The coronavirus has served as a catalytic force to accelerate the adoption of voice assistants. The inability to work closely in the physical world is pushing many businesses to proactively embrace voice assistants to better serve their customers, partners and employees. Yet, as voice emerges as a new battleground for market differentiation, pioneering companies are confronting various challenges.
To understand the potential and pitfalls of the voice odyssey already underway, we recently surveyed 1,400 top marketing and IT executives of leading companies from APAC and the Middle East region. A vast majority (93%) of the respondents firmly believe that the shift from “touch” to “voice” is posed to accelerate.
In fact, 74% of our respondents consider voice vital to their business. And they have begun walking the talk too — their companies are gearing up to spend 3% of their revenues over the next five years on voice capabilities. They are also quite optimistic of the ability of voice to deliver revenue growth. They project revenue growth at around 6.3% over the next five years.
Many plan to focus voice assistants initially on the customer — as well as on employee engagement. Their goal: improve response time to customers, (65%), personalization (60%) and enhance customer service levels (57%).
However, the challenges are many. For starters, only 40% of respondents expressed confidence in their ability to integrate voice into existing business processes. Prominent among the challenges are privacy (89%), creating content for voice (84%) and developing a voice personality (81%).
We believe that there is no one-size-fits-all solution to the issues surrounding the successful embrace of voice. Instead, companies need a way to assess their current stage of maturity along the voice path and plan their next moves in a measured way.
A three-phased model to transition smoothly to the new age of “voice”
Armed with these findings, we created a three-phased maturity model to help businesses find their brand’s voice (see Figure below). The model is designed to enhance customer trust and envisions natural language processing (NLP), machine learning (ML) and other artificial intelligence (AI) technologies as vital to imbuing the intelligence to continuously improve over time.