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

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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!!!