This document discusses optimizing user engagement on Facebook by leveraging user attributes and predictive algorithms. It introduces predictive best-fit optimization as an automated solution that can optimize in-app and open graph performance in real-time using various user data sources. This approach aims to provide insights and maximize key performance indicators like revenue, virality, and retention without the effort and limitations of traditional techniques like A/B testing and segmentation. The document also provides examples of how open graph optimizations around elements like publishing, creative, and timing increased user engagement for various games and apps.

1. Welcome to:
Real-Time Optimization:
Putting Facebook User Attributes to Work
- Going Beyond A/B Testing and User Segmentation
- Optimizing Open Graph
Alan Avidan − Executive Director
alan@BeesAndPollen.com
@beesandpollen

2. We’ll Cover:
1. The Playground: Games/Apps/Campaigns
2. Which User Attributes Can You Use for Optimization?
3. Predictive Best-Fit Optimization, and How Does it Lift
KPIs like Revenue, Virality, Engagement, Retention
4. Traditional Optimization Tools:
Analytics, A/B Testing, User Segmentation
5. Open Graph Optimization with Predictive Best-Fit

3. • Lots of Successful Apps, Games and Campaigns with
Millions of (Individual) Users
• Low Retention, Low %Pay, High User Acquisition Costs
• Notifications/Posts Can Become Spammy and Blocked
• KPIs Under Pressure – Need Lift - Perform or Perish!
• Vast Amounts of User Attributes

4. Terminology
• Attributes
• Elements (Events/Decision Points)
• Options (Variants)
Low Range High Range

5. User DNA - Attributes Sources
Facebook attributes: Friends, Influence, Likes, Interests, Posts, Events, etc.
Open Graph: scores, achievements, published stories, custom actions, etc.
Behavioral attributes: level, spending, score, health, custom, etc.
Session attributes: time of day, day, duration, etc.
Geo-Demographic attributes: age, gender, education, country, etc.
3rd Party attributes: income level, education, etc.

6. Predictive Best-Fit – Core Concepts
Predictive Best-Fit Algorithms Find Correlations
Between User DNA and Conversions
User Social, open-graph Predictive Best-Fit
DNA Generation Algorithm Real-
User and Behavioral Data
Time action

7. Traditional Optimization Technologies
A Quick Tour
Analytics
Segmentation A/B Testing

8. A/B Testing
Define options Split traffic Measure results Deploy winner Max Result
high range
Low range
High range

9. A/B Testing – Bottom Line
Upside
• Conceptually simple and understandable
Can achieve good results – up to a point
Downside:
• One-size-fits-all
• Results may deteriorate over time

10. A Priori Segmentation
Define segments Define Options and rule Result
base
Low range
high range

11. A Priori Segmentation
Upside
• Can be effective if segmentation was meaningful
Downside
• Segments are predefined and cannot be changed
during the analysis
• Different elements might require different segments
• Hard to scale in terms of data-set and number of
elements
• Hard to fine-tune

12. Clustering Segmentation
Define A/B test Segment users Deploy winner
options options based on result
Low
range
High range

13. Clustering Segmentation
Upside:
• Highest Lift
• Discover correlations you never knew existed
Downside:
• Requires storage of terabytes of data
• Need really smart people to work on it
• Effort = Very High

14. Predictive Best-Fit
• Can optimize in-app and open graph performance
• Automated end-to-end solution
(Acquire data, analyze, predict, enact)
• Machine self-learning
• Real-time
• No user history required
• Numerous data sources
• In full compliance with facebook privacy rules
• Deep new insights
Effort/Resources

15. Elements For Predictive
Best-Fit Optimization
Open Graph Engagement Retention
• Publish Yes/No? • Offers • Email
• Timing • Products • Message Timing
• Art and Copy • Content • Incentives
• Call-to-Action • Communications • Gifts
• Story
Virality Look & Feel Monetization
• Share Messages • Colors • Payment Page:
• Invite Friends • Graphics Ranges, Incentives
• Layouts • Shop Order

16. Open Graph Big Impact
SongPop Hits Major Milestones Just Three Months After Launch
• 25 Million unique players to date
• Has consistently received a coveted 5 start rating
• 4 million people play every day, and growing
Ford created an app that publish a story each time a user
customized his dream Mustang and then battle others’ model.
Although their goal was 2 million engagement they had more than
5 millions and more than 17,000 referrals.
Since revamping Open Graph stories with custom art and content,
BINGO Blitz got 20% more likes and comments on news feed
stories and 500% more unique clicks to the game.
The food finding and sharing app has seen a 3X increase in number
of visits and activities shared by helping people share the dishes
they want, try and ate with friends on Facebook

17. Open Graph Optimizations
1 2
3 4
5
6
1 2 3 4
Publish by User – Yes/No Story Image Landing Page
5 6
Action Verb Object Time

18. Open Graph 1 Publish by User – Yes/No
Yes No
Publish only by the right users!

19. Open Graph 2 Story
Post with the right content to engage the viewer
• Publish achievements the player unlocked
• Publish scores the player achieved
• Publish custom activities:
Jeff E. finished Level 4 on MyGame!
• Publish extended custom activities:
Jeff E. won a game against Chris on MyGame!

20. Open Graph 3 Image
Option A Option A
Image of song, leading to Image taken from to
clip game
Option B Option B
Image of genre, leading Image of real-world
friends to songs/albums landscape
recently listened to by user
Publish using the most effective creative

21. Open Graph 4 Landing Page
Option A
Landing page with the song playing
Option B
Landing page with the latest songs of that genre listened by
friends’
Option C
Landing page of that album with a discount coupon
Publish with the best landing page to convert the viewer

22. Open Graph 5 Action Verb Object
listen
Option A
Justin listened to [SONG X] by [SINGER-NAME] on Spotify
Option B
Justin listened to Classic [GENRE Y] music on Spotify
Publish the most effective actions and objects

23. Open Graph 6 Timing
Publish at the right time to get maximal exposure
Friends newsfeeds

24. The Last Word
Consider optimization if you wish to
become successful or stay relevant
Consider Predictive Best-Fit Optimization
All the Gain without the Pain

25. Welcome to:
Real-Time Optimization:
Putting Facebook User Attributes to Work
- Going Beyond A/B Testing and User Segmentation
- Optimizing Open Graph
Alan Avidan − Executive Director, Business Development
alan@BeesAndPollen.com
@beesandpollen