Augmented reality (AR) is the overlaying of digital content onto real-life environments and
objects, a technology which is quickly transforming marketing and media in the professional
landscape.
In this guide, we will explore some of the various types of data AR integrates, focusing on
real-time environmental data, user interaction metrics, and 3D model information. We’ll also
discuss the importance of data quality, to demonstrate how leveraging the right metrics can
enable businesses to create truly engaging AR applications.
So, how exactly does AR use data to create immersive experiences? Let’s find out.
Real-time environmental data
Real-time environmental data refers to the information collected from the physical
surroundings of the user, such as lighting conditions, spatial geometry, and object
recognition.
AR devices use sensors like cameras and LiDAR (Light Detection and Ranging) to scan and
map the environment. This is called spatial mapping, and is crucial for placing digital objects
accurately in the physical world. High-quality spatial data ensures that digital objects are
placed correctly relative to the physical environment, providing an accurate augmented
reality.
Real-time data about the lighting conditions helps AR applications adjust the brightness and
shadowing of digital objects. This creates a sense of realism, making digital elements blend
seamlessly into the real world and enhancing the user experience.
By recognizing and tracking real-world objects, AR can offer interactive experiences on a
digital platform, such as overlaying additional information or animations on top of recognized
objects. If the object recognition data is reliable, this allows for quick and accurate
identification and smooth interactions.
User interaction metrics
User interaction metrics involve tracking how users engage with AR content, including touch
interactions, eye movements, and gesture controls. By analyzing user interactions, AR
applications can tailor experiences to individual preferences and behaviors. As many as 80%
of brands implementing AR say that it has helped to drive sales and boost performance
of brands implementing AR say that it has helped to drive sales and boost performance
metrics on their marketing campaigns.
Tracking metrics like session duration, frequency of use, and types of interactions helps
developers understand how users engage with their AR applications. High-quality data
allows for better personalisation and customisation, which boosts the overall satisfaction and
engagement of a user. It also boosts optimisation, allowing developers to use these
performance metrics to maximize performance and fix issues based on the feedback data.
3D model information
3D model information includes the data that defines the geometry, texture, and behavior of
digital objects used in AR applications. High-quality 3D models enhance the visual
appearance of AR applications, making them more appealing to users.
These models can be designed to interact with the user and other digital or physical objects,
creating a dynamic experience – with the functional accuracy of the model’s data ensuring
that digital objects behave as expected.
3D models can also simulate real-world physics, such as gravity and collision detection, to
make the AR interactions more believable. In addition, an optimized 3D model reduces the
computational load, ensuring smooth performance even on less powerful devices. This
maximizes the efficiency and diversity of AR applications.
Data quality matters
The quality of real-time environmental data, user interaction metrics, and 3D model
information directly impacts the effectiveness and user satisfaction of AR applications. For
those looking to develop engaging, seamless AR experiences, understanding these data
types and their importance is crucial.
