Liftoff Mobile, Inc. · NASDAQ:LFTO

Liftoff Mobile — Liftoff and Adjust Mobile Fraud Webinar (May 2017)

19 slides from Liftoff Mobile's conference presentation, May 2017

  1. Slide 1: Liftoff and Adjust

    A LIFTOFF @) adjust

  2. Slide 2: Meet the Speakers

    Meet the Speakers Dennis Mink Andreas Naumann VP Marketing, Liftoff Fraud specialist, Adjust A LIFTOFF ()adjust

  3. Slide 3: Liftoff and Adjust company descriptions

    Liftoff is a performance-based, app marketing platform helping companies drive adoption and engagement in mobile apps. Adjust is a mobile attribution and analytics company that provides app marketers with a comprehensive business intelligence platform.

  4. Slide 4: It's Poll Time!

    It’s Poll Time!

  5. Slide 5: First things first

    First things first Attribution follows engagement - aka eyes and fingers on screens banners interstitial native TL LIFTOFF

  6. Slide 6: Word cloud of fraud types

    tot tats cooling click-spam ada 8¢0 spoofing . abet Sostglls dick injection popups ad-stacking Satin vores cai chines ° glick’spam geo spoofing “ro spooting ad-Stacking rebrokering rebrokering Ninders _ fingerprint-spam bot installs Boe ee ag semwent — popunders _ad-stacking ke prouenne installs POP

  7. Slide 7: There are two variations

    There are two variations Technical Fraud Un-compliance Manipulation of any part of tracking Intentional or unintentional breaches and/or attribution in the user of campaign rules and regulations conversion flow e False targeting (especially geo) e Fake installs e Mixing in undesired traffic sources

  8. Slide 8: Fake installs

    Fake installs Everything is fake Perpetrators MO e Ad engagement e Emulation e User e Virtualized environment e Device e Scale e Install e Post install behaviour A LIFTOFF ()adjust

  9. Slide 9: Fake installs: how to find them

    Fake installs How to find them High CR Low post install performance Hides in incentivized traffic Low count of distinct IPs, subnets, ASNs Pro tip: filter anonymous installs A LIFTOFF ()adjust

  10. Slide 10: Click spam

    Click spam Nearly everything is real The one thing that is fake e User e Ad engagement e Device e = Install e Post install behaviour A LIFTOFF ()adjust

  11. Slide 11: Click spam: perpetrator MO

    Click spam Perpetrator MO (mobile) web Mostly illegal content No other means of monetization High amount of unique visitors Low user knowledge High amount of spam Any campaign will do TL LIFTOFF Perpetrator MO (native) in-app Legit app Legit monetization High count of active users Intricate user kno

  12. Slide 12: Click spam: how to find it

    Click spam How to find it on (mobile) web How to find it (native) in-app e Very low CR e Very low CR e Inconsistent CTR e Inconsistent CTR e Very good post install metrics e Very good post install metrics e High amount of identical clicks e Low amount of identical clicks e Possibly static click freq

  13. Slide 13: Click spammers randomly match installs

    Click spammers randomly match installs across attribution windows Click-to-install time distribution for a “click-spammed” campaign, sample data Install count Lee” Time after click T T J | 0 fh 2h 3h 4h Sh @ Real Installs e@ Click Spam Installs TL LIFTOFF

  14. Slide 14: Click injections

    Click injections Again, nearly everything is real But also, one thing is fake e User e Ad engagement e Device e = Install e Post install behaviour A LIFTOFF ()adjust

  15. Slide 15: Click injections: perpetrators MO

    Click injections Perpetrators MO (native) in-app How to find it on (mobile) web e Android only e Inconsistent CTR e Additional source of income e Above average post install metrics e Listens to ‘broadcast intents’ for e Mostly very low CTIT app installs e Inject correct click for the installed Pro t

  16. Slide 16: Chart of an abnormal distribution

    Chart of an abnormal distribition How to find it on (mobile) web amount of Installs e Inconsistent CTR e Above average post install metrics e Mostly very low CTIT time in seconds Chart of a normal distribition Pro tip: filter pn exceptionally high concentration of extremely low CTIT, extreme chance

  17. Slide 17: False positives

    False positives Worse than fraud! e Strong detrimental effect on volumes e Breaks relationships with your most valuable sources e Regaining each will be costly A LIFTOFF ()adjust

  18. Slide 18: Questions?

  19. Slide 19: Resources

    Resources e Read more on fraud liftoff.io/blog e More resources liftoff.io/resources e Mobile Heroes heroes. liftoff.io Coming up in June: e Shopping apps report e Shopping apps webinar

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