Nearly 3 billion people worldwide use smartphones. For many of us, these devices are our primary connection to the larger world. These personal devices store and express our digital identities and, as they become more sophisticated, they offer us more personalized experiences.
Our devices have become hyper-personalized, serving up tailored ads and social media suggestions while automating simple conveniences, such as automatically adjusting screen brightness levels to our observed tastes. In this way, our phones increasingly provide experiences that reflects our exact preferences. Customized push notifications in particular have the potential to offer users individualized alerts on a moment-appropriate basis.
But there is a dark side to hyper-personalization. Astonishingly, 2.5 quintillion bytes of data are generated per day, a rate which will only increase. This mass of data is a tremendous tool to improve the digital lives of devices users, properly employed it can be used to offer a customized experience across all platforms. Recent data security breaches, such as the Cambridge Analytica scandal, have shown the risks of exposing personal data. But where is the line between mobile engagement and mobile invasiveness?
The Architecture of Push Notification Platforms
Traditional push notification platforms take a three-step approach to sending personalized notifications to mobile users:
- Push tokens from the mobile app are first uploaded to an application’s backend server.
- The backend server forwards the notifications to a cloud service along with the personalised notification message, such as APNS for iOS devices or Firebase for Android.
- APNS or Firebase then makes reasonable efforts to deliver that notification to the user’s device. The mobile app will likely track if the user taps on the notification (when it opens the app)
While this model works well enough, it also proves to be problematic.
First, reliability is a key pain point in the push notification industry. In a fast-paced world where news and situations can change faster than the information about them can relay, it’s crucial to be able to communicate with users and customers in real-time. The use of traditional cloud servers can cause hours of delay as notifications are held until some data or information is collected from the mobile app on the device. In some cases, this can also cause notifications to be sent in the wrong order, or even fail to be delivered.
Second, there are ever-increasing concerns over data security. Since the passage of the EU’s GDPR, push notification platforms have updated their privacy policies to clarify that the onus is on the mobile app itself to guarantee compliance. This means mobile apps need to ask users for their consent to have their data processed by third-party servers.
Edge computing offers and alternative. By pushing the messaging platform to the edge, it’s possible to bypass the use of centralized servers altogether. This is where edge computing comes in.
Edge Computing and the Next Stage of Push Notifications
By processing data at the edge of the last mile network, algorithms can be built that ensure only crucial data is forwarded to a permanent, centralized server. This has tremendous potential in terms of real-time information and analytics, not to mention a reduction in the amount of data that has to be transmitted to a centralized server. It also has endless implications for ways it could disrupt the way people and devices interact, as the Internet of Things (IoT) becomes increasingly interconnected.
So how will this affect push notifications?
By incorporating edge computing into the design of a push notification SDK, it’s possible to cut out the necessity of a cloud storage center. Data analysis for segmentation will thus occur on the device itself, with push tokens being stored on the app’s backend servers located at the edge rather than in a centralized cloud. By cutting out the roundtrip path to centralized servers, we can create a more direct, agile flow of data—with the ability to communicate and respond to data triggers in true real-time.
Edge computing can provide more ways to communicate with users without sacrificing privacy, and these can be provided in highly context-sensitive ways, with messages for the exact moment on a person-to-person basis.
For example, a person using the Domino’s app on their phone can be coordinating with the GPS on the device without revealing the user’s location to a centralized server. Walk within a certain distance of a Domino’s restaurant and the app can offer a discount code for a pizza. Or, imagine purchasing plane tickets to Madrid with a travel app. In this scenario, future push notifications could direct them to an in-app function to book hotels for the dates required, or could suggest the top 10 tourist attractions to visit in Madrid, or could keep you up-to-date with real-time flight information.
Sending the Right Notification at the Right Time
With access to a user’s calendars, travel habits based on phone usage, and local weather and news data, an app can pinpoint the exact moment the message will be relevant to you, which is also the moment you will be most likely to engage with the message. For example, if a traffic app that reports of inclement weather or a traffic collision in your area can send a notification warning you to drive carefully, or offer you alternate routes to their destination.
Crucially, app developers can set notifications to pause notifications when the user is busy—say, in the morning when they’re getting ready for work, during rush hour, or when they’re sleeping. There’s a sweet spot in terms of number of notifications an app can send out before it becomes a nuisance (of course, this number varies from app to app), so it’s important to make every notification count.
For apps the present entertaining content, the best moment to offer a notification might be when the user is relaxed, at home, and scrolling through content on their phone without other distractions. If a user has their headphone jack in use and their phone is unlocked, this can be the ideal time to send them rich content, such as a video or a GIF. If a user’s device is offline, it may be better to set notification to go out when they are back online or within range of a Wi-Fi hotspot.
Edge Computing Lets Users Keep Agency and Ownership of Their Data
To offer rich and contextual notifications with traditional notification mechanisms requires mass quantities of data to be stored on centralized servers. This creates substantial risk for data breaches, particularly for highly sensitive data, including data from financial or medical apps. Even when data is being processed exactly as intended—for example, when user data is sold to advertisers, as is often the case for free push notification packages—this may expose companies to consumer backlash as users become much more discerning about where their data is stored and who has access to it.
Edge computing provides a mechanism for implementing a notification platform that is more sophisticated and offers real-time interactions with users. These modern notification platforms will completely replace the problematic architecture of traditional push notification services. By interacting, processing, and analyzing data at its source—on the device itself—mobile apps can personalize their communications while reducing the risk of data breaches. Data stays on the user’s device at all times, so the user retains full ownership and agency of their data.
In a world where personal data is fast becoming appreciated as one of our most valuable resources, edge computing means mobile app users can be confident their information isn’t being sent to unknown third parties. Similarly, the apps are safe from liability should a breach occur. And above all, user engagement is optimized by providing them with timely, hyper-personalized notifications that are tailor-made to fit their interests, needs, and changing schedule.
David Shackleton is a co-founder of OpenBack, the only mobile engagement platform that uses edge computing and device-side decisions to deliver smart push notifications. David also co-founded Ding, the largest international top-up platform which launched in 2006 and delivers a top-up every second, across more than 130 countries. Prior to Ding, David was a management consultant with the Monitor Group in the US, working in Boston and New York.