Your guide to predictive analytics for mobile apps

Without the right data, it’s difficult for mobile app publishers to understand their consumers’ behavior and maintain user engagement. The process of gathering and analyzing relevant data can be challenging for mobile app publishers that lack resources or expertise.

That’s where mobility data – and predictive mobility data and analytics ­– comes in.

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Here’s what you’ll learn

• Predictive mobility data: What is it, and how can it anticipate where and when users will travel – enabling timely, relevant offers.
• Benefits: How predictive analytics can improve personalization, engagement, retention, and revenue.
• SDK advantage: How telematics SDKs can simplify data collection and analysis for accurate insights.
• Actionable insights: How predictive analytics can illuminate the following:
  • Frequent routes and locations for targeted messaging.
  • Trip frequency, duration, and transport mode for timing and relevance.
• Use cases: What predictive analytics can offer consumers, such as weather alerts, fitness safety routes, QSR deals, fuel stop notifications, banking cashback offers.
• Privacy best practices: How to give users control, ensure transparency, and maintain ongoing value exchange.