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Device Intelligence
In the connected world, device intelligence underpins everything: user experience, security, advertising and analytics.
Understanding the device is key to understanding your user.
What is device intelligence?
Device intelligence is the deep understanding of an end user device.
DeviceAtlas breaks down device intelligence into three separate layers: device identification, device characterization and device verification.
All 3 are needed to have a full understanding of the end user device, with device identification being the critical first step. No PII is involved at any level.
Breaking down the layers
Device Identification
The foundation layer
Device identification, also known as the foundation layer, determines the device vendor/brand, the model and the consumer recognized name or product family. There can be different device identifiers for any given device: for example the HTTP headers at the browser layer, make/model strings at the OS layer, and TAC (type allocation code) at the hardware layer. Any one of these identifiers can be used to identify the device model, which in turn links to the device characteristics.
Device Characterization
The enrichment layer
Device characterization probes the device further, offering deep insights on its characteristics and capabilities. It provides a set of metadata on the device, covering a wide range of areas including hardware capabilities, connectivity supported, multimedia codecs supported, OS and browser information. This layer is where the bulk of business use cases (analytics, optimization, targeting) are manifested and knowledge of user devices becomes critical.
Device Verification
The assurance layer
Device verification leverages both the identification and characterization layers to perform some key validation checks: firstly, to ensure that the different device identifiers are aligned, and secondly, that the actual device characteristics match those of the device identifiers. Verification of a user’s device is as important as verification of the user’s identity when providing access to proprietary resources, and even as part of paywall protection measures.
Existing challenges in the market
Increasing diversity of devices
The number of new devices and device types being released to the market is growing rapidly.
Lack of visibility on connected devices
Analytics reporting on visiting devices is limited and offers little granularity to businesses.
Growth in average page weight
Heavier page loads result in higher mobile bounce rates and accessibility issues.
Weak internal indexing
Inconsistent data between back end and front end systems can cause internal reporting discrepancies.
In-house device catalog maintenance
Significant engineering time and resources are required to build and maintain an internal database of user devices.
Growth of masquerading devices
The number of devices being tampered with or misrepresented, i.e. cloned, counterfeit, stolen, jailrooted, etc has grown exponentially in recent years.
Why is device intelligence critical for businesses?
Digital content world
All digital content is consumed on a connected device. Therefore, in a digital content world, the device forms a significant part of the interaction between a business and its user. If you want to understand the user experience, you need to understand the device being used to consume your content.
Broad spectrum of devices
The gap between high and low-end phone capabilities is increasing, so it’s no longer enough to simply say that a visitor is connecting via a smartphone. More and more users are also consuming content via a broad spectrum of devices, e.g. games consoles, TVs, set top boxes. Knowledge of these devices and their capabilities is critical.
User knowledge in a non‑PII context
The increasing sensitivity around privacy with legislative frameworks such as the GDPR are limiting the amount that businesses can know about their users. Therefore, knowledge of the device as a contextual signal increases in value and doesn’t require the need for PII.
Competitive differentiation
Businesses that want to gain competitive advantage over other players in the market will be the most data driven and consider the end user device as a key data point. The more they know about their users, the more they can improve their business outcomes and extend their reach.
What device intelligence is used for
Analytics Enrichment
Device intelligence is one of the most fundamental and critical components of analytics enrichment because it can uncover which device characteristics are materially influencing business metrics. e.g. Does screen size play a role in conversion rate? Does the number of CPU cores affect engagement?
Optimization
The outcome from analytics helps to enrich or optimize experiences and maximize engagement for each visiting device. e.g. a real-time decision to serve lighter pages to less capable devices. Device intelligence enables optimization of performance to steer business metrics and change outcomes.
Targeting
Device intelligence allows businesses to infer more about their users based on the device they are using, which can result in new targeting opportunities. e.g. Users with high end devices having more disposable income vs users with entry level devices, or users with newly released phones being early adopters.
Security
Device intelligence is critical within a security context, as it can provide additional signals at the device level about a user which may cause concern, e.g. are there any anomalies in how the device is presenting itself? Are the internal identifiers consistent with each other? These questions can determine whether an extra layer of authentication is needed.
Links to more resources
Technical resources
General resources
Interested to learn more?
Get in touch if you have any questions or would like to know more about integrating device intelligence into your stack.
