTV on steroids
The document discusses advanced strategies for marketing involving customer lifetime value (LTV) with a focus on feature selection using machine learning techniques to optimize user acquisition campaigns. It emphasizes the importance of identifying relevant user behaviors and conversion probabilities to enhance campaign effectiveness, particularly in mobile gaming environments where the majority of users do not make purchases. The insights provided aim to help advertisers target high-value users more effectively through data analysis and strategic feature implementation.
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User Acquisition focused on LTV on steroids
- 1. Proprietary + Confidential UAfocused on LTV On steroids with Feature Selection Przemyslaw Modrzewski, Principal Analytical Lead, Google @modrzewski
- 2. Proprietary + ConfidentialProprietary+ Confidential We are facing a marketing revolution for…… last 20 years... Clicks Installs ROAS / ROI Profit Customer Equity Customer Lifetime Value
- 3. Proprietary + ConfidentialProprietary+ Confidential What LTV is after all? Profits Acquisition Retention Cross,up-selling Costs Customers life-cycle
- 4. Proprietary + ConfidentialProprietary+ Confidential Problem with game players !
- 5. Proprietary + ConfidentialProprietary+ Confidential Reality…. (we all know that) 98% to analyze intent All In-App Users Most Apps have only <2% Paid Users Paid Users >60% One-time Purchasers Big Whales<10%
- 6. Proprietary + ConfidentialProprietary+ Confidential Acquisition strategy - Options we have…. Paid Users Will-Pay Users Active Users TOPLayer -- to Predict pLTV ● Goal KPI：ROI, to acquire more high value users ● Data Needed：All Paid User in-app behavior & payment data MIDDLE Layer -- to Predict Conversion Probability ● Goal KPI：Payer Rate, to acquire more paid users ● Data Needed：Feature Selected Active Users in-app behavior data Baseline -- Feature Selection ● Goal: Select what user behaviors are important to payments ● Data Needed：All Active Users in-app behavior data
- 7. Proprietary + ConfidentialProprietary+ Confidential Feature selection makes a difference OBJECTIVE A mobile advertiser wants to identify the best event for UAC Action where IAP as the optimization goal does not work well FEATURE SELECTION APPROACH Run through all performance related features and find the one(s) with the both high relevance to IAP and high occurrence itself PREVIOUS APPROACH Use install or IAP as UAC optimization goal IAP Install
- 8. Proprietary + ConfidentialProprietary+ Confidential Events can extend “the pool” of users Events in game Whales Conversions
- 9. Proprietary + Confidential Whatmakes Feature Selection
- 10. Proprietary + ConfidentialProprietary+ Confidential TECHNOLOGY Use Cutting edge Machine Learning (e.g. ExtraRandomForest) to find optimum feature for action OUTCOME Each feature gets an Importance, Frequency and Correlation scores. Selected features will need a high score on these 4 criterions. IMPLEMENTATION Directly leverage the in-app events in AdWords Importance: Unique User Frequency: Active User Correlation: Correlation: PRIMARY criterion for sorting the list. The higher the number, the more important the feature is for user classification Number of unique users triggered this feature/action Criterion measuring how likely increasing the frequency of actions can make a user convert to paid user Criterion measuring how likely a user triggered a certain action will be converting to a paid user Feature Selection System
- 11. Proprietary + Confidential Somegames is community-like where valuable users are not only who made in-app-purchase but also non-paid but highly active. Select the most suitable features used in UAC to enhance the performance of UAC campaign Feature Selection - what can do with it?
- 12. Proprietary + Confidential PaymentAmount above threshold* (Y/N) Paid user (Y/N) Pay_Count above threshold* (Y/N) Active Days above threshold* (Y/N) Login Times above threshold* (Y/N) Online Time above threshold* (Y/N) *threshold is determined by clients*threshold is determined by clients ROI/PURCHASE OBJECTIVE RETENTION OBJECTIVE Different objectives of conversion
- 13. Proprietary + Confidential Segmentmarkets into 4 tiers by Quadrant Analysis with: ● Install to In-app-Purchase Conversion Rate ● Conversion Lag in Days X-axis, Install to In-app-Purchase Conversion Rate, Y-axis, Conversion Lag in Days, Each dot represents a market, Quadrant Segment Threshold, average statics of x and y axis Pay Rate ConversionLag average average IAP event is very often difficult to recognize by UA systems
- 14. Proprietary + ConfidentialProprietary+ Confidential We have to remember about an important criteria for events in UAC DELAY No later than 7 days post install Ideally D2/3 The shorter the better RELEVANCY Has to be deterministic and correlated with the business objective CONVERSION VOLUME Min. 20 unique user converted per day Ideally 50+ The higher the better Purchase Registration Add to cart
- 15. Proprietary + Confidential Identifydifferent proxy events, with Feature Selection, for different markets that are on the path to purchase T3/T4 Markets: combine the upper funnel events ● Android: Buy Item ● iOS: Group and clan message All Markets: ● IAP T1/T2 Markets: lower funnel event ● IAP ● Start payment Results T2 IAP -> BuyItem* AU/CA/SG Android NZ/CH IOS Tier Optimize T2 T3 25% 7 Days’ ROI 6X 2X AU/CA/SG IOS None -> Group & Clan Message IAP -> Group & Clan Message * Approach * BuyItem : Buy items i.e. weapon, skins, etc. with gaming currency *Group & Clan Message : How many messages sent in group or clan We can go wider (upper-funnel) but still be careful
- 16. Proprietary + Confidential UACfor in-app actions with Feature Selection (3 events) Campaign 1 for IAP Campaign 2 for IAP Campaign 3 for IAP Campaign 4 for IAP Campaign 5 for IAP Campaign 1 for FS events We can acquire 35 users (ave.) instead of one.
- 17. Proprietary + Confidential Wecan be flexible in picking events if FS shows significance
- 18. Proprietary + Confidential UACfor in-app actions with Feature Selection
- 19. Proprietary + Confidential Eventsare 250 cheaper then IAP…… ;) Event 1 Event 2 Event 3 Event 4 Event 5
- 20. Proprietary + Confidential Dowe have a correlation in event and revenue?
- 21. Proprietary + Confidential Becareful with counting profitability with events
- 22. Proprietary + Confidential Lastbut not least Deep but less Volume Condition A AND Condition B 1. Use “AND” to combine features only if no single feature is insightful and you don’t want to explore new features 2. Use “AND” when you are ROI driven 3. KPI: ROI, CPA, CVR to pay Shadow but more Volume Condition A OR Condition B 1. Use “OR” to combine features only if multiple single features are insightful 2. Use “OR” when you are Ecosystem driven 3. KPI: ROI, Retention Rate, Cost per Retention
- 23. Proprietary + ConfidentialProprietary+ Confidential Thanks to Feature Selection we can “swim in bigger pool” ;) 98% to analyze intent All In-App Users Most Apps have only <2% Paid Users Paid Users >60% One-time Purchasers Big Whales<10%
- 24. Proprietary + Confidential FeatureSelection is easy in GCP :) Cloud AutoML Model is now trained and ready to make predictions This model can scale as needed to adapt to customer demands Upload labeled structured data Train your model Evaluate (Classification/Regression) Class A Class B Class C Class D Class E ID Feature Feature ... Label ... ... ID Feature Feature ... ... ...
- 25. Proprietary + Confidential ThankYou Thank You Thank You Contact: modrzewski@google.com