Voice-based systems have now become established in everyday life. For example, companies can use the underlying conversational AI technologies to optimize their customer experience. With these nine tips, companies can put them into practice.
Whether Alexa, Siri, Cortana, or Google Assistant: Voice-based systems have quickly established themselves in many people’s everyday lives. With the underlying technologies around conversational AI, i.e., voice-based artificial intelligence, companies can optimize their customer experience, for example. The chances of becoming more professional here have seldom been more significant. This is all the more true in the corona pandemic and the associated even more robust growth in online trade.
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Companies should pay attention to a few fundamental aspects for appropriate strategies and projects to optimize the customer experience to be successfully implemented. “Wherever people understand the different dimensions of a conversation, such as a subtext, emphasis, and emotionality, in addition to the plain text, machines are still very much limited to text.
The machine cannot yet reliably recognize what remains unsaid but resonates in the conversation – but conversational AI will still come to that”. “With all the euphoria about voice-based AI, which is justified in my opinion, it is still advisable to stick to the ground.” Nine tips on how companies can implement conversational AI projects:
In addition to technologists, the team should include content strategists, UX designers, data analysts, and team members with textual skills. Right from the start, so that this talent pool can develop its effect. Those involved should continuously look at the work of the team from an ethical perspective.
It is essential to define what a company wants to achieve clearly. Because it depends on whether spoken language is the proper means at all – or perhaps a chatbot, a specific or generic agent, or another medium.
Who is part of the target group, which personas need to be considered? What are the intentions and goals? It is not enough to know who opens a call center. For example, it is also about knowing the reasons and questions. How do users achieve the best result of the interaction or, in short: When are the users happy?
Companies should understand what data will be available to them and what ethical aspects must be considered when using this data. If the aim is to build an AI that enables an honest dialogue, there must be no inadvertently built-in approaches to prejudice.
Companies have to keep in mind that conversational AI is also and above all about brand management. The digital voice they develop – including tone, gender, and persona – must align with and empower the brand.
Target groups are heterogeneous, so the interface, regardless of whether it is voice or chat, must be as widely accessible and understandable for everyone as possible. This is particularly difficult with spoken language when pitch, accents, slang, regionalisms, and other factors play a role. But there are also variables in chat that determine whether users can gain access, such as the balance between colloquial language and a formal style.
Companies should first test extensively in-house, even if a voice assistant or chatbot is intended for external users. So you can fine-tune the solution in advance. It is helpful to plan some on-the-wall research and think about small, concentrated, and moderated outer test rounds.
One thing is sure: Any company that embarks on conversational AI will be surprised at what it can learn from the design and development of such an approach. There is still too little known about Conversational AI for all results to be precisely predicted without trial and error. It is simply unknown what happens and whether or not what is spoken beats the written word or an image for a particular application after the next iteration.
Companies have to decide whether they prefer to develop something themselves or buy a ready-made solution – with the respective advantages and disadvantages. However, neither one nor the other leads to a quick solution for little money. Top brands like Mercedes, BMW, Capital One, and Bank of America (BoA) have already developed voice assistants.
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