Contextual Intelligence, Data and Mobile Technology: How Are They Shaping The Digital Future?
The number of mobile users has dramatically increased in the last 5 years, generating a huge dependency on mobile technologies. In the current year, 2016, 61% of web traffic is generated from wireless devices, as opposed to the more ‘traditional’ desktop computers, a statistic which suggests that mobile technologies are strongly contributing to the generation and growth of big data. In 2015, the big data market was esteemed to be worth a staggering $16.9b with, again, more than half of the data being produced by mobile technology.
Mobile web traffic in 2016
A new approach to exploiting big data is to merge it with location-based data, real-time information and sensors’ input – this is creating a revolution in the world of mobile innovation, creating the basis for a new paradigm that will affect our socio-economic structure and even our life as consumer-based users. This is known as Contextual Intelligence.
Focusing in on the detail of a single user’s data, collected thanks to mobile devices and their sensors, has been the first step in creating an ecosystem based on personalisation, customisation and real timing information and services, something that mobile users now constantly crave. Users’ data from mobile devices is in fact the basis of what we call Contextual Intelligence in mobile innovation, a direction that the market is quickly heading towards.
How mobile contextual innovation will change (and has changed) consumer behaviour and users’ lives?
Before the smartphone revolution of mid-2000’s, entire ecosystem of the telecommunication industry was based on coverage, quality and price of cellular networks. Features such as phone, messaging, contacts and camera were at the centre of the whole UX of a mobile device user. With the introduction of the first iPhone, the mobile ecosystem completely changed. After 2007 and Apple’s mobile devices success, technology has since referred to how well a mobile device computes as opposed to how well it communicates. This brand new approach to mobile computing was suddenly focusing more on integrating elements like applications and sensing platforms, with these elements constantly talking to the user to gather information from their physical, virtual and social environments.
As this framework develops, mobile shifts towards generative sources of data that have been able to reshape business mechanisms and consumers’ behaviours. Thus, mobile devices become an extension through which a large number of people can broadcast preferences, intent or even telemetry about their physical bodies, location or socio-demographics through interaction with cloud services and other smart objects. A sample of apps that are currently employing sensors to provide information about a user’s behaviour are the well known Fitbit, Up from Jawbone, Withings, Beddit and other activity trackers similar to these.
Thus, this new technological ecosystem has generated what is known as “Contextual Intelligence” from mobile users’ physical, virtual and social environments.
For instance, a day in the contextual life of a salesman can be improved by using real-time data to monitor his location, calendar and the time, with the goal being to improve his working experience. For example, his mobile device could alert him that his next meeting is in 15 minutes (without the need to manually set a reminder), prompt him to send a message to his client notifying them of his impending arrival and provide him with the optimum driving route to reach his next client on time by avoiding bad traffic conditions. By leveraging such knowledge, smart devices can add value to users’ lives by managing unexpected situations and offering opportunities and solutions based on real time data.
As mentioned earlier, contextual intelligence is contributing to the transformation of mobile devices to behave more as a digital assistant and less as simply a communication or internet access point tool. A digital assistant tries to understand the user’s contextual situation in order to offer suggestions or services that help accomplish the user’s goals. The first steps for delivering a digital assistant is to understand a user’s immediate physical environment.
By gathering all of this information, it is possible to anticipate users’ needs and preferences and enable businesses and organisations to provide services at the right time and in the right location. Technology consulting firm, PwC, predict that “more than simply storing data or processing applications, contextually aware mobile devices, applications and services will continually ‘learn’ about their users to provide better experiences the more they are used”.
To demonstrate some practical examples that have occurred in the last five years, the most well-known example of a contextually intelligent mobile service is Apple’s Siri – this voice-activated virtual assistant responds with information and services that grow in relevance the more the system is used. Other general virtual assistants, such as Google Now or Microsoft’s Cortana, have since launched to try and establish themselves in this newborn market for mobile contextual services. All the abovementioned elements of contextual intelligence interact at several levels and across different players. As a consequence, no single business or industry is likely to own and control the contextual value chain because the success of contextual technologies is dependent on the openness of the ecosystem.
The possible number of uses and business models unleashed by better location and sensor data is huge and growing. For instance, when looking at mobile applications, one of the latest award-winning apps – the first release from the Innovation Lab of PGi – is Agenday, which seeks to bring an increased level of contextual intelligence to business users as well as providing a more frictionless collaboration experience.
As we’ve seen before, contemporary mobile devices and services are designed to provide contextually intelligent data or even take actions on behalf of the user in a natural, seamless and non-invasive manner. Consequently, this scenario has also raised huge concerns over user privacy in the face of such detailed tracking and represents a delicate, controversial issue in the future development of such technologies.
Nowadays, mobile innovation is one of four market forces that are redefining customer demand, expectations and business opportunities. In this framework, Contextual Intelligence is the driving technology that fosters the ‘just-in-time’ (JIT) mobile lifestyle that is becoming more prevalent. Several studies suggest that mobile users are using their devices as much for organising their daily lives as for communication. Thus, the definition of a generic mobile user experience has essentially become obsolete.
Users now want experiences specifically tailored for them; experiences that have the ability to be dynamic and face/solve specific situations.The result of these trends will be a boost in the contextual information market ecosystem – activities, locations, transactions, preferences and emotional states will all be logged, and deployed in unison with patterns and archived behavioral information to create contextual experiences that bring Just in Time mobile markets to the fore.
One downside of the rise of this new ecosystem is privacy management. Guaranteeing privacy will become one of the biggest and most important industry sectors in the contextual age, just as the industry players dedicated to managing and visualising the contextual information spaces of users will too.
The opportunities in the contextual services paradigm are both huge and challenging and will create a large shift in the actual technologic panorama. As with all big movements of change, many of us will be reticent but, at Pomegranate, we believe that the value of mutual interaction with a device that will know us better as both users and consumers will be hard to denigrate.