After a decade of taking the commercial market by storm, it’s official: voice technology is no longer the loudest secret in Silicon Valley. The speech and voice recognition market is currently worth over $10 billion. By 2025, it is projected to surpass $30 billion. No longer is it monumental or unconventional to simply speak to a robot not named WALL-E and hold basic conversations. Voice products already oversee our personal tech ecosystems at home while organizing our daily lives. And they bring similar skill sets to enterprises in hopes of optimizing project management efforts.
The future arrived a long time ago. Problems at work and in life are now more complex. Settling for linear solutions will not suffice. So how do we know what separates a high-quality modern voice user experience (UX) from the rest?
Navigating an ever-changing voice technology landscape does not require a fancy manual or a DeLorean (although we at Alan proudly believe DeLoreans are pretty cool). A basic understanding of which qualities make the biggest difference on a modern voice product’s UX can catch us up to warp speed and help anyone better understand this market. Here are four features each user experience must have to create win-win scenarios for users and developers.
Pitfalls in communication between people and voice technology exist because limited insights were available until a decade ago. For instance, voice assistants were forced to play a guessing game upon finally rolling out to market and predict user behavior in their first-ever interactions. They lacked experience engaging back and forth with human beings. Even when we communicate verbally, we still rely on subtle cues to shape how we say what we mean. Without any prior context, voice products struggled to grasp the world around us.
By gathering Visual, Dialog, and Workflow contexts, it becomes easier to understand user intent, respond to inquiries, and engage in multi-stage conversations. Visual contexts are developed to spark nonverbal communication through physical tools like screens. This does not include scenarios where a voice product collects data from a disengaged user. Dialog contexts process long conversations requiring a more advanced understanding. And Workflow contexts improve accuracy for predictions made by data models. Overall, user dialogue can be understood by voice products more often.
When two or more contexts work together, they are more likely to help support multiple user interfaces. Multimodal UX unites two or more interfaces into a voice product’s UX. Rather than take a one-track-minded approach and place all bets on a single UX that may fail alone, this strategy aims to maximize user engagement. Together, different interfaces — such as a visual and voice — can flex their best qualities while covering each of their weaknesses. In turn, more human senses are interacted with. Product accessibility and functionality improve vastly. And higher-quality product-user relationships are produced.
Developers want to design a convenient and accurate voice UX. This is why using multiple workflows matters — it empowers voice technology to keep up with faster conversations. In turn, optimizing personalization feels less like a chore. The more user scenarios a voice product is prepared to resolve quickly, the better chance it has to cater to a diverse set of user needs across large markets.
There is no single workflow matrix that works best for every UX. Typically, voice assistants combine two types: task-oriented and knowledge-oriented. Task-oriented workflows complete almost anything a user asks their device to do, such as setting alarms. Knowledge-oriented workflows lean on secondary sources like the internet to complete a task, such as searching for a question about Mt. Everest’s height.
Hard work that goes into product development can be wasted if the experience curated cannot be shared with the world. This mantra applies to the notion of developing realistic contexts and refining workflows without ensuring the voice product will seamlessly integrate. While app integrations can result in system dependencies, having an API connect the dots between a wide variety of systems saves stress, time, and money during development and on future projects. Doing so allows for speedier and more interactive builds to bring cutting-edge voice UX to life.
Voice tech has notoriously failed to respect user privacy — especially when products have collected too much data at unnecessary times. One Adobe survey reported 81% of users were concerned about their privacy when relying on voice recognition tools. Since there is little to no trust, an underlying paranoia defines these negative user experiences far too often.
Enterprises often believe their platforms are designed well-enough to side-step past these user sentiments. Forward-thinking approaches to user privacy must promote transparency on matters regarding who owns user data, where that data is accessible, whether it is encrypted, and for how long. A good UX platform will take care of computer infrastructure and provide each customer with separate containers and their own customized AI model.
If you’re looking for a voice platform to bring your application, get started with the Alan AI platform today.