How Effective Are AI Chatbots For Customers?

The first chatbot, ELIZA, was created at MIT in 1966 to act as a psychotherapist as part of the DOCTOR Program. Although ELIZA was incredibly basic compared to today’s digital chatbots, it was the start of a tech revolution. 

Today, chatbots are used by various industries to handle customer queries, manage bookings, and generate leads. They can be accessed via websites, SMS, WhatsApp, and social media messaging services. 

There needs to be a distinction made between the two types of chatbots customers interact with today. Rule-based bots are also called decision-tree bots, and are similar to the “Press 3 for accounts” customer service over the phone. They respond to customers based on set answers and queries. AI chatbots are the latest in customer service. They use machine learning and natural language processing (NLP) to understand exactly what the customer is saying and respond accurately. 

AI chatbots are increasingly being used by various industries to offer support. Although mostly common in online retail and e-commerce, these virtual assistants are also used in the following industries:

• Online gambling: There are many trusted options in the US where players can access online casino games and connect with chatbots for onboarding, transaction concerns, or finding out about wagering requirements.
• Healthcare: Bots are used to book and manage appointments, answer basic health questions, and provide tips for at-home treatments. 
• Finance: Banks use bots to answer account inquiries or assist with transactions.
• Hospitality: It is common to connect with chatbots on sites like Booking.com to manage reservations and ask about facilities. 
• Education: Helps students who are involved with e-learning processes. Can answer questions or give tips to solve difficult puzzles. 

AI chatbots are considered effective for customers based on the many advantages that they offer. They also provide benefits to businesses that don’t have to employ additional customer service staff for basic queries, freeing up employees for more pressing matters. 

AI chatbots are able to answer questions almost instantly. The answers provided will address the query specifically, thanks to the natural language processing abilities of artificial intelligence. These bots will also remember previous conversations, improving customer satisfaction.

Chatbots can also anticipate a customer’s needs based on the conversation. For example, if a customer types into the chatbox on an online retailer platform: “I am looking for shoes”, the chatbot will be able to determine the user’s gender and preferences based on previous sales or login information, and suggest shoes that match their style. If a user is adding several items to their cart, the chatbot can help them with the checkout process. 

Artificial intelligence has the ability to communicate in almost any language (including in a secret “bot” language), creating a more seamless customer journey. Even if a website is only in English, AI chatbots can respond in the user’s home language. This is highly efficient, as training customer service staff in all the world’s languages won’t be feasible. 

The biggest benefit of chatbots is that they’re online 24/7. Customers can always access information, even if their business hours don’t align with those of the platform. This is highly effective, as customers who are experiencing problems or have concerns can have them addressed instantly without having to wait for a company to open.

Of course, no matter how effective a chatbot is, human preference should be factored in. A study conducted by Katana discovered that only 51% of respondents (or 1 in 2) were happy to communicate with an AI chatbot, while the rest wanted to talk to a person. This percentage shifted according to generations, with Millennials and Gen Z more likely to chat with bots compared to older generations. 

So, although chatbots have their place and are becoming increasingly sophisticated, there is still a place for human customer service agents to deal with larger or more pressing queries.