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Predictive analytics for marketers - Predict dashboard
Predictive analytics

Know what to do, right from the start

Our predictive analytics solution gives you clear and actionable insights into your customers’ LTV so you can confidently optimize your campaigns, and predict long term results, without having to wait

Privacy-centric insights that help you make good choices fast

Predictive analytics for marketers - make smarter decisions

Make smarter decisions faster with machine learning

The more time you spend waiting for campaign results, the more money you may be wasting. Our predictive analytics engine uses machine learning to identify and map correlations between early user engagement indicators and expected user value to give you accurate predictive insights early in a campaign’s lifetime.

Predictive analytics for marketers - customer privacy at center

Put your customers’ privacy at the center

When you respect user privacy you build stronger, longer lasting relationships. Predictive analytics gives you the ability to use aggregate customer behavior without relying on user identity, so that you can base your decisions on comprehensive engagement data while preserving customer privacy.

Predictive analytics for marketers - make data-driven optimization decisions

Make data-driven optimization decisions

More data enables better decisions. Our predictive analytics engine gives you an accurate, predictive score based on every measurable event, within a minimal timeframe, so that you can make all of your in-app engagement data count when making optimization decisions.

Key features

An ever evolving industry requires forward thinking solutions. Discover how our predictive analytics solution can help you optimize your campaigns, without the wait, while preserving customer privacy.

Predict dashboard

Get clear data science insights for your marketing efforts from one comprehensive dashboard

Seamless SKAdNetwork communication

Sync with Apple’s SKAdNetwork to easily translate predictive benefit scores into conversion values

Detailed campaign view

Get a detailed, aggregate view of predicted campaign performance scores, broken down by monetization, engagement, retention, and cost

Privacy by design

Preserve your customers’ privacy by basing your insights on actual engagement and behavioral data without relying on user identity

Personalized predictive model

Leverage a unique predictive model for your app using distinct LTV logic, first party historical data, and correlations in customer behavior

Media partner postback & API

Enjoy immediate access to predicted scores for accurate feedback on media quality and performance

Advanced data science made available to every app developer

Predictive analytics uses machine learning and advanced data science techniques to give you a competitive advantage in an ever-shifting environment.

Predictive analytics for marketers - advanced data science
Predictive analytics for marketers - benefit score

Frequently asked questions

How can PredictSK help with SKAdNetwork?

AppsFlyer’s SDK measures all of a user’s engagement data in their initial 24 hours post-install, this information is analyzed by the PredictSK engine and broken into three predicted pillars: Retention, engagement, and monetization – constructing the user’s overall benefit score – all ranked from 1-9.
The benefit score will go through an additional compression algorithm to create a conversion value between 0-63 in accordance with SKAdNetwork’s 6 bit requirements. SKAdNetwork will then send the aggregated data alongside campaign information – giving PredictSK the ability to present the aggregate campaign score and relevant media data, and for you to optimize accordingly.

Is PredictSK aligned with Apple’s user-privacy requirements?

Yes, AppsFlyer’s predictive analytics solution is fully aligned with Apple’s ATT and user-privacy requirements.

How soon can I start using PredictSK?

PredictSK is currently in beta, and only available for qualified AppsFlyer customers.
Prior to onboarding PredictSK, a machine training period is required in which PredictSK’s AI engine will review an app’s historical data, identify correlations between user engagement points and their eventual value to the app. Developers are also encouraged to add their input in the form of highlighting key events, association of events to one or more of the three KPI pillars and more.

Ready to know what to do right from the start?