Select Page
Blog - Pulsing Perceptions and Use of AI Voice Apps

Pulsing Perceptions and Use of AI Voice Apps

The time is right for investing in the global natural language processing (NLP) market, projected to grow from $20.98 billion in 2021 to $127.26 billion in 2028 at a CAGR of 29.4% in that forecast period.

To get a sense on NLP user perspectives, this past February, Applause surveyed its global crowdtesting community to gain insight into perceptions around the use of artificial intelligence (AI) voice applications such as chatbots, interactive voice response (IVR), and other conversational assistants. Check out our summary infographic for some highlights. We had over 6,600 responses from around the world. I want to share our findings and call out a few interesting points.

The global view

While just over half of respondents reported they prefer to wait for a human agent when calling a company for customer support (51%), 25% said they prefer immediate access to an automated touch tone response system and 22% prefer an automated virtual service representative that responds to voice commands.

Consumers increasingly expect businesses to have automated chatbots and automated voice systems: 31% said they always expect companies to have chatbots, 61% said it depended on the industry. A vast minority, 6.7%, stated they never expect chat functionality on a company’s website or app, while 11% don’t expect call centers to have IVR systems that greet them. Still, customers expect IVR more often than not: 46% always expect call centers to have IVR systems that greet them while another 40% said their expectations varied by industry.

Webinars

Unexpected Ai Use Cases And Their Hidden Benefits

Join voicebot.ai founder Bret Kinsella and Applause’s Emerson Sklar as they cover lessons learned through global testing efforts and new models for conversational AI and other AI projects.

Users expect mobile apps to include voice functionality as well: 44% always expect mobile apps to have voice assistants or voice search features while 41% said it depends on the app category.

Of the 5896 respondents (88%) who said they had used chat functionality on a website at least once, 63% said they were somewhat satisfied or extremely satisfied with the experience. Of the 19% who found the experiences dissatisfying, the top three complaints were:

  • They could not find the answers they were looking for (29%)

  • The chatbot did not understand what they were asking (25%)

  • The chatbot wasted users’ time (did not add value) before connecting them with an agent (20%)

Getting voice right

Customers expect companies to have automated chatbots and automated voice systems to greet them — and there is tremendous ROI for companies who get the NLP experience right, such as freeing up customer service reps for higher-value activities and reducing wait time for customers — yet developing NLP technologies requires special attention to details that many other digital products may not.

Ebooks

4 Best Practices for Better Natural Language Assistants

Natural language assistants offer advantages to businesses. Our whitepaper covers these in detail and lists best practices for creating great user experiences.

Want to see more like this?
Published: March 30, 2022
Reading Time: 7 min

Usability Testing for Agentic Interactions: Ensuring Intuitive AI-Powered Smart Device Assistants

See why early usability testing is a critical investment in building agentic AI systems that respect user autonomy and enhance collaboration.

Do Your IVR And Chatbot Experiences Empower Your Customers?

A recent webinar offers key points for organizations to consider as they evaluate the effectiveness of their customer-facing IVRs and chatbots.

Agentic Workflows in the Enterprise

As the level of interest in building agentic workflows in the enterprise increases, there is a corresponding development in the “AI Stack” that enables agentic deployments at scale.

What is Agentic AI?

Learn what differentiates agentic AI from generative AI and traditional AI and how agentic raises the stakes for software developers.

How Crowdtesters Reveal AI Chatbot Blind Spots

You can’t fix what AI can’t see

A Snapshot of the State of Digital Quality in AI

Explore the results of our annual survey on trends in developing and testing AI applications, and how those applications are living up to consumer expectations.
No results found.