How to incorporate user-led engagement in mobile app design
Today, both consumers and employees instinctively reach for their smartphones and apps to accomplish a task or get the information they need at any given moment. In fact, according to the Daily Mail, studies show that mobile devices are so ingrained in people’s daily lives that users check them 85 times a day — taking up five hours every day — to get the information they need on demand.
Recognizing this, organizations are becoming smarter about how they approach mobile app design. They’re now trying to harness their full potential to engage users and make customers happy. In addition, they’re increasingly using more information and intelligence in the app, including the following:
- Contextual information, such as the user’s current location or activity. For example, is he at the airport or running his favorite trail?
- Individual data, such as app preferences or frequent tasks that help better anticipate what the user is trying to accomplish.
- Speech recognition and gesture detection that facilitate more human forms of interaction.
These developments point to a key insight: Mobile enables new types of interactions that necessitate rethinking the app experience. Instead of apps dictating when and how a user should accomplish a task, the app enables customers or employees to choose when and how to engage and can proactively guide users as they try to accomplish specific goals.
Improving experiences from hallways to fairways
This new interaction paradigm is driving a world of new, enriched mobile experiences. For example, a hospital app can inform a patient arriving at the hospital that there is a longer-than-expected line for his first appointment and that he should proceed first to the blood lab. It can also use indoor location technologies to guide the patient to the lab. This rich interaction can improve hospital efficiency in addition to patient satisfaction.
Mobile app design can also give users the flexibility to choose how to engage. For instance, a fan at a golf tournament might incorporate a tournament app to follow her favorite players. She can get notifications when her favorite players are about to tee off, compare their stats, pinpoint their locations on the course and socially interact with other fans cheering for those same players. The app may even predict how well players will do given their past performances on holes with similar layouts, lengths and hazards.
Cognitive capabilities up the game
With the advent of cognitive services, it will become even easier for apps to further identify the user’s intent and provide a tailored experience.
Machine learning can learn a user’s preferences and incorporate that knowledge to personalize the app. For example, the golf fan mentioned above may never specify which players she follows, but the app can infer her favorite players by following her previous actions.
Using a service such as a tone analyzer, you can differentiate between satisfied customers and unsatisfied ones, or ones that are just in a hurry. With that insight, you can tailor the dialog with the customer (in the app’s chat box) to address concerns and mood, just as a customer service representative would.
Using additional cognitive services, you can guide technicians in the field to solve unexpected problems. A technician could describe the symptoms of a malfunctioning appliance in natural language, and the app would suggest which chip on the board is likely to be defective. If the technician reports that changing the chip didn’t help, the app can suggest a different action to take. Capturing these interactions has the added benefit of continuous improvement, learning which troubleshooting paths are most likely to solve specific problems and improving outcomes each time the app is used.
3 keys for engaging mobile experiences
Building these engaging applications requires three main capabilities: profiling, cognitive services and an event-based architecture.
- Enterprise profiles: These profiles can combine both static information, such as demographic data with rapidly changing dynamic information, such as the features in the app that are being used. The profile becomes the central source of information to segment different types of users and to customize their experiences.
- Cognitive services: Enabling a natural language conversation with the user, cognitive services also use profile data, together with user actions, to figure out what the user is trying to accomplish. It then proposes the best way to help this user achieve his goals.
- Events: To create timely and engaging experiences, events must propagate from the device to the cognitive services and then back to the device. For example, when an employee gets stalled in a task, it can trigger an event that feeds the current context (where the employee is stalled) and a profile snippet (how proficient the employee is in this task, as well as her preferences) to the cognitive engine. The cognitive engine decides how to aid the user and sends a message back to the device with a suggested resolution. Event-trigger-action technologies are ideal for building out interaction patterns like this.
When using these technologies, it’s important to never forget that the goal is to help users accomplish their tasks. The mobile app design technologies may create a torrent of behind-the-scenes events and analysis for each user action, but the result is a simple intuitive interface, guiding the user and creating a delightful experience. In the future, the bar for apps will only continue to rise. Only apps that provide an engaging, cognitive and context-based experience will succeed in the market and with users.