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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 [email protected] @beesandpollen

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Page 1: Alan Avidan

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 [email protected] @beesandpollen

Page 2: Alan Avidan

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

Page 3: Alan Avidan

• 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

Page 4: Alan Avidan

Terminology • Attributes • Elements (Events/Decision Points) • Options (Variants)

Low Range High Range

Page 5: Alan Avidan

User DNA - Attributes Sources

Geo-Demographic attributes: age, gender, education, country, 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.

3rd Party attributes: income level, education, etc.

Facebook attributes: Friends, Influence, Likes, Interests, Posts, Events, etc.

Page 6: Alan Avidan

Predictive Best-Fit Algorithms Find Correlations Between User DNA and Conversions

Predictive Best-Fit – Core Concepts

User User Social, open-graph

and Behavioral Data DNA Generation

Predictive Best-Fit Algorithm Real-

Time action

Page 7: Alan Avidan

Analytics

Segmentation

Traditional Optimization Technologies A Quick Tour

A/B Testing

Page 8: Alan Avidan

Define options Split traffic Measure results Deploy winner Max Result

Low range

High range

high range

A/B Testing

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Upside

• Conceptually simple and understandable Can achieve good results – up to a point

Downside:

• One-size-fits-all

• Results may deteriorate over time

A/B Testing – Bottom Line

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Define segments Define Options and rule base

Result

A Priori Segmentation

Low range

high range

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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

A Priori Segmentation

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Clustering Segmentation

Define options

A/B test options

Segment users based on result

Deploy winner

Low

range

High range

Page 13: Alan Avidan

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

Clustering Segmentation

Page 14: Alan Avidan

• 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

Predictive Best-Fit

Effort/Resources

Page 15: Alan Avidan

Elements For Predictive Best-Fit Optimization

Monetization

• Payment Page: Ranges, Incentives

• Shop Order

Retention

• Email

• Message Timing

• Incentives

• Gifts

Engagement

• Offers

• Products

• Content

• Communications

Virality

• Share Messages

• Invite Friends

Look & Feel

• Colors

• Graphics

• Layouts

Open Graph

• Publish Yes/No?

• Timing

• Art and Copy

• Call-to-Action

• Story

Page 16: Alan Avidan

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.

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

Big Impact Open Graph

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.

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

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1 2

5

4 3

6

Open Graph Optimizations

Publish by User – Yes/No 1

Image 3

Landing Page 4

Time 6

Story 2

Action Verb Object 5

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Yes No

Publish only by the right users!

Publish by User – Yes/No 1 Open Graph

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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!

Story 2 Open Graph

Page 20: Alan Avidan

Publish using the most effective creative

Option A

Image taken from to

game

Option B

Image of real-world

landscape

Option A Image of song, leading to

clip

Option B Image of genre, leading

friends to songs/albums

recently listened to by user

Image 3 Open Graph

Page 21: Alan Avidan

Publish with the best landing page to convert the viewer

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

Landing Page 4 Open Graph

Page 22: Alan Avidan

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

Action Verb Object 5 Open Graph

listen

Page 23: Alan Avidan

Publish at the right time to get maximal exposure Friends newsfeeds

Timing 6 Open Graph

Page 24: Alan Avidan

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

Page 25: Alan Avidan

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 [email protected] @beesandpollen