Device fingerprinting is a method for identifying devices and users, especially across multiple browsers or apps. Using this technique, clues are left behind by devices as they interact with websites and mobile apps that can be used to generate a unique device ID for each operating system. By capturing these clues, attribution providers can accurately identify and track user behavior across different sites, applications, and devices.
Accurately collecting and interpreting device device fingerprint SDK data is a complex challenge. The complexity stems from the fact that device data consists of a multitude of factors, including device identifiers, network information, sensor data, behavioral patterns, and more. Capturing this data and extracting meaningful insights requires a robust data processing pipeline that uses various algorithms and statistical techniques.
In addition, ensuring that all the collected data is secure and accurate requires an elaborate data management architecture. These architectures typically consist of various layers, such as encryption protocols and hashing methods. Moreover, these infrastructures need to be regularly updated and patched to address vulnerabilities.
Developing a reliable and commercially viable device fingerprinting solution is an extensive and time-consuming endeavor. As such, companies that choose to build their own solutions often face significant development hurdles. For example, many of these systems require sophisticated software algorithms and machine learning models to accurately capture, interpret, and analyze device data and generate unique fingerprints. This is in addition to ensuring that the collected data can be trusted and maintained in compliance with privacy laws and regulations.
To overcome these challenges, it’s recommended that businesses consider leveraging third-party solutions. The benefits of leveraging an existing fingerprinting technology include reduced development time, lower costs, and a reduction in the risk of error. In addition, third-party device fingerprinting solutions are able to offer a wide range of features that are not available in open-source fingerprinting tools.
An important consideration in selecting a device fingerprinting SDK is how it can be integrated into your business systems. For instance, you should ensure that it is compatible with the authentication and fraud detection policies of your business. In particular, you should check if it supports the Bazaarvoice Authenticity Policy. This policy requires that submissions include a device fingerprint attached to them. Failure to send a device fingerprint with a submission can result in actions taken by the Bazaarvoice network, such as rejection of your content or halting of syndication of your submissions on the Bazaarvoice site.
Bazaarvoice’s device fingerprinting API enables you to detect a variety of fraud patterns and violations, such as resetting the fingerprint, emulators, fake accounts, and more. It also enables you to match the device fingerprint with previous fingerprints to provide a more complete picture of the user’s device behavior.
In order to use the fingerprinting API, you must have a user profile on your business server. This user profile should have a PIN or an email address. When the fingerprinting API detects that a user has failed to scan their fingerprint for more than an allowed number of times, all fingerprint refresh tokens associated with the user will be revoked on both the client and server side.