Understanding How AI Voice Assistants Shape Consumer Behavior

Artificial intelligence (AI) has begun to shape the way consumers behave. In fact, AI-enabled voice assistants (VAs) can affect consumer behavior in various direct and indirect ways. In a study by the California State University-Bakersfield, researchers examined how customers responded to using Amazon’s Alexa, Microsoft’s Cortana, and Google’s Assistant based on their different VA personality traits. They found that VAs incorporating sincerity, functional intelligence, and creativity can actually lead customers to take active charge of their interactions with AI.

Customers who observed these traits in their interactions with these three common mobile voice applications were not only more focused, but were also more willing to engage in exploratory behavior. In turn, this type of behavior not only fosters customer satisfaction, but also increases their overall willingness to use a VA for whatever purpose. This underscores what data analytics specialists and software developers have known for years: AI will take over the world. But instead of the post-apocalyptic picture painted by science fiction movies, the real AI takeover will be faster, more efficient, and fully integrated with advanced consumer-focused applications.

Actions on Google Assistant may be powered by True Reply with no engineering, zero code AI: bridging data and advanced voice technologies

This is just the tip of the iceberg in terms of how AI-enabled VAs can direct consumer behavior. Further understanding of this effect starts with how VAs leverage consumer business data. While the aforementioned VAs each have their own unique architecture, their continued development essentially rests on certain AI capabilities. Machine learning (ML)-enabled natural language processing (NLP) in particular is crucial to this process.

In a nutshell, ML refers to AI’s capacity to analyze data sets and improve on its own. Meanwhile, NLP refers to how AI can be programmed to collect, parcel, and analyze massive data sets of human language. Empowered by ML, an AI’s ability to implement NLP processes can exponentially grow with the amount of data that it can get its digital hands on. This is also how AI improves voice recognition for identity verification and other security purposes.

In short, ML-enabled NLP is how modern VAs can function with intelligence, creativity, and sincerity – essentially mimicking the organic speech patterns of consumers. These same functions are what makes True Reply an ideal solution for customized branded consumer market research.

The global implications of AI-enabled VA development

The more data is available for analytics, the more intuitive an AI-powered VA can become. This is why Amazon recently opened its Alexa AI tech to automakers. By giving the auto manufacturing industry more direct access to its advanced AI VA technology, Amazon is opening a rich vein of big data to the car consumer market. In a nutshell, the bigger the data, the more VAs and other AI applications can predict and shape the way consumers behave. And alongside the rapid development of AI applications, the world’s biggest industries are increasingly recognizing the value of big data. In the race to predict and influence consumer behavior by leveraging continually growing business data sets, market experts are also seeing noted increases in the demand for both data scientists and software specialists.

In fact, IT security professionals, cloud architects, database administrators, and programmer-analysts are the most in-demand jobs in CIO’s career projections for those pursuing tech/IT careers. As the worldwide volume of annual data created is projected to reach 180 trillion gigabytes by 2025, it’s safe to say that these data and software specialists have their work cut out for them. Furthermore, a career in data analytics post by Maryville University notes how graduates are also well-placed to acquire jobs as big data engineers, market research specialists, and digital marketers. As big data continues to prove itself essential to how VAs can direct the way consumers interact with brands, these specialists will continue to be in high demand. In turn, VA use cases will continue to emerge in different sectors such as marketing, healthcare, insurance, finance, and government applications.

Powered by data-hungry AI, VAs are not only shaping consumer behavior. Their development is also empowering huge strides forward in data analytics and software development. Over the next decade, we can expect VAs to dominate not just marketing and advertising, but any industry that produces massive amounts of consumer voice data.


Understanding How AI Voice Assistants Shape Consumer Behavior
Written by Percy Hopper, Contributing Author