Context as a Service – Makeing mobile moments more accessable

The industry is awash with the buzz of context these days especially when it comes to mobile engagement and the software industry long ago went “all in” with the service based model. It’s inevitable, context as a service would emerge, and it has.

Integrating context into mobile engagement strategies is one of the biggest challenges for mobile marketers in today’s digital business. Blasting push messaging and indiscriminately invading the personal space of the mobile device is unacceptable. But, capturing the mobile moment to delight users is extremely valuable for brands to build loyalty. Unfortunately this is easier said than done.

A number of analytics companies and push messaging firms are bring to market platforms that track in-app behaviors and trigger messages or other calls to action. Some of the more sophisticated ones can segment users into cohorts and personas and integrate it with location base on proximity to a beacon and personalize messages.

A few vendors have emerged that are much more focused on context. These vendors have taken the solution to a next level focusing on a multitude of sensory data generated in the digital and physical world to infer the current user environment, mood or moment in their day. For example, based on a user’s home address and current GPS location, contextual apps can determine when a user is home. Accessing accelerometers and compasses, platforms can also sense that the user is on their way home. More granular data integrated with sophisticated AI and computer learning can provide high definition context that not only provides info on the current environment but predicts future environments. Specific data that some of these platform are tracking in include:

  • Location and gefoncing that integrates more than location but matches it against zipcode or country
  • Current weather and forecasts
  • Speed of movement and direction, not only where a user is but where they are headed
  • Identity, not just personas or personalization
  • Understanding past behavior inside the app and in real life
  • Individuals proximity to each other and places
  • Health metrics
  • Preferences such as music

To integrate all these data points, developers would have to call multiple APIs and create sophisticated logic to interpret each piece of data and how they relate to each other. Context as a service vendors are orchestrating and integrating a wide variety of data points along with AI and Machine learning to provide sophisticated platforms and tools that are simple for mobile app developers and marketers to use. Some of these platforms are also offering prepackaged experiences that can be delivered to users at the right moments.

Four vendors we have identified include:

Flybits – Providing context as a service. This commercialization of an academic project provides a platform targeting marketers. The platform also enables developers to customize content for each contextual situation.

Trnql – Provides smart services that are targeted at mobile app developers but are designed to simplify the process of building contextual aware applications.

Alohar mobile – This is another company that was developing a context aware platform but was bought by Alibaba and folded into the company.

Clever NudgeProviding mobile conversion platform that integrates with existing engagement and analytics platforms.

By putting the technology closer to the service and marketing professional who understand the various use cases and their clients contextual situations will benefit both user and marketer. The challenge will be constantly delivering real-time data and running algorithms without wearing down the device battery. Of course the quality of the AI and machine learning will separate the men from the boys. Communications as a service has already claimed CaaS so what do we call context as a service CXaaS?

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