Trend 2015: Pro-active Experiences
The proliferation of mobile devices lead Google CEO Eric Schmidt 2010 to its development mantra “mobile first”: every product developed by Google had to have the mobile experience and the mobile user as the starting point. Today, no company can afford not to offer experiences optimized for mobile. Websites still not meeting this requirement are even penalized in Google’s search algorithm, giving them less prominence in the search results.
Mobile optimization is therefore expected and doesn’t suffice for differentiation anymore. Recent developments are using mobile as an enabler to enrich the experience in a much more integrated fashion, taking into account all the information gathered by the smartphone 24/7: data on preferences, locations visited, daily routines and much more are all up for grabs with the goal of creating an omniscient companion. Users should not be required to explicitly state their goals anymore – the app should be able to infer the user’s intent and provide him with just the right information at exactly the right time. In this setup a user tells the system (explicitly or implicitly) only what he wants – not how to get it anymore, as the computer will be able to hide this complexity from the user.
Affected Industries: Travel, Navigation, Entertainment, Home Automation, Automotive, Software, Energy/Utilities, Insurance
From responsive to pro-active
The majority of the current systems and interfaces have only limited pro-active or anticipatory capabilities – if any at all. They react to actions in the present – i.e. they are responsive. Pro-active, anticipatory or predictive experiences in contrast take actions taken in the past, the present and expectations about future actions into consideration. Forrester defines these predictive apps as follows:
“Apps that leverage big data and predictive analytics to anticipate and provide the right functionality and content on the right device at the right time for the right person by continuously learning about them.”
These technologies really only became visible in the consumer mainstream this year and will have an increasing impact in 2015. Artificial Intelligence makes the machines smarter, while the exponential increase in processing power enables them to handle more and more data at a fraction of the time and cost.
The proliferation of anticipatory experiences, however, is not just driven by these technological factors but also by an change in the users’ perception of technology, which is increasingly disappearing in the background and less visible (Trend 2015: Blurring of Online/Offline). Technology has morphed from a tool into a mobile, social and functional companion.
Home- und Life-Automation
Nest, the company recently acquired by Google, is a good example for an anticipatory solution. The intelligent thermostats manufactured by Nest are creating individual energy consumption profiles for their users, taking into account not only the user behavior and weather related variables dynamically, but also the pricing structure of various energy providers. Based on all that data, Nest can anticipate the preferred energy settings of the user at any given time.
With potentially disruptive implications for energy providers, aggregators and middlemen in the value chain to the consumer: not only will Nest be able to optimize the consumption and lower the costs in an anticipatory fashion but it will also enable them to recommend the most reasonable tariff and provider to the consumer. To secure their access to consumers, energy providers and utilities are therefore already in the process of signing contracts with Nest. Utilizing the wealth of data collected through sensors distributed throughout their clients’ homes, Nest is generating a treasure trove of information for insurance companies.
LG’s intelligent fridge knows its content and can generate shopping lists automatically. It can also be pinged via direct message to check if there is enough beer on stock or it can also send reminders if you’re running out of milk.
Another promising foray into pro-active experiences is Google Now. The app provides its user automatically with information relevant to the user’s context without requiring the user to explicitly ask for the information. In order to be able to do so in a meaningful way, the app learns and analyzes the user’s routines and meshes these insights up with other data, such as location data and numerous other context-related variables. Depending on the typical routines, the app can infer if the user is at home or at work, what the most probable next destination will be, check the traffic status on the road to the next destination and suggest alternative routes to avoid traffic jams and alert the user to leave early – without requiring the user to explicitly state a request.
By using all the data available and “understanding” the relation between all the variables within the Internet of Things, the computer is able to create pro-active experiences while hiding the complexity of the decision making process from the user in the background, providing him just with the information that he needs:
Navigation systems determine alternative routes based on the traffic conditions automatically, directing drivers pro-actively to avoid obstacles without requiring the user to actively get involved.
For most people the widespread reporting on Amazon’s “Anticipatory Shipping” system brought these kind of experiences to their attention for the first time. By analyzing shopping- and search-patterns, Amazon plans to be able to identify the products a customer is going to order next, pro-actively supplying them to a warehouse in the customers vicinity prior to the actual order of the products, shortening delivery times in the process.
Just like with wearables (Trend 2015: Quantified-Self/Wearables) the user’s personal data is at the center of pro-active experiences. Only with access to a wide array of data points are these apps able to predict the user’s needs and alleviate a significant chunk of the manual work. For a widespread adoption and the realization of the potential of these solutions, the users’ trust is therefore a crucial component. The large number of negative comments and ratings of the Google Now product video and on all similar solutions are a strong indication that privacy and personal data (Trend 2015: Redefinition of Privacy) are still and increasingly a major issue in the user’s perception.
Pro-active experiences have in common that they are hiding complexity from the user while reducing the load of decisions the user has to make. Users only have to state explicitly or implicitly, what they want and what the constraints are – the decision about how the goal is reached is handled by the application.
Suppliers of these kinds of pro-active solutions are therefore turning into influential middlemen in the distribution channel – with profound implication on all companies still believing in influencing consumers with their marketing message: if apps are starting to take the consumer’s place in the decision-making, entirely new dependencies will require the formation of new alliances to secure the distribution channel, as already demonstrated by Nest.
In the development of pro-active experiences, the following ground-rules have to be kept in mind:
- be relevant – but don’t creep the user out: the use of personal data is a prerequisite for turning these apps into a useful companion; the use should be limited to an extent, however, that prevents the user from being creeped out by having a stalker instead
- support – but don’t patronize the user: the app should feel like having a thoughtful butler, offering his help in a discrete fashion when needed – instead of an overprotective mother, always knowing what’s best and making the user feel he’s not in control by patronizing him
- avoid frustration: at first glance, a pro-active app that is right 85 percent of the the time might be considered a success; if the suggestions provided are wrong in 15 percent of the cases, however, the user’s trust will quickly erode
Pro-active experiences are still only in an infancy stage but powerful players like Apple, Google, Facebook and Amazon already have a lot of the building blocks required in place. In 2015, improved iterations will hit the market, driving mainstream adoption – with far-reaching implications on existing players and the users’ UX expectations.