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Advanced Targeting Techniques to Drive More App Installs
 

Advanced Targeting Techniques to Drive More App Installs

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In a sea of potential users, how do you find the most valuable users for your app? Traditionally, developers have targeted users through standard targeting techniques such as demography, location, ...

In a sea of potential users, how do you find the most valuable users for your app? Traditionally, developers have targeted users through standard targeting techniques such as demography, location, carrier, device, etc while promoting their apps on an ad network.

However, there are several new age targeting techniques that leverage the power of big data and allow developers to reach the right audience for their apps in smarter ways.

Click here to view a recording of the webinar: https://vimeo.com/79282931

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    Advanced Targeting Techniques to Drive More App Installs Advanced Targeting Techniques to Drive More App Installs Presentation Transcript

    • LOOKING BEYOND TRADITIONAL TARGETED ADVERTISING TO DRIVE APP DOWNLOADS Shringar Pangal | November 2013
    • “Traditional” Targeting On Mobile Device Context Carrier User Interest Geo Demographic Location
    • EXPLORING USER TARGETING ENGINEERED FOR APP DISCOVERY
    • Advanced Targeting For App Developers Cross Channel Retargeting 2 ~ Cross Channel Lookalike Modeling ~ ~ Cross Channel Negative Targeting ! ~ 3 1
    • 1. Retargeting Clickers App Your friends are waiting for you. Play today! Viewers or Clickers Downloaders App Your friends are waiting for you. Play today! App
    • 2. Look-alike Modeling and Targeting High LTV Users Analyze User Interests Target Enriched with 3rd Party Data ~ Travelers ~ Food Enthusiasts ~ Sport Enthusiasts
    • 3. Negative Targeting Publisher App Your friends are playing. Play today!
    • But before that… Ensure targeting is accurate and effective
    • Cross Channel De-duplication IDFA IDFA ODIN1 Fingerprin t IDFA WITHOUT Cross Channel De-duplication IDFA ODIN1 Fingerprint IDFA (App 1) Global User Identifier ODIN1 Fingerprin t IDFA (App 2) IDFA (App 3) WITH Cross Channel De-duplication IDFA ODIN1 Fingerprint
    • Auto-Fatigue Management User clicks the ad a number of times before downloading the app Probability of Conversion Optimal Frequency Number of clicks After a while, number of clicks and user interest drops
    • Top 5 Questions To Ask Your Ad Network • • • • • Unique User Identification Personally Identifiable Information Potential Scale Of Campaign Tracking Solutions Combination Of Targeting
    • THANK YOU