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.

A lack of data results in an incomplete picture of users’ journeys — making it difficult for publishers to understand how their app fits into users’ daily lives and how they can deliver more value to users.

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

Introduction to predictive mobility data

Predictive mobility data is information about where and when a consumer is likely to go, based on where and when we know they’ve gone in the past.

For mobile apps, it can be used to anticipate a consumer’s upcoming mobility patterns and to display offers most likely to be helpful and relevant to them.

With predictive mobility data, mobile publishers can tailor ad messaging and timing based on how, when, and where users drive, increasing the likelihood that they will click on an ad as they move throughout their day.

Core concepts of device data and mobility data

Device data is any data that a mobile phone or mobile device collects; this includes location data (where you are in a point of time) based on GPS sources. When a device owner gives permission to share device data, they may be granting access to trillions of data points from apps on mobile devices.

But instead of looking at device data on its own, mobile device technology has reached a point where we can layer that device data with other data points for additional context.

By layering contextual information in this way, you’re not only looking at the location of a vehicle at different points in time, but you’re also receiving a moment-by-moment picture of how an individual is moving from point A to point B, because their phone is always with them.

From mobility data to predictive analytics

With this type of information, mobile apps can develop insights that help open up new value-add opportunities. Predictive mobility data — knowing when someone will be on the move, where they are going, when they are going, and the route they take to get there — is one such insight.

So what solutions are available to help you gather and analyze data quickly, without reinventing the wheel? Telematics software development kits (SDKs) help you gather and analyze mobility data without building your own solutions. These SDKs can save time and resources and provide a more accurate and comprehensive picture of your users’ driver behavior.

Predictive analytics as a mobile app growth strategy

This kind of information can be used to:

• Enhance user engagement by delivering personalized content, offers, and recommendations based on predicted behaviors
• Drive user retention
• Increase revenue

By analyzing mobility data, you can understand where your customers are traveling and how they’re getting there. Mobility data allows you to craft a more relevant experience for users by providing insights such as:

1. Customer journey: Understand their real-world consumer behavior through the lens of driving data.
2. Common routes: Insights into frequently traveled routes can indicate when someone may be passing a specific location on a drive they often make. Before they even get in their car, the consumer may receive a notification such as: “Stop in for 25% off any breakfast item, today only” which happens to be along the route they will take that day.
3. Location: Strategic mobile app decisions can be tailored to location details to help narrow down points of interest for consumers and yield a better understanding of their buying needs for more accurate messaging and offers
4. Trip frequency and duration: Gain insights into average times on the road or durations at various locations to understand where consumers are spending their time. This can help you understandwhere and when your consumers should receive certain types of messaging.
5. Mode of transport: A mobility SDK can help you understand how people travel in specific regions.

Examples of predictive mobility use cases by retail app vertical

• A weather app that integrates commute times and routes with weather forecasts to notify users of commute disruptions
• A fitness app that recommends safer running routes by avoiding high-traffic intersections
• A quick-serve restaurant app that pushes offers and deals before customers are expected to drive near the restaurant
• A fuel and convenience app that sends an alert with a c-store on the day they’re most likely to stop for gas
• A bank app that sends cashback offers for businesses located along a customer’s frequent routes

There are countless ways businesses across industries can leverage driving data to enhance their app’s value prop – turning people into loyal app users and customers.

Predictive mobility considerations

Apart from providing frequent and tangible value to consumers, best practices to ensure a win-win mobile app experience include:

• Giving consumers confidence and control – According to a 2023 Pew Research Center data privacy study, 81% of those surveyed are concerned about how companies use the data they collect about them with automated decision-making tools like AI. A majority of those polled (73%) believe that they have little to no control over what companies do with their data. These statistics suggest that it’s important that mobile apps empower users to customize their data sharing.
• Being transparent about data – That same survey revealed that the public says they don’t understand what companies are doing with their data. A majority of those polled (67%) say they understand little to nothing about what companies are doing with their personal data. That percentage is up from 59% in 2019. The takeaway: Be clear about what data you are collecting and how it will provide value to your mobile app users.

The value exchange needs to be at the forefront of communications throughout a user’s journey – not just at the beginning. Once an app builds a story of value, it can gain users’ trust along with more installs and engagement – which can result in financial growth.

Arity mobile app solutions

Arity Predictive Mobility works within brands’ mobile apps, connecting to users and using their driving behavior insights to deliver unmatched personalization and offers.

Find out more about how to use mobility data to create in-app experiences that differentiate your services and help attract, retain, and delight customers.