The potential of language assistants in B2B.

How Google Assistant, Alexa and Co. are used in their own home, has long been known. Your benefit in B2B unthinkable? Not correct! Voice Assistants Powered by Conversational interfaces and Artificial Intelligence can facilitate work in companies, save valuable time and revolutionize lead generation.

In the office, people communicate with the machine via mouse and keyboard. It feels completely intuitive to everyone – at least more intuitive than writing code snippets into a black window. But until a person has learned where to look for the desired function, sometimes a lot of time passes.

Chatbots are out – voice control is in

Therefore, for example, chatbots should help simplify this man-machine interaction. Chatbots are technical dialog systems that the user controls by text input. Asked questions answered automatically, without human intervention. They are still used in many places, even if the technology, despite the hype as “Next Big Thing” could not prevail. However, leading companies are already focusing on a new development – voice control.

In the Smart Home area, speech recognition software such as Siri and Co. have been in use for quite some time – whether for switching on the light or controlling the blinds. But also for the reading of news and simple searches on the Internet, the voice input gains in importance. As early as 2020, half of all search requests should be made by voice , according to a study by ComScore on search behavior. As early as 2019, the entire speech recognition business will be around 600 million . How can this trend also be used in the B2B sector?

Whenever applications for computers, tablets or smartphones use Graphic User Interfaces (GUI), at least one hand is needed to control them. As a result, the user hardly has the opportunity to do anything else by the way, as he is exclusively concerned with the operation. This is a hindrance in many professions, such as for example, with a repairer or production staff. From an abstract point of view, they lose a lot of time in every trivial question, which they could better use for other tasks. But this is exactly where Intelligent Voice Assistants (IVA) will make the job easier. For example, if the logistics expert asks Alexa, where the goods are xy, he does not have to click through awkward menus and then enter the search term or even search out yourself.

Generate leads via smart conversations

However, conversations with voice assistants can do more than answer simple questions. Smart conversations can bring B2B companies significant lead generation benefits in the future. Conversation-qualified lead generation makes it possible to query the purchase intent as well as the needs of potential customers regarding a product – fully automated and in real time. This method is much faster than generating leads based on other sales or marketing actions and makes it easier to decide if a lead qualifies or not.

Intelligent conversations of this kind also help to improve customer service. There is a lot going on in the B2B sector, yet shopping processes are often still slow, complicated and not very digital. However, in a business environment where end users are seeing more and more customer service in real time, businesses can excel if they meet their expectations in the B2B environment as well and enable their customers to engage in digital dialogue.

Voice assistants save time in the office

Voice assistants can also assist in the office. If the user asks, “How many people visited our website yesterday?” Or “What are my sales doing?” Then he loses less time than looking for the same information on Google Analytics. For this scenario, an Australian startup has developed a solution. Its data analysis program makes it possible to intuitively ask for business developments using natural language commands, and the program also responds by voice. For example, while Google Analytics is not too difficult to use, business software often involves long click paths. The more complex the software, the greater the effort to achieve the desired result. Quick answers to questions are thus a clear driver of efficiency.

From machine learning algorithms to strong AI

In the context of language assistants, Artificial Intelligence (AI) is of great importance. Because she evaluates the spoken word. In fact, language assistants are more based on machine-learning algorithms than on powerful AI, which in principle transcribe and then execute the instructions. However, for an AI to become stronger, it needs a steadily growing amount of high-quality data. Their evaluation requires the expertise of specialized data scientists. These convert the data into valuable information so that insights can be gained from it. The learning process of AI can be well thought of as a cycle: More data facilitates the development of new, more complex applications. New applications generate new, more comprehensive data,

The golden mean: the hybrid form of chatbots and voice assistants

Although voice assistants can already capture 95 percent of the requests correctly, there is still a long way to go to perfection. Especially the Natural Language Understanding (NLU), not only the recognition, but also the understanding of language, is the biggest challenge. If difficult dialects, unclear pronunciation or simply colloquial language are added, the Google Assistant and Co. get really sweaty. Hybrid forms of speech-driven and graphical user interfaces could represent the golden mean. Basically, applications are served using natural language, but the user is also allowed to enter text. Through an additional graphical interface, buttons, pictures,

Outlook: Use of AI and Conversational Interfaces

Although there is an infinite number of use cases for language assistants, real applications in the B2B environment are still rare. But through digitization, the boundaries between work and private life are becoming blurred.

Requirements for applications that users make in their private lives, they are constantly taking over for professional tools. It, therefore, does not look any different in the use of AI and Conversational Interfaces (CI). CI enable intuitive and easy conversations with machines. As a result, the user experience of human-machine interaction is less and less different from “real” human interactions. Where something works intuitively, the learning effort is low. This eliminates the learning curve for time-consuming workflows and leaves room in the head and, above all, time for more important tasks in the company.

Firms should therefore already consider the component “Voice” for internal processes and their customer service – otherwise, they quickly lose the connection to competitors.

amardeep kaushal

Blogger, Marketer & Data Analyst.

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