Voice-enable your product
Jan 13, 2021
7 MIN READ

The 5 Critical Steps to Voice-Enabling Your Product or Service

If you’re like most companies, the discussion around voice-enabling your products, services, or mobile apps started some time ago. Maybe you’ve already started some internal development and maybe you’re looking for a starting point.

No matter where you are in the process, you’ve probably already discovered that developing a robust voice user interface that meets business needs and delivers on its promise of better user experiences isn’t the same as developing a new product or adding on enhancements to existing products. In fact, it’s a lot harder.

The biggest surprise for most of the companies I’ve worked with is the amount of time it takes to really develop a voice user interface that meets all the requirements. The challenge for many of those companies is that teams—unaware of where to begin—skip critical steps that result in delays and longer development timelines. 

Take a moment to assess your progress and consider taking a step back to set the foundation that will lead to a successful implementation of a voice assistant. Here are 5 critical steps to take (or steps to retrace) to make sure your voice project ends in the development of a voice assistant that adds functionality to your products and increases their value.

The challenge for many of those companies is that teams—unaware of where to begin—skip critical steps that result in delays and longer development timelines. 

1. Get organized and plan for the long-term

The first critical step to ensuring the success of any project—especially a voice project—begins with organization and planning. Good planning includes determining parameters around how internal and external teams will collaborate, and setting schedules with goals and deadlines for each phase of the project. 

I recommend planning regular check in meetings, setting up sprint planning meetings, and developing milestones that have some fluidity to them. The more planning and effort you put into communication internally and with external teams, the better the expected outcomes will be.

If you use agile, it’s important to get onto a sprint cycle so that you can develop a cadence and understand that this is not going to be a short term endeavor. Most voice service projects take a year or more and shouldn’t be considered in weeks. Although there are some voice services that you might be able to get done in a couple months, those would be very limited in scope and maturity in terms of user experience.

As companies start the conversation with their internal engineering teams, it’s important to realize that putting together a proper voice assistant takes a tremendous amount of time. It’s taken several years, if not decades, for voice technology platform providers to get to the point where they’re able to offer voice AI services to other companies. Thinking that your internal teams can accomplish the same goal in a matter of months is not realistic.

As companies start the conversation with their internal engineering teams, it’s important to realize that putting together a proper voice assistant takes a tremendous amount of time.

Before you embark on any engineering effort, take the time to look closely at what is going to be involved and what resources and outside support you’ll need to develop a robust voice assistant. Spend a month or so in the planning stage. Determine what sort of engineering efforts are going to be needed internally and how your teams will interact with the tools available from the voice AI platform provider.

2. Understand your customers and use cases

When first deciding on the voice user interface (VUI) for your products, I think it’s important to understand the use cases for the voice assistant. Begin by understanding how your customers interact with the product, service, or app you intend to voice-enable, and drill down as to the behavior they currently exhibit when they’re addressing your product.

It’s important to understand your core use cases, build the voice user interface around them, and then use them to set goals and identify requirements. Ultimately, a KPI report will be developed from the use cases to track the iteration and improvement cycles of the voice assistant.

Of course, when you first expose the voice user interface to users, you’ll also need to provide guidance and ongoing education. User education is a key element to the initial adoption and continued engagement. Afterall, if your users don’t know what your product can or can’t do, they may abandon the voice interface and your product in frustration.

It’s really important to understand your core use cases, build the voice user interface around them, and then use them to set goals and identify requirements.

A lot of people are still getting used to using voice assistants and the more guidance you can give them, the happier they’re going to be interacting with that interface. Once your voice assistant has been in the market for a while, you will want to go back and look at your user data to understand what functions your customers are and aren’t using. Then, you can make improvements and continue to iterate.

3. Make improvements and learn from regressions

Developing a voice assistant is never a one and done project. Even voice user interfaces that have been in the market for the last couple of years are going through regular rounds of iterations based on user data. While many of those iterations will happen during the development phase, teams need to plan for ongoing maintenance and changes to meet user needs. 

It’s also important to note that during the development phase, not every change is going to result in an improvement. Oftentimes. injecting new data into the models for training purposes produces regressions. It’s important to understand anytime a regression occurs and to understand how the data is affecting the training of the models.

Engineering teams are often surprised that new data doesn’t always result in improvements. Make sure your teams understand that you will see regressions and accept that it’s part of the learning and development process. Over time, regressions get smaller and smaller as teams move towards a specific goal. However, the process can be a bit of a bumpy road, so be prepared to roll with the ups and downs of voice development.

Engineering teams are often surprised that new data doesn’t always result in improvements. Make sure your teams understand that you will see regressions and accept that it’s part of the learning and development process.

Putting time into planning and establishing clear lines of communication will significantly mitigate misunderstandings around the development process and keep the project moving forward. Setting expectations that there will be setbacks and regressions up front will help teams to communicate these events as normal stages in the development process.

4. Use data not opinion to guide voice assistant development

It’s also important to understand that new processes are going to have to be created in order to support your voice project. It’s important to gather and use the most accurate and detailed information about user behavior and product functionality. 

If you begin with information that is imperfect, it makes the process of creating an effective voice assistant a lot more difficult. If, for example, you are creating a voice user interface that relies on movie titles and you start with movie titles that are spelled incorrectly or were abbreviated, the voice user interface will never meet customer expectations. Any information that isn’t high quality will affect the output and result in inaccurate responses.

Collecting accurate and timely data is key to every stage of building and delivering a custom voice assistant. Brands can get the most value out of their data by understanding how users are interacting with the voice assistant, identifying gaps, and then making the modifications that will improve the voice interface over time. 

Collecting accurate and timely data is key to every stage of building and delivering a custom voice assistant.

The data you collect at various stages of development can be used to train future models and create an exceptionally robust voice service. You’ll want to perform a variety of experiments in collaboration with your voice AI provider to ensure that the data is robust and can be used to improve your voice model.

5. Set realistic time frames for developing a voice assistant

If you’re exploring the idea of developing a voice user interface internally without the help of an outside voice AI platform provider, you should know that most companies who take this path spend a lot of time trying to determine their approach to voice. While that might be time well spent, in the end teams are no closer to a final product than when they started. 

Partnering with a voice AI platform provider, like SoundHound Inc., removes the burden of developing a voice assistant from scratch, and allows your teams to stand on the shoulders of our 15 years of voice AI technology development. We’ve already put a lot of the trials and tribulations of voice AI development behind us.

If you are exploring doing something internally, I highly suggest reaching out to people in the community to get a realistic sense of what it takes to put a voice assistant together. Even with companies like ours, the time to get a proper voice user interface ready for the market is significant.

Developers can explore Houndify’s independent voice AI platform at Houndify.com and register for a free account. Want to learn more? Talk to us about how we can help you bring your voice strategy to life.

Jason Barros, SoundHound Inc

Jason Barros is the senior partner program manager at SoundHound Inc.  He’s been working in the tech industry for over 12 years and has over 25 years of leadership and management experience.

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