Blog Post:In a world where 60 percent of adults interact with at least two screens per day (see image below), it’s essential that marketing campaigns target people rather than devices. But, whether you’ve decided to send anonymized customer IDs directly to the walled gardens of Facebook and Google, or you’ve hosted them securely within your own data-management platform (DMP), it’s challenging to do cross-device marketing right. What’s more, the cost of not solving this issue is huge. Forrester estimates that America’s millennials will spend over $600 billion this year across an average of 5.5 connected devices per person. The recent eMarketer webinar, “Cross-Device Targeting — What to Watch for in 2017,” goes into detail regarding the trends and key challenges facing marketers who must deliver consistent, cross-device experiences. The much-discussed solution to this cross-device challenge is to build or buy a device graph. A device graph is a set of ID mappings that are used to define groups of anonymous devices as being used by the same person based on commonalities among the signals collected from each device. These signals indicate levels of identity. The most accurate signal is from a log-in event (signing into a website or app, for instance); however, other signals (such as IP address or device meta-data) can also be used. When layered over an audience segment comprised of device IDs, these device graphs can be used to anonymously classify the common identity behind each device in the audience segment (typically, a person or household). This allows a marketer to deliver a consistent cross-device experience to the audience segment, tailored perfectly to the person (or people) using each device. That said, factors such as scale, accuracy, privacy, and control make it very difficult to find the perfect device graph to use and the best platform on which to use it. Top-Three Tips for Using Device Graphs to Deliver Optimal Cross-Device Experiences Following are my top-three tips for delivering successful cross-device experiences with device graphs: 1. Be Flexible. Every device graph has its own unique advantages, so put your business in the position to leverage all of them. If you build your own device graph based on signals collected from your own websites and apps, you’ll ensure maximum control over how the graph is built and used; but, inevitably, it will be limited by scale. On the other hand, if you decide to use a device graph from within a publisher’s walled garden (think Facebook, Google, Twitter, etc.), you’ll increase your scale but be limited to using the graph with audiences defined by each of these publishers for use only on the inventory they sell. In other words, your device graph won’t exist outside of that publisher’s ecosystem. The solution here is to build your audience segments in a platform-agnostic environment that offers the ability to construct your own device graph, opt-in to a shared device graph, or to lease a third-party device graph. The obvious choice for such an environment is the data-management platform (DMP). The DMP should offer integrations with all major targeting platforms, publishers, and data providers to ensure optimum scale, accuracy, and consistency of the audiences it defines. Adobe’s DMP, Adobe Audience Manager, enables marketers and publishers to create their own device graphs from their first-party data as part of its built-in Identity Management capabilities. In addition, Audience Manager has integrations with multiple device-graph vendors, including Adobe’s own Device Co-op as well as the LiveRamp and Tapad device graphs. 2. Understand the Importance of Scale. Targeting and retargeting your existing customers using your own device graph built from anonymized first-party data is a common example of people-based marketing. The challenge is, by definition, this device graph can only include the devices you’ve not only seen, but also been able to connect to known customers based on their actions across your digital properties. If you want to extend your reach to also target your customers (and even your prospects) across the devices they own that you’ve never seen, you’ll need a bigger graph. This is where the Adobe Device Co-op can help. The Device Co-op is a device graph comprised of data collected from multiple businesses that have joined forces to contribute to and benefit from a shared device graph. Importantly, the graph extends far beyond the devices any one business has seen on its owned digital properties, allowing it to increase the reach of its campaigns and target users across all their devices — even if they’ve only been identified on one device. The Adobe Device Co-op is currently the largest device graph of its kind in North America and is being used to help marketers both activate and measure the performance of people-based audience segments without having to sacrifice scale. 3. Be in Control. If you’re going to use device graphs to define, target, and measure the effectiveness of your marketing campaigns, be sure to have complete control over how they are being used. Audience Manager’s Profile Merge Rules allow marketers to create sophisticated logic regarding how a device graph defines the people within a segment for any number of marketing scenarios. For instance, one rule may be configured for use with known customer segments leveraging a first-party device graph; whereas, another rule could be used to define anonymous prospects leveraging a third-party device graph. In addition, marketers can use Profile Merge Rules to define which platforms the segments using a device graph can be exported to in compliance with their company’s privacy policy. As more advocacy groups and governments create new legislation around consumer privacy, it’s critical to maintain control over which device graphs you use and how they are used across your business. In Conclusion Customers have come to expect the experience they have on one connected device to continue when they access a second or third device. By following the three principles outlined above — be flexible; understand the importance of scale; and be in control — marketers can take the necessary steps to meet these expectations by delivering consistent user experiences and enabling new cross-device marketing tactics that will, ultimately, improve their ROIs. Author: Date Created:April 20, 2017 Date Published: Headline:Cross-Device Marketing: Three Tips for Success Social Counts: Keywords: Publisher:Adobe Image:https://blogs.adobe.com/digitalmarketing/wp-content/uploads/2017/04/Image-Cross-Device-Marketing-Three-Tips-for-Success-e1492667114624.jpeg

In a world where 60 percent of adults interact with at least two screens per day (see image below), it’s essential that marketing campaigns target people rather than devices. But, whether you’ve decided to send anonymized customer IDs directly to the walled gardens of Facebook and Google, or you’ve hosted them securely within your own data-management platform (DMP), it’s challenging to do cross-device marketing right. What’s more, the cost of not solving this issue is huge.

Forrester estimates that America’s millennials will spend over $600 billion this year across an average of 5.5 connected devices per person. The recent eMarketer webinar, “Cross-Device Targeting — What to Watch for in 2017,” goes into detail regarding the trends and key challenges facing marketers who must deliver consistent, cross-device experiences.

The much-discussed solution to this cross-device challenge is to build or buy a device graph. A device graph is a set of ID mappings that are used to define groups of anonymous devices as being used by the same person based on commonalities among the signals collected from each device. These signals indicate levels of identity. The most accurate signal is from a log-in event (signing into a website or app, for instance); however, other signals (such as IP address or device meta-data) can also be used. When layered over an audience segment comprised of device IDs, these device graphs can be used to anonymously classify the common identity behind each device in the audience segment (typically, a person or household). This allows a marketer to deliver a consistent cross-device experience to the audience segment, tailored perfectly to the person (or people) using each device. That said, factors such as scale, accuracy, privacy, and control make it very difficult to find the perfect device graph to use and the best platform on which to use it.

Top-Three Tips for Using Device Graphs to Deliver Optimal Cross-Device Experiences
Following are my top-three tips for delivering successful cross-device experiences with device graphs:

1. Be Flexible.
Every device graph has its own unique advantages, so put your business in the position to leverage all of them. If you build your own device graph based on signals collected from your own websites and apps, you’ll ensure maximum control over how the graph is built and used; but, inevitably, it will be limited by scale. On the other hand, if you decide to use a device graph from within a publisher’s walled garden (think Facebook, Google, Twitter, etc.), you’ll increase your scale but be limited to using the graph with audiences defined by each of these publishers for use only on the inventory they sell. In other words, your device graph won’t exist outside of that publisher’s ecosystem.

The solution here is to build your audience segments in a platform-agnostic environment that offers the ability to construct your own device graph, opt-in to a shared device graph, or to lease a third-party device graph. The obvious choice for such an environment is the data-management platform (DMP). The DMP should offer integrations with all major targeting platforms, publishers, and data providers to ensure optimum scale, accuracy, and consistency of the audiences it defines. Adobe’s DMP, Adobe Audience Manager, enables marketers and publishers to create their own device graphs from their first-party data as part of its built-in Identity Management capabilities. In addition, Audience Manager has integrations with multiple device-graph vendors, including Adobe’s own Device Co-op as well as the LiveRamp and Tapad device graphs.

2. Understand the Importance of Scale.
Targeting and retargeting your existing customers using your own device graph built from anonymized first-party data is a common example of people-based marketing. The challenge is, by definition, this device graph can only include the devices you’ve not only seen, but also been able to connect to known customers based on their actions across your digital properties. If you want to extend your reach to also target your customers (and even your prospects) across the devices they own that you’ve never seen, you’ll need a bigger graph.

This is where the Adobe Device Co-op can help. The Device Co-op is a device graph comprised of data collected from multiple businesses that have joined forces to contribute to and benefit from a shared device graph. Importantly, the graph extends far beyond the devices any one business has seen on its owned digital properties, allowing it to increase the reach of its campaigns and target users across all their devices — even if they’ve only been identified on one device. The Adobe Device Co-op is currently the largest device graph of its kind in North America and is being used to help marketers both activate and measure the performance of people-based audience segments without having to sacrifice scale.

3. Be in Control.
If you’re going to use device graphs to define, target, and measure the effectiveness of your marketing campaigns, be sure to have complete control over how they are being used. Audience Manager’s Profile Merge Rules allow marketers to create sophisticated logic regarding how a device graph defines the people within a segment for any number of marketing scenarios. For instance, one rule may be configured for use with known customer segments leveraging a first-party device graph; whereas, another rule could be used to define anonymous prospects leveraging a third-party device graph. In addition, marketers can use Profile Merge Rules to define which platforms the segments using a device graph can be exported to in compliance with their company’s privacy policy. As more advocacy groups and governments create new legislation around consumer privacy, it’s critical to maintain control over which device graphs you use and how they are used across your business.

In Conclusion
Customers have come to expect the experience they have on one connected device to continue when they access a second or third device. By following the three principles outlined above — be flexible; understand the importance of scale; and be in control — marketers can take the necessary steps to meet these expectations by delivering consistent user experiences and enabling new cross-device marketing tactics that will, ultimately, improve their ROIs.