Udi Baronehttp://www.beesandpollen.com

Common misconception

Facebook privacy policymakes it hard for Facebook apps to have optimized targeting?

NOT!

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Optimized ads/offersThis is what 3rd parties such as ad-networks and offers-wall are after

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3rd parties

3rd parties optimization is critical for maximizing ads/offers relevancy and conversion rate

banner

Publisher

Ad-Network

Offers-wall

Facebook AppOr

Facebook GameOffers

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User’s dataThis is the key elements for good ads/offers optimization

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3rd partiesPublisher

Ad-Network

Offers-wall

Facebook AppOr

Facebook Game

Facebook user’s data (e.g. age, gender, interests, pages, posts)

FacebookUser Id

DataAggregators

FacebookUser Id

Scrapinguser’sprofile

The ideal solution for 3rd parties would be to have free access to all Facebook user’s data

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the big BUT is…

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… Facebook banns any disclosure of user’s data or UID (User Id) from any 3rd party!

information

“Our policy has always stated that data received from Facebook, including UIDs, cannot be shared with data brokers and ad networks. Moving forward, our policy will state that UIDs cannot leave your application or any of the infrastructure, code, and services you need to build and run your application. You can use services, such as Akamai, Amazon Web Services and analytics services as long as those services keep UIDs confidential to your application. “

Facebook user’s data (e.g. age, gender,

interests, pages, posts)

FacebookUser Id

Scraping user’sprofile (based on

Facebook User Id)

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So, what is the solution for Facebook app/game?

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Publisher

Facebook AppOr

Facebook Game

Categorized3rd parties

(or internal)ads/offers

Ads/Offers - category 1

Ads/Offers - category n

…

OptimizationTool

When the optimization tool requests the ad/offer from the 3rd party for a given user it already knows which category is the most relevant to him

Using Facebook API the optimization tool accesses

freely the user’s data

Do the optimization in-house! This way the Facebook app can optimize using any Facebook user’s data it likes(e.g. interests, pages, posts, demographics)

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Tips for developing in-house optimization systems

Algorithms:• No single ML (Machine Learning) algorithm can win it all! • Test wide range of algorithms (e.g. regressions, AI, frequency tables, decision

trees)• Get professional academic help concerning algorithms

User Data:• Check carefully which user attributes to weight-in!• Beware of attributes like age with 50% users availability. Click here for

alternatives

User Data Privacy:• Do all optimization job in-house. Beware of breaching Facebook user data

privacy

Automation:• Don’t settle with manual or semi-manual analysis• Save tons of time on trial and error by using turn-key solutions

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