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MOBILE MEASUREMENT 2.0: WHAT IT REALLY MEANS
������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
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
1. What are we up against - and how do we fight it? Who is to blame?
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*
+ 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
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
+ 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
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.
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
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
2. The market is moving beyond just installsof marketers increased their KPIs with personalisation94%
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
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
‣ Reach more prospects‣ Increase relevancy/conversion rates‣ Create tailored marketing programs‣ Improve customer relationship‣ Chance user behaviour‣ Improve ROI
Segmenting to
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
‣ Lack of control‣ Data oversharing‣ Spamming your users‣ Human error
Don’t compromise on
18
2017 with• Accurate data• Personalized communication
Thank you for listening!!!