fabian schaeffer (adjust): adjust topic - mobile measurement 2.0: what it really means
TRANSCRIPT
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MOBILE MEASUREMENT 2.0: WHAT IT REALLY MEANS
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������AD NETWORKS
ADVERTISERS
AGENCIES
DISCOVERY
ENGAGEMENT
CONVERSION
VIEW AD
CLICK AD
DOWNLOAD APP
OPEN APP
ENGAGED
HIGHLY ENGAGED USER
YOUR DATA
“Half of the money I spend on advertising is wasted; the trouble is I don’t know which half”– John Wanamaker
Navigating the complexity of a fragmented ecosystem
+ Complicated Network integrations, multiple SDKs, reportings, double payment for same user
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AD NETWORK
Fraud PreventionDeliverables Cohorts
This month
Network_BTracker
Organic
Network_I
Network_C
Network_F
Network_D
Network_B
Network_E
Network_H
Network_J
Network_G
Network_A
TOTAL
1,800
1,600
1,400
1,200
1,000
800
600
400
200
0
535
Installs Linear
Network_D764
Network_G
Network_J558
578Network_H1,667
Network_I837
23.10.2016
01.10 05.10 09.10 13.10 17.10 21.10 25.10
France Australia
PLATFORMS
VIEW BY
COUNTRIES
Select platforms
Tracker
The power of mobile attributionDiscover your best value users
2017: 268bn Downloads77bn in app revenueBUTFRAUD
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1. What are we up against - and how do we fight it? Who is to blame?
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The three different types of fraud
Click Spam
Simulated Devices
Servers Faking SDK Traffic/Installs
Some App
*emarketer data
Risk for Mobile Ad fraud
Mobile Ad benchmarks worldwide: Share of attempted ad fraud, by app vertical, 2016*
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+ Servers pretend to be apps and talk to analytics platforms. You can fake server calls by sniffing out the connections your device is making using free tools like Wireshark.
Fraud
+ Analytics SDK with SSL encryption+ Shared secret
Prevention
Faking HTTP calls to trigger false installs
+ Publishers are paid for fake installs+ Too many installs counted+ Retention rates very low
Effect
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Simulated installs & behaviour
+ Exclude all IPs from known data centers, proxies, Tor exit nodes or cloud providers from attribution.
Fraud
Solution
+ Devices are simulated with full OS stack or are triggered by "mechanical turks" to create legit install requests.
Effect+ Installs (and events) attributed to fraudulent publishers+ Geo spoofing+ Undercounted retention rates
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+ Limit number of clicks considered for fingerprinting from single IPs.
+ Detect extremely low yielding campaigns and deliver landing pages with Javascript
to create redirects and stop crawlers.
Fraud
Solution
Background clicks (Click spamming & Preloading)
+ Apps that, without the users interaction, crawl ads and click through any URL they find to spam fingerprinting and claim organic traffic.
Effect+ Organic users are attributed to
publishers+ Ads show very strong in-app retention
& engagement (organic)+ Very low conversion rates
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Purchase Verification protects your revenue
numbers, secures accurate reporting,
prevents wrongful CPA payouts
89% of in-app purchases are fake
30%
Valid Invalid
Valid Invalid
70%
4% 96%
In-app purchase fraud happens when USERS hack apps and fool the app into
thinking that they paid for the goods when they actually didn’t.
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Before the fact vs. after the fact!
Exploited ad budgets are only one of the problems caused by fraud
• Organic user activity is poached • Un-real view of campaign performance
• No benchmarking possibilities• Lost budgets
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I now see that the fraud prevention suite is serving a different purpose beyond just preventing a ‘bad’ install:
It’s my insurance policy when working with new partners.
We can try new things, and I’m free to experiment because I trust the data. We can go big, and not hold back.
An VuUser Acquisition Lead at Rovio
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2. The market is moving beyond just installsof marketers increased their KPIs with personalisation94%
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95% of apps are abandoned after the first few months **
58% of users will churn in the first 30 days of using an app ***
62% will use an app less than 11 times***
LOST USERS & DECREASED
ENGAGEMENT =
biggest fear of APP developers
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Measuring your user behaviour by the hour in any timezone
• Measure burst campaigns and user behaviour in greater granularity: i.e. Friday is a good day but when exactly?
• True retention and conversion rates
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‣ Reach more prospects‣ Increase relevancy/conversion rates‣ Create tailored marketing programs‣ Improve customer relationship‣ Chance user behaviour‣ Improve ROI
Segmenting to
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Create highly targeted user segments on the fly powered by your own data without sharing all your data
Being in control of creating your user segments
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‣ Lack of control‣ Data oversharing‣ Spamming your users‣ Human error
Don’t compromise on
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2017 with• Accurate data• Personalized communication
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Thank you for listening!!!