Despite the compute power, memory and connectivity available on a mobile phone, the experience of using it to get online is not the same as a desktop computer. Not that we want it to be either. The web on your mobile should be a completely divergent experience – one that offers much more than the current PC-based standards.
That does not mean a break with the standards that spawned the growth of the internet; IP, HTML, Java et al are the cornerstones of the openness that allowed the world to become digitally connected. They permit content and applications to be delivered using the ‘Martini’ marketing mantra – anyone, anytime, anyplace on anything. Unlike the silos of proprietary technologies that once dominated IT, this open model has led to the explosive growth in online content, services and apps.
Great; except there is also a need for quality, especially around the user interface (UI), and this is one area where Apple in particular has excelled. True, it has also closed down options and kept overly high levels of control, but the end user experience is simple, effective and pleasant, especially on a mobile platform.
A few easy-to-use and relatively discrete applications on a mobile device works fine, but the difficulty comes as they become front ends into something more sophisticated within the network. It might be the combination of a number of back-end services or an element of a complex process, but there comes a point on a mobile device where a smart UI is no longer sufficient to keep it simple and easy to use – it needs more intelligence and integration.
The first stage is context awareness, and this is something the mobile phone is ideally suited to, with the combination of known device capabilities added to location awareness via cell triangulation and GPS. The focus is no longer about applications working in a generic way, but being tailored to fit the needs of one person, at a particular time and place and on a device with known constraints and capabilities. Mobile phones are far more personal than the PC ever was – identified to an individual by contract and always carried.
This concept of context awareness is not new, and one element at least – location – has been at the heart of a category of mobile services (location based services) for some time. However, even here the innovation has been sparse and more about finding ways to charge for location-based applications – turn-by-turn navigation, ‘find my nearest xxx’, etc – rather than incorporating the location context into the background intelligence of an application to make it easier to use.
It was only when GPS became a basic feature of mobile smart phones with the second generation of the iPhone that application developers latched onto the value location awareness could bring to their apps.
The idea that mobile applications should be tailored to a specific device is more complex, and opinion sways between universal browser-based approaches and native apps. There is value in being tuned to and taking advantage of device-specific features, but this means dealing with the time and costs of the extra porting and support effort. Betting the right horse in terms of mobile device platform market leaders is not easy either, especially over the development timeframes for more complex applications.
More value, at least in terms of ease of use, could be derived from tailoring the application, decision making and process flow to the individual and what their likely actions or needs might be. This requires more effort on behalf of the developer, but the rewards could be very significant.
Mobile applications that fit the needs and constraints of the mobile user are more likely to be adopted and much more likely to be retained. In an environment where there are tens of thousands of applications clamouring for attention, mobile application user loyalty will come not from prominent features, but from hidden polish.
The aim of the developer should be to think ahead removing obstacles and issues and retrieving useful information before the user has to take explicit action themselves. This prescient action can be taken by applying rules and logic to data already collected – about the user, past actions, information from social media sources – and feeding back the resulting action to improve future results.
For example, it might take the form of filtering search results for a restaurant to what that particular user in that place at that time might find most appealing (based on past experience and recommendations from friends), or it might limit the options in an optional selection list to those most relevant in that situation. Either way, a little prescience considerably improves the mobile user experience and makes apps that little bit more useful and ‘sticky’.