optimization for advanced app marketers

This ebook outlines an optimization technology for mobile app marketing that automates the optimization process, is simple to implement, and is already generating exceptional results for leading mobile app businesses.

High Performance App Marketing Platform

Optimization

Advanced

Technology and Practices for High-Performance Results

As a mobile app marketer, choosing the right media sources to promote your app is too much of a guessing game As you plan your campaign, there’s no sure way of knowing which ad networks will cost-effectively deliver the largest number of installs, which will drive loyal users you can monetize, and which will merely drain your budget.

You have limited insights on which to base your media buys Mobile ad targeting is not as sophisticated as what you may be used to in the online marketing world

This is why optimization technology is so crucial to mobile app marketing With optimization technology, you can gain detailed and immediate insights into the advertising that’s driving your business, and optimize on those insights early and often during the campaign, to deliver the price/perfor- mance results you need

This ebook outlines an optimization technology for mobile app marketing that automates the optimization process,

is simple to implement, and is already generating exceptional results for leading mobile app businesses.

While this occurs, the advertiser may also compare performance between networks, outlined in #2 below.

2 Advertiser-Driven Optimization Between Networks

The advertiser compares results between networks, to identify the networks that are performing well, and those that are not The advertiser conducts data analysis based on reports from the different networks, and allocates more budget to the high-performing networks, and less budget to the low-performing networks

What’s wrong with these approaches?

With advertiser-driven optimization between networks, the advertiser must consolidate multiple network reports, each with unique formats and with differing information This is time consuming and difficult because each net

Why Traditional Optimization

Approaches Fall Short

work provides a different type of report, tracking different types of data For example, some networks report that

a download occurs on the day an ad is displayed Others report when the app was physically opened the first time Data is reported differently from network to network, and somehow the advertiser needs to reconcile this It can take

an enormous amount of manual spreadsheet work to consolidate all of these reports and, without the ability to do so,

it is difficult to identify the best value for the ad spend

An even bigger issue with both approaches is that ad networks typically optimize only to downloads Most networks are not able to optimize ad spend to the publishers that drive the users that take the high-value actions that your business values – such as purchases or repeat launches They’re focused primarily on optimizing to downloads Unfortunately, downloads often don’t convert into productive users A large proportion of apps are used only once

or twice This is why it’s crucial to:

n Track the post-download events, such as purchases, repeat engagement, game levels, etc that are important

to your business and;

n Optimize to the sources driving the users who take these post-download actions because they are the loyal users that drive your business

Ad networks are focused primarily on ads and clicks So it needs to be up to you as an advertiser to be pro-active about tying post-download events back to the media source and optimizing to these sources Many app marketers have recognized the need to optimize to the sources driving loyal users Some have tried to address this optimization quality concern through the following optimization method

3 Attribution of Post-Download Events with Standalone Ad Tracking Products

Some advertisers have tried to address optimization quality by either purchasing or building standalone ad

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As campaigns run, the ad tracking software attributes downloads, and possibly also post-download user actions (i.e., purchases, repeat launches)

to the media source

The advertiser performs analysis by reviewing results within the tracking software dashboard, or by creating spreadsheets from the dashboard and conducting data analysis to draw conclusions This can potentially involve tens of thousands of data points This step can be very time consuming and complex because it is manual.

The advertiser identifies potential top-performing sources and poorly performing sources

The advertiser contacts the networks to request changes to the media buy

or enters changes in network interfaces This process varies from network

to network and can also involve significant manual effort

Sounds easy.

In theory, it is But in practice, marketers have found that this approach is fraught with challenges

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* Performance data by publisher is available from select networks.

Challenge #1:

It’s extremely labor intensive.

Tracking solutions provide raw data Therefore, it’s entirely up to the advertiser to make

something of this data

Consider a sample advertising program with:

For the best possible optimization, the data analysis must be as granular as

possible For example, Japan may be the country driving the most downloads,

but in what combinations?

For example, is it:

• Creative A, 720 x 90, on Network 1, xxx Publishers, on Device 1?

• Or is it Creative B, 320 x 50, on Network 2, xxx Publishers, on OS 1?

• Or could it be Creative C, 300 x 250, on Network 3, xxx Publishers, on Device 2, OS 2?

COUNTRY ?

DEVICE?

OPERATING SYSTEM

To achieve optimal ad spend, app marketers are taking this granular approach

to optimization But it’s nearly impossible to do so through manual analysis that is required when using standalone ad tracking products or through network dashboards

?

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Challenge #2:

Optimization is delayed.

Data obtained through the ad tracking software or through network dashboards is not actionable

immediately, due to the manual nature of the data analysis There are no algorithms that make

optimization decisions, such as what media is most cost-effective, how to bid, or how to manage

volume and budget Nor is there any infrastructure to execute on these decisions It’s up to

marketing staff to do their best to draw conclusions from massive amounts of data and implement

optimization decisions according to the processes of each network

This manual optimization process can take several days or longer, particularly when working with

multiple networks Each day of optimization lag leads to another day of less than optimal ad spend

and compromised performance

ON HOLD

ON HOLD

ON HOLD

ON HOLD

Optimization decisions can be applied only to networks on which campaigns are running With ad tracking products, there is no systematic way to apply performance insights to potential new media sources with high potential to perform well It’s important to be able

to apply performance insights to new ad networks and real-time bidding exchanges that should perform well, to expand your marketing reach

In addition, ad tracking products typically employ one type of attribution technology, such

as HTML cookie tracking or digital fingerprinting Some ad networks may not support a particular attribution technology, thereby limiting the ability to gain performance insights

on which to optimize

What many app marketers have found with ad tracking products is that, although they do provide a greater level of performance insights than most ad networks, it’s still a manual, time-consuming and limiting approach Most marketers either don’t have the time,

the expertise, or the tools to efficiently turn these insights into the best possible optimization decisions – so they end up settling

Challenge #3:

Optimization options are limited.

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App marketers who need to deliver measurable results have identified

5 characteristics of high-performance optimization:

1 Optimizes on Post-Download Events

Provides the ability to optimize on post-download events, such as in-app purchases and repeat launches This helps ensure that media spend is allocated to the sources that are truly driving business results

2 Integrates Attribution with Optimization

By integrating attribution with optimization technology, marketers can react quickly to the performance insights gained through attribution

This integrated approach delivers more value because attribution insights are actionable immediately, without the delay caused by manual analysis

3 Enables the Ability to “Get Granular” with “Big Data”

When tracking and analyzing post-download events, there are enormous amounts of data that need to be considered to arrive at the best optimization decisions And it’s crucial to analyze all this data quickly, and at the most granular level to zero in on the best performance drivers

The 5 Characteristics of

High-Performance Optimization

4 Enables Broad Media Deployment

Optimization decisions can be deployed beyond existing media sources –

to new media sources that are highly likely to perform well

5 Provides Immediate and Continuous Optimization

Optimization is not a one-time event To achieve the best possible price/performance results, optimization must be early and often

As advertising dynamics change, the optimization needs to be in lockstep with these evolving performance changes to deliver the best possible results

These cannot be performed manually

They require technology.

Today, many mobile app marketers are benefitting from these capabilities, with a mobile app marketing and optimization technology from Fiksu

Hundreds of app marketers have completely automated and integrated their attribution, optimization and media buying all in one real-time solution that delivers exceptional price/performance results

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Fiksu is a mobile app marketing platform that combines attribution and optimization technology with ized media buying from the world’s largest mobile app media inventory By combining these capabilities into one technology solution, app marketers are able to confidently deploy their ad dollars on the media sources that perform best and deliver true business results

central-Fiksu removes the complexity and limitations of manual optimization, by automating and integrating the entire optimization process, with a focus on optimization quality, efficiency and performance

The Fiksu Platform employs three primary technologies that work together to drive optimization performance:

Fiksu Mobile App Marketing Platform with Optimized Marketing Performance

Integrated Post-Download Event Attribution

Automated Optimization Engine

Broad and Real-time Media Buying

1 Integrated Post-Download Event Attribution

The Fiksu Mobile App Marketing Platform automates attribution of downloads plus post-download events, enabling marketers to optimize to the sources that drive ROI

As campaigns run, Fiksu records post-download user actions (in-app purchases, repeat launches, game levels and more), and attributes each of these actions back to the media source, ad creative and other campaign elements, to identify the sources of high-value, loyal users This information is updated

in real-time and available for viewing in Fiksu’s online dashboard Because Fiksu integrates attribution and optimization technologies, this attribution data is fed into Fiksu’s optimization engine automatically and continuously This unique integration of attribution and optimization technology makes attribution data actionable immediately and continuously, to make the attribution data truly impactful, and to deliver the best possible results

2 Automated Optimization Technology

As Fiksu attributes users’ post download events, Fiksu feeds this attribution data into its optimization engine in real time Fiksu’s optimization engine rapidly analyzes the performance of every possible campaign variable (ad source, creative, country, location, device, operating system, day, time, cost and more) in every possible combination, and isolates the best performing media sources and campaign attributes based on the advertiser’s specific user acquisition goals

Fiksu’s attributes more than

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Fiksu’s optimization engine analyzes a virtually unlimited number of combinations of variables, to identify the combinations of media source, ad creative and other variables that deliver most effectively on

acquisition, cost and ROI goals

Fiksu applies this intelligence automatically and continuously to marketing programs to ensure the most productive ad spend and best user acquisition results

“Smart Allocation” determines the best spending combinations in real time

Fiksu’s optimization technology systematically identifies the most economically efficient ad options Fiksu algorithms leverage conversion data to determine an expected conversion rate for each combination of ad variables These conversion rates are then weighed against the expected ad cost (the bid) and turned into an expected value for each transaction Fiksu identifies the best ad choices and then allocates ad spending to ensure volume goals are met while minimizing cost and generating the best possible ROI

In addition, because the Fiksu Platform employs tight integrations with a number of leading networks, Fiksu can measure performance and optimize at the publisher level This enables much more targeted optimization that often is not available to advertisers

Store Optimization Drives Organic Users

Achieving a high rank in the stores can be extremely expensive The Fiksu Platform continually monitors the relationship between ad spend and an app’s rank to optimize campaigns to deliver the rank that delivers the most organic users at the best cost Rather than simply focusing on getting the highest possible rank, Fiksu’s platform determines an app’s optimal rank level Some apps get no more organic users at a rank of 10 than 20 So why pay to achieve a ranking of 10 when a rank of 20 delivers the same number of organic users for a lower cost? Fiksu identifies the optimal rank and optimizes to attain that rank By closely monitoring rank behaviors during a live campaign, Fiksu can optimize ad spend to achieve the rank that yields the best ROI

Optimization on Real-Time Bidding Exchanges

Fiksu’s optimization algorithms are also integrated with the leading real-time bidding exchanges, which offer highly targetable ad traffic through real time bidding auctions These exchanges provide an opportunity for acquiring users in a highly efficient, cost effective manner Fiksu’s high-speed, intelligent infrastructure enables access to this highly effective, growing pool of impression-based media

• Employs rank and discovery methods specific to each store

• Drives the most efficient rank

• Delivers the most organic users

Exceptional Store Optimization

for Increased Visibility