Conversational artificial intelligence uses machine learning to speak to users in a natural and personalized way. The term carries some weight, but ultimately it comes down to the practical difference it can make for your business. The use of conversational AI allows you to manage large-scale conversations personalized and in real-time. Here are some proven high-performance use cases: lead generation bots can convert ten times more than static forms.
Ketan Parmar
Digital Marketing Manager at Weboccult Technologies
Conversational artificial intelligence uses machine learning to speak to users in a natural and personalized way. The term carries some weight, but ultimately it comes down to the practical difference it can make for your business.
In this article, we will take the time to explain what conversational AI is: principles and examples to have a better idea of how you can implement it in your business.
What is conversational AI?
It is a system in which three distinct technologies converge: artificial intelligence, messaging applications, and voice recognition. These different technologies have been known for decades, but the union of the three languages has completely changed that.
Software that combines these functions to conduct a human conversation might be called a “bot.” And bots that use text interfaces are commonly referred to as a chatbot. If you’ve ever interacted with Google Home or Amazon Alexa, you’ve experienced conversational AI before.
This technology learns from us as we learn from it. Deep learning allows these systems to mature their conversational experiences so that with practice, their conversations are more useful and more prosperous.
Principles of conversational AI
Before you start your business with conversational AI, you need to decide which principles apply and how they can help you achieve your goals.
Objectives and context
First, understand your goals behind using this type of technology. Then, don’t force your business to adopt this technology just because it’s new.
Build it into a customer service strategy that delivers value; keep in mind that conversational artificial intelligence is perfect for simple, straightforward tasks. If you want to find a use case, think about three areas of context that influence the decision to use AI.
User demographics and interests.History and previous interactions.The type of activity, mood, and intention of the user.
A bot could excel by allowing a repeat customer to re-order their favorite products through Facebook Messenger.
However, if the bot’s responsibility were to submit an anonymous report of an ethics violation via SMS, it would surely do so very badly. By this, we mean that you need to plan where and what solutions the bot can deliver.
Security and confidentiality
This is the second principle to define when it comes to bots. Almost half of the users who interact with bots are concerned about the security of their data.
It is why you must provide your users with a set of rules and guidelines for data and conversations in the app.
How businesses can use conversational AI?
Some use cases may benefit from conversational artificial intelligence better than others in a business. Here are some proven high-performance use cases:
Lead Generation: Lead generation bots can convert ten times more than tedious static forms. Users prefer to interact with a bot rather than having to fill in the blanks of a form.
Customer Engagement: Human customer service agents can’t be everywhere, all the time. Instead, bots can run circles that aren’t easily scalable and be everywhere 24/7.
Customer Support: According to Gartner, by 2021, 25% of businesses worldwide will have a virtual assistant to handle support issues.
Receive Customer Feedback: Bots can receive valuable customer feedback after an exciting conversation ends. So instead of filling out an uncomfortable survey form, the customer has the option of leaving their opinion about the brand, its products or services, in a conversation.
The use of conversational artificial intelligence allows you to manage large-scale conversations personalized and in real-time.
Examples of conversational AI
Customer experience and brand building
Implementing a well-designed bot on a popular platform allows you to build relationships with prospects and customers in a personalized, positive way that wouldn’t be profitable without automation.
Alternatively, you collect a constantly refreshed and expanding data set that can help you understand your customers in much more detail. Traditional techniques do not provide this level of detail.
Customer service chatbots, for example, typically with humans willing to tap into conversations as needed to ensure quality, can provide customer service and problem-solve with reduced response times and increased satisfaction.
No matter how fully prepared your agents are, no one wants to wait too long for a response, which is why these AIs are flattering.
An example of this use that we have with the qualification of potential customers. Many companies lose potential customers due to confusion with their products, and they waste a lot of their staff time cultivating low-quality contacts.
Setting up a chatbot to inform and help qualify potential customers is, therefore, an excellent idea. As a result, conversion rates can even triple.
Likewise, renowned brand Tommy Hilfiger was an early adopter of customer relationships through conversational AI, with consumers returning an average of three times to its Facebook Messenger chatbot. They made the wise decision to make their New York Fashion Week collection available through the chatbot and thus made 3.5 times more revenue than through other digital channels.
Autodesk needed more efficient customer service. So they introduced a chatbot to handle basic requests that don’t require a human agent.
As a result, resolution times have dropped from a day and a half to just over five minutes, and the cost of resolving these issues has been reduced by 90%. After getting a taste of what conversational AI could do for their business, they couldn’t let go.
Employee experience
Rarely when it comes to conversational AI is it mentioned that it also has effective and efficient uses for employees. We are, of course, talking about the role they can play in the human resources department.
It turns out that recruiting bots can give candidates a personalized presentation of the company and make it ideal to schedule interviews. For current employees, there are also benefits.
Chat interfaces can automate many internal communication processes and provide an efficient and user-friendly way for employees to access information that, if they were doing it the old-fashioned way, should look up manuals, consult with colleagues, and more.
Finally, conversational AI-based employee training and survey processes are increasingly used and promising.
Conversational interfaces built with artificial intelligence are becoming very common, from travel agencies to banks. And it is that conversational artificial intelligence helps companies of all kinds achieve their business goals. Therefore, the benefits are not just for the customer but your business.
Operating costs are reduced, and operations are increasingly scalable, giving you more opportunities for growth as a business.
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What Is Conversational AI: Principles and Examples
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